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Abstract Sea level rise (SLR) poses a significant threat to coastal regions worldwide, particularly affecting over 60 million people living below 10 m above sea level along the African coast. This study analyzes the spatio-temporal trends of sea level anomaly (SLA) and its components (thermosteric, halosteric and ocean mass) in the Eastern Tropical Atlantic Ocean (ETAO) from 1993 to 2022. The SLA trend for the ETAO, derived from satellite altimetry, is 3.52 ± 0.47 mm/year, similar to the global average of 3.56 ± 0.67 mm/year. Of the three upwelling regions, the Gulf of Guinea (GoG) shows the highest regional trend of 3.42 ± 0.12 mm/year. Using the ARMORD3D dataset, a positive thermosteric sea level trend of 0.88 ± 0.04 mm/year is observed, particularly in the equatorial and southern Atlantic regions. The steric component drives the interannual SLA variability, while the ocean mass component dominates the long-term trends, as confirmed by the GRACE and GRACE-FO missions for 2002–2022. For those two decades, the total SLR from altimetry amounts to 3.80 ± 0.8 mm/year, whilst the steric component is reduced to only 0.19 ± 0.05 mm/year, leaving a residual increase in the ETAO of 3.69 ± 0.5 mm/year. The independent mass change from GRACE amounts to 2.78 ± 0.6 mm/year for this region, which just closes the sea level budget within present uncertainty levels. Spatial analysis of the steric components indicates a warming along the equatorial African coast including the GoG and a freshening near Angola. Strong correlations with regional climate factors, particularly the Tropical South Atlantic Index, highlight the influence of persistent climate modes. These findings underscore the urgent need for mitigation and adaptation strategies to SLR in the ETAO, especially for densely populated coastal communities.

Abstract Inelastic dark matter with moderate splittings, O $$ \mathcal{O} $$ (few to 150) keV, can upscatter to an excited state in the Earth, with the excited state subsequently decaying, leaving a distinctive monoenergetic photon signal in large underground detectors. The photon signal can exhibit sidereal-daily modulation, providing excellent separation from backgrounds. Using a detailed numerical simulation, we examine this process as a search strategy for magnetic inelastic dark matter with the dark matter mass near the weak scale, where the upscatter to the excited state and decay proceed through the same magnetic dipole transition operator. At lower inelastic splittings, the scattering is dominated by moderate mass elements in the Earth with high spin, especially 27Al, while at larger splittings, 56Fe becomes the dominant target. We show that the proposed large volume gaseous detector CYGNUS will have excellent sensitivity to this signal. Xenon detectors also provide excellent sensitivity through the inelastic nuclear recoil signal, and if a future signal is seen, we show that the synergy among both types of detection can provide strong evidence for magnetic inelastic dark matter. In the course we have calculated nuclear response functions for elements relevant for scattering in the Earth, which are publicly available on GitHub .

Abstract RyR1 is an intracellular Ca2+ channel important in excitable cells such as neurons and muscle fibers. Ca2+ activates it at low concentrations and inhibits it at high concentrations. Mg2+ is the main physiological RyR1 inhibitor, an effect that is overridden upon activation. Despite the significance of Mg2+-mediated inhibition, the molecular-level mechanisms remain unclear. In this work we determined two cryo-EM structures of RyR1 with Mg2+ up to 2.8 Å resolution, identifying multiple Mg2+ binding sites. Mg2+ inhibits at the known Ca2+ activating site and we propose that the EF hand domain is an inhibitory divalent cation sensor. Both divalent cations bind to ATP within a crevice, contributing to the precise transmission of allosteric changes within the enormous channel protein. Notably, Mg2+ inhibits RyR1 by interacting with the gating helices as validated by molecular dynamics. This structural insight enhances our understanding of how Mg2+ inhibition is overcome during excitation.

Abstract Cyclone Gabrielle passed along the northern coast of Aotearoa New Zealand in February 2023, producing historic rainfall accumulations and impacts. Gabrielle was an ex‐tropical cyclone that stalled and re‐energised off the north coast, resembling descriptions of worst case scenarios for the northeast of the country. Here we report on a comparison of the actual forecast of the storm against forecasts under conditions representative of a climate without anthropogenic interference and of a climate +2.0°C warmer than pre‐industrial (about 1.0°C cooler and warmer than present respectively). We find that regional total rainfall accumulations from a Gabrielle‐like storm are about 10% higher because of the historical anthropogenic warming, and will increase by a larger amount under similar future warming. These differences are driven by a 20% (relative to a non‐anthropogenic world) to 30% (relative to a +2.0°C world) rise in peak rainfall rates, which in turn is mainly driven by a more temporally concentrated column‐integrated moisture flux. The forecast model generates the larger increase for the +2.0°C world through greater precipitation efficiency, reflecting the importance of unresolved precipitation processes in the climate change response of rainfall extremes.

Abstract We study confining dark sectors where the lightest hadrons are glueballs. Such models can provide viable dark matter candidates and appear in some neutral naturalness scenarios. In this work, we introduce a new phenomenological model of dark glueball hadronization inspired by the Lund string model. This enables us to make the most physically-motivated predictions for dark glueball phenomenology at the LHC to date. Our model approximately reproduces the expected thermal distribution of hadron species as an emergent consequence of hadronization dynamics. The ability to predict the production of glueball states heavier than the lightest species significantly expands the reach of long-lived glueball searches in MATHUSLA compared to previous simplified estimates. We also characterize regions of parameter space where emerging and/or semivisible jets could arise from pure-glue dark sectors, thereby providing new benchmark models that motivate searches for these signatures.

ABSTRACTPancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy that is refractory to immune checkpoint inhibitor therapy. However, intratumoral T-cell infiltration correlates with improved overall survival (OS). Herein, we characterized the diversity and antigen specificity of the PDAC T-cell receptor (TCR) repertoire to identify novel immune-relevant biomarkers. Demographic, clinical, and TCR-beta sequencing data were collated from 353 patients across three cohorts that underwent surgical resection for PDAC. TCR diversity was calculated using Shannon Wiener index, Inverse Simpson index, and “True entropy.” Patients were clustered by shared repertoire specificity. TCRs predictive of OS were identified and their associated transcriptional states were characterized by single-cell RNAseq. In multivariate Cox regression models controlling for relevant covariates, high intratumoral TCR diversity predicted OS across multiple cohorts. Conversely, in peripheral blood, high abundance of T-cells, but not high diversity, predicted OS. Clustering patients based on TCR specificity revealed a subset of TCRs that predicts OS. Interestingly, these TCR sequences were more likely to encode CD8+ effector memory and CD4+ T-regulatory (Tregs) T-cells, all with the capacity to recognize beta islet-derived autoantigens. As opposed to T-cell abundance, intratumoral TCR diversity was predictive of OS in multiple PDAC cohorts, and a subset of TCRs enriched in high-diversity patients independently correlated with OS. These findings emphasize the importance of evaluating peripheral and intratumoral TCR repertoires as distinct and relevant biomarkers in PDAC.

