Emulation of chemical stimulus triggered head movement in the C. elegans nematode

For a considerable time, it has been the goal of computational neuroscientists to understand biological nervous systems. However, the vast complexity of such systems has made it very difficult to fully understand even basic functions such as movement. Because of its small neuron count, the C. elegans nematode offers the opportunity to study a fully described connectome and attempt to link neural network activity to behaviour. In this paper a simulation of the neural network in C. elegans that responds to chemical stimulus is presented and a consequent realistic head movement demonstrated. An evolutionary algorithm (EA) has been utilised to search for estimates of the values of the synaptic conductances and also to determine whether each synapse is excitatory or inhibitory in nature. The chemotaxis neural network was designed and implemented, using the parameterization obtained with the EA, on the Si elegans platform a state-of-the-art hardware emulation platform specially designed to emulate the C. elegans nematode

Upper Limb Posture Estimation in Robotic and Virtual Reality-based Rehabilitation.

New motor rehabilitation therapies include virtual reality (VR) and robotic technologies. In limb rehabilitation, limb posture is required to (1) provide a limb realistic representation in VR games and (2) assess the patient improvement. When exoskeleton devices are used in the therapy, the measurements of their joint angles cannot be directly used to represent the posture of the patient limb, since the human and exoskeleton kinematic models differ. In response to this shortcoming, we propose a method to estimate the posture of the human limb attached to the exoskeleton. We use the exoskeleton joint angles measurements and the constraints of the exoskeleton on the limb to estimate the human limb joints angles. This paper presents (a) the mathematical formulation and solution to the problem, (b) the implementation of the proposed solution on a commercial exoskeleton system for the upper limb rehabilitation, (c) its integration into a rehabilitation VR game platform, and (d) the quantitative assessment of the method during elbow and wrist analytic training. Results show that this method properly estimates the limb posture to (i) animate avatars that represent the patient in VR games and (ii) obtain kinematic data for the patient assessment during elbow and wrist analytic rehabilitation

Alteration of the tree–soil microbial system triggers a feedback loop that boosts holm oak decline

In anthropic savanna ecosystems from the Iberian Peninsula (i.e. dehesa), complex interactions between climate change, pathogen outbreaks and human land use are presumed to be behind the observed increase in holm oak decline. These environmental disturbances alter the plant–soil microbial continuum, which can destabilize the ecological balance that sustains tree health. Yet, little is known about the underlying mechanisms, particularly the directions and nature of the causal–effect relationships between plants and soil microbial communities. In this study, we aimed to determine the role of plant–soil feedbacks in climate-induced holm oak decline in the Iberian dehesa. Using a gradient of holm oak health, we reconstructed key soil biogeochemical cycles mediated by soil microbial communities. We used quantitative microbial element cycling (QMEC), a functional gene-array-based high-throughput technique to assess microbial functional potential in carbon, nitrogen, phosphorus and sulphur cycling. The onset of holm oak decline was positively related to the increase in relative abundance of soil microbial functional genes associated with denitrification and phosphorus mineralization (i.e. nirS3, ppx and pqqC; parameter value: 0.21, 0.23 and 0.4; p < 0.05). Structural equation model (χ2 = 32.26, p-value = 0.73), moreover, showed a negative association between these functional genes and soil nutrient availability (i.e. mainly mineral nitrogen and phosphate). Particularly, the holm oak crown health was mainly determined by the abundance of phosphate (parameter value = 0.27; p-value < 0.05) and organic phosphorus (parameter value = −0.37; p-value < 0.5). Hence, we propose a potential tree–soil feedback loop, in which the decline of holm oak promotes changes in the soil environment that triggers changes in key microbial-mediated metabolic pathways related to the net loss of soil nitrogen and phosphorus mineral forms. The shortage of essential nutrients, in turn, affects the ability of the trees to withstand the environmental stressors to which they are exposed. Read the free Plain Language Summary for this article on the Journal blog. © 2023 The Authors. Functional Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.This research has been mainly funded by the Spanish Government through the IBERYCA project (CGL2017‐84723‐P), its associated FPI scholarship BES‐2014‐067971 (ME‐V), the SMARTSOIL (PID2020‐113244GB‐C21) and SMARTHEALTH (PID2020‐113244GA‐C22) projects (both funded by MCIN/AEI/10.13039/501100011033). It has been further supported by the BC3 María de Maeztu excellence accreditation (MDM‐2017‐0714; the Spanish Government), by the BERC 2018–2021 and by the UPV/EHU‐GV IT‐1648‐22 (from the Basque Government). Additionally, this research was further supported through the grant Holistic management practices, modelling and monitoring for European forest soils—HoliSoils (EU Horizon 2020 Grant Agreement No 101000289) and the ‘Juan de la Cierva programme’ (MV; IJCI‐2017‐34640; the Spanish Government). We acknowledge the Nutrilab‐URJC (Mostoles, Spain) laboratory services for the soil chemical analyses and SGIker of UPV/EHU (Leioa, Spain) for the technical and staff support for the high‐throughput quantitative‐PCR analysis. We also thank the private owners of the dehesas for facilitating our access to their properties. We are thankful to Celia López‐Carrasco Fernández and the ‘Consejería de Agricultura, Medioambiente y Desarrollo rural de la Junta de Castilla‐La Mancha’ for all the logistical support. The ‘Tree’ icon by Hey Rabbit illustrator, from thenounproject.com were used to design the Graphical abstract. Open Access funding provided by the Univer

