This study aimed to investigate the effect and mechanism of Buyang Huanwu Decoction in regulating endoplasmic reticulum stress via the inositol-requiring enzyme 1α(IRE1α)/apoptosis signal-regulating kinase 1(ASK1)/c-Jun N-terminal kinase(JNK) pathway to improve neurological function in rats with cerebral ischemia/reperfusion injury(CIRI). SPF-grade male sprague-dawley(SD) rats were randomly divided into Sham group, model group, Buyang Huanwu Decoction group, and edaravone group. Except for the Sham group, the other groups were subjected to the modified suture method to establish a middle cerebral artery occlusion/reperfusion(MCAO/R) model. After treatment, neurological function was assessed using the Zea Longa scoring system. Gait analysis was used to detect the motor function. Detection of relative infarct area in brain tissue using 2,3,5-triphenyltetrazolium chloride(TTC) staining. Nissl staining was used to observe the structure of neuronal cells. Western blot and real-time fluorescence quantitative PCR(RT-qPCR) were used to detect IRE1α, ASK1, JNK, B cell lymphoma-2(Bcl-2), Bcl-2 related X protein(Bax), and Caspase-3 in the brain tissue. Immunohistochemistry was used to detect the positive expression of IRE1α, ASK1, and JNK. Immunofluorescence was used to detect the fluorescence expression levels of Bax, Bcl-2, and Caspase-3. The results showed that compared with the Sham group, the model group exhibited increased neurological scores(P<0.01), increased ratio of ground contact area and strength in both forelimbs(P<0.01), enlarged relative infarct area of brain tissue(P<0.05), and a reduced number of Nissl staining-positive cells(P<0.01). The protein and mRNA expression levels of IRE1α, ASK1, JNK, Bax, and Caspase-3 in brain tissue were significantly elevated, while those of Bcl-2 were decreased(P<0.05). Compared with the model group, both the Buyang Huanwu Decoction group and edaravone group showed reduced neurological scores(P<0.05), decreased ratio of ground contact area and strength in both forelimbs(P<0.05), smaller relative infarct area(P<0.05), alleviated neuronal damage, and increased number of Nissl staining-positive cells(P<0.05). The expression levels of IRE1α, ASK1, JNK, Bax, and Caspase-3 protein and mRNA in brain tissue were significantly reduced, while those of Bcl-2 were significantly increased(P<0.05). The results indicated that Buyang Huanwu Decoction can effectively improve brain injury in CIRI rats, and its mechanism of action may be related to regulating the endoplasmic reticulum stress IRE1α/ASK1/JNK signaling pathway.
Animals ; Male ; Rats, Sprague-Dawley ; Protein Serine-Threonine Kinases/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; MAP Kinase Kinase Kinase 5/genetics* ; Ischemic Stroke/physiopathology* ; Humans ; MAP Kinase Signaling System/drug effects* ; Apoptosis/drug effects* ; Endoribonucleases/genetics* ; JNK Mitogen-Activated Protein Kinases/genetics* ; Endoplasmic Reticulum Stress/drug effects* ; Multienzyme Complexes

Objective To construct a usability scale for smart hospital platforms based on Quality of Experience(QoE)theory,and provide scientific measurement tool for the construction,operation,and improvement of smart hospitals.Method Literature review,focus meeting method,and pre survey were used to screen and revise the scale items,forming a formal scale.Using convenience sampling method,1 000 users from 8 smart hospital platforms in Shandong Province were selected as the research subjects to evaluate the reliability and validity of the scale.Result The availability scale of the smart hospital platform includes 6 dimensions and 24 items.Exploratory factor extraction identified 6 common factors,with a cumulative variance contribution rate of 64.045%.The overall Cronbach's with a coefficient of 0.941 for 6 dimensions.The coefficient is between 0.782 and 0.963,and the retest reliability is 0.967.The Average Standardized Content Validity Index is 0.972,and the Item-level Content Validity Index is between 0.86 and 1.00.The correlation coefficient between the six dimensions of the scale and the System Usability Scale is 0.606-0.653,and the overall correlation coefficient is 0.647.Conclusion The usability scale of the smart hospital platform developed based on QoE theory has good reliability and validity,and can be used to measure the user experience of the smart hospital platform.

