bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetic Influence on Social Support: A Twin Study
Authors: Gonggrijp Bodine M.A. , van de Weijer Steve G.A. , van Dongen Jenny , Bijleveld Catrien C.J.H. , Boomsma Dorret I. 
Published: October 2024

AbstractSocial support is often considered an environmental factor affecting health, especially in aging populations. However, its genetic underpinnings suggest a more complex origin. This study investigates the heritability of social support through applying a threshold model on data of a large adult sample of twins (N = 8019) from the Netherlands Twin Register, collected between 2009 and 2011. The study employed the Duke – UNC Functional Social Support Questionnaire to assess social support quality. Our analysis revealed genetic contributions to social support, with heritability estimated at 37%, without a contribution of shared environment and no differences between men and women in heritability. The study’s results underscore the complexity of social support as a trait influenced by genetic and environmental factors, challenging the notion that it is solely an environmental construct.
Zygosity Effects on Human Voice: Fundamental Frequency Analysis of Brazilian Twins’ Speech
Authors: Luchesi Lilian C. , Cavalcanti Julio C. , Lucci Tania K. , David Vinicius F. , Otta Emma , Monticelli Patricia F. 
Published: October 2024

AbstractVoice production can be influenced by interindividual variations related to genetic, physiological, behavioral, and several environmental factors. Here we examined the effect of zygosity on speaking fundamental frequency (F0) statistical descriptors. Our aims were: (1) to determine whether the genetic similarity between monozygotic (MZ) and dizygotic (DZ) twins affects F0 characteristics, and (2) to quantify the contribution of genetic factors to these characteristics. The study involved 79 same-sex twin pairs of Brazilian Portuguese speakers, comprising 65 MZ and 14 DZ twins, aged 18 to 66 years (31.7 ± 11.6 years), with 21 male and 58 female pairs. Participants were recorded while uttering a greeting phrase and the Brazilian Portuguese version of the ‘Happy Birthday to You’ song. Speech segments were analyzed using Praat free software, and F0 measures were automatically extracted in both Hertz and semitone scales. Statistical descriptors, including centrality, dispersion, and extreme values of F0 were examined, and the ACE model (i.e., total genetic effects, A; shared environmental influences, C; and nonshared environmental influences, E) was employed to estimate the additive effect;ts of monozygosity. As anticipated, we observed a zygosity effect on several F0 parameters, with more similarity between MZ twins compared to DZ twins. We discuss the genetic influences on F0 parameters and the absence of a monozygosity effect in two of them. Additionally, we briefly address potential biases associated with the selected measurement scale for statistical modeling. Finally, we explore the influence of genetic factors on F0 patterns, as well as environmental, life history and linguistic factors, particularly concerning F0 variation in speech.
Type 2 diabetes mellitus in adults: pathogenesis, prevention and therapy
Authors: Lu Xi , Xie Qingxing , Pan Xiaohui , Zhang Ruining , Zhang Xinyi , Peng Ge , Zhang Yuwei , Shen Sumin , Tong Nanwei 
Published: October 2024

AbstractType 2 diabetes (T2D) is a disease characterized by heterogeneously progressive loss of islet β cell insulin secretion usually occurring after the presence of insulin resistance (IR) and it is one component of metabolic syndrome (MS), and we named it metabolic dysfunction syndrome (MDS). The pathogenesis of T2D is not fully understood, with IR and β cell dysfunction playing central roles in its pathophysiology. Dyslipidemia, hyperglycemia, along with other metabolic disorders, results in IR and/or islet β cell dysfunction via some shared pathways, such as inflammation, endoplasmic reticulum stress (ERS), oxidative stress, and ectopic lipid deposition. There is currently no cure for T2D, but it can be prevented or in remission by lifestyle intervention and/or some medication. If prevention fails, holistic and personalized management should be taken as soon as possible through timely detection and diagnosis, considering target organ protection, comorbidities, treatment goals, and other factors in reality. T2D is often accompanied by other components of MDS, such as preobesity/obesity, metabolic dysfunction associated steatotic liver disease, dyslipidemia, which usually occurs before it, and they are considered as the upstream diseases of T2D. It is more appropriate to call “diabetic complications” as “MDS-related target organ damage (TOD)”, since their development involves not only hyperglycemia but also other metabolic disorders of MDS, promoting an up-to-date management philosophy. In this review, we aim to summarize the underlying mechanism, screening, diagnosis, prevention, and treatment of T2D, especially regarding the personalized selection of hypoglycemic agents and holistic management based on the concept of “MDS-related TOD”.
Dronedarone hydrochloride (DH) induces pancreatic cancer cell death by triggering mtDNA-mediated pyroptosis
Authors: Li Ming-Qiao , He Yu-Qi , Zhang Meng-Ni , Tang Wan , Tan Ya , Cheng Yue , Yang Mei , Zhao Nan , Li Ling , Yu Si-Rui , Li Ruo-Lan , Pan Qiong , Wu Ming-Yue , Chai Jin 
Published: October 2024

