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1
Moron-Lopez, Sara, Sushama Telwatte, Indra Sarabia, Emilie Battivelli, Mauricio Montano, Amanda B. Macedo, Dvir Aran et al. "Human splice factors contribute to latent HIV infection in primary cell models and blood CD4+ T cells from ART-treated individuals". PLOS Pathogens 16, n. 11 (30 novembre 2020): e1009060. http://dx.doi.org/10.1371/journal.ppat.1009060.
Testo completoAbstract (sommario):
It is unclear what mechanisms govern latent HIV infection in vivo or in primary cell models. To investigate these questions, we compared the HIV and cellular transcription profile in three primary cell models and peripheral CD4+ T cells from HIV-infected ART-suppressed individuals using RT-ddPCR and RNA-seq. All primary cell models recapitulated the block to HIV multiple splicing seen in cells from ART-suppressed individuals, suggesting that this may be a key feature of HIV latency in primary CD4+ T cells. Blocks to HIV transcriptional initiation and elongation were observed more variably among models. A common set of 234 cellular genes, including members of the minor spliceosome pathway, was differentially expressed between unstimulated and activated cells from primary cell models and ART-suppressed individuals, suggesting these genes may play a role in the blocks to HIV transcription and splicing underlying latent infection. These genes may represent new targets for therapies designed to reactivate or silence latently-infected cells.
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SANTOS, Naiara Caroline Aparecido dos, e Jorge Luiz BAZÁN. "RESIDUAL ANALYSIS IN RASCH POISSON COUNTS MODELS". REVISTA BRASILEIRA DE BIOMETRIA 39, n. 1 (31 marzo 2021): 206–20. http://dx.doi.org/10.28951/rbb.v39i1.531.
Testo completoAbstract (sommario):
A Rasch Poisson counts (RPC) model is described to identify individual latent traits and facilities of the items of tests that model the error (or success) count in several tasks over time, instead of modeling the correct responses to items in a test as in the dichotomous item response theory (IRT) model. These types of tests can be more informative than traditional tests. To estimate the model parameters, we consider a Bayesian approach using the integrated nested Laplace approximation (INLA). We develop residual analysis to assess model t by introducing randomized quantile residuals for items. The data used to illustrate the method comes from 228 people who took a selective attention test. The test has 20 blocks (items), with a time limit of 15 seconds for each block. The results of the residual analysis of the RPC were promising and indicated that the studied attention data are not well tted by the RPC model.
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Norget, Julia, e Axel Mayer. "Block-Wise Model Fit for Structural Equation Models With Experience Sampling Data". Zeitschrift für Psychologie 230, n. 1 (gennaio 2022): 47–59. http://dx.doi.org/10.1027/2151-2604/a000482.
Testo completoAbstract (sommario):
Abstract. Common model fit indices behave poorly in structural equation models for experience sampling data which typically contain many manifest variables. In this article, we propose a block-wise fit assessment for large models as an alternative. The entire model is estimated jointly, and block-wise versions of common fit indices are then determined from smaller blocks of the variance-covariance matrix using simulated degrees of freedom. In a first simulation study, we show that block-wise fit indices, contrary to global fit indices, correctly identify correctly specified latent state-trait models with 49 occasions and N = 200. In a second simulation, we find that block-wise fit indices cannot identify misspecification purely between days but correctly rejects other misspecified models. In some cases, the block-wise fit is superior in judging the strength of the misspecification. Lastly, we discuss the practical use of block-wise fit evaluation and its limitations.
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Vidal, E., A. Moreno, E. Bertolini e M. Cambra. "Estimation of the accuracy of two diagnostic methods for the detection of Plum pox virus in nursery blocks by latent class models". Plant Pathology 61, n. 2 (13 luglio 2011): 413–22. http://dx.doi.org/10.1111/j.1365-3059.2011.02505.x.
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Messick, Troy E., Garry R. Smith, Samantha S. Soldan, Mark E. McDonnell, Julianna S. Deakyne, Kimberly A. Malecka, Lois Tolvinski et al. "Structure-based design of small-molecule inhibitors of EBNA1 DNA binding blocks Epstein-Barr virus latent infection and tumor growth". Science Translational Medicine 11, n. 482 (6 marzo 2019): eaau5612. http://dx.doi.org/10.1126/scitranslmed.aau5612.
Testo completoAbstract (sommario):
Epstein-Barr virus (EBV) is a DNA tumor virus responsible for 1 to 2% of human cancers including subtypes of Burkitt’s lymphoma, Hodgkin’s lymphoma, gastric carcinoma, and nasopharyngeal carcinoma (NPC). Persistent latent infection drives EBV-associated tumorigenesis. Epstein-Barr nuclear antigen 1 (EBNA1) is the only viral protein consistently expressed in all EBV-associated tumors and is therefore an attractive target for therapeutic intervention. It is a multifunctional DNA binding protein critical for viral replication, genome maintenance, viral gene expression, and host cell survival. Using a fragment-based approach and x-ray crystallography, we identify a 2,3-disubstituted benzoic acid series that selectively inhibits the DNA binding activity of EBNA1. We characterize these inhibitors biochemically and in cell-based assays, including chromatin immunoprecipitation and DNA replication assays. In addition, we demonstrate the potency of EBNA1 inhibitors to suppress tumor growth in several EBV-dependent xenograft models, including patient-derived xenografts for NPC. These inhibitors selectively block EBV gene transcription and alter the cellular transforming growth factor–β (TGF-β) signaling pathway in NPC tumor xenografts. These EBNA1-specific inhibitors show favorable pharmacological properties and have the potential to be further developed for the treatment of EBV-associated malignancies.
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Cisneros, William J., Shimaa H. A. Soliman, Miriam Walter, Lacy M. Simons, Daphne Cornish, Simone De Fabritiis, Ariel W. Halle et al. "Release of P-TEFb from the Super Elongation Complex promotes HIV-1 latency reversal". PLOS Pathogens 20, n. 9 (11 settembre 2024): e1012083. http://dx.doi.org/10.1371/journal.ppat.1012083.
Testo completoAbstract (sommario):
The persistence of HIV-1 in long-lived latent reservoirs during suppressive antiretroviral therapy (ART) remains one of the principal barriers to a functional cure. Blocks to transcriptional elongation play a central role in maintaining the latent state, and several latency reversal strategies focus on the release of positive transcription elongation factor b (P-TEFb) from sequestration by negative regulatory complexes, such as the 7SK complex and BRD4. Another major cellular reservoir of P-TEFb is in Super Elongation Complexes (SECs), which play broad regulatory roles in host gene expression. Still, it is unknown if the release of P-TEFb from SECs is a viable latency reversal strategy. Here, we demonstrate that the SEC is not required for HIV-1 replication in primary CD4+ T cells and that a small molecular inhibitor of the P-TEFb/SEC interaction (termed KL-2) increases viral transcription. KL-2 acts synergistically with other latency reversing agents (LRAs) to reactivate viral transcription in several cell line models of latency in a manner that is, at least in part, dependent on the viral Tat protein. Finally, we demonstrate that KL-2 enhances viral reactivation in peripheral blood mononuclear cells (PBMCs) from people living with HIV (PLWH) on suppressive ART, most notably in combination with inhibitor of apoptosis protein antagonists (IAPi). Taken together, these results suggest that the release of P-TEFb from cellular SECs may be a novel route for HIV-1 latency reactivation.
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Ma, Suqiang, Chun Liu, Zheng Li e Wei Yang. "Integrating Adversarial Generative Network with Variational Autoencoders towards Cross-Modal Alignment for Zero-Shot Remote Sensing Image Scene Classification". Remote Sensing 14, n. 18 (11 settembre 2022): 4533. http://dx.doi.org/10.3390/rs14184533.
Testo completoAbstract (sommario):
Remote sensing image scene classification takes image blocks as classification units and predicts their semantic descriptors. Because it is difficult to obtain enough labeled samples for all classes of remote sensing image scenes, zero-shot classification methods which can recognize image scenes that are not seen in the training stage are of great significance. By projecting the image visual features and the class semantic features into the latent space and ensuring their alignment, the variational autoencoder (VAE) generative model has been applied to address remote-sensing image scene classification under a zero-shot setting. However, the VAE model takes the element-wise square error as the reconstruction loss, which may not be suitable for measuring the reconstruction quality of the visual and semantic features. Therefore, this paper proposes to augment the VAE models with the generative adversarial network (GAN) to make use of the GAN’s discriminator in order to learn a suitable reconstruction quality metric for VAE. To promote feature alignment in the latent space, we have also proposed cross-modal feature-matching loss to make sure that the visual features of one class are aligned with the semantic features of the class and not those of other classes. Based on a public dataset, our experiments have shown the effects of the proposed improvements. Moreover, taking the ResNet models of ResNet18, extracting 512-dimensional visual features, and ResNet50 and ResNet101, both extracting 2048-dimensional visual features for testing, the impact of the different visual feature extractors has also been investigated. The experimental results show that better performance is achieved by ResNet18. This indicates that more layers of the extractors and larger dimensions of the extracted features may not contribute to the image scene classification under a zero-shot setting.
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Demir, Rezan, Lewis B. Haberly e Meyer B. Jackson. "Characteristics of Plateau Activity During the Latent Period Prior to Epileptiform Discharges in Slices From Rat Piriform Cortex". Journal of Neurophysiology 83, n. 2 (1 febbraio 2000): 1088–98. http://dx.doi.org/10.1152/jn.2000.83.2.1088.
Testo completoAbstract (sommario):
The deep piriform region has an unusually high seizure susceptibility. Voltage imaging previously located the sites of epileptiform discharge onset in slices of rat piriform cortex and revealed the spatiotemporal pattern of development of two types of electrical activity during the latent period prior to discharge onset. A ramplike depolarization (onset activity) appears at the site of discharge onset. Onset activity is preceded by a sustained low-amplitude depolarization (plateau activity) at another site, which shows little if any overlap with the site of onset. Because synaptic blockade at either of these two sites blocks discharges, it was proposed that both forms of latent period activity are necessary for the generation of epileptiform discharges and that the onset and plateau sites work together in the amplification of electrical activity. The capacity for amplification was examined here by studying subthreshold responses in slices of piriform cortex using two different in vitro models of epilepsy. Under some conditions electrically evoked responses showed a nonlinear dependence on stimulus current, suggesting amplification by strong polysynaptic excitatory responses. The sites of plateau and onset activity were mapped for different in vitro models of epilepsy and different sites of stimulation. These experiments showed that the site of plateau activity expanded into deep layers of neighboring neocortex in parallel with expansions of the onset site into neocortex. These results provide further evidence that interactions between the sites of onset and plateau activity play an important role in the initiation of epileptiform discharges. The site of plateau activity showed little variation with different stimulation sites in the piriform cortex, but when stimulation was applied in the endopiriform nucleus (in the sites of onset of plateau activity), plateau activity had a lower amplitude and became distributed over a much wider area. These results indicate that in the initiation of epileptiform discharges, the location of the circuit that generates plateau activity is not rigidly defined but can exhibit flexibility.
