Meditation aims to guide individuals into a state of deep calm and focused attention, and in recent years, it has shown promising potential in the field of medical treatment. Numerous studies have demonstrated that electroencephalogram (EEG) patterns change during meditation, suggesting the feasibility of using deep learning techniques to monitor meditation states. However, significant inter-subject differences in EEG signals poses challenges to the performance of such monitoring systems. To address this issue, this study proposed a novel model-calibrated multi-source adversarial adaptation network (CMAAN). The model first trained multiple domain-adversarial neural networks in a pairwise manner between various source-domain individuals and the target-domain individual. These networks were then integrated through a calibration process using a small amount of labeled data from the target domain to enhance performance. We evaluated the proposed model on an EEG dataset collected from 18 subjects undergoing methamphetamine rehabilitation. The model achieved a classification accuracy of 73.09%. Additionally, based on the learned model, we analyzed the key EEG frequency bands and brain regions involved in the meditation process. The proposed multi-source domain adaptation framework improves both the performance and robustness of EEG-based meditation monitoring and holds great promise for applications in biomedical informatics and clinical practice.
Humans ; Electroencephalography/methods* ; Meditation ; Calibration ; Neural Networks, Computer ; Brain/physiology* ; Rest/physiology* ; Deep Learning ; Signal Processing, Computer-Assisted

PURPOSE: The rate of complications among patients undergoing surgery has increased due to infection with SARS-CoV-2 and other variants of concern. However, Omicron has shown decreased pathogenicity, raising questions about the risk of postoperative complications among patients who are infected with this variant. This study aimed to investigate complications and related factors among patients with recent Omicron infection prior to undergoing orthopedic surgery. METHODS: A historical control study was conducted. Data were collected from all patients who underwent surgery during 2 distinct periods: (1) between Dec 12, 2022 and Jan 31, 2023 (COVID-19 positive group), (2) between Dec 12, 2021 and Jan 31, 2022 (COVID-19 negative control group). The patients were at least 18 years old. Patients who received conservative treatment after admission or had high-risk diseases or special circumstances (use of anticoagulants before surgery) were excluded from the study. The study outcomes were the total complication rate and related factors. Binary logistic regression analysis was used to identify related factors, and odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the impact of COVID-19 infection on complications. RESULTS: In the analysis, a total of 847 patients who underwent surgery were included, with 275 of these patients testing positive for COVID-19 and 572 testing negative. The COVID-19-positive group had a significantly higher rate of total complications (11.27%) than the control group (4.90%, p < 0.001). After adjusting for relevant factors, the OR was 3.08 (95% CI: 1.45-6.53). Patients who were diagnosed with COVID-19 at 3-4 weeks (OR = 0.20 (95% CI: 0.06-0.59), p = 0.005), 5-6 weeks (OR = 0.16 (95% CI: 0.04-0.59), p = 0.010), or ≥7 weeks (OR = 0.26 (95% CI: 0.06-1.02), p = 0.069) prior to surgery had a lower risk of complications than those who were diagnosed at 0-2 weeks prior to surgery. Seven factors (age, indications for surgery, time of operation, time of COVID-19 diagnosis prior to surgery, C-reactive protein levels, alanine transaminase levels, and aspartate aminotransferase levels) were found to be associated with complications; thus, these factors were used to create a nomogram. CONCLUSION Omicron continues to be a significant factor in the incidence of postoperative complications among patients undergoing orthopedic surgery. By identifying the factors associated with these complications, we can determine the optimal surgical timing, provide more accurate prognostic information, and offer appropriate consultation for orthopedic surgery patients who have been infected with Omicron.
Humans ; COVID-19/complications* ; Male ; Female ; Middle Aged ; Postoperative Complications/epidemiology* ; SARS-CoV-2 ; Orthopedic Procedures/adverse effects* ; Aged ; Nomograms ; Adult ; Retrospective Studies ; Risk Factors

