bluuebunny/crossref_metadata_2025_split huggingface dataset:
More Accurate Quantification of Direct Aerosol Radiative Effects Using Vertical Profiles of Single‐Scattering Albedo Derived From Tethered Balloon Observations
Authors: Guan Xu , Tian Pengfei , Wang Wenfang , Zhang Min , Song Xin , Zhang Zhida , Zhang Lei 
Published: July 2024

AbstractAerosol single‐scattering albedo (SSA) is the most critical factor for the accurately calculating of aerosol radiative effects, however, the observation of vertical profiles of SSA is difficult to realize. Current assessments of aerosol radiative effects remain uncertain because of the lack of long‐term, high‐resolution vertical profiles of SSA observations. High‐resolution SSA vertical profiles were observed in a semi‐arid region of Northwest China during winter using a tethered balloon. The observed SSA vertical profiles were used to calculate the aerosol direct radiative forcing and radiative heating rates. Significant differences in the calculated radiative forcing were found (e.g., a 48.3% relative difference for the heating effect in the atmosphere at 14:00) between the observed SSA profiles and the constant assumption with SSA = 0.90. Diurnal variations in the vertical distribution of SSA decisively influenced direct radiative forcing of aerosols. Furthermore, high‐resolution vertical profiles of absorbing aerosols and meteorological parameters provide robust observational evidence of the heating effect of an elevated absorbing aerosol layer. This study provides a more accurate calculation of aerosol radiative forcing using observed aerosol SSA profiles.
Disentangling Forced Trends in the North Atlantic Jet From Natural Variability Using Deep Learning
Authors: Hermoso Alejandro , Schemm Sebastian 
Published: July 2024

AbstractRegional weather variability and extremes over Europe are strongly linked to variations in the North Atlantic jet stream, especially during the winter season. Projections of the evolution of the North Atlantic jet are essential for estimating the regional impacts of climate change. Therefore, separating forced trends in the North Atlantic jet from its natural variability is an extremely relevant task. Here, a deep learning based method, the Latent Linear Adjustment Autoencoder (LLAE), is used for this purpose on an ensemble of fully‐coupled climate simulations. The LLAE is based on a variational autoencoder and an additional linear component. The model uses detrended temperature and geopotential to predict the component of the zonal wind associated with natural variability. The residual between this prediction and the original wind field is interpreted as the forced component of the jet. The method is first tested for the geostrophic wind for which the forced trend can be obtained analytically from the difference between geostrophic wind computed from detrended and full geopotential. Despite the large variability of the total trends, the LLAE is shown to be effective in extracting the forced component of the trend for each individual ensemble member in both geostrophic and full wind fields. The LLAE‐derived forced trend shows an increase in the upper‐level zonal wind speed along a southwest–northeast oriented band over the ocean and a jet extension toward Europe. These are common characteristics over different periods and show some similarities to the upper‐level zonal wind speed trend obtained from the ERA5 reanalysis.
Characterizing Hydrated Sulfates and Altered Phases in Jezero Crater Fan and Floor Geologic Units With SHERLOC on Mars 2020
Authors: Phua Yu Yu , Ehlmann Bethany L. , Siljeström Sandra , Czaja Andrew D. , Beck Pierre , Connell Stephanie , Wiens Roger C. , Jakubek Ryan S. , Williams Rebecca M. E. , Zorzano Maria‐Paz , Minitti Michelle E. , Pascuzzo Alyssa C. , Hand Kevin P. , Bhartia Rohit , Kah Linda C. , Mandon Lucia , Razzell Hollis Joseph , Scheller Eva L. , Sharma Sunanda , Steele Andrew , Uckert Kyle , Williford Kenneth H. , Yanchilina Anastasia G. 
Published: July 2024

