OBJECTIVE: To investigate the effect of aquaporin 5 (AQP5) on Toll-like receptor 4 (TLR4)/myeloid differentiation factor 88 (MyD88)/nuclear factor κB (NF-κB) signaling pathway in Sjögren syndrome (SS) rats. METHODS: The SS gene expression data sets GSE406611 and GSE84844 were extracted from the Gene Expression Omnibus (GEO), and the AQP5 mRNA expression was analyzed by R software. The rat SS model was constructed. The successfully modeled rats were divided into SS group, SS+NC group, and SS+pc group, 10 rats in each group; and 10 rats were set as Normal group. The rats in the SS+NC group were injected with 10 μg of rno-pcDNA3.1-AQP5-NC at the submandibular gland, subcutaneously every day for 28 days. The rats in the SS+pc group were injected with 10 μg of rno-pcDNA3.1-AQP5 at the submandibular gland, subcutaneously every day for 28 days. The enzyme-linked immunosorbent assay (ELISA) kit was used to detect the content of tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) in the serum. High-throughput sequencing was used to identify the target genes. Quantitative real-time PCR (qPCR) and Western blot were used to detect the mRNA and protein expressions of AQP5, TLR4, MyD88, and NF-κB in the rat submandibular gland tissue. RESULTS: In the SS dataset GSE406611 and GSE84844, the mRNA expression of AQP5 in SS was significantly reduced. Compared with the Normal group, the content of TNF-α and IL-1β in the serum, the mRNA and protein expressions of TLR4, MyD88, and NF-κB in the SS group were significantly increased, the mRNA and protein expressions of AQP5 were significantly decreased. After overexpression of AQP5, the content of TNF-α and IL-1β in the serum, the mRNA and protein expressions of TLR4, MyD88, and NF-κB in the SS+pc group were significantly decreased, the mRNA and protein expressions of AQP5 were significantly increased. The differences were statistically significant (all P < 0.05). CONCLUSION The expression of AQP5 is involved in the progression of SS. Increasing the expression of AQP5 can significantly inhibit inflammatory stress and reduce the pathological damage of submandibular gland tissue. This may be related to the inhibition of TLR4/MyD88/NF-κB conduction.
Animals ; Toll-Like Receptor 4/genetics* ; Myeloid Differentiation Factor 88/genetics* ; Aquaporin 5/metabolism* ; Sjogren's Syndrome/genetics* ; Signal Transduction ; NF-kappa B/metabolism* ; Rats ; Rats, Sprague-Dawley ; Interleukin-1beta/metabolism* ; Female

Objective:To predict the risk of cryptogenic stroke (CS) patients with right-to-left shunt (RLS) by machine learning, and provide potential solutions for accurate and efficient prediction of CS.Methods:A retrospective analysis of clinical data on 289 subjects with positive RLS detected by contrast-enhanced transcranial Doppler tests (c-TCD) treated in the Department of Neurology at Laoshan Campus, the Affiliated Hospital of Qingdao University, from January 2018 to September 2023, including demographic information, medical history, laboratory test indicators, diagnosis, and treatment.The dataset was randomly divided into a training set and a testing set by the machine learning function train_test_split(), with a ratio of 8∶2.Risk prediction models for CS in RLS subjects were constructed by algorithms such as Logistic regression, decision trees, random forests, extreme gradient boosting, artificial neural networks, gradient boosting, extra trees, and adaptive Boosting.The model performance was evaluated by receiver operating characteristic curves (ROC), area under curve (AUC), confusion matrix, precision, recall, accuracy, F1 score, calibration curves, and decision curve analysis.The optimal model was subjected to interpretability analysis by feature importance and SHAP values.The t-test, Mann-Whitney U test and χ2 test were used for data analysis by SPSS 25.0 software.Delong test was used to compare the differences in AUC between the two models. Results:In 289 RLS subjects, there were 166 cases of CS (57.5%) and 123 cases of non-CS (42.5%).The statistical analysis results showed that blood biochemical indicators such as D-dimer, mean platelet volume, and fibrinogen in CS patients were higher than those in non-CS patients (all P<0.01).There were no statistically significant differences in variables between the training and testing sets(all P>0.05).Random forest model achieved the highest AUC (0.885), precision (0.806), recall (0.879), accuracy (0.810), and F1 score (0.841) for CS risk prediction in the testing set.The calibration curve showed that the random forest model was closest to the reference line, and the decision curve analysis indicated that it had a greater net benefit.The interpretability analysis revealed that high-risk factors included mean platelet volume, D-dimer, international normalized ratio, body mass index, and age. Conclusion:The random forest-based prediction tool exhibits excellent performance, demonstrating high accuracy in predicting CS risk in RLS population.

