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Abstract Hydrogels are extensively explored as biomaterials for tissue scaffolds, and their controlled fabrication has been the subject of wide investigation. However, the tedious mechanical property adjusting process through formula control hindered their application for diverse tissue scaffolds. To overcome this limitation, we proposed a two-step process to realize simple adjustment of mechanical modulus over a broad range, by combining digital light processing (DLP) and post-processing steps. UV-curable hydrogels (polyacrylamide-alginate) are 3D printed via DLP, with the ability to create complex 3D patterns. Subsequent post-processing with Fe3+ ions bath induces secondary crosslinking of hydrogel scaffolds, tuning the modulus as required through soaking in solutions with different Fe3+ concentrations. This innovative two-step process offers high-precision (10 μm) and broad modulus adjusting capability (15.8–345 kPa), covering a broad range of tissues in the human body. As a practical demonstration, hydrogel scaffolds with tissue-mimicking patterns were printed for cultivating cardiac tissue and vascular scaffolds, which can effectively support tissue growth and induce tissue morphologies.

Hemoglobin Constant Spring (Hb CS) is the most common non-deletional and clinically significant α-thalassemic mutation, and it is caused by an anti-termination mutation at the α2-globin gene stop codon. We developed a prime editing strategy for the creation and correction of Hb CS. We showed that prime editing could efficiently introduce Hb CS mutations in both human erythroblast cell lines (an average frequency of 32%) and primary hematopoietic stem and progenitor cells (HSPCs) from healthy donors (an average frequency of 27%). By targeting the established Hb CS homozygous erythroblasts, we achieved an average frequency of 32% in situ correction without selection. Notably, prime editing corrected the Hb CS mutation to wild type at an average frequency of 21% in HSPCs from three patients with hemoglobin H Constant Spring (HCS). Erythrocytes that differentiated from prime-edited erythroblasts or HSPCs exhibited a significant reduction in the amount of αCS-globin chains. Insertions and deletions on HBA2 locus and Cas9-dependent DNA off-target editing were detected with relatively low frequency after prime editing. Our findings showed that prime editing can successfully correct Hb CS in erythroblasts and patient HSPCs, which provides proof of principle for its therapeutic potential in HCS.

Postoperative dry eye is a common complication following femtosecond laser-assisted cataract surgery, and the patient interface (PI) used during the procedure may play a significant role in its occurrence. This study, utilizing a meticulous scientific search strategy, identified seven relevant articles through literature search engines. Most of these studies employed contact-type PI during surgeries, while one researcher used a non-contact PI. All studies assessed dry eye symptoms at various postoperative periods using metrics such as the Ocular Surface Disease Index (OSDI), tear Break-Up Time (BUT), Schirmer I test (SIt), and so on. However, the findings were inconsistent. On this basis, this comprehensive review delves into the potential impact of different patient interfaces on corneal nerve damage and conjunctival goblet cell injury, possibly contributing to an increased risk of postoperative dry eye. The review also explores various preventive and solution strategies, including improving PI design, reducing surgical time, and utilizing tear protective agents. The findings highlight the importance of optimizing the PI to minimize the risk of postoperative dry eye in femtosecond laser-assisted cataract surgery.

Summary: Background: Large language models (LLMs) have shown promising performance in various healthcare domains, but their effectiveness in identifying specific clinical conditions in real medical records is less explored. This study evaluates LLMs for detecting signs of cognitive decline in real electronic health record (EHR) clinical notes, comparing their error profiles with traditional models. The insights gained will inform strategies for performance enhancement. Methods: This study, conducted at Mass General Brigham in Boston, MA, analysed clinical notes from the four years prior to a 2019 diagnosis of mild cognitive impairment in patients aged 50 and older. We developed prompts for two LLMs, Llama 2 and GPT-4, on Health Insurance Portability and Accountability Act (HIPAA)-compliant cloud-computing platforms using multiple approaches (e.g., hard prompting, retrieval augmented generation, and error analysis-based instructions) to select the optimal LLM-based method. Baseline models included a hierarchical attention-based neural network and XGBoost. Subsequently, we constructed an ensemble of the three models using a majority vote approach. Confusion-matrix-based scores were used for model evaluation. Findings: We used a randomly annotated sample of 4949 note sections from 1969 patients (women: 1046 [53.1%]; age: mean, 76.0 [SD, 13.3] years), filtered with keywords related to cognitive functions, for model development. For testing, a random annotated sample of 1996 note sections from 1161 patients (women: 619 [53.3%]; age: mean, 76.5 [SD, 10.2] years) without keyword filtering was utilised. GPT-4 demonstrated superior accuracy and efficiency compared to Llama 2, but did not outperform traditional models. The ensemble model outperformed the individual models in terms of all evaluation metrics with statistical significance (p

ObjectivesThis study aimed to investigate the association between the weight-adjusted waist index (WWI) and the prevalence of hypertension in U.S. adults.MethodsData were sourced from the National Health and Nutrition Examination Survey (NHANES) spanning 2005–2018. In our cross-sectional study, we focused on the non-institutional U.S. population over the age of 18 from various communities in the United States. WWI is derived by dividing waist circumference by the square root of body weight. The definition of hypertension was based on self-reported history of hypertension, antihypertensive drug use, and blood pressure measurements. Participants without complete information on WWI and hypertension were excluded. The independent relationship and consistency between WWI and hypertension were assessed through weighted multivariate regression. The Pearson correlation test was used to detect the association between WWI and BMI. Subgroup analyses were used to verify the stability of the relationship between WWI and the prevalence of hypertension, and interaction tests were also conducted by gender, age, smoking, and triglycerides.ResultsAmong the 37,299 participants included, the hypertension prevalence was 33.9%. After adjusting for confounding variables, WWI demonstrated a significant association with hypertension. Individuals in the top quarter of WWI had a 2.27fold higher chance of hypertension prevalence compared with the bottom quarter (OR = 2.27, 95% CI 1.97–2.61; P

Abstract BackgroundSystematic literature review (SLR), a robust method to identify and summarize evidence from published sources, is considered to be a complex, time-consuming, labor-intensive, and expensive task. ObjectiveThis study aimed to present a solution based on natural language processing (NLP) that accelerates and streamlines the SLR process for observational studies using real-world data. MethodsWe followed an agile software development and iterative software engineering methodology to build a customized intelligent end-to-end living NLP-assisted solution for observational SLR tasks. Multiple machine learning–based NLP algorithms were adopted to automate article screening and data element extraction processes. The NLP prediction results can be further reviewed and verified by domain experts, following the human-in-the-loop design. The system integrates explainable articificial intelligence to provide evidence for NLP algorithms and add transparency to extracted literature data elements. The system was developed based on 3 existing SLR projects of observational studies, including the epidemiology studies of human papillomavirus–associated diseases, the disease burden of pneumococcal diseases, and cost-effectiveness studies on pneumococcal vaccines. ResultsOur Intelligent SLR Platform covers major SLR steps, including study protocol setting, literature retrieval, abstract screening, full-text screening, data element extraction from full-text articles, results summary, and data visualization. The NLP algorithms achieved accuracy scores of 0.86-0.90 on article screening tasks (framed as text classification tasks) and macroaverage F1 scores of 0.57-0.89 on data element extraction tasks (framed as named entity recognition tasks). ConclusionsCutting-edge NLP algorithms expedite SLR for observational studies, thus allowing scientists to have more time to focus on the quality of data and the synthesis of evidence in observational studies. Aligning the living SLR concept, the system has the potential to update literature data and enable scientists to easily stay current with the literature related to observational studies prospectively and continuously.

