This study evaluated the effects of chenodeoxycholic acid (CDCA), a farnesoid X receptor (FXR) potential activator, on growth performance, antioxidant capacity, glucose metabolism, and inflammation in largemouth bass (Micropterus salmoides) (initial body weight: 5.45 ± 0.02 g) fed a high-carbohydrate diet. Experimental diets included a positive control (5 % α-starch), a negative control (10 % α-starch), and two diets containing 10 % α-starch supplemented with either 0.05 % or 0.10 % CDCA. After 8 weeks, the high-carbohydrate diet reduced growth performance and increased hepatosomatic and viscerosomatic indexes, which were mitigated by 0.10 % CDCA supplementation. The high-carbohydrate diet also increased hepatic glycogen and crude lipid content, both of which were reduced by 0.10 % CDCA. Furthermore, the high-carbohydrate diet induced oxidative stress, histopathological changes, and reduced liver lysozyme activity, which were ameliorated by CDCA supplementation. Molecular analysis showed that the high-carbohydrate diet suppressed FXR and phosphorylated AKT1 (p-AKT1) protein expression in the liver, downregulated insulin signaling (ira, irs, pi3kr1 and akt1), gluconeogenesis (pepck and g6pc), and glycolysis genes (gk, pk and pfkl). CDCA supplementation upregulated fxr expression, activated shp, enhanced the expression of insulin signaling and glycolytic genes (gk, pk and pfkl), and inhibited gluconeogenesis. Additionally, CDCA reduced inflammatory markers (nf-κb and il-1β) and restored anti-inflammatory mediators (il-10, iκb, and tgf-β). In conclusion, 0.10 % CDCA improved carbohydrate metabolism and alleviated liver inflammation in largemouth bass fed a high dietary carbohydrate, partially through FXR activation.

This paper presents a notched ultra-wideband antenna designed to suppress interference from narrowband communication systems. The antenna features a defected ground structure and a stepped microstrip feedline for improved impedance matching and enhanced bandwidth. A bent slot structure is incorporated into the radiating patch to achieve the band-notched characteristic. It has a wide tunable frequency range which allows for flexible adjustment of the notch frequency. Traditional optimization methods, such as numerical analysis, are computationally expensive and inefficient, while heuristic algorithms are less precise. To address these challenges, an improved one-dimensional convolutional neural network (1DCNN-IPS) model is proposed for optimizing the bent slot design more efficiently. The trained 1DCNN-IPS model can accurately predict the antenna’s electromagnetic parameters, reducing mean squared error and training times compared to traditional methods. This provides an efficient and precise solution for antenna structural optimization.

Matching-adjusted indirect comparison (MAIC) has been increasingly applied in health technology assessments (HTA). By reweighting subjects from a trial with individual participant data (IPD) to match the summary statistics of covariates in another trial with aggregate data (AgD), MAIC enables a comparison of the interventions for the AgD trial population. However, when there are imbalances in effect modifiers with different magnitudes of modification across treatments, contradictory conclusions may arise if MAIC is performed with the IPD and AgD swapped between trials. This can lead to the “MAIC paradox,” where different entities reach opposing conclusions about which treatment is more effective, despite analyzing the same data. In this paper, we use synthetic data to illustrate this paradox and emphasize the importance of clearly defining the target population in HTA submissions. Additionally, we recommend making de-identified IPD available to HTA agencies, enabling further indirect comparisons that better reflect the overall population represented by both IPD and AgD trials, as well as other relevant target populations for policy decisions. This would help ensure more accurate and consistent assessments of comparative effectiveness.

Machine learning (ML) models have been developed to identify randomised controlled trials (RCTs) to accelerate systematic reviews (SRs). However, their use has been limited due to concerns about their performance and practical benefits. We developed a high-recall ensemble learning model using Cochrane RCT data to enhance the identification of RCTs for rapid title and abstract screening in SRs and evaluated the model externally with our annotated RCT datasets. Additionally, we assessed the practical impact in terms of labour time savings and recall improvement under two scenarios: ML-assisted double screening (where ML and one reviewer screened all citations in parallel) and ML-assisted stepwise screening (where ML flagged all potential RCTs, and at least two reviewers subsequently filtered the flagged citations). Our model achieved twice the precision compared to the existing SVM model while maintaining a recall of 0.99 in both internal and external tests. In a practical evaluation with ML-assisted double screening, our model led to significant labour time savings (average 45.4%) and improved recall (average 0.998 compared to 0.919 for a single reviewer). In ML-assisted stepwise screening, the model performed similarly to standard manual screening but with average labour time savings of 74.4%. In conclusion, compared with existing methods, the proposed model can reduce workload while maintaining comparable recall when identifying RCTs during the title and abstract screening stages, thereby accelerating SRs. We propose practical recommendations to effectively apply ML-assisted manual screening when conducting SRs, depending on reviewer availability (ML-assisted double screening) or time constraints (ML-assisted stepwise screening).