AbstractPancreatic cancer is one of the leading causes of cancer-associated mortality, with a poor treatment approach. Previous study has shown that inducing pyroptosis in pancreatic ductal adenocarcinoma (PDAC) slows the growth of PDACs, implying that pyroptosis inducers are potentially effective for PDAC therapy. Here, we found that Dronedarone hydrochloride (DH), an antiarrhythmic drug, induces pyroptosis in pancreatic cancer cells and inhibits PDAC development in mice. In PANC-1 cells, DH caused cell death in a dosage- and time-dependent manner, with only pyroptosis inhibitors and GSDMD silencing rescuing the cell death, indicating that DH triggered GSDMD-dependent pyroptosis. Further work revealed that DH increased mitochondrial stresses and caused mitochondrial DNA (mtDNA) leakage, activating the cytosolic STING-cGAS and pyroptosis pathways. Finally, we assessed the anti-cancer effects of DH in a pancreatic cancer mouse model and found that DH treatment suppressed pancreatic tumor development in vivo. Collectively, our investigation demonstrates that DH triggers pyroptosis in PDAC and proposes its potential effects on anti-PDAC growth.
Regionally enriched rare deleterious exonic variants in the UK and Ireland
Authors: Halachev Mihail , Gountouna Viktoria-Eleni , Meynert Alison , Tzoneva Gannie , Shuldiner Alan R. , Semple Colin A. , Wilson James F. 
Published: October 2024

AbstractIt is unclear how patterns of regional genetic differentiation in the UK and Ireland might impact the protein-coding fraction of the genome. We exploit UK Biobank (UKB) and Viking Genes whole exome sequencing data to study regional genetic differentiation across the UK and Ireland in protein coding genes, encompassing 44,696 unrelated individuals from 20 regions of origin. We demonstrate substantial exonic differentiation among Shetlanders, Orcadians, individuals with full or partial Ashkenazi Jewish ancestry and in several mainland regions (particularly north and south Wales, southeast Scotland and Ireland). With stringent filtering criteria, we find 67 regionally enriched (≥5-fold) variants likely to have adverse biomedical consequences in homozygous individuals. Here, we show that regional genetic variation across the UK and Ireland should be considered in the design of genetic studies and may inform effective genetic screening and counselling.
Metabolic interactions shape emergent biofilm structures in a conceptual model of gut mucosal bacterial communities
Authors: Valiei Amin , Dickson Andrew , Aminian-Dehkordi Javad , Mofrad Mohammad R. K. 
Published: October 2024

AbstractThe gut microbiome plays a major role in human health; however, little is known about the structural arrangement of microbes and factors governing their distribution. In this work, we present an in silico agent-based model (ABM) to conceptually simulate the dynamics of gut mucosal bacterial communities. We explored how various types of metabolic interactions, including competition, neutralism, commensalism, and mutualism, affect community structure, through nutrient consumption and metabolite exchange. Results showed that, across scenarios with different initial species abundances, cross-feeding promotes species coexistence. Morphologically, competition and neutralism resulted in segregation, while mutualism and commensalism fostered high intermixing. In addition, cooperative relations resulted in community properties with little sensitivity to the selective uptake of metabolites produced by the host. Moreover, metabolic interactions strongly influenced colonization success following the invasion of newcomer species. These results provide important insights into the utility of ABM in deciphering complex microbiome patterns.
Gate-set evaluation metrics for closed-loop optimal control on nitrogen-vacancy center ensembles in diamond
Authors: Vetter Philipp J. , Reisser Thomas , Hirsch Maximilian G. , Calarco Tommaso , Motzoi Felix , Jelezko Fedor , Müller Matthias M. 
Published: October 2024

