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Objective: To find a viable alternative to reduce the number of doses required for the patients with post-traumatic stress disorder (PTSD), and to improve efficacy and patient compliance. Methods: In this study, we used ginger oil, a phytochemical with potential therapeutic properties, to prepare ginger oil patches. High-performance liquid chromatography (HPLC) was used to quantify the main active component of ginger oil, 6-gingerol. Transdermal absorption experiments were conducted to optimize the various pressure-sensitive adhesives and permeation enhancers, including their type and concentration. Subsequently, the ginger oil patches were optimized and subjected to content determination and property evaluations. A PTSD mouse model was established using the foot-shock method. The therapeutic effect of ginger oil patches on PTSD was assessed through pathological sections, behavioral tests, and the evaluation of biomarkers such as tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), brain-derived neurotrophic factor (BDNF), and melatonin (MT). Results: The results demonstrated that ginger oil patches exerted therapeutic effects against PTSD by inhibiting inflammatory responses and modulating MT and BDNF levels. Pharmacokinetic experiments revealed that ginger oil patches maintained a stable blood drug concentration for at least one day, addressing the rapid metabolism drawback of 6-gingerol and enhancing its therapeutic efficacy. Conclusions: Ginger oil can be prepared as a transdermal drug patch that meets these requirements, and the bioavailability of the prepared patch is better than that of oral administration. It can improve PTSD with good patient compliance and ease of administration. Therefore, it is a promising therapeutic formulation for the treatment of PTSD.

Abstract Post-hepatectomy liver failure (PHLF) is a potentially life-threatening complication following liver resection. Hepatocellular carcinoma (HCC) often occurs in patients with chronic liver disease, which increases the risk of PHLF. This study aimed to investigate the ability of the combination of liver function and fibrosis markers (ALBI score and FIB-4 index) to predict PHLF in patients with HCC. Patients who underwent hepatectomy for HCC between August 2012 and September 2022 were considered for inclusion. Multivariable logistic regression analysis was used to identify factors associated with PHLF, and ALBI score and FIB-4 index were combined based on their regression coefficients. The performance of the combined ALBI-FIB4 score in predicting PHLF and postoperative mortality was compared with Child–Pugh score, MELD score, ALBI score, and FIB-4 index. A total of 215 patients were enrolled in this study. PHLF occurred in 35 patients (16.3%). The incidence of severe PHLF (grade B and grade C PHLF) was 9.3%. Postoperative 90‐d mortality was 2.8%. ALBI score, FIB-4 index, prothrombin time, and extent of liver resection were identified as independent factors for predicting PHLF. The AUC of the ALBI-FIB4 score in predicting PHLF was 0.783(95%CI: 0.694–0.872), higher than other models. The ALBI-FIB4 score could divide patients into two risk groups based on a cut-off value of − 1.82. High-risk patients had a high incidence of PHLF of 39.1%, while PHLF just occurred in 6.6% of low-risk patients. Similarly, the AUCs of the ALBI-FIB4 score in predicting severe PHLF and postoperative 90-d mortality were also higher than other models. Preoperative ALBI-FIB4 score showed good performance in predicting PHLF and postoperative mortality in patients undergoing hepatectomy for HCC, superior to the currently commonly used liver function and fibrosis scoring systems.

Abstract Various therapies have been utilized for treating diabetic wounds, yet current regiments do not simultaneously address the key intrinsic causes of slow wound healing, i.e., abnormal skin cell functions (particularly migration), delayed angiogenesis, and chronic inflammation. To address this clinical gap, we develop a wound dressing that contains a peptide-based TGFβ receptor II inhibitor (PTβR2I), and a thermosensitive and reactive oxygen species (ROS)-scavenging hydrogel. The wound dressing can quickly solidify on the diabetic wounds following administration. The released PTβR2I inhibits the TGFβ1/p38 pathway, leading to improved cell migration and angiogenesis, and decreased inflammation. Meanwhile, the PTβR2I does not interfere with the TGFβ1/Smad2/3 pathway that is required to regulate myofibroblasts, a critical cell type for wound healing. The hydrogel’s ability to scavenge ROS in diabetic wounds further decreases inflammation. Single-dose application of the wound dressing significantly accelerates wound healing with complete wound closure after 14 days. Overall, using wound dressings capable of adaptively modulating TGFβ pathways provides a new strategy for diabetic wound treatment.

