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Abstract Sepsis is a life-threatening condition influenced by various factors. Although gene expression profiling has offered new insights, accurately assessing patient risk and prognosis remains challenging. We utilized single-cell and gene expression data of sepsis patients from public databases. The Seurat package was applied for preprocessing and clustering single-cell data, focusing on neutrophils. Lasso regression identified key genes, and a prognostic model was built. Model performance was evaluated using Receiver Operating Characteristic (ROC) curves, and further analyses, including immune cell infiltration, Gene Set Enrichment Analysis (GSEA), and clinical correlation, were conducted. Several neutrophil subtypes were identified with distinct gene expression profiles. A prognostic model based on these profiles demonstrated strong predictive accuracy. Risk scores were significantly correlated with clinical features, immune responses, and key signalling pathways. This study provides a comprehensive analysis of sepsis at the molecular level. The prognostic model shows promise in predicting patient outcomes, offering potential new strategies for diagnosis and treatment.

Abstract Background Sphingosine-1-phosphate (S1P) is a multifunctional sphingolipid that has been implicated in regulating cellular activities in mammalian cells. Due to its therapeutic potential, there is a growing interest in developing efficient methods for S1P production. To date, the production of S1P has been achieved through chemical synthesis or blood extraction, but these processes have limitations such as complexity and cost. In this study, we generated an S1P-producing Saccharomyces cerevisiae strain by using metabolic engineering and introducing a heterologous sphingolipid biosynthetic pathway to demonstrate the possibility of microbial S1P production. Results To construct the sphingosine-producing S. cerevisiae strain, both the sphingolipid delta 4 desaturase gene (DES1) and the alkaline ceramidase gene (ACER1) derived from Homo sapiens were introduced into the genome of S. cerevisiae by deleting the dihydrosphingosine phosphate lyase gene (DPL1) and the sphingoid long-chain base kinase gene (LCB5) to prevent S1P degradation and byproduct formation, respectively. The sphingosine-producing strain, DDLA, produced sphingolipids containing sphingosine. In flask fed-batch fermentation, the DDLA strain showed a higher production level of sphingosine under aerobic conditions with high initial cell density. The S1P-producing strain was generated by expressing the human sphingosine kinase gene (SPHK1) under the control of the inducible promoter, while deleting the ORM1 gene involved in the regulation of sphingolipid biosynthesis. The S1P-producing strain, DDLAOgS, exhibited the highest sphingosine production level under fed-batch fermentation in a bioreactor, achieving a 2.6-fold increase compared to flask fermentation. S1P biosynthesis in the DDLAOgS strain was verified by qualitative analysis using electrospray ionization mass spectrometry (ESI–MS). Conclusions We successfully developed a metabolically engineered S. cerevisiae as a platform strain for microbial production of S1P by introducing an exogenous pathway of sphingolipids metabolism. The engineered yeast strains showed significant capabilities for sphingolipid production, including S1P. To our knowledge, this is the first report demonstrating that engineered S. cerevisiae can be a major platform strain for producing microbial S1P. Graphical Abstract

In this study, we proposed a multi-source approach for mapping local-scale population density of England. Specifically, we mapped both the working and daytime population densities by integrating the multi-source data such as residential population density, point-of-interest density, point-of-interest category mix, and nighttime light intensity. It is demonstrated that combining remote sensing and social sensing data provides a plausible way to map annual working or daytime population densities. In this paper, we trained models with England-wide data and subsequently tested these models with Wales-wide data. In addition, we further tested the models with England-wide data at a higher level of spatial granularity. Particularly, the random forest and convolutional neural network models were adopted to map population density. The estimated results and validation suggest that the three built models have high prediction accuracies at the local authority district level. It is shown that the convolutional neural network models have the greatest prediction accuracies at the local authority district level though they are most time-consuming. The models trained with the data at the local authority district level are less appropriately applicable to test data at a higher level of spatial granularity. The proposed multi-source approach performs well in mapping local-scale population density. It indicates that combining remote sensing and social sensing data is advantageous to mapping socioeconomic variables.

Regulating macrophage phenotypes to reconcile the conflict between bacterial suppression and tissue regeneration is ideal for treating infectious skin wounds. Here, an injectable immunoregulatory hydrogel (SrmE20) that sequentially drives macrophage phenotypic polarization (M0 to M1, then to M2) was constructed by integrating anti-inflammatory components and proinflammatory solvents. In vitro experiments demonstrated that the proinflammatory solvent ethanol stabilized the hydrogel structure, maintained the phenolic hydroxyl group activity, and achieved macrophages' proinflammatory transition (M0 to M1) to enhance antibacterial effects. With ethanol depletion, the hydrogel's cations and phenolic hydroxyl groups synergistically regulated macrophages' anti-inflammatory transition (M1 to M2) to initiate regeneration. In the anti-contraction full-thickness wound model with infection, this hydrogel effectively eliminated bacteria and even achieved anti-inflammatory M2 macrophage accumulation at three days post-surgery, accelerated angiogenesis and collagen deposition. By sequentially driving macrophage phenotypic polarization, this injectable immunoregulatory hydrogel will bring new guidance for the care and treatment of infected wounds.

As the penetration rate of renewable energy in new power systems continues to increase, these systems face serious frequency control issues. The limitations of traditional methods for addressing frequency control lie primarily in their reliance on the frequency regulation capability of a single battery energy storage system (BESS). This dependence not only requires a complex communication infrastructure to transmit remote control signals but also is susceptible to communication delays, leading to system instability. This paper proposes a distributed BESS robust frequency control method (load frequency control (LFC)) based on a sparse communication network, aiming to address the limitations of traditional methods in terms of communication infrastructure requirements and the impact of communication delays. Subsequently, a dual-layer model predictive control (MPC) strategy is designed. The first layer uses a nominal model for predictive control, while the second layer considers system uncertainties for auxiliary control to improve the response characteristics of the BESS, thus significantly enhancing LFC performance and achieving more effective frequency regulation. Finally, simulation results show that under different parameter conditions, such as capacity, state of charge (SoC), and time constants, the response capability and frequency regulation effect of the distributed BESS are significantly better than those of traditional methods.

Abstract Background There is no optimal reconstruction technique after proximal gastrectomy. The esophagogastrostomy (EG) is a rather simple procedure technically, but the incidences of reflux esophagitis and anastomotic stricture are higher. While the double-tract reconstruction (DTR) can lessen postoperative reflux esophagitis, it is technically complex with a long operation time. The purpose of this study was to evaluate the quality of life (QoL) and short-term outcomes of the two reconstruction techniques. Methods We retrospectively collected consecutive patients with upper-third gastric adenocarcinoma and adenocarcinoma of the esophagogastric junction (AEG) at our center between 2019 June and 2023 May. Patients who underwent laparoscopic proximal gastrectomy (LPG) with EG or DTR were included in this study. A comparison was made between the clinical and pathological characteristics of patients and their surgical parameters, postoperative complications, and its 1-year QoL in two groups. The QoL of the two groups was assessed by Visick grading, the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 and EORTC QLQ-STO22 scales at 1 year after operation. The nutritional status of the two groups was evaluated by BMI, hemoglobin and serum albumin. Results AII the qualified patients were divided EG group (n = 63) and DTR group (n = 93). Compared to the DTR group, the blood loss volume of EG group was more (p = 0.001). There were no significant differences in operation duration, number of lymph nodes dissected, and postoperative length of stay between the two groups(p > 0.05). No statistical differences were observed in terms of the incidence of early complications and Clavien-Dindo classification as well(p > 0.05). After one year, the Visick grade of the DTR group was better than EG group (p = 0.040). The multivariable logistic regression analysis showed the only independent risk factor for reflux esophagitis was the reconstruction method. According to the EORTC QLQ-C30 questionnaire, patients in the DTR group had a better global health status(p = 0.001) and complained less about nausea and vomiting(p = 0.033), and appetite loss (p = 0.022). Patients in the DTR group complained less about reflux (p = 0.030) based on the EORTC QLQ-STO22 questionnaire. The multiple linear regression analysis revealed that the reconstruction method, reflux esophagitis and age had a linear relationship with the global health status score. Regarding nutritional status, BMI of the two groups both decreased 1 year after operation, and BMI decline value of the DTR group was lower than EG group (p = 0.001). There is no statistically significant difference between the two groups as for postoperative change in hemoglobin and serum albumin. Conclusion Our findings suggest that it is possible for skilled surgeons to achieve minimal blood loss volume without significantly increasing operation duration when performing DRT, which does not raise risk. In terms of anti-reflux, postoperative QoL and BMI maintenance, 1-year postoperative follow-up outcomes reveal the DTR is superior to EG, which deserve further research and promotion.

