The Rising Status of Phenobarbital: A Case for Use in Severe Refractory Hyperactive Poststroke Delirium.

INTRODUCTION: Up to 48% of patients who have had a stroke will experience poststroke delirium (PSD) that can be hyperactive, hypoactive, or mixed. Literature on treatment of the hyperactive subtype is specifically lacking. This case report describes the rapid resolution of severe refractory hyperactive PSD with phenobarbital. CASE REPORT: A 58-year-old man with a left middle cerebral artery stroke presented with severe hyperactive PSD of 12 days duration, refractory to antipsychotics, alpha-2 agonists, gabapentin, therapeutic valproic acid, benzodiazepines, and ketamine infusion. An oral dose of phenobarbital 30.4 mg, followed by oral maintenance therapy was initiated on day 13 of admission with dramatic improvement. As his Richmond Agitation-Sedation score trended downwards to 0, he was able to cooperate with therapies. This allowed for discharge to a skilled nursing facility for rehabilitation and subsequently home 2 weeks later. CONCLUSION: Hyperactive PSD is a common complication of stroke with little evidence to guide treatment strategies. This report suggests that phenobarbital, because of its varied mechanisms of action and unique neurochemistry, may be an unrecognized potential therapy.

Schizophrenia: a disorder of broken brain bioenergetics.

A substantial and diverse body of literature suggests that the pathophysiology of schizophrenia is related to deficits of bioenergetic function. While antipsychotics are an effective therapy for the management of positive psychotic symptoms, they are not efficacious for the complete schizophrenia symptom profile, such as the negative and cognitive symptoms. In this review, we discuss the relationship between dysfunction of various metabolic pathways across different brain regions in relation to schizophrenia. We contend that several bioenergetic subprocesses are affected across the brain and such deficits are a core feature of the illness. We provide an overview of central perturbations of insulin signaling, glycolysis, pentose-phosphate pathway, tricarboxylic acid cycle, and oxidative phosphorylation in schizophrenia. Importantly, we discuss pharmacologic and nonpharmacologic interventions that target these pathways and how such interventions may be exploited to improve the symptoms of schizophrenia.

The active kinome: The modern view of how active protein kinase networks fit in biological research.

Biological regulatory networks are dynamic, intertwined, and complex systems making them challenging to study. While quantitative measurements of transcripts and proteins are key to investigate the state of a biological system, they do not inform the "active" state of regulatory networks. In consideration of that fact, "functional" proteomics assessments are needed to decipher active regulatory processes. Phosphorylation, a key post-translation modification, is a reversible regulatory mechanism that controls the functional state of proteins. Recent advancements of high-throughput protein kinase activity profiling platforms allow for a broad assessment of protein kinase networks in complex biological systems. In conjunction with sophisticated computational modeling techniques, these profiling platforms provide datasets that inform the active state of regulatory systems in disease models and highlight potential drug targets. Taken together, system-wide profiling of protein kinase activity has become a critical component of modern molecular biology research and presents a promising avenue for drug discovery.

Cellular, molecular, and therapeutic characterization of pilocarpine-induced temporal lobe epilepsy.

Animal models have expanded our understanding of temporal lobe epilepsy (TLE). However, translating these to cell-specific druggable hypotheses is not explored. Herein, we conducted an integrative insilico-analysis of an available transcriptomics dataset obtained from animals with pilocarpine-induced-TLE. A set of 119 genes with subtle-to-moderate impact predicted most forms of epilepsy with ~ 97% accuracy and characteristically mapped to upregulated homeostatic and downregulated synaptic pathways. The deconvolution of cellular proportions revealed opposing changes in diverse cell types. The proportion of nonneuronal cells increased whereas that of interneurons, except for those expressing vasoactive intestinal peptide (Vip), decreased, and pyramidal neurons of the cornu-ammonis (CA) subfields showed the highest variation in proportion. A probabilistic Bayesian-network demonstrated an aberrant and oscillating physiological interaction between nonneuronal cells involved in the blood-brain-barrier and Vip interneurons in driving seizures, and their role was evaluated insilico using transcriptomic changes induced by valproic-acid, which showed opposing effects in the two cell-types. Additionally, we revealed novel epileptic and antiepileptic mechanisms and predicted drugs using causal inference, outperforming the present drug repurposing approaches. These well-powered findings not only expand the understanding of TLE and seizure oscillation, but also provide predictive biomarkers of epilepsy, cellular and causal micro-circuitry changes associated with it, and a drug-discovery method focusing on these events.

