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Abstract Securely dated archaeological sites from key regions and periods are critical for understanding early modern human adaptive responses to past environmental change. Here, we report new radiocarbon dates of > 42,000 cal years BP for an intensive human occupation of Gorgora rockshelter in the Ethiopian Highlands. We also document the development of innovative technologies and symbolic behaviors starting around this time. The evidenced occupation and behavioral patterns coincide with the onset and persistence of a stable wet phase in the geographically proximate high-resolution core record of Lake Tana. Range expansion into montane habitats and the subsequent development of innovative technologies and behaviors are consistent with population dispersal waves within Africa and beyond during wetter phases ~ 60–40 thousand years ago (ka).

Abstract [11C]Carfentanil ([11C]CFN) is the only selective carbon-11 labeled radiotracer currently available for positron emission tomography (PET) imaging of mu opioid receptors (MORs). Though used extensively in clinical research, [11C]CFN has not been thoroughly characterized as a tool for preclinical PET imaging. As we were occasionally observing severe vital sign instability in rat [11C]CFN studies, we set out to investigate physiological effects of CFN mass and to explore its influence on MOR quantification. In anesthetized rats (n = 15), significant dose-dependent PCO2 increases and heart rate decreases were observed at a conventional tracer dose range (IV, > 100 ng/kg). Next, we conducted baseline and retest [11C]CFN PET scans over a wide range of molar activities. Baseline [11C]CFN PET studies (n = 27) found that nondisplaceable binding potential (BPND) in the thalamus was positively correlated to CFN injected mass, demonstrating increase of MOR availability at higher injected CFN mass. Consistently, when CFN injected mass was constrained

The paradigm of past climate-driven range shifts structuring the distribution of marine intraspecific biodiversity lacks replication in biological models exposed to comparable limiting conditions in independent regions. This may lead to confounding effects unlinked to climate drivers. We aim to fill in this gap by asking whether the global distribution of intraspecific biodiversity of giant kelp (Macrocystis pyrifera) is explained by past climate changes occurring across the two hemispheres. We compared the species population genetic diversity and structure inferred with microsatellite markers, with range shifts and long-term refugial regions predicted with species distribution modelling (SDM) from the last glacial maximum (LGM) to the present. The broad antitropical distribution of Macrocystis pyrifera is composed by six significantly differentiated genetic groups, for which current genetic diversity levels match the expectations of past climate changes. Range shifts from the LGM to the present structured low latitude refugial regions where genetic relics with higher and unique diversity were found (particularly in the Channel Islands of California and in Peru), while post-glacial expansions following ~ 40% range contraction explained extensive regions with homogenous reduced diversity. The estimated effect of past climate-driven range shifts was comparable between hemispheres, largely demonstrating that the distribution of intraspecific marine biodiversity can be structured by comparable evolutionary forces across the global ocean. Additionally, the differentiation and endemicity of regional genetic groups, confers high conservation value to these localized intraspecific biodiversity hotspots of giant kelp forests.

Abstract The southern coast of Africa is one of the few places in the world where water temperatures are predicted to cool in the future. This endemism-rich coastline is home to two sister species of kelps of the genus Ecklonia maxima and Ecklonia radiata, each associated with specific thermal niches, and occuring primarily on opposite sides of the southern tip of Africa. Historical distribution records indicate that E. maxima has recently shifted its distribution ~ 70 km eastward, to sites where only E. radiata was previously reported. The contact of sister species with contrasting thermal affinities and the occurrence of mixed morphologies raised the hypothesis that hybridization might be occurring in this contact zone. Here we describe the genetic structure of the genus Ecklonia along the southern coast of Africa and investigate potential hybridization and cryptic diversity using a combination of nuclear microsatellites and mitochondrial markers. We found that both species have geographically discrete genetic clusters, consistent with expected phylogeographic breaks along this coastline. In addition, depth-isolated populations were found to harbor unique genetic diversity, including a third Ecklonia lineage. Mito-nuclear discordance and high genetic divergence in the contact zones suggest multiple hybridization events between Ecklonia species. Discordance between morphological and molecular identification suggests the potential influence of abiotic factors leading to convergent phenotypes in the contact zones. Our results highlight an example of cryptic diversity and hybridization driven by contact between two closely related keystone species with contrasting thermal affinities.

Abstract Natriuretic peptides (NP) have multiple actions benefitting cardiovascular and metabolic health. Although many of these are mediated by Guanylyl Cyclase (GC) receptors NPR1 and NPR2, their role and relative importance in vivo is unclear. The intracellular mediator of NPR1 and NPR2, cGMP, circulates in plasma and can be used to examine relationships between receptor activity and tissue responses targeted by NPs. Plasma cGMP was measured in 348 participants previously recruited in a multidisciplinary community study (CHALICE) at age 50 years at a single centre. Associations between bio-active NPs and bio-inactive aminoterminal products with cGMP, and of cGMP with tissue response, were analysed using linear regression. Mediation of associations by NPs was assessed by Causal Mediation Analysis (CMA). ANP’s contribution to cGMP far exceed those of other NPs. Modelling across three components (demographics, NPs and cardiovascular function) shows that ANP and CNP are independent and positive predictors of cGMP. Counter intuitively, findings from CMA imply that in specific tissues, NPR1 responds more to BNP stimulation than ANP. Collectively these findings align with longer tissue half-life of BNP, and direct further therapeutic interventions towards extending tissue activity of ANP and CNP.

Terrestrial open water evaporation is difficult to measure both in situ and remotely yet is critical for understanding changes in reservoirs, lakes, and inland seas from human management and climatically altered hydrological cycling. Multiple satellite missions and data systems (e.g., ECOSTRESS, OpenET) now operationally produce evapotranspiration (ET), but the open water evaporation data produced over millions of water bodies are algorithmically produced differently than the main ET data and are often overlooked in evaluation. Here, we evaluated the open water evaporation algorithm, AquaSEBS, used by ECOSTRESS and OpenET against 19 in situ open water evaporation sites from around the world using MODIS and Landsat data, making this one of the largest open water evaporation validations to date. Overall, our remotely sensed open water evaporation retrieval captured some variability and magnitude in the in situ data when controlling for high wind events (instantaneous: r2 = 0.71; bias = 13% of mean; RMSE = 38% of mean). Much of the instantaneous uncertainty was due to high wind events (u > mean daily 7.5 m·s-1) when the open water evaporation process shifts from radiatively-controlled to atmospherically-controlled; not accounting for high wind events decreases instantaneous accuracy significantly (r2 = 0.47; bias = 36% of mean; RMSE = 62% of mean). However, this sensitivity minimizes with temporal integration (e.g., daily RMSE = 1.2-1.5 mm·day-1). To benchmark AquaSEBS, we ran a suite of 11 machine learning models, but found that they did not significantly improve on the process-based formulation of AquaSEBS suggesting that the remaining error is from a combination of the in situ evaporation measurements, forcing data, and/or scaling mismatch; the machine learning models were able to predict error well in and of itself (r2 = 0.74). Our results provide confidence in the remotely sensed open water evaporation data, though not without uncertainty, and a foundation by which current and future missions may build such operational data.

Abstract Dietary interventions can reduce progression to type 2 diabetes mellitus (T2DM) in people with non-diabetic hyperglycaemia. In this study we aimed to determine the impact of a DNA-personalised nutrition intervention in people with non-diabetic hyperglycaemia over 26 weeks. ASPIRE-DNA was a pilot study. Participants were randomised into three arms to receive either (i) Control arm: standard care (NICE guidelines) (n = 51), (ii) Intervention arm: DNA-personalised dietary advice (n = 50), or (iii) Exploratory arm: DNA-personalised dietary advice via a self-guided app and wearable device (n = 46). The primary outcome was the difference in fasting plasma glucose (FPG) between the Control and Intervention arms after 6 weeks. 180 people were recruited, of whom 148 people were randomised, mean age of 59 years (SD = 11), 69% of whom were female. There was no significant difference in the FPG change between the Control and Intervention arms at 6 weeks (− 0.13 mmol/L (95% CI [− 0.37, 0.11]), p = 0.29), however, we found that a DNA-personalised dietary intervention led to a significant reduction of FPG at 26 weeks in the Intervention arm when compared to standard care (− 0.019 (SD = 0.008), p = 0.01), as did the Exploratory arm (− 0.021 (SD = 0.008), p = 0.006). HbA1c at 26 weeks was significantly reduced in the Intervention arm when compared to standard care (− 0.038 (SD = 0.018), p = 0.04). There was some evidence suggesting prevention of progression to T2DM across the groups that received a DNA-based intervention (p = 0.06). Personalisation of dietary advice based on DNA did not result in glucose changes within the first 6 weeks but was associated with significant reduction of FPG and HbA1c at 26 weeks when compared to standard care. The DNA-based diet was effective regardless of intervention type, though results should be interpreted with caution due to the low sample size. These findings suggest that DNA-based dietary guidance is an effective intervention compared to standard care, but there is still a minimum timeframe of adherence to the intervention before changes in clinical outcomes become apparent. Trial Registration: www.clinicaltrials.gov.uk Ref: NCT03702465.

Abstract Repetitive, long-term inhalation of radioactive radon gas is one of the leading causes of lung cancer, with exposure differences being a function of geographic location, built environment, personal demographics, activity patterns, and decision-making. Here, we examine radon exposure disparities across the urban-to-rural landscape, based on 42,051 Canadian residential properties in 2034 distinct communities. People living in rural, lower population density communities experience as much as 31.2% greater average residential radon levels relative to urban equivalents, equating to an additional 26.7 Bq/m3 excess in geometric mean indoor air radon, and an additional 1 mSv/year in excess alpha radiation exposure dose rate to the lungs for occupants. Pairwise and multivariate analyses indicate that community-based radon exposure disparities are, in part, explained by increased prevalence of larger floorplan bungalows in rural areas, but that a majority of the effect is attributed to proximity to, but not water use from, drilled groundwater wells. We propose that unintended radon gas migration in the annulus of drilled groundwater wells provides radon migration pathways from the deeper subsurface into near-surface materials. Our findings highlight a previously under-appreciated determinant of radon-induced lung cancer risk, and support a need for targeted radon testing and reduction in rural communities.

Abstract Dysfunctional fear responses in post-traumatic stress disorder (PTSD) may be partly explained by an inability to effectively extinguish fear responses elicited by trauma-related cues. However, only a subset of individuals exposed to traumatic stress develop PTSD. Therefore, studying fear extinction deficits in animal models of individual differences could help identify neural substrates underlying vulnerability or resilience to the effects of stress. We used a rat model of social defeat in which rats segregate into passively and actively coping rats. In previous work, we showed that passively coping rats exhibit disruptions in social interaction whereas actively coping rats do not display behaviors differently from controls, indicating their resilience. Here, adult male rats exposed to 7 days of social defeat were tested for fear extinction, retention of extinction, and persistence of retention using contextual fear and ethologically-relevant fear tests. Passively coping rats exhibited elevated freezing in response to the previously extinguished context. Analyses of cFos expressing cells across select brain regions showed high correlations within dorsal hippocampal subregions, while passively coping rats had high correlations between the dorsal hippocampus CA1 and the central and basolateral subregions of the amygdala. Importantly, although control and actively coping rats showed similar levels of behavioral extinction, there was little similarity between activated structures, suggesting stress resilience in response to chronic social defeat involves an adaptive differential recruitment of brain circuits to successfully extinguish fear memories.

Abstract Parent–child interactions are a critical pathway to emotion socialization, with disruption to these processes associated with risk for childhood behavior problems. Using computational linguistics methods, we tested whether (1) play context influenced parent–child socioemotional language, and (2) child conduct problems or callous-unemotional traits were associated with patterns of socioemotional or nonsocial language across contexts. Seventy-nine parent–child dyads (children, 5–6 years old) played a socioemotional skills (“social context”) or math (“nonsocial context”) game at home. We transcribed and analyzed game play, which had been audio recorded by participants. The social context elicited more socioemotional and cognitive words, while the nonsocial context elicited more mathematical words. The use of socioemotional language by parents and children was more strongly correlated in the social context, but context did not moderate the degree of correlation in cognitive or mathematical word use between parents and children. Children with more conduct problems used fewer socioemotional words in the social context, while children with higher callous-unemotional traits used fewer cognitive words in both contexts. We highlight the role of context in supporting socioemotionally rich parent–child language interactions and provide preliminary evidence for the existence of linguistic markers of child behavior problems. Our results also inform naturalistic assessments of parent–child interactions and home-based interventions for parents and children facing socioemotional or behavioral challenges.

Abstract Immunotherapy has dramatically transformed the cancer treatment landscape largely due to the efficacy of immune checkpoint inhibitors (ICIs). Although ICIs have shown promising results for many patients, the low response rates in many cancers highlight the ongoing challenges in cancer treatment. Cytotoxic T lymphocytes (CTLs) execute their cell-killing function via two distinct mechanisms: a fast-acting, perforin-mediated process and a slower, Fas ligand (FasL)-driven pathway. Evidence also suggests that the preferred killing mechanism of CTLs depends on the antigenicity of tumor cells. To determine the critical factors affecting responses to ICIs, we construct an ordinary differential equation model describing in vivo tumor-immune dynamics in the presence of active or blocked PD-1/PD-L1 immune checkpoint. Specifically, we identify important aspects of the tumor-immune landscape that affect tumor size and composition in the short and long term. We also generate a virtual cohort of mice with diverse tumor and immune attributes to simulate the outcomes of immune checkpoint blockade in a heterogeneous population. By identifying key tumor and immune characteristics associated with tumor elimination, dormancy, and escape, we predict which fraction of a population potentially responds well to ICIs and ways to enhance therapeutic outcomes with combination therapy.

Abstract The Streptococcus pyogenes cell envelope protease (SpyCEP) is vital to streptococcal pathogenesis and disease progression. Despite its strong association with invasive disease, little is known about enzymatic function beyond the ELR+ CXC chemokine substrate range. As a serine protease, SpyCEP has a catalytic triad consisting of aspartate (D151), histidine (H279), and serine (S617) residues which are all thought to be mandatory for full activity. We utilised a range of SpyCEP constructs to investigate the protein domains and catalytic residues necessary for enzyme function. We designed a high-throughput mass spectrometry assay to measure CXCL8 cleavage and applied this for the first time to study the enzyme kinetics of SpyCEP. Results revealed a remarkably low Michaelis-Menton constant (KM) of 82 nM and a turnover of 1.65 molecules per second. We found that an N-terminally-truncated SpyCEP C-terminal construct containing just the catalytic dyad of H279 and S617 was capable of cleaving CXCL8 with a similar KM of 55 nM, albeit with a reduced substrate turnover of 2.7 molecules per hour, representing a 2200-fold reduction in activity. We conclude that the SpyCEP C-terminus plays a key role in high affinity substrate recognition and binding, but that the N-terminus is required for full catalytic activity.

Abstract Ethiopia has the greatest burden of Plasmodium vivax in Africa, but little is known about the epidemiological landscape of parasites across the country. We analysed the genomic diversity of 137 P. vivax isolates collected nine Ethiopian districts from 2012 to 2016. Signatures of selection were detected by cross-country comparisons with isolates from Thailand (n = 104) and Indonesia (n = 111), representing regions with low and high chloroquine resistance respectively. 26% (35/137) of Ethiopian infections were polyclonal, and 48.5% (17/35) of these comprised highly related clones (within-host identity-by-descent > 25%), indicating frequent co-transmission and superinfection. Parasite gene flow between districts could not be explained entirely by geographic distance, with economic and cultural factors hypothesised to have an impact on connectivity. Amplification of the duffy binding protein gene (pvdbp1) was prevalent across all districts (16–75%). Cross-population haplotype homozygosity revealed positive selection in a region proximal to the putative chloroquine resistance transporter gene (pvcrt-o). An S25P variant in amino acid transporter 1 (pvaat1), whose homologue has recently been implicated in P. falciparum chloroquine resistance evolution, was prevalent in Ethiopia (96%) but not Thailand or Indonesia (35–53%). The genomic architecture in Ethiopia highlights circulating variants of potential public health concern in an endemic setting with evidence of stable transmission.

Abstract Significant progress has been made in preventing severe COVID-19 disease through the development of vaccines. However, we still lack a validated baseline predictive biologic signature for the development of more severe disease in both outpatients and inpatients infected with SARS-CoV-2. The objective of this study was to develop and externally validate, via 5 international outpatient and inpatient trials and/or prospective cohort studies, a novel baseline proteomic signature, which predicts the development of moderate or severe (vs mild) disease in patients with COVID-19 from a proteomic analysis of 7000 + proteins. The secondary objective was exploratory, to identify (1) individual baseline protein levels and/or (2) protein level changes within the first 2 weeks of acute infection that are associated with the development of moderate/severe (vs mild) disease. For model development, samples collected from 2 randomized controlled trials were used. Plasma was isolated and the SomaLogic SomaScan platform was used to characterize protein levels for 7301 proteins of interest for all studies. We dichotomized 113 patients as having mild or moderate/severe COVID-19 disease. An elastic net approach was used to develop a predictive proteomic signature. For validation, we applied our signature to data from three independent prospective biomarker studies. We found 4110 proteins measured at baseline that significantly differed between patients with mild COVID-19 and those with moderate/severe COVID-19 after adjusting for multiple hypothesis testing. Baseline protein expression was associated with predicted disease severity with an error rate of 4.7% (AUC = 0.964). We also found that five proteins (Afamin, I-309, NKG2A, PRS57, LIPK) and patient age serve as a signature that separates patients with mild COVID-19 and patients with moderate/severe COVID-19 with an error rate of 1.77% (AUC = 0.9804). This panel was validated using data from 3 external studies with AUCs of 0.764 (Harvard University), 0.696 (University of Colorado), and 0.893 (Karolinska Institutet). In this study we developed and externally validated a baseline COVID-19 proteomic signature associated with disease severity for potential use in both outpatients and inpatients with COVID-19.

Abstract Colombia aims to eliminate malaria by 2030 but remains one of the highest burden countries in the Americas. Plasmodium vivax contributes half of all malaria cases, with its control challenged by relapsing parasitaemia, drug resistance and cross-border spread. Using 64 Colombian P. vivax genomes collected between 2013 and 2017, we explored diversity and selection in two major foci of transmission: Chocó and Córdoba. Open-access data from other countries were used for comparative assessment of drug resistance candidates and to assess cross-border spread. Across Colombia, polyclonal infections were infrequent (12%), and infection connectivity was relatively high (median IBD = 5%), consistent with low endemicity. Chocó exhibited a higher frequency of polyclonal infections (23%) than Córdoba (7%), although the difference was not significant (P = 0.300). Most Colombian infections carried double pvdhfr (95%) and single pvdhps (71%) mutants, but other drug resistance mutations were less prevalent (

Abstract The impact of climate change on biodiversity has stimulated the need to understand environmental stress responses, particularly for ecosystem engineers whose responses to climate affect large numbers of associated organisms. Distinct species differ substantially in their resilience to thermal stress but there are also within-species variations in thermal tolerance for which the molecular mechanisms underpinning such variation remain largely unclear. Intertidal mussels are well-known for their role as ecosystem engineers. First, we exposed two genetic lineages of the intertidal mussel Perna perna to heat stress treatments in air and water. Next, we ran a high throughput RNA sequencing experiment to identify differences in gene expression between the thermally resilient eastern lineage and the thermally sensitive western lineage. We highlight different thermal tolerances that concord with their distributional ranges. Critically, we also identified lineage-specific patterns of gene expression under heat stress and revealed intraspecific differences in the underlying transcriptional pathways in response to warmer temperatures that are potentially linked to the within-species differences in thermal tolerance. Beyond the species, we show how unravelling within-species variability in mechanistic responses to heat stress promotes a better understanding of global evolutionary trajectories of the species as a whole in response to changing climate.

The SARS-CoV-2 pandemic has challenged humankind's ability to quickly determine the cascade of health effects caused by a novel infection. Even with the unprecedented speed at which vaccines were developed and introduced into society, identifying therapeutic interventions and drug targets for patients infected with the virus remains important as new strains of the virus evolve, or future coronaviruses may emerge that are resistant to current vaccines. The application of transcriptomic RNA sequencing of infected samples may shed new light on the pathways involved in viral mechanisms and host responses. We describe the application of the previously developed "dual RNA-seq" approach to investigate, for the first time, the co-regulation between the human and SARS-CoV-2 transcriptomes. Together with differential expression analysis, we describe the tissue specificity of SARS-CoV-2 expression, an inferred lipopolysaccharide response, and co-regulation of CXCL's, SPRR's, S100's with SARS-CoV-2 expression. Lipopolysaccharide response pathways in particular offer promise for future therapeutic research and the prospect of subgrouping patients based on chemokine expression that may help explain the vastly different reactions patients have to infection. Taken together these findings highlight unappreciated SARS-CoV-2 expression signatures and emphasize new considerations and mechanisms for SARS-CoV-2 therapeutic intervention.

Abstract The paradigm of past climate-driven range shifts structuring the distribution of marine intraspecific biodiversity lacks replication in biological models exposed to comparable limiting conditions in independent regions. This may lead to confounding effects unlinked to climate drivers. We aim to fill in this gap by asking whether the global distribution of intraspecific biodiversity of giant kelp (Macrocystis pyrifera) is explained by past climate changes occurring across the two hemispheres. We compared the species’ population genetic diversity and structure inferred with microsatellite markers, with range shifts and long-term refugial regions predicted with species distribution modelling (SDM) from the last glacial maximum (LGM) to the present. The broad antitropical distribution of Macrocystis pyrifera is composed by six significantly differentiated genetic groups, for which current genetic diversity levels match the expectations of past climate changes. Range shifts from the LGM to the present structured low latitude refugial regions where genetic relics with higher and unique diversity were found (particularly in the Channel Islands of California and in Peru), while post-glacial expansions following ~ 40% range contraction explained extensive regions with homogenous reduced diversity. The estimated effect of past climate-driven range shifts was comparable between hemispheres, largely demonstrating that the distribution of intraspecific marine biodiversity can be structured by comparable evolutionary forces across the global ocean. Additionally, the differentiation and endemicity of regional genetic groups, confers high conservation value to these localized intraspecific biodiversity hotspots of giant kelp forests.

Abstract We present an ocean-basin-scale dataset that includes tail fluke photographic identification (photo-ID) and encounter data for most living individual humpback whales (Megaptera novaeangliae) in the North Pacific Ocean. The dataset was built through a broad collaboration combining 39 separate curated photo-ID catalogs, supplemented with community science data. Data from throughout the North Pacific were aggregated into 13 regions, including six breeding regions, six feeding regions, and one migratory corridor. All images were compared with minimal pre-processing using a recently developed image recognition algorithm based on machine learning through artificial intelligence; this system is capable of rapidly detecting matches between individuals with an estimated 97–99% accuracy. For the 2001–2021 study period, a total of 27,956 unique individuals were documented in 157,350 encounters. Each individual was encountered, on average, in 5.6 sampling periods (i.e., breeding and feeding seasons), with an annual average of 87% of whales encountered in more than one season. The combined dataset and image recognition tool represents a living and accessible resource for collaborative, basin-wide studies of a keystone marine mammal in a time of rapid ecological change.

Abstract The transport of passively dispersed organisms across tropical margins remains poorly understood. Hypotheses of oceanographic transportation potential lack testing with large scale empirical data. To address this gap, we used the seagrass species, Halodule wrightii, which is unique in spanning the entire tropical Atlantic. We tested the hypothesis that genetic differentiation estimated across its large-scale biogeographic range can be predicted by simulated oceanographic transport. The alternative hypothesis posits that dispersal is independent of ocean currents, such as transport by grazers. We compared empirical genetic estimates and modelled predictions of dispersal along the distribution of H. wrightii. We genotyped eight microsatellite loci on 19 populations distributed across Atlantic Africa, Gulf of Mexico, Caribbean, Brazil and developed a biophysical model with high-resolution ocean currents. Genetic data revealed low gene flow and highest differentiation between (1) the Gulf of Mexico and two other regions: (2) Caribbean-Brazil and (3) Atlantic Africa. These two were more genetically similar despite separation by an ocean. The biophysical model indicated low or no probability of passive dispersal among populations and did not match the empirical genetic data. The results support the alternative hypothesis of a role for active dispersal vectors like grazers.

Abstract The high antibiotic resistance of Pseudomonas aeruginosa (PA) makes it critical to develop alternative antimicrobial agents that are effective and affordable. One of the many applications of silver nanoparticles (Ag NPs) is their use as an antimicrobial agent against bacteria resistant to common antibiotics. The key purpose of this research was to assess the antibacterial and antibiofilm effectiveness of biosynthesized Ag NPs against six biofilm-forming clinically isolated strains of PA and one reference strain (ATCC 27853). Ag NPs were biosynthesized using a seed extract of Peganum harmala as a reducing agent. Ag NPs were characterized by Ultraviolet–visible (UV–Vis) spectroscopy and scanning transmission electron microscopy (STEM). The effect of Ag NPs on biofilm formation and eradication was examined through micro-titer plate assays, and the minimal inhibitory (MIC) and minimum bactericidal (MBC) concentrations determined. In addition, real-time polymerase chain reactions (RT-PCR) were performed to examine the effects of Ag NPs on the expression of seven PA biofilm-encoding genes (LasR, LasI, LssB, rhIR, rhII, pqsA and pqsR). The biosynthesized Ag NPs were spherically-shaped with a mean diameter of 11 nm. The MIC for each PA strain was 15.6 µg/ml, while the MBC was 31.25 µg/ml. All PA strains exposed to Ag NPs at sub-inhibitory concentrations (0.22–7.5 µg/ml) showed significant inhibitory effects on growth and biofilm formation. Biomass and biofilm metabolism were reduced dependent on Ag NP concentration. The expression of the quorum-sensing genes of all strains were significantly reduced at an Ag NP concentration of 7.5 µg/ml. The results demonstrate the extensive in-vitro antibacterial and antibiofilm performance of Ag NPs and their potential in the treatment of PA infection. It is recommended that future studies examine the possible synergy between Ag NPs and antibiotics.

Abstract Most biomedical knowledge is published as text, making it challenging to analyse using traditional statistical methods. In contrast, machine-interpretable data primarily comes from structured property databases, which represent only a fraction of the knowledge present in the biomedical literature. Crucial insights and inferences can be drawn from these publications by the scientific community. We trained language models on literature from different time periods to evaluate their ranking of prospective gene-disease associations and protein–protein interactions. Using 28 distinct historical text corpora of abstracts published between 1995 and 2022, we trained independent Word2Vec models to prioritise associations that were likely to be reported in future years. This study demonstrates that biomedical knowledge can be encoded as word embeddings without the need for human labelling or supervision. Language models effectively capture drug discovery concepts such as clinical tractability, disease associations, and biochemical pathways. Additionally, these models can prioritise hypotheses years before their initial reporting. Our findings underscore the potential for extracting yet-to-be-discovered relationships through data-driven approaches, leading to generalised biomedical literature mining for potential therapeutic drug targets. The Publication-Wide Association Study (PWAS) enables the prioritisation of under-explored targets and provides a scalable system for accelerating early-stage target ranking, irrespective of the specific disease of interest.

Abstract Many species exhibit seasonal patterns of breeding. Although humans can shield themselves from many season-related stressors, they appear to exhibit seasonal patterns of investment in reproductive function nonetheless, with levels of sex steroid hormones being highest during the spring and summer months. The current research builds on this work, examining the relationship between day length and ovarian function in two large samples of women using data from the Natural Cycles birth control application in each Sweden and the United States. We hypothesized that longer days would predict higher ovulation rates and sexual motivation. Results revealed that increasing day length duration predicts increased ovulation rate and sexual behavior, even while controlling for other relevant factors. Results suggest that day length may contribute to observed variance in women’s ovarian function and sexual desire.

Abstract Terrestrial open water evaporation is difficult to measure both in situ and remotely yet is critical for understanding changes in reservoirs, lakes, and inland seas from human management and climatically altered hydrological cycling. Multiple satellite missions and data systems (e.g., ECOSTRESS, OpenET) now operationally produce evapotranspiration (ET), but the open water evaporation data produced over millions of water bodies are algorithmically produced differently than the main ET data and are often overlooked in evaluation. Here, we evaluated the open water evaporation algorithm, AquaSEBS, used by ECOSTRESS and OpenET against 19 in situ open water evaporation sites from around the world using MODIS and Landsat data, making this one of the largest open water evaporation validations to date. Overall, our remotely sensed open water evaporation retrieval captured some variability and magnitude in the in situ data when controlling for high wind events (instantaneous: r2 = 0.71; bias = 13% of mean; RMSE = 38% of mean). Much of the instantaneous uncertainty was due to high wind events (u > mean daily 7.5 m·s−1) when the open water evaporation process shifts from radiatively-controlled to atmospherically-controlled; not accounting for high wind events decreases instantaneous accuracy significantly (r2 = 0.47; bias = 36% of mean; RMSE = 62% of mean). However, this sensitivity minimizes with temporal integration (e.g., daily RMSE = 1.2–1.5 mm·day−1). To benchmark AquaSEBS, we ran a suite of 11 machine learning models, but found that they did not significantly improve on the process-based formulation of AquaSEBS suggesting that the remaining error is from a combination of the in situ evaporation measurements, forcing data, and/or scaling mismatch; the machine learning models were able to predict error well in and of itself (r2 = 0.74). Our results provide confidence in the remotely sensed open water evaporation data, though not without uncertainty, and a foundation by which current and future missions may build such operational data.

Abstract Uncertainty estimation is crucial for understanding the reliability of deep learning (DL) predictions, and critical for deploying DL in the clinic. Differences between training and production datasets can lead to incorrect predictions with underestimated uncertainty. To investigate this pitfall, we benchmarked one pointwise and three approximate Bayesian DL models for predicting cancer of unknown primary, using three RNA-seq datasets with 10,968 samples across 57 cancer types. Our results highlight that simple and scalable Bayesian DL significantly improves the generalisation of uncertainty estimation. Moreover, we designed a prototypical metric—the area between development and production curve (ADP), which evaluates the accuracy loss when deploying models from development to production. Using ADP, we demonstrate that Bayesian DL improves accuracy under data distributional shifts when utilising ‘uncertainty thresholding’. In summary, Bayesian DL is a promising approach for generalising uncertainty, improving performance, transparency, and safety of DL models for deployment in the real world.

Abstract The precise date of the 2nd millennium BCE (“Minoan”) eruption of Thera (Santorini) has long been a focus of controversy due to a discrepancy between archaeological and radiocarbon-based dating of materials from stratigraphic layers above and below tsunami, ash and pumice deposits resulting from the eruption. A critical, though controversial, piece of evidence has been four segments of a radiocarbon-dated olive tree branch, buried on Thera during the eruption. Here we report new radiocarbon evidence from an olive shrub found carbonized by the same eruption deposits on neighboring Therasia (Santorini). The Therasia olive shrub dates slightly younger than the previous olive branch. Calibrated results and growth increment counts indicate increased probabilities for a mid-16th century BCE date for the eruption, overlapping with multiple volcanic sulfate markers from ice core records.