AIM To optimize the extraction process for total polyphenols from Conioselinum vaginatu(Spreng.)Thell.,make component analysis,and evaluate their anti-oxidant,hypoglycemic activities.METHODS The effects of ultrasound,enzymatic hydrolysis,acid hydrolysis,alcohol extraction and hydrolysis processes on the extraction quantity of total polyphenols were investigated,respectively.With extraction temperature,extraction time,ethanol concetration and liquid-solid ratio as influencing factors,extraction quantity of total polyphenols as an evaluation index,the extraction process was optimized by response surface method.HPLC was adopted in the identification of polyphenolic composition and determination of their contents.Subsequently,total polyphenols' scavenging capacities on DPPH,ABTS,OH free radicals,total reducing power and inhibitory capacity on α-glucosidase were determined.RESULTS The highest extraction quantity of total polyphenols was observable when extraction process was employed.The optimal conditions were determined to be 62 ℃ for extraction temperature,54 min for extraction time,69％for ethanol concentration,and 50∶1 for liquid-solid ratio,the extraction quantity of total polyphenols was(9.51±0.2)mg GAE/g.Seven constituents existed in C.vaginatu,among which ferulic acid demonstrated the highest content,followed by that of myricetin,while D-tryptophan content was the lowest.At the concentration of 7.61 mg/L,total polyphenols displayed the scavenging rates on DPPH,ABTS,OH free radicals of 80.70％,85.97％,28.60％,total reducing power of 0.22,and inhibition rate on α-glucosidase of 77.23％,respectively.CONCLUSION This stable and reliable method can be used for the extraction of total polyphenols from C.vaginatum with strong anti-oxidant,hypoglycemic activities.

Microplastics are widely present in various environments such as water bodies,land,and atmosphere,which pose threats to the ecological environment and human health through transmission and accumulation in the food chain.The existing detection techniques for microplastics face challenges such as complex preparation procedure of samples,low efficiency in processing large batches of samples,and difficulties in handling complex samples.Therefore,there is an urgent need for rapid and efficient detection techniques suitable for complex microplastics samples in the field of environmental monitoring.Raman spectroscopy,known for its advantages such as rapidity,accuracy,high sensitivity,non-destructiveness,and non-contact,demonstrates great application potential in detection of microplastics.Deep learning,an artificial intelligence method known for its large-scale data processing,nonlinear modeling and automatic feature extraction capabilities,is receiving increasing attention in the analysis of Raman spectroscopy signals.The application of deep learning-based Raman spectroscopy has significantly improved performance indicators such as detection efficiency and accuracy.This article introduced the existing Raman enhancement techniques,summarized the deep learning methods applied in Raman spectroscopy signal analysis,reviewed the recent research and application progress of deep learning-based Raman spectroscopy in detection of microplastics,and finally discussed the challenges and future prospects of deep learning-based Raman spectroscopy in detection of microplastics.

The traditional detection methods for monitoring the biomass,protein,chlorophyll content and other key indicators in the growth of chlorella have some problems,including complicated operation,slow detection speed and difficult large-scale application.In this study,a fast and efficient monitoring method for the key indicators in the growth of chlorella was established using near infrared spectroscopy and chemometrics.Near-infrared spectroscopy was used to collect near-infrared spectra of chlorella algal fluid at different growth stages,and standard methods were used to detect the biomass,protein and chlorophyll contents of corresponding samples.A quantitative analysis model was established based on partial least squares regression(PLSR).To improve the prediction ability of the model,multiplicative scatter correction(MSC)was used to reduce the interference of scattering on the raw spectrum(RS),standard normal variate(SNV)was used to normalize the original spectral data to eliminate differences between samples,continuous wavelet transform(CWT)was used to obtain the key features of spectral data,the first derivative(1st)was used to enhance the differentiation of the original spectral features,and monte carlo-uninformative variable elimination(MC-UVE)and randomization test(RT)were used to screen the valid variables in the wavelength.By evaluating the prediction ability of different models,the quantitative analysis models of chlorella biomass,protein and chlorophyll content were finally determined.The results showed that the model based on 1st combined with RT spectra had better predictive ability for chlorella nutrient content detection,and the root mean square errors of prediction(RMSEP)and coefficients of determination(R2)were 0.041 and 0.933 for biomass,0.012 and 0.973 for protein,and 0.517 and 0.962 for chlorophyll,respectively.This model showed practical application value,and could realize the rapid and accurate detection of chlorella biomass,protein and chlorophyll content at the same time.

