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The global outbreak of clade 2.3.4.4b H5N1 highly pathogenic influenza A virus (HP H5N1) has had an unprecedented impact on wild birds including raptors, but long-term population impacts have not been addressed. To determine if raptors survive infections with HP H5N1, raptors from the upper Midwest United States were serologically tested for antibodies to influenza A virus (IAV), H5 and N1. Raptors were sampled at The Raptor Center's (University of Minnesota) wildlife rehabilitation hospital and at Hawk Ridge Bird Observatory. Samples were tested for IAV antibodies using a commercially available blocking ELISA, with positive samples tested for antibodies to H5 and N1. Antibodies to IAV were detected in 86 out of 316 individuals representing 7 species. Antibodies to H5 and N1 were detected in 60 individuals representing 6 species. Bald eagles had the highest seroprevalence with 67/97 (69.1%) seropositive for IAV and 52 of these 67 (77.6%) testing positive for antibodies to both H5 and N1. Prevalence of antibodies to IAV observed in this study was higher than reported from raptors sampled in this same region in 2012. The high prevalence of antibodies to H5 and N1 indicates a higher survival rate post-HP H5N1 infection in raptors than previously believed., Competing Interests: Declaration. Competing interests: The authors declare no competing interests. Ethics approval: All sampling was performed according to protocols approved by the Institutional Animal Care and Use Committee (IACUC) of the University of Minnesota (2208-40268A) and sampling was performed in accordance with relevant guidelines and regulations including the ARRIVE guidelines. Wildlife rehabilitation performed at TRC was conducted under permits from the United States Fish and Wildlife Service (USFWS) (MB716900-0) and the state of Minnesota (32613). Additionally, collection of scientific samples was accomplished under permits from the USFWS (MB28288A), the state of Minnesota (#32616), and the state of Wisconsin (E/T Permit #3013 and SCPSRLN-23–66). At (HRBO) all bird banding activities and sample collection was performed using standard methods and was covered by a USGS Federal Bird Banding Permit (MBPER0014234)., (© 2025. The Author(s).)

Bovine tuberculosis (bTB) is a threat to cattle health and public safety. The current control programs are hampered by wildlife reservoirs and socioeconomic barriers. Vaccinating cattle with Bacillus Calmette-Guérin (BCG) effectively reduces transmission, offering a potential solution for controlling bTB. A key requirement for vaccination strategies using BCG is the validation of defined antigens to differentiate infections among vaccinated animals (DIVA). We compared tuberculin with DIVA peptide cocktails (ESAT-6, CFP-10, and Rv3615c) in 67 unvaccinated and 67 BCG-vaccinated cattle exposed to M. bovis in a natural setting. The cattle were tested every 4 months with a skin test and every 2 months with interferon-gamma (IFN-γ) release assays (IGRA) over a year of exposure. Before exposure, the DIVA skin, DIVA IGRA, and tuberculin tests showed 100% specificity in unvaccinated control calves. After exposure, the DIVA skin, DIVA IGRA, and comparative cervical tuberculin (CCT) tests had comparable sensitivities of 46% (95% CI 36, 56), 45% (95% CI 35, 55), and 47 (95% CI 37, 57), respectively, when assessed against animals positive by M. bovis culture PCR. The results suggest that test-and-slaughter control strategies using tests with low sensitivity are not expected to be effective in controlling bTB in high-prevalence herds, and highlight an urgent need to improve the sensitivity of diagnostic tests for bTB in these settings., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2025. Crown.)

The two "large low velocity provinces" (LLVPs) are broad, low seismic wave speed anomalies in Earth's lower mantle beneath Africa and the Pacific Ocean. Recent research suggests they contain relatively dense subducted oceanic crust (SOC), but the relative concentration of this recycled material within them is an open question. Using simulations of 3-D global mantle circulation over the past 1 Gyr, we find that two antipodal LLVPs develop naturally as a consequence of Earth's recent subduction history and the gravitational settling and stirring of SOC. Shear-wave velocity reductions in the two LLVPs are similar due to the dominating influence of temperature over composition. However, the formation histories are distinct. Circum-Pacific subduction of oceanic lithosphere has continuously replenished the Pacific LLVP with relatively young SOC since 300 Ma, while the African LLVP comprises older, well-mixed material. Our models suggest the Pacific LLVP stores up to 53% more SOC produced in the last 1.2 Gyr than the African LLVP, potentially making the Pacific domain denser and less buoyant., Competing Interests: Declarations. Competing Interests: The authors declare no competing interests., (© 2025. The Author(s).)

Osteochondrodysplasia, affecting 2-3% of newborns globally, is a group of bone and cartilage disorders that often result in head malformations, contributing to childhood morbidity and reduced quality of life. Current research on this disease using mouse models faces challenges since it involves accurately segmenting (precisely delineating) the developing cartilage in 3D micro-CT images of embryonic mice. Tackling this segmentation task with deep learning (DL) methods is laborious due to the big burden of manual image annotation, expensive due to the high acquisition costs of 3D micro-CT images, and difficult due to embryonic cartilage's complex and rapidly changing shapes. While DL approaches have been proposed to automate cartilage segmentation, most such models have limited accuracy and generalizability, especially across data from different embryonic age groups. To address these limitations, we propose novel DL methods that can be adopted by any DL architectures-including Convolutional Neural Networks (CNNs), Transformers, or hybrid models-which effectively leverage age and spatial information to enhance model performance. Specifically, we propose two new mechanisms, one conditioned on discrete age categories and the other on continuous image crop locations, to enable an accurate representation of cartilage shape changes across ages and local shape details throughout the cranial region. Extensive experiments on multi-age cartilage segmentation datasets show significant and consistent performance improvements when integrating our conditional modules into popular DL segmentation architectures. On average, we achieve a 1.7% Dice score increase with minimal computational overhead and a 7.5% improvement on unseen data. These results highlight the potential of our approach for developing robust, universal models capable of handling diverse datasets with limited annotated data, a key challenge in DL-based medical image analysis., Competing Interests: Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Cancer cells exhibit altered metabolism, often relying on glutamine (Gln) for growth. Breast cancer (BC) is a heterogeneous disease with varying clinical outcomes. We investigated the role of the amino acid transporter SLC1A5 (ASCT2) and its association with BC subtypes and patient outcomes. In large BC cohorts, SLC1A5 mRNA (n = 9488) and SLC1A5 protein (n = 1274) levels were assessed and correlated their expression with clinicopathological features, molecular subtypes, and patient outcomes. In vitro SLC1A5 knockdown and inhibition studies in luminal BC cell lines (ZR-75-1 and HCC1500) were used to further explore the role of SLC1A5 in Gln metabolism. Statistical analysis was performed using chi-squared tests, ANOVA, Spearman's correlation, Kaplan-Meier analysis, and Cox regression. SLC1A5 mRNA and SLC1A5 protein expression were strongly correlated in luminal B, HER2 + and triple-negative BC (TNBC). Both high SLC1A5 mRNA and SLC1A5 protein expression were associated with larger tumour size, higher grade, and positive axillary lymph node metastases (P < 0.01). Importantly, high SLC1A5 expression correlated with poor BC-specific survival specifically in the highly proliferative luminal subtype (P < 0.001). Furthermore, SLC1A5 knockdown by siRNA or GPNA inhibition significantly reduced cell proliferation and glutamine uptake in ZR-75-1 cells. Our findings suggest SLC1A5 plays a key role in the aggressive luminal BC subtype and represents a potential therapeutic target. Further research is needed to explore SLC1A5 function in luminal BC and its association with Gln metabolism pathways., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Ethical approval: This article does not contain any studies with human participants or animals performed This work was performed according to REMARK guidelines or tumour prognostic study and obtained ethics approval by the North West–Greater Manchester Central Research Ethics Committee under the title: Nottingham Health Science Biobank (NHSB), reference number 15/NW/0685. We can declare that this study is complying with Helsinki declaration., (© 2025. The Author(s).)

