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Initially, we relied on the Elective Surgery Acuity Scale (ESAS), Department Chairs and an EO 109 surgical committee to determine which cases were appropriate to go to the operating room. [...]some aspects of the MeNTS scoring system are subjective. MeNTS 2019 Elective P-value Outpatient Surgeries Patients 32 1983 Median LOS (IQR) 3 days (1–3) 1 day (1-1) <0.001 Blood Transfusions (%) 0 (0%) 0 (0%) 1 30-day readmissions (%) 0 (0%) 0 (0%) 1 Mortality (%) 0 (0%) 0 (0%) 1 Inpatient Surgeries Patients 184 1898 Median LOS (IQR) 4 days (1–9) 3 days (2–6) 0.234 Blood Transfusions (%) 40 (22%) 225 (12%) <0.001 30-day readmissions (%) 20 (11%) 141 (7.4%) 0.110 Mortality (%) 3 (1.6%) 24 (1.3%) 0.727 Table 1 Comparison of outcomes from MeNTS cases operated on during the period of restricted surgery and elective surgeries from the same time period in 2019.

Hydroxychloroquine has been touted as a potential COVID-19 treatment. Tocilizumab, an inhibitor of IL-6, has also been proposed as a treatment of critically ill patients. In this retrospective observational cohort study drawn from electronic health records we sought to describe the association between mortality and hydroxychloroquine or tocilizumab therapy among hospitalized COVID-19 patients. Patients were hospitalized at a 13-hospital network spanning New Jersey USA between March 1, 2020 and April 22, 2020 with positive polymerase chain reaction results for SARS-CoV-2. Follow up was through May 5, 2020. Among 2512 hospitalized patients with COVID-19 there have been 547 deaths (22%), 1539 (61%) discharges and 426 (17%) remain hospitalized. 1914 (76%) received at least one dose of hydroxychloroquine and 1473 (59%) received hydroxychloroquine with azithromycin. After adjusting for imbalances via propensity modeling, compared to receiving neither drug, there were no significant differences in associated mortality for patients receiving any hydroxychloroquine during the hospitalization (HR, 0.99 [95% CI, 0.80-1.22]), hydroxychloroquine alone (HR, 1.02 [95% CI, 0.83-1.27]), or hydroxychloroquine with azithromycin (HR, 0.98 [95% CI, 0.75-1.28]). The 30-day unadjusted mortality for patients receiving hydroxychloroquine alone, azithromycin alone, the combination or neither drug was 25%, 20%, 18%, and 20%, respectively. Among 547 evaluable ICU patients, including 134 receiving tocilizumab in the ICU, an exploratory analysis found a trend towards an improved survival association with tocilizumab treatment (adjusted HR, 0.76 [95% CI, 0.57-1.00]), with 30 day unadjusted mortality with and without tocilizumab of 46% versus 56%. This observational cohort study suggests hydroxychloroquine, either alone or in combination with azithromycin, was not associated with a survival benefit among hospitalized COVID-19 patients. Tocilizumab demonstrated a trend association towards reduced mortality among ICU patients. Our findings are limited to hospitalized patients and must be interpreted with caution while awaiting results of randomized trials. Trial Registration: Clinicaltrials.gov Identifier: NCT04347993.

Background Traumatic injury in a growing geriatric population is associated with higher mortality and complication rates. Geriatric consultation (GC) is vital in reducing risk factors that contribute to adverse outcomes. This study aims to determine if receiving a GC had an impact on high-risk medication usage. Methods Patients eligible for a GC, age ≥ 65, and length of stay > two days, were identified via a chart review from July 2013 to July 2014 at a Level II trauma center. This population was divided into those with and without a GC. Data collected included demographics, injury severity, medications, delirium, mortality, and readmissions. High-risk medications were defined using the Beers Criteria. Statistical analysis involved using appropriate standard tests to compare groups, including multivariate logistic regression. Results Forty-nine of a total of 104 patients received a GC. Groups were comparable on injury severity score, co-morbidities, and high-risk medication use upon admissions. The GC group was 74% less likely to be discharged on high-risk medications than the non-GC group. Conclusion GC in elderly trauma patients reduces high-risk medication use upon discharge. Further studies are needed to explore how GC impacts readmission rates and mortality. A multidisciplinary trauma team, including a geriatrician, must exist to address the unique medical, psychological, functional, and social issues of a growing, aged trauma population.

