bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantifying Relative Contribution of Submerged Macrophytes to Sedimentary Organic Matter Using Concentrations and δ13C of n‐Alkanes With the Bayesian Multi‐Source Mixing Model: A Case Study From the Yangtze Floodplain
Authors: Zeng Linghan , Huang Xianyu , Yang Deming , Yang Guang , Zhang Yiming , Chen Xu 
Published: September 2024

AbstractSubmerged macrophytes are important indicators of the state of shallow freshwater ecosystems. Reconstruction long‐term changes in submerged macrophytes remains a challenge in paleoecology. Here, the relative biomass (mass weight) of different plants to sedimentary organic matter in a shallow lake in central China was estimated using a Bayesian multi‐source mixing model with concentrations and δ13C of n‐alkanes extracted from surface lake sediments. The spatial distribution of submerged macrophytes biomass estimated by the model correlates with water transparency, water depth, and total nitrogen. The correlation patterns are consistent with previously established patterns of submerged macrophyte growth and water conditions, which supports the utility of the Bayesian approach in shallow freshwater lakes. In comparison, Paq, proportion of mid‐chain length (C23, C25) to long‐chain length (C29, C31) homologs, underestimated the contribution of submerged macrophytes, especially in samples with moderate Paq values (0.3 < Paq < 0.4). On the other hand, some discrepancies between the model output and the satellite imagery estimated macrophyte coverage are present, which suggests that ground‐truthing is needed to further evaluate this approach. Our study demonstrates that the Bayesian mixing model combining the abundance and isotopes of n‐alkanes makes a reasonable estimation of the relative biomass of submerged macrophytes in the sediments. This approach provides new insights into reconstructing long‐term variations in submerged macrophytes for paleoecological studies, which is valuable for the restoration and conservation of shallow freshwater lakes when long‐term limnological monitoring is lacking.
IKKε-deficient macrophages impede cardiac repair after myocardial infarction by enhancing the macrophage–myofibroblast transition
Authors: Cho Hyang Hee , Rhee Siyeon , Cho Dong Im , Jun Ju Hee , Heo HyoJung , Cho Su Han , Kim Dohyup , Wang Mingqiang , Kang Bo Gyeong , Yoo Soo Ji , Cho Meeyoung , Lim Soo yeon , Cho Jae Yeong , Jeong In Seok , Kim Yong Sook , Ahn Youngkeun 
Published: September 2024

AbstractThe regulatory role of the inhibitor of NF-kB kinase ε (IKKε) in postmyocardial infarction (MI) inflammation remains uncertain. Using an MI mouse model, we examined the cardiac outcomes of IKKε knockout (KO) mice and wild-type mice. We employed single-cell RNA sequencing (scRNA-seq) and phosphorylated protein array techniques to profile cardiac macrophages. IKKε KO mice exhibited compromised survival, heightened inflammation, pronounced cardiac fibrosis, and a reduced ejection fraction. A distinct cardiac macrophage subset in IKKε KO mice exhibited increased fibrotic marker expression and decreased phosphorylated p38 (p-p38) levels, indicating an enhanced macrophage–myofibroblast transition (MMT) post-MI. While cardiac inflammation is crucial for initiating compensatory pathways, the timely resolution of inflammation was impaired in the IKKε KO group, while the MMT in macrophages accelerated post-MI, leading to cardiac failure. Additionally, our study highlighted the potential of 5-azacytidine (5-Aza), known for its anti-inflammatory and cardioprotective effects, in restoring p-p38 levels in stimulated macrophages. The administration of 5-Aza significantly reduced the MMT in cardiac macrophages from the IKKε KO group. These findings underscore the regulation of the inflammatory response and macrophage transition by the IKKε-p38 axis, indicating that the MMT is a promising therapeutic target for ischemic heart disease.
Live birth and maternity outcome in childhood and adolescent cancer survivors under 18 years at diagnosis: a 40-year population-based cohort study
Authors: Wallace W. H. , Kelsey T. W. , Morrison D. , Anderson R. A. 
Published: September 2024

Abstract
Background
Survival from childhood and adolescent cancer has increased, but the chance of a livebirth in female survivors under 18 years at diagnosis may be reduced.

Methods
We performed a national population-based analysis, including all female cancer survivors diagnosed in Scotland before the age of 18 years between 1981 and 2012. Scottish Cancer Registry records were linked to Scottish maternity records. Females from the exposed group with no pregnancies before cancer diagnosis (n = 2118) were compared with three general population controls matched for age and year of diagnosis.