Background: The gut microbiota thrives in a complex ecological environment and its dynamic balance is closely related to host health. Recent studies have shown that the occurrence of various diseases including prostate inflammation is related to the dysregulation of the gut microbiome. Objective: This review focus on the mechanisms by which the gut microbiota induces prostate inflammation and benign prostatic hyperplasia and its therapeutic implications. Materials and methods: Publications related to gut microbiota, prostate inflammation, and benign prostatic hyperplasia (BPH) until April 2023 were systematically reviewed. The research questions were formulated using the Problem, Intervention, Comparison/Control, and Outcome (PICO) frameworks. Results: Fifteen articles covering the relationship between the gut microbiota and prostate inflammation/BPH, the mechanisms by which the gut microbiota influences prostate inflammation and BPH, and potential therapeutic approaches targeting the gut microbiota for these conditions were included. Conclusion: Short-chain fatty acids (SCFAs), which are metabolites of the intestinal microbiota, protect the integrity of the intestinal barrier, regulate immunity, and inhibit inflammation. However, dysregulation of the gut microbiota significantly reduces the SCFA content in feces and impairs the integrity of the gut barrier, leading to the translocation of bacteria and bacterial components such as lipopolysaccharide, mediating the development of prostate inflammation through microbe-associated molecular patterns (MAMPs).

Abstract Autonomous vehicles navigating urban roads require technology that combines low latency with high computing power. The limited resources of the vehicle itself compel it to offload task requirements to edge server (ES) for processing assistance. However, as the number of vehicles continues to increase, how edge servers reasonably allocate limited resources to autonomous vehicles becomes critical to the success of urban intelligent transportation services. This paper establishes an urban road scenario with multiple autonomous vehicles and an edge computing server and considers two main driving behaviour transition resource requests, namely car‐following behaviour requests and lane‐changing behaviour requests. Simultaneously, acknowledging that vehicles may encounter unforeseen traffic hazards when switching driving behaviours, a safety redundancy setting strategy is employed to allocate additional resources to the vehicle to ensure safety and model the vehicle resource allocation problem in the autonomous driving system. Double‐deep Q‐network (DDQN) is then used to solve this model and maximize the total system utility by comprehensively considering resource costs, system revenue, and autonomous vehicle safety. Finally, results from the simulation experiment indicate that the proposed dynamic resource allocation scheme, based on deep reinforcement learning for autonomous vehicles under edge computing, not only greatly improves the system's benefits and reduces processing delays compared to traditional greedy algorithms and value iteration, but also effectively ensures security.

Abstract Objective Systematic literature reviews (SLRs) are critical for life-science research. However, the manual selection and retrieval of relevant publications can be a time-consuming process. This study aims to (1) develop two disease-specific annotated corpora, one for human papillomavirus (HPV) associated diseases and the other for pneumococcal-associated pediatric diseases (PAPD), and (2) optimize machine- and deep-learning models to facilitate automation of the SLR abstract screening. Methods This study constructed two disease-specific SLR screening corpora for HPV and PAPD, which contained citation metadata and corresponding abstracts. Performance was evaluated using precision, recall, accuracy, and F1-score of multiple combinations of machine- and deep-learning algorithms and features such as keywords and MeSH terms. Results and conclusions The HPV corpus contained 1697 entries, with 538 relevant and 1159 irrelevant articles. The PAPD corpus included 2865 entries, with 711 relevant and 2154 irrelevant articles. Adding additional features beyond title and abstract improved the performance (measured in Accuracy) of machine learning models by 3% for HPV corpus and 2% for PAPD corpus. Transformer-based deep learning models that consistently outperformed conventional machine learning algorithms, highlighting the strength of domain-specific pre-trained language models for SLR abstract screening. This study provides a foundation for the development of more intelligent SLR systems.

In order to develop functional rice flour products with anti-digestive and antioxidant activities, the effects of adding Wuyi rock tea (WRT) on the quality, in vitro digestive characteristics and antioxidant activity of rice noodles were studied. The texture and sensory quality of rice noodles were determined by texture analyzer and sensory evaluation method, respectively. The flavor components were characterized by GC-MS, and the antioxidant activity was assessed by FRAP, DPPH and ABTS+ assays. The digestive characteristics of rice noodles were detected by the in vitro simulated digestion method. The results showed that compared to the control rice noodles, the breaking rate of rice noodles added with 2.9%~7.0%. WRT was not significantly changed (P>0.05), while the breaking rate of rice noodles added with 8.3% WRT was significantly increased (P

Abstract The IPv6 extension header mechanism, a new feature of the IPv6 protocol, enhances flexibility and scalability but introduces numerous security threats like firewall evasion and covert channels. Existing threat detection methods face limitations in detection types, universality, and speed. Hence, an adaptive detection model for IPv6 extension header threats (ADM-DDA6) is proposed. Firstly, standard rule sets are designed for common IPv6 extension headers, successfully detecting 70 types of threats from THC-IPv6 and ExtHdr tools using only 20 rules. Secondly, by parsing IPv6 extension headers, matching rules, establishing transition relationships, and deciding packet threat status based on final states (Normal or Abnormal), complex threats like header disorder and header repetition can be detected. Finally, an adaptive rule matching method is introduced, which dynamically selects rule sets based on IPv6 extension header types, effectively reducing rule matching time. Experimental results show that under different threat magnitudes, ADM-DDA6 is 32% faster than Suricata v6.0.12 and 21.2% faster than Snort v3.1.61.0 in detection speed. Additionally, as the number of threats increases, on commodity hardware, ADM-DDA6 incurs only a 0.7% increase in CPU overhead with no significant memory consumption increase, maintains maximum throughput, and exhibits minor performance changes under low and moderate network load conditions.

Abstract Hypomyelinating leukodystrophy (HLD) is a rare genetic heterogeneous disease that can affect myelin development in the central nervous system. This study aims to analyze the clinical phenotype and genetic function of a family with HLD-7 caused by POLR3A mutation. The proband (IV6) in this family mainly showed progressive cognitive decline, dentin dysplasia, and hypogonadotropic hypogonadism. Her three old brothers (IV1, IV2, and IV4) also had different degrees of ataxia, dystonia, or dysarthria besides the aforementioned manifestations. Their brain magnetic resonance imaging showed bilateral periventricular white matter atrophy, brain atrophy, and corpus callosum atrophy and thinning. The proband and her two living brothers (IV2 and IV4) were detected to carry a homozygous mutation of the POLR3A (NM_007055.4) gene c. 2300G > T (p.Cys767Phe), and her consanguineous married parents (III1 and III2) were p.Cys767Phe heterozygous carriers. In the constructed POLR3A wild-type and p.Cys767Phe mutant cells, it was seen that overexpression of wild-type POLR3A protein significantly enhanced Pol III transcription of 5S rRNA and tRNA Leu-CAA. However, although the mutant POLR3A protein overexpression was increased compared to the wild-type protein overexpression, it did not show the expected further enhancement of Pol III function. On the contrary, Pol III transcription function was frustrated (POLR3A, BC200, and tRNA Leu-CAA expression decreased), and MBP and 18S rRNA expressions were decreased. This study indicates that the POLR3A p.Cys767Phe variant caused increased expression of mutated POLR3A protein and abnormal expression of Pol III transcripts, and the mutant POLR3A protein function was abnormal.