Transvaginal ultrasound (TVUS) is pivotal for diagnosing reproductive pathologies in individuals assigned female at birth, often serving as the primary imaging method for gynecologic evaluation. Despite recent advancements in AI-driven segmentation, its application to gynecological ultrasound still needs further attention. Our study aims to bridge this gap by training and evaluating two state-of-the-art deep learning (DL) segmentation models on TVUS data. An experienced gynecological expert manually segmented the uterus in our TVUS dataset of 124 patients with adenomyosis, comprising still images (n = 122), video screenshots (n = 472), and 3D volume screenshots (n = 452). Two popular DL segmentation models, U-Net and nnU-Net, were trained on the entire dataset, and each imaging type was trained separately. Optimization for U-Net included varying batch size, image resolution, pre-processing, and augmentation. Model performance was measured using the Dice score (DSC). U-Net and nnU-Net had good mean segmentation performances on the TVUS uterus segmentation dataset (0.75 to 0.97 DSC). We observed that training on specific imaging types (still images, video screenshots, 3D volume screenshots) tended to yield better segmentation performance than training on the complete dataset for both models. Furthermore, nnU-Net outperformed the U-Net across all imaging types. Lastly, we report the best results using the U-Net model with limited pre-processing and augmentations. TVUS datasets are well-suited for DL-based segmentation. nnU-Net training was faster and yielded higher segmentation performance; thus, it is recommended over manual U-Net tuning. We also recommend creating TVUS datasets that include only one imaging type and are as clutter-free as possible. The nnU-Net strongly benefited from being trained on 3D volume screenshots in our dataset, likely due to their lack of clutter. Further validation is needed to confirm the robustness of these models on TVUS datasets. Our code is available on https://github.com/dilaratank/UtiSeg.

Enhanced warming of the Northern high latitudes has intensified thermokarst processes throughout the permafrost zone. Retrogressive thaw slumps (RTS), where thaw-driven erosion caused by ground ice melt creates terrain disturbances extending over tens of hectares, represent particularly dynamic thermokarst features. Biogeochemical transformation of the mobilized substrate may release CO 2 to the atmosphere and impact downstream ecosystems, yet its fate remains unclear. The Peel Plateau in northwestern Canada hosts some of the largest RTS features in the Arctic. Here, thick deposits of Pleistocene-aged glacial tills are overlain by a thinner layer of relatively organic-rich Holocene-aged permafrost that aggraded upward following deeper thaw and soil development during the early Holocene warm period. In this study, we characterize exposed soil layers and the mobilized material by analysing sediment properties and organic matter composition in active layer, Holocene and Pleistocene permafrost, recently thawed debris deposits and fresh deposits of slump outflow from four separate RTS features. We found that organic matter content, radiocarbon age and biomarker concentrations in debris and outflow deposits from all four sites were most similar to permafrost soils, with a lesser influence of the organic-rich active layer. Lipid biomarkers suggested a significant contribution of petrogenic carbon especially in Pleistocene permafrost. Active layer samples contained abundant intrinsically labile macromolecular components (polysaccharides, lignin markers, phenolic and N-containing compounds). All other samples were dominated by degraded organic constituents. Active layer soils, although heterogeneous, also had the highest median grain sizes, whereas debris and runoff deposits consisted of finer mineral grains and were generally more homogeneous, similar to permafrost. We thus infer that both organic matter degradation and hydrodynamic sorting during transport affect the mobilized material. Determining the relative magnitude of these two processes will be crucial to better assess the role of intensifying RTS activity in CO 2 release and ecosystem carbon fluxes.

We investigate the role of landslide dams, spatial changes in lithology, and rock uplift on faults in the formation of knickzones on bedrock rivers. We focus our analysis in the southwestern Annapurna Range of the central Nepalese Himalaya where detailed geologic maps, topographic data, field observations, and aerial photographs are available. We identified knickzones in our study area from normalized river steepness indices (ksn values) extracted from river longitudinal profiles derived from a 25 m digital elevation model we interpolated from digitized topographic map contours. We compared the location of these knickzones with (1) lithologic contacts and faults from a detailed geologic map of the Modi Khola valley and (2) inferred ancient landslide dam features mapped from field observations and aerial photographs. The steepest location on the Modi Khola occurs near the same latitude as the steepest reach on the Mardi Khola located directly to the east, potentially highlighting a major topographic transition across the Annapurna. However, we find that landslide dams once blocked the flow of the Modi Khola, and damming followed by incision after landslide breaching can explain the location of these knickzones without the need for active faulting near the Main Central thrust. We also conclude that (1) knickzones do not correlate with any spatial changes in lithology and (2) knickzones generated by rock uplift on unmapped faults cannot be ruled out. We emphasize that disentangling the processes responsible for knickzone formation remains challenging even when high‐resolution geologic and topographic data are available. Key Points Landslide dams explain river knickzones without the need for active faulting We observe no correlation between river knickzones and lithologic contacts Out‐of‐sequence thrust faulting near the MCT may not be necessary

Historical in situ sub-daily rainfall observations are essential for the understanding of short-duration rainfall extremes but records are typically not readily accessible and data are often subject to errors and inhomogeneities. Furthermore, these events are poorly quantified in projections of future climate change making adaptation to the risk of flash flooding problematic. Consequently, knowledge of the processes contributing to intense, short-duration rainfall is less complete compared with those on daily timescales. The INTENSE project is addressing this global challenge by undertaking a data collection initiative that is coupled with advances in high-resolution climate modelling to better understand key processes and likely future change. The project has so far acquired data from over 23 000 rain gauges for its global sub-daily rainfall dataset (GSDR) and has provided evidence of an intensification of hourly extremes over the US. Studies of these observations, combined with model simulations, will continue to advance our understanding of the role of local-scale thermodynamics and large-scale atmospheric circulation in the generation of these events and how these might change in the future.

