bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical and radiological evaluation of surgical treatment of medial epicondyle fractures of humerus in children. A two-centre study
Authors: Stelmach Wojciech , Beczkowski Jacek , Zając Piotr , Małecki Krzysztof , Sibiński Marcin , Niedzielski Kryspin 
Published: June 2023

AbstractThe present study analyses the outcome of open reduction and internal fixation (ORIF) of humerus medial epicondyle fracture with the use of Kirschner (K) wires, and determine the effect of elbow dislocation. The study included 112 patients operated on in 2005–2016. Of these, 81presented with an isolated medial epicondyle fracture (mean age 11.6 years), and 31 with an elbow dislocation (mean age 11.9 years). Out of 112 patients tested, 98 achieved an excellent treatment result, ten good and a mean Mayo Elbow Performance Score (MEPS); no significant differences were observed between dislocated and non-dislocated elbow groups. Those with an isolated medial epicondyle fracture demonstrated a mean flexion of 140.7° and extension deficit of 3.0°, while those with an elbow dislocation displayed a mean flexion of 134.5° and extension deficit 6.1°. The dislocation group demonstrated significantly greater extension and flexion deficits (p = 0.019, p < 0.001, respectively). One patient required revision surgery due to nonunion. Ulnar nerve function was normal in 110 patients: in the other two, it resolved spontaneously in one, and the nerve was transposed in the other. Medial elbow instability was found in seven patients: two with elbow dislocation and five without. ORIF with K wires is a safe procedure for treating medial epicondyle humeral fractures that yields good or very good results. Similar outcomes are observed between patients with and without dislocation according to MEPS; however, flexion and extension are more limited in the former group.
Radiation attenuation properties of chemically prepared MgO nanoparticles/HDPE composites
Authors: El-Khatib Ahmed M. , Gouda Mona M. , Fouad Mohamed S. , Abd-Elzaher Mohamed , Ramadan Wegdan 
Published: June 2023

AbstractSheets of high-density polyethylene (HDPE) loaded with magnesium oxide in micro and nano were synthesized with different weight percentages of micro-MgO (0,5,10,20 and 30% by weight) and nano-MgO (5 and 30%) and shaped in form of disc and dog bone shape. The morphological, mechanical, and attenuation characteristics of each concentration were determined. The linear attenuation coefficients (LAC) of the prepared discs were calculated using a well-calibrated scintillation detector and five standard gamma-ray point sources (241Am, 133Ba, 137Cs, 60Co and 152Eu). The LAC was theoretically calculated for HDPE/micro-MgO composites using XCOM software. A good agreement between the theoretical and experimental results was observed. The comparison between micro and nano-MgO as a filler in HDPE was evaluated. The results proved that the loaded nano-MgO in different proportions of HDPE produced greater attenuation coefficients than its micro counterpart. The addition of nano MgO with different weight percentage led to a significant improvement in the mechanical properties of HDPE, the ultimate force and ultimate stress increased as the concentration of nano MgO increased, and the young modulus of HDPE also increased with increasing concentration of micro and nano MgO.
The impact of extreme summer temperatures in the United Kingdom on infant sleep: Implications for learning and development
Authors: Berger Sarah E. , Ordway Monica R. , Schoneveld Emiel , Lucchini Maristella , Thakur Shambhavi , Anders Thomas , Natale Liza , Barnett Natalie 
Published: June 2023

AbstractThe U.S. Global Change Research Program reports that the frequency and intensity of extreme heat are increasing globally. Studies of the impact of climate change on child health often exclude sleep, despite its importance for healthy growth and development. To address this gap in the literature, we studied the impact of unusually high temperatures in the summer of 2022 on infants’ sleep. Sleep was assessed objectively using Nanit camera monitors in infants’ homes. Generally, sleep was not impacted when temperatures stayed below 88° but was negatively impacted when temperatures reached over 100°. Compared to non-heatwave nights, infants had less total sleep, less efficient sleep, took longer to fall asleep, had more fragmented sleep, and parents’ visits were more frequent during the night. Following peaks in temperature, sleep metrics rebounded to better than average compared to non-peak nights, suggesting that infants compensated for disrupted sleep by sleeping more and with fewer interruptions once the temperature dropped below 85°. Increased instances of disrupted sleep in infancy have important implications for psychological health and development. Climate disruptions such as heat waves that create occasional or ongoing sleep disruptions can leave infants vulnerable and unprepared for learning.
Structural connectome alterations in anxious dogs: a DTI-based study
Authors: Chen Qinyuan , Xu Yangfeng , Christiaen Emma , Wu Guo-Rong , De Witte Sara , Vanhove Christian , Saunders Jimmy , Peremans Kathelijne , Baeken Chris 
Published: June 2023

