BackgroundLow medication compliance among patients with severe mental disorders increases the disease burden on both the patients' families and the society. Medication adherence is influenced by numerous factors. Traditional methods such as Logistic regression struggle to quantify the importance of these factors. By introducing Extreme Gradient Boosting （XGBoost） combined with Shapley Additive Explanations （SHAP）， enables the quantification of the relative contribution weights of each factor， providing support for identifying the core influencing factors. ObjectiveTo explore the influencing factors of medication adherence among patients with severe mental disorders in Zhuhai， aiming to provide references for optimizing patient management strategies. MethodsExtract the data of patients with severe mental disorders who were registered on the mental health system platform in Zhuhai City from January 1， 2023 to March 31， 2025. A total of 9 329 patients were finally included for analysis. Influencing factors were screened using univariate analysis and multivariate logistic regression analysis， and an XGBoost model combined with the SHAP algorithm was constructed to quantify the importance of each influencing factor. ResultsAmong 9 329 patients， 8 446 demonstrated medication adherence， yielding an adherence rate of 90.53%. Multivariable analysis identified several risk factors significantly associated with medication non-adherence， being unmarried （OR=1.237， 95% CI： 1.019–1.502） or divorced （OR=1.389， 95% CI： 1.038–1.832）， a diagnosis of mental retardation with psychiatric disorders （OR=3.025， 95% CI： 2.402–3.796） or paranoid psychosis （OR=5.117， 95% CI： 3.086–8.299）， a disease duration of 2–4 years （OR=1.355， 95% CI： 1.085–1.696）， 4–6 years （OR=2.143， 95% CI： 1.671–2.747）， or >6 years （OR=1.681， 95% CI： 1.365–2.079）， lack of guardian subsidies （OR=1.412， 95% CI： 1.099–1.801）， absence of a disability certificate （OR=1.900， 95% CI： 1.588–2.282）， not being enrolled in care and support groups （OR=1.384， 95% CI： 1.183–1.617） or community services （OR=1.313， 95% CI： 1.042–1.645）， and not cohabiting with a guardian （OR=1.257， 95% CI： 1.048–1.501）. Conversely， the enrollment in special outpatient disease programs （OR=0.716， 95% CI： 0.609–0.842） and a family history of mental illness （OR=0.713， 95% CI： 0.503–0.982） were identified as protective factors. The XGBoost model exhibited robust predictive performance， with a sensitivity of 0.433， specificity of 0.944， accuracy of 0.891， Area Under the Curve （AUC） of 0.837， and F1 value of 0.449. Feature importance ranking indicated that the top three factors were disease duration， diagnosis， and the acquisition of disability certificates. ConclusionPolicy-based support （acquisition of disability certificates， special outpatient disease enrollment） and clinical disease characteristics （disease duration， diagnosis type） are key factors affecting medication adherence among patients with severe mental disorders in Zhuhai City. ［Funded by Zhuhai Medical Research Project （number， 2220009000281）］

ObjectiveTo investigate the role of the Toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor-κB （NF-κB） signaling pathway in intestinal mucosal barrier damage in ulcerative colitis， as well as the intervention mechanism of Shaoyaotang. MethodsSixty SD rats were allocated into a blank group， a model group， a mesalazine （0.42 g·kg^-1） group， and low-， medium-， and high-dose （11.1， 22.2， 44.4 g·kg^-1， respectively） Shaoyaotang groups. A model of ulcerative colitis was induced by 2，4，6-trinitrobenzenesulfonic acid （TNBS）. After successful modeling， rats were administrated with corresponding agents via gavage for 7 days. Changes in colon length and colon weight were observed. Hematoxylin-eosin staining was performed to examine the pathological changes of the colon， and immunohistochemistry was employed to detect the expression of the inflammatory cytokine interleukin-8 （IL-8）， cyclooxygenase-2 （COX-2）， junction adhesion molecule-1 （JAM-1）， and claudin-1 in the colon. Western blot analysis was performed to determine the protein levels of TLR4， MyD88， and NF-κB in the colon. ResultsCompared with the blank group， the model group showed elevated DAI score （P<0.01）， reduced colon length and colon weight （P<0.01）， down-regulated protein levels of JAM-1 and claudin-1 （P<0.01）， and up-regulated protein levels of IL-8， COX-2， TLR4， MyD88， and NF-κB p65 （P<0.01） in the colon tissue. Compared with the model group， each treatment group showed decreased DAI score （P<0.05， P<0.01）， increased colon length and colon weight （P<0.05， P<0.01）， up-regulated protein levels of JAM-1 and claudin-1 （P<0.01）， and down-regulated protein levels of IL-8， COX-2， TLR4， MyD88， and NF-κB p65 （P<0.01） in the colon tissue. ConclusionShaoyaotang alleviates intestinal inflammation and intestinal mucosal damage to protect intestinal barrier integrity by regulating the TLR4/MyD88/NF-κB signaling pathway.

