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While Ginsenoside Re has been shown to protect the central nervous system, reports of its effects on memory in the model of scopolamine-induced memory impairment are rare. The aim of this study was to investigate the effects of Ginsenoside Re on scopolamine (SCOP)-induced memory damage and the mechanism of action. Male ICR mice were treated with SCOP (3 mg/kg) for 7 days and with or without Ginsenoside Re for 14 days. As evidenced by behavioral studies (escape latency and cross platform position), brain tissue morphology, and oxidative stress indicators after Ginsenoside Re treatment, the memory damage caused by SCOP was significantly ameliorated. Further mechanism research indicated that Ginsenoside Re inhibited cell apoptosis by regulating the PI3K/Akt/Nrf2 pathway, thereby exerting a cognitive impairment improvement effect. This research suggests that Ginsenoside Re could protect against SCOP-induced memory defects possibly through inhibiting oxidative stress and cell apoptosis.

Abstract The rapid rise in the availability and scale of scRNA-seq data needs scalable methods for integrative analysis. Though many methods for data integration have been developed, few focus on understanding the heterogeneous effects of biological conditions across different cell populations in integrative analysis. Our proposed scalable approach, scParser, models the heterogeneous effects from biological conditions, which unveils the key mechanisms by which gene expression contributes to phenotypes. Notably, the extended scParser pinpoints biological processes in cell subpopulations that contribute to disease pathogenesis. scParser achieves favorable performance in cell clustering compared to state-of-the-art methods and has a broad and diverse applicability.

Soil has an intricate pore structure, with the macropore structure serving as a pivotal component of gas exchange, liquid flow, and solute transport within the soil matrix. Scientifically understanding the macropore structure is important for the exploration of soil ecological functions. Drawing upon research literature from diverse nations, this study presents a comprehensive summary of past research findings, thoroughly examining the definition and taxonomy of soil macropores. Additionally, we delve into the factors that affect macropore structure, the effects of macropores on soil ecological functions, and the indicators that describe the nature of macropores. Furthermore, the principles, suitability conditions, benefits, and limitations of the widely utilized techniques for characterizing soil macropore structure were outlined, including staining observation, soil water retention curve, mercury intrusion porosimetry, gas adsorption, nuclear magnetic resonance, scanning electron microscopy, and computed tomography (CT). A comparative analysis was conducted to assist scholars in comprehending the theory of soil macropores, facilitating the selection of suitable macropore structure characterization techniques, and enabling the development of collaborative application modes among these techniques. Using the Web of Science core collection database, bibliometric software such as VOSviewer and CiteSpace were employed to explore the research hotspots and trends in CT, which is currently the most popular technique for characterizing soil macropore structure. This analysis offers insights into the future prospects of CT in the field of soil macropore structure characterization techniques. This article is of particular interest to readers engaged in the characterization of soil macropores.

Background Although the optimization of brain oxygenation is thought to improve the prognosis, the effect of brain tissue oxygen pressure (PbtO2) for patients with severe traumatic brain injury (STBI) remains controversial. Therefore, the present study aimed to determine whether adding PbtO2 to intracranial pressure (ICP) monitoring improves clinical outcomes for patients with STBI. Methods PubMed, Embase, Scopus and Cochrane Library were searched for eligible trials from their respective inception through April 10th, 2024. We included clinical trials contrasting the combined monitoring of PbtO2 and ICP versus isolated ICP monitoring among patients with STBI. The primary outcome was favorable neurological outcome at 6 months, and secondary outcomes including the in-hospital mortality, long-term mortality, length of stay in intensive care unit (ICU) and hospital. Results A total of 16 studies (four randomized studies and 12 cohort studies) were included in the meta-analysis. Compared with isolated ICP monitoring, the combined monitoring was associated with a higher favorable neurological outcome rate at 6 months (RR 1.33, 95% CI [1.17–1.51], P

This study aimed to explore the role of lncRNA MALAT1 (Long non-coding RNAs metastasis-associated lung adenocarcinoma transcript), and its underlying mechanisms in Hypopharyngeal Squamous Cell Carcinoma (HSCC). Quantitative real-time PCR (qRT-PCR) was employed to measure lncRNA MALAT1 expression in HSCC and adjacent non-cancerous tissues, along with the expression of the downstream target mitogen-activated protein kinase kinase 1 (MAP2K1). The independent prognostic significance of lncRNA MALAT1 was assessed using Cox regression analysis. Potential downstream targets of MALAT1 were identified through PRM analysis and validated using the TCGA-HNSC database, Western blotting, and immunohistochemistry. CCK-8, flow cytometry, and Transwell assays were conducted to assess the effects of the lncRNA MALAT1/MAP2K1 axis on FaDu cells. Additionally, a nude mouse xenograft model was used to confirm the role of lncRNA MALAT1/MAP2K1 in tumor growth. LncRNA MALAT1 was significantly upregulated in HSCC tissues and closely associated with poor prognosis. Bioinformatics analysis, including parallel reaction monitoring (PRM) screening and TCGA-HNSC data, identified FERMT2, CSNK2A2, and MAP2K1 as potential downstream targets of MALAT1. Validation through qPCR, Western blotting, and immunohistochemistry confirmed MAP2K1 as a downstream target. In vitro and in vivo experiments demonstrated that inhibiting lncRNA MALAT1 suppressed cell proliferation, migration, and epithelial-to-mesenchymal transition (EMT) by downregulating MAP2K1 expression. Additionally, it induced apoptosis, affected the cell cycle, and inhibited tumor growth. Our study uniquely demonstrates that targeting MALAT1 significantly impedes HSCC progression by downregulating its novel downstream target, MAP2K1, offering new insights into potential therapeutic strategies.

Abstract Degenerated endplate appears with cheese-like morphology and sensory innervation, contributing to low back pain and subsequently inducing intervertebral disc degeneration in the aged population.1 However, the origin and development mechanism of the cheese-like morphology remain unclear. Here in this study, we report lumbar instability induced cartilage endplate remodeling is responsible for this pathological change. Transcriptome sequencing of the endplate chondrocytes under abnormal stress revealed that the Hippo signaling was key for this process. Activation of Hippo signaling or knockout of the key gene Yap1 in the cartilage endplate severed the cheese-like morphological change and disc degeneration after lumbar spine instability (LSI) surgery, while blocking the Hippo signaling reversed this process. Meanwhile, transcriptome sequencing data also showed osteoclast differentiation related gene set expression was up regulated in the endplate chondrocytes under abnormal mechanical stress, which was activated after the Hippo signaling. Among the discovered osteoclast differentiation gene set, CCL3 was found to be largely released from the chondrocytes under abnormal stress, which functioned to recruit and promote osteoclasts formation for cartilage endplate remodeling. Over-expression of Yap1 inhibited CCL3 transcription by blocking its promoter, which then reversed the endplate from remodeling to the cheese-like morphology. Finally, LSI-induced cartilage endplate remodeling was successfully rescued by local injection of an AAV5 wrapped Yap1 over-expression plasmid at the site. These findings suggest that the Hippo signaling induced osteoclast gene set activation in the cartilage endplate is a potential new target for the management of instability induced low back pain and lumbar degeneration.

Abstract Despite the record speed of developing vaccines and therapeutics against the SARS-CoV-2 virus, it is not a given that such success can be secured in future pandemics. In addition, COVID-19 vaccination and application of therapeutics remain low in developing countries. Rapid and low cost mass production of antiviral IgY antibodies could be an attractive alternative or complementary option for vaccine and therapeutic development. In this article, we rapidly produced SARS-CoV-2 antigens, immunized hens and purified IgY antibodies in 2 months after the SARS-CoV-2 gene sequence became public. We further demonstrated that the IgY antibodies competitively block RBD binding to ACE2, neutralize authentic SARS-CoV-2 virus and effectively protect hamsters from SARS-CoV-2 challenge by preventing weight loss and lung pathology, representing the first comprehensive study with IgY antibodies. The process of mass production can be easily implemented in most developing countries and hence could become a new vital option in our toolbox for combating viral pandemics. This study could stimulate further studies, optimization and potential applications of IgY antibodies as therapeutics and prophylactics for human and animals.

