Model predictions for anthelmintic resistance amongst Haemonchus contortus populations in southern Brazil

A computer model developed to study Ostertagia circumcincta resistance to anthelmintics in UK sheep flocks has been adapted for use with Haemonchus contortus under southern Brazilian conditions. The model simulates the effect of different anthelmintic control regimens on the year-to-year pattern of resistance in breeding ewes. The nematode control regimen most used by Brazilian sheep farmers was found to increase the frequency of genes which confer resistance from approximately 3% to 14% in an H. contortus population over a 20 year period. The effect of early versus late season anthelmintic treatment was investigated. This indicated that early season treatment would select for resistance rapidly, whereas late season treatments would not, owing to large numbers of untreated parasites accumulating at the beginning of the season. A model which can predict the development of anthelmintic resistance in parasites of ewes is a valuable tool in the understanding of the effect of different strategies on nematode control programmes and merits further consideration

Human knee joint finite element model using a two bundle anterior cruciate ligament: Validation and gait analysis

Anterior cruciate ligament (ACL) deficient individuals are at a much higher risk of developing osteoarthritis (OA) compared to those with intact ACLs, likely due to altered biomechanical loading [1]. Research indicates the ACL is comprised of two “bundles”, the anteromedial (AM) and posterolateral (PL) bundles [2]. Although the function of both bundles is to restrain anterior tibial translation (ATT), each bundle has their own distinct range of knee flexion where they are most effective [3]. Articular cartilage contact stress measurements are difficult to measure in vivo. An alternative approach is to use knee joint finite element models (FEMs) to predict soft tissue stresses and strains throughout the knee. Initial and boundary conditions for these FEMs may be determined from knee joint kinematics estimated from motion analysis experiments. However, there is a lack of knee joint FEMs which include both AM and PL bundles to predict changes to articular cartilage contact pressures resulting from ACL injuries. The purpose of this study is to develop and validate a knee joint FEM using both AM and PL bundles and subsequently perform a gait analysis of varying ACL injuries

Using OpenSim to predict knee joint moments during cycling

Cycling is a relatively low impact activity conventionally recommended as a rehabilitative or fitness sustaining exercise for patients at a high risk for knee osteoarthritis (OA) [1,2]. Expanding our understanding of knee joint loads is necessary to develop and improve evidence-based prescriptions for cycling as a rehabilitative and fitness therapy that limits the risk for knee OA. OpenSim (www.simtk.org) is an open source biomechanical analysis software that can partition predictions of external joint loads (or net muscle moments) into muscle and joint contact loads [3]. Joint contact loads more accurately represent cartilage tissue loading and hence risk for cartilage damage and/or OA [4]. As a first step towards predicting knee joint contact loads during cycling, we hypothesized that OpenSim can predict external knee joint moments that are consistent with published data [5,6]. To address this hypothesis, we conducted cycling experiments and used OpenSim’s scale tool, inverse kinematics (IK) solver, and inverse dynamics (ID) solver to model the recorded activity

Identifying molecular mediators of the relationship between body mass index and endometrial cancer risk:a Mendelian randomization analysis

Endometrial cancer is the most common gynaecological cancer in high-income countries. Elevated body mass index (BMI) is an established modifiable risk factor for this condition and is estimated to confer a larger effect on endometrial cancer risk than any other cancer site. However, the molecular mechanisms underpinning this association remain unclear. We used Mendelian randomization (MR) to evaluate the causal role of 14 molecular risk factors (hormonal, metabolic and inflammatory markers) in endometrial cancer risk. We then evaluated and quantified the potential mediating role of these molecular traits in the relationship between BMI and endometrial cancer using multivariable MR. Methods Genetic instruments to proxy 14 molecular risk factors and BMI were constructed by identifying single-nucleotide polymorphisms (SNPs) reliably associated (P < 5.0 × 10−8) with each respective risk factor in previous genome-wide association studies (GWAS). Summary statistics for the association of these SNPs with overall and subtype-specific endometrial cancer risk (12,906 cases and 108,979 controls) were obtained from a GWAS meta-analysis of the Endometrial Cancer Association Consortium (ECAC), Epidemiology of Endometrial Cancer Consortium (E2C2) and UK Biobank. SNPs were combined into multi-allelic models and odds ratios (ORs) and 95% confidence intervals (95% CIs) were generated using inverse-variance weighted random-effects models. The mediating roles of the molecular risk factors in the relationship between BMI and endometrial cancer were then estimated using multivariable MR