Energy drives the development of human civilization, and hydrogen energy is an inevitable choice under the goal of “global energy transition”. As hydrogen technology continues to advance, solid-state hydrogen storage materials have garnered significant attention as an efficient solution for hydrogen energy storage. However, existing research methods, such as experimental preparation and theoretical calculations, are inefficient and costly. Here, we summarize the latest advancements of high-throughput screening (HTS) and machine learning (ML) solid-state hydrogen storage materials. We elaborate on the advantages of HTS and ML in rapid material screening, performance assessment and prediction, and so on. We place particular emphasis on the exploration and analysis of research progress involving the application of HTS and ML in various types of solid-state hydrogen storage materials. Additionally, we discuss the advantages of integrating HTS and ML, emphasizing the application of this comprehensive strategy in solid-state hydrogen storage. In the realm of hydrogen storage, artificial intelligence plays a dual role. It not only enhances the efficiency of material screening but also offers novel research tools for future material design and development. This will aid in the discovery of new-type high-performance solid-state hydrogen storage materials and facilitate their rapid commercialization and practical application.

BackgroundGlaucoma, a leading cause of global blindness, is characterized by optic nerve damage and visual field loss. Previous studies have suggested a potential association between glaucoma and anxiety disorders. However, the causal relationship between these two conditions remains unclear.MethodsIn this study, we conducted a Mendelian Randomization analysis to investigate the causal relationship between glaucoma and anxiety disorders. We sourced Genome-Wide Association Study (GWAS) datasets for glaucoma and anxiety with the largest sample sizes from the Integrative Epidemiology Unit OpenGWAS (IEU OpenGWAS) project website. Instrumental variables were selected based on specific criteria, and statistical analyses were performed using the R programming language.ResultsAfter filtering and merging the datasets, a total of 60 Single Nucleotide Polymorphisms (SNPs) were obtained for analysis. Regression models were applied to assess the causal relationship between glaucoma and anxiety disorders. The results from all four methods indicated that glaucoma does not cause anxiety disorders (p > 0.05).ConclusionThrough rigorous Mendelian Randomization analysis, our findings indicate that glaucoma is not a causative factor for anxiety, with minimal influence from confounding factors in this study. These findings enhance our understanding of the relationship between glaucoma and anxiety.

Light-flavor Baijiu (LFB) fermentation is a representative spontaneous mixed-culture solid-state fermentation process in which sorghum is used as the raw material. Raw materials and microorganisms are crucial to the flavor formation and quality of LFB. However, the microbial and physicochemical dynamics of different sorghum varieties during LFB fermentation, as well as their impact on flavor compounds are still largely unknown. Herein, PacBio single-molecule real-time (SMRT) sequencing and headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME-GC–MS) were applied to investigate microbial community succession and volatile flavor formation in glutinous/non-glutinous sorghum-based fermented grains during LFB fermentation. Fermented grains made of glutinous sorghum Liangnuo No. 1 (GLN) had higher bacterial α-diversity and lower fungal α-diversity than those with fermented grains prepared with non-glutinous red sorghum (NRS) (p

Abstract Purpose The aim of this study was to assess the potential application of a radiomics features‐based nomogram for predicting therapeutic responses to neoadjuvant chemohormonal therapy (NCHT) in patients with high‐risk non‐metastatic prostate cancer (PCa). Methods Clinicopathologic information was retrospectively collected from 162 patients with high‐risk non‐metastatic PCa receiving NCHT and radical prostatectomy at our center. The postoperative pathological findings were used as the gold standard for evaluating the efficacy of NCHT. The least absolute shrinkage and selection operator (LASSO) was conducted to develop radiomics signature. Multivariate logistic regression analyses were conducted to identify the predictors of a positive pathological response to NCHT, and a nomogram was constructed based on these predictors. Results Sixty‐three patients (38.89%) experienced positive pathological response to NCHT. Receiver operating characteristic analyses showed that the area under the curve (AUC) of periprostatic fat (PPF) radiomics signature was 0.835 (95% CI, 0.754–0.898), while the AUC of intratumoral radiomics signature was 0.822 (95% CI, 0.739–0.888). Multivariate logistic regression analysis revealed that PSA level, PPF radiomics signature and intratumoral radiomics signature were independent predictors of positive pathological response. A nomogram based on these three predictors was constructed. The AUC was 0.908 (95% CI, 0.839–0.954). The Hosmer–Lemeshow goodness‐of‐fit test showed that the nomogram was well calibrated. Decision curve analysis revealed the favorable clinical practicability of the nomogram. The nomogram was successfully validated in the validation cohort. Kaplan–Meier analyses showed that nomogram and positive pathological response were significantly related with survival of PCa. Conclusion The radiomics–clinical nomogram based on mpMRI radiomics features exhibited superior predictive ability for positive pathological response to NCHT in high‐risk non‐metastatic PCa.

“Green-covering and red-heart” Guanyin Tuqu (GRTQ), as a type of special fermentation starter, is characterized by the “green-covering” formed on the surface of Guanyin Tuqu (SQ) and the “red-heart” in the center of Guanyin Tuqu (CQ). However, the mechanisms that promote temporal succession in the GRTQ microbial ecology and the formation of “green-covering and red-heart” characteristics remain unclear. Herein, we correlated the temporal profiles of microbial community succession with the main environmental variables (temperature, moisture, and acidity) and spatial position (center and surface) in GRTQ throughout fermentation. According to the results of high-throughput sequencing and culture-dependent methods, the microbial communities in the CQ and SQ demonstrated functional complementarity. For instance, the bacterial richness index of the CQ was greater than that of SQ, and the fungal richness index of the SQ was greater than that of CQ at the later stage of fermentation. Furthermore, Saccharomycopsis, Saccharomyces, Aspergillus, Monascus, Lactobacillus, Bacillus, Rhodanobacter, and Chitinophaga were identified as the dominant microorganisms in the center, while the surface was represented by Saccharomycopsis, Aspergillus, Monascus, Lactobacillus, Acetobacter, and Weissella. By revealing the physiological characteristics of core microorganisms at different spatial positions of GRTQ, such as Aspergillus clavatus and Monascus purpureus, as well as their interactions with environmental factors, we elucidated the color formation mechanism behind the phenomenon of “green” outside and “red” inside. This study provides fundamental information support for optimizing the production process of GRTQ.

BackgroundPreterm birth has been associated with an increased risk of myopia, but the causal relationship between these two factors remains unclear. Traditional epidemiological studies are limited by confounding factors and reverse causality. Mendelian randomization (MR) analysis, utilizing genetic variants as instrumental variables, provides a robust approach to investigate causal relationships. In this study, we aimed to explore the potential causal link between preterm birth and myopia risk using a two-sample MR analysis strategy.MethodsWe conducted a Mendelian randomization study to investigate the causal relationship between preterm birth and myopia risk. Genetic variants (single nucleotide polymorphisms, SNPs) were used as instrumental variables, and summary data from genome-wide association studies (GWAS) were utilized. Four regression models, including MR-Egger regression, weighted median regression, inverse variance weighted regression, and Weighted mode regression, were employed to validate the causal relationship. Sensitivity analysis was performed using the leave-one-out method. At the same time, the funnel diagram and MR-Egger test were used to judge the stability of the research results.ResultsThe MR analysis revealed a significant causal effect of preterm birth on myopia risk. Both the inverse variance weighted regression and weighted median regression models showed a p-value less than 0.05, indicating a robust association. The risk of myopia increased by approximately 30% for everyone standard deviation increase in preterm birth. Sensitivity analysis, funnel plot and MR-Egger test all confirm the stability of the research results.ConclusionOur findings provide evidence supporting a causal relationship between preterm birth and myopia risk. Preterm infants are at a higher risk of developing myopia, and this association is not likely to be influenced by confounding factors or reverse causality. The SNP loci rs6699397, rs10871582, and rs2570497 should be closely monitored as they may lead to abnormal concentrations of intraocular cytokines, particularly vascular endothelial growth factor, potentially elucidating one of the pathogenic mechanisms contributing to the higher incidence of myopia in preterm infants. However the complex interconnections involved extend beyond these factors alone.

