To attain superior fire safety epoxy resins (EP), aluminum diethylphosphonate (AlPi) and nickel alginate were incorporated to EP in different proportions. The synergistic flame retardant effects ...between AlPi and nickel alginate on fire safety and mechanical properties of EP were investigated in detail. EP/AlPi9.5‐Nickel Alginate0.5 acquired the UL‐94 V‐0 rating with the highest limiting oxygen index value (28.9%). Besides, the thermal decomposition behaviors of the samples were researched by thermogravimetric analysis, implying that EP/AlPi‐Nickel Alginate exhibited the better thermal stability and char‐forming ability. Compared with EP, the peak heat release rate and total heat release were declined by 58.3% and 12.8%. And the addition of nickel alginate reduced the release of smoke. In particular, the incorporation of AlPi and nickel alginate increased the impact strength, flexural strength and glass transition temperature of EP. In perspective, the synergistic effect of bio‐based nickel alginate and AlPi opens a practicable avenue in decreasing the fire risk and improving the mechanical properties of EP.
Marine algae have attracted a great deal of interest as excellent sources of nutrients. Polysaccharides are the main components in marine algae, hence a great deal of attention has been directed at ...isolation and characterization of marine algae polysaccharides because of their numerous health benefits. In this review, extraction and purification approaches and chemico-physical properties of marine algae polysaccharides (MAPs) are summarized. The biological activities, which include immunomodulatory, antitumor, antiviral, antioxidant, and hypolipidemic, are also discussed. Additionally, structure-function relationships are analyzed and summarized. MAPs' biological activities are closely correlated with their monosaccharide composition, molecular weights, linkage types, and chain conformation. In order to promote further exploitation and utilization of polysaccharides from marine algae for functional food and pharmaceutical areas, high efficiency, and low-cost polysaccharide extraction and purification methods, quality control, structure-function activity relationships, and specific mechanisms of MAPs activation need to be extensively investigated.
Abstract
Background
The emergence of coronavirus disease 2019 (COVID-19) is a major healthcare threat. The current method of detection involves a quantitative polymerase chain reaction (qPCR)–based ...technique, which identifies the viral nucleic acids when present in sufficient quantity. False-negative results can be achieved and failure to quarantine the infected patient would be a major setback in containing the viral transmission. We aim to describe the time kinetics of various antibodies produced against the 2019 novel coronavirus (SARS-CoV-2) and evaluate the potential of antibody testing to diagnose COVID-19.
Methods
The host humoral response against SARS-CoV-2, including IgA, IgM, and IgG response, was examined by using an ELISA-based assay on the recombinant viral nucleocapsid protein. 208 plasma samples were collected from 82 confirmed and 58 probable cases (qPCR negative but with typical manifestation). The diagnostic value of IgM was evaluated in this cohort.
Results
The median duration of IgM and IgA antibody detection was 5 (IQR, 3–6) days, while IgG was detected 14 (IQR, 10–18) days after symptom onset, with a positive rate of 85.4%, 92.7%, and 77.9%, respectively. In confirmed and probable cases, the positive rates of IgM antibodies were 75.6% and 93.1%, respectively. The detection efficiency by IgM ELISA is higher than that of qPCR after 5.5 days of symptom onset. The positive detection rate is significantly increased (98.6%) when combining IgM ELISA assay with PCR for each patient compared with a single qPCR test (51.9%).
Conclusions
The humoral response to SARS-CoV-2 can aid in the diagnosis of COVID-19, including subclinical cases.
The time kinetics of humoral responses against the novel coronavirus (SARS-CoV-2) are characterized in patients with COVID-19 by nucleocapsid-based enzyme-linked immunosorbent assay. The antibody testing can aid in the diagnosis of COVID-19 when combined with quantitative polymerase chain reaction, including in subclinical cases.
