bluuebunny/crossref_metadata_2025_split huggingface dataset:
Heinrich events drove major intensification of the Indo-Australian monsoon over the last 150,000 years
Authors: Bird Michael , Brand Michael , Comley Rainy , Hadeen Xennephone , Jacobs Zenobia , Rowe Cassandra , Saltré Frédérik , Wurster Christopher , Zwart Costijn , Bradshaw Corey 
Published: March 2024

Abstract
Nearly two thirds of the world’s population depend on monsoon rainfall. Monsoon failure and extreme precipitation have affected societies for millennia. The distribution and amount of monsoon precipitation is predicted to change as the climate warms, albeit with uncertain regional trajectories. Multiple glacial-interglacial terrestrial records of east Asian monsoon variability have been developed, but there are no terrestrial records of equivalent length of the coupled Indo-Australian monsoon at the southern monsoon limit — Australia. Here we present a continuous, absolute-dated, 150,000-year record of monsoon dynamics from a permanent lagoon in the core monsoon region of northern Australia. We show that Australian rainfall is broadly anti-phased with the East Asian monsoon. We identify periods of intense monsoon activity associated with high local insolation in Marine Isotope Stage 5 during ‘megalake’ phases in Australia’s arid interior. We also identify periods of monsoon intensification that are associated with Heinrich events and coincide with weak monsoon events in East Asia. The results suggest that strong asymmetry in inter-hemispheric monsoon rainfall might accompany the current weakening in the strength of the Atlantic meridional overturning circulation. This asymmetry will involve drying in the heavily populated regions north of the equator, and intensification of rainfall in northern Australia.
Description and first insights on a large genomic biobank of lung transplantation
Authors: Limou Sophie , Brocard Simon , Morin Martin , Silva Nayane Dos Santos Brito , Renaud-Picard Benjamin , Coiffard Benjamin , Demant Xavier , Falque Loïc , Pavec Jérome Le , Roux Antoine , Villeneuve Thomas , Knoop Christiane , Mornex Jean-François , Salpin Mathilde , Boussaud Véronique , Rousseau Olivia , Mauduit Vincent , Durand Axelle , Magnan Antoine , Gourraud Pierre-Antoine , Vince Nicolas , Südholt Mario , Tissot Adrien 
Published: March 2024

Abstract

The main limitation to long-term lung transplant (LT) survival is chronic lung allograft dysfunction (CLAD), which leads to irreversible lung damage and significant mortality. Individual factors can impact CLAD, but no large genetic investigation has been conducted to date. We established the multicentric Genetic COhort in Lung Transplantation (GenCOLT) biobank upon the rich and homogeneous COLT cohort. GenCOLT collected DNA, high-quality GWAS (genome-wide association study) genotyping and robust HLA data for donors and recipients to supplement COLT clinical data. GenCOLT closely mirrors the global COLT cohort without significant variations in variables like demographics, initial disease and survival rates (P > 0.05). The GenCOLT donors were 45 years-old on average, 44% women, and primarily died of stroke (54%). The recipients were 48 years-old at transplantation on average, 45% women, and the main underlying disease was chronic obstructive pulmonary disease (45%). The mean follow-up time was 67 months and survival at 5 years was 57.3% for the CLAD subgroup and 97.4% for the stable subgroup. After stringent quality controls, GenCOLT gathered more than 7.3 million SNP and HLA genotypes for 387 LT pairs, including 91% pairs composed of donor and recipient of European ancestry. Overall, GenCOLT is an accurate snapshot of LT clinical practice in France and Belgium between 2009 and 2018. It currently represents one of the largest genetic biobanks dedicated to LT with data available simultaneously for donors and recipients. This unique cohort will empower to run comprehensive GWAS investigations of CLAD and other LT outcomes.
An Integrated Supply Chain Risk Mitigation tool - Model, Analysis, and Insights
Authors: Balan Srinivasan , Handfield Robert 
Published: March 2024

