Observation of 2D-magnesium-intercalated gallium nitride superlattices.

Since the demonstration of p-type gallium nitride (GaN) through doping with substitutional magnesium (Mg) atoms1,2, rapid and comprehensive developments, such as blue light-emitting diodes, have considerably shaped our modern lives and contributed to a more carbon-neutral society3-5. However, the details of the interplay between GaN and Mg have remained largely unknown6-11. Here we observe that Mg-intercalated GaN superlattices can form spontaneously by annealing a metallic Mg film on GaN at atmospheric pressure. To our knowledge, this marks the first instance of a two-dimensional metal intercalated into a bulk semiconductor, with each Mg monolayer being intricately inserted between several monolayers of hexagonal GaN. Characterized as an interstitial intercalation, this process induces substantial uniaxial compressive strain perpendicular to the interstitial layers. Consequently, the GaN layers in the Mg-intercalated GaN superlattices exhibit an exceptional elastic strain exceeding -10% (equivalent to a stress of more than 20 GPa), among the highest recorded for thin-film materials12. The strain alters the electronic band structure and greatly enhances hole transport along the compression direction. Furthermore, the Mg sheets induce a unique periodic transition in GaN polarity, generating polarization-field-induced net charges. These characteristics offer fresh insights into semiconductor doping and conductivity enhancement, as well as into elastic strain engineering of nanomaterials and metal-semiconductor superlattices13.

Correlation Between Basal Metabolic Rate and Clinical Outcomes in Gastric Cancer Patients: A Retrospective Study.

OBJECTIVES: Hypermetabolism is associated with clinical prognosis of cancer patients. The aim of this study was to explore the association between basal metabolic rate (BMR) and postoperative clinical outcomes in gastric cancer patients. METHODS: We collected data of 958 gastric cancer patients admitted at our center from June 2014 to December 2018. The optimal cutoff value of BMR (BMR ≤1149 kcal/day) was obtained using the X-tile plot. Logistic and Cox regression analyses were then performed to evaluate the relevant influencing factors of clinical outcomes. Finally, R software was utilized to construct the nomogram. RESULTS: A total of 213 patients were defined as having a lower basal metabolic rate (LBMR). Univariate and multivariate analyses showed that gastric cancer patients with LBMR were more prone to postoperative complications and had poor long-term overall survival (OS). The established nomogram had good predictive power to assess the risk of OS in gastric cancer patients after radical gastrectomy (c-index was 0.764). CONCLUSIONS: Overall, LBMR on admission is associated with the occurrence of postoperative complications in gastric cancer patients, and this population has a poorer long-term survival. Therefore, there should be more focus on the perioperative management of patients with this risk factor before surgery.

Cis-eQTLs in seven duck tissues identify novel candidate genes for growth and carcass traits.

BACKGROUND: Expression quantitative trait loci (eQTL) studies aim to understand the influence of genetic variants on gene expression. The colocalization of eQTL mapping and GWAS strategy could help identify essential candidate genes and causal DNA variants vital to complex traits in human and many farm animals. However, eQTL mapping has not been conducted in ducks. It is desirable to know whether eQTLs within GWAS signals contributed to duck economic traits. RESULTS: In this study, we conducted an eQTL analysis using publicly available RNA sequencing data from 820 samples, focusing on liver, muscle, blood, adipose, ovary, spleen, and lung tissues. We identified 113,374 cis-eQTLs for 12,266 genes, a substantial fraction 39.1% of which were discovered in at least two tissues. The cis-eQTLs of blood were less conserved across tissues, while cis-eQTLs from any tissue exhibit a strong sharing pattern to liver tissue. Colocalization between cis-eQTLs and genome-wide association studies (GWAS) of 50 traits uncovered new associations between gene expression and potential loci influencing growth and carcass traits. SRSF4, GSS, and IGF2BP1 in liver, NDUFC2 in muscle, ELF3 in adipose, and RUNDC1 in blood could serve as the candidate genes for duck growth and carcass traits. CONCLUSIONS: Our findings highlight substantial differences in genetic regulation of gene expression across duck primary tissues, shedding light on potential mechanisms through which candidate genes may impact growth and carcass traits. Furthermore, this availability of eQTL data offers a valuable resource for deciphering further genetic association signals that may arise from ongoing extensive endeavors aimed at enhancing duck production traits.

