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Abstract Background Integrating multi-layered information can enhance the accuracy of genomic prediction for complex traits. However, the improvement and application of effective strategies for genomic prediction (GP) using multi-omics data remains challenging. Methods We generated 11 feature sets for sequencing variants from genomics, transcriptomics, metabolomics, and epigenetics data in beef cattle, then we assessed the contribution of functional variants using genomic restricted maximum likelihood (GREML). We next estimated and ranked variant scores for 43 economically important traits, and compared the prediction accuracy of the top and bottom sets using genomic best linear unbiased prediction (GBLUP) and BayesB model. In addition, we annotated the variants from GWAS with functional feature sets and performed enrichment analysis. Results We observed significant enrichments for 32 functional categories in 11 feature sets. The evolutionary related sets (conservation regions and selection signatures) contributed significantly to heritability (31.78-fold and 14.48-fold enrichment), while metabolomics and transcriptomics showed low heritability enrichments. We observed a significant increase in prediction accuracy using the top feature set variants compared to whole-genome sequencing (WGS) data. The prediction accuracy based on the top 10% variant set showed an average increase of 11.6% and 7.54% using BayesB and GBLUP across traits, respectively. Notably, the greatest increase of 31.52% was obtained for spleen weight (SW) using BayesB. Also, we found that the top 10% of variants show strong enrichment with weight related QTLs based on the Cattle QTL database. Conclusions Our findings suggest that integrating biological prior information from multiple layers can enhance our understanding of the genetic architecture underlying complex traits and further improve genomic prediction in beef cattle.

Leveraging whole-genome sequencing (WGS) that includes the full spectrum of genetic variation provides a better understanding of the biological mechanisms involved in the economically important traits of farm animals. However, the effectiveness of WGS in improving the accuracy of genomic prediction (GP) is limited. Recent genetic analyses of complex traits, such as genome-wide association study (GWAS), have identified numerous genomic regions and potential genes, which can provide valuable prior information for the improvement of genomic selection (GS). In this study, we applied different genome prediction methods to integrate GWAS results and gene feature annotations, which significantly improved the accuracy of GS for beef production traits. The Bayesian models incorporating genomic features showed the highest prediction accuracy, particularly for average daily gain (ADG) and bone weight (BW). Compared to prediction models based on WGS data, GP including biological prior can optimize the prediction accuracy by up to 11.56% for ADG and 14.60% for BW. Also, GP using GBLUP and Bayesian methods integrating biological priors for single-trait GWAS can significantly increase the prediction accuracy. Bayesian methods generally outperformed GBLUP models, with average improvements of 2.25% for ADG, 5.04% for BW, and 3.44% for live weight (LW). Our results indicate that leveraging biological prior knowledge can significantly refine GS models and underline the potential of combining WGS data with biological prior knowledge to further enhance the breeding process.

Abstract Background Bile acids (BAs) concentration can affect metabolic improvement caused by bariatric surgery and BA concentrations increase in patients after sleeve gastrectomy (SG). Here, how BAs after SG affect metabolism in nonalcoholic fatty liver disease (NAFLD) was studied. Methods Mice were given high‐fat diet (HFD) to induce NAFLD and received SG surgery. Hepatic and fecal BA concentrations in mice were detected by liquid chromatography‐tandem mass spectrometry method. BA‐related genes were detected by quantitative real‐time polymerase chain reaction. G protein BA receptor 1 (GPBAR1) expression was identified using western blot analysis. NAFLD mice after SG received GPBAR1 inhibitor Triamterene. The weight of mice and mice liver was detected. Mouse liver tissue was observed by hematoxylin–eosin and Oil Red O staining. Triglyceride (TG), nonesterified fatty acid (NEFA), and cyclic adenosine monophosphate (cAMP) levels in mouse liver tissue were analyzed by metabolic assay and enzyme‐linked immune sorbent assay. Results SG boosted increase in hepatic total/conjugated BAs and related genes and GPBAR1 expression, and attenuated increase in fecal total BAs/muricholic acid in HFD‐induced mice and increased fecal taurine‐BAs in HFD‐induced mice. Triamterene (72 mg/kg) reversed the inhibitory role of SG in HFD‐induced increase of body weight, lipid accumulation, inflammatory cell infiltration, and increase of hepatic weight and TG/NEFA content, and counteracted the positive role of SG in HFD‐induced increase of hepatic cAMP concentration in mice. Conclusions BAs improve metabolism via activating GPBAR1 to increase cAMP in NAFLD mice after SG.

BackgroundTo explore the effective dose to immune cells (EDIC) for better prognosis while avoiding radiation-induced lymphopenia (RIL) in patients with locally advanced esophageal squamous cell carcinoma (ESCC).Materials and methodsOverall, 381 patients with locally advanced ESCC receiving definitive radiotherapy with or without chemotherapy (dRT ± CT) between 2014 and 2020 were included in this study. The EDIC model was calculated by radiation fraction number and mean doses to the heart, lung, and integral body. The correlation between EDIC and clinical outcomes was analyzed using Cox proportional hazards regression, and risk factors for RIL were determined by logistic regression analysis.ResultsThe median EDIC was 4.38 Gy. Multivariate analysis revealed that low-EDIC significantly improved the OS of patients when compared with high-EDIC (HR = 1.614, P = 0.003) and PFS (HR = 1.401, P = 0.022). Moreover, high-EDIC was associated with a higher incidence of grade 4 RIL (OR = 2.053, P = 0.007) than low-EDIC. In addition, we identified body mass index (BMI), tumor thickness, and nodal stage as independent prognostic factors of OS and PFS, while BMI (OR = 0.576, P = 0.046) and weight loss (OR = 2.214, P = 0.005) as independent risk factors of grade 4 RIL. In subgroup analyses, the good group had better clinical outcomes than the remaining two groups (P< 0.001).ConclusionThis study demonstrated that EDIC significantly correlates with poor clinical outcomes and severe RIL. Optimizing treatment plans to decrease the radiation doses to immune cells is critical for improving the outcomes.

