Pair Combinations Research Articles

MILK PRODUCTIVITY OF COWS UNDER DIFFERENT OPTIONS OF PARENTAL PAIR SELECTION

Introduction. One of the main ways to improve dairy herds is through the identification and utilization of the most effective combinations of parent pairs. This can be achieved by both within-line selection and crossbreeding. It is important to identify the most promising lines and their optimal combinations to ensure their effective utilization for further herd improvement. According to many authors, a systematic approach that involves identifying successful and unsuccessful combinations with the repeated use of the most effective variants will reliably contribute to the increase of the genetic potential of dairy cattle productivity.
 Materials and methods of research. In light of the above, the aim of our research was to investigate the formation of milk production traits in Ukrainian Black-and-White dairy cows in different farms of Ukraine, depending on various options for parent selection. The research was conducted on first-calf heifers and mature cows (third lactation) of Ukrainian Black-and-White dairy breed in three farms: SE EF "Oleksandrivske" in Vinnytsia region (Forest-Steppe zone, n = 714), LLC AE "Imeni Volovikova" in Rivne region (Polissya zone, n = 1840), and SE "Experimental farm "Askaniyske" in Kherson region (Steppe zone, n = 926). The sample included cows that had completed at least the third lactation during the research. In the study animals, the milk production traits (milk yield, milk fat content, and milk fat yield) were studied based on various options of within-line and between-line parent selection through retrospective analysis of zootechnical records data over the past ten years.
 Research results. The analysis of between-line selection of Ukrainian Black-and-White dairy animals in SE EF "Oleksandrivske" showed that the most successful combinations for milk yield and milk fat yield in first-calf heifers were when the dams belonged to the Valiant line and the sires belonged to the Chif line. For mature cows (third lactation), the most successful combinations were when the dams belonged to the Eleveishn line and the sires belonged to the Starbuck line. The lowest values of the mentioned traits for the studied lactations were observed in cows obtained from the crossbreeding of the R. Meximes-Chif and S. T. Rokita-Chif lines, respectively.
 In LLC AE "Imeni Volovikova", the most productive animals for the first lactation were those obtained from the combination of the Starbuck-Bella lines, while for the third lactation, the individuals derived from the crossbreeding of the Bella-Chif lines showed the highest productivity. The least successful combination for both studied lactations was when the dams belonged to the S. T. Rokita line and the sires belonged to the Bella line, as animals resulting from this crossbreeding had the lowest milk yield and milk fat yield values.
 SE "Experimental farm "Askaniyske", the highest milk yield and milk fat yield values for the first lactation were observed in individuals whose dams belonged to the Seateischna line and the sires belonged to the Starbuck line. For the third lactation, the highest values of the mentioned traits were found in cows obtained from the combination of the Chif-Starbuck lines. The lowest productivity for the mentioned lactations was observed in cows resulting from the crossbreeding of the R. Sovering-Bella and R. Sovering-Chif lines, respectively.
 In the internal line breeding at the SE EF "Oleksandrivske," the most productive individuals were found to be first-generation offspring whose parents belonged to the Chief line, and mature cows from the Starbuck line. In the LLC AE "Imeni Volovikova" the animals from the Bella line showed superior performance in both lactations. In the SE "Experimental farm "Askaniyske" cows from the Eleveishn line were found to be the most productive.
 Regarding milk fat content in the Forest-Steppe zone, the best performers were first-generation offspring resulting from the combination of the Cavalier-Chief lines, as well as mature cows from the Eleveishn-Starbuck cross. In the Polissya zone, animals obtained from the Eleveishn-Bella and Starbuck-Bella crosses showed the highest milk fat content. In the Steppe zone, first-generation and mature cows whose mothers belonged to the R. Sovereign line and fathers belonged to the Chief and Bella lines, respectively, demonstrated superior traits.
 Conclusions. Thus, improvement of economically important traits in animals can be achieved through both internal line breeding and interline breeding. In this regard, it is crucial to identify the best line combinations and effectively utilize them in further breeding work.

