Increased emergency cardiovascular events among under-40 population in Israel during vaccine rollout and third COVID-19 wave.

Cardiovascular adverse conditions are caused by coronavirus disease 2019 (COVID-19) infections and reported as side-effects of the COVID-19 vaccines. Enriching current vaccine safety surveillance systems with additional data sources may improve the understanding of COVID-19 vaccine safety. Using a unique dataset from Israel National Emergency Medical Services (EMS) from 2019 to 2021, the study aims to evaluate the association between the volume of cardiac arrest and acute coronary syndrome EMS calls in the 16-39-year-old population with potential factors including COVID-19 infection and vaccination rates. An increase of over 25% was detected in both call types during January-May 2021, compared with the years 2019-2020. Using Negative Binomial regression models, the weekly emergency call counts were significantly associated with the rates of 1st and 2nd vaccine doses administered to this age group but were not with COVID-19 infection rates. While not establishing causal relationships, the findings raise concerns regarding vaccine-induced undetected severe cardiovascular side-effects and underscore the already established causal relationship between vaccines and myocarditis, a frequent cause of unexpected cardiac arrest in young individuals. Surveillance of potential vaccine side-effects and COVID-19 outcomes should incorporate EMS and other health data to identify public health trends (e.g., increased in EMS calls), and promptly investigate potential underlying causes.

Low-Volume Bowel Preparation Is Associated With Reduced Time to Colonoscopy in Hospitalized Patients: A Propensity-Matched Analysis.

INTRODUCTION: Delays in inpatient colonoscopy are commonly caused by inadequate bowel preparation and result in increased hospital length of stay (LOS) and healthcare costs. Low-volume bowel preparation (LV-BP; sodium sulfate, potassium sulfate, and magnesium sulfate ) has been shown to improve outpatient bowel preparation quality compared with standard high-volume bowel preparations (HV-BP; polyethylene glycol ). However, its efficacy in hospitalized patients has not been well-studied. We assessed the impact of LV-BP on time to colonoscopy, hospital LOS, and bowel preparation quality among inpatients. METHODS: We performed a propensity score-matched analysis of adult inpatients undergoing colonoscopy who received either LV-BP or HV-BP before colonoscopy at a quaternary academic medical center. Multivariate regression models with feature selection were developed to assess the association between LV-BP and study outcomes. RESULTS: Among 1,807 inpatients included in this study, 293 and 1,514 patients received LV-BP and HV-BP, respectively. Among the propensity score-matched population, LV-BP was associated with a shorter time to colonoscopy (ß: -0.43 [95% confidence interval: -0.56 to -0.30]) while having similar odds of adequate preparation (odds ratio: 1.02 [95% confidence interval: 0.71-1.46]; P = 0.92). LV-BP was also significantly associated with decreased hospital LOS among older patients (age ≥ 75 years), patients with chronic kidney disease, and patients who were hospitalized with gastrointestinal bleeding. DISCUSSION: LV-BP is associated with decreased time to colonoscopy in hospitalized patients. Older inpatients, inpatients with chronic kidney disease, and inpatients with gastrointestinal bleeding may particularly benefit from LV-BP. Prospective studies are needed to further establish the role of LV-BP for inpatient colonoscopies.

Moderating effects of out-of-hospital cardiac arrest characteristics on the association between EMS response time and survival.

BACKGROUND: Although several Utstein variables are known to independently improve survival, how they moderate the effect of emergency medical service (EMS) response times on survival is unknown. OBJECTIVES: To quantify how public location, witnessed status, bystander CPR, and bystander AED shock individually and jointly moderate the effect of EMS response time delays on OHCA survival. METHODS: This retrospective cohort study was a secondary analysis of the Resuscitation Outcomes Consortium Epistry-Cardiac Arrest database (December 2005 to June 2015). We included all adult, non-traumatic, non-EMS witnessed, and EMS-treated OHCAs from eleven sites across the US and Canada. We trained a logistic regression model with standard Utstein control variables and interaction terms between EMS response time and the four aforementioned OHCA characteristics. RESULTS: 102,216 patients were included. Three of the four characteristics - witnessed OHCAs (OR = 0.962), bystander CPR (OR = 0.968) and public location (OR = 0.980) - increased the negative effect of a one-minute delay on the odds of survival. In contrast, a bystander AED shock decreased the negative effect of a one-minute response time delay on the odds of survival (OR = 1.064). The magnitude of the effect of a one-minute delay in EMS response time on the odds of survival ranged from 1.3% to 9.8% (average: 5.3%), depending on the underlying OHCA characteristics. CONCLUSIONS: Delays in EMS response time had the largest reduction in survival odds for OHCAs that did not receive a bystander AED shock but were witnessed, occurred in public, and/or received bystander CPR. A bystander AED shock appears to be protective against a delay in EMS response time.

