The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

ObjectiveTo develop a nomogram-based risk prediction model for chronic obstructive pulmonary disease (COPD) incidence among the community-dwelling population aged 40 years old and above, so as to provide targeted references for the screening and prevention of COPD. MethodsBased on a natural population cohort in suburban Shanghai, a total of 3 381 randomly selected participants aged ≥40 years underwent pulmonary function tests between July and October 2021. Cox stepwise regression analysis was used to develop overall and gender-specific risk prediction models, along with the construction of corresponding risk nomograms. Model predictive performance was evaluated using the C-indice, area under the curve (AUC) values, and Brier score. Stability was assessed through 10-fold cross-validation and sensitivity analysis. ResultsA total of 3 019 participants were included, with a median follow-up duration of 4.6 years. The COPD incidence density was 17.22 per 1 000 person-years, significantly higher in males (32.04/1 000 person-years) than that in females (7.38/1 000 person-years) (P<0.001). The overall risk prediction model included the variables such as gender, age, education level, BMI, smoking, passive smoking, and respiratory comorbidities. The male-specific model incorporated the variables such as age, BMI, respiratory comorbidities, and smoking, while the female-specific model included age, marital status, respiratory comorbidities, and pulmonary tuberculosis history. The C-indices for the overall, male-specific, and female-specific models were 0.829, 0.749, and 0.807, respectively. The 5-year AUC values were 0.785, 0.658, and 0.811, with Brier scores of 0.103, 0.176, and 0.059, respectively. Both 10-fold cross-validated C-indices and sensitivity analysis (excluding participants with a follow-up duration of <6 months) yielded C-indices were above 0.740. ConclusionThis study developed concise and practical overall and gender-specific COPD risk prediction models and corresponding nomograms. The models demonstrated robust performance in predicting COPD incidence, providing a valuable reference for identifying high-risk populations and formulating targeted screening and personalized management strategies.

This study explored the drying kinetics of Salviae Miltiorrhizae Radix et Rhizoma(SM), established the suitable models simulating the drying kinetics, and then analyzed the dynamic changes of active components during the drying processes with different methods, aiming to provide a basis for the establishment of suitable drying methods and the quality control of SM. The drying kinetics were studied based on the drying curve, drying rate, moisture effective diffusion coefficient, and drying activation energy, and the appropriate drying kinetics model of SM was established. The drying performance of different methods, such as hot air drying, infrared drying, and microwave drying of SM was evaluated, and the changes in the content of 10 salvianolic acids and 6 tanshinones during drying were analyzed by UPLC-TQ-MS. The Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS) was employed to evaluate the quality of SM dried with different methods. The results showed that the drying rate and moisture effective diffusion coefficient of SM increased with the rise in drying temperature, and the maximum drying rates of different methods were in the order of microwave drying > infrared drying > hot air drying, slice > whole root. The drying rate decreased with the rise in temperature and the extension of drying time. The activation energy of hot air drying was higher than that of infrared drying in SM. The most suitable model for simulating the drying process of SM was the Page model. The TOPSIS results suggested infrared drying at 50 ℃ was the optimal drying method for SM. During the drying process, the content of salvianolic acids increased in different degrees with the loss of moisture, among which salvianolic acid B showed the largest increase of 44 times compared with that in the fresh medicinal material. Tanshinones also existed in the fresh herb of SM, and the content of tanshinone Ⅱ_A increased by 3 times after drying. The results provided a basis for the establishment of suitable drying methods and the quality control of SM.
Salvia miltiorrhiza/chemistry* ; Desiccation/methods* ; Drugs, Chinese Herbal/chemistry* ; Rhizome/chemistry* ; Kinetics ; Quality Control ; Abietanes

