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Abstract Species with different genetic backgrounds exhibit distinct metabolic traits. Nine beef cattle were selected for the experiment to study changes in serum metabolic phenotypes, rumen microbiota diversity, and composition in beef cattle from different genetic backgrounds. Three groups were Chinese Simmental (S group), Simmental×Chinese Holstein (SH group), and Simmental × Mongolian (SM group) cattle. We used ELISA to detect serum biochemical indicators. The Short-chain fatty acids (SCFAs) in the rumen were examined, and a significant difference was observed in the acetic acid content of the three experimental groups (p

Fenofibrate, a peroxisome proliferator-activated receptor α (PPARα) agonist, is widely prescribed for hyperlipidemia management. Recent studies also showed that it has therapeutic potential in various liver diseases. However, its effects on hepatomegaly and liver regeneration and the involved mechanisms remain unclear. Here, the study showed that fenofibrate significantly promoted liver enlargement and regeneration post-partial hepatectomy in mice, which was dependent on hepatocyte-expressed PPARα. Yes-associated protein (YAP) is pivotal in manipulating liver growth and regeneration. We further identified that fenofibrate activated YAP signaling by suppressing its K48-linked ubiquitination, promoting its K63-linked ubiquitination, and enhancing the interaction and transcriptional activity of the YAP–TEAD complex. Pharmacological inhibition of YAP–TEAD interaction using verteporfin or suppression of YAP using AAV Yap shRNA in mice significantly attenuated fenofibrate-induced hepatomegaly. Other factors, such as MYC, KRT23, RAS, and RHOA, might also participate in fenofibrate-promoted hepatomegaly and liver regeneration. These studies demonstrate that fenofibrate-promoted liver enlargement and regeneration are PPARα-dependent and partially through activating the YAP signaling, with clinical implications of fenofibrate as a novel therapeutic agent for promoting liver regeneration.

Abstract Background The relationship between variation in serum uric acid (SUA) levels and brain health is largely unknown. This study aimed to examine the associations of long-term variability in SUA levels with neuroimaging metrics and cognitive function. Methods This study recruited 1111 participants aged 25–83 years from a multicenter, community-based cohort study. The SUA concentrations were measured every two years from 2006 to 2018. We measured the intraindividual SUA variability, including the direction and magnitude of change by calculating the slope value. The associations of SUA variability with neuroimaging markers (brain macrostructural volume, microstructural integrity, white matter hyperintensity, and the presence of cerebral small vessel disease) and cognitive function were examined using generalized linear models. Mediation analyses were performed to assess whether neuroimaging markers mediate the relationship between SUA variation and cognitive function. Results Compared with the stable group, subjects with increased or decreased SUA levels were all featured by smaller brain white matter volume (beta = − 0.25, 95% confidence interval [CI] − 0.39 to − 0.11 and beta = − 0.15, 95% CI − 0.29 to − 0.02). Participants with progressively increased SUA exhibited widespread disrupted microstructural integrity, featured by lower global fractional anisotropy (beta = − 0.24, 95% CI − 0.38 to − 0.10), higher mean diffusivity (beta = 0.16, 95% CI 0.04 to 0.28) and radial diffusivity (beta = 0.19, 95% CI 0.06 to 0.31). Elevated SUA was also associated with cognitive decline (beta = − 0.18, 95% CI − 0.32 to − 0.04). White matter atrophy and impaired brain microstructural integrity mediated the impact of SUA increase on cognitive decline. Conclusions It is the magnitude of SUA variation rather than the direction that plays a critical negative role in brain health, especially for participants with hyperuricemia. Smaller brain white matter volume and impaired microstructural integrity mediate the relationship between increased SUA level and cognitive function decline. Long-term stability of SUA level is recommended for maintaining brain health and preventing cognitive decline.

Cancer has a significant negative social and economic impact on both developed and developing countries. As a result, understanding the onset and progression of cancer is critical for developing therapies that can improve the well-being and health of individuals with cancer. With time, study has revealed, the tumor microenvironment has great influence on this process. Micro and nanoscale engineering techniques can be used to study the tumor microenvironment. Nanoscale and Microscale engineering use Novel technologies and designs with small dimensions to recreate the TME. Knowing how cancer cells interact with one another can help researchers develop therapeutic approaches that anticipate and counteract cancer cells' techniques for evading detection and fighting anti-cancer treatments, such as microfabrication techniques, microfluidic devices, nanosensors, and nanodevices used to study or recreate the tumor microenvironment. Nevertheless, a complicated action just like the growth and in cancer advancement, and their intensive association along the environment around it that has to be studied in more detail.

Short-term residential load forecasting (STRLF) holds great significance for the stable and economic operation of distributed power systems. Different households in the same region may exhibit similar consumption patterns owing to the analogous environmental parameters. Incorporating the spatiotemporal correlations can enhance the load forecasting performance of individual households. To this end, a spatiotemporal graph attention (STGA)-enabled Transformer is proposed for multivariate, multi-step residential load forecasting in this paper. Specifically, the multiple residential loads are cast to a graph and a Transformer with a graph sequence-to-sequence (Seq2Seq) structure is employed to model the multi-step load forecasting problem. Gated fusion-based STGA blocks are embedded in the encoder and decoder of the Transformer to extract dynamic spatial correlations and non-linear temporal patterns among multiple residential loads. A transform attention block is further designed to transfer historical graph observations into future graph predictions and alleviate the error propagation between the encoder and decoder. The embedding of multiple attention modules in the Seq2Seq framework allows us to capture the spatiotemporal correlations between residents and achieve confident inference of load values several steps ahead. Numerical simulations on residential data from three different regions demonstrate that the developed Transformer method improves multi-step load forecasting by 14.7% at least, compared to the state-of-the-art benchmarks.

Portland cement has a limited shelf life because of the prehydration that can occur during storage. One approach to mitigating strength losses observed for concrete is to pretreat cement with a protective coating to slow the advance of prehydration. This study compared cement pretreatments with alkyl ketene dimer (AKD) wax and a combination of AKD + paraffin wax to a more traditional pretreatment approach using oleic acid. After exposing the treated cements to elevated temperature and humidity conditions, paste and mortar calorimetry tests showed improved resistance to prehydration reactions. The cements aged up to 12 weeks under the accelerated regime showed strength improvement for the mortars made with AKD and AKD + paraffin-treated cements relative to the mortars made with oleic acid-treated cement and mortars made with untreated cement. The wax can be added during clinker milling and additionally functions as a grinding aid.

Abstract In individuals with acne vulgaris, alterations occur in serum metabolite composition, yet the exact causal link between these metabolites and acne development remains elusive. Using genome-wide association datasets, we performed bidirectional Mendelian randomization (MR) to investigate the potential causal relationship between 309 serum metabolites and acne vulgaris. We performed sensitivity analysis to evaluate the presence of heterogeneity and pleiotropy. Forward MR analysis found 14 serum metabolites significantly associated with acne vulgaris, and reverse MR analysis found no significant association between acne vulgaris and these serum metabolites. Through validation using data from the FinnGen database of acne vulgaris studies, we found a conclusive and significant correlation between stearoylcarnitine and acne vulgaris. This provides new evidence in the search for new targets for the treatment of acne vulgaris.