Implications for cardiac arrest coverage using straight-line versus route distance to nearest automated external defibrillator.

AIM: Quantifying the ratio describing the difference between "true route" and "straight-line" distances from out-of-hospital cardiac arrests (OHCAs) to the closest accessible automated external defibrillator (AED) can help correct likely overestimations in AED coverage. Furthermore, we aimed to examine to what extent the closest AED based on true route distance differed from the closest AED using "straight-line". METHODS: OHCAs (1994-2016) and AEDs (2016) in Copenhagen, Denmark and in Toronto, Canada (2007-2015 and 2015, respectively) were identified. Three distances were calculated between OHCA and target AED: 1) the straight-line distance ("straight-line") to the closest AED, 2) the corresponding true route distance to the same AED ("true route"), and 3) the closest AED based only on true route distance ("shortest true route"). The ratio between "true route" and "straight-line" distance was calculated and differences in AED coverage (an OHCA ≤ 100 m of an accessible AED) were examined. RESULTS: The "straight-line" AED coverage of 100 m was 24.2% (n = 2008/8295) in Copenhagen and 6.9% (n = 964/13916) in Toronto. The corresponding "true route" distance reduced coverage to 9.5% (n = 786) and 3.8% (n = 529), respectively. The median ratio between "true route" and "straight-line" distance was 1.6 in Copenhagen and 1.4 in Toronto. In 26.1% (n = 2167) and 22.9% (n = 3181) of all Copenhagen and Toronto OHCAs respectively, the closest AED in "shortest true route" was different than the closest AED initially found by "straight-line". CONCLUSIONS: Straight-line distance is not an accurate measure of distance and overestimates the actual AED coverage compared to a more realistic true route distance by a factor 1.4-1.6.

Predicting Coronavirus Disease 2019 Infection Risk and Related Risk Drivers in Nursing Homes: A Machine Learning Approach.

OBJECTIVE: Inform coronavirus disease 2019 (COVID-19) infection prevention measures by identifying and assessing risk and possible vectors of infection in nursing homes (NHs) using a machine-learning approach. DESIGN: This retrospective cohort study used a gradient boosting algorithm to evaluate risk of COVID-19 infection (ie, presence of at least 1 confirmed COVID-19 resident) in NHs. SETTING AND PARTICIPANTS: The model was trained on outcomes from 1146 NHs in Massachusetts, Georgia, and New Jersey, reporting COVID-19 case data on April 20, 2020. Risk indices generated from the model using data from May 4 were prospectively validated against outcomes reported on May 11 from 1021 NHs in California. METHODS: Model features, pertaining to facility and community characteristics, were obtained from a self-constructed dataset based on multiple public and private sources. The model was assessed via out-of-sample area under the receiver operating characteristic curve (AUC), sensitivity, and specificity in the training (via 10-fold cross-validation) and validation datasets. RESULTS: The mean AUC, sensitivity, and specificity of the model over 10-fold cross-validation were 0.729 [95% confidence interval (CI) 0.690‒0.767], 0.670 (95% CI 0.477‒0.862), and 0.611 (95% CI 0.412‒0.809), respectively. Prospective out-of-sample validation yielded similar performance measures (AUC 0.721; sensitivity 0.622; specificity 0.713). The strongest predictors of COVID-19 infection were identified as the NH's county's infection rate and the number of separate units in the NH; other predictors included the county's population density, historical Centers of Medicare and Medicaid Services cited health deficiencies, and the NH's resident density (in persons per 1000 square feet). In addition, the NH's historical percentage of non-Hispanic white residents was identified as a protective factor. CONCLUSIONS AND IMPLICATIONS: A machine-learning model can help quantify and predict NH infection risk. The identified risk factors support the early identification and management of presymptomatic and asymptomatic individuals (eg, staff) entering the NH from the surrounding community and the development of financially sustainable staff testing initiatives in preventing COVID-19 infection.

