bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association of systemic inflammatory indices with anthropometric measures, metabolic factors, and liver function in non-alcoholic fatty liver disease
Authors: Arefhosseini Sara , Aghajani Taha , Tutunchi Helda , Ebrahimi-Mameghani Mehrangiz 
Published: June 2024

AbstractThe present cross-sectional study aimed to explore the relationship between systemic inflammatory indices (SIIs) and anthropometric measures, metabolic, and liver function biomarkers in patients with non-alcoholic fatty liver disease (NAFLD). This study was carried out on 238 NAFLD patients with overweight or obesity, aged 18–55 years. Anthropometric measurements were done and body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were estimated. Metabolic factors including serum glucose, lipid profile, liver function biomarkers, and complete blood cell count were assessed after a 24-h fasting state. SIIs including the ratios of neutrophil to lymphocyte (NLR), monocytes to lymphocyte (MLR), platelet to lymphocyte (PLR), and monocytes to high-density lipoprotein cholesterol (MHR) were calculated. Results indicate that apart from PLR, all of the SIIs significantly changed by increasing steatosis severity (all p < 0.05). Moreover, changes in NLR showed a significant association with anthropometric indices including waist circumference (p = 0.032), BMI (p = 0.047), and WHtR (p = 0.002), as well as levels of fasting blood sugar (p = 0.045), triglycerides, (p = 0.025) and low-density lipoprotein cholesterol (p = 0.006). The findings also indicate the relations between lipid profile and all studied SIIs, notably MHR and MLR. All of the SIIs exhibited associations with some liver function indices as well. MHR was positively correlated with the metabolic risk factors of NAFLD while, oppositely, PLR was considered as a preventive marker of NAFLD.
Intelligent Bell facial paralysis assessment: a facial recognition model using improved SSD network
Authors: Shi Haiping , Fan Yinqiu , Zhang Yu , Li Xiaowei , Shu Yuling , Deng Xinyuan , Zhang Yating , Zheng Yunzi , Yang Jun 
Published: June 2024

AbstractWith the continuous progress of technology, the subject of life science plays an increasingly important role, among which the application of artificial intelligence in the medical field has attracted more and more attention. Bell facial palsy, a neurological ailment characterized by facial muscle weakness or paralysis, exerts a profound impact on patients’ facial expressions and masticatory abilities, thereby inflicting considerable distress upon their overall quality of life and mental well-being. In this study, we designed a facial attribute recognition model specifically for individuals with Bell’s facial palsy. The model utilizes an enhanced SSD network and scientific computing to perform a graded assessment of the patients’ condition. By replacing the VGG network with a more efficient backbone, we improved the model’s accuracy and significantly reduced its computational burden. The results show that the improved SSD network has an average precision of 87.9% in the classification of light, middle and severe facial palsy, and effectively performs the classification of patients with facial palsy, where scientific calculations also increase the precision of the classification. This is also one of the most significant contributions of this article, which provides intelligent means and objective data for future research on intelligent diagnosis and treatment as well as progressive rehabilitation.
Enhanced analysis of tabular data through Multi-representation DeepInsight
Authors: Sharma Alok , López Yosvany , Jia Shangru , Lysenko Artem , Boroevich Keith A. , Tsunoda Tatsuhiko 
Published: June 2024

AbstractTabular data analysis is a critical task in various domains, enabling us to uncover valuable insights from structured datasets. While traditional machine learning methods can be used for feature engineering and dimensionality reduction, they often struggle to capture the intricate relationships and dependencies within real-world datasets. In this paper, we present Multi-representation DeepInsight (MRep-DeepInsight), a novel extension of the DeepInsight method designed to enhance the analysis of tabular data. By generating multiple representations of samples using diverse feature extraction techniques, our approach is able to capture a broader range of features and reveal deeper insights. We demonstrate the effectiveness of MRep-DeepInsight on single-cell datasets, Alzheimer's data, and artificial data, showcasing an improved accuracy over the original DeepInsight approach and machine learning methods like random forest, XGBoost, LightGBM, FT-Transformer and L2-regularized logistic regression. Our results highlight the value of incorporating multiple representations for robust and accurate tabular data analysis. By leveraging the power of diverse representations, MRep-DeepInsight offers a promising new avenue for advancing decision-making and scientific discovery across a wide range of fields.
A dSPACE-based implementation of ANFIS and predictive current control for a single phase boost power factor corrector
Authors: Babes Badreddine , Latrèche Samia , Bouafassa Amar , Aissa Oualid , Badoud Abd Essalam , Khemliche Mabrouk , Bajaj Mohit , Zaitsev Ievgen 
Published: June 2024