Abstract Background Cancer is the leading cause of disease-related mortality in children. Causes of leukemia, the most common form, are largely unknown. Growing evidence points to an origin in-utero, when global redistribution of DNA methylation occurs driving tissue differentiation. Methods Epigenome-wide DNA methylation was profiled in surrogate (blood) and target (bone marrow) tissues at birth, diagnosis, remission and relapse of pediatric pre-B acute lymphoblastic leukemia (pre-B ALL) patients. Double-blinded analyses was performed between prospective cohorts extending from birth to diagnosis and retrospective studies backtracking from clinical disease to birth. Validation was carried out using independent technologies and populations. Results The imprinted and immuno-modulating VTRNA2-1 was hypermethylated (FDR

Abstract Salmonella Enteritidis is a major foodborne pathogen throughout the world and the increase in antibiotic resistance of Salmonella poses a significant threat to public safety. Natural nanobodies exhibit high affinity, thermal stability, ease of production, and notably higher diversity, making them widely applicable for the treatment of viral and bacterial infections. Recombinant expression using Lactococcus lactis leverages both acid resistance and mucosal colonization properties of these bacteria, allowing the effective expression of exogenous proteins for therapeutic effects. In this study, nine specific nanobodies against the flagellar protein FliC were identified and expressed. In vitro experiments demonstrated that FliC-Nb-76 effectively inhibited the motility of S. Enteritidis and inhibited its adhesion to and invasion of HIEC-6, RAW264.7, and chicken intestinal epithelial cells. Additionally, a recombinant L. lactis strain secreting the nanobody, L. lactis-Nb76, was obtained. Animal experiments confirmed that it could significantly reduce the mortality rates of chickens infected with S. Enteritidis, together with alleviating the inflammatory response caused by the pathogen. These results provide a novel strategy for the treatment of antibiotic-resistant S. Enteritidis infection in the intestinal tract. Graphical Abstract

Abstract Background Early targeted antibiotic therapy is crucial for improving the prognosis of immunocompromised patients with severe respiratory infections (SRIs) in the intensive care unit (ICU). Metagenomic next-generation sequencing (mNGS) has shown significant value in pathogen detection, but research on lower respiratory tract microorganisms remains limited. Methods This study enrolled 234 patients with SRIs in the ICU, and individuals were categorized into immunocompromised and immunocompetent groups. We compared the diagnostic performance of mNGS using bronchoalveolar lavage fluid (BALF) with conventional microbiological tests (CMTs) and analyzed the value of mNGS in immunocompromised patients with SRIs in the ICU. Results Among all patients, the pathogenic microorganism detection rate of mNGS was higher than that of CMTs (94.02% vs 66.67%, P 0.05; 42.67% vs 45.83%, P > 0.05). Conclusion mNGS shows significant value in detecting pathogens in immunocompromised patients with SRIs in ICU. For immunocompromised patients who respond poorly to empirical treatment, mNGS can provide an etiological basis, helping adjust antibiotic regimens more precisely and thereby improving patient prognosis.

Abstract Anaerobic digestion (AD) is an efficient technology for treating organic solid wastes, and the volatile fatty acids (VFAs) produced during AD have significant value due to their wide range of applications and higher added value compared to methane. This study investigated the long-term effects of high solid content and straw proportion in mixed substrates (straw, sludge, and food wastes) on VFAs production through semi-continuous reactors under thermophilic and mesophilic conditions. Results showed that both reactors achieved a maximum VFAs concentration of ~ 22 g/L as the straw proportion increased to 50%. Acetate (48.3 – 64.5%) was the main component of produced VFAs in both reactors, while butyrate and propionate production in thermophilic temperature were superior compared to mesophilic conditions. Microbial community analysis revealed that Defluviitoga plays a pivotal role in acidogenesis within both reactors; besides, unclassified Hungateiclostridiaceae and Caproiciproducen were found to be dominant in thermophilic reactor, while Lachnospiraceae_NK3A20_group and Rikenellaceae_RC9_gut_group were essential for VFAs production under mesophilic conditions. These findings provide valuable insights for the biotechnological exploration of acidogenic fermentation for large-scale mechanized production of VFAs from agricultural wastes.

Abstract Purpose The aim of this study is to delve into the value of N6-Methyladenosine (m6A)-associated genes (MAGs) in pancreatic cancer (PC) prognosis. Methods PC sequencing data and corresponding clinicopathological information were retrieved from GEO and TCGA databases. We filtered 19 MAGs in PC specimens and implemented functional annotation in biology. Later, the m6A modification pattern was stratified into m6Acluster A-B according to MAG expression levels, and further categorized into genecluster A-C based on differentially expressed genes between m6Acluster A and B. Next, a MAG-based prognostic prediction model was established by the least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate Cox regression analysis. At last, the role of KRT7 in PC were explored. Results We found m6Acluster A pattern presented enrichment pathways associated with cell apoptosis, proliferation, migration, and cancer pathways. Additionally, high-risk group displayed more dismal prognosis and a higher programmed death-ligand 1 expression. The survival prediction ability of the model was verified in three independent PC GEO datasets. KRT7 is the most momentous risk gene in the established prognostic model. Among 18 clinical samples, the KRT7 protein in the surviving patient samples is lower than that in the deceased patient samples. We also identified elevated expression of KRT7 in PC tumor tissues compared to normal tissues using GEPIA 2. Then, the metastasis of PC cells was promoted by overexpressed KRT7 in vitro and in vivo. And IGF2BP3 upregulated KRT7 by increasing the mRNA stability of KRT7. Conclusions The PPM built based on CXCL5, LY6K and KRT7 is an encouraging biomarker to define the prognosis. Additionally, IGF2BP3 promoted KRT7 by stabilizing mRNA of KRT7. And KRT7 promoted the metastasis of PC cells by promoting EMT.

