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In this study, we genotyped 939 unrelated healthy individuals to investigate the genetic polymorphisms of 38 Y chromosome short tandem repeats(Y-STRs) loci included in the Yfiler™ Platinum kit in the Hui population of Shaanxi Province. Comprehensive population comparisons were performed using analysis of molecular variance(AMOVA), multidimensional scaling(MDS), and molecular evolutionary genetics analysis(MEGA) to explore population relationships. The allele frequencies of the single-copy loci ranged from 0.001 to 0.940 (DYS645), while those of the multi-copy loci ranged from 0.001 to 0.138 (DYS527). The highest genetic diversity (GD) value was observed for DYS385 (0.9723), and the lowest for DYS645 (0.1138). A total of 849 distinct haplotypes were identified among the 939 Hui individuals, with 808 (95.2 %) being unique. Haplotype diversity (HD), haplotype match probability, and discriminatory power (DC) in the Shaanxi Hui population were 0.9996, 0.0015, and 0.9041, respectively. Interpopulation comparisons based on Rst genetic distance values, phylogenetic trees, and MDS indicated that the Shaanxi Hui population has a close genetic relationship with the Ningxia Hui, Qinghai Hui, Xinjiang Hui, and Yunnan Hui populations. The population genetic stratification largely coincides with geographic distribution and language families. Our study revealed that the 38 Y-STR loci exhibit high genetic polymorphisms in the Hui population from Shaanxi Province.

Abstract Respiratory syncytial virus (RSV), a member of the Pneumoviridae family, can cause severe acute lower respiratory tract infection in infants, young children, immunocompromised individuals and elderly people. RSV is associated with an augmented innate immune response, enhanced secretion of inflammatory cytokines, and necrosis of infected cells. Oxidative stress, which is mainly characterized as an imbalance in the production of reactive oxygen species (ROS) and antioxidant responses, interacts with all the pathophysiologic processes above and is receiving increasing attention in RSV infection. A gradual accumulation of evidence indicates that ROS overproduction plays an important role in the pathogenesis of severe RSV infection and serves as a major factor in pulmonary inflammation and tissue damage. Thus, antioxidants seem to be an effective treatment for severe RSV infection. This article mainly reviews the information on oxidative stress and ROS-mediated cellular events during RSV infection for the first time.

Abstract The superhydrophobic characteristics and functional durability of the lotus leaf are determined by its surface flexible multistage topography. In this study, it is found that the hybrid arrangement of sub‐millimeter (sub‐mm) and micron papillae arrays on the edge of lotus leaves is more conducive to its resistance to hydrostatic and hydrodynamic water pressure, which provides a guarantee for the survival of lotus leaves. Inspired by this special design, a flexible hybrid structure is prepared by the template method, whose surface contains sub‐mm pillars, micropillars, and nanostructures. It has obvious advantages in resisting the continuous impact of water droplets. This systematic study reveals why the surface of the lotus leaf can withstand the fluid impact, and it provides a theoretical and experimental basis for improving the durability of artificial superhydrophobic function.

A Yagi plasma antenna model was established by HFSS according to the relationship between plasma dielectric constant and electron density. The patterns were simulated by changing plasma parameters and the number of director dipoles. Results show that when the passive vibrators were switched off, the antenna is omnidirectional antenna. The directionality increases with the increase of the number of passive dipole and the main lobe of which narrows down. Then the plasma Yagi antenna model is established by plasma tube, the gain changed by changing the number of passive dipoles, so the plasma Yagi antenna has a very good reconfigurability. Results prove that the feasibility of the plasma Yagi antenna can be used on AIS base station of Ships’ Routeing waters. It can promote the communication and capability of maritime supervision in Ships’ Routeing waters.

