Objective: To analyze respiratory syncytial virus(RSV) outbreaks surveillance results and the epidemiological characteristics in kindergarten and school in Shenzhen during 2017-2023 , so as to provide a scientific reference for control and prevention of RSV. Methods: Epidemiological data and surveillance results of RSV outbreaks in kindergarten and school from 2017 to 2023 were collected for descriptive analyses. Results: A total of 31 RSV outbreaks were identified in kindergarten and school in 2017-2023 in Shenzhen, 346 cases were reported, the average incidence rate was 22.02%. The most annual RSV outbreaks were reported in 2020 with 14 outbreaks, followed by 8 outbreaks in 2023. A total of 64.52% of RSV outbreaks were identified in kindergarten with rest occurring in primary school or middle school. The greatest monthly count of outbreak was 18 (58.06%) in September, followed by 3 outbreaks (9.68%) in March and October. A total of 244 swab samples were collected, 169 samples were positive for respiratory viruses, the positive rate was 69.26%, 121 samples were positive for RSV,from 31 respiratory syncytical virus outbreaks 57 and samples were positive for other respiratory viruses(9 samples were positive for two respiratory viruses). A toral of 14(45.16%) outbreaks are caused by RSV alone, 17 outbreaks (54.84%) were caused by RSV and other respiratory viruses. Conclusions Most RSV outbreaks in kindergarten and school are reported after 2020 in Shenzhen, most RSV outbreaks occur in kindergarten, peak seasons of RSV outbreaks are autumn and spring.

BACKGROUND: Chronic kidney disease (CKD) is associated with common pathophysiological processes, such as inflammation and fibrosis, in both the heart and the kidney. However, the underlying molecular mechanisms that drive these processes are not yet fully understood. Therefore, this study focused on the molecular mechanism of heart and kidney injury in CKD. METHODS: We generated an microRNA (miR)-26a knockout (KO) mouse model to investigate the role of miR-26a in angiotensin (Ang)-II-induced cardiac and renal injury. We performed Ang-II modeling in wild type (WT) mice and miR-26a KO mice, with six mice in each group. In addition, Ang-II-treated AC16 cells and HK2 cells were used as in vitro models of cardiac and renal injury in the context of CKD. Histological staining, immunohistochemistry, quantitative real-time polymerase chain reaction (PCR), and Western blotting were applied to study the regulation of miR-26a on Ang-II-induced cardiac and renal injury. Immunofluorescence reporter assays were used to detect downstream genes of miR-26a, and immunoprecipitation was employed to identify the interacting protein of LIM and senescent cell antigen-like domain 1 (LIMS1). We also used an adeno-associated virus (AAV) to supplement LIMS1 and explored the specific regulatory mechanism of miR-26a on Ang-II-induced cardiac and renal injury. Dunnett's multiple comparison and t -test were used to analyze the data. RESULTS: Compared with the control mice, miR-26a expression was significantly downregulated in both the kidney and the heart after Ang-II infusion. Our study identified LIMS1 as a novel target gene of miR-26a in both heart and kidney tissues. Downregulation of miR-26a activated the LIMS1/integrin-linked kinase (ILK) signaling pathway in the heart and kidney, which represents a common molecular mechanism underlying inflammation and fibrosis in heart and kidney tissues during CKD. Furthermore, knockout of miR-26a worsened inflammation and fibrosis in the heart and kidney by inhibiting the LIMS1/ILK signaling pathway; on the contrary, supplementation with exogenous miR-26a reversed all these changes. CONCLUSIONS Our findings suggest that miR-26a could be a promising therapeutic target for the treatment of cardiorenal injury in CKD. This is attributed to its ability to regulate the LIMS1/ILK signaling pathway, which represents a common molecular mechanism in both heart and kidney tissues.
Animals ; MicroRNAs/metabolism* ; Angiotensin II/toxicity* ; Mice ; Renal Insufficiency, Chronic/chemically induced* ; Mice, Knockout ; Disease Models, Animal ; Male ; Signal Transduction/genetics* ; LIM Domain Proteins/genetics* ; Mice, Inbred C57BL ; Cell Line ; Humans