ML-based Real-Time Control at the Edge: An Approach Using hls4ml

This study focuses on implementing a real-time control system for a particle accelerator facility that performs high energy physics experiments. A critical operating parameter in this facility is beam loss, which is the fraction of particles deviating from the accelerated proton beam into a cascade of secondary particles. Accelerators employ a large number of sensors to monitor beam loss. The data from these sensors is monitored by human operators who predict the relative contribution of different sub-systems to the beam loss. Using this information, they engage control interventions. In this paper, we present a controller to track this phenomenon in real-time using edge-Machine Learning (ML) and support control with low latency and high accuracy. We implemented this system on an Intel Arria 10 SoC. Optimizations at the algorithm, high-level synthesis, and interface levels to improve latency and resource usage are presented. Our design implements a neural network, which can predict the main source of beam loss (between two possible causes) at speeds up to 575 frames per second (fps) (average latency of 1.74 ms). The practical deployed system is required to operate at 320 fps, with a 3ms latency requirement, which has been met by our design successfully

The structural properties of sexual fantasies for sexual offenders : a preliminary model

While the phenomenon of sexual fantasy has been researched extensively, little contemporary inquiry has investigated the structural properties of sexual fantasy within the context of sexual offending. In this study, a qualitative analysis was used to develop a descriptive model of the phenomena of sexual fantasy during the offence process. Twenty-four adult males convicted of sexual offences provided detailed retrospective descriptions of their thoughts, emotions and behaviours&mdash;before, during and after their offences. A data-driven approach to model development, known as Grounded Theory, was undertaken to analyse the interview transcripts. A model was developed to elucidate the structural properties of sexual fantasy in the process of sexual offending, as well as the physiological and psychological variables associated with it. The Sexual Fantasy Structural Properties Model (SFSPM) comprises eight categories that describe various properties of sexual fantasy across the offence process. These categories are: origin, context, trigger, perceptual modality, clarity, motion, intensity and emotion. The strengths of the SFSPM are discussed and its clinical implications are reviewed. Finally, the limitations of the study are presented and future research directions discussed

Hypermethioninaemia due to methionine adenosyltransferase I/III (MAT I/III) deficiency: diagnosis in an expanded neonatal screening programme

The Expanded Newborn Screening Program (MS/MS) in the region of Galicia (NW Spain) was initiated in 2000 and includes the measurement of methionine levels in dried blood spots. Between June 2000 and June 2007, 140 818 newborns were analysed, and six cases of persistent hypermethioninaemia were detected: one homocystinuria due to cystathionine β-synthase (CβS) deficiency, and five methionine adenosyltransferase I/III (MAT I/III) deficiencies. The five cases of MAT I/III deficiency represent an incidence of 1/28 163 newborns. In these five patients, methionine levels in dried blood spots ranged from 50 to 147 μmol/L. At confirmation of the persistence of the hypermethioninaemia in a subsequent plasma sample, plasma methionine concentrations were moderately elevated in 4 of the 5 patients (mean 256 μmol/L), while total homocysteine (tHcy) was normal; the remaining patient showed plasma methionine of 573 μmol/L and tHcy of 22.8 μmol/L. All five patients were heterozygous for the same dominant mutation, R264H in the MAT1A gene. With a diet not exceeding recommended protein requirements for their age, all patients maintained methionine levels below 300 μmol/L. Currently, with a mean of 2.5 years since diagnosis, the patients are asymptomatic and show developmental quotients within the normal range. Our results show a rather high frequency of hypermethioninaemia due to MAT I/III deficiency in the Galician neonatal population, indicating a need for further studies to evaluate the impact of persistent isolated hypermethioninaemia in neonatal screening programmes