Abstract Objective To analyze the spatial autocorrelation and spatiotemporal clustering characteristics of severe fever with thrombocytopenia syndrome(SFTS) in Anhui Province from 2011 to 2023. Methods Data of SFTS in Anhui Province from 2011 to 2023 were collected. Spatial autocorrelation analysis was conducted using GeoDa software, while spatiotemporal scanning was performed using SaTScan 10.0.1 software to identify significant spatiotemporal clusters of SFTS. Results From 2011 to 2023, 5720 SFTS cases were reported in Anhui Province, with an average annual incidence rate of 0.7131/100,000. The incidence of SFTS in Anhui Province reached its peak mainly from April to May, with a small peak in October. The spatial autocorrelation results showed that from 2011 to 2023, there was a spatial positive correlation(P

Abstract T cell immunoglobulin and mucin-containing molecule 3 (TIM-3) exhibits unique, cell type- and context-dependent characteristics and functions. Here, we report that TIM-3 on myeloid cells plays essential roles in modulating lung inflammation. We found that myeloid cell-specific TIM-3 knock-in (FSF-TIM3/LysM-Cre+) mice have lower body weight and shorter lifespan than WT mice. Intriguingly, the lungs of FSF-TIM3/LysM-Cre+ mice display excessive inflammation and features of disease-associated pathology. We further revealed that galectin-3 levels are notably elevated in TIM-3-overexpressing lung-derived myeloid cells. Furthermore, both TIM-3 blockade and GB1107, a galectin-3 inhibitor, ameliorated lung inflammation in FSF-TIM3/LysM-Cre+/− mice. Using an LPS-induced lung inflammation model with myeloid cell-specific TIM-3 knock-out mice, we demonstrated the association of TIM-3 with both lung inflammation and galectin-3. Collectively, our findings suggest that myeloid TIM-3 is an important regulator in the lungs and that modulation of TIM-3 and galectin-3 could offer therapeutic benefits for inflammation-associated lung diseases.

Epoxy resin is widely used in electrical equipment and electronic devices fields due to its excellent electrical, thermal, and mechanical properties. However, its internal three-dimensional covalent interconnection structure brings barriers to its degradability and recycling because covalent bonds cannot be broken easily. With the replacements of power equipment and electronic devices, there will be more and more epoxy resins and their composites in them to be treated and effective recycling is of great significance for resource conservation and environmental protection. In this review article, recent progress in degradation and recycling of epoxy resin is introduced and the effect of three traditional degradation methods is discussed. The drawbacks of these methods are thought to come from the intrinsic properties of these epoxy resins. So the urgency of developing new kinds of degradable epoxy resins is proposed. Then different types of new degradable epoxy resins are reviewed. Degradation mechanisms of the opened-loop recycling and recycling methods of the closed-loop recycling are summarized in detail. Finally, the challenges and perspectives are discussed based on their current developments. This review comprehensively considers both traditional degradation methods and new methods for developing degradable epoxy resins. It covers not only an overview of the state-of-the-art advances of degradation and recycling of epoxy resin but also the prospects that provide reference for the synthesis of degradable epoxy resin materials.

Osteoporosis (OP)-associated fractures can result in severe morbidity and disability, reduced quality of life, and death. Previous studies have suggested that small noncoding RNAs, for example, small regulatory microRNAs (miRNAs), play a key role in OP by inhibiting target gene expression. Cuproptosis, a recently proposed copper-induced cell death pathway, is linked with OP. Here, we describe the contribution of exosomal miRNAs and cuproptosis to OP. First, we highlight the characteristics of exosomes and roles of exosome-related miRNAs. Next, we discuss the relationship between cuproptosis and OP. Subsequently, we analyze the crosstalk of exosomal miRNAs with cuproptosis in the development of OP. This review aims to investigate a new clinical treatment method for OP.

Abstract It remains unresolved whether the La Niña-like sea surface temperature (SST) trend pattern during the satellite era, featuring a distinct warming in the northwest/southwest Pacific but cooling in the tropical eastern Pacific, is driven by either external forcing or internal variability. Here, by conducting a comprehensive analysis of observations and a series of climate model simulations for the historical period, we show that a combination of internal variability and human activity may have shaped the observed La Niña-like SST trend pattern. As in observations, SSTs in each model ensemble member show a distinct multi-decadal swing between El Niño-like and La Niña-like trend patterns due to internal variability. The ensemble-mean trends for some models are, however, found to exhibit an enhanced zonal SST gradient along the equatorial Pacific over periods such as 1979–2010, suggesting a role of external forcing. In line with this hypothesis, single-forcing large ensemble model simulations show that human-induced stratospheric ozone depletion and/or aerosol changes have acted to enhance the zonal SST gradient via strengthening of Pacific trade winds, although the effect is model dependent. Our finding suggests that the La Niña-like SST trend is unlikely to persist under sustained global warming because both the ozone and aerosol impacts will eventually weaken.

The conversion of biomass into sugar platform compounds is very important for the biorefinery industry. Pretreatment is essential to the biomass of the sugar platform, however, the lignin obtained by pretreatment, as a key part of lignocellulose, generally has a passive effect on the enzymatic hydrolysis of cellulose into sugars. In this study, p-TsOH (p-toluenesulfonic acid), DES (Deep eutectic solvent) and CAOSA (cooking with active oxygen and solid alkali) pretreatment ways were used to fraction lignin from bamboo biomass. After CAOSA treatment, the hydrolysis efficiency of the pulp was 95.57%. Moreover, the effect of different treatment methods on lignin properties was studied and the promotion effect of lignin was investigated by adding it to the cellulose enzymatic hydrolysis system. In this work, the results showed that CAOSA-extracted lignin with lower Đ (1.31–1.25) had a better adsorption effect on the enzyme protein. p-TsOH-extracted lignin with a larger S/G ratio enhanced the inhibition of enzymatic hydrolysis. In addition, the presence of -COOHs in lignin could reduce its inhibitory effect on cellulose saccharification.

The eukaryotic serine/threonine protein phosphatase PP2A is a heterotrimeric enzyme composed of a scaffold A subunit, a regulatory B subunit, and a catalytic C subunit. Of the four known B subunits, the B"' subunit (known as striatin) interacts with the multi-protein striatin-interacting phosphatase and kinase (STRIPAK) complex. Orthologs of STRIPAK components were identified in Cryptococcus neoformans, namely PP2AA/Tpd3, PP2AC/Pph22, PP2AB/Far8, STRIP/Far11, SLMAP/Far9, and Mob3. Structural modeling, protein domain analysis, and detected protein-protein interactions suggest C. neoformans STRIPAK is assembled similarly to the human and fungal orthologs. Here, STRIPAK components Pph22, Far8, and Mob3 were functionally characterized. Whole-genome sequencing revealed that mutations in STRIPAK complex subunits lead to increased segmental and chromosomal aneuploidy, suggesting STRIPAK functions in maintaining genome stability. We demonstrate that PPH22 is a haploinsufficient gene: heterozygous PPH22/pph22Δ mutant diploid strains exhibit defects in hyphal growth and sporulation and have a significant fitness disadvantage when grown in competition against a wild-type diploid. Deletion mutants pph22Δ, far8Δ, and mob3Δ exhibit defects in mating and sexual differentiation, including impaired hyphae, basidia, and basidiospore production. Loss of either PPH22 or FAR8 in a haploid background leads to growth defects at 30°C, severely reduced growth at elevated temperature, abnormal cell morphology, and impaired virulence. Additionally, pph22Δ strains frequently accumulate suppressor mutations that result in overexpression of another putative PP2A catalytic subunit, PPG1. The pph22Δ and far8Δ mutants are also unable to grow in the presence of the calcineurin inhibitors cyclosporine A or FK506, and thus these mutations are synthetically lethal with loss of calcineurin activity. Conversely, mob3Δ mutants display increased thermotolerance, capsule production, and melanization, and are hypervirulent in a murine infection model. Taken together, these findings reveal that the C. neoformans STRIPAK complex plays an important role in genome stability, vegetative growth, sexual development, and virulence in this prominent human fungal pathogen.

