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Lai, Po-Ting, Wei-Liang Lu, Ting-Rung Kuo, Chia-Ru Chung, Jen-Chieh Han, Richard Tzong-Han Tsai, and Jorng-Tzong Horng. "Using a Large Margin Context-Aware Convolutional Neural Network to Automatically Extract Disease-Disease Association from Literature: Comparative Analytic Study." JMIR Medical Informatics 7, no. 4 (November 26, 2019): e14502. http://dx.doi.org/10.2196/14502.
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Background Research on disease-disease association (DDA), like comorbidity and complication, provides important insights into disease treatment and drug discovery, and a large body of the literature has been published in the field. However, using current search tools, it is not easy for researchers to retrieve information on the latest DDA findings. First, comorbidity and complication keywords pull up large numbers of PubMed studies. Second, disease is not highlighted in search results. Finally, DDA is not identified, as currently no disease-disease association extraction (DDAE) dataset or tools are available. Objective As there are no available DDAE datasets or tools, this study aimed to develop (1) a DDAE dataset and (2) a neural network model for extracting DDA from the literature. Methods In this study, we formulated DDAE as a supervised machine learning classification problem. To develop the system, we first built a DDAE dataset. We then employed two machine learning models, support vector machine and convolutional neural network, to extract DDA. Furthermore, we evaluated the effect of using the output layer as features of the support vector machine-based model. Finally, we implemented large margin context-aware convolutional neural network architecture to integrate context features and convolutional neural networks through the large margin function. Results Our DDAE dataset consisted of 521 PubMed abstracts. Experiment results showed that the support vector machine-based approach achieved an F1 measure of 80.32%, which is higher than the convolutional neural network-based approach (73.32%). Using the output layer of convolutional neural network as a feature for the support vector machine does not further improve the performance of support vector machine. However, our large margin context-aware-convolutional neural network achieved the highest F1 measure of 84.18% and demonstrated that combining the hinge loss function of support vector machine with a convolutional neural network into a single neural network architecture outperforms other approaches. Conclusions To facilitate the development of text-mining research for DDAE, we developed the first publicly available DDAE dataset consisting of disease mentions, Medical Subject Heading IDs, and relation annotations. We developed different conventional machine learning models and neural network architectures and evaluated their effects on our DDAE dataset. To further improve DDAE performance, we propose an large margin context-aware-convolutional neural network model for DDAE that outperforms other approaches.
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Unger, Benjamin. "Discontinuity Propagation in Delay Differential-Algebraic Equations." Electronic Journal of Linear Algebra 34 (February 21, 2018): 582–601. http://dx.doi.org/10.13001/1081-3810.3759.
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The propagation of primary discontinuities in initial value problems for linear delay differential-algebraic equations (DDAEs) is discussed. Based on the (quasi-) Weierstra{\ss} form for regular matrix pencils, a complete characterization of the different propagation types is given and algebraic criteria in terms of the matrices are developed. The analysis, which is based on the method of steps, takes into account all possible inhomogeneities and history functions and thus serves as a worst-case scenario. Moreover, it reveals possible hidden delays in the DDAE and allows to study exponential stability of the DDAE based on the spectral abscissa. The new classification for DDAEs is compared to existing approaches in the literature and the impact of splicing conditions on the classification is studied.
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Azmat, A., I. Ali, W. Ariyanti, M. G. L. Putra, and T. Nadeem. "Environmental Noise Reduction based on Deep Denoising Autoencoder." Engineering, Technology & Applied Science Research 12, no. 6 (December 1, 2022): 9532–35. http://dx.doi.org/10.48084/etasr.5239.
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Speech enhancement plays an important role in Automatic Speech Recognition (ASR) even though this task remains challenging in real-world scenarios of human-level performance. To cope with this challenge, an explicit denoising framework called Deep Denoising Autoencoder (DDAE) is introduced in this paper. The parameters of DDAE encoder and decoder are optimized based on the backpropagation criterion, where all denoising autoencoders are stacked up instead of recurrent connections. For better speech estimation in real and noisy environments, we include matched and mismatched noisy and clean pairs of speech data to train the DDAE. The DDAE has the ability to achieve optimal results even for a limited amount of training data. Our experimental results show that the proposed DDAE outperformed the baseline algorithms. The DDAE shows superior performances based on three-evaluation metrics in noisy and clean pairs of speech data compared to three baseline algorithms.
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Saad, Omar M., and Yangkang Chen. "Deep denoising autoencoder for seismic random noise attenuation." GEOPHYSICS 85, no. 4 (June 5, 2020): V367—V376. http://dx.doi.org/10.1190/geo2019-0468.1.
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Attenuation of seismic random noise is considered an important processing step to enhance the signal-to-noise ratio of seismic data. A new approach is proposed to attenuate random noise based on a deep-denoising autoencoder (DDAE). In this approach, the time-series seismic data are used as an input for the DDAE. The DDAE encodes the input seismic data to multiple levels of abstraction, and then it decodes those levels to reconstruct the seismic signal without noise. The DDAE is pretrained in a supervised way using synthetic data; following this, the pretrained model is used to denoise the field data set in an unsupervised scheme using a new customized loss function. We have assessed the proposed algorithm based on four synthetic data sets and two field examples, and we compare the results with several benchmark algorithms, such as f- x deconvolution ( f- x deconv) and the f- x singular spectrum analysis ( f- x SSA). As a result, our algorithm succeeds in attenuating the random noise in an effective manner.
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Lazim, Raghad Yaseen, Zhu Yun, and Xiaojun Wu. "Improving Speech Quality for Hearing Aid Applications Based on Wiener Filter and Composite of Deep Denoising Autoencoders." Signals 1, no. 2 (October 21, 2020): 138–56. http://dx.doi.org/10.3390/signals1020008.
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In hearing aid devices, speech enhancement techniques are a critical component to enable users with hearing loss to attain improved speech quality under noisy conditions. Recently, the deep denoising autoencoder (DDAE) was adopted successfully for recovering the desired speech from noisy observations. However, a single DDAE cannot extract contextual information sufficiently due to the poor generalization in an unknown signal-to-noise ratio (SNR), the local minima, and the fact that the enhanced output shows some residual noise and some level of discontinuity. In this paper, we propose a hybrid approach for hearing aid applications based on two stages: (1) the Wiener filter, which attenuates the noise component and generates a clean speech signal; (2) a composite of three DDAEs with different window lengths, each of which is specialized for a specific enhancement task. Two typical high-frequency hearing loss audiograms were used to test the performance of the approach: Audiogram 1 = (0, 0, 0, 60, 80, 90) and Audiogram 2 = (0, 15, 30, 60, 80, 85). The hearing-aid speech perception index, the hearing-aid speech quality index, and the perceptual evaluation of speech quality were used to evaluate the performance. The experimental results show that the proposed method achieved significantly better results compared with the Wiener filter or a single deep denoising autoencoder alone.
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Driessen, W. L., R. A. G. de Graaff, F. J. Parlevliet, J. Reedijk, and R. M. de Vos. "Transition metal compounds of the tridentate pyrazole substituted amine ligand bis(2-(3,5-dimethyl-1-pyrazolyl)ethyl)ethylamine (ddae). X-ray structures of [Co(ddae)(NO3)2], [Cu(ddae)(NO3)(H2O)](NO3) and [Cu(ddae)(Cl)2]·C2H5OH." Inorganica Chimica Acta 216, no. 1-2 (February 1994): 43–49. http://dx.doi.org/10.1016/0020-1693(93)03707-h.
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Chen, Honghao, Xiangwen Kong, Xiangyu Zhang, Xin Zhao, and Kaiqi Huang. "DDAE: Towards Deep Dynamic Vision BERT Pretraining." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 2 (March 24, 2024): 1037–45. http://dx.doi.org/10.1609/aaai.v38i2.27864.
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Recently, masked image modeling (MIM) has demonstrated promising prospects in self-supervised representation learning. However, existing MIM frameworks recover all masked patches equivalently, ignoring that the reconstruction difficulty of different patches can vary sharply due to their diverse distance from visible patches. In this paper, we propose a novel deep dynamic supervision to enable MIM methods to dynamically reconstruct patches with different degrees of difficulty at different pretraining phases and depths of the model. Our deep dynamic supervision helps to provide more locality inductive bias for ViTs especially in deep layers, which inherently makes up for the absence of local prior for self-attention mechanism. Built upon the deep dynamic supervision, we propose Deep Dynamic AutoEncoder (DDAE), a simple yet effective MIM framework that utilizes dynamic mechanisms for pixel regression and feature self-distillation simultaneously. Extensive experiments across a variety of vision tasks including ImageNet classification, semantic segmentation on ADE20K and object detection on COCO demonstrate the effectiveness of our approach.
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Sulkhana, Sayyidah Irma, Fathul Niam, and Ahmad Saifudin. "Pengembangan Media DAKOTAR (Dakon Matematika Pintar) Materi Satuan Panjang dan Satuan Berat untuk Meningkatkan Keaktifan dan Kemampuan Berhitung Siswa Kelas IV di SDN Gogodeso 01." Patria Eduacational Journal (PEJ) 2, no. 2 (July 7, 2022): 7–12. http://dx.doi.org/10.28926/pej.v2i2.376.
