bluuebunny/crossref_metadata_2025_split huggingface dataset:
Advanced 3D TH and THM Modeling to Shed Light on Thermal Convection in Fault Zones With Varying Thicknesses
Authors: Duwiquet H. , Genter A. , Guillou‐Frottier L. , Donzé F. V. , Ledru P. , Magri F. , Guillon T. , Horne R. N. , Arbaret L. , Souque C. 
Published: April 2024

AbstractFault zones exhibit 3D variable thickness, a feature that remains inadequately explored, particularly with regard to the impact on fluid flow. Upon analyzing an analytic solution, we examine 3D thermal‐hydraulic (TH) dynamical models through a benchmark experiment, which incorporates a fault zone with thickness variations corresponding to realistic orders of magnitude. The findings emphasize an area of interest where vigorous convection drives fluid flow, resulting in a temperature increase to 150°C at a shallow depth of 2.7 km in the thickest sections of the fault zone. Moreover, by considering various tectonic regimes (compressional, extensional, and strike‐slip) within 3D thermal‐hydraulic‐mechanical (THM) models and comparing them to the benchmark experiment, we observe variations in fluid pressure induced by poroelastic forces acting on fluid flow within the area of interest. These tectonic‐induced pressure changes influence the thermal distribution of the region and the intensity of temperature anomalies. Outcomes of this study emphasize the impact of poroelasticity‐driven forces on transfer processes and highlight the importance of addressing fault geometry as a crucial parameter in future investigations of fluid flow in fractured systems. Such research has relevant applications in geothermal energy, CO2 storage, and mineral deposits.
Regional Responses of Vegetation Productivity to the Two Phases of ENSO
Authors: Wu Mousong , Jiang Fei , Scholze Marko , Chen Deliang , Ju Weimin , Wang Songhan , Kaminski Thomas , Lu Zhengyao , Vossbeck Michael , Zheng Minjie 
Published: April 2024

AbstractThe two phases of El‐Niño‐Southern Oscillation (ENSO) influence both regional and global terrestrial vegetation productivity on inter‐annual scales. However, the major drivers for the regional vegetation productivity and their controlling strengths during different phases of ENSO remain unclear. We herein disentangled the impacts of two phases of ENSO on regional carbon cycle using multiple data sets. We found that soil moisture predominantly accounts for ∼40% of the variability in regional vegetation productivity during ENSO events. Our results showed that the satellite‐derived vegetation productivity proxies, gross primary productivity from data‐driven models (FLUXCOM) and observation‐constrained ecosystem model (Carbon Cycle Data Assimilation System) generally agree in depicting the contribution of soil moisture and air temperature in modulating regional vegetation productivity. However, the ensemble of weakly constrained ecosystem models exhibits non‐negligible discrepancies in the roles of vapor pressure deficit and radiation over extra‐tropics. This study highlights the significance of water in regulating regional vegetation productivity during ENSO.
First PWV Retrieval Using MERSI‐LL Onboard FY‐3E and Cross Validation With Co‐Platform Occultation and Ground GNSS
Authors: Jiang Nan , Wu Yuhao , Li Song , Xu Yan , Wang Yubo , Xu Tianhe 
Published: April 2024

AbstractFY‐3E plays a vital role in the meteorological global earth observing system. Precipitable water vapor (PWV) is an essential parameter for the water cycle and global climate change. Here, we carry out the PWV retrieval using the MERSI‐LL sensor onboard the FY‐3E satellite for the first time. The retrieval accuracy under different cloudage conditions is validated by the extra PWV from ground‐based GNSS and spaceborne occultation. For the results against ground‐based GNSS, the total accuracy shows an RMSE of 2.69–3.36 mm as the clouds increase, and correlation coefficients higher than 0.95. The spatial accuracy distribution indicates that inland stations have higher accuracy than the coast and island stations. As for the results against spaceborne occultation, the verification accuracy varies with the spatial pairing distance, showing poor accuracy in the low latitude area. This study can provide an essential reference for the community to understand the current water vapor inversion performance of MERSI‐LL.
Data Drought in the Humid Tropics: How to Overcome the Cloud Barrier in Greenhouse Gas Remote Sensing
Authors: Frankenberg C. , Bar‐On Y. M. , Yin Y. , Wennberg P. O. , Jacob D. J. , Michalak A. M. 
Published: April 2024

