OBJECTIVE: To observe the efficacy and safety of Tiaowei Jiannao acupuncture (acupuncture for regulating defensive qi and nourishing brain) for post-ischemic stroke insomnia (PISI). METHODS: A total of 96 patients with PISI were randomized into an acupuncture group (32 cases, 1 case was excluded), a medication group (32 cases, 1 case dropped out, 1 case was excluded) and a sham-acupuncture group (32 cases, 1 case dropped out, 1 case was excluded). In the acupuncture group, Tiaowei Jiannao acupuncture was applied at bilateral Shenmai (BL62), Zhaohai (KI6), Hegu (LI4), Taichong (LR3), and Baihui (GV20), Sishencong (EX-HN1), Yintang (GV24⁺), Shenting (GV24), once a day, 1-day interval was taken after 6-day treatment, for 3 weeks totally. In the medication group, eszopiclone tablet was given orally, 1-3 mg a time, once a day for 3 weeks. In the sham-acupuncture group, non-invasive sham acupuncture was applied, the acupoint selection, frequency and course of treatment were the same as the acupuncture group. Before treatment, after 2,3 weeks of treatment, the scores of Pittsburgh sleep quality index (PSQI), self-rating sleep scale (SRSS), National Institutes of Health Stroke scale (NIHSS), Hamilton depression scale-17 (HAMD-17) were observed; before and after treatment, the sleep parameters were recorded using polysomnography (PSG); and the efficacy and safety were evaluated after treatment in the 3 groups. RESULTS: After 2,3 weeks of treatment, the scores of PSQI, HAMD-17 and SRSS in the acupuncture group and the medication group, as well as the SRSS scores in the sham-acupuncture group were decreased compared with those before treatment (P<0.05); after 2 weeks of treatment, the NIHSS score in the acupuncture group was decreased compared with that before treatment (P<0.05); after 3 weeks of treatment, the NIHSS scores in the acupuncture group, the medication group and the sham-acupuncture group were decreased compared with those before treatment (P<0.05). After 3 weeks of treatment, the scores of PSQI, SRSS, HAMD-17 and NIHSS in the acupuncture group and the medication group, as well as the NIHSS score in the sham-acupuncture group were decreased compared with those after 2 weeks of treatment (P<0.05). After 2,3 weeks of treatment, the scores of PSQI, SRSS and HAMD-17 in the acupuncture group and the medication group were lower than those in the sham-acupuncture group (P<0.05), the NIHSS scores in the acupuncture group were lower than those in the medication group and the sham-acupuncture group (P<0.05); after 3 weeks of treatment, HAMD-17 score in the acupuncture group was lower than that in the medication group (P<0.05), the NIHSS score in the medication group was lower than that in the sham-acupuncture group (P<0.05). Compared before treatment, after treatment, the total sleep time was prolonged (P<0.05), the wake after sleep onset, sleep latency, and non-rapid eye movement (NREM) sleep latency were shortened (P<0.05), the sleep efficiency was improved (P<0.05), the number of awakenings was reduced (P<0.05), the percentage of rapid eye movement (REM%) and the percentage of NREM stage 1 (N1%) were decreased (P<0.05), the percentage of NREM stage 2 (N2%) and the percentage of NREM stage 3 (N3%) were increased (P<0.05) in the acupuncture group and the medication group; the sleep latency was shortened in the sham-acupuncture group (P<0.05). After treatment, the PSG indexes in the acupuncture group and the medication group were superior to those in the sham-acupuncture group (P<0.05); in the acupuncture group, the number of awakenings was less than that in the medication group (P<0.05), the REM% and N1% were lower than those in the medication group (P<0.05), the N2% and N3% were higher than those in the medication group (P<0.05). The total effective rate were 93.5% (29/31) and 90.0% (27/30) in the acupuncture group and the medication group respectively, which were higher than 10.0% (3/30) in the sham-acupuncture group (P<0.05). There was no serious adverse events in any of the 3 groups. CONCLUSION Tiaowei Jiannao acupuncture improves the insomnia symptoms in patients with ischemic stroke, improves the quality of sleep, increases the deep sleep, promotes the recovery of neurological function, and relieves the depression. It is effective and safe for the treatment of PISI.
