ObjectiveTo investigate the therapeutic effect and mechanism of Solanum nigrum on hepatic fibrosis induced by carbon tetrachloride （CCl₄） in rats. MethodsSixty SD rats were randomly allocated into blank， model， low-， medium-， and high-dose （0.9， 1.8， 3.6 g·kg^-1， respectively） S. nigrum， and silibinin capsules （18.9 mg·kg^-1） groups. Except the blank group， the other groups were subjected to intraperitoneal injection of 40% CCl₄ solution for the modeling of hepatic fibrosis. After 4 weeks of gavage， blood was collected from the abdominal aorta following intraperitoneal anesthesia. The rats were sacrificed， and the liver was separated. The pathological changes were observed by hematoxylin-eosin staining and Masson staining. The levels of alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， and liver fibrosis indexes ［type Ⅲ procollagen （PCⅢ）， type Ⅳ collagen （Col Ⅳ）， laminin （LN）， and hyaluronic acid （HA）］ in the rat serum were determined. The mRNA and protein levels of B cell lymphoma-2 （Bcl-2）/Bcl-2-associated X protein （Bax）/cysteinyl aspartate-specific proteinase-3 （Caspase-3） pathway-related factors were determined by Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and Western blot， respectively. ResultsCompared with the blank group， the model group exhibited significant hepatocyte edema， infiltration of inflammatory cells， connective tissue proliferation， and collagen fiber deposition in the liver tissue. Compared with the model group， low-， medium-， and high-dose S. nigrum and silymarin capsules significantly improved the structure of liver cells and alleviated the edema， inflammatory cell infiltration， connective tissue proliferation， and collagen fiber deposition. Compared with those in the blank group， the serum levels of ALT， AST， PCⅢ， Col Ⅳ， LN， and HA were elevated in the model group （P<0.01）. Compared with the model group， the serum levels of ALT， AST， PCⅢ， Col Ⅳ， LN， and HA were reduced in all the treatment groups （P<0.05）. Real-time PCR and Western blot results showed that compared with the blank group， the model group had up-regulated mRNA and protein levels of Bcl-2 and down-regulated mRNA and protein levels of Bax and Caspase-3 （P<0.01）. Compared with the model group， all the treatment groups showed down-regulated mRNA and protein levels of Bcl-2 and up-regulated mRNA and protein levels of Bax and Caspase-3 （P<0.05）， with the high-dose S. nigrum group showing the best therapeutic effect. ConclusionS. nigrum modulates the progression of hepatic fibrosis in rats by regulating apoptosis through the Bcl-2/Bax/caspase-3 pathway.

This paper outlines the development of artificial intelligence （AI） and its applications in traditional Chinese medicine （TCM） research， and elucidates the roles and advantages of large language models， knowledge graphs， and natural language processing in advancing syndrome identification， prescription generation， and mechanism exploration. Using spleen-stomach diseases as an example， it demonstrates the empowering effects of AI in classical literature mining， precise clinical syndrome differentiation， efficacy and safety prediction， and intelligent education， highlighting an upgraded research paradigm that evolves from data-driven and knowledge-driven approaches to intelligence-driven models. To address challenges related to privacy protection and regulatory compliance in cross-institutional data collaboration， a "trusted federated evidence-based analysis platform for TCM spleen-stomach diseases" is proposed， integrating blockchain-based smart contracts， federated learning， and secure multi-party computation. The deep integration of AI with privacy-preserving computing is reshaping research and clinical practice in TCM spleen-stomach diseases， providing feasible pathways and a technical framework for building a high-quality， trustworthy TCM big-data ecosystem and achieving precision syndrome differentiation.

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.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

ObjectiveTo investigate the contamination status, transmission risk and drug resistance of Klebsiella pneumoniae (KP) on the object surfaces in the surrounding environment of hospitalized patients infected with carbapenem-resistant Klebsiella pneumoniae (CRKP) , so as to provide a scientific guidance for the prevention and control of healthcare-associated infection. MethodsSamples from the surfaces of objects in the surrounding environment of CRKP infected patients living in the intensive care unit (ICU) and hand specimens from healthcare workers were collected for KP isolation and identification, as well as drug susceptible test in a medical institution located in Minhang District, Shanghai from 2021 to 2023. Additionally, both univariate and multivariate logistic regression analyses were used to identify the influencing factors associated with KP contamination in the hospital environment. ResultsA total of 546 surface samples were collected from the surrounding environment objects of 15 patients infected with CRKP, with a KP detection rate of 6.59% (36/546).The KP detection rate in the ICU of general ward (10.22%) was higher than that in the ICU of emergency department (2.94%) (χ²=12.142, P<0.001). Moreover, the KP detection rate on the surfaces of patient-contacted items (15.66%) was higher than that on shared-use items (6.25%), cleaning items (10.00%), and medical supplies (3.30%) (χ²=17.943, P<0.001). Besides, the detection rate of KP in items sent out of hospital for disinfection (15.38%) was higher than that in those self-disinfected (4.20%) (χ²=19.996, P<0.001).The highest detection rate of KP was observed in high-temperature washing (15.13%, 18/119) (χ²=21.219, P<0.001), while the lowest detection rate was observed in antibacterial hand sanitizer with trichlorohydroxydiphenyl ether sanitizing factor (0, 0/60) ( χ²=21.219, P<0.001).The detection rate of KP in samples taken more than 24 hours after the last disinfection (23.08%) was higher than that in those taken at 4 to24 hours (12.90%) and less than 4 hours (4.22%) (χ²=23.398,P<0.001).ICU of general ward (OR=4.045, 95%CI: 2.206‒7.416), patient-contacted items (OR=3.113, 95%CI: 1.191‒8.141), and self-disinfection ( OR=0.241, 95%CI:0.144‒0.402) were influencing factors for KP contamination in environmental surface. From 2021 to 2023, the drug resistance rates of hospital environmental KP isolates showed an upward trend (P<0.001) to antibiotics such as ceftazidime and gentamicin. Furthermore, high drug resistance rates of KP (>90%) were observed to ciprofloxacin, levofloxacin, cefotaxime, ceftriaxone, and cefepime. ConclusionCRKP can be transmitted outward through the surfaces of objects in the patients’ surroundings, and the drug resistance situation is severe. In clinical settings, it is necessary to implement isolation measures for CRKP infection patients, to increase the frequency of disinfection for objects in their surroundings, to strengthen hand hygiene practices, and to use antibiotics appropriately.