AbstractAnxiety and fear are dysfunctional behaviors commonly observed in domesticated dogs. Although dogs and humans share psychopathological similarities, little is known about how dysfunctional fear behaviors are represented in brain networks in dogs diagnosed with anxiety disorders. A combination of diffusion tensor imaging (DTI) and graph theory was used to investigate the underlying structural connections of dysfunctional anxiety in anxious dogs and compared with healthy dogs with normal behavior. The degree of anxiety was assessed using the Canine Behavioral Assessment & Research Questionnaire (C-BARQ), a widely used, validated questionnaire for abnormal behaviors in dogs. Anxious dogs showed significantly decreased clustering coefficient ($${C}_{p}$$

C
p

), decreased global efficiency ($${E}_{glob}$$

E

glob

), and increased small-worldness (σ) when compared with healthy dogs. The nodal parameters that differed between the anxious dogs and healthy dogs were mainly located in the posterior part of the brain, including the occipital lobe, posterior cingulate gyrus, hippocampus, mesencephalon, and cerebellum. Furthermore, the nodal degree ($${K}_{i}$$

K
i

) of the left cerebellum was significantly negatively correlated with “excitability” in the C-BARQ of anxious dogs. These findings could contribute to the understanding of a disrupted brain structural connectome underlying the pathological mechanisms of anxiety-related disorders in dogs.
Fractional calculus in mathematical oncology
Authors: Alinei-Poiana Tudor , Dulf Eva-H. , Kovacs Levente 
Published: June 2023

AbstractEven though, nowadays, cancer is one of the leading causes of death, too little is known about the behavior of this disease due to its unpredictability from one patient to another. Classical mathematical models of tumor growth have shaped our understanding of cancer and have broad practical implications for treatment scheduling and dosage. However, improvements are still necessary on these models. The primary objective of the present research is to prove the efficiency of fractional order calculus in mathematical oncology, more specifically in tumor growth modeling. For this, a generalization of the four most used differential equation models in tumor volume measurements fitting is realized, using the corresponding fractional order equivalent. Are established the fractional order Exponential, Logistic, Gompertz, General Bertalanffy-Pütter and Classical Bertalanffy-Pütter models for a treated and untreated dataset. The obtained results are compared by Mean Squared Error (MSE) with the integer order correspondent of each model. The results prove the superiority of the fractional order models. The MSE of fractional order models are reduced at least at half in comparison with the MSE of the integer order equivalent. It is demonstrated in this way that fractional order deterministic models can offer a good starting point in finding a proper mathematical model for tumor evolution prediction. Fractional calculus is a suitable method in this case due to its memory property, aspect that particularly characterizes biological processes.
Factors influencing oral microbiome analysis: from saliva sampling methods to next-generation sequencing platforms
Authors: Bang Eunsik , Oh Sujin , Ju Uijin , Chang Ho Eun , Hong Jin-Sil , Baek Hyeong-Jin , Kim Keun-Suh , Lee Hyo-Jung , Park Kyoung Un 
Published: June 2023

AbstractThe exploration of oral microbiome has been increasing due to its relatedness with various systemic diseases, but standardization of saliva sampling for microbiome analysis has not been established, contributing to the lack of data comparability. Here, we evaluated the factors that influence the microbiome data. Saliva samples were collected by the two collection methods (passive drooling and mouthwash) using three saliva-preservation methods (OMNIgene, DNA/RNA shield, and simple collection). A total of 18 samples were sequenced by both Illumina short-read and Nanopore long-read next-generation sequencing (NGS). The component of the oral microbiome in each sample was compared with alpha and beta diversity and the taxonomic abundances, to find out the effects of factors on oral microbiome data. The alpha diversity indices of the mouthwash sample were significantly higher than that of the drooling group with both short-read and long-read NGS, while no significant differences in microbial diversities were found between the three saliva-preservation methods. Our study shows mouthwash and simple collection are not inferior to other sample collection and saliva-preservation methods, respectively. This result is promising since the convenience and cost-effectiveness of mouthwash and simple collection can simplify the saliva sample preparation, which would greatly help clinical operators and lab workers.
Quantitative elemental mapping of biological tissues by laser-induced breakdown spectroscopy using matrix recognition
Authors: Janovszky Patrick , Kéri Albert , Palásti Dávid J. , Brunnbauer Lukas , Domoki Ferenc , Limbeck Andreas , Galbács Gábor 
Published: June 2023

