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The foliar application of nano-potassium followed by humic acid increased all the studied characteristics. The interaction between compost manure (10 ton/ha) and nano-potassium (500 cm3/ha) or humic acid (10 ton/ha) recorded the highest mean values for all parameters during both harvest seasons.Genomic selection has become a reality in plant breeding programs with the reduction in genotyping costs. Especially in maize breeding programs, it emerges as a promising tool for predicting hybrid performance. The dynamics of a commercial breeding program involve the evaluation of several traits simultaneously in a large set of target environments. Therefore, multi-trait multi-environment (MTME) genomic prediction models can leverage these datasets by exploring the correlation between traits and Genotype-by-Environment (G×E) interaction. Herein, we assess predictive abilities of univariate and multivariate genomic prediction models in a maize breeding program. check details To this end, we used data from 415 maize hybrids evaluated in 4 years of second season field trials for the traits grain yield, number of ears, and grain moisture. Genotypes of these hybrids were inferred in silico based on their parental inbred lines using single nucleotide polymorphisms (SNPs) markers obtained via genotyping-by-sequencing (GBS). Because genotypic information was available for only 257 hybrids, we used the genomic and pedigree relationship matrices to obtain the H matrix for all 415 hybrids. Our results demonstrated that in the single-environment context the use of multi-trait models was always superior in comparison to their univariate counterparts. Besides that, although MTME models were not particularly successful in predicting hybrid performance in untested years, they improved the ability to predict the performance of hybrids that had not been evaluated in any environment. However, the computational requirements of this kind of model could represent a limitation to its practical implementation and further investigation is necessary.Recombination is a central biological process with implications for many areas in the life sciences. Yet we are only beginning to appreciate variation in the recombination rate along the genome and among individuals, populations and species. Spurred by technological advances, we are now able to bring variation in this key biological parameter to centre stage. Here, we review the conceptual implications of recombination rate variation and guide the reader through the assumptions, strengths and weaknesses of genomic inference methods, including population-based, pedigree-based and gamete-based approaches. Appreciation of the differences and commonalities of these approaches is a prerequisite to formulate a unifying and comparative framework for understanding the molecular and evolutionary mechanisms shaping, and being shaped by, recombination.To estimate dementia incidence rates using Australian administrative datasets and compare the characteristics of people identified with dementia across different datasets. This data linkage study used a cohort of 267,153 from the Australian 45 and Up Study. link2 Participants completed a survey in 2006-2009 and subsequent dementia was identified through pharmaceutical claims, hospitalisations, aged care eligibility assessments, care needs at residential aged care entry and death certificates. Age-specific, and age-standardised incidence rates, incidence rate ratios and survival from first dementia diagnosis were estimated. Estimated age-standardised dementia incidence rates using all linked datasets was 16.8 cases per 1000 person years for people aged 65+. link3 Comparing incidence rates to the global published rates suggested 77% of cases were identified but this varied by age with highest coverage among those aged 80-84 years (92%). Incidence rate ratios were inconsistent across datasets for sex, socio-economic disadvantage, size of support network, marital status, functional limitations and diabetes. Median survival from first dementia diagnosis ranged from 1.80 years in the care needs dataset to 3.74 years in the pharmaceutical claims dataset. Characteristics of people identified with dementia in different administrative datasets reflect the factors that drive interaction with specific services; this may introduce bias in observational studies using a single data-source to identify dementia.Electrochemiluminescence (ECL) is a powerful transduction technique with a leading role in the biosensing field due to its high sensitivity and low background signal. Although the intrinsic analytical strength of ECL depends critically on the overall efficiency of the mechanisms of its generation, studies aimed at enhancing the ECL signal have mostly focused on the investigation of materials, either luminophores or coreactants, while fundamental mechanistic studies are relatively scarce. Here, we discover an unexpected but highly efficient mechanistic path for ECL generation close to the electrode surface (signal enhancement, 128%) using an innovative combination of ECL imaging techniques and electrochemical mapping of radical generation. Our findings, which are also supported by quantum chemical calculations and spin trapping methods, led to the identification of a family of alternative branched amine coreactants, which raises the analytical strength of ECL well beyond that of present state-of-the-art immunoassays, thus creating potential ECL applications in ultrasensitive bioanalysis.Scholars have long argued for the central role of agency-the size of one's choice set-in the human experience. We demonstrate the