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Journal articles on the topic 'NET'

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Published: 4 June 2021

Last updated: 24 August 2024

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1

Sabrin, F., M. A. Uddin, and A. K. F. Haque. "Applicability of Vaisburd and Evdokimov Model to Ionic Targets." Journal of Scientific Research 4, no. 2 (April 19, 2012): 307. http://dx.doi.org/10.3329/jsr.v4i2.8704.

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The Vaisburd and Evdokimov proposed an empirical model to calculate the electron impact single ionization cross-sections of atoms and molecules. The model has been applied to some atoms and molecules. To examine the efficiency of the model, the present work applies the model to calculate cross-sections for Ne-isonuclear series Ne+, Ne2+, Ne3+, Ne4+, Ne5+, Ne6+, Ne7+, Ne8+, Ne9+ . The separate sets of values of the parameters of the model are determined by comparison with the available experimental data using a non-linear least-squares fitting computer code. Keywords: Electron impact ionization; Empirical model; Ionic targets. © 2012 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved. doi: http://dx.doi.org/10.3329/jsr.v4i2.8704 J. Sci. Res. 4 (2), 307-313 (2012)

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2

Abduloeva, N. K., V. M. Moiseenko, F. V. Moiseenko, O. A. Skripko, M. V. Scriabin, and R. A. Ryanjina. "Long-term outcomes of neoadjuvant endocrine therapy versus chemotherapy in luminal HER2-breast cancer." Practical oncology 25, no. 1 (March 30, 2024): 41–48. http://dx.doi.org/10.31917/2501041.

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Introduction. Neoadjuvant endocrine therapy (NET) is an effective treatment modality that can downsize breast tumors in a cohort of postmenopausal women with HR-positive HER2-negative breast cancer. A lack of data regarding efficacy of NET vs neoadjuvant cytotoxic chemotherapy (NCT) leads to limited usage of NET despite its favorable toxicity profile. Perioperative endocrine therapy is mainly used for the elderly or patients with comorbidities that limit their access to NCT. The COVID-19 pandemic led to increased data of NET efficacy. Nevertheless, long-term outcomes of NET application are underrepresented in literature. Objective. Assessment of long-term outcomes in patients treated with neoadjuvant endocrine therapy (NAT) versus neoadjuvant cytotoxic chemotherapy in a cohort of postmenopausal women with HR-positive HER2-negative breast cancer. Materials and methods. We retrospectively evaluated the results of treatment of 154postmenopausal patients with luminal HER2-breast cancer who were treated with neoadjuvant systemic therapy (NET or NCT) at the State Medical Institution «St. Petersburg Clinical Scientific and Practical Center for Specialized Types of Medical Care (Oncological)» from 01.01.2019 to 31.11.2020. We analyzed data on radiological, pathomorphological and long-term treatment outcomes (rate of locoregional and overall recurrence) in two groups.Results. 154 patients received neoadjuvant hormone therapy (n=78) or neoadjuvant chemotherapy (n=76). The clinical response was evaluated according to the RECIST criteria after 12 weeks and after study treatment using MMG. Partial or complete radiological response was achieved in 41.0% (n=32) in the NET group vs 69.7% (n=53) in the NCT group (p<0.001). All patients included in the study underwent surgery. A complete pathologic response was observed in 9.2% (n=7) of patients in the chemotherapy group, and in 0% of patients in the endocrine therapy group (p=0.006). Median follow-up was 46.2 months. Progression was recorded in 23.2% (n=29) of participants, with no significant benefit of NCT over NET in the frequency of locoregional relapses (NET n=8 (10.3%) vs NCT n=4 (5.3%)) (p= 0.369) or the occurrence of distant metastases NAT n=8 (10.3%) vs NCT n=13 (17.1%)) (p=0.216). Multivariate analysis showed that only pathologic lymph node status (ypN2–3) was an independent predictor of progression (p=0.007, OR=3.2; 95%CI: 1.380-7.422). Conclusions. Long-term outcomes after neoadjuvant hormone therapy are comparable with chemotherapy in the group of postmenopausal women with luminal HER2-breast cancer. The small sample size and limited follow-up period are significant limitations of our work.

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3

Kinoshita, S. "Kyoshin Net (K-NET)." Seismological Research Letters 69, no. 4 (July 1, 1998): 309–32. http://dx.doi.org/10.1785/gssrl.69.4.309.

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4

Kramarae, Cheris, and Jana Kramer. "Net Gains, Net Losses." Women's Review of Books 12, no. 5 (February 1995): 33. http://dx.doi.org/10.2307/4021979.

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5

Grover, Jan Zita, Paulina Borsook, Susan Hawthorne, and Renate Klein. "Bad Net, Good Net." Women's Review of Books 17, no. 12 (September 2000): 12. http://dx.doi.org/10.2307/4023550.

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6

Berghel, Hal. "Net Neutrality vs. Net Neutering." Computer 49, no. 3 (March 2016): 73–77. http://dx.doi.org/10.1109/mc.2016.84.

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7

Blaxter, J. H. S. "Net profit or net loss?" Nature 371, no. 6497 (October 1994): 483. http://dx.doi.org/10.1038/371483a0.