Summary: Non-small cell lung cancer (NSCLC) collective invasion is supported by cooperativity of proliferative (follower) and invasive (leader) cells. H1299-isolated follower cells exhibit higher Yes-associated protein (YAP) expression, while leader cells were found to express elevated transcriptional coactivator with PDZ-binding motif (TAZ/WWTR1) expression. Suppressing TAZ (not YAP) in leader cells reduced invasion. TAZ-regulated leader cell invasion is associated with activation of the EGFR-PI3K-AKT axis. NSCLC patient samples also demonstrated heterogeneity in YAP and TAZ expression. YAP and TAZ regulate proliferation of follower and leader cells. Our results highlight the need to inhibit both YAP and TAZ to effectively target their regulation of collective invasion. We identify that the SUMOylation inhibitor TAK-981 reduces YAP and TAZ expression, decreasing tumor burden and metastasis in a murine NSCLC model. Our study reveals an intra-tumoral division of labor, driven by differential YAP and TAZ expression, which can be effectively targeted with TAK-981 for NSCLC therapy.

The spontaneous coal combustion seriously affects the safety production of coal mine, and halogenation is one of the main measures to prevent and control the spontaneous coal combustion. The prerequisite for optimizing the inhibition process and improving the inhibition effect is to master the physical and chemical inhibition mechanism of inhibitor. Therefore, it is particularly important to explore the main inhibition methods of spontaneous coal combustion by halogen inhibitor, and to determine the contribution ratio of the physical and chemical inhibition to coal seam. Based on this, a method was proposed to quantitatively identify the inhibition effect of halogen inhibitor. The representative MgCl2 inhibitor in halogenation was selected, the ultrasonic washer was used to repeatedly rinse the inhibiting and washing coal samples to obtain the experimental and reference coal samples. The change law of index gas concentration, cross point temperature, retarding rate and active functional group of different coal samples was investigated by temperature programmed experiments and infrared spectrum experiments. The physical and chemical retarding effect of halide retarder was studied from both macro and micro perspectives. The results indicated that the gas production concentration, cross-point temperature, inhibition rate and active functional group content of the washed and inhibited coal sample were significantly lower than those of the original coal sample, but higher than those of the inhibited coal sample. This suggested that the MgCl2 inhibitor had a synergistic effect on inhibiting the spontaneous coal combustion and possessed a dual physicochemical inhibition effect. In the initial stage of coal oxygen reaction, there was a greater physical resistance compared to chemical resistance. However, in the later stages of the reaction, the chemical resistance dominated and significantly surpassed the physical resistance. The chemical inhibition effect of MgCl2 was reflected in that it can react with the active substances in coal to form a relatively stable substance (ROCl) and magnesium complex (Mg(OH)Cl). This transformation significantly diminished the reactivity of coal, thereby mitigated the potential risk of coal self-heating. The contribution ratios of physical and chemical effects of MgCl2 inhibitors to Pingzhuang lignite were 56.37% and 43.63%, to Tongxin bituminous coal 57.91% and 42.09%, and to Baijigou anthracite 59.60% and 40.40%. With the increase of metamorphism degree of coal samples, the contribution ratio of physical resistance increased, and the contribution ratio of chemical resistance decreased. The chemical resistance ratio of Pingzhuang lignite was 1.08 times that of Baijigou anthracite. This paper was of great significance to the mechanism of the rich halide inhibitor and provides theoretical guidance for optimizing the fire prevention process.

Abstract The progression of colorectal cancer is closely associated with diet. Fasting-mimicking diet (FMD) is a promising type of dietary intervention that have beneficial effects in the prevention and treatment of various cancers. We investigated the therapeutic effect of 4-day FMD against colorectal cancer in mice through immune cell analysis, microbiota composition analysis and anti-PD-1 treatment. These FMD cycles effectively suppressed colorectal cancer growth, reduced cell proliferation and angiogenesis, increased tumor-infiltration lymphocytes especially CD8+T cells. FMD stimulated protective gut microbiota, especially Lactobacillus. Supplementation of Lactobacillus johnsonii induced similar results as FMD intervention, which also suppressed tumor growth and increased CD45+ and CD8+ T cells. Additionally, FMD synthesizing with anti-PD-1 therapy effectively inhibited CRC progression. These findings suggest that Lactobacillus. johnsonii is necessary for the anticancer process of FMD in CRC. FMD through its effects on both gut microbiota and immune system, effectively suppressed colorectal cancer progression in mouse model.

Abstract How to prevent and resolve COVID-19 pandemic and similar public health crisis is a significant research topic. Although research on science literacy has been involved in dealing with public health crisis, there is a lack of empirical tests between the mass public’s science literacy and co-production during COVID-19 pandemic. With the empirical evidence from 140 cities in China, the study finds that the public’s science literacy significantly promotes co-production in the battle against pandemic. Specifically, for every 1% increase in the mass public’s science literacy in the city, co-production increased by 14.2%. Meanwhile, regional education level and local government capacity can expand the positive role of the public’s science literacy on co-production to fight against COVID-19 pandemic. In addition, the performance of the public’s science literacy on co-production against pandemic shows heterogeneity at different stages of pandemic prevention, in different regions, and in cities of different scales. This study complemented the gaps in existing research on science literacy and co-production and empirically verified the potential positive role of the public’s science literacy in pandemic prevention and control. Furthermore, it provided new ideas for improving the effectiveness of public co-production in public health crisis governance.

Abstract The mid-Piacenzian warm period (MPWP, ~3.264–3.025 Ma) has gained widespread interest due to its partial analogy with future climate. However, quantitative data–model comparison of East Asian Summer Monsoon (EASM) precipitation during the MPWP is relatively rare, especially due to problems in decoding the imprint of physical processes to climate signals in the records. In this study, pollen-based precipitation records are reconstructed and compared to the multi-model ensemble mean of the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2). We find spatially consistent precipitation increase in most simulations but a spatially divergent change in MPWP records. We reconcile proxy data and simulation by decomposing physical processes that control precipitation. Our results 1) reveal thermodynamic control of an overall enhancement of EASM precipitation and 2) highlight a distinct control of thermodynamic and dynamical processes on increases of tropical and subtropical EASM precipitation, reflecting the two pathways of water vapor supply that enhance EASM precipitation, respectively.

Abstract Background Patients with primary multifocal hepatocellular carcinoma (HCC) have a poor prognosis and often experience a high rate of treatment failure. Multifocal HCC is mainly caused by intrahepatic metastasis (IM), and though portal vein tumor thrombosis (PVTT) is considered a hallmark of IM, the molecular mechanism by which primary HCC cells invade the portal veins remains unclear. Therefore, it is necessary to recognize the early signs of metastasis of HCC to arrange better treatment for patients. Results To determine the differential molecular features between primary HCC with and without phenotype of metastasis, we used the CIBERSORTx software to deconvolute cell types from bulk RNA-Seq based on a single-cell transcriptomic dataset. According to the relative abundance of tumorigenic and metastatic hepatoma cells, VEGFA + macrophages, effector memory T cells, and natural killer cells, HCC samples were divided into five groups: Pro-T, Mix, Pro-Meta, NKC, and MemT, and the transcriptomic and genomic features of the first three groups were analyzed. We found that the Pro-T group appeared to retain native hepatic metabolic activity, whereas the Pro-Meta group underwent dedifferentiation. Genes highly expressed in the group Pro-Meta often signify a worse outcome. Conclusions The HCC cohort can be well-typed and prognosis predicted according to tumor microenvironment components. Primary hepatocellular carcinoma may have obtained corresponding molecular features before metastasis occurred.

