Natural Resistance of Sri Lankan Rice (Oryza sativa L.) Varieties to Broad-Spectrum Herbicides (Glyphosate and Glufosinate)

Since studies on herbicide-resistant rice (HRR) are limited in Sri Lanka, the present study conducted to screen the naturally existing glyphosate and glufosinate resistance in traditional and inbred rice varieties. Six traditional varieties and nineteen inbred lines were selected for the study. Complete randomized design with three pots with 10 replicates for each herbicide concentration was employed. Optimal concentrations of glyphosate (0.5 gl−1) and glufosinate (0.05 gl−1) were applied at 3–4 leaf stages. Varieties ≥50% survival percentage was considered as resistant to respective herbicides. Twelve varieties showed resistance (≥50%) at 0.5 gl−1 glyphosate concentration. Survived plants were monitored and agro-morphological and yield characters/parameters were measured. Fifteen varieties were to glufosinate at 0.05 gl−1. Even though no significant differences (p > 0.05) were observed in growth parameters across control and treated plants, there was a yield penalty. Nine varieties (At362, Bg352, Bg359, Bg366, Bg369, Bg379-2, Bg403, Bg454, and Pachchaperumal) indicated moderate resistance to both glyphosate and glufosinate. The emerged HRRs indicated varying responses of agro-morphological and yield characters across the type of herbicide and the variety. Glyphosate reduced the growth parameters and yield penalty compared to glufosinate treated varieties. These HRR varieties have a higher potential in rice breeding programs and in developing HR rice varieties in future

Auditing face mask practice among the general public

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Antibacterial activity of eight invasive alien plants against selected multi-drug resistant microorganisms

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Nonvolatile voltage controlled molecular spin‐state switching for memory applications

Nonvolatile, molecular multiferroic devices have now been demonstrated, but it is worth giving some consideration to the issue of whether such devices could be a competitive alternative for solid-state nonvolatile memory. For the Fe (II) spin crossover complex [Fe{H2B(pz)2}2(bipy)], where pz = tris(pyrazol-1-yl)-borohydride and bipy = 2,20-bipyridine, voltage-controlled isothermal changes in the electronic structure and spin state have been demonstrated and are accompanied by changes in conductance. Higher conductance is seen with [Fe{H2B(pz)2}2(bipy)] in the high spin state, while lower conductance occurs for the low spin state. Plausibly, there is the potential here for low-cost molecular solid-state memory because the essential molecular thin films are easily fabricated. However, successful device fabrication does not mean a device that has a practical value. Here, we discuss the progress and challenges yet facing the fabrication of molecular multiferroic devices, which could be considered competitive to silicon

Ketone bodies mediate alterations in brain energy metabolism and biomarkers of Alzheimer’s disease

Alzheimer’s disease (AD) is the most common form of dementia. AD is a progressive neurodegenerative disorder characterized by cognitive dysfunction, including learning and memory deficits, and behavioral changes. Neuropathology hallmarks of AD such as amyloid beta (Aβ) plaques and neurofibrillary tangles containing the neuron-specific protein tau is associated with changes in fluid biomarkers including Aβ, phosphorylated tau (p-tau)-181, p-tau 231, p-tau 217, glial fibrillary acidic protein (GFAP), and neurofilament light (NFL). Another pathological feature of AD is neural damage and hyperactivation of astrocytes, that can cause increased pro-inflammatory mediators and oxidative stress. In addition, reduced brain glucose metabolism and mitochondrial dysfunction appears up to 15 years before the onset of clinical AD symptoms. As glucose utilization is compromised in the brain of patients with AD, ketone bodies (KBs) may serve as an alternative source of energy. KBs are generated from the β-oxidation of fatty acids, which are enhanced following consumption of ketogenic diets with high fat, moderate protein, and low carbohydrate. KBs have been shown to cross the blood brain barrier to improve brain energy metabolism. This review comprehensively summarizes the current literature on how increasing KBs support brain energy metabolism. In addition, for the first time, this review discusses the effects of ketogenic diet on the putative AD biomarkers such as Aβ, tau (mainly p-tau 181), GFAP, and NFL, and discusses the role of KBs on neuroinflammation, oxidative stress, and mitochondrial metabolism

