AIM: To construct a risk nomogram prediction model of macular edema(ME)based on the risk factors of ME after phacoemulsification in diabetic cataract(DC)patients.METHODS: A retrospective collection of data was conducted on 1 751 DC patients(1 751 eyes)who underwent cataract phacoemulsification surgery in the hospital from January 2022 to December 2024. Based on whether they developed ME after surgery, the patients were divided into the ME group(n=138)and the N-ME group(n=1 613). By conducting univariate and Logistic multiple regression analysis, the risk factors for postoperative ME in DC patients undergoing phacoemulsification were identified. A nomogram of risk prediction model was constructed, and the receiver operating characteristic(ROC)curve, calibration curve, Hosmer-Lemeshow goodness of fit test were plotted to evaluate the discrimination and calibration of the model. The decision curve was used to evaluate the clinical return on investment of the model.RESULTS: Age, course of diabetes, proportion of insulin treatment, proportion of retinopathy, best corrected visual acuity(BCVA), central subfield macular thickness(CSMT), macular volume, glycated hemoglobin(HbA1c), vascular endothelial growth factor(VEGF)in the ME group were higher than those in the N-ME group(all P<0.05). Multivariate Logistic regression analysis showed that diabetes course, retinopathy, BCVA, CSMT, macular volume, HbA1c and VEGF were the risk factors for ME after phacoemulsification in DC patients(all P<0.05). A nomogram of risk prediction model was constructed based on risk factors, and the ROC curve suggested good model differentiation [AUC of training set was 0.998(95% CI: 0.997-1.000), and AUC of validation set was 0.999(95% CI: 0.997-1.000)], set: R2=0.917, χ2=0.806, P=0.999; verification set: R2=0.900, χ2=0.675, P=1.000). The decision curve showed that the model had a high net return rate within the probability range of 0.00-1.00 threshold.CONCLUSION: Diabetes course, retinopathy, BCVA, CSMT, macular volume, HbA1c and VEGF are risk factors for ME after cataract phacoemulsification in DC patients. The nomogram of risk prediction model based on this construction has good differentiation and consistency in predicting the risk of ME after cataract phacoemulsification in DC patients.

Objective　To analyse the crude detection rate and trends of newly detected HIV/AIDS cases in medical institutions in China from 2017 to 2023, and to provide a reference for optimizing HIV testing strategies in medical institutions. Methods　Data on HIV testing and newly reported HIV/AIDS cases were analysed using data from the Comprehensive AIDS Prevention and Control Information System of the China Information System for Disease Control and Prevention for the period from 2017 to 2023. HIV testing in medical institutions includes patients tested preoperatively, those tested before transfusion, those tested in sexually transmitted disease (STD) clinics, prenatal care clinics, and other types of patients. Descriptive statistical analysis and χ2 test were performed using SAS 9.4 software. Joinpoint regression was performed using Joinpoint 4.9.0 software to analyse trends of the crude detection rates over time. Results　From 2017 to 2023, the person-times of HIV tests in medical institutions increased from 143 million to 255 million, with an increase of 78.07%. The number of newly detected HIV/AIDS cases increased from 74 000 to 88 000 and then declined to 69 000. The crude detection rate of new HIV/AIDS cases declined from 5.18/10 000 to 2.71/10 000, showed a declining trend, the mean annual percentage change was -9.99%(P<0.001). The crude detection rate of new HIV/AIDS cases in STD clinics was the highest among all types of clinic visits (12.79/10 000-24.47/10 000), and the crude detection rate of new cases among all types of clinic visits showed a decreasing trend(P<0.05). Among different medical institutions, general hospitals were the most important source of the number of tests and the number of newly detected HIV/AIDS cases, accounting for more than 62.93% and 62.68%, respectively. Specialised medical institutions had the highest crude detection rate of new cases, which was maintained at more than 5.13/10 000. The crude detection rate of new cases for all four types of medical institutions, except for primary medical institutions, showed a decreasing trend (P<0.05). Conclusions　The detection rate of new cases in medical institutions showed a decreasing trend in 2017-2023, and the efficiency of STD clinics testing and detection was higher among all types of attendees. General hospitals are the main source of new cases detection, and testing in specialised medical institutions is more efficient. Testing should be strengthened in key groups of patients and in key medical institutions.