The amount of data collected for sensing tasks in scientific computing is based on the Shannon-Nyquist sampling theorem proposed in the 1940s. Sensor data generation will surpass 73 trillion GB by 2025 as we increase the high-fidelity digitization of the physical world. Skyrocketing data infrastructure costs and time to maintain and compute on all this data are increasingly common. To address this, we introduce a selective learning approach, where the amount of data collected is problem dependent. We develop novel shift-invariant and spectrally stable neural networks to solve real-time sensing problems formulated as classification or regression problems. We demonstrate that (i) less data can be collected while preserving information, and (ii) test accuracy improves with data augmentation (size of training data), rather than by collecting more than a certain fraction of raw data, unlike information theoretic approaches. While sampling at Nyquist rates, every data point does not have to be resolved at Nyquist and the network learns the amount of data to be collected. This has significant implications (orders of magnitude reduction) on the amount of data collected, computation, power, time, bandwidth, and latency required for several embedded applications ranging from low earth orbit economy to unmanned underwater vehicles., Competing Interests: Declarations. Competing interests: AV and SK have filed two provisional patent applications on some implementations of the above technology, on April 13th, 2022 (U.S. Prov. Pat. App. No. 63330669), and on September 22nd, 2022 (U.S. Prov. Pat. App. No. 63408961). AV, AG, and SK have filed a provisional patent application on some implementations of the above technology, on January 4th, 2024 (U.S. Prov. Pat. App. No. 63/617,463), and on December 17th, 2024 (PCT/US24/60489). AV, AG, and SK have financial interests in Lightscline. SS has no competing interests to declare. As of May, and June 2024, AV and AG respectively are employed with Lightscline Inc., (© 2024. The Author(s).)

Wave ripples can provide valuable information on their formative hydrodynamic conditions in past subaqueous environments by inverting dimension predictors. However, these inversions do not usually take the mixed non-cohesive/cohesive nature of sediment beds into account. Recent experiments involving sand-kaolinite mixtures have demonstrated that wave-ripple dimensions and the threshold of motion are affected by bed clay content. Here, a clean-sand method to determine wave climate from orbital ripple wavelength has been adapted to include the effect of clay and a consistent shear-stress threshold parameterisation. From present-day examples with known wave conditions, the results show that the largest clay effect occurs for coarse sand with median grain diameters over 0.45 mm. For a 7.4% volumetric clay concentration, the range of possible water-surface wavelengths and water depths can be reduced significantly, by factors of three and four compared to clean sand, indicating that neglecting clay when present will underestimate the wave climate., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

We report a strategic development of asymmetric (supercapacitive-pseudocapacitive) and hybrid (supercapacitive/pseudocapacitive-battery) energy device architectures as generation-II electrochemical energy systems. We derived performance-potential estimation regarding the specific power, specific energy, and fast charge-discharge cyclic capability. Among the conceived group, pseudocapacitor-battery hybrid device is constructed with a high-rate intrinsic asymmetric pseudocapacitive (α - MnO 2 /rGO) and a high-capacity Li-ion intercalation battery type (po-nSi/rGO) electrodes. The experimental setup was developed to measure the current sharing between the two different active materials in a single device allowing us to distinguish the contribution of each active electrode material. The combined potentiostatic cyclic voltammograms and galvanostatic charge-discharge cycling profiles provided gravimetric capacity exceeding 600 F/g (or 180.5 mAh g -1 and ≥ 35mC/cm 2 ) resulting in higher specific power and specific energy densities of 6.5 kW kg -1 and 33.5 Wh kg -1 with Coulombic efficiency (CE) and capacitance retention exceeding ≥ 85-90%, reported to date for full cell configuration, compared with symmetric or half-cell configurations (ca. 0.1 kW kg -1 and 13.7 Wh kg -1 ). Other systems studied provided specific energy ranged between 28 Wh kg -1 and 50 Wh kg -1 and specific power between 6.5 kW kg -1 and 1.3 kW kg -1 . Moreover, the behavior of such asymmetric hybrid devices represented a linear combination of the two active electrode material systems. The use of aqueous (and organic) electrolytes for asymmetric electrodes dramatically improved device performance and stability depending upon the electrode combination forming hybrid energy devices. We attribute the observed efficient performance of these hybrid devices induced by hybridized and emergent redox chemistries of merged electrode materials and dynamical processes at the electrode-electrolyte interfaces (intrinsic electroactivity, optimized double-layer and quantum capacitance) which play multiple roles. These energy devices are commercially relevant due to their potential viability in future hybrid electric vehicles, smart electric grids, electrocatalytic fuel production, space (micro-satellites), and miniaturized flexible electronic and wearable biomedical devices., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

