The effects of general anesthetics on mitochondrial structure and function in the developing brain

The use of general anesthetics in modern clinical practice is commonly regarded as safe for healthy individuals, but exposures at the extreme ends of the age spectrum have been linked to chronic cognitive impairments and persistent functional and structural alterations to the nervous system. The accumulation of evidence at both the epidemiological and experimental level prompted the addition of a warning label to inhaled anesthetics by the Food and Drug Administration cautioning their use in children under 3  years of age. Though the mechanism by which anesthetics may induce these detrimental changes remains to be fully elucidated, increasing evidence implicates mitochondria as a potential primary target of anesthetic damage, meditating many of the associated neurotoxic effects. Along with their commonly cited role in energy production via oxidative phosphorylation, mitochondria also play a central role in other critical cellular processes including calcium buffering, cell death pathways, and metabolite synthesis. In addition to meeting their immense energy demands, neurons are particularly dependent on the proper function and spatial organization of mitochondria to mediate specialized functions including neurotransmitter trafficking and release. Mitochondrial dependence is further highlighted in the developing brain, requiring spatiotemporally complex and metabolically expensive processes such as neurogenesis, synaptogenesis, and synaptic pruning, making the consequence of functional alterations potentially impactful. To this end, we explore and summarize the current mechanistic understanding of the effects of anesthetic exposure on mitochondria in the developing nervous system. We will specifically focus on the impact of anesthetic agents on mitochondrial dynamics, apoptosis, bioenergetics, stress pathways, and redox homeostasis. In addition, we will highlight critical knowledge gaps, pertinent challenges, and potential therapeutic targets warranting future exploration to guide mechanistic and outcomes research

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

iPSC-cardiomyocytes in the preclinical prediction of candidate pharmaceutical toxicity

Many challenges remain in the preclinical evaluation, adjudication, and prioritization of novel compounds in therapeutic discovery pipelines. These obstacles are evident by the large number of candidate or lead compounds failing to reach clinical trials, significantly due to a lack of efficacy in the disease paradigm of interest and/or the presence of innate chemical toxicity. The consequential compound attrition in discovery pipelines results in added monetary and time costs, potential danger to patients, and a slowed discovery of true therapeutics. The low rate of successful translation calls for improved models that can recapitulate in vivo function in preclinical testing to ensure the removal of toxic compounds earlier in the discovery process, in particular for the assessment of cardiotoxicity, the leading cause of post-market drug withdrawal. With recent advances in the development of human Inducible pluripotent stem cell derived cardiomyocytes (iPSC-CMs), novel compounds can be assessed with better disease relevance while more accurately assessing human safety. In this review, we discuss the utility of iPSC-CMs in preclinical testing by taking advantage of the inherent ability to mimic CMs in vivo. We explore the similarities and differences in electrophysiology, calcium handling, cellular signaling, contractile machinery, and metabolism between iPSC-CMs and adult CMs as these complex coordinated functions directly relate to toxicity evaluation. We will highlight considerations when using iPSC-CMs, such as maturation protocols, to ensure a more representative phenotype of the adult human CM, and how different populations of CMs can affect results in compound testing

Impact of Opioids on Cellular Metabolism: Implications for Metabolic Pathways Involved in Cancer

Opioid utilization for pain management is prevalent among cancer patients. There is significant evidence describing the many effects of opioids on cancer development. Despite the pivotal role of metabolic reprogramming in facilitating cancer growth and metastasis, the specific impact of opioids on crucial oncogenic metabolic pathways remains inadequately investigated. This review provides an understanding of the current research on opioid-mediated changes to cellular metabolic pathways crucial for oncogenesis, including glycolysis, the tricarboxylic acid cycle, glutaminolysis, and oxidative phosphorylation (OXPHOS). The existing literature suggests that opioids affect energy production pathways via increasing intracellular glucose levels, increasing the production of lactic acid, and reducing ATP levels through impediment of OXPHOS. Opioids modulate pathways involved in redox balance which may allow cancer cells to overcome ROS-mediated apoptotic signaling. The majority of studies have been conducted in healthy tissue with a predominant focus on neuronal cells. To comprehensively understand the impact of opioids on metabolic pathways critical to cancer progression, research must extend beyond healthy tissue and encompass patient-derived cancer tissue, allowing for a better understanding in the context of the metabolic reprogramming already undergone by cancer cells. The current literature is limited by a lack of direct experimentation exploring opioid-induced changes to cancer metabolism as they relate to tumor growth and patient outcome

Rodent Models of Dilated Cardiomyopathy and Heart Failure for Translational Investigations and Therapeutic Discovery

Even with modern therapy, patients with heart failure only have a 50% five-year survival rate. To improve the development of new therapeutic strategies, preclinical models of disease are needed to properly emulate the human condition. Determining the most appropriate model represents the first key step for reliable and translatable experimental research. Rodent models of heart failure provide a strategic compromise between human in vivo similarity and the ability to perform a larger number of experiments and explore many therapeutic candidates. We herein review the currently available rodent models of heart failure, summarizing their physiopathological basis, the timeline of the development of ventricular failure, and their specific clinical features. In order to facilitate the future planning of investigations in the field of heart failure, a detailed overview of the advantages and possible drawbacks of each model is provided