Abstract Background The function of diverse ruminal microbes is tightly linked to rumen development and host physiology. The system of ruminal microbes is an excellent model to clarify the fundamental ecological relationships among complex nutrient–microbiome–host interactions. Here, neonatal lambs are introduced to different dietary regimes to investigate the influences of early-life crosstalk between nutrients and microbiome on rumen development. Results We find starchy corn-soybean starter-fed lambs exhibit the thickest ruminal epithelia and fiber-rich alfalfa hay-fed lambs have the thickest rumen muscle. Metabolome and metagenome data reveal that indole-3-carboxaldehyde (3-IAld) and prostaglandin D2 (PGD2) are the top characteristic ruminal metabolites associated with ruminal epithelial and muscular development, which depend on the enhanced ruminal microbial synthesis potential of 3-IAld and PGD2. Moreover, microbial culture experiment first demonstrates that Bifidobacterium pseudolongum is able to convert tryptophan into 3-IAld and Candida albicans is a key producer for PGD2. Transcriptome sequencing of the ruminal epithelia and smooth muscle shows that ruminal epithelial and muscular development is accompanied by Wnt and Ca2+ signaling pathway activation. Primary cell cultures further confirm that 3-IAld promotes ruminal epithelial cell proliferation depending on AhR-wnt/β-catenin signaling pathway and PGD2 accelerates ruminal smooth muscle cell proliferation via Ca2+ signaling pathway. Furthermore, we find that 3-IAld and PGD2 infusion promote ruminal epithelial and musculature development in lambs. Conclusions This study demonstrates that early-life ruminal microbiome-derived 3-IAld and PGD2 are effective promoters of rumen development, which enhances our understanding of nutrient–microbiome–host interactions in early life.

Statins therapy is efficacious in diminishing the risk of major cardiovascular events in diabetic patients. However, our research has uncovered a correlation between the prolonged administration of statins and an elevated risk of myocardial dysfunction in patients with type II diabetes mellitus (TIIDM). Here, we report the induction of sterol regulatory element-binding protein 1 (SREBP1) activation, associated lipid peroxidation, and the consequent diabetic myocardial dysfunction after statin treatment and explored the underlying mechanisms. In db/db mice, we observed that 40 weeks atorvastatin (5 and 10 mg/kg) and rosuvastatin (20 mg/kg) administration exacerbated diabetic myocardial dysfunction by echocardiography and cardiomyocyte contractility assay, increased myocardial inflammation and fibrosis as shown by CD68, IL-1β, Masson's staining and Collagen1A1 immunohistochemistry (IHC) staining, increased respiratory exchange ratio (RER) by metabolic cage system assessment, exacerbated mitochondrial structural pathological changes by transmission electron microscopy (TEM) examination, increased deposition of lipid and glycogen by TEM, Oil-red and periodic acid-schiff stain (PAS) staining, which were corresponded with augmented levels of myocardial SREBP1 protein and lipid peroxidation marked by 4-hydroxynonenal (4-HNE) staining. Comparable myocardial fibrosis was also observed in KK-ay and low-dose streptozotocin (STZ)-induced TIIDM mice. Elevated SREBP1 levels were observed in the heart tissues from diabetic patients, which was positively correlated with their myocardial dysfunction. To elucidate the role of statin induced SREBP1 in lipid peroxidation and lipid deposition and related mechanism, we cultured neonatal mouse primary cardiomyocytes (NMPCs) and treated them with atorvastatin (10 μM, 24 h), tracing with [U–13C]-glucose and evaluating for SREBP1 expression and localization. We found that statin treatment elevated de novo lipogenesis (DNL) and the levels of SREBP1 cleavage-activating protein (SCAP), reduced the interaction of SCAP with insulin-induced gene 1 (Insig1), and enhance SCAP/SREBP1 translocation to the Golgi, which facilitate SREBP1 cleavage leading to its nuclear trans-localization and activation in NMPCs. Ultimately, SREBP1 knockdown or l-carnitine mitigated long-term statins therapy induced lipid peroxidation and myocardial fibrosis in low-dose STZ treated SREBP1+/− mice and l-carnitine treated db/db mice. In conclusion, we demonstrated that statin therapy may augment DNL by activating SREBP1, resulting in myocardial lipid peroxidation and lipid deposition.

Summary: Emerging evidence highlights the regulatory role of paired-like (PRD-like) homeobox transcription factors (TFs) in embryonic genome activation (EGA). However, the majority of PRD-like genes are lost in rodents, thus prompting an investigation into PRD-like TFs in other mammals. Here, we showed that PRD-like TFs were transiently expressed during EGA in human, monkey, and porcine fertilized embryos, yet they exhibited inadequate expression in their cloned embryos. This study, using pig as the research model, identified LEUTX as a key PRD-like activator of porcine EGA through genomic profiling and found that LEUTX overexpression restored EGA failure and improved preimplantation development and cloning efficiency in porcine cloned embryos. Mechanistically, LEUTX opened EGA-related genomic regions and established histone acetylation via recruiting acetyltransferases p300 and KAT2A. These findings reveal the regulatory mechanism of LEUTX to govern EGA in pigs, which may provide valuable insights into the study of early embryo development for other non-rodent mammals.

Habitual dietary changes have the potential to induce alterations in the host’s gut microbiota. Mandarin fish (Siniperca chuatsi), an aquatic vertebrate species with distinct feeding habits, were fed with natural feeds (NF) and artificial feeds (AF) to simulate the effects of natural and processed food consumption on host gut microbiota assemblages. The results showed that the alpha diversity index was reduced in the AF diet treatment, as lower abundance and diversity of the gut microbiota were observed, which could be attributed to the colonized microorganisms of the diet itself and the incorporation of plant-derived proteins or carbohydrates. The β-diversity analysis indicated that the two dietary treatments were associated with distinct bacterial communities. The AF diet had a significantly higher abundance of Bacteroidota and a lower abundance of Actinomycetota, Acidobacteriota, and Chloroflexota compared to the NF group. In addition, Bacteroidota was the biomarker in the gut of mandarin fish from the AF treatment, while Acidobacteriota was distinguished in the NF treatments. Additionally, the increased abundance of Bacteroidota in the AF diet group contributed to the improved fermentation and nutrient assimilation, as supported by the metabolic functional prediction and transcriptome verification. Overall, the present work used the mandarin fish as a vertebrate model to uncover the effects of habitual dietary changes on the evolution of the host microbiota, which may provide potential insights for the substitution of natural foods by processed foods in mammals.

Background To investigate the effects of arsenic trioxide (ATO) on human colorectal cancer cells (HCT116) growth and the role of transient receptor potential melastatin 4 (TRPM4) channel in this process. Methods The viability of HCT116 cells was assessed using the CCK-8 assay. Western blot analysis was employed to examine the protein expression of TRPM4. The apoptosis of HCT116 cells was determined using TUNEL and Flow cytometry. Cell migration was assessed through the cell scratch recovery assay and Transwell cell migration assay. Additionally, Transwell cell invasion assay was performed to determine the invasion ability of HCT116 cells. Results ATO suppressed the viability of HCT116 cells in a dose-dependent manner, accompanied by a decline in cell migration and invasion, and an increase in apoptosis. 9-phenanthroline (9-Ph), a specific inhibitor of TRPM4, abrogated the ATO-induced upregulation of TRPM4 expression. Additionally, blocking TRPM4 reversed the effects of ATO on HCT116 cells proliferation, including restoration of cell viability, migration and invasion, as well as the inhibition of apoptosis. Conclusion ATO inhibits CRC cell growth by inducing TRPM4 expression, our findings indicate that ATO is a promising therapeutic strategy and TRPM4 may be a novel target for the treatment of CRC.