Abstract

In this paper, we propose a two-phase approach that seeks to create insights into disruptions, allowing managers to mitigate supply chain risks using an integrated risk-mitigation tool. In the first phase, the problem is formulated as a Markov Decision Process (MDP) that maximizes the expected long-run revenue induced by supply chain risks, given the current state of the risk score. We map four decision states to four specific managerial actions: "do nothing," "track the supplier," "monitor the supplier," and "change the supplier." If the optimal policy is "do nothing", then the supply chain risk scores are continued to be monitored. In the case of "track the supplier", the firm will track the supplier’s performance internally, however, in the case of "monitor the supplier", the firm will hire an external contractor to monitor the external supply chain risks in the supplier’s country and macroeconomic factors. Lastly, if the optimal policy from phase 1 is to ’change the supplier,’ the best-performing supplier is identified using an integrated best-worst goal programming (BWGP) method as a multi-criteria decision-making (MCDM) method. This second phase of decision support can help allocate supply contracts to the least risky supplier. We demonstrate the integrated risk-based model and the proposed best-worst goal programming (BWGP) method on a global automation technologies company and share the risk-mitigating capability as a case study. Results based on consistency ratio, conformity, and total deviation show that the BWGP performs better than the other MCDM methods and can be used effectively in the integrated two-phase approach with MDP as a supply chain risk mitigation tool.
The screening evaluation of environmental odors: a new dispersion modelling-based tool
Authors: Pelliconi Martina , Andretta Massimo , Righi Serena 
Published: March 2024

Abstract

Odor pollution is the biggest source of complaints from citizens concerning environmental issues after noise. Often, the need for corrective actions is evaluated through simulations performed with atmospheric dispersion models. To save resources, air pollution control institutions perform a first-level odor impact assessment, for screening purposes. This is often based on Gaussian Dispersion Models (GDM), which can be executed through user-friendly software that doesn’t need high computational power. However, their outputs tend to be excessively conservative regarding the analyzed situation, rather than representative of the real in-site conditions. Hence, regulations and guidelines adopted at an institutional level for authorization/control purposes, are based on Lagrangian Particle Dispersion Models (LPDM). These grant a more accurate modelling of the pollutants’ dispersion but are very demanding regarding both the needed users’ technical skills and high computing power. The present study aims to increase the accuracy of screening odor impact assessment, by identifying the correlation function of the outputs derived from the two simulation models. The case-study is placed in northern Italy, where a single-point source, with various stack heights, was considered. The identified correlation functions could allow institutions to estimate the results that would have been forecasted with the application of the more complex LPDM, applying, however, the much simpler GDM. This grants an accurate tool which can be used to address citizens’ concerns while saving workforce and technical resources.
Z-DNA formation in promoters conserved between human and mouse are associated with increased transcription initiation rates
Authors: Popstova Maria , Herbert Alan , Beknazarov Nazar , Konovalov Dmitrii 
Published: March 2024

Abstract

A long-standing question concerns the role of Z-DNA in transcription. Here we use a deep learning approach DeepZ that predicts Z-flipons based on DNA sequence, structural properties of nucleotides and omics data. We examined Z-flipons that are conserved between human and mouse genomes after generating whole-genome Z-flipon map and then validated them by orthogonal approaches based on high resolution chemical mapping of Z-DNA and the transformer algorithm Z-DNABERT. For human and mouse, we revealed similar pattern of transcription factors, chromatin remodelers, and histone marks associated with conserved Z-flipons. We found significant enrichment of Z-flipons in alternative and bidirectional promoters associated with neurogenesis genes. We show that conserved Z-flipons are associated with increased experimentally determined transcription initiation rates compared to promoters without Z-flipons, but without affecting elongation or pausing. Our findings support a model where Z-flipons impact phenotype by regulating the reset of preinitiation complexes.
Molecular architecture of primate specific neural circuit formation
Authors: Shimogori Tomomi , Onishi Kohei , Hoshino Takafumi , Nakanishi Moe 
Published: March 2024

