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Nitrogen is an essential element for maize growth, but excessive application can lead to various environmental and ecological issues, including water pollution, air pollution, greenhouse gas emissions, and biodiversity loss. Hence, developing maize hybrids resilient to low-N conditions is vital for sustainable agriculture, particularly in nitrogen-deficient soils. Combining ability and genetic relationships among parental lines is crucial for breeding superior hybrids under diverse nitrogen levels. This study aimed to assess the genetic diversity of maize inbred lines using simple sequence repeat (SSR) markers and evaluate their combining ability to identify superior hybrids under low-N and recommended conditions. Local and exotic inbred lines were genotyped using SSR markers, revealing substantial genetic variation with high gene diversity (He = 0.60), moderate polymorphism information content (PIC = 0.54), and an average of 3.64 alleles per locus. Twenty-one F1 hybrids were generated through a diallel mating design using these diverse lines. These hybrids and a high yielding commercial check (SC-131) were field-tested under low-N and recommended N conditions. Significant variations (p < 0.01) were observed among nitrogen levels, hybrids, and their interaction for all recorded traits. Additive genetic variances predominated over non-additive genetic variances for grain yield and most traits. Inbred IL3 emerged as an effective combiner for developing early maturing genotypes with lower ear placement. Additionally, inbreds IL1, IL2, and IL3 showed promise as superior combiners for enhancing grain yield and related traits under both low-N and recommended conditions. Notably, hybrids IL1×IL4, IL2×IL5, IL2×IL6, and IL5×IL7 exhibited specific combining abilities for increasing grain yield and associated traits under low-N stress conditions. Furthermore, strong positive associations were identified between grain yield and specific traits like plant height, ear length, number of rows per ear, and number of kernels per row. Due to their straightforward measurability, these relationships underscore the potential of using these traits as proxies for indirect selection in early breeding generations, particularly under low-N stress. This research contributes to breeding nitrogen-efficient maize hybrids and advances our understanding of the genetic foundations for tolerance to nitrogen limitations.

Drought stress and nutrient status are highly important for plant growth and productivity. Two field experiments were conducted during two consecutive seasons (2017–2018 and 2018–2019) at El-Molak, Abo-Hammad, Sharkia, Egypt. This work was conducted under sandy soil conditions to evaluate the effects of foliar application with growth regulators (PGRs) such as cycocel (CCC), applied at 0, 500, or 1000 mg L−1, and/or salicylic acid (SA), applied at 0, 0.05, or 0.1 mM on the productivity as well as improving drought tolerance of three wheat cultivars, i.e., Gemmeiza 11, Misr 1, and Giza 171 under three irrigation intervals, i.e., 10, 15, and 20 days. Foliar spray was given at 35 and 50 days after planting (DAP). The obtained results showed that mean squares as a result of the main effect and first- and second-order interactions were significant (p ≤ 0.01) for all studied traits. The application of SA increased total chlorophyll content and flag leaf area (cm2) while the number of days to 50% heading was decreased; however, the number of spikes m−2, protein and proline contents were increased with the application of CCC. The cultivar Misr 1 outperformed the other cultivars in the most studied traits. Estimates of heritability in the broad sense (h2b) were, on average, higher in five physiological traits than other agronomic traits, and the highest estimate of h2b (95.1%) was shown by the number of days to 50% heading followed by protein content (91.90%). Among the interactions between irrigation and growth regulators, the I(10) × SA(0.1) recorded the highest flag leaf area (cm2), SPAD value, number of grains spike−1, 1000-grain weight (g), and grain yield (t ha−1). Among the interactions between irrigation and cultivars, the I(10) × Misr 1 recorded the highest flag leaf area (cm2), SPAD value, number of grains spike−1, and grain yield (t ha−1). Among the interactions among irrigation, growth regulators and cultivars, the I(10) × SA(0.1) × Misr 1 recorded the highest flag leaf area (cm2), number of grains spike−1, 1000-grain weight (g), and grain yield (t ha−1). Correlation coefficient between grain yield (t ha−1) and each of the number of days to 50% heading, flag leaf area, total chlorophyll content, number of spikes m−2, number of grains spike−1, and 1000-grain weight was positive and significant. Three main factors for the studied variables were created from the application of the factor analysis technique. Grain yield ha−1 (Y) can be predicted by the method of forwarding stepwise through applying the automatic linear regression analysis. Besides, the best prediction equation of grain yield ha−1 (Y) was formulated as: Ỷ = −14.36 + 0.11 number of grains spike−1 (NGS) + 0.09 1000-grain weight (THW) + 0.04 number of spike m−2 (NSm) + 0.03 days to 50% heading (DF) + 0.02 total chlorophyll content (TC) with adjusted-R2 (87.33%).

