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Parcel-level risk (PLR) describes how wildfire risk varies from home to home based on characteristics that relate to likely fire behavior, the susceptibility of homes to fire, and the ability of firefighters to safely access properties. Here, we describe the WiRē Rapid Assessment (RA), a parcel-level rapid wildfire risk assessment tool designed to evaluate PLR with a small set of measures for all homes in a community. We investigate the relationship between 2019 WiRē RA data collected in the Columbine Lake community in Grand County, Colorado, and whether assessed homes were destroyed in the 2020 East Troublesome Fire. We find that the overall parcel-level risk scores, as well as many individual attributes, relate to the chance that a home was destroyed. We also find strong evidence of risk spillovers across neighboring properties. The results demonstrate that even coarsely measured RA data capture meaningful differences in wildfire risk across a community. The findings also demonstrate the importance of accounting for multiple aspects of PLR, including both hazards and susceptibility, when assessing the risk of wildfire to homes and communities. Finally, the results underscore that relatively small actions by residents before a fire can influence wildfire outcomes.

Intrinsically disordered proteins (IDPs) present a functional paradox because they lack stable tertiary structure, but nonetheless play a central role in signaling, utilizing a process known as allostery. Historically, allostery in structured proteins has been interpreted in terms of propagated structural changes that are induced by effector binding. Thus, it is not clear how IDPs, lacking such well-defined structures, can allosterically affect function. Here, we show a mechanism by which an IDP can allosterically control function by simultaneously tuning transcriptional activation and repression, using a novel strategy that relies on the principle of ‘energetic frustration’. We demonstrate that human glucocorticoid receptor tunes this signaling in vivo by producing translational isoforms differing only in the length of the disordered region, which modulates the degree of frustration. We expect this frustration-based model of allostery will prove to be generally important in explaining signaling in other IDPs. Proteins carry out most of the key tasks inside cells. To perform these roles, proteins must fold up to form complex three-dimensional structures. Researchers used to think that the useful parts of proteins all had set structures. However, we now know that ‘disordered’ proteins with variable structures are common and disordered parts of proteins can have vital roles. In a process called allosteric regulation, regulator molecules can increase or decrease the activity of a protein by binding to it. This binding was thought to work by changing the structure of the protein, but it was not clear how this works in disordered proteins. To investigate, Li et al. studied a disordered protein called glucocorticoid receptor, and found that disordered regions can have opposing effects on other regions of the protein. This creates a ‘tug-of-war’ that Li et al. term “energetic frustration”, whereby the activity of the protein results from the combination of the opposing interactions. Further investigation revealed that the glucorticoid receptor produces different versions of itself that have different degrees of energetic frustration, which alters how effectively the proteins perform their tasks. This means that the protein can regulate its own activity even in the absence of binding to regulator molecules. The concept of energetic frustration could enhance our understanding of the many different proteins that contain disordered regions. Eventually, this knowledge could be used to develop drugs that alter the activity of these proteins and so could form part of treatments for a wide range of conditions including autoimmune diseases (such as rheumatoid arthritis and lupus), cancers, and organ rejection for transplant patients. The results presented by Li et al. suggest where more research is needed to achieve this goal. For example, we need to understand more about the stability of disordered protein regions, and to identify which surfaces of the proteins interact with each other.

Ergot alkaloids present in endophyte-infected tall fescue can cause a series of negative effects in exposed cattle. This study evaluated the effectiveness of molasses-based block supplements (MBSs) in alleviating vasoconstriction, which leads to reduced peripheral blood flow, heat stress, and impaired growth performance in cattle. A total of 100 crossbred steers were assigned to five treatment groups: a negative control with no tall fescue seed; a positive control with ergot-infected tall fescue seeds; and three MBS treatments, including a control block, a block containing menthol, and a block containing capsaicin. Blood flow was assessed through ultrasound imaging of the coccygeal artery, while thermal imaging was used to monitor body temperature regulation. Growth performance, feed intake, and blood biomarkers were also measured. Cattle consuming MBS had improved weight gain, greater arterial diameters, and enhanced thermoregulation compared to those without supplements. No significant differences were observed between the different MBS formulations. These results suggest that molasses-based block supplementation can help mitigate heat stress and poor growth performance associated with ergot alkaloid consumption, potentially providing a practical nutritional strategy for cattle producers managing cattle exposed to ergot alkaloids.

•64% of the sample indicated willingness to get a Lyme disease vaccine.•30% were uncertain about getting a Lyme disease vaccine; 7% were unwilling.•The uncertain were parents, were non-white, and had vaccine safety concerns.•Safety messaging should be delivered by clinicians, especially to uncertain groups.•More studies will be useful once Lyme disease vaccine parameters are available. Lyme disease incidence is increasing, despite current prevention options. New Lyme disease vaccine candidates are in development, however, investigation of the acceptability of a Lyme disease vaccine among potential consumers is needed prior to any vaccine coming to market. We conducted a population-based, cross-sectional study to estimate willingness to receive a potential Lyme disease vaccine and factors associated with willingness. The web-based survey was administered to a random sample of Connecticut, Maryland, Minnesota, and New York residents June–July 2018. Survey-weighted descriptive statistics were conducted to estimate the proportion willing to receive a potential Lyme disease vaccine. Multivariable multinomial logistic regression models were used to quantify the association of sociodemographic characteristics and Lyme disease vaccine attitudes with willingness to be vaccinated. Surveys were completed by 3313 respondents (6% response rate). We estimated that 64% of residents were willing to receive a Lyme disease vaccine, while 30% were uncertain and 7% were unwilling. Compared to those who were willing, those who were uncertain were more likely to be parents, adults 45–65 years old, non-White, have less than a bachelor’s degree, or have safety concerns about a potential Lyme disease vaccine. Those who were unwilling were also more likely to be non-White, have less than a bachelor’s degree, or have safety concerns about a potential Lyme disease vaccine. In addition, the unwilling had low confidence in vaccines in general, had low perceived risk of contracting Lyme disease, and said they would not be influenced by a positive recommendation from a healthcare provider. Overall, willingness to receive a Lyme disease vaccine was high. Effective communication by clinicians regarding safety and other vaccine parameters to those groups who are uncertain will be critical for increasing vaccine uptake and reducing Lyme disease incidence.

Background Mannheimia haemolytica strains isolated from North American cattle have been classified into two genotypes (1 and 2). Although members of both genotypes have been isolated from the upper and lower respiratory tracts of cattle with or without bovine respiratory disease (BRD), genotype 2 strains are much more frequently isolated from diseased lungs than genotype 1 strains. The mechanisms behind the increased association of genotype 2  M. haemolytica with BRD are not fully understood. To address that, and to search for interventions against genotype 2  M. haemolytica , complete, closed chromosome assemblies for 35 genotype 1 and 34 genotype 2 strains were generated and compared. Searches were conducted for the pan genome, core genes shared between the genotypes, and for genes specific to either genotype. Additionally, genes encoding outer membrane proteins (OMPs) specific to genotype 2  M. haemolytica were identified, and the diversity of their protein isoforms was characterized with predominantly unassembled, short-read genomic sequences for up to 1075 additional strains. Results The pan genome of the 69 sequenced M. haemolytica strains consisted of 3111 genes, of which 1880 comprised a shared core between the genotypes. A core of 112 and 179 genes or gene variants were specific to genotype 1 and 2, respectively. Seven genes encoding predicted OMPs; a peptidase S6, a ligand-gated channel, an autotransporter outer membrane beta-barrel domain-containing protein (AOMB-BD-CP), a porin, and three different trimeric autotransporter adhesins were specific to genotype 2 as their genotype 1 homologs were either pseudogenes, or not detected. The AOMB-BD-CP gene, however, appeared to be truncated across all examined genotype 2 strains and to likely encode dysfunctional protein. Homologous gene sequences from additional M. haemolytica strains confirmed the specificity of the remaining six genotype 2 OMP genes and revealed they encoded low isoform diversity at the population level. Conclusion Genotype 2  M. haemolytica possess genes encoding conserved OMPs not found intact in more commensally prone genotype 1 strains. Some of the genotype 2 specific genes identified in this study are likely to have important biological roles in the pathogenicity of genotype 2  M. haemolytica , which is the primary bacterial cause of BRD.

Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021-22 and 2022-23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021-22 and 12 out of 18 models in 2022-23. Averaging across all forecast targets, the FluSight ensemble is the 2 most accurate model measured by WIS in 2021-22 and the 5 most accurate in the 2022-23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change.

Internal carotid artery (ICA) dissection is a rare and potentially devastating cause of cerebral ischaemia, initiated by an intimal tear or rupture of the vasa vasorum, that can lead to an intraluminal thrombus, vascular stenosis, occlusion, or dissecting aneurysm formation. Management is challenging due to its complex pathophysiology and non‐specific nature of symptoms. In this case–control study, we were able to document the clinical presentation and management of an ICA dissection in a hypertensive, 50‐year‐old male triathlete following an acute bout of intermittent apnoeic (pyramid breathing) swimming. He developed blurred vision in his left eye, ipsilateral headache, pulsatile tinnitus and later noticed left‐sided ptosis and pupil miosis consistent with Horner's syndrome, prompting specialist referral. Neuroimaging confirmed a dissection of the left ICA and incidental pseudoaneurysm of the distal right ICA. The patient recovered well due to a combination of pharmacological/dietary management of hypertension and graduated, structured return to physical activity and competition, culminating in significant re‐expansion of the ICA true lumen calibre. We also conducted a laboratory‐based, dry‐land, static swimming simulation in an age‐ and physical activity‐matched healthy male control. This demonstrated that exercise‐induced ICA shear stress was more exaggerated during dynamic apnoeic breathing compared to normal breathing, which, in the setting of the patient's hypertension, may have been a precipitating factor underlying ICA dissection. Collectively, these findings provide unique insights into the pathophysiology and management of this rare condition while highlighting the inherent risks associated with this mode of exercise training in susceptible individuals with hypertension. What is the main observation in this case? This case–control study describes the clinical presentation and treatment of a hypertensive competitive male triathlete who suffered an internal carotid artery (ICA) dissection after intermittent apnoeic (pyramid breathing) swimming. Dry‐land, static swimming simulated in a healthy male control demonstrated that this mode of exercise caused an exaggerated elevation in ICA shear stress, which may have been a precipitating factor. What insights does it reveal? These findings highlight the inherent risks in this mode of exercise and provide unique insights into the pathophysiology and management of this rare and potentially devastating cause of cerebral ischaemia.

Background Mannheimia haemolytica typically resides in cattle as a commensal member of the upper respiratory tract microbiome. However, some strains can invade their lungs and cause respiratory disease and death, including those with multi-drug resistance. A nucleotide polymorphism typing system was developed for M. haemolytica from the genome sequences of 1133 North American isolates, and used to identify genetic differences between isolates from the lungs and upper respiratory tract of cattle with and without clinical signs of respiratory disease. Results A total of 26,081 nucleotide polymorphisms were characterized after quality control filtering of 48,403 putative polymorphisms. Phylogenetic analyses of nucleotide polymorphism genotypes split M. haemolytica into two major genotypes (1 and 2) that each were further divided into multiple subtypes. Multiple polymorphisms were identified with alleles that tagged genotypes 1 or 2, and their respective subtypes. Only genotype 2 M. haemolytica associated with the lungs of diseased cattle and the sequence of a particular integrative and conjugative element (ICE). Additionally, isolates belonging to one subtype of genotype 2 (2b), had the majority of antibiotic resistance genes detected in this study, which were assorted into seven combinations that ranged from 1 to 12 resistance genes. Conclusions Typing of diverse M. haemolytica by nucleotide polymorphism genotypes successfully identified associations with diseased cattle lungs, ICE sequence, and antibiotic resistance genes. Management of cattle by their carriage of M. haemolytica could be an effective intervention strategy to reduce the prevalence of respiratory disease and supplemental needs for antibiotic treatments in North American herds.

Background: As machine learning becomes increasingly utilized in orthopaedic clinical research, the application of machine learning methodology to cohort data from the Multicenter ACL Revision Study (MARS) presents a valuable opportunity to translate data into patient-specific insights. Purpose: To apply novel machine learning methodology to MARS cohort data to determine a predictive model of revision anterior cruciate ligament reconstruction (rACLR) graft failure and features most predictive of failure. Study Design: Cohort study; Level of evidence, 3. Methods: The authors prospectively recruited patients undergoing rACLR from the MARS cohort and obtained preoperative radiographs, surgeon-reported intraoperative findings, and 2- and 6-year follow-up data on patient-reported outcomes, additional surgeries, and graft failure. Machine learning models including logistic regression (LR), XGBoost, gradient boosting (GB), random forest (RF), and a validated ensemble algorithm (AutoPrognosis) were built to predict graft failure by 6 years postoperatively. Validated performance metrics and feature importance measures were used to evaluate model performance. Results: The cohort included 960 patients who completed 6-year follow-up, with 5.7% (n = 55) experiencing graft failure. AutoPrognosis demonstrated the highest discriminative power (model area under the receiver operating characteristic curve: AutoPrognosis, 0.703; RF, 0.618; GB, 0.660; XGBoost, 0.680; LR, 0.592), with well-calibrated scores (model Brier score: AutoPrognosis, 0.053; RF, 0.054; GB, 0.057; XGBoost, 0.058; LR, 0.111). The most important features for AutoPrognosis model performance were prior compromised femoral and tibial tunnels (placement and size) and allograft graft type used in current rACLR. Conclusion: The present study demonstrated the ability of the novel AutoPrognosis machine learning model to best predict the risk of graft failure in patients undergoing rACLR at 6 years postoperatively with moderate predictive ability. Femoral and tibial tunnel size and position in prior ACLR and allograft use in current rACLR were all risk factors for rACLR failure in the context of the AutoPrognosis model. This study describes a unique model that can be externally validated with larger data sets and contribute toward the creation of a robust rACLR bedside risk calculator in future studies. Registration: NCT00625885 (ClinicalTrials.gov identifier).