Background Immune checkpoint inhibitors (ICIs), including anti-PD-1 therapy, have limited efficacy in patients with microsatellite stable (MSS) colorectal cancer (CRC). Interleukin 17A (IL-17A) activity leads to a protumor microenvironment, dependent on its ability to induce the production of inflammatory mediators, mobilize myeloid cells and reshape the tumor environment. In the present study, we aimed to investigate the role of IL-17A in resistance to antitumor immunity and to explore the feasibility of anti-IL-17A combined with anti-PD-1 therapy in MSS CRC murine models.Methods The expression of programmed cell death-ligand 1 (PD-L1) and its regulation by miR-15b-5p were investigated in MSS CRC cell lines and tissues. The effects of miR-15b-5p on tumorigenesis and anti-PD-1 treatment sensitivity were verified both in vitro and in colitis-associated cancer (CAC) and APCmin/+ murine models. In vivo efficacy and mechanistic studies were conducted using antibodies targeting IL-17A and PD-1 in mice bearing subcutaneous CT26 and MC38 tumors.Results Evaluation of clinical pathological specimens confirmed that PD-L1 mRNA levels are associated with CD8+ T cell infiltration and better prognosis. miR-15b-5p was found to downregulate the expression of PD-L1 at the protein level, inhibit tumorigenesis and enhance anti-PD-1 sensitivity in CAC and APCmin/+ CRC models. IL-17A led to high PD-L1 expression in CRC cells through regulating the P65/NRF1/miR-15b-5p axis. Combined IL-17A and PD-1 blockade had efficacy in CT26 and MC38 tumors, with more cytotoxic T lymphocytes cells and fewer myeloid-derived suppressor cells in tumors.Conclusions IL-17A increases PD-L1 expression through the p65/NRF1/miR-15b-5p axis and promotes resistance to anti-PD-1 therapy. Blocking IL-17A improved the efficacy of anti-PD-1 therapy in MSS CRC murine models. IL-17A might serve as a therapeutic target to sensitize patients with MSS CRC to ICI therapy.

Biomaterial with the dual-functions of bone regeneration and antibacterial is a novel therapy for infective bone defects. Three-dimensional (3D)-printed porous titanium (pTi) benefits bone ingrowth, but its microporous structure conducive to bacteria reproduction. Herein, a multifunctional hydrogel was prepared from dynamic supramolecular assembly of sodium tetraborate (Na 2 B 4 O 7 ), polyvinyl alcohol (PVA), silver nanoparticles (AgNPs) and tetraethyl orthosilicate (TEOS), and composited with pTi as an implant system. The pTi scaffolds have ideal pore size and porosity matching with bone, while the supramolecular hydrogel endows pTi scaffolds with antibacterial and biological activity. In vitro assessments indicated the 3D composite implant was biocompatible, promoted bone marrow mesenchymal stem cells (BMSCs) proliferation and osteogenic differentiation, and inhibited bacteria, simultaneously. In vivo experiments further demonstrated that the implant showed effective antibacterial ability while promoting bone regeneration. Besides distal femur defect, the innovative scaffolds may also serve as an ideal biomaterial (e.g. dental implants) for other contaminated defects.

Abstract Circulating exosome holds great potentials as biomarker for diagnosis and prognosis of human cancers. Previously, we have applied small RNA sequencing to identify aberrantly expressed exosomal miRNAs as candidates for diagnostic markers in colon cancer patients. In this validation cohort, plasma derived exosomal miRNA was isolated from 50 early-stage colon cancer patients and 50 matched healthy volunteers. Real-time qRT-PCR revealed that miR-125a-3p, miR-320c were significantly up-regulated in plasma exosomes of the patients with early stage colon cancer. ROC curve showed that miR-125a-3p abundant level may predict colon cancer with an area of under the curve (AUC) of 68.5%, in comparison to that of CEA at 83.6%. Combination of miR-125a-3P and CEA improved the AUC to 85.5%. In addition, plasma exosome level of miR-125a-3p and miR-320c showed significant correlation with nerve infiltration (P 0.05). On the contrary, plasma CEA level is correlated with tumor size, infiltration depth, and differentiation degree (P

Abstract Drug resistance, which is closely correlated with an imbalance in apoptosis, endows colorectal cancer (CRC) with enhanced progression capacity irrespective of the treatment with therapeutics. We report that miR-15b-5p is a tumor suppressor whose level is globally decreased in CRC cells and tissues. Over-expression of miR-15b-5p not only promoted 5-fluorouracil (5-FU)-induced cellular apoptosis but also reversed the chemoresistance of 5-FU in vitro and in vivo. As a key mediator of inflammation-induced cancer, miR-15b-5p enhances these therapeutic effects are mainly attributed to targeting of the NF-κB signaling pathway through negative regulation of NF-κB1 and one of its kinase complexes IKK-α. miR-15b-5p mediates NF-ĸB regulation by targeting the anti-apoptosis protein XIAP in vitro. Together, these results establish an axis of miR-15b-mediated apoptosis regulation, which reverses chemoresistance and suppresses CRC progression. These findings suggest that miR-15b-5p may be a potential agent for CRC treatment, particularly for 5-FU-resistant CRC.