As a result of two crosses among three local varieties of wheat, five populations (P1, P2, F5, F6 and F7) were used as parents and grown during two successive seasons; 2016/2017 and 2017/2018. To estimate five types of gene action (e.g., mean effects, additive, dominance, additive × additive, and dominance × dominance), five formulas were developed from with algebraic solution, algebraic proof, and mathematical proof. Besides, to test adequate of a simple additive-dominance model, three formulas A, B, and C scaling test were developed. The path analysis method by PROCESS Macro, AMOS, and Bootstrapping was employed to assess the relationships between grain yield/plant (GYP) as the dependent variable and each one of the number of spikes (NS) and 1000-grain weight (TW) as the independent variables. The results show that there are eight validated equations used to estimate the scaling test (A, B and C) and five types of gene effects (m, a, D, I and L), respectively. Confidence interval using Bootstrapping results indicate that TW was played as the partial mediator between NS as an exogenous variable and GYP as an endogenous variable. Generation means analysis is a relatively simple and statistically reliable tool suitable for the fundamental estimation of different genetic influences.

There has been an increased interest in oilseed crops for agro-industry research and development breeding programs to secure sustainable food and agriculture. The introgression of exotic genotypes of oilseed Brassica into cultivated relatives is inevitable in the genetic improvement of oilseed crops. This experimental attempt aimed to characterize the morphological and molecular basis for the identification and characterization of some Brassica genotypes. Fatty acid profile, yield, and morphology are under genetic control and can be used to identify genotypes. Characterization and identification were fulfilled for five accessions from Brassica spp. Plant height, height of first branch, number of branches and pods per plant, seed yield per plant, average pod length, number of seeds per pod, protein and oil contents (%), and fatty acid profile were examined. Besides, the relationship between seed yield and seed yield-contributing characteristics was estimated, as well as the phylogenetic relationship of the internal transcribed spacer (ITS). The genotypes varied significantly for all examined traits, taking into account the most important traits: seed yield per plant and oil content. For example, oil content in the samples ranged between 41.1 and 49.3%. Path analysis results showed a high and positive direct effect between each number of primary branches and the number of pods per plant with seed yield per plant (0.48). The morphological and molecular observations suggest that the Fay1, Fay3, Fay4, and Fay6 accessions belong to Brassica rapa, while Fay2 belongs to Brassica carinata. It can be concluded based on the present findings that the Fay3 genotype with the highest oil content and the lowest erucic acid content compared to the other genotypes can be proposed as a potential donor for future breeding programs for oil production and quality, while Fay1 can be utilized as donor to increase the seed yield per plant.

The present study examines the role of leguminous compost (LC), humic acids (HA), and phosphate-solubilizing bacteria (P-SB) in alleviating the stress effects of high soil CaCO3 content in Phaseolus vulgaris. Two pot trials for two consecutive seasons; fall 2019 and summer 2020 were implemented in an open greenhouse. A mixed three-way ANOVA, two independent factors (season and soil treatments) and one within factors (time) were used with four replicates. Residual maximum likelihood (REML) analysis was used for the mixed model of the studied traits. Inoculation of calcareous soil with P-SB (a 1:1 mixture of two Pseudomonas sp.; Ps. mallei and Ps. cepaceae) significantly exceeded LC, HA, or even LC+HA for the positive results obtained. P-SB facilitated nutrient solubility (e.g., N, K, Fe, and Mn), including conversion of insoluble phosphorous into a form available in the tested soil due to increased soil enzymatic activities (e.g., phosphatases and phytases). This mechanism, combined with a decrease in soil calcium carbonate content and an increase in cation exchange capacity (CEC) and organic matter (OM) content, increased the availability of various nutrients to plants, including P, in the soil, which contributed to the increased plant output. Adequate P content in plants led to a marked decrease in plant acid phosphatase activity under high content of CaCO3. The study concluded that the use of P-SB promotes biological activities, nutrient availability, and thus the productivity of calcareous soils, enabling Phaseolus vulgaris plants to withstand stress produced by high CaCO3 content through the development and/or adoption of potentially effective mechanisms. Strong highly significant interactions between the treatments and time were observed using the Wald’s statistics test, which indicates a positive correlation.