AbstractThis paper presents an innovative control scheme designed to significantly enhance the power factor of AC/DC boost rectifiers by integrating an adaptive neuro-fuzzy inference system (ANFIS) with predictive current control. The innovative control strategy addresses key challenges in power quality and energy efficiency, demonstrating exceptional performance under diverse operating conditions. Through rigorous simulation, the proposed system achieves precise input current shaping, resulting in a remarkably low total harmonic distortion (THD) of 3.5%, which is well below the IEEE-519 standard threshold of 5%. Moreover, the power factor reaches an outstanding 0.990, indicating highly efficient energy utilization and near-unity power factor operation. To validate the theoretical findings, a 500 W laboratory prototype was implemented using the dSPACE ds1104 digital controller. Steady-state analysis reveals sinusoidal input currents with minimal THD and a power factor approaching unity, thereby enhancing grid stability and energy efficiency. Transient response tests further demonstrate the system’s robustness against load and voltage fluctuations, maintaining output voltage stability within an 18 V overshoot and a 20 V undershoot during load changes, and achieving rapid response times as low as 0.2 s. Comparative evaluations against conventional methods underscore the superiority of the proposed control strategy in terms of both performance and implementation simplicity. By harnessing the strengths of ANFIS-based voltage regulation and predictive current control, this scheme offers a robust solution to power quality issues in AC/DC boost rectifiers, promising substantial energy savings and improved grid stability. The results affirm the potential of the proposed system to set new benchmarks in power factor correction technology.
Circadian rhythm analysis using wearable-based accelerometry as a digital biomarker of aging and healthspan
Authors: Shim Jinjoo , Fleisch Elgar , Barata Filipe 
Published: June 2024

AbstractRecognizing the pivotal role of circadian rhythm in the human aging process and its scalability through wearables, we introduce CosinorAge, a digital biomarker of aging developed from wearable-derived circadian rhythmicity from 80,000 midlife and older adults in the UK and US. A one-year increase in CosinorAge corresponded to 8–12% higher all-cause and cause-specific mortality risks and 3–14% increased prospective incidences of age-related diseases. CosinorAge also captured a non-linear decline in resilience and physical functioning, evidenced by an 8–33% reduction in self-rated health and a 3–23% decline in health-related quality of life score, adjusting for covariates and multiple testing. The associations were robust in sensitivity analyses and external validation using an independent cohort from a disparate geographical region using a different wearable device. Moreover, we illustrated a heterogeneous impact of circadian parameters associated with biological aging, with young (<45 years) and fast agers experiencing a substantially delayed acrophase with a 25-minute difference in peak timing compared to slow agers, diminishing to a 7-minute difference in older adults (>65 years). We demonstrated a significant enhancement in the predictive performance when integrating circadian rhythmicity in the estimation of biological aging over physical activity. Our findings underscore CosinorAge’s potential as a scalable, economic, and digital solution for promoting healthy longevity, elucidating the critical and multifaceted circadian rhythmicity in aging processes. Consequently, our research contributes to advancing preventive measures in digital medicine.
A culture method with berbamine, a plant alkaloid, enhances CAR-T cell efficacy through modulating cellular metabolism
Authors: Takayanagi Shin-ichiro , Chuganji Sayaka , Tanaka Masahiro , Wang Bo , Hasegawa Saki , Fukumoto Ken , Wasano Nariaki , Kakitani Makoto , Ochiai Nakaba , Kawai Yohei , Ueda Tatsuki , Ishikawa Akihiro , Kurimoto Yuko , Fukui Asami , Kamibayashi Sanae , Imai Eri , Kunisato Atsushi , Nozawa Hajime , Kaneko Shin 
Published: June 2024