Aim To perform high-throughput screen-ing of immunomodulatory traditional Chinese medicine(TCMs)based on an in vitro B cell differentiation-antibody secretion model,identifying active herbal candidates with immune-enhancing properties to pro-vide novel therapeutic options and theoretical support for influenza virus treatment in immunocompromised in-dividuals.Methods B cells were stimulated with dif-ferent concentrations of cytosine-phosphate-guanine oli-godeoxynucleotide 2006(CpG)and nterleukin-2(IL-2)to promote proliferation,differentiation,and anti-body secretion,and the effects of varying concentra-tions of the solvent DMSO were also evaluated.The op-timal conditions for the B cell differentiation-anti-body secretion model were determined based on the se-cretion levels of three antibody isotypes.The feasibility of the model was further validated using rapamycin,a known B cell function inhibitor.On this basis,a high-throughput screening platform for immunomodulatory a-gents was optimized and established.Subsequently,the immune-enhancing activity of 465 polarity extract from TCMs was evaluated.Results The optimal con-ditions for the model were determined as 2 mg·L-1 CpG,1.67 × 106 nkat·L-1 IL-2,and DMSO with a volume fraction of 0.1％.Rapamycin effectively inhib-ited B cell differentiation into plasmablast and signifi-cantly reduced antibody production,indicating the reli-ability of the model.Multiple rounds of screening re-vealed that the dichloromethane extract of licorice,the dichloromethane extract of Vinegar-processed Curcumae Rhizoma,the cyclohexane extract of Honey-prepared Radix Asteris,and the aqueous extract of Siphonostegia chinensis Benth were identified to significantly promote both B cell proliferation and differentiation and anti-body secretion at a concentration of 600 μg·L-1.Conclusion This study successfully optimizes an in vitro B cell differentiation-antibody secretion model and identifies several TCM extracts,including licorice,with potential immune-enhancing activity.

Objectives:To investigate the expression and clinical prognostic implication of secreted frizzled-related protein 4(SFRP4)in the peripheral blood of patients with dilated cardiomyopathy(DCM)and its.Methods:A total of 259 consecutive patients diagnosed with DCM who were admitted to the Cardiac Center of Zhongshan Hospital,Fudan University,from January 2017 to January 2019 were selected for the DCM group.Additionally,84 individuals who underwent health examinations and echocardiography at our hospital during this period,confirmed to be free of cardiovascular diseases,were selected as the control group.Peripheral serum samples were collected from both groups,and serum SFRP4 levels were measured using enzyme-linked immunosorbent assay(ELISA).The correlation between SFRP4 levels and DCM severity,as well as its predictive value for DCM prognosis,were analyzed.Results:Compared to the control group,the serum SFRP4 levels in the DCM group were significantly elevated([28.54±10.25]ng/ml vs.[52.70±19.74]ng/ml,P<0.05).The DCM group was randomly divided into a training set and a validation set in a 2:1 ratio.Multivariate logistic regression analysis in the training set revealed that serum SFRP4 levels were independently associated with all-cause mortality in DCM patients(OR=1.06,95% CI:1.03-1.10,P<0.001).We further evaluated the model's predictive performance with the receiver operating characteristic(ROC)curves(area under curve>0.8),calibration curves,and decision curve analysis,results indicated that the predictive model containing serum SFRP4 levels showed good performance on predicting all-cause mortality in DCM patients.Kaplan-Meier survival curve analysis demonstrated that during a median follow-up of 33.5(11.0,49.0)months,DCM patients with high peripheral blood SFRP4 levels(≥75th percentile)had a significantly higher incidence of all-cause mortality compared to those with low levels(<75th percentile)(28.81% vs.16.57%,P=0.02).Conclusions:The level of SFRP4 in the peripheral blood of DCM patients is significantly elevated,and peripheral serum SFRP4 levels have potential prognostic value for predicting the all-cause mortality in DCM patients.