Abstract African swine fever virus (ASFV) is a highly pathogenic and rapidly disseminated virus with strong viability in the environment, suggesting the importance of environmental detection for prevention and control in all the pig industry. However, the detection results of environmental swabs cannot always reflect the accurate status of viral pollution, leading to persistent ASFV environmental contamination. In this study, we developed an ASFV eluant with higher environmental ASFV detection efficiency relative to 0.85% saline solution, which obtains the patent certificate issued by the China Intellectual Property Office (patent number:202010976050.9). qPCR analysis showed that in the environmental swab samples, the number of viral copies was 100 times higher for the ASFV eluant treatment than the traditional eluant treatment (0.85% saline solution). And besides, the high sensitivity of the ASFV eluant had be verified in a slaughterhouse environmental sampling detection. In soil samples, the ASFV eluent showed the same extraction effect as the TIANamp Soil DNA Kit, in contrast to no extraction effect for 0.85% saline solution. Simultaneously, this eluent could protect ASFV from degradation and allow the transportation of samples at ambient temperature without refrigeration. In clinical practice, we monitored the environmental contamination condition of the ASFV in a large-scale pig farm. The results shown that the ASFV load decreased after every disinfection in environment. This study provides an effective solution for surveilling the potential threat of ASFV in environment.

In fractured geothermal reservoirs, the fracture networks and internal fluid flow behaviors can significantly impact the thermal performance. In this study, we proposed a non-Darcy rough discrete fracture network (NR-DFN) model that can simultaneously consider the fracture evolution and non-Darcy flow dynamics in studying the thermo-hydro-mechanical (THM) coupling processes for heat extraction in geothermal reservoir. We further employed the model on the Habanero enhanced geothermal systems (EGS) project located in Australia. First, our findings illustrate a clear spatial-temporal variation in the thermal stress and pressure perturbations, as well as uneven spatial distribution of shear failure in 3D fracture networks. Activated shear failure is mainly concentrated in the first fracture cluster. Secondly, channeling flow have also been observed in DFNs during heat extraction and are further intensified by the expansion of fractures driven by thermal stresses. Moreover, the combined effect of non-Darcy flow and fracture evolution triggers a rapid decline in the resulting heat rate and temperature. The NR-DFN model framework and the Habanero EGS’s results illustrate the importance of both fracture evolution and non-Darcy flow on the efficiency of EGS production and have the potential to promote the development of more sustainable and efficient EGS operations for stakeholders.

The Sulige tight sandstone gas reservoir is marked by low permeability, intricate pore structures, and notable lateral heterogeneity, making it difficult to predict the productivity of fractured horizontal wells in the reservoir. In this study, a productivity prediction model for fractured horizontal wells is developed based on the characteristics of the Sulige gas reservoir, including its high start-up pressure gradient, strong stress sensitivity, obvious non-Darcy flow, and typical slippage and diffusion effects. This new model fully accounts for each hydraulic fracture in the horizontal wells based on the superposition principle and Green's function. This model facilitates efficient productivity calculations and enables rapid quantitative analysis of the influencing factors specific to horizontal wells with hydraulic fractures, fully integrating the specific characteristics of the Sulige gas field. The accuracy of this model is tested against field data from Wells LX1 and LX2 in the Sulige field, indicating good agreement between the predicted values and field data. Well LX2 is used as a case study to analyze the influences of geological and engineering factors on well productivity. The following conclusions are drawn: 1) Well productivity is notably influenced by the start-up pressure gradient and stress sensitivity, with a minor impact from non-Darcy effects. 2) Productivity linearly decreases with increased hydraulic fracture spacing. 3) Productivity increases, and the increment rate gradually decreases, with increases in the length and conductivity of the hydraulic fractures. This model provides valuable guidance on predicting productivity in tight sandstone gas reservoirs, such as that of the Sulige gas field.

Secure cognitive radio (SCR) system based on reconfigurable intelligent surface (RIS) assumes that secondary user (SU) and primary user (PU) locate on the same side of the base station (BS), which can only cover part of the communication area and limits the deployment flexibility and effectiveness of the RIS.In order to solve the above problem, a new SCR system based on simultaneously transmitting and reflecting surface (STARS) was proposed.In the system, STARS could achieve full coverage of communication area, improve the received signal strength of the SU with the transmission beamforming vector and reduce the interference of the SU to the PU with the reflection beamforming vector, which provided new optimization degree of freedom (DoF) for the design of the SCR system.Considering secrecy rate constraint of the SU, interference power constraint (IPC) of the PU and transmission/reflection parameters constraint of the STARS, BS active beamforming vector and STARS transmission/reflection beamforming vectors were jointly optimized to minimize the BS’s transmit power from the perspective of reducing the total power consumption of the system.The minimization problem is a variable coupling non-convex problem, which is difficult to tackle directly.An alternating optimization (AO) algorithm based on difference-of-convex relaxation (DCR) method and sequential rank-one constraint relaxation (SROCR) method was proposed to jointly design the BS active beamforming vector and STARS transmission/reflection beamforming vectors.Simulation results show that the proposed algorithm has good convergence performance and effectively reduces the interference of SU on PU.Compared with the traditional RIS, random phase, maximum-ratio transmission (MRT) and equal energy splitting (Equal ES) schemes, the BS transmitting power is reduced by 8.3%, 15.4%, 5.9% and 5.3%, respectively.

Information and communication technologies enable the transformation of traditional energy systems into cyber-physical energy systems (CPESs), but such systems have also become popular targets of cyberattacks. Currently, available methods for evaluating the impacts of cyberattacks suffer from limited resilience, efficacy, and practical value. To mitigate their potentially disastrous consequences, this study suggests a two-stage, discrepancy-based optimization approach that considers both preparatory actions and response measures, integrating concepts from social computing. The proposed Kullback-Leibler divergence-based, distributionally robust optimization (KDR) method has a hierarchical, two-stage objective function that incorporates the operating costs of both system infrastructures (e.g., energy resources, reserve capacity) and real-time response measures (e.g., load shedding, demand-side management, electric vehicle charging station management). By incorporating social computing principles, the optimization framework can also capture the social behavior and interactions of energy consumers in response to cyberattacks. The preparatory stage entails day-ahead operational decisions, leveraging insights from social computing to model and predict the behaviors of individuals and communities affected by potential cyberattacks. The mitigation stage generates responses designed to contain the consequences of the attack by directing and optimizing energy use from the demand side, taking into account the social context and preferences of energy consumers, to ensure resilient, economically efficient CPES operations. Our method can determine optimal schemes in both stages, accounting for the social dimensions of the problem. An original disaster mitigation model uses an abstract formulation to develop a risk-neutral model that characterizes cyberattacks through KDR, incorporating social computing techniques to enhance the understanding and response to cyber threats. This approach can mitigate the impacts more effectively than several existing methods, even with limited data availability. To extend this risk-neutral model, we incorporate conditional value at risk as an essential risk measure, capturing the uncertainty and diverse impact scenarios arising from social computing factors. The empirical results affirm that the KDR method, which is enriched with social computing considerations, produces resilient, economically efficient solutions for managing the impacts of cyberattacks on a CPES. By integrating social computing principles into the optimization framework, it becomes possible to better anticipate and address the social and behavioral aspects associated with cyberattacks on CPESs, ultimately improving the overall resilience and effectiveness of the system's response measures.

The reversible CO2 absorption/desorption of lithium orthosilicate (Li4SiO4) sorbents holds potential for high temperature capture of CO2 from hot flue gases, sorption-enhanced reforming and solar thermochemical energy storage. In this study, we have prepared a series of Li4SiO4 sorbents using a combination of K2CO3 addition and dry ball-milling procedure to improve the relatively slow kinetics under low CO2 partial pressure conditions. The synergistic effects of dry ball-milling and K2CO3 addition on the intrinsic properties of Li4SiO4 sorbents were explored by thermogravimetric analysis and structural characterizations. Thermogravimetric analysis indicate that the highest CO2 uptakes were achieved with dry ball-milling combined with K2CO3 physical addition. The structural characterizations further reveal that this sorbent (P-3K-1.5 M) had the smallest crystallite/particle size, largest surface area, and highest availability of surface alkaline-sites. The kinetics analysis also demonstrates that P-3K-1.5 M exhibited the fastest sorption kinetics during a double process. Additionally, P-3K-1.5 M maintained a high capacity over 10 sorption/desorption cycles. Therefore, this synthesis technique, which is simple, cost-effective, and easily scalable, shows great promise for high-temperature CO2 capture.

