Long-term BMI change trajectories in Chinese adults and its association with the hazard of type 2 diabetes: evidence from a 20-year China Health and Nutrition Survey.

INTRODUCTION To investigate the relationship between long-term change trajectory in body mass index (BMI) and the hazard of type 2 diabetes among Chinese adults. RESEARCH DESIGN AND METHODS Data were obtained from the China Health and Nutrition Survey (CHNS). Type 2 diabetes was reported by participants themselves in each survey wave. The duration of follow-up was defined as the period from the first visit to the first time self-reported type 2 diabetes, death, or other loss to follow-up from CHNS. The patterns of change trajectories in BMI were derived by latent class trajectory analysis method. The Fine and Gray regression model was used to estimate HRs with corresponding 95% CIs for type 2 diabetes. RESULTS Four patterns of the trajectories of change in BMI were identified among Chinese adults, 42.7% of participants had stable BMI change, 40.8% for moderate BMI gain, 8.9% for substantial BMI gain and 7.7% for weight loss. During the follow-up with mean 11.2 years (158 637 person-years contributed by 14 185 participants), 498 people with type 2 diabetes (3.7%) occurred. Risk of type 2 diabetes was increased by 47% among people who gained BMI more substantially and rapidly (HR: 1.47, 95% CI 1.08 to 2.02, p=0.016) and increased by 20% among those in people with the moderate BMI gain (HR: 1.20, 95% CI 0.98 to 1.48, p=0.078), compared with those with stable BMI change. CONCLUSIONS Long-term substantial gain of BMI was significantly associated with an increased risk of type 2 diabetes in the Chinese adults

Acoustofluidic Engineering Functional Vessel-on-a-Chip

Construction of in vitro vascular models is of great significance to various biomedical research, such as pharmacokinetics and hemodynamics, thus is an important direction in tissue engineering. In this work, a standing surface acoustic wave field was constructed to spatially arrange suspended endothelial cells into a designated patterning. The cell patterning was maintained after the acoustic field was withdrawn by the solidified hydrogel. Then, interstitial flow was provided to activate vessel tube formation. Thus, a functional vessel-on-a-chip was engineered with specific vessel geometry. Vascular function, including perfusability and vascular barrier function, was characterized by beads loading and dextran diffusion, respectively. A computational atomistic simulation model was proposed to illustrate how solutes cross vascular lipid bilayer. The reported acoustofluidic methodology is capable of facile and reproducible fabrication of functional vessel network with specific geometry. It is promising to facilitate the development of both fundamental research and regenerative therapy

Identification of biomarkers and mechanisms of diabetic cardiomyopathy using microarray data

Background: The study aimed to uncover the regulation mechanisms of diabetic cardiomyopathy (DCM) and provide novel prognostic biomarkers. Methods: The dataset GSE62203 downloaded from the Gene Expression Omnibus database was utilized in the present study. After pretreatment using the Affy package, differentially expressed genes (DEGs) were identified by the limma package, followed by functional enrichment analysis and protein– protein interaction (PPI) network analysis. Furthermore, module analysis was conducted using MCODE plug-in of Cytoscape, and functional enrichment analysis was also performed for genes in the modules. Results: A set of 560 DEGs were screened, mainly enriched in the metabolic process and cell cycle related process. Hub nodes in the PPI network were LDHA (lactate dehydrogenase A), ALDOC (aldolase C, fructose-bisphosphate) and ABCE1 (ATP Binding Cassette Subfamily E Member 1), which were also highlighted in Module 1 or Module 2 and predominantly enriched in the processes of glycolysis and ribosome biogenesis. Additionally, LDHA were linked with ALDOC in the PPI network. Besides, activating transcription factor 4 (ATF4) was prominent in Module 3; while myosin heavy chain 6 (MYH6) was highlighted in Module 4 and was mainly involved in muscle cells related biological processes. Conclusions: Five potential biomarkers including LDHA, ALDOC, ABCE1, ATF4 and MYH6 were identified for DCM prognosis

Identification and validation of prognostically relevant gene signature in melanoma

