Accessing primary health care: A meta-ethnography of the experiences of British South Asian patients with diabetes, coronary heart disease or a mental health problem

Objectives: To develop an explanatory framework of the problems accessing primary care health services experienced by British South Asian patients with a long-term condition or mental health problem. Methods: This study used meta-ethnographic methods. Published qualitative studies were identified from a structured search of six databases and themes synthesized across studies to develop a new explanatory framework. Results: Initial searches identified 951 potentially relevant records from which a total of 27 articles were identified that met inclusion and exclusion criteria. Twelve of these articles were chosen on the basis of their quality and relevance. These 12 articles described themes relating to the cultural, spatial and temporal dimensions of patient experiences of accessing and using health care. Our interpretive synthesis showed that access to primary care among British South Asians with diabetes, coronary heart disease and psychological health problems is co-constructed and negotiated over time and space along the key domains of the candidacy model of access: from help-seeking to interactions at the interface to following treatment advice. In the case of each condition, British South Asians’ claims to candidacy were constrained where their individual as well as broader social and cultural characteristics lacked fit with professionals’ ways of working and cultural typifications. Conclusion: Interventions that positively affect professionals’ capacity to support patient claims to candidacy are likely to help support British South Asians overcome a broad range of barriers to care for physical and mental health problems. </jats:p

Transparency and sustainability in global commodity supply chains

Over the last few decades rapid advances in processes to collect, monitor, disclose, and disseminate information have contributed towards the development of entirely new modes of sustainability governance for global commodity supply chains. However, there has been very little critical appraisal of the contribution made by different transparency initiatives to sustainability and the ways in which they can (and cannot) influence new governance arrangements. Here we seek to strengthen the theoretical underpinning of research and action on supply chain transparency by addressing four questions: (1) What is meant by supply chain transparency? (2) What is the relevance of supply chain transparency to supply chain sustainability governance? (3) What is the current status of supply chain transparency, and what are the strengths and weaknesses of existing initiatives? and (4) What propositions can be advanced for how transparency can have a positive transformative effect on the governance interventions that seek to strengthen sustainability outcomes? We use examples from agricultural supply chains and the zero-deforestation agenda as a focus of our analysis but draw insights that are relevant to the transparency and sustainability of supply chains in general. We propose a typology to distinguish among types of supply chain information that are needed to support improvements in sustainability governance, and illustrate a number of major shortfalls and systematic biases in existing information systems. We also propose a set of ten propositions that, taken together, serve to expose some of the potential pitfalls and undesirable outcomes that may result from (inevitably) limited or poorly designed transparency systems, whilst offering guidance on some of the ways in which greater transparency can make a more effective, lasting and positive contribution to sustainability

Beyond the black box: promoting mathematical collaborations for elucidating interactions in soil ecology

This work is licensed under a Creative Commons Attribution 4.0 International License.Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant–soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: theory spanning scales and ecological hierarchies, processes, and evolution

Beyond the black box: Promoting mathematical collaborations for elucidating interactions in soil ecology

© 2019 The Authors. Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant-soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: Theory spanning scales and ecological hierarchies, processes, and evolution

Talking about depression: a qualitative study of barriers to managing depression in people with long term conditions in primary care

<p>Abstract</p> <p>Background</p> <p>The risk of depression is increased in people with long term conditions (LTCs) and is associated with poorer patient outcomes for both the depressive illness and the LTC, but often remains undetected and poorly managed. The aim of this study was to identify and explore barriers to detecting and managing depression in primary care in people with two exemplar LTCs: diabetes and coronary heart disease (CHD).</p> <p>Methods</p> <p>Qualitative in-depth interviews were conducted with 19 healthcare professionals drawn predominately from primary care, along with 7 service users and 3 carers (n = 29). One focus group was then held with a set of 6 healthcare professionals and a set of 7 service users and 1 carer (n = 14). Interviews and the focus group were digitally recorded, transcribed verbatim, and analysed independently. The two data sets were then inspected for commonalities using a constant comparative method, leading to a final thematic framework used in this paper.</p> <p>Results</p> <p>Barriers to detecting and managing depression in people with LTCs in primary care exist: i) when practitioners in partnership with patients conceptualise depression as a common and understandable response to the losses associated with LTCs - depression in the presence of LTCs is normalised, militating against its recognition and treatment; ii) where highly performanced managed consultations under the terms of the Quality and Outcomes Framework encourage reductionist approaches to case-finding in people with CHD and diabetes, and iii) where there is uncertainty among practitioners about how to negotiate labels for depression in people with LTCs in ways that might facilitate shared understanding and future management.</p> <p>Conclusion</p> <p>Depression was often normalised in the presence of LTCs, obviating rather than facilitating further assessment and management. Furthermore, structural constraints imposed by the QOF encouraged reductionist approaches to case-finding for depression in consultations for CHD and diabetes. Future work might focus on how interventions that draw on the principles of the chronic care model, such as collaborative care, could support primary care practitioners to better recognise and manage depression in patients with LTCs.</p

