Allele specific expression analysis identifies regulatory variation associated with stress-related genes in the Mexican highland maize landrace Palomero Toluqueño.

BackgroundGene regulatory variation has been proposed to play an important role in the adaptation of plants to environmental stress. In the central highlands of Mexico, farmer selection has generated a unique group of maize landraces adapted to the challenges of the highland niche. In this study, gene expression in Mexican highland maize and a reference maize breeding line were compared to identify evidence of regulatory variation in stress-related genes. It was hypothesised that local adaptation in Mexican highland maize would be associated with a transcriptional signature observable even under benign conditions.MethodsAllele specific expression analysis was performed using the seedling-leaf transcriptome of an F1 individual generated from the cross between the highland adapted Mexican landrace Palomero Toluqueño and the reference line B73, grown under benign conditions. Results were compared with a published dataset describing the transcriptional response of B73 seedlings to cold, heat, salt and UV treatments.ResultsA total of 2,386 genes were identified to show allele specific expression. Of these, 277 showed an expression difference between Palomero Toluqueño and B73 alleles under benign conditions that anticipated the response of B73 cold, heat, salt and/or UV treatments, and, as such, were considered to display a prior stress response. Prior stress response candidates included genes associated with plant hormone signaling and a number of transcription factors. Construction of a gene co-expression network revealed further signaling and stress-related genes to be among the potential targets of the transcription factors candidates.DiscussionPrior activation of responses may represent the best strategy when stresses are severe but predictable. Expression differences observed here between Palomero Toluqueño and B73 alleles indicate the presence of cis-acting regulatory variation linked to stress-related genes in Palomero Toluqueño. Considered alongside gene annotation and population data, allele specific expression analysis of plants grown under benign conditions provides an attractive strategy to identify functional variation potentially linked to local adaptation

Vegetation Changes Following Biosolids Applications at an Old Boer Lovegrass Pasture in Northern Sonora, México

Short grass prairies (Bouteloua-Aristida) are the main vegetation type in northern Sonora, México, however, factors such as land fragmentation, overgrazing, severe droughts and lack of infrastructure in most ranches poor grazing management has caused land degradation. Boer lovegrass (Eragrostis curvula var. conferta) is an introduced species planted to increase productivity on deteriorated rangelands. Forage production with Boer lovegrass increases two to three fold as compared to native grasses after range seeding but productivity declines as stands become old. Biosolids have been recognized as a useful soil amendment and source of nitrogen, phosphorus, organic matter and other nutrients, which can enhance soil physical properties as well as plant yield (US Environmental Protection Agency 1999, Kinney et al. 2006). These organic compounds of human origins may play an important role in rangelands increasing soil fertility, however data do not exist to justify its use in México. This study was conducted to evaluate forage responses of old Boer lovegrass stands to biosolids applications

Regionalization of fish production in Mexico based on production value data in MXN pesos.

Objective: Generate a fishing regionalization activity in Mexico based on the economic criteria due to thevalue of fishery production.Design/Methodology/Approach: Socioeconomic data was taken as well as analyzed from the StatisticalYearbook of Aquaculture and Fisheries of fisheries in Mexico. Subsequently, the findings were organizedin a database with geospatial referent reclassified into nominal or ordinal qualitative statistical values. Thereclassification process was done through the use of a Geographic Information System, specifically withArcview 3.2 software, which allowed the generation of geostatistical analysis procedures through the use ofthe Kriging tool.Results: The results are displayed in a visually referenced database shown on a map constructed by datavectorization. The regionalization map of fisheries in Mexico is based on economic criteria of production valueclassified in four zones with different fishing priority.Limitations/implications: The lack of studies and social, economic and productive indexes of the Mexicanfishery is a limitation in the work of regionalization of fishing activity.Findings/conclusions: The efficiency of the use of Kriging as a multispecific analysis tool can be proven.The proposed regionalization is based solely on the monetary value, an item that has a greater weight inthe decisions made by the institutions, due to its importance in terms of Mexico’s Gross Domestic Product.These criteria together with the use of computational tools allowed the geolocalized regional categorizationof zones with similar characteristics classified into four fishing regions according to their degree of economicimportance: low, medium, high and main

2030 agenda and its considerations in the framework of artisanal fishing cooperatives in Mexico

