Objective: To explore the relationship between visual acuity and physical fitness of university freshmen, so as to provide reference for myopia prevention and control for freshmen. Methods: From October to November 2022, 2 160 college freshman without majoring in public safety administration, selected from Guangxi Police College in 2022 by using the stratified cluster random sampling method, were reviewed for the results of visual acuity test and physical fitness scores. The physical fitness indices were evaluated by using the Z scores of physical fitness test scores, and the strength of association between the level of physical fitness index and myopia was analyzed by using Logistic regression model. Results: Among 2 160 college freshman without majoring in public safety administration, 917 (42.5%) students were diagnosed screening myopia, including 66 (3.1%) cases of high myopia, 383 (17.7%) cases of moderate myopia and 468 (21.7%) cases of mild myopia. The differences in the distribution of visual acuity tests among students with different physical fitness indices, body mass index, and gender were statistically significant ( Z/H=54.50, 49.53, 15.51, P <0.01). Low level and low middle level physical fitness indices were associated with screening myopia among freshmen[ OR (95% CI )=2.81(1.93-4.08),1.87(1.38-2.54)], and low level physical fitness indexes were associated with high myopia [ OR (95% CI )=7.22(2.33-22.32)] ( P <0.01). Conclusions Screening myopia among college freshman without majoring in public safety administration is related to physical fitness, and low level and low middle level physical fitness index are risk factors for myopia. Improving the level of physical fitness might be effective in preventing myopia.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

ObjectiveTo investigate the value of different noninvasive diagnostic models in the diagnosis of esophageal and gastric varices since there is a high risk of esophageal and gastric varices in patients with compensated hepatitis B cirrhosis and significant portal hypertension， and to provide a basis for the early diagnosis of esophageal and gastric varices. MethodsA total of 108 patients with significant portal hypertension due to compensated hepatitis B cirrhosis who attended Guangdong Provincial Hospital of Traditional Chinese Medicine from November 2017 to November 2023 were enrolled， and according to the presence or absence of esophageal and gastric varices under gastroscopy， they were divided into esophageal and gastric varices group （GOV group） and non-esophageal and gastric varices group （NGOV group）. Related data were collected， including age， sex， imaging findings， and laboratory markers. The chi-square test was used for comparison of categorical data between groups； the least significant difference t-test was used for comparison of normally distributed continuous data between groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups. The receiver operating characteristic （ROC） curve was plotted to evaluate the diagnostic value of five scoring models， i.e.， fibrosis-4 （FIB-4）， LOK index， LPRI， aspartate aminotransferase-to-platelet ratio index （APRI）， and aspartate aminotransferase/alanine aminotransferase ratio （AAR）. The binary logistic regression method was used to establish a combined model， and the area under the ROC curve （AUC） was compared between the combined model and each scoring model used alone. The Delong test was used to compare the AUC value between any two noninvasive diagnostic models. ResultsThere were 55 patients in the GOV group and 53 patients in the NGOV group. Compared with the NGOV group， the GOV group had a significantly higher age （52.64±1.44 years vs 47.96±1.68 years， t=0.453， P<0.05） and significantly lower levels of alanine aminotransferase ［42.00 （24.00 — 17.00） U/L vs 82.00 （46.00 — 271.00） U/L， Z=-3.065， P<0.05］， aspartate aminotransferase ［44.00 （32.00 — 96.00） U/L vs 62.00 （42.50 — 154.50） U/L，Z=-2.351， P<0.05］， and platelet count ［100.00 （69.00 — 120.00）×10⁹/L vs 119.00 （108.50 — 140.50）×10⁹/L， Z=-3.667， P<0.05］. The ROC curve analysis showed that FIB-4， LOK index， LPRI， and AAR used alone had an accuracy of 0.667， 0.681， 0.730， and 0.639， respectively， in the diagnosis of esophageal and gastric varices （all P<0.05）， and the positive diagnostic rates of GOV were 69.97%， 65.28%， 67.33%， and 58.86%， respectively， with no significant differences in AUC values （all P>0.05）， while APRI used alone had no diagnostic value （P>0.05）. A combined model （LAF） was established based on the binary logistic regression analysis and had an AUC of 0.805 and a positive diagnostic rate of GOV of 75.80%， with a significantly higher AUC than FIB-4， LOK index， LPRI， and AAR used alone （Z=-2.773，-2.479，-2.206， and-2.672， all P<0.05）. ConclusionFIB-4， LOK index， LPRI， and AAR have a similar diagnostic value for esophageal and gastric varices in patients with compensated hepatitis B cirrhosis and significant portal hypertension， and APRI alone has no diagnostic value. The combined model LAF had the best diagnostic efficacy， which provides a certain reference for clinical promotion and application.