AbstractThe Mars 2020 Perseverance rover has explored fluvio‐lacustrine sedimentary rocks within Jezero crater. Prior work showed that igneous crater floor Séítah and Máaz formations have mafic mineralogy with alteration phases that indicate multiple episodes of aqueous alteration. In this work, we extend the analyses of hydration to targets in the Jezero western fan delta, using data from the SHERLOC (Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals) Raman spectrometer. Spectral features, for example, sulfate and hydration peak positions and shapes, vary within, and across the crater floor and western fan. The proportion of targets with hydration associated with sulfates was approximately equal in the crater floor and the western fan. All hydrated targets in the crater floor and upper fan showed bimodal hydration peaks at ∼3,200 and ∼3,400 cm−1. The sulfate symmetric stretch at ∼1,000 cm−1 coupled with a hydration peak at ∼3,400 cm−1 indicate that MgSO4·nH2O (2 < n ≤ 5) is a likely hydration carrier phase in all units, perhaps paired with low‐hydration (n ≤ 1) amorphous Mg‐sulfates, indicated by the ∼3,200 cm−1 peak. Low‐hydration MgSO4·nH2O (n = 1–2) are more prevalent in the fan, and hydrated targets in the fan front only had one peak at ∼3,400 cm−1. While anhydrite co‐occurs with hydrated Mg‐sulfates in the crater floor and fan front, hydrated Ca‐sulfates are observed instead at the top of the upper fan. Collectively, the data imply aqueous deposition of sediments with formation of salts from high ionic strength fluids and subsequent aridity to preserve the observed hydration states.
High‐Resolution Neural Network Demonstrates Strong CO2 Source‐Sink Juxtaposition in the Coastal Zone
Authors: Duke P. J. , Hamme R. C. , Ianson D. , Landschützer P. , Swart N. C. , Covert P. A. 
Published: July 2024

AbstractThe role of coastal oceans in regulating atmospheric carbon dioxide remains poorly quantified and understood. Here, we use a two‐step neural network approach to generate estimates from sparse observational data in the coastal Northeast Pacific Ocean at an unprecedented spatial resolution of 1/12° with coverage in the nearshore (0–25 km offshore). We compiled partial pressure of carbon dioxide (pCO2) observations as well as a range of predictor variables including satellite‐based and physical oceanographic reanalysis products. With the predictor variables representing processes affecting pCO2, we created non‐linear relationships to interpolate observations from 1998 to 2019. Compared to in situ shipboard and mooring observations, our coastal pCO2 product captures broad spatial patterns and seasonal cycle variability well. A sensitivity analysis identifies that the parameters responsible for the neural network's ability to capture regional pCO2 variability are associated with mechanistic processes, including mixed layer deepening, mesoscale eddies, and gyre upwelling. Using wind speed and atmospheric CO2, we calculated air‐sea CO2 fluxes. We report an anticorrelation between annual air‐sea CO2 flux and its seasonal amplitude with the relationship driven by circulation, opposing seasonal upwelling/relaxation versus downwelling, and the effects of winter mixing and primary productivity. We show that the inclusion of nearshore net outgassing fluxes lowers the overall regional net flux. Overall, our results suggest that the region is a net sink (−0.7 mol m−2 yr−1) for atmospheric CO2 with trends indicating increasing oceanic uptake due to strong connectivity to subsurface waters.
An Objective Detection of Separation Scenario in Tropical Cyclone Trajectories Based On Ensemble Weather Forecast Data
Authors: Oettli P. , Kotsuki S. 
Published: July 2024

AbstractIn ensemble weather forecast, tropical cyclone (TC) tracks sometimes group together into trajectories parting away from each other. The goal of this study is to propose an objective method, based on a robust clustering approach, to detect such separation scenarios in the Japan Meteorological Agency Meso‐scale Ensemble Prediction System (MEPS) for three TCs: “Dolphin” (2020), “Nepartak” (2021), and “Meari” (2022). Taking advantage of the independence of the density‐based spatial clustering of applications with noise algorithm to the prior choice of the number of clusters, we first describe an objective way to calculate the aggregation distance, by searching the most frequent Euclidean distance between all the tracks. The clustering is then applied to the forecasted tracks, for each initialization time of MEPS (every 6 hr). Separation scenarios exist when the number of clusters is greater than one.
Drivers of PM2.5 Episodes and Exceedance in India: A Synthesis From the COALESCE Network
Authors: Venkataraman Chandra , Anand Abhinav , Maji Sujit , Barman Neeldip , Tiwari Dewashish , Muduchuru Kaushik , Sharma Arushi , Gupta Ganesh , Bhardwaj Ankur , Haswani Diksha , Pullokaran Delwin , Yadav Kajal , Sunder Raman Ramya , Imran Mohd. , Habib Gazala , Kapoor Taveen Singh , Anurag Gupta , Sharma Renuka , Phuleria Harish C. , Qadri Adnan Mateen , Singh Gyanesh Kumar , Gupta Tarun , Dhandapani Abisheg , Kumar R. Naresh , Mukherjee Sauryadeep , Chatterjee Abhijit , Rabha Shahadev , Saikia Binoy K. , Saikia Prasenjit , Ganguly Dilip , Chaudhary Pooja , Sinha Baerbel , Roy Sayantee , Muthalagu Akila , Qureshi Asif , Lian Yang , Pandithurai Govindan , Prasad Laxmi , Murthy Sadashiva , Duhan Sandeep Singh , Laura Jitender S. , Chhangani Anil Kumar , Najar Tanveer Ahmad , Jehangir Arshid , Kesarkar Amit P. , Singh Vikas 
Published: July 2024

AbstractEmission sources influencing high particulate air pollution levels and related mortality in India have been studied earlier on country‐wide and sub‐national scales. Here, we use novel data sets of emissions (for 2019) and observations created under the Carbonaceous Aerosol Emissions, Source Apportionment, and Climate Impacts network in India (Venkataraman et al., 2020, https://doi.org/10.1175/bams‐d‐19‐0030.1) in WRF‐Chem simulations to evaluate drivers of high PM2.5 levels during episodes and in airsheds with different pollution levels. We identify airsheds in “extreme” (110–140 μg/m3), “severe” (80–110 μg/m3) and “significant” (40–80 μg/m3) exceedance of the Indian annual ambient air quality standard (National Ambient Air Quality Standards [NAAQS]) of 40 μg/m3 for PM2.5. We find that primary organic matter and anthropogenic mineral matter (largely coal fly‐ash) drive high PM2.5 levels, both annually and during high PM2.5 episodes. PM2.5 episodes are driven by organic aerosol in north India (Mohali) in wintertime but are additionally influenced by mineral matter and secondary inorganics in central (Bhopal), south India (Mysuru) and eastern India (Shyamnagar). Across airsheds in exceedance of the NAAQS and during high PM2.5 episodes, primary PM2.5 emissions arise largely from the residential sector (50%–75%). Formal sector emissions (industry, thermal power and transport; 40%–55%) drive airshed and episode scale PM2.5 exceedance in northern and eastern India. Agricultural residue burning emissions predominate (50%–75%) on episode scales, both in northern and central India, but not on annual scales. Interestingly, residential sector emissions strongly influence (60%–90%) airsheds in compliance with the NAAQS (annual mean PM2.5 < 40 μg/m3), implying the need for modern residential energy transitions for the reduction of ambient air pollution across India.
Prolonged Quasi‐6‐Day Wave Activities in the Northern Hemisphere MLT Region Due To Antarctic Stratospheric Minor Warming Around September Equinox of 2013 and 2014
Authors: Qin Yusong , Gu Sheng‐Yang , Dou Xiankang , Sun Ruidi , Wei Yafei , Wang Wenxuan , Wang Dong 
Published: July 2024

AbstractThe geopotential height observations from the Aura Microwave Limb Sounder show that the quasi‐6‐day wave (Q6DW) events with westward zonal wavenumber 1 (W1) in the Northern Hemisphere (NH) mesosphere and lower thermosphere (MLT) during September 2013 and 2014 had a prolonged lifetime of ∼45–50 days and reached their maximum amplitudes after the September equinox, while the climatological Q6DW‐W1 is completely dissipated in the background atmosphere before the equinoxes. The Eliassen‐Palm flux diagnostic results indicate that Q6DW‐W1 during September 2013 and 2014 obtained an additional source at ∼60°‐80°S and ∼40–50 km as the September equinox approached, which is related to the baroclinic/barotropic instability in this region. Further investigation on the background atmosphere reveals that several stratospheric minor warming (SMW) events occurred in the Antarctic region during September 2013 and 2014 due to the enhancement of wavenumber 1 activities, accompanied by the increase in the stratospheric temperature, changes in the shape of the polar vortex and the reversal in the zonal mean circulation. The strong planetary wave breaking during the September 2013 and 2014 Antarctic SMW events significantly weakened the strength of the polar night jet (PNJ) and made its peak height descend below ∼35 km, which generated the baroclinic/barotropic instability at the new upper boundary of the PNJ (∼60°‐80°S and ∼40–50 km) by an anomalous double‐jet configuration in the background winds. This unusual instability provided additional wave source and energy for the trans‐equatorial propagation of Q6DW‐W1, which finally led to prolonged wave activities in the NH MLT region.
What Drove the GICs >10 A During the 17 March 2013 Event at Mäntsälä? A Novel Framework for Distinguishing the Magnetospheric Sources
Authors: Waghule Bhagyashree , Knipp D. J. , Gannon J. L. , Billet D. , Vines S. K. , Goldstein J. 
Published: July 2024