In the convolutional retinex approach to image lightness processing, an image is filtered by a centre/surround operator that is designed to mitigate the effects of shading (illumination gradients), which in turn compresses the dynamic range. Typically, the parameters that define the shape and extent of the filter are tuned to provide visually pleasing results, and a mapping function such as a logarithm is included for further image enhancement. In contrast, a statistical approach to convolutional retinex has recently been introduced, which is based upon known or estimated autocorrelation statistics of the image albedo and shading components. By introducing models for the autocorrelation matrices and solving a linear regression, the optimal filter is obtained in closed form. Unlike existing methods, the aim is simply to objectively mitigate shading, and so image enhancement components such as a logarithmic mapping function are not included. Here, the full mathematical details of the method are provided, along with implementation details. Significantly, it is shown that the shapes of the autocorrelation matrices directly impact the shape of the optimal filter. To investigate the performance of the method, we address the problem of shading removal from text documents. Further experiments on a challenging image dataset validate the method.

ABSTRACTChlamydiae are obligate intracellular bacterial pathogens that may cause genital pathology via induction of destructive host immune responses. Human-adapted Chlamydia trachomatis causes inflammatory disease in human hosts but is easily cleared in mice, and mouse-adapted Chlamydia muridarum establishes a productive and pathogenic infection in murine hosts. While numerous anti-chlamydial host resistance factors have been discovered in mice and humans alike, little is known about host factors promoting host fitness independent of host resistance. Here, we show that interferon-inducible immunity-related GTPase M (Irgm) proteins function as such host factors ameliorating infection-associated sequalae in the murine female genital tract, thus characterizing Irgm proteins as mediators of disease tolerance. Specifically, we demonstrate that mice deficient for all three murine Irgm paralogs (pan-Irgm−/−) are defective for cell-autonomous immunity to C. trachomatis, which correlates with an early and transient increase in bacterial burden and sustained hyperinflammation in vivo. In contrast, upon infection of pan-Irgm−/− mice with C. muridarum, bacterial burden is unaffected, yet genital inflammation and scarring pathology are nonetheless increased, demonstrating that Irgm proteins can promote host fitness without altering bacterial burden. Additionally, pan-Irgm−/− mice display increased granulomatous inflammation in genital Chlamydia infection, implicating Irgm proteins in the regulation of granuloma formation and maintenance. These findings demonstrate that Irgm proteins regulate pathogenic immune responses to Chlamydia infection in vivo, establishing an effective infection model to examine the immunoregulatory functions and mechanisms of Irgm proteins.IMPORTANCEIn response to genital Chlamydia infection, the immune system mounts a proinflammatory response to resist the pathogen, yet inflammation must be tightly controlled to avoid collateral damage and scarring to host genital tissue. Variation in the human IRGM gene is associated with susceptibility to autoinflammatory diseases but its role in ameliorating inflammatory diseases caused by infections is poorly defined. Here, we use mice deficient for all three murine Irgm paralogs to demonstrate that Irgm proteins not only provide host resistance to Chlamydia infections but also limit associated inflammation in the female genital tract. In particular, we find that murine Irgm expression prevents granulomatous inflammation, which parallels inflammatory diseases associated with variants in human IRGM. Our findings therefore establish genital Chlamydia infection as a useful model to study the roles for Irgm proteins in both promoting protective immunity and limiting pathogenic inflammation.

Abstract As the fields of optical microscopy, semiconductor technology and fundamental science increasingly aim for precision at or below the nanoscale, there is a burgeoning demand for sub-nanometric displacement and position sensing. We show that the speckle patterns produced by multiple reflections of light inside an integrating sphere provide an exceptionally sensitive probe of displacement. We use an integrating sphere split into two independent hemispheres, one of which is free to move in any given direction. The relative motion of the two hemispheres produces a change in the speckle pattern from which we can analytically infer the amplitude of the displacement. The method allows a noise floor of 5 pm/ $$\sqrt{\hbox {Hz}}$$ Hz ( $$\lambda /160,000$$ λ / 160 , 000 ) above 30 Hz in a facile implementation, which we use to measure oscillations of 17 pm amplitude ( $$\lambda /50,000$$ λ / 50 , 000 ) with a signal to noise ratio of 3.

Abstract Birefringent microspheres, trapped in vacuum and set into rotation by circularly polarised light, demonstrate remarkably stable translational motion. This is in marked contrast to isotropic particles in similar conditions. Here we demonstrate that this stability is obtained because the fast rotation of these birefringent spheres reduces the effect of azimuthal spin forces created by the inhomogeneous optical spin of circularly polarised light. At reduced pressures, the unique profile of these rotationally averaged, effective azimuthal forces results in the formation of nano-scale limit cycles. We demonstrate feedback cooling of these non-equilibrium oscillators, resulting in effective temperatures on the order of a milliKelvin. The principles we elaborate here can inform the design of high-stability rotors carrying enhanced centripetal loads or result in more efficient cooling schemes for autonomous limit cycle oscillations. Ultimately, this latter development could provide experimental access to non-equilibrium quantum effects within the mesoscopic regime.

Abstract Net photosynthetic CO2 assimilation rate (A n) decreases at leaf temperatures above a relatively mild optimum (T opt) in most higher plants. This decline is often attributed to reduced CO2 conductance, increased CO2 loss from photorespiration and respiration, reduced chloroplast electron transport rate (J), or deactivation of Ribulose-1,5-bisphosphate Carboxylase Oxygenase (Rubisco). However, it is unclear which of these factors can best predict species independent declines in A n at high temperature. We show that independent of species, and on a global scale, the observed decline in A n with rising temperatures can be effectively accounted for by Rubisco deactivation and declines in J. Our finding that A n declines with Rubisco deactivation and J supports a coordinated down-regulation of Rubisco and chloroplast electron transport rates to heat stress. We provide a model that, in the absence of CO2 supply limitations, can predict the response of photosynthesis to short-term increases in leaf temperature.

Background: Cardiovascular magnetic resonance (CMR) imaging is an important tool for evaluating the severity of aortic stenosis (AS), co-existing aortic disease, and concurrent myocardial abnormalities. Acquiring this additional information requires protocol adaptations and additional scanner time, but is not necessary for the majority of patients who do not have AS. We observed that the relative signal intensity of blood in the ascending aorta on a balanced steady state free precession (bSSFP) 3-chamber cine was often reduced in those with significant aortic stenosis. We investigated whether this effect could be quantified and used to predict AS severity in comparison to existing gold-standard measurements. Methods: Multi-centre, multi-vendor retrospective analysis of patients with AS undergoing CMR and transthoracic echocardiography (TTE). Blood signal intensity was measured in a ∼1 cm2 region of interest (ROI) in the aorta and left ventricle (LV) in the 3-chamber bSSFP cine. Because signal intensity varied across patients and scanner vendors, a ratio of the mean signal intensity in the aorta ROI to the LV ROI (Ao:LV) was used. This ratio was compared using Pearson correlations against TTE parameters of AS severity: aortic valve peak velocity, mean pressure gradient and the dimensionless index. The study also assessed whether field strength (1.5 T vs. 3 T) and patient characteristics (presence of bicuspid aortic valves (BAV), dilated aortic root and low flow states) altered this signal relationship. Results: 314 patients (median age 69 [IQR 57–77], 64% male) who had undergone both CMR and TTE were studied; 84 had severe AS, 78 had moderate AS, 66 had mild AS and 86 without AS were studied as a comparator group. The median time between CMR and TTE was 12 weeks (IQR 4–26). The Ao:LV ratio at 1.5 T strongly correlated with peak velocity (r = −0.796, p = 0.001), peak gradient (r = −0.772, p = 0.001) and dimensionless index (r = 0.743, p = 0.001). An Ao:LV ratio of

