Sustained inflammatory responses are closely related to various severe diseases, and inhibiting the excessive activation of inflammasomes and pyroptosis has significant implications for clinical treatment. Natural products have garnered considerable concern for the treatment of inflammation. Huanglian-Wumei decoction (HLWMD) is a classic prescription used for treating inflammatory diseases, but the necessity of their combination and the exact underlying anti-inflammatory mechanism have not yet been elucidated. Inspired by the supramolecular self-assembly strategy and natural drug compatibility theory, we successfully obtained berberine (BBR)-chlorogenic acid (CGA) supramolecular (BCS), which is an herbal pair from HLWMD. Using a series of characterization methods, we confirmed the self-assembly mechanism of BCS. BBR and CGA were self-assembled and stacked into amphiphilic spherical supramolecules in a 2:1 molar ratio, driven by electrostatic interactions, hydrophobic interactions, and π-π stacking; the hydrophilic fragments of CGA were outside, and the hydrophobic fragments of BBR were inside. This stacking pattern significantly improved the anti-inflammatory performance of BCS compared with that of single free molecules. Compared with free molecules, BCS significantly attenuated the release of multiple inflammatory mediators and lipopolysaccharide (LPS)-induced pyroptosis. Its anti-inflammatory mechanism is closely related to the inhibition of intracellular nuclear factor-kappaB (NF-κB) p65 phosphorylation and the noncanonical pyroptosis signalling pathway mediated by caspase-11.

Objective:To analyze the temporal distribution of other infectious diarrhea (OID) in Shenzhen and provide evidence for the prevention and control of OID.Methods:The incidence data of OID in Shenzhen from 2011 to 2023 were collected. The seasonal and trend decomposition using loess (STL), seasonal index method, concentration degree and circular distribution method were used to analyze the incidence trend and temporal distribution of OID.Results:A total of 477 611 cases of OID were reported in Shenzhen from 2011 to 2023, with an average annual incidence rate of 260.19/100 000 showing a fluctuating upward trend. The seasonal index method indicated that October-January was period with high incidence of OID in Shenzhen and the seasonal intensity began to decrease in 2020. STL revealed an obvious incidence peak in winter. The concentration method showed that OID had a certain seasonality before 2018 except 2016, but the seasonality was not obvious after 2018. The circular distribution results showed that r was 0.05, mean angle ā was 1.92° and angular standard deviation s was 141.93° ( Z=1 033.37, P<0.001), with the peak on January 1 st and the high incidence period from August 11 th to May 25 th. Conclusions:OID had a certain degree of seasonality in Shenzhen, with an obvious incidence peak in winter. Since the seasonal intensity of OID decreased after 2018, the surveillance, early warning and risk assessment of OID should be continued, and prevention and control measures should be adjusted timely according to the change in the characteristics of the epidemic.

Objectives:To analyze the epidemiological characteristics and incidence trends of chronic hepatitis B in Shenzhen from 2005 to 2023, develop a prediction models with performance evaluation, explore its associations with social demographic index (SDI) and inform targeted prevention strategy development.Methods:Based on surveillance data of infectious diseases, descriptive epidemiological methods were applied to analyze the spatiotemporal and population distribution characteristics. A multifactorial prediction model integrating the SDI was established, and its predictive performance was evaluated by using data from 2020-2023. Model accuracy was evaluated by using root mean square error and mean absolute percentage error ( MAPE). The association between SDI and incidence rates was assessed through generalized linear models. Results:A total of 235 703 chronic hepatitis B cases were reported cumulatively in Shenzhen from 2005-2023, with an annual average incidence rate of 98.84/100 000. Long-term trends revealed a significant increase in the incidence from 2005 to 2019. The incidence rate was 2.48 times higher in men than in women, and the majority of cases occurred in age group 20-50 years. The cases were mainly workers in manufacturing and services. Seasonal incidence peaks were observed in March and during May to November. The overall SDI exhibited a consistent upward trend, and the positive correlation between SDI and incidence rate was observed in central urban districts (Futian and Nanshan). In contrast, industrial zones (Guangming and Bao'an) saw a significant decline in incidence rates due to intensified prevention interventions despite the increase of SDI level. Model predictions indicated that the multivariate long short-term memory (LSTM) deep learning model integrating SDI parameters outperformed both the spatiotemporal covariate- enhanced model and the augmented Bayesian structural time series model, with MAPE of 4.71%, 7.66% and 10.30%, respectively. Conclusion:SDI is a key social determinant associated with hepatitis B transmission risks, and dynamic thresholds can be established to develop tiered early warning mechanisms. It is suggested to integrate multisource SDI data into the LSTM framework, implement targeted interventions such as "rapid antibody screening in key areas + vaccination boosters for high-risk populations" and improve the timeliness of epidemic response through hybrid models to reduce disease burden level.

