143174 research outputs found
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Modelling the effects of adult emergence on the surveillance and age distribution of medically important mosquitoes
No full textEntomological surveillance is an important component of mosquito-borne disease control. Mosquito abundance, infection prevalence and the entomological inoculation rate are the most widely reported entomological metrics, although these data are notoriously noisy and difficult to interpret. For many infections, only older mosquitoes are infectious, which is why, in part, vector control tools that reduce mosquito life expectancy have been so successful. The age structure of wild mosquitoes has been proposed as a metric to assess the effectiveness of interventions that kill adult mosquitoes, and age grading tools are becoming increasingly advanced. Mosquito populations show seasonal dynamics with temporal fluctuations. How seasonal changes in adult mosquito emergence and vector control could affect the mosquito age distribution or other important metrics is unclear. We develop stochastic mathematical models of mosquito population dynamics to show how variability in mosquito emergence causes substantial heterogeneity in the mosquito age distribution, with low frequency, positively autocorrelated changes in emergence being the most important driver of this variability. Fitting a population model to mosquito abundance data collected in experimental hut trials indicates these dynamics are likely to exist in wild Anopheles gambiae populations. Incorporating age structuring into an established compartmental model of mosquito dynamics and vector control, indicates that the use of mosquito age as a metric to assess the efficacy of vector-control tools will require an understanding of underlying variability in mosquito ages, with the mean age and other entomological metrics affected by short-term and seasonal fluctuations in mosquito emergence
Circulating prothymosin alpha and immunoglobulin G3 in acute rheumatic fever and rheumatic heart disease: a case-control study
No full textIntroduction
The lack of specific diagnostic tests for acute rheumatic fever (ARF) and its consequence rheumatic heart disease (RHD) is a key barrier to effective control of these diseases in low resource settings.
Methods
We used immunoassays to evaluate blood prothymosin alpha (PTA) and immunoglobulin G3 (IgG3) in patients with ARF, RHD and controls using serum samples from Pakistan and plasma samples from Uganda.
Results
Across both sets of samples, we found total IgG3 was significantly elevated in definite ARF (n = 24) compared to controls (n = 36), possible ARF (n = 15) and chronic RHD (n = 11). Whether measured in serum or plasma, PTA levels were similar across these groups.
Discussion
Our findings conflict with a previous report that found PTA was elevated in RHD compared to healthy controls. In contrast, while less marked than before, we found IgG3 was elevated in ARF, extending this observation to settings where the impact of RHD is greatest
Deep learning for medical ultrasound video understanding and generation
No full textMedical ultrasound imaging, particularly echocardiography, is widely used in healthcare due to its non-invasive nature and real-time capabilities. However, the application of deep learning to echocardiography faces significant challenges, including limited data availability, strict privacy regulations restricting data sharing, and inefficient clinical workflows reliant on manual interpretation. This thesis addresses these challenges by offering three major contributions that bridge deep learning and medical ultrasound imaging.
Firstly, we develop novel transformer-based architectures specifically designed for echocardiogram video analysis, enabling automated detection of end-systolic and end-diastolic frames and accurate estimation of left ventricular ejection fraction. These architectures effectively capture the temporal dynamics of cardiac motion, representing one of the first vision transformer approaches tailored for echocardiography.
Secondly, we present an evolution of generative approaches for echocardiogram synthesis, progressing from GAN-based frameworks to diffusion models and finally to cascaded video diffusion architectures. This progression yields increasingly realistic synthetic echocardiograms with precise control over ejection fraction, culminating in videos indistinguishable from real data by clinical experts.
Finally, we establish frameworks for creating privacy-preserving synthetic echocardiogram datasets that maintain both visual fidelity and real-world utility for downstream tasks. Our latent flow matching approach achieves performance parity between synthetic and real datasets when training downstream models, marking a significant breakthrough in synthetic medical image and video generation.