Analysis and application of RNA binding protein gene pairs to predict the prognosis of gastric cancer

BackgroundRNA-binding proteins (RBPs) are closely related to tumors, but little is known about the mechanism of RBPs in tumorigenesis and progression of gastric cancer (GC). As genes do not usually act alone in the pathway deregulation, gene pair combinations are more likely to become stable and accurate biomarkers. The purpose of our research is to establish a novel signature based on RBP gene pairs to predict the prognosis of gastric cancer patients. MethodsWe downloaded genetic and clinical information from the TCGA and GEO database. TCGA and GSE13911 were used for screening differentially expressed genes (DEGs). The RBP genes were gathered from previous studies and employed to screen out DE-RBP genes after intersecting with DEGs. Samples were classified according to the relative expression of each pair of DE-RBP genes. The univariate Cox regression analysis and random forest were used to identify hub gene pairs to construct signature for predicting the prognosis of gastric cancer. Time-dependent ROC curves and KM survival curves were performed to evaluate the signature. GSEA was performed in TCGA training cohort and GSE62254 testing cohort to analyze enrichment pathways. Finally, the influence of these gene pairs on the prognosis of GC patients was further elucidated respectively through the combination of high and low expression of the two genes in each hub gene pair. ResultsWe screened out 6 hub RBP gene pairs (COL5A2/FEN1, POP1/GFRA1, EXO1/PLEKHS1, SLC39A10/CHI3L1, MMP7/PPP1R1 B and SLC5A6/BYSL) to predict the prognosis of patients with gastric cancer. Using the optimal cut-off value to divide patients into high-risk and low-risk groups in the training and testing cohort, we found that the overall survival (OS) of the low-risk group was higher than that of the high-risk group (P < 0.05). The area under the ROC curves for 1, 3, and 5 years were (0.659, 0.744, 0.758) and (0.624, 0.650, 0.653) in two cohorts. Univariate and multivariate Cox regression analysis showed that 6 RBP gene pairs signature were independent prognostic factors for gastric cancer (P < 0.05). In addition, the prognostic survival analysis showed that COL5A2-high/FEN1-low, POP1-low/GFRA1-high, EXO1-low/PLEKHS1-low,SLC39A10-high/CHI3L1-low, MMP7-high/PPP1R1 B-low, SLC5A6-low/BYSL-low had worse OS (P < 0.05). And the gene correlation analysis showed that there was no obvious correlation between the genes in each gene pairs except SLC5A6/BYSL and POP1/GFRA1. Finally, GSEA analysis showed that the high-risk group was enriched in tumor migration, invasion and growth-related pathways. ConclusionOur study identified a novel 6 RBP gene pairs signature to predict the prognosis of gastric cancer patients and provide potential targets for clinical gene therapy.

Effects of primers, PCR approaches and sample preservation methods on diversity studies of myxobacteria

Myxobacteria have potential application value in developing new antibiotics and environmental protection. In this study, in order to establish a more suitable method for diversity studies of myxobacteria, the effects of primers, polymerase chain reaction (PCR) approaches and sample preservation methods on the results were compared by Illumina high-throughput sequencing. The results showed that the relative abundance and operational taxonomic unit (OTU) ratio of myxobacteria amplified by the universal primers accounted for 0.91–1.85% and 2.82–4.10% of total bacteria, indicating that myxobacteria were the dominant bacteria both in population and species numbers. The relative abundance and OTU number and ratio of myxobacteria amplified by the myxobacteria semi-specific primers were significantly higher than those amplified by the universal primers, of which the primer pair W2/802R specifically amplified myxobacteria of suborder Cystobacterineae, while the primer pair W5/802R mainly amplified myxobacteria of suborder Sorangineae and also amplified more species of suborder Nannocystineae at the same time. Among three PCR approaches, the relative abundance and OTU ratio of myxobacteria amplified by the touch-down PCR were the highest. More myxobacterial OTUs were detected in most dried samples. In conclusion, the combination of the myxobacteria semi-specific primer pairs W2/802R and W5/802R, touch-down PCR, and dry preservation of samples were more conducive to diversity studies of myxobacteria.

Discovery of effective combination from Renshen-Fuzi herbal pair against heart failure by spectrum-effect relationship analysis and zebrafish models