Identification of candidate repurposable drugs to combat COVID-19 using a signature-based approach.

The COVID-19 pandemic caused by the novel SARS-CoV-2 is more contagious than other coronaviruses and has higher rates of mortality than influenza. Identification of effective therapeutics is a crucial tool to treat those infected with SARS-CoV-2 and limit the spread of this novel disease globally. We deployed a bioinformatics workflow to identify candidate drugs for the treatment of COVID-19. Using an "omics" repository, the Library of Integrated Network-Based Cellular Signatures (LINCS), we simultaneously probed transcriptomic signatures of putative COVID-19 drugs and publicly available SARS-CoV-2 infected cell lines to identify novel therapeutics. We identified a shortlist of 20 candidate drugs: 8 are already under trial for the treatment of COVID-19, the remaining 12 have antiviral properties and 6 have antiviral efficacy against coronaviruses specifically, in vitro. All candidate drugs are either FDA approved or are under investigation. Our candidate drug findings are discordant with (i.e., reverse) SARS-CoV-2 transcriptome signatures generated in vitro, and a subset are also identified in transcriptome signatures generated from COVID-19 patient samples, like the MEK inhibitor selumetinib. Overall, our findings provide additional support for drugs that are already being explored as therapeutic agents for the treatment of COVID-19 and identify promising novel targets that are worthy of further investigation.

Similarities and dissimilarities between psychiatric cluster disorders.

The common molecular mechanisms underlying psychiatric disorders are not well understood. Prior attempts to assess the pathological mechanisms responsible for psychiatric disorders have been limited by biased selection of comparable disorders, datasets/cohort availability, and challenges with data normalization. Here, using DisGeNET, a gene-disease associations database, we sought to expand such investigations in terms of number and types of diseases. In a top-down manner, we analyzed an unbiased cluster of 36 psychiatric disorders and comorbid conditions at biological pathway, cell-type, drug-target, and chromosome levels and deployed density index, a novel metric to quantify similarities (close to 1) and dissimilarities (close to 0) between these disorders at each level. At pathway level, we show that cognition and neurotransmission drive the similarity and are involved across all disorders, whereas immune-system and signal-response coupling (cell surface receptors, signal transduction, gene expression, and metabolic process) drives the dissimilarity and are involved with specific disorders. The analysis at the drug-target level supports the involvement of neurotransmission-related changes across these disorders. At cell-type level, dendrite-targeting interneurons, across all layers, are most involved. Finally, by matching the clustering pattern at each level of analysis, we showed that the similarity between the disorders is influenced most at the chromosomal level and to some extent at the cellular level. Together, these findings provide first insights into distinct cellular and molecular pathologies, druggable mechanisms associated with several psychiatric disorders and comorbid conditions and demonstrate that similarities between these disorders originate at the chromosome level and disperse in a bottom-up manner at cellular and pathway levels.

Signature-based approaches for informed drug repurposing: targeting CNS disorders.

CNS disorders, and in particular psychiatric illnesses, lack definitive disease-altering therapeutics. The limited understanding of the mechanisms driving these illnesses with the slow pace and high cost of drug development exacerbates this issue. For these reasons, drug repurposing - both a less expensive and time-efficient practice compared to de novo drug development - has been a promising strategy to overcome the paucity of treatments available for these debilitating disorders. While empirical drug-repurposing has been a routine practice in clinical psychiatry, innovative, informed, and cost-effective repurposing efforts using big data ("omics") have been designed to characterize drugs by structural and transcriptomic signatures. These strategies, in conjunction with ontological integration, provide an important opportunity to address knowledge-based challenges associated with drug development for CNS disorders. In this review, we discuss various signature-based in silico approaches to drug repurposing, its integration with multiple omics platforms, and how this data can be used for clinically relevant, evidence-based drug repurposing. These tools provide an exciting translational avenue to merge omics-based drug discovery platforms with patient-specific disease signatures, ultimately facilitating the identification of new therapies for numerous psychiatric disorders.

Emerging Kinase Therapeutic Targets in Pancreatic Ductal Adenocarcinoma and Pancreatic Cancer Desmoplasia.