Humans ; Acupuncture Therapy ; Male ; Sleep Initiation and Maintenance Disorders/physiopathology* ; Female ; Middle Aged ; Aged ; Acupuncture Points ; Treatment Outcome ; Adult ; Ischemic Stroke/complications* ; Stroke/complications* ; Sleep

ObjectiveTo explore the effects of Renshentang on atherosclerosis （AS） in mice based on the role of transient receptor potential vanilloid1 （TRPV1） in regulating cholesterol metabolism in foam cells. MethodsNine SPF-grade 8-week-old C57BL/6J mice were set as a normal group， and 60 ApoE^-/- mice were randomized into model， positive drug （simvastatin， 0.02 g·kg^-1·d^-1）， and low-， medium-， and high-dose （1.77， 3.54， 7.08 g·kg^-1·d^-1， respectively） Renshentang groups （n=12） according to body weight. The normal group was fed with a normal diet， and the other groups were fed with a high-fat diet and given corresponding drugs by oral gavage for the modeling of AS. The mice were administrated with corresponding drugs once a day for 12 weeks. After the last administration and fasting for 12 h， the aorta was collected. Plaque conditions， pathological changes， levels of total cholesterol （TC）， triglcerides （TG）， low-density lipoprotein-cholesterol （LDL-C）， and high-density lipoprotein-cholesterol （HDL-C）， and the expression of TRPV1， liver X receptor （LXR）， inducible degrader of the low-density lipoprotein receptor （IDOL）， and low-density lipoprotein receptor （LDLR） in the aortic tissue were observed and detected by gross oil red O staining， HE staining， Western blot， immunohistochemistry， and real-time PCR. ResultsCompared with the normal group， the model group presented obvious plaque deposition in the aorta， raised levels of TC， TG， and LDL-C in the serum （P<0.01）， up-regulated expression level of LDLR in the aorta （P<0.01）， lowered level of HDL-C in the serum， and down-regulated expression levels of TRPV1， LXR， and IDOL in the aorta （P<0.05， P<0.01）. Compared with the model group， the positive drug and Renshentang at different doses alleviated AS， elevated the levels of HDL-C， TRPV1， LXR， and IDOL （P<0.05， P<0.01）， while lowering the levels of TC， TG， LDL-C， and LDLR （P<0.05， P<0.01）. ConclusionRenshentang has a lipid-lowering effect on AS mice. It can effectively reduce lipid deposition， lipid levels， and plaque area of AS mice by activating TRPV1 expression and regulating the LXR/IDOL/LDLR pathway.

ObjectiveTo explore the effects of Renshentang on atherosclerosis （AS） in mice based on the role of transient receptor potential vanilloid1 （TRPV1） in regulating cholesterol metabolism in foam cells. MethodsNine SPF-grade 8-week-old C57BL/6J mice were set as a normal group， and 60 ApoE^-/- mice were randomized into model， positive drug （simvastatin， 0.02 g·kg^-1·d^-1）， and low-， medium-， and high-dose （1.77， 3.54， 7.08 g·kg^-1·d^-1， respectively） Renshentang groups （n=12） according to body weight. The normal group was fed with a normal diet， and the other groups were fed with a high-fat diet and given corresponding drugs by oral gavage for the modeling of AS. The mice were administrated with corresponding drugs once a day for 12 weeks. After the last administration and fasting for 12 h， the aorta was collected. Plaque conditions， pathological changes， levels of total cholesterol （TC）， triglcerides （TG）， low-density lipoprotein-cholesterol （LDL-C）， and high-density lipoprotein-cholesterol （HDL-C）， and the expression of TRPV1， liver X receptor （LXR）， inducible degrader of the low-density lipoprotein receptor （IDOL）， and low-density lipoprotein receptor （LDLR） in the aortic tissue were observed and detected by gross oil red O staining， HE staining， Western blot， immunohistochemistry， and real-time PCR. ResultsCompared with the normal group， the model group presented obvious plaque deposition in the aorta， raised levels of TC， TG， and LDL-C in the serum （P<0.01）， up-regulated expression level of LDLR in the aorta （P<0.01）， lowered level of HDL-C in the serum， and down-regulated expression levels of TRPV1， LXR， and IDOL in the aorta （P<0.05， P<0.01）. Compared with the model group， the positive drug and Renshentang at different doses alleviated AS， elevated the levels of HDL-C， TRPV1， LXR， and IDOL （P<0.05， P<0.01）， while lowering the levels of TC， TG， LDL-C， and LDLR （P<0.05， P<0.01）. ConclusionRenshentang has a lipid-lowering effect on AS mice. It can effectively reduce lipid deposition， lipid levels， and plaque area of AS mice by activating TRPV1 expression and regulating the LXR/IDOL/LDLR pathway.

