bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of Global Ocean Biogeochemistry Models for Ocean Carbon Sink Estimates in RECCAP2 and Recommendations for Future Studies
Authors: Terhaar Jens , Goris Nadine , Müller Jens D. , DeVries Tim , Gruber Nicolas , Hauck Judith , Perez Fiz F. , Séférian Roland 
Published: March 2024

AbstractThe ocean is a major carbon sink and takes up 25%–30% of the anthropogenically emitted CO2. A state‐of‐the‐art method to quantify this sink are global ocean biogeochemistry models (GOBMs), but their simulated CO2 uptake differs between models and is systematically lower than estimates based on statistical methods using surface ocean pCO2 and interior ocean measurements. Here, we provide an in‐depth evaluation of ocean carbon sink estimates from 1980 to 2018 from a GOBM ensemble. As sources of inter‐model differences and ensemble‐mean biases our study identifies (a) the model setup, such as the length of the spin‐up, the starting date of the simulation, and carbon fluxes from rivers and into sediments, (b) the simulated ocean circulation, such as Atlantic Meridional Overturning Circulation and Southern Ocean mode and intermediate water formation, and (c) the simulated oceanic buffer capacity. Our analysis suggests that a late starting date and biases in the ocean circulation cause a too low anthropogenic CO2 uptake across the GOBM ensemble. Surface ocean biogeochemistry biases might also cause simulated anthropogenic fluxes to be too low, but the current setup prevents a robust assessment. For simulations of the ocean carbon sink, we recommend in the short‐term to (a) start simulations at a common date before the industrialization and the associated atmospheric CO2 increase, (b) conduct a sufficiently long spin‐up such that the GOBMs reach steady‐state, and (c) provide key metrics for circulation, biogeochemistry, and the land‐ocean interface. In the long‐term, we recommend improving the representation of these metrics in the GOBMs.
Identification of circulating apolipoprotein M as a new determinant of insulin sensitivity and relationship with adiponectin
Authors: Frances Laurie , Croyal Mikaël , Ruidavets Jean-Bernard , Maraninchi Marie , Combes Guillaume , Raffin Jérémy , de Souto Barreto Philippe , Ferrières Jean , Blaak Ellen E. , Perret Bertrand , Moro Cédric , Valéro René , Martinez Laurent O. , Viguerie Nathalie 
Published: March 2024

Abstract
Background
The adiponectin is one of the rare adipokines down-regulated with obesity and protects against obesity-related disorders. Similarly, the apolipoprotein M (apoM) is expressed in adipocytes and its expression in adipose tissue is associated with metabolic health. We compared circulating apoM with adiponectin regarding their relationship with metabolic parameters and insulin sensitivity and examined their gene expression patterns in adipocytes and in the adipose tissue.

Methods
Circulating apoM and adiponectin were examined in 169 men with overweight in a cross-sectional study, and 13 patients with obesity during a surgery-induced slimming program. Correlations with clinical parameters including the insulin resistance index (HOMA-IR) were analyzed. Multiple regression analyses were performed on HOMA-IR. The APOM and ADIPOQ gene expression were measured in the adipose tissue from 267 individuals with obesity and a human adipocyte cell line.

Results
Participants with type 2 diabetes had lower circulating adiponectin and apoM, while apoM was higher in individuals with dyslipidemia. Similar to adiponectin, apoM showed negative associations with HOMA-IR and hs-CRP (r < −0.2), and positive correlations with HDL markers (HDL-C and apoA-I, r > 0.3). Unlike adiponectin, apoM was positively associated with LDL markers (LDL-C and apoB100, r < 0.20) and negatively correlated with insulin and age (r < −0.2). The apoM was the sole negative determinant of HOMA-IR in multiple regression models, while adiponectin not contributing significantly. After surgery, the change in HOMA-IR was negatively associated with the change in circulating apoM (r = −0.71), but not with the change in adiponectin. The APOM and ADIPOQ gene expression positively correlated in adipose tissue (r > 0.44) as well as in adipocytes (r > 0.81). In adipocytes, APOM was downregulated by inflammatory factors and upregulated by adiponectin.