Communications Biophysics

Contains reports on eight research projects split into four sections.National Institutes of Health (Grant 5 P01 NS13126)National Institutes of Health (Grant 5 K04 NS00113)National Institutes of Health (Training Grant 5 T32 NS07047)National Science Foundation (Grant BNS80-06369)National Institutes of Health (Grant 5 ROl NS11153)National Institutes of Health (Fellowship 1 F32 NS06544)National Science Foundation (Grant BNS77-16861)National Institutes of Health (Grant 5 R01 NS10916)National Institutes of Health (Grant 5 RO1 NS12846)National Science Foundation (Grant BNS77-21751)National Institutes of Health (Grant 1 R01 NS14092)National Institutes of Health (Grant 2 R01 NS11680)National Institutes of Health (Grant 5 ROl1 NS11080)National Institutes of Health (Training Grant 5 T32 GM07301

Neonatal Colonisation Expands a Specific Intestinal Antigen-Presenting Cell Subset Prior to CD4 T-Cell Expansion, without Altering T-Cell Repertoire

Interactions between the early-life colonising intestinal microbiota and the developing immune system are critical in determining the nature of immune responses in later life. Studies in neonatal animals in which this interaction can be examined are central to understanding the mechanisms by which the microbiota impacts on immune development and to developing therapies based on manipulation of the microbiome. The inbred piglet model represents a system that is comparable to human neonates and allows for control of the impact of maternal factors. Here we show that colonisation with a defined microbiota produces expansion of mucosal plasma cells and of T-lymphocytes without altering the repertoire of alpha beta T-cells in the intestine. Importantly, this is preceded by microbially-induced expansion of a signal regulatory protein α-positive (SIRPα+) antigen-presenting cell subset, whilst SIRPα−CD11R1+ antigen-presenting cells (APCs) are unaffected by colonisation. The central role of intestinal APCs in the induction and maintenance of mucosal immunity implicates SIRPα+ antigen-presenting cells as orchestrators of early-life mucosal immune development

Communications Biophysics

Contains reports on nine research projects split into four sections.National Institutes of Health (Grant 5 P01 NS13126)National Institutes of Health (Grant 5 K04 NS00113)National Institutes of Health (Training Grant 5 T32 NS07047)National Institutes of Health (Grant 5 ROl NS11153-03)National Institutes of Health (Fellowship 1 T32 NS07099-01)National Science Foundation (Grant BNS77-16861)National Institutes of Health (Grant 5 ROl NS10916)National Institutes of Health (Grant 5 ROl NS12846)National Science Foundation (Grant BNS77-21751)National Institutes of Health (Grant 1 RO1 NS14092)Health Sciences FundNational Institutes of Health (Grant 2 R01 NS11680)National Institutes of Health (Grant 2 RO1 NS11080)National Institutes of Health (Training Grant 5 T32 GM07301

A Controversy That Has Been Tough to Swallow: Is the Treatment of Achalasia Now Digested?

Esophageal achalasia is a rare neurodegenerative disease of the esophagus and the lower esophageal sphincter that presents within a spectrum of disease severity related to progressive pathological changes, most commonly resulting in dysphagia. The pathophysiology of achalasia is still incompletely understood, but recent evidence suggests that degeneration of the postganglionic inhibitory nerves of the myenteric plexus could be due to an infectious or autoimmune mechanism, and nitric oxide is the neurotransmitter affected. Current treatment of achalasia is directed at palliation of symptoms. Therapies include pharmacological therapy, endoscopic injection of botulinum toxin, endoscopic dilation, and surgery. Until the late 1980s, endoscopic dilation was the first line of therapy. The advent of safe and effective minimally invasive surgical techniques in the early 1990s paved the way for the introduction of laparoscopic myotomy. This review will discuss the most up-to-date information regarding the pathophysiology, diagnosis, and treatment of achalasia, including a historical perspective. The laparoscopic Heller myotomy with partial fundoplication performed at an experienced center is currently the first line of therapy because it offers a low complication rate, the most durable symptom relief, and the lowest incidence of postoperative gastroesophageal reflux

From Data to Software to Science with the Rubin Observatory LSST

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science.Comment: White paper from "From Data to Software to Science with the Rubin Observatory LSST" worksho