OBJECTIVE: Chromosome conformation-based karyotype analysis (C-MoKa) technology was used to test a couple who had experienced multiple adverse pregnancies in order to provide them with genetic counseling and reproductive guidance. METHODS: A couple presented at the Reproductive Medicine Center of the First Hospital of Lanzhou University in 2023 was selected as the study subject. Through C-MoKa testing, copy number variation sequencing (CNV-seq), and preimplantation genetic testing for aneuploidy (PGT-A), it was found that the couple's repeatedly miscarried fetuses and abnormal embryos exhibited highly similar chromosomal structural abnormalities. Using C-MoKa, the potential genetic abnormalities in both partners were traced, and reproductive guidance was provided based on the result. This study was approved by the Medical Ethics Committee of the Hospital (Ethics No.: LDYYSZLLKH2025-09). RESULTS: CNV-seq analysis of the couple's miscarriage fetal chorionic villi showed del(18)(q21.2q23)(28.90 Mb) and dup(13)(q31.2q34)(26.26 Mb). Chromosomal karyotyping analysis of both partners showed no abnormality. From 2024 to 2025, the couple underwent three rounds of PGT-A assisted reproduction. The first embryo test showed del(13)(q31.2q34)(26.77 Mb) and dup(18)(q21.2q23)(29.08 Mb). The second embryo test showed dup(13)(q31.2q34)(26.26 Mb) and del(18)(q21.2q23)(28.90 Mb). And the third embryo test results showed complex chromosomal abnormalities. In 2025, after genetic counseling, the couple had opted C-MoKa test, which has detected no abnormality in the wife, but a balanced 46,XY,t(13;18)(q31.2;q21.2) translocation in the husband. CONCLUSION As a high-throughput sequencing method based on the three-dimensional conformation of chromatin, C-MoKa has the advantages of high resolution and high accuracy, and can accurately detect balanced translocations with similar banding patterns. It has therefore offered a powerful new tool for chromosomal analysis.
Female ; Humans ; Male ; Pregnancy ; Abortion, Habitual/genetics* ; DNA Copy Number Variations ; Karyotyping/methods* ; Preimplantation Diagnosis ; Translocation, Genetic

Objective To evaluate answers to typical clinical questions related to neuro-ophthalmology generated by Artificial Intelligence(AI)Large Language Models(LLM)and to explore the performance of neuro-ophthalmology-related questions on LLM in a multidimensional manner using objective and expert assessment.Methods Multicenter,random-ized,cross-sectional pilot study.Thirty typical questions related to neuro-ophthalmology were selected based on four per-spectives:definition,etiology,clinical manifestations and signs,and treatment and prognosis,and were analyzed quantita-tively using Deepseek,Wenxin Yiyin 4.0,Doubao,and Kimi 1.5,which are four open-source LLMs in China,and quantita-tively analyzed with objective assessment;and quantitatively rated by three ophthalmologists using expert assessment for 120 answer texts.Three ophthalmology experts quantitatively scored the 120 answer texts.Three ophthalmologists quantita-tively scored the 120 answer texts.Level 3,5,and 4 Likert scales were developed according to the completeness,accura-cy,professionalism,relevance,and criticality of the question texts,respectively.The best-performing LLM was selected,and its performance was observed across the four types of questions.Additionally,three other experts assessed whether the best-performing one could be evaluated as a substitute for real-world doctor-patient communication.Results In the objective Chinese text reading difficulty analysis,the differences in total word count among the four LLMs were statistically significant(all P＜0.001).Of the four LLMs,Kimi 1.5 performed the best,with frequencies of 61％,29％,and 41％for the highest scores in completeness(3),accuracy and professionalism(5),and relevance and usefulness(4),respective-ly.Kimi 1.5 performed more consistently on the questions on the four areas of neuro-ophthalmologic disorders:definition,etiology,clinical manifestations and signs,treatment,and prognosis,with no between-group differences(P＞0.05).Con-clusion Chinese language LLMs have great potential in the clinical application of neuro-ophthalmology.Kimi 1.5 outper-forms other LLMs in terms of completeness,accuracy,professionalism,relevance,and usefulness,but it still cannot re-place real-world doctor-patient communication.There is a need to explore new diagnostic and therapeutic model of AI+physician in the future.