MG53 is an essential component of the cell membrane repair machinery, participating in the healing of dermal wounds. Here we develop a novel delivery system using recombinant human MG53 (rhMG53) protein and a reactive oxygen species (ROS)-scavenging gel to treat diabetic wounds. Mice with ablation of MG53 display defective hair follicle structure, and topical application of rhMG53 can promote hair growth in the mg53−/− mice. Cell lineage tracing studies reveal a physiological function of MG53 in modulating the proliferation of hair follicle stem cells (HFSCs). We find that rhMG53 protects HFSCs from oxidative stress-induced apoptosis and stimulates differentiation of HSFCs into keratinocytes. The cytoprotective function of MG53 is mediated by STATs and MAPK signaling in HFSCs. The thermosensitive ROS-scavenging gel encapsulated with rhMG53 allows for sustained release of rhMG53 and promotes healing of chronic cutaneous wounds and hair follicle development in the db/db mice. These findings support the potential therapeutic value of using rhMG53 in combination with ROS-scavenging gel to treat diabetic wounds.

Abstract Recently, the physical limitation of range‐domain security guarantee for directional modulation with frequency diverse array was disclosed in Ding et al. (IEEE Access 8, 63302–63309 (2020)). Therefore, to recreate this significant secrecy realisation in both direction and range domain, the authors conceive an artificial noise aided directional modulation scheme via reconfigurable intelligent surface. Specifically, the angle of departure from the reconfigurable intelligent surface to co‐direction receivers varies with distance, which provides the freedom to distinguish users in the range domain. With locations of the active eavesdroppers, an optimisation problem is further formulated to maximise the secrecy rate, which is then solved by applying genetic algorithm and alternating optimisation. On the other hand, when the eavesdroppers are silent, we employ maximum‐ratio transmission precoding and artificial noise to guarantee information security. Finally, simulation results demonstrate that, due to the aid of reconfigurable intelligent surface, the developed directional modulation structure can robustly guarantee the information security in the range domain, whether the information of eavesdroppers is achieved.

Abstract Polysaccharides from the rhizome of Polygonatum sibiricum display a variety of biological activities, including the regulation of intestinal microbiota, but the polysaccharides from the leaves of P. sibiricum have not been studied extensively. Here, we extracted crude polysaccharides from the leaves of P. sibiricum and further separated and purified them to study the effects of P. sibiricum polysaccharides (PsPs) on intestinal microbes and short-chain fatty acids (SCFAs). The PsPs had a total sugar content of 97.48% and a monosaccharide composition comprising mannose, rhamnose, galacturonic acid, glucose, xylose, and arabinose, with molar ratios of 6.6:15.4:4.5:8.8:40.7:24, respectively. The effects of PsPs on intestinal microflora in mice were also studied, with 16S sequencing results showing an increase in the relative abundance of Firmicutes and a decrease in Bacteroidetes at the phylum level. The abundance of Lactobacillus increased, while those of Lachnospiraceae and Bacteroides reduced (at the genus level) by PsPs treatment. The composition of microbes changed. Levels of SCFAs in the PsPs group were significantly increased compared with control mice, including acetic acid, propionic acid, and butyric acid. These results suggest that PsPs can act as prebiotics, regulating the intestinal tract probiotics.

Groundwater age and groundwater residence time contain important information about groundwater circulation and evolutionary processes, and have been widely used in the study of groundwater circulation patterns in basins.In this paper, we simulated a three-stage flow system model through a multi-stage groundwater flow system demonstrator, and simulated the groundwater age distribution and groundwater residence time distribution based, and found that the bottom of the basin, the downstream of the regional flow, and the basin retention area responded the latest.The local flow system in the shallow part has relatively low concentration values after stabilization, the intermediate flow system is also relatively low compared to the regional flow system in the deep part, and the stagnant zone has relatively large concentration values due to salt accumulation.The groundwater age distribution curves are single-peaked, and the circulation time of the regional flow system is greater than that of the intermediate flow system than that of the local flow system.The residence time distribution monitored in the discharge zones shows that different levels of recharge will produce early, middle and late peaks, and the peaks correspond exactly to the level of the groundwater flow system.It can be judged from the peaks in the discharge zones that the groundwater is recharged from the local, intermediate or regional flow system, and thus the source of contaminants can be determined.The present research results have some significance for the evolution of groundwater circulation and the improvement of groundwater flow system theory.