Matrine (MT) and Oxymatrine (OMT) are two natural alkaloids derived from plants. These bioactive compounds are notable for their diverse pharmacological effects and have been extensively studied and recognized in the treatment of cardiovascular diseases in recent years. The cardioprotective effects of MT and OMT involve multiple aspects, primarily including antioxidative stress, anti-inflammatory actions, anti-atherosclerosis, restoration of vascular function, and inhibition of cardiac remodeling and failure. Clinical pharmacology research has identified numerous novel molecular mechanisms of OMT and MT, such as JAK/STAT, Nrf2/HO-1, PI3 K/AKT, TGF-β1/Smad, and Notch pathways, providing new evidence supporting their promising therapeutic potential against cardiovascular diseases. Thus, this review aims to investigate the potential applications of MT and OMT in treating cardiovascular diseases, encompassing their mechanisms, efficacy, and safety, confirming their promise as lead compounds in anti-cardiovascular disease drug development.

Rutting is a prevalent issue in the Gussasphalt (GA) mixture layer of steel bridge deck pavements. This study aims to investigate the correlation between the rheology of GA mastic and the high-temperature performance of the GA mixture. To achieve this objective, GA mastic underwent temperature and frequency sweep tests, along with multiple stress creep and recovery tests employing a dynamic shear rheometer. Additionally, indentation tests, uniaxial penetration tests, and Lueer fluidity tests were conducted on the GA mixture. The Grey Relational Analysis method was employed to evaluate the relationship between asphalt mastic rheology and the high-temperature deformation resistance of the GA mixture. The findings reveal that the addition of mineral filler enhances the deformation resistance of both GA mastic and the mixture. The percent difference in non-recoverable creep compliance (Jnr-diff) was minimized when the weight ratio of filler to asphalt binder (F/B) was 2.5. Furthermore, increasing the F/B ratio from 2.0 to 3.5 resulted in a more than twofold increase in the GA mixture’s shear strength. Asphalt type emerged as a significant factor affecting the indentation parameter of the GA mixture, with an F-value reaching 8.82 based on ANOVA analysis. The rheological properties of GA mastic exhibited a significant correlation with the high-temperature performance of the mixture. The highest Grey Relational Grade of 0.87 was observed between the non-recoverable creep compliance at a 3.2 kPa stress level (Jnr3.2) and indentation. In future research, greater emphasis can be placed on exploring the micromechanical properties of the GA mastic-aggregate interface.

Abstract Childhood obesity not only has a negative impact on a child's health but is also a significant risk factor for adult obesity and related metabolic disorders, making it a major global public health concern. Recent studies have revealed the crucial role of gut microbiota in the occurrence and development of obesity, in addition to genetic and lifestyle factors. In this study, we recruited 19 normal-weight children and 47 children with varying degrees of obesity. A questionnaire survey was conducted to inquire about the family background, lifestyle habits and dietary composition of the 66 children. Findings indicate that fathers of obese children tend to be obese themselves, while children with highly educated mothers are more likely to maintain a normal weight. Furthermore, overweight children tend to spend more time on electronic devices and less time on physical activities compared to their normal-weight counterparts. Obese children exhibit significant differences in breakfast and dinner dietary composition when compared to children with normal weight. Additionally, the gut microbiota of these 66 children was analyzed using 16S rRNA sequencing. Analysis of gut microbiota composition showed similar compositions among children with varying degrees of obesity, but significant differences were observed in comparison to normal-weight children. Obese children exhibited a reduced proportion of Bacteroidota and an increased proportion of Firmicutes, resulting in an elevated Firmicutes/Bacteroidota ratio. Moreover, Actinobacteriota were found to be increased in the gut microbiota of children with varying degrees of obesity. PICRUSt analysis indicated significant metabolic differences in the microbiota functions between obese and normal-weight children, suggesting the composition of gut microbiota could be a crucial factor contributing to obesity. These findings provide valuable insights for the treatment of childhood obesity.

Abstract Metagenomic binning is an essential technique for genome-resolved characterization of uncultured microorganisms in various ecosystems but hampered by the low efficiency of binning tools in adequately recovering metagenome-assembled genomes (MAGs). Here, we introduce BASALT (Binning Across a Series of Assemblies Toolkit) for binning and refinement of short- and long-read sequencing data. BASALT employs multiple binners with multiple thresholds to produce initial bins, then utilizes neural networks to identify core sequences to remove redundant bins and refine non-redundant bins. Using the same assemblies generated from Critical Assessment of Metagenome Interpretation (CAMI) datasets, BASALT produces up to twice as many MAGs as VAMB, DASTool, or metaWRAP. Processing assemblies from a lake sediment dataset, BASALT produces ~30% more MAGs than metaWRAP, including 21 unique class-level prokaryotic lineages. Functional annotations reveal that BASALT can retrieve 47.6% more non-redundant opening-reading frames than metaWRAP. These results highlight the robust handling of metagenomic sequencing data of BASALT.

With the increasing amount of space debris in near-earth space, the surveillance of space has become more crucial to prevent potential space collisions. In an optical surveillance system, a multitude of debris with varying sizes, speeds, and intensities exists within images, which brings great difficulties for the extraction of targets. Current methodologies mainly emphasize local saliency enhancement and source extraction based on global statistical attributes, yet often overlook the distribution similarity of individuals and how to map them in a standardized space. To address this limitation, this article introduces an innovative transformation from the grayscale space to the correlation space. Initially, a fourfold-structure model is designed to measure the local correlation for each element in the grayscale space. Subsequently, the standardized correlation space is constructed by correlation measurement. Then, combining an adaptive threshold choosing method based on statistics and a threshold limitation strategy based on correlation, the individuals can be separated from the feature space. Finally, a deblending method is applied to disentangle merged individuals based on the local gradient correlation. Thoroughly assessed using ten subimage sequences featuring targets with typical traits against complex backgrounds, the results confirm its superior extraction capabilities and effectiveness when compared to ten common baseline methods, which achieves an average 90.9% true positive rate in just 2.8 ms. Furthermore, the extraction outcomes serve as a basis for detecting true target trajectories in continuous sequences. This integration holds significant implications for practical applications in space surveillance engineering.

A digital controlled unipolar hysteresis current control strategy applied to the single-phase grid-connected inverter is studied in the paper. In view of the problem of current zero-crossing distortion in the traditional unipolar hysteresis current control based on finite state machines (FSM), a new unipolar hysteresis current control strategy based on current decoupling is proposed. By introducing a virtual zero-sequence current, the single-phase full-bridge inverter is decoupled into two independent half-bridge inverter units, which are controlled by two bipolar hysteresis current control loops under the constraints of a finite state machine. Therefore, the operation rules of the FSM ensure the frequency doubling output of the unipolar modulation, and the virtual two-phase decoupled current eliminates the zero-crossing distortion problem of inverter output current. Finally, the effectiveness and feasibility of the proposed method were verified by building a 1kW single-phase full-bridge grid-connected inverter in the laboratory.