Background: Late gadolinium enhancement (LGE) of the myocardium has significant diagnostic and prognostic implications, with even small areas of enhancement being important. Distinguishing between definitely normal and definitely abnormal LGE images is usually straightforward, but diagnostic uncertainty arises when reporters are not sure whether the observed LGE is genuine or not. This uncertainty might be resolved by repetition (to remove artifact) or further acquisition of intersecting images, but this must take place before the scan finishes. Real-time quality assurance by humans is a complex task requiring training and experience, so being able to identify which images have an intermediate likelihood of LGE while the scan is ongoing, without the presence of an expert is of high value. This decision-support could prompt immediate image optimization or acquisition of supplementary images to confirm or refute the presence of genuine LGE. This could reduce ambiguity in reports. Methods: Short-axis, phase-sensitive inversion recovery late gadolinium images were extracted from our clinical cardiac magnetic resonance (CMR) database and shuffled. Two, independent, blinded experts scored each individual slice for “LGE likelihood” on a visual analog scale, from 0 (absolute certainty of no LGE) to 100 (absolute certainty of LGE), with 50 representing clinical equipoise. The scored images were split into two classes—either “high certainty” of whether LGE was present or not, or “low certainty.” The dataset was split into training, validation, and test sets (70:15:15). A deep learning binary classifier based on the EfficientNetV2 convolutional neural network architecture was trained to distinguish between these categories. Classifier performance on the test set was evaluated by calculating the accuracy, precision, recall, F1-score, and area under the receiver operating characteristics curve (ROC AUC). Performance was also evaluated on an external test set of images from a different center. Results: One thousand six hundred and forty-five images (from 272 patients) were labeled and split at the patient level into training (1151 images), validation (247 images), and test (247 images) sets for the deep learning binary classifier. Of these, 1208 images were “high certainty” (255 for LGE, 953 for no LGE), and 437 were “low certainty”. An external test comprising 247 images from 41 patients from another center was also employed. After 100 epochs, the performance on the internal test set was accuracy = 0.94, recall = 0.80, precision = 0.97, F1-score = 0.87, and ROC AUC = 0.94. The classifier also performed robustly on the external test set (accuracy = 0.91, recall = 0.73, precision = 0.93, F1-score = 0.82, and ROC AUC = 0.91). These results were benchmarked against a reference inter-expert accuracy of 0.86. Conclusion: Deep learning shows potential to automate quality control of late gadolinium imaging in CMR. The ability to identify short-axis images with intermediate LGE likelihood in real-time may serve as a useful decision-support tool. This approach has the potential to guide immediate further imaging while the patient is still in the scanner, thereby reducing the frequency of recalls and inconclusive reports due to diagnostic indecision.

Background: Accurate measurements from cardiovascular magnetic resonance (CMR) images require precise positioning of scan planes and elimination of motion artifacts from arrhythmia or breathing. Unidentified or incorrectly managed artifacts degrade image quality, invalidate clinical measurements, and decrease diagnostic confidence. Currently, radiographers must manually inspect each acquired image to confirm diagnostic quality and decide whether reacquisition or a change in sequences is warranted. We aimed to develop artificial intelligence (AI) to provide continuous quality scores across different quality domains, and from these, determine whether cines are clinically adequate, require replanning, or warrant a change in protocol. Methods: A three-dimensional convolutional neural network was trained to predict cine quality graded on a continuous scale by a level 3 CMR expert, focusing separately on planning and motion artifacts. It incorporated four distinct output heads for the assessment of image quality in terms of (a, b, c) 2-, 3- and 4-chamber misplanning, and (d) long- and short-axis arrhythmia/breathing artifact. Backpropagation was selectively performed across these heads based on the labels present for each cine. Each image in the testing set was reported by four level 3 CMR experts, providing a consensus on clinical adequacy. The AI's assessment of image quality and ability to identify images requiring replanning or sequence changes were evaluated with Spearman’s rho and the area under receiver operating characteristic curve (AUROC), respectively. Results: A total of 1940 cines across 1387 studies were included. On the test set of 383 cines, AI-judged image quality correlated strongly with expert judgment, with Spearman’s rho of 0.84, 0.84, 0.81, and 0.81 for 2-, 3- and 4-chamber planning quality and the extent of arrhythmia or breathing artifacts, respectively. The AI also showed high efficacy in flagging clinically inadequate cines (AUROC 0.88, 0.93, and 0.93 for identifying misplanning of 2-, 3- and 4-chamber cines, and 0.90 for identifying movement artifacts). Conclusion: AI can assess distinct domains of CMR cine quality and provide continuous quality scores that correlate closely with a consensus of experts. These ratings could be used to identify cases where reacquisition is warranted and guide corrective actions to optimize image quality, including replanning, prospective gating, or real-time imaging.

Reliable identification of high-value products such as whisky is vital due to rising issues of brand substitution and quality control in the industry. We have developed a novel framework that can perform whisky analysis directly from raw spectral data with no human intervention by integrating machine learning models with a portable Raman device. We demonstrate that machine learning models can achieve over 99% accuracy in brand or product identification across twenty-eight commercial samples. To demonstrate the flexibility of this approach, we utilized the same algorithms to quantify ethanol concentrations, as well as measuring methanol levels in spiked whisky samples. To demonstrate the potential use of these algorithms in a real-world environment we tested our algorithms on spectral measurements performed through the original whisky bottle. Through the bottle measurements are facilitated by a beam geometry hitherto not applied to whisky brand identification in conjunction with machine learning. Removing the need for decanting greatly enhances the practicality and commercial potential of this technique, enabling its use in detecting counterfeit or adulterated spirits and other high-value liquids. The techniques established in this paper aim to function as a rapid and non-destructive initial screening mechanism for detecting falsified and tampered spirits, complementing more comprehensive and stringent analytical methods.

Satellite observations have given us a clear idea of the changes in chlorophyll in the surface ocean on both a seasonal and interannual basis, but repeated observations at depth are much rarer. The permanently-stratified subtropical gyres in the Atlantic are highly oligotrophic, with most production centred on a deep chlorophyll maximum (DCM) just above the nitracline. This study explores the variations in this feature in the core of both gyres, considering both seasonal and interannual variations, and the linkages between changes at the surface and sub-surface. The in situ observations come from the Atlantic Meridional Transect (AMT), a long-running UK monitoring programme, and also from biogeochemical Argo floats. AMT provides measurements spanning more than 25 years directed through the centres of these gyres, but samples only 2 to 4 months per year and thus cannot resolve the seasonal variations, whereas the profiling floats give coverage throughout the year, but without the rigid spatial repeatability. These observational records are contrasted with representation of the centres of the gyres in two different biogeochemical models: MEDUSA and ERSEM, thus fulfilling one of AMT’s stated aims: the assessment of biogeochemical models. Whilst the four datasets show broadly the same seasonal patterns and that the DCM shallows when surface chlorophyll increases, the depth and peak concentration of the DCM differ among datasets. For most of the datasets the column-integrated chlorophyll for both gyres is around 19 mg m-2 (with the AMT fluorescence-derived values being much lower); however the MEDUSA model has a disparity between the northern and southern gyres that is not understood. Although the seasonal increase in surface chlorophyll is tied to a commensurate decrease in concentration at depth, on an interannual basis years with enhanced surface levels of chlorophyll correspond to increases at depth. Satellite-derived observations of surface chlorophyll concentration act as a good predictor of interannual changes in DCM depth for both gyres during their autumn season, but provide less skill in spring.

