Genetic resources and product diversification in a transitioning coffee agroecosystem in Mecayapan, Veracruz, Mexico

Objective: To analyze a coffee agroecosystem in agroecological transition, as an alternative for the use and conservation of resources. For this, an agroecological design was carried out associated with three legumes and one cucurbit in coffee cultivation. Design/methodology/approach: Collection and identification of genetic resources present in the agroecosystem, agroecological design associated with three legumes and one cucurbit in coffee cultivation; zig-zag soil sampling for physical, chemical, and biological analyses, data analysis using JASP version 0.16.2. Results: Identification of 42 species of weeds with various uses, as well as the criteria for association of species according to use, the soil analyzes showed that there is a significant connection between micronutrients and nitrogen-fixing bacteria, the variable Boron has influence in the development of nitrogen-fixing bacteria. Limitations on study/implications: The results are applicable to the agroecological model in transition that is presented. Findings/conclusions: Coffee agroecosystems in agroecological transition are slow processes, but they contribute to improving soil conditions. They allow the reappearance of weed species with some use. There is a significant correlation between Boron and the development of nitrogen-fixing bacteria, likewise the physical properties have a direct relationship with their development. Keywords: agroecology, transition, agroecosystemObjective: To analyze a coffee agroecosystem undergoing an agroecological transition —considered as an alternative for the efficient use and the conservation of resources— through an agroecological association design with three legumes and one cucurbit in coffee cultivation. Design/Methodology/Approach: Collection and identification of genetic resources found in the agroecosystem; agroecological association design with three legumes and one cucurbit in a coffee crop; zig-zag soil sampling for physical, chemical, and biological analyses; data analysis using JASP software version 0.16.2. Results: We identified 42 weed species with various uses within the coffee agroecosystem, as well as the criteria for the association of species according to use. The soil analysis showed a significant correlation between micronutrients and nitrogen-fixing bacteria. The boron variable also influences the growth of such bacteria. Study Limitations/Implications: The results apply to the agroecological model in transition presented. Findings/Conclusions: Agroecological transition in coffee agroecosystems is slow but contributes to improving soil conditions. It also allows for the reappearance of usable weed species. There is a significant correlation between boron and the development of nitrogen-fixing bacteria. Likewise, the physical properties of soil have a direct impact on the growth of such bacteri

Tau aggregation

Here we revisit tau protein aggregation at primary, secondary, tertiary and quaternary structures. In addition, the presence of non-aggregated tau protein, which has been recently discovered, is also commented o

Inhaled Methoxyflurane Provides Greater Analgesia and Faster Onset of Action Versus Standard Analgesia in Patients With Trauma Pain: InMEDIATE: A Randomized Controlled Trial in Emergency Departments

Study objective: The objective of the InMEDIATE study was to evaluate the change in intensity of traumatic pain over the first 20 min in adult patients treated with methoxyflurane versus standard analgesic treatment in Spain. This the first randomized, active-controlled, multicenter trial of methoxyflurane in the emergency setting in Europe. Methods: This was a randomized, controlled study that enrolled adult patients with acute moderate to severe (score >= 4 on the 11-point Numeric Rating Scale) trauma-associated pain in 14 Spanish emergency departments. Patients were randomized 1:1 to methoxyflurane (up to 2x3 mL) or standard analgesic treatment. Coprimary endpoints were the change from baseline in Numeric Rating Scale pain intensity score during the first 20 minutes of treatment and time to first pain relief. Results: Three hundred five patients were randomized (methoxyflurane 156; standard analgesic treatment 149). Most patients in the standard analgesic treatment group (70%) received intravenous first-step analgesics and 9.4% of patients were treated with opioids. Mean decrease from baseline in Numeric Rating Scale pain intensity score was greater for methoxyflurane than standard analgesic treatment at all points, with a significant treatment difference overall up to 20 minutes (repeated-measures model 2.47 versus 1.39; treatment difference 1.00; 95% confidence interval 0.84 to 1.32). Median time to first pain relief was significantly shorter for methoxyflurane than standard analgesic treatment (3 versus 10 minutes). Methoxyflurane achieved better patient and clinician ratings for pain control and comfort of treatment than standard analgesic treatment and exceeded patient and clinician expectations of treatment in, respectively, 77% and 72% of cases compared with 38% and 19% for standard analgesic treatment. Conclusion: These results support consideration of methoxyflurane as a nonnarcotic, easy-to-administer, rapid-acting, first-line alternative to currently available analgesic treatments for trauma pain

Mutational screening of newly diagnosed multiple myeloma patients by deep targeted sequencing

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Predictors of Global Non-Motor Symptoms Burden Progression in Parkinson’s Disease. Results from the COPPADIS Cohort at 2-Year Follow-Up

