Objective: To determine 17 types of phthalic acid esters (PAEs) in drinking water using solid-phase extraction coupled with gas chromatography-mass spectrometry (GC-MS) in multiple reaction monitoring (MRM) mode. Methods: One litre of commercially available bottled water was purified using an HLB solid-phase extraction column, and was eluted with ethyl acetate, dichloromethane and average methanol. Seventeen types of PAEs were detected using a triple quadrupole gas chromatography-mass spectrometer in MRM mode. By optimizing the temperature programming and adjusting the mass spectrometry collision energy, collection efficiency was improved and matrix interference was reduced. The precision and accuracy of this method were assessed by determining the standard curves, detection limits, quantification limits, relative standard deviations (RSD) and average spiked recovery rates for the 17 types of PAEs. Results: The 17 types of PAEs showed good linear relationships between mass concentration and chromatographic peak areas in the range of 0.02 to 1.0 mg/L, with correlation coefficients all greater than 0.999 1. The detection limits ranged from 0.002 9 to 0.009 7 mg/kg, the quantification limits ranged from 0.008 7 to 0.029 1 mg/kg, the RSD ranged from 0.8% to 3.0%, and the average spiked recovery rates ranged from 88.8% to 111.8%. Conclusion Solid-phase extraction coupled with MRM of GC-MS can better determine low concentrations of PAEs in drinking water.

Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

OBJECTIVE To compare the efficacy and safety of different daily doses of aspirin in the prevention of preeclampsia （PE）. METHODS The case-control studies and prospective randomized controlled trials on aspirin with daily dose ≥ 100 mg （trial group） vs. ＜100 mg （control group） in the prevention of PE were retrieved from PubMed， Medline， Embase， the Cochrane Library， CNKI， China Biomedical Literatue Database and Wanfang Data from base-building to January 2025. After literature screening， data extraction and quality evaluation， meta-analysis was performed by using RevMan 5.3 software. RESULTS A total of 11 literatures were included， involving 3 052 pregnant women. Meta-analysis showed the incidence of PE [RR＝0.63， 95%CI （0.53，0.76）， P＜0.000 01]， gestational hypertension [RR＝0.69， 95%CI （0.50，0.94），P＝0.02]， preterm birth [RR＝0.56， 95%CI （0.47，0.66）， P＜0.000 01]， and intrauterine growth retardation [RR＝0.73，95%CI （0.61，0.87），P＝0.000 5] in trial groups were significantly lower than control group. The incidence of postpartum hemorrhage between the two groups had no statistically significant difference [RR＝1.17， 95%CI （0.90，1.53），P＝0.25]. Subgroup analysis showed that the incidence of PE in Chinese pregnant women taking 150 mg of aspirin was significantly higher than taking 100 mg of aspirin [RR＝3.40， 95%CI （1.29， 8.93）， P＝0.01]； but there was no significant difference between the two groups in the incidences of postpartum hemorrhage， preterm birth （P＞0.05）. CONCLUSIONS Aspirin with daily dose ≥100 mg is more effective in preventing PE than daily dose ＜100 mg， with lower rates of gestational hypertension， preterm birth， and intrauterine growth retardation. It does not increase the risk of postpartum hemorrhage. For pregnant women in China， daily dose 100 mg of aspirin may be more effective in preventing PE than 150 mg.

