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Reversible post-translational modifications represent a mechanism to control tumor metabolism. Here we show that mitochondrial Sirtuin5 (SIRT5), which mediates lysine desuccinylation, deglutarylation, and demalonylation, plays a role in colorectal cancer (CRC) glutamine metabolic rewiring. Metabolic profiling identifies that deletion of SIRT5 causes a marked decrease in 13 C-glutamine incorporation into tricarboxylic-acid (TCA) cycle intermediates and glutamine-derived non-essential amino acids. This reduces the building blocks required for rapid growth. Mechanistically, the direct interaction between SIRT5 and glutamate dehydrogenase 1 (GLUD1) causes deglutarylation and functional activation of GLUD1, a critical regulator of cellular glutaminolysis. Consistently, GLUD1 knockdown diminishes SIRT5-induced proliferation, both in vivo and in vitro. Clinically, overexpression of SIRT5 is significantly correlated with poor prognosis in CRC. Thus, SIRT5 supports the anaplerotic entry of glutamine into the TCA cycle in malignant phenotypes of CRC via activating GLUD1. Tumour metabolism can be controlled through post-translational modifications. Here the authors show that Sirtuin5 promotes glutaminolysis in colorectal cancer cells via glutamate dehydrogenase-1, a critical regulator of glutaminolysis, inducing its deglutarylation and functional activation.

Abscisic acid (ABA) is a key hormone involved in tuning responses to several abiotic stresses and also has remarkable impacts on plant defense against various pathogens. The roles of ABA in plant defense against bacteria and fungi are multifaceted, inducing or reducing defense responses depending on its time of action. However, ABA induces different resistance mechanisms to viruses regardless of the induction time. Recent studies have linked ABA to the antiviral silencing pathway, which interferes with virus accumulation, and the micro RNA (miRNA) pathway through which ABA affects the maturation and stability of miRNAs. ABA also induces callose deposition at plasmodesmata, a mechanism that limits viral cell-to-cell movement. Bamboo mosaic virus (BaMV) is a member of the potexvirus group and is one of the most studied viruses in terms of the effects of ABA on its accumulation and resistance. In this review, we summarize how ABA interferes with the accumulation and movement of BaMV and other viruses. We also highlight aspects of ABA that may have an effect on other types of resistance and that require further investigation.

Current deep-learning approaches often encounter significant challenges in English literary analysis, including low accuracy, information loss, and semantic ambiguity. Therefore, this study introduces a novel model combining convolutional neural networks (CNNs), bidirectional gated recurrent units (BiGRUs), and graph neural networks (GNNs). The CNN component is utilized for efficient feature extraction from the input text, whereas the BiGRU layer captures bidirectional dependencies, enabling a more comprehensive understanding of the textual context. Additionally, GNN is employed to model the global dependencies within the text, which is crucial for tasks like sentiment analysis and topic recognition. To further enhance feature extraction, Bidirectional Encoder Representations from Transformers (BERT) is integrated into the model, leveraging its deep contextual representations. For sequence labeling tasks, conditional random fields are utilized to improve prediction accuracy by capturing interdependencies between labels. To optimize the GNN hyperparameters, particle swarm optimization algorithm is applied, ensuring the model’s fine-tuning for better performance. Experimental evaluation on the Microsoft Academic Research Corpus dataset demonstrates the efficacy of the proposed model. Compared to baseline models such as BERT-BiLSTM, BERT-CNN-BiGRU, and BERT-CNN-BiLSTM-ATT, the CNN-BiGRU-GNN model yields significant improvements in accuracy, with gains of 4.57%, 4.11%, and 3.01%, respectively. These results highlight the ability of the model to effectively address the complexities of English literary analysis.

Background The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China has been declared a public health emergency of international concern. The cardiac injury is a common condition among the hospitalized patients with COVID-19. However, whether N terminal pro B type natriuretic peptide (NT-proBNP) predicted outcome of severe COVID-19 patients was unknown. Methods The study initially enrolled 102 patients with severe COVID-19 from a continuous sample. After screening out the ineligible cases, 54 patients were analyzed in this study. The primary outcome was in-hospital death defined as the case fatality rate. Research information and following-up data were obtained from their medical records. Results The best cut-off value of NT-proBNP for predicting in-hospital death was 88.64 pg/mL with the sensitivity for 100% and the specificity for 66.67%. Patients with high NT-proBNP values (> 88.64 pg/mL) had a significantly increased risk of death during the days of following-up compared with those with low values (≤88.64 pg/mL). After adjustment for potential risk factors, NT-proBNP was independently correlated with in-hospital death. Conclusion NT-proBNP might be an independent risk factor for in-hospital death in patients with severe COVID-19. Trial registration ClinicalTrials, NCT04292964. Registered 03 March 2020,

Summary Submergence limits plants' access to oxygen and light, causing massive changes in metabolism; after submergence, plants experience additional stresses, including reoxygenation, dehydration, photoinhibition and accelerated senescence. Plant responses to waterlogging and partial or complete submergence have been well studied, but our understanding of plant responses during post‐submergence recovery remains limited. During post‐submergence recovery, whether a plant can repair the damage caused by submergence and reoxygenation and re‐activate key processes to continue to grow, determines whether the plant survives. Here, we summarize the challenges plants face when recovering from submergence, primarily focusing on studies of Arabidopsis thaliana and rice (Oryza sativa). We also highlight recent progress in elucidating the interplay among various regulatory pathways, compare post‐hypoxia reoxygenation between plants and animals and provide new perspectives for future studies.