Dataset of integrin-linked kinase protein: Protein interactions in cardiomyocytes identified by mass spectrometry

Using hearts from mice overexpressing integrin linked kinase (ILK) behind the cardiac specific promoter αMHC, we have performed immunoprecipitation and mass spectrometry to identify novel ILK protein:protein interactions that regulate cardiomyocyte activity and calcium flux. Integrin linked kinase complexes were captured from mouse heart lysates using a commercial antibody, with subsequent liquid chromatography tandem mass spectral analysis. Interacting partners were identified using the MASCOT server, and important interactions verified using reverse immunoprecipitation and mass spectrometry. All ILK interacting proteins were identified in a non-biased manner, and are stored in the ProteomeXchange Consortium via the PRIDE partner repository (reference ID PRIDE: http://www.ebi.ac.uk/pride/archive/projects/PXD001053). The functional role of identified ILK interactions in cardiomyocyte function and arrhythmia were subsequently confirmed in human iPSC-cardiomyocytes. Keywords: Cardiology, Protein:protein interactions, Calcium regulation, Mass spectrometr

Biallelic mutations in CRB1 underlie autosomal recessive familial foveal retinoschisis

Purpose: To identify the genetic cause of autosomal recessive familial foveal retinoschisis (FFR). Methods: A female sibship with FFR was identified (Family-A; 17 and 16 years, respectively); panel based genetic sequencing (132 genes) and comparative genome hybridization (142 genes) were performed. Whole-exome sequencing (WES) was performed on both siblings using the Illumina-HiSeq-2500 platform. A sporadic male (Family-B; 35 years) with FFR underwent WES using Illumina NextSeq500. All three affected subjects underwent detailed ophthalmologic evaluation including fundus photography, autofluorescence imaging, spectral-domain optical coherence tomography (SD-OCT), and full-field electroretinogram (ERG). Results: Panel-based genetic testing identified two presumed disease causing variants in CRB1 (p.Gly123Cys and p.Cys948Tyr) in Family-A sibship; no deletion or duplication was detected. WES analysis in the sibship identified nine genes with two or more shared nonsynonymous rare coding sequence variants; CRB1 remained a strong candidate gene, and CRB1 variants segregated with the disease. WES in Family-B identified two presumed disease causing variants in CRB1 (p.Ile167_Gly169del and p.Arg764Cys) that segregated with the disease phenotype. Distance visual acuity was 20/40 or better in all three affected except for the left eye of the older subject (Family-B), which showed macular atrophy. Fundus evaluation showed spoke-wheel appearance at the macula in five eyes. The SD-OCT showed macular schitic changes in inner and outer nuclear layers in all cases. The ERG responses were normal in all subjects. Conclusions: This is the first report to implicate CRB1 as the underlying cause of FFR. This phenotype forms the mildest end of the spectrum of CRB1-related diseases

General medical publications during COVID-19 show increased dissemination despite lower validation.

BackgroundThe COVID-19 pandemic has yielded an unprecedented quantity of new publications, contributing to an overwhelming quantity of information and leading to the rapid dissemination of less stringently validated information. Yet, a formal analysis of how the medical literature has changed during the pandemic is lacking. In this analysis, we aimed to quantify how scientific publications changed at the outset of the COVID-19 pandemic.MethodsWe performed a cross-sectional bibliometric study of published studies in four high-impact medical journals to identify differences in the characteristics of COVID-19 related publications compared to non-pandemic studies. Original investigations related to SARS-CoV-2 and COVID-19 published in March and April 2020 were identified and compared to non-COVID-19 research publications over the same two-month period in 2019 and 2020. Extracted data included publication characteristics, study characteristics, author characteristics, and impact metrics. Our primary measure was principal component analysis (PCA) of publication characteristics and impact metrics across groups.ResultsWe identified 402 publications that met inclusion criteria: 76 were related to COVID-19; 154 and 172 were non-COVID publications over the same period in 2020 and 2019, respectively. PCA utilizing the collected bibliometric data revealed segregation of the COVID-19 literature subset from both groups of non-COVID literature (2019 and 2020). COVID-19 publications were more likely to describe prospective observational (31.6%) or case series (41.8%) studies without industry funding as compared with non-COVID articles, which were represented primarily by randomized controlled trials (32.5% and 36.6% in the non-COVID literature from 2020 and 2019, respectively).ConclusionsIn this cross-sectional study of publications in four general medical journals, COVID-related articles were significantly different from non-COVID articles based on article characteristics and impact metrics. COVID-related studies were generally shorter articles reporting observational studies with less literature cited and fewer study sites, suggestive of more limited scientific support. They nevertheless had much higher dissemination