Carbon mineralization and storage in basaltic rock sequences is a developing technology but faces challenges with uptake and increases in scale. Northern Ireland (UK) is a useful analog for many parts of the world where thick basalt sequences could be used to aid in reaching carbon reduction and removal targets. Here I reanalyze and reinterpret available lithological, geochemical, and geophysical data to assess carbon storage potential. The physical and geochemical properties of the basalts are indistinguishable from those used for successful carbon sequestration in Iceland and Washington State (USA). Based on the thickness, composition, and potential permeability, I propose that this is a viable location for a series of small-volume stores (total volume ~9–12 MTCO2) suitable for capture at industrial point-sources or purpose-built CO2 “harvesting” facilities. The case for exploiting the CO2 storage potential in Northern Ireland is strengthened by (1) an increasingly urgent need to find socially and economically just decarbonization pathways needed to meet NI's targets, (2) increasing realization among policy experts that point-source CO2 capture and industrial decarbonization will be insufficient to meet those goals, due in part, to the size of the agricultural sector, and (3) the coincidence with plentiful renewable energy and geothermally-sourced industrial heat. These serendipitous relationships could be leveraged to develop CO2-“farms” where direct air capture operations are supplied by renewable energy (biomass and geothermal) and on-site geological storage. I envisage that these sites could be supplemented by CO2 from locally produced biomass as farmers are encouraged to transition away from raising livestock. Because CO2 can be captured directly from the atmosphere or via suitable biomass anywhere, NI's small size and position on the periphery of the UK and Europe need not be a disadvantage. Instead, NI's access to geological storage, renewable energy, and agricultural land may be a boon, and provide new opportunities to become a leader in carbon removal in basalt-covered regions.

Background & Aims: DNA methylation alterations may provide important insights into gene-environment interaction in cancer, aging, and complex diseases, such as inflammatory bowel disease (IBD). We aim first to determine whether the circulating DNA methylome in patients requiring surgery may predict Crohn’s disease (CD) recurrence following intestinal resection; and second to compare the circulating methylome seen in patients with established CD with that we had reported in a series of inception cohorts. Methods: TOPPIC was a placebo-controlled, randomized controlled trial of 6-mercaptopurine at 29 UK centers in patients with CD undergoing ileocolic resection between 2008 and 2012. Genomic DNA was extracted from whole blood samples from 229 of the 240 patients taken before intestinal surgery and analyzed using 450KHumanMethylation and Infinium Omni Express Exome arrays (Illumina, San Diego, CA). Coprimary objectives were to determine whether methylation alterations may predict clinical disease recurrence; and to assess whether the epigenetic alterations previously reported in newly diagnosed IBD were present in the patients with CD recruited into the TOPPIC study. Differential methylation and variance analysis was performed comparing patients with and without clinical evidence of recurrence. Secondary analyses included investigation of methylation associations with smoking, genotype (MeQTLs), and chronologic age. Validation of our previously published case-control observation of the methylome was performed using historical control data (CD, n = 123; Control, n = 198). Results: CD recurrence in patients following surgery is associated with 5 differentially methylated positions (Holm P < .05), including probes mapping to WHSC1 (P = 4.1 × 10-9, Holm P = .002) and EFNA3 (P = 4.9 × 10-8, Holm P = .02). Five differentially variable positions are demonstrated in the group of patients with evidence of disease recurrence including a probe mapping to MAD1L1 (P = 6.4 × 10-5). DNA methylation clock analyses demonstrated significant age acceleration in CD compared with control subjects (GrimAge + 2 years; 95% confidence interval, 1.2–2.7 years), with some evidence for accelerated aging in patients with CD with disease recurrence following surgery (GrimAge +1.04 years; 95% confidence interval, -0.04 to 2.22). Significant methylation differences between CD cases and control subjects were seen by comparing this cohort in conjunction with previously published control data, including validation of our previously described differentially methylated positions (RPS6KA2 P = 1.2 × 10-19, SBNO2 = 1.2 × 10-11) and regions (TXK [false discovery rate, P = 3.6 × 10-14], WRAP73 [false discovery rate, P = 1.9 × 10-9], VMP1 [false discovery rate, P = 1.7 × 10-7], and ITGB2 [false discovery rate, P = 1.4 × 10-7]). Conclusions: We demonstrate differential methylation and differentially variable methylation in patients developing clinical recurrence within 3 years of surgery. Moreover, we report replication of the CD-associated methylome, previously characterized only in adult and pediatric inception cohorts, in patients with medically refractory disease needing surgery.

Abstract In nearly every ecosystem, human predators (hunters and fishers) exploit animals at extraordinarily high rates, as well as target different age classes and phenotypes, compared to other apex predators. Demographically decoupled from prey populations and technologically advanced, humans now impose widespread and significant ecological and evolutionary change. In this paper, we investigate whether there is evidence that humans provide complementary services and whether ecosystem services of predators can be maintained by humans where wild predators are lost. Our objective is to contribute to two key ecological themes: the compatibility of human harvesting within ecosystems and management approaches in consideration of the intentional or unintentional loss of predators. We reviewed evidence for five key effects of predators: natural selection of prey, disease dynamics, landscape effects, carbon cycling and human well‐being. Without carefully designed management strategies, such changes can impose harm to ecosystems and their constituents, including humankind. Ultimately, we applied this information to consider management paradigms in which humans could better support the role of, and potentially behave more like, apex predators and discuss the challenges to such coexistence. Read the free Plain Language Summary for this article on the Journal blog.

CD8+ T cells drive anti-cancer immunity in response to antigen-presenting cells such as dendritic cells and subpopulations of monocytes and macrophages. While CD14+ classical monocytes modulate CD8+ T cell responses, the contributions of CD16+ nonclassical monocytes to this process remain unclear. Herein we explored the role of nonclassical monocytes in CD8+ T cell activation by utilizing E2-deficient (E2-/-) mice that lack nonclassical monocytes. During early metastatic seeding, modeled by B16F10-OVA cancer cells injected into E2-/- mice, we noted lower CD8+ effector memory and effector T cell frequencies within the lungs as well as in lung-draining mediastinal lymph nodes in the E2-/- mice. Analysis of the myeloid compartment revealed that these changes were associated with depletion of MHC-IIloLy6Clo nonclassical monocytes within these tissues, with little change in other monocyte or macrophage populations. Additionally, nonclassical monocytes preferentially trafficked to primary tumor sites in the lungs, rather than to the lung-draining lymph nodes, and did not cross-present antigen to CD8+ T cells. Examination of the lung microenvironment in E2-/- mice revealed reduced CCL21 expression in endothelial cells, which is chemokine involved in T cell trafficking. Our results highlight the previously unappreciated importance of nonclassical monocytes in shaping the tumor microenvironment via CCL21 production and CD8+ T cell recruitment.

Colour correction is the process of converting RAW RGB pixel values of digital cameras to a standard colour space such as CIE XYZ. A range of regression methods including linear, polynomial and root-polynomial least-squares have been deployed. However, in recent years, various neural network (NN) models have also started to appear in the literature as an alternative to classical methods. In the first part of this paper, a leading neural network approach is compared and contrasted with regression methods. We find that, although the neural network model supports improved colour correction compared with simple least-squares regression, it performs less well than the more advanced root-polynomial regression. Moreover, the relative improvement afforded by NNs, compared to linear least-squares, is diminished when the regression methods are adapted to minimise a perceptual colour error. Problematically, unlike linear and root-polynomial regressions, the NN approach is tied to a fixed exposure (and when exposure changes, the afforded colour correction can be quite poor). We explore two solutions that make NNs more exposure-invariant. First, we use data augmentation to train the NN for a range of typical exposures and second, we propose a new NN architecture which, by construction, is exposure-invariant. Finally, we look into how the performance of these algorithms is influenced when models are trained and tested on different datasets. As expected, the performance of all methods drops when tested with completely different datasets. However, we noticed that the regression methods still outperform the NNs in terms of colour correction, even though the relative performance of the regression methods does change based on the train and test datasets.