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Abstract: Learning media is an intermediary tool to convey messages or learning materials used dby dteachers/educators dto dstudents dso dthat dthey dcan dattract dstudents' dattention, dthoughts dand dinterests dto dparticipate din dthe dlearning dprocess. dBased don dinterviews dthat dresearchers dconducted dwith dfourth dgrade dteachers dat dSDN dGogodeso dd01, ddthey ddfound ddproblems, ddnamely dd(1) ddlack ddof ddvariety ddof ddlearning ddmedia dd(2) ddteachers ddstill dduse ddthe ddlecture ddmethod ddin ddthe ddlearning ddprocess. ddThe ddpurpose ddof ddthis dddevelopment ddresearch ddis ddto ddproduce ddDAKOTAR ddmedia dd(Dakon ddMathematics ddPintar) ddclass ddIV ddat ddSDN ddGogodeso dd01. ddThis ddstudy dduses dd5 ddstages ddof ddthe ddADDIE ddmodel, ddnamely ddanalysis, dddesign, dddevelopment, ddimplementation, ddand ddevaluation. ddData ddcollection ddtechniques ddused ddin ddthe ddform ddof ddquestionnaires, ddtests ddand dddocumentation. ddThe dddata ddcollection ddinstruments ddused ddwere ddquestionnaires ddfor ddmaterial ddexperts ddand ddmedia ddexperts ddas ddwell ddas ddactivity ddquestionnaires ddand ddtests ddfor ddstudents. ddThe ddresults ddof ddthis ddstudy ddinclude ddmaterial ddexpert ddvalidation, ddobtained dda ddpercentage ddof dd86% ddwith ddvery ddvalid ddcriteria ddwithout ddrevision ddand ddmedia ddexpert ddvalidation ddobtained dda ddpercentage ddof dd81% ddwith ddfairly ddvalid ddcriteria ddwith ddslight ddrevisions, ddthe ddresults ddof ddthe ddstudent ddactivity ddtest ddget dda ddscore ddof dd85.7% ddwith ddvery ddactive ddcategory. ddDAKOTAR dd(Dakon ddMathematics ddPintar) ddfor ddincreasing ddnumeracy ddskills ddfor ddclass ddIV ddis ddcategorized ddas ddhaving dda ddmoderate ddincrease ddwith ddan ddoverall ddN-Gain ddscore ddof dd0.37. ddSo ddthe dddevelopment ddof ddDAKOTAR dd(Dakon ddMathematics ddPintar) dis dvalid dand dcan dincrease dstudents' dactiveness dand dnumeracy dskills.
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Deshmukh, Venkatesh. "Approximate Stability Analysis and Computation of Solutions of Nonlinear Delay Differential Algebraic Equations with Time Periodic Coefficients." Journal of Vibration and Control 16, no. 7-8 (June 2010): 1235–60. http://dx.doi.org/10.1177/1077546309341137.
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Approximate stability analysis of nonlinear delay differential algebraic equations (DDAEs) with periodic coefficients is proposed with a geometric interpretation of evolution of the linearized system. Firstly, a numerical algorithm based on direct integration by expansion in terms of Chebyshev polynomials is derived for linear analysis. The proposed algorithm is shown to have deeper connections with and be computationally less cumbersome than the solution of the underlying semi-explicit system via a similarity transformation. The stability of time periodic DDAE systems is characterized by the spectral radius of a “monodromy matrix”, which is a finite-dimensional approximation of a compact infinite-dimensional operator. The monodromy matrix is essentially a map of the Chebyshev coefficients (or collocation vector) of the state from the delay interval to the next adjacent interval of time. The computations are entirely performed with the original system to avoid cumbersome transformations associated with the semi-explicit form of the system. Next, two computational algorithms, the first based on perturbation series and the second based on Chebyshev spectral collocation, are detailed to obtain solutions of nonlinear DDAEs with periodic coefficients for consistent initial functions.
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Wei, Chengyan, and Shenxiang Wang. "Research on Improving the Executive Ability of University Administrators Based on Deep Learning." Computational and Mathematical Methods in Medicine 2022 (June 9, 2022): 1–10. http://dx.doi.org/10.1155/2022/6354801.
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Over the years, experts have focused their research on ways to increase the executive capacity of university administrators. This is because only by improving the quality of execution of college and university administrative personnel can they actively execute various policies and measures, fully exploit their subjective initiative, and ensure the educational reform of colleges and universities. Increasing the executive capacity of administrative staff can help colleges and universities manage more effectively. Therefore, in the development process of higher education institutions, it is necessary to strengthen the execution of administrative staff, especially the need to adhere to the problem as the basic orientation. Take scientific and practical steps to strengthen administrative personnel’s executive ability in light of current issues with administrative management personnel’s executive power, and establish the groundwork for ensuring the quality of management work. Combining deep learning, this paper proposes a path to improve the executive power of college administrators based on deep learning. To begin, familiarize yourself with the deep noise reduction autoencoder model and support vector regression (SVR) theory and build the DDAE-SVR deep neural network (DNN) model. Then, input a small-scale feature index sample data set and a large-scale short-term traffic flow data set for experiments; then, assess the model’s parameters to achieve the optimal model. Finally, use performance indicators such as MSE and MAPE to compare with other shallow models to verify the effectiveness and advantages of the DDAE-SVR DNN model in the execution improvement path output of university administrators and large-scale data sets.
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Pañella, Anna, Josefina Pons, Jordi García-Antón, Xavier Solans, Mercè Font-Bardia, and Josep Ros. "Synthesis of New Palladium(II) Complexes Containing HemilabileN-(Alkylamino)pyrazole Ligands: Spectroscopic Analysis and Crystal Structure of [PdCl(ddae)]Cl·H2O {ddae = Bis[2-(3,5-dimethyl-1-pyrazolyl)ethyl]ethylamine}." European Journal of Inorganic Chemistry 2006, no. 8 (April 2006): 1678–85. http://dx.doi.org/10.1002/ejic.200501056.
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Bao, Fuli, and Chong Wang. "A Method for Evaluating the Quality of Mathematics Education Based on Artificial Neural Network." Computational and Mathematical Methods in Medicine 2022 (August 12, 2022): 1–11. http://dx.doi.org/10.1155/2022/6976654.
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Teaching quality evaluation (TQE) is an important link in the process of school teaching management. Evaluation indicators and teaching quality have a complicated and nonlinear connection that is influenced by several variables. Some of these drawbacks include too much subjectivity and unpredictability, difficulty in defining index weights, sluggish convergence, and weak computer capacity. The current assessment techniques and models have these issues as well. This research uses an ANN model to assess the quality of mathematics instruction at colleges and universities (CAU) in order to address the challenging nonlinear issue of TQE and completes the following tasks. (1) The background and significance of TQE research are analyzed, and the domestic and foreign research status of TQE and neural network is systematically expounded. (2) The technical principle of DNN is introduced and the DDAE-SVR DNN model is constructed, and then, the evaluation index system of mathematics teaching quality is constructed. (3) The DDAE-SVR DNN model is put out as a potential alternative. The Adam method is used in the unsupervised training process to dynamically modify the learning step size for each training parameter. The spatial properties of the original data may be modified several times such that the reconstruction can be completed after many hidden layers have been applied. Data essentials such as precision, accuracy, and consistency are prioritized above all other considerations when generating the final product. Unsupervised prediction uses SVR and maps the complicated nonlinear connection into high-dimensional space in order to attain linearity in low-dimensional space, which is the goal of the supervised prediction process. The usefulness and benefits of the model provided in this research in the mathematics TQE may be verified by tests including the use of the TQE dataset and comparisons with other shallow models.
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Galambos, Jörg, Claudia Meuli-Simmen, Regula Schmid, Lisa S. Steinmann, and Werner Kempf. "Diffuse Dermal Angiomatosis of the Breast: A Distinct Entity in the Spectrum of Cutaneous Reactive Angiomatoses – Clinicopathologic Study of Two Cases and Comprehensive Review of the Literature." Case Reports in Dermatology 9, no. 3 (October 13, 2017): 194–205. http://dx.doi.org/10.1159/000480721.
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Diffuse dermal angiomatosis (DDA) is a rare reactive angioproliferation in the skin and considered to be a subtype in the group of cutaneous reactive angiomatoses. DDA is clinically characterized by livedoid patches and plaques with tender ulceration. Its histologic features are a reactive diffuse proliferation of bland endothelial cells and pericytes within the dermis, forming small capillary vessels. Previously described cases of DDA most commonly involved the limbs and were associated with a wide spectrum of predisposing comorbidities, especially advanced atherosclerotic vascular disease and arteriovenous fistula. However, several cases of DDA of the breast (DDAB) have been reported in recent years. In this study we present 2 additional patients with DDAB and review all 36 cases of DDAB published in the literature. We describe the clinical and histopathologic characteristics, hypothesized pathogenetic mechanisms, and predisposing conditions of this rare skin disorder and discuss treatment options. The breast is a more commonly involved site of DDA than previously believed. DDAB typically occurs in middle-aged women and is associated with macromastia, overweight or obesity, and probably smoking. Predisposing comorbid conditions differ from those of DDA involving other parts of the body, making DDAB a unique clinicopathologic entity in the spectrum of cutaneous reactive angiomatoses. Currently there is no consensus on the best therapeutic approach. Isotretinoin and other medical therapies have been used with limited success. Breast reduction surgery appears to be a viable treatment option for DDAB in women with macromastia and might provide definitive healing.
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Al-Qudsy, Zainab N. Al, Zainab Mahmood Fadhil, Refed Adnan Jaleel, and Musaddak Maher Abdul Zahra. "Blockchain and 1D-CNN based IoTs for securing and classifying of PCG sound signal data." Fusion: Practice and Applications 12, no. 2 (2023): 28–41. http://dx.doi.org/10.54216/fpa.120203.
