OBJECTIVE To establish a content determination method for multiple components in Sophora flavescens from different origins and to evaluate its quality by combining with chemometrics. METHODS Thirteen batches （No. K1-K13） of S. flavescens from different origins were selected as test samples. A high-performance liquid chromatography-tandem triple quadrupole mass spectrometry （HPLC-MS/MS） method was established to determine the contents of 12 components， including matrine， oxymatrine， betaine， cytisine， N-methylcytisine， sophoridine， genistein， sophoricoside， sophorone， formononetin， sophorolone Ⅰ and norkurarinone in S. flavescens. Chromatographic separation was performed on a Shim-pack GIST-HP C18 column with a mobile phase consisting of methanol （A） and water containing 0.1% formic acid （B）， using gradient elution at a flow rate of 0.25 mL/min， column temperature of 35 ℃， and an injection volume of 3 μL. Mass spectrometry was conducted using an electrospray ionization source with positive and negative ion scanning. Data were collected in segments using the multiple reaction monitoring mode. Technique for order preference by similarity to ideal solution （TOPSIS） and grey relational analysis （GRA）methods were employed to compare and comprehensively evaluate the 13 batches of S. flavescens from different origins. RESULTS The methodological validation for the content determination met the relevant regulatory requirements. The contents of the 12 components were 490.66-1 231.00， 11 088.10- 18 021.50， 7.91-25.38， 903.97-1 713.64， 336.08-1 485.54，1 065.33-2 075.50， 27.52-71.80， 109.36-517.83， 6 034.55-10 632.73， 21.26-145.35， 814.84-1 911.32， 1 040.87-3 446.37 μg/g）， respectively. TOPSIS results showed that the top 7 samples in Euclidean distance ranking were K6， K12， K11， K3， K5， K10， K13. The GRA results showed that the top 7 samples in the relative correlation ranking were K12， K11， K10， K6， K13， K5， K3. CONCLUSIONS The established HPLC-MS/MS method is rapid， accurate， highly sensitive， stable and reliable. Combined with chemometrics methods， it can be used for the quality control and evaluation of S. flavescens. The comprehensive quality of samples K3， K5， K6（ from Hebei）， K10（ from Sichuan）， K11-K13（ from Shanxi）， etc. is relatively superior.

[This corrects the article DOI: 10.1016/j.apsb.2022.05.019.].

Ursodeoxycholic acid (UDCA) is a naturally occurring, low-toxicity, and hydrophilic bile acid (BA) in the human body that is converted by intestinal flora using primary BA. Solute carrier family 7 member 11 (SLC7A11) functions to uptake extracellular cystine in exchange for glutamate, and is highly expressed in a variety of human cancers. Retroperitoneal liposarcoma (RLPS) refers to liposarcoma originating from the retroperitoneal area. Lipidomics analysis revealed that UDCA was one of the most significantly downregulated metabolites in sera of RLPS patients compared with healthy subjects. The augmentation of UDCA concentration (≥25 μg/mL) demonstrated a suppressive effect on the proliferation of liposarcoma cells. [¹⁵N₂]-cystine and [¹³C₅]-glutamine isotope tracing revealed that UDCA impairs cystine uptake and glutathione (GSH) synthesis. Mechanistically, UDCA binds to the cystine transporter SLC7A11 to inhibit cystine uptake and impair GSH de novo synthesis, leading to reactive oxygen species (ROS) accumulation and mitochondrial oxidative damage. Furthermore, UDCA can promote the anti-cancer effects of ferroptosis inducers (Erastin, RSL3), the murine double minute 2 (MDM2) inhibitors (Nutlin 3a, RG7112), cyclin dependent kinase 4 (CDK4) inhibitor (Abemaciclib), and glutaminase inhibitor (CB839). Together, UDCA functions as a cystine exchange factor that binds to SLC7A11 for antitumor activity, and SLC7A11 is not only a new transporter for BA but also a clinically applicable target for UDCA. More importantly, in combination with other antitumor chemotherapy or physiotherapy treatments, UDCA may provide effective and promising treatment strategies for RLPS or other types of tumors in a ROS-dependent manner.