The great pond snail Lymnaea stagnalis has served as a model organism for over a century in diverse disciplines such as neurophysiology, evolution, ecotoxicology and developmental biology. To support both established uses and newly emerging research interests we have performed whole genome sequencing (avg.176 × depth), assembly and annotation of a single individual derived from an inbred line. These efforts resulted in a final assembly of 943 Mb (L50 = 257; N50 = 957,215) with a total of 22,499 predicted gene models. The mitogenome was found to be 13,834 bp long and similarly organized as in other lymnaeid species, with minor differences in location of tRNA genes. As a first step towards understanding the hermaphroditic reproductive biology of L. stagnalis, we identified molecular receptors, specifically nuclear receptors (including newly discovered 2xDNA binding domain-NRs), G protein-coupled receptors, and receptor tyrosine kinases, that may be involved in the cellular specification and maintenance of simultaneously active male and female reproductive systems. A phylogenetic analysis of one particular family of GPCRs (Rhodopsin neuropeptide FMRFamide-receptor-like genes) shows a remarkable expansion that coincides with the occurrence of simultaneous hermaphroditism in the Euthyneura gastropods. As some GPCRs and NRs also showed qualitative differences in expression in female (albumen gland) and male (prostate gland) organs, it is possible that separate regulation of male and female reproductive processes may in part have been enabled by an increased abundance of receptors in the transition from a separate-sexed state to a hermaphroditic condition. These findings will support efforts to pair receptors with their activating ligands, and more generally stimulate deeper insight into the mechanisms that underlie the modes of action of compounds involved in neuroendocrine regulation of reproduction, induced toxicity, and development in L. stagnalis, and molluscs in general., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Whiteflies (Bemisia tabaci) and the diseases they transmit are a major detriment to crop yields and a significant contributor to world hunger. The highly evolved interactions of host plant, phloem-feeding insect vector with endosymbionts and persistently transmitted virus represent a tremendous challenge for interdisciplinary study. Presented here is the establishment of a colony of axenic whiteflies on tissue-cultured plants. Efficient colony establishment was achieved by a surface sterilization of eggs laid on axenic phototrophically tissue-cultured plants. The transfer of emerging whiteflies through coupled tissue culture vessels to new axenic plants facilitates robust subculturing and produces hundreds of whitefly adults per month. Whitefly proliferation on more than two dozen plant species is shown as well as in vitro testing of whitefly preference for different plants. This novel multi-organism system provides the high-level of biocontainment required by Federal permitting to conduct virus transmission experiments. Axenic whitefly adults were able to acquire and transmit a begomovirus into tissue-cultured plants, indicating that culturable gut microorganisms are not required for virus transmission. The approach described enables a wide range of hypotheses regarding whitefly phytopathology without the expense, facilities, and contamination ambiguity associated with current approaches., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Extreme short-duration rainfall is intensifying with climate warming, and growing evidence suggests that subhourly rainfall extremes are increasing faster than more widely studied durations at hourly and daily timescales. In this case study, we used 55 years (1968-2022) of 5-min precipitation data from Mahantango Creek, a long-term experimental agricultural watershed in east-central Pennsylvania, United States, to examine annual and seasonal changes in subhourly (15-min), hourly, and daily rainfall extremes. Specifically, we evaluated temporal trends in the magnitude and frequency of subhourly, hourly, and daily rainfall extremes. We then estimated apparent scaling rates between rainfall extremes and dew point temperature (Td) and compared these rates to the Clausius-Clapeyron (CC) rate (∼ 7% per °C). We also determined the coincidence of extreme rainfall trends with indicators of atmospheric instability and convective-type precipitation. Overall, we found the most significant changes in rainfall extremes at 15-min durations during the spring, with magnitudes of these subhourly extremes increasing by 0.6 to 0.9% per year, and frequencies rising by 3.4% per year. Apparent scaling rates in the spring showed that 15-min rainfall extremes transitioned from sub-CC scaling to greater than 2CC scaling when Td reached 11° C, implying a possible shift from stratiform rains to more intense convective rains above this Td threshold. Notably, trends in maximum hourly convective available potential energy (CAPE) increased during spring, as did the ratio of 15-min rainfall extremes to their corresponding daily rainfall totals. Findings indicate that convective-type precipitation may be playing an increasing role in the intensification of springtime 15-min rainfall extremes in Mahantango Creek., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Deep Neural Networks (DNNs) have achieved remarkable accuracy for numerous applications, yet their complexity often renders the explanation of predictions a challenging task. This complexity contrasts with easily interpretable statistical models, which, however, often suffer from lower accuracy. Our work suggests that this underperformance may stem more from inadequate training methods than from the inherent limitations of model structures. We hereby introduce the Synced Explanation-Enhanced Neural Network (SEE-Net), a novel architecture integrating a guiding DNN with a shallow neural network, functionally equivalent to a two-layer mixture of linear models. This shallow network is trained under the guidance of the DNN, effectively bridging the gap between the prediction power of deep learning and the need for explainable models. Experiments on image and tabular data demonstrate that SEE-Net can leverage the advantage of DNNs while providing an interpretable prediction framework. Critically, SEE-Net embodies a new paradigm in machine learning: it achieves high-level explainability with minimal compromise on prediction accuracy by training an almost "white-box" model under the co-supervision of a "black-box" model, which can be tailored for diverse applications., (© 2024. The Author(s).)

Older adults are at risk of committing cognitive and decision-making errors due to the decline in cognitive functions. However, the understanding of the determining factors of cognitive errors among ageing adults is limited. In this study, we explored the role of various psychiatric factors, life satisfaction, and other socioeconomic, health and behavioural risk factors of committing cognitive errors among middle-aged and older adults in India. The study utilized the data from the experimental module of the Longitudinal Ageing Study in India (LASI) Wave-1 (2017-2018) with a sample of 12,754 adults aged 45 years and above. The cognitive error was measured using logical fallacies committed in the activity-based experiments. The study employed descriptive, bivariate statistics and multivariable logistic regression models to identify the factors associated with cognitive errors among the study participants. Depression (aOR = 1.28, 99%, CI: 1.16-1.41), life satisfaction (aOR = 0.99, 99%, CI: 0.98-1.00), and cognitive impairment (aOR = 1.13, 90% CI: 1.00-1.30) self-reported psychiatric) were significantly associated with higher odds of committing cognitive errors among the middle-aged and older adults. Also, ageing adults with low educational levels, functional limitations, sleep disturbances, smoking history, living in rural areas and belonging to scheduled tribes had a higher probability of committing cognitive errors. However, involvement in physical activity, reading habits and social interactions reduced the odds of cognitive errors among this sample. Mental health and well-being indicators, including depression, life satisfaction, cognitive impairment, and other health and behavioural health factors, determine cognitive errors among ageing adults. Programs and policies should be initiated to address these factors, reduce cognitive errors, and ensure active ageing., (© 2024. The Author(s).)

Various machine learning (ML) and deep learning (DL) techniques have been recently applied to the forecasting of laboratory earthquakes from friction experiments. The magnitude and timing of shear failures in stick-slip cycles are predicted using features extracted from the recorded ultrasonic or acoustic emission (AE) signals. In addition, the Rate and State Friction (RSF) constitutive laws are extensively used to model the frictional behavior of faults. In this work, we use data from shear experiments coupled with passive acoustic (variance, kurtosis, and AE rate) interleaved with active source ultrasonic monitoring (transmitted wave amplitude) to develop physics-informed neural network (PINN) models incorporating the RSF law and AE rate generation equation with wave amplitude serving as a proxy for friction state variable. This PINN framework allows learning RSF parameters from stick-slip experiments rather than measuring them through a series of velocity step experiments. We observe that when the stick-slip cycles are irregular, the PINN models outperform the data-driven DL models. Transfer learning (TL) PINN models are also developed by pre-training on data collected at one normal stress level followed by forecasting shear failures and retrieving RSF parameters at other stress levels (i.e., with different recurrence intervals) after retraining on a limited amount of new data. Our findings suggest that TL models perform better compared to standalone models. Both standalone and TL PINN-estimated RSF parameters and their ground truth values show excellent agreements thus demonstrating that RSF parameters can be retrieved from laboratory stick-slip experiments using the corresponding acoustic data and that the transmitted wave amplitude provides a good representation of the evolving frictional state during stick-slips., (© 2024. The Author(s).)

