OBJECTIVE: To apply optical genome mapping (OGM) technique for the analysis of genetic etiology in two rare families with complex chromosomal rearrangements (CCRs) and to provide precise reproductive guidance to them. METHODS: Two Chinese families diagnosed with chromosomal rearrangements by chromosomal microarray analysis (CMA) or whole-exome sequencing (WES) between June and December 2023 at the Affiliated Women and Children's Hospital of Ningbo University were selected as the study subjects. In both cases, unbalanced chromosomal translocations were suspected. Clinical data were collected, and peripheral blood from the couple, amniotic fluid sample and aborted fetal tissue was subjected to combined G-banding karyotyping and OGM for comprehensive genetic analysis. This study has been approved by the Medical Ethics Committee of the Hospital (Ethics No.: EC2023-094). RESULTS: In family 1, the fetus was signaled to have abnormal chromosome 7 by non-invasive prenatal testing (NIPT), prompting amniocentesis and CMA detection. In family 2, a pregnancy loss had occurred at 10 weeks' gestation, and trio-WES was carried out. Both fetuses were found to harbor copy number variations (CNVs) suggestive of unbalanced CCRs. Further analysis with OGM has revealed that, in family 1, an unbalanced rearrangement involving chromosomes 7, 8, and 10 was carried by the fetus and the pregnant woman, which has formed der(8) and der(10) derivative chromosomes. In family 2, a maternal CCR was found, which involved chromosomes 2 and 13 with seven breakpoints, resulting in unbalanced fetal CNVs. After genetic counseling, family 1 opted to continue with the pregnancy, considering the woman's normal appearance and inheritance of the rearrangement. For both families remained to have a risk for unbalanced rearrangements in subsequent pregnancies, preimplantation genetic testing (PGT) was recommended. CONCLUSION In both families, the OGM has precisely delineated the genetic basis of fetal CNVs and mapped the maternal CCR breakpoints, providing critical insights for genetic counseling and reproductive decision-making.
Adult ; Female ; Humans ; Male ; Pregnancy ; Chromosome Aberrations ; Chromosome Disorders/genetics* ; Chromosome Mapping/methods* ; Genetic Testing/methods* ; Pedigree ; Prenatal Diagnosis/methods* ; Translocation, Genetic

OBJECTIVE: To assess the value of Optical genome mapping (OGM) for the verification of chromosomal structural variations among patients undergoing assisting reproduction. METHODS: A retrospective analysis was carried out on the clinical data of 12 patients presented at the Reproductive Center of Ningbo University Women and Children's Hospital from October 2022 to October 2024. All patients had undergone OGM testing due to suspection of structural variants by chromosomal karyotyping or a suggestive medical history. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: EC2024-148). RESULTS: Among the 12 patients verified by OGM, one (8.3%) was in keeping with the result of chromosomal karyotyping. Revised karyotypes were confirmed in seven cases (58.3%), including four with complex chromosomal rearrangements. Structural variation was excluded in three cases (25.0%). Of note, OGM has identified a previously undetected cryptic balanced translocation, i.e., ogm[GRCh38] t(7;12)(q36.3;q24.23)(157511190_157523142;119205703_119198409). CONCLUSION OGM can serve as an auxiliary diagnostic technique to conventional karyotyping and enable validation of suspected structural variations in those with ambiguous karyotype results or a history of adverse pregnancies. This can provide more precise genetic diagnosis for patients undergoing assisted reproduction and selection of clinical intervention strategies.
Humans ; Female ; Adult ; Retrospective Studies ; Karyotyping ; Reproductive Techniques, Assisted ; Chromosome Mapping/methods* ; Chromosome Aberrations

