Search

Background: The current method for liver graft implantation during the anhepatic phase is complex. Therefore, this study aimed to introduce a modified orthotopic liver transplantation (OLT) technique with major vascular reconstruction using cuff technique to simplify the process of liver graft implantation during the anhepatic phase. Methods: Twenty-four canines were randomly assigned to two groups: the modified orthotopic liver transplantation group (M-OLT, n = 12) and the control group (n = 12). All animals were randomly assigned to the donor or recipient groups. The recipients received orthotopic liver transplantation using a modified technique in the M-OLT group, and OLT using traditional implantation technique without venovenous bypass was performed in the control group. The donor and recipient characteristics were compared between the two groups. Vascular anastomotic patency was evaluated using angiography immediately and one week after surgery. Results: All recipients underwent successful liver transplantation. There were no significant differences between the two groups in terms of sex, body weight, or cold ischemia time of the donor liver. However, recipients in the M-OLT group had a shorter operation time, less intraoperative blood loss, shorter anhepatic phase, shorter vascular occlusion time, and shorter warm ischemia time than that in the control group (all p

Brachial plexus injury (BPI) with motor neurons (MNs) damage still remain poor recovery in preclinical research and clinical therapy, while cell-based therapy approaches emerged as novel strategies. Previous work of rat skin precursor-derived Schwann cells (SKP–SCs) provided substantial foundation for repairing peripheral nerve injury (PNI). Given that, our present work focused on exploring the repair efficacy and possible mechanisms of SKP-SCs implantation on rat BPI combined with neurorrhaphy post-neurotomy. Results indicated the significant locomotive and sensory function recovery, with improved morphological remodeling of regenerated nerves and angiogenesis, as well as amelioration of target muscles atrophy and motor endplate degeneration. Besides, MNs could restore from oxygen-glucose-deprivation (OGD) injury upon SKP-SCs-sourced secretome treatment, implying the underlying paracrine mechanisms. Moreover, rat cytokine array assay detected 67 cytokines from SKP-SC-secretome, and bioinformatic analyses of screened 32 cytokines presented multiple functional clusters covering diverse cell types, including inflammatory cells, Schwann cells, vascular endothelial cells (VECs), neurons, and SKP-SCs themselves, relating distinct biological processes to nerve regeneration. Especially, a panel of hypoxia-responsive cytokines (HRCK), can participate into multicellular biological process regulation for permissive regeneration milieu, which underscored the benefits of SKP-SCs and sourced secretome, facilitating the chorus of nerve regenerative microenvironment. Furthermore, platelet-derived growth factor-AA (PDGF-AA) and vascular endothelial growth factor-A (VEGF-A) were outstanding cytokines involved with nerve regenerative microenvironment regulating, with significantly elevated mRNA expression level in hypoxia-responsive SKP-SCs. Altogether, through recapitulating the implanted SKP-SCs and derived secretome as niche sensor and paracrine transmitters respectively, HRCK would be further excavated as molecular underpinning of the neural recuperative mechanizations for efficient cell therapy; meanwhile, the analysis paradigm in this study validated and anticipated the actions and mechanisms of SKP-SCs on traumatic BPI repair, and was beneficial to identify promising bioactive molecule cocktail and signaling targets for cell-free therapy strategy on neural repair and regeneration.

Enhancing the electrical conductivity of metals remains a critical challenge, as it directly determines the transmission efficiency of power electronic systems. Graphene-reinforced metal matrix composites have garnered widespread attention due to their exceptional electrical conductivity and low-temperature coefficient of resistance. This review thoroughly examines the intrinsic physical properties of Graphene and Cu, identifying specific obstacles in developing highly conductive composite materials. Despite the weak van der Waals interactions between Graphene and Cu, the work principle and interaction mechanism between Cu and Graphene are elucidated. The primary focus of this review is to explore methods for enhancing the electrical conductivity of Cu/Graphene composites through different design strategies and processing techniques. The more complex and critical factors encompass the quality of raw materials, processing techniques, dimensional precision, crystallographic orientation, and the interfacial properties between Graphene and Cu. The perspectives on the research gap and further development trends of Cu/Graphene composites are also discussed.

This study explores the global problem of misinformation dissemination on social media, particularly Twitter, due to the COVID-19 pandemic. It identifies prominent disseminators, investigates the spread of false information and the ecosystem of disinformation spreaders, and assesses their online personalities. We track the interaction among fake news spreaders using the User–User Interaction Graph. The study reveals a rapidly growing population of disseminators, including professional spreaders, with over 3% dominating the others. The collaboration among fake news spreaders is high, highlighting the need for further research using publicly available online data to understand the community spreading malicious misinformation about COVID-19.

Introduction: Gibberellin (GA) is a vital phytohormone in regulating plant growth and development. During the “Green Revolution”, modification of GA-related genes created semi-dwarfing phenotype in cereal crops but adversely affected grain weight. Gibberellin 2-oxidases (GA2oxs) in barley act as key catabolic enzymes in deactivating GA, but their functions are still less known. Objectives: This study investigates the physiological function of two HvGA2ox genes in barley and identifies novel semi-dwarf alleles with minimum impacts on other agronomic traits. Methods: Virus-induced gene silencing and CRISPR/Cas9 technology were used to manipulate gene expression of HvGA2ox9 and HvGA2ox8a in barley and RNA-seq was conducted to compare the transcriptome between wild type and mutants. Also, field trials in multiple environments were performed to detect the functional haplotypes. Results: There were ten GA2oxs that distinctly expressed in shoot, tiller, inflorescence, grain, embryo and root. Knockdown of HvGA2ox9 did not affect plant height, while ga2ox8a mutants generated by CRISPR/Cas9 increased plant height and significantly altered seed width and weight due to the increased bioactive GA4 level. RNA-seq analysis revealed that genes involved in starch and sucrose metabolism were significantly decreased in the inflorescence of ga2ox8a mutants. Furthermore, haplotype analysis revealed one naturally occurring HvGA2ox8a haplotype was associated with decreased plant height, early flowering and wider and heavier seed. Conclusion: Our results demonstrate the potential of manipulating GA2ox genes to fine tune GA signalling and biofunctions in desired plant tissues and open a promising avenue for minimising the trade-off effects of Green Revolution semi-dwarfing genes on grain size and weight. The knowledge will promote the development of next generation barley cultivars with better adaptation to a changing climate.

Microplastics (MPs) in aquatic environments easily support biofilm development, which can interact with other environmental pollutants and act as harbors for microorganisms. Recently, numerous studies have investigated the fate and behavior of MP biofilms in aquatic environments, highlighting their roles in the spread of pathogens and antibiotic resistance genes (ARGs) to aquatic organisms and new habitats. The prevalence and effects of MP biofilms in aquatic environments have been extensively investigated in recent decades, and their behaviors in aquatic environments need to be synthesized systematically with updated information. This review aims to reveal the development of MP biofilm and its interactions with antibiotics, ARGs, and pathogens in aquatic environments. Recent research has shown that the adsorption capabilities of MPs to antibiotics are enhanced after the biofilm formation, and the adsorption of biofilms to antibiotics is biased towards chemisorption. ARGs and microorganisms, especially pathogens, are selectively enriched in biofilms and significantly different from those in surrounding waters. MP biofilm promotes the propagation of ARGs through horizontal gene transfer (HGT) and vertical gene transfer (VGT) and induces the emergence of antibiotic-resistant pathogens, resulting in increased threats to aquatic ecosystems and human health. Some future research needs and strategies in this review are also proposed to better understand the antibiotic resistance induced by MP biofilms in aquatic environments.