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Bessac, Julie, Pierre Ailliot, Julien Cattiaux e Valerie Monbet. "Comparison of hidden and observed regime-switching autoregressive models for (u, v)-components of wind fields in the northeastern Atlantic". Advances in Statistical Climatology, Meteorology and Oceanography 2, n. 1 (29 febbraio 2016): 1–16. http://dx.doi.org/10.5194/ascmo-2-1-2016.
Testo completoAbstract (sommario):
Abstract. Several multi-site stochastic generators of zonal and meridional components of wind are proposed in this paper. A regime-switching framework is introduced to account for the alternation of intensity and variability that is observed in wind conditions due to the existence of different weather types. This modeling blocks time series into periods in which the series is described by a single model. The regime-switching is modeled by a discrete variable that can be introduced as a latent (or hidden) variable or as an observed variable. In the latter case a clustering algorithm is used before fitting the model to extract the regime. Conditional on the regimes, the observed wind conditions are assumed to evolve as a linear Gaussian vector autoregressive (VAR) model. Various questions are explored, such as the modeling of the regime in a multi-site context, the extraction of relevant clusterings from extra variables or from the local wind data, and the link between weather types extracted from wind data and large-scale weather regimes derived from a descriptor of the atmospheric circulation. We also discuss the relative advantages of hidden and observed regime-switching models. For artificial stochastic generation of wind sequences, we show that the proposed models reproduce the average space–time motions of wind conditions, and we highlight the advantage of regime-switching models in reproducing the alternation of intensity and variability in wind conditions.
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Lai, Zhi-Fei, Gang Zhang, Xiao-Bo Zhang e Hong-Tao Liu. "High-Resolution Histopathological Image Classification Model Based on Fused Heterogeneous Networks with Self-Supervised Feature Representation". BioMed Research International 2022 (21 agosto 2022): 1–10. http://dx.doi.org/10.1155/2022/8007713.
Testo completoAbstract (sommario):
Applying machine learning technology to automatic image analysis and auxiliary diagnosis of whole slide image (WSI) may help to improve the efficiency, objectivity, and consistency of pathological diagnosis. Due to its extremely high resolution, it is still a great challenge to directly process WSI through deep neural networks. In this paper, we propose a novel model for the task of classification of WSIs. The model is composed of two parts. The first part is a self-supervised encoding network with a UNet-like architecture. Each patch from a WSI is encoded as a compressed latent representation. These features are placed according to their corresponding patch’s original location in WSI, forming a feature cube. The second part is a classification network fused by 4 famous network blocks with heterogeneous architectures, with feature cube as input. Our model effectively expresses the feature and preserves location information of each patch. The fused network integrates heterogeneous features generated by different networks which yields robust classification results. The model is evaluated on two public datasets with comparison to baseline models. The evaluation results show the effectiveness of the proposed model.
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Bai, Haitao, Pinghui Wang, Ruofei Zhang e Zhou Su. "SegFormer: A Topic Segmentation Model with Controllable Range of Attention". Proceedings of the AAAI Conference on Artificial Intelligence 37, n. 11 (26 giugno 2023): 12545–52. http://dx.doi.org/10.1609/aaai.v37i11.26477.
Testo completoAbstract (sommario):
Topic segmentation aims to reveal the latent structure of a document and divide it into multiple parts. However, current neural solutions are limited in the context modeling of sentences and feature representation of candidate boundaries. This causes the model to suffer from inefficient sentence context encoding and noise information interference. In this paper, we design a new text segmentation model SegFormer with unidirectional attention blocks to better model sentence representations. To alleviate the problem of noise information interference, SegFormer uses a novel additional context aggregator and a topic classification loss to guide the model to aggregate the information within the appropriate range. In addition, SegFormer applies an iterative prediction algorithm to search for optimal boundaries progressively. We evaluate SegFormer's generalization ability, multilingual ability, and application ability on multiple challenging real-world datasets. Experiments show that our model significantly improves the performance by 7.5% on the benchmark WIKI-SECTION compared to several strong baselines. The application of SegFormer to a real-world dataset to separate normal and advertisement segments in product marketing essays also achieves superior performance in the evaluation with other cutting-edge models.
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Bejiga, Mesay Belete, Farid Melgani e Pietro Beraldini. "Domain Adversarial Neural Networks for Large-Scale Land Cover Classification". Remote Sensing 11, n. 10 (14 maggio 2019): 1153. http://dx.doi.org/10.3390/rs11101153.
Testo completoAbstract (sommario):
Learning classification models require sufficiently labeled training samples, however, collecting labeled samples for every new problem is time-consuming and costly. An alternative approach is to transfer knowledge from one problem to another, which is called transfer learning. Domain adaptation (DA) is a type of transfer learning that aims to find a new latent space where the domain discrepancy between the source and the target domain is negligible. In this work, we propose an unsupervised DA technique called domain adversarial neural networks (DANNs), composed of a feature extractor, a class predictor, and domain classifier blocks, for large-scale land cover classification. Contrary to the traditional methods that perform representation and classifier learning in separate stages, DANNs combine them into a single stage, thereby learning a new representation of the input data that is both domain-invariant and discriminative. Once trained, the classifier of a DANN can be used to predict both source and target domain labels. Additionally, we also modify the domain classifier of a DANN to evaluate its suitability for multi-target domain adaptation problems. Experimental results obtained for both single and multiple target DA problems show that the proposed method provides a performance gain of up to 40%.
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Sun, Fusheng, Jiahao Zhang, Xiaodong Wu, Zhong Zheng e Xiaowen Yang. "Video Anomaly Detection Based on Global–Local Convolutional Autoencoder". Electronics 13, n. 22 (11 novembre 2024): 4415. http://dx.doi.org/10.3390/electronics13224415.
Testo completoAbstract (sommario):
Video anomaly detection (VAD) plays a crucial role in fields such as security, production, and transportation. To address the issue of overgeneralization in anomaly behavior prediction by deep neural networks, we propose a network called AMFCFBMem-Net (appearance and motion feature cross-fusion block memory network), which combines appearance and motion feature cross-fusion blocks. Firstly, dual encoders for appearance and motion are employed to separately extract these features, which are then integrated into the skip connection layer to mitigate the model’s tendency to predict abnormal behavior, ultimately enhancing the prediction accuracy for abnormal samples. Secondly, a motion foreground extraction module is integrated into the network to generate a foreground mask map based on speed differences, thereby widening the prediction error margin between normal and abnormal behaviors. To capture the latent features of various models for normal samples, a memory module is introduced at the bottleneck of the encoder and decoder structures. This further enhances the model’s anomaly detection capabilities and diminishes its predictive generalization towards abnormal samples. The experimental results on the UCSD Pedestrian dataset 2 (UCSD Ped2) and CUHK Avenue anomaly detection dataset (CUHK Avenue) demonstrate that, compared to current cutting-edge video anomaly detection algorithms, our proposed method achieves frame-level AUCs of 97.5% and 88.8%, respectively, effectively enhancing anomaly detection capabilities.
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Kolodziej, Andrew, Eric Haines, Richard Morse e Eugene Zhukovsky. "Abstract 5611: CRB-601: A highly potent and selective integrin αvβ8 blocking antibody with anti-tumoral properties". Cancer Research 82, n. 12_Supplement (15 giugno 2022): 5611. http://dx.doi.org/10.1158/1538-7445.am2022-5611.
Testo completoAbstract (sommario):
Abstract TGFβ is a secreted protein produced by tumors that promotes cancer progression primarily via the suppression of both the innate and adaptive immune systems. This makes TGFβ a promising immunotherapeutic target in cancer. It is ubiquitously expressed in a latent (L-TGFβ) form and the latent form has been shown to promote an immune suppressive phenotype within the tumor microenvironment. Integrin αvβ8 specifically binds to L-TGFβ. This interaction is essential for the activation of L-TGFβ-mediated signals in a variety of immune cell types. Interestingly, it has been recently shown that integrin αvβ8-mediated TGFβ activation can active directly through L-TGFβ and does not require the release of active TGFβ (1). Inhibition of integrin αvβ8-mediated TGFβ activation has been shown to block immunosuppressive regulatory T cell differentiation and enhance the recruitment of cytotoxic T cells into the tumor microenvironment (2). Here, we demonstrate by Surface Plasmon Resonance (SPR) that CRB-601, our selective inhibitor of integrin αvβ8 monoclonal antibody candidate, has a high affinity and specificity for the integrin αvβ8 complex. Moreover, in comparison to competitor molecules, such as ADWA-11, CRB-601 substantially blocks TGFβ activation in a reporter cell assay system. Additionally, using syngeneic mouse models, we evaluated the anti-tumoral properties of CRB-601 as a monotherapy, as well as in combination with immune checkpoints therapies. Findings from this study highlight the importance of integrin αvβ8 blockade in mediating the immune landscape within the tumor and leads to an enhanced response to immune checkpoint therapy. In conclusion, CRB-601 is a potent and selective integrin αvβ8 blocking monoclonal antibody that enhances the activity of immune checkpoint inhibitors in vivo and holds promise as a potential combination partner for immunotherapy. Investigational New Drug (IND) enabling studies are currently underway. References: 1: Campbell MG. et al. (2020) Cyro-EM reveals integrin-mediated TGF-β activation without release from latent TGF-β. Cell 180, 490-501. 2: Mariathasan S. et al. (2018) TGFbeta attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells. Nature 554, 544-48. Citation Format: Andrew Kolodziej, Eric Haines, Richard Morse, Eugene Zhukovsky. CRB-601: A highly potent and selective integrin αvβ8 blocking antibody with anti-tumoral properties [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5611.
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Han, Xian-Hua, Jian Wang e Yen-Wei Chen. "Mask-Guided Spatial–Spectral MLP Network for High-Resolution Hyperspectral Image Reconstruction". Sensors 24, n. 22 (18 novembre 2024): 7362. http://dx.doi.org/10.3390/s24227362.
Testo completoAbstract (sommario):
Hyperspectral image (HSI) reconstruction is a critical and indispensable step in spectral compressive imaging (CASSI) systems and directly affects our ability to capture high-quality images in dynamic environments. Recent research has increasingly focused on deep unfolding frameworks for HSI reconstruction, showing notable progress. However, these approaches have to break the optimization task into two sub-problems, solving them iteratively over multiple stages, which leads to large models and high computational overheads. This study presents a simple yet effective method that passes the degradation information (sensing mask) through a deep learning network to disentangle the degradation and the latent target’s representations. Specifically, we design a lightweight MLP block to capture non-local similarities and long-range dependencies across both spatial and spectral domains, and investigate an attention-based mask modelling module to achieve the spatial–spectral-adaptive degradation representationthat is fed to the MLP-based network. To enhance the information flow between MLP blocks, we introduce a multi-level fusion module and apply reconstruction heads to different MLP features for deeper supervision. Additionally, we combine the projection loss from compressive measurements with reconstruction loss to create a dual-domain loss, ensuring consistent optical detection during HS reconstruction. Experiments on benchmark HS datasets show that our method outperforms state-of-the-art approaches in terms of both reconstruction accuracy and efficiency, reducing computational and memory costs.
