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Many nocturnally active fireflies use precisely timed bioluminescent patterns to identify mates, making them especially vulnerable to light pollution. As urbanization continues to brighten the night sky, firefly populations are under constant stress, and close to half of the species are now threatened. Ensuring the survival of firefly biodiversity depends on a large-scale conservation effort to monitor and protect thousands of populations. While species can be identified by their flash patterns, current methods require expert measurement and manual classification and are infeasible given the number and geographic distribution of fireflies. Here we present the application of a recurrent neural network (RNN) for accurate automated firefly flash pattern classification. Using recordings from commodity cameras, we can extract flash trajectories of individuals within a swarm and classify their species with a precision and recall of approximately seventy percent. In addition to scaling population monitoring, automated classification provides the means to study firefly behavior at the population level. We employ the classifier to measure and characterize the variability within and between swarms, unlocking a new dimension of their behavior. Our method is open source, and deployment in community science applications could revolutionize our ability to monitor and understand firefly populations.

Exposure of isolated human islets to proinflammatory cytokines leads to up-regulation of inducible nitric oxide synthase (iNOS), raised NO, and beta cell toxicity. These findings have led to increasing interest in the clinical utility of iNOS blockade to mitigate beta cell destruction in human type 1 diabetes (T1D). However, recent studies show that iNOS-derived NO may also confer beta cell protection. To investigate this dichotomy, we compared islet cell distributions and intensity of iNOS immunostaining in pancreatic sections, co-stained for insulin and glucagon, from new-onset T1D donors (group 1), with non-diabetic autoantibody-negative (group 2), non-diabetic autoantibody-positive (group 3) and long-term diabetic donors (group 4). The cellular origins of iNOS, its frequency and graded intensities in islets and number in peri-islet, intra-islet and exocrine regions were determined. All donors showed iNOS positivity, irrespective of disease and presence of beta cells, had variable labelling intensities, without significant differences in the frequency of iNOS-positive islets among study groups. iNOS was co-localised in selective beta, alpha and other endocrine cells, and in beta cell-negative islets of diabetic donors. The number of peri- and intra-islet iNOS cells was low, being significantly higher in the peri-islet area. Exocrine iNOS cells also remained low, but were much lower in group 1. We demonstrate that iNOS expression in islet cells is variable, heterogeneous and independent of co-existing beta cells. Its distribution and staining intensities in islets and extra-islet areas do not correlate with T1D or its duration. Interventions to inactivate the enzyme to alleviate disease are currently not justified.

Currently, bicuspid aortic valve (BAV) anatomy remains a relative contraindication for transcatheter aortic valve replacement (TAVR) due to concerns of suboptimal anatomy. However, recent advancements in the field have provided a wealth of promising data and more clinicians are opting for TAVR as an alternative to surgical repair. We aim to review and analyze the available data for TAVR in BAV patients, targeting procedural outcomes, clinical outcomes and mortality with up to two years of follow-up.A literature search of five databases was performed and all primary studies published between 2002 and 2021 that reported procedural, clinical or mortality outcome data were identified. Following data extraction, a meta-analysis of means or proportions was performed using a random effects model. Heterogeneity was assessed using the IA total of 22 studies with 1,945 BAV patients were identified. The mean age was 74.1 years and 58.8% of patients were male. Device success rates was 87.5%. Moderate to severe paravalvular leak (PVL) was seen in 3.7% of procedures. Clinical outcomes included new permanent pacemaker insertion (PPI) (11.8%), major bleeding (3.5%), major vascular complications (2.5%), stroke (2.3%), acute kidney injury (2.1%) and coronary obstruction (0.1%). Mortality in hospital, at 30-days, one and two years of follow-up were 1.9%, 2.1%, 9.6% and 12.9%, respectively.This assessment of the available data on TAVR for BAV shows promising outcomes and low rates of complications. However, further research is warranted to reduce the heterogeneity of the available data and provide insight into outcomes beyond two years of follow-up.

In isolation from their peers,Photinus carolinusfireflies flash with no intrinsic period between successive bursts. Yet, when congregating into large mating swarms, these fireflies transition into predictability, synchronizing with their neighbors with a rhythmic periodicity. Here we propose a mechanism for emergence of synchrony and periodicity, and formulate the principle in a mathematical framework. Remarkably, with no fitting parameters, analytic predictions from this simple principle and framework agree strikingly well with data. Next, we add further sophistication to the framework using a computational approach featuring groups of random oscillators via integrate-and-fire interactions controlled by a tunable parameter. This agent-based framework ofP. carolinusfireflies interacting in swarms of increasing density also shows quantitatively similar phenomenology and reduces to the analytic framework in the appropriate limit of the tunable coupling strength. We discuss our findings and note that the resulting dynamics follow the style of a decentralized follow-the-leader synchronization, where any of the randomly flashing individuals may take the role of the leader of any subsequent synchronized flash burst.

Background: In 2015, Bristol (South West England) experienced a large increase in cases of meticillin-resistant Staphylococcus aureus (MRSA) infection in people who inject drugs (PWID). Aim: We aimed to characterise and estimate the prevalence of MRSA colonisation among PWID in Bristol and test evidence of a clonal outbreak. Methods: PWID recruited through an unlinked-anonymous community survey during 2016 completed behavioural questionnaires and were screened for MRSA. Univariable logistic regression examined associations with MRSA colonisation. Whole-genome sequencing used lineage-matched MRSA isolates, comparing PWID (screening and retrospective bacteraemia samples from 2012-2017) with non-PWID (Bristol screening) in Bristol and national reference laboratory database samples. Results: The MRSA colonisation prevalence was 8.7% (13/149) and was associated with frequently injecting in public places (odds ratio (OR): 5.5; 95% confidence interval (CI):1.34–22.70), recent healthcare contact (OR: 4.3; 95% CI: 1.34–13.80) and injecting in groups of three or more (OR: 15.8; 95% CI: 2.51–99.28). People reporting any one of: injecting in public places, injection site skin and soft tissue infection or hospital contact accounted for 12/13 MRSA positive cases (sensitivity 92.3%; specificity 51.5%). Phylogenetic analysis identified a dominant clade associated with infection and colonisation among PWID in Bristol belonging to ST5-SCCmecIVg. Conclusions: MRSA colonisation in Bristol PWID is substantially elevated compared with general population estimates and there is evidence of clonal expansion, community-based transmission and increased infection risk related to the colonising strain. Targeted interventions, including community screening and suppression therapy, education and basic infection control are needed to reduce MRSA infections in PWID.