IntroductionBreast cancer, as the most prevalent malignancy among women globally, continues to exhibit rising incidence rates, particularly in China. The disease predominantly affects women aged 40 to 60 and is influenced by both genetic and environmental factors. This study focuses on the role of H19 gene polymorphisms, investigating their impact on breast cancer susceptibility, clinical outcomes, and response to treatment.MethodsWe engaged 581 breast cancer patients and 558 healthy controls, using TaqMan assays and DNA sequencing to determine genotypes at specific loci (rs11042167, rs2071095, rs2251375). We employed in situ hybridization and immunohistochemistry to measure the expression levels of LincRNA H19, miR-675, MRP3, HOXA1, and MMP16 in formalin-fixed, paraffin-embedded samples. Statistical analyses included chi-squared tests, logistic regression, and Kaplan-Meier survival curves to evaluate associations between genetic variations, gene expression, and clinical outcomes.ResultsGenotypes AG at rs11042167, GT at rs2071095, and AC at rs2251375 were significantly associated with increased risk of breast cancer. Notably, the AA genotype at rs11042167 and TT genotype at rs2071095 were linked to favorable prognosis. High expression levels of LincRNA H19, miR-675, MRP3, HOXA1, and MMP16 in cancer tissues correlated with advanced disease stages and poorer survival rates. Spearman correlation analysis revealed significant positive correlations between the expression of LincRNA H19 and miR-675 and specific genotypes, highlighting their potential regulatory roles in tumor progression.DiscussionThe study underscores the critical roles of LincRNA H19 and miR-675 as prognostic biomarkers in breast cancer, with their overexpression associated with disease progression and adverse outcomes. The H19/LincRNA H19/miR-675/MRP3-HOXA1-MMP16 axis offers promising targets for new therapeutic strategies, reflecting the complex interplay between genetic markers and breast cancer pathology.ConclusionThe findings confirm that certain H19 SNPs are associated with heightened breast cancer risk and that the expression profiles of related genetic markers can significantly influence prognosis and treatment response. These biomarkers hold potential as targets for personalized therapy and early detection strategies in breast cancer, underscoring the importance of genetic research in understanding and managing this disease.

IntroductionThe design of the maize metering device involves centrifugal variable diameter pneumatic and cleaning mechanisms, aiming to enhance the performance and power efficiency of pneumatic maize metering devices. Leveraging the impact of changes in centrifugal diameter and the guidance and positioning of airflow, we optimize the hole insert, seeding plate, seed limit board, and integrated front shell. This optimization facilitates the adjustment of both the quantity and posture of seed filling. As a result, seeds can form a uniform flow within the annular cavity, reducing the wind pressure necessary for regular operation and decreasing power consumption.MethodsA quadratic regression orthogonal rotation combination experiment is conducted using a self-made experiment bench, considering ground speed, wind pressure, and seeding rate as the experiment factors. Furthermore, a comparative experiment involving a novel centrifugal variable-diameter type metering device.ResultsThe results indicate optimal seeding performance when the ground speed is 13.2 km/h, the wind pressure is 1.2 kPa, and the feeding rate is 25 seeds/s. Under these conditions, the quality of feed index reaches 95.20%, the multi-index is 3.87%, and the miss index is 0.93%. Findings reveal that the developed seed metering device achieved a quality of feed index exceeding 93.00% across varying speeds of 12~18 km/h, aligning with the production requirements. Moreover, the actual power consumption of Type B and C is about 85.00% and 98.00% lower than Type A, standing at only 32.90 W at 18 km/h. The COP of Type C is about 86 times and 12 times that of Type A and B, respectively, meeting the demands for efficient production of maize seed metering devices.DiscussionIn comparison to traditional design and structural parameter optimization methods for maize seed metering device, this study is helpful to the sustainable development of maize industry and reduce environmental pollution.

Objectives: The purpose of this study is to investigate the lung function in Chronic Rhinosinusitis (CRS) patients with Chronic Cough (CC). Methods: A total of 1413 CC patients were retrospectively screened and 109 CRS patients with CC were enrolled. Lung function, Lund-Mackay Computed Tomography (CT) score, smoking status, peripheral blood eosinophil count, and immunoglobulin E concentration in serum samples, and Sino-Nasal Outcome Test were examined. Normal control subjects are also recruited. Results: The Forced Expiratory Volume in 1 second (FEV1.0), Percent Predicted FEV1.0, and FEV1.0/Forced Vital Capacity (FVC) ratio in the patients were significantly low as compared with the control subjects. The FEV1.0/FVC ratio was negatively correlated with the Lund-Mackay CT scores of the patients with a high CT score. Conclusions: The CRS patients with CC should be investigated with lung function. In addition, the multidisciplinary evaluation including a pulmonologist is needed to manage the CRS patients with CC. Level of evidence: Level 4.

Introduction: Ampiroxicam is a long-acting, non-steroidal anti-inflammatory drug that selectively inhibits human cyclooxygenase, effectively mitigating fever, pain, and inflammation. This study evaluated the drug's tolerability and pharmacokinetics to support personalized dosing strategies.Methods: The study involved healthy participants and focused on the pharmacokinetics of ampiroxicam. Plasma levels of piroxicam, a key metabolite of ampiroxicam, were measured using ultra-performance liquid chromatography. Piroxicam was chosen due to its integral role in ampiroxicam's metabolic pathway. The analytical method underwent rigorous validation to ensure precision and accuracy, addressing potential interference from endogenous plasma substances.Results: Participants received ampiroxicam in single doses (low, medium, and high) and multiple doses. Pharmacokinetic parameters, including AUC0–216, AUC0–∞, and Cmax, exhibited a dose-dependent increase. No significant differences were noted across the dosage groups, and sex-specific differences were minimal, with the exception of mean residence time (MRT) in the multiple-dose group, which appeared influenced by body weight variations.Discussion: The findings affirm the safety and efficacy of ampiroxicam across different dosing regimens, validating its clinical utility and potential for personalized medicine in the treatment of pain and inflammation.

Summary: Accurate detection of pathogens, particularly distinguishing between Gram-positive and Gram-negative bacteria, could improve disease treatment. Host gene expression can capture the immune system’s response to infections caused by various pathogens. Here, we present a deep neural network model, bvnGPS2, which incorporates the attention mechanism based on a large-scale integrated host transcriptome dataset to precisely identify Gram-positive and Gram-negative bacterial infections as well as viral infections. We performed analysis of 4,949 blood samples across 40 cohorts from 10 countries using our previously designed omics data integration method, iPAGE, to select discriminant gene pairs and train the bvnGPS2. The performance of the model was evaluated on six independent cohorts comprising 374 samples. Overall, our deep neural network model shows robust capability to accurately identify specific infections, paving the way for precise medicine strategies in infection treatment and potentially also for identifying subtypes of other diseases.