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Wyse, Jason, e Nial Friel. "Block clustering with collapsed latent block models". Statistics and Computing 22, n. 2 (5 maggio 2011): 415–28. http://dx.doi.org/10.1007/s11222-011-9233-4.
Testo completo
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Ramos, Juan Carlos, Luis M. Diaz, Michele Manrique, Rosangela Lima, Ngoc L. Toomey, Tianli Xia, Lisa Cabral, Toumy Guettouche, Carlos Brites e William J. Harrington. "Zidovudine Blocks NF-κB activity in Vivo in Adult T-Cell Leukemia". Blood 112, n. 11 (16 novembre 2008): 2524. http://dx.doi.org/10.1182/blood.v112.11.2524.2524.
Testo completoAbstract (sommario):
Abstract Adult T-cell leukemia (ATL) is a lymphoid malignancy caused by the human T-cell leukemia virus type I (HTLV-I), which carries a poor prognosis. A hallmark of ATL is the high constitutive expression of NF-κB, which predominantly exerts an anti-apoptotic effect contributing to chemotherapy resistance. Many of the elegant studies about the pathogenesis of ATL have focused on Tax, a viral transactivator of NF-κB, using HTLV-I expressing cell lines and mouse models, however in primary tumors the virus remains latent and Tax is not detected. We and other investigators have demonstrated the clinical efficacy of Zidovudine (AZT) and interferon-alpha (IFNα) combination therapy in both chronic and acute ATL subtypes with some patients achieving clinical remission or stable disease for many years while on maintenance therapy. The exact mechanisms of these antiviral drugs in ATL remain unclear. In a recent analysis of primary ATL tumors, we implicated the expression of both c-Rel and the NF-κB target gene product IRF-4/MUM-1 in AZT/IFN resistant disease. We have recently opened to accrual a Phase II clinical trial titled Prospective Study of the Molecular Characteristics of Sensitive and Resistant Disease in Patients with HTLV-I Associated Adult T Cell Leukemia Treated with Zidovudine Plus Interferon alpha-2b, which includes the novel use of pegylated interferon-alpha and valproic acid (as HDAC inhibitor) in the maintenance phase as an attempt to eradicate residual ATL clones, which usually occurs after AZT and IFNα therapy even after longterm remission. Our goals are also to study the anti-tumor mechanisms of these drugs in ATL, and define molecular criteria for response. As part of the correlative studies in our Phase II trial, we have analyzed leukemic ATL cells collected from patients during the first 48 hours of treatment (AZT given alone prior to IFN) and found in vivo stabilization of IκB (the repressor protein of NF-κB) by Western Blot in patients responding to the treatment, suggesting a role for this antiviral drug in blocking NF-κB activity as previously hypothesized in our laboratory. We also examined the expression of NF-κB related genes using a custom designed gene expression array by a novel technology (NanoString Inc.) of selected NF-κB target genes and found downregulation of most these genes in vivo by AZT alone. So far, all ATL tumors analyzed exhibited high expression of many NF-κB target genes, and over forty of these are differentially overexpressed in ATL specimens as compared to normal CD4+ T-cells. Some the differentially expressed genes include those encoding NF-κB/Rel, interferon regulatory factor (IRF), and bcl-2 related proteins. A comprehensive analysis of over forty ATL tumors, including specimens collected in both Miami and Brazil, is ongoing and expected to be completed soon. Baseline tumor characteristics and prognostic variables of previously collected tumors, as well interim results of our clinical and molecular studies will be reported.
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Liu, Tong, e Zheng Wang. "DeepChIA-PET: Accurately predicting ChIA-PET from Hi-C and ChIP-seq with deep dilated networks". PLOS Computational Biology 19, n. 7 (13 luglio 2023): e1011307. http://dx.doi.org/10.1371/journal.pcbi.1011307.
Testo completoAbstract (sommario):
Chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) can capture genome-wide chromatin interactions mediated by a specific DNA-associated protein. The ChIA-PET experiments have been applied to explore the key roles of different protein factors in chromatin folding and transcription regulation. However, compared with widely available Hi-C and ChIP-seq data, there are not many ChIA-PET datasets available in the literature. A computational method for accurately predicting ChIA-PET interactions from Hi-C and ChIP-seq data is needed that can save the efforts of performing wet-lab experiments. Here we present DeepChIA-PET, a supervised deep learning approach that can accurately predict ChIA-PET interactions by learning the latent relationships between ChIA-PET and two widely used data types: Hi-C and ChIP-seq. We trained our deep models with CTCF-mediated ChIA-PET of GM12878 as ground truth, and the deep network contains 40 dilated residual convolutional blocks. We first showed that DeepChIA-PET with only Hi-C as input significantly outperforms Peakachu, another computational method for predicting ChIA-PET from Hi-C but using random forests. We next proved that adding ChIP-seq as one extra input does improve the classification performance of DeepChIA-PET, but Hi-C plays a more prominent role in DeepChIA-PET than ChIP-seq. Our evaluation results indicate that our learned models can accurately predict not only CTCF-mediated ChIA-ET in GM12878 and HeLa but also non-CTCF ChIA-PET interactions, including RNA polymerase II (RNAPII) ChIA-PET of GM12878, RAD21 ChIA-PET of GM12878, and RAD21 ChIA-PET of K562. In total, DeepChIA-PET is an accurate tool for predicting the ChIA-PET interactions mediated by various chromatin-associated proteins from different cell types.
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Monaco, Maria Chiara G., Samantha S. Soldan, Chenhe Su, Annaliese Clauze, John F. Cooper, Rishi J. Patel, Fang Lu et al. "EBNA1 Inhibitors Block Proliferation of Spontaneous Lymphoblastoid Cell Lines From Patients With Multiple Sclerosis and Healthy Controls". Neurology - Neuroimmunology Neuroinflammation 10, n. 5 (10 agosto 2023): e200149. http://dx.doi.org/10.1212/nxi.0000000000200149.
Testo completoAbstract (sommario):
Background and ObjectivesEpstein-Barr virus (EBV) is a ubiquitous herpesvirus that establishes lifelong latency in memory B cells and has been identified as a major risk factor of multiple sclerosis (MS). B cell depletion therapies have disease-modifying benefit in MS. However, it is unclear whether this benefit is partly attributable to the elimination of EBV+B cells. Currently, there are no EBV-specific antiviral therapies available for targeting EBV latent infection in MS and limited experimental models to study EBV in MS.MethodsIn this study, we describe the establishment of spontaneous lymphoblastoid cell lines (SLCLs) generated ex vivo with the endogenous EBV of patients with MS and controls and treated with either an Epstein-Barr virus nuclear antigen 1 (EBNA1) inhibitor (VK-1727) or cladribine, a nucleoside analog that eliminates B cells.ResultsWe showed that a small molecule inhibitor of EBNA1, a critical regulator of the EBV life cycle, blocks the proliferation and metabolic activity of these SLCLs. In contrast to cladribine, a highly cytotoxic B cell depleting therapy currently used in MS, the EBNA1 inhibitor VK-1727 was cytostatic rather than cytotoxic and selective for EBV+cells, while having no discernible effects on EBV−cells. We validate that VK-1727 reduces EBNA1 DNA binding at known viral and cellular sites by ChIP-qPCR.DiscussionThis study shows that patient-derived SLCLs provide a useful tool for interrogating the role of EBV+B cells in MS and suggests that a clinical trial testing the effect of EBNA1 inhibitors in MS may be warranted.
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Cui, Haifu, Liang Wu, Sheng Hu, Rujuan Lu e Shanlin Wang. "Recognition of Urban Functions and Mixed Use Based on Residents’ Movement and Topic Generation Model: The Case of Wuhan, China". Remote Sensing 12, n. 18 (6 settembre 2020): 2889. http://dx.doi.org/10.3390/rs12182889.
Testo completoAbstract (sommario):
The rapid evolution of cities has brought new challenges to urban planning and management. The accurate evaluation of urban functional structure and mixed use is critical, especially at a fine scale such as by blocks. The composition and mixing of urban spatial functions calculated by remote sensing and statistics are non-quantitative and undetailed. The text topic models are often applied to process text data, but are rarely used to mine semantic information in quantitative data. Therefore, this paper attempts to carry out research on the recognition of urban functions and mixed use using a text topic generation model based on resident mobile data. First, the area within Wuhan Third Ring Road was divided into 2451 units at a grid size of 500 m × 500 m. The histogram-latent Dirichlet allocation (H-LDA) and information entropy were applied to assign different grid units to correct the functional topics and topic information entropy (TIE). Second, the functional categories of different analysis units were calculated using the point of interest (POI), frequency density (FD) and category proportion (CP) indicators, while the functional information entropy (FIE) based on the POI was calculated. Then, the urban functions and mixtures identified by the two kinds of data were compared and analyzed. Finally, referring to the geographic information in streetscape map and applying correlation analysis, the function and mixing results obtained from the experiment were verified. Studies have shown that the H-LDA model can identify bridges, which the POI data have shown is challenging to identify without attributes such as length. The function recognition accuracy of the H-LDA model is 89.3%, which is higher than K-means algorithm and Word2vec models. The correlation coefficient between FIE and TIE is 0.587, indicating that both are highly correlated. These explain the accuracy and rationality of identifying city functions and mixtures based on the H-LDA model. The H-LDA model can be applied to functional computing and fine-scale urban mixed function planning.
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Zhang, Qingjie, Junjuan Zhao, Xiangmeng Long, Quanyong Luo, Ren Wang, Xuehai Ding e Chentian Shen. "AUE-Net: Automated Generation of Ultrasound Elastography Using Generative Adversarial Network". Diagnostics 12, n. 2 (20 gennaio 2022): 253. http://dx.doi.org/10.3390/diagnostics12020253.
Testo completoAbstract (sommario):
Problem: Ultrasonography is recommended as the first choice for evaluation of thyroid nodules, however, conventional ultrasound features may not be able to adequately predict malignancy. Ultrasound elastography, adjunct to conventional B-mode ultrasound, can effectively improve the diagnostic accuracy of thyroid nodules. However, this technology requires professional elastography equipment and experienced physicians. Aim: in the field of computational medicine, Generative Adversarial Networks (GANs) were proven to be a powerful tool for generating high-quality images. This work therefore utilizes GANs to generate ultrasound elastography images. Methods: this paper proposes a new automated generation method of ultrasound elastography (AUE-net) to generate elastography images from conventional ultrasound images. The AUE-net was based on the U-Net architecture and optimized by attention modules and feature residual blocks, which could improve the adaptability of feature extraction for nodules of different sizes. The additional color loss function was used to balance color distribution. In this network, we first attempted to extract the tissue features of the ultrasound image in the latent space, then converted the attributes by modeling the strain, and finally reconstructed them into the corresponding elastography image. Results: a total of 726 thyroid ultrasound elastography images with corresponding conventional images from 397 patients were obtained between 2019 and 2021 as the dataset (646 in training set and 80 in testing set). The mean rating accuracy of the AUE-net generated elastography images by ultrasound specialists was 84.38%. Compared with that of the existing models in the visual aspect, the presented model generated relatively higher quality elastography images. Conclusion: the AUE-net generated ultrasound elastography images showed natural appearance and retained tissue information. Accordingly, it seems that B-mode ultrasound harbors information that can link to tissue elasticity. This study may pave the way to generate ultrasound elastography images readily without the need for professional equipment.
