Neonatal diabetes mellitus （NDM） is a rare monogenic disorder primarily caused by insufficient insulin secretion resulting from mutations in the KCNJ11 and ABCC8 genes. Sulfonylureas， represented by glibenclamide， have become the standard therapy for this type of NDM by precisely closing the mutated ATP-sensitive potassium channels in pancreatic β cells， thereby restoring insulin secretion. Clinical studies confirm that sulfonylureas enable over 90% of patients to successfully transition from insulin to oral treatment， achieving long-term stable glycemic control and improving neurological outcomes to a certain extent. In terms of safety， severe hypoglycemia induced by sulfonylureas is relatively rare and gastrointestinal reactions are mild； moreover， sulfonylureas show good long-term tolerability， and have no adverse effects on child growth and development. In the future， by further refining the full-chain management pathway of “rapid genetic diagnosis-early intervention-specialized dosage forms-long-term follow-up”， the clinical application of sulfonylureas is expected to provide NDM patients with an optimized treatment regimen and maximize their health benefits.

Objective: To investigate the relationship between physical development indicators and the onset and progression of myopia among children and adolescents, so as to provide theoretical support for coordinated vision and physical health management. Methods: A prospective cohort study was conducted. In September 2022, 3 102 students from grade one in primary school to grade three in junior high school (five year primary school and four year junior high school) from six schools in Huantai County, Shandong Province, were selected using multistage cluster random sampling method to participate in an epidemiological survey on myopia, with follow up completed in September 2023. Follow up value minus baseline value( d ) was used to assess changes in physical development and vision indicators. Multivariate Logistic regression analysis was used to examine the relationship between physical development indicators and the incidence of myopia. Generalized linear models were established to analyze the relationship between physical development indicators and changes in d spherical equivalent (SE) and d axial length (AL) . Results: Multivariate Logistic regression analysis showed that, after adjusting for factors such as gender, age, and baseline body mass index, the third ( Q 3)and fourth ( Q 4)quartiles of d height showed increased risks of myopia onset within one year compared to the first quartile( Q 1) ( OR =1.85,95% CI =1.18-2.88; OR =1.74,95% CI =1.09-2.78,both P ＜0.05). Results from the generalized linear model indicated that, after adjusting for confounding factors such as gender, age, and baseline SE, d SE was negatively correlated with d height and d weight in children and adolescents ( β =-0.024, 95% CI =-0.031 to -0.018; β =-0.006, 95% CI =-0.011 to -0.001), d AL was positively correlated with d height and d weight in children and adolescents ( β =0.011, 95% CI =0.008-0.013; β =0.005, 95% CI =0.003-0.007) (all P ＜0.05). Conclusions Physical development indicators in children and adolescents were associated with the onset and progression of myopia. Dynamic monitoring and early intervention of myopia should be strengthened for children and adolescents with rapid height and weight gain to achieve coordinated management of myopia and physical development.

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

Increasing evidence has underscored the significance of post-stroke alterations along gut-brain axis, while its role in pathogenesis and treatment of ischemic stroke (IS) remains largely unexplored. This study aimed to elucidate the therapeutic effects and action targets of Panax notoginseng saponins (PNS) on IS and explore a novel pathogenesis and treatment strategy of IS via profiling the microbial community and metabolic characteristics along gut-brain axis. Our findings revealed for the first time that the therapeutic effect of PNS on IS was microbiota-dependent. Ischemia/reperfusion (I/R) modeling significantly down-regulated Lactobacilli in rats, and PNS markedly recovered Lactobacilli, particularly Lactobacillus reuteri (L.Reu). Metabolomics showed a significant reduction in serum histidine (HIS) in clinical obsolete IS patients and rehabilitation period I/R rats. Meanwhile, the L.Reu colonization in I/R rats exhibited significant neuroprotective activity and greatly increased HIS in serum, gut microbiota, and brain. Moreover, exogenous HIS demonstrated indirect neuroprotective effects through metabolizing to histamine. Notably, vagus nerve severance in I/R rats was performed to investigate HIS's neuroprotective mechanism. The results innovatively revealed that PNS could promote HIS synthesis in gut by enhancing L.Reu proportion, thereby increasing intracerebral HIS through peripheral pathway. Consequently, our data provided novel insights into HIS metabolism mediated by L.Reu in the pathogenesis and treatment of IS.

