This study used machine learning techniques combined with routine blood cell analysis parameters to build preliminary prediction models, helping differentiate patients with depression from healthy controls, or patients with anxiety. A multicenter study was performed by collecting blood cell analysis data of Beijing Chaoyang Hospital and the First Hospital of Hebei Medical University from 2020 to 2021. Machine learning techniques, including support vector machine, decision tree, naïve Bayes, random forest and multi-layer perceptron were explored to establish a prediction model of depression. The results showed that based on the blood cell analysis results of healthy controls and depression group, the accuracy of prediction model reached as high as 0.99, F1 was 0.975. Receiver operating characteristic curve area and average accuracy were 0.985 and 0.967, respectively. Platelet parameters contributed mostly to depression prediction model. While, to random forest differential diagnosis model based on the data from depression and anxiety groups, prediction accuracy reached 0.68 and AUC 0.622. Age, platelet parameters, and average volume of red blood cells contributed the most to the model. In conclusion, the study researched on the prediction model of depression by exploring blood cell analysis parameters, revealing that machine learning models were more objective in the evaluation of mental illness.
Humans ; Depression ; Bayes Theorem ; Machine Learning ; Support Vector Machine ; Blood Cell Count

Objective: To establish a method for the rapid determination of acetaminophen (APAP) in human plasma by LC-MS/MS. Methods: The plasma samples were extracted by methanol and acetonitrile (1: 1) and purified directly. C(18) column was used for sample separation. The mobile phase were methanol (5 mmol/L ammonium acetate) and water (5 mmol/L ammonium acetate). Samples were analyzed by LC MS/MS with the electrospray ionization multi reaction monitoring (MRM) mode. Results: The calibration curves of APAP was linear in the concentration range of 0~10 mg/L, the correlation coefficient (r) was greater than 0.999 0. The relative standard deviation within and between batches was less than 10%. The recovery rate were 96.81%~101.7%. The detection limit of the method was 0.1 μg/L and the lower limit of quantification was 0.3 μg/L. Conclusion: This method has strong specificity, high sensitivity and reliable determination results. It is suitable for the rapid analysis of clinical plasma samples.
Humans ; Chromatography, Liquid/methods* ; Acetaminophen ; Tandem Mass Spectrometry/methods* ; Methanol ; Chromatography, High Pressure Liquid/methods*

ObjectiveTo investigate the association between serum 25-hydroxy vitamin D [25(OH)D] and the occurrence and outcome of stroke-associated pneumonia (SAP) in patients with acute ischemic stroke (AIS) in emergency ward. MethodsThe clinical data of 256 patients with AIS from January, 2019 to December, 2021 were collected in the emergency department of Beijing Bo'ai Hospital. Blood routine, biochemical indicators and serum concentration of 25(OH)D were detected within 24 hours after enrollment; meanwhile, National Institute of Health Stroke Scale (NIHSS) and A2DS2 score were evaluated. The patients were divided into non-SAP group (n = 164) and SAP group (n = 92) according to whether pneumonia occurred during hospitalization. Multivariable logistic regression model was used to analyze the influencing factors of SAP. The predictive ability of serum 25(OH)D and A2DS2 for SAP were evaluated by receiver operating characteristic (ROC) curves. The 28-day survival of patients with SAP was followed up. Multivariable Cox proportional hazard regression model was used to investigate the association between vitamin D nutritional status and 28-day all-cause mortality. ResultsSerum 25(OH)D was significantly lower in the SAP group than that in the non-SAP group (Z = 6.896, P < 0.001). After adjusting age, sex, infarct volume, A2DS2 score and other factors, lower serum 25(OH)D level (OR = 0.934, 95%CI 0.884 to 0.986, P = 0.014) was an independent risk factor for SAP. The areas under curve (95%CI) of serum 25(OH)D, A2DS2 score and their combined model for predicting SAP were 0.774 (0.718 to 0.824), 0.832 (0.781 to 0.876) and 0.851 (0.802 to 0.893) (P < 0.001), respectively; and the optimum cut-off values were 25(OH)D < 10.2 ng/mL, A2DS2 score > 5 points, combined prediction > 0.207, and the Youden index were 0.493, 0.662 and 0.616, respectively. A2DS2 score could improve the prediction efficiency of serum 25(OH)D (Z = 2.106, P = 0.035). After adjusting age, sex, infarct volume and NIHSS score, vitamin D deficiency was an independent risk factor for all-cause mortality after 28 days of SAP (HR = 2.871, 95%CI 1.004 to 8.208, P = 0.049) . ConclusionSerum 25(OH)D is independently associated with the occurrence and outcome of SAP in patients with AIS in emergency ward, which could serve as an independent predictor for SAP.