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8

Zou, Jinghan, Shuhui Yin, Mingxing Guo, Xuesong Xu, Li Che, Lei Li, and Hong Gao. "Isotopic Effect on Stereodynamics of the Reactions H + NeH+/H + NeD+/H + NeT+." Bulletin of the Chemical Society of Japan 86, no. 4 (April 15, 2013): 472–78. http://dx.doi.org/10.1246/bcsj.20120109.

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9

Endo, Shunji, Tsutomu Dousei, Yukinobu Yoshikawa, Nobutaka Hatanaka, Kiyomi Taniyama, Amane Yamauchi, Wataru Kamiike, and Junichi Nishijima. "Gastric Neuroendocrine Tumors in Our Institutions According to the WHO 2010 Classification." International Surgery 97, no. 4 (January 1, 2013): 335–39. http://dx.doi.org/10.9738/cc134.1.

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Abstract In 2010, World Health Organization classified gastric neuroendocrine tumor (NET) as follows: NET grade (G) 1, NET G2, neuroendocrine carcinoma (NEC). We reviewed 22 gastric NETs that were encountered in our institutions. Nine, 6, and 4 were NET G1, G2, and NEC, respectively. We also encountered 3 NET G3. NET G1 was treated with observation in 2 patients, endoscopic mucosal resection (EMR) in 3, and gastrectomy in 4 patients. No recurrence was experienced during a median of 53 months of follow-up. All NET G2 was treated with gastrectomy. No patient experienced recurrence during a median of 25 months of follow-up. NET G3 was treated with gastrectomy. One patient died of liver metastasis 52 months after gastrectomy. For NEC, gastrectomy was performed in 3 cases and no patients died of tumor-related death. We conclude that the prognoses of NET G1 and G2 were good. We also experienced long-term survivors of NEC. An accumulation of more patients is needed for further investigation.

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10

Heetfeld, M., C. N. Chougnet, I. H. Olsen, A. Rinke, I. Borbath, G. Crespo, J. Barriuso, et al. "Characteristics and treatment of patients with G3 gastroenteropancreatic neuroendocrine neoplasms." Endocrine-Related Cancer 22, no. 4 (June 25, 2015): 657–64. http://dx.doi.org/10.1530/erc-15-0119.

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Data on gastroenteropancreatic neuroendocrine neoplasms (NEN) G3 (well-differentiated neuroendocrine tumors (NET G3) and neuroendocrine carcinoma (NEC)) are limited. We retrospectively study patients with NET G3 and NEC from eight European centers. Data examined included clinical and pathological characteristics at diagnosis, therapies and outcomes. Two hundred and four patients were analyzed (37 NET G3 and 167 NEC). Median age was 64 (21–89) years. Tumor origin included pancreas (32%) and colon-rectum (27%). The primary tumor was resected in 82 (40%) patients. Metastatic disease was evident at diagnosis in 88% (liver metastases: 67%). Median Ki-67 index was 70% (30% in NET G3 and 80% in NEC;P<0.001). Median overall survival (OS) for all patients was 23 (95% CI: 18–28) months and significantly higher in NET G3 (99 vs 17 months in NEC; HR=8.3;P<0.001). Platinum-etoposide first line chemotherapy was administered in 113 (68%) NEC and 12 (32%) NET G3 patients. Disease control rate and progression free survival (PFS) were significantly higher in NEC compared to NET G3 (P<0.05), whereas OS was significantly longer in NET G3 (P=0.003). Second- and third-line therapies (mainly FOLFIRI and FOLFOX) were given in 79 and 39 of NEC patients; median PFS and OS were 3.0 and 7.6 months respectively after second-line and 2.5 and 6.2 months after third-line chemotherapy. In conclusion, NET G3 and NEC are characterized by significant differences in Ki-67 index and outcomes. While platinum-based chemotherapy is effective in NEC, it seems to have limited value in NET G3.

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Busse, Antonia, Liliana H. Mochmann, Christiane Spenke, Ruza Arsenic, Franziska Briest, Korinna Jöhrens, Hedwig Lammert, et al. "Immunoprofiling in Neuroendocrine Neoplasms Unveil Immunosuppressive Microenvironment." Cancers 12, no. 11 (November 19, 2020): 3448. http://dx.doi.org/10.3390/cancers12113448.

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Checkpoint inhibitors have shown promising results in a variety of tumors; however, in neuroendocrine tumors (NET) and neuroendocrine carcinomas (NEC), low response rates were reported. We aimed herein to investigate the tumor immune microenvironment in NET/NEC to determine whether checkpoint pathways like programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) might play a role in immune escape and whether other escape mechanisms might need to be targeted to enable a functional antitumor response. Forty-eight NET and thirty NEC samples were analyzed by immunohistochemistry (IHC) and mRNA immunoprofiling including digital spatial profiling. Through IHC, both NET/NEC showed stromal, but less intratumoral CD3+ T cell infiltration, although this was significantly higher in NEC compared to NET. Expression of PD1, PD-L1, and T cell immunoglobulin and mucin domain-containing protein 3 (TIM3) on immune cells was low or nearly absent. mRNA immunoprofiling revealed low expression of IFNγ inducible genes in NET and NEC without any spatial heterogeneity. However, we observed an increased mRNA expression of chemokines, which attract myeloid cells in NET and NEC, and a high abundance of genes related to immunosuppressive myeloid cells and genes with immunosuppressive functions like CD47 and CD74. In conclusion, NET and NEC lack signs of an activation of the adaptive immune system, but rather show abundance of several immunosuppressive genes that represent potential targets for immunomodulation.