AbstractA recurring challenge in quantum science and technology is the precise control of their underlying dynamics that lead to the desired quantum operations, often described by a set of quantum gates. These gates can be subject to application-specific errors, leading to a dependence of their controls on the chosen circuit, the quality measure and the gate-set itself. A natural solution would be to apply quantum optimal control in an application-oriented fashion. In turn, this requires the definition of a meaningful measure of the contextual gate-set performance. Therefore, we explore and compare the applicability of quantum process tomography, linear inversion gate-set tomography, randomized linear gate-set tomography, and randomized benchmarking as measures for closed-loop quantum optimal control experiments, using a macroscopic ensemble of nitrogen-vacancy centers in diamond as a test-bed. Our work demonstrates the relative trade-offs between those measures and how to significantly enhance the gate-set performance, leading to an improvement across all investigated methods.
Connectomic reconstruction predicts visual features used for navigation
Authors: Garner Dustin , Kind Emil , Lai Jennifer Yuet Ha , Nern Aljoscha , Zhao Arthur , Houghton Lucy , Sancer Gizem , Wolff Tanya , Rubin Gerald M. , Wernet Mathias F. , Kim Sung Soo 
Published: October 2024

AbstractMany animals use visual information to navigate1–4, but how such information is encoded and integrated by the navigation system remains incompletely understood. In Drosophila melanogaster, EPG neurons in the central complex compute the heading direction5 by integrating visual input from ER neurons6–12, which are part of the anterior visual pathway (AVP)10,13–16. Here we densely reconstruct all neurons in the AVP using electron-microscopy data17. The AVP comprises four neuropils, sequentially linked by three major classes of neurons: MeTu neurons10,14,15, which connect the medulla in the optic lobe to the small unit of the anterior optic tubercle (AOTUsu) in the central brain; TuBu neurons9,16, which connect the AOTUsu to the bulb neuropil; and ER neurons6–12, which connect the bulb to the EPG neurons. On the basis of morphologies, connectivity between neural classes and the locations of synapses, we identify distinct information channels that originate from four types of MeTu neurons, and we further divide these into ten subtypes according to the presynaptic connections in the medulla and the postsynaptic connections in the AOTUsu. Using the connectivity of the entire AVP and the dendritic fields of the MeTu neurons in the optic lobes, we infer potential visual features and the visual area from which any ER neuron receives input. We confirm some of these predictions physiologically. These results provide a strong foundation for understanding how distinct sensory features can be extracted and transformed across multiple processing stages to construct higher-order cognitive representations.
Barrier-free, open-top microfluidic chip for generating two distinct, interconnected 3D microvascular networks
Authors: Yrjänäinen Alma , Mesiä Elina , Lampela Ella , Kreutzer Joose , Vihinen Jorma , Tornberg Kaisa , Vuorenpää Hanna , Miettinen Susanna , Kallio Pasi , Mäki Antti-Juhana 
Published: October 2024

AbstractDeveloping microphysiological cell culture platforms with a three-dimensional (3D) microenvironment has been a significant advancement from traditional monolayer cultures. Still, most of the current microphysiological platforms are limited in closed designs, i.e. are not accessible after 3D cell culture loading. Here, we report an open-top microfluidic chip which enables the generation of two sequentially loaded 3D cell cultures without physical barriers restricting the nurture, gas exchange and cellular communication. As a proof-of-concept, we demonstrated the formation of two 3D vasculatures, one in the upper and the other in the lower compartment, under three distinct flow conditions: asymmetric side-to-center, symmetric side-to-center and symmetric center-to-side. We used computational modelling to characterize initial flow pressures in cell culture compartments. We showed prominent vessel formation and branched vasculatures in upper and lower cell culture compartments with interconnecting, lumenized vessels with in vivo-relevant diameter in all flow conditions. With advanced image processing, we quantified and compared the overall vascular network volume and the total length formed in asymmetric side-to-center, symmetric side-to-center and symmetric center-to-side flow conditions. Our results indicate that the developed chip can house two distinct 3D cell cultures with merging vessels between compartments and by providing asymmetric side-to-center or symmetric center-to-side flow vascular morphogenesis is enhanced in terms of overall network length. The developed open-top microfluidic chip may find various applications in generation of tissue-specific 3D-3D co-cultures for studying cellular interactions in vascularized tissues and organs.
A phenocopy signature of TP53 loss predicts response to chemotherapy
Authors: Bakhtiar Hamza , Sharifi Marina N. , Helzer Kyle T. , Shi Yue , Bootsma Matthew L. , Shang Tianfu A. , Chrostek Matthew R. , Berg Tracy J. , Carson Callahan S. , Carreno Viridiana , Blitzer Grace C. , West Malinda T. , O’Regan Ruth M. , Wisinski Kari B. , Sjöström Martin , Zhao Shuang G. 
Published: October 2024

