Mortality risk and burden of aortic aneurysm and dissection attributable to low temperatures: A nationwide case-crossover analysis in Brazil, a predominantly tropical country.

BACKGROUND: Low temperatures are adverse contributors to cardiovascular diseases, but the associations between short-term exposure to cold and the risk of death from aortic dissection and aneurysm remain unclear, particularly in tropical regions. OBJECTIVE: This study was conducted based on 123,951 records of deaths caused by aortic dissection and aneurysms extracted from the national Mortality Information System in Brazil between 2000 and 2019. METHODS: Relative risks and 95 % confidence intervals (CI) for the aortic-related deaths associated with low ambient temperatures were estimated using the conditional logistic model combined with the distributed lag nonlinear model. Subgroup analyses were performed by age group, sex, race, education level, and residential region. Furthermore, this study calculated the number and fraction of aortic-related deaths attributed to temperatures below the temperature threshold to quantify the cold-related mortality burden of aortic diseases. RESULTS: During the study period, aortic-related deaths and mortality rates in Brazil exhibited a steady increase, rising from 4419 (2.66/100,000) in 2000 to 8152 (3.88/100,000) in 2019. Under the identified temperature threshold (26 °C), per 1 °C decrease in daily mean temperature was associated with a 4.77 % (95 % CI: 4.35, 5.19) increase in mortality risk of aortic-related diseases over lag 0-3 days. Females, individuals aged 50 years or older, Asian and Black race, and northern residents were more susceptible to low temperatures. Low temperatures were responsible for 19.10 % (95 % CI: 17.71, 20.45) of aortic-related deaths in Brazil. CONCLUSION: This study highlights that low temperatures were associated with an increased risk of aortic-related deaths, with a remarkable burden even in this predominantly tropical country.

Unveiling the power of MYB transcription factors: Master regulators of multi-stress responses and development in cotton.

Plants, being immobile, are subject to environmental stresses more than other creatures, necessitating highly effective stress tolerance systems. Transcription factors (TFs) play a crucial role in the adaptation mechanism as they can be activated by diverse signals and ultimately control the expression of stress-responsive genes. One of the most prominent plant TFs family is MYB (myeloblastosis), which is involved in secondary metabolites, developmental mechanisms, biological processes, cellular architecture, metabolic pathways, and stress responses. Extensive research has been conducted on the involvement of MYB TFs in crops, while their role in cotton remains largely unexplored. We also utilized genome-wide data to discover potential 440 MYB genes and investigated their plausible roles in abiotic and biotic stress conditions, as well as in different tissues across diverse transcriptome databases. This review primarily summarized the structure and classification of MYB TFs biotic and abiotic stress tolerance and their role in secondary metabolism in different crops, especially in cotton. However, it intends to identify gaps in current knowledge and emphasize the need for further research to enhance our understanding of MYB roles in plants.

A Tumor-Targeting Dual-Modal imaging probe for nitroreductase in vivo.

Nitroreductase (NTR) overexpression often occurs in tumors, highlighting the significance of effective NTR detection. Despite the utilization of various optical methods for this purpose, the absence of an efficient tumor-targeting optical probe for NTR detection remains a challenge. In this research, a novel tumor-targeting probe (Cy-Bio-NO2) is developed to perform dual-modal NTR detection using near-infrared fluorescence and photoacoustic techniques. This probe exhibits exceptional sensitivity and selectivity to NTR. Upon the reaction with NTR, Cy-Bio-NO2 demonstrates a distinct fluorescence "off-on" response at 800 nm, with an impressive detection limit of 12 ng/mL. Furthermore, the probe shows on-off photoacoustic signal with NTR. Cy-Bio-NO2 has been successfully employed for dual-modal NTR detection in living cells, specifically targeting biotin receptor-positive cancer cells for imaging purposes. Notably, this probe effectively detects tumor hypoxia through dual-modal imaging in tumor-bearing mice. The strategy of biotin incorporation markedly enhances the probe's tumor-targeting capability, facilitating its engagement in dual-modal imaging at tumor sites. This imaging capacity holds substantial promise as an accurate tool for cancer diagnosis.