Mobile edge computing is envisioned as a prospective technology for supporting time-sensitive and computation-intensive applications in marine vehicle systems. However, the offloading performance is highly impacted by the poor wireless channel. Recently, an Unmanned Aerial Vehicle (UAV) equipped with an Intelligent Reflecting Surface (IRS), i.e., UIRS, has drawn attention due to its capability to control wireless signals so as to improve the data rate. In this paper, we consider a multi-UIRS-assisted marine vehicle system where UIRSs are deployed to assist in the computation offloading of Unmanned Surface Vehicles (USVs). To improve energy efficiency, the optimization problem of the association relationships, computation resources of USVs, multi-UIRS phase shifts, and multi-UIRS trajectories is formulated. To solve the mixed-integer nonlinear programming problem, we decompose it into two layers and propose an integrated convex optimization and deep reinforcement learning algorithm to attain the near-optimal solution. Specifically, the inner layer solves the discrete variables by using the convex optimization based on Dinkelbach and relaxation methods, and the outer layer optimizes the continuous variables based on the Multi-Agent Twin Delayed Deep Deterministic Policy Gradient (MATD3). The numerical results demonstrate that the proposed algorithm can effectively improve the energy efficiency of the multi-UIRS-assisted marine vehicle system in comparison with the benchmarks.

Mooring chains are key components of offshore floating photovoltaic systems. Although their service safety is often affected by the harsh service environment, the influence of surface roughness on their corrosion resistance is not clear. This study investigated the corrosion behavior of mooring chain steel using cyclic salt-spray corrosion and electrochemical tests. Scanning electron microscopy, energy-dispersive spectrometry, optical profilometry, and other analytical techniques were used to study the composition and morphology of the corrosion products. The corrosion behavior was studied by electrochemical polarization curves, alternating current impedance spectroscopy, and X-ray photoelectron spectroscopy. The results show that the salt-spray corrosion resistance of mooring chain steel significantly improved with the reduction in specimen surface roughness, and the number and depth of corrosion pits were reduced. Mass loss after 24 h of salt-spray corrosion was exponentially related to initial roughness (Ra). Improved surface roughness significantly increased the pitting potential of the specimens, widened the passivation range, and enhanced the repassivation capability, thus significantly improving the pitting resistance. The pitting potential is linearly related to the initial roughness of the specimen. The oxide contents of Fe, Mo, and Si in the passivation film tended to increase with a smoother surface, which contributes to its densification. This effectively blocks chloride ion attack, thus improving the corrosion resistance of the mooring chain steel.

Anthracycline drugs mainly include doxorubicin, epirubicin, pirarubicin, and aclamycin, which are widely used to treat a variety of malignant tumors, such as breast cancer, gastrointestinal tumors, lymphoma, etc. With the accumulation of anthracycline drugs in the body, they can induce serious heart damage, limiting their clinical application. The mechanism by which anthracycline drugs cause cardiotoxicity is not yet clear. This review provides an overview of the different types of cardiac damage induced by anthracycline-class drugs and delves into the molecular mechanisms behind these injuries. Cardiac damage primarily involves alterations in myocardial cell function and pathological cell death, encompassing mitochondrial dysfunction, topoisomerase inhibition, disruptions in iron ion metabolism, myofibril degradation, and oxidative stress. Mechanisms of uptake and transport in anthracycline-induced cardiotoxicity are emphasized, as well as the role and breakthroughs of iPSC in cardiotoxicity studies. Selected novel cardioprotective therapies and mechanisms are updated. Mechanisms and protective strategies associated with anthracycline cardiotoxicity in animal experiments are examined, and the definition of drug damage in humans and animal models is discussed. Understanding these molecular mechanisms is of paramount importance in mitigating anthracycline-induced cardiac toxicity and guiding the development of safer approaches in cancer treatment.

To date, few FDA-approved medical countermeasures are available for addressing hematopoietic acute radiation syndrome (H-ARS). In this study, we present our latest research findings focusing on the evaluation of a novel radiation mitigator known as the mitigating amino acid mixture (MAAM). MAAM is composed of five amino acids as the recently reported amino acid-based oral rehydration solution for mitigating gastrointestinal (GI)-ARS. CD2F1 male and female mice were exposed to 60Co-γ total body irradiation (TBI) at 9.0 or 9.5 Gy. Following irradiation, mice were orally administered with MAAM or a saline vehicle control once daily for a duration of 14 days, commencing 24 h after TBI. Mouse survival and body weight change were monitored for 30 days after irradiation. Complete blood counts (CBCs), bone marrow (BM) stem and progenitor cell survival (clonogenicity), and a serum cytokine antibody array were analyzed using samples from day 30 surviving mice. Our data revealed that MAAM treatment significantly enhanced survival rates in irradiated male CD2F1 mice, and the survival rate increased from 25% in the vehicle control group to 60% in the MAAM-treated group (p

Summary: The swift advancement of the solid oxide fuel cell (SOFC) sector necessitates a harmony between electrode performance and commercialization cost. The economic value of elements is frequently linked to their abundance in the Earth’s crust. Here, we develop abundant rare-earth iron perovskite electrodes of Ln0.6Sr0.4FeO3-δ (Ln = La, Pr, and Nd) with high abundant rare-earth metals and preferred iron metal for SOFCs. All three symmetric electrode materials display a cubic perovskite phase and excellent chemical compatibility with Gd0.2Ce0.8O2-δ electrolyte. All three electrodes possess exceptional surface oxygen exchange ability. At 800°C, single cells with La0.6Sr0.4FeO3-δ, Pr0.6Sr0.4FeO3-δ, and Nd0.6Sr0.4FeO3-δ symmetric electrodes attained excellent open circuit voltages of 1.108, 1.101, and 1.097 V, respectively, as well as peak powers of 213.52, 281.12, and 254.58 mW cm−2. The results suggest that overall performance of abundant rare-earth iron perovskite electrodes has a favorable impact on the extensive expansion of SOFCs, presenting significant potential for practical applications.

IntroductionTreatments that currently exist in the strategic national stockpile for acute radiation syndrome (ARS) focus on the hematopoietic subsyndrome, with no treatments on gastrointestinal (GI)-ARS. While the gut microbiota helps maintain host homeostasis by mediating GI epithelial and mucosal integrity, radiation exposure can alter gut commensal microbiota which may leave the host susceptible to opportunistic pathogens and serious sequelae such as sepsis. To mitigate the effects of hematopoietic ARS irradiation, currently approved treatments exist in the form of colony stimulating factors and antibiotics: however, there are few studies examining how these therapeutics affect GI-ARS and the gut microbiota. The aim of our study was to examine the longitudinal effects of Neulasta and/or ciprofloxacin treatment on the gut microbiota after exposure to 9.5 Gy 60Co gamma-radiation in mice.MethodsThe gut microbiota of vehicle and drug-treated mice exposed to sham or gamma-radiation was characterized by shotgun sequencing with alpha diversity, beta diversity, and taxonomy analyzed on days 2, 4, 9, and 15 post-irradiation.ResultsNo significant alpha diversity differences were observed following radiation, while beta diversity shifts and taxonomic profiles revealed significant alterations in Akkermansia, Bacteroides, and Lactobacillus. Ciprofloxacin generally led to lower Shannon diversity and Bacteroides prevalence with increases in Akkermansia and Lactobacillus compared to vehicle treated and irradiated mice. While Neulasta increased Shannon diversity and by day 9 had more similar taxonomic profiles to sham than ciprofloxacin-or vehicle-treated irradiated animals. Combined therapy of Neulasta and ciprofloxacin induced a decrease in Shannon diversity and resulted in unique taxonomic profiles early post-irradiation, returning closer to vehicle-treated levels over time, but persistent increases in Akkermansia and Bacteroides compared to Neulasta alone.DiscussionThis study provides a framework for the identification of microbial elements that may influence radiosensitivity, biodosimetry and the efficacy of potential therapeutics. Moreover, increased survival from H-ARS using these therapeutics may affect the symptoms and appearance of what may have been subclinical GI-ARS.