ObjectiveTo observe the effect of gene mutation on the effectiveness of arsenic-containing Chinese herbal compound formulas in the treatment of myelodysplastic syndromes （MDS） of different traditional Chinese medicine （TCM） patterns， so as to provide the basis for the clinical application. MethodsClinical data of 442 MDS patients who were treated with arsenic-containing herbal compound formulas were retrospectively collected， including the baseline demographic and clinical characteristics of the patients. Based on the TCM four examinations， the patients were divided into the spleen-kidney deficiency group as well as the qi-yin deficiency group， and according to the results of the next-generation sequencing （NGS） test， they were divided into the group with and without gene mutation respectively. The influence of gene mutation on the clinical effectiveness of patients with different TCM patterns was analyzed， the baseline demographic and clinical characteristics of the patients with different outcomes of the two TCM patterns were compared， and multivariate Logistic regression analysis was conducted on the influencing factors of the effective rate of MDS patients with gene mutation. ResultsA total of 190 cases were included in the spleen-kidney deficiency group （119 cases with gene mutation） and 43 cases in the qi-yin deficiency group （23 cases with gene mutation）. No statistically significant differences were noted in effectiveness assessment， total effective rate， and total response rate between the spleen-kidney deficiency group and the qi-yin deficiency group （P＞0.05）. In the spleen-kidney deficiency group， the total effective rate of MDS with gene mutation was 65.55% （78/119）， which was lower than 80.28% （57/71） of MDS without gene mutation， with statistical significance （P = 0.033）， while no statistical differences in effectiveness assessment and total response rate were noted （P＞0.05）. In the qi-yin deficiency group， no statistical differences were observed in effectiveness assessment， total effective rate， and total response rate of the patients in with or without gene mutation （P＞0.05）. In the spleen-kidney deficiency group with gene mutation， the rate of complex karyotype （P = 0.031） and the mutation rate of CBL gene （P = 0.032） in the ineffective population were higher than those in the effective population， while the mutation rate of DDX41 gene in the effective population was higher than that in the ineffective population （P = 0.033）. No statistically significant differences were found in other gene mutations， age， gender distribution， number of gene mutations， bone marrow hyperplasia degree， blast cell range， reticular fiber tissue proliferation or not， and prognosis of chromosomal abnormalities between the effective and ineffective populations （P＞0.05）. In the qi-yin deficiency group with gene mutation， no statistically significant differences were found in various items between populations with different outcomes （P＞0.05）. Multivariate Logistic regression analysis showed that complex karyotype， CBL mutation， and DDX41 mutation were independently associated with the effective rate of MDS with spleen-kidney deficiency and gene mutation （P＜0.05）. DDX41 mutation was an independent protective factor in the spleen-kidney deficiency group （OR＞1）， while complex karyotype and CBL mutation were independent risk factors （OR＜1）. ConclusionThe arsenic-containing TCM compound formulas exhibited better effectiveness in MDS with spleen-kidney deficiency pattern without mutation； and in MDS with spleen-kidney deficiency pattern without complex karyotypes， CBL mutation， and with DDX41 mutations. Furthermore， DDX41 mutation was an independent protective factor in the spleen-kidney deficiency group， while complex karyotype and CBL mutation were independent risk factors. In MDS with qi-yin deficiency pattern， gene mutation-related factors showed no significant impact on the effectiveness of arsenic-containing TCM compound formulas.

