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Reprogramming of amino acid metabolism (AAM) has been established as conducive to tumor cell proliferation and modulation of cellular oxidation-reduction dynamics. However, the intricate characteristics of amino acid metabolism-related genes (AAMRGs) in laryngeal squamous cell carcinoma (LSCC) remain incompletely understood. This study seeks to elucidate these characteristics and construct a prognostic risk model based on AAMRGs to facilitate the development of personalized treatment strategies. Differentially expressed AAMRGs were identified from comprehensive datasets including The Cancer Genome Atlas (TCGA) database, GSE27020 dataset from Gene Expression Omnibus (GEO), and Molecular Signatures Database (MSigDB). Subsequently, protein-protein interaction network analysis and functional enrichment assessment of differentially expressed AAMRGs were conducted. A prognostic risk model was established using least absolute shrinkage and selection operator (LASSO) regression analysis followed by Cox regression analysis. The predictive performance of this risk signature was evaluated using Kaplan-Meier curves and receiver operating characteristic (ROC) curves in both the training and validation sets. Furthermore, the independent prognostic factors were validated using univariate and multivariate Cox regression analyses, and a nomogram was constructed based on these results. Immunohistochemical staining, western blotting, and real-time quantitative polymerase chain reaction (RT-qPCR) were employed to validate the expression of key genes in LSCC clinical samples and cell lines. The effects of SHMT1 overexpression on TU686 cell line was evaluated by CCK-8, wound healing, transwell assay, and flow cytometry. From 45 differentially expressed AAMRGs, SMS, SHMT1, and GPT were identified to compose a prognostic risk scoring model. The high-risk group demonstrated a significantly worse prognosis in both the training and validation sets. Additionally, a nomogram based on independent prognostic factors was developed. Notably, data mining of public databases and analysis of cellular and clinical specimens using IHC, RT-qPCR, and WB demonstrated that SHMT1 expression was decreased in LSCC. Moreover, SHMT1 not only correlated with prognosis but also exhibited associations with the clinical stage of LSCC. We also found that SHMT1 could inhibit the proliferation, migration, and invasion of laryngeal squamous cell carcinoma cells while promoting cell apoptosis by constructing SHMT1-overexpressing cell lines. This study presents a validated prognostic risk score model comprising AAMRGs in LSCC. Furthermore, our findings highlight the downregulation of SHMT1 in LSCC and its significant association with patient prognosis and tumor stage.

The state of health and remaining useful life of lithium-ion batteries are important indicators to ensure the reliable operation of these batteries. However, because they cannot be directly measured and are affected by many factors, they are difficult to predict. This paper presents method of jointly predicting state of health and RUL based on the long short-term memory neural network and Gaussian process regression. This method extracts the batteries’ health factors from the charging curve, selects health factors with more relevance than the setting standard as the characteristic of capacity by the maximum information coefficient method, and establishes the battery aging and remaining useful life prediction models with Gaussian process regression. On this basis, the long short-term memory neural network is used to predict the trend of the change in health factors with the increase in cycles, and the results are input into a Gaussian process regression aging model to predict the state of health. Taking the health factors and state of health as the characteristics of remaining useful battery life, a battery remaining useful life model based on Gaussian process regression is established, and the change trend in the remaining useful life can be obtained by inputting the predicted health factors and state of health. In this study, four battery data sets with different depths of charge were used to verify the accuracy and adaptability of the algorithm. The results show that the proposed algorithm has high accuracy and reliability.

Lithium-ion battery energy storage systems have achieved rapid development and are a key part of the achievement of renewable energy transition and the 2030 “Carbon Peak” strategy of China. However, due to the complexity of this electrochemical equipment, the large-scale use of lithium-ion batteries brings severe challenges to the safety of the energy storage system. In this paper, a new method, based simultaneously on the concepts of statistics and density, is proposed for the potential failure prediction of lithium-ion batteries. As there are no strong assumptions about feature independence and sample distribution, and the estimation of the anomaly scores is conducted by integrating several trees on the isolation path, the algorithm has strong adaptability and robustness, simultaneously. For validation, the proposed method was first applied to two artificial datasets, and the results showed that the method was effective in dealing with different types of anomalies. Then, a comprehensive evaluation was carried out on six public datasets, and the proposed method showed a better performance with different criteria when compared to the conventional algorithms. Finally, the potential failure prediction of lithium-ion batteries of a real energy storage system was conducted in this paper. In order to make full use of the time series characteristics, voltage variation during a whole discharge cycle was taken as the representation of the operation condition of the lithium-ion batteries, and three different types of voltage deviation anomalies were successfully detected. The proposed method can be effectively used for the predictive maintenance of energy storage systems.

