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BACKGROUND: Reducing hospital readmission offer potential benefits for patients, providers, payers, and policymakers to improve quality of healthcare, reduce cost, and improve patient experience. We investigated effectiveness of remdesivir in reducing 30-day coronavirus disease 2019 (COVID-19)-related readmission during the Omicron era, including older adults and those with underlying immunocompromising conditions. METHODS: This retrospective study utilized the US PINC AI Healthcare Database to identify adult patients discharged alive from an index COVID-19 hospitalization between December 2021 and February 2024. Odds of 30-day COVID-19-related readmission to the same hospital were compared between patients who received remdesivir vs those who did not, after balancing characteristics of the two groups using inverse probability of treatment weighting (IPTW). Analyses were stratified by maximum supplemental oxygen requirement during index hospitalization. RESULTS: Of 326 033 patients hospitalized for COVID-19 during study period, 210 586 patients met the eligibility criteria. Of these, 109 551 (52%) patients were treated with remdesivir. After IPTW, lower odds of 30-day COVID-19-related readmission were observed in patients who received remdesivir vs those who did not, in the overall population (3.3% vs 4.2%, respectively; odds ratio [95% confidence interval {CI}]: 0.78 [.75-.80]), elderly population (3.7% vs 4.7%, respectively; 0.78 [.75-.81]), and those with underlying immunocompromising conditions (5.3% vs 6.2%, respectively; 0.86 [.80-.92]). These results were consistent irrespective of supplemental oxygen requirements. CONCLUSIONS: Treating patients hospitalized for COVID-19 with remdesivir was associated with a significantly lower likelihood of 30-day COVID-19-related readmission across all patients discharged alive from the initial COVID-19 hospitalization, including older adults and those with underlying immunocompromising conditions.

Aim: This observational study investigated the association between remdesivir treatment during hospitalization for COVID-19 and 30-day COVID-19-related and all-cause readmission across different variants time periods. Patients & methods: Hospitalization records for adult patients discharged from a COVID-19 hospitalization between 1 May 2020 to 30 April 2022 were extracted from the US PINC AI Healthcare Database. Likelihood of 30-day readmission was compared among remdesivir-treated and nonremdesivir-treated patients using multivariable logistic regression models adjusted for age, corticosteroid treatment, Charlson comorbidity index and intensive care unit stay during the COVID-19 hospitalization. Analyses were stratified by maximum supplemental oxygen requirement and variant time period (pre-Delta, Delta and Omicron). Results: Of the 440,601 patients discharged alive after a COVID-19 hospitalization, 248,785 (56.5%) patients received remdesivir. Overall, remdesivir patients had a 30-day COVID-19-related readmission rate of 3.0% and all-cause readmission rate of 6.3% compared with 5.4% and 9.1%, respectively, for patients who did not receive remdesivir during their COVID-19 hospitalization. After adjusting for demographics and clinical characteristics, remdesivir treatment was associated with significantly lower odds of 30-day COVID-19-related readmission (odds ratio 0.60 [95% confidence interval: 0.58-0.62]), and all-cause readmission (0.73 [0.72-0.75]). Significantly lower odds of 30-day readmission in remdesivir-treated patients was observed across all variant time periods. Conclusion: Treating patients hospitalized for COVID-19 with remdesivir is associated with a statistically significant reduction in 30-day COVID-19-related and all-cause readmission across variant time periods. These findings indicate that the clinical benefit of remdesivir may extend beyond the COVID-19 hospitalization.

Introduction The approval of Bruton tyrosine kinase (BTK) inhibitor ibrutinib and PI3K inhibitor idelalisib has revolutionized chronic lymphocytic leukemia (CLL) therapy (1-4). These B cell receptor (BCR) inhibitors induce transient [...], Bruton tyrosine kinase (BTK) inhibitor therapy induces peripheral blood lymphocytosis in chronic lymphocytic leukemia (CLL), which lasts for several months. It remains unclear whether nongenetic adaptation mechanisms exist, allowing CLL cells' survival during BTK inhibitor-induced lymphocytosis and/or playing a role in therapy resistance. We show that in approximately 70% of CLL cases, ibrutinib treatment in vivo increases Akt activity above pretherapy levels within several weeks, leading to compensatory CLL cell survival and a more prominent lymphocytosis on therapy. Ibrutinib-induced Akt phosphorylation ([pAkt.sup.S473]) is caused by the upregulation of Forkhead box protein 01 (FoxO1) transcription factor, which induces expression of Rictor, an assembly protein for the mTORC2 protein complex that directly phosphorylates Akt at serine 473 (S473). Knockout or inhibition of FoxO1 or Rictor led to a dramatic decrease in Akt phosphorylation and growth disadvantage for malignant B cells in the presence of ibrutinib (or PI3K inhibitor idelalisib) in vitro and in vivo. The FoxO1/ Rictor/[pAkt.sup.S473] axis represents an early nongenetic adaptation to B cell receptor (BCR) inhibitor therapy not requiring PI3K[delta] or BTK kinase activity. We further demonstrate that FoxO1 can be targeted therapeutically and its inhibition induces CLL cells' apoptosis alone or in combination with BTK inhibitors (ibrutinib, acalabrutinib, pirtobrutinib) and blocks their proliferation triggered by T cell factors (CD40L, IL-4, and IL-21).

