bluuebunny/crossref_metadata_2025_split huggingface dataset:
High versus low measurement frequency during 24-h ambulatory blood pressure monitoring - a randomized crossover study
Authors: Thomsen Martin B. , Nyvad Jakob , Christensen Kent L. , Reinhard Mark , Buus Niels Henrik 
Published: October 2023

AbstractAmbulatory blood pressure monitoring (ABPM) may be stressful and associated with discomfort, possibly influenced by the number of cuff inflations. We compared a low frequency (LF-ABPM) regimen with one cuff inflation per hour, with a high frequency (HF-ABPM) regimen performed according to current guidelines using three cuff-inflations per hour during daytime and two cuff-inflations during night time. In a crossover study, patients underwent ABPMs with both frequencies, in a randomized order, within an interval of a few days. Patients reported pain (visual analogue scale from 0 to 10) and sleep disturbances after each ABPM. The primary endpoint was the difference in mean 24 h systolic BP (SBP) between HF-ABPM and LF-ABPM. A total of 171 patients were randomized, and data from 131 (age 58 ± 14 years, 47% females, 24% normotensive, 53% mildly hypertensive, and 22% moderately-severely hypertensive) completing both ABPMs were included in the analysis. Mean SBP was 137.5 mmHg (95% CI, 134.8;140.2) for HF-ABPM and 138.2 mmHg (95%CI, 135.2;141.1) for LF-ABPM. The 95% limits of agreement were −15.3 mmHg and +14.0 mmHg. Mean 24 h SBP difference between HF-ABPM and LF-ABPM was −0.7 mmHg (95%CI, −2.0;0.6). Coefficients of variation were similar for LF-ABPM and HF-ABPM. Pain scores (median with interquartile range), for HF-ABPM and LF-ABPM were 1.5 (0.6;3.0) and 1.3 (0.6;2.9) during daytime, and 1.3 (0.4:3.4) and 0.9 (0.4;2.0) during nighttime (P < 0.05 for both differences). We conclude that LF-ABPM and HF-ABPM values are in good agreement without any clinically relevant differences in BP. Furthermore, LF-ABPM causes a relatively modest reduction in procedure-related pain.
Mexican Biobank advances population and medical genomics of diverse ancestries
Authors: Sohail Mashaal , Palma-Martínez María J. , Chong Amanda Y. , Quinto-Cortés Consuelo D. , Barberena-Jonas Carmina , Medina-Muñoz Santiago G. , Ragsdale Aaron , Delgado-Sánchez Guadalupe , Cruz-Hervert Luis Pablo , Ferreyra-Reyes Leticia , Ferreira-Guerrero Elizabeth , Mongua-Rodríguez Norma , Canizales-Quintero Sergio , Jimenez-Kaufmann Andrés , Moreno-Macías Hortensia , Aguilar-Salinas Carlos A. , Auckland Kathryn , Cortés Adrián , Acuña-Alonzo Víctor , Gignoux Christopher R. , Wojcik Genevieve L. , Ioannidis Alexander G. , Fernández-Valverde Selene L. , Hill Adrian V. S. , Tusié-Luna María Teresa , Mentzer Alexander J. , Novembre John , García-García Lourdes , Moreno-Estrada Andrés 
Published: October 2023

AbstractLatin America continues to be severely underrepresented in genomics research, and fine-scale genetic histories and complex trait architectures remain hidden owing to insufficient data1. To fill this gap, the Mexican Biobank project genotyped 6,057 individuals from 898 rural and urban localities across all 32 states in Mexico at a resolution of 1.8 million genome-wide markers with linked complex trait and disease information creating a valuable nationwide genotype–phenotype database. Here, using ancestry deconvolution and inference of identity-by-descent segments, we inferred ancestral population sizes across Mesoamerican regions over time, unravelling Indigenous, colonial and postcolonial demographic dynamics2–6. We observed variation in runs of homozygosity among genomic regions with different ancestries reflecting distinct demographic histories and, in turn, different distributions of rare deleterious variants. We conducted genome-wide association studies (GWAS) for 22 complex traits and found that several traits are better predicted using the Mexican Biobank GWAS compared to the UK Biobank GWAS7,8. We identified genetic and environmental factors associating with trait variation, such as the length of the genome in runs of homozygosity as a predictor for body mass index, triglycerides, glucose and height. This study provides insights into the genetic histories of individuals in Mexico and dissects their complex trait architectures, both crucial for making precision and preventive medicine initiatives accessible worldwide.
Ultra-fast deep-learned CNS tumour classification during surgery
Authors: Vermeulen C. , Pagès-Gallego M. , Kester L. , Kranendonk M. E. G. , Wesseling P. , Verburg N. , de Witt Hamer P. , Kooi E. J. , Dankmeijer L. , van der Lugt J. , van Baarsen K. , Hoving E. W. , Tops B. B. J. , de Ridder J. 
Published: October 2023

