Entropy for the Brain and Applied Computation

An understanding of the interplay between the brain region and the state of consciousness and the evolution of brain complexity, regarded as an entropy-enhancing process, has recently been proposed, leading to an increase in the space of states that can be visited, and to the accessibility of new channels. Nowadays, nonlinear and complex system theories are considered promising candidates for analyzing the principles of operation of neural networks and their entropic content. The concept of computational entropy, for example, has been utilized in cryptographic primitives, namely, in cryptographic algorithms that are used to create cryptographic protocols in computer security systems

Breastfeeding and transmission of cytomegalovirus to preterm infants. Case report and kinetic of CMV-DNA in breast milk

<p>Abstract</p> <p>Background</p> <p>Breastfeeding has a major impact on CMV epidemiology. Postnatal CMV reactivation's incidence during lactation is nearby the maternal seroprevalence. Although perinatal CMV infection has practically no consequences in term newborn, it may cause, in some cases, a severe symptomatic disease in preterm newborns.</p> <p>The aims of the present study are to evaluate the rate and clinical expression of CMV infection breast milk transmitted in preterm infants and to check the safety of the freezing treated breast milk.</p> <p>Methods</p> <p>The study included fifty-seven preterm infants and their CMV seropositive mothers. Fresh breast milk samples have been collected from 1^stto 9^thpostpartum week. Both fresh breast milk and 72, 96, 120 hours frozen samples have been examined, checking the presence of CMV; urine samples have been tested too.</p> <p>Results</p> <p>70.2% of tested mothers showed reactivation of the infection, and CMV-positive breast milk during the six weeks postpartum has been found. However, only one infant was infected by CMV, developing hepatic affection concomitantly with a multi-system involvement, as shown CMV DNA detection in urine, saliva, blood, gastric aspirate, and stools.</p> <p>Conclusion</p> <p>Freezing breast milk at -20°C and pasteurization may respectively reduce or eliminate the viral load.</p

Transcriptome analysis of human primary endothelial cells (HUVEC) from umbilical cords of gestational diabetic mothers reveals candidate sites for an epigenetic modulation of specific gene expression.

Within the complex pathological picture associated to diabetes, high glucose (HG) has ". per se" effects on cells and tissues that involve epigenetic reprogramming of gene expression. In fetal tissues, epigenetic changes occur genome-wide and are believed to induce specific long term effects. Human umbilical vein endothelial cells (HUVEC) obtained at delivery from gestational diabetic women were used to study the transcriptomic effects of chronic hyperglycemia in fetal vascular cells using Affymetrix microarrays. In spite of the small number of samples analyzed (n=6), genes related to insulin sensing and extracellular matrix reorganization were found significantly affected by HG. Quantitative PCR analysis of gene promoters identified a significant differential DNA methylation in TGFB2. Use of Ea.hy926 endothelial cells confirms data on HUVEC. Our study corroborates recent evidences suggesting that epigenetic reprogramming of gene expression occurs with persistent HG and provides a background for future investigations addressing genomic consequences of chronic HG. © 2014 Elsevier Inc

Culture-negative infective endocarditis (CNIE): impact on postoperative mortality