Abstract Background Beef cuts in different regions of the carcass have different meat quality due to their distinct physiological function. The objective of this study was to characterize the region-specific expression differences using comparative transcriptomics analysis among five representative beef cuts (tenderloin, longissimus lumborum, rump, neck, chuck). Results We obtained 15,701 expressed genes in 30 muscle samples across five regions from carcass meat. We identified a total of 80 region-specific genes (RSGs), ranging from three (identified in the rump cut) to thirty (identified in the longissimus lumborum cut), and detected 25 transcription factors (TFs) for RSGs. Using a co-expression network analysis, we detected seven region-specific modules, including three positively correlated modules and four negatively correlated modules. We finally obtained 91 candidate genes related to meat quality, and the functional enrichment analyses showed that these genes were mainly involved in muscle fiber structure (e.g., TNNI1, TNNT1), fatty acids (e.g., SCD, LPL), amino acids (ALDH2, IVD, ACADS), ion channel binding (PHPT1, SNTA1, SUMO1, CNBP), protein processing (e.g., CDC37, GAPDH, NRBP1), as well as energy production and conversion (e.g., ATP8, COX8B, NDUFB6). Moreover, four candidate genes (ALDH2, CANX, IVD, PHPT1) were validated using RT-qPCR analyses which further supported our RNA-seq results. Conclusions Our results provide valuable insights into understanding the transcriptome regulation of meat quality in different beef cuts, and these findings may further help to improve the selection for health-beneficial meat in beef cattle.

Abstract Accumulating evidence indicates that inflammation and nutrition status are associated with clinical outcomes in patients with various malignancies. This study aimed to evaluate the prognostic significance of the pretreatment platelet to albumin ratio (PAR) in esophageal squamous cell carcinoma (ESCC) patients undergoing definitive radiotherapy. A total of 470 patients who underwent definitive radiotherapy with or without chemotherapy were enrolled. The optimal cut-off values of PAR and other indicators were determined by the X-tile. The Kaplan–Meier method, multivariate analyses Cox regression were conducted to identify the association between those indicators and the survival outcomes. The median follow-up time was 23.5 months. The optimal cut-off value of PAR was 5.7 × 109 and patients were stratified as the low PAR group and the high PAR group. In the univariate analysis, a low overall survival rate was significantly associated with T stage (P = 0.005), TNM stage (P

Abstract Background A comprehensive analysis of gene expression profiling across tissues can provide necessary information for an in-depth understanding of their biological functions. We performed a large-scale gene expression analysis and generated a high-resolution atlas of the transcriptome in beef cattle. Results Our transcriptome atlas was generated from 135 bovine tissues in adult beef cattle, covering 51 tissue types of major organ systems (e.g., muscular system, digestive system, immune system, reproductive system). Approximately 94.76% of sequencing reads were successfully mapped to the reference genome assembly ARS-UCD1.2. We detected a total of 60,488 transcripts, and 32% of them were not reported before. We identified 2654 housekeeping genes (HKGs) and 477 tissue-specific genes (TSGs) across tissues. Using weighted gene co-expression network analysis, we obtained 24 modules with 237 hub genes (HUBGs). Functional enrichment analysis showed that HKGs mainly maintain the basic biological activities of cells, while TSGs were involved in tissue differentiation and specific physiological processes. HKGs in bovine tissues were more conserved in terms of expression pattern as compared to TSGs and HUBGs among multiple species. Finally, we obtained a subset of tissue-specific differentially expressed genes (DEGs) between beef and dairy cattle and several functional pathways, which may be involved in production and health traits. Conclusions We generated a large-scale gene expression atlas across the major tissues in beef cattle, providing valuable information for enhancing genome assembly and annotation. HKGs, TSGs, and HUBGs further contribute to better understanding the biology and evolution of multiple tissues in cattle. DEGs between beef and dairy cattle also fill in the knowledge gaps about differential transcriptome regulation of bovine tissues underlying economically important traits.

Abstract Background Calcium-activated nucleotidase 1 (CANT1), functions as a calcium-dependent nucleotidase with a preference for UDP. However, the potential clinical value of CANT1 in lung adenocarcinoma (LA) has not been fully clarified. Thus, we sought to identify its potential biological function and mechanism through bioinformatics analysis and in vitro experiments in LA. Methods In the present study, we comprehensively investigated the prognostic role of CANT1 in LA patients through bioinformatics analysis and in vitro experiments. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were utilized to analyze the expression of CANT1 in LA patients and their clinical-prognostic value. The immunohistochemistry staining was obtained from the Human Protein Atlas (HPA). A Cox regression model was used to evaluate prognostic factors. Gene ontology (GO) and Gene set enrichment analysis (GSEA) was performed to explore the potential regulatory mechanism of CANT1 in the development of LA. Moreover, we also examined the relationship between CANT1 expression and DNA methylation. Finally, we did in vitro experiments to evaluate the biological behavior and role of CANT1 in LA cells (LACs). Results Our study showed that the CANT1 expression was significantly elevated in the LA tissues compared with the normal lung tissues. Increased CANT1 expression was significantly associated with the TN stage. A univariate Cox analysis indicated that high CANT1 expression levels were correlated with poor overall survival (OS) in LA. Besides, CANT1 expression was independently associated with OS in multivariate analysis. GO and GSEA analysis showed the enrichment of mitotic nuclear division, DNA methylation, and DNA damage. Then we found that the high expression of CANT1 is positively correlated with hypomethylation. The methylation level was associated with prognosis in LA patients. Finally, in vitro experiments indicated that knockdown of CANT1 resulted in decreased cell proliferation, invasion, and G1 phase cell-cycle arrest in LACs. Conclusion The present study suggested that CANT1 may serve as a potential prognosis biomarker in patients with LA. High CANT1 expression and promoter demethylation was associated with worse outcome. Finally, in vitro experiments verified the biological functions and behaviors of CANT1 in LA.

Abstract Background Studies have shown that the Sec61 gamma subunit (SEC61G) is overexpressed in several tumors and could serve as a potential prognostic marker. However, the correlation between SEC61G and lung adenocarcinoma (LUAD) remains unclear. In the current study, we aimed to demonstrate the prognostic value and potential biological function of the SEC61G gene in LUAD. Methods Public datasets were used for SEC61G expression analyses. The prognostic value of SEC61G in LUAD was investigated using the Kaplan–Meier survival and Cox analyses. The correlation between the methylation level of SEC61G and its mRNA expression was evaluated via cBioPortal. Additionally, MethSurv was used to determine the prognostic value of the SEC61G methylation levels in LUAD. Functional enrichment analysis was conducted to explore the potential mechanism of SEC61G. Also, single sample GSEA (ssGSEA) and TIMER online tool were applied to identify the correlation between SEC61G and immune filtration. Furthermore, cell functional experiments were conducted to verify the biological behavior of SEC61G in lung adenocarcinoma cells (LAC). Results SEC61G was upregulated in pan-cancers, including LUAD. High SEC61G expression was significantly correlated with worse prognosis in LUAD patients. Multivariate analysis demonstrated that high SEC61G expression was an independent prognostic factor in the TCGA cohort. (HR = 1.760 95% CI: 1.297–2.388, p

Background. Systemic inflammation may be involved in the entire cancer process as a promoter and is associated with antitumor immunity. The systemic immune-inflammation index (SII) has been shown to be a promising prognostic factor. However, the relationship between SII and tumor-infiltrating lymphocytes (TIL) have not been established in esophageal cancer (EC) patients receiving concurrent chemoradiotherapy (CCRT). Methods. Retrospective analysis of 160 patients with EC was performed, peripheral blood cell counts were collected, and TIL concentration was assessed in H&E-stained sections. Correlations of SII and clinical outcomes with TIL were analyzed. Cox proportional hazard model and Kaplan–Meier method were used to perform survival outcomes. Results. Compared with high SII, low SII had longer overall survival (OS) (P=0.036, hazard ratio (HR) = 0.59) and progression-free survival (PFS) (P=0.041, HR = 0.60). Low TIL showed worse OS (P

Background. Advanced glycation end products’ receptor (AGER) is a multiligand receptor that interacts with a wide range of ligands. Previous studies have shown that abnormal AGER expression is closely related to immune infiltration and tumorigenesis. However, the AGER DNA methylation relationship between prognosis and infiltrating immune cells in LUAD and LUSC is still unclear. Methods. AGER expression in pan-cancer was obtained by using the UALCAN databases. Kaplan–Meier plotter showed the correlation of AGER mRNA expression levels and clinicopathological parameters. The protein expression levels for AGER were derived from Human Protein Atlas Database Analysis. The copy number, somatic mutation, and DNA methylation of AGER were presented with UCSC Xena database. TIMER platform and TISIDB website were used to show the correlation between AGER expression and tumor immune cell infiltration level. Results. The expression level of AGER was significantly reduced in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Low expression of AGER was significantly correlated with histology, stage, lymph node metastasis, and tumor protein 53 (TP53) mutation and could be used as a potential indicator of poor prognosis of LUAD and LUSC. Moreover, AGER expression was positively correlated with the infiltrating immune cells. Further analysis showed that copy number variation (CNV), mutation, and DNA methylation were involved in AGER downregulation. In addition, we also found that hypermethylated AGER was significantly correlated with tumor-infiltrating lymphocytes. Conclusion. AGER may be a candidate for the prognostic biomarker of LUAD and LUSC related to tumor immune microenvironment.

ObjectiveRadiation esophagitis (RE) is a common adverse effect in small cell lung cancer (SCLC) patients undergoing thoracic radiotherapy. We aim to develop a novel nomogram to predict the acute severe RE (grade≥2) receiving chemoradiation in SCLC patients.Materials and methodsthe risk factors were analyzed by logistic regression, and a nomogram was constructed based on multivariate analysis results. The clinical value of the model was evaluated using the area under the receiver operating curve (ROC) curve (AUC), calibration curves, and decision curve analysis (DCA). The correlations of inflammation indexes were assessed using Spearman correlation analysis.ResultsEighty-four of 187 patients (44.9%) developed grade ≥2 RE. Univariate analysis indicated that concurrent chemoradiotherapy (CCRT, p < 0.001), chemotherapy cycle (p = 0.097), system inflammation response index (SIRI, p = 0.048), prognostic-nutrition index (PNI, p = 0.073), platelets-lymphocyte radio (PLR, p = 0.026), platelets-albumin ratio (PAR, p = 0.029) were potential predictors of RE. In multivariate analysis, CCRT [p < 0.001; OR, 3.380; 95% CI, 1.767-6.465], SIRI (p = 0.047; OR, 0.436; 95% CI, 0.192-0.989), and PAR (p = 0.036; OR, 2.907; 95% CI, 1.071-7.891) were independent predictors of grade ≥2 RE. The AUC of nomogram was 0.702 (95% CI, 0.626-0.778), which was greater than each independent predictor (CCRT: 0.645; SIRI: 0.558; PAR: 0.559). Calibration curves showed high coherence between the predicted and actual observation RE, and DCA displayed satisfactory clinical utility.ConclusionIn this study, CCRT, SIRI, and PAR were independent predictors for RE (grade ≥2) in patients with SCLC receiving chemoradiotherapy. We developed and validated a predictive model through these factors. The developed nomogram with superior prediction ability can be used as a quantitative model to predict RE.