Neoplasms characterized by the expression of markers of neuroendocrine differentiation in neoplastic cells are defined as neuroendocrine neoplasms. A case of neuroendocrine carcinomas (NECs) with a small amount of papillary adenocarcinoma and significantly vacuolar nucleus at the esophagogastric junction was reported in this article. A 77-year-old male had dysphagia for one week. Endoscopy revealed early-stage esophagogastric junction carcinoma, and biopsy was diagnosed as poorly differentiated carcinoma. Endoscopic submucosal dissection was performed. Histologically, the papillary adenocarcinoma progresses from typically branching papillary structures (well-differentiated) to hyperplasia of the lining epithelium of the papilla to form a cribriform structure (moderately differentiated), to solid area lacking papillary structures (poorly differentiated). There was a continuous process, and during this process, the vacuoles in the nuclei of tumor cells showed progressive changes from mild to obvious and finally to significant vacuoles. The tumor was mainly composed of solid areas (about 95%), with single cell, large cell, round or oval to irregular nuclei, and significantly vacuolar nuclei, nuclei with larger vacuoles appeared in a loop, a few thin weakly basophilic or weakly eosinophilic fine particles could be seen in the vacuoles, and the vacuoles had rough edges. The nucleus chromatin at the outer edge of the vacuoles was fine particles, and mitosis was common (20-30/mm²), atypical mitosis could be seen, and nucleoli could be seen easily, the cytoplasm was weakly eosinophilic, and the boundaries of cells were unclear. The cells were arranged in a nested, trabecular, or diffuse sheet shape, with some arranged in a glandular tube shape. Tumor thrombus was found in the vein of submucosa; the interstitial tissue rich in capillaries within the tumor was accompanied by a large number of neutrophil infiltration. Immunohistochemical staining showed that the solid area of the tumor was positive for synaptophysin (Syn) and chromogranin A (CgA), while papillary adenocarcinoma was negative. Mucin 5AC (MUC5AC) was diffusely positive in papillary adenocarcinoma, while the proportion of positive cells in the solid area of the tumor was about 10% to 15%. In a word, this case showed the extreme situation of the vacuolar nuclear characteristics of NECs, extremely rare, in a sense, this case expanded the boundary of the morphological spectrum of NECs. Understanding the extreme vacuolar features of this nucleus is helpful to make a correct pathological diagnosis.
Humans ; Male ; Esophagogastric Junction/pathology* ; Aged ; Carcinoma, Neuroendocrine/pathology* ; Vacuoles/pathology* ; Esophageal Neoplasms/pathology* ; Cell Nucleus/pathology* ; Adenocarcinoma, Papillary/pathology* ; Stomach Neoplasms/pathology*

Metformin has been demonstrated to attenuate hyperglycaemia by modulating the gut microbiota. However, the mechanisms through which the microbiome mediates metformin monotherapy failure (MMF) are unclear. Herein, in a prospective clinical cohort study of newly diagnosed type 2 diabetes mellitus (T2DM) patients treated with metformin monotherapy, metagenomic sequencing of faecal samples revealed that Phocaeicola vulgatus abundance was approximately 12 times higher in nonresponders than in responders. P. vulgatus rapidly hydrolysed taurine-conjugated bile acids, leading to ceramide accumulation and reversing the improvements in glucose intolerance conferred by metformin in high-fat diet-fed mice. Interestingly, C22:0 ceramide bound to mitochondrial fission factor to induce mitochondrial fragmentation and impair hepatic oxidative phosphorylation in P. vulgatus-colonized hyperglycaemic mice, which could be exacerbated by metformin. This work suggests that metformin may be unsuitable for P. vulgatus-rich T2DM patients and that clinicians should be aware of metformin toxicity to mitochondria. Suppressing P. vulgatus growth with cefaclor or improving mitochondrial function using adenosylcobalamin may represent simple, safe, effective therapeutic strategies for addressing MMF.