Temporomandibular joint osteoarthritis (TMJ-OA) is a common disease often accompanied by pain, seriously affecting physical and mental health of patients. Abnormal innervation at the osteochondral junction has been considered as a predominant origin of arthralgia, while the specific mechanism mediating pain remains unclear. To investigate the underlying mechanism of TMJ-OA pain, an abnormal joint loading model was used to induce TMJ-OA pain. We found that during the development of TMJ-OA, the increased innervation of sympathetic nerve of subchondral bone precedes that of sensory nerves. Furthermore, these two types of nerves are spatially closely associated. Additionally, it was discovered that activation of sympathetic neural signals promotes osteoarthritic pain in mice, whereas blocking these signals effectively alleviates pain. In vitro experiments also confirmed that norepinephrine released by sympathetic neurons promotes the activation and axonal growth of sensory neurons. Moreover, we also discovered that through releasing norepinephrine, regional sympathetic nerves of subchondral bone were found to regulate growth and activation of local sensory nerves synergistically with other pain regulators. This study identified the role of regional sympathetic nerves in mediating pain in TMJ-OA. It sheds light on a new mechanism of abnormal innervation at the osteochondral junction and the regional crosstalk between peripheral nerves, providing a potential target for treating TMJ-OA pain.
Animals ; Osteoarthritis/physiopathology* ; Mice ; Sympathetic Nervous System/physiopathology* ; Temporomandibular Joint Disorders/physiopathology* ; Arthralgia ; Sensory Receptor Cells ; Disease Models, Animal ; Norepinephrine ; Male ; Temporomandibular Joint/physiopathology* ; Pain Measurement

Objective:To investigate the clinical phenotype and genetic characteristics of a family with Dentinogenesis imperfecta type Ⅰ(DGI-Ⅰ).Methods:Clinical data were collected from a patient with DGI-Ⅰ admitted to the Reproductive Medicine Department of the Affiliated Hospital of Jining Medical University in March 2024. Clinical and familial data were retrospectively collected. Peripheral blood samples (5 mL each) were obtained from the proband and her family members for genomic DNA extraction, followed by whole-exome sequencing (WES) and Sanger sequencing validation. The pathogenicity of the detected variants was assessed according to the Classification Standards and Guidelines for Genetic Variants formulated by the American Society of Medical Genetics and Genomics (ACMG) (hereinafter referred to as the " ACMG Guidelines" ). The study was approved by the Ethics Committee of the Affiliated Hospital of Jining Medical University (Ethics No. 2024-08-C012), and written informed consent for clinical research were obtained from all participants.Results:The proband, a 35-year-old female, presented with translucent yellow primary teeth and progressive browning, darkening, and loss of permanent teeth, without skeletal abnormalities. Affected family members exhibited similar phenotypes. Genetic testing revealed a heterozygous COL1A2 variant (c.1503+ 1G>A) in the patient and other members, while unaffected family all members lacked this variant. Based on the ACMG Guidelines, this variant was classified as likely pathogenic(PM4 + PP1_Strong + PM2_Supporting). Conclusion:The COL1A2 c. 1503+ 1G>A heterozygous variant is the disease-causing mutation in this family. Above finding has expanded the mutational spectrum of the COL1A2 gene and provided a basis for genetic counseling and diagnosis in similar cases.

Objective To explore the value of support vector machine(SVM)model based on gray matter volume(GMV)for identifying amyotrophic lateral sclerosis(ALS),also to analyze the relevant brain regions.Methods MR 3D T1WI data of 60 ALS patients(ALS group)and 60 healthy volunteers(control group)were retrospectively analyzed.Taken GMV of each brain region obtained by voxel-based morphometry as the input features.F-score analysis was used to select feature with the highest classification accuracy to construct SVM model.Receiver operating characteristic curve was drawn to evaluate the efficacy of SVM model for identifying ALS,and top 10％was used as the weight threshold to obtain gray matter brain regions contributed the most to this model.Results SVM model constructed based on the top 40％GMV features had the highest classification accuracy(82.50％),with sensitivity,specificity and area under the curve(AUG)of 85.05％,80.40％and 0.890,respectively.The left precentral gyrus,left anterior cingulate gyrus and paracingulate gyrus,right middle temporal gyrus,opercular part of left inferior frontal gyrus,right dorsolateral superior frontal gyrus,left temporal pole:middle temporal gyrus,right superior occipital gyrus,orbital part of right middle frontal gyrus,right calcarine fissure and surrounding cortex,right fusiform gyrus were the top 1-10 gray matter brain regions contributed to this model.Conclusion ALS had specific GMV change pattern.SVM model based on GMV could be used to effectively identify ALS,while the left precentral gyrus was the most contributive brain region to this model.