Meat quality is an economically important trait for global food production. Copy number variations (CNVs) have been previously implicated in elucidating the genetic basis of complex traits. In this article, we detected a total of 112,198 CNVs and 10,102 CNV regions (CNVRs) based on the Bovine HD SNP array. Next, we performed a CNV-based genome-wide association analysis (GWAS) of six meat quality traits and identified 12 significant CNV segments corresponding to eight candidate genes, including PCDH15, CSMD3, etc. Using region-based association analysis, we further identified six CNV segments relevant to meat quality in beef cattle. Among these, TRIM77 and TRIM64 within CNVR4 on BTA29 were detected as candidate genes for backfat thickness (BFT). Notably, we identified a 34 kb duplication for meat color (MC) which was supported by read-depth signals, and this duplication was embedded within the keratin gene family including KRT4, KRT78, and KRT79. Our findings will help to dissect the genetic architecture of meat quality traits from the aspects of CNVs, and subsequently improve the selection process in breeding programs.

The optimized selection method can maximize the genetic gain in offspring under the premise of controlling the inbreeding level of the population. At present, genetic gain has been largely improved by using genomic selection in multiple farm animals. However, the design of the optimal selection method and assessment of its effects during long-term selection in beef cattle breeding are yet to be fully explored. In this study, a simulated beef cattle population was constructed, and 15 generations of simulated breeding were carried out using the linear programming breeding strategy (LP) and optimal contribution selection strategy (OCS), respectively. The truncation selection strategy (TS−I and TS−II) was used as the control. During the breeding process, genetic parameters including genetic gain, average kinship coefficient, QTL effect variance, and average observed heterozygosity were calculated and compared across generations. Our results showed that the LP method can significantly improve the genetic gain in the population, especially the genetic performance of the traits with high heritability and the traits with high weight in the breeding process, but the inbreeding level of the population is higher under LP strategy. Although the genetic gain in the population under the OCS strategy is lower than the TS−II strategy, this method can effectively control the inbreeding level of the population. Our findings also suggest that the LP and OCS method can be used as an effective means to improve genetic gain, while the OCS method is a more ideal method to obtain sustainable genetic gain during long-term selection.

Abstract Objective There is still no definitely therapeutic evidence of a beneficial effect of chemotherapy with radiotherapy for older patients with esophageal squamous cell carcinoma (ESCC). We aim to determine the influence of chemoradiotherapy (CRT) and radiotherapy (RT) alone in patients aged 65 years or older with locally advanced ESCC. Methods We retrospectively analyzed 581 ESCC patients who underwent CRT and RT alone. Univariate and multivariate Cox regression analysis was used to analyze the impact of clinical factors on long‐term overall survival (OS) and progression-free survival (PFS). Finally, we compared the toxicity rates of these patients. Results The median OS and PFS of the overall population were 23.2 months (2.0–162.6 months) and 18.6 months (1.1–159.6 months). Multivariate Cox regression analysis showed that chemotherapy (p 0.05). Besides, higher staged ESCC has the inferior OS and PFS than lower staged ESCC for patients received RT alone and aged 65–74 years (both p

Abstract Background Genomic regions with a high frequency of runs of homozygosity (ROH) are related to important traits in farm animals. We carried out a comprehensive analysis of ROH and evaluated their association with production traits using the BovineHD (770 K) SNP array in Chinese Simmental beef cattle. Results We detected a total of 116,953 homozygous segments with 2.47Gb across the genome in the studied population. The average number of ROH per individual was 99.03 and the average length was 117.29 Mb. Notably, we detected 42 regions with a frequency of more than 0.2. We obtained 17 candidate genes related to body size, meat quality, and reproductive traits. Furthermore, using Fisher’s exact test, we found 101 regions were associated with production traits by comparing high groups with low groups in terms of production traits. Of those, we identified several significant regions for production traits (P

ObjectiveNo study has reported the risk stratification of BMI and PNI in patients with locally advanced esophageal squamous cell carcinoma (ESCC) undergoing definitive chemoradiotherapy (dCRT). This study aimed to construct a risk stratification to guide the treatment of ESCC following dCRT.MethodsA total of 1,068 patients with locally advanced ESCC who received dCRT were retrospectively analyzed. The impacts of clinicopathological factors on overall survival (OS) and progression-free survival (PFS) were analyzed. Besides, the novel prognostic indices of pre-therapeutic nutritional index (PTNI) and prognostic index (PI) were developed.ResultsThe median follow-up period of OS and PFS were 22.9 and 17.4 months, respectively. The high body mass index (BMI) group had better 5-year OS and PFS (36.4 and 34.0%) than the low BMI group (18.8 and 17.2%). The high prognostic nutritional index (PNI) group also had better 5-year OS and PFS (33.4 and 30.9%) than the low PNI group (17.5 and 17.2%). Multivariate Cox regression analysis showed that BMI and PNI were independent prognostic factors for OS and PFS. Based on nutritional indices, patients were categorized into the low-risk (PTNI = 1), medium-risk (PTNI = 2), and high-risk (PTNI = 3) groups with 5-year OS rates of 38.5, 18.9, 17.5%, respectively (p < 0.001) and 5-year PFS rates of 35.8, 17.6, 16.8%, respectively (p < 0.001). Besides, we also constructed a prognostic index (PI) for OS and PFS which was calculated based on statistically significant factors for predicting OS and PFS. The results revealed that the high-risk group had worse OS and PFS than the low-risk group (p < 0.001). Finally, RCS analysis demonstrated a non-linear relationship between the PNI, BMI, and survival for patients with ESCC. The death hazard of PNI and BMI sharply decreased to 41.8 and 19.7.ConclusionThe decreased pre-therapeutic BMI and PNI levels were associated with a worse survival outcome. BMI and PNI are readily available and can be used to stratify risk factors for locally advanced ESCC patients undergoing dCRT. The novel risk stratification may help to evaluate patients’ pre-therapeutic status and guide dCRT for locally advanced ESCC patients.

Abstract GREB1L is a protein-coding gene that is an important paralog of GREB1. However, its effects in lung adenocarcinoma (LUAD) have not been determined. Thus, we evaluated the prognostic value of GREB1L in LUAD using bioinformatics approaches. In particular, we evaluated the relationship between GREB1L and LUAD using a wide range of databases and analysis tools, including TCGA, GEO, HPA, TIMER, cBioPortal, and MethSurv. Compared with its expression in normal lung tissues, GREB1L expression was significantly increased in LUAD tissues. A univariate Cox analysis showed that high GREB1L expression levels were correlated with a poor OS in LUAD. Additionally, GREB1L expression was independently associated with OS through a multivariate Cox analysis. GSEA analysis revealed enrichment in cell cycle, immune regulation, and methylation. Moreover, high GREB1L expression was associated with poor survival. We also found that the methylation and genetic alteration level was associated with prognosis in patients with LUAD. Finally, an analysis of immune infiltration showed that GREB1L is correlated with immune cell infiltration, PD-1, and PD-L1. In summary, these results indicate that GREB1L is a potential molecular marker for poor prognosis in LUAD and provide additional insight for the development of therapies and prognostic markers.

A low-profile broadband dual-polarized antenna is investigated for base station applications. It consists of two orthogonal dipoles, fork-shaped feeding lines, an artificial magnetic conductor (AMC), and parasitic strips. By utilizing the Brillouin dispersion diagram, the AMC is designed as the antenna reflector. It has a wide in-phase reflection bandwidth of 54.7% (1.54–2.70 GHz) and a surface-wave bound range of 0–2.65 GHz. This design effectively reduces the antenna profile by over 50% compared to traditional antennas without an AMC. For demonstration, a prototype is fabricated for 2G/3G/LTE base station applications. Good agreement between the simulations and measurements is observed. The measured −10-dB impedance bandwidth of our antenna is 55.4% (1.58–2.79 GHz), with a stable gain of 9.5 dBi and a high isolation of more than 30 dB across the impedance passband. As a result, this antenna is an excellent candidate for miniaturized base station antenna applications.

Objective: We aimed to construct risk stratification to help set individualized treatment strategies and intensities for different subgroups of patients. Methods: The Esophagus Immune Prognostic Index (EIPI) scores were constructed according to the levels of derived neutrophil-to-lymphocyte ratio (dNLR) and lactate dehydrogenase (LDH) before treatment, and the patients were divided into low-, medium-, and high-risk groups. Finally, restricted cubic splines (RCS) were used to explore the relationship between dNLR, LDH, and survival outcomes. Results: The median follow-up period of overall survival (OS) and progression-free survival (PFS) were 25.2 and 17.6 months, respectively. Multivariate Cox regression analysis showed dNLR were the independent prognostic factors that were associated with OS and PFS. The 3-year OS and PFS rates in the low-, medium-, and high-risk groups were 44.4% and 38.2%, 26.1% and 23.6%, and 10.5% and 5.3%, respectively. Patients who received chemotherapy had better OS and PFS than those who did not receive chemotherapy in low-risk and medium/high-risk groups (all p

BackgroundThis study was conducted to determine risk factors for developing brain metastasis (BM) and to predict brain metastasis free survival (BMFS) and overall survival (OS) by combining several clinical parameters and inflammatory indexes.Materials and MethodsA nomogram and risk stratification were developed based on multivariate analysis results. The prognostic index (PI) predicting the high risk of BM was calculated by multiplying the weighted factor (β coefficient) with each variable.ResultsThirty-two of one hundred patients (32.0%) developed BM. Multivariate cox regression analysis revealed that concurrent chemoradiotherapy (CCRT; hazard ratio (HR), 3.356; p = 0.020), monocyte–lymphocyte ratio (MLR; HR, 4.511; p = 0.002), neutrophil–lymphocyte ratio (NLR; HR, 4.023; p = 0.033), and prognostic-nutrition index (PNI; HR, 2.902; p = 0.018) were independent prognostic factors of BMFS. The nomogram has good accuracy in predicting BMFS, and the C-index was 0.73. The ROC curve showed that these risk factors have good discriminant ability. Similarly, tumor location (HR, 1.675; p = 0.035) and MLR (HR, 2.076; p = 0.013) were independent prognostic factors of OS. In the subgroup analysis of OS, the good group had a better prognosis than the other groups. Risk stratification by PI: the high-risk group had worse BMFS than the low-risk group, which also has certain practical significance for clinical practice in OS.ConclusionWe developed a nomogram and corresponding risk stratification in stage III SCLC patients who developed BM. This model and risk stratification can help clinicians improve patient treatment management and better deliver personalized therapy.

