bluuebunny/crossref_metadata_2025_split huggingface dataset:
Patterns of change and factors associated with IADL function decline in community-dwelling older adults with arthritis
Authors: Shin Jinhee , Kim Gwang Suk 
Published: October 2022

AbstractArthritis is a major cause of functional decline, which affects the quality of life (QoL) of older adults. This study analyzed instrumental activities of daily living (IADL) patterns in older adults with arthritis and the risk factors of functional decline. Data from the Korean Longitudinal Study of Aging (KLoSA), in which the participants were community-dwelling older adults aged ≥ 65 years and conducted every two years, were used to examine patterns in IADL performance between 2006 and 2016. The participants comprised 1,822 older adults, divided into an arthritis group and a non-arthritis group. A Generalized Estimating Equations (GEE) model and Kaplan–Meier analysis was used for the data analysis. The arthritis groups showed a statistically significant decrease in IADL function in 2012 (β = 1.283, p = 0.026), 2014 (β = 1.323, p = 0.028), and 2016 (β = 1.484, p = 0.014). The GEE model identified psychological conditions (depressive symptoms, cognitive function) and number of chronic diseases in the arthritis group as risk factors for increased IADL dependence. Healthcare providers should develop strategies to manage long-term functional decline, including programs to manage and prevent chronic diseases, cognitive function decline, and keep depressive symptoms under control, beginning within six years of arthritis diagnosis.
Wide-range IR spectra of diarylethene derivatives and their simulation using the density functional theory
Authors: Jarota Arkadiusz , Drwal Daria , Pięta Jakub , Pastorczak Ewa 
Published: October 2022

AbstractDiarylethenes (DAEs), promising photochromic molecular switches, undergo pericyclic reactions upon ultraviolet or visible light illumination. For this reason, most studies on DAEs employ UV–vis spectroscopies. However, also their infrared (IR) spectra are valuable, in particular, for understanding the vibrational dynamics which accompanies the relevant photoreactions. An accurate assignment of IR bands to molecular modes can be achieved through a comparison between experimental and computed theoretical spectra. Even though more sophisticated computational methods are available, the density functional theory (DFT) is usually employed for this task, because of its modest cost and versatility. Here, we have tested the ability of several DFT functionals to reproduce the wide-range, 400–3200 cm−1, IR spectra of open and closed isomers of four representative DAE molecules. We find that global and range-separated, corrected for anharmonicity by scaling factors, hybrid DFT functionals are able to reproduce the IR spectra of DAEs, however, instead of the popular B3LYP functional we propose the use of the dispersion-corrected PBE0 functional. The paper also proposes a semi-automatic method of band assignment.
Reduced subgenual cingulate–dorsolateral prefrontal connectivity as an electrophysiological marker for depression
Authors: Benschop Lars , Vanhollebeke Gert , Li Jian , Leahy Richard M. , Vanderhasselt Marie-Anne , Baeken Chris 
Published: October 2022

AbstractMajor Depressive Disorder (MDD) is a widespread mental illness that causes considerable suffering, and neuroimaging studies are trying to reduce this burden by developing biomarkers that can facilitate detection. Prior fMRI- and neurostimulation studies suggest that aberrant subgenual Anterior Cingulate (sgACC)—dorsolateral Prefrontal Cortex (DLPFC) functional connectivity is consistently present within MDD. Combining the need for reliable depression markers with the electroencephalogram’s (EEG) high clinical utility, we investigated whether aberrant EEG sgACC–DLPFC functional connectivity could serve as a marker for depression. Source-space Amplitude Envelope Correlations (AEC) of 20 MDD patients and 20 matched controls were contrasted using non-parametric permutation tests. In addition, extracted AEC values were used to (a) correlate with characteristics of depression and (b) train a Support Vector Machine (SVM) to determine sgACC–DLPFC connectivity’s discriminative power. FDR-thresholded statistical maps showed reduced sgACC–DLPFC AEC connectivity in MDD patients relative to controls. This diminished AEC connectivity is located in the beta-1 (13–17 Hz) band and is associated with patients’ lifetime number of depressive episodes. Using extracted sgACC–DLPFC AEC values, the SVM achieved a classification accuracy of 84.6% (80% sensitivity and 89.5% specificity) indicating that EEG sgACC–DLPFC connectivity has promise as a biomarker for MDD.
Mechanoresponsive regulation of fibroblast-to-myofibroblast transition in three-dimensional tissue analogues: mechanical strain amplitude dependency of fibrosis
Authors: Jacho Diego , Rabino Agustin , Garcia-Mata Rafael , Yildirim-Ayan Eda 
Published: October 2022

