145 research outputs found

    Multi-index based analysis of genotype × environment interaction and selection of superior maize (Zea mays L.) hybrids

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    Genotype-environment interaction (GEI) plays a critical role in genotype adaptation, making it essential for selecting stable, widely adapted genotypes for cultivation. GEI estimation enables the identification of genotypes that perform consistently across diverse conditions. Models and stability indices derived from fixed-effect and/or mixed-effect models are frequently utilized for analyzing GEI and selecting genotypes. In this study, thirty hybrids developed through a diallele fashion, along with two checks, were grown across three environments during kharif 2023. Analysis of variance revealed significant contributions from the environment and GEI, alongside genotypic effects for eight traits studied, covering flowering, plant architecture and yield. Plot yield (t/ha) was subjected to additive main effects and multiplicative interaction effects (AMMI) analysis to study the stability and genotype interactions with the environment. The first two principal components (PCs) of AMMI analysis explained 69.1% and 30.9% of the total variation, respectively, identifying stable hybrids such as MH-TN-15 and MH-TN-30. The Genotype-genotype×environment (GGE) biplot further highlighted the adaptability and stability of all the genotypes, with the first two PCs explaining 86.11% of the G+GE variation. A multi-trait stability index (MTSI) was employed to select stable and high-performing genotypes across multiple traits. A comprehensive analysis of all the genotypes through various indices showed that hybrids MH-TN-15 and MH-TN-30 were consistently selected as stable and high-yielding genotypes across all indices, demonstrating higher yields than check hybrids and being identified for cultivation. These methods underscore the importance of combining yield and stability metrics for effective genotype selection in varied environments

    Designing a broad-spectrum integrative approach for cancer prevention and treatment

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    Targeted therapies and the consequent adoption of "personalized" oncology have achieved notablesuccesses in some cancers; however, significant problems remain with this approach. Many targetedtherapies are highly toxic, costs are extremely high, and most patients experience relapse after a fewdisease-free months. Relapses arise from genetic heterogeneity in tumors, which harbor therapy-resistantimmortalized cells that have adopted alternate and compensatory pathways (i.e., pathways that are notreliant upon the same mechanisms as those which have been targeted). To address these limitations, aninternational task force of 180 scientists was assembled to explore the concept of a low-toxicity "broad-spectrum" therapeutic approach that could simultaneously target many key pathways and mechanisms. Using cancer hallmark phenotypes and the tumor microenvironment to account for the various aspectsof relevant cancer biology, interdisciplinary teams reviewed each hallmark area and nominated a widerange of high-priority targets (74 in total) that could be modified to improve patient outcomes. For thesetargets, corresponding low-toxicity therapeutic approaches were then suggested, many of which werephytochemicals. Proposed actions on each target and all of the approaches were further reviewed forknown effects on other hallmark areas and the tumor microenvironment. Potential contrary or procar-cinogenic effects were found for 3.9% of the relationships between targets and hallmarks, and mixedevidence of complementary and contrary relationships was found for 7.1%. Approximately 67% of therelationships revealed potentially complementary effects, and the remainder had no known relationship. Among the approaches, 1.1% had contrary, 2.8% had mixed and 62.1% had complementary relationships. These results suggest that a broad-spectrum approach should be feasible from a safety standpoint. Thisnovel approach has potential to be relatively inexpensive, it should help us address stages and types ofcancer that lack conventional treatment, and it may reduce relapse risks. A proposed agenda for futureresearch is offered

    Automated Analysis in Feature Modelling and Product Configuration

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    The automated analysis of feature models is one of the thriving topics of research in the software product line and variability management communities that has attracted more attention in the last years. A recent literature review reported that more than 30 analysis operations have been identi ed and di erent analysis mechanisms have been proposed. Product con guration is a well established research eld with more than 30 years of successful applications in di erent industrial domains. Our hypothesis, that is not really new, is that these two independent areas of research have interesting synergies that have not been fully explored. To try to explore the potential synergies systematically, in this paper we provide a rapid review to bring together these previously disparate streams of work. We de ne a set of research questions and give a preliminary answer to some of them. We conclude that there are many research opportunities in the synergy of these independent areas.Ministerio de Ciencia e Innovación TIN2009- 07366Junta de Andalucía TIC-590

    Differential Effects of Pravastatin and Simvastatin on the Growth of Tumor Cells from Different Organ Sites

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    3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) inhibitors, commonly known as statins, may possess cancer preventive and therapeutic properties. Statins are effective suppressors of cholesterol synthesis with a well-established risk-benefit ratio in cardiovascular disease prevention. Mechanistically, targeting HMGCR activity primarily influences cholesterol biosynthesis and prenylation of signaling proteins. Pravastatin is a hydrophilic statin that is selectively taken up by a sodium-independent organic anion transporter protein-1B1 (OATP1B1) exclusively expressed in liver. Simvastatin is a hydrophobic statin that enters cells by other mechanisms. Poorly-differentiated and well-differentiated cancer cell lines were selected from various tissues and examined for their response to these two statins. Simvastatin inhibited the growth of most tumor cell lines more effectively than pravastatin in a dose dependent manner. Poorly-differentiated cancer cells were generally more responsive to simvastatin than well-differentiated cancer cells, and the levels of HMGCR expression did not consistently correlate with response to statin treatment. Pravastatin had a significant effect on normal hepatocytes due to facilitated uptake and a lesser effect on prostate PC3 and colon Caco-2 cancer cells since the OATP1B1 mRNA and protein were only found in the normal liver and hepatocytes. The inhibition of cell growth was accompanied by distinct alterations in mitochondrial networks and dramatic changes in cellular morphology related to cofilin regulation and loss of p-caveolin. Both statins, hydrophilic pravastatin and hypdrophobic simvastatin caused redistribution of OATP1B1 and HMGCR to perinuclear sites. In conclusion, the specific chemical properties of different classes of statins dictate mechanistic properties which may be relevant when evaluating biological responses to statins

    Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

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    Background: Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods: The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results: A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P < 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion: Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)

    Antagonizing retinoic acid receptors increases myeloid cell production by cultured human hematopoietic stem cells

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    Activities of the retinoic acid receptor (RAR)α and RARγ are important to hematopoiesis. Here, we have investigated the effects of receptor selective agonists and antagonists on the primitive human hematopoietic cell lines KG1 and NB-4 and purified normal human hematopoietic stem cells (HSCs). Agonizing RARα (by AGN195183) was effective in driving neutrophil differentiation of NB-4 cells and this agonist synergized with a low amount (10 nM) of 1α,25-dihydroxyvitamin D(3) to drive monocyte differentiation of NB-4 and KG1 cells. Treatment of cultures of human HSCs (supplemented with stem cell factor ± interleukin 3) with an antagonist of all RARs (AGN194310) or of RARα (AGN196996) prolonged the lifespan of cultures, up to 55 days, and increased the production of neutrophils and monocytes. Slowing down of cell differentiation was not observed, and instead, hematopoietic stem and progenitor cells had expanded in number. Antagonism of RARγ (by AGN205728) did not affect cultures of HSCs. Studies of CV-1 and LNCaP cells transfected with RAR expression vectors and a reporter vector revealed that RARγ and RARβ are activated by sub-nM all-trans retinoic acid (EC(50)–0.3 nM): ~50-fold more is required for activation of RARα (EC(50)–16 nM). These findings further support the notion that the balance of expression and activity of RARα and RARγ are important to hematopoietic stem and progenitor cell expansion and differentiation
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