KnockTF 2.0: a comprehensive gene expression profile database with knockdown/knockout of transcription (co-)factors in multiple species.

Transcription factors (TFs), transcription co-factors (TcoFs) and their target genes perform essential functions in diseases and biological processes. KnockTF 2.0 (http://www.licpathway.net/KnockTF/index.html) aims to provide comprehensive gene expression profile datasets before/after T(co)F knockdown/knockout across multiple tissue/cell types of different species. Compared with KnockTF 1.0, KnockTF 2.0 has the following improvements: (i) Newly added T(co)F knockdown/knockout datasets in mice, Arabidopsis thaliana and Zea mays and also an expanded scale of datasets in humans. Currently, KnockTF 2.0 stores 1468 manually curated RNA-seq and microarray datasets associated with 612 TFs and 172 TcoFs disrupted by different knockdown/knockout techniques, which are 2.5 times larger than those of KnockTF 1.0. (ii) Newly added (epi)genetic annotations for T(co)F target genes in humans and mice, such as super-enhancers, common SNPs, methylation sites and chromatin interactions. (iii) Newly embedded and updated search and analysis tools, including T(co)F Enrichment (GSEA), Pathway Downstream Analysis and Search by Target Gene (BLAST). KnockTF 2.0 is a comprehensive update of KnockTF 1.0, which provides more T(co)F knockdown/knockout datasets and (epi)genetic annotations across multiple species than KnockTF 1.0. KnockTF 2.0 facilitates not only the identification of functional T(co)Fs and target genes but also the investigation of their roles in the physiological and pathological processes.

LncSEA 2.0: an updated platform for long non-coding RNA related sets and enrichment analysis.

Long non-coding RNAs (lncRNAs) possess a wide range of biological functions, and research has demonstrated their significance in regulating major biological processes such as development, differentiation, and immune response. The accelerating accumulation of lncRNA research has greatly expanded our understanding of lncRNA functions. Here, we introduce LncSEA 2.0 (http://bio.liclab.net/LncSEA/index.php), aiming to provide a more comprehensive set of functional lncRNAs and enhanced enrichment analysis capabilities. Compared with LncSEA 1.0, we have made the following improvements: (i) We updated the lncRNA sets for 11 categories and extremely expanded the lncRNA scopes for each set. (ii) We newly introduced 15 functional lncRNA categories from multiple resources. This update not only included a significant amount of downstream regulatory data for lncRNAs, but also covered numerous epigenetic regulatory data sets, including lncRNA-related transcription co-factor binding, chromatin regulator binding, and chromatin interaction data. (iii) We incorporated two new lncRNA set enrichment analysis functions based on GSEA and GSVA. (iv) We adopted the snakemake analysis pipeline to track data processing and analysis. In summary, LncSEA 2.0 offers a more comprehensive collection of lncRNA sets and a greater variety of enrichment analysis modules, assisting researchers in a more comprehensive study of the functional mechanisms of lncRNAs.

scATAC-Ref: a reference of scATAC-seq with known cell labels in multiple species.

Chromatin accessibility profiles at single cell resolution can reveal cell type-specific regulatory programs, help dissect highly specialized cell functions and trace cell origin and evolution. Accurate cell type assignment is critical for effectively gaining biological and pathological insights, but is difficult in scATAC-seq. Hence, by extensively reviewing the literature, we designed scATAC-Ref (https://bio.liclab.net/scATAC-Ref/), a manually curated scATAC-seq database aimed at providing a comprehensive, high-quality source of chromatin accessibility profiles with known cell labels across broad cell types. Currently, scATAC-Ref comprises 1 694 372 cells with known cell labels, across various biological conditions, >400 cell/tissue types and five species. We used uniform system environment and software parameters to perform comprehensive downstream analysis on these chromatin accessibility profiles with known labels, including gene activity score, TF enrichment score, differential chromatin accessibility regions, pathway/GO term enrichment analysis and co-accessibility interactions. The scATAC-Ref also provided a user-friendly interface to query, browse and visualize cell types of interest, thereby providing a valuable resource for exploring epigenetic regulation in different tissues and cell types.

CRdb: a comprehensive resource for deciphering chromatin regulators in human.