Dendrobium nobile (Lindl.) have long been used as herbal tea and a traditional herbal medicine to treat Alzheimer’s disease (AD). In the current study, nineteen compounds (1–19), including two new vitamin E homologues (1–2), one new sesquiterpene (6), and two new dendrobines (7, 8), were isolated and identified from stems of Dendrobium nobile. Their structures were elucidated on the basis of NMR, 13C NMR calculation, and DP4+ probability analyses. The absolute configurations of new compounds were determined by electronic circular dichroism (ECD) data analysis. Antioxidant, anti-inflammatory, and cytotoxic activities of isolated compounds were evaluated. Among them, compound 2 demonstrated significant antioxidant activity compared with ascorbic acid (VC), while compounds 2 and 4 also exhibited an equal effect to positive control cisplatin. This study on the biological activity of the new vitamin E homologues from Dendrobium nobile may indicate its potential application in the pharmaceutical and food industries.

Angelica dahurica is an ancient herbaceous plant and a famous traditional Chinese medicine. A. dahurica polysaccharides (AdPs) are macromolecular bioactive carbohydrates that have many functions. The animal gut contains a remarkable abundance of microbes that are closely related and play a major role in maintaining the overall health. The intestinal flora is also known as the ‘second genome’ of the human body. To study the functional interactions between AdPs and gut microbiota, we extracted AdPs using water extraction. After a series of treatments, including degreasing, alcohol precipitation, protein decolorization and purification by cellulose column, 200 mg/kg of purified AdPs were administered daily to 5 weeks old Kunming (KM) mice for 21 days. Microbial composition was evaluated in fecal samples using high-throughput sequencing. Our results revealed that AdPs affected the composition and structure of gut microbiota and can potentially regulate the intestinal flora as prebiotics.

Five undescribed polyketide derivatives, pestaloketides A–E (1–5), along with eleven known analogues (6–16), were isolated from the sponge-derived fungus Pestalotiopsis sp. Their structures, including absolute configurations, were elucidated by analyses of NMR spectroscopic HRESIMS data and electronic circular dichroism (ECD) calculations. Compounds 5, 6, 9, and 14 exhibited weak cytotoxicities against four human cancer cell lines, with IC50 values ranging from 22.1 to 100 μM. Pestaloketide A (1) is an unusual polyketide, featuring a rare 5/10/5-fused ring system. Pestaloketides A (1) and B (2) exhibited moderately inhibited LPS-induced NO production activity, with IC50 values of 23.6 and 14.5 μM, respectively, without cytotoxicity observed. Preliminary bioactivity evaluations and molecular docking analysis indicated that pestaloketides A (1) and B (2) had the potential to be developed into anti-inflammatory activity drug leads.

Abstract Background Fatty acids are important traits that affect meat quality and nutritive values in beef cattle. Detection of genetic variants for fatty acid composition can help to elucidate the genetic mechanism underpinning these traits and promote the improvement of fatty acid profiles. In this study, we performed a genome-wide association study (GWAS) on fatty acid composition using high-density single nucleotide polymorphism (SNP) arrays in Chinese Wagyu cattle. Results In total, we detected 15 and 8 significant genome-wide SNPs for individual fatty acids and fatty acid groups in Chinese Wagyu cattle, respectively. Also, we identified nine candidate genes based on 100 kb regions around associated SNPs. Four SNPs significantly associated with C14:1 cis-9 were embedded with stearoyl-CoA desaturase (SCD), while three SNPs in total were identified for C22:6 n-3 within Phospholipid scramblase family member 5 (PLSCR5), Cytoplasmic linker associated protein 1 (CLASP1), and Chymosin (CYM). Notably, we found the top candidate SNP within SCD can explain ~ 7.37% of phenotypic variance for C14:1 cis-9. Moreover, we detected several blocks with high LD in the 100 kb region around SCD. In addition, we found three significant SNPs within a 100 kb region showing pleiotropic effects related to multiple FA groups (PUFA, n-6, and PUFA/SFA), which contains BAI1 associated protein 2 like 2 (BAIAP2L2), MAF bZIP transcription factor F (MAFF), and transmembrane protein 184B (TMEM184B). Conclusions Our study identified several significant SNPs and candidate genes for individual fatty acids and fatty acid groups in Chinese Wagyu cattle, and these findings will further assist the design of breeding programs for meat quality in cattle.

