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Insights into the utility of small form air quality monitoring in health care environments: lessons learned from the University Hospitals Birmingham NHS Foundation Trust
No full textAir pollution is a major environmental and public health challenge, with exposure to air pollution linked to 29,000–43,000 premature deaths annually in the UK. The National Health Service (NHS) experiences increased burden on its services due to air pollution related disease. Acute NHS Trusts and other healthcare settings are often locations with high inpatient and outpatient populations at enhanced vulnerability to air pollution related disease, including the young and older adults, and those with chronic health conditions. Many UK healthcare facilities are located in areas of poor air quality. Non-communicable disease from air pollution (PM2.5 and NO2) could cost health and social care providers estimated to >£18billion in the UK (between 2018 and 2035) if pollutant concentrations are not reduced. The NHS Long Term Plan recognised the need for NHS services to take action to mitigate air pollutant emissions, including those arising from site activities and patient, visitor and staff travel. However undertaking air quality monitoring and implementing targeted air-pollution interventions can present organisational, financial, and logistical challenges. Furthermore, evidence of the effectiveness of highly localised interventions is limited in the healthcare context. The recent expansion in utility of small form air quality sensors offers major potential to overcome some of the challenges in monitoring and understanding efficacy of targeted interventions at healthcare settings. Here, we present a case study from Queen Elizabeth Hospital Birmingham, a tertiary site managed by University Hospitals Birmingham NHS Foundation Trust. This study assesses the feasibility of small form monitoring (diffusion tubes and sensors) for evaluating local air quality interventions in healthcare settings, via an assessment of a localised traffic management scheme aiming to reduce local air pollutant concentrations
Prospects for detecting new dark physics with the next generation of atomic clocks
No full textWide classes of new fundamental physics theories cause apparent variations in particle mass ratios in space and time. In theories that violate the weak equivalence principle (EP), those variations are not uniform across all particles and may be detected with atomic and molecular clock frequency comparisons. In this work we explore the potential to detect those variations with near-future clock comparisons. We begin by searching published clock data for variations in the electron-proton mass ratio. We then undertake a statistical analysis to model the noise in a variety of clock pairs that can be built in the near future according to the current state of the art, determining their sensitivity to various fundamental physics signals. Those signals are then connected to constraints on fundamental physics theories that lead directly or indirectly to an effective EP-violating, including those motivated by dark matter, dark energy, the vacuum energy problem, unification or other open questions of fundamental physics. This work results in projections for tight new bounds on fundamental physics that could be achieved with atomic and molecular clocks within the next few years. Our code for this work is packaged into a forecast tool that translates clock characteristics into bounds on fundamental physics
Effect of combined high temperature and tensile load on the post-fire performance of high-strength steel
No full textAn experimental campaign to evaluate the post-fire performance of grade S700 steel specimens subjected to a range of temperatures between 300 °C and 1000 °C and simultaneous tensile load, followed by natural cooling to room temperature, has been undertaken and is presented herein. The adopted test procedure provides a close representation of real fire and post-fire scenarios, since during a fire a structure is also subjected to a certain load level, an aspect that is usually neglected in research on this topic. The residual values of the key mechanical properties, including the yield strength, ultimate strength, Young’s modulus, strain at fracture and ultimate strain, were computed. According to the experimental results, the post-fire response was found to be dependent on the production route of the tested material and, under some combinations of temperature and tensile load, the residual values of ultimate strain did not meet the Eurocode 3 ductility requirements, indicating that the residual ductility of a steel structure surviving a fire could be compromised. The present work provides valuable data for the safety assessment of structures after fires, and aids decision-making on whether to re-use, retrofit or demolish
SOLeNNoID: a deep learning pipeline for solenoid residue detection in protein structures
No full textMotivation: Solenoid proteins, a subset of tandem repeat proteins, have structurally distinct, modular, and elongated architectures that
differentiate them from globular proteins. These proteins play essential roles in diverse biological processes, including protein binding,
enzymatic catalysis, ice binding, and nucleic acid interactions. Despite their biological significance and increasing commercial applications–such
as in therapeutic engineered variants like DARPins and designed PPR proteins–accurate identification and annotation of solenoid structures
remain challenging. Given that solenoid structures are more conserved than their sequences, recent advances in protein structure prediction
suggest that structure-based solenoid detection methods are preferable to sequence-based ones.
