ObjectiveTo investigate the role and mechanism of Lck/Yes-related novel protein tyrosine kinase （Lyn） on lipopolysaccharide （LPS）-induced M1-type polarization of macrophage. MethodsThe LentiCRISPR-V2 plasmid was digested with the restriction endonuclease BSMBI-V2， and the digested DNA fragments were recovered. The digested plasmid was ligated with Lyn-sgRNA using T4 ligase to generate the Lenti-Lyn-gRNA lentivirus. THP-1 cells were infected with the Lenti-Lyn-gRNA lentivirus to obtain a stable cell line with Lyn knockout， and a monoclonal THP-1 cell line with complete Lyn knockout （Lyn^⁻/⁻） was established subsequently. Wild-type Lyn （Lyn^WT） and Lyn^⁻/⁻ THP-1 cells were induced with 100 ng/mL phorbol myristate acetate （PMA） for 48 h to differentiate into M0 macrophages， which were further polarized into M1 macrophages by stimulation with 100 ng/mL LPS for 24 h. Quantitative real-time polymerase chain reaction （qPCR） was performed to detect the expression of M0 macrophage markers， including integrin αM （CD11b）， macrophage antigen （CD68）， and monocyte differentiation antigen （CD14）. The expression of Lyn in M1 macrophages differentiated from wild-type THP-1 cells （Lyn^WT-M1） was measured by qPCR， and the ratio of phosphorylated Lyn to total Lyn （P-Lyn/Lyn） in Lyn^WT-M1 cells was determined by Western blot. In M1 macrophages differentiated from Lyn-knockout THP-1 cells （Lyn^⁻/⁻-M1）， qPCR was used to detect the mRNA expression of inducible nitric oxide synthase （iNOS）， interleukin-6 （IL-6）， and chemokine （C-X-C motif） ligand 10 （CXCL-10）. Western blot was conducted to assess the protein expression of iNOS， as well as the protein levels of molecules related to the Janus kinase 1 （JAK1）-signal transducer and activator of transcription 1 （STAT1）signaling pathway， including JAK1， phosphorylated JAK1 （P-JAK1）， STAT1， and phosphorylated STAT1 （P-STAT1）. Additionally， the expression of the M1 macrophage marker cluster of differentiation 80 （CD80） was analyzed by flow cytometry. ResultsThe Lyn^-/- monoclonal cell line was successfully constructed. The expression of CD11b was significantly elevated in Lyn^-/- M0 macrophages， and the differentiation of M1 macrophages was successful. Knockdown of Lyn inhibited mRNA expression of iNOS， IL⁃6， CXCL⁃10， protein expression of iNOS and CD80 expression in M1 macrophages （P<0.05）. Western blot assay showed that Lyn knockdown inhibited protein expression of JAK1 and P-STAT1 （P<0.01）. ConclusionAfter CRISPR/Cas9-mediated Lyn knockout， the expression levels of JAK1 and P-STAT1， the key molecules in the JAK/STAT signaling pathway of M1 macrophages， are significantly downregulated； concomitantly， the expression of M1 macrophage-specific secretory factors （iNOS， IL⁃6， CXCL⁃10 mRNA） and CD80 is also downregulated， which may be achieved via targeted regulation of the JAK1/P-STAT1-mediated JAK/STAT signaling pathway.

OBJECTIVE To formulate the Hazardous Drug List in China， and provide a scientific basis for standardizing the management of hazardous drugs， preventing and controlling occupational exposure risks in medical institutions at all levels in China. METHODS Under the joint organization of the Intravenous Medication Admixture Management Professional Committee of the Chinese Pharmaceutical Association and the National Medical Quality Control Center for Pharmaceutical Management， based on literature research and international hazardous drug lists and their development procedures， the scope of hazardous drug selection， selection principles， and evidence confirmation criteria were determined through expert panel seminars and expert questionnaire survey method （Delphi method）. Chemical drugs， biological agents， and Chinese patent medicines marketed in China that met the selecti on principles were screened to form the Chinese Expert Consensus on the Hazardous Drug List . RESULTS Five principles for selecting hazardous drugs were established （including protective labeling in package inserts， carcinogenicity， reproductive toxicity， genotoxicity， and organ toxicity at low doses）， along with the corresponding evidence confirmation criteria. The Hazardous Drug List containing 210 drugs was formulated， covering anti-tumor drugs， endocrine system drugs， nervous system drugs， immunomodulators， anti-infective drugs， cardiovascular system drugs， hematological system drugs， urinary system drugs， obstetrics and gynecology drugs， dermatological drugs and other categories. Compared with international hazardous drug lists， 25 newly included hazardous drugs were added， including 15 anti-tumor drugs， 6 Chinese patent medicines and 4 biological agents. In addition， 88 Chinese patent medicines that may have potential occupational exposure risks are listed in the appendix for reference by medical institutions in management. CONCLUSIONS The development of this consensus closely aligns with the actual clinical drug use in China， with a scientific and rigorous methodology， and can serve as a reference for medical institutions at all levels to standardize the management of hazardous drugs and prevent and control occupational exposure risks.

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*

The development of blood purification materials has progressed from cellulose membranes to high-strength polymer membranes, but the blood compatibility of the membranes remains a major challenge for their clinical applications. In this review, blood purification materials were categorized according to the commonly used material surface modification strategies, including surface grafting of anticoagulant groups, surface coating of materials and electrostatic layer-by-layer self-assembly, covalent attachment of superhydrophilic hydrogels, and blending method. Anticoagulant properties such as clotting time and surface hydrophilicity of various blood purification materials were also discussed to further analyze the value and challenges of blood purification materials in clinical practice.