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Effectiveness of early vocational rehabilitation versus usual care to support RETurn to work after stroKE: A pragmatic, parallel-arm multicenter, randomized controlled trial
Get PDFBackground: Return-to-work is a major goal achieved by fewer than 50% stroke survivors. Evidence on how to support return-to-work is lacking. Aims: This study aimed to evaluate the clinical effectiveness of Early Stroke Specialist Vocational Rehabilitation (ESSVR) plus usual care (UC) (i.e. usual NHS rehabilitation) versus UC alone for helping people return-to-work after stroke. Methods: This pragmatic, multicentre, individually randomized controlled trial with embedded economic and process evaluations compared ESSVR with UC in 21 NHS stroke services across England and Wales. Eligible participants were aged ⩾ 18 years, in work at stroke onset, hospitalized with new stroke and within 12 weeks of stroke. People not intending to return-to-work were excluded. Participants were randomized (5:4) to individually tailored ESSVR delivered by stroke specialist occupational therapists for up to 12 months or usual National Health Service rehabilitation. Primary outcome was self-reported return-to-work for ⩾ 2 h per week at 12 months. Primary and safety analyses were done in the intention-to-treat population. Results: Between 1 June 2018, and 7 March 2022, 583 participants (Mage 54.1 years (SD 11.0), 69% male) were randomized to ESSVR (n = 324) or UC (n = 259). Primary outcome data were available for 454 (77.9%) participants. Intention-to-treat analysis showed no evidence of a difference in the proportion of participants returned-to-work at 12 months (165/257 (64.2%) ESSVR vs 117/197 (59.4%) UC; adjusted odds ratio 1.12 (95% CI: 0.75–1.68), p = 0.5678). There was some indication that older participants and those with more post-stroke impairment were more likely to benefit from ESSVR (interaction p = 0.0239 and p = 0.0959, respectively). Conclusion: To our knowledge, this is the largest trial of a stroke vocational rehabilitation (VR) intervention ever conducted. We found no evidence that ESSVR conferred any benefits over UC in improving return-to-work rates 12 months post-stroke. Return-to-work (for at least 2 h per week) rates were higher than in previous studies (64.2% ESSVR vs 59.4% UC) at 12 months and more than double that observed in our feasibility trial (26%). Interpretation of findings was limited by a predominantly mild–moderate sample of participants and the COVID-19 pandemic. The pandemic impacted the trial, ESSVR and UC delivery, altering the work environment and employer behavior. These changes influenced our primary outcome and the meaning of work in people’s lives; all pivotal to the context of ESSVR delivery and its mechanisms of action. Data access: Data available on reasonable request. Registration: ISRCTN12464275
Gastroenterology Training and Career in Women: Challenges and Opportunities
Get PDFThis review highlights gender gaps in training, career, and work-life balance in gastroenterology. Stereotypes and biases toward women’s abilities and commitment to their careers can influence evaluations, advancement in gastroenterology training, and career progression. The findings indicate that lack of or limited access to mentorship and sponsorship, as well as support networks, can hinder the professional development of women. Moreover, results indicate that we must improve work-life balance measures, for example offering flexible working hours and compensation and support for women during pregnancy, after childbirth, and motherhood. However, reports on such equity measures are scarce, and we lack scientific evidence of their impact. This review concludes that to reduce gender gaps and make a positive impact, we need educational and promotional programs and monitoring of their outcomes
Import processing and trade costs
No full textWe estimate import processing costs based on the time it takes to import. To do so, we first develop a theoretical model that extends existing time-cost measures to account for uncertainty in import processing. Second, we use detailed, highly disaggregated data on import processing dates and import values to provide estimates of processing costs that are consistent with the theory. This evidence indicates that our extensions to time-cost estimates are economically relevant to determining processing costs. According to our estimates, the tariff equivalent import processing cost is as high as 18 percent. WTO estimates suggest that the full implementation of the 2013 Trade Facilitation Agreement would reduce the time to trade by 1.5 days. In that case, processing costs would decrease to 13 percent
