Based on the theory of "sweet-flavored medicinals retaining and restoring body fluid"， this paper proposed that the core pathogenesis of hypercoagulable state in malignant tumors is qi deficiency and fluid consumption， blood stasis and vessels stagnation， which evolves dynamically according to the pattern "qi deficiency → fluid consumption → blood stasis". Accordingly， a staged treatment system is established with the general principle of "fortifying the middle jiao， restoring fluid and activating blood circulation". In the initial stage， invigorating the spleen and boosting qi to generate body fluid， targeting the onset of middle jiao deficiency and body fluid consumption； in the middle stage， nourishing yin and unblocking collaterals to facilitate body fluid circulation， addressing the disorder of body fluid transportation and collateral injury caused by internal dryness； in the late stage， consolidating yin and resolving blood stasis to retain body fluid， resolving yin impairment， fluid exhaustion， and binding of stasis and toxin. By regulating body fluid metabolism to improve the hypercoagulable state， this system is intended to provide insights for the prevention and treatment of hypercoagulable state in malignant tumors with traditional Chinese medicine.

Objective: To investigate the status of heat illness, knowledge awareness and adaptive behaviors of heat wave knowledge among food delivery riders, so as to provide a basis for optimizing heat wave response measures for food delivery riders. Methods: In November 2022, food delivery riders from a large food delivery platform in Ningbo City, Zhejiang Province were selected as survey subjects using a cluster sampling method. A self-designed electronic questionnaire was used to select demographic information, work status, lifestyle behaviors and disease history, heat illness status, knowledge awareness and adaptive behaviors of heatwave. Results: A total of 911 questionnaires were distributed, and 830 valid questionnaires were recovered, resulting in a valid response rate of 91.11%. Among the respondents, 796 (95.90%) were male, and 818 (98.55%) worked full-time. The mean age was (27.75±8.00) years. A total of 470 respondents (56.63%) had a work tenure of less than 1 year. The primary working hours were 8-<12 hours, with 504 people accounting for 60.72%. There were 108 cases of heatstroke, with an occurrence rate of 13.01%. And 286 people reported heat-related symptoms, with an occurrence rate of 34.46%. The overall awareness rate of heat wave knowledge was 73.22%, while the awareness rate of heat warning signal classification was relatively low at 9.04%. The heat wave cognition score was (5.86±1.31) points. There were statistically significant differences in heat wave cognition scores among food delivery riders of different ages, educational levels, family annual income, work tenures, and work durations (all P<0.05). Regarding positive adaptive behaviors, the number of riders paying attention to weather forecasts and actively learning about preventive measures was higher (734 people each, accounting for 88.43%). Regarding negative adaptive behaviors, the number of riders who often drank ice-cold beverages was higher (509 people, accounting for 61.33%). The heat wave adaptive behavior score was (6.88±1.77) points. There were statistically significant differences in adaptive behavior scores among riders with different educational levels, family annual income, work tenures, and smoking frequency (all P<0.05). Conclusions The occurrence rates of heatstroke and heat-related symptoms among food delivery riders are relatively high. The knowledge awareness and adaptive behaviors regarding heat wave are at a moderate level. It is suggested to strengthen health education, reinforce risk cognition of heat wave, and promote positive adaptive behaviors among food delivery riders.

Blood standardization is a crucial means of promoting the healthy and sustainable development of China's blood industry. The construction of a blood standard system serves as the foundational work for blood standardization. To facilitate the continuous improvement of blood standardization efforts, this paper begins by describing the current status and analyzing the issues within China's blood standard system. Through systematic research, it proposes a framework for constructing a blood standard system and offers revision recommendations for its enhancement. Based on the first five editions of the blood standard system developed by Sub-Committee of Blood Standards of National Committee of Health Standards, this study further refines the revision and detailed construction of the standards framework—the primary task in establishing the blood standard system. It provides specific guidance for both the construction and application of the blood standard system. This work serves as a reference and basis for the reasonable and standardized formulation and revision of blood standards, as well as for the management and implementation of blood standardization efforts.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

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.

