OBJECTIVE: To establish and validate a novel diabetic retinopathy (DR) risk-prediction model using a whole-exome sequencing (WES)-based machine learning (ML) method. METHODS: WES was performed to identify potential single nucleotide polymorphism (SNP) or mutation sites in a DR pedigree comprising 10 members. A prediction model was established and validated in a cohort of 420 type 2 diabetic patients based on both genetic and demographic features. The contribution of each feature was assessed using Shapley Additive explanation analysis. The efficacies of the models with and without SNP were compared. RESULTS: WES revealed that seven SNPs/mutations ( rs116911833 in TRIM7, 1997T>C in LRBA, 1643T>C in PRMT10, rs117858678 in C9orf152, rs201922794 in CLDN25, rs146694895 in SH3GLB2, and rs201407189 in FANCC) were associated with DR. Notably, the model including rs146694895 and rs201407189 achieved better performance in predicting DR (accuracy: 80.2%; sensitivity: 83.3%; specificity: 76.7%; area under the receiver operating characteristic curve [AUC]: 80.0%) than the model without these SNPs (accuracy: 79.4%; sensitivity: 80.3%; specificity: 78.3%; AUC: 79.3%). CONCLUSION Novel SNP sites associated with DR were identified in the DR pedigree. Inclusion of rs146694895 and rs201407189 significantly enhanced the performance of the ML-based DR prediction model.
Diabetic Retinopathy/diagnosis* ; Humans ; Machine Learning ; Male ; Female ; Polymorphism, Single Nucleotide ; Middle Aged ; Exome Sequencing ; Aged ; Adult ; Pedigree ; Diabetes Mellitus, Type 2/complications* ; Genetic Predisposition to Disease ; Mutation

Objective:To investigate the feasibility of deep learning based on computed tomography(CT)radiomics in improving diagnostic accuracy for pulmonary nodules.Methods:A total of 500 patients with pulmonary nodules who admitted to our hospital from January 2023 to January 2024 were selected as study subjects,and they were randomly divided into a training set(350 patients)and a test set(150 patients)as 7:3 ratio.All patients underwent CT examination,and pathological diagnosis was used as gold standard to record pulmonary nodules that were judged by clinical judgment.The radiomics features were screened from the CT images of the patients,and these features were used to construct multiple machine learning models.The predictive value of different models in diagnosing pulmonary nodules was analyzed through confusion matrices and receiver operating characteristic(ROC)curve.Results:A total of 1,594 radiomics features,including 1,195 texture features(74.97%)that was the largest ratio,334 first-order histograms(20.95%),and 65 second-order histograms(4.08%),were extracted in this study.After least absolute shrinkage and selection operator(LASSO)regression analysis and ten-fold cross-validation processing,a total of six radiomics features were screened out.The screened radiomics features were incorporated respectively into four assembled models with machine learning,including ResNet50,DenseNet121,Inception_V3 and VGG19.The constructed models were evaluated respectively using the training set and the test set.The results showed that the assembled model had the highest accuracies in both training set and the test set(96.57%and 95.33%),which area under curve(AUC)values were 0.934 and 0.923,and specificities were 81.64%and 80.52%,and sensitivities were 90.25%and 88.71%,respectively.The results of consistency test indicated that the assembled model had the best classification consistency(Kappa=0.856,P<0.001)in the constructed diagnostic model for pulmonary nodule,which was the best-performing model.Conclusion:The deep learning technique based on CT radiomics has a certain feasibility in improving the diagnostic accuracy for pulmonary nodules,and the machine learning model that is included in this study has favorable predictive value in diagnosing pulmonary nodules.In them,the assembled model that is constructed on the basis of ResNet50,DenseNet121,Inception_V3,and VGG19 has better classification ability.