OBJECTIVE: To investigate the genetic characteristics and clinical utility of Optical genome mapping (OGM) in resolving complex genomic rearrangements in families with recurrent pregnancy loss. METHODS: A recurrent miscarriage family which presented at both the People's Hospital of Qianxinan Buyi and Miao Autonomous Prefecture and the Affiliated Women and Children's Hospital of Ningbo University in September 2024 was selected as the study subject. Relevant clinical information was collected. Peripheral blood samples of the couple were collected for G banding karyotyping analysis, and copy number variation sequencing (CNV-seq) and OGM were used for verification. This study was approved by the Medical Ethics Committee of the Affiliated Women and Children's Hospital of Ningbo University (Ethics No.: EC2024-148). RESULTS: CNV-seq in an external hospital detected a 10.67 Mb deletion in the 16q12.1q21 region, a 142.4 kb deletion in the 5p15.2 region, and a 359.55 kb duplication in the 7p22.2 region. No abnormality was found in the chromosomal karyotype of the male partner, and the initial karyotyping of the female partner suggested 46,XX,?del(16)(q12.1q22). The CNV-seq verification of her indicated only variations in the 5p15.2 and 7p22.2 fragments, and no deletion of 16q was detected. As indicated by precise OGM analysis, multiple intrachromosomal and interchromosomal translocation variations had occurred between chromosomes 10 and 16 in the female partner, with complex balanced rearrangements (including 5 transchromosomal breakpoints). CONCLUSION The complex balanced rearrangements of the female partner's chromosomes had occurred during meiosis, the resultant unbalanced gametes may be the cause of repeated miscarriage in this family. OGM can delineate complex rearrangement breakpoints and directions that are difficult to reveal by conventional karyotyping analysis and provide a basis for accurate reproductive genetic counseling.
Humans ; Abortion, Habitual/etiology* ; Female ; Pregnancy ; Male ; DNA Copy Number Variations/genetics* ; Adult ; Karyotyping ; Pedigree ; Gene Rearrangement ; Chromosome Mapping

The scaphoid bone is one of the important bone of hand,which is frequently injured and difficult to treat in clinical practice.Therefore,it is very important to deeply study the microstructure and biomechanical characteristics of the scaphoid bone for understanding its injury mechanism and optimizing treatment scheme.Microcomputed tomography(micro-CT)provides high-resolution imaging of bone tissue,while finite element analysis can help to simulate the stress distribution and behavioral patterns of the scaphoid bone under various physiological and pathological states.The high-resolution three-dimensional image of the scaphoid bone obtained by micro-CT technology can be used to construct finite element models of real anatomical structure of the scaphoid bone,thus achieving accurate simulation of the mechanical properties of the scaphoid bone.The fusion of these two advanced technologies provides a new perspective for revealing the structural and functional relationships and injury mechanism of the scaphoid bone.Therefore,this paper reviews the anatomical characteristics of the scaphoid bone and its biomechanical behavior in different states,emphasizing the specific applications and advantages of micro-CT and finite element analysis techniques in the study of the scaphoid bone.By summarizing the research findings in recent years,this paper provides novel scientific basis and methods for the diagnosis,treatment,and prevention of scaphoid bone-related disorders.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Objective To explore the mechanism of action of jolkinolide B in the treatment of gastric cancer by network pharmacology combined with molecular docking technique.Methods The SwissTargetPrediction database was used to obtain the targets of the active compounds.Search Genecards,OMIM,Drugbank,TTD,and PharmGKB databases to obtain targets for gastric cancer.The intersection between the targets of jolkinolide B and those of gastric cancer was identified pinpoint potential targets for jolkinolide B in treating gastric cancer.The String database was utilized construct a protein-protein interaction(PPI)network.Bioconductor bioinformatics packages with R software was employed conduct Gene Ontology(GO)functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis on the shared targets.This process revealed significant regulatory pathways crucial for jolkinolide B's efficacy in treating gastric cancer.Cytoscape 3.7.1 software was utilized create the core network of"Potential Targets of Triptolide B in Gastric Cancer Treatment",and SYBYL-X2.1.1 software was employed conduct molecular docking validation of the selected main active ingredients and critical targets.Results Jolkinolide B may target multiple proteins,including MAPK1,glycogen synthase kinae-3β(GSK-3β),and JUN,impacting the proliferation,invasion,and metastasis of gastric cancer,ultimately inhibiting its growth.Conclusion We predicted the possible molecular mechanism of jolkinolide B in the treatment of gastric cancer to provide guide information for the subsequent experimental research and clinical application.