Tenderness is one of the most important properties of meat quality, which is influenced by genetic and environmental factors. As an intensively studied epigenetic marker, histone methylation, occurring on arginine and lysine residues, has pivotal regulatory functions on gene expression. To examine whether histone methylation involves in beef tenderness variation, we analyzed the transcriptome and H3K4me3 enrichment profiles of muscle strips obtained from the longissimus dorsi (LD) of Angus steers previously classify to the tender or tough group. We first plotted a global bovine H3K4me3 map on chromosomes and called peak-enriched regions and genes. We found that majorities of H3K4me3 on genes were occupying the first intron and intergenic regions and its maps displayed similar patterns in tender and tough groups, with high H3K4me3 enrichment surrounding the transcription start site (TSS). We also explored the relationship of H3K4me3 and gene expression. The results showed that H3K4me3 enrichment is highly positively correlated with gene expression across the whole genome. Cluster analysis results confirmed the relationship of H3K4me3 enrichment and gene expression. By using a pathway-based approach in genes with H3K4me3 enrichment in promoter regions from the tender cluster, we revealed that those genes involved in the development of different tissues-connective tissue, skeletal and muscular system and functional tissues-; while in tough group those genes engaged in cell death, lipid metabolism and small molecule biochemistry. The results from this study provide a deep insight into understanding of the mechanisms of epigenetic regulations in meat quality and beef tenderness.

Abstract Objective Tumor blood vessels are tortuous and dilated, contributing to the aberrant tumor microenvironment. CD93 is a newly reported transmembrane receptor, mainly expressed in tumor endothelial cells, that has demonstrated prognostic value in some cancer types. However, the role of CD93 in the vasculature of colorectal cancer (CRC) tissues and its prognostic significance remain unknown. It is therefore necessary to explore the effect of CD93 in patients with CRC. Method We detected the expression of CD93 in human CRC tissues using immunohistochemistry. We then examined the correlation between CD93 expression and clinicopathological factors in cancer tissues from 134 patients with CRC. Result CD93 expression levels were higher in CRC vessels than in vessels in adjacent normal tissues. Upregulation of CD93 was associated with tumor site and microsatellite instability. CD93 protein expression was positively related to macrophage infiltration in CRC. High expression of CD93 may indicate normalization of the tumor vasculature and was associated with better overall survival. Conclusion CD93 was highly expressed in CRC vessels and correlated with infiltration of immune cells. Our findings reveal that vascular normalization and patient prognosis can be predicted by detecting CD93 expression in CRC tumor tissues.

Abstract The Streptococcus suis (S. suis) is an important zoonotic pathogen that causes streptococcal disease in pigs and poses a threat to humans. This study provides an understanding of the prevalence of S.suis in eastern China and provides guidance for clinical prophylaxis. From 2021 to 2023, a total of 143 strains of S. suis were isolated from 1642 lung tissue and nasal swabs from healthy and suspected infected pigs in Shandong Province, China, using the Phenotypic tests and PCR technique. The isolates were then tested for serotype, virulence-related genes, and resistance genes. Among the 143 isolates, type 2 was the predominant serotype with 98 isolates (98/143, 68.5%), followed by type 5 with 22 isolates (22/143, 15.3%), type 4 with 6 isolates (6/143, 4.2%), type 19 with 4 isolates (4/143, 2.8%) and type 21 with 5 isolates (5/143, 3.5%), respectively. A minimum of 78.3% of the strains exhibited the presence of virulence-related genes including pgda, dlta, mann, fbps, orf2, and sspa, whereas the virulence-associated genes Sum, Sly, and Salkr are not widely prevalent. For the detection of resistance genes, it was found that the tetO gene had a high detection rate of 70.1% (101/143), whereas neither the pbp2b gene nor the cat1 and cat2 genes were detected. Antimicrobial susceptibility testing revealed that 96.5% (138/143) of the isolates exhibited multidrug resistance (MDR). And polypeptide B was found to be tolerated by 125 of the 143 strains (87.4%). Although we did not detect the β-lactam resistance gene in any of the 143 strains, an average of 39.2% of the strains were resistant to β-lactam antibiotics. The results of the current study is thought it may be help to understand the prevalence of S. suis and provide important insights into treatment and prevention.

