Mammalian Genome最新文献

{"title":"Unraveling the genetic and physiological potential of donkeys: insights from genomics, proteomics, and metabolomics approaches.","authors":"Ram Parsad, Meena Bagiyal, Sonika Ahlawat, Reena Arora, Ritika Gera, Pooja Chhabra, Upasna Sharma","doi":"10.1007/s00335-024-10083-y","DOIUrl":"10.1007/s00335-024-10083-y","url":null,"abstract":"<p><p>Donkeys (Equus asinus) have played a vital role in agriculture, transportation, and companionship, particularly in developing regions where they are indispensable working animals. The domestication of donkeys marked a significant turning point in human history, as they became essential for transportation, agriculture, and trade, especially in arid and semi-arid areas where their resilience and endurance were highly valued. In modern society, donkeys are indispensable due to their diversified applications, including meat, dairy, medicine, and functional bioproducts, supporting economic, cultural, and medical industries. Despite their critical importance, research on donkeys has historically been overshadowed with studies on horses. However, recent advancements in high-throughput sequencing and bioinformatics have significantly deepened our understanding of the molecular landscape of donkey genome, uncovering their unique adaptations, genetic diversity, and potential therapeutic applications. Microsatellite and mitochondrial DNA (mtDNA) markers have proven effective in assessing the genetic diversity of donkeys across various regions of the world. Additionally, significant strides have been made in characterizing differentially abundant genes, proteins, and metabolic profiles in donkey milk, meat, and skin, and in identifying specific genes/proteins/metabolites associated with sperm quality, motility, and reproduction. Advanced genomic technologies, such as genome-wide association studies and the identification of selection signatures, have also been instrumental in delineating genomic regions associated with phenotypic and adaptive traits. This review integrates data from diverse studies, including those on genetic diversity, transcriptomics, whole genome sequencing, protein analysis, and metabolic profiling, to provide a comprehensive overview of donkey biology. It underscores the unique characteristics of donkeys and emphasizes the importance of continued research to improve their genetic management, conservation, and agricultural use, ensuring their ongoing contribution to human societies.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":"10-24"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142605183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: A fascination with tailless mice: a scientific historical review of studies of the T/t complex.","authors":"Robert P Erickson","doi":"10.1007/s00335-024-10087-8","DOIUrl":"10.1007/s00335-024-10087-8","url":null,"abstract":"","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":"52"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142739881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unraveling the maternal heritage: identifying the complex origins of indigenous Indian horse and pony breeds through mitochondrial genome analysis.","authors":"Sonika Ahlawat, Upasna Sharma, S K Niranjan, Pooja Chhabra, Reena Arora, Rekha Sharma, Karan Veer Singh, R K Vijh, S C Mehta","doi":"10.1007/s00335-024-10089-6","DOIUrl":"10.1007/s00335-024-10089-6","url":null,"abstract":"<p><p>This study explored the maternal genetic diversity of six indigenous Indian horse and pony breeds (Bhutia, Kathiawari, Manipuri, Marwari, Spiti, and Zanskari) using comprehensive mitochondrial genome (mitogenome) analysis. Blood samples from 53 horses across diverse agro-climatic zones of India were analyzed, revealing 36 distinct haplotypes, with a haplotype diversity of 0.889 and nucleotide diversity of 0.00347. These indices suggest significant maternal genetic diversity in Indian equines. A median-joining (MJ) network, based on the hypervariable region of the D-loop along with sequences of Indian equids retrieved from the NCBI, identified 55 haplotypes, including shared haplotypes across 2-5 breeds. Hierarchical AMOVA analysis revealed that 95.20% of genetic variation was within populations, while only 4.80% was among different groups, indicating minimal genetic structuring based on geographic distribution. Phylogenetic analysis of these mitogenomes, alongside global sequences, revealed significant genetic variability without clear geographic clustering, highlighting extensive gene flow and interbreeding across regions. Median-Joining network based on D-loop sequence revealed that Indian horses conform to seven of the 18 globally recognized haplogroups (A, B, G, J, L, M, and P), with haplogroup A being the most frequent. This research contributes to the broader understanding of equine genetic diversity, aligning with global patterns of extensive maternal haplotype diversity, and underscores the intricate genetic backgrounds resulting from historical breeding practices.