Advancements in artificial intelligence (AI) and emerging technologies are rapidly expanding the exploration of chemical space, facilitating innovative drug discovery. However, the transformation of novel compounds into safe and effective drugs remains a lengthy, high-risk, and costly process. Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development. Despite this need, no comprehensive tool currently supports systematic evaluation and efficient screening. Here, we present druglikeFilter, a deep learning-based framework designed to assess drug-likeness across four critical dimensions: 1) physicochemical rule evaluated by systematic determination, 2) toxicity alert investigated from multiple perspectives, 3) binding affinity measured by dual-path analysis, and 4) compound synthesizability assessed by retro-route prediction. By enabling automated, multidimensional filtering of compound libraries, druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates, which can be freely accessed at https://idrblab.org/drugfilter/.

This research investigates the regulatory role of the transcription factor PU.1 in type 1 conventional dendritic cells (cDC1) and its therapeutic potential of modulating the nuclear factor kappaB (NF-κB) cells signaling pathway in non-small cell lung cancer (NSCLC). Utilizing single-cell transcriptome sequencing and comprehensive bioinformatics tools, including the CIBERSORT algorithm, we analyzed the immune cell landscape within NSCLC tissues. Our analysis revealed distinct NSCLC subtypes and delineated the developmental trajectories and functional distinctions of cDC1 cells. Key differentially expressed genes (DEGs) and pivotal functional modules within these cells were identified, highlighting PU.1 as a critical mediator underexpressed in NSCLC samples. Functionally, PU.1 demonstrated the induction of the NF-κB pathway, which led to inhibited tumor proliferation and enhanced activation of cDC1, thereby suggesting its role in tumor immune surveillance. In vivo models confirmed the suppressive effect of PU.1 on NSCLC progression, mediated through its influence on cDC1 functionality via the NF-κB pathway. These findings propose PU.1 as a promising target for NSCLC therapeutic strategies, emphasizing the importance of transcriptional regulators in the tumor microenvironment.

Drug development encompasses multiple processes, wherein protein subcellular localization is essential. It promotes target identification, treatment development, and the design of drug delivery systems. In this research, a deep learning framework called LocPro is presented for predicting protein subcellular localization. Specifically, LocPro is unique in (a) combining protein representations from the pre-trained large language model (LLM) ESM2 and the expert-driven tool PROFEAT, (b) implementing a hybrid deep neural network architecture that integrates convolutional neural network (CNN), fully connected (FC) layer, and bidirectional long short-term memory (BiLSTM) blocks, and (c) developing a multi-label framework for predicting protein subcellular localization at multiple granularity levels. Additionally, a dataset was curated and divided using a homology-based strategy for training and validation. Comparative analyses show that LocPro outperforms existing methods in sequence-based multi-label protein subcellular localization prediction. The practical utility of this framework is further demonstrated through case studies on drug target subcellular localization. All in all, LocPro serves as a valuable complement to existing protein localization prediction tools. The web server is freely accessible at https://idrblab.org/LocPro/.

Abstract In recent years, the prevalence of overweight and obesity among children and adolescents has risen rapidly, posing a serious threat to their physical and mental health. To provide scientific, systematic, and standardized weight management guidance for overweight and obese children and adolescents, the study focuses on the core concept of healthy lifestyle intervention, integrates multidisciplinary expert opinions and research findings,and proposes a comprehensive multidisciplinary intervention framework covering scientific exercise intervention, precise nutrition and diet, optimized sleep management, and standardized psychological support. It calls for the establishment of a multi agent collaborative management mechanism led by the government, implemented by families, fostered by schools, initiated by individuals, optimized by communities, reinforced by healthcare, and coordinated by multiple stakeholders. Emphasizing a child and adolescent centered approach, the consensus advocates for comprehensive, multi level, and personalized guidance strategies to promote the internalization and maintenance of a healthy lifestyle. It serves as a reference and provides recommendations for the effective prevention and control of overweight and obesity, and enhancing the health level of children and adolescents.