Chromatin regulators (CRs) regulate epigenetic patterns on a partial or global scale, playing a critical role in affecting multi-target gene expression. As chromatin immunoprecipitation sequencing (ChIP-seq) data associated with CRs are rapidly accumulating, a comprehensive resource of CRs needs to be built urgently for collecting, integrating, and processing these data, which can provide abundant annotated information on CR upstream and downstream regulatory analyses as well as CR-related analysis functions. This study established an integrative CR resource, named CRdb (http://cr.liclab.net/crdb/), with the aim of curating a large number of available resources for CRs and providing extensive annotations and analyses of CRs to help biological researchers clarify the regulation mechanism and function of CRs. The CRdb database comprised a total of 647 CRs and 2,591 ChIP-seq samples from more than 300 human tissues and cell types. These samples have been manually curated from NCBI GEO/SRA and ENCODE. Importantly, CRdb provided the abundant and detailed genetic annotations in CR-binding regions based on ChIP-seq. Furthermore, CRdb supported various functional annotations and upstream regulatory information on CRs. In particular, it embedded four types of CR regulatory analyses: CR gene set enrichment, CR-binding genomic region annotation, CR-TF co-occupancy analysis, and CR regulatory axis analysis. CRdb is a useful and powerful resource that can help in exploring the potential functions of CRs and their regulatory mechanism in diseases and biological processes.

SEdb 2.0: a comprehensive super-enhancer database of human and mouse.

Super-enhancers (SEs) are cell-specific DNA cis-regulatory elements that can supervise the transcriptional regulation processes of downstream genes. SEdb 2.0 (http://www.licpathway.net/sedb) aims to provide a comprehensive SE resource and annotate their potential roles in gene transcriptions. Compared with SEdb 1.0, we have made the following improvements: (i) Newly added the mouse SEs and expanded the scale of human SEs. SEdb 2.0 contained 1 167 518 SEs from 1739 human H3K27ac chromatin immunoprecipitation sequencing (ChIP-seq) samples and 550 226 SEs from 931 mouse H3K27ac ChIP-seq samples, which was five times that of SEdb 1.0. (ii) Newly added transcription factor binding sites (TFBSs) in SEs identified by TF motifs and TF ChIP-seq data. (iii) Added comprehensive (epi)genetic annotations of SEs, including chromatin accessibility regions, methylation sites, chromatin interaction regions and topologically associating domains (TADs). (iv) Newly embedded and updated search and analysis tools, including 'Search SE by TF-based', 'Differential-Overlapping-SE analysis' and 'SE-based TF-Gene analysis'. (v) Newly provided quality control (QC) metrics for ChIP-seq processing. In summary, SEdb 2.0 is a comprehensive update of SEdb 1.0, which curates more SEs and annotation information than SEdb 1.0. SEdb 2.0 provides a friendly platform for researchers to more comprehensively clarify the important role of SEs in the biological process.

SEanalysis 2.0: a comprehensive super-enhancer regulatory network analysis tool for human and mouse.

Super-enhancers (SEs) play an essential regulatory role in various biological processes and diseases through their specific interaction with transcription factors (TFs). Here, we present the release of SEanalysis 2.0 (http://licpathway.net/SEanalysis), an updated version of the SEanalysis web server for the comprehensive analyses of transcriptional regulatory networks formed by SEs, pathways, TFs, and genes. The current version added mouse SEs and further expanded the scale of human SEs, documenting 1 167 518 human SEs from 1739 samples and 550 226 mouse SEs from 931 samples. The SE-related samples in SEanalysis 2.0 were more than five times that in version 1.0, which significantly improved the ability of original SE-related network analyses ('pathway downstream analysis', 'upstream regulatory analysis' and 'genomic region annotation') for understanding context-specific gene regulation. Furthermore, we designed two novel analysis models, 'TF regulatory analysis' and 'Sample comparative analysis' for supporting more comprehensive analyses of SE regulatory networks driven by TFs. Further, the risk SNPs were annotated to the SE regions to provide potential SE-related disease/trait information. Hence, we believe that SEanalysis 2.0 has significantly expanded the data and analytical capabilities of SEs, which helps researchers in an in-depth understanding of the regulatory mechanisms of SEs.

TGFB2-AS1 inhibits triple-negative breast cancer progression via interaction with SMARCA4 and regulating its targets TGFB2 and SOX2.