A novel plant growth regulator B2 mediates drought resistance by regulating reactive oxygen species, phytohormone signaling, phenylpropanoid biosynthesis, and starch metabolism pathways in Carex breviculmis.

Drought is one of the most common environmental stressors that severely threatens plant growth, development, and productivity. B2 (2,4-dichloroformamide cyclopropane acid), a novel plant growth regulator, plays an essential role in drought adaptation, significantly enhancing the tolerance of Carex breviculmis seedlings. Its beneficial effects include improved ornamental value, sustained chlorophyll content, increased leaf dry weight, elevated relative water content, and enhanced root activity under drought conditions. B2 also directly scavenges hydrogen peroxide and superoxide anion contents while indirectly enhancing the activities of antioxidant enzymes (superoxide dismutase, peroxidase, catalase, and ascorbate peroxidase) to detoxify reactive oxygen species (ROS) oxidative damage. Transcriptome analysis demonstrated that B2 activates drought-responsive transcription factors (AP2/ERF-ERF, WRKY, and mTERF), leading to significant upregulation of genes associated with phenylpropanoid biosynthesis (HCT, POD, and COMT). Additionally, these transcription factors were found to suppress the degradation of starch. B2 regulates phytohormone signaling related-genes, leading to an increase in abscisic acid contents in drought-stressed plants. Collectively, these findings offer new insights into the intricate mechanisms underlying C. breviculmis' resistance to drought damage, highlighting the potential application of B2 for future turfgrass establishment and management with enhanced drought tolerance.

Causal association of immune cells and endometriosis: a Mendelian randomization study.

Objective: To investigate the causal effect of immune cells on endometriosis (EMS), we performed a Mendelian randomization analysis. Methods: Mendelian randomization (MR) uses genetic variants as instrumental variables to investigate the causal effects of exposures on outcomes in observational data. In this study, we conducted a thorough two-sample MR analysis to investigate the causal relationship between 731 immune cells and endometriosis. We used complementary Mendelian randomization (MR) methods, including weighted median estimator (WME) and inverse variance weighted (IVW), and performed sensitivity analyses to assess the robustness of our results. Results: Four immune phenotypes have been found to be significantly associated with the risk of developing EMS: B cell %lymphocyte (WME: OR: 1.074, p = 0.027 and IVW: OR: 1.058, p = 0.008), CD14 on Mo MDSC (WME: OR: 1.056, p =0.021 and IVW: OR: 1.047, p = 0.021), CD14+ CD16- monocyte %monocyte (WME: OR: 0.947, p = 0.024 and IVW: OR: 0.958, p = 0.011), CD25 on unsw mem (WME: OR: 1.055, p = 0.030 and IVW: OR: 1.048, p = 0.003). Sensitivity analyses confirmed the main findings, demonstrating consistency across analyses. Conclusions: Our MR analysis provides compelling evidence for a direct causal link between immune cells and EMS, thereby advancing our understanding of the disease. It also provides new avenues and opportunities for the development of immunomodulatory therapeutic strategies in the future.

A near-infrared fluorescent probe for imaging peroxynitrite levels in paw edema mice and drug evaluation.

A near-infrared fluorescent probe (TX-P) for detecting peroxynitrite is constructed. The probe has a near-infrared emission (725 nm), large Stokes shift (125 nm) and excellent sensitivity and selectivity. In addition, TX-P can be used to visualize ONOO- in living cells, image ONOO- in paw edema mice and evaluate anti-inflammatory drugs.

Molecular engineering of thiophene- and pyrrole-fused core arylamine systems: Tuning redox properties, NIR spectral responsiveness and bacterial imaging applications.

