36 research outputs found

    Physical activity and weight loss among adults with type 2 diabetes and overweight or obesity: a post hoc analysis of the Look AHEAD trial

    Get PDF
    Importance: Prior findings from the Look AHEAD trial showed no significant reduction in the risk of cardiovascular events by lifestyle-induced weight loss among individuals with type 2 diabetes (T2D) and overweight or obesity. However, physical activity (PA) may modify the changes in cardiovascular risk associated with weight loss. Objective: To examine the joint association of weight loss and PA with the risk of adverse cardiovascular events in patients with T2D and overweight or obesity. Design, Setting, and Participants: This cohort study was a post hoc analysis of the Look AHEAD randomized clinical trial, which compared the cardiovascular effects of weight loss by intensive lifestyle intervention vs diabetes support and education among individuals with T2D and overweight or obesity. The study was conducted from June 2001 to September 2012, and participants were patients in the substudy of accelerometry-measured PA from 8 locations in the United States. Data were analyzed from June to August 2023. Exposures: Body weight change and accelerometer-derived PA volume across the first 4 years. Main Outcomes and Measures: The primary outcome was a composite cardiovascular outcome including cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for angina. Results: Among a total of 1229 participants (mean [SD] age, 60 [7] years; 533 male [43%]), 333 (27%) achieved and maintained weight loss for the first 4 years. Among the individuals who maintained weight loss, 105 (32%) maintained high PA volume. During a median of 9.5 years of follow-up, 198 participants (16.1%) experienced the primary outcome. Compared with those with low PA volume and no weight loss (105 [15.8%]), maintaining high PA volume and weight loss was associated with a 61% lower risk of the primary end point (hazard ratio, 0.39; 95% CI, 0.19-0.81; P = .01). However, there was no significant difference in the risk of the primary end point among those with either weight loss only or high PA only. The multiplicative interaction between weight loss and PA for the risk of cardiovascular events was also significant (P for interaction = .01). Conclusions and Relevance: In this cohort study, maintaining weight loss and higher PA volume was associated with a lower risk of the composite cardiovascular outcome. The findings suggest that the cardiovascular benefits of PA may vary and be enhanced by weight loss among individuals with T2D and overweight or obesity

    Small RNA Profile in Moso Bamboo Root and Leaf Obtained by High Definition Adapters

    Get PDF
    Moso bamboo (Phyllostachy heterocycla cv. pubescens L.) is an economically important fast-growing tree. In order to gain better understanding of gene expression regulation in this important species we used next generation sequencing to profile small RNAs in leaf and roots of young seedlings. Since standard kits to produce cDNA of small RNAs are biased for certain small RNAs, we used High Definition adapters that reduce ligation bias. We identified and experimentally validated five new microRNAs and a few other small non-coding RNAs that were not microRNAs. The biological implication of microRNA expression levels and targets of microRNAs are discussed

    Author Correction: The flying spider-monkey tree fern genome provides insights into fern evolution and arborescence (Nature Plants, (2022), 8, 5, (500-512), 10.1038/s41477-022-01146-6)

    Get PDF
    Correction to: Nature Plantshttps://doi.org/10.1038/s41477-022-01146-6, published online 9 May 2022. In the version of the article initially published, Dipak Khadka, who collected the samples in Nepal, was thanked in the Acknowledgements instead of being listed as an author. His name and affiliation (GoldenGate International College, Tribhuvan University, Battisputali, Kathmandu, Nepal) have been added to the authorship in the HTML and PDF versions of the article

    Paleolimnological environments and organic accumulation of the Nenjiang formation in the southeastern Songliao basin, China

    No full text
    Thick layers of dark lacustrine mudstone in the Nenjiang Formation record the evolution of local depositional environments in the Songliao Basin. This evolution in lake water is accurately reflected in variations in trace element compositions in sedimentary rocks. In this study, element geochemistry and clay mineralogy in successive cores were investigated to have a closer insight into the paleolimnological environment and organic accumulation during the Nenjiang epoch. Analysis of the contents of Mn, Ca and Ti, as well as Rb/Sr and Sr/Cu revealed that paleoclimate cycled between warm and humid to semi-arid and hot. The study of Sr/Ba ratios, clay minerals and stable isotopes indicated that both high and low salinity existed in two stages, and that high salinity in Member 1 of the Nenjiang Formation is likely correlated with transgressive events. Analysis of the ratios of V/V + Ni, Ni/V and Th/U suggested that the paleolimnological environment was reducing. The investigation of paleotemperature demonstrated that the Nenjiang Formation was deposited in a warm water environment, analysis of carbon and oxygen isotopes revealed its deposition in open paleolake. High paleoproductivity and salinity as well as redox potentials represent the most favorable environment for oil shale enrichment.</p

    MDCT: Multi-Kernel Dilated Convolution and Transformer for One-Stage Object Detection of Remote Sensing Images

    No full text
    Deep learning (DL)-based object detection algorithms have gained impressive achievements in natural images and have gradually matured in recent years. However, compared with natural images, remote sensing images are faced with severe challenges due to the complex backgrounds and difficult detection of small objects in dense scenes. To address these problems, a novel one-stage object detection model named MDCT is proposed based on a multi-kernel dilated convolution (MDC) block and transformer block. Firstly, a new feature enhancement module, MDC block, is developed in the one-stage object detection model to enhance small objects’ ontology and adjacent spatial features. Secondly, we integrate a transformer block into the neck network of the one-stage object detection model in order to prevent the loss of object information in complex backgrounds and dense scenes. Finally, a depthwise separable convolution is introduced to each MDC block to reduce the computational cost. We conduct experiments on three datasets: DIOR, DOTA, and NWPU VHR-10. Compared with the YOLOv5, our model improves the object detection accuracy by 2.3%, 0.9%, and 2.9% on the DIOR, DOTA, and NWPU VHR-10 datasets, respectively
    corecore