ИСПОЛЬЗОВАНИЕ СЕЛЕКЦИОННЫХ ИНДЕКСОВ В ПЛЕМЕННОЙ РАБОТЕ

В практике современной селекционной работы отбор животных ведется одно-временно по нескольким хозяйственно полезным признакам. Поэтому задача разработ-ки комплексного числового показателя, который бы с высокой степенью достоверно-сти мог оценить перспективы использования животных в селекционной работе, явля-ется весьма актуальной. Таким комплексным показателем является селекционный ин-декс. В то же время селекционный индекс проводит оценку животного только по его собственной продуктивности. Представляет интерес добавление в этот индекс компо-нентов, которые позволили бы провести комплексную оценку животного не только с учетом его собственной продуктивности, но и с учетом качества его потомства. Наилучшим образом оценить потомство позволяет известный метод BLUP (Best Linear Unbiased Prediction – наилучший линейный несмещенный прогноз), в котором исполь-зуется смешанная биометрическая модель, учитывающая генотип животного, среду его обитания и случайные факторы. В работе показано, что для формирования комбиниро-ванного индекса подойдет только селекционный индекс на основе селекционного от-ношения. Метод BLUP позволяет провести оценку животных только по одному хозяй-ственно полезному признаку. Следовательно, при построении комбинированных се-лекционных индексов оценку по методу BLUP будет необходимо проводить несколько раз, по количеству используемых в составе индекса признаков. При этом предлагается одновременно формировать два набора комбинированных селекционных индексов: с учетом только эффектов оцениваемых отцов; с совместным учетом эффектов отцов и эффектов генетических групп. Это даст более объективную картину при малом коли-честве потомков оцениваемых животных. Данный подход поможет селекционеру вы-брать наиболее оптимальную стратегию дальнейшей селекционной работы.

The aim and tasks of the study included to evaluate and identify soft spring wheat varieties by selection indices. Material and methods. The researches were conducted during 2014-2015 under conditions of research field of the V.M. Remeslo Myronivka Institute of Wheat of NAAS of Ukraine at the laboratory of spring wheat breeding. 33 varieties of soft spring wheat were evaluated by selection indices: Finn-Scandinavian (FSI) and Mexican (MI) index, index of perceptiveness (IP), linear ear density (LED) and ear density(ED). Results and discussions. Evaluation of soft spring wheat varieties by selective indices allows increasing the efficiency of selections using additional information about the secondary marker traits. Middle straw varieties had the optimal balance between elements of productivity and stem length and were characterized the highest values of the indices. It is important in breeding to use indices including traits that reliably correlate with indicators of crop capacity. FSI (r = 0.77±0.06) and LED (r = 0.74±0.06) were revealed to be the most effective indices in our work, as they were characterized with strong correlation with crop capacity. The rest indices we studied: IP (r = 0.66±0.07), ED (r = 0.52±0.07), MI (r = 0.51±0.07) had middle and moderate correlation with crop capacity, since they were also important. That shows in their favour as informative indicators being suitable to use in breeding practice. Conclusions. Soft spring wheat varieties were identified by complex of selection indices: Venera, Struna myronivs`ka, Aranka, Alliance, Etiud, Krasa Polissia, Simkoda myronivs`ka, Katiusha (UKR), PHRSV-03 (USA), Leguan (CZE), Jasna, Koksa (POL). They are recommended as a sourse material in breeding process for productivity. Correlations between crop capacity and selective indices were analyzed and it was established that the strength of connection between them was various and ranged from moderate to strong.

