OBJECTIVE: To analyze a patient with infertility due to complex chromosome rearrangement by optical genome mapping (OGM). METHODS: A female patient who was diagnosed with "primary infertility" at Shenzhen Longhua District Maternal and Child Health Care Hospital in April 2024 was selected as the study subject. Clinical data of the patient was collected. Chromosome G banding karyotyping analysis was carried out for the patient and her parents, in addition with OGM and copy number variation sequencing (CNV-seq). This study was approved by the Medical Ethics Committee of the Hospital (Ethics No.: 2023052504). RESULTS: The patient, a 33-year-old female, had infertility for the past 5 years. OGM revealed formation of two derivative chromosomes through rearrangement of chromosomes 5 and 18. A loss of heterozygosity on chromosome 5 was also detected by OGM and CNV-seq techniques. Both of her parents had a normal karyotype. CONCLUSION The OGM technique can refine the position of chromosomal breakpoints and determine the direction and position of insertional fragment. Combined with karyotype analysis, the OGM can accurately determine the chromosomal karyotype of the patient and facilitate genetic counseling.
Humans ; Female ; Adult ; Karyotyping ; DNA Copy Number Variations/genetics* ; Chromosome Mapping/methods* ; Chromosome Aberrations ; Infertility, Female/diagnosis*

Objective:To evaluate the clinical value of an obstetric intelligent assistant in predicting postpartum hemorrhage (PPH) after vaginal delivery.Methods:This retrospective cohort study included 4 832 women who delivered vaginally at ≥26 weeks of gestation at the Third Affiliated Hospital, Guangzhou Medical University between May 2023 and April 2025. Participants were categorized into PPH (382 cases, blood loss ≥500 ml within 24 h after delivery) and non-PPH groups (4 450 cases). Using traditional statistical methods combined with machine learning approaches, including support vector machines and extreme gradient boosting, supplemented with deep learning techniques, we developed a novel artificial neural network model—the obstetric intelligent assistant. This model provides a refined classification of PPH occurrence and estimated blood loss volume. The obstetric intelligent assistant integrates 70 antenatal and intrapartum risk factors through hospital information system interfacing to generate visualized risk probability outputs. Predictive performance was compared between the obstetric intelligent assistant and four conventional prediction tools (Chinese Labor Room Traffic Light System; Association of Women's Health, Obstetric and Neonatal Nurses; American College of Obstetrics and Gynecology Safe Motherhood Initiative; and California Maternal Quality Care Collaborative prediction tools) using receiver operating characteristic curve.Results:(1) For antenatal prediction, the obstetric intelligent assistant achieved an area under the curve of 0.826 (95% CI: 0.774-0.838), with sensitivity of 0.794 and specificity of 0.712, while the four conventional prediction tools showed area under the curve ranging from 0.569 to 0.586. (2) For intrapartum prediction, the obstetric intelligent assistant achieved an area under the curve of 0.786 (95% CI: 0.751-0.820), with sensitivity of 0.837 and specificity of 0.762, whereas the conventional tools showed area under the curve between 0.600 and 0.613. Conclusion:The obstetric intelligent assistant demonstrates superior performance in predicting PPH compared to conventional prediction tools.

Objective:To analyze a patient with infertility due to complex chromosome rearrangement by optical genome mapping (OGM).Methods:A female patient who was diagnosed with " primary infertility" at Shenzhen Longhua District Maternal and Child Health Care Hospital in April 2024 was selected as the study subject. Clinical data of the patient was collected. Chromosomal G banding karyotyping analysis was carried out for the patients and her parents, in addition with OGM and copy number variation sequencing (CNV-seq). This study was approved by the Medical Ethics Committee of the Hospital (Ethics No.: 2023052504).Results:The patient, a 33-year-old female, had infertility for the past 5 years. OGM revealed formation of two derivative chromosomes through rearrangement of chromosomal 5 and 18. A loss of heterozygosity on chromosome 5 was also detected by OGM and CNV-seq techniques. Both of her parents had a normal karyotype.Conclusion:The OGM technique can refine the position of chromosome breakpoints and determine the direction and position of insertional fragment. Combined with karyotype analysis, the OGM can accurately determine the chromosomal karyotype of the patient and facilitate genetic counseling.

Objective:To develop an admission assessment index system for hospice care tailored to emergency patients.Methods:Using a mixed-methods approach, a preliminary framework was established through literature review and qualitative interviews. From May to September 2024, a two-round Delphi consultation was conducted with 26 experts to screen and refine indicators. The final system was determined using a priority chart method for weight assignment.Results:Twenty-five experts in fields of emergency medicine, emergency nursing, palliative care nursing, palliative care medicine and general practice completed both consultation rounds. The experts ranged in age from 36 to 56 years and had 12 to 36 years of work experience. All held intermediate or higher professional titles. The effective recovery rates for the two rounds of consultation questionnaires were 96.15%(25/26) and 100.00%(25/25), respectively. Expert authority coefficients were 0.891 and 0.911, with Kendall′s coordination coefficients of 0.348 and 0.399 ( P<0.001), and variation coefficients ranging from 0.040 to 0.204 and 0.000 to 0.179. The finalized system comprises 5 primary indicators (weighted coefficients: life-limiting disease status 0.268, symptom control 0.236, patient/familywishes 0.201, social support needs 0.162, medical resource utilization 0.133) and 27 secondary indicators. Conclusion:The index system developed in this study provides a comprehensive and practical tool for identification of emergency patients requiring hospice care, facilitating timely clinical decision-making.