OBJECTIVE: This study aimed to identify high-risk areas for type 2 diabetes mellitus (T2DM) mortality to provide relevant evidence for interventions in emerging economies. METHODS: Empirical Bayesian Kriging and a discrete Poisson space-time scan statistic were applied to identify the spatiotemporal clusters of T2DM mortality. The relationships between economic factors, air pollutants, and the mortality risk of T2DM were assessed using regression analysis and the Poisson Log-linear Model. RESULTS: A coastal district in East Guangdong, China, had the highest risk (Relative Risk [RR] = 4.58, P < 0.01), followed by the 10 coastal districts/counties in West Guangdong, China (RR = 2.88, P < 0.01). The coastal county in the Pearl River Delta, China (RR = 2.24, P < 0.01), had the third-highest risk. The remaining risk areas were two coastal counties in East Guangdong, 16 districts/counties in the Pearl River Delta, and two counties in North Guangdong, China. Mortality due to T2DM was associated with gross domestic product per capita (GDP per capita). In pilot assessments, T2DM mortality was significantly associated with carbon monoxide. CONCLUSION High mortality from T2DM occurred in the coastal areas of East and West Guangdong, especially where the economy was progressing towards the upper middle-income level.
Diabetes Mellitus, Type 2/epidemiology* ; China/epidemiology* ; Humans ; Risk Factors ; Spatio-Temporal Analysis ; Air Pollutants/analysis* ; Socioeconomic Factors ; Bayes Theorem ; Female ; Male ; Middle Aged

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

The rapid and non-destructive detection of constituent content of fresh tea leaves shows an important reference value for quality identification of tea.Visible near infrared(Vis-NIR)spectroscopy has been used for qualitative and quantitative analysis of chemical components in plant samples with the advantages such as simple,rapid and non-destructive detection.In this study,residual attention convolutional neural network(RACNN)was used to predict the internal constituent content of fresh tea leaves.Firstly,the reflectance spectral data of the samples in the Vis-NIR band range and the constituent contents of gallic acid(GA),gallocatechin(GC),epigallocatechin(EGC),and epigallocatechin gallate(ECG)in fresh tea leaves were collected.Based on the preprocessing of the spectral data,the contents of the four components were predicted using a partial least squares regression(PLSR)model,and the optimal preprocessing was determined.Subsequently,the characteristic bands were extracted using the random forest(RF)algorithm.Finally,the performances of PLSR,convolutional neural network(CNN)and RACNN models were compared.The results showed that for GA,the RACNN model worked best with a validation set coefficient of determination(R2)of 0.946 and a root mean square error of the prediction set(RMSEP)of 1.173;for GC,the RACNN model works best with a validation set R2 of 0.928 and RMSEP of 6.081;for EGC,the RACNN model works best with a validation set R2 of 0.891 and a RMSEP of 15.197;for ECG,the RACNN model worked best with a validation set R2 of 0.878 and a RMSEP of 7.837.The RACNN model established by Vis-NIR spectroscopy combined with chemometrics could realize the accurate detection of the contents of components in fresh tea.

Objective To investigate the diagnostic value of 4 novel inflammatory markers related to routine blood tests,namely neutrophil-to-lymphocyte ratio(NLR),red blood cell distribution width(RDW),hemoglobin-to-RDW ratio(HRR)and systemic immune-inflammation index(SII),in elderly patients with chronic cardiovascular disease(CVD)complicated with frailty.Methods Retrospectively analyze 110 patients with chronic stable CVD who were hospitalized in the cadre ward of cardiovascular medicine at the Air Force Characteristic Medical Center from January 2022 to June 2023.According to the assessment results of the Fried scale,they were divided into three groups:non-frailty group(Fried score=0,n=30),the pre-frailty group(Fried score 1 or 2,n=40)and frailty group(Fried score≥3,n=40).The differences in general information,the impairment rate of daily living activities,miniature nutritional assessment-short form(MNA-SF)scores,mini-mental state examination(MMSE)scores,and the indicators such as NLR,RDW,HRR,and SII among the three groups were compared.Spearman rank correlation was used to analyze the correlation between NLR,RDW,HRR,SII and frailty scores as well as each frailty indicator.Multivariate logistic regression analysis was performed to identify the independent risk factors for frailty in elderly patients with chronic CVD,and the receiver operating characteristic(ROC)curve was used to assess the clinical diagnostic value of NLR and HRR in elderly patients with chronic CVD complicated with frailty.Results Compared with non-frailty group and pre-frailty group,patients in frailty group were older,with higher impaired rates of daily living activities,NLR,RDW,and SII,and lower MNA-SF scores,MMSE scores,and HRR,and differences were statistically significant(P<0.05).Spearman rank correlation analysis showed that the frailty score was positively correlated with NLR(rs=0.354,P<0.001),and RDW(rs=0.448,P<0.001),negatively correlated with HRR(rs=-0.232,P=0.024),and had no significant correlation with SII(rs=0.144,P=0.167).Further analysis of the correlation between the above novel inflammatory markers and the 5 components of frailty showed that NLR was positively correlated with fatigue(rs=0.228,P=0.017),slowed walking speed(rs=0.299,P<0.001),and low physical function(rs=0.319,P<0.001);RDW was positively correlated with decreased grip strength(rs=0.321,P<0.001),slowed walking speed(rs=0.422,P<0.001),and low physical function(rs=0.246,P=0.001);and HRR was negatively correlated with slowed walking speed(rs=-0.230,P=0.025),and low physical function(rs=-0.299,P=0.003).Multivariate logistic regression analysis showed that MNA-SF score(OR=0.577,95%CI 0.342-0.973)was an independent protective factor for pre-frailty in elderly patients with chronic CVD(P<0.05);NLR(OR=7.866,95%CI 1.101-56.185)was an independent risk factor for frailty,while HRR(OR=0.344,95%CI 0.120-0.983)and MNA-SF score(OR=0.292,95%CI 0.146-0.580)were independent protective factors for frailty in elderly CVD patients(P<0.05).The area under the ROC curve of NLR and HRR for diagnosing frailty in elderly patients with chronic CVD were 0.778 and 0.749,respectively.Conclusion NLR and HRR have high clinical diagnostic value for frailty in elderly patients with chronic CVD,and are expected to become effective inflammatory markers for screening elderly patients with chronic CVD complicated with frailty.