BACKGROUND:U937 cells can be used as a cell model for studying the biological characteristics,signaling pathways,and therapeutic targets of acute myeloid leukemia.Although it has been reported that long non-coding RNA KIAA0125 is highly expressed in acute myeloid leukemia,its biological function in U937 cells remains unclear,and its mechanism of action in the occurrence and development of acute myeloid leukemia needs to be further clarified. OBJECTIVE:To investigate the expression level of long non-coding RNA KIAA0125 in peripheral blood of patients with acute myeloid leukemia and its effect on the proliferation and apoptosis of U937 cells. METHODS:RNA-sequencing was used to analyze the bone marrow monocyte samples from acute myeloid leukemia patients,and the differentially expressed gene long non-coding RNA KIAA0125 was screened.The expression of long non-coding RNA KIAA0125 in peripheral blood of patients with acute myeloid leukemia was detected by qRT-PCR.The relationship between long non-coding RNA KIAA0125 mRNA expression and prognosis in bone marrow cells of 173 acute myeloid leukemia patients and 70 healthy people was statistically analyzed by GEPIA database.Subsequently,recombinant lentivirus technology and CRISPR/Cas9-SAM technology were used to construct U937 cell lines with knockdown/overexpression of long non-coding RNA KIAA0125.qRT-PCR was used to detect the knockdown/overexpression efficiency of long non-coding RNA KIAA0125.Next,CCK-8 assay,flow cytometry,and western blot assay were used to detect the effects of knockdown/overexpression of long non-coding RNA KIAA0125 on the proliferation and apoptosis of U937 cells.Finally,western blot assay was used to detect the effect of knockdown/overexpressed long non-coding RNA KIAA0125 on Wnt/β-catenin signaling pathway-related proteins. RESULTS AND CONCLUSION:(1)The results of qRT-PCR showed that long non-coding RNA KIAA0125 was highly expressed in peripheral blood of acute myeloid leukemia patients.The results of GEPIA database showed that long non-coding RNA KIAA0125 was highly expressed in bone marrow cells of acute myeloid leukemia patients,and the high expression group had worse overall survival.(2)The knockdown efficiency of long non-coding RNA KIAA0125 in knockdown group was 70%,and the U937 cells that stably down-regulated long non-coding RNA KIAA0125 expression were successfully constructed.The expression of long non-coding RNA KIAA0125 in overexpression group was four times that of vector group,and stable U937 cells were successfully constructed.(3)Knockdown of long non-coding RNA KIAA0125 inhibited the proliferation of U937 cells and promoted their apoptosis.Overexpression of long non-coding RNA KIAA0125 promoted the proliferation of U937 cells but had no significant effect on the apoptosis of U937 cells.(4)Knockdown of long non-coding RNA KIAA0125 inhibited the activity of Wnt/β-catenin signaling pathway,while overexpression of long non-coding RNA KIAA0125 activated Wnt/β-catenin signaling pathway.These results confirm that long non-coding RNA KIAA0125 is highly expressed in acute myeloid leukemia peripheral blood.Long non-coding RNA KIAA0125 may affect the proliferation and apoptosis of U937 cells by regulating the Wnt/β-catenin signaling pathway,and may be a potential prognostic marker for acute myeloid leukemia.

To evaluate the diagnostic performance of a three-gene (GBP5, DUSP3, and TBP) tuberculosis (TB) score in bacteriologically-negative pulmonary tuberculosis, and to develop and validate a discriminative diagnostic model by integrating inflammatory cytokines (IL-2, IL-5, IL-17, and IFN-γ). A prospective cohort study was conducted, a total of 238 patients admitted to the Affiliated Infectious Disease Hospital of Soochow University from May 2023 to May 2024 were enrolled, including 119 pathogen-negative pulmonary tuberculosis patients and 119 patients with other pulmonary diseases (OPD). The GeneXpert MTB-HR kit was used to detect the three-gene TB scores from residual blood routine samples. The diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis. Concurrent data on 12 inflammatory cytokines were collected from patients. Potential biomarkers were screened using univariate analysis and multivariate logistic regression, and selected features were incorporated into the construction of four machine learning models: logistic regression, support vector machine (SVM), K-nearest neighbors (KNN), and adaptive boosting (AdaBoost). The samples were randomly split into a training set (85%) and a test set (15%). The models were trained on the training set, and their diagnostic performance was validated using the test set. The predictive ability of each model was evaluated based on ROC curve parameters. The results showed that the three-gene TB score alone yielded an AUC of 0.539 (sensitivity: 50.94%, specificity: 60.50%) in distinguishing pathogen-negative pulmonary tuberculosis from OPD. Four non-col-linear inflammatory factors (IL-2, IL-5, IL-17, and IFN-γ) were selected and combined with the three-gene TB score to construct machine learning models. The AdaBoost model demonstrated the best performance, achieving an AUC of 0.893 (sensitivity: 85.4%, specificity: 73.0%) in the training set and an AUC of 0.873 (sensitivity: 88.2%, specificity: 72.2%) in the test set. In conclusion,the AdaBoost diagnostic model integrating the three-gene TB score with inflammatory factors (IL-2, IL-5, IL-17, and IFN-γ) exhibits superior discriminating performance for pathogen-negative pulmonary tuberculosis compared to OPD, significantly outperforming the three-gene TB score alone.