Findings
The cumulative incidence of a livebirth for all diagnoses was reduced to 37% (95% CI 33–40%) for cancer survivors at 30 years of age vs 58% (57–60%) for controls. The deficit varying by diagnosis: for lymphoid leukaemia, the cumulative incidence at 30 years was 29% (23–36%) vs 57% (52–61%) for controls with similar deficits in CNS tumours and retinoblastoma. There was a steady improvement in the chance of livebirth in those diagnosed more recently.

Interpretation
We have shown a reduced chance of livebirth in female survivors of cancer diagnosed before age 18. The deficit is present for all diagnoses.
CD36-mediated ferroptosis destabilizes CD4+ T cell homeostasis in acute Stanford type-A aortic dissection
Authors: Li Hui , Wang Peng-Fei , Luo Wei , Fu Di , Shen Wei-Yun , Zhang Yan-Ling , Zhao Shuai , Dai Ru-Ping 
Published: September 2024

AbstractAcute type A aortic dissection (ATAAD) is a lethal pathological process within the aorta with high mortality and morbidity. T lymphocytes are perturbed and implicated in the clinical outcome of ATAAD, but the exact characteristics of T cell phenotype and its underlying mechanisms in ATAAD remain poorly understood. Here we report that CD4+ T cells from ATAAD patients presented with a hypofunctional phenotype that was correlated with poor outcomes. Whole transcriptome profiles showed that ferroptosis and lipid binding pathways were enriched in CD4+ T cells. Inhibiting ferroptosis or reducing intrinsic reactive oxygen species limited CD4+ T cell dysfunction. Mechanistically, CD36 was elevated in CD4+ T cells, whose blockade effectively alleviated palmitic acid-induced ferroptosis and CD4+ T cell hypofunction. Therefore, targeting the CD36-ferroptosis pathway to restore the functions of CD4+ T cells is a promising therapeutic strategy to improve clinical outcomes in ATAAD patients.
Pervasive heteroplasmy in an invasive ambrosia beetle (Scolytinae) in southern California
Authors: Rugman-Jones Paul F. , Dodge Christine E. , Stouthamer Richard 
Published: September 2024

AbstractHeteroplasmy, the presence of multiple mitochondrial genotypes (mitotypes) within an individual, has long been thought to be a rare aberrance that is quickly removed by selection or drift. However, heteroplasmy is being reported in natural populations of eukaryotes with increasing frequency, in part due to improved diagnostic methods. Here, we report a seemingly stable heteroplasmic state in California populations of the polyphagous shothole borer (PSHB), Euwallacea fornicatus; an invasive ambrosia beetle that is causing significant tree dieback. We develop and validate a qPCR assay utilizing locked nucleic acid probes to detect different mitotypes, and qualitatively assess heteroplasmy in individual PSHB. We prove the utility of this assay by: (1) mitotyping field-collected PSHB, documenting the prevalence of heteroplasmy across its range in California; and, (2) measuring relative titers of each mitotype across multiple generations of heteroplasmic laboratory colonies to assess the stability of transmission through the maternal germline. We show that our findings are unlikely to be explained by the existence of NUMTs by next generation sequencing of contiguous sections of mitochondrial DNA, where each of the observed heteroplasmic sites are found within fully functional coding regions of mtDNA. Subsequently, we find heteroplasmic individuals are common in Californian field populations, and that heteroplasmy persists for at least 10 generations in experimental colonies. We also looked for evidence of the common occurrence of paternal leakage, but found none. In light of our results, we discuss competing hypotheses as to how heteroplasmy may have arisen, and continues to perpetuate, in Californian PSHB populations.
Adipocyte inflammation is the primary driver of hepatic insulin resistance in a human iPSC-based microphysiological system
Authors: Qi Lin , Groeger Marko , Sharma Aditi , Goswami Ishan , Chen Erzhen , Zhong Fenmiao , Ram Apsara , Healy Kevin , Hsiao Edward C. , Willenbring Holger , Stahl Andreas 
Published: September 2024