BACKGROUND:Metformin is currently considered the first-line medication for the treatment of type 2 diabetes.Metformin may delay the progression of osteoarthritis,but its specific mechanism of action remains unclear.OBJECTIVE:To evaluate the therapeutic effects and the related action mechanisms of metformin on osteoarthritis in rats.METHODS:(1)Network pharmacology:Potential common targets for metformin,osteoarthritis,and ferroptosis were screened using the CTD,SwissTargetPrediction,GeneCards,and OMIM databases.After importing the targets into the STRING database,protein-protein interaction analysis was conducted to identify the key targets for metformin,osteoarthritis,and ferroptosis.(2)Molecular docking:P53 and its downstream factor SLC7A11 protein structures in PDB format were downloaded from the PDB database.The 2D structure of metformin was converted to a 3D structure,and molecular docking of metformin with the proteins was performed using Discovery Studio 2019 Client.(3)In vivo experiments:Thirty male SD rats were randomly divided into three groups(n=10).The blank group did not receive surgery.The osteoarthritis model was established using the modified Hulth method for the model and metformin groups.One day after the surgery,rats in the metformin group were gavaged with metformin 200 mg/kg per day,while the blank and model groups were gavaged with physiological saline.Treatment continued for 4 weeks.Hematoxylin-eosin staining and Safranin O-fast green staining were used to observe the pathological morphology and structure of the knee cartilage,and Mankin scoring was performed.ELISA was used to measure the levels of tumor necrosis factor-α and interleukin-6 in the serum.The microplate method was used to measure serum ferroptosis-related indicators,including glutathione,malondialdehyde,and Fe2+.Immunofluorescence staining,western blot assay,and real-time qPCR were used to detect the protein and mRNA expression of P53,SLC7A11,glutathione peroxidase 4,proteoglycans,and matrix metalloproteinase 13 in the cartilage tissue of the rats.RESULTS AND CONCLUSION:(1)A total of 96 intersecting targets among metformin,osteoarthritis,and ferroptosis were identified.After protein-protein interaction analysis,77 potential targets were found.Further screening identified the core targets as TP53,AKT1,JUN,interleukin-6,MYC,interleukin-1β,and tumor necrosis factor-α,among others.(2)Docking analysis results showed that metformin bound strongly and stably with P53 and its downstream factor SLC7A11.(3)In the model group,the knee cartilage surface was irregular,with cartilage tissue defects and reduced chondrocyte numbers.Compared to the model group,the knee cartilage structure damage in the metformin group was significantly improved,with a smoother cartilage surface and increased chondrocyte numbers.The Mankin score in the model group was significantly higher than that in the blank group,while the Mankin score in the intervention group was significantly lower than that in the model group.(4)Compared with the model group,the metformin group had significantly lower levels of tumor necrosis factor-α,interleukin-6,malondialdehyde,and Fe2+,and significantly higher glutathione levels.(5)Compared to the model group,the metformin group had significantly increased protein and mRNA expression of SLC7A11,glutathione peroxidase 4,and proteoglycans,and significantly decreased protein and mRNA expression of P53 and matrix metalloproteinase 13 in their cartilage tissue.(6)The results indicate that metformin can effectively improve cartilage damage in osteoarthritis rats and alleviate chondrocyte ferroptosis by inhibiting the aberrantly activated P53/SLC7A11/glutathione peroxidase 4 signaling pathway.This improvement in chondrocyte iron metabolism and lipid peroxidation response further reduces cartilage matrix degradation and prevents further cartilage damage and inflammatory response.