BackgroundWe aimed to determine whether the tumor length and tumor thickness should be used as prognostic factors for esophageal squamous cell carcinoma (ESCC) patients treated with definitive chemoradiotherapy (dCRT).MethodsA retrospective analysis consists of 902 non-operative ESCC patients received dCRT. The nomogram was used to predict the survival. Besides, Restricted Cubic Splines (RCS) was used to examine the relationship between prognostic factors and survival outcomes. Finally, the prognostic index (PI) scores were constructed according to the tumor length and tumor thickness, and the patients were divided into the low-, medium-, and high-risk groups.ResultsThe median follow-up of overall survival (OS) and progression-free survival (PFS) were 23.0 months and 17.5 months. Multivariate Cox regression analysis showed that tumor length and tumor thickness were independent prognostic factors associated with survival. Our novel nomograms for OS and PFS were superior to the TNM classification (p < 0.001). Besides, RCS analysis demonstrated that the death hazard of tumor length and tumor thickness sharply increased at 7.7 cm and 1.6 cm (p < 0.001). Finally, there were significant differences for ESCC patients with clinical TNM stage group of the OS and PFS in different risk groups. The higher risk group was significantly associated with shorter OS and PFS in ESCC patients (both p < 0.001 for all).ConclusionThe study results suggest that the novel models integrating tumor length and tumor thickness may provide a simple and widely available method for evaluating the prognosis of non-operative ESCC patients. The tumor length and tumor thickness should be considered as prognostic factors for ESCC.

Recent evidence suggested that N6-methyladenosine (m6A) methylation can determine m6A-modified mRNA fate and play an important role in skeletal muscle development. It was well known that transforming growth factor beta 1 (TGFβ1) is involved in a variety of cellular processes, such as proliferation, differentiation, and apoptosis. However, little is known about the m6A-mediated TGFβ1 regulation in myogenesis. Here, we observed an increase in endogenous TGFβ1 expression and activity during myotube differentiation. However, the knockdown of TGFβ1 inhibits the proliferation and induces cell apoptosis of myoblast. Moreover, we found that m6A in 5′-untranslated regions (5′UTR) of TGFβ1 promote its decay and inhibit its expression, leading to the blockage of the TGFβ1/SMAD2 signaling pathway. Furthermore, the targeted specific demethylation of TGFβ1 m6A using dCas13b-FTO significantly increased the TGFβ1-mediated activity of the SMAD2 signaling pathway, promoting myoblast proliferation. These findings suggest that TGFβ1 is an essential regulator of myoblast growth that is negatively regulated by m6A. Overall, these results highlight the critical role of m6A-mediated post-transcriptional regulation in myogenesis.

BackgroundPostoperative ileus (POI) is an important complication of gastrointestinal (GI) surgery. Acupuncture has been increasingly used in treating POI. This study aimed to assess the effectiveness and safety of acupuncture for POI following GI surgery.MethodsSeven databases (PubMed, Embase, the Cochrane Library, China National Knowledge Infrastructure, Wan fang Data, VIP Database for Chinese Technical Periodicals, and Chinese Biomedical Literature Database) and related resources were searched from inception to May 30, 2021. Randomized controlled trials (RCTs) reporting the acupuncture for POI in GI were included. The quality of RCTs was assessed by the Cochrane Collaboration Risk of Bias tool, and the certainty of the evidence was evaluated by the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. A meta-analysis was performed by using RevMan 5.4 software.ResultsEighteen RCTs involving 1413 participants were included. The meta-analysis showed that acupuncture could reduce the time to first flatus (TFF) (standardized mean difference [SMD] = -1.14, 95% confidence interval [CI]: -1.54 to -0.73, P < 0.00001), time to first defecation (TFD) (SMD = -1.31, 95% CI: -1.88 to -0.74, P < 0.00001), time to bowel sounds recovery (TBSR) (SMD = -1.57, 95% CI: -2.14 to -1.01, P < 0.00001), and length of hospital stay (LOS) (mean difference [MD] = -1.68, 95% CI: -2.55 to -0.80, P = 0.0002) compared with usual care. A subgroup analysis found that acupuncture at distal acupoints once daily after surgery had superior effects on reducing TFF and TFD. A sensitivity analysis supported the validity of the finding. Acupuncture also manifested an effect of reducing TFF, TFD and TBSR compared with sham acupuncture but the result was not stable. Relatively few trials have reported whether adverse events have occurred.ConclusionsAcupuncture showed a certain effect in reducing POI following GI surgery with very low-to-moderate quality of evidence. The overall safety of acupuncture should be further validated. More high-quality, large-scale, and multicenter original trials are needed in the future.

Bone weight is critical to affect body conformation and stature in cattle. In this study, we conducted a genome-wide association study for bone weight in Chinese Simmental beef cattle based on the imputed sequence variants. We identified 364 variants associated with bone weight, while 350 of them were not included in the Illumina BovineHD SNP array, and several candidate genes and GO terms were captured to be associated with bone weight. Remarkably, we identified four potential variants in a candidate region on BTA6 using Bayesian fine-mapping. Several important candidate genes were captured, including LAP3, MED28, NCAPG, LCORL, SLIT2, and IBSP, which have been previously reported to be associated with carcass traits, body measurements, and growth traits. Notably, we found that the transcription factors related to MED28 and LCORL showed high conservation across multiple species. Our findings provide some valuable information for understanding the genetic basis of body stature in beef cattle.

In this work, a cellulose nanofibrils (CNFs)/few-layer graphene (FLG) hybrid is mechanically stripped from bamboo pulp and expanded graphene (EG) using a grinder. This strategy is scalable and environmentally friendly for high-efficiency exfoliation and dispersion of graphene in an aqueous medium. The in situ-generated CNFs play a key role in this process, acting as a “green” dispersant. Next, the obtained CNFs-FLG is used as a functional filler in a polyoxyethylene (PEO) matrix. When the composition of CNFs-FLG is 50 wt.%, the resultant PEO/CNFs-FLG nanocomposite film exhibits a Young’s modulus of 1.8 GPa and a tensile strength of 25.7 MPa, showing 480% and 260% enhancement as compared to those of the pure PEO film, respectively. Remarkably, the incorporation of CNFs-FLG also provides the nanocomposite films with a stunning electrical conductivity (72.6 S/m). These attractive features make PEO/CNFs-FLG nanocomposite films a promising candidate for future electronic devices.