Psoriasis is an immune-mediated systemic disease with associated comorbidities, including metabolic syndrome (MetS) which contributes substantially to premature mortality in patients with psoriasis. However, the pathological mechanisms underlying this comorbidity are unclear. Studies have shown that the pathological parameters of psoriasis mediate the development of MetS. We reviewed the potential mechanisms which mediate the association between psoriasis and MetS, including endoplasmic reticulum stress, pro-inflammatory cytokine releases, excess production of reactive oxygen species, alterations in adipocytokine levels and gut microbiota dysbiosis. Here, we highlight important research questions regarding this association and offer insights into MetS research and treatment.

The Cambrian saw a dramatic increase in metazoan diversity and abundance. Between-assemblage diversity (beta diversity) soared in the first three Cambrian stages, suggesting a rapid increase in the geodisparity of marine animals during the Cambrian radiation. However, it remains unclear how these changes scale up to first-order biogeographic patterns. Here we outline time-traceable provinces for marine invertebrates across the Cambrian period using a compositional network based on species-level fossil occurrence data. Results confirm an increase in regional differences of faunal composition and a decrease in by-species geographic distribution during the first three stages. We also show that general biogeography tends to be reshaped after global extinction pulses. We suggest that the abrupt biogeographic differentiation during the Cambrian radiation was controlled by a combination of tectonics, paleoclimate, and dispersal capacity changes.

Background Green tea drinking has been proven to lower lipid and exert cardiovascular protection, while the potential mechanism has not been fully determined. This study was to investigate whether the beneficial impact of epigallocatechingallate (EGCG), a type of catechin in green tea on lipids is associated with proprotein convertase subtilisin/kexin type 9 (PCSK9) pathways. Methods We studied the effects and underlying molecular mechanism of EGCG or green tea on regulating cholesterol from human, animal and in vitro. Results In the age- and gender-matched case control observation, we found that individuals with frequent tea consumption (n = 224) had the lower plasma PCSK9 and low density lipoprotein cholesterol (LDL-C) levels compared with ones without tea consumption (n = 224, p < 0.05). In the high fat diet (HFD) fed rats, EGCG administration significantly lowered circulating PCSK9 concentration and liver PCSK9 expression, along with up-regulated LDL receptor (LDLR) expression but decreased level of LDL-C. In hepatic cell study, similar results were obtained regarding the impact of EGCG on LDLR and PCSK9 expression. The assay transposase-accessible chromatic with high-throughput sequencing (ATAC-seq) and subsequent results suggested that two transcription factors, hepatocyte nuclear factor-1α (HNF-1α) and forkhead box class O (FoxO) 3a involved in inhibitory action of EGCG on PCSK9 expression. Conclusions The present study demonstrates that EGCG suppresses PCSK9 production by promoting nuclear FoxO3a, and reducing nuclear HNF1α, resulting in up-regulated LDLR expression and LDL uptake in hepatocytes. Thereby inhibiting liver and circulating PCSK9 levels, and ultimately lowering LDL-C levels.

One great challenge in understanding the history of life is resolving the influence of environmental change on biodiversity. Simulated annealing and genetic algorithms were used to synthesize data from 11,000 marine fossil species, collected from more than 3000 stratigraphic sections, to generate a new Cambrian to Triassic biodiversity curve with an imputed temporal resolution of 26 ± 14.9 thousand years. This increased resolution clarifies the timing of known diversification and extinction events. Comparative analysis suggests that partial pressure of carbon dioxide (PCO2) is the only environmental factor that seems to display a secular pattern similar to that of biodiversity, but this similarity was not confirmed when autocorrelation within that time series was analyzed by detrending. These results demonstrate that fossil data can provide the temporal and taxonomic resolutions necessary to test (paleo)biological hypotheses at a level of detail approaching those of long-term ecological analyses.

The congruence between rock quantity and biodiversity through the Phanerozoic has long been acknowledged. Rock record bias and common cause are the most discussed hypotheses: the former emphasizes that the changes in diversity through time fully reflect rock availability; the latter posits that the correlation between rock and fossil records is driven by a common cause, such as sea-level changes. Here, we use the Geobiodiversity Database (GBDB), a large compilation of the rock and fossil records, to test the rock bias hypothesis. In contrast to other databases on fossil occurrences, the section-based GBDB also records unfossiliferous units. Our multiple regression analysis shows that 85% of the variation in sampled diversity can be attributed to the rock record, meaning that major peaks and drops in observed diversity are mainly due to the rock record. Our results support a strong covariation between the number of unfossiliferous units and sampled diversity, indicating a genuine rock bias that arose from sampling effort that is independent of fossil content. This provides a compelling argument that the rock record bias is more prominent than common cause in explaining large-scale variations in sampled diversity. Our study suggests that (1) no single proxy can fully represent rock record bias in predicting biodiversity, (2) rock bias strongly governs sampled diversity in both marine and terrestrial communities, and (3) unfossiliferous strata contain critical information in predicting diversity of marine and terrestrial animals.