Safflower ( Carthamus tinctorius L.) is of potential interest to agriculture due to mainly variability of fatty acid composition of seeds oil. The purpose of this study was to evaluate various exotic genotypes of safflower for agronomic traits, components of seed yield and fatty acid content. For this purpose, plant height (cm), number of first, second and third branches/plant, seed yield/plant (g), thousand-seed weight (g), oil content (%), and composition of fatty acid were investigated. Stepwise multiple regression analysis was used to develop fitted equation to predicate seed yield/plant. Analysis of variance of agronomic traits showed high differences among genotypes. Although the safflower oil genotype K2 had the highest oil seed content (42.8%), K13 obtained the highest percentage of monounsaturated fatty acids (MUFA). Highest oleic type of safflower oil has been found in K13 and K26, which can be used as a source oil quality for plant breeding. Heritability as broad sense was high and ranged from 82% in number of secondary branches (NSB) and number of third branches (NTHB) to 99% in seed index (1000 seeds weight) and oil content. High genetic advance was found in plant height (PH), seed yield/plant (SYP) and 1000-seed weight, estimated at 43.41 cm, 21.34 g and 17.62 g, respectively. Stepwise multiple regression analysis indicated that, 99.2% of the total variation in seed yield/plant could be explained by variation in yield of secondary (YSB) branches, yield of first branches (YFB), yield of third branches (YTHB), plant height (PH) and spiny as dummy variable. 23.56% of the total variation in seed oil percent could be explained by variation in yield of first branches (YFB), seed index and spiny as dummy variable. The information detected here may be a useful tool for the selection of parents in safflower breeding program. Le carthame ( Carthamus tinctorius L.) présente un intérêt potentiel pour l’agriculture, principalement en raison de la variabilité de la composition en acides gras de l’huile issus de ses graines. L’objectif de cette étude était d’évaluer divers génotypes exotiques de carthame pour leurs caractéristiques agronomiques, leurs composantes du rendement des graines et leur teneur en acides gras. À cette fin, la hauteur de la plante (cm), le nombre de premières, deuxièmes et troisièmes ramifications/plante, le rendement en graines/plante (g), le poids de mille graines (g), la teneur en huile (%) et la composition en acides gras ont été étudiés. Une analyse de régression multiple par étapes a été utilisée pour élaborer une équation ajustée permettant de prédire le rendement en graines/plante. L’analyse de la variance des caractères agronomiques a montré de grandes différences entre les génotypes. Bien que le génotype K2 de carthame oléagineux ait eu la plus forte teneur en huile (42,8%), le génotype K13 a obtenu le pourcentage le plus élevé d’acides gras monoinsaturés (AGMI). Le type de carthame le plus riche en acide oléique a été identifié dans les génotypes K13 et K26, qui peuvent être utilisés comme sources d’huile de qualité lors de la sélection des plantes. L’héritabilité au sens large était élevée et variait de 82 % sur le nombre de ramifications secondaires (NSB) et en nombre de ramifications tertiaires (NTHB), à 99 % en indice de graines (poids de 1000 grains) et en teneur en huile. Un progrès génétique important a été constaté en ce qui concerne la hauteur de la plante (PH), le rendement en graines/plante (SYP) et le poids de 1000 grains, estimés respectivement à 43,41 cm, 21,34 g et 17,62 g. L’analyse en régression multiple par étapes a indiqué que 99,2 % de la variation totale du rendement en graines/plante pouvait être expliquée par la variation du rendement des branches secondaires (YSB), du rendement des premières branches (YFB), du rendement des troisièmes branches (YTHB), de la hauteur de la plante (PH) et d’indices de graines et d’épines comme variable fictive. 23,56 % de la variation totale du pourcentage d’huile de graines pourrait être expliquée par la variation du rendement des premières branches (YFB), de l’indice de graines et des épines comme variable fictive. Les informations trouvées ici peuvent être un outil utile pour la sélection des parents dans le programme de sélection du carthame.

Inflammasome targeting and controlling dysbiosis are promising therapeutic approaches to control ulcerative colitis. This report is the first to investigate the mechanisms underlying the coloprotective effects of rosuvastatin and Lactobacillus and their combined therapy on dextran sodium sulfate (DSS)-induced colitis in high-fat diet (HFD)-fed rats. Our results demonstrate the aggravation of intestinal inflammation as a consequence of an HFD following DSS administration. An association between dyslipidemia, LDL oxidation, CD36 expression, ROS generation, thioredoxin-interacting protein (TXNIP) upregulation, and NLRP3 inflammasome activation was demonstrated by DSS exposure in HFD-fed rats. We demonstrated that rosuvastatin/Lactobacillus significantly suppressed the DSS/HFD-induced increase in colon weight/length ratio, DAI, MDI, and myeloperoxidase, as well as corrected dysbiosis and improved histological characteristics. Additionally, caspase-1 activity and IL-1β-driven pyroptotic activity was significantly reduced. Rosuvastatin/Lactobacillus showed prominent anti-inflammatory effects as revealed by the IL-10/IL-12 ratio and the levels of TNF-α and IL-6. These latter effects may be attributed to the inhibition of phosphorylation-induced activation of NF-κB and a concomitant reduction in the expression of NLRP3, pro-IL-1β, and pro-IL-18. Furthermore, rosuvastatin/Lactobacillus reduced Ox-LDL-induced TXNIP and attenuated the inflammatory response by inhibiting NLRP3 inflammasome assembly. To conclude, rosuvastatin/Lactobacillus offers a safe and effective strategy for the management of ulcerative colitis.