ABSTRACT Due to growing interest in less common languages, Portuguese as an additional language has seen a rise in popularity, particularly in academic settings. Despite this, research on foreign graduate students learning Portuguese in Brazil remains scarce. This study investigates the cultural and identity (re)construction of one such student. Grounded in Vygotsky’s (1978) theory and informed by the Sociocultural Theory of Second Language Development (Lantolf, 2013) and investment theory developed by Bonny Norton (1995), which emphasize identity and motivation, we explore the experiences of a foreign graduate student at a southern Brazilian public university. Our analysis reveals a complex interplay between language development and cultural integration, ultimately suggesting the participant achieved his academic and professional goals - including successful completion of Portuguese courses - through language proficiency. By recollecting Abdul’s Muslim identity, it becomes clearer how social identities are constructed and reconstructed in and from social interactions. This highlights the limitations of simplistic views about learning - they are far more intricate than we often realize. The interplay between social interactions, power dynamics, and language development becomes clear: these elements are fundamentally linked.

Melt ponds are a core component of the summer sea ice system in the Arctic, increasing the uptake of solar energy and impacting the ice-associated ecosystem. They were thus one of the key topics during the 1-year drift campaign Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) in the Transpolar Drift 2019/2020. Pond depth is a dominating factor in describing the surface meltwater volume; it is necessary to estimate budgets and used in model parameterization to simulate pond coverage evolution. However, observational data on pond depth are spatially and temporally strongly limited to a few in situ measurements. Pond bathymetry, which is pond depth spatially fully resolved, remains unexplored. Here, we present a newly developed method to derive pond bathymetry from aerial images. We determine it from a photogrammetric multi-view reconstruction of the summer ice surface topography. Based on images recorded on dedicated grid flights and facilitated assumptions, we were able to obtain pond depth with a mean deviation of 3.5 cm compared to manual in situ observations. The method is independent of pond color and sky conditions, which is an advantage over recently developed radiometric airborne retrieval methods. It can furthermore be implemented in any typical photogrammetry workflow. We present the retrieval algorithm, including requirements for the data recording and survey planning, and a correction method for refraction at the air–pond interface. In addition, we show how the retrieved surface topography model synergizes with the initial image data to retrieve the water level of individual ponds from the visually determined pond margins. We use the method to give a profound overview of the pond coverage on the MOSAiC floe, on which we found unexpected steady pond coverage and volume. We were able to derive individual pond properties of more than 1600 ponds on the floe, including their size, bathymetry, volume, surface elevation above sea level, and temporal evolution. We present a scaling factor for single in situ depth measurements, discuss the representativeness of in situ pond measurements and the importance of such high-resolution data for new satellite retrievals, and show indications for non-rigid pond bottoms. The study points out the great potential to derive geometric properties of the summer sea ice surface emerging from the increasingly available visual image data recorded from uncrewed aerial vehicles (UAVs) or aircraft, allowing for an integrated understanding and improved formulation of the thermodynamic and hydrological pond system in models.

Objective: To evaluate the efficacy and safety of 2 doses of vilaprisan vs. placebo in participants with symptomatic endometriosis. Design: Multicenter, randomized, double-blind, placebo-controlled, parallel-group phase 2b trial (NCT03573336). The initially planned sample size was 315 patients. Recruitment was paused to assess long-term toxicity findings in rodents; although the findings were assessed as likely to be of limited clinical relevance in humans, the study was closed by the sponsor. During the pause, enrolled patients completed 3 or 6 months of treatment per their assigned regimen. Setting: University hospitals, a regional hospital, and a private clinic. Patients: Premenopausal adults with confirmed endometriosis and moderate-to-severe pelvic pain (≥4/10 on a numerical rating scale) were enrolled. Inclusion required protocol adherence, including ≥24 diary entries, and an average pain score of ≥3.5. Intervention: Participants were randomly assigned 1:1:1 to receive vilaprisan (2 mg), vilaprisan (4 mg), or placebo. Main Outcome Measures: The primary outcome was a change in the 7-day mean “worst pain” (per the endometriosis symptom diary item 1) from baseline to month 3. All analyses were descriptive only. Results: Eight participants were randomly assigned to treatment before the study pause: 6 received vilaprisan (4 mg, n = 4 and 2 mg, n = 2), and 2 received placebo. The 6 vilaprisan recipients experienced an improvement in endometriosis-associated pelvic pain, whereas the 2 placebo recipients experienced no change or increased pain; all 8 participants had decreased use of pain medication. Bleeding intensity decreased from baseline in the vilaprisan group. Conclusion: The study findings suggest that vilaprisan may improve outcomes in patients with endometriosis. Further studies in larger populations would be needed to accurately assess treatment effects. Clinical Trial Registration Number: NCT03573336

