Putting the PASS in Class: Peer Mentors’ Identities in Science Workshops on Campus and Online

In this paper, we analyse the introduction of peer mentors into timetabled classes to understand how in-class mentoring supports students’ learning. The peer mentors in this study are high-achieving students who previously completed the same course and who were hired and trained to facilitate Peer Assisted Study Sessions (PASS). PASS gives students the opportunity to deepen their understanding through revision and active learning and are typically held outside of class time. In contrast, our trial embedded peer mentors into classes for a large (~250 students) first-year workshop-based course. We employed a participatory action research methodology to facilitate the peer mentors’ co-creation of the research process. Data sources include peer mentors’ journal entries, student cohort data, and a focus group with teaching staff. We found that during face-to-face workshops, peer mentors role-modelled ideal student behaviour (e.g., asking questions) rather than acting as additional teachers, and this helped students to better understand how to interact effectively in class. The identity of embedded peer mentors is neither that of teachers nor of students, and it instead spans aspects of both as described using a three-part schema comprising (i) identity, (ii) associated roles, and (iii) associated practices. As we moved classes online mid-semester in response to the COVID-19 pandemic, mentors’ identities remained stable, but mentors adjusted their associated roles and practices, including through the technical aspects of their engagement with students. This study highlights the benefits of embedding mentors in classrooms on campus and online

The same frequency of planets inside and outside open clusters of stars

Most stars and their planets form in open clusters. Over 95 per cent of such clusters have stellar densities too low (less than a hundred stars per cubic parsec) to withstand internal and external dynamical stresses and fall apart within a few hundred million years. Older open clusters have survived by virtue of being richer and denser in stars (1,000 to 10,000 per cubic parsec) when they formed. Such clusters represent a stellar environment very different from the birthplace of the Sun and other planet-hosting field stars. So far more than 800 planets have been found around Sun-like stars in the field. The field planets are usually the size of Neptune or smaller. In contrast, only four planets have been found orbiting stars in open clusters, all with masses similar to or greater than that of Jupiter. Here we report observations of the transits of two Sun-like stars by planets smaller than Neptune in the billion-year-old open cluster NGC6811. This demonstrates that small planets can form and survive in a dense cluster environment, and implies that the frequency and properties of planets in open clusters are consistent with those of planets around field stars in the Galaxy.Comment: 18 pages, 6 figures, 1 table (main text + supplementary information

2024 roadmap for sustainable batteries

Modern batteries are highly complex devices. The cells contain many components—which in turn all have many variations, both in terms of chemistry and physical properties. A few examples: the active materials making the electrodes are coated on current collectors using solvents, binders and additives; the multicomponent electrolyte, contains salts, solvents, and additives; the electrolyte can also be a solid ceramic, polymer or a glass material; batteries also contain a separator, which can be made of glass fibres, polymeric, ceramic, composite, etc. Moving up in scale all these components are assembled in cells of different formats and geometries, coin cells and Swagelok cells for funamental testing and understanding, and pouch, prismatic and cylindrical cells for application. Given this complexity dictated by so many components and variations, there is no wonder that addressing the crucial issue of true sustainability is an extremely challenging task. How can we make sure that each component is sustainable? How can the performance can be delivered using more sustainable battery components? What actions do we need to take to address battery sustainability properly? How do we actually qualify and quantify the sustainability in the best way possible? And perhaps most importantly; how can we all work—academia and battery industry together—to enable the latter to manufacture more sustainable batteries for a truly cleaner future? This Roadmap assembles views from experts from academia, industry, research institutes, and other organisations on how we could and should achieve a more sustainable battery future. The palette has many colours: it discusses the very definition of a sustainable battery, the need for diversification beyond lithium-ion batteries (LIBs), the importance of sustainability assessments, the threat of scarcity of raw materials and the possible impact on future manufacturing of LIBs, the possibility of more sustainable cells by electrode and electrolyte chemistries as well as manufacturing, the important role of new battery chemistries, the crucial role of AI and automation in the discovery of the truly sustainable batteries of the future and the importance of developimg a circular battery economy

2024 roadmap for sustainable batteries

Modern batteries are highly complex devices. The cells contain many components-which in turn all have many variations, both in terms of chemistry and physical properties. A few examples: the active materials making the electrodes are coated on current collectors using solvents, binders and additives; the multicomponent electrolyte, contains salts, solvents, and additives; the electrolyte can also be a solid ceramic, polymer or a glass material; batteries also contain a separator, which can be made of glass fibres, polymeric, ceramic, composite, etc. Moving up in scale all these components are assembled in cells of different formats and geometries, coin cells and Swagelok cells for funamental testing and understanding, and pouch, prismatic and cylindrical cells for application. Given this complexity dictated by so many components and variations, there is no wonder that addressing the crucial issue of true sustainability is an extremely challenging task. How can we make sure that each component is sustainable? How can the performance can be delivered using more sustainable battery components? What actions do we need to take to address battery sustainability properly? How do we actually qualify and quantify the sustainability in the best way possible? And perhaps most importantly; how can we all work-academia and battery industry together-to enable the latter to manufacture more sustainable batteries for a truly cleaner future? This Roadmap assembles views from experts from academia, industry, research institutes, and other organisations on how we could and should achieve a more sustainable battery future. The palette has many colours: it discusses the very definition of a sustainable battery, the need for diversification beyond lithium-ion batteries (LIBs), the importance of sustainability assessments, the threat of scarcity of raw materials and the possible impact on future manufacturing of LIBs, the possibility of more sustainable cells by electrode and electrolyte chemistries as well as manufacturing, the important role of new battery chemistries, the crucial role of AI and automation in the discovery of the truly sustainable batteries of the future and the importance of developimg a circular battery economy

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Universal germline genetic testing in patients with hematologic malignancies using DNA isolated from nail clippings

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Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data