Circular RNAs (circRNAs) are ideal biomarkers of oral squamous cell carcinoma (OSCC) because of their highly stable closed-loop structure, and they can act as microRNA (miRNA) sponges to regulate OSCC progression. By analyzing clinical samples, we identified circCPNE1, a dysregulated circRNA in OSCC, and its expression level was negatively correlated with the clinical stage of OSCC patients. Gain-of-function assays revealed the tumor-suppressive effect of circCPNE1, which was then identified as a miR-330-3p sponge. MiR-330-3p was recognized as a tumor promoter in multiple studies, consistent with our finding that it could promote the proliferation, migration, and invasion of OSCC cells. These results indicated that selective inhibition of miR-330-3p could be an effective strategy to inhibit OSCC progression. Therefore, we designed cationic polylysine-cisplatin prodrugs to deliver antagomiR-330-3p (a miRNA inhibitory analog) via electrostatic interactions to form PP@miR nanoparticles (NPs). Paratumoral administration results revealed that PP@miR NPs effectively inhibited subcutaneous tumor progression and achieved partial tumor elimination (2/5), which confirmed the critical role of miR-330-3p in OSCC development. These findings provide a new perspective for the development of OSCC treatments.

Alginate oligosaccharides (AOS) are low molecular mass linear polymers containing 2–10 monosaccharides obtained by the degradation of alginate. They have various bioactivities including anti-inflammatory, antibacterial, antioxidant, antitumor, and immunomodulation. Thus, AOS have a wide range of applications in the fields of medicine, food, feed and agriculture. The bioactivity of AOS is closely related to its structure, including mode of degradation, degree of polymerization, ratio of mannuronic acid to guluronic acid, non-reducing end structure, and modification. Directed enzymatic degradation of alginate produces functional AOS with specific monomer composition and polymerization degree. Furthermore, the sources, properties and reaction conditions of enzymes affect the product distribution. In this article, the enzymatic preparation of functional AOS and its influential factors are systematically reviewed, and the structure-function relationship of functional AOS is discussed. It is expected that this review will provide a theoretical reference for the directed preparation and application of AOS.

Abstract The advent of Industry 4.0 has significantly promoted the field of intelligent manufacturing, which is facilitated by the development of new technologies are emerging. Robot technology and robot intelligence methods have rapidly developed and been widely applied. Manipulators are widely used in industry, and their control is a crucial research topic. The inverse kinematics solution of manipulators is an important part of manipulator control, which calculates the joint angles required for the end effector to reach a desired position and posture. Traditional inverse kinematics solution algorithms often face the problem of insufficient generalization, and iterative methods have challenges such as large computation and long solution time. This paper proposes a reinforcement learning-based inverse kinematics solution algorithm, called the MAPPO-IK algorithm. The algorithm trains the manipulator agent using the MAPPO algorithm and calculates the difference between the end effector state of the manipulator and the target posture in real-time by designing a reward mechanism, while considering Gaussian distance and cosine distance. Through experimental comparative analysis, the feasibility, computational efficiency, and superiority of this reinforcement learning algorithm are verified. Compared with traditional inverse kinematics solution algorithms, this method has good generalization and supports real-time computation, and the obtained result is a unique solution. Reinforcement learning algorithms have better adaptability to complex environments and can handle different sudden situations in different environments. This algorithm also has the advantages of path planning, intelligent obstacle avoidance, and other advantages in dynamically processing complex environmental scenes.

Abstract Background The production of succinic acid (SA) from biomass has attracted worldwide interest. Saccharomyces cerevisiae is preferred for SA production due to its strong tolerance to low pH conditions, ease of genetic manipulation, and extensive application in industrial processes. However, when compared with bacterial producers, the SA titers and productivities achieved by engineered S. cerevisiae strains were relatively low. To develop efficient SA-producing strains, it’s necessary to clearly understand how S. cerevisiae cells respond to SA. Results In this study, we cultivated five S. cerevisiae strains with different genetic backgrounds under different concentrations of SA. Among them, KF7 and NBRC1958 demonstrated high tolerance to SA, whereas NBRC2018 displayed the least tolerance. Therefore, these three strains were chosen to study how S. cerevisiae responds to SA. Under a concentration of 20 g/L SA, only a few differentially expressed genes were observed in three strains. At the higher concentration of 60 g/L SA, the response mechanisms of the three strains diverged notably. For KF7, genes involved in the glyoxylate cycle were significantly downregulated, whereas genes involved in gluconeogenesis, the pentose phosphate pathway, protein folding, and meiosis were significantly upregulated. For NBRC1958, genes related to the biosynthesis of vitamin B6, thiamin, and purine were significantly downregulated, whereas genes related to protein folding, toxin efflux, and cell wall remodeling were significantly upregulated. For NBRC2018, there was a significant upregulation of genes connected to the pentose phosphate pathway, gluconeogenesis, fatty acid utilization, and protein folding, except for the small heat shock protein gene HSP26. Overexpression of HSP26 and HSP42 notably enhanced the cell growth of NBRC1958 both in the presence and absence of SA. Conclusions The inherent activities of small heat shock proteins, the levels of acetyl-CoA and the strains’ potential capacity to consume SA all seem to affect the responses and tolerances of S. cerevisiae strains to SA. These factors should be taken into consideration when choosing host strains for SA production. This study provides a theoretical basis and identifies potential host strains for the development of robust and efficient SA-producing strains.

Abstract Previous studies have shown that low platelet count combined with high plasma total homocysteine (tHcy) increased stroke risk and can be lowered by 73% with folic acid. However, the combined role of other platelet activation parameters and the methylenetetrahydrofolate reductase (MTHFR) C677T genotypes on stroke risk and folic acid treatment benefit remain to be examined. This study aimed to investigate if platelet activation parameters and MTHFR genotypes jointly impact folic acid treatment efficacy in first stroke prevention. Data were derived from the China Stroke Primary Prevention Trial. This study includes a total of 11,185 adult hypertensive patients with relevant platelet activation parameters and MTHFR genotype data. When simultaneously considering both platelet activation parameters (plateletcrit, platelet count, mean platelet volume, platelet distribution width) and MTHFR genotypes, patients with both low plateletcrit (Q1) and the TT genotype had the highest stroke incidence rate (5.6%) in the enalapril group. This subgroup significantly benefited from folic acid treatment, with a 66% reduction in first stroke (HR: 0.34; 95% CI: 0.14–0.82; p = 0.016). Consistently, the subgroup with low plateletcrit (Q1) and the CC/CT genotype also benefited from folic acid treatment (HR: 0.40; 95% CI: 0.23–0.70; p = 0.001). In Chinese hypertensive adults, low plateletcrit can identify those who may greatly benefit from folic acid treatment, in particular, those with the TT genotype, a subpopulation known to have the highest stroke risk.

Abstract To address the limitations of traditional photothermal therapy (PTT)/ photodynamic therapy (PDT) and real-time cancer metastasis detection, a pH-responsive nanoplatform (NP) with dual-modality imaging capability was rationally designed. Herein, 1 H,1 H-undecafluorohexylamine (PFC), served as both an oxygen carrier and a 19F magnetic resonance imaging (MRI) probe, and photosensitizer indocyanine green (ICG) were grafted onto the pH-responsive peptide hexahistidine (H6) to form H6-PFC-ICG (HPI). Subsequently, the heat shock protein 90 inhibitor, gambogic acid (GA), was incorporated into hyaluronic acid (HA) modified HPI (HHPI), yielding the ultimate HHPI@GA NPs. Upon self-assembly, HHPI@GA NPs passively accumulated in tumor tissues, facilitating oxygen release and HA-mediated cell uptake. Once phagocytosed by lysosomes, protonation of H6 was triggered due to the low pH, resulting in the release of GA. With near-infrared laser irradiation, GA-mediated decreased HSP90 expression and PFC-mediated increased ROS generation amplified the PTT/PDT effect of HHPI@GA, leading to excellent in vitro and in vivo anticancer efficacies. Additionally, the fluorescence and 19F MRI dual-imaging capabilities of HHPI@GA NPs enabled effective real-time primary cancer and lung metastasis monitoring. This work offers a novel approach for enhanced cancer phototherapy, as well as precise cancer diagnosis.

