BACKGROUND: Neoadjuvant chemoradiotherapy followed by radical surgery has been a common practice for patients with locally advanced rectal cancer, but the response rate varies among patients. This study aimed to develop a ResNet-Vision Transformer based magnetic resonance imaging (MRI)-endoscopy fusion model to precisely predict treatment response and provide personalized treatment. METHODS: In this multicenter study, 366 eligible patients who had undergone neoadjuvant chemoradiotherapy followed by radical surgery at eight Chinese tertiary hospitals between January 2017 and June 2024 were recruited, with 2928 pretreatment colonic endoscopic images and 366 pelvic MRI images. An MRI-endoscopy fusion model was constructed based on the ResNet backbone and Transformer network using pretreatment MRI and endoscopic images. Treatment response was defined as good response or non-good response based on the tumor regression grade. The Delong test and the Hanley-McNeil test were utilized to compare prediction performance among different models and different subgroups, respectively. The predictive performance of the MRI-endoscopy fusion model was comprehensively validated in the test sets and was further compared to that of the single-modal MRI model and single-modal endoscopy model. RESULTS: The MRI-endoscopy fusion model demonstrated favorable prediction performance. In the internal validation set, the area under the curve (AUC) and accuracy were 0.852 (95% confidence interval [CI]: 0.744-0.940) and 0.737 (95% CI: 0.712-0.844), respectively. Moreover, the AUC and accuracy reached 0.769 (95% CI: 0.678-0.861) and 0.729 (95% CI: 0.628-0.821), respectively, in the external test set. In addition, the MRI-endoscopy fusion model outperformed the single-modal MRI model (AUC: 0.692 [95% CI: 0.609-0.783], accuracy: 0.659 [95% CI: 0.565-0.775]) and the single-modal endoscopy model (AUC: 0.720 [95% CI: 0.617-0.823], accuracy: 0.713 [95% CI: 0.612-0.809]) in the external test set. CONCLUSION The MRI-endoscopy fusion model based on ResNet-Vision Transformer achieved favorable performance in predicting treatment response to neoadjuvant chemoradiotherapy and holds tremendous potential for enabling personalized treatment regimens for locally advanced rectal cancer patients.
Humans ; Rectal Neoplasms/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Middle Aged ; Neoadjuvant Therapy/methods* ; Aged ; Adult ; Chemoradiotherapy/methods* ; Endoscopy/methods* ; Treatment Outcome

The continuous emergence of SARS-CoV-2 variants as well as other potential future coronavirus has challenged the effectiveness of current COVID-19 vaccines. Therefore, there remains a need for alternative antivirals that target processes less susceptible to mutations, such as the formation of six-helix bundle (6-HB) during the viral fusion step of host cell entry. In this study, a novel high-throughput screening (HTS) assay employing a yeast-two-hybrid (Y2H) system was established to identify inhibitors of HR1/HR2 interaction. The compound IMB-9C, which achieved single-digit micromolar inhibition of SARS-CoV-2 and its Omicron variants with low cytotoxicity, was selected. IMB-9C effectively blocks the HR1/HR2 interaction in vitro and inhibits SARS-CoV-2-S-mediated cell-cell fusion. It binds to both HR1 and HR2 through non-covalent interaction and influences the secondary structure of HR1/HR2 complex. In addition, virtual docking and site-mutagenesis results suggest that amino acid residues A930, I931, K933, T941, and L945 are critical for IMB-9C binding to HR1. Collectively, in this study, we have developed a novel screening method for HR1/HR2 interaction inhibitors and identified IMB-9C as a potential antiviral small molecule against COVID-19 and its variants.

Objective To calculate and analyze the research and development(R&D)efficiency,as well as the technological achievements transformation efficiency,of ten"Double First-Class"medical universities and ten medical universities in the accumulative science and technology evaluation metrics over the last five years,in order to make recommendations for improving technological achievements transformation management at these universities.Methods The study used both classic data envelopment analysis and super-effectiveness data envelopment analysis models to assess the effectiveness of the R&D stage and technological achievements transformation stage at the selected medical universities.Furthermore,the Malmquist model was used to measure the changes in the efficiency of the transformation of scientific and technological achievements of the medical universities as a whole.Results Among the 20 medical universities chosen,the output efficiency in the R&D stage was greater than that in the technological achievements transformation stage.Five medical universities were output-effective at the R&D stage,and two medical universities were in the technological achievements transformation stage.The overall efficiency of scientific and technological achievements transformation in medical universities was steadily improving.Conclusion Based on the current situation,medical universities in China should strengthen effective collaboration between industry,academia,and research,establish professional teams for technological achievements transformation,improve the technological achievements transformation management system,improve talent team construction,and increase technological achievements transformation efficiency.