Rabbits can efficiently utilize plant fibers that are indigestible to humans, and hence may contribute to the alleviation of feed–food competition. Therefore, it is economically and ecologically important to genetically improve the growth performance and feed efficiency of meat rabbits. In this study, we combined pedigree, genomic, and gut microbiota data to estimate genetic and microbial parameters for nine growth and feed efficiency traits of 739 New Zealand White rabbits, including body weight (BW) at 35 (BW35), 70 (BW70), and 84 (BW84) days of age, and average daily gain (ADG), feed conversion ratio (FCR), and residual feed intake (RFI) within two age intervals of 35–70 days (ADG70, FCR70, and RFI70) and 35–84 days (ADG84, FCR84, and RFI84). Based on single-step genomic best linear unbiased prediction, three BW traits and two ADG traits had the high estimates (±standard error, SE) of heritability, ranging from 0.44 ± 0.13 of BW35 to 0.66 ± 0.08 of BW70. Moderate heritabilities were observed for RFI70 (0.22 ± 0.07) and RFI84 (0.29 ± 0.07), whereas the estimates did not significantly deviate from zero for the two FCR traits. There was moderate positive genetic correlation (±SE) between BW70 and ADG70 (0.579 ± 0.086), but BW70 did not correlate with RFI70. Based on microbial best linear unbiased prediction, the estimates of microbiability did not significantly deviate from zero for any trait. Based on the combined use of genomic and gut microbiota data, the parameters obtained in this study could help us to implement efficient breeding schemes in meat rabbits.

Pre-trained language models perform well in various natural language processing tasks. However, their large number of parameters poses significant challenges for edge devices with limited resources, greatly limiting their application in practical deployment. This paper introduces a simple and efficient method called Autocorrelation Matrix Knowledge Distillation (AMKD), aimed at improving the performance of smaller BERT models for specific tasks and making them more applicable in practical deployment scenarios. The AMKD method effectively captures the relationships between features using the autocorrelation matrix, enabling the student model to learn not only the performance of individual features from the teacher model but also the correlations among these features. Additionally, it addresses the issue of dimensional mismatch between the hidden states of the student and teacher models. Even in cases where the dimensions are smaller, AMKD retains the essential features from the teacher model, thereby minimizing information loss. Experimental results demonstrate that BERTTINY-AMKD outperforms traditional distillation methods and baseline models, achieving an average score of 83.6% on GLUE tasks. This represents a 4.1% improvement over BERTTINY-KD and exceeds the performance of BERT4-PKD and DistilBERT4 by 2.6% and 3.9%, respectively. Moreover, despite having only 13.3% of the parameters of BERTBASE, the BERTTINY-AMKD model retains over 96.3% of the performance of the teacher model, BERTBASE.

The electric network frequency (ENF), often referred to as the industrial heartbeat, plays a crucial role in the power system. In recent years, it has found applications in multimedia evidence identification for court proceedings and audio–visual temporal source identification. This paper introduces an ENF region classification model named UniTS-SinSpec within the UniTS framework. The model integrates the sinusoidal activation function and spectral attention mechanism while also redesigning the model framework. Training is conducted using a public dataset on the open science framework (OSF) platform, with final experimental results demonstrating that, after parameter optimization, the UniTS-SinSpec model achieves an average validation accuracy of 97.47%, surpassing current state-of-the-art and baseline models. Accurate classification can significantly aid in ENF temporal source identification. Future research will focus on expanding dataset coverage and diversity to verify the model’s generality and robustness across different regions, time spans, and data sources. Additionally, it aims to explore the extensive application potential of ENF region classification in preventing crimes such as telecommunications fraud, terrorism, and child pornography.

Well placement optimization is one of the most important means to control the decline of oilfields and improve the recovery rate in the development process of deep and heterogeneous reservoirs, such as deep buried carbonate oil reservoirs. However, the mapping relationship from deployed well positions to actual profits is non-linear and multi-modal. At the same time, the injection and production relationship of new wells also affects the contribution of well positions to final profits. Currently, common algorithms include gradient-based and heuristic non-gradient algorithms, which have advantages, but face problems of high computational complexity, slow optimization speed, and difficulty in convergence. We propose an evolutionary algorithm for well placement optimization in carbonate reservoirs. This algorithm improves well placement optimization and computational speed by constraining the sampling process to effective sampling spaces, integrating prior knowledge to enhance sampling efficiency, strengthening local optima exploration, and utilizing parallel computing. Additionally, it refines the optimized variable content based on actual control factors, enhancing the algorithm’s robustness in practical applications. A case study from a carbonate reservoir in northwestern China demonstrated that this algorithm not only improved the performance by 50% compared to the classic DE algorithm but also achieved 15% higher optimization effectiveness than the current state-of-the-art algorithms.

In response to the challenge of existing wireless communication anti-jamming methods in effectively handling unknown jamming, this paper proposes a multi-parameter control anti-jamming algorithm for wireless communication systems based on the Linear–Quadratic Regulator (LQR). First, the proposed algorithm models the wireless communication system as a linear switched system based on the modulation and coding scheme. Subsequently, a feedback controller design method based on the LQR is introduced. By utilizing the multiple Lyapunov function method combined with linear matrix inequalities, sufficient criteria for the asymptotic stability of the system under unknown jamming conditions are provided. Finally, theoretical analysis and simulation results indicate that the proposed algorithm can rapidly adjust modulation and coding schemes as well as transmission power in complex jamming environments, thereby maintaining bit error rate (BER) stability and enhancing the reliability of the communication system.

Purpose The optimal range of protein dosage and effect of high-dose protein on critically ill patients remain controversial. We conducted a meta-analysis to compare higher and lower doses of protein supplementation for nutritional support in critically ill patients. Methods We searched the PubMed, Embase, Scopus, and Cochrane Library databases for randomized controlled trials that compared higher (≥1.2 g/kg per day) versus lower (

Abstract Growing regulatory requirements set barriers around genetic data sharing and collaborations. Moreover, existing privacy-aware paradigms are challenging to deploy in collaborative settings. We present COLLAGENE, a tool base for building secure collaborative genomic data analysis methods. COLLAGENE protects data using shared-key homomorphic encryption and combines encryption with multiparty strategies for efficient privacy-aware collaborative method development. COLLAGENE provides ready-to-run tools for encryption/decryption, matrix processing, and network transfers, which can be immediately integrated into existing pipelines. We demonstrate the usage of COLLAGENE by building a practical federated GWAS protocol for binary phenotypes and a secure meta-analysis protocol. COLLAGENE is available at https://zenodo.org/record/8125935 .

Accurate wind power prediction helps to fully utilize wind energy and improve the stability of the power grid. However, existing studies mostly analyze key wind power-related features equally without distinguishing the importance of different features. In addition, single models have limitations in fully extracting input feature information and capturing the time-dependent relationships of feature sequences, posing significant challenges to wind power prediction. To solve these problems, this paper presents a wind power forecasting approach that combines feature weighting and a combination model. Firstly, we use the attention mechanism to learn the weights of different input features, highlighting the more important features. Secondly, a Multi-Convolutional Neural Network (MCNN) with different convolutional kernels is employed to extract feature information comprehensively. Next, the extracted feature information is input into a Stacked BiLSTM (SBiLSTM) network to capture the temporal dependencies of the feature sequence. Finally, the prediction results are obtained. This article conducted four comparative experiments using measured data from wind farms. The experimental results demonstrate that the model has significant advantages; compared to the CNN-BiLSTM model, the mean absolute error, mean squared error, and root mean squared error of multi-step prediction at different prediction time resolutions are reduced by 35.59%, 59.84%, and 36.77% on average, respectively, and the coefficient of determination is increased by 1.35% on average.