This paper explored the specific mechanism of ginsenoside Rg_1 in regulating mitochondrial fusion through the neurogenic gene Notch homologous protein 1(Notch1) pathway to alleviate hypoxia/reoxygenation(H/R) injury in HL-1 cells. The relative viability of HL-1 cells after six hours of hypoxia and two hours of reoxygenation was detected by cell counting kit-8(CCK-8). The lactate dehydrogenase(LDH) activity in the cell supernatant was detected by the lactate substrate method. The content of adenosine triphosphate(ATP) was detected by the luciferin method. Fluorescence probes were used to detect intracellular reactive oxygen species(Cyto-ROS) levels and mitochondrial membrane potential(ΔΨ_m). Mito-Tracker and Actin were co-imaged to detect the number of mitochondria in cells. Fluorescence quantitative polymerase chain reaction and Western blot were used to detect the mRNA and protein expression levels of Notch1, mitochondrial fusion protein 2(Mfn2), and mitochondrial fusion protein 1(Mfn1). The results showed that compared with that of the control group, the cell activity of the model group decreased, and the LDH released into the cell culture supernatant increased. The level of Cyto-ROS increased, and the content of ATP decreased. Compared with that of the model group, the cell activity of the ginsenoside Rg_1 group increased, and the LDH released into the cell culture supernatant decreased. The level of Cyto-ROS decreased, and the ATP content increased. Ginsenoside Rg_1 elevated ΔΨ_m and increased mitochondrial quantity in HL-1 cells with H/R injury and had good protection for mitochondria. After H/R injury, the mRNA and protein expression levels of Notch1 and Mfn1 decreased, while the mRNA and protein expression levels of Mfn2 increased. Ginsenoside Rg_1 increased the mRNA and protein levels of Notch1 and Mfn1, and decreased the mRNA and protein levels of Mfn2. Silencing Notch1 inhibited the action of ginsenoside Rg_1, decreased the mRNA and protein levels of Notch1 and Mfn1, and increased the mRNA and protein levels of Mfn2. In summary, ginsenoside Rg_1 regulated mitochondrial fusion through the Notch1 pathway to alleviate H/R injury in HL-1 cells.
Ginsenosides/pharmacology* ; Receptor, Notch1/genetics* ; Signal Transduction/drug effects* ; Mice ; Animals ; Mitochondrial Dynamics/drug effects* ; Mitochondria/metabolism* ; Cell Line ; Reactive Oxygen Species/metabolism* ; Oxygen/metabolism* ; Cell Hypoxia/drug effects* ; Cell Survival/drug effects* ; Membrane Potential, Mitochondrial/drug effects* ; Humans

PURPOSE: To investigate the protective effect of sub-hypothermic mechanical perfusion combined with membrane lung oxygenation on ischemic hypoxic injury of yorkshire brain tissue caused by traumatic blood loss. METHODS: This article performed a random controlled trial. Brain tissue of 7 yorkshire was selected and divided into the sub-low temperature anterograde machine perfusion group (n = 4) and the blank control group (n = 3) using the random number table method. A yorkshire model of brain tissue injury induced by traumatic blood loss was established. Firstly, the perfusion temperature and blood oxygen saturation were monitored in real-time during the perfusion process. The number of red blood cells, hemoglobin content, NA⁺, K⁺, and Ca²⁺ ions concentrations and pH of the perfusate were detected. Following perfusion, we specifically examined the parietal lobe to assess its water content. The prefrontal cortex and hippocampus were then dissected for histological evaluation, allowing us to investigate potential regional differences in tissue injury. The blank control group was sampled directly before perfusion. All statistical analyses and graphs were performed using GraphPad Prism 8.0 Student t-test. All tests were two-sided, and p value of less than 0.05 was considered to indicate statistical significance. RESULTS: The contents of red blood cells and hemoglobin during perfusion were maintained at normal levels but more red blood cells were destroyed 3 h after the perfusion. The blood oxygen saturation of the perfusion group was maintained at 95% - 98%. NA⁺ and K⁺ concentrations were normal most of the time during perfusion but increased significantly at about 4 h. The Ca²⁺ concentration remained within the normal range at each period. Glucose levels were slightly higher than the baseline level. The pH of the perfusion solution was slightly lower at the beginning of perfusion, and then gradually increased to the normal level. The water content of brain tissue in the sub-low and docile perfusion group was 78.95% ± 0.39%, which was significantly higher than that in the control group (75.27% ± 0.55%, t = 10.49, p < 0.001), and the difference was statistically significant. Compared with the blank control group, the structure and morphology of pyramidal neurons in the prefrontal cortex and CA1 region of the hippocampal gyrus were similar, and their integrity was better. The structural integrity of granulosa neurons was destroyed and cell edema increased in the perfusion group compared with the blank control group. Immunofluorescence staining for glail fibrillary acidic protein and Iba1, markers of glial cells, revealed well-preserved cell structures in the perfusion group. While there were indications of abnormal cellular activity, the analysis showed no significant difference in axon thickness or integrity compared to the 1-h blank control group. CONCLUSIONS Mild hypothermic machine perfusion can improve ischemia and hypoxia injury of yorkshire brain tissue caused by traumatic blood loss and delay the necrosis and apoptosis of yorkshire brain tissue by continuous oxygen supply, maintaining ion homeostasis and reducing tissue metabolism level.
