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Abstract Background Sleep and physical activity (PA) are thought to be interconnected with the development of rheumatoid arthritis (RA). However, the precise nature and extent of these relationships have yet to be fully quantified. This study aimed to quantify the longitudinal effects of sleep behaviors, PA, and genetic susceptibility on the incidence of RA and to estimate the combined effects and interactions among these exposures. Methods A total of 363,211 adults were derived from a large European cohort. We incorporated five sleep behaviors (sleep duration, insomnia, snoring, chronotype, and daytime sleepiness) to generate sleep patterns, which were defined based on healthy sleep scores. Multivariate-adjusted Cox proportional hazard models were conducted to assess the individual and combined associations of sleep patterns, PA, and genetic susceptibility with the risk of RA occurrence. Multiplicative and additive interactions were estimated by P interaction and relative excess risk due to interaction (RERI) between each of the two exposures. Results During a follow-up of 12.5 years, 4262 RA cases were ascertained. A healthy sleep pattern was associated with a decreased risk of RA in a dose-response manner, with an adjusted hazard ratio (HR) of 0.79 (95% confidence interval [CI] = 0.75–0.84), independent of traditional risk factors and genetic predisposition. Under the restricted cubic splines model, a non-linear association was detected for PA and RA risk. Participants in the intermediate quintile 3 showed the lowest risk for developing RA, with a HR 95% CI of 0.84 (0.76–0.92). Moreover, there was an additive interaction effect of intermediate sleep pattern and PA, with a 0.45 (95% CI = 0.02–0.87) RERI of developing RA. Additionally, individuals at high genetic risk had the greatest 10-year absolute risk reduction (10.58 per 1000 person-years) when adopting both favorable behaviors. Conclusions A healthy sleep pattern and moderate PA were associated with a reduced risk of developing RA, which can offset the deleterious effects of predisposing genetic components. Implementing these modifiable lifestyle factors into public health practices is beneficial for RA prevention.

Abstract In contrast to conventional cognitive training paradigms, where learning effects are specific to trained parameters, playing action video games has been shown to produce broad enhancements in many cognitive functions. These remarkable generalizations challenge the conventional theory of generalization that learned knowledge can be immediately applied to novel situations (i.e., immediate generalization). Instead, a new “learning to learn” theory has recently been proposed, suggesting that these broad generalizations are attained because action video game players (AVGPs) can quickly acquire the statistical regularities of novel tasks in order to increase the learning rate and ultimately achieve better performance. Although enhanced learning rate has been found for several tasks, it remains unclear whether AVGPs efficiently learn task statistics and use learned task knowledge to guide learning. To address this question, we tested 34 AVGPs and 36 non-video game players (NVGPs) on a cue-response associative learning task. Importantly, unlike conventional cognitive tasks with fixed task statistics, in this task, cue-response associations either remain stable or change rapidly (i.e., are volatile) in different blocks. To complete the task, participants should not only learn the lower-level cue-response associations through explicit feedback but also actively estimate the high-level task statistics (i.e., volatility) to dynamically guide lower-level learning. Such a dual learning system is modelled using a hierarchical Bayesian learning framework, and we found that AVGPs indeed quickly extract the volatility information and use the estimated higher volatility to accelerate learning of the cue-response associations. These results provide strong evidence for the “learning to learn” theory of generalization in AVGPs. Taken together, our work highlights enhanced hierarchical learning of both task statistics and cognitive abilities as a mechanism underlying the broad enhancements associated with action video game play.

Abstract Objective The underlying mechanisms of Overactive Bladder (OAB) remain unclear. This research is designed to investigate the correlation between the intake of dietary live microorganisms and OAB. Methods This analysis encompasses a cross-sectional study of broad population information gathered from the National Health and Nutrition Examination Surveys (NHANES) spanning the years 2007 to 2018. Participants were categorized into three groups—low, medium, and high—according to their consumption of dietary live microorganisms, as per the Sanders Dietary Active Microbiota Classification System. We utilized a weighted logistic regression model, restricted cubic spline (RCS), and subgroup analyses to investigate the relationship between dietary live microorganism intake and OAB. Results This research encompassed 16,795 subjects. The incidence of OAB was reduced in the group consuming a high amount of live dietary microbes compared to the groups with low and medium intake of such microbes. After detailed adjustments for covariates, analysis revealed that participants in the high live dietary microbe group had notably reduced odds of OAB compared to those in the low live dietary microbe group (OR: 0.84, 95% CI: 0.71–0.99, p = 0.03). RCS analysis indicated a nonlinear correlation between high dietary active microbiota intake and the incidence of OAB. Conclusion This research emphasizes the potential advantages of a high dietary intake of active microbiota for preventing OAB. These findings support incorporating active microbiota into dietary guidelines, demonstrating their connection with a decreased incidence of OAB.

Abstract. Background:. Although some well-established oncogenes are involved in cancer initiation and progression such as prostate cancer (PCa), the long tail of cancer genes remains to be defined. Goosecoid (GSC) has been implicated in cancer development. However, the comprehensive biological role of GSC in pan-cancer, specifically in PCa, remains unexplored. The aim of this study was to investigate the role of GSC in PCa development. Methods:. We performed a systematic bioinformatics exploration of GSC using datasets from The Cancer Genome Atlas, Genotype-Tissue Expression, Gene Expression Omnibus, German Cancer Research Center, and our in-house cohorts. First, we evaluated the expression of GSC and its association with patient prognosis, and identified GSC-relevant genetic alterations in cancers. Further, we focused on the clinical characterization and prognostic analysis of GSC in PCa. To understand the transcriptional regulation of GSC by E2F transcription factor 1 (E2F1), we performed chromatin immunoprecipitation quantitative polymerase chain reaction (qPCR). Functional experiments were conducted to validate the effect of GSC on the tumor cellular phenotype and sensitivity to trametinib. Results:. GSC expression was elevated in various tumors and significantly correlated with patient prognosis. The alterations of GSC contribute to the progression of various tumors especially in PCa. Patients with PCa and high GSC expression exhibited worse progression-free survival and biochemical recurrence outcomes. Further, GSC upregulation in patients with PCa was mostly accompanied with higher Gleason score, advanced tumor stage, lymph node metastasis, and elevated prostate-specific antigen (PSA) levels. Mechanistically, the transcription factor, E2F1, stimulates GSC by binding to its promoter region. Detailed experiments further demonstrated that GSC acted as an oncogene and influenced the response of PCa cells to trametinib treatment. Conclusions:. GSC was highly overexpressed and strongly correlated with patient prognosis in PCa. We found that GSC, regulated by E2F1, acted as an oncogene and impeded the therapeutic efficacy of trametinib in PCa.

The timely and accurate recognition of multi-type structural surface damage (e.g., cracks, spalling, corrosion, etc.) is vital for ensuring the structural safety and service performance of civil infrastructure and for accomplishing the intelligent maintenance of smart cities. Deep learning and computer vision have made profound impacts on automatic structural damage recognition using nondestructive test techniques, especially non-contact vision-based algorithms. However, the recognition accuracy highly depends on the training data volume and damage completeness in the conventional supervised learning pipeline, which significantly limits the model performance under actual application scenarios; the model performance and stability for multi-type structural damage categories are still challenging. To address the above issues, this study proposes a dual-stage optimization-based few-shot learning segmentation method using only a few images with supervised information for multi-type structural damage recognition. A dual-stage optimization paradigm is established encompassing an internal network optimization based on meta-task and an external meta-learning machine optimization based on meta-batch. The underlying image features pertinent to various structural damage types are learned as prior knowledge to expedite adaptability across diverse damage categories via only a few samples. Furthermore, a mathematical framework of optimization-based few-shot learning is formulated to intuitively express the perception mechanism. Comparative experiments are conducted to verify the effectiveness and necessity of the proposed method on a small-scale multi-type structural damage image set. The results show that the proposed method could achieve higher segmentation accuracies for various types of structural damage than directly training the original image segmentation network. In addition, the generalization ability for the unseen structural damage category is also validated. The proposed method provides an effective solution to achieve image-based structural damage recognition with high accuracy and robustness for bridges and buildings, which assists the unmanned intelligent inspection of civil infrastructure using drones and robotics in smart cities.