Objective:To investigate whether continued low-dose aspirin (LDA) intervention affects the incidence of pre-eclampsia (PE) and adverse pregnancy outcomes in pregnant women with high-risk PE screening in the first trimester and reassessed as low risk at 28 weeks of gestation.Methods:This study was a prospective observational cohort study. From April 2022 to April 2024, a total of 106 pregnant women who underwent prenatal examination in the Affiliated Jiangyin Hospital of Nantong University were enrolled. They were assessed as high risk of PE by multiple indicators combined screening at 11-13 +6 weeks of gestation, received LDA intervention, and were reassessed as low risk of PE at 28 weeks of gestation. The patients were divided into withdrawal group (49 cases) and continuation group (57 cases). The incidence of PE and adverse pregnancy outcomes were compared between the two groups. Results:(1) There were no statistically significant differences in general conditions and the incidence of pregnancy complications between the two groups (all P>0.05). During the PE risk screening at 11-13 +6 weeks of gestation, there were no statistically significant differences in mean arterial pressure (MAP) and ultrasound uterine artery pulsation index (UtPI) between the two groups (all P>0.05), but the placental growth factor (PlGF) level in the withdrawal group was significantly lower than that in the continuation group ( P=0.023). There was no significant difference in the proportion of pregnant women with high risk of PE before 32 weeks and 34 weeks of pregnancy between the two groups (all P>0.05). (2) There were 7 cases (14%, 7/49) of PE in the withdrawal group, including 1 case (2%, 1/49) of early-onset PE and 3 cases (6%, 3/49) of PE before 37 weeks of pregnancy. There were 11 cases (19%, 11/57) of PE in the continuation group, including 2 cases (4%, 2/57) of early-onset PE and 4 cases (7%, 4/57) of PE before 37 weeks of pregnancy. There were no significant differences in the incidence of PE (including early-onset PE and PE before 37 weeks of pregnancy), gestational hypertension, severe PE, chronic hypertension complicated with PE and chronic hypertension complicated with pregnancy between the two groups (all P>0.05). (3) There were no significant differences in cesarean section rate, preterm birth rate, placental abruption, postpartum hemorrhage, fetal growth restriction, fetal distress rate, neonatal birth weight, neonatal asphyxia, and 1-minute and 5-minute Apgar scores between the two groups (all P>0.05). No stillbirth occurred in the two groups. Conclusion:For pregnant women with high risk of PE screening in the first trimester and taking LDA intervention, there is no difference in the incidence of PE and adverse pregnancy outcomes whether to continue LDA or not after being reassessed as low risk at 28 weeks of gestation.

Objective:To develop a convolutional neural network model of whole slide imaging of cerebrospinal fluid cells for rapid and accurate identification and classification of tumor cells in cerebrospinal fluid.Methods:A total of 8 692 cerebrospinal fluid cytology smears from Huashan Hospital Affiliated to Fudan University from January 2nd, 2019, to December 27th, 2024. As randomly assigned, the training set included 4 941 benign and 1 745 malignant samples, while the validation set comprised of 1 368 benign and 638 malignant samples. Whole-slide digital images were acquired using a cytopathology scanner, cells (clusters) were annotated for classification, and a deep learning model was constructed via tiled image patches for cell detection and classification. Model performance was evaluated using accuracy, sensitivity, specificity, and other indicators. The classification efficiency of manual microscopy was compared.Results:The model achieved a mean precision of 96.75% for cerebrospinal fluid cell classification. For malignant tumor cells, the classification accuracy was 96.61% (mAP=98.36%, AUC=0.97). Subtype classification accuracies for epithelial/epithelioid tumors and small round cell tumors were 97.13% (AUC=0.98) and 95.58% (AUC=0.93), respectively. Compared with manual microscopy, which took (9.70±0.82) minutes for classifying 200 cells, (18.27±1.21) minutes for 500 cells, and often exceeded 60 minutes or infeasible for full slides, the AI model took (3.46±0.49) seconds for 200 cells, (6.76±0.82) seconds for 500 cells, and a median of 48.57 seconds for full slides ( P<0.001), representing an efficiency improvement of approximately 161-170 times, significantly enhancing diagnostic efficiency. Conclusion:This fully automated hierarchical deep learning model enables efficient and accurate tumor cell identification and classification in CSF, providing an effective auxiliary tool for the rapid diagnosis of meningeal carcinomatosis.