This study aims to evaluate the anthropogenic pressure in the St. Lawrence River by assessing the relationships between composition and chemical contamination of sediments and macroinvertebrate community structure using a selection of indices and metrics. The aims of this study are to (i) determine the composition of macroinvertebrate community in sediments across a gradient of disturbance, (ii) select relevant macroinvertebrate indices and metrics for the assessment of sediment quality, (iii) investigate whether responses of selected indices and metrics differ across habitats and/or sediment quality classes, and finally, (iv) determine the thresholds for critical contaminants related to significant changes in the most relevant indices and metrics. Organic and inorganic contaminants as well as other sediment variables (sediment grain size, total organic carbon, nutrients, etc.) and macroinvertebrate assemblages were determined in 59 sites along the river. Fourteen macroinvertebrate indices and metrics, on the 264 initially selected, were shown to be the most effective to be used in bioassessment for the St. Lawrence River. However, the variation in macroinvertebrate indices and metrics remains strongly explained by habitat characteristics, such as sediment grain size or the level of nutrients. There is also an influence of metals and, to a lesser extent, organic contaminants such as petroleum hydrocarbons. The 14 selected indices and metrics are promising bioassessment tools that are easy to use and interpret in an environmental assessment of sediment quality in the St. Lawrence River.

Asymptotic response to four-path selection due to index and single trait selection according to genomically enhanced breeding values

Solanum torvum has antioksidan. This study aimed to analyse cytotoxic activity and selectivity index of Solanum torvum on T47D breast cancer cells invitro. Identification of Solanum torvum fruit chemical compounds with LCMS containing Clorogenic acid, 4-O-caffeoylquinic acid, 3-O-caffeoylquinic acid, 3-O-feruloyquinic acid, 5-O-feruloylquinic acid, 3-O-feruloylquinic acid, 3,4 - O dicaffeoylquinic acid, 3,5-dicaffeoylquinic acid, 3-O-feruloylquinic acid, 5-O-feruloylquinic acid, putative dicaffeoylquinic lactone. Cytotoxic assays showed that the Solanum torvum Without Fermentation were IC 50 (IGT) 1111.62μg/ mL, IC 50 (MGT)1889.20μg/mL, IC 50 (EGT) 1171.90μg/mL, IC 50 (FEGT) 305.98 μg/mL. Cytotoxic assays showed that the treatment of fermentation was IC 50 (IBT) 1760.36 μg/mL, IC 50 (MBT) 1631.06 μg/mL, IC 50 (EBT) of 1111.58 μg/mL, IC 50 (FEBT) 39.17μg/mL, IC 50 (FHBT) 85.58 μg/mL. Index of selectivity (IS) Solanum torvum (without fermentation) were IS (IGT) 5.23, IS (MGT) 0.61, IS (EGT) 1.06, IS (FEGT) 1.45. Index of selectivity of Solanum torvum (fermentation treatment) were IS (IBT) 2.41, IS (MBT) 0.78, IS (EBT) 0.18, IS (FEBT) 4.64, IS (FHBT) 1.67. The best results are treatment of ethyl acetate fraction of Solanum torvum (FEBT) has IC 50 was 39.17 μg/mL and Index selectivity was 4.64, declared safe/not toxic to normal cells, thus potentially developed as T47D breast anticancer cells.

Solanum torvum has antioksidan. This study aimed to analyse cytotoxic activity and selectivity index of Solanum torvum on T47D breast cancer cells invitro. Identification of Solanum torvum fruit chemical compounds with LCMS containing Clorogenic acid, 4-O-caffeoylquinic acid, 3-O-caffeoylquinic acid, 3-O-feruloyquinic acid, 5-O-feruloylquinic acid, 3-O-feruloylquinic acid, 3,4-O-dicaffeoylquinic acid, 3,5-dicaffeoylquinic acid, 3-O-feruloylquinic acid, 5-O-feruloylquinic acid, putative dicaffeoylquinic lactone. Cytotoxic assays showed that the Solanum torvum Without Fermentation were IC 50 (IGT) 1111.62 μg/ mL, IC 50 (MGT) 1889.20 μg/mL, IC 50 (EGT) 1171.90 μg/mL, IC 50 (FEGT) 305.98 μg/mL. Cytotoxic assays showed thatthe treatment of fermentation was IC 50 (IBT) 1760.36 μg/mL, IC 50 (MBT) 1631.06 μg/mL, IC 50 (EBT) of 1111.58 μg/mL, IC 50 (FEBT) 39.17μg/mL, IC 50 (FHBT) 85.58 μg/mL. Index of selectivity (IS) Solanum torvum (without fermentation) were IS (IGT) 5.23, IS (MGT) 0.61, IS (EGT) 1.06, IS (FEGT) 1.45. Index of selectivity of Solanum torvum (fermentation treatment) were IS (IBT) 2.41, IS (MBT) 0.78, IS (EBT) 0.18, IS (FEBT) 4.64, IS (FHBT) 1.67. The best results are treatment of ethyl acetate fraction of Solanum torvum(FEBT) has IC 50 was 39.17 μg/mL and Index selectivity was 4.64, declared safe/not toxic to normal cells, thus potentially developed as T47D breast anticancer cells.