Abstract Background Breast cancer remains the most prevalent malignancy and the leading cause of cancer-related mortality among women worldwide. The primary factors contributing to the deterioration and death of patients with breast cancer are metastasis, recurrence, and drug resistance. These phenomena are closely related to the presence of breast cancer stem cells; however, the exact mechanisms regulating stemness remain to be elucidated. Rack1 (Receptor for Activated C Kinase 1), a well-known versatile scaffold protein, has been implicated in tumorigenesis and progression in numerous cancer types; however, its specific role in breast cancer stemness remains to be elucidated. Methods Using bioinformatic and immunohistochemical approaches, we validated that the expression level of Rack1 is associated with cancer stemness and affects the prognosis of patients. Through a series of experimental methods including mammosphere formation assay, flow cytometry, qPCR, Western blotting, and CHX assays, we validated at the molecular and cellular levels the mechanism by which Rack1 influences cancer stemness via the E2F1/SOX2 axis. Furthermore, by designing and utilizing lentiviral constructs to establish xenograft tumor models in mice, we further confirmed in vivo the impact of the Rack1/E2F1/SOX2 axis on the tumorigenic capacity of breast cancer cells. Results Our findings indicate that Rack1 plays a critical role in preserving the stemness characteristics of breast cancer cells. Mechanistically, the observed effects of Rack1 are achieved through the modulation of SOX2 expression, a master transcription factor that regulates cancer cell stemness and maintenance. We further demonstrate that Rack1 increases the stability of the E2F1 protein by inhibiting its ubiquitination and subsequent proteasome-mediated degradation, which in turn transcriptionally upregulates SOX2, thereby maintaining breast cancer cell stemness and tumorigenesis. Conclusion This study thus unveils a novel mechanism through which Rack1 executes its oncogenic function. This study also demonstrates that targeting the Rack1-E2F-SOX2 axis may be a potential strategy to inhibit breast cancer development and progression.

Highlights A three-dimensional multiscale liquid metal/polyacrylonitrile evaporator is fabricated through wet spinning and assembly. The evaporator exhibits an outstanding water evaporation rate of 2.66 kg m−2 h−1 with a solar energy efficiency of 96.5% under one sun irradiation. The evaporator demonstrates a superior purification performance for seawater and sewage under light irradiation.

ABSTRACT In response to the severe problem of coal powder production in the Panhe block coalbed methane wells in the southern Qinshui Basin, the characteristics of coal powder production in the study area were identified through sample testing, indoor experiments, and theoretical calculations. The settling velocity of coal powder with different mesh sizes was clarified, and a correction factor α was proposed for the experimental and theoretical results of settling velocity. The research results indicate that the coal powder concentration in the Panhe block ranges from 0.03 to 7.14 g/L, with an average of 1.26 g/L. The particle size of the coal powder produced was 4.10–237.64 μm, with an average of 35.82 μm. The settling velocity of coal powder particles with a mesh size of 40–400 is between 0.0041 and 0.029 m/s. The larger the particle size of coal powder particles, the higher the settling velocity of coal powder; the correction coefficient ranges from 2.3 to 13.67. A corrected settling velocity calculation model was obtained by fitting the coal powder particle size data to the correction coefficient. The research results provide a theoretical basis for developing production conditions, coal powder prevention, and control measures for coalbed methane wells in the Panhe area.

Abstract Purpose Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide. The Fat mass and obesity-associated protein (FTO), a genetic variant associated with obesity, significantly impact the energetic metabolism of mechanical tumors. However, research on the function of FTO in CRC is scarce. Methods Bioinformatics analysis of TCGA and UALCAN databases was conducted to examine FTO expression in CRC. Immunohistochemistry was used to assess FTO and PKM2 protein expression in clinical specimens. In vitro experiments utilized five human colon cancer cell lines and a normal colon epithelial cell line, with Western blotting and RT-PCR for protein and mRNA quantification, respectively, and lentiviral transfection to modulate FTO expression. Cellular behaviors such as proliferation, migration, invasion, and apoptosis were evaluated using various assays. Immunofluorescence and Seahorse Xfe96 metabolic analysis were employed to study PKM2 expression changes and glycolytic stress. The effects of PKM2 inhibition by shikonin on cell viability and glycolytic activity were assessed using CCK-8 assay and Seahorse analysis. Results An upregulation of FTO was observed in colon cancer through data mining and analysis of pathological specimens. Besides, we discovered that the impact of FTO on colon cancer glycolysis has significant implications for colon proliferation, invasion, and metastasis. The protein expression of PKM2 and the intensity of fluorescence staining in the nucleus of PKM2 were detected to be increased in colon carcinoma cells with over-expression of FTO. Conclusion FTO plays a significant role in CRC progression by regulating PKM2 and promoting glycolysis.

