Search

To adhere to and capitalize on the benefits of the FAIR (findable, accessible, interoperable, and reusable) principles in agricultural genome-to-phenome studies, it is crucial to address privacy and intellectual property issues that prevent sharing and reuse of data in research and industry. Direct sharing of genotype and phenotype data is often prohibited due to intellectual property and privacy concerns. Thus, there is a pressing need for encryption methods that obscure confidential aspects of the data, without affecting the outcomes of certain statistical analyses. A homomorphic encryption method for genotypes and phenotypes (HEGP) has been proposed for single-marker regression in genome-wide association studies (GWAS) using linear mixed models with Gaussian errors. This methodology permits frequentist likelihood-based parameter estimation and inference. In this paper, we extend HEGP to broader applications in genome-to-phenome analyses. We show that HEGP is suited to commonly used linear mixed models for genetic analyses of quantitative traits including genomic best linear unbiased prediction (GBLUP) and ridge-regression best linear unbiased prediction (RR-BLUP), as well as Bayesian variable selection methods (e.g. those in Bayesian Alphabet), for genetic parameter estimation, genomic prediction, and GWAS. By advancing the capabilities of HEGP, we offer researchers and industry professionals a secure and efficient approach for collaborative genomic analyses while preserving data confidentiality.

We describe the case of a returned traveler to the United States from Ecuador who had an acute febrile illness, initially diagnosed as Oropouche fever. This illness was later confirmed to be a rare infection with Iquitos virus, a related bunyavirus that shares 2 of 3 genome segments with Oropouche virus.

Mountain snowpack forecasting relies on accurate mass and energy input information in relation to the snowpack. For this reason, coupled snow–atmosphere models, which downscale input fields to the snow model using atmospheric physics, have been developed. These coupled models are often limited in the spatial and temporal extents of their use by computational constraints. In addressing this challenge, we introduce HICARsnow, an intermediate-complexity coupled snow–atmosphere model. HICARsnow couples two physics-based models of intermediate complexity to enable basin-scale snow and atmospheric modeling at seasonal timescales. To showcase the efficacy and capability of HICARsnow, we present results from its application to a high-elevation basin in the Swiss Alps. The simulated snow depth is compared throughout the snow season to aerial lidar data. The model shows reasonable agreement with observations from peak accumulation through late-season melt-out, representing areas of high snow accumulation due to redistribution processes, as well as melt patterns caused by interactions between radiation and topography. HICARsnow is also found to resolve preferential deposition, with model outputs suggesting that parameterizations of the process using surface wind fields may only be inappropriate under certain atmospheric conditions. The two-way coupled model also improves surface air temperatures over late-season snow, demonstrating added value for the atmospheric model as well. Differences between observations and model outputs during the accumulation season indicate a poor representation of redistribution processes away from exposed ridges and steep terrain and a low bias in albedo at high elevations during the ablation season. Overall, HICARsnow shows great promise for applications in operational snow forecasting and in studying the representation of snow accumulation and ablation processes.

Abstract Quality improvements and reduction of disease risk for low-resource shared sanitation facilities require cleanliness assessment approaches that are both rigorous and practical. Using Adenosine Triphosphate (ATP) bioluminescence testing, we assessed contamination on high-touch (HT) surfaces (inner door handles) at 32 shared toilet sites in Kisumu, Kenya. In public toilets, contamination was lowest after cleaning and disinfection (C&D) with 0.5% chlorine solution (adjusted difference in mean log10 Relative Light Units per 100 cm2 (aDiff): −1.61; CI: −2.43, −0.59), followed by C&D with 0.1% chlorine solution (aDiff: −1.16; CI: −1.77, −0.55). ATP levels were not associated with overall observable toilet cleanliness and had poor agreement with visually assessed HT surface cleanliness. Our findings demonstrate the utility of this field-feasible method for detecting the impact of recent C&D in low-resource shared toilets, a novel setting for ATP cleanliness testing, while also highlighting the importance of using effective C&D procedures and addressing HT surfaces within cleaning protocols.