AbstractMemory T cells demonstrate superior in vivo persistence and antitumor efficacy. However, methods for manufacturing less differentiated T cells are not yet well-established. Here, we show that producing chimeric antigen receptor (CAR)-T cells using berbamine (BBM), a natural compound found in the Chinese herbal medicine Berberis amurensis, enhances the antitumor efficacy of CAR-T cells. BBM is identified through cell-based screening of chemical compounds using induced pluripotent stem cell-derived T cells, leading to improved viability with a memory T cell phenotype. Transcriptomics and metabolomics using stem cell memory T cells reveal that BBM broadly enhances lipid metabolism. Furthermore, the addition of BBM downregulates the phosphorylation of p38 mitogen-activated protein kinase and enhanced mitochondrial respiration. CD19-CAR-T cells cultured with BBM also extend the survival of leukaemia mouse models due to their superior in vivo persistence. This technology offers a straightforward approach to enhancing the antitumor efficacy of CAR-T cells.
Viscoelasticity of diverse biological samples quantified by Acoustic Force Microrheology (AFMR)
Authors: Bergamaschi Giulia , Taris Kees-Karel H. , Biebricher Andreas S. , Seymonson Xamanie M. R. , Witt Hannes , Peterman Erwin J. G. , Wuite Gijs J. L. 
Published: June 2024

AbstractIn the context of soft matter and cellular mechanics, microrheology - the use of micron-sized particles to probe the frequency-dependent viscoelastic response of materials – is widely used to shed light onto the mechanics and dynamics of molecular structures. Here we present the implementation of active microrheology in an Acoustic Force Spectroscopy setup (AFMR), which combines multiplexing with the possibility of probing a wide range of forces ( ~ pN to ~nN) and frequencies (0.01–100 Hz). To demonstrate the potential of this approach, we perform active microrheology on biological samples of increasing complexity and stiffness: collagen gels, red blood cells (RBCs), and human fibroblasts, spanning a viscoelastic modulus range of five orders of magnitude. We show that AFMR can successfully quantify viscoelastic properties by probing many beads with high single-particle precision and reproducibility. Finally, we demonstrate that AFMR to map local sample heterogeneities as well as detect cellular responses to drugs.
Benchmarking compound activity prediction for real-world drug discovery applications
Authors: Tian Tingzhong , Li Shuya , Zhang Ziting , Chen Lin , Zou Ziheng , Zhao Dan , Zeng Jianyang 
Published: June 2024

AbstractIdentifying active compounds for target proteins is fundamental in early drug discovery. Recently, data-driven computational methods have demonstrated promising potential in predicting compound activities. However, there lacks a well-designed benchmark to comprehensively evaluate these methods from a practical perspective. To fill this gap, we propose a Compound Activity benchmark for Real-world Applications (CARA). Through carefully distinguishing assay types, designing train-test splitting schemes and selecting evaluation metrics, CARA can consider the biased distribution of current real-world compound activity data and avoid overestimation of model performances. We observed that although current models can make successful predictions for certain proportions of assays, their performances varied across different assays. In addition, evaluation of several few-shot training strategies demonstrated different performances related to task types. Overall, we provide a high-quality dataset for developing and evaluating compound activity prediction models, and the analyses in this work may inspire better applications of data-driven models in drug discovery.
Direct probing of low-energy intra d-band transitions in gas-phase cobalt clusters
Authors: Kaw Kevin A. , Louwerse Rick J. , Bakker Joost M. , Lievens Peter , Janssens Ewald , Ferrari Piero 
Published: June 2024

