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In diamond wire saw cutting monocrystalline silicon (mono-Si), the material brittleness removal can cause microcrack damage in the subsurface of the as-sawn silicon wafer, which has a significant impact on the mechanical properties and subsequent processing steps of the wafers. In order to quickly and non-destructively obtain the subsurface microcrack damage depth (SSD) of as-sawn silicon wafers, this paper conducted research on the SSD prediction model for diamond wire saw cutting of mono-Si, and established the relationship between the SSD and the as-sawn surface roughness value (SR) by comprehensively considering the effect of tangential force and the influence of the elastic stress field and residual stress field below the abrasive on the propagation of median cracks. Furthermore, the theoretical relationship model between SR and SSD has been improved by adding a coefficient considering the influence of material ductile regime removal on SR values based on experiments sawing mono-Si along the (111) crystal plane, making the theoretical prediction value of SSD more accurate. The research results indicate that a decrease in wire speed and an increase in feed speed result in an increase in SR and SSD in silicon wafers. There is a non-linear increasing relationship between silicon wafer SSD and SR, with SSD = 21.179 Ra4/3. The larger the SR, the deeper the SSD, and the smaller the relative error of SSD between the theoretical predicted and experimental measurements. The research results provide a theoretical and experimental basis for predicting silicon wafer SSD in diamond wire sawing and optimizing the process.
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OBJECTIVE: To developed a magnetic resonance imaging (MRI) radiomics nomogram to identify adenocarcinoma at the cervix-corpus junction originating from the endometrium or cervix in order to better guide clinical treatment. METHODS: Between February 2011 and September 2021, the clinicopathological data and MRI in 143 patients with histopathologically confirmed cervical adenocarcinoma (CAC, n = 86) and endometrioid adenocarcinoma (EAC, n = 57) were retrospectively analyzed at the cervix-corpus junction. Radiomics features were extracted from fat-suppressed T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) maps, and delayed phase contrast-enhanced T1-weighted imaging (CE-T1WI) sequences. A radiomics nomogram was developed integrating radscore with independent clinical risk factors. The area under the curve (AUC) was used to evaluate the diagnostic efficacy of the radscore, nomogram and two different experienced radiologists in differentiating CAC from EAC at the cervix-corpus junction, and Delong test was applied to compare the differences of their diagnostic performance. RESULTS: In the training cohort, the AUC was 0.93 for radscore; 0.97 for radiomics nomograms; 0.85 and 0.86 for radiologists 1 and 2, respectively. Delong test showed that the differential efficacy of nomogram was significant better than those of radiologists in the training cohort (both P < 0.05). CONCLUSIONS: The nomogram based on radscore and clinical risk factors could better differentiate CAC from EAC at the cervix-corpus junction than radiologists, and preoperatively and non-invasively identify the origin of adenocarcinoma at the cervix-corpus junction, which facilitates clinicians to make individualized treatment decision.
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Adenocarcinoma , Carcinoma Endometrioide , Neoplasias Endometriales , Imágenes de Resonancia Magnética Multiparamétrica , Nomogramas , Neoplasias del Cuello Uterino , Humanos , Femenino , Neoplasias del Cuello Uterino/diagnóstico por imagen , Neoplasias del Cuello Uterino/patología , Persona de Mediana Edad , Estudios Retrospectivos , Adenocarcinoma/diagnóstico por imagen , Adenocarcinoma/patología , Carcinoma Endometrioide/diagnóstico por imagen , Carcinoma Endometrioide/patología , Neoplasias Endometriales/diagnóstico por imagen , Neoplasias Endometriales/patología , Adulto , Imágenes de Resonancia Magnética Multiparamétrica/métodos , Anciano , Diagnóstico Diferencial , Cuello del Útero/diagnóstico por imagen , Cuello del Útero/patología , Medios de Contraste , RadiómicaRESUMEN
Ulcerative colitis (UC) is a chronic gastrointestinal disease that results from repeated inflammation and serious complications. Sinapic acid (SA) is a hydroxycinnamic acid present in a variety of plants that has antioxidant, anti-inflammatory, anticancer, and other protective effects. This study investigated the antifibrotic effect of SA on chronic colitis induced by dextran sulfate sodium salt (DSS) in mice. We observed that SA could significantly reduce clinical symptoms (such as improved body weight loss, increased colon length, and decreased disease activity index score) and pathological changes in mice with chronic colitis. SA supplementation has been demonstrated to repair intestinal mucosal barrier function and maintain epithelial homeostasis by inhibiting activation of the NLRP3 inflammasome and decreasing the expression of IL-6, TNF-α, IL-17A, IL-18, and IL-1ß. Furthermore, SA could induce the expression of antioxidant enzymes (Cat, Sod1, Sod2, Mgst1) by activating the Nrf2/keap1 pathway, thus improving antioxidant capacity. Additionally, SA could increase the protein expression of downstream LC3-II/LC3-I and Beclin1 and induce autophagy by regulating the AMPK-Akt/mTOR signaling pathway, thereby reducing the production of intestinal fibrosis-associated proteins Collagen-I and α-SMA. These findings suggest that SA can enhance intestinal antioxidant enzymes, reduce oxidative stress, expedite intestinal epithelial repair, and promote autophagy, thereby ameliorating DSS-induced colitis and intestinal fibrosis.
