Objective:To investigate the impact of early invasive arterial blood pressure (IBP) monitoring on survival and neurological outcomes in out-of-hospital cardiac arrest (OHCA) patients undergoing extracorporeal cardiopulmonary resuscitation (ECPR).Methods:This retrospective cohort study analyzed 44 OHCA patients receiving ECPR between January 2021 and January 2023. Patients were divided into: Early intervention group : IBP established within 3 min of ECMO initiation; Late intervention group : IBP established after ICU admission. Baseline characteristics, ECMO parameters, and clinical outcomes were compared. Multivariable logistic regression (adjusted for age, initial rhythm, etc.) and Spearman's correlation were used.Results:This study included a total of 44 patients treated with OHCA and ECPR, divided into an early intervention group of 23 cases and a late intervention group of 21 cases. The early intervention group showed significantly higher: Survival to discharge (43.5% vs. 9.5%, P<0.05), Good neurological recovery (CPC 1-2: 34.8% vs. 9.5%, P<0.05).Early intervention independently predicted survival (adjusted OR=18.84, 95% CI:1.97-179.98, P=0.01). Stratified analysis by pH (cutoff 7.0) demonstrated consistent benefits in both pH>7.0 ( aOR=0.392, 95% CI:0.106-0.678) and pH≤7.0 subgroups ( aOR=0.385, 95% CI: 0.075-0.695; interaction P=0.183). Early IBP positively correlated with CPC scores ( ρ=0.40, P=0.007). Conclusions:Early IBP monitoring significantly improves survival and neurological outcomes in OHCA-ECPR patients, supporting its integration into standardized protocols.

By systematically summarizing the basic situation of the Arctium lappa L.industry in our country,the strengths,weaknesses,opportunities,and threats(SWOT)analysis method,and the multi-expert review method were used to analyze,screen,and test the elements obtained.It is determined that the development of Arctium lappa L.industry should adopt the S-O strategy of relying on internal advantages to use external opportunities and judging from the orientation,the external opportunities are more pronounced,to take the opportunity of pioneering strategy.Based on utilizing external opportunities and exerting our advantages,we should adopt the strategy of product diversification,the strategy of expanding the international market,and the strategy of promoting science and technology to promote the efficient development of Arctium lappa L.industry.

Objective:To explore the application value of machine learning algorithms in constructing a predictive model for cardiovascular toxicity in breast cancer patients receiving anthracycline-based chemotherapy.Methods:This study was a retrospective cohort study. The female patients with breast cancer who received anthracyclines in the Affiliated Cancer Hospital of Xinjiang Medical University from January 2020 to December 2023 were enrolled. The endpoint event was abnormal electrocardiogram (ECG). According to whether the patients had ECG abnormalities during chemotherapy, they were divided into the ECG abnormal group and the ECG normal group. The dataset was divided into the training set and the test set at a ratio of 8∶2, and logistic regression, random forest, extreme gradient boosting (XGBoost), support vector machine (SVM) and multilayer perceptron (MLP) were used to construct a risk prediction model for cardiovascular toxicity in breast cancer patients, and the receiver operating characteristic curve, calibration curve and clinical decision curve were used to evaluate the model.Results:A total of 731 female patients with breast cancer, aged (51.6±9.4) years, were enrolled. The follow-up time was (130.3±37.1) days. There were 333 cases in the ECG abnormal group and 398 cases in the ECG normal group. Seven factors influencing cardiovascular toxicity were identified, including age, menstrual history, diabetes, combination therapy with trastuzumab, combination therapy with dexrazoxane, creatine kinase isoenzymes, and α-hydroxybutyrate dehydrogenase. In the training set, the area under the curve ( AUC) for the logistic regression, random forest, XGBoost, SVM, and MLP models was 0.712, 0.863, 0.774, 0.813, and 0.733, respectively. In the test set, the AUC was 0.671, 0.778, 0.746, 0.771, and 0.705, respectively. Calibration curves and clinical decision curves showed that the random forest model performed the best. Conclusion:Models constructed with machine learning algorithms show promise in predicting cardiovascular toxicity in breast cancer patients receiving anthracycline-based chemotherapy, with the random forest prediction model performing the best.

By systematically summarizing the basic situation of the Arctium lappa L.industry in our country,the strengths,weaknesses,opportunities,and threats(SWOT)analysis method,and the multi-expert review method were used to analyze,screen,and test the elements obtained.It is determined that the development of Arctium lappa L.industry should adopt the S-O strategy of relying on internal advantages to use external opportunities and judging from the orientation,the external opportunities are more pronounced,to take the opportunity of pioneering strategy.Based on utilizing external opportunities and exerting our advantages,we should adopt the strategy of product diversification,the strategy of expanding the international market,and the strategy of promoting science and technology to promote the efficient development of Arctium lappa L.industry.