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Watanabe, Chihiro, e Taiji Suzuki. "Goodness-of-fit test for latent block models". Computational Statistics & Data Analysis 154 (febbraio 2021): 107090. http://dx.doi.org/10.1016/j.csda.2020.107090.
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Busenhart, Philipp, Ana Montalban-Arques, Egle Katkeviciute, Yasser Morsy, Chiara Van Passen, Larissa Hering, Kirstin Atrott et al. "Inhibition of integrin αvβ6 sparks T-cell antitumor response and enhances immune checkpoint blockade therapy in colorectal cancer". Journal for ImmunoTherapy of Cancer 10, n. 2 (febbraio 2022): e003465. http://dx.doi.org/10.1136/jitc-2021-003465.
Testo completoAbstract (sommario):
BackgroundIntegrin αvβ6 is a heterodimeric cell surface protein whose cellular expression is determined by the availability of the integrin β6 subunit (ITGB6). It is expressed at very low levels in most organs during tissue homeostasis but shows highly upregulated expression during the process of tumorigenesis in many cancers of epithelial origin. Notably, enhanced expression of integrin αvβ6 is associated with aggressive disease and poor prognosis in numerous carcinoma entities. Integrin αvβ6 is one of the major physiological activators of transforming growth factor-β (TGF-β), which has been shown to inhibit the antitumor T-cell response and cause resistance to immunotherapy in mouse models of colorectal and mammary cancer. In this study, we investigated the effect of ITGB6 expression and antibody-mediated integrin αvβ6 inhibition on the tumor immune response in colorectal cancer.MethodsUsing orthotopic and heterotopic tumor cell injection, we assessed the effect of ITGB6 on tumor growth and tumor immune response in wild type mice, mice with defective TGF-β signaling, and mice treated with anti-integrin αvβ6 antibodies. To examine the effect of ITGB6 in human colorectal cancer, we analyzed RNAseq data from the colon adenocarcinoma dataset of The Cancer Genome Atlas (TCGA-COAD).ResultsWe demonstrate that expression of ITGB6 is an immune evasion strategy in colorectal cancer, causing inhibition of the antitumor immune response and resistance to immune checkpoint blockade therapy by activating latent TGF-β. Antibody-mediated inhibition of integrin αvβ6 sparked a potent cytotoxic T-cell response and overcame resistance to programmed cell death protein 1 (PD-1) blockade therapy in ITGB6 expressing tumors, provoking a drastic increase in anti-PD-1 treatment efficacy. Further, we show that the majority of tumors in patients with colorectal cancer express sufficient ITGB6 to provoke inhibition of the cytotoxic T-cell response, indicating that most patients could benefit from integrin αvβ6 blockade therapy.ConclusionsThese findings propose inhibition of integrin αvβ6 as a promising new therapy for colorectal cancer, which blocks tumor-promoting TGF-β activation, prevents tumor exclusion of cytotoxic T-cells and enhances the efficacy of immune checkpoint blockade therapy.
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Pruess, Karsten. "A Practical Method for Modeling Fluid and Heat Flow in Fractured Porous Media". Society of Petroleum Engineers Journal 25, n. 01 (1 febbraio 1985): 14–26. http://dx.doi.org/10.2118/10509-pa.
Testo completoAbstract (sommario):
Abstract A multiple interacting continua (MINC) method is presented, which is applicable for numerical simulation presented, which is applicable for numerical simulation of heat and multiphase fluid flow in multidimensional, fractured porous media. This method is a generalization of the double-porosity concept. The partitioning of the flow domain into computational volume elements is based on the criterion of approximate thermodynamic equilibrium at all times within each element. The thermodynamic conditions in the rock matrix are assumed to be controlled primarily by the distance from the fractures, which leads to the use of nested gridblocks. The MINC concept is implemented through the integral finite difference (IFD) method. No analytical approximations are made for coupling between the fracture and matrix continua. Instead, the transient flow of fluid and heat between matrix and fractures is treated by a numerical method. The geometric parameters needed in simulation are preprocessed from a specification of fracture spacings and apertures and geometry of the matrix blocks. The numerical implementation of the MINC method is verified by comparison with the analytical solution of Warren and Root. Illustrative applications are given for several geothermal reservoir engineering problems. Introduction In this paper, we present a numerical method for simulating transient nonisothermal, two-phase flow of water in fractured porous medium. The method is base on a generalization of a concept originally proposed by Barenblatt et al. and introduced into the petroleum literature by Warren and Root, Odeh, and others in the form of what has been termed the "double-porosity" model. The essence of this approach is that in a fractured porous medium, fractures are characterized by much porous medium, fractures are characterized by much larger diffusivities (and hence, much smaller response times) than the rock matrix. Therefore, the early system response is influenced by the matrix. In seeking to analytically solve such a system, all fractures were grouped into one continuum and all the matrix blocks into another, resulting in two interacting continua coupled through a mass transfer function determined by the size and shape of the blocks, as well as the local difference in potentials between the two continua. Later, Kazemi and Duguid and Lee incorporated the double-porosity concept into a numerical model. For a more detailed description of the concept and its application, see Refs. 6 through 8. Very little work has been done in investigating nonisothermal, two-phase fluid flow in fractured porous media. Moench and coworkers used the discrete fracture approach to study the behavior of fissured, vapor-dominated geothermal reservoirs. The purpose of our work is first to generalize the double-porosity concept into one of many interacting continua. We then incorporate the MINC model into a simulator for nonisothermal transport of a homogeneous two-phase fluid (water and steam) in multidimensional systems. Our approach is considerably broader in scope and more general than any previous models discussed in the literature. The MINC previous models discussed in the literature. The MINC method permits treatment of multiphase fluids with large and variable compressibility and allows for phase transitions with latent heat effects, as well as for coupling between fluid and heat flow. The transient interaction between matrix and fractures is treated in a realistic way. Although the model can permit alternative formulations for the equation of motion, we shall assume that, macroscopically, each continuum obeys Darcy's law; in particular, we shall use the "cubic law" for the flow of particular, we shall use the "cubic law" for the flow of fluids in fracture. While the methodology presented in this paper is generally applicable to multiphase compositional thermal systems, our illustrative calculations were restricted to geothermal reservoir problems. The numerical method chosen to implement the MINC concept is the IFD method. In this method, all thermophysical and thermodynamic properties are represented by averages over explicitly defined finite subdomains, while fluxes of mass or energy across surface segments are evaluated through finite difference approximations. An important aspect of this method is that the geometric quantities required to evaluate the conductance between two communicating volume elements are provided directly as input data rather than having them generated from data on nodal arrangements and nodal coordinates. Thus, a remarkable flexibility is attained by which one can allow a volume element in any one continuum to communicate with another element in its own or any other continuum. Inasmuch as the interaction between volume elements of different continua is handled as a geometric feature, the IFD methodology does not distinguish between the MINC method and the conventional porous-medium type approaches to modeling. porous-medium type approaches to modeling. SPEJ p. 14
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Mariadassou, Mahendra, e Catherine Matias. "Convergence of the groups posterior distribution in latent or stochastic block models". Bernoulli 21, n. 1 (febbraio 2015): 537–73. http://dx.doi.org/10.3150/13-bej579.
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Colevas, A. Dimitrios Dimitrios, Michelle A. Rudek, Caroline Even, Victor Ho-Fun Lee, Maura L. Gillison, Saad A. Khan, Rong Lu et al. "Phase I/IIa clinical trial of a small molecule EBNA1 inhibitor, VK-2019, in patients with Epstein Barr virus–positive nasopharyngeal cancer with pharmacokinetic and pharmacodynamic correlative studies." Journal of Clinical Oncology 41, n. 16_suppl (1 giugno 2023): 6035. http://dx.doi.org/10.1200/jco.2023.41.16_suppl.6035.
Testo completoAbstract (sommario):
6035 Background: Epstein-Barr Virus (EBV) is associated with a diverse collection of malignancies, including nasopharyngeal carcinoma (NPC). One viral-encoded protein, EBNA1, is consistently expressed in all known EBV-associated malignancies and is critical for the replication and maintenance of the EBV genome in latently infected cells. VK-2019 is a first-in-class, orally bioavailable EBNA1 inhibitor that blocks latent replication and proliferation in preclinical studies. Methods: We conducted a Phase I/IIa clinical trial of VK-2019 as a single therapeutic agent in patients with advanced (recurrent or metastatic) NPC. An accelerated titration design allowed dose escalation to proceed rapidly from 60 mg/day to 1800 mg/day. Blood samples for detailed pharmacokinetic analyses were collected after the first and multiple doses. In addition, tumor biopsies were collected from 2 patients at the 1800 mg/day dose level at baseline and during treatment and analyzed for EBV copy number and viral and cellular gene expression. Results: A total of 22 advanced NPC patients were enrolled. VK-2019 was well tolerated with mostly grade 1-3 adverse events being reported. VK-2019 is rapidly absorbed with a biphasic distribution and a terminal T1/2 of ~12h after single or multiple doses. Cmax and AUC increases with dose escalation through 920 mg with large variability at 1800mg. Accumulation has been observed with multiple doses up to 460mg. Based on preclinical efficacy models, target exposures are at or above expected activity levels for patients at least on the 920 mg daily dose and above. A partial response ( > 30% decrease in tumor size) was observed for one patient. Preliminary results from biopsies from 2 patients show decreases in EBV copy number and viral gene expression (LMP2 and gp150). We also observed decreases in EBER-positive cells in one patient. Conclusions: In this study, VK-2019 was well tolerated, exhibiting an excellent safety profile and exposure above in vitro efficacy. An MTD has not been yet established. Preliminary results indicate a decrease in EBV copy number and viral gene expression in latently infected tumor cells in some patients. Alternate dose schedules are justified to determine the clinical efficacy of an EBNA1 inhibitor in patients with advanced NPC. Funded by NCI, R01-CA235633 and Cullinan Oncology. Clinical trial information: NCT04925544 .
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Wenta, Marta, Christian M. Grams, Lukas Papritz e Marc Federer. "Linking Gulf Stream air–sea interactions to the exceptional blocking episode in February 2019: a Lagrangian perspective". Weather and Climate Dynamics 5, n. 1 (8 febbraio 2024): 181–209. http://dx.doi.org/10.5194/wcd-5-181-2024.
