Childhood adversity and adult health:The role of developmental timing and associations with accelerated aging

Childhood adversity has been associated with poor adult health. However, it is unclear whether timing of adversity matters in this association and whether adversity is related to poorer age-related physical health status. A representative sample of the adult Dutch population (N = 3,586, age M = 54.94, age range = 18–92) completed surveys on health and diagnoses of age-related diseases. Information about weight and fat percentage was collected using weighing scales and childhood experiences were assessed retrospectively. Adversity was associated with higher body mass index and fat percentage, more physical problems, and high cholesterol, and this association was most pronounced in individuals with experiences of adversity during early adolescence. In addition, individuals with adversity more often reported physical problems or a medical diagnosis at a younger age. This study indicates that (1) timing of exposure to adversity matters in the relationship between experienced childhood adversity and health and (2) adversity is associated with a higher prevalence of age-related diseases at earlier ages

La cura e l'incontro

Il saggio presenta la complessa evoluzione del pensiero filosofico-culturale di Riane Eisler sulla 'cura' e le sue applicazioni anche in ambito letterario

The pathophysiological basis of pharmacological interventions in CAVD

Calcific aortic valve disease (CAVD) results in aortic valve stenosis and is one of the most common cardiac diseases in both Western and developing countries. The burden of this disease is expected to increase rapidly in the future, but there are still no relevant pharmacological therapies available and aortic valve replacement remains the sole definite therapy. This review presents an overview of the most common causes of CAVD, followed by current debates and trials related to the onset and progression of this disease. Several differences and similarities between the different causes of CAVD are presented. Additionally, stages of CAVD are compared with stages in atherosclerosis. Finally, future directions for research on CAVD will be discussed

Continuous Myoelectric Prediction of Future Ankle Angle and Moment Across Ambulation Conditions and Their Transitions

A hallmark of human locomotion is that it continuously adapts to changes in the environment and predictively adjusts to changes in the terrain, both of which are major challenges to lower limb amputees due to the limitations in prostheses and control algorithms. Here, the ability of a single-network nonlinear autoregressive model to continuously predict future ankle kinematics and kinetics simultaneously across ambulation conditions using lower limb surface electromyography (EMG) signals was examined. Ankle plantarflexor and dorsiflexor EMG from ten healthy young adults were mapped to normal ranges of ankle angle and ankle moment during level overground walking, stair ascent, and stair descent, including transitions between terrains (i.e., transitions to/from staircase). Prediction performance was characterized as a function of the time between current EMG/angle/moment inputs and future angle/moment model predictions (prediction interval), the number of past EMG/angle/moment input values over time (sampling window), and the number of units in the network hidden layer that minimized error between experimentally measured values (targets) and model predictions of ankle angle and moment. Ankle angle and moment predictions were robust across ambulation conditions with root mean squared errors less than 1° and 0.04 Nm/kg, respectively, and cross-correlations (R2) greater than 0.99 for prediction intervals of 58 ms. Model predictions at critical points of trip-related fall risk fell within the variability of the ankle angle and moment targets (Benjamini-Hochberg adjusted p \u3e 0.065). EMG contribution to ankle angle and moment predictions occurred consistently across ambulation conditions and model outputs. EMG signals had the greatest impact on noncyclic regions of gait such as double limb support, transitions between terrains, and around plantarflexion and moment peaks. The use of natural muscle activation patterns to continuously predict variations in normal gait and the model’s predictive capabilities to counteract electromechanical inherent delays suggest that this approach could provide robust and intuitive user-driven real-time control of a wide variety of lower limb robotic devices, including active powered ankle-foot prostheses

Oxytocin Receptor Gene Associated with the Efficiency of Social Auditory Processing

Oxytocin has been shown to facilitate social aspects of sensory processing, thereby enhancing social communicative behaviors and empathy. Here we report that compared to the AA/AG genotypes, the presumably more efficient GG genotype of an oxytocin receptor gene polymorphism (OXTR rs53576) that has previously been associated with increased sensitivity of social processing is related to less self-reported difficulty in hearing and understanding people when there is background noise. The present result extends associations between oxytocin and social processing to the auditory and vocal domain. We discuss the relevance of our findings for autistic spectrum disorders (ASD), as ASD seems related to specific impairments in the orienting to, and selection of speech sounds from background noise, and some social processing impairments in patients with ASD have been found responsive to oxytocin treatment

