Objective: To explore the characteristics of distribution on Chinese adult body mass index (BMI) in different age groups and genders and to provide reference related to obesity and related chronic diseases. Methods: Data from the China Health and Nutrition Survey in 2009 were used. Sequential sample cluster method was used to analyze the characteristics of BMI distribution in different age groups and genders by SAS. Results: Our results showed that the adult BMI in China should be divided into 3 groups according to their age, as 20 to 40 years old, 40 to 65 years old, and> 65 years old, in females or in total when grouped by difference of 5 years. For groupings in male, the three groups should be as 20 to 40, 40 to 60 years old and>60 years old. There were differences on distribution between the male and female groups. When grouped by difference of 10 years, all of the clusters for male, female and total groups as 20-40, 40-60 and>60 years old, became similar for the three classes, respectively, with no differences of distribution between gender, suggesting that the 5-years grouping was more accurate than the 10-years one, and BMI showing gender differences. Conclusions: BMI of the Chinese adults should be divided into 3 categories according to the characteristics of their age. Our results showed that BMI was increasing with age in youths and adolescents, remained unchanged in the middle-aged but decreasing in the elderly.
Adolescent ; Adult ; Age Distribution ; Aged ; Asian People/statistics & numerical data* ; Body Mass Index ; China/epidemiology* ; Female ; Humans ; Male ; Middle Aged ; Nutrition Surveys ; Obesity/ethnology* ; Sex Distribution ; Sex Factors ; Young Adult

Objective    To systematically evaluate the clinical value of machine learning (ML) for predicting the neurological outcome of out-of-hospital cardiac arrest (OHCA), and to develop a prediction model. Methods    We searched the PubMed, Web of Science, EMbase, CNKI, Wanfang database from January 1, 2011 to November 24, 2021. Studies on ML for predicting neurological outcomes in OHCA pateints were collected. Two researchers independently screened the literature, extracted the data and evaluated the bias of the included literature, evaluated the accuracy of different models and compared the area under the receiver operating characteristic curve (AUC). Results    A total of 20 studies were included. Eleven of the studies were from open source databases and nine were from retrospective studies. Sixteen studies directly predicted OHCA neurological outcomes, and four predicted OHCA neurological outcomes after target temperature management. A total of seven ML algorithms were used, among which neural network was the ML algorithm with the highest frequency (n=5), followed by support vector machine and random forest (n=4). Three papers used multiple algorithms. The most frequently used input characteristic was age (n=19), followed by heart rate (n=17) and gender (n=13). A total of 4 studies compared the predictive value of ML with other classical statistical models, and the AUC value of ML model was higher than that of classical statistical models. Conclusion    Existing evidence suggests that ML can more accurately predict OHCA nervous system outcomes, and the predictive performance of ML is superior to traditional statistical models in certain situations.

As a global disease, heart failure affects at least 26 million people, and its prevalence is still rising. Besides, the mortality rate and readmission rate remain high. Advanced heart failure is the terminal stage of various heart diseases, and often requires some treatments other than drug intervention, such as heart transplantation which is the gold standard for treatment of heart failure. However, limited by the number of donors, the number of heart transplants in the world has reached a bottleneck. There is a huge gap between the number of patients who need heart transplants and patients who get hearts for survival successfully in reality. With the exploration and development of mechanical circulation support devices for more than half a century, they have become a wonderful treatment for patients with advanced heart failure. This article will introduce the latest progress of mechanical circulatory support devices at home and abroad from the aspects of temporary and long-term devices.

