As a major global public health concern,cancer has witnessed a continues rise in both incidence and mortality rates.It pose not only a severe threat to human health but also a heavy burden on socioeconomic systems.Despite remarkable advancements in oncology research,critical challenges such as tumor heterogeneity,drug resistance,and limitations in early screening and diagnostic technologies remain to be addressed.Against this backdrop,artificial intelligence(AI),with its unique advantages in big data analysis,pattern recognition,and predictive modeling,has opened new avenues for cancer research.By integrating multi-modal data,including omics,imaging,and clinical information,AI not only accelerates investigations into fundamental tumor mechanisms but also demonstrates immense potential in areas such as early screening,biomarker discovery,and personalized treatment.These advancements have fostered a deeper integration of precision medicine and oncology.This review provides a comprehensive overview of the most recent progresses in the application of AI in cancer diagnosis and treatment research,with a focus on its practical value across diverse data types and clinical scenarios,as well as future directions for its development.

Systemic lupus erythematosus （SLE） may lead to secondary gynecological and obstetric disorders such as decreased ovarian reserve function， menstrual abnormalities， and adverse pregnancy outcomes. Based on "bi （痹） of both body and viscera" theory， this paper proposed that the core mechanism of SLE secondary gynecological and obstetric diseases lies in the mutual transformation between "body bi" and "viscera bi"， which together affect the uterus. Physiologically， uterus forms an internal-external network with the body and viscera through the meridians and blood vessels. Pathologically， when the healthy qi is deficient， nourishment of the body and viscera is impaired； when toxins and stasis accumulate， pathogenic factors disturb the uterus through the chong （冲） and ren （任） meri-dians. The resulting obstruction in the uterus can， in turn， manifest externally and aggravate damage to the body and viscera. Therefore， the pathogenesis of SLE secondary gynecological and obstetric diseases follows a dynamic trajectory of "body bi first， body bi affecting viscera， and then bi of both body and viscera". In treatment， the principle of harmonizing and balancing the healthy qi is emphasized. The main approach is to regulate the viscera， stabilize the body， and nourish the uterus， with the coordination of nourishing the viscera through the body， thereby achieving simultaneous treatment of both body and viscera. This highlights the guiding significance of the "bi of both body and viscera" theory in preventing and treating SLE secondary gynecological and obstetric diseases.

ObjectiveTo explore the correlation between the occurrence of cardiovascular events in rheumatoid arthritis（RA） and traditional Chinese medicine（TCM） syndrome. MethodsThe cross-sectional study selected 6713 RA patients from 122 centres nationwide， in which general information such as name， gender， age， height， body weight， and course of disease were collected by completing a questionnaire； patients were classified into eight types of syndrome according to the information of their four examinations，i.e. wind-dampness obstruction syndrome， cold-dampness obstruction syndrome， dampness-heat obstruction syndrome， phlegm-stasis obstruction syndrome， stasis-blood obstructing collateral syndrome， qi-blood deficiency syndrome， liver-kidney insufficiency syndrome， and qi-yin deficiency syndrome. According to the occurrence of cardiovascular events， they were divided into the occurrence group and the non-occurrence group， and the condition assessment data and laboratory examination indexes were recorded. The test of difference between groups was used to analyse the possible risk factors for the occurrence of RA cardiovascular events， and binary logistic regression was used to analyse the correlation between TCM syndromes and RA cardiovascular events. ResultsA total of 6713 RA patients were included， including 256 cases in occurrence group and 6457 in non-occurrence group. There was no statistically significant difference between groups in terms of height， gender， insomnia， appetite， white blood cell（WBC）， hemoglobin（HGB）， platelets（PLT）， rheumatoid factor（RF）， anti-cyclic peptide containing citrulline（CCP）， alanine aminotransferase（ALT）， aspartate aminotransferase（AST）， γ-glutamyl transpeptidase（GGT）， urea creatinine（CREA）， and glucose（GLU）（P＞0.05）. The TCM syndromes between groups showed significant statistic differences（P＜0.05）. Patients in occurrence group had longer disease duration， heavier body weight， and older age； more severe conditions such as disease activity（DAS-28）， number of painful joints（TJC）， number of swollen joints（SJC）， health questionnaire scores（HAQ）， visual analog scores（VAS）， restlessness， and fatigue； higher blood sedimentation rate（ESR）， low-density lipoprotein（LDL-C）， triglyceride（TG）， total cholesterol（TC）， D-Dimer， and lower high-density lipoprotein（HDL-C）（P＜0.05）. The distribution of syndrome types showed that dampness-heat obstruction syndrome accounted for the largest proportion of patients in both groups and was higher in RA cardiovascular events. Logistic regression analysis showed that the occurrence of RA cardiovascular events was strongly associated with dampness-heat obstruction syndrome［OR=5.937， 95%CI （4.434， 7.949）， P＜0.001］. ConclusionThe occurrence of RA cardiovascular events were associated with TCM syndromes， and the probability of cardiovascular events in the RA patients with dampness-heat obstruction syndrome was 5.937 times higher than patients with other TCM syndromes.