Effect of Optimized Versus Guidelines-Based Automated External Defibrillator Placement on Out-of-Hospital Cardiac Arrest Coverage: An In Silico Trial.

Background Mathematical optimization of automated external defibrillator (AED) placement may improve AED accessibility and out-of-hospital cardiac arrest (OHCA) outcomes compared with American Heart Association (AHA) and European Resuscitation Council (ERC) placement guidelines. We conducted an in silico trial (simulated prospective cohort study) comparing mathematically optimized placements with placements derived from current AHA and ERC guidelines, which recommend placement in locations where OHCAs are usually witnessed. Methods and Results We identified all public OHCAs of presumed cardiac cause from 2008 to 2016 in Copenhagen, Denmark. For the control, we computationally simulated placing 24/7-accessible AEDs at every unique, public, witnessed OHCA location at monthly intervals over the study period. The intervention consisted of an equal number of simulated AEDs placements, deployed monthly, at mathematically optimized locations, using a model that analyzed historical OHCAs before that month. For each approach, we calculated the number of OHCAs in the study period that occurred within a 100-m route distance based on Copenhagen's road network of an available AED after it was placed ("OHCA coverage"). Estimated impact on bystander defibrillation and 30-day survival was calculated by multivariate logistic regression. The control scenario involved 393 AEDs at historical, public, witnessed OHCA locations, covering 15.8% of the 653 public OHCAs from 2008 to 2016. The optimized locations provided significantly higher coverage (24.2%; P<0.001). Estimated bystander defibrillation and 30-day survival rates increased from 15.6% to 18.2% (P<0.05) and from 32.6% to 34.0% (P<0.05), respectively. As a baseline, the 1573 real AEDs in Copenhagen covered 14.4% of the OHCAs. Conclusions Mathematical optimization can significantly improve OHCA coverage and estimated clinical outcomes compared with a guidelines-based approach to AED placement.

Optimal in-hospital defibrillator placement.

AIMS: To determine if mathematical optimization of in-hospital defibrillator placements can reduce in-hospital cardiac arrest-to-defibrillator distance compared to existing defibrillators in a single hospital. METHODS: We identified treated IHCAs and defibrillator placements in St. Michael's Hospital in Toronto, Canada from Jan. 2013 to Jun. 2017 and mapped them to a 3-D computer model of the hospital. An optimization model identified an equal number of optimal defibrillator locations that minimized the average distance between IHCAs and the closest defibrillator using a 10-fold cross-validation approach. The optimized and existing defibrillator locations were compared in terms of average distance to the out-of-sample IHCAs. We repeated the analysis excluding intensive care units (ICUs), operating theatres (OTs), and the emergency department (ED). We also re-solved the model using fewer defibrillators to determine when the average distance matched the performance of existing defibrillators. RESULTS: We identified 433 treated IHCAs and 53 defibrillators. Of these, 167 IHCAs and 31 defibrillators were outside of ICUs, OTs, and the ED. Optimal defibrillator placements reduced the average IHCA-to-defibrillator distance from 16.1 m to 2.7 m (relative decrease of 83.0%; P = 0.002) compared to existing defibrillator placements. For non-ICU/OT/ED IHCAs, the average distance was reduced from 24.4 m to 11.9 m (relative decrease of 51.3%; P = 0.002. 8-9 optimized defibrillator locations were sufficient to match the average IHCA-to-defibrillator distance of existing defibrillator placements. CONCLUSIONS: Optimization-guided placement of in-hospital defibrillators can reduce the distance from an IHCA to the closest defibrillator. Equivalently, optimization can match existing defibrillator performance using far fewer defibrillators.

In Silico Trial of Optimized Versus Actual Public Defibrillator Locations.