The inaccurate positioning of a plat valve is a crucial factor affecting the efficiency and safety of drilling operations. Because of the complicated structure of vertical drilling, it is difficult to obtain the actual position of a plat valve during the working process. This work effectively addresses the challenge of accurately measuring the deflection angle of a plat valve in mechanical automatic vertical drilling. Initially, a comprehensive mathematical model was proposed for determining the angle range of the plat valve, which was founded on the thrust generated by vertical drilling. Furthermore, this work proposed a precise measurement methodology for acquiring the crucial parameters of the MVDT. The actual deviation angle range for the N-MVDT and O-MVDT vertical drilling was calculated using data obtained from measurements of the tools. At the same time, the influence of TID on the performance of the MVDT was determined. Then, a simulation was carried out to compare the calculation results. From this, it was determined that the deflection angle range of the O-MVDT at a higher rotational speed was [86°, 58°], and the deflection angle range of the N-MVDT was [−14°, 14°]. By comparing the two methods, the error in the angle range was derived. The error of the N-MVDT was less than 16.67%, and the error of O-MVDT was less than 9.43%, proving that the measurement method and the mathematical model can accurately estimate the deflection angle range of a plat valve for mechanical automatic vertical drilling. The experimental and mathematical model results consistently showed that the deflection angle φ of the N-MVDT was significantly smaller than that of the O-MVDT, so the TID significantly improved the stability of the MVDT.

To address the difficulty in obtaining a large number of labeled jamming signals in complex electromagnetic environments, this paper proposes a small-sample communication jamming signal recognition method based on WDCGAN-SA (Wasserstein Deep Convolution Generative Adversarial Network–Self Attention) and C-ResNet (Convolution Block Attention Module–Residual Network). Firstly, leveraging the DCGAN architecture, we integrate the Wasserstein distance measurement and gradient penalty mechanism to design the jamming signal generation model WDCGAN for data augmentation. Secondly, we introduce a self-attention mechanism to make the generation model focus on global correlation features in time–frequency maps while optimizing training strategies to enhance the quality of generated samples. Finally, real samples are mixed with generated samples and fed into the classification network, incorporating cross-channel and spatial information in the classification network to improve jamming signal recognition rates. The simulation results demonstrate that under small-sample conditions with a Jamming-to-Noise Ratio (JNR) ranging from −10 dB to 10 dB, the proposed algorithm significantly outperforms GAN, WGAN and DCGAN comparative algorithms in recognizing six types of communication jamming signals.

Before the construction of a bridge begins, workers arrange the necessary parts and then cut and process them. The quality of the cutting layout directly affects the material utilization rate and the efficiency of the subsequent processes. During bridge construction, an intelligent part layout can improve work efficiency, save time, and reduce the labor intensity and production costs for the company. In this study, we studied a layout optimization algorithm, focusing on rectangular parts in the material preparation process. A mathematical model for the rectangular layout problem was constructed, and a hybrid genetic whale optimization algorithm is proposed that is a combination of the whale optimization algorithm and the genetic algorithm. Based on the “one size fits all” layout strategy, the materials are divided into strips, which are further divided into stacks, serving as the positioning strategy to determine the positional relationships of the parts. Test cases and actual engineering data were used to compare the layouts generated using different algorithms. The results show that the genetic whale algorithm proposed in this paper results in a high utilization rate and is highly effective.

Abstract Background N6-methyladenosine (m6A) and 5-methylcytosine (m5C) are the main RNA methylation modifications involved in the oncogenesis of cancer. However, it remains obscure whether m6A/m5C-related long non-coding RNAs (lncRNAs) affect the development and progression of low grade gliomas (LGG). Methods We summarized 926 LGG tumor samples with RNA-seq data and clinical information from The Cancer Genome Atlas and Chinese Glioma Genome Atlas. 105 normal brain samples with RNA-seq data from the Genotype Tissue Expression project were collected for control. We obtained a molecular classification cluster from the expression pattern of sreened lncRNAs. The least absolute shrinkage and selection operator Cox regression was employed to construct a m6A/m5C-related lncRNAs prognostic signature of LGG. In vitro experiments were employed to validate the biological functions of lncRNAs in our risk model. Results The expression pattern of 14 sreened highly correlated lncRNAs could cluster samples into two groups, in which various clinicopathological features and the tumor immune microenvironment were significantly distinct. The survival time of cluster 1 was significantly reduced compared with cluster 2. This prognostic signature is based on 8 m6A/m5C-related lncRNAs (GDNF-AS1, HOXA-AS3, LINC00346, LINC00664, LINC00665, MIR155HG, NEAT1, RHPN1-AS1). Patients in the high-risk group harbored shorter survival times. Immunity microenvironment analysis showed B cells, CD4 + T cells, macrophages, and myeloid-derived DC cells were significantly increased in the high-risk group. Patients in high-risk group had the worse overall survival time regardless of followed TMZ therapy or radiotherapy. All observed results from the TCGA-LGG cohort could be validated in CGGA cohort. Afterwards, LINC00664 was found to promote cell viability, invasion and migration ability of glioma cells in vitro. Conclusion Our study elucidated a prognostic prediction model of LGG by 8 m6A/m5C methylated lncRNAs and a critical lncRNA regulation function involved in LGG progression. High-risk patients have shorter survival times and a pro-tumor immune microenvironment.

Type II diabetes mellitus (TIIDM) remains a challenging clinical issue for both dentists and orthopedists. By virtue of persistent hyperglycemia and altered host metabolism, the pathologic diabetic micromilieu with chronic inflammation, advanced glycation end products accumulation, and attenuated biomineralization severely impairs bone regeneration efficiency. Aiming to “remodel” the pathologic diabetic micromilieu, we 3D-printed bioscaffolds composed of Sr-containing mesoporous bioactive glass nanoparticles (Sr-MBGNs) and gelatin methacrylate (GelMA). Sr-MBGNs act as a biomineralization precursor embedded in the GelMA-simulated extracellular matrix and release Sr, Ca, and Si ions enhancing osteogenic, angiogenic, and immunomodulatory properties. In addition to angiogenic and anti-inflammatory outcomes, this innovative design reveals that the nanocomposites can modulate extracellular matrix reconstruction and simulate biomineralization by activating lysyl oxidase to form healthy enzymatic crosslinked collagen, promoting cell focal adhesion, modulating osteoblast differentiation, and boosting the release of OCN, the noncollagenous proteins (intrafibrillar mineralization dependent), and thus orchestrating osteogenesis through the Kindlin-2/PTH1R/OCN axis. This 3D-printed bioscaffold provides a multifunctional biomineralization-inspired system that remodels the “barren” diabetic microenvironment and sheds light on the new bone regeneration approaches for TIIDM.

The infections in open fracture induce high morbidity worldwide. Thus, developing efficient anti-infective orthopedic devices is of great significance. In this work, we designed a kind of infection-responsive long-term antibacterial bone plates. Through a facile and flexible volatilization method, a multi-aldehyde polysaccharide derivative, oxidized sodium alginate, was crosslinked with multi-amino compounds, gentamycin and gelatin, to fabricate a uniform coating on Ti bone plates via Schiff base reaction, which was followed by a secondary crosslinking process by glutaraldehyde. The double-crosslinked coating was stable under normal condition, and could responsively release gentamycin by the triggering of the acidic microenvironment caused by bacterial metabolism, owning to the pH-responsiveness of imine structure. The thickness of the coating was ranging from 22.0 μm to 63.6 μm. The coated bone plates (Ti-GOGs) showed infection-triggered antibacterial properties (>99%) and high biocompatibility. After being soaked for five months, it still possessed efficient antibacterial ability, showing its sustainable antibacterial performance. The in vivo anti-infection ability was demonstrated by an animal model of infection after fracture fixation (IAFF). At the early stage of IAFF, Ti-GOGs could inhibit the bacterial infection (>99%). Subsequently, Ti-GOGs could promote recovery of fracture of IAFF. This work provides a convenient and universal strategy for fabrication of various antibacterial orthopedic devices, which is promising to prevent and treat IAFF.