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12

Seth, H. ".Net." Computer Bulletin 44, no. 1 (January 1, 2002): 32. http://dx.doi.org/10.1093/combul/44.1.32.

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13

Madoff, David. "NET." Journal of Vascular and Interventional Radiology 16, no. 2 (February 2005): P18. http://dx.doi.org/10.1016/s1051-0443(05)70031-2.

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14

Jablonska, Jadwiga. "To NET or not to NET." American Journal of Immunology 10, no. 4 (April 1, 2014): 174–75. http://dx.doi.org/10.3844/ajisp.2014.174.175.

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15

Rokach, Joshua Z. "Net Metering Needs a Safety Net." Electricity Journal 24, no. 9 (November 2011): 106–8. http://dx.doi.org/10.1016/j.tej.2011.09.018.

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16

Peters, R. "NET TIP:Job Hunting with a Net." Science 281, no. 5375 (July 17, 1998): 366–67. http://dx.doi.org/10.1126/science.281.5375.366.

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17

Schwartau, Winn. "To net or not to net?" Network Security 1994, no. 12 (December 1994): 7–11. http://dx.doi.org/10.1016/1353-4858(94)90024-8.

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18

Adnan, Shah Ali, and Akanksha . "Net Zero/Net Zero Carbon Emission." ADHYAYAN: A JOURNAL OF MANAGEMENT SCIENCES 12, no. 02 (March 4, 2023): 1–5. http://dx.doi.org/10.21567/adhyayan.v12i2.01.

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Every other day we hear about environmental and climate issues and the effect of global warming or carbon emission. Many companies are shifting their concerns from making profits to making sustainable profits. The idea of saving the environment has propelled many start-ups also. Organizations worldwide are concerned about the consequences of wasting natural resources and trying their best to find a solution as soon as possible. The Paris Agreement and the Net Zero Coalition are some of the treaties the UN organization is trying to implement. The problem is that some people are ignoring climate change altogether or still think this is not a big concern. So, this article answers the following questions: what is net zero or net zero emission, how does it create an impact on our lives, and what, as an individual, do we could do about it?

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19

Basnet, Alina, Dongliang Wang, and Abirami Sivapiragasam. "Utilization, trend and impact of neoadjuvant endocrine therapy compared to neoadjuvant chemotherapy in postmenopausal breast cancer patients: Analysis of the National Cancer Data Base." Journal of Clinical Oncology 35, no. 15_suppl (May 20, 2017): 578. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.578.

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578 Background: Three small prospective trials that compared the efficacy of neoadjuvant endocrine therapy (NET) to neoadjuvant chemotherapy (NCT) showed no statistically significant difference. We report the differences in utilization of NET and NCT using National Cancer Data Base (NCDB) and their trend, response rates (RR) and breast conservation rates (BCR). Methods: A retrospective review of hormone receptor positive breast cancer patients ≥ 50 yrs without metastasis using NCDB was performed (2004-2014). Patients underwent NET or NCT prior to definitive surgery. Utilization pattern, practice trend, RR and BCR between NET and NCT was assessed using univariate and multivariate logistic analysis. Results: Out of 2,246,279 breast cancer patients reported in NCDB, 38,632 met our inclusion criteria. 9178 received NET and 29,454 received NCT. On multivariate analysis NET use was higher in academic vs community centers [Odds ratio (OR) 1.355, 95% CI 1.270-1.445], age >70 vs < 70 (OR 6.603, 95% CI 6.110-7.137) and high vs low Charlson Deyo comorbidity index (OR 1.817, 95% CI 1.548-2.133). NET use was lower in black vs white (OR 0.790, 95% CI 0.712- 0.875), tumors with higher vs lower grade (OR 0.153, 95% CI 0.138-0.169), higher vs lower T stage (OR 0.372, 95% CI 0.340-0.407), higher vs lower N stage (OR 0.274, 95% CI 0.243-0.310) and private vs no insurance (OR 0.600, 95% CI 0.509- 0.707), (all p<0.0001). A significant upward trend in utilization of NET was observed from year 2011 (25.9%) compared to before (22.2%), p<0.0001. RR was significantly higher for patients receiving NCT (90.5%) compared to NET (77.2%), with an [adjusted OR (aOR) 2.413; 95% CI 2.116-2.752], however the BCR was superior in the NET group (50.0%) compared to NCT group (31.1%) with (aOR 1.676; 95% CI 1.567-1.794). Conclusions: Our study is the first to compare NET and NCT utilization and their efficacy using NCDB database. Our results have shown striking differences in outcome among these two strategies as compared to other prospective trials. Despite high RR, more patients underwent mastectomy in the NCT group. We also see a steady upward trend in usage of NET from year 2011.

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20

Okada, Yoshimitsu, Keiji Kasahara, Sadaki Hori, Kazushige Obara, Shoji Sekiguchi, Hiroyuki Fujiwara, and Akira Yamamoto. "Recent progress of seismic observation networks in Japan —Hi-net, F-net, K-NET and KiK-net—." Earth, Planets and Space 56, no. 8 (August 2004): xv—xxviii. http://dx.doi.org/10.1186/bf03353076.

