The impacts of increased heat stress events on wheat yield under climate change in China

China is the largest wheat producing country in the world. Wheat is one of the two major staple cereals consumed in the country and about 60% of Chinese population eats the grain daily. To safeguard the production of this important crop, about 85% of wheat areas in the country are under irrigation or high rainfall conditions. However, wheat production in the future will be challenged by the increasing occurrence and magnitude of adverse and extreme weather events. In this paper, we present an analysis that combines outputs from a wide range of General Circulation Models (GCMs) with observational data to produce more detailed projections of local climate suitable for assessing the impact of increasing heat stress events on wheat yield. We run the assessment at 36 representative sites in China using the crop growth model CSM-CropSim Wheat of DSSAT 4.5. The simulations based on historical data show that this model is suitable for quantifying yield damages caused by heat stress. In comparison with the observations of baseline 1996-2005, our simulations for the future indicate that by 2100, the projected increases in heat stress would lead to an ensemble-mean yield reduction of –7.1% (with a probability of 80%) and –17.5% (with a probability of 96%) for winter wheat and spring wheat, respectively, under the irrigated condition. Although such losses can be fully compensated by CO2 fertilization effect as parameterized in DSSAT 4.5, a great caution is needed in interpreting this fertilization effect because existing crop dynamic models are unable to incorporate the effect of CO2 acclimation (the growth enhancing effect decreases over time) and other offsetting forces

Non-invasive localization of atrial ectopic beats by using simulated body surface P-wave integral maps

Non-invasive localization of continuous atrial ectopic beats remains a cornerstone for the treatment of atrial arrhythmias. The lack of accurate tools to guide electrophysiologists leads to an increase in the recurrence rate of ablation procedures. Existing approaches are based on the analysis of the P-waves main characteristics and the forward body surface potential maps (BSPMs) or on the inverse estimation of the electric activity of the heart from those BSPMs. These methods have not provided an efficient and systematic tool to localize ectopic triggers. In this work, we propose the use of machine learning techniques to spatially cluster and classify ectopic atrial foci into clearly differentiated atrial regions by using the body surface P-wave integral map (BSPiM) as a biomarker. Our simulated results show that ectopic foci with similar BSPiM naturally cluster into differentiated non-intersected atrial regions and that new patterns could be correctly classified with an accuracy of 97% when considering 2 clusters and 96% for 4 clusters. Our results also suggest that an increase in the number of clusters is feasible at the cost of decreasing accuracy.This work was partially supported by The "Programa Prometeu" from Conselleria d'Educacio Formacio I Ocupacio, Generalitat Valenciana (www.edu.gva.es/fio/index_es.asp) Award Number: PROMETEU/2016/088 to JS; The "Plan Estatal de Investigacion Cientifica y Tecnica y de Innovacion 2013-2016" from the Ministerio de Economia, Industria y Competitividad of Spain, Agencia Estatal de Investigacion (www.mineco.gob.es) and the European Commission (European Regional Development Funds - ERDF -FEDER) (ec.europa.eu/regional_policy/es/funding/erdf/) Award Number: DPI2016-75799-R to JS and The "Programa Estatal de Investigacion, Desarrollo e Innovacion Orientado a los Retos de la Sociedad" from the Ministerio de Economia y Competitividad of Spain, Agencia Estatal de Investigacion (www.mineco.gob.es) and the European Commission (European Regional Development Funds - ERDF -FEDER) (ec.europa.eu/regional_policy/es/funding/erdf/) Award Number: TIN2014-59932-JIN to AFA and RS. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ferrer Albero, A.; Godoy, EJ.; Lozano, M.; Martínez Mateu, L.; Alonso Atienza, F.; Saiz Rodríguez, FJ.; Sebastián Aguilar, R. (2017). Non-invasive localization of atrial ectopic beats by using simulated body surface P-wave integral maps. PLoS ONE. 12(7):1-23. https://doi.org/10.1371/journal.pone.0181263S12312

Contextualising adverse events of special interest to characterise the baseline incidence rates in 24 million patients with COVID-19 across 26 databases: a multinational retrospective cohort study