This study used machine learning techniques combined with routine blood cell analysis parameters to build preliminary prediction models, helping differentiate patients with depression from healthy controls, or patients with anxiety. A multicenter study was performed by collecting blood cell analysis data of Beijing Chaoyang Hospital and the First Hospital of Hebei Medical University from 2020 to 2021. Machine learning techniques, including support vector machine, decision tree, naïve Bayes, random forest and multi-layer perceptron were explored to establish a prediction model of depression. The results showed that based on the blood cell analysis results of healthy controls and depression group, the accuracy of prediction model reached as high as 0.99, F1 was 0.975. Receiver operating characteristic curve area and average accuracy were 0.985 and 0.967, respectively. Platelet parameters contributed mostly to depression prediction model. While, to random forest differential diagnosis model based on the data from depression and anxiety groups, prediction accuracy reached 0.68 and AUC 0.622. Age, platelet parameters, and average volume of red blood cells contributed the most to the model. In conclusion, the study researched on the prediction model of depression by exploring blood cell analysis parameters, revealing that machine learning models were more objective in the evaluation of mental illness.
Humans ; Depression ; Bayes Theorem ; Machine Learning ; Support Vector Machine ; Blood Cell Count

Objective: To establish a method for rapid determination of bongkrekic acid (BA) in plasma by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Methods: In November 2020, plasma samples were extracted by methanol and acetonitrile (1∶1) and purified directly. The samples were separated by C18 column. Gradient elution was carried out with 5 mmol/L ammonium acetate water acetonitrile solution as mobile phase. Under the optimized instrument conditions, the electrospray ionization multiple reaction monitoring (MRM) mode was used, and the external standard method was used for quantitative analysis. Results: The linear relationship of BA in plasma was good in the concentration range of 2-100 μg/L, the correlation coefficient was 0.9998, the average recovery was 83.7%-112.0%, the relative standard deviation within and between batches was less than 10%, the detection limit of the method was 0.7 μg/L and the lower limit of quantification was 2.0 μg/L. Conclusion: The method is simple, rapid, accurate and sensitive, and can meet the requirements for the determination of BA in blood samples of poisoning patients.
Bongkrekic Acid ; Chromatography, High Pressure Liquid ; Humans ; Solid Phase Extraction ; Tandem Mass Spectrometry

Objective: This study sought to investigate the impact of different obesity patterns on coronary microvascular function in male patients with non-obstructive coronary artery disease. Methods: We retrospectively analyzed clinical data of male patients diagnosed with suspected coronary microvascular dysfunction (CMD) in the First Hospital of Shanxi Medical University between December 2015 and August 2021. All patients underwent the one-day rest and stress ¹³N-ammonia positron emission tomography myocardial perfusion imaging. Overall obesity was defined by body mass index (BMI) ≥28 kg/m² and abdominal obesity was defined by waist circumference ≥90 cm. Hyperemic myocardial blood flow (MBF)<2.3 ml·min^-1·g^-1 or coronary flow reserve (CFR)<2.5 were referred as CMD. All patients were grouped based on their BMI and waist circumference. MBF, CFR, the incidence of CMD, hemodynamic parameters, and cardiac function were compared among the groups. Results: A total of 136 patients were included. According to BMI and waist circumference, patients were categorized into 3 groups: control group (n=45), simple abdominal obesity group (n=53) and compound obesity group (n=38). Resting MBF did not differ between groups (F=0.02,P=0.994). Compared with the control group, hyperemic MBF was significantly lower in the simple abdominal obesity and compound obesity groups ((2.82±0.64) ml·min^-1·g^-1, (2.44±0.85) ml·min^-1·g^-1 and (2.49±0.71) ml·min^-1·g^-1, both P<0.05, respectively). Hyperemic MBF was comparable among the groups of patients with obesity (P=0.772). CFR was significantly lower in the simle abdominal obesity group compared with the control group (2.87±0.99 vs. 3.32±0.62,P=0.012). Compared with the control group, CFR tended to be lower in the compound obesity group (3.02±0.91 vs. 3.32±0.62,P=0.117). The incidence of CMD was significantly higher in both the simple abdominal obesity and compound obesity groups than in the control group (62.3%, 52.6% vs. 22.2%, both P<0.01, respectively). Waist circumference was an independent risk factor for male CMD (OR=1.057, 95%CI: 1.013-1.103, P=0.011). Conclusions: In male patients with non-obstructive coronary artery disease, abdominal obesity is associated with decreased coronary microvascular function. Male patients with simple abdominal obesity face the highest risk of CMD.
Humans ; Male ; Coronary Artery Disease ; Coronary Circulation/physiology* ; Obesity, Abdominal ; Retrospective Studies ; Obesity/epidemiology* ; Hyperemia

Blue space is an important place for physical activity and provides physical and mental health benefits to residents. However, little is known about the mechanism of association between blue space and physical activity. Based on China National Knowledge Infrastructure and Web of Science Core Collection, the Chinese and English literature on the correlation between blue space and physical activity were selected and analyzed. The research field has the following characteristics so far: there are few studies on blue space in inland cities, developing countries, and vulnerable populations, and it is an emerging research field. Most included studies demonstrate positive effects of blue space exposure on physical activity, while studies conducted in different populations demonstrate population differences. The combination of multi-source data and multidisciplinary approaches should be an important foundation of this research field. Based on this, a research framework was proposed in this paper to analyze the complex association between them from a perspective of multi-dimensional characteristics, and blue physical activity was modeled as ecosystem services to explore the relationship between blue space and physical activity from a perspective of ecosystem service supply-demand and flow.