AbstractIn preclinical studies, p53 loss of function impacts chemotherapy response, but this has not been consistently validated clinically. We trained a TP53-loss phenocopy gene expression signature from pan-cancer clinical samples in the TCGA. In vitro, the TP53-loss phenocopy signature predicted chemotherapy response across cancer types. In a clinical dataset of 3003 breast cancer samples treated with neoadjuvant chemotherapy, the TP53-loss phenocopy samples were 56% more likely to have a pathologic complete response (pCR), with a significant association between TP53-loss phenocopy and pCR in both ER positive and ER negative tumors. In an independent clinical validation in the I-SPY2 trial (N = 987), we confirmed the association with neoadjuvant chemotherapy pCR and found higher rates of chemoimmunotherapy response in TP53-loss phenocopy tumors compared to non-TP53-loss phenocopy tumors (64% vs. 28%). The TP53-loss phenocopy signature predicts chemotherapy response across cancer types in vitro, and in a proof-of-concept clinical validation is associated with neoadjuvant chemotherapy response across multiple clinical breast cancer cohorts.
Algorithmovigilance, lessons from pharmacovigilance
Authors: Balendran Alan , Benchoufi Mehdi , Evgeniou Theodoros , Ravaud Philippe 
Published: October 2024

AbstractArtificial Intelligence (AI) systems are increasingly being deployed across various high-risk applications, especially in healthcare. Despite significant attention to evaluating these systems, post-deployment incidents are not uncommon, and effective mitigation strategies remain challenging. Drug safety has a well-established history of assessing, monitoring, understanding, and preventing adverse effects in real-world usage, known as pharmacovigilance. Drawing inspiration from pharmacovigilance methods, we discuss concepts that can be adapted for monitoring AI systems in healthcare. This discussion aims to improve responses to adverse effects and potential incidents and risks associated with AI deployment in healthcare but also beyond.
Machine learning explains response variability of deep brain stimulation on Parkinson’s disease quality of life
Authors: Ferrea Enrico , Negahbani Farzin , Cebi Idil , Weiss Daniel , Gharabaghi Alireza 
Published: October 2024

AbstractImproving health-related quality of life (QoL) is crucial for managing Parkinson’s disease. However, QoL outcomes after deep brain stimulation (DBS) of the subthalamic nucleus (STN) vary considerably. Current approaches lack integration of demographic, patient-reported, neuroimaging, and neurophysiological data to understand this variability. This study used explainable machine learning to analyze multimodal factors affecting QoL changes, measured by the Parkinson’s Disease Questionnaire (PDQ-39) in 63 patients, and quantified each variable’s contribution. Results showed that preoperative PDQ-39 scores and upper beta band activity (>20 Hz) in the left STN were key predictors of QoL changes. Lower initial QoL burden predicted worsening, while improvement was associated with higher beta activity. Additionally, electrode positions along the superior-inferior axis, especially relative to the z = −7 coordinate in standard space, influenced outcomes, with improved and worsened QoL above and below this marker. This study emphasizes a tailored, data-informed approach to optimize DBS treatment and improve patient QoL.
Atomic-scale imaging of laser-driven electron dynamics in solids
Authors: Popova-Gorelova Daria , Santra Robin 
Published: October 2024

