bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effect of chemical and structural modifiers on the haemostatic process and cytotoxicity of the beta-chitin patch
Authors: Sabab Ahad , Liu Sha , Javadiyan Shari , McAdam C. John , Hanton Lyall R