AbstractThe present study demonstrates the importance of converting signal intensity maps of organic tissues collected by laser-induced breakdown spectroscopy (LIBS) to elemental concentration maps and also proposes a methodology based on machine learning for its execution. The proposed methodology employs matrix-matched external calibration supported by a pixel-by-pixel automatic matrix (tissue type) recognition performed by linear discriminant analysis of the spatially resolved LIBS hyperspectral data set. On a swine (porcine) brain sample, we successfully performed this matrix recognition with an accuracy of 98% for the grey and white matter and we converted a LIBS intensity map of a tissue sample to a correct concentration map for the elements Na, K and Mg. Found concentrations in the grey and white matter agreed the element concentrations published in the literature and our reference measurements. Our results revealed that the actual concentration distribution in tissues can be quite different from what is suggested by the LIBS signal intensity map, therefore this conversion is always suggested to be performed if an accurate concentration distribution is to be assessed.
Genome segment ratios change during whitefly transmission of two bipartite cassava mosaic begomoviruses
Authors: Kennedy George G. , Sharpee William , Jacobson Alana L. , Wambugu Mary , Mware Benard , Hanley-Bowdoin Linda 
Published: June 2023

AbstractCassava mosaic disease is caused by a complex of whitefly-transmitted begomoviruses, which often occur in co-infections. These viruses have bipartite genomes consisting of DNA-A and DNA-B that are encapsidated into separate virions. Individual viruses exist in plants and whitefly vectors as populations comprising both genome segments, which can occur at different frequencies. Both segments are required for infection, and must be transmitted for virus spread to occur. Cassava plants infected with African cassava mosaic virus (ACMV) and/or East African cassava mosaic Cameroon virus (EACMCV), in which the ratios of DNA-A:DNA-B titers differed between plants, were used to examine how titers of the segments in a plant relate to their respective probabilities of acquisition by whiteflies and to the titers of each segment acquired and subsequently transmitted by whiteflies. The probabilities of acquiring each segment of ACMV did not reflect their relative titers in the source plant but they did for EACMCV. However, for both viruses, DNA-A:DNA-B ratios acquired by whiteflies differed from those in the source plant and the ratios transmitted by the whitefly did not differ from one – the ratio at which the highest probability of transmitting both segments is expected.
Regional aerosol forecasts based on deep learning and numerical weather prediction
Authors: Qiu Yulu , Feng Jin , Zhang Ziyin , Zhao Xiujuan , Li Ziming , Ma Zhiqiang , Liu Ruijin , Zhu Jia 
Published: June 2023

