Objective:To construct logistic regression, decision tree, and neural network models to predict pressure injury in neurocritically ill patients using machine learning algorithms, and compare the predictive performance of the three models.Methods:The clinical data of 341 neurocritically ill patients who received treatment in the Department of Neurosurgery at The First Affiliated Hospital of Wenzhou Medical University from May 2020 to February 2023 were collected retrospectively. The patients were randomly divided into a training set and a testing set in a 7:3 ratio. Univariate and multivariate analyses were conducted based on the clinical data from the training set. According to the results of the multivariate analysis, logistic regression, decision tree, and neural network models were constructed. The predictive performance of the three models was validated and compared using receiver operating characteristic curve analysis.Results:Among the 341 patients, 35 developed pressure injury (a total of 40 occurrences), with an incidence rate of 10.26%. Multivariate analysis indicated that incontinence ( OR = 47.32, 95% CI: 1.360-1 647.700), decreased albumin levels ( OR = 0.56, 95% CI: 0.360-0.870), increased sensory ability ( OR = 0.00, 95% CI: 0.000-0.190), and increased mobility ( OR = 0.03, 95% CI: 0.000-0.390) were independent risk factors for pressure injury in neurocritically ill patients (all P < 0.05). Based on these independent risk factors, logistic regression, decision tree, and neural network models were constructed. Receiver operating characteristic curve analysis revealed that the area under the curve for the three models was 0.987 (95% CI: 0.941-0.999), 0.945 (95% CI: 0.881-0.980), and 0.908 (95% CI: 0.834-0.956), respectively. These results suggest that all three models exhibited high predictive performance for pressure injury in neurocritically ill patients, with the logistic regression model showing a significantly greater area under the curve than the neural network model. Conclusions:The occurrence of pressure injury in neurocritically ill patients is closely related to incontinence, albumin levels, sensory ability, and mobility. Constructing predictive models using machine learning algorithms can provide valuable insights for the early prevention and management of pressure injury in neurocritically ill patients.

Neuropsychiatric disorders arise from complex interactions between genetic and environmental factors. DNA methylation, a reversible and environmentally responsive epigenetic regulatory mechanism, serves as a crucial bridge linking environmental exposure, gene expression regulation, and neurobehavioral outcomes. During long-duration deep-space missions, astronauts face multiple stressors-including microgravity, cosmic radiation, circadian rhythm disruption, and social isolation, which can induce alterations in DNA methylation and increase the risk of neuropsychiatric disorders. Genome-wide DNA methylation research can be divided into 3 major methodological stages: Study design, sample preparation and detection, and data analysis, each of which can be applied to astronaut neuropsychiatric health monitoring. Systematic comparison of the Illumina MethylationEPIC array and whole-genome bisulfite sequencing reveals their complementary strengths in terms of genomic coverage, resolution, cost, and application scenarios: the array method is cost-effective and suitable for large-scale population studies and longitudinal monitoring, whereas sequencing provides higher resolution and coverage and is more suitable for constructing detailed methylation maps and characterizing individual variation. Furthermore, emerging technologies such as single-cell methylation sequencing, nanopore long-read sequencing, and machine-learning-based multi-omics integration are expected to greatly enhance the precision and interpretability of epigenetic studies. These methodological advances provide key support for establishing DNA-methylation-based monitoring systems for neuropsychiatric risk in astronauts and lay an epigenetic foundation for safeguarding neuropsychiatric health during future long-term deep-space missions.
DNA Methylation ; Humans ; Space Flight ; Mental Disorders/genetics* ; Epigenesis, Genetic ; Astronauts/psychology* ; Weightlessness/adverse effects* ; Epigenomics