A 61-kb biosynthetic gene cluster (BGC), which is accountable for the biosynthesis of hibarimicin (HBM) B from Microbispora rosea subsp. hibaria TP-A0121, was heterologously expressed in Streptomyces coelicolor M1154, which generated a trace of the target products but accumulated a large amount of shunt products. Based on rational analysis of the relevant secondary metabolism, directed engineering of the biosynthetic pathways resulted in the high production of HBM B, as well as new HBM derivates with improved antitumor activity. These results not only establish a biosynthetic system to effectively synthesize HBMs—a class of the largest and most complex Type-II polyketides, with a unique pseudo-dimeric structure—but also set the stage for further engineering and deep investigation of this complex biosynthetic pathway toward potent anticancer drugs.

Abstract Evolution of SARS-CoV-2 variants emphasizes the need for multivalent vaccines capable of simultaneously targeting multiple strains. SCTV01E is a tetravalent COVID-19 vaccine derived from the spike protein of SARS-CoV-2 variants Alpha, Beta, Delta, and Omicron BA.1. In this double-blinded placebo-controlled pivotal efficacy trial (NCT05308576), the primary endpoint was vaccine efficacy (VE) against COVID-19 seven days post-vaccination in individuals without recent infection. Other endpoints included evaluating safety, immunogenicity, and the VE against all SARS-CoV-2 infections in individuals meeting the study criteria. Between December 26, 2022, and January 15, 2023, 9,223 individuals were randomized at a 1:1 ratio to receive SCTV01E or a placebo. SCTV01E showed a VE of 69.4% (95% CI: 50.6, 81.0) 7 days post-vaccination, with 75 cases in the placebo group and 23 in the SCTV01E group for the primary endpoint. VEs were 79.7% (95% CI: 51.0, 91.6) and 82.4% (95% CI: 57.9, 92.6), respectively, for preventing symptomatic infection and all SARS-CoV-2 infections 14 days post-vaccination. SCTV01E elicited a 25.0-fold higher neutralizing antibody response against Omicron BA.5 28 days post-vaccination compared to placebo. Reactogenicity was generally mild and transient, with no reported vaccine-related SAE, adverse events of special interest (AESI), or deaths. The trial aligned with the shift from dominant variants BA.5 and BF.7 to XBB, suggesting SCTV01E as a potential vaccine alternative effective against present and future variants.

Abstract In the context of globalization, the integration of cultural elements into scientific research, particularly through the incorporation of traditional Chinese cultural motifs in scientific illustrations, represents a novel frontier in enhancing the universality and appeal of scientific discoveries. This paper explores the innovative practice of embedding traditional Chinese cultural elements into scientific paper illustrations, highlighting its significant role in augmenting the global appeal of research findings, promoting diversity and innovation in scientific inquiry, and facilitating cross-cultural understanding. Through a series of case studies, including symbolic representations of ancient myths and the use of traditional themes to elucidate complex scientific phenomena, we demonstrate how this cultural integration not only makes scientific content more accessible and engaging but also fosters a deeper appreciation of Chinese heritage among international audiences. This approach not only bridges the gap between science and culture but also contributes to a more inclusive and interconnected global scientific community, underscoring the importance of cultural diversity in enriching scientific exploration and communication.

Abstract Cracks in tunnel lining structures constitute a common and serious problem that jeopardizes the safety of traffic and the durability of the tunnel. The similarity between lining seams and cracks in terms of strength and morphological characteristics renders the detection of cracks in tunnel lining structures challenging. To address this issue, a new deep learning-based method for crack detection in tunnel lining structures is proposed. First, an improved attention mechanism is introduced for the morphological features of lining seams, which not only aggregates global spatial information but also features along two dimensions, height and width, to mine more long-distance feature information. Furthermore, a mixed strip convolution module leveraging four different directions of strip convolution is proposed. This module captures remote contextual information from various angles to avoid interference from background pixels. To evaluate the proposed approach, the two modules are integrated into a U-shaped network, and experiments are conducted on Tunnel200, a tunnel lining crack dataset, as well as the publicly available crack datasets Crack500 and DeepCrack. The results show that the approach outperforms existing methods and achieves superior performance on these datasets.

The increasing utilization of transparent ceramics in laser systems, particularly the magnesium aluminate spinel (MgAl2O4) transparent ceramic, has positioned it as the primary candidate for high energy laser system exit windows. Nevertheless, the increased energy and power of laser output necessitate higher standards for the laser-induced damage threshold in transparent ceramics. Residual micropores within transparent ceramics pose a potential source of damage. In this study, we employed the post-annealing process to effectively modulate the density and size of micropores. We first established the relationship between the density and size of micropores and laser damage threshold, which described the damage morphology of transparent ceramic in detail. Subsequently, we developed a multi-physical field coupled kinetic model of laser damage in micropores, providing a quantitative analysis of how factors such as micropore size and density influence the damage morphology of transparent ceramic surfaces when subjected to laser irradiation. Using time-resolved pumping and probing technology, we conducted in situ detection of laser damage caused by micropores, enabling detailed examination of damage kinetic behavior. Ultimately, this study elucidated the physical mechanism behind micropore-induced transparent ceramic damage. This has significant implications for enhancing the anti-laser damage performance of transparent ceramics in high-intensity laser systems.

Abstract Background Jasmonate ZIM-domain (JAZ) proteins, which act as negative regulators in the jasmonic acid (JA) signalling pathway, have significant implications for plant development and response to abiotic stress. Results Through a comprehensive genome-wide analysis, a total of 20 members of the JAZ gene family specific to alfalfa were identified in its genome. Phylogenetic analysis divided these 20 MsJAZ genes into five subgroups. Gene structure analysis, protein motif analysis, and 3D protein structure analysis revealed that alfalfa JAZ genes in the same evolutionary branch share similar exon‒intron, motif, and 3D structure compositions. Eight segmental duplication events were identified among these 20 MsJAZ genes through collinearity analysis. Among the 32 chromosomes of the autotetraploid cultivated alfalfa, there were 20 MsJAZ genes distributed on 17 chromosomes. Extensive stress-related cis-acting elements were detected in the upstream sequences of MsJAZ genes, suggesting that their response to stress has an underlying function. Furthermore, the expression levels of MsJAZ genes were examined across various tissues and under the influence of salt stress conditions, revealing tissue-specific expression and regulation by salt stress. Through RT‒qPCR experiments, it was discovered that the relative expression levels of these six MsJAZ genes increased under salt stress. Conclusions In summary, our study represents the first comprehensive identification and analysis of the JAZ gene family in alfalfa. These results provide important information for exploring the mechanism of JAZ genes in alfalfa salt tolerance and identifying candidate genes for improving the salt tolerance of autotetraploid cultivated alfalfa via genetic engineering in the future.

Abstract Medullary Carcinoma of the Colon (MCC) is a rare histological subtype of colon cancer, and there is currently no recognized optimal treatment plan for it, with its prognosis remaining unclear. The aim of this study is to analyze the independent prognostic factors for MCC patients and develop and validate nomograms to predict overall survival (OS). A total of 760 patients newly diagnosed with MCC from 2004 to 2020 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. All patients were randomly allocated to a training group and a validation group in a 7:3 ratio. Univariate and multivariable Cox regression analyses were conducted to identify prognostic factors and construct nomograms. The nomogram prediction model was evaluated and validated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). The study found that elderly women are more susceptible to MCC, and the ascending colon and cecum are the most common sites of involvement. MCC is poorly differentiated, with stages II and III being the most common. Surgery is the primary treatment for MCC. The prognosis for patients with stage IV MCC is poor, with a median survival time of only 10 months. Independent prognostic factors for MCC include age, N stage, M stage, surgery, chemotherapy, and tumor size. Among them, age 7 cm (HR = 1.66, 95%CI 1.20–2.30) were risk factors for colon medullary carcinoma. The results of ROC, AUC, calibration curves, and DCA demonstrate that the nomogram prediction model exhibits good predictive performance. We have updated the demographic characteristics of colon medullary carcinoma and identified age, N staging, M staging, surgery, chemotherapy and tumor size as independent prognostic factors for colon medullary carcinoma. Additionally, we have established nomograms for prognostic prediction. These nomograms can provide personalized predictions and serve as valuable references for clinical decision-making.

Abstract The Jishishan Ms 6.2 earthquake occurred at 23:59 on December 18, 2023 in Gansu Province, China. We conducted a field survey to assess the hazards and damages caused by the earthquake and its associated geo-activities. Subsequently, we organized a seminar to discuss the possible causes of the destruction of a prehistoric site—Lajia Settlement—dated back to four thousand years B.P. and located only several kilometers away from the epicenter of the Jishishan earthquake. The Jishishan earthquake was unique for its hazard and disaster process, which featured ground shaking and a series of complex geological and geomorphological activities: sediment and soil spray piles, liquefaction, collapse, landslide, and mudflow along water channels. We define this phenomenon as the Jishishan earthquake ripple hazard (JERH). The most recent evidence from the JERH suggests that a prehistoric earthquake similar to the JERH, instead of riverine floods or earthquake-induced landslide dam outburst flood, as previously hypothesized, destroyed the Lajia Settlement.