BACKGROUND:Metformin is currently considered the first-line medication for the treatment of type 2 diabetes.Metformin may delay the progression of osteoarthritis,but its specific mechanism of action remains unclear.OBJECTIVE:To evaluate the therapeutic effects and the related action mechanisms of metformin on osteoarthritis in rats.METHODS:(1)Network pharmacology:Potential common targets for metformin,osteoarthritis,and ferroptosis were screened using the CTD,SwissTargetPrediction,GeneCards,and OMIM databases.After importing the targets into the STRING database,protein-protein interaction analysis was conducted to identify the key targets for metformin,osteoarthritis,and ferroptosis.(2)Molecular docking:P53 and its downstream factor SLC7A11 protein structures in PDB format were downloaded from the PDB database.The 2D structure of metformin was converted to a 3D structure,and molecular docking of metformin with the proteins was performed using Discovery Studio 2019 Client.(3)In vivo experiments:Thirty male SD rats were randomly divided into three groups(n=10).The blank group did not receive surgery.The osteoarthritis model was established using the modified Hulth method for the model and metformin groups.One day after the surgery,rats in the metformin group were gavaged with metformin 200 mg/kg per day,while the blank and model groups were gavaged with physiological saline.Treatment continued for 4 weeks.Hematoxylin-eosin staining and Safranin O-fast green staining were used to observe the pathological morphology and structure of the knee cartilage,and Mankin scoring was performed.ELISA was used to measure the levels of tumor necrosis factor-α and interleukin-6 in the serum.The microplate method was used to measure serum ferroptosis-related indicators,including glutathione,malondialdehyde,and Fe2+.Immunofluorescence staining,western blot assay,and real-time qPCR were used to detect the protein and mRNA expression of P53,SLC7A11,glutathione peroxidase 4,proteoglycans,and matrix metalloproteinase 13 in the cartilage tissue of the rats.RESULTS AND CONCLUSION:(1)A total of 96 intersecting targets among metformin,osteoarthritis,and ferroptosis were identified.After protein-protein interaction analysis,77 potential targets were found.Further screening identified the core targets as TP53,AKT1,JUN,interleukin-6,MYC,interleukin-1β,and tumor necrosis factor-α,among others.(2)Docking analysis results showed that metformin bound strongly and stably with P53 and its downstream factor SLC7A11.(3)In the model group,the knee cartilage surface was irregular,with cartilage tissue defects and reduced chondrocyte numbers.Compared to the model group,the knee cartilage structure damage in the metformin group was significantly improved,with a smoother cartilage surface and increased chondrocyte numbers.The Mankin score in the model group was significantly higher than that in the blank group,while the Mankin score in the intervention group was significantly lower than that in the model group.(4)Compared with the model group,the metformin group had significantly lower levels of tumor necrosis factor-α,interleukin-6,malondialdehyde,and Fe2+,and significantly higher glutathione levels.(5)Compared to the model group,the metformin group had significantly increased protein and mRNA expression of SLC7A11,glutathione peroxidase 4,and proteoglycans,and significantly decreased protein and mRNA expression of P53 and matrix metalloproteinase 13 in their cartilage tissue.(6)The results indicate that metformin can effectively improve cartilage damage in osteoarthritis rats and alleviate chondrocyte ferroptosis by inhibiting the aberrantly activated P53/SLC7A11/glutathione peroxidase 4 signaling pathway.This improvement in chondrocyte iron metabolism and lipid peroxidation response further reduces cartilage matrix degradation and prevents further cartilage damage and inflammatory response.

Objective To evaluate answers to typical clinical questions related to neuro-ophthalmology generated by Artificial Intelligence(AI)Large Language Models(LLM)and to explore the performance of neuro-ophthalmology-related questions on LLM in a multidimensional manner using objective and expert assessment.Methods Multicenter,random-ized,cross-sectional pilot study.Thirty typical questions related to neuro-ophthalmology were selected based on four per-spectives:definition,etiology,clinical manifestations and signs,and treatment and prognosis,and were analyzed quantita-tively using Deepseek,Wenxin Yiyin 4.0,Doubao,and Kimi 1.5,which are four open-source LLMs in China,and quantita-tively analyzed with objective assessment;and quantitatively rated by three ophthalmologists using expert assessment for 120 answer texts.Three ophthalmology experts quantitatively scored the 120 answer texts.Three ophthalmologists quantita-tively scored the 120 answer texts.Level 3,5,and 4 Likert scales were developed according to the completeness,accura-cy,professionalism,relevance,and criticality of the question texts,respectively.The best-performing LLM was selected,and its performance was observed across the four types of questions.Additionally,three other experts assessed whether the best-performing one could be evaluated as a substitute for real-world doctor-patient communication.Results In the objective Chinese text reading difficulty analysis,the differences in total word count among the four LLMs were statistically significant(all P＜0.001).Of the four LLMs,Kimi 1.5 performed the best,with frequencies of 61％,29％,and 41％for the highest scores in completeness(3),accuracy and professionalism(5),and relevance and usefulness(4),respective-ly.Kimi 1.5 performed more consistently on the questions on the four areas of neuro-ophthalmologic disorders:definition,etiology,clinical manifestations and signs,treatment,and prognosis,with no between-group differences(P＞0.05).Con-clusion Chinese language LLMs have great potential in the clinical application of neuro-ophthalmology.Kimi 1.5 outper-forms other LLMs in terms of completeness,accuracy,professionalism,relevance,and usefulness,but it still cannot re-place real-world doctor-patient communication.There is a need to explore new diagnostic and therapeutic model of AI+physician in the future.