The development of algorithms for remote sensing of water quality (RSWQ) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 59 institutions worldwide and come from 450 different water bodies, making GLORIA the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity. Each measurement is documented with comprehensive methodological details, allowing users to evaluate fitness-for-purpose, and providing a reference for practitioners planning similar measurements. We provide open and free access to this dataset with the goal of enabling scientific and technological advancement towards operational regional and global RSWQ monitoring.

Melt ponds play a crucial role in the melting of Arctic sea ice. Studying the evolution of melt ponds is essential for understanding changes in Arctic sea ice. In this study, we used a revised sea ice model to simulate the evolution of melt ponds along the MOSAiC drift at a resolution of 10 m. A novel melt pond parameterization scheme simulates the movement of meltwater under the influence of gravity over a realistic sea ice topography. We evaluated different melt pond parameterization schemes based on remote sensing observations. The absolute deviation of the maximum pond coverage simulated by the new scheme is within 3%, while differences among parameterization schemes exceed 50%. Errors were found to be primarily due to the calculation of macroscopic meltwater loss, which is related to sea ice surface topography. Previous studies have indicated that sea ice with a lower surface roughness has a larger catchment area, resulting in larger pond coverage during the melt season. This study has identified an opposing mechanism: sea ice with lower surface roughness has a larger catchment area connected to the macroscopic flaws of the sea ice surface, which leads to more macroscopic drainage into the ocean and thereby a decrease in melt pond coverage. Experimental simulations showed that sea ice with 46% higher surface roughness, resulting in 12% less macroscopic drainage, exhibited a 38% higher maximum pond fraction. The presence of macroscopic flaws is related to the fragmentation of sea ice cover. As Arctic sea ice cover becomes increasingly fragmented and mobile, this mechanism will become more significant.

Abstract Background Breastfeeding provides the optimal nutrition for infants and offers numerous benefits for both mother and child. The World Health Organisation recommends exclusive breastfeeding during the first 6 months of life and the introduction of complementary feeding between the fifth and seventh months of life. There is a discrepancy between breastfeeding recommendations and the actual duration of breastfeeding. The aim of this study was to analyse breastfeeding behaviour in primiparous women in order to be able to provide support for mothers. Methods In this prospective, questionnaire-based study conducted between 2020 and 2022, primiparous women were asked to complete three questionnaires at three defined survey time points (routine prepartum presentation, postpartum hospitalization, completed sixth month of life). Results A total of 140 women were included and returned all three questionnaires. Fifty-eight percent performed breastfeeding exclusively at least until their baby had reached the age of 6 months, whereas 20% already stopped within the first 6 months. The main reasons given for early cessation were insufficient milk supply and inadequate infant weight gain. A comprehensive level of prepartum knowledge had a significant positive effect on participants’ sense of confidence with breastfeeding. Sociodemographic factors such as age and educational level were also associated with breastfeeding behaviour, but significant corresponding differences in the duration of breastfeeding were not observed. Women with postpartum midwifery care breastfed significantly longer (p

Numerous studies have focused on constructing multimodal machine learning models for estimating a person's cognitive load. However, a prevalent limitation is that these models are typically evaluated on data from the same scenario they were trained on. Little attention has been given to their robustness against data distribution shifts, which may occur during deployment. The aim of this paper is to investigate the performance of these models when confronted with a scenario different from the one on which they were trained. For this evaluation, we utilized a dataset encompassing two distinct scenarios: an n-Back test and a driving simulation. We selected a variety of classic machine learning and deep learning architectures, which were further complemented by various fusion techniques. The models were trained on the data from the n-Back task and tested on both scenarios to evaluate their predictive performance. However, the predictive performance alone may not lead to a trustworthy model. Therefore, we looked at the uncertainty estimates of these models. By leveraging these estimates, we can reduce misclassification by resorting to alternative measures in situations of high uncertainty. The findings indicate that late fusion produces stable classification results across the examined models for both scenarios, enhancing robustness compared to feature-based fusion methods. Although a simple logistic regression tends to provide the best predictive performance for n-Back, this is not always the case if the data distribution is shifted. Finally, the predictive performance of individual modalities differs significantly between the two scenarios. This research provides insights into the capabilities and limitations of multimodal machine learning models in handling distribution shifts and identifies which approaches may potentially be suitable for achieving robust results.