As a major global public health concern,cancer has witnessed a continues rise in both incidence and mortality rates.It pose not only a severe threat to human health but also a heavy burden on socioeconomic systems.Despite remarkable advancements in oncology research,critical challenges such as tumor heterogeneity,drug resistance,and limitations in early screening and diagnostic technologies remain to be addressed.Against this backdrop,artificial intelligence(AI),with its unique advantages in big data analysis,pattern recognition,and predictive modeling,has opened new avenues for cancer research.By integrating multi-modal data,including omics,imaging,and clinical information,AI not only accelerates investigations into fundamental tumor mechanisms but also demonstrates immense potential in areas such as early screening,biomarker discovery,and personalized treatment.These advancements have fostered a deeper integration of precision medicine and oncology.This review provides a comprehensive overview of the most recent progresses in the application of AI in cancer diagnosis and treatment research,with a focus on its practical value across diverse data types and clinical scenarios,as well as future directions for its development.

Adverse drug reactions (ADRs) significantly impact clinical medication safety. The timely identification and prediction of ADRs rely on the efficient analysis of real-world data, such as electronic health records, social media, and spontaneous reporting databases. In recent years, the rapid advancement of artificial intelligence, particularly large language models, in natural language processing, causal reasoning, and complex data mining has provided new technological means for real-time ADRs monitoring and individualized prediction. This paper summarizes the latest research achievements in AI-driven ADRs monitoring. Focusing on diverse data sources, including structured databases and electronic health records, it elaborates on the advantages andchallenges of AI in ADRs event extraction, relationship identification, causal analysis, and risk prediction. The aim is to provide a theoretical reference for constructing more intelligent and efficient ADRs monitoring systems.

ObjectiveTo evaluate the clinical efficacy and safety of Tripterygium wilfordii polyglycoside tablets （TWP） in the treatment of rheumatoid arthritis （RA） in the real world. MethodDiagnosis and treatment data of patients with RA in Chinese medicine rheumatology registration research information platform information database （CERTAIN） from January 1，2019 to January， 2024 were collected. According to the inclusion and exclusion criteria， data were screened. The included data were divided into an exposure group and a control group according to the use of TWP or not. Propensity score matching （PSM） was used in both groups to keep the baseline balanced and comparable. The disease activity score （DAS28-ESR） of 28 joints based on the erythrocyte sedimentation rate （ESR）before and after treatment was compared between the two groups， as well as health assessment questionnaire （HAQ），visual analogue scale （VAS），tender joint count （TJC），swollen joint count （SJC）， patient's global assessment （PGA），evaluator's global assessment （EGA），laboratory indexes， clinical curative effect， and adverse reactions. ResultA total of 3 978 patients were included，including 929 in the exposure group and 3 049 in the control group. Before PSM，there were significant differences in demographic information，DAS28-ESR score，PGA，EGA，HAQ，VAS scores，SJC， and TJC between the two groups （P<0.05）. After successful PSM matching，922 patients in the exposure group and 922 patients in the control group were included. There was no significant difference in demographic information and DAS28-ESR between the two groups before treatment，and the differences in other indexes between the two groups decreased to varying degrees. After treatment，the DAS28-ESR，PGA，EGA，HAQ，SJC，TJC，VAS scores， ESR，and IgG immune index of the two groups were significantly lower （P<0.01）. Compared with those in the control group after treatment，the DAS28-ESR，PGA，EGA，HAQ，VAS scores， and ESR in the exposure group after treatment decreased more significantly （P<0.05，P<0.01）. There was no significant difference in TJC in the exposure group after treatment. However， TJC in the exposure group was significantly higher than that in the control group before treatment （P<0.05）. In terms of TJC reduction，the exposure group performed better than the control group. There was no significant difference in SJC and IgG between the exposure group and the control group after treatment. After treatment，the clinical symptoms of poor appetite，insomnia and many dreams，upset，fatigue，and fear of wind and cold in the two groups were improved. Except that the proportion of women in the exposure group was higher than that in the control group （P<0.01），there was no significant difference in the incidence of other adverse reactions between the two groups after treatment. ConclusionTWP to treat RA can effectively reduce DAS28-ESR，PGA，EGA，HAQ，TJC，and VAS scores and improve the general symptoms. Except for the women at childbearing age with fertility requirements that TWP is not applicable，it shows good security.

