Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.

ObjectiveTo investigate the effect of mucin 1 (MUC1) on the proliferation and apoptosis of nasopharyngeal carcinoma (NPC) and its regulatory mechanism. MethodsThe 60 NPC and paired para-cancer normal tissues were collected from October 2020 to July 2021 in Quanzhou First Hospital. The expression of MUC1 was measured by real-time quantitative PCR (qPCR) in the patients with PNC. The 5-8F and HNE1 cells were transfected with siRNA control (si-control) or siRNA targeting MUC1 (si-MUC1). Cell proliferation was analyzed by cell counting kit-8 and colony formation assay, and apoptosis was analyzed by flow cytometry analysis in the 5-8F and HNE1 cells. The qPCR and ELISA were executed to analyze the levels of TNF-α and IL-6. Western blot was performed to measure the expression of MUC1, NF-кB and apoptosis-related proteins (Bax and Bcl-2). ResultsThe expression of MUC1 was up-regulated in the NPC tissues, and NPC patients with the high MUC1 expression were inclined to EBV infection, growth and metastasis of NPC. Loss of MUC1 restrained malignant features, including the proliferation and apoptosis, downregulated the expression of p-IкB、p-P65 and Bcl-2 and upregulated the expression of Bax in the NPC cells. ConclusionDownregulation of MUC1 restrained biological characteristics of malignancy, including cell proliferation and apoptosis, by inactivating NF-κB signaling pathway in NPC.

A precursor ion selection (PIS) based ultra high performance liquid chromatography-quadrupole time of flight mass spectrometry (UHPLC-Q-TOF-MS) analytical method was used to screen the chemical components in Jiawei Dingzhi pills (JWDZP) comprehensively and rapidly. To compile the components of the compound medicine, a total of 1 921 components were found utilizing online databases and literature. After verifying the sources, unifying the component names, merging the multi-flavor attributed components, and removing the weak polar molecules, 450 components were successfully retained. The Acquity UPLC HSS T3 column (100 mm × 2.1 mm, 1.8 μm) was used, with a 0.1% formic acid water (A)-acetonitrile (B) as the mobile phase. The flow rate was 0.35 mL·min^-1, the column temperature was 35 ℃, and an electrospray ion source was used. Data was collected with the PIS strategy in both positive and negative ion modes. Compounds were screened through matching accurate molecular weight of the database, and identified according to MS/MS data (characteristic fragment ions and neutral loss), with comparison of reference. Some compounds were confirmed using standard products. A total of 176 compounds were screened out in the extract of JWDZP, among which 26 compounds were confirmed by standard products. These compounds include 96 components from the sovereign drug, and 34 coefflux components with low ion intensity. The PIS-UHPLC-Q-TOF-MS/MS method established in this study can quickly and comprehensively screen the chemical components of JWDZP, which enhanced the screening rate of components with co-elution compounds of low ion intensities and provided a basis for the study of the material foundation of JWDZP.

Eighteen compounds were isolated from the methanol extract of the fruits of Litsea cubeba by silica gel, ODS, Sephadex LH-20 column chromatography, semi-preparative RP-HPLC, chiral HPLC and recrystallization. Their structures were elucidated by spectroscopic analyses and by comparison with reported spectroscopic data and physicochemical properties, and the absolute configurations of the enantiomers were established by experimental and calculated electronic circular dichroism spectra. These compounds were identified as (+)-(R)-4-hydroxypiperitenone (1a), (-)-(S)-4-hydroxypiperitenone (1b), (3S,4S,6R)-3,6-dihydroxy-1-menthene (2), (4S,5R)-4-hydroxy-5-isopropyl-2-methylcyclohex-2-en-1-one (3), (R)-6-hydroxy-3-(2-hydroxypropan-2-yl)-6-methylcyclohex-2-enone (4), (4S,6R)-4-hydroxy-6-isopropyl-3-methylcyclohex-2-enone (5), (1R,3S,4R)-3-hydroxy isopulegol (6), subamone (7), (6S)-3,7-dimethyl-7-hydroxy-2(Z)-octen-6-olide (8), (6S)-6,7-dihydroxy-3,7-dimethyloct-2(Z)-enoate (9), holostylactone (10), sesamin (11), dimethylmatairesinol (12), p-hydroxybenzoylcarbinol (13), syringaldehyde (14), p-hydroxybenzaldehyde (15), 4-hydroxy-3-methoxybenzaldehyde (16), 5,4ʹ-dihydroxy-7-methoxyflavone (17). Among them, compounds 1a and 1b were a pair of new monoterpenoid enantiomers, 8 and 9 were new natural products, 2-7, 10, 11 and 17 were isolated from Litsea genus for the first time. The in vitro anti-inflammatory effects of compounds 1-17 were evaluated using lipopolysaccharide-stimulated RAW264.7 cells, the results showed that compound 14 exhibited significant anti-inflammatory activity with NO inhibitory rate of 66.27% at a concentration of 40 μmol·L^-1.