The study aims were to present in vitro susceptibilities of clinical isolates from Gram-negative bacteria bloodstream infections (GNBSI) collected in China. GNBSI isolates were collected from 18 tertiary hospitals in 7 regions of China from 2018 to 2020. Minimum inhibitory concentrations were assessed using a Trek Diagnostic System. Susceptibility was determined using CLSI broth microdilution, and breakpoints were interpreted using CLSI M100 (2021). A total of 1,815 GNBSI strains were collected, with E. coli (42.4%) and Klebsiella pneumoniae (28.6%) being the most prevalent species, followed by P. aeruginosa (6.7%). Susceptibility analyses revealed low susceptibilities (<40%) of ESBL-producing E. coli and K. pneumonia to third-/fourth-generation cephalosporins, monobactamases, and fluoroquinolones. High susceptibilities to colistin (95.0%) and amikacin (81.3%) were found for K. pneumoniae, while Acinetobacter baumannii exhibited a high susceptibility (99.2%) to colistin but a low susceptibility to other antimicrobials (<27.5%). Isolates from ICUs displayed lower drug susceptibility rates of K. pneumoniae and A. baumannii than isolates from non-ICUs (all P < 0.05). Carbapenem-resistant and ESBL-producing K. pneumoniae detection was different across regions (both P < 0.05). E. coli and K. pneumoniae were major contributors to GNBSI, while A. baumannii exhibited severe drug resistance in isolates obtained from ICU departments.

Contemporary business and management research in China has advanced rapidly, making significant strides in the introduction of theoretical frameworks, research methodologies, local theory development, and practical applications. Much of this research continues to draw on Western theories, and since the reform and opening up, Chinese management research has evolved through distinct stages of globalization and localization. Today, it faces new challenges amid anti-globalization trends. At this critical juncture, the key question is whether China should continue integrating Western theories or capitalize on the opportunity to develop indigenous management theories. This paper explores the differences in scientific development concepts and focuses between China and the West, the historical trajectory of Chinese management research, and the challenges and opportunities that lie ahead. To enhance China's contribution to global management research, we propose that it is essential to sustain international collaboration, deepen understanding of frontline enterprise practices, promote micro-level research and interpretation with Chinese characteristics, and cultivate an open academic community, while optimizing the research evaluation system.

This paper provides an overview of the current status of ultrafast and ultra-intense lasers with peak powers exceeding 100 TW and examines the research activities in high-energy-density physics within China. Currently, 10 high-intensity lasers with powers over 100 TW are operational, and about 10 additional lasers are being constructed at various institutes and universities. These facilities operate either independently or are combined with one another, thereby offering substantial support for both Chinese and international research and development efforts in high-energy-density physics.

We replicate and extend Jia, You, and Du's (2012) study. We added samples from the last 13 years (from 2011 to 2023) and analyzed these new samples using the same methodology as the 2012 article. Our replication found that in the last 13 years, 4 articles in the six leading journals and 16 articles in Management and Organization Review (MOR) have the highest degree of Chinese contextualization in concepts (what), their relationships (how), and the logics underlying the relationships (why). The Chinese context continues to contribute novel knowledge. The extension study fully demonstrates that in the 20 years since its birth, MOR has been on the path of pursuing its original aspiration and realizing its mission. On the what, why, and joint contextualization dimensions, the proportion of articles published in MOR with high contextualized theoretical contributions is higher than the proportion in the six leading journals. On the theory-building dimension, the overall degree of the articles published in MOR is higher than that of those published in the six leading journals. This indicates that MOR publishes articles that are not only of high quality and make general theoretical contributions, but also are highly relevant to the Chinese context.

How do academics interested in the study of legal topics that implicate the state relate to and deal with pressures that shape the space available to conduct research? This article examines the nature and impact of such pressures on Asia-focused public law scholars who must contend with a more diverse socio-political environment than the liberal democratic setting in which questions of academic freedom are typically explored. We find that the Asia-centric academy is affected by a wide range of constraints that notably extends beyond intra-institutional demands to those put in place by the state. This article also highlights how the scholarly agenda as set in and by the Global North may reduce the room for Asia-centric research to engage in theory-building and concept formation and explores how Asia-centric scholars can assert agency in the face of pressures. We conclude by emphasising the need for greater self-reflectivity within the legal academy.