Recent advancements in low Earth orbit (LEO) satellite technology have facilitated a substantial increase in the number of Earth observation (EO) satellites launched. However, transmitting voluminous imagery generated by these EO satellites to the ground still faces the challenges of limited satellite resources and dynamic satellite networks. To address this problem, we propose SEC-DT, a Satellite Edge Computing (SEC) enabled computation-aware dynamic Data Transmission framework for jointly optimizing the routing selection and in-orbit imagery compression adoption. Specifically, we formulate an online optimization problem for concurrently delivering data from multiple EO satellites in a single EO mission, aiming to minimize the overall transmission and computation latency while ensuring the decent quality of the final downloaded data. Then we cast the problem as a partially observable Markov decision process and adopt an augmented multi-agent reinforcement learning (MARL) algorithm to solve this intractable online decision problem. Considering the natural graph structure of the satellite network, we innovatively integrate the graph neural network (GNN) into the MARL algorithm to form a GNN-assisted MARL framework, wherein GNN can capture the enriched semantic information present in satellite topology to achieve the fusion of diverse environmental states, which is beneficial for improving the decision-making effectiveness of agents. Finally, we conduct extensive experiments and ablation studies in various settings based on real-world datasets of StarLink and SkySat constellations. The experimental results have demonstrated the scalability and excellent performance of our algorithm compared with other baseline schemes.

Abstract Optimizing the installation parameters of photovoltaic panels in a photovoltaic array to reduce dust accumulation, thereby enhancing their power generation, is a crucial research topic in the construction of solar power stations in desert regions. Utilizing a series of wind tunnel experiments on a photovoltaic array comprising four equally sized panels, this study assessed how variations in tilt angle, mounting height, spacing, and incoming flow direction influence both the accumulation mass of dust and the particle size distribution in a photovoltaic array. The results indicate that the dust accumulation on the first panel exponential growth with increasing tilt angle, incoming flow angles, and height, while subsequent panels displayed a trend of initial increase followed by a decrease, with a maximum increasing ratio achieved at specific installation configurations, the difference of dust mass on each panel can even be several times. Notably, when the spacing between panels exceeds twice the panel height, the mutual influence on dust deposition becomes negligible, providing a quantifiable threshold for optimal panel spacing. Additionally, significant differences exist in the particle size characteristics of dust in the panel of the array, influenced by the installation parameters of panels and the direction of the incoming flow. This research not only enhances the understanding of dust accumulation in solar energy systems but also offers practical recommendations for optimizing installation strategies, thereby improving the economic viability of solar power stations, particularly in desert regions.

Abstract This study proved that the curves of carbon monoxide (CO), carbon dioxide (CO2), and CO + CO2 in the off-gas profile were forecastable, and realized a 32-s-ahead forecasting for them. It established a technical foundation for addressing the delay in off-gas profile display and for enabling pre-control in BOF steelmaking based on the forecasted curves’ features. First, a data pre-processing method was proposed based on the characteristics of the off-gas curves, where there are many samples, but each sample contains limited time-steps. It is termed the mixed-batch approach. The importance of the time series’ channels and time-steps were also analyzed by models with attention mechanism. Then, a deep-learning model is proposed to forecast the dynamic off-gas profile, named attention-based convolutional aggregation (ABCA). It incorporates artificial intelligence (AI) techniques, such as aggregation structures, causal dilation convolution, attention mechanisms, residual connections, etc. Its forecasting coefficient of determination (R 2 ) values for the curves of CO, CO2, and CO + CO2 reached 0.9386, 0.8566, and 0.9428, respectively, while the mean squared errors (MSEs) values were 47.3884, 11.9314, and 54.3583, respectively. These results outperform the benchmark state-of-the-art (SOTA) models. Additionally, ABCA was implemented in a forecasting tool for external validation. The results of external validation showed that ABCA has good forecasting accuracy and robustness. What is more, approaches in four aspects of pre-control of BOF steelmaking process with forecasted off-gas profile were also provided as pre-control examples.

Effective perovskite crystallization control strategies for flexible substrates with scalable processing techniques have rarely been reported and remain an important challenge. In this study, 3-mercaptobenzoic acid (3-MBA) was introduced into the perovskite precursor to modulate the crystallization dynamics, facilitating rapid nucleation while slowing down crystal growth. This approach enabled the formation of uniform, dense large-area perovskite films on flexible substrates. Consequently, a 12 cm² flexible perovskite solar module achieved a power conversion efficiency (PCE) of 16.43%. Additionally, the module exhibited enhanced mechanical stability under various bending radii and improved light stability, marking a substantial advance toward the practical application of flexible perovskite solar modules.