Pot experiments were conducted to evaluate the effects of magnetized water irrigation (100 mT) and root cutting (three pruning intensities) on phytoremediation efficiency of Celosia argentea. In the absence of magnetic field treatment, low root cutting intensity increased the dry weight of the below-ground and aerial parts of C. argentea. Moderate and severe cutting intensities decreased the biomass yield of the plant roots by 11.3% and 31.0%, and increased the dry weight of aerial parts by 75.9% and 27.6%, respectively, alleviating the detrimental effects of these pruning treatments on the plant roots. In the presence of magnetic field treatment, 10% and 25% of pruning treatments increased the dry weight of plant roots by 52.1% and 33.8%, and 33% pruning treatment decreased it by 14.1%. Under both irrigation treatments, low and moderate root cutting strategies did not affect the take up of Cd by the plant roots, while severe cutting decreased it significantly. Enzyme activities decreased with the increment of pruning intensity, and magnetic field can alleviate the negative impact, increasing the capacity of the root pruned species to scavenge the excessive ROS induced by the accumulated Cd. The results showed that root pruning enhanced the phytoremediation efficiency of C. argentea, and this effect was enhanced when combined with magnetized water irrigation.

Abstract Background Running multiple-chain Markov Chain Monte Carlo (MCMC) provides an efficient parallel computing method for complex Bayesian models, although the efficiency of the approach critically depends on the length of the non-parallelizable burn-in period, for which all simulated data are discarded. In practice, this burn-in period is set arbitrarily and often leads to the performance of far more iterations than required. In addition, the accuracy of genomic predictions does not improve after the MCMC reaches equilibrium. Results Automatic tuning of the burn-in length for running multiple-chain MCMC was proposed in the context of genomic predictions using BayesA and BayesCπ models. The performance of parallel computing versus sequential computing and tunable burn-in MCMC versus fixed burn-in MCMC was assessed using simulation data sets as well by applying these methods to genomic predictions of a Chinese Simmental beef cattle population. The results showed that tunable burn-in parallel MCMC had greater speedups than fixed burn-in parallel MCMC, and both had greater speedups relative to sequential (single-chain) MCMC. Nevertheless, genomic estimated breeding values (GEBVs) and genomic prediction accuracies were highly comparable between the various computing approaches. When applied to the genomic predictions of four quantitative traits in a Chinese Simmental population of 1217 beef cattle genotyped by an Illumina Bovine 770 K SNP BeadChip, tunable burn-in multiple-chain BayesCπ (TBM-BayesCπ) outperformed tunable burn-in multiple-chain BayesCπ (TBM-BayesA) and Genomic Best Linear Unbiased Prediction (GBLUP) in terms of the prediction accuracy, although the differences were not necessarily caused by computational factors and could have been intrinsic to the statistical models per se. Conclusions Automatically tunable burn-in multiple-chain MCMC provides an accurate and cost-effective tool for high-performance computing of Bayesian genomic prediction models, and this algorithm is generally applicable to high-performance computing of any complex Bayesian statistical model.

One strain-many compounds (OSMAC) manipulation of the sponge-derived fungus Pestalotiopsis heterocornis XWS03F09 resulted in the production of new secondary metabolites. The chemical study of the fermentation, cultivated on 3% artificial sea salt in the rice media, led to the isolation of twelve compounds, including eight new polyketide derivatives, heterocornols Q–X (1–8), one new ceramide (9), and three known analogues (10–12). The structures and absolute configurations of the new compounds were elucidated by spectroscopic data and calculated ECD analysis. Heterocornols Q (1) and R (2) are novel 6/5/7/5 tetracyclic polyketide derivatives featuring dihydroisobenzofuran and benzo-fused dioxabicyclo [4.2.1] nonane system, which might be derived from the acetyl-CoA by epoxidation, polyene cyclization, and rearrangement to form the core skeleton. Compound 12 showed moderate or weak antimicrobial activities against with MIC values ranging from 25 to 100 μg/mL. Heterocornols T and X (7 and 8) could inhibit the production of LPS-induced NO significantly, comparable to dexamethasone. Further Western blotting analysis showed 7 and 8 markedly suppressed the iNOS protein expression in LPS-induced RAW 264.7 cells in a dose-dependent manner. The result showed that 7 and 8 might serve as potential leads for development of anti-inflammatory activity.

Abstract: Traditionally, Chinese indigenous cattle is geographically widespread. The present study analyzed based on genome-wide variants to evaluate the genetic background among 157 individuals from four representative indigenous cattle breeds of Hubei Province of China: Yiling yellow cattle (YL), Bashan cattle (BS), Wuling cattle (WL), Zaobei cattle (ZB), and 21 individuals of Qinchuan cattle (QC) from the nearby Shanxi Province of China. Linkage disequilibrium (LD) analysis showed the LD of YL was the lowest (r2=0.32) when the distance between markers was approximately 2 kb. Principle component analysis (PCA), and neighbor-joining (NJ)-tree revealed a separation of Yiling yellow cattle from other geographic nearby local cattle breeds. In PCA plot, the YL and QC groups were segregated as expected; moreover, YL individuals clustered together more obviously. In the NJ-tree, the YL group formed an independent branch and BS, WL, ZB groups were mixed. We then used the FST statistic approach to reveal long-term selection sweep of YL and other 4 cattle breeds. According to the selective sweep, we identified the unique pathways of YL, associated with production traits. Based on the results, it can be proposed that YL has its unique genetic characteristics of excellence resource, and it is an indispensable cattle breed in China.

Abstract Background Fatty acid composition of muscle is an important trait contributing to meat quality. Recently, genome-wide association study (GWAS) has been extensively used to explore the molecular mechanism underlying important traits in cattle. In this study, we performed GWAS using high density SNP array to analyze the association between SNPs and fatty acids and evaluated the accuracy of genomic prediction for fatty acids in Chinese Simmental cattle. Results Using the BayesB method, we identified 35 and 7 regions in Chinese Simmental cattle that displayed significant associations with individual fatty acids and fatty acid groups, respectively. We further obtained several candidate genes which may be involved in fatty acid biosynthesis including elongation of very long chain fatty acids protein 5 (ELOVL5), fatty acid synthase (FASN), caspase 2 (CASP2) and thyroglobulin (TG). Specifically, we obtained strong evidence of association signals for one SNP located at 51.3 Mb for FASN using Genome-wide Rapid Association Mixed Model and Regression-Genomic Control (GRAMMAR-GC) approaches. Also, region-based association test identified multiple SNPs within FASN and ELOVL5 for C14:0. In addition, our result revealed that the effectiveness of genomic prediction for fatty acid composition using BayesB was slightly superior over GBLUP in Chinese Simmental cattle. Conclusions We identified several significantly associated regions and loci which can be considered as potential candidate markers for genomics-assisted breeding programs. Using multiple methods, our results revealed that FASN and ELOVL5 are associated with fatty acids with strong evidence. Our finding also suggested that it is feasible to perform genomic selection for fatty acids in Chinese Simmental cattle.