Distinctive from their normal counterparts, cancer cells exhibit unique metabolic dependencies on glutamine to fuel anabolic processes. Specifically, pancreatic ductal adenocarcinoma (PDAC) cells ...rely on an unconventional metabolic pathway catalyzed by aspartate aminotransferase, malate dehydrogenase 1 (MDH1), and malic enzyme 1 to rewire glutamine metabolism and support nicotinamide adenine dinucleotide phosphate (NADPH) production. Here, we report that methylation on arginine 248 (R248) negatively regulates MDH1. Protein arginine methyltransferase 4 (PRMT4/CARM1) methylates and inhibits MDH1 by disrupting its dimerization. Knockdown of MDH1 represses mitochondria respiration and inhibits glutamine metabolism, which sensitizes PDAC cells to oxidative stress and suppresses cell proliferation. Meanwhile, re-expression of wild-type MDH1, but not its methylation-mimetic mutant, protects cells from oxidative injury and restores cell growth and clonogenic activity. Importantly, MDH1 is hypomethylated at R248 in clinical PDAC samples. Our study reveals that arginine methylation of MDH1 by CARM1 regulates cellular redox homeostasis and suppresses glutamine metabolism of pancreatic cancer.
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•Arginine methylation at R248 negatively regulates MDH1 activity•PRMT4/CARM1 methylates MDH1 at R248 and inhibits its dimerization•MDH1 methylation suppresses glutamine metabolism of pancreatic cancer•R248 methylation of MDH1 is downregulated in clinical PDAC samples
Wang et al. show that arginine methylation at R248 of MDH1, which is catalyzed by PRMT4/CARM1, regulates glutamine metabolism and redox homeostasis of pancreatic cancer cells. MDH1 methylation is downregulated in human PDAC samples.
Cooling load estimation is crucial for energy conservation in cooling systems, with applications like advanced air-conditioning control and chiller optimization. Traditional methods include energy ...simulation and regression analysis, but artificial intelligence outperforms them. Artificial intelligence models autonomously capture complex patterns, adapt, and scale with more data. They excel at predicting cooling loads influenced by various factors, like weather, building materials, and occupancy, leading to dynamic, responsive predictions and energy optimization. Traditional methods simplify real-world complexities, highlighting artificial intelligence’s role in precise cooling load forecasting for energy-efficient building management. This study evaluates Naive Bayes-based models for estimating building cooling load consumption. These models encompass a single model, one optimized with the Mountain Gazelle Optimizer and another optimized with the horse herd optimization algorithm. The training dataset consists of 70% of the data, which incorporates eight input variables related to the geometric and glazing characteristics of the buildings. Following the validation of 15% of the dataset, the performance of the remaining 15% is tested. Based on analysis through evaluation metrics, among the three candidate models, Naive Bayes optimized with the Mountain Gazelle Optimizer (NBMG) demonstrates remarkable accuracy and stability, reducing prediction errors by an average of 18% and 31% compared to the other two models (NB and NBHH) and achieving a maximum R
2
value of 0.983 for cooling load prediction.
The brain is a common site for metastasis in non-small-cell lung cancer (NSCLC). This study was designed to evaluate the relationship between the mutational of the epidermal growth factor receptor ...(EGFR) and overall survival (OS) in NSCLC patients with brain metastases.
Searches were performed in PubMed, EmBase, and the Cochrane Library to identify studies evaluating the association of EGFR mutation with OS in NSCLC patients through September 2017.
4373 NSCLC patients with brain metastases in 18 studies were involved. Mutated EGFR associated with significantly improved OS compared with wild type. Subgroup analyses suggested that this relationship persisted in studies conducted in Eastern, with retrospective design, with sample size ≥500, mean age of patients ≥65.0 years, percentage male < 50.0%, percentage of patients receiving tyrosine kinase inhibitor ≥30.0%. Finally, although significant publication bias was observed using the Egger test, the results were not changed after adjustment using the trim and fill method.
This meta-analysis suggests that EGFR mutation is an important predictive factor linked to improved OS for NSCLC patients with brain metastases. It can serve as a useful index in the prognostic assessment of NSCLC patients with brain metastases.