Production of transmitochondrial cybrids containing naturally occurring pathogenic mtDNA variants

The human mitochondrial genome (mtDNA) encodes polypeptides that are critical for coupling oxidative phosphorylation. Our detailed understanding of the molecular processes that mediate mitochondrial gene expression and the structure–function relationships of the OXPHOS components could be greatly improved if we were able to transfect mitochondria and manipulate mtDNA in vivo. Increasing our knowledge of this process is not merely of fundamental importance, as mutations of the mitochondrial genome are known to cause a spectrum of clinical disorders and have been implicated in more common neurodegenerative disease and the ageing process. In organellar or in vitro reconstitution studies have identified many factors central to the mechanisms of mitochondrial gene expression, but being able to investigate the molecular aetiology of a limited number of cell lines from patients harbouring mutated mtDNA has been enormously beneficial. In the absence of a mechanism for manipulating mtDNA, a much larger pool of pathogenic mtDNA mutations would increase our knowledge of mitochondrial gene expression. Colonic crypts from ageing individuals harbour mutated mtDNA. Here we show that by generating cytoplasts from colonocytes, standard fusion techniques can be used to transfer mtDNA into rapidly dividing immortalized cells and, thereby, respiratory-deficient transmitochondrial cybrids can be isolated. A simple screen identified clones that carried putative pathogenic mutations in MTRNR1, MTRNR2, MTCOI and MTND2, MTND4 and MTND6. This method can therefore be exploited to produce a library of cell lines carrying pathogenic human mtDNA for further study

AI Driven Analysis of MRI To Measure Health and Disease Progression in FSHD

Facioscapulohumeral muscular dystrophy (FSHD) affects roughly 1 in 7500 individuals. While at the population level there is a general pattern of affected muscles, there is substantial heterogeneity in muscle expression across- and within-patients. There can also be substantial variation in the pattern of fat and water signal intensity within a single muscle. While quantifying individual muscles across their full length using magnetic resonance imaging (MRI) represents the optimal approach to follow disease progression and evaluate therapeutic response, the ability to automate this process has been limited. The goal of this work was to develop and optimize an artificial intelligence-based image segmentation approach to comprehensively measure muscle volume, fat fraction, fat fraction distribution, and elevated short-tau inversion recovery signal in the musculature of patients with FSHD. Intra-rater, inter-rater, and scan-rescan analyses demonstrated that the developed methods are robust and precise. Representative cases and derived metrics of volume, cross-sectional area, and 3D pixel-maps demonstrate unique intramuscular patterns of disease. Future work focuses on leveraging these AI methods to include upper body output and aggregating individual muscle data across studies to determine best-fit models for characterizing progression and monitoring therapeutic modulation of MRI biomarkers

The detection of fraud activities on the stock market through forward analysis methodology of financial discussion boards

Financial discussion boards (FDBs) have been widely used for a variety of financial knowledge exchange activities through the posting of comments on the FDBs. Popular public FDBs are prone to be used as a medium to spread false financial information due to having a larger group of audiences. Although online forums, in general, are usually integrated with anti-spam tools such as Akismet, moderation of posted contents heavily relies on human moderators. Unfortunately, popular FDBs attract many comments per day which realistically prevents human moderators from continuously monitoring and moderating possibly fraudulent contents. Such manual moderation can be extremely time-consuming. Moreover, due to the absence of useful tools, no relevant authorities are actively monitoring and handling potential financial crimes on FDBs. This paper presents a novel forward analysis methodology implemented in an Information Extraction (IE) prototype system named FDBs Miner (FDBM). This methodology aims to detect potentially illegal comments on FDBs while integrating share prices in the detection process as this helps to categorise the potentially illegal comments into different risk levels for investigation priority. The IE prototype system will first extract the public comments and per minute share prices from FDBs for the selected listed companies on London Stock Exchange (LSE). In the forward analysis process, the comments are flagged using a predefined Pump and Dump financial crime related keyword template. By only flagging the comments against the keyword template yields an average of 9.82% potentially illegal comments. It is unrealistic and unaffordable for human moderators to read these comments on a daily basis in long run. Hence, by integrating the share prices’ hikes and falls to categorise the flagged comments based on risk levels, it saves time and allows relevant authorities to prioritise and investigate into the higher risk flagged comments as it can potentially indicate real Pump and Dump crimes on FDBs