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21

Shiba, Satoshi, Chigusa Morizane, Shunsuke Kondo, Hideki Ueno, Masafumi Ikeda, Tomohiro Yamaguchi, Takuji Okusaka, Kazuaki Shimada, Tomoo Kosuge, and Nobuyoshi Hiraoka. "Pancreatic neuroendocrine tumors: Twenty years’ experience of 100 patients at a single center." Journal of Clinical Oncology 30, no. 4_suppl (February 1, 2012): 179. http://dx.doi.org/10.1200/jco.2012.30.4_suppl.179.

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179 Background: Pancreatic neuroendocrine tumors (NETs) are rare neoplasms that exhibit a variety of diverse morphological, functional and behavioral characteristics. However, only a few reports have evaluated large case series of pancreatic endocrine tumors. Methods: We conducted a retrospective review of 100 consecutive patients with pancreatic NETs diagnosed pathologically and treated at the National Cancer Center Hospital between 1991 and 2010. Results: The characteristics of the 100 patients were as follows: male, 49; female, 51; median age, 55 years. Fourteen patients gave a history of endocrine symptoms at the time of diagnosis. The primary tumors arose in the head, body and tail of the pancreas in 54, 25 and 21 patients, respectively. According to the 2010 grading classification of the World Health Organization, 11 patients were classified as having NET G1, 44 as having NET G2 and 29 as having NEC. The five-year survival rates of the patients with NET G1, NET G2 and NEC were 91%, 78% and 12%, respectively. The five-year survival rates of the patients with stage I, II and III, and IV disease classified according to the American Joint Committee on Cancer (AJCC) were 100%, 68% and 9%, respectively. Distant metastases occurred in 18% percent of the NET G1 patients, 39% of the NET G2 patients and 83% of the NEC patients. Treatment was undertaken by surgical resection in 82%, 59% and 24% of patients with NET G1, NET G2 and NEC, respectively. The five-year survival rates of the patients with NET G1, NET G2 and NEC after radical surgery were 100%, 91% and 36%, respectively. Among the 33 patients treated by systemic chemotherapy, the median survival period was 22.9 months in the patients with NET G1/G2 and 6.6 months in those with NEC. A multivariate analysis identified lower age, good performance status (PS) and lower histopathologic grade as independent favorable prognostic factors. Conclusions: Patients with NET G1, G2 treated by surgical resection had a good prognosis. Most patients with NEC exhibited distant metastases and had a poor prognosis. Histopathologic grade is an important factor for selecting the appropriate treatment strategy and predicting the prognosis in patients with pancreatic NETs.

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Basnet, Alina, Dongliang Wang, and Abirami Sivapiragasam. "Survival advantage associated with neoadjuvant chemotherapy compared to neoadjuvant hormonal therapy in postmenopausal women with hormone receptor positive breast cancer: A National Cancer Data Base study." Journal of Clinical Oncology 35, no. 15_suppl (May 20, 2017): e12119-e12119. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.e12119.

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e12119 Background: Neoadjuvant endocrine therapy (NET) and neoadjuvant chemotherapy (NCT) are both considered effective strategies in postmenopausal, hormone receptor positive breast cancer patients. Small prospective studies show comparable response rates and breast conservation rates. Using National Cancer Data Base (NCDB) we report overall survival (OS) differences between these two strategies with subgroup analysis by Estrogen Receptor (ER), Progesterone Receptor (PgR) status. Methods: We extracted data on hormone receptor positive breast cancer patients without metastasis in women aged ≥ 50 from the NCDB registry (2004-2014). We excluded patients who did not receive adjuvant endocrine therapy after NCT and patients who received adjuvant chemotherapy after NET as this could affect OS. We calculated OS using Kaplan Meier analysis with hazard ratio (HR) from cox regression model. Subgroup analysis was performed by ER, PgR status. Results: Out of 2,246,279 patients, 30,348 patients met our inclusion criteria. 7836 received NET and 22512 received NCT. OS rate was 70.8% vs 81.7% at 5 yrs and 42.5% vs 62.1% at 9 yrs for NET and NCT respectively with adjusted hazard ratio (HR) of 1.818; 95% CI (1.657-1.996). OS outcome for ER+/PgR+ group was 72.3% vs 83.5% at 5 yrs and 43.5% vs 64% at 9 yrs for NET and NCT respectively with adjusted HR of 1.807; 95% CI (1.624-2.010). OS for ER+/pgR- group was 62.9% vs 76.8% at 5 yrs and 33.1% vs 54.2% at 9 yrs for NET and NCT respectively with adjusted HR of 1.890; 95% CI (1.549-2.306). Our analysis also revealed that 5591 T1 patients received neoadjuvant therapy among which 2541 received NET and 3050 received NCT. Conclusions: We find a significant survival advantage in patients treated with NCT as opposed to NET. All subgroups showed imporved OS with NCT compared with NET. Limitations that should be considered in this registry based study are: not accounting for Her-2 status, differences in surgical technique, duration and choices of adjuvant chemotherapy and radiotherapy options.

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23

Dodson, Thomas B. "When Net Loss Threatens Safety Net Loss." Journal of Oral and Maxillofacial Surgery 76, no. 12 (December 2018): 2459–60. http://dx.doi.org/10.1016/j.joms.2018.09.016.