The thiophene- and pyrrole-fused heterocyclic compounds have garnered significant interest for their distinctive electron-rich characteristics and notable optoelectronic properties. However, the construction of high-performance systems within this class is of great challenge. Herein, we develop a series of novel dithieno[3,2-b:2',3'-d] pyrrole (DTP) and tetrathieno[3,2-b:2',3'-d] pyrrole (TTP) bridged arylamine compounds (DTP-C4, DTP-C12, DTP-C4-Fc, TTP-C4-OMe, TTP-C4, and TTP-C12) with varying carbon chain lengths. The pertinent experimental results reveal that this series of compounds undergo completely reversible multistep redox processes. Notably, TTP-bridged compounds TTP-C4 and TTP-C12 exhibit impressive multistep near-infrared (NIR) absorption alterations with notable color changes and electroluminescent behaviors, which are mainly attributed to the charge transfer transitions from terminal arylamine units to central bridges, as supported by theoretical calculations. Additionally, compound DTP-C4 demonstrates the ability to visually identify gram-positive and gram-negative bacteria. Therefore, this work suggests the promising electroresponsive nature of compounds TTP-C4 and TTP-C12, positioning them as excellent materials for various applications. It also provides a facile approach to constructing high-performance multifunctional luminescent materials, particularly those with strong and long-wavelength NIR absorption capabilities.

Predictive value of a stemness-based classifier for prognosis and immunotherapy response of hepatocellular carcinoma based on bioinformatics and machine-learning strategies.

Objective: Significant advancements have been made in hepatocellular carcinoma (HCC) therapeutics, such as immunotherapy for treating patients with HCC. However, there is a lack of reliable biomarkers for predicting the response of patients to therapy, which continues to be challenging. Cancer stem cells (CSCs) are involved in the oncogenesis, drug resistance, and invasion, as well as metastasis of HCC cells. Therefore, in this study, we aimed to create an mRNA expression-based stemness index (mRNAsi) model to predict the response of patients with HCC to immunotherapy. Methods: We retrieved gene expression and clinical data of patients with HCC from the GSE14520 dataset and the Cancer Genome Atlas (TCGA) database. Next, we used the "one-class logistic regression (OCLR)" algorithm to obtain the mRNAsi of patients with HCC. We performed "unsupervised consensus clustering" to classify patients with HCC based on the mRNAsi scores and stemness subtypes. The relationships between the mRNAsi model, clinicopathological features, and genetic profiles of patients were compared using various bioinformatic methods. We screened for differentially expressed genes to establish a stemness-based classifier for predicting the patient's prognosis. Next, we determined the effect of risk scores on the tumor immune microenvironment (TIME) and the response of patients to immune checkpoint blockade (ICB). Finally, we used qRT-PCR to investigate gene expression in patients with HCC. Results: We screened CSC-related genes using various bioinformatics tools in patients from the TCGA-LIHC cohort. We constructed a stemness classifier based on a nine-gene (PPARGC1A, FTCD, CFHR3, MAGEA6, CXCL8, CABYR, EPO, HMMR, and UCK2) signature for predicting the patient's prognosis and response to ICBs. Further, the model was validated in an independent GSE14520 dataset and performed well. Our model could predict the status of TIME, immunogenomic expressions, congenic pathway, and response to chemotherapy drugs. Furthermore, a significant increase in the proportion of infiltrating macrophages, Treg cells, and immune checkpoints was observed in patients in the high-risk group. In addition, tumor cells in patients with high mRNAsi scores could escape immune surveillance. Finally, we observed that the constructed model had a good expression in the clinical samples. The HCC tumor size and UCK2 genes expression were significantly alleviated and decreased, respectively, by treatments of anti-PD1 antibody. We also found knockdown UCK2 changed expressions of immune genes in HCC cell lines. Conclusion: The novel stemness-related model could predict the prognosis of patients and aid in creating personalized immuno- and targeted therapy for patients in HCC.

Vegetation redistribution is predicted to intensify soil organic carbon loss under future climate changes on the Tibetan Plateau.

