Objective: To discuss the university students early-stage interpersonal perception and selection in internet Method; Totally 362 university students who used internet instant chat system were surveyed with the self-designed questionnaires. They were required to assess the influence degree of internet information on their feeling and choosing in a five degree scale. The differences in gender, subject and lasting time were also compared. Re-sults: (1) Age (4. 39 ± 1.94), nick name (3.71 ± 1.92) and self-explained (3.67 ± 1.97) were the most important information for choosing a friend in internet, which were higher than three most unimportant information including blood type (1.23 ±0. 80), level (1.40 ±0.95), and operation (1.41 ±0.89) (P<0.01) . (2) All students trended to evaluate others or selves information veritable. In all items, the veracity rate of self evaluate was high than 78.2% , and the veracity degrees of evaluating others'information were between 2.05 ～ 2.91. (3) Bad manners (1. 33 ±0.72), rough speech (1.41 ±0.71), and bored dialogue (1.50 ±0. 80) were the most related factors to choose friend, which were higher than three most unimportant information including no meeting chance (4.47±0.94), slow typing (3.13 ±1.12), poor motivation (2.32 ± 1.05) (P<0.01) . Conclusion: This study suggests that peoples early-stage perception and selection in internet are based on the selection, confirmation and conjecture of users, which will have certain effects on the development of network interpersonal relationship.

Based on the existing literatures,four basic models for drug addiction and relapse behavior researches were generalized,namely,the motive and self-concept model,the social-environment model,the cognitive processing model,and the neuropsychological model.Analyzing the research evidence in the area,the authors considered that relapse behavior was caused by a great many diverse factors,consequently,any of these models failed to make strong predication for relapse behavior.After reviewing the addiction models,the possibilities of future integrative research in the area were discussed.

Objective To analyze the serotypes distribution characteristics of salmonella infection in infants below 2 years old in Dongguan.Methods Feces samples collected in children below 2 years old with diarrhea,caused by salmonella infection,were cultured for salmonella isolates,which were then identified for serotypes.The distribution characteristics of different serotypes of salmonella were analyzed.Results A total of 369 strains of salmonella were isolated,including 36 serotypes.The most common three serotypes were Salmonella typhimurium(S.ty),Salmonella stanley(S.st) and Salmonella enteritidis(S.en),which accounted for 68.7%.In all infants with diarrhea,there were 253 boys and 143 girls,and the male:female ratio was 1.77∶1.The average age of infants was (9.3±2.3) months.In male and female infants,the most serotype was S.ty,accounting for 62.3% and 53.3%,but the least serotypes in male and female infants were S.st(16.8%) and S.en(19.0%) respectively.S.ty was the most common serotype in different age groups.The least serotypes in low-age group(0-5.99 months) and middle-age group(6-11.99 months)were S.st(18.4%) and S.en(14.4%) respectively.In high-age group(12-24 months),the proportion of S.st and S.en were both 21.8%.The diversity of salmonella serotypes in male infants was higher than female infants,and with the increasing of age,the diversity was more obvious.Conclusion There could be unique serotype distribution characteristics of salmonella infection in infants with diarrhea,and the diversity of salmonella serotypes should be paid more attention.

Objective: To evaluate the application of laplacian-regularized mean apparent propagator (MAPL)-MRI to brain glioma-induced corticospinal tract (CST) injury. Materials and Methods: This study included 20 patients with glioma adjacent to the CST pathway who had undergone structural and diffusion MRI. The entire CSTs of the affected and healthy sides were reconstructed, and the peritumoral CSTs were manually segmented. The morphological characteristics of the CST (track number, average length, volume, displacement of the affected CST) were examined and the diffusion parameter values, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), mean squared displacement (MSD), q-space inverse variance (QIV), returnto-origin probability (RTOP), return-to-axis probabilities (RTAP), and return-to-plane probabilities (RTPP) along the entire and peritumoral CSTs, were calculated. The entire and peritumoral CST characteristics of the affected and healthy sides as well as those relative CST characteristics of the patients with motor weakness and normal motor function were compared. Results: The track number, volume, MD, RD, MSD, QIV, RTAP, RTOP, and RTPP of the entire and peritumoral CSTs changed significantly for the affected side, whereas the AD and FA changed significantly only in the peritumoral CST (p < 0.05). In patients with motor weakness, the relative MSD of the entire CST, QIV of the entire and peritumoral CSTs, and the AD, MD, RD of the peritumoral CST were significantly higher, whereas the RTPP of the entire and peritumoral CSTs and the RTOP of the peritumoral CST were significantly lower than those in patients with normal motor function (p < 0.05 for all). In contrast, no significant changes were found in the CST morphological characteristics, FA, or RTAP (p > 0.05 for all). Conclusion MAPL-MRI is an effective approach for evaluating microstructural changes after CST injury. Its sensitivity may improve when using the peritumoral CST features.