Objective:To investigate the feasibility of deep learning based on computed tomography(CT)radiomics in improving diagnostic accuracy for pulmonary nodules.Methods:A total of 500 patients with pulmonary nodules who admitted to our hospital from January 2023 to January 2024 were selected as study subjects,and they were randomly divided into a training set(350 patients)and a test set(150 patients)as 7:3 ratio.All patients underwent CT examination,and pathological diagnosis was used as gold standard to record pulmonary nodules that were judged by clinical judgment.The radiomics features were screened from the CT images of the patients,and these features were used to construct multiple machine learning models.The predictive value of different models in diagnosing pulmonary nodules was analyzed through confusion matrices and receiver operating characteristic(ROC)curve.Results:A total of 1,594 radiomics features,including 1,195 texture features(74.97%)that was the largest ratio,334 first-order histograms(20.95%),and 65 second-order histograms(4.08%),were extracted in this study.After least absolute shrinkage and selection operator(LASSO)regression analysis and ten-fold cross-validation processing,a total of six radiomics features were screened out.The screened radiomics features were incorporated respectively into four assembled models with machine learning,including ResNet50,DenseNet121,Inception_V3 and VGG19.The constructed models were evaluated respectively using the training set and the test set.The results showed that the assembled model had the highest accuracies in both training set and the test set(96.57%and 95.33%),which area under curve(AUC)values were 0.934 and 0.923,and specificities were 81.64%and 80.52%,and sensitivities were 90.25%and 88.71%,respectively.The results of consistency test indicated that the assembled model had the best classification consistency(Kappa=0.856,P<0.001)in the constructed diagnostic model for pulmonary nodule,which was the best-performing model.Conclusion:The deep learning technique based on CT radiomics has a certain feasibility in improving the diagnostic accuracy for pulmonary nodules,and the machine learning model that is included in this study has favorable predictive value in diagnosing pulmonary nodules.In them,the assembled model that is constructed on the basis of ResNet50,DenseNet121,Inception_V3,and VGG19 has better classification ability.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

Objective: To determine IgG antibody levels of measles, rubella, mumps in healthy population in Shanghai from 2010 to 2020 and analyze the trend of antibody changes in different age groups. Methods: 10 828 healthy people without measles, rubella and mumps in Shanghai were included in the study from 2010 to 2020. Serum samples were collected from 12 age groups, and the serum IgG antibody of measles, rubella and mumps were detected by ELISA. The difference of antibody positive rates and antibody levels were analyzed. Results: The median age M (Q₁, Q₃) of 10 828 objects were 8 years old (9 months old, 20 years old). Males accounted for 48.34% (5 234/10 828) and females accounted for 50.92% (5 514/10 828). Unknown gender information accounted for 0.74% (80/10 828), and 27.03% (2 927/10 828) of participants had unknown MMR immunization history. The total positive rates of measles, rubella and mumps IgG antibody were 76.78%, 64.46% and 64.29% and their GMCs were 541.45 mIU/ml, 31.76 IU/ml and 133.73 U/ml respectively. There were significant differences in serum IgG antibody GMC of measles, rubella and mumps in each year (F_measles=180.74, P<0.001; F_rubella=189.95, P<0.001; F_mumps=122.40, P<0.001). The positive rate of measles antibody was higher than that of rubella and mumps, and the difference was statistically significant (χ²=518.09, P<0.001). Conclusion: The level of measles IgG antibody in healthy people in Shanghai is higher, while the level of rubella and mumps IgG antibody is slightly lower.
Adult ; Antibodies, Viral ; Child ; China/epidemiology* ; Female ; Humans ; Immunoglobulin G ; Infant ; Male ; Measles/prevention & control* ; Measles-Mumps-Rubella Vaccine ; Mumps/prevention & control* ; Mumps virus ; Rubella/prevention & control* ; Young Adult

Biomarkers, Tumor ; Humans ; Sarcoma, Synovial/surgery* ; Stomach

OBJECTIVE: To analyze the characteristics of gene mutation and overexpression in newly diagnosed multiple myeloma (NDMM) patients. METHODS: Bone marrow cells from 208 NDMM patients were collected and analyzed. The gene mutation of 28 genes and overexpression of 6 genes was detected by DNA sequencing. Chromosome structure abnormalities were detected by fluorescence in situ hybridization (FISH). RESULTS: Gene mutations were detected in 61 (29.33%) NDMM patients. Some mutations occurred in 5 or more cases, such as NRAS, PRDM1, FAM46C, MYC, CCND1, LTB, DIS3, KRAS, and CRBN. Overexpression of six genes (CCND1, CCND3, BCL-2, CCND2, FGFR3, and MYC) were detected in 83 (39.9%) patients, and cell cycle regulation gene was the most common. Single nucleotide polymorphisms (SNP) changes were detected in 169 (81.25%) patients, the TP53 P72R gene SNP (70.17%) was the most common. Abnormality in chromosome structure was correlated to gene overexpression. Compared to the patients with normal chromosome structure, patients with 14q32 deletion showed higher proportion of CCND1 overexpression. Similarly, patients with 13q14 deletion showed higher proportion of FGFR3 overexpression, whereas patients with 1q21 amplification showed higher proportion of CCND2, BCL-2 and FGFR3 overexpression. CONCLUSION There are multiple gene mutations and overexpression in NDMM. However, there is no dominated single mutation or overexpression of genes. The most common gene mutations are those in the RAS/MAPK pathway and the genes of cyclin family CCND are overexpression.
Chromosome Aberrations ; Humans ; In Situ Hybridization, Fluorescence ; Multiple Myeloma/genetics* ; Mutation