Objective To explore the mechanism by which zinc-regulated transporters, iron-regulated transporter-likeprotein 4 (ZIP4) regulates glycolysis and its impact on tumor progression in cholangiocarcinoma (CCA), providing a theoretical basis for targeted therapy of CCA. Methods ZIP4 expression in CCA was analyzed using the GEPIA database. Immuno-histochemistry (IHC) was used to detect ZIP4 expression in 20 paired CCA and adjacent non-tumor tissues. Stable ZIP4-overexpressing CCA cell lines (ZIP4-OE) were established. Gene set enrichment analysis was used to screen differentially expressed genes and pathways in ZIP-OE CCA cells. ZIP4, N-myc proto-oncogene protein (MYCN), and histone-lysine N-methyltransferase 2E (KMT2E) were knocked down using small interfering RNAs (siRNAs). The expression of glycolysis-related gene (glucose transporter 1 [Glut1], hexokinase 2 [HK2], and lactate dehydrogenase A [LDHA]) was measured by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). Glycolytic activity was assessed by measuring the extracellular acidification rate (ECAR). Cell proliferation was evaluated using colony formation assays, and cell migration was assessed using Transwell assays. A xenograft mouse model was constructed to examine CCA tumor growth. Protein levels of ZIP4, KMT2E, H3K4me3 (tri-methylation of lysine 4 on histone H3), and MYCN were detected by Western blotting. Results GEPIA database analysis and IHC results confirmed significantly higher ZIP4 expression levels in CCA tissues compared to adjacent non-tumor tissues (P＜0.05). Compared to the control group, the ZIP4-OE group exhibited a significantly increased ECAR, along with significantly enhanced proliferation and migration abilities (P＜0.01). Conversely, knockdown of ZIP4 suppressed CCA cells proliferation and migration. GEPIA analysis indicated that ZIP4 upregulates the transcription of oncogene MYCN, as well as glycolysis-related genes. Knockdown of MYCN abolished the ZIP4 overexpression-induced upregulation of Glut1, HK2, and LDHA gene transcription, reduced glycolysis, and significantly inhibited CCA cell proliferation and migration (P＜0.05). Mechanistic studies demonstrated that ZIP4 increases H3K4me3 level via KMT2E, leading to MYCN transcription. Knockdown of KMT2E in CCA cells suppressed the ZIP4 overexpression-induced enhancement in H3K4me3 modification, resulting in MYCN downregulation and significantly reduced CCA cells proliferation and migration (P＜0.05). Conclusions ZIP4 upregulates H3K4me3 modification through KMT2E, which recruits transcription factors to activate the transcription of MYCN. This subsequently enhances cellular glycolysis and promotes the proliferation and migration of CCA cells.