Abstract
The mammalian cortex is a highly evolved brain region, but we still lack a comprehensive understanding of the molecular mechanisms underlying primate-specific neural circuits formation. In this study, we employed spatial transcriptomics to assess gene expression dynamics in the marmoset cortex during development, focusing on key regions and time points. Spatial transcriptomics identified genes that are sexually, spatially, and temporally differentially expressed in the developing marmoset cortex. Our detailed analysis of the visual cortex unveiled dynamic changes in gene expression across layers with distinct projections and functions. Notably, we discovered numerous axon guidance molecules with spatiotemporal expression patterns unique to the developing marmoset prefrontal cortex (PFC), which control PFC neuronal circuits. Among these molecules, PRSS12 (Protease, Serine, 12 (neurotrypsin, motopsin), when ectopically expressed in the mouse prelimbic cortex, caused similar changes in connectivity as observed in the marmoset A32 area. Furthermore, PRSS12 showed similar expression patterns in both marmoset and human PFC during development, suggesting parallels between marmoset and human brain development. The differential expression of axon guidance molecules in the developing PFC, varying by region, likely contributes to the formation of unique circuits observed in primates.
A modular framework for treatment effect estimation in latent subgroups
Authors: Lindhagen Lars , Garmo Hans , Östlund Ollie 
Published: March 2024

Abstract
Latent subgroups arise when patients are randomized to an intended treatment, that can only be given for certain, treatable, patients. For biological efficacy, the relevant estimand is then the treatment effect in the subgroup of treatable patients, with the obvious issue that this subgroup is latent, identified only in the intervention arm.
We present a modular framework for effect estimation in such latent subgroups. The framework consists of a core and three plug-in models, for subgroup membership and outcomes among treatable and non-treatable patients. The core computes maximum likelihood estimates using the EM algorithm, together with standard errors. It does so without any knowledge about the details of the plug-in models, giving the user great flexibility. The methods are implemented in an R package.
The framework is validated in a simulation, where we also explore the use of predictors. Particularly intriguing are predictors of treatability, partly identifying the latent subgroup from baseline data. The results suggest that this can dramatically increase the power, while being robust against model misspecifications. Finally, the methods are applied to a prostate cancer trial.
Flavones enrich rhizosphere Pseudomonas to enhance nitrogen utilization and lateral root growth in Populus
Authors: Xie Jianbo , Zhang Deqiang , Wu Jiadong , Liu Sijia , Wang Yue , Si Jingna , Chen Sisi , Tan Shuxian , Du Yuxin , Jin Zhelun 
Published: March 2024

Abstract

Plant growth behavior is a function of genetic network architecture. The importance of root microbiome variation driving plant functional traits is increasingly recognized, but the genetic mechanisms governing this variation are less studied. Here, we collected roots and rhizosphere soils from nine Populus species belonging to four sections, generated metabolite and transcription data for roots and microbiota data for rhizospheres, and conducted comprehensive multi-omics analyses. We demonstrated that the roots of robust Leuce poplar enriched more plant growth-promoting rhizobacteria, which compared with the poorly performing poplar, agreeing with the ‘Matthew effect’ on poplar-microbe interaction. Moreover, we confirmed that Pseudomonas was strongly associated with tricin and apigenin biosynthesis and identified that gene GL3 was critical for tricin secretion. The elevated tricin secretion via constitutive transcription of PopGL3 and PopCHS4 could drive Pseudomonas colonization in the rhizosphere and further enhance poplar growth, nitrogen acquisition, and lateral root development in nitrogen-poor soil. This study reveals plant-metabolite-microbe regulation patterns contribute to the poplar fitness and thoroughly decoded the key regulatory mechanisms of tricin, and provided new insights into the interactions of the plant’s key metabolites with its transcriptome, rhizosphere microbes.
Improving prognostication of pneumonia among elderly patients: usefulness of suPAR
Authors: Ulaj Artida , Ibsen Arni , Azurmendi Leire , Sanchez Jean-Charles , Prendki Virginie , Roux Xavier 
Published: March 2024