Triple-negative breast cancer (TNBC) is the most challenging breast cancer subtype for its high rates of relapse, great metastatic potential, and short overall survival. How cancer cells acquire metastatic potency through the conversion of noncancer stem-like cells into cancer cells with stem-cell properties is poorly understood. Here, we identified the long noncoding RNA (lncRNA) TGFB2-AS1 as an important regulator of the reversibility and plasticity of noncancer stem cell populations in TNBC. We revealed that TGFB2-AS1 impairs the breast cancer stem-like cell (BCSC) traits of TNBC cells in vitro and dramatically decreases tumorigenic frequency and lung metastasis in vivo. Mechanistically, TGFB2-AS1 interacts with SMARCA4, a core subunit of the SWI/SNF chromatin remodeling complex, and results in transcriptional repression of its target genes including TGFB2 and SOX2 in an in cis or in trans way, leading to inhibition of transforming growth factor ß (TGFß) signaling and BCSC characteristics. In line with this, TGFB2-AS1 overexpression in an orthotopic TNBC mouse model remarkably abrogates the enhancement of tumor growth and lung metastasis endowed by TGFß2. Furthermore, combined prognosis analysis of TGFB2-AS1 and TGFß2 in TNBC patients shows that high TGFB2-AS1 and low TGFß2 levels are correlated with better outcome. These findings demonstrate a key role of TGFB2-AS1 in inhibiting disease progression of TNBC based on switching the cancer cell fate of TNBC and also shed light on the treatment of TNBC patients.

PBAC: A pathway-based attention convolution neural network for predicting clinical drug treatment responses.

Precise and personalized drug application is crucial in the clinical treatment of complex diseases. Although neural networks offer a new approach to improving drug strategies, their internal structure is difficult to interpret. Here, we propose PBAC (Pathway-Based Attention Convolution neural network), which integrates a deep learning framework and attention mechanism to address the complex biological pathway information, thereby provide a biology function-based robust drug responsiveness prediction model. PBAC has four layers: gene-pathway layer, attention layer, convolution layer and fully connected layer. PBAC improves the performance of predicting drug responsiveness by focusing on important pathways, helping us understand the mechanism of drug action in diseases. We validated the PBAC model using data from four chemotherapy drugs (Bortezomib, Cisplatin, Docetaxel and Paclitaxel) and 11 immunotherapy datasets. In the majority of datasets, PBAC exhibits superior performance compared to traditional machine learning methods and other research approaches (area under curve = 0.81, the area under the precision-recall curve = 0.73). Using PBAC attention layer output, we identified some pathways as potential core cancer regulators, providing good interpretability for drug treatment prediction. In summary, we presented PBAC, a powerful tool to predict drug responsiveness based on the biology pathway information and explore the potential cancer-driving pathways.

GREAP: a comprehensive enrichment analysis software for human genomic regions.

The rapid development of genomic high-throughput sequencing has identified a large number of DNA regulatory elements with abundant epigenetics markers, which promotes the rapid accumulation of functional genomic region data. The comprehensively understanding and research of human functional genomic regions is still a relatively urgent work at present. However, the existing analysis tools lack extensive annotation and enrichment analytical abilities for these regions. Here, we designed a novel software, Genomic Region sets Enrichment Analysis Platform (GREAP), which provides comprehensive region annotation and enrichment analysis capabilities. Currently, GREAP supports 85 370 genomic region reference sets, which cover 634 681 107 regions across 11 different data types, including super enhancers, transcription factors, accessible chromatins, etc. GREAP provides widespread annotation and enrichment analysis of genomic regions. To reflect the significance of enrichment analysis, we used the hypergeometric test and also provided a Locus Overlap Analysis. In summary, GREAP is a powerful platform that provides many types of genomic region sets for users and supports genomic region annotations and enrichment analyses. In addition, we developed a customizable genome browser containing >400 000 000 customizable tracks for visualization. The platform is freely available at http://www.liclab.net/Greap/view/index.

CanMethdb: a database for genome-wide DNA methylation annotation in cancers.

