Social Sensing of Heatwaves.

This is the final version. Available on open access from MDPI via the DOI in this recordData Availability Statement: The Twitter data used in this word was collected using the official API (https://developer.twitter.com/en/docs/twitter-api (accessed on 20 August 2020)). The temperature data was collected from the NOAA GSOD dataset (https://www.ncei.noaa.gov/access/search/data-search/global-summary-of-the-day (accessed on 15 August 2020)) and the Met Office MIDAS dataset (https://catalogue.ceda.ac.uk/uuid/220a65615218d5c9cc9e4785a3234bd0 (accessed on 15 August 2020)).Heatwaves cause thousands of deaths every year, yet the social impacts of heat are poorly measured. Temperature alone is not sufficient to measure impacts and "heatwaves" are defined differently in different cities/countries. This study used data from the microblogging platform Twitter to detect different scales of response and varying attitudes to heatwaves within the United Kingdom (UK), the United States of America (US) and Australia. At the country scale, the volume of heat-related Twitter activity increased exponentially as temperature increased. The initial social reaction differed between countries, with a larger response to heatwaves elicited from the UK than from Australia, despite the comparatively milder conditions in the UK. Language analysis reveals that the UK user population typically responds with concern for individual wellbeing and discomfort, whereas Australian and US users typically focus on the environmental consequences. At the city scale, differing responses are seen in London, Sydney and New York on governmentally defined heatwave days; sentiment changes predictably in London and New York over a 24-h period, while sentiment is more constant in Sydney. This study shows that social media data can provide robust observations of public response to heat, suggesting that social sensing of heatwaves might be useful for preparedness and mitigation.Engineering and Physical Sciences Research Council (EPSRC

Social sensing of flood impacts in India: A case study of Kerala 2018

This is the final version. Available on open access from Elsevier via the DOI in this recordData availability: The Twitter data used in this word was purchased using the official Twitter PowerTrack API (https://developer.twitter.com/en/docs/twitter-api/enterprise/powertrack-api/overview (accessed on 15 December 2020)). The Telegram data was collected from the Telegram desktop application (https://telegram.org/blog/export-and-more (accessed on 13 October 2020)). The Kerala Rescue data was initially sourced from the RebuildEarth Slack channel (https://rebuildearth.slack.com/(accessed on 15 October 2020)). The Rebuild Kerala data was collected from the Rebuild Kerala Database site (https://rebuild.lsgkerala.gov.in/rebuild2018/(accessed on 6 November 2020)).Flooding is a major hazard that is responsible for substantial damage and risks to human health worldwide. The 2018 flood event in Kerala, India, killed 433 people and displaced more than 1 million people from their homes. Accurate and timely information can help mitigate the impacts of flooding through better preparedness (e.g. forecasting of flood impacts) and situational awareness (e.g. more effective civil response and relief). However, good information on flood impacts is difficult to source; governmental records are often slow and costly to produce, while insurance claim data is commercially sensitive and does not exist for many vulnerable populations. Here we explore “social sensing” – the systematic collection and analysis of social media data to observe real-world events – as a method to locate and characterise the impacts (social, economic and other) of the 2018 Kerala Floods. Data is collected from two social media platforms, Telegram and Twitter, as well as a citizen-produced relief coordination web application, Kerala Rescue, and a government flood damage database, Rebuild Kerala. After careful filtering to retain only flood-related social media posts, content is analysed to map the extent of flood impacts and to identify different kinds of impact (e.g. requests for help, reports of medical or other issues). Maps of flood impacts derived from Telegram and Twitter both show substantial agreement with Kerala Rescue and the damage reports from Rebuild Kerala. Social media content also detects similar kinds of impact to those reported through the more structured Kerala Rescue application. Overall, the results suggest that social sensing can be an effective source of flood impact information that produces outputs in broad agreement with government sources. Furthermore, social sensing information can be produced in near real-time, whereas government records take several months to produce. This suggests that social sensing may be a useful data source to guide decisions around flood relief and emergency response.Newton FundWCSSP IndiaNatural Environment Research Council (NERC)Engineering and Physical Sciences Research Council (EPSRC

