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SIGNIFICANCE: Spatial frequency domain imaging (SFDI) applies patterned near-infrared illumination to quantify the optical properties of subsurface tissue. The periocular region is unique due to its complex ocular adnexal anatomy. Although SFDI has been successfully applied to relatively flat in vivo tissues, regions that have significant height variations and curvature may result in optical property inaccuracies. AIM: We characterize the geometric impact of the periocular region on SFDI imaging reliability. APPROACH: SFDI was employed to measure the reduced scattering coefficient ( μ s ) and absorption coefficient ( μ a ) of the periocular region in a cast facial tissue-simulating phantom by capturing images along regions of interest (ROIs): inferior temporal quadrant (ITQ), inferior nasal quadrant (INQ), superior temporal quadrant (STQ), central eyelid margin (CEM), rostral lateral nasal bridge (RLNB), and forehead (FH). The phantom was placed on a chin rest and imaged nine times from an en face or side profile position, and the flat back of the phantom was measured 15 times. RESULTS: The measured μ a and μ s of a cast facial phantom are accurate when comparing the ITQ, INQ, STQ, and FH to its flat posterior surface. Paired t tests of ITQ, INQ, STQ, and FH μ a and μ s concluded that there is not enough evidence to suggest that imaging orientation impacted the measurement accuracy. Regions of extreme topographical variation, i.e., CEM and RLNB, did exhibit differences in measured optical properties. CONCLUSIONS: We are the first to evaluate the geometric implications of wide-field imaging along the periocular region using a solid tissue-simulating facial phantom. Results suggest that the ITQ, INQ, STQ, and FH of a generalized face have minimal impact on the SFDI measurement accuracy. Areas with heightened topographic variation exhibit measurement variability. Device and facial positioning do not appear to bias measurements. These findings confirm the need to carefully select ROIs when measuring optical properties along the periocular region.

One of the justifiable criticisms of human genetic studies is the underrepresentation of participants from diverse populations. Lack of inclusion must be addressed at-scale to identify causal disease factors and understand the genetic causes of health disparities. We present genome-wide associations for 2068 traits from 635,969 participants in the Department of Veterans Affairs Million Veteran Program, a longitudinal study of diverse United States Veterans. Systematic analysis revealed 13,672 genomic risk loci; 1608 were only significant after including non-European populations. Fine-mapping identified causal variants at 6318 signals across 613 traits. One-third (n = 2069) were identified in participants from non-European populations. This reveals a broadly similar genetic architecture across populations, highlights genetic insights gained from underrepresented groups, and presents an extensive atlas of genetic associations.

PURPOSE: Data are limited on sodium glucose co-transport 2 inhibitors (SGLT2-is) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) among real-world cohorts of underrepresented patients. We examined these therapies and glycemic control in US adults with diabetes mellitus (DM) by atherosclerotic cardiovascular disease (ASCVD) risk and sociodemographic factors. METHODS: In the NIH Precision Medicine Initiative All of Us Research Program, we categorized DM as (1) moderate risk, (2) high risk, and (3) with ASCVD. We examined proportions on DM therapies, including SGLT2-i or GLP-1 RA, and at glycemic control by sociodemographic factors and CVD risk groups. RESULTS: Our 81,332 adults aged ≥ 18 years with DM across 340 US sites included 22.3% non-Hispanic Black, 17.2% Hispanic, and 1.8% Asian participants; 31.1%, 30.3%, and 38.6% were at moderate risk, high risk, or with ASCVD, respectively. Those with DM and ASCVD were most likely on SGLT2-i (8.6%) or GLP-1 RA (11.9%). SGLT2-i use was

In the original publication [...].