Successful problem-based learning (PBL) often requires students to collectively regulate their learning processes as a group and engage in socially shared regulation of learning (SSRL). This paper focuses on how facilitators supported SSRL in the context of middle-school game-based PBL. Using conversation analysis, this study analyzed text-based chat messages of facilitators and students collected during gameplay. The analysis revealed direct modeling strategies such as performing regulative processes, promoting group awareness, and dealing with contingency as well as indirect strategies including prompting questions and acknowledgment of regulation, and the patterns of how facilitation faded to yield responsibilities to students to regulate their own learning. The findings will inform researchers and practitioners to design prompts and develop technological tools such as adaptive scaffolding to support SSRL in PBL or other collaborative inquiry processes.

BACKGROUND: Dominance and other non-additive genetic effects arise from the interaction between alleles, and historically these phenomena play a major role in quantitative genetics. However, most genome-wide association studies (GWAS) assume alleles act additively. RESULTS: We systematically investigate both dominance-here representing any non-additive within-locus interaction-and additivity across 574 physiological and gene expression traits in three mammalian stocks: F2 intercross pigs, rat heterogeneous stock, and mice heterogeneous stock. Dominance accounts for about one quarter of heritable variance across all physiological traits in all species. Hematological and immunological traits exhibit the highest dominance variance, possibly reflecting balancing selection in response to pathogens. Although most quantitative trait loci (QTLs) are detectable as additive QTLs, we identify 154, 64, and 62 novel dominance QTLs in pigs, rats, and mice respectively that are undetectable as additive QTLs. Similarly, even though most cis-acting expression QTLs are additive, gene expression exhibits a large fraction of dominance variance, and trans-acting eQTLs are enriched for dominance. Genes causal for dominance physiological QTLs are less likely to be physically linked to their QTLs but instead act via trans-acting dominance eQTLs. In addition, thousands of eQTLs are associated with alternatively spliced isoforms with complex additive and dominant architectures in heterogeneous stock rats, suggesting a possible mechanism for dominance. CONCLUSIONS: Although heritability is predominantly additive, many mammalian genetic effects are dominant and likely arise through distinct mechanisms. It is therefore advantageous to consider both additive and dominance effects in GWAS to improve power and uncover causality.

Snow hydrological regimes in mountainous catchments are strongly influenced by snowpack heterogeneity resulting from wind- and gravity-induced redistribution processes, requiring them to be modelled at hectometre and finer resolutions. This study presents a novel modelling approach to address this issue, aiming at an intermediate-complexity solution to best represent these processes while maintaining operationally viable computational times. To this end, the physics-based snowpack model FSM2oshd was complemented by integrating the modules SnowTran-3D and SnowSlide to represent wind- and gravity-driven redistribution, respectively. This new modelling framework was further enhanced by implementing a density-dependent layering to account for erodible snow without the need to resolve microstructural properties. Seasonal simulations were performed over a 1180 km2 mountain range in the Swiss Alps at 25, 50 and 100 m resolution, using appropriate downscaling and snow data assimilation techniques to provide accurate meteorological forcing. In particular, wind fields were dynamically downscaled using WindNinja to better reflect topographically induced flow patterns. The model results were assessed using snow depths from airborne lidar measurements. We found a remarkable improvement in the representation of snow accumulation and erosion areas, with major contributions from saltation and suspension as well as avalanches and with modest contributions from snowdrift sublimation. The aggregated snow depth distribution curve, key to snowmelt dynamics, significantly and consistently matched the measured distribution better than reference simulations from the peak of winter to the end of the melt season, with improvements at all spatial resolutions. This outcome is promising for a better representation of snow hydrological processes within an operational framework.

Abstract Psychedelics have experienced renewed interest following positive clinical effects, however the neurobiological mechanisms underlying effects remain unclear. The paraventricular nucleus of the hypothalamus (PVN) plays an integral role in stress response, autonomic function, social behavior, and other affective processes. We investigated the effect of psilocin, the psychoactive metabolite of psilocybin, on PVN reactivity in Sprague Dawley rats. Psilocin increased stimulus-independent PVN activity as measured by c-Fos expression in male and female rats. Psilocin increased PVN reactivity to an aversive air-puff stimulus in males but not females. Reactivity was restored at 2- and 7-days post-injection with no group differences. Additionally, prior psilocin injection did not affect PVN reactivity following acute restraint stress. Experimental groups sub-classified by baseline threat responding indicate that increased male PVN reactivity is driven by active threat responders. These findings identify the PVN as a significant site of psychedelic drug action with implications for threat responding behavior.

David John Mott,1 Jake Hitch,1,2 Samantha Nier,3 Zack Pemberton-Whiteley,3,4 Chris Skedgel1 1Office of Health Economics, London, UK; 2Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK; 3Acute Leukemia Advocates Network, Bern, Switzerland; 4Leukemia Care, Worcester, UKCorrespondence: David John Mott, Email dmott@ohe.orgBackground: Acute leukemia is a cancer of the white blood cells which progresses rapidly and aggressively. There are two types: acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). The latter has a rare subtype: acute promyelocytic leukemia (APL). For some patients, following first-line treatment, remission is not achieved (“refractory disease”), and for others the leukemia returns after achieving remission (“relapse”). For these individuals, outcomes are typically poor. It is, therefore, important to understand patients’ treatment priorities in this context.Methods: Building upon formative qualitative research, an online survey containing a discrete choice experiment (DCE) was designed to explore patients’ treatment preferences in the relapsed/refractory setting. The DCE attributes were mode of administration; quality of life during treatment; chance of response; duration of response; and quality of life during response. Each respondent completed twelve scenarios containing two hypothetical treatments. Participants were eligible if they lived in the United Kingdom and had a diagnosis of acute leukemia. The data were analysed using a latent class model.Results: A total of 95 patients completed the survey. The latent class analysis identified two classes. For both, chance of response was the most important attribute. For class 1, every attribute was important, whereas for class 2, the only important attributes were quality of life (during treatment and response) and chance of response. A greater proportion of respondents would fall into class 1 overall, and those with ALL or APL and those more recently diagnosed were more likely to be in class 2.Conclusion: Our results indicate that patients are strongly concerned about the chance of response, as well as quality of life (to a lesser extent), when faced with different treatment options in the relapsed/refractory setting. However, there is significant preference heterogeneity within the patient population, and other treatment characteristics also matter to many.Keywords: acute leukemia, hematology, oncology, patient preferences, discrete choice experiment

Abstract Methotrexate (MTX) doses on days +1, +3, +6, and +11 after match unrelated donor allogeneic stem cell transplant (MUD HSCT) is a common graft‐versus‐host disease (GVHD) prophylaxis regimen. However, the overlapping toxicity of MTX with conditioning chemotherapy sometimes warrants the omission of the fourth dose of MTX. Prior single‐institution studies showed conflicting results comparing the outcomes of patients who received three versus four doses of MTX, but to our knowledge, the effect of concomitant antithymocyte globulin (ATG) has not been reported. Charts of patients who underwent MUD HSCT between 2009 and 2023 were reviewed. Patients received rabbit ATG (Thymoglobulin), given at 0.5 mg/kg on day −3, 2 mg/kg on day −2, and 2.5 mg/kg on day −1. MTX is given at 15 mg/m2 on day +1 and 10 mg/m2 on days +3, +6, and +11. Severe mucositis was the most common indication for day +11 MTX omission (82%). We identified 292 patients (116 in 3 dose cohort and 176 in 4 dose cohort). Median follow‐up was 23 months (range 1–151). Patients in the 4 doses cohort were more frequently male (68% vs. 50%, p

The near-surface boundary layer over patchy snow is highly heterogeneous and dynamic. Layers of opposing stability coexist within only a few horizontal meters. Conventional experimental methods to investigate this layer suffer from limitations related to the fixed positions of eddy covariance sensors. To overcome these difficulties, we set up a centimeter-resolution large eddy simulation of flow across an idealised transition from bare ground to snow. We force the simulation with high-frequency eddy covariance data recorded during a field campaign. We show that the model can represent the real flow by comparing it to independent eddy covariance data. However, the simulation underestimates vertical wind speed fluctuations, especially at high frequencies. Sensitivity analyses show that this is influenced by grid resolution and surface roughness representation but not much by subgrid-scale parameterization. Nevertheless, the model can reproduce the experimentally observed plumes of warm air intermittently detaching from bare ground and being advected over snow. This process is highly dynamic, with time scales of only a few seconds. We can show that the growth of a stable internal boundary layer adjacent to the snow surface can be approximated by a power law. With low wind speeds, deeper stable layers develop, while strong wind speeds limit the growth. Even close to the surface, the buoyancy fluxes are heterogeneous and driven by terrain variations, which also induce the frequent decoupling of a thin layer adjacent to the snow surface. Our simulations point the path towards generalizing point-based and aerial measurements to three dimensions.

BACKGROUND: Women are at increased risk for psychosocial stress-related anxiety disorders, yet mechanisms regulating this risk are unknown. Psychosocial stressors activate microglia, and the resulting neuroimmune responses that females exhibit heightened sensitivity to may serve as an etiological factor in their elevated risk. However, studies examining the role of microglia during stress in females are lacking. METHODS: Microglia were manipulated in the stress-sensitive locus coeruleus (LC) of female rats in the context of social stress in two ways. First, intra-LC lipopolysaccharide (LPS; 0 or 3 μg/side, n = 5-6/group), a potent TLR4 agonist and microglial activator, was administered. One hour later, rats were exposed to control or an aggressive social defeat encounter between two males (WS, 15-min). In a separate study, females were treated with intra-LC or intra-central amygdala mannosylated liposomes containing clodronate (m-CLD; 0 or 25 μg/side, n = 13-14/group), a compound toxic to microglia. WS-evoked burying, cardiovascular responses, and sucrose preference were measured. Brain and plasma cytokines were quantified, and cardiovascular telemetry assessed autonomic balance. RESULTS: Intra-LC LPS augmented the WS-induced burying response and increased plasma corticosterone and interleukin-1β (IL-1β). Further, the efficacy and selectivity of microinjected m-CLD was fully characterized. In the context of WS, intra-LC m-CLD attenuated the hypervigilant burying response during WS as well as the accumulation of intra-LC IL-1β. Intra-central amygdala m-CLD had no effect on WS-evoked behavior. CONCLUSIONS: These studies highlight an innovative method for depleting microglia in a brain region specific manner and indicate that microglia in the LC differentially regulate hypervigilant WS-evoked behavioral and autonomic responses.

With accelerating advances in artificial intelligence, it is clear that introducing K-12 students to AI is essential for preparation to interact with and potentially develop AI technologies. To succeed as the workers, creators, and innovators of the future, we argue students should encounter core concepts of AI as early as elementary school. However, building a curriculum that introduces AI content to K-12 students presents significant challenges, such as connecting to prior knowledge, developing curricula that are meaningful for students, and creating content that teachers feel confident to teach. To lay the groundwork for elementary AI education, we investigated the everyday experiences and ideas of students in grades 4 and 5 (ages 9 to 11) about AI to inform possible entry points for learning. This yielded themes around student conceptions, examples, and ethics of AI. For each theme, we juxtapose the student ideas with the teachers' reflections on those ideas as frames of reference to consider in co-designing curricular approaches.

Among plants, there is considerable variation in lifespan: annuals live less than one year, whereas perennials live for several years, with the longest-living perennial having survived 43,600 years. As proposed by the Disposable Soma Theory, this lifespan variation among plants likely reflects differential investment of limited energy and nutrient resources, with perennials investing more energy and nutrients into biomolecular maintenance compared to annuals in order to ensure persistence over multiple seasons. Such differential investment may be particularly important during periods of exogenous stress, which are known to accelerate biomolecular damage. The present study evaluated this hypothesis using annual and perennial flax (Linum L.) subjected to two exogenous stressors—increased oxidative stress (i.e., foliar H2O2 spraying) and complete prolonged darkness. As chlorophyll has been shown to exhibit degradation in response to changes in environmental conditions, we utilized changes in chlorophyll levels during and after periods of exogenous stress to evaluate our hypotheses. We predicted that i) perennials would exhibit a slower rate of chlorophyll degradation during exposure to exogenous stressors compared to annuals, and ii) perennials would exhibit a faster rate of chlorophyll resynthesis following such exposure compared to annuals. Chlorophyll levels before, during, and after exposure to both exogenous stressors were measured in two separate trails, once using image colour analysis and once using spectrophotometry. While chlorophyll degradation rates in response to oxidative stress did not differ between annuals and perennials, contrary to our predictions, chlorophyll resynthesis rates following such exposure were significantly higher in perennials, as predicted. When plants were subjected to complete prolonged darkness, chlorophyll degradation rates were significantly lower in perennials than annuals, as predicted; however, when plants were subsequently reintroduced to natural photoperiod, chlorophyll resynthesis rates did not consistently differ between annuals and perennials, though they tended to be higher in the latter, as predicted. Overall, our study illuminates that evolutionary transitions between life history strategies in plants have been accompanied by physiological modifications to chlorophyll dynamics that permit perennial species to better maintain chlorophyll levels—and thus photosynthetic energy acquisition—in the face of exogenous stressors, which likely underlies their capacity to survive for multiple growing seasons. Future studies should explore whether other key biomolecules (e.g., proteins, DNA) are also better maintained in perennial plants, especially in the face of exogenous stress.

Abstract The health of honey bee queens is crucial for colony success, particularly during stressful periods like overwintering. To accompany a previous longitudinal study of colony and worker health, we explored niche-specific gut microbiota, host gene expression, and pathogen prevalence in honey bee queens overwintering in a warm southern climate. We found differential gene expression and bacterial abundance with respect to various pathogens throughout the season. Biologically older queens had larger microbiotas, particularly enriched in Bombella and Bifidobacterium. Both Deformed Wing Virus A and B subtypes were highest in the fat body tissue in January, correlating with colony Varroa levels, and Deformed Wing Virus titers in workers. High viral titers in queens were associated with decreased vitellogenin expression, suggesting a potential trade-off between immune function and reproductive capacity. Additionally, we found a complex and dynamic relationship between these viral loads and immune gene expression, indicating a possible breakdown in the coordinated immune response as the season progressed. Our study also revealed a potential link between Nosema and Melissococcus plutonius infections in queens, demonstrating that seasonal opportunism is not confined to just workers. Overall, our findings highlight the intricate interplay between pathogens, metabolic state, and immune response in honey bee queens. Combined with worker and colony-level metrics from the same colonies, our findings illustrate the social aspect of queen health and resilience over the winter dearth.

RNA-binding motif 8A (RBM8A) is a core component of the exon junction complex (EJC) that binds pre-mRNAs and regulates their splicing, transport, translation, and nonsense-mediated decay (NMD). Dysfunction in the core proteins has been linked to several detriments in brain development and neuropsychiatric diseases. To understand the functional role of Rbm8a in brain development, we have generated brain-specific Rbm8a knockout mice and used next-generation RNA-sequencing to identify differentially expressed genes (DEGs) in mice with heterozygous, conditional knockout (cKO) of Rbm8a in the brain at postnatal day 17 (P17) and at embryonic day 12. Additionally, we analyzed enriched gene clusters and signaling pathways within the DEGs. At the P17 time point, between the control and cKO mice, about 251 significant DEGs were identified. At E12, only 25 DEGs were identified in the hindbrain samples. Bioinformatics analyses have revealed many signaling pathways related to the central nervous system (CNS). When E12 and P17 results were compared, three DEGs, Spp1, Gpnmb, and Top2a, appeared to peak at different developmental time points in the Rbm8a cKO mice. Enrichment analyses suggested altered activity in pathways affecting cellular proliferation, differentiation, and survival. The results support the hypothesis that loss of Rbm8a causes decreased cellular proliferation, increased apoptosis, and early differentiation of neuronal subtypes, which may lead ultimately to an altered neuronal subtype composition in the brain.

Purpose: Multiple brain metastases can be treated efficiently with stereotactic radiosurgery (SRS) using a single-isocenter dynamic conformal arc (SIDCA) technique. Currently, plans are manually optimized, which may lead to unnecessary table angles and arcs being used. This study aimed to evaluate an automatic 4π optimization SIDCA algorithm for treatment efficiency and plan quality. Methods and Materials: Automatic 4π-optimized SIDCA plans were created and compared with the manually optimized clinical plans for 54 patients who underwent single-fraction SRS for 2 to 10 metastases. The number of table angles and number of arcs were compared with a paired t test using a Bonferroni-corrected significance level of P < .05/4 = .0125. The reduction in treatment time was estimated from the difference in the number of table angles and arcs. Plan quality was assessed through the volume-averaged inverse Paddick Conformity Index (CI) and Gradient Index (GI) and the volume of normal brain surrounding each metastasis receiving 12 Gy (local V12 Gy). For a 5-patient subset, the automatic plans were manually adjusted further. CI and GI were assessed for noninferiority using a 1-sided t test with the noninferiority limit equal to the 95% interobserver reproducibility limit from a separate planning study (corrected significance level P < .05/[4 − 1] = .017). Results: The automatic plans significantly improved treatment efficiency with a mean reduction in the number of table angles and arcs of −0.5 ± 0.1 and −1.3 ± 0.2, respectively (±SE; both P < .001). Estimated treatment time saving was −2.7 ± 0.5 minutes, 14% of the total treatment time. The volume-averaged CI and GI were noninferior to the clinical plans (both P < .001), although there was a small systematic shift in CI of 0.07 ± 0.01. The resulting difference in local V12 Gy, 0.25 ± 0.04 cm3, was not clinically significant. Minor manual adjustment of the automatic plans removed these slight differences while preserving the improved treatment efficiency. Conclusions: Automatic 4π optimization can generate SIDCA SRS plans with improved treatment efficiency and noninferior plan quality.

BackgroundPatients with small cell lung cancer (SCLC) often respond to first-line chemoimmunotherapy. However, relapse is inevitable and is associated with a poor prognosis. Treatments for relapsed SCLC, such as lurbinectedin and topotecan, are limited by modest efficacy and significant hematologic adverse events, leaving a need for newer therapeutic agents or regimens. The combination of gemcitabine and nab-paclitaxel is active and safe in other types of malignancies, such as pancreatic cancer.Patients and methodsWe conducted a phase II trial evaluating the efficacy and safety of gemcitabine and nab-paclitaxel in patients with relapsed/refractory SCLC. The primary endpoint was objective response rate (ORR), defined as the proportion of patients with confirmed complete or partial response. Secondary endpoints included time to progression (TTP), progression-free survival (PFS), overall survival (OS), and safety.ResultsBetween October 2016 and May 2021, 32 patients were enrolled. Patients were followed for a median of 9.3 months (range 1.8–65.2). Median age was 65 years (range 48–81). Fifty percent of patients were female. Fifty-three percent of patients had platinum-resistant/refractory relapsed SCLC. The ORR was 28.1% (95% confidence interval [CI] 15.5–100%). Median PFS was 2.9 months (95% CI 2.4–3.6), and median OS was 9.3 months (95% CI 5.2–12.4). Seven patients (21.9%) developed grade 3 or 4 neutropenia.ConclusionOur study showed that the combination of gemcitabine and nab-paclitaxel led to encouraging outcomes in relapsed/refractory SCLC. Further studies are needed to compare this combination with other treatments used for relapsed SCLC, including lurbinectedin, temozolomide, and topotecan.Clinical trial registrationhttps://clinicaltrials.gov/study/NCT02769832?cond=NCT02769832&rank=1, identifier NCT02769832.