In October 2023, a patient with locally advanced breast cancer was treated in the Department of Reconstructive Microsurgery, Xuzhou Renci Hospital. Radical mastectomy for breast cancer was performed, and the huge soft tissue defect (40.0 cm×22.0 cm) was reconstructed by a pedicled transverse rectus abdominis myocutaneous flap (TRAMF) combined with a free deep inferior epigastric artery perforator flap (DIEPF) and a free anterolateral thigh perforator flap (ALTPF). The size of the lower abdominal flap was 28.0 cm×11.0 cm, and the size of ALTPF was 30.0 cm×11.0 cm. All flaps survived well with soft texture. Scores of Karnofsky Performance Status (KPS) and Visual Analogue Scale (VAS) were significantly improved at 1 month after the surgery. The patient refused chemotherapy, radiotherapy and other comprehensive treatments at the time. A local cancer recurrence in chest wall was found at 9 months after surgery, the patient was currently under chemotherapy and other comprehensive therapies.

This study aims to analyze the screening results and epidemiological characteristics of prostate cancer (PCa) among elderly males in the rural areas of Songjiang, Shanghai City, through the implementation of a preliminary prostate-specific antigen (PSA) screening based on a community-linkage model, and to explore an effective screening approach. A retrospective observational study design was employed to collect data from residents who underwent PSA screening at Songjiang Hospital affiliated to Shanghai Jiao Tong University School of Medicine, in collaboration with multiple community health service centers in Songjiang District, Shanghai City, between June 2022 and June 2024, through free clinics and annual health examinations. Prostate biopsy was recommended for individuals with total PSA (tPSA) levels >10 ng/ml and those with 4 ng/ml≤tPSA≤10 ng/ml and abnormal free-to-total PSA (f/tPSA) ratios. Clinical characteristics of detected PCa patients were analyzed. Follow-up was conducted through phone calls and home visits by family doctors, coupled with enhanced health education. The results indicated that a total of 17 198 residents participated in the screening, among which 2 234 (12.99%) had tPSA levels between 4 ng/ml and 10 ng/ml, and 257 (1.49%) had tPSA levels >10 ng/ml. Ultimately, 417 residents underwent prostate biopsy, with 171 being diagnosed with PCa, yielding a positive biopsy rate of 41.00% and a PCa detection rate of 0.99%. The predominant pathological subtype among PCa patients was adenocarcinoma (168 cases, 98.24%). Of the 146 PCa patients who received treatment, the majority were classified as intermediate or high-risk (124 cases, 84.93%). Furthermore, with the optimization of the screening model, there was a significant increase in the proportion of subsequent outpatient visits. In conclusion, the community-linkage-based PSA screening model demonstrated high effectiveness in screening for PCa among elderly males in the rural areas of Songjiang, Shanghai City. Epidemiological findings revealed that PCa patients in this region are primarily composed of intermediate and high-risk groups, highlighting the need for intensified early screening and health education.

Aim To perform high-throughput screen-ing of immunomodulatory traditional Chinese medicine(TCMs)based on an in vitro B cell differentiation-antibody secretion model,identifying active herbal candidates with immune-enhancing properties to pro-vide novel therapeutic options and theoretical support for influenza virus treatment in immunocompromised in-dividuals.Methods B cells were stimulated with dif-ferent concentrations of cytosine-phosphate-guanine oli-godeoxynucleotide 2006(CpG)and nterleukin-2(IL-2)to promote proliferation,differentiation,and anti-body secretion,and the effects of varying concentra-tions of the solvent DMSO were also evaluated.The op-timal conditions for the B cell differentiation-anti-body secretion model were determined based on the se-cretion levels of three antibody isotypes.The feasibility of the model was further validated using rapamycin,a known B cell function inhibitor.On this basis,a high-throughput screening platform for immunomodulatory a-gents was optimized and established.Subsequently,the immune-enhancing activity of 465 polarity extract from TCMs was evaluated.Results The optimal con-ditions for the model were determined as 2 mg·L-1 CpG,1.67 × 106 nkat·L-1 IL-2,and DMSO with a volume fraction of 0.1％.Rapamycin effectively inhib-ited B cell differentiation into plasmablast and signifi-cantly reduced antibody production,indicating the reli-ability of the model.Multiple rounds of screening re-vealed that the dichloromethane extract of licorice,the dichloromethane extract of Vinegar-processed Curcumae Rhizoma,the cyclohexane extract of Honey-prepared Radix Asteris,and the aqueous extract of Siphonostegia chinensis Benth were identified to significantly promote both B cell proliferation and differentiation and anti-body secretion at a concentration of 600 μg·L-1.Conclusion This study successfully optimizes an in vitro B cell differentiation-antibody secretion model and identifies several TCM extracts,including licorice,with potential immune-enhancing activity.