Background::The serum vitamin D level varies widely by population, and studies have linked vitamin D levels with the risk of type 2 diabetes mellitus (T2DM). However, the relationship is inconsistent and the impact of vitamin D on T2DM among East Chinese adults is unclear. The study aimed to investigate the association between serum 25-hydroxyvitamin D (25[OH]D) levels and the risk of T2DM and evaluated whether the association is modified by genetic predisposition.Methods::In the Survey on Prevalence in East China for Metabolic Diseases and Risk Factors (SPECT-China) cohort, 1862 participants free of T2DM at baseline were included. A weighted genetic risk score was calculated with 28 variants associated with T2DM. Hierarchical logistic models were used to examine the association of serum 25(OH)D and genetic risk with T2DM.Results::After a 5-year follow-up, 132 cases of T2DM were documented. We observed no significant association between quartiles of serum 25(OH)D and T2DM risk after multivariable adjustment (&chi; 2 = 0.571, Pfor trend = 0.426). Compared to those in the lowest quartile of 25(OH)D, the odds ratios (ORs) (95% confidence interval [CI]) for participants with increased quartiles were 1.29 (0.74-2.25), 1.35 (0.77-2.36), and 1.27 (0.72-2.24), respectively. We observed a positive association of glycated hemoglobin (HbA1c) with 25(OH)D at baseline (β = 1.752, P = 0.001) and after follow-up (β = 1.385, P = 0.003), and a negative association of ln conversion homeostasis model assessment (HOMA)-β with 25(OH)D at baseline (β = -0.982, P = 0.021). There was no significant interaction between 25(OH)D and diabetes genetic predisposition on the risk of T2DM (&chi; 2 = 2.710, Pfor interaction = 0.100). The lowest OR (95% CI) of T2DM was among participants with low genetic risk and the highest quartile of 25(OH)D (0.17 [0.05–0.62]). Conclusion::Serum 25(OH)D may be irrelevant to the risk of incident T2DM among East Chinese adults regardless of genetic predisposition.

Objective:We aimed to develop a novel visualized model based on nomogram to predict postoperative overall survival.Methods:This was a multicenter, retrospective, observational cohort study, including participants with histologically confirmed gastric and colorectal cancer who underwent radical surgery from 11 medical centers in China from August 1, 2015 to June 30, 2018. Baseline characteristics, histopathological data and nutritional status, as assessed using Nutrition Risk Screening 2002 (NRS 2002) score and the scored Patient-Generated Subjective Global Assessment, were collected. The least absolute shrinkage and selection operator regression and Cox regression were used to identify variables to be included in the predictive model. Internal and external validations were performed.Results:There were 681 and 127 patients in the training and validation cohorts, respectively. A total of 188 deaths were observed over a median follow-up period of 59 (range: 58 to 60) months. Two independent predictors of NRS 2002 and Tumor-Node-Metastasis (TNM) stage were identified and incorporated into the prediction nomogram model together with the factor of age. The model's concordance index for 1-, 3- and 5-year overall survival was 0.696, 0.724, and 0.738 in the training cohort and 0.801, 0.812, and 0.793 in the validation cohort, respectively.Conclusions:In this study, a new nomogram prediction model based on NRS 2002 score was developed and validated for predicting the overall postoperative survival of patients with gastric colorectal cancer. This model has good differentiation, calibration and clinical practicability in predicting the long-term survival rate of patients with gastrointestinal cancer after radical surgery.