Background. Currently, effective genetic markers are limited to predict the clinical outcome of melanoma. High-throughput multiomics sequencing data have provided a valuable approach for the identification of genes associated with cancer prognosis. Method. The multidimensional data of melanoma patients, including clinical, genomic, and transcriptomic data, were obtained from The Cancer Genome Atlas (TCGA). These samples were then randomly divided into two groups, one for training dataset and the other for validation dataset. In order to select reliable biomarkers, we screened prognosis-related genes, copy number variation genes, and SNP variation genes and integrated these genes to further select features using random forests in the training dataset. We screened for robust biomarkers and established a gene-related prognostic model. Finally, we verified the selected biomarkers in the test sets (GSE19234 and GSE65904) and on clinical samples extracted from melanoma patients using qRT-PCR and immunohistochemistry analysis. Results. We obtained 1569 prognostic-related genes and 1101 copy-amplification, 1093 copy-deletions, and 92 significant mutations in genomic variants. These genomic variant genes were closely related to the development of tumors and genes that integrate genomic variation. A total of 141 candidate genes were obtained from prognosis-related genes. Six characteristic genes (IQCE, RFX6, GPAA1, BAHCC1, CLEC2B, and AGAP2) were selected by random forest feature selection, many of which have been reported to be associated with tumor progression. Cox regression analysis was used to establish a 6-gene signature. Experimental verification with qRT-PCR and immunohistochemical staining proved that these selected genes were indeed expressed at a significantly higher level compared with the normal tissues. This signature comprised an independent prognostic factor for melanoma patients. Conclusions. We constructed a 6-gene signature (IQCE, RFX6, GPAA1, BAHCC1, CLEC2B, and AGAP2) as a novel prognostic marker for predicting the survival of melanoma patients

A 5-year review of invasive fungal infection at an academic medical center

Background: Invasive fungal infection (IFI) is one of the most common nosocomial infections. However, data on the epidemiology of IFI and susceptibility to antifungal agents in China are quite limited, and in particular, no current data exist on the microbiological, and clinical characteristics of IFI patients in Northeast China. Objectives: The purpose of this study was to provide a retrospective review of the clinical characteristics, laboratory test results, and risk factor predictions of inpatients diagnosed with IFI. Multivariate regression analysis was used to assess prognostic factors associated with the mortality of these patients. Methods: We retrospectively analyzed the results from 509 patients with IFI extracted from the First Hospital of China Medical University from January 2013 to January 2018. Results: Neutrophil numbers, total bilirubin, length of stay in the ICU, renal failure, use of immunosuppressants within the past 30 days, stomach tube placement and septic shock were risk factors for death from IFI. Recent surgery (within 2 weeks) and drainage tube placement did not increase mortality in these IFI patients. Increased serum levels of PCT (AUC 0.601, 95% CI 0.536–0.665, P = 0.003) and CRP (AUC 0.578, 95% CI 0.512–0.644, P = 0.020) provided effective predictors of 30-day mortality rates. Conclusions: We report for the first time epidemiological data on invasive fungal infections in Northeast China over the past 5 years. Despite the limited available clinical data, these findings will greatly aid clinical health care workers with regard to the identification, prevention, and treatment of IFI in hospitalized patients

The Lesson Learned from the Unique Evolutionary Story of Avirulence Gene AvrPii of Magnaporthe oryzae

Blast, caused by Magnaporthe oryzae, is one of the most destructive diseases affecting rice production. Understanding population dynamics of the pathogen's avirulence genes is pre-required for breeding and then deploying new cultivars carrying promising resistance genes. The divergence and population structure of AvrPii was dissected in the populations of southern (Guangdong, Hunan, and Guizhou) and northern (Jilin, Liaoning, and Heilongjiang) China, via population genetic and evolutionary approaches. The evolutionary divergence between a known haplotype AvrPii-J and a novel one AvrPii-C was demonstrated by haplotype-specific amplicon-based sequencing and genetic transformation. The different avirulent performances of a set of seven haplotype-chimeric mutants suggested that the integrity of the full-length gene structures is crucial to express functionality of individual haplotypes. All the four combinations of phenotypes/genotypes were detected in the three southern populations, and only two in the northern three, suggesting that genic diversity in the southern region was higher than those in the northern one. The population structure of the AvrPii family was shaped by balancing, purifying, and positive selection pressures in the Chinese populations. The AvrPii-J was recognized as the wild type that emerged before rice domestication. Considering higher frequencies of avirulent isolates were detected in Hunan, Guizhou, and Liaoning, the cognate resistance gene Pii could be continuously used as a basic and critical resistance resource in such regions. The unique population structures of the AvrPii family found in China have significant implications for understanding how the AvrPii family has kept an artful balance and purity among its members (haplotypes) those keenly interact with Pii under gene-for-gene relationships. The lesson learned from case studies on the AvrPii family is that much attention should be paid to haplotype divergence of target gene