Objective: To investigate the functional changes of key gut microbiota (GM) that produce lipopolysaccharide (LPS) in atrial fibrillation (AF) patients and to explore their potential role in the pathogenesis of AF. Methods: This was a prospective cross-sectional study. Patients with AF admitted to Beijing Chaoyang Hospital of Capital Medical University were enrolled from March 2016 to December 2018. Subjects with matched genetic backgrounds undergoing physical examination during the same period were selected as controls. Clinical baseline data and fecal samples were collected. Bacterial DNA was extracted and metagenomic sequencing was performed by using Illumina Novaseq. Based on metagenomic data, the relative abundances of KEGG Orthology (KO), enzymatic genes and species that harbored enzymatic genes were acquired. The key features were selected via the least absolute shrinkage and selection operator (LASSO) analysis. The role of GM-derived LPS biosynthetic feature in the development of AF was assessed by receiver operating characteristic (ROC) curve, partial least squares structural equation modeling (PLS-SEM) and logistic regression analysis. Results: Fifty nonvalvular AF patients (mean age: 66.0 (57.0, 71.3), 32 males(64%)) were enrolled as AF group. Fifty individuals (mean age 55.0 (50.5, 57.5), 41 males(82%)) were recruited as controls. Compared with the controls, AF patients showed a marked difference in the GM genes underlying LPS-biosynthesis, including 20 potential LPS-synthesis KO, 7 LPS-biosynthesis enzymatic genes and 89 species that were assigned as taxa harbored nine LPS-enzymatic genes. LASSO regression analysis showed that 5 KO, 3 enzymatic genes and 9 species could be selected to construct the KO, enzyme and species scoring system. Genes enriched in AF group included 2 KO (K02851 and K00972), 3 enzymatic genes (LpxH, LpxC and LpxK) and 7 species (Intestinibacter bartlettii、Ruminococcus sp. JC304、Coprococcus catus、uncultured Eubacterium sp.、Eubacterium sp. CAG:251、Anaerostipes hadrus、Dorea longicatena). ROC curve analysis revealed the predictive capacity of differential GM-derived LPS signatures to distinguish AF patients in terms of above KO, enzymatic and species scores: area under curve (AUC)=0.957, 95%CI: 0.918-0.995, AUC=0.940, 95%CI 0.889-0.991, AUC=0.972, 95%CI 0.948-0.997. PLS-SEM showed that changes in lipopolysaccharide-producing bacteria could be involved in the pathogenesis of AF. The key KO mediated 35.17% of the total effect of key bacteria on AF. After incorporating the clinical factors of AF, the KO score was positively associated with the significantly increased risk of AF (OR<0.001, 95%CI:<0.001-0.021, P<0.001). Conclusion: Microbes involved in LPS synthesis are enriched in the gut of AF patients, accompanied with up-regulated LPS synthesis function by encoding the LPS-enzymatic biosynthesis gene.
Aged ; Atrial Fibrillation/complications* ; Cross-Sectional Studies ; Gastrointestinal Microbiome ; Humans ; Lipopolysaccharides ; Male ; Middle Aged ; Prospective Studies

The paper introduces professor MA Hui-fang's experience in age-related macular degeneration treated with acupuncture at Jingming (BL 1). It is believed that the basic pathogenesis of this disease refers to liver and kidney insufficiency and weakness of spleen qi. Based on the academic ideas of yang qi and meridian-collateral system, the treatment principle is proposed as "invigorating yang qi, replenishing the liver and kidney and nourishing the spleen and stomach". Regarding acupoint selection, Jingming (BL 1) is specially used, combined with the 4 front-mu points (Zhongwan [CV 12], Guanyuan [CV 4] and bilateral Tianshu [ST 25]), as well as the empirical points for eye diseases (Jingming [BL 1], Baihui [GV 20] and Zulinqi [GB 41]). Concerning to needling technique, shuci (transport needling), fenci (intermuscular needling) and yuandaoci (distal needling) are dominated. Eventually, a set of unique therapeutic method has been accumulated through professor MA Hui-fang's clinical practice in treatment of age-related macular degeneration.
Acupuncture ; Acupuncture Points ; Acupuncture Therapy ; Humans ; Macular Degeneration/therapy* ; Meridians

Adult ; Aged ; Antibodies, Viral/metabolism* ; China ; Female ; Humans ; Immunoglobulin G/metabolism* ; Male ; Measles/metabolism* ; Measles virus/physiology* ; Medical Staff ; Middle Aged ; Saliva/virology* ; Young Adult