AbstractCentral nervous system tumours represent one of the most lethal cancer types, particularly among children1. Primary treatment includes neurosurgical resection of the tumour, in which a delicate balance must be struck between maximizing the extent of resection and minimizing risk of neurological damage and comorbidity2,3. However, surgeons have limited knowledge of the precise tumour type prior to surgery. Current standard practice relies on preoperative imaging and intraoperative histological analysis, but these are not always conclusive and occasionally wrong. Using rapid nanopore sequencing, a sparse methylation profile can be obtained during surgery4. Here we developed Sturgeon, a patient-agnostic transfer-learned neural network, to enable molecular subclassification of central nervous system tumours based on such sparse profiles. Sturgeon delivered an accurate diagnosis within 40 minutes after starting sequencing in 45 out of 50 retrospectively sequenced samples (abstaining from diagnosis of the other 5 samples). Furthermore, we demonstrated its applicability in real time during 25 surgeries, achieving a diagnostic turnaround time of less than 90 min. Of these, 18 (72%) diagnoses were correct and 7 did not reach the required confidence threshold. We conclude that machine-learned diagnosis based on low-cost intraoperative sequencing can assist neurosurgical decision-making, potentially preventing neurological comorbidity and avoiding additional surgeries.
Apoptotic stress causes mtDNA release during senescence and drives the SASP
Authors: Victorelli Stella , Salmonowicz Hanna , Chapman James , Martini Helene , Vizioli Maria Grazia , Riley Joel S. , Cloix Catherine , Hall-Younger Ella , Machado Espindola-Netto Jair , Jurk Diana , Lagnado Anthony B. , Sales Gomez Lilian , Farr Joshua N. , Saul Dominik , Reed Rebecca , Kelly George , Eppard Madeline , Greaves Laura C. , Dou Zhixun , Pirius Nicholas , Szczepanowska Karolina , Porritt Rebecca A. , Huang Huijie , Huang Timothy Y. , Mann Derek A. , Masuda Claudio Akio , Khosla Sundeep , Dai Haiming , Kaufmann Scott H. , Zacharioudakis Emmanouil , Gavathiotis Evripidis , LeBrasseur Nathan K. , Lei Xue , Sainz Alva G. , Korolchuk Viktor I. , Adams Peter D. , Shadel Gerald S. , Tait Stephen W. G. , Passos João F. 
Published: October 2023

AbstractSenescent cells drive age-related tissue dysfunction partially through the induction of a chronic senescence-associated secretory phenotype (SASP)1. Mitochondria are major regulators of the SASP; however, the underlying mechanisms have not been elucidated2. Mitochondria are often essential for apoptosis, a cell fate distinct from cellular senescence. During apoptosis, widespread mitochondrial outer membrane permeabilization (MOMP) commits a cell to die3. Here we find that MOMP occurring in a subset of mitochondria is a feature of cellular senescence. This process, called minority MOMP (miMOMP), requires BAX and BAK macropores enabling the release of mitochondrial DNA (mtDNA) into the cytosol. Cytosolic mtDNA in turn activates the cGAS–STING pathway, a major regulator of the SASP. We find that inhibition of MOMP in vivo decreases inflammatory markers and improves healthspan in aged mice. Our results reveal that apoptosis and senescence are regulated by similar mitochondria-dependent mechanisms and that sublethal mitochondrial apoptotic stress is a major driver of the SASP. We provide proof-of-concept that inhibition of miMOMP-induced inflammation may be a therapeutic route to improve healthspan.
Maximizing reusability of learning objects through machine learning techniques
Authors: Amane Meryem , Gouiouez Mounir , Berrada Mohammed 
Published: October 2023

AbstractMaximizing the reusability of learning objects through machine learning techniques has significantly transformed the landscape of e-learning systems. This progress has fostered authentic resource sharing and expanded opportunities for learners to explore these materials with ease. Consequently, a pressing need arises for an efficient categorization system to organize these learning objects effectively. This study consists of two primary phases. Firstly, we extract metadata from learning objects using web exploration algorithms, specifically employing feature selection techniques to identify the most relevant features while eliminating redundant ones. This step drastically reduces the dataset’s dimensionality, enabling the creation of practical and useful models. In the second phase, we employ machine learning algorithms to categorize learning objects based on their specific forms of similarity. These algorithms are adept at accurately classifying objects by measuring their similarity using Euclidean distance metrics. To evaluate the effectiveness of learning objects through machine learning techniques, a series of experimental studies were conducted using a real-world dataset. The results of this study demonstrate that the proposed machine learning approach surpasses traditional methods, yielding promising and efficient outcomes for enhancing learning object reusability.
Prognostic significance of serum fucosylated pro-haptoglobin in advanced renal cell carcinoma patients treated with immune checkpoint inhibitors
Authors: Kato Taigo , Morishita Koichi , Tomiyama Eisuke , Hayashibara Ayumu , Ishizuya Yu , Yamamoto Yoshiyuki , Hatano Koji , Kawashima Atsunari , Fukuhara Shinichiro , Nonomura Norio , Miyoshi Eiji , Fujita Kazutoshi 
Published: October 2023

AbstractWith the widespread use of immune checkpoint inhibitors (ICIs), identifying predictive biomarkers is critical. Recently, serum fucosylated haptoglobin (Fuc-Hp) was thought to play an important role in tumour immunity in several types of cancer. Therefore, evaluating serum Fuc-Hp in the peripheral blood can potentially identify non-invasive predictive biomarkers for the clinical efficacy of ICIs. In this study, 31 patients with advanced renal cell carcinoma (RCC) treated with nivolumab were enrolled and defined as responders or non-responders according to RECIST criteria. Serum samples were collected before and 1 month after treatment initiation, and an ELISA assay was performed using Aleuria Aurantia Lectin (AAL) and 10-7G monoclonal antibodies that recognise Fuc-mature Hp (Fuc-mHp) and Fuc-pro Hp (Fuc-pHp), respectively. We first measured AAL-haptoglobin (Fuc-mHp) and total haptoglobin levels before nivolumab and found that neither value could predict the clinical response. Notably, serum 10-7G levels were significantly lower in the responder group (p = 0.035). We also confirmed the use of serum 10-7G levels for predicting progressive disease after nivolumab (area under the curve, 0.816). Accordingly, low 10-7G levels were significantly correlated with better progression-free survival (p = 0.041). In conclusion, serum Fuc-pHp analysis may identify patients with advanced RCC who benefit from ICIs.
Anisotropy in spinodal-like dynamics of unknown water at ice V–water interface
Authors: Niinomi Hiromasa , Yamazaki Tomoya , Nada Hiroki , Hama Tetsuya , Kouchi Akira , Oshikiri Tomoya , Nakagawa Masaru , Kimura Yuki 
Published: October 2023

AbstractExperimentally demonstrating the existence of waters with local structures unlike that of common water is critical for understanding both the origin of the mysterious properties of water and liquid polymorphism in single component liquids. At the interfaces between water and ices Ih, III, and VI grown/melted under pressure, we previously discovered low- and high-density unknown waters, that are immiscible with the surrounding water. Here, we show, by in-situ optical microscopy, that an unknown water appears at the ice V–water interface via spinodal-like dynamics. The dewetting dynamics of the unknown water indicate that its characteristic velocity is ~ 90 m/s. The time evolution of the characteristic length of the spinodal-like undulation suggests that the dynamics may be described by a common model for spinodal decomposition of an immiscible liquid mixture. Spinodal-like dewetting dynamics of the unknown water transiently showed anisotropy, implying the property of a liquid crystal.
Experimental analysis of oil flow and drag torque generation in disengaged wet clutches
Authors: Pointner-Gabriel Lukas , Schermer Elias , Schneider Thomas , Stahl Karsten 
Published: October 2023

AbstractFundamental knowledge of the oil flow in a disengaged wet clutch is essential for optimizing the cooling performance and the drag losses. However, no fundamental information on the oil flow and drag torque generation is available for dip-lubricated wet clutches. Therefore, the oil flow and drag torque generation in the sub-millimeter gap of a dip-lubricated wet clutch was experimentally investigated for three practically relevant oil levels. To enable optical access to the gap, transparent components were used. Further, a high-speed camera was used to capture the oil flow in the gap and grooving. Independent of the set oil level, the gap is oil-filled at low differential speeds, resulting in a single-phase flow. The drag torque increases approximately linearly with increasing differential speed due to the fluid shearing. In certain regions of the waffle grooving, air bubbles form locally. The air bubbles preferably occur in the grooves oriented in the radial direction, while the grooves oriented in the peripheral direction are filled with oil. Above a certain differential speed, the oil is continuously displaced from the gap, starting from the inside, due to the increasing centrifugal force. Consequently, the drag torque increases in a degressive manner until a maximum value is finally reached. The ongoing displacement of oil from the gap eventually results in a decrease in the drag torque. A steady drag torque is generated only when the oil is almost entirely displaced from the gap. Since the oil displacement from the gap already commences at a low differential speed, the cooling performance is limited for dip-lubricated wet clutches. The continuous displacement of oil from the gap can be held up, among other things, by increasing the oil level.
The effects of lineup size on the processes underlying eyewitness decisions
Authors: Menne Nicola Marie , Winter Kristina , Bell Raoul , Buchner Axel 
Published: October 2023

AbstractHere we apply the two-high threshold eyewitness identification model to identify the effects of lineup size on the detection-based and non-detection-based processes underlying eyewitness decisions. In Experiment 1, lineup size was manipulated by showing participants simultaneous or sequential lineups that contained either three or six persons. In Experiment 2, the lineups contained either two or five persons. In both experiments, the culprit was better detected in smaller than in larger lineups. Furthermore, participants made fewer guessing-based selections in smaller than in larger lineups. However, guessing-based selection in larger lineups was not increased to a level sufficient to offset the effect of increased protection of suspects in larger lineups due to the fact that the guessing-based selections that occur are distributed across more persons. The results show that increasing the lineup size causes several changes in the detection-based and non-detection-based processes underlying eyewitness decisions.
CFD-DEM model of plugging in flow with cohesive particles
Authors: Saparbayeva Nazerke , Balakin Boris V. 
Published: October 2023

AbstractPlugging in flows with cohesive particles is crucial in many industrial and real-life applications such as hemodynamics, water distribution, and petroleum flow assurance. Although probabilistic models for plugging risk estimation are presented in the literature, multiple details of the process remain unclear. In this paper, we present a CFD-DEM model of plugging validated against several experimental benchmarks. Using the simulations, we consider the process of plugging in a slurry of ice in decane, focusing on inter-particle collisions and plugging dynamics. We conduct a parametric study altering the Reynolds number (3000...9000), particle concentration (1.6...7.3%), and surface energy (21...541 mJ/m$$^2$$

2

). We note the process possesses complex non-linear behaviour for the cases where particle-wall adhesion reduces by more than 20% relative to inter-particle cohesion. Finally, we demonstrate how the simulation results match the flow maps based on the third-party experiments.
Computing all persistent subspaces of a reaction-diffusion system
Authors: Peter Stephan , Woitke Linus , Dittrich Peter , Ibrahim Bashar 
Published: October 2023

AbstractAn algorithm is presented for computing a reaction-diffusion partial differential equation (PDE) system for all possible subspaces that can hold a persistent solution of the equation. For this, all possible sub-networks of the underlying reaction network that are distributed organizations (DOs) are identified. Recently it has been shown that a persistent subspace must be a DO. The algorithm computes the hierarchy of DOs starting from the largest by a linear programming approach using integer cuts. The underlying constraints use elementary reaction closures as minimal building blocks to guarantee local closedness and global self-maintenance, required for a DO. Additionally, the algorithm delivers for each subspace an affiliated set of organizational reactions and minimal compartmentalization that is necessary for this subspace to persist. It is proved that all sets of organizational reactions of a reaction network, as already DOs, form a lattice. This lattice contains all potentially persistent sets of reactions of all constrained solutions of reaction-diffusion PDEs. This provides a hierarchical structure of all persistent subspaces with regard to the species and also to the reactions of the reaction-diffusion PDE system. Here, the algorithm is described and the corresponding Python source code is provided. Furthermore, an analysis of its run time is performed and all models from the BioModels database as well as further examples are examined. Apart from the practical implications of the algorithm the results also give insights into the complexity of solving reaction-diffusion PDEs.
Predicting maximum temperatures over India 10-days ahead using machine learning models
Authors: Ratnam J. V. , Behera Swadhin K. , Nonaka Masami , Martineau Patrick , Patil Kalpesh R. 
Published: October 2023