Objective To explore the mechanism of cinobufagin(CBG)in treating gastric cancer based on network pharmacology combined with bioinformatics and molecular docking technology.Methods Active ingredients and potential targets of CBG in treating gastric cancer were collected from PubChem,TCMSP,and SwissTargetPrediction databases.Transcriptional data of gastric cancer samples were obtained from TGGA database,and gastric cancer-related targets were identified through differential gene analysis.Intersection of targets between CBG and gastric cancer diseases was subjected to Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis.Protein-protein interaction(PPI)network of common targets was constructed using STRING database,and core targets were selected using Cytoscape software.Molecular docking verification of core targets screened with SYBYL-X 2.1.1 software was conducted with CBG.Results CBG treatment of gastric cancer involved 59 targets,with 19 key targets identified.Key targets such as aurora kinase A(AURKA),cyclin-dependent kinase 1(CDK1),enhancer of zeste homolog 2(EZH2),hepatocyte growth factor receptor(MET),matrix metallopeptidase 3(MMP-3),progesterone receptor(PGR),prostaglandin-endoperoxide synthase 1(PTGS1),and thymidylate synthase(TYMS)which exhibited good binding activity with CBG and were closely associated with gastric cancer prognosis.Conclusion CBG may exert anti-gastric cancer effects through multiple targets and pathways.

Aim To explore the relevant mechanisms of isoliquiritigenin(ISL)in inhibiting the proliferation and migration of vascular smooth muscle cells(VSMCs)by regulating the GRB2/ERK signaling pathway.Methods Human primary vascular smooth muscle cells(hVSMCs)were cultured,and stimulated with different concentrations of ISL and fixed concen-trations of growth factors PDGF-BB and EGF,respec-tively.Subsequently,the effect of overexpressing GRB2 on the efficacy of ISL was observed.CCK-8 assay was used to detect cell proliferation;BrdU assay was used to detect DNA synthesis;Western blot was used to de-tect the expression levels of OPN,ICAM-1,VCAM-1,GRB2,ERK1/2,and p-ERK1/2;wound healing assay was used to detect cell migration;transwell assay was used to detect cell invasion.Results Compared with the blank control group and the ISL 20 mg·L-1 group,the PDGF-BB group and the EGF group showed increased cell viability and DNA synthesis,decreased cell migration distance,and increased number of inva-sive cells.Additionally,the expression levels of GRB2 and p-ERK1/2 increased.Compared with the PDGF-BB 40 μg·L-1group or the EGF 10 mg·L-1 group,the ISL drug intervention group showed decreased cell viability and DNA synthesis,increased migration dis-tance of cells,decreased number of invasive cells,and decreased expression levels of GRB2 and p-ERK1/2.Compared with the ISL 20 mg·L-1+PDGF-BB and ISL 20 mg·L-1+EGF groups,the groups with ISL+PDGF-BB+pcDNA-GRB2 group and ISL+EGF+pcDNA-GRB2 group showed increased expression lev-els of GRB2,p-ERK1/2,OPN,ICAM-1,and VCAM-1,increased cell viability and DNA synthesis,decreased migration distance,and increased number of invasive cells.Compared with the ISL+PDGF-BB+pcDNA-GRB2 group and the ISL+EGF+pcDNA-GRB2 group,the pcDNA-GRB2+PDGF-BB group or the pcDNA-GRB2+EGF group showed increased expres-sion levels of GRB2,p-ERK1/2,OPN,ICAM-1,and VCAM-1,increased cell viability and DNA synthesis,decreased migration distance,and increased number of invasive cells.Conclusions Isoliquiritigenin inhibits the proliferation and migration of vascular smooth mus-cle cells by regulating the GRB2/ERK signaling path-way.

Lung transplantation is an important means to treat end-stage lung disease and improve the survival rate and quality of life of patients. However, many postoperative complications seriously affect the prognosis of recipients. Accurate identification of key prognostic factors and construction of individualized and accurate prediction models are of great significance for postoperative prognosis evaluation, treatment strategy formulation and clinical decision-making. In recent years, the clinical prediction model of lung transplantation has gradually changed from traditional statistical methods to machine learning-driven. Compared with traditional models such as Cox regression and Logistic regression, machine learning models such as random forest, support vector machine and artificial neural network have certain advantages in postoperative survival rate prediction, early warning of complications and pulmonary function evaluation. However, their application is also affected by insufficient sample size and poor interpretability of models. Under the condition of small samples, the traditional model still has important value in prediction accuracy. The appropriate prediction model should be selected according to the clinical status of lung transplantation in China, considering the factors such as sample size, variable complexity and model interpretability. In the future, a multi-center, large-sample lung transplantation database should be constructed to further optimize and tap the potential of machine learning algorithms to improve the robustness and clinical applicability of the model.