Objective To investigate the value of serum lipoprotein-associated phospholipase A2(Lp-PLA2)for predicting high-risk coronary plaques in elderly males.Methods A retrospective study was conducted on 46 elderly males aged ≥60 years undergoing health check-ups and coro-nary computed tomography angiography in our hospital between May and July 2024.Their general clinical data were collected.Artificial intelligence software was used to analyze coronary calcium scores and plaque characteristics.The participants were divided into a high-risk plaque group(n=15)and a non-high-risk plaque group(n=31).The differences were compared between the two groups.Multivariate logistic regression analysis was used to identify the influencing factors for high-risk coronary plaques.ROC curve was plotted to determine the predictive value of serum Lp-PLA2 for high-risk plaques,and its AUC value was calculated.Results The high-risk plaque group had significantly larger proportions of smoking history and hyperlipidemia,and higher level of homocysteine and Lp-PLA2 than the non-high-risk plaque group(P＜0.05,P＜0.01).Multiva-riate logistic regression analysis indicated that Lp-PLA2 was an independent risk factor for high-risk coronary plaques(HR=1.030,95％CI:1.008-1.053,P＜0.05).ROC curve analysis revealed that the AUC value of Lp-PLA2 in predicting high-risk coronary plaques was 0.833(95％CI:0.694-0.927,P＜0.01),with a sensitivity of 93.3％,a specificity of 71.0％,a positive predictive value of 62.5％,and a negative predictive value of 100％.Conclusion Serum Lp-PLA2 is of signif-icant value in predicting high-risk coronary plaques in elderly men.

Fragility fractures represent the final clinical manifestation of osteoporosis and are influenced by a range of risk factors. This article discusses the findings from two large-scale studies utilizing biobank and genomic data to investigate the relationships among obesity, type 2 diabetes and fracture risk, and to explore their implications for health management. The studies suggest that general obesity(defined by body mass index, BMI), central obesity(defined by waist circumference), and peripheral obesity exert different effects on fracture risk in older adults. Specifically, individuals who are overweight based on BMI have a lower fracture risk compared to those with normal weight, whereas an increased waist circumference is associated with a higher fracture risk. Moreover, genetic research indicates that genetically determined type 2 diabetes is not causally associated with increased fracture risk. In contrast, observational studies have reported a higher fracture risk in patients with type 2 diabetes; however, this association becomes non-significant after adjusting for diabetes-related risk factors. These findings highlight that maintaining a moderately elevated BMI may benefit bone formation in the elderly by providing mechanical loading to stimulate bone formation. Additionally, effective management of type 2 diabetes complications is essential for reducing fracture risk, and a certain degree of obesity may confer a protective effect against fractures in individuals with type 2 diabetes.

Screening carbonyl reductases with the ability to catalyze the reduction of complex carbonyl compounds is of great significance for the biosynthesis of R-tolvaptan(R-TVP). In this study, the target carbonyl reductase in the crude enzyme extract of rabbit liver was separated, purified, and identified by ammonium sulfate precipitation, gel-filtration chromatography, ion exchange chromatography, affinity chromatography, and protein mass spectrometry. With the rabbit liver genome as the template, the gene encoding the carbonyl reductase rlsr5 was amplified by PCR and the recombinant strain was successfully constructed. After RLSR5 was purified by affinity chromatography, its enzymatic properties were characterized. The results indicated that the gene sequence of rlsr5 was 972 bp, encoding a protein with a molecular weight of 40 kDa. RLSR5 was a dimeric protein, and each monomer was composed of a (α/β)₈-barrel structure. RLSR5 could asymmetrically reduce 7-chloro-1-[2-methyl-4-[(2- methylbenzoyl)amino]benzoyl]-5-oxo-2,3,4,5-tetrahydro-1H-1-benzazepine (prochiral ketone, PK) to synthesize R-TVP. The specific activity of the enzyme was 36.64 U/mg, and the optical purity of the product was 99%. This enzyme showcased the optimal performance at pH 6.0 and 30 °C. It was independent of metal ions, with the activity enhanced by Mn²⁺. This study lays a foundation for the biosynthesis of tolvaptan of optical grade.
Animals ; Rabbits ; Alcohol Oxidoreductases/biosynthesis* ; Recombinant Proteins/metabolism* ; Escherichia coli/metabolism* ; Liver/enzymology*