Anticipatory anxiety is a negative emotion that arises when individuals encounter potential threats or uncertainties in the future. It is the core symptom of a variety of anxiety disorders, and is closely associated with the occurrence, severity, treatment outcome, and prognosis of anxiety disorders, which has garnered a growing amount of focus in clinical practice. Nevertheless, scientific research on anticipatory anxiety continues to face obstacles such as unclear pathological mechanisms, the absence of simple and consistent self-assessment tools, and effective interventions. To improve understanding of the role of anticipatory anxiety in the diagnosis and treatment of anxiety disorders, this study reviews pertinent domestic and international literature, and briefly introduces the concept, assessment and measurement, activation paradigm, pathological mechanisms, and interventions of anticipatory anxiety.

Objective: To investigate the basic situation of pre-analytical quality management in blood station laboratories in North China, and to provide baseline data for promoting the homogenization and standardization of these pre-analytical processes in each blood station laboratory. Methods: A cross-sectional status survey was designed based on the quality management regulations of blood stations, ISO15189 standards and relevant quality management requirements. This survey covering various aspects including laboratory general situation, sample collection and temporary storage, transportation, reception, and quality continuous improvement situations. Data analysis was performed on the survey results of each laboratory. Results: All the 38 blood station laboratories in North China had established a pre-analytical quality management system framework and implemented basic pre-analytical quality control activities; however, there were differences in implementation. 1) Among the 12 basic quality items, 3 items were monitored by all the investigated laboratories (100%), 6 items were monitored by the vast majority of laboratories (about 90%), and 3 items were monitored by a portion of laboratories (about 60%). There were no significant differences in the monitoring index among the three regions and among different types of laboratories (P>0.05). 2) Among the total of 26 items in the three key processes before testing (sample collection and storage, transportation, reception and processing), 12 items were monitored by all laboratories (100%), 11 items were monitored by the vast majority of laboratories (about 90%), and 3 items were monitored by a portion of laboratories (about 75%). There were no significant differences in monitoring index among different regions and types of laboratories (P>0.05). Conclusion: This survey provides a reference and basis for the gap analysis of the pre-analytical process quality management in 38 blood station laboratories across North China. It facilitates laboratories in identifying pre-analytical quality problems, resolving problems, preventing errors, and ensuring that the quality of blood samples before testing meets the established requirements. It lays a foundation for the homogenization of pre-analytical quality management in regional blood stations.

Objective: To determine the frequency and main reasons of unqualified samples by analyzing the quality of pre-analytical samples in blood stations in North China, thereby providing a reference and basis for gap analysis in the implementation of pre-analytical process quality management for participating laboratories and ensuring that only high-standard and high-quality blood samples proceed to testing. Methods: Data on the quality of pre-analytical samples from blood station laboratories in North China was collected via questionnaire. Statistical analysis were performed on: 1) the basic information of samples quality monitoring in the laboratories; 2) the distribution of the overall pre-analytical unqualified rate of samples and the pre-analytical unqualified rate of samples in each laboratory; 3) the distribution of reasons for sample disqualification. Results: 1) The overall pre-analytical unqualified rate of samples in blood station laboratories in North China was 4.55, with a total sigma level of 5.39σ. The 25th, 50th and 75th percentiles (P25, P50, P75) for the total unqualified rate were 0.00, 1.10 and 5.96, respectively. The corresponding percentiles for the Sigma level were 5.34σ, 5.71σ, and 6.00σ, respectively. The pre-analytical unqualified rate of serological and nucleic acid samples (4.89 vs 4.22) showed a significant difference (χ =9.575, P<0.05). 2) The average unqualified rate of samples in region A, B and C was 1.71, 9.50 and 12.64 (χ =1 590.721, P<0.05), and the sigma level was 5.66σ, 5.21σ and 5.16σ, respectively. 3) The main reasons for unqualified serological samples were chylous blood (72.65%), hemolysis (17.39%), abnormal hematocrit (5.80%), and insufficient volume (3.50%). The main reasons for the unqualified nucleic acid samples were chylous blood (78.26%), hemolysis (8.84%), failure to centrifuge as required (5.01%), abnormal hematocrit (4.66%), and insufficient volume (1.92%). Conclusion: In North China, the quality indicators for the pre-analytical processes in blood station laboratories are generally well-managed. Laboratories in region A outperformed the national average in pre-analytical specimen quality control. However, participating laboratories exhibit gaps in implementing pre-analytical quality management. Through effective analysis of pre-analytical process quality metrics and inter-laboratory comparisons, laboratories can identify discrepancies and address shortcomings. By establishing clear quality objectives, they can achieve continuous improvement and ensure the validity of test results.