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Background Here, we jointly summarise scientific evidence for genetic variation in resistance to infection with Mycobacterium bovis , the primary agent of bovine tuberculosis ( TB ), provided by two recent and separate studies of Holstein-Friesian dairy cow populations in Great Britain ( GB ) and Ireland. Methods The studies quantified genetic variation within archived data from field and abattoir surveillance control programmes within each country. These data included results from the single intradermal comparative tuberculin test ( SICTT ), abattoir inspection for TB lesions and laboratory confirmation of disease status. Threshold animal models were used to estimate variance components for responsiveness to the SICTT and abattoir confirmed M. bovis infection. The link functions between the observed 0/1 scale and the liability scale were the complementary log-log in the GB, and logit link function in the Irish population. Results and discussion The estimated heritability of susceptibility to TB, as judged by responsiveness to the SICTT, was 0.16 (0.012) and 0.14 (0.025) in the GB and Irish populations, respectively. For abattoir or laboratory confirmation of infection, estimates were 0.18 (0.044) and 0.18 (0.041) from the GB and the Irish populations, respectively. Conclusions Estimates were all significantly different from zero and indicate that exploitable variation exists among GB and Irish Holstein Friesian dairy cows for resistance to TB. Epidemiological analysis suggests that factors such as variation in exposure or imperfect sensitivity and specificity would have resulted in underestimation of the true values.

The treatment landscape of acute myeloid leukemia (AML) is evolving, with promising therapies entering clinical translation, yet patient responses remain heterogeneous, and biomarkers for tailoring treatment are lacking. To understand how disease heterogeneity links with therapy response, we determined the leukemia cell hierarchy makeup from bulk transcriptomes of more than 1,000 patients through deconvolution using single-cell reference profiles of leukemia stem, progenitor and mature cell types. Leukemia hierarchy composition was associated with functional, genomic and clinical properties and converged into four overall classes, spanning Primitive, Mature, GMP and Intermediate. Critically, variation in hierarchy composition along the Primitive versus GMP or Primitive versus Mature axes were associated with response to chemotherapy or drug sensitivity profiles of targeted therapies, respectively. A seven-gene biomarker derived from the Primitive versus Mature axis was associated with response to 105 investigational drugs. Cellular hierarchy composition constitutes a novel framework for understanding disease biology and advancing precision medicine in AML. A novel gene expression classifier of AML heterogeneity captures patient-specific variation in leukemia cell composition and predicts clinical responses to treatment.

It has been argued that climate change is the biggest global health threat of the 21st century. The extreme high temperatures of the summer of 2003 were associated with up to seventy thousand excess deaths across Europe. Previous studies have attributed the meteorological event to the human influence on climate, or examined the role of heat waves on human health. Here, for the first time, we explicitly quantify the role of human activity on climate and heat-related mortality in an event attribution framework, analysing both the Europe-wide temperature response in 2003, and localised responses over London and Paris. Using publicly-donated computing, we perform many thousands of climate simulations of a high-resolution regional climate model. This allows generation of a comprehensive statistical description of the 2003 event and the role of human influence within it, using the results as input to a health impact assessment model of human mortality. We find large-scale dynamical modes of atmospheric variability remain largely unchanged under anthropogenic climate change, and hence the direct thermodynamical response is mainly responsible for the increased mortality. In summer 2003, anthropogenic climate change increased the risk of heat-related mortality in Central Paris by ∼70% and by ∼20% in London, which experienced lower extreme heat. Out of the estimated ∼315 and ∼735 summer deaths attributed to the heatwave event in Greater London and Central Paris, respectively, 64 ( 3) deaths were attributable to anthropogenic climate change in London, and 506 ( 51) in Paris. Such an ability to robustly attribute specific damages to anthropogenic drivers of increased extreme heat can inform societal responses to, and responsibilities for, climate change.

Stomatal conductance schemes that optimize with respect to photosynthetic and hydraulic functions have been proposed to address biases in land‐surface model (LSM) simulations during drought. However, systematic evaluations of both optimality‐based and alternative empirical formulations for coupling carbon and water fluxes are lacking. Here, we embed 12 empirical and optimization approaches within a LSM framework. We use theoretical model experiments to explore parameter identifiability and understand how model behaviors differ in response to abiotic changes. We also evaluate the models against leaf‐level observations of gas‐exchange and hydraulic variables, from xeric to wet forest/woody species spanning a mean annual precipitation range of 361–3,286 mm yr−1. We find that models differ in how easily parameterized they are, due to: (a) poorly constrained optimality criteria (i.e., resulting in multiple solutions), (b) low influence parameters, (c) sensitivities to environmental drivers. In both the idealized experiments and compared to observations, sensitivities to variability in environmental drivers do not agree among models. Marked differences arise in sensitivities to soil moisture (soil water potential) and vapor pressure deficit. For example, stomatal closure rates at high vapor pressure deficit range between −45% and +70% of those observed. Although over half the new generation of stomatal schemes perform to a similar standard compared to observations of leaf‐gas exchange, two models do so through large biases in simulated leaf water potential (up to 11 MPa). Our results provide guidance for LSM development, by highlighting key areas in need for additional experimentation and theory, and by constraining currently viable stomatal hypotheses. Plain Language Summary Water availability is critical for plants to maintain normal function, so droughts have considerable impact on natural ecosystems. However, predicting the impact of future drought on ecosystems is hard because current global models make systematic errors in their predictions of plant responses when water is scarce. In turn, uncertainty in the modeled terrestrial water and carbon cycles remains high. Here, we evaluate a range of new modeling approaches that have the capacity to mechanistically capture plant responses to water stress. Both in theoretical experiments and comparisons to observations, we find large differences among these new modeling approaches in response to water availability and atmospheric dryness. Importantly, some approaches achieve what seems like “good” performance through compensatory mechanisms that are not supported by observations and/or through incorrect representation of plant processes. Our results provide important guidance for future model development, by highlighting areas in need of continued research, and by constraining the range of approaches presently able to reduce uncertainty in modeled plant responses and suitable for inclusion in global models. Key Points Parameter identifiability differs among stomatal conductance schemes, implying some are more suitable to global modeling than others In some schemes, seemingly good performance can result from misrepresentation of physiological processes and sensitivities to model drivers We identify a subset of hydraulics‐based stomatal optimization approaches that could improve predictive capacity in novel climate spaces