Vegetation redistribution may bring unexpected climate-soil carbon cycling in terrestrial biomes. However, whether and how vegetation redistribution alters the soil carbon pool under climate change is still poorly understood on the Tibetan Plateau. Here, we applied the G-Range model to simulate the cover of herbs, shrubs and trees, net primary productivity (NPP) and soil organic carbon density (SOCD) at the depth of 60 cm on Tibetan Plateau for the individual years 2020 and 2060, using climate projection for Representative Concentration Pathways (RCP) 4.5 and RCP8.5 scenarios with the RegCM4.6 model system. Vegetation redistribution was defined as the transitions in bare ground, herbs, shrubs and trees between 2020 and 2060, with approximately 57.9 % (RCP4.5) and 59 % (RCP8.5) of the area will redistribute vegetation over the whole Tibetan Plateau. The vegetation cover will increase by about 2.4 % (RCP4.5) and 1.9 % (RCP8.5), while the NPP and SOCD will decrease by about -14.3 g C m-2 yr-1 and -907 g C m-2 (RCP4.5), and -1.8 g C m-2 yr-1and -920 g C m-2 (RCP8.5). Shrubs and trees will expand in the east, and herbs will expand in the northwest part of the Plateau. These areas are projected to be hotspots with greater SOCD reduction in response to future climate change, and will include lower net plant carbon input due to the negative NPP. Our study indicates that the SOC pool will become a carbon source under increased air temperature and rainfall on the Tibetan Plateau by 2060, especially for the area with vegetation redistribution. These results revealed the potential risk of vegetation redistribution under climate change in alpine ecosystems, indicating the policymakers need to pay attention on the vegetation redistribution to mitigate the soil carbon emission and achieve the goal of carbon neutrality on the Tibetan Plateau.

Transcriptome dynamics of Gossypium purpurascens in response to abiotic stresses by Iso-seq and RNA-seq data.

Gossypium purpurascens is a member of the Malvaceae family, holds immense economic significance as a fiber crop worldwide. Abiotic stresses harm cotton crops, reduce yields, and cause economic losses. Generating high-quality reference genomes and large-scale transcriptomic datasets across diverse conditions can offer valuable insights into identifying preferred agronomic traits for crop breeding. The present research used leaf tissues to conduct PacBio Iso-seq and RNA-seq analysis. We carried out an in-depth analysis of DEGs using both correlations with cluster analysis and principal component analysis. Additionally, the study also involved the identification of both lncRNAs and CDS. We have prepared RNA-seq libraries from 75 RNA samples to study the effects of drought, salinity, alkali, and saline-alkali stress, as well as control conditions. A total of 454.06 Gigabytes of transcriptome data were effectively validated through the identification of differentially expressed genes and KEGG and GO analysis. Overwhelmingly, gene expression profiles and full-length transcripts from cotton tissues will aid in understanding the genetic mechanism of abiotic stress tolerance in G. purpurascens.

Case report: Intrahepatic cholangiectasis with Clonorchis sinensis infection.

Clonorchis sinensis infections persist globally among humans. These pathogens mainly inhabit the intrahepatic biliary system. Most individuals with clonorchiasis exhibit mild symptoms. The absence of distinctive symptoms often results in delayed diagnosis and treatment, potentially leading to chronic infection. We herein report a case of a 29-year-old female presented with a year-long history of abdominal distention and dyspepsia. Imaging revealed intrahepatic bile duct dilatation, intrahepatic bile duct cyst, and associated deposits. One month post-cystectomy, the patient developed massive ascites and a significant increase in eosinophil count. After treatment, multiple worms were observed in the drainage tube. Morphological and DNA metagenomic analyses confirmed the presence of C. sinensis. Clinical manifestations of C. sinensis vary widely. Imaging serves as a valuable diagnostic tool in endemic areas, especially in detecting intrahepatic duct dilation where the flukes reside. In addition to intrahepatic bile duct dilation, abnormal echoes within the bile duct and the presence of floating objects in the gallbladder significantly aid in diagnosis. Clinicians may encounter these parasitic diseases unexpectedly, underscoring the importance of understating such cases in routine practice and contributing to our broader understanding of managing similar cases in clinical settings.

GhiPLATZ17 and GhiPLATZ22, zinc-dependent DNA-binding transcription factors, promote salt tolerance in upland cotton.