Results: We introduce SOLeNNoID, a deep-learning-based pipeline for predicting solenoid residues in protein structures. Our method employs a
convolutional neural network architecture to analyse protein distance matrices, enabling accurate identification of solenoid-containing regions.
SOLeNNoID covers all three solenoid subclasses: α-, α/β-, and β-solenoids. Comparative evaluation against existing structure-based methods
demonstrates the superior performance of our approach. Applying SOLeNNoID to the entire Protein Data Bank led to a 71% increase in detected
solenoid-containing entries compared to the gold-standard RepeatsDB database, significantly expanding the known solenoid protein repertoire.
Availability and implementation: SOLeNNoID is implemented in Python and available on github at https://github.com/gnik2018/SOLeNNoID.
The source code and pre-trained models are accessible under a free-software license. Training data are available on Zenodo at https://zenodo.
org/records/1492749
The impact and cost-effectiveness of pulse oximetry and oxygen on acute lower respiratory infection outcomes in children in Malawi: a modelling study
No full textBackground
acute lower respiratory infections (ALRIs) are the leading global cause of post-neonatal death in children younger than 5 years. The impact, cost, and cost-effectiveness of routine pulse oximetry and oxygen on ALRI outcomes at scale remain unquantified.
Methods
We evaluate the impact and cost-effectiveness of scaling up pulse oximetry and oxygen on childhood ALRI outcomes in Malawi using a new and detailed individual-based model, together with a comprehensive costing assessment for 2024 that includes both capital and operational expenditures. We model 15 scenarios ranging from no pulse oximetry or oxygen (null scenario) to high coverage (90% pulse oximetry usage and 80% oxygen availability) across the health system. Cost-effectiveness results are presented in incremental cost-effectiveness ratios (ICERs) and incremental net health benefits (INHBs) using a Malawi-specific cost-effectiveness threshold of US35 (33–36) per DALY averted and $924 (887–963) per death averted. The INHB is 40 200 (37 300–43 100) net DALYs averted.
Interpretation
Pulse oximetry and oxygen are complementary cost-effective interventions in Malawi, where health expenditure is low, and should be scaled up in parallel.
Funding
UK Research and Innovation, Wellcome Trust, Department for International Development, EU, Clinton Health Access Initiative, and Unitaid
Raman spectroscopic stress mapping of carbon nanotube coated single high modulus carbon fibres in compression
No full textSingle walled carbon nanotubes (SWCNTs) can be introduced onto the surface of carbon fibres to modulate stress transfer, introduce functionality, or act as local mechanical sensors. This study explores the effects of such a coating on the micromechanics of single fibre epoxy composites, under compression, using in situ Raman spectroscopy to obtain local and spatial stress maps. These maps can be analysed to quantify interfacial shear stress and show that the introduction of the SWCNTs increases the maximum interfacial shear stress of this carbon fibre epoxy system (M55/M46-DGEBA) from 23 MPa to 45 MPa. There is a corresponding decrease in the critical stress transfer length (from 420 μm to 252 μm), verified by optically measuring mean fragment lengths. The use of SWCNTs as a means to enhance the compressive properties of bulk carbon fibre-based composites is discussed, in the light of these new micromechanics results
Postoperative pain following gynecology oncological surgery: a systematic review by tumor site
No full textIntroduction: Postoperative pain management is complex and crucial in major gynecology oncological surgery. Currently, there is no well-defined standardized approach, resulting in significant variability in practices worldwide. This systematic review evaluates the effectiveness of analgesic strategies used postoperatively in gynecological cancer surgery. Methods: A systematic review was conducted from inception to June 26th 2024 to identify all randomized controlled trials (RCTs) assessing pain management following any surgery for gynecological cancer. This was performed on the CENTRAL, PubMed, Embase, and MEDLINE databases. Results: A total of 46 RCTs met the inclusion criteria. Of these 5316 patients, 1844 patients had cervical cancer, 99 had endometrial cancer, and 158 had ovarian cancer. The