Early correction of childhood malocclusion is timely managing morphological, structural, and functional abnormalities at different dentomaxillofacial developmental stages. The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion. This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence, aiming to provide general guidance on appropriate imaging examination selection, comprehensive and accurate imaging assessment for early orthodontic treatment patients.
Humans ; Malocclusion/diagnostic imaging* ; Child ; Consensus

Negative logarithm of the acid dissociation constant (pK _a) significantly influences the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of molecules and is a crucial indicator in drug research. Given the rapid and accurate characteristics of computational methods, their role in predicting drug properties is increasingly important. Although many pK _a prediction models currently exist, they often focus on enhancing model precision while neglecting interpretability. In this study, we present GraFpK _a, a pK _a prediction model using graph neural networks (GNNs) and molecular fingerprints. The results show that our acidic and basic models achieved mean absolute errors (MAEs) of 0.621 and 0.402, respectively, on the test set, demonstrating good predictive performance. Notably, to improve interpretability, GraFpK _a also incorporates Integrated Gradients (IGs), providing a clearer visual description of the atoms significantly affecting the pK _a values. The high reliability and interpretability of GraFpK _a ensure accurate pK _a predictions while also facilitating a deeper understanding of the relationship between molecular structure and pK _a values, making it a valuable tool in the field of pK _a prediction.

Activity cliffs (ACs) are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target. ACs offer crucial insights that aid medicinal chemists in optimizing molecular structures. Nonetheless, they also form a major source of prediction error in structure-activity relationship (SAR) models. To date, several studies have demonstrated that deep neural networks based on molecular images or graphs might need to be improved further in predicting the potency of ACs. In this paper, we integrated the triplet loss in face recognition with pre-training strategy to develop a prediction model ACtriplet, tailored for ACs. Through extensive comparison with multiple baseline models on 30 benchmark datasets, the results showed that ACtriplet was significantly better than those deep learning (DL) models without pre-training. In addition, we explored the effect of pre-training on data representation. Finally, the case study demonstrated that our model's interpretability module could explain the prediction results reasonably. In the dilemma that the amount of data could not be increased rapidly, this innovative framework would better make use of the existing data, which would propel the potential of DL in the early stage of drug discovery and optimization.

OBJECTIVE: To explore the relationship between the geriatric nutritional risk index (GNRI) and cognitive function. METHODS: A cross-sectional study method was conducted. People aged ≥ 60 years from the National Health and Nutrition Examination Survey (NHANES) databases from 1999 to 2002 and 2011 to 2014 were included as study subjects. The participants were divided into three groups based on their GNRI scores: a medium-high risk group (82 ≤ GNRI < 92), a low risk group (92 ≤ GNRI < 98), and a no-risk group (GNRI ≥ 98). Demographic characteristics (gender, age, race, education), chronic diseases [chronic bronchitis, emphysema, thyroid problems, coronary heart disease, angina pectoris, stroke, hypertension, diabetes mellitus, and depression score on the patient health questionnaire (PHQ-9)], lifestyle habits (history of smoking, hours of sleep), etc., were collected. Cognitive function was assessed using the consortium to establish a registry for Alzheimer's disease word learning subtest (CERAD-WL), animal fluency test (AFT), and digit symbol substitution test (DSST) for the 2011-2014 data, while only the DSST was used for the 1999-2002 data. Differences in the above information among the GNRI cohorts were compared. Factors affecting cognitive function in the population were analyzed using multifactorial Logistic regression. RESULTS: 2 653 participants from 2011 to 2014 and 2 380 participants from 1999 to 2002 were enrolled, with a total of 5 033 participants in the study. There were statistically significant differences in age, stroke, diabetes mellitus, DSST score, AFT score, CERAD score test 1 recall (Cst1), and CERAD score test 2 recall (Cst2) among the GNRI groups. Multifactorial Logistic regression analysis of data from 2011 to 2014 showed that in model 3 (DSST score, age, gender, race, marriage, education, hours of sleep, history of smoking, emphysema, thyroid problems, chronic bronchitis, coronary heart disease, angina pectoris, hypertension, diabetes mellitus, depression score on the PHQ-9, and stroke) adjusted for all covariates, GNRI was a protective factor for DSST [odds ratio (OR) = 1.03, 95% confidence interval (95%CI) was 1.00 to 1.05, P = 0.03]; Logistic regression analyse for 1999 to 2002 and 2011 to 2014 showed a significant association even after adjustment for covariates (OR = 1.02, 95%CI was 1.00 to 1.03, P = 0.02). Subgroup Logistic regression analyses of the total population from 2011 to 2014 showed a significant association between GNRI and DSST scores (OR = 1.02, 95%CI was 1.01 to 1.03, P < 0.001), with significant associations in the age subgroups of 60 to 64 years old, across gender, non-Hispanic Whites and Blacks, by education, and by marital status associations were significant (all P < 0.05). Subgroup Logistic regression analyse of the total populations from 1999 to 2002 and 2011 to 2014 showed a significant association between the GNRI and DSST score (OR = 1.01, 95%CI was 1.01 to 1.02, P < 0.001), but did not show a significant year difference (interaction P = 0.503), and the newly found in the smoking population the association was also more significant (P < 0.01). CONCLUSION The GNRI correlates with the presence of cognitive functions related to processing speed, sustained attention, and executive function, and may be able to serve as an indicator for the assessment or prediction of related cognitive functions.
Humans ; Cross-Sectional Studies ; Aged ; Middle Aged ; Nutrition Surveys ; Cognition ; Female ; Male ; Nutritional Status ; Risk Factors ; Geriatric Assessment

