AIM:To investigate the associations of triglyceride glucose(TyG)index, triglyceride glucose-body mass index(TyG-BMI), and homeostatic model assessment of insulin resistance(HOMA-IR)with diabetic retinopathy(DR), and to evaluate their diagnostic value.METHODS: This study was a single-center retrospective study. Patients with type 2 diabetes mellitus(T2DM)who were hospitalized in the endocrinology department of 3201 Hospital from January 1, 2023 to March 1, 2025 were included. According to the diagnostic criteria for DR, participants were classified into DR group and non-DR(NDR)group. Then the association of TyG index, TyG-BMI, and HOMA-IR index with DR of the two groups of patients were alalyzed.RESULTS:A total of 969 patients with T2DM were enrolled in this study, including 816 patients in the DR group. Among DR group, 271 were males(33.2%)and 545 were females(66.8%), with a mean age of 56.78±11.88 years. The NDR group consisted of 153 patients, including 41 males(26.8%)and 112 females(73.2%), with a mean age of 59.40±10.52 years. Statistically significant differences were observed between the DR group and the NDR group in terms of age, BMI, TyG index, TyG-BMI, HOMA-IR index, fasting blood glucose(FBG), 2-h postprandial blood glucose(2 hPBG), fasting insulin(FINS), 2-h postprandial insulin(2 hPINS), fasting C-peptide(FCP), 2-h postprandial C-peptide(2 hPCP), total cholesterol(CHO), triglyceride(TG), low-density lipoprotein(LDL-C), blood urea nitrogen(BUN), uric acid(UA), direct bilirubin(DBIL), glycated hemoglobin(HbA1c), milligrams per total protein(M-TP), microalbuminuria(MALB), urinary albumin to creatinine ratio(UACR), 24-hour urine protein, white blood cell(WBC), neutrophil(N), and platelets(PLT; all P<0.05), while no significant differences were found in the remaining indicators(all P>0.05). In multivariable Logistic regression, both TyG index(aOR=198.65, 95% CI: 66.73-591.41, P<0.001)and TyG-BMI(aOR=1.03, 95% CI: 1.02-1.04, P<0.001)remained independently positive associated with DR. Quartile analysis indicated a progressive increase in DR risk with ascending quartiles of TyG index and TyG-BMI(all Ptrend<0.001). In contrast, HOMA-IR was not significantly associated with DR. Restricted cubic spline analysis, fully adjusted for confounders, showed a nonlinear upward trend in DR risk with increasing TyG index(Pnonlinearity<0.001), whereas TyG-BMI exhibited a U-shaped association(Pnonlinearity<0.05). No significant association was found between HOMA-IR and DR after propensity score matching. Receiver operating characteristic(ROC)curve demonstrated area under curve(AUC)values of 0.870(95% CI: 0.839-0.901)for TyG index, 0.710(95% CI: 0.665-0.755)for TyG-BMI, and 0.657(95% CI: 0.608-0.706)for HOMA-IR.CONCLUSION:The TyG index and TyG-BMI are risk factors for DR. A dose-dependent increase in DR risk was associated with elevated TyG index values. TyG-BMI exhibited an inverted U-shaped relationship with DR risk. The TyG index had better diagnostic efficiency for DR compared to both TyG-BMI and HOMA-IR index.

The frequent extreme climatic events post multifaceted impacts on the distribution of Oncomelania hupensis, the intermediate host of Schistosoma japonicum in the context of global climate change. This article systematically reviews the effects of four types of extreme climatic events, including floods, droughts, heat waves, and cold waves, on the survival, reproduction, and distribution of Oncomelania hupensis. Floods may expand suitable snail habitats, and increase both emerging and re-emerging snail habitats; however, the impact of floods on O. hupensis density is characterized by a lag effect of a decline followed by a rise. Droughts may cause fragmentation of suitable O. hupensis snail habitats, reduced O. hupensis snail egg production rates, and increased O. hupensis snail mortality, and heat waves may cause an increase in O. hupensis snail mortality, a reduction in numbers of O. hupensis snail populations and shrinking of O. hupensis snail distribution, while cold waves may cause a reduction in O. hupensis snail density and a rise in O. hupensis snail mortality. Extreme climate events pose both shortand long-term effects on the distribution of O. hupensis. Intensified surveillance of O. hupensis snails is required in high-risk environments.

