This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

Oral squamous cell carcinoma (OSCC) is the most common head and neck malignancy worldwide, accounting for more than 90% of all oral cancers, and is characterized by high invasiveness and poor long-term prognosis. Its etiology is multifactorial, involving tobacco use, alcohol consumption, and human papillomavirus (HPV) infection. Oral leukoplakia and erythroplakia are the main precancerous lesions lesions, with oral leukoplakia being the most common. Both OSCC and premalignant lesions are closely associated with aberrant activation of multiple signaling pathways. Post-translational modifications (such as ubiquitination and deubiquitination) play key roles in regulating these pathways by controlling protein stability and activity. Growing evidence indicates that dysregulated ubiquitination/deubiquitination can mediate OSCC initiation and progression via aberrant activation of signaling pathways. The ubiquitination/deubiquitination process mainly involves E3 ligases (E3s) that catalyze substrate ubiquitination, deubiquitinating enzymes (DUBs) that remove ubiquitin chains, and the 26S proteasome complex that degrades ubiquitinated substrates. Abnormal expression or mutation of E3s and DUBs can lead to altered stability of critical tumor-related proteins, thereby driving OSCC initiation and progression. Therefore, understanding the aberrantly activated signaling pathways in OSCC and the ubiquitination/deubiquitination mechanisms within these pathways will help elucidate the molecular mechanisms and improve OSCC treatment by targeting relevant components. Here, we summarize four aberrantly activated signaling pathways in OSCC―the PI3K/AKT/mTOR pathway, Wnt/β-catenin pathway, Hippo pathway, and canonical NF-κB pathway―and systematically review the regulatory mechanisms of ubiquitination/deubiquitination within these pathways, along with potential drug targets. PI3K/AKT/mTOR pathway is aberrantly activated in approximately 70% of OSCC cases. It is modulated by E3s (e.g., FBXW7 and NEDD4) and DUBs (e.g., USP7 and USP10): FBXW7 and USP10 inhibit signaling, while NEDD4 and USP7 potentiate it. Aberrant activation of the Wnt/β‑catenin pathway leads to β‑catenin nuclear translocation and induction of cell proliferation. This pathway is modulated by E3s (e.g., c-Cbl and RNF43) and DUBs (e.g., USP9X and USP20): c-Cbl and RNF43 inhibit signaling, while USP9X and USP20 potentiate it. Hippo pathway inactivation permits YAP/TAZ to enter the nucleus and promotes cancer cell metastasis. This pathway is modulated by E3s (e.g., CRL4^DCAF1 and SIAH2) and DUBs (e.g., USP1 and USP21): CRL4^DCAF1 and SIAH2 inhibit signaling, while USP1 and USP21 potentiate it. Persistent activation of the canonical NF-κB pathway is associated with an inflammatory microenvironment and chemotherapy resistance. This pathway is modulated by E3s (e.g., TRAF6 and LUBAC) and DUBs (e.g., A20 and CYLD): A20 and CYLD inhibit signaling, while TRAF6 and LUBAC potentiate it. Targeting these E3s and DUBs provides directions for OSCC drug research. Small-molecule inhibitors such as YCH2823 (a USP7 inhibitor), GSK2643943A (a USP20 inhibitor), and HOIPIN-8 (a LUBAC inhibitor) have shown promising antitumor activity in preclinical models; PROTAC molecules, by binding to surface sites of target proteins and recruiting E3s, achieve targeted ubiquitination and degradation of proteins insensitive to small-molecule inhibitors, for example, PU7-1-mediated USP7 degradation, offering new strategies to overcome traditional drug limitations. Currently, NX-1607 (a Cbl-b inhibitor) has entered phase I clinical trials, with preliminary results confirming its safety and antitumor activity. Future research on aberrant E3s and DUBs in OSCC and the development of highly specific inhibitors will be of great significance for OSCC precision therapy.