AbstractDiagnosing land‐atmosphere fluxes of carbon‐dioxide (CO2) and methane (CH4) is essential for evaluating carbon‐climate feedbacks. Greenhouse gas satellite missions aim to fill data gaps in regions like the humid tropics but obtain very few valid measurements due to cloud contamination. We examined data yields from the Orbiting Carbon Observatory alongside Sentinel‐2 cloud statistics. We find that the main contribution to low data yields are frequent shallow cumulus clouds. In the Amazon, the success rate in obtaining valid measurements vary from 0.1% to 1.0%. By far the lowest yields occur in the wet season, consistent with Sentinel‐2 cloud patterns. We find that increasing the spatial resolution of observations to ∼200 m would increase yields by 2–3 orders of magnitude and allow regular measurements in the wet season. Thus, the key to effective tropical greenhouse gas observations lies in regularly acquiring high‐spatial resolution data.
Using Satellite and ARM Observations to Evaluate Cold Air Outbreak Cloud Transitions in E3SM Global Storm‐Resolving Simulations
Authors: Zheng X. , Zhang Y. , Klein S. A. , Zhang M. , Zhang Z. , Deng M. , Tian J. , Terai C. R. , Geerts B. , Caldwell P. , Bogenschutz P. A. 
Published: April 2024

AbstractThis study examines marine boundary layer cloud regime transition during a cold air outbreak (CAO) over the Norwegian Sea, simulated by a global storm‐resolving model (GSRM) known as the Simple Cloud‐Resolving Energy Exascale Earth System Model Atmosphere Model (SCREAM). By selecting observational references based on a combination of large‐scale conditions rather than strict time‐matched comparisons, this study finds that SCREAM qualitatively captures the CAO cloud transition, including boundary layer growth, cloud mesoscale structure, and phase partitioning. SCREAM also accurately locates the greatest ice and liquid in the mesoscale updrafts, however, underestimates supercooled liquid water in cumulus clouds. The model evaluation approach adopted by this study takes advantages of the existing computational‐expensive global simulations of GSRM and the available observations to understand model performance and can be applied to assessments of other cloud regimes in different regions. Such practice provides valuable guidance on the future effort to correct and improve biased model behaviors.
Advances in body composition: a 100-year journey
Authors: Heymsfield Steven B. 
Published: April 2024

Abstract
Knowledge of human body composition at the dawn of the twentieth century was based largely on cadaver studies and chemical analyses of isolated organs and tissues. Matters soon changed by the nineteen twenties when the Czech anthropologist Jindřich Matiegka introduced an influential new anthropometric method of fractionating body mass into subcutaneous adipose tissue and other major body components. Today, one century later, investigators can not only quantify every major body component in vivo at the atomic, molecular, cellular, tissue-organ, and whole-body organizational levels, but go far beyond to organ and tissue-specific composition and metabolite estimates. These advances are leading to an improved understanding of adiposity structure-function relations, discovery of new obesity phenotypes, and a mechanistic basis of some weight-related pathophysiological processes and adverse clinical outcomes. What factors over the past one hundred years combined to generate these profound new body composition measurement capabilities in living humans? This perspective tracks the origins of these scientific innovations with the aim of providing insights on current methodology gaps and future research needs.
Tumour-associated myeloid cells expressing IL-10R2/IL-22R1 as a potential biomarker for diagnosis and recurrence of pancreatic ductal adenocarcinoma
Authors: Lee Hyung Keun , Kim So Young , Chung Soo-Hyun , Choi Bongkun , Kim Ji-Eun , Yoon Dohee , Jang Sung Ill , Yeo Areum , Kang Hyun Goo , Lee Jusung , Choi Yoon Ha , Park Joon Seong , Sung Yoolim , Kim Jong Kyoung , Chang Eun-Ju , Lee Dong Ki 
Published: April 2024

Abstract
Background
Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a poor survival rate, largely due to the lack of early diagnosis. Although myeloid cells are crucial in the tumour microenvironment, whether their specific subset can be a biomarker of PDAC progression is unclear.

Methods
We analysed IL-22 receptor expression in PDAC and peripheral blood. Additionally, we analysed gene expression profiles of IL-10R2+/IL-22R1+ myeloid cells and the presence of these cells using single-cell RNA sequencing and murine orthotropic PDAC models, respectively, followed by examining the immunosuppressive function of IL-10R2+/IL-22R1+ myeloid cells. Finally, the correlation between IL-10R2 expression and PDAC progression was evaluated.

Results
IL-10R2+/IL-22R1+ myeloid cells were present in PDAC and peripheral blood. Blood IL-10R2+ myeloid cells displayed a gene expression signature associated with tumour-educated circulating monocytes. IL-10R2+/IL-22R1+ myeloid cells from human myeloid cell culture inhibited T cell proliferation. By mouse models for PDAC, we found a positive correlation between pancreatic tumour growth and increased blood IL-10R2+/IL-22R1+ myeloid cells. IL-10R2+/IL-22R1+ myeloid cells from an early phase of the PDAC model suppressed T cell proliferation and cytotoxicity. IL-10R2+ myeloid cells indicated tumour recurrence 130 days sooner than CA19-9 in post-pancreatectomy patients.

