Objective To explore the potential molecular mechanism of Sangma Xingbei Tang （SMXBT） in the treatment of acute exacerbation of chronic obstructive pulmonary disease （AECOPD）. Methods TCMSP and TCMID databases were searched for the active ingredients of SMXBT, the targets of the active ingredients were predicted by SwissTargetPrediction database, and the AECOPD-related targets were searched by GeneCards and OMIM databases; the drug-active ingredient-target network and protein interaction network were constructed, and the GO enrichment and KEGG pathway enrichment were analyzed by the DAVID database. The drug-active ingredient-target network and protein interaction network were constructed, and the GO enrichment and KEGG pathway enrichment were analyzed by DAVID database, and molecular docking was performed by AutoDock Tools software. Animal experiments were conducted for validation. Results 192 active ingredients were obtained and 1066 targets were predicted in SMXBT. Network analysis showed that the top 3 active ingredients in SMXBT were quercetin, kaempferol, and glycyrrhizin, and the top 3 therapeutic targets were TNF, ALB, and IL-1β, etc. The GO analysis and KEGG showed that the main pathways were the cancer pathway, the MAPK signaling pathway, and the PI3K-Akt signaling pathway. Molecular docking showed that the binding energies of glycyrrhizin and AKT1, IL-1β, GFR, SRC, and quercetin and kaempferol and IL-1β were all <−5 kcal·mol. Animal experiments showed that Sangma Xingbei Decoction could treat AECOPD by anti-inflammatory effects and reduce changes in lung tissue structure. Additionally, it could lower the serum inflammatory levels of TNF-α, IL-6, and IL-8. Conclusion SMXBT may act on the targets of AKT1, IL-1β, EGFR, SRC, etc., reduce the serum inflammation levels of TNF-α, IL-6, IL-8, and improve the lung tissue structure and inflammatory response to achieve the therapeutic effect on AECOPD through the modulation of the PI3K/Akt signaling pathway, the MAPK signaling pathway, the cancer pathway, and other pathways of action.

Digital biopsy for liver diseases is characterized by the deep integration of artificial intelligence （AI） technologies and large-scale liver disease data， through which intelligent analytics are applied to support clinical decision-making and full-cycle management. This article reviews the AI technical framework based on standardized data governance and centered on multimodal large medical models， covering the application of natural language processing， knowledge map， generative AI， and large language models in the establishment of databases for specialty diseases， diagnosis， prognosis prediction， treatment， and automated medical documentation. This article also discusses the application prospects of this framework in medical education， scientific research， and healthcare management. Although this technique shows broad application potential， it still faces challenges in areas such as multi-center data integration， model interpretability， ethics， and data security. In the future， a smart ecosystem with closed-loop optimization and human-AI collaboration should be established to promote the comprehensive implementation of digital biopsy in the whole process of medicine， education， research， and management， thereby providing help for the precise prevention and control and holistic health management of liver diseases.

Objective To develop an ultra-high performance liquid chromatography-mass spectrometry method(UPLC-MS/MS)for the determination of nirmatrelvir concentration in mouse plasma.Methods The ACQUITY UPLC system was used in tandem with an API 4000 triple quadrupole mass spectrometer.The analytical column was Waters BEH C18(2.1 mm×5.0 mm,1.7 μm)column,and the mobile phases consisted of water(containing 0.1％formic acid)and methanol(containing 0.1％formic acid)under gradient elution at the flow rate of 0.4 mL·min-1.The column temperature was set at 40 ℃,and the injection volume was 5 μL.Electrospray ionization was used as ion source,and positive multiple reaction monitoring mode was adopted to quantitatively analyze the ionization pairs m/z 500.3→110.3(nirmatrelvir)and m/z 237.3→193.3(carbamazepine).Carbamazepine was employed as an internal standard.Results The linear range of nirmatrelvir was from 10 ng·mL-1 to 2 560 ng·mL-1.For the quality control nirmatrelvir samples,the accuracies of intra-and inter-batch were less than±15％,and the precisions of intra-and inter-batch were lower than 15％.Nirmatrelvir in plasma was stable at room temperature for 24 h and remained stable after three freeze-thaw cycles.The extracted nirmatrelvir solution could be stored at 4℃ for 3 d without any visible change.Conclusion The method was characterized by good specificity,high sensitivity,and appropriate linear range.The methodological validation was in accordance with the 2020 edition of the Chinese Pharmacopoeia and could be applied to the quantitative detection of nirmatrelvir in plasma.

