Transcellular chaperone signaling is an intercellular stress-response distinct from the HSF-1-mediated heat shock response.

Organismal proteostasis is maintained by intercellular signaling processes including cell nonautonomous stress responses such as transcellular chaperone signaling (TCS). When TCS is activated upon tissue-specific knockdown of hsp-90 in the Caenorhabditis elegans intestine, heat-inducible hsp-70 is induced in muscle cells at the permissive temperature resulting in increased heat stress resistance and lifespan extension. However, our understanding of the molecular mechanism and signaling factors mediating transcellular activation of hsp-70 expression from one tissue to another is still in its infancy. Here, we conducted a combinatorial approach using transcriptome RNA-Seq profiling and a forward genetic mutagenesis screen to elucidate how stress signaling from the intestine to the muscle is regulated. We find that the TCS-mediated "gut-to-muscle" induction of hsp-70 expression is suppressed by HSF-1 and instead relies on transcellular-X-cross-tissue (txt) genes. We identify a key role for the PDZ-domain guanylate cyclase txt-1 and the homeobox transcription factor ceh-58 as signaling hubs in the stress receiving muscle cells to initiate hsp-70 expression and facilitate TCS-mediated heat stress resistance and lifespan extension. Our results provide a new view on cell-nonautonomous regulation of "inter-tissue" stress responses in an organism that highlight a key role for the gut. Our data suggest that the HSF-1-mediated heat shock response is switched off upon TCS activation, in favor of an intercellular stress-signaling route to safeguard survival.

Application of Global Lung Function Initiative Global Spirometry Reference Equations across a Large, Multicenter Pulmonary Function Lab Population.

Rationale: Global Lung Function Initiative (GLI) Global spirometry reference equations were recently derived to offer a "race-neutral" interpretation option. The impact of transitioning from the race-specific GLI-2012 to the GLI Global reference equations is unknown. Objectives: Describe the direction and magnitude of changes in predicted lung function measurements in a population of diverse race and ethnicity using GLI Global in place of GLI-2012 reference equations. Methods: In this multicenter cross-sectional study using a large pulmonary function laboratory database, 109,447 spirometry tests were reanalyzed using GLI Global reference equations and compared with the existing GLI-2012 standard, stratified by self-reported race and ethnicity. Measurements and Main Results: Mean FEV1 and FVC percent predicted increased in the White and Northeast Asian groups and decreased in the Black, Southeast Asian, and mixed/other race groups. The prevalence of obstruction increased by 9.7% in the White group, and prevalences of possible restriction increased by 51.1% and 37.1% in the Black and Southeast Asian groups, respectively. Using GLI Global in a population with equal representation of all five race and ethnicity groups altered the interpretation category for 10.2% of spirometry tests. Subjects who self-identified as Black were the only group with a relative increase in the frequency of abnormal spirometry test results (32.9%). Conclusions: The use of GLI Global reference equations will significantly impact spirometry interpretation. Although GLI Global offers an innovative approach to transition from race-specific reference equations, it is important to recognize the continued need to place these data within an appropriate clinical context.

Interim Results of a Phase 1-2a Trial of Ad26.COV2.S Covid-19 Vaccine.