Objective: To analyze the epidemiological characteristics and changing trends of non suicidal self injury (NSSI) behaviors among middle school students in Jiading District of Shanghai, from 2015 to 2023, so as to provide a basis for the development of NSSI prevention and control measures among students. Methods: Using a stratified cluster random sampling method, a total of five times for Shanghai Adolescent Health Risk Behavior Surveys were conducted for every two years in Jiading District of Shanghai from 2015 to 2023. A total of 5 231 middle school students from junior high schools and senior high schools were selected for questionnaire surveys. Intergroup comparisons were performed using the x 2 test or the χ 2 trend test, and the JointPoint 5.0 software was used to analyze the changing trends, with the annual percent change (APC) used for evaluation. A binary Logistic regression model was employed to analyze the related factors of NSSI behavior among middle school students. Results: In 2023, the reported NSSI rate among middle school students in Jiading District was 14.2%. The rate was significantly higher among junior high school students (17.1%) than that among senior high school students (11.1%), and higher among females (19.2%) than that among males (10.0%) ( χ 2=10.04, 23.21, both P <0.01). From 2015 to 2023, the overall reported NSSI rate showed an increasing trend, rising from 8.6% in 2015 to 14.2% in 2023 ( χ 2 trend =22.25), with an APC of 6.64% ( t =3.49), and the APC for girls was 9.79 % ( t =3.20) (all P <0.05). Among students reporting NSSI, the proportion experiencing ≥6 episodes increased from 10.8% in 2015 to 19.2% in 2023 ( χ 2 trend =6.57, P <0.05). Multivariate Logistic regression analysis indicated that girls, junior high school students, those with insomnia, depressive emotion and drinkers had higher risks of NSSI, compared to boys, senior high school students, those without insomnia, non depressive emotion students and non drinkers ( OR =1.71, 1.96, 3.44, 4.76, 1.77, all P < 0.05 ). Conclusions The reported rate of NSSI among middle school students in Jiading District of Shanghai, increased annually from 2015 to 2023, and the proportion of repeated NSSI also showed an upward trend. Early intervention measures targeting middle school students, especially junior high school students and females, should be implemented to prevent and control its occurrence and development.

Metastasis remains the primary cause of cancer-related mortality worldwide. Circulating tumor cells (CTCs) represent critical targets for metastasis prevention and treatment. Traditional Chinese medicine may prevent lung cancer metastasis through long-term intervention in CTC activity. Tiao-Shen-Zhi-Ai Formular (TSZAF) represents a Chinese medicine compound prescription utilized clinically for lung cancer treatment. This study combined three principal active ingredients from TSZAF into a novel TSZAF monomer combination (TSZAF mc) to investigate its anti-metastatic effects and mechanisms. TSZAF mc demonstrated significant inhibition of proliferation, migration, and invasion in CTC-TJH-01 and LLC cells, while inducing cellular apoptosis in vitro. Moreover, TSZAF mc substantially inhibited LLC cell growth and metastasis in vivo. Mechanistically, TAZSF mc significantly suppressed the Wnt/β-catenin signaling pathway and CXCL5 expression in lung cancer cells and tissues. Additionally, TAZSF mc notably reduced neutrophil infiltration in metastatic lesions. These findings indicate that TSZAF mc inhibits lung cancer growth and metastasis by suppressing the Wnt/β-catenin signaling pathway and reducing CXCL5 secretion, thereby decreasing neutrophil recruitment and infiltration. TSZAF mc demonstrates potential as an effective therapeutic agent for lung cancer metastasis.
Lung Neoplasms/genetics* ; Wnt Signaling Pathway/drug effects* ; Animals ; Humans ; Drugs, Chinese Herbal/pharmacology* ; Mice ; Neoplasm Metastasis/prevention & control* ; Cell Proliferation/drug effects* ; Cell Line, Tumor ; Neutrophil Infiltration/drug effects* ; Down-Regulation/drug effects* ; Cell Movement/drug effects* ; beta Catenin/genetics* ; Apoptosis/drug effects* ; Mice, Inbred C57BL ; Male ; Neoplastic Cells, Circulating/drug effects*