This study investigates the mechanism by which Xintong Granules improve myocardial ischemia-reperfusion injury(MIRI) through the regulation of gut microbiota and their metabolites, specifically short-chain fatty acids(SCFAs). Rats were randomly divided based on body weight into the sham operation group, model group, low-dose Xintong Granules group(1.43 g·kg~(-1)·d~(-1)), medium-dose Xintong Granules group(2.86 g·kg~(-1)·d~(-1)), high-dose Xintong Granules group(5.72 g·kg~(-1)·d~(-1)), and metoprolol group(10 mg·kg~(-1)·d~(-1)). After 14 days of pre-administration, the MIRI rat model was established by ligating the left anterior descending coronary artery. The myocardial infarction area was assessed using the 2,3,5-triphenyltetrazolium chloride(TTC) staining method. Apoptosis in tissue cells was detected by the terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling(TUNEL) assay. Pathological changes in myocardial cells and colonic tissue were observed using hematoxylin-eosin(HE) staining. The levels of tumor necrosis factor-α(TNF-α), interleukin-1β(IL-1β), interleukin-6(IL-6), creatine kinase MB isoenzyme(CK-MB), and cardiac troponin T(cTnT) in rat serum were quantitatively measured using enzyme-linked immunosorbent assay(ELISA) kits. The activities of lactate dehydrogenase(LDH), creatine kinase(CK), and superoxide dismutase(SOD) in myocardial tissue, as well as the level of malondialdehyde(MDA), were determined using colorimetric assays. Gut microbiota composition was analyzed by 16S rDNA sequencing, and fecal SCFAs were quantified using gas chromatography-mass spectrometry(GC-MS). The results show that Xintong Granules significantly reduced the myocardial infarction area, suppressed cardiomyocyte apoptosis, and decreased serum levels of pro-inflammatory cytokines(TNF-α, IL-1β, and IL-6), myocardial injury markers(CK-MB, cTnT, LDH, and CK), and oxidative stress marker MDA. Additionally, Xintong Granules significantly improved intestinal inflammation in MIRI rats, regulated gut microbiota composition and diversity, and increased the levels of SCFAs(acetate, propionate, isobutyrate, etc.). In summary, Xintong Granules effectively alleviate MIRI symptoms. This study preliminarily confirms that Xintong Granules exert their inhibitory effects on MIRI by regulating gut microbiota imbalance and increasing SCFA levels.
Animals ; Gastrointestinal Microbiome/drug effects* ; Rats ; Male ; Myocardial Reperfusion Injury/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Apoptosis/drug effects* ; Humans ; Tumor Necrosis Factor-alpha/metabolism* ; Interleukin-6/genetics* ; Malondialdehyde/metabolism*