ABSTRACT: Postpartum cows experience lipolysis in adipose tissue due to negative energy balance, and accumulation of free fatty acids leads to metabolic stress in adipose tissue. Ferroptosis is a type of cell death triggered by excessive buildup of iron-dependent lipid peroxides and is involved in the occurrence and development of various metabolic diseases in nonruminants. However, whether ferroptosis occurs in the adipose tissue of ketotic cows and the regulatory mechanisms behind ferroptosis are still unclear. Despite multiple studies demonstrating the significant involvement of hypoxia-inducible-factor-1α (HIF-1α) in regulating cellular dysfunction, its specific function in the adipose tissue of ketotic dairy cows remains uncertain, particularly its regulation of oxidative stress and ferroptosis. This study aimed to explore the effect of HIF-1α on oxidative stress and ferroptosis in bovine subcutaneous adipose tissue and isolated adipocytes. The adipose tissue of clinical ketosis cows (n = 15) with a serum BHB concentration of 3.13 mM (interquartile range = 0.14) and healthy cows (n = 15) with a serum BHB concentration of and 0.58 mM (interquartile range = 0.13) was collected. The results showed that the concentrations of lipid peroxidation malondialdehyde (MDA), reactive oxygen species (ROS), Fe2+, and total iron were increased in adipose tissue of cows with ketosis, but the contents of glutathione (GSH) were reduced. Furthermore, the protein levels of HIF-1α, heme oxygenase 1 (HMOX1), catalase (CAT), superoxide dismutase 1 (SOD1), acyl-CoA synthetase 4, and nuclear factor erythroid-derived 2-like 2 (NFE2L2) exhibited higher abundance in adipose tissue obtained from cows with ketosis, whereas the protein abundance of solute carrier family 7 member 11 (SLC7A11), glutamate-cysteine ligase catalytic subunit (GCLC), kelch-like ECH-associated protein 1, glutamate-cysteine ligase regulatory subunit (GCLM), and glutathione peroxidase 4 (GPX4) were lower. To simulate the ferroptosis state of adipose tissue in ketotic cows, primary bovine adipocytes were isolated from the adipose tissue of healthy cows and cultured with erastin to construct the ferroptosis model. Adipocytes were cultured with either an adenovirus overexpressing HIF-1α or small interfering RNA targeting HIF for 48 h, followed by exposure to erastin (1 μM) for 24 h. Treatment with erastin led to higher protein abundance of CAT, SOD1, NFE2L2 and HMOX1, and it inhibited the protein expression levels of GCLC, SLC7A11, GCLM, GPX4, and kelch-like ECH-associated protein 1. Furthermore, erastin treatment elevated the levels of ROS, MDA, Fe2+, and total iron and reduced the content of GSH. The overexpression of HIF-1α reversed the erastin-induced decreases in the protein abundance of GPX4 and SLC7A11, as well as the levels of MDA, ROS, Fe2+, and total iron, while significantly increasing protein abundance and content of CAT, SOD1, NFE2L2, HMOX1, GCLC, GCLM, GPX4, SLC7A11, and GSH. Conversely, the silencing of HIF-1α further exacerbated the erastin-induced levels of MDA, ROS, Fe2+, and total iron, while inhibiting the upregulation of SOD1, CAT, NFE2L2 and HMOX1. Collectively, these findings suggest that activation of HIF-1α may function as an adaptive mechanism to mitigate ferroptosis and alleviate oxidative stress in adipose tissue.

Summary: Polycystic ovary syndrome (PCOS) is a multifactorial disease, which is closely related to obesity. This study evaluated the efficacy of bariatric surgery on obesity complicated with PCOS through meta-analysis. PubMed, Cochrane, EMbase, and WOS databases were searched from 2012 to November 2022. Studies on the efficacy of bariatric surgery in the treatment of obesity combined with PCOS were included. Outcome indicators included menstrual abnormalities, BMI, free testosterone, hypertrichosis, and ovarian volume. Methodological quality of the included studies was evaluated, and statistical analysis was performed using RevMan 5.3 software. Finally, 9 studies were included, and the results of meta-analysis were as follows: After weight loss surgery, menstrual irregularity decreased (RR = -0.83, 95%CI:-1.00∼-0.65, P

Purpose: To explore the effect of green channel for stroke patients on the treatment of severe aneurysmal subarachnoid hemorrhage. Methods: This is a retrospective case-control study. The clinical data of patients with severe aneurysmal subarachnoid hemorrhage admitted to the emergency department of our hospital from January 2015 to June 2022 were retrospectively analyzed. Patients diagnosed with subarachnoid hemorrhage, confirmed intracranial aneurysm by preoperative CT angiography or digital subtraction, graded Hunt-Hess grade III, IV, and V, < 72 h from the onset to the time of consultation received surgical treatment in our hospital were included in this study. Patients with serious underlying diseases, such as heart, liver, kidney diseases, or malignant tumors, traumatic subarachnoid hemorrhage, previous history of cerebral hemorrhage, and incomplete data were excluded. The control group included patients with severe aneurysmal subarachnoid hemorrhage admitted from January 2015 to December 2018 before the establishment of the green channel for stroke patients, and the observation group included patients with severe aneurysmal subarachnoid hemorrhage admitted from January 2019 to June 2022 after the establishment of the green channel. The control group received routine treatment in the emergency department; the observation group received improved treatment of green channel for stroke patients. Gender, age, Hunt-Hess grade on admission, modified Rankin scale (mRS) on admission, aneurysm location, aneurysm size and whether accompanied by intracerebral hemorrhage, the time from onset to emergency department, the time from emergency department to vascular diagnostic examination, the time from onset to surgery, the time from emergency department to surgery, the time from hospital admission to surgery, length of hospital stay, complications, treatment effect were analyzed and compared between the 2 groups. SPSS 23.0 software was utilized to conduct comparisons between the 2 groups. The t-test, Chi-square test, or Mann-Whitney U test was chosen based on the data type. Statistical significance was established when p 0.05). The time (min) from visit to vascular diagnostic test (60.50 vs. 120.00, p = 0.027), the time (min) from onset to surgery (1792.00 vs. 2868.00, p = 0.023), the time (min) from emergency department to surgery (1568.50 vs. 2778.00, p = 0.016), the time (min) from hospital admission to surgery (1188.50 vs. 2708.00, p = 0.043), all of them were shorter in the observation group than those in the control group. The relative values of admission and 7-day postoperative mRS scores and the relative values of admission and discharge mRS scores ≥ 2 were used as the criteria for determining better efficacy, and the treatment effect was better than that in the control group, and the differences were statistically significant (admission to 7 days postoperative mRS score ≥ 2, 17 (50.0 %) vs. 8 (21.6 %), p = 0.012; admission to discharge mRS score ≥ 2, 19 (55.9 %) vs. 11 (29.7 %), p = 0.026). Conclusion: The green channel for stroke patients with severe aneurysmal subarachnoid hemorrhage can effectively shorten the time from arrival at the emergency department to vascular diagnostic examination and the time from the emergency department to surgery, and achieve a better therapeutic effect, which is worth popularizing and applying.

Background: This study aims to evaluate the clinical effectiveness of repetitive transcranial magnetic stimulation (rTMS) when used as an add-on therapy for individuals with persistent postural-perceptual dizziness (PPPD). Methods: In this randomized controlled, double-blind trial conducted at Shangluo Central Hospital, patients with PPPD diagnosed in the neurology departments were included. Participants were randomized into a rTMS treatment group and a control group in a 1:1 ratio by the randomized grouping method. Patients in both groups received conventional treatment, with the rTMS treatment group underwent daily rTMS sessions, whereas the control group received sham rTMS treatments following the same schedule. The effectiveness of the treatments was primarily assessed using the Dizziness Handicap Inventory (DHI), Hamilton Anxiety Rating Scale (HAMA), and Hamilton Depression Rating Scale (HAMD), which measured symptoms of vertigo, anxiety, and depression at baseline, after two weeks, and at the end of four weeks. Findings: Of the 46 participants recruited, 2 were excluded due to contraindications, 22 were randomly assigned to the rTMS treatment group, and 22 were assigned to the control group. Ultimately, 2 withdrew for personal reasons, and data from 42 participants were included in the outcome analysis. HAMA, HAMD and DHI scores were significantly lower in the rTMS treatment group than in the control group after 4 weeks of treatment (p

Identifying novel compound–protein interactions (CPIs) plays a pivotal role in target identification and drug discovery. Although the recent multimodal methods have achieved outstanding advances in CPI prediction, they fail to effectively learn both intra-modality and inter-modality dynamics, which limits their prediction performance. To address the limitation, we propose a novel multimodal tensor fusion CPI prediction framework, named MMTF-CPI, which contains three unimodal learning modules for structure, heterogeneous network and transcriptional profiling modalities, a tensor fusion module and a prediction module. MMTF-CPI is capable of focusing on both intra-modality and inter-modality dynamics with the tensor fusion module. We demonstrated that MMTF-CPI is superior to multiple state-of-the-art multimodal methods across seven datasets. The prediction performance of MMTF-CPI is significantly improved with the tensor fusion module compared to other fusion methods. Moreover, our case studies confirmed the practical value of MMTF-CPI in target identification. Via MMTF-CPI, we also discovered several candidate compounds for the therapy of breast cancer and non-small cell lung cancer.

