somatic cell
Recently Published Documents





2022 ◽  
Vol 2022 ◽  
pp. 1-6
Sergei Yu. Zaitsev ◽  
Oksana A. Voronina ◽  
Anastasia A. Savina ◽  
Larisa P. Ignatieva ◽  
Nadezhda V. Bogolyubova

The aim of the work was to study the correlations between the total amount of water-soluble antioxidants (TAWSA) and biochemical parameters (BC) of cow milk depending on the somatic cell count (SCC). The BC and TAWSA values of cow milk were measured by spectroscopic and amperometric methods, respectively. The milk samples from the black-and-white cows (Moscow region) were divided according to SCС values: (1) ≤200, (2) 200-499, (3) 500-999, and (4) ≥1000 thousand units/mL. The average TAWSA values for groups 1, 2, 3, and 4 (33, 15, 13, and 12 milk samples) were the following: 15.95 ± 0.74 , 14.45 ± 0.84 , 16.04 ± 0.63 , and 14.58 ± 1.18 . The correlations between TAWSA and BC (group 1) were the following: total fat percentage (TFP) -0.305; true protein percentage (TP1) -0.197; total nitrogen percentage (TN2) -0.210; lactose -0.156; solids-not-fat (SNF) -0.276; total dry matter (TDM) -0.399; freezing point (FP) -0.112; pH -0.114; somatic cell count (SCC) - (-0,052). The correlations between TAWSA and BC (group 2) were the following: TFP -0.332; TP1 -0.296; TN2 -0.303; lactose - (-0.308); SNF -0.159; TDM -0.391; FP -0.226; pH - (-0.211); SCC -0.193. The correlations between TAWSA and BC (group 3) were the following: TFP - (-0.352); TP1 - (-0.411); TN2 – (-0.401); lactose - (-0.166); SNF - (-0.462); TDM - (-0.504); FP - (-0.766); pH - (-0.047); SCC - (-0.698). The correlations between TAWSA and BC (group 4) were the following: TFP -0.159; TP1 -0.046; TN2 – 0.077; lactose - (-0.317); SNF - (-0.237); TDM -0.058; FP - (-0.036); pH - (-0.477); SCC - (-0.072). These data are important in assessing the physiological-biochemical status and state of the antioxidant defense system of cows’ organism.

2022 ◽  
Vol 54 (1) ◽  
Salma Elzaki ◽  
Paula Korkuc ◽  
Danny Arends ◽  
Monika Reissmann ◽  
Siham A. Rahmatalla ◽  

AbstractThe Bos indicus zebu cattle Butana is the most commonly used indigenous dairy cattle breed in Sudan. In the last years, high-yielding Holstein dairy cattle were introgressed into Butana cattle to improve their milk yield and simultaneously keep their good adaption to extreme environmental conditions. With the focus on the improvement of milk production, other problems arose such as an increased susceptibility to mastitis. Thus, genetic selection for mastitis resistance should be considered to maintain healthy and productive cows. In this study, we tested 10 single nucleotide polymorphisms (SNPs) which had been associated with somatic cell score (SCS) in Holstein cattle for association with SCS in 37 purebred Butana and 203 Butana × Holstein crossbred cattle from Sudan. Animals were genotyped by competitive allele-specific PCR assays and association analysis was performed using a linear mixed model. All 10 SNPs were segregating in the crossbred Butana × Holstein populations, but only 8 SNPs in Sudanese purebred Butana cattle. The SNP on chromosome 13 was suggestively associated with SCS in the Butana × Holstein crossbred population (rs109441194, 13:79,365,467, PBF = 0.054) and the SNP on chromosome 19 was significantly associated with SCS in both populations (rs41257403, 19:50,027,458, Butana: PBF = 0.003, Butana × Holstein: PBF = 6.2 × 10−16). The minor allele of both SNPs showed an increase in SCS. Therefore, selection against the disadvantageous minor allele could be used for genetic improvement of mastitis resistance in the studied populations. However, investigations in a bigger population and across the whole genome are needed to identify additional genomic loci.