MOTIVATION: DNA methylation within gene body and promoters in cancer cells is well documented. An increasing number of studies showed that cytosine-phosphate-guanine (CpG) sites falling within other regulatory elements could also regulate target gene activation, mainly by affecting transcription factors (TFs) binding in human cancers. This led to the urgent need for comprehensively and effectively collecting distinct cis-regulatory elements and TF-binding sites (TFBS) to annotate DNA methylation regulation. RESULTS: We developed a database (CanMethdb, http://meth.liclab.net/CanMethdb/) that focused on the upstream and downstream annotations for CpG-genes in cancers. This included upstream cis-regulatory elements, especially those involving distal regions to genes, and TFBS annotations for the CpGs and downstream functional annotations for the target genes, computed through integrating abundant DNA methylation and gene expression profiles in diverse cancers. Users could inquire CpG-target gene pairs for a cancer type through inputting a genomic region, a CpG, a gene name, or select hypo/hypermethylated CpG sets. The current version of CanMethdb documented a total of 38 986 060 CpG-target gene pairs (with 6 769 130 unique pairs), involving 385 217 CpGs and 18 044 target genes, abundant cis-regulatory elements and TFs for 33 TCGA cancer types. CanMethdb might help biologists perform in-depth studies of target gene regulations based on DNA methylations in cancer. AVAILABILITY AND IMPLEMENTATION: The main program is available at https://github.com/chunquanlipathway/CanMethdb. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Parathyroid hormone receptor-1 signaling aggravates hepatic fibrosis through upregulating cAMP response element-binding protein-like 2.

BACKGROUND AND AIMS: Parathyroid hormone receptor-1 (PTH1R) is a class B G protein-coupled receptor central to skeletal development, bone turnover, and calcium homeostasis. However, the role of PTH1R signaling in liver fibrosis is largely unknown. Here, the role of PTH1R signaling in the activation of HSCs and hepatic fibrosis was examined. APPROACH AND RESULTS: PTH1R was highly expressed in activated HSCs and fibrotic liver by using human liver specimens or carbon tetrachloride (CCl 4 )-treated or methionine and choline-deficient diet (MCD)-fed C57/BL6 mice. The mRNA level of hepatic PTH1R was positively correlated to α-smooth muscle actin in patients with liver cirrhosis. Mice with HSCs-specific PTH1R deletion were protected from CCl 4 , MCD, or western diet, plus low-dose CCl 4 -induced liver fibrosis. Conversely, parathyroid hormone (PTH) aggravated liver fibrosis in CCl 4 -treated mice. Mouse primary HSCs and LX2 cell lines were used for in vitro experiments. Molecular analyses by luciferase reporter assays and chromatin immunoprecipitation assays in combination with mRNA sequencing in HSCs revealed that cAMP response element-binding protein-like 2 (Crebl2), a novel regulator in HSCs treated by PTH that interacted with mothers against decapentaplegic homolog 3 (SMAD3) and increased the transcription of TGFß in activating HSCs and collagen deposition. In agreement, HSCs-specific Crebl2 deletion ameliorated PTH-induced liver fibrosis in CCl 4 -treated mice. CONCLUSIONS: In both mouse and human models, we found that PTH1R was highly expressed in activated HSCs and fibrotic liver. PTH1R signaling regulated collagen production in the HSCs through Crebl2/SMAD3/TGFß regulatory circuits. Blockade of PTH1R signaling in HSCs might help mitigate the development of liver fibrosis.

Intrahepatic paracrine signaling by cardiotrophin-like cytokine factor 1 ameliorates diet-induced NASH in mice.

BACKGROUND AND AIMS: The mammalian liver harbors heterogeneous cell types that communicate via local paracrine signaling. Recent studies have delineated the transcriptomic landscape of the liver in NASH that provides insights into liver cell heterogeneity, intercellular crosstalk, and disease-associated reprogramming. However, the nature of intrahepatic signaling and its role in NASH progression remain obscure. APPROACH AND RESULTS: Here, we performed transcriptomic analyses and identified cardiotrophin-like cytokine factor 1 (CLCF1), a member of the IL-6 family cytokines, as a cholangiocyte-derived paracrine factor that was elevated in the liver from diet-induced NASH mice and patients with NASH. Adenovirus-associated virus-mediated overexpression of CLCF1 in the liver ameliorated NASH pathologies in two diet-induced NASH models in mice, illustrating that CLCF1 induction may serve an adaptive and protective role during NASH pathogenesis. Unexpectedly, messenger RNA and protein levels of leukemia inhibitory factor receptor (LIFR), a subunit of the receptor complex for CLCF1, were markedly downregulated in NASH liver. Hepatocyte-specific inactivation of LIFR accelerated NASH progression in mice, supporting an important role of intrahepatic cytokine signaling in maintaining tissue homeostasis under metabolic stress conditions. CONCLUSIONS: Together, this study sheds light on the molecular nature of intrahepatic paracrine signaling during NASH pathogenesis and uncovers potential targets for therapeutic intervention.