Objective    To explore the potential role of tumor spread through air spaces (STAS) as a prognostic indicator of non-small cell lung cancer (NSCLC) through meta-analysis. Methods    PubMed, EMbase and Web of Science, from inception to February 2022 were searched by computer about the research of the 5-year overall survival (OS) and recurrence free survival (RFS) of NSCLC patients with or without STAS. The Newcastle-Ottawa scale (NOS) was used to evaluate the quality of each study. Results    Totally 13 published articles were included with 4 647 patients, and 1 424 (30.6%) patients had STAS. The NOS score of all studies≥6 points. The meta-analysis showed that compared with the NSCLC patients without STAS, those with STAS had a worse prognosis of 5-year RFS, and the combined HR was 1.89 (95%CI 1.61-2.23); they had a shorter 5-year OS, and the combined HR was 2.25 (95%CI 1.79-2.84). There was no statistical heterogeneity among studies. Conclusion    The presence of STAS may be a poor prognostic factor for patients with NSCLC, and enough attention should be paid. The STAS should be recorded in the pathological report to guide the comprehensive treatment and evaluate the prognosis of patients.

Intelligent medical image segmentation methods have been rapidly developed and applied, while a significant challenge is domain shift. That is, the segmentation performance degrades due to distribution differences between the source domain and the target domain. This paper proposed an unsupervised end-to-end domain adaptation medical image segmentation method based on the generative adversarial network (GAN). A network training and adjustment model was designed, including segmentation and discriminant networks. In the segmentation network, the residual module was used as the basic module to increase feature reusability and reduce model optimization difficulty. Further, it learned cross-domain features at the image feature level with the help of the discriminant network and a combination of segmentation loss with adversarial loss. The discriminant network took the convolutional neural network and used the labels from the source domain, to distinguish whether the segmentation result of the generated network is from the source domain or the target domain. The whole training process was unsupervised. The proposed method was tested with experiments on a public dataset of knee magnetic resonance (MR) images and the clinical dataset from our cooperative hospital. With our method, the mean Dice similarity coefficient (DSC) of segmentation results increased by 2.52% and 6.10% to the classical feature level and image level domain adaptive method. The proposed method effectively improves the domain adaptive ability of the segmentation method, significantly improves the segmentation accuracy of the tibia and femur, and can better solve the domain transfer problem in MR image segmentation.
Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Magnetic Resonance Imaging ; Knee ; Knee Joint

<p>OBJECTIVETo analyze the strains of bacteria in burn infection and their resistance to antibiotics in our burn unit in the recent years.p><p>METHODSBacteria were isolated from specimens from the wounds, venous lines, blood, urine and feces of the hospitalized burn patients from January 2003 to December 2005 to analyze the vicissitude of bacteria and their drug resistance.p><p>RESULTSThe number of Gram-negative bacteria (372 strains) was larger than Gram-positive ones (292 strains). Staphylococcus aureus (accounting for 16.7%) was predominant among Gram-positive bacteria, among which methicillin resistant staphylococcus aureus (MRSA) accounted for 82.5%. Among the Gram-negative bacteria, Pseudomonas aeruginosa accounted for 12.5%, and Escherichia coli accounted for 11.1%. The drug resistant ESPL-producing strains of Escherichia coli and Klebsiella pneumoniae accounted for 60.8% and 42.9%, respectively.p><p>CONCLUSIONDrug resistance to antibiotics is a serious problem in a burn unit, calling for monitoring the vicissitude of bacteria strains and antibiotics sensitivity in order to control bacterial infection and dissemination.p>
Adolescent ; Adult ; Aged ; Anti-Bacterial Agents ; pharmacology ; Bacterial Infections ; microbiology ; Burn Units ; Burns ; microbiology ; Child ; Child, Preschool ; Drug Resistance, Bacterial ; Female ; Gram-Negative Bacteria ; drug effects ; isolation & purification ; Gram-Positive Bacteria ; drug effects ; isolation & purification ; Humans ; Male ; Middle Aged ; Young Adult

Objective To observe the effect of artemether in the control of prevalence and acute infection of Schistosoma japonicum in humans in high endemic areas. Methods During the transmission season (May-October), the residents in the pilot village took artemether with a 15- day interval to prevent the infection of S. japonicum. Results By the end of the transmission season, the egg positive rate was 0.83% and no acute case occurred in the artemether group, while 15.01% and 3 acute cases were observed in the placebo group. Conclusions Oral administration of artemether at a 15-day interval shows an effective protection from infection of S. japonicum, with a protection rate of 94.47% in residents of a high endemic area and it also shows marked effect to prevent acute schistosomiasis.