BACKGROUND: Automated external defibrillators (AEDs) are often placed in areas of low risk and limited temporal availability. Mathematical optimization can improve AED accessibility but has not been compared with current practices. OBJECTIVES: This study sought to determine whether, compared with real AED locations, optimized AED locations improve coverage of out-of-hospital cardiac arrests (OHCAs). METHODS: The authors conducted the first retrospective in silico trial of an AED placement intervention. This study identified all public OHCAs of presumed cardiac cause and real AED deployed (control group) from 2007 to 2016 in Copenhagen, Denmark. Optimization models trained on historical OHCAs (1994 to 2007) were used to optimize an equal number of AEDs to the control group in locations with availabilities based on building hours (intervention #1) or 24/7 access (intervention #2). The 2 interventions and control scenario were compared using the number of OHCAs that occurred within 100 m of an accessible AED ("OHCA coverage") during the 2007 to 2016 period. Change in bystander defibrillation and 30-day survival were estimated using multivariate logistic regression. RESULTS: There were 673 public OHCAs and 1,573 registered AEDs from 2007 to 2016. OHCA coverage of real AED placements was 22.0%. OHCA coverage of interventions #1 and #2 was significantly higher at 33.4% and 43.1%, respectively; relative gains of 52.0% to 95.9% (p < 0.001). Bystander defibrillation increased from 14.6% (control group) to 22.5% to 26.9% (intervention #1 to intervention #2); relative increase of 52.9% to 83.5% (p < 0.001). The 30-day survival rates increased from 31.3% (control group) to 34.7% to 35.4%, which is a relative increase of 11.0% to 13.3% (p < 0.001). CONCLUSIONS: Optimized AED placements increased OHCA coverage by approximately 50% to 100% over real AED placements, leading to significant predicted increases in bystander defibrillation and 30-day survival.

Spatiotemporal AED optimization is generalizable.

AIMS: Mathematical optimization of automated external defibrillator (AED) placements has the potential to improve out-of-hospital cardiac arrest (OHCA) coverage and reverse the negative effects of limited AED accessibility. However, the generalizability of optimization approaches has not yet been investigated. Our goal is to examine the performance and generalizability of a spatiotemporal AED placement optimization methodology, initially developed for Toronto, Canada, to the new study setting of Copenhagen, Denmark. METHODS: We identified all public OHCAs (1994-2016) and all registered AEDs (2016) in Copenhagen, Denmark. We calculated the coverage loss associated with limited temporal accessibility of registered AEDs, and used a spatiotemporal optimization model to quantify the potential coverage gain of optimized AED deployment. Coverage gain of spatiotemporal deployment over a spatial-only solution was quantified through 10-fold cross-validation. Statistical testing was performed using χ2 and McNemar's tests. RESULTS: We found 2149 public OHCAs and 1573 registered AED locations. Coverage loss was found to be 24.4% (1104 OHCAs covered under assumed 24/7 coverage, and 835 OHCAs under actual coverage). The coverage gain from using the spatiotemporal model over a spatial-only approach was 15.3%. Temporal and geographical trends in coverage gain were similar to Toronto. CONCLUSIONS: Without modification, a previously developed spatiotemporal AED optimization approach was applied to Copenhagen, resulting in similar OHCA coverage findings as Toronto, despite large geographic and cultural differences between the two cities. In addition to reinforcing the importance of temporal accessibility of AEDs, these similarities demonstrate the generalizability of optimization approaches to improve AED placement and accessibility.

Ranking Businesses and Municipal Locations by Spatiotemporal Cardiac Arrest Risk to Guide Public Defibrillator Placement.

BACKGROUND: Efforts to guide automated external defibrillator placement for out-of-hospital cardiac arrest (OHCA) treatment have focused on identifying broadly defined location categories without considering hours of operation. Broad location categories may be composed of many businesses with varying accessibility. Identifying specific locations for automated external defibrillator deployment incorporating operating hours and time of OHCA occurrence may improve automated external defibrillator accessibility. We aim to identify specific businesses and municipal locations that maximize OHCA coverage on the basis of spatiotemporal assessment of OHCA risk in the immediate vicinity of franchise locations. METHODS: This study was a retrospective population-based cohort study using data from the Toronto Regional RescuNET Epistry cardiac arrest database. We identified all nontraumatic public OHCAs occurring in Toronto, ON, Canada, from January 2007 through December 2015. We identified 41 unique businesses and municipal location types with ≥20 locations in Toronto from the YellowPages, Canadian Franchise Association, and the City of Toronto Open Data Portal. We obtained their geographic coordinates and hours of operation from Web sites, by phone, or in person. We determined the number of OHCAs that occurred within 100 m of each location when it was open (spatiotemporal coverage) for Toronto overall and downtown. The businesses and municipal locations were then ranked by spatiotemporal OHCA coverage. To evaluate temporal stability of the rankings, we calculated intraclass correlation of the annual coverage values. RESULTS: There were 2654 nontraumatic public OHCAs. Tim Hortons ranked first in Toronto, covering 286 OHCAs. Starbucks ranked first in downtown, covering 110 OHCAs. Coffee shops and bank machines from the 5 largest Canadian banks occupied 8 of the top 10 spots in both Toronto and downtown. The rankings exhibited high temporal stability with intraclass correlation values of 0.88 (95% confidence interval, 0.83-0.93) in Toronto and 0.79 (95% confidence interval, 0.71-0.86) in downtown. CONCLUSIONS: We identified and ranked businesses and municipal locations by spatiotemporal OHCA risk in their immediate vicinity. This approach may help policy makers and funders to identify and prioritize potential partnerships for automated external defibrillator deployment in public-access defibrillator programs.