Abstract Background Bacterial transfers from plants to insect herbivore guts have been well investigated. However, bacterial exchanges between plant phyllospheres and insect cuticles remain unclear, as does their related biological function. Results Here, we report that the cuticular bacterial loads of silkworm larvae quickly increased after molting and feeding on the white mulberry (Morus alba) leaves. The isolation and examination of silkworm cuticular bacteria identified one bacterium Mammaliicoccus sciuri that could completely inhibit the spore germination of fungal entomopathogens Metarhizium robertsii and Beauveria bassiana. Interestingly, Ma. sciuri was evident originally from mulberry leaves, which could produce a secreted chitinolytic lysozyme (termed Msp1) to damage fungal cell walls. In consistency, the deletion of Msp1 substantially impaired bacterial antifungal activity. Pretreating silkworm larvae with Ma. sciuri cells followed by fungal topical infections revealed that this bacterium could help defend silkworms against fungal infections. Unsurprisingly, the protective efficacy of ΔMsp1 was considerably reduced when compared with that of wild-type bacterium. Administration of bacterium-treated diets had no negative effect on silkworm development; instead, bacterial supplementation could protect the artificial diet from Aspergillus contamination. Conclusions The results of this study evidence that the cross-kingdom transfer of bacteria from plant phyllospheres to insect herbivore cuticles can help protect insects against fungal parasite attacks. Video Abstract

Abstract Metabolic diseases and their complications impose health and economic burdens worldwide. Evidence from past experimental studies and clinical trials suggests our body may have the ability to remember the past metabolic environment, such as hyperglycemia or hyperlipidemia, thus leading to chronic inflammatory disorders and other diseases even after the elimination of these metabolic environments. The long-term effects of that aberrant metabolism on the body have been summarized as metabolic memory and are found to assume a crucial role in states of health and disease. Multiple molecular mechanisms collectively participate in metabolic memory management, resulting in different cellular alterations as well as tissue and organ dysfunctions, culminating in disease progression and even affecting offspring. The elucidation and expansion of the concept of metabolic memory provides more comprehensive insight into pathogenic mechanisms underlying metabolic diseases and complications and promises to be a new target in disease detection and management. Here, we retrace the history of relevant research on metabolic memory and summarize its salient characteristics. We provide a detailed discussion of the mechanisms by which metabolic memory may be involved in disease development at molecular, cellular, and organ levels, with emphasis on the impact of epigenetic modulations. Finally, we present some of the pivotal findings arguing in favor of targeting metabolic memory to develop therapeutic strategies for metabolic diseases and provide the latest reflections on the consequences of metabolic memory as well as their implications for human health and diseases.

To reduce the difficulty and enhance the enthusiasm of private-owned electric vehicles (EVs) to participate in frequency regulation ancillary service market (FRASM), a decision aid model (DAM) is proposed. This paper presents three options for EV participating in FRASM, i. e., the base mode (BM), unidirectional charging mode (UCM), and bidirectional charging/discharging mode (BCDM), based on a reasonable simplification of users' participating willingness. In BM, individual EVs will not be involved in FRASM, and DAM will assist users to set the optimal charging schemes based on travel plans under the time-of-use (TOU) price. UCM and BCDM are two modes in which EVs can take part in FRASM. DAM can assist EV users to create their quotation plan, which includes hourly upper and lower reserve capabilities and regulation market mileage prices. In UCM and BCDM, the difference is that only the charging rate can be adjusted in the UCM, and the EVs in BCDM can not only charge but also discharge if necessary. DAM can estimate the expected revenue of all three modes, and EV users can make the final decision based on their preferences. Simulation results indicate that all the three modes of DAM can reduce the cost, while BCDM can get the maximum expected revenue.

Adaptation is one of the fundamental characteristics of life activities; humans and animals inhabiting high altitudes are well adapted to hypobaric hypoxic environments, and studies on the mechanisms of this adaptation emerged a hundred years ago. Based on these studies, this paper reviews the adaptive changes in hypoxia-sensitive tissues and organs, as well as at the molecular genetic level, such as pulmonary, cardiovascular, O2-consuming tissues, and the hemoglobin and HIF pathway, that occur in animals in response to the challenge of hypobaric hypoxia. High-altitude hypoxia adaptation may be due to the coordinated action of genetic variants in multiple genes and, as a result, adaptive changes in multiple tissues and organs at the physiological and biochemical levels. Unraveling their mechanisms of action can provide a reference for the prevention and treatment of multiple diseases caused by chronic hypoxia.

The structural characteristics of large-span structures inherently differ from those of conventional multistorey structures, making it challenging to accurately describe the contribution of various vibration modes to the overall response using traditional dynamic response analysis methods. Based on the response spectrum method, this paper investigates the influence of the first torsional mode on the overall effects of large-span structures. It proposes a new metric, called the torsional mode contribution factor, to characterize the contribution of torsional modes. Focusing primarily on single-span frames, the study explores the impact of factors such as eccentricity ratio, aspect ratio, and roof stiffness on the torsional mode contribution factor. Additionally, the relationship between the period ratio and the torsional mode contribution factor is examined to assess the necessity of controlling the period ratio. The findings reveal that the contribution of torsional modes to the overall seismic response varies significantly under different conditions, such as eccentricity ratio, aspect ratio, roof stiffness, and torsional stiffness. The torsional mode’s contribution is minimal for small eccentricity ratios, with the response primarily driven by translational modes. As eccentricity increases, translational-torsional coupling becomes more pronounced, amplifying the influence of torsional modes on the overall dynamic response. The study also highlights that increasing roof stiffness and aspect ratios can mitigate torsional effects to a certain extent. Still, excessive eccentricity ratios and stiffness may result in higher torsional contributions. Additionally, it is found that increasing torsional stiffness reduces the influence of torsional modes but does not eliminate the overall torsional deformation. The proposed torsional mode contribution factor offers an effective way to quantify these effects, demonstrating that traditional control methods, such as period ratio control, may not fully capture the torsional contributions.

The period ratio and the drift ratio are commonly used as plane regularity control indices for multi-story buildings. However, they fail to reasonably reflect the regularity of lateral force-resisting component configuration and deformation characteristics in non-rigid plate bent frame structures. This study focuses on the analysis of non-rigid single-span bent frames, examining the variation patterns of a suitable regularity index for non-rigid plate bent frame structures, referred to as the shear force lateral stiffness matching index, under various parameters. Additionally, it introduces indices to quantify the deformation response of non-rigid plate bent frame structures, providing a detailed analysis of the impact of factors such as eccentricity, torsional stiffness, and roof slab stiffness on the deformation characteristics of non-rigid plate bent frame structures and the shear force lateral stiffness matching index. The results show that the shear force lateral stiffness matching index can reflect the inconsistency in the horizontal displacement response of lateral force-resisting components caused by deformations in the roof slab. The proposed indices for torsional and bending deformations accurately quantify the roof slab’s deformation response, revealing the horizontal deformation characteristics of lateral force-resisting components in non-rigid frames. When eccentricity is present, the stiffness of the roof slab has a non-monotonic effect on the torsional component of the structural seismic response.

Qualitative researchers often take for granted that the process of translation involves finding in the target language an equivalent linguistic expression to the one used in the source language. The validity of translation in qualitative research is thus based on the equivalence between the original and the translated texts, and correspondingly, uncertainty and differences between the two are treated as threats to validity and trustworthiness. Integrating insights from critical translational theories and Phil Carspecken’s critical reconstructive analysis, we demonstrate that a series of possible meanings always co-exists in the interpretation of a single speech act in both an original text and its translation. These nuanced meanings carry both foregrounded and backgrounded historical, inter-, and intra-cultural references. Through the application of critical reconstructive analyses to original and translated texts, we use examples to demonstrate an approach to achieve reflexivity and criticality through embracing, dialoguing about, and reflecting upon the uncertainty and difference in the meaning-making process of translation. Under this new approach, equivalence is not the sole criterion to evaluate the validity and trustworthiness of translation-related work in qualitative research; uncertainty and difference are not merely threats to the validity of qualitative research. We argue that, if addressed appropriately, uncertainty and difference can catalyze researchers’ interrogation of their own positionality as well as various forms of power dynamics, and thus enhance the validity of qualitative research.

