Optimization and deployment of CNNs at the Edge: The ALOHA experience

Deep learning (DL) algorithms have already proved their effectiveness on a wide variety of application domains, including speech recognition, natural language processing, and image classification. To foster their pervasive adoption in applications where low latency, privacy issues and data bandwidth are paramount, the current trend is to perform inference tasks at the edge. This requires deployment of DL algorithms on low-energy and resource-constrained computing nodes, often heterogenous and parallel, that are usually more complex to program and to manage without adequate support and experience. In this paper, we present ALOHA, an integrated tool flow that tries to facilitate the design of DL applications and their porting on embedded heterogenous architectures. The proposed tool flow aims at automating different design steps and reducing development costs. ALOHA considers hardware-related variables and security, power efficiency, and adaptivity aspects during the whole development process, from pre-training hyperparameter optimization and algorithm configuration to deployment

Kinetic modelling of quantitative proteome data predicts metabolic reprogramming of liver cancer

BACKGROUND: Metabolic alterations can serve as targets for diagnosis and cancer therapy. Due to the highly complex regulation of cellular metabolism, definite identification of metabolic pathway alterations remains challenging and requires sophisticated experimentation. METHODS: We applied a comprehensive kinetic model of the central carbon metabolism (CCM) to characterise metabolic reprogramming in murine liver cancer. RESULTS: We show that relative differences of protein abundances of metabolic enzymes obtained by mass spectrometry can be used to assess their maximal velocity values. Model simulations predicted tumour-specific alterations of various components of the CCM, a selected number of which were subsequently verified by in vitro and in vivo experiments. Furthermore, we demonstrate the ability of the kinetic model to identify metabolic pathways whose inhibition results in selective tumour cell killing. CONCLUSIONS: Our systems biology approach establishes that combining cellular experimentation with computer simulations of physiology-based metabolic models enables a comprehensive understanding of deregulated energetics in cancer. We propose that modelling proteomics data from human HCC with our approach will enable an individualised metabolic profiling of tumours and predictions of the efficacy of drug therapies targeting specific metabolic pathways

The effects of exercise on cardiovascular disease risk factors and cardiovascular physiology in rheumatoid arthritis

© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. Cardiovascular disease (CVD) morbidity and mortality is highly prevalent in patients with rheumatoid arthritis (RA) with debilitating effects for the individual as well as significant healthcare impact. Current evidence demonstrates that engaging in aerobic and resistance exercise (i.e. structured physical activity) can significantly improve patient-reported and clinical index-assessed outcomes in RA. In addition to this, engagement in exercise programmes improves, in a dose-dependent manner, the risk of developing CVD as well as CVD symptoms and outcomes. The present narrative review uses evidence from systematic reviews and meta-analyses as well as controlled trials, to synthesize the current state-of-the-art on the potential effects of aerobic and resistance exercise on CVD risk factors as well as on cardiac and vascular function and structure in people with RA. Where there is a lack of evidence in RA to explain potential mechanisms, relevant studies from the general population are also discussed and linked to RA.Published versio

Position Statement on Exercise Dosage in Rheumatic and Musculoskeletal Diseases: The Fole of the IMPACT-RMD Toolkit

There is convincing evidence to suggest that exercise interventions can significantly improve disease-related outcomes as well as comorbidities in rheumatic and musculoskeletal diseases (RMDs). All exercise interventions should be appropriately defined by their dose, which comprises of two components: a) the FITT (frequency, intensity, time and type) and b) the training (ie, specificity, overload, progression, initial values, reversibility, and diminishing returns) principles. In the published RMD literature, exercise dosage is often misreported, which in "pharmaceutical treatment terms", this would be the equivalent of receiving the wrong medication dosage. Lack of appropriately reporting exercise dosage in RMDs, therefore, results in limited clarity on the effects of exercise interventions on different outcomes while it also hinders reproducibility, generalisability and accuracy of research findings. Based on the collective but limited current knowledge, the main purpose of the present Position Statement is to provide specific guidance for RMD researchers to help improve the reporting of exercise dosage and help advance research into this important field of investigation. We also propose the use of the IMPACT-RMD toolkit, a tool that can be used in the design and reporting phase of every trial

Abatacept in individuals at high risk of rheumatoid arthritis (APIPPRA): a randomised, double-blind, multicentre, parallel, placebo-controlled, phase 2b clinical trial