AbstractThe interplay between constituent localized and itinerant electrons of metal clusters defines their physical and chemical properties. In turn, the electronic and geometrical structures are strongly entwined and exhibit strong size-dependent variations. Current understanding of low-energy excited states of metal clusters relies on stand-alone theoretical investigations and few comparisons with measured properties, since direct identification of low-lying states is lacking hitherto. Here, we report on the measurement of low-lying electronic transitions in cationic cobalt clusters using infrared photofragmentation spectroscopy. Broad and size-dependent absorption features were observed within 0.056 – 0.446 eV, well above the energies of the sharp absorption bands caused by cluster vibrations. Complementary time-dependent density functional theory calculations reproduce the main observed absorption features, providing direct evidence that they correspond to transitions between electronic states of mainly d-character, arising from the open d-shells of the Co atoms and the high spin multiplicity of the clusters.
Monolithic optical resonator for ultrastable laser and photonic millimeter-wave synthesis
Authors: Zhang Wei , Kittlaus Eric , Savchenkov Anatoliy , Iltchenko Vladimir , Yi Lin , Papp Scott B. , Matsko Andrey 
Published: June 2024

AbstractOptical resonators are indispensable tools in optical metrology that usually benefit from an evacuated and highly-isolated environment to achieve peak performance. Even in the more sophisticated design of Fabry-Perot (FP) cavities, the material choice limits the achievable quality factors. For this reason, monolithic resonators are emerging as promising alternative to traditional designs, but their design is still at preliminary stage and far from being optimized. Here, we demonstrate a monolithic FP resonator with 4.5 cm3 volume and 2 × 105 finesse. In the ambient environment, we achieve 18 Hz integrated laser linewidth and 7 × 10−14 frequency stability measured from 0.08 s to 0.3 s averaging time, the highest spectral purity and stability demonstrated to date in the context of monolithic reference resonators. By locking two separate lasers to distinct modes of the same resonator, a 96 GHz microwave signals is generated with phase noise -100 dBc/Hz at 10 kHz frequency offset, achieving orders of magnitude improvement in the approach of photonic heterodyne synthesis. The compact monolithic FP resonator is promising for applications in spectrally-pure, high-frequency microwave photonic references as well as optical clocks and other metrological devices. ©2024. All rights reserved.
Accurate hyperfine tensors for solid state quantum applications: case of the NV center in diamond
Authors: Takács István , Ivády Viktor 
Published: June 2024

AbstractThe decoherence of point defect qubits is often governed by the electron spin-nuclear spin hyperfine interaction that can be parameterized by using ab inito calculations in principle. So far most of the theoretical works have focused on the hyperfine interaction of the closest nuclear spins, while the accuracy of the predictions for distinct nuclear spins is barely discussed. Here we demonstrate for the case of the NV center in diamond that the absolute relative error of the computed hyperfine parameters can exceed 100% using an industry standards first-principles code. To overcome this issue, we implement an alternative method and report on significantly improved hyperfine values with $${{{{{{{\mathcal{O}}}}}}}}$$
O
(1%) relative mean error at all distances. The provided accurate hyperfine data for the NV center enables high-precision simulation of NV quantum nodes for quantum information processing and positioning of nuclear spins by comparing experimental and theoretical hyperfine data.
Quasi-localization and Wannier obstruction in partially flat bands
Authors: Park Jin-Hong , Rhim Jun-Won 
Published: June 2024

AbstractThe localized nature of a flat band is understood by the existence of a compact localized eigenstate. However, the localization properties of a partially flat band, ubiquitous in surface modes of topological semimetals, have been unknown. We show that the partially flat band is characterized by a non-normalizable quasi-compact localized state (Q-CLS), which is compactly localized along several directions but extended in at least one direction. The partially flat band develops at momenta where normalizable Bloch wave functions can be obtained from a linear combination of the non-normalizable Q-CLSs. Outside this momentum region, a ghost flat band, unseen from the band structure, is introduced based on a counting argument. Then, we demonstrate that the Wannier function corresponding to the partially flat band exhibits an algebraic decay behavior. Namely, one can have the Wannier obstruction in a band with a vanishing Chern number if it is partially flat. Finally, we develop the construction scheme of a tight-binding model for a topological semimetal by designing a Q-CLS.
Acoustic metamaterials characterization via laser plasma sound sources
Authors: Kaleris Konstantinos , Kaniolakis-Kaloudis Emmanouil , Aravantinos-Zafiris Nikolaos , Katerelos Dionysios. T. G. , Dimitriou Vassilis M. , Bakarezos Makis , Tatarakis Michael , Mourjopoulos John , Sigalas Michail M. , Papadogiannis Nektarios A. 
Published: June 2024

