Brain bioelectrical activity changes in patients with poststroke depression and apathy

Objective: to study the specific features of brain bioelectrical activity in patents with poststroke apathy and depressive disorders.Patients and methods. The investigation enrolled 175 patients (84 men and 91 women) with new-onset cerebral stroke at different sites. A total of 107 (61%) patients of them were observed to have depressive disorders (n=41 (38%)) and apathy (n=66 (62%)) within a year after disease onset. A control group included 68 (39%) patients without poststroke affective disorders. The mean age of the study group patients was 66±10 years and that of the control patients was 68±11 years. The severity and magnitude of neurological deficit were evaluated using the U.S. National Institutes of Health Stroke Scale (NIHSS). The patients underwent electroencephalography (EEG), brain computed tomography and magnetic resonance imaging. The investigators used diagnostic and statistical manual of mental disorders (DSM-IV) criteria to diagnose depression and the Hamilton depression rating scale (HAM-D) and the mini-mental status examination (MMSE) to evaluate the mental status. The basic rhythmic power indices in the affected and unaffected hemispheres were calculated, as well as anteroposterior alpha rhythm distribution coefficient and interhemispheric asymmetry coefficient. Results and discussion. The computer EEG analysis was shown to identify the hallmark characteristics of brain bioelectric activity in patients with different types of affective disorders in the acute, early and late recovery periods of stroke. The patients with affective disorders were found to have brain bioelectrical activity changes predominantly in the rapid frequency sub-band on EEG, suggesting midbrain structural dysfunction. In the patients with poststroke depression, depressive disorder scale scores were related to the power of bioelectric activity in the slow and alpha frequency bands manly in the acute stroke period whereas those were correlated with the EEG beta band power in the delayed period

ARDD 2020: from aging mechanisms to interventions

Aging is emerging as a druggable target with growing interest from academia, industry and investors. New technologies such as artificial intelligence and advanced screening techniques, as well as a strong influence from the industry sector may lead to novel discoveries to treat age-related diseases. The present review summarizes presentations from the 7th Annual Aging Research and Drug Discovery (ARDD) meeting, held online on the 1st to 4th of September 2020. The meeting covered topics related to new methodologies to study aging, knowledge about basic mechanisms of longevity, latest interventional strategies to target the aging process as well as discussions about the impact of aging research on society and economy. More than 2000 participants and 65 speakers joined the meeting and we already look forward to an even larger meeting next year. Please mark your calendars for the 8th ARDD meeting that is scheduled for the 31st of August to 3rd of September, 2021, at Columbia University, USA

Aging and drug discovery

Multiple interventions in the aging process have been discovered to extend the healthspan of model organisms. Both industry and academia are therefore exploring possible transformative molecules that target aging and age‐associated diseases. In this overview, we summarize the presented talks and discussion points of the 5th Annual Aging and Drug Discovery Forum 2018 in Basel, Switzerland. Here academia and industry came together, to discuss the latest progress and issues in aging research. The meeting covered talks about the mechanistic cause of aging, how longevity signatures may be highly conserved, emerging biomarkers of aging, possible interventions in the aging process and the use of artificial intelligence for aging research and drug discovery. Importantly, a consensus is emerging both in industry and academia, that molecules able to intervene in the aging process may contain the potential to transform both societies and healthcareDB is supported by the German Research Foundation (Forschungsstipendium; BA 6276/1-1). CYE is supported by Swiss National Science Foundation [163898]. VNG is supported by grants from National Institutes of Health, and by the Russian Federation grant 14.W03.31.0012. DWL presented the results of research supported in part by research grants and funds from the National Institutes of Health, the Wisconsin Partnership Program, the Progeria Research Foundation, the American Federation for Aging Research, and the University of Wisconsin-Madison School of Medicine and Public Health and Department of Medicine, as well as the facilities and resources of the William S. Middleton Memorial Veterans Hospital. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This work does not represent the views of the Department of Veterans Affairs or the United States Government. MSL is supported by an LUMC research fellowship and a VIDI grant from the Netherlands scientific organization (NWO- ALW-016.161.320). A.M.-M. is supported by grants from the Instituto de Salud Carlos III co-funded by Instituto de Salud Carlos III and FEdeR (CP14/00105 and PI15/00134). SM was supported by the FWO-OP/Odysseus program (42/FA010100/32/6484). SJO's current work is funded by The Glenn Award from the Glenn Foundation for Medical Research. MR is supported by the Swiss National Science Foundation and the European Union Horizon 2020 program. MSK is supported by grants from the Danish Cancer Society (#R167-A11015_001), the Independent Research Fund Denmark (#7016- 00230B) and the Novo Nordisk Foundation (NNF17OC0027812).Peer reviewe