Objective:To construct a non-invasive pre-hospital screening model and early based on artificial intelligence algorithms to provide the severity of stroke in patients, provide screening, guidance and early warning for stroke patients and their families, and provide data support for clinical decision-making.Methods:A retrospective study was conducted. The clinical information of stroke patients ( n = 53?793) were extracted from the Yidu cloud big data server system of the Second Affiliated Hospital of Dalian Medical University from January 1, 2001 to July 31, 2023. Combined with the results of single factor screening and the opinions of experts with senior professional titles in neurology, the input variable was determined, and the output variable was the National Institutes of Health Stroke Scale (NIHSS) representing the severity of the disease at admission. Python 3.7 was used to build DeepFM algorithm model, and five data mining models including Logistic regression, CART decision tree, C5.0 decision tree, Bayesian network and deep neural network (DNN) were built at the same time. The original data were randomly divided into 80% training set and 20% test set, which were used to train and test the models, adjust the parameters of each model, respectively calculate the accuracy, sensitivity and F-index of the six models, carry out the comprehensive comparison and evaluation of the model. The receiver operator characteristic curve (ROC curve) and calibration curve were drawn, compared the prediction performance of DeepFM model and the other five algorithms. In addition, the data of stroke patients ( n = 1?028) were extracted from Dalian Central Hospital for external verification of the model. Results:A total of 14?015 stroke patients with complete information were selected, including 11?212 in the training set and 2?803 in the testing set. After univariate screening, 14 indicators were included to construct the model, including gender, age, recurrence, physical impairment, facial problems, speech disorders, head reactions, disturbance of consciousness, visual disorders, abnormal cough and swallowing, high risk factor, family history, smoking history and drinking history. DeepFM model adopted the two-order crossover feature. The number of hidden layers in DNN layer was 3. Dropout was used to discard the neurons in the neural network. Rule was used as the activation function. Each layer used Dense full connection. The objective function was random gradient descent. The number of iterations was 15. There were 133?922 training parameters in total. Comparing the predictive value of the six models showed that the accuracy of DeepFM model was 0.951, the sensitivity was 0.992, the specificity was 0.814, the F-index was 0.950, and the area under the curve (AUC) was 0.916. The accuracy of the other five data mining models were between 0.771-0.780, the sensitivity were between 0.978-0.987, the F-index were between 0.690-0.707, and the AUC were between 0.568-0.639. The calibration curve of the DeepFM model was more aligned with the ideal curve than the other five data mining models. Suggesting that the prediction performance of DeepFM model was the best. External validation was conducted on the DeepFM model, and its accuracy was 0.891, indicating good generalization performance of the model.Conclusion:The pre-hospital non-invasive screening prediction model based on DeepFM can accurately predict the severity grading of stroke patients, and has potential application value in rapid screening and early clinical decision-making of stroke.

Objective To investigate corneal biomechanical differences in different geometric design parameters of orthokeratology lenses(OK lenses)and to further reveal the corneal shaping mechanism of OK lenses.Methods A coupled finite element model of the aspheric OK lens corneosclera was established for various geometric design parameters of the OK lens,corresponding to different degrees of myopia correction.The distribution trends of the profile and curvature of the corneal anterior surface,as well as the von Mises stress(VMS)and eye axis displacement on both the corneal anterior surface and superior corneal stroma surface were analyzed numerically.Results The stress concentration of the corneal anterior surface was observed in the mid-peripheral and peripheral zones,whereas that of the superior corneal stroma surface appeared in the mid-peripheral zones.The sagittal height of the base curve of the OK lens decreased with increasing degree of myopia correction.At myopia correction degrees of-2.0,-3.0,-4.0,-5.0,and-6.0 D,the maximum corneal VMS increased by 0.81%,1.86%,2.84%,3.81%,and 7.04%,respectively,compared with that at-1.0 D;the curvature of the corneal central zone was reduced by an average of 2.59,3.78,4.51,4.99,5.33,and 6.41 D compared with that without OK lenses.Conclusions The sagittal height of the base curve of the OK lens decreased with increasing degree of myopia correction,resulting in a flatter central curvature of the cornea.The base curve of the OK lens plays a crucial role in both correction and control of myopia.