This article summarized the clinical experience of Yan Dexin,a master of traditional Chinese medicine,in differentiating and treating abdominal distention,in terms of its pathogenesis,therapeutic principles,differentiation of syndrome types and treatment.Master Yan believes that the pathogenesis of abdominal distention is characterized by deficiency in origin and excess in superficiality.Its fundamental pathogenesis is due to the dysfunction of liver,spleen and kidney,which results into the accumulation of qi stagnation,blood stasis,and fluid retention in the abdomen.The syndrome differentiation of abdominal distention can be mainly categorized into damp-heat accumulation type,cold-damp retention and accumulation type,and internal obstruction of stasis and stagnation type.The therapeutic principle is to warm kidney yang for the recovery of qi transformation,invigorate middle energizer and promoting qi movement.For the treatment of abdominal distention of damp-heat accumulation syndrome type,therapies of clearing heat and draining dampness,suppressing the liver and strengthening the spleen are suggested;for the treatment of abdominal distention of cold-damp retention and accumulation type,therapies of mediating middle-yang and eliminating cold-damp can be adopted;for the treatment of abdominal distention of internal obstruction of stasis and stagnation type,therapies of activating blood to remove stasis,unblocking the collaterals and dissipating mass are recommended.A proven medical case was presented for the analysis of the inspiration of Master Yan's thinking on the treatment of abdominal distention.

Objective:To analyze the clinical characteristics and related factors of cognition disorders in elderly hypertensive patients.Methods:It was a cross-sectional study. A total of 612 hypertensive patients with the age of (69.06±6.58) years (median 68.00 years) admitted in the Department of Cardiology, General Hospital of Chinese People′s Liberation Army from October 2022 to April 2024 were enrolled. The demographic and clinical data were collected, the cognition status was assessed with Mini-Mental State Examination (MMSE) at admission. The related factors of cognition disorders were analyzed with univariate and multivariate logistic regression.Results:The results showed that female hypertensive patients and those with older age, lower education, higher fasting blood glucose (FBG) and diabetes mellitus, higher low-density lipoprotein cholesterol (LDL-C) level, higher systolic blood pressure (SBP) and more cardiovascular comorbidities were likely to have cognition disorders (all P<0.05). Multivariate logistic regression analysis showed that smoking history, elevated SBP, elevated heart rate, elevated FBG, and elevated LDL-C were independent risk factors for cognition disorders in elderly hypertensive patients,while higher education level was an independent protective factor (all P<0.05). Conclusion:Smoking, increased SBP, increased heart rate, increased FBG, increased LDL-C and lower education level are independently associated with cognition disorders in elderly hypertensive patients.

Objective:To construct logistic regression, decision tree, and neural network models to predict pressure injury in neurocritically ill patients using machine learning algorithms, and compare the predictive performance of the three models.Methods:The clinical data of 341 neurocritically ill patients who received treatment in the Department of Neurosurgery at The First Affiliated Hospital of Wenzhou Medical University from May 2020 to February 2023 were collected retrospectively. The patients were randomly divided into a training set and a testing set in a 7:3 ratio. Univariate and multivariate analyses were conducted based on the clinical data from the training set. According to the results of the multivariate analysis, logistic regression, decision tree, and neural network models were constructed. The predictive performance of the three models was validated and compared using receiver operating characteristic curve analysis.Results:Among the 341 patients, 35 developed pressure injury (a total of 40 occurrences), with an incidence rate of 10.26%. Multivariate analysis indicated that incontinence ( OR = 47.32, 95% CI: 1.360-1 647.700), decreased albumin levels ( OR = 0.56, 95% CI: 0.360-0.870), increased sensory ability ( OR = 0.00, 95% CI: 0.000-0.190), and increased mobility ( OR = 0.03, 95% CI: 0.000-0.390) were independent risk factors for pressure injury in neurocritically ill patients (all P < 0.05). Based on these independent risk factors, logistic regression, decision tree, and neural network models were constructed. Receiver operating characteristic curve analysis revealed that the area under the curve for the three models was 0.987 (95% CI: 0.941-0.999), 0.945 (95% CI: 0.881-0.980), and 0.908 (95% CI: 0.834-0.956), respectively. These results suggest that all three models exhibited high predictive performance for pressure injury in neurocritically ill patients, with the logistic regression model showing a significantly greater area under the curve than the neural network model. Conclusions:The occurrence of pressure injury in neurocritically ill patients is closely related to incontinence, albumin levels, sensory ability, and mobility. Constructing predictive models using machine learning algorithms can provide valuable insights for the early prevention and management of pressure injury in neurocritically ill patients.