Bone-related diseases refer to a group of skeletal disorders that are characterized by bone and cartilage destruction. Conventional approaches can regulate bone homeostasis to a certain extent. However, these therapies are still associated with some undesirable problems. Fortunately, recent advances in nanomaterials have provided unprecedented opportunities for diagnosis and therapy of bone-related diseases. This review provides a comprehensive and up-to-date overview of current advanced theranostic nanomaterials in bone-related diseases. First, the potential utility of nanomaterials for biological imaging and biomarker detection is illustrated. Second, nanomaterials serve as therapeutic delivery platforms with special functions for bone homeostasis regulation and cellular modulation are highlighted. Finally, perspectives in this field are offered, including current key bottlenecks and future directions, which may be helpful for exploiting nanomaterials with novel properties and unique functions. This review will provide scientific guidance to enhance the development of advanced nanomaterials for the diagnosis and therapy of bone-related diseases.

Radial spokes (RS) are T-shaped multiprotein complexes on the axonemal microtubules. Repeated RS1, RS2, and RS3 couple the central pair to modulate ciliary and flagellar motility. Despite the cell type specificity of RS3 substructures, their molecular components remain largely unknown. Here, we report that a leucine-rich repeat-containing protein, LRRC23, is an RS3 head component essential for its head assembly and flagellar motility in mammalian spermatozoa. From infertile male patients with defective sperm motility, we identified a splice site variant of LRRC23. A mutant mouse model mimicking this variant produces a truncated LRRC23 at the C-terminus that fails to localize to the sperm tail, causing male infertility due to defective sperm motility. LRRC23 was previously proposed to be an ortholog of the RS stalk protein RSP15. However, we found that purified recombinant LRRC23 interacts with an RS head protein RSPH9, which is abolished by the C-terminal truncation. Evolutionary and structural comparison also shows that LRRC34, not LRRC23, is the RSP15 ortholog. Cryo-electron tomography clearly revealed that the absence of the RS3 head and the sperm-specific RS2-RS3 bridge structure in LRRC23 mutant spermatozoa. Our study provides new insights into the structure and function of RS3 in mammalian spermatozoa and the molecular pathogenicity of LRRC23 underlying reduced sperm motility in infertile human males.

Background Obstructive sleep apnea (OSA) is a complex and multi-gene inherited disease caused by both genetic and environmental factors. However, due to the high cost of diagnosis and complex operation, its clinical application is limited. This study aims to explore potential target genes associated with OSA and establish a corresponding diagnostic model. Methods This study used microarray datasets from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) related to OSA and perform functional annotation and pathway analysis. The study employed multi-scale embedded gene co-expression network analysis (MEGENA) combined with least absolute shrinkage and selection operator (LASSO) regression analysis to select hub genes and construct a diagnostic model for OSA. In addition, the study conducted correlation analysis between hub genes and OSA-related genes, immunoinfiltration, gene set enrichment analysis (GSEA), miRNA network analysis, and identified potential transcription factors (TFs) and targeted drugs for hub genes. Finally, the study used chronic intermittent hypoxia (CIH) mouse model to simulate OSA hypoxic conditions and verify the expression of hub genes in CIH mice. Results In this study, a total of 401 upregulated genes and 275 downregulated genes were identified, and enrichment analysis revealed that these differentially expressed genes may be associated with pathways such as vasculature development, cellular response to cytokine stimulus, and negative regulation of cell population proliferation. Through MEGENA combined with LASSO regression, seven OSA hub genes were identified, including C12orf54, FOS, GPR1, OR9A4, MYO5B, RAB39B, and KLHL4. The diagnostic model constructed based on these genes showed strong stability. The expression levels of hub genes were significantly correlated with the expression levels of OSA-related genes and mainly acted on pathways such as the JAK/STAT signaling pathway and the cytosolic DNA-sensing pathway. Drug-target predictions for hub genes were made using the Connectivity Map (CMap) database and the Drug-Gene Interaction database (Dgidb), which identified targeted therapeutic drugs for the hub genes. In vivo experiments showed that the hub genes were all decreasing in the OSA mouse model. Conclusions This study identified novel biomarkers for OSA and established a reliable diagnostic model. The transcriptional changes identified may help to reveal the pathogenesis, mechanisms, and sequelae of OSA.

Abstract Background The factors that maintain phenotypic and genetic variation within a population have received long-term attention in evolutionary biology. Here the genetic basis and evolution of the geographically widespread variation in twig trichome color (from red to white) in a shrub Melastoma normale was investigated using Pool-seq and evolutionary analyses. Results The results show that the twig trichome coloration is under selection in different light environments and that a 6-kb region containing an R2R3 MYB transcription factor gene is the major region of divergence between the extreme red and white morphs. This gene has two highly divergent groups of alleles, one of which likely originated from introgression from another species in this genus and has risen to high frequency (> 0.6) within each of the three populations under investigation. In contrast, polymorphisms in other regions of the genome show no sign of differentiation between the two morphs, suggesting that genomic patterns of diversity have been shaped by homogenizing gene flow. Population genetics analysis reveals signals of balancing selection acting on this gene, and it is suggested that spatially varying selection is the most likely mechanism of balancing selection in this case. Conclusions This study demonstrate that polymorphisms on a single transcription factor gene largely confer the twig trichome color variation in M. normale, while also explaining how adaptive divergence can occur and be maintained in the face of gene flow.

Abstract Background Tremendous amounts of omics data accumulated have made it possible to identify cancer driver pathways through computational methods, which is believed to be able to offer critical information in such downstream research as ascertaining cancer pathogenesis, developing anti-cancer drugs, and so on. It is a challenging problem to identify cancer driver pathways by integrating multiple omics data. Results In this study, a parameter-free identification model SMCMN, incorporating both pathway features and gene associations in Protein–Protein Interaction (PPI) network, is proposed. A novel measurement of mutual exclusivity is devised to exclude some gene sets with “inclusion” relationship. By introducing gene clustering based operators, a partheno-genetic algorithm CPGA is put forward for solving the SMCMN model. Experiments were implemented on three real cancer datasets to compare the identification performance of models and methods. The comparisons of models demonstrate that the SMCMN model does eliminate the “inclusion” relationship, and produces gene sets with better enrichment performance compared with the classical model MWSM in most cases. Conclusions The gene sets recognized by the proposed CPGA-SMCMN method possess more genes engaging in known cancer related pathways, as well as stronger connectivity in PPI network. All of which have been demonstrated through extensive contrast experiments among the CPGA-SMCMN method and six state-of-the-art ones.

Zearalenone (ZEA) exposure has carcinogenic effects on human and animal health by exhibiting intestinal, hepatic, and renal toxicity. At present, the un-derlying mechanisms on how ZEA induces apoptosis and damage to tissues still remain unclear. In this study, we aimed to identify genes that modulate the cellular response to ZEA using clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 screening, and further validate novel gene functions to elucidate molecular mechanisms underlying particular biological processes in vivo and in vitro. Two ZEA-resistant cell lines, designated Ov-KCNJ4 and Ov-KCNJ12, were yielded by CRISPR activation screening which had significant changes in ZEA resistance and growth rates. Results showed that ZEA could interact with the cell membrane proteins KCNJ4 and KCNJ12, inducing cell cycle arrest, disruption of DNA replication and base excision repair. Overexpression of KCNJ4 and KCNJ12 was involved in ZEA resistance by regulating cell cycle to neutralize toxicity, sustaining mitochondrial morphology and function via at-tenuating the damage from oxidative stress in the KCNJ4-mitoKATP pathway. In vivo experiments showed that AAV-KCNJ4 delivery significantly improved ZEA-induced renal impairment and increased antioxidative enzyme activity by im-proving mitochondrial function. Our findings suggest that increasing potassium channel levels may be a putative therapeutic target for mycotoxin-induced damage.