Genetic parameters and genomic prediction of growth and breast morphological traits in a crossbreed duck population.

Genomic selection (GS) has great potential to increase genetic gain in poultry breeding. However, the performance of genomic prediction in duck growth and breast morphological (BM) traits remains largely unknown. The objective of this study was to evaluate the benefits of genomic prediction for duck growth and BM traits using methods such as GBLUP, single-step GBLUP, Bayesian models, and different marker densities. This study collected phenotypic data for 14 growth and BM traits in a crossbreed population of 1893 Pekin duck × mallard, which included 941 genotyped ducks. The estimation of genetic parameters indicated high heritabilities for body weight (0.54-0.72), whereas moderate-to-high heritabilities for average daily gain (0.21-0.57) traits. The heritabilities of BM traits ranged from low to moderate (0.18-0.39). The prediction ability of GS on growth and BM traits increased by 7.6% on average compared to the pedigree-based BLUP method. The single-step GBLUP outperformed GBLUP in most traits with an average of 0.3% higher reliability in our study. Most of the Bayesian models had better performance on predictive reliability, except for BayesR. BayesN emerged as the top-performing model for genomic prediction of both growth and BM traits, exhibiting an average increase in reliability of 3.0% compared to GBLUP. The permutation studies revealed that 50 K markers had achieved ideal prediction reliability, while 3 K markers still achieved 90.8% predictive capability would further reduce the cost for duck growth and BM traits. This study provides promising evidence for the application of GS in improving duck growth and BM traits. Our findings offer some useful strategies for optimizing the predictive ability of GS in growth and BM traits and provide theoretical foundations for designing a low-density panel in ducks.

Ce doped V-W/Ti as selective catalytic reduction catalysts for cement kiln flue gas denitration.

In cement industry, the selection of catalyst temperature window and the inhibition effect of dust composition in flue gas on catalyst are the key issues of flue gas denitrification. In this article, a pilot study with Ce doped V-W/Ti catalyst on the removal of NOx by selective catalytic reduction with ammonia (NH3-SCR) from the cement kiln flue gas was presented. Cement kiln dust loading on catalysts obviously decreased the NO conversion in the absence of SO2 and H2O, while the denitration efficiency restored from 75 to 98% at 280 ℃ after SO2 and H2O introduced into the reaction system, which mainly because the SO2 may enhance the acidic site on the catalyst surface, and prefer to be bonded with the coordinated Ca species, releasing the active sites poisoned by dust. The NH3-temperature programmed desorption (NH3-TPD), X-ray photoelectron spectroscopy (XPS), and H2-temperature programmed reduction (H2-TPR) detections were performed to reveal that the appropriate Ce and W ratios catalyst contributed better denitrification activity. The optimum ratio of Ce doped catalyst was amplified to form the standard honeycomb monomer catalyst, and then, the activity of catalyst was verified on the side line of cement kiln. The effect of temperature and space velocity on denitrification efficiency was investigated, and the denitration efficiency reached to 92.5% at 300℃ and 3000 h-1 space velocity. Moreover, the life of catalyst was verified and predicted by GM (1,1) grey model. The study realized the innovation from the laboratory data rules to the industrial pilot application, providing positive promoting value for the industrial large-scale demonstration application of the catalyst.

Free-Standing Electrode and Fixed Surface Tiny Electrode Implemented Triboelectric Nanogenerator with High Instantaneous Current.

Conventional triboelectric nanogenerators (TENGs) face challenges pertaining to low output current density at low working frequencies and high internal impedance. While strategies, such as surface modification to enhance surface charge density, permittivity regulation of materials, and circuit management, have partially mitigated these issues. However, they have also resulted in increased complexity in the fabrication process. Therefore, there is an urgent demand for a universal and simplified approach to address these challenges. To fulfill this need, this work presents a free-standing electrode and fixed surface tiny electrode implemented triboelectric nanogenerator (FFI-TENG). It is fabricated by a straightforward yet effective method: introducing a tiny electrode onto the surface of the tribo-negative material. This approach yields substantial enhancements in performance, notably a more than tenfold increase in output current density, a reduction in effective working frequencies, and a decrease in matching resistance as compared to vertical contact-separation TENGs (CS-TENGs) or single-electrode TENGs (SE-TENGs). Simultaneously, a comprehensive examination and proposition regarding the operational mechanism of FFI-TENG, highlighting its extensive applicability are also offered. Significantly, FFI-TENG excels in mechanical energy harvesting even under ultra-low working frequencies (0.1 Hz), outperforming similar contact-separation models. This innovation positions it as a practical and efficient solution for the development of low-entropy energy harvesters.