Abstract The remnants of Hurricane Ida caused major damage and death in the United States on September 1st, 2021, and 11 people drowned in flooded basement apartments within New York City (NYC). It was catastrophic because the maximum hourly precipitation intensity, recorded as 3.47 inches (88.1 mm) per hour at Central Park, was unprecedentedly high for the NYC region. The stormwater infrastructure in NYC is built for 1.75 inches (44.5 mm) per hour, and so understanding the dynamic risk associated with Ida can inform city planning efforts for climate change’s impact on short duration extreme precipitation events. We contextualize this storm’s record-breaking hourly intensity within the historical record as well as project its risk in the near- to medium-term future using nonstationary stochastic models. These models are conditioned on average temperature (T avg ) and cooling degree day (CDD) projections from three climate models as a covariate, each with a SSP 126 and SSP 370 scenario. The likelihood of such a storm was slowly increasing even before Ida happened, but the projected aggregate reoccurrence risk of an event of Ida’s magnitude over time from the non-stationary models ranges from 4 to 52 times higher than the risk given by the stationary model. Using CDD as a covariate resulted in risks that were more than twice the magnitude than when using T avg . Presenting both covariates provides a broader envelope of uncertainty, which highlights the importance and nuances in the choice of a regionally appropriate covariate for non-stationary risk analysis.

Abstract Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program cohort (approximately 95% male cases) and a previous study of European-ancestry individuals, jointly comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We then carry out conditional meta-analyses on cigarettes per day and identify two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in squamous cell lung carcinoma. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma, and squamous cell lung carcinoma, nine of which are externally replicated. Finally, we perform PheWAS on polygenic risk scores for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer polygenic risk score is associated with smoking status in controls, illustrating a reduced predictive utility in non-smokers. Additionally, our polygenic risk score demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits.

PurposeChronic age-related imbalance is a common cause of falls and subsequent death in the elderly and can arise from dysfunction of the vestibular system, an elegant neuroanatomical group of pathways that mediates human perception of acceleration, gravity, and angular head motion. Studies indicate that 27-46% of the risk of age-related chronic imbalance is genetic; nevertheless, the underlying genes remain unknown.MethodsThe cohort consisted of 50,339 cases and 366,900 controls in the Million Veteran Program. The phenotype comprised cases with two ICD diagnoses of vertigo or dizziness at least 6 months apart, excluding acute or recurrent vertiginous syndromes and other non-vestibular disorders. Genome-wide association studies were performed as individual logistic regressions on European, African American, and Hispanic ancestries followed by trans-ancestry meta-analysis. Downstream analysis included case-case-GWAS, fine mapping, probabilistic colocalization of significant variants and genes with eQTLs, and functional analysis of significant hits.ResultsTwo significant loci were identified in Europeans, another in the Hispanic population, and two additional in trans-ancestry meta-analysis, including three novel loci. Fine mapping revealed credible sets of intronic single nucleotide polymorphisms (SNPs) in MLLT10 - a histone methyl transferase cofactor, BPTF - a subunit of a nucleosome remodeling complex implicated in neurodevelopment, and LINC01224 - a proto-oncogene receptor tyrosine kinase.ConclusionDespite the difficulties of phenotyping the nature of chronic imbalance, we replicated two loci from previous vertigo GWAS studies and identified three novel loci. Findings suggest candidates for further study and ultimate treatment of this common elderly disorder.

The current understanding of the genetic determinants of thoracic aortic aneurysms and dissections (TAAD) has largely been informed through studies of rare, Mendelian forms of disease. Here, we conducted a genome-wide association study (GWAS) of TAAD, testing ~25 million DNA sequence variants in 8,626 participants with and 453,043 participants without TAAD in the Million Veteran Program, with replication in an independent sample of 4,459 individuals with and 512,463 without TAAD from six cohorts. We identified 21 TAAD risk loci, 17 of which have not been previously reported. We leverage multiple downstream analytic methods to identify causal TAAD risk genes and cell types and provide human genetic evidence that TAAD is a non-atherosclerotic aortic disorder distinct from other forms of vascular disease. Our results demonstrate that the genetic architecture of TAAD mirrors that of other complex traits and that it is not solely inherited through protein-altering variants of large effect size.