The far-UVC (222 nm) system has emerged as a solution for controlling airborne transmission, yet its effect on indoor air quality, particularly concerning positioning, remains understudied. In this study, we examined the impact of far-UVC lamp position on the disinfection and secondary contaminant formation in a small office. We employed a three-dimensional computational fluid dynamics (CFD) model to integrate UV intensity fields formed by different lamp positions (ceiling-mounted, wall-mounted, and stand-alone types) along with the air quality model. Our findings reveal that the ceiling-mounted type reduces human exposure to airborne pathogens by up to 80% compared to scenarios without far-UVC. For all the lamp positions, O 3 concentration in the breathing zone increases by 4-6 ppb after one hour of operation. However, it should be noted that a high concentration zone (> 25 ppb) forms near the lamp when it is turned on. Moreover, ventilation plays a crucial role in determining human exposure to airborne pathogens and secondary contaminants. Increasing the ventilation rate from 0.7 h -1 to 4 h -1 reduces airborne pathogen and secondary contaminant concentrations by up to 90%. However, caution is warranted as higher ventilation rates can lead to elevated O 3 indoors, especially under conditions of high outdoor O 3 concentrations., (© 2024. The Author(s).)

Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample size. These efforts unveil new questions about how to integrate data across distinct sources and instruments. The goal of this study was to link scores across common auditory verbal learning tasks (AVLTs). This international secondary analysis aggregated multisite raw data for AVLTs across 53 studies totaling 10,505 individuals. Using the ComBat-GAM algorithm, we isolated and removed the component of memory scores associated with site effects while preserving instrumental effects. After adjustment, a continuous item response theory model used multiple memory items of varying difficulty to estimate each individual's latent verbal learning ability on a single scale. Equivalent raw scores across AVLTs were then found by linking individuals through the ability scale. Harmonization reduced total cross-site score variance by 37% while preserving meaningful memory effects. Age had the largest impact on scores overall (- 11.4%), while race/ethnicity variable was not significant (p > 0.05). The resulting tools were validated on dually administered tests. The conversion tool is available online so researchers and clinicians can convert memory scores across instruments. This work demonstrates that global harmonization initiatives can address reproducibility challenges across the behavioral sciences., (© 2024. The Author(s).)

Hope is a vital coping mechanism, enabling individuals to effectively confront life's challenges. This study proposes a technique employing Natural Language Processing (NLP) tools like Linguistic Inquiry and Word Count (LIWC), NRC-emotion-lexicon, and vaderSentiment to analyze social media posts, extracting psycholinguistic, emotional, and sentimental features from a hope speech dataset. The findings of this study reveal distinct cognitive, emotional, and communicative characteristics and psycholinguistic dimensions, emotions, and sentiments associated with different types of hope shared in social media. Furthermore, the study investigates the potential of leveraging this data to classify different types of hope using machine learning algorithms. Notably, models such as LightGBM and CatBoost demonstrate impressive performance, surpassing traditional methods and competing effectively with deep learning techniques. We employed hyperparameter tuning to optimize the models' parameters and compared their performance using both default and tuned settings. The results highlight the enhanced efficiency achieved through hyperparameter tuning for these models., (© 2024. The Author(s).)

Collective cancer invasion exhibits a hierarchical structure characterized by leader-follower organization. Dynamic gene expression analysis of invading cells using nanobiosensors within 3D microenvironments provides a valuable means to explore the regulation of leader cells during collective cancer invasion. Nonetheless, the analysis of time-lapse, multimodal images that capture the intricacies of complex invading structures and gene expression profiles in 3D tumor spheroids poses a significant technological challenge. Here, we present a computer vision-based workflow that streamlines the identification of protrusions and detached clusters from 3D tumor spheroids. This methodology not only discerns invading multicellular structures and quantifies their physical properties, but also captures gene expression patterns associated with these invasive mechanisms using an intracellular nanobiosensor. Consequently, it empowers a systematic exploration of the genotypic and phenotypic heterogeneities inherent in cancer invasion. To illustrate the effectiveness of this approach, we applied it to the analysis of a long noncoding RNA, MALAT1, in tumor spheroids derived from patients with muscle-invasive bladder cancer. Our investigation delved into the heterogeneity of cancer invasion and its relationship to MALAT1 expression. Overall, this workflow represents a valuable tool for gaining insights into the complexities of cancer invasion., (© 2024. The Author(s).)

One of the main challenges in coral reef conservation and restoration is the identification of coral populations resilient under global warming. Seascape genomics is a powerful tool to uncover genetic markers potentially involved in heat tolerance among large populations without prior information on phenotypes. Here, we aimed to provide first insights on the role of candidate heat associated loci identified using seascape genomics in driving the phenotypic response of Acropora millepora from New Caledonia to thermal stress. We subjected 7 colonies to a long-term ex-situ heat stress assay (4 °C above the maximum monthly mean) and investigated their physiological response along with their Symbiodiniaceae communities and genotypes. Despite sharing similar thermal histories and associated symbionts, these conspecific individuals differed greatly in their tolerance to heat stress. More importantly, the clustering of individuals based on their genotype at heat-associated loci matched the phenotypic variation in heat tolerance. Colonies that sustained on average lower mortality, higher Symbiodiniaceae/chlorophyll concentrations and photosynthetic efficiency under prolonged heat stress were also the closest based on their genotypes, although the low sample size prevented testing loci predictive accuracy. Together these preliminary results support the relevance of coupling seascape genomics and long-term heat stress experiments in the future, to evaluate the effect size of candidate heat associated loci and pave the way for genomic predictive models of corals heat tolerance., (© 2024. The Author(s).)