BACKGROUND:Studies have shown that metformin has anti-inflammatory,anti-tumor,anti-aging and vasoprotective effects,and can inhibit the progression of osteoarthritis,but its specific mechanism of action remains unclear. OBJECTIVE:To investigate the mechanism of metformin on cartilage protection in a rat model of osteoarthritis. METHODS:Forty male Sprague-Dawley rats were randomly divided into four groups(n=10 per group):blank,control,sham-operated,and metformin groups.The blank group did not undergo any surgery.In the sham-operated group,the joint cavity was exposed.In the model group and the metformin group,the modified Hulth method was used to establish the osteoarthritis model.At 1 day after modeling,the rats in the metformin group were given 200 mg/kg/d metformin by gavage,and the model,blank,and sham-operated groups were given normal saline by gavage.Administration in each group was given for 4 weeks consecutively.Hematoxylin-eosin staining,toluidine blue staining,and safranin O-fast green staining were used to observe the morphological structure of rat knee joints.Immunohistochemical staining and western blot were used to detect the protein expression of SOX9,type Ⅱ collagen,a disintegrin and metalloproteinase with thrombospondin motifs 5(ADAMTS5),Beclin1,P62,phosphatidylinositol 3-kinase(PI3K),p-PI3K,protein kinase B(AKT),p-AKT,mammalian target of rapamycin(Mtor),and p-Mtor in rat cartilage tissue. RESULTS AND CONCLUSION:The results of hematoxylin-eosin,toluidine blue and safranin O-fast green staining showed smooth cartilage surface of the knee joints and normal histomorphology in the blank group and the sham-operated group,while in the model group,there was irregular cartilage surface of the knee joint and cartilage damage,with a decrease in the number of chondrocytes and the content of proteoglycans in the cartilage matrix.In the metformin group,there was a significant improvement in the damage to the structure of the cartilage in the knee joints of the rats,and the cartilage surface tended to be smooth,with an increase in the number of chondrocytes and the content of proteoglycans in the cartilage matrix.Immunohistochemistry staining and western blot results showed that compared with the control and sham-operated groups,the expression of SOX9,type Ⅱ collagen,and Beclin1 proteins in the cartilage tissue of rats in the model group was significantly decreased(P<0.05).Conversely,the expression of ADAMTS5,P62,as well as p-PI3K,p-AKT,and p-Mtor proteins was significantly increased(P<0.05).Furthermore,compared with the model group,the expression of SOX9,type Ⅱ collagen,and Beclin1 proteins in the cartilage tissue of rats in the metformin group was significantly increased(P<0.05),while the expression of ADAMTS5,P62,as well as p-PI3K,p-AKT,and p-Mtor proteins was significantly decreased(P<0.05).To conclude,Metformin can improve the autophagy activity of chondrocytes and reduce the degradation of cartilage matrix in osteoarthritis rats by inhibiting the activation of PI3K/AKT/Mtor signaling pathway,thus exerting a protective effect on articular cartilage.

Objective To investigate the expression profile of cell adhesion molecular 3(CADM3)on pulmonary endothelial cells,analyze its role in mediating specific adhesion to monocyte,and explore a new mechanism of hypoxia inducing peripheral monocyte infiltration in pulmonary vessels.Methods Human umbilical vein endothelial cells(HUVEC),rat pulmonary vascular endothelial cells(rPEC),and rat aortic endothelial cells(rAEC)were subjected,and divided into normoxic(21%O2)control group and hypoxic(1%O2 or 5%O2)treatment group.Analyzing the transcriptome data of HUVEC exposure to hypoxia for 8 h screened a differentially expressed molecule,CADM3.Cell adhesion experiments,siRNA interference,immunohistochemical assay,Western blotting,and flow cytometry were used to study the role of CADM3 in hypoxia specific high adhesion of HUVEC monocytes.Iron chelator deferoxamine(DFX)and shRNA interference were employed to enhance the expression of HIF-1α,and the effect of HIF-1 transcriptional activity on CADM3 expression was analyzed.Results Hypoxic treatment resulted in enhanced expression of CADM3 in HUVEC,and the expression level reached the peak at 6-8 h after hypoxia,and then decreased.Transfection with siRNA targeting CADM3 decreased the expression of CADM3,and significantly reduced the adhesion rate of hypoxic HUVEC-U937 cells when compared with the negative control group(P<0.05).Compared with the solvent control group,the protein levels of HIF-1α and its target protein STC2 in HUVEC treated with DFX(100 μmol/L)were increased.Transfection with shRNA targeting HIF-1α led the protein levels of HIF-1α and its target protein STC2 decreased,but had no effect on the protein expression of CADM3 in comparison to the negative control group.The protein level and distribution of CADM3 on the cell membrane were increased in hypoxic rPEC.No expression of CADM3 protein was found in the rAEC when compared with rPEC.After treatment with 5 μg/mL LPS,there were no significant changes in HIF-1α,STC2 and CADM3 in rPEC cultured under normoxia or hypoxia.The adhesion rate between hypoxia rPEC with CD11b+cells was the highest,with statistical significance(P<0.01).After incubation with anti-CADM3 antibody,the adhesion of hypoxic rPEC-U937 was significantly decreased compared with the solvent control group(P<0.05).Conclusion Hypoxia specifically induces the expression of CADM3 in pulmonary vascular endothelial cells in a HIF-1-independent manner,and promotes the specific adhesion of pulmonary vascular endothelial cells and monocytes induced by hypoxia.