Background and Aims:Single-incision laparoscopic cholecystectomy(LC)has become increasingly popular due to its minimal invasiveness and cosmetic advantages,but challenges remain in biliary identification and limited operative space.Indocyanine green(ICG)fluorescence navigation enables real-time visualization of the biliary tract and may enhance surgical safety and efficiency.This study aimed to evaluate the clinical application value of ICG fluorescence navigation in single-incision LC.Methods:A retrospective analysis was conducted on 59 patients with benign gallbladder diseases who underwent elective single-incision LC at Yixing Hospital affiliated to Jiangsu University from January 2023 to December 2024.Patients were divided into a fluorescence group(n=27)and a white-light group(n=32)according to whether ICG fluorescence navigation was applied.The two groups were compared in terms of Calot's triangle dissection time,operative time,intraoperative blood loss,surgeon satisfaction,hospital stay,and postoperative complications.Results:No significant differences were observed in baseline clinical characteristics between the two groups(all P＞0.05).In the fluorescence group,the cystic duct,common hepatic duct,and common bile duct were all successfully visualized.Compared with the white-light group,the fluorescence group had significantly shorter Calot's triangle dissection time[(25.56±3.49)min vs.(38.81±5.59)min],shorter operative time[(44.67±3.06)min vs.(61.31±4.96)min],and less intraoperative blood loss[(13.44±1.70)mL vs.(14.50±2.11)mL](all P＜0.05),with significantly higher surgeon satisfaction(P＜0.05).No intraoperative bile duct injury,conversion to three-port surgery,or postoperative complications occurred in either group.Conclusion:ICG fluorescence navigation can significantly improve biliary identification efficiency in single-incision LC,shorten operative time,reduce blood loss,and enhance surgeon satisfaction,demonstrating promising clinical application prospects.

Objective To investigate the weight loss efficacy and mechanisms of oligopeptide-herbal medicine composite,and to provide new approaches for obesity treatment.Methods Twenty-three SPF female SD rats were randomly divided into control group(n=3)and modeling group(n=20).The control group was fed an ordinary diet for 6 consecutive weeks,and the modeling group was fed a high-fat diet for 6 consecutive weeks to establish a simple obesity rat model.After successful modeling,the modeling group was randomly divided into model group(n=10)and treatment group(n=10).The treatment group started anoint-and-massage therapy with oligopeptide-herbal medicine composite(3 g per rat per time,once a day,20 min each time),which was recorded as day 1.The control group and model group were not treated with oligopeptide-herbal medicine composite but received the same massage,and continued to be fed ordinary feed and high-fat feed respectively.Ten rats in the model group and ten in the treatment group were each divided into 3 groups,with 3,3,and 4 rats in each group.On days 3,6,and 9 after treatment,the rats in the three groups were weighed and cardiac blood collection was performed after isoflurane respiratory anesthesia.After euthanasia by cardiac bloodletting,abdominal subcutaneous adipose tissue(aSAT)and perirenal white adipose tissue(pWAT)samples were collected and weighed.Serum triglycerides(TG)and high-density lipoprotein cholesterol(HDL-C)levels were measured.Image J software was used to measure aSAT thickness and the diameter and area of perirenal white adipocytes and abdominal subcutaneous adipocytes.Immunofluorescence technique was used to observe the number of telocytes(TCs),cell junctions and exosomes per unit area of aSAT.Transmission electron microscopy was used to measure the length of telopodes(Tps)of dermal and subcutaneous TCs in abdominal skin,and to observe the distribution of exosome vesicles,rough endoplasmic reticulum,mitochondria,and cell junctions.Results Compared with the control group,the body weight of rats in the modeling group increased significantly(P＜0.05).Compared with the control group,rats in the model group showed a significant increase in serum TG level,a significant decrease in HDL-C level,and a significant increase in pWAT mass(all P＜0.05).Compared with the model group,the treatment group showed a significantly increased rate of body weight reduction,significantly decreased pWAT mass,significantly decreased serum TG level,and significantly increased HDL-C level(all P＜0.05).Compared with the model group,the treatment group showed significant reductions in aSAT thickness,as well as cell diameter and area in both aSAT and pWAT(all P＜0.05).Compared with the model group,the treatment group showed significantly increased number of TCs per unit area of aSAT,number of exosomes from TCs in aSAT,and Tps length(all P＜0.05).The treatment group showed an increasing trend in the numbers of mitochondria,rough endoplasmic reticulum,and cell junctions in TCs.Conclusion Oligopeptide-herbal medicine composite applied via anoint-and-massage therapy effectively improves obesity-related symptoms such as dyslipidemia and fat accumulation in obese rats by regulating TCs and their intercellular communication.

