A Typha Angustifolia-like MoS2/carbon nanofiber composite for high performance Li-S batteries

A Typha Angustifolia-like MoS2/carbon nanofiber composite as both a chemically trapping agent and redox conversion catalyst for lithium polysulfides has been successfully synthesized via a simple hydrothermal method. Cycling performance and coulombic efficiency have been improved significantly by applying the Typha Angustifolia-like MoS2/carbon nanofiber as the interlayer of a pure sulfur cathode, resulting in a capacity degradation of only 0.09% per cycle and a coulombic efficiency which can reach as high as 99%

SNP discovery by high-throughput sequencing in soybean

<p>Abstract</p> <p>Background</p> <p>With the advance of new massively parallel genotyping technologies, quantitative trait loci (QTL) fine mapping and map-based cloning become more achievable in identifying genes for important and complex traits. Development of high-density genetic markers in the QTL regions of specific mapping populations is essential for fine-mapping and map-based cloning of economically important genes. Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variation existing between any diverse genotypes that are usually used for QTL mapping studies. The massively parallel sequencing technologies (Roche GS/454, Illumina GA/Solexa, and ABI/SOLiD), have been widely applied to identify genome-wide sequence variations. However, it is still remains unclear whether sequence data at a low sequencing depth are enough to detect the variations existing in any QTL regions of interest in a crop genome, and how to prepare sequencing samples for a complex genome such as soybean. Therefore, with the aims of identifying SNP markers in a cost effective way for fine-mapping several QTL regions, and testing the validation rate of the putative SNPs predicted with Solexa short sequence reads at a low sequencing depth, we evaluated a pooled DNA fragment reduced representation library and SNP detection methods applied to short read sequences generated by Solexa high-throughput sequencing technology.</p> <p>Results</p> <p>A total of 39,022 putative SNPs were identified by the Illumina/Solexa sequencing system using a reduced representation DNA library of two parental lines of a mapping population. The validation rates of these putative SNPs predicted with low and high stringency were 72% and 85%, respectively. One hundred sixty four SNP markers resulted from the validation of putative SNPs and have been selectively chosen to target a known QTL, thereby increasing the marker density of the targeted region to one marker per 42 K bp.</p> <p>Conclusions</p> <p>We have demonstrated how to quickly identify large numbers of SNPs for fine mapping of QTL regions by applying massively parallel sequencing combined with genome complexity reduction techniques. This SNP discovery approach is more efficient for targeting multiple QTL regions in a same genetic population, which can be applied to other crops.</p

Arabidopsis Transcriptome Analysis Reveals Key Roles of Melatonin in Plant Defense Systems

Melatonin is a ubiquitous molecule and exists across kingdoms including plant species. Studies on melatonin in plants have mainly focused on its physiological influence on growth and development, and on its biosynthesis. Much less attention has been drawn to its affect on genome-wide gene expression. To comprehensively investigate the role(s) of melatonin at the genomics level, we utilized mRNA-seq technology to analyze Arabidopsis plants subjected to a 16-hour 100 pM (low) and 1 mM (high) melatonin treatment. The expression profiles were analyzed to identify differentially expressed genes. 100 pM melatonin treatment significantly affected the expression of only 81 genes with 51 down-regulated and 30 up-regulated. However, 1 mM melatonin significantly altered 1308 genes with 566 up-regulated and 742 down-regulated. Not all genes altered by low melatonin were affected by high melatonin, indicating different roles of melatonin in regulation of plant growth and development under low and high concentrations. Furthermore, a large number of genes altered by melatonin were involved in plant stress defense. Transcript levels for many stress receptors, kinases, and stress-associated calcium signals were up-regulated. The majority of transcription factors identified were also involved in plant stress defense. Additionally, most identified genes in ABA, ET, SA and JA pathways were up-regulated, while genes pertaining to auxin responses and signaling, peroxidases, and those associated with cell wall synthesis and modifications were mostly down-regulated. Our results indicate critical roles of melatonin in plant defense against various environmental stresses, and provide a framework for functional analysis of genes in melatonin-mediated signaling pathways