ABSTRACT The variability and unpredictability of wind power generation present significant challenges for grid management and planning. Enhancing the accuracy of wind power forecasting is crucial for improving the reliability of renewable energy systems. To enhance the accuracy of temporal wind power predictions, the IVMD–DCInformer–HSSA framework has been introduced. Initially, the original wind power data is decomposed into multiple intrinsic mode function (IMF) components using the improved variational mode decomposition (IVMD) technique. Subsequently, the Sparrow search algorithm (HSSA) is employed to optimize the parameters of the enhanced Informer deep neural network, which are then integrated into the improved Informer model. The predictions of each IMF component resulting from the IVMD decomposition are then combined to generate the final prediction outcome. The experimental results show that the R‐squared value of the proposed combined model is increased to 0.9903, and the accuracy is increased by 1%–3% compared with other models, which has a good prediction effect.

Abstract Background and objective Chronic prostatitis (CP) is a condition markered by persistent prostate inflammation, yet the specific cytokines driving its progression remain largely undefined. This study aims to identify key cytokines involved in CP and investigate their role in driving inflammatory responses through mechanistic and therapeutic exploration. Methods A 48-cytokine panel test was conducted to compare the plasma cytokine profiles between participants with CP-like symptoms (CP-LS) and healthy controls. Experimental autoimmune prostatitis (EAP) models were used for functional validation, with further mechanistic studies performed through in vivo and in vitro assays. Pharmacological inhibition was applied using maraviroc, and pathway inhibitors to assess therapeutic potential. Results Our analysis identified CCL5 as one of the most prominently elevated cytokines in CP-LS patients. Further validation in the EAP model mice confirmed elevated CCL5 levels, highlighting its role in driving prostatic inflammation. Mechanistic studies revealed that CCL5 interacts with the CCR5 receptor, promoting M1 macrophage polarization and activating key inflammatory signaling pathways, including Stat1 and NF-κB, as indicated by increased phosphorylation of Stat1 and p65. In vitro, CCL5 combined with LPS stimulation amplified these effects, further promoting M1 polarization. CCL5 also sustained Stat1 activation by inhibiting its dephosphorylation through reduced interaction with SHP2, leading to prolonged inflammatory signaling. Single-cell transcriptomics confirmed high CCR5 expression in macrophages, correlating with inflammatory pathways. Pharmacological inhibition of CCR5, or its downstream signaling, significantly reduced macrophage-driven inflammation both in vivo and in vitro. Conclusion These findings establish the CCL5/CCR5 axis as a critical driver of persistant prostatic inflammation and present it as a potential therapeutic target for CP. Graphic Abstract The graphic abstract illustrates the central role of the CCL5/CCR5 axis in promoting chronic prostatitis progression. CCL5 binds to the CCR5 receptor on macrophages, enhancing M1 polarization and activating key inflammatory pathways, including Stat1 and NF-κB, as shown by the increased phosphorylation of Stat1 and p65. The interaction also inhibits SHP2-mediated Stat1 dephosphorylation, sustaining prolonged inflammatory signaling. Pharmacological inhibition of CCR5 or its downstream pathways attenuates macrophage-driven inflammation, highlighting this axis as a critical driver and potential therapeutic target for chronic prostatitis.

First, the stability and tensile properties of the Al/Mg2Si interface doped with alloying elements in the Al–Mg–Si system of aluminum alloys are calculated from first principles. Then, the two experimental alloys with different components were heat treated and the properties were characterized. Calculations show that when the interface is doped with Cu, the tensile stress that the interface can withstand increases to 3.13 GPa; when the interface is doped with Cu and Ce, the tensile strain that the interface can withstand increases to 20% and the tensile stress that the interface can withstand increases to 4.17 GPa; when the interface is doped with Cu and Sc, the tensile strain that the interface can withstand increases to more than 25% and the tensile stress that the interface can withstand increases to 5.08 GPa or more. Characterization of the organization and properties of the experimental alloys showed that Ce not only increased the peak solid solution temperature of the alloys, but also increased the tensile and yield strengths of the alloys in the extruded state by 16% and 13.74%, respectively. During hot extrusion, Ce was able to promote the precipitation of precipitated phases. During aging, the addition of Ce promoted the aging precipitation of the alloy, which not only increased the number of precipitated phases in the alloy, but also refined the precipitated phases and enhanced the aging strengthening effect of the alloy. This study provides technical guidance for the development of new aluminum alloy materials with high strength and low cost.