Objective:To explore the application value of machine learning algorithms in constructing a predictive model for cardiovascular toxicity in breast cancer patients receiving anthracycline-based chemotherapy.Methods:This study was a retrospective cohort study. The female patients with breast cancer who received anthracyclines in the Affiliated Cancer Hospital of Xinjiang Medical University from January 2020 to December 2023 were enrolled. The endpoint event was abnormal electrocardiogram (ECG). According to whether the patients had ECG abnormalities during chemotherapy, they were divided into the ECG abnormal group and the ECG normal group. The dataset was divided into the training set and the test set at a ratio of 8∶2, and logistic regression, random forest, extreme gradient boosting (XGBoost), support vector machine (SVM) and multilayer perceptron (MLP) were used to construct a risk prediction model for cardiovascular toxicity in breast cancer patients, and the receiver operating characteristic curve, calibration curve and clinical decision curve were used to evaluate the model.Results:A total of 731 female patients with breast cancer, aged (51.6±9.4) years, were enrolled. The follow-up time was (130.3±37.1) days. There were 333 cases in the ECG abnormal group and 398 cases in the ECG normal group. Seven factors influencing cardiovascular toxicity were identified, including age, menstrual history, diabetes, combination therapy with trastuzumab, combination therapy with dexrazoxane, creatine kinase isoenzymes, and α-hydroxybutyrate dehydrogenase. In the training set, the area under the curve ( AUC) for the logistic regression, random forest, XGBoost, SVM, and MLP models was 0.712, 0.863, 0.774, 0.813, and 0.733, respectively. In the test set, the AUC was 0.671, 0.778, 0.746, 0.771, and 0.705, respectively. Calibration curves and clinical decision curves showed that the random forest model performed the best. Conclusion:Models constructed with machine learning algorithms show promise in predicting cardiovascular toxicity in breast cancer patients receiving anthracycline-based chemotherapy, with the random forest prediction model performing the best.

It is found that Jiangxi,as a province with large traditional Chinese medicine resources,has developed rapidly in the traditional Chinese medicine health industry in recent years,but there are still problems such as the uneven development degree of the health industry in various regions of the province,the imperfection of relevant policies,and the need to strengthen the training and introduction of talents.On the basis of an in-depth analysis of the development status of the traditional Chinese medicine and health industry in Jiangxi Province,it focuses on the following development strategies:deepening the reform of the traditional Chi-nese medicine and health industry system,integrating and developing the traditional Chinese medicine health industry chain with Ji-angxi characteristics with"heat-sensitive moxibustion"and"Xujiang medicine"as the core,improving the level of traditional Chinese medicine health services,and strengthening the cultivation of traditional Chinese medicine talents and international communi-cation.

An efficient vacuum suction system is a necessary prerequisite for the smooth operation of the oral diagnosis and treatment.During the use of the dental units,there is often a situation of vacuum suction weakness,resulting in the inability to discharge the mixture of blood,saliva,dental tissue and other mixtures in time,which affects the doctor's treatment field and increases the risk of aspiration pneumonia and cross-infection in patients.The working principle,pipeline system,filters and other aspects of the vacuum suction system that may affect the suction efficiency was analyzed.The causes and solutions of vacuum suction weakness were discussed,and operation suggestions were proposed to ensure the safe and effective use of equipment and ensure the safety of diagnosis and treatment.

Objective:To observe the effects of Huatan Quyu Decoction on the protein expressions of β-catenin and GSK-3 β and the expression of anticardiolipin antibody and β-amyloid protein related to cognitive function in rats with vascular dementia based on Wnt/β-catenin signal pathway.Methods:A total of 96 male SD rats were divided into blank group, model group, Donepezil hydrochloride group and Huatan Quyu Decoction low-, midium-, high-dosage group according to random number table method, with 16 rats in each group. Except for the blank group, the rat model of vascular dementia was prepared by modified 2-VO method. Huatan Quyu Decoction low-, medium- and high-dosage groups were administrated with Huatan Quyu Decoction 6.1, 12.1 and 24.2 g/kg, respectively; the Western medicine group was administrated with Donepezil hydrochloride 0.5 mg/kg; the blank group and the model group were administrated with the same amount of normal saline for 28 consecutive days. On the 1st, 7th, 14th and 28th day after administration, the learning and memory ability of rats was evaluated by Morris water maze test, the levels of ACA and Aβ in serum were measured by enzyme linked immunosorbent assay (ELISA), and the expressions of β-catenin and GSK-3β proteins related to Wnt/β-catenin signal pathway in hippocampus were measured by Western blot.Results:Compared with model group, the escape latency was shortened in the Huatan Quyu Decoction high-dosage group and Donepezil group on 7 and 14 days of administration ( P<0.05), and the times of crossing the platform increased in Huatan Quyu Decoction high-dosage group on 1 and 28 days of administration ( P<0.05). Compared with model group, the serum ACA level in Donepezil group, Huatan Quyu Decoction medium- and high-dosage groups decreased at day 1, 7, 14 and 28 after administration ( P<0.05). The serum Aβ level in Donepezil group, Huatan Quyu Decoction medium- and high-dosage groups decreased at 7, 14 and 28 days after administration ( P<0.05); On the 14th and 28th days after administration, the levels of ACA and Aβ in TCM low-dosage group decreased ( P<0.05). Compared with model group, the expression of β-catenin protein in hippocampus of Donepezil group and Huatan Quyu Decoction medium- and high-dosage groups increased ( P<0.05), while the expression of GSK-3β in hippocampus of Donepezil group and Huatan Quyu Decoction low-, medium- and high-dosage groups decreased ( P<0.01). Conclusion:Huatan Quyu Decoction can activate the Wnt/β-catenin signaling pathway, up-regulate the expression of β-catenin protein in hippocampal tissue of rats, inhibit the expression of GSK-3β, reduce the levels of ACA and Aβ in serum of rats, and improve the cognitive function of rats with vascular dementia.