Simultaneous nitrification and denitrification (SND) is an efficient method to remove nitrogen in municipal wastewater treatment. However, low dissolved oxygen (DO) concentrations are generally required, leading to serious membrane fouling in membrane bioreactors (MBRs). This study aimed to clarify the synergistic effect of biomass and DO on nitrogen removal and membrane fouling. To achieve this goal, four submerged MBRs equipped with ceramic membranes were operated with different biomass (mixed liquor suspended solids (MLSS)) concentrations (3 000 mg/L, 5 000 mg/L, 7 500 mg/L, and 12 000 mg/L) under various DO concentrations (2.0 mg/L, 1.0 mg/L, and 0.5 mg/L). As a result, increasing biomass in the MBRs enhanced total nitrogen (TN) removal via SND, and excellent TN removal efficiencies of 60.7% and 75.8% were obtained using the MBR with an MLSS concentration of 12 000 mg/L and DO concentrations of 2.0 mg/L and 1.0 mg/L. However, a further decrease in DO deteriorated TN removal due to the inhibition of nitrification. Moreover, high MLSS concentrations were beneficial to membrane fouling control for ceramic membranes in MBRs. The lowest transmembrane pressure development rate was observed for the MBR with an MLSS concentration of 12 000 mg/L. High biomass offset the adverse effect of DO decrease on membrane fouling to some extent, and improved the stability of the reactor. Therefore, biomass might be an important parameter for membrane fouling reduction in ceramic MBRs. Overall, optimal biomass and DO concentrations for TN removal were identified, providing useful information for the successful operation of MBRs with efficient TN removal and membrane fouling control.

WHO classified Helicobacter pylori as a Group I carcinogen for gastric cancer as early as 1994. However, despite the high prevalence of H. pylori infection, only about 3 % of infected individuals eventually develop gastric cancer, with the highly virulent H. pylori strains expressing cytotoxin-associated protein (CagA) and vacuolating cytotoxin (VacA) being critical factors in gastric carcinogenesis. It is well known that H. pylori infection is divided into two types in terms of the presence and absence of CagA and VacA toxins in serum, that is, carcinogenic Type I infection (CagA+/VacA+, CagA+/VacA-, CagA-/VacA+) and non-carcinogenic Type II infection (CagA-/VacA-). Currently, detecting the two carcinogenic toxins in active modes is mainly done by diagnosing their serological antibodies. However, the method is restricted by expensive reagents and intricate procedures. Therefore, establishing a rapid, accurate, and cost-effective way for serological profiling of carcinogenic H. pylori infection holds significant implications for effectively guiding H. pylori eradication and gastric cancer prevention. In this study, we developed a novel method by combining surface-enhanced Raman spectroscopy with the deep learning algorithm convolutional neural network to create a model for distinguishing between serum samples with Type I and Type II H. pylori infections. This method holds the potential to facilitate rapid screening of H. pylori infections with high risks of carcinogenesis at the population level, which can have long-term benefits in reducing gastric cancer incidence when used for guiding the eradication of H. pylori infections.

Inspecting in high-altitude windy environments requires maintaining a stable attitude to avoid significant oscillations, which is a crucial factor in advancing the use of hybrid power transmission line inspection robots (PTLIRs) in real-world scenarios for the electrical power and energy industry. We developed and optimized a novel walking device to improve the safety of hybrid PTLIRs operating in strong wind conditions. First, we investigate the operational conditions of transmission line inspection and design a walking device capable of transporting a flight device to be suspended under the line for inspection purposes. Second, a force equilibrium analysis is performed to explore the relationship between the key structural parameters of the walking device and the wind-induced deflection of the robot. A multiobjective optimization model is formulated to minimize the maximum deflection angle of the robot along three axes under wind loads. Finally, an optimization algorithm, using an improved non-dominated sorting particle swarm optimization (NSPSO) approach, is proposed to solve the model with good global search ability and fast convergence speed. A test platform is constructed to collect the wind deflection angle of a self-developed hybrid PTLIR under the transmission line. The test results demonstrate that the walking device can carry 30 kg to move along the transmission line. The average deflection angle of the robot around the Z axis is the highest under the influence of wind force level 7 (wind speed of 15.5 m/s) perpendicular to the windward surface of the robot. After optimization, the maximum deflection angle is limited to 10.38°, aligning within safety thresholds. The optimization algorithm effectively reduces the maximum deflection angles around the X, Z, and Y axes by 33.19 %, 39.21 %, and 13.23 %, with minimal average errors of 2.40 %, 3.87 %, and 2.13 %, respectively. The research in this paper can solve the bottleneck problem of robot practicality, which has important theoretical significance and practical application value for the safety, stability, and intelligent operation and maintenance management of power transmission lines.

Human pose estimation in sports training is a critical application within Internet of Things (IoT) environments, leveraging IoT devices to enhance performance analysis and injury prevention. Current methods struggle with real-time processing and accuracy in dynamic settings, especially with high-speed movements and diverse data. To address these challenges, we propose a novel dual-channel architecture combining Spatiotemporal Transformer and Temporal Convolutional Network (TCN), integrated into an IoT system. Our model collects real-time motion data through IoT devices, including videos, depth information, and sensor data, combining global spatiotemporal features with local temporal dependencies to enhance pose understanding and estimation accuracy. The Spatiotemporal Transformer uses multi-head self-attention to process global features, while the TCN captures local temporal dependencies across frames. A residual fusion mechanism integrates these features for comprehensive pose estimation. Extensive experiments on the Human3.6M and MPI-INF-3DHP datasets demonstrate that our model significantly outperforms existing methods, achieving Mean Per Joint Position Error (MPJPE) scores of 42.2 mm and 29.1 mm on Human3.6M. This research advances 3D human pose estimation and offers a practical tool for sports training through precise, efficient pose analysis, leveraging deep learning and IoT technologies to enhance athletic performance and prevent injuries.

With the increasing frequency of extreme weather events, heavy rainfall and flooding pose significant pressure on the flood discharge systems of tailings dams. Simple discharge systems are insufficient to meet the flood discharge requirements of tailings dams, while complex discharge systems, with their greater flood discharge capacity, are gradually being promoted. Although complex discharge systems can increase the flood discharge capacity of tailings dams, the flow patterns within the discharge systems become more complex. As a new type of discharge system layout, existing research lacks systematic analysis, and its complex flow characteristics are not clear. This paper relies on the flood discharge system of a large tailings dam to carry out theoretical calculations and derivations of the hydraulic characteristics of the complex flood discharge system. Hydraulic characteristics are observed through hydraulic model tests and verified using numerical simulations. Based on these three methods, a basis for further research on the hydraulic characteristics of complex flood discharge systems is provided. The main results are as follows: (1) The formulas for calculating the discharge flow rate Q under different flow states in the tailings dam design manual are not applicable to complex discharge systems; (2) Formulas for calculating the discharge flow rate Q under different flow states in complex discharge systems are proposed; by comparing model test values and numerical simulation values, the accuracy of the formulas for calculating the discharge flow rate Q in complex discharge systems is verified; (3) If the traditional mode is used to calculate the discharge flow rate Q in complex discharge systems, it is recommended to take the reduction coefficient as 0.55–0.56, and the model test values should also be referred to during flow state transitions.