Objective To construct and apply a management plan for microaspiration of oropharyngeal secretions in ICU intubated patients.Methods Based on evidence summaries and expert consultation,a management plan for microaspiration of oropharyngeal secretions in ICU intubated patients was constructed,consisting of 19 items covering 7 aspects including identification of risk factors,position management,tube and cuff selection,cuff management,mechanical ventilation management,pain and sedation management,removal of oropharyngeal and subglottic secretions,and oral care.Convenience sampling was used to select 141 ICU intubated patients from a tertiary A comprehensive hospital in Suzhou from June,2022 to September,2023.Patients were divided into an experimental group(n=72)and a control group(n=69)according to the wards.The experimental group received the management plan for microaspiration of oropharyngeal secretions in ICU intubated patients.The control group received the nursing bundle for ventilator associated pneumonia(VAP).The incidence and time from intubation to microaspiration and VAP,duration of mechanical ventilation,ICU length of stay,and disease outcome were compared between the 2 groups.Results The incidence of microaspiration of oropharyngeal secretions,the duration of mechanical ventilation,time from intubation to microaspiration showed significant differences between the 2 groups(P<0.05).There were no significant differences in the incidence of ventilator associated pneumonia,ICU length of stay,and disease outcome between the 2 groups(P>0.05).The time from intubation to VAP in the experimental group was 7.5 days,and that in the control group was 3.8 days.Conclusion The application of the management plan for microaspiration of orophaiyngeal secretions in ICU intubated patients is beneficial for reducing the incidence of microaspiration,delaying the time from intubation to microaspiration and VAP,and shortening the duration of mechanical ventilation.

Objective:To study the efficacy of bisoprolol fumarate tablets combined with tiotropium bromide powder aerosol inhalation in the treatment of acute exacerbation of chronic obstructive pulmonary disease (AECOPD) complicated with pulmonary heart disease and its effect on high-sensitivity C-reactive protein (hs-CRP) and brain natriuretic peptide (BNP).Methods:From June 2016 to October 2021, 96 patients with AECOPD complicated with pulmonary heart disease admitted to the Affiliated Hospital of Jining Medical University were randomly divided into a control group and an observation group with 48 patients in each group. The patients in both groups were treated with oxygen inhalation, expectorant, cough relieving, asthma relieving and empirical antibiotics. The control group was treated with atomized inhalation of tiotropium bromide powder, and the observation group was treated with bisoprolol fumarate tablets on the basis of the control group. The left ventricular ejection fraction (LVEF), 6-minute walking distance (6MWD), 1 s forced expiratory volume (FEV 1), forced vital capacity (FVC), serum hs-CRP, BNP and other factors were compared between the two groups after treatment, and the total effective rate and adverse drug reaction of the two groups were counted. Results:After treatment, the total effective rates of the observation group and the control group were 91.67%(44/48) and 77.08%(37/48), respectively, with a statistically significant difference ( P<0.05). After treatment, the LVEF of the observation group and the control group were (43.15±6.04)% and (38.96±5.67)% respectively, the 6MWD was (294.86±30.11)m and (261.35±25.88)m, the FEV 1 was (2.36±0.69)L and (1.75±0.52)L, the FVC was (3.58±0.51)L and (2.96±0.45)L, the hs-CRP was (4.47±1.25)mg/L and (7.86±2.01)mg/L, and the BNP was (418.25±32.25)ng/ml and (496.52±43.21)ng/ml; ESR was (16.78±2.11)mm/h and (21.02±1.69)mm/h, ET-1 was (54.26±6.45)ng/ml and (73.21±8.24)ng/ml, and Interleukin 6 was (22.63±8.45)ng/L and (31.85±12.24)ng/L, respectively, with statistical significance ( P<0.05). The total incidence of adverse drug reaction in the observation group and the control group was 8.33%(4/48) and 4.17%(2/48), respectively, with no statistically significant difference ( P>0.05). Conclusions:Bisoprolol fumarate tablets combined with tiotropium bromide powder aerosol inhalation in the treatment of AECOPD complicated with cor pulmonale can improve the heart and lung function of patients, regulate the expression level of hs-CRP, BNP and other factors, improve the efficacy, and do not increase adverse reactions.

