Gasparyan AY, et al. J Korean Med Sci. 2017 Aug;32(8):1220-1227. https://doi.org/10.3346/jkms.2017.32.8.1220

Numerous quantitative indicators are currently available for evaluating research productivity. No single metric is suitable for comprehensive evaluation of the author-level impact. The choice of particular metrics depends on the purpose and context of the evaluation. The aim of this article is to overview some of the widely employed author impact metrics and highlight perspectives of their optimal use. The h-index is one of the most popular metrics for research evaluation, which is easy to calculate and understandable for non-experts. It is automatically displayed on researcher and author profiles on citation databases such as Scopus and Web of Science. Its main advantage relates to the combined approach to the quantification of publication and citation counts. This index is increasingly cited globally. Being an appropriate indicator of publication and citation activity of highly productive and successfully promoted authors, the h-index has been criticized primarily for disadvantaging early career researchers and authors with a few indexed publications. Numerous variants of the index have been proposed to overcome its limitations. Alternative metrics have also emerged to highlight 'societal impact.' However, each of these traditional and alternative metrics has its own drawbacks, necessitating careful analyses of the context of social attention and value of publication and citation sets. Perspectives of the optimal use of researcher and author metrics is dependent on evaluation purposes and compounded by information sourced from various global, national, and specialist bibliographic databases.

One of the main problems in the poultry industry is the search for a viable replacement for antibiotic growth promoters. This issue requires a “one health” approach because the uncontrolled use of antibiotics in poultry can lead to the development of antimicrobial resistance, which is a concern not only in animals, but for humans as well. One of the promising ways to overcome this challenge is found in probiotics due to their wide range of features and mechanisms of action for health promotion. Moreover, spore-forming probiotics are suitable for use in the poultry industry because of their unique ability, encapsulation, granting them protection from the harshest conditions and resulting in improved availability for hosts’ organisms. This review summarizes the information on gastrointestinal tract microbiota of poultry and their interaction with commensal and probiotic spore-forming bacteria. One of the most important topics of this review is the absence of uniformity in spore-forming probiotic trials in poultry. In our opinion, this problem can be solved by the creation of standards and checklists for these kinds of trials such as those used for pre-clinical and clinical trials in human medicine. Last but not least, this review covers problems and challenges related to spore-forming probiotic manufacturing.

Gasparyan AY, et al. J Korean Med Sci. 2016 May;31(5):660-673. https://doi.org/10.3346/jkms.2016.31.5.660

This study is first to perform a genome-wide association study (GWAS) to investigate the milk quality traits in Karachai goats. The objective of the study was to identify candidate genes associated with milk composition traits based on the identification and subsequent analysis of all possible SNPs, both genome-wide (high-confidence) and suggestive (subthreshold significance). To estimate the milk components, 22 traits were determined, including several types of fatty acids. DNA was extracted from ear tissue or blood samples. A total of 167 Karachai goats were genotyped using an Illumina GoatSNP53K BeadChip panel (Illumina Inc., San Diego, CA, USA). Overall, we identified 167 highly significant and subthreshold SNPs associated with the milk components of Karachai goats. A total of 10 SNPs were located within protein-coding genes and 33 SNPs in close proximity to them (±0.2 Mb). The largest number of genome-wide significant SNPs was found on chromosomes 2 and 8 and some of them were associated with several traits. The greatest number of genome-wide significant SNPs was identified for crude protein and lactose (6), and the smallest number—only 1 SNP—for freezing point depression. No SNPs were identified for monounsaturated and polyunsaturated fatty acids. Functional annotation of all 43 SNPs allowed us to identify 66 significant candidate genes on chromosomes 1, 2, 3, 4, 5, 8, 10, 13, 16, 18, 21, 23, 25, 26, and 27. We considered these genes potential DNA markers of the fatty acid composition of Karachai goat milk. Also, we found 12 genes that had a polygenic effect: most of them were simultaneously associated with the dry matter content and fatty acids (METTL, SLC1A 8, PHACTR1, FMO2, ECI1, PGP, ABCA3, AMDHD2). Our results suggest that the genes identified in our study affecting the milk components in Karachai goats differed from those identified in other breeds of dairy goats.