Objectives: This study aimed to analyze the epidemiology and trends of hemorrhagic fever with renal syndrome (HFRS) in Weifang, China (2013–2021) and to guide prevention strategies. Methods: The study examined the prevalence and incidence trends of HFRS in Weifang (2013–2021). Spearman correlation and wavelet analysis were employed to explore variable relationships and their associations with HFRS incidence. Generalized additive models (GAMs)were used to identify key risk factors, while structural equation modeling (SEM) quantified direct and indirect pathways influencing HFRS transmission. Finally, Bayesian time-series models wereapplied to predict future HFRS risk. Results: Weifang reported 2,118 HFRS cases, which displayed distinct seasonality. Spearman correlation linked economic factors (gross domestic product [GDP], crop area, grain output, green space) and meteorological factors (temperature, pressure) to incidence (r > 0.8). Wavelet analysis identified Mus musculus (2013–2016) and Rattus norvegicus (2017–2021) as dominant reservoirs, with temperature, precipitation, and humidity correlating with incidence. GAMsrevealed a U-shaped relationship between rodent density and HFRS and an inverted U-shapedrelationship between temperature (threshold, 11.64 °C) and HFRS. SEM highlighted the direct and indirect effects of climate via rodent density, mirrored by economic factors (e.g., GDP). Bayesianmodels effectively predicted HFRS (root mean square error, 7.36; mean absolute percentage error, 0.28; R2 = 0.65). Conclusion Climate, economic, and anthropogenic factors drive the spread of HFRS. Preventionstrategies should integrate local economic conditions with meteorological and anthropogenicfactors. Bayesian time-series modeling effectively predicts HFRS trends, supporting precisionprevention strategies.

AIM To optimize the extraction process for total polyphenols from Conioselinum vaginatu(Spreng.)Thell.,make component analysis,and evaluate their anti-oxidant,hypoglycemic activities.METHODS The effects of ultrasound,enzymatic hydrolysis,acid hydrolysis,alcohol extraction and hydrolysis processes on the extraction quantity of total polyphenols were investigated,respectively.With extraction temperature,extraction time,ethanol concetration and liquid-solid ratio as influencing factors,extraction quantity of total polyphenols as an evaluation index,the extraction process was optimized by response surface method.HPLC was adopted in the identification of polyphenolic composition and determination of their contents.Subsequently,total polyphenols' scavenging capacities on DPPH,ABTS,OH free radicals,total reducing power and inhibitory capacity on α-glucosidase were determined.RESULTS The highest extraction quantity of total polyphenols was observable when extraction process was employed.The optimal conditions were determined to be 62 ℃ for extraction temperature,54 min for extraction time,69％for ethanol concentration,and 50∶1 for liquid-solid ratio,the extraction quantity of total polyphenols was(9.51±0.2)mg GAE/g.Seven constituents existed in C.vaginatu,among which ferulic acid demonstrated the highest content,followed by that of myricetin,while D-tryptophan content was the lowest.At the concentration of 7.61 mg/L,total polyphenols displayed the scavenging rates on DPPH,ABTS,OH free radicals of 80.70％,85.97％,28.60％,total reducing power of 0.22,and inhibition rate on α-glucosidase of 77.23％,respectively.CONCLUSION This stable and reliable method can be used for the extraction of total polyphenols from C.vaginatum with strong anti-oxidant,hypoglycemic activities.