Abstract Due to global warming and the disturbance of the interannual variability of precipitation, the frequency of extreme drought events has increased. The impact of global climate change on water resources is becoming increasingly apparent, then it is particularly necessary to explore the carrying capacity of water ecological environment under extreme drought conditions, which can guarantee the ecological water security in river basins. This study takes the Guanzhong area of the Wei River Basin as an example, calculating the water environment carrying capacity of 40 areas in the Weihe Guanzhong area in different levels of years under extreme drought conditions by comprehensive evaluation model of carrying capacity and using geographic information system GIS to display the spatial distribution of water environment carrying capacity in 40 regions. According to the results of the spatial distribution of water environmental bearing capacity, four different schemes are designed to improve the bearing capacity. The first plan reduces the industrial water consumption and irrigation quota by 5%, the second plan increases the industrial water and sewage treatment rate on this basis. the third plan further improves the development and utilization rate of surface and groundwater, and the fourth plan, on the basis of the first three plans, supplies 600 million cubic meters of industrial and agricultural water to Guanzhong region. Through comparative analysis, without taking any measures, under the extreme drought conditions, the water environment carrying capacity of the 40 areas in Guanzhong is all in an unbearable state. Overall, plan 4 has the most significant improvement in the water environment-carrying capacity, especially the Dong zhuang Reservoir of the Jing River which has played a very important role in enhancing the water ecological environment carrying capacity of the downstream water of the Wei River.

Abstract The LAT1-4F2hc complex (SLC7A5-SLC3A2) facilitates uptake of essential amino acids, hormones and drugs. Its dysfunction is associated with many cancers and immune/neurological disorders. Here, we apply native mass spectrometry (MS)-based approaches to provide evidence of super-dimer formation (LAT1-4F2hc)2. When combined with lipidomics, and site-directed mutagenesis, we discover four endogenous phosphatidylethanolamine (PE) molecules at the interface and C-terminus of both LAT1 subunits. We find that interfacial PE binding is regulated by 4F2hc-R183 and is critical for regulation of palmitoylation on neighbouring LAT1-C187. Combining native MS with mass photometry (MP), we reveal that super-dimerization is sensitive to pH, and modulated by complex N-glycans on the 4F2hc subunit. We further validate the dynamic assemblies of LAT1-4F2hc on plasma membrane and in the lysosome. Together our results link PTM and lipid binding with regulation and localisation of the LAT1-4F2hc super-dimer.

Silicosis is a systemic disease caused by long-term exposure to high concentrations of free silica dust particles in the workplace. It is characterized by a persistent inflammatory response, fibroblast proliferation, and excessive collagen deposition, leading to pulmonary interstitial fibrosis. Epithelial interstitial transformation (EMT) can cause epithelial cells to lose their tight junctions, cell polarity, and epithelial properties, thereby enhancing the properties of interstitial cells, which can lead to the progression of fibrosis and the formation of scar tissue. Integrin 1 (ITGB1) is considered an important factor for promoting EMT and tumor invasion in a variety of tumors and also plays an important role in the progression of fibrotic diseases. Therefore, ITGB1 can be used as a potential target for the treatment of silicosis. In this study, we found that silica exposure induced epithelial-mesenchymal transformation in rats and that the expression of integrin ITGB1 was elevated along with the EMT. We used CRISPR/Cas9 technology to construct integrin ITGB1 knockdown cell lines for in vitro experiments. We compared the expression of the EMT key proteins E-cadherin and vimentin in the ITGB1 knockdown cells and wild-type cells simultaneously stimulated by silica and detected the aggregation point distribution of E-cadherin and vimentin in the cells using laser confocal microscopy. Our results showed that ITGB1 knockout inhibited the ITGB1/ILK/Snail signaling pathway and attenuated the EMT occurrence compared to control cells. These results suggested that ITGB1 is associated with silica-induced EMT and may be a potential target for the treatment of silicosis.

Currently, there is a scarcity of studies exploring the safe operating parameters for coal-fired power units at loads below 30%.To accurately understand the operating characteristics of coal-fired units under low load conditions, and to provide a design basis for flexibility modifications, a simulation model coupled with boiler and turbine was established, which includes the flue gas and air system, steam and water system, steam turbine, and steam extraction heat recovery system, and the iterative calculation strategy for low load conditions was proposed. The simulation calculation was performed on a 350 MW supercritical coal-fired unit, with the model results showing a high degree of alignment with the unit’s design and operational parameters. Under the condition of 269MW, the maximum calculation error between the model’s predicted exit flue gas temperature of the air preheater and the actual operational results was 8.84%. This discrepancy was due to a sudden increase in the operating flue gas temperature, which may be associated with a blockage in the air preheater. And the simulation results under low load conditions indicate that when the unit load is below 20%, the furnace total airflow is controlled to no less than 30% of the airflow at Maximum Continuous Rating (BMCR) and the minimum feedwater flow rate can be reduced to 20% of that in Turbine Heat Acceptance (THA) load, and the unit switches to wet state operation around 20% load. As the unit load decreases, the coal consumption rate for power generation and steam turbine heat consumption rate both increase significantly. The coal consumption rate for power generation at 30% load is increased by 13.3% compared to BMCR load, and it is increased by 32.5% at 15% load which is operated in wet state. Under low load conditions, the coal consumption rate of the unit can be reduced by decreasing the oxygen content in the flue gas, reducing the minimum feedwater flow rate, and implementing boiler water recirculation.

The recent years have witnessed a great leap for near-infrared (NIR) spectroscopy technology in multifunctional application fields. In this study, a double-perovskite structured Cr3+-doped Cs2KScF6 fluoride NIR phosphor with peak location at 778 nm and full-width at half maximum (FWHM) of 95 nm was synthesized by a co-precipitation method. The integral emission intensity at 423 K retains 70 % of that at room temperature (RT), showing good luminescent thermal stability. Combining the obtained phosphor in an NIR phosphor converted light-emitting diode (NIR pc-LED) device, the output power and photoelectric conversion efficiency can reach 72.28 mW and 6.83 % at 320 mA. By virtue of the good optical performance, clear structural images of different fruits were visualized by using the NIR pc-LED as light source, suggesting the potential of Cs2KScF6:Cr3+ phosphor to be used in high-power LED devices.

Coronary microcirculation dysfunction (CMD) is one of the main causes of cardiovascular disease. Traditional treatment methods lack specificity, making it difficult to fully consider the differences in patient conditions and achieve effective treatment and intervention. The complexity and diversity of CMD require more standardized diagnosis and treatment plans to clarify the best treatment strategy and long-term outcomes. The existing treatment measures mainly focus on symptom management, including medication treatment, lifestyle intervention, and psychological therapy. However, the efficacy of these methods is not consistent for all patients, and the long-term efficacy is not yet clear. GSEA is a bioinformatics method used to interpret gene expression data, particularly for identifying the enrichment of predefined gene sets in gene expression data. In order to achieve personalized treatment and improve the quality and effectiveness of interventions, this article combined GSEA (Gene Set Enrichment Analysis) technology to conduct in-depth research on potential drug targets and their interaction networks in coronary microcirculation dysfunctions. This article first utilized the Coremine medical database, GeneCards, and DrugBank public databases to collect gene data. Then, filtering methods were used to preprocess the data, and GSEA was used to analyze the preprocessed gene expression data to identify and calculate pathways and enrichment scores related to CMD. Finally, protein sequence features were extracted through the calculation of autocorrelation features. To verify the effectiveness of GSEA, this article conducted experimental analysis from four aspects: precision, receiver operating characteristic (ROC) curve, correlation, and potential drug targets, and compared them with Gene Regulatory Networks (GRN) and Random Forest (RF) methods. The results showed that compared to the GRN and RF methods, the average precision of GSEA improved by 0.11. The conclusion indicated that GSEA helped identify and explore potential drug targets and their interaction networks, providing new ideas for personalized quality of CMD.