Conclusions
The apoM rises as a new partner of adiponectin regarding insulin sensitivity. At the adipose tissue level, the adiponectin may be supported by apoM to promote a healthy adipose tissue.

Trial registration
NCT01277068, registered 13 January 2011; NCT02332434, registered 5 January 2015; and NCT00390637, registered 20 October 2006.
Ultra-high-Q free-space coupling to microtoroid resonators
Authors: Suebka Sartanee , McLeod Euan , Su Judith 
Published: March 2024

AbstractWhispering gallery mode (WGM) microtoroid resonators are one of the most sensitive biochemical sensors in existence, capable of detecting single molecules. The main barrier for translating these devices out of the laboratory is that light is evanescently coupled into these devices though a tapered optical fiber. This hinders translation of these devices as the taper is fragile, suffers from mechanical vibration, and requires precise positioning. Here, we eliminate the need for an optical fiber by coupling light into and out from a toroid via free-space coupling and monitoring the scattered resonant light. A single long working distance objective lens combined with a digital micromirror device (DMD) was used for light injection, scattered light collection, and imaging. We obtain Q-factors as high as $$1.6\times {10}^{8}$$

1.6
×

10

8

with this approach. Electromagnetically induced transparency (EIT)-like and Fano resonances were observed in a single cavity due to indirect coupling in free space. This enables improved sensing sensitivity. The large effective coupling area (~10 μm in diameter for numerical aperture = 0.14) removes the need for precise positioning. Sensing performance was verified by combining the system with the frequency locked whispering evanescent resonator (FLOWER) approach to perform temperature sensing experiments. A thermal nonlinear optical effect was examined by tracking the resonance through FLOWER while adjusting the input power. We believe that this work will be a foundation for expanding the implementation of WGM microtoroid resonators to real-world applications.
A resonant high-pressure microsensor based on a composite pressure-sensitive mechanism of diaphragm bending and volume compression
Authors: Qian Pan , Yu Zongze , Yu Jie , Lu Yulan , Xie Bo , Chen Jian , Chen Deyong , Wang Junbo 
Published: March 2024

AbstractIn this paper, a composite pressure-sensitive mechanism combining diaphragm bending and volume compression was developed for resonant pressure microsensors to achieve high-pressure measurements with excellent accuracy. The composite mechanism was explained, and the sensor structure was designed based on theoretical analysis and finite element simulation. An all-silicon resonant high-pressure microsensor with multiple miniaturized cavities and dual resonators was developed, where dual resonators positioned in two resonant cavities with suitably different widths are used to perform opposite characteristics in pressure and the same characteristics at different temperatures, which can improve pressure sensitivities and realize temperature self-compensation by differential frequency output. The microsensor was fabricated by microfabrication, and the experimental results showed that the sensor had an accuracy of ±0.015% full scale (FS) in a pressure range of 0.1~100 MPa and a temperature range of −10~50 °C. The pressure sensitivity of the differential frequency was 261.10 Hz/MPa (~2523 ppm/MPa) at a temperature of 20 °C, and the temperature sensitivities of the dual resonators were −1.54 Hz/°C (~−14.5 ppm/°C) and −1.57 Hz/°C (~−15.6 ppm/°C) at a pressure of 2 MPa. The differential output had an outstanding stability within ±0.02 Hz under constant temperature and pressure. Thus, this research provides a convenient solution for high-pressure measurements because of its advantages, namely, large range, excellent accuracy and stability.
Dual inhibitors of DNMT and HDAC induce viral mimicry to induce antitumour immunity in breast cancer
Authors: Huang Wenjun , Zhu Qingyun , Shi Zhichao , Tu Yao , Li Qinyuan , Zheng Wenwen , Yuan Zigao , Li Lulu , Zu Xuyu , Hao Yue , Chu Bizhu , Jiang Yuyang 
Published: March 2024