5-formylcytidine (f5C) is a unique post-transcriptional RNA modification found in mRNA and tRNA at the wobble site, playing a crucial role in mitochondrial protein synthesis and potentially contributing to the regulation of translation. Recent studies have unveiled that the f5C modifications may drive mitochondrial mRNA translation to power cancer metastasis. Accurate identification of f5C sites is essential for further unraveling their molecular functions and regulatory mechanisms, but there are currently no computational methods available for predicting their locations. In this study, we introduce an innovative ensemble approach, successfully enabling the computational recognition of Saccharomyces cerevisiae f5C. We conducted a comprehensive model selection process that involved multiple basic machine learning and deep learning algorithms such as recurrent neural networks, convolutional neural networks and Transformer-based models. Initially trained only on sequence information, these individual models achieved an AUROC ranging from 0.7104 to 0.7492. Through the integration of 32 novel domain-derived genomic features, the performance of individual models has significantly improved to an AUROC between 0.7309 and 0.8076. To further enhance accuracy and robustness, we then constructed the ensembles of these individual models with different combinations. The best performance attained by our ensemble models reached an AUROC of 0.8391. Shapley additive explanations were conducted to explain the significant contributions of genomic features, providing insights into the putative distribution of f5C across various topological regions and potentially paving the way for revealing their functional relevance within distinct genomic contexts. A freely accessible web server that allows real-time analysis of user-uploaded sites can be accessed at: www.rnamd.org/Resf5C-Pred.

Escherichia coli (E. coli) has become a particular concern due to the increasing incidence of antimicrobial resistance (AMR) observed worldwide. Using machine learning (ML) to predict E. coli AMR is a more efficient method than traditional laboratory testing. However, further improvement in the predictive performance of existing models remains challenging. In this study, we collected 1937 high-quality whole genome sequencing (WGS) data from public databases with an antimicrobial resistance phenotype and modified the existing workflow by adding an attention mechanism to enable the modified workflow to focus more on core single nucleotide polymorphisms (SNPs) that may significantly lead to the development of AMR in E. coli. While comparing the model performance before and after adding the attention mechanism, we also performed a cross-comparison among the published models using random forest (RF), support vector machine (SVM), logistic regression (LR), and convolutional neural network (CNN). Our study demonstrates that the discriminative positional colors of Chaos Game Representation (CGR) images can selectively influence and highlight genome regions without prior knowledge, enhancing prediction accuracy. Furthermore, we developed an online tool (https://github.com/tjiaa/E.coli-ML/tree/main) for assisting clinicians in the rapid prediction of the AMR phenotype of E. coli and accelerating clinical decision-making.

The effective promotion of wound healing poses a substantial challenge for clinical treatment. Despite evidence supporting the role of extracellular vesicles (EVs) in this process, their therapeutic potential is currently restrict by challenges in targeting and maintaining them. The manufacturing process for rhCol III, or recombinant human collagen III, is stable, and the rejection rate is low. We used a cross-linking method to prepare a rhCol III incorporated sodium alginate (SA) hydrogel, which enabled to accomplish an EV sustained release that was site-specific. Cell viability through MTT assay, proliferation and ROS generation were performed with MC3T3-E1cell lines. In addition, diabetic wounds are characterised by an environment of hyper-inflammation and elevated oxidative stress. The rhCol III/SA-EVs hydrogel, which is a delivery vehicle with anti-inflammatory and antioxidant characteristics, promotes wound healing in this setting. The In vivo effectiveness of the created wound dressing on a diabetic wound model was examined in this study. After 21 days of treatment, the wound dressing significantly (p

Background: One of the key obstacles to the healing of diabetic wound is the persistence of active inflammation. We previously demonstrated the potential of cell-free fat extract (CEFFE) to promote the healing of diabetic wounds, and annexin A5 (A5) is a crucial anti-inflammatory protein within CEFFE. This study aimed to evaluate the therapeutic potential of A5 in diabetic wounds. Methods: A5 was loaded into GelMA hydrogels and applied to skin wounds of diabetic mice in vivo. The diabetic wounds with the treatment of GelMA-A5 were observed for 14 days and evaluated by histological analysis. Accessment of inflammation regulation were conducted through anti-CD68 staining, anti-CD86 and anti-CD206 staining, and qRT-PCR of wound tissue. In presence of A5, macrophages stimulated by lipopolysaccharide (LPS) in vitro, and detected through qRT-PCR, flow cytometry, and immunocytofluorescence staining. Besides, epithelial cells were co-cultured with A5 for epithelialization regulation by CCK-8 assay and cell migration assay. Results: A5 could promote diabetic wound healing and regulate inflammations by promoting the transition of macrophages from M1 to M2 phenotype. In vitro experiments demonstrated that A5 exerted a significant effect on reducing pro-inflammatory factors and inhibiting the polarization of macrophages from M0 toward M1 phenotype. A5 significantly promoted the migration of epithelial cells. Conclusion: Annexin A5 has a significant impact on the regulation of macrophage inflammation and promotion of epithelialization.

RNA plays an extensive role in a multi-dimensional regulatory system, and its biomedical relationships are scattered across numerous biological studies. However, text mining works dedicated to the extraction of RNA biomedical relations remain limited. In this study, we established a comprehensive and reliable corpus of RNA biomedical relations, recruiting over 30,000 sentences manually curated from more than 15,000 biomedical literature. We also updated RIscoper 2.0, a BERT-based deep learning tool to extract RNA biomedical relation sentences from literature. Benefiting from approximately 100,000 annotated named entities, we integrated the text classification and named entity recognition tasks in this tool. Additionally, RIscoper 2.0 outperformed the original tool in both tasks and can discover new RNA biomedical relations. Additionally, we provided a user-friendly online search tool that enables rapid scanning of RNA biomedical relationships using local and online resources. Both the online tools and data resources of RIscoper 2.0 are available at http://www.rnainter.org/riscoper.

Objectives: Combination therapy of lenvatinib and immune checkpoint inhibitors (CLICI) has emerged as a promising approach for managing unresectable hepatocellular carcinoma (HCC). However, the response to such treatment is observed in only a subset of patients, underscoring the pressing need for reliable methods to identify potential responders. Materials & methods: This was a retrospective analysis involving 120 patients with unresectable HCC. They were divided into training (n = 72) and validation (n = 48) cohorts. We developed an interpretable deep learning model using multiphase computed tomography (CT) images to predict whether patients will respond or not to CLICI treatment, based on the Response Evaluation Criteria in Solid Tumors, version 1.1 (RECIST v1.1). We evaluated the models' performance and analyzed the impact of each CT phase. Critical regions influencing predictions were identified and visualized through heatmaps. Results: The multiphase model outperformed the best biphase and uniphase models, achieving an area under the curve (AUC) of 0.802 (95% CI = 0.780–0.824). The portal phase images were found to significantly enhance the model's predictive accuracy. Heatmaps identified six critical features influencing treatment response, offering valuable insights to clinicians. Additionally, we have made this model accessible via a web server at http://uhccnet.com/ for ease of use. Conclusions: The integration of multiphase CT images with deep learning-generated heatmaps for predicting treatment response provides a robust and practical tool for guiding CLICI therapy in patients with unresectable HCC.

Cerebral cavernous malformation (CCM) is a polygenic disease with intricate genetic interactions contributing to quantitative pathogenesis across multiple factors. The principal pathogenic genes of CCM, specifically KRIT1, CCM2, and PDCD10, have been reported, accompanied by a growing wealth of genetic data related to mutations. Furthermore, numerous other molecules associated with CCM have been unearthed. However, tackling such massive volumes of unstructured data remains challenging until the advent of advanced large language models. In this study, we developed an automated analytical pipeline specialized in single nucleotide variants (SNVs) related biomedical text analysis called BRLM. To facilitate this, BioBERT was employed to vectorize the rich information of SNVs, while a deep residue network was used to discriminate the classes of the SNVs. BRLM was initially constructed on mutations from 12 different types of TCGA cancers, achieving an accuracy exceeding 99%. It was further examined for CCM mutations in familial sequencing data analysis, highlighting an upstream master regulator gene fibroblast growth factor 1 (FGF1). With multi-omics characterization and validation in biological function, FGF1 demonstrated to play a significant role in the development of CCMs, which proved the effectiveness of our model. The BRLM web server is available at http://1.117.230.196.