BACKGROUND: Efficacious vaccines are urgently needed to contain the ongoing coronavirus disease 2019 (Covid-19) pandemic of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A candidate vaccine, Ad26.COV2.S, is a recombinant, replication-incompetent adenovirus serotype 26 (Ad26) vector encoding a full-length and stabilized SARS-CoV-2 spike protein. METHODS: In this multicenter, placebo-controlled, phase 1-2a trial, we randomly assigned healthy adults between the ages of 18 and 55 years (cohort 1) and those 65 years of age or older (cohort 3) to receive the Ad26.COV2.S vaccine at a dose of 5×1010 viral particles (low dose) or 1×1011 viral particles (high dose) per milliliter or placebo in a single-dose or two-dose schedule. Longer-term data comparing a single-dose regimen with a two-dose regimen are being collected in cohort 2; those results are not reported here. The primary end points were the safety and reactogenicity of each dose schedule. RESULTS: After the administration of the first vaccine dose in 805 participants in cohorts 1 and 3 and after the second dose in cohort 1, the most frequent solicited adverse events were fatigue, headache, myalgia, and injection-site pain. The most frequent systemic adverse event was fever. Systemic adverse events were less common in cohort 3 than in cohort 1 and in those who received the low vaccine dose than in those who received the high dose. Reactogenicity was lower after the second dose. Neutralizing-antibody titers against wild-type virus were detected in 90% or more of all participants on day 29 after the first vaccine dose (geometric mean titer [GMT], 212 to 354), regardless of vaccine dose or age group, and reached 96% by day 57 with a further increase in titers (GMT, 288 to 488) in cohort 1a. Titers remained stable until at least day 71. A second dose provided an increase in the titer by a factor of 2.6 to 2.9 (GMT, 827 to 1266). Spike-binding antibody responses were similar to neutralizing-antibody responses. On day 15, CD4+ T-cell responses were detected in 76 to 83% of the participants in cohort 1 and in 60 to 67% of those in cohort 3, with a clear skewing toward type 1 helper T cells. CD8+ T-cell responses were robust overall but lower in cohort 3. CONCLUSIONS: The safety and immunogenicity profiles of Ad26.COV2.S support further development of this vaccine candidate. (Funded by Johnson & Johnson and the Biomedical Advanced Research and Development Authority of the Department of Health and Human Services; COV1001 ClinicalTrials.gov number, NCT04436276.).

Dynamic regulation of water potential in Juniperus osteosperma mediates ecosystem carbon fluxes.

Some plants exhibit dynamic hydraulic regulation, in which the strictness of hydraulic regulation (i.e. iso/anisohydry) changes in response to environmental conditions. However, the environmental controls over iso/anisohydry and the implications of flexible hydraulic regulation for plant productivity remain unknown. In Juniperus osteosperma, a drought-resistant dryland conifer, we collected a 5-month growing season time series of in situ, high temporal-resolution plant water potential ( Ψ ) and stand gross primary productivity (GPP). We quantified the stringency of hydraulic regulation associated with environmental covariates and evaluated how predawn water potential contributes to empirically predicting carbon uptake. Juniperus osteosperma showed less stringent hydraulic regulation (more anisohydric) after monsoon precipitation pulses, when soil moisture and atmospheric demand were high, and corresponded with GPP pulses. Predawn water potential matched the timing of GPP fluxes and improved estimates of GPP more strongly than soil and/or atmospheric moisture, notably resolving GPP underestimation before vegetation green-up. Flexible hydraulic regulation appears to allow J. osteosperma to prolong soil water extraction and, therefore, the period of high carbon uptake following monsoon precipitation pulses. Water potential and its dynamic regulation may account for why process-based and empirical models commonly underestimate the magnitude and temporal variability of dryland GPP.

Phase 1 trial supports safety and mechanism of action of peptide immunotherapy for peanut allergy.

BACKGROUND: Food allergy is a leading cause of anaphylaxis worldwide. Allergen-specific immunotherapy is the only treatment shown to modify the natural history of allergic disease, but application to food allergy has been hindered by risk of severe allergic reactions and short-lived efficacy. Allergen-derived peptides could provide a solution. PVX108 comprises seven short peptides representing immunodominant T-cell epitopes of major peanut allergens for treatment of peanut allergy. METHODS: Pre-clinical safety of PVX108 was assessed using ex vivo basophil activation tests (n = 185). Clinical safety and tolerability of single and repeat PVX108 doses were evaluated in a first-in-human, randomized, double-blind, placebo-controlled trial in peanut-allergic adults (46 active, 21 placebo). The repeat-dose cohort received six doses over 16 weeks with safety monitored to 21 weeks. Exploratory immunological analyses were performed at pre-dose, Week 21 and Month 18 after treatment. RESULTS: PVX108 induced negligible activation of peanut-sensitised basophils. PVX108 was safe and well tolerated in peanut-allergic adults. There were no treatment-related hypersensitivity events or AEs of clinical concern. The only events occurring more frequently in active than placebo were mild injection site reactions. Exploratory immunological analyses revealed a decrease in the ratio of ST2+ Th2A:CCR6+ Th17-like cells within the peanut-reactive Th pool which strengthened following treatment. CONCLUSION: This study supports the concept that PVX108 could provide a safe alternative to whole peanut immunotherapies and provides evidence of durable peanut-specific T-cell modulation. Translation of these findings to clinical efficacy in ongoing Phase 2 trials would provide important proof-of-concept for using peptides to treat food allergy.