AbstractThe existing conventional treatments for breast cancer, including immune checkpoint blockade, exhibit limited effects in some cancers, particularly triple-negative breast cancer. Epigenetic alterations, specifically DNMT and HDAC alterations, are implicated in breast cancer pathogenesis. We demonstrated that DNMTs and HDACs are overexpressed and positively correlated in breast cancer. The combination of DNMT and HDAC inhibitors has shown synergistic antitumour effects, and our previously designed dual DNMT and HDAC inhibitor (termed DNMT/HDACi) 15a potently inhibits breast cancer cell proliferation, migration, and invasion and induces apoptosis in vitro and in vivo. Mechanistically, 15a induces a viral mimicry response by promoting the expression of endogenous retroviral elements in breast cancer cells, thus increasing the intracellular level of double-stranded RNA to activate the RIG-I–MAVS pathway. This in turn promotes the production of interferons and chemokines and augments the expression of interferon-stimulated genes and PD-L1. The combination of 15a and an anti-PD-L1 antibody had an additive effect in vivo. These findings indicate that this DNMT/HDACi has immunomodulatory functions and enhances the effectiveness of immune checkpoint blockade therapy.
piRNA loading triggers MIWI translocation from the intermitochondrial cement to chromatoid body during mouse spermatogenesis
Authors: Wei Huan , Gao Jie , Lin Di-Hang , Geng Ruirong , Liao Jiaoyang , Huang Tian-Yu , Shang Guanyi , Jing Jiongjie , Fan Zong-Wei , Pan Duo , Yin Zi-Qi , Li Tianming , Liu Xinyu , Zhao Shuang , Chen Chen , Li Jinsong , Wang Xin , Ding Deqiang , Liu Mo-Fang 
Published: March 2024

AbstractThe intermitochondrial cement (IMC) and chromatoid body (CB) are posited as central sites for piRNA activity in mice, with MIWI initially assembling in the IMC for piRNA processing before translocating to the CB for functional deployment. The regulatory mechanism underpinning MIWI translocation, however, has remained elusive. We unveil that piRNA loading is the trigger for MIWI translocation from the IMC to CB. Mechanistically, piRNA loading facilitates MIWI release from the IMC by weakening its ties with the mitochondria-anchored TDRKH. This, in turn, enables arginine methylation of MIWI, augmenting its binding affinity for TDRD6 and ensuring its integration within the CB. Notably, loss of piRNA-loading ability causes MIWI entrapment in the IMC and its destabilization in male germ cells, leading to defective spermatogenesis and male infertility in mice. Collectively, our findings establish the critical role of piRNA loading in MIWI translocation during spermatogenesis, offering new insights into piRNA biology in mammals.
Large-scale modular and uniformly thick origami-inspired adaptable and load-carrying structures
Authors: Zhu Yi , Filipov Evgueni T. 
Published: March 2024

AbstractExisting Civil Engineering structures have limited capability to adapt their configurations for new functions, non-stationary environments, or future reuse. Although origami principles provide capabilities of dense packaging and reconfiguration, existing origami systems have not achieved deployable metre-scale structures that can support large loads. Here, we established modular and uniformly thick origami-inspired structures that can deploy into metre-scale structures, adapt into different shapes, and carry remarkably large loads. This work first derives general conditions for degree-N origami vertices to be flat foldable, developable, and uniformly thick, and uses these conditions to create the proposed origami-inspired structures. We then show that these origami-inspired structures can utilize high modularity for rapid repair and adaptability of shapes and functions; can harness multi-path folding motions to reconfigure between storage and structural states; and can exploit uniform thickness to carry large loads. We believe concepts of modular and uniformly thick origami-inspired structures will challenge traditional practice in Civil Engineering by enabling large-scale, adaptable, deployable, and load-carrying structures, and offer broader applications in aerospace systems, space habitats, robotics, and more.
Photooxidation triggered ultralong afterglow in carbon nanodots
Authors: Zheng Guang-Song , Shen Cheng-Long , Niu Chun-Yao , Lou Qing , Jiang Tian-Ci , Li Peng-Fei , Shi Xiao-Jing , Song Run-Wei , Deng Yuan , Lv Chao-Fan , Liu Kai-Kai , Zang Jin-Hao , Cheng Zhe , Dong Lin , Shan Chong-Xin 
Published: March 2024