ALBINO EMBRYO AND SEEDLING is required for RNA splicing and chloroplast homeostasis in Arabidopsis.

Pentatricopeptide repeat (PPR) proteins form a large protein family and have diverse functions in plant development. Here, we identified an ALBINO EMBRYO AND SEEDLING (AES) gene that encodes a P-type PPR protein expressed in various tissues, especially the young leaves of Arabidopsis (Arabidopsis thaliana). Its null mutant aes exhibited a collapsed chloroplast membrane system, reduced pigment content and photosynthetic activity, decreased transcript levels of PEP (plastid-encoded polymerase)-dependent chloroplast genes, and defective RNA splicing. Further work revealed that AES could directly bind to psbB-psbT, psbH-petB, rps8-rpl36, clpP, ycf3, and ndhA in vivo and in vitro and that the splicing efficiencies of these genes and the expression levels of ycf3, ndhA, and cis-tron psbB-psbT-psbH-petB-petD decreased dramatically, leading to defective PSI, PSII, and Cyt b6f in aes. Moreover, AES could be transported into the chloroplast stroma via the TOC-TIC channel with the assistance of Tic110 and cpSRP54 and may recruit HCF244, SOT1, and CAF1 to participate in the target RNA process. These findings suggested that AES is an essential protein for the assembly of photosynthetic complexes, providing insights into the splicing of psbB operon (psbB-psbT-psbH-petB-petD), ycf3, and ndhA, as well as maintaining chloroplast homeostasis.

Neural mechanism of non-adaptive cognitive emotion regulation in patients with non-suicidal self-injury.

BACKGROUND: The incidence of non-suicidal self-injury (NSSI) has been on the rise in recent years. Studies have shown that people with NSSI have difficulties in emotion regulation and cognitive control. In addition, some studies have investigated the cognitive emotion regulation of people with NSSI which found that they have difficulties in cognitive emotion regulation, but there was a lack of research on cognitive emotion regulation strategies and related neural mechanisms. METHODS: This study included 117 people with NSSI (age = 19.47 ± 5.13, male = 17) and 84 non-NSSI participants (age = 19.86 ± 4.14, male = 16). People with NSSI met the DSM-5 diagnostic criteria, and non-NSSI participants had no mental or physical disorders. The study collected all participants' data of Cognitive Emotion Regulation Questionnaire (CERQ) and functional magnetic resonance imaging (fMRI) to explore the differences in psychological performance and brain between two groups. Afterwards, Machine learning was used to select the found differential brain regions to obtain the highest correlation regions with NSSI. Then, Allen's Human Brain Atlas database was used to compare with the information on the abnormal brain regions of people with NSSI to find the genetic information related to NSSI. In addition, gene enrichment analysis was carried out to find the related pathways and specific cells that may have differences. RESULTS: The differences between NSSI participants and non-NSSI participants were as follows: positive refocusing (t = -4.74, p < 0.01); refocusing on plans (t = -4.11, p < 0.01); positive reappraisal (t = -9.22, p < 0.01); self-blame (t = 6.30, p < 0.01); rumination (t = 3.64, p < 0.01); catastrophizing (t = 9.10, p < 0.01), and blaming others (t = 2.52, p < 0.01), the precentral gyrus (t = 6.04, pFDR < 0.05) and the rolandic operculum (t = -4.57, pFDR < 0.05). Rolandic operculum activity was negatively correlated with blaming others (r = -0.20, p < 0.05). Epigenetic results showed that excitatory neurons (p < 0.01) and inhibitory neurons (p < 0.01) were significant differences in two pathways, "trans-synaptic signaling" (p < -log108) and "modulation of chemical synaptic transmission" (p < -log108) in both cells. CONCLUSIONS: People with NSSI are more inclined to adopt non-adaptive cognitive emotion regulation strategies. Rolandic operculum is also abnormally active. Abnormal changes in the rolandic operculum of them are associated with non-adaptive cognitive emotion regulation strategies. Changes in the excitatory and inhibitory neurons provide hints to explore the abnormalities of the neurological mechanisms at the cellular level of them. Trial registration number NCT04094623.