Machine learning on national shopping data reliably estimates childhood obesity prevalence and socio-economic deprivation
Get PDFDeprivation pushes people to choose cheap, calorie-dense foods instead of nutritious but expensive alternatives. Diseases, such as obesity, cardiovascular disease, and diabetes, resulting from these poor dietary choices place a significant burden on public health systems. Measuring nutritional insecurity is difficult to achieve at scale and so the ability to study the relationship between nutritional outcomes and deprivation at a national level is very challenging. This makes it difficult to understand the effect of new policies or track changes over time. To address this challenge, we develop a machine learning approach using massive anonymised transactional data (4 million members and 2.5 billion transactions) in partnership with the retailer The Co-operative Group UK. We engineer a series of variables related to obesogenic diets, including a new measure called ‘Calorie-oriented purchasing’. These variables help illustrate how large-scale transactional data can discriminate between neighbourhoods most affected by deprivation and childhood obesity. Through comparative assessment of machine learning approaches, we find better performance from tree-based models (Random Forest, XGBoost) with the best-achieving accuracy of 0.88 for predicting deprivation and an accuracy of 0.79 for childhood obesity. Calorie-oriented purchasing emerges as a robust predictor of deprivation and childhood obesity at the census area level. Results show this approach can help summarise nutritional insecurity, and support its spatio-temporal monitoring. We conclude with policy implications and recommend retailers adopt new measures for measuring national nutrition insecurity
Neuropilin-1 inhibition suppresses nerve growth factor signaling and nociception in pain models
Get PDFNerve growth factor (NGF) monoclonal antibodies inhibit chronic pain, yet failed to gain approval due to worsened joint damage in osteoarthritis patients. We report that neuropilin-1 (NRP1) is a coreceptor for NGF and tropomyosin-related kinase A (TrkA) pain signaling. NRP1 was coexpressed with TrkA in human and mouse nociceptors. NRP1 inhibitors suppressed NGF-stimulated excitation of human and mouse nociceptors and NGF-evoked nociception in mice. NRP1 knockdown inhibited NGF/TrkA signaling, whereas NRP1 overexpression enhanced signaling. NGF bound NRP1 with high affinity and interacted with and chaperoned TrkA from the biosynthetic pathway to the plasma membrane and endosomes, enhancing TrkA signaling. Molecular modeling suggested that the C-terminal R/KXXR/K NGF motif interacts with the extracellular “b” NRP1 domain within a plasma membrane NGF/TrkA/NRP1 of 2:2:2 stoichiometry. G α interacting protein C-terminus 1 (GIPC1), which scaffolds NRP1 and TrkA to myosin VI, colocalized in nociceptors with NRP1/TrkA. GIPC1 knockdown abrogated NGF-evoked excitation of nociceptors and pain-like behavior. Thus, NRP1 is a nociceptor-enriched coreceptor that facilitates NGF/ TrkA pain signaling. NRP binds NGF and chaperones TrkA to the plasma membrane and signaling endosomes via the GIPC1 adaptor. NRP1 and GIPC1 antagonism in nociceptors offers a long-awaited nonopioid alternative to systemic antibody NGF sequestration for the treatment of chronic pain
Negating self-induced parametric excitation in capacitive ring-based MEMS Coriolis vibrating gyroscopes
Get PDFRate sensing performance of ring-based capacitive Coriolis Vibratory Gyroscopes (CVGs) is degraded by the presence of imperfections and self-induced parametric excitation caused by electrostatic nonlinearities as the drive amplitude increases. This paper investigates the feasibility of using electrostatic forces to negate self-induced parametric excitation for a ring based CVG having 8 electrodes uniformly spaced inside and outside the ring. A mathematical model is developed to describe sensor dynamics under operating conditions and negation of self-induced parametric excitation is achieved by including additional parametric pumping voltages that generate electrostatic forces in antiphase with the self-induced parametric excitation. Numerical results are obtained for the rate sensitivity, bias rate and quadrature error of the sense output as the drive amplitude is increased and it is found that negating self-induced parametric excitation can enhance device performance under specific conditions by enabling nonlinear frequency matching. The proposed approach is more effective for larger electrode spans and improves the linearity of the rate sensing performance with drive amplitude. Numerical results are presented which include a comparison with results obtained using the Finite Element method to validate the proposed approach
A Holistic Analysis and Experimental Testing of a Passive Heat Path for Electric Motors Slots
Get PDFThis paper presents a thorough and broad analysis of the passive slot heat path concept. Six heat path shapes are proposed and compared in terms of their combined thermal and electrical performance. Through an extensive search pool that covers a wide range of motor and slot designs and operating conditions, this paper assesses the heat removal capabilities of the heat path from the slot. The analysis is performed through a lumped parameter thermal network approach. Additionally, statistical analyses using correlations and linear regression models are carried out to improve understanding of this concept. Furthermore, a neural-network model is created to improve the regression model accuracy in predicting the slot temperature and temperature reduction. Finally, experimental testing and validation of the modelling are carried out on one of the six heat path shapes
Programming of pluripotency and the germ line co-evolved from a Nanog ancestor
Get PDFFrancois Jacob proposed that evolutionary novelty arises through incremental tinkering with pre-existing genetic mechanisms. Vertebrate evolution was predicated on pluripotency, the ability of embryonic cells to form somatic germ layers and primordial germ cells (PGCs). The origins of pluripotency remain unclear, as key regulators, such as Nanog, are not conserved outside of vertebrates. Given NANOG's role in mammalian development, we hypothesized that NANOG activity might exist in ancestral invertebrate genes. Here, we find that Vent from the hemichordate Saccoglossus kowalevskii exhibits NANOG activity, programming pluripotency in Nanog−/− mouse pre-induced pluripotent stem cells (iPSCs) and NANOG-depleted axolotl embryos. Vent from the cnidarian Nematostella vectensis showed partial activity, whereas Vent from sponges and vertebrates had no activity. VENTX knockdown in axolotls revealed a role in germline-competent mesoderm, which Saccoglossus Vent could rescue but Nematostella Vent could not. This suggests that the last deuterostome ancestor had a Vent gene capable of programming pluripotency and germline competence
Generating new cellular structures for additive manufacturing through an unconditional 3D latent diffusion model
Get PDFAdvances in additive manufacturing (AM) have facilitated the fabrication of cellular structures inspired by those in the natural world. But the design of complex, tessellating cellular structures remains a challenge for human designers, and only a small number of geometries, defined either by connected walls or struts, or by surface equations, have been investigated. This study introduces generative deep learning to the problem, with the aim of synthesising novel cellular geometries producible by AM. Our unconditional 3D latent diffusion model (U3LDM) explores the design space from a new class of training data comprising 10,650 unit cells. A critical task involved developing a varied set of cell geometries based on random permutations of trigonometric surface equations. This was coupled with a stringent set of pass/fail tests to ensure the generated structures possessed structural connectivity and could tessellate in 3D. The new cellular structures were analysed numerically using finite element analysis, fabricated by polymer AM, and subjected to compression tests to verify their manufacturability and mechanical properties. Results indicate that the U3LDM is capable of generating new ‘unseen’ cellular structures with geometries and mechanical properties consistent with those of the training specimens. This method also demonstrates the potential universal technique for creating nature-inspired and AM-manufacturable structures beyond the currently limited set of human-derived geometries
The ionizing photon budget and effective clumping factor in radiative transfer simulations calibrated to Lyman-α forest data
Get PDFRecent JWST observations have allowed for the first time to obtain comprehensive measurements of the ionizing photon production efficiency ξion for a wide range of reionization-epoch galaxies. We explore implications for the inferred UV luminosity functions and escape fractions of ionizing sources in our suite of simulations. These are run with the graphics processing unit (GPU) based radiative transfer code ATON-HE and are calibrated to the XQR-30 Lyman-α forest data at 5 50 per cent at z > 10, disfavouring the oligarchic source model at very high redshift. The inferred effective clumping factors in our simulations are in the range of 3–6, suggesting consistency between the observed ionizing properties of reionization-epoch galaxies and the ionizing photon budget in our simulations
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