In this study,a sensitive lateral flow immunoassay(LFIA)platform based on carbon dots-mesoporous silica nanocomposite(CD-MSNs)fluorescent probes was constructed for high-performance detection of inflammatory marker interleukin-6(IL-6).Green fluorescent carbon dots(CDs)were prepared by hydrothermal method with 3,9-perylenic acid and 3-aminopropyltriethoxysilane(APTES)as raw materials,and highly fluorescent CD-MSNs composites were then constructed by encapsulating the prepared CDs in mesoporous silica nanoparticles(MSNs).Fluorescent probes were prepared by covalent coupling of CD-MSNs with IL-6 antibody.Fluorescent immunochromatographic test strips were constructed by spraying IL-6 capture antibody and goat anti-mouse IgG on nitrocellulose membrane as detection line(T-line)and quality control line(C-line),respectively.The fluorescence immunoassay analyzer was used to quantitatively detect the fluorescence intensity of T-line,and the experimental results showed that the LFIA platform based on this probe had a good linear relationship in IL-6 concentration range of 102-106 pg/mL,and the detection limit was 64 pg/mL,which was two orders of magnitude more sensitive than that of the traditional colloidal gold test strips.This method effectively solved the issue of insufficient sensitivity of traditional LFIA technique,and provided a rapid and highly sensitive detection method for early diagnosis of inflammatory diseases.

Objective To compare the application effects of plankton multiplex polymerase chain reac-tion-capillary electrophoresis(PCR-CE),SYBR Green Ⅰ real-time quantitative PCR(qPCR)and microwave digestion-vacuum filtration-automated scanning electron microscopy(MD-VF-Auto SEM)in the diagnosis of drowning.Methods Lung,liver and kidney tissues from 212 drowned corpses and 30 non-drowned corpses were examined respectively by the three drowning-related plankton testing methods,and the detection rates of plankton in each tissue by three methods were compared.Results In drowned corpses,the total detection rates of PCR-CE,qPCR,and MD-VF-Auto SEM were 93.9%,96.2%,and 95.3%,respectively,with no statistically significant difference(P>0.05).The detection rate of lung tissue by MD-VF-Auto SEM(100%)was higher than those of PCR-CE and qPCR(P<0.05),and there was no significant difference in the detection rates of the three methods in liver or kidney tissues(P>0.05).In non-drowning corpses,a small number of diatoms(less than 10 cells/10 g)were detected by MD-VF-Auto SEM method,only in liver and kidney tissues,while the other two methods yielded negative results for all tissues.Conclusion All three methods have good efficacy in the examination of drowned corpses.The MD-VF-Auto SEM method directly observes diatom morpho-logical characteristics through scanning electron microscopy,and the qualitative and quantitative analy-ses are intuitive and accurate.It has great advantages in the examination of difficult degradation samples.The PCR-CE method and qPCR method have a low sample demand(0.5 g),are easy to operate and have short detection time(4-7 h).They are easy to be applied in the grassroots depart-ments and are suitable for the rapid determination of drowned corpses in routin cases.The combina-tion of the two DNA methods with the MD-VF-Auto SEM method can increase the detection rate of plankton,ensuring the reliability of examination results.This combined use is of significant importance in the application of drowning diagnosis.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Aim To infer novel therapeutic and phar-macological targets related to lung cancer treatment through multiomics approaches,so as to provide new directions for developing more personalized and effec-tive treatment strategies.Methods Genome-wide as-sociation study(GWAS)data analysis,pan-cancer,single-cell,transcriptomics,and protein-protein interac-tion analysis were employed in this study.Results We analyzed biomarkers and therapeutic targets associ-ated with lung cancer.The study identified key bio-markers closely related to lung cancer progression and explored the interrelationships between these biomark-ers and viral infections.According to KEGG pathway annotation,the number of genes related to metabolic processes increased significantly.In particular,metab-olites such as alanine and isoleucine emerged as pivotal factors in therapeutic interventions.The IgD+CD24+and IgD+CD24-B cell subsets were identified as cen-tral elements in immune evasion and treatment re-sponse.Concurrently,the Lachnospiraceae and Prevo-tella were shown to modulate host immune responses and the tumor microenvironment by regulating short-chain fatty acid levels,thereby opening novel avenues for cancer research.Conclusions Through mul-tiomics analysis combined with transcriptomics and pro-teomics analysis,we identify several potential therapeu-tic targets for lung cancer,providing key insights for developing novel treatment strategies.

