The Effects of Mergers and Acquisitions on Acquiring Banks’ Contribution to Systemic Risk

This paper is the first to examine the effects of international bank mergers and acquisitions on acquirers' contribution to systemic risk covering the period from 1998 to 2015. Our sample consists of 608 international bank mergers, involved domestic and cross-border deals as well as conglomerate and non-conglomerate mergers. Using the Marginal Expected Shortfall (as in Acharya et al., 2017) as well as Conditional Value-at-Risk (as in Adrian and Brunnermeier, 2016) as systemic risk measurements, we find that on average, mergers do not impact on the acquiring banks’ contribution to systemic risk regardless of the increased potential for risk diversification exhibited by cross-border and cross-industry bank mergers. Determinants that contributes to the decrease in acquirers’ systemic risk include product diversifying deals, deals conducted in a more concentrated banking system and a stable political environment. Whereas, for deals financed by cash only and much smaller compared to acquirers as well as involved private targets, acquirers' contribution to systemic risk increase after the merger

Connectivity in MEG resting-state networks increases after resective surgery for low-grade glioma and correlates with improved cognitive performance☆

Purpose Low-grade glioma (LGG) patients often have cognitive deficits. Several disease- and treatment related factors affect cognitive processing. Cognitive outcome of resective surgery is unpredictable, both for improvement and deterioration, especially for complex domains such as attention and executive functioning. MEG analysis of resting-state networks (RSNs) is a good candidate for presurgical prediction of cognitive outcome. In this study, we explore the relation between alterations in connectivity of RSNs and changes in cognitive processing after resective surgery, as a stepping stone to ultimately predict postsurgical cognitive outcome. Methods: Ten patients with LGG were included, who had no adjuvant therapy. MEG recording and neuropsychological assessment were obtained before and after resective surgery. MEG data were recorded during a no-task eyes-closed condition, and projected to the anatomical space of the AAL atlas. Alterations in functional connectivity, as characterized by the phase lag index (PLI), within the default mode network (DMN), executive control network (ECN), and left- and right-sided frontoparietal networks (FPN) were compared to cognitive changes. Results: Lower alpha band DMN connectivity was increased after surgery, and this increase was related to improved verbal memory functioning. Similarly, right FPN connectivity was increased after resection in the upper alpha band, which correlated with improved attention, working memory and executive functioning. Discussion Increased alpha band RSN functional connectivity in MEG recordings correlates with improved cognitive outcome after resective surgery. The mechanisms resulting in functional connectivity alterations after resection remain to be elucidated. Importantly, our findings indicate that connectivity of MEG RSNs may be used for presurgical prediction of cognitive outcome in future studies

The Jacob2 Lectin of the Entamoeba histolytica Cyst Wall Binds Chitin and Is Polymorphic

For many years, we and others have used cysts of Entamoeba invadens (Ei), a reptilian parasite, to model the infectious and diagnostic cysts of the human pathogen Entamoeba histolytica (Eh). The Ei cyst wall is composed of chitin fibrils, as well as Jacob and Jessie lectins that have unique chitin-binding domains. Our recent results suggest a “wattle and daub” model of the Ei cyst wall, where the wattle or sticks (chitin fibrils bound by multivalent Jacob lectins) is constructed prior to the addition of the mortar or daub (self-aggregating Jessie3 lectins). Here we “humanize” the Ei model of the cyst wall with four findings. First, a recombinant Eh Jacob2 lectin, which has three predicted chitin-binding domains surrounding a large spacer domain, binds chitin beads. Second, polymorphisms in the spacer domain of EhJacob2 discriminate clinical isolates of Entamoeba. Third, chitinase, Jacob2 lectin, and Jessie3 lectin are present in cyst walls of clinical isolates of Entamoeba. Finally, numerous sera from patients infected with Entamoeba recognize recombinant Eh Jacob1 and Jessie3 lectins

Kidney Transplantation From Donors With Acute Kidney Injury: Are the Concerns Justified? A Systematic Review and Meta-Analysis.