Abstract The equivalence of absorption rates and extents between generic drugs and their reference formulations is crucial for ensuring therapeutic comparability. Bioequivalence (BE) studies are widely utilized and play a pivotal role in substantiating the approval and promotional efforts for generic drugs. Virtual BE simulation is a valuable tool for mitigating risks and guiding clinical BE studies, thereby minimizing redundant in vivo BE assessments. Herein, we successfully developed a physiologically based absorption model for virtual BE simulations, which precisely predicts the BE of the apixaban test and reference formulations. The modeling results confirm that the test and reference formulations were bioequivalent under both fasted and fed conditions, consistent with clinical studies. This highlights the efficacy of physiologically based absorption modeling as a powerful tool for formulation screening and can be adopted as a methodological and risk assessment strategy to detect potential clinical BE risks.

ObjectiveEndocrinopathies are the most common immune-related adverse events (irAEs) observed during therapy with PD-1 inhibitors. In this study, we conducted a comprehensive systematic review and meta-analysis to evaluate the risk of immune-related endocrinopathies in patients treated with PD-1 inhibitors.MethodsWe performed a systematic search in the PubMed, Embase, and Cochrane Library databases to retrieve all randomized controlled trials (RCTs) involving PD-1 inhibitors, spanning from their inception to November 24, 2023. The comparative analysis encompassed patients undergoing chemotherapy, targeted therapy, or receiving placebo as control treatments. This study protocol has been registered with PROSPERO (CRD42023488303).ResultsA total of 48 clinical trials comprising 24,514 patients were included. Compared with control groups, patients treated with PD-1 inhibitors showed an increased risk of immune-related adverse events, including hypothyroidism, hyperthyroidism, hypophysitis, thyroiditis, diabetes mellitus, and adrenal insufficiency. Pembrolizumab was associated with an increased risk of all aforementioned endocrinopathies (hypothyroidism: RR=4.76, 95%CI: 3.55-6.39; hyperthyroidism: RR=9.69, 95%CI: 6.95-13.52; hypophysitis: RR=5.47, 95%CI: 2.73-10.97; thyroiditis: RR=5.95, 95%CI: 3.02-11.72; diabetes mellitus: RR=3.60, 95%CI: 1.65-7.88; adrenal insufficiency: RR=4.80, 95%CI: 2.60-8.88). Nivolumab was associated with an increased risk of hypothyroidism (RR=7.67, 95%CI: 5.00-11.75) and hyperthyroidism (RR=9.22, 95%CI: 4.71-18.04). Tislelizumab and sintilimab were associated with an increased risk of hypothyroidism (RR=19.07, 95%CI: 5.46-66.69 for tislelizumab and RR=18.36, 95%CI: 3.58-94.21 for sintilimab). For different tumor types, both hypothyroidism and hyperthyroidism were at high risks. Besides, patients with non-small cell lung cancer were at a higher risk of thyroiditis and adrenal insufficiency. Patients with melanoma were at a higher risk of hypophysitis and diabetes mellitus. Both low- and high-dose group increased risks of hypothyroidism and hyperthyroidism.ConclusionRisk of endocrine irAEs may vary in different PD-1 inhibitors and different tumor types. Increased awareness and understanding of the risk features of endocrine irAEs associated with PD-1 inhibitors is critical for clinicians.Systematic review registrationcrd.york.ac.uk/prospero, identifier PROSPERO (CRD42023488303).

IntroductionThe hair coat status of cattle serves as an easily observed indicator of economic value in livestock production; however, the underlying mechanism remains largely unknown. Therefore, the objective of the current study was to determine differences in the intestinal microbiota and metabolome of cattle based on a division of with either slick and shining (SHC) or rough and dull (MHC) hair coat in Simmental cows.MethodsEight SHC and eight MHC late-pregnancy Simmental cows (with similar parities, body weights, and body conditions) were selected based on their hair coat status, and blood samples (plasma) from coccygeal venipuncture and fecal samples from the rectum were collected. The intestinal microbiota (in the fecal samples) was characterized by employing 16S rRNA gene sequencing targeting the V3–V4 hypervariable region on the Illumina MiSeq PE300 platform, and plasma samples were subjected to LC–MS/MS-based metabolomics with Progenesis QI 2.3. Plasma macromolecular metabolites were examined for differences in the metabolism of lipids, proteins, mineral elements, and hormones.ResultsNotable differences between the SHC and MHC groups related to host hair coat status were observed in the host metabolome and intestinal microbiota (P < 0.05). The host metabolome was enriched in histidine metabolism, cysteine and methionine metabolism, and purine metabolism in the SHC group, and the intestinal microbiota were also enriched in histidine metabolism (P < 0.05). In the MHC group, the symbiotic relationship transitioned from cooperation to competition in the MHC group, and an uncoupling effect was present in the microbe–metabolite association of intestine microbiota–host interactions. The hubs mediating the relationships between intestinal microbiota and plasma metabolites were the intestinal bacterial genus g__norank_f__Eubacterium_coprostanoligenes_group, plasma inosine, triiodothyronine, and phosphorus, which could be used to differentiate cows’ hair coat status (P < 0.05).ConclusionOverall, the present study identified the relationships between the features of the intestinal microbiota and host hair coat status, thereby providing evidence and a new direction (intestine microbiota–host interplay) for future studies aimed at understanding the hair coat status of cattle.

Summary: Background: The relationship between the fluctuation in body size and brain health is poorly understood. This study aimed to examine the associations of long-term variability in body mass index (BMI) and waist-to-hip ratio (WHR) with neuroimaging metrics that approximate brain health. Methods: This cohort study recruited 1114 participants aged 25–83 years from a multicenter, community-based cohort study in China. We modeled the BMI and WHR trajectories of participants during 2006–2018 and assessed the BMI and WHR variability (direction and speed of change) by calculating the slope. Generalized linear models were applied to investigate the associations of BMI and WHR variability with MRI markers of brain tissue volume, white matter microstructural integrity, white matter hyperintensity (WMH), and cerebral small vessel disease (CSVD). Findings: Progressive weight gain during follow-up was associated with lower global fractional anisotropy (beta = −0.18, 95% confidence interval [CI] −0.34 to −0.02), higher mean diffusivity (beta = 0.15, 95% CI 0.01–0.30) and radial diffusivity (beta = 0.17, 95% CI 0.02–0.32). Weight loss was also associated with a lower burden of periventricular WMH (beta = −0.26, 95% CI −0.48 to −0.03) and a lower risk of moderate-to-severe basal ganglia enlarged perivascular spaces (BG-EPVS, odds ratio [OR] = 0.41, 95% CI 0.20–0.83). Among overweight populations, weight loss was linked with smaller volumes of WMH (beta = −0.47, 95% CI −0.79 to −0.15), periventricular WMH (beta = −0.57, 95% CI −0.88 to −0.26), and deep WMH (beta = −0.36, 95% CI −0.69 to −0.03), as well as lower risk of CSVD (OR = 0.22, 95% CI 0.08–0.62), lacune (OR = 0.12, 95% CI 0.01–0.91) and moderate-to-severe BG-EPVS (OR = 0.24, 95% CI 0.09–0.61). In adults with central obesity, WHR loss was positively associated with larger gray matter volume (beta = 0.50, 95% CI 0.11–0.89), hippocampus volume (beta = 0.62, 95% CI 0.15–1.09), and parahippocampal gyrus volume (beta = 0.85, 95% CI 0.34–1.37). The sex-stratification and age-stratification analyses revealed similar findings with the main results, with the pattern of associations significantly presented in the individuals at mid-life and late-life. Interpretation: Long-term stability of BMI level is essential for maintaining brain health. Progressive weight gain is associated with impaired white matter microstructural integrity. Weight and WHR losses are associated with improved general brain health. Our results contribute to a better understanding of the integrated associations between variations in obesity measures and brain health. Funding: This study was supported by grants No. 62171297 (Han Lv) and 61931013 (Zhenchang Wang) from the National Natural Science Foundation of China, No. 7242267 from the Beijing Natural Science Foundation (Han Lv), and No. [2015] 160 from the Beijing Scholars Program (Zhenchang Wang).