ObjectiveThis study aimed to investigate the HIV genotypic subtypes and molecular transmission clusters among men who have sex with men （MSM） with newly reported HIV infections in Dehong Dai and Jingpo Autonomous Prefecture （Dehong Prefecture）， Yunnan Province， China， between 2010 and 2019. The study aimed to identify potential high-risk transmitters and provide reference data for screening， management， and intervention of infection sources. MethodsPlasma samples from newly reported HIV-positive MSM individuals in Dehong Prefecture between 2010 and 2019 were collected. The viral pol gene fragments were amplified， sequenced， and genotyped. Genetic distances （GD） between pairwise sequences were analyzed and calculated. MEGA 7.0 and Gephi were used for phylogenetic and molecular transmission network analysis. ResultsA total of 159 newly reported HIV infections among MSM were included in the study， with successful genotyping of 100 cases. Nine HIV-1 subtypes were identified， with the most prevalent being CRF01_AE subtype （52%）， followed by CRF07_BC subtype （31%）， CRF55_01B subtype （10%）， and others （7%）. Cluster analysis revealed a total network access rate of 67%， forming three transmission clusters. CRF01_AE subtype formed two transmission clusters with 38 and 3 infected individuals， while CRF07_BC subtypes formed one transmission cluster with 26 infected individuals. The transmission network within the CRF01_AE clusters exhibited a more complex relationship. Significant differences in educational level were observed between the two main transmission clusters. ConclusionThe predominant HIV subtypes among newly reported MSM cases in Dehong Prefecture between 2010 and 2019 were CRF01_AE and CRF07_BC. Significant cultural differences are observed between the main transmission clusters. Continued monitoring of genotypic subtypes and targeted interventions within transmission clusters are warranted.

OBJECTIVE: To analyze the risk factors of in-hospital death in patients with sepsis in the intensive care unit (ICU) based on machine learning, and to construct a predictive model, and to explore the predictive value of the predictive model. METHODS: The clinical data of patients with sepsis who were hospitalized in the ICU of the Affiliated Hospital of Jining Medical University from April 2015 to April 2021 were retrospectively analyzed,including demographic information, vital signs, complications, laboratory examination indicators, diagnosis, treatment, etc. Patients were divided into death group and survival group according to whether in-hospital death occurred. The cases in the dataset (70%) were randomly selected as the training set for building the model, and the remaining 30% of the cases were used as the validation set. Based on seven machine learning models including logistic regression (LR), K-nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), random forest (RF), extreme gradient boosting (XGBoost) and artificial neural network (ANN), a prediction model for in-hospital mortality of sepsis patients was constructed. The receiver operator characteristic curve (ROC curve), calibration curve and decision curve analysis (DCA) were used to evaluate the predictive performance of the seven models from the aspects of identification, calibration and clinical application, respectively. In addition, the predictive model based on machine learning was compared with the sequential organ failure assessment (SOFA) and acute physiology and chronic health evaluation II (APACHE II) models. RESULTS: A total of 741 patients with sepsis were included, of which 390 were discharged after improvement, 351 died in hospital, and the in-hospital mortality was 47.4%. There were significant differences in gender, age, APACHE II score, SOFA score, Glasgow coma score (GCS), heart rate, oxygen index (PaO₂/FiO₂), mechanical ventilation ratio, mechanical ventilation time, proportion of norepinephrine (NE) used, maximum NE, lactic acid (Lac), activated partial thromboplastin time (APTT), albumin (ALB), serum creatinine (SCr), blood urea nitrogen (BUN), blood uric acid (BUA), pH value, base excess (BE), and K⁺ between the death group and the survival group. ROC curve analysis showed that the area under the curve (AUC) of RF, XGBoost, LR, ANN, DT, SVM, KNN models, SOFA score, and APACHE II score for predicting in-hospital mortality of sepsis patients were 0.871, 0.846, 0.751, 0.747, 0.677, 0.657, 0.555, 0.749 and 0.760, respectively. Among all the models, the RF model had the highest precision (0.750), accuracy (0.785), recall (0.773), and F1 score (0.761), and best discrimination. The calibration curve showed that the RF model performed best among the seven machine learning models. DCA curve showed that the RF model exhibited greater net benefit as well as threshold probability compared to other models, indicating that the RF model was the best model with good clinical utility. CONCLUSIONS The machine learning model can be used as a reliable tool for predicting in-hospital mortality in sepsis patients. RF models has the best predictive performance, which is helpful for clinicians to identify high-risk patients and implement early intervention to reduce mortality.
Humans ; Hospital Mortality ; Retrospective Studies ; ROC Curve ; Prognosis ; Sepsis/diagnosis* ; Intensive Care Units

