Bupropiooni augmentatsiooni toime estsitalopraamravi suhtes resistentsetel depressiivsetel patsientidel

Üha enam on andmeid, et bupropioon on üks efektiivsemaid valikuid augmentatsiooniks neil depressiivsetel patsientidel, kes serotoniini tagasihaarde inhibiitoritele reageerivad osaliselt või mitteküllaldaselt. Käesolevas uuringus jälgiti bupropiooni augmentatsiooni efektiivsust ja talutavust estsitalopraamravile mittereageerinud patsientidel. Seisundi kliinilist raskusastet ja paranemist hinnati kahenädalase intervalliga, kasutades selleks erinevaid skaalasid. Patsiendid hindasid sümptomeid ja võimalikke kõrvaltoimeid enesehinnangulistel skaaladel. Sarnaselt eelnevate uuringutega leiti, et bupropiooni augmentatsioon oli üldiselt hästi talutav ja aitas edukalt saada ravivastust enamikul serotoniini tagasihaarde inhibiitori monoteraapia suhtes resistentsetel patsientidel. Melanhoolset tüüpi depressioon oli seotud ebapiisava või osalise ravivastusega estsitalopraamile. Tulemused toetasid seisukohta, et bupropioon on esmavaliku antidepressant melanhoolse depressiooni ravis. Eesti Arst 2009; 88(2):82−9

Size- and charge-dependent non-specific uptake of PEGylated nanoparticles by macrophages

The assessment of macrophage response to nanoparticles is a central component in the evaluation of new nanoparticle designs for future in vivo application. This work investigates which feature, nanoparticle size or charge, is more predictive of non-specific uptake of nanoparticles by macrophages. This was investigated by synthesizing a library of polymer-coated iron oxide micelles, spanning a range of 30–100 nm in diameter and −23 mV to +9 mV, and measuring internalization into macrophages in vitro. Nanoparticle size and charge both contributed towards non-specific uptake, but within the ranges investigated, size appears to be a more dominant predictor of uptake. Based on these results, a protease-responsive nanoparticle was synthesized, displaying a matrix metalloproteinase-9 (MMP-9)-cleavable polymeric corona. These nanoparticles are able to respond to MMP-9 activity through the shedding of 10–20 nm of hydrodynamic diameter. This MMP-9-triggered decrease in nanoparticle size also led to up to a six-fold decrease in nanoparticle internalization by macrophages and is observable by T2-weighted magnetic resonance imaging. These findings guide the design of imaging or therapeutic nanoparticles for in vivo targeting of macrophage activity in pathologic states

International criteria for electrocardiographic interpretation in athletes: Consensus statement.

Sudden cardiac death (SCD) is the leading cause of mortality in athletes during sport. A variety of mostly hereditary, structural or electrical cardiac disorders are associated with SCD in young athletes, the majority of which can be identified or suggested by abnormalities on a resting 12-lead electrocardiogram (ECG). Whether used for diagnostic or screening purposes, physicians responsible for the cardiovascular care of athletes should be knowledgeable and competent in ECG interpretation in athletes. However, in most countries a shortage of physician expertise limits wider application of the ECG in the care of the athlete. A critical need exists for physician education in modern ECG interpretation that distinguishes normal physiological adaptations in athletes from distinctly abnormal findings suggestive of underlying pathology. Since the original 2010 European Society of Cardiology recommendations for ECG interpretation in athletes, ECG standards have evolved quickly, advanced by a growing body of scientific data and investigations that both examine proposed criteria sets and establish new evidence to guide refinements. On 26-27 February 2015, an international group of experts in sports cardiology, inherited cardiac disease, and sports medicine convened in Seattle, Washington (USA), to update contemporary standards for ECG interpretation in athletes. The objective of the meeting was to define and revise ECG interpretation standards based on new and emerging research and to develop a clear guide to the proper evaluation of ECG abnormalities in athletes. This statement represents an international consensus for ECG interpretation in athletes and provides expert opinion-based recommendations linking specific ECG abnormalities and the secondary evaluation for conditions associated with SCD

