Knowledge-driven Meta-learning for CSI Feedback

Accurate and effective channel state information (CSI) feedback is a key technology for massive multiple-input and multiple-output systems. Recently, deep learning (DL) has been introduced for CSI feedback enhancement through massive collected training data and lengthy training time, which is quite costly and impractical for realistic deployment. In this article, a knowledge-driven meta-learning approach is proposed, where the DL model initialized by the meta model obtained from meta training phase is able to achieve rapid convergence when facing a new scenario during target retraining phase. Specifically, instead of training with massive data collected from various scenarios, the meta task environment is constructed based on the intrinsic knowledge of spatial-frequency characteristics of CSI for meta training. Moreover, the target task dataset is also augmented by exploiting the knowledge of statistical characteristics of wireless channel, so that the DL model can achieve higher performance with small actually collected dataset and short training time. In addition, we provide analyses of rationale for the improvement yielded by the knowledge in both phases. Simulation results demonstrate the superiority of the proposed approach from the perspective of feedback performance and convergence speed.Comment: arXiv admin note: text overlap with arXiv:2301.1347

Variety-driven rhizosphere microbiome bestows differential salt tolerance to alfalfa for coping with salinity stress

Soil salinization is a global environmental issue and a significant abiotic stress that threatens crop production. Root-associated rhizosphere microbiota play a pivotal role in enhancing plant tolerance to abiotic stresses. However, limited information is available concerning the specific variations in rhizosphere microbiota driven by different plant genotypes (varieties) in response to varying levels of salinity stress. In this study, we compared the growth performance of three alfalfa varieties with varying salt tolerance levels in soils with different degrees of salinization. High-throughput 16S rRNA and ITS sequencing were employed to analyze the rhizosphere microbial communities. Undoubtedly, the increasing salinity significantly inhibited alfalfa growth and reduced rhizosphere microbial diversity. However, intriguingly, salt-tolerant varieties exhibited relatively lower susceptibility to salinity, maintaining more stable rhizosphere bacterial community structure, whereas the reverse was observed for salt-sensitive varieties. Bacillus emerged as the dominant species in alfalfa's adaptation to salinity stress, constituting 21.20% of the shared bacterial genera among the three varieties. The higher abundance of Bacillus, Ensifer, and Pseudomonas in the rhizosphere of salt-tolerant alfalfa varieties is crucial in determining their elevated salt tolerance. As salinity levels increased, salt-sensitive varieties gradually accumulated a substantial population of pathogenic fungi, such as Fusarium and Rhizoctonia. Furthermore, rhizosphere bacteria of salt-tolerant varieties exhibited increased activity in various metabolic pathways, including biosynthesis of secondary metabolites, carbon metabolism, and biosynthesis of amino acids. It is suggested that salt-tolerant alfalfa varieties can provide more carbon sources to the rhizosphere, enriching more effective plant growth-promoting bacteria (PGPB) such as Pseudomonas to mitigate salinity stress. In conclusion, our results highlight the variety-mediated enrichment of rhizosphere microbiota in response to salinity stress, confirming that the high-abundance enrichment of specific dominant rhizosphere microbes and their vital roles play a significant role in conferring high salt adaptability to these varieties

BAM15 as a mitochondrial uncoupler: a promising therapeutic agent for diverse diseases

Subcellular organelles dysfunction is implicated in various diseases, including metabolic diseases, neurodegenerative diseases, cancer, and cardiovascular diseases. BAM15, a selective mitochondrial uncoupler, has emerged as a promising therapeutic agent due to its ability to enhance mitochondrial respiration and metabolic flexibility. By disrupting the coupling between electron transport and ATP synthesis, BAM15 dissipates the proton gradient, leading to increased mitochondrial respiration and energy expenditure. This review provides a comprehensive overview of BAM15, including its mechanism of action and potential therapeutic applications in diverse disease contexts. BAM15 has shown promise in obesity by increasing energy expenditure and reducing fat accumulation. In diabetes, it improves glycemic control and reverses insulin resistance. Additionally, BAM15 has potential in non-alcoholic fatty liver disease, sepsis, and cardiovascular diseases by mitigating oxidative stress, modulating inflammatory responses, and promoting cardioprotection. The safety profile of BAM15 is encouraging, with minimal adverse effects and remarkable tolerability. However, challenges such as its high lipophilicity and the need for alternative delivery methods need to be addressed. Further research is necessary to fully understand the therapeutic potential of BAM15 and optimize its application in clinical settings

JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles.

International audienceJASPAR (http://jaspar.genereg.net) is an open-access database storing curated, non-redundant transcription factor (TF) binding profiles representing transcription factor binding preferences as position frequency matrices for multiple species in six taxonomic groups. For this 2016 release, we expanded the JASPAR CORE collection with 494 new TF binding profiles (315 in vertebrates, 11 in nematodes, 3 in insects, 1 in fungi and 164 in plants) and updated 59 profiles (58 in vertebrates and 1 in fungi). The introduced profiles represent an 83% expansion and 10% update when compared to the previous release. We updated the structural annotation of the TF DNA binding domains (DBDs) following a published hierarchical structural classification. In addition, we introduced 130 transcription factor flexible models trained on ChIP-seq data for vertebrates, which capture dinucleotide dependencies within TF binding sites. This new JASPAR release is accompanied by a new web tool to infer JASPAR TF binding profiles recognized by a given TF protein sequence. Moreover, we provide the users with a Ruby module complementing the JASPAR API to ease programmatic access and use of the JASPAR collection of profiles. Finally, we provide the JASPAR2016 R/Bioconductor data package with the data of this release

JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles.