The conversion of abundant and low-cost biomass waste into highly efficient two-electron oxygen reduction(ORR)electrocatalyst is an important link in the degradation of pollutants in industrial wastewater through the electro-Fenton process.In this work,porous biocarbon materials doped with manganese and nitrogen(MnNBC)were prepared from corn stalk.The H2O2 selectivity of MnNBC in acidic media was up to 81% @0.6 Vvs RHE,also MnNBC exhibited a long-term stability in a 10-h uninterrupted lifetime test.The ORR activity of MnNBC could be attributed to the synergistic effect of the hierarchical porous structure,improved defect level and heteroatom doping.Moreover,MnNBC as a cathode material for the electro-Fenton system could completely degrade four kinds of common organic dye pollutants,e.g.,Rhodamine B,methyl orange,methylene blue and crystal violet(25 mg/L),respectively,within 40?60 min.The present study provided valuable insights into the transformation of corn stalk waste into efficient cathode materials for the electro-Fenton process.

An effective method for simultaneously detecting four semivolatile earthy-musty odors in freshwater fish by gas chromatography-mass spectrometry(GC-MS)was developed.The concurrent extraction of geosmin(GSM),2-methylisoborneol(MIB),2-isopropyl-3-methoxypyrazine(IPMP),and 2-isobutyl-3-methoxypyrazine(IBMP)in fish tissue was conducted with n-hexane.The optimized QuEChERS material was implemented,and it was found that C18,primary secondary amine(PSA)and MgSO4 could adsorb the target analytes in n-hexane.So only the graphitized carbon black(GCB)could be used to purify the extraction.The adsorption rates of different materials for the four kinds of odors materials were explored in n-hexane and ethyl acetate.The experimental results revealed that the adsorption rates of silica for the four targets were 99.5%-100%in n-hexane and 0.7%-5.0%in ethyl acetate respectively.Then the silica solid phase extraction(SPE)method was utilized to eluent the compounds using 1.0 mL n-hexane/ethyl acetate in different proportions.The results of the comparative analysis demonstrated that n-hexane/ethyl acetate(4∶1,V/V)was the optimized eluent.Based on the obtained results,n-hexane extraction and GCB purification combined with silica SPE were used to isolate GSM,MIB,IPMP and IBMP from fish and the method was validated.It was found that the method showed good linearity in the range of 0.5-200 ng/mL,and with detection limits of 0.6 μg/kg for GSM and MIB,0.2 μg/kg for IPMP and IBMP.The limits of quantitation(LOQ)were 1.0 μg/kg for GSM and MIB,0.6 μg/kg for IPMP and IBMP.Good recoveries(77.5%-112.0%)and relative standard deviations(1.56%-9.42%)were also obtained.The use of silica SPE greatly mitigated the issue that the off-flavor compounds were easily lost in the gas blowing concentration process.There was no cross contamination in this method because the sample pretreatments were conducted separately,which was different with the most commonly used HS-SPME method for detecting semi-volatile substances.The sensitivity of this method was high enough to produce good quantitative results below the odor thresholds of the examined off-flavor compounds.

Under the background of forensic medicine becoming a first-level discipline,the opportuni-ties and challenges of discipline development coexist.Starting from the actual situation and characteris-tics of local medical colleges and universities,this paper discusses the problems and solutions for the development of forensic medicine discipline from the perspective of building a regional high-level medical university.Combined with the experiences of carrying out forensic medicine education in our college,this paper supplies our thoughts and practices on improving the discipline system,enhancing the ability to serve society,perfecting the talent cultivation model and promoting forensic culture,to provide reference and inspiration for the development of forensic medicine in other universities,jointly promote the advancement of forensic medicine in China to a new stage,and contribute the wisdom and strength of forensic medical experts to the construction of a law-based China,a safe China and a healthy China.

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.