P4408Quadruple imaging stress echocardiography as the new standard

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Stability of leaf yerba mate (Ilex paraguariensis) metabolite concentrations over the time from the prism of secondary Sexual dimorphism.

Abstract: The yerba mate leaf metabolic composition depends mainly on genetics, sex, plant and leaf age, light intensity, harvest time, climate, and fertilization. In yerba mate, the secondary sexual dimorphism (SSD), the leaf metabolic SSD association with the frequency of leaf harvests, and the stability of the metabolites in the two genders over the years is not known. It was hypothesized that (1) the SSD in the metabolite segregation would differ among the winter and summer growth pauses, (2) females would show lower metabolite concentrations, and (3) the metabolic concentrations would show stability over the years on the same plants, not obligatorily associated with the SSD stability expression. Variations in theobromine, caffeine, chlorogenic and caffeic acids were correlated to the increasing time since the previous harvest, especially in females. However, the frequency of the metabolic SSD were associated with the studied growth pauses, rejecting the first hypothesis. No regular gender superiority was expressed in the yerba mate leaf secondary metabolites, rejecting our second hypothesis, even though more cases of superior female metabolite accumulation were identified. The stability of the leaf protein was preserved over the four years, with no SSD cases observed. The leaf methylxanthines were time stable, while the decrease in the phenolic content occurred with tree aging, which was not associated with the SSD expression, partially proving our third hypothesis. The novelty was related to the time stability of the leaf metabolic SSD observed over the winter and summer growth pauses, and over the four consecutive years without a regular expression of the male- or female-biased concentrations in the studied metabolites. To demystify the random metabolic gender responses in yerba mate, gender-orientated experiments with a high number of tree repetitions must be conducted, including clonal plants grown in various environments, such as monoculture and agroforestry, or on plantations in different climates and altitudes

Elevated plasma levels of cardiac troponin-I predict left ventricular systolic dysfunction in patients with myotonic dystrophy type 1:A multicentre cohort follow-up study

Objective: High sensitivity plasma cardiac troponin-I (cTnI) is emerging as a strong predictor of cardiac events in a variety of settings. We have explored its utility in patients with myotonic dystrophy type 1 (DM1). Methods: 117 patients with DM1 were recruited from routine outpatient clinics across three health boards. A single measurement of cTnI was made using the ARCHITECT STAT Troponin I assay. Demographic, ECG, echocardiographic and other clinical data were obtained from electronic medical records. Follow up was for a mean of 23 months. Results: Fifty five females and 62 males (mean age 47.7 years) were included. Complete data were available for ECG in 107, echocardiography in 53. Muscle Impairment Rating Scale score was recorded for all patients. A highly significant excess (p = 0.0007) of DM1 patients presented with cTnI levels greater than the 99th centile of the range usually observed in the general population (9 patients; 7.6%). Three patients with elevated troponin were found to have left ventricular systolic dysfunction (LVSD), compared with four of those with normal range cTnI (33.3% versus 3.7%; p = 0.001). Sixty two patients had a cTnI level < 5ng/L, of whom only one had documented evidence of LVSD. Elevated cTnI was not predictive of severe conduction abnormalities on ECG, or presence of a cardiac device, nor did cTnI level correlate with muscle strength expressed by Muscle Impairment Rating Scale score. Conclusions: Plasma cTnI is highly elevated in some ambulatory patients with DM1 and shows promise as a tool to aid cardiac risk stratification, possibly by detecting myocardial involvement. Further studies with larger patient numbers are warranted to assess its utility in this setting

The physiological responses of cacao to the environment and the implications for climate change resilience. A review