Pancreatic metastases originating in colon cancer are very rare clinically, and there are few reports on their imaging manifestations. In this paper, it improves the diagnosis of the disease by reporting a case of pancreatic head metastases and focusing on the appearance of contrast-enhanced ultrasound.

Objective:To evaluate the efficacy of medical cold patches in relieving burning pain and restoring skin homeostasis after hematoporphyrin monomethyl ether-based photodynamic therapy (HMME-PDT) for the treatment of port-wine stains.Methods:Forty patients with port-wine stains in the middle face, who met the inclusion and exclusion criteria, were collected from Department of Dermatology, the Seventh Medical Center of Chinese PLA General Hospital from November 2019 to April 2021, and randomly and equally divided into test group and control group. Patients in the test group received cold compress with medical cold patches at treatment sites for 1 hour immediately after HMME-PDT, and then once a day for 3 consecutive days, while those in the control group received no special treatment and experienced a spontaneous recovery. Pain numeric rating scale (NRS) scores were recorded immediately, 0.5, 1 and 12 hours after HMME-PDT. Skin surface temperature was measured 10 minutes before, and immediately, 30 minutes and 1 hour after HMME-PDT. Transepidermal water loss (TEWL) and water content of the stratum corneum (WCSC) were measured 10 minutes before, and immediately, 24, 48 and 72 hours after HMME-PDT. The scabbing rate was calculated at weeks 1, 2 and 3 after HMME-PDT. Two-way repeated measures analysis of variance was used for comparisons of observation indicators at different time points before and after treatment, and Bonferroni or Sidak′s test was used for comparisons between groups and within groups.Results:There were no significant differences in age, gender composition, TEWL or WCSC between the test group and control group before HMME-PDT (all P > 0.05) . Immediately after HMME-PDT, no significant difference in the NRS score was observed between the test group and control group (8.00 ± 1.17 vs. 8.20 ± 1.06, F = 0.30, P = 0.592) ; at 0.5 and 1 hour after HMME-PDT, the NRS score was significantly lower in the test group (6.25 ± 1.29, 4.80 ± 0.77, respectively) than in the control group (7.15 ± 0.99, 6.50 ± 0.69, respectively, both P < 0.05) . Immediately after HMME-PDT, the skin surface temperature in the test group and control group increased to 35.21 ± 1.333 ℃ and 35.64 ± 0.832 ℃, respectively, and there was no significant difference between the two groups ( P = 0.062) ; at 30 and 60 minutes after HMME-PDT, the skin surface temperature in the test group was 29.11 ± 1.59 ℃ and 32.46 ± 1.07 ℃ respectively, which were significantly lower than those in the control group (35.01 ± 0.91 ℃, 34.86 ± 0.74 ℃, F = 212.63, 100.20, respectively, both P < 0.001) . At 48 and 72 hours after HMME-PDT, the TEWL in the test group was 12.44 ± 0.67 g·h -1·m -2 and 10.85 ± 0.81 g·h -1·m -2 respectively, which were significantly lower than those in the control group (14.61 ± 0.34 g·h -1·m -2, 14.93 ± 0.24 g·h -1·m -2, F = 195.87, 520.54, respectively, both P < 0.001) , while the WCSC was significantly higher in the test group (57.83 ± 9.29 AU, 52.64 ± 8.09 AU, respectively) than in the control group (43.87 ± 4.82 AU, 38.68 ± 5.33 AU, F = 24.41, 49.22, respectively, both P < 0.001) . At 1 week after HMME-PDT, scab formation was observed in 3 cases in the test group, as well as in 6 cases in the control group, and there was no significant difference in the scabbing rate between the two groups ( P = 0.451) . Conclusion:The application of medical cold patches after HMME-PDT for the treatment of port-wine stains can reduce skin surface temperature, exert analgesic effects, shorten duration of postoperative pain, and promote the recovery of skin permeability barrier function.