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OBJECTIVE: Neurosurgeons demonstrate some of the highest levels of burnout among surgeons, yet little research has been done to understand the underlying stressors that neurosurgeons and trainees experience and the emotional responses to them. Our goal was to conduct a feasibility study identifying job stressors and emotional responses among neurosurgeons rather than generalize findings across the profession. METHODS: Emphasizing a qualitative approach in this feasibility and descriptive study, we strategically selected a small sample of neurosurgical attendings, residents, and fellows at 2 United States academic neurosurgical departments to ensure an in-depth analysis laying the groundwork for future extensive research. Participants were asked to complete a questionnaire regarding work-related stressors and high- and low-arousal emotional responses to these stressors, as well as a standardized Depression, Anxiety, and Stress Scale. Both quantitative and qualitative analyses evaluating types of stressors and emotional responses reported were assessed based on participant training level. RESULTS: Participants identified 3 main stressors: 1) administrative deficiencies; 2) delivering bad news/saving lives; and 3) work-life balance. A low frequency of negative emotional responses was reported, but those reported were mainly high-arousal emotions. Limited prior training in coping strategies was also reported. We also found that residents, fellows, and faculty surgeons reported about work stressors and coping strategies differently. CONCLUSIONS: The results of our study provide an understanding of neurosurgical professionals' unique emotional landscape, emphasizing the need for reforms in administrative practices, enhanced, healthy coping strategies, and career stage-specific mental health support.
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Homotypic membrane fusion of the endoplasmic reticulum (ER) is mediated by dynamin-like GTPase atlastin (ATL). This fundamental process relies on GTP-dependent domain rearrangements in the N-terminal region of ATL (ATLcyto), including the GTPase domain and three-helix bundle (3HB). However, its conformational dynamics during the GTPase cycle remain elusive. Here, we combine single-molecule FRET imaging and molecular dynamics simulations to address this conundrum. Different from the prevailing model, ATLcyto can form a loose crossover dimer upon GTP binding, which is tightened by GTP hydrolysis for membrane fusion. Furthermore, the α-helical motif between the 3HB and transmembrane domain, which is embedded in the surface of the lipid bilayer and self-associates in the crossover dimer, is required for ATL function. To recycle the proteins, Pi release, which disassembles the dimer, activates frequent relative movements between the GTPase domain and 3HB, and subsequent GDP dissociation alters the conformational preference of the ATLcyto monomer for entering the next reaction cycle. Finally, we found that two disease-causing mutations affect human ATL1 activity by destabilizing GTP binding-induced loose crossover dimer formation and the membrane-embedded helix, respectively. These results provide insights into ATL-mediated homotypic membrane fusion and the pathological mechanisms of related disease.