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":"118-128"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142770399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The effect of different approaches to determining the regularization parameter of bayesian LASSO on the accuracy of genomic prediction.","authors":"Hamid Sahebalam, Mohsen Gholizadeh, Seyed Hassan Hafezian","doi":"10.1007/s00335-024-10088-7","DOIUrl":"10.1007/s00335-024-10088-7","url":null,"abstract":"<p><p>Using dense genomic markers opens up new opportunities and challenges for breeding programs. The need to penalize marker-specific regression coefficients becomes particularly important when dense markers are available. Therefore, fitting the marker effects to observations using a regularization technique, such as Bayesian LASSO (BL) regression, is of great interesting. When the Laplace prior distribution is applied to the regression coefficients, BL can be interpreted as a regularization of the <math><mrow><mspace></mspace> <mi>L</mi> <mn>1</mn></mrow> </math> norm based on the Bayesian approach. A critical issue is the appropriate selection of hyperparameters values in the prior distributions of regularization techniques, as these values essentially control the sparsity in the estimated model. The purpose of this study was to evaluate different approaches for selecting the regularization parameter in BL, based on fully Bayesian approaches-such as gamma prior (BL_Gamma), beta prior (BL_Beta) and fixed prior (BL_Fixed) as well as data-driven approaches like cross-validation based on mean square error (BL_CV_MSE) and prediction accuracy (BL_CV_PA). Additionally, information-criteria-based methods including Akaike's information criterion (BL_AIC), Bayesian information criterion (BL_BIC) and Deviance information criterion (BL_DIC), were explored. For this purpose, a genome containing eight chromosomes (each 1 Morgan in length) with 100 randomly distributed quantitative trait loci was simulated. The studied scenarios were as follows: Scenario 1 involved 4000 markers and heritability of 0.2, scenario 2 involved 4000 markers and heritability of 0.6, scenario 3 involved 16,000 markers and heritability of 0.2; and scenario 4 involved 16,000 markers and heritability of 0.6. The results showed that among the fully Bayesian and cross-validation approaches, BL_Gamma, BL_Beta, and BL_CV_MSE provided the highest prediction accuracy (PA) in scenario 1 and 3. With increased marker density and heritability (scenario 4), the cross-validation approaches performed slightly better. The information-criteria-based methods demonstrated the lowest PA. Increasing heritability and marker density led to a decrease and an increase in the model penalty on the regression coefficients, respectively. The PA obtained in the target population ranged from 0.210 to 0.413 in Scenario 1, 0.402 to 0.600 in Scenario 2, 0.256 to 0.442 in Scenario 3, and 0.478 to 0.653 in Scenario 4. In generally, fully Bayesian approaches based on random priors for the regularization parameter are recommended for BL, as they provide acceptable PA with lower computational loads.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":"331-345"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142807598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genome-wide study for signatures of selection identifies genomic regions and candidate genes associated with milk traits in sheep.","authors":"Fatemeh Ebrahimi, Mohsen Gholizadeh, Hamid Sahebalam","doi":"10.1007/s00335-025-10107-1","DOIUrl":"10.1007/s00335-025-10107-1","url":null,"abstract":"<p><p>Milk production traits in sheep are influenced by complex genetic factors, and understanding these traits requires the identification of candidate genes under selection. This study employed two methods, FST and XP-EHH, to identify selection signatures and candidate genes associated with milk production traits in sheep. For this purpose, 9 different breeds from the Sheep HapMap dataset generated by the International Sheep Genomics Consortium (ISGC) based on analysis of the Ovine SNP50 BeadChip were used. The dairy breeds included Brown East Friesian (n = 39), Milk Lacaune (n = 103), Chios (n = 23), Churra (n = 120), and Comisana (n = 24), while the non-dairy breeds included Afshari (n = 37), Moghani (n = 34), Galway (n = 49), and Australian Suffolk (n = 109). Genomic regions in the top 0.1 percentile of FST values revealed 71 genes, while regions with the highest positive XP-EHH values identified 69 genes. Five overlapping genes-DHRS3, TNFRSF1B, AADACL4, ARHGEF11, and LRRC71-were detected by both methods, highlighting their relevance to milk production. Several candidate genes in regions identified from FST, such as PER2, SH3PXD2A, TMEM117, DDX6, PDCD11, CALHM2, and CALHM3, have been previously associated with milk production traits. Notably, CRABP2, PEAR1, PGM1, ALG6, COX15, and OAT were identified in regions with high XP-EHH values in the dairy group. Gene ontology analysis indicated that the identified genes are enriched in pathways related to chemokine receptor activity, gap junction channel activity, and gap junction-mediated intercellular transport, as well as cellular components like the connexin complex. Further studies on these genes may improve understanding of the genetic architecture of milk production traits in sheep.