PhosMap: An ensemble bioinformatic platform to empower interactive analysis of quantitative phosphoproteomics.

BACKGROUND: Liquid chromatography-mass spectrometry (LC-MS)-based quantitative phosphoproteomics has been widely used to detect thousands of protein phosphorylation modifications simultaneously from the biological specimens. However, the complicated procedures for analyzing phosphoproteomics data has become a bottleneck to widening its application. METHODS: Here, we develop PhosMap, a versatile and scalable tool to accomplish phosphoproteomics data analysis. A standardized phosphorylation data format was created for data analyses, from data preprocessing to downstream bioinformatic analyses such as dimension reduction, differential phosphorylation analysis, kinase activity, survival analysis, and so on. For better usability, we distribute PhosMap as a Docker image for easy local deployment upon any of Windows, Linux, and Mac system. RESULTS: The source code is deposited at https://github.com/BADD-XMU/PhosMap. A free PhosMap webserver (https://huggingface.co/spaces/Bio-Add/PhosMap), with easy-to-follow fashion of dashboards, is curated for interactive data analysis. CONCLUSIONS: PhosMap fills the technical gap of large-scale phosphorylation research by empowering researchers to process their own phosphoproteomics data expediently and efficiently, and facilitates better data interpretation.

Epigenome-augmented eQTL-hotspots reveal genome-wide transcriptional programs in 36 human tissues.

Expression quantitative trait loci (eQTLs) are used to inform the mechanisms of transcriptional regulation in eukaryotic cells. However, the specificity of genome-wide eQTL identification is limited by stringent control for false discoveries. Here, we described a method based on the non-homogeneous Poisson process to identify 125 489 regions with highly frequent, multiple eQTL associations, or 'eQTL-hotspots', from the public database of 59 human tissues or cell types. We stratified the eQTL-hotspots into two classes with their distinct sequence and epigenomic characteristics. Based on these classifications, we developed a machine-learning model, E-SpotFinder, for augmented discovery of tissue- or cell-type-specific eQTL-hotspots. We applied this model to 36 tissues or cell types. Using augmented eQTL-hotspots, we recovered 655 402 eSNPs and reconstructed a comprehensive regulatory network of 2 725 380 cis-interactions among eQTL-hotspots. We further identified 52 012 modules representing transcriptional programs with unique functional backgrounds. In summary, our study provided a framework of epigenome-augmented eQTL analysis and thereby constructed comprehensive genome-wide networks of cis-regulations across diverse human tissues or cell types.

The application of plasma technology for the preparation of supercapacitor electrode materials.

With the rapidly growing demand for clean energy and energy interconnection, there is an urgent need for rapid and high-capacity energy storage technologies to realize large-scale energy storage, transfer energy, and establish the energy internet. Supercapacitors, which have advantages such as high specific capacitance, fast charging and discharging rates, and long cycle lifetimes, are being widely used in electric vehicles, information technology, aerospace, and other fields. The performance of supercapacitors is crucially dependent on electrode materials. These can be categorized into electric double-layer capacitors and pseudocapacitors, primarily made from carbon and transition metal oxides, respectively. However, effectively monitoring the physicochemical properties of electrode materials during preparation and processing is challenging, which limits the improvement of supercapacitors' performance. Plasma materials preparation technology can effectively affect the materials preparation processing by energetic electrons, ions, free radicals, and multiple effects in plasma, which are easily manipulated by operation parameters. Therefore, plasma material preparation technology is considered a promising method to precisely monitor the physicochemical and electrochemical properties of energy storage materials and has been widely studied. This paper provides an overview of plasma materials preparation mechanisms, and details of the plasma technology application in the preparation of transition metal hybrids, carbon, and composite electrode materials, as well as a comparison with traditional methods. In conclusion, the advantages, challenges, and research directions of plasma materials preparation technology in the field of electrode materials preparation are summarized.

Unveiling the Role of Ge in CZTSSe Solar Cells by Advanced Micro-To-Atom Scale Characterizations.