Abstract Background The identification of disease-related genes is of great significance for the diagnosis and treatment of human disease. Most studies have focused on developing efficient and accurate computational methods to predict disease-causing genes. Due to the sparsity and complexity of biomedical data, it is still a challenge to develop an effective multi-feature fusion model to identify disease genes. Results This paper proposes an approach to predict the pathogenic gene based on multi-head attention fusion (MHAGP). Firstly, the heterogeneous biological information networks of disease genes are constructed by integrating multiple biomedical knowledge databases. Secondly, two graph representation learning algorithms are used to capture the feature vectors of gene-disease pairs from the network, and the features are fused by introducing multi-head attention. Finally, multi-layer perceptron model is used to predict the gene-disease association. Conclusions The MHAGP model outperforms all of other methods in comparative experiments. Case studies also show that MHAGP is able to predict genes potentially associated with diseases. In the future, more biological entity association data, such as gene-drug, disease phenotype-gene ontology and so on, can be added to expand the information in heterogeneous biological networks and achieve more accurate predictions. In addition, MHAGP with strong expansibility can be used for potential tasks such as gene-drug association and drug-disease association prediction.

Nowadays, infectious diseases persist as a global crisis by causing significant destruction to public health and the economic stability of countries worldwide. Especially bacterial infections remain a most severe concern due to the prevalence and emergence of multi-drug resistance (MDR) and limitations with existing therapeutic options. Antibacterial photodynamic therapy (APDT) is a potential therapeutic modality that involves the systematic administration of photosensitizers (PSs), light, and molecular oxygen (O2) for coping with bacterial infections. Although the existing porphyrin and non-porphyrin PSs were effective in APDT, the poor solubility, limited efficacy against Gram-negative bacteria, and non-specific distribution hinder their clinical applications. Accordingly, to promote the efficiency of conventional PSs, various polymer-driven modification and functionalization strategies have been adopted to engineer multifunctional hybrid phototherapeutics. This review assesses recent advancements and state-of-the-art research in polymer-PSs hybrid materials developed for APDT applications. Further, the key research findings of the following aspects are considered in-depth with constructive discussions: i) PSs-integrated/functionalized polymeric composites through various molecular interactions; ii) PSs-deposited coatings on different substrates and devices to eliminate healthcare-associated infections; and iii) PSs-embedded films, scaffolds, and hydrogels for regenerative medicine applications.

One previously undescribed alkaloid, named penifuranone A (1), and three known compounds (2–4) were isolated from the mangrove endophytic fungus Penicillium crustosum SCNU-F0006. The structure of the new alkaloid (1) was elucidated based on extensive spectroscopic data analysis and single-crystal X-ray diffraction analysis. Four natural isolates and one new synthetic derivative of penifuranone A, compound 1a, were screened for their antimicrobial, antioxidant, and anti-inflammatory activities. Bioassays revealed that penifuranone A (1) exhibited strong anti-inflammatory activity in vitro by inhibiting nitric oxide (NO) production in lipopolysaccharide-activated RAW264.7 cells with an IC50 value of 42.2 μM. The docking study revealed that compound 1 exhibited an ideal fit within the active site of the murine inducible nitric oxide synthase (iNOS), establishing characteristic hydrogen bonds.

In order to effectively improve the drilling speed in deep hard rock and save drilling costs, this study explores the transformation mechanism and critical velocity range of ultra-high-speed diamond drilling technology on rock breaking effect, using marble as an example. The study establishes an ultra-high-speed single diamond fragmentation model using the finite element method (FEM) and solves for the unknown critical velocity of marble in this drilling technique. Additionally, small diameter bit drilling experiments were conducted on our self-developed ultra-high-speed diamond drilling test bench. Based on existing simulation results and experimental studies, we discuss the critical velocity problem and compare and analyze the change in the rock-breaking mechanism and mechanical specific energy (MSE) under conventional drilling versus ultra-high-speed rotary drilling conditions. Our results indicate that changes in rock breaking mechanisms under ultra-high-speed diamond drilling conditions are limited to a specific speed range and do not persist with increasing speeds. Furthermore, experimental verification confirms that ultra-high-speed diamond drilling can effectively reduce MSE and increase the rate of penetration (ROP) by altering the rock-breaking mode. It is hoped that these findings will provide valuable insights for applying this technology to various hard rocks.

The BRI1 EMS suppressor 1(BES1) transcription factor is a crucial regulator in the signaling pathway of Brassinosteroid (BR) and plays an important role in plant growth and response to abiotic stress. Although the identification and functional validation of BES1 genes have been extensively explored in various plant species, the understanding of their role in woody plants—particularly the endangered species Phoebe bournei (Hemsl.) Yang—remains limited. In this study, we identified nine members of the BES1 gene family in the genome of P. bournei; these nine members were unevenly distributed across four chromosomes. In our further evolutionary analysis of PbBES1, we discovered that PbBES1 can be divided into three subfamilies (Class I, Class II, and Class IV) based on the evolutionary tree constructed with Arabidopsis thaliana, Oryza sativa, and Solanum lycopersicum. Each subfamily contains 2–5 PbBES1 genes. There were nine pairs of homologous BES1 genes in the synteny analysis of PbBES1 and AtBES1. Three segmental replication events and one pair of tandem duplication events were present among the PbBES1 family members. Additionally, we conducted promoter cis-acting element analysis and discovered that PbBES1 contains binding sites for plant growth and development, cell cycle regulation, and response to abiotic stress. PbBES1.2 is highly expressed in root bark, stem bark, root xylem, and stem xylem. PbBES1.3 was expressed in five tissues. Moreover, we examined the expression profiles of five representative PbBES1 genes under heat and drought stress. These experiments preliminarily verified their responsiveness and functional roles in mediating responses to abiotic stress. This study provides important clues to elucidate the functional characteristics of the BES1 gene family, and at the same time provides new insights and valuable information for the regulation of resistance in P. bournei.

As an enzootic pathogen, the Lyme disease bacterium Borrelia burgdorferi possesses multiple copies of chemotaxis proteins, including two chemotaxis histidine kinases (CHK), CheA1 and CheA2. Our previous study showed that CheA2 is a genuine CHK that is required for chemotaxis; however, the role of CheA1 remains mysterious. This report first compares the structural features that differentiate CheA1 and CheA2 and then provides evidence to show that CheA1 is an atypical CHK that controls the virulence of B. burgdorferi through modulating the stability of RpoS, a key transcriptional regulator of the spirochete. First, microscopic analyses using green-fluorescence-protein (GFP) tags reveal that CheA1 has a unique and dynamic cellular localization. Second, loss-of-function studies indicate that CheA1 is not required for chemotaxis in vitro despite sharing a high sequence and structural similarity to its counterparts from other bacteria. Third, mouse infection studies using needle inoculations show that a deletion mutant of CheA1 (cheA1mut) is able to establish systemic infection in immune-deficient mice but fails to do so in immune-competent mice albeit the mutant can survive at the inoculation site for up to 28 days. Tick and mouse infection studies further demonstrate that CheA1 is dispensable for tick colonization and acquisition but essential for tick transmission. Lastly, mechanistic studies combining immunoblotting, protein turnover, mutagenesis, and RNA-seq analyses reveal that depletion of CheA1 affects RpoS stability, leading to reduced expression of several RpoS-regulated virulence factors (i.e., OspC, BBK32, and DbpA), likely due to dysregulated clpX and lon protease expression. Bulk RNA-seq analysis of infected mouse skin tissues further show that cheA1mut fails to elicit mouse tnf-α, il-10, il-1β, and ccl2 expression, four important cytokines for Lyme disease development and B. burgdorferi transmigration. Collectively, these results reveal a unique role and regulatory mechanism of CheA1 in modulating virulence factor expression and add new insights into understanding the regulatory network of B. burgdorferi.