Objective:To analyze the association between inflammation-related dietary patterns and the risk for cognitive impairment in older adults aged ≥65 years in longevity areas in China by using reduced rank regression (RRR) analysis.Methods:This study used cross-sectional data from the 2021 Healthy Aging and Biomarkers Cohort Study, including the information about study participants' demographic characteristics, lifestyles, daily life activities, and disease histories. Dietary intake was obtained by using a simplified food frequency questionnaire. Cognitive impairment was evaluated based on the Mini-Mental State Examination Scale combined with years of education. Fasting venous blood samples were collected to detect inflammatory markers, especially high-sensitivity C-reactive protein (hs-CRP) and the platelet-to-lymphocyte ratio (PLR). RRR analysis was used to obtain inflammation-related dietary patterns using hs-CRP and PLR as response variables. Multivariate logistic regression model was used to analyze the association between dietary pattern score and the risk for cognitive impairment. Restricted cubic spline was used to explore the dose response relationship, and mediation analysis was used to quantify the mediating effects of hs-CRP and PLR.Results:Two dietary patterns were identified with RRR. The primary pattern was characterized by higher intakes of flour, red meat, and dairy products, and lower intake of fresh vegetables, explaining 6.84% of the variance in food intake and 0.50% of the variance in inflammatory markers. Compared with the T1 group, the T3 group had significantly higher risk for cognitive impairment ( OR=1.242, 95% CI: 1.034-1.491). Each one standard deviation increase in the dietary pattern score was associated with an 8.7% increase in the risk for cognitive impairment ( OR=1.087, 95% CI: 1.008-1.172), with a significant linear trend (overall-model P<0.001, non-linear P=0.295). Mediation analysis indicated that hs-CRP mediated 6.2% of the association between the dietary pattern and the risk for cognitive impairment. Conclusion:The inflammation- related dietary pattern characterized by higher consumption of flour, red meat, and dairy products and lower consumption of fresh vegetables is associated with an increased risk for cognitive impairment in older adults, and hs-CRP partially mediates this association.

Objective:To investigate the relationship between dietary behavior and sarcopenia in older adults aged ≥65 years in longevity areas of China based on latent class analysis.Methods:A total of 4 358 older adults aged ≥65 years were selected from the 2021 Healthy Aging and Biomarkers Cohort Study. The information about their demographic characteristics, lifestyles, and chronic disease histories were collected. A simplified food frequency questionnaire was used to collect information about their dietary intake in the last month. The food intake frequency and food category score were calculated, and the higher the food category score, the richer the dietary intake. Latent class analysis was used to identify the latent classes of the dietary behavior. Sarcopenia was diagnosed using the SARC-CalF. Multivariate logistic regression model was used to analyze the association of food category scores and different latent classes of the dietary behavior with the risk for sarcopenia.Results:In 4 358 older adults, 1 841 (42.24%) had sarcopenia. The frequencies of intakes of cereals and potatoes, vegetable and fruit, meat and bean products were lower in the sarcopenia group than in the non-sarcopenia group. The risk for sarcopenia decreased with the increase of food category score in older adults ( OR=0.850, 95% CI: 0.796-0.907). Latent class analysis identified 4 latent classes of the dietary behavior. Compared with those with class 1 (frequency of intake of all 5 food species was higher probability in T3 group), those with class 2 (frequency of intake of vegetables and fruits and energy-only foods were less likely to be in the T3 group) and class 3 (frequency of intake of all 5 food species was lower probability in T3 group) had significantly increased risk for sarcopenia ( OR=1.377, 95% CI: 1.131-1.676) and ( OR=1.354, 95% CI: 1.091-1.680), 37.7% and 35.4% increased risk for sarcopenia, respectively. Conclusion:Increasing dietary intake category and sufficient intake of various foods for a balanced dietary pattern can reduce the risk of sarcopenia in older adults.