ObjectiveTo observe the effect of Yifei Jianpi prescription on the of signal transducer and activator of transcription protein 1 （STAT1）/interferon regulatory factor 3 （IRF3） signaling pathway in a pneumonia model induced by lipopolysaccharide （LPS） and to explore the mechanism of Yifei Jianpi prescription in improving lung immune and inflammatory responses. MethodsSixty male SPF SD rats were used in this study. Ten rats were randomly assigned to the normal control group， and the remaining 50 were instilled with LPS in the trachea to establish a pneumonia model. After successful modeling， the rats were randomly divided into the model group， dexamethasone group （0.5 mg·kg^-1）， and Yifei Jianpi prescription high-dose （12 mg·kg^-1）， medium-dose （6 mg·kg^-1）， and low-dose （3 mg·kg^-1） groups， with 10 rats in each group. Treatment was administered once daily， and the normal control and model groups received the same volume of normal saline. After 14 days， flow cytometry was used to detect the classification of whole blood lymphocytes. Enzyme-linked immunosorbent assay （ELISA） was used to measure serum levels of immunoglobulin G （IgG）， immunoglobulin A （IgA）， immunoglobulin M （IgM）， and the content of tumor necrosis factor-α （TNF-α）， interleukin-8 （IL-8）， interleukin-6 （IL-6）， and interleukin-10 （IL-10） in alveolar lavage fluid （BALF）. Hematoxylin-eosin （HE） staining was used to observe lung tissue pathology and score the damage. Thymus weight， spleen weight， and wet-to-dry weight ratio （W/D） were recorded. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of STAT1， IRF3， IL-6， and interferon-alpha （IFN-α） in lung tissues， while Western blot was performed to assess the protein expression of STAT1， IRF3， IL-6， and IFN-α. ResultsCompared with the normal control group， the model group showed significantly increased proportion of B lymphocytes in peripheral blood， decreased proportions of NK cells and CD4⁺/CD8⁺ （P<0.05， P<0.01）， decreased serum levels of IgG and IgA， significantly increased IgM levels （P<0.01）， significantly elevated content of TNF-α， IL-6， and IL-8 in BALF， and significantly decreased IL-10 levels （P<0.01）. Lung tissue damage was evident， with significant increases in thymus and spleen weights and a higher W/D ratio （P<0.01）. The mRNA and protein expression of STAT1， IRF3， IFN-α， and IL-6 in lung tissues was significantly upregulated （P<0.05，P<0.01）. Compared with the model group， the Yifei Jianpi prescription groups showed significantly reduced proportions of B lymphocytes in peripheral blood， increased proportions of NK cells and CD4⁺/CD8⁺ ratios （P<0.05， P<0.01）， significantly increased serum levels of IgG and IgA， significantly decreased IgM levels （P<0.05， P<0.01）， significantly reduced levels of TNF-α， IL-6， and IL-8 in BALF， and significantly increased IL-10 levels （P<0.01）. Lung tissue damage was alleviated， thymus and spleen weights were significantly reduced， and the W/D ratio was markedly decreased （P<0.01）. The mRNA and protein expression of STAT1， IRF3， IFN-α， and IL-6 in lung tissues was significantly downregulated （P<0.05， P<0.01）. ConclusionYifei Jianpi prescription can alleviate lung tissue damage and improve immune and inflammatory responses in LPS-induced pneumonia rats. The mechanism may be related to the inhibition of STAT1/IRF3 signaling pathway activation.

Insulin is an important protein hormone that participates in multiple metabolic pathways.Biosynthetic insulin has been widely used in the treatment of type 1 and type 2 diabetes.Currently,the number of reported cases of insulin overdose both at home and abroad is gradually increasing,and insulin homicide is no longer a means of"committing murder without leaving a trace".At present,there are no systematic protocols for the identification of insulin overdose in the field of forensic medi-cine in China.This article introduces the causes,toxicological characteristics,forensic examination,labo-ratory testing methods and indicator reference of insulin overdose.Based on the identification practice and research results and referring to relevant studies on insulin overdose at home and abroad,this pa-per aims to provide recommendations and references for the formulation of forensic identification guide-lines for insulin overdose cases.

Objective:To explore the value of a scoring system based on preoperative abdominal computed tomography (CT) for predicting the difficulty of laparoscopic cholecystectomy (LC).Methods:A retrospective analysis was conducted on 105 patients diagnosed with gallstones or cholecystitis who underwent LC at Beijing Jishuitan Hospital, Capital Medical University from January 2021 and February 2022. Based on surgical video reviews, patients were divided into the easy group ( n=58) and the difficult group ( n=47) according to the intraoperative Parkland Grading Scale (PGS), with PGS grades 1-2 assigned to the easy group, and PGS grades 3-5 assigned to the difficult group. The normally distributed measurement data were expressed as mean±standard deviation ( ± s), and compared using independent samples t-test; the non-normally distributed measurement data were expressed as median (interquartile range) [ M ( Q1, Q3)], and compared using the rank-sum test. The count data were expressed as the number of cases and percentage, and compared using the Chi-square test or Fisher exact probability method. Univariate analysis and cut-off value determination: for continuous CT variables, univariate Logistic regression and stepwise regression analyses (with surgical difficulty grouping as the dependent variable) were performed to identify the optimal combination of predictive variables and establish a scoring system. For each significantly associated continuous variable or important CT image feature from a clinical perspective, receiver operating characteristic (ROC) curve analysis was used to evaluate its predictive performance for difficult surgery. The area under the curve (AUC) was calculated, and the optimal cut-off value was determined using the Youden index to maximize the sum of sensitivity and specificity. The categorical CT image features were scored according to their original groups. The Kappa consistency test was used to assess the strength of agreement between the preoperative abdominal CT score (grouped by the optimal cut-off) and PGS grades (easy/difficult). Decision curve analysis (DCA) was employed to validate the predictive performance of the model. Results:Stepwise Logistic regression identified seven key imaging features as the optimal predictive variables for constructing the preoperative abdominal CT scoring system: maximum gallbladder cross-sectional diameter, maximum gallbladder cross-sectional width, gallbladder wall thickness, common bile duct diameter, pericholecystic fat stranding, periductal fat stranding, and impacted cystic duct stones. Each case was scored after assigning scores based on the optimal cut-off values. The total score of the preoperative abdominal CT scoring system was ≥3 points predicted difficult LC with an AUC of 0.745 (95% CI: 0.650-0.839), sensitivity of 66.0%, and specificity of 75.9%. DCA confirmed the model′s reliable predictive performance, and the preoperative abdominal CT scoring system showed good agreement with PGS grades ( Kappa value was 0.420, P<0.001). Conclusions:The preoperative abdominal CT scoring system based on pericholecystic imaging features can effectively predict the difficulty of LC with good discriminative ability. It provides a quantitative tool for preoperative assessment, surgical scheduling, and ambulatory surgery management.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