Objective:To analyze the risk factors of acute kidney injury (AKI) in patients with septic shock in intensive care unit (ICU), construct a predictive model, and explore the predictive value of the predictive model.Methods:The clinical data of patients with septic shock who were hospitalized in the ICU of the Affiliated Hospital of Jining Medical College from April 2015 to June 2019 were retrospectively analyzed. According to whether the patients had AKI within 7 days of admission to the ICU, they were divided into AKI group and non-AKI group. 70% of the cases were randomly selected as the training set for building the model, and the remaining 30% of the cases were used as the validation set. XGBoost model was used to integrate relevant parameters to predict the risk of AKI in patients with septic shock. The predictive ability was assessed through receiver operator characteristic curve (ROC curve), and was correlated with acute physiology and chronic health evaluationⅡ(APACHEⅡ), sequential organ failure assessment (SOFA), procalcitonin (PCT) and other comparative verification models to verify the predictive value.Results:A total of 303 patients with septic shock were enrolled, including 153 patients with AKI and 150 patients without AKI. The incidence of AKI was 50.50%. Compared with the non-AKI group, the AKI group had higher APACHEⅡscore, SOFA score and blood lactate (Lac), higher dose of norepinephrine (NE), higher proportion of mechanical ventilation, and tachycardiac. In the XGBoost prediction model of AKI risk in septic shock patients, the top 10 features were serum creatinine (SCr) level at ICU admission, NE use, drinking history, albumin, serum sodium, C-reactive protein (CRP), Lac, body mass index (BMI), platelet count (PLT), and blood urea nitrogen (BUN) levels. Area under the ROC curve (AUC) of the XGBoost model for predicting the risk of AKI in patients with septic shock was 0.816, with a sensitivity of 73.3%, a specificity of 71.7%, and an accuracy of 72.5%. Compared with the APACHEⅡscore, SOFA score and PCT, the performance of the model improved significantly. The calibration curve of the model showed that the goodness of fit of the XGBoost model was higher than the other scores (the calibration curve had the lowest score, with a score of 0.205).Conclusion:Compared with the commonly used clinical scores, the XGBoost model can more accurately predict the risk of AKI in patients with septic shock, which helps to make appropriate diagnosis, treatment and follow-up strategies while predicting the prognosis of patients.

ObjectiveTo determine the trend and influencing factors of HIV subtypes in newly reported HIV/AIDS cases in Dehong Dai and Jingpo Autonomous Prefecture （Dehong Prefecture） from 2017 to 2019. MethodsRNA extraction was conducted among newly reported HIV/AIDS cases in Dehong Prefecture from 2017 to 2019 whose plasma volume was more than 200 μL. The gag， env and pol genes were amplified by using RT-PCR and then sequenced to determine the subtypes. ResultsA total of 3 287 HIV-infected cases were newly reported in Dehong from 2017 to 2019. The HIV gag， env and pol genotypes were determined in 1 813 cases. The major subtypes were subtype C （28.4%，515/1 813）， recombination form BC （22.0%，398/1 813） and CRF_01AE （18.1%，329/1 813）. Furthermore， the proportion of subtype B， subtype C and CRF01_AE decreased over years， whereas 01/BC， CRF07_BC and CRF08_BC increased over years in both Chinese and Burmese patients （χ²=75.212，P<0.001）. There were significant differences in gender， age， marital status， ethnicity， educational level and transmission route among Chinese and Burmese HIV-infected cases with diverse HIV genotypes （all P<0.05）. ConclusionHIV subtypes in Dehong change over time， which demonstrates that the proportion of BC recombinant subtypes and unique recombinant subtypes increased significantly.

