OBJECTIVE: To explore the application value of artificial intelligence (AI)-assisted chromosomal karyotype analysis in the diagnosis of prenatal chromosomal mosaicism. METHODS: A retrospective analysis was conducted on 172 pregnant women who underwent amniocentesis at the Department of Medical Genetics and Prenatal Diagnosis, the Third Affiliated Hospital of Zhengzhou University between January 2019 and December 2024. All cases whose fetuses were diagnosed with chromosomal mosaicism via karyotype analysis and stratified into two groups based on the analytical software employed: the conventional analysis group (n = 70), which utilized Leica analysis software for karyotype image recognition and cell counting; and the AI-assisted analysis group (n = 102), which utilized AI-assisted software for the same procedures. The clinical performance of AI-assisted karyotype analysis in diagnosing chromosomal mosaicism was comprehensively evaluated by comparing the types of mosaic karyotypes, distribution of mosaic ratios, and verification outcomes of different detection modalities between the two groups. This study was approved by the Medical Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethics No.: 2024-406-01). RESULTS: No statistically significant difference was observed in baseline characteristics (maternal age, gestational week, and indications for prenatal diagnosis) between the two groups. Regarding the detection efficacy for numerical and structural mosaicisms, no significant difference was found in the detection of numerical mosaicism. However, the conventional analysis group exhibited a significantly higher detection rate of autosomal structural mosaicism compared to the AI-assisted group (11.43% vs. 0.98%, P < 0.05). Numerical mosaicism cases were further verified using copy number variation sequencing (CNV-seq) and/or fluorescence in situ hybridization (FISH). The AI-assisted group demonstrated a significantly lower inconsistency rate (5.56% vs. 20.41%, P < 0.05) compared to the conventional group. For low-proportion (< 10%) chromosomal mosaicism, the AI-assisted group had a significantly lower detection rate (13.25% vs. 29.69%, P < 0.05). Subsequent validation of low-proportion mosaicism by CNV-seq and/or FISH showed a higher consistency rate in the AI-assisted group (81.82% vs. 54.55%), though the difference did not reach statistical significance (P = 0.360). CONCLUSION For the karyotyping analysis of prenatal chromosomal mosaicism, AI-assisted karyotype analysis shows high accuracy and consistency in identifying numerical chromosomal mosaicism, particularly in reducing the detection of low-proportion (< 10%) mosaicism while improving verification accuracy. AI-assisted analysis can significantly improve the detection accuracy of numerical mosaicism and mitigate the risk of misclassification for low-proportion (< 10%) mosaicism, thereby providing more precise clinical evidence for the prenatal diagnosis of chromosomal mosaicisms.
Humans ; Female ; Mosaicism ; Pregnancy ; Karyotyping/methods* ; Artificial Intelligence ; Prenatal Diagnosis/methods* ; Adult ; Retrospective Studies ; Chromosome Disorders/genetics* ; Amniocentesis

A growing body of research points out that gut microbiota plays a key role in tumor immunotherapy. By optimizing the composition of intestinal microbiota, it is possible to effectively improve immunotherapy resistance and enhance its therapeutic effect. This article comprehensively analyzes the mechanism of intestinal microbiota influencing tumor immunotherapy resistance, expounds the current strategies for targeted regulation of intestinal microbiota, such as traditional Chinese medicine and plant components, fecal microbiota transplantation, probiotics, prebiotics and dietary therapy, and explores the potential mechanisms of these strategies to improve patients' resistance to tumor immunotherapy. At the same time, the article also briefly discusses the prospects and challenges of targeting intestinal microbiota to improve tumor immunotherapy resistance, which provides a reference for related research to help the strategy research of reversing tumor immunotherapy resistance.