The aim of the research was to develop a selection index for the evaluation and selection of dairy cattle for increasing milk production and reproductive traits. Materials of the research were data on milk production and reproduction of cows of the Ukrainian Black-and-White dairy breed in commercial farm in Kharkiv region. Studies showed that there was a certain antagonism between milk productivity and reproduction of the Ukrainian Black-and-White dairy cow. The coefficients of phenotypic correlation between milk yield, fat and protein yield and the days open ranged from +0.284 to +0.293. Selection indexes were built, which included protein, fat yield, and days open. The developed selection indexes were characterized by a high relationship with the protein yield (α<0.001), much lower – with the fat yield (α<0.05), while the relationship of the selection indexes with the days open was almost absent. The calculated estimates of correlation and regression coefficients made possible to predict correlated responses of milk production and reproduction traits on selection index. The results showed that the developed selection indexes allow increase the milk production of cows and at the same time to prevent decrease in the level of reproduction.

Objective: This study explores repurposing combined Canagliflozin and Metronidazole therapy as a dual-target approach for cervical cancer, focusing on Akt signaling mechanisms.Materials and methods: This study systematically evaluated the cytotoxic effects of Canagliflozin, Metronidazole, their 1:1 combination, and the reference drug 5-Fluorouracil (5-FU) on HeLa (human cervical cancer) and HFF (normal human Foreskin Fibroblast) cell lines. Using the MTT assay at 24 and 72 hours, cellular viability was assessed, and the selective toxicity index (SI) was calculated to determine specificity towards cancer cells. Drug interactions were analyzed through combination index (CI) using Compusyn software. Molecular docking simulation predicted compounds' binding affinities to kinases in the Akt pathway, including PI3K, PDK1, Akt, and mTOR.Results: The drug combination demonstrated potent, selective cytotoxicity against HeLa cells, with an IC₅₀ of 25.1 µg/mL at 72 hours, while showing minimal toxicity to HFF cells (IC₅₀ > 1000 µg/mL). The selectivity index (SI) surpassed that of 5-fluorouracil, and the combination index (CI) analysis indicated strong synergy. Molecular docking revealed substantial binding affinities to the Akt pathway, with docking scores of -10.5, -9.0, -9.7, and -8.9 kcal/mol for canagliflozin and -5.5, -5.4, -5.5, and -5.1 kcal/mol for metronidazole across PI3K, PDK1, Akt, and mTOR kinases. Conclusion: The mixture demonstrates notable synergistic anticancer activity with a high degree of selectivity for cervical cancer cells. This effect is likely mediated through the suggested dual inhibition of the Akt signaling pathway. Such a repurposing strategy presents a promising targeted therapeutic approach that warrants further investigation.