Spirometra erinaceieuropaei casein kinase I (SeCKI) was analyzed using bioinformatical methods to predict its structure and function based on the deduced amino acid sequence from full length cDNA sequence of SeCKI gene with online sites and software programs. The longest open reading frame contains 448 amino acids, 50 kDa and theoretical pI of 4.73, with a complete tubulin domain, a SMART tubulin_C domain and a low complexity region. SeCKI has no signal sequence and no transmembrane domain, but is predicted to be located extracellularly. The secondary structure of SeCKI contains 12 α-helixes, 11 β-strands and 22 coils. SeCKI had 19 potential antigenic epitopes and 25 HLA-I restricted epitopes. Based on phylogenetic analysis of SeCKI sequence, S. erinaceieuropaei has the closest evolutionary status with Hymenolepis microstoma. Information from this study could provide important insights into the identification of diagnostic antigens and molecular targets of antisparganum drugs.

With the wide popularization of low-dose computed tomography screening for lung cancer, the proportion of early detection of lung cancer has increased significantly. Due to the favorable prognosis of ground-glass nodule-lung cancer, a prospective multicenter clinical trial in Japan has confirmed the safety and efficacy of segmentectomy. Identification of the intersegmental plane is one of the key steps in segmentectomy. Understanding its physiological mechanism can provide a theoretical basis for optimizing the identification technique, identifying intersegmental plane more accurately and quickly, improving the surgical effect and reducing complications. This article mainly introduces the identification technology of the intersegmental plane and its physiological mechanism in pulmonary segmentectomy.

Objective    To investigate the changes of fibrinogen and classical markers of collagen metabolism [carboxy-terminal propeptide of type Ⅰ procollagen (PICP) and carboxy-terminal cross-linked peptide of type Ⅰ collagen (ICTP)] in peripheral blood and pericardial drainage after coronary artery bypass grafting (CABG) and/or heart valve replacement (VR), and to evaluate their relationship with postoperative atrial fibrillation (POAF) after cardiac surgery. Methods    Patients who underwent CABG and/or VR in the Heart Center of Beijing Chao-Yang Hospital from March to June 2021 were included. Peripheral blood and pericardial drainage fluid samples were collected before surgery and at 0 h, 6 h, 24 h and 48 h after surgery to detect PICP, ICTP and fibrinogen levels, and preoperative, intraoperative and postoperative confounding factors were also collected. PICP, ICTP and fibrinogen levels were measured by enzyme-linked immunosorbent assay (ELISA). Results    A total of 26 patients with 125 blood samples and 78 drainage samples were collected. There were 18 males and 8 females with an average age of 64.04±7.27 years. The incidence rate of POAF was 34.6%. Among the factors, the fibrinogen level in pericardial drainage showed two peaks within 48 h after operation (0 h and 24 h after operation) in the POAF group, while it showed a continuous downward trend in the sinus rhythm (SR) group, and the change trend of fibrinogen in pericardial drainage was significantly different over time between the two groups (P=0.022). Fibrinogen in blood, PICP and ICTP in blood and drainage showed an overall decreasing trend, and their trends over time were not significantly different between the two groups of patients (P>0.05). Univariate analysis showed that fibrinogen at 24 h and 48 h after pericardial drainage, fibrinogen in preoperative blood, PICP immediately after surgery and right atrial long axis diameter were significantly higher or longer in the POAF group than those in the SR group. Multiple regression showed that fibrinogen≥11.47 ng/mL in pericardial drainage 24 h after surgery (OR=14.911, 95%CI 1.371-162.122, P=0.026), right atrial long axis diameter≥46 mm (OR=10.801, 95%CI 1.011-115.391, P=0.049) were independent predictors of POAF. Conclusion    This study finds the regularity of changes in fibrinogen and collagen metabolic markers after CABG and/or VR surgery, and to find that fibrinogen in pericardial drainage 24 h after surgery is a potential novel and predictive factor for POAF. The results provide a new idea for exploring the mechanism of POAF, and provide a research basis for the accurate prediction and prevention of clinical POAF.