Introduction Biological disease-modifying antirheumatic drugs (bDMARDs) have revolutionised the treatment of inflammatory arthritis (IA). However, many people with IA still require planned orthopaedic surgery to reduce pain and improve function. Currently, bDMARDs are withheld during the perioperative period due to potential infection risk. However, this predisposes patients to IA flares and loss of disease control. The question of whether to stop or continue bDMARDs in the perioperative period has not been adequately addressed in a randomised controlled trial (RCT).Methods and analysis PERISCOPE is a multicentre, superiority, pragmatic RCT investigating the stoppage or continuation of bDMARDs. Participants will be assigned 1:1 to either stop or continue their bDMARDs during the perioperative period. We aim to recruit 394 adult participants with IA. Potential participants will be identified in secondary care hospitals in the UK, screened by a delegated clinician. If eligible and consenting, baseline data will be collected and randomisation completed. The primary outcome will be the self-reported PROMIS-29 (Patient Reported Outcome Measurement Information System) over the first 12 weeks postsurgery. Secondary outcome measures are as follows: PROMIS - Health Assessment Questionnaire (PROMIS-HAQ), EQ-5D-5L, Disease activity: generic global Numeric Rating Scale (patient and clinician), Self-Administered Patient Satisfaction scale, Health care resource use and costs, Medication use, Surgical site infection, delayed wound healing, Adverse events (including systemic infections) and disease-specific outcomes (according to IA diagnosis). The costs associated with stopping and continuing bDMARDs will be assessed. A qualitative study will explore the patients’ and clinicians’ acceptability and experience of continuation/stoppage of bDMARDs in the perioperative period and the impact postoperatively.Ethics and dissemination Ethical approval for this study was received from the West of Scotland Research Ethics Committee on 25 April 2023 (REC Ref: 23/WS/0049). The findings from PERISCOPE will be submitted to peer-reviewed journals and feed directly into practice guidelines for the use of bDMARDs in the perioperative period.Trial registration number ISRCTN17691638.

Dynamic downscaling of atmospheric forcing data to the hectometer resolution has shown increases in accuracy for landsurface models, but at great computational cost. Here we present a validation of a novel intermediate complexity atmospheric model, HICAR, developed for hectometer scale applications. HICAR can run more than 500x faster than conventional atmospheric models, while containing many of the same physics parameterizations. Station measurements of air temperature, wind speed, and radiation, in combination with data from a scanning Doppler wind LiDAR, are compared to 50 m resolution HICAR output during late spring. We examine the model’s performance over bare ground and melting snow. The model shows a smaller root mean squared error in 2 m air temperature than the driving model, and approximates the 3D flow features present around ridges and along slopes. Timing and magnitude of changes in shortwave and longwave radiation also show agreement with measurements. Nocturnal cooling during clear nights is overestimated at the snow covered site. Additionally, the thermal wind parameterization employed by the model typically produces excessively strong surface winds, driven in part by this excessive nocturnal cooling over snow. These findings highlight the utility of HICAR as a tool for dynamically downscaling forcing datasets, and expose the need for improvements to the snow model used in HICAR.