To investigate the mechanism of the major capsid protein VP5 (encoded by the UL19 gene) of oncolytic herpes simplex virus type Ⅱ (oHSV2) in regulating the antitumor function of immune cells, we constructed a mouse breast cancer cell line 4T1-iRFP-VP5-GFP stably expressing VP5 protein, near-infrared fluorescent protein (iRFP), and green fluorescent protein (GFP) by using the PiggyBac transposon system. Flow cytometry and Western blotting were employed to screen the monoclonal cell lines expressing both GFP and VP5 and examine the expression stability of UL19 in the constructed cell line. The results of SYBR Green I real-time PCR and Western blotting showed that the copies of UL19 and the expression level of VP5 protein in the 15th passage of 4T1-iRFP-VP5-GFP cells were significantly higher than those in the 4T1 cells transiently transfected with UL19, demonstrating the stable insertion of UL19 into the 4T1 cell genome. The real-time cell analysis (RTCA) was employed to monitor the proliferation of 4T1-iRFP-VP5-GFP cells, which showed similar proliferation activity to their parental 4T1 cells. Further studies confirmed that NK92 cells exhibited stronger cytotoxicity against 4T1-iRFP-VP5-GFP cells than against 4T1 cells. This study layed a foundation for elucidating the role of VP5 protein in regulating immune cells, including T cells and NK cells, via HLA-E in 4T1 cells to exert the anti-tumor function.
Animals ; Mice ; DNA Transposable Elements/genetics* ; Cell Line, Tumor ; Capsid Proteins/biosynthesis* ; Transfection ; Green Fluorescent Proteins/metabolism* ; Oncolytic Viruses/genetics* ; Female ; Simplexvirus/genetics*

OBJECTIVE To develop an individualized medication list for elderly patients by evidence-based pharmacy method， and to support clinical decisions on rational use of METHODS　Firstly， drugs with risk genetic information were screened out by systematically reviewing evidence-based pharmacy information. Secondly， researchers investigated the included drugs in lists from different data E- sources. Drugs included in three or more data sources and drugs proposed by the expert committee were then included in the medication list. Thirdly， for the drugs included in two data sources， researchers designed questionnaires to investigate the necessity of drug-related gene testing. According to the scoring results of the expert questionnaire， drugs with higher scores were included in the list. Data sources included real-world data （list of high frequency medication in hospitals， high frequency medication for elderly outpatients and inpatients in National Health Care Claims Data， drugs related to frequent medication errors and so on） and evidence-based pharmacy evidence （the websites of Clinical Pharmacogenomics Implementation Consortium， Dutch Pharmacogenetics Working Group， Food and Drug Administration and so on）. RESULTS　The study obtain 68 drugs with risk genetic information which were included in three data sources. Combined with 23 drugs proposed by the expert committee， a list containing 74 drugs was preliminarily formed after de-duplication. A total of 37 drugs included in two databases with risk genetic information were scored through the questionnaire survey to form a supplementary list of 26 drugs. This is the final composition of the list of 100 drugs developed in this study. Among them， there are 43 drugs for the central nervous system， 15 drugs for the cardiovascular system， 12 anti-tumor drugs and so on. Twelve drugs were included in six or more data sources， which mainly consisted of drugs for digestive system， all proton pump inhibitors. CONCLUSION　In this study， a list of 100 commonly used drugs which require individualized medication for the elderly was developed by evidence-based pharmacy method. The drug list will be updated in time as available evidence changes， and can provide guidance for rational use of medicines for elderly patients.