AbstractIntroductionPoor postoperative outcomes have been reported after surgery for infective endocarditis (IE). Whether the absence of positive cultures impacts the prognosis remains a matter of discussion. The aim of this study was to evaluate the impact of negative cultures on the prognosis of surgically treated IE.MethodsThis was a single-center, retrospective study. From January 2000 to June 2019, all patients who underwent valvular surgery for IE were included in the study. The primary endpoint was early postoperative mortality. A covariate balancing propensity score was developed to minimize the differences between the culture-positive IE (CPIE) and culture-negative IE (CNIE) cohorts. Using the estimated propensity scores as weights, an inverse probability treatment weighting (IPTW) model was built to generate a weighted cohort. Then, to adjust for confounding related to CPIE and CNIE, a doubly robust method that combines regression model with IPTW by propensity score was adopted to estimate the causal effect of the exposure on the outcome.ResultsDuring the study period, 327 consecutive patients underwent valvular repair/replacement with the use of cardiopulmonary bypass and cardioplegic cardiac arrest for IE. Their mean age was 61.4 ± 15.4 years, and 246 were males (75.2%). Native valve IE and prosthetic valve IE accounted for 87.5% and 12.5% of cases, respectively. Aortic (182/327, 55.7%) and mitral valves (166/327, 50.8%) were mostly involved; 20.5% of isolated mitral valve diseases were repaired (22/107 patients). The tricuspid valve was involved in 10 patients (3.3%), and the pulmonary valve in 1 patient (<1%). Fifty-nine patients had multiple-valve disease (18.0%). Blood cultures were negative in 136/327 (41.6 %). A higher postoperative mortality was registered in CNIE than in CPIE patients (19% vs 9%, respectively, p = 0.01). The doubly robust analysis after IPTW by propensity score showed CNIE to be associated with early postoperative mortality (odds ratio 2.10; 95% CI, 1.04–4.26, p = 0.04).ConclusionsIn our cohort, CNIE was associated with a higher early postoperative mortality in surgically treated IE patients after dedicated adjustment for confounding. In this perspective, any effort to improve preoperative microbiological diagnosis, thus allowing targeted therapeutic initiatives, might lead to overall better postoperative outcomes in surgically treated IE

Nahoum Index in Brachyfacial Patients: A Pilot Study

Objective:Our aim is to test the Nahoum Index as a support in the cephalometric study of vertical dimension and therapeutic orientation in adult patients suffering from Class II malocclusion, deep bite, or short face syndrome.Methods:Twenty-three patients with molar Class II and an overbite >4 mm were stratified into two groups: orthodontic (G2) and surgical orthodontic (G1). The ANB angle and Nahoum Index were calculated for cephalometric tracing pre- and post-treatment. The difference between the ANB and Nahoum Index values were analyzed using the Statistical Package for the Social Sciences software.Results:In G1, the Nahoum Index decreased from 0.954 to 0.797, and the ANB angle decreased from 5.2° to 3.2°. In G2, the Nahoum Index decreased from 0.825 to 0.817, and the ANB angle decreased from 4.4° to 4°.Conclusion:In G1, the difference between before and after treatment was significant for the Nahoum Index only. The difference between before and after values was not significant in the G2 group. It is possible to indicate the Nahoum Index of 0.934 as the limit value in case of which a patient may be treated with orthodontics only. This limit is the opposite of the limit proposed by Nahoum for vertical excess cases and respect the same interval. Therefore, we can consider the range 0.81-0.934 to indicate borderline patients, and >0.934 to indicate surgical patients. If the ratio is close to the normal value as 0.81, the treatment will be orthodontic; if it is further increased, the treatment will be surgical

Deep learning for necrosis detection using canine perivascular wall tumour whole slide images

Necrosis seen in histopathology Whole Slide Images is a major criterion that contributes towards scoring tumour grade which then determines treatment options. However conventional manual assessment suffers from inter-operator reproducibility impacting grading precision. To address this, automatic necrosis detection using AI may be used to assess necrosis for final scoring that contributes towards the final clinical grade. Using deep learning AI, we describe a novel approach for automating necrosis detection in Whole Slide Images, tested on a canine Soft Tissue Sarcoma (cSTS) data set consisting of canine Perivascular Wall Tumours (cPWTs). A patch-based deep learning approach was developed where different variations of training a DenseNet-161 Convolutional Neural Network architecture were investigated as well as a stacking ensemble. An optimised DenseNet-161 with post-processing produced a hold-out test F1-score of 0.708 demonstrating state-of-the-art performance. This represents a novel first-time automated necrosis detection method in the cSTS domain as well specifically in detecting necrosis in cPWTs demonstrating a significant step forward in reproducible and reliable necrosis assessment for improving the precision of tumour grading