NewsMeSH: a new classifier designed to annotate health news with MeSH headings

Motivation In the age of big data, the amount of scientific information available online dwarfs the ability of current tools to support researchers in locating and securing access to the necessary materials. Well-structured open data and the smart systems that make the appropriate use of it are invaluable and can help health researchers and professionals to find the appropriate information by, e.g., configuring the monitoring of information or refining a specific query on a disease. Methods We present an automated text classifier approach based on the MEDLINE/MeSH thesaurus, trained on the manual annotation of more than 26 million expert-annotated scientific abstracts. The classifier was developed tailor-fit to the public health and health research domain experts, in the light of their specific challenges and needs. We have applied the proposed methodology on three specific health domains: the Coronavirus, Mental Health and Diabetes, considering the pertinence of the first, and the known relations with the other two health topics. Results A classifier is trained on the MEDLINE dataset that can automatically annotate text, such as scientific articles, news articles or medical reports with relevant concepts from the MeSH thesaurus. Conclusions The proposed text classifier shows promising results in the evaluation of health-related news. The application of the developed classifier enables the exploration of news and extraction of health-related insights, based on the MeSH thesaurus, through a similar workflow as in the usage of PubMed, with which most health researchers are familiar

System Architecture of A European Platform for Health Policy Decision Making: MIDAS

Background: Healthcare data is a rich yet underutilized resource due to its disconnected, heterogeneous nature. A means of connecting healthcare data and integrating it with additional open and social data in a secure way can support the monumental challenge policy-makers face in safely accessing all relevant data to assist in managing the health and wellbeing of all. The goal of this study was to develop a novel health data platform within the MIDAS (Meaningful Integration of Data Analytics and Services) project, that harnesses the potential of latent healthcare data in combination with open and social data to support evidence-based health policy decision-making in a privacy-preserving manner. Methods: The MIDAS platform was developed in an iterative and collaborative way with close involvement of academia, industry, healthcare staff and policy-makers, to solve tasks including data storage, data harmonization, data analytics and visualizations, and open and social data analytics. The platform has been piloted and tested by health departments in four European countries, each focusing on different region-specific health challenges and related data sources. Results: A novel health data platform solving the needs of Public Health decision-makers was successfully implemented within the four pilot regions connecting heterogeneous healthcare datasets and open datasets and turning large amounts of previously isolated data into actionable information allowing for evidence-based health policy-making and risk stratification through the application and visualization of advanced analytics. Conclusions: The MIDAS platform delivers a secure, effective and integrated solution to deal with health data, providing support for health policy decision-making, planning of public health activities and the implementation of the Health in All Policies approach. The platform has proven transferable, sustainable and scalable across policies, data and regions

Effect of Systemic Hypertension With Versus Without Left Ventricular Hypertrophy on the Progression of Atrial Fibrillation (from the Euro Heart Survey).