BackgroundCancer immunotherapy has made significant progress in recent years, with numerous studies worldwide. Immunotherapy has had a transformative impact on oncology and autoimmune diseases. In the biomedical arena, hydrogels with good properties are widely used in cancer immunotherapy. Our study used bibliometrics to analyze the changing trends in using hydrogels for cancer immunotherapy.MethodsFrom 2013 to 2023, a systematic search was conducted in the Web of Science Core Collection database to identify reviews and articles discussing the applications of hydrogels in cancer immunotherapy. The software CiteSpace was used to visually perform the bibliometric analysis in terms of research trends, countries, institutions, authors, journals, and keywords. Individual authors’ productivity was assessed with the Lotka’s law. The most relevant publication sources were identified by Bradford’s law.ResultsA total of 422 English-language publications related to hydrogels in cancer immunotherapy were collected. The number of annual publications increased rapidly after 2021 and remained constant for the past two years. China published the most articles in this field. The institution with the maximum number of published articles was the Chinese Academy of Sciences in China. Chen. Q was the most prolific author, and Liu. Z was the second most published author. In terms of journal contributions, the journal “Biomaterials” had the highest number of publications (n = 30). Biomaterials, Advanced Functional Materials and Journal of Controlled Release were the most influential journals. Keyword analysis revealed that cancer immunotherapy, drug delivery, immunogenic cell death, tumor microenvironment, injectable hydrogels, and immune checkpoint blockade were the primary research hotspots. In recent 3 years, adoptive T-cell therapy, black phosphorus, cell capture, adaptive cell therapy, tumor microenvironment, photodynamic therapy, and sustained release were the research hotspots in this field. Our study summarizes the objective of hydrogels in cancer immunotherapy in recent years, providing a reference for potential researchers in related field.ConclusionThis bibliometric analysis shows the progress and trend of research on hydrogels in cancer immunotherapy. This study provides a significant avenue for future investigation into current concerns and trends in research within this field.

Human exposure to per- and polyfluoroalkyl substances (PFASs) has received considerable attention, particularly in pregnant women because of their dramatic changes in physiological status and dietary patterns. Predicting internal PFAS exposure in pregnant women, based on external and relevant parameters, has not been investigated. Here, machine learning (ML) models were developed to predict the serum concentrations of PFOA and PFOS in a large population of 588 pregnant participants. Dietary exposure characteristics, demographic parameters, and in particular, serum fatty acid (FA) data were used for the model development. The fitting results showed that the inclusion of FAs as covariates significantly improved the performance of the ML models, with the random forest (RF) model having the best predictive performance for PFOA (R2 = 0.33, MAE = 1.51 ng/mL, and RMSE = 1.89 ng/mL) and PFOS (R2 = 0.12, MAE = 2.65 ng/mL, and RMSE = 3.37 ng/mL). The feature importance analysis revealed that serum FAs greatly affected PFOA concentration in the pregnant women, with saturated FAs being associated with decreased PFOA levels and unsaturated FAs with increased levels. Comparison with one-compartment pharmacokinetic model further demonstrated the advantage of the ML models in predicting PFAS exposure in pregnant women. Our models correlate for the first time blood chemical concentrations with human FA status using ML, introducing a novel perspective on predicting PFAS levels in pregnant women. This study provides valuable insights concerning internal exposure of PFASs generated from external exposure, and contributes to risk assessment and management in pregnant populations.

Background: Silicosis, characterized by interstitial lung inflammation and fibrosis, poses a significant health threat. ATII cells play a crucial role in alveolar epithelial repair and structural integrity maintenance. Inhibiting ATII cell senescence has shown promise in silicosis treatment.However, the mechanism behind silica-induced senescence remains elusive. Methods: The study employed male C57BL/6 N mice and A549 human alveolar epithelial cells to investigate silicosis and its potential treatment. Silicosis was induced in mice via intratracheal instillation of crystalline silica particles, with honokiol administered intraperitoneally for 14 days. Silica-induced senescence in A549 cells was confirmed, and SIRT3 knockout and overexpression cell lines were generated. Various analyses were conducted, including immunoblotting, qRT-PCR, histology, and transmission electron microscopy. Statistical significance was determined using one-way ANOVA with Tukey's post-hoc test. Results: This study elucidates how silica induces ATII cell senescence, emphasizing mtDNA damage. Notably, honokiol (HKL) emerges as a promising anti-senescence and anti-fibrosis agent, acting through sirt3. honokiol effectively attenuated senescence in ATII cells, dependent on sirt3 expression, while mitigating mtDNA damage. Sirt3, a class III histone deacetylase, regulates senescence and mitochondrial stress. HKL activates sirt3, protecting against pulmonary fibrosis and mitochondrial damage. Additionally, HKL downregulated cGAS expression in senescent ATII cells induced by silica, suggesting sirt3's role as an upstream regulator of the cGAS/STING signaling pathway. Moreover, honokiol treatment inhibited the activation of the NF-κB signaling pathway, associated with reduced oxidative stress and mtDNA damage. Notably, HKL enhanced the activity of SOD2, crucial for mitochondrial function, through sirt3-mediated deacetylation. Additionally, HKL promoted the deacetylation activity of sirt3, further safeguarding mtDNA integrity. Conclusions: This study uncovers a natural compound, HKL, with significant anti-fibrotic properties through activating sirt3, shedding light on silicosis pathogenesis and treatment avenues.

Ultrahigh-temperature–pressure experiments are crucial for understanding the physical and chemical properties of matter. The recent development of boron-doped diamond (BDD) heaters has made such melting experiments possible in large-volume presses. However, estimates of temperatures above 2600 K and of the temperature distributions inside BDD heaters are not well constrained, owing to the lack of a suitable thermometer. Here, we establish a three-dimensional finite element model as a virtual thermometer to estimate the temperature and temperature field above 2600 K. The advantage of this virtual thermometer over those proposed in previous studies is that it considers both alternating and direct current heating modes, the actual sizes of cell assemblies after compression, the effects of the electrode, thermocouple and anvil, and the heat dissipation by the pressure-transmitting medium. The virtual thermometer reproduces the power–temperature relationships of ultrahigh-temperature–pressure experiments below 2600 K at press loads of 2.8–7.9 MN (∼19 to 28 GPa) within experimental uncertainties. The temperatures above 2600 K predicted by our virtual thermometer are within the uncertainty of those extrapolated from power–temperature relationships below 2600 K. Furthermore, our model shows that the temperature distribution inside a BDD heater (19–26 K/mm along the radial direction and

Abstract Boulenophrys sangzhiensis and Boulenophrys tuberogranulata, two narrow‐distributed toad species within the Megophryidae family in southern China, are experiencing population declines due to habitat loss and degradation. Despite their critical conservation status, the two species remain largely overlooked in public and scientific spheres. This study presented the first sequencing, assembly, and annotation of the complete mitogenomes of both species using next‐generation sequencing. The mitogenome of B. sangzhiensis was 16,950 bp, while that of B. tuberogranulata was 16,841 bp, each comprising 13 protein‐coding genes (PCGs), 22 transfer RNA genes (tRNAs), two ribosomal RNA genes (rRNAs), and a noncoding control region (D‐loop). The gene content, nucleotide composition, and evolutionary rates of each mitogenome were analyzed. Both mitogenomes exhibited negative AT skew and GC skew with high A + T content. ATP8 exhibited the highest evolutionary rate, while COI had the lowest. A phylogenetic analysis based on 28 mitogenomes revealed two major clades of Megophryidae, supporting the classification of two subfamilies, Megophryinae and Leptobrachiinae. Within the subfamily Megophryinae, the genus Boulenophrys was divided into two species groups. Intriguingly, despite coexisting in Zhangjiajie City, B. sangzhiensis and B. tuberogranulata exhibited distinct origins from the two different species groups, underscoring the unique role of the coexisting area Zhangjiajie in driving their speciation and preserving their current populations. A parallel pattern was also identified in the Leptobrachiinae genus Leptobrachium within the same region. This study provided valuable data references and enhanced our understanding of the molecular characteristics of these threatened amphibian species.

