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Background:The scale of the 2022 global mpox (formerly known as monkeypox) outbreak has been unprecedented. In less than 6 months, non-endemic countries have reported more than 67 000 cases of a disease that had previously been rare outside of Africa. Mortality has been reported as rare but hospital admission has been relatively common. We aimed to describe the clinical and laboratory characteristics and outcomes of individuals admitted to hospital with mpox and associated complications, including tecovirimat recipients. Methods:In this cohort study, we undertook retrospective review of electronic clinical records and pathology data for all individuals admitted between May 6, and Aug 3, 2022, to 16 hospitals from the Specialist and High Consequence Infectious Diseases Network for Monkeypox. The hospitals were located in ten cities in England and Northern Ireland. Inclusion criteria were clinical signs consistent with mpox and MPXV DNA detected from at least one clinical sample by PCR testing. Patients admitted solely for isolation purposes were excluded from the study. Key outcomes included admission indication, complications (including pain, secondary infection, and mortality) and use of antibiotic and anti-viral treatments. Routine biochemistry, haematology, microbiology, and virology data were also collected. Outcomes were assessed in all patients with available data. Findings:156 individuals were admitted to hospital with complicated mpox during the study period. 153 (98%) were male and three (2%) were female, with a median age of 35 years (IQR 30–44). Gender data were collected from electronic patient records, which encompassed full formal review of clincian notes. The prespecified options for data collection for gender were male, female, trans, non-binary, or unknown. 105 (71%) of 148 participants with available ethnicity data were of White ethnicity and 47 (30%) of 155 were living with HIV with a median CD4 count of 510 cells per mm3(IQR 349–828). Rectal or perianal pain (including proctitis) was the most common indication for hospital admission (44 [28%] of 156). Severe pain was reported in 89 (57%) of 156, and secondary bacterial infection in 82 (58%) of 142 individuals with available data. Median admission duration was 5 days (IQR 2–9). Ten individuals required surgery and two cases of encephalitis were reported. 38 (24%) of the 156 individuals received tecovirimat with early cessation in four cases (two owing to hepatic transaminitis, one to rapid treatment response, and one to patient choice). No deaths occurred during the study period. Interpretation:Although life-threatening mpox appears rare in hospitalised populations during the current outbreak, severe mpox and associated complications can occur in immunocompetent individuals. Analgesia and management of superimposed bacterial infection are priorities for patients admitted to hospital.

Breast parenchymal patterns on radiologic images are associated with breast cancer risk. Radiomic features have been proposed as quantitative measures of parenchymal patterns. We defined intrinsic imaging phenotypes of breast parenchymal patterns based on radiomic features extracted from full field digital mammography (FFDM) in breast screening populations and assessed whether these phenotypes are associated with breast cancer risk and masking. We selected 30,000 women with 4-view FFDM exams from Hologic machines from three institutions (Hospital of the University of Pennsylvania, Mayo Clinic, and San Francisco Mammography Registry), randomly split into a training (20,000 women) and test set (10,000 women). In total, 390 radiomic features were automatically extracted from each image using a validated software pipeline, standardized, and adjusted for site differences using ComBat. We used two methods, hierarchical clustering and Principal Components (PCs) analysis, to classify significant variation among