Abstract Objective To explore the influence of postoperative body mass index (BMI) change on postoperative quality of life (QOL) in patients undergoing radical cystectomy (RC) plus modified single stoma cutaneous ureterostomy (MSSCU) or ileal conduit (IC). Methods Patients were divided into two groups according to different BMI change patterns: patients experiencing an elevated postoperative BMI level, along with a clinically significant increase in their BMI (an increase of more than 10%) were categorized as Group 1, while patients experiencing a decrease postoperative BMI level, along with a clinically significant reduction in their BMI (a decrease of more than 5%) were categorized as Group 2. Spearman correlation analysis was used to examine the correlations between quality‐of‐life scores and postoperative clinical parameters. Results Spearman correlation analysis showed that postoperative BMI, late complications and catheter‐free state were significantly associated with postoperative global QoL and symptom scale in MSSCU and postoperative global QoL and physical scale in IC patients. Additionally, postoperative BMI, catheter‐free state and the use of adjuvant therapy were associated with bad performance in many scales of QoL like body image, future perspective, social scale, future perspective (MSSCU), and abdominal bloating (IC) (Table 2, p

Abstract Due to the advantages of rapid deployment, flexible response and strong invulnerability, unmanned aerial vehicle (UAV) swarm has been widely applied in collaborative warfare and emergency communication. However, UAV swarm in complex environments is prone to chaotic collapse due to obstructions. A UAV swarm obstacle avoidance system model for multi-narrow type obstacles is established. Due to the fact that only one UAV is allowed to pass through each small hole at any given moment, addressing the issue of congestion caused by swarming effects becomes crucial in addition to managing the competitive allocation of multiple UAVs to multiple holes. Aiming at this problem, a dual-game real-time obstacle avoidance scheme is proposed for UAV swarm with multi-narrow type obstacle scenarios, which divides the flight process of the UAV swarm into two stages: maintaining the flight state of the UAV swarm unchanged when no obstacles are encountered, and implementing matching separation and motion state switching by means of dual-game strategy when facing multi-narrow type obstacles, ultimately achieving orderly passage after multiple rounds of games. For the proposed scheme, a dual-game based Flocking (DGF) obstacle avoidance algorithm is proposed. Specifically, the motion state of each UAV obtained from the game is parameterized and integrated with the Flocking algorithm to calculate the motion control input for each UAV. The solution is iteratively obtained until the UAV swarm completes the obstacle avoidance. Simulation results demonstrate that the proposed DGF algorithm not only enables smooth obstacle avoidance for the UAV swarm in multi-narrow type obstacle scenarios, but also effectively resolves the internal chaos problem in the UAV swarm, thereby preventing rigid collisions.

Abstract Renal vein thrombosis (RVT) is a rare vascular complication that occurs after renal transplantation and usually results in irreversible kidney damage and graft loss. We report the case of a patient who underwent right iliac fossa allogeneic kidney transplantation and developed RVT combined with ipsilateral thrombosis from the popliteal to the femoral veins, with extension to the common iliac veins, 4 months after transplantation. Under unfractionated heparin anticoagulation, an Aegisy (Life Tech Scientific Co., Ltd., Shenzhen, China) vena cava filter was placed to prevent pulmonary embolism. Percutaneous mechanical thrombectomy combined with balloon angioplasty was performed to aspirate the thrombus and successfully dilate the narrow venous lumen. The patient’s renal function was restored postoperatively. Ultrasonography showed the allograft and ipsilateral lower extremity deep veins to be fluent and patent. To conclude, in patients with RVT after renal transplantation, percutaneous mechanical thrombectomy in conjunction with balloon angioplasty can be performed with desirable outcomes and no severe adverse effects. This method reduces the risk of bleeding from exposure to systemic intravenous thrombolysis and avoids surgery-associated trauma.

Fermentation of mulberry juice not only improves its shelf life, but also effectively enhances their flavor and nutritional quality. This study elucidated the phytochemical and flavor characteristics of mulberry juice fermented with Lactiplantibacillus plantarum BXM2, originally isolated from naturally fermented fruit beverage, through widely targeted metabolomics. The fermentation produced the unique flavor of fermented juice and decreased the pH from 4.15 to 3.19. The metabolomic analysis detected 907 non-volatile metabolites, from which 359 significantly different non-volatile metabolites (up 238, down 121) were screened out. Among 731 identified volatile metabolites, 26 flavor substances were the major contributors to the flavor differences between fermented and unfermented mulberry juices. It is hypothesized that lipid metabolism and amino acid catabolism are crucial pathways for the flavor enhancement of mulberry juice fermented with L. plantarum BXM2. Meanwhile, significant increases of the contents of a variety of bioactive substances, such as indole-3-lactic acid, octadeca-9,12,15-trienoic acid, di-/tri-peptides, etc., conferred additional health potential to BXM2-fermented mulberry juice.

Weizmannia coagulans is increasingly employed in food processing owing to its health benefits. Our previous research developed Oolong tea-fortified rice noodles with unique flavor and potent antioxidant activity; however, their texture still requires improvement. In this study, Oolong tea-fortified rice noodles were fermented using W. coagulans PR06 at inoculation amounts of 1%, 3%, and 5% (v/v), and assessed for cooking quality, texture, and starch digestibility. The results indicated that fermentation with 3% and 5% W. coagulans PR06 altered the amylopectin length distribution in the rice noodles and increased the degree of starch short-range order. Furthermore, the fermentation process increased the storage modulus (G′) and loss modulus (G″) values, decreased the tan δ value, and strengthened the interactions among tea polyphenols, proteins, and starch in the rice flour gel. Consequently, this process increased the hardness and chewiness of the rice noodles, decreased their broken strip rate and cooking loss, and significantly reduced their in vitro starch digestibility. Overall, fermentation with W. coagulans PR06 markedly improved the texture and cooking quality of Oolong tea-fortified rice noodles while effectively delaying starch digestion. This study highlights the potential application of W. coagulans PR06 in developing diverse and functional rice noodle products.

Defect-engineering accelerates the conduction of lithium ions in the cathode materials of lithium-ion batteries. However, the effects of defect-engineering on ion conduction and its mechanisms in humid environments remain unclear in the academic discourse. Here, we report on the effect of vacancy defects on the electronic properties of and Li-ion diffusion in a LiFePO4 material in humid environments. The research findings indicate that vacancy defects reduce the lattice constant and unit cell volume of LiFePO4. Additionally, the water molecules occupy the Li-ion vacancies, leading to an increase in the lattice constant of LiFePO4. The computational results of the electronic properties show that the introduction of water molecules induces a transition in LiFePO4 from a semiconductor to a metallic behavior, with a transfer of 0.38 e of charge from the water molecules to LiFePO4. Additionally, the migration barrier for Li ions in the H2O + LiFePO4 system is found to be 0.50 eV, representing an 11.1% increase compared to the pristine LiFePO4 migration barrier. Our findings suggest that water molecules impede the migration of Li ions and provide important insights into the effect of defect-engineering on electronic properties and ion conduction under humid conditions.