BACKGROUND: Adverse events of special interest (AESIs) were pre-specified to be monitored for the COVID-19 vaccines. Some AESIs are not only associated with the vaccines, but with COVID-19. Our aim was to characterise the incidence rates of AESIs following SARS-CoV-2 infection in patients and compare these to historical rates in the general population. METHODS: A multi-national cohort study with data from primary care, electronic health records, and insurance claims mapped to a common data model. This study's evidence was collected between Jan 1, 2017 and the conclusion of each database (which ranged from Jul 2020 to May 2022). The 16 pre-specified prevalent AESIs were: acute myocardial infarction, anaphylaxis, appendicitis, Bell's palsy, deep vein thrombosis, disseminated intravascular coagulation, encephalomyelitis, Guillain- Barré syndrome, haemorrhagic stroke, non-haemorrhagic stroke, immune thrombocytopenia, myocarditis/pericarditis, narcolepsy, pulmonary embolism, transverse myelitis, and thrombosis with thrombocytopenia. Age-sex standardised incidence rate ratios (SIR) were estimated to compare post-COVID-19 to pre-pandemic rates in each of the databases. FINDINGS: Substantial heterogeneity by age was seen for AESI rates, with some clearly increasing with age but others following the opposite trend. Similarly, differences were also observed across databases for same health outcome and age-sex strata. All studied AESIs appeared consistently more common in the post-COVID-19 compared to the historical cohorts, with related meta-analytic SIRs ranging from 1.32 (1.05 to 1.66) for narcolepsy to 11.70 (10.10 to 13.70) for pulmonary embolism. INTERPRETATION: Our findings suggest all AESIs are more common after COVID-19 than in the general population. Thromboembolic events were particularly common, and over 10-fold more so. More research is needed to contextualise post-COVID-19 complications in the longer term. FUNDING: None

A High Density SNP Array for the Domestic Horse and Extant Perissodactyla: Utility for Association Mapping, Genetic Diversity, and Phylogeny Studies

An equine SNP genotyping array was developed and evaluated on a panel of samples representing 14 domestic horse breeds and 18 evolutionarily related species. More than 54,000 polymorphic SNPs provided an average inter-SNP spacing of ∼43 kb. The mean minor allele frequency across domestic horse breeds was 0.23, and the number of polymorphic SNPs within breeds ranged from 43,287 to 52,085. Genome-wide linkage disequilibrium (LD) in most breeds declined rapidly over the first 50–100 kb and reached background levels within 1–2 Mb. The extent of LD and the level of inbreeding were highest in the Thoroughbred and lowest in the Mongolian and Quarter Horse. Multidimensional scaling (MDS) analyses demonstrated the tight grouping of individuals within most breeds, close proximity of related breeds, and less tight grouping in admixed breeds. The close relationship between the Przewalski's Horse and the domestic horse was demonstrated by pair-wise genetic distance and MDS. Genotyping of other Perissodactyla (zebras, asses, tapirs, and rhinoceros) was variably successful, with call rates and the number of polymorphic loci varying across taxa. Parsimony analysis placed the modern horse as sister taxa to Equus przewalski. The utility of the SNP array in genome-wide association was confirmed by mapping the known recessive chestnut coat color locus (MC1R) and defining a conserved haplotype of ∼750 kb across all breeds. These results demonstrate the high quality of this SNP genotyping resource, its usefulness in diverse genome analyses of the horse, and potential use in related species

A comparison of low-dose risperidone to paroxetine in the treatment of panic attacks: a randomized, single-blind study

<p>Abstract</p> <p>Background</p> <p>Because a large proportion of patients with panic attacks receiving approved pharmacotherapy do not respond or respond poorly to medication, it is important to identify additional therapeutic strategies for the management of panic symptoms. This article describes a randomized, rater-blind study comparing low-dose risperidone to standard-of-care paroxetine for the treatment of panic attacks.</p> <p>Methods</p> <p>Fifty six subjects with a history of panic attacks were randomized to receive either risperidone or paroxetine. The subjects were then followed for eight weeks. Outcome measures included the Panic Disorder Severity Scale (PDSS), the Hamilton Anxiety Scale (Ham-A), the Hamilton Depression Rating Scale (Ham-D), the Sheehan Panic Anxiety Scale-Patient (SPAS-P), and the Clinical Global Impression scale (CGI).</p> <p>Results</p> <p>All subjects demonstrated a reduction in both the frequency and severity of panic attacks regardless of treatment received. Statistically significant improvements in rating scale scores for both groups were identified for the PDSS, the Ham-A, the Ham-D, and the CGI. There was no difference between treatment groups in the improvement in scores on the measures PDSS, Ham-A, Ham-D, and CGI. Post hoc tests suggest that subjects receiving risperidone may have a quicker clinical response than subjects receiving paroxetine.</p> <p>Conclusion</p> <p>We can identify no difference in the efficacy of paroxetine and low-dose risperidone in the treatment of panic attacks. Low-dose risperidone appears to be tolerated equally well as paroxetine. Low-dose risperidone may be an effective treatment for anxiety disorders in which panic attacks are a significant component.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov Identifier: NCT100457106</p

Effects of American ginseng (Panax quinquefolius) on neurocognitive function: an acute, randomised, double-blind, placebo-controlled, crossover study

