Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

Objective To determine the scores of patients with a confirmed diagnosis of drug-induced liver injury(DILI)using Roussel Uclaf Causality Assessment Method(RUCAM),Maria&Victorino assessment scale,and Revised Electronic Causality Assessment Method(RECAM),to compare the accuracy of the three scales in diagnosis,and to investigate their clinical significance in the diagnosis of DILI.Methods A total of 98 patients with a confirmed diagnosis of DILI who were hospitalized in Peking University First Hospital from January 2011 to December 2022 were enrolled,with liver biopsy results supporting DILI and a clear history of medication.Clinical data were collected from all subjects,and the above causality assessment scales were used for scoring.The chi-square test was used to analyze the diagnostic accuracy of the causality assessment scales,and the weighted kappa coefficient was used to analyze the consistency between the three scales.Results For all patients with DILI enrolled,RECAM had the highest accuracy,with a significant difference compared with RUCAM(χ2=5.667,P=0.017).RUCAM and RECAM had moderate consistency in diagnosis(κw=0.469),while RECAM and Maria&Victorino scale had poor consistency(κw=0.156).For the patients with acute DILI,RECAM,RUCAM,and Maria&Victorino scales had a diagnostic inconsistency rate of 3.7%,11.1%,and 42.6%,respectively;for the patients with hepatocellular type DILI,the three scales of a diagnostic inconsistency rate of 8.9%,21.4%,and 62.5%,respectively;for the patients with cholestasis type or mixed type DILI,the three scales of a diagnostic inconsistency rate of 10.0%,22.5%,and 47.5%,respectively.Conclusion The use of RECAM and RUCAM scales in acute DILI can improve diagnostic rate,and for hepatocellular type DILI and DILI with the clinical manifestation of cholestasis(cholestasis type DILI and mixed type DILI),the use of RECAM and RUCAM scales can also improve diagnostic rate.The selection of causality assessment scales with a relatively high accuracy based on the course and clinical classification of the disease may help to further improve clinical diagnostic rate.

Objective: To understand the prevalence of HIV testing and related factors among young students who had sex in Guangdong Province, in order to provide evidence for relevant education programs and HIV testing promotion in young students. Methods: From September to December 2022, a convenient sampling method was used to select 48 749 young students from 16 universities and mechanic colleges in 6 cities including Guangzhou, Shantou, Maoming, Huizhou, Dongguan, and Zhongshan in Guangdong Province for online questionnaire survey. A total of 2 971 students who ever had sexual experiences were screened out, and the HIV testing situation and related factors were investigated by using the questionnaire designed by AIDS Prevention and Education Project for College Students of China STD and AIDS Prevention Association.The influencing factors of HIV testing were analyzed using Chi square test and multiple Logistic regression model. Results: Among students who had sexual experiences, 11.92% (354/2 971) were tested for HIV. The results of multivariate Logistic regression analysis showed that among young sexual students, using psychoactive substances during sexual activity in the last 1 year ( OR =7.70), having first sex with the same sex ( OR =3.87), having commercial sex ( OR =2.37), having heard of PEP ( OR =2.20), having a high level of self assessed understanding of HIV testing ( OR =1.73), inconsistent use of condoms ( OR =1.56), being aware of HIV infection ( OR =1.53), being aware of HIV knowledge ( OR =1.51) were more likely to test for HIV, and females ( OR =0.39) were less likely to test for HIV ( P < 0.05). Conclusions The proportion of HIV testing is low among sexually active young students in Guangdong Province. Targeted interventions should be tailored to promote HIV testing coverage.