With the rapid development of the biopharmaceutical field, the efficient and simultaneous extraction of multiple biological components from biological samples has become a critical process for advancing scientific research. The ability to simultaneously extract various molecular components such as metabolites, DNA, RNA, and proteins is pivotal for multi-omics studies, which aim to comprehensively understand the molecular mechanisms of biological systems. Traditional methods often extract these components separately, leading to challenges such as sample loss, time consumption, contamination, and inconsistencies across different data types. In contrast, simultaneous extraction techniques address these issues by maintaining the consistency of each biological component’s physiological state, improving data reliability and facilitating integration across omic platforms. This review systematically summarizes recent advances in simultaneous extraction technologies, focusing on methods such as methanol/chloroform extraction, TRIzol reagent extraction, and modified Folch extraction, which have shown significant promise in improving the efficiency and integrity of biological sample preparation. These methods offer various advantages, such as reduced sample volume requirements, decreased contamination risk, and enhanced extraction consistency, which are crucial for studies involving small sample sizes or precious clinical specimens. Among these, methanol/chloroform extraction stands out for its simplicity, low cost, and ability to extract a wide range of biological molecules. However, it does face limitations, such as its inefficiency in extracting lipids and potential RNA contamination. On the other hand, the TRIzol reagent method has become a widely adopted technique due to its ability to simultaneously isolate RNA, proteins, and metabolites from the same sample. Despite its effectiveness, the TRIzol method has limitations in RNA quality, especially when handling complex samples or those with high protein content. Modified Folch extraction, which combines liquid-liquid extraction with commercial kits, offers a highly efficient way to extract polar metabolites, lipids, RNA, DNA, and proteins from small tissue samples. This method has proven advantageous in terms of extraction yield, especially for challenging or rare samples, although it requires precise handling to avoid cross-contamination between phases. The integration of automated platforms, microfluidics, and high-throughput systems is another exciting avenue for improving simultaneous extraction. Automation facilitates large-scale, reproducible sample processing with minimal human error, while microfluidics provides high precision in sample handling and enables real-time monitoring of extraction efficiency. These innovations not only enhance the speed and reproducibility of sample preparation but also open new possibilities for single-cell analysis, where sample volumes are often limited, and extraction efficiency is critical. In addition to the technical aspects, the review also highlights the importance of optimizing extraction protocols for specific sample types, such as clinical tissues, plants, and microorganisms. For example, the challenge of extracting multiple components from cancer tissues, where sample degradation and contamination risks are high, can be mitigated by carefully selecting extraction reagents and minimizing sample handling steps. Similarly, in plant studies, where metabolite diversity is vast, the simultaneous extraction methods must be optimized to account for the unique composition of plant tissues, which often include complex secondary metabolites and cell wall components. Looking forward, the development of more efficient and standardized simultaneous extraction methods will be crucial for advancing multi-omics research. There is a growing need for protocols that can be tailored to specific research needs, ensuring both reproducibility and flexibility in diverse applications. Additionally, combining these extraction methods with high-resolution analytical techniques such as mass spectrometry and next-generation sequencing will further enhance the potential of multi-omics studies to provide comprehensive insights into biological systems. As these technologies continue to evolve, their application in personalized medicine, environmental research, and agriculture holds great promise for addressing critical scientific challenges. In conclusion, while simultaneous extraction technologies have made significant strides, several challenges remain in optimizing extraction efficiency, ensuring reproducibility, and reducing costs. Future research should focus on refining extraction protocols, developing innovative extraction reagents, and expanding the scope of these methods to cater to a broader range of biological samples. Ultimately, the continued integration of these advanced techniques will revolutionize the way biological samples are prepared, analyzed, and understood in the context of multi-omics research.