We conducted a longitudinal randomized controlled experiment between September 2021 and May 2022 to evaluate whether anti-tobacco industry beliefs and attitudes mediate the effect of culturally tailored anti-smoking messages on quit intentions among US young adult sexual minority women (SMW) ages 18–30 who smoke. Participants were randomized to view up to a total of 20 tailored versus non-tailored messages over one month. Outcomes were assessed at baseline and one-month follow-up. We fit a structural equation model testing the effect of LGBTQ + community-tailored, anti-smoking messages on quit intentions and mediating roles of anti-industry attitudes and beliefs ( n  = 966). Anti-industry beliefs (indirect effect size = 0.024, 95% confidence interval [CI] = [0.040, 0.056]) and attitudes (indirect effect size = 0.034, 95% CI = [0.006, 0.077]) significantly mediated the effect of the tailored condition on quit intentions. These findings suggest that LGBTQ + -tailored cues in anti-smoking messaging may promote quit intentions indirectly through influencing young adult SMW’s beliefs and attitudes about the tobacco industry. Future campaigns to promote quitting among young adult SMW who smoke should consider incorporating themes to change their beliefs and attitudes about the tobacco industry. Trial registration This study was registered in ClinicalTrials.gov (NCT04812795) on 24/03/2021.

BackgroundWe conducted a phase I trial evaluating pembrolizumab+hypofractionated radiotherapy (HFRT) for patients with metastatic cancers.MethodsThere were two strata (12 patients each): (i) NSCLC/melanoma progressing on prior anti-PD-1 therapy, (ii) other cancer types; anti-PD-1-naive. Patients received 6 cycles of pembrolizumab, starting 1 week before HFRT. Patients had ≥2 lesions; only one was irradiated (8 Gy × 3 for first half; 17 Gy × 1 for second half in each stratum) and the other(s) followed for response.ResultsOf the 24 patients, 20 (83%) had treatment-related adverse events (AEs) (all grade 1 or 2). There were eight grade 3 AEs, none treatment related. There were no dose-limiting toxicities or grade 4/5 AEs. Stratum 1: two patients (of 12) with progression on prior PD-1 blockade experienced prolonged responses (9.2 and 28.1 months). Stratum 2: one patient experienced a complete response and two had prolonged stable disease (7.4 and 7.0 months). Immune profiling demonstrated that anti-PD-1 therapy and radiation induced a consistent increase in the proliferation marker Ki67 in PD-1-expressing CD8 T cells.ConclusionsHFRT was well tolerated with pembrolizumab, and in some patients with metastatic NSCLC or melanoma, it reinvigorated a systemic response despite previous progression on anti-PD-1 therapy. Clinical Trial Registration: NCT02303990 (www.clinicaltrials.gov).

Human chromosome 15q25 is involved in several disease-associated structural rearrangements, including microdeletions and chromosomal markers with inverted duplications. Using comparative fluorescence in situ hybridization, strand-sequencing, single-molecule, real-time sequencing and Bionano optical mapping analyses, we investigated the organization of the 15q25 region in human and nonhuman primates. We found that two independent inversions occurred in this region after the fission event that gave rise to phylogenetic chromosomes XIV and XV in humans and great apes. One of these inversions is still polymorphic in the human population today and may confer differential susceptibility to 15q25 microdeletions and inverted duplications. The inversion breakpoints map within segmental duplications containing core duplicons of the GOLGA gene family and correspond to the site of an ancestral centromere, which became inactivated about 25 million years ago. The inactivation of this centromere likely released segmental duplications from recombination repression typical of centromeric regions. We hypothesize that this increased the frequency of ectopic recombination creating a hotspot of hominid inversions where dispersed GOLGA core elements now predispose this region to recurrent genomic rearrangements associated with disease.

Interspecific interactions can play an essential role in shaping wildlife populations and communities. To date, assessments of interspecific interactions, and more specifically predator–prey dynamics, in aquatic systems over broad spatial and temporal scales (i.e., hundreds of kilometers and multiple years) are rare due to constraints on our abilities to measure effectively at those scales. We applied new methods to identify space-use overlap and potential predation risk to Atlantic tarpon (Megalops atlanticus) and permit (Trachinotus falcatus) from two known predators, great hammerhead (Sphyrna mokarran) and bull (Carcharhinus leucas) sharks, over a 3-year period using acoustic telemetry in the coastal region of the Florida Keys (USA). By examining spatiotemporal overlap, as well as the timing and order of arrival at specific locations compared to random chance, we show that potential predation risk from great hammerhead and bull sharks to Atlantic tarpon and permit are heterogeneous across the Florida Keys. Additionally, we find that predator encounter rates with these game fishes are elevated at specific locations and times, including a prespawning aggregation site in the case of Atlantic tarpon. Further, using machine learning algorithms, we identify environmental variability in overlap between predators and their potential prey, including location, habitat, time of year, lunar cycle, depth, and water temperature. These predator–prey landscapes provide insights into fundamental ecosystem function and biological conservation, especially in the context of emerging fisheryrelated depredation issues in coastal marine ecosystems.