Objective: This study assesses the effectiveness of combining Dapagliflozin and etoricoxib in inhibiting cancer cell growth and investigates its effects on the mutant PI3K/Akt/mTOR signaling pathway to understand the underlying mechanisms. Methods: After incubation periods of 24 and 72 hours, HeLa cells and normal human fibroblasts (NHF) were utilized to assess the anticancer efficacy and safety profile of Dapagliflozin, Etoricoxib, their combination, and 5-fluorouracil (5FU). The tested concentrations ranged from 0.1 to 1000 µg/ml. To determine potential synergy and selectivity, the combination index (CI) and the selective toxicity index (SI) were estimated. Additionally, molecular docking simulations were performed to evaluate the binding affinities of Dapagliflozin and Etoricoxib to mutant proteins within the PI3K/Akt/mTOR signaling pathway. Results: The MTT assays showed that a combination of Dapagliflozin and etoricoxib has significant anticancer activity. The mixture effectively inhibits the growth of cervical cancer cells, achieving results similar to 5-fluorouracil (5FU) and outperforming Dapagliflozin or etoricoxib alone. Additionally, the cytotoxic effects of the mixture on normal human fibroblast (NHF) cells were much lower than those seen with 5FU, indicating decreased toxicity. The combined use of Dapagliflozin and etoricoxib exhibited synergistic cytotoxic effects, as indicated by the combination index (CI) score. This drug pair also showed selectivity in targeting cancer cells, as reflected by the selectivity index (SI). The molecular docking results showed that Dapagliflozin and Etoricoxib have affinities for interacting with the mutant PI3K/Akt/mTOR signaling protein. Docking scores for Dapagliflozin binding to these proteins were -8, -6.7, and -7.3 kcal/mol, while those for Etoricoxib were -8, -6.6, and -6.8 kcal/mol, respectively. Conclusion: The findings, supported by established pharmacokinetic and safety data, suggest that combining Dapagliflozin and Etoricoxib may provide a safer and more effective treatment option for cervical conditions, with a possible mechanism involving the PI3K/Akt/mTOR pathway, as predicted by molecular docking.

Fertility and mortality differentials among the population groups of the Himalayas.

A Selection Index for Fat Production in Dairy Cattle Utilizing the Fat Yields of the Cow and Her Close Relatives

Optimal lower bounds for rank and select indexes

Objective: This study aimed to evaluate the effect of the metronidazole-Esomeprazole mixture on the inhibition of cervical cancer proliferation and its ability to target heat shock protein 90.Methods: During 24 to 72 hours of incubation, the anticancer effects of metronidazole, esomeprazole, and their mixture were evaluated using the HeLa cervical cancer cell line. In contrast, the human fibroblast cell line (HFF) was used to assess the safety of the mixture. The concentrations of metronidazole, esomeprazole, and the mixture ranged from 0.1 to 1000 µg/ml. The combination index (CI) and selectivity index (SI) study assessed the potential synergistic effects among the ingredients and mixtures' selective toxicity. Computational molecular docking simulations were utilized to evaluate the binding affinity of metronidazole and esomeprazole with heat shock protein 90. Results: The study's findings indicated that the metronidazole-esomeprazole mixture significantly restricted the proliferation of cervical cancer cells. Simultaneously, it exhibited a reduced impact on the viability of the HFF cell line. The CI and SI scores demonstrate that the interaction between metronidazole and esomeprazole had a synergistic effect, with the mixture selectively killing the cancer cells. Conversely, the computational molecular docking simulation suggested that metronidazole and esomeprazole tended to associate with Hsp90, with docking scores measured at -5 kcal/mol and -9.7 kcal/mol, respectively. Conclusion: The study outcomes of MTT, CI, and SI demonstrated the mixture's ability to inhibit cervical cancer growth selectively. Given the established pharmacokinetics and safety profile of the mixture medication, it presents a promising, effective, and safer option for cervical cancer.