Ethnopharmacological relevanceTraditional herbal pair Ginseng Radix et Rhizoma (roots and rhizomes of Panax ginseng C.A. Mey, Renshen in Chinese) and Aconiti Lateralis Radix Praeparata (lateral roots of Aconitum carmichaelii Debeaux, Fuzi in Chinese), composition of two traditional Chinese medicinal herbs, has been widely used in traditional Chinese medicine formula, in which Shenfu decoction has been used clinically in China for the treatment of heart failure at present. Aim of the studyAlthough the ginsenosides and aconite alkaloids have been proven as the essential bioactive components in Renshen-Fuzi herbal pair, the exact composition of effective components to combat heart failure are still unclear. Therefore, spectrum-effect relationship analysis was performed to reveal its effective combination for anti-heart failure effect. Materials and methodsFirstly, the chemical constituents of Renshen-Fuzi herbal pair were identified using ultra high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF MS). The 39 major compounds in Renshen-Fuzi with five different compatibility ratios were simultaneously quantified using ultra high-performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UHPLC-QQQ MS/MS). Subsequently, zebrafish models induced by verapamil hydrochloride were constructed and four heart failure-related indexes were selected for pharmacodynamic evaluation of Renshen-Fuzi. To analyze the spectrum-effect relationships, partial least squares regression (PLSR) models were established among the contents of 39 compounds in Renshen-Fuzi with each pharmacodynamic index. According to the contribution of each compound to the whole efficacy, 12 compounds were finally screened out as the effective combination. ResultsA total of 157 chemical compounds of Renshen-Fuzi herbal pair were identified, in which 39 components were simultaneously determined. The pharmacological effects indicated that Renshen-Fuzi with 1:2 ratio exhibited the best effect based on zebrafish model, which could improve cardiac output and blood flow velocity and inhibit pericardial enlargement and venous blood stasis significantly. A combination of 9 ginsenosides and 3 aconite alkaloids based on a component–efficacy modeling by PLSR was screened, and exerted approximately equivalent pharmacological effects compared with Renshen-Fuzi herbal pair. ConclusionsOur findings elucidated the effective combination of Renshen-Fuzi herbal pair that has been used in clinic for the treatment of heart failure, which could also promote the pharmacological research and quality control of their formula such as Shenfu decoction.

Genotoxicity of cytokines at chemotherapy-induced 'storm' concentrations in a model of the human bone marrow.

Donor cell leukaemia (DCL) is a complication of haematopoietic stem cell transplantation where donated cells become malignant within the patient's bone marrow. As DCL predominates as acute myeloid leukaemia, we hypothesized that the cytokine storm following chemotherapy played a role in promoting and supporting leukaemogenesis. Cytokines have also been implicated in genotoxicity; thus, we explored a cell line model of the human bone marrow (BM) to secrete myeloid cytokines following drug treatment and their potential to induce micronuclei. HS-5 human stromal cells were exposed to mitoxantrone (MTX) and chlorambucil (CHL) and, for the first time, were profiled for 80 cytokines using an array. Fifty-four cytokines were detected in untreated cells, of which 24 were upregulated and 10 were downregulated by both drugs. FGF-7 was the lowest cytokine to be detected in both untreated and treated cells. Eleven cytokines not detected at baseline were detected following drug exposure. TNFα, IL6, GM-CSF, G-CSF, and TGFβ1 were selected for micronuclei induction. TK6 cells were exposed to these cytokines in isolation and in paired combinations. Only TNFα and TGFβ1 induced micronuclei at healthy concentrations, but all five cytokines induced micronuclei at storm levels, which was further increased when combined in pairs. Of particular concern was that some combinations induced micronuclei at levels above the mitomycin C positive control; however, most combinations were less than the sum of micronuclei induced following exposure to each cytokine in isolation. These data infer a possible role for cytokines through chemotherapy-induced cytokine storm, in the instigation and support of leukaemogenesis in the BM, and implicate the need to evaluate individuals for variability in cytokine secretion as a potential risk factor for complications such as DCL.

A method for constructing non-elementary Cobb – Douglas production functions

The actual scientific problem in machine learning is the development of new interpretable mathematical models, as well as methods and programs for their construction. Many well-known regression models have good interpretative properties, for example, linear and power models (Cobb – Douglas production functions). Previously, the author developed non-elementary linear regressions, the problem of constructing which was reduced to the mixed integer 0–1 linear programming problem.Based on non-elementary linear regressions, in this paper, for the first time, non-elementary Cobb-Douglas production functions are proposed, which include not only explanatory variables in degrees, but also all their possible pair combinations, transformed using binary operations min and max. The proposed models are linearized, which makes it possible to apply for their construction the mixed integer 0–1 linear programming problem formulated in the same way as for non-elementary linear regressions. As a result of its solution, the optimal structure model is automatically determined. The advantage of such a formulation is that the solution of the problem can be obtained faster than using enumeration procedures, and also that the signs of the estimates of the constructed model are guaranteed to be consistent with the meaningful meaning of the factors. At the same time, it is possible to control the requirements for the structure of the model using linear constraints on binary variables. In particular, the problem can be used to select the optimal structures for traditional elementary Cobb – Douglas production functions.The problem of modeling the gross regional product of the Tomsk region is solved. The following variables were chosen as explanatory variables: average per capita cash income of the population, investments in fixed capital, costs of innovative activities of organizations, average annual number of employees, cost of fixed assets, internal costs for research and development. The LPSolve package was chosen as the solver of the mixed integer 0–1 linear programming problem. As a result of solving this problem, the optimal structure of the non-elementary Cobb – Douglas production function was chosen, which contains all six explanatory variables in three regressors. The coefficient of determination for the constructed model turned out to be 0.997. All regression coefficients turned out to be significant according to Student's t-test, and their signs satisfy the meaningful meaning of the factors. An interpretation for the constructed model is given.