Objective:To investigate the value of CT radiomic model based on analysis of primary gastric cancer and the adipose tissue outside the gastric wall beside cancer in differentiating stage T1-2 from stage T3-4 gastric cancer.Methods:This study was a case-control study. Totally 465 patients with gastric cancer treated in Affiliated People′s Hospital of Jiangsu University from December 2011 to December 2019 were retrospectively collected. According to postoperative pathology, they were divided into 2 groups, one with 150 cases of T1-2 tumors and another with 315 cases of T3-4 tumors. The cases were divided into a training set (326 cases) and a test set (139 cases) by stratified sampling method at 7∶3. There were 104 cases of T1-2 stage and 222 cases of T3-4 stage in the training set, 46 cases of T1-2 stage and 93 cases of T3-4 stage in the test set. The axial CT images in the venous phase during one week before surgery were selected to delineate the region of interest (ROI) at the primary lesion and the extramural gastric adipose tissue adjacent to the cancer areas. The radiomic features of the ROIs were extracted by Pyradiomics software. The least absolute shrinkage and selection operator was used to screen features related to T stage to establish the radiomic models of primary gastric cancer and the adipose tissue outside the gastric wall beside cancer. Independent sample t test or χ2 test were used to compare the differences in clinical features between T1-2 and T3-4 patients in the training set, and the features with statistical significance were combined to establish a clinical model. Two radiomic signatures and clinical features were combined to construct a clinical-radiomics model and generate a nomogram. The area under the receiver operating characteristic curve (AUC) was used to evaluate the efficacy of each model in differentiating stage T1-2 from stage T3-4 gastric cancer. The calibration curve was used to evaluate the consistency between the T stage predicted by the nomogram and the actual T stage of gastric cancer. And the decision curve analysis was used to evaluate the clinical net benefit of treatment guided by the nomogram and by the clinical model. Results:There were significant differences in CT-T stage and CT-N stage between T1-2 and T3-4 patients in the training set ( χ2=10.59, 15.92, P=0.014, 0.001) and the clinical model was established. After screening and dimensionality reduction, the 5 features from primary gastric cancer and the 6 features from the adipose tissue outside the gastric wall beside cancer established the radiomic models respectively. In the training set and the test set, the AUC values of the primary gastric cancer radiomic model were 0.864 (95% CI 0.820-0.908) and 0.836 (95% CI 0.762-0.910), and the adipose tissue outside the gastric wall beside cancer radiomic model were 0.782 (95% CI 0.731-0.833) and 0.784 (95% CI 0.702-0.866). The AUC values of the clinical model were 0.761 (95% CI 0.705-0.817) and 0.758 (95% CI 0.671-0.845), and the nomogram were 0.876 (95% CI 0.835-0.917) and 0.851 (95% CI 0.781-0.921). The calibration curve reflected that there was a high consistency between the T stage predicted by the nomogram and the actual T stage in the training set ( χ2=1.70, P=0.989). And the decision curve showed that at the risk threshold 0.01-0.74, a higher clinical net benefit could be obtained by using a nomogram to guide treatment. Conclusions:The CT radiomics features of primary gastric cancer lesions and the adipose tissue outside the gastric wall beside cancer can effectively distinguish T1-2 from T3-4 gastric cancer, and the combination of CT radiomic features and clinical features can further improve the prediction accuracy.