This study established the HPLC fingerprints, characteristic chromatograms, and a multi-component content determination method for Bidens bipinnata and B. biternata. The chemical pattern recognition analysis was then employed to clarify the characteristic indexes of quality differences between the two original plants of Bidentis Herba, providing a reference for establishing the quality standards of Bidentis Herba. HPLC was launched on an Agilent Poroshell 120 EC-C_(18) chromatographic column(4.6 mm×250 mm, 4 μm) by gradient elution with a mobile phase of 0.1% aqueous phosphoric acid-acetonitrile at a flow rate of 0.7 mL·min~(-1), detection wavelength of 270 nm, column temperature of 25 ℃, and an injection volume of 5 μL. The similarity between the fingerprints of 18 batches of Bidentis Herba samples and the common pattern(R) ranged from 0.572 to 0.933. A total of 23 chromatographic peaks were calibrated. Through comparison with the reference substances, six components(neochlorogenic acid, chlorogenic acid, isochlorogenic acid A, isochlorogenic acid B, rutin, and hyperoside) were identified and subjected to quantitative analysis. The characteristic fingerprints of B. bipinnata and B. biternata were calibrated with 20 and 17 characteristic peaks, respectively. Among them, peaks 8, 9, 22, and 23 were the characteristic peaks of B. bipinnata, and peak 7 was the characteristic peak of B. biternata, which can be used to distinguish the two original plants of Bidentis Herba. The relative standard deviation of the content of the above-mentioned six components ranged from 36% to 123%. The cluster analysis, principal component analysis, and orthogonal partial least squares-discriminant analysis(OPLS-DA) classified the 18 batches of Bidentis Herba samples into two categories. Additionally, through the analysis of variable importance in projection(VIP) under OPLS-DA, three characteristic indexes, rutin, isochlorogenic acid A, and isochlorogenic acid B, were identified. The analytical method established in this study can comprehensively evaluate the consistency of Bidentis Herba samples derived from different original plants, specifically identify the differential components between them, and effectively distinguish the two original plants of Bidentis Herba, providing a basis for the differentiation between different original plants and the quality control of Bidentis Herba.
Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Bidens/chemistry*

OBJECTIVES: To investigate the effects of methylenetetrahydrofolate reductase (MTHFR) rs1801133 and γ-glutamyl hydrolase (GGH) rs11545078 gene polymorphisms on plasma concentrations and toxicity following high-dose methotrexate (MTX) therapy in children with acute lymphoblastic leukemia (ALL). METHODS: Children with ALL treated at the Xuzhou Children's Hospital of Xuzhou Medical University from January 2021 to April 2024 were selected for this study. Genotypes of MTHFR rs1801133 and GGH rs11545078 were determined using multiplex polymerase chain reaction. MTX plasma concentrations were measured by enzyme-multiplied immunoassay technique, and toxicity was graded according to the Common Terminology Criteria for Adverse Events version 5.0. The relationships between MTHFR rs1801133 and GGH rs11545078 genotypes and both MTX plasma concentrations and associated toxicities were analyzed. RESULTS: In the low-risk ALL group, the MTHFR rs1801133 genotype was associated with increased MTX plasma concentrations at 72 hours (P<0.05). In the intermediate- to high-risk group, the MTHFR rs1801133 genotype was associated with increased MTX plasma concentrations at 48 hours (P<0.05), and the GGH rs11545078 genotype was associated with increased MTX plasma concentrations at 48 hours (P<0.05). In the intermediate- to high-risk group, the MTHFR rs1801133 genotype was associated with the occurrence of reduced hemoglobin (P<0.05), and the GGH rs11545078 genotype was associated with the occurrence of thrombocytopenia (P<0.05). CONCLUSIONS Detection of MTHFR rs1801133 and GGH rs11545078 genotypes can be used to predict increased MTX plasma concentrations and the occurrence of toxic reactions in high-dose MTX treatment of ALL, enabling timely interventions to enhance safety.
Humans ; Methotrexate/toxicity* ; Methylenetetrahydrofolate Reductase (NADPH2)/genetics* ; Precursor Cell Lymphoblastic Leukemia-Lymphoma/blood* ; Male ; Female ; Child ; Child, Preschool ; gamma-Glutamyl Hydrolase/genetics* ; Antimetabolites, Antineoplastic/adverse effects* ; Infant ; Polymorphism, Genetic ; Adolescent ; Genotype ; Polymorphism, Single Nucleotide

