bluuebunny/crossref_metadata_2025_split huggingface dataset:
Method for determining a Prostate Cancer LET Sensitivity Index (PCLSI) using tumour-specific DDR mutations for proton RBE
Authors: Artz Mark E. , Vieceli Michael J. , Park Jiyeon , Saki Mohammad , Zhang Yawei , Brooks Eric D. , Mendenhall Nancy P. , Johnson Perry B. , Grewal Hardev S. 
Published: February 2025

Abstract

Purpose:
This study introduces the prostate cancer linear energy transfer sensitivity index (PCLSI) as a novel method to predict relative biological effectiveness (RBE) in prostate cancer using linear energy transfer (LET) in proton therapy based on screening for DNA repair mutations.

Materials and Methods:
Five prostate cancer cell lines with DNA repair mutations known to cause sensitivity to LET and DNA repair inhibitors were examined using published data. Relative Du145 LET sensitivity data were leveraged to deduce the LET equivalent of olaparib doses. The PCLSI model was built using three of the prostate cancer cell lines (LNCaP, 22Rv1 and Du145) with DNA mutation frequency from patient cohorts. The PCLSI model was compared against two established RBE models, McNamara and McMahon, for LET-optimized prostate cancer treatment plans.

Results:
The PCLSI model relies on the presence of eight DNA repair mutations: AR, ATM, BRCA1, BRCA2, CDH1, ETV1, PTEN and TP53, which are most likely to predict increased LET sensitivity and RBE in proton therapy. In the LET-optimized plan, the PCLSI model indicates that prostate cancer cells with these DNA repair mutations are more sensitive to increased LET than the McNamara and McMahon RBE models, with expected RBE increases ranging from 11%–33% at 2keV/µm.

Conclusions:
The PCLSI model predicts increasing RBE as a function of LET in the presence of certain genetic mutations. The integration of LET-optimized proton therapy and genetic mutation profiling could be a significant step toward the use of individualized medicine to improve outcomes using RBE escalation without the potential toxicity of physical dose escalation.
Population genetics studies of sour orange in Iran
Authors: Ghahremani Rabeeh , Sheidai Masoud , Koohdar Fahimeh 
Published: February 2025

Abstract
Citrus aurantium also known as sour orange or bitter orange is among important Citrus species of the angiosperm subfamily Aurantioideae of the Rutaceae family. Due to importance of Citrus species as the source of food and medicine, they have been subject of been extensive genetic studies throughout the world. Sour orange plants are cultivated in the north and south parts of Iran but we have very limited genetic data on them. Therefore, the present study was conducted with the aim to study the population genetics of these important fruit plants in the country and provide information on their genetic structure and diversity. We used SCoT molecular markers in 61 plants of 12 sour orange populations. We obtained 33 SCoT bands of which one to two private bands were observed in populations 1 and 5. Genetic diversity parameters determine in the studied populations revealed a low to moderate genetic diversity. Genetic grouping of the populations by UPGMA dendrogram and multidimensional scaling identified two major genetic groups. The studied populations differed significantly in their genetic content as revealed by AMOVA. Distinguishing SCoT loci are identified by Neis'and Gst as well as DAPC analysis. Some of the SCoT loci were significantly associated with geographical variables as revealed by RDA and LFMM analyses.
Containment or bad detection? Poor state capacity implications on reported Covid-19 cases
Authors: Belmonte Alessandro , Magnani Michele 
Published: February 2025

Abstract
This paper examines the effects of state capacity on the reported Covid-19 infection (and mortality) rate and its policy implications. We analyse two dimensions of state capacity which were critical during the pandemic. The healthcare capacity acted to contain the virus outbreak (an effect we call containment). The information capacity acted to detect contagious yet asymptomatic cases (an effect we call detection). We argue that containment pushes down the reported infection rate. In contrast, detection pushes it up, thus generating a non-linear combined effect that we estimate systematically using Colombian municipality-level as well as country-level data, different data sources, and various empirical strategies. Our findings indicate that the infection (and mortality) rates were likely under-reported, especially in areas with a low state capacity level, due to their poor capabilities to detect the virus. Our study put the emphasis on the many facets of state capacity, each affecting in complex ways our understanding of important phenomena, such as the Covid-19 outbreak.
A higher-order spectral element method for modeling eccentric anisotropic multilayered waveguides via transformation optics
Authors: Ribeiro Raul O. , Rosa Guilherme S. , Bergmann José R. , Teixeira Fernando L. 
Published: February 2025