importance of agency in shaping people's preferences. We first examine the effects of resource scarcity-which has been associated with both impatience and a lack of agency-on patience and risk tolerance, successfully replicating the decrease in patience among those exposed to scarcity. Critically, however, we show that endowing individuals with agency over scarcity fully moderates this effect, increasing patience substantially. We further demonstrate that agency's impact on patience is partly driven by greater risk tolerance. These results hold even though nearly all individuals with greater agency do not exercise it, suggesting that merely knowing that one could alleviate scarcity is sufficient to change behavior. We then demonstrate that the effects of agency generalize to other adverse states, highlighting the potential for agency-based policy and institutional design.In the past decade, the high morbidity and mortality of atherosclerotic disease have been prevalent worldwide. High-fat food consumption has been suggested to be an overarching factor for atherosclerosis incidence. This study aims to investigate the effects of kefir peptides on high-fat diet (HFD)-induced atherosclerosis in apolipoprotein E knockout (ApoE-/-) mice. 7-week old male ApoE-/- and normal C57BL/6 mice were randomly divided into five groups (n = 8). Atherosclerotic lesion development in ApoE-/- mice was established after fed the HFD for 12 weeks compared to standard chow diet (SCD)-fed C57BL/6 and ApoE-/- control groups. Kefir peptides oral administration significantly improved atherosclerotic lesion development by protecting against endothelial dysfunction, decreasing oxidative stress, reducing aortic lipid deposition, attenuating macrophage accumulation, and suppressing the inflammatory immune response compared with the HFD/ApoE-/- mock group. Moreover, the high dose of kefir peptides substantially inhibited aortic fibrosis and restored the fibrosis in the aorta root close to that observed in the C57BL/6 normal control group. Our findings show, for the first time, anti-atherosclerotic progression via kefir peptides consumption in HFD-fed ApoE-/- mice. The profitable effects of kefir peptides provide new perspectives for its use as an anti-atherosclerotic agent in the preventive medicine.Discovery of new anti-tuberculosis (TB) drugs is a time-consuming process due to the slow-growing nature of Mycobacterium tuberculosis (Mtb). A requirement of biosafety level 3 (BSL-3) facility for performing research associated with Mtb is another limitation for the development of TB drug discovery. In our screening of BSL-1 Mycobacterium spp. against a battery of TB drugs, M. smegmatis (ATCC607) exhibits good agreement with its drug susceptibility against the TB drugs under a low-nutrient culture medium (0.5% Tween 80 in Middlebrook 7H9 broth). M. smegmatis (ATCC607) enters its dormant form in 14 days under a nutrient-deficient condition (a PBS buffer), and shows resistance to a majority of TB drugs, but shows susceptibility to amikacin, capreomycin, ethambutol, and rifampicin (with high concentrations) whose activities against non-replicating (or dormant) Mtb were previously validated.Phallus luteus (Phallaceae), previously known as Dictyophora indusiata, is an edible and medicinal mushroom. As part of a continuing project to discover structurally and/or biologically novel natural products from wild mushrooms, we aimed to perform a chemical investigation of the methanol extract of P. luteus combined with a liquid chromatography-mass spectrometry-guided analysis coupled to an in-house UV spectral library. Two new sesquiterpenes, phallac acids A (1) and B (2), were isolated and determined. The chemical structure of the new natural products was unambiguously determined using a combination of 1D and 2D NMR and high-resolution electrospray ionization mass spectrometry data. To our knowledge, this is the first study to report linear sesquiterpene carboxylic acids from P. luteus. The new compounds were evaluated for α-glucosidase inhibitory activities where phallac acid B (2) showed α-glucosidase inhibitory potential (IC50 value of 94.89 ± 5.57 μM) compared with the standard acarbose (IC50 value of 26.23 ± 1.31 μM).Two novel milbemycin derivatives, 5,27-epoxy-13α-hydroxy milbemycin β11 (1) and 5,27-epoxy-13α-hydroxy-25-ethyl milbemycin β11 (2), were isolated from the genetically engineered strain Streptomyces avermitilis AVE-H39. Their structures were elucidated through the interpretation of HR-ESIMS and extensive NMR spectroscopic data. Compounds 1 and 2 exhibited moderate acaricidal and nematicidal activities.Predictive biology is the next great chapter in synthetic and systems biology, particularly for microorganisms. Tasks that once seemed infeasible are increasingly being realized such as designing and implementing intricate synthetic gene circuits that perform complex sensing and actuation functions, and assembling multi-species bacterial communities with specific, predefined compositions. These achievements have been made possible by the integration of diverse expertise across biology, physics and engineering, resulting in an emerging, quantitative understanding of biological design. As ever-expanding multi-omic data sets become available, their potential utility in transforming theory into practice remains firmly rooted in the underlying quantitative principles that govern biological systems. In this Review, we discuss key areas of predictive biology that are of growing interest to microbiology, the challenges associated with the innate complexity of microorganisms and the value of quantitative methods in making microbiology more predictable.