BACKGROUND: The neoadjuvant chemotherapy is increasingly used in advanced gastric cancer, but the effects on safety and survival are still controversial. The objective of this meta-analysis was to compare the overall survival and short-term surgical outcomes between neoadjuvant chemotherapy followed by surgery (NACS) and surgery alone (SA) for locally advanced gastric cancer. METHODS: Databases (PubMed, Embase, Web of Science, Cochrane Library, and Google Scholar) were explored for relative studies from January 2000 to January 2021. The quality of randomized controlled trials and cohort studies was evaluated using the modified Jadad scoring system and the Newcastle-Ottawa scale, respectively. The Review Manager software (version 5.3) was used to perform this meta-analysis. The overall survival was evaluated as the primary outcome, while perioperative indicators and post-operative complications were evaluated as the secondary outcomes. RESULTS: Twenty studies, including 1420 NACS cases and 1942 SA cases, were enrolled. The results showed that there were no significant differences in overall survival (P = 0.240), harvested lymph nodes (P = 0.200), total complications (P = 0.080), and 30-day post-operative mortality (P = 0.490) between the NACS and SA groups. However, the NACS group was associated with a longer operation time (P < 0.0001), a higher R0 resection rate (P = 0.003), less reoperation (P = 0.030), and less anastomotic leakage (P = 0.007) compared with SA group. CONCLUSIONS Compared with SA, NACS was considered safe and feasible for improved R0 resection rate as well as decreased reoperation and anastomotic leakage. While unbenefited overall survival indicated a less important effect of NACS on long-term oncological outcomes.
Humans ; Neoadjuvant Therapy ; Stomach Neoplasms/surgery* ; Treatment Outcome

OBJECTIVE: To analyze the correlation between occupational stress and hypertension in steel production workers.METHODS: By the stratified cluster sampling method,1 580 steel production workers from an iron and steel group company were selected as study subjects. Occupational stress was measured by the Chinese version of Job Content Questionnaire.The identification of having occupational stress was the ratio of job requirement dimension score over job self-decision dimension score turned to be ≥1. 00. The steel production workers' blood pressure was measured by the updated mercury sphygmomanometer. The effect of occupational stress on blood pressure in steel production workers was analyzed. RESULTS: The dimension score of job self-decision in hypertension group was lower than that in non-hypertension group [20( 16,23) vs 20( 17,24) scores,P < 0. 05]. There was no statistical significant difference in occupational stress ratio,job requirement and social support dimension scores between two groups( P > 0. 05). The multiple logistic regression analysis showed that job self-decision and social support scores were negatively correlated with the incidence of hypertension [odds ratios( 95% confidence intervals) were 0. 68( 0. 51,0. 90) and 0. 54( 0. 45,0. 76),P < 0. 01]. CONCLUSION: Job selfdecision and social support are the influencing factors of the incidence of hypertension in steel production workers. The correlation among occupational stress,job requirement and hypertension are not found in steel production workers.

OBJECTIVETo study the changes in cardiopulmonary function induced by mid/long-term simulated microgravity with 6° head down bed rest (HDBR), and the effects of Taikong Yangxin Prescription (, TYP) as a countermeasure.

METHODSFourteen healthy male volunteers were randomly divided into a control group and a Chinese medicine (CM) group (7 in each group) by a random digital table based on their body weight. Both groups underwent 6° HDBR for 60 days. Subjects in the CM group received daily TYP pills and subjects in the control group received daily placebo pills. Cardiac systolic and pumping functions were measured by echocardiography before HDBR; on days 20, 42, and 57 of HDBR; and on day 3 of recovery after HDBR (R+3). Cardiopulmonary functional reserve and exercise capacity were evaluated before HDBR, on day 29, and on day R+3 by exercise testing.

RESULTSThe heart rate (HR) increased gradually during HDBR. The HR was significantly higher on day 57 than before HDBR in the control group (P<0.05), but did not increase significantly in the CM group. The stroke volume/stroke volume index, ejection fraction, and left ventricular fractional shortening tended to decrease over time in the control group, but not in the CM group. These parameters were significantly higher in the CM group than in the control group on day 42 (P<0.05 or <0.01). Exercise testing showed that maximum O2 consumption (VO2max), metabolic equivalents, relative O2 consumption (VO2), O2 pulse, and exercise duration were significantly lower on day 29 than before HDBR in the control group, but not in the CM group.

CONCLUSIONSSixty days of 6° HDBR induced a reduction in cardiac systolic and pumping functions, and reduced cardiopulmonary functional reserve and exercise capacity. Administration of TYP significantly improved cardiac systolic and pumping functions, and maintained cardiopulmonary functional reserve and exercise capacity.

Adult ; Bed Rest ; Drugs, Chinese Herbal ; Exercise Test ; Heart ; physiology ; Humans ; Lung ; physiology ; Male