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

OBJECTIVE: To study the clinical effects of pomalidomide-based regimen in the treatment of relapsed and refractory multiple myeloma (RRMM). METHODS: 60 patients with RRMM in hematology department of the First Affiliated Hospital of Xinxiang Medical University from November 2020 to January 2023 were selected. Among them, 15 cases were treated with PDD regimen (pomalidomide + daratumumab + dexamethasone), and 45 cases were treated with PCD regimen (pomalidomide + cyclophosphamide + dexamethasone). The clinical effects were evaluated. RESULTS: The median number of treatment cycles for the entire cohort was 5 (2-11), with an overall response rate (ORR) of 75.0%. The ORR of patients treated with PDD regimen was 73.3%, while the ORR of patients treated with PCD regimen was 75.6%. The ORR of 46 patients with non high-risk cytogenetic abnormalities (non-HRCA) was 86.9%, significantly higher than the 35.7% of 14 patients with HRCA (χ² =15.031, P < 0.05). The median PFS for all patients was 8.0(95%CI : 6.8-9.1) months and the median OS was 14.0 (95%CI : 11.3-16.7) months. Among patients treated with PDD regimen, the PFS and OS of patients with non-HRCA were significantly higher than those of patients with HRCA [PFS: 7.0(95%CI : 4.6-9.3) months vs 4.0(95%CI : 3.1-4.8) months, χ² =5.120, P < 0.05; OS: not reached vs 6.0(95%CI : 1.1-10.9) months, χ² =9.870, P < 0.05]. Among patients treated with PCD regimen, the PFS and OS of patients with non-HRCA were significantly higher than those of patients with HRCA [PFS: 9.0(95%CI : 6.2-11.8) months vs 6.0(95%CI : 5.4-6.6) months, χ²=14.396, P < 0.05; OS: not reached vs 11.0(95%CI : 6.4-15.6) months, χ² =7.471, P < 0.05]. CONCLUSION The pomalidomide-based regimen has a good clinical effect and safety in the treatment of RRMM.
Humans ; Multiple Myeloma/drug therapy* ; Thalidomide/administration & dosage* ; Dexamethasone/therapeutic use* ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Female ; Male ; Middle Aged ; Recurrence ; Aged ; Cyclophosphamide/therapeutic use* ; Treatment Outcome ; Antibodies, Monoclonal

Hiatal hernia (HH) refers to a common digestive system disorder in which the stomach or other abdominal organs protrude into the thoracic cavity through the esophageal hiatus.With changes of people's lifestyles,accelerated aging,and rising rates of obesity and overweight,the incidence of HH in China has been steadily increasing.Early diagnosis and accurate classification of HH are critical for guiding treatment decisions. Conventional diagnostic methods-such as barium swallow X-ray,gastroscopy,computed tomography,and high resolution esophageal manometry-have limitations,including invasiveness,radiation exposure,high costs,or inadequate dynamic assessment.Gastric contrast-enhanced ultrasound,as a novel non-invasive imaging technique,has demonstrated unique advantages in the evaluation of HH in recent years.This article reviews the technical principles,clinical applications,and recent advancements of gastric contrast-enhanced ultrasound.
Humans ; Hernia, Hiatal/therapy* ; Contrast Media ; Ultrasonography ; Stomach/diagnostic imaging*

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

Travelling wave structures for lossless ion manipulations(TW-SLIM)employ travelling wave electric fields to propel ions forward,enabling exceptionally long transmission paths and holding great potential for applications in material transportation and separation.In this study,different from previous studies focusing on the transport performance of macromolecules such as proteins in TW-SLIM,the transmission performance of small molecules(<200 amu)was investigated and analyzed in the turning TW-SLIM through the COMSOL simulation platform,to explore the influence of electrostatic field of protective electrode and radio frequency(RF)electric field on ion transport efficiency,and obtain the optimal value.Compared to macromolecules,small molecules required lower voltage amplitudes from guard electrodes but stricter requirements in terms of the peak-to-peak amplitude and frequency of RF voltage for lossless transmission.Using dimethyl methylphosphonate(DMMP)as a sample and testing it on the TW-SLIM experimental platform,when the protective voltage amplitude was 5 V and the peak-to-peak voltage of the radio-frequency electrode was 440 V at 1.5 MHz,the ion transmission efficiency reached 100%,achieving lossless transmission.The experimental results provided valuable references for application of TW-SLIM in separation and detection of small molecular substances,such as explosives and drugs.