Background/Aims Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by fat accumulation in the liver. MASLD encompasses both steatosis and MASH. Since MASH can lead to cirrhosis and liver cancer, steatosis and MASH must be distinguished during patient treatment. Here, we investigate the genomes, epigenomes, and transcriptomes of MASLD patients to identify signature gene set for more accurate tracking of MASLD progression. Methods Biopsy-tissue and blood samples from patients with 134 MASLD, comprising 60 steatosis and 74 MASH patients were performed omics analysis. SVM learning algorithm were used to calculate most predictive features. Linear regression was applied to find signature gene set that distinguish the stage of MASLD and to validate their application into independent cohort of MASLD. Results After performing WGS, WES, WGBS, and total RNA-seq on 134 biopsy samples from confirmed MASLD patients, we provided 1,955 MASLD-associated features, out of 3,176 somatic variant callings, 58 DMRs, and 1,393 DEGs that track MASLD progression. Then, we used a SVM learning algorithm to analyze the data and select the most predictive features. Using linear regression, we identified a signature gene set capable of differentiating the various stages of MASLD and verified it in different independent cohorts of MASLD and a liver cancer cohort. Conclusions We identified a signature gene set (i.e., CAPG, HYAL3, WIPI1, TREM2, SPP1, and RNASE6) with strong potential as a panel of diagnostic genes of MASLD-associated disease.

Abstract Decoding movement intentions from motor unit (MU) activities to represent neural drive information plays a central role in establishing neural interfaces, but there remains a great challenge for obtaining precise MU activities during sustained muscle contractions. In this paper, we presented an online muscle force prediction method driven by individual MU activities that were decomposed from prolonged surface electromyogram (SEMG) signals in real time. In the training stage of the proposed method, a set of separation vectors was initialized for decomposing MU activities. After transferring each decomposed MU activity into a twitch force train according to its action potential waveform, a neural network was designed and trained for predicting muscle force. In the subsequent online stage, a practical double-thread-parallel algorithm was developed. One frontend thread predicted the muscle force in real time utilizing the trained network and the other backend thread simultaneously updated the separation vectors. To assess the performance of the proposed method, SEMG signals were recorded from the abductor pollicis brevis muscles of eight subjects and the contraction force was simultaneously collected. With the update procedure in the backend thread, the force prediction performance of the proposed method was significantly improved in terms of lower root mean square deviation (RMSD) of around 10% and higher fitness (R2) of around 0.90, outperforming two conventional methods. This study provides a promising technique for real-time myoelectric applications in movement control and health.

Abstract There is an urgent need to fully understand the biology of third generation EGFR‐tyrosine kinase inhibitors (EGFR‐TKIs), particularly osimertinib, and to develop mechanism‐driven strategies to manage their acquired resistance. Transient receptor potential melastatin‐2 (TRPM2) functions as an important regulator of Ca2+ influx, but its role in mediating therapeutic efficacies of EGFR‐TKIs and acquired resistance to EGFR‐TKIs has been rarely studied. This study has demonstrated a previously undiscovered role of suppression of TRPM2 and subsequent inhibition of Ca2+ influx and induction of ROS and DNA damage in mediating apoptosis induction and the therapeutic efficacy of osimertinib against EGFR mutant NSCLC. The rebound elevation represents a key mechanism accounting for the emergence of acquired resistance to osimertinib and other third generation EGFR‐TKIs. Accordingly, targeting TRPM2 is a potentially promising strategy for overcoming and preventing acquired resistance to osimertinib, warranting further study in this direction including the development of cancer therapy‐optimized TRPM2 inhibitors.

BackgroundDetecting cardiac thrombus in patients with acute ischemic stroke is crucial in determine stroke etiology and predict prognosis. However, the prevalence of cardiac thrombus in patients with acute ischemic stroke is unclear.ObjectThis study aimed to evaluate the prevalence of cardiac thrombus detected by cardiac computed tomography angiography (CCTA) in patients with acute ischemic stroke through a meta-analysis.MethodsEmbase, Web of Science, MEDLINE, and CENTRAL were searched from January 1, 2000, to May 1, 2024. We included observational studies enrolling patients who underwent CCTA within 1 month following acute ischemic stroke, and reporting the incidence of cardiac thrombi on CCTA. Meta-analysis was performed using random effects models.ResultsTwenty-six studies involving 4,516 patients were identified. The pooled prevalence of cardiac thrombus detected on CCTA in patients with acute ischemic stroke was 0.08 (95% confidence interval [CI]: 0.06–0.11). Inter-study heterogeneity was high (I2 = 88%). Among stroke type, the prevalence of atrial fibrillation, timing of CCTA and CCTA technology, the prevalence of atrial fibrillation was the only factor associated with cardiac thrombi prevalence detected by CCTA. However, atrial fibrillation was not documented in 41.5% of the patients with cardiac thrombi.ConclusionCCTA is a useful non-invasive imaging approach for detecting cardiac thrombus in patients with acute ischemic stroke, which might be helpful to determine the stroke etiology.

Traditionally, the ampacity of an overhead transmission line (OHTL) is a static value obtained based on adverse weather conditions, which constrains the transmission capacity. With the continuous growth of power system load, it is increasingly necessary to dynamically adjust the ampacity based on weather conditions. To this end, this paper models the heat balance relationship of the OHTL based on a BP neural network using Bayesian optimization (BO-BP). On this basis, an OHTL ampacity prediction method considering the model error is proposed. First, a two-stage current-stepping ampacity prediction model is established to obtain the initial ampacity prediction results. Then, the risk control strategy of ampacity prediction considering the model error is proposed to correct the ampacity based on the quartile of the model error to reduce the risk of the conductor overheating caused by the model error. Finally, a simulation is carried out based on the operation data of a 220-kV transmission line. The simulation results show that the accuracy of the BO-BP model is improved by more than 20% compared with the traditional heat balance equation. The proposed ampacity prediction method can improve the transmission capacity by more than 150% compared with the original static ampacity.

IntroductionAnimal waste proteins have been increasing in the past decade, along with consumer demands. Their huge volume and the environmental issues caused by improper treatment probably pose a massive threat to human health. These animal waste proteins contain many valuable bioactive peptides and can be used not only as nutrient substances but also as primary functional ingredients in many industries, including agriculture, food, and pharmaceuticals. However, the advancement of the value-added application of animal waste proteins within the past 10 years has not been elucidated yet. In this regard, this paper scrutinized the studies on the applications of hydrolysates and peptides from animal waste proteins throughout the last decade, hoping to display a whole picture of their value-adding applications.MethodsThe Web of Science and Google Scholar were searched from January 1, 2013, to December 12, 2023. This review included field trials, in vitro and in vivo assays, and in silico analysis based on literature surveys or proteolysis simulation. The quality of the included studies was evaluated by Journal Citation Reports, and the rationality of the discussion of studies included.ResultsNumerous studies were performed on the application potential of hydrolysates and peptides of animal waste proteins in agricultural, food, and medicinal industries. Particularly, due to the nutritional value, safety, and especially competitive effects, the peptide with antioxidant, antimicrobial, antihypertensive, antidiabetic, or antithrombotic activities can be used as a primary functional ingredient in food and pharmaceuticals.DiscussionThese value-added applications of animal waste proteins could be a step towards sustainable animal by-products management, and simultaneously, open new avenues in the rapid development of nutraceuticals and pharmaceuticals. However, further studies on the bioavailability and structure-activity relationship are required to verify their therapeutic effects.