AbstractInteractions between adipose tissue, liver and immune system are at the center of metabolic dysfunction-associated steatotic liver disease and type 2 diabetes. To address the need for an accurate in vitro model, we establish an interconnected microphysiological system (MPS) containing white adipocytes, hepatocytes and proinflammatory macrophages derived from isogenic human induced pluripotent stem cells. Using this MPS, we find that increasing the adipocyte-to-hepatocyte ratio moderately affects hepatocyte function, whereas macrophage-induced adipocyte inflammation causes lipid accumulation in hepatocytes and MPS-wide insulin resistance, corresponding to initiation of metabolic dysfunction-associated steatotic liver disease. We also use our MPS to identify and characterize pharmacological intervention strategies for hepatic steatosis and systemic insulin resistance and find that the glucagon-like peptide-1 receptor agonist semaglutide improves hepatocyte function by acting specifically on adipocytes. These results establish our MPS modeling the adipose tissue-liver axis as an alternative to animal models for mechanistic studies or drug discovery in metabolic diseases.
Virtual birefringence imaging and histological staining of amyloid deposits in label-free tissue using autofluorescence microscopy and deep learning
Authors: Yang Xilin , Bai Bijie , Zhang Yijie , Aydin Musa , Li Yuzhu , Selcuk Sahan Yoruc , Casteleiro Costa Paloma , Guo Zhen , Fishbein Gregory A. , Atlan Karine , Wallace William Dean , Pillar Nir , Ozcan Aydogan 
Published: September 2024

AbstractSystemic amyloidosis involves the deposition of misfolded proteins in organs/tissues, leading to progressive organ dysfunction and failure. Congo red is the gold-standard chemical stain for visualizing amyloid deposits in tissue, showing birefringence under polarization microscopy. However, Congo red staining is tedious and costly to perform, and prone to false diagnoses due to variations in amyloid amount, staining quality and manual examination of tissue under a polarization microscope. We report virtual birefringence imaging and virtual Congo red staining of label-free human tissue to show that a single neural network can transform autofluorescence images of label-free tissue into brightfield and polarized microscopy images, matching their histochemically stained versions. Blind testing with quantitative metrics and pathologist evaluations on cardiac tissue showed that our virtually stained polarization and brightfield images highlight amyloid patterns in a consistent manner, mitigating challenges due to variations in chemical staining quality and manual imaging processes in the clinical workflow.
Context-aware single-cell multiomics approach identifies cell-type-specific lung cancer susceptibility genes
Authors: Long Erping , Yin Jinhu , Shin Ju Hye , Li Yuyan , Li Bolun , Kane Alexander , Patel Harsh , Sun Xinti , Wang Cong , Luong Thong , Xia Jun , Han Younghun , Byun Jinyoung , Zhang Tongwu , Zhao Wei , Landi Maria Teresa , Rothman Nathaniel , Lan Qing , Chang Yoon Soo , Yu Fulong , Amos Christopher I. , Shi Jianxin , Lee Jin Gu , Kim Eun Young , Choi Jiyeon 
Published: September 2024

AbstractGenome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, underlying mechanisms and target genes are largely unknown, as most risk-associated variants might regulate gene expression in a context-specific manner. Here, we generate a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Identified candidate cis-regulatory elements (cCREs) are largely cell type-specific, with 37% detected in one cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs combined with transcription factor footprinting prioritize the variants for 68% of the GWAS loci. CCV-colocalization and trait relevance score indicate that epithelial and immune cell categories, including rare cell types, contribute to lung cancer susceptibility the most. A multi-level cCRE-gene linking system identifies candidate susceptibility genes from 57% of the loci, where most loci display cell-category-specific target genes, suggesting context-specific susceptibility gene function.
Highly-stable, injectable, conductive hydrogel for chronic neuromodulation
Authors: Yang Ming , Wang Lufang , Liu Wenliang , Li Wenlong , Huang Yewei , Jin Qiaofeng , Zhang Li , Jiang Yuanwen , Luo Zhiqiang 
Published: September 2024

AbstractElectroceuticals, through the selective modulation of peripheral nerves near target organs, are promising for treating refractory diseases. However, the small sizes and the delicate nature of these nerves present challenges in simplifying the fixation and stabilizing the electrical-coupling interface for neural electrodes. Herein, we construct a robust neural interface for fine peripheral nerves using an injectable bio-adhesive hydrogel bioelectronics. By incorporating a multifunctional molecular regulator during network formation, we optimize the injectability and conductivity of the hydrogel through fine-tuning reaction kinetics and multi-scale interactions within the conductive network. Meanwhile, the mechanical and electrical stability of the hydrogel is achieved without compromising its injectability. Minimal tissue damage along with low and stable impedance of the injectable neural interface enables chronic vagus neuromodulation for myocardial infarction therapy in the male rat model. Our highly-stable, injectable, conductive hydrogel bioelectronics are readily available to target challenging anatomical locations, paving the way for future precision bioelectronic medicine.
Navigation performance in glaucoma: virtual-reality-based assessment of path integration
Authors: Andac Safa , Stolle Francie H. , Bernard Matthieu , Al-Nosairy Khaldoon O. , Wolbers Thomas , Hoffmann Michael B. 
Published: September 2024