Objective:To investigate the personnel, equipment, new technology of various radiotherapy units in Gansu Province, aiming to deeply understand the current status of radiotherapy in Gansu Province.Methods:From March 2023 to March 2024, the data of personnel, equipment and technology of different radiotherapy units in Gansu Province were investigated via online questionnaire survey and offline field visits by Gansu Provincial Quality Control Center for Radiation Oncology. The questionable data were reviewed, logical verification and outlier identification were conducted, and all information was entered according to the principle of double entry. Qualitative data were described by frequency (percentage).Results:As of March 2024, there are 26 radiotherapy units in Gansu Province, including 7 units in Lanzhou, capital city of Gansu Province and none in Linxia Hui Autonomous Prefecture and Gannan Tibetan Autonomous Prefecture. The ratio of radiotherapy physicians and physicists was 2.71 vs. 1, lower than the national level of 3.51 vs. 1. Radiotherapy physicians with intermediate and senior titles accounted for 66.2%, 54% for physicists with intermediate and senior titles and 34.0% for therapists with intermediate and senior titles, respectively. There were 1.70 accelerators per million population in Gansu Province. Among 42 accelerators in Gansu Province, 40 were linac and 2 heavy ion accelerators. In Lanzhou, 7 radiotherapy units had 17 linac, and the remaining 11 cities had 23 linac. All 40 linac could perform 3D conformal radiotherapy and intensity-modulated radiotherapy. The high-end equipment could apply advanced technologies such as volumetric modulated arc radiotherapy, stereotactic body radiotherapy, optical surface-guided radiation therapy and adaptive radiation therapy, etc. Relevant data in this survey were improved compared with those in the national surveys conducted in 2006, 2015 and 2019. Conclusions:The radiotherapy status has developed in Gansu Province, whereas uneven development still exists among regions. According to the actual demands of equipment, talents and technology in each region, the structural adjustment should be oriented to the underdeveloped cities and counties in the province to meet the local medical needs.

Aim To investigate the effect of angioten-sin Ⅱ type 1a receptor(AT1aR)knockout on cardiac dysfunction in rats with obesity and its possible molecu-lar mechanism.Methods SD rats(n=24)were used to generated the whole-body AT1 aR-deficiency rats by sgRNA and the CRISPR/Cas9 system,and the obesity model was constructed by feeding with high-fat diet(HFD).They were divided into four groups:wildtype(WT)and knockout(KO)groups with nor-mal feeding and their respective high-fat diets groups.Color ultrasound diagnostic instrument was uses to e-valuate the cardiac function;oil red O staining was a-dopted to stain the myocardial lipids;RT-PCR was used to detect the levels of GPX4 and Ptgs2 genes in myocardial tissue.Western blot was employed to detect the expression of GPX4,ferritin,Nrf2,HO-1 and NQO1 in rat myocardial tissue.ELISA and other kits were used to determine the lipid contents in serum and myocardium.Results It was found that high-fat feed-ing caused cardiac dysfunction,serum lipid disorders,oxidative stress and ferroptosis in SD rats.However,these changes were attenuated in AT1aR knockout rats fed with high-fat diet.Furthermore,compared with WT-HFD group,KO-HFD rats showed enhanced acti-vation of the Nrf2/HO-1 pathway in the myocardium,reduced ferroptosis,decreased lipid accumulation,and reduced cardiac dysfunction.Conclusion AT1aR knockout can improve HFD-induced cardiac dysfunc-tion by enhancing antioxidant capacity and reducing the degree of ferroptosis.

Aim To investigate the effect of angioten-sin Ⅱ type 1a receptor(AT1aR)knockout on cardiac dysfunction in rats with obesity and its possible molecu-lar mechanism.Methods SD rats(n=24)were used to generated the whole-body AT1 aR-deficiency rats by sgRNA and the CRISPR/Cas9 system,and the obesity model was constructed by feeding with high-fat diet(HFD).They were divided into four groups:wildtype(WT)and knockout(KO)groups with nor-mal feeding and their respective high-fat diets groups.Color ultrasound diagnostic instrument was uses to e-valuate the cardiac function;oil red O staining was a-dopted to stain the myocardial lipids;RT-PCR was used to detect the levels of GPX4 and Ptgs2 genes in myocardial tissue.Western blot was employed to detect the expression of GPX4,ferritin,Nrf2,HO-1 and NQO1 in rat myocardial tissue.ELISA and other kits were used to determine the lipid contents in serum and myocardium.Results It was found that high-fat feed-ing caused cardiac dysfunction,serum lipid disorders,oxidative stress and ferroptosis in SD rats.However,these changes were attenuated in AT1aR knockout rats fed with high-fat diet.Furthermore,compared with WT-HFD group,KO-HFD rats showed enhanced acti-vation of the Nrf2/HO-1 pathway in the myocardium,reduced ferroptosis,decreased lipid accumulation,and reduced cardiac dysfunction.Conclusion AT1aR knockout can improve HFD-induced cardiac dysfunc-tion by enhancing antioxidant capacity and reducing the degree of ferroptosis.