the features in the training set and replicate among the test set. Next, we applied the replicated clusters and PCs to an independent nested case-control set [1082 invasive breast cancer (BC) cases (of which 151 were Black and 893 White women, 38 other race) matched to 2837 controls (411 Black and 2345 White women, 81 other race) on age, race, timing of images, and site]. We examined associations of the clusters and PCs with invasive breast cancer risk, as well as masking [defined as a false-negative (FN) screen (124 cases and 319 matched controls) and additionally the subset with symptomatic interval cancer (IC) within 12 months of negative screen (88 cases and 223 matched controls)] using conditional logistic regression. We evaluated their association with breast cancer alone, and with adjustment for age, body mass index (BMI) and breast density assessed by Breast Imaging Reporting and Data System (BI-RADS) using likelihood ratio tests. We estimated discrimination using area under the curve (AUC) and compared AUCs for models that included the radiomic clusters and PCs with the model that included only age, BMI and density. We also stratified analyses by race (Black/White). From hierarchical clustering, we defined six statistically significant phenotype clusters (each of at least 1000 women) in the training set which were replicated in the test set. For PC Analysis, we identified six PCs in the training set, explaining 85% of the variation in texture features and reproduced these in the test set. The six radiomic phenotype clusters (P< 0.001) and six PCs (P< 0.001) were both associated with invasive BC, including after adjusting for age, BMI, and density (cluster P=0.004; PCs P< 0.001). Improvements in discrimination of invasive BC with inclusion of PCs or clusters were more pronounced among Black women (Table). Further, the PCs (P< 0.001) and clusters (P< 0.001) were significantly associated with FN overall and for symptomatic IC (PCs P< 0.001; clusters P=0.001), but only PCs remained significant after adjusting for age, BMI and density (PCs P=0.004 for FN; PCs P=0.007 for symptomatic IC). Discrimination of masking also improved with inclusion of both clusters and PCs (Table). We identified reproducible radiomic phenotypes that are associated with invasive BC risk, above and beyond breast density with the strongest associations for invasive BC among Black women and symptomatic interval cancers. Citation Format: Stacey Winham, Anne Marie McCarthy, Aimilia Gastounioti, Christopher Scott, Aaron Norman, Walter C. Mankowski, Lauren Pantalone, Matthew Jensen, Eric A. Cohen, Hannah Horng, Kathleen Brandt, Emily F. Conant, Karla Kerlikowske, Despina Kontos, Celine Vachon. Radiomic phenotypes of breast texture and association with breast cancer risk and masking [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr GS4-06.

INTRODUCTIONIt remains unclear to which extent vascular burden promotes neurodegeneration and cognitive dysfunction in a cohort spanning low-to-severe small vessel disease (SVD) and amyloid-beta pathology.METHODSIn 120 subjects, we investigated 1) whether vascular burden, quantified as total or lobar white matter hyperintensity (WMH) volumes, is associated with different cognitive domains; and 2) whether the total WMH effect on cognition is mediated by amyloid (18F-AV45-PET), glucose metabolism (18F-FDG-PET), and/or cortical atrophy.RESULTSIncreased total WMH volume was associated with poorer performance in all cognitive domains tested, with the strongest effects observed for semantic fluency. These relationships were mediated mainly through cortical atrophy, particularly in the temporal lobe, and to a lesser extent through amyloid and metabolism. WMH volumes differentially impacted cognition depending on lobar location and amyloid status.DISCUSSIONOur study suggests mainly an amyloid-independent pathway in which vascular burden affects cognitive impairment through temporal lobe atrophy.