\ua9 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Background: Individuals with serum antibodies to citrullinated protein antigens (ACPA), rheumatoid factor, and symptoms, such as inflammatory joint pain, are at high risk of developing rheumatoid arthritis. In the arthritis prevention in the pre-clinical phase of rheumatoid arthritis with abatacept (APIPPRA) trial, we aimed to evaluate the feasibility, efficacy, and acceptability of treating high risk individuals with the T-cell co-stimulation modulator abatacept. Methods: The APIPPRA study was a randomised, double-blind, multicentre, parallel, placebo-controlled, phase 2b clinical trial done in 28 hospital-based early arthritis clinics in the UK and three in the Netherlands. Participants (aged ≥18 years) at risk of rheumatoid arthritis positive for ACPA and rheumatoid factor with inflammatory joint pain were recruited. Exclusion criteria included previous episodes of clinical synovitis and previous use of corticosteroids or disease-modifying antirheumatic drugs. Participants were randomly assigned (1:1) using a computer-generated permuted block randomisation (block sizes of 2 and 4) stratified by sex, smoking, and country, to 125 mg abatacept subcutaneous injections weekly or placebo for 12 months, and then followed up for 12 months. Masking was achieved by providing four kits (identical in appearance and packaging) with pre-filled syringes with coded labels of abatacept or placebo every 3 months. The primary endpoint was the time to development of clinical synovitis in three or more joints or rheumatoid arthritis according to American College of Rheumatology and European Alliance of Associations for Rheumatology 2010 criteria, whichever was met first. Synovitis was confirmed by ultrasonography. Follow-up was completed on Jan 13, 2021. All participants meeting the intention-to-treat principle were included in the analysis. This trial was registered with EudraCT (2013–003413–18). Findings: Between Dec 22, 2014, and Jan 14, 2019, 280 individuals were evaluated for eligibility and, of 213 participants, 110 were randomly assigned to abatacept and 103 to placebo. During the treatment period, seven (6%) of 110 participants in the abatacept group and 30 (29%) of 103 participants in the placebo group met the primary endpoint. At 24 months, 27 (25%) of 110 participants in the abatacept group had progressed to rheumatoid arthritis, compared with 38 (37%) of 103 in the placebo group. The estimated proportion of participants remaining arthritis-free at 12 months was 92\ub78% (SE 2\ub76) in the abatacept group and 69\ub72% (4\ub77) in the placebo group. Kaplan–Meier arthritis-free survival plots over 24 months favoured abatacept (log-rank test p=0\ub7044). The difference in restricted mean survival time between groups was 53 days (95% CI 28–78; p<0\ub70001) at 12 months and 99 days (95% CI 38–161; p=0\ub70016) at 24 months in favour of abatacept. During treatment, abatacept was associated with improvements in pain scores, functional wellbeing, and quality-of-life measurements, as well as low scores of subclinical synovitis by ultrasonography, compared with placebo. However, the effects were not sustained at 24 months. Seven serious adverse events occurred in the abatacept group and 11 in the placebo group, including one death in each group deemed unrelated to treatment. Interpretation: Therapeutic intervention during the at-risk phase of rheumatoid arthritis is feasible, with acceptable safety profiles. T-cell co-stimulation modulation with abatacept for 12 months reduces progression to rheumatoid arthritis, with evidence of sustained efficacy beyond the treatment period, and with no new safety signals. Funding: Bristol Myers Squibb

Non-canonical HIF-1 stabilization contributes to intestinal tumorigenesis

The hypoxia-inducible transcription factor HIF-1 is appreciated as a promising target for cancer therapy. However, conditional deletion of HIF-1 and HIF-1 target genes in cells of the tumor microenvironment can result in accelerated tumor growth, calling for a detailed characterization of the cellular context to fully comprehend HIF-1's role in tumorigenesis. We dissected cell type-specific functions of HIF-1 for intestinal tumorigenesis by lineage-restricted deletion of the Hif1a locus. Intestinal epithelial cell-specific Hif1a loss reduced activation of Wnt/β-catenin, tumor-specific metabolism and inflammation, significantly inhibiting tumor growth. Deletion of Hif1a in myeloid cells reduced the expression of fibroblast-activating factors in tumor-associated macrophages resulting in decreased abundance of tumor-associated fibroblasts (TAF) and robustly reduced tumor formation. Interestingly, hypoxia was detectable only sparsely and without spatial association with HIF-1α, arguing for an importance of hypoxia-independent, i.e., non-canonical, HIF-1 stabilization for intestinal tumorigenesis that has not been previously appreciated. This adds a further layer of complexity to the regulation of HIF-1 and suggests that hypoxia and HIF-1α stabilization can be uncoupled in cancer. Collectively, our data show that HIF-1 is a pivotal pro-tumorigenic factor for intestinal tumor formation, controlling key oncogenic programs in both the epithelial tumor compartment and the tumor microenvironment