AbstractNavigation is essential for moving between locations in our daily lives. We investigated the relationship between visual impairment in glaucoma and path-integration-based navigation. Fourteen glaucoma and 15 controls underwent ophthalmological examination (including visual acuity (logMAR), visual field sensitivity (MD: mean deviation from matched reference cohort), and peripapillary retinal nerve fiber layer (pRNFL)). Both groups navigated physically in virtual reality (VR) environments during daylight and dawn conditions. Briefly, the participants traversed a path marked by three targets, subsequently pointing back to the path’s origin. Outcome measures included (i) travel-time, (ii) pointing-time, and (iii) Euclidian-distance error between indicated and starting position. Robust linear regression was conducted between visual function outcomes of the better eye and VR outcome measures. Glaucoma patients showed increase in travel-time (by 8.2 ± 1.7 s; p = 0.002) and in pointing-time (by 5.3 ± 1.6 s; p = 0.016). Predictors were MD for all outcome measures (p < 0.01) and pRNFL for travel-time (p < 0.01). The results suggest that the effect of glaucoma on the elapsed time depends on disease progression, i.e. people with stronger visual impairment need more time. This uncertainty during everyday navigation tasks may adversely affect their quality of life.
Analyzing spatio-temporal dynamics of dissolved oxygen for the River Thames using superstatistical methods and machine learning
Authors: He Hankun , Boehringer Takuya , Schäfer Benjamin , Heppell Kate , Beck Christian 
Published: September 2024

AbstractBy employing superstatistical methods and machine learning, we analyze time series data of water quality indicators for the River Thames (UK). The indicators analyzed include dissolved oxygen, temperature, electrical conductivity, pH, ammonium, turbidity, and rainfall, with a specific focus on the dynamics of dissolved oxygen. After detrending, the probability density functions of dissolved oxygen fluctuations exhibit heavy tails that are effectively modeled using q-Gaussian distributions. Our findings indicate that the multiplicative Empirical Mode Decomposition method stands out as the most effective detrending technique, yielding the highest log-likelihood in nearly all fittings. We also observe that the optimally fitted width parameter of the q-Gaussian shows a negative correlation with the distance to the sea, highlighting the influence of geographical factors on water quality dynamics. In the context of same-time prediction of dissolved oxygen, regression analysis incorporating various water quality indicators and temporal features identify the Light Gradient Boosting Machine as the best model. SHapley Additive exPlanations reveal that temperature, pH, and time of year play crucial roles in the predictions. Furthermore, we use the Transformer, a state-of-the-art machine learning model, to forecast dissolved oxygen concentrations. For long-term forecasting, the Informer model consistently delivers superior performance, achieving the lowest Mean Absolute Error (0.15) and Symmetric Mean Absolute Percentage Error (21.96%) with the 192 historical time steps that we used. This performance is attributed to the Informer’s ProbSparse self-attention mechanism, which allows it to capture long-range dependencies in time-series data more effectively than other machine learning models. It effectively recognizes the half-life cycle of dissolved oxygen, with particular attention to critical periods such as morning to early afternoon, late evening to early morning, and key intervals between the 16th and 26th quarter-hours of the previous half-day. Our findings provide valuable insights for policymakers involved in ecological health assessments, aiding in accurate predictions of river water quality and the maintenance of healthy aquatic ecosystems.
Stable and sustainable perovskite solar modules by optimizing blade coating nickel oxide deposition over 15 × 15 cm2 area
Authors: Jafarzadeh Farshad , Castriotta Luigi Angelo , Calabrò Emanuele , Spinelli Pierpaolo , Generosi Amanda , Paci Barbara , Becerril Rodriguez David , Luce Marco , Cricenti Antonio , Di Giacomo Francesco , Matteocci Fabio , Brunetti Francesca , Di Carlo Aldo 
Published: September 2024