Natural Extracellular Electron Transfer Between Semiconducting Minerals and Electroactive Bacterial Communities Occurred on the Rock Varnish

Rock varnish is a thin coating enriched with manganese (Mn) and iron (Fe) oxides. The mineral composition and formation of rock varnish elicit considerable attention from geologists and microbiologists. However, limited research has been devoted to the semiconducting properties of these Fe/Mn oxides in varnish and relatively little attention is paid to the mineral–microbe interaction under sunlight. In this study, the mineral composition and the bacterial communities on varnish from the Gobi Desert in Xinjiang, China were analyzed. Results of principal components analysis and t-test indicated that more electroactive genera such as Acinetobacter, Staphylococcus, Dietzia, and Pseudomonas gathered on varnish bacterial communities than on substrate rock and surrounding soils. We then explored the culture of varnish, substrate and soil samples in media and the extracellular electron transfer (EET) between bacterial communities and mineral electrodes under light/dark conditions for the first time. Orthogonal electrochemical experiments demonstrated that the most remarkable photocurrent density of 6.1 ± 0.4 μA/cm2 was observed between varnish electrode and varnish microflora. Finally, based on Raman and 16S rRNA gene–sequencing results, coculture system of birnessite and Pseudomonas (the major Mn oxide and a common electroactive bacterium in varnish) was established to study underlying mechanism. A steadily growing photocurrent (205 μA at 100 h) under light was observed with a stable birnessite after 110 h. However, only 47 μA was generated in the dark control and birnessite was reduced to Mn2+ in 13 h, suggesting that birnessite helped deliver electrons instead of serving as an electron acceptor under light. Our study demonstrated that electroactive bacterial communities were positively correlated with Fe/Mn semiconducting minerals in varnish, and diversified EET process occurred on varnish under sunlight. Overall, these phenomena may influence bacterial–community structure in natural environments over time

The Epitope Study on the SARS-CoV Nucleocapsid Protein

The nucleocapsid protein (N protein) has been found to be an antigenic protein in a number of coronaviruses. Whether the N protein in severe acute respiratory syndrome-associated coronavirus (SARS-CoV) is antigenic remains to be elucidated. Using Western blot and Enzyme-linked Immunosorbent Assay (ELISA), the recombinant N proteins and the synthesized peptides derived from the N protein were screened in sera from SARS patients. All patient sera in this study displayed strong positive immunoreactivities against the recombinant N proteins, whereas normal sera gave negative immunoresponses to these proteins, indicating that the N protein of SARS-CoV is an antigenic protein. Furthermore, the epitope sites in the N protein were determined by competition experiments, in which the recombinant proteins or the synthesized peptides competed against the SARS-CoV proteins to bind to the antibodies raised in SARS sera. One epitope site located at the C-terminus was confirmed as the most antigenic region in this protein. A detailed screening of peptide with ELISA demonstrated that the amino sequence from Codons 371 to 407 was the epitope site at the C-terminus of the N protein. Understanding of the epitope sites could be very significant for developing an effective diagnostic approach to SARS

Non-destructive 3D Microtomography of Cerebral Angioarchitecture Changes Following Ischemic Stroke in Rats Using Synchrotron Radiation

A better understanding of functional changes in the cerebral microvasculature following ischemic injury is essential to elucidate the pathogenesis of stroke. Up to now, the simultaneous depiction and stereological analysis of 3D micro-architectural changes of brain vasculature with network disorders remains a technical challenge. We aimed to explore the three dimensional (3D) microstructural changes of microvasculature in the rat brain on 4, 6 hours, 3 and 18 days post-ischemia using synchrotron radiation micro-computed tomography (SRμCT) with a per pixel size of 5.2 μm. The plasticity of angioarchitecture was distinctly visualized. Quantitative assessments of time-related trends after focal ischemia, including number of branches, number of nodes, and frequency distribution of vessel diameter, reached a peak at 6 h and significantly decreased at 3 days and initiated to form cavities. The detected pathological changes were also proven by histological tests. We depicted a novel methodology for the 3D analysis of vascular repair in ischemic injury, both qualitatively and quantitatively. Cerebral angioarchitecture sustained 3D remodeling and modification during the healing process. The results might provide a deeper insight into the compensatory mechanisms of microvasculature after injury, suggesting that SRμCT is able to provide a potential new platform for deepening imaging pathological changes in complicated angioarchitecture and evaluating potential therapeutic targets for stroke