Kesterite is an earth-abundant energy material with high predicted power conversion efficiency, making it a sustainable and promising option for photovoltaics. However, a large open circuit voltage Voc deficit due to non-radiative recombination at intrinsic defects remains a major hurdle, limiting device performance. Incorporating Ge into the kesterite structure emerges as an effective approach for enhancing performance by manipulating defects and morphology. Herein, how different amounts of Ge affect the kesterite growth pathways through the combination of advanced microscopy characterization techniques are systematically investigated. The results demonstrate the significance of incorporating Ge during the selenization process of the CZTSSe thin film. At high temperature, the Ge incorporation effectively delays the selenization process due to the formation of a ZnSe layer on top of the metal alloys through decomposition of the Cu-Zn alloy and formation of Cu-Sn alloy, subsequently forming of Cu-Sn-Se phase. Such an effect is compounded by more Ge incorporation that further postpones kesterite formation. Furthermore, introducing Ge mitigates detrimental "horizontal" grain boundaries by increasing the grain size on upper layer. The Ge incorporation strategy discussed in this study holds great promise for improving device performance and grain quality in CZTSSe and other polycrystalline chalcogenide solar cells.

SIMarker: Cellular similarity detection and its application to diagnosis and prognosis of liver cancer.

BACKGROUND: The emergence of single-cell technology offers a unique opportunity to explore cellular similarity and heterogeneity between precancerous diseases and solid tumors. However, there is lacking a systematic study for identifying and characterizing similarities at single-cell resolution. METHODS: We developed SIMarker, a computational framework to detect cellular similarities between precancerous diseases and solid tumors based on gene expression at single-cell resolution. Taking hepatocellular carcinoma (HCC) as a case study, we quantified the cellular and molecular connections between HCC and cirrhosis. Core analysis modules of SIMarker is publicly available at https://github.com/xmuhuanglab/SIMarker ("SIM" means "similarity" and "Marker" means "biomarkers). RESULTS: We found PGA5+ hepatocytes in HCC showed cirrhosis-like characteristics, including similar transcriptional programs and gene regulatory networks. Consequently, the genes constituting the gene expression program of these cirrhosis-like subpopulations were designated as cirrhosis-like signatures (CLS). Strikingly, our utilization of CLS enabled the development of diagnosis and prognosis biomarkers based on within-sample relative expression orderings of gene pairs. These biomarkers achieved high precision and concordance compared with previous studies. CONCLUSIONS: Our work provides a systematic method to investigate the clinical translational significance of cellular similarities between HCC and cirrhosis, which opens avenues for identifying similar paradigms in other categories of cancers and diseases.

PI3K/Akt signaling pathway mediates the effect of low-dose boron on barrier function, proliferation and apoptosis in rat intestinal epithelial cells.

Boron is an essential trace element with roles in growth, development, and physiological functions; however, its mechanism of action is still unclear. In this study, the regulatory roles of the PI3K/Akt signaling pathway on boron-induced changes in barrier function, proliferation, and apoptosis in rat intestinal epithelial cells were evaluated. Occludin levels, the proportion of cells in the G2/M phase, cell proliferation rate, and mRNA and protein expression levels of PCNA were higher, while the proportions of cells in the G0/G1 and S phases, apoptosis rate, and caspase-3 mRNA and protein expression levels were lower in cells treated with 0.8 mmol/L boron than in control IEC-6 cells (P < 0.01 or P < 0.05). However, 40 mmol/L boron decreased ZO-1 and Occludin levels, the proportion of cells in the G2/M phase, cell proliferation rate, and mRNA and protein levels of PCNA and increased the apoptosis rate and caspase-3 mRNA expression (P < 0.01 or P < 0.05). After specifically blocking PI3K and Akt signals (using LY294002 and MK-2206 2HCL), 0.8 mmol/L boron had no effects on Occludin, PCNA level, apoptosis rates, and caspase-3 levels (P < 0.05); however, the proliferation rate and PCNA levels decreased significantly (P < 0.01 or P < 0.05). The addition of 40 mmol/L boron did not affect ZO-1 and Occludin levels and did not affect the apoptosis rate or PCNA and caspase-3 levels. These results suggested that the PI3K/Akt signaling pathway mediates the effects of low-dose boron on IEC-6 cells.