Objective To construct a usability scale for smart hospital platforms based on Quality of Experience(QoE)theory,and provide scientific measurement tool for the construction,operation,and improvement of smart hospitals.Method Literature review,focus meeting method,and pre survey were used to screen and revise the scale items,forming a formal scale.Using convenience sampling method,1 000 users from 8 smart hospital platforms in Shandong Province were selected as the research subjects to evaluate the reliability and validity of the scale.Result The availability scale of the smart hospital platform includes 6 dimensions and 24 items.Exploratory factor extraction identified 6 common factors,with a cumulative variance contribution rate of 64.045%.The overall Cronbach's with a coefficient of 0.941 for 6 dimensions.The coefficient is between 0.782 and 0.963,and the retest reliability is 0.967.The Average Standardized Content Validity Index is 0.972,and the Item-level Content Validity Index is between 0.86 and 1.00.The correlation coefficient between the six dimensions of the scale and the System Usability Scale is 0.606-0.653,and the overall correlation coefficient is 0.647.Conclusion The usability scale of the smart hospital platform developed based on QoE theory has good reliability and validity,and can be used to measure the user experience of the smart hospital platform.

Objective To construct a usability scale for smart hospital platforms based on Quality of Experience(QoE)theory,and provide scientific measurement tool for the construction,operation,and improvement of smart hospitals.Method Literature review,focus meeting method,and pre survey were used to screen and revise the scale items,forming a formal scale.Using convenience sampling method,1 000 users from 8 smart hospital platforms in Shandong Province were selected as the research subjects to evaluate the reliability and validity of the scale.Result The availability scale of the smart hospital platform includes 6 dimensions and 24 items.Exploratory factor extraction identified 6 common factors,with a cumulative variance contribution rate of 64.045%.The overall Cronbach's with a coefficient of 0.941 for 6 dimensions.The coefficient is between 0.782 and 0.963,and the retest reliability is 0.967.The Average Standardized Content Validity Index is 0.972,and the Item-level Content Validity Index is between 0.86 and 1.00.The correlation coefficient between the six dimensions of the scale and the System Usability Scale is 0.606-0.653,and the overall correlation coefficient is 0.647.Conclusion The usability scale of the smart hospital platform developed based on QoE theory has good reliability and validity,and can be used to measure the user experience of the smart hospital platform.

Objective To construct a usability scale for smart hospital platforms based on Quality of Experience(QoE)theory,and provide scientific measurement tool for the construction,operation,and improvement of smart hospitals.Method Literature review,focus meeting method,and pre survey were used to screen and revise the scale items,forming a formal scale.Using convenience sampling method,1 000 users from 8 smart hospital platforms in Shandong Province were selected as the research subjects to evaluate the reliability and validity of the scale.Result The availability scale of the smart hospital platform includes 6 dimensions and 24 items.Exploratory factor extraction identified 6 common factors,with a cumulative variance contribution rate of 64.045%.The overall Cronbach's with a coefficient of 0.941 for 6 dimensions.The coefficient is between 0.782 and 0.963,and the retest reliability is 0.967.The Average Standardized Content Validity Index is 0.972,and the Item-level Content Validity Index is between 0.86 and 1.00.The correlation coefficient between the six dimensions of the scale and the System Usability Scale is 0.606-0.653,and the overall correlation coefficient is 0.647.Conclusion The usability scale of the smart hospital platform developed based on QoE theory has good reliability and validity,and can be used to measure the user experience of the smart hospital platform.

Objective To construct a usability scale for smart hospital platforms based on Quality of Experience(QoE)theory,and provide scientific measurement tool for the construction,operation,and improvement of smart hospitals.Method Literature review,focus meeting method,and pre survey were used to screen and revise the scale items,forming a formal scale.Using convenience sampling method,1 000 users from 8 smart hospital platforms in Shandong Province were selected as the research subjects to evaluate the reliability and validity of the scale.Result The availability scale of the smart hospital platform includes 6 dimensions and 24 items.Exploratory factor extraction identified 6 common factors,with a cumulative variance contribution rate of 64.045%.The overall Cronbach's with a coefficient of 0.941 for 6 dimensions.The coefficient is between 0.782 and 0.963,and the retest reliability is 0.967.The Average Standardized Content Validity Index is 0.972,and the Item-level Content Validity Index is between 0.86 and 1.00.The correlation coefficient between the six dimensions of the scale and the System Usability Scale is 0.606-0.653,and the overall correlation coefficient is 0.647.Conclusion The usability scale of the smart hospital platform developed based on QoE theory has good reliability and validity,and can be used to measure the user experience of the smart hospital platform.