MicroRNAs (MiRNAs) play multiple crucial regulating roles in cell which can regulate one third of protein-coding genes. MiRNAs participate in the developmental and physiological processes of human ...body, while their aberrant adjustment will be more likely to trigger diseases such as cancers, kidney disease, central nervous system diseases, cardiovascular diseases, diabetes, viral infections and so on. What's worse, for the detection of miRNAs, their small size, high sequence similarity, low abundance and difficult extraction from cells impose great challenges in the analysis. Hence, it's necessary to fabricate accurate and sensitive biosensing platform for miRNAs detection. Up to now, researchers have developed many signal-amplification strategies for miRNAs detection, including hybridization chain reaction, nuclease amplification, rolling circle amplification, catalyzed hairpin assembly amplification and nanomaterials based amplification. These methods are typical, feasible and frequently used. In this review, we retrospect recent advances in signal amplification strategies for detecting miRNAs and point out the pros and cons of them. Furthermore, further prospects and promising developments of the signal-amplification strategies for detecting miRNAs are proposed.
•The development and applications of miRNA is shortly discussed.•Signal-amplification strategies for microRNA detection are discussed in detail.•Emphasis is on the strategies based on oligonucleotide.•Signal-amplification strategies based on nanomaterials are introduced in brief.•Further prospects of signal-amplification strategies are proposed.
Besides the conventional carbon sources, acetyl-CoA has recently been shown to be generated from acetate in various types of cancers, where it promotes lipid synthesis and tumour growth. The ...underlying mechanism, however, remains largely unknown. We find that acetate induces a hyperacetylated state of histone H3 in hypoxic cells. Acetate predominately activates lipogenic genes ACACA and FASN expression by increasing H3K9, H3K27 and H3K56 acetylation levels at their promoter regions, thus enhancing de novo lipid synthesis, which combines with its function as the metabolic precursor for fatty acid synthesis. Acetyl-CoA synthetases (ACSS1, ACSS2) are involved in this acetate-mediated epigenetic regulation. More importantly, human hepatocellular carcinoma with high ACSS1/2 expression exhibit increased histone H3 acetylation and FASN expression. Taken together, this study demonstrates that acetate, in addition to its ability to induce fatty acid synthesis as an immediate metabolic precursor, also functions as an epigenetic metabolite to promote cancer cell survival under hypoxic stress.
Abstract
Background
Protein biomarkers play important roles in cancer diagnosis. Many efforts have been made on measuring abnormal expression intensity in biological samples to identity cancer types ...and stages. However, the change of subcellular location of proteins, which is also critical for understanding and detecting diseases, has been rarely studied.
Results
In this work, we developed a machine learning model to classify protein subcellular locations based on immunohistochemistry images of human colon tissues, and validated the ability of the model to detect subcellular location changes of biomarker proteins related to colon cancer. The model uses representative image patches as inputs, and integrates feature engineering and deep learning methods. It achieves 92.69% accuracy in classification of new proteins. Two validation datasets of colon cancer biomarkers derived from published literatures and the human protein atlas database respectively are employed. It turns out that 81.82 and 65.66% of the biomarker proteins can be identified to change locations.
Conclusions
Our results demonstrate that using image patches and combining predefined and deep features can improve the performance of protein subcellular localization, and our model can effectively detect biomarkers based on protein subcellular translocations. This study is anticipated to be useful in annotating unknown subcellular localization for proteins and discovering new potential location biomarkers.
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•The HTL pathways and mechanisms of lignocellulose components are outlined.•The impact of operating parameters on producing bio-oil are discussed in detail.•Bio-oil upgrades ...contribute to produce liquid fuels and bio-based chemicals.•The limitations and prospects of the current HTL technology are presented.
Abundant, environmentally friendly, and sustainable lignocellulose is a promising feedstock for replacing fossil fuels, and hydrothermal liquefaction is an effective technology to convert it into liquid fuels and high-value chemicals. This review summarizes and discusses the reaction mechanism, main influence factor and the production application of hydrothermal liquefaction. Particular attention has been paid to the reaction mechanism of the structural components of lignocellulose, i.e., cellulose, hemicellulose, and lignin. In addition, the influence factors including types of lignocellulose, temperature, heating rate, retention time, pressure, solid–to-liquid ratio, and catalyst are discussed in detail. The limitations in the hydrothermal liquefaction of lignocellulose and the prospects are proposed. This provides deep knowledge for understanding the process as well as the development of advanced products from lignocellulose.
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