Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Objective To investigate the implementation of surveillance,prevention and control measures for healthcare-associated infection(HAI)in maternal and child healthcare(MCH)institutions,and provide policy evi-dence for optimizing HAI prevention and control in MCH institutions.Methods Stratified sampling was conducted among the MCH institutions at provincial,municipal and county levels in 8 provinces/autonomous regions.A uni-fied questionnaire was designed and the online survey was conducted through"Questionnaire Star".Results The data from 123 MCH institutions were included in the analysis.90.24％of the MCH institutions carried out compre-hensive surveillance on HAI.The ratios of MCH institutions which implemented targeted surveillance on HAI in neonatal intensive care unit(NICU),surgical site infection,multidrug-resistant organisms(MDROs)and HAI in intensive care units(non-NICU excluded)were 89.66％,85.96％,80.77％,and 74.19％,respectively.51.22％MCH institutions adopted information surveillance system on HAI cases.94.31％MCH institutions carried out surveillance on hand hygiene compliance.Over 90％MCH institutions carried out surveillance on environment hy-giene in high-risk departments.71.54％MCH institutions conducted centralized cleaning,disinfection,sterilization and supply for reusable medical instruments in the central sterile supply department(CSSD).Over 90％MCH insti-tutions established three-level pre-examination triage systems.86.18％set up transitional wards.MCH institutions generally adopted a management model with established effective communication,full appointment visits,and sepa-rate visits for special medical groups,such as registered pregnant women,high-risk newborns,healthcare groups,and long-term rehabilitation patients.However,the ratio of institutions conducting on-line follow-up visits was less than 50％.Conclusion MCH institutions have generally carried out comprehensive and targeted surveillance on HAI.Information surveillance need to be facilitated.Hand hygiene and environmental hygiene surveillance has been popularized to a certain extent at all levels of MCH institutions.The cleaning,disinfection,sterilization,and supply processes of reusable medical devices in a few MCH institutions are not standardized.Special medical populations get effective management.On-line healthcare is to be further promoted.

A liquid chromatography-tandem mass spectrometry method was established and validated for determining the concentrations of costunolide(CO), piperine(PI), agarotetrol(AG), glycyrrhizic acid(GL), vanillic acid(VA), and glycyrrhetinic acid(GA) in rat plasma. This method was then applied to the toxicokinetic study of these six compounds in rats with chronic cerebral ischemia(CCI) following multiple oral doses of Zhachong Shisanwei Pills. Finally, the effects of continuous multiple-dose administration of Zhachong Shisanwei Pills on the liver of CCI rats were investigated. The results showed that after oral administration of different doses of Zhachong Shisanwei Pills, the in vivo exposure of AG, VA, and GA was relatively high, with AUC_(0-∞) values ranging from 604.0-2 494.2, 1 305.4-4 634.5, and 2 177.5-4 045.7 h·ng·mL~(-1), respectively, while the exposure of CO, PI, and GL was relatively low, with AUC_(0-∞) values ranging from 37.8-238.2, 2.4-17.0, and 146.9-408.5 h·ng·mL~(-1), respectively. The C_(max) and AUC_(0-∞) of the six compounds were positively correlated with the administered dose. The T_(max) of PI and AG ranged from 0.3 to 2.0 h, their T_(1/2) ranged from 0.8 to 2.9 h, and their mean residence time(MRT) ranged from 1.0 to 3.7 h. The T_(max) of GL and VA was shorter(0.4-1.9 h), while their T_(1/2)(2.6-5.9 h) and MRT(2.5-8.5 h) were longer. Both CO and GA exhibited a bimodal phenomenon, with T_(max) ranging from 1.6 to 6.6 h, T_(1/2) ranging from 2.8 to 7.7 h, and MRT ranging from 4.1 to 12.9 h. Liver histopathology after 28 days of continuous multiple-dose administration of Zhachong Shisanwei Pills showed that the liver tissue remained normal at a low dose(crude drug 0.8 g·kg~(-1), approximately 5 times the clinical equivalent dose). However, as the dose increased(crude drug 1.1-3.0 g·kg~(-1), 6.9-18.8 times the clinical equivalent dose), varying degrees of liver damage were observed. Blood biochemical tests revealed no significant changes in the serum levels of alanine aminotransferase(ALT), aspartate aminotransferase(AST), alkaline phosphatase(ALP), and total bile acid(TBA) in CCI rats from administration groups 1 to 3(crude drug 0.8, 1.1, 1.5 g·kg~(-1)). However, ALT, AST, ALP, and TBA levels in groups 4 and 5(crude drug 2.1, 3.0 g·kg~(-1)) showed significant increases. This study preliminarily elucidated the toxicokinetic characteristics of the six compounds in Zhachong Shisanwei Pills and their effects on liver tissue in CCI rats, providing data as a reference for clinical use.
Animals ; Tandem Mass Spectrometry/methods* ; Rats ; Drugs, Chinese Herbal/toxicity* ; Male ; Rats, Sprague-Dawley ; Brain Ischemia/blood* ; Chromatography, Liquid/methods* ; Polyunsaturated Alkamides/blood* ; Piperidines/toxicity* ; Benzodioxoles/toxicity* ; Alkaloids/blood* ; Liquid Chromatography-Mass Spectrometry