Preventing metal deposition by cathodic reduction is a formidable challenge during transition-metal-catalysed electrosynthesis under direct current (d.c.) electrolysis conditions, especially for noble metal catalysis. To overcome the limitation of reductive metal deposition, we now report an asymmetric-waveform alternating current (a.c.) electrolysis protocol for silver-catalysed C–H phosphorylation, where our a.c.-based approach achieves smooth regeneration of the silver catalyst. A wide variety of alkynes, alkenes and (hetero)arenes are reactive under our a.c. electrolysis conditions, delivering the desired phosphite ester derivatives (88 examples) in good yields, whereas these products are often obtained in poor yields under d.c. electrolysis conditions. Notably, this protocol can be expanded to Pd- and Cu-catalysed C–H functionalization. This electrochemical metal-catalysis strategy is distinct from traditional d.c. electrosynthesis and has great potential to be used in the fine organic chemical industry.Preventing metal deposition by cathodic reduction under direct current electrolysis conditions is a formidable challenge in transition-metal-catalysed electrosynthesis. Now, an asymmetric-waveform alternating current (a.c.) electrolysis approach is developed for silver-catalysed C–H phosphorylation where this a.c.-based approach regenerates the silver catalyst and keeps the catalyst loading balanced during the reaction.

Background Coxsackievirus B3 (CV-B3) is usually associated with aseptic meningitis and myocarditis; however, the association between CV-B3 and hand, foot, and mouth disease (HFMD) has not been clearly demonstrated, and the phylogenetic dynamics and transmission history of CV-B3 have not been well summarized. Method Two HFMD outbreaks caused by CV-B3 were described in Hebei Province in 2012 and in Shandong Province in 2016 in China. To analyze the epidemiological features of two CV-B3 outbreaks, a retrospective analysis was conducted. All clinical specimens from CV-B3 outbreaks were collected and disposed according to the standard procedures supported by the WHO Global Poliovirus Specialized Laboratory. EV genotyping and phylogenetic analysis were performed to illustrate the genetic characteristics of CV-B3 in China and worldwide. Results Two transmissible lineages (lineage 2 and 3) were observed in Northern China, which acted as an important “reservoir” for the transmission of CV-B3. Sporadic exporting and importing of cases were observed in almost all regions. In addition, the global sequences of CV-B3 showed a tendency of geographic-specific clustering, indicating that geographic-driven adaptation plays a major role in the diversification and evolution of CV-B3. Conclusions Overall, our study indicated that CV-B3 is a causative agent of HFMD outbreak and revealed the phylogenetic dynamics of CV-B3 worldwide, as well as provided an insight on CV-B3 outbreaks for effective intervention and countermeasures.

The aim of this study was to determine the global genetic diversity and transmission dynamics of coxsackievirus B4 (CVB4) and to propose future directions for disease surveillance. Next-generation sequencing was performed to obtain the complete genome sequence of CVB4, and the genetic diversity and transmission dynamics of CVB4 worldwide were analyzed using bioinformatics methods such as phylogenetic analysis, evolutionary dynamics, and phylogeographic analysis. Forty complete genomes of CVB4 were identified from asymptomatic infected individuals and hand, foot, and mouth disease (HFMD) patients. Frequent recombination between CVB4 and EV-B multiple serotypes in the 3Dpol region was found and formed 12 recombinant patterns (A-L). Among these, the CVB4 isolated from asymptomatic infected persons and HFMD patients belonged to lineages H and I, respectively. Transmission dynamics analysis based on the VP1 region revealed that CVB4 epidemics in countries outside China were dominated by the D genotype, whereas the E genotype was dominant in China, and both genotypes evolved at a rate of > 6.50 × 10−3 substitutions/site/year. CVB4 spreads through the population unseen, with the risk of disease outbreaks persisting as susceptible individuals accumulate. Our findings add to publicly available CVB4 genomic sequence data and deepen our understanding of CVB4 molecular epidemiology.

Nineteen CVA9 isolates were obtained between 2010 and 2019 from six provinces of mainland China, using the HFMD surveillance network established in China. Nucleotide sequencing revealed that the full-length VP1 of 19 CVA9 isolates was 906 bases encoding 302 amino acids. The combination of the thresholds of the phylogenetic tree and nucleotide divergence of different genotypes within the same serotype led to a value of 15–25%, and enabled CVA9 worldwide to be categorized into ten genotypes: A–J. The phylogenetic tree showed that the prototype strain was included in genotype A, and that the B, C, D, E, H, and J genotypes disappeared during virus evolution, whereas the F, I, and G genotypes showed co-circulation. Lineage G was the dominant genotype of CVA9 and included most of the strains from nine countries in Asia, North America, Oceania, and Europe. Most Chinese strains belonged to the G genotype, suggesting that the molecular epidemiology of China is consistent with that observed worldwide. The 165 partial VP1 strains (723 nt) showed a mean substitution rate of 3.27 × 10−3 substitution/site/year (95% HPD range 2.93–3.6 × 10−3), dating the tMRCA of CVA9 back to approximately 1922 (1911–1932). The spatiotemporal dynamics of CVA9 showed the spread of CVA9 obviously increased in recent years. Most CVA9 isolates originated in USA, but the epidemic areas of CVA9 are now concentrated in the Asia–Pacific region, European countries, and North America. Recombination analysis within the enterovirus B specie (59 serotypes) revealed eight recombination patterns in China at present, CVB4, CVB5, E30, CVB2, E11, HEV106, HEV85, and HEV75. E14, and E6 may act as recombinant donors in multiple regions. Comparison of temperature sensitivity revealed that temperature-insensitive strains have more amino acid substitutions in the RGD motif of the VP1 region, and the sites T283S, V284M, and R288K in the VP1 region may be related to the temperature tolerance of CVA9.