AbstractIn the months of March-June, India experiences high daytime temperatures (Tmax), which sometimes lead to heatwave-like conditions over India. In this study, 10 different machine learning models are evaluated for their ability to predict the daily Tmax anomalies 10 days ahead in the months of March-June. Several model experiments were carried out to identify an optimal model to predict daily Tmax anomalies over India. The results indicate that the AdaBoost regressor with Multi-layer Perceptron as the base estimator is an optimal model to predict the Tmax anomalies over India in the months of March-June. The optimal model predictions are benchmarked against 10-day persistence predictions and the predictions from the Climate Forecast System (CFS) reforecast. The results indicate that the machine learning model skill is higher than persistence and comparable to CFS reforecast 10-day predictions in April and May. In March and June, the machine learning models have low skill scores and perform no better than persistence. These results indicate that the machine learning models are promising tools to predict the surface air maximum temperature anomalies over India in April and May and can complement predictions from more sophisticated numerical models.
Long-lasting effects of World War II trauma on PTSD symptoms and embodiment levels in a national sample of Poles
Authors: Rzeszutek Marcin , Dragan Małgorzata , Lis-Turlejska Maja , Schier Katarzyna , Holas Paweł , Pięta Małgorzata , Van Hoy Angelika , Drabarek Katarzyna , Poncyliusz Cecylia , Michałowska Magdalena , Wdowczyk Gabriela , Borowska Natalia , Szumiał Szymon 
Published: October 2023

AbstractThe main aim of this study was to investigate the long-lasting influences of World War II (WWII) trauma in a national sample of Poles, based on Danieli’s (1998) survivors’ post-trauma adaptational styles (fighter, numb, victim) and their link with current post-traumatic stress disorder (PTSD) symptoms and embodiment level among participants. We also sought to investigate whether the level of knowledge about WWII trauma among ancestors could moderate that association. The study was conducted among a representative sample of 1598 adult Poles obtained from an external company. Participants filled out the Danieli Inventory of Multigenerational Legacies of Trauma, the knowledge about traumatic World War II experiences in the family questionnaire, the Posttraumatic Diagnostic Scale-5, and the Experience of Embodiment Scale. We observed a positive relationship between all survivors’ post-trauma adaptational styles and current levels of PTSD symptoms among participants. In addition, PTSD level mediated the relationships between those adaptational styles and embodiment intensity; that mediation was additionally moderated by a lack of knowledge about WWII trauma among ancestors in our participants. Our study adds to the literature on intergenerational trauma by highlighting the importance of evaluating embodiment in understanding the mechanisms of trauma transmission. Furthermore, it highlights the moderating effect of knowledge of family history in this mechanism and the need to share family histories with subsequent generations.
Human equivalent doses of l-DOPA rescues retinal morphology and visual function in a murine model of albinism
Authors: Sanchez-Bretano Aida , Keeling Eloise , Scott Jennifer A. , Lynn Savannah A. , Soundara-Pandi Sudha Priya , Macdonald Sarah L. , Newall Tutte , Griffiths Helen , Lotery Andrew J. , Ratnayaka J. Arjuna , Self Jay E. , Lee Helena 
Published: October 2023

Abstractl-DOPA is deficient in the developing albino eye, resulting in abnormalities of retinal development and visual impairment. Ongoing retinal development after birth has also been demonstrated in the developing albino eye offering a potential therapeutic window in humans. To study whether human equivalent doses of l-DOPA/Carbidopa administered during the crucial postnatal period of neuroplasticity can rescue visual function, OCA C57BL/6 J-c2J OCA1 mice were treated with a 28-day course of oral l-DOPA/Carbidopa at 3 different doses from 15 to 43 days postnatal age (PNA) and for 3 different lengths of treatment, to identify optimum dosage and treatment length. Visual electrophysiology, acuity, and retinal morphology were measured at 4, 5, 6, 12 and 16 weeks PNA and compared to untreated C57BL/6 J (WT) and OCA1 mice. Quantification of PEDF, βIII-tubulin and syntaxin-3 expression was also performed. Our data showed impaired retinal morphology, decreased retinal function and lower visual acuity in untreated OCA1 mice compared to WT mice. These changes were diminished or eliminated when treated with higher doses of l-DOPA/Carbidopa. Our results demonstrate that oral l-DOPA/Carbidopa supplementation at human equivalent doses during the postnatal critical period of retinal neuroplasticity can rescue visual retinal morphology and retinal function, via PEDF upregulation and modulation of retinal synaptogenesis, providing a further step towards developing an effective treatment for albinism patients.