Objective:To investigate the effectiveness and feasibility of a 3D U-Net in conjunction with a three-phase CT image segmentation model in the automatic segmentation of GTVnx and GTVnd in nasopharyngeal carcinoma.Methods:A total of 645 sets of computed tomography (CT) images were retrospectively collected from 215 nasopharyngeal carcinoma cases, including three phases: plain scan (CT), contrast-enhanced CT (CTC), and delayed CT (CTD). The dataset was grouped into a training set consisting of 172 cases and a test set comprising 43 cases using the random number table method. Meanwhile, six experimental groups, A1, A2, A3, A4, B1, and B2, were established. Among them, the former four groups used only CT, only CTC, only CTD, and all three phases, respectively. The B1 and B2 groups used phase fine-tuning CTC models. The Dice similarity coefficient (DSC) and 95% Hausdorff distance (HD95) served as quantitative evaluation indicators.Results:Compared to only monophasic CT (group A1/A2/A3), triphasic CT (group A4) yielded better result in the automatic segmentation of GTVnd (DSC: 0.67 vs. 0.61, 0.64, 0.64; t = 7.48, 3.27, 4.84, P < 0.01; HD95: 36.45 vs. 79.23, 59.55, 65.17; t = 5.24, 2.99, 3.89, P < 0.01), with statistically significant differences ( P < 0.01). However, triphasic CT (group A4) showed no significant enhancement in the automatic segmentation of GTVnx compared to monophasic CT (group A1/A2/A3) (DSC: 0.73 vs. 0.74, 0.74, 0.73; HD95: 14.17 mm vs. 8.06, 8.11, 8.10 mm), with no statistically significant difference ( P > 0.05). For the automatic segmentation of GTVnd, group B1/B2 showed higher automatic segmentation accuracy compared to group A1 (DSC: 0.63, 0.63 vs. 0.61, t = 4.10, 3.03, P<0.01; HD95: 58.11, 50.31 mm vs. 79.23 mm, t = 2.75, 3.10, P < 0.01). Conclusions:Triphasic CT scanning can improve the automatic segmentation of the GTVnd in nasopharyngeal carcinoma. Additionally, phase fine-tuning models can enhance the automatic segmentation accuracy of the GTVnd on plain CT images.

Objective:To explore high-risk sexual behaviors of HIV/AIDS and related factors in young students in Guangzhou.Methods:A cross-sectional survey was conducted in 5 different types of Guangzhou colleges by convenience sampling with minimum number of classes per grade and 600 samples per school from September to November 2021. The R 4.2.2 software was used to consolidate databases. Simultaneously, a logistic regression model and a decision tree algorithm model, stratifying by whether sexual behaviors had occurred before, were constructed. In each layer, the prediction performance of the two models was evaluated through area under receiver operating characteristic and the confusion matrix, and then the model with high prediction performance was retained.Results:A total of 7 346 students were surveyed. The proportion of the respondents reporting sexual experience were 9.08% (667/7 346), in whom 26.24% (175/667) had risky sexual activity in the past year. The decision tree algorithm model performs well in predicting whether high-risk sexual behaviors have occurred in the past year. When the complexity parameter value is 0.018, and nsplit reaches 4, which means there are 5 leaf nodes in the model, the cross error of the tree will be the smallest. The first best grouping variable in the decision tree was whether to use condoms throughout the first sexual behavior. If condoms were used at their sexual debut, but homosexual practices have occurred in the past year, the probability of risky sexual behavior will increase. If homosexual practices have not occurred in the past year, but the age of sexual debut was below 18 years old while the period of HIV education was after high school, the probability of risk sexual behavior will also increase.Conclusions:AIDS-related risky behaviors of young students still deserved attention. The experience of sexual debut and whether AIDS-related health education has been received before the sexual debut were significant predictors for the occurrence of high-risk sexual behavior. The decision tree algorithm model has particular applicability for predicting and screening potential risk populations.

A case of idiopathic hypertrophic spinal pachymeningitis is reported. The patient was a middle-aged female, with the course of disease more than 1 year. Clinical manifestations included recurrent fever,headache and backache, and the magnetic resonance imaging showed diffuse enhancement and thickening of the spinal dura mater. Dural biopsy pathology finally confirmed hypertrophic spinal pachymeningitis. After treatment with surgery and immunotherapy, the patient′s clinical symptoms improved.