Overcoming Spatial and Temporal Barriers to Public Access Defibrillators Via Optimization.

BACKGROUND: Immediate access to an automated external defibrillator (AED) increases the chance of survival for out-of-hospital cardiac arrest (OHCA). Current deployment usually considers spatial AED access, assuming AEDs are available 24 h a day. OBJECTIVES: The goal of this study was to develop an optimization model for AED deployment, accounting for spatial and temporal accessibility, to evaluate if OHCA coverage would improve compared with deployment based on spatial accessibility alone. METHODS: This study was a retrospective population-based cohort trial using data from the Toronto Regional RescuNET Epistry cardiac arrest database. We identified all nontraumatic public location OHCAs in Toronto, Ontario, Canada (January 2006 through August 2014) and obtained a list of registered AEDs (March 2015) from Toronto Paramedic Services. Coverage loss due to limited temporal access was quantified by comparing the number of OHCAs that occurred within 100 meters of a registered AED (assumed coverage 24 h per day, 7 days per week) with the number that occurred both within 100 meters of a registered AED and when the AED was available (actual coverage). A spatiotemporal optimization model was then developed that determined AED locations to maximize OHCA actual coverage and overcome the reported coverage loss. The coverage gain between the spatiotemporal model and a spatial-only model was computed by using 10-fold cross-validation. RESULTS: A total of 2,440 nontraumatic public OHCAs and 737 registered AED locations were identified. A total of 451 OHCAs were covered by registered AEDs under assumed coverage 24 h per day, 7 days per week, and 354 OHCAs under actual coverage, representing a coverage loss of 21.5% (p < 0.001). Using the spatiotemporal model to optimize AED deployment, a 25.3% relative increase in actual coverage was achieved compared with the spatial-only approach (p < 0.001). CONCLUSIONS: One in 5 OHCAs occurred near an inaccessible AED at the time of the OHCA. Potential AED use was significantly improved with a spatiotemporal optimization model guiding deployment.

Cerebrovascular Safety of Sulfonylureas: The Role of KATP Channels in Neuroprotection and the Risk of Stroke in Patients With Type 2 Diabetes.

Sulfonylureas are ATP-sensitive potassium (KATP) channel blockers commonly used in the treatment of type 2 diabetes mellitus (T2DM). Activation of KATP channels plays a neuroprotective role in ischemia; thus, whether sulfonylureas affect the outcomes of stroke in patients with T2DM needs to be further studied. In our study, streptozotocin (STZ)-induced diabetic mice subjected to transient middle cerebral artery occlusion (MCAO) showed larger areas of brain damage and poorer behavioral outcomes. Blocking the KATP channel by tolbutamide increased neuronal injury induced by oxygen-glucose deprivation (OGD) in vitro and permanent MCAO (pMCAO) in vivo. Activating the KATP channel by diazoxide reduced the effects of both the OGD and pMCAO. Western blot analysis in STZ mouse brains indicated an early increase in protein levels of N-methyl-d-aspartate receptor 2B and postsynaptic density protein-95, followed by a decrease in phosphorylation of glycogen synthase kinase 3ß. Our systematic meta-analysis indicated that patients with T2DM treated with sulfonylureas had a higher odds ratio for stroke morbidity than those who received comparator drugs. Taken together, these results suggest that sulfonylurea treatment in patients with T2DM may inhibit the neuroprotective effects of KATP channels and increase the risk of stroke.

Neuroprotective Effects of a PSD-95 Inhibitor in Neonatal Hypoxic-Ischemic Brain Injury.