Objective To screen the influencing factors associated with adverse clinical out-comes in hospitalized elderly patients with Alzheimer's disease(AD)using LASSO-Logistic regression analysis and to construct a nomogram prediction model.Methods A retrospective selection of 214 hospitalized elderly patients with AD who visited the Department of Geriatric Medicine in the hospital from February 2021 to March 2023 was conducted,and clinical data of all patients were collected.Patients were divided into adverse events group(n=53)and non-adverse events group(n=161)based on the occurrence of adverse clinical outcomes.After variable screening using LASSO regres-sion,multivariate Logistic regression analysis was performed to identify independent factors influen-cing adverse clinical outcomes in hospitalized elderly patients with AD.A Nomogram model for pre-dicting adverse clinical outcomes in these patients was established based on the results of multivariate analysis.The predictive performance,calibration,and clinical utility of the Nomogram model were evaluated using the concordance index,calibration curve,and decision curve analysis(DCA).The diagnostic performance of the Nomogram model for adverse clinical outcomes in hospitalized elderly patients with AD was assessed using the receiver operating characteristic(ROC)curve and the area under the curve(AUC).Results LASSO-Logistic regression analysis revealed that the Mini-Men-tal State Examination(MMSE)score was an independent protective factor against adverse clinical outcomes in hospitalized elderly patients with AD(P＜0.05),while the Charlson Comorbidity In-dex(CCI score),creatinine,urea,and fasting blood glucose(FBG)levels were all independent risk factors for adverse clinical outcomes in these patients(P＜0.05).The Nomogram model con-structed based on the influencing factors screened by LASSO-Logistic regression analysis showed a concordance index of 0.994(95％CI,0.958 to 1.000)for predicting adverse clinical outcomes in hospitalized elderly patients with AD.The Hosmer-Lemeshow test results indicated x2=1.909,P=0.984,suggesting good model fit.The DCA result demonstrated that the model had favorable threshold probabilities and net clinical benefits.Conclusion The Nomogram model for predicting clinical outcomes in elderly inpatients with AD constructed based on LASSO-Logistic regression anal-ysis exhibits high predictive value,and can be used to forecast the occurrence of adverse clinical outcomes in these patients.

Sustained inflammatory responses are closely related to various severe diseases,and inhibiting the excessive activation of inflammasomes and pyroptosis has significant implications for clinical treatment.Natural products have garnered considerable concern for the treatment of inflammation.Huanglian-Wumei decoction(HLWMD)is a classic prescription used for treating inflammatory diseases,but the necessity of their combination and the exact underlying anti-inflammatory mechanism have not yet been elucidated.Inspired by the supramolecular self-assembly strategy and natural drug compatibility theory,we successfully obtained berberine(BBR)-chlorogenic acid(CGA)supramolecular(BCS),which is an herbal pair from HLWMD.Using a series of characterization methods,we confirmed the self-assembly mechanism of BCS.BBR and CGA were self-assembled and stacked into amphiphilic spherical supra-molecules in a 2:1 molar ratio,driven by electrostatic interactions,hydrophobic interactions,and π-πstacking;the hydrophilic fragments of CGA were outside,and the hydrophobic fragments of BBR were inside.This stacking pattern significantly improved the anti-inflammatory performance of BCS compared with that of single free molecules.Compared with free molecules,BCS significantly attenuated the release of multiple inflammatory mediators and lipopolysaccharide(LPS)-induced pyroptosis.Its anti-inflammatory mechanism is closely related to the inhibition of intracellular nuclear factor-kappaB(NF-κB)p65 phosphorylation and the noncanonical pyroptosis signalling pathway mediated by caspase-11.

Objective:To report the nationwide surveillance results of pathogenic profiles and antimicrobial resistance patterns of Gram-positive bloodstream infections in China in 2023.Methods:The clinical isolates of Gram-posttive bacteria from blood cultures were collected in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System（BRICS）during January to December 2023. Antimicrobial susceptibility testing was performed using the dilution method recommended by the Clinical and Laboratory Standards Institute（CLSI）. Statistical analyses were conducted using WHONET 5.6 and SPSS 25.0 software.Results:A total of 4 385 Gram-positive bacterial isolates were obtained from 60 participating center. The top five pathogens were Staphylococcus aureus（ n=1 544，35.2%），coagulase-negative Staphylococci（ n=1 441，32.9%）， Enterococcus faecium（ n=574，13.1%）， Enterococcus faecalis（ n=385，8.8%），and α-hemolytic Streptococci（ n=187，4.3%）. The prevalence of methicillin-resistant Staphylococcus aureus（MRSA）and methicillin-resistant coagulase-negative Staphylococci（MRCNS）was 26.2%（405/1 544）and 69.8%（1 006/1 441），respectively. Notably，all Staphylococci remained susceptible to glycopeptide or daptomycin. Staphylococcus aureus demonstrated excellent susceptibility（>97.0%）to cephalobiol，rifampicin，trimethoprim-sulfamethoxazole，linezolid，minocycline，tigecycline，and eravacycline. No Enterococcus exhibiting resistance to linezolid were detected. Glycopeptide resistance was uncommon but more frequent in Enterococcus faecium（resistance to vancomycin and teicoplanin：both 1.7%）compared to Enterococcus faecalis（both 0.3%）. The detection rates of MRSA and MRCNS exhibited significant regional variations across the country（ χ2=17.674 and 148.650，respectively，both P<0.001）. No vancomycin-resistant Enterococci were detected in central China. Institutional comparison demonstrated higher prevalence of MRSA（ χ2=14.111， P<0.001）and MRCNS（ χ2=4.828， P=0.028）in provincial hospitals than that in municipal hospitals. Socioeconomic analysis identified elevated detection rates of both MRSA（ χ2=18.986， P<0.001）and MRCNS（ χ2=4.477， P=0.034）in less developed regions（per capita GDP