Glutamine provides carbon and nitrogen to support the proliferation of cancer cells. However, the precise reason why cancer cells are particularly dependent on glutamine remains unclear. In this study, we report that glutamine modulates the tumor suppressor F-box and WD repeat domain-containing 7 (FBW7) to promote cancer cell proliferation and survival. Specifically, lysine 604 (K604) in the sixth of the 7 substrate-recruiting WD repeats of FBW7 undergoes glutaminylation (Gln-K604) by glutaminyl tRNA synthetase. Gln-K604 inhibits SCFFBW7-mediated degradation of c-Myc and Mcl-1, enhances glutamine utilization, and stimulates nucleotide and DNA biosynthesis through the activation of c-Myc. Additionally, Gln-K604 promotes resistance to apoptosis by activating Mcl-1. In contrast, SIRT1 deglutaminylates Gln-K604, thereby reversing its effects. Cancer cells lacking Gln-K604 exhibit overexpression of c-Myc and Mcl-1 and display resistance to chemotherapy-induced apoptosis. Silencing both c-MYC and MCL-1 in these cells sensitizes them to chemotherapy. These findings indicate that the glutamine-mediated signal via Gln-K604 is a key driver of cancer progression and suggest potential strategies for targeted cancer therapies based on varying Gln-K604 status.
Glutamine/metabolism* ; Myeloid Cell Leukemia Sequence 1 Protein/genetics* ; Humans ; Proto-Oncogene Proteins c-myc/genetics* ; Cell Proliferation ; Signal Transduction ; Neoplasms/pathology* ; F-Box-WD Repeat-Containing Protein 7/genetics* ; Cell Survival ; Cell Line, Tumor ; Apoptosis

Deep vein thrombosis(DVT)is a common peripheral vascular disease in clinical practice.The lack of precise and efficient early diagnostic techniques renders it susceptible to being overlooked or misdiagnosed,and therefore,identifying trustworthy biomarkers is a major issue that has to be resolved.In this study,the endogenous metabolites in the urine of DVT rats were screened by metabolomics technology based on gas chromatograph-mass spectrometry(GC-MS)and the characteristic metabolites were identified by multiple feature selection algorithms and multivariate statistical analysis,for the development of a machine learning-based diagnostic model for DVT.The urine samples in metabolic cage in the thrombus development phase(between 48 and 72 h)of rats were collected,which was used as the models for inferior vena cava ligation.The metabolic profiles of the control group and DVT were obtained using the GC-MS method.A total of 176 kinds of endogenous metabolites were identified in rat urine through comparison with the FiehnLib database,26 kinds of differential metabolites associated with DVT were screened through a combination of the Mann-Whitney U test and orthogonal partial least squares discriminant analysis(OPLS-DA),and 13 kinds of significant metabolites strongly correlated with DVT were further evaluated in conjunction with various machine learning feature selection techniques.For DVT diagnosis,machine learning models such as Gaussian Naive Bayes(GNB),support vector machine(SVM),logistic regression(LR),and linear discriminant analysis(LDA)were developed.The diagnostic model constructed using 13 kinds of key metabolites demonstrated excellent accuracy and stability,and surpassed the predictive performance of the models utilizing 176 kinds of metabolites and 26 kinds of differential metabolites,as evidenced by examination and comparison of each model's efficacy.The study showed that the integration of multiple feature selection algorithms for analyzing metabolite information in DVT rat urine was capable of effectively identifying reliable potential markers of DVT.Furthermore,the developed machine learning model offered a novel technical approach for the automated diagnosis of DVT.