AbstractAtmospheric chemistry transport models have been extensively applied in aerosol forecasts over recent decades, whereas they are facing challenges from uncertainties in emission rates, meteorological data, and over-simplified chemical parameterizations. Here, we developed a spatial-temporal deep learning framework, named PPN (Pollution-Predicting Net for PM2.5), to accurately and efficiently predict regional PM2.5 concentrations. It has an encoder-decoder architecture and combines the preceding PM2.5 observations and numerical weather prediction. Besides, the model proposes a weighted loss function to promote the forecasting performance in extreme events. We applied the proposed model to forecast 3-day PM2.5 concentrations over the Beijing-Tianjin-Hebei region in China on a three-hour-by-three-hour basis. Overall, the model showed good performance with R2 and RMSE values of 0.7 and 17.7 μg m−3, respectively. It could capture the high PM2.5 concentration in the south and relatively low concentration in the north and exhibit better performance within the next 24 h. The use of the weighted loss function decreased the level of “high values underestimation, low values overestimation”, while incorporating the preceding PM2.5 observations into the encoder phase improved the predictive accuracy within 24 h. We also compared the model result with that from a state-of-the-art numerical model (WRF-Chem with pollutant data assimilation). The temporal R2 and RMSE from the WRF-Chem were 0.30−0.77 and 19−45 μg m−3 while those from the PPN model were 0.42−0.84 and 15−42 μg m−3. The proposed model shows powerful capacity in aerosol forecasts and provides an efficient and accurate tool for early warning and management of regional pollution events.
Deep-learning-enabled brain hemodynamic mapping using resting-state fMRI
Authors: Hou Xirui , Guo Pengfei , Wang Puyang , Liu Peiying , Lin Doris D. M. , Fan Hongli , Li Yang , Wei Zhiliang , Lin Zixuan , Jiang Dengrong , Jin Jin , Kelly Catherine , Pillai Jay J. , Huang Judy , Pinho Marco C. , Thomas Binu P. , Welch Babu G. , Park Denise C. , Patel Vishal M. , Hillis Argye E. , Lu Hanzhang 
Published: June 2023

AbstractCerebrovascular disease is a leading cause of death globally. Prevention and early intervention are known to be the most effective forms of its management. Non-invasive imaging methods hold great promises for early stratification, but at present lack the sensitivity for personalized prognosis. Resting-state functional magnetic resonance imaging (rs-fMRI), a powerful tool previously used for mapping neural activity, is available in most hospitals. Here we show that rs-fMRI can be used to map cerebral hemodynamic function and delineate impairment. By exploiting time variations in breathing pattern during rs-fMRI, deep learning enables reproducible mapping of cerebrovascular reactivity (CVR) and bolus arrival time (BAT) of the human brain using resting-state CO2 fluctuations as a natural “contrast media”. The deep-learning network is trained with CVR and BAT maps obtained with a reference method of CO2-inhalation MRI, which includes data from young and older healthy subjects and patients with Moyamoya disease and brain tumors. We demonstrate the performance of deep-learning cerebrovascular mapping in the detection of vascular abnormalities, evaluation of revascularization effects, and vascular alterations in normal aging. In addition, cerebrovascular maps obtained with the proposed method exhibit excellent reproducibility in both healthy volunteers and stroke patients. Deep-learning resting-state vascular imaging has the potential to become a useful tool in clinical cerebrovascular imaging.
Auditory-motor synchronization varies among individuals and is critically shaped by acoustic features
Authors: Mares Cecilia , Echavarría Solana Ricardo , Assaneo M. Florencia 
Published: June 2023

AbstractThe ability to synchronize body movements with quasi-regular auditory stimuli represents a fundamental trait in humans at the core of speech and music. Despite the long trajectory of the study of such ability, little attention has been paid to how acoustic features of the stimuli and individual differences can modulate auditory-motor synchrony. Here, by exploring auditory-motor synchronization abilities across different effectors and types of stimuli, we revealed that this capability is more restricted than previously assumed. While the general population can synchronize to sequences composed of the repetitions of the same acoustic unit, the synchrony in a subgroup of participants is impaired when the unit’s identity varies across the sequence. In addition, synchronization in this group can be temporarily restored by being primed by a facilitator stimulus. Auditory-motor integration is stable across effectors, supporting the hypothesis of a central clock mechanism subserving the different articulators but critically shaped by the acoustic features of the stimulus and individual abilities.
Molecular and cellular evidence for the impact of a hypertrophic cardiomyopathy-associated RAF1 variant on the structure and function of contractile machinery in bioartificial cardiac tissues
Authors: Nakhaei-Rad Saeideh , Haghighi Fereshteh , Bazgir Farhad , Dahlmann Julia , Busley Alexandra Viktoria , Buchholzer Marcel , Kleemann Karolin , Schänzer Anne , Borchardt Andrea , Hahn Andreas , Kötter Sebastian , Schanze Denny , Anand Ruchika , Funk Florian , Kronenbitter Annette Vera , Scheller Jürgen , Piekorz Roland P. , Reichert Andreas S. , Volleth Marianne , Wolf Matthew J. , Cirstea Ion Cristian , Gelb Bruce D. , Tartaglia Marco , Schmitt Joachim P. , Krüger Martina , Kutschka Ingo , Cyganek Lukas , Zenker Martin , Kensah George , Ahmadian Mohammad R. 
Published: June 2023