KEY MESSAGE: The utilization of transcriptome analysis, functional validation, VIGS, and DAB techniques have provided evidence that GhiPLATZ17 and GhiPLATZ22 play a pivotal role in improving the salt tolerance of upland cotton. PLATZ (Plant AT-rich sequences and zinc-binding proteins) are known to be key regulators in plant growth, development, and response to salt stress. In this study, we comprehensively analyzed the PLATZ family in ten cotton species in response to salinity stress. Gossypium herbaceum boasts 25 distinct PLATZ genes, paralleled by 24 in G. raimondii, 25 in G. arboreum, 46 in G. hirsutum, 48 in G. barbadense, 43 in G. tomentosum, 67 in G. mustelinum, 60 in G. darwinii, 46 in G. ekmanianum, and a total of 53 PLATZ genes attributed to G. stephensii. The PLATZ gene family shed light on the hybridization and allopolyploidy events that occurred during the evolutionary history of allotetraploid cotton. Ka/Ks analysis suggested that the PLATZ gene family underwent intense purifying selection during cotton evolution. Analysis of synteny and gene collinearity revealed a complex pattern of segmental and dispersed duplication events to expand PLATZ genes in cotton. Cis-acting elements and gene expressions revealed that GhiPLATZ exhibited salt stress resistance. Transcriptome analysis, functional validation, virus-induced gene silencing (VIGS), and diaminobenzidine staining (DAB) demonstrated that GhiPLATZ17 and GhiPLATZ22 enhance salt tolerance in upland cotton. The study can potentially advance our understanding of identifying salt-resistant genes in cotton.

Near-infrared fluorescent probe for the imaging of viscosity in fatty liver mice and valuation of drug efficacy.

Fatty liver disease affects at least 25 percent of the population worldwide and is a severe metabolic syndrome. Viscosity is closely related to fatty liver disease, so it is urgent to develop an effective tool for monitoring viscosity. Herein, a NIR fluorescent probe called MBC-V is developed for imaging viscosity, consisting of dimethylaniline and malonitrile-benzopyran. MBC-V is non-fluorescent in low viscosity solutions due to intramolecular rotation. In high viscosity solution, the intramolecular rotation of MBC-V is suppressed and the fluorescence is triggered. MBC-V has long emission wavelength at 720 nm and large Stokes shift about 160 nm. Moreover, MBC-V can detect changes in cell viscosity in fatty liver cells, and can image the therapeutic effects of drug in fatty liver cells. By taking advantage of NIR emission, MBC-V can be used as an imaging tool for fatty liver disease and a way to evaluate the therapeutic effect of drug for fatty liver disease.

Learning dynamic graph representations through timespan view contrasts.

The rich information underlying graphs has inspired further investigation of unsupervised graph representation. Existing studies mainly depend on node features and topological properties within static graphs to create self-supervised signals, neglecting the temporal components carried by real-world graph data, such as timestamps of edges. To overcome this limitation, this paper explores how to model temporal evolution on dynamic graphs elegantly. Specifically, we introduce a new inductive bias, namely temporal translation invariance, which illustrates the tendency of the identical node to keep similar labels across different timespans. Based on this assumption, we develop a dynamic graph representation framework CLDG that encourages the node to maintain locally consistent temporal translation invariance through contrastive learning on different timespans. Except for standard CLDG which only considers explicit topological links, our further proposed CLDG＋＋additionally employs graph diffusion to uncover global contextual correlations between nodes, and designs a multi-scale contrastive learning objective composed of local-local, local-global, and global-global contrasts to enhance representation capabilities. Interestingly, by measuring the consistency between different timespans to shape anomaly indicators, CLDG and CLDG＋＋are seamlessly integrated with the task of spotting anomalies on dynamic graphs, which has broad applications in many high-impact domains, such as finance, cybersecurity, and healthcare. Experiments demonstrate that CLDG and CLDG＋＋both exhibit desirable performance in downstream tasks including node classification and dynamic graph anomaly detection. Moreover, CLDG significantly reduces time and space complexity by implicitly exploiting temporal cues instead of complicated sequence models. The code and data are available at https://github.com/yimingxu24/CLDG.

Genomic variation, environmental adaptation, and feralization in ramie, an ancient fiber crop.

Feralization is an important evolutionary process, but the mechanisms behind it remain poorly understood. Here, we use the ancient fiber crop ramie (Boehmeria nivea (L.) Gaudich.) as a model to investigate genomic changes associated with both domestication and feralization. We first produced a chromosome-scale de novo genome assembly of feral ramie and investigated structural variations between feral and domesticated ramie genomes. Next, we gathered 915 accessions from 23 countries, comprising cultivars, major landraces, feral populations, and the wild progenitor. Based on whole-genome resequencing of these accessions, we constructed the most comprehensive ramie genomic variation map to date. Phylogenetic, demographic, and admixture signal detection analyses indicated that feral ramie is of exoferal or exo-endo origin, i.e., descended from hybridization between domesticated ramie and the wild progenitor or ancient landraces. Feral ramie has higher genetic diversity than wild or domesticated ramie, and genomic regions affected by natural selection during feralization differ from those under selection during domestication. Ecological analyses showed that feral and domesticated ramie have similar ecological niches that differ substantially from the niche of the wild progenitor, and three environmental variables are associated with habitat-specific adaptation in feral ramie. These findings advance our understanding of feralization, providing a scientific basis for the excavation of new crop germplasm resources and offering novel insights into the evolution of feralization in nature.