Non-migrating tides are understood to be an important coupling mechanism through which lower atmospheric conditions influence the variability of the near-Earth space environment. Tidal variations have been exhaustively characterized in the mesosphere/lower thermosphere and the upper thermosphere, yet it is not quite known to what extent tides appear in the middle thermosphere due to a lack of global-scale systematic observations. This dissertation addresses the middle thermospheric "gap" of tidal observations. Using far ultraviolet (FUV) observations of the Earth, the recent NASA GOLD and ICON missions retrieve thermospheric parameters, the former from geostationary orbit (GEO) and the latter from low Earth orbit. Both missions infer the daytime column O/N2 ratio, while GOLD also retrieves the daytime thermospheric disk temperature. Traditional spectral tidal decomposition cannot be employed on GOLD data due its incomplete longitude/local solar time sampling. The known limitation introduced by ionospheric contamination of emissions at 135.6 nm and the dependence of the GOLD disk temperature on solar zenith angle both serve as additional obstacles. This dissertation proposes a pair of algorithms, based on the local time sum and difference approaches, that retrieves diurnal and semidiurnal tidal parameters for temperature and O/N2 in a single inversion, while constraining the tidal phase differences in temperature and O/N2 using a general circulation model. The first estimates of non-migrating tidal amplitudes and phases in middle thermospheric temperature and O/N2 using a geostationary observational platform are presented. Comparisons to physics-based and empirical models reveal that modeled amplitudes are generally weaker than the amplitudes retrieved from GOLD data, highlighting the need for better representation of tidal dynamics. In addition, this dissertation proposes a universal approach to systematically reduce the ionospheric contamination of O/N2 and thus determine the true thermospheric tidal variations. The approach considers biases between the remote sensing and ionospheric data sets, and due to its universality can be adapted for any retrieval of O/N2 from far ultraviolet emissions. The modified O/N2 shows a wavenumber-3 pattern indicative of the diurnal eastward propagating zonal wavenumber 2 tide (DE2), where it was not present in the original O/N2. This DE2 presence as well as the finding of DE3 and SE2 signatures in wavenumber-4 patterns is consistent with the theory that upward propagating tides influence the longitudinal structure of the thermospheric composition. Doctor of Philosophy A remarkable amount of variability in the upper atmosphere is not explained by the state-of-the-art description of the connected Sun-Earth system. Understanding the mechanisms of said variability is instrumental to achieving operational space weather forecasting, a capability that would alleviate the uncertainties faced by space activities such as GPS. Solar atmospheric tides have been studied as a coupling mechanism between terrestrial weather and space weather, and thus believed to be responsible for much of the variability not accounted for. These tides are periodic planetary-scale oscillations of the atmosphere, principally forced by the heating of the atmosphere by solar radiation. A subset of them, called non-migrating tides, do not track the motion of the Sun across the sky. Non-migrating tides in the upper atmosphere are forced in a myriad of ways, including but not limited to large-scale tropical weather systems and the interactions of the migrating tide with other waves. They are known to redistribute the charged particles of the ionosphere, thus influencing radio communications. This dissertation presents novel methods to studying non-migrating tides in a region of the upper atmosphere, the middle thermosphere (around 150 km altitude), where observations of them are sparse. A pair of methods was devised to overcome the limited sampling of temperature and composition from geostationary orbit, where a satellite appears fixed to a ground-based observer. Another method addresses a limitation that has afflicted prior investigations of non-migrating tides in neutral composition based on far ultraviolet observations. These methods use data collected by the NASA GOLD and ICON missions, modern space-based Earth observation missions that make crucial measurements of the middle thermosphere. The successful development of these methods paves the way for better understanding the nature of upper atmospheric variability introduced by tides. Comparison to models indicate that models generally underestimate the tidal amplitudes. Analysis of neutral composition variations is consistent with the theory that upward propagating tides influence the longitudinal structure of thermospheric composition.

Many hazards, including precipitation-induced landslides and coseismic liquefaction, are strongly influenced by the variability of groundwater levels. Simplified or coarse-resolution groundwater models are available for regional-scale studies of infrastructure networks; however, these models often do not consider spatial and temporal variations observed within wells and may not provide sufficient local resolution for critical hazard studies. We extend a conventional, physics-based groundwater model to include spatial and temporal variability based on Gaussian process (GP) interpolation to better understand the local and temporal variation of groundwater between well observations. In this probabilistic model, the physics-based groundwater elevation model serves as an ergodic function and the GP interpolation serves as a model of the well observation residuals. We demonstrate the applicability and accuracy of the model by developing phreatic groundwater estimates for an approximately 10,000 km2 area surrounding San Francisco Bay, California, USA. The resulting model accurately estimates the seasonally variable groundwater depth in a blind holdout dataset within 1.11 m with 90% confidence. The model is well constrained with a standard deviation of approximately 1.1 m near wells, but the uncertainty increases dramatically in mountainous terrain where well observations are limited. The model results also indicate that the average seasonal variability is typically modest relative to non-seasonal events, but nonetheless could have significant impacts on hazard evaluations such as earthquake-induced liquefaction or shallow slope instability.