Pregnancy with chronic kidney disease (CKD), particularly in stages 4-5, carries high risks of adverse outcomes including maternal renal failure, preeclampsia/eclampsia, fetal growth restriction, and preterm birth. This report described a 26-year-old woman with congenital solitary kidney, polycystic ovaries, and uterine septum due to PAX2 gene variant, complicated by CKD stage 4. Through multidisciplinary team precision management and individualized treatment strategies, including timely initiation of dialysis, the patient successfully maintained pregnancy until 34 +1 weeks and delivered a female infant via cesarean section. This case summarizes key management experiences for end-stage renal disease in pregnancy, highlighting early risk assessment, precise nutritional management, hemodialysis protocol optimization, and the crucial role of multidisciplinary collaboration, providing valuable references for managing CKD-complicated pregnancies.

Objective To evaluate the efficiency of intra-tumor and peri-tumor ultrasound radiomics models based on machine learning algorithms for predicting benign and malignant Breast Imaging Reporting and Data System (BI-RADS) 4 breast lesions, and provide insights into early diagnosis of breast cancer. Methods A retrospective analysis was conducted based on the medical records of 450 female patients who underwent breast ultrasound examination in the Affiliated Cancer Hospital of Xinjiang Medical University from June 2020 to April 2022. The patients were divided into the benign (n = 199) and malignant (n = 195) groups according to pathological examination, and randomized into the training (n = 275) and validation (n = 119) sets at a ratio of 7∶3. Radiomics features were extracted and screened. Intra-tumor, peri-tumor, and intra-tumor + peri-tumor ultrasound radiomics models were constructed based on three machine learning algorithms, including logistic regression (LR), support vector machine (SVM), and multi-layer perceptron (MLP). Receiver operating characteristics (ROC) curves, calibration curves, and decision curves were plotted to evaluate the efficacy of the radiomics models for prediction of benign and malignant breast lesions. Results A total of 17 intra-tumor, 16 peri-tumor, and 17 intra-tumor + peri-tumor radiomics features were selected for model construction. Based on LR, MLP, and SVM algorithms, the intra-tumor + peri-tumor radiomics models showed higher predictive efficacy than intra-tumor and peri-tumor radiomics models. The predictive efficacy of intra-tumor, peri-tumor, and intra-tumor + peri-tumor radiomics models were higher based on the SVM algorithm than based on LR and MLP algorithms. For the intra-tumor radiomics model based on the SVM algorithm, the area under the ROC curve (AUC), accuracy, sensitivity, and a specificity were 0.909, 0.851, 0.860, and 0.842, respectively, in the training set and 0.866, 0.832, 0.847, and 0.817, respectively, in the validation set. For the peri-tumor radiomics model based on the SVM algorithm, these values were 0.899, 0.855, 0.882, and 0.827, respectively, in the training set and 0.844, 0.815, 0.847, and 0.783, respectively, in the validation set. For the intra-tumor + peri-tumor radiomics model based on the SVM algorithm, these values were 0.943, 0.876, 0.860, and 0.892, respectively, in the training set and 0.881, 0.849, 0.915, and 0.783, respectively, in the validation set. Conclusion The intra-tumor and peri-tumor ultrasound radiomics models based on machine learning algorithms are highly valuable for prediction of benign and malignant BI-RADS 4 breast lesions. The intra-tumor + peri-tumor ultrasound radiomics model based on the SVM algorithm has the optimal efficacy for prediction of benign and malignant BI-RADS 4 breast lesions.