A three-dimensional robust nonlinear cooperative guidance law is proposed to address the challenge of multiple missiles intercepting manoeuvering targets under stringent input constraints and thruster failure. The finite-time convergence theory is used to design a distributed nonlinear sliding mode guidance law, ensuring that the system converges in finite time, with the upper limit of convergence time related to the initial state. A nonlinear sliding surface is adopted to mitigate actuator saturation issues. Then, considering thruster failure, a robust cooperative guidance law is further introduced, ensuring mission completion through the reconstruction of the guidance law. The closed-loop system is proven to be stable using Lyapunov theory, and the influence of hyperparameters on the cooperative guidance law is analysed. Additionally, the results of numerical simulations and hardware-in-the-loop experiments demonstrate the effectiveness and robustness of the proposed algorithm in dealing with stringent input saturation and various disturbances.

Public acceptability is crucial for the effectiveness of policy implementation. The carbon trading market is widely adopted by many countries and regions to achieve carbon neutrality and mitigate climate change. Our paper utilizes China's carbon trading market as a quasi-natural experiment, drawing on microdata from the China Residential Energy Consumption Survey to analyze the policy's impact on public acceptance of carbon pricing. We find that the carbon trading market significantly reduces the acceptability of carbon prices among households working in carbon-related industries in the pilot areas. This conclusion is still valid after a series of robustness checks. Regarding the mechanism of influence, the carbon trading market raises households' perceived costs, mainly reflected in the negative impact of rising product prices and increasing living costs. Finally, enhancing public perception of carbon, improving the distribution effect and decreasing the information asymmetry of the policy implementation can improve public acceptability of carbon prices.

DNA barcoding approaches have been successfully applied for estimating diet composition. However, an accurate quantification in the diets of herbivores remains to be achieved. In the current study, we present a novel methodology that reveals the relationship between the actual proportions (by mass) of each herbage species in the diets and the relative proportions of the ITS2 gene sequences obtained from faecal samples to evaluate the diet composition of sheep in a meadow steppe. Nine common and twelve rare species of plants were employed for formulating six diets, along with the addition of feed supplements for improving the growth performance of sheep. Faecal samples were collected for DNA analysis over the period spanning days 7–12. A significant positive correlation (Spearman’s ρ = 0.389) was obtained between the actual proportions (by mass) of the herbage in the diet provided and the relative abundance of ITS2 sequences obtained from the faecal samples. A significant regression coefficient was found between the relative abundance of all common species and their respective herbage mass proportions. The accuracy of the relation equations, evaluated by utilizing the similarity coefficient, showed 84.69% similarity between the actual diet composition and the correct percentage. Taken together, the current study has provided empirical evidence for the accuracy and applicability of ITS2 as a DNA barcode for obtaining quantitative information about the diet composition of sheep grazing in species-rich grasslands.

C-type lectins (CTLs), a diverse family of pattern recognition receptors, are essential for immune recognition and pathogen clearance in invertebrates. TcCTL17 contains one carbohydrate recognition domain and three scavenger receptor Cys-rich domains. Spatial and temporal expression analysis revealed that TcCTL17 is highly expressed in early pupa, early adult stages, and the larval gut at 20 days. The recombinant TcCTL17 exhibited dose-dependent binding to lipopolysaccharides and peptidoglycans, Ca2+-dependent binding and agglutination of bacteria in vitro. Knocking down TcCTL17 before bacterial exposure reduced survival rates and increased bacterial loads in T. castaneum larvae, accompanied by decreased antimicrobial peptide expression and haemolymph phenoloxidase activity. Additionally, TcCTL17 RNA interference caused developmental abnormalities, affecting metamorphosis and fecundity, possibly by influencing the 20E, JH, and vitellogenin pathways. These findings underscore dual functions of TcCTL17 in immunity and development, making it a potential target for pest management.

Network meta-analysis (NMA), also known as mixed treatment comparison meta-analysis or multiple treatments meta-analysis, extends conventional pairwise meta-analysis by simultaneously synthesizing multiple interventions in a single integrated analysis. Despite the growing popularity of NMA within comparative effectiveness research, it comes with potential challenges. For example, within-study correlations among treatment comparisons are rarely reported in the published literature. Yet, these correlations are pivotal for valid statistical inference. As demonstrated in earlier studies, ignoring these correlations can inflate mean squared errors of the resulting point estimates and lead to inaccurate standard error estimates. This article introduces a composite likelihood-based approach that ensures accurate statistical inference without requiring knowledge of the within-study correlations. The proposed method is computationally robust and efficient, with substantially reduced computational time compared to the state-of-the-science methods implemented in R packages. The proposed method was evaluated through extensive simulations and applied to two important applications including an NMA comparing interventions for primary open-angle glaucoma, and another comparing treatments for chronic prostatitis and chronic pelvic pain syndrome.