Under the background of the severe human health and world economic burden caused by COVID-19, the attenuation of vaccine protection efficacy, and the prevalence and immune escape of emerging variants of concern (VOCs), the third dose of booster immunization has been put on the agenda. Systems biology approaches can help us gain new perspectives on the characterization of immune responses and the identification of factors underlying vaccine-induced immune efficacy. We analyzed the antibody signature and transcriptional responses of participants vaccinated with COVID-19 inactivated vaccine and protein subunit vaccine as a third booster dose. The results from the antibody indicated that the third booster dose was effective, and that heterologous vaccination with the protein subunit vaccine as a booster dose induced stronger humoral immune responses than the homologous vaccination with inactivated vaccine, and might be more effective against VOCs. In transcriptomic analysis, protein subunit vaccine induced more differentially expressed genes that were significantly associated with many important innate immune pathways. Both the homologous and heterologous boosters could increase the effectiveness against COVID-19, and compared with the inactivated vaccine, the protein subunit vaccine, mediated a stronger humoral immune response and had a more significant correlation with the innate immune function module, which provided certain data support for the third booster immunization strategy.

Keel bone damage negatively affects the welfare, production performance, egg quality, and mobility of laying hens. This study aimed to investigate whether abnormal bone metabolism causes keel bone damage in laying hens. Eighty Hy-line Brown laying hens were housed in eight furnished cages with 10 birds per cage and studied from 18 to 29 weeks of age (WOA). Accordingly, keel bone status was assessed at 18, 22, 25, and 29 WOA using the X-ray method, and the serum samples of laying hens with normal keel (NK), deviated keel (DK), and fractured keel (FK) that occurred at 29 WOA were collected across all the time-points. Subsequently, the serum samples were used to measure markers related to the metabolism of Ca and P and activities of osteoblast and osteoclast. The results showed that FK laying hens had lighter bodyweight than NK and DK birds throughout the trial (p < 0.05), while the keel bone length and weight were not different in NK, DK, and FK hens at 29 WOA (p > 0.05). Moreover, bone hematoxylin and eosin (H&E) staining and tartrate-resistant acid phosphatase (TRAP) staining indicated that damaged keel bone had evident pathological changes. In the FK hens, serum P level was reduced but serum 1,25-dihydroxy-vitamin D3 (1,25-(OH)2D3) and 25-hydroxyvitamin D3 (25-OHD3) levels were elevated compared to NK hens (p < 0.05). Additionally, DK hens had higher levels of serum 1,25-(OH)2D3, parathyroid hormone (PTH) and calcitonin (CT), and lower level of serum 25-OHD3 than the NK birds (p < 0.05). Furthermore, serum alkaline phosphatase (ALP), osteocalcin (OC), osteoprotegerin (OPG), TRAP, and corticosterone (CORT) levels were elevated in DK and FK hens compared to NK hens (p < 0.05). The levels of serum Ca, P, PTH, ALP, TRAP, OPG, OC, and CORT in laying hens fluctuated with the age of the birds. Generally, the results of this study indicate that keel bone damage, especially fractures, could be associated with abnormal bone metabolism in laying hens.

Two-dimensional transition-metal dichalcogenides (TMDs) possess interesting catalytic properties for the electrochemical-assisted hydrogen-evolution reaction (HER). We used niobium diselenide (NbSe2) as a representative TMD, and prepared single-layer NbSe2 porous nanosheets (PNS) by a double-sonication liquid-phase exfoliation, with H2O2 as a pore-forming agent. The single-layer NbSe2 PNS were drop-cast on carbon foam (CF) to fabricate a three-dimensional robust NbSe2 PNS/CF electrode. The NbSe2 PNS/CF electrode exhibits a high current density of −50 mA cm−2 with an overpotential of 148 mV and a Tafel slope of 75.8 eV dec−1 for the HER process. Little deactivation is detected in continuous CV testing up to 20,000 cycles, which suggests that this novel NbSe2 PNS/CF is a promising catalytic electrode in the HER application. The porous structure of single-layer NbSe2 nanosheets can enhance the electrochemical performance compared with that of pore-free NbSe2 nanosheets. These findings illustrate that the single-layer NbSe2 PNS is a potential electrocatalytic material for HER. More importantly, the electrochemical performance of the NbSe2 PNS/CF expands the use of two-dimensional TMDs in electrocatalysis-related fields.