Hypertension is a risk factor for both progression of atrial fibrillation (AF) and development of AF-related complications, that is major adverse cardiac and cerebrovascular events (MACCE). It is unknown whether left ventricular hypertrophy (LVH) as a consequence of hypertension is also a risk factor for both these end points. We aimed to assess this in low-risk AF patients, also assessing gender-related differences. We included 799 patients from the Euro Heart Survey with nonvalvular AF and a baseline echocardiogram. Patients with and without hypertension were included. End points after 1 year were occurrence of AF progression, that is paroxysmal AF becoming persistent and/or permanent AF, and MACCE. Echocardiographic LVH was present in 33% of 379 hypertensive patients. AF progression after 1 year occurred in 10.2% of 373 patients with rhythm follow-up. In hypertensive patients with LVH, AF progression occurred more frequently as compared with hypertensive patients without LVH (23.3% vs 8.8%, p = 0.011). In hypertensive AF patients, LVH was the most important multivariably adjusted determinant of AF progression on multivariable logistic regression (odds ratio 4.84, 95% confidence interval 1.70 to 13.78, p = 0.003). This effect was only seen in male patients (27.5% vs 5.8%, p = 0.002), while in female hypertensive patients, no differences were found in AF progression rates regarding the presence or absence of LVH (15.2% vs 15.0%, p = 0.999). No differences were seen in MACCE for hypertensive patients with and without LVH. In conclusion, in men with hypertension, LVH is associated with AF progression. This association seems to be absent in hypertensive women

Progression From Paroxysmal to Persistent Atrial Fibrillation. Clinical Correlates and Prognosis

Objectives: We investigated clinical correlates of atrial fibrillation (AF) progression and evaluated the prognosis of patients demonstrating AF progression in a large population. Background: Progression of paroxysmal AF to more sustained forms is frequently seen. However, not all patients will progress to persistent AF. Methods: We included 1,219 patients with paroxysmal AF who participated in the Euro Heart Survey on AF and had a known rhythm status at follow-up. Patients who experienced AF progression after 1 year of follow-up were identified. Results: Progression of AF occurred in 178 (15%) patients. Multivariate analysis showed that heart failure, age, previous transient ischemic attack or stroke, chronic obstructive pulmonary disease, and hypertension were the only independent predictors of AF progression. Using the regression coefficient as a benchmark, we calculated the HATCH score. Nearly 50% of the patients with a HATCH score &gt;5 progressed to persistent AF compared with only 6% of the patients with a HATCH score of 0. During follow-up, patients with AF progression were more often admitted to the hospital and had more major adverse cardiovascular events. Conclusions: A substantial number of patients progress to sustained AF within 1 year. The clinical outcome of these patients regarding hospital admissions and major adverse cardiovascular events was worse compared with patients demonstrating no AF progression. Factors known to cause atrial structural remodeling (age and underlying heart disease) were independent predictors of AF progression. The HATCH score may help to identify patients who are likely to progress to sustained forms of AF in the near future. \ua9 2010 American College of Cardiology Foundation

Why Are Outcomes Different for Registry Patients Enrolled Prospectively and Retrospectively? Insights from the Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF).

Background: Retrospective and prospective observational studies are designed to reflect real-world evidence on clinical practice, but can yield conflicting results. The GARFIELD-AF Registry includes both methods of enrolment and allows analysis of differences in patient characteristics and outcomes that may result. Methods and Results: Patients with atrial fibrillation (AF) and ≥1 risk factor for stroke at diagnosis of AF were recruited either retrospectively (n = 5069) or prospectively (n = 5501) from 19 countries and then followed prospectively. The retrospectively enrolled cohort comprised patients with established AF (for a least 6, and up to 24 months before enrolment), who were identified retrospectively (and baseline and partial follow-up data were collected from the emedical records) and then followed prospectively between 0-18 months (such that the total time of follow-up was 24 months; data collection Dec-2009 and Oct-2010). In the prospectively enrolled cohort, patients with newly diagnosed AF (≤6 weeks after diagnosis) were recruited between Mar-2010 and Oct-2011 and were followed for 24 months after enrolment. Differences between the cohorts were observed in clinical characteristics, including type of AF, stroke prevention strategies, and event rates. More patients in the retrospectively identified cohort received vitamin K antagonists (62.1% vs. 53.2%) and fewer received non-vitamin K oral anticoagulants (1.8% vs . 4.2%). All-cause mortality rates per 100 person-years during the prospective follow-up (starting the first study visit up to 1 year) were significantly lower in the retrospective than prospectively identified cohort (3.04 [95% CI 2.51 to 3.67] vs . 4.05 [95% CI 3.53 to 4.63]; p = 0.016). Conclusions: Interpretations of data from registries that aim to evaluate the characteristics and outcomes of patients with AF must take account of differences in registry design and the impact of recall bias and survivorship bias that is incurred with retrospective enrolment. Clinical Trial Registration: - URL: http://www.clinicaltrials.gov . Unique identifier for GARFIELD-AF (NCT01090362)

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362