Objective To investigate how maternal MTR gene polymorphisms and their interactions with periconceptional folic acid supplementation are associated with the incidence of ventricular septal defects(VSD)in offspring.Methods A case-control study was conducted,recruiting 426 mothers of infants with VSD under one year old and 740 mothers of age-matched healthy infants.A questionnaire survey collected data on maternal exposures,and blood samples were analyzed for genetic polymorphisms.Multivariable logistic regression analysis and inverse probability of treatment weighting were used to analyze the associations between genetic loci and VSD.Crossover analysis and logistic regression were utilized to examine the additive and multiplicative interactions between the loci and folic acid intake.Results The CT and TT genotypes of the maternal MTR gene at rs6668344 increased the susceptibility of offspring to VSD(P<0.05).The GC and CC genotypes at rs3768139,AG and GG at rs1050993,AT and TT at rs4659743,GG at rs3768142,and GT and TT at rs3820571 were associated with a decreased risk of VSD(P<0.05).The variations at rs6668344 demonstrated an antagonistic multiplicative interaction with folic acid supplementation in relation to VSD(P<0.05).Conclusions Maternal MTR gene polymorphisms significantly correlate with the incidence of VSD in offspring.Mothers with variations at rs6668344 can decrease the susceptibility to VSD in their offspring by supplementing with folic acid during the periconceptional period,suggesting the importance of periconceptional folic acid supplementation in genetically at-risk populations to prevent VSD in offspring.

Objective:To develop and validate a model to predict the risk of malnutrition in patients with nasopharyngeal carcinoma receiving concurrent chemoradiotherapy. Methods:From April 2022 to August 2023, 430 patients with nasopharyngeal carcinoma who were admitted to the department of radiotherapy of the first affiliated hospital of Guangxi medical university in Nanning were conveniently selected as the study subjects, and they were divided into the modelling group (300 cases) and the internal validation group (130 cases) in the internal validation group in the ratio of 7:3, and 61 patients with nasopharyngeal carcinoma admitted to the affiliated cancer hospital of Guangxi medical university in Nanning City were selected as the external validation group. Logistic regression was used to establish the risk prediction model and draw nomograms,Hosmer-Lemeshow, calibration curve and ROC were used to verify the goodness of fit and predictive power of the model, and clinical decision curve was used to assess the clinical utility. Results:Logistic regression analysis showed that skeletal muscle mass index, self-rated anxiety scale score, Pittsburgh sleep quality questionnaire score, Chinese diet pagoda score, regular exercise, and digestive symptom groups were the influencing factors for malnutrition in patients with nasopharyngeal carcinoma receiving concurrent chemoradiotherapy. In the modelling group, the area under the ROC curve was 0.853 (95％CI:0.81 ～ 0.89), the maximum Youden was 0.600, and the corresponding specificity was 0.764 and the sensitivity was 0.836. The Hosmer-Lemeshow test=4.040 and P=0.853 indicated that the model had good predictive ability. Calibration curve of the calibration showed that the predictive effect of the model matched actual probability well, with an average absolute error was 0.024. When the threshold probability of the clinical decision curve is 0.05 ～ 0.85, the clinical response rate is higher. The area under the operating curve of the subjects in the internal validation group was 0.891, the sensitivity was 77.36％, the specificity was 89.61％, and the practical application accuracy was 84.62％. The area under the operating curve of the subjects in the external validation group was 0.886, the sensitivity was 76.00％, the specificity was 83.33％, and the overall accuracy was 80.33％. Conclusion:The risk prediction model constructed in this study has a good effect, which can effectively predict the incidence of malnutrition in patients receiving concurrent radiotherapy and chemotherapy for nasopharyngeal carcinoma, and provide a reference for clinical staff to formulate and implement nutritional interventions.

