Numerical simulation of lead-free vacancy ordered Cs 2 PtI 6 based perovskite solar cell using SCAPS-1D

In recent years, vacancy-ordered halide double perovskites have emerged as promising non-toxic and stable alternatives for their lead-based counterparts in optoelectronic applications. In particular, vacancy ordered Cs2PtI6 has emerged as a star material because of its high absorption coefficient, band gap of 1.37 eV, and long minority carrier lifetime. Despite substantial experimental research on this new class of material, theoretical simulations of their device properties remain scarce. In this work, a novel n-i-p device architecture (FTO/SnO2/Cs2PtI6/MoO3/C) is theoretically investigated using a solar cell capacitance simulator (SCAPS-1D). Theoretical investigations are carried out in order to optimize the device performance structure by varying the perovskite and selective charge transport layer thickness, absorber and interface defect density, operating temperature, back contact, series and shunt resistance, respectively. The optimized device showed an impressive power conversion efficiency (PCE) of 23.52% at 300 K, which is higher than the previously reported values. Subsequent analysis of the device's spectral response indicated that it possessed 98.9% quantum efficiency (QE) and was visibly active. These findings will provide theoretical guidelines for enhancing the performance of Cs2PtI6-based photovoltaic solar cells (PSCs) and pave the way for the widespread implementation of environmentally benign and stable perovskites

CR Cistrome: a ChIP-Seq database for chromatin regulators and histone modification linkages in human and mouse

Diversified histone modifications (HMs) are essential epigenetic features. They play important roles in fundamental biological processes including transcription, DNA repair and DNA replication. Chromatin regulators (CRs), which are indispensable in epigenetics, can mediate HMs to adjust chromatin structures and functions. With the development of ChIP-Seq technology, there is an opportunity to study CR and HM profiles at the whole-genome scale. However, no specific resource for the integration of CR ChIP-Seq data or CR-HM ChIP-Seq linkage pairs is currently available. Therefore, we constructed the CR Cistrome database, available online at http://compbio.tongji.edu.cn/cr and http://cistrome.org/cr/, to further elucidate CR functions and CR-HM linkages. Within this database, we collected all publicly available ChIP-Seq data on CRs in human and mouse and categorized the data into four cohorts: the reader, writer, eraser and remodeler cohorts, together with curated introductions and ChIP-Seq data analysis results. For the HM readers, writers and erasers, we provided further ChIP-Seq analysis data for the targeted HMs and schematized the relationships between them. We believe CR Cistrome is a valuable resource for the epigenetics community

Active anti-acetylcholinesterase component of secondary metabolites produced by the endophytic fungi of Huperzia serrata

Background: An endophytic fungus lives within a healthy plant during certain stages of, or throughout, its life cycle. Endophytic fungi do not always cause plant disease, and they include fungi that yield different effects, including mutual benefit, and neutral and pathogenic effects. Endophytic fungi promote plant growth, improve the host plant's resistance to biotic and abiotic stresses, and can produce the same or similar biologically active substances as the host. Thus, endophytic fungal products have important implications in drug development. Result: Among the numerous endophytic fungi, we identified two strains, L10Q37 and LQ2F02, that have anti-acetylcholinesterase activity, but the active compound was not huperzine A. The aim of this study was to investigate the anti-acetylcholinesterase activity of secondary metabolites isolated from the endophytic fungi of Huperzia serrata . Microbial cultivation and fermentation were used to obtain secondary metabolites. Active components were then extracted from the secondary metabolites, and their activities were tracked. Two compounds that were isolated from endophytic fungi of H. serrata were identified and had acetylcholine inhibitory activities. In conclusion, endophytic fungal strains were found in H. serrata that had the same anti-acetylcholinesterase activity. Conclusion: We isolated 4 compounds from the endophytic fungus L10Q37, among them S1 and S3 are new compounds. 6 compounds were isolated from LQ2F02, all 6 compounds are new compounds. After tested anti acetylcholinesterase activity, S5 has the best activity. Other compounds' anti acetylcholinesterase activity was not better compared with huperzine A

Transcriptome profiling of genes regulated by phosphate-solubilizing bacteria Bacillus megaterium P68 in potato (Solanum tuberosum L.)