ObjectiveTo establish a neuroinflammation-based obesity and depression comorbidity （COM） model in mice and explore the pharmacodynamics and preliminary pharmacological mechanism of tripterine on COM mice. MethodC57BL/6J mice were randomly divided into a normal group （Chow）， a diet-induced obesity group （DIO）， and a COM group. The mice in the COM group were fed on a high-fat diet and chronically stressed with moist litter for 12 weeks to establish the COM model. C57BL/6J mice were randomly divided into a Chow group， a COM group， and a tumor necrosis factor-α（TNF-α） knock-down group. In the TNF-α knock-down group， TNF-α shRNA adeno-associated virus was injected into the amygdala through brain stereotaxis， and the expression of TNF-α in the amygdala was down-regulated. C57BL/6J mice were randomly divided into a Chow group， a DIO group， a DIO + low-dose tripterine group （0.5 mg·kg^-1）， a DIO + high-dose tripterine group （1.0 mg·kg^-1）， a COM group， a COM + low-dose tripterine group （0.5 mg·kg^-1）， and a COM + high-dose tripterine group （1.0 mg·kg^-1）. The body weight， food intake， glucose tolerance， white/brown fat ratio， serum total cholesterol （TC）， triglyceride （TG）， and high-/low-density lipoprotein cholesterol （HDL-C and LDL-C） content were recorded， and obesity of mice in each group was evaluated. Forced swimming test （FST）， tail suspension test （TST）， and open field test were used to evaluate the degree of depression of mice in each group. Immunofluorescence staining was used to detect the protein expression levels of neuropeptide Y， tryptophan hydroxylase 2 （TPH2）， and brain-derived neurotrophic factor （BDNF） in various brain nuclei of mice. Correlation analysis was used to detect the correlation of obesity and depression indexes. ResultThe comparison of the Chow group and the DIO group indicated that COM mice showed obesity and depression. To be specific， obesity was manifested as increased body weight and food intake （P<0.05， P<0.01）， as well as increased NPY expression in the central amygdala， and depression was manifested as prolonged immobility time in FST and TST （P<0.01）， and reduced TPH2-positive 5-hydroxytryptamine neurons in the dorsal raphe nucleus （DRN） and basolateral nucleus of the amygdala （BLA）. The down-regulation of TNF-α protein in BLA of COM mice shortened the immobility time in FST and TST （P<0.05， P<0.01）， increased TPH2/BDNF-positive neurons in BLA， and showed no significant changes in obesity. In DIO mice， the administration of 0.5 mg·kg^-1 tripterine for 9 days significantly decreased the 60 min blood glucose in glucose tolerance （P<0.01） and food intake （P<0.05）. In COM mice， 1.0 mg·kg^-1 tripterine was administered for 14 days to significantly decrease 30 min blood glucose in glucose tolerance （P<0.01）， and food intake （P<0.05）， and immobility time in TST （P<0.01）， increase TPH2-BDNF double-labeled cells in BLA and DRN， and reduce the area of TMEM119-stained cells. ConclusionThe model of obesity and depression comorbidity can be properly induced in mice under the condition of dual stress of energy environment. Tripterine can effectively interfere with obesity-depression comorbidity， and its mechanism may be related to the inhibition of central nervous system inflammation.

Identification of significant biological relationships or patterns is central to many metagenomic studies.Methods that estimate association networks have been proposed for this pur-pose;however,they assume that associations are static,neglecting the fact that relationships in a microbial ecosystem may vary with changes in environmental factors(EFs),which can result in inaccurate estimations.Therefore,in this study,we propose a computational model,called the k-Lognormal-Dirichlet-Multinomial(kLDM)model,which estimates multiple association networks that correspond to specific environmental conditions,and simultaneously infers microbe-microbe and EF-microbe associations for each network.The effectiveness of the kLDM model was demonstrated on synthetic data,a colorectal cancer(CRC)dataset,the Tara Oceans dataset,and the American Gut Project dataset.The results revealed that the widely-used Spearman's rank correlation coefficient method performed much worse than the other methods,indicating the importance of separating samples by environmental conditions.Cancer fecal samples were then compared with cancer-free samples,and the estimation achieved by kLDM exhibited fewer associations among microbes but stronger associations between specific bacteria,especially five CRC-associated operational taxonomic units,indicating gut microbe translocation in cancer patients.Some EF-dependent associations were then found within a marine eukaryotic community.Finally,the gut microbial heterogeneity of inflammatory bowel disease patients was detected.These results demonstrate that kLDM can elucidate the complex associations within microbial ecosys-tems.The kLDM program,R,and Python scripts,together with all experimental datasets,are accessible at https://github.com/tinglab/kLDM.git.