With the rapid development of the biopharmaceutical field, the efficient and simultaneous extraction of multiple biological components from biological samples has become a critical process for advancing scientific research. The ability to simultaneously extract various molecular components such as metabolites, DNA, RNA, and proteins is pivotal for multi-omics studies, which aim to comprehensively understand the molecular mechanisms of biological systems. Traditional methods often extract these components separately, leading to challenges such as sample loss, time consumption, contamination, and inconsistencies across different data types. In contrast, simultaneous extraction techniques address these issues by maintaining the consistency of each biological component’s physiological state, improving data reliability and facilitating integration across omic platforms. This review systematically summarizes recent advances in simultaneous extraction technologies, focusing on methods such as methanol/chloroform extraction, TRIzol reagent extraction, and modified Folch extraction, which have shown significant promise in improving the efficiency and integrity of biological sample preparation. These methods offer various advantages, such as reduced sample volume requirements, decreased contamination risk, and enhanced extraction consistency, which are crucial for studies involving small sample sizes or precious clinical specimens. Among these, methanol/chloroform extraction stands out for its simplicity, low cost, and ability to extract a wide range of biological molecules. However, it does face limitations, such as its inefficiency in extracting lipids and potential RNA contamination. On the other hand, the TRIzol reagent method has become a widely adopted technique due to its ability to simultaneously isolate RNA, proteins, and metabolites from the same sample. Despite its effectiveness, the TRIzol method has limitations in RNA quality, especially when handling complex samples or those with high protein content. Modified Folch extraction, which combines liquid-liquid extraction with commercial kits, offers a highly efficient way to extract polar metabolites, lipids, RNA, DNA, and proteins from small tissue samples. This method has proven advantageous in terms of extraction yield, especially for challenging or rare samples, although it requires precise handling to avoid cross-contamination between phases. The integration of automated platforms, microfluidics, and high-throughput systems is another exciting avenue for improving simultaneous extraction. Automation facilitates large-scale, reproducible sample processing with minimal human error, while microfluidics provides high precision in sample handling and enables real-time monitoring of extraction efficiency. These innovations not only enhance the speed and reproducibility of sample preparation but also open new possibilities for single-cell analysis, where sample volumes are often limited, and extraction efficiency is critical. In addition to the technical aspects, the review also highlights the importance of optimizing extraction protocols for specific sample types, such as clinical tissues, plants, and microorganisms. For example, the challenge of extracting multiple components from cancer tissues, where sample degradation and contamination risks are high, can be mitigated by carefully selecting extraction reagents and minimizing sample handling steps. Similarly, in plant studies, where metabolite diversity is vast, the simultaneous extraction methods must be optimized to account for the unique composition of plant tissues, which often include complex secondary metabolites and cell wall components. Looking forward, the development of more efficient and standardized simultaneous extraction methods will be crucial for advancing multi-omics research. There is a growing need for protocols that can be tailored to specific research needs, ensuring both reproducibility and flexibility in diverse applications. Additionally, combining these extraction methods with high-resolution analytical techniques such as mass spectrometry and next-generation sequencing will further enhance the potential of multi-omics studies to provide comprehensive insights into biological systems. As these technologies continue to evolve, their application in personalized medicine, environmental research, and agriculture holds great promise for addressing critical scientific challenges. In conclusion, while simultaneous extraction technologies have made significant strides, several challenges remain in optimizing extraction efficiency, ensuring reproducibility, and reducing costs. Future research should focus on refining extraction protocols, developing innovative extraction reagents, and expanding the scope of these methods to cater to a broader range of biological samples. Ultimately, the continued integration of these advanced techniques will revolutionize the way biological samples are prepared, analyzed, and understood in the context of multi-omics research.

Objective To assess the survival vulnerability of Oncomelania hupensis in Jiangxi Province under future climate scenarios, and to identify low-vulnerability areas for its survival in this province. Methods Village-level O. hupensis snail survey and O. hupensis snail control with chemical treatments in Jiangxi Province from 2016 to 2024 were captured from the Parasitic Disease Prevention and Control Information Management System of China Disease Prevention and Control Information System. Climatic data were primarily sourced from the Resource and Environmental Science Data Platform, Chinese Academy of Sciences (http://www.resdc.cn/), including annual average temperature, annual average precipitation, annual accumulated temperature above 10 °C, annual accumulated temperature above 0 °C, annual maximum temperature, annual minimum temperature, and annual average relative humidity, and nineteen bioclimatic variables were downloaded from the WorldClim website (https://www.worldclim.org/), including mean diurnal range, isothermality, temperature seasonality, and so on. Elevation and normalized difference vegetation index were catprued from the Resource and Environmental Science Data Platform, Chinese Academy of Sciences (http://www.resdc.cn/), and distance to rivers was downloaded from the WorldPop website (http://www.worldpop.org), and land use and land cover (LULC) data were downloaded from the Big Earth Data Center, Chinese Academy of Sciences (https://data.casearth.cn/), and nature reserve data were obtained from the China Nature Reserve Specimen Resource Sharing Platform (http://www.papc.cn/). Three Shared Socioeconomic Pathways (SSPs) from the Beijing Climate Center-Climate System Model version 2-Medium Resolution (BCC-CSM2-MR) global climate model were employed as future climate scenarios, including SSP126, SSP245, SSP585, and the biomod2 ensemble model in R package was used to simulate suitable habitats for O. hupensis snails in Jiangxi Province in 2050 and 2070 under these scenarios. A snail survival vulnerability index was constructed based on the area of suitable snail habitats, area covered by snail control through chemical treatment, area covered by nature reserves, and changes in snail habitat fragmentation, and a map of snail survival vulnerability distribution was plotted. Results The real area of snail habitats ranged from 78 486.76 to 85 309.47 hm², and the area of snail control with chemical treatment ranged from 10 138.98 to 13 240.16 hm² in Jiangxi Province from 2016 to 2024. There were 429 to 531 villages detected with snails during the nine-year period, and the number of actually snail-infested villages ranged from 645 to 686. A total of 818 snail-present points and 1 996 snail-absent points were obtained from snail survey records. The best performance of the biomod2 ensemble model was achieved if a weighted mean approach was used as the ensemble strategy, with a true skill statistic value of 0.799 and an area under the receiver operating characteristic curve of 0.957, and modeling identified annual average relative humidity and annual average precipitation as two most influencing climatic variables for snail distribution. Relative to the current areas of suitable snail habitats under present climate conditions, the area of suitable snail habitats was projected to expand by 24.49% to 46.28% in Jiangxi Province under future climate scenarios, and the proportion of nature reserves areas in the areas of suitable snail habitats was projected to decrease slightly from the current 2.77% to approximately 2.52%, while the proportion of areas of snail control through chemical treatment in areas of suitable snail habitats varied from 0.64% to 19.57%, and the percentage of changes in snail habitat fragmentation ranged from 3.86% to 12.23%. Based on these four indicators, the snail survival vulnerability index was estimated to range from –1.96 to 0.62 in Jiangxi Province. The arithmetic mean of the snail survival vulnerability index differed under three SSP scenarios (SSP126, SSP245 and SSP585), with the highest mean value (–0.69) in 2070 under SSP126, and the lowest mean value (–0.78) in 2070 under SSP585. Conclusions The snail survival vulnerability index ranges from –1.96 to 0.62 in Jiangxi Province under future climate scenarios, and the suitable habitats for O. hupensis snails appear an overall tendency towards expansion. Low-vulnerability snail habitats are mainly distributed along the shores of Poyang Lake and the Yangtze River in Jiangxi Province, partially overlapping with nature reserves. Intensified surveillance of O. hupensis snails is recommended in these areas in the future.

Objective: To analyze the results of national external quality assessment (EQA) for transfusion compatibility test from 2018 to 2023, with the aim of providing references for improving laboratory testing quality and ensuring the safety of clinical blood transfusion. Methods: Three EQA programs were conducted annually, each distributing 22 quality assessment samples. Participating transfusion laboratories were required to complete testing within specified deadlines and to submit results along with documentation of testing methodologies, reagents, and equipment used. National Center for Clinical Laboratories (NCCL) conducted statistical analysis of laboratory results, evaluated testing outcomes and related circumstances, and provided feedback to participating laboratories. EQA data from transfusion laboratories across China from 2018 to 2023 were collected and systematically analyzed. Results: From 2018 to 2023, the qualification rates for all five items (ABO forward typing, ABO reverse typing, Rh blood group typing, antibody screening, and cross-matching) were 67.59%, 77.11%, 77.38%, 72.78%, 79.96%, and 85.16%, respectively. The mean qualification rates for ABO forward typing, ABO reverse typing, RhD blood group typing, antibody screening, and cross-matching over the past six years were 96.25%±0.59%, 90.45%±4.52%, 96.05%±0.71%, 90.88%±2.86%, and 88.34%±3.48%, respectively. The qualification rates in 2019, 2020, 2022, and 2023 all showed a stable trend of "blood stations>tertiary hospitals>secondary hospitals". The mean qualification rate of laboratories in secondary hospitals from 2018 to 2023 was significantly lower than those of laboratories in tertiary hospitals and blood stations (P<0.05), while no significant difference was observed between laboratories in tertiary hospitals and blood stations (P>0.05). The micro column agglutination method was the most widely used in all five tests. In the four test items, namely ABO forward typing, ABO reverse typing, antibody screening, and cross-matching, there was a statistically significant difference in the qualification rate of micro column agglutination method compared to other methods (P<0.05). There was a statistical difference in the qualification rate between manual and automated detection using micro column agglutination method in the cross-matching tests (P<0.05), whereas no significant difference was noted for the other test items (P>0.05). Conclusion: From 2018 to 2023, the number of laboratories participating in EQA activities has been increasing year by year, and the qualification rate has shown an overall upward trend. The type of laboratory is a key factor affecting the qualification rate, and the testing capabilities of some laboratories still need to be improved. The micro column agglutination method is widely used in transfusion compatibility tests. The established EQA program effectively monitors quality issues in laboratories, drives continuous improvement, and ensures sustained enhancement of testing standards to safeguard clinical blood safety.