AbstractThe spatiotemporal interaction and constant iterative feedback between fibroblasts, extracellular matrix, and environmental cues are central for investigating the fibroblast-induced musculoskeletal tissue regeneration and fibroblast-to-myofibroblast transition (FMT). In this study, we created a fibroblast-laden 3D tissue analogue to study (1) how mechanical loading exerted on three-dimensional (3D) tissues affected the residing fibroblast phenotype and (2) to identify the ideal mechanical strain amplitude for promoting tissue regeneration without initiating myofibroblast differentiation. We applied uniaxial tensile strain (0, 4, 8, and 12%) to the cell-laden 3D tissue analogues to understand the interrelation between the degree of applied mechanical loading amplitudes and FMT. Our data demonstrated that 4% mechanical strain created an anabolic effect toward tissue regeneration, but higher strain amplitudes over-stimulated the cells and initiated fibrotic tissue formation. Under increased mechanical strain amplitudes, fibroblasts were activated from a homeostatic state to a proto-myofibroblast state which resulted in increased cellularity accompanied by increased expressions of extracellular matrix (ECM) components, activation stressors (TGF-β1 and TGF-βR1), and profibrotic markers. This further transformed fibroblasts into α-smooth muscle actin expressing myofibroblasts. Understanding the interplay between the applied degree of mechanical loading exerted on 3D tissues and residing fibroblast phenotypic response is important to identify specific mechanomodulatory approaches for tissue regeneration and the informed mechanotherapy-guided tissue healing strategies.
Evidence of self-organized criticality in time series by the horizontal visibility graph approach
Authors: Kaki Bardia , Farhang Nastaran , Safari Hossein 
Published: October 2022

AbstractDetermination of self-organized criticality (SOC) is crucial in evaluating the dynamical behavior of a time series. Here, we apply the complex network approach to assess the SOC characteristics in synthesis and real-world data sets. For this purpose, we employ the horizontal visibility graph (HVG) method and construct the relevant networks for two numerical avalanche-based samples (i.e., sand-pile models), several financial markets, and a solar nano-flare emission model. These series are shown to have long-temporal correlations via the detrended fluctuation analysis. We compute the degree distribution, maximum eigenvalue, and average clustering coefficient of the constructed HVGs and compare them with the values obtained for random and chaotic processes. The results manifest a perceptible deviation between these parameters in random and SOC time series. We conclude that the mentioned HVG’s features can distinguish between SOC and random systems.
Sarco/endoplasmic reticulum calcium ATPase activity is unchanged despite increased myofilament calcium sensitivity in Zucker type 2 diabetic fatty rat heart
Authors: Ng Yann Huey , Lamberts Regis R. , Jones Peter P. , Sammut Ivan A. , Diffee Gary M. , Wilkins Gerard T. , Baldi James C. 
Published: October 2022

AbstractSystolic and diastolic dysfunction in diabetes have frequently been associated with abnormal calcium (Ca2+) regulation. However, there is emerging evidence that Ca2+ mishandling alone is insufficient to fully explain diabetic heart dysfunction, with focus shifting to the properties of the myofilament proteins. Our aim was to examine the effects of diabetes on myofilament Ca2+ sensitivity and Ca2+ handling in left ventricular tissues isolated from the same type 2 diabetic rat hearts. We measured the force-pCa relationship in skinned left ventricular cardiomyocytes isolated from 20-week-old type 2 diabetic and non-diabetic rats. Myofilament Ca2+ sensitivity was greater in the diabetic relative to non-diabetic cardiomyocytes, and this corresponded with lower phosphorylation of cardiac troponin I (cTnI) at ser23/24 in the diabetic left ventricular tissues. Protein expression of sarco/endoplasmic reticulum Ca2+-ATPase (SERCA), phosphorylation of phospholamban (PLB) at Ser16, and SERCA/PLB ratio were lower in the diabetic left ventricular tissues. However, the maximum SERCA Ca2+ uptake rate was not different between the diabetic and non-diabetic myocardium. Our data suggest that impaired contractility in the diabetic heart is not caused by SERCA Ca2+ mishandling. This study highlights the important role of the cardiac myofilament and provides new insight on the pathophysiology of diabetic heart dysfunction.
Optimization of inelastic multistory structures under seismic vibrations using shape-memory-alloy material
Authors: Shmerling Assaf , Gerdts Matthias 
Published: October 2022