AbstractPerovskite solar cells have rapidly advanced, achieving over 26% power conversion efficiency on the laboratory scale. However, transitioning to large-scale production remains a challenge due to limitations in conventional fabrication methods like spin coating. Here, we introduce an optimized blade coating process for the scalable fabrication of large-area (15 cm × 15 cm) perovskite solar modules with a nickel oxide hole transport layer, performed in ambient air and utilizing a non-toxic solvent system. Self-assembled monolayers between the nickel oxide and perovskite layer improve the uniformity and morphology of the perovskite film. Perovskite solar modules with a 110 cm2 active area achieve a power conversion efficiency of 12.6%. Moreover, encapsulated modules retained 84% of their initial efficiency after 1,000 hours at 85 °C in air (ISOS-T-1). This study demonstrates progress in the large-scale production of perovskite solar cells that combine efficiency with long-term stability.
Overview and recommendations for research on plants and microbes in regolith-based agriculture
Authors: Fackrell Laura E. , Humphrey Samson , Loureiro Rafael , Palmer Andrew G. , Long-Fox Jared 
Published: September 2024

AbstractThe domestication of agriculture is widely recognized as one of the most crucial technological adaptations for the transition of humanity from hunter-and-gatherer groups into early city-states and ultimately, complex civilizations. As humankind sets forth to permanently establish itself on the Moon and use it as a testing ground to colonize other worlds, like Mars, agriculture will again play a pivotal role. In this case, the development of sustainable crop production systems capable of succeeding in these harsh environments becomes vital to the success of our star-faring journey. Over decades, studies varying in species and approaches have been conducted in microgravity, testing the limits of plants and various growth systems, to better understand how Earth-based agriculture could be translated into environmental conditions and therefore evolutionary pressures beyond what life on our planet has known. While we have passed several significant milestones, we are still far from the goal of a sustainable agricultural system beyond our planet Regolith-based agriculture (RBA) should be a component of sustainable agriculture solutions beyond Earth, one which can also provide insight into plant growth in poor soils across our own world. However, RBA studies are in their infancy and, like any other new field, need an established set of parameters to be followed by the RBA community so the generated data can be standardized and validated. Here, we provide an extensive multi-disciplinary review of the state of RBA, outline important knowledge gaps, and propose a set of standardized methods and benchmarks for regolith simulant development and selection as well as plant, microbe, and plant-microbe interaction studies conducted in lunar and Martian regolith. Our goal is to spur dialog within the RBA community on proper regolith simulant selection, experimental design, and reporting. Our methods are divided into complexity tiers, providing a clear path for even the simplest experiments to contribute to the bulk of the knowledge that will shape the future of RBA science and see it mature as an integrated part of sustainable off-world agriculture.
Loss of cardiomyocyte-specific adhesion G-protein-coupled receptor G1 (ADGRG1/GPR56) promotes pressure overload-induced heart failure
Authors: Einspahr Jeanette , Xu Heli , Roy Rajika , Dietz Nikki , Melchior Jacob , Raja Jhansi , Carter Rhonda , Piao Xianhua , Tilley Douglas G. 
Published: September 2024

Abstract
Adhesion G-protein-coupled receptors (AGPCRs), containing large N-terminal ligand-binding domains for environmental mechano-sensing, have been increasingly recognized to play important roles in numerous physiologic and pathologic processes. However, their impact on the heart, which undergoes dynamic mechanical alterations in healthy and failing states, remains understudied. ADGRG1 (formerly known as GPR56) is widely expressed, including in skeletal muscle where it was previously shown to mediate mechanical overload-induced muscle hypertrophy; thus, we hypothesized that it could impact the development of cardiac dysfunction and remodeling in response to pressure overload. In this study, we generated a cardiomyocyte (CM)-specific ADGRG1 knockout mouse model, which, although not initially displaying features of cardiac dysfunction, does develop increased systolic and diastolic LV volumes and internal diameters over time. Notably, when challenged with chronic pressure overload, CM-specific ADGRG1 deletion accelerates cardiac dysfunction, concurrent with blunted CM hypertrophy, enhanced cardiac inflammation and increased mortality, suggesting that ADGRG1 plays an important role in the early adaptation to chronic cardiac stress. Altogether, the present study provides an important proof-of-concept that targeting CM-expressed AGPCRs may offer a new avenue for regulating the development of heart failure.