The insoluble phosphorus in the soil is extremely difficult to be absorbed and used directly through the potato root system. Although many studies have reported that phosphorus-solubilizing bacteria (PSB) can promote plant growth and uptake of phosphorus, the molecular mechanism of phosphorus uptake and growth by PSB has not been investigated yet. In the present study, PSB were isolated from rhizosphere soil in soybean. The data of potato yield and quality revealed that the strain P68 was the most effective In the present study, PSB identification, potato field experiment, pot experiment and transcriptome profiling to explored the role of PSB on potato growth and related molecular mechanisms. The results showed that the P68 strain (P68) was identified as Bacillus megaterium by sequencing, with a P-solubilizing ability of 461.86 mg·L−1 after 7-day incubation in National Botanical Research Institute’s Phosphate (NBRIP) medium. Compared with the control group (CK), P68 significantly increased the yield of potato commercial tubers by 17.02% and P accumulation by 27.31% in the field. Similarly, pot trials showed that the application of P68 significantly increased the biomass, total phosphorus content of the potato plants, and available phosphorus of the soil up by 32.33, 37.50, and 29.15%, respectively. Furthermore, the transcriptome profiling results of the pot potato roots revealed that the total number of bases was about 6G, and Q30 (%) was 92.35–94.8%. Compared with the CK, there were a total of 784 differential genes (DEGs) regulated when treated with P68, which 439 genes were upregulated and 345 genes were downregulated. Interestingly, most of the DEGs were mainly related to cellular carbohydrate metabolic process, photosynthesis, and cellular carbohydrate biosynthesis process. According to the KEGG pathway analysis, a total of 46 categorical metabolic pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database were annotated to 101 DEGs found in potato roots. Compared with the CK, most of the DEGs were mainly enriched in glyoxylate and dicarboxylate metabolism (sot00630), nitrogen metabolism (sot00910), tryptophan metabolism (sot00380), and plant hormone signal transduction (sot04075), and these DEGs might be involved in the interactions between Bacillus megaterium P68 and potato growth. The qRT-PCR analysis of differentially expressed genes showed that inoculated treatments P68 significantly upregulated expression of the phosphate transport, nitrate transport, glutamine synthesis, and abscisic acid regulatory pathways, respectively, and the data from qRT-PCR were consistent with that obtained from RNA-seq. In summary, PSB may be involved in the regulation of nitrogen and phosphorus nutrition, glutaminase synthesis, and abscisic acid-related metabolic pathways. This research would provide a new perspective for studying the molecular mechanism of potato growth promotion by PSB in the level of gene expression and related metabolic pathways in potato roots under the application of Bacillus megaterium P68

Performance for MIMO-RSN with Different Power Allocation Methods

Investigation in MIMO-RSN (Multi-input Multi-output radar sensor networks) is becoming more attractive in current literature. In a MIMO system, power allocation in accordance with the channel gain can significantly improve the system throughput performance. This paper investigates three power allocation methods in MIMO-RSN: water-filling, equal power and channel inversion. Their performances are analyzed in terms of target detection probability, false alarm rate, and amount of information for flat fading channels. Baker code is applied in the transmitting signal with different power control schemes to improve the target detection performance. The simulation results show that the water-filling in MIMO-RSN achieves the best detection performance while the channel inversion gets the worst

Biophysical properties as determinants for soil organic carbon and total nitrogen in grassland salinization.

Grassland salinization causes considerable changes to soil and vegetation, which can lead to changes in soil organic carbon (C) and total nitrogen (N). These changes have complex causal relationships. A significant correlation between soil organic C and total N and any soil or vegetation property does not necessarily imply a significant direct effect of the property on soil organic C and total N. In this study, a field survey was conducted to investigate the changes in soil organic C and total N in grassland along a salinity gradient in Hexi corridor, China, and the direct and indirect effects of soil and vegetation properties on both stocks were quantified using a path analysis approach. Significant decrease in soil organic C and total N contents were observed with increasing salinity. Both had significant positive correlations with the Normalized Difference Vegetation Index (NDVI), soil water, and fine particles (silt+clay) content (p<0.01) and significant negative correlations with soil EC, and sand content (p<0.01). NDVI, fine particles content and soil water content had positive direct effects on soil organic C and total N stocks. Soil EC affected soil organic C and total N stocks mainly through its indirect negative effect on NDVI, soil texture, and water content. NDVI, soil texture, and moisture also indirectly affected soil organic C and total N stocks via changes in each other. These indirect effects augmented each other, although in some cases indirect effects worked in opposing directions

The Prevalence and Characteristics of Mitral Regurgitation in Heart Failure: A Chart Review Study