Abstract Menaquinone (MK) in bacterial membrane is an attractive target for the development of novel therapeutic agents. Mining the untapped chemical diversity encoded by Gram-negative bacteria presents an opportunity to identify additional MK-binding antibiotics (MBAs). By MK-binding motif searching of bioinformatically predicted linear non-ribosomal peptides from 14,298 sequenced genomes of 45 underexplored Gram-negative bacterial genera, here we identify a novel MBA structural family, including silvmeb and pseudomeb, using structure prediction-guided chemical synthesis. Both MBAs show rapid bacteriolysis by MK-dependent membrane depolarization to achieve their potent activities against a panel of Gram-positive pathogens. Furthermore, both MBAs are proven to be effective against methicillin-resistant Staphylococcus aureus in a murine peritonitis-sepsis model. Our findings suggest that MBAs are a kind of structurally diverse and still underexplored antibacterial lipodepsipeptide class. The interrogation of underexplored bacterial taxa using synthetic bioinformatic natural product methods is an appealing strategy for discovering novel biomedically relevant agents to confront the crisis of antimicrobial resistance.

Abstract Background Plant-specific TIFY proteins play crucial roles in regulating plant growth, development, and various stress responses. However, there is no information available about this family in Artemisia argyi, a well-known traditional medicinal plant with great economic value. Results A total of 34 AaTIFY genes were identified, including 4 TIFY, 22 JAZ, 5 PPD, and 3 ZML genes. Structural, motif scanning, and phylogenetic relationships analysis of these genes revealed that members within the same group or subgroup exhibit similar exon-intron structures and conserved motif compositions. The TIFY genes were unevenly distributed across the 15 chromosomes. Tandem duplication events and segmental duplication events have been identified in the TIFY family in A. argyi. These events have played a crucial role in the gene multiplication and compression of different subfamilies within the TIFY family. Promoter analysis revealed that most AaTIFY genes contain multiple cis-elements associated with stress response, phytohormone signal transduction, and plant growth and development. Expression analysis of roots and leaves using RNA-seq data revealed that certain AaTIFY genes showed tissue-specific expression patterns, and some AaTIFY genes, such as AaTIFY19/29, were found to be involved in regulating salt and saline-alkali stresses. In addition, RT-qPCR analysis showed that TIFY genes, especially AaTIFY19/23/27/29, respond to a variety of hormonal treatments, such as MeJA, ABA, SA, and IAA. This suggested that TIFY genes in A. argyi regulate plant growth and respond to different stresses by following different hormone signaling pathways. Conclusion Taken together, our study conducted a comprehensive identification and analysis of the TIFY gene family in A. argyi. These findings suggested that TIFY might play an important role in plant development and stress responses, which laid a valuable foundation for further understanding the function of TIFY genes in multiple stress responses and phytohormone crosstalk in A. argyi.

Abstract Understanding litter decomposition processes in coastal macrophyte habitats is critically important for predicting ecosystem functioning. However, decomposition processes of litter mixtures in coastal habitats remain largely unexplored. Here, we evaluated the litter mixture effects on the decomposition of six marine macrophytes (two seagrasses and four macroalgae) through in situ litter-mixing experiments with five levels of litter species richness and 36 different litter compositions. We found that the litter species identity and composition, rather than species richness, were crucial in structuring benthic faunal communities. Macroalgal litter, particularly Sargassum sp., hosted higher numbers of polychaetes and crustaceans than seagrass litter. More macroalgal presence induced faster decomposition rates of seagrass litter in the late stage, but not in the early stage. These findings suggest that changes in macrophyte diversity and composition can alter decomposition processes and, consequently, the sediment organic carbon stock through the transition of litter sources and benthic faunas.