Abstract Introduction: Most students in MD-PhD programs take a leave of absence from medical school to complete PhD training, which promotes a natural loss of clinical skills and knowledge and could negatively impact a student’s long-term clinical knowledge. To address this concern, clinical refresher courses in the final year of PhD training have traditionally been used; however, effectiveness of such courses versus a longitudinal clinical course spanning all PhD training years is unclear. Methods: The University of Alabama at Birmingham MD-PhD Program implemented a comprehensive continuing clinical education (CCE) course spanning PhD training years that features three course components: (1) clinical skills; (2) clinical knowledge; and (3) specialty exposure activities. To evaluate course effectiveness, data from an anonymous student survey completed at the end of each semester were analyzed. Results: Five hundred and ninety-seven surveys were completed by MD-PhD students from fall 2014 to 2022. Survey responses indicated that the majority of students found the course helpful to: maintain clinical skills and knowledge (544/597, 91% and 559/597, 94%; respectively), gain exposure to clinical specialties (568/597, 95%), and prepare them for responsibilities during clinical clerkships. During semesters following lockdowns from the COVID-19 pandemic, there were significant drops in students’ perceived preparedness. Conclusions: Positive student survey feedback and improved preparedness to return to clinic after development of the course suggests the CCE course is a useful approach to maintain clinical knowledge during research training.

Abstract We used DNA barcoding to assess the diversity and distribution of New Zealand's groundwater amphipods and isopods (Crustacea) and to determine whether biodiversity and endemism within tectonically active New Zealand are similar to those of more tectonically stable continents. Sixty‐five wells were sampled in seven aquifers across four regions within the North and South islands of New Zealand, and resident invertebrates were morphologically identified and then assessed using sequencing of the mitochondrial DNA cytochrome c oxidase subunit one (COI) gene. Invertebrates were found in 54 wells. Of the 228 individual amphipods and isopods found in 36 of the wells, 154 individuals were successfully sequenced for COI (68% success rate) from 25 wells, with at least one well in each aquifer containing sequenced individuals. Of the 45 putative species identified using Barcode Index Numbers (BINs), 30 BINs (78% of all taxa and 83% of amphipods) were previously unrecorded. Substantial morphologically cryptic, species‐level diversity was revealed, particularly within the amphipod Family Paraleptamphopidae. Similarly, one isopod taxon morphologically identified as Cruregens fontanus was assigned to five well‐separated BINs based on COI sequences. Endemism appeared high, with all taxa regionally endemic; 87% of species were restricted to one aquifer and more than 50% restricted to one well. Non‐saturated species accumulation curves indicated that, while additional sampling may increase the range of some currently identified taxa, additional range‐restricted taxa are also likely to be discovered. Patterns of diversity and short‐range endemism were similar to those found elsewhere, including locations which are more tectonically stable. The predominance of local endemism within New Zealand's groundwater fauna suggests that land‐use activities and groundwater extraction require careful evaluation to minimize threats to groundwater biodiversity.

BackgroundCancer neoantigens are important targets of cancer immunotherapy and neoantigen vaccines are currently in development in pancreatic ductal adenocarcinoma (PDAC) and other cancer types. Immune regulatory mechanisms in pancreatic cancer may limit the efficacy of neoantigen vaccines. Targeting immune checkpoint signaling pathways in PDAC may improve the efficacy of neoantigen vaccines.MethodsWe used KPC4580P, an established model of PDAC, to test whether neoantigen vaccines can generate therapeutic efficacy against PDAC. We focused on two immunogenic neoantigens associated with genetic alterations in the CAR12 and CDK12 genes. We tested a neoantigen vaccine comprised of two 20-mer synthetic long peptides and poly IC, a Toll-like receptor (TLR) agonist. We investigated the ability of neoantigen vaccine alone, or in combination with PD-1 and TIGIT signaling blockade to impact tumor growth. We also assessed the impact of TIGIT signaling on T cell responses in human PDAC.ResultsNeoantigen vaccines induce neoantigen-specific T cell responses in tumor-bearing mice and slow KPC4580P tumor growth. However, KPC4580P tumors express high levels of PD-L1 and the TIGIT ligand, CD155. A subset of neoantigen-specific T cells in KPC4580P tumors are dysfunctional, and express high levels of TIGIT. PD-1 and TIGIT signaling blockade in vivo reverses T cell dysfunction and enhances neoantigen vaccine-induced T cell responses and tumor regression. In human translational studies, TIGIT signaling blockade in vitro enhances neoantigen-specific T cell function following vaccination.ConclusionsTaken together, preclinical and human translational studies support testing neoantigen vaccines in combination with therapies targeting the PD-1 and TIGIT signaling pathways in patients with PDAC.

Abstract High prevalence of non-healing chronic wounds contributes to a huge healthcare burden across the world. Early treatment interventions for non-healing wounds are vital. It was previously shown that accumulation of 15% or more of senescent cells in a chronic wound edge is an indicator that the wound is unlikely to heal. However, determining the presence of senescent cells would require invasive procedures such as tissue biopsies to be taken. In this study, we found a strong correlation between decreased collagen area and presence of senescent cells in human chronic wounds i.e. venous leg ulcer (VLU), diabetic foot ulcer (DFU) and pressure ulcer (PRU). We also report that the lowest collagen levels were found in VLU patients less than 60 years of age, with a persistent wound of > 24 months. Elevated levels of senescent cells were also found in VLU of males. Second harmonic imaging of collagen at the edge of chronic wounds with a handheld multiphoton device could be used to predict the number of senescent cells, indicating if the wound is on a healing trajectory or not. Our data support the use of collagen imaging in cutaneous wound assessment for a faster and non-invasive method to predict cellular senescence and determining wound trajectory of healing.

Abstract Background Artificial intelligence (AI) technologies are increasingly used in clinical practice. Although there is robust evidence that AI innovations can improve patient care, reduce clinicians’ workload and increase efficiency, their impact on medical training and education remains unclear. Methods A survey of trainee doctors’ perceived impact of AI technologies on clinical training and education was conducted at UK NHS postgraduate centers in London between October and December 2020. Impact assessment mirrored domains in training curricula such as ‘clinical judgement’, ‘practical skills’ and ‘research and quality improvement skills’. Significance between Likert-type data was analysed using Fisher’s exact test. Response variations between clinical specialities were analysed using k-modes clustering. Free-text responses were analysed by thematic analysis. Results Two hundred ten doctors responded to the survey (response rate 72%). The majority (58%) perceived an overall positive impact of AI technologies on their training and education. Respondents agreed that AI would reduce clinical workload (62%) and improve research and audit training (68%). Trainees were skeptical that it would improve clinical judgement (46% agree, p = 0.12) and practical skills training (32% agree, p