Ursodeoxycholic acid(UDCA)is a naturally occurring,low-toxicity,and hydrophilic bile acid(BA)in the human body that is converted by intestinal flora using primary BA.Solute carrier family 7 member 11(SLC7A11)functions to uptake extracellular cystine in exchange for glutamate,and is highly expressed in a variety of human cancers.Retroperitoneal liposarcoma(RLPS)refers to liposarcoma originating from the retroperitoneal area.Lipidomics analysis revealed that UDCA was one of the most significantly down-regulated metabolites in sera of RIPS patients compared with healthy subjects.The augmentation of UDCA concentration(≥25 μg/mL)demonstrated a suppressive effect on the proliferation of liposarcoma cells.[15N2]-cystine and[13Cs]-glutamine isotope tracing revealed that UDCA impairs cystine uptake and glutathione(GSH)synthesis.Mechanistically,UDCA binds to the cystine transporter SLC7A11 to inhibit cystine uptake and impair GSH de novo synthesis,leading to reactive oxygen species(ROS)accumulation and mitochondrial oxidative damage.Furthermore,UDCA can promote the anti-cancer effects of ferroptosis inducers(Erastin,RSL3),the murine double minute 2(MDM2)inhibitors(Nutlin 3a,RG7112),cyclin dependent kinase 4(CDK4)inhibitor(Abemaciclib),and glutaminase inhibitor(CB839).Together,UDCA functions as a cystine exchange factor that binds to SLC7A11 for antitumor activity,and SLC7A11 is not only a new transporter for BA but also a clinically applicable target for UDCA.More importantly,in combination with other antitumor chemotherapy or physiotherapy treatments,UDCA may provide effective and promising treatment strategies for RLPS or other types of tumors in a ROS-dependent manner.

The Piezo protein is a non-selective mechanosensitive cation channel that exhibits sensitivity to mechanical stimuli such as pressure and shear stress. It converts mechanical signals into bioelectric activity within cells, thus triggering specific biological responses. In the digestive system, Piezo protein plays a crucial role in maintaining normal physiological activities, including digestion, absorption, metabolic regulation, and immune modulation. However, dysregulation in Piezo protein expression may lead to the occurrence of several pathological conditions, including visceral hypersensitivity, impairment of intestinal mucosal barrier function, and immune inflammation.Therefore, conducting a comprehensive review of the physiological functions and pathological roles of Piezo protein in the digestive system is of paramount importance. In this review, we systematically summarize the structural and dynamic characteristics of Piezo protein, its expression patterns, and physiological functions in the digestive system. We particularly focus on elucidating the mechanisms of action of Piezo protein in digestive system tumor diseases, inflammatory diseases, fibrotic diseases, and functional disorders. Through the integration of the latest research findings, we have observed that Piezo protein plays a crucial role in the pathogenesis of various digestive system diseases. There exist intricate interactions between Piezo protein and multiple phenotypes of digestive system tumors such as proliferation, apoptosis, and metastasis. In inflammatory diseases, Piezo protein promotes intestinal immune responses and pancreatic trypsinogen activation, contributing to the development of ulcerative colitis, Crohn’s disease, and pancreatitis. Additionally, Piezo1, through pathways involving co-action with the TRPV4 ion channel, facilitates neutrophil recruitment and suppresses HIF-1α ubiquitination, thereby mediating organ fibrosis in organs like the liver and pancreas. Moreover, Piezo protein regulation by gut microbiota or factors like age and gender can result in increased or decreased visceral sensitivity, and alterations in intestinal mucosal barrier structure and permeability, which are closely associated with functional disorders like irritable bowel sydrome (IBS) and functional consitipaction (FC). A thorough exploration of Piezo protein as a potential therapeutic target in digestive system diseases can provide a scientific basis and theoretical support for future clinical diagnosis and treatment strategies.