Abstract To compare the efficacy and advantages of mini percutaneous nephrostomy (MPCN), micropercutaneous nephrostomy (MicroPCN), and retrograde ureteric stenting (RUS) in the treatment of acute upper urinary tract calculi (UUTC) obstruction with hydronephrosis and infection, and verify the safety and indications of clinical application of micropercutaneous nephrostomy. Clinical-epidemiological data of patients with acute upper urinary tract calculi obstruction and infection treated in Ningbo No.2 hospital were retrospectively collected from May 2019 to May 2023. 64 patients (20 patients in MPCN group, 13 patients in MicroPCN group, and 31 patients in RUS group) were eligible for analysis based on inclusion and exclusion criteria. P value

Abstract Objective To evaluate the clinical outcomes of arthroscopic inside-out ganglionectomy of dominant dorsal wrist ganglion. Methods Patients with dominant wrist ganglion cyst treated in our hospital from January 1, 2014 to June 31, 2023 was enrolled in this retrospective analysis. All patients underwent dye-assist arthroscopic inside-out ganglionectomy. After discharge, the patients were followed for a minimum of 6 months. The primary outcomes were to assess patient wrist function using the Patient-Rated Wrist Evaluation (PRWE) and Mayo Modified Wrist Score (MMWS). The secondary outcomes were visual analog score (VAS), wrist active range of motion (ROM), grip strength, recurrence rate and complication. Results All ganglion were successfully resected after dye staining. Patients were followed for an average of 12.17 months. There were no significant changes between preoperative and postoperative wrist active ROM or grip strength, except for wrist flexion (which showed a slightly greater improvement after surgery, P = 0.049), there were notable improvements in VAS, MMWS, and PRWE postoperatively. Recurrence occurred in 3 patients. No major complications observed during the follow-up period. Conclusion Dye-assist arthroscopic inside-out ganglionectomy is safe and uncomplicated, worth of clinical promotion.

Abstract Background The acute levodopa challenge test (ALCT) is a universal method for evaluating levodopa response (LR). Assessment of Movement Disorder Society’s Unified Parkinson’s Disease Rating Scale part III (MDS-UPDRS III) is a key step in ALCT, which is some extent subjective and inconvenience. Methods This study developed a machine learning method based on instrumented Timed Up and Go (iTUG) test to evaluate the patients’ response to levodopa and compared it with classic ALCT. Forty-two patients with parkinsonism were recruited and administered with levodopa. MDS-UPDRS III and the iTUG were conducted in both OFF-and ON-medication state. Kinematic parameters, signal time and frequency domain features were extracted from sensor data. Two XGBoost models, levodopa response regression (LRR) model and motor symptom evaluation (MSE) model, were trained to predict the levodopa response (LR) of the patients using leave-one-subject-out cross-validation. Results The LR predicted by the LRR model agreed with that calculated by the classic ALCT (ICC = 0.95). When the LRR model was used to detect patients with a positive LR, the positive predictive value was 0.94. Conclusions Machine learning based on wearable sensor data and the iTUG test may be effective and comprehensive for evaluating LR and predicting the benefit of dopaminergic therapy.

Abstract Background The active functionalities of RNA are recognized to be heavily dependent on the structure and sequence. Therefore, a model that can accurately evaluate a design by giving RNA sequence-structure pairs would be a valuable tool for many researchers. Machine learning methods have been explored to develop such tools, showing promising results. However, two key issues remain. Firstly, the performance of machine learning models is affected by the features used to characterize RNA. Currently, there is no consensus on which features are the most effective for characterizing RNA sequence-structure pairs. Secondly, most existing machine learning methods extract features describing entire RNA molecule. We argue that it is essential to define additional features that characterize nucleotides and specific sections of RNA structure to enhance the overall efficacy of the RNA design process. Results We develop two deep learning models for evaluating RNA sequence-secondary structure pairs. The first model, NU-ResNet, uses a convolutional neural network architecture that solves the aforementioned problems by explicitly encoding RNA sequence-structure information into a 3D matrix. Building upon NU-ResNet, our second model, NUMO-ResNet, incorporates additional information derived from the characterizations of RNA, specifically the 2D folding motifs. In this work, we introduce an automated method to extract these motifs based on fundamental secondary structure descriptions. We evaluate the performance of both models on an independent testing dataset. Our proposed models outperform the models from literatures in this independent testing dataset. To assess the robustness of our models, we conduct 10-fold cross validation. To evaluate the generalization ability of NU-ResNet and NUMO-ResNet across different RNA families, we train and test our proposed models in different RNA families. Our proposed models show superior performance compared to the models from literatures when being tested across different independent RNA families. Conclusions In this study, we propose two deep learning models, NU-ResNet and NUMO-ResNet, to evaluate RNA sequence-secondary structure pairs. These two models expand the field of data-driven approaches for learning RNA. Furthermore, these two models provide the new method to encode RNA sequence-secondary structure pairs.