Neat high-temperature vulcanized silicone rubber (HTV SR) showed bad hydrophobicity due to the existence of a large number of inorganic reinforcing fillers on its surface, which affected its security application in outdoor insulation systems. In this work, hydrophobic silane chains were grafted onto the surface of inorganic particles on the skin layer of HTV SR by a one-step coupling modification to improve its hydrophobicity. The effects of coupling agent types and coupling reaction conditions on the hydrophobicity of HTV SR were investigated. It was determined that the perfluorooctane trichlorosilicon with a large number of low surface energy fluorine atoms was the preferred coupling agent. The contact angle of HTV SR was increased by 15.70% when the optimal coupling reaction conditions were determined to be a reaction temperature of 60°C, a reaction time of 4 h, and an amount of coupling agent of 0.5%. The study found that both etching reaction and grafting reaction occurred during the whole coupling modification process, which led to the disappearance or decrease of a lot of holes on the HTV SR surface. After the fluorination coupling reaction, the surface of HTV SR became smooth and dense that led to the decrease of water absorption. The result of Fourier-transform infrared spectroscopy analysis showed the formation of C-F bond in HTV SR after fluorination modification, and the energetic dispersive spectroscopy analysis showed that the fluorine content on the surface of the fluorinated HTV SR increased significantly. Moreover, the stability analysis showed that the fluorinated HTV SR still had a good thermal stability and mechanical property stability.

ABSTRACT Mitogen-activated protein kinase (MAPK) pathways are fundamental to the regulation of biological processes in eukaryotic organisms. The basidiomycete Cryptococcus neoformans, known for causing fungal meningitis worldwide, possesses five MAPKs. Among these, Cpk1, Hog1, and Mpk1 have established roles in sexual reproduction, stress responses, and cell wall integrity. However, the roles of Cpk2 and Mpk2 are less understood. Our study elucidates the functional interplay between the Cpk1/Cpk2 and Mpk1/Mpk2 MAPK pathways in C. neoformans. We discovered that CPK2 overexpression compensates for cpk1Δ mating deficiencies via the Mat2 transcription factor, revealing functional redundancy between Cpk1 and Cpk2. We also found that Mpk2 is phosphorylated in response to cell wall stress, a process regulated by the MAPK kinase (MAP2K) Mkk2 and MAP2K kinases (MAP3Ks) Ssk2 and Ste11. Overexpression of MPK2 partially restores cell wall integrity in mpk1Δ by influencing key cell wall components, such as chitin and the polysaccharide capsule. Contrarily, MPK2 overexpression cannot restore thermotolerance and cell membrane integrity in mpk1Δ. These results suggest that Mpk1 and Mpk2 have redundant and opposing roles in the cellular response to cell wall and membrane stresses. Most notably, the dual deletion of MPK1 and MPK2 restores wild-type mating efficiency in cpk1Δ mutants via upregulation of the mating-regulating transcription factors MAT2 and ZNF2, suggesting that the Mpk1 and Mpk2 cooperate to negatively regulate the pheromone-responsive Cpk1 MAPK pathway. Our research collectively underscores a sophisticated regulatory network of cryptococcal MAPK signaling pathways that intricately govern sexual reproduction and cell wall integrity, thereby controlling fungal development and pathogenicity.IMPORTANCEIn the realm of fungal biology, our study on Cryptococcus neoformans offers pivotal insights into the roles of specific proteins called mitogen-activated protein kinases (MAPKs). Here, we discovered the cryptic functions of Cpk2 and Mpk2, two MAPKs previously overshadowed by their dominant counterparts Cpk1 and Mpk1, respectively. Our findings reveal that these “underdog” proteins are not just backup players; they play crucial roles in vital processes like mating and cell wall maintenance in C. neoformans. Their ability to step in and compensate when their dominant counterparts are absent showcases the adaptability of C. neoformans. This newfound understanding not only enriches our knowledge of fungal MAPK mechanisms but also underscores the intricate balance and interplay of proteins in ensuring the organism’s survival and adaptability.

Abstract Deep penetration and downregulation of heat shock protein (HSP) expression in multimodal synergistic therapy are promising approaches for curing cancer in clinical trials. However, free small‐molecule drugs and most drug vehicles have a low delivery efficiency deep into the tumor owing to poor drug penetration and hypoxic conditions at the tumor site. In this study, the objective is to use reactive oxygen species (ROS)‐responsive supramolecular gels co‐loaded with the photosensitizer Zn(II) phthalocyanine tetrasulfonic acid (ZnPCS4) and functionalized tetrahedral DNA (TGSAs) (G@P/TGSAs) to enhance deep tissue and cell penetration and block the HSP90 pathway for chemo‐ photodynamic therapy (PDT) ‐ photothermal therapy (PTT) trimodal synergistic therapy. The (G@P/TGSAs) are injected in situ into the tumor to release ZnPCS4 and TGSAs under high ROS concentrations originating from both the tumor and PDT. TGSAs penetrate deeply into tumor tissues and augment photothermal therapy by inhibiting the HSP90 pathway. Proteomics show that HSP‐related proteins and molecular chaperones are inhibited/activated, inhibiting the HSP90 pathway. Simultaneously, the TGSA‐regulated apoptotic pathway is activated. In vivo study demonstrates efficient tumor penetration and excellent trimodal synergistic therapy (45% tumor growth inhibition).

Water treatment public–private partnership (PPP) projects are pivotal for sustainable water management but are often challenged by complex risk factors. Efficient risk management in these projects is crucial, yet traditional methodologies often fall short of addressing the dynamic and intricate nature of these risks. Addressing this gap, this comprehensive study introduces an advanced risk classification prediction model tailored for water treatment PPP projects, aimed at enhancing risk management capabilities. The proposed model encompasses an intricate evaluation of crucial risk areas: the natural and ecological environments, socio-economic factors, and engineering entities. It delves into the complex relationships between these risk elements and the overall risk profile of projects. Grounded in a sophisticated ensemble learning framework employing stacking, our model is further refined through a weighted voting mechanism, significantly elevating its predictive accuracy. Rigorous validation using data from the Jiujiang City water environment system project Phase I confirms the model's superiority over standard machine learning models. The development of this model marks a significant stride in risk classification for water treatment PPP projects, offering a powerful tool for enhancing risk management practices. Beyond accurately predicting project risks, this model also aids in developing effective government risk management strategies. HIGHLIGHTS Pioneers data-driven risk management in water treatment PPP projects using machine learning.; Introduces an effective weighted voting mechanism for handling data irregularities in risk assessment.; Demonstrates superior performance of WETPR-SVM model over conventional machine learning models.;

Abstract The assembly of oligopeptide and polypeptide molecules can reconstruct various ordered advanced structures through intermolecular interactions to achieve protein-like biofunction. Here, we develop a “molecular velcro”-inspired peptide and gelatin co-assembly strategy, in which amphiphilic supramolecular tripeptides are attached to the molecular chain of gelatin methacryloyl via intra-/intermolecular interactions. We perform molecular docking and dynamics simulations to demonstrate the feasibility of this strategy and reveal the advanced structural transition of the co-assembled hydrogel, which brings more ordered β-sheet content and 10-fold or more compressive strength improvement. We conduct transcriptome analysis to reveal the role of co-assembled hydrogel in promoting cell proliferation and chondrogenic differentiation. Subcutaneous implantation evaluation confirms considerably reduced inflammatory responses and immunogenicity in comparison with type I collagen. We demonstrate that bone mesenchymal stem cells-laden co-assembled hydrogel can be stably fixed in rabbit knee joint defects by photocuring, which significantly facilitates hyaline cartilage regeneration after three months. This co-assembly strategy provides an approach for developing cartilage regenerative biomaterials.

