Molecular and biochemical evaluation of oxidative effects of cord blood CD34+ MPs on hematopoietic cells.

A graft source for allogeneic hematopoietic stem cell transplantation is umbilical cord blood, which contains umbilical cord blood mononuclear cells (MNCs and mesenchymal stem cells, both an excellent source of extracellular microparticles (MPs). MPs act as cell communication mediators, which are implicated in reactive oxygen species formation or detoxification depending on their origin. Oxidative stress plays a crucial role in both the development of cancer and its treatment by triggering apoptotic mechanisms, in which CD34+ cells are implicated.

Review: Endometrial function in pregnancy establishment in cattle.

The endometrium is fundamentally required for successful pregnancy in ruminants and species where the posthatching conceptus undergoes a protracted elongation and peri-implantation phase of pregnancy. Moreover, there are substantial waves of pregnancy loss during this pre- and peri-implantation period of pregnancy the precise source of which has not been clearly defined i.e.

Beyond Supervised Learning for Pervasive Healthcare.

The integration of machine/deep learning and sensing technologies is transforming healthcare and medical practice. However, inherent limitations in healthcare data, namely scarcity, quality, and heterogeneity, hinder the effectiveness of supervised learning techniques which are mainly based on pure statistical fitting between data and labels. In this article, we first identify the challenges present in machine learning for pervasive healthcare and we then review the current trends beyond fully supervised learning that are developed to address these three issues.

Development of a Semiautomated Database for Patients With Adult Congenital Heart Disease.

Background: Databases for Congenital Heart Disease (CHD) are effective in delivering accessible datasets ready for statistical inference. Data collection hitherto has, however, been labour and time intensive and has required substantial financial support to ensure sustainability. We propose here creation and piloting of a semiautomated technique for data extraction from clinic letters to populate a clinical database.

Delirium and the risk of developing dementia: a cohort study of 12 949 patients.

Background: Delirium is an important risk factor for subsequent dementia. However, the field lacks large studies with long-term follow-up of delirium in subjects initially free of dementia to clearly establish clinical trajectories.

Methods: We undertook a retrospective cohort study of all patients over the age of 65 diagnosed with an episode of delirium who were initially dementia free at onset of delirium within National Health Service Greater Glasgow & Clyde between 1996 and 2020 using the Safe Haven database.

Prediction models in first-episode psychosis: systematic review and critical appraisal.

Background: People presenting with first-episode psychosis (FEP) have heterogenous outcomes. More than 40% fail to achieve symptomatic remission. Accurate prediction of individual outcome in FEP could facilitate early intervention to change the clinical trajectory and improve prognosis.

A Single RGB Camera Based Gait Analysis With A Mobile Tele-Robot For Healthcare.

With the increasing awareness of high-quality life, there is a growing need for health monitoring devices running robust algorithms in home environment. Health monitoring technologies enable real-time analysis of users' health status, offering long-term healthcare support and reducing hospitalization time. The propose of this work is twofold, the software focuses on the analysis of gait, which is widely adopted for joint correction and assessing any lower limb, or spinal problem.

Cross-Subject and Cross-Modal Transfer for Generalized Abnormal Gait Pattern Recognition.

For abnormal gait recognition, pattern-specific features indicating abnormalities are interleaved with the subject-specific differences representing biometric traits. Deep representations are, therefore, prone to overfitting, and the models derived cannot generalize well to new subjects. Furthermore, there is limited availability of abnormal gait data obtained from precise Motion Capture (Mocap) systems because of regulatory issues and slow adaptation of new technologies in health care.

Coupled Real-Synthetic Domain Adaptation for Real-World Deep Depth Enhancement.

Advances in depth sensing technologies have allowed simultaneous acquisition of both color and depth data under different environments. However, most depth sensors have lower resolution than that of the associated color channels and such a mismatch can affect applications that require accurate depth recovery. Existing depth enhancement methods use simplistic noise models and cannot generalize well under real-world conditions.

From Emotions to Mood Disorders: A Survey on Gait Analysis Methodology.

Mood disorders affect more than 300 million people worldwide and can cause devastating consequences. Elderly people and patients with neurological conditions are particularly susceptible to depression. Gait and body movements can be affected by mood disorders, and thus they can be used as a surrogate sign, as well as an objective index for pervasive monitoring of emotion and mood disorders in daily life.

NODDI and Tensor-Based Microstructural Indices as Predictors of Functional Connectivity.