[Reform and exploration of biopharmaceutics blended teaching in the context of "first-class undergraduate education"].

In recent years, the biopharmaceutical industry has developed rapidly, creating urgent demand for high-quality, innovative, and application-oriented talents. In the context of "first-class undergraduate education", it is of great significance to reform and explore biopharmaceutics blended learning to foster professional talents who can adapt to the industrial development. The blended teaching of biopharmaceutics course in Hubei University was based on small private online course (SPOC) and ChaoXing platform, aiming to meet the first-class "AIC (advanced, innovation, challenge)". The course strengthened the three phases of teaching: before, during, and after class, and innovated teaching methods actively to achieve curriculum goals, and integrated typical cases organically. In addition, the course improved the discriminative power of assessment by strengthening the formative performance evaluation. Moreover, the course provided guidance for students to improve the learning efficiency through investigating the students' learning behavior and employing the marginal utility curve to analyze the characteristics of group activities. Furthermore, the course also offered students personalized learning guidance based on their career planning. The reform of biopharmaceutics blended teaching has achieved significant outcomes, such as improving students' satisfaction, students' innovation and entrepreneurship ability, and curriculum construction level, thus may serve as a reference for the teaching reform and research of the related courses.

Dietary riboflavin supplementation improves meat quality, antioxidant capacity, fatty acid composition, lipidomic, volatilomic, and proteomic profiles of breast muscle in Pekin ducks.

Our objective was to determine effects of supplemental dietary riboflavin on meat quality, antioxidant capacity, fatty acid composition, lipidomic, volatilomic, and proteomic profiling of duck breast muscle. The results showed that dietary riboflavin supplementation significantly increased growth performance, breast meat yield, intramuscular fat content, polyunsaturated fatty acid (PUFA), n3-PUFA, n6-PUFA, redness (a*), and pH24h, but decreased lightness (L*) and yellowness (b*). Furthermore, riboflavin supplementation significantly improved muscle antioxidant capacity based on various biochemical parameters. Lipidomic and volatilomic analyses revealed that riboflavin supplementation markedly increased breast meat phosphatidylglycerol and coenzyme Q contents and two favourable key odorants, citronellyl acetate and 3-(methylthio)-propanal. Proteomics analyses confirmed that riboflavin supplementation activated mitochondrial aerobic respiration, including fatty acid beta oxidation, the tricarboxylic acid cycle, and oxidative phosphorylation. In conclusion, supplementing duck diets with riboflavin enhanced breast meat quality, attributed to increases in antioxidant capacity and mitochondrial functions.

Non-heme Iron Single-Atom Nanozymes as Peroxidase Mimics for Tumor Catalytic Therapy.

Single-atom nanozymes (SAzymes) open new possibilities for the development of artificial enzymes that have catalytic activity comparable to that of natural peroxidase (POD). So far, most efforts have focused on the structural modulation of the Fe-N4 moiety to mimic the metalloprotein heme center. However, non-heme-iron POD with much higher activity, for example, HppE, has not been mimicked successfully due to its structural complexity. Herein, carbon dots (CDs)-supported SAzymes with twisted, nonplanar Fe-O3N2 active sites, highly similar to the non-heme iron center of HppE, was synthesized by exploiting disordered and subnanoscale domains in CDs. The Fe-CDs exhibit an excellent POD activity of 750 units/mg, surpassing the values of conventional SAzymes with planar Fe-N4. We further fabricated an activatable Fe-CDs-based therapeutic agent with near-infrared enhanced POD activity, a photothermal effect, and tumor-targeting ability. Our results represent a big step in the design of high-performance SAzymes and provide guidance for future applications for synergistic tumor therapy.

The effect of metabolic syndrome on postoperative complications and long-term survival of patients with colorectal cancer.