Abstract
We present a higher-order spectral element method (SEM) for analyzing eccentric anisotropic multilayered waveguides. The formulation uses conformal transformation optics to map the original eccentric waveguide to an equivalent concentric one. This transformation is extended to handle anisotropic non-reciprocal media characterized by non-symmetric and non-Hermitian tensors. In the transformed concentric domain, higher-order two-dimensional basis functions associated with the zeros of the completed Lobatto polynomial are used to expand the fields. To simulate radially unbounded problems, we employ a complex-stretched perfectly matched layer to mimic open space. The method is validated with radially bounded two-layer and three-layer waveguides and radially unbounded three-layer waveguides. Comparisons with the finite element method (FEM) demonstrate that our SEM approach requires significantly fewer degrees of freedom than FEM.
The Mystery of Baselevel Controls in the Incision History of the Central Colorado Plateau
Authors: Tanski Natalie M. , Pederson Joel L. , Hidy Alan J. , Rittenour Tammy M. , Mauch James P. 
Published: February 2025

AbstractErosion can remain active and changing in landscapes long after tectonic drivers have ceased, potentially due to local‐geologic controls, climate changes, or geodynamics. We present new fluvial incision‐rate histories and terrain analyses of the Colorado River system through the central Colorado Plateau to understand what has caused the variable erosion across this post‐orogenic landscape. Results from new cosmogenic and luminescence dating of fluvial terrace and upland gravel deposits in Glen and Meander Canyons establish incision‐rate histories that are marked by an Early‐Middle Pleistocene erosion hiatus, followed by ∼200 m of rapid incision over the last ∼350 kyr. Projection of fluvial topography from above knickzones of the Colorado River drainage system roughly agree with the observed magnitude of recent incision and reflect a common baselevel fall from Pliocene river integration through Grand Canyon, which is still propagating through the drainage. A response‐time model indicates that baselevel fall from integration likely took 2–4 Myr to reach the central Colorado Plateau and 100s kyr to travel across the study area, potentially accounting for incision rate changes in the fluvial terrace records of Meander and Glen Canyons. The upstream‐migrating incision has likely been partitioned into multiple waves across the landscape due to the local geologic controls of lava damming, salt tectonics, and heterogenous bedrock. As baselevel fall from Pliocene Colorado River integration diffuses upstream, it can only account for perhaps a quarter of the total ∼2 km of exhumation in the central Colorado Plateau, demanding an unknown driver for significant erosion in the Pliocene.
GOES‐R PM2.5 Evaluation and Bias Correction: A Deep Learning Approach
Authors: Sayeed Alqamah , Gupta Pawan , Henderson Barron , Kondragunta Shobha , Zhang Hai , Liu Yang 
Published: February 2025

