Sub region-specific modulation of synchronous neuronal burst firing after a kainic acid insult in organotypic hippocampal cultures

<p>Abstract</p> <p>Background</p> <p>Excitotoxicity occurs in a number of pathogenic states including stroke and epilepsy. The adaptations of neuronal circuits in response to such insults may be expected to play an underlying role in pathogenesis. Synchronous neuronal firing can be induced in isolated hippocampal slices and involves all regions of this structure, thereby providing a measure of circuit activity. The effect of an excitotoxic insult (kainic acid, KA) on Mg²⁺-free-induced synchronized neuronal firing was tested in organotypic hippocampal culture by measuring extracellular field activity in CA1 and CA3.</p> <p>Results</p> <p>Within 24 hrs of the insult regional specific changes in neuronal firing patterns were evident as: (i) a dramatic <it>reduction </it>in the ability of CA3 to generate firing; and (ii) a contrasting <it>increase </it>in the frequency and duration of synchronized neuronal firing events in CA1. Two distinct processes underlie the increased propensity of CA1 to generate synchronized burst firing; a lack of ability of the CA3 region to 'pace' CA1 resulting in an increased frequency of synchronized events; and a change in the 'intrinsic' properties limited to the CA1 region, which is responsible for increased event duration. Neuronal quantification using NeuN immunoflurescent staining and stereological confocal microscopy revealed no significant cell loss in hippocampal sub regions, suggesting that changes in the properties of neurons within this region were responsible for the KA-mediated excitability changes.</p> <p>Conclusion</p> <p>These results provide novel insight into adaptation of hippocampal circuits following excitotoxic injury. KA-mediated disruption of the interplay between CA3 and CA1 clearly increases the propensity to synchronized firing in CA1.</p

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Information and Profitability Estimates: Modelling the Firm's Decision to Adopt a New Technology

This paper uses a response surface based on catastrophe theory to examine the interaction of information and profitability estimates on the firm's adoption of a new technology or innovation. As such, the paper builds on the conceptual ideas behind McCardle's (1985) work. An illustrative example using simulated data is presented to indicate how one might operationalize the key constructs for the purpose of estimating the model.technology, information, adoption, catastrophe theory, profitability

An Algorithm for Estimating Multivariate Catastrophe Models: GEMCAT II

Following the framework in Oliva et al. 1987, GEMCAT II implements a flexible method to test catastrophe models containing multivariate (i.e., latent) variables while allowing for a priori variable specifications. The system uses an efficient hybrid minimization algorithm combining the Downhill Simplex and Powell's Conjugate Gradient method. GEMCAT II is compiled in Delphi V3.0 and is sufficiently fast to allow for the use of resampling methods (bootstrap as well as jackknife) to determine the statistical significance of latent variables' indicator weights. In addition, a Pseudo-R2 index of model fit is provided, together with a test of significance, and options are included to facilitate competitive model tests of nested and non-nested catastrophe models as well as linear models. Two simulation studies are reported. Based on 61,250 simulated data sets of varying sizes, the first study addressed the effects of indicator reliability on the quality of the weight estimations, and the second dealt with the problem of false positives in model identification. The results strongly support the viability of the GEMCAT II approach over a wide range of reasonable indicator reliabilities and sample sizes. Moreover, it proved possible to distinguish reliably between cusp catastrophes and linear models based on the Pseudo-R2 values. Finally, GEMCAT II is applied to actual market data in order to demonstrate its use in an economic context. Using 34 quarters of panel data, we examine the fit of a cusp catastrophe model of organizational product adoption as applied to competing software standards in the presence of network externalities. The results are consistent with economic theory and published work on network externalities. This example also illustrates GEMCAT II's bootstrap tests for indicator weights and its options for competitive model testing.

Strategy Maps: A Spatial Representation of Intra-Industry Competitive Strategy

We introduce an integrative tool, called a strategy map, for describing the nature of a given competitive environment. The approach can also suggest specific courses of actions for competing businesses in those environments. The strength of the method is its ability to capture and communicate visually through a map the complex relations among competitive strategy variables and performance simultaneously. This article focuses on theory from the strategy field to develop a basic model that ties together the key elements in the development of any competitive strategy map. This theoretical development is followed with an examination of some of the important methodological developments in the field. The article then goes into the statistical development of the methodology. Then the maps are developed through a methodology which captures the simultaneous, multidimensional, and interrelated nature of business strategy and performance for a group of businesses within an industry. Specifically, we (a) present a multidimensional scaling methodology for describing the competitive nature of a given industry, (b) examine the necessary tradeoffs that a competitor must make in targeting its performance goals, and (c) explore the relative importance the different strategy variables have for achieving these performance goals in the given competitive environment. An empirical application using PIMS data is presented---strategy maps are derived for a mature, industrial supplier to illustrate how the method can be employed as a descriptive tool in competitive strategy. The findings are then validated for a randomly selected business.competitive analysis, business level strategy, multidimensional scaling, strategic maps