Outline of fungi and fungus-like taxa

This article provides an outline of the classification of the kingdom Fungi (including fossil fungi. i.e. dispersed spores, mycelia, sporophores, mycorrhizas). We treat 19 phyla of fungi. These are Aphelidiomycota, Ascomycota, Basidiobolomycota, Basidiomycota, Blastocladiomycota, Calcarisporiellomycota, Caulochytriomycota, Chytridiomycota, Entomophthoromycota, Entorrhizomycota, Glomeromycota, Kickxellomycota, Monoblepharomycota, Mortierellomycota, Mucoromycota, Neocallimastigomycota, Olpidiomycota, Rozellomycota and Zoopagomycota. The placement of all fungal genera is provided at the class-, order- and family-level. The described number of species per genus is also given. Notes are provided of taxa for which recent changes or disagreements have been presented. Fungus-like taxa that were traditionally treated as fungi are also incorporated in this outline (i.e. Eumycetozoa, Dictyosteliomycetes, Ceratiomyxomycetes and Myxomycetes). Four new taxa are introduced: Amblyosporida ord. nov. Neopereziida ord. nov. and Ovavesiculida ord. nov. in Rozellomycota, and Protosporangiaceae fam. nov. in Dictyosteliomycetes. Two different classifications (in outline section and in discussion) are provided for Glomeromycota and Leotiomycetes based on recent studies. The phylogenetic reconstruction of a four-gene dataset (18S and 28S rRNA, RPB1, RPB2) of 433 taxa is presented, including all currently described orders of fungi.Fil: Wijayawardene, N. N.. Qujing Normal University; ChinaFil: Hyde, K. D.. Mae Fah Luang University; TailandiaFil: Al-Ani, L. K. T.. University of Baghdad; IraqFil: Tedersoo, L.. University of Tartu; EstoniaFil: Haelewaters, D.. University of South Bohemia; República Checa. Purdue University; Estados Unidos. Universidad Autónoma de Chiriquí; PanamáFil: Becerra, Alejandra Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Schnittler, M.. Ernst Moritz Arndt University Greifswald; AlemaniaFil: Shchepin, O. N.. The Komarov Botanical Institute of the Russian Academy of Sciences; RusiaFil: Novozhilov, Y. K.. The Komarov Botanical Institute of the Russian Academy of Sciences; RusiaFil: Silva-Filho, A.G. S.. Universidade Federal do Rio Grande do Norte; BrasilFil: Gentekaki, E.. Mae Fah Luang University; TailandiaFil: Liu, P.. Jilin Agricultural University; ChinaFil: Cavender, J. C.. Ohio University; Estados UnidosFil: Kang, Y.. Guizhou Medical University; ChinaFil: Mohammad, S.. Iranian Research Organization for Science and Technology; IránFil: Zhang, L. F.. Qujing Normal University; ChinaFil: Xu, R. F.. Qujing Normal University; ChinaFil: Li, Y. M.. Qujing Normal University; ChinaFil: Dayarathne, M. C.. Guizhou University; ChinaFil: Ekanayaka, A. H.. Mae Fah Luang University; TailandiaFil: Wen, T. C.. Guizhou University; ChinaFil: Deng, C. Y.. Guizhou Academy of Science; ChinaFil: Pereira, O. L.. Universidade Federal de Viçosa; BrasilFil: Navathe, S.. Agharkar Research Institute; IndiaFil: Hawksworth, D. L.. The Natural History Museum; Reino UnidoFil: Fan, X. L.. Beijing Forestry University; ChinaFil: Dissanayake, L. S.. Guizhou University; ChinaFil: Kuhnert, E.. Leibniz University Hannover; AlemaniaFil: Grossart, H. P.. Leibnitz Institute of Freshwater Ecology and Inland Fisheries; AlemaniaFil: Thines, M.. Senckenberg Biodiversity and Climate Research Centre; Alemani

The Influence of Life History Milestones and Association Networks on Crop-Raiding Behavior in Male African Elephants

Factors that influence learning and the spread of behavior in wild animal populations are important for understanding species responses to changing environments and for species conservation. In populations of wildlife species that come into conflict with humans by raiding cultivated crops, simple models of exposure of individual animals to crops do not entirely explain the prevalence of crop raiding behavior. We investigated the influence of life history milestones using age and association patterns on the probability of being a crop raider among wild free ranging male African elephants; we focused on males because female elephants are not known to raid crops in our study population. We examined several features of an elephant association network; network density, community structure and association based on age similarity since they are known to influence the spread of behaviors in a population. We found that older males were more likely to be raiders than younger males, that males were more likely to be raiders when their closest associates were also raiders, and that males were more likely to be raiders when their second closest associates were raiders older than them. The male association network had sparse associations, a tendency for individuals similar in age and raiding status to associate, and a strong community structure. However, raiders were randomly distributed between communities. These features of the elephant association network may limit the spread of raiding behavior and likely determine the prevalence of raiding behavior in elephant populations. Our results suggest that social learning has a major influence on the acquisition of raiding behavior in younger males whereas life history factors are important drivers of raiding behavior in older males. Further, both life-history and network patterns may influence the acquisition and spread of complex behaviors in animal populations and provide insight on managing human-wildlife conflict

Effects of alirocumab on types of myocardial infarction: insights from the ODYSSEY OUTCOMES trial

Aims  The third Universal Definition of Myocardial Infarction (MI) Task Force classified MIs into five types: Type 1, spontaneous; Type 2, related to oxygen supply/demand imbalance; Type 3, fatal without ascertainment of cardiac biomarkers; Type 4, related to percutaneous coronary intervention; and Type 5, related to coronary artery bypass surgery. Low-density lipoprotein cholesterol (LDL-C) reduction with statins and proprotein convertase subtilisin–kexin Type 9 (PCSK9) inhibitors reduces risk of MI, but less is known about effects on types of MI. ODYSSEY OUTCOMES compared the PCSK9 inhibitor alirocumab with placebo in 18 924 patients with recent acute coronary syndrome (ACS) and elevated LDL-C (≥1.8 mmol/L) despite intensive statin therapy. In a pre-specified analysis, we assessed the effects of alirocumab on types of MI. Methods and results  Median follow-up was 2.8 years. Myocardial infarction types were prospectively adjudicated and classified. Of 1860 total MIs, 1223 (65.8%) were adjudicated as Type 1, 386 (20.8%) as Type 2, and 244 (13.1%) as Type 4. Few events were Type 3 (n = 2) or Type 5 (n = 5). Alirocumab reduced first MIs [hazard ratio (HR) 0.85, 95% confidence interval (CI) 0.77–0.95; P = 0.003], with reductions in both Type 1 (HR 0.87, 95% CI 0.77–0.99; P = 0.032) and Type 2 (0.77, 0.61–0.97; P = 0.025), but not Type 4 MI. Conclusion  After ACS, alirocumab added to intensive statin therapy favourably impacted on Type 1 and 2 MIs. The data indicate for the first time that a lipid-lowering therapy can attenuate the risk of Type 2 MI. Low-density lipoprotein cholesterol reduction below levels achievable with statins is an effective preventive strategy for both MI types.For complete list of authors see http://dx.doi.org/10.1093/eurheartj/ehz299</p