Aim To evaluate the effects of puerarin (PR) on pancreatic islet MIN6 cell injury and apopto- sis induced by palmitic acirl ( PA).Methods MIN6 cells pretreated with 2 h different concentrations of PR were then co-cultured with 120 (xmol • L"1 PA for 24 h to establish the cell injury and apoptosis model.MTT, LDH,MDA and GSH were used to determine the dam¬age of MIN6 cells.AOEB fluorescence staining was used to detect the apoptosis of MIN6 cells.Western blot was used to detect the expressions of inflammation- related protein NF-kB , apoptosis-related factors Bcl-2 and Bax.Results Compared with model group, cell viability and GSH activity of puerarin administration groups increased, LDH and MDA contents decreased.the protein expressions of p-NF-KB and Bax were down-regulated, and the protein expressions of Bcl-2 were up-regulated (P <0.05).Conclusions Puerar- in ean improve the function of pancreatic islet cells by inhibiting apoptosis and inflammation, and ameliorate pancreatic islet MIN6 cell injury and apoptosis induced by palmitic acid-induced, alleviate MIN6 cell injury in¬duced by inflammatory factors, which may be achieved by down-regulating the expression of p-NF-KB and Bax proteins,and up-regulating the expression of Bcl-2 pro¬tein.

Objective Airway-related patient safety incident (PSI) has always been the top concern of anesthesiologists because this type of incidents could severely threaten patient safety if not treated immediately and properly. This study intends to reveal the composition, prognosis, and to identify risk factors for airway related incidents reported by anesthesiologists. Methods All airway related PSIs reported by anesthesiologists in a Chinese academic hospital between September 2009 and May 2022 were collected from the PSI reporting system. Patients with airway incidents reported were matched 1:1 with controls based on sex and type of surgery. Univariable and multivariable analysis were performed to find risk factors associated with airway incident occurrence, and to evaluate influence of airway PSIs on patient prognosis. Results Among 1,038 PSIs voluntarily reported by anesthesiologists during the study period, 281 cases (27.1%) were airway-related incidents, with an overall reporting incidence of 4.74 per 10,000 among 592,884 anesthesia care episodes. Only ASA physical status was found to be significant independent predictor of these airway PSIs (P = 0.020). Patients with airway PSIs reported had longer extubation time (0.72 ± 1.56 d vs. 0.16 ± 0.77 d, 95%CI: 0.29 to 0.82, P < 0.001), longer ICU length of stay (LOS) (1.63 ± 5.71 d vs. 0.19 ± 0.84 d, 95%CI: 0.57 to 2.32, P= 0.001), longer post operative LOS (10.56 ± 13.09 d vs. 7.59 ± 10.76 d, 95%CI: 0.41 to 5.53, P = 0.023), and longer total in-hospital LOS (14.99 ± 15.18 d vs. 11.62 ± 11.88 d, 95%CI: 0.46 to 6.27,P = 0.024). Conclusions This single-center retrospective case-control study describes the composition of airway-related PSIs reported by anesthesiologists within thirteen years. Airway incidents might influence patient prognosis by elongating extubation time and LOS. Airway PSI data were worth analyzing to improve patient safety.
Humans ; Patient Safety ; Retrospective Studies ; Case-Control Studies ; Anesthesia/adverse effects* ; Risk Factors