Whole-genome resequencing of Chinese indigenous sheep provides insight into the genetic basis underlying climate adaptation.

BACKGROUND: Chinese indigenous sheep are valuable resources with unique features and characteristics. They are distributed across regions with different climates in mainland China; however, few reports have analyzed the environmental adaptability of sheep based on their genome. We examined the variants and signatures of selection involved in adaptation to extreme humidity, altitude, and temperature conditions in 173 sheep genomes from 41 phenotypically and geographically representative Chinese indigenous sheep breeds to characterize the genetic basis underlying environmental adaptation in these populations. RESULTS: Based on the analysis of population structure, we inferred that Chinese indigenous sheep are divided into four groups: Kazakh (KAZ), Mongolian (MON), Tibetan (TIB), and Yunnan (YUN). We also detected a set of candidate genes that are relevant to adaptation to extreme environmental conditions, such as drought-prone regions (TBXT, TG, and HOXA1), high-altitude regions (DYSF, EPAS1, JAZF1, PDGFD, and NF1) and warm-temperature regions (TSHR, ABCD4, and TEX11). Among all these candidate genes, eight ABCD4, CNTN4, DOCK10, LOC105608545, LOC121816479, SEM3A, SVIL, and TSHR overlap between extreme environmental conditions. The TSHR gene shows a strong signature for positive selection in the warm-temperature group and harbors a single nucleotide polymorphism (SNP) missense mutation located between positions 90,600,001 and 90,650,001 on chromosome 7, which leads to a change in the protein structure of TSHR and influences its stability. CONCLUSIONS: Analysis of the signatures of selection uncovered genes that are likely related to environmental adaptation and a SNP missense mutation in the TSHR gene that affects the protein structure and stability. It also provides information on the evolution of the phylogeographic structure of Chinese indigenous sheep populations. These results provide important genetic resources for future breeding studies and new perspectives on how animals can adapt to climate change.

Prediction and analysis of quality markers for Chuantieling gel patches based on HPLC fingerprinting and network pharmacology.

The Chuantieling gel patch (CGP), a traditional Chinese medicine compound, is an external treatment for asthma. It has shown remarkable effectiveness in alleviating asthma-related airway hyperresponsiveness and inflammation. Nevertheless, there is currently no information available regarding the analysis of quality markers for CGP, and there is a need for further improvement in quality control research. In this study, we developed an HPLC fingerprinting method for CGP and conducted a comprehensive methodological investigation. We assessed the similarity among 10 batches of CGP, identified common peaks, and quantified the content of seven major quality markers. Furthermore, we built a network pharmacology-based 'active ingredients-targets-pathways-diseases' network to forecast the potential mechanisms of action for the primary active components in asthma treatment. Our findings demonstrated that the developed CGP fingerprinting and content determination methods were consistent and trustworthy. We verified the existence of 25 shared peaks and successfully identified 7 chromatographic peaks, including sinigrin thiocyanate, ephedrine hydrochloride, methyleugenol, imperatorin, cinnamaldehyde, emodin, and 6-gingerol, using reference standards. The network pharmacology analysis suggested that these seven active components may target proteins such as STAT3 (signal transducer and activator of transcription 3), MAPK3 (mitogen-activated protein kinase 3), and TP53 (tumor protein P53) and influence various diseases through pathways including cancer pathways, hepatitis B, and PI3K-Akt (phosphoinositide 3-kinase-protein kinase B) signaling. This study provides insight into the complex multicomponent composition of CGP, and the predictive analysis through network pharmacology sets the stage for uncovering the mechanisms responsible for the therapeutic effects of CGP.

Advances in Nanoparticles in the Prevention and Treatment of Myocardial Infarction.