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The Internet of Things (IoTs) has accelerated with the introduction of powerful biomedical sensors, telemedicine services and population ageing are concerns that can be solved by smart healthcare systems. However, the security of medical signal data that collected from sensors of IoTs technology, while it is being transmitted over public channels has grown to be a serious problem that has limited the adoption of intelligent healthcare systems. This suggests using the technology of blockchain to create a safe and reliable heart sound signal (PCG) that can communicate with wireless body area networks. The security plan offers a totally dependable and safe environment for every data flowing from the back end to front-end. Also in this paper, to classify heart sound signals, we suggested a one-dimensional convolutional neural network (1D-CNN) model. The denoising autoencoder extracted the heart sounds' deep features as an input feature of 1D-CNN. To extract the detailed characteristics from the PCG signals, a Data Denoising Auto Encoder (DDAE) was used instead of the standard MFCC, the suggested model shows significant improvement. The system's benefits include a less difficult encryption algorithm and a more capable and effective blockchain-based data transfer and storage system.
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Stukel, M. R., V. J. Coles, M. T. Brooks, and R. R. Hood. "Top-down, bottom-up and physical controls on diatom-diazotroph assemblage growth in the Amazon River plume." Biogeosciences 11, no. 12 (June 19, 2014): 3259–78. http://dx.doi.org/10.5194/bg-11-3259-2014.
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Abstract. The nutrient-rich waters of the Amazon River plume (ARP) support dense blooms of diatom-diazotroph assemblages (DDAs) that introduce large quantities of new nitrogen to the planktonic ecosystem and, unlike other nitrogen-fixers, are likely to directly fuel vertical carbon flux. To investigate the factors controlling DDA blooms, we develop a five phytoplankton (cyanobacteria, diatoms, unicellular microbial diazotrophs, DDAs, and Trichodesmium), two zooplankton model and embed it within a 1/6° resolution physical model of the tropical and subtropical Atlantic. The model generates realistic DDA blooms in the ARP and also exhibits basin-wide primary production, nitrogen fixation, and grazing rates consistent with observed values. By following ARP water parcels with synthetic Lagrangian drifters released at the river mouth we are able to assess the relative impacts of grazing, nutrient supply, and physical forcing on DDA bloom formation. DDA bloom formation is stimulated in the nitrogen-poor and silica-rich water of the ARP by decreases in grazing pressure when mesozooplankton (which co-occur in high densities with coastal diatom blooms) concentrations decrease. Bloom termination is driven primarily by silica limitation of the DDAs. In agreement with in situ data, this net growth niche for DDAs exists in a salinity range from ∼20–34 PSU, although this co-occurrence is coincidental rather than causative. Because net growth rates are relatively modest, bloom formation in ARP water parcels depends critically on the time spent in this ideal habitat, with high DDA biomass only occurring when water parcels spent >23 days in the optimal habitat niche.
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Law, Brian K., Mary E. Law, Elham Yaaghubi, Amanda Ghilardi, Brad J. Davis, Renan Ferreira, Samantha Eggleston, et al. "Abstract 6148: Disulfide isomerases AGR2, ERp44, and PDIA1 maintain death receptor 5 in an auto-inhibited, monomeric form." Cancer Research 83, no. 7_Supplement (April 4, 2023): 6148. http://dx.doi.org/10.1158/1538-7445.am2023-6148.
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Abstract Previous studies indicated that compounds termed Disulfide bond Disrupting Agents (DDAs) exhibit anti-cancer activity that is associated with downregulation of EGFR/HER1, HER2, and HER3, and activation of Death Receptors 4 and 5 (DR4/5). DDA-induced HER1-3 downregulation is preceded by disulfide-mediated oligomerization. In contrast, DDA-mediated DR4/5 oligomerization results in DR5 upregulation, and activation of DR4/5 pro-apoptotic signaling through Caspases 8 and 3. However, the precise mechanisms by which altered disulfide bonding stabilizes and activates DR5 are unknown. A recent report indicated that the extracellular domain of DR5 acts in an auto-inhibitory manner to prevent DR5 oligomerization and pro-apoptotic signaling in the absence of its ligand, TRAIL. A subsequent paper showed that the DR5 auto-inhibitory domain is a positive patch consisting of three basic residues. Importantly, the structure of the auto-inhibitory loop is formed by two disulfide bonds. We hypothesize that DDAs disrupt the disulfide bonds that make up the auto-inhibitory loop, resulting in DR5 oligomerization, and activation of Caspase 8/3-driven apoptosis in a TRAIL-independent manner. Due to their novel mechanisms of action, DDAs may overcome the pharmacological liabilities that have limited the efficacy of TRAIL analogs and DR5 agonist antibodies. Another unanswered question is how precisely DDAs alter DR5 and EGFR disulfide bonding. The direct targets of DDA action were revealed through affinity purification studies with biotinylated-DDA analogs. These studies identified the protein disulfide isomerases AGR2, ERp44, and PDIA1 as DDA target proteins, explaining how DDAs alter DR5 and EGFR disulfide bonding patterns. Consistent with this interpretation, knockdown of AGR2 or ERp44, or expression of catalytically null AGR2 or ERp44 mutants, mimicked DDAs in inducing disulfide-mediated DR5 oligomerization and Caspase 8 activation. Together, these results demonstrate a fundamentally novel, ligand-independent mechanism for activation of DR5 through DDA-mediated inhibition of the PDIs AGR2, ERp44, and PDIA1. Significantly, DDAs are the first identified active site inhibitors of AGR2 and ERp44. Citation Format: Brian K. Law, Mary E. Law, Elham Yaaghubi, Amanda Ghilardi, Brad J. Davis, Renan Ferreira, Samantha Eggleston, Jade Nguyen, Grace Alexandrow, Jin Koh, Sixue Chen, Chi-Wu Chiang, Coy Heldermon, Peter Norgaard, Ronald K. Castallano, Zaafir M. Dulloo. Disulfide isomerases AGR2, ERp44, and PDIA1 maintain death receptor 5 in an auto-inhibited, monomeric form. [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 6148.
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Law, Mary E., Zaafir M. Dulloo, Elham Yaaghubi, Grace M. Alexandrow, Bianca Forsyth, Hanyu Su, Ronald K. Castellano, and Brian K. Law. "Abstract 552: Non-canonical disulfide isomerases are strongly selective, understudied targets for cancer therapy." Cancer Research 84, no. 6_Supplement (March 22, 2024): 552. http://dx.doi.org/10.1158/1538-7445.am2024-552.
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Abstract A major challenge in cancer therapy is the identification of drug targets that are essential for cancer cells but not non-transformed cells. The Broad Institute’s Dependency Map (DepMap) evaluates whether knocking down or knocking out expression of specific genes is “strongly selective” against subsets of cancer cells, in contrast with genes that are “common essential.” Of the 22 human Protein Disulfide Isomerases (PDIs), only four, ERp44, TMX1, AGR2, and AGR3, were identified as strongly selective in the DepMap. Importantly, our team previously identified ERp44, AGR2, and AGR3 as targets of bicyclic thiosulfonate compounds termed Disulfide bond Disrupting Agents (DDAs). DDAs exhibit striking anti-cancer activity in xenograft tumor studies. DDA treatment of cancer cells blocks ERp44, AGR2, and AGR3 active site Cys residues, ablating their catalytic activity and binding to client proteins. Evaluation of cancer cell lines predicted to be sensitive to DDAs, based on their AGR2, AGR3, or ERp44 dependence, accurately predicts DDA sensitivity. Cell lines from a variety of tumor types exhibit AGR2, AGR3, or ERp44 dependencies. Our previous work identified HER-family members (i.e., EGFR, HER2, and HER3) and TRAIL receptors (Death Receptors 4 and 5) as important clients of DDA-sensitive PDIs in breast cancer cells, but it was unknown if these observations extend to other tumor types. Initial studies indicate that AGR2 DepMap dependencies are a strong predictor of sensitivity of cancer cells to DDAs, irrespective of their site of origin. It will be important in future studies to determine what the key client proteins for these DDA-sensitive PDIs are and whether they vary across tumor types. Citation Format: Mary E. Law, Zaafir M. Dulloo, Elham Yaaghubi, Grace M. Alexandrow, Bianca Forsyth, Hanyu Su, Ronald K. Castellano, Brian K. Law. Non-canonical disulfide isomerases are strongly selective, understudied targets for cancer therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 552.
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Suratanee, Apichat, and Kitiporn Plaimas. "DDA: A Novel Network-Based Scoring Method to Identify Disease-Disease Associations." Bioinformatics and Biology Insights 9 (January 2015): BBI.S35237. http://dx.doi.org/10.4137/bbi.s35237.
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Categorizing human diseases provides higher efficiency and accuracy for disease diagnosis, prognosis, and treatment. Disease-disease association (DDA) is a precious information that indicates the large-scale structure of complex relationships of diseases. However, the number of known and reliable associations is very small. Therefore, identification of DDAs is a challenging task in systems biology and medicine. Here, we developed a novel network-based scoring algorithm called DDA to identify the relationships between diseases in a large-scale study. Our method is developed based on a random walk prioritization in a protein-protein interaction network. This approach considers not only whether two diseases directly share associated genes but also the statistical relationships between two different diseases using known disease-related genes. Predicted associations were validated by known DDAs from a database and literature supports. The method yielded a good performance with an area under the curve of 71% and outperformed other standard association indices. Furthermore, novel DDAs and relationships among diseases from the clusters analysis were reported. This method is efficient to identify disease-disease relationships on an interaction network and can also be generalized to other association studies to further enhance knowledge in medical studies.