Objective: Analyze the objectives proposed by the UN, linking them in a theoretical and practical way with the real situation of artisanal fishing cooperativism in Mexico, opposing the theoretical scope of the 2030 Agenda vs. the real praxis of artisanal fishing communities. Design/methodology/approach: Through the application of a Participatory Rapid Assessment Workshop, the points of the 2030 Agenda were discussed with three artisanal fishing communities in Mexico. The participants got to know in a theoretical way the objectives presented by the UN, they selected those that, in their opinion, are an important and punctual part of their fishing activity, to later analyze these objectives and compare them with their practical reality.   Results: Conclusions, proposals and points were obtained by the social subjects recognizing as a general argument that for the Mexican artisanal fishing cooperativism the objectives of the 2030 Agenda are possible as long as the action strategy promotes a cooperative culture with community values ??and social bond, respect for their environment and way of life, as well as the sustainability of the sea as an object of work. Limitations of the study/implications: The main implication was the enormous importance that exists in bringing the theoretical considerations of international organizations and decision makers to the social base where these proposals operate. , since these spaces create discussions that allow the necessary theoretical-practical analysis in the social sciences. Finding/conclusions: The neoliberal global economic system is the main disagreement of the 2030 Agenda. The Agenda encourages developed countries to support underdeveloped countries with knowledge, technology and investments to achieve sustainability, but it does not recognize local knowledge, uses and customs of developing countries as an effective alternative.Objective: To analyze the objectives proposed by the UN, linking them in a theoretical and practical way with the real condition of artisanal fishing cooperatives in Mexico, contrasting the theoretical scope of the 2030 Agenda vs. the real praxis of the communities of artisanal fishermen. Design / Methodology / Approach: Through the application of a Participatory Rapid Appraisal Workshop (PRAW) points of the Agenda 2030 were discussed with three artisanal fishing communities in Mexico. The participants learned in a theoretical way the objectives presented by the UN; selected those that in their opinion are important and punctual parts of their fishing activity; and then analyzed these objectives comparing them with their practical daily reality. Results: Conclusions and clarifications were obtained from the social subjects in which it was recognized as a general argument that for the Mexican artisanal fishing cooperatives framework the objectives of the 2030 Agenda are possible as long as the action strategy promotes a cooperative culture with community values and social bonds; respect for their environment and way of life; as well as the sustainability of the ocean as their means of work. Limitations / Implications of the study: the main implication noticed was the enormous importance that exists towards delivering theoretical considerations from international organizations and decision makers, to the social base who operates these proposals. These spaces create discussions that allow the theoretical analysis of practical needs which is mandatory in the social sciences. Findings / Conclusions: The neoliberal globalized economic system is the main disagreement for the 2030 Agenda. The 2030 Agenda encourages developed countries to support under-developed countries with knowledge, technology and investments to achieve sustainability. However, the Agenda does not recognize local knowledge, use forms and customs in those developing countries, as effective operational alternatives

Searching for Secluded Dark Matter via Direct Detection of Recoiling Nuclei as well as Low Energy Electrons

Motivated by recent cosmic ray experimental results there has been a proposition for a scenario where a secluded dark matter particle annihilates, primarily, into Standard Model leptons through a low mass mediator particle. We consider several varieties of this scenario depending on the type of mixing among gauge bosons and we study the implications in novel direct dark matter experiments for detecting low energy recoiling electrons. We find significant event rates and time modulation effects, especially in the case where the mediator is massless, that may be complementary to those from recoiling nuclei.Comment: 27 pages, references added, published versio

Severity Index for Suspected Arbovirus (SISA) : machine learning for accurate prediction of hospitalization in subjects suspected of arboviral infection

Funding: This study was supported, in part, by the Department of Defense Global Emerging Infection Surveillance (https://health.mil/Military-Health-Topics/Combat-Support/Armed-Forces-Health-Surveillance-Branch/Global-Emerging-Infections-Surveillance-and-Response) grant (P0220_13_OT) and the Department of Medicine of SUNY Upstate Medical University (http://www.upstate.edu/medicine/). D.F., M.H. and P.H. were supported by the Ben Kean Fellowship from the American Society for Tropical Medicine and Hygeine (https://www.astmh.org/awards-fellowships-medals/benjamin-h-keen-travel-fellowship-in-tropical-medi). S.J.R and A.M.S-I were supported by NSF DEB EEID 1518681, NSF DEB RAPID 1641145 (https://www.nsf.gov/), A.M.S-I was additionally supported by the Prometeo program of the National Secretary of Higher Education, Science, Technology, and Innovation of Ecuador (http://prometeo.educacionsuperior.gob.ec/).Background: Dengue, chikungunya, and Zika are arboviruses of major global health concern. Decisions regarding the clinical management of suspected arboviral infection are challenging in resource-limited settings, particularly when deciding on patient hospitalization. The objective of this study was to determine if hospitalization of individuals with suspected arboviral infections could be predicted using subject intake data. Methodology/Principal findings: Two prediction models were developed using data from a surveillance study in Machala, a city in southern coastal Ecuador with a high burden of arboviral infections. Data were obtained from subjects who presented at sentinel medical centers with suspected arboviral infection (November 2013 to September 2017). The first prediction model-called the Severity Index for Suspected Arbovirus (SISA)-used only demographic and symptom data. The second prediction model-called the Severity Index for Suspected Arbovirus with Laboratory (SISAL)-incorporated laboratory data. These models were selected by comparing the prediction ability of seven machine learning algorithms; the area under the receiver operating characteristic curve from the prediction of a test dataset was used to select the final algorithm for each model. After eliminating those with missing data, the SISA dataset had 534 subjects, and the SISAL dataset had 98 subjects. For SISA, the best prediction algorithm was the generalized boosting model, with an AUC of 0.91. For SISAL, the best prediction algorithm was the elastic net with an AUC of 0.94. A sensitivity analysis revealed that SISA and SISAL are not directly comparable to one another. Conclusions/Significance: Both SISA and SISAL were able to predict arbovirus hospitalization with a high degree of accuracy in our dataset. These algorithms will need to be tested and validated on new data from future patients. Machine learning is a powerful prediction tool and provides an excellent option for new management tools and clinical assessment of arboviral infection.Publisher PDFPeer reviewe

Lepton Number Violation from Colored States at the LHC

The possibility to search for lepton number violating signals at the Large Hadron Collider (LHC) in the colored seesaw scenario is investigated. In this context the fields that generate neutrino masses at the one-loop level are scalar and Majorana fermionic color-octets of SU(3). Due to the QCD strong interaction these states may be produced at the LHC with a favorable rate. We study the production mechanisms and decays relevant to search for lepton number violation signals in the channels with same-sign dileptons. In the simplest case when the two fermionic color-octets are degenerate in mass, one could use their decays to distinguish between the neutrino spectra. We find that for fermionic octets with mass up to about 1 TeV the number of same-sign dilepton events is larger than the standard model background indicating a promising signal for new physics.Comment: minor corrections, added reference