Abstracts: Introduction: Metabolic disturbances are major contributors to the onset and progression of non-alcoholic fatty liver disease (NAFLD), which includes a histological spectrum ranging from single steatosis (SS) to non-alcoholic steatohepatitis (NASH). This study aimed to identify serum metabolites and lipids enriched in different histological stages of NAFLD and to explore metabolites/lipids as non-invasive biomarkers in risk prediction of NAFLD and NASH in obese Chinese. Methods: Serum samples and liver biopsies were obtained from 250 NAFLD subjects. Untargeted metabolomic and lipidomic profiling were performed using Liquid Chromatography-Mass Spectrometry. Significantly altered metabolites and lipids were identified by MaAsLin2. Pathway enrichment was conducted with MetaboAnalyst and LIPEA. WGCNA was implemented to construct the co-expression network. Logistic regression models were developed to classify different histological stages of NAFLD. Results: A total of 263 metabolites and 550 lipid species were detected in serum samples. Differential analysis and pathway enrichment analysis revealed the progressive patterns in metabolic mechanisms during the transition from normal liver to SS and to NASH, including N-palmitoyltaurine, tridecylic acid, and branched-chain amino acid signaling pathways. The co-expression network showed a distinct correlation between different triglyceride and phosphatidylcholine species with disease severity. Multiple models classifying NAFLD versus normal liver and NASH versus SS identified important metabolic features associated with significant improvement in disease prediction compared to conventional clinical parameters. Conclusion: Different histological stages of NAFLD are enriched with distinct sets of metabolites, lipids, and metabolic pathways. Integrated algorithms highlight the important metabolic and lipidomic features for diagnosis and staging of NAFLD in obese individuals.

Objective: We aimed to develop a rapid, simple, and precise ultra performance liquid chromatography − tandem mass spectrometry (UPLC-MS/MS) technique for simultaneous measurement of omadacycline (OMA) and tigecycline (TGC) in the bloodstream of individuals suffering from serious bacterial infections. Methods: All analytes were extracted using a 0.2 % formic acid–water dilution and acetonitrile plasma protein precipitation. The quantification was performed by electrospray ionization-triple quadrupole mass spectrometry with selected reaction monitoring and positive ion mode detection. Tetracycline was used as an internal standard in this experiment, with the mobile phase composed of water (with 0.1 % formic acid) and acetonitrile (using gradient elution) flowing at a rate of 0.35 ml/min, and the column temperature set at 30 °C. Each individual analysis was completed in under 3.5 min. Results: The method was validated based on FDA recommendations, including the assessment of extraction recovery (92.65–101.72 %) and matrix effects (86.22–91.12 %). The standard curve ranges for both OMA and TGC are 0.025 µg/mL to 2.5 µg/mL. The plasma samples were found to be consistent after undergoing three rounds of freezing and thawing at room temperature for 24 h, being placed in an automated sample injector for 24 h, and then frozen for 45 days. Clinical cases were used to demonstrate the application of the therapeutic drug monitoring (TDM) assay, showing how an analytical test can quickly provide information on antibiotic levels in patients and impact their treatment. Conclusion: Multiplex UPLC-MS/MS assays for the simultaneous measurement of plasma OMA and TGC concentrations are the ideal choice for clinically TDM applications.

The advantages of multi-element carbides with combination of outstanding physical properties such as high hardness, high melting points, good resistance to corrosion, oxidation are attracting considerable interests due to their potential applications at extreme conditions. Herein, a new type of hexagonal ternary transition metal carbosilicides TM0.5Si0.5C (TM = Cr, Mo, W) possessing high-temperature stability and improved mechanical properties like hardness, toughness and strengths relative to the well-known SiC are firstly reported and systematically studied using first-principles calculations. Employing a hybrid approach that integrates ab initio molecular dynamics (AIMD) simulations with lattice dynamics, we determined the renormalized phonon spectra at high temperatures, confirming their dynamic and thermodynamic stabilities up to 2500 K. Utilizing a refined approach within density-functional AIMD simulations, we also investigate the ideal strengths at different temperatures, revealing these compounds exhibit large tensile strengths up to 35 GPa even at 2000 K. Electronic analysis indicates that the orbital hybridizations of TM-d and C-p as well as Si-p and C-p play the key role in determining the exceptional mechanical properties. Correlating the current results with our prior findings, we formulate a general principle guiding the design of a new class of hard multi-element ceramic compounds with superior mechanical properties and high-temperature stability.

In this study, nanotwinned Cu (NT-Cu) and SiO2 hybrid joints were fabricated at 200 °C and subjected to thermal cycling tests (TCTs) up to 2000 cycles for the reliability evaluation. It is intriguing that the measured electrical resistance of the Cu–Cu joints decreased as the cycle number increased. Interfacial microstructure analyses were carried out by plan-view and cross-sectional scanning transmission electron microscope (STEM) to analyze the evolution of microstructures at the bonding interfaces and correlate with the increase in the electrical conductivity. Results showed that the bonding quality and conductivity of the NT-Cu/SiO2 hybrid joints were enhanced after the TCTs. The electrical resistance of the joints decreased by 18% after 2000 temperature cycles. Plan-view STEM images indicate the boning interface consisted of numerous discrete nanoscale voids for the as-fabricated Cu–Cu joints, and they merged into larger voids of approximately 100 nm in diameter through Ostwald ripening mechanism during thermal cycling. Furthermore, grain growth also occurred in the interface, resulting in excellent bonding interfaces.

Background: The use of near-infrared lasers for transcranial photobiomodulation (tPBM) offers a non-invasive method for influencing brain activity and is beneficial for various neurological conditions. However, comprehensive quantitative studies on its safety are lacking. Objective: This study aims to investigate the safety of 1064-nm laser-based tPBM across brain structure, brain function, neural damage, cognitive ability and tolerance. Methods: We employed a multimodal approach, using magnetic resonance imaging (MRI), electroencephalogram (EEG), biochemical analyses, and cognitive testing to quantitatively assess the potential adverse effects of tPBM on brain structure or function, neurons, glial cells, and executive function (EF). Additionally, a detailed questionnaire was used to evaluate subjective tolerance. Results: At the whole-brain structural level, no significant variations in gray matter, white matter, or cerebrospinal fluid volume or density were observed as a result of tPBM. There was no increase in neuron-specific enolase (NSE) or S100β levels suggesting no neuronal damage, but an unexpected significant reduction in NSE was detected which requires further study to assess its implications. EEG, analyzed through power spectra and expert evaluation, revealed no potential disease-inducing effects. A series of cognitive tests demonstrated no impairment in any of the EF components. Furthermore, the questionnaire data revealed minimal discomfort across fatigue, itching, pain, burning, warmth, dizziness, and drowsiness. Conclusions: Our data indicate that 1064 nm laser tPBM does not induce adverse effects on brain structure or function, nor does it impair cognitive abilities. tPBM is safe for specific parameters, highlighting its good tolerability.

In traditional wire arc additive manufacturing process, it is difficult to control the chemical composition of deposition layer. A double filler wire with alternating current was proposed to fabricate the NiTi alloy. In this process, Ni filling wire and Ti filling wire were connected to alternating current. The macrographic, phase evolution, and mechanical properties of the as-printed sample at various wire feed speed ratios were studied. The results show that the deposition layers were consistently uniform in the deposition process. The coarse dendritic grain structure gradually changed with decreasing Ni wire feed speed. Columnar and equiaxed microstructures were observed in the deposition sample at different wire feed speed ratios. Different wire feeding speed ratios lead to variations in Ni concentration in the molten pool. The content of Ni might affect the formation of martensite and austenite during solidification. The average microhardness increases with increasing Ni wire feed speed. When the wire feeding ratio of Ni/Ti was 1.2, the compressive strength reached 1664 MPa. This study introduces an innovative method in arc additive manufacturing of NiTi alloy by utilizing an AC power source into the double filler wires.

The accumulation of ice and snow on cables in winter poses a serious threat to the transmission and safety of electricity. It is extremely necessary to prepare a strong superhydrophobic anti-icing coating on the surface of the cable to gently remove the ice and snow on its surface. In this study, we constructed rough structures using inexpensive nano SiO2, modified the hydrophobicity and flexibility of epoxy resin with acrylic resin and polydimethylsiloxane as modifiers, and prepared a robust superhydrophobic anti-icing coating that combines multiple binders. The coating was prepared by a simple air spraying process and has compatibility with both flat and curved surfaces. Compared with the pristine cable, this coating can reduce ice accumulation by about 4 times, shorten deicing time by about 2.1 times, and lower the average ice adhesion strength to 12.5 KPa, a reduction of about 90%; On stainless steel plates, the anti-icing time can be extended by about 5.8 times. In addition, the coating still has low ice adhesion strength and good hydrophobic properties after being scratched by a knife, impacted by 12 h of water flow, impacted by 500 mL sand drop, and peeled off by 60 adhesive tapes. The preparation of this coating has a simple process flow and excellent anti-icing performance, and has broad application prospects in the field of anti-icing for transmission lines.