ObjectiveTo determine the efficacy of mechanical thrombectomy combined with prolonged mild hypothermia compared with conventional treatment in managing acute middle cerebral artery occlusion, and to explore whether extending the duration of hypothermia can improve neurological function.MethodFrom 2018 to June 2023, a retrospective analysis was conducted on 45 patients with acute middle cerebral artery occlusion treated at the NICU of Suzhou Kowloon Hospital, affiliated with Shanghai Jiao Tong University School of Medicine. After thrombectomy, patients were admitted to the neurological intensive care unit (NICU) for targeted temperature management. Patients were divided into two groups: the mild hypothermia group (34.5–35.9°C) receiving 5–7 days of treatment, and the normothermia group (control group) whose body temperature was kept between 36 and 37.5°C using pharmacological and physical cooling methods. Baseline characteristics and temperature changes were compared between the two groups of patients. The primary outcome was the modified Rankin Scale (mRS) score at 3 month after surgery, and the secondary outcomes were related complications and mortality rate. Prognostic risk factors were investigated using both univariate and multivariate logistic regression analyses.ResultsAmong 45 patients, 21 underwent prolonged mild hypothermia, and 24 received normothermia, with no significant differences in baseline characteristics between the two groups. The duration of mild hypothermia ranged from 5 to 7 days. The incidence of chills (33.3% vs. 8.3%, p = 0.031) and constipation (57.1% vs. 20.8%, p = 0.028) was significantly higher in the mild hypothermia group compared with the control group. There was no significant difference in mortality rates between the mild hypothermia and the control group (4.76% vs. 8.33%, p = 1.000, OR = 1.75, 95% CI, 0.171–17.949). At 3 month, there was no significant difference in the modified mRS (0–3) score between the mild hypothermia and control groups (52.4% vs. 25%, p = 0.114, OR = 0.477, 95% CI, 0.214–1.066). Infarct core volume was an independent risk factor for adverse neurological outcomes.ConclusionProlonged mild hypothermia following mechanical thrombectomy had no severe complications and shows a trend to improve the prognosis of neurological function. The Infarct core volume on CTP was an independent risk factor for predicting neurological function.

Abstract Background This study aimed to investigate the impact of self-consciousness on depression of college students, and mainly focus on confirming the mediator role of life meaningful and self-efficacy, as well as the moderator role of social support. Methods In the present study, convenient sampling method was adopted, 583 college students were recruited from Harbin city and Wenzhou city in China. All students were assessed using self-assessment scales, including self-consciousness scale, life meaningful scale, self-efficacy scale, social support scale, and self-rating depression scale. Descriptive statistical analysis and correlation analysis, structural equation model analysis were conducted by SPSS 25.0 and M-plus. Results Results showed that self-consciousness was negatively related to depression, life meaningful and self-efficacy partially mediated the relation between self-consciousness and depression. Moderated mediation analysis further indicated that the relation between self-efficacy and depression were moderated bu social support. Compare with college students who had high social support, depression in those with low social support was more susceptible to the effect of self-efficacy. Conclusion These findings imply that college students with low levels of self-consciousness are more easy to be depressive, enhancing their sense of life meaning and self-efficacy can effectively alleviate depression, and college student with high social support can benefit more from self-efficacy. Therefore we should pay more attention to the mental health problems of low levels self-consciousness college students in university.

Abstract Tumor-secreted factors contribute to the development of a microenvironment that facilitates the escape of cancer cells from immunotherapy. In this study, we conduct a retrospective comparison of the proteins secreted by hepatocellular carcinoma (HCC) cells in responders and non-responders among a cohort of ten patients who received Nivolumab (anti-PD-1 antibody). Our findings indicate that non-responders have a high abundance of secreted RNase1, which is associated with a poor prognosis in various cancer types. Furthermore, mice implanted with HCC cells that overexpress RNase1 exhibit immunosuppressive tumor microenvironments and diminished response to anti-PD-1 therapy. RNase1 induces the polarization of macrophages towards a tumor growth-promoting phenotype through activation of the anaplastic lymphoma kinase (ALK) signaling pathway. Targeting the RNase1/ALK axis reprograms the macrophage polarization, with increased CD8+ T- and Th1- cell recruitment. Moreover, simultaneous targeting of the checkpoint protein PD-1 unleashes cytotoxic CD8+ T-cell responses. Treatment utilizing both an ALK inhibitor and an anti-PD-1 antibody exhibits enhanced tumor regression and facilitates long-term immunity. Our study elucidates the role of RNase1 in mediating tumor resistance to immunotherapy and reveals an RNase1-mediated immunosuppressive tumor microenvironment, highlighting the potential of targeting RNase1 as a promising strategy for cancer immunotherapy in HCC.

Abstract To advance the full potential of quantum networks one should be able to distribute quantum resources over long distances at appreciable rates. As a consequence, all components in such networks need to have large multimode capacity to manipulate photonic quantum states. Towards this end, a photonic quantum memory with a large multimode capacity, especially one operating at telecom wavelength, remains an important challenge. Here we optimize the preparation of atomic frequency combs and demonstrate a spectro-temporally multiplexed quantum memory in a 10-m-long cryogenically cooled erbium doped silica fibre. Our multiplexing storage has five spectral channels - each 10 GHz wide with 5 GHz separation - with up to 330 temporal modes in each, thus resulting in a simultaneous storage of 1,650 modes of heralded single photons with a 1000-fold increasing in coincidence detection rate with respect to single mode storage. Our results could pave the way for high speed quantum networks compatible with the infrastructure of fibre optical communication.

By considering the joint effects of the Kelvin–Helmholtz (KH) and Rayleigh–Taylor (RT) instabilities, this paper presents an interpretation of the wavy patterns that occur in explosive welding. It is assumed that the elasticity of the material at the interface effectively determines the wavelength, because explosive welding is basically a solid-state welding process. To this end, an analytical model of elastic hydrodynamic instabilities is proposed, and the most unstable mode is selected in the solid phase. Similar approaches have been widely used to study the interfacial behavior of solid metals in high-energy-density physics. By comparing the experimental and theoretical results, it is concluded that thermal softening, which significantly reduces the shear modulus, is necessary and sufficient for successful welding. The thermal softening is verified by theoretical analysis of the increase in temperature due to the impacting and sliding of the flyer and base plates, and some experimental observations are qualitatively validated. In summary, the combined effect of the KH and RT instabilities in solids determines the wavy morphology, and our theoretical results are in good qualitative agreement with experimental and numerical observations.

Taking CL-20 (Hexanitrohexaazaisowurtzitane)-based aluminized explosives with high gurney energy as the research object, this research experimentally investigates the work capability of different aluminized explosive formulations when driving metal flyer plates in the denotation wave propagation direction. The research results showed that the formulations with 43 μm aluminum (Al) powder particles (The particle sizes of Al powder were in the range of 2∼43 μm) exhibited the optimal performance in driving flyer plates along the denotation wave propagation direction. Compared to the formulations with Al powder 13 μm, the formulations with Al powder 2 μm delivered better performance in accelerating metal flyer plates in the early stage, which, however, turned to be poor in the later stage. The CL-20-based explosives containing 25% Al far under-performed those containing 15% Al. Based on the proposed quasi-isentropic hypothesis, relevant isentropy theories, and the functional relationship between detonation parameters and entropy as well as Al reaction degree, the characteristic lines of aluminized explosives in accelerating flyer plates were theoretically studied, a quasi-isentropic theoretical model for the aluminized explosive driving the flyer plate was built and the calculation methods for the variations of flyer plate velocity, Al reaction degree, and detonation product parameters with time and axial positions were developed. The theoretical model built is verified by the experimental results of the CL-20-based aluminized explosive driving flyer plate. It was found that the model built could accurately calculate the variations of flyer plate velocity and Al reaction degree over time. In addition, how physical parameters including detonation product pressure and temperature varied with time and axial positions was identified. The action time of the positive pressure after the detonation of aluminized explosives was found prolonged and the downtrend of the temperature was slowed down and even reversed to a slight rise due to the aftereffect reaction between the Al powder and the detonation products.

Abstract Background The chloroplast genome (cp genome) is directly related to the study and analysis of molecular phylogeny and evolution of plants in the phylogenomics era. The cp genome, whereas, is highly plastic and exists as a heterogeneous mixture of sizes and physical conformations. It is advantageous to purify/enrich the circular chloroplast DNA (cpDNA) to reduce sequence complexity in cp genome research. Large-insert, ordered DNA libraries are more practical for genomics research than conventional, unordered ones. From this, a technique of constructing the ordered BAC library with the goal-insert cpDNA fragment is developed in this paper. Results This novel in-situ-process technique will efficiently extract circular cpDNA from crops and construct a high-quality cpDNA library. The protocol combines the in-situ chloroplast lysis for the high-purity circular cpDNA with the in-situ substitute/ligation for the high-quality cpDNA library. Individually, a series of original buffers/solutions and optimized procedures for chloroplast lysis in-situ is different than bacterial lysis in-situ; the in-situ substitute/ligation that reacts on the MCE membrane is suitable for constructing the goal-insert, ordered cpDNA library while preventing the large-insert cpDNA fragment breakage. The goal-insert, ordered cpDNA library is arrayed on the microtiter plate by three colonies with the definite cpDNA fragment that are homologous-corresponds to the whole circular cpDNA of the chloroplast. Conclusion The novel in-situ-process technique amply furtherance of research in genome-wide functional analysis and characterization of chloroplasts, such as genome sequencing, bioinformatics analysis, cloning, physical mapping, molecular phylogeny and evolution.