Automated morphological phenotyping using learned shape descriptors and functional maps: A novel approach to geometric morphometrics.

The methods of geometric morphometrics are commonly used to quantify morphology in a broad range of biological sciences. The application of these methods to large datasets is constrained by manual landmark placement limiting the number of landmarks and introducing observer bias. To move the field forward, we need to automate morphological phenotyping in ways that capture comprehensive representations of morphological variation with minimal observer bias. Here, we present Morphological Variation Quantifier (morphVQ), a shape analysis pipeline for quantifying, analyzing, and exploring shape variation in the functional domain. morphVQ uses descriptor learning to estimate the functional correspondence between whole triangular meshes in lieu of landmark configurations. With functional maps between pairs of specimens in a dataset we can analyze and explore shape variation. morphVQ uses Consistent ZoomOut refinement to improve these functional maps and produce a new representation of shape variation, area-based and conformal (angular) latent shape space differences (LSSDs). We compare this new representation of shape variation to shape variables obtained via manual digitization and auto3DGM, an existing approach to automated morphological phenotyping. We find that LSSDs compare favorably to modern 3DGM and auto3DGM while being more computationally efficient. By characterizing whole surfaces, our method incorporates more morphological detail in shape analysis. We can classify known biological groupings, such as Genus affiliation with comparable accuracy. The shape spaces produced by our method are similar to those produced by modern 3DGM and to auto3DGM, and distinctiveness functions derived from LSSDs show us how shape variation differs between groups. morphVQ can capture shape in an automated fashion while avoiding the limitations of manually digitized landmarks, and thus represents a novel and computationally efficient addition to the geometric morphometrics toolkit.

Automating incidence and prevalence analysis in open cohorts.

MOTIVATION: Data is increasingly used for improvement and research in public health, especially administrative data such as that collected in electronic health records. Patients enter and exit these typically open-cohort datasets non-uniformly; this can render simple questions about incidence and prevalence time-consuming and with unnecessary variation between analyses. We therefore developed methods to automate analysis of incidence and prevalence in open cohort datasets, to improve transparency, productivity and reproducibility of analyses. IMPLEMENTATION: We provide both a code-free set of rules for incidence and prevalence that can be applied to any open cohort, and a python Command Line Interface implementation of these rules requiring python 3.9 or later. GENERAL FEATURES: The Command Line Interface is used to calculate incidence and point prevalence time series from open cohort data. The ruleset can be used in developing other implementations or can be rearranged to form other analytical questions such as period prevalence. AVAILABILITY: The command line interface is freely available from https://github.com/THINKINGGroup/analogy_publication .

Widespread seasonal compensation effects of spring warming on northern plant productivity.

Climate change is shifting the phenological cycles of plants1, thereby altering the functioning of ecosystems, which in turn induces feedbacks to the climate system2. In northern (north of 30° N) ecosystems, warmer springs lead generally to an earlier onset of the growing season3,4 and increased ecosystem productivity early in the season5. In situ6 and regional7-9 studies also provide evidence for lagged effects of spring warmth on plant productivity during the subsequent summer and autumn. However, our current understanding of these lagged effects, including their direction (beneficial or adverse) and geographic distribution, is still very limited. Here we analyse satellite, field-based and modelled data for the period 1982-2011 and show that there are widespread and contrasting lagged productivity responses to spring warmth across northern ecosystems. On the basis of the observational data, we find that roughly 15 per cent of the total study area of about 41 million square kilometres exhibits adverse lagged effects and that roughly 5 per cent of the total study area exhibits beneficial lagged effects. By contrast, current-generation terrestrial carbon-cycle models predict much lower areal fractions of adverse lagged effects (ranging from 1 to 14 per cent) and much higher areal fractions of beneficial lagged effects (ranging from 9 to 54 per cent). We find that elevation and seasonal precipitation patterns largely dictate the geographic pattern and direction of the lagged effects. Inadequate consideration in current models of the effects of the seasonal build-up of water stress on seasonal vegetation growth may therefore be able to explain the differences that we found between our observation-constrained estimates and the model-constrained estimates of lagged effects associated with spring warming. Overall, our results suggest that for many northern ecosystems the benefits of warmer springs on growing-season ecosystem productivity are effectively compensated for by the accumulation of seasonal water deficits, despite the fact that northern ecosystems are thought to be largely temperature- and radiation-limited10.

Improving the performance of machine learning penicillin adverse drug reaction classification with synthetic data and transfer learning.

BACKGROUND: Machine learning may assist with the identification of potentially inappropriate penicillin allergy labels. Strategies to improve the performance of existing models for this task include the use of additional training data, synthetic data and transfer learning. AIMS: The aims of this study were to investigate the use of additional training data and novel machine learning strategies, namely synthetic data and transfer learning, to improve the performance of penicillin adverse drug reaction (ADR) machine learning classification. METHODS: Machine learning natural language processing was applied to free-text penicillin ADR data extracted from a public health system electronic health record (EHR). The models were developed by training on various labelled data sets. ADR entries were split into training and testing data sets and used to develop and test a variety of machine learning models. The effect of training on additional data and synthetic data versus the use of transfer learning was analysed. RESULTS: Following the application of these techniques, the area under the receiver operator curve of best-performing models for the classification of penicillin allergy (vs intolerance) and high-risk allergy (vs low-risk allergy) improved to 0.984 (using the artificial neural network model) and 0.995 (with the transfer learning approach) respectively. CONCLUSIONS: Machine learning models demonstrate high levels of accuracy in the classification and risk stratification of penicillin ADR labels using the reaction documented in the EHR. The model can be further optimised by incorporating additional training data and using transfer learning. Practical applications include automating case detection for penicillin allergy delabelling programmes.

Endocervical crypt involvement by high-grade cervical intraepithelial neoplasia and its association with high-grade histopathological recurrence after cervical excision in women with negative excision margins: a systematic review and meta-analysis.

BACKGROUND: There is a growing body of evidence suggesting that endocervical crypt involvement by high-grade cervical intraepithelial neoplasia (CIN) may represent a risk factor for disease recurrence after cervical treatment. OBJECTIVES: To provide a systematic review and meta-analysis on whether endocervical crypt involvement by high-grade CIN on the excised cervical specimen is associated with high-grade histopathological recurrence during the follow-up of women after cervical excisional treatment. SEARCH STRATEGY: We searched the Medline, Scopus, Central, and Clinical Trials.gov databases from inception till May 2023. SELECTION CRITERIA: Studies that reported on women with a single cervical treatment with any method of excision for CIN2 or CIN3 lesion, negative excision margins, and whose recurrence was defined histopathologically were included. DATA COLLECTION AND ANALYSIS: Two reviewers independently evaluated study eligibility. We used the fixed effects model for meta-analysis. MAIN RESULTS: There were 4 eligible studies included in the present systematic review that evaluated 1088 women treated with either large loop excision of the transformation zone (LLETZ) or with cold knife conization (CKC). We found no significant association of endocervical crypt involvement by CIN2-3 with high-grade histopathological recurrence at follow-up after cervical excision (OR 1.93; 95% CI 0.51-3.35). The subgroup analysis of women with LLETZ cervical excision showed again no significant association with high-grade histopathological recurrence at follow-up (OR 2.00; 95% CI 0.26-3.74). CONCLUSION: Endocervical crypt involvement by high-grade CIN does not seem to be a risk factor for high-grade histopathological recurrence after cervical excision with negative excision margins.

Impact of racial microaggressions in psychotherapy vignettes with african american clients: An experimental analogue design.

Mental health researchers have focused on promoting culturally sensitive clinical care (Herman et al., 2007; Whaley & Davis, 2007), emphasizing the need to understand how biases may impact client well-being. Clients report that their therapists commit racial microaggressions-subtle, sometimes unintentional, racial slights-during treatment (Owen et al., 2014). Yet, existing studies often rely on retrospective evaluations of clients and cannot establish the causal impact of varying ambiguity of microaggressions on clients. This study uses an experimental analogue design to examine offensiveness, emotional reactions, and evaluations of the interaction across three distinct levels of microaggression statements: subtle, moderate, and overt. We recruited 158 adult African American participants and randomly assigned them to watch a brief counseling vignette. We found significant differences between the control and three microaggression statements on all outcome variables. We did not find significant differences between the microaggression conditions. This study, in conjunction with previous correlational research, highlights the detrimental impact of microaggressions within psychotherapy, regardless of racially explicit content. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

IgE receptor of mast cells signals mediator release and inflammation via adaptor protein 14-3-3ζ.

BACKGROUND: Mast cells (MCs) are tissue-resident immune cells that mediate IgE-dependent allergic responses. Downstream of FcεRI, an intricate network of receptor-specific signaling pathways and adaptor proteins govern MC function. The 14-3-3 family of serine-threonine phosphorylation-dependent adapter proteins are known to organize intracellular signaling. However, the role of 14-3-3 in IgE-dependent activation remains poorly defined. OBJECTIVE: We sought to determine whether 14-3-3 proteins are required for IgE-dependent MC activation and whether 14-3-3 is a viable target for the treatment of MC-mediated inflammatory diseases. METHODS: Genetic manipulation of 14-3-3ζ expression in human and mouse MCs was performed and IgE-dependent mediator release assessed. Pharmacologic inhibitors of 14-3-3 and 14-3-3ζ knockout mice were used to assess 14-3-3ζ function in a MC-dependent in vivo passive cutaneous anaphylaxis (PCA) model of allergic inflammation. Expression and function of 14-3-3ζ were assessed in human nasal polyp tissue MCs. RESULTS: IgE-dependent mediator release from human MCs was decreased by 14-3-3ζ knockdown and increased by 14-3-3ζ overexpression. Deletion of the 14-3-3ζ gene decreased IgE-dependent activation of mouse MCs in vitro and PCA responses in vivo. Furthermore, the 14-3-3 inhibitor, RB-11, which impairs dimerization of 14-3-3, inhibited cultured MC and polyp tissue MC activation and signaling downstream of the FcεRI receptor and dose-dependently attenuated PCA responses. CONCLUSION: IgE/FcεRI-mediated MC activation is positively regulated by 14-3-3ζ. We identify a critical role for this p-Ser/Thr-binding protein in the regulation of MC FcεRI signaling and IgE-dependent immune responses and show that this pathway may be amenable to pharmacologic targeting.

Evidence for Topological Magnon-Phonon Hybridization in a 2D Antiferromagnet down to the Monolayer Limit.

Topological phonons and magnons potentially enable low-loss, quantum coherent, and chiral transport of information and energy at the atomic scale. Van der Waals magnetic materials are promising to realize such states due to their recently discovered strong interactions among the electronic, spin, and lattice degrees of freedom. Here, we report the first observation of coherent hybridization of magnons and phonons in monolayer antiferromagnet FePSe3 by cavity-enhanced magneto-Raman spectroscopy. The robust magnon-phonon cooperativity in the 2D limit occurs even in zero magnetic field, which enables nontrivial band inversion between longitudinal and transverse optical phonons caused by the strong coupling with magnons. The spin and lattice symmetry theoretically guarantee magnetic-field-controlled topological phase transition, verified by nonzero Chern numbers calculated from the coupled spin-lattice model. The 2D topological magnon-phonon hybridization potentially offers a new route toward quantum phononics and magnonics with an ultrasmall footprint.

Wilderness Medical Society Clinical Practice Guidelines for Prevention and Management of Avalanche and Nonavalanche Snow Burial Accidents: 2024 Update.

To provide guidance to the general public, clinicians, and avalanche professionals about best practices, the Wilderness Medical Society convened an expert panel to revise the evidence-based guidelines for the prevention, rescue, and resuscitation of avalanche and nonavalanche snow burial victims. The original panel authored the Wilderness Medical Society Practice Guidelines for Prevention and Management of Avalanche and Nonavalanche Snow Burial Accidents in 2017. A second panel was convened to update these guidelines and make recommendations based on quality of supporting evidence.

Wilderness Medical Society Clinical Practice Guidelines for the Treatment of Acute Pain in Austere Environments: 2024 Update.

The Wilderness Medical Society (WMS) convened an expert panel to develop evidence-based guidelines for the management of pain in austere environments. Recommendations are graded based on the quality of supporting evidence as defined by criteria put forth by the American College of Chest Physicians. This is an update of the 2014 version of the "WMS Practice Guidelines for the Treatment of Acute Pain in Remote Environments" published in Wilderness & Environmental Medicine 2014; 25:41-49.

A robust approach to 3D neuron shape representation for quantification and classification.

We consider the problem of finding an accurate representation of neuron shapes, extracting sub-cellular features, and classifying neurons based on neuron shapes. In neuroscience research, the skeleton representation is often used as a compact and abstract representation of neuron shapes. However, existing methods are limited to getting and analyzing "curve" skeletons which can only be applied for tubular shapes. This paper presents a 3D neuron morphology analysis method for more general and complex neuron shapes. First, we introduce the concept of skeleton mesh to represent general neuron shapes and propose a novel method for computing mesh representations from 3D surface point clouds. A skeleton graph is then obtained from skeleton mesh and is used to extract sub-cellular features. Finally, an unsupervised learning method is used to embed the skeleton graph for neuron classification. Extensive experiment results are provided and demonstrate the robustness of our method to analyze neuron morphology.

Machine Learning for Adrenal Gland Segmentation and Classification of Normal and Adrenal Masses at CT.

Background Adrenal masses are common, but radiology reporting and recommendations for management can be variable. Purpose To create a machine learning algorithm to segment adrenal glands on contrast-enhanced CT images and classify glands as normal or mass-containing and to assess algorithm performance. Materials and Methods This retrospective study included two groups of contrast-enhanced abdominal CT examinations (development data set and secondary test set). Adrenal glands in the development data set were manually segmented by radiologists. Images in both the development data set and the secondary test set were manually classified as normal or mass-containing. Deep learning segmentation and classification models were trained on the development data set and evaluated on both data sets. Segmentation performance was evaluated with use of the Dice similarity coefficient (DSC), and classification performance with use of sensitivity and specificity. Results The development data set contained 274 CT examinations (251 patients; median age, 61 years; 133 women), and the secondary test set contained 991 CT examinations (991 patients; median age, 62 years; 578 women). The median model DSC on the development test set was 0.80 (IQR, 0.78-0.89) for normal glands and 0.84 (IQR, 0.79-0.90) for adrenal masses. On the development reader set, the median interreader DSC was 0.89 (IQR, 0.78-0.93) for normal glands and 0.89 (IQR, 0.85-0.97) for adrenal masses. Interreader DSC for radiologist manual segmentation did not differ from automated machine segmentation (P = .35). On the development test set, the model had a classification sensitivity of 83% (95% CI: 55, 95) and specificity of 89% (95% CI: 75, 96). On the secondary test set, the model had a classification sensitivity of 69% (95% CI: 58, 79) and specificity of 91% (95% CI: 90, 92). Conclusion A two-stage machine learning pipeline was able to segment the adrenal glands and differentiate normal adrenal glands from those containing masses. © RSNA, 2022 Online supplemental material is available for this article.

The association between menstrual cycle characteristics and cardiometabolic outcomes in later life: a retrospective matched cohort study of 704,743 women from the UK.

BACKGROUND: Female reproductive factors are gaining prominence as factors that enhance cardiovascular disease (CVD) risk; nonetheless, menstrual cycle characteristics are under-recognized as a factor associated with CVD. Additionally, there is limited data from the UK pertaining to menstrual cycle characteristics and CVD risk. METHODS: A UK retrospective cohort study (1995-2021) using data from a nationwide database (The Health Improvement Network). Women aged 18-40 years at index date were included. 252,325 women with history of abnormal menstruation were matched with up to two controls. Two exposures were examined: regularity and frequency of menstrual cycles; participants were assigned accordingly to one of two separate cohorts. The primary outcome was composite cardiovascular disease (CVD). Secondary outcomes were ischemic heart disease (IHD), cerebrovascular disease, heart failure (HF), hypertension, and type 2 diabetes mellitus (T2DM). Cox proportional hazards regression models were used to derive adjusted hazard ratios (aHR) of cardiometabolic outcomes in women in the exposed groups compared matched controls. RESULTS: During 26 years of follow-up, 20,605 cardiometabolic events occurred in 704,743 patients. Compared to women with regular menstrual cycles, the aHRs (95% CI) for cardiometabolic outcomes in women with irregular menstrual cycles were as follows: composite CVD 1.08 (95% CI 1.00-1.19), IHD 1.18 (1.01-1.37), cerebrovascular disease 1.04 (0.92-1.17), HF 1.30 (1.02-1.65), hypertension 1.07 (1.03-1.11), T2DM 1.37 (1.29-1.45). The aHR comparing frequent or infrequent menstrual cycles to menstrual cycles of normal frequency were as follows: composite CVD 1.24 (1.02-1.52), IHD 1.13 (0.81-1.57), cerebrovascular disease 1.43 (1.10-1.87), HF 0.99 (0.57-1.75), hypertension 1.31 (1.21-1.43), T2DM 1.74 (1.52-1.98). CONCLUSIONS: History of either menstrual cycle irregularity or frequent or infrequent cycles were associated with an increased risk of cardiometabolic outcomes in later life. Menstrual history may be a useful tool in identifying women eligible for periodic assessment of their cardiometabolic health.

The Ethics of Risk Prediction for Psychosis and Suicide Attempt in Youth Mental Health.

OBJECTIVE: To identify potential clinical utility of polygenic risk scores (PRS) and exposomic risk scores (ERS) for psychosis and suicide attempt in youth and assess the ethical implications of these tools. STUDY DESIGN: We conducted a narrative literature review of emerging findings on PRS and ERS for suicide and psychosis as well as a literature review on the ethics of PRS. We discuss the ethical implications of the emerging findings for the clinical potential of PRS and ERS. RESULTS: Emerging evidence suggests that PRS and ERS may offer clinical utility in the relatively near future but that this utility will be limited to specific, narrow clinical questions, in contrast to the suggestion that population-level screening will have sweeping impact. Combining PRS and ERS might optimize prediction. This clinical utility would change the risk-benefit balance of PRS, and further empirical assessment of proposed risks would be necessary. Some concerns for PRS, such as those about counseling, privacy, and inequities, apply to ERS. ERS raise distinct ethical challenges as well, including some that involve informed consent and direct-to-consumer advertising. Both raise questions about the ethics of machine-learning/artificial intelligence approaches. CONCLUSIONS: Predictive analytics using PRS and ERS may soon play a role in youth mental health settings. Our findings help educate clinicians about potential capabilities, limitations, and ethical implications of these tools. We suggest that a broader discussion with the public is needed to avoid overenthusiasm and determine regulations and guidelines for use of predictive scores.

Thermography captures the differential sensitivity of dryland functional types to changes in rainfall event timing and magnitude.

Drylands of the southwestern United States are rapidly warming, and rainfall is becoming less frequent and more intense, with major yet poorly understood implications for ecosystem structure and function. Thermography-based estimates of plant temperature can be integrated with air temperature to infer changes in plant physiology and response to climate change. However, very few studies have evaluated plant temperature dynamics at high spatiotemporal resolution in rainfall pulse-driven dryland ecosystems. We address this gap by incorporating high-frequency thermal imaging into a field-based precipitation manipulation experiment in a semi-arid grassland to investigate the impacts of rainfall temporal repackaging. All other factors held constant, we found that fewer/larger precipitation events led to cooler plant temperatures (1.4°C) compared to that of many/smaller precipitation events. Perennials, in particular, were 2.5°C cooler than annuals under the fewest/largest treatment. We show these patterns were driven by: increased and consistent soil moisture availability in the deeper soil layers in the fewest/largest treatment; and deeper roots of perennials providing access to deeper plant available water. Our findings highlight the potential for high spatiotemporal resolution thermography to quantify the differential sensitivity of plant functional groups to soil water availability. Detecting these sensitivities is vital to understanding the ecohydrological implications of hydroclimate change.