СТРУКТУРНЫЙ СИНТЕЗ ЗАМКНУТЫХ КИНЕМАТИЧЕСКИХ ЦЕПЕЙ ПОДВИЖНЫХ ЗВЕНЬЕВ ПЯТОГО, ШЕСТОГО, СЕДЬМОГО И ВОСЬМОГО ПОДСЕМЕЙСТВ ПЕРВОГО СЕМЕЙСТВА

The study objective is to develop a method of structural synthesis of closed kinematic chains of moving links into the fifth, sixth, seventh and eighth subfamilies of the first family.&#x0D; Tasks: to obtain a complete set of solutions describing the arrangement of closed kinematic chains of moving links of the fifth, sixth, seventh and eighth subfamilies of the first family with the complexity of the basic chain link equal to two and three, the mobility of the chain equaling to six and the total number of chain links from 3 to 6 based on the universal structural system of Professor L.T. Dvornikov for closed kinematic chains of moving links of the first family. Using the data obtained, consider the construction of a block diagram of a closed kinematic chain of moving links of the first family on a specific example.&#x0D; Research methods: a method of structural synthesis of closed kinematic chains of moving links of the first family is used.&#x0D; The novelty of the work: the peculiarities of applying a universal structural system for determining the composition of closed kinematic chains of moving links of the fifth, sixth, seventh and eighth subfamilies of the first family are considered. An example of using the obtained combinations of kinematic pairs and links for the synthesis of structural schemes of closed kinematic chains of moving links of the first family is shown.&#x0D; Study results: combinations of kinematic pairs and links are obtained, which make it possible to find structural schemes of closed kinematic chains of moving links of the fifth, sixth, seventh and eighth subfamilies of the first family under given parameters, from which single-moving mechanisms of the first family can be formed by stopping the link.

Asymmetric trichotomous partitioning overcomes dataset limitations in building machine learning models for predicting siRNA efficacy

Chemically modified small interfering RNAs (siRNAs) are promising therapeutics guiding sequence-specific silencing of disease genes. Identifying chemically modified siRNA sequences that effectively silence target genes remains challenging. Such determinations necessitate computational algorithms. Machine learning is a powerful predictive approach for tackling biological problems but typically requires datasets significantly larger than most available siRNA datasets. Here, we describe a framework applying machine learning to a small dataset (356 modified sequences) for siRNA efficacy prediction. To overcome noise and biological limitations in siRNA datasets, we apply a trichotomous, two-threshold, partitioning approach, producing several combinations of classification threshold pairs. We then test the effects of different thresholds on random forest machine learning model performance using a novel evaluation metric accounting for class imbalances. We identify thresholds yielding a model with high predictive power, outperforming a linear model generated from the same data, that was predictive upon experimental evaluation. Using a novel model feature extraction method, we observe target site base importances and base preferences consistent with our current understanding of the siRNA-mediated silencing mechanism, with the random forest providing higher resolution than the linear model. This framework applies to any classification challenge involving small biological datasets, providing an opportunity to develop high-performing design algorithms for oligonucleotide therapies.