Objective Sequencing depth is a key parameter in next generation sequencing,which is closely related to the accuracy of sequencing results.Forensic biological evidence examination requires extremely high accuracy.It is crucial to scientifically and reasonably set the sequencing depth analysis threshold for forensic next generation sequencing testing.Methods This study used targeted sequencing data of microhaplotypes from 50 samples with known genotypes.By calculating the accuracy,precision,recall,and F1 score of each locus under various threshold conditions,two types of analysis threshold setting methods,which were based on fixed read count and fixed sequencing depth ratio,were studied extensively.Results The results showed that false positives were observed when the analysis threshold was set at 50×or 100×.When the analysis threshold was set at 200×,false negatives were observed.When the analysis threshold was set at 1.5%,3.0%,or 4.5%,false positives were observed.This study further proposed a third type of analysis threshold setting method,which was based on sequencing depth ratio scatter plots.With this method,no false positive or false negative was observed in the results.This article then explored four factors that lead to significant differences in the sequencing depth of forensic next generation sequencing experiments,compared with the analysis threshold setting method for capillary electrophoresis technology,and discussed the correlation between analysis thresholds and the ability to distinguish mixed DNA.Conclusion Employing the sequencing depth ratio scatter plot method to set analysis threshold has significant application value in next generation sequencing-based forensic genetic marker genotyping.

Objective To explore the risk factors for myocardial injury in esophagogastric variceal bleeding(EGVB)patients with liver cirrhosis during hospitalization.Methods A case-control trial was conducted on 235 EGVB patients admitted to our hospital between May 2021 and July 2022.Their basic information,laboratory results and relevant data during hospitalization were collected.According to their myocardial enzyme profiles during hospitalization,they were divided into myocardial injury group(n=46)and non-myocardial injury group(n=189).Univariate regression analysis and clinical correlation analysis were used to preliminarily screen the risk factors for myocardial injury secondary to EGVB caused by liver cirrhosis.Then,multivariate logistic regression analysis was used to further screen the risk factors.A nomogram was constructed based on the selected risk factors and the occurrence of myocardial injury.Receiver operating characteristic(ROC)curve was plotted to analyze the independent predictive value of these factors alone or combined together.Calibration curve analysis and internal verification were utilized to evaluate the predictive performance of the nomogram model.Subgroup verification was performed in the myocardial infarction group.Results Univariate analysis revealed that statistical differences were observed in age,sex,hypertension,renal disease,underlying diseases,vomiting,leukocytosis,increased alanine aminotransferase(ALT)or aspartate aminotransferase(AST),albumin,red blood cell hematocrit(HCT),international normalized ratio(INR),endoscopy within 6 h after admission,and Child-Pugh(CP)class between the myocardial injury group and the non-myocardial injury group(P＜0.01).Multivariate logistic regression analysis showed that age(P=0.014,OR=1.153,95％CI:1.030～1.291),underlying diseases(P=0.005,OR=1.122,95％CI:1.032～2.437),and albumin(P=0.012,OR=0.449,95％CI:0.241～0.837)were independent risk factors for inhospital myocardial injury in EGVB patients with liver cirrhosis.The AUC value of the above indicators combined together for predicting myocardial injury was 0.902.Hosmer-Lemeshow test and calibration curve analysis indicated that the nomogram had good prediction consistency(Chi-square=12.88,P=0.615).Internal verification correctly distinguished 86.4％of verification objects.Subgroup analysis of myocardial injury patients showed that albumin was also an independent risk factor for in-hospital myocardial injury in this population(AUC=0.80).Conclusion Age,underlying diseases,and albumin level are independent risk factors for in-hospital myocardial injury in EGVB patients with liver cirrhosis.Albumin level can be used as an independent risk factor for predicting myocardial infarction.Combination of the above 3 indicators has a high diagnostic value in early identification and prevention of myocardial injury in this patient population.