Abstract Purpose To compare the diagnostic sensitivity of ultra-high-resolution computed tomography (U-HRCT) and HRCT in isolated fenestral otosclerosis (IFO). Methods A retrospective analysis was conducted on 85 patients (85 ears) diagnosed with IFO between October 2020 and November 2022. U-HRCT (0.1 mm thickness) was performed for 20 ears, HRCT (0.67 mm thickness) for 45 ears, and both for 20 ears. The images were evaluated by general radiologists and neuroradiologists who were blinded to the diagnosis and surgical information. The diagnostic sensitivity of U-HRCT and HRCT for detecting IFO was compared between the two groups. Results Excellent inter-observer agreement existed between the two neuroradiologists (Cohen’s κ coefficient 0.806, 95% CI 0.692–0.920), with good agreement between the general radiologists (Cohen’s κ coefficient 0.680, 95% CI 0.417–0.943). U-HRCT had a sensitivity of 100% (40/40 ears) for neuroradiologists and 87.5% (35/40 ears) for general radiologists, significantly higher than HRCT (89.2% [58/65 ears] for neuroradiologists; 41.5% [27/65 ears] for general radiologists) (p = 0.042, p′

Abstract Osteoporosis is a prevalent bone disorder characterized by low bone mineral density (BMD) and deteriorated bone microarchitecture, leading to an increased risk of fractures. Vitamin D (VD), an essential nutrient for skeletal health, plays a vital role in maintaining bone homeostasis. The biological effects of VD are primarily mediated through the vitamin D receptor (VDR), a nuclear receptor that regulates the transcription of target genes involved in calcium and phosphate metabolism, bone mineralization, and bone remodeling. In this review article, we conduct a thorough literature search of the PubMed and EMBASE databases, spanning from January 2000 to September 2023. Utilizing the keywords “vitamin D,” “vitamin D receptor,” “osteoporosis,” and “therapy,” we aim to provide an exhaustive overview of the role of the VD/VDR system in osteoporosis pathogenesis, highlighting the most recent findings in this field. We explore the molecular mechanisms underlying VDR’s effects on bone cells, including osteoblasts and osteoclasts, and discuss the impact of VDR polymorphisms on BMD and fracture risk. Additionally, we examine the interplay between VDR and other factors, such as hormonal regulation, genetic variants, and epigenetic modifications, that contribute to osteoporosis susceptibility. The therapeutic implications of targeting the VDR pathway for osteoporosis management are also discussed. By bringing together these diverse aspects, this review enhances our understanding of the VD/VDR system’s critical role in the pathogenesis of osteoporosis and highlights its significance as a potential therapeutic target.

Abstract In vivo pharmacokinetic simulations and virtual bioequivalence (BE) evaluation of cilostazol have not yet been described for humans. Here, we successfully developed a physiologically based absorption model to simulate plasma concentrations of cilostazol. In addition, virtual population simulations integrating dissolution of 0.3% sodium dodecyl sulfate water media were executed to evaluate the BE of test and reference formulations. Simulation results show that test and reference formulations were bioequivalent among 28 subjects, but not nine subjects, consistent with clinical studies. The model proved to be an important tool to show potential BE for cilostazol. This finding may facilitate understanding of the potential risks during the development of generic products.

The influence of temperature on the deformation mechanisms of a new Ni-based superalloy named K4800 containing 35 vol% γ′ were investigated. We studied the temperature dependence of deformation mechanisms and used the alloying method to optimize the high-temperature properties of the alloy. By analyzing slightly deformed microstructures, the dominant deformation mechanisms of alloy K4800 at the yielding stage were identified as: the anti-phase boundary (APB) shearing from RT to 600 °C, stacking faults (SFs) shearing and Orowan looping at 600–800 °C, and Orowan looping/cross-slip/climbing above 800 °C. We found that it was the activation of thermally assisted processes declined the strengthening effect of γ′ phase and impaired the high-temperature strength of the alloy above 800 °C. First-principles calculations were employed to investigate the effects of alloying elements on the formation and stability of stacking faults in K4800 alloy by using a 48-atom Ni3(Al, Ti) orthorhombic supercell. Considering the effectiveness of elements in lowering stacking faults energy, Co and W elements were chosen to alleviate the strength degradation of K4800 alloy above 800 °C. The deformation mechanism and properties of these three alloys at elevated temperature were also revealed and discussed.

Abstract The sustainable development of urban agglomerations plays a pivotal role in national and global efforts to reduce emissions. By focusing on the efficient exchange and optimization of energy consumption across various sectors, the sustainable development of energy systems within urban agglomerations can be achieved. However, the overall impact of the cross-sector energy optimization and complementarity has not been quantitatively analyzed. Here, we focused on the Yangtze River Delta (YRD) urban agglomeration in China and proposed an optimization framework for energy, environment, and economy. The framework considered four sectors: transportation sector, power sector, industry sector, and building sector, in order to determine the most sustainable development pathway for the urban agglomeration. The optimization model considers total costs and greenhouse gas emissions reduction as the objectives and utilizes technologies as constraints to optimize the pathway. We found that this optimization strategy resulted in a 53.1 billion tons increase in CO2 emissions reduction in the region. The results of emission reduction varied across sectors, ranging from 4.5 to 22.2 billion tons CO2 equivalent, and across cities, ranging from 7.1 to 4688.1 Mt. The results suggest that the core cities in the urban agglomeration can take on a leadership role. By promoting cross-sector collaboration and implementing energy recycling, the energy efficiency of surrounding cities can be greatly improved, leading to the sustainable development of the urban agglomeration.

Abstract Ciprofol (also known as HSK3486) is a promising intravenous anesthetic candidate derived from propofol and independently developed by Haisco Pharmaceutical Group Co., Ltd. (Chengdu, China). Compared with propofol, ciprofol has the potential to reduce the dose required and the associated risks. Ciprofol is extensively metabolized in vivo, and its interaction with other concurrently administered drugs during clinical application is worthy of attention. Therefore, an open‐label, two‐stage sequential study was performed in healthy subjects who received either a single administration of ciprofol injection or ciprofol injection after oral administration of sodium divalproex. The aim of the study was to evaluate the effects of sodium divalproex on ciprofol with respect to pharmacokinetics, pharmacodynamics, and safety, thus providing a basis for the rational clinical use of ciprofol and sodium divalproex.