Disruption of the intestinal mucosal barrier caused by gut dysbiosis and metabolic imbalance is the underlying pathology of inflammatory bowel disease (IBD). Traditional Chinese medicine Wuji Wan (WJW) is commonly used to treat digestive system disorders and showed therapeutic potential for IBD. In this interdisciplinary study, we aim to investigate the pharmacological effects of WJW against experimental colitis by combining functional metabolomics and gut-microbiota sequencing techniques. Treatment with WJW altered the profile of the intestinal microbiota and notably increased the abundance of Lactobacillus, thereby facilitating the conversion of tryptophan into indole-3-acetic acid (IAA) and indoleacrylic acid (IA). These indole derivatives activated the aryl hydrocarbon receptor (AhR) pathway, which reduced colonic inflammation and restored the expression of intestinal barrier proteins. Interestingly, the beneficial effects of WJW on gut barrier function improvement and tryptophan metabolism were disappeared in the absence of gut microbiota. Finally, pre-treatment with the AhR antagonist CH-223191 confirmed the essential role of IAA-mediated AhR activation in the therapeutic effects of WJW. Overall, WJW enhanced intestinal barrier function and reduced colonic inflammation in a murine colitis model by modulating Lactobacillus-IAA-AhR signaling pathway. This study provides novel insights into colitis pathogenesis and presents an effective therapeutic and preventive approach against IBD.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To analyze the epidemiological characteristics and changing trends of non suicidal self injury (NSSI) behaviors among middle school students in Jiading District of Shanghai, from 2015 to 2023, so as to provide a basis for the development of NSSI prevention and control measures among students. Methods: Using a stratified cluster random sampling method, a total of five times for Shanghai Adolescent Health Risk Behavior Surveys were conducted for every two years in Jiading District of Shanghai from 2015 to 2023. A total of 5 231 middle school students from junior high schools and senior high schools were selected for questionnaire surveys. Intergroup comparisons were performed using the x 2 test or the χ 2 trend test, and the JointPoint 5.0 software was used to analyze the changing trends, with the annual percent change (APC) used for evaluation. A binary Logistic regression model was employed to analyze the related factors of NSSI behavior among middle school students. Results: In 2023, the reported NSSI rate among middle school students in Jiading District was 14.2%. The rate was significantly higher among junior high school students (17.1%) than that among senior high school students (11.1%), and higher among females (19.2%) than that among males (10.0%) ( χ 2=10.04, 23.21, both P <0.01). From 2015 to 2023, the overall reported NSSI rate showed an increasing trend, rising from 8.6% in 2015 to 14.2% in 2023 ( χ 2 trend =22.25), with an APC of 6.64% ( t =3.49), and the APC for girls was 9.79 % ( t =3.20) (all P <0.05). Among students reporting NSSI, the proportion experiencing ≥6 episodes increased from 10.8% in 2015 to 19.2% in 2023 ( χ 2 trend =6.57, P <0.05). Multivariate Logistic regression analysis indicated that girls, junior high school students, those with insomnia, depressive emotion and drinkers had higher risks of NSSI, compared to boys, senior high school students, those without insomnia, non depressive emotion students and non drinkers ( OR =1.71, 1.96, 3.44, 4.76, 1.77, all P < 0.05 ). Conclusions The reported rate of NSSI among middle school students in Jiading District of Shanghai, increased annually from 2015 to 2023, and the proportion of repeated NSSI also showed an upward trend. Early intervention measures targeting middle school students, especially junior high school students and females, should be implemented to prevent and control its occurrence and development.