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Yang, Jingmin, Shanghui Deng, Li Xu, and Wenjie Zhang. "Calibration-Free 3D Indoor Positioning Algorithms Based on DNN and DIFF." Sensors 22, no. 15 (August 7, 2022): 5891. http://dx.doi.org/10.3390/s22155891.
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The heterogeneity of wireless receiving devices, co-channel interference, and multi-path effect make the received signal strength indication (RSSI) of Wi-Fi fluctuate greatly, which seriously degrades the RSSI-based positioning accuracy. Signal strength difference (DIFF), a calibration-free solution for handling the received signal strength variance between diverse devices, can effectively reduce the negative impact of signal fluctuation. However, DIFF also leads to the explosion of the RSSI data dimension, expanding the number of dimensions from m to Cm2, which reduces the positioning efficiency. To this end, we design a data hierarchical processing strategy based on a building-floor-specific location, which effectively improves the efficiency of high-dimensional data processing. Moreover, based on a deep neural network (DNN), we design three different positioning algorithms for multi-building, multi-floor, and specific-location respectively, extending the indoor positioning from the single plane to three dimensions. Specifically, in the stage of data preprocessing, we first create the original RSSI database. Next, we create the optimized RSSI database by identifying and deleting the unavailable data in the RSSI database. Finally, we perform DIFF processing on the optimized RSSI database to create the DIFF database. In the stage of positioning, firstly, we design an improved multi-building positioning algorithm based on a denoising autoencoder (DAE). Secondly, we design an enhanced DNN for multi-floor positioning. Finally, the newly deep denoising autoencoder (DDAE) used for specific location positioning is proposed. The experimental results show that the proposed algorithms have better positioning efficiency and accuracy compared with the traditional machine learning algorithms and the current advanced deep learning algorithms.
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Feng, Wenyan, and Fan Feng. "Research on the Multimodal Digital Teaching Quality Data Evaluation Model Based on Fuzzy BP Neural Network." Computational Intelligence and Neuroscience 2022 (June 11, 2022): 1–12. http://dx.doi.org/10.1155/2022/7893792.
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We propose in this paper a fuzzy BP neural network model and DDAE-SVR deep neural network model to analyze multimodal digital teaching, establish a multimodal digital teaching quality data evaluation model based on a fuzzy BP neural network, and optimize the initial weights and thresholds of BP neural network by using adaptive variation genetic algorithm. Since the BP neural network is highly dependent on the initial weights and points, the improved genetic algorithm is used to optimize the initial weights and thresholds of the BP neural network, reduce the time for the BP neural network to find the importance and points that satisfy the training termination conditions, and improve the prediction accuracy and convergence speed of the neural network on the teaching quality evaluation results. The entropy value method, a data-based objectivity evaluation method, is introduced as the guidance mechanism of the BP neural network. The a priori guidance sample is obtained by the entropy method. Then, the adaptive variational genetic algorithm is used to optimize the BP neural network model to learn the a priori sample knowledge and establish the evaluation model, which reduces the subjectivity of the BP neural network learning sample. To better reflect and compare the effects of the two neural network evaluation models, BP and GA-BP, the sample data were continued to be input into the original GA and BSA to obtain the evaluation results and errors; then, the evaluation results of the two evaluation models, BP and GA-BP, were compared with the evaluation results of the two algorithms, GA and BSA. It was found that the GA-BP neural network evaluation model has higher accuracy and can be used for multimodal digital teaching quality evaluation, providing a more feasible solution.
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Mariano Silva, Luis Felipe, Ana Kleiber Pessoa Borges, and Janaina De Sousa Menezes. "ANÁLISE DA OCORRENCIA DE DOENÇAS DIARREICAS NO PERÍODO DE 2015 A 2020 EM PALMAS-TO." Revista de Patologia do Tocantins 8, no. 3 (November 5, 2021): 120–24. http://dx.doi.org/10.20873/uft.2446-6492.2021v8n3p120.
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Introdução: As doenças diarreicas agudas (DDAs) são caracterizadas pelo aumento da frequência, quantidade de evacuações e pela diminuição da consistência fecal. as DDAs têm expressiva influência nas taxas de morbimortalidade em países subdesenvolvidos e em desenvolvimento, como o Brasil, tornando-se um problema de saúde pública. Esta pesquisa tem como objetivo analisar a ocorrência de doenças diarreicas na população do município de Palmas-TO entre os anos de 2015 a 2020. Método: Foi realizado um estudo descritivo com dados secundários, no município de Palmas-TO. O estudo foi realizado através da coleta de dados no Sistema Informatizado de Vigilância Epidemiológica de Doenças Diarreicas Agudas (SIVEP-DDA) na secretaria estadual de saúde (SES-TO). Resultados: Segundo o SIVEP-DDA, de 2015 a 2020, foram registrados 68.202 casos de doença diarreica aguda em Palmas-TO. A faixa etária de 1 a 4 anos é a que apresenta maior incidência de doenças diarreicas em todos os anos do estudo nas crianças. De 2015 a 2017 a taxa de incidência anual de doenças diarreicas no município por mil habitantes ficou acima das taxas estadual e nacional. O ano de 2016 se destacou negativamente pois nesse período a incidência municipal superou a estadual e nacional em 95% e 203%, respectivamente. O sistema de informações hospitalares (SIH) durante o período estudado registrou 693 internações por diarreias e outras infecções de origem presumível. Essas internações representaram um custo total de R$ 248.246,81. Conclusão: Os números reais de casos de doenças diarreicas no município de Palmas-TO, supostamente, encontram-se subnotificados, principalmente no ano de 2020 devido a pandemia de COVID-19. O número de casos em crianças de 1 a 4 foi expressivo. O estudo teve uma barreira para identificar os casos de DDAs em idosos. Os números do SIH sobre as internações de pacientes com diarreia divergem do SIVEP-DDA afetando o cálculo real dos custos.
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Konopelchenko, B. G. "On the Deformation Theory of Structure Constants for Associative Algebras." Advances in Mathematical Physics 2010 (2010): 1–21. http://dx.doi.org/10.1155/2010/389091.
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An algebraic scheme for constructing deformations of structure constants for associative algebras generated by deformation driving algebras (DDAs) is discussed. An ideal of left divisors of zero plays a central role in this construction. Deformations of associative three-dimensional algebras with the DDA being a three-dimensional Lie algebra and their connection with integrable systems are studied.
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Zhang, Min, Chong-sheng Peng, and Xiao-bo Li. "In VivoandIn VitroMetabolites from the Main Diester and Monoester Diterpenoid Alkaloids in a Traditional Chinese Herb, theAconitumSpecies." Evidence-Based Complementary and Alternative Medicine 2015 (2015): 1–23. http://dx.doi.org/10.1155/2015/252434.
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Diester diterpenoid alkaloids (DDAs), such as aconitine (AC), mesaconitine (MA), and hypaconitine (HA), are both pharmacologically active compounds and toxic ingredients in a traditional Chinese herb, theAconitumspecies. Many DDA metabolism studies have been performed to explore mechanisms for reducing toxicity in these compounds and inAconitumspecies extracts for safe clinical administration. In this review, we summarize recent progress on the metabolism of toxic AC, MA, and HA and corresponding monoester diterpenoid alkaloids (MDAs) in the gastrointestinal tract and liver in different animal species and humansin vivoand/orin vitro, where these alkaloids are primarily metabolized by cytochrome P450 enzymes, carboxylesterases, and intestinal bacteria, which produces phase I metabolites, ester hydrolysed products, and lipoalkaloids. Furthermore, we classify metabolites detected in the blood and urine, where the aforementioned metabolites are absorbed and excreted. Less toxic MDAs and nontoxic alcohol amines are the primary DDA metabolites detected in the blood. Most other DDAs metabolites produced in the intestine and liver detected in the urine have not been reported in the blood. We propose an explanation for this nonconformity. Finally, taking AC, for instance, we generalize a process of toxicity reduction in the body after oral AC administration for the first time.
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Gao, Meng, Gabrielle Armin, and Keisuke Inomura. "Low-Ammonium Environment Increases the Nutrient Exchange between Diatom–Diazotroph Association Cells and Facilitates Photosynthesis and N2 Fixation—a Mechanistic Modeling Analysis." Cells 11, no. 18 (September 17, 2022): 2911. http://dx.doi.org/10.3390/cells11182911.
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Diatom–diazotroph associations (DDAs) are one of the most important symbiotic dinitrogen (N2) fixing groups in the oligotrophic ocean. Despite their capability to fix N2, ammonium (NH4+) remains a key nitrogen (N) source for DDAs, and the effect of NH4+ on their metabolism remains elusive. Here, we developed a coarse-grained, cellular model of the DDA with NH4+ uptake and quantified how the level of extracellular NH4+ influences metabolism and nutrient exchange within the symbiosis. The model shows that, under a fixed growth rate, an increased NH4+ concentration may lower the required level of N2 fixation and photosynthesis, and decrease carbon (C) and N exchange. A low-NH4+ environment leads to more C and N in nutrient exchange and more fixed N2 to support a higher growth rate. With higher growth rates, nutrient exchange and metabolism increased. Our study shows a strong effect of NH4+ on metabolic processes within DDAs, and thus highlights the importance of in situ measurement of NH4+ concentrations.