Abstract Background Osseous changes of the temporomandibular joint (TMJ) are related to the progression of temporomandibular disorders (TMD), and computed tomography (CT) plays a vital role in disease evaluation. Objective The aims of this study were to evaluate the image quality and diagnostic value of ultra-high-resolution CT (U-HRCT) in TMD compared to cone-beam CT (CBCT). Methods TMD patients who underwent both CBCT and U-HRCT between November 2021 and September 2022 were retrospectively included. Image quality scores were assigned for four osseous structures (the cortical and trabecular bones of the condyle, articular eminence, and glenoid fossa) by two independent observers from Score 1 (unacceptable) to Score 5 (excellent). Diagnostic classification of TMD was categorized as follows: Class A (no evident lesion), Class B (indeterminate condition) and Class C (definitive lesion). Image quality scores and diagnostic classifications were compared between CBCT and U-HRCT. The Cohen’s Kappa test, Wilcoxon signed-rank test, Chi-square test and Fisher’s exact test were conducted for statistical analysis. Results Thirty TMD patients (median age, 30 years; interquartile range, 26–43 years; 25 females) with 60 TMJs were enrolled. Image quality scores were higher for U-HRCT than for CBCT by both observers (all Ps

Abstract The extreme power output scenarios of renewable energy sources (RES) proposed new challenges to the safe and stable operation of the power system. Transmission expansion planning (TEP) with large‐scale RES grid integration needs considering the risk of extreme scenarios. In this paper, an adaptive decision‐making approach for the TEP problem based on planning‐risk assessment‐replanning iterative process is proposed. The method obtains massive temporal and spatial correlated wind‐photovoltaic (PV) power output scenarios by generalizing the historical data to describe the uncertainties. A data‐driven load loss risk assessment model (RAM) based on the power system's actual operating state is built, referring to the degree of extreme scenario risks on the balance of supply and demand, and the probability of extreme scenario occurrence. The planning decision is progressively revised according to the risk assessment result. The Garver's 6‐bus system and the IEEE RTS 24‐bus system are adopted as simulation cases. The results show that the optimal expansion plans achieve a balance between the economy and robustness, which verifies the effectiveness of the proposed method.

Abstract. Background:. The effect of arteriosclerotic intracranial arterial vessel wall enhancement (IAVWE) on downstream collateral flow found in vessel wall imaging (VWI) is not clear. Regardless of the mechanism underlying IAVWE on VWI, damage to the patient's nervous system caused by IAVWE is likely achieved by affecting downstream cerebral blood flow. The present study aimed to investigate the effect of arteriosclerotic IAVWE on downstream collateral flow. Methods:. The present study recruited 63 consecutive patients at the Second Hospital of Hebei Medical University from January 2021 to November 2021 with underlying atherosclerotic diseases and unilateral middle cerebral artery (MCA) M1-segment stenosis who underwent an magnetic resonance scan within 3 days of symptom onset. The patients were divided into 4 groups according to IAVWE and the stenosis ratio (Group 1, n = 17; Group 2, n = 19; Group 3, n = 13; Group 4, n = 14), and downstream collateral flow was analyzed using three-dimensional pseudocontinuous arterial spin labeling (3D-pCASL) and RAPID software. The National Institutes of Health Stroke Scale (NIHSS) scores of the patients were also recorded. Two-factor multivariate analysis of variance using Pillai's trace was used as the main statistical method. Results:. No statistically significant difference was found in baseline demographic characteristics among the groups. IAVWE, but not the stenosis ratio, had a statistically significant significance on the late-arriving retrograde flow proportion (LARFP), hypoperfusion intensity ratio (HIR), and NIHSS scores (F = 20.941, P

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread worldwide. Effective treatments against COVID-19 remain urgently in need although vaccination significantly reduces the incidence, hospitalization, and mortality. At present, antiviral drugs including Nirmatrelvir/Ritonavir (Paxlovid™), Remdesivir, and Molnupiravir have been authorized to treat COVID-19 and become more globally available. On the other hand, traditional Chinese medicine (TCM) has been used for the treatment of epidemic diseases for a long history. Currently, various TCM formulae against COVID-19 such as Qingfei Paidu decoction, Xuanfei Baidu granule, Huashi Baidu granule, Jinhua Qinggan granule, Lianhua Qingwen capsule, and Xuebijing injection have been widely used in clinical practice in China, which may cause potential herb–drug interactions (HDIs) in patients under treatment with antiviral drugs and affect the efficacy and safety of medicines. However, information on potential HDIs between the above anti-COVID-19 drugs and TCM formulae is lacking, and thus this work seeks to summarize and highlight potential HDIs between antiviral drugs and TCM formulae against COVID-19, and especially pharmacokinetic HDIs mediated by metabolizing enzymes and/or transporters. These well-characterized HDIs could provide useful information on clinical concomitant medicine use to maximize clinical outcomes and minimize adverse and toxic effects.

In large-scale dairy farming, the use of high-temperature-fermented dairy manure bedding instead of rice husk-based bedding and other commercial types of bedding is widely favored. Strip-stacking aerobic fermentation is the main production method of dairy manure bedding, but it has problems including unstable fermentation and the secondary breeding of pathogens. In this work, a multi-probe, integrated, online monitoring system for temperature and relative humidity was used for fermentation process optimization. The effects of the temporal and spatial distribution of fermentation temperature and relative humidity on the nutrient content curve and the moisture and ash content of manure bedding materials were systematically studied. The effect of the fermentation process on the retention rate of effective bedding materials (cellulose, hemicellulose, and lignin) was analyzed. The experiments proved that high-quality bedding material can be obtained through reasonable stacking fermentation. The fabricated bedding material has a total dry base content consisting of cellulose, hemicellulose, and lignin of 78%, an ash content of 6%, and a nutrient content of 17%. The obtained bedding material was produced to increase the bed rest rate and continuously inhibit the bedding bacteria content, keeping it at a low level for 5 days. This study proves that temperature and humidity monitoring can guide the optimization of the strip-stacking fermentation process of dairy manure and that it can be applied to large-scale farms to improve fermentation parameters.

This study aimed to investigate the effect of the transverse sinus (TS) stenosis (TSS) position caused by arachnoid granulation on patients with venous pulsatile tinnitus (VPT) and to further identify the types of TSS that are of therapeutic significance for patients. Multiphysics interaction models of six patients with moderate TSS caused by arachnoid granulation and virtual stent placement in TSS were reconstructed, including three patients with TSS located in the middle segment of the TS (group 1) and three patients with TTS in the middle and proximal involvement segment of the TS (group 2). The transient multiphysics interaction simulation method was applied to elucidate the differences in biomechanical and acoustic parameters between the two groups. The results revealed that the blood flow pattern at the TS and sigmoid sinus junction was significantly changed depending on the stenosis position. Preoperative patients had increased blood flow in the TSS region and TSS downstream where the blood flow impacted the vessel wall. In group 1, the postoperative blood flow pattern, average wall pressure, vessel wall vibration, and sound pressure level of the three patients were comparable to the preoperative state. However, the postoperative blood flow velocity decreased in group 2. The postoperative average wall pressure, vessel wall vibration, and sound pressure level of the three patients were significantly improved compared with the preoperative state. Intravascular intervention therapy should be considered for patients with moderate TSS caused by arachnoid granulations in the middle and proximal involvement segment of the TS. TSS might not be considered the cause of VPT symptoms in patients with moderate TSS caused by arachnoid granulation in the middle segment of the TS.

Babesia duncani (B. duncani), a protozoan parasite prevalent in North America, is a significant threat for human health. Given the regulatory role of pyruvate kinase I (PyK I) in glycolytic metabolism flux and ATP generation, PyK I has been considered the target for drug intervention for a long time. In this study, B. duncani PyK I (BdPyK I) was successfully cloned, expressed, and purified. Polyclonal antibodies were confirmed to recognize the native BdPyK I protein (56 kDa) using Western blotting. AlphaFold software predicted the three-dimensional structure of BdPyK I, and molecular docking with small molecules was conducted to identify potential binding sites of inhibitor on BdPyK I. Moreover, inhibitory effects of six inhibitors (tannic acid, apigenin, shikonin, PKM2 inhibitor, rosiglitazone, and pioglitazone) on BdPyK I were examined under the optimal enzymatic conditions of 3 mM PEP and 3 mM ADP, and significant activity reduction was found. Enzyme kinetics and growth inhibition assays further confirmed the reliability of these inhibitors, with PKM2 inhibitor, tannic acid, and apigenin exhibiting the highest selectivity index as specific inhibitors for B. duncani. Subsequently, key amino acid residues were mutated in both BdPyK I and Homo sapiens pyruvate kinase I (HPyK I), and two differential amino acid residues (isoleucine and phenylalanine) were identified between HPyK I and BdPyK I through PyK activity detection experiments. These findings lay foundation for understanding the role of PyK I in the growth and development of B. duncani, providing insights for babesiosis prevention and drug development.