The Dwarfs

The Dwarfs

Genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement

BackgroundGenomic selection involves choosing as parents those elite individuals with the higher genomic estimated breeding values (GEBV) to accelerate the speed of genetic improvement in domestic animals. But after multi-generation selection, the rate of inbreeding and the occurrence of homozygous harmful alleles might increase, which would reduce performance and genetic diversity. To mitigate the above problems, we can utilize genomic mating (GM) based upon optimal mate allocation to construct the best genotypic combinations in the next generation. In this study, we used stochastic simulation to investigate the impact of various factors on the efficiencies of GM to optimize pairing combinations after genomic selection of candidates in a pig population. These factors included: the algorithm used to derive inbreeding coefficients; the trait heritability (0.1, 0.3 or 0.5); the kind of GM scheme (focused average GEBV or inbreeding); the approach for computing the genomic relationship matrix (by SNP or runs of homozygosity (ROH)). The outcomes were compared to three traditional mating schemes (random, positive assortative or negative assortative matings). In addition, the performance of the GM approach was tested on real datasets obtained from a Large White pig breeding population.ResultsGenomic mating outperforms other approaches in limiting the inbreeding accumulation for the same expected genetic gain. The use of ROH-based genealogical relatedness in GM achieved faster genetic gains than using relatedness based on individual SNPs. The GROH-based GM schemes with the maximum genetic gain resulted in 0.9%–2.6% higher rates of genetic gain ΔG, and 13%–83.3% lower ΔF than positive assortative mating regardless of heritability. The rates of inbreeding were always the fastest with positive assortative mating. Results from a purebred Large White pig population, confirmed that GM with ROH-based GRM was more efficient than traditional mating schemes.ConclusionCompared with traditional mating schemes, genomic mating can not only achieve sustainable genetic progress but also effectively control the rates of inbreeding accumulation in the population. Our findings demonstrated that breeders should consider using genomic mating for genetic improvement of pigs.

Viability and In Vitro Gastrointestinal Transit Tolerance of Multispecies Probiotic Combinations Incorporated into Orange Juice and Drinking Water.

Little is known about how combining probiotics affects the storage survival and functional performance of individual probiotics when incorporated into non-dairy drinks. Viability of Lacticaseibacillus rhamnosus GG (LG), Limosilactobacillus reuteri ATCC 55730 (LR), Bifidobacterium animalis subsp. lactis BB-12 (Bb), and Propionibacterium jensenii 702 (PJ), either alone or in multi-species combinations included in orange juice (OJ), were assessed during storage in refrigerated conditions and compared with bottled water (BW). The tolerance of probiotics included in refrigerated OJ to simulated gastrointestinal conditions was also examined. LG and LR viabilities were significantly higher in OJ than in BW (p ≤ 0.001), while the reverse was evident for PJ. Bb maintained high viability in both drinks. LG-PJ in both drinks and Bb-PJ in BW resulted in greater viabilities among the paired combinations compared to their respective monocultures when incorporated separately (p ≤ 0.001). The viability of LG in the LG-Bb-PJ combination improved significantly in BW compared with LG alone (p ≤ 0.001). OJ did not alter bacterial tolerance to simulated gastric juice but diminished tolerance to simulated intestinal juice (SIJ). In all combinations, tolerance of LG and LR to SIJ was improved, whereas tolerance of PJ declined significantly compared with respective monocultures (p ≤ 0.001). In conclusion, probiotic storage stability and gastrointestinal transit tolerance were species-dependent and affected by carrier type and combinations. These effects should be considered when formulating probiotic products.

Cross-domain augmentation diagnosis: An adversarial domain-augmented generalization method for fault diagnosis under unseen working conditions

Intelligent fault diagnosis based on domain adaptation has recently been extensively researched to promote reliability of safety-critical assets under different working conditions. However, target data may be inaccessible in the model training phase, resulting in the degradation or failure of the diagnosis model. Therefore, this paper introduces a new idea called cross-domain augmentation (CDA) to achieve diagnosis under unseen working conditions, which are frequently occurred in industrial scenarios. To realize this idea, an adversarial domain-augmented generalization (ADAG) method is proposed with domain augmentation via convex combination of data and feature-label pairs. Through adversarial training on multi-source domains and the augmented domain, ADAG enables learning generalized and augmented features, which are proximal representation in the unseen domain, facilitating the generalization ability of the model. Moreover, feature extractor and domain classifier are optimized as adversaries in model training to obtain domain-invariant features, while the fault classifier is trained to identify the features. Extensive experiment studies indicate that ADAG can successfully solve the cross-domain diagnosis problem under unseen working conditions. For SDUST case study, ADAG promotes the model accuracy by 1.44%; while for a more challenging Ottawa case study, it promotes the model accuracy by 5.34%. Moreover, the domain discrepancy is reduced by 4.6%.