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24

Mateosian, R. "Microsoft's .NET platform introducing .NET [Book Reviews]." IEEE Micro 21, no. 2 (March 2001): 94–95. http://dx.doi.org/10.1109/mm.2001.918030.

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25

Boeve, M. N. (Marlon). "‘No net land take’ of net niks?" Tijdschrift voor Omgevingsrecht 23, no. 1 (May 2023): 3–4. http://dx.doi.org/10.5553/to/156850122023023001002.

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gu, chongshan, yingjian he, jinfeng li, tianfeng wang, zhaoqing Fan, and tao ouyang. "Abstract P5-09-04: Efficacy of neoadjuvant endocrine therapy compared with neoadjuvant chemotherapy in pre-menopausal patients with hormone-responsive and HER2-negative, lymph node-negative breast cancer." Cancer Research 83, no. 5_Supplement (March 1, 2023): P5–09–04—P5–09–04. http://dx.doi.org/10.1158/1538-7445.sabcs22-p5-09-04.

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Abstract Background: Neoadjuvant endocrine therapy (NET) has demonstrated efficacy in post-menopausal patients with hormone-responsive and her2-negative breast cancer. This trial was designed to compare the efficacy of neoadjuvant chemotherapy (NCT) with NET in pre-menopausal patients with hormone-responsive, her2-negative and lymph node-negative breast cancer. Materials and Methods: In this prospective, randomised study, pre-menopausal patients with hormone-responsive, her2-negative and lymph node-negative breast cancer were recruited. Enrolled patients were randomly assigned (1:1) to receive either NCT or NET with goserelin and tamoxifen, followed by goserelin and anastrozole. The primary purpose was to evaluate the non-inferiority of NET compared to NCT using clinical response, assessed by ultrasound. Results: A total of 68 patients were assigned to receive NCT (n = 31) or NET (n = 37). The clinical response rate was 16.1% for NCT and 35.1% for NET (estimated difference19%, 95%CI:-1.1%-39.1%, non-inferior p = 0.002). Rates of breast-conserving surgery were similar between NCT and NET (90.3% vs 83.8%, p=0.494). Conclusions: The clinical response rate of NET is non-inferior to NCT in pre-menopausal patients with hormone-responsive, HER2-negative, lymph node-negative breast cancer. Summary of ultrasound clinical response The breast surgery and MP grading system Citation Format: chongshan gu, yingjian he, jinfeng li, tianfeng wang, zhaoqing Fan, tao ouyang. Efficacy of neoadjuvant endocrine therapy compared with neoadjuvant chemotherapy in pre-menopausal patients with hormone-responsive and HER2-negative, lymph node-negative breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-09-04.

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Jeon, Young Kyung, Ji-Yeon Kim, Jin Seok Ahn, Young Hyunk Im, Kyue-Hee Choi, Sun Young Jeong, Yeji Jung, et al. "Abstract P3-05-07: Primary neuroendocrine carcinoma of the breast: A case series by WHO classfication in 2019." Cancer Research 83, no. 5_Supplement (March 1, 2023): P3–05–07—P3–05–07. http://dx.doi.org/10.1158/1538-7445.sabcs22-p3-05-07.

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Abstract Introduction Neuroendocrine tumours (NET) are thought to arise from cells throughout the diffuse endocrine system and can occur almost everywhere in the body. Most NETs arise from the gastrointestinal tract, lung, thymus, and pancreas. Primary neuroendocrine carcinoma (NEC) of the breast is a rare and under-recognized subtype, accounting for less than 1% of breast carcinomas. Only a few small studies and case reports have been reported and there are no clear diagnostic criteria and established treatment options. World Health Organization (WHO) classification of tumor series’ fifth edition was published in 2019 and adopted ‘Neuroendocrine neoplasm (NEN)’ as a term encompassing all tumour classes with predominant neuroendocrine differentiation. NENs of the breast are classified into invasive ductal carcinoma (IDC) with neuroendocrine differentiation (NED), NET, and NEC of small cell or large cell types. Thus we aim to report pathologic reviews and treatment outcomes of patients with NENs of the breast at a single center. Methods We retrospectively screened the medical record of 34,370 patients diagnosed with breast cancer from 2007 to 2022 by Corporate Data Warehouse (CDW) and revealed there were 22 patients diagnosed with primary breast NEN. The pathologist reviewed the pathology slides and reclassified the diagnosis according to the WHO classification of tumor series’ fifth edition. Clinical characteristics, treatment modalities, and therapeutic outcomes were reviewed retrospectively. Results We reviewed pathology slides of 22 patients with histologically proven diagnoses of primary breast NEN from 2007 to 2022. We found only 8 patients meet the criteria of primary breast NEC (large cell 2, small cell 6), 3 patients with NET, and 3 patients with IDC with NED. We excluded 8 patients who did not fulfill the criteria of NEN. The median age of NEN was 48.5 years (range, 31-70) and 6 patients (42.9%) were postmenopausal women. The median follow-up duration was 25.3 months (Interquartile range(IQR), 15.0-54.7). All patients underwent surgery, 3 patients underwent a mastectomy and 11 patients underwent breast-conserving surgery (BCS) with a curative aim. Five patients had lymph node metastasis. There was no expression of the human epidermal growth factor receptor 2 (HER2) in all 14 cases. Hormone receptor expression was shown in 4 of NECs (50%) and all NETs or IDC with NED patients. Patients with primary breast NEC had a median recurrence-free period (RFP) of 14.6 months (95% confidence interval (CI), 11.0-18.2) and median overall survival (OS) of 52.1 months (95% CI, 0.0-120.0). Patients with NET or IDC with NED had an overall favorable outcome, none of the patients died and only one patient with IDC with NED experienced disease progression. The median PFS and OS were not reached in NET or IDC with NED subgroups. Conclusion NETs are rare tumours with a wide range of clinical presentations according to the site of involvement. Primary breast NENs are extremely rare and there are no specific guidelines for treatment. NENs are often underdiagnosed, as neuroendocrine markers are not routinely tested in breast cancer. In this retrospective single-center study, the incidence of primary breast NENs was 0.04% (14 of 34,370 patients) and primary breast NEC was associated with poor prognosis compared with breast NET or IDC with NED. Identifying innovative treatment strategies is needed to overcome poor outcomes of primary breast NEC. Citation Format: Young Kyung Jeon, Ji-Yeon Kim, Jin Seok Ahn, Young Hyunk Im, Kyue-Hee Choi, Sun Young Jeong, Yeji Jung, Jae Yeon Jang, Daeho Choi, Joohyun Hong, Hyo Jung Kim, Soo Youn Cho, Yeon H. Park. Primary neuroendocrine carcinoma of the breast: A case series by WHO classfication in 2019 [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-05-07.