2022 ◽  
Vol 43 (1) ◽  
pp. 141-158
Mauricio Fanin ◽  
Isabela Carvalho dos Santos ◽  
Geysiane Moreira Gerotti ◽  
Camila de Cuffa Matusaiki ◽  

Milk and its derivatives are highly consumed foods worldwide, with recognized nutritional importance. The search for the production of products with superior quality is constant. For the present work, 26 milk-producing properties were selected, with a total of 506 milk samples collected during the period from October 2019 to May 2020 being evaluated. The objective of this study was to evaluate the quality of milk produced in dairy properties in the region west Paraná, classified as good or bad based on the results of the Somatic Cell Count (SCC) and through sampling (n = 10) to evaluate the resistance profile of enterobacteria and Staphylococcus spp. isolated from milk samples, in addition to the presence of the mecA gene in strains of Staphylococcus spp. resistant to oxacillin. There were significant differences between the good and bad properties for the levels of lactose, SCC (cell/mL), and Standard Plate Count (SPC) (CFU/mL). The strains of Staphylococcus spp. showed differences in the percentage of resistance in relation to the good and bad properties for antibiotics: tetracycline, ciprofloxacin, oxacillin, amikacin, clindamycin, gentamycin, and erythromycin. The mecA gene was not detected in any of the coagulase-negative Staphylococcus isolates that showed resistance to oxacillin. For enterobacteria, the isolated species differed in relation to the classification of properties, with predominance for Escherichia coli (40%) for properties classified as bad and Hafnia alvei (40%) for those classified as good. The percentage of antibiotic resistance compared to enterobacteria isolates was higher in properties classified as good. Monitoring through microbial culture and antibiogram is extremely important, favoring the correct choice for the treatment of animals with a reduced selection of resistant strains.

2022 ◽  
Vol 12 ◽  
Gai-Yuan Hu ◽  
Jia-Yi Ma ◽  
Fen Li ◽  
Jing-Ruo Zhao ◽  
Fu-Chun Xu ◽  

Protein fluorescence reporting systems are of crucial importance to in-depth life science research, providing systematic labeling tools for visualization of microscopic biological activities in vivo and revolutionizing basic research. Cotton somatic cell regeneration efficiency is low, causing difficulty in cotton transformation. It is conducive to screening transgenic somatic embryo using the fluorescence reporting system. However, available fluorescence labeling systems in cotton are currently limited. To optimize the fluorescence reporting system of cotton with an expanded range of available fluorescent proteins, we selected 11 fluorescent proteins covering red, green, yellow, and cyan fluorescence colors and expressed them in cotton. Besides mRuby2 and G3GFP, the other nine fluorescent proteins (mCherry, tdTomato, sfGFP, Clover, EYFP, YPet, mVenus, mCerulean, and ECFP) were stably and intensely expressed in transgenic callus and embryo, and inherited in different cotton organs derive from the screened embryo. In addition, transgenic cotton expressing tdTomato appears pink under white light, not only for callus and embryo tissues but also various organs of mature plants, providing a visual marker in the cotton genetic transformation process, accelerating the evaluation of transgenic events. Further, we constructed transgenic cotton expressing mCherry-labeled organelle markers in vivo that cover seven specific subcellular compartments: plasma membrane, endoplasmic reticulum, tonoplast, mitochondrion, plastid, Golgi apparatus, and peroxisome. We also provide a simple and highly efficient strategy to quickly determine the subcellular localization of uncharacterized proteins in cotton cells using organelle markers. Lastly, we built the first cotton stomatal fluorescence reporting system using stomata-specific expression promoters (ProKST1, ProGbSLSP, and ProGC1) to drive Clover expression. The optimized fluorescence labeling system for transgenic somatic embryo screening and functional gene labeling in this study offers the potential to accelerating somatic cell regeneration efficiency and the in vivo monitoring of diverse cellular processes in cotton.

2022 ◽  
Vol 36 (2) ◽  
Lianjun Zhang ◽  
Yaqiong Li ◽  
Yuqiong Hu ◽  
Min Chen ◽  
Changhuo Cen ◽  

2022 ◽  
pp. 39-51
Birbal Singh ◽  
Gorakh Mal ◽  
Rinku Sharma ◽  
Devi Gopinath ◽  
Gauri Jairath ◽  

2022 ◽  
Vol 34 (2) ◽  
pp. 292
E. N. Shedova ◽  
G. N. Singina ◽  
V. P. Sergiev ◽  
M. P. Rubtsova ◽  
N. V. Ravin ◽  

Raymond Ching-Bong Wong ◽  
Junjiu Huang ◽  
Dali Li ◽  
Olga Amaral

Sign in / Sign up

Export Citation Format

Share Document