Cacao (Theobroma cacao L.) is a tropical perennial crop which is of great economic importance to the confectionary industry and to the economies of many countries of the humid tropics where it is grown. Some recent studies have suggested climate change could severely impact cacao production in West Africa. It is essential to incorporate our understanding of the physiology and genetic variation within cacao germplasm when discussing the implications of climate change on cacao productivity and developing strategies for climate resilience in cacao production. Here we review the current research on the physiological responses of cacao to various climate factors. Our main findings are 1) water limitation causes significant yield reduction in cacao but genotypic variation in sensitivity is evident, 2) in the field cacao experiences higher temperatures than is often reported in the literature, 3) the complexity of the cacao/ shade tree interaction can lead to contradictory results, 4) elevated CO2 may alleviate some negative effects of climate change 5) implementation of mitigation strategies can help reduce environmental stress, 6) significant gaps in the research need addressing to accelerate the development of climate resilience. Harnessing the significant genetic variation apparent within cacao germplasm is essential to develop modern varieties capable of high yields in non-optimal conditions. Mitigation strategies will also be essential but to use shading to best effect shade tree selection is crucial to avoid resource competition. Cacao is often described as being sensitive to climate change but genetic variation, adaptive responses, appropriate mitigation strategies and interactive climate effects should all be considered when predicting the future of cacao production. Incorporating these physiological responses to various environmental conditions and developing a deeper understanding of the processes underlying these responses will help to accelerate the development of a more resource use efficient tree ensuring sustainable production into the future

Diagnosis and management of glutaric aciduria type I – revised recommendations

Glutaric aciduria type I (synonym, glutaric acidemia type I) is a rare organic aciduria. Untreated patients characteristically develop dystonia during infancy resulting in a high morbidity and mortality. The neuropathological correlate is striatal injury which results from encephalopathic crises precipitated by infectious diseases, immunizations and surgery during a finite period of brain development, or develops insidiously without clinically apparent crises. Glutaric aciduria type I is caused by inherited deficiency of glutaryl-CoA dehydrogenase which is involved in the catabolic pathways of L-lysine, L-hydroxylysine and L-tryptophan. This defect gives rise to elevated glutaric acid, 3-hydroxyglutaric acid, glutaconic acid, and glutarylcarnitine which can be detected by gas chromatography/mass spectrometry (organic acids) or tandem mass spectrometry (acylcarnitines). Glutaric aciduria type I is included in the panel of diseases that are identified by expanded newborn screening in some countries. It has been shown that in the majority of neonatally diagnosed patients striatal injury can be prevented by combined metabolic treatment. Metabolic treatment that includes a low lysine diet, carnitine supplementation and intensified emergency treatment during acute episodes of intercurrent illness should be introduced and monitored by an experienced interdisciplinary team. However, initiation of treatment after the onset of symptoms is generally not effective in preventing permanent damage. Secondary dystonia is often difficult to treat, and the efficacy of available drugs cannot be predicted precisely in individual patients. The major aim of this revision is to re-evaluate the previous diagnostic and therapeutic recommendations for patients with this disease and incorporate new research findings into the guideline

Synthesizing controversial sentences for testing the brain-predictivity of language models

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2021Cataloged from the official PDF of thesis.Includes bibliographical references (pages 55-58).Recent research has seen the rise of powerful neural-network language models that are sufficiently computationally precise and neurally plausible as to serve as a jumping-off base for our understanding of language processing in the brain. Because these models have been developed for optimizing a similar objective (word prediction), their brain predictions are often correlated, even though the models differ along several architectural and conceptual features, yielding a major challenge for testing which model features are most relevant for predicting language processing in the brain. Here, we address this challenge by synthesizing new sentence stimuli that maximally expose the disagreement between the predictions of a set of language models ('controversial stimuli'), which would not naturally occur in large language corpora . To do so, we develop a platform for systematizing this sentence synthesis process, providing a way to test different model-based hypotheses easily and efficiently. An initial exploration with this platform has begun to give us some intuition for how choosing from different pools of candidate words affect the kinds of sentences produced, and what kinds of changes tend to produce controversial sentences. For example, we show that the disagreement score, or the maximum amount of disagreement between models for a sentence, converges. This approach will eventually allow us to determine which models perform in the most human-like way and are most successful in predicting language processing in the brain, thus hopefully leading to insights on the mechanisms of human language understanding.by Lara I. Rakocevic.M. Eng.M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienc