Engaging teenagers with text-message services for glycaemic control

Commentary on: McGill, D E., Volkening, D.A., Wasserman, R.M., Anderson, B.J., and Laffel, L.M. (2019). Text-message responsiveness is associated with HbA1c benefit in teenagers with Type 1 diabetes. Diabetic Medicine. Diabet Med. 2019 May;36(5):600-605. doi: 10.1111/dme.13929

Belongingness: Student ODPs’ learning experiences in clinical placements

The aim of this qualitative study is to explore student Operating Department Practitioners’ experiences of belongingness in clinical placements. Belongingness has been shown to be significant for learning in clinical placements for student nurses and midwives. This study was designed to look specifically at student Operating Department Practitioners’ experiences. Semi-structured interviews were conducted with eight student Operating Department Practitioners. The interviews were transcribed and coded. All student Operating Department Practitioners could describe clinical placement experiences where they felt they belonged and those where they felt they did not belong. Both had a significant impact on students learning experience. Students also described their own sense of responsibility for belonging while in placement. This study provides qualitative data to help understand how belongingness can positively or negatively affect, the learning experiences of student Operating Department Practitioners in clinical placements

Experiences of nurse case managers within a central discharge planning role of collaboration between physicians, patients and other healthcare professionals: a sociocultural qualitative study

Aims and objectives. Purpose of this study was to gain knowledge of Nurse Case Managers’ (NCM) experiences within the German acute care context of collaboration with patients and physicians in a discharge planning role. Further to learn about patients’ assignment to the management of the NCMs. Explicitly, to explore critical incidences of interactions between NCM, patients and health care practitioner in discharge planning to understand the factor that contributes to effective collaboration. Background and Purpose. The defined role of Nursing Case Manager (NCM) in many contexts is a patient-centred responsibility for a central task of discharge management of patients with complex physical and social needs. Some studies have indicated that the general impact of the role reduces readmission rates. Given the necessity to work interprofessionally to achieve a safe discharge little is known about how NCMs achieve this collaboratively. Methods. A qualitative case study within a German teaching hospital of NCMs (N=8). Data were collected through semi-structured interviews prompted by a critical incident technique and rigorously analysed through the lenses of sociocultural theory. Results. Consistent object being worked upon was a safe and effective discharge from hospital with a focus on patient advocacy. Significant themes were a self-value or recognition by others of professional expertise, reciprocal value on the capabilities of others thorough relational expertise and negotiation with patients and an identification of case trajectories. Conclusion. More continuity of NCMs’ care and management, clarity of role and transparency to peers, physicians and other professionals would be beneficial in ensuring appropriate referral of complex patients to NCM responsibility. Relevance to clinical practice. Clearer role description and benefit realisation of the NCM could be achieved by interventions that are interprofessional and focus on the tasks that matter from a collaborative perspective. This could lead to refinement of available indicators and policy developments

Human factors and data logging processes with the use of advanced technology for adults with type 1 diabetes (T1DM): A systematic integrative review

Background: People with T1DM are confronted with self-management tasks and strategies to reduce risks of long-term complications against the risk of hypoglycemic events. The potential of advanced and evolving technology to address these issues involves consideration of psychological and behavioral constructs alongside the usability of devices. Access and uptake of advanced technology is further influenced by economic factors and health care provider capacity to support such interventions. Previous reviews have focused upon either clinical outcomes or descriptively scoped the literature or have synthesized studies on adults with children and young people where human factors are different. Objective: The objective of this review was to describe the relationship between human factors and adherence with technology for data logging processes in adults (> 18 years) with T1DM and to explore the factors which influence this association. Methods: A systematic literature review. Results: 18 studies were included in the review following a literature search using the PRISMA guidelines and a quality appraisal process. This included 3320 participants with a mean age of 42 years. Overall, adults felt more satisfied with their treatment on transition to advanced technology (insulin pump and CGM), the most significant contributing factor was when BG levels were consistently < 7.00mmol/l (P =.009). However, participants spent considerable time on their diabetes self-care. There was evidence that logging of data was positively correlated with increasing age with the use of an app that provided meaningful feedback (regression coefficient = 55.8 recordings/ year; P = 0.009). Furthermore, there were benefits of CGM use for older adults in mediating complexities and their fears of hypoglycemia with reported significant differences in well-being (P= .009). Qualitative studies within the review aimed to explore the use and uptake of technology within the context of everyday lives. Participants experienced ‘frustrations’ with CGM, CSII, calibration of devices and alarms. In addition, there were implications for ‘body image’ when carrying and using a device. This takes into account wide variations in individual use and interaction with technology across a continuum of sociocultural contexts. This has implications for the way in which future technologies are designed. Conclusions: Many of the quantitative studies in the review were limited by small sample sizes. This may make it difficult to generalize findings to other contexts. This is further limited by a sample that was predominantly Caucasian, well-controlled and engaged with their self-care. However, the use of critical appraisal frameworks has highlighted areas where research into human factors and data logging processes of individuals could be improved. This includes engaging people in the design of the technology, and further exploration of the way in which significant others impact on the behavior and attitude of the individual towards technology use

Fifteen essential science advances needed for effective restoration of the world's forest landscapes

There has never been a more pressing and opportune time for science and practice to collaborate towards restoration of the world's forests. Multiple uncertainties remain for achieving successful, long-term forest landscape restoration (FLR). In this article, we use expert knowledge and literature review to identify knowledge gaps that need closing to advance restoration practice, as an introduction to a landmark theme issue on FLR and the UN Decade on Ecosystem Restoration. Aligned with an Adaptive Management Cycle for FLR, we identify 15 essential science advances required to facilitate FLR success for nature and people. They highlight that the greatest science challenges lie in the conceptualization, planning and assessment stages of restoration, which require an evidence base for why, where and how to restore, at realistic scales. FLR and underlying sciences are complex, requiring spatially explicit approaches across disciplines and sectors, considering multiple objectives, drivers and trade-offs critical for decision-making and financing. The developing tropics are a priority region, where scientists must work with stakeholders across the Adaptive Management Cycle. Clearly communicated scientific evidence for action at the outset of restoration planning will enable donors, decision makers and implementers to develop informed objectives, realistic targets and processes for accountability. This article paves the way for 19 further articles in this theme issue, with author contributions from across the world. This introduction article is part of the theme issue ‘Understanding forest landscape restoration: reinforcing scientific foundations for the UN Decade on Ecosystem Restoration’

A manually annotated Actinidia chinensis var. chinensis (kiwifruit) genome highlights the challenges associated with draft genomes and gene prediction in plants

Most published genome sequences are drafts, and most are dominated by computational gene prediction. Draft genomes typically incorporate considerable sequence data that are not assigned to chromosomes, and predicted genes without quality confidence measures. The current Actinidia chinensis (kiwifruit) 'Hongyang' draft genome has 164\ua0Mb of sequences unassigned to pseudo-chromosomes, and omissions have been identified in the gene models

Identification of the top TESS objects of interest for atmospheric characterization of transiting exoplanets with JWST