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":"140-150"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143189822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climate resilience in goats: a comprehensive review of the genetic basis for adaptation to varied climatic conditions.","authors":"Ram Parsad, Sonika Ahlawat, Meena Bagiyal, Reena Arora, Ritika Gera, Pooja Chhabra, Upasna Sharma, Ajay Singh","doi":"10.1007/s00335-024-10101-z","DOIUrl":"10.1007/s00335-024-10101-z","url":null,"abstract":"<p><p>The sustainability of livestock systems is widely acknowledged to be threatened by climate change on a worldwide scale. There are worries about the effects this phenomenon may have on the productivity and performance of native livestock species due to its influence on environmental stresses, such as the frequency and severity of unfavorable weather occurrences and the ongoing changes in the agro-ecological landscape. Among the most climatically tolerant livestock animals, goats can survive in a range of environments, from deserts to alpine areas. The domestic goat has undergone significant phenotypic changes in terms of shape, behavior, physiological adaptation, reproduction, and production over their evolutionary journey. It will be possible to better understand the genetic mechanisms underlying successful domestication and the practical breeding strategies leading to the improvement in productivity and resilience to environmental challenges by identifying the genes underlying these modifications. This review explores current knowledge on goat adaptation strategies, emphasizing gene expression patterns, epigenetic modifications, and whole-genome selection signatures. It examines how these molecular mechanisms enable goats to endure heat stress, hypoxia, and other environmental challenges. Furthermore, the review highlights the potential of epigenetic markers and selection signatures in developing climate-resilient goat breeds through marker-assisted selection and genome editing, offering actionable insights into sustainable goat production in the context of global climate change.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":"151-161"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142909941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comprehensive analysis reveals the prognostic and immunological role of PSMD13 in hepatocellular carcinoma.","authors":"Yun Li, Honghui Liu, Na Liu, Lin Chen, Ruijie Liu","doi":"10.1007/s00335-024-10097-6","DOIUrl":"10.1007/s00335-024-10097-6","url":null,"abstract":"<p><p>Immune cell infiltration in liver hepatocellular carcinoma (LIHC) is promising for immunotherapy. However, effective predictive markers to accurately predict a tumour's immune status are lacking. PSMD13, a native component of the 26 S proteasome subunit involved in intracellular metabolism, has an unclear association with cancer and immunity. Using bioinformatics analysis of data from the TCGA, we investigated the expression patterns, prognostic values, gene functions, and tumour immune relationships of PSMD13 in LIHC. We developed a prognostic model that incorporates PSMD13 for LIHC and validated the biological functions of PSMD13 in LIHC cells. Furthermore, we analysed the associations between PSMD13 expression and the tumour immune markers CD206 and CD8 in 101 paired liver tissues using immunohistochemistry. PSMD13 was upregulated in LIHC and served as a prognostic biomarker of LIHC. The knockdown of PMSD13 significantly affected the proliferation, migration, and colony formation of LIHC cells. PSMD13 was closely associated with the infiltration of M2 macrophages and the expression of various tumour immune checkpoints. Our study revealed that PSMD13 is a crucial component contributing to the malignant behaviour of LIHC, indicating its essential role in both the prognosis and potential immune microenvironment profile of LIHC.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":"317-330"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11880097/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142909959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EEF1A2 identified as a hub gene associated with the severity of metabolic dysfunction-associated steatotic liver disease.","authors":"Jian Zhang, Huiwen Wang, Qianbing Wang, Juan Mo, Lei Fu, Shifang Peng","doi":"10.1007/s00335-024-10078-9","DOIUrl":"10.1007/s00335-024-10078-9","url":null,"abstract":"<p><p>Metabolic dysfunction-associated steatotic liver disease (MASLD) is a prevalent chronic liver disease that ranges from metabolic dysfunction-associated steatotic liver (MASL) to metabolic dysfunction-associated steatohepatitis (MASH), and may eventually progress to cirrhosis and hepatocellular carcinoma (HCC). The underlying mechanism of MASLD remains incompletely understood. This study aimed to identify key gene implicated in MASLD pathogenesis and validate its correlation with disease severity through an integration of bioinformatics and experimental approaches. Liver transcriptome data from MASLD patients were obtained from the Gene Expression Omnibus (GEO) database. A diet-induced MASLD mouse model was developed, and liver RNA-sequencing was performed. Liver specimens and clinical data from patients were collected for further analysis. A total of 120 differentially expressed genes (DEGs) were shared between datasets GSE89632 and GSE213621, with functional enrichment in inflammatory, metabolic, and cell cycle-related pathways. Protein-protein interaction (PPI) network analysis identified three modules associated with MASLD, with the cell cycle-related module being the most notable. EEF1A2 was identified as a novel hub gene and revealed to be elevated with MASLD progression through dataset analysis. EEF1A2 was confirmed to be highly expressed in the livers of both MASLD mouse models and patients. Moreover, the increased expression of EEF1A2 in MASH was positively correlated with higher serum alanine aminotransferase (ALT), alanine aminotransferase (AST), total cholesterol (TC), and body mass index (BMI). In conclusion, EEF1A2 is a novel hub gene significantly associated with MASLD severity and is a promising biomarker and therapeutic target for MASLD.