This research proposes a novel hybrid reliability analysis method for rare failure events, which integrates the coupled Adaptive Kriging model and Generalized Subset Simulation (AK-GSS). In the proposed method, the adaptive Kriging model is applied to approximate the actual Performance Function (PF) to reduce the number of PF calls. A newly updated strategy is proposed to look for samples on the limit state surface to achieve active learning of the Kriging model. This updated strategy avoids the limitations of most current learning functions based on the prediction variance of Kriging models. The advantages of AK-GSS are illustrated through five examples, including two engineering applications of aircraft wings and hydraulic turbine rotor brackets. The results show that the proposed method is more efficient and accurate for rare failure events.

As converter stations are increasingly constructed at high altitudes, how to reasonably select the minimum air spacing of converter station substation equipment has become an important issue for DC power transmission at high altitudes. In order to study the influence of air environment on switching impulse discharge characteristics of air gap at high altitudes, this paper conducts switching impulse discharge tests on 1 m rod-plate air gap under different air pressure, temperature, and humidity conditions, investigates switching impulse discharge characteristics of rod-plate air gap at high altitude, and compares and analyses differences in correction results of various discharge voltage correction methods. Studies have shown that air pressure, temperature, and humidity have an effect on air gap discharge voltage. Meanwhile, based on different atmospheric parameters, correction formulas are obtained for 1m rod-plate air gap discharge voltage, and the elevation correction coefficients of 1m rod-plate air gap at each altitude was obtained. The results of the study provide a reference for external insulation of equipment and its insulation fit in converter stations at high altitude.

Applying liquid-applied sound deadener (LASD) in the interiors of high-speed trains effectively reduces noise and vibration, thereby enhancing passenger comfort. Currently, the application of LASD relies on manual spraying methods, with the quality dependent on the workers’ experience, making it challenging to ensure uniform coating thickness over large areas. Additionally, the occupational health risks for the workers cannot be ignored. This paper analyzes the process requirements for spraying LASD in high-speed train interiors and designs an automated robotic spraying system suitable for this application. A kinematic and dynamic model of a six-degrees-of-freedom (6-DOF) spraying robot is established. A slice generation and boundary fitting method is applied to the STL model of the high-speed train, generating the initial spraying trajectory. Under time-optimal constraints, the generated trajectory points are optimized for multiple objectives using an improved particle swarm optimization (IMPSO) method. Furthermore, this study proposes an ISMC-RBF control algorithm, which utilizes an integral sliding mode control (ISMC) algorithm to improve the precision of robot trajectory tracking, and a radial basis function (RBF) neural network estimation method to suppress disturbances. Simulation results demonstrate that the optimized trajectory reduced the spraying operation time by approximately 30%, additionally, the ISMC-RBF controller can reduce trajectory tracking errors to 50% of those achieved with PID control, while significantly improving the system’s dynamic response and steady-state performance. Overall, the proposed methods substantially increase the operational efficiency and precision of the spraying robot, providing effective technical support for high-speed train interior spraying.

Owing to its ability to provide more accurate and detailed battlefield situational information, fine-grained detection research on soldier targets is of significant importance for military decision-making and firepower threat assessment. To address the issues of low detection accuracy and inaccurate classification in the fine-grained detection of soldier targets, we propose a fine-gain soldier target detection model based on the improved YOLOv8 (You Only Look Once v8). First, we developed a multi-branch feature fusion module to effectively fuse multi-scale feature information and used a dynamic deformable attention mechanism to help the detection model focus on key areas in deep-level features. Second, we proposed a decoupled lightweight dynamic head to extract the position and category information of soldier targets separately, effectively solving the problem of misclassification of soldier targets’ attack actions under different poses. Finally, we used the Inner Minimum Points Distance Intersection over Union (Inner-MPDIoU) to further improve the convergence speed and accuracy of the network model. The proposed improvements are evaluated through comparative experiments conducted in published twenty-six test groups, and the effectiveness of the proposed method is demonstrated. Compared with the original model, our method achieved a detection precision of 78.9%, a 6.91% improvement; the mAP@50 (mean Average Precision at 50) was 79.6%, a 3.51% increase; and an mAP@50-95 of 63.8%, a gain of 5.28%. The proposed method achieves high precision and recall while reducing the computational complexity of the model, thereby enhancing its efficiency and robustness for fine-grained soldier target detection.

In urban warfare and rescue scenarios, the localization of soldiers in staircase environments presents substantial challenges. Addressing this issue, this study introduces the “Target Localization in Staircase Environments-Proximal Policy Optimization” module, which combines object detection with reinforcement learning algorithms. Utilizing a bespoke dataset, “Soldier-Staircase for Tracked Robots”, and design standards tailored for swing-arm tracked robots, the module meets the requirements for autonomous precise localization in staircase environments. A series of experiments conducted in simulated environments verify the module’s efficacy in autonomously and accurately localizing soldier targets in staircase environments, laying the groundwork for further research into the application of reinforcement learning in autonomous robot control.

Fossil fuel depletion and environmental pollution problems promote development of renewable energy (RE) globally. With increasing penetration of RE, operation security and economy of power systems (PS) are greatly impacted by fluctuation and intermittence of renewable power. In this paper, information gap decision theory (IGDT) is adapted to handle uncertainty of wind power generation. Based on conventional IGDT method, linear regulation strategy (LRS) and robust linear optimization (RLO) method are integrated to reformulate the model for rigorously considering security constraints. Then a robustness assessment method based on hybrid RLO-IGDT approach is proposed for analyzing robustness and economic performance of PS. Moreover, a risk-averse linearization method is adapted to convert the proposed assessment model into a mixed integer linear programming (MILP) problem for convenient optimization without robustness loss. Finally, results of case studies validate superiority of proposed method in guaranteeing operation security rigorously and effectiveness in assessment of RSR for PS without overestimation.

The importance of the loss function in object detection algorithms based on deep learning has grown significantly technological progress. The accuracy of object detection is significantly affected by bounding box regression, which is a crucial factor. Since the introduction of the Intersection over Union (IoU) loss in 2016, many improvements have been proposed based on this loss function. These studies considered various geometric factors related to bounding boxes, and constructed penalty terms to address this issue. This paper summarizes these functions and introduces a new Fused IoU (FIoU) loss function that leads to superior performance. The FIoU loss function not only solves the problem of gradient vanishing during the backpropagation process of the IoU loss function but also solves the problem of some IoU-based loss functions degenerating into IoU loss functions under certain conditions. In addition, in the simulation experiments, the FIoU loss function resulted in faster convergence speed. In our ablation experiments across different datasets and algorithms, our aim was to compare the mAP metrics under different loss functions. On the test set of the Pascal VOC dataset, employing the Faster R-CNN algorithm, FIoU demonstrated improvements of 1.1% and 1.7% over GIoU and Smooth $\ell _{1}$ , respectively. With the YOLOX algorithm, FIoU outperformed GIoU and IoU by 1.0% and 0.8%. Utilizing the YOLOv7 algorithm, we evaluated seven loss functions, achieving optimal results with FIoU. On the validation set of the MS-COCO 2017 dataset, using YOLOv7 and YOLOv8, FIoU exhibited gains of 0.4%, 0.2%, 0.2% over EIoU, DIoU, GIoU, and 0.3%, 0.5%, 0.3% over EIoU, DIoU, GIoU, respectively.