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To accelerate medical breakthroughs, the All of Us Research Program aims to collect data from over one million participants. This report outlines processes used to construct the All of Us Social Determinants of Health (SDOH) survey and presents the psychometric characteristics of SDOH survey measures in All of Us. A consensus process was used to select SDOH measures, prioritizing concepts validated in diverse populations and other national cohort surveys. Survey item non-response was calculated, and Cronbachs alpha was used to analyze psychometric properties of scales. Multivariable logistic regression models were used to examine associations between demographic categories and item non-response. Twenty-nine percent (N = 117,783) of eligible All of Us participants submitted SDOH survey data for these analyses. Most scales had less than 5% incalculable scores due to item non-response. Patterns of item non-response were seen by racial identity, educational attainment, income level, survey language, and age. Internal consistency reliability was greater than 0.80 for almost all scales and most demographic groups. The SDOH survey demonstrated good to excellent reliability across several measures and within multiple populations underrepresented in biomedical research. Bias due to survey non-response and item non-response will be monitored and addressed as the survey is fielded more completely.

Correlations between altered body temperature and depression have been reported in small samples; greater confidence in these associations would provide a rationale for further examining potential mechanisms of depression related to body temperature regulation. We sought to test the hypotheses that greater depression symptom severity is associated with (1) higher body temperature, (2) smaller differences between body temperature when awake versus asleep, and (3) lower diurnal body temperature amplitude. Data collected included both self-reported body temperature (using standard thermometers), wearable sensor-assessed distal body temperature (using an off-the-shelf wearable sensor that collected minute-level physiological data), and self-reported depressive symptoms from > 20,000 participants over the course of ~ 7 months as part of the TemPredict Study. Higher self-reported and wearable sensor-assessed body temperatures when awake were associated with greater depression symptom severity. Lower diurnal body temperature amplitude, computed using wearable sensor-assessed distal body temperature data, tended to be associated with greater depression symptom severity, though this association did not achieve statistical significance. These findings, drawn from a large sample, replicate and expand upon prior data pointing to body temperature alterations as potentially relevant factors in depression etiology and may hold implications for development of novel approaches to the treatment of major depressive disorder.

Abstract The use of antimicrobial drugs in food-producing animals contributes to the selection pressure on pathogenic and commensal bacteria to become resistant. This study aims to evaluate the existence of trade-offs between treatment effectiveness, cost, and the dynamics of resistance in gut commensal bacteria. We developed a within-host ordinary differential equation model to track the dynamics of antimicrobial drug concentrations and bacterial populations in the site of infection (lung) and the gut. The model was parameterized to represent enrofloxacin treatment for bovine respiratory disease (BRD) caused by Pastereulla multocida in cattle. Three approved enrofloxacin dosing regimens were compared for their effects on resistance on P. multocida and commensal E. coli: 12.5 mg/kg and 7.5 mg/kg as a single dose, and 5 mg/kg as three doses. Additionally, we explored non-FDA-approved regimes. Our results indicated that both 12.5 mg/kg and 7.5 mg/kg as a single dose scenario increased the most the treatment costs and prevalence of P. multocida resistance in the lungs, while 5 mg/kg as three doses increased resistance in commensal E. coli bacteria in the gut the most out of the approved scenarios. A proposed non-FDA-approved scenario (7.5 mg/kg, two doses 24 h apart) showed low economic costs, minimal P. multocida, and moderate effects on resistant E. coli. Overall, the scenarios that decrease P. multocida, including resistant P. multocida did not coincide with those that decrease resistant E. coli the most, suggesting a trade-off between both outcomes. The sensitivity analysis suggests that bacterial populations were the most sensitive to drug conversion factors into plasma ( $${\beta}$$ β ), elimination of the drug from the colon ( $$\vartheta$$ ϑ ), fifty percent sensitive bacteria (P. multocida) killing effect ( $${\text{L}}_{\text{s50}}$$ L s50 ), fifty percent of bacteria (E. coli) above ECOFF killing effect ( $${\text{C}}_{\text{r50}}$$ C r50 ), and net drug transfer rate in the lung ( $$\gamma$$ γ ) parameters.