Funding: Funding for the TESS mission is provided by NASA's Science Mission Directorate. This work makes use of observations from the LCOGT network. Part of the LCOGT telescope time was granted by NOIRLab through the Mid-Scale Innovations Program (MSIP). MSIP is funded by NSF. This paper is based on observations made with the MuSCAT3 instrument, developed by the Astrobiology Center and under financial support by JSPS KAKENHI (grant No. JP18H05439) and JST PRESTO (grant No. JPMJPR1775), at Faulkes Telescope North on Maui, HI, operated by the Las Cumbres Observatory. This paper makes use of data from the MEarth Project, which is a collaboration between Harvard University and the Smithsonian Astrophysical Observatory. The MEarth Project acknowledges funding from the David and Lucile Packard Fellowship for Science and Engineering, the National Science Foundation under grant Nos. AST-0807690, AST-1109468, AST-1616624 and AST-1004488 (Alan T. Waterman Award), the National Aeronautics and Space Administration under grant No. 80NSSC18K0476 issued through the XRP Program, and the John Templeton Foundation. C.M. would like to gratefully acknowledge the entire Dragonfly Telephoto Array team, and Bob Abraham in particular, for allowing their telescope bright time to be put to use observing exoplanets. B.J.H. acknowledges support from the Future Investigators in NASA Earth and Space Science and Technology (FINESST) program (grant No. 80NSSC20K1551) and support by NASA under grant No. 80GSFC21M0002. K.A.C. and C.N.W. acknowledge support from the TESS mission via subaward s3449 from MIT. D.R.C. and C.A.C. acknowledge support from NASA through the XRP grant No. 18-2XRP18_2-0007. C.A.C. acknowledges that this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). S.Z. and A.B. acknowledge support from the Israel Ministry of Science and Technology (grant No. 3-18143). The research leading to these results has received funding from the ARC grant for Concerted Research Actions, financed by the Wallonia-Brussels Federation. TRAPPIST is funded by the Belgian Fund for Scientific Research (Fond National de la Recherche Scientifique, FNRS) under the grant No. PDR T.0120.21. The postdoctoral fellowship of K.B. is funded by F.R.S.-FNRS grant No. T.0109.20 and by the Francqui Foundation. H.P.O.'s contribution has been carried out within the framework of the NCCR PlanetS supported by the Swiss National Science Foundation under grant Nos. 51NF40_182901 and 51NF40_205606. F.J.P. acknowledges financial support from the grant No. CEX2021-001131-S funded by MCIN/AEI/ 10.13039/501100011033. A.J. acknowledges support from ANID—Millennium Science Initiative—ICN12_009 and from FONDECYT project 1210718. Z.L.D. acknowledges the MIT Presidential Fellowship and that this material is based upon work supported by the National Science Foundation Graduate Research Fellowship under grant No. 1745302. P.R. acknowledges support from the National Science Foundation grant No. 1952545. This work is partly supported by JSPS KAKENHI grant Nos. JP17H04574, JP18H05439, JP21K20376; JST CREST grant No. JPMJCR1761; and Astrobiology Center SATELLITE Research project AB022006. This publication benefits from the support of the French Community of Belgium in the context of the FRIA Doctoral Grant awarded to M.T. D.D. acknowledges support from TESS Guest Investigator Program grant Nos. 80NSSC22K1353, 80NSSC22K0185, and 80NSSC23K0769. A.B. acknowledges the support of M.V. Lomonosov Moscow State University Program of Development. T.D. was supported in part by the McDonnell Center for the Space Sciences. V.K. acknowledges support from the youth scientific laboratory project, topic FEUZ-2020-0038.JWST has ushered in an era of unprecedented ability to characterize exoplanetary atmospheres. While there are over 5000 confirmed planets, more than 4000 Transiting Exoplanet Survey Satellite (TESS) planet candidates are still unconfirmed and many of the best planets for atmospheric characterization may remain to be identified. We present a sample of TESS planets and planet candidates that we identify as “best-in-class” for transmission and emission spectroscopy with JWST. These targets are sorted into bins across equilibrium temperature Teq and planetary radius Rp and are ranked by a transmission and an emission spectroscopy metric (TSM and ESM, respectively) within each bin. We perform cuts for expected signal size and stellar brightness to remove suboptimal targets for JWST. Of the 194 targets in the resulting sample, 103 are unconfirmed TESS planet candidates, also known as TESS Objects of Interest (TOIs). We perform vetting and statistical validation analyses on these 103 targets to determine which are likely planets and which are likely false positives, incorporating ground-based follow-up from the TESS Follow-up Observation Program to aid the vetting and validation process. We statistically validate 18 TOIs, marginally validate 31 TOIs to varying levels of confidence, deem 29 TOIs likely false positives, and leave the dispositions for four TOIs as inconclusive. Twenty-one of the 103 TOIs were confirmed independently over the course of our analysis. We intend for this work to serve as a community resource and motivate formal confirmation and mass measurements of each validated planet. We encourage more detailed analysis of individual targets by the community.Peer reviewe

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing