A life course approach to injury prevention: a "lens and telescope" conceptual model

<p>Abstract</p> <p>Background</p> <p>Although life course epidemiology is increasingly employed to conceptualize the determinants of health, the implications of this approach for strategies to reduce the burden of injuries have received little recognition to date.</p> <p>Methods</p> <p>The authors reviewed core injury concepts and the principles of the life course approach. Based on this understanding, a conceptual model was developed, to provide a holistic view of the mechanisms that underlie the accumulation of injury risk and their consequences over the life course.</p> <p>Results</p> <p>A "lens and telescope" model is proposed that particularly draws on (a) the extended temporal dimension inherent in the life course approach, with links between exposures and outcomes that span many years, or even generations, and (b) an ecological perspective, according to which the contexts in which individuals live are critical, as are changes in those contexts over time.</p> <p>Conclusions</p> <p>By explicitly examining longer-term, intergenerational and ecological perspectives, life course concepts can inform and strengthen traditional approaches to injury prevention and control that have a strong focus on proximal factors. The model proposed also serves as a tool to identify intervention strategies that have co-benefits for other areas of health.</p

Obesity prevention: the role of policies, laws and regulations

The commercial drivers of the obesity epidemic are so influential that obesity can be considered a robust sign of commercial success – consumers are buying more food, more cars and more energy-saving machines. It is unlikely that these powerful economic forces will change sufficiently in response to consumer desires to eat less and move more or corporate desires to be more socially responsible. When the free market creates substantial population detriments and health inequalities, government policies are needed to change the ground rules in favour of population benefits

Interaction of galectin-3 with MUC1 on cell surface promotes EGFR dimerization and activation in human epithelial cancer cells

Epidermal growth factor receptor (EGFR) is an important regulator of epithelial cell growth and survival in normal and cancerous tissues and is a principal therapeutic target for cancer treatment. EGFR is associated in epithelial cells with the heavily glycosylated transmembrane mucin protein MUC1, a natural ligand of galectin-3 that is overexpressed in cancer. This study reveals that the expression of cell surface MUC1 is a critical enhancer of EGF-induced EGFR activation in human breast and colon cancer cells. Both the MUC1 extracellular and intracellular domains are involved in EGFR activation but the predominant influence comes from its extracellular domain. Binding of galectin-3 to the MUC1 extracellular domain induces MUC1 cell surface polarization and increases MUC1–EGFR association. This leads to a rapid increase of EGFR homo-/hetero-dimerization and subsequently increased, and also prolonged, EGFR activation and signalling. This effect requires both the galectin-3 C-terminal carbohydrate recognition domain and its N-terminal ligand multi-merization domain. Thus, interaction of galectin-3 with MUC1 on cell surface promotes EGFR dimerization and activation in epithelial cancer cells. As MUC1 and galectin-3 are both commonly overexpressed in most types of epithelial cancers, their interaction and impact on EGFR activation likely makes important contribution to EGFR-associated tumorigenesis and cancer progression and may also influence the effectiveness of EGFR-targeted cancer therapy

VIDIIA Hunter: a low-cost, smartphone connected, artificial intelligence-assisted COVID-19 rapid diagnostic platform approved for medical use in the UK