Abstract Sepsis is a life-threatening condition characterized by a harmful host response to infection with organ dysfunction. Annually about 20 million people are dead owing to sepsis and its mortality rates is as high as 20%. However, no studies have been carried out to investigate sepsis from the system biology point of view, as previous research predominantly focused on individual genes without considering their interactions and associations. Here, we conducted a comprehensive exploration of genome-wide expression alterations in both mRNAs and long non-coding RNAs (lncRNAs) in sepsis, using six microarray datasets. Co-expression networks were conducted to identify mRNA and lncRNA modules, respectively. Comparing these sepsis modules with normal modules, we observed a homogeneous expression pattern within the mRNA/lncRNA members, with the majority of them displaying consistent expression direction. Moreover, we identified consistent modules across diverse datasets, consisting of 20 common mRNA members and two lncRNAs, namely CHRM3-AS2 and PRKCQ-AS1, which are potential regulators of sepsis. Our results reveal that the up-regulated common mRNAs are mainly involved in the processes of neutrophil mediated immunity, while the down-regulated mRNAs and lncRNAs are significantly overrepresented in T-cell mediated immunity functions. This study sheds light on the co-expression patterns of mRNAs and lncRNAs in sepsis, providing a novel perspective and insight into the sepsis transcriptome, which may facilitate the exploration of candidate therapeutic targets and molecular biomarkers for sepsis.

Distracted driving is one of the main causes of road crashes. Therefore, effective distinguishing of distracted driving behaviour and its category is the key to reducing the incidence of road crashes. To identify distracted driving behaviour accurately and effectively, this paper uses the head posture as a relevant variable and realizes the classification of distracted driving behaviour based on the relevant literature and investigation. Adistracted driving discrimination algorithm based on the facial feature triangle is proposed. In the proposed algorithm, the Bayesian network is employed to judge driving behaviour categories. The proposed algorithm is verified by experiments using data from 20 volunteers. The experimental results show that the discrimination accuracy of the proposed algorithm is as high as 90%, which indicates that the head posture parameters used in this study are closely related to the distracted driving state. The results show that the proposed algorithm achieves high accuracy in the discrimination and classification of distracted driving behaviour and can effectively reduce the accident rate caused by distracted driving. Moreover, it can provide a basis for the research of distracted driving behaviour and is conducive to the formulation of the corresponding laws and regulations.

Abstract One of the main capabilities of grid‐forming converters is the ability to operate in both islanded and grid‐connected modes. The grid‐forming converters work autonomously and behave as an AC voltage source when they are isolated from the bulk power system. In a grid‐connected mode, it is necessary for them to offer a set of grid‐forming capabilities for enhancing system inertia and strength. A grid‐forming converter may experience significant fluctuations in voltage, current, and frequency when the transition occurs. This paper investigates an improved adaptive model predictive control (AMPC) method for grid‐forming converters to achieve a smooth transition from islanded to grid‐connected mode and balance the contradiction between frequency stability and response speed. The AMPC method uses the angular frequency and phase angle as the performance indicators and introduces the angular frequency variations to adaptively adjust its weight coefficient in the objective function. The implementations and effects of the proposed AMPC method on the grid‐forming converter are theoretically evaluated. Compared to the conventional control, the proposed control scheme can not only suppress voltage, current, and frequency fluctuations, but also achieve a smooth transition. Additionally, the frequency control strategy in the islanded mode is improved for better independent operation. Finally, experiment tests on a controller‐level hardware‐in‐the‐loop simulation platform are carried out to validate the proposed control strategy for achieving a smooth transition.

Abstract Demand responsive transit (DRT) with app‐based reservation platforms is experiencing a renaissance to bring the tremendous potential for mobility in the urban universe. Nevertheless, how to attract and retain passengers for long‐term use has become one of the most significant problems. The decision‐making psychology of passengers is often overlooked but incredibly critical in the practical applicability of DRT services. This paper proposes a more flexible DRT service with soft time windows considering boundedly rational passengers. A compensation mechanism is developed to alleviate the dissatisfaction of passengers while considerably promoting the system efficiency. A two‐stage model is designed to incorporate bounded rationality into the optimization process of mixed demand, including the static phase for reservation passengers and the dynamic phase for real‐time passengers. To enhance the computational efficiency, a hybrid heuristic algorithm combining spatiotemporal clustering and non‐dominated sorting genetic algorithm (NSGA)‐II is constructed to obtain the Pareto solutions set. An illustrative example of the Nguyen–Dupuis network is presented to demonstrate the validity of the algorithm. Subsequently, a large‐scale case study in Beijing evaluated the applicability of DRT in the real‐world network. The results reveal that dynamic DRT with compensation mechanism can substantially improve the system performance while ensuring the service quality. The response rate of passengers has been dramatically promoted to 80%. The operating profit has been enormously improved by up to 73%. Therefore, this study is radically conducive to understanding the passenger's decision‐making psychology while constructing a more cost‐efficient flexible strategy for the service provider.

Problematic Smartphone Use (PSU) is associated with a series of mental health issues including depression; yet, the directionality and underlying mechanisms for these associations are underdetermined. This study investigated the possible reinforcement effects of PSU on perceived stress and later depression and the moderating effect of social support on the associations between perceived stress and smartphone use and PSU. This study further explored the differential effects for separate types of smartphone use. With a sample of 222 college students, we found that PSU reinforced perceived stress especially for people with high levels of stress, and perceived stress fully mediated the association between PSU and depression. Regarding types of smartphone use, we found that perceived stress was associated with both person-to-person and social networking smartphone use. In addition, for people with low to medium levels of social support, perceived stress was linked to increased PSU via social networking smartphone use.

Cephalopod skin is capable of fast color changing enabled by tunable skin transparency as well as structure color. Under this inspiration, herein, a flexible surface with unique hierarchical structure that integrates both transparency change in chemical color (optical scattering) and structure coloration (optical interfering) is developed by harnessing wrinkling instability, thanks to the interfacial Au catalysis in soft lithography. As a result, a hierarchical structure in terms of wrinkled film overlaid by nano‐dome array is obtained in the flexile surface. Experiments find that subject to biaxial strains from 0% to 60%, the hierarchical surface first experiences a transition from nontransparent to transparent owing to the flattening of the wrinkles and then exhibits iridescence structure color shifting from blue to red. The switchable and dynamical tunable mechanochromic characteristics are demonstrated in a smart window, offering potentials for developing flexible devices with optical multiple functionality.

IntroductionThe capacity to speak English for academic purposes is a pivotal facet of language education and assessment. Despite the substantial research approving the significant role of teachers in L2 learning, it remains unclear how exactly teachers’ support for students’ learning autonomy influences EFL learners’ academic English speaking performance.MethodsTo address this primary concern, this study drew ground from the Self-System Model of Motivational Development (SSMMD) and adopted a mixed-method approach to examine teacher autonomy support’s direct and indirect effects on Chinese EFL undergraduates’ academic English speaking performance through the mediation of basic psychological needs and classroom engagement. 247 first-year university students participating in academic English speaking courses were recruited in this study.Results and discussionThe quantitative results of the questionnaire indicated that students’ perceived teacher support for autonomy directly predicted English speaking performance, and it also indirectly influenced students’ speaking performance via the mediation of classroom engagement and basic psychological needs. Students’ responses in the semi-structured interview further verified the positive effect of teacher autonomy support on academic English speaking development in the classroom. Pedagogical implications were also discussed based on the findings.