Conclusions
IL-10R2+/IL-22R1+ myeloid cells in the peripheral blood might be an early marker of PDAC prognosis.
FBXO32-mediated degradation of PTEN promotes lung adenocarcinoma progression
Authors: Wu Jie , Wen Ting , Marzio Antonio , Song Dingli , Chen Sisi , Yang Chengcheng , Zhao Fengyu , Zhang Boxiang , Zhao Guang , Ferri Alessandra , Cheng Hao , Ma Jiao , Ren Hong , Chen Qiao Yi , Yang Yiping , Qin Sida 
Published: April 2024

AbstractFBXO32, a member of the F-box protein family, is known to play both oncogenic and tumor-suppressive roles in different cancers. However, the functions and the molecular mechanisms regulated by FBXO32 in lung adenocarcinoma (LUAD) remain unclear. Here, we report that FBXO32 is overexpressed in LUAD compared with normal lung tissues, and high expression of FBXO32 correlates with poor prognosis in LUAD patients. Firstly, we observed with a series of functional experiments that FBXO32 alters the cell cycle and promotes the invasion and metastasis of LUAD cells. We further corroborate our findings using in vivo mouse models of metastasis and confirmed that FBXO32 positively regulates LUAD tumor metastasis. Using a proteomic-based approach combined with computational analyses, we found a positive correlation between FBXO32 and the PI3K/AKT/mTOR pathway, and identified PTEN as a FBXO32 interactor. More important, FBXO32 binds PTEN via its C-terminal substrate binding domain and we also validated PTEN as a bona fide FBXO32 substrate. Finally, we demonstrated that FBXO32 promotes EMT and regulates the cell cycle by targeting PTEN for proteasomal-dependent degradation. In summary, our study highlights the role of FBXO32 in promoting the PI3K/AKT/mTOR pathway via PTEN degradation, thereby fostering lung adenocarcinoma progression.
Replicative senescence and high glucose induce the accrual of self-derived cytosolic nucleic acids in human endothelial cells
Authors: Ramini Deborah , Giuliani Angelica , Kwiatkowska Katarzyna Malgorzata , Guescini Michele , Storci Gianluca , Mensà Emanuela , Recchioni Rina , Xumerle Luciano , Zago Elisa , Sabbatinelli Jacopo , Santi Spartaco , Garagnani Paolo , Bonafè Massimiliano , Olivieri Fabiola 
Published: April 2024

AbstractRecent literature shows that loss of replicative ability and acquisition of a proinflammatory secretory phenotype in senescent cells is coupled with the build-in of nucleic acids in the cytoplasm. Its implication in human age-related diseases is under scrutiny. In human endothelial cells (ECs), we assessed the accumulation of intracellular nucleic acids during in vitro replicative senescence and after exposure to high glucose concentrations, which mimic an in vivo condition of hyperglycemia. We showed that exposure to high glucose induces senescent-like features in ECs, including telomere shortening and proinflammatory cytokine release, coupled with the accrual in the cytoplasm of telomeres, double-stranded DNA and RNA (dsDNA, dsRNA), as well as RNA:DNA hybrid molecules. Senescent ECs showed an activation of the dsRNA sensors RIG-I and MDA5 and of the DNA sensor TLR9, which was not paralleled by the involvement of the canonical (cGAS) and non-canonical (IFI16) activation of the STING pathway. Under high glucose conditions, only a sustained activation of TLR9 was observed. Notably, senescent cells exhibit increased proinflammatory cytokine (IL-1β, IL-6, IL-8) production without a detectable secretion of type I interferon (IFN), a phenomenon that can be explained, at least in part, by the accumulation of methyl-adenosine containing RNAs. At variance, exposure to exogenous nucleic acids enhances both IL-6 and IFN-β1 expression in senescent cells. This study highlights the accrual of cytoplasmic nucleic acids as a marker of senescence-related endothelial dysfunction, that may play a role in dysmetabolic age-related diseases.
GENESIS CGDYN: large-scale coarse-grained MD simulation with dynamic load balancing for heterogeneous biomolecular systems
Authors: Jung Jaewoon , Tan Cheng , Sugita Yuji 
Published: April 2024