AbstractWe combine wavelet analysis and data fusion to investigate geomagnetically induced currents (GICs) on the Mäntsälä pipeline and the associated horizontal geomagnetic field, BH, variations during the late main phase of the 17 March 2013 geomagnetic storm. The wavelet analysis decomposes the GIC and BH signals at increasing “scales” to show distinct multi‐minute spectral features around the GIC spikes. Four GIC spikes >10 A occurred while the pipeline was in the dusk sector—the first sine‐wave‐like spike at ∼16 UT was “compound.” It was followed by three “self‐similar” spikes 2 hr later. The contemporaneous multi‐resolution observations from ground‐(magnetometer, SuperMAG, SuperDARN), and space‐based (AMPERE, Two Wide‐Angle Imaging Neutral‐atom Spectrometers) platforms capture multi‐scale activity to reveal two magnetospheric modes causing the spikes. The GIC at ∼16 UT occurred in two parts with the negative spike associated with a transient sub‐auroral eastward electrojet that closed a developing partial ring current loop, whereas the positive spike developed with the arrival of the associated mesoscale flow‐channel in the auroral zone. The three spikes between 18 and 19 UT were due to bursty bulk flows (BBFs). We attribute all spikes to flow‐channel injections (substorms) of varying scales. We use previously published MHD simulations of the event to substantiate our conclusions, given the dearth of timely in‐situ satellite observations. Our results show that multi‐scale magnetosphere‐ionosphere activity that drives GICs can be understood using multi‐resolution analysis. This new framework of combining wavelet analysis with multi‐platform observations opens a research avenue for GIC investigations and other space weather impacts.
Addressing the need for individual-level exposure monitoring for firefighters using silicone samplers
Authors: Bonner Emily M. , Poutasse Carolyn M. , Haddock Christopher K. , Poston Walker S. C. , Jahnke Sara A. , Tidwell Lane G. , Anderson Kim A. 
Published: July 2024

Abstract
Background
Firefighters are occupationally exposed to hazardous chemical mixtures. Silicone passive sampling devices capture unique exposures over time with minimal impact to the participant and allow for the analysis of a broad chemical space.

Objective
Silicone dog tags were worn by firefighters while on- and off-duty to measure individual exposures, identify potential occupational exposures, and assess their relation to occupational variables including fire response frequency, rank, and years as a firefighter.

Methods
Fifty-six firefighters were recruited from two fire departments with relatively high and low call volumes in the Kansas City metropolitan area to wear two different silicone dog tags as passive samplers while on- and off-duty. Each dog tag was worn for a cumulative 30-day exposure period. Extracts of the dog tags were analyzed with gas chromatography, mass spectrometry methods for 43 flame retardants (FRs), 21 volatile organic compounds (VOCs), 42 polychlorinated biphenyls (PCBs), and 63 polycyclic aromatic hydrocarbons (PAHs).

Results
Ninety-two total chemicals were detected, with eight chemicals not previously reported in firefighter exposure studies. Based on the magnitude and frequency of increased exposure in on-duty dog tags, relative to paired off-duty dog tags, five PBDEs and sec-butylbenzene were identified as potential occupational exposures; sec-butylbenzene and PBDE 49 have not previously been reported in firefighter exposure studies to the authors’ knowledge. Multivariate analyses for these six compounds indicated that firefighter rank, fire response rates, and years in the fire service were poor indicators of increased occupational exposure. The greatest on-duty exposures to PBDEs were found in the low-call volume department among operational firefighters. Dog tags from firefighters at the high-call volume department accounted for 75% of PCB detections; one particular fire response may have contributed to this. Additionally, there was measurable similarity in total chemical exposure profiles between paired on- and off-duty tags for some firefighters.

Impact

This study used personal silicone passive samplers in the configuration of dog tags worn around the neck to quantify firefighter occupational exposure in on-duty samples relative to paired off-duty samples for several chemical categories: flame retardants, VOCs, and PCBs. Five PBDEs and sec-butylbenzene were identified as potential occupational exposures, however their prevalence in on-duty tags was not associated with frequency of fire responses, firefighter rank, or years the firefighter has been in the fire service. Additionally, similarity between chemical exposures in on- and off-duty tags from the same firefighter invites further investigation into individual behaviors influencing occupational and para-occupational exposures.
Increased risk of severe neonatal opioid withdrawal syndrome in pregnancies with low placental ABCB1 DNA methylation
Authors: Townsel Courtney , Truax Burnley , Quaid Margaret , Covault Jonathan , Dolinoy Dana C. , Goodrich Jaclyn M. 
Published: July 2024

Abstract
Background
Neonatal opioid withdrawal syndrome (NOWS) is unpredictable. We assessed relationships between placental DNA methylation with in-utero opioid exposure and NOWS severity.