Accurate prediction of drug-target interactions (DTIs) plays a pivotal role in drug discovery, facilitating optimization of lead compounds, drug repurposing and elucidation of drug side effects. However, traditional DTI prediction methods are often limited by incomplete biological data and insufficient representation of protein features. In this study, we proposed KG-CNNDTI, a novel knowledge graph-enhanced framework for DTI prediction, which integrates heterogeneous biological information to improve model generalizability and predictive performance. The proposed model utilized protein embeddings derived from a biomedical knowledge graph via the Node2Vec algorithm, which were further enriched with contextualized sequence representations obtained from ProteinBERT. For compound representation, multiple molecular fingerprint schemes alongside the Uni-Mol pre-trained model were evaluated. The fused representations served as inputs to both classical machine learning models and a convolutional neural network-based predictor. Experimental evaluations across benchmark datasets demonstrated that KG-CNNDTI achieved superior performance compared to state-of-the-art methods, particularly in terms of Precision, Recall, F1-Score and area under the precision-recall curve (AUPR). Ablation analysis highlighted the substantial contribution of knowledge graph-derived features. Moreover, KG-CNNDTI was employed for virtual screening of natural products against Alzheimer's disease, resulting in 40 candidate compounds. 5 were supported by literature evidence, among which 3 were further validated in vitro assays.
Alzheimer Disease/drug therapy* ; Biological Products/therapeutic use* ; Humans ; Neural Networks, Computer ; Machine Learning ; Drug Discovery/methods* ; Algorithms ; Drug Evaluation, Preclinical/methods*

ObjectiveTo investigate the application of endoscopy in obtaining the great saphenous vein （GSV） during coronary artery bypass grafting （CABG） and explore the learning curve， with a particular focus on common challenges encountered during the learning process and their impact on early clinical outcomes. MethodsA retrospective analysis was conducted on clinical data from 83 patients who underwent off-pump CABG with endoscopic GSV harvesting at the First Affiliated Hospital of Zhengzhou University from July 2013 to April 2014. Patients were categorized into four groups based on the chronological order of their hospitalization： Group A （novice group， n=20）， Group B （proficient group， n=20）， Group C （progressive group， n=20）， and Group D （mature group， n=23）. Differences in perioperative and midterm follow-up outcomes among the groups were analyzed to determine the learning curve period. ResultsThe study population had a mean age of （60.22±8.06） years and a mean body weight of （69.77±11.66） kg. Comorbidities included hypertension （24 cases）， diabetes （26 cases）， and subacute cerebral infarction （14 cases）. The novice group exhibited significantly shorter GSV length-to-harvest time ratio relative to the other three groups （P<0.001） and a significantly higher incidence of main vein damage （P=0.006）. However， there was no statistically significant difference in graft patency at the 1-year follow-up. ConclusionThorough and reliable technical training in endoscopic GSV harvesting is essential to minimize vascular injury caused by novice operators. Approximately 20 cases of hands-on experience and a careful self-analysis of procedural challenges are likely required to achieve proficiency in GSV harvesting.