Reliability is a crucial factor to consider for multi-level inverters (MLIs) used in industrial applications. With the increasing number of power semiconductor devices, the potential for defects to significantly degrade the overall system is heightened. A highly effective fault-detection technique is required to minimize the impact of faults. This paper provides a comprehensive overview of the fundamental principles of multi-level inverters and the various sorts of faults that can occur in multi-level inverters. This study provides a comprehensive analysis of five-level cascaded H-bridge multilevel inverters (MLIs) under both normal and defective conditions. The paper outlines a fault-detection method that utilizes total harmonic distortion and a normalized output voltage factor. In addition, the paper discusses a fault-isolation strategy that relies on reducing amplitude modulation. This method leads to the development of a fault-tolerant inverter. The utilization of level-shifted pulse-width modulation (LSPWM) technology is employed for the purpose of switching operations. LSPWM is the most appropriate technique for MLIs that require a low amount of computational resources. The fault-diagnosis approach given is suitable for MLI-based drives, grid-connected operations, and other applications. This paper presents a comprehensive examination of the 5L-CMLI (5-Level Cascaded Multi-Level Inverter) under various fault scenarios in CMLI. Subsequently, various fault diagnosis approaches will be examined, including their advantages and disadvantages. The paper discusses several defects that can occur in the Insulated Gate Bipolar Transistor (IGBT) of a Current Mode Logic Inverter (CMLI), and also presents a design for a reliable fault diagnosis system. Furthermore, this analysis examines several fault detection strategies in CMLI, categorized according to open-loop and closed-loop dynamic systems fault classifications.

Summary: How do neural circuits coordinate multiple behavioral responses to a single sensory cue? Here, we investigate how sweet taste drives appetitive behaviors in Drosophila, including feeding, locomotor suppression, spatial preference, and associative learning. We find that neural circuits mediating different innate responses to sugar are partially overlapping and diverge at the second and third layers. Connectomic analyses reveal distinct subcircuits that mediate different behaviors. Connectome-based simulations of neuronal activity predict that second-order sugar neurons act synergistically to promote downstream activity and that bitter input overrides the sugar circuit through multiple pathways acting at third- and fourth-order neurons. Consistent with the latter prediction, optogenetic experiments suggest that bitter input inhibits third- and fourth-order sugar neurons to override the sugar pathway, whereas hunger and diet act earlier in the circuit to modulate behavior. Together, these studies provide insight into how circuits are organized to drive diverse behavioral responses to a single stimulus.

Real-world data on lipid levels and treatment among adults with diabetes mellitus (DM) are relatively limited. We studied lipid levels and treatment status in patients with DM across cardiovascular disease (CVD) risk groups and sociodemographic factors. In the All of Us Research Program, we categorized DM as (1) moderate risk (≤1 CVD risk factor), (2) high risk (≥2 CVD risk factors), and (3) DM with atherosclerotic CVD (ASCVD). We examined the use of statin and non-statin therapy as well as LDL-C and triglyceride levels. We studied 81,332 participants with DM, which included 22.3% non-Hispanic Black and 17.2% Hispanic. A total of 31.1% had ≤1 DM risk factor, 30.3% had ≥2 DM risk factors, and 38.6% of participants had DM with ASCVD. Only 18.2% of those with DM and ASCVD were on high-intensity statins. Overall, 5.1% were using ezetimibe and 0.6% PCSK9 inhibitors. Among those with DM and ASCVD, only 21.1% had LDL-C < 70 mg/dL. Overall, 1.9% of participants with triglycerides ≥ 150 mg/dL were on icosapent ethyl. Those with DM and ASCVD were more likely to be on high-intensity statins, ezetimibe, and icosapent ethyl. Guideline-recommended use of high-intensity statins and non-statin therapy among our higher risk DM patients is lacking, with LDL-C inadequately controlled.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Cardiovascular diseases stand out as the foremost cause of mortality on a global scale and encompass conditions that require long term self-care. Coronary heart disease and heart failure are two cardiovascular conditions that require significant lifestyle modifications. Adherence to self-care is a multifaceted phenomenon, and is influenced by various factors that include social, economic, disease-related and healthcare system-related factors. A key factor in adherence to self-care in chronic illnesses is social support. To explore this relationship between social support and adherence to self-care, a systematic review was carried out across Scopus, EBSCO host and ProQuest from October 2022 to February 2023 using predefined search criteria. Studies from inception to February 2023 were considered for the review, ultimately incorporating a total of 11 studies. Six studies had an adult population with coronary heart disease while the remaining five had adults with heart failure. All the studies reported a significant positive correlation between social support and adherence to self-care. Our findings revealed that social support plays a significant role in promoting self-care, emphasizing the need for a holistic understanding of self-care to develop effective interventions. Along with self-report measures, objective measures should be used to assess adherence accurately. There is a need for scales that assess all aspects of self-care, as well as the development of new interventions and teaching strategies to facilitate the individual’s self-care journey. In addition, family members and trusted resources should be involved in encouraging self-care, and interventions should target both patients and their family members.

OBJECTIVE Medicine being an endless path and a challenging career leaves many medical students drained and burned out in comparison to their same aged peers. Recently burnout levels have become a growing concern as it not only affects the academic performance but also their personal wellbeing and future professional practice. Thus, this study aims to assess the effect of burnout among undergraduate students of medical college.

This study utilized Harris Hawk optimization to analyze the harmonic distortions of a symmetric capacitor based multilevel converter. The proposed multilevel converter uses identical and symmetric DC sources in its input. The proposed topology for a multilevel converter uses fewer switches than typical cascaded designs. It can output 9-level outputs and can be scaled up to higher levels. The proposed multilevel converter can be improved by implementing a low frequency pulse width modulation technique to reduce the stress on the switches. The optimization of the switching angles using Harris Hawk was able to solve the non-linear aspects of the Selective Harmonic Elimination Pulse Width Modulation. The output voltage's THD was compared with that of other optimization methods, such as ant colony and particle swarm. The comparison shows that the output THD of the Harris Hawk optimizer is lower than that of other methods, which is about 5 %, according to the standards of IEEE-519.

BackgroundLiver cancer is one of the most rapidly increasing cancers in the United States, and hepatocellular carcinoma (HCC) is its most common form. Disease burden and risk factors differ by sex and race/ethnicity, but a comprehensive analysis of disparities by socioeconomic status (SES) is lacking. We examined the relative impact of race/ethnicity, sex, and SES on HCC incidence, stage, and survival.MethodsWe used Surveillance, Epidemiology, and End Results (SEER) 18 data to identify histologically confirmed cases of HCC diagnosed between January 1, 2000 and December 31, 2015. We calculated age-adjusted HCC incidence, stage at diagnosis (local, regional, distant, unstaged), and 5-year survival, by race/ethnicity, SES and sex, using SEER*Stat version 8.3.5.ResultsWe identified 45,789 cases of HCC. Incidence was highest among low-SES Asian/Pacific Islanders (API; 12.1) and lowest in high-SES Whites (3.2). Incidence was significantly higher among those with low-SES compared with high-SES for each racial/ethnic group (P < 0.001), except American Indian/Alaska Natives (AI/AN). High-SES API had the highest percentage of HCC diagnosed at the local stage. Of all race/ethnicities, Blacks had the highest proportion of distant stage disease in the low- and high-SES groups. Survival was greater in all high-SES racial/ethnic groups compared with low-SES (P < 0.001), except among AI/ANs. Black, low-SES males had the lowest 5-year survival.ConclusionsWith few exceptions, HCC incidence, distant stage at diagnosis, and poor survival were highest among the low-SES groups for all race/ethnicities in this national sample.ImpactHCC prevention and control efforts should target low SES populations, in addition to specific racial/ethnic groups.

Abstract Understanding spatially correlated floods and modeling joint hazard associated with threshold exceedances across multiple locations is crucial for accurate estimation of continental‐scale portfolio risk. This work uses a non‐parametric copula‐based spatial simulator to analyze peak floods across the United States to derive the first‐of‐its‐kind continental portfolio risk estimates at the 10‐ and 100‐year return levels. We find significant interdependence in floods across the nation, revealing the recurring pattern of extreme events affecting the Northeast, Central, West, and Northwest United States in the same year. The stochastic simulator effectively manages high‐dimensional data and offers reliable uncertainty estimates for both spatially dependent floods and the aggregated flood losses at the continental level. El Niño‐Southern Oscillation and Atlantic Multidecadal Oscillation are identified as statistically significant tele‐connectors of aggregate loss. This research aims to advance the understanding of compound continental flood hazard and the potential large‐scale climate teleconnections that lead to such compound floods.

We introduce a hierarchical Bayesian model for the spatial distribution of rainfall corresponding to an extreme event of a specified duration that could be used with regional hydrologic models to perform a regional hydrologic risk analysis. An extreme event is defined if any gaging site in the watershed experiences an annual maximum rainfall event and the spatial field of rainfall at all sites corresponding to that occurrence is modeled. Applications to data from New York City demonstrate the effectiveness of the model for providing spatial scenarios that could be used for simulating loadings into the urban drainage system. Insights as to the homogeneity in spatial rainfall and its implications for modeling are provided by considering partial pooling in the hierarchical Bayesian framework.

This study aimed to assess the incidental radiation exposure of the hippocampus (HC) in locoregionally-advanced oropharyngeal cancer patients undergoing volumetric modulated arc therapy and the feasibility of HC-sparing plan optimization. The initial plans were generated without dose-volume constraints to the HC and were compared with the HC-sparing plans. The incidental Dmean_median doses to the bilateral, ipsilateral and contralateral HC were 2.9, 3.1, and 2.5 Gy in the initial plans and 1.4, 1.6, and 1.3 Gy with HC-sparing. It was feasible to reduce the HC dose with HC-sparing plan optimization without compromising target coverage and/or dose constraints to other OARs.

Using optimization models with climate, crop & economic data, the authors show that India can stop groundwater depletion, reduce energy use and meet food/nutrition targets by changing where it sources crops for its food procurement and distribution system.

Abstract Adenoid cystic carcinoma (ACC) is primarily a salivary gland tumour that rarely involves the respiratory tract. A 58‐year‐old lady was admitted with worsening dyspnoea, cough and wheezing for 2 days. CT pulmonary angiogram was done due to persistent dyspnoea which revealed a 12 mm mass protruding into the posterior aspect of the trachea with multiple enlarged nodes. There was a complete collapse of the left lower lobe and right middle lobe with right upper lobe pulmonary embolism which was thought to be contributing to her hypoxia. She was struggling with secretion clearance and initial measures to clear her secretions were not successful. She was treated with a tracheal stent, followed by an interval endoscopic ultrasound‐guided biopsy of the tracheal wall lesion which revealed ACC. She was referred to cardiothoracic surgeons for excision of the tumour after discussing in MDT. Surgery followed by radiotherapy is advised in cases with incomplete resection margins.

As a mega-biobank linked to a national healthcare system, the Million Veteran Program (MVP) can directly improve the health care of participants. To determine the feasibility and outcomes of returning medically actionable genetic results to MVP participants, the program launched the MVP Return of Actionable Results (MVP-ROAR) Study, with familial hypercholesterolemia (FH) as an exemplar actionable condition. The MVP-ROAR Study consists of a completed single-arm pilot phase and an ongoing randomized clinical trial (RCT), in which MVP participants are recontacted and invited to receive clinical confirmatory gene sequencing testing and a telegenetic counseling intervention. The primary outcome of the RCT is 6-month change in low-density lipoprotein cholesterol (LDL-C) between participants receiving results at baseline and those receiving results after 6 months. The pilot developed processes to identify and recontact participants nationally with probable pathogenic variants in low-density lipoprotein receptor (LDLR) on the MVP genotype array, invite them to clinical confirmatory gene sequencing, and deliver a telegenetic counseling intervention. Among participants in the pilot phase, 8 (100%) had active statin prescriptions after 6 months. Results were shared with 16 first-degree family members. Six-month ΔLDL-C (low-density lipoprotein cholesterol) after the genetic counseling intervention was −37 mg/dL (95% CI: −12 to −61; P =.03). The ongoing RCT will determine between-arm differences in this primary outcome. While underscoring the importance of clinical confirmation of research results, the pilot phase of the MVP-ROAR Study marks a turning point in MVP and demonstrates the feasibility of returning genetic results to participants and their providers. The ongoing RCT will contribute to understanding how such a program might improve patient health care and outcomes. Clinical Trial Registration: ClinicalTrials.gov ID NCT04178122. [ABSTRACT FROM AUTHOR]

We present allele frequencies of pharmacogenomics relevant variants across multiple ancestry in a sample representative of the US population. We analyzed 658,582 individuals with genotype data and extracted pharmacogenomics relevant single nucleotide variant (SNV) alleles, human leukocyte antigens (HLA) 4-digit alleles and an important copy number variant (CNV), the full deletion/duplication of CYP2D6. We compiled distinct allele frequency tables for European, African American, Hispanic, and Asian ancestry individuals. In addition, we compiled allele frequencies based on local ancestry reconstruction in the African-American (2-way deconvolution) and Hispanic (3-way deconvolution) cohorts.

A fundamental question in sensory processing is how different channels of sensory input are processed to regulate behavior. Different input channels may converge onto common downstream pathways to drive the same behaviors, or they may activate separate pathways to regulate distinct behaviors. We investigated this question in the Drosophila bitter taste system, which contains diverse bitter-sensing cells residing in different taste organs. First, we optogenetically activated subsets of bitter neurons within each organ. These subsets elicited broad and highly overlapping behavioral effects, suggesting that they converge onto common downstream pathways, but we also observed behavioral differences that argue for biased convergence. Consistent with these results, transsynaptic tracing revealed that bitter neurons in different organs connect to overlapping downstream pathways with biased connectivity. We investigated taste processing in one type of downstream bitter neuron that projects to the higher brain. These neurons integrate input from multiple organs and regulate specific taste-related behaviors. We then traced downstream circuits, providing the first glimpse into taste processing in the higher brain. Together, these results reveal that different bitter inputs are selectively integrated early in the circuit, enabling the pooling of information, while the circuit then diverges into multiple pathways that may have different roles.

Summary: Antiquated and inefficient data-sharing practices represent one of the key obstacles to advancing sustainability goals through green chemistry. To this end, we need to robustly link data on chemical impacts with new chemical design strategies, which requires the development of next-generation data-sharing platforms to harmonize both data and efforts. These decentralized and interactive programs should be structured as live ecosystems for data generation and exchange, inviting conversations about the reliability and relevance of information used to make decisions regarding chemical performance and safety.

Summary: Taste cues regulate immediate feeding behavior, but their ability to modulate future behavior has been less well studied. Pairing one taste with another can modulate subsequent feeding responses through associative learning, but this requires simultaneous exposure to both stimuli. We investigated whether exposure to one taste modulates future responses to other tastes even when they do not overlap in time. Using Drosophila, we found that brief exposure to sugar enhanced future feeding responses, whereas bitter exposure suppressed them. This modulation relies on neural pathways distinct from those that acutely regulate feeding or mediate learning-dependent changes. Sensory neuron activity was required not only during initial taste exposure but also afterward, suggesting that ongoing sensory activity may maintain experience-dependent changes in downstream circuits. Thus, the brain stores a memory of each taste stimulus after it disappears, enabling animals to integrate information as they sequentially sample different taste cues that signal local food quality.

Abstract The nuclear receptor retinoid-related orphan receptor gamma t (RORγt) plays a critical role in driving Th17 cell differentiation and expansion, as well as IL-17 production in innate and adaptive immune cells. The IL-23/IL-17 axis is implicated in several autoimmune and inflammatory diseases, and biologics targeting IL-23 and IL-17 have shown significant clinical efficacy in treating psoriasis and psoriatic arthritis. JNJ-61803534 is a potent RORγt inverse agonist, selectively inhibiting RORγt-driven transcription versus closely-related family members, RORα and RORβ. JNJ-61803534 inhibited IL-17A production in human CD4+ T cells under Th17 differentiation conditions, but did not inhibit IFNγ production under Th1 differentiation conditions, and had no impact on in vitro differentiation of regulatory T cells (Treg), nor on the suppressive activity of natural Tregs. In the mouse collagen-induced arthritis model, JNJ-61803534 dose-dependently attenuated inflammation, achieving ~ 90% maximum inhibition of clinical score. JNJ-61803534 significantly inhibited disease score in the imiquimod-induced mouse skin inflammation model, and dose-dependently inhibited the expression of RORγt-regulated genes, including IL-17A, IL-17F, IL-22 and IL-23R. Preclinical 1-month toxicity studies in rats and dogs identified doses that were well tolerated supporting progression into first-in-human studies. An oral formulation of JNJ-61803534 was studied in a phase 1 randomized double-blind study in healthy human volunteers to assess safety, pharmacokinetics, and pharmacodynamics. The compound was well tolerated in single ascending doses (SAD) up to 200 mg, and exhibited dose-dependent increases in exposure upon oral dosing, with a plasma half-life of 164 to 170 h. In addition, dose-dependent inhibition of ex vivo stimulated IL-17A production in whole blood was observed, demonstrating in vivo target engagement. In conclusion, JNJ-61803534 is a potent and selective RORγt inhibitor that exhibited acceptable preclinical safety and efficacy, as well as an acceptable safety profile in a healthy volunteer SAD study, with clear evidence of a pharmacodynamic effect in humans.

Abstract The annual frequency of tornadoes during 1950–2018 across the major tornado-impacted states were examined and modeled using anthropogenic and large-scale climate covariates in a hierarchical Bayesian inference framework. Anthropogenic factors include increases in population density and better detection systems since the mid-1990s. Large-scale climate variables include El Niño Southern Oscillation (ENSO), Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), Arctic Oscillation (AO), and Atlantic Multi-decadal Oscillation (AMO). The model provides a robust way of estimating the response coefficients by considering pooling of information across groups of states that belong to Tornado Alley, Dixie Alley, and Other States, thereby reducing their uncertainty. The influence of the anthropogenic factors and the large-scale climate variables are modeled in a nested framework to unravel secular trend from cyclical variability. Population density explains the long-term trend in Dixie Alley. The step-increase induced due to the installation of the Doppler Radar systems explains the long-term trend in Tornado Alley. NAO and the interplay between NAO and ENSO explained the interannual to multi-decadal variability in Tornado Alley. PDO and AMO are also contributing to this multi-time scale variability. SOI and AO explain the cyclical variability in Dixie Alley. This improved understanding of the variability and trends in tornadoes should be of immense value to public planners, businesses, and insurance-based risk management agencies.

Switching and relocating crops could be a key pathway for agricultural adaptation to climate change. Here, Rising and Devineni use data-driven Bayesian modelling to estimate the potential for crop switching to mitigate climate impacts on US crop production under a high-emission scenario, showing considerable opportunities but also limitations.