International audienceJASPAR (http://jaspar.genereg.net) is an open-access database storing curated, non-redundant transcription factor (TF) binding profiles representing transcription factor binding preferences as position frequency matrices for multiple species in six taxonomic groups. For this 2016 release, we expanded the JASPAR CORE collection with 494 new TF binding profiles (315 in vertebrates, 11 in nematodes, 3 in insects, 1 in fungi and 164 in plants) and updated 59 profiles (58 in vertebrates and 1 in fungi). The introduced profiles represent an 83% expansion and 10% update when compared to the previous release. We updated the structural annotation of the TF DNA binding domains (DBDs) following a published hierarchical structural classification. In addition, we introduced 130 transcription factor flexible models trained on ChIP-seq data for vertebrates, which capture dinucleotide dependencies within TF binding sites. This new JASPAR release is accompanied by a new web tool to infer JASPAR TF binding profiles recognized by a given TF protein sequence. Moreover, we provide the users with a Ruby module complementing the JASPAR API to ease programmatic access and use of the JASPAR collection of profiles. Finally, we provide the JASPAR2016 R/Bioconductor data package with the data of this release

Human impact overwhelms long-term climate control of fire in the Yangtze River Basin since 3.0 ka BP

A high-resolution fire history in the Yangtze River Basin over the past 7.0 ka BP is reconstructed based on the proxy of black carbon of sediment core ECMZ on the continental shelf of the East China Sea in order to reveal the interactions among fire, climate, vegetation and human activity on a regional scale. A comparison of fire activity with climatic and vegetation proxies suggests that changes in fire activity prior to 3.0 ka BP on both millennial- and centennial-timescales were closely related to variations in temperature and precipitation, with more fire during warm and humid periods, suggesting climatic control on regional fire activities. In contrast, the significant decoupling between fire and climate on multi-timescales since similar to 3.0 ka BP implies increasing anthropogenic impact on regional fire activity. There is also a distinct response of fire activity to human disturbance at different time scales. Long-term reduction in regional fire activity since similar to 3.0 ka BP was caused by a general decrease in forest cover with increasing human activity while short-term (centennial-timescale) enhancement in biomass burning usually coincides with periods characterized by increasing human activity associated with population migration or technological advances. (C) 2020 Elsevier Ltd. All rights reserved

Estimation of cancer incidence and mortality attributable to alcohol drinking in china

Background. Cancer constitutes a serious burden of disease worldwide and has become the second leading cause of death in China. Alcohol consumption is causally associated with the increased risk of certain cancers. Due to the current lack of data and the imperative need to guide policymakers on issues of cancer prevention and control, we aim to estimate the role of alcohol on the cancer burden in China in 2005. Methods. We calculated the proportion of cancers attributable to alcohol use to estimate the burden of alcohol-related cancer. The population attributable fraction was calculated based on the assumption of no alcohol drinking. Data on alcohol drinking prevalence were from two large-scale national surveys of representative samples of the Chinese population. Data on relative risk were obtained from meta-analyses and large-scale studies. Results. We found that a total of 78,881 cancer deaths were attributable to alcohol drinking in China in 2005, representing 4.40% of all cancers (6.69% in men, 0.42% in women). The corresponding figure for cancer incidence was 93,596 cases (3.63% of all cancer cases). Liver cancer was the main alcohol-related cancer, contributing more than 60% of alcohol-related cancers. Conclusions. Particular attention needs to be paid to the harm of alcohol as well as its potential benefits when making public health recommendations on alcohol drinking. \ua9 2010 Liang et al; licensee BioMed Central Ltd

Intermolecular coupling enhanced thermopower in single- molecule diketopyrrolopyrrole junctions

Sorting out organic molecules with high thermopower is essential for understanding molecular thermoelectrics. The intermolecular coupling offers a unique chance to enhance the thermopower by tuning the bandgap structure of molecular devices, but the investigation of intermolecular coupling in bulk materials remains challenging. Herein, we investigated the thermopower of diketopyrrolopyrrole (DPP) cored single-molecule junctions with different coupling strengths by varying the packing density of the self-assembled monolayers (SAM) using a customized scanning tunneling microscope break junction (STM-BJ) technique. We found that the thermopower of DPP molecules could be enhanced up to one order of magnitude with increasing packing density, suggesting that the thermopower increases with larger neighboring intermolecular interactions. The combined density functional theory (DFT) calculations revealed that the closely-packed configuration brings stronger intermolecular coupling and then reduces the highest occupied molecular orbital (HOMO)-lowest unoccupied molecular orbital (LUMO) gap, leading to an enhanced thermopower. Our findings offer a new strategy for developing organic thermoelectric devices with high thermopower