AbstractEstimating surface‐level fine particulate matter from satellite remote sensing can expand the spatial coverage of ground‐based monitors. This approach is particularly effective in assessing rapidly changing air pollution events such as wildland fires that often start far away from centralized ground monitors. We developed Deep Neural Network (DNN) algorithm to improve hourly PM2.5 estimates informed by GOES‐R; meteorology forecasts, and PM2.5 observations from AirNow. The surface‐satellite‐model collocated data sets for the period of 2020–2021 were used to assess the biases in GOES‐GWR PM2.5 (only operationally available data set) against AirNow measurements at hourly and daily scales. Then a DNN based bias correction algorithm is used to improve the accuracies of GOES‐GWR PM2.5. The DNN uses GOES‐GWR PM2.5, GOES‐R aerosol parameters, and HRRR meteorological fields as input and AirNow PM2.5 is used as target variable. The application of DNN reduced the PM2.5 biases as compared to GOES‐GWR estimates. RMSE was also reduced to 6.55 μg/m3 from 8.72 μg/m3 in GOES‐GWR estimates. The DNN model was also evaluated on two sets of independent data sets for its robustness. In the first independent data set for the first half of 2020, ∼89% of stations show an increase in correlation (r) and, ∼76% and ∼62% of stations show a reduction in bias. The IOA and r for the independent data were 0.77 and 0.61 (GWR: 0.68 and 0.53) and RMSE was 4.48 μg/m3 (GWR = 6.13 μg/m3) for the same period. The algorithm will be operationally deployed by NOAA and US‐EPA to estimate surface level PM2.5 from satellite derived Aerosol optical depth.
Muted Amazon Rainfall Response to Deforestation in a Global Storm‐Resolving Model
Authors: Yoon Arim , Hohenegger Cathy 
Published: February 2025

AbstractOngoing Amazon deforestation has raised concerns about forest dieback via induced precipitation changes. Previous studies have found that complete deforestation reduces evapotranspiration, contributing to low precipitation rates that would limit the regrowth of the forest, but such studies have used climate models with convective parameterization and/or fixed large‐scale circulation. For the first time, we simulate a complete Amazon deforestation scenario without convective parameterization, allowing full interaction between convection and large‐scale circulation, for 3 years. Our results show no significant reduction in annual mean precipitation. Changes in the 700 hPa circulation and associated moisture convergence compensate for the reduction in evapotranspiration. These changes also lead to a north‐south dipole pattern in the precipitation response during the dry and wet seasons. The uncovered dynamics suggest that Amazon mean precipitation may be more resilient to land surface perturbations than previously thought.
Unveiling Energy Conversions of the Venus Atmosphere by the Bred Vectors
Authors: Liang Jianyu , Sugimoto Norihiko , Miyoshi Takemasa 
Published: February 2025

AbstractThe Lorenz energy cycle was often used to analyze energy conversions related to instabilities in planetary atmospheres using zonal means as basic states. Alternatively, the bred vector (BV) energy equations use the control run as basic states and detect longitudinal dependency of the energy conversions. Additionally, it quantifies contributions from baroclinic and barotropic instabilities separately. We apply this method to understand energy conversions of the Venus atmosphere. BVs are obtained from breeding cycles emphasizing perturbation growths in the cloud layer. The BV potential energy in the pressure coordinate is newly derived. Energy conversions at different latitudes in the cloud layer are examined. Results show that baroclinic conversions are stronger at higher latitudes and exceed barotropic conversions at mid‐ to high‐latitudes. Thermal tides increase energy conversions in the morning hemisphere at mid‐latitudes. This study offers new insights into energy conversions of the Venus atmosphere, with potential applications to other planetary atmospheres.
Knickpoint Dynamics During the Outward Growth of the Northeastern Tibetan Plateau
Authors: Li Zhengchen , Wang Xianyan , Yuan Xiaoping , He Chuanqi , Su Qi , Lu Huayu 
Published: February 2025