A Survey of Large Language Models

Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for comprehending and grasping a language. As a major approach, language modeling has been widely studied for language understanding and generation in the past two decades, evolving from statistical language models to neural language models. Recently, pre-trained language models (PLMs) have been proposed by pre-training Transformer models over large-scale corpora, showing strong capabilities in solving various NLP tasks. Since researchers have found that model scaling can lead to performance improvement, they further study the scaling effect by increasing the model size to an even larger size. Interestingly, when the parameter scale exceeds a certain level, these enlarged language models not only achieve a significant performance improvement but also show some special abilities that are not present in small-scale language models. To discriminate the difference in parameter scale, the research community has coined the term large language models (LLM) for the PLMs of significant size. Recently, the research on LLMs has been largely advanced by both academia and industry, and a remarkable progress is the launch of ChatGPT, which has attracted widespread attention from society. The technical evolution of LLMs has been making an important impact on the entire AI community, which would revolutionize the way how we develop and use AI algorithms. In this survey, we review the recent advances of LLMs by introducing the background, key findings, and mainstream techniques. In particular, we focus on four major aspects of LLMs, namely pre-training, adaptation tuning, utilization, and capacity evaluation. Besides, we also summarize the available resources for developing LLMs and discuss the remaining issues for future directions.Comment: ongoing work; 51 page

Reliability analysis of the Ahringer Caenorhabditis elegans RNAi feeding library: a guide for genome-wide screens

<p>Abstract</p> <p>Background</p> <p>The Ahringer <it>C. elegans </it>RNAi feeding library prepared by cloning genomic DNA fragments has been widely used in genome-wide analysis of gene function. However, the library has not been thoroughly validated by direct sequencing, and there are potential errors, including: 1) mis-annotation (the clone with the retired gene name should be remapped to the actual target gene); 2) nonspecific PCR amplification; 3) cross-RNAi; 4) mis-operation such as sample loading error, <it>etc</it>.</p> <p>Results</p> <p>Here we performed a reliability analysis on the Ahringer <it>C. elegans </it>RNAi feeding library, which contains 16,256 bacterial strains, using a bioinformatics approach. Results demonstrated that most (98.3%) of the bacterial strains in the library are reliable. However, we also found that 2,851 (17.54%) bacterial strains need to be re-annotated even they are reliable. Most of these bacterial strains are the clones having the retired gene names. Besides, 28 strains are grouped into unreliable category and 226 strains are marginal because of probably expressing unrelated double-stranded RNAs (dsRNAs). The accuracy of the prediction was further confirmed by direct sequencing analysis of 496 bacterial strains. Finally, a freely accessible database named CelRNAi (<url>http://biocompute.bmi.ac.cn/CelRNAi/</url>) was developed as a valuable complement resource for the feeding RNAi library by providing the predicted information on all bacterial strains. Moreover, submission of the direct sequencing result or any other annotations for the bacterial strains to the database are allowed and will be integrated into the CelRNAi database to improve the accuracy of the library. In addition, we provide five candidate primer sets for each of the unreliable and marginal bacterial strains for users to construct an alternative vector for their own RNAi studies.</p> <p>Conclusions</p> <p>Because of the potential unreliability of the Ahringer <it>C. elegans </it>RNAi feeding library, we strongly suggest the user examine the reliability information of the bacterial strains in the CelRNAi database before performing RNAi experiments, as well as the post-RNAi experiment analysis.</p