Data Augmentations in Deep Weight Spaces

Learning in weight spaces, where neural networks process the weights of other deep neural networks, has emerged as a promising research direction with applications in various fields, from analyzing and editing neural fields and implicit neural representations, to network pruning and quantization. Recent works designed architectures for effective learning in that space, which takes into account its unique, permutation-equivariant, structure. Unfortunately, so far these architectures suffer from severe overfitting and were shown to benefit from large datasets. This poses a significant challenge because generating data for this learning setup is laborious and time-consuming since each data sample is a full set of network weights that has to be trained. In this paper, we address this difficulty by investigating data augmentations for weight spaces, a set of techniques that enable generating new data examples on the fly without having to train additional input weight space elements. We first review several recently proposed data augmentation schemes %that were proposed recently and divide them into categories. We then introduce a novel augmentation scheme based on the Mixup method. We evaluate the performance of these techniques on existing benchmarks as well as new benchmarks we generate, which can be valuable for future studies.Comment: Accepted to NeurIPS 2023 Workshop on Symmetry and Geometry in Neural Representation

Dialysis Initiation in Patients With Chronic Coronary Disease and Advanced Chronic Kidney Disease in ISCHEMIA-CKD

BACKGROUND: In participants with concomitant chronic coronary disease and advanced chronic kidney disease (CKD), the effect of treatment strategies on the timing of dialysis initiation is not well characterized. METHODS AND RESULTS: In ISCHEMIA‐CKD (International Study of Comparative Health Effectiveness With Medical and Invasive Approaches–Chronic Kidney Disease), 777 participants with advanced CKD and moderate or severe ischemia were randomized to either an initial invasive or conservative management strategy. Herein, we compare the proportion of randomized participants with non–dialysis‐requiring CKD at baseline (n=362) who initiated dialysis and compare the time to dialysis initiation between invasive versus conservative management arms. Using multivariable Cox regression analysis, we also sought to identify the effect of invasive versus conservative chronic coronary disease management strategies on dialysis initiation. At a median follow‐up of 23 months (25th–75th interquartile range, 14–32 months), dialysis was initiated in 18.9% of participants (36/190) in the invasive strategy and 16.9% of participants (29/172) in the conservative strategy (P=0.22). The median time to dialysis initiation was 6.0 months (interquartile range, 3.0–16.0 months) in the invasive group and 18.2 months (interquartile range, 12.2–25.0 months) in the conservative group (P=0.004), with no difference in procedural acute kidney injury rates between the groups (7.8% versus 5.4%; P=0.26). Baseline clinical factors associated with earlier dialysis initiation were lower baseline estimated glomerular filtration rate (hazard ratio [HR] associated with 5‐unit decrease, 2.08 [95% CI, 1.72–2.56]; P<0.001), diabetes (HR, 2.30 [95% CI, 1.28–4.13]; P=0.005), hypertension (HR, 7.97 [95% CI, 1.09–58.21]; P=0.041), and Hispanic ethnicity (HR, 2.34 [95% CI, 1.22–4.47]; P=0.010). CONCLUSIONS: In participants with non–dialysis‐requiring CKD in ISCHEMIA‐CKD, randomization to an invasive chronic coronary disease management strategy (relative to a conservative chronic coronary disease management strategy) is associated with an accelerated time to initiation of maintenance dialysis for kidney failure

Time spent with cats is never wasted: Lessons learned from feline acromegalic cardiomyopathy, a naturally occurring animal model of the human disease

<div><p>Background</p><p>In humans, acromegaly due to a pituitary somatotrophic adenoma is a recognized cause of increased left ventricular (LV) mass. Acromegalic cardiomyopathy is incompletely understood, and represents a major cause of morbidity and mortality. We describe the clinical, echocardiographic and histopathologic features of naturally occurring feline acromegalic cardiomyopathy, an emerging disease among domestic cats.</p><p>Methods</p><p>Cats with confirmed hypersomatotropism (IGF-1>1000ng/ml and pituitary mass; n = 67) were prospectively recruited, as were two control groups: diabetics (IGF-1<800ng/ml; n = 24) and healthy cats without known endocrinopathy or cardiovascular disease (n = 16). Echocardiography was performed in all cases, including after hypersomatotropism treatment where applicable. Additionally, tissue samples from deceased cats with hypersomatotropism, hypertrophic cardiomyopathy and age-matched controls (n = 21 each) were collected and systematically histopathologically reviewed and compared.</p><p>Results</p><p>By echocardiography, cats with hypersomatotropism had a greater maximum LV wall thickness (6.5mm, 4.1–10.1mm) than diabetic (5.9mm, 4.2–9.1mm; Mann Whitney, p<0.001) or control cats (5.2mm, 4.1–6.5mm; Mann Whitney, p<0.001). Left atrial diameter was also greater in cats with hypersomatotropism (16.6mm, 13.0–29.5mm) than in diabetic (15.4mm, 11.2–20.3mm; Mann Whitney, p<0.001) and control cats (14.0mm, 12.6–17.4mm; Mann Whitney, p<0.001). After hypophysectomy and normalization of IGF-1 concentration (n = 20), echocardiographic changes proved mostly reversible. As in humans, histopathology of the feline acromegalic heart was dominated by myocyte hypertrophy with interstitial fibrosis and minimal myofiber disarray.</p><p>Conclusions</p><p>These results demonstrate cats could be considered a naturally occurring model of acromegalic cardiomyopathy, and as such help elucidate mechanisms driving cardiovascular remodeling in this disease.</p></div