To investigate the mechanism of action of Syngnathus extract in treating knee osteoarthritis of rats, forty-eight male SD rats were randomly divided into the blank group, model group, positive drug group, as well as low-dose, medium-dose, and high-dose groups of Syngnathus extract. The rat model of knee osteoarthritis was constructed by intra-articular injection of sodium iodoacetate. After successful modeling, celecoxib(18 mg·kg~(-1)·d~(-1)) and Syngnathus extract(0.4, 0.8, and 1.6 g·kg~(-1)·d~(-1)) were given in different groups by gavage intervention for two weeks. Hematoxylin-eosin(HE) staining was used to observe the histopathological changes of cartilage in knee joints, and enzyme-linked immunosorbent assay(ELISA) was used to detect the expression level of inflammatory factors in serum. Real-time fluorescence quantitative PCR, Western blot, and immunohistochemistry were used to detect the levels of phosphatidylinositol 3-kinase(PI3K)/protein kinase B(Akt)/mammalian target protein of rapamycin(mTOR) pathway-related mRNA and protein expression. The results showed that, comparied with the blank group, the cartilage surface of the knee joints of rats in the model group was uneven, with disorganized levels and defective cartilage tissue. The serum levels of interleukin-1β(IL-1β), interleukin-6(IL-6), and tumor necrosis factor-α(TNF-α) and the mRNA levels of PI3K, Akt, and mTOR in cartilage tissue, as well as the protein expression levels of phosphorylated PI3K(p-PI3K)/PI3K, phosphorylated Akt(p-Akt)/Akt, phosphorylated mTOR(p-mTOR)/mTOR, and P62 were significantly increased. Beclin1 protein expression was decreased. Comparied with the model group, the number of chondrocytes in the knee joint of rats in each group of Syngnathus extract increased, and the arrangement of chondrocytes was relatively neat. The cartilage layer was restored, and the serum levels of IL-1β, IL-6, and TNF-α, as well as the mRNA expression levels of PI3K, Akt, and mTOR in cartilage tissue were significantly reduced. The protein expression levels of p-PI3K/PI3K, p-Akt/Akt, p-mTOR/mTOR, and P62 were significantly reduced in the rats in the middle-dose and high-dose groups of Syngnathus extract, and the Beclin1 protein expression was significantly increased. The protein expression levels of p-PI3K/PI3K, p-Akt/Akt, and P62 in rats in the low-dose group of Syngnathus extract were significantly reduced. In summary, Syngnathus extract may be used to treat knee osteoarthritis by inhibiting the expression of PI3K/Akt/mTOR signaling pathway, so as to alleviate the inflammatory response in the organism, enhance the autophagy activity of chondrocytes, and reduce the apoptosis of chondrocytes.
Animals ; TOR Serine-Threonine Kinases/genetics* ; Male ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; Proto-Oncogene Proteins c-akt/genetics* ; Rats ; Osteoarthritis, Knee/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Phosphatidylinositol 3-Kinases/genetics* ; Humans

This study predicts the potential mechanism of Hippocampus in the treatment of knee osteoarthritis(KOA) through network pharmacology, with preliminary verification using molecular docking and animal experiments. The database was used to screen the active chemical components of Hippocampus and the targets of KOA, and Gene Ontology(GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis, and molecular docking were performed on the relevant core targets to preliminarily explore the potential targets and mechanisms of Hippocampus in the treatment of KOA. A rat KOA model was constructed by intra-articular injection of sodium iodoacetate, and the rats were intervened with different doses of Hippocampus decoction and celecoxib. The expression of relevant targets was detected through hematoxylin-eosin(HE) staining, enzyme-linked immunosorbent assay(ELISA), RT-qPCR, and Western blot to further validate the network pharmacology results. A total of 23 drug-like components of the Hippocampus were screened, and 128 common targets with KOA were identified, involving interleukin-17(IL-17) signaling pathway, transcription factor(FoxO) signaling pathway, tumor necrosis factor(TNF) signaling pathway. Molecular docking results showed that the screened core chemical components exhibited good affinity with key targets. HE staining demonstrated that Hippocampus improved the morphology of the cartilage layer. ELISA confirmed that Hippocampus significantly reduced the levels of IL-6 and TNF-α in the serum of KOA rats. Western blot and RT-qPCR analysis showed that Hippocampus significantly reduced the expression of IL-6, TNF-α, matrix metalloproteinase(MMP) 13, IL-17A, nuclear factor κB activator 1(ACT1), tumor necrosis factor receptor-associated factor 6(TRAF6) and nuclear factor κB(NF-κB) in cartilage tissue. The results suggest that Hippocampus can alleviate the degree of joint damage in the KOA rat model induced by sodium iodoacetate. The mechanism of action is related to the inhibition of the IL-17 signaling pathway, reduction of inflammation, and inhibition of extracellular matrix(ECM) degradation.