Calpain-3 (CAPN3) is a muscle-specific member of the calpain family of Ca2+-dependent proteases. It has been reported that CAPN3 can also be autolytically activated by Na+ ions in the absence of Ca2+, although this was only shown under non-physiological ionic conditions. Here we confirm that CAPN3 does undergo autolysis in the presence of high [Na+], but this only occurred if all K+ normally present in a muscle cell was absent, and it did not occur even in 36 mM Na+, higher than what would ever be reached in exercising muscle if normal [K+] was present. CAPN3 in human muscle homogenates was autolytically activated by Ca2+, with ~50% CAPN3 autolysing in 60 min in the presence of 2 µM Ca2+. In comparison, autolytic activation of CAPN1 required about 5-fold higher [Ca2+] in the same conditions and tissue. After it was autolysed, CAPN3 unbound from its tight binding on titin and became diffusible, but only if the autolysis led to complete removal of the IS1 inhibitory peptide within CAPN3, reducing the C-terminal fragment to 55 kDa. Contrary to a previous report, activation of CAPN3, either by raised [Ca2+] or Na+ treatment, did not cause proteolysis of the skeletal muscle Ca2+ release channel-ryanodine receptor, RyR1, in physiological ionic conditions. Treatment of human muscle homogenates with high [Ca2+] caused autolytic activation of CAPN1, accompanied by proteolysis of some titin and complete proteolysis of junctophilin (JP1, full length ~95 kDa), generating an equimolar amount of a diffusible ~75 kDa N-terminal JP1 fragment, but without any proteolysis of RyR1.

Abstract Aims Despite medical therapy for heart failure (HF) having proven benefits of improving quality of life and survival, many patients remain under‐treated. This may be due to a combination of under‐prescription by medical professionals and poor adherence from patients. In HF, as with many other chronic diseases, adherence to medication can deteriorate over time particularly when symptoms are well controlled. Therefore, detecting and addressing non‐adherence has a crucial role in the management of HF. Significant flaws and inaccuracies exist in the methods currently used to assess adherence such as patient reporting, pill counts, and pharmacy fill records. We aim to use high‐performance liquid chromatography–tandem mass spectrometry (HPLC‐MS) to detect metabolites of HF medications in the urine samples of chronic HF patients. Methods and results Urine samples were collected from 35 patients in a specialist HF clinic. Patients were included if they had an ejection fraction

Abstract By interacting with the mRNA 5′ cap, the translation initiation factor eIF4E plays a critical role in selecting mRNAs for protein synthesis in eukaryotic cells. Caf20 is a member of the family of proteins found across eukaryotes termed 4E-BPs, which compete with eIF4G for interaction with eIF4E. Caf20 independently interacts with ribosomes. Thus, Caf20 modulates the mRNA selection process via poorly understood mechanisms. Here we performed unbiased mutagenesis across Caf20 to characterise which regions of Caf20 are important for interaction with eIF4E and with ribosomes. Caf20 binding to eIF4E is entirely dependent on a canonical motif shared with other 4E-BPs. However, binding to ribosomes is weakened by mutations throughout the protein, suggesting an extended binding interface that partially overlaps with the eIF4E-interaction region. By using chemical crosslinking, we identify a potential ribosome interaction region on the ribosome surface that spans both small and large subunits and is close to a known interaction site of eIF3. The function of ribosome binding by Caf20 remains unclear.

Reprocessed data from satellite altimetry show that the mean significant wave height decreases globally by 22% on average from 30 km to 3 km from the coast. By combining these data with wave period from reanalysis, we estimate a mean reduction of 38% concerning the mean wave energy flux.

Abstract Many government organizations use recovery planning to synthesize threats, propose management strategies, and determine recovery criteria for threatened wildlife. Little is known about the extent to which physiological knowledge has been used in recovery planning, despite its potential to offer key biological information that could aid in recovery success. Using recovery strategies for at‐risk animal species in Canada as a case study, we analyzed the prevalence, purpose, and type of physiological knowledge being used in recovery planning. We found that 73% of strategies contained mention of physiology and that incorporation of physiology has increased since 2006. Of the various types of physiological tools available, reference to stress, immune, thermal, and bioenergetic metrics appeared most frequently. Physiological information was more likely to be found in the background and threat assessment sections compared to action and future research sections, and less likely to be included in strategies for arthropods and birds compared to other taxonomic groups. By synthesizing our results with previous studies, we provide recommendations to encourage the application of physiological tools in recovery planning worldwide, such as increased incorporation of physiology in ongoing threat monitoring, critical habitat assessments, monitoring the success of recovery actions, and modeling responses to future environmental changes.

eIF5A is critical for protein synthesis but has not yet been associated with congenital human disease. Here, the authors show that EIF5A variants cause a Mendelian disorder via reduced eIF5A-ribosome interactions and this phenotype is partially corrected by spermidine supplementation in yeast and zebrafish.

Human ageing is accompanied by poor responses to infection and decreased vaccine efficacy. While the causes of this can be attributed to defects in the immune system that increase with age, it is unknown whether mitochondrial dysfunction may also contribute to these phenomena. This study aims to assess mitochondrial dysfunction in CD4+ terminal effector memory T cells re-expressing CD45RA (TEMRA) cells and other CD4+ memory T cell subtypes, which are increased in number in the elderly population, with respect to how their metabolic responses to stimulation are altered compared to CD4+ naïve T cells. In this study, we show that CD4+ TEMRA cells exhibit altered mitochondrial dynamics compared to CD4+ naïve cells and CD4+ central and effector memory cells, with a 25% reduction in OPA1 expression. CD4+ TEMRA and memory cells show increased upregulation of Glucose transporter 1 following stimulation and higher levels of mitochondrial mass compared to CD4+ naïve T cells. Additionally, TEMRA cells exhibit a decrease in mitochondrial membrane potential compared to other CD4+ memory cell subsets by up to 50%. By comparing young to aged individuals, more significant mitochondria mass and lower membrane potential were observed in CD4+ TEMRA of young individuals. In conclusion, we suggest that CD4+ TEMRA cells may be impaired with respect to their metabolic response to stimulation, possibly contributing to impaired responses to infection and vaccination.

Recently, many deep neural networks (DNN) have been proposed to solve the spectral reconstruction (SR) problem: recovering spectra from RGB measurements. Most DNNs seek to learn the relationship between an RGB viewed in a given spatial context and its corresponding spectra. Significantly, it is argued that the same RGB can map to different spectra depending on the context with respect to which it is seen and, more generally, that accounting for spatial context leads to improved SR. However, as it stands, DNN performance is only slightly better than the much simpler pixel-based methods where spatial context is not used. In this paper, we present a new pixel-based algorithm called A++ (an extension of the A+ sparse coding algorithm). In A+, RGBs are clustered, and within each cluster, a designated linear SR map is trained to recover spectra. In A++, we cluster the spectra instead in an attempt to ensure neighboring spectra (i.e., spectra in the same cluster) are recovered by the same SR map. A polynomial regression framework is developed to estimate the spectral neighborhoods given only the RGB values in testing, which in turn determines which mapping should be used to map each testing RGB to its reconstructed spectrum. Compared to the leading DNNs, not only does A++ deliver the best results, it is parameterized by orders of magnitude fewer parameters and has a significantly faster implementation. Moreover, in contradistinction to some DNN methods, A++ uses pixel-based processing, which is robust to image manipulations that alter the spatial context (e.g., blurring and rotations). Our demonstration on the scene relighting application also shows that, while SR methods, in general, provide more accurate relighting results compared to the traditional diagonal matrix correction, A++ provides superior color accuracy and robustness compared to the top DNN methods.