Abstract

Purpose:Elderly patients with suspected pneumonia represent a significant proportion of hospital admissions, which is a prognostic challenge for physicians. Our research aimed to assess the prognosis of patients with pneumonia using soluble urokinase plasminogen activator receptor (suPAR) combined with clinical data.
Methods:In a prospective observational study including 164 patients >65 years (mean age 84.2 (+/-7.64) years) who were hospitalized for a suspicion of pneumonia, suPAR was assessed for each patient, as was the prognosis score (PSI, CURB65) and inflammatory biomarkers (C-reactive protein, procalcitonin, white blood cells). The prognostic value of the suPAR for 30-day mortality was assessed using receiver operating characteristic (ROC) curve analyses. Optimal cut-offs with corresponding sensitivity (SE) and specificity (SP) were determined using the Youden index.
Results:A suPAR >5.1 ng/mL was predictive of 30-day mortality with a sensitivity of 100% and a specificity of 40.4%. A combination of the following parameters exhibited an SE of 100% (95% CI, 100–100) for an SP value of 64.9% (95% CI, 57.6-72.2) when at least two of them were above or below the following cut-off threshold values: suPAR > 9.8 ng/mL, BMI < 29.3 kg/m2 and PSI >106.5.
Conclusion:The suPAR seems to be a promising biomarker that can be combined with the PSI and BMI to improve the prognosis of pneumonia among elderly patients. Prospective studies with larger populations are needed to confirm whether this new approach can improve patient outcomes.
CD109 drives pro-tumorigenic cell properties in human non-small cell lung cancer through interaction with desmoglein-2
Authors: Lückstädt Wiebke , Rathod Maitreyi , Möbus Lena , Bub Simon , Lucius Ralph , Elsner Felix , Spindler Volker , Arnold Philipp 
Published: March 2024

Abstract
Cluster of differentiation 109 (CD109) is a glycosylphosphatidylinositol (GPI) anchored cell surface protein, expressed on epithelial and endothelial cells, CD4+ and CD8+ T-cells, and premature lymphocytes. CD109 interacts with different cell surface receptors and thereby modulates intracellular signaling pathways, which ultimately changes cellular functions. One well-studied example is the interaction of CD109 with the TGFβ/TGFβ-receptor complex at the cell surface. CD109 silences intracellular SMAD2/3 signaling and targets TGFβ/TGFβ-receptor to the endosomal/lysosomal compartment. In recent years, CD109 emerged as a tumor marker for different tumor entities and expression of CD109 could be linked to adverse outcome in patients. In this study, we show that silencing of CD109 in human non-small cell lung cancer (NSCLC) cells, returns these cells to an epithelial like growth phenotype. On the transcriptional level, we describe changes in cell-cell contact and epithelial-mesenchymal transition associated gene clusters. At the cell surface, we identify desmoglein-2 (DSG2) as a new interaction partner of CD109 and demonstrate CD109 dependent targeting of DSG2 to the apical cell surface, where it forms desmosomes between apical and basal cell poles. Both, CD109 and DSG2 are genetic risk factors, linked to reduced overall survival in lung adenocarcinoma patients (subtype of NSCLC). In this study, we show the expression of both proteins in the same tumor and suggest a new CD109-DSG2 axis in NSCLC patients that could present a targetable therapeutic option in the future.
GRK6 promotes triple-negative breast cancer metastasis via recruiting the β-Arrestin 2/MAPKs/NF-κB signaling axis
Authors: Wang Wen-Ke , Lin Hui-Yu , Lin Che-Hsuan , Lee Hsun-Hua , Chen Yen-Lin , Lin Yu -Hsien Kent , Sheen-Chen Shry-Ming , Lin Yuan-Feng 
Published: March 2024