Animals ; Perfusion/methods* ; Disease Models, Animal ; Brain Injuries/etiology* ; Swine ; Male ; Hypothermia, Induced/methods*

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a major health concern in northwest China; however, the impact of particulate matter (PM) exposure during sand-dust storms (SDS) remains poorly understood. Therefore, this study aimed to investigate the association between PM exposure on SDS days and COPD hospitalization risk in arid regions. METHODS: Data on daily COPD hospitalizations were collected from 323 hospitals from 2018 to 2022, along with the corresponding air pollutant and meteorological data for each city in Gansu Province. Employing a space-time-stratified case-crossover design and conditional Poisson regression, we analyzed 265,379 COPD hospitalizations. RESULTS: PM exposure during SDS days significantly increased COPD hospitalization risk [relative risk ( RR) for PM _2.5, lag 3:1.028, 95% confidence interval ( CI): 1.021-1.034], particularly among men and the elderly, and during the cold season. The burden of PM exposure on COPD hospitalization was substantially high in Northwest China, especially in the arid and semi-arid regions. CONCLUSION Our findings revealed a positive correlation between PM exposure during SDS episodes and elevated hospitalization rates for COPD in arid and semi-arid zones in China. This highlights the urgency of developing region-specific public health strategies to address adverse respiratory outcomes associated with SDS-related air quality deterioration.
Humans ; China/epidemiology* ; Pulmonary Disease, Chronic Obstructive/chemically induced* ; Particulate Matter/analysis* ; Hospitalization/statistics & numerical data* ; Male ; Female ; Middle Aged ; Aged ; Air Pollutants/analysis* ; Environmental Exposure/adverse effects* ; Spatio-Temporal Analysis ; Adult ; Sand ; Air Pollution

Objective:To evaluate the validity and reliability of the Chinese version of the Lubeck Alcohol Withdrawal Risk Scale(C-LARS).Methods:Referring to previous literature and clinical expert opinions using the Delphi method,a C-LARS was established through translation and back-translation.Principal component analysis was used to evaluate the structural validity of C-LARS,and the maximum variance method was used to calculate factors and factor loadings to evaluate the structural validity of C-LARS.The severity of alcohol withdrawal syn-drome in patients was evaluated using the the Alcohol Withdrawal Scale(AWS),and the criterion validity of C-LARS was evaluated by calculating the correlation coefficient between AWS and C-LARS.Results:The internal correlation coefficient(ICC)of the evaluation factors was 0.972,and the total Cronbach α coefficient was 0.938.Factor analysis and ROC analysis showed that a C-LARS score of ≥ 3 could predict the occurrence of mild alcohol withdrawal syndrome,with sensitivity and specificity of 0.945 and 0.899,respectively.The C-LARS scores of ≥ 5 could predict the occurrence of moderate alcohol withdrawal syndrome,with sensitivity and specificity of 0.910 and 0.905,respectively.The C-LARS scores of≥7 could predict the occurrence of severe alcohol with-drawal syndrome within 12 hours,the sensitivity and specificity were 0.990 and 0.877,respectively.Conclusion:The C-LARS has good validity and reliability,which could be used as a tool to assess the incidence and severity of alcohol withdrawal syndrome within 12 hours after visit.