Abstract Aims Patients with cardiovascular disease appear particularly susceptible to severe COVID‐19 disease, but the impact of COVID‐19 infection on patients with heart failure (HF) is not known. This study aimed to quantify the impact of COVID‐19 infection on mortality in hospitalized patients known to have HF. Methods and results We undertook a retrospective analysis of all patients admitted with a pre‐existing diagnosis of HF between 1 March and 6 May 2020 to our unit. We assessed the impact of concomitant COVID‐19 infection on in‐hospital mortality, incidence of acute kidney injury, and myocardial injury. One hundred and thirty‐four HF patients were hospitalized, 40 (29.9%) with concomitant COVID‐19 infection. Those with COVID‐19 infection had a significantly increased in‐hospital mortality {50.0% vs. 10.6%; relative risk [RR] 4.70 [95% confidence interval (CI) 2.42–9.12], P

Abstract Massive U(1) gauge theories featuring parametrically light vectors are suspected to belong in the Swampland of consistent EFTs that cannot be embedded into a theory of quantum gravity. We study four-dimensional, chiral U(1) gauge theories that appear anomalous over a range of energies up to the scale of anomaly-cancelling massive chiral fermions. We show that such theories must be UV-completed at a finite cutoff below which a radial mode must appear, and cannot be decoupled — a Stückelberg limit does not exist. When the infrared fermion spectrum contains a mixed U(1)-gravitational anomaly, this class of theories provides a toy model of a boundary into the Swampland, for sufficiently small values of the vector mass. In this context, we show that the limit of a parametrically light vector comes at the cost of a quantum gravity scale that lies parametrically below M P1, and our result provides field theoretic evidence for the existence of a Swampland of EFTs that is disconnected from the subset of theories compatible with a gravitational UV-completion. Moreover, when the low energy theory also contains a U(1)3 anomaly, the Weak Gravity Conjecture scale makes an appearance in the form of a quantum gravity cutoff for values of the gauge coupling above a certain critical size.

Background: To investigate the expansion force of current colonic stents and to match these to industry standards. Methods: Samples of all colonic stents were requested from manufactures world-wide. Expansion forces were tested with an RX650 compression tool (MSI, Flagstaff, AZ, USA). Measurements were averaged over three cycles of compression and expansion, independently performed at 37°C by specialist engineers of MSI. In parallel, a survey was undertaken on standards, and tests used by manufacturers in their production process. As a labbased study, Institutional Review Board approval was not required. Results: A literature search did not identify any industry standards for testing expansion force or a suggested range for this primary stent function. Median expansion force of all stents was 24.4 N, (35.1 N for braided, 20.7 N for knitted stents) with a vast range from 5.6–130.8 N. Covering braided stents in liquid silicone increased their median force 5.5-fold, separate membranes attached to knitted stents only had a minor effect on expansion force. Five of eight manufacturers replied, describing three different test methods with three different units for expansion force. Conclusion: There are no standards on assessing expansion force, or what the ideal range should be. Consequently, the variation is remarkable, but values are not published, and even if they were, they could not be compared. Consequently, interventionists are unable to discriminate between different stents and to select the most suitable device for their patients, and no recommendation can be made on the ‘best stent’. The industry needs an agreed test standard and an acceptable range of stent forces.

Alzheimer’s disease (AD), characterized by memory loss and cognitive decline, is one of the diseases with the highest attrition rate in drug development. As with other neurodegenerative diseases, AD manifests on several scales (molecular, cellular and organismal), resulting in an organismal phenotype that is difficult to replicate and exploit for screening in vitro. Development of high-throughput drug screening platforms using invertebrate organisms may therefore facilitate drug discovery in AD, at least for compounds that target mechanisms that can be modelled in invertebrates, such as metabolic defects and mitochondrial toxicity. Here we present a potentially high-throughput screening platform against AD in Caenorhabditis elegans (C. elegans). The system is based on our transgenic AD model strain (GRU102) that expresses a pathogenic human amyloid-beta peptide (Aβ1-42) specifically in neurons and we use this approach to identify Metformin, Lithium and Curcumin as potential “hits”. We find that the ability to rescue the swim-exhaustion phenotype correlates well with lifespan and healthspan improvements in GRU102. Importantly, several other drugs, such as Thioflavin T that have been reported previously to extend lifespan, modify aspects of ageing or for which protective effects in AD model might be suspected did not rescue the swim performance nor lifespan of GRU102. This illustrates the predictive value of the screening assay and confirms that not all compounds targeting ageing are capable of compensating for the toxic effects of Aβ1-42 in GRU102. Together, these findings demonstrate the utility of our screen towards the Aβ-induced defects in GRU102.

Mild cognitive impairment (MCI) or dementia often leads to behavioral and psychiatric symptoms of dementia (BPSD). Sensory processing abnormalities may be associated with BPSD. The purpose of this study was to explore relationships among sensory processing, behavior, and environmental features within the homes of people with MCI or dementia. This project used mixed methods to assess participants’ sensory processing, care partner perspectives on behaviors, and in situ observations of the home environment. Nine participants with cognitive impairment (MCI n = 8, early dementia = 1) and their care partners were included. Seven participants with cognitive impairment were reported to have abnormal sensory processing. Findings suggest that unique environmental adaptations, tailored to personal and sensory preferences for each participant, were associated with a decreased level of behavioral disruption during the observation periods. Implementing sensory-based approaches to maximize environment adaptation may be beneficial in reducing disruptive behaviors for adults with cognitive impairment.

Human NK cells are comprised of phenotypic subsets, whose potentially unique functions remain largely unexplored. C-X-C-motif-chemokine-receptor-6 (CXCR6)+ NK cells have been identified as phenotypically immature tissue-resident NK cells in mice and humans. A small fraction of peripheral blood (PB)-NK cells also expresses CXCR6. However, prior reports about their phenotypic and functional plasticity are conflicting. In this study, we isolated, expanded, and phenotypically and functionally evaluated CXCR6+ and CXCR6– PB-NK cells, and contrasted results to bulk liver and spleen NK cells. We found that CXCR6+ and CXCR6– PB-NK cells preserved their distinct phenotypic profiles throughout 14 days of in vitro expansion (“day 14”), after which phenotypically immature CXCR6+ PB-NK cells became functionally equivalent to CXCR6– PB-NK cells. Despite a consistent reduction in CD16 expression and enhanced expression of the transcription factor Eomesodermin (Eomes), day 14 CXCR6+ PB-NK cells had superior antibody-dependent cellular cytotoxicity (ADCC) compared to CXCR6– PB-NK cells. Further, bulk liver NK cells responded to IL-15, but not IL-2 stimulation, with STAT-5 phosphorylation. In contrast, bulk splenic and PB-NK cells robustly responded to both cytokines. Our findings may allow for the selection of superior NK cell subsets for infusion products increasingly used to treat human diseases.