Top-down environmental policies aim to mitigate environmental risks but inevitably lead to economic losses due to the market entry or exit of enterprises. This study developed a universal dynamic agent-based supply chain model to achieve tradeoffs between environmental risk reduction and economic sustainability. The model was used to conduct high-resolution daily simulations of the dynamic shifts in enterprise operations and their cascading effects on supply chain networks. It includes production, consumption, and transportation agents, attributing economic features to supply chain components and capturing their interactions. It also accounts for adaptive responses to daily external shocks and replicates realistic firm behaviors. By coupling high spatial–temporal resolution firm-level data from 18 916 chemical enterprises, this study investigates the economic and environmental impacts of an environmental policy resulting in the closure of 1800 chemical enterprises over three years. The results revealed a significant economic loss of 25.8 billion USD, ranging from 23.8 billion to 31.8 billion USD. Notably, over 80% of this loss was attributed to supply chain propagation. Counterfactual analyses indicated that implementing a staggered shutdown strategy prevented 18.8% of supply chain losses, highlighting the importance of a gradual policy implementation to prevent abrupt supply chain disruptions. Furthermore, the study highlights the effectiveness of a multi-objective policy design in reducing economic losses (about 29%) and environmental risks (about 40%), substantially enhancing the efficiency of the environmental policy. The high-resolution simulations provide valuable insights for policy designers to formulate strategies with staggered implementation and multiple objectives to mitigate supply chain losses and environmental risks and ensure a sustainable future.

The lower Cambrian Qiongzhusi (Є1q) shale in the Sichuan Basin, formerly considered a source rock, recently achieved high gas production (7.388 × 105 m3·d−1) from well Z201 in the Deyang–Anyue rift trough (DART), marking an exploration breakthrough of the world’s oldest industrial shale gas reservoir. However, the shale gas enrichment mechanism within the DART is not fully understood. This study reviews the formation of the Qiongzhusi shale gas reservoirs within the DART by comparing them with cotemporaneous deposits outside the DART, and several findings are presented. The gas production interval was correlated with the main phase of the Cambrian explosion (lower Cambrian stage 3). In the early Cambrian ecosystem, dominant animals likely accelerated the settling rates of organic matter (OM) in the upper 1st member of Є1q (Є1q12) by feeding on small planktonic organisms and producing larger organic fragments and fecal pellets. High primary productivity and euxinic conditions contributed to OM enrichment in the lower 1st member of Є1q (Є1q11). Additionally, shale reservoirs inside the DART demonstrated better properties than those outside in terms of thickness, brittle minerals, gas content, and porosity. In particular, the abundant OM pores inside the DART facilitated shale gas enrichment, whereas the higher thermal maturity of the shales outside the DART possibly led to the graphitization and collapse of some OM pores. Meanwhile, the overpressure of high-production wells inside the DART generally reflects better shale gas preservation, benefiting from the shale’s self-sealing nature, “upper capping and lower plugging” configuration, and limited faults and microfractures. Considering these insights, we introduced a “ternary enrichment” model for the Qiongzhusi shale gas. Although the current high gas production of Z201 was found at the reservoir 3, two additional reservoirs were identified with significant potential, thus suggesting a “multilayer stereoscopic development” strategy in future shale gas exploration within the DART.

In response to the current challenges of low cutting efficiency and poor surface quality in processing single-crystal silicon, this article proposes the utilization of the micro-discharge abrasive cutting (MDAC) method for processing single-crystal silicon. A comprehensive comparison is conducted among the processing characteristics of the new cutting method and fixed abrasive wire sawing (FAWS) and wire electrical discharge machining (WEDM), including cutting efficiency, surface morphology, subsurface damage, surface roughness, wire saw wear, elemental spectrum analysis, and kerf width. Besides, two material removal modes at different feed rates are discussed. The results indicate that compared with WEDM, MDAC has the advantages of minimal subsurface damage, low surface roughness, low residual elements, and small kerf width. MDAC has higher cutting efficiency and shallower scratch depth than FAWS. However, compared with WEDM and FAWS, MDAC results in more significant wire saw wear and leaves a small amount of residual nickel on the silicon surface. In MDAC, the discharge occurs first. When the discharge energy within the pulse width is sufficient to remove the material within the current pulse cycle, the material is completely removed by the discharge action, the discharge products remain on the surface of the silicon wafer. When the discharge energy is insufficient to remove the material within the current pulse cycle, the silicon ingot is removed under the combined action of discharge and grinding, the diamond on wire saw surface will remove most of the discharge products.

In-situ synchrotron X-radiography studied the impact of TiCN nanoparticles (TiCNnp) on α-Al dendrite morphology and growth in Al–13Cu–7Si alloys. Comparative experiments were conducted without nanoparticles and with the addition of Al–5Ti–1B. Despite Al–5Ti–1B had almost no refining effect, 0.5% TiCNnp notably reduced α-Al grain size of Al–Cu–Si alloys, especially at higher cooling rates. When cooled at a rate of 0.2K/s, the dendrite tip radius of α-Al with the addition of TiCNnp (18.2 μm) was approximately twice as large as that without nanoparticles (9.8 μm). Concurrently, the primary dendrite growth rate of α-Al without nanoparticles exceeded that with TiCNnp by approximately 15 times. This discrepancy can be attributed to the coarser dendrite tip of α-Al induced by TiCNnp, which led to a greater solute accumulation in front of the tip. Furthermore, the area growth rate of both grain and solute suppressed nucleation zone (SSNZ) with addition of TiCNnp was only one-tenth of that observed with Al–5Ti–1B. Consequently, the incorporation of TiCNnp resulted in a significantly smaller nucleation-free zone, facilitating the activation of a greater number of nucleation sites within the melt. This study sheds light on the growth inhibition mechanism of TiCNnp in Al–Si alloys.

Our previous studies have reported that hydrogen sulfide (H2S) has ability to improve diabetes-associated cognitive dysfunction (DACD), but the exact mechanisms remain unknown. Recent research reveals that Warburg effect is associated with synaptic plasticity which plays a key role in cognition promotion. Herein, the present study was aimed to demonstrate whether hippocampal Warburg effect contributes to H2S-ameliorated DACD and further explore its potential mechanism. We found that H2S promoted the hippocampal Warburg effect and inhibited the OxPhos in the hippocampus of STZ-induced diabetic rats. It also improved the hippocampal synaptic plasticity in STZ-induced diabetic rats, as evidenced by the change of microstructures and the expression of different key-enzymes. Furthermore, inhibited hippocampal Warburg effect induced by DCA markedly abolished the improvement of H2S on synaptic plasticity in the hippocampus of STZ-induced diabetic rats. DCA blocked H2S-attenuated the cognitive dysfunction in STZ-induced diabetic rats, according to the Y-maze, Novel Objective Recognition, and Morris Water Maze tests. Collectively, these findings indicated that the hippocampal Warburg effect mediates H2S-ameliorated DACD by improving hippocampal synaptic plasticity.

Multi-component alloys have been confirmed to be excellent reinforcing phases in high-entropy alloy-based composite. However, achieving a balance between strength and ductility by controlling the reinforcement content remains a major challenge in the design of high-entropy alloy-based composites. In this study, CoCrFeMnNi HEA/NiCoFeAlTi HER high-entropy alloy composites were prepared using SLM technology. Interestingly, gas-atomized NiCoFeAlTi high-entropy intermetallic (HER) powder was selected as the reinforcing phase, and the CoCrFeMnNi HEA matrix was used for comparison. The influence of the reinforcement content on the composite was investigated, and high-performance HEA/HER composites were obtained, with the strengthening mechanism elucidated. The results showed that the composite with 1 wt% HER reinforcement exhibited the optimal performance, with hardness, yield strength, ultimate tensile strength, and ductility at room temperature being approximately 226.9 HV, 562 MPa, 683 MPa, and 16%, respectively. The excellent mechanical properties at both room and elevated temperatures are attributed to the synergistic effects of heterogeneous microstructure strengthening, grain refinement, and precipitation strengthening. This work provides a foundation for the development of high-entropy alloy composites reinforced by high-entropy intermetallics.