Objective:To analyze the clinical characteristics and related factors of cognition disorders in elderly hypertensive patients.Methods:It was a cross-sectional study. A total of 612 hypertensive patients with the age of (69.06±6.58) years (median 68.00 years) admitted in the Department of Cardiology, General Hospital of Chinese People′s Liberation Army from October 2022 to April 2024 were enrolled. The demographic and clinical data were collected, the cognition status was assessed with Mini-Mental State Examination (MMSE) at admission. The related factors of cognition disorders were analyzed with univariate and multivariate logistic regression.Results:The results showed that female hypertensive patients and those with older age, lower education, higher fasting blood glucose (FBG) and diabetes mellitus, higher low-density lipoprotein cholesterol (LDL-C) level, higher systolic blood pressure (SBP) and more cardiovascular comorbidities were likely to have cognition disorders (all P<0.05). Multivariate logistic regression analysis showed that smoking history, elevated SBP, elevated heart rate, elevated FBG, and elevated LDL-C were independent risk factors for cognition disorders in elderly hypertensive patients,while higher education level was an independent protective factor (all P<0.05). Conclusion:Smoking, increased SBP, increased heart rate, increased FBG, increased LDL-C and lower education level are independently associated with cognition disorders in elderly hypertensive patients.

Lung cancer is considered as the leading cause of cancer-related mortality worldwide. Non-small cell lung cancer (NSCLC) accounts for about 85% of primary lung cancer. Owing to the improved utilization of medical technological level and the popularization of health examinations, the detection rate of early-stage NSCLC is gradually increasing. The main treatment modalities for early-stage NSCLC are surgical resection and adjuvant chemotherapy. Platinum-based chemotherapy is recommended as the standard postoperative adjuvant treatment for patients with completely resected stageⅡ-ⅢA NSCLC. However, adjuvant therapy remains a controversial option in stageⅠB NSCLC. This review focuses on postoperative adjuvant therapy such as adjuvant chemotherapy, targeted therapy, and immunotherapy for completely resected stageⅠB NSCLC. Moreover, the biomarkers and prognostic factors of high-risk patients are discussed.

Objective:To evaluate the relationship between mitochondrial calcium uniporter protein (MCU)-mediated mitochondrial dynamics and intestinal ischemia-reperfusion (I/R) injury in mice.Methods:Twenty-four wild-type adult male C57BL/6J mice, aged 6-8 weeks, weighing 18-20 g, were divided into 4 groups ( n=6 each) using a random number table method: sham operation group (S group), intestinal I/R group (IIR group), sham operation+ MCU inhibitor Ru360 group (S+ Ru360 group) and intestinal I/R + Ru360 group (IIR+ Ru360 group). The mouse model of intestinal I/R injury was prepared by clamping the root of the superior mesenteric artery for 45 min followed by 2 h of reperfusion in anesthetized animals. Small intestinal tissues were obtained at the end of reperfusion for examination of the intestinal mucosal injury which was scored according to Chiu and for determination of the content of malondialdehyde (MDA) (TBA method), activity of superoxide dismutase (SOD) (WST-8 method), content of lactic dehydrogenase (LDH) (colorimetric method), and expression of MCU, dynamin-related protein 1 (Drp1), recombinant human mitochondrial fission 1 protein (Fis1), mitofusin-1 (Mfn1) and Mfn2 (by Western blot). Results:Compared with S and S+ Ru360 groups, the Chiu′s score and contents of MDA and LDH were significantly increased, the activity of SOD was decreased, the expression of MCU, Drp1 and Fis1 was up-regulated, and the expression of Mfn1 and Mfn2 was down-regulated in IIR and IIR+ Ru360 groups ( P<0.05). Compared with IIR group, the Chiu′s score and contents of MDA and LDH were significantly decreased, the activity of SOD was increased, the expression of MCU, Drp1 and Fis1 was down-regulated, and the expression of Mfn1 and Mfn2 was up-regulated in IIR+ Ru360 group ( P<0.05). Conclusions:The mechanism underlying intestinal I/R injury may be related to MCU-induced promotion of mitochondrial fission, reduction of mitochondrial fusion and mediation of imbalance in mitochondrial dynamics in mice.