AbstractThis paper develops a novel optimization methodology for designing Shape-memory-alloy resisting devices (SMARDs) and optimally allocating them to inelastic multistory structures. The solution algorithm is a control gains optimization procedure that refers to a formal optimization problem with an objective function subject to the state-space equation and design limitations. The objective function integrates the squared state components in time, and the state-space equation consists of a newly introduced state vector form that reflects the system's inelasticity. The control gains are the number of total Shape-memory-alloy (SMA) wires attached to the devices in each story, and the design limitations dictate the minimum/maximum number of wires. The solution algorithm consists of five iterative steps that employ the defined Hamiltonian gradients in state and gains and cater to the necessary optimality conditions. The numerical example deals with upgrading an eight-story shear-type frame system. It studies the algorithm efficiency and elaborates on the effect of the optimal weighting matrix by investigating three different configurations. In all cases, the algorithm improves the system's inelastic seismic response—showcasing the reliability of the developed design methodology and the utilization of SMA material.
Towards a comprehensive approach for characterizing cell activity in bright-field microscopic images
Authors: Baar Stefan , Kuragano Masahiro , Tokuraku Kiyotaka , Watanabe Shinya 
Published: October 2022

AbstractWhen studying physical cellular response observed by light microscopy, variations in cell behavior are difficult to quantitatively measure and are often only discussed on a subjective level. Hence, cell properties are described qualitatively based on a researcher’s impressions. In this study, we aim to define a comprehensive approach to estimate the physical cell activity based on migration and morphology based on statistical analysis of a cell population within a predefined field of view and timespan. We present quantitative measurements of the influence of drugs such as cytochalasin D and taxol on human neuroblastoma, SH-SY5Y cell populations. Both chemicals are well known to interact with the cytoskeleton and affect the cell morphology and motility. Being able to compute the physical properties of each cell for a given observation time, requires precise localization of each cell even when in an adhesive state, where cells are not visually differentiable. Also, the risk of confusion through contaminants is desired to be minimized. In relation to the cell detection process, we have developed a customized encoder-decoder based deep learning cell detection and tracking procedure. Further, we discuss the accuracy of our approach to quantify cell activity and its viability in regard to the cell detection accuracy.
Gender differences in fasting and postprandial metabolic traits predictive of subclinical atherosclerosis in an asymptomatic Chinese population
Authors: Loh Xinpeng , Sun Lijuan , Allen John Carson , Goh Hui Jen , Kong Siew Ching , Huang Weiting , Ding Cherlyn , Bosco Nabil , Egli Leonie , Actis-Goretta Lucas , Magkos Faidon , Arigoni Fabrizio , Yeo Khung Keong , Leow Melvin Khee-Shing 
Published: October 2022

AbstractThe prediction utility of Framingham Risk Score in populations with low conventional cardiovascular risk burden is limited, particularly among women. Gender-specific markers to predict cardiovascular risk in overtly healthy people are lacking. In this study we hypothesize that postprandial responses triggered by a high-calorie meal test differ by gender in their ability to triage asymptomatic subjects into those with and without subclinical atherosclerosis. A total of 101 healthy Chinese subjects (46 females, 55 males) at low risk of coronary heart disease completed the study. Subjects underwent cardiovascular imaging and postprandial blood phenotyping after consuming a standardized macronutrient meal. Prediction models were developed using logistic regression and subsequently subjected to cross-validation to obtain a de-optimized receiver operating characteristic (ROC) curve. Distinctive gender differences in postprandial trajectories of glucose, lipids and inflammatory markers were observed. We used gender-specific association with different combinations of postprandial predictors to develop 2 models for predicting risk of subclinical atherosclerosis in males (ROC AUC = 0.7867, 95% CI 0.6567, 0.9166) and females (ROC AUC = 0.9161, 95% CI 0.8340, 0.9982) respectively. We report novel postprandial models for predicting subclinical atherosclerosis in apparently healthy Asian subjects using a gender-specific approach, complementing the conventional Framingham Risk Score.Clinical Trial Registration: The trial was registered at clinicaltrials.gov as NCT03531879.
Molecular and expression analysis indicate the role of CBL interacting protein kinases (CIPKs) in abiotic stress signaling and development in chickpea
Authors: Poddar Nikita , Deepika Deepika , Chitkara Pragya , Singh Amarjeet , Kumar Shailesh 
Published: October 2022