Abstract
Background: Triple negative breast cancer (TNBC) belongs to the worst prognosis of breast cancer subtype probably because of distant metastasis to other organs, e.g. lungs. However, the mechanism underlying TNBC metastasis remains largely unknown.
Methods: Bioinformatics analysis was conducted to evaluate the mRNA/protein expression and prognostic significance of G protein–coupled receptor kinase 6 (GRK6) in BC subtypes. RT-PCR assays were used to test the GRK6 expression in human BC tissues and cell lines. The in vitrocellular migration and in vivo lung colony-forming assays were established to estimate the metastatic potentials of TNBC cells. Western blotting was employed to examine protein phosphorylation, translocation and expression in the designed experiments.
Results: Here we show that GRK6 upregulation is extensively detected in TNBC compared to normal mammary tissues and other BC subtypes and correlates with an increased risk for distant metastasis in TNBC patients. GRK6 knockdown suppressed but overexpression potentiated the cellular migration and lung colony-forming abilities of TNBC cells. Moreover, our data demonstrated that the posttranslational palmitoylation of GRK6 is extremely critical for activating b-Arrestin 2/mitogen-activated protein kinases (MAPKs)/NF-kB signaling axis and fostering the metastatic potentials of TNBC cells. Accordingly, the pharmaceutical inhibition of GRK6 kinase activity dramatically suppressed the activation of b-Arrestin 2, MAPKs and NF-kB and the cellular migration ability of highly metastatic MDA-MB231 cells.
Conclusion: Our results not only provide a novel mechanism for TNBC metastasis but also offer a new therapeutic strategy to combat metastatic TNBC via targeting GRK6 activity.
An Efficient Matching Method for Causal Inference Using Sufficient Dimension Reduction
Authors: Cheng Debo , Xie Yang , Li Jiuyong , Liu Lin , Zhao Haoran , Zhang Yinghao , Feng Zaiwen 
Published: March 2024

Abstract

Estimating the causal effect of a treatment on an outcome of interest, i.e., causal effect estimation, is critical to understanding the mechanism underlying the data in various domains. However, the estimation of causal effects, particularly with high-dimensional data, is challenging due to the presence of high-dimensional catastrophes and complex relationships between variables. While matching is a commonly used method for causal effect estimation from observational data, it fails to address the curse of dimensionality associated with high-dimensional data. In this work, we propose a solution to the dimensionality catastrophe problem using the property of sufficient dimension reduction (SDR) method for the average treatment effect (ATE) and conditional average treatment effect (CATE) estimation. Theoretically, we demonstrate that the reduced covariates corresponding to the outcome variable obtained through SDR is a balance score for ATE and CATE estimation. Based on the proposed theorem, we propose an efficient nearest neighbor Matching method (MIRE) using the Inverse Regression Estimator to learn a low-dimensional set from the original covariates for ATE and CATE estimation. Experimental results on two semi-synthetic datasets show that the proposed MIRE method is sufficient for ATE and CATE estimation from 1 observational data. Furthermore, experiments conducted on real-world data have shown the potential of the proposed MIRE method.
Spatiotemporal variation in carbon sequestration in the forest ecosystem of Hainan Island over a 30-year period and its driving factors
Authors: Pi ZhiHao , Wang Xu , Zang Zhuo , Song XiQang , Zhou GuangYi , Guo Hao , BaoYin ManDa , Zhao HouBen , Li ZhaoJia , Qiu ZhiJun , Wu ZhongMin 
Published: March 2024

Abstract
This study examines long-term carbon sequestration in the forest ecosystems of Hainan Island from 1990 to 2020 using the InVEST model and a geographic detector technique. We analysed changes in land use and forest cover, observing an 85.78%, 87.55%, and 256.96% decrease in undeveloped, shrub-covered, and burned urbanised land, respectively. Urbanised land increased by 4.01% annually. Forested land decreased by 3.62%, agricultural land expanded by 5.27%, and aquatic bodies decreased by 2.05%. The forest ecosystems sequestered 335.09–372.80 TgC of carbon, showing an upward trend from 1991 to 1997, a decline from 1997 to 2004, an increase from 2004 to 2010, a decrease from 2010 to 2015, and overall stability from 2015 to 2020. Spatial clustering analysis revealed substantial clustering of carbon sequestration, with central mountainous regions exhibiting elevated levels, coastal areas having diminished levels, the east experiencing higher levels than the west, and the south showing escalated levels compared to the north. Geographical detector analysis identified NDVI, elevation, and slope as primary drivers of spatial variance in carbon sequestration. Forested area changes and government forestry policies played a pivotal role in enhancing carbon sequestration. The combined effect of NDVI and elevation normalisation on vegetation coverage had the most potent synergistic impact.