This study aims to explore the effects and action mechanisms of the active ingredients in Buyang Huanwu Decoction(BYHWD), namely tetramethylpyrazine(TMP) and hydroxy-safflor yellow A(HSYA), on oxygen-glucose deprivation/reglucose-reoxygenation(OGD/R)-induced inflammation and oxidative stress of microglia(MG). Network pharmacology was used to screen the effective monomer ingredients of BYHWD and determine the safe concentration range for each component. Inflammation and oxidative stress models were established to further screen the best ingredient combination and optimal concentration ratio with the most effective anti-inflammatory and antioxidant effects. OGD/R BV2 cell models were constructed, and BV2 cells in the logarithmic growth phase were divided into a normal group, a model group, an HSYA group, a TMP group, and an HSYA + TMP group. Enzyme-linked immunosorbent assay(ELISA) was used to detect the levels of inflammatory cytokines such as interleukin-1β(IL-1β), tumor necrosis factor-α(TNF-α), and interleukin-6(IL-6). Oxidative stress markers, including superoxide dismutase(SOD), nitric oxide(NO), and malondialdehyde(MDA), were also measured. Western blot was used to analyze the protein expression of both inflammation-related pathway [Toll-like receptor 4(TLR4)/nuclear factor-kappa B(NF-κB)] and oxidative stress-related pathway [nuclear factor erythroid 2-related factor 2(Nrf2)/heme oxygenase-1(HO-1)]. Immunofluorescence was used to assess the expression of proteins such as inducible nitric oxide synthase(iNOS) and arginase-1(Arg-1). The most effective ingredients for anti-inflammatory and antioxidant effects in BYHWD were TMP and HSYA. Compared to the normal group, the model group showed significantly increased levels of IL-1β, TNF-α, IL-6, NO, and MDA, along with significantly higher protein expression of NF-κB, TLR4, Nrf2, and HO-1 and significantly lower SOD levels. The differences between the two groups were statistically significant. Compared to the model group, both the HSYA group and the TMP group showed significantly reduced levels of IL-1β, TNF-α, IL-6, NO, and MDA, lower expression of NF-κB and TLR4 proteins, higher levels of SOD, and significantly increased protein expression of Nrf2 and HO-1. Additionally, the expression of the M1-type MG marker iNOS was significantly reduced, while the expression of the M2-type MG marker Arg-1 was significantly increased. The results of the HSYA group and the TMP group had statistically significant differences from those of the model group. Compared to the HSYA group and the TMP group, the HSYA + TMP group showed further significant reductions in IL-1β, TNF-α, IL-6, NO, and MDA levels, along with significant reductions in NF-κB and TLR4 protein expression, an increase in SOD levels, and elevated Nrf2 and HO-1 protein expression. Additionally, the expression of the M1-type MG marker iNOS was reduced, while the M2-type MG marker Arg-1 expression increased significantly in the HSYA + TMP group compared to the TMP or HSYA group. The differences in the results were statistically significant between the HSYA + TMP group and the TMP or HSYA group. The findings indicated that the combined use of HSYA and TMP, the active ingredients of BYHWD, can effectively inhibit OGD/R-induced inflammation and oxidative stress of MG, showing superior effects compared to the individual use of either component.
Oxidative Stress/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Animals ; Mice ; Glucose/metabolism* ; Cell Line ; Inflammation/genetics* ; Oxygen/metabolism* ; Pyrazines/pharmacology* ; Microglia/metabolism* ; NF-E2-Related Factor 2/immunology* ; NF-kappa B/immunology* ; Toll-Like Receptor 4/immunology* ; Anti-Inflammatory Agents/pharmacology* ; Humans

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

This study aimed to comprehensively examine the association of gallstones, cholecystectomy, and cancer risk. Multivariable logistic regressions were performed to estimate the observational associations of gallstones and cholecystectomy with cancer risk, using data from a nationwide cohort involving 239 799 participants. General and gender-specific two-sample Mendelian randomization (MR) analysis was further conducted to assess the causalities of the observed associations. Observationally, a history of gallstones without cholecystectomy was associated with a high risk of stomach cancer (adjusted odds ratio (aOR)=2.54, 95% confidence interval (CI) 1.50-4.28), liver and bile duct cancer (aOR=2.46, 95% CI 1.17-5.16), kidney cancer (aOR=2.04, 95% CI 1.05-3.94), and bladder cancer (aOR=2.23, 95% CI 1.01-5.13) in the general population, as well as cervical cancer (aOR=1.69, 95% CI 1.12-2.56) in women. Moreover, cholecystectomy was associated with high odds of stomach cancer (aOR=2.41, 95% CI 1.29-4.49), colorectal cancer (aOR=1.83, 95% CI 1.18-2.85), and cancer of liver and bile duct (aOR=2.58, 95% CI 1.11-6.02). MR analysis only supported the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer. This study added evidence to the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer, highlighting the importance of cancer screening in individuals with gallstones.
Humans ; Mendelian Randomization Analysis ; Gallstones/complications* ; Female ; Male ; Cholecystectomy/statistics & numerical data* ; Middle Aged ; Risk Factors ; Aged ; Adult ; Neoplasms/etiology* ; Stomach Neoplasms/epidemiology*