remaining 3215 participants had unspecified gynecological cancers or benign pathology. No studies focused on postoperative analgesia for vulval cancer. A meta-analysis was not feasible due to heterogeneity in study design, analgesic interventions (i.e., opioids, local anesthetics, paracetamol, NSAIDs, and holistic and complementary therapies), and multiple routes of administration (i.e., oral, parenteral, regional, neuraxial, local infiltration, intraperitoneal, intramuscular, patient-controlled, topical, and rectal). No single analgesic modality demonstrated clear superiority. The median Jadad score for methodological quality of the included trials was 4. Conclusions: The limited cancer-specific RCTs and diversity of analgesia modalities utilized reflect the wide range of applications. Postoperative pain is multifactorial and cannot be adequately managed with a single agent. National and international guidelines should aim to establish a standardized framework for postoperative pain management in gynecological cancers, ensuring accessible, evidence-based care that enhances both short- and long-term patient quality of life
Transport and mixing in control volumes through the lens of probability
No full textA partial differential equation governing the evolution of the joint probability distribution of multicomponent flow observations, drawn randomly from one or more control volumes, is derived and applied to examples involving irreversible mixing. Unlike local probability density methods, this work adopts an integral perspective by regarding a control volume as a sample space with an associated probability distribution. A natural and general definition for the boundary of such control volumes comes from the magnitude of the gradient of the sample space distribution, which can accommodate Eulerian or Lagrangian frames of reference as particular cases. The resulting equation exposes contributions made by uncertain or stochastic boundary fluxes and internal cross-gradient mixing in the equation governing the observables’ joint probability distribution. Advection and diffusion over a control volume’s boundary result in source and drift terms, respectively, whereas internal mixing, in general, corresponds to the sign-indefinite diffusion of probability density. Several typical circumstances for which the corresponding diffusion coefficient is negative semidefinite are identified and discussed in detail. The framework is a natural setting for examining available potential energy, the incorporation of uncertainty into bulk models and establishing a link with the Feynman-Kac formula and Kolmogorov equations that are used to analyse stochastic processes
Partial nuclear extrusion in chronic lymphocytic leukemia observed to be an in vitro artefact
No full textComparing NASA discovery and new frontiers class mission concepts for the Io volcano observer
No full textJupiter’s moon Io is a highly compelling target for future exploration that offers critical insight into tidal dissipation processes and the geology of high heat flux worlds, including primitive planetary bodies, such as the early Earth, that are shaped by enhanced rates of volcanism. Io is important for understanding the development of volcanogenic atmospheres and mass exchange within the Jupiter system. However, fundamental questions remain about the state of Io’s interior, surface, and atmosphere, as well as its role in the evolution of the Galilean satellites. The Io Volcano Observer (IVO) would advance answers to these questions by addressing three key goals: (A) determine how and where tidal heat is generated inside Io, (B) understand how tidal heat is transported to the surface of Io, and (C) understand how Io is evolving. IVO was selected for Phase A study through the NASA Discovery program in 2020, and, in anticipation of the next New Frontiers (NF) opportunity, an enhanced IVO-NF mission concept would increase the Baseline mission from 10 flybys to 20, with an improved radiation design; employ a Ka-band communication system to double IVO’s total data downlink; add a wide-angle camera for color and stereo mapping; add a dust mass spectrometer; and lower the altitude of later flybys to enable new science. This study compares the architecture, instrument suite, and science objectives for Discovery (IVO) and NF (IVO-NF) missions to Io. IVO can achieve outstanding science results at the Discovery level, but we advocate for continued prioritization of Io for NF