Myocardial hypothermia increases autophagic flux, mitochondrial mass and myocardial function after ischemia-reperfusion injury.

Animal studies have demonstrated beneficial effects of therapeutic hypothermia on myocardial function, yet exact mechanisms remain unclear. Impaired autophagy leads to heart failure and mitophagy is important for mitigating ischemia/reperfusion injury. This study aims to investigate whether the beneficial effects of therapeutic hypothermia are due to preserved autophagy and mitophagy. Under general anesthesia, the left anterior descending coronary artery of 19 female farm pigs was occluded for 90 minutes with consecutive reperfusion. 30 minutes after reperfusion, we performed pericardial irrigation with warm or cold saline for 60 minutes. Myocardial tissue analysis was performed one and four weeks after infarction. Therapeutic hypothermia induced a significant increase in autophagic flux, mitophagy, mitochondrial mass and function in the myocardium after infarction. Cell stress, apoptosis, inflammation as well as fibrosis were reduced, with significant preservation of systolic and diastolic function four weeks post infarction. We found similar biochemical changes in human samples undergoing open chest surgery under hypothermic conditions when compared to the warm. These results suggest that autophagic flux and mitophagy are important mechanisms implicated in cardiomyocyte recovery after myocardial infarction under hypothermic conditions. New therapeutic strategies targeting these pathways directly could lead to improvements in prevention of heart failure

Waiting Time for Specialist Consultation and Visit Requested in the Emergency Department; a Cross-Sectional Study

Introduction: Waiting time in the hospital directly affects the quality of healthcare providing centers. One of the waiting times in hospital is the time spent waiting for receiving various consultations and visits requested by emergency medicine specialists from specialist services. Objective: The present study was designed and performed to assess the waiting times for receiving specialist visits and consultations requested in the emergency department based on the corresponding service in a referral hospital in Isfahan, Iran. Method: In the present cross-sectional study, patients presenting to emergency department of Dr. Shariati Hospital, Isfahan, Iran, from October 2017 to March 2018, who were in need of visit or consultation from other specialist services based on the opinion of the emergency medicine specialist, were studied. By attending the patients' bedside, the researcher filled out a checklist consisting of demographic data and waiting time of the patients and other probable related factors. Finally, raw data were entered to the computer and after correction of errors were statistically analyzed via SPSS software. Results: Overall, 400 patients with the mean age of 53.3 ± 24.3 years were included in the study, 58.8% of which were male. Mean waiting time for receiving a visit or consultation among the studied patients was 242.0 ± 202.4 (min: 5 and max: 1200) minutes. Mean waiting time for a visit or consultation did not significantly correlate with the corresponding physician being resident or on-call. However, it showed a statistically significant correlation with triage level (p = 0.013), work shift (p = 0.000), type of service requested/the specialist service asked for a consultation or visit (p = 0.049), and the consultation or visit being emergent or non-emergent (p = 0.000). In addition, emergent visits or consultations by on-call physicians had been performed significantly faster than those by resident physicians; while non-emergent visits or consultations by resident physicians had been performed significantly faster than those by on-call physicians (p = 0.001). Conclusion: The results of the present study showed that patients with triage level 2, emergent visit of consultation and a visit or consultation request in the morning or evening shift wait a shorter time for receiving the visit or consultation. In addition, neurosurgery, nephrology, and pediatrics services had the shortest waiting times, while gastroenterology, gynecology, and infectious disease services had the longest waiting times for giving the visit or consultation requested from them

Paraunitary oversampled filter bank design for channel coding

Oversampled filter banks (OSFBs) have been considered for channel coding, since their redundancy can be utilised to permit the detection and correction of channel errors. In this paper, we propose an OSFB-based channel coder for a correlated additive Gaussian noise channel, of which the noise covariance matrix is assumed to be known. Based on a suitable factorisation of this matrix, we develop a design for the decoder's synthesis filter bank in order to minimise the noise power in the decoded signal, subject to admitting perfect reconstruction through paraunitarity of the filter bank. We demonstrate that this approach can lead to a significant reduction of the noise interference by exploiting both the correlation of the channel and the redundancy of the filter banks. Simulation results providing some insight into these mechanisms are provided

Report From the American Society of Transplantation Conference on Donor Heart Selection in Adult Cardiac Transplantation in the United States

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138918/1/ajt14354.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138918/2/ajt14354_am.pd

Purchase prediction and item suggestion based on HTTP sessions in absence of user information

In this paper, the task is to determine whether an HTTP session buys an item, or not, and if so, which items will be purchased. An HTTP session is a series of item clicks. A session has type buy, if it buys at least one item, or non- buy otherwise. Accordingly, data is in (session, item, time) format, which tells us when an item is clicked or purchased during an HTTP session. The main challenge comes from the fact that (1) user information is not available for clicked or purchased items, which are merely tagged with anony- mous sessions, and (2) suggestions are highly temporal as they are suggested to sessions instead of users. In other words, users which are stable and identi ed are replaced with sessions which are temporal and anonymous. In this work, we propose a feature-based system that predicts the type of a session, and determines which items are going to be purchased. As the main contribution, we have modeled ses- sions separated by the number of unique items, prioritized item-features based on the number of clicks, and utilized cu- mulative statistics of similar items to attenuate the sparsity problem

Community detection in signed networks: The role of negative ties in different scales

Extracting community structure of complex network systems has many applications from engineering to biology and social sciences. There exist many algorithms to discover community structure of networks. However, it has been significantly under-explored for networks with positive and negative links as compared to unsigned ones. Trying to fill this gap, we measured the quality of partitions by introducing a Map Equation for signed networks. It is based on the assumption that negative relations weaken positive flow from a node towards a community, and thus, external (internal) negative ties increase the probability of staying inside (escaping from) a community. We further extended the Constant Potts Model, providing a map spectrum for signed networks. Accordingly, a partition is selected through balancing between abridgment and expatiation of a signed network. Most importantly, multi-scale spectrum of signed networks revealed how informative are negative ties in different scales, and quantified the topological placement of negative ties between dense positive ones. Moreover, an inconsistency was found in the signed Modularity: as the number of negative ties increases, the density of positive ties is neglected more. These results shed lights on the community structure of signed networks

Mesoscopic analysis of online social networks: the role of negative ties

A class of networks are those with both positive and negative links. In this manuscript, we studied the interplay between positive and negative ties on mesoscopic level of these networks, i.e., their community structure. A community is considered as a tightly interconnected group of actors; therefore, it does not borrow any assumption from balance theory and merely uses the well-known assumption in the community detection literature. We found that if one detects the communities based on only positive relations (by ignoring the negative ones), the majority of negative relations are already placed between the communities. In other words, negative ties do not have a major role in community formation of signed networks. Moreover, regarding the internal negative ties, we proved that most unbalanced communities are maximally balanced, and hence they cannot be partitioned into k nonempty sub-clusters with higher balancedness (k≥2). Furthermore, we showed that although the mediator triad ++- (hostile-mediator-hostile) is underrepresented, it constitutes a considerable portion of triadic relations among communities. Hence, mediator triads should not be ignored by community detection and clustering algorithms. As a result, if one uses a clustering algorithm that operates merely based on social balance, mesoscopic structure of signed networks significantly remains hidden