Objective To construct and validate a risk prediction model for delayed healing of venous leg ulcer(VLU),so as to provide a reference basis for early identification of people at high risk of delayed healing.Methods Using a convenience sampling method,331 VLU patients attending vascular surgery departments in 2 tertiary A hospitals in Sichuan Province from January 2018 to December 2022 were selected as a modeling group and an internal validation group,and 112 patients admitted to another tertiary A hospital were selected as an external validation group.Risk factors for delayed healing in VLU patients were screened using univariate analysis,LASSO regression,and multivariate logistic regression analysis,and a risk prediction model was constructed using R software,and the predictive effects of the models were examined using the area under the receiver operating characteristic curve,the Hosmer-Lemeshow test,decision curve,and the bootstrap resampling for internal validation and spatial external validation were performed,respectively.Results The predictors that ultimately entered the prediction model were diabetes(OR=4.752),deep vein thrombosis(OR=4.104),lipodermatosclerosis(OR=5.405),ulcer recurrence(OR=3.239),and ankle mobility(OR=5.520).The model had good discrimination(AUC:0.819 for internal validation and 0.858 for external validation),calibration(Hosmer-Lemeshow test:χ2=13.517,P=0.095 for internal validation and χ2=3.375,P=0.909 for external validation)and clinical validity.Conclusion The model constructed in this study has good differentiation and calibration,and it can effectively predict people at high risk of delayed healing of VLU,which facilitates targeted clinical interventions to improve ulcer outcomes and reduce the risk of delayed ulcer healing.

We previously identified a unique nucleus, the cerebrospinal fluid (CSF)-contacting nucleus. This study aims to understand its gene architecture and preliminarily suggest its functions. The results showed that there were about 19,666 genes in this nucleus, of which 913 were distinct from the dorsal raphe nucleus (non-CSF contacting). The top 40 highly-expressed genes are mainly related to energy metabolism, protein synthesis, transport, secretion, and hydrolysis. The main neurotransmitter is 5-HT. The receptors of 5-HT and GABA are abundant. The channels for Cl^-, Na⁺, K⁺, and Ca²⁺ are routinely expressed. The signaling molecules associated with the CaMK, JAK, and MAPK pathways were identified accurately. In particular, the channels of transient receptor potential associated with nociceptors and the solute carrier superfamily members associated with cell membrane transport were significantly expressed. The relationship between the main genes of the nucleus and life activities is preliminarily verified.
Rats ; Animals ; Rats, Sprague-Dawley ; Serotonin/metabolism* ; Signal Transduction ; Cerebrospinal Fluid/metabolism*

OBJECTIVE: To investigate the effect of Akt2 inhibitor on macrophage polarization in the periapical tissue in a rat model of periapical inflammation. METHODS: Rat models of periapical inflammation were established in 28 normal SD rats by opening the pulp cavity of the mandibular first molars, followed by injection of normal saline and Akt2 inhibitor into the left and right medullary cavities, respectively. Four rats without any treatment served as the healthy control group. At 7, 14, 21 and 28 days after modeling, 7 rat models and 1 control rat were randomly selected for observation of inflammatory infiltration in the periapical tissues by X-ray and HE staining. Immunohistochemistry was used to detect the expression and localization of Akt2, macrophages and the inflammatory mediators. RT-PCR was performed to detect the mRNA expressions of Akt2, CD86, CD163, inflammatory mediators, miR-155-5p and C/EBPβ to analyze the changes in macrophage polarization. RESULTS: X-ray and HE staining showed that periapical inflammation was the most obvious at 21 days after modeling in the rats. Immunohistochemistry and RT-PCR showed that compared with those in the control rats, the expressions of Akt2, CD86, CD163, miR-155-5p, C/EBPβ, and IL-10 increased significantly in the rat models at 21 days (P < 0.05). Compared with saline treatment, treatment with the Akt2 inhibitor significantly decreased the expression levels of Akt2, CD86, miR-155-5p and IL-6 and the ratio of CD86⁺M1/CD163⁺M2 macrophages (P < 0.05) and increased the expression levels of CD163, C/EBPβ and IL-10 in the rat models (P < 0.05). CONCLUSION Inhibition of Akt2 can delay the progression of periapical inflammation in rats and promote M2 macrophage polarization in the periapical inflammatory microenvironment possibly by reducing miR-155-5p expression and activating the expression of C/EBPβ in the Akt signaling pathway.
Rats ; Animals ; Proto-Oncogene Proteins c-akt/metabolism* ; MicroRNAs/genetics* ; Interleukin-10 ; Rats, Sprague-Dawley ; Macrophages/metabolism* ; Inflammation/metabolism*