Background: Metabolic syndrome (MetS) is associated with poor prognosis in many cancers. However, the relationship between metabolic syndrome and overall survival (OS) in patients with colorectal cancer (CRC) remains unclear. We aimed to comprehensively analyze whether MetS could affect postoperative complications and long-term survival in patients with CRC. Methods: We included patients who underwent CRC resection at our center between January 2016 and December 2018. Bias was reduced through propensity score matching analysis. Patients with CRC were divided into the MetS and non-MetS groups based on whether they had MetS. Univariate and multivariate analyses were used to identify risk factors affecting OS. Results: We included 268 patients; among them, 120 were included for further analysis after propensity score matching. There were no significant between-group differences in the clinicopathological features after matching. Compared with the non-MetS group, the MetS group had a shorter OS (P = 0.027); however, there was no significant between-group difference in postoperative complications. Multivariate analysis revealed that MetS (hazard ratio [HR] = 1.997, P = 0.042), tumor-node-metastasis stage (HR = 2.422, P = 0.003), and intestinal obstruction (HR = 2.761, P = 0.010) were independent risk factors for OS. Conclusions: MetS affects the long-term survival of patients with CRC without affecting postoperative complications.

The eQTL colocalization and transcriptome-wide association study identify potentially causal genes responsible for economic traits in Simmental beef cattle.

BACKGROUND: A detailed understanding of genetic variants that affect beef merit helps maximize the efficiency of breeding for improved production merit in beef cattle. To prioritize the putative variants and genes, we ran a comprehensive genome-wide association studies (GWAS) analysis for 21 agronomic traits using imputed whole-genome variants in Simmental beef cattle. Then, we applied expression quantitative trait loci (eQTL) mapping between the genotype variants and transcriptome of three tissues (longissimus dorsi muscle, backfat, and liver) in 120 cattle. RESULTS: We identified 1,580 association signals for 21 beef agronomic traits using GWAS. We then illuminated 854,498 cis-eQTLs for 6,017 genes and 46,970 trans-eQTLs for 1,903 genes in three tissues and built a synergistic network by integrating transcriptomics with agronomic traits. These cis-eQTLs were preferentially close to the transcription start site and enriched in functional regulatory regions. We observed an average of 43.5% improvement in cis-eQTL discovery using multi-tissue eQTL mapping. Fine-mapping analysis revealed that 111, 192, and 194 variants were most likely to be causative to regulate gene expression in backfat, liver, and muscle, respectively. The transcriptome-wide association studies identified 722 genes significantly associated with 11 agronomic traits. Via the colocalization and Mendelian randomization analyses, we found that eQTLs of several genes were associated with the GWAS signals of agronomic traits in three tissues, which included genes, such as NADSYN1, NDUFS3, LTF and KIFC2 in liver, GRAMD1C, TMTC2 and ZNF613 in backfat, as well as TIGAR, NDUFS3 and L3HYPDH in muscle that could serve as the candidate genes for economic traits. CONCLUSIONS: The extensive atlas of GWAS, eQTL, fine-mapping, and transcriptome-wide association studies aid in the suggestion of potentially functional variants and genes in cattle agronomic traits and will be an invaluable source for genomics and breeding in beef cattle.

Strategies to improve genomic predictions for 35 duck carcass traits in an F2 population.

BACKGROUND: Carcass traits are crucial for broiler ducks, but carcass traits can only be measured postmortem. Genomic selection (GS) is an effective approach in animal breeding to improve selection and reduce costs. However, the performance of genomic prediction in duck carcass traits remains largely unknown. RESULTS: In this study, we estimated the genetic parameters, performed GS using different models and marker densities, and compared the estimation performance between GS and conventional BLUP on 35 carcass traits in an F2 population of ducks. Most of the cut weight traits and intestine length traits were estimated to be high and moderate heritabilities, respectively, while the heritabilities of percentage slaughter traits were dynamic. The reliability of genome prediction using GBLUP increased by an average of 0.06 compared to the conventional BLUP method. The Permutation studies revealed that 50K markers had achieved ideal prediction reliability, while 3K markers still achieved 90.7% predictive capability would further reduce the cost for duck carcass traits. The genomic relationship matrix normalized by our true variance method instead of the widely used [Formula: see text] could achieve an increase in prediction reliability in most traits. We detected most of the bayesian models had a better performance, especially for BayesN. Compared to GBLUP, BayesN can further improve the predictive reliability with an average of 0.06 for duck carcass traits. CONCLUSION: This study demonstrates genomic selection for duck carcass traits is promising. The genomic prediction can be further improved by modifying the genomic relationship matrix using our proposed true variance method and several Bayesian models. Permutation study provides a theoretical basis for the fact that low-density arrays can be used to reduce genotype costs in duck genome selection.