To improve the corrosion resistance and wide the application of Al alloy sheet in the engineering production, a corrosion potential gradient along the thickness of the Al alloy sheet was fabricated using the sprayed Zn layer. The process of arc spraying was employed to obtain the Zn coating with optimizing the parameters. Electrochemical testing was conducted on the surface of Al alloy sprayed with Zn layers at different depths. As the depth in the thickness direction increases, the content of Zn alloy elements gradually decreases and the potential gradually increases. This exhibits a gradual decrease in corrosion tendency. The results of electrochemical impedance spectra (EIS) revealed the existence of pitting corrosion on the surface of the Al alloy. This even extended to the underlying substrate material. In contrast, the Zn coating, when exposed to a corrosive environment, demonstrated the beneficial cathodic effect as a sacrificial anode and the protective function of a passivating film, thus mitigating corrosion. The gradual increase in charge transfer resistance in the impedance spectrum suggested that the corrosion resistance of the sample is increasingly improved. Therefore, it exhibited remarkable resistance to corrosion. Additionally, the SEM surface morphology and XRD pattern were utilized to further explain the corrosion mechanism of the arc-sprayed Zn coating. The Zn coating can provide sacrificial protection to the Al layer due to its higher negative potential and localized corrosion reactivity. This is attributed to the micro-galvanic couples formed between the Zn and Al layer, thus increasing the corrosion resistance of the sheets.

Objective: The aim of this study was to investigate the value of genetic testing using exome sequencing (ES) in oligohydramnios pregnancies with or without other structural abnormalities. Materials and methods: A total of 110 singleton pregnancies complicated by oligohydramnios were enrolled, including 52 of isolated oligohydramnios and 58 of non-isolated oligohydramnios. All fetal samples were first tested by quantitative fluorescent polymerase chain reaction (QF-PCR) and followed by chromosomal microarray analysis (CMA). Those with normal CMA were informed of the option of trio ES. Results: QF-PCR detected chromosomal abnormality in 4 cases (4/110, 3.6%), including 1 of XXY, 1 of XYY and 2 of triploidy. The remaining 106 cases were tested by CMA, with pathogenic copy number variations (CNVs) detected in 5 cases (5/106, 4.7%), and uniparental disomy (UPD) in 2 cases (2/106, 1.9%). As an option for cases with a normal CMA, ES was accepted by 12 non-isolated cases, and pathogenic or likely pathogenic variants were detected in 5, involving the following genes: PBX1, FREM2, PKHD1 and BBS2, with a 41.7% (5/12) diagnostic rate. Conclusion: We provided further evidence of using advanced genetic approaches for oligohydramnios pregnancy. Non-isolated oligohydramnios increases the risk of having monogenetic conditions.

Penile erection is unwanted during transurethral interventions as it may be associated with adverse events such as impaired access, prolonged operation time, abortion of the procedure, or a need for ancillary measures to reach penis flaccidity, such as intracorporeal injection of vasoactive drugs. In recent years, anesthesia with propofol has been favored over sevoflurane for environmental reasons. To the best of our knowledge, there have been no prospective randomized clinical trials evaluating the impact of general narcosis medications on the risk of such unwanted penile erections during transurethral surgery. To fill this gap, we have planned a prospective, double-blind (surgeon and patient), single-center, randomized controlled trial. The primary outcome is the occurrence of an intraoperative penile erection. The secondary outcomes are related to the impact of the primary outcome on the surgery, such as changes in operative strategy or operation duration, abortion of the procedure, and adverse events. The plan is to randomize 200 patients undergoing transurethral surgery to receive general anesthesia with either propofol or sevoflurane. The inclusion criteria are men aged

Introduction: Ginsenosides (GS) derived from Panax ginseng can regulate protein acetylation to promote mitochondrial function for protecting cardiomyocytes. However, the potential mechanisms of GS for regulating acetylation modification are not yet clear. Objectives: This study aimed to explore the potential mechanisms of GS in regulating protein acetylation and identify ginsenoside monomer for fighting myocardial ischemia-related diseases. Methods: The 4D-lable free acetylomic analysis was employed to gain the acetylated proteins regulated by GS pretreatment. The co-immunoprecipitation assay, immunofluorescent staining, and mitochondrial respiration measurement were performed to detect the effect of GS or ginsenoside monomer on acetylated protein level and mitochondrial function. RNA sequencing, site-specific mutation, and shRNA interference were used to explore the downstream targets of acetylation modificationby GS. Cellular thermal shift assay and surface plasmon resonance were used for identifying the binding of ginsenoside with target protein. Results: In the cardiomyocytes of normal, oxygen glucose deprivation and/or reperfusion conditions, the acetylomic analysis identified that the acetylated levels of spliceosome proteins were inhibited by GS pretreatment and SF3A2 acetylation at lysine 10 (K10) was significantly decreased as a potential target of GS. Ginsenoside Rb2 was identified as one of the active ginsenoside monomers for reducing the acetylation of SF3A2 (K10), which enhanced mitochondrial respiration against myocardial ischemic injury in in vivo and in vitro experiments. RNA-seq analysis showed that ginsenoside Rb2 promoted alternative splicing of mitochondrial function-related genes and the level of fascin actin-bundling protein 1 (Fscn1) was obviously upregulated, which was dependent on SF3A2 acetylation. Critically, thermodynamic, kinetic and enzymatic experiments demonstrated that ginsenoside Rb2 directly interacted with p300 for inhibiting its activity. Conclusion: These findings provide a novel mechanism underlying cardiomyocyte protection of ginsenoside Rb2 by inhibiting p300-mediated SF3A2 acteylation for promoting Fscn1 expression, which might be a promising approach for the prevention and treatment of myocardial ischemic diseases.

Introduction: Ovarian cancer (OC) is known for its high mortality rate. Although sodium citrate has anti-tumor effects in various cancers, its effect and mechanism in OC remain unclear. Objectives: To analyze the inhibitory effect of sodium citrate on ovarian cancer cells and the underlying mechanism. Methods: Cell apoptosis was examined by TUNEL staining, flow cytometry, and ferroptosis was examined intracellular Fe2+, MDA, LPO assays, respectively. Cell metabolism was examined by OCR and ECAR measurements. Immunoblotting and immunoprecipitation were used to elucidate the mechanism. Results: This study suggested that sodium citrate not only promoted ovarian cancer cell apoptosis but also triggered ferroptosis, manifested as elevated levels of Fe2+, LPO, MDA and lipid ROS production. On one hand, sodium citrate treatment led to a decrease of Ca2+ content in the cytosol by chelating Ca2+, which further inhibited the Ca2+/CAMKK2/AKT/mTOR signaling, thereby suppressing HIF1α-dependent glycolysis pathway and inducing cell apoptosis. On the other hand, the chelation of Ca2+ by sodium citrate resulted in inactivation of CAMKK2 and AMPK, leading to increase of NCOA4-mediated ferritinophagy, causing increased intracellular Fe2+ levels. More importantly, the inhibition of Ca2+/CAMKK2/AMPK signaling pathway reduced the activity of the MCU and Ca2+ concentration within the mitochondria, resulting in an increase in mitochondrial ROS. Additionally, metabolomic analysis indicated that sodium citrate treatment significantly increased de novo lipid synthesis. Altogether, these factors contributed to ferroptosis. As expected, Ca2+ supplementation successfully reversed the cell death and decreased tumor growth induced by sodium citrate. Inspiringly, it was found that coadministration of sodium citrate increased the sensitivity of OC cells to chemo-drugs. Conclusion: These results revealed that the sodium citrate exerted its anti-cancer activity by inhibiting Ca2+/CAMKK2-dependent cell apoptosis and ferroptosis. Sodium citrate will hopefully serve as a prospective compound for OC treatment and for improving the efficacy of chemo-drugs.