Objective To establish a novel localization method for sacral nerve foramen puncture by analyzing the characteristic of sacral nerve foramen trying to help improve the success rate of sacral foramen puncture.Methods Clinical data and sacrococcyx CT and three-dimensional reconstruction imaging data of 158 patients who received sacral nerve modulation(SNM)during Jan.2019 and Aug.2022 in our hospital were retrospectively analyzed.The distance between inferior margin of articulatio sacroiliaca and the internal edge of the 3rd neural foramen(D1),and the distance between the internal edge of the 3rd neural foramen and sacral midline(D2)were measured,and the ratio of D1 and D2 was calculated for precise intraoperative positioning.The measurement data characteristic and puncture results were analyzed.Results A total of 89 males and 69 females were included,with an average age of(49.0±16.9)years.The average D1,D2,and D1/D2 were(29.6±4.9)mm,(13.8±3.2)mm,and(2.2±0.6),respectively.Female patients had greater D1[(30.7±5.5)mm vs.(28.7±4.2)mm,P=0.010]and D1/D2[(2.4±0.7)vs.(2.1±0.5),P=0.001]than male patients.Compared with adults,the adolescents had smaller D1[(29.8±4.7)mm vs.(25.7±5.4)mm,P=0.006].After precise intraoperative positioning using this positioning method,158 patients were successfully punctured,152(96.20％)had excellent intraoperative neural response,2(1.27％)had good response,and 4(2.53％)had average response.Conclusion The surface projection of sacral nerve was approximately at the middle-inner 1/3 of the inferior margin of articulatio sacroiliaca to sacral midline.Through measuring distance from inferior margin of articulatio sacroiliacato sacral midline via X-ray,sacral nerve situation could be performed in surface,which might be a secure way to accessorily situate electrode implantation site for sacral neuromodulation.

OBJECTIVE To investigate the in vitro inhibitory mechanism of berberine on the proliferation of tumor stem cells and evaluate its in vivo safety. METHODS Flow cytometry was used to select tumor stem cells from mouse skin melanoma B16F10 cells； CD44， CD133， Nanog homologous box protein （NANOG） and octamer-binding transcription factor 4 （OCT4） were used as indicators to characterize tumor stem cells. Tumor stem cells were divided into control group， all-trans retinoic acid （ATRA） group， and berberine group， and the CCK-8 method was used to detect the effects of berberine on the viability of tumor stem cells； flow cytometry was adopted to detect cell apoptotic rate， the proportion of CD44+/CD133+ and the positive cell rate of sex determining region Y box protein 2 （SOX2）； the morphological changes of tumor balls were recorded after treatment with berberine； the morphology of cell pyroptosis in each group was recorded， and the release rate of lactate dehydrogenase （LDH） was detected； Western blot assay was adopted to detect the expressions of pyroptosis-related protein gasdermin E （GSDME）， GSDME- N， caspase-3 and cleaved caspase-3. Preliminary evaluation of in vivo safety of berberine was conducted by using zebrafish embryo toxicity experiments. RESULTS Compared with B16F10 cells， the proportion of CD44+/CD133+ cells in tumor stem cells and the fluorescence intensity of NANOG and OCT4 were significantly increased （P＜0.000 1）. The half-inhibitory concentration of berberine to tumor stem cells was 50.98 μmol/L. Compared with the control group， the apoptotic rate of cells in the berberine group was significantly increased， while the proportion of CD44+/CD133+ cells and the rate of SOX2 positive cells were reduced significantly （P＜0.000 1）； tumor stem cell spheroids were atrophied， with partial cell death. After treatment with berberine， tumor stem cells exhibited swelling in their outermost layer， the release rate of LDH of cells was significantly increased and the release rate of LDH increased with increasing dose； the protein expressions of GSDME-N and cleaved-caspase-3 of cells in berberine 20， 40 μmol/L groups were significantly increased， and the protein expressions of GSDME and caspase-3 were significantly reduced （except for berberine 20 μmol/L group， P＜0.05）. The embryonic development of zebrafish treated with berberine was almost unaffected， and the survival rate of embryo reached 100%， with no obvious abnormalities observed. CONCLUSIONS Berberine has good activity against the proliferation of tumor stem cells， and its mechanism of action may be related to activating GSDME and promoting cell pyroptosis； berberine has good in vivo safety.

Diabetic kidney disease(DKD)is one of the most important complications of diabetes.In recent years,domestic and foreign studies have found that mammalian target protein of rapamycin(mTOR)related signaling pathway is a classic pathway involved in the regulation of autophagy,which can achieve the therapeutic effect of DKD by targeting the autophagy pathway,and plays a crucial role in the prevention and treatment of DKD.In this paper,we reviewed the mechanism of mTOR-related signaling pathway targeted autophagy in the prevention and treatment of DKD,in order to provide a new reference and basis for clinical prevention and treatment of DKD.