Myocardial infarction (MI) is one of the most prevalent types of cardiovascular disease. During MI, myocardial cells become ischemic and necrotic due to inadequate blood perfusion, leading to irreversible damage to the heart. Despite the development of therapeutic strategies for the prevention and treatment of MI, their effects are still unsatisfactory. Nanoparticles represent a new strategy for the pre-treatment and treatment of MI, and novel multifunctional nanoparticles with preventive and therapeutic capabilities hold promise for the prevention and treatment of this disease. This review summarizes the common types and properties of nanoparticles, and focuses on the research progress of nanoparticles for the prevention and treatment of MI.

MRI-based radiomics model for distinguishing Stage I endometrial carcinoma from endometrial polyp: a multicenter study.

BACKGROUND: Patients with early endometrial carcinoma (EC) have a good prognosis, but it is difficult to distinguish from endometrial polyps (EPs). PURPOSE: To develop and assess magnetic resonance imaging (MRI)-based radiomics models for discriminating Stage I EC from EP in a multicenter setting. MATERIAL AND METHODS: Patients with Stage I EC (n = 202) and EP (n = 99) who underwent preoperative MRI scans were collected in three centers (seven devices). The images from devices 1-3 were utilized for training and validation, and the images from devices 4-7 were utilized for testing, leading to three models. They were evaluated by the area under the receiver operating characteristic curve (AUC) and metrics including accuracy, sensitivity, and specificity. Two radiologists evaluated the endometrial lesions and compared them with the three models. RESULTS: The AUCs of device 1, 2_ada, device 1, 3_ada, and device 2, 3_ada for discriminating Stage I EC from EP were 0.951, 0.912, and 0.896 for the training set, 0.755, 0.928, and 1.000 for the validation set, and 0.883, 0.956, and 0.878 for the external validation set, respectively. The specificity of the three models was higher, but the accuracy and sensitivity were lower than those of radiologists. CONCLUSION: Our MRI-based models showed good potential in differentiating Stage I EC from EP and had been validated in multiple centers. Their specificity was higher than that of radiologists and may be used for computer-aided diagnosis in the future to assist clinical diagnosis.

Therapeutic Potential of Ginsenoside Rb1-PLGA Nanoparticles for Heart Failure Treatment via the ROS/PPARα/PGC1α Pathway.

(1) Background: Ginsenoside Rb1-PLGA nanoparticles (GRb1@PLGA@NPs) represent a novel nanotherapeutic system, yet their therapeutic efficacy and underlying mechanisms for treating heart failure (HF) remain unexplored. This study aims to investigate the potential mechanisms underlying the therapeutic effects of GRb1@PLGA@NPs in HF treatment; (2) Methods: The left anterior descending coronary artery ligation was employed to establish a HF model in Sprague-Dawley rats, along with an in vitro oxidative stress model using H9c2 myocardial cells. Following treatment with GRb1@PLGA@NPs, cardiac tissue pathological changes and cell proliferation were observed. Additionally, the serum levels of biomarkers such as NT-proBNP, TNF-α, and IL-1ß were measured, along with the expression of the ROS/PPARα/PGC1α pathway; (3) Results: GRb1@PLGA@NPs effectively ameliorated the pathological status of cardiac tissues in HF rats, mitigated oxidative stress-induced myocardial cell damage, elevated SOD and MMP levels, and reduced LDH, MDA, ROS, NT-proBNP, TNF-α, and IL-1ß levels. Furthermore, the expression of PPARα and PGC1α proteins was upregulated; (4) Conclusions: GRb1@PLGA@NPs may attenuate myocardial cell injury and treat HF through the ROS/PPARα/PGC1α pathway.

A comparative study between deep learning and radiomics models in grading liver tumors using hepatobiliary phase contrast-enhanced MR images.