Background Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is the central enzyme of glycolysis and plays important regulatory roles in plant growth and development and responses to adverse stress conditions. However, studies on the characteristics and functions of cotton GAPDH family genes are still lacking. Methods In this study, genome-wide identification of the cotton GAPDH gene family was performed, and the phylogeny, gene structures, promoter progenitors and expression profiles of upland cotton GAPDH gene family members were explored by bioinformatics analysis to highlight potential functions. The functions of GhGAPDH9 in response to drought stress were initially validated based on RNA-seq, qRT‒PCR, VIGS techniques and overexpression laying a foundation for further studies on the functions of GAPDH genes. Results This study is the first systematic analysis of the cotton GAPDH gene family, which contains a total of 84 GAPDH genes, among which upland cotton contains 27 members. Quantitative, phylogenetic and covariance analyses of the genes revealed that the GAPDH gene family has been conserved during the evolution of cotton. Promoter analysis revealed that most cis-acting elements were related to MeJA and ABA. Based on the identified promoter cis-acting elements and RNA-seq data, it was hypothesized that Gh_GAPDH9, Gh_GAPDH11, Gh_GAPDH19 and Gh_GAPDH21 are involved in the response of cotton to abiotic stress. The expression levels of the Gh_GAPDH9 gene in two drought-resistant and two drought-sensitive materials were analyzed by qRT‒PCR and found to be high early in the treatment period in the drought-resistant material. The silencing of Gh_GAPDH9 based on virus-induced gene silencing (VIGS) technology resulted in significant leaf wilting or whole-plant dieback in silenced plants after drought stress compared to the control. The content of—malondialdehyde (MDA) in cotton leaves was significantly increased, and the content of proline (Pro) and chlorophyll (Chl) was reduced. In addition, the leaf wilting and dryness of transgenic lines under drought stress were lower than those of wild-type Arabidopsis, indicating that Gh_GAPDH9 is a positive regulator of drought resistance. In conclusion, our results demonstrate that GAPDH genes play an important role in the response of cotton to abiotic stresses and provide preliminary validation of the function of the Gh_GAPDH9 gene under drought stress. These findings provide an important theoretical basis for further studies on the function of the Gh_GAPDH9 gene and the molecular mechanism of the drought response in cotton.

Healing of an anterior cruciate ligament (ACL) autologous graft in a bone tunnel occurs through the formation of fibrovascular scar tissue, which is structurally and compositionally inferior to normal fibrocartilaginous insertion and thus may increase the reconstruction failure and the rate of failure recurrence. In this study, an injectable hydroxyapatite/type I collagen (HAp/Col Ⅰ) paste was developed to construct a suitable local microenvironment to accelerate the healing of bone-tendon interface. Physicochemical characterization demonstrated that the HAp/Col Ⅰ paste was injectable, uniform and stable. The in vitro cell culture illustrated that the paste could promote MC3T3-E1 cells proliferation and osteogenic expression. The results of a canine ACL reconstruction study showed that the reconstructive ACL had similar texture and color as the native ACL. The average width of the tunnel, total bone volume, bone volume/tissue volume and trabecular number acquired from micro-CT analysis suggested that the healing of tendon-bone interface in experimental group was better than that in control group. The biomechanical test showed the maximal loads in experimental group achieved approximately half of native ACL's maximal load at 24 weeks. According to histological examination, Sharpey fibers could be observed as early as 12 weeks postoperatively while a typical four-layer transitional structure of insertion site was regenerated at 48 weeks in the experimental group. The injectable HAp/Col Ⅰ paste provided a biomimetic scaffold and microenvironment for early cell attachment and proliferation, further osteogenic expression and extracellular matrix deposition, and in vivo structural and functional regeneration of the tendon-bone interface.

Abstract Background Immune-related genes (IRGs) remain poorly understood in their function in the onset and progression of sepsis. Methods GSE65682 was obtained from the Gene Expression Omnibus database. The IRGs associated with survival were screened for subsequent modeling using univariate Cox regression analysis and least absolute shrinkage and selection operator in the training cohort. Then, we assessed the reliability of the 7 IRGs signature's independent predictive value in the training and validation cohorts following the creation of a signature applying multivariable Cox regression analysis. After that, we utilized the E-MTAB-4451 external dataset in order to do an independent validation of the prognostic signature. Finally, the CIBERSORT algorithm and single-sample gene set enrichment analysis was utilized to investigate and characterize the properties of the immune microenvironment. Results Based on 7 IRGs signature, patients could be separated into low-risk and high-risk groups. Patients in the low-risk group had a remarkably increased 28-day survival compared to those in the high-risk group (P

Abstract Background Hepatocellular carcinoma (HCC) belongs to a representative lethality gastrointestinal malignancy, and comprehensive management of HCC remains intractable at present on account of its invasive biological feature that is easy to relapse and early metastasis. The intimate connection between platelets and tumor progression has been widely reported, and platelet-related indicators are also used in the clinical practice of carcinoma. This work is designed to investigate the significance of platelet-related genes in the prognostic prediction of patients with HCC and their potential role in the cross-talk between HCC cells and platelets in the tumor microenvironment. Methods By integrating the RNA-seq data and clinicopathological information of HCC patients, we extracted prognosis-associated platelet-related genes based on the univariate cox analysis and further established a relevant prognostic signature via the lasso cox regression analysis, and two independent HCC cohorts were used as external validation. Multiple bioinformatics methods were utilized to explore the underlying functional discrepancy between different risk groups classified by the risk model. And in vitro proliferation, invasion, and migration assays were conducted to investigate the effect of platelet stimulation on HCC cells’ viability and motility, and flow cytometric analysis was exerted to demonstrate the influence of HCC cells on platelet activation. Results A novel platelet-related risk model was developed and patients both in the training and testing cohorts were divided into distinct risk subgroups according to the median risk score. It was observed that the high-risk status was closely associated with poor prognosis and worse clinicopathological parameters. Meanwhile, an obvious discrepancy in the constitution of the immune microenvironment also indicated that distinct immune status might be a potential determinant affecting prognosis as well as immunotherapy reactiveness. Moreover, in vitro experiments demonstrated that PRKCD could act as a molecular bridge between tumor cells and platelets, which could either participate in regulating tumor malignant phenotype or mediating platelet activation. Conclusions In brief, this work reveals a novel platelet-related risk signature for prognostic evaluation of HCC patients and confirms that PRKCD is a key messenger in HCC cell-platelet interaction and plays a crucial role in mediating platelet-induced tumor progression.

Cytochalasans, with diverse structures and pharmacological activities, are a class of compounds containing isoindolinone moieties fused to the tricyclic or tetracyclic ring system. Chaetoglobosin A (cheA), mainly produced by Chaetomium globosum, is the most abundant cytochalasan. However, limited understanding of transcriptional regulation of morphological development and cheA biosynthesis in C. globosum has hindered cheA application in agriculture and biomedical field. This study examined the regulatory role of CgVeA gene in C. globosum. CgVeA had significant effect on secondary metabolites production in C. globosum, similar to that reported in other filamentous fungi. Inactivation of CgVeA caused an obvious decrease in cheA production from 51.32 to 19.76 mg/L under dark conditions. In contrast, CgVeA overexpression resulted in a dramatic increase in cheA production, reaching 206.59 mg/L under light conditions, which was higher than that noted under dark condition. The RT-qPCR results confirmed that CgVeA, as a light responsive regulator, positively regulated cheA biosynthesis by controlling the expression of core genes of the cheA biosynthetic gene cluster and other relevant regulators. Electrophoretic mobility shift assays proved that CgVeA directly regulated LaeA, cheR, and p450, and indirectly regulated PKS. Moreover, CgVeA had a significant effect on the regulation of asexual spores production. When compared with wild-type C. globosum, CgVeA-silenced and CgVeA overexpression mutants presented remarkable differences in sporulation, irrespective of light or dark condition. Besides, CgVeA expression was speculated to negatively regulate spore formation. These findings illustrated the regulatory mechanism of a hypothetical global regulator, CgVeA, in C. globosum, suggesting its potential application in industrial-scale cheA biosynthesis.