Visitors to Colter Bay Village in Grand Teton National Park were surveyed to elicit their evaluations of experimental outdoor lighting conditions. Luminaires capable of dimming and switching between two LED modules (white, blended red-white) were installed in street and parking areas. The blended red-white lamps consisted of 30 narrowband LED with a peak wavelength 623 nm and two 3000 K white LEDs. Similar "red" lamps were previously shown to reduce impacts to bats and insects. The white and red lamps were closely matched for luminance. Measured horizontal illuminance at survey locations had an interquartile range from 0.63 to 3.82 lx. The red lamps produced lower perceived brightness (V B2 (λ)), even after reflection off asphalt, yet survey participants expressed higher ratings for visual comfort and safety under red lighting. Surveys conducted earlier in the evening, with higher levels of predicted solar and measured horizontal illuminance, rated higher on visual comfort and safety, though these correlations were not as strong as the effect of lamp color. Streetlight ratings and support for lighting that protected natural resources were not contingent upon age or gender. Survey participants assessed red lighting as more protective of the environment. These results demonstrate that outdoor lighting designed to reduce ecological impacts can yield superior nocturnal experience for pedestrians., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Huanglongbing (HLB), associated with the psyllid-vectored phloem-limited bacterium, Candidatus Liberibacter asiaticus (CLas), is a disease threat to all citrus production worldwide. Currently, there are no sustainable curative or prophylactic treatments available. In this study, we utilized mass spectrometry (MS)-based metabolomics in combination with 3D molecular mapping to visualize complex chemistries within plant tissues to explore how these chemistries change in vivo in HLB-infected trees. We demonstrate how spatial information from molecular maps of branches and single leaves yields insight into the biology not accessible otherwise. In particular, we found evidence that flavonoid biosynthesis is disrupted in HLB-infected trees, and an increase in the polyamine, feruloylputrescine, is highly correlated with an increase in disease severity. Based on mechanistic details revealed by these molecular maps, followed by metabolic modeling, we formulated and tested the hypothesis that CLas infection either directly or indirectly converts the precursor compound, ferulic acid, to feruloylputrescine to suppress the antimicrobial effects of ferulic acid and biosynthetically downstream flavonoids. Using in vitro bioassays, we demonstrated that ferulic acid and bioflavonoids are indeed highly bactericidal to CLas, with the activity on par with a reference antibiotic, oxytetracycline, recently approved for HLB management. We propose these compounds should be evaluated as therapeutics alternatives to the antibiotics for HLB treatment. Overall, the utilized 3D metabolic mapping approach provides a promising methodological framework to identify pathogen-specific inhibitory compounds in planta for potential prophylactic or therapeutic applications., (© 2024. The Author(s).)

This paper investigates the impact of big data on deep learning models to help solve the full waveform inversion (FWI) problem. While it is well known that big data can boost the performance of deep learning models in many tasks, its effectiveness has not been validated for FWI. To address this gap, we present an empirical study that investigates how deep learning models in FWI behave when trained on OPENFWI, a collection of large-scale, multi-structural, synthetic datasets published recently. In particular, we train and evaluate the FWI models on a combination of 10 2D subsets in OPENFWI that contain 470 K pairs of seismic data and velocity maps in total. Our experiments demonstrate that training on the combined dataset yields an average improvement of 13.03% in MAE, 7.19% in MSE and 1.87% in SSIM compared to each split dataset, and an average improvement of 28.60%, 21.55% and 8.22% in the leave-one-out generalization test. We further demonstrate that model capacity needs to scale in accordance with data size for optimal improvement, where our largest model yields an average improvement of 20.06%, 13.39% and 0.72% compared to the smallest one., (© 2024. The Author(s).)

This study tests whether memory impairment and perceived increases in stress due to life changes independently contribute to similar personality changes, such as increased neuroticism and decreased conscientiousness. Longitudinal data from 12,912 participants aged 50+ from the Health and Retirement Study (2006-2020) were analyzed using Latent Growth Curve Models (LGCMs). Six LGCMs were simultaneously estimated to examine how changes in personality across three data points spanning 8 years are predicted by both the classification of memory impairment (MI) statuses assessed via the Telephone Interview for Cognitive Status and estimated increases in life stress. Decreases were observed in all Big Five personality factors (B =  - 0.240/- 0.510, SE = 0.085/0.089) over the 8-year period. No significant differences in personality changes were found between MI cases and non-MI cases. Increased life stress was significantly associated with a rise in neuroticism (B = 0.587, SE = 0.094) and reductions in conscientiousness, extraversion, agreeableness, and openness (B ranges from - 0.223 to - 0.497). The findings emphasize adaptive/developmental shifts in personality in response to life stress rather than neuropathological ones related to memory impairment. Clinical assessment of personality changes in mid-to-late life should first consider psychological maladaptation to situational threats and challenges., (© 2024. The Author(s).)

Climate-induced changes in hypoxia are among the most serious threats facing estuaries, which are among the most productive ecosystems on Earth. Future projections of estuarine hypoxia typically involve long-term multi-decadal continuous simulations or more computationally efficient time slice and delta methods that are restricted to short historical and future periods. We make a first comparison of these three methods by applying a linked terrestrial-estuarine model to the Chesapeake Bay, a large coastal-plain estuary in the eastern United States. Results show that the time slice approach accurately captures the behavior of the continuous approach, indicating a minimal impact of model memory. However, increases in mean annual hypoxic volume by the mid-twenty-first century simulated by the delta approach (+ 19%) are approximately twice as large as the time slice and continuous experiments (+ 9% and + 11%, respectively), indicating an important impact of changes in climate variability. Our findings suggest that system memory and projected changes in climate variability, as well as simulation length and natural variability of system hypoxia, should be considered when deciding to apply the more computationally efficient delta and time slice methods., (© 2024. The Author(s).)

Using a system that incorporates a variety of food items rather than focusing on individual components can aid in assessing the inflammatory effects of a diet on disease outcomes such as chronic kidney disease (CKD). Therefore, we decided to investigate the association between dietary inflammatory index (DII) and the risk of protein-energy wasting (PEW) and sarcopenia in patients with CKD. In this cross-sectional study, 109 patients with CKD were selected from two clinics in Shiraz, Iran. The intake of individuals' diets was recorded using a validated 168-item food frequency questionnaire. Additionally, Asian Working Group for Sarcopenia (AWGS) guidelines were utilized to evaluate muscles' strength, mass, and function. Also, four International Society of Renal Nutrition and Metabolism (ISRNM) criteria (body mass index, intake of protein, albumin, and urine creatinine) were used  to diagnose PEW. Logistic regression was used to assess the association between DII and sarcopenia as well as PEW. The results showed that the intake of saturated fatty acids, trans fatty acids, niacin, beta-carotene, and vitamin C was significantly different between lower and higher DII groups. In the univariate model, higher odds of sarcopenia was observed by each unit increase in DII (odds ratio (OR) = 1.379, 95% confidence interval (CI): 1.042-1.824) and age (OR = 1.073, 95% CI: 1.017-1.132). Additionally, in the multivariate model, the association between DII and age with odds of sarcopenia remained significant (DII: OR = 1.379, 95% CI: 1.030-1.846 and age: OR = 1.063, 95% CI: 1.007-1.121). The current study suggests the possible role of pro-inflammatory foods in worsening muscle health, specifically sarcopenia, in CKD patients. Future longitudinal studies may reveal the causative nature of these correlations., (© 2024. The Author(s).)