Methods
Secondary analysis of a prospective multicenter cohort study of pregnancies on methadone or buprenorphine, ≥34 weeks, singleton, 18 or greater. Placental biopsies were collected. Placental DNA methylation levels of ABCG1, ABCG2, CYP19A1, and HSD11B2 were quantified via pyrosequencing following bisulfite conversion. CYP19A1 mRNA levels and umbilical cord drug levels were determined by RT-qPCR and LC-MS respectively. Severe NOWS was diagnosed through Finnegan scoring. P value < 0.05 was significant.

Results
Thirty-eight dyads were included. Promoter region methylation for placental ABCB1 was lower in severe NOWS compared to non-severe NOWS (p = 0.04). Placental CYP19A1 methylation was inversely related to CYP19A1 mRNA levels and associated with umbilical cord norbuprenorphine levels (p < 0.01), but not umbilical cord methadone levels.

Discussion
Lower placental ABCB1 methylation was associated with severe NOWS. Higher placental CYP19A1 methylation correlated with higher umbilical cord norbuprenorphine levels.
Subunit-specific analysis of cohesin-mutant myeloid malignancies reveals distinct ontogeny and outcomes
Authors: Jann Johann-Christoph , Hergott Christopher B. , Winkler Marisa , Liu Yiwen , Braun Benjamin , Charles Anne , Copson Kevin M. , Barua Shougat , Meggendorfer Manja , Nadarajah Niroshan , Shimony Shai , Winer Eric S. , Wadleigh Martha , Stone Richard M. , DeAngelo Daniel J. , Garcia Jacqueline S. , Haferlach Torsten , Lindsley R. Coleman , Luskin Marlise R. , Stahl Maximilian , Tothova Zuzana 
Published: July 2024

AbstractMutations in the cohesin complex components (STAG2, RAD21, SMC1A, SMC3, and PDS5B) are recurrent genetic drivers in myelodysplastic neoplasm (MDS) and acute myeloid leukemia (AML). Whether the different cohesin subunit mutations share clinical characteristics and prognostic significance is not known. We analyzed 790 cohesin-mutant patients from the Dana-Farber Cancer Institute (DFCI) and the Munich Leukemia Laboratory (MLL), 390 of which had available outcome data, and identified subunit-specific clinical, prognostic, and genetic characteristics suggestive of distinct ontogenies. We found that STAG2 mutations are acquired at MDS stage and are associated with secondary AML, adverse prognosis, and co-occurrence of secondary AML-type mutations. In contrast, mutations in RAD21, SMC1A and SMC3 share features with de novo AML with better prognosis, and co-occurrence with de novo AML-type lesions. The findings show the heterogeneous nature of cohesin complex mutations, and inform clinical and prognostic classification, as well as distinct biology of the cohesin complex.
Targeting cytokine and chemokine signaling pathways for cancer therapy
Authors: Yi Ming , Li Tianye , Niu Mengke , Zhang Haoxiang , Wu Yuze , Wu Kongming , Dai Zhijun 
Published: July 2024

AbstractCytokines are critical in regulating immune responses and cellular behavior, playing dual roles in both normal physiology and the pathology of diseases such as cancer. These molecules, including interleukins, interferons, tumor necrosis factors, chemokines, and growth factors like TGF-β, VEGF, and EGF, can promote or inhibit tumor growth, influence the tumor microenvironment, and impact the efficacy of cancer treatments. Recent advances in targeting these pathways have shown promising therapeutic potential, offering new strategies to modulate the immune system, inhibit tumor progression, and overcome resistance to conventional therapies. In this review, we summarized the current understanding and therapeutic implications of targeting cytokine and chemokine signaling pathways in cancer. By exploring the roles of these molecules in tumor biology and the immune response, we highlighted the development of novel therapeutic agents aimed at modulating these pathways to combat cancer. The review elaborated on the dual nature of cytokines as both promoters and suppressors of tumorigenesis, depending on the context, and discussed the challenges and opportunities this presents for therapeutic intervention. We also examined the latest advancements in targeted therapies, including monoclonal antibodies, bispecific antibodies, receptor inhibitors, fusion proteins, engineered cytokine variants, and their impact on tumor growth, metastasis, and the tumor microenvironment. Additionally, we evaluated the potential of combining these targeted therapies with other treatment modalities to overcome resistance and improve patient outcomes. Besides, we also focused on the ongoing research and clinical trials that are pivotal in advancing our understanding and application of cytokine- and chemokine-targeted therapies for cancer patients.