AbstractIt remains a challenge to obtain biocompatible afterglow materials with long emission wavelengths, durable lifetimes, and good water solubility. Herein we develop a photooxidation strategy to construct near-infrared afterglow carbon nanodots with an extra-long lifetime of up to 5.9 h, comparable to that of the well-known rare-earth or organic long-persistent luminescent materials. Intriguingly, size-dependent afterglow lifetime evolution from 3.4 to 5.9 h has been observed from the carbon nanodots systems in aqueous solution. With structural/ultrafast dynamics analysis and density functional theory simulations, we reveal that the persistent luminescence in carbon nanodots is activated by a photooxidation-induced dioxetane intermediate, which can slowly release and convert energy into luminous emission via the steric hindrance effect of nanoparticles. With the persistent near-infrared luminescence, tissue penetration depth of 20 mm can be achieved. Thanks to the high signal-to-background ratio, biological safety and cancer-specific targeting ability of carbon nanodots, ultralong-afterglow guided surgery has been successfully performed on mice model to remove tumor tissues accurately, demonstrating potential clinical applications. These results may facilitate the development of long-lasting luminescent materials for precision tumor resection.
Associations between handedness and brain functional connectivity patterns in children
Authors: Tomasi Dardo , Volkow Nora D. 
Published: March 2024

Abstract
Handedness develops early in life, but the structural and functional brain connectivity patterns associated with it remains unknown. Here we investigate associations between handedness and the asymmetry of brain connectivity in 9- to 10-years old children from the Adolescent Brain Cognitive Development (ABCD) study. Compared to right-handers, left-handers had increased global functional connectivity density in the left-hand motor area and decreased it in the right-hand motor area. A connectivity-based index of handedness provided a sharper differentiation between right- and left-handers. The laterality of hand-motor connectivity varied as a function of handedness in unimodal sensorimotor cortices, heteromodal areas, and cerebellum (P < 0.001) and reproduced across all regions of interest in Discovery and Replication subsamples. Here we show a strong association between handedness and the laterality of the functional connectivity patterns in the absence of differences in structural connectivity, brain morphometrics, and cortical myelin between left, right, and mixed handed children.
Lanthanide luminescence nanothermometer with working wavelength beyond 1500 nm for cerebrovascular temperature imaging in vivo
Authors: Wu Yukai , Li Fang , Wu Yanan , Wang Hao , Gu Liangtao , Zhang Jieying , Qi Yukun , Meng Lingkai , Kong Na , Chai Yingjie , Hu Qian , Xing Zhenyu , Ren Wuwei , Li Fuyou , Zhu Xingjun 
Published: March 2024

AbstractNanothermometers enable the detection of temperature changes at the microscopic scale, which is crucial for elucidating biological mechanisms and guiding treatment strategies. However, temperature monitoring of micron-scale structures in vivo using luminescent nanothermometers remains challenging, primarily due to the severe scattering effect of biological tissue that compromises the imaging resolution. Herein, a lanthanide luminescence nanothermometer with a working wavelength beyond 1500 nm is developed to achieve high-resolution temperature imaging in vivo. The energy transfer between lanthanide ions (Er3+ and Yb3+) and H2O molecules, called the environment quenching assisted downshifting process, is utilized to establish temperature-sensitive emissions at 1550 and 980 nm. Using an optimized thin active shell doped with Yb3+ ions, the nanothermometer’s thermal sensitivity and the 1550 nm emission intensity are enhanced by modulating the environment quenching assisted downshifting process. Consequently, minimally invasive temperature imaging of the cerebrovascular system in mice with an imaging resolution of nearly 200 μm is achieved using the nanothermometer. This work points to a method for high-resolution temperature imaging of micron-level structures in vivo, potentially giving insights into research in temperature sensing, disease diagnosis, and treatment development.
Automated all-functionals infrared and Raman spectra
Authors: Bastonero Lorenzo , Marzari Nicola 
Published: March 2024