Predicting risk for Alcohol Use Disorder using longitudinal data with multimodal biomarkers and family history: a machine learning study.

Predictive models have succeeded in distinguishing between individuals with Alcohol use Disorder (AUD) and controls. However, predictive models identifying who is prone to develop AUD and the biomarkers indicating a predisposition to AUD are still unclear. Our sample (n = 656) included offspring and non-offspring of European American (EA) and African American (AA) ancestry from the Collaborative Study of the Genetics of Alcoholism (COGA) who were recruited as early as age 12 and were unaffected at first assessment and reassessed years later as AUD (DSM-5) (n = 328) or unaffected (n = 328). Machine learning analysis was performed for 220 EEG measures, 149 alcohol-related single nucleotide polymorphisms (SNPs) from a recent large Genome-wide Association Study (GWAS) of alcohol use/misuse and two family history (mother DSM-5 AUD and father DSM-5 AUD) features using supervised, Linear Support Vector Machine (SVM) classifier to test which features assessed before developing AUD predict those who go on to develop AUD. Age, gender, and ancestry stratified analyses were performed. Results indicate significant and higher accuracy rates for the AA compared with the EA prediction models and a higher model accuracy trend among females compared with males for both ancestries. Combined EEG and SNP features model outperformed models based on only EEG features or only SNP features for both EA and AA samples. This multidimensional superiority was confirmed in a follow-up analysis in the AA age groups (12-15, 16-19, 20-30) and EA age group (16-19). In both ancestry samples, the youngest age group achieved higher accuracy score than the two other older age groups. Maternal AUD increased the model's accuracy in both ancestries' samples. Several discriminative EEG measures and SNPs features were identified, including lower posterior gamma, higher slow wave connectivity (delta, theta, alpha), higher frontal gamma ratio, higher beta correlation in the parietal area, and 5 SNPs: rs4780836, rs2605140, rs11690265, rs692854, and rs13380649. Results highlight the significance of sampling uniformity followed by stratified (e.g., ancestry, gender, developmental period) analysis, and wider selection of features, to generate better prediction scores allowing a more accurate estimation of AUD development

Filling Key Gaps in Population and Community Ecology

We propose research to fill key gaps in the areas of population and community ecology, based on a National Science Foundation workshop identifying funding priorities for the next 5–10 years. Our vision for the near future of ecology focuses on three core areas: predicting the strength and context-dependence of species interactions across multiple scales; identifying the importance of feedbacks from individual interactions to ecosystem dynamics; and linking pattern with process to understand species coexistence. We outline a combination of theory development and explicit, realistic tests of hypotheses needed to advance population and community ecology

Integrating plant- and animal-based perspectives for more effective restoration of biodiversity

Ecological restoration of modified and degraded landscapes is an important challenge for the 21st century, with potential for major gains in the recovery of biodiversity. However, there is a general lack of agreement between plant- and animal-based approaches to restoration, both in theory and practice. Here, we review these approaches, identify limitations from failing to effectively integrate their different perspectives, and suggest ways to improve outcomes for biodiversity recovery in agricultural landscapes. We highlight the need to strengthen collaboration between plant and animal ecologists, to overcome disciplinary and cultural differences, and to achieve a more unified approach to restoration ecology. Explicit consideration of key ecosystem functions, the need to plan at multiple spatial and temporal scales, and the importance of plant–animal interactions can provide a bridge between plant- and animal-based methods. A systematic approach to restoration planning is critical to achieving effective biodiversity outcomes while meeting long-term social and economic needs