Genomic selection (GS) has been widely used in livestock breeding. However, the long-term impact of GS on genetic gain, as well as inbreeding levels, has not been fully explored in beef cattle. In this study, we carried out simulation analysis using different approaches involving two types of SNP density (54 K and 100 K) and three levels of heritability traits (h2 = 0.1, 0.3, and 0.5) to explore the long-term effects of selection strategies on genetic gain and average kinship coefficients. Our results showed that GS can improve the genetic gain across generations, and the GBLUP strategy showed slightly better performance than the BayesA model. Higher trait heritability can generate higher genetic gain in all scenarios. Moreover, simulation results using GBLUP and BayesA strategies showed higher average kinship coefficients compared with other strategies. Our study suggested that it is important to design GS strategies by considering the SNP density and trait heritability to achieve long-term and sustainable genetic gain and to effectively control inbreeding levels.

ObjectiveRadiation esophagitis (RE) is common in patients treated with radiotherapy (RT) for locally advanced esophageal squamous cell carcinoma (ESCC). We aim to construct a nomogram predicting the severe RE (grade ≥2) in patients with ESCC receiving definitive chemoradiotherapy (dCRT).Materials and MethodsLogistic regression was performed to evaluate the risk factors in predicting RE. Nomogram was built based on the multivariate analysis result. The model was validated using the area under the receiver operating curve (ROC) curve (AUC), calibration curves, and decision curve analyses (DCA). Spearman correlation analysis was used to evaluate the correlation between inflammation indexes.ResultsA total of 547 patients with stage II–IVA ESCC treated with dCRT from the retrospective study were included. Two hundred and thirty-two of 547 patients (42.4%) developed grade ≥2 RE. Univariate analysis indicated that gender (p = 0.090), RT dose (p < 0.001), targeted therapy (p = 0.047), tumor thickness (p = 0.013), lymphocyte-monocyte ratio (LMR, p = 0.016), neutrophil-lymphocyte ratio (NLR, p < 0.001), and platelet-lymphocyte ratio (PLR, p < 0.001) were the significant factors for a higher incidence of RE. In multivariate analysis, RT dose [p < 0.001; odds ratio (OR), 4.680; 95% confidence interval (CI), 2.841–6.709], NLR (p < 0.001; OR, 0.384; 95% CI, 0.239–0.619), and PLR (p < 0.001; OR, 3.539; 95% CI: 2.226–5.626) were independently associated grade ≥2 RE and were involved in the nomogram. ROC curves showed the AUC of the nomogram was 0.714 (95% CI, 0.670–0.757), which was greater than each factor alone (RT dose: 0.615; NLR: 0.596; PLR: 0.590). Calibration curves showed good consistency between the actual observation and the predicted RE. DCA showed satisfactory positive net benefits of the nomogram among most threshold probabilities.ConclusionsThe study demonstrated that RT dose, NLR, and PLR were independent risk factors for grade ≥2 RE in patients with locally advanced ESCC receiving dCRT. A predictive model including all these factors was built and performed better than it based on each separately. Further validation in large patient populations is still warranted.

Abstract Background As Twitter has become an active data source for health surveillance research, it is important that efficient and effective methods are developed to identify tweets related to personal health experience. Conventional classification algorithms rely on features engineered by human domain experts, and engineering such features is a challenging task and requires much human intelligence. The resultant features may not be optimal for the classification problem, and can make it challenging for conventional classifiers to correctly predict personal experience tweets (PETs) due to the various ways to express and/or describe personal experience in tweets. In this study, we developed a method that combines word embedding and long short-term memory (LSTM) model without the need to engineer any specific features. Through word embedding, tweet texts were represented as dense vectors which in turn were fed to the LSTM neural network as sequences. Results Statistical analyses of the results of 10-fold cross-validations of our method and conventional methods indicate that there exist significant differences (p

Beef is an important dietary source of quality animal proteins and amino acids in human nutrition. The fatty acid composition is one of the indispensable indicators affecting nutritional value of beef. However, a comprehensive understanding of the expression changes underlying fatty acid composition in representative beef cuts is needed in cattle. This study aimed to characterize the dynamics of fatty acid composition using comparative transcriptomic analysis in five different type of beef cuts. We identified 7545 differentially expressed genes (DEGs) among 10 pair-wise comparisons. Co-expression gene network analysis identified two modules, which were significantly correlated with 2 and 20 fatty acid composition, respectively. We also identified 38 candidate genes, and functional enrichment showed that these genes were involved in fatty acid biosynthetic process and degradation, PPAR, and AMPK signaling pathway. Moreover, we observed a cluster of DEGs (e.g., SCD, LPL, FABP3, and PPARD) which were involved in the regulation of lipid metabolism and adipocyte differentiation. Our results provide some valuable insights into understanding the transcriptome regulation of candidate genes on fatty acid composition of beef cuts, and our findings may facilitate the designs of genetic selection program for beneficial fatty acid composition in beef cattle.

Chinese Simmental beef cattle play a key role in the Chinese beef industry due to their great adaptability and marketability. To achieve efficient genetic gain at a low breeding cost, it is crucial to develop a customized cost-effective low-density SNP panel for this cattle population. Thirteen growth, carcass, and meat quality traits and a BovineHD Beadchip genotyping of 1346 individuals were used to select trait-associated variants and variants contributing to great genetic variance. In addition, highly informative SNPs with high MAF in each 500 kb sliding window and in each genic region were also included separately. A low-density SNP panel consisting of 30,684 SNPs was developed, with an imputation accuracy of 97.4% when imputed to the 770 K level. Among 13 traits, the average prediction accuracy levels evaluated by genomic best linear unbiased prediction (GBLUP) and BayesA/B/Cπ were 0.22–0.47 and 0.18–0.60 for the ~30 K array and BovineHD Beadchip, respectively. Generally, the predictive performance of the ~30 K array was trait-dependent, with reduced prediction accuracies for seven traits. While differences in terms of prediction accuracy were observed among the 13 traits, the low-density SNP panel achieved moderate to high accuracies for most of the traits and even improved the accuracies for some traits.