Agomir-122-loaded nanoparticles coated with cell membrane of activated fibroblasts to treat frozen shoulder based on homologous targeting.

As a common musculoskeletal disorder, frozen shoulder is characterized by thickened joint capsule and limited range of motion, affecting 2-5% of the general population and more than 20% of patients with diabetes mellitus. Pathologically, joint capsule fibrosis resulting from fibroblast activation is the key event. The activated fibroblasts are proliferative and contractive, producing excessive collagen. Albeit high prevalence, effective anti-fibrosis modalities, especially fibroblast-targeting therapies, are still lacking. In this study, microRNA-122 was first identified from sequencing data as a potential therapeutic agent to antagonize fibroblast activation. Then, Agomir-122, an analog of microRNA-122, was loaded into poly(lactic-co-glycolic acid) (PLGA) nanoparticles (Agomir-122@NP), a carrier with excellent biocompatibility for the agent delivery. Moreover, relying on the homologous targeting effect, we coated Agomir-122@NP with the cell membrane derived from activated fibroblasts (Agomir-122@MNP), with an attempt to inhibit the proliferation, contraction, and collagen production of abnormally activated fibroblasts. After confirming the targeting effect of Agomir-122@MNP on activated fibroblasts in vitro, we proved that Agomir-122@MNP effectively curtailed fibroblasts activation, ameliorated joint capsule fibrosis, and restored range of motion in mouse models both prophylactically and therapeutically. Overall, an effective targeted delivery method was developed with promising translational value against frozen shoulder.

Promising probiotic-fermented soymilk for alleviating acute diarrhea: insights into the microbiome and metabolomics.

Fermented soymilk (FSM4) has attracted much attention due to its nutritional and health characteristics. Exploring FSM4 products to alleviate diarrhea can ensure their effectiveness as a therapeutic food for alleviating gastrointestinal disorders. However, the relationship between gut microbiota and gut metabolite production remains unknown during diarrheal episodes. Therefore, the diarrhea-alleviating role and mechanisms of FSM4 in diarrhea rats were investigated via biochemical, gut microbiota, and serum metabolite analyses. The findings showed that consuming FSM4 improved diarrhea symptoms and reduced systemic inflammation better than non-fermented soymilk (NFSM). It is worth noting that FSM4 promoted the diversity, richness, structure, and composition of gut microbiota. It increased the ability to reduce inflammation associated with harmful bacteria (Anaerofilum, Flavonifractor, Bilophila, Anaerostipes, [Ruminococcus]_torques_group, Clostridium_sensu_stricto_1, Turicibacter, Ruminococcus_1, Ruminiclostridium_6, Prevotellaceae_NK3B31_group and Fusicatenibacter), while stimulating the growth of healthy species (Lactobacillus, Ruminococcaceae_UCG-014, Oscillibacter, [Eubacterium]_coprostanoligenes_group, Negativibacillus, and Erysipelotrichaceae_UCG-003). Moreover, metabolomics analysis showed that lipid metabolites such as lysophosphatidylethanolamine (LysoPE) and sphingolipids were upregulated in the NG group, closely related to pro-inflammatory cytokines (IL-6, IL-1ß, TNF-α, and IFN-γ) and the aforementioned pathogenic bacteria. Notably, in treatment groups, especially FSM4, the accumulation of L-ornithine, aspartic acid, ursocholic acid, 18-oxooleate, and cyclopentanethiol was increased, which was robustly associated with the anti-inflammatory factor IL-10 and beneficial bacteria mentioned above. Therefore, it can be inferred that the amino acids, bile acid, 18-oxooleate, and cyclopentanethiol produced in the FSM4 group can serve as metabolic biomarkers, which synergistically act with the gut microbiota to help alleviate inflammation for diarrhea remission. Overall, FSM4 may provide a new alternative, as an anti-inflammatory diet, to alleviate diarrhea.