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Psathas, Emmanouil D., Athanasios Katsargyris, Stella Lioudaki, Demetrios N. Moris, Mikes Doulaptsis, and Chris Klonaris. "Treatment paradigms for ductus arteriosus aneurysms in adults." Vascular 22, no. 4 (July 2, 2013): 297–301. http://dx.doi.org/10.1177/1708538113495680.
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We report two symptomatic cases of ductus arteriosus aneurysm (DDA) in adults treated in our department over a 5-years period. One patient underwent an open off-pump surgical procedure, while the second one was treated with partial aortic arch debranching and endovascular stent-grafting. DDA in adults is an uncommon condition and can present with rupture, hoarseness or symptoms of airway obstruction. Although indications for intervention are not clearly established, most authors advocate that DDAs should be treated regardless of their size, to avoid the risk of rupture, while others reserve intervention for symptomatic patients. We report on the management of these patients and provide an updated review of the current literature.
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Yang, H. H., F. C. Jin, and L. M. Wei. "The hydrogen bonding characteristic of (H2O)n (n=14-17)：quantum theory of atoms in molecules." Digest Journal of Nanomaterials and Biostructures 16, no. 4 (December 2021): 1401–9. http://dx.doi.org/10.15251/djnb.2021.164.1401.
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The hydrogen bonding characteristics of water clusters (H2O)n (n=14-17) are investigated by using Quantum Theory of Atoms in Molecules (QTAIM). The stabilities of the water clusters are related to the strength and number of hydrogen bonding. The strength of hydrogen bonding is primarily concerned with the characteristic of the donor molecule. The electron densities of bonding critical points of hydrogen bonding formed by DAA, DDAA and DDA molecule as hydrogen-donor (H-donor) are about 0.045 a.u., 0.035 a.u. and 0.025 a.u. respectively. The strength of hydrogen bonding formed by DAA as H-donor is the strongest, and that formed by DDA as H-donor is the weakest. The strength of hydrogen bonding in pentagonal rings is stronger than that in the cubes.
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Kartheeswaran, Karpaga Priyaa, Arockia Xavier Annie Rayan, and Geetha Thekkumpurath Varrieth. "Enhanced disease-disease association with information enriched disease representation." Mathematical Biosciences and Engineering 20, no. 5 (2023): 8892–932. http://dx.doi.org/10.3934/mbe.2023391.
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<abstract> <sec><title>Objective</title><p>Quantification of disease-disease association (DDA) enables the understanding of disease relationships for discovering disease progression and finding comorbidity. For effective DDA strength calculation, there is a need to address the main challenge of integration of various biomedical aspects of DDA is to obtain an information rich disease representation. Materials and</p> </sec> <sec><title>Methods</title><p>An enhanced and integrated DDA framework is developed that integrates enriched literature-based with concept-based DDA representation. The literature component of the proposed framework uses PubMed abstracts and consists of improved neural network model that classifies DDAs for an enhanced literature-based DDA representation. Similarly, an ontology-based joint multi-source association embedding model is proposed in the ontology component using Disease Ontology (DO), UMLS, claims insurance, clinical notes etc. Results and</p> </sec> <sec><title>Discussion</title><p>The obtained information rich disease representation is evaluated on different aspects of DDA datasets such as Gene, Variant, Gene Ontology (GO) and a human rated benchmark dataset. The DDA scores calculated using the proposed method achieved a high correlation mainly in gene-based dataset. The quantified scores also shown better correlation of 0.821, when evaluated on human rated 213 disease pairs. In addition, the generated disease representation is proved to have substantial effect on correlation of DDA scores for different categories of disease pairs.</p> </sec> <sec><title>Conclusion</title><p>The enhanced context and semantic DDA framework provides an enriched disease representation, resulting in high correlated results with different DDA datasets. We have also presented the biological interpretation of disease pairs. The developed framework can also be used for deriving the strength of other biomedical associations.</p> </sec> </abstract>
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Poruchynsky, Marianne S., Edina Komlodi-Pasztor, Shana Trostel, Julia Wilkerson, Marie Regairaz, Yves Pommier, Xu Zhang, et al. "Microtubule-targeting agents augment the toxicity of DNA-damaging agents by disrupting intracellular trafficking of DNA repair proteins." Proceedings of the National Academy of Sciences 112, no. 5 (January 20, 2015): 1571–76. http://dx.doi.org/10.1073/pnas.1416418112.
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The paradigm that microtubule-targeting agents (MTAs) cause cell death via mitotic arrest applies to rapidly dividing cells but cannot explain MTA activity in slowly growing human cancers. Many preferred cancer regimens combine a MTA with a DNA-damaging agent (DDA). We hypothesized that MTAs synergize with DDAs by interfering with trafficking of DNA repair proteins on interphase microtubules. We investigated nine proteins involved in DNA repair: ATM, ATR, DNA-PK, Rad50, Mre11, p95/NBS1, p53, 53BP1, and p63. The proteins were sequestered in the cytoplasm by vincristine and paclitaxel but not by an aurora kinase inhibitor, colocalized with tubulin by confocal microscopy and coimmunoprecipitated with the microtubule motor dynein. Furthermore, adding MTAs to radiation, doxorubicin, or etoposide led to more sustained γ-H2AX levels. We conclude DNA damage-repair proteins traffic on microtubules and addition of MTAs sequesters them in the cytoplasm, explaining why MTA/DDA combinations are common anticancer regimens.
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Li, Manqing, Elaine Kao, Dane Malone, Xia Gao, Jean Y. J. Wang, and Michael David. "Human intrinsic immunity factor SLFN11 promotes cell death upon DNA damages through cleavage of distinct type II tRNAs and inhibition of proteins syntheses related to DNA damage responses and repairs." Journal of Immunology 202, no. 1_Supplement (May 1, 2019): 194.20. http://dx.doi.org/10.4049/jimmunol.202.supp.194.20.
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Abstract Previously we showed that as an intrinsic immunity factor, human SLFN11 inhibits HIV viral proteins syntheses by modulating tRNAs abundances and exploiting the biased codon usage of the virus. Transcriptome analysis in vast collection of cancer cell lines revealed that SLFN11 is the only gene whose expression significantly sensitizes tumor cells to DNA damaging agents (DDAs). We hereby report that SLFN11 preferentially inhibits translation of genes involved in DNA damage response and repair, including ATR and ATM, upon DDAs treatment based on their distinct codon usages without disrupting early DNA damage response signaling. Type II tRNAs, which include all serine and leucine tRNAs, are cleaved in a SLFN11-dependent manner in response to DDAs. Genes with high TTA (Leu) codon usage such as ATR display utmost susceptibility to translational suppression by SLFN11 due to the extreme low abundance of cognate tRNA-Leu-TAA. Specific attenuation of tRNA-Leu-TAA with antisense oligonucleotides (ASO) sufficed to ablate ATR protein expression and restore DDA sensitivity of SLFN11-deficient tumor cells. Our study uncovered a novel mechanism of DNA damage response regulation mediated by SLFN11-dependent tRNA cleavage and codon-specific translational inhibition. The immunomodulation of SLFN11 expression and activation can be a potent novel approach to overcome the wide-spreading resistance of tumor cells to chemo-/radio-therapies.
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Zhang, Saining, Yuhang Zhang, Ye Zhang, Yufei Wang, and Zhigang Song. "A Dual-Direction Attention Mixed Feature Network for Facial Expression Recognition." Electronics 12, no. 17 (August 25, 2023): 3595. http://dx.doi.org/10.3390/electronics12173595.
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In recent years, facial expression recognition (FER) has garnered significant attention within the realm of computer vision research. This paper presents an innovative network called the Dual-Direction Attention Mixed Feature Network (DDAMFN) specifically designed for FER, boasting both robustness and lightweight characteristics. The network architecture comprises two primary components: the Mixed Feature Network (MFN) serving as the backbone, and the Dual-Direction Attention Network (DDAN) functioning as the head. To enhance the network’s capability in the MFN, resilient features are extracted by utilizing mixed-size kernels. Additionally, a new Dual-Direction Attention (DDA) head that generates attention maps in two orientations is proposed, enabling the model to capture long-range dependencies effectively. To further improve the accuracy, a novel attention loss mechanism for the DDAN is introduced with different heads focusing on distinct areas of the input. Experimental evaluations on several widely used public datasets, including AffectNet, RAF-DB, and FERPlus, demonstrate the superiority of the DDAMFN compared to other existing models, which establishes that the DDAMFN as the state-of-the-art model in the field of FER.
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Jabir, T., V. Dhanya, Y. Jesmi, M. P. Prabhakaran, N. Saravanane, G. V. M. Gupta, and A. A. M. Hatha. "Occurrence and Distribution of a Diatom-Diazotrophic Cyanobacteria Association during a Trichodesmium Bloom in the Southeastern Arabian Sea." International Journal of Oceanography 2013 (August 6, 2013): 1–6. http://dx.doi.org/10.1155/2013/350594.
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Symbiotic diatom-diazotrophic cyanobacteria association (DDA) of Rhizosolenia hebetata and Rhizosolenia formosa with endosymbiotic cyanobacteria Richelia intracellularis was noticed and documented for the first time during a bloom of the cyanobacterium Trichodesmium erythraeum in the oligotrophic shelf waters along Kochi and Mangalore transects, southeastern Arabian Sea (SEAS), during spring intermonsoon (April 2012). Although the host is frequently seen, the symbiont is rarely reported in the Indian EEZ. The presence of nitrogen-fixing symbiotic association of Rhizosolenia-Richelia along with Trichodesmium erythraeum highlights the significance of DDAs on the nutrient and energy budgets of phytoplankton in the oligotrophic environments of the Arabian Sea during spring intermonsoon.