AbstractInfrared and Raman spectroscopies are ubiquitous techniques employed in many experimental laboratories, thanks to their fast and non-destructive nature able to capture materials’ features as spectroscopic fingerprints. Nevertheless, these measurements frequently need theoretical and computational support in order to unambiguously decipher and assign complex spectra. Linear-response theory provides an effective way to obtain the higher-order derivatives needed, but its applicability to modern exchange-correlation functionals and pseudopotential formalism remains limited. Here, we devise an automated, open-source, user-friendly approach based on density-functional theory and the electric-enthalpy functional to allow seamless calculation from first principles of infrared absorption and reflectivity, together with zone-center phonons, static dielectric tensor, and Raman spectra. By employing a finite-displacement and finite-field approach, we allow for the use of any functional, as well as an efficient treatment of large low-symmetry structures. Additionally, we propose a simple scheme for efficiently sampling the Brillouin zone at different electric fields. To demonstrate the capabilities of the present approach, we study ferroelectric LiNbO3 crystal as a paradigmatic example, and predict infrared and Raman spectra using various (semi)local, Hubbard corrected, and hybrid functionals. Our results also show how PBE0 and extended Hubbard functionals (PBEsol+U+V) yield for this case the best match in term of peak positions and intensities, respectively.
A deep learning approach for quantum dots sizing from wide-angle X-ray scattering data
Authors: Allara Lucia , Bertolotti Federica , Guagliardi Antonietta 
Published: March 2024

AbstractDisclosing the full potential of functional nanomaterials requires the optimization of synthetic protocols and an effective size screening tool, aiming at triggering their size-dependent properties. Here we demonstrate the successful combination of a wide-angle X-ray total scattering approach with a deep learning classifier for quantum dots sizing in both colloidal and dry states. This work offers a compelling alternative to the lengthy process of deriving sizing curves from transmission electron microscopy coupled with spectroscopic measurements, especially in the ultra-small size regime, where empirical functions exhibit larger discrepancies. The core of our algorithm is an all-convolutional neural network trained on Debye scattering equation simulations, incorporating atomistic models to capture structural and morphological features, and augmented with physics-informed perturbations to account for different predictable experimental conditions. The model performances are evaluated using both wide-angle X-ray total scattering simulations and experimental datasets collected on lead sulfide quantum dots, resulting in size classification accuracies surpassing 97%. With the developed deep learning size classifier, we overcome the need for calibration curves for quantum dots sizing and thanks to the unified modeling approach at the basis of the total scattering method implemented, we include simultaneously structural and microstructural aspects in the classification process. This algorithm can be complemented by incorporating input information from other experimental observations (e.g., small angle X-ray scattering data) and, after proper training with the pertinent simulations, can be extended to other classes of quantum dots, providing the nanoscience community with a powerful and broad tool to accelerate the development of functional (nano)materials.
Mapping the landscape: a bibliometric analysis of resting-state fMRI research on schizophrenia over the past 25 years
Authors: Fu Linhan , Aximu Remilai , Zhao Guoshu , Chen Yayuan , Sun Zuhao , Xue Hui , Wang Shaoying , Zhang Nannan , Zhang Zhihui , Lei Minghuan , Zhai Ying , Xu Jinglei , Sun Jie , Ma Juanwei , Liu Feng 
Published: March 2024

AbstractSchizophrenia, a multifaceted mental disorder characterized by disturbances in thought, perception, and emotion, has been extensively investigated through resting-state fMRI, uncovering changes in spontaneous brain activity among those affected. However, a bibliometric examination regarding publication trends in resting-state fMRI studies related to schizophrenia is lacking. This study obtained relevant publications from the Web of Science Core Collection spanning the period from 1998 to 2022. Data extracted from these publications included information on countries/regions, institutions, authors, journals, and keywords. The collected data underwent analysis and visualization using VOSviewer software. The primary analyses included examination of international and institutional collaborations, authorship patterns, co-citation analyses of authors and journals, as well as exploration of keyword co-occurrence and temporal trend networks. A total of 859 publications were retrieved, indicating an overall growth trend from 1998 to 2022. China and the United States emerged as the leading contributors in both publication outputs and citations, with Central South University and the University of New Mexico being identified as the most productive institutions. Vince D. Calhoun had the highest number of publications and citation counts, while Karl J. Friston was recognized as the most influential author based on co-citations. Key journals such as Neuroimage, Schizophrenia Research, Schizophrenia Bulletin, and Biological Psychiatry played pivotal roles in advancing this field. Recent popular keywords included support vector machine, antipsychotic medication, transcranial magnetic stimulation, and related terms. This study systematically synthesizes the historical development, current status, and future trends in resting-state fMRI research in schizophrenia, offering valuable insights for future research directions.