PURPOSE: To compare a deep learning model with a radiomics model in differentiating high-grade (LR-3, LR-4, LR-5) liver imaging reporting and data system (LI-RADS) liver tumors from low-grade (LR-1, LR-2) LI-RADS tumors based on the contrast-enhanced magnetic resonance images. METHODS: Magnetic resonance imaging scans of 361 suspected hepatocellular carcinoma patients were retrospectively reviewed. Lesion volume segmentation was manually performed by two radiologists, resulting in 426 lesions from the training set and 83 lesions from the test set. The radiomics model was constructed using a support vector machine (SVM) with pre-defined features, which was first selected using Chi-square test, followed by refining using binary least absolute shrinkage and selection operator (LASSO) regression. The deep learning model was established based on the DenseNet. Performance of the models was quantified by area under the receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity and F1-score. RESULTS: A set of 8 most informative features was selected from 1049 features to train the SVM classifier. The AUCs of the radiomics model were 0.857 (95% confidence interval [CI] 0.816-0.888) for the training set and 0.879 (95% CI 0.779-0.935) for the test set. The deep learning method achieved AUCs of 0.838 (95% CI 0.799-0.871) for the training set and 0.717 (95% CI 0.601-0.814) for the test set. The performance difference between these two models was assessed by t-test, which showed the results in both training and test sets were statistically significant. CONCLUSION: The deep learning based model can be trained end-to-end with little extra domain knowledge, while the radiomics model requires complex feature selection. However, this process makes the radiomics model achieve better performance in this study with smaller computational cost and more potential on model interpretability.

Genome of the webworm Hyphantria cunea unveils genetic adaptations supporting its rapid invasion and spread.

BACKGROUND: The fall webworm Hyphantria cunea is an invasive and polyphagous defoliator pest that feeds on nearly any type of deciduous tree worldwide. The silk web of H. cunea aids its aggregating behavior, provides thermal regulation and is regarded as one of causes for its rapid spread. In addition, both chemosensory and detoxification genes are vital for host adaptation in insects. RESULTS: Here, a high-quality genome of H. cunea was obtained. Silk-web-related genes were identified from the genome, and successful silencing of the silk protein gene HcunFib-H resulted in a significant decrease in silk web shelter production. The CAFE analysis showed that some chemosensory and detoxification gene families, such as CSPs, CCEs, GSTs and UGTs, were expanded. A transcriptome analysis using the newly sequenced H. cunea genome showed that most chemosensory genes were specifically expressed in the antennae, while most detoxification genes were highly expressed during the feeding peak. Moreover, we found that many nutrient-related genes and one detoxification gene, HcunP450 (CYP306A1), were under significant positive selection, suggesting a crucial role of these genes in host adaptation in H. cunea. At the metagenomic level, several microbial communities in H. cunea gut and their metabolic pathways might be beneficial to H. cunea for nutrient metabolism and detoxification, and might also contribute to its host adaptation. CONCLUSIONS: These findings explain the host and environmental adaptations of H. cunea at the genetic level and provide partial evidence for the cause of its rapid invasion and potential gene targets for innovative pest management strategies.

Genome-wide association studies revealed candidate genes for tail fat deposition and body size in the Hulun Buir sheep.

Fat-tailed sheep have a unique characteristic of depositing fat in their tails. In the present study, we conducted genome-wide association studies (GWAS) on traits related to tail fat deposition and body size in the Hulun Buir sheep. A total number of 300 individuals belonging to two fat-tailed lines of the Hulun Buir sheep breed genotyped with the Ovine Infinium HD SNP BeadChip were included in the current study. Two mixed models, one for continuous and one for binary phenotypic traits, were employed to analyse ten traits, that is, body length (BL), body height (BH), chest girth (CG), tail length (TL), tail width (TW), tail circumference (TC), carcass weight (CW), tail fat weight (TF), ratio of CW to TF (RCT) and tail type (TT). We identified 7, 6, 7, 2, 10 and 1 SNPs significantly associated with traits TF, CW, RCT, TW, TT and CG, respectively. Their associated genomic regions harboured 42 positional candidate genes. Out of them, 13 candidate genes including SMURF2, FBF1, DTNBP1, SETD7 and RBM11 have been associated with fat metabolism in sheep. The RBM11 gene has already been identified in a previous study on signatures of selection in this specific sheep population. Two more genes, that is, SMARCA5 and GAB1 were associated with body size in sheep. The present study has identified candidate genes that might be implicated in tail fat deposition and body size in sheep.