Carbon aerogels (CA) derived from bamboo cellulose fibers were coupled with TiO2 to form CA/TiO2 hybrids, which exhibited extraordinary performance on the photo-catalytic degradation of methylene blue (MB). The structure and morphology of CA/TiO2 were characterized by field emission scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, X-ray diffraction, and Raman spectrum. The CA displayed a highly porous and interconnected three-dimensional framework structure, while introducing the catalytic active sites of TiO2 onto the aerogel scaffold could remarkably enhance its photo-catalytic activity. The adsorption and photo-catalytic degradation of MB by the CA/TiO2 hybrid were investigated. The maximum adsorption capacity of CA/TiO2 for MB was 18.5 mg/g, which outperformed many similar materials reported in the literature. In addition, compared with other photo-catalysts, the present CA/TiO2 demonstrated superior photo-catalytic performance. Almost 85% of MB in 50 mL solution with a MB concentration of 10 mg/L could be effectively degraded by 15 mg CA/TiO2 in 300 min.

Long-term antibiotic use generates pan-resistant super pathogens. Anti-infective compounds that selectively disrupt virulence pathways without affecting cell viability may be used to efficiently combat infections caused by these pathogens. A candidate target pathway is quorum sensing (QS), which many bacterial pathogens use to coordinately regulate virulence determinants. The Pseudomonas aeruginosa MvfR-dependent QS regulatory pathway controls the expression of key virulence genes; and is activated via the extracellular signals 4-hydroxy-2-heptylquinoline (HHQ) and 3,4-dihydroxy-2-heptylquinoline (PQS), whose syntheses depend on anthranilic acid (AA), the primary precursor of 4-hydroxy-2-alkylquinolines (HAQs). Here, we identified halogenated AA analogs that specifically inhibited HAQ biosynthesis and disrupted MvfR-dependent gene expression. These compounds restricted P. aeruginosa systemic dissemination and mortality in mice, without perturbing bacterial viability, and inhibited osmoprotection, a widespread bacterial function. These compounds provide a starting point for the design and development of selective anti-infectives that restrict human P. aeruginosa pathogenesis, and possibly other clinically significant pathogens.

BACKGROUND: Increasing evidence indicated plasma D-dimer could be regarded as a marker in cancers, however, its role in gastric cancer is still largely unknown. METHODS: Plasma D-dimer levels were measured by enzyme linked fluorescent immunoassays and evaluated by receiver operating characteristic (ROC) curves for peritoneal dissemination in gastric cancer and healthy subjects. The overall survival (OS) characteristics were determined using Kaplan-Meier and Cox regression analyses. RESULTS: The average of the plasma D-dimer levels for gastric cancer patients was significantly higher than the healthy subjects. A Spearman correlation analysis showed that plasma D-dimer levels correlated with the depth of invasion, lymph node metastasis, peritoneal dissemination, distant metastasis, tumor size and TNM stage. The mean plasma D-dimer level was 2.20 ± 1.51 µg/mL in peritoneal dissemination patients and 1.01 ± 0.79 µg/mL in non-peritoneal dissemination patients (P

BACKGROUND AND AIMS:To identify and validate N-glycan biomarkers in gastric cancer (GC) and to elucidate their underlying molecular mechanism of action. METHODS:In total, 347 individuals, including patients with GC (gastric cancer) or atrophic gastritis and healthy controls, were randomly divided into a training group (n=287) and a retrospective validation group (n=60). Serum N-glycan profiling was achieved with DNA sequencer-assisted/fluorophore-assisted carbohydrate electrophoresis (DSA-FACE). Two diagnostic models were constructed based on the N-glycan profiles using logistic stepwise regression. The diagnostic performance of each model was assessed in retrospective, prospective (n=60), and follow-up (n=40) cohorts. Lectin blotting was performed to determine total core-fucosylation, and the expression of genes involved in core-fucosylation in GC was analyzed by reverse transcriptase-polymerase chain reaction. RESULTS:We identified at least 9 N-glycan structures (peaks) and the levels of core fucose residues and fucosyltransferase were significantly decreased in GC. Two diagnostic models, designated GCglycoA and GCglycoB, were constructed to differentiate GC from control and atrophic gastritis. The areas under the receiver operating characteristic (ROC) curves (AUC) for both GCglycoA and GCglycoB were higher than those for CEA, CA19-9, CA125 and CA72-4. Compared with CEA, CA19-9, CA125 and CA72-4, the sensitivity of GCglycoA increased 29.66%, 37.28%, 56.78% and 61.86%, respectively, and the accuracy increased 10.62%, 16.82%, 25.67% and 28.76%, respectively. For GCglycoB, the sensitivity increased 27.97%, 35.59%, 55.09% and 60.17% and the accuracy increased 21.26%, 24.64%, 31.40% and 34.30% compared with CEA, CA19-9, CA125 and CA72-4, respectively. After curative surgery, the core fucosylated peak (peak 3) and the total core fucosylated N-glycans (sumfuc) were reversed. CONCLUSIONS:The results indicated that the diagnostic models based on N-glycan markers are valuable and noninvasive alternatives for identifying GC. We concluded that decreased core-fucosylation in both tissue and serum from GC patients may result from the decreased expression of fucosyltransferase.