The genus Ebolavirus contains multiple species of viruses that are highly contagious and lethal, often causing severe hemorrhagic fever. To minimize the global threat from Ebola virus disease (EVD), sustainable, field-appropriate tools are needed to quickly screen and triage symptomatic patients and conduct rapid screening of cadavers to ensure proper handling of human remains. The OraQuick® Ebola Rapid Antigen Test is an in vitro diagnostic single-use immunoassay for the qualitative detection of Ebola virus antigens that detects all known species within the genus Ebolavirus. Here, we report the performance of the OraQuick® Ebola Rapid Antigen Test and provide a comparison of its performance with other rapid diagnostic tests (RDTs) for EVD. OraQuick® Ebola demonstrated clinical sensitivity of 84.0% in archived EVD patient venous whole-blood (WB) samples, 90.9% in Ebola virus-infected monkey fingerstick samples, and 97.1% in EVD patient cadaver buccal swabs, as well as clinical specificity of 98.0–100% in venous WB samples and 99.1–100% in contrived saliva samples. It is the only 510(k)-cleared Ebola rapid test, has analytical sensitivity as good as or better than all RDT comparators for EVD, and can detect the Sudan virus. Our data demonstrate that the OraQuick® Ebola Rapid Antigen Test is a sensitive and specific assay that can be used for rapid detection of EBOV in humans and could support efforts for EVD-specific interventions and control over outbreaks.

Background: Acute myocardial damage is common in severe COVID-19. Post-mortem studies have implicated microvascular thrombosis, with cardiovascular magnetic resonance (CMR) demonstrating a high prevalence of myocardial infarction and myocarditis-like scar. The microcirculatory sequelae are incompletely characterized. Perfusion CMR can quantify the stress myocardial blood flow (MBF) and identify its association with infarction and myocarditis.Objectives: To determine the impact of the severe hospitalized COVID-19 on global and regional myocardial perfusion in recovered patients.Methods: A case-control study of previously hospitalized, troponin-positive COVID-19 patients was undertaken. The results were compared with a propensity-matched, pre-COVID chest pain cohort (referred for clinical CMR; angiography subsequently demonstrating unobstructed coronary arteries) and 27 healthy volunteers (HV). The analysis used visual assessment for the regional perfusion defects and AI-based segmentation to derive the global and regional stress and rest MBF.Results: Ninety recovered post-COVID patients {median age 64 [interquartile range (IQR) 54–71] years, 83% male, 44% requiring the intensive care unit (ICU)} underwent adenosine-stress perfusion CMR at a median of 61 (IQR 29–146) days post-discharge. The mean left ventricular ejection fraction (LVEF) was 67 ± 10%; 10 (11%) with impaired LVEF. Fifty patients (56%) had late gadolinium enhancement (LGE); 15 (17%) had infarct-pattern, 31 (34%) had non-ischemic, and 4 (4.4%) had mixed pattern LGE. Thirty-two patients (36%) had adenosine-induced regional perfusion defects, 26 out of 32 with at least one segment without prior infarction. The global stress MBF in post-COVID patients was similar to the age-, sex- and co-morbidities of the matched controls (2.53 ± 0.77 vs. 2.52 ± 0.79 ml/g/min, p = 0.10), though lower than HV (3.00 ± 0.76 ml/g/min, p< 0.01).Conclusions: After severe hospitalized COVID-19 infection, patients who attended clinical ischemia testing had little evidence of significant microvascular disease at 2 months post-discharge. The high prevalence of regional inducible ischemia and/or infarction (nearly 40%) may suggest that occult coronary disease is an important putative mechanism for troponin elevation in this cohort. This should be considered hypothesis-generating for future studies which combine ischemia and anatomical assessment.

Summary: eIF2B is the guanine nucleotide exchange factor (GEF) required for cytoplasmic protein synthesis initiation in eukaryotes and its regulation within the integrated stress response (ISR). It activates its partner factor eIF2, thereby promoting translation initiation. Here we provide evidence through biochemical and genetic approaches that eIF2B can bind directly to GTP and this can enhance its rate of GEF activity toward eIF2–GDP in vitro. GTP binds to a subcomplex of the eIF2Bγ and ε subunits. The eIF2Bγ amino-terminal domain shares structural homology with hexose sugar phosphate pyrophosphorylase enzymes that bind specific nucleotides. A K66R mutation in eIF2Bγ is especially sensitive to guanine or GTP in a range of functional assays. Taken together, our data suggest eIF2Bγ may act as a sensor of purine nucleotide availability and thus modulate eIF2B activity and protein synthesis in response to fluctuations in cellular nucleotide levels.

Enhancer of Zeste Homolog 2 (EZH2) inhibitors (EZH2i) are approved to treat certain cancer types. Previous studies have suggested the potential to combine EZH2i with immune checkpoint blockade targeting coinhibitory receptors like PD-(L)1 and CTLA-4, but whether it can also enhance the activity of agents targeting costimulatory receptors is not known. Here, we explore the combination between EZH2i and an agonist antibody targeting the T cell costimulatory receptor 4-1BB (α4-1BB). Our data show that EZH2i compromise the efficacy of α4-1BB in both CT26 colon carcinoma and in an in vivo protein immunization model. We link this to reduced effector survival and increased BIM expression in CD8+ T cells upon EZH2i treatment. These data support the requirement of EZH2 function in 4-1BB-mediated CD8+ T cell expansion and effector programming and emphasize the consideration that must be given when combining such antitumoral therapies.

The SH-SY5Y neuroblastoma cells are a widely used in vitro model approximating neurons for testing the target engagement of therapeutics designed for neurodegenerative diseases and pain disorders. However, their potential as a model for receptor-mediated delivery and uptake of novel modalities, such as antibody-drug conjugates, remains understudied. Investigation of the SH-SY5Y cell surfaceome will aid in greater in vitro to in vivo correlation of delivery and uptake, thereby accelerating drug discovery. So far, the majority of studies have focused on total cell proteomics from undifferentiated and differentiated SH-SY5Y cells. While some studies have investigated the expression of specific proteins in neuroblastoma tissue, a global approach for comparison of neuroblastoma cell surfaceome to the brain and dorsal root ganglion (DRG) neurons remains uninvestigated. Furthermore, an isoform-specific evaluation of cell surface proteins expressed on neuroblastoma cells remains unexplored. In this study, we define a bioinformatic workflow for the identification of high-confidence surface proteins expressed on brain and DRG neurons using tissue proteomic and transcriptomic data. We then delineate the SH-SY5Y cell surfaceome by surface proteomics and show that it significantly overlaps with the human brain and DRG neuronal surface proteome. We find that, for 32% of common surface proteins, SH-SY5Y-specific major isoforms are alternatively spliced, maintaining their protein-coding ability, and are predicted to localize to the cell surface. Validation of these isoforms using surface proteomics confirms a SH-SY5Y-specific alternative NRCAM (neuron-glia related cell adhesion molecule) isoform, which is absent in typical brain neurons, but present in neuroblastomas, making it a receptor of interest for neuroblastoma-specific therapeutics.

A paradigm shift in the understanding of the exhausted CD8+ T cell (Tex) lineage is underway. Originally thought to be a uniform population that progressively loses effector function in response to persistent antigen, single-cell analysis has now revealed that CD8+ Tex is composed of multiple interconnected subpopulations. The heterogeneity within the CD8+ Tex lineage is comprised of immune checkpoint blockade (ICB) permissive and refractory subsets termed stem-like and terminally differentiated cells, respectively. These populations occupy distinct peripheral and intratumoral niches and are characterized by transcriptional processes that govern transitions between cell states. This review presents key findings in the field to construct an updated view of the spatial, transcriptional, and functional heterogeneity of anti-tumoral CD8+ Tex. These emerging insights broadly call for (re-)focusing cancer immunotherapies to center on the driver mechanism(s) underlying the CD8+ Tex developmental continuum aimed at stabilizing functional subsets.