Background: Mitral regurgitation (MR) is one of the common complications of heart failure (HF). The prevalence and characteristics of MR are rarely investigated, especially in the Chinese population. Objectives: The purpose of this study was to determine the prevalence and characteristics of non-organic MR in HF patients and subgroups defined by ejection fraction. Methods: A single-center, hospital-based, and retrospective chart review study included patients with heart failure admitted to the cardiovascular department from January 2017 to April 2020. Demographic characteristics, laboratory results, and echocardiogram results before discharge were analyzed in different groups defined by left ventricular ejection fraction (EF) using logistic regression and adjusted for confounders. Results: Finally, 2418 validated HF patients (age 67.2 ± 13.5 years; 68.03% men) were included. The prevalence of MR was 32.7% in HF, 16.7% in HF with preserve EF patients, 28.4% in HF with mid-range EF patients and 49.7% in HF with reduced EF (HFrEF) patients. In the HF with preserved EF group, multivariable logistic regression showed that 4 factors associated with MR including EF (odds ratio (OR) 0.954 (0.928–0.981), p = 0.001), left ventricular posterior wall thickness in diastolic phase (LVPWd) (OR 0.274 (0.081–0.932), p = 0.038), left atrium (LA) dimension (OR 2.049 (1.631–2.576), p < 0.001) and age (OR 1.024 (1.007–1.041), p = 0.007). In the HF with midrange EF group, multivariable logistic regression showed that 3 factors associated with MR including LA dimension (OR 2.009 (1.427–2.829), p < 0.001), triglycerides (TG) (OR 0.552 (0.359–0.849), p = 0.007) and digoxin (OR 2.836 (1.624–4.951), p < 0.001). In the HFrEF group, multivariable logistic regression showed that 7 factors associated with MR including EF (OR 0.969 (0.949–0.990), p = 0.004), (OR 0.161 (0.067–0.387), p < 0.001), LA dimension (OR 2.289 (1.821–2.878), p < 0.001), age (OR 1.016 (1.004–1.027)), p = 0.009), TG (OR 0.746 (0.595–0.936), p = 0.011), diuretics (OR 0.559 (0.334–0.934), p = 0.026) and ICD (OR 1.898 (1.074–3.354), p = 0.027). Conclusions: HF patients had a high burden of MR, particularly in the HFrEF group. Worsen cardiac structure (LA dimension and LVPWd) and function (EF), age, and medical treatment strategy played essential roles in MR

Dr.seq2: A quality control and analysis pipeline for parallel single cell transcriptome and epigenome data

<div><p>An increasing number of single cell transcriptome and epigenome technologies, including single cell ATAC-seq (scATAC-seq), have been recently developed as powerful tools to analyze the features of many individual cells simultaneously. However, the methods and software were designed for one certain data type and only for single cell transcriptome data. A systematic approach for epigenome data and multiple types of transcriptome data is needed to control data quality and to perform cell-to-cell heterogeneity analysis on these ultra-high-dimensional transcriptome and epigenome datasets. Here we developed Dr.seq2, a Quality Control (QC) and analysis pipeline for multiple types of single cell transcriptome and epigenome data, including scATAC-seq and Drop-ChIP data. Application of this pipeline provides four groups of QC measurements and different analyses, including cell heterogeneity analysis. Dr.seq2 produced reliable results on published single cell transcriptome and epigenome datasets. Overall, Dr.seq2 is a systematic and comprehensive QC and analysis pipeline designed for parallel single cell transcriptome and epigenome data. Dr.seq2 is freely available at: <a href="http://www.tongji.edu.cn/~zhanglab/drseq2/" target="_blank">http://www.tongji.edu.cn/~zhanglab/drseq2/</a> and <a href="https://github.com/ChengchenZhao/DrSeq2" target="_blank">https://github.com/ChengchenZhao/DrSeq2</a>.</p></div

Cell-clustering level QC and single-cell level QC for scATAC-seq data.

<p><b>A)</b> Upper panel shows cell-clustering results for combined scATAC samples generated from 3 different cell types. Bottom panel shows corresponding cell type labels of each cell marked by different colors (red stand for H1 cells, yellow stand for GM12878 cells and blue stand for K562 cells). The clustering step of Dr.seq2 clearly separated the scATAC-seq samples from three different cell types into different groups that were consistent with the cell type labels. B) Distribution of peak number for each single cell. C) Cell Clustering tree and peak region in each cell. The upper panel represents the hieratical clustering results based on each single cell. The second panel with different colors represents decision of cell clustering. The bottom two panels (heatmap and color bar) represent the “combined peaks” occupancy of each single cell. D) Barplot shows Silhouette score of each cluster. Silhouette method is used to interpret and validate the consistency within clusters defined in previous steps. E) Cluster specific regions in each chromosome. Specific regions for different cell clusters are marked by different colors and ordered according to genomic loci.</p