Brief isoflurane administration as an adjunct treatment to control organophosphate-induced convulsions and neuropathology

Organophosphate-based chemical agents (OP), including nerve agents and certain pesticides such as paraoxon, are potent acetylcholinesterase inhibitors that cause severe convulsions and seizures, leading to permanent central nervous system (CNS) damage if not treated promptly. The current treatment regimen for OP poisoning is intramuscular injection of atropine sulfate with an oxime such as pralidoxime (2-PAM) to mitigate cholinergic over-activation of the somatic musculature and autonomic nervous system. This treatment does not provide protection against CNS cholinergic overactivation and therefore convulsions require additional medication. Benzodiazepines are the currently accepted treatment for OP-induced convulsions, but the convulsions become refractory to these GABAA agonists and repeated dosing has diminishing effectiveness. As such, adjunct anticonvulsant treatments are needed to provide improved protection against recurrent and prolonged convulsions and the associated excitotoxic CNS damage that results from them. Previously we have shown that brief, 4-min administration of 3%–5% isoflurane in 100% oxygen has profound anticonvulsant and CNS protective effects when administered 30 min after a lethal dose of paraoxon. In this report we provide an extended time course of the effectiveness of 5% isoflurane delivered for 5 min, ranging from 60 to 180 min after a lethal dose of paraoxon in rats. We observed substantial effectiveness in preventing neuronal loss as shown by Fluoro-Jade B staining when isoflurane was administered 1 h after paraoxon, with diminishing effectiveness at 90, 120 and 180 min. In vivo magnetic resonance imaging (MRI) derived T2 and mean diffusivity (MD) values showed that 5-min isoflurane administration at a concentration of 5% prevents brain edema and tissue damage when administered 1 h after a lethal dose of paraoxon. We also observed reduced astrogliosis as shown by GFAP immunohistochemistry. Studies with continuous EEG monitoring are ongoing to demonstrate effectiveness in animal models of soman poisoning

Microstructural Alterations and Oligodendrocyte Dysmaturation in White Matter After Cardiopulmonary Bypass in a Juvenile Porcine Model.

BACKGROUND: Newly developed white matter (WM) injury is common after cardiopulmonary bypass (CPB) in severe/complex congenital heart disease. Fractional anisotropy (FA) allows measurement of macroscopic organization of WM pathology but has rarely been applied after CPB. The aims of our animal study were to define CPB-induced FA alterations and to determine correlations between these changes and cellular events after congenital heart disease surgery. METHODS AND RESULTS: Normal porcine WM development was first assessed between 3 and 7 weeks of age: 3-week-old piglets were randomly assigned to 1 of 3 CPB-induced insults. FA was analyzed in 31 WM structures. WM oligodendrocytes, astrocytes, and microglia were assessed immunohistologically. Normal porcine WM development resembles human WM development in early infancy. We found region-specific WM vulnerability to insults associated with CPB. FA changes after CPB were also insult dependent. Within various WM areas, WM within the frontal cortex was susceptible, suggesting that FA in the frontal cortex should be a biomarker for WM injury after CPB. FA increases occur parallel to cellular processes of WM maturation during normal development; however, they are altered following surgery. CPB-induced oligodendrocyte dysmaturation, astrogliosis, and microglial expansion affect these changes. FA enabled capturing CPB-induced cellular events 4 weeks postoperatively. Regions most resilient to CPB-induced FA reduction were those that maintained mature oligodendrocytes. CONCLUSIONS: Reducing alterations of oligodendrocyte development in the frontal cortex can be both a metric and a goal to improve neurodevelopmental impairment in the congenital heart disease population. Studies using this model can provide important data needed to better interpret human imaging studies

Transplantation of induced neural stem cells (iNSCs) into chronically demyelinated corpus callosum ameliorates motor deficits