Kinase drug discovery represents an active area of therapeutic research, with previous pharmaceutical success improving patient outcomes across a wide variety of human diseases. In pancreatic ductal adenocarcinoma (PDAC), innovative pharmaceutical strategies such as kinase targeting have been unable to appreciably increase patient survival. This may be due, in part, to unchecked desmoplastic reactions to pancreatic tumors. Desmoplastic stroma enhances tumor development and progression while simultaneously restricting drug delivery to the tumor cells it protects. Emerging evidence indicates that many of the pathologic fibrotic processes directly or indirectly supporting desmoplasia may be driven by targetable protein tyrosine kinases such as Fyn-related kinase (FRK); B lymphoid kinase (BLK); hemopoietic cell kinase (HCK); ABL proto-oncogene 2 kinase (ABL2); discoidin domain receptor 1 kinase (DDR1); Lck/Yes-related novel kinase (LYN); ephrin receptor A8 kinase (EPHA8); FYN proto-oncogene kinase (FYN); lymphocyte cell-specific kinase (LCK); tec protein kinase (TEC). Herein, we review literature related to these kinases and posit signaling networks, mechanisms, and biochemical relationships by which this group may contribute to PDAC tumor growth and desmoplasia.

Outcomes of treatment modalities for ruptured intracranial aneurysms based on age - A meta-analysis.

BACKGROUND: Data comparing the effect of age on outcomes of patients who underwent either endovascular coiling (EVC) or neurosurgical clipping (NSC) for ruptured intracranial aneurysms remains limited. OBJECTIVE: To better elucidate the preferred intervention for ruptured aneurysm management by presenting the results of our systematic review of the literature that evaluated the potential advantages of the two interventions between different age groups. METHODS: Systematic review of PubMed and Embase was performed (2002 - June 10, 2019) following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2013 guidelines. Median ages of EVC and NSC cohorts were 54 and 56, respectively. Ages below the median were used in our "younger" cohort; ages above the median were used in our "older" cohort. RESULTS: We reviewed 13 studies on 7,137 patients. In the younger cohort, there were 2840 (EVC: 1412, NSC: 1428) patients. In the older cohort, there were 4297 (EVC: 2552, NSC: 1745) patients. Overall, there was a significant difference in functionality between EVC (77.70%) and NSC (69.23%) (OR=1.69; 95% C.I.: 1.10-2.60, p = 0.0212). In our younger cohort, functionality was significantly different between EVC (77%) and NSC (69%) (OR=1.54; 95% C.I.: 1.29-1.84, p < 0.001). For the older cohort, there was no significant difference in functionality, complications, or efficacy. CONCLUSIONS: We have highlighted the importance of considering age prior to deciding which intervention is most appropriate for ruptured aneurysms, with higher morbidity and mortality with NSC versus EVC in the younger population.

Risk Factors Associated With Hyperammonemia Following Unprovoked Convulsive Seizures.

This report describes a unique case of recurrent transient hyperammonemia (THA) following a first-time occurrence of generalized tonic-clonic seizure in a young adult, who went on to develop post-stroke epilepsy. Although this phenomenon has been described in recent literature, we report not only the highest initial ammonia level to date, 549 µmol/L, but we also document serial trends of the ammonia levels at multiple admissions for the same patient for the management of breakthrough seizures. Interestingly enough, persistence of the elevation of the ammonia levels was accompanied by no other significant metabolic derangements, unlike reported in similar cases. Of prior studies, high ammonia levels have been reported in the context of alcohol-induced seizures, with resolution of ammonia levels within eight hours. Here, we highlight the importance of medication compliance, as well as the need for serial ammonia levels for improving patient outcomes, with the knowledge that ammonia accumulation leads to potential irreversible neurotoxicity. Additionally, we completed a systematic literature review on data pertaining to the risk factors associated with hyperammonemia following unprovoked convulsive seizures in an effort to analyze our case in the context of the existing literature. Our objective is to ultimately understand the utility of serial ammonia levels for unprovoked convulsive seizures in the context of the patient's initial presentation, and whether treatment of these episodes of hyperammonemia can significantly alter outcomes.

Identification of new drug treatments to combat COVID19: A signature-based approach using iLINCS.

The COVID-19 pandemic caused by the novel SARS-CoV-2 is more contagious than other coronaviruses and has higher rates of mortality than influenza. As no vaccine or drugs are currently approved to specifically treat COVID-19, identification of effective therapeutics is crucial to treat the afflicted and limit disease spread. We deployed a bioinformatics workflow to identify candidate drugs for the treatment of COVID-19. Using an "omics" repository, the Library of Integrated Network-Based Cellular Signatures (LINCS), we simultaneously probed transcriptomic signatures of putative COVID-19 drugs and signatures of coronavirus-infected cell lines to identify therapeutics with concordant signatures and discordant signatures, respectively. Our findings include three FDA approved drugs that have established antiviral activity, including protein kinase inhibitors, providing a promising new category of candidates for COVID-19 interventions.