Objective:To investigate the personnel, equipment, new technology of various radiotherapy units in Gansu Province, aiming to deeply understand the current status of radiotherapy in Gansu Province.Methods:From March 2023 to March 2024, the data of personnel, equipment and technology of different radiotherapy units in Gansu Province were investigated via online questionnaire survey and offline field visits by Gansu Provincial Quality Control Center for Radiation Oncology. The questionable data were reviewed, logical verification and outlier identification were conducted, and all information was entered according to the principle of double entry. Qualitative data were described by frequency (percentage).Results:As of March 2024, there are 26 radiotherapy units in Gansu Province, including 7 units in Lanzhou, capital city of Gansu Province and none in Linxia Hui Autonomous Prefecture and Gannan Tibetan Autonomous Prefecture. The ratio of radiotherapy physicians and physicists was 2.71 vs. 1, lower than the national level of 3.51 vs. 1. Radiotherapy physicians with intermediate and senior titles accounted for 66.2%, 54% for physicists with intermediate and senior titles and 34.0% for therapists with intermediate and senior titles, respectively. There were 1.70 accelerators per million population in Gansu Province. Among 42 accelerators in Gansu Province, 40 were linac and 2 heavy ion accelerators. In Lanzhou, 7 radiotherapy units had 17 linac, and the remaining 11 cities had 23 linac. All 40 linac could perform 3D conformal radiotherapy and intensity-modulated radiotherapy. The high-end equipment could apply advanced technologies such as volumetric modulated arc radiotherapy, stereotactic body radiotherapy, optical surface-guided radiation therapy and adaptive radiation therapy, etc. Relevant data in this survey were improved compared with those in the national surveys conducted in 2006, 2015 and 2019. Conclusions:The radiotherapy status has developed in Gansu Province, whereas uneven development still exists among regions. According to the actual demands of equipment, talents and technology in each region, the structural adjustment should be oriented to the underdeveloped cities and counties in the province to meet the local medical needs.

Objective:To construct an ensemble machine learning model for predicting the occurrence of clinically relevant postoperative pancreatic fistula (CR-POPF) after pancreaticoduodenectomy and evaluate its application value.Methods:This is a research on predictive model. Clinical data of 421 patients undergoing pancreaticoduodenectomy in the Department of Pancreatic Surgery,Union Hospital, Tongji Medical College,Huazhong University of Science and Technology from June 2020 to May 2023 were retrospectively collected. There were 241 males (57.2%) and 180 females (42.8%) with an age of (59.7±11.0)years (range: 12 to 85 years).The research objects were divided into training set (315 cases) and test set (106 cases) by stratified random sampling in the ratio of 3∶1. Recursive feature elimination is used to screen features,nine machine learning algorithms are used to model,three groups of models with better fitting ability are selected,and the ensemble model was constructed by Stacking algorithm for model fusion. The model performance was evaluated by various indexes,and the interpretability of the optimal model was analyzed by Shapley Additive Explanations(SHAP) method. The patients in the test set were divided into different risk groups according to the prediction probability (P) of the alternative pancreatic fistula risk score system (a-FRS). The a-FRS score was validated and the predictive efficacy of the model was compared.Results:Among 421 patients,CR-POPF occurred in 84 cases (20.0%). In the test set,the Stacking ensemble model performs best,with the area under the curve (AUC) of the subject′s work characteristic curve being 0.823,the accuracy being 0.83,the F1 score being 0.63,and the Brier score being 0.097. SHAP summary map showed that the top 9 factors affecting CR-POPF after pancreaticoduodenectomy were pancreatic duct diameter,CT value ratio,postoperative serum amylase,IL-6,body mass index,operative time,albumin difference before and after surgery,procalcitonin and IL-10. The effects of each feature on the occurrence of CR-POPF after pancreaticoduodenectomy showed a complex nonlinear relationship. The risk of CR-POPF increased when pancreatic duct diameter<3.5 mm,CT value ratio<0.95,postoperative serum amylase concentration>150 U/L,IL-6 level>280 ng/L,operative time>350 minutes,and albumin decreased by more than 10 g/L. The AUC of a-FRS in the test set was 0.668,and the prediction performance of a-FRS was lower than that of the Stacking ensemble machine learning model.Conclusion:The ensemble machine learning model constructed in this study can predict the occurrence of CR-POPF after pancreaticoduodenectomy,and has the potential to be a tool for personalized diagnosis and treatment after pancreaticoduodenectomy.