In Diffusion Weighted MR Imaging (DWI), the signal is affected by the biophysical properties of neuronal cells and their relative placement, as well as extra-cellular tissue compartments. Typically, microstructural indices, such as fractional anisotropy (FA) and mean diffusivity (MD), are based on a tensor model that cannot disentangle the influence of these parameters. Recently, Neurite Orientation Dispersion and Density Imaging (NODDI) has exploited multi-shell acquisition protocols to model the diffusion signal as the contribution of three tissue compartments.

Consensus between pipelines in structural brain networks.

Structural brain networks may be reconstructed from diffusion MRI tractography data and have great potential to further our understanding of the topological organisation of brain structure in health and disease. Network reconstruction is complex and involves a series of processesing methods including anatomical parcellation, registration, fiber orientation estimation and whole-brain fiber tractography. Methodological choices at each stage can affect the anatomical accuracy and graph theoretical properties of the reconstructed networks, meaning applying different combinations in a network reconstruction pipeline may produce substantially different networks.

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands.

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast.

A Framework for Inter-Subject Prediction of Functional Connectivity From Structural Networks.

Functional connections between brain regions are supported by structural connectivity. Both functional and structural connectivity are estimated from in vivo magnetic resonance imaging and offer complementary information on brain organization and function. However, imaging only provides noisy measures, and we lack a good neuroscientific understanding of the links between structure and function.

Automated gaze-contingent objects elicit orientation following in 8-month-old infants.

The current study tested whether the purely amodal cue of contingency elicits orientation following behavior in 8-month-old infants. We presented 8-month-old infants with automated objects without human features that did or did not react contingently to the infants' fixations recorded by an eye tracker. We found that an object's occasional orientation toward peripheral targets was reciprocated by a congruent visual orientation following response by infants only when it had displayed gaze-contingent interactivity.

A probabilistic framework to infer brain functional connectivity from anatomical connections.

We present a novel probabilistic framework to learn across several subjects a mapping from brain anatomical connectivity to functional connectivity, i.e. the covariance structure of brain activity.

Early cortical specialization for face-to-face communication in human infants.

This study examined the brain bases of early human social cognitive abilities. Specifically, we investigated whether cortical regions implicated in adults' perception of facial communication signals are functionally active in early human development. Four-month-old infants watched two kinds of dynamic scenarios in which a face either established mutual gaze or averted its gaze, both of which were followed by an eyebrow raise with accompanying smile.

Non-rigid 2D-3D registration with catheter tip EM tracking for patient specific bronchoscope simulation.

This paper investigates the use of Active Shape Models (ASM) to capture the variability of the intra-thoracic airway tree. The method significantly reduces the dimensionality of the non-rigid 2D/3D registration problem and leads to a rapid and robust registration framework. In this study, EM tracking data has been also incorporated through a probabilistic framework for providing a statistically optimal pose given both the EM and the image-based registration measurements.

Nonrigid 2-D/3-D registration for patient specific bronchoscopy simulation with statistical shape modeling: phantom validation.

This paper presents a nonrigid registration two-dimensional/three-dimensional (2-D/3-D) framework and its phantom validation for subject-specific bronchoscope simulation. The method exploits the recent development of five degrees-of-freedom miniaturized catheter tip electromagnetic trackers such that the position and orientation of the bronchoscope can be accurately determined. This allows the effective recovery of unknown camera rotation and airway deformation, which is modelled by an active shape model (ASM).

Soft-tissue motion tracking and structure estimation for robotic assisted MIS procedures.

In robotically assisted laparoscopic surgery, soft-tissue motion tracking and structure recovery are important for intraoperative surgical guidance, motion compensation and delivering active constraints. In this paper, we present a novel method for feature based motion tracking of deformable soft-tissue surfaces in totally endoscopic coronary artery bypass graft (TECAB) surgery. We combine two feature detectors to recover distinct regions on the epicardial surface for which the sparse 3D surface geometry may be computed using a pre-calibrated stereo laparoscope.

Predictive camera tracking for bronchoscope simulation with CONDensation.

This paper exploits the use of temporal information to minimize the ambiguity of camera motion tracking in bronchoscope simulation. The condensation algorithm (Sequential Monte Carlo) has been used to propagate the probability distribution of the state space. For motion prediction, a second-order auto-regressive model has been used to characterize camera motion in a bounded lumen as encountered in bronchoscope examination.

Gaze-contingent soft tissue deformation tracking for minimally invasive robotic surgery.

The introduction of surgical robots in Minimally Invasive Surgery (MIS) has allowed enhanced manual dexterity through the use of microprocessor controlled mechanical wrists. Although fully autonomous robots are attractive, both ethical and legal barriers can prohibit their practical use in surgery. The purpose of this paper is to demonstrate that it is possible to use real-time binocular eye tracking for empowering robots with human vision by using knowledge acquired in situ.