Cd-Free Pure Sulfide Kesterite Cu2 ZnSnS4 Solar Cell with Over 800 mV Open-Circuit Voltage Enabled by Phase Evolution Intervention.

The Cd-free Cu2 ZnSnS4 (CZTS) solar cell is an ideal candidate for producing low-cost clean energy through green materials owing to its inherent environmental friendliness and earth abundance. Nevertheless, sulfide CZTS has long suffered from severe open-circuit voltage (VOC ) deficits, limiting the full exploitation of performance potential and further progress. Here, an effective strategy is proposed to alleviate the nonradiative VOC loss by manipulating the phase evolution during the critical kesterite phase formation stage. With a Ge cap layer on the precursor, premature CZTS grain formation is suppressed at low temperatures, leading to fewer nucleation centers at the initial crystallization stage. Consequently, the CZTS grain formation and crystallization are deferred to high temperatures, resulting in enhanced grain interior quality and less unfavorable grain boundaries in the final film. As a result, a champion efficiency of 10.7% for Cd-free CZTS solar cells with remarkably high VOC beyond 800 mV (63.2% Schockley-Queisser limit) is realized, indicating that nonradiative recombination is effectively inhibited. This strategy may advance other compound semiconductors seeking high-quality crystallization.

CovidShiny: An Integrated Web Tool for SARS-CoV-2 Mutation Profiling and Molecular Diagnosis Assay Evaluation In Silico.

The coronavirus disease 2019 (COVID-19) pandemic is still ongoing, with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continuing to evolve and accumulate mutations. While various bioinformatics tools have been developed for SARS-CoV-2, a well-curated mutation-tracking database integrated with in silico evaluation for molecular diagnostic assays is currently unavailable. To address this, we introduce CovidShiny, a web tool that integrates mutation profiling, in silico evaluation, and data download capabilities for genomic sequence-based SARS-CoV-2 assays and data download. It offers a feasible framework for surveilling the mutation of SARS-CoV-2 and evaluating the coverage of the molecular diagnostic assay for SARS-CoV-2. With CovidShiny, we examined the dynamic mutation pattern of SARS-CoV-2 and evaluated the coverage of commonly used assays on a large scale. Based on our in silico analysis, we stress the importance of using multiple target molecular diagnostic assays for SARS-CoV-2 to avoid potential false-negative results caused by viral mutations. Overall, CovidShiny is a valuable tool for SARS-CoV-2 mutation surveillance and in silico assay design and evaluation.

Bifacial and Semitransparent Sb2 (S,Se)3 Solar Cells for Single-Junction and Tandem Photovoltaic Applications.

Thin-film solar cells are expected to play a significant role in the space industry, building integrated photovoltaic (BIPV), indoor applications, and tandem solar cells, where bifaciality and semitransparency are highly desired. Sb2 (S,Se)3 has emerged as a promising new photovoltaic (PV) material for its high absorption coefficient, tunable bandgap, and nontoxic and earth-abundant constituents. However, high-efficiency Sb2 (S,Se)3 solar cells exclusively employ monofacial architectures, leaving a considerable gap toward large-scale application in aforementioned fields. Here, a bifacial and semitransparent Sb2 (S,Se)3 solar cell and its extended application in tandem solar cells are reported. The transparent conductive oxides (TCOs) and the ultrathin inner n-i-p structure provide high long-wavelength transmittance. Despite the MnS/ITO Schottky junction, power conversion efficiencies (PCEs) of 7.41% and 6.36% are achieved with front and rear illumination, respectively, contributing to a great bifaciality of 0.86. Consequently, the reported device gains great enhancement in PV performance by exploiting albedo of surroundings and shows exceptional capability in absorbing tilt incident light. Moreover, an Sb2 (S,Se)3 /Si tandem solar cell with a PCE of 11.66% is achieved in preliminary trials. These exciting findings imply that bifacial and semitransparent Sb2 (S,Se)3 solar cells possess tremendous potential in practical applications based on their unique characteristics.

Activatable BODIPY-chromene NIR-II probes with small spectral crosstalk enable high-contrast in vivo bioimaging.