Laser powder bed fusion (LPBF) is the most widely used metal additive manufacturing technology, but it still faces challenges in manufacturing efficiency. To address the issue, high-power LPBF (HP-LPBF) which employs kilowatt-level lasers emerges in recent years. In this study, a 4 kW Flat-top laser was used for the HP-LPBF of Ti6Al4V alloy. The samples in as-built state and annealed states (750 °C/2h, 850 °C/2h, 950 °C/2h, 1050 °C/2h) were investigated in terms of defects, microstructure, and mechanical properties. Results show that keyhole mode melting is avoided by adopting the Flat-top laser, so the relative density of as-built Ti6Al4V is generally positively correlated with the employed laser energy density. The minimum laser energy density to obtain the high-density (≥99.9%) sample is 50.0 J/mm3, and the highest build rate is 288 cm3/h. The microstructure in as-built state exhibits a unique alternating pattern of ''bright bands/dark bands''. The dark bands consist of needle-shaped α′ martensite, while the bright bands consist of needle-shaped α+β, which results from the decomposition of α′ under the in-situ annealing effect of the 4 kW Flat-top laser. After annealing at 750 °C, most of the residual α′ decomposes into needle-shaped α+β. As the annealing temperature increases from 750 °C to 1050 °C, the microstructure undergoes an evolution from needle-shaped α+β to lamellar α+β then to lamellar α+β with some globular α and finally to duplex α+β. An optimum strength-ductility balance is achieved after annealing at 850 °C, both the tensile strength and the elongation exceed the standard values of Ti6Al4V forgings.

Joint replacement surgery, essential for managing joint diseases, requires improvements in tribocorrosion performance to ensure surgical success and longevity of joint implants. Transition-metal light-element (TMLE) compound coatings, known for their high hardness and chemical stability, have been extensively researched and applied for surface protection of joint implants. However, these coatings typically lack a lubrication phase, leading to high friction coefficients and severe corrosion wear, which makes long-term effective protection challenging. A promising approach is to utilize the natural lubricating proteins present in body fluids, which are continuously available and can thus address long-term service issues of TMLE coatings. In this work, we utilized micro-arc oxidation (MAO) technology to develop an underlying morphology, then conformally deposited a TiB2 layer, resulting in a cratered dual-layer TiB2/MAO coating. This unique cratered dual-layer structure not only preserves the high hardness and wear resistance of TiB2 but also aims to (1) absorb wear particles to prevent abrasive wear and (2) increase surface energy to optimize protein lubrication capacity. Consequently, the TiB2/MAO coating exhibits low friction coefficients and wear rates in protein-containing simulated body fluids. Furthermore, the dual-layer TiB2/MAO coating demonstrates excellent corrosion resistance and biocompatibility. This dual-layer coating design synergistically combines the superior intrinsic properties of material with unique structural construction, while also harnessing continuously available external proteins as lubricants to further optimize performance, thereby introducing an advanced strategy for developing protective coatings for implant materials.

Creep, as a long-term deformation characteristic of shotcrete, significantly influences the load-bearing performance and durability of tunnel support structures. This study conducted creep tests on shotcrete under varying stress levels. The results reveal that shotcrete exhibits linear creep response within the stress range of 30%–40%, while the critical stress range for nonlinear creep response occurs between 40% and 50%. Employing SEM-EDS and XRD analysis methods, the impact of accelerator on the microstructure evolution and creep mechanism of shotcrete is explored. The accelerator accelerates the hydration of C3S, promoting the generation of AFt and C–S–H gel, leading to rapid solidification of the matrix and enhanced early strength. With the consumption of SO42− ions, AFt gradually transforms into AFm, resulting in increased matrix porosity. This phenomenon contributes to the reduced later-stage strength and substantial creep deformation of shotcrete. Based on experimental outcomes, this study evaluates the applicability of existing creep calculation models to shotcrete.

Osteoporosis is a chronic metabolic disease that increases bone fragility and, leads to severe osteoporotic fractures. In recent years, the use of high-throughput omics to explore physiological and pathological biomarkers related to bone metabolism has gained popularity. In this review, we first briefly review the technical approaches of proteomics. Additionally, we summarize the relevant literature in the last decade to provide a comprehensive overview of advances in human proteomics related to osteoporosis. We describe the specific roles of various proteins related to human bone metabolism, highlighting their potential as biomarkers for risk assessment, early diagnosis and disease course monitoring in osteoporosis. Finally, we outline the main challenges currently faced by human proteomics in the field of osteoporosis and offer suggestions to address these challenges, to inspire the search for novel osteoporosis biomarkers and a foundation for their clinical translation. In conclusion, proteomics is a powerful tool for discovering osteoporosis-related biomarkers, which can not only provide risk assessment, early diagnosis and disease course monitoring, but also reveal the underlying mechanisms of disease and provide key information for personalized treatment. The translational potential of this article: This review provides an insightful summary of recent human-based studies on osteoporosis-associated proteomics, which can aid the search for novel osteoporosis biomarkers based on human proteomics and the clinical translation of research results.

The die-casting process of ADC12 aluminum alloy right crankcase cover was simulated based on AnyCasting software, and the influence of pouring temperature, initial mold temperature and injection speed on the filling and solidification process of ADC12 right crankcase cover casting was explored by orthogonal experiment method. The optimal process parameters were obtained through optimization, and the die-casting mold was designed. The program was verified in production. The results show that the porosity and shrinkage of the right crankcase cover are mainly concentrated in the thick wall part. The sequence of process parameters that affect the residual melt modulus is pouring temperature, initial mold temperature, and injection speed; The best combination of process parameters: pouring temperature is ∼680 °C, initial mold temperature is ∼200 °C, injection speed is ∼5 m/s. By analyzing the filling process and temperature field simulation results, the casting structure, mold structure and cooling system were optimized, and the process plan was improved. The production verification was carried out according to the optimized process plan. The casting quality is good and has no obvious defects, which meets the actual production needs.

Pherosphaera fitzgeraldii, the Dwarf Mountain Pine, is a critically endangered conifer restricted to cliff ledges within waterfall spray zones in the Greater Blue Mountains Area of New South Wales, Australia. This species is under threat from pollution, invasive weeds, and limited recruitment, which are contributing to its declining population. Using a comprehensive conservation genomic approach, we assessed the population health of P. fitzgeraldii and developed strategic recommendations for its management.Genomic analysis of P. fitzgeraldii revealed the presence of two distinct genetic groups despite the limited distribution of the species. This genetic structure aligns with prevailing wind currents, indicating potential restrictions to pollen or seed exchange between subpopulations. Furthermore, limited gene flow was observed even among nearby subpopulations, emphasizing the risk of increased genetic differentiation due to ongoing isolation. Clonality is widespread in some subpopulations, and all subpopulations displayed signs of inbreeding and genetic depletion despite subdioecy, indicative of historical constraints on gene flow and small population sizes.We offer genomic-based recommendations for prioritizing conservation sites, enhancing genetic diversity in ex situ collections, and guiding future management. Further studies to uncover the sex determination mechanism of P. fitzgeraldii could help maintain balanced sex ratios in ex situ collections and support future genetic rescue efforts. This study underscores the value of genomics in informing protection and recovery of unique threatened species.

Currently, the rapid development of the industrial Internet has led to the creation of a massive number of intelligent agents that are widely and distributively applied in various edge scenarios. The work conditions in these edge scenarios are complex, uncertain, and random. Traditional manual updates or human judgments are used for task decision-making in large-scale distributive intelligent agent edge work scenarios, which lack dynamic perception and autonomous recognition capabilities for edge work conditions. This inevitably leads to low decision-making accuracy, poor reliability, and ultimately, task failure. To address this issue, this study proposes an adaptive task identification strategy based on cloud-edge collaboration. This method utilizes a cloud-edge collaborative industrial intelligent application architecture to achieve cloud-based training and encapsulation of the task model, with online calling at the edge-end. Then, edge-end intelligent agents identify edge work conditions through multi-source data fusion, enabling accurate task decision-making. Finally, the edge-end requests the cloud for task model matching. The effectiveness of the proposed method is validated in an industrial safety situation virtual detection system.