Testo completoAbstract (sommario):
Abstract. The development of atmospheric blocks over the North Atlantic–European region can lead to extreme weather events like heat waves or cold air outbreaks. Despite their potential severe impact on surface weather, the correct prediction of blocking lifecycles remains a key challenge in current numerical weather prediction (NWP) models. Increasing evidence suggests that latent heat release in cyclones, the advection of cold air (cold air outbreaks, CAOs) from the Arctic over the North Atlantic, and associated air–sea interactions over the Gulf Stream are key processes contributing to the onset, maintenance, and persistence of such flow regimes. To better understand the mechanism connecting air–sea interactions over the Gulf Stream with changes in the large-scale flow, we focus on an episode between 20 and 27 February 2019, when a quasi-stationary upper-level ridge was established over western Europe accompanied by an intensified storm track in the northwestern North Atlantic. During that time, a record-breaking winter warm spell occurred over western Europe bringing temperatures above 20 ∘C to the United Kingdom, the Netherlands, and northern France. The event was preceded and accompanied by the development of several rapidly intensifying cyclones that originated in the Gulf Stream region and traversed the North Atlantic. To explore the mechanistic linkage between the formation of this block and air–sea interactions over the Gulf Stream, we adopt a Lagrangian perspective, using kinematic trajectories. This allows us to study the pathways and transformations of air masses that form the upper-level potential vorticity anomaly and interact with the ocean front. We establish that more than one-fifth of these air masses interact with the Gulf Stream in the lower troposphere, experiencing intense heating and moistening over the region due to the frequent occurrence of CAOs behind the cold front of the cyclones. Trajectories moistened by the advection of cold air over a warm ocean by one cyclone later ascend into the upper troposphere with the ascending airstream of a subsequent cyclone, fueled by the strong surface fluxes. These findings highlight the importance of CAOs in the Gulf Stream region, indicating that their intense coupling between the ocean and atmosphere plays a role in block development. Additionally, they provide a mechanistic pathway linking air–sea interactions in the lower troposphere and the upper-level flow.
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Antero, Unai, Francisco Blanco, Jon Oñativia, Damien Sallé e Basilio Sierra. "Harnessing the Power of Large Language Models for Automated Code Generation and Verification". Robotics 13, n. 9 (11 settembre 2024): 137. http://dx.doi.org/10.3390/robotics13090137.
Testo completoAbstract (sommario):
The cost landscape in advanced technology systems is shifting dramatically. Traditionally, hardware costs took the spotlight, but now, programming and debugging complexities are gaining prominence. This paper explores this shift and its implications, focusing on reducing the cost of programming complex robot behaviors, using the latest innovations from the Generative AI field, such as large language models (LLMs). We leverage finite state machines (FSMs) and LLMs to streamline robot programming while ensuring functionality. The paper addresses LLM challenges related to content quality, emphasizing a two-fold approach using predefined software blocks and a Supervisory LLM.
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Babudzhan, Ruslan A., Oleksii O. Vodka e Mariia I. Shapovalova. "Application of computational intelligence methods for the heterogeneous material stress state evaluation". Herald of Advanced Information Technology 5, n. 3 (27 ottobre 2022): 198–209. http://dx.doi.org/10.15276/hait.05.2022.15.
Testo completoAbstract (sommario):
The use of surrogate models providesgreat advantages in working with computer-aided design and 3D modeling systems, which opens up new opportunities for designing complex systems. They also allow us to significantly rationalize the use of computing power in automated systems, for which response time and low energy consumption are critical. This work is devoted to the creation of a surrogate model for approximating the finite element solution of the problem of dispersion–strengthened composite plane sample deformation. An algorithm for constructing a parametric two–dimensional model of a composite is proposed. The calculation model is created using the ANSYS Mechanical computer-aided design and analysis program using the APDL scripting model builder. The parameters of the stress-strain state of the material microstructure are processed using a convolutional neural network. A neural network based on the U–Net architecture of the encoder-decoder type has been created to predict the distribution of equivalent stresses in the material according to the sample geometry and load values. A direct sequence of layers is takenfrom the specified architecture. To increase the speed and stability of training, the type of part of the convolutional layers has been changed. The architecture of the network consists of serially connected blocks, each of which combines layers such as convolution, normalization, activation, subsampling, and a latent space that connects the encoder and decoder and adds load data. To combine the load vector, such a neural network architecture as a concatenator is created, which additionally includes the Dense, Reshape and Concatenate layers. The model loss function is defined as the root mean square error over all points of the source matrix, which calculates the difference between the actual value of the target variable and the value generated by the surrogate model. Optimization ofthe loss function is performed using the first–order gradient local optimization method ADAM. The study of the model learning process is illustrated by plots of loss functions and additional metrics. There is a tendency for the indicators to coincide between the training and validation sets, which indicates the generalizing capability of the model. Analyzing the output of the model andthe value of the metrics, a conclusion is made about the sufficient quality of the model. However, the values of the network weights after training are still not optimal in terms of minimizing the loss function. And also, to accurately reproduce the solution of the finite element method (FEM), the proposed model is quite simple and requires clarification. The speed comparisonof obtaining results by the FEM and using the architecture of the neural network is proposed. The surrogate model is significantly ahead of the FEM and is used to speed up calculations and determine the overall quality of the approximation of problems of mechanics of this type
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Solovitskiy, Aleksandr. "Digital cartographic support of geodynamic safety of subsoil use based on UAV technologies". E3S Web of Conferences 164 (2020): 07001. http://dx.doi.org/10.1051/e3sconf/202016407001.
Testo completoAbstract (sommario):
It is established that the problem of digital cartographic support for geodynamic safety based on UAV technologies is the following: on the one hand, a significant increase in accuracy and efficiency of survey work and on the other hand – the lack of new models for approximating the crustal blocks, taking into account the adequacy of their configuration, hierarchy, structure, interaction and geodynamic activity. Traditional technologies are focused on the use of flat models of crustal blocks, which are not adequate and give ambiguous state parameters. The aim of the research is to develop a theory of digital cartographic support for the geodynamic safety of subsurface use, which provides not only the creation of new models of blocks of the earth’s crust based on their selection and identification, taking into account the accuracy of cartographic materials, but also provides an information basis for gaining new knowledge about their stress-strain state according to the structure hierarchy which is necessary to solve this problem. Based on the performed research, it was found that the morphostructural analysis of the cartographic materials of the territory in the area of the mining enterprise, obtained on the basis of UAV technologies, is more informative and automated, covers the latest period up to one million years and takes into account the dependence of their errors on the duration and relaxation of geodynamic processes . The practical use of this theory is safe subsoil use.
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Luo, Xiaoling, Chengliang Liu, Waikeung Wong, Jie Wen, Xiaopeng Jin e Yong Xu. "MVCINN: Multi-View Diabetic Retinopathy Detection Using a Deep Cross-Interaction Neural Network". Proceedings of the AAAI Conference on Artificial Intelligence 37, n. 7 (26 giugno 2023): 8993–9001. http://dx.doi.org/10.1609/aaai.v37i7.26080.
Testo completoAbstract (sommario):
Diabetic retinopathy (DR) is the main cause of irreversible blindness for working-age adults. The previous models for DR detection have difficulties in clinical application. The main reason is that most of the previous methods only use single-view data, and the single field of view (FOV) only accounts for about 13% of the FOV of the retina, resulting in the loss of most lesion features. To alleviate this problem, we propose a multi-view model for DR detection, which takes full advantage of multi-view images covering almost all of the retinal field. To be specific, we design a Cross-Interaction Self-Attention based Module (CISAM) that interfuses local features extracted from convolutional blocks with long-range global features learned from transformer blocks. Furthermore, considering the pathological association in different views, we use the feature jigsaw to assemble and learn the features of multiple views. Extensive experiments on the latest public multi-view MFIDDR dataset with 34,452 images demonstrate the superiority of our method, which performs favorably against state-of-the-art models. To the best of our knowledge, this work is the first study on the public large-scale multi-view fundus images dataset for DR detection.
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Fu, Siqing, Gerald S. Falchook, Minal Barve, Meredith McKean, Tira J. Tan, Charlotte Lemech, Cheng E. Chee et al. "Abstract 2155: Joint modeling of safety and peripheral mode-of-action (MoA) biomarkers to support RP2D identification in Phase 1 study of SAR444245 (SAR’245) as monotherapy (mono) or combined with pembrolizumab (pembro) in patients with advanced solid tumors". Cancer Research 83, n. 7_Supplement (4 aprile 2023): 2155. http://dx.doi.org/10.1158/1538-7445.am2023-2155.
Testo completoAbstract (sommario):
Abstract Background: SAR’245 is a clinical-stage site-specific pegylated human IL-2 that blocks IL-2 alpha receptor binding but retains near-native binding affinity for beta/gamma IL-2 receptor subunits. When administered in preclinical models, a unique ‘T-cell remodeling’ MoA characterized by robust increase of CD8+Teff/CD4+Treg coupled with potent NK-cell activation/expansion was observed. Circulating tumor DNA (ctDNA) can be used as a non-invasive biomarker of early clinical response whilst overcoming challenges of obtaining repeat tumor biopsies from patients. Previously, we reported results of the Phase 1 HAMMER study (NCT04009681); herein, we describe an innovative integrative approach that considers peripheral key MoA biomarkers with objective response and dose-limiting toxicity (DLT) rate to help identify the recommended Phase 2 dose (RP2D) for SAR’245. Methods: SAR’245 was given IV as mono Q3W [Cohort B] or Q3W + IV pembro 200 mg Q3W/400 mg Q6W [Cohort C]. Joint modeling was carried out to account for the relationship between dose and 1) MoA biomarkers, and NK cells in blood measured by flow cytometry; 2) response surrogate biomarker: ctDNA measured by Guardant Omni 500 panel; and 3) DLTs. In the model, a latent variable was used to model correlation between DLT and the MoA or response surrogate biomarkers, Bayesian approach was used to derive posterior probabilities (PP) at each dose level of the target region (defined by >20% probability of fold change of biomarker values post-treatment above a predefined threshold and DLT rate <33%) and the PP of the overdose region (defined by DLT rate ≥33%). RP2D dose level was determined by maximizing the PP of target region among doses with PP of the overdose region probability <40%. Results: Samples from 35 subjects (Cohort B) and 34 subjects (Cohort C) were available. The results from SAR’245 mono suggests that the CD8/CD4 ratio and the concentrations of NK, CD8, and CD4 achieve maximum probability of reaching meaningful modulation (based on pre-defined threshold) around 32 ug/kg. When SAR’245 was combined with pembro, the results with PoM biomarkers showed the best performance at 24-32 µg/kg, while results with ctDNA showed the best results at 16-24 µg/kg. When all parameters were considered, either 24 or 32 µg/kg could serve as an adequate dose at Q3W scheduling. Conclusions: In early oncology studies, joint modeling using non-invasive biomarkers, including MoA and response biomarkers, and a safety profile can inform dose-response relationships and support RP2D selection. This innovative integrative modeling will guide clinical study design. Studies of SAR’245 that further explore the dosing and scheduling are on-going. Disclosures: This study was sponsored by Synthorx, a Sanofi company. Citation Format: Siqing Fu, Gerald S. Falchook, Minal Barve, Meredith McKean, Tira J. Tan, Charlotte Lemech, Cheng E. Chee, Neyssa Marina, Giovanni Abbadessa, Robin Meng, Federico Rotolo, Hong Wang, Jason Deng, Wenting Wang, Rui Wang, Tarek Meniawy. Joint modeling of safety and peripheral mode-of-action (MoA) biomarkers to support RP2D identification in Phase 1 study of SAR444245 (SAR’245) as monotherapy (mono) or combined with pembrolizumab (pembro) in patients with advanced solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2155.