Exploring the regulatory role of non-coding RNAs in fiber development and direct regulation of GhKCR2 in the fatty acid metabolic pathway in upland cotton.

Cotton fiber holds immense importance as the primary raw material for the textile industry. Consequently, comprehending the regulatory mechanisms governing fiber development is pivotal for enhancing fiber quality. Our study aimed to construct a regulatory network of competing endogenous RNAs (ceRNAs) and assess the impact of non-coding RNAs on gene expression throughout fiber development. Through whole transcriptome data analysis, we identified differentially expressed genes (DEGs) regulated by non-coding RNA (ncRNA) that were predominantly enriched in phenylpropanoid biosynthesis and the fatty acid elongation pathway. This analysis involved two contrasting phenotypic materials (J02-508 and ZRI015) at five stages of fiber development. Additionally, we conducted a detailed analysis of genes involved in fatty acid elongation, including KCS, KCR, HACD, ECR, and ACOT, to unveil the factors contributing to the variation in fatty acid elongation between J02-508 and ZRI015. Through the integration of histochemical GUS staining, dual luciferase assay experiments, and correlation analysis of expression levels during fiber development stages for lncRNA MSTRG.44818.23 (MST23) and GhKCR2, we elucidated that MST23 positively regulates GhKCR2 expression in the fatty acid elongation pathway. This identification provides valuable insights into the molecular mechanisms underlying fiber development, emphasizing the intricate interplay between non-coding RNAs and protein-coding genes.

Preparation of novel membranes with multiple hydrogen bonding sites and π-conjugated structure for high temperature proton exchange membrane fuel cells.

A novel poly(dibenzofuran isatin) (PBFI) with π conjugated structure was synthesized. Through the facile ring-opening reaction, flexible and hydrophilic side chains with hydroxyl and quaternary ammounium groups were grafted into PBFI. Obtained PBFI-x%GTA membranes with twisted polymer structure and multiple hydrogen bonding sites displayed high HT-PEMFC performance.

Probiotic-fermented tomato with hepatic lipid metabolism modulation effects: analysis of physicochemical properties, bioactivities, and potential bioactive compounds.

Lactiplantibacillus plantarum NCUH001046 (LP)-fermented tomatoes exhibited the potential to alleviate obesity in our previous study. This subsequent study further delves deeper into the effects of LP fermentation on the physicochemical properties, bioactivities, and hepatic lipid metabolism modulation of tomatoes, as well as the analysis of potential bioactive compounds exerting obesity-alleviating effects. Results showed that after LP fermentation, viable bacterial counts peaked at 9.11 log CFU mL-1 and sugar decreased, while organic acids, umami amino acids, total phenols, and total flavonoids increased. LP fermentation also improved the inhibition capacities of three digestive enzyme activities and Enterobacter cloacae growth, as well as antioxidant activities. Western blot results indicated that fermented tomatoes, especially live probiotic-fermented tomatoes (LFT), showed improved effects compared to unfermented tomatoes in reducing hepatic lipid accumulation by activating the AMPK signal pathway. UHPLC-Q-TOF/MS-based untargeted metabolomics analysis showed that chlorogenic acid, capsiate, tiliroside, irisflorentin, and homoeriodictyol levels increased after fermentation. Subsequent cell culture assays demonstrated that irisflorentin and homoeriodictyol reduced lipid accumulation via enhancing AMPK expression in oleic acid-induced hyperlipidemic HepG2 cells. Furthermore, Spearman's correlation analysis indicated that the five phenols were positively associated with hepatic AMPK pathway activation. Consequently, it could be inferred that the five phenols may be potential bioactive compounds in LFT to alleviate obesity and lipid metabolism disorders. In summary, these findings underscored the transformative potential of LP fermentation in enhancing the bioactive profile of tomatoes and augmenting its capacity to alleviate obesity and lipid metabolism disorders. This study furnished theoretical underpinnings for the functional investigation of probiotic-fermented plant-based foods.