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Proteínas de Drosophila , Humanos , Proteínas de Drosophila/metabolismo , Fusión de Membrana/fisiología , GTP Fosfohidrolasas/metabolismo , Hidrólisis , Guanosina Trifosfato/metabolismoRESUMEN
Background: Only a few studies have focused on the association between Schistosoma japonicum and human malignancy. The aim of this study was to update the prevalence rate, mortality, and 5-year overall survival of S. japonicum patients with human malignancy. Methods: From January 20, 2018, to January 31, 2021, 5,866 inpatients were included in the study. A total of 656 S. japonicum patients with malignancy were identified. Cases were stratified by gender and age groups. The cancer sites, prevalence rate, mortality, and 5-year overall survival of the patients were reported. The S. japonicum patients with malignancy were further divided into a non-digestive system tumor group (n = 309) and a digestive system tumor group (n = 347), including those with cancer in the esophagus, stomach, colon, rectum, liver, gallbladder, bile duct, or pancreas. Chi-squared test and odds ratio with confidence intervals were performed between these two groups. Results: Lung cancer was found the most common malignancy, accounting for 18.6% of all malignancies, followed by colorectal, stomach, liver, and gallbladder cancers. These five leading malignancies accounted for approximately 61.8% of all cases. Colorectal cancer was the leading cause of malignancy death, followed by lung, stomach, gallbladder, and liver cancers. These five leading causes of death accounted for approximately 55.6% of all death cases. Statistical significance was found in the prevalence rate between S. japonicum and non-S. japonicum patients with/without digestive system tumor (p < 0.001). The odds ratio of S. japonicum patients with digestive system tumors was 1.6 (95%CI: 1.4-1.9). Conclusion: S. japonicum contributes to a significant prevalence and mortality in digestive system tumors, including colorectal, stomach, liver, and gallbladder cancers.
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Background: Accurate diagnosis of pneumonia is vital for effective disease management and mortality reduction, but it can be easily confused with other conditions on chest computed tomography (CT) due to an overlap in imaging features. We aimed to develop and validate a deep learning (DL) model based on chest CT for accurate classification of viral pneumonia (VP), bacterial pneumonia (BP), fungal pneumonia (FP), pulmonary tuberculosis (PTB), and no pneumonia (NP) conditions. Methods: In total, 1,776 cases from five hospitals in different regions were retrospectively collected from September 2019 to June 2023. All cases were enrolled according to inclusion and exclusion criteria, and ultimately 1,611 cases were used to develop the DL model with 5-fold cross-validation, with 165 cases being used as the external test set. Five radiologists blindly reviewed the images from the internal and external test sets first without and then with DL model assistance. Precision, recall, F1-score, weighted F1-average, and area under the curve (AUC) were used to evaluate the model performance. Results: The F1-scores of the DL model on the internal and external test sets were, respectively, 0.947 [95% confidence interval (CI): 0.936-0.958] and 0.933 (95% CI: 0.916-0.950) for VP, 0.511 (95% CI: 0.487-0.536) and 0.591 (95% CI: 0.557-0.624) for BP, 0.842 (95% CI: 0.824-0.860) and 0.848 (95% CI: 0.824-0.873) for FP, 0.843 (95% CI: 0.826-0.861) and 0.795 (95% CI: 0.767-0.822) for PTB, and 0.975 (95% CI: 0.968-0.983) and 0.976 (95% CI: 0.965-0.986) for NP, with a weighted F1-average of 0.883 (95% CI: 0.867-0.898) and 0.846 (95% CI: 0.822-0.871), respectively. The model performed well and showed comparable performance in both the internal and external test sets. The F1-score of the DL model was higher than that of radiologists, and with DL model assistance, radiologists achieved a higher F1-score. On the external test set, the F1-score of the DL model (F1-score 0.848; 95% CI: 0.824-0.873) was higher than that of the radiologists (F1-score 0.541; 95% CI: 0.507-0.575) as was its precision for the other three pneumonia conditions (all P values <0.001). With DL model assistance, the F1-score for FP (F1-score 0.541; 95% CI: 0.507-0.575) was higher than that achieved without assistance (F1-score 0.778; 95% CI: 0.750-0.807) as was its precision for the other three pneumonia conditions (all P values <0.001). Conclusions: The DL approach can effectively classify pneumonia and can help improve radiologists' performance, supporting the full integration of DL results into the routine workflow of clinicians.