AbstractCalcineurin B-like proteins (CBL)-interacting protein kinases (CIPKs) regulate the developmental processes, hormone signal transduction and stress responses in plants. Although the genome sequence of chickpea is available, information related to the CIPK gene family is missing in this important crop plant. Here, a total of 22 CIPK genes were identified and characterized in chickpea. We found a high degree of structural and evolutionary conservation in the chickpea CIPK family. Our analysis showed that chickpea CIPKs have evolved with dicots such as Arabidopsis and soybean, and extensive gene duplication events have played an important role in the evolution and expansion of the CIPK gene family in chickpea. The three-dimensional structure of chickpea CIPKs was described by protein homology modelling. Most CIPK proteins are localized in the cytoplasm and nucleus, as predicted by subcellular localization analysis. Promoter analysis revealed various cis-regulatory elements related to plant development, hormone signaling, and abiotic stresses. RNA-seq expression analysis indicated that CIPKs are significantly expressed through a spectrum of developmental stages, tissue/organs that hinted at their important role in plant development. The qRT-PCR analysis revealed that several CaCIPK genes had specific and overlapping expressions in different abiotic stresses like drought, salt, and ABA, suggesting the important role of this gene family in abiotic stress signaling in chickpea. Thus, this study provides an avenue for detailed functional characterization of the CIPK gene family in chickpea and other legume crops.
CDK4/6 initiates Rb inactivation and CDK2 activity coordinates cell-cycle commitment and G1/S transition
Authors: Kim Sungsoo , Leong Alessandra , Kim Minah , Yang Hee Won 
Published: October 2022

AbstractExternal signaling controls cell-cycle entry until cells irreversibly commit to the cell cycle to ensure faithful DNA replication. This process is tightly regulated by cyclin-dependent kinases (CDKs) and the retinoblastoma protein (Rb). Here, using live-cell sensors for CDK4/6 and CDK2 activities, we propose that CDK4/6 initiates Rb inactivation and CDK2 activation, which coordinates the timing of cell-cycle commitment and sequential G1/S transition. Our data show that CDK4/6 activation induces Rb inactivation and thereby E2F activation, driving a gradual increase in CDK2 activity. We found that rapid CDK4/6 inhibition can reverse cell-cycle entry until CDK2 activity reaches to high levels. This suggests that high CDK2 activity is required to initiate CDK2-Rb positive feedback and CDK4/6-indpendent cell-cycle progression. Since CDK2 activation also facilitates initiation of DNA replication, the timing of CDK2-Rb positive feedback is coupled with the G1/S transition. Our experiments, which acutely increased CDK2 activity by cyclin E1 overexpression, indicate that cells commit to the cell cycle before triggering DNA replication. Together, our data suggest that CDK4/6 inactivates Rb to begin E2F and CDK2 activation, and high CDK2 activity is necessary and sufficient to generate a bistable switch for Rb phosphorylation before DNA replication. These findings highlight how cells initiate the cell cycle and subsequently commit to the cell cycle before the G1/S transition.
Multi-objective optimization and prediction of surface roughness and printing time in FFF printed ABS polymer
Authors: Selvam Arivazhagan , Mayilswamy Suresh , Whenish Ruban , Naresh K. , Shanmugam Vigneshwaran , Das Oisik 
Published: October 2022