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Peter Jan, Mark Verheyden. "A Theoretical Framework for the Analysis of Messages on Enterprise Social Media / Conocer el Contenido de los Medios Sociales Empresariales: Hacia el Desarrollo de un Marco Analítico Comunicativo". Revista Internacional de Relaciones Públicas 7, n. 13 (27 giugno 2017): 5–22. http://dx.doi.org/10.5783/revrrpp.v7i13.455.
Testo completoAbstract (sommario):
This article uses the structure of Harold Lasswell's communication act to develop a theoretical instrument with which the content of messages on Enterprise Social Media can be analyzed. Each of the elements in Lasswell's model are the building blocks of our own theoretical framework. With the help of the latest literature on the use of corporate social networks, we aim to develop an instrument that will allow both scholars and practitioners to analyze the content on these platforms in a systematic way.En este artículo se adapta el modelo comunicativo de Lasswell en un nuevo marco para el análisis de contenido en los Medios Sociales aplicados al ámbito empresarial (ESM en sus siglas en inglés). Para ello, el autor revisa sistemáticamente una década de literatura (2007-2016) en tres bases de datos científicas (Web of Science, Scopus y Business Source Premier) y examina críticamente cómo el nuevo marco complementa los modelos existentes. El nuevo instrumento consta de catorce parámetros organizados en las distintas fases del modelo de Lasswell (1948). En el ámbito teórico, el artículo llena el vacío existente en el análisis de la intersección entre relaciones públicas y medios sociales. A nivel aplicado, el modelo puede ser de utilidad para evaluar si las ESM sirven a la comunicación profesional.
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Hall, Thomas. "Post-war new town 'models': a European comparison". Urban Morphology 9, n. 2 (3 giugno 2005): 109–21. http://dx.doi.org/10.51347/jum.v9i2.3923.
Testo completoAbstract (sommario):
Stevenage, Tapiola (Hagalund) and Vällingby were the first exponents of the new town concept in Britain, Finland and Sweden respectively, attracting attention not only within their home countries but also widely in Europe. In all three places, general plans were finalized around 1950, testing the latest ideas B such as neighbourhood units, the Radburn concept and community centres. The towns were to be organized in cohesive neighbour-hood areas, each with its own identity and its own community centre. The three towns differ in their morphological character. In Tapiola the scale is modest but the variation all the greater. In Stevenage the single-family house predominates, while in Tapiola there is a mixture of house types. Vällingby is dominated by blocks of flats, though there are also row houses and detached houses. In all three towns resources and interest were invested in achieving a modern main centre, which included cultural and social activities as well as commercial ones. Each town epitomized a new, brighter future, perhaps reflecting an optimism that was stronger in Scandinavia and Britain than elsewhere. The firm faith that characterized the drive to build the three new towns may seem slightly naive from today=s point of view. Yet it is clear that we can learn a lot from the enthusiasm and fighting spirit of the 1950s, the social commitment, and the desire to create good housing, preferably with ample outdoor environments, affordable to broad groups of citizens.
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Boiko, Maksym, Viacheslav Moskalenko e Oksana Shovkoplias. "Advanced file carving: ontology, models and methods". Radioelectronic and Computer Systems, n. 3 (29 settembre 2023): 204–16. http://dx.doi.org/10.32620/reks.2023.3.16.
Testo completoAbstract (sommario):
File carving techniques are important in the field of digital forensics. At the same time, the rapid growth in the amount and types of data requires the development of file carving methods in terms of capabilities, accuracy, and computational efficiency. However, most of the methods are developed to solve specific tasks and are based on a certain set of assumptions and a priori knowledge about the files to be recovered. There is a lack of research that systematizes methods and structures approaches to identify gaps and determine perspective directions for development, considering the latest advances in information technology and artificial intelligence. The subject matter of this article is the structure, factors, efficiency criteria, methods, and tools of file carving, as well as the current state and tendencies of development of file carving methods. The goal of this study is to systematize knowledge about advanced file carving methods and identify perspective directions for their development. The tasks to be solved are as follows: to identify the main stages of file carving and analyze approaches to their implementation; to build an ontological scheme of file carving; and to identify perspective directions for the development of carving methods. The methods used were literature review, systematization, and summarization. The obtained results are as follows. An ontological scheme for the file carving concept is constructed. The scheme includes the principles, properties, phases, techniques, evaluation criteria, tools used, and factors influencing file carving. The features, limitations, and fields of application of the data recovery methods are provided. It was established that the most widespread approach to file reconstruction is still a manually detailed analysis of the internal structure of files and/or their contents, identifying specific patterns that allow reassembling the sequence of data fragments in the correct order. However, most of the methods do not provide one hundred percent guaranteed results. This article analyzes the current state and prospects of using artificial intelligence methods in the field of digital forensics, particularly for identifying data blocks, clustering, and reconstructing files, as well as restoring the contents of media files with damaged or lost headers. The necessity of having priori information about the file structure or content for successfully carving fragmented data is determined. Conclusions. The scientific novelty of the obtained results is as follows: for the first time, advanced file carving methods are systematized and analyzed by directions of development and the perspectives of using artificial intelligence for identifying data blocks, clustering, and file content restoration; for the first time, an ontological scheme of file carving is constructed, which can be used as a roadmap for developing new advanced systems in the digital forensics field.
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Junk, Philipp, e Christina Kiel. "HOMELETTE: a unified interface to homology modelling software". Bioinformatics 38, n. 6 (25 dicembre 2021): 1749–51. http://dx.doi.org/10.1093/bioinformatics/btab866.
Testo completoAbstract (sommario):
Abstract Summary Homology modelling, the technique of generating models of 3D protein structures based on experimental structures from related proteins, has become increasingly popular over the years. An abundance of different tools for model generation and model evaluation is available from various research groups. We present HOMELETTE, an interface which implements a unified programmatic access to these tools. This allows for the assemble of custom pipelines from pre- or self-implemented building blocks. Availability and implementation HOMELETTE is implemented in Python, compatible with version 3.6 and newer. It is distributed under the MIT license. Documentation and tutorials are available at Read the Docs (https://homelette.readthedocs.io/). The latest version of HOMELETTE is available on PyPI (https://pypi.org/project/homelette/) and GitHub (https://github.com/PhilippJunk/homelette). A full installation of the latest version of HOMELETTE with all dependencies is also available as a Docker container (https://hub.docker.com/r/philippjunk/homelette_template). Supplementary information Supplementary data are available at Bioinformatics online.
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Antić, S., J. R. Stone e A. W. Thomas. "Neutron stars from crust to core within the Quark-meson coupling model". EPJ Web of Conferences 232 (2020): 03001. http://dx.doi.org/10.1051/epjconf/202023203001.
Testo completoAbstract (sommario):
Recent years continue to be an exciting time for the neutron star physics, providing many new observations and insights to these natural ‘laboratories’ of cold dense matter. To describe them, there are many models on the market but still none that would reproduce all observed and experimental data. The quark-meson coupling model stands out with its natural inclusion of hyperons as dense matter building blocks, and fewer parameters necessary to obtain the nuclear matter equation of state. The latest advances of the QMC model and its application to the neutron star physics will be presented, within which we build the neutron star’s outer crust from finite nuclei up to the neutron drip line. The appearance of different elements and their position in the crust of a neutron star is explored and compared to the predictions of various models, giving the same quality of the results for the QMC model as for the models when the nucleon structure is not taken into account.
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Rodriguez-Salvador, Marisela, Baruc Emet Perez-Benitez e Karen Marcela Padilla-Aguirre. "Discovering the Latest Scientific Pathways on Tissue Spheroids: Opportunities to Innovate". International Journal of Bioprinting 7, n. 1 (29 gennaio 2021): 331. http://dx.doi.org/10.18063/ijb.v7i1.331.
Testo completoAbstract (sommario):
Tissue spheroids consist of a three-dimensional model of cells which is capable of imitating the complicated composition of healthy and unhealthy human tissue. Due to their unique properties, they can bring innovative solutions to tissue engineering and regenerative medicine, where they can be used as building blocks for the formation of organ and tissue models used in drug experimentation. Considering the rapid transformation of the health industry, it is crucial to assess the research dynamics of this field to support the development of innovative applications. In this research, a scientometric analysis was performed as part of a Competitive Technology Intelligence methodology, to determine the main applications of tissue spheroids. Papers from Scopus and Web of Science published between 2000 and 2019 were organized and analyzed. In total, 868 scientific publications were identified, and four main categories of application were determined. Main subject areas, countries, cities, authors, journals, and institutions were established. In addition, a cluster analysis was performed to determine networks of collaborations between institutions and authors. This article provides insights into the applications of cell aggregates and the research dynamics of this field, which can help in the decision-making process to incorporate emerging and innovative technologies in the health industry.
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Williams, Harold, e M. A. J. Piasecki. "The Cold Spring Melange and a possible model for Dunnage–Gander zone interaction in central Newfoundland". Canadian Journal of Earth Sciences 27, n. 8 (1 agosto 1990): 1126–34. http://dx.doi.org/10.1139/e90-117.
