Search

BackgroundCircadian variations in the timing of the onset of stroke symptoms have been described, showing a morning excess of cardiovascular risk. To date, no differences have been found between stroke subtype and time distribution throughout the day. The present study aims to compare the seasonal and circadian rhythm of symptoms onset in ischemic, hemorrhagic, and stroke mimic patients.MethodsThis study was conducted prospectively at a hospital and involved a cohort of stroke alert patients from 2018 to 2021. Stroke subtypes were classified as ischemic stroke, intracerebral hemorrhage (ICH), transient ischemic attack (TIA), and stroke mimic. Clinical variables were recorded, and each patient was assigned to a 4-h interval of the day according to the time of onset of symptoms; unwitnessed stroke patients were analyzed separately. Seasonal changes in stroke distribution were analyzed at 3-month intervals.ResultsA total of 2,348 patients were included in this analysis (ischemic 67%, ICH 13%, mimic 16%, and TIA 3%). Regardless of stroke subtype, most of the patients were distributed between 08–12 h and 12–16 h. Significant differences were found in the time distribution depending on stroke subtype, with ICH predominating in the 4–8 h period (dawn), most of which were hypertensive, TIA in the 12–16 h period (afternoon), and stroke mimic in the 20 h period (evening). The ischemic stroke was evenly distributed throughout the different periods of the day. There were no differences in the seasonal pattern between different stroke subtypes, with winter being the one that accumulated the most cases.ConclusionThe present study showed different circadian patterns of stroke subtypes, with a predominance of ICH at dawn and stroke mimic in the afternoon. The stroke circadian rhythm resembles previous studies, with a higher incidence in the morning and a second peak in the afternoon.

The emerging field of vascular composite allotransplantation (VCA) has become a clinical reality. Building upon cutting edge understandings of transplant surgery and immunology, complex grafts such as hands and faces can now be transplanted with success. Many of the challenges that have historically been limiting factors in transplantation, such as rejection and the morbidity of immunosuppression, remain challenges in VCA. Because of the accessibility of most VCA grafts, and the highly immunogenic nature of the skin in particular, VCA has become the focal point for cross-disciplinary approaches to developing novel approaches for some of the most challenging immunological problems in transplantation, particularly the early diagnoses and assessment of rejection. This paper provides a historically oriented introduction to the field of organ transplantation and the evolution of VCA.

AbstractDetermining protein structures is crucial to understanding the mechanisms of infection and designing drugs. However, the elucidation of protein folds by crystallographic experiments can be a bottleneck in the development process. In this article, we present a probabilistic graphical model framework, conditional graphical models, for predicting protein structural motifs. It represents the structure characteristics of a structural motif using a graph, where the nodes denote the secondary structure elements, and the edges indicate the side-chain interactions between the components either within one protein chain or between chains. Then the model defines the optimal segmentation of a protein sequence against the graph by maximizing its “conditional” probability so that it can take advantages of the discriminative training approach. Efficient approximate inference algorithms using reversible jump Markov Chain Monte Carlo (MCMC) algorithm are developed to handle the resulting complex graphical models. We test our algorithm on four important structural motifs, and our method outperforms other state-of-art algorithms for motif recognition. We also hypothesize potential membership proteins of target folds from Swiss-Prot, which further supports the evolutionary hypothesis about viral folds. [ABSTRACT FROM AUTHOR]