OBJECTIVES: To investigate the relationship between the polygenic risks for various psychiatric disorders and clinical and neuropsychological characteristics in children with attention-deficit/hyperactivity disorder (ADHD). METHODS: Using a cross-sectional design, 285 children with ADHD and 107 healthy controls were assessed using the Child Behavior Checklist, the Behavior Rating Inventory of Executive Function for parents, the Wechsler Intelligence Scale for Children, Fourth Edition, and the Cambridge Neuropsychological Test Automated Battery. Blood samples were collected for genetic data. Polygenic risk scores (PRSs) for various psychiatric disorders were calculated using the PRSice-2 software. RESULTS: Compared with the healthy controls, the children with ADHD displayed significantly higher PRSs for ADHD, major depressive disorder, anxiety disorder, and obsessive-compulsive disorder (P<0.05). In terms of daily-life executive function, ADHD-related PRS was significantly correlated with the working memory factor; panic disorder-related PRS was significantly correlated with the initiation factor; bipolar disorder-related PRS was significantly correlated with the shift factor; schizophrenia-related PRS was significantly correlated with the inhibition, emotional control, initiation, working memory, planning, organization, and monitoring factors (P<0.05). The PRS related to anxiety disorders was negatively correlated with total IQ and processing speed index (P<0.05). The PRS related to obsessive-compulsive disorder was negatively correlated with the processing speed index and positively correlated with the stop-signal reaction time index of the stop-signal task (P<0.05). CONCLUSIONS PRSs for various psychiatric disorders are closely correlated with the behavioral and cognitive characteristics in children with ADHD, which provides more insights into the heterogeneity of ADHD.
Humans ; Attention Deficit Disorder with Hyperactivity/genetics* ; Child ; Male ; Female ; Cross-Sectional Studies ; Neuropsychological Tests ; Multifactorial Inheritance ; Adolescent ; Mental Disorders/etiology* ; Executive Function ; Genetic Risk Score

OBJECTIVES: To investigate the causal relationship between Helicobacter pylori (Hp) infection and immune thrombocytopenia (ITP) using Mendelian randomization (MR), as well as the association between Hp infection and chronic ITP (cITP) through a clinical study. METHODS: The datasets from genome-wide association studies were used to select the single nucleotide polymorphism loci significantly associated with Hp infection as genetic instrumental variables. The MR analysis model was used to investigate the causal relationship between ITP and Hp infection. A retrospective analysis was conducted on the medical data of 316 children with newly diagnosed ITP at the First Affiliated Hospital of Xinjiang Medical University from January 2020 to December 2023. The children were followed up for 1 year, and a multivariate logistic regression analysis was used to investigate the risk factors for cITP. RESULTS: The inverse variance weighted analysis revealed that Hp infection was significantly associated with an increased risk of ITP (OR=1.280, 95%CI: 1.098-1.492, P=0.002). There was no heterogeneity or pleiotropy in this MR study (P>0.05), and the model was stable. The "leave-one-out" sensitivity analysis verified the reliability of the results. The multivariate logistic regression analysis demonstrated that Hp infection was an independent risk factor for progression to cITP (OR=7.916, 95%CI: 3.327-18.832, P<0.001). CONCLUSIONS Hp infection is a risk factor for the onset of ITP and is an independent risk factor for cITP in children.
Humans ; Helicobacter Infections/complications* ; Purpura, Thrombocytopenic, Idiopathic/etiology* ; Child ; Male ; Female ; Helicobacter pylori ; Prognosis ; Child, Preschool ; Logistic Models ; Retrospective Studies ; Risk Factors ; Polymorphism, Single Nucleotide ; Adolescent ; Infant