OBJECTIVE: To develop and validate a nomogram model for predicting 30-day mortality among elderly patients with sepsis-associated liver dysfunction (SALD), to identify high-risk patients and improve prognosis. METHODS: A retrospective cohort study was conducted using data extracted from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database for elderly patients with SALD who were first admitted to the intensive care unit (ICU) of Beth Israel Deaconess Medical Center between 2008 and 2019, including basic characteristics, severity scores, underlying diseases, infection foci, 24-hour vital signs, initial laboratory indicators, 24-hour complications, and prognosis related indicators. Patients were randomly assigned to training group and validation group in a ratio of 7 : 3. The training group used the LASSO regression analysis, as well as multivariate Logistic regression analysis to screen for independent risk factors for 30-day mortality. A nomogram prediction model was constructed, and receiver operator characteristic curve (ROC curve), calibration curves, and decision curve analysis (DCA) were used to evaluate the model, and validate the model using the validation cohort. RESULTS: A total of 630 elderly patients with SLAD were included in the study, including 441 in the training group and 189 in the validation group. Oxford acute severity of illness score (OASIS) for training group [odds ratio (OR) = 1.060, 95% confidence interval (95%CI) was 1.034-1.086], 24-hour pulse oxygen saturation (SpO₂; OR = 0.876, 95%CI was 0.797-0.962), initial mean corpuscular volume (MCV; OR = 1.043, 95%CI was 1.009-1.077), initial red blood cell distribution width (RDW; OR = 1.237, 95%CI was 1.123-1.362), initial blood glucose (OR = 1.008, 95%CI was 1.004-1.013), and initial aspartate aminotransferase (AST; OR = 1.000, 95%CI was 1.000-1.001) were independent risk factors for 30-day mortality in patients (all P < 0.05). Based on the above variables, a nomogram model was constructed, and the ROC curve showed that the area under the curve (AUC) of the model in the training group was 0.757 (95%CI was 0.712-0.803), with a sensitivity of 65.05% and a specificity of 74.90%; the AUC of the model in the validation group was 0.712 (95%CI was 0.631-0.792), with a sensitivity of 58.67% and a specificity of 81.58%. The calibration curves of the training and validation groups show that both the fitted curves were close to the standard curves. The Hosmer-Lemeshow test: the training group (χ ² = 6.729, P = 0.566), the validation group (χ ² = 13.889, P = 0.085), indicating that the model can fit the observed data well. The DCA curve shows that when the threshold probability of the training group was 16% to 94% and the threshold probability of the validation group was 27% to 99%, the net benefit of the model was good. CONCLUSIONS OASIS, 24-hour SpO₂, initial MCV, initial RDW, initial blood glucose and initial AST are independent risk factors for 30-day mortality in elderly patients with SALD. The nomogram based on these six variables demonstrates good predictive performance.
Humans ; Sepsis/complications* ; Retrospective Studies ; Nomograms ; Aged ; Prognosis ; Risk Factors ; Liver Diseases/mortality* ; Intensive Care Units ; ROC Curve ; Male ; Female ; Logistic Models

As global greenhouse gases continue rising, the urgency of more ambitious action is clearer than ever before. China is the world's biggest emitter of greenhouse gases and one of the countries affected most by climate change. The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts. This article aimed to review the evidence of environmental damages and health risks posed by climate change and to provide a new science-based perspective for the delivery of sustainable development goals. Over recent decades, China has experienced a strong warming pattern with a growing frequency of extreme weather events, and the impacts of climate change on China's environment and human health have been consistently observed, with increasing O ₃ air pollution, decreases in water resources and availability, land degradation, and increased risks for both communicable and non-communicable diseases. Therefore, China's climate policy should target the key factors driving climate change and scale up strategic measures to curb carbon emissions and adapt to inevitable increasing climate impacts. It provides new insights for not only China but also other countries, particularly developing and emerging economies, to ensure climate and environmental sustainability whilst pursuing economic growth.
Climate Change ; China ; Humans ; Greenhouse Gases ; Air Pollution ; Sustainable Development ; Environment