Glaucoma, a group of diseases characterized by progressive optic nerve degeneration, is the world's first irreversible blinding eye disease.There is increasing evidence that the pathogenesis of glaucomatous neurodegeneration and neurodegenerative diseases of the central nervous system share many similarities.Epidemiologic studies have shown that there is a close relationship between obesity, metabolic dysfunction and neurodegeneration.Changes in serum levels of leptin and ghrelin, two major metabolic factors, are important links in the pathogenesis of glaucomatous retinal ganglion cells.Leptin resistance and ghrelin resistance in physiological states support that obesity is an independent risk factor for the pathogenesis of glaucoma.This review explores the protective effects of leptin and ghrelin on retinal ganglion cells and the optic nerve and considers their potential role in the prevention and treatment of glaucoma.

Objective To explore the prediction effect of communicative vocalization on expressive vocabulary in children with au-tism spectrum disorder(ASD).Methods From February,2021 to February,2022,40 children with ASD whose expressive vocabularies contained fewer than 20 words were recruited at East China Normal University.Communicative vocalization was assessed using a semi-structured play-based interaction at baseline.Twelve months later,expressive vocabulary was measured with the Putonghua Communicative Development Inventory.Results Communicative canonical syllable vocalization significantly and positively predicted expressive vocabulary in children with ASD(B=0.939,β=0.586,t=4.655,P<0.001).Conclusion Communicative canonical syllable vocalization in children with ASD may predict subsequent development in expressive vocabulary.Clinical interventions should place greater emphasis on fostering communicative canon-ical syllable vocalization in ASD.

Objective:To assess the fall risk of hospitalized patients with cardiovascular diseases, analyze the related influencing factors, and construct a prediction model based on machine learning technology, so as to provide a basis for the fall management of hospitalized patients with cardiovascular diseases.Methods:This study was a retrospective cohort study. A total of 450 patients admitted to the Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University from June 2017 to June 2024 were selected as the research objects by convenience sampling method. By reviewing electronic medical records, trained nurses extracted the patients' general information and Activities of Daily Living Scale (ADL) scores during hospitalization. Lasso regression was used to screen risk factors, and machine learning libraries were used to construct support vector machine (SVM), decision tree, XGBoost, and neural network models. Bootstrap resampling method and area under the curve (AUC) were used to verify the model performance.Results:Among the 450 patients, there were 261 males and 189 females, with a mean age of (66.0 ± 8.4) years. Among them, 90 patients fell during hospitalization and 360 patients did not fall. The results of Lasso regression showed that ADL score ≤60 points, use of hypnotics, hypokalemia, nighttime toilet visits≥2 times, use of antihypertensive drugs, no caregiver, and history of atrial fibrillation were all risk factors for falls in hospitalized patients with cardiovascular diseases (regression coefficients ranging from 0.61 to 1.20, all P<0.01). Among the machine learning models, XGBoost had the best comprehensive performance (AUC=0.98), which was better than decision tree (AUC=0.66), SVM (AUC=0.95), and neural network (AUC=0.87). Conclusions:The fall risk of hospitalized patients with cardiovascular diseases is jointly affected by physiological, medication and behavioral factors, and the XGBoost model can effectively identify high-risk groups. In actual clinical work, nursing strategies can be optimized in combination with risk factors, and the application of intelligent fall prediction and assessment tools can be promoted.

Glaucoma, a group of diseases characterized by progressive optic nerve degeneration, is the world's first irreversible blinding eye disease.There is increasing evidence that the pathogenesis of glaucomatous neurodegeneration and neurodegenerative diseases of the central nervous system share many similarities.Epidemiologic studies have shown that there is a close relationship between obesity, metabolic dysfunction and neurodegeneration.Changes in serum levels of leptin and ghrelin, two major metabolic factors, are important links in the pathogenesis of glaucomatous retinal ganglion cells.Leptin resistance and ghrelin resistance in physiological states support that obesity is an independent risk factor for the pathogenesis of glaucoma.This review explores the protective effects of leptin and ghrelin on retinal ganglion cells and the optic nerve and considers their potential role in the prevention and treatment of glaucoma.