The postsynaptic density-95 inhibitor NA-1 uncouples NMDA glutamate receptors from downstream neurotoxic signaling pathways without affecting normal glutamate receptor function. NA-1 attenuates NMDA receptor-mediated neuronal cell death after stroke in multiple models and species. However, its efficacy in providing neuroprotection in models of neonatal hypoxic-ischemic brain injury has not yet been tested. In this study, a modified version of the Rice-Vannucci method for the induction of neonatal hypoxic-ischemic brain injury was performed on postnatal day 7 mouse pups. Animals received a single dose of NA-1 intraperitoneally either before or after right common carotid artery occlusion. All experiments were performed in a blinded manner. Infarct volumes were measured 1 and 7 days after the injury, while behavioral tests were conducted 1, 3, and 7 days after injury. Administration of NA-1 before right common carotid artery occlusion or immediately after ischemia significantly reduced infarct volume and improved neurobehavioral outcomes 1, 3, and 7 days post-injury. The neuroprotection and improvement in neurobehavioral outcomes conferred by NA-1 in this mouse neonatal hypoxic-ischemic injury model imply that NA-1 will be effective in reducing neonatal stroke damage and thus could potentially serve as a therapeutic drug for prevention or treatment of neonatal stroke.

Xyloketal B suppresses glioblastoma cell proliferation and migration in vitro through inhibiting TRPM7-regulated PI3K/Akt and MEK/ERK signaling pathways.

Glioblastoma, the most common and aggressive type of brain tumors, has devastatingly proliferative and invasive characteristics. The need for finding a novel and specific drug target is urgent as the current approaches have limited therapeutic effects in treating glioblastoma. Xyloketal B is a marine compound obtained from mangrove fungus Xylaria sp. (No. 2508) from the South China Sea, and has displayed antioxidant activity and protective effects on endothelial and neuronal oxidative injuries. In this study, we used a glioblastoma U251 cell line to (1) explore the effects of xyloketal B on cell viability, proliferation, and migration; and (2) investigate the underlying molecular mechanisms and signaling pathways. MTT assay, colony formation, wound healing, western blot, and patch clamp techniques were employed. We found that xyloketal B reduced cell viability, proliferation, and migration of U251 cells. In addition, xyloketal B decreased p-Akt and p-ERK1/2 protein expressions. Furthermore, xyloketal B blocked TRPM7 currents in HEK-293 cells overexpressing TRPM7. These effects were confirmed by using a TRPM7 inhibitor, carvacrol, in a parallel experiment. Our findings indicate that TRPM7-regulated PI3K/Akt and MEK/ERK signaling is involved in anti-proliferation and migration effects of xyloketal B on U251 cells, providing in vitro evidence for the marine compound xyloketal B to be a potential drug for treating glioblastoma.

TRPM7 inhibitor carvacrol protects brain from neonatal hypoxic-ischemic injury.

BACKGROUND: Our previous study found that suppression of TRPM7 reduced neuronal death in adult rat ischemic brain injury. It was reported that carvacrol blocked TRPM7 and attenuated brain injury in an adult rat MCAO model. The effects of carvacrol on neonatal stroke remain unknown. This study investigated the effects of carvacrol on neuronal injury and behavioral impairment after hypoxia-ischemia in neonatal mice and the potential signaling pathway underlying these effects. RESULTS: Carvacrol inhibited TRPM7 current in HEK293 cells over-expressing TRPM7 and TRPM7-like current in hippocampal neurons in a dose-dependent manner. Carvacrol (>200 µM) reduced OGD-induced neuronal injury in cortical neurons. 24 hours after HI, TRPM7 protein level in the ipsilateral hemisphere was significantly higher than in the contralateral hemisphere. Carvacrol (30 and 50 mg/kg) pre-treatment reduced brain infarct volume 24 hours after HI in a dose-dependent manner. Carvacrol pre-treatment also improved neurobehavioral outcomes. Furthermore, animals pre-treated with carvacrol had fewer TUNEL-positive cells in the brain compared to vehicle-treated animals 3 days after HI. Carvacrol pre-treatment also increased Bcl-2/Bax and p-Akt/t-Akt protein ratios and decreased cleaved caspase-3 protein expression 24 hours after HI. CONCLUSIONS: Carvacrol pre-treatment protects against neonatal hypoxic-ischemic brain injury by reducing brain infarct volume, promoting pro-survival signaling and inhibiting pro-apoptotic signaling, as well as improving behavioral outcomes. The neuroprotective effect may be mediated by the inhibition of TRPM7 channel function. Carvacrol is a potential drug development target for the treatment of neonatal stroke.