AbstractResidue-level coarse-grained (CG) molecular dynamics (MD) simulation is widely used to investigate slow biological processes that involve multiple proteins, nucleic acids, and their complexes. Biomolecules in a large simulation system are distributed non-uniformly, limiting computational efficiency with conventional methods. Here, we develop a hierarchical domain decomposition scheme with dynamic load balancing for heterogeneous biomolecular systems to keep computational efficiency even after drastic changes in particle distribution. These schemes are applied to the dynamics of intrinsically disordered protein (IDP) droplets. During the fusion of two droplets, we find that the changes in droplet shape correlate with the mixing of IDP chains. Additionally, we simulate large systems with multiple IDP droplets, achieving simulation sizes comparable to those observed in microscopy. In our MD simulations, we directly observe Ostwald ripening, a phenomenon where small droplets dissolve and their molecules redeposit into larger droplets. These methods have been implemented in CGDYN of the GENESIS software, offering a tool for investigating mesoscopic biological processes using the residue-level CG models.
Deviations in RSV epidemiological patterns and population structures in the United States following the COVID-19 pandemic
Authors: Rios-Guzman Estefany , Simons Lacy M. , Dean Taylor J. , Agnes Francesca , Pawlowski Anna , Alisoltanidehkordi Arghavan , Nam Hannah H. , Ison Michael G. , Ozer Egon A. , Lorenzo-Redondo Ramon , Hultquist Judd F. 
Published: April 2024

AbstractRespiratory Syncytial Virus (RSV) is a leading cause of acute respiratory tract infection, with the greatest impact on infants, immunocompromised individuals, and older adults. RSV prevalence decreased substantially in the United States (US) following the implementation of COVID-19-related non-pharmaceutical interventions but later rebounded with abnormal seasonality. The biological and epidemiological factors underlying this altered behavior remain poorly defined. In this retrospective cohort study from 2009 to 2023 in Chicago, Illinois, US, we examined RSV epidemiology, clinical severity, and genetic diversity. We found that changes in RSV diagnostic platforms drove increased detections in outpatient settings post-2020 and that hospitalized adults infected with RSV-A were at higher risk of intensive care admission than those with RSV-B. While population structures of RSV-A remained unchanged, RSV-B exhibited a genetic shift into geographically distinct clusters. Mutations in the antigenic regions of the fusion protein suggest convergent evolution with potential implications for vaccine and therapeutic development.
Bispecific CAR T cell therapy targeting BCMA and CD19 in relapsed/refractory multiple myeloma: a phase I/II trial
Authors: Shi Ming , Wang Jiaojiao , Huang Hongming , Liu Dan , Cheng Hai , Wang Xu , Chen Wei , Yan Zhiling , Sang Wei , Qi Kunming , Li Depeng , Zhu Feng , Li Zhenyu , Qiao Jianlin , Wu Qingyun , Zeng Lingyu , Fei Xiaoming , Gu Weiying , Miao Yuqing , Xu Kailin , Zheng Junnian , Cao Jiang 
Published: April 2024

AbstractDespite the high therapeutic response achieved with B-cell maturation antigen (BCMA)-specific chimeric antigen receptor (CAR) T-cell therapy in relapsed and refractory multiple myeloma (R/R MM), primary resistance and relapse exist with single-target immunotherapy. Here, we design bispecific BC19 CAR T cells targeting BCMA/CD19 and evaluate antimyeloma activity in vitro and in vivo. Preclinical results indicate that BC19 CAR specifically recognize target antigens, and BC19 CAR T cells mediate selective killing of BCMA or CD19-positive cancer cells. BC19 CAR T cells also exhibit potent antigen-specific anti-tumor activity in xenograft mouse models. We conduct an open-label, single-arm, phase I/II study of BC19 CAR T cells in 50 patients with R/R MM (ChiCTR2000033567). The primary endpoint was safety. BC19 CAR T cells are well tolerated with grade 3 or higher cytokine release syndrome in 8% of patients and grade 1 neurotoxic events in 4% of patients, which meet the pre-specified primary endpoint. Secondary endpoints include overall response rate (92%), median progression-free survival (19.7 months), median overall survival (19.7 months) and median duration of response (not reached). Our study demonstrates that bispecific BC19 CAR T cells are feasible, safe and effective in treating patients with R/R MM.
FastMRI Prostate: A public, biparametric MRI dataset to advance machine learning for prostate cancer imaging
Authors: Tibrewala Radhika , Dutt Tarun , Tong Angela , Ginocchio Luke , Lattanzi Riccardo , Keerthivasan Mahesh B. , Baete Steven H. , Chopra Sumit , Lui Yvonne W. , Sodickson Daniel K. , Chandarana Hersh , Johnson Patricia M. 
Published: April 2024