Solving the mystery of discrepancies and double counting in air cargo through demand and supply big data analysis

This paper estimates and analyses the air cargo demand and supply imbalances between large geographical regions based on newly collected demand and supply data. Due to the need for more data for academics and the industry, and the lesser research interest compared to its passenger counterpart, limited empirical research on air cargo market dynamics has been conducted. Live flight and aircraft data were collected for five consecutive years to reconstruct the air cargo network and capacity. Air cargo sales tonnes data were collected and introduced as these data eliminate double counting of transfer route volumes. Both datasets were used and compared to analyse the air cargo trade imbalances. The major findings indicate an imbalance in demand on most of the 110 studied region pair combinations. The supply data indicate a high imbalance for freighter capacity, a relatively smaller imbalance for integrator capacity and a limited imbalance for the wide-body belly capacity. The data indicate that the Middle East, Northeast Asia, Russia, Central Asia, and Central America regions are all transfer or in-transit regions where a large amount of cargo passes through. However, limited cargo volumes originate or find their final destination here. Although the general assumption indicates that air cargo supply follows air cargo demand, imbalances between demand and supply in opposing directions were found for several region pairs. To the best of our knowledge, this paper is one of the first academic sources to introduce data analysis based on sales tonnes. This research assists academics and the industry in getting a better understanding of the current air cargo market dynamics. It also provides a base to enhance future air cargo market research, analysis and forecasting.

Analysis of Medication Law in Treatment of Chronic Atrophic Gastritis Based on TCM Inheritance Auxiliary System

Object: The use of traditional Ghinese Medicine Inheritance assistance system (TMC) for the treatment of chronic atrophic gastritis prescription and the rule of compatibility. Methods: Computer - based Retrieval of Chinese journal full-text database (CNKI) for the treatment of chronic atrophic gastritis related literature, search time limit: 2008-2018. In order to explore the combination of high frequency drug pairs and new prescriptions, the database was established with the aid of traditional Chinese medicine inheritance system. The purpose of this paper was to demonstrate the clinical experience of traditional Chinese medicine in the past ten years, and to find a new breakthrough for the treatment of CAG in traditional Chinese medicine. Result: After screening 223 prescriptions that met the inclusion criteria, including 217 herbs of traditional Chinese medicine, the statistical results show that in the treatment of CAG, the main medicine is invigorating qi and invigorating spleen and Codonopsis and Atractylodes macrocephala are the most common. Combined rule analysis showed that Atractylodes macrocephala had the most association with other drugs. The six new formulas are summarized again. Conclusion: Through the data mining statistical analysis, the prescription of treating CAG included in the selected database is mainly invigorating spleen and stomach, regulating qi, warming and tonifying deficiency, activating blood circulation, nourishing yin and nourishing stomach, clearing heat and dispelling dampness and so on. It has developed a new way of thinking for the clinical treatment of CAG in traditional Chinese medicine.

Development of Novel Herbal Compound Formulations Targeting Neuroinflammation: Network Pharmacology, Molecular Docking, and Experimental Verification.

Neuroinflammation plays an important role in the onset and progression of neurodegenerative diseases. The multicomponent and multitarget approach may provide a practical strategy to address the complex pathological mechanisms of neuroinflammation. This study aimed to develop synergistic herbal compound formulas to attenuate neuroinflammation using integrated network pharmacology, molecular docking, and experimental bioassays. Eight phytochemicals with anti-neuroinflammatory potential were selected in the present study. A compound-gene target-signaling pathway network was constructed to illustrate the mechanisms of action of each phytochemical and the interactions among them at the molecular level. Molecular docking was performed to verify the binding affinity of each phytochemical and its key gene targets. An experimental study was conducted to identify synergistic interactions among the eight phytochemicals, and the associated molecular mechanisms were examined by immunoblotting based on the findings from the network pharmacology analysis. Two paired combinations, andrographolide and 6-shogaol (AN-SG) (IC50 = 2.85 μg/mL), and baicalein-6-shogaol (BA-SG) (IC50 = 3.28 μg/mL), were found to synergistically (combination index <1) inhibit the lipopolysaccharides (LPS)-induced nitric oxide production in microglia N11 cells. Network pharmacology analysis suggested that MAPK14, MAPK8, and NOS3 were the top three relevant gene targets for the three phytochemicals, and molecular docking demonstrated strong binding affinities of the phytochemicals to their coded proteins. Immunoblotting suggested that the AN-SG and BA-SG both showed prominent effects in inhibiting inducible nitric oxide synthase (iNOS) (p < 0.01 and p < 0.05, respectively) and MAPKp-p38 (both p < 0.05) compared with those induced by the LPS stimulation only. The AN-SG combination exhibited greater inhibitions of the protein expressions of iNOS (p < 0.05 vs. individual components), which may partly explain the mechanisms of the synergy observed. This study established a practical approach to developing novel herbal-compound formulations using integrated network pharmacology analysis, molecular docking, and experimental bioassays. The study provides a scientific basis and new insight into the two synergistic combinations against neuroinflammation.