OBJECTIVE： To optimize and improve the quality standard for Citrus reticulata formula granules. METHODS： Totally 13 batches of C. Reticulata formula granules from 4 different manufacturers were used as trial samples， and qualitative identification of hesperidin and nobiletin in the samples were carried out by TLC according to the method of 2015 edition of Chinese Pharmacopoeia （part Ⅳ）. The quantitative analysis of naringin， hesperidin， hesperetin， nobiletin and tangeretin in C. reticulatae formula granules were conducted by UPLC[The determination was performed on Waters Acquity UPLC BEH C18 column with mobile phase consisted of acetonitrile-0.2％ phosphoric acid aqueous solution （gradient elution）. The detection wavelength was set at 283 nm， and sample size was 3 μL]. RESULTS： The results of TLC showed that in the chromatograms of samples， same color spots were shown in the corresponding positions of the chromatogram of reference substance. The results of UPLC showed， that the linear range of naringin， hesperidin， hesperetin， nobiletin and tangeretin were 0.64-6.44， 15.78-157.80， 0.17-1.66， 2.08-20.85 and 2.04-20.43 μg/mL， respectively （all r≥0.999 2）； the limits of detection were 0.03， 0.33， 0.10， 0.20 and 0.06       μg/mL； the limits of quantitation were 0.07， 1.34， 0.20， 0.60 and 0.22 μg/mL. The average recoveries were 99.4％， 99.6％， 99.7％， 99.7％ and 99.7％ （n＝9）； RSDs of precision （n＝6）， stability （n＝7） and reproducibility （n＝6） tests were all≤2.03％； naringin was detected in only 3 batches of samples from one manufacturer （the content ranged from 0.067 3 to 0.069.6    mg/g）， while the other 4 components were detected in 13 batches of samples （the contents of them ranged 0.646 5-1.728 0，   0.102 6-0.290 5， 0.023 1-0.689 8， 0.018 2-0.270 7 mg/g）. CONCLUSIONS： In this study， the quality standard of C. reticulata formula granules was improved by qualitative and quantitative methods， and the contents of hesperidin， hesperetin， nobiletin and tangeretin were not less than 0.60， 0.10， 0.02 and 0.01 mg/g， respectively.

Objective To explore the imaging features of MRI in the patients with gouty arthritis of knee and the diagnostic value.Methods The MR imaging and clinical date of 31 knees in 22 patients with gouty arthri-tis of the knee confirmed by pathology were retrospectively analyzed. Results All of the 31 knees showed synovial thickness,21 knees showed hydrarthrosis.29 knees had the gouty tophus which located at the patella bursa,patel-lar fat pad,joint cavity,intercondylar fossa,femoral condyle or surrounding,patella or before,and tibial platform or before.Tophi showed hypointensity on T1WI,showed isointensity,slight hyperintensity,and hypo-/slight hyper-intensity on T2WI.Conclusion MRI is very effective image examination method of diagnosis the gout arthritis of the knee,MRI can clearly show synovial thickeness,hydrarthrosis and soft tissue swelling,sensitively observe the bone erosion and the gouty tophi.