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.

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 affected members, while unaffected family members all 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.
Humans ; Female ; Dentinogenesis Imperfecta/genetics* ; Collagen Type I/genetics* ; Adult ; Pedigree ; Mutation ; Male ; Phenotype ; Exome Sequencing

To investigate the effectiveness of a self-developed intelligent medical record writing assistant in enhancing the efficiency of discharge record writing and improving the quality of discharge records, and to assess physicians' satisfaction with the assistant.

Objective To explore the effects of oleanolic acid on NF-κB/caspase-9 signaling pathway in kidneys of rat with diabetic nephropathy.Methods The diabetic nephropathy model rats were established,and the model rats were randomly divided intooleanolic acid low,medium and high dose groups,metformin group,and model group,with another 12 healthy SD rats as control group.The levels of blood glucose were measured at weeks 1,2 and 3 post-drug administration,and blood lipid and 24h urine urinary microalbumin(UMA)were measured after entire drug administration.Furthermore,we also detected the renal histopathology of rats,apoptosis of renal tubular,glomerular cells,tumor necrosis factor-α(TNF-α),interleukin-6(IL-6)and protein expression of NF-κB/caspase-9 signaling pathway.Results Compared with the control group,the model group demonstrated higher levels of blood glucose at weeks 1,2 and 3,blood lipid,UMA,TNF-α and IL-6,higher proportion of apoptotic renal tubular and glomerular,and higher expressions of caspase-9 protein and p-NF-κB p65/NF-κB p65(P＜0.05).Compared with the model group,the pathological damage of renal tissue in the metformin group and oleanolic acid low,middle and high dose groups were alleviated,the levels of blood glucose at weeks 1,2 and 3,blood lipid,UMA,TNF-α and IL-6,the proportion of apoptotic renal tubular and glomerular,and the expressions of caspase-9 proteins and p-NF-κB p65/NF-κB p65 were decreased,and these indexes in oleanolic acid groups showed a dose-dependent manner(P＜0.05).Conclusion Oleanolic acid can improve the metabolism of glucose and lipid,reduce the pathological damage of renal tissue,inhibit the apoptosis of renal tubular and glomerular,and inhibit the NF-κB/caspase-9 pathway in diabetic nephropathy rats.

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.

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 establish an early warning model of oral infection risk in patients with acute leukemia undergoing chemotherapy and to verify its predictive efficacy, so as to provide reference for formulating strategies to prevent oral infections.Methods:A retrospective study was conducted to select 288 patients with acute leukemia undergoing chemotherapy from January 2021 to January 2023 in Hematology Hospital of Chinese Academy of Medical Sciences (Institute of Hematology, Chinese Academy of Medical Sciences) as the training set. According to whether they developed oral infection after chemotherapy, they were divided into the infected group and the non-infected group. The risk factors of oral infection in patients with acute leukemia undergoing chemotherapy were investigated, and a risk warning model was established. A total of 246 acute leukemia undergoing chemotherapy patients admitted to the same hospital from February 2023 to February 2024 were selected as the validation set to conduct external verification of the model.Results:The oral infection rate was 19.44% (56/288) in the training set. There were 21 males and 35 females in the infected group (56 cases), with 49 cases<60 years old and 7 cases ≥60 years old. There were 102 males and 130 females in the non infected group (232 cases), with 196 cases<60 years old and 36 cases ≥60 years old. Multivariate analysis showed that neutrophil count <1.5×10 9/L, nutritional risk screening 2002≥3 points, high-dose of methotrexate, antibiotic types ≥3, poor oral self-cleaning habits, oral pH ≤6.5 were the risk factors for oral infection in patients with acute leukemia undergoing chemotherapy ( OR values were 2.716-10.074, all P<0.05). Based on this, the risk early warning model was as follows: Logit ( P)=-5.849+2.310× neutrophil count <1.5×10 9/L+1.363× nutritional risk screening 2002≥3 points +1.150× high-dose methotrexate +1.132× antibiotic types ≥3 + 1.044× oral pH ≤6.5 + 0.999× poor oral self-cleaning habits. The area under receiver operator characteristics curves (ROC) curve of this model Logit ( P) was 0.892, the maximum approximate entry index was 0.653, the sensitivity was 0.804, and the specificity was 0.849. Hosmer-Lemeshow test results indicated that χ2=4.91, P=0.768. For external validation, the goodness of fit test results were χ2=6.47, P=0.595. The area under ROC curve was 0.884, the sensitivity was 0.832, and the specificity was 0.825. Conclusions:The established early warning model of oral infection risk in patients with acute leukemia undergoing chemotherapy has good predictive value, which is helpful for medical staff to conduct early risk assessment of oral infection in such patients, and formulate countermeasures to reduce the incidence and improve the treatment effect of the disease.

AIM: To explore the efficacy of 0.05% cyclosporine A combined with olopatadine eye drops in treating allergic conjunctivitis-related dry eye disease.METHODS: A total of 63 patients(63 eyes)with allergic conjunctivitis-related dry eye disease in the People's Hospital of Guangxi Zhuang Autonomous Region from August 2022 to April 2023 were enrolled and randomly divided into control group(n=33)and observation group(n=30). The patients of the control group were administrated with 0.1% olopatadine eye drops and 0.3% sodium hyaluronate eye drops, while the observation group was administrated with 0.1% olopatadine eye drops and 0.05% cyclosporine A eye drops. The ocular surface disease index(OSDI), total ocular symptom score(TOSS), conjunctival congestion score, conjunctival papillae and follicle score, Schirmer I test(SⅠt), tear meniscus height(TMH), meibomian gland secretion ability and property score, meibomian gland loss area score, corneal fluorescein staining(CFS), tear film break-up time(BUT), noninvasive first tear film break-up time(NIBUTf), noninvasive average tear film break-up time(NIBUTav)before and after treatment and the drug safety during the treatment period of both groups of patients were evaluated.RESULTS: After treatment, OSDI, TOSS, conjunctival congestion score, conjunctival papillae and follicle score, SⅠt, TMH, meibomian gland secretion ability score and property score, CFS, BUT, NIBUTf, and NIBUTav of the observation group showed improvements compared with those before treatment(all P<0.017). Among these, OSDI, TOSS, conjunctival congestion score, conjunctival papillae and follicle score, BUT, NIBUTf, and NIBUTav demonstrated significant improvement compared with the control group(all P<0.05). There was no statistically significant difference in meibomian gland loss area score between the two groups before and after treatment(P>0.05). During the treatment period, there were no local or systemic adverse reactions.CONCLUSION: The combined use of 0.05% cyclosporine A and olopatadine eye drops can significantly improve ocular discomfort symptoms of patients with dry eye disease associated with allergic conjunctivitis, such as red eyes, itchy eyes and foreign body sensation, promote tear film stability and have high safety.