The methods developed throughout this thesis have broad implications for improving clinical workflows, enhancing research collaboration through privacy-preserving data sharing, and democratizing access to high-quality training data across institutions.Open Acces
Modelling transitional rough-wall turbulence with quasi-linear approximations
No full textThe effects of surface roughness in the transitionally rough regime on the overlying near-wall turbulence are modelled using quasi-linear approximations proposed recently: minimal quasi-linear approximation (MQLA) (Hwang & Ekchardt, 2020, J. Fluid Mech., vol. 894, A23), data-driven quasi-linear approximation (DQLA) (Holford et al., 2024, J. Fluid Mech., vol. 980, A12) and a newly established variant of MQLA (M2QLA, minimal two-mode quasi-linear approximation). The transpiration-resistance model (TRM) for boundary conditions is applied to account for the surface roughness (Lācis et al., 2020, J. Fluid Mech., vol. 884, A21). It is shown that many essential near-wall turbulence statistics are fairly well captured by the quasi-linear approximations in a wide range of slip and transpiration lengths for the TRM boundary conditions. In particular, the virtual origins and the resulting roughness functions are well predicted, showing good agreement with those from previous direct numerical simulations (DNS) in mild roughness cases. The DQLA and M2QLA, which incorporate streamwise-dependent Fourier modes in the approximations, are also shown to perform a little better than MQLA, especially with DQLA reproducing the two-dimensional energy spectra qualitatively consistent with the DNS. Finally, with a computational cost much lower than DNS, it is shown that the proposed quasi-linear approximation frameworks offer an efficient tool to rapidly explore the roughness effects within a large parameter space
When “nobody knowns anything”: imitation of resource allocation decisions under uncertainty
No full textThis paper explores how environmental uncertainty influences the interorganizational imitation of resource allocation decisions. Existing literature proposes contrasting findings: one highlighting reduced imitation under high uncertainty due to limitations in observational learning, and the other emphasizing the use of imitation to mitigate the risk of falling behind competitors in such environments. We attempt to reconcile the different views by proposing that imitation depends on the interplay between the type of environmental uncertainty (demand and competitive), the focal organization’s performance rank (first vs. last), and the organizational leader’s inexperience. We test our hypotheses using data on the allocation of new investments across different movie genres made by major Hollywood film studios (1986-2004). The results reveal that imitation under uncertainty depends on the interplay between competitive and social considerations shaping incentives to focus on managing reputational risk versus creating opportunities to catch up
Circulating non-coding RNAS as indicators of fibrosis and heart failure severity
No full textHeart failure (HF) is a leading cause of morbidity and mortality worldwide, representing a complex clinical syndrome in which the heart’s ability to pump blood efficiently is impaired. HF can be subclassified into heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF), each with distinct pathophysiological mechanisms and varying levels of severity. The progression of HF is significantly driven by cardiac fibrosis, a pathological process in which the extracellular matrix undergoes abnormal and uncontrolled remodelling. Cardiac fibrosis is characterized by excessive matrix protein deposition and the activation of myofibroblasts, increasing the stiffness of the heart, thus disrupting its normal structure and function and promoting lethal arrythmia. MicroRNAs, long non-coding RNAs, and circular RNAs, collectively known as non-coding RNAs (ncRNAs), have recently gained significant attention due to a growing body of evidence suggesting their involvement in cardiac remodelling such as fibrosis. ncRNAs can be found in the peripheral blood, indicating their potential as biomarkers for assessing HF severity. In this review, we critically examine recent advancements and findings related to the use of ncRNAs as biomarkers of HF and discuss their implication in fibrosis development
TERT expression attenuates metabolic disorders in obese mice by promoting adipose stem and progenitor cell expansion and differentiation
No full textBackground and aims
Adipose tissue (AT) senescence, induced by obesity or aging, leads to a reduced capacity for tissue remodeling and a chronic pro-inflammatory state, which leads to the onset of metabolic pathologies. Cellular senescence is triggered by various stresses, in particular excessive shortening of telomeres, which activates the p21 pathway and leads to the arrest of the cell cycle. We used the mouse model p21+/Tert expressing TERT from the Cdkn1a locus to investigate whether counteracting telomere shortening by telomerase (TERT) specifically in pre-senescent cells could improve obesity-induced metabolic disorders.
Results
Our study demonstrates that conditional expression of TERT reduces insulin-resistance and glucose intolerance associated with obesity. In AT, this is accompanied by a decrease in the number of senescent p21-positive cells, very short telomeres, and oxidative DNA damage. Single nucleus RNA-seq data reveal TERT expression attenuates senescence induced by HFD in particular in adipose stem and progenitor cells (ASPC). We demonstrate that ASPC expansion and differentiation are promoted in p21+/Tert obese mice, thereby improving AT plasticity. Furthermore, we show that TERT expression enhances mitochondrial function and alleviates oxidative stress in ASPC. This process contributes to the AT hyperplasia with increased number of adipocytes which has been shown to have a protective effect against obesity-associated metabolic disorders.
Conclusions
These results underscore TERT's role in mitigating obesity-related metabolic dysfunction. Conditional TERT expression may therefore represent as a promising therapeutic strategy for obesity-associated metabolic disorders
Preliminary qualification of a machine learning-based assessment of the tumour immune infiltrate as a predictor of outcome in patients with hepatocellular carcinoma treated with atezolizumab plus bevacizumab
No full textIntroduction: Spontaneously immunogenic hepatocellular cancer (HCC), identified by dense immune cell infiltration (ICI), responds better to immunotherapy, although no validated biomarker exists to identify these cases. We utilized machine learning (ML) to quantify ICI from standard Haematoxylin & Eosin (H&E) stained tissue and evaluated its correlation with characteristics of the tumour microenvironment and clinical outcome from atezolizumab plus bevacizumab (A+B).