Objective:To report the results of bacterial resistant investigation collaborative system（BRICS）on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2023，and provide reference for clinical tretment of bloodstream infections and prevention and control of bacterial resistance.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of BRICS were collected during January 2023 to December 2023. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute（CLSI）. WHONET 5.6 and SPSS 25.0 were used to analyze the data.Results:During the study period，11 492 strains of Gram-negative bacteria were collected from 60 hospitals，of which 10 098（87.9%）were Enterobacterales and 1 394（12.1%）were non-fermentative bacteria. The top 5 bacterial species were Escherichia coli（50.0%）， Klebsiella pneumoniae（26.1%）， Pseudomonas aeruginosa（5.1%）， Acinetobacter baumannii complex（5.0%）and Enterobacter cloacae complex（4.1%）. The ESBL-producing rates in Escherichia coli， Klebsiella pneumoniae and Proteus mirablilis were 46.8%（2 685/5 741），18.3%（549/2 999）and 44.0%（77/175），respectively. The prevalence of carbapenem-resistant Escherichia coli（CREC）and carbapenem-resistant Klebsiella pneumoniae（CRKP）were 1.3%（76/5 741）and 15.0%（450/2 999）；32.9%（25/76）and 78.0%（351/450）of CREC and CRKP were sensitive to ceftazidime/avibactam combination，respectively. 94.7%（72/76）and 90.2%（406/450）of CREC and CRKP were sensitive to aztreonam/avibactam combination. Furthermore，57.9%（44/76）and 79.1%（356/450）were sensitive to imipenem/relebactam combination. The prevalence of carbapenem-resistant Acinetobacter baumannii（CRAB）complex was 64.6%（370/573），while more than 80.0% of CRAB complex was sensitive to tigecycline，eravacycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa（CRPA）was 17.0%（99/581）. There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of important Gram-negative bacteria resistance among different regions in China，with statistically significant differences in the prevalence of CREC，CRKP，CRPA and CRAB complex（ χ2=10.6，28.6，10.8 and 19.3， P<0.05）. The prevalence of ESBL-producing Escherichia coli， CREC，CRAB complex and CRKP were higher in provincial hospitals than those in municipal hospitals（ χ2=12.5，9.8，12.7 and 57.8，all P<0.01）. Conclusions:Gram-negative bacteria are the main pathogens causing bloodstream infections in China，and Escherichia coli is ranked in the top，while the trend of Klebsiella pneumoniae increases continuously with time. CRKP infection shows a slow upward trend，CREC infecton maintains a low prevalence level，and CRAB complex infection continues to exhibit a high prevalence rate. The composition and resistance patterns of pathogens causing bloodstream infections vary to some extent across different regions and levels of hospitals in China.

OBJECTIVE To investigate the pharmacological efficacy and mechanism of action of Atractylenolide Ⅰ(Atr-Ⅰ)in inhibiting colorectal cancer.METHODS Among three active compounds of Atractylodes macrocephala,Atr-Ⅰ exhibited the highest anti-tumor potency by MTT assay.The optimal concentration of Atr-Ⅰ was determined.The effect of Atr-Ⅰ on LoVo cell prolifera-tion was assessed via a clonogenic assay,while its impact on apoptosis and cell cycle progression was evaluated using flow cytometry.The influence of Atr-Ⅰ on the migration and invasion of LoVo cell line was examined through wound healing and Transwell migration assays.Western blot analysis was performed to explore the effects and mechanisms of Atr-Ⅰ on proteins associated with mi-gration,proliferation,and epithelial-mesenchymal transition(EMT)in LoVo cells.The CT26 mouse subcutaneous tumor model was established,and histopathological analysis was conducted using hematoxylin-eosin(HE)staining.Western blot was also used to assess the effects of Atr-Ⅰ on EMT-related proteins in mouse tissues to elucidate underlying mechanisms.RESULTS Atr-Ⅰ significantly reduced colorectal cancer cell viability,with statistically significant differences between treatment and control groups(P<0.05,P<0.01).Atr-Ⅰ induced apoptosis in LoVo cells,with the treatment group showing significant differences compared to the control(P<0.05,P<0.01).Cell cycle analysis revealed that Atr-Ⅰ exerted anti-tumor effects by inducing G2/M phase arrest,with increased G2 phase cell numbers in the LoVo treatment group compared to the control(P<0.05).Wound healing and Transwell migration assays confirmed that Atr-Ⅰ significantly inhibited tumor cell migration and invasion(P<0.05,P<0.01).Western blot analysis demonstra-ted that Atr-Ⅰ specifically suppressed the expression of c-Myc and Bcl-2(P<0.05),as well as cell cycle-related proteins CDK1,Cyclin B1,and Cyclin D1(P<0.05),and angiogenesis-related proteins VEGF and MMP9(P<0.05).Additionally,Atr-Ⅰ down-regulated EMT-related protein N-cadherin and upregulated E-cadherin expression(P<0.05).It also reduced the expression of p-AKT and p-S6K1(P<0.05).CONCLUSION Atr-Ⅰ exhibits potent anti-tumor effects against colorectal cancer,potentially through modulation of the AKT/S6K1 signaling pathway.

Objective:To analyze the temporal distribution of other infectious diarrhea (OID) in Shenzhen and provide evidence for the prevention and control of OID.Methods:The incidence data of OID in Shenzhen from 2011 to 2023 were collected. The seasonal and trend decomposition using loess (STL), seasonal index method, concentration degree and circular distribution method were used to analyze the incidence trend and temporal distribution of OID.Results:A total of 477 611 cases of OID were reported in Shenzhen from 2011 to 2023, with an average annual incidence rate of 260.19/100 000 showing a fluctuating upward trend. The seasonal index method indicated that October-January was period with high incidence of OID in Shenzhen and the seasonal intensity began to decrease in 2020. STL revealed an obvious incidence peak in winter. The concentration method showed that OID had a certain seasonality before 2018 except 2016, but the seasonality was not obvious after 2018. The circular distribution results showed that r was 0.05, mean angle ā was 1.92° and angular standard deviation s was 141.93° ( Z=1 033.37, P<0.001), with the peak on January 1 st and the high incidence period from August 11 th to May 25 th. Conclusions:OID had a certain degree of seasonality in Shenzhen, with an obvious incidence peak in winter. Since the seasonal intensity of OID decreased after 2018, the surveillance, early warning and risk assessment of OID should be continued, and prevention and control measures should be adjusted timely according to the change in the characteristics of the epidemic.

Objectives:To analyze the epidemiological characteristics and incidence trends of chronic hepatitis B in Shenzhen from 2005 to 2023, develop a prediction models with performance evaluation, explore its associations with social demographic index (SDI) and inform targeted prevention strategy development.Methods:Based on surveillance data of infectious diseases, descriptive epidemiological methods were applied to analyze the spatiotemporal and population distribution characteristics. A multifactorial prediction model integrating the SDI was established, and its predictive performance was evaluated by using data from 2020-2023. Model accuracy was evaluated by using root mean square error and mean absolute percentage error ( MAPE). The association between SDI and incidence rates was assessed through generalized linear models. Results:A total of 235 703 chronic hepatitis B cases were reported cumulatively in Shenzhen from 2005-2023, with an annual average incidence rate of 98.84/100 000. Long-term trends revealed a significant increase in the incidence from 2005 to 2019. The incidence rate was 2.48 times higher in men than in women, and the majority of cases occurred in age group 20-50 years. The cases were mainly workers in manufacturing and services. Seasonal incidence peaks were observed in March and during May to November. The overall SDI exhibited a consistent upward trend, and the positive correlation between SDI and incidence rate was observed in central urban districts (Futian and Nanshan). In contrast, industrial zones (Guangming and Bao'an) saw a significant decline in incidence rates due to intensified prevention interventions despite the increase of SDI level. Model predictions indicated that the multivariate long short-term memory (LSTM) deep learning model integrating SDI parameters outperformed both the spatiotemporal covariate- enhanced model and the augmented Bayesian structural time series model, with MAPE of 4.71%, 7.66% and 10.30%, respectively. Conclusion:SDI is a key social determinant associated with hepatitis B transmission risks, and dynamic thresholds can be established to develop tiered early warning mechanisms. It is suggested to integrate multisource SDI data into the LSTM framework, implement targeted interventions such as "rapid antibody screening in key areas + vaccination boosters for high-risk populations" and improve the timeliness of epidemic response through hybrid models to reduce disease burden level.