Long Noncoding RNA Lnc-SEMT Modulates IGF2 Expression by Sponging miR-125b to Promote Sheep Muscle Development and Growth.

BACKGROUND/AIMS: Long noncoding RNAs (lncRNAs) are RNA transcripts that are more than 200 nt long but have little protein-coding potential. Within the last few years, thousands of lncRNAs have been identified and their functions in biological processes have begun to be understood. Although many studies havebegun to examine the functions of many noncoding RNAs, very little is known about the functions of long noncoding (lncRNA) function of livestock production and molecular mechanisms of their functions are still lackingrelated to livestock production. METHODS: Expression of sheep enhanced muscularityTranscript lncRNA (lnc-SEMT) and miR-125b were examined in sheep using quantitative reverse-transcription polymerase chain reaction. Expression of Myod (myogenic determination factor), Myog (myoglobin) and Insulin-like growth factor 2 (IGF2)were examined by Western Blot.Luciferase reporter assays were performedto confirm the relationship between lnc-SEMT and miR-125b. RESULTS: Here, we identified a novel lnc-SEMT that promote sheep myoblast differentiation in vitro and enhanced sheep muscularity in vivo. Functional analyses showed that lnc-SEMT accelerates sheep myoblast differentiation in vitro. lnc-SEMT transgenic sheep exhibit a muscle hypertrophy phenotype characterized by increased body weight, and increased the number of muscle fibers indicating that lnc-SEMT play an important role in the regulation of skeletal muscle differentiation in vivo. Our results show that lnc-SEMT acts as a molecular sponge by antagonizing miR-125b to control IGF2 protein labundance in vitro and in vivo. CONCLUSION: In brief, lnc-SEMT is the first example of a lncRNA could be a useful candidate for improving biological growth traits such as skeletal muscle production in sheep.

The diagnostic value of multimodality MRI in endometrial carcinoma staging.

Background Multimodality magnetic resonance imaging (MRI) is an imaging technology that is used to integrate the structural and functional information of lesions. MRI can determine the staging of endometrial carcinoma, provide guidance for selection of surgical treatment and postoperative prognostic assessment, and has an important role in improving the survival of patients with endometrial carcinoma. Purpose To evaluate multimodality MRI staging accuracy for endometrial carcinoma based on the International Federation of Gynecology and Obstetrics (FIGO 2009) staging system. Material and Methods This is a retrospective study of the complete clinical and surgical pathology data from 83 patients with endometrial carcinoma treated between June 2011 and August 2015. Using a blind design, the preoperative clinical staging according to the current FIGO2009 MRI-based staging for each endometrial carcinoma was analyzed and corrected by postoperative histopathological results, which served as the staging standard. The role of multimodality MRI on clinical staging accuracy for endometrial carcinoma was studied. Results Based on the pathological evaluation after surgery, the 83 endometrial carcinoma patients were staged according to the current FIGO2009 staging criteria as: stage I, n = 56; stage II, n = 17; stage III, n = 7; and stage IV, n = 3. The multimodality MRI staging accuracy for endometrial carcinoma stages I-IV by FIGO2009 were 91.6% (76/83), 91.6% (76/83), 92.8% (77/83), and 97.6% (81/83), respectively. Conclusion Multimodality MRI is an important imaging tool in the pre-operative clinical staging of endometrial carcinoma. The current FIGO staging system appears to be a concise, reasonable, and practical set of criteria for the clinical management of endometrial carcinoma.

Advances in genome-wide association studies for important traits in sheep and goats.