Objective To construct a usability scale for smart hospital platforms based on Quality of Experience(QoE)theory,and provide scientific measurement tool for the construction,operation,and improvement of smart hospitals.Method Literature review,focus meeting method,and pre survey were used to screen and revise the scale items,forming a formal scale.Using convenience sampling method,1 000 users from 8 smart hospital platforms in Shandong Province were selected as the research subjects to evaluate the reliability and validity of the scale.Result The availability scale of the smart hospital platform includes 6 dimensions and 24 items.Exploratory factor extraction identified 6 common factors,with a cumulative variance contribution rate of 64.045%.The overall Cronbach's with a coefficient of 0.941 for 6 dimensions.The coefficient is between 0.782 and 0.963,and the retest reliability is 0.967.The Average Standardized Content Validity Index is 0.972,and the Item-level Content Validity Index is between 0.86 and 1.00.The correlation coefficient between the six dimensions of the scale and the System Usability Scale is 0.606-0.653,and the overall correlation coefficient is 0.647.Conclusion The usability scale of the smart hospital platform developed based on QoE theory has good reliability and validity,and can be used to measure the user experience of the smart hospital platform.

Near-infrared(NIR)spectroscopy reflects the vibrational information of hydrogen-containing groups,allowing the detection of changes in components such as proteins and lipids in biological samples caused by diseases.Due to the advantages such as rapidity,non-destructiveness and non-invasiveness,NIR spectroscopy has been widely used in disease diagnosis.Malignant tumor cells exhibit significant differences in structure and composition compared to normal cells,and abnormal metabolic functions cause changes in the composition of biological tissues and fluids,leading to the variation in spectra.This makes NIR spectroscopy a promising tool for detecting cancer.However,severe overlapping of spectral peaks in the spectra requires the help of chemometrics methods to analyze the spectra and extract diagnostic information.This review summarizes the recent advances in NIR spectroscopy technology in cancer detection,including the methods of spectral preprocessing,diagnosis modeling and the development in NIR hyperspectral imaging combined with deep learning methods.The quantitative information and structural changes of molecules in biological systems can be extracted.Furthermore,the sensitivity of NIR spectra to water is utilized to analyze the content and structural changes of water induced by cancer and its role in cancer detection.

Objective:To summarize the current research status, assessment tools, and influencing factors of fatigue in patients receiving maintenance hemodialysis (MHD) and provide a reference for the management of fatigue in this patient population.Methods:A literature search was conducted in databases including PubMed, Web of Science, ProQuest, Cochrane Library, Science Direct, Embase, CINAHL, China National Knowledge Infrastructure, WanFang Data, VIP, and China Biology Medicine disc for studies related to fatigue in patients receiving MHD. The search timeframe was from establishing the databases to January 23, 2024.Results:A total of 46 studies were included. Various assessment tools for fatigue in patients receiving MHD were identified, though specific tools were limited. The Short Form 36 Vitality Subscale (SF-36 VS) was the most commonly used assessment tool. The main factors influencing fatigue in these patients included sociodemographic, dialysis-related, disease-related, physical, nutritional, and psychological factors.Conclusions:Fatigue is a significant symptom in patients receiving MHD. Healthcare professionals must develop specific tools for accurately assessing fatigue in this population and explore standardized management plans.

Data analysis models may assist the transmission of traditional Chinese medicine （TCM） experience and clinical diagnosis and treatment， and the possibility of constructing a “data-knowledge” dual-drive model was explored by taking gastric precancerous state as an example. Data-driven is to make clinical decisions around data analysis， and its syndrome-differentiation decision-making research relies on hidden structural models and partially observable Markov decision-making processes to identify the etiology of diseases， syndrome elements， evolution of pathogenesis， and syndrome differentiation protocols； knowledge-driven is to make use of data and information to promote decision-making and action processes， and its syndrome-differentiation decision-making research relies on convolutional neural networks to improve the accuracy of local disease identification and syndrome differentiation. The “data-knowledge” dual-driven model can make up for the shortcomings of single-drive numerical simulation accuracy， and achieve a balance between local disease identification and macroscopic syndrome differentiation. On the basis of previous research， we explored the construction method of diagnostic assisted decision-making platform for gastric precancerous state， and believed that the diagnostic and decision-making ability of doctors can be extended through the assistance of machines and algorithms. Meanwhile， the related research methods were integrated and the core features of gastric precancerous state based on TCM syndrome differentiation and endoscopic pathology diagnosis and prediction were obtained， and the elements of endoscopic pathology recognition based on TCM syndrome differentiation were explored， so as to provide ideas for the in-depth research and innovative application of cutting-edge data analysis technology in the field of intelligent TCM syndrome differentiation.