As one of the popular and effective supervised classification methods, linear regression is extensively used in image classification. However, the zero-one labeling matrix is too strict to be conducive to linear regression methods for learning labeling information. In addition, the linear regression focuses only on the fit of the input features to the corresponding output labels and ignores the distinctiveness between the samples. To address these two issues, this paper proposes a new method, namely, discriminative regression with latent label learning, for image classification. In contrast to the other methods, the proposed method learns labeling information in the latent label space instead of the input zero-one labeling space, doing so has the advantage that the proposed method can learn the labeling information in the data more flexibly. To guide the transform matrix to learn the discriminative information in the data, a regularization term with the idea of shortening the distance between samples within a class and lengthening the distance between samples between classes is integrated into the objective function of the proposed method. To obtain the solution of the proposed model, an iterative optimization algorithm is developed. Comprehensive experiments show that the classification performance of the proposed method outperforms the current state-of-the-art methods and deep learning methods on public image datasets with small sample sizes.

As the protective component, steel plate had attracted extensive attention because of frequently threats of explosive loads. In this paper, the evolution of microstructure and the mechanism of damage in the quasi-cracking area of steel plate subjected to explosive load were discussed and the relationships between micro defects and dynamic mechanical response were revealed. After the explosion experiment, five observation points were selected equidistant from the quasi-cracking area of the section of the steel plate along the thickness direction, and the characteristics of micro defects at the observation points were analyzed by optical microscope (OM), scanning electron microscope (SEM) and electron back-scattered diffraction (EBSD). The observation result shows that many slip bands (SBs) appeared, and the grain orientation changed obviously in the steel plate, the two were the main damage types of micro defects. In addition, cracks, peeling pits, grooves and other lager micro defects were appeared in the lower area of the plate. The stress parameters of the observation points were obtained through an effective numerical model. The mechanism of damage generation and crack propagation in the quasi-cracking area were clarified by comparing the specific impulse of each observation point with the corresponding micro defects. The result shows that the generation and expansion of micro defects are related to the stress area (i.e. the upper compression area, the neutral plane area, and the lower tension area). The micro defects gather and expand at the grain boundary, and will become macroscopic damage under the continuous action of tensile stress. Besides, the micro defects at the midpoint of the section of the steel plate in the direction away from the explosion center (i.e. the horizontal direction) were also studied. It was found that the specific impulse at these positions were much smaller than that in the thickness direction, the micro defects were only SBs and a few micro cracks, and the those decreased with the increase of the distance from the explosion center.

AbstractThe genus Sinosenecio B. Nordenstam is a group of perennial or sometimes annual or biennial herbs in the family Asteraceae. Here, we have successfully assembled and characterized the complete chloroplast (cp) genome of S. globigerus, which shows a typical quadratic structure with an overall GC content of 37.4%, comprising a pair of inverted repeat regions (IRs) of 24,848 bp, a large single-copy region (LSC) of 83,379 bp and a small single-copy region (SSC) of 18,180 bp. 133 genes were annotated, including 88 protein-coding genes, 37 tRNA genes and eight rRNA genes. Further nucleotide diversity analysis indicated that three genomic regions (accD-psaI, trnK-rps16, and ycf1) exhibited sufficient variability and thus could be recommended as valuable barcodes for the delimitation and identification of Sinosenecio species. Phylogenetic reconstruction presented clear interspecific relationships within Sinosenecio, which were supported to some extent by cytology, morphology and geographic distributions. Our study will provide valuable and high-quality genetic information to further elucidate the diversified mechanisms in Sinosenecio.

Grain weight is one of the key components of wheat (Triticum aestivum L.) yield. Genetic manipulation of grain weight is an efficient approach for improving yield potential in breeding programs. A recombinant inbred line (RIL) population derived from a cross between W7268 and Chuanyu 12 (CY12) was employed to detect quantitative trait loci (QTLs) for thousand-grain weight (TGW), grain length (GL), grain width (GW), and the ratio of grain length to width (GLW) in six environments. Seven major QTLs, QGl.cib-2D, QGw.cib-2D, QGw.cib-3B, QGw.cib-4B.1, QGlw.cib-2D.1, QTgw.cib-2D.1 and QTgw.cib-3B.1, were consistently identified in at least four environments and the best linear unbiased estimation (BLUE) datasets, and they explained 2.61 to 34.85% of the phenotypic variance. Significant interactions were detected between the two major TGW QTLs and three major GW loci. In addition, QTgw.cib-3B.1 and QGw.cib-3B were co-located, and the improved TGW at this locus was contributed by GW. Unlike other loci, QTgw.cib-3B.1/QGw.cib-3B had no effect on grain number per spike (GNS). They were further validated in advanced lines using Kompetitive Allele Specific PCR (KASP) markers, and a comparison analysis indicated that QTgw.cib-3B.1/QGw.cib-3B is likely a novel locus. Six haplotypes were identified in the region of this QTL and their distribution frequencies varied between the landraces and cultivars. According to gene annotation, spatial expression patterns, ortholog analysis and sequence variation, the candidate gene of QTgw.cib-3B.1/QGw.cib-3B was predicted. Collectively, the major QTLs and KASP markers reported here provide valuable information for elucidating the genetic architecture of grain weight and for molecular marker-assisted breeding in grain yield improvement.

Steel-like density HfZrTiTa0.2Al0.8 high entropy alloy (HEA) with a density of 7.78 g/cm3 is designed and fabricated as a novel energetic structural material (ESM). The microstructure, thermal analysis, compressive mechanical properties, ignition and energy release under dynamic loading are systemically investigated. The experimental results show that the HfZrTiTa0.2Al0.8 HEA has a single BCC solid solution structure, and spinodal decomposition with elements segregation in the nanoscale is observed. Thermal analysis shows the HEA keeps stable in the Ar atmosphere and the oxidizing reaction occurs in the Air atmosphere. The mechanical properties show brittle characteristics with maximum strength with 1520 MPa and fracture strain 0.07 and strain rate effect from 0.001s−1 to 3000s−1 is observed. Under high strain rate loading, the fracture-induced spark is observed, which is caused by an oxidizing reaction due to the rise. By direct ballistic test, the energy release velocity threshold is measured as 980 m/s, and the energy release intensity is more violent in higher velocity impact conditions. Moreover, the impact reaction degree is increased with increasing fragmentation degree and adiabatic temperature rise induced by impact. The designed HEA-ESM is a promising candidate that simultaneously possesses both high strength, high reactive heat and excellent energetic characteristics in the application field of high-strength ESM fragment.

Copper/stainless steel composite is often used for preparation of superconducting busbar “double box” lap joints. However, it is a challenge for the large thickness T2 copper/316L stainless steel composite is fabricated by explosive welding, because of the bonding interface is always present many problems such as large ripple size, many microscopic defects, low bonding strength and poor sealing etc. In this paper, the big-thickness T2 copper/316L stainless steel composite with small size wavy interface was successfully fabricated by explosive welding. Microstructure of bonding interface indicated that the welding process could be divided into three stages: detonation growth stage, detonation stabilization stage, detonation descent stage. The morphology of bonding interface presented a regular wavy interface and no defects such as cracks, voids and intermetallic compound were formed in the stable stage, which was consistent with the results of ultrasonic and permeability quality inspection. The hardness of copper side and stainless steel side close to the bonding interface reached 131HV and 432HV, respectively. Dynamic recrystallization and fine grain generated in the bonding interface. The mechanical properties of tensile strength, pull-off strength and shear strength in the stable detonation stage is greater than 110 MPa, which is meeting the requirements of preparation of superconducting busbar “double box” lap joints. The deformation failure mainly occurred in the copper side near the bonding interface, which presented a higher bonding strength than copper. Some dimples and tearing edges with different sizes on the fracture surfaces, indicating that the fracture was a typical ductile fracture.