Objective:To investigate the role of serum adenosine deaminase(ADA)combined with globulin(GLB),creatinine(CREA),β2-microglobulin(β2-MG)and hemoglobin(HGB)in the initial screening of multiple myeloma(MM),in order to reduce missed diagnosis and misdiagnosis of MM.Methods:A retrospective analysis was performed on 62 newly diagnosed multiple myeloma(NDMM)patients who were admitted to the Department of Hematology of the First Affiliated Hospital of Chengdu Medical College from April 2018 to December 2021,and 33 patients with benign hematologic diseases and 30 healthy subjects were selected as the control group.The expression of ADA in pan-cancer was analyzed using TCGA and GTEx databases.The general data and laboratory indicators of the subjects were collected,and the differences of ADA activity and other laboratory indicators in each group were compared.The relationship between serum ADA activity and clinical data of NDMM patients was analyzed.The changes of ADA activity before and after chemotherapy in NDMM patients and the differences of ADA activity in NDMM patients with different DS and ISS stages were compared.Multivariate logistic regression was used to analyze the risk factors of NDMM.The receiver operating characteristic(ROC)curve was used to evaluate the diagnostic efficacy of ADA and other laboratory indicators in MM.Bioinformatics method was used to analyze the co-expression networks and enrichment pathways of ADA.Results:ADA level was significantly upregulated in tissues of 14 types of cancer in TCGA database,and ADA was highly expressed in 11 types of cancer in TCGA combined with GTEx databases.The serum levels of ADA,GLB,uric acid(UA),cystatin C(CysC)and β2-MG in the NDMM group were significantly higher than those in benign hematologic disease group and healthy control group(P＜0.05),while the levels of ALB and the value of albumin to globulin ratio(A:G)in the NDMM group were significantly lower than those in the other two groups(P＜0.001).There were significant differences in DS stage(P=0.036),ISS stage(P=0.019)and the levels of CREA(P=0.036),UA(P=0.034),β2-MG(P=0.019)in NDMM patients with different ADA activity levels.After primary chemotherapy,ADA activity and(32-MG concentration were decreased in NDMM patients(P＜0.01).The comparison results of patients in different stages showed that ADA activity of patients in DS stage I+11 was significantly lower than that of patients in DS stage Ⅲ(P＜0.05),and ADA activity of patiens in ISS stage Ⅰ+Ⅱ was significantly lower than that of patients in ISS stage Ⅲ(P＜0.01).Multivariate logistic regression analysis showed that increased GLB,increased ADA activity,increased CREA,increased β2-MG and decreased HGB were independent risk factors for NDMM.The area under the curve(AUC)of ADA in the diagnosis of MM was 0.847,and the AUC of ADA combined with GLB,CREA,(32-MG and HGB in the diagnosis of MM was 0.940.The results of co-expression network and enrichment pathway analysis showed that ADA bounded to 20 proteins and it was significantly associated with the metabolic pathways of purine,pyrimidine,nicotinate and nicotinamide.Conclusion:The detection of ADA activity in serum is of positive significance for the auxiliary diagnosis,therapeutic evaluation and monitoring the progress of NDMM patients.ADA combined with GLB,CREA,β2-MG and HGB can improve the detection rate of MM,and reduce missed diagnosis and misdiagnosis to a certain extent.

Objective:To establish a morphologic classification system for characterizing blast cells in patients with acute promyelocytic leukemia(APL)and analyze the correlation of different APL morphologic characteristics with conventional tests and genetic variants.Methods:Based on the morphological characteristics of APL blast cells,a classification system of 14 categories was established to characterize the inter-and intra-individual cellular morphological heterogeneity of patients.The classification system was used for the morphological analysis of 40 APL patients,and the classification results were statistically analyzed with the patients'conventional test indexes and gene variant characteristics to analyze the correlation of different APL blast cell morphological features with conventional test indexes and gene variants.Results:In the FLT3-ITD mutation-positive group,there were significantly fewer cells with regular nuclear shape,hyper granularity,and missing Auer rods(category 1)than in the FLT3 mutation-negative group(P＜0.05).The activated partial thromboplastin(APTT)was significantly longer in the group with regular nucleus compared to the group with irregular nucleus(P＜0.05).In the hypo-granular group,the APTT was also significantly longer compared to the hyper-granular group(P＜0.01),and the proportion of myeloid blast cells was relatively lower(P＜0.05).The peripheral blood white blood cell counts,D-dimer,lactate dehydrogenase and proportion of bone marrow blast cells were significantly higher in the Auer rods(-)group than Auer rods increasing group(all P＜0.05).Conclusion:The newly established morphologic classification system in this study can objectively characterize different types of APL blast cells,which helps to better assess the intra-and inter-individual heterogeneity of APL blast cells,and further use in accurately analyzing the correlation of morphological phenotypes with biological properties of APL.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is an increasingly common liver disease worldwide. MAFLD is diagnosed based on the presence of steatosis on images, histological findings, or serum marker levels as well as the presence of at least one of the three metabolic features: overweight/obesity, type 2 diabetes mellitus, and metabolic risk factors. MAFLD is not only a liver disease but also a factor contributing to or related to cardiovascular diseases (CVD), which is the major etiology responsible for morbidity and mortality in patients with MAFLD. Hence, understanding the association between MAFLD and CVD, surveillance and risk stratification of MAFLD in patients with CVD, and assessment of the current status of MAFLD management are urgent requirements for both hepatologists and cardiologists. This Taiwan position statement reviews the literature and provides suggestions regarding the epidemiology, etiology, risk factors, risk stratification, nonpharmacological interventions, and potential drug treatments of MAFLD, focusing on its association with CVD.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.