AbstractNoonan syndrome (NS), the most common among RASopathies, is caused by germline variants in genes encoding components of the RAS-MAPK pathway. Distinct variants, including the recurrent Ser257Leu substitution in RAF1, are associated with severe hypertrophic cardiomyopathy (HCM). Here, we investigated the elusive mechanistic link between NS-associated RAF1S257L and HCM using three-dimensional cardiac bodies and bioartificial cardiac tissues generated from patient-derived induced pluripotent stem cells (iPSCs) harboring the pathogenic RAF1 c.770 C > T missense change. We characterize the molecular, structural, and functional consequences of aberrant RAF1–associated signaling on the cardiac models. Ultrastructural assessment of the sarcomere revealed a shortening of the I-bands along the Z disc area in both iPSC-derived RAF1S257L cardiomyocytes and myocardial tissue biopsies. The aforementioned changes correlated with the isoform shift of titin from a longer (N2BA) to a shorter isoform (N2B) that also affected the active force generation and contractile tensions. The genotype-phenotype correlation was confirmed using cardiomyocyte progeny of an isogenic gene-corrected RAF1S257L-iPSC line and was mainly reversed by MEK inhibition. Collectively, our findings uncovered a direct link between a RASopathy gene variant and the abnormal sarcomere structure resulting in a cardiac dysfunction that remarkably recapitulates the human disease.
Wnt signaling preserves progenitor cell multipotency during adipose tissue development
Authors: Yang Loureiro Zinger , Joyce Shannon , DeSouza Tiffany , Solivan-Rivera Javier , Desai Anand , Skritakis Pantos , Yang Qin , Ziegler Rachel , Zhong Denise , Nguyen Tammy T. , MacDougald Ormond A. , Corvera Silvia 
Published: June 2023

AbstractMesenchymal stem/progenitor cells are essential for tissue development and repair throughout life, but how they are maintained under chronic differentiation pressure is not known. Using single-cell transcriptomics of human progenitor cells we find that adipose differentiation stimuli elicit two cellular trajectories: one toward mature adipocytes and another toward a pool of non-differentiated cells that maintain progenitor characteristics. These cells are induced by transient Wnt pathway activation and express numerous extracellular matrix genes and are therefore named structural Wnt-regulated adipose tissue cells. We find that the genetic signature of structural Wnt-regulated adipose tissue cells is present in adult human adipose tissue and adipose tissue developed from human progenitor cells in mice. Our results suggest a mechanism whereby adipose differentiation occurs concurrently with the maintenance of a mesenchymal progenitor cell pool, ensuring tissue development, repair and appropriate metabolic control over the lifetime.
A multimodal atlas of tumour metabolism reveals the architecture of gene–metabolite covariation
Authors: Benedetti Elisa , Liu Eric Minwei , Tang Cerise , Kuo Fengshen , Buyukozkan Mustafa , Park Tricia , Park Jinsung , Correa Fabian , Hakimi A. Ari , Intlekofer Andrew M. , Krumsiek Jan , Reznik Ed 
Published: June 2023

AbstractTumour metabolism is controlled by coordinated changes in metabolite abundance and gene expression, but simultaneous quantification of metabolites and transcripts in primary tissue is rare. To overcome this limitation and to study gene–metabolite covariation in cancer, we assemble the Cancer Atlas of Metabolic Profiles of metabolomic and transcriptomic data from 988 tumour and control specimens spanning 11 cancer types in published and newly generated datasets. Meta-analysis of the Cancer Atlas of Metabolic Profiles reveals two classes of gene–metabolite covariation that transcend cancer types. The first corresponds to gene–metabolite pairs engaged in direct enzyme–substrate interactions, identifying putative genes controlling metabolite pool sizes. A second class of gene–metabolite covariation represents a small number of hub metabolites, including quinolinate and nicotinamide adenine dinucleotide, which correlate to many genes specifically expressed in immune cell populations. These results provide evidence that gene–metabolite covariation in cellularly heterogeneous tissue arises, in part, from both mechanistic interactions between genes and metabolites, and from remodelling of the bulk metabolome in specific immune microenvironments.