Objective: To evaluate the application of laplacian-regularized mean apparent propagator (MAPL)-MRI to brain glioma-induced corticospinal tract (CST) injury. Materials and Methods: This study included 20 patients with glioma adjacent to the CST pathway who had undergone structural and diffusion MRI. The entire CSTs of the affected and healthy sides were reconstructed, and the peritumoral CSTs were manually segmented. The morphological characteristics of the CST (track number, average length, volume, displacement of the affected CST) were examined and the diffusion parameter values, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), mean squared displacement (MSD), q-space inverse variance (QIV), returnto-origin probability (RTOP), return-to-axis probabilities (RTAP), and return-to-plane probabilities (RTPP) along the entire and peritumoral CSTs, were calculated. The entire and peritumoral CST characteristics of the affected and healthy sides as well as those relative CST characteristics of the patients with motor weakness and normal motor function were compared. Results: The track number, volume, MD, RD, MSD, QIV, RTAP, RTOP, and RTPP of the entire and peritumoral CSTs changed significantly for the affected side, whereas the AD and FA changed significantly only in the peritumoral CST (p < 0.05). In patients with motor weakness, the relative MSD of the entire CST, QIV of the entire and peritumoral CSTs, and the AD, MD, RD of the peritumoral CST were significantly higher, whereas the RTPP of the entire and peritumoral CSTs and the RTOP of the peritumoral CST were significantly lower than those in patients with normal motor function (p < 0.05 for all). In contrast, no significant changes were found in the CST morphological characteristics, FA, or RTAP (p > 0.05 for all). Conclusion MAPL-MRI is an effective approach for evaluating microstructural changes after CST injury. Its sensitivity may improve when using the peritumoral CST features.

Objective:To study the efficacy of endoscopic papillary balloon dilatation (EPBD) in the treatment of non-dilated small choledocholithiasis.Methods:Clinical data of 142 patients with non-dilated small choledocholithiasis admitted to Zhanjiang Central People's Hospital from April 2021 to March 2023 were retrospectively analyzed, including 63 males and 79 females, aged (55.1±15.4) years old. Patients were divided into the EPBD group ( n=63) and endoscopic sphincterotomy (EST) group ( n=79). Blood amylase, liver enzymology, liver metabolism, and blood routine were monitored before and 48 hours after treatment. The occurrences of intraoperative bleeding, perforation, post-ERCP pancreatitis (PEP), and cholangitis were compared between the groups. Patients were followed up and screened for stone recurrence by outpatient review 3 to 12 months from discharge. Results:Compared to preoperative data, the white blood cell count, alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, total bili-rubin, and direct bilirubin decreased 48 hours after treatment (all P<0.05). The operation time in EPBD group was slightly longer than that in EST group [(43.1±5.9) min vs. (38.5±4.5) min, P=0.064] without statistical significance. There were no case of perforation in both groups. The incidences of intraopera-tive bleeding [3.17%(2/63) vs. 6.33%(5/79)], PEP [17.46%(11/63) vs. 10.53%(8/79)], and postoperative cholangitis [4.76%(3/63) vs. 1.27%(1/79)] were comparable between the groups (all P>0.05). Conclusion:EPBD could be feasible for non-dilated small choledocholithiasis, which does not increase the operation time and incidence of adverse events compared to EST.

OBJECTIVES: Firefighters are prone to suffer from psychological trauma and post-traumatic stress disorder (PTSD) in the workplace, and have a poor prognosis after PTSD. Reliable models for predicting PTSD allow for effective identification and intervention for patients with early PTSD. By collecting the psychological traits, psychological states and work situations of firefighters, this study aims to develop a machine learning algorithm with the aim of effectively and accurately identifying the onset of PTSD in firefighters, as well as detecting some important predictors of PTSD onset. METHODS: This study conducted a cross-sectional survey through convenient sampling of firefighters from 20 fire brigades in Changsha, which were evenly distributed across 6 districts and Changsha County, with a total of 628 firefighters. We used the synthetic minority oversampling technique (SMOTE) to process data sets and used grid search to finish the parameter tuning. The predictive capability of several commonly used machine learning models was compared by 5-fold cross-validation and using the area under the receiver operating characteristic curve (ROC-AUC), accuracy, precision, recall, and F1 score. RESULTS: The random forest model achieved good performance in predicting PTSD with an average AUC score at 0.790. The mean accuracy of the model was 90.1%, with an F1 score of 0.945. The three most important predictors were perseverance, forced thinking, and reflective deep thinking, with weights of 0.165, 0.158, and 0.152, respectively. The next most important predictors were employment time, psychological power, and optimism. CONCLUSIONS PTSD onset prediction model for Changsha firefighters constructed by random forest has strong predictive ability, and both psychological characteristics and work situation can be used as predictors of PTSD onset risk for firefighters. In the next step of the study, validation using other large datasets is needed to ensure that the predictive models can be used in clinical setting.
Humans ; Stress Disorders, Post-Traumatic/diagnosis* ; Firefighters/psychology* ; Cross-Sectional Studies ; Algorithms ; Machine Learning