Abstract A potential probiotic strain BXM2 was isolated from naturally fermented honey passion fruit beverage, and identified as Lactiplantibacillus plantarum using 16S rDNA sequence analysis, rpoA gene sequence analysis combined with API bacterial identification method. BXM2 was evaluated for its probiotic and technological properties, such as growth efficiency, gastrointestinal tolerance, antibacterial activity and antibiotic resistance. The results showed that the optimum growth efficiency of BXM2 was achieved under the fermentation temperature ranged from 30°C to 37°C. The initial content of BXM2 (8.50 log CFU/mL) was decreased to 7.53 log CFU/mL after 3 h treatment in simulated gastric fluid (pH = 3.0) and 8.12 log CFU/mL after 6 h treatment in simulated intestinal fluid (pH = 8.0) (p

Abstract Background Recent studies have shown that gut microbiome plays important roles in response to radiation exposure. IL-18, an inflammatory cytokine, is highly elevated in mice, mini-pigs and nonhuman primates after radiation exposure. Blocking IL-18 using its endogenous binding protein (IL-18BP) increases mice survival after radiation exposure by decreasing bone marrow interferon-gamma levels. Methods To further characterize the roles of IL-18 in response to radiation, both wild type and IL-18 knockout (IL-18 KO) mice were exposed to 9.0 Gy total body irradiation (TBI). The 30-day survival result demonstrated that IL-18 KO mice were significantly more resistant to radiation compared to the wild type mice (p

The shadow mode-based regular sampling methods are usually used in the digital control of power inverters, which introduce a control delay of one and a half sampling periods. The control delay affects the closed loop bandwidth and the stability of dc–ac inverters. Recently, regular sampling methods based on the immediate mode is emerging and helpful for reducing the digital control delay. When employing the immediate mode, the induced vertical crossings may arouse the duty-cycle loss and dead-band effect during the modulation process, which deteriorate the normal operation of the inverters. Although the duty-cycle loss can be avoided by forcing the PWM signal to flip at the occurrence of vertical crossings, the introduced dead bands still exist. Thus, this paper investigates the phenomenon of vertical crossings and proposes a control algorithm composed of predicting the occurrence of vertical crossings and compensating the dead-band effect for regular sampling methods based on the immediate mode. Finally, experimental results on a single-phase dc–ac inverter prototype are provided to compare the efficacy of different approaches.

With the high flexibility and low cost of the deployment of UAVs, the application of UAV-assisted data collection has become widespread in the Internet of Things (IoT) systems. Meanwhile, the age of information (AoI) has been adopted as a key metric to evaluate the quality of the collected data. Most of the literature generally focuses on minimizing the age of all information. However, minimizing the overall AoI may lead to high costs and massive energy consumption. In addition, not all types of data need to be updated highly frequently. In this paper, we consider both the diversity of different tasks in terms of the data update period and the AoI of the collected sensing information. An efficient data collection method is proposed to maximize the system utility while ensuring the freshness of the collected information relative to their respective update periods. This problem is NP-hard. With the decomposition, we optimize the upload strategy of sensor nodes at each time slot, as well as the hovering positions and flight speeds of UAVs. Simulation results show that our method ensures the relative freshness of all information and reduces the time-averaged AoI by 96.5%, 44%, 90.4%, and 26% when the number of UAVs is 1 compared to the corresponding EMA, AOA, DROA, and DRL-eFresh, respectively.

ABSTRACTThe psychological factors of senior executives have an important impact on the firm’s financial policies. In this paper, we investigate the association between CEO risk-taking entrepreneurial spirit and firm cash holdings, and find that firms with higher CEO risk-taking entrepreneurial spirit have less cash holdings. Further, we find that financing constraints can mitigate the negative association between CEO risk-taking entrepreneurial spirit and firm cash holdings, whereas financing needs enhances the association between them. Mechanism test illustrates that CEO risk-taking entrepreneurial spirit affects firm cash holdings through corporate investment. Finally, the results reveal that CEO risk-taking entrepreneurial spirit not only promotes the value of cash holdings, but also is significantly positively associated with both accounting performance and market performance. Our findings shed lights on the impact of executive psychological factors on financial decisions and have important implications for cash-holding decisions of listed firms.

Abstract Although the ‘one ticket transfer’ mode brings convenience to passengers, it also poses challenges to the passenger flow assignment. The current widely used multi‐path probability assignment model based on traffic cost realizes the passenger flow distribution from the macro‐perspective but lacks the consideration of passenger attributes and the time‐varying characteristics of passenger travel time. Here, a novel spatiotemporal path inference model is proposed for Urban Rail Transit (URT) passengers based on the travel time data and train operation information. In this study, the impact of passengers detained at the platform on passenger travel itinerary is considered by characterizing the passenger detention rate. The proposed method realizes the reverse inference of passenger path from the micro‐perspective, and can accurately describe the specific travel process of each passenger. Moreover, the real‐world data of Shenzhen Metro in China is taken to verify the rationality of the proposed model. The results show that the model is in good agreement with the existing clearance model and can accurately infer the passenger travel itinerary from the micro‐perspective. The proposed method provides a more refined solution for the spatial‐temporal assignment of URT passenger flow.

Introduction: Due to the cardiotoxicity of pirarubicin (THP), it is necessary to investigate new compounds for the treatment of THP-induced cardiotoxicity. Isoquercitrin (IQC) is a natural flavonoid with anti-oxidant and anti-apoptosis properties. Thus, the present study aimed to investigate the influence of IQC on preventing the THP-induced cardiotoxicity in vivo and in vitro.Methods: The optimal concentration and time required for IQC to prevent THP-induced cardiomyocyte damage were determined by an MTT assay. The protective effect was further verified in H9c2 and HCM cells using dichlorodihydrofluorescein diacetate fluorescent probes, MitoTracker Red probe, enzyme-linked immunosorbent assay, JC-1 probe, and real time-quantitative polymerase chain reaction (RT-qPCR). Rats were administered THP to establish cardiotoxicity. An electrocardiogram (ECG) was performed, and cardiac hemodynamics, myocardial enzymes, oxidative stress indicators, and hematoxylin-eosin staining were studied. Voltage-dependent anion channel 1 (VDAC1), adenine nucleotide translocase 1 (ANT1), and cyclophilin D (CYPD) were detected by qRT-PCR, and the Phlpp1/AKT/Bcl-2 axis proteins were detected by western blot, confirming that IQC markedly increased cell viability and superoxide dismutase (SOD) levels, diminished the levels of ROS and MDA, and elevated mitochondrial function and apoptosis in vivo and in vitro.Results: Results showed that IQC reduced THP-induced myocardial histopathological injury, electrocardiogram (ECG) abnormalities, and cardiac dysfunction in vivo. IQC also decreased serum levels of MDA, BNP, CK-MB, c-TnT, and LDH, while increasing levels of SOD and GSH. We also found that IQC significantly reduced VDAC1, ANT1, and CYPD mRNA expression. In addition, IQC controlled apoptosis by modulating Phlpp1/AKT/Bcl-2 signaling pathways. IQC markedly increased H9c2 and HCM cell viability and SOD levels, diminished the levels of ROS and MDA, and elevated mitochondrial function in H9c2 and HCM cells to defend against THP-induced cardiomyocyte apoptosis in vitro. The AKT inhibitor IMQ demonstrated that IQC lacked antioxidant and anti-apoptotic properties. Moreover, our data showed that IQC regulates Phlpp1 expression, thereby influencing the expression levels of p-AKT, cytochrome c, caspase-3, caspase-9, Bcl-2, and Bax.Discussion: In conclusion, our results indicate that IQC protects the changes in mitochondrial membrane permeability in cardiomyocytes by regulating the Phlpp1/AKT/Bcl-2 signaling pathway, inhibits the release of cytc from the mitochondrial inner membrane to the cytoplasm, forms apoptotic bodies, induces cell apoptosis, and reduces THP induced cardiotoxicity.