The improved corrosion resistance, osteogenic activity, and antibacterial ability are the key factors for promoting the large-scale clinical application of magnesium (Mg)-based implants. In the present study, a novel nanocomposite coating composed of inner magnesium hydroxide, middle graphene oxide, and outer hydroxyapatite (Mg(OH)2/GO/HA) is constructed on the surface of Mg-0.8Ca–5Zn-1.5Ag by a combined strategy of hydrothermal treatment, electrophoretic deposition, and electrochemical deposition. The results of material characterization and electrochemical corrosion test showed that all the three coatings have high bonding strength, hydrophilicity and corrosion resistance. In vitro studies show that Mg(OH)2 indeed improves the antibacterial activity of the substrate. The next GO and GO/HA coating procedures both promote the osteogenic differentiation of MC3T3-E1 cells and show no harm to the antibacterial activity of Mg(OH)2 coating, but the latter exhibits the best promoting effect. In vivo studies demonstrate that the Mg alloy with the composite coating not only ameliorates osteolysis induced by bacterial invasion but also promotes bone regeneration under both normal and infected conditions. The current study provides a promising surface modification strategy for developing multifunctional Mg-based implants with good corrosion resistance, antibacterial ability and osteogenic activity to enlarge their biomedical applications.

The fast development of biomaterials science and engineering has generated significant number of studies and publications as well as tremendous amount of research data. A methodology is needed to translate such research data and results to validated scientific evidence. This article for the first time proposes the concept and methodology of evidence-based biomaterials research, which is to use evidence-based research approach represented by systematic reviews to generate evidence for answering scientific questions related to biomaterials. After briefly introducing the advancement of biomaterials since 1950s, the scientific and engineering nature of biomaterials are discussed along with the roadmap of biomaterials translation from basic research to commercialized medical products, and the needs of scientific evidence. Key information of the evidence-based approach such as its origination from evidence-based medicine, levels of evidence, systematic review and meta-analysis, differences between systematic and narrative reviews is then highlighted. Applications with a step-by-step procedure of conducting evidence-based biomaterials research, three examples of biomaterials research using evidence-based approach to generate scientific evidence, and opportunities and challenges of evidence-based biomaterials research are presented. With its notable impact on the practice of medicine, the evidence-based approach is also expected to make influential contributions to the biomaterials field.

Introduction: Proteins located in subcellular compartments have played an indispensable role in the physiological function of eukaryotic organisms. The pattern of protein subcellular localization is conducive to understanding the mechanism and function of proteins, contributing to investigating pathological changes of cells, and providing technical support for targeted drug research on human diseases. Automated systems based on featurization or representation learning and classifier design have attracted interest in predicting the subcellular location of proteins due to a considerable rise in proteins. However, large-scale, fine-grained protein microscopic images are prone to trapping and losing feature information in the general deep learning models, and the shallow features derived from statistical methods have weak supervision abilities.Methods: In this work, a novel model called HAR_Locator was developed to predict the subcellular location of proteins by concatenating multi-view abstract features and shallow features, whose advanced advantages are summarized in the following three protocols. Firstly, to get discriminative abstract feature information on protein subcellular location, an abstract feature extractor called HARnet based on Hybrid Attention modules and Residual units was proposed to relieve gradient dispersion and focus on protein-target regions. Secondly, it not only improves the supervision ability of image information but also enhances the generalization ability of the HAR_Locator through concatenating abstract features and shallow features. Finally, a multi-category multi-classifier decision system based on an Artificial Neural Network (ANN) was introduced to obtain the final output results of samples by fitting the most representative result from five subset predictors.Results: To evaluate the model, a collection of 6,778 immunohistochemistry (IHC) images from the Human Protein Atlas (HPA) database was used to present experimental results, and the accuracy, precision, and recall evaluation indicators were significantly increased to 84.73%, 84.77%, and 84.70%, respectively, compared with baseline predictors.

Glycerophospholipids including phosphatidylethanolamine (PE) and phosphatidylcholine (PC) are vital components of biological membranes. Trypanosomatid parasites of the genus Leishmania can acquire PE and PC via de novo synthesis and the uptake/remodeling of host lipids. In this study, we investigated the ethanolaminephosphate cytidylyltransferase (EPCT) in Leishmania major, which is the causative agent for cutaneous leishmaniasis. EPCT is a key enzyme in the ethanolamine branch of the Kennedy pathway which is responsible for the de novo synthesis of PE. Our results demonstrate that L. major EPCT is a cytosolic protein capable of catalyzing the formation of CDP-ethanolamine from ethanolamine-phosphate and cytidine triphosphate. Genetic manipulation experiments indicate that EPCT is essential in both the promastigote and amastigote stages of L. major as the chromosomal null mutants cannot survive without the episomal expression of EPCT. This differs from our previous findings on the choline branch of the Kennedy pathway (responsible for PC synthesis) which is required only in promastigotes but not amastigotes. While episomal EPCT expression does not affect promastigote proliferation under normal conditions, it leads to reduced production of ethanolamine plasmalogen or plasmenylethanolamine, the dominant PE subtype in Leishmania. In addition, parasites with episomal EPCT exhibit heightened sensitivity to acidic pH and starvation stress, and significant reduction in virulence. In summary, our investigation demonstrates that proper regulation of EPCT expression is crucial for PE synthesis, stress response, and survival of Leishmania parasites throughout their life cycle.

Background: The treatment of microtia or acquired ear deformities by surgery is a significant challenge for plastic and ENT surgeons; one of the most difficult points is constructing the scaffold for auricular reconstruction. As a type of cell with multiple differentiation potentials, stem cells play an essential role in the construction of cartilage scaffolds, and therefore have received widespread attention in ear reconstructive research.Methods: A literature search was conducted for peer-reviewed articles between 2005 and 2023 with the following keywords: stem cells; auricular cartilage; ear cartilage; conchal cartilage; auricular reconstruction, regeneration, and reparation of chondrocytes; tissue engineering in the following databases: PubMed, MEDLINE, Cochrane, and Ovid.Results: Thirty-three research articles were finally selected and their main characteristics were summarized. Adipose-derived stem cells (ADSCs), bone marrow mesenchymal stem cells (BMMSCs), perichondrial stem/progenitor cells (PPCs), and cartilage stem/progenitor cells (CSPCs) were mainly used in chondrocyte regeneration. Injecting the stem cells into the cartilage niche directly, co-culturing the stem cells with the auricular cartilage cells, and inducing the cells in the chondrogenic medium in vitro were the main methods that have been demonstrated in the studies. The chondrogenic ability of these cells was observed in vitro, and they also maintained good elasticity and morphology after implantation in vivo for a period of time.Conclusion: ADSC, BMMSC, PPC, and CSPC were the main stem cells that have been researched in craniofacial cartilage reconstruction, the regenerative cartilage performed highly similar to normal cartilage, and the test of AGA and type II collagen content also proved the cartilage property of the neo-cartilage. However, stem cell reconstruction of the auricle is still in the initial stage of animal experiments, transplantation with such scaffolds in large animals is still lacking, and there is still a long way to go.