AbstractIn this study, fused filament fabrication (FFF) printing parameters were optimized to improve the surface quality and reduce the printing time of Acrylonitrile Butadiene Styrene (ABS) polymer using the Analysis of Variance (ANOVA), it is a statistical analysis tool. A multi-objective optimization technique was employed to predict the optimum process parameter values using particle swarm optimization (PSO) and response surface methodology (RSM) techniques. Printing time and surface roughness were analyzed as a function of layer thickness, printing speed and nozzle temperature. A central composite design was preferred by employing the RSM method, and experiments were carried out as per the design of experiments (DoE). To understand the relationship between the identified input parameters and the output responses, several mathematical models were developed. After validating the accuracy of the developed regression model, these models were then coupled with PSO and RSM to predict the optimum parameter values. Moreover, the weighted aggregated sum product assessment (WASPAS) ranking method was employed to compare the RSM and PSO to identify the best optimization technique. WASPAS ranking method shows PSO has finer optimal values [printing speed of 125.6 mm/sec, nozzle temperature of 221 °C and layer thickness of 0.29 mm] than the RSM method. The optimum values were compared with the experimental results. Predicted parameter values through the PSO method showed high surface quality for the type of the surfaces, i.e., the surface roughness value of flat upper and down surfaces is approximately 3.92 µm, and this value for the other surfaces is lower, which is approximately 1.78 µm, at a minimum printing time of 24 min.
Differential patterns of cross-reactive antibody response against SARS-CoV-2 spike protein detected for chronically ill and healthy COVID-19 naïve individuals
Authors: Jaago Mariliis , Rähni Annika , Pupina Nadežda , Pihlak Arno , Sadam Helle , Tuvikene Jürgen , Avarlaid Annela , Planken Anu , Planken Margus , Haring Liina , Vasar Eero , Baćević Miljana , Lambert France , Kalso Eija , Pussinen Pirkko , Tienari Pentti J. , Vaheri Antti , Lindholm Dan , Timmusk Tõnis , Ghaemmaghami Amir M. , Palm Kaia 
Published: October 2022

AbstractImmunity to previously encountered viruses can alter response to unrelated pathogens. We reasoned that similar mechanism may also involve SARS-CoV-2 and thereby affect the specificity and the quality of the immune response against the virus. Here, we employed high-throughput next generation phage display method to explore the link between antibody immune response to previously encountered antigens and spike (S) glycoprotein. By profiling the antibody response in COVID-19 naïve individuals with a diverse clinical history (including cardiovascular, neurological, or oncological diseases), we identified 15 highly antigenic epitopes on spike protein that showed cross-reactivity with antigens of seasonal, persistent, latent or chronic infections from common human viruses. We observed varying degrees of cross-reactivity of different viral antigens with S in an epitope-specific manner. The data show that pre-existing SARS-CoV-2 S1 and S2 cross-reactive serum antibody is readily detectable in pre-pandemic cohort. In the severe COVID-19 cases, we found differential antibody response to the 15 defined antigenic and cross-reactive epitopes on spike. We also noted that despite the high mutation rates of Omicron (B.1.1.529) variants of SARS-CoV-2, some of the epitopes overlapped with the described mutations. Finally, we propose that the resolved epitopes on spike if targeted by re-called antibody response from SARS-CoV-2 infections or vaccinations can function in chronically ill COVID-19 naïve/unvaccinated individuals as immunogenic targets to boost antibodies augmenting the chronic conditions. Understanding the relationships between prior antigen exposure at the antibody epitope level and the immune response to subsequent infections with viruses from a different strain is paramount to guiding strategies to exit the COVID-19 pandemic.
Comparative studies on multi-carrier transmission schemes in mountainous and dense forest environment
Authors: Ding Chuanfei , Gao Xiang , Yang Kai , Song Jinpeng , Li Ruide , Bu Xiangyuan , An Jianping 
Published: October 2022

AbstractEarthquakes, forest fires, mudslides and other natural disasters occur frequently in recent years. They usually occur in the mountainous and dense forests, where local communication facilities do not exist or have been destroyed by the disasters. Adverse geographical environment poses a huge challenge to emergency communications and rescue. This paper presents comparative studies on multi-carrier transmission schemes in the mountainous and dense forest environment. The comprehensive communication performance for various multi-carrier waveform schemes, has been extensively analyzed by using the Stanford University Interim channel model. Simulation results show that the pruned discrete Fourier transform spread filter bank multi-carrier scheme exhibits generally the best performance in terms of transmission rate and distance for most operation modes.