To solve the problems of poor top coal drawing, lagging collapse, and difficulty in parallel operation of mining and drawing in extra-thick coal seams, considering the 8222 working face of the Tashan Mine as the engineering background, we first investigate the basic problems of fully mechanized top coal drawing mining in extra-thick coal seams using the single-round group drawing method (GDM). We then analyze the drawing law of top coal with different thicknesses under the single-round GDM from the aspects of top coal recovery (TCR) and drawing efficiency, coal loss mechanism, and the relation between TCR and gangue content (GC), providing a basis for determining the process parameters of GDM. Results indicate that as the top coal thickness increases, the number of drawing openings considerably influences drawing efficiency and top coal loss. And there is a notable thickness effect of the number of drawing openings on the top coal loss. There is a quantitative relationship among TCR, cumulative GC (CGC) and instantaneous GC (IGC), and CGC and TCR can be predicted based on the IGC. Consequently, theoretical analysis and numerical simulation results indicate that the optimal IGC threshold at the coal drawing openings between 31.2 and 40%. Through optimizing the coal drawing method and strictly controlling the IGC at the coal drawing openings on-site, the measured working face TCR increased from 75.25 to 90.12%, and CGC was controlled at approximately 9%. Meanwhile, the average coordination efficiency of mining and drawing time reaches 68.2%, effectively ensuring the construction of a coal mine with an annual output of 15 million tons., (© 2024. The Author(s).)

Advances in tagging technologies are expanding opportunities to estimate survival of fish and wildlife populations. Yet, capture and handling effects could impact survival outcomes and bias inference about natural mortality processes. We developed a multistage time-to-event model that can partition the survival process into sequential phases that reflect the tagged animal experience, including handling and release mortality, post-release recovery mortality, and subsequently, natural mortality. We demonstrate performance of multistage survival models through simulation testing and through fish and bird telemetry case studies. Models are implemented in a Bayesian framework and can accommodate left, right, and interval censorship events. Our results indicate that accurate survival estimates can be achieved with reasonable sample sizes ( n ≈ 100 + ) and that multimodel inference can inform hypotheses about the configuration and length of survival stages needed to adequately describe mortality processes for tracked specimens. While we focus on survival estimation for tagged fish and wildlife populations, multistage time-to-event models could be used to understand other phenomena of interest such as migration, reproduction, or disease events across a range of taxa including plants and insects., (© 2024. The Author(s).)

The study presents a series of examples of magnetic nanoparticle systems designed for the diagnosis of viral diseases. In this interdisciplinary work, we describe one of the most comprehensive synthetic approaches for the preparation and functionalization of smart nanoparticle systems for rapid and effective RT-PCR diagnostics and isolation of viral RNA. Twelve different organic ligands and inorganic porous silica were used for surface functionalization of the Fe 3 O 4 magnetic core to increase the number of active centres for efficient RNA binding from human swab samples. Different nanoparticle systems with common beads were characterized by HRTEM, SEM, FT-IR, XRD, XPS and magnetic measurements. We demonstrate the application of the fundamental models modified to fit the experimental zero-field cooling magnetization data. We discuss the influence of the nanoparticle shell parameters (morphology, thickness, ligands) on the overall magnetic performance of the systems. The prepared nanoparticles were tested for the isolation of viral RNA from tissue samples infected with hepatitis E virus-HEV and from biofluid samples of SARS-CoV-2 positive patients. The efficiency of RNA isolation was quantified by RT-qPCR method., (© 2024. The Author(s).)

Bovine tuberculosis (bTB) is endemic and has a substantial impact on the livestock sector in Ethiopia and other low and middle-income countries (LMICs). With a national emphasis on dairy farm intensification to boost milk production and spur economic growth, the incidence of bTB is anticipated to rise. However, Ethiopia, like other LMICs, lacks a comprehensive national bTB control strategy due to the economic and social infeasibility of traditional test-and-cull (TC) approaches. To inform the development of such a strategy, we evaluated the effectiveness and feasibility of TC and test-and-segregation (TSg) strategies for bTB control on Ethiopian dairy farms. A TC approach was used at Farm A [N = 62; comparative cervical test (CCT) > 4 mm, starting prevalence 11.3%] while TSg was implemented at Farm B (N = 45; CCT > 4 mm, prevalence 22.2%), with testing intervals of 2-4 months. Both strategies achieved a reduction in bTB prevalence to 0%, requiring seven rounds of TC over 18 months at Farm A, and five rounds of TSg over 12 months at Farm B's negative herd. The results show that adopting more sensitive thresholds [CCT > 0 mm or single cervical test (SCT) > 2 mm] during later rounds was pivotal in identifying and managing previously undetected infections, emphasizing the critical need for optimized diagnostic thresholds. Cost analysis revealed that TC was approximately twice as expensive as TSg, primarily due to testing, labor, and cow losses in TC, versus construction of new facilities and additional labor for TSg. This underscores the economic and logistical challenges of bTB management in resource-limited settings. Taken together, our study highlights an urgent need for the exploration of alternative approaches including TSg and or vaccination to mitigate within herd transmission and enable implementation of bTB control in regions where TC is not feasible., (© 2024. The Author(s).)

Despite of excellent thermal properties and high sputtering resistance, pure tungsten cannot fully satisfy the requirements for plasma facing materials in future high-duty cycle nuclear fusion reactions due to the coupled extreme environments, including the high thermal loads, plasma exposure, and radiation damage. Here, we demonstrated that tungsten-based composite materials fabricated using spark-plasma sintering (SPS) present promising solutions to these challenges. Through the examination of two model systems, i.e., tungsten-zirconium composite for producing porous tungsten near the surface and dispersoid-strengthened tungsten, we discussed both the strengths and limitations of the SPS-fabricated materials. Our findings point towards the need for future studies aimed at optimizing the SPS process to achieve desired microstructures and effective control of oxygen impurities in the tungsten-based composite materials., (© 2024. The Author(s).)

Genome interpretation (GI) encompasses the computational attempts to model the relationship between genotype and phenotype with the goal of understanding how the first leads to the second. While traditional approaches have focused on sub-problems such as predicting the effect of single nucleotide variants or finding genetic associations, recent advances in neural networks (NNs) have made it possible to develop end-to-end GI models that take genomic data as input and predict phenotypes as output. However, technical and modeling issues still need to be fixed for these models to be effective, including the widespread underdetermination of genomic datasets, making them unsuitable for training large, overfitting-prone, NNs. Here we propose novel GI models to address this issue, exploring the use of two types of transfer learning approaches and proposing a novel Biologically Meaningful Sparse NN layer specifically designed for end-to-end GI. Our models predict the leaf and seed ionome in A.thaliana, obtaining comparable results to our previous over-parameterized model while reducing the number of parameters by 8.8 folds. We also investigate how the effect of population stratification influences the evaluation of the performances, highlighting how it leads to (1) an instance of the Simpson's Paradox, and (2) model generalization limitations., (© 2024. The Author(s).)