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Bale, Nicole J., Tracy A. Villareal, Ellen C. Hopmans, Corina P. D. Brussaard, Marc Besseling, Denise Dorhout, Jaap S. Sinninghe Damsté, and Stefan Schouten. "C<sub>5</sub> glycolipids of heterocystous cyanobacteria track symbiont abundance in the diatom <i>Hemiaulus hauckii</i> across the tropical North Atlantic." Biogeosciences 15, no. 4 (March 1, 2018): 1229–41. http://dx.doi.org/10.5194/bg-15-1229-2018.
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Abstract. Diatom–diazotroph associations (DDAs) include marine heterocystous cyanobacteria found as exosymbionts and endosymbionts in multiple diatom species. Heterocysts are the site of N2 fixation and have thickened cell walls containing unique heterocyst glycolipids which maintain a low oxygen environment within the heterocyst. The endosymbiotic cyanobacterium Richelia intracellularis found in species of the diatom genus Hemiaulus and Rhizosolenia makes heterocyst glycolipids (HGs) which are composed of C30 and C32 diols and triols with pentose (C5) moieties that are distinct from limnetic cyanobacterial HGs with predominantly hexose (C6) moieties. Here we applied a method for analysis of intact polar lipids to the study of HGs in suspended particulate matter (SPM) and surface sediment from across the tropical North Atlantic. The study focused on the Amazon plume region, where DDAs are documented to form extensive surface blooms, in order to examine the utility of C5 HGs as markers for DDAs as well as their transportation to underlying sediments. C30 and C32 triols with C5 pentose moieties were detected in both marine SPM and surface sediments. We found a significant correlation between the water column concentration of these long-chain C5 HGs and DDA symbiont counts. In particular, the concentrations of both the C5 HGs (1-(O-ribose)-3,27,29-triacontanetriol (C5 HG30 triol) and 1-(O-ribose)-3,29,31-dotriacontanetriol (C5 HG32 triol)) in SPM exhibited a significant correlation with the number of Hemiaulus hauckii symbionts. This result strengthens the idea that long-chain C5 HGs can be applied as biomarkers for marine endosymbiotic heterocystous cyanobacteria. The presence of the same C5 HGs in surface sediment provides evidence that they are effectively transported to the sediment and hence have potential as biomarkers for studies of the contribution of DDAs to the paleo-marine N cycle.
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Potvin, Corey K., and Louis J. Wicker. "Comparison between Dual-Doppler and EnKF Storm-Scale Wind Analyses: Observing System Simulation Experiments with a Supercell Thunderstorm." Monthly Weather Review 140, no. 12 (December 1, 2012): 3972–91. http://dx.doi.org/10.1175/mwr-d-12-00044.1.
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Abstract Kinematical analyses of mobile radar observations are critical to advancing the understanding of supercell thunderstorms. Maximizing the accuracy of these and subsequent dynamical analyses, and appropriately characterizing the uncertainty in ensuing conclusions about storm structure and processes, requires thorough knowledge of the typical errors obtained using different retrieval techniques. This study adopts an observing system simulation experiment (OSSE) framework to explore the errors obtained from ensemble Kalman filter (EnKF) assimilation versus dual-Doppler analysis (DDA) of storm-scale mobile radar data. The radar characteristics and EnKF model errors are varied to explore a range of plausible scenarios. When dual-radar data are assimilated, the EnKF produces substantially better wind retrievals at higher altitudes, where DDAs are more sensitive to unaccounted flow evolution, and in data-sparse regions such as the storm inflow sector. Near the ground, however, the EnKF analyses are comparable to the DDAs when the radar cross-beam angles (CBAs) are poor, and slightly worse than the DDAs when the CBAs are optimal. In the single-radar case, the wind analyses benefit substantially from using finer grid spacing than in the dual-radar case for the objective analysis of radar observations. The analyses generally degrade when only single-radar data are assimilated, particularly when microphysical parameterization or low-level environmental wind errors are introduced. In some instances, this leads to large errors in low-level vorticity stretching and Lagrangian circulation calculations. Nevertheless, the results show that while multiradar observations of supercells are always preferable, judicious use of single-radar EnKF assimilation can yield useful analyses.
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Willis, Sophie E., Claudia Winkler, Martine P. Roudier, Tarrion Baird, Paola Marco-Casanova, Emma V. Jones, Philip Rowe, et al. "Retrospective analysis of Schlafen11 (SLFN11) to predict the outcomes to therapies affecting the DNA damage response." British Journal of Cancer 125, no. 12 (October 18, 2021): 1666–76. http://dx.doi.org/10.1038/s41416-021-01560-1.
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Abstract Background The absence of the putative DNA/RNA helicase Schlafen11 (SLFN11) is thought to cause resistance to DNA-damaging agents (DDAs) and PARP inhibitors. Methods We developed and validated a clinically applicable SLFN11 immunohistochemistry assay and retrospectively correlated SLFN11 tumour levels to patient outcome to the standard of care therapies and olaparib maintenance. Results High SLFN11 associated with improved prognosis to the first-line treatment with DDAs platinum-plus-etoposide in SCLC patients, but was not strongly linked to paclitaxel–platinum response in ovarian cancer patients. Multivariate analysis of patients with relapsed platinum-sensitive ovarian cancer from the randomised, placebo-controlled Phase II olaparib maintenance Study19 showed SLFN11 tumour levels associated with sensitivity to olaparib. Study19 patients with high SLFN11 had a lower progression-free survival (PFS) hazard ratio compared to patients with low SLFN11, although both groups had the benefit of olaparib over placebo. Whilst caveated by small sample size, this trend was maintained for PFS, but not overall survival, when adjusting for BRCA status across the olaparib and placebo treatment groups, a key driver of PARP inhibitor sensitivity. Conclusion We provide clinical evidence supporting the role of SLFN11 as a DDA therapy selection biomarker in SCLC and highlight the need for further clinical investigation into SLFN11 as a PARP inhibitor predictive biomarker.
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Hollenhorst, Marie A., Jon Clardy, and Christopher T. Walsh. "The ATP-Dependent Amide Ligases DdaG and DdaF Assemble the Fumaramoyl-Dipeptide Scaffold of the Dapdiamide Antibiotics." Biochemistry 49, no. 29 (July 27, 2010): 6296. http://dx.doi.org/10.1021/bi101016e.
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Hollenhorst, Marie A., Jon Clardy, and Christopher T. Walsh. "The ATP-Dependent Amide Ligases DdaG and DdaF Assemble the Fumaramoyl-Dipeptide Scaffold of the Dapdiamide Antibiotics." Biochemistry 48, no. 43 (November 3, 2009): 10467–72. http://dx.doi.org/10.1021/bi9013165.
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Dantoni, Patrícia, Ana Clara B. Rodrigues, Margareth Mie N. Matsuda, and Nina Coichev. "Effect of some surfactants on the chemiluminescent reactions of bis(2,4,6-trichlorophenyl)oxalate and bis(2-nitrophenyl)oxalate with hydrogen peroxide." Canadian Journal of Chemistry 90, no. 6 (June 2012): 534–41. http://dx.doi.org/10.1139/v2012-025.
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The chemiluminescent reactions of bis(2,4,6-trichlorophenyl)oxalate (TCPO) and bis(2-nitrophenyl)oxalate (2-NPO) with hydrogen peroxide in acetonitrile/water micellar systems (anionic, cationic, and non-ionic) and γ-cyclodextrin were studied in the presence of fluoranthene or 9,10-diphenylanthracene, imidazole, and two buffer solutions, HTRIS+/TRIS and H2PO4–/HPO42–. The relative chemiluminenscence (CL) intensity is higher in the presence of the cationic (DDAB, CTAC, DODAC, and OTAC), anionic (SDS), and non-ionic (Tween 80) surfactants. In the presence of some non-ionic surfactants (Brij 35, Brij 76, and Tween 20), the CL intensity was partially quenched compared with the reaction with no surfactant. The sensitivity for hydrogen peroxide determination in the range 0.01 × 10−4 to 1.0 × 10−4 mol L–1, considering the slope of the calibration curves (maximum peak height of CL vs. concentration), improved with the introduction of DDAH, CTAB, and SDS in HTRIS+/TRIS buffer.
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Hollenhorst, Marie A., Jon Clardy, and Christopher T. Walsh. "Correction to The ATP-Dependent Amide Ligases DdaG and DdaF Assemble the Fumaramoyl-Dipeptide Scaffold of the Dapdiamide Antibiotics." Biochemistry 49, no. 8 (March 2, 2010): 1808. http://dx.doi.org/10.1021/bi100095k.
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Fu, Xiaodan, Lin Zhu, Li Li, Tan Zhang, Meng Li, and Haijin Mou. "Eco-friendly preparation of chitooligosaccharides with different degrees of deacetylation from shrimp shell waste and their effects on the germination of wheat seeds." Marine Life Science & Technology 1, no. 1 (November 2019): 95–103. http://dx.doi.org/10.1007/s42995-019-00012-3.