In order for cognitive radios to identify and take advantage of unused frequency bands, spectrum sensing is essential. Conventional techniques for spectrum sensing rely on extracting features from received signals at specific locations. However, convolutional neural networks (CNNs) and recurrent neural networks (RNNs) have recently demonstrated promise in improving the precision and efficacy of spectrum sensing. Our research introduces a groundbreaking approach to spectrum sensing by leveraging convolutional neural networks (CNNs) to significantly advance the precision and effectiveness of identifying unused frequency bands. We treat spectrum sensing as a classification task and train our model with diverse signal types and noise data, enabling unparalleled adaptability to novel signals. Our method surpasses traditional techniques such as the maximum–minimum eigenvalue ratio-based and frequency domain entropy-based methods, showcasing superior performance and adaptability. In particular, our CNN-based approach demonstrates exceptional accuracy, even outperforming established methods when faced with additive white Gaussian noise (AWGN).

The Wadi El-Rayan lakes are important aquatic environments located at the border of the great North African Sahara. Quantifying the temporal changes in these lakes due to natural and/or anthropogenic stressors is critical when assessing potential impacts on aquatic ecosystem health and the sustainability of fisheries. To detect the changes in fish communities and their drivers, the landing composition of the Wadi El-Rayan lakes over the past 30 years was quantitatively analyzed. The areas of the lakes dramatically decreased from 110 km2 in 1991 to 73 km2 in 2019. The loss of the lake area was attributed to climate warming, where the evaporation rate exceeded the volume of recharge and the recharge decreased due to an increase in agriculture and aquaculture. The total landing significantly increased in the past three decades due to an increase in the fishing effort (number of licensed boats). Nile tilapia, mullet, and grass carp dominated the landings. The pelagic-to-demersal ratio indicated a shift in the fish community composition towards demersal species. This shift was attributed to an increase in the eutrophication level. The fish communities of the landing data were clustered into four distinct groups. These clusters were significantly differentiated (p < 0.001) in both a PERMANOVA test and a PCA plot. There was a gradual replacement of the dominant species among these clusters. The most recent cluster (2018–2019) was characterized by rare species dominating the community. This shift in species composition suggests that target taxa may have been overexploited. The total landing also decreased, which may have been a result of climate warming. Furthermore, the presence of alien and warm-water species significantly increased. The fish community structure and composition shift could be attributed to anthropogenic (mismanagement) and natural climatic changes (warming).

PurposeObesity is associated with fat accumulation in ectopic sites such as the pancreas, the so-called pancreatic steatosis (PS). Bariatric surgery has been shown to be associated with reducing pancreatic fat. This study investigated the effect of laparoscopic sleeve gastrectomy (LSG) on pancreatic volume and its fat content and glucose homeostasis.MethodsThe study enrolled 54 patients subjected to LSG. Metabolic variables and pancreatic exocrine function were assessed immediately before surgery and 12 months after. MRI of the abdomen was performed to measure pancreatic fat content and its total volume and visceral adipose tissue (VAT).ResultsSurgery resulted in a significant reduction in body weight and BMI. HbA1c, fasting insulin, C-peptide levels, HOMA-IR, and Hs-CRP levels decreased significantly. Surgery resulted in significant improvement in lipid profile except for HDL-cholesterol and liver function tests. Total VAT volume decreased significantly. Total pancreas volume decreased by a mean of 9.0 cm3 (95% CI: 6.6–11.3). The median change of pancreatic fat was −26.1% (range: −55.6 to 58.3%). Pancreatic lipase decreased significantly ( P < 0.001). There was a positive correlation between the percentage of total weight loss and decrease in pancreatic fat volume ( r = 0.295, P = 0.030).ConclusionWeight loss after LSG is associated with a reduction of total VAT volume, total pancreatic volume, and pancreatic fat content. These changes are associated with improved glucose homeostasis, reduced systemic inflammation, and decreased pancreatic lipase secretion.