Abstract: Multiple Sclerosis (MS) causes neurologic disability due to inflammation, demyelination, and neurodegeneration. Immunosuppressive treatments can modify the disease course but do not effectively promote remyelination or prevent long term neurodegeneration. As a novel approach to mitigate chronic stage pathology, we tested transplantation of mouse induced neural stem cells (iNSCs) into the chronically demyelinated corpus callosum (CC) in adult mice. Male C57BL/6 mice fed 0.3% cuprizone for 12 weeks exhibited CC atrophy with chronic demyelination, astrogliosis, and microglial activation. Syngeneic iNSCs were transplanted into the CC after ending cuprizone and perfused for neuropathology 2 weeks later. Magnetic resonance imaging (MRI) sequences for magnetization transfer ratio (MTR), diffusion-weighted imaging (T2), and diffusion tensor imaging (DTI) quantified CC pathology in live mice before and after iNSC transplantation. Each MRI technique detected progressive CC pathology. Mice that received iNSCs had normalized DTI radial diffusivity, and reduced astrogliosis post-imaging. A motor skill task that engages the CC is Miss-step wheel running, which demonstrated functional deficits from cuprizone demyelination. Transplantation of iNSCs resulted in marked recovery of running velocity. Neuropathology after wheel running showed that iNSC grafts significantly increased host oligodendrocytes and proliferating oligodendrocyte progenitors, while modulating axon damage. Transplanted iNSCs differentiated along astrocyte and oligodendrocyte lineages, without myelinating, and many remained neural stem cells. Our findings demonstrate the applicability of neuroimaging and functional assessments for pre-clinical interventional trials during chronic demyelination and detect improved function from iNSC transplantation. Directly reprogramming fibroblasts into iNSCs facilitates the future translation towards exogenous autologous cell therapies

Transplantation of induced neural stem cells (iNSCs) into chronically demyelinated corpus callosum ameliorates motor deficits

Abstract: Multiple Sclerosis (MS) causes neurologic disability due to inflammation, demyelination, and neurodegeneration. Immunosuppressive treatments can modify the disease course but do not effectively promote remyelination or prevent long term neurodegeneration. As a novel approach to mitigate chronic stage pathology, we tested transplantation of mouse induced neural stem cells (iNSCs) into the chronically demyelinated corpus callosum (CC) in adult mice. Male C57BL/6 mice fed 0.3% cuprizone for 12 weeks exhibited CC atrophy with chronic demyelination, astrogliosis, and microglial activation. Syngeneic iNSCs were transplanted into the CC after ending cuprizone and perfused for neuropathology 2 weeks later. Magnetic resonance imaging (MRI) sequences for magnetization transfer ratio (MTR), diffusion-weighted imaging (T2), and diffusion tensor imaging (DTI) quantified CC pathology in live mice before and after iNSC transplantation. Each MRI technique detected progressive CC pathology. Mice that received iNSCs had normalized DTI radial diffusivity, and reduced astrogliosis post-imaging. A motor skill task that engages the CC is Miss-step wheel running, which demonstrated functional deficits from cuprizone demyelination. Transplantation of iNSCs resulted in marked recovery of running velocity. Neuropathology after wheel running showed that iNSC grafts significantly increased host oligodendrocytes and proliferating oligodendrocyte progenitors, while modulating axon damage. Transplanted iNSCs differentiated along astrocyte and oligodendrocyte lineages, without myelinating, and many remained neural stem cells. Our findings demonstrate the applicability of neuroimaging and functional assessments for pre-clinical interventional trials during chronic demyelination and detect improved function from iNSC transplantation. Directly reprogramming fibroblasts into iNSCs facilitates the future translation towards exogenous autologous cell therapies

CATMoS: Collaborative Acute Toxicity Modeling Suite.