Mineral oil contaminants composed of saturated hydrocarbons(MOSH)and aromatic hydrocarbons(MOAH)are commonly found in edible oils and related processed foods.Currently,the analysis of mineral oils primarily employs the liquid chromatography-gas chromatography-flame ionization detector(LC-GC-FID)method.Liquid chromatography is used to purify and separate MOSH and MOAH from interfering substances,and the interface technology transfers MOSH or MOAH into different GC channels for quantitative analysis.The MOSH and MOAH chromatograms typically exhibit an irregular hump shape,with sharp peaks above the hump representing natural hydrocarbon interferences,which usually do not affect the identification of the hump profile.However,when the purification of interferences is incomplete,they can form one or more gaps above the hump,interfering with the accurate judgment and delineation of the hump profile,and leading to poor reproducibility of analysis results of mineral oil.In this study,an algorithm that mimicked the manual drawing of the hump shape or contour was proposed for automatically determining the mineral oil hump contour(i.e.,the lower envelope line).The algorithm used a multiple second-order difference quotient filtering method to identify and remove the gaps above the hump.The method involved first searching and determining the lowest value of the mineral oil hump,which was the valley point sequence,and then applying second-order difference quotient filtering to the valley point sequence.Compared to the hump,the second-order difference quotient of sharp peaks was a significantly larger negative value.By filtering out the points in the valley point sequence with larger negative second-order difference quotients(or multiple second-order difference quotients),the sharp peaks above the hump were removed.To verify the accuracy of the algorithm,42 different types of samples,including edible oils and milk powders were analyzed,using both the automatic algorithm and manual methods.The results showed that there were no significant differences in the detected mineral oil contents between these two methods.

Objective:To analyze the clinical characteristics and treatment outcomes of children with anti-3-hydroxy-3-methylglutaryl-coenzyme A reductase (anti-HMGCR) antibody-mediated necrotizing myopathy, and to explore early identification and management strategies to provide reference for clinical diagnosis and treatment.Methods:A retrospective analysis was conducted on the clinical data and treatment outcomes of 10 pediatric patients with anti-HMGCR antibody-mediated necrotizing myopathy admitted to the Department of Rheumatology, Children′s Hospital of Fudan University from December 2020 to December 2024. Statistical description was performed using SPSS 22.0.Results:Among the 10 patients, the male-to-female ratio was 1:4, the age of onset was (7.2±4.0) years, and the disease duration at diagnosis was (22.2±19.6) months. None had a history of statin exposure. Six patients presented with muscle weakness, and4 were diagnosed due to asymptomatic elevation of creatine kinase (CK); 4 had dermatomyositis-like rashes. All patients showed significantly elevated CK levels [median 3 291(1 969, 8 776)U/L] and underwent muscle biopsy. Histopathological findings revealed myofiber degeneration, necrosis, and regeneration in all cases, with inflammatory infiltration in 9 cases, MHC-Ⅰ positivity in all, and C5b-9 positivity in 9 cases. The median follow-up duration was (15.7±6.3) months. At the last follow-up, muscle strength was normal or nearly normal, and the CK median value had decreased to 977.5 (211.0, 3 536.0) U/L.Conclusion:For patients with suspected idiopathic inflammatory myopathy and significantly elevated CK, muscle-specific antibody testing-including anti-HMGCR-and muscle biopsy should be performed promptly regardless of the presence of skin rash, to ensure accurate diagnosis and guide treatment, thereby avoiding misdiagnosis or missed diagnosis.