AbstractMagnetic resonance imaging (MRI) has experienced remarkable advancements in the integration of artificial intelligence (AI) for image acquisition and reconstruction. The availability of raw k-space data is crucial for training AI models in such tasks, but public MRI datasets are mostly restricted to DICOM images only. To address this limitation, the fastMRI initiative released brain and knee k-space datasets, which have since seen vigorous use. In May 2023, fastMRI was expanded to include biparametric (T2- and diffusion-weighted) prostate MRI data from a clinical population. Biparametric MRI plays a vital role in the diagnosis and management of prostate cancer. Advances in imaging methods, such as reconstructing under-sampled data from accelerated acquisitions, can improve cost-effectiveness and accessibility of prostate MRI. Raw k-space data, reconstructed images and slice, volume and exam level annotations for likelihood of prostate cancer are provided in this dataset for 47468 slices corresponding to 1560 volumes from 312 patients. This dataset facilitates AI and algorithm development for prostate image reconstruction, with the ultimate goal of enhancing prostate cancer diagnosis.
RAS Dataset: A 3D Cardiac LGE-MRI Dataset for Segmentation of Right Atrial Cavity
Authors: Zhu Jinwen , Bai Jieyun , Zhou Zihao , Liang Yaqi , Chen Zhiting , Chen Xiaoming , Zhang Xiaoshen 
Published: April 2024

AbstractThe current challenge in effectively treating atrial fibrillation (AF) stems from a limited understanding of the intricate structure of the human atria. The objective and quantitative interpretation of the right atrium (RA) in late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) scans relies heavily on its precise segmentation. Leveraging the potential of artificial intelligence (AI) for RA segmentation presents a promising solution. However, the successful implementation of AI in this context necessitates access to a substantial volume of annotated LGE-MRI images for model training. In this paper, we present a comprehensive 3D cardiac dataset comprising 50 high-resolution LGE-MRI scans, each meticulously annotated at the pixel level. The annotation process underwent rigorous standardization through crowdsourcing among a panel of medical experts, ensuring the accuracy and consistency of the annotations. Our dataset represents a significant contribution to the field, providing a valuable resource for advancing RA segmentation methods.
Self-compassion and grit mediated the relation between mindfulness and mind wandering based on cross-sectional survey data
Authors: Cheung Rebecca Y. M. , Djekou Lemuela 
Published: April 2024

AbstractPrevious research suggests that mindfulness and mind wandering are opposing constructs. However, little is known about why and how they are negatively related. Through a process-oriented approach, this cross-sectional study tested self-compassion and grit as mediators for the relation between mindfulness and mind wandering. A total of 487 self-identified meditators were recruited from the UK (241 female, 49.49%). Participants reported a mean age of 38.98 years (SD = 10.03), with an average of 2.26 h of meditation practice per week (SD = 4.47). Upon informed consent, the participants completed a self-report questionnaire that assessed the core variables under study. Path analysis indicated that mindfulness was related to self-compassion. Greater self-compassion was, in turn, related to greater grit, which was then related to lower mind wandering. Bootstrapping analysis further indicated that self-compassion and grit as mediators between mindfulness and mind wandering, above and beyond age, gender, hours of meditation, income, and education as covariates. The cross-sectional findings provided initial evidence of mediation by showing that mindfulness and mind wandering were related through self-compassion and grit.
An all phosphorene lattice nanometric spin valve
Authors: Kumari P. , Majumder S. , Kar S. , Rani S. , Nair A. K. , Kumari K. , Kamalakar M. Venkata , Ray S. J. 
Published: April 2024

AbstractPhosphorene is a unique semiconducting two-dimensional platform for enabling spintronic devices integrated with phosphorene nanoelectronics. Here, we have designed an all phosphorene lattice lateral spin valve device, conceived via patterned magnetic substituted atoms of 3d-block elements at both ends of a phosphorene nanoribbon acting as ferromagnetic electrodes in the spin valve. Through First-principles based calculations, we have extensively studied the spin-dependent transport characteristics of the new spin valve structures. Systematic exploration of the magnetoresistance (MR) of the spin valve for various substitutional atoms and bias voltage resulted in a phase diagram offering a colossal MR for V and Cr-substitutional atoms. Such MR can be directly attributed to their specific electronic structure, which can be further tuned by a gate voltage, for electric field controlled spin valves. The spin-dependent transport characteristics here reveal new features such as negative conductance oscillation and switching of the sign of MR due to change in the majority spin carrier type. Our study creates possibilities for the design of nanometric spin valves, which could enable integration of memory and logic elements for all phosphorene 2D processors.