Testo completoAbstract (sommario):
Structural relationships at Cold Spring Pond and the recognition of ophiolitic melange bear on the important questions of timing and style of structural superpositioning of Dunnage Zone rocks above Gander Zone rocks in central Newfoundland. The latest models emphasize ductile shear boundaries and orogen-parallel movements. Previous models proposed west-to-east or head-on obduction of Dunnage ophiolitic rocks across the Gander Zone.At the Dunnage (Exploits Subzone) – Gander (Meelpaeg Subzone) boundary at Cold Spring Pond, discrete, outcrop-size ultramafic blocks and smaller quartzite blocks are randomly distributed, and they are surrounded by, or are embedded in, homogeneous black graphitic shale or phyllite. The ultramafic blocks are typical of nearby Early Ordovician Dunnage ophiolite suites, the quartzite blocks are typical of adjacent Early Ordovician or earlier Gander clastic rocks, and the matrix black shales are similar to those of Middle or Early Ordovician age that occur throughout central Newfoundland. This chaotic mixture of almost coeval lithologies at Cold Spring Pond is interpreted as an olistostromal melange; the Cold Spring Melange. It resembles melanges that are dated as Ordovician elsewhere in Newfoundland.The Cold Spring Melange is overprinted by the full range of structures and metamorphic effects evident in adjacent rocks of the Exploits (Dunnage) and Meelpaeg (Gander) subzones. These include the development of lineations, cleavages, schistosities, zones of ductile shearing, regional metamorphism, and contact metamorphism. The oldest of these effects are interpreted as Silurian, based on isotopic dating in southern Newfoundland.The formation of olistostromal, ophiolitic melange implies disruption of the oceanic tract (Exploits Subzone of the Dunnage Zone), and in the case of the Cold Spring example, juxtapositioning or transport of Exploits Subzone ophiolite suites against or across the supracrustal rocks of the Meelpaeg Subzone (Gander Zone). The age and provenance of Cold Spring components, lack of post-Ordovician components, overprinting structural relationships, and comparison with other Newfoundland melanges all support an Ordovician age of formation. Overprinting relationships indicate that major ductile shears at other Dunnage–Gander zone boundaries postdate initial Dunnage–Gander superpositioning.
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Zhang, Chao, Xiaoxuan Xu, Timothy Trotter, Amjad Javed, Joanne E. Murphy-Ullrich, Juan Li e Yang Yang. "Runx2 Deficiency in Osteoblasts Promotes Myeloma Resistance to Bortezomib By Increasing TSP-1-Dependent TGF-β1 Activation in Bone Marrow". Blood 138, Supplement 1 (5 novembre 2021): 1575. http://dx.doi.org/10.1182/blood-2021-149310.
Testo completoAbstract (sommario):
Abstract Multiple myeloma (MM) is a plasma cell malignancy that thrives in the bone marrow (BM). The proteasome inhibitor bortezomib (BTZ) is one of the most effective front-line chemotherapeutic drugs for MM; however, 15-20% of high-risk patients do not respond to or become resistant to this drug and the mechanisms of chemoresistance remain unclear. We previously demonstrated that MM cells inhibit Runt-related transcription factor 2 (Runx2) in pre- and immature osteoblasts (OBs). In the current study, we investigated the impact of OB-Runx2 deficiency on the outcome of BTZ treatment using our syngeneic mouse model of MM in which Runx2 is specifically deleted in the immature OBs of C57BL6/KaLwRij mice (OB-Runx2 -/- mice) and OB-Runx2 +/+ mice as control. Five-week-old OB-Runx2 +/+ mice and OB-Runx2 -/- mice were i.v. injected with 5TGM1-Luc murine MM cells (2×10 6). On day 8, after the tumor injection, mice were randomly assigned to treatment for 4 weeks, with either BTZ (i.p. injection, 0.5 mg/kg body weight, twice/week) or PBS. Bioluminescence imaging and serum IgG2bκ (a soluble marker of 5TGM1 MM cells) ELISA showed that BTZ significantly inhibited tumor growth in OB-Runx2 +/+ mice, but not in OB-Runx2 -/- mice. Cytokine array and ELISA showed that in PBS-treated, tumor-bearing OB-Runx2 -/- mice, BM levels of thrombospondin-1 (TSP-1), a matricellular protein that converts latent TGF-β1 to its active form, and active TGF-β1 were significantly higher than levels in tumor-bearing OB-Runx2 +/+ counterparts. Interestingly, BTZ treatment further increased the levels of both TSP-1 and active TGF-β1 in the BM of tumor-bearing OB-Runx2 -/- mice, but it did not affect the level of either TSP-1 or TGF-β1 in the BM of tumor-bearing OB-Runx2 +/+ mice. These results suggest that OB-Runx2 deficiency increases TGF-β1 activation via TSP-1 in BM and BTZ treatment further enhances this effect. SRI31277 is a tripeptide antagonist that blocks TSP-1-mediated activation of TGF-β1 and it has been shown to reduce tumor burden, TGF-β signaling, and osteolytic bone disease in multiple mouse models of MM. To confirm the involvement of TSP-1/TGF-β1 activation in MM BTZ resistance induced by OB-Runx2 deficiency and to test whether blocking TSP1-mediated TGF-β1 activation can alleviate BTZ resistance, 5TGM1-Luc MM tumor-bearing OB-Runx2 +/+ and OB-Runx2 -/- mice were treated with PBS, BTZ, SRI31277 (osmotic pump, 30 mg/kg body weight per day), or BTZ + SRI31277 for 4 weeks. While SRI31277 did not further increase BTZ-induced MM inhibition in OB-Runx2 +/+ mice, SRI31277 treatment significantly reduced the tumor burden in OB-Runx2 -/- mice. Furthermore, treatment with BTZ + SRI31277 augmented the reduction in tumor burden induced by SRI31277 treatment alone. Flow cytometry and Western blot analyses demonstrated that SRI31277 treatment enhanced apoptosis, reduced Ki-67 expression as well as the activity of both canonical (SMAD2/3) and non-canonical (ERK1/2) signaling pathways of TGF-β1 in MM cells in OB-Runx2 -/- mice; and BTZ+SRI31277 treatment augmented these effects. Furthermore, TGF-β has immunosuppressive effects in MM and our data show that SRI31277 overcomes this by reducing myeloid derived suppressor cells, checkpoint, and T cell exhaustion markers and by increasing cytotoxic T cells. In conclusion, OB-Runx2 deficiency, induced by MM cells, promotes MM resistance to BTZ through the upregulation of TGF-β1 activation in the BM and TGF-β1 signaling in MM cells. Importantly, blocking TSP-1-mediated TGF-β1 activation with SRI31277 can reverse this resistance and immune dysfunction. Our findings demonstrate a novel mechanism for BTZ resistance in MM and identify a new target and strategy for overcoming immune dysregulation and chemoresistance in MM. Disclosures Murphy-Ullrich: Millipore Sigma: Patents & Royalties.
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Koya, Junji, Tomohiko Tanigawa, Kota Mizuno, Haryoon Kim, Yuta Ito, Mitsuhiro Yuasa, Kentaro Yamaguchi et al. "Modeling NK-Cell Lymphoma in Mice Reveals Cell-of-Origin, Microenvironment, and Therapeutic Targets". Blood 144, Supplement 1 (5 novembre 2024): 1608. https://doi.org/10.1182/blood-2024-207082.
Testo completoAbstract (sommario):
Extranodal NK/T-cell lymphoma (ENKTCL) is an Epstein-Barr virus (EBV)-related neoplasm preferentially involving the upper aerodigestive tract. However, what mechanisms underlie such site predilection and which NK-cell subpopulation is responsible for ENKTCL remain unclear. As current treatment shows limited efficacy, exploring the pathogenic mechanisms and developing novel therapeutic strategies are required in ENKTCL. However, an important limitation of the field is the lack of a genetically engineered mouse model (GEMM) recapitulating genetic events in human ENKTCL. To address this, we developed a mouse model by NK-cell-specific Trp53 disruption (Trp53-/-), which died earlier than wild-type mice, with a median survival of 417 days. Macroscopic evaluation at death demonstrated the enlargement of the salivary glands, in addition to hepatosplenomegaly and occasional abdominal mass. Histological and flow cytometric analyses of the tumors revealed atypical lymphoid infiltration with a population of Lin-CD122+NK1.1- cells, resembling immature NK cells. Thus, Trp53-/- mice developed NK-cell lymphomas involving the salivary glands and the hematopoietic system. Salivary gland NK cells are tissue-resident NK cells that are distinct from conventional NK cells. We investigated how Trp53 deficiency has different effects on NK cells across these tissues in the pre-tumor state. Remarkably, Trp53 knockout caused an increase of Lin-CD122+NK1.1- cells and extensive gene expression changes of NK cells exclusively in the salivary glands. Thus, we evaluated characteristic phenotypes of tissue-resident NK cells and found that not only murine NK-cell tumors but also human ENKTCL samples expressed tissue-resident markers such as CD69 and CD49a, suggesting tissue-resident NK cells as their cell-of-origin. To investigate genetic profiles of Trp53-/- tumors, we performed whole-exome sequencing, which revealed recurrent Myc amplifications. In addition, RNA sequencing (RNA-seq) showed the significant enrichment of MYC target gene signatures in these tumors. To investigate the role of EBV-encoded latent membrane protein 1 (LMP1) in NK-cell lymphomagenesis, we introduced the expression of LMP1 into our mouse model (Trp53-/-LMP1+). LMP1 expression significantly accelerated NK-cell lymphomagenesis. Single-cell RNA-seq of the tumors showed LMP1-mediated propagation of myeloid cells, including monocytes and conventional dendritic cells (DC), through interferon-γ signaling. Cell-cell interaction analysis revealed that LMP1-induced myeloid cell expansion promoted tumor cell proliferation through upregulated CXCL16-CXCR6 signaling. We validated the presence of CD11c+ DC in the tumor microenvironment and CXCR6 and CXCR3 protein expressions in tumor cells by immunohistochemical analysis of human ENKTCL samples. Importantly, inhibition of CXCL16-CXCR6 signaling was effective against NK-cell tumors in vivo. Using single-cell RNA-seq and flow cytometric analyses, we also found the significant expansion of KLRG1-expressing cells within the tumors. These cells harbored the capacity to repopulate tumors in secondary recipients. We validated the upregulation of KLRG1 expression in human ENKTCL samples through RNA-seq data and immunohistochemical analysis. We then examined whether targeting tumor cells with anti-KLRG1 antibody is effective against murine NK-cell tumors and found that anti-KLRG1 antibody strikingly prolonged the survival of mice transplanted with Trp53-/- tumors. As the effectiveness of anti-KLRG1 antibody was modest against Trp53-/-LMP1+ tumors, we further explored another therapeutic target and identified further upregulation of MYC target gene signature in Trp53-/-LMP1+ tumors. Therefore, we treated mice bearing Trp53-/-LMP1+ tumors with silvestrol, an eIF4A inhibitor that blocks Myc translation. While silvestrol alone slightly improved the survival, combining it with an anti-KLRG1 antibody further extended the survival. In conclusion, using GEMM recapitulating the human disease, we have delineated the cell-of-origin and microenvironmental changes and exploited novel therapeutic targets, including CXCL16, KLRG1, and MYC for ENKTCL. These observations prove that our mouse models will serve as valuable tools for elucidating the pathogenic mechanisms and refining diagnostic and therapeutic strategies in ENKTCL.
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Ametova, Elnara. "Framework development for software functionality in Uzbekistan’s block route centralization system". E3S Web of Conferences 592 (2024): 07017. http://dx.doi.org/10.1051/e3sconf/202459207017.