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Abstract Production of chitosan and its derivatives by traditional methods involves the excessive use of a reaction solution comprised of sodium hydroxide and hydrochloric acid. Waste water resulting from this process has limited the application of chitosan as a fertilizer as the process causes serious environmental pollution. Specifically, the resulting waste water contains high levels of dissolved nitrogen and minerals from shrimp shells. In this study, an eco-friendly method was established to produce chitooligosaccharides (COS) with different degrees of deacetylation (DDAs) from shrimp shell waste. At a solid-to-solvent ratio of 1:6, the degree of demineralization was above 90% with the treatment of 30 g·L−1 H3PO4, and the degree of deproteinization was above 80% when treated with 30 g·L−1 KOH at 70 °C. Chitosans with different DDAs were obtained by microwave-assisted KOH metathesis and the COS with Mw approximately 1500 Da were then prepared by oxidative degradation. In summary, 33.73 kg H3PO4, 12.77 kg, and 241.31 kg KOH were supplied during the processes of demineralization, deproteinization, and deacetylation of 100 kg shrimp shell waste, respectively. The process water was totally recycled, demonstrating that the shrimp shell could be wholly transformed into fertilizer. The entire process created a product with the fractions of N:P2O5:K2O:COS = 7.94:24.44:10.72:18.27. The test on the germination promotion of wheat seeds revealed that the COS with 72.12% DDA significantly promoted germination. This work demonstrated the use of an eco-friendly preparation method of COS with a specific degree of deacetylation that can be applied as a fertilizer.
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LEIPER, James M., Joanne SANTA MARIA, Ann CHUBB, Raymond J. MACALLISTER, Ian G. CHARLES, Guy St J. WHITLEY, and Patrick VALLANCE. "Identification of two human dimethylarginine dimethylaminohydrolases with distinct tissue distributions and homology with microbial arginine deiminases." Biochemical Journal 343, no. 1 (September 24, 1999): 209–14. http://dx.doi.org/10.1042/bj3430209.
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Methylarginines inhibit nitric oxide synthases (NOS). Cellular concentrations of methylarginines are determined in part by the activity of dimethylarginine dimethylaminohydrolase (DDAH; EC 3.5.3.18). We have cloned human DDAH and identified and expressed a second novel DDAH isoform (DDAH I and II respectively). DDAH I predominates in tissues that express neuronal NOS. DDAH II predominates in tissues expressing endothelial NOS. These results strengthen the hypothesis that methylarginine concentration is actively regulated and identify molecular targets for the tissue and cell-specific regulation of methylarginine concentration.
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Duru, Metin. "Demir Dikeni (Tribulus terrestris) Saponin Ekstraktının Yumurtacı Tavuklarda Performans, Yumurta Kalite Kriterleri ve Bazı Kan Parametreleri Üzerine Etkileri." Turkish Journal of Agriculture - Food Science and Technology 12, no. 3 (March 22, 2024): 423–29. http://dx.doi.org/10.24925/turjaf.v12i3.423-429.6684.
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Bu çalışma, karma yeme demir dikeni bitkisi (Tribulus terrestris) saponin ekstraktı (DDSE) ilavesinin yumurtacı tavuklarda performans, iç-dış yumurta kalite kriterleri, yumurta kolesterol düzeyleri ve bazı kan serum parametreleri üzerine etkisini incelemek amacıyla yürütülmüştür. Araştırma grupları ticari yumurtacı karma yemine 0 (kontrol); 1 g DDSE, 2 g DDSE, 4 g DDSE ve 8 g DDSE eklenerek 5 gruptan oluşturulmuştur. Toplam 80 adet yumurtacı tavuk her bir grupta 16 hayvan olacak şekilde gruplara rastgele dağıtılmıştır. Araştırma sonuçlarına göre; kontrol grubu hariç diğer deneme gruplarına göre 1 g DDSE grubunda yumurta sarısı kolesterol değeri düşmüştür. Deneme ortasında 2, 4 ve 8 g DDSE grupları kontrol grubuna göre daha yüksek ak uzunluğu değerleri vermişlerdir. Performans ve kan serumu parametre değerleri bakımından gruplar arasında herhangi bir farklılığa rastlanmamıştır. Sonuç olarak DDSE tavuklarda performans, yumurta kalite kriterleri ve bazı kan parametreleri üzerine etkisi olmadığı tespit edilmiştir.
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Drmić, Z., M. Čačija, H. Virić Gašparić, D. Lemić, and R. Bažok. "Phenology of the sugar beet weevil, Bothynoderes punctiventris Germar (Coleoptera: Curculionidae), in Croatia." Bulletin of Entomological Research 109, no. 4 (November 27, 2018): 518–27. http://dx.doi.org/10.1017/s000748531800086x.
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AbstractThe sugar beet weevil (SBW), Bothynoderes punctiventris Germar, 1824, is a significant pest in most of Eastern Europe. Here, the SBW is described and its seasonal activity characterized, in terms of its different developmental stages in relation to Julian days (JDs), degree-day accumulations (DDAs), and precipitation, as a key to improving monitoring and forecasting of the pest. The phenology and population characteristics of SBW were investigated in sugar beet fields in eastern Croatia over a 4-year period (2012–2015). By using the degree-day model (lower development threshold of 5°C, no upper development threshold, biofix 1 January), the first emergence of overwintering adults was determined as becoming established when the DDA reached 20. The adult emergence was completed when the DDA reached 428. SBW males emerged first, following which the females dominated the adult population. Overwintering adults were present in the field until early July. In August, adults of the offspring generation began to appear. The eggs laid by the overwintering generation required, on average, 10–15 days to develop into larvae; however, eggs were found in soil samples over a period of 102 days (between JDs 112 and 214). Larvae were present in the soil samples over a period of a maximum of 143 days (the first larvae were established on JD 122 and the last one on JD 265), and pupae were established in the soil over a period of 102 days (between JDs 143 and 245). This study provides important data for understanding SBW population dynamics and developing potential population dynamic models for pest forecasting on a regional scale.
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Chen, YingJie, Yunfang Li, Ping Zhang, Jay H. Traverse, Mingxiao Hou, Xin Xu, Masumi Kimoto, and Robert J. Bache. "Dimethylarginine dimethylaminohydrolase and endothelial dysfunction in failing hearts." American Journal of Physiology-Heart and Circulatory Physiology 289, no. 5 (November 2005): H2212—H2219. http://dx.doi.org/10.1152/ajpheart.00224.2005.
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Congestive heart failure (CHF) is associated with impaired endothelium-dependent nitric oxide (NO)-mediated vasodilation (endothelial dysfunction). We hypothesized that coronary endothelial dysfunction in CHF may be due in part to decreased dimethylarginine dimethylaminohydrolase (DDAH), the enzyme that degrades endogenous inhibitors of NO synthase (NOS), including asymmetric dimethylarginine. Coronary blood flow and the endothelium-dependent vasodilator response to acetylcholine were studied in dogs in which CHF was produced by rapid ventricular pacing for 4 wk. Coronary flow and myocardial O2 consumption at rest and during treadmill exercise were decreased after development of CHF, and the vasodilator response to intracoronary acetylcholine (75 μg/min) was decreased by 39 ± 5%. DDAH activity and DDAH isoform 2 (DDAH-2) protein content were decreased by 53 ± 13% and 58 ± 14%, respectively, in hearts with CHF, whereas endothelial NOS and DDAH isoform 1 (DDAH-1) were increased. Caveolin-1 and protein arginine N-methyltransferase 1, the enzyme that produces asymmetric dimethylarginine, were unchanged. Immunohistochemical staining showed DDAH-1 strongly expressed in coronary endothelium and smooth muscle and in the sarcolemma of cardiac myocytes. In cultured human endothelial cells, DDAH-1 was uniformly distributed in the cytosol and nucleus, whereas DDAH-2 was found only in the cytosol. Decreased DDAH activity and DDAH-2 protein expression may cause accumulation of endogenous inhibitors of endothelial NOS, thereby contributing to endothelial dysfunction in the failing heart.
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Lin, Heng-Huei, Tzong-Shyuan Lee, Shing-Jong Lin, Yi-Chen Yeh, Tse-Min Lu, and Chiao-Po Hsu. "DDAH-2 alleviates contrast medium iopromide-induced acute kidney injury through nitric oxide synthase." Clinical Science 133, no. 23 (December 2019): 2361–78. http://dx.doi.org/10.1042/cs20190455.
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Abstract Background: Contrast medium-induced acute kidney injury (CI-AKI) is one of the most common causes of hospital-acquired acute renal failure. However, the pathogenesis of CI-AKI remains unclear. Asymmetric dimethylarginine (ADMA) is an endogenous nitric oxide synthase (NOS) inhibitor that is largely metabolised by dimethylarginine dimethylaminohydroxylase (DDAH) in humans. Two isoforms of DDAH exist, namely, DDAH-1 and DDAH-2. In the present study, we examined whether the DDAH-2/ADMA/NOS pathway is involved in the pathogenesis of CI-AKI. Methods and Results: Exposure to the contrast medium iopromide led to increase in creatinine and blood urea nitrogen (BUN) levels, accumulation of ADMA, increase in reactive oxygen species (ROS) generation, and an inflammatory response in mice kidney tissue. The injection of adenovirus-harbouring DDAH-2 lowered renal ADMA levels and had a reno-protective effect against contrast-medium injury by decreasing cell apoptosis, ROS, and fibrosis. By contrast, contrast medium-induced renal injury was exacerbated in heterozygous DDAH-2 knockout mice. In the in vitro study, overexpression of DDAH-2 increased the levels of nitrite and intracellular cGMP, while the DDAH-2 knockdown induced the opposite effect. These findings were also observed in the in vivo sample. Conclusions: Our findings provide the first evidence that the DDAH-2/ADMA/NOS pathway is involved in the pathogenesis of CI-AKI and that the protective effect of DDAH-2 probably arises from the modulation of NOS activity, oxidative stress, and the inflammatory process.