To address the key challenges in multivariate statistical modeling,a higher-order derivative approach combined with vector space angle multiplicative error correction was proposed for establishing an acid value prediction ordinary least squares(OLS)regression model based on attenuated total reflectance-Fourier transform infrared(ATR-FTIR)spectroscopy.By using acid values measured by potentiometric titration as reference,ATR-FTIR spectroscopy was utilized for direct calibration and prediction of acid values on 96 kinds of lubricating oil samples from a wind turbine.Firstly,the simulated hyperbolic(SH)method was employed to obtain accurate fourth derivative spectrum,resolving overlapping bands and enhancing spectral selectivity.Then,from the calibration set(48 samples),informative spectral regions were identified based on correlation coefficients.Next,the sample with the highest acid value was selected as the reference and1/(1+tan(θ/2))was used as the metric relation of the spectrum to suppress the multiplicity error caused by factors such as the change of effective optical path in ATR-FTIR spectroscopy.After pretreatment of the spectrum by the method of fourth-order derivative combined with angular quantity,the number of variables decreased from 1737 to 8,and the matrix condition number decreased from 1.85×1015 to 56.34,which effectively eliminated the collinearity issue for OLS regression.Direct OLS modeling on spectral preprocessed data achieved a determination coefficient of 0.981 for 47 validation samples,with a relative error range of-8.38%-8.22%,outperforming the commonly used partial least squares(PLS)method(Determination coefficient of 0.865,relative error of-27.82%-22.38%).It was proved that effective data preprocessing significantly improved the prediction accuracy of the model.Furthermore,when the number of calibration set was compressed to 25 and the number of validation set was expanded to 70,the model retained 8 variables with a condition number of 42.60,the determination coefficient of validation set was 0.972,and the relative error ranged from-10.80%to 12.31%.Comparing with the PLS method(Determination coefficient of 0.724,relative error of-34.26%-53.84%),the improvement was more obvious,which showed that the method could still have high prediction accuracy even with fewer modeling samples as well as robustness against multiplicative error interference.

Objective:To construct a non-invasive pre-hospital screening model and early based on artificial intelligence algorithms to provide the severity of stroke in patients, provide screening, guidance and early warning for stroke patients and their families, and provide data support for clinical decision-making.Methods:A retrospective study was conducted. The clinical information of stroke patients ( n = 53?793) were extracted from the Yidu cloud big data server system of the Second Affiliated Hospital of Dalian Medical University from January 1, 2001 to July 31, 2023. Combined with the results of single factor screening and the opinions of experts with senior professional titles in neurology, the input variable was determined, and the output variable was the National Institutes of Health Stroke Scale (NIHSS) representing the severity of the disease at admission. Python 3.7 was used to build DeepFM algorithm model, and five data mining models including Logistic regression, CART decision tree, C5.0 decision tree, Bayesian network and deep neural network (DNN) were built at the same time. The original data were randomly divided into 80% training set and 20% test set, which were used to train and test the models, adjust the parameters of each model, respectively calculate the accuracy, sensitivity and F-index of the six models, carry out the comprehensive comparison and evaluation of the model. The receiver operator characteristic curve (ROC curve) and calibration curve were drawn, compared the prediction performance of DeepFM model and the other five algorithms. In addition, the data of stroke patients ( n = 1?028) were extracted from Dalian Central Hospital for external verification of the model. Results:A total of 14?015 stroke patients with complete information were selected, including 11?212 in the training set and 2?803 in the testing set. After univariate screening, 14 indicators were included to construct the model, including gender, age, recurrence, physical impairment, facial problems, speech disorders, head reactions, disturbance of consciousness, visual disorders, abnormal cough and swallowing, high risk factor, family history, smoking history and drinking history. DeepFM model adopted the two-order crossover feature. The number of hidden layers in DNN layer was 3. Dropout was used to discard the neurons in the neural network. Rule was used as the activation function. Each layer used Dense full connection. The objective function was random gradient descent. The number of iterations was 15. There were 133?922 training parameters in total. Comparing the predictive value of the six models showed that the accuracy of DeepFM model was 0.951, the sensitivity was 0.992, the specificity was 0.814, the F-index was 0.950, and the area under the curve (AUC) was 0.916. The accuracy of the other five data mining models were between 0.771-0.780, the sensitivity were between 0.978-0.987, the F-index were between 0.690-0.707, and the AUC were between 0.568-0.639. The calibration curve of the DeepFM model was more aligned with the ideal curve than the other five data mining models. Suggesting that the prediction performance of DeepFM model was the best. External validation was conducted on the DeepFM model, and its accuracy was 0.891, indicating good generalization performance of the model.Conclusion:The pre-hospital non-invasive screening prediction model based on DeepFM can accurately predict the severity grading of stroke patients, and has potential application value in rapid screening and early clinical decision-making of stroke.