Social sensing of heatwaves

Heatwaves cause thousands of deaths every year, yet the social impacts of heat are poorly measured. Temperature alone is not sufficient to measure impacts and “heatwaves” are defined differently in different cities/countries. This study used data from the microblogging platform Twitter to detect different scales of response and varying attitudes to heatwaves within the United Kingdom (UK), the United States of America (US) and Australia. At the country scale, the volume of heat-related Twitter activity increased exponentially as temperature increased. The initial social reaction differed between countries, with a larger response to heatwaves elicited from the UK than from Australia, despite the comparatively milder conditions in the UK. Language analysis reveals that the UK user population typically responds with concern for individual wellbeing and discomfort, whereas Australian and US users typically focus on the environmental consequences. At the city scale, differing responses are seen in London, Sydney and New York on governmentally defined heatwave days; sentiment changes predictably in London and New York over a 24-h period, while sentiment is more constant in Sydney. This study shows that social media data can provide robust observations of public response to heat, suggesting that social sensing of heatwaves might be useful for preparedness and mitigation

miR-132/212 knockout mice reveal roles for these miRNAs in regulating cortical synaptic transmission and plasticity

miR-132 and miR-212 are two closely related miRNAs encoded in the same intron of a small non-coding gene, which have been suggested to play roles in both immune and neuronal function. We describe here the generation and initial characterisation of a miR-132/212 double knockout mouse. These mice were viable and fertile with no overt adverse phenotype. Analysis of innate immune responses, including TLR-induced cytokine production and IFNβ induction in response to viral infection of primary fibroblasts did not reveal any phenotype in the knockouts. In contrast, the loss of miR-132 and miR-212, while not overtly affecting neuronal morphology, did affect synaptic function. In both hippocampal and neocortical slices miR-132/212 knockout reduced basal synaptic transmission, without affecting paired-pulse facilitation. Hippocampal long-term potentiation (LTP) induced by tetanic stimulation was not affected by miR-132/212 deletion, whilst theta burst LTP was enhanced. In contrast, neocortical theta burst-induced LTP was inhibited by loss of miR-132/212. Together these results indicate that miR-132 and/or miR-212 play a significant role in synaptic function, possibly by regulating the number of postsynaptic AMPA receptors under basal conditions and during activity-dependent synaptic plasticity

SynthRAD2023 Grand Challenge dataset: generating synthetic CT for radiotherapy

Purpose: Medical imaging has become increasingly important in diagnosing and treating oncological patients, particularly in radiotherapy. Recent advances in synthetic computed tomography (sCT) generation have increased interest in public challenges to provide data and evaluation metrics for comparing different approaches openly. This paper describes a dataset of brain and pelvis computed tomography (CT) images with rigidly registered CBCT and MRI images to facilitate the development and evaluation of sCT generation for radiotherapy planning. Acquisition and validation methods: The dataset consists of CT, CBCT, and MRI of 540 brains and 540 pelvic radiotherapy patients from three Dutch university medical centers. Subjects' ages ranged from 3 to 93 years, with a mean age of 60. Various scanner models and acquisition settings were used across patients from the three data-providing centers. Details are available in CSV files provided with the datasets. Data format and usage notes: The data is available on Zenodo (https://doi.org/10.5281/zenodo.7260705) under the SynthRAD2023 collection. The images for each subject are available in nifti format. Potential applications: This dataset will enable the evaluation and development of image synthesis algorithms for radiotherapy purposes on a realistic multi-center dataset with varying acquisition protocols. Synthetic CT generation has numerous applications in radiation therapy, including diagnosis, treatment planning, treatment monitoring, and surgical planning.Comment: 15 pages, 4 figures, 9 tables, pre-print submitted to Medical Physics - dataset. The training dataset is available on Zenodo at https://doi.org/10.5281/zenodo.7260705 from April, 1st 202

Results of isolated posterolateral corner reconstruction

BACKGROUND: Isolated posterolateral corner (PLC) tears are relatively rare events. Various surgical techniques to treat posterolateral knee instability have been described; because surgical results are linked to cruciate reconstructions it has been difficult to date to define whether one surgical procedure has better prognosis than another. The goal of this study is to determine the clinical outcome of PLC reconstruction following fibular-based technique. MATERIALS AND METHODS: We retrospectively evaluated a case series of patients who received isolated PLC reconstruction between March 2005 and January 2007. Ten patients were surgically treated for isolated injuries and were available for follow-up; average patient age was 27.4 years (range 16-47 years). All patients were treated following the fibular-based technique: double femoral tunnel was performed in six patients, while in the remaining four patients, the reconstruction of the PLC was performed with a single femoral tunnel. Six patients had semitendinosus allograft and four had semitendinosus autograft. All patients had the same evaluation and the same rehabilitation protocol. RESULTS: Mean follow-up was 27.5 months (range 18-40 months). Mean range of motion (ROM) was 143.5 degrees for flexion (range 135-150 degrees) and 0.5 degrees for extension (range 0-3 degrees). Three patients showed 1+ on varus stress test, while on Dial test another three patients showed 10 degrees reduction of external rotation compared with contralateral knee. The average Lysholm score was 94 points (range 83-100), and the mean International Knee Documentation Committee (IKDC) subjective result was 88.48 (range 74-96.5). Based on Lysholm score, the results were excellent in eight knees and good in two knees. On IKDC evaluation, two patients were grade A and eight were grade B. No significant difference in clinical results was observed between single and double femoral tunnel. CONCLUSION: Fibular-based technique showed good results in terms of clinical outcome, restoring varus and rotation stability of knees in treatment of chronic isolated PLC injury

The Relationship Between HR Practices and Firm Performance: Examining Causal Order

Significant research attention has been devoted to examining the relationship between HR practices and firm performance, and the research support has assumed HR as the causal variable. Using data from 45 business units (with 62 data points), this study examines how measures of HR practices correlate with past, concurrent, and future operational performance measures. The results indicate that correlations with performance measures at all three times are both high and invariant, and that controlling for past or concurrent performance virtually eliminates the correlation of HR with future performance. Implications are discussed

The catalytic subunit of the system L1 amino acid transporter (S<i>lc7a5</i>) facilitates nutrient signalling in mouse skeletal muscle

The System L1-type amino acid transporter mediates transport of large neutral amino acids (LNAA) in many mammalian cell-types. LNAA such as leucine are required for full activation of the mTOR-S6K signalling pathway promoting protein synthesis and cell growth. The SLC7A5 (LAT1) catalytic subunit of high-affinity System L1 functions as a glycoprotein-associated heterodimer with the multifunctional protein SLC3A2 (CD98). We generated a floxed Slc7a5 mouse strain which, when crossed with mice expressing Cre driven by a global promoter, produced Slc7a5 heterozygous knockout (Slc7a5+/-) animals with no overt phenotype, although homozygous global knockout of Slc7a5 was embryonically lethal. Muscle-specific (MCK Cre-mediated) Slc7a5 knockout (MS-Slc7a5-KO) mice were used to study the role of intracellular LNAA delivery by the SLC7A5 transporter for mTOR-S6K pathway activation in skeletal muscle. Activation of muscle mTOR-S6K (Thr389 phosphorylation) in vivo by intraperitoneal leucine injection was blunted in homozygous MS-Slc7a5-KO mice relative to wild-type animals. Dietary intake and growth rate were similar for MS-Slc7a5-KO mice and wild-type littermates fed for 10 weeks (to age 120 days) with diets containing 10%, 20% or 30% of protein. In MS-Slc7a5-KO mice, Leu and Ile concentrations in gastrocnemius muscle were reduced by ∼40% as dietary protein content was reduced from 30 to 10%. These changes were associated with >50% decrease in S6K Thr389 phosphorylation in muscles from MS-Slc7a5-KO mice, indicating reduced mTOR-S6K pathway activation, despite no significant differences in lean tissue mass between groups on the same diet. MS-Slc7a5-KO mice on 30% protein diet exhibited mild insulin resistance (e.g. reduced glucose clearance, larger gonadal adipose depots) relative to control animals. Thus, SLC7A5 modulates LNAA-dependent muscle mTOR-S6K signalling in mice, although it appears non-essential (or is sufficiently compensated by e.g. SLC7A8 (LAT2)) for maintenance of normal muscle mass