Understanding local patterns of rainfall variability is of great concern in East Africa, where agricultural productivity is dominantly rainfall dependent. However, East African rainfall climatology is influenced by numerous drivers operating at multiple scales, and local patterns of variability are not adequately understood. Here, we show evidence of substantial variability of local rainfall patterns between 1981 and 2021 at the national and county level in Kenya, East Africa. Results show anomalous patterns of both wetting and drying in both the long and short rainy seasons, with evidence of increased frequency of extreme wet and dry events through time. Observations also indicate that seasonal and intraseasonal variability increased significantly after 2013, coincident with diminished coherence between ENSO (El Nino Southern Oscillation) and rainfall. Increasing frequency and magnitude of rainfall variability suggests increasing need for local-level climate change adaptation strategies., (© 2024. The Author(s).)

Genetics studies are used by wildlife managers and researchers to gain inference into a population of a species of interest. To gain these insights, microsatellites have been the primary method; however, there currently is a shift from microsatellites to single nucleotide polymorphisms (SNPs). With the different DNA requirements between microsatellites and SNPs, an investigation into which samples can provide adequate DNA yield is warranted. Using samples that were collected from previous genetic projects from regions in the USA from 2014 to 2021, we investigated the DNA yield of eight sample categories to gain insights into which provided adequate DNA to be used in ddRADseq or already developed high- or medium-density SNP panels. We found seven sample categories that met the DNA requirements for use in all three panels, and one sample category that did not meet any of the three panels requirements; however, DNA integrity was highly variable and not all sample categories that met panel DNA requirements could be considered high quality DNA. Additionally, we used linear random-effects models to determine which covariates would have the greatest influence on DNA yield. We determined that all covariates (tissue type, storage method, preservative, DNA quality, time until DNA extraction and time after DNA extraction) could influence DNA yield., (© 2024. The Author(s).)

Aquatic detritivores are highly sensitive to changes in temperature and leaf litter quality caused by increases in atmospheric CO 2 . While impacts on detritivores are evident at the organismal and population level, the mechanisms shaping ecological communities remain unclear. Here, we conducted field and laboratory experiments to examine the interactive effects of changes in leaf litter quality, due to increasing atmospheric CO 2 , and warming, on detritivore survival (at both organismal and community levels) and detritus consumption rates. Detritivore community consisted of the collector-gathering Polypedilum (Chironomidae), the scraper and facultative filtering-collector Atalophlebiinae (Leptophlebiidae), and Calamoceratidae (Trichoptera), a typical shredder. Our findings reveal intricate responses across taxonomic levels. At the organismal level, poor-quality leaf litter decreased survivorship of Polypedilum and Atalophlebiinae. We observed taxon-specific responses to warming, with varying effects on growth and consumption rates. Notably, species interactions (competition, facilitation) might have mediated detritivore responses to climate stressors, influencing community dynamics. While poor-quality leaf litter and warming independently affected detritivore larvae abundance of Atalophebiinae and Calamoceratidae, their combined effects altered detritus consumption and emergence of adults of Atalophlebiinae. Furthermore, warming influenced species abundances differently, likely exacerbating intraspecific competition in some taxa while accelerating development in others. Our study underscores the importance of considering complex ecological interactions in predicting the impact of climate change on freshwater ecosystem functioning. Understanding these emergent properties contributes to a better understanding of how detritivore communities may respond to future environmental conditions, providing valuable insights for ecosystem management and conservation efforts., (© 2024. The Author(s).)

The squash family (Cucurbitaceae) contains some of the most important crops cultivated worldwide and has played an important ecological, economic, and cultural role for millennia. In the American tropics, squashes were among the first cultivated crop species, but little is known about how their domestication unfolded. Here, we employ direct radiocarbon dating and morphological analyses of desiccated cucurbit seeds, rinds, and stems from El Gigante Rockshelter in Honduras to reconstruct human practices of selection and cultivation of Lagenaria siceraria, Cucurbita pepo, and Cucurbita moschata. Direct radiocarbon dating indicates that humans started using Lagenaria and wild Cucurbita starting ~ 10,950 calendar years before present (cal B.P.), primarily as watertight vessels and possibly as cooking and drinking containers. A rind directly dated to 11,150-10,765 cal B.P. represents the oldest known bottle gourd in the Americas. Domesticated C. moschata subsequently appeared ~ 4035 cal B.P., followed by domesticated C. pepo ~ 2190 cal B.P. associated with increasing evidence for their use as food crops. Multivariate statistical analysis of seed size and shape show that the archaeological C. pepo assemblage exhibits significant variability, representing at least three varieties: one similar to present-day zucchini, another like present-day vegetable marrow, and a native cultivar without modern analogs. Our archaeobotanical data supports the hypothesis that Indigenous cucurbit use started in the Early Holocene, and that agricultural complexity during the Late Holocene involved selective breeding that encouraged crop diversification., (© 2024. The Author(s).)

Amphibians are often recognized as bioindicators of healthy ecosystems. The persistence of amphibian populations in heavily contaminated environments provides an excellent opportunity to investigate rapid vertebrate adaptations to harmful contaminants. Using a combination of culture-based challenge assays and a skin permeability assay, we tested whether the skin-associated microbiota may confer adaptive tolerance to tropical amphibians in regions heavily contaminated with arsenic, thus supporting the adaptive microbiome principle and immune interactions of the amphibian mucus. At lower arsenic concentrations (1 and 5 mM As 3+ ), we found a significantly higher number of bacterial isolates tolerant to arsenic from amphibians sampled at an arsenic contaminated region (TES) than from amphibians sampled at an arsenic free region (JN). Strikingly, none of the bacterial isolates from our arsenic free region tolerated high concentrations of arsenic. In our skin permeability experiment, where we tested whether a subset of arsenic-tolerant bacterial isolates could reduce skin permeability to arsenic, we found that isolates known to tolerate high concentrations of arsenic significantly reduced amphibian skin permeability to this metalloid. This pattern did not hold true for bacterial isolates with low arsenic tolerance. Our results describe a pattern of environmental selection of arsenic-tolerant skin bacteria capable of protecting amphibians from intoxication, which helps explain the persistence of amphibian populations in water bodies heavily contaminated with arsenic., (© 2024. The Author(s).)

Prior COVID-19 infection may elevate activity of the behavioral immune system-the psychological mechanisms that foster avoidance of infection cues-to protect the individual from contracting the infection in the future. Such "adaptive behavioral immunity" may come with psychological costs, such as exacerbating the global pandemic's disruption of social and emotional processes (i.e., pandemic disruption). To investigate that idea, we tested a mediational pathway linking prior COVID infection and pandemic disruption through behavioral immunity markers, assessed with subjective emotional ratings. This was tested in a sample of 734 Mechanical Turk workers who completed study procedures online during the global pandemic (September 2021-January 2022). Behavioral immunity markers were estimated with an affective image rating paradigm. Here, participants reported experienced disgust/fear and appraisals of sickness/harm risk to images varying in emotional content. Participants self-reported on their previous COVID-19 diagnosis history and level of pandemic disruption. The findings support the proposed mediational pathway and suggest that a prior COVID-19 infection is associated with broadly elevated threat emotionality, even to neutral stimuli that do not typically elicit threat emotions. This elevated threat emotionality was in turn related to disrupted socioemotional functioning within the pandemic context. These findings inform the psychological mechanisms that might predispose COVID survivors to mental health difficulties., (© 2024. The Author(s).)

The control of arthropod disease vectors using chemical insecticides is vital in combating malaria, however the increasing insecticide resistance (IR) poses a challenge. Furthermore, climate variability affects mosquito population dynamics and subsequently IR propagation. We present a mathematical model to decipher the relationship between IR in Anopheles gambiae populations and climate variability. By adapting the susceptible-infected-resistant (SIR) framework and integrating temperature and rainfall data, our model examines the connection between mosquito dynamics, IR, and climate. Model validation using field data achieved 92% accuracy, and the sensitivity of model parameters on the transmission potential of IR was elucidated (e.g. μPRCC = 0.85958, p-value < 0.001). In this study, the integration of high-resolution covariates with the SIR model had a significant impact on the spatial and temporal variation of IR among mosquito populations across Africa. Importantly, we demonstrated a clear association between climatic variability and increased IR (width = [0-3.78], α = 0.05). Regions with high IR variability, such as western Africa, also had high malaria incidences thereby corroborating the World Health Organization Malaria Report 2021. More importantly, this study seeks to bolster global malaria combat strategies by highlighting potential IR 'hotspots' for targeted intervention by National malria control programmes., (© 2024. The Author(s).)

Due to the increasing demand for energy storage devices, the development of high-energy density batteries is very necessary. Lithium-sulfur (Li-S) batteries have gained wide interest due to their particularly high-energy density. However, even this type of battery still needs to be improved. Novel Cu(II)-based metal-organic framework STAM-1 was synthesized and applied as a composite cathode material as a sulfur host in the lithium-sulfur battery with the aim of regulating the redox kinetics of sulfur cathodes. Prepared STAM-1 was characterized by infrared spectroscopy at ambient temperature and after in-situ heating, elemental analysis, X-ray photoelectron spectroscopy and textural properties by nitrogen and carbon dioxide adsorption at - 196 and 0 °C, respectively. Results of the SEM showed that crystals of STAM-1 created a flake-like structure, the surface was uniform and porous enough for electrolyte and sulfur infiltration. Subsequently, STAM-1 was used as a sulfur carrier in the cathode construction of a Li-S battery. The charge/discharge measurements of the novel S/STAM-1/Super P/PVDF cathode demonstrated the initial discharge capacity of 452 mAh g -1 at 0.5 C and after 100 cycles of 430 mAh g -1 , with Coulombic efficiency of 97% during the whole cycling procedure at 0.5 C. It was confirmed that novel Cu-based STAM-1 flakes could accelerate the conversion of sulfur species in the cathode material., (© 2024. The Author(s).)

Endocrine therapy (ET) for breast cancer treatment is associated with cognitive complaints, but their etiology is poorly understood. To address this, we developed and implemented an ambulatory assessment protocol consisting of wearable activity monitors, brief surveys of affect, context, and perceived impairments, and ultra-brief performance-based measures of cognition. Newly diagnosed, ER/PR+, stage 0-III, female breast cancer patients, were recruited. Ambulatory assessments were conducted on smart phones and wearable activity monitors were used to monitor sleep and physical activity. Participants were asked to complete five 7-day measurement bursts (one before starting ET and one each month for 4 consecutive months while on ET). We observed a consent rate of 36%, 27 women completed the study. Of the women that withdrew, 91% dropped prior to the midpoint of follow up. There were no significant differences in demographics, clinical breast cancer characteristics, sleep or physical activity patterns, or measures of cognition between women who completed versus withdrew. Women who did not complete the study provided fewer valid days of baseline data. In conclusion, while some women may be overwhelmed with their cancer diagnosis, we did not identify any predictive characteristics of women whom did not complete the study. This novel method enables the prospective study of psychological changes associated with cancer treatment, capturing a wide array of information about behavior, experience, and cognition, thus providing a picture of the lived experiences of cancer patients before and during exposure to ET., (© 2024. The Author(s).)

The oral cavity is the portal of entry for many microorganisms that affect swine, and the swine oral fluid has been used as a specimen for the diagnosis of several infectious diseases. The oral microbiota has been shown to play important roles in humans, such as protection against non-indigenous bacteria. In swine, studies that have investigated the microbial composition of the oral cavity of pigs are scarce. This study aimed to characterize the oral fluid microbiota of weaned pigs from five commercial farms in Brazil and compare it to their respective fecal and environmental microbiotas. Bacterial compositions were determined by 16S rRNA gene sequencing and analyzed in R Studio. Oral fluid samples were significantly less diverse (alpha diversity) than pen floor and fecal samples (P < 0.01). Alpha diversity changed among farms in oral fluid and pen floor samples, but no differences were observed in fecal samples. Permutational ANOVA revealed that beta diversity was significantly different among sample types (P = 0.001) and farms (P = 0.001), with separation of sample types (feces, pen floor, and oral fluid) on the principal coordinates analysis. Most counts obtained from oral fluid samples were classified as Firmicutes (80.4%) and Proteobacteria (7.7%). The genera Streptococcus, members of the Pasteurellaceae family, and Veillonella were differentially abundant in oral fluid samples when compared to fecal samples, in which Streptococcus was identified as a core genus that was strongly correlated (SparCC) with other taxa. Firmicutes and Bacteroidota were the most relatively abundant phyla identified in fecal and pen floor samples, and Prevotella&#95;9 was the most classified genus. No differentially abundant taxa were identified when comparing fecal samples and pen floor samples. We concluded that under the conditions of our study, the oral fluid microbiota of weaned piglets is different (beta diversity) and less diverse (alpha diversity) than the fecal and environmental microbiotas. Several differentially abundant taxa were identified in the oral fluid samples, and some have been described as important colonizers of the oral cavity in human microbiome studies. Further understanding of the relationship between the oral fluid microbiota and swine is necessary and would create opportunities for the development of innovative solutions that target the microbiota to improve swine health and production., (© 2024. The Author(s).)