Animals ; Molecular Docking Simulation ; Rats ; Drugs, Chinese Herbal/administration & dosage* ; Network Pharmacology ; Male ; Osteoarthritis, Knee/metabolism* ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; Humans ; Interleukin-17/metabolism* ; Tumor Necrosis Factor-alpha/metabolism* ; Disease Models, Animal ; Hippocampus/chemistry*

Retrieving keyframes most relevant to text from small intestine videos with given labels can efficiently and accurately locate pathological regions. However, training directly on raw video data is extremely slow, while learning visual representations from image-text datasets leads to computational inconsistency. To tackle this challenge, a small bowel video keyframe retrieval based on multi-modal contrastive learning (KRCL) is proposed. This framework fully utilizes textual information from video category labels to learn video features closely related to text, while modeling temporal information within a pretrained image-text model. It transfers knowledge learned from image-text multimodal models to the video domain, enabling interaction among medical videos, images, and text data. Experimental results on the hyper-spectral and Kvasir dataset for gastrointestinal disease detection (Hyper-Kvasir) and the Microsoft Research video-to-text (MSR-VTT) retrieval dataset demonstrate the effectiveness and robustness of KRCL, with the proposed method achieving state-of-the-art performance across nearly all evaluation metrics.
Humans ; Video Recording ; Intestine, Small/diagnostic imaging* ; Machine Learning ; Image Processing, Computer-Assisted/methods* ; Algorithms

ObjectiveThe proteome of biological evidence contains rich genetic information, namely single amino acid polymorphisms (SAPs) in protein sequences. However, due to the lack of efficient and convenient analysis tools, the application of SAP in public security still faces many challenges. This paper aims to meet the application requirements of SAP analysis for forensic biological evidence’s proteome data. MethodsThe software is divided into three modules. First, based on a built-in database of common non-synonymous single nucleotide polymorphisms (nsSNPs) and SAPs in East Asian populations, the software integrates and annotates newly identified exonic nsSNPs as SAPs, thereby constructing a customized SAP protein sequence database. It then utilizes a pre-installed search engine—either pFind or MaxQuant—to perform analysis and output SAP typing results, identifying both reference and variant types, along with their corresponding imputed nsSNPs. Finally, SAPTyper compares the proteome-based typing results with the individual’s exome-derived nsSNP profile and outputs the comparison report. ResultsSAPTyper accepts proteomic DDA mass spectrometry raw data (DDA acquisition mode) and exome sequencing results of nsSNPs as input and outputs the report of SAPs result. The pFind and Maxquant search engines were used to test the proteome data of 2 hair shafts of2 individuals, and both obtained SAP results. It was found that the results of the Maxquant search engine were slightly less than those of pFind. This result shows that SAPTyper can achieve SAP fingding function. Moreover, the pFind search engine was used to test the proteome data of 3 hair shafts from 1 European person and 1 African person in the literature. Among the sites fully matched by the literature method, sites detected by SAPTyper are also included; for semi-matching sites, that is, nsSNPs are heterozygous, both literature method and SAPTyper method had the risk of missing detection for one type of the allele. Comparing the analysis results of SAPTyper with the SAP test results reported in the literature, it was found that some imputed nsSNP sites identified by the literature method but not detected by SAPTyper had a MAF of less than 0.1% in East Asian populations, and therefore they were not included in the common nsSNP database of East Asian populations constructed by this software. Since the database construction of this software is based on the genetic variation information of East Asian populations, it is currently unable to effectively identify representative unique common variation sites in European or African populations, but it can still identify SAP sites shared by these populations and East Asian populations. ConclusionAn automated SAP analysis algorithm was developed for East Asian populations, and the software named SAPTyper was developed. This software provides a convenient and efficient analysis tool for the research and application of forensic proteomic SAP and has important application prospects in individual identification and phenotypic inference based on SAP.