AbstractMountain‐building events often initiate fluvial erosion waves that usually propagate upstream. Previous studies have delved into the erosion wave, manifested as knickpoint migration, presuming a spatially consistent uplift of plateaus. However, the expansion of plateaus can spatially result in spatially variable rock uplift rates across different regions, complicating our understanding of knickpoint dynamics. In this study, conducted at the edge of the northeastern Tibetan Plateau, we investigated the impact of plateau expansion on erosion wave processes within the upper Yellow River basin. Through river profile analyses and landscape evolution simulations, we reveal that the continuous outward expansion of the northeastern Tibetan Plateau into its periphery has induced localized uplift followed by erosion. Subsequently, an erosion wave migrated headward along the Yellow River during the Pleistocene. Observations from the Digital Elevation Model and modeling results show that this erosion wave spread within the tectonically active sub‐block at the margin of the plateau, but did not continue further upstream. In contrast, modeling results suggest that erosion waves would consistently migrate upstream under conditions of spatially uniform rock uplift. Our findings highlight that spatially variable rock uplift rates, driven by the expansion of the plateau, are crucial in determining whether fluvial erosion waves migrate or remain stationary. This refined understanding of knickpoint dynamics during plateau development offers insights into the persistence of relict high‐elevation and low‐relief landscapes.
Using Water Level Responses to Atmospheric Pressure Variations to Measure and Monitor Vertical Leakage Through Confining Units, With Application to the Jurassic Shaximiao Crust, China
Authors: Zhang Yan , Yang Qiu‐Ye , Manga Michael , Fu Li‐Yun , Zhang Huai , Chu Bingfei , Chen Gaoxiang , Huang Tianming , Han Tongcheng , Qi Shengwen 
Published: February 2025

AbstractThe upper few hundreds of meters of the crust often hosts leaky aquifers. Quantifying leakage is important if those aquifers are used as a water resource. The responses of water level to external forcing such as tides and barometric pressure changes offer the opportunity to measure aquifer hydrogeological properties and monitor possible changes in those properties. Around the Huayingshan faults adjacent to Sichuan and Chongqing provinces, China, inclined fold‐and‐thrust belts form the crust, and frequent earthquakes might impact aquifers in the shallow crust that are used for drinking water. We introduce a new computational approach for continuous modeling of water level changes in response to barometric pressure variations to identify when the signals are reliable and then determine values of aquifer transmissivity and aquitard hydraulic diffusivity. Computed aquifer transmissivity agrees with values from well tests. We obtain horizontal and vertical hydraulic parameters for more than 10 years (from 2008 to 2019). Of the six wells studied, five have aquitard vertical hydraulic diffusivities at least two orders of magnitude greater than aquifer horizontal transmissivity. Although several regional and teleseismic earthquakes caused changes in water levels in one of the wells with relatively low vertical permeability, we do not see clear changes in hydraulic properties in response to the earthquakes. We also identify small long‐term trends and seasonal variations in hydrogeological properties.
Hot beverage intake and oesophageal cancer in the UK Biobank: prospective cohort study
Authors: Inoue-Choi Maki , Ramirez Yesenia , O’Connell Caitlin , Berrington de Gonzalez Amy , Dawsey Sanford M. , Abnet Christian C. , Freedman Neal D. , Loftfield Erikka 
Published: February 2025

Abstract

Background
Drinking maté, a type of tea consumed at a very hot temperature in South America has been considered as a risk factor for oesophageal squamous cell carcinoma (ESCC).

Methods
We assessed daily intake and preferred temperature of hot beverages (tea and coffee) in relation to incident ESCC (n = 242) and adenocarcinoma (EAC; n = 710) among 454,796 adults in the UK Biobank. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using multivariable Cox proportional hazards regression.

Results
Relative to non-drinkers and warm temperature drinkers (referent group), drinking 4–6 cups/d (HR, 1.97; 95% CI, 1.14–3.38) or more of hot temperature beverages was associated with higher risk of ESCC; HRs increased with increasing daily intake of hot temperature beverages (P-trend < 0.01). ESCC risk was still higher for those who drank very hot beverages; drinking ≤ 4 cups/d was associated with a 2.5-fold higher risk (HR, 2.52; 95% CI, 1.27–5.03), and risk increased with increasing daily intake of very hot temperature beverages (P-trend < 0.01). There was no clear association for EAC.