Prognostic value of the preoperative albumin-bilirubin score among patients with stages I-III gastric cancer undergoing radical resection: A retrospective study.

The albumin-bilirubin (ALBI) score was originally used to accurately assess liver dysfunction and predict the prognoses of patients with hepatocellular carcinoma. Following its more recent application to patients with gastrointestinal tumors, this study analyzed the prognostic value of the ALBI score in Chinese patients with advanced resectable (tumor-node-metastasis [TNM] stages I-III) gastric cancer (GC). This study investigated 1185 patients with advanced GC, including 429 with TNM stage I. The patients were divided into training and verifications groups (593 and 592 patients, respectively) in which these patients were classified as high risk (ALBI score ≥ -2.65) or low risk (ALBI score < -2.65). Univariate and multivariate Cox regression analyses were performed, and a visual survival prediction model (nomogram) was created. On Kaplan-Meier analysis, patients who were low-risk and high-risk according to their ALBI scores had significantly different survival rates in both the training and verification groups (p < 0.01). The difference was also significant when analyzing only patients with TNM stage I GC (p = 0.031). Univariate and multivariate analyses showed that the ALBI score (p = 0.014), age (p < 0.001), Nutritional Risk Screening 2002 score (p = 0.024), sarcopenia (p = 0.049), tumor differentiation (p = 0.027), and TNM stage (p < 0.001) were independent risk factors for survival. Our survival prediction model that incorporated the ALBI score accurately predicted the 5-year survival rate of Chinese patients with GC. Therefore, the ALBI score is a valid clinical indicator and good predictor of survival after surgery for progressive GC. Moreover, this score is simple to derive and does not burden patients with additional costs.

Profiling of intracellular and extracellular antibiotic resistance genes in municipal wastewater treatment plant and their effluent-receiving river.

The presence of antibiotic resistance genes (ARGs) and heavy metal resistance genes (MRGs) in extracellular and intracellular DNA (eDNA and iDNA) has received considerable attention in recent years owing to the potential threat to human health and the ecosystem. As a result, we investigated six ARGs, three MRGs, and two mobile genetic elements (MGEs) in the municipal wastewater treatment plant (MWWTP) and its adjacent environments. Results revealed that the absolute abundances of eARGs and eMRGs were lower than iARGs and iMRGs in MWWTP. By contrast, eARGs and eMRGs were higher in river sediments. Among ARGs, aminoglycoside resistance genes (aadA) was the most abundant gene (3.13 × 102 to 2.31 × 106 copies/mL in iDNA; 1.27 × 103 to 7.23 × 105 copies/mL in eDNA) in MWWTP, while zntA gene (9.4 × 102 to 3.97 × 106 copies/mL in iDNA; 3.2 × 103 to 6 × 105 copies/mL in eDNA) was amongst the MRGs. Notably, intI1 was enriched and positively correlated with iDNA (tetA, sul1, blaCTX-M, ermB, and merA) and eDNA (blaCTX-M, ermB, and merA), demonstrating its function in the proliferation of resistance genes. This widespread distribution of ARGs, MRGs, and MGEs in MWWTP and its adjacent river sediments will help clarify the transmission routes within these environments and provide a theoretical basis for better monitoring and mitigation of such dissemination.

Anti-hepatitis B virus activity of lithospermic acid, a polyphenol from Salvia miltiorrhiza, in vitro and in vivo by autophagy regulation.