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":"93-105"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142469174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pan-cancer TCGA analysis reveals the potential involvement of B-type lamins in dysregulating chromosome segregation in human cancer.","authors":"Subhadip Kundu, Bimal Prasad Jit, Ashok Sharma","doi":"10.1007/s00335-024-10086-9","DOIUrl":"10.1007/s00335-024-10086-9","url":null,"abstract":"<p><p>Lamins play a crucial role in maintaining nuclear structure and function. Our study investigates the expression patterns and clinical implications of B-type lamins with a special focus on lamin B2 across various cancer types using comprehensive RNA sequencing datasets. We found that high expression levels of lamin B1 and lamin B2 are associated with decreased overall and disease-free survival in cancer. This association is further pronounced when both lamins are co-expressed, indicating a compounded negative impact on patient prognosis. Additionally, we highlighted the relationship between B-type lamins and the tumor microenvironment. Lamin B1 mRNA expression shows a strong positive correlation with activated CD4⁺ T-cells and type 2 T-helper cells (Th2), suggesting its role in immune cell infiltration and response within tumors. Lamin B2 expression also correlates moderately with these immune cells, indicating a potential but lesser role in modulating the immune landscape. Notably, the epigenetic state of lamin B1 significantly affects the tumor microenvironment, suggesting a dual role in structural integrity and immune modulation. We have identified 9 lamin B2 interacting proteins that are co-expressed with B-type lamins in cancerous conditions and modulate cytokinesis and cell division pathways during tumorigenesis. Furthermore, we have identified specific molecular targets of B-type lamins that co-express with them in a range of human cancers and are potentially involved in dysregulating chromosome segregation and mRNA binding. Overexpression of these targets alongside B-type lamins correlates with poor prognosis in multiple cancers. These findings underscore the potential of B-type lamins as biomarkers for poor prognosis and as targets for cancer therapies.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":"230-249"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142729978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of novel biomarkers for atherosclerosis using single-cell RNA sequencing and machine learning.","authors":"Xi Yong, Tengyao Kang, Mingzhu Li, Sixuan Li, Xiang Yan, Jiuxin Li, Jie Lin, Bo Lu, Jianghua Zheng, Zhengmin Xu, Qin Yang, Jingdong Li","doi":"10.1007/s00335-024-10077-w","DOIUrl":"10.1007/s00335-024-10077-w","url":null,"abstract":"<p><p>Atherosclerosis (AS) is a predominant etiological factor in numerous cardiovascular diseases, with its associated complications such as myocardial infarction and stroke serving as major contributors to worldwide mortality rates. Here, we devised dependable AS-related biomarkers through the utilization of single-cell RNA sequencing, weighted co-expression network (WGCNA), and differential expression analysis. Furthermore, we employed various machine learning techniques (LASSO and SVM-RFE) to enhance the identification of AS biomarkers, subsequently validating them using the GEO dataset. Following this, CIBERSORT was employed to investigate the correlation between biomarkers and infiltrating immune cells. Consequently, 256 differentially expressed genes (DEGs) were selected in samples of AS and normal. GO and KEGG analyses indicated that these DEGs may be related to the negative regulation of leukocyte-mediated immunity, leukocyte cell-cell adhesion, and immune system processes. Notably, C1QC and COL1A1 were pinpointed as potential diagnostic markers for AS, a finding that was further validated in the GSE21545 dataset. Moreover, the area under the curve (AUC) values for these markers exceeded 0.8, underscoring their diagnostic utility. Analysis of immune cell infiltration revealed that the expression of C1QC was correlated with M0 macrophages, gamma delta T cells, activated mast cells and memory B cells. Similarly, COL1A1 expression was linked to M0 macrophages, memory B cells, activated mast cells, gamma delta T cells, and CD4 native T cells. Finally, these results were validated using mice and human samples through immunofluorescence, immunohistochemistry, and ELISA analysis. Overall, C1QC and COL1A1 would be potential biomarkers for AS diagnosis, and that would provides novel perspectives on the diagnosis and treatment of AS.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":"183-199"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11880100/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142469175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}