Neuronal K(ATP) channels mediate hypoxic preconditioning and reduce subsequent neonatal hypoxic-ischemic brain injury.

Neonatal hypoxic-ischemic brain injury and its related illness hypoxic-ischemic encephalopathy (HIE) are major causes of nervous system damage and neurological morbidity in children. Hypoxic preconditioning (HPC) is known to be neuroprotective in cerebral ischemic brain injury. K(ATP) channels are involved in ischemic preconditioning in the heart; however the involvement of neuronal K(ATP) channels in HPC in the brain has not been fully investigated. In this study, we investigated the role of HPC in hypoxia-ischemia (HI)-induced brain injury in postnatal seven-day-old (P7) CD1 mouse pups. Specifically, TTC (2,3,5-triphenyltetrazolium chloride) staining was used to assess the infarct volume, TUNEL (Terminal deoxynucleotidyl transferase mediated dUTP nick end-labeling) to detect apoptotic cells, Western blots to evaluate protein level, and patch-clamp recordings to measure K(ATP) channel current activities. Behavioral tests were performed to assess the functional recovery after hypoxic-ischemic insults. We found that hypoxic preconditioning reduced infarct volume, decreased the number of TUNEL-positive cells, and improved neurobehavioral functional recovery in neonatal mice following hypoxic-ischemic insults. Pre-treatment with a K(ATP) channel blocker, tolbutamide, inhibited hypoxic preconditioning-induced neuroprotection and augmented neurodegeneration following hypoxic-ischemic injury. Pre-treatment with a K(ATP) channel opener, diazoxide, reduced infarct volume and mimicked hypoxic preconditioning-induced neuroprotection. Hypoxic preconditioning induced upregulation of the protein level of the Kir6.2 isoform and enhanced current activities of K(ATP) channels. Hypoxic preconditioning restored the HI-reduced PKC and pAkt levels, and reduced caspase-3 level, while tolbutamide inhibited the effects of hypoxic preconditioning. We conclude that K(ATP) channels are involved in hypoxic preconditioning-induced neuroprotection in neonatal hypoxic-ischemic brain injury. K(ATP) channel openers may therefore have therapeutic effects in neonatal hypoxic-ischemic brain injury.

Neuroprotective effects of volume-regulated anion channel blocker DCPIB on neonatal hypoxic-ischemic injury.

AIM: To evaluate the role of swelling-induced activation of volume-regulated anion channels (VRACs) in a neonatal hypoxic-ischemic injury model using the selective VRAC blocker 4-(2-butyl-6,7-dichloro-2-cyclopentyl-indan-1-on5-yl) oxobutyric acid (DCPIB). METHODS: Cerebral hypoxic-ischemic injury was induced in 7-day-old mouse pups with Rice-Vannucci method. Prior to the onset of ischemia, the animals were ip administered DCPIB (10 mg/kg). The animals were sacrificed 24 h afterwards, coronal sections of the brains were cut and the areas of infarct were examined using TTC staining and an image-analysis system. Cultured PC12 cells were subjected to oxygen-glucose deprivation (OGD) for 4 h. The cellular viability was assessed using Cell Counting Kit 8. Intracellular chloride concentration [Cl(-)](i) was measured using 6-methoxy-N-ethylquinolinium iodide. RESULTS: DCPIB-treated mice showed a significant reduction in hemispheric corrected infarct volume (26.65%±2.23%) compared to that in vehicle-treated mice (45.52%±1.45%, P<0.001). DCPIB-treated mice also showed better functional recovery as they were more active than vehicle-treated mice at 4 and 24 h post injury. In cultured PC12 cells, DCPIB (10 µmol/L) significantly reduced OGD-induced cell death. Moreover, DCPIB (20 µmol/L) blocked hypotonic-induced decrease in [Cl(-)](i) in PC12 cells of both control and OGD groups. CONCLUSION: The results further support the pathophysiological role of VRACs in ischemic brain injury, and suggest DCPIB as a potential, easily administrable agent targeting VRACs in the context of perinatal and neonatal hypoxic-ischemic brain injury.