Data availability statement: The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors.The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmolb.2023.1144001/full#supplementary-material SUPPLEMENTARY TABLE S1 | Full data set obtained from the 400 clinical samples, as it was submitted to the CTDA for approval.A correction has been applied to this article in: Corrigendum: VIDIIA Hunter: a low-cost, smartphone connected, artificial intelligence-assisted COVID-19 rapid diagnostic platform approved for medical use in the UK - correction: In the published article, there was an error in the Article title. Instead of “VIDIIA Hunter diagnostic platform: a low-cost, smartphone connected, artificial intelligence-assisted COVID-19 rapid diagnostics approved for medical use in the UK,” it should be “VIDIIA Hunter: a low-cost, smartphone connected, artificial intelligence-assisted COVID-19 rapid diagnostic platform approved for medical use in the UK”. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.Copyright . Introduction: Accurate and rapid diagnostics paired with effective tracking and tracing systems are key to halting the spread of infectious diseases, limiting the emergence of new variants and to monitor vaccine efficacy. The current gold standard test (RT-qPCR) for COVID-19 is highly accurate and sensitive, but is time-consuming, and requires expensive specialised, lab-based equipment. Methods: Herein, we report on the development of a SARS-CoV-2 (COVID-19) rapid and inexpensive diagnostic platform that relies on a reverse-transcription loop-mediated isothermal amplification (RT-LAMP) assay and a portable smart diagnostic device. Automated image acquisition and an Artificial Intelligence (AI) deep learning model embedded in the Virus Hunter 6 (VH6) device allow to remove any subjectivity in the interpretation of results. The VH6 device is also linked to a smartphone companion application that registers patients for swab collection and manages the entire process, thus ensuring tests are traced and data securely stored. Results: Our designed AI-implemented diagnostic platform recognises the nucleocapsid protein gene of SARS-CoV-2 with high analytical sensitivity and specificity. A total of 752 NHS patient samples, 367 confirmed positives for coronavirus disease (COVID-19) and 385 negatives, were used for the development and validation of the test and the AI-assisted platform. The smart diagnostic platform was then used to test 150 positive clinical samples covering a dynamic range of clinically meaningful viral loads and 250 negative samples. When compared to RT-qPCR, our AI-assisted diagnostics platform was shown to be reliable, highly specific (100%) and sensitive (98–100% depending on viral load) with a limit of detection of 1.4 copies of RNA per µL in 30 min. Using this data, our CE-IVD and MHRA approved test and associated diagnostic platform has been approved for medical use in the United Kingdom under the UK Health Security Agency’s Medical Devices (Coronavirus Test Device Approvals, CTDA) Regulations 2022. Laboratory and in-silico data presented here also indicates that the VIDIIA diagnostic platform is able to detect the main variants of concern in the United Kingdom (September 2023). Discussion: This system could provide an efficient, time and cost-effective platform to diagnose SARS-CoV-2 and other infectious diseases in resource-limited settings.The study was funded by a Biotechnology and Biological Sciences Research Council grant (BB/R012695/1), awarded to Brunel University, University of Surrey, and Lancaster University. The study also received funding from the Higher Education Innovation Funding (HEIF–KN9190A) and the UK Research and Innovation (UKRI) EPSRC Impact Acceleration Accounts (IAA–RN0441R, RN0461E, and EP/R511560/1), which were awarded to the University of Surrey and Lancaster University in collaboration with Brunel University, United Kingdom

A Novel Function of DELTA-NOTCH Signalling Mediates the Transition from Proliferation to Neurogenesis in Neural Progenitor Cells

A complete account of the whole developmental process of neurogenesis involves understanding a number of complex underlying molecular processes. Among them, those that govern the crucial transition from proliferative (self-replicating) to neurogenic neural progenitor (NP) cells remain largely unknown. Due to its sequential rostro-caudal gradients of proliferation and neurogenesis, the prospective spinal cord of the chick embryo is a good experimental system to study this issue. We report that the NOTCH ligand DELTA-1 is expressed in scattered cycling NP cells in the prospective chick spinal cord preceding the onset of neurogenesis. These Delta-1-expressing progenitors are placed in between the proliferating caudal neural plate (stem zone) and the rostral neurogenic zone (NZ) where neurons are born. Thus, these Delta-1-expressing progenitors define a proliferation to neurogenesis transition zone (PNTZ). Gain and loss of function experiments carried by electroporation demonstrate that the expression of Delta-1 in individual progenitors of the PNTZ is necessary and sufficient to induce neuronal generation. The activation of NOTCH signalling by DELTA-1 in the adjacent progenitors inhibits neurogenesis and is required to maintain proliferation. However, rather than inducing cell cycle exit and neuronal differentiation by a typical lateral inhibition mechanism as in the NZ, DELTA-1/NOTCH signalling functions in a distinct manner in the PNTZ. Thus, the inhibition of NOTCH signalling arrests proliferation but it is not sufficient to elicit neuronal differentiation. Moreover, after the expression of Delta-1 PNTZ NP continue cycling and induce the expression of Tis21, a gene that is upregulated in neurogenic progenitors, before generating neurons. Together, these experiments unravel a novel function of DELTA–NOTCH signalling that regulates the transition from proliferation to neurogenesis in NP cells. We hypothesize that this novel function is evolutionary conserved