PurposeTransvaginal ultrasound (TVUS) is pivotal for diagnosing reproductive pathologies in individuals assigned female at birth, often serving as the primary imaging method for gynecologic evaluation. Despite recent advancements in AI-driven segmentation, its application to gynecological ultrasound still needs further attention. Our study aims to bridge this gap by training and evaluating two state-of-the-art deep learning (DL) segmentation models on TVUS data.Materials and methodsAn experienced gynecological expert manually segmented the uterus in our TVUS dataset of 124 patients with adenomyosis, comprising still images (n = 122), video screenshots (n = 472), and 3D volume screenshots (n = 452). Two popular DL segmentation models, U-Net and nnU-Net, were trained on the entire dataset, and each imaging type was trained separately. Optimization for U-Net included varying batch size, image resolution, pre-processing, and augmentation. Model performance was measured using the Dice score (DSC).ResultsU-Net and nnU-Net had good mean segmentation performances on the TVUS uterus segmentation dataset (0.75 to 0.97 DSC). We observed that training on specific imaging types (still images, video screenshots, 3D volume screenshots) tended to yield better segmentation performance than training on the complete dataset for both models. Furthermore, nnU-Net outperformed the U-Net across all imaging types. Lastly, we report the best results using the U-Net model with limited pre-processing and augmentations.ConclusionsTVUS datasets are well-suited for DL-based segmentation. nnU-Net training was faster and yielded higher segmentation performance; thus, it is recommended over manual U-Net tuning. We also recommend creating TVUS datasets that include only one imaging type and are as clutter-free as possible. The nnU-Net strongly benefited from being trained on 3D volume screenshots in our dataset, likely due to their lack of clutter. Further validation is needed to confirm the robustness of these models on TVUS datasets. Our code is available on https://github.com/dilaratank/UtiSeg.

We investigated the role of Lef1, one of the four transcription factors that transmit Wnt signaling to the genome, in the regulation of bone mass. Microcomputed tomographic analysis of 13- and 17-week-old mice revealed significantly reduced trabecular bone mass in Lef1(+/-) females compared to littermate wild-type females. This was attributable to decreased osteoblast activity and bone formation as indicated by histomorphometric analysis of bone remodeling. In contrast to females, bone mass was unaffected by Lef1 haploinsufficiency in males. Similarly, females were substantially more responsive than males to haploinsufficiency in Gsk3beta, a negative regulator of the Wnt pathway, displaying in this case a high bone mass phenotype. Lef1 haploinsufficiency also led to low bone mass in males lacking functional androgen receptor (AR) (tfm mutants). The protective skeletal effect of AR against Wnt-related low bone mass is not necessarily a result of direct interaction between the AR and Wnt signaling pathways, because Lef1(+/-) female mice had normal bone mass at the age of 34 weeks. Thus, our results indicate an age- and gender-dependent role for Lef1 in regulating bone formation and bone mass in vivo. The resistance to Lef1 haploinsufficiency in males with active AR and in old females could be due to the reduced bone turnover in these mice.

Nickel (Ni) is a naturally occurring element with many industrial uses, including in stainless steel, electroplating, pigments, and ceramics. Consequently, Ni may enter the environment from anthropogenic sources, resulting in locally elevated concentrations in soils. However, Ni is a minor essential element, and, therefore, biota have established systems that maintain Ni homeostasis. This paper discusses the role of Ni as an essential element and reviews storage, uptake, and transport systems used to maintain homeostasis within terrestrial biota. The bioaccumulation and distribution of metals in these organisms are also addressed. In all cases, information on Ni essentiality is very limited compared to other essential metals. However, the available data indicate that Ni behaves in a similar manner to other metals. Therefore, inferences specific to Ni may be made from an understanding of metal homeostasis in general. Nevertheless, it is evident that tissue and organ Ni concentrations and requirements vary considerably within and between species, and metal accumulation in various tissues within a single organism differs as well. High rates of Ni deposition around smelters indicate that Ni in acidic soils may reach concentrations that are toxic to plants and soil decomposers. However, with the exception of hyperaccumulator plants, Ni does not biomagnify in the terrestrial food web, suggesting that toxicity to higher trophic levels is unlikely.