Methods: We employed a supervised ML algorithm on 102 pre-treatment H&E slides collected from patients treated with A+B. We quantified tumour, stroma and immune cell counts/mm2 and dichotomized patients into ICI-high and ICI-low for clinicopathologic analysis. We correlated ICI signature with characteristics of the T-cell infiltrate (CD4+, FOXP3+, CD8+, PD1+) using multiplex immunohistochemistry in 62 resected specimens and evaluated gene expression profiles by bulk RNA-seq in 44 samples.
Results: All patients treated with A+B were Child-Pugh A and received first-line A+B treatment for BCLC Stage C HCC (n=77, 75.5%) on a background of viral (n=53, 52%) and non-viral (n=49, 48%) liver disease. Median ICI density was 429.9 (IQR: 194.6-666.7) cells/mm2. Two-thirds of patients (n=67, 65.7%) had ICI counts ≥236/mm2, derived as the optimal prognostic cut-off (ICI-high). Baseline characteristics, including disease aetiology, liver function, performance status, stage, prior therapy and alpha-fetoprotein levels, were comparable between ICI-high vs. ICI-low patients. Patients with ICI-high demonstrated a significantly longer OS compared to ICI-low: 20.9 (95%CI: 13.8-27.9) vs. 15.3 (95%CI: 6.0-24.6 months, p=0.026). Multivariable analyses demonstrated ICI-low status to remain as an independent prognostic parameter (adjusted Hazard Ratio (aHR): 2.02, 95%CI: 1.03-3.96) alongside AFP concentration (per 100 ng/mL: aHR 1.00, 95%CI: 1.00-1.00). ICI-high tumours were characterized by STC1-underexpression and enrichment in pro-inflammatory gene expression sets previously associated with response to immunotherapy. The pro-inflammatory environment identified by ICI status was not exclusively mediated by T-cell phenotype polarisation as shown by a lack of correlation between ICI-high status and CD4+, CD4+FOXP3+, CD8+ and CD8+PD1+ T-cell density.
Conclusion: We propose a ML-based algorithm to identify pro-inflamed HCC tumour microenvironments bearing a positive correlation with the patient’s OS. Digital characterisation of the tumour microenvironment should be validated as a tool to improve precision delivery of anti-cancer immunotherapy
The margin of stability is bigger in girls with Lenke I adolescent idiopathic scoliosis: a case-control study
No full textBackground
The Margin of Stability is used to measure stability in adults with pathologic gait including spinal deformity. The aim was to compare anterior-posterior and mediolateral Margin of Stability in girls with Adolescent Idiopathic Scoliosis to typically-developing girls, and to test the effect of speed and Cobb angle on the Margin of Stability.
Methods
Eight girls with Lenke 1 Adolescent Idiopathic Scoliosis (Cobb: 53.9±15.2°) were recruited from the Royal National Orthopaedic Hospital between July 2021 and August 2022, and seven propensity-matched typically-developing girls were recruited. Participants walked at three speeds on an instrumented treadmill wearing a full-body plug-in-gait marker set. Mean Margin of Stability at heel strike during 30-seconds of walking was calculated. The Margin of Stability was compared between girls with Adolescent Idiopathic Scoliosis and controls using a Two-way ANOVA with paired analysis and was correlated to Cobb angle in girls with Adolescent Idiopathic Scoliosis using Pearson’s r2.
Findings
There was weak evidence for a Group-Speed interaction between for anterior-posterior Margin of Stability at 1.2 m/s. It was higher in Cases than at 1.2 m/s compared to Controls (left: p = 0.05; right: p = 0.06). Anterior-posterior Margin of Stability was not significantly correlated with Cobb angle. Mediolateral Margin of Stability did not differ between Group or Group-Speed interaction but was negatively correlated with increasing Cobb angle (left: p = 0.002; right: p = 0.04).
Interpretation
Girls with moderate-severe Lenke I Adolescent Idiopathic Scoliosis were more anterior-posteriorly stable than Controls at higher speeds. Gait challenges may require compensatory mechanisms for perceived instability caused by their spinal deformity
Magnetic control of a two-layer pipe flow
No full textThe gap between two solid, coaxial cylinders is filled with two ferrofluids of differing viscosity and magnetic susceptibility. Axial motion is driven by a pressure gradient and/or translation of the inner cylinder. An axial magnetic field is imposed externally, while current flowing in the inner cylinder generates an azimuthal field. It is known that the axisymmetric capillary instability of the cylindrical fluid interface may be controlled either by hydrodynamic shear or magnetic effects, but each of these can give rise to other instabilities, often nonaxisymmetric. This paper investigates the 10-dimensional parameter space to determine when combined action of shear and magnetic effects can provide overall stability, essentially using shear to stabilize the troublesome helical "tearing" mode, while magnetic stresses control the hydrodynamic instability. Stability is easier to obtain when the inner fluid is more magnetic