The issue of registration of breeding animals of different breeds is dealt with by organizations that keep state books of breeding animals. In Ukraine, the functions of keeping state books of breeding animals in cattle breeding, pig breeding, sheep breeding and horse breeding belong to the powers of the minister, which ensures the formation of state policy in the field of animal husbandry. The issue of animal breeding books is relevant because it is an ongoing process that requires a set of measures aimed at registration, maintenance and promotion of domestic breeding livestock. The purpose of research. To monitor the state books of breeding animals (SBBA) in dairy and meat cattle breeding, sheep breeding and pig breeding for the period 2002–2010. Also, establish the number of potential females that could be entered in the stud books. Materials and methods of research. The material for the study was data on the presence of breeding cows of dairy and meat production, sows and ewes of breeds registered in the State Register of Breeding Subjects in Animal Husbandry (until 2009, the State Breeding Register, SBR) during 2002–2019. The results of research. According to the SBR, 15 dairy breeds of cattle have been registered in Ukraine. During the study period, 15 volumes of SBBA of four breeds of dairy cattle were published in Ukraine, which included information on 12331 breeding animals, including 11477 cows. The largest number of recorded breeding animals of the Ukrainian Black-and-White dairy cattle, of which 144 breeding bulls and 4989 cows, are concentrated in six volumes. In second place is the Ukrainian Red-and-White dairy cattle, namely 4554 animals. Then there is the Simmental with 871 animals, of which 809 cows, and the red steppe 1773 heads, including 1609 cows. It is established that 48.7% of breeding animals were born in the period from 1990 to 1999. A small proportion, namely 0.3%, are animals born before 1979, and only 24% after 2000. Younger animals are recorded in the breeding books of Ukrainian Black-and-White dairy cattle and Ukrainian Red-and-White dairy cattle, and older – in the books of the red steppe. Of the 14 meat breeds used in Ukraine, only 5 have breeding animals that are registered with the SBBA. The total number of meat-producing animals recorded in the SBBA is 5586, including 4649 cows. Of the twelve breeds of pigs bred in Ukraine, only seven breeds, namely the Ukrainian white steppe (1451 heads) and Ukrainian spotted steppe (974), Myrhorod breed (123), Great Black (181), Landrace (727), Poltava meat breed (290) and Ukrainian meat breed (300) during the study period were published state pedigree books. Half (50.7%) of all recorded breeding pigs have a year of birth before 2000. Young (born in 2000) animals are recorded in the breeding books of the Landrace breed and the Ukrainian white steppe, Ukrainian meat breed and Poltava meat breed, where their share varies from 64 to 98%. During the study period, 9 volumes of state books of breeding sheep were published. In addition to Tsigai (884 goals), Askanian Karakul (700), fine-wool (1168), meat-wool with crossbred wool (1917) and Sokol (443), in 2003, 2004 and 2009 3 volumes of SBBA sheep of the Prekos breed were published. The calculation of potential females that could be recorded in the state breeding books revealed the presence of 1251102 breeding animals, including 100796 ewes, 70678 sows, 71341 beef cows and 1008287 dairy cows. The largest number of potential females of different breeds in cattle breeding, sheep breeding and pig breeding in the regions of Ukraine showed a certain pattern, namely the centers for dairy cattle breeding – Vinnytsia (83395 heads), Kyiv (111650), Khmelnytsky (64667), Cherkasy (68035) regions, beef cattle breeding – Volyn (13.466 head), Chernihiv (10.907 head), sheep breeding – Kherson (13.837), Odessa (19078) and pig breeding – Dnipropetrovsk (6452), Poltava (4621). The main goal for calculating potential females was to try to determine the size of the breed in dairy and beef cattle, sheep breeding and pigs breeding. Because the more animals included in the breeding model, the better the results of genetic improvement. In addition, it is possible to address the dynamics of the development of breeding traits, identify successful methods of selection and selection, assessment of population and genetic parameters over time and the creation of breeding programs with breeds of farm animals. Conclusion. State books of breeding animals are an important element of selection. Animal information databases help to estimate the populations of domestic and transboundary breeds in general by a set of characteristics, to determine the population-genetic parameters over time and to develop programs for the improvement of farm animals. Studies have identified a significant number (1251102 heads) of breeding cows, ewes and sows, which at one time could be recorded in the breeding books of the respective breeds.