AbstractResolving laser-driven electron dynamics on their natural time and length scales is essential for understanding and controlling light-induced phenomena. Capabilities to reveal these dynamics are limited by challenges in interpreting wave mixing of a driving and a probe pulse, low energy resolution at ultrashort time scales and a lack of atomic-scale resolution by standard spectroscopic techniques. Here, we demonstrate how ultrafast x-ray diffraction can access fundamental information on laser-driven electronic motion in solids. We propose a method based on subcycle-resolved x-ray-optical wave mixing that allows for a straightforward reconstruction of key properties of strong-field-induced electron dynamics with atomic spatial resolution. Namely, this technique provides both phases and amplitudes of the spatial Fourier transform of optically-induced charge distributions, their temporal behavior, and the direction of the instantaneous microscopic optically-induced electron current flow. It captures the rich microscopic structures and symmetry features of laser-driven electronic charge and current density distributions.
Strategies to control humidity sensitivity of azobenzene isomerisation kinetics in polymer thin films
Authors: Vesamäki Sami , Meteling Henning , Nasare Roshan , Siiskonen Antti , Patrakka Jani , Roas-Escalona Nelmary , Linder Markus , Virkki Matti , Priimagi Arri 
Published: October 2024

AbstractAzobenzenes are versatile photoswitches that garner interest in applications ranging from photobiology to energy storage. Despite their great potential, transforming azobenzene-based discoveries and proof-of-concept demonstrations from the lab to the market is highly challenging. Herein we give an overview of a journey that started from a discovery of hydroxyazobenzene’s humidity sensitive isomerisation kinetics, developed into commercialization efforts of azobenzene-containing thin film sensors for optical monitoring of the relative humidity of air, and arrives to the present work aiming for better design of such sensors by understanding the different factors affecting the humidity sensitivity. Our concept is based on thermal isomerisation kinetics of tautomerizable azobenzenes in polymer matrices which, using pre-defined calibration curves, can be converted to relative humidity at known temperature. We present a small library of tautomerizable azobenzenes exhibiting humidity sensitive isomerisation kinetics in hygroscopic polymer films. We also investigate how water absorption properties of the polymer used, and the isomerisation kinetics are linked and how the azobenzene content in the thin film affects both properties. Based on our findings we propose simple strategies for further development of azobenzene-based optical humidity sensors.
Temporal dynamics in vertical leaf angles can confound vegetation indices widely used in Earth observations
Authors: Kattenborn Teja , Wieneke Sebastian , Montero David , Mahecha Miguel D. , Richter Ronny , Guimarães-Steinicke Claudia , Wirth Christian , Ferlian Olga , Feilhauer Hannes , Sachsenmaier Lena , Eisenhauer Nico , Dechant Benjamin 
Published: October 2024

AbstractEarth observation data is key for monitoring vegetation dynamics across temporal and spatial scales. The most widely used method to estimate vegetation properties from Earth observation data is vegetation indices. However, temporal dynamics in vertical leaf angles can strongly alter reflectance signals and, hence, vegetation indices. Here, we derive leaf angles from plant photographs to simulate the effect on vegetation indices with radiative transfer models. We show that leaf angle dynamics systematically confound widely applied vegetation indices. Moreover, we demonstrate that these effects are not random but tightly linked to abiotic environmental conditions. These systematic effects of vertical leaf angles have implications for monitoring plant properties, biodiversity, and ecosystem functional properties. We discuss the related challenges and opportunities to assess spatio-temporal vegetation dynamics with remote sensing and vegetation indices.
Deep stratospheric intrusion events in China revealed on the ground by cosmogenic 10Be/7Be
Authors: Liu Xuke , Fu Yunchong , Zhang Li , Li Haogen , Burr George S. , Bi Yanting , Zhao Guoqing 
Published: October 2024

AbstractGiven the impact of deep stratospheric intrusion on air quality, the development of more extensive trace substances to quantify stratospheric intrusion intensity can better distinguish between stratospheric ozone pollution and anthropogenic factors. The ratio of cosmogenic beryllium-10 to beryllium-7 (10Be/7Be), primarily generated in the stratosphere, has the potential to identify stratospheric air masses on the ground. Here we constructed a 10Be/7Be time-series (July 2020 to September 2021) in rainwater and aerosols from Xi’an, China. Combining in-situ pollutants, reanalysis data, and model calculations support a stratospheric origin for increased 10Be/7Be and identify it as a means of quantifying intrusion intensity. It was found that anticyclones formed by the Asian summer monsoon drive a sudden increase in deep stratospheric intrusion in spring, exacerbating ozone pollution beyond China’s air quality standards. Based on the sufficiently sensitive 10Be/7Be, it further indicates the process of six weak upper atmosphere intrusions in Xi’an during winter.