Over the last decade, Asian ginseng (Panax ginseng) has been shown to improve aspects of human cognitive function. American ginseng (Panax quinquefolius) has a distinct ginsenoside profile from P. ginseng, promising cognitive enhancing properties in preclinical studies and benefits processes linked to human cognition. The availability of a highly standardised extract of P. quinquefolius (Cereboost (TM)) led us to evaluate its neurocognitive properties in humans for the first time. This randomised, double-blind, placebo-controlled, crossover trial (N = 32, healthy young adults) assessed the acute mood, neurocognitive and glycaemic effects of three doses (100, 200 400 mg) of Cereboost (TM) (P. quinquefolius standardised to 10.65% ginsenosides). Participants' mood, cognitive function and blood glucose were measured 1, 3 and 6 h following administration. There was a significant improvement of working memory (WM) performance associated with P. quinquefolius. Corsi block performance was improved by all doses at all testing times. There were differential effects of all doses on other WM tasks which were maintained across the testing day. Choice reaction time accuracy and 'calmness' were significantly improved by 100 mg. There were no changes in blood glucose levels. This preliminary study has identified robust working memory enhancement following administration of American ginseng. These effects are distinct from those of Asian ginseng and suggest that psychopharmacological properties depend critically on ginsenoside profiles. These results have ramifications for the psychopharmacology of herbal extracts and merit further study using different dosing regimens and in populations where cognition is fragile

Better Few than Hungry: Flexible Feeding Ecology of Collared Lemurs Eulemur collaris in Littoral Forest Fragments

Frugivorous primates are known to encounter many problems to cope with habitat degradation, due to the fluctuating spatial and temporal distribution of their food resources. Since lemur communities evolved strategies to deal with periods of food scarcity, these primates are expected to be naturally adapted to fluctuating ecological conditions and to tolerate a certain degree of habitat changes. However, behavioral and ecological strategies adopted by frugivorous lemurs to survive in secondary habitats have been little investigated. Here, we compared the behavioral ecology of collared lemurs (Eulemur collaris) in a degraded fragment of littoral forest of south-east Madagascar, Mandena, with that of their conspecifics in a more intact habitat, Sainte Luce.Lemur groups in Mandena and in Sainte Luce were censused in 2004/2007 and in 2000, respectively. Data were collected via instantaneous sampling on five lemur groups totaling 1,698 observation hours. The Shannon index was used to determine dietary diversity and nutritional analyses were conducted to assess food quality. All feeding trees were identified and measured, and ranging areas determined via the minimum convex polygon. In the degraded area lemurs were able to modify several aspects of their feeding strategies by decreasing group size and by increasing feeding time, ranging areas, and number of feeding trees. The above strategies were apparently able to counteract a clear reduction in both food quality and size of feeding trees.Our findings indicate that collared lemurs in littoral forest fragments modified their behavior to cope with the pressures of fluctuating resource availability. The observed flexibility is likely to be an adaptation to Malagasy rainforests, which are known to undergo periods of fruit scarcity and low productivity. These results should be carefully considered when relocating lemurs or when selecting suitable areas for their conservation

Understanding the Warburg effect and the prognostic value of stromal caveolin-1 as a marker of a lethal tumor microenvironment

Cancer cells show a broad spectrum of bioenergetic states, with some cells using aerobic glycolysis while others rely on oxidative phosphorylation as their main source of energy. In addition, there is mounting evidence that metabolic coupling occurs in aggressive tumors, between epithelial cancer cells and the stromal compartment, and between well-oxygenated and hypoxic compartments. We recently showed that oxidative stress in the tumor stroma, due to aerobic glycolysis and mitochondrial dysfunction, is important for cancer cell mutagenesis and tumor progression. More specifically , increased autophagy/mitophagy in the tumor stroma drives a form of parasitic epithelial-stromal metabolic coupling. These findings explain why it is effective to treat tumors with either inducers or inhibitors of autophagy, as both would disrupt this energetic coupling. We also discuss evidence that glutamine addiction in cancer cells produces ammonia via oxidative mitochondrial metabolism. Ammonia production in cancer cells, in turn, could then help maintain autophagy in the tumor stromal compartment. In this vicious cycle, the initial glutamine provided to cancer cells would be produced by autophagy in the tumor stroma. Thus, we believe that parasitic epithelial-stromal metabolic coupling has important implications for cancer diagnosis and therapy, for example, in designing novel metabolic imaging techniques and establishing new targeted therapies. In direct support of this notion, we identified a loss of stromal caveolin-1 as a marker of oxidative stress, hypoxia, and autophagy in the tumor microenvironment, explaining its powerful predictive value. Loss of stromal caveolin-1 in breast cancers is associated with early tumor recurrence, metastasis, and drug resistance, leading to poor clinical outcome