Objective:To analyze the association between inflammation-related dietary patterns and the risk for cognitive impairment in older adults aged ≥65 years in longevity areas in China by using reduced rank regression (RRR) analysis.Methods:This study used cross-sectional data from the 2021 Healthy Aging and Biomarkers Cohort Study, including the information about study participants' demographic characteristics, lifestyles, daily life activities, and disease histories. Dietary intake was obtained by using a simplified food frequency questionnaire. Cognitive impairment was evaluated based on the Mini-Mental State Examination Scale combined with years of education. Fasting venous blood samples were collected to detect inflammatory markers, especially high-sensitivity C-reactive protein (hs-CRP) and the platelet-to-lymphocyte ratio (PLR). RRR analysis was used to obtain inflammation-related dietary patterns using hs-CRP and PLR as response variables. Multivariate logistic regression model was used to analyze the association between dietary pattern score and the risk for cognitive impairment. Restricted cubic spline was used to explore the dose response relationship, and mediation analysis was used to quantify the mediating effects of hs-CRP and PLR.Results:Two dietary patterns were identified with RRR. The primary pattern was characterized by higher intakes of flour, red meat, and dairy products, and lower intake of fresh vegetables, explaining 6.84% of the variance in food intake and 0.50% of the variance in inflammatory markers. Compared with the T1 group, the T3 group had significantly higher risk for cognitive impairment ( OR=1.242, 95% CI: 1.034-1.491). Each one standard deviation increase in the dietary pattern score was associated with an 8.7% increase in the risk for cognitive impairment ( OR=1.087, 95% CI: 1.008-1.172), with a significant linear trend (overall-model P<0.001, non-linear P=0.295). Mediation analysis indicated that hs-CRP mediated 6.2% of the association between the dietary pattern and the risk for cognitive impairment. Conclusion:The inflammation- related dietary pattern characterized by higher consumption of flour, red meat, and dairy products and lower consumption of fresh vegetables is associated with an increased risk for cognitive impairment in older adults, and hs-CRP partially mediates this association.

Objective:To investigate the relationship between dietary behavior and sarcopenia in older adults aged ≥65 years in longevity areas of China based on latent class analysis.Methods:A total of 4 358 older adults aged ≥65 years were selected from the 2021 Healthy Aging and Biomarkers Cohort Study. The information about their demographic characteristics, lifestyles, and chronic disease histories were collected. A simplified food frequency questionnaire was used to collect information about their dietary intake in the last month. The food intake frequency and food category score were calculated, and the higher the food category score, the richer the dietary intake. Latent class analysis was used to identify the latent classes of the dietary behavior. Sarcopenia was diagnosed using the SARC-CalF. Multivariate logistic regression model was used to analyze the association of food category scores and different latent classes of the dietary behavior with the risk for sarcopenia.Results:In 4 358 older adults, 1 841 (42.24%) had sarcopenia. The frequencies of intakes of cereals and potatoes, vegetable and fruit, meat and bean products were lower in the sarcopenia group than in the non-sarcopenia group. The risk for sarcopenia decreased with the increase of food category score in older adults ( OR=0.850, 95% CI: 0.796-0.907). Latent class analysis identified 4 latent classes of the dietary behavior. Compared with those with class 1 (frequency of intake of all 5 food species was higher probability in T3 group), those with class 2 (frequency of intake of vegetables and fruits and energy-only foods were less likely to be in the T3 group) and class 3 (frequency of intake of all 5 food species was lower probability in T3 group) had significantly increased risk for sarcopenia ( OR=1.377, 95% CI: 1.131-1.676) and ( OR=1.354, 95% CI: 1.091-1.680), 37.7% and 35.4% increased risk for sarcopenia, respectively. Conclusion:Increasing dietary intake category and sufficient intake of various foods for a balanced dietary pattern can reduce the risk of sarcopenia in older adults.

Medical imaging large-scale models demonstrate broad application prospects in the field of tumor diagnosis and treatment.Their powerful high-dimensional feature extraction and data analysis capabilities have brought revolutionary breakthroughs to precision oncology,driving the transformation of diagnostic and therapeutic paradigms.However,current research in this field still faces numerous challenges and technical bot-tlenecks.Based on the research background of artificial intelligence(AI)large-scale models,this article sys-tematically reviews the current research status of medical imaging large-scale models from three key dimensions:the construction of large-scale medical imaging datasets,optimization of large-scale model algorithms,and com-putational resource requirements.Furthermore,it elaborates on the application scenarios of these models in pre-cision oncology and provides a forward-looking perspective on their future development.The aim is to offer prac-tical guidance for advancing precision diagnosis and treatment of tumors.