Herein, we design a novel "crossbreeding" dye (BC-OH) within the second near-infrared (NIR-II) window based on BODIPY and chromene chromophores. BC-OH can serve as a platform to construct activatable NIR-II probes with small spectral crosstalk, thereby making a breakthrough in imaging in vivo H2O2 fluctuation in an APAP-induced liver injury model with high signal-to-background ratio.

The glycolysis/HIF-1α axis defines the inflammatory role of IL-4-primed macrophages.

T helper type 2 (Th2) cytokine-activated M2 macrophages contribute to inflammation resolution and wound healing. This study shows that IL-4-primed macrophages exhibit a stronger response to lipopolysaccharide stimulation while maintaining M2 signature gene expression. Metabolic divergence between canonical M2 and non-canonical proinflammatory-prone M2 (M2INF) macrophages occurs after the IL-4Rα/Stat6 axis. Glycolysis supports Hif-1α stabilization and proinflammatory phenotype of M2INF macrophages. Inhibiting glycolysis blunts Hif-1α accumulation and M2INF phenotype. Wdr5-dependent H3K4me3 mediates the long-lasting effect of IL-4, with Wdr5 knockdown inhibiting M2INF macrophages. Our results also show that the induction of M2INF macrophages by IL-4 intraperitoneal injection and transferring of M2INF macrophages confer a survival advantage against bacterial infection in vivo. In conclusion, our findings highlight the previously neglected non-canonical role of M2INF macrophages and broaden our understanding of IL-4-mediated physiological changes. These results have immediate implications for how Th2-skewed infections could redirect disease progression in response to pathogen infection.

Prioritizing prognostic-associated subpopulations and individualized recurrence risk signatures from single-cell transcriptomes of colorectal cancer.

Colorectal cancer (CRC) is one of the most common gastrointestinal malignancies. There are few recurrence risk signatures for CRC patients. Single-cell RNA-sequencing (scRNA-seq) provides a high-resolution platform for prognostic signature detection. However, scRNA-seq is not practical in large cohorts due to its high cost and most single-cell experiments lack clinical phenotype information. Few studies have been reported to use external bulk transcriptome with survival time to guide the detection of key cell subtypes in scRNA-seq data. We proposed scRankXMBD, a computational framework to prioritize prognostic-associated cell subpopulations based on within-cell relative expression orderings of gene pairs from single-cell transcriptomes. scRankXMBD achieves higher precision and concordance compared with five existing methods. Moreover, we developed single-cell gene pair signatures to predict recurrence risk for patients individually. Our work facilitates the application of the rank-based method in scRNA-seq data for prognostic biomarker discovery and precision oncology. scRankXMBD is available at https://github.com/xmuyulab/scRank-XMBD. (XMBD:Xiamen Big Data, a biomedical open software initiative in the National Institute for Data Science in Health and Medicine, Xiamen University, China.).

Insights into multisource sludge distributed in the Yangtze River basin, China: Characteristics, correlation, treatment and disposal.

Sludge is the by-product of wastewater treatment process. Multisource sludge can be defined as sludge from different sources. Based on the sludge properties of five typical cities in the Yangtze River basin, including Jiujiang, Wuhu, Lu'an, Zhenjiang and Wuhan, this study investigated and summarized the characteristic variations and distribution differences of multiple indicators and substances from municipal sludge, dredged sludge, and river and lake sediments. The results demonstrated pH of multisource sludge was relatively stable in the neutral range. Organic matter and water content among municipal sludge were high and varied considerably between different wastewater treatment plants. Dredged sludge had an obviously higher sand content and wider particle distribution, which could be considered for graded utilization depending on its size. The nutrients composition of river and lake sediments was usually stable and special, with lower nitrogen and phosphorus content but higher potassium levels. The sources of heavy metals and persistent organic pollutants in multisource sludge were correlated, generally much higher among municipal sludge than dredged sludge and river and lake sediments, which were the most important limitation for final land utilization. Despite various properties of multisource sludge, the final fate and destination have some overall similarities, which need to be supplemented and improved by standards and laws. The study provided a preliminary analysis of suitable technical routes for municipal sludge, dredged sludge, river and lake sediments based on their different characteristics respectively, which was of great significance for multisource sludge co-treatment and disposal in the future of China.

Complexity of enhancer networks predicts cell identity and disease genes revealed by single-cell multi-omics analysis.