Genome-wide association study (GWAS), an effective strategy to identify genetic variants associated with complex traits, has been used to study candidate genes of economical traits in animals. With the recent completion of sheep and goat genomes, single nucleotide polymorphism (SNP) chips of different densities are developed and commercialized. All these advances have enlarged the collection of molecular markers and also shed new light on the genetics of traits of interest in sheep and goats. In this review, we focus on the adoption of GWAS for important traits in sheep and goats, such as horn types, wool, dairy, growth and meat, reproduction and disease types, etc., and summarize the populations, major statistical methods and results of the GWAS analysis. Moreover, we also discuss the current state of GWAS, aiming to provide a reference for further studies on the genetic background of the important traits of sheep and goats by GWAS.

Screening of reproduction-related single-nucleotide variations from MeDIP-seq data in sheep.

Extensive variation in reproduction has arisen in Chinese Mongolian sheep during recent domestication. Hu and Small-tailed Han sheep, for example, have become non-seasonal breeders and exhibit higher fecundity than Tan and Ujumqin breeds. We therefore scanned reproduction-related single-nucleotide variations from methylated DNA-immunoprecipitation sequencing data generated from each of those four breeds to uncover potential mechanisms underlying this breed variation. We generated a high-quality map of single nucleotide variations (SNVs) in DNA methylation enriched regions, and found that the majority of variants are located within non-coding regions. We identified 359 SNVs within the Sheep Quantitative Trait Locus (QTL) database. Nineteen of these SNVs associated with the Aseasonal Reproduction QTL, and 10 out of the 19 reside close to genes with known reproduction functions. We also identified the well-known FecB mutation in high-fecundity sheep (Hu and Small-tailed Han sheep). When we applied these FecB finding to our breeding system, we improved lambing rate by 175%. In summary, this study provided strong candidate SNVs associated with sheep fecundity that can serve as targets for functional testing and to enhance selective breeding strategies. Mol. Reprod. Dev. 83: 958-967, 2016 © 2016 Wiley Periodicals, Inc.

Effect of polymorphisms in the CAMKMT gene on growth traits in Ujumqin sheep.

Our previous genome-wide association study in sheep revealed that OAR3-84073899.1 (SNP31) in intron 8 of the CAMKMT gene was significantly associated with post-weaning gain at the genomic level. Herein, we performed a replication study to investigate single nucleotide polymorphisms (SNPs) within the CAMKMT gene exons, and 1000 bp of the 5'- and 3'-intranslated regions (UTRs) and their associations with growth traits in Ujumqin sheep. Five SNPs were identified through DNA pool sequencing technology: SNP26 in the 5'-UTR, SNP06 in exon 5, SNP07 in exon 8 and SNP27 and SNP28 in the 3'-UTR. Six SNPs, including SNP31 in intron 8, were genotyped in the validation group of 343 Ujumqin sheep, and each SNP was classified into three genotypes. The chi-square test suggested that all the variations were in Hardy-Weinberg equilibrium (P > 0.05) except for SNP28 and SNP31. Linkage disequilibrium analysis showed that SNP07 and SNP31 were strongly linked. An association analysis suggested that SNP06 was significantly associated with chest girth at 6 months of age (P < 0.05). SNP07 exhibited significant correlation with body weight and chest girth at 4 months of age and with body weight, chest girth and chest width at 6 months of age (P < 0.05). SNP27 was highly associated with body weight and chest girth at 4 months of age (P < 0.05), and SNP28 was extremely significantly associated with body weight and chest girth at 4 months of age and with chest girth at 6 months of age (P < 0.01). SNP31 was significantly associated with body weight and shin circumference at 4 months of age and with post-weaning gain (P < 0.05). Association analysis of the combined effect of SNP07 and SNP31 showed significant correlation with body weight and chest girth at four of months of age (P < 0.05) and with body weight and chest girth at 6 months of age (P < 0.05). These results indicate that the SNPs could be used as meritorious and available genetic markers in growth traits breeding and that the CAMKMT gene may be one of the key candidate genes that affect Ujumqin economic traits.