Genomic selection has been demonstrated as a powerful technology to revolutionize animal breeding. However, marker density and minor allele frequency can affect the predictive ability of genomic estimated breeding values (GEBVs). To investigate the impact of marker density and minor allele frequency on predictive ability, we estimated GEBVs by constructing the different subsets of single nucleotide polymorphisms (SNPs) based on varying markers densities and minor allele frequency (MAF) for average daily gain (ADG), live weight (LW) and carcass weight (CW) in 1 059 Chinese Simmental beef cattle. Two strategies were proposed for SNP selection to construct different marker densities: 1) select evenly-spaced SNPs (Strategy 1), and 2) select SNPs with large effects estimated from BayesB (Strategy 2). Furthermore, predictive ability was assessed in terms of the correlation between predicted genomic values and corrected phenotypes from 10-fold cross-validation. Predictive ability for ADG, LW and CW using autosomal SNPs were 0.13±0.002, 0.21±0.003 and 0.25±0.003, respectively. In our study, the predictive ability increased dramatically as more SNPs were included in analysis until 200K for Strategy 1. Under Strategy 2, we found the predictive ability slightly increased when marker densities increased from 5K to 20K, which indicated the predictive ability of 20K (3% of 770K) SNPs with large effects was equal to the predictive ability of using all SNPs. For different MAF bins, we obtained the highest predictive ability for three traits with MAF bin 0.01–0.1. Our result suggested that designing a low-density chip by selecting low frequency markers with large SNP effects sizes should be helpful for commercial application in Chinese Simmental cattle.

The residence time distribution (RTD) curve is widely applied to describe the fluid flow in a tundish, different tracer mass concentrations and different tracer volumes give different residence time distribution curves for the same flow field. Thus, it is necessary to have a deep insight into the effects of the mass concentration and the volume of tracer solution on the residence time distribution curve. In order to describe the interaction between the tracer and the fluid, solute buoyancy is considered in the Navier–Stokes equation. Numerical results show that, with the increase of the mass concentration and the volume of the tracer, the shape of the residence time distribution curve changes from single flat peak to single sharp peak and then to double peaks. This change comes from the stratified flow of the tracer. Furthermore, the velocity difference number is introduced to demonstrate the importance of the density difference between the tracer and the fluid.

Four new compounds, including two new polyketides, heterocornols M and N (1, 2), and a pair of epimers, heterocornols O and P (3, 4), were isolated from the fermentation broth of the marine sponge-derived fungus Pestalotiopsis heterocornis XWS03F09, together with three known compounds (5−7). The new chemical structures were established on the basis of a spectroscopic analysis, optical rotation, experimental and calculated electronic circular dichroism (ECD). All of the compounds (1−7) were evaluated for their cytotoxic activities, and heterocornols M-P (1−4) exhibited cytotoxicities against four human cancer cell lines with IC50 values of 20.4−94.2 μM.

Genomic selection has been widely used for complex quantitative trait in farm animals. Estimations of breeding values for slaughter traits are most important to beef cattle industry, and it is worthwhile to investigate prediction accuracies of genomic selection for these traits. In this study, we assessed genomic predictive abilities for average daily gain weight (ADG), live weight (LW), carcass weight (CW), dressing percentage (DP), lean meat percentage (LMP) and retail meat weight (RMW) using Illumina Bovine 770K SNP Beadchip in Chinese Simmental cattle. To evaluate the abilities of prediction, marker effects were estimated using genomic BLUP (GBLUP) and three parallel Bayesian models, including multiple chains parallel BayesA, BayesB and BayesCπ (PBayesA, PBayesB and PBayesCπ). Training set and validation set were divided by random allocation, and the predictive accuracies were evaluated using 5-fold cross validations. We found the accuracies of genomic predictions ranged from 0.195±0.084 (GBLUP for LMP) to 0.424±0.147 (PBayesB for CW). The average accuracies across traits were 0.327±0.085 (GBLUP), 0.335±0.063 (PBayesA), 0.347±0.093 (PBayesB) and 0.334±0.077 (PBayesCπ), respectively. Notably, parallel Bayesian models were more accurate than GBLUP across six traits. Our study suggested that genomic selections with multiple chains parallel Bayesian models are feasible for slaughter traits in Chinese Simmental cattle. The estimations of direct genomic breeding values using parallel Bayesian methods can offer important insights into improving prediction accuracy at young ages and may also help to identify superior candidates in breeding programs.