Due to the randomness of hard and brittle material damage evolution, assessing damage and interpreting mechanisms is challenging. This study focuses on analyzing material damage mechanisms by employing extensive multi-source heterogeneous data to extract quantitative information. A machine vision-based method for detecting and assessing defects in ceramics was proposed, achieving 98 % accuracy. Leveraging this method in scratching experiments, the progression of damage and micro-failure mechanisms in Si3N4 was investigated through the analysis of defect area distribution, force and acoustical signals. Results revealed that the distribution of defect areas conforms to a three-parameter Weibull distribution. At scratch depths of 0.01, 0.02 mm, approximately 90 % of damage accumulated within 1e2–1e4 μm2; conversely, 0.03–0.06 mm led to a decrease to 30 – 40 %. Extensive crack propagation occurs within 0.02–0.03 mm, resulting in the intersecting formation of spalling blocks. Damage evolution occurs in three stages: shallow and small cracks with scattered spalling blocks in the first stage, deep and long cracks with continuous and irregularly shaped spalling blocks in the second stage, and nearly no cracks with continuous and regularly shaped blocks in the third stage. This study not only proposes an efficient method to detect and evaluate ceramic defects, but also deeply understands the evolution process of material damage mechanism. Considering defect distribution and statistical trends, this research not only provide guidance for the optimization of machining parameters, especially in the scene of specific precision and high removal rate. At the same time, the damage evolution and failure mechanism of Si3N4 provide useful experimental basis and data support for deepening the understanding of material behavior during ultra-precision grinding.

We developed a simple method of in-situ synthesize carbon nanotubes (CNTs) on Ti–6Al–4V (TC4) alloy powder to fabricate CNTs/TC4 compound powders through plasma-enhanced chemical vapor deposition (PECVD). By this approach, CNTs on TC4 alloy powder exhibit better uniform dispersion and morphology compared with the traditional CVD methods. In order to reveal the growth behavior of CNTs during the PECVD process, XRD, SEM, TEM, and Raman spectroscopy were used to analyze the morphology and graphitization of CNTs at different synthesis conditions. The plasma is benefit to the pyrolysis of CH4, but overmuch plasma bombardment also reduces the yield and quality of CNTs. The number of CNTs can be significantly improved with appropriately increasing the temperature and time, but excessive temperature, time and carbon concentration can increase the number of impurities such as amorphous carbon. Significantly, the growth mechanism of CNTs synthesized in TC4 powders is following tip-growth mode in PECVD process. Additionally, the quantity and quality were satisfactory at 600 °C for 30 min with 50 W plasma power. This study about PECVD process lays a foundation for improving the comprehensive properties of CNTs/TC4 composites in the future.

IntroductionBrain hemorrhage was found between 13 and 16 days after acute whole-body 9.5 Gy 60Co-γ irradiation (IR). This study tested countermeasures mitigating brain hemorrhage and increasing survival from IR. Previously, we found that pegylated G-CSF therapy (PEG) (i.e., Neulasta®, an FDA-approved drug) improved survival post-IR by 20–40%. This study investigated whether Ciprofloxacin (CIP) could enhance PEG-induced survival and whether IR-induced brain hemorrhage could be mitigated by PEG alone or combined with CIP.MethodsB6D2F1 female mice were exposed to 60Co-γ-radiation. CIP was fed to mice for 21 days. PEG was injected on days 1, 8, and 15. 30-day survival and weight loss were studied in mice treated with vehicles, CIP, PEG, or PEG + CIP. For the early time point study, blood and sternums on days 2, 4, 9, and 15 and brains on day 15 post-IR were collected. Platelet numbers, brain hemorrhage, and histopathology were analyzed. The cerebellum/pons/medulla oblongata were detected with glial fibrillary acidic protein (GFAP), p53, p16, interleukin-18 (IL-18), ICAM1, Claudin 2, ZO-1, and complement protein 3 (C3).ResultsCIP + PEG enhanced survival after IR by 85% vs. the 30% improvement by PEG alone. IR depleted platelets, which was mitigated by PEG or CIP + PEG. Brain hemorrhage, both surface and intracranial, was observed, whereas the sham mice displayed no hemorrhage. CIP or CIP + PEG significantly mitigated brain hemorrhage. IR reduced GFAP levels that were recovered by CIP or CIP + PEG, but not by PEG alone. IR increased IL-18 levels on day 4 only, which was inhibited by CIP alone, PEG alone, or PEG + CIP. IR increased C3 on day 4 and day 15 and that coincided with the occurrence of brain hemorrhage on day 15. IR increased phosphorylated p53 and p53 levels, which was mitigated by CIP, PEG or PEG + CIP. P16, Claudin 2, and ZO-1 were not altered; ICAM1 was increased.DiscussionCIP + PEG enhanced survival post-IR more than PEG alone. The Concurrence of brain hemorrhage, C3 increases and p53 activation post-IR suggests their involvement in the IR-induced brain impairment. CIP + PEG effectively mitigated the brain lesions, suggesting effectiveness of CIP + PEG therapy for treating the IR-induced brain hemorrhage by recovering GFAP and platelets and reducing C3 and p53.

IntroductionPrevious studies have shown disrupted effective connectivity in the large-scale brain networks of individuals with major depressive disorder (MDD). However, it is unclear whether these changes differ between first-episode drug-naive MDD (FEDN-MDD) and recurrent MDD (R-MDD).MethodsThis study utilized resting-state fMRI data from 17 sites in the Chinese REST-meta-MDD project, consisting of 839 patients with MDD and 788 normal controls (NCs). All data was preprocessed using a standardized protocol. Then, we performed a granger causality analysis to calculate the effectivity connectivity (EC) within and between brain networks for each participant, and compared the differences between the groups.ResultsOur findings revealed that R-MDD exhibited increased EC in the fronto-parietal network (FPN) and decreased EC in the cerebellum network, while FEDN-MDD demonstrated increased EC from the sensorimotor network (SMN) to the FPN compared with the NCs. Importantly, the two MDD subgroups displayed significant differences in EC within the FPN and between the SMN and visual network. Moreover, the EC from the cingulo-opercular network to the SMN showed a significant negative correlation with the Hamilton Rating Scale for Depression (HAMD) score in the FEDN-MDD group.ConclusionThese findings suggest that first-episode and recurrent MDD have distinct effects on the effective connectivity in large-scale brain networks, which could be potential neural mechanisms underlying their different clinical manifestations.

With global warming and an increase in extreme weather, reducing carbon emissions in response to climate change has become a global consensus. Compared with traditional fuel vehicles, hybrid vehicles have the benefits of energy savings, low grid-load, and low emissions. The hybrid vehicles use the internal combustion engine and lithium-ion batteries as the hybrid power source to achieve the best match between the engine and the motor. However, the current commercial hybrid vehicle still has such defects as high dependence on fossil fuels, high carbon emissions, poor safety, etc. As such, it is necessary to explore and develop the next generation low-carbon hybrid vehicles. Herein, we propose a new-type hybrid of ammonia fuel cell and internal combustion engine with high-energy conversion efficiency and low-carbon emissions. Considering the advantages of low-carbon emissions, high mileage, fast refueling, low-cost, high-energy conversion efficiency, and high safety, a green low-carbon concept of the ammonia fuel cell-internal combustion engine hybrid vehicle (AFC-ICE HV) is proposed. This will help improve the scale and efficiency of China's green energy conversion, establish a green, low-carbon and sustainable economic system, provide new impetus for tackling climate change and environmental protection recovery, and help China and the world to achieve the Carbon Peak and Carbon Neutrality goal.