Conclusions
Our findings provide new evidence that drinking hot or very hot beverages is a risk factor for ESCC in the UK where drinking hot tea and coffee is common.
Non-classical neutrophil extracellular traps induced by PAR2-signaling proteases
Authors: Bryzek Danuta , Gasiorek Anna , Kowalczyk Dominik , Santocki Michal , Ciaston Izabela , Dobosz Ewelina , Kolaczkowska Elzbieta , Kjøge Katarzyna , Kantyka Tomasz , Lech Maciej , Potempa Barbara , Enghild Jan J. , Potempa Jan , Koziel Joanna 
Published: February 2025

Abstract
Neutrophil extracellular traps (NETs) are associated with diseases linked to aberrant coagulation. The blood clotting cascade involves a series of proteases, some of which induce NET formation via a yet unknown mechanism. We hypothesized that this formation involves signaling via a factor Xa (FXa) activation of the protease-activated receptor 2 (PAR2). Our findings revealed that NETs can be triggered in vitro by enzymatically active proteases and PAR2 agonists. Intravital microscopy of the liver vasculature revealed that both FXa infusion and activation of endogenous FX promoted NET formation, effects that were prevented by the FXa inhibitor, apixaban. Unlike classical NETs, these protease-induced NETs lacked bactericidal activity and their proteomic signature indicates their role in inflammatory disorders, including autoimmune diseases and carcinogenesis. Our findings suggest a novel mechanism of NET formation under aseptic conditions, potentially contributing to a self-amplifying clotting and NET formation cycle. This mechanism may underlie the pathogenesis of disseminated intravascular coagulation and other aseptic conditions.
Sephin1 suppresses ER stress-induced cell death by inhibiting the formation of PP2A holoenzyme
Authors: Gojo Satoshi , Kami Daisuke , Sano Arata , Teruyama Fumiya , Ogata Takehiro , Matoba Satoaki 
Published: February 2025

Abstract
Sephin1 was discovered as a protein phosphatase inhibitor, and its efficacy against neurodegenerative diseases has been confirmed. There are conflicting reports on whether inhibition of eIF2α dephosphorylation by PP1 holoenzyme with the protein phosphatase 1 regulatory subunit 15 A is the mechanism of action of Sephin1. In the present study, we found that Sephin1 significantly suppressed renal tubular cell death in an animal model of ER stress administered with tunicamycin. CHOP, which plays a central role in the ER stress-induced cell death pathway, requires nuclear translocation to act as a transcription factor to increase the expression of cell death-related genes. Sephin1 markedly suppressed this nuclear translocation of CHOP. To elucidate the molecular mechanism underlying the cell death suppressive effect of Sephin1, we used human renal tubular epithelial cells under ER stress with tunicamycin. Sephin1 reduced intracellular CHOP levels by promoting CHOP phosphorylation at Ser30, which led to protein degradation in UPS. Phosphorylated CHOP is generated by Thr172-phosphorylated activated AMPK, and Sephin1 increased phosphorylated AMPK. Phosphorylated AMPK is inactivated by PP2A through dephosphorylation of its Thr172, and Sephin1 inhibits the formation of the PP2A holoenzyme with the PP2A subunit B isoform delta. These results indicate that inhibition of PP2A holoenzyme formation is the molecular target of Sephin1 in this experimental system.
Deciphering neuronal variability across states reveals dynamic sensory encoding
Authors: Akella Shailaja , Ledochowitsch Peter , Siegle Joshua H. , Belski Hannah , Denman Daniel D. , Buice Michael A. , Durand Severine , Koch Christof , Olsen Shawn R. , Jia Xiaoxuan 
Published: February 2025

Abstract
Influenced by non-stationary factors such as brain states and behavior, neurons exhibit substantial response variability even to identical stimuli. However, it remains unclear how their relative impact on neuronal variability evolves over time. To address this question, we designed an encoding model conditioned on latent states to partition variability in the mouse visual cortex across internal brain dynamics, behavior, and external visual stimulus. Applying a hidden Markov model to local field potentials, we consistently identified three distinct oscillation states, each with a unique variability profile. Regression models within each state revealed a dynamic composition of factors influencing spiking variability, with the dominant factor switching within seconds. The state-conditioned regression model uncovered extensive diversity in source contributions across units, varying in accordance with anatomical hierarchy and internal state. This heterogeneity in encoding underscores the importance of partitioning variability over time, particularly when considering the influence of non-stationary factors on sensory processing.