Renal transplantation improves quality of life and prolongs survival in patients with end-stage kidney disease, although challenges exist due to the paucity of suitable donor organs. This has been addressed by expanding the donor pool to include AKI kidneys. We aimed to establish whether transplanting such kidneys had a detrimental effect on graft outcome. The primary aim was to define early outcomes: delayed graft function (DGF) and primary non-function (PNF). The secondary aims were to define the relationship to acute rejection, allograft survival, eGFR and length of hospital stay (LOS). A systematic literature review and meta-analysis was conducted on the studies reporting the above outcomes from PubMed, Embase, and Cochrane Library databases. This analysis included 30 studies. There is a higher risk of DGF in the AKI group (OR = 2.20, p p = 0.98), acute rejection (OR 1.29, p = 0.08), eGFR decline (p = 0.05) and prolonged LOS (p = 0.11). The odds of allograft survival are similar (OR 0.95, p = 0.54). Transplanting kidneys from donors with AKI can lead to satisfactory outcomes. This is an underutilised resource which can address organ demand

Raising awareness of unspecified living kidney donation: An ELPAT

Background: Living donor kidney transplantation (LDKT) is the preferred treatment for patients with end-stage renal disease and unspecified living kidney donation is morally justified. Despite the excellent outcomes of LDKT, unspecified kidney donation (UKD) is limited to a minority of European countries due to legal constraints and moral objections. Consequently, there are significant variations in practice and approach between countries and the contribution of UKD is undervalued. Where UKD is accepted as routine, an increasing number of patients in the kidney exchange programme are successfully transplanted when a 'chain' of transplants is triggered by a single unspecified donor. By expanding the shared living donor pool, the benefit of LDKT is extended to patients who do not have their own living donor because a recipient on the national transplant list always completes the chain. Is there a moral imperative to increase the scope of UKD and how could this be achieved? Methods: An examination of the literature and individual country practices was performed to identify the limitations on UKD in Europe and recommend strategies to increase transplant opportunities. Results: Primary limitations to UKD, key players and their roles and responsibilities were identified. Conclusions: Raising awareness to encourage the public to volunteer to donate is appropriate and desirable to increase UKD. Recommendations are made to provide a framework for increasing awareness and engagement in UKD. The public, healthcare professionals, policy makers and society and religious leaders have a role to play in creating an environment for change

Outcome prediction of electroconvulsive therapy for depression

Introduction: We developed and tested a Bayesian network(BN) model to predict ECT remission for depression, with non-response as a secondary outcome. Methods: We performed a systematic literature search on clinically available predictors. We combined these predictors with variables from a dataset of clinical ECT trajectories (performed in the University Medical Center Utrecht) to create priors and train the BN. Temporal validation was performed in an independent sample. Results: The systematic literature search yielded three meta-analyses, which provided prior knowledge on outcome predictors. The clinical dataset consisted of 248 treatment trajectories in the training set and 44 trajectories in the test set at the same medical center. The AUC for the primary outcome remission estimated on an independent validation set was 0.686 (95%CI 0.513–0.859) (AUC values of 0.505 – 0.763 observed in 5-fold cross validation of the model within the train set). Accuracy 0.73 (balanced accuracy 0.67), sensitivity 0.55, specificity 0.79, after temporal validation in the independent sample. Prior literature information marginally reduced CI width. Discussion: A BN model comprised of prior knowledge and clinical data can predict remission of depression after ECT with reasonable performance. This approach can be used to make outcome predictions in psychiatry, and offers a methodological framework to weigh additional information, such as patient characteristics, symptoms and biomarkers. In time, it may be used to improve shared decision-making in clinical practice

Single-channel qEEG characteristics distinguish delirium from no delirium, but not postoperative from non-postoperative delirium

OBJECTIVE: This exploratory study examined quantitative electroencephalography (qEEG) changes in delirium and the use of qEEG features to distinguish postoperative from non-postoperative delirium. METHODS: This project was part of the DeltaStudy, a cross-sectional,multicenterstudy in Intensive Care Units (ICUs) and non-ICU wards. Single-channel (Fp2-Pz) four-minutes resting-state EEG was analyzed in 456 patients. After calculating 98 qEEG features per epoch, random forest (RF) classification was used to analyze qEEG changes in delirium and to test whether postoperative and non-postoperative delirium could be distinguished. RESULTS: An area under the receiver operatingcharacteristic curve (AUC) of 0.76 (95% Confidence Interval (CI) 0.71-0.80) was found when classifying delirium with a sensitivity of 0.77 and a specificity of 0.63 at the optimal operating point. The classification of postoperative versus non-postoperative delirium resulted in an AUC of 0.50 (95%CI 0.38-0.61). CONCLUSIONS: RF classification was able to discriminate delirium from no delirium with reasonable accuracy, while also identifying new delirium qEEG markers like autocorrelation and theta peak frequency. RF classification could not distinguish postoperative from non-postoperative delirium. SIGNIFICANCE: Single-channel EEG differentiates between delirium and no delirium with reasonable accuracy. We found no distinct EEG profile for postoperative delirium, which may suggest that delirium is one entity, whether it develops postoperatively or not