ObjectiveTo clearly identify the difference between rescue injuries and agonal injuries and to avoid duplicate identifications and misidentifications. MethodsBased on the forensic pathological data of 5 923 cases of death cause identification from 2013 to 2022 in Sun Yat-sen University Forensic Identification Center and Guangzhou Tianhe District Branch of Guangzhou Public Security Bureau， this study retrospectively studied the characteristics of rescue injuries and agonal injuries seen in cause of death identification and their influence on cause of death identification. ResultsAmong all the 5 923 cases， 640 cases were found to have rescue injuries or agonal injuries， and 624 cases received treatment， of which 609 cases were found to have rescue injuries （97.60%）， 44 cases were found to have agonal injuries， and 13 cases were found to have both types of injuries. Among the 640 cases， 441 were male and 199 were female. The age of death was discontinuously distributed from 0 to 95 years old. The leading cause of death was disease， followed by mechanical injury and asphyxia. The main manifestations of rescue injuries were rib and sternum fractures， soft tissue injuries in the prechest area or face， and pericardial rupture. The most common injuries in agonal stage were falling after unconsciousness， inhalation of foreign body in respiratory tract or multiple violent injuries. Among the 640 cases， 19 cases were repeatedly identified， including 15 cases of rescue injuries， 6 cases of agonal injuries， and 2 cases of both types of injuries. Compared with the cases where neither type of injuries was detected， the repeated identification rate of treatment injuries and agonal injuries was significantly increased （χ²=4.04， P=0.044； χ²=43.49， P<0.001）. Among the 640 cases， 11 cases （1.72%） were misidentified as the initial injuries in the first identification， and 13 cases had combined rescue injuries or agonal injuries that were involved in death. ConclusionsBy elucidating the epidemiological characteristics of the two types of injuries， this study proved that the two types of injuries were associated with higher rates of repeated identification and misidentification， which provided a reference for reducing repeated identification and misidentification and improving the accuracy of cause of death identification.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

Objective To establish a scientific, comprehensive, and operable community resilience evaluation index system for emergent major infectious diseases. Methods Based on the social ecosystem theory, a preliminary evaluation index system was formed by using content analysis and boundary analysis. The index system was then supplemented and revised through panel discussions. The final index system and index weights were clarified by two rounds of Delphi method. Results The expert positive coefficient, expert authority coefficient, and expert coordination coefficient of the two rounds of expert consultations were examined. According to the screening principle of the ^“threshold method^”, the indicators were screened, and the weights of each indicator were determined in the second round of Delphi expert consultation. The analysis of the reliability of the indicator system showed Cronbach's α= 0.399 , indicating that the indicator system had a relatively high reliability. Factor analysis was carried out on 7 primary indicators, and the measure of sampling adequacy (MSA) values were all greater than 0.5, which passed the validity test. Conclusion A set of evaluation index system that can accurately reflect the resilience level of communities with emergent major infectious diseases has been constructed, including 7 primary indicators, 21 secondary indicators, 54 tertiary indicators, and 108 tertiary indicators, which has realized the quantitative evaluation of the hidden resilience level of communities.

Clinical practice guidelines represent the best recommendations for patient care. They are developed through systematically reviewing currently available clinical evidence and weighing the relative benefits and risks of various interventions. However, clinical practice guidelines have to go through a long translation cycle from development and revision to clinical promotion and application, facing problems such as scattered distribution, high duplication rate, and low actual utilization. At present, the clinical practice guideline information platform can directly or indirectly solve the problems related to the lengthy revision cycles, decentralized dissemination and limited application of clinical practice guidelines. Therefore, this paper systematically examines different types of clinical practice guideline information platforms and investigates their corresponding challenges and emerging trends in platform design, data integration, and practical implementation, with the aim of clarifying the current status of this field and providing valuable reference for future research on clinical practice guideline information platforms.

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.