Objective:To understand the epidemiological characteristics of brucellosis in non-occupational population reported in Hangzhou, and provide basis for diagnosis and further prevention and control of brucellosis in non-occupational population.Methods:The basic information, epidemiological characteristics, clinical characteristics and laboratory test data of brucellosis patients reported in Hangzhou from 2008 to 2019 were collected retrospectively. The data were obtained from the case questionnaire of confirmed brucellosis and annual report of brucellosis prevention and control work of Hangzhou Center for Disease Control and Prevention over the years. The epidemiological characteristics, clinical characteristics and diagnosis of brucellosis in non-occupational population were analyzed.Results:From 2008 to 2019, 76 cases of brucellosis in non-occupational population were reported in Hangzhou, accounting for 34.23% (76/222) of the total reported brucellosis cases. In the 76 cases of brucellosis in non-occupational population, there were 47 males and 29 females, the ratio of male to female was 1.62∶1.00; the age was (47.37 ± 16.04) years old, ranging from 6 to 84 years old. The peak incidence of brucellosis in non-occupational population was from March to May, accounting for 59.21% (45/76); the main routes of infection were direct contact and digestive tract, accounting for 80.26% (61/76). The main clinical symptoms were fever (100.00%, 76/76), hyperhidrosis (73.68%, 56/76) and muscle and joint pain (69.74%, 53/76); the diagnosis time was 27 (14, 49) d, and the longest diagnosis time was 190 d. Among them, 39 cases were misdiagnosed, accounting for 51.32% (39/76). Sixty suspected Brucella strains were identified by routine culture of automatic blood culture apparatus in hospital laboratory, and 54 strains of Brucella melitensis were identified by typing, with a coincidence rate of 90.00%. The blood culture rate of patients from 2015 to 2019 (88.46%, 46/52) was significantly higher than that from 2008 to 2014 (58.33%, 14/24), the difference was statistically significant (χ 2=8.968, P < 0.05). Conclusions:From 2008 to 2019, the onset of brucellosis in non-occupational population is seasonal in Hangzhou, the infection mode is diverse, the clinical symptoms are not typical, and it is easy to be misdiagnosed. Blood culture for suspected brucellosis patients in high incidence season is conducive to the early diagnosis of brucellosis.

Objective:To investigate the effect of Relative Bedrest Condition Morita Therapy(RBCMT) on the improvement of depression and anxiety symptoms and personality in patients with recurrent depression disorder.Methods:Seventy patients with recurrent depressive disorder hospitalized in Kailuan Mental Health Center were randomly divided into study group and control group( n=35 in each group) from June to October, 2019.The study group was given RBCMT on the basis of conventional treatment and nursing.The Eysenck personality questionnaire (EPQ), Hamilton depression scale (HAMD) and Hamilton anxiety scale (HAMA) were used to assess the clinical symptoms and personality characteristics of the patients and to analyze and compare them. Results:(1) EPQ score in each dimension: There were significant differences within group among different time in introverted and extroverted dimension (study group: baseline: 46.14±10.99, the fifth weekend: 50.43±8.86, the eighth weekend: 53.86±7.08, F=6.291, P=0.003.Control group: baseline: 45.29±8.99, the fifth weekend: 48.29±8.31, the eighth weekend: 50.29±7.57, F=3.211, P=0.044) and neuroticism dimension score (study group: baseline: 60.14±5.49, the fifth weekend: 53.29±4.53, the eighth weekend: 50.57±4.33, F=36.809, P<0.001.Control group: baseline: 60.29±6.18, the fifth weekend: 55.86±6.00, the eighth weekend: 53.14±5.30, F=13.353, P<0.001) among different time points in the group.Neuroticism scores between the two groups at the same time were statistically significant(the fifth weekend: F=4.095, P=0.047, the eighth weekend: F=4.940, P=0.030). After 8 weeks of inclusion, there was a statistically significant difference between the two groups in the score of introverted and extroverted dimension ( F=4.157, P=0.045). There was no significant difference in the score of spiritual quality dimension at different time within the group or at the same time point between the groups.(2)HAMD score: There were statistically significant differences within group among different time(study group: baseline: 32.00±4.04, the fifth weekend: 15.23±5.01, the eighth weekend: 9.31±3.15, F=282.376, P<0.001.Control group: baseline: 31.91±4.59, the fifth weekend: 17.86±5.11, the eighth weekend: 11.17±3.64, F=195.019, P<0.001), and the differences between the two groups at the same time were statistically significant (the fifth weekend: F=4.724, P=0.033, the eighth weekend: F=5.205, P=0.026). (3)HAMA score: There were statistically significant differences within group among different time(study group: baseline: 18.69±8.87, the fifth weekend: 10.34±5.34, the eighth weekend: 7.97±2.98, F=28.679, P<0.001.Control group: baseline: 18.60±8.02, the fifth weekend: 13.31±6.35, the eighth weekend: 10.37±4.86, F=14.241, P<0.001). The difference between the two groups at the same time point was statistically significant (the fifth weekend: F=4.161, P=0.045, the eighth weekend: F=8.315, P=005). (4)Multiple linear regression results indicated that RBCMT ( β=-0.312, t=-2.360, P=0.022) and introverted and extroverted dimension personality ( β=-0.334, t=-2.355, P=0.022) were the influencing factors of HAMA. Conclusion:Compared with the conventional treatment, the Relative Bedrest Condition Morita Therapy can reduce the anxiety symptoms and improve the depressive symptoms by enhancing the extraversion personality characteristics of the patients.