BACKGROUND: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. OBJECTIVES: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different end points: Lethal Dose 50 (LD50 value, U.S. Environmental Protection Agency hazard (four) categories, Globally Harmonized System for Classification and Labeling hazard (five) categories, very toxic chemicals [LD50 (LD50≤50mg/kg)], and nontoxic chemicals (LD50>2,000mg/kg). METHODS: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. RESULTS: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared with in vivo results. DISCUSSION: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for more than 800,000 chemicals have been made available via the National Toxicology Program's Integrated Chemical Environment tools and data sets (ice.ntp.niehs.nih.gov). The models are also implemented in a free, standalone, open-source tool, OPERA, which allows predictions of new and untested chemicals to be made. https://doi.org/10.1289/EHP8495

Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets

Machine learning methods have been applied to many data sets in pharmaceutical research for several decades. The relative ease and availability of fingerprint type molecular descriptors paired with Bayesian methods resulted in the widespread use of this approach for a diverse array of end points relevant to drug discovery. Deep learning is the latest machine learning algorithm attracting attention for many of pharmaceutical applications from docking to virtual screening. Deep learning is based on an artificial neural network with multiple hidden layers and has found considerable traction for many artificial intelligence applications. We have previously suggested the need for a comparison of different machine learning methods with deep learning across an array of varying data sets that is applicable to pharmaceutical research. End points relevant to pharmaceutical research include absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties, as well as activity against pathogens and drug discovery data sets. In this study, we have used data sets for solubility, probe-likeness, hERG, KCNQ1, bubonic plague, Chagas, tuberculosis, and malaria to compare different machine learning methods using FCFP6 fingerprints. These data sets represent whole cell screens, individual proteins, physicochemical properties as well as a data set with a complex end point. Our aim was to assess whether deep learning offered any improvement in testing when assessed using an array of metrics including AUC, F1 score, Cohen’s kappa, Matthews correlation coefficient and others. Based on ranked normalized scores for the metrics or data sets Deep Neural Networks (DNN) ranked higher than SVM, which in turn was ranked higher than all the other machine learning methods. Visualizing these properties for training and test sets using radar type plots indicates when models are inferior or perhaps over trained. These results also suggest the need for assessing deep learning further using multiple metrics with much larger scale comparisons, prospective testing as well as assessment of different fingerprints and DNN architectures beyond those used

Salvianolic acid B inhibits growth of head and neck squamous cell carcinoma in vitro and in vivo via cyclooxygenase-2 and apoptotic pathways

Overexpression of cyclooxygenase-2 (COX-2) in oral mucosa has been associated with increased risk of head and neck squamous cell carcinoma (HNSCC). Celecoxib is a nonsteroidal anti-inflammatory drug, which inhibits COX-2 but not COX-1. This selective COX-2 inhibitor holds promise as a cancer preventive agent. Concerns about cardiotoxicity of celecoxib, limits its use in long-term chemoprevention and therapy. Salvianolic acid B (Sal-B) is a leading bioactive component of Salvia miltiorrhiza Bge, which is used for treating neoplastic and chronic inflammatory diseases in China. The purpose of this study was to investigate the mechanisms by which Sal-B inhibits HNSCC growth. Sal-B was isolated from S. miltiorrhiza Bge by solvent extraction followed by 2 chromatographic steps. Pharmacological activity of Sal-B was assessed in HNSCC and other cell lines by estimating COX-2 expression, cell viability and caspase-dependent apoptosis. Sal-B inhibited growth of HNSCC JHU-022 and JHU-013 cells with IC50 of 18 and 50 lM, respectively. Nude mice with HNSCC solid tumor xenografts were treated with Sal-B (80 mg/kg/day) or celecoxib (5 mg/ kg/day) for 25 days to investigate in vivo effects of the COX-2 inhibitors. Tumor volumes in Sal-B treated group were signifi-cantly lower than those in celecoxib treated or untreated control groups (p \u3c 0.05). Sal-B inhibited COX-2 expression in cultured HNSCC cells and in HNSCC cells isolated from tumor xenografts. Sal-B also caused dose-dependent inhibition of prostaglandin E 2 synthesis, either with or without lipopolysaccharide stimulation. Taken together, Sal-B shows promise as a COX-2 targeted anticancer agent for HNSCC prevention and treatment. © 2008 Wiley-Liss, Inc