CD36 is a highly glycosylated integral membrane protein that belongs to the scavenger receptor class B family and regulates the pathological progress of metabolic diseases. CD36 was recently found to be widely expressed in various cell types in the nervous system, including endothelial cells, pericytes, astrocytes, and microglia. CD36 mediates a number of regulatory processes, such as endothelial dysfunction, oxidative stress, mitochondrial dysfunction, and inflammatory responses, which are involved in many central nervous system diseases, such as stroke, Alzheimer’s disease, Parkinson’s disease, and spinal cord injury. CD36 antagonists can suppress CD36 expression or prevent CD36 binding to its ligand, thereby achieving inhibition of CD36-mediated pathways or functions. Here, we reviewed the mechanisms of action of CD36 antagonists, such as Salvianolic acid B, tanshinone IIA, curcumin, sulfosuccinimidyl oleate, antioxidants, and small-molecule compounds. Moreover, we predicted the structures of binding sites between CD36 and antagonists. These sites can provide targets for more efficient and safer CD36 antagonists for the treatment of central nervous system diseases.

Pattern-illuminated Fourier ptychography (piFP) is an elegant combination of structured illumination imaging and a Fourier ptychographic algorithm with the ability to image beyond the diffraction limit of the employed optics. Artifact-free piFP super-resolution reconstruction requires a high level of stability in the illumination pattern. However, unpredictable pattern variation occurs in the presence of environment perturbation, intensity fluctuation, and pointing instability at the source, leading to declines in image reconstruction quality. To address this issue, we present an efficient and robust piFP algorithm based on low-rank approximation (LRA-piFP), which relaxes the requirement for the stability of illumination patterns. This LRA-piFP method can model frame-wise pattern variation during a full scan, thus improve the reconstruction quality significantly. We take numerical simulations and proof-of-principle experiments with both long-range imaging and microscopy for demonstrations. Results show that the LRA-piFP method can handle different kinds of pattern variation and outperforms other state-of-the-art techniques in terms of reconstruction quality and resolution improvement. Our method provides effective experimental robustness to piFP with a natural algorithmic extension, paving the way for its application in both macroscopic and microscopic imaging.

Abstract Mechanically robust hydrogel fibers have demonstrated great potential in energy dissipation and shock‐absorbing applications. However, developing such materials that are recyclable, energy‐efficient, and environmentally friendly remains an enormous challenge. Herein, inspired by spider silk, a continuous and scalable method is introduced for spinning a polyacrylamide hydrogel microfiber with a hierarchical sheath‐core structure under ambient conditions. Applying pre‐stretch and twist in the as‐spun hydrogel microfibers results in a tensile strength of 525 MPa, a toughness of 385 MJ m−3, and a damping capacity of 99%, which is attributed to the reinforcement of hydrogen‐bond nanoclusters within the microfiber matrix. Moreover, it maintains both structural and mechanical stability for several days, and can be directly dissolved in water, providing a sustainable spinning dope for re‐spinning into new microfibers. This work provides a new strategy for the spinning of robust and recyclable hydrogel‐based fibrous materials.

Abstract Aspirin, also named acetylsalicylate, can directly acetylate the side‐chain of lysine in protein, which leads to the possibility of unexplained drug effects. Here, the study used isotopic‐labeling aspirin‐d3 with mass spectrometry analysis to discover that aspirin directly acetylates 10 HDACs proteins, including SIRT1, the most studied NAD+‐dependent deacetylase. SIRT1 is also acetylated by aspirin in vitro. It is also identified that aspirin directly acetylates lysine 408 of SIRT1, which abolishes SIRT1 deacetylation activity by impairing the substrates binding affinity. Interestingly, the lysine 408 of SIRT1 can be acetylated by CBP acetyltransferase in cells without aspirin supplement. Aspirin can inhibit SIRT1 to increase the levels of acetylated p53 and promote p53‐dependent apoptosis. Moreover, the knock‐in mice of the acetylation‐mimic mutant of SIRT1 show the decreased production of pro‐inflammatory cytokines and maintain intestinal immune homeostasis. The study indicates the importance of the acetylated internal functional site of SIRT1 in maintaining intestinal immune homeostasis.

[Abstract]: Objective: This study aimed to investigate the relationship between methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism and early neurological deterioration (END) in patients with acute ischemic stroke (AIS) and any possible interactions between specific MTHFR alleles and traditional risk factors among a Han Chinese cohort. Methods: 434 AIS patients were consecutively recruited between January 2017 and June 2019, including 129 END and 305 non-END cases. A candidate gene association study design was used to analyze the association between MTHFR gene polymorphism and END risk. The polymerase chain reaction-restriction fragment length polymorphism (RFLP) method was employed to genotype the MTHFR C677T polymorphism. The interactional analyses were performed using the multifactor dimensionality reduction test. Results: Hyperglycemia (odds ratio [OR]: 2.410, 95 % confidence interval [CI]: 1.436–4.046, p = 0.001), neurological function impairment (NIHSS score >5) (OR: 2.158, 95%CI: 1.337–3.484, p = 0.002) on admission, and hyperhomocysteinemia (HHcy) (OR: 2.570, 95%CI: 1.229–5.376, p = 0.012) were independently associated with END. The TT genotype (OR: 1.710, 95%CI: 1.021–2.863, p = 0.043) and T allele (OR: 1.710, 95%CI: 1.021–2.863, p = 0.043) of this C677T polymorphism were associated with susceptibility to END, and the TT genotype was more common in the subjects with HHcy (OR: 2.525, 95%CI: 1.111–5.739, P = 0.023). In addition, we also found interactions for END risk between the C677T polymorphism and traditional risk factors for END, including: hyperglycemia on admission, drinking, and moderate to severe neurological deficits (OR 1.237, 95 % CI 0.227–6.734), although the results were not statistically significant (p = 0.806). Conclusions: Our results show a possible association between MTHFR C677T polymorphism and gene–environment interactions with END susceptibility in a Han Chinese cohort.

BackgroundWhile increasing concerns arise about the health effects of environmental pollutants, the relationship between blood manganese (Mn) and sarcopenia has yet to be fully explored in the general population.ObjectiveThis study aims to investigate the association between blood manganese (Mn) levels and sarcopenia in adults.MethodsIn our study, we evaluated 8,135 individuals aged 18–59 years, utilizing data from the National Health and Nutrition Examination Survey (NHANES) spanning 2011 to 2018. We employed generalized additive model (GAM) to discern potential non-linear relationships and utilized the two-piecewise linear regression model to probe the association between blood Mn levels and sarcopenia.ResultsAfter adjusting for potential confounders, we identified non-linear association between blood Mn levels and sarcopenia, with an inflection point at 13.45 μg/L. The effect sizes and the confidence intervals on the left and right sides of the inflection point were 1.006 (0.996 to 1.048) and 1.082 (1.043 to 1.122), respectively. Subgroup analysis showed that the effect sizes of blood Mn on sarcopenia have significant differences in gender and different BMI groups.ConclusionOur results showed that a reverse U-shaped curve between blood Mn levels and sarcopenia, with an identified the inflection point at blood Mn level of 13.45 μg/L.

BackgroundThere is a dearth of feasibility assessments regarding using large language models (LLMs) for responding to inquiries from autistic patients within a Chinese-language context. Despite Chinese being one of the most widely spoken languages globally, the predominant research focus on applying these models in the medical field has been on English-speaking populations. ObjectiveThis study aims to assess the effectiveness of LLM chatbots, specifically ChatGPT-4 (OpenAI) and ERNIE Bot (version 2.2.3; Baidu, Inc), one of the most advanced LLMs in China, in addressing inquiries from autistic individuals in a Chinese setting. MethodsFor this study, we gathered data from DXY—a widely acknowledged, web-based, medical consultation platform in China with a user base of over 100 million individuals. A total of 100 patient consultation samples were rigorously selected from January 2018 to August 2023, amounting to 239 questions extracted from publicly available autism-related documents on the platform. To maintain objectivity, both the original questions and responses were anonymized and randomized. An evaluation team of 3 chief physicians assessed the responses across 4 dimensions: relevance, accuracy, usefulness, and empathy. The team completed 717 evaluations. The team initially identified the best response and then used a Likert scale with 5 response categories to gauge the responses, each representing a distinct level of quality. Finally, we compared the responses collected from different sources. ResultsAmong the 717 evaluations conducted, 46.86% (95% CI 43.21%-50.51%) of assessors displayed varying preferences for responses from physicians, with 34.87% (95% CI 31.38%-38.36%) of assessors favoring ChatGPT and 18.27% (95% CI 15.44%-21.10%) of assessors favoring ERNIE Bot. The average relevance scores for physicians, ChatGPT, and ERNIE Bot were 3.75 (95% CI 3.69-3.82), 3.69 (95% CI 3.63-3.74), and 3.41 (95% CI 3.35-3.46), respectively. Physicians (3.66, 95% CI 3.60-3.73) and ChatGPT (3.73, 95% CI 3.69-3.77) demonstrated higher accuracy ratings compared to ERNIE Bot (3.52, 95% CI 3.47-3.57). In terms of usefulness scores, physicians (3.54, 95% CI 3.47-3.62) received higher ratings than ChatGPT (3.40, 95% CI 3.34-3.47) and ERNIE Bot (3.05, 95% CI 2.99-3.12). Finally, concerning the empathy dimension, ChatGPT (3.64, 95% CI 3.57-3.71) outperformed physicians (3.13, 95% CI 3.04-3.21) and ERNIE Bot (3.11, 95% CI 3.04-3.18). ConclusionsIn this cross-sectional study, physicians’ responses exhibited superiority in the present Chinese-language context. Nonetheless, LLMs can provide valuable medical guidance to autistic patients and may even surpass physicians in demonstrating empathy. However, it is crucial to acknowledge that further optimization and research are imperative prerequisites before the effective integration of LLMs in clinical settings across diverse linguistic environments can be realized. Trial RegistrationChinese Clinical Trial Registry ChiCTR2300074655; https://www.chictr.org.cn/bin/project/edit?pid=199432