TF-Marker: a comprehensive manually curated database for transcription factors and related markers in specific cell and tissue types in human.

Transcription factors (TFs) play key roles in biological processes and are usually used as cell markers. The emerging importance of TFs and related markers in identifying specific cell types in human diseases increases the need for a comprehensive collection of human TFs and related markers sets. Here, we developed the TF-Marker database (TF-Marker, http://bio.liclab.net/TF-Marker/), aiming to provide cell/tissue-specific TFs and related markers for human. By manually curating thousands of published literature, 5905 entries including information about TFs and related markers were classified into five types according to their functions: (i) TF: TFs which regulate expression of the markers; (ii) T Marker: markers which are regulated by the TF; (iii) I Marker: markers which influence the activity of TFs; (iv) TFMarker: TFs which play roles as markers and (v) TF Pmarker: TFs which play roles as potential markers. The 5905 entries of TF-Marker include 1316 TFs, 1092 T Markers, 473 I Markers, 1600 TFMarkers and 1424 TF Pmarkers, involving 383 cell types and 95 tissue types in human. TF-Marker further provides a user-friendly interface to browse, query and visualize the detailed information about TFs and related markers. We believe TF-Marker will become a valuable resource to understand the regulation patterns of different tissues and cells.

TcoFBase: a comprehensive database for decoding the regulatory transcription co-factors in human and mouse.

Transcription co-factors (TcoFs) play crucial roles in gene expression regulation by communicating regulatory cues from enhancers to promoters. With the rapid accumulation of TcoF associated chromatin immunoprecipitation sequencing (ChIP-seq) data, the comprehensive collection and integrative analyses of these data are urgently required. Here, we developed the TcoFBase database (http://tcof.liclab.net/TcoFbase), which aimed to document a large number of available resources for mammalian TcoFs and provided annotations and enrichment analyses of TcoFs. TcoFBase curated 2322 TcoFs and 6759 TcoFs associated ChIP-seq data from over 500 tissues/cell types in human and mouse. Importantly, TcoFBase provided detailed and abundant (epi) genetic annotations of ChIP-seq based TcoF binding regions. Furthermore, TcoFBase supported regulatory annotation information and various functional annotations for TcoFs. Meanwhile, TcoFBase embedded five types of TcoF regulatory analyses for users, including TcoF gene set enrichment, TcoF binding genomic region annotation, TcoF regulatory network analysis, TcoF-TF co-occupancy analysis and TcoF regulatory axis analysis. TcoFBase was designed to be a useful resource that will help reveal the potential biological effects of TcoFs and elucidate TcoF-related regulatory mechanisms.

Significance Analysis of the Improvement in Postoperative Recovery of Cardiac Surgery Patients Based on the Graded Management Established Using the Delirium Prediction Model.

Objective: To investigate the impact of graded management based on delirium prediction modeling on the improvement of recovery of cardiac surgery patients. Methods: Three hundred and twenty patients admitted to the Department of Critical Care Medicine of Nanjing Hospital affiliated with Nanjing Medical University from June 2021 to December 2023 after Type A aortic coarctation were selected as study subjects. They were grouped according to the randomized scale method and divided into 160 cases in each the control group and the observation group. In the control group, conventional nursing measures were adopted, and in the observation group, graded nursing interventions were carried out according to the established delirium risk prediction model. Comparison between the two groups in terms of the intensive care unit (ICU) monitoring time, hospitalization time, duration of delirium, and delirium incidence, and investigated nursing satisfaction, and quality of care scores. Results: Compared with the control group, the observation group's ICU custody time, hospitalization time, and delirium duration, decreased, and the quality of care, and satisfaction increased (P < .05). At the same time, the incidence of delirium in the observation group was also lower than that in the control group (P < .05). Conclusion: The graded management based on the delirium prediction model can effectively reduce the incidence of postoperative delirium in critically ill patients with Type A aortic coarctation, and at the same time improve patient satisfaction and quality of care.

A Three-Wavelength Optical Sensor for Measuring the Multi-Particle-Size Channel Mass Concentration of Thermal Power Plant Emissions.