Introduction In poultry breeding, the aim is to increase the genetic merit of animals at different stages of the production column (e.g. multiplier and grower). To maximize the genetic response given such an aim, the use of information on both purebred and crossbred performance was proposed: combined crossbred and purebred selection (CCPS; Wei 1992 ). According to CCPS methodology, purebred and crossbred performance are treated as different but genetically correlated traits. Wei et al . (1991a , b ), Baumung (1997b) and Uimari & Gibson (1998) have given a complete theoretical description for this phenomenon. Evidence in chicken can be found in papers by, for example, Orozco & Campo (1975) . Wei & Van Der Werf (1994) constructed a simple index combining crossbred and purebred information and showed that under all circumstances CCPS was better than pure line selection (PLS) and crossbred selection (CS). Genetic correlation between purebred and crossbred performance ( rpc ) and crossbred heritability ( h c 2 ) are crucial factors that influenced the relative value of CCPS over PLS & CS. B ijma & van A rendonk (1998) developed a selection index which utilizes both purebred and crossbred information to predict response to BLUP selection with an animal model over multiple generations. It was again concluded that the benefit of including information on crossbred animals was largest when the genetic correlation between purebred and crossbred performance was low. Both Wei & Van Der Werf (1994) and Bijma & Van Arendonk (1998) defined the breeding goal only as an increase in genetic merit of crossbreds, and assumed simplified structures of the breeding programmes, especially in terms of moment of availability of information on performance. Harvey (cited by Hartmann 1992 ) compared the accuracy of breeding values of purebred animals for crossbred combining ability estimated from different information sources, assuming equal weighting of purebred and crossbred records. Wei & Van Der Werf (1994) suggested that weighting factors of purebred and crossbred information should be derived by the discounted gene flow methodology. As a result, groups of traits (i.e. production versus reproduction, purebred versus crossbred) will have different weightings according to the position of a line in the crossbreeding scheme ( Smith 1964 ; Jiang 1998b ). The aim of this study was to construct a breeding goal for a specialized dam line and a realistic scheme for combined purebred and crossbred selection in broilers, and to appraise the relative value of information on purebred and crossbred performance in such a scheme. Materials and methods Consider a three‐way crossbreeding system, A × (C × D), in which A is a specialized sire line, and C and D are specialized dam lines ( Fig. 1 ). This paper focuses on selection in line D. Generally, both production and reproduction traits should be considered in this line, but here only one reproduction trait is considered, namely, hatching egg number. Discrete generations are assumed. Hens of line D mate to cocks of the same line D to produce purebred offspring. D × D offspring is used for testing and as such includes the selection candidates. Hens of line D also mate to cocks of line C to produce crossbred offspring (C × D) for testing. As a result, every purebred animal has purebred full sibs (FS), purebred half sibs (HS, same sire of line D, different D dams) and crossbred HS (same dam of line D, different sires of line C). After a certain number of offspring are bred, the hens and cocks of line D could be used for other commercial operations, either to produce D × D offspring as great‐grandparent (GGP) stock or to produce C × D offspring as parent stock. The position of specialized dam line D in the three‐way crossbreeding system of chickens image Definition of the breeding goal Hatching egg number is expressed at various stages of the production column, for example, in a three‐way crossbreeding system it is expressed by great‐grandparents (GGP), grandparents (GP) and parents ( Fig. 1 ). The lower is the stage in the production column, the larger is the number of animals. In this study, the GP stage is a representative of purebred expression of hatching egg number and parent stage is a representative of crossbred expression. Index selection methodology ( Hazel 1943 ) is applied. Hatching egg number for purebred and crossbred birds are treated as different but genetically correlated traits. The breeding goal consists of both purebred and crossbred genetic improvements image (1) where, H l is the aggregate genotype of a crossbred animal in C × D for selection path l ( l = s , selection for sires; l = d , selection for dams), g p [egg/purebred female] and g c [egg/crossbred female] are (true) breeding values for hatching egg number, and v pl and v cl are economic weightings for purebred D and crossbred C*D, respectively, with image (2) image (3) where ev p (Dfl/egg per purebred female) and ev c (Dfl/egg per crossbred female) are economic values for traits expressed in purebred and crossbred animals; cde pl and cde cl are the number of times purebred and crossbred females, respectively, will express hatching egg number over a time horizon of 20 years (i.e. cumulative discounted expressions for selection path l ). p / c is the ratio of the number of animals at purebred stage to that at crossbred stage. The model by Groen et al . (1998) is used to derive economic values for hatching egg number. In a three‐way crossbreeding system, a GP breeder purchases line D female chicks and line C males, and sells C × D chicks. A parent breeder purchases C × D female chicks and line A males to produce A × (C × D) chicks. The production process of GP is quite similar to that of a parent breeder and cost and revenue components are almost the same. Therefore, we made use of the multiplier part of the model to simulate the production of a GP breeder in a situation of non‐integration. Input parameters are adopted from Jiang et al . (1998a) . The parameters that are changed to fit the situation of a GP breeder are in Table 1 . Market