ETHNOPHARMACOLOGICAL RELEVANCE: Salvia miltiorrhiza (the roots of S. miltiorrhiza Bunge, Danshen in Chinese), a traditional Chinese medicine, has been clinically used to prevent and treat various diseases, such as cardiovascular and cerebrovascular diseases, diabetes, and hepatitis B, in China and some other Asian countries. Lithospermic acid (LA), a polyphenol derived from S. miltiorrhiza, has been reported to exhibit multiple pharmacological properties, such as anti-inflammatory, anti-HIV, and anti-carbon tetrachloride-induced liver injury activities. However, little is known about the anti-hepatitis B virus (HBV) activity of LA. AIM OF THE STUDY: The study was projected to investigate the anti-HBV activity of LA in vitro (HepG2.2.15 and pHBV1.3-transfected HepG2 cells) and in vivo (pAAV-HBV1.2 hydrodynamic injection [HBV-HDI] mice) and explore the potential mechanism as well. MATERIALS AND METHODS: Hepatitis B surface antigen (HBsAg) and hepatitis B e antigen (HBeAg) contents were detected by ELISA kits. HBV DNA and hepatitis B core antigen (HBcAg) levels were evaluated by quantitative real-time polymerase chain reaction and immunohistochemistry assay, respectively. The proteins in autophagy process, lysosomal acidic function, and autophagy-related signaling pathways were examined by Western blot. Transmission electron microscopy was used to observe the number of autophagosomes and autolysosomes. Confocal microscopy was applied to analyze the autophagic flux and lysosomal acidification, using mCherry-enhanced green fluorescent protein (EGFP)-microtubule-associated protein light chain (LC)3 and lysosomal probes, respectively. RESULTS: LA exhibited anti-HBV activity by inhibiting HBV DNA replication in HepG2.2.15 and pHBV-transfected HepG2 cells in dose- and time-dependent manners and hampering HBsAg and HBeAg levels in HepG2.2.15 cells to a certain extent. LA reduced HBV DNA, HBsAg/HBeAg, and HBcAg levels in the serum/liver tissues of HBV-HDI C57BL/6 mice during the 3-week treatment and suppressed the withdrawal rebound of HBV DNA and HBsAg in the mice serum. LA increased LC3-II protein expression and the number of autolysosomes/autophagosomes and promoted the degradation of sequestosome 1(p62) protein in vitro and in vivo. LA enhanced the co-localization of LC3 protein with autolysosomes, further confirming the ability of LA to induce a complete autophagy. Knockdown of autophagy-related gene (Atg) 7 or 5 in vitro and administration of 3-methyladenine (an autophagic inhibitor) in vivo disabled the inhibitory efficacy of LA on HBV DNA replication, suggesting that the anti-HBV efficacy of LA depended on its ability of inducing autophagy. LA could enhance lysosomal acidification and improve the function of lysosomes by promoting the protein expression of lysosomal-associated membrane protein (LAMP)-1, LAMP-2, and mature cathepsin D, which may contribute to the autophagic induction of LA. LA inhibited the activation of AKT and mammalian target of rapamycin (mTOR) induced by HBV, which was reversed by IGF-1 (an agonist of the PI3K/AKT/mTOR signaling pathway), indicating that LA elicited autophagy through hampering the PI3K/AKT/mTOR signaling pathway. CONCLUSION: We revealed the anti-HBV activity and mechanism of LA in vitro and in vivo. This study facilitates a new understanding of the anti-HBV potent components of S. miltiorrhiza and sheds light on LA for further development as an active constituent or candidate used in the therapy against HBV infection.

Genomic prediction of carcass traits using different haplotype block partitioning methods in beef cattle.

Genomic prediction (GP) based on haplotype alleles can capture quantitative trait loci (QTL) effects and increase predictive ability because the haplotypes are expected to be in linkage disequilibrium (LD) with QTL. In this study, we constructed haploblocks using LD-based and the fixed number of single nucleotide polymorphisms (fixed-SNP) methods with Illumina BovineHD chip in beef cattle. To evaluate the performance of different haplotype block partitioning methods, we constructed haploblocks based on LD thresholds (from r 2 > 0.2 to r 2 > 0.8) and the number of fixed-SNPs (5, 10, 20). The performance of predictive methods for three carcass traits including liveweight (LW), dressing percentage (DP), and longissimus dorsi muscle weight (LDMW) was evaluated using three approaches (GBLUP and BayesB model based on the SNP, GHBLUP, and BayesBH models based on the haploblock, and GHBLUP+GBLUP and BayesBH+BayesB models based on the combined haploblock and the nonblocked SNPs, which were located between blocks). In this study, we found the accuracies of LD-based and fixed-SNP haplotype Bayesian methods outperformed the Bayesian models (up to 8.54 ± 7.44% and 5.74 ± 2.95%, respectively). GHBLUP showed a high improvement (up to 11.29 ± 9.87%) compared with GBLUP. The Bayesian models have higher accuracies than BLUP models in most scenarios. The average computing time of the BayesBH+BayesB model can reduce by 29.3% compared with the BayesB model. The prediction accuracies using the LD-based haplotype method showed higher improvements than the fixed-SNP haplotype method. In addition, to avoid the influence of rare haplotypes generated from haplotype construction, we compared the performance of GP by filtering four types of minor haplotype allele frequency (MHAF) (0.01, 0.025, 0.05, and 0.1) under different conditions (LD levels were set at r 2 > 0.3, and the fixed number of SNPs was 5). We found the optimal MHAF threshold for LW was 0.01, and the optimal MHAF threshold for DP and LDMW was 0.025.