Three conventional Bayesian approaches (BayesA, BayesB and BayesCπ) have been demonstrated to be powerful in predicting genomic merit for complex traits in livestock. A priori, these Bayesian models assume that the non-zero SNP effects (marginally) follow a t-distribution depending on two fixed hyperparameters, degrees of freedom and scale parameters. In this study, we performed genomic prediction in Chinese Simmental beef cattle and treated degrees of freedom and scale parameters as unknown with inappropriate priors. Furthermore, we compared the modified methods (BayesFA, BayesFB and BayesFCπ) with their corresponding counterparts using simulation datasets. We found that the modified methods with distribution assumed to the two hyperparameters were beneficial for improving the predictive accuracy. Our results showed that the predictive accuracies of the modified methods were slightly higher than those of their counterparts especially for traits with low heritability and a small number of QTLs. Moreover, cross-validation analysis for three traits, namely carcass weight, live weight and tenderloin weight, in 1136 Simmental beef cattle suggested that predictive accuracy of BayesFCπ noticeably outperformed BayesCπ with the highest increase (3.8%) for live weight using the cohort masking cross-validation.

Carcass traits of beef cattle have been genetically improved to increase yield of high quality meat. Genome-wide association study (GWAS) is a powerful method to identify genetic variants associated with carcass traits. For the 770K genotyped SNPs from 1141 Chinese Simmental cattle, we used the compressed mixed linear model (CMLM) to perform a genome-wide association study for knuckle, biceps and shank of beef carcass traits. Seventeen significantly associated SNPs were found, which are located on BTA6, BTA14 and BTA15. Interestingly, one pleiotropic quantitative trait nucleotide (QTN), named BovineHD1400007259 (p < 10-8) within the well-known gene region PLAG1-CHCHD7 on BTA14, was found to govern variation of the knuckle, biceps and shank traits. The QTN accounted for 8.6% of phenotypic variance for biceps. In addition, 16 more SNPs distributed on BTA14 were detected as being associated with the carcass traits.

To keep the resources renewable, a singular ecological-economic model is proposed for the populations with harvesting and migration. The local stability and the dynamic behavior of the model are studied. Singular induced bifurcation appears when economic interest is zero, which is different from the ordinary differential models. In order to apply variable structure control to eliminate these complex behaviors, the singular model is transformed into a single-input and single-output model with parameter varying within definite intervals. And then, a variable structure controller is designed to make the model stable. Finally, an inshore-offshore fishery model is given to illustrate the proposed method, and some numerical simulations are shown to demonstrate the control results.

Biomass, heralded as sustainable "green coal", plays a crucial role in energy conservation and achieving "dual carbon" objectives through clean conversion. This paper reviews advancements in biomass catalytic gasification, a technology pivotal for converting biomass to hydrogen-rich fuel and syngas. It highlights the efficiency gains afforded by various catalysts, including natural minerals, alkali metals, nickel-based compounds, zeolites, and rare earth-modified composites. The focus is on their influence on hydrogen output, syngas quality, and tar reduction. The synthesis of these insights paves the way for novel catalyst development and optimized gasification processes, hence advancing catalytic gasification technology toward more sustainable energy solutions. [ABSTRACT FROM AUTHOR]

Radiative cooling glass with spectral selectivity is an effective energy-saving strategy for buildings and vehicles. Nevertheless, the current research still has limitations; for example, the absorption of ultraviolet light by the glass results in a large amount of heat generated inside the space, which affects the radiative cooling performance. Herein, distinct spectral bands of solar radiation are precisely controlled through independently designing epsilon-near-zero (ENZ) regions within the hyperbolic metamaterials (HMMs) composed of Ag/SiO2 and Ag/TiO2 nanoscale-thick layers, which exhibit outstanding spectral regulation capability. The HMM glass features a high visible light transmittance (0.654), superior near-infrared reflectance (0.858), and good ultraviolet reflectance (0.576), while also possessing a high infrared emissivity of 95.6% in the atmospheric window. Outdoor simulation results suggest that with a convective heat transfer coefficient of 6 W/(m² K), the internal equilibrium temperature of the HMM glass can be reduced by 32.8°C compared to that of normal glass. Furthermore, the HMM glass can save up to 91.8-216.4 MJ/m² of cooling energy annually in China in comparison to normal glass. The radiative cooling glass showcased in this work, with its superior spectral regulation capabilities, plays a crucial role in energy conservation and fostering sustainable progress and thus makes it suitable for use in building glass curtain walls or roofs, vehicles windows, and so on. [ABSTRACT FROM AUTHOR]