Balancing quality and productivity of Apocynum venetum with N and P fertilizer management under drip irrigation in arid conditions of Northwest China

Although Apocynum venetum L. is a valuable native species in China for economic and industrial purposes, less studies have been conducted to determine the optimum fertilizer application rate for cultivating it. The leaves of A. venetum are used as traditional Chinese herbs and the fiber is referred to as “king of wild fiber’’ because of its anti-microbial and anti-UV features. It grows in poor soils but currently populations of wild A. venetum in China are decreasing rapidly. Developing cultivation techniques for endangered A. venetum to achieve sustainable long-term use of this plant resource has become urgent and important. The role of nutrient supply in increasing yield and quality is currently unknown. To maximize the productivity and economic value of A. venetum, a 3-yr nutrient trial was conducted under drip irrigation to evaluate optimal fertilizer application for producing high yield (dry leaves) and better quality. The effects of N/P combination (N0-0 kg/ha, N1-17.4 kg/ha, N2-34.8 kg/ha, and N3-52.2 kg/ha; P0-0 kg/ha, P1-28.6 kg/ha, P2-57.2 kg/ha, and P3-85.8 kg/ha) on plant growth, yield, as well as the quality of drip-fertilized A. venetum, in northwest China were also investigated. Principal component analysis (PCA) and membership function analysis were implemented to develop a comprehensive evaluation model of nutrient interactions to determine the best N/P fertilizer application scheme for simultaneous yield and quality improvement of A. venetum. Overall, fertilization promoted the growth of A. venetum. With increasing fertilizer application, the growth, leaf yield, and quality of A. venetum tended to increase and then decrease. The maximum leaf yield was achieved under T6 (N2P2) treatment that was increased by 213.1 %, 184.3 %, and 88.3 % compared with controls from 2018 to 2020, respectively. Under T6 as well, the best total flavonoid, rutin, and isoquercitrin contents were observed, which were increased by 52.17 %, 68.39 %, and 128.07 % on average for three years. Correlation analysis showed that agronomic traits (plant height, stem diameter, secondary branch, and reproductive branch number) were positively correlated with both yield (aboveground biomass, yield) and quality (rutin, isoquercitrin, and total flavonoids content). According to the comprehensive evaluation model, the optimum N/P fertilizer pairing combination was N2P2, which resulted in the best quality and highest yield of A. venetum. The current research determined the fertilizer application to cultivate A. venetum and elucidated the effects on productivity and quality. This study provides a foundation for developing cultivation practices of A. venetum and promoting its application.

Половой диморфизм размеров тела в раннем и первом детстве и «качество» среды: уровень антропогенной нагрузки и степень экстремальности климата места жительства

Sexual somatic dimorphism through early and first childhood and «quality» of environment (the level of anthropogenic stress and climatic extremeness of the residence place) Introduction. The goal of study – quantitative conformities of intergroup variability of the level of sexual dimorphism (SD) of somatic traits of children of early and first childhood in connection with ecological factors – the degree of urbanization and the geographic latitude of the residence place of population. Material and methods. The analysis embraces the wide specter of ethno-territorial samples of 3-year-old and 6-year-old children from Russia and former USSR of the second part of XX century (literary data). Each sample has minimal necessary number of statistical characteristics: number of sex/age groups, means and standard deviations for height, weight, chest girth. The quantitative estimation of SD level is performed using Kullback divergence, the analogue of Makhalanobis distance. To estimate the direction and the level of associations of SD of anthropometric traits and ecological parameters the classic correlation analysis for pair combinations of indices in age groups of 3- and 6-year-old children was used. Results. For the compact block of Slavonic samples, examined in 1960s–1970s, the increase of the level of the quantity of population of the residence place is associated with significant decrease of SD of height and SD of weight. The same association for 3-year-old children has the character of tendency, but the same vector of dynamics. SD of chest girth has some small negative significant correlations with the latitude for 3-year-old children and close to significant level for 6-year-old children. The estimation of comparable dynamics of SD of somatic traits in pairs of rural and urban samples of the same region revealed less meanings of SD of height and weight of urban children, that is higher synchrony of growth processes of sexes through the increase of the level of urbanization. Conclusion. The decrease of SD of height/weight parameters and greater sex synchrony of growth dynamics apart with increase of the level of urbanization of the residence place may be the result of better quality of the urban environment (medicine service, nutrition quality, social family status). The decrease of the level of SD of chest girth apart with the increase of the values of geographic latitude witness to the greater sex uniformity of adaptive reactions to the more extremal climatic conditions. @ 2023. This work is licensed under a CC BY 4.0 license.

