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Millennial-to-orbital-scale subsurface ocean warming and Polynya formation off Dronning Maud Land during the last glacial
Abstract We present a millennial-scale multi-proxy reconstruction of changes in properties of the upper water column near the East Antarctic ice shelf based on planktonic foraminifera from a unique sedimentary archive spanning the glacial period from 75,000 to 20,000 years. Our results imply that variations in the thermohaline structure between Antarctic Surface Water and Warm Deep Water (WDW) may have resulted in either strengthening the stratification of the upper water column or promoting polynya formation (convective overturning). Oceanic subsurface warming during glacial Antarctic stadials and periods of low obliquity, combined with increased salinity and nutrient content, suggests the breakdown in stratification and polynya presence. This glacial polynya formed off Dronning Maud Land (DML) reflects a hybrid coastal-open-ocean polynya mode. We attribute the development of the Glacial DML Polynya to sea-ice induced subsurface warming of WDW and a decrease in density stratification in combination with circulation changes in the atmosphere and ocean. The polynya-driven oceanic heat release during the glacial stadials may have increased the moisture supply to Antarctica and thus promoted the accumulation of ice and the thickening of an advancing ice sheet at the continental shelf margin.
Good Compressions
Photonic ‘ski jump’ steers light beam from silicon chip
Dual-stiffness nanoparticles for compartment-specific drug delivery in stroke
Health Consequences of Immigration Enforcement in U.S. Communities
Volatile resorption expedites eruption onset in large silicic systems
Abstract Silicic caldera-forming eruptions are among the most hazardous natural phenomena on Earth, yet their triggering mechanisms remain poorly understood. While volatile exsolution is widely recognized as a potential eruption driver in large silicic systems, we find that volatile resorption can, counterintuitively, promote chamber pressurization faster than volatile exsolution. Using a thermo-mechanical magma chamber model, we show that resorption is a common process in rapidly recharged systems, driven by pressure increase and crystal melting. The Aso-4 eruption offers a natural case where volatile resorption may have occurred, with model results predicting resorption at recharge rates >10 -2.4 km 3 /yr. Through reducing bulk magma compressibility, resorption amplifies pressurization, driving chamber destabilization and potentially expediting eruption onset. Here, we propose that volatile resorption is a natural process both accommodating and promoting rapid chamber pressurization, fundamental to destabilizing large-scale silicic systems. Detecting its signatures in monitoring signals could provide early warning of imminent eruption.
Thrombopoietin-Receptor Agonists in Chemotherapy-Induced Thrombocytopenia
Matrix stress relaxation promotes glioblastoma cell migration in a ligand-specific manner
ctDNA and tumor-based biomarkers of giredestrant response in acelERA breast cancer
Abstract Endocrine therapy (ET) resistance in estrogen receptor positive (ER+) advanced breast cancer is often linked to ESR1 mutations, yet responses to oral selective ER degraders vary within mutant subgroups. Through a biomarker analysis of acelERA Breast Cancer (NCT04576455), we show that tumor ER transcriptional activity as well as circulating tumor DNA (ctDNA) genomics and dynamics effectively stratify response to ET, including giredestrant. We find that following first-line therapy, the ctDNA genomic landscape is diverse and influenced by CDK4/6 inhibitor exposure. Despite this complexity, ER activity in ESR1 -mutant tumors remains comparable to early breast cancer but is reduced in most non-mutant cases. This maintained ER activity is associated with giredestrant benefit. Furthermore, early ctDNA clearance identifies responding patients, and the combination of low ER activity and high ctDNA burden predicts rapid clinical progression. These findings provide a framework for personalizing future breast cancer therapies by integrating liquid biopsies with tissue-based signatures.
Massive Intravascular Hemolysis from <i>Clostridium perfringens</i> Bacteremia
Nonlinear dynamics and stability of a delayed leukemia model with real-world applications
Proteostasis failure and mitochondrial dysfunction contribute to chromosomal instability-induced microcephaly
European Study of Prostate Cancer Screening — 23-Year Follow-up
Development and validation of a cardiometabolic multimorbidity prediction model in middle-aged and older adults
Abstract Cardiometabolic multimorbidity (CMM) is a prevalent syndrome among middle-aged and older adults, significantly impairing quality of life and imposing substantial health and economic burdens on China’s aging healthcare system. The development of timely predictive models is crucial for enabling early intervention. This study aimed to integrate multidimensional data from the China Health and Retirement Longitudinal Study (CHARLS) to develop an effective predictive model for assessing the five-year risk of CMM onset, thereby facilitating early intervention and management for individuals at risk in China. We analyzed data from the 2015 to 2020 CHARLS surveys, involving 5,388 middle-aged and older adults initially free of CMM. The dataset was randomly split into a training set (70%) and a validation set (30%). Key predictors were identified from 31 potential variables using LASSO regression with 10-fold cross-validation. Selected predictors underwent correlation analysis and were used to construct both Extreme Gradient Boosting (XGBoost) and Logistic Regression (LR) models. Variable contributions in the XGBoost model were interpreted using SHapley Additive exPlanations (SHAP) values, while the LR model was visualized via a nomogram. The performance of the superior model was evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis. LASSO regression screened significant variables from the initial 31 candidates. Correlation analysis ultimately identified nine key predictors: systolic blood pressure, BMI, fasting blood glucose, total cholesterol, triglycerides, uric acid, age, comorbidities, and pain. The logistic regression model demonstrated superior and more stable predictive performance on the validation set, with an area under the curve (AUC) of 0.732 (95% CI: 0.703–0.761). Calibration curves indicated reliable predictive accuracy, and decision curve analysis established the clinical net benefit across a range of risk thresholds. This study developed and validated a reliable, clinically applicable logistic regression model, supplemented by a nomogram, for assessing the five-year risk of CMM in Chinese middle-aged and older adults. The model effectively identifies high-risk individuals, supporting targeted early intervention and management strategies to alleviate the health and economic burdens associated with CMM in this population.
Microgravity-activated high-performance van der Waals InSe ferroelectric semiconductor
A Feverish Pace
Achieving precise chip control for high-end manufacturing
Abstract In high-end manufacturing, where precision and automation are strictly required, chip control presents an incredibly daunting challenge during the machining process. In this paper, a novel chip control method called grooves induced chip-breaking (GICB) is comprehensively investigated. The core concept of GICB is to achieve spontaneous chip-breaking through the pre-processed micro grooves (PPMG) on the workpiece surface. To understand the underlying chip-breaking mechanisms, PPMG with identical geometric shapes are fabricated on the surface of a 316 L stainless steel workpiece using laser ablation. A cutting experiment is then conducted, where the cutting depth ( d ) and feed rate ( f ) are varied. Experimental observations reveal that, apart from enabling controllable chip-breaking, the GICB method can also enhance the quality of the machined surface. Specifically, the surface roughness (Ra) is reduced by up to 26.6%. Further in-depth analyses indicate that the primary cause of this improvement is the reduced fluctuation of the thrust force. With the assistance of PPMG, the chips produced under controlled periodic fracture exhibit similar lengths and curvatures. Benefiting from that, chip agglomeration and entanglement are effectively avoided. In addition, the fluctuation of cutting force is greatly reduced, which in turn improves the machined surface quality. The practical significance of this study is twofold. Firstly, a high-performance chip control method with significant potential applications is systematically explored. Secondly, for the first time, the crucial relationship between chip control and machined surface quality is experimentally verified.