AbstractPhononic crystals and acoustic metamaterials are expected to become an important enabling technology for science and industry. Currently, various experimental methods are used for evaluation of acoustic meta-structures, such as impedance tubes and anechoic chambers. Here we present a method for the precise characterization of acoustic meta-structures that utilizes rapid broadband acoustic pulses generated by point-like and effectively massless laser plasma sound sources. The method allows for broadband frequency response and directivity evaluations of meta-structures with arbitrary geometries in multiple sound propagation axes while also enabling acoustic excitation inside the structure. Experimental results are presented from acoustic evaluations of various phononic crystals with band gaps in the audible range, notably also in the very low frequencies, validating the predictions of numerical models with high accuracy. The proposed method is expected to boost research and commercial adoption of acoustic metamaterials in the near future.
Geochemical constraints on ridge-plume interaction in the West Philippine Basin
Authors: Yan Quanshu , Yuan Long , Shi Xuefa 
Published: June 2024

AbstractThe West Philippine Basin is not only a back-arc basin resulting from the subduction of the paleo-plates, but it has also undergone modification due to intraplate processes. However, the interaction between intraplate processes and back-arc spreading processes remains unclear. In this study, we present geochemical compositions of basaltic lavas from various tectonic sites in the West Philippine Basin. Lavas from the Benham Rise and its adjacent seamount, as well as basement crust samples from the West Philippine Basin, are similar to oceanic island basalts and mid-oceanic ridge basalts, respectively. The lavas from the Central Basin Fault lie between the two aforementioned types. Based on the mixing modeling of geochemical data, morphological structure of the West Philippine Basin, and age data for lavas, we developed a conceptual model for the three-stage tectonic evolution, with the simultaneous influence of back-arc spreading and mantle plume processes.
Association of Life’s Simple 7 lifestyle metric with cardiometabolic disease-free life expectancy in older British men
Authors: Wang Qiaoye , Schmidt Amand Floriaan , Lennon Lucy T. , Papacosta Olia , Whincup Peter H. , Wannamethee Goya 
Published: June 2024

Abstract
Background
Cardiometabolic diseases (CMD), including myocardial infarction, stroke, and type 2 diabetes, are leading causes of disability and mortality globally, particularly for people at an older age. The impact of adhering to the Life’s Simple 7 (LS7) on the number of years an individual will live without CMD in older adults remains less studied.

Methods
This study included a cohort of 2662 British men aged 60–79 years free of CMD at baseline from the British Regional Heart Study (BRHS). Each LS7 factor (BMI, blood pressure, blood glucose, total cholesterol, smoking, physical activity, and diet) was categorized as poor, intermediate, or ideal, and a composite LS7 adherence was determined by summing the number of LS7 ideal levels achieved. Flexible parametric Royston–Parmar proportional-hazards model was applied to estimate CMD-free life expectancy.

Results
Here we show that compared to men with the lowest LS7 adherence [with 18.42 years (95% CI: 16.93, 19.90) of CMD-free life at age 60], men having an ideal LS7 adherence are estimated to gain an additional 4.37 years (95% CI: 2.95, 5.79) of CMD-free life. The CMD-free life gain benefits are consistent across social class groups of manual and non-manual workers. Among LS7 factors, achieving an ideal physical activity provides the largest CMD-free survival benefit: 4.84 years (95% CI: 3.37, 6.32) of additional CMD-free life compared with the physically inactive group.

Conclusions
Our study quantifies and highlights the benefits of adhering to the LS7 ideal levels for living a longer life without CMD in older adults.