Background and Objective: Non-motor symptoms (NMS) progress in different ways between Parkinson's disease (PD) patients. The aim of the present study was to (1) analyze the change in global NMS burden in a PD cohort after a 2-year follow-up, (2) to compare the changes with a control group, and (3) to identify predictors of global NMS burden progression in the PD group. Material and Methods: PD patients and controls, recruited from 35 centers of Spain from the COPPADIS cohort from January 2016 to November 2017, were followed-up with after 2 years. The Non-Motor Symptoms Scale (NMSS) was administered at baseline (V0) and at 24 months ± 1 month (V2). Linear regression models were used for determining predictive factors of global NMS burden progression (NMSS total score change from V0 to V2 as dependent variable). Results: After the 2-year follow-up, the mean NMS burden (NMSS total score) significantly increased in PD patients by 18.8% (from 45.08 ± 37.62 to 53.55 ± 42.28; p < 0.0001; N = 501; 60.2% males, mean age 62.59 ± 8.91) compared to no change observed in controls (from 14.74 ± 18.72 to 14.65 ± 21.82; p = 0.428; N = 122; 49.5% males, mean age 60.99 ± 8.32) (p < 0.0001). NMSS total score at baseline (β = -0.52), change from V0 to V2 in PDSS (Parkinson's Disease Sleep Scale) (β = -0.34), and change from V0 to V2 in NPI (Neuropsychiatric Inventory) (β = 0.25) provided the highest contributions to the model (adjusted R-squared 0.41; Durbin-Watson test = 1.865). Conclusions: Global NMS burden demonstrates short-term progression in PD patients but not in controls and identifies worsening sleep problems and neuropsychiatric symptoms as significant independent predictors of this NMS progression

Biomarkers Associated with Regorafenib First-Line Treatment Benefits in Metastatic Colorectal Cancer Patients: REFRAME Molecular Study

© 2021 by the authors.First-line treatment with regorafenib in frail metastatic colorectal cancer (mCRC) patients has shown some benefit. To accurately identify such patients before treatment, we studied blood biomarkers and primary tumor molecules. We unveiled serum microRNAs (miRNAs), single-nucleotide polymorphisms (SNPs) in angiogenic-related genes, and Notch 1 expression as biomarkers associated with response or toxicity. MicroRNA array profiling and genotyping of selected SNPs were performed in the blood of fragile mCRC patients treated with regorafenib. Notch 1 and CRC-associated miRNA expression was also analyzed in tumors. High levels of miR-185-5p in serum, rs7993418 in the vascular endothelial growth factor receptor 1 (VEGFR1) gene, and Notch 1 expression in biopsies were associated with a favorable response to treatment. Serum levels of miR-126-3p and miR-152-3p and tumor expression of miR-92a-1-5p were associated with treatment toxicity, particularly interesting in patients exhibiting comorbidities, and high levels of miR-362-3p were associated with asthenia. Additionally, several miRNAs were associated with the presence of metastasis, local recurrence, and peritoneal metastasis. Besides, miRNAs determined in primary tumors were associated with tumor-node-metastasis (TNM) staging. The rs2305948 and rs699947 SNPs in VEGFR2 and VEGFA, respectively, were markers of poor prognosis correlating with locoregional relapse, a higher N stage, and metastatic shedding. In conclusion, VEGF and VEGFR SNPs, miRNAs, and Notch 1 levels are potential useful biomarkers for the management of advanced CRC under regorafenib treatment.Financial support for this research was provided by Bayer Hispania, which had no role in the design of the study; the collection, analysis, and interpretation of data; and the writing of the manuscript.Peer reviewe

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort

Background Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster.Methods Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3.Results Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3.Conclusions During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis

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Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Simple reparameterization to improve convergence in linear mixed models

Slow convergence and mixing are one of the main problems of Markov chain Monte Carlo (McMC) algorithms applied to mixed models in animal breeding. Poor convergence is to a large extent caused by high posterior correlation between variance components and solutions for the levels of associated effects. A simple reparameterization of the conventional model for variance component estimation is presented which improves McMC sampling and provides the same posterior distributions as the conventional model. Reparameterization is based on the rescaling of hierarchical (random) effects in a model, which alleviates posterior correlation. The developed model is compared against the conventional model using several simulated data sets. Results show that presented reparameterization has better behaviour of associated sampling methods and is several times more efficient for the low values of heritability.Počasna konvergenca je eden največjih problemov uporabe metode Monte Carlo z Markovimi verigami (McMC) za mešane modele na področju genetike in selekcije domačih živali. Slaba konvergenca je v veliki meri posledica visoke posteriorne korelacije med komponentami variance in rešitvami za ravni pripadajočih vplivov. Predstavljamo enostavno reparametrizacijo običajnega modela, ki izboljša lastnosti metode McMC in daje enake posteriorne porazdelitve parametrov modela kot standardni pristop. Reparametrizacija temelji na standardizaciji hierarhičnih (naključnih) vplivov v modelu, kar posledično spremeni posteriorne korelacije med parametri. Oba pristopa smo primerjali na večjem setu simuliranih podatkov. Rezultati kažejo, da reparametrizacija vodi do bolj učinkovitih metod McMC vzorčenja in je nekajkrat bolj učinkovita za analizo lastnosti z nizko heritabilitet