Objective:To construct an ensemble machine learning model for predicting the occurrence of clinically relevant postoperative pancreatic fistula (CR-POPF) after pancreaticoduodenectomy and evaluate its application value.Methods:This is a research on predictive model. Clinical data of 421 patients undergoing pancreaticoduodenectomy in the Department of Pancreatic Surgery,Union Hospital, Tongji Medical College,Huazhong University of Science and Technology from June 2020 to May 2023 were retrospectively collected. There were 241 males (57.2%) and 180 females (42.8%) with an age of (59.7±11.0)years (range: 12 to 85 years).The research objects were divided into training set (315 cases) and test set (106 cases) by stratified random sampling in the ratio of 3∶1. Recursive feature elimination is used to screen features,nine machine learning algorithms are used to model,three groups of models with better fitting ability are selected,and the ensemble model was constructed by Stacking algorithm for model fusion. The model performance was evaluated by various indexes,and the interpretability of the optimal model was analyzed by Shapley Additive Explanations(SHAP) method. The patients in the test set were divided into different risk groups according to the prediction probability (P) of the alternative pancreatic fistula risk score system (a-FRS). The a-FRS score was validated and the predictive efficacy of the model was compared.Results:Among 421 patients,CR-POPF occurred in 84 cases (20.0%). In the test set,the Stacking ensemble model performs best,with the area under the curve (AUC) of the subject′s work characteristic curve being 0.823,the accuracy being 0.83,the F1 score being 0.63,and the Brier score being 0.097. SHAP summary map showed that the top 9 factors affecting CR-POPF after pancreaticoduodenectomy were pancreatic duct diameter,CT value ratio,postoperative serum amylase,IL-6,body mass index,operative time,albumin difference before and after surgery,procalcitonin and IL-10. The effects of each feature on the occurrence of CR-POPF after pancreaticoduodenectomy showed a complex nonlinear relationship. The risk of CR-POPF increased when pancreatic duct diameter<3.5 mm,CT value ratio<0.95,postoperative serum amylase concentration>150 U/L,IL-6 level>280 ng/L,operative time>350 minutes,and albumin decreased by more than 10 g/L. The AUC of a-FRS in the test set was 0.668,and the prediction performance of a-FRS was lower than that of the Stacking ensemble machine learning model.Conclusion:The ensemble machine learning model constructed in this study can predict the occurrence of CR-POPF after pancreaticoduodenectomy,and has the potential to be a tool for personalized diagnosis and treatment after pancreaticoduodenectomy.

Objective:This study conducted mosquito-borne viruses RNA screening and analysis of virus evolution characteristics on mosquito specimens collected in 2023 from Hunchun city, Jilin province, China.Methods:Firstly, morphological method were employed for mosquito specimen classification. Then, real-time fluorescence quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to detect the RNA of six mosquito-borne viruses in the collected mosquitos, i. e., Banna virus (BAV), Kadipiro virus (KDV), Liaoning virus (LNV), Tahyna virus (TAHV), Getah virus (GETV) and Japanese encephalitis virus (JEV). And by sequencing, the viral genome sequence of positive samples was obtained.Results:A total of 5490 mosquito specimens were collected from Hunchun city, Jilin province, included 4400 Aedes vexans (80.15%), 1090 Anopheles sinensis (19.85%). A total of 41 groups were obtained by mixing samples according to the time, location, and mosquito species collected. qRT-PCR result showed that only the Aedes vexans sample with the number JLHC2321 was tested positive for LNV, while the remaining samples were tested negative for the detected viruses. According to the phylogenetic analysis of the segment 10 gene, this LNV strain had the closest genetic relationship with NE9731 and belonged to the type II branch. Meanwhile, the amino acid sequence analysis based on the coding sequence (CDS) in the segment 10 showed that JLHC2321 only had 2 amino acid differential sites with the GII reference strain NE9731.Conclusions:This study detected LNV for the first time in Aedes vexans in Hunchun city, and our result provide important basic data for the monitoring and prevention strategies of mosquito-borne viruses in the region.

In the past 20 years,near infrared spectrum technology has been widely used in human body monitoring due to its non-invasive and real-time characteristics.Oxygen,as the main metabolic substance of the human body,is consumed the most in brain tissue.In order to prevent complications caused by a decrease in brain tissue oxygen during treatment,the patient's brain tissue blood oxygen saturation needs to be monitored in real time.Currently,most of the clinically used non-invasive cerebral blood oxygen detection equipments use dual wavelengths.Other substances on the detection path will cause errors in the measurement results.Therefore,this article proposes a three-wavelength method based on the basic principle of non-invasive monitoring of cerebral blood oxygen using near-infrared spectrum.The brain tissue oxygen saturation monitoring method of detecting light sources was initially verified through the built system,laying the foundation for subsequent system engineering.