Antibody-Drug Conjugates, the Combination of Large and Small Therapeutic Molecules

Antibody-drug conjugates are a promising therapeutic class of cytostatic agents. They consist of a monoclonal antibody, usually of the IgG type, to which one or more molecules of a cytotoxic drug are conjugated via a suitable linker (covalent chain). The conjugated form of the drug has significantly lower toxicity than the free form, which cannot be used alone in therapy. The Czech State Institute for Drug Control database has so far registered 9 antibody-drug conjugates for use in oncology. Given the vast number of possible combinations of antibody-drug pairs, a boom in sales is expected by 2025. In the blood circulation, the antibody-drug conjugate specifically targets the antigen expressed on the surface of the tumour cell. The linker between the antibody and the drug must be stable in the blood circulation environment and only be completely degraded in the target tumour cell after internalization of the conjugate or remain bound to the drug after degradation of the protein part of the conjugate (the so-called cleavable or non-cleavable linkers). Subsequently, the drug causes apoptosis of the tumour cell by various mecha­nisms. The drugs used in the 2nd generation antibody-drug conjugates were up to 1,000 times more toxic than the chemotherapeutic drug doxorubicin and were mainly auristatin and maytansine derivatives. Less toxic drugs based on camptothecins, amanitins, etc. are also being tested in the current 3rd generation of conjugates under development. The linker drug is attached to the antibody by various bioconjugation methods. Here, a range of synthetic chemistry techniques are applied, and bioconjugation can be either non-specific or specific. In particular, the peripheral amino acids of the antibody – cysteine, lysine, histidine, tyrosine, glutamine and reduced disulfide bridges between the two heavy chains or between the heavy and light chains – are conjugated. For a specific conjugation, e.g. glycoengineering techniques based on N‑glycosylation of antibody on asparagine (N297) have been developed. Conjugation techniques, as well as the synthesis of "naked" human antibodies are the subject of classified "know-how" of a number of commercial progressive companies and laboratories.

A Framework for Future-Oriented Assessment of Converging Technologies at National Level

Converging technologies require intelligent policy-making as they have significant capabilities to develop disruptive innovations. In this regard, future-oriented technology assessment is vital given the great uncertainty about the consequences of and barriers to accessing these technologies. However, few frameworks have been developed to evaluate converging technologies, and most of those have neglected the unique dimensions of these technologies. Therefore, this study aims to provide a policymaking framework for converging technology development. Accordingly, the proposed framework is designed through a meta-synthesis of previous technology assessment frameworks by considering the feasibility, challenges, and achievements of converging technologies development pathways (CTDPs) as the key factors. Then, the framework is implemented in a case study of Iran and an appropriate strategy for each converging technologies development pathway is proposed based on a quadruple matrix of achievements and challenges. The results show that in Iran, biotechnology and cognitive technologies have the highest and lowest development horizons, respectively; and surprisingly, the combined field of biotechnology-cognitive is the most promising pair combination of converging technologies.

Genetic Factors for the Natural Elimination of Hepatitis C Virus

Relevance. The identification of determinants of the human genome, such as single nucleotide polymorphisms (SNPs), in association with various disease patterns, including infectious diseases, is one of the most actively developing areas of scientific research in the world.. Hepatitis C (HC), which remains a serious global health problem, belongs to the number of infections that attract the attention of specialists.Aims. Determination of genetic markers of hepatitis C virus (HCV) natural elimination and assessment of their role as a monitoring parameter of the epidemiological surveillance system.Materials and methods. The study included 660 people divided into 2 groups: persons with chronic HC (CHC) and blood donors (indicator group of the healthy population). In the studied groups, the following SNPs were typed: rs1143634, rs1143627 (IL-1B); rs4251961, rs419598 (IL1RN); rs1800795 (IL6); rs1800896 (IL-10); rs4986790 (TLR4); rs4374383 (MERTK). The associative relationship between SNPs and CHC alleles was identified using logistic regression analysis within four models (codominant, dominant, recessive, and overdominant). Additionally, the significance of polymorphisms at the intragenic and intergenic levels was assessed using modern bioinformatic resources in the field of functional genomics.Results. In this study, genotypes associated with the natural elimination of HCV were identified. Paired combinations of IL 1RA/IL-1B genotypes associated with the probability of the formation of CHC have been established. It is shown that synonymous SNPs can be associated with any characteristics of the pathological process, which can be explained by disequilibrium in coupling with functionally significant alleles of other genetic loci.Conclusion. The detection of the association of SNPs with clinical manifestations of the pathological process is not final and requires further study taking into account ONP coupling groups.