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Cho, Hyung-Gyo, Wonkyung Jung, Soo Ick Cho, Jiwon Shin, Gahee Park, Jimin Moon, Minuk Ma, et al. "Artificial intelligence-powered whole-slide image analyzer reveals a distinctive distribution of tumor-infiltrating lymphocytes in neuroendocrine tumors and carcinomas." Journal of Clinical Oncology 40, no. 16_suppl (June 1, 2022): e16214-e16214. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.e16214.

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e16214 Background: Immune checkpoint inhibitors (ICIs) have shown promising treatment outcomes for various types of tumors. However, in neuroendocrine tumors and carcinomas (NET/NEC), ICI has proven to be applicable for only limited cases. In addition, little is known about the immunoprofile of NET/NEC. Here we investigate the landscape of tumor-infiltrating lymphocytes (TIL) using artificial intelligence (AI)-powered H&E whole-slide image (WSI) analyzer to elucidate the tumor microenvironment of NET/NEC. Methods: A total of 240 H&E stained pathologic slides diagnosed with NET/NEC were obtained from Ajou University Medical Center in Korea (from January 2020 to December 2021). For spatial TIL analysis, we used Lunit SCOPE IO, an AI-powered H&E WSI analyzer, which identifies and quantifies TIL within the cancer or stroma area. The AI was developed with a 13.5 x 109 μm2 area and 6.2 x 106 TIL from 17,849 H&E WSI of multiple cancer types, annotated by 104 board-certified pathologists. Intra-tumoral TIL, stromal TIL, and combined (cancer + stroma) TIL density were defined as the TIL count divided by the area of interest respectively. NET with histological grade 1 and 2 were labeled as low grade and NET with histological grade 3 and together with NEC were labeled as high grade. Primary origins of the NET/NEC were grouped by colorectum, stomach, small intestine, hepatopancreatobiliary, lung, and other organs (including anus, appendix, breast, cervix, and larynx). Results: Total slides classified as low grade and high grade were 211 and 29, respectively; 175 samples were from colorectal, 19 from stomach, 16 from small intestine, 16 from hepatopancreaticobiliary, seven from lung, and seven from other organs. The median intra-tumoral TIL, stromal TIL, and combined TIL density were 4.2/mm2 (IQR 1.718 - 11.478), 139.1/mm2 (IQR 75.4 - 313.9), and 62.4/mm2 (IQR 36.3 - 162.6), respectively. The median intra-tumoral TIL density was significantly higher in patients with high grade NET/NEC compared with low grade (11.9/mm2 [IQR 4.51 - 30.9] vs 3.45/mm2 [IQR 1.63 - 9.81], p < 0.001). However, statistical differences in stromal TIL density and combined TIL density were not observed between low grade and high grade NET/NEC. The highest intra-tumoral TIL density in the group classified according to primary origins was lung (n = 7, median: 16.5/mm2, IQR 5.01 - 34.1) and was followed by stomach (n = 19, median: 11.8/mm2, IQR 8.64 - 20.8), and small intestine (n = 16, median: 7.23/mm2, IQR 4.12 - 25.2). Conclusions: AI-powered TIL analysis reveals that the intra-tumoral TIL density is significantly higher in high grade NET/NEC than low grade NET. Our findings align with recent evidence that ICIs are effective against large cell NEC and small cell carcinoma.Therefore, AI-powered TIL analysis should be investigated as a predictive biomarker for ICI response in NET/NEC.