Accurately predicting the production rate and estimated ultimate recovery (EUR) of shale oil wells is vital for efficient shale oil development. Although numerical simulations provide accurate predictions, their high time, data, and labor demands call for a swifter, yet precise, method. This study introduces the Duong–CNN–LSTM (D-C-L) model, which integrates a convolutional neural network (CNN) with a long short-term memory (LSTM) network and is grounded on the empirical Duong model for physical constraints. Compared to traditional approaches, the D-C-L model demonstrates superior precision, efficiency, and cost-effectiveness in predicting shale oil production.

BackgroundA growing body of evidence suggests that immunological processes have a significant role in developing idiopathic sudden sensorineural hearing loss (SSHL). However, few studies have examined the association between immune cell phenotype and SSHL using Mendelian Randomization (MR).MethodsThe online genome-wide association studies (GWAS) database was used to compile data from GWAS covering 731 immunophenotypes and SSHL. Inverse variance weighted (IVW) analysis was primarily used for MR study, and single nucleotide polymorphisms (SNPs) associated with immunophenotypes served as dependent variables. A sensitivity study and the false discovery rate (FDR) correction were used to examine the MR hypothesis. In addition, the possibility of reverse causality between immunophenotype and SSHL was validated by reverse MR. Reverse MR was analyzed in a manner consistent with forward MR.ResultsAfter FDR correction and sensitivity analysis, we screened 7 immunophenotypes, including IgD+ CD38dim %lymphocyte (95% CI: 1.0019, 1.0742, p = 3.87 × 10−2, FDR = 1.15 × 10−2); Unsw mem AC (95% CI: 1.004, 1.2522, p = 4.23 × 10−2, FDR = 2.25 × 10−2); CD86+ myeloid DC AC (95% CI: 1.0083, 1.1147, p = 2.24 × 10−2, FDR = 4.27 × 10−2); CD33dim HLA DR− AC (95% CI: 1.0046, 1.0583, p = 2.12 × 10−2, FDR = 4.69 × 10−2); SSC-A on CD8br (95% CI: 1.0028, 1.1461, p = 4.12 × 10−2, FDR = 4.71 × 10−2); CD45RA− CD4+ %T cell (95% CI: 1.0036, 1.0503, p = 2.32 × 10−2, FDR = 4.82 × 10−2); DP (CD4+CD8+) AC (95% CI: 1.011, 1.2091, p = 2.78 × 10−2, FDR = 4.97 × 10−2). There was a strong causal relationship with SSHL onset, and the reliability of the results was verified. Furthermore, the immunological cell profile and SSHL did not appear to be closely associated, as shown by reverse MR analysis.ConclusionOur study provides more support for the current hypothesis that immunophenotypes and the pathophysiology of SSHL are closely associated. Further validation is needed to assess the role of these immunophenotypes in SSHL.

Abstract Abnormal activation of the intestinal mucosal immune system, resulting from damage to the intestinal mucosal barrier and extensive invasion by pathogens, contributes to the pathogenesis of inflammatory bowel disease (IBD). Current first‐line treatments for IBD have limited efficacy and significant side effects. An innovative H2S‐releasing montmorillonite nanoformulation (DPs@MMT) capable of remodeling intestinal mucosal immune homeostasis, repairing the mucosal barrier, and modulating gut microbiota is developed by electrostatically adsorbing diallyl trisulfide‐loaded peptide dendrimer nanogels (DATS@PDNs, abbreviated as DPs) onto the montmorillonite (MMT) surface. Upon rectal administration, DPs@MMT specifically binds to and covers the damaged mucosa, promoting the accumulation and subsequent internalization of DPs by activated immune cells in the IBD site. DPs release H2S intracellularly in response to glutathione, initiating multiple therapeutic effects. In vitro and in vivo studies have shown that DPs@MMT effectively alleviates colitis by eliminating reactive oxygen species (ROS), inhibiting inflammation, repairing the mucosal barrier, and eradicating pathogens. RNA sequencing revealed that DPs@MMT exerts significant immunoregulatory and mucosal barrier repair effects, by activating pathways such as Nrf2/HO‐1, PI3K‐AKT, and RAS/MAPK/AP‐1, and inhibiting the p38/ERK MAPK, p65 NF‐κB, and JAK‐STAT3 pathways, as well as glycolysis. 16S rRNA sequencing demonstrated that DPs@MMT remodels the gut microbiota by eliminating pathogens and increasing probiotics. This study develops a promising nanoformulation for IBD management.

Currently, the energy dissipation efficiency of intermediate column dampers is extremely low, and traditional lever amplification damping systems occupy a large space in buildings. Aiming at solving these problems, this paper puts forward a new intermediate column–lever negative stiffness viscous damper (CLNVD), which has the characteristics of small impact on building space and significant amplification of the damper displacement. The CLNVD consists of the following four parts: the viscous damper, the negative stiffness device, the lever, and the intermediate column. This paper introduces the displacement amplification coefficient (fd) to assess the CLNVD’s displacement amplification effect and introduces the energy dissipation coefficient (fE) to assess the CLNVD’s energy dissipation effect. The expressions for fd and fE are derived according to the geometric magnification coefficient and effective displacement factor. Moreover, the impacts of multiple factors including the CLNVD’s position, the lever’s amplification coefficient, the bending line stiffness of beam, the negative stiffness, the damping coefficient, the damping index, and the inter-story displacement on the CLNVD’s fd and fE are elaborated. The analysis results reveal the following: when the CLNVD is located in the middle of the span, the fd and fE of the CLNVD will be maximized, and fE will increase first and then decrease as the beam’s bending line stiffness increases. Meanwhile, the amplification capability of the CLNVD increases as the lever’s amplification coefficient χ rises. When the negative stiffness does not exist, there exists an optimum lever’s amplification coefficient χ that maximizes fE. When the combination of damping coefficient c and index α satisfies a specific relationship, fE of the CLNVD reaches its largest value. When the negative stiffness and the loss stiffness of VD are within the region proposed in this paper, the CLNVD will achieve a higher fd and avoid providing significant negative stiffness. Subsequently, this paper proposes an optimization design method of the CLNVD. Finally, the amplification effect of CLNVD as well as the effectiveness of its optimization design method are verified through examples. In the case study, the CLNVD offers a larger damping ratio under the circumstance of fortification earthquakes. Under fortification and rare earthquakes, the inter-story displacement of Scheme 1 has been decreased by half roughly. According to the above-mentioned results, the CLNVD provides a brand-new approach for designers in the seismic design of buildings. Furthermore, this paper will provide beneficial reference for the damping design of other amplification devices equipped with negative stiffness dampers.

The recovery of scandium (Sc) from highly acidic industrial effluents is currently hindered by the use of large quantities of flammable and toxic organic solvents. This study developed an extraction system using ionic liquids (ILs) and phenylphosphinic acid (PPAH) as diluents and an extractant, respectively, to selectively recover Sc from the aqueous phase. The effect of IL chemical structure, aqueous pH and temperature on the extraction of Sc was systematically investigated and the findings revealed that ILs with longer alkyl side chains had reduced Sc extraction ability due to the presence of continuous nonpolar domains formed by the self-aggregation of the IL alkyl side chain. The IL/PPAH system maintained high extraction ability toward Sc across a wide temperature range (288 K to 318 K) and the extraction efficiency of Sc could be improved significantly by increasing the aqueous pH. The extraction process involved proton exchange, resulting in the formation of a metal−ligand complex (Sc(PPA)3).