Objective To explore the association between disease activity and health utility values(HUV)in patients with rheumatoid arthritis(RA)in China,and to analyze other factors that may affect health utility values,providing a basis for individualized treatment and health management for RA patients.Methods Based on the Chinese Registry of Rheumatoid arthritis cohort,this study included 1 017 diagnosed RA patients.The EQ-5D-3L scale was used to assess the health utility values,while clinical data,disease activity,and potential influencing fac-tors(such as age,gender,and comorbidities)were collected.Tobit regression models were employed to analyze the association between disease activity and health utility values,and to investigate other potential influencing factors.Results The median health utility value for RA patients was 0.78[0.59,0.89].Patients with moderate to high dis-ease activity had significantly lower health utility values as compared to those in remission phase or with low disease activity(median 0.70 vs.0.87,P＜0.001).Tobit regression analysis showed a significant association between disease activity and health utility values(P＜0.001).Additionally,older age,female gender,use of glucocorticoids,and co-morbidity with diabetes were associated with lower health utility values(P＜0.05).Conclusions Health utility values of RA patients are closely related to disease activity,with higher disease activity leading to a significant reduction in health utility values.Early control of RA disease activity may help improve patients' quality of life.

Objective To establish a multi-state Markov model of systemic lupus erythematosus(SLE)for patients in China and to explore the transition rule of organ damage accumulation and possible factors affecting the transition between states.Methods A retrospective cohort study was conducted using the data from CSTAR.The Systemic Lu-pus International Collaborating Clinics/American College of Rheumatology Damage Index(SDI)was divided into five irreversible disease states(SDI=0,1,2,≥3,and death,marked as S0,S1,S2,S3,Death).The R"mstate"package was used for statistical analysis.Results This study included 23 926 cases of SLE patients with cumulative follow-up of 12 030 visits.Among these patients,21 070 patients had no any organ damage at baseline.At the follow-up period,the transition probabilities of organ damage of S0→S1,S1→S2,S2→S3,S3→Death were 7.01％,12.58％,10.64％,and 12.19％,respectively.The multi-state Markov model showed that age,gender,disease dura-tion,SLEDAI score,corticosteroid dosage,and involvement of major organs were associated with the transition of or-gan damage status,each 1 year increased was associated with a 2％～3％increase in risk of damage accumulation risk(P＜0.01).Also,neurological(S0→S 1:HR=1.34;S1 →S2:HR=1.53;S2→S3:HR=1.73),cardiopulmonary(S0→S1:HR=3.66;S 1→S2:HR=1.51;S2→S3:HR=1.52),renal(S0→S 1:HR=1.24)and hematological involvement(S0→S1:HR=1.24)might be the risk factors.Conclusions The probability of organ damage accumulation in SLE pa-tients increases over time.Therefore,in the early stage of the disease,the involvement of important organs needs to be minimized and the treatment strategy should be dynamically adjusted at different stages of treatment.

Objective To investigate the efficacy of lacosamide combined with ketogenic diet in the treatment of pediatric epilepsy and its impacts on the levels of serum glial fibrillary acidic protein(GFAP)and specific protein of the central nervous system(S-100β).Methods A total of 64 chil-dren with epilepsy from July 2022 to April 2024 were selected and randomly divided into conventional group(n=32)receiving oral lacosamide tablets and combined group(n=32)receiving ketogenic di-et therapy based on the conventional group.The efficacy,cognitive function,and intelligence of chil-dren in both groups after treatment,as well as the levels of serum GFAP and S-100β,the frequency of seizures,and electroencephalogram(EEG)findings before and after treatment were evaluated.Results After treatment,the number of alpha waves,the Full-scale Intelligence Quotient(FIQ)of the Wechsler Intelligence Scale for Children,and the Montreal Cognitive Assessment(MoCA)scores increased in both groups,with a greater increase in the combined group compared to the conventional group,and the differences were statistically significant(P＜0.05).The levels of serum S-100β and GFAP,the frequency of seizures,and the number of cases with slow waves and epileptiform waves decreased after treatmen,and these indicators were lower in the combined group than in the conventional group,with sta-tistically significant differences(P＜0.05).The total effective rate was 90.63％in the combined group and 68.75％in the conventional group,with a statistically significant difference(P＜0.05).The incidence of adverse reactions was 12.50％in the combined group and 9.38％in the conventional group,with no statistically significant difference(P＞0.05).Conclusion Lacosamide combined with ketogenic diet shows good efficacy in the treatment of pediatric epilepsy,and the combined therapy improves neurological function by synergistically reducing the levels of GFAP/S-100β.

Electroencephalogram(EEG)refers to the electrical activity generated by neuronal discharges in the human brain,conventionallyrecorded on the scalp of the brain.EEG technology enables the non-invasive detection of electrophysiological activity in neuronal populations within the cerebral cortex,capturing millisecond-level changes in brain potentials with high temporal resolution.In recent years,lots of international researchers have leveraged EEG technology to investigate smoking addiction and further explore the millisecond-level electrophysiological changes in the brains of smokers.This review synthesizes recent advances in resting-state EEG and task-evoked event-related potential research among smokers,summarizing the electrophysiological activity changes associated with smoking addiction.Future researches will employ both longitudinal tracking and machine learning algorithms to further reveal the relationship between EEG signatures and smoking behaviors,thereby providing a scientific foundation for early intervention and treatment strategies targeting smoking addiction.