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Scoazec, Jean-Yves, Anne Couvelard, Genevieve Monges, Emmanuelle Leteurtre, Genevieve Belleannee, Serge Guyetant, Pierre Duvillard, Marie Danjoux, Xavier Parot, and Come Lepage. "Well-differentiated grade 3 digestive neuroendocrine tumors: Myth or reality? The PRONET study group." Journal of Clinical Oncology 30, no. 15_suppl (May 20, 2012): 4129. http://dx.doi.org/10.1200/jco.2012.30.15_suppl.4129.

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4129 Background: In contrast to the 2000 World Health Organization (WHO) classification of digestive neuroendocrine tumors (NET) in which morphologic differentiation was the first criterion, the 2010 WHO classification of NET is based mostly on histologic grade. NET are now classified into three main categories: NET G1 (mitotic count <2/10 HPF and/or ≤2% Ki67 index), NET G2 (2-20/10 HPF and/or 3-20%), and neuroendocrine carcinoma (NEC) of small or large cell type. While NET G1 and G2 are well-differentiated tumors, NEC are considered poorly differentiated G3 tumors. We looked at the agreement between grade and differentiation to determine whether all NET can be readily classified according to the 2010 WHO classification. Methods: We designed a 1-year prospective, epidemiologic study to assess the characteristics of newly diagnosed NET, including diagnostic pathology. From August 2010 to July 2011, all pathology laboratories in France were invited to register all incident cases of gastroenteropancreatic (GEP) and thoracic NET, excluding small cell carcinoma. For GEP-NET, investigators were asked to indicate morphologic differentiation (according to WHO 2000) and elements of histologic grade (mitotic index, Ki67 index), according to ENETS. Results: Of 500 invited centers, 80 participated; 1417 incidental cases were included and 77 excluded (duplicates or exclusion criteria), totaling 1340 cases; 778 (58.1%) were GEP-NET; 660/778 (85%) were well differentiated, 72 (9%) poorly differentiated, and 46 (6%) adenocarcinoid, nonclassified, or not evaluable; 422 (54.2%) were G1, 220 (28%) G2, 104 (13.5%) G3, and 32 (4.1%) had missing grades. Of those deemed G3, 72 (69%) were described as poorly differentiated, 21 (20%) as well differentiated (mean Ki67 index 35%, range 25%-60%), and 11 (10.5%) as adenocarcinoid. Conclusions: In this prospective, epidemiologic study, overall agreement between grade and differentiation was good. However, a significant proportion of G3 NET were classified as well differentiated and thus unclassifiable by 2010 WHO classification. This group of tumor deserves to be included in future classifications to help the clinician decide whether they should be treated as NET G1/G2 or NEC G3.

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Farmer, Jane, and Amanda Richardson. "Net profit." Nursing Standard 12, no. 17 (January 14, 1998): 28–31. http://dx.doi.org/10.7748/ns.12.17.28.s46.

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Cookson, Amelia. "Net gains." Nursing Older People 21, no. 1 (February 5, 2009): 6–7. http://dx.doi.org/10.7748/nop.21.1.6.s9.

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Anthony, Denis. "Net profits." Nursing Standard 20, no. 3 (September 28, 2005): 38–39. http://dx.doi.org/10.7748/ns.20.3.38.s63.

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Hise, Thomas L., Robert G. Chester, and Charlotte Omoto. "Net Pluses." Science News 157, no. 16 (April 15, 2000): 243. http://dx.doi.org/10.2307/4012481.

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Botia Paniagua, Enrique, and Santiago Mola Caballero de Rodas. "Neurologia@net." Revista de Neurología 26, no. 151 (1998): 497. http://dx.doi.org/10.33588/rn.26151.98232.

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Botia Paniagua, Enrique, and Santiago Mola Caballero de Rodas. "Neurologia@net." Revista de Neurología 26, no. 152 (1998): 672. http://dx.doi.org/10.33588/rn.26152.98233.

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Botia Paniagua, Enrique. "Neurologia@net." Revista de Neurología 26, no. 153 (1998): 846. http://dx.doi.org/10.33588/rn.26153.98234.

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Bandini, Micha. "The Net." Performance Research 26, no. 6 (August 18, 2021): 34–35. http://dx.doi.org/10.1080/13528165.2021.2059181.

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Kester, Grant. "Net Profits." Afterimage 22, no. 7-8 (February 1995): 8–10. http://dx.doi.org/10.1525/aft.1995.22.7-8.8.

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Xie, Liuyue, Tinglin Duan, and Kenji Shimada. "SAGA-net." ACM SIGAPP Applied Computing Review 22, no. 2 (June 2022): 21–33. http://dx.doi.org/10.1145/3558053.3558055.

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In this paper, we propose a real-time shape-assisted graph attention neural network to perform local pointcloud repairment. The orderless pointclouds require an effective shape encoder to distill local and global geometric feature descriptors. Previous work has attempted to convert pointcloud representation into a voxelized shape or perform grid-transformations. While these approaches can subsequently allow common convolution operations on the structured data, they either pose additional computational cost or disrupt the local geometric information. We present SAGA-Net, an efficient graph attention neural network framework with a prior shape inquiry protocol that effectively extracts local geometric information, locates the descriptor for the missing region and accurately reconstructs the local region in a real-time manner. Our framework has been validated on a benchmark dataset, ShapeNet. We demonstrate that our framework can repair each partial pointcloud with accuracy surpassing other frameworks in most object categories, and improve the computational efficiency by orders of magnitude in terms of time cost.