Abstract Identifying mechanisms that drive population divergence under varying geographic and ecological scenarios can inform our understanding of evolution and speciation. In particular, analysis of genetic data from island populations with known colonisation timelines allows us to identify potential source populations of diverging island subspecies and current relationships among populations. Silvereyes (Zosterops lateralis) are a small passerine that have served as a valuable study system to investigate evolutionary patterns on both large and small geographic scales. We examined genetic relatedness and diversity of two silvereye subspecies, the mainland Z. l. cornwalli and island Z. l. chlorocephalus, and used 18 077 single nucleotide polymorphisms (SNPs), to compare locations across southeast Queensland, Australia. Although silvereyes are prolific island colonisers our findings revealed population divergence over relatively small spatial scales was strongly influenced by geographic isolation mediated by water barriers. Strong genetic connectivity was displayed between mainland sites, but minimal inter-island connectivity was shown despite comparable sampling distances. Genetic diversity analysis showed little difference in heterozygosity between island and mainland populations, but lower inbreeding scores among the island populations. Our study confirmed the range of the Z. l. chlorocephalus subspecies throughout the southern Great Barrier Reef. Our results show that water barriers and not geographic distance per se are important in driving incipient divergence in island populations. This helps to explain the relatively high number of phenotypically differentiated, but often geographically proximate, island silvereye subspecies compared to a lower number of phenotypically less well-defined Australian continental subspecies.

Abstract With their long lives and extreme reproductive output, social insect queens have escaped the classic trade-off between fecundity and lifespan, but evidence for a trade-off between fecundity and immunity has been inconclusive. This is in part because pathogenic effects are seldom decoupled from effects of immune induction. We conducted parallel, blind virus infection experiments in the laboratory and in the field to interrogate the idea of a reproductive immunity trade-off in honey bee (Apis mellifera) queens and to better understand how these ubiquitous stressors affect honey bee queen health. We found that queens injected with infectious virus had smaller ovaries and were less likely to recommence egg-laying than controls, while queens injected with UV-inactivated virus displayed an intermediate phenotype. In the field, heavily infected queens had smaller ovaries and infection was a meaningful predictor of whether supersedure cells were observed in the colony. Immune responses in queens receiving live virus were similar to queens receiving inactivated virus, and several of the same immune proteins were negatively associated with ovary mass in the field. This work supports the hypothesized relationship between virus infection and symptoms associated with queen failure and suggests that a reproductive-immunity trade-off is partially, but not wholly responsible for these effects.

Abstract The impact of multimodal prehabilitation on postoperative complications in upper abdominal surgeries is understudied. This review analyzes randomized trials on multimodal prehabilitation with patient and hospital outcomes. MEDLINE, Embase, CINAHL, and Cochrane CENTRAL were searched for trials on prehabilitation before elective (non-emergency) abdominal surgery. Two reviewers independently screened studies, extracted data, and assessed study quality. Primary outcomes of interest were postoperative pulmonary complications (PPCs) and all-cause complications; secondary outcomes included hospital and intensive care length of stay. A meta-analysis with random-effect models was performed, and heterogeneity was evaluated with I-square and Cochran’s Q test. Dichotomous variables were reported in log-odds ratio and continuous variables were presented as mean difference. Ten studies (total 1503 patients) were included. Odds of developing complications after prehabilitation were significantly lower compared to various control groups (− 0.38 [− 0.75– − 0.004], P = 0.048). Five studies described PPCs, and participants with prehabilitation had decreased odds of PPC (− 0.96 [− 1.38– − 0.54], P

Abstract Cartilage tissue engineering aims to develop functional substitutes for treating cartilage defects and osteoarthritis. Traditional two-dimensional (2D) cell culture systems lack the complexity of native cartilage, leading to the development of 3D regenerative cartilage models. In this study, we developed a 3D model using Gelatin Methacryloyl (GelMA)-based hydrogels seeded with Y201 cells, a bone marrow mesenchymal stem cell line. The model investigated chondrogenic differentiation potential in response to Wnt3a stimulation within the GelMA scaffold and validated using known chondrogenic agonists. Y201 cells demonstrated suitability for the model, with increased proteoglycan content and upregulated chondrogenic marker expression under chondrogenic conditions. Wnt3a enhanced cell proliferation, indicating activation of the Wnt/β-catenin pathway, which plays a role in cartilage development. GelMA hydrogels provided an optimal scaffold, supporting cell viability and proliferation. The 3D model exhibited consistent responses to chondrogenic agonists, with TGF-β3 enhancing cartilage-specific extracellular matrix (ECM) production and chondrogenic differentiation. The combination of Wnt3a and TGF-β3 showed synergistic effects, promoting chondrogenic differentiation and ECM production. This study presents a 3D regenerative cartilage model with potential for investigating cartilage biology, disease mechanisms, and drug screening. The model provides insights into complex cartilage regeneration mechanisms and offers a platform for developing therapeutic approaches for cartilage repair and osteoarthritis treatment.

Abstract This study aimed to examine whether acute myocardial infarction (AMI) patients in Switzerland return to work and identify factors associated therewith. Data of 4315 working-age AMI patients enrolled in the Swiss AMIS Plus registry between 01/2006 and 09/2021 with 1-year follow-up and self-reported work status were analyzed. Patient characteristics were compared between those who did not reduce their work hours, those who reduced, and those who were no longer working 1 year after AMI. Multinomial logistic regression was used to analyze independent predictors of working ability. Of the patients, 3204 (74.3%) did not reduce their work hours, 592 (13.7%) reduced and 519 (12.0%) were no longer working 1 year after AMI. Women were more likely to reduce or stop working. Patients who did not reduce were more frequently young and male. Multinomial logistic regression showed that work reduction was associated with female sex and a Killip class > 2 at admission whereas stopping work was associated with female sex and comorbidities. A high rate of AMI patients in Switzerland (88%) return to work 1 year after AMI. Approximately 1 in 8 did not return to work and approximately 1 in 7 reduced their work hours. Important factors associated with reducing or no longer working after AMI were female sex, older age and a higher proportion of comorbidities.

Abstract The chemical and isotopic composition of stony coral skeletons form an important archive of past climate. However, these reconstructions are largely based on empirical relationships often complicated by “vital effects” arising from uncertain physiological processes of the coral holobiont. The skeletons of deep-sea corals, such as Desmophyllum dianthus, are characterised by micron-scale or larger geochemical heterogeneity associated with: (1) centres of calcification (COCs) where nucleation of new skeleton begins, and (2) fibres that thicken the skeleton. These features are difficult to sample cleanly using traditional techniques, resulting in uncertainty surrounding both the causes of geochemical differences and their influence on environmental signals. Here we combine optical, and in-situ chemical and isotopic, imaging tools across a range of spatial resolutions (~ 100 nm to 10 s of μm) in a correlative multimodal imaging (CMI) approach to isolate the microstructural geochemistry of each component. This reveals COCs are characterised by higher organic content, Mg, Li and Sr and lower U, B and δ11B compared to fibres, reflecting the contrasting biomineralisation mechanisms employed to construct each feature. CMI is rarely applied in Environmental/Earth Sciences, but here we illustrate the power of this approach to unpick the “vital effects” in D. dianthus, and by extension, other scleractinian corals.

Abstract Early detection of sepsis is key to ensure timely clinical intervention. Since very few end-to-end pipelines are publicly available, fair comparisons between methodologies are difficult if not impossible. Progress is further limited by discrepancies in the reconstruction of sepsis onset time. This retrospective cohort study highlights the variation in performance of predictive models under three subtly different interpretations of sepsis onset from the sepsis-III definition and compares this against inter-model differences. The models are chosen to cover tree-based, deep learning, and survival analysis methods. Using the MIMIC-III database, between 867 and 2178 intensive care unit admissions with sepsis were identified, depending on the onset definition. We show that model performance can be more sensitive to differences in the definition of sepsis onset than to the model itself. Given a fixed sepsis definition, the best performing method had a gain of 1–5% in the area under the receiver operating characteristic (AUROC). However, the choice of onset time can cause a greater effect, with variation of 0–6% in AUROC. We illustrate that misleading conclusions can be drawn if models are compared without consideration of the sepsis definition used which emphasizes the need for a standardized definition for sepsis onset.

Abstract To accelerate medical breakthroughs, the All of Us Research Program aims to collect data from over one million participants. This report outlines processes used to construct the All of Us Social Determinants of Health (SDOH) survey and presents the psychometric characteristics of SDOH survey measures in All of Us. A consensus process was used to select SDOH measures, prioritizing concepts validated in diverse populations and other national cohort surveys. Survey item non-response was calculated, and Cronbach’s alpha was used to analyze psychometric properties of scales. Multivariable logistic regression models were used to examine associations between demographic categories and item non-response. Twenty-nine percent (N = 117,783) of eligible All of Us participants submitted SDOH survey data for these analyses. Most scales had less than 5% incalculable scores due to item non-response. Patterns of item non-response were seen by racial identity, educational attainment, income level, survey language, and age. Internal consistency reliability was greater than 0.80 for almost all scales and most demographic groups. The SDOH survey demonstrated good to excellent reliability across several measures and within multiple populations underrepresented in biomedical research. Bias due to survey non-response and item non-response will be monitored and addressed as the survey is fielded more completely.

Abstract Air quality negatively impacts agriculture, reducing the yield of staple food crops. While measured data on African ground-level ozone levels are scarce, experimental studies demonstrate the damaging impact of ozone on crops. Common beans (Phaseolus vulgaris), an ozone-sensitive crop, are widely grown in Uganda. Using modelled ozone flux, agricultural surveys, and a flux-effect relationship, this study estimates yield and production losses due to ozone for Ugandan beans in 2015. Analysis at this scale allows the use of localised data, and results can be presented at a sub-regional level. Soil nutrient stress, drought, flood risk, temperature and deprivation were also mapped to investigate where stresses may coincide. Average bean yield losses due to ozone were 17% and 14% (first and second growing season respectively), equating to 184 thousand tonnes production loss. However, for some sub-regions, losses were up to 27.5% and other crop stresses also coincided in these areas. This methodology could be applied widely, allowing estimates of ozone impact for countries lacking air quality and/or experimental data. As crop productivity is below its potential in many areas of the world, changing agricultural practices to mitigate against losses due to ozone could help to reduce the crop yield gap.

Abstract When someone violates a social norm, others may think that some sanction would be appropriate. We examine how the experience of emotions like anger and disgust relate to the judged appropriateness of sanctions, in a pre-registered analysis of data from a large-scale study in 56 societies. Across the world, we find that individuals who experience anger and disgust over a norm violation are more likely to endorse confrontation, ostracism and, to a smaller extent, gossip. Moreover, we find that the experience of anger is consistently the strongest predictor of judgments of confrontation, compared to other emotions. Although the link between state-based emotions and judgments may seem universal, its strength varies across countries. Aligned with theoretical predictions, this link is stronger in societies, and among individuals, that place higher value on individual autonomy. Thus, autonomy values may increase the role that emotions play in guiding judgments of social sanctions.

Abstract The innate immune response is the first line of defense for all animals to not only detect invading microbes and toxins but also sense and interface with the environment. One such environment that can significantly affect innate immunity is spaceflight. In this study, we explored the impact of microgravity stress on key elements of the NFκB innate immune pathway. The symbiosis between the bobtail squid Euprymna scolopes and its beneficial symbiont Vibrio fischeri was used as a model system under a simulated microgravity environment. The expression of genes associated with the NFκB pathway was monitored over time as the symbiosis progressed. Results revealed that although the onset of the symbiosis was the major driver in the differential expression of NFκB signaling, the stress of simulated low-shear microgravity also caused a dysregulation of expression. Several genes were expressed at earlier time points suggesting that elements of the E. scolopes NFκB pathway are stress-inducible, whereas expression of other pathway components was delayed. The results provide new insights into the role of NFκB signaling in the squid-vibrio symbiosis, and how the stress of microgravity negatively impacts the host immune response. Together, these results provide a foundation to develop mitigation strategies to maintain host-microbe homeostasis during spaceflight.

Abstract The food animal sector’s use of antimicrobials is heavily critiqued for its role in allowing resistance to develop against critically important antimicrobials in human health. The WHO recommends using lower tier antimicrobials such as florfenicol for disease treatment. The primary objective of this study was to assess the differences in resistance profiles of enteric microbes following administration of florfenicol to steers using both FDA-approved dosing regimens and two different detection methods. Our hypothesis was that we would identify an increased prevalence of resistance in the steers administered the repeated, lower dose of florfenicol; additionally, we hypothesized resistance profiles would be similar between both detection methods. Twelve steers were administered either two intramuscular (20 mg/kg q 48 h; n = 6) or a single subcutaneous dose (40 mg/kg, n = 6). Fecal samples were collected for 38 days, and E. coli and Enterococcus were isolated and tested for resistance. Fecal samples were submitted for metagenomic sequencing analysis. Metagenomics revealed genes conferring resistance to aminoglycosides as the most abundant drug class. Most multidrug resistance genes contained phenicols. The genotypic and phenotypic patterns of resistance were not similar between drug classes. Observed increases in resistant isolates and relative abundance of resistance genes peaked after drug administration and returned to baseline by the end of the sampling period. The use of a “lower tier” antimicrobial, such as florfenicol, may cause an increased amount of resistance to critically important antimicrobials for a brief period, but these changes largely resolve by the end of the drug withdrawal period.

Abstract Quantum dots are promising candidates for telecom single photon sources due to their tunable emission across the different low-loss telecommunications bands, making them compatible with existing fiber networks. Their suitability for integration into photonic structures allows for enhanced brightness through the Purcell effect, supporting efficient quantum communication technologies. Our work focuses on InAs/InP QDs created via droplet epitaxy MOVPE to operate within the telecoms C-band. We observe a short radiative lifetime of 340 ps, arising from a Purcell factor of 5, owing to integration of the QD within a low-mode-volume photonic crystal cavity. Through in-situ control of the sample temperature, we show both temperature tuning of the QD’s emission wavelength and a preserved single photon emission purity at temperatures up to 25K. These findings suggest the viability of QD-based, cryogen-free C-band single photon sources, supporting applicability in quantum communication technologies.

Abstract Correlations between altered body temperature and depression have been reported in small samples; greater confidence in these associations would provide a rationale for further examining potential mechanisms of depression related to body temperature regulation. We sought to test the hypotheses that greater depression symptom severity is associated with (1) higher body temperature, (2) smaller differences between body temperature when awake versus asleep, and (3) lower diurnal body temperature amplitude. Data collected included both self-reported body temperature (using standard thermometers), wearable sensor-assessed distal body temperature (using an off-the-shelf wearable sensor that collected minute-level physiological data), and self-reported depressive symptoms from > 20,000 participants over the course of ~ 7 months as part of the TemPredict Study. Higher self-reported and wearable sensor-assessed body temperatures when awake were associated with greater depression symptom severity. Lower diurnal body temperature amplitude, computed using wearable sensor-assessed distal body temperature data, tended to be associated with greater depression symptom severity, though this association did not achieve statistical significance. These findings, drawn from a large sample, replicate and expand upon prior data pointing to body temperature alterations as potentially relevant factors in depression etiology and may hold implications for development of novel approaches to the treatment of major depressive disorder.

Abstract Understanding precisely what is in food products is not always straightforward due to food fraud, differing labelling regulations, naming inconsistencies and the hierarchical nature of ingredients. Despite this, the need to detect and substitute ingredients in consumer food products is far-reaching. The cultivation and production of many ingredients is unsustainable, and can lead to widespread deforestation and biodiversity loss. Understanding the presence and replaceability of these ingredients is an important step in reducing their use. Furthermore, certain ingredients are critical to consumer food products, and identifying these ingredients and evaluating supply-chain resilience in the event of losing access to them is vital for food security analysis. To address these issues, we first present a novel machine learning approach for detecting the presence of unlabelled ingredients. We then characterise the unsolved problem of proposing viable food substitutions as a directed link prediction task and solve it with a graph neural network (GNN).

Abstract In response to the escalating global obesity crisis and its associated health and financial burdens, this paper presents a novel methodology for analyzing longitudinal weight loss data and assessing the effectiveness of financial incentives. Drawing from the Keep It Off trial—a three-arm randomized controlled study with 189 participants—we examined the potential impact of financial incentives on weight loss maintenance. Given that some participants choose not to weigh themselves because of small weight change or weight gains, which is a common phenomenon in many weight-loss studies, traditional methods, for example, the Generalized Estimating Equations (GEE) method tends to overestimate the effect size due to the assumption that data are missing completely at random. To address this challenge, we proposed a framework which can identify evidence of missing not at random and conduct bias correction using the estimating equation derived from pairwise composite likelihood. By analyzing the Keep It Off data, we found that the data in this trial are most likely characterized by non-random missingness. Notably, we also found that the enrollment time (i.e., duration time) would be positively associated with the weight loss maintenance after adjusting for the baseline participant characteristics (e.g., age, sex). Moreover, the lottery-based intervention was found to be more effective in weight loss maintenance compared with the direct payment intervention, though the difference was non-statistically significant. This framework's significance extends beyond weight loss research, offering a semi-parametric approach to assess missing data mechanisms and robustly explore associations between exposures (e.g., financial incentives) and key outcomes (e.g., weight loss maintenance). In essence, the proposed methodology provides a powerful toolkit for analyzing real-world longitudinal data, particularly in scenarios with data missing not at random, enriching comprehension of intricate dataset dynamics.

Abstract Monitoring sleep and activity through wearable devices such as wrist-worn actigraphs has the potential for long-term measurement in the individual’s own environment. Long periods of data collection require a complex approach, including standardized pre-processing and data trimming, and robust algorithms to address non-wear and missing data. In this study, we used a data-driven approach to quality control, pre-processing and analysis of longitudinal actigraphy data collected over the course of 1 year in a sample of 95 participants. We implemented a data processing pipeline using open-source packages for longitudinal data thereby providing a framework for treating missing data patterns, non-wear scoring, sleep/wake scoring, and conducted a sensitivity analysis to demonstrate the impact of non-wear and missing data on the relationship between sleep variables and depressive symptoms. Compliance with actigraph wear decreased over time, with missing data proportion increasing from a mean of 4.8% in the first week to 23.6% at the end of the 12 months of data collection. Sensitivity analyses demonstrated the importance of defining a pre-processing threshold, as it substantially impacts the predictive value of variables on sleep-related outcomes. We developed a novel non-wear algorithm which outperformed several other algorithms and a capacitive wear sensor in quality control. These findings provide essential insight informing study design in digital health research.

Disease results from interactions among the host, pathogen, and environment. Inoculation trials can quantify interactions among these players and explain aspects of disease ecology to inform management in variable and dynamic natural environments. White-nose Syndrome, a disease caused by the fungal pathogen, Pseudogymnoascus destructans (Pd), has caused severe population declines of several bat species in North America. We conducted the first experimental infection trial on the tri-colored bat, Perimyotis subflavus, to test the effect of temperature and humidity on disease severity. We also tested the effects of temperature and humidity on fungal growth and persistence on substrates. Unexpectedly, only 37% (35/95) of bats experimentally inoculated with Pd at the start of the experiment showed any infection response or disease symptoms after 83 days of captive hibernation. There was no evidence that temperature or humidity influenced infection response. Temperature had a strong effect on fungal growth on media plates, but the influence of humidity was more variable and uncertain. Designing laboratory studies to maximize research outcomes would be beneficial given the high costs of such efforts and potential for unexpected outcomes. Understanding the influence of microclimates on host-pathogen interactions remains an important consideration for managing wildlife diseases, particularly in variable environments.

Abstract In grafted apple, rootstock-derived signals influence scion cold tolerance by initiating physiological changes to survive over the winter. To understand the underlying molecular interactions between scion and rootstock responsive to cold, we developed transcriptomics and metabolomics data in the stems of two scion/rootstock combinations, ‘Gala’/‘G202’ (cold resistant rootstock) and ‘Gala’/‘M9’ (cold susceptible rootstock). Outer layers of scion and rootstock stem, including vascular tissues, were collected from the field-grown grafted apple during the winter. The clustering of differentially expressed genes (DEGs) and gene ontology enrichment indicated distinct expression dynamics in the two graft combinations, which supports the dependency of scion cold tolerance on the rootstock genotypes. We identified 544 potentially mobile mRNAs of DEGs showing highly-correlated seasonal dynamics between scion and rootstock. The mobility of a subset of 544 mRNAs was validated by translocated genome-wide variants and the measurements of selected RNA mobility in tobacco and Arabidopsis. We detected orthologous genes of potentially mobile mRNAs in Arabidopsis thaliana, which belong to cold regulatory networks with RNA mobility. Together, our study provides a comprehensive insight into gene interactions and signal exchange between scion and rootstock responsive to cold. This will serve for future research to enhance cold tolerance of grafted tree crops.