Global leaders malnutrition initiative-defined malnutrition affects long-term survival of different subgroups of patients with gastric cancer: A propensity score-matched analysis.

As defined by the Global Leaders Malnutrition Initiative (GLIM), malnutrition is strongly associated with a lower quality of life and poor prognosis in gastric cancer patients. However, few studies have precisely explored the predictors of malnutrition, as defined by the GLIM, for overall survival (OS) after gastric cancer surgery in subgroups of patients stratified according to population characteristics. Our research aimed to analyze whether the predictors of malnutrition defined by the GLIM for postoperative OS in gastric cancer patients differ across subgroups. Patients who underwent radical gastric cancer surgery at our center between July 2014 and February 2019 were included in the study. Propensity score matching (PSM) was used to minimize bias. The study population was divided into malnourished and normal groups based on whether they were malnourished as defined by the GLIM. Univariate and multivariate analyses were performed to identify the risk factors affecting OS. The Kaplan-Meier curve and log-rank test were performed to determine the survival rate difference between subgroups. Overall, 1,007 patients were enrolled in the research. Multivariate analysis showed that malnutrition among the patients was 33.47%. Additionally, GLIM-defined malnutrition was an independent risk factor [hazard ratio (HR): 1.429, P = 0.001] for a shorter OS in gastric cancer patients. Furthermore, subgroup analysis showed that the GLIM was more appropriate for predicting OS in older aged patients (≥65 years), females, those with comorbidities (Charlson comorbidity index ≥ 2), and those with advanced gastric cancer (TNM stage = 3). GLIM-defined malnutrition affects the long-term survival of gastric cancer patients, especially older patients, females, patients with comorbidities, and patients with advanced gastric cancer.

A multi-tissue atlas of regulatory variants in cattle.

Characterization of genetic regulatory variants acting on livestock gene expression is essential for interpreting the molecular mechanisms underlying traits of economic value and for increasing the rate of genetic gain through artificial selection. Here we build a Cattle Genotype-Tissue Expression atlas (CattleGTEx) as part of the pilot phase of the Farm animal GTEx (FarmGTEx) project for the research community based on 7,180 publicly available RNA-sequencing (RNA-seq) samples. We describe the transcriptomic landscape of more than 100 tissues/cell types and report hundreds of thousands of genetic associations with gene expression and alternative splicing for 23 distinct tissues. We evaluate the tissue-sharing patterns of these genetic regulatory effects, and functionally annotate them using multiomics data. Finally, we link gene expression in different tissues to 43 economically important traits using both transcriptome-wide association and colocalization analyses to decipher the molecular regulatory mechanisms underpinning such agronomic traits in cattle.

Integrating genomics and transcriptomics to identify candidate genes for subcutaneous fat deposition in beef cattle.

Fat deposition is a complex economic trait regulated by polygenic genetic basis and environmental factors. Therefore, integrating multi-omics data to uncover its internal regulatory mechanism has attracted extensive attention. Here, we performed genomics and transcriptomics analysis to detect candidates affecting subcutaneous fat (SCF) deposition in beef cattle. The association of 770K SNPs with the backfat thickness captured nine significant SNPs within or near 11 genes. Additionally, 13 overlapping genes regarding fat deposition were determined via the analysis of differentially expressed genes and weighted gene co-expression network analysis (WGCNA). We then calculated the correlations of these genes with BFT and constructed their interaction network. Finally, seven biomarkers including ACACA, SCD, FASN, ACOX1, ELOVL5, HACD2, and HSD17B12 were screened. Notably, ACACA, identified by the integration of genomics and transcriptomics, was more likely to exert profound effects on SCF deposition. These findings provided novel insights into the regulation mechanism underlying bovine fat accumulation.