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Men, Yifang, Yuan Yao, Miaomiao Cui, Zhouhui Lian, and Xuansong Xie. "DCT-net." ACM Transactions on Graphics 41, no. 4 (July 2022): 1–9. http://dx.doi.org/10.1145/3528223.3530159.

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This paper introduces DCT-Net, a novel image translation architecture for few-shot portrait stylization. Given limited style exemplars (~100), the new architecture can produce high-quality style transfer results with advanced ability to synthesize high-fidelity contents and strong generality to handle complicated scenes (e.g., occlusions and accessories). Moreover, it enables full-body image translation via one elegant evaluation network trained by partial observations (i.e., stylized heads). Few-shot learning based style transfer is challenging since the learned model can easily become overfitted in the target domain, due to the biased distribution formed by only a few training examples. This paper aims to handle the challenge by adopting the key idea of "calibration first, translation later" and exploring the augmented global structure with locally-focused translation. Specifically, the proposed DCT-Net consists of three modules: a content adapter borrowing the powerful prior from source photos to calibrate the content distribution of target samples; a geometry expansion module using affine transformations to release spatially semantic constraints; and a texture translation module leveraging samples produced by the calibrated distribution to learn a fine-grained conversion. Experimental results demonstrate the proposed method's superiority over the state of the art in head stylization and its effectiveness on full image translation with adaptive deformations. Our code is publicly available at https://github.com/menyifang/DCT-Net.

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Vinay, A., Paras S. Khurana, T. B. Sudarshan, S. Natarajan, Vivek Nagesh, Vishruth Lakshminarayanan, and Niput Bhat. "AFMB-Net." Tehnički glasnik 16, no. 4 (September 26, 2022): 503–8. http://dx.doi.org/10.31803/tg-20220403080215.

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With advances in deepfake generating technology, it is getting increasingly difficult to detect deepfakes. Deepfakes can be used for many malpractices such as blackmail, politics, social media, etc. These can lead to widespread misinformation and can be harmful to an individual or an institution’s reputation. It has become important to be able to identify deepfakes effectively, while there exist many machine learning techniques to identify them, these methods are not able to cope up with the rapidly improving GAN technology which is used to generate deepfakes. Our project aims to identify deepfakes successfully using machine learning along with Heart Rate Analysis. The heart rate identified by our model is unique to each individual and cannot be spoofed or imitated by a GAN and is thus susceptible to improving GAN technology. To solve the deepfake detection problem we employ various machine learning models along with heart rate analysis to detect deepfakes.

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Feingold, Ken. "Net-Works." Leonardo 29, no. 5 (1996): 459. http://dx.doi.org/10.2307/1576410.

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Feingold, Ken. "Net-Works." Leonardo 30, no. 5 (1997): 449. http://dx.doi.org/10.2307/1576503.

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Pivec, Franci. "Net generacija." Organizacija znanja 13, no. 2 (2008): 61–63. http://dx.doi.org/10.3359/oz0802061.

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Burke, Katherine. "Net profits." Nursing Standard 13, no. 47 (August 11, 1999): 12–13. http://dx.doi.org/10.7748/ns.13.47.12.s29.

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Fourmentraux, Jean-Paul. "Net art." Communications 88, no. 1 (2011): 113. http://dx.doi.org/10.3917/commu.088.0113.

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Brown, Greg. "Net Needle." World Literature Today 91, no. 1 (2017): 83–84. http://dx.doi.org/10.1353/wlt.2017.0234.

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Gao, Lin, Tong Wu, Yu-Jie Yuan, Ming-Xian Lin, Yu-Kun Lai, and Hao Zhang. "TM-NET." ACM Transactions on Graphics 40, no. 6 (December 2021): 1–15. http://dx.doi.org/10.1145/3478513.3480503.

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We introduce TM-NET, a novel deep generative model for synthesizing textured meshes in a part-aware manner. Once trained, the network can generate novel textured meshes from scratch or predict textures for a given 3D mesh, without image guidance. Plausible and diverse textures can be generated for the same mesh part, while texture compatibility between parts in the same shape is achieved via conditional generation. Specifically, our method produces texture maps for individual shape parts, each as a deformable box, leading to a natural UV map with limited distortion. The network separately embeds part geometry (via a PartVAE) and part texture (via a TextureVAE) into their respective latent spaces, so as to facilitate learning texture probability distributions conditioned on geometry. We introduce a conditional autoregressive model for texture generation, which can be conditioned on both part geometry and textures already generated for other parts to achieve texture compatibility. To produce high-frequency texture details, our TextureVAE operates in a high-dimensional latent space via dictionary-based vector quantization. We also exploit transparencies in the texture as an effective means to model complex shape structures including topological details. Extensive experiments demonstrate the plausibility, quality, and diversity of the textures and geometries generated by our network, while avoiding inconsistency issues that are common to novel view synthesis methods.

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Cartwright, Tina. "Net profits." Nursing Standard 15, no. 35 (May 16, 2001): 24–25. http://dx.doi.org/10.7748/ns.15.35.24.s35.

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Sultana, Farheen. "Net Metering." International Journal for Research in Applied Science and Engineering Technology 7, no. 4 (April 30, 2019): 2436–40. http://dx.doi.org/10.22214/ijraset.2019.4443.

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