Emissions from thermal power plants have always been the central consideration for environmental protection. Existing optical sensors in thermal power plants usually measure the total mass concentration of the particulate matter (PM) by a single-wavelength laser, bearing intrinsic errors owing to the variation in particle size distribution (PSD). However, the total mass concentration alone cannot characterize all the harmful effects of the air pollution caused by the power plant. Therefore, it is necessary to measure the mass concentration and PSD simultaneously, based on which we can obtain multi-particle-size channel mass concentration. To achieve this, we designed an optical sensor based on the three-wavelength technique and tested its performance in a practical environment. Results showed that the prototype cannot only correctly measure the mass concentration of the emitted PM but also determine the mean diameter and standard deviation of the PSDs. Hence, the mass concentrations of PM10, PM2.5, and PM1 are calculated, and the air pollutants emission by a thermal power plant can be estimated comprehensively.

Genome-Wide Identification and Analysis of the EIN3/EIL Transcription Factor Gene Family in Doubled Haploid (DH) Poplar.

Ethylene (ET) is an important phytohormone that regulates plant growth, development and stress responses. The ethylene-insensitive3/ethylene-insensitive3-like (EIN3/EIL) transcription factor family, as a key regulator of the ET signal transduction pathway, plays an important role in regulating the expression of ET-responsive genes. Although studies of EIN3/EIL family members have been completed in many species, their role in doubled haploid (DH) poplar derived from another culture of diploid Populus simonii × P. nigra (donor tree, DT) remains ambiguous. In this study, a total of seven EIN3/EIL gene family members in the DH poplar genome were identified. Basic physical and chemical property analyses of these genes were performed, and these proteins were predicted to be localized to the nucleus. According to the phylogenetic relationship, EIN3/EIL genes were divided into two groups, and the genes in the same group had a similar gene structure and conserved motifs. The expression patterns of EIN3/EIL genes in the apical buds of different DH poplar plants were analyzed based on transcriptome data. At the same time, the expression patterns of PsnEIL1, PsnEIN3, PsnEIL4 and PsnEIL5 genes in different tissues of different DH plants were detected via RT-qPCR, including the apical buds, young leaves, functional leaves, xylem, cambium and roots. The findings presented above indicate notable variations in the expression levels of PsnEIL genes across various tissues of distinct DH plants. Finally, the PsnEIL1 gene was overexpressed in DT, and the transgenic plants showed a dwarf phenotype, indicating that the PsnEIL1 gene was involved in regulating the growth and development of poplar. In this study, the EIN3/EIL gene family of DH poplar was analyzed and functionally characterized, which provides a theoretical basis for the future exploration of the EIN3/EIL gene function.

Stability mechanism of Monascus pigment-soy protein isolate-maltodextrin complex.

BACKGROUND: Monascus pigment (MP) is a natural food coloring with vital physiological functions but prone to degradation and color fading under light conditions. RESULTS: This study investigated the effect of complex formation of soybean protein isolate (SPI), maltodextrin (MD), and MP on the photostability of MP. Light stability was assessed through retention rate and color difference. Fluorescence spectroscopy (FS), circular dichroism (CD), Fourier-transform infrared (FTIR) spectroscopy, and X-ray diffraction (XRD) explored MP, SPI, and MD interactions, clarifying the MP-SPI-MD complex mechanism on the light stability of MP. Microstructure and differential scanning calorimetry (DSC) analyzed the morphology and thermal properties. The retention rate of MP increased to approximately 80%, and minimal color difference was observed when adding SPI and MD simultaneously. FS revealed hydrophobic interaction between MP and SPI. FTIR analysis showed intensity changes and peak shifts in amide I band and amide II band, which proved the hydrophobic interaction. CD showed a decrease in α-helix content and an increase in ß-sheet content after complex formation, indicating strengthened hydrogen bonding interactions. Scanning electron microscopy (SEM) analysis demonstrated that MP was attached to the surface and interior of complexes. XRD showed MP as crystalline, while SPI and MD were amorphous, complexes exhibited weakened or absent peaks, suggesting MP encapsulation. The results of DSC were consistent with XRD. CONCLUSION: SPI and MD enveloped MP through hydrogen bonding and hydrophobic interaction, ultimately enhancing its light stability and providing insights for pigment-protein-polysaccharide interactions and improving pigment stability in the food industry. © 2024 Society of Chemical Industry.