Testo completoAbstract (sommario):
The article notes the relevance of the use of the latest scientific and technical developments, in transportation management justified by the need to increase the intensity of train traffic and ever-increasing freight turnover while maintaining the safety of train traffic. The solution of actual innovative tasks on the application of electronic devices in railway automation and telemechanics devices will allow to increase the level of transportation safety. Digital information processing and frame modeling techniques were used to achieve this goal. The method of microelectronic implementation of blocks of the set group of the route relay centralization system functional purpose is considered. To formalize the description of blocks of the set group, the method of role frames has been developed, which allows to obtaining of unified information and mathematical support for microprocessor blocks of the set group that control the switching of points, the operation of shunting, and trainset signals. The software purpose of the coupled point control unit is to constantly survey the slot descriptions to determine a positive or negative response. Change of state〖g〗_“PU1,” g_“MU1” indicates the beginning of the procedure for setting a route passing through this point. Changes in the state of the variable g_“NKN,” g_“KN” control units of shunting and trainset signals determine the directions of the software when setting routes. The use of role frame models allowed to optimize the software structure of microcontrollers used to replace the relay contact hardware of the route relay centralization system.
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Sentsov, A. A., e A. O. Agibalov. "Determination of seismic generation zones of Fennoscandia according to data of analysis of seismicity and computer geodynamic modelling". Moscow University Bulletin. Series 4. Geology 1, n. 1 (27 gennaio 2022): 15–22. http://dx.doi.org/10.33623/0579-9406-2021-1-15-22.
Testo completoAbstract (sommario):
The work is devoted to the problem of identifying zones of seismic generstion zones of Fennoscandia, for the solution of which structural-geomorphological interpretation was carried out, seismicity analysis and computer modeling of the latest geodynamics were performed. According to the results of structural-geomorphological interpretation, the territory under consideration was divided into 6 large blocks. Computer modeling showed that each of them is characterized by a certain type of stress state in recent times, and also allowed us to calculate the probability of the formation of new short-distance faults. The reliability of the constructed models is evidenced by the established numerical correlation between this parameter and the density of earthquake epicenters. Based on the data on the density of earthquake epicenters and areas of the possible formation of new faults, a map of seismic generation zones of Fennoscandia was developed.
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Nawalany, Marek, e Grzegorz Sinicyn. "Scale problems in assessment of hydrogeological parameters of groundwater flow models". Geologos 21, n. 3 (1 settembre 2015): 179–85. http://dx.doi.org/10.1515/logos-2015-0012.
Testo completoAbstract (sommario):
Abstract An overview is presented of scale problems in groundwater flow, with emphasis on upscaling of hydraulic conductivity, being a brief summary of the conventional upscaling approach with some attention paid to recently emerged approaches. The focus is on essential aspects which may be an advantage in comparison to the occasionally extremely extensive summaries presented in the literature. In the present paper the concept of scale is introduced as an indispensable part of system analysis applied to hydrogeology. The concept is illustrated with a simple hydrogeological system for which definitions of four major ingredients of scale are presented: (i) spatial extent and geometry of hydrogeological system, (ii) spatial continuity and granularity of both natural and man-made objects within the system, (iii) duration of the system and (iv) continuity/granularity of natural and man-related variables of groundwater flow system. Scales used in hydrogeology are categorised into five classes: micro-scale – scale of pores, meso-scale – scale of laboratory sample, macro-scale – scale of typical blocks in numerical models of groundwater flow, local-scale – scale of an aquifer/aquitard and regional-scale – scale of series of aquifers and aquitards. Variables, parameters and groundwater flow equations for the three lowest scales, i.e., pore-scale, sample-scale and (numerical) block-scale, are discussed in detail, with the aim to justify physically deterministic procedures of upscaling from finer to coarser scales (stochastic issues of upscaling are not discussed here). Since the procedure of transition from sample-scale to block-scale is physically well based, it is a good candidate for upscaling block-scale models to local-scale models and likewise for upscaling local-scale models to regional-scale models. Also the latest results in downscaling from block-scale to sample scale are briefly referred to.
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Valenti, Michael. "Fluid Rising". Mechanical Engineering 121, n. 03 (1 marzo 1999): 60–63. http://dx.doi.org/10.1115/1.1999-mar-3.
Testo completoAbstract (sommario):
This article describes that ergonomic design, improved operation, and increased lifting capability are key elements in the latest models of hydraulic forklifts. More supportive seats and touch-sensitive hydraulic controls are among the ergonomic innovations that Mitsubishi engineered into its latest generation of forklifts. Mitsubishi forklift engines are equipped with hardened steel valve inserts and automatic valves to extend their reliability throughout the length of their performance life. The Mitsubishi designers worked on improving the operator's ability to see through the forklift truck's mast, the structure that carries the forks, by repositioning the hydraulic cylinders and the multiplying chain. Outdoor forklift trucks, also known as rough terrain lift trucks, have been undergoing a change as well. These vehicles offload pallets of bricks, concrete blocks, insulation, and lumber delivered to construction sites. An operator mounts the Manitransit forklift on the rear of a trailer by inserting its forks into the truck's sleeves so that it can be transported to and from unloading sites. The forklifts give drivers full visibility because the telescopic boom needs no mast that might obstruct the view over the forks and load. The boom is mounted low on the truck to ensure a clear field of vision.
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Usmani, Anisul Ain, Syed Afsar Abbas, Usuf Rahaman, Mohammad Ikram e Farooq Hussain Bhat. "The role of the elemental nature of A = 3 nuclei in neutron-rich nuclei". International Journal of Modern Physics E 27, n. 07 (luglio 2018): 1850060. http://dx.doi.org/10.1142/s021830131850060x.
Testo completoAbstract (sommario):
The idea of treating the trinucleon systems as elementary entities in the elementary particle model (EPM) as an Effective Field Theory has been a success in explaining the weak charge-changing processes in nuclei. The EPM results are found to be as good as those obtained from nuclear microscopic models using two-and three-body forces. We extend this concept to investigate the validity of the elemental nature of [Formula: see text] nuclei through studies of nuclear structure of neutron-rich nuclei. By treating neutron-rich nuclei as primarily made up of tritons as its building blocks, we extract one- and two-triton separation energies of these nuclei. Calculations have been performed here within relativistic mean field (RMF) models with latest interactions. Clear evidence arises of a new shell structure with well-defined predictions of new magic nuclei. These unique predictions have been consolidated by standard one- and two-neutron separation energy calculations. The binding energy per nucleon plots of these nuclei also confirm these predictions. We make unambiguous prediction of six magic nuclei: [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text].
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Mikami, Hiro, Kei Torigoe, Makoto Inokawa e Masato Edahiro. "LLVM Instruction Latency Measurement for Software-Hardware Interface for Multi-many-core". INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 22 (27 maggio 2022): 50–63. http://dx.doi.org/10.24297/ijct.v22i.9231.
Testo completoAbstract (sommario):
The increasing scale and complexity of embedded systems and the use of multi-many-core processors have resulted in a corresponding increase in the demand for software development with a high degree of parallelism. The degree of parallelism in software and the accuracy of performance estimation in the early design stages of model-based development can be improved by estimating performance of blocks in models and utilizing the estimate for parallelization. Research is therefore being performed on a software performance estimation technique that uses the IEEE2804-2019 hardware feature description called software-hardware interface for multi-many-core (SHIM). In SHIM, each LLVM-IR instruction is associated with the execution cycle of the target processor. Because several types of assembly instruction sequences for the target processor are generated from a given LLVM-IR instruction, it is not easy to estimate the number of execution cycles. In this study, we propose a regression analysis method to estimate the execution cycles for each LLVM-IR instruction. It is observed that our method estimated the execution cycles within the target error of ±20% in experiments using a Raspberry Pi3 Model B+.
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Kaldunski, Pawel, e Leon Kukielka. "Numerical Analysis and Simulation of Drawpiece Forming Process by Finite Element Method". Applied Mechanics and Materials 474 (gennaio 2014): 153–58. http://dx.doi.org/10.4028/www.scientific.net/amm.474.153.
Testo completoAbstract (sommario):
This paper shows the application of an incremental modelling and numerical solution of the contact problem between movable elastic or rigid tool and elastic/visco-plastic bodies developed in [ to the numerical simulation of drawpiece forming process for the case of rigid tool (punch and die block) and elastic-plastic body (drawpiece). Also the current state of knowledge of the subject matter of the drawing process, modelling and simulation of this process is discussed. The latest and unconventional methods of drawpiece forming have been presented. The important factors determining the proper formation of drawpiece and the ways of their determination have been described. Three types of material models have been used: elastic-plastic model with the linear hardening, elastic-plastic model with the power-law hardening and Frederic's Barlat model which takes into account the anisotropy in three main directions and three tangents. For an example of selected simulations, dependence of punch force from its displacement for different types of die blocks has been presented.
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Sudha, S., A. Narmadha, G. Amutha e Nishu Ayedee. "Role of emerging technologies in marketing and decision making – PRISMA Model". Journal of Information and Optimization Sciences 45, n. 6 (2024): 1591–605. http://dx.doi.org/10.47974/jios-1636.
Testo completoAbstract (sommario):
In recent years technology and its applications have brought a lot of transformation into business and various industries. ChatGPT, natural language processing, machine learning, and deep learning have become the buzzword and have taken the world by storm. It has brought a lot of transformation to the industry. The latest ChatGPT-3 have helped to determine the megatrends i.e., technological, demographic, economic and societal changes. Sentimental analysis is used in the healthcare industry using Ernie-Tiny and BiGRU to understand the patient’s challenges. Artificial neural networks, deep learning models and hybrid models are used in the transportation industry to estimate vehicle efficiency and effectiveness. Artificial Intelligence in Biobanking studies helps to understand the pathological outcomes of patients in the medical care sector. Blockchain, another cutting-edge technology, is a decentralised network of blocks used to safeguard the accuracy of transactions. Utilising business analytics has improved efficacy, efficiency and productivity due to the internet of things. The paper analyses the various research papers available in Pro-quest and Google Scholar. The paper also presents the benefits of emerging technologies in sector and business growth. This paper reviews the role of emerging technologies in different sectors through a literature review. Based on the bibliometric analysis conclusions are been provided.
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Rocco, Gaetano, Claudia Pipino e Claudio Pagano. "An Overview of Urban Mobility: Revolutionizing with Innovative Smart Parking Systems". Sustainability 15, n. 17 (1 settembre 2023): 13174. http://dx.doi.org/10.3390/su151713174.
Testo completoAbstract (sommario):
This feasibility study aims to propose the design of a smart parking architecture that is able to offer new services by exploiting the latest IoT technologies. This innovative solution is designed for use by both public authorities and private individuals who need to manage urban parking areas efficiently. The contribution of this work is to attempt to define the requirements and technical choices that can be made for the design of a system that adheres to the paradigm of innovation and efficiency in smart parking. Indeed, there is a practical limit between the existing models and the best solutions to apply. For each technology, the following details are provided: the problem to be managed, the current state of the art on the market, the main solutions, and also the related commercial policies. We proceed with the “Outline Design”, which integrates the technical specifications and defines the main information flows between the functional blocks. The results of experimentation show that the proposed reservation-based parking policy has the potential to simplify the operations of parking systems, as well as alleviate cities’ traffic congestion.