Many enhancers exist as clusters in the genome and control cell identity and disease genes; however, the underlying mechanism remains largely unknown. Here, we introduce an algorithm, eNet, to build enhancer networks by integrating single-cell chromatin accessibility and gene expression profiles. The complexity of enhancer networks is assessed by two metrics: the number of enhancers and the frequency of predicted enhancer interactions (PEIs) based on chromatin co-accessibility. We apply eNet algorithm to a human blood dataset and find cell identity and disease genes tend to be regulated by complex enhancer networks. The network hub enhancers (enhancers with frequent PEIs) are the most functionally important. Compared with super-enhancers, enhancer networks show better performance in predicting cell identity and disease genes. eNet is robust and widely applicable in various human or mouse tissues datasets. Thus, we propose a model of enhancer networks containing three modes: Simple, Multiple and Complex, which are distinguished by their complexity in regulating gene expression. Taken together, our work provides an unsupervised approach to simultaneously identify key cell identity and disease genes and explore the underlying regulatory relationships among enhancers in single cells.

A controllable SERS biosensor for ultrasensitive detection of miRNAs based on porous MOFs and subject-object recognition ability.

In this work, a simple and sensitive SERS-based miRNA biosensor was constructed based on porous MOFs nanoparticles and efficient subject-object recognition ability. MOFs as a container can package lots of signal probe neutral red (NR) for the advantages of three dimensional structure and porosity. The partially complementary duplex DNA can as a "lock" to lock up the hole for obtaining a weak Raman signal. In the present of miRNA, miRNA just like a "key" to open the duplex structure with the results of releasing NR. At this time, the released NR can be captured by SERS substrate AuNS@CB[7] for the subject-object recognition ability to produce a strong Raman signal which was positive correlation to target miRNA. By this way, the proposed SERS biosensor can achieve sensitively and selectively detect miRNA with a detection limit of 0.562 fM. This MOF-based SERS biosensor also be hopeful application for clinical diagnostics.

Hericium erinaceus polysaccharide improves the microstructure, immune function, proliferation and reduces apoptosis of thymus and spleen tissue cells of immunosuppressed mice.

In order to study the effect of Hericium erinaceus polysaccharide (HEP) on the immune and antioxidation functions of immunosuppressed mice. The control group received distilled water orally and the model and experimental groups I, II, and III received 0, 80, 160, and 320 mg/kg HEP respectively for a fortnight after re-molding with cyoclphosphnalide (CTX). Compared with the control group, the secretion of IL-2, IL-4, and IFN-γ, the activity or content of T-AOC, T-SOD, and GSH-PX, and the expression of PCNA mRNA in the thymus and spleen were reduced in immunosuppressed mice (P < .05 or P < .01). Compared with immunosuppressed mice, the levels of IL-2, IFN-γ, and GSH-PX and the PCNA mRNA expression of spleen and thymus were increased (P < .05 or P < .01), and the microstructure were also obviously improved in the experimental group III. Overall, 320 mg/kg of HEP significantly improved the immune and antioxidant functions.

Motivation crowding effects on the intention for continued use of gamified fitness apps: a mixed-methods approach.

It has become an emerging idea for fitness apps to be gamified to intrinsically and extrinsically motivate user's usage intention or behavior. For the long-term success of gamified fitness apps, understanding what and how various motivations affect continued use is critical. A combination of qualitative and quantitative methodologies was used to explore two research questions concerning gamified fitness applications. Specifically, the research questions focused on understanding the impacts of intrinsic and extrinsic motivations on continued usage. Additionally, the study aimed to investigate whether extrinsic motivations enhance or diminish the influence of intrinsic motivations. Results from qualitative study identified three intrinsic motivations (self-development, self-control and hedonic motivation) and two extrinsic motivations (social recognition and financial reward) in gamified fitness apps. Results from quantitative study indicated that intrinsic motivations (formed by self-development, self-control and hedonic motivation), financial reward and social recognition could significantly improve intention for continued use; and further, both financial reward and social recognition could crowd-in intrinsic motivations. This research offers insights into the phenomenon of motivation crowding effects on the intention to continue using gamified fitness apps.