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Palm, Fredrik, Maristela L. Onozato, Zaiming Luo, and Christopher S. Wilcox. "Dimethylarginine dimethylaminohydrolase (DDAH): expression, regulation, and function in the cardiovascular and renal systems." American Journal of Physiology-Heart and Circulatory Physiology 293, no. 6 (December 2007): H3227—H3245. http://dx.doi.org/10.1152/ajpheart.00998.2007.
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Asymmetric ( NG, NG)-dimethylarginine (ADMA) inhibits nitric oxide (NO) synthases (NOS). ADMA is a risk factor for endothelial dysfunction, cardiovascular mortality, and progression of chronic kidney disease. Two isoforms of dimethylarginine dimethylaminohydrolase (DDAH) metabolize ADMA. DDAH-1 is the predominant isoform in the proximal tubules of the kidney and in the liver. These organs extract ADMA from the circulation. DDAH-2 is the predominant isoform in the vasculature, where it is found in endothelial cells adjacent to the cell membrane and in intracellular vesicles and in vascular smooth muscle cells among the myofibrils and the nuclear envelope. In vivo gene silencing of DDAH-1 in the rat and DDAH +/− mice both have increased circulating ADMA, whereas gene silencing of DDAH-2 reduces vascular NO generation and endothelium-derived relaxation factor responses. DDAH-2 also is expressed in the kidney in the macula densa and distal nephron. Angiotensin type 1 receptor activation in kidneys reduces the expression of DDAH-1 but increases the expression of DDAH-2. This rapidly evolving evidence of isoform-specific distribution and regulation of DDAH expression in the kidney and blood vessels provides potential mechanisms for nephron site-specific regulation of NO production. In this review, the recent advances in the regulation and function of DDAH enzymes, their roles in the regulation of NO generation, and their possible contribution to endothelial dysfunction in patients with cardiovascular and kidney diseases are discussed.
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Wetzel, Michael D., Ting Gao, Kristen Stanley, Timothy K. Cooper, Sidney M. Morris, and Alaa S. Awad. "Enhancing kidney DDAH-1 expression by adenovirus delivery reduces ADMA and ameliorates diabetic nephropathy." American Journal of Physiology-Renal Physiology 318, no. 2 (February 1, 2020): F509—F517. http://dx.doi.org/10.1152/ajprenal.00518.2019.
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Endothelial dysfunction, characterized by reduced bioavailability of nitric oxide and increased oxidative stress, is a hallmark characteristic in diabetes and diabetic nephropathy (DN). High levels of asymmetric dimethylarginine (ADMA) are observed in several diseases including DN and are a strong prognostic marker for cardiovascular events in patients with diabetes and end-stage renal disease. ADMA, an endogenous endothelial nitric oxide synthase (NOS3) inhibitor, is selectively metabolized by dimethylarginine dimethylaminohydrolase (DDAH). Low DDAH levels have been associated with cardiac and renal dysfunction, but its effects on DN are unknown. We hypothesized that enhanced renal DDAH-1 expression would improve DN by reducing ADMA and restoring NOS3 levels. DBA/2J mice injected with multiple low doses of vehicle or streptozotocin were subsequently injected intrarenally with adenovirus expressing DDAH-1 (Ad-h-DDAH-1) or vector control [Ad-green fluorescent protein (GFP)], and mice were followed for 6 wk. Diabetes was associated with increased kidney ADMA and reduced kidney DDAH activity and DDAH-1 expression but had no effect on kidney DDAH-2 expression. Ad-GFP-treated diabetic mice showed significant increases in albuminuria, histological changes, glomerular macrophage recruitment, inflammatory cytokine and fibrotic markers, kidney ADMA levels, and urinary thiobarbituric acid reactive substances excretion as an indicator of oxidative stress, along with a significant reduction in kidney DDAH activity and kidney NOS3 mRNA compared with normal mice. In contrast, Ad-h-DDAH-1 treatment of diabetic mice reversed these effects. These data indicate, for the first time, that DDAH-1 mediates renal tissue protection in DN via the ADMA-NOS3-interaction. Enhanced renal DDAH-1 activity could be a novel therapeutic tool for treating patients with diabetes.
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Tezel, U., S. G. Pavlostathis, and J. A. Pierson. "Effect of didecyl dimethyl ammonium chloride on nitrate reduction in a mixed methanogenic culture." Water Science and Technology 57, no. 4 (March 1, 2008): 541–46. http://dx.doi.org/10.2166/wst.2008.068.
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The effect of the quaternary ammonium compound, didecyl dimethyl ammonium chloride (DDAC), on nitrate reduction was investigated at concentrations up to 100 mg/L in a batch assay using a mixed, mesophilic (35°C) methanogenic culture. Glucose was used as the carbon and energy source and the initial nitrate concentration was 70 mg N/L. Dissimilatory nitrate reduction to ammonia (DNRA) and to dinitrogen (denitrification) were observed at DDAC concentrations up to 25 mg/L. At and above 50 mg DDAC/L, DNRA was inhibited and denitrification was incomplete resulting in accumulation of nitrous oxide. At DDAC concentrations above 10 mg/L, production of nitrous oxide, even transiently, resulted in complete, long-term inhibition of methanogenesis and accumulation of volatile fatty acids. Fermentation was inhibited at and above 75 mg DDAC/L. DDAC suppressed microbial growth and caused cell lysis at a concentration 50 mg/L or higher. Most of the added DDAC was adsorbed on the biomass. Over 96% of the added DDAC was recovered from all cultures at the end of the 100-days incubation period, indicating that DDAC did not degrade in the mixed methanogenic culture under the conditions of this study.
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Yang, Jeong-Sun, Sung-Bong Choi, Sang-Yong Park, and Sung-Bae Lee. "Analysis of didecydimethylammonium chloride (DDAC) aerosol in inhalation chamber." Analytical Science and Technology 25, no. 5 (October 25, 2012): 307–12. http://dx.doi.org/10.5806/ast.2012.25.5.307.
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Shane, Hillary L., Ewa Lukomska, and Stacey E. Anderson. "Type 2 innate lymphoid cells contribute to a mixed-type allergic response following topical exposure to the quaternary ammonium compound didecyldimethylammonium chloride." Journal of Immunology 200, no. 1_Supplement (May 1, 2018): 104.9. http://dx.doi.org/10.4049/jimmunol.200.supp.104.9.
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Abstract Didecyldimethylammonium chloride (DDAC) is an antimicrobial dialkyl-quaternary ammonium compound used in numerous industrial and commercial products. Clinical and animal data suggest that DDAC exposure elicits multiple types of hypersensitivity reactions. To examine the immunological mechanism behind this mixed type response and the potential involvement of ILCs, we assessed early immune responses in the skin following dermal DDAC exposure (0.25% and 0.5%) in a BALB/c murine model. DDAC exposure resulted in a rapid and dramatic increase in the Th2-skewing and ILC2 activating cytokine TSLP in the skin. Correspondingly, dermal ILC2s were activated 24 hours after DDAC exposure, resulting in increased levels of CD25, ICOS and KLRG1, and decreased CD127 on a per cell basis throughout a 7 day period of exposure. Following ILC2 activation, the Th2 cytokine IL-4 was found to be elevated compared to control mice in total ear protein lysate in the 0.5% DDAC treated mice. To determine a functional role for ILC2s in DDAC induced sensitization we used Rag2−/− mice, which lack mature T and B cells. ILC2s from Rag2−/− were similarly activated by DDAC and importantly, produced significant levels of IL-4 (0.5%DDAC) and IL-5 (0.25% and 0.5%) in the skin. These data indicate that ILC2s contribute to Th2 immune responses early after DDAC exposure. ILC2s have been previously implicated allergic responses, but to our knowledge have not been thoroughly investigated in chemical sensitization. These results indicate that skin resident ILC2s become activated and produce TH2 cytokines following exposure to DDAC, providing a possible mechanism for the development of a mixed-type allergic response commonly observed with chemical sensitizers.
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Zhang, Jing, Sa Ma, Wenchang Wang, and Zhidong Chen. "Electrochemical Sensing of Bisphenol A by a Didodecyldimethylammonium Bromide-Modified Expanded Graphite Paste Electrode." Journal of AOAC INTERNATIONAL 99, no. 4 (July 1, 2016): 1066–72. http://dx.doi.org/10.5740/jaoacint.16-0072.
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Abstract An electrochemical and sensitive sensing of 2,2-bis(4-hydroxyphenyl) propane [bisphenol A (BPA)] was developed based on a didodecyldimethylammonium bromide-modified expanded graphite paste electrode (DDAB-EGPE). The DDAB-EGPE was prepared by suspending an EGPE in a DDAB aqueous solution, and allowing the DDAB to form a hydrophobic film on the expanded graphite surface. Compared with the EGPE, the DDAB-EGPE showed improved electrochemical response of BPA because of the preconcentration of BPA in DDAB via hydrophobic interaction. Due to the electrocatalytic activity of BPA, a sensor for BPA was constructed based on the DDAB-EGPE. The DDAB-EGPE exhibited a wide linear response to BPA ranging from 6.0 × 10−8 to 2.0 × 10−5 mol/L with a detection limit of 7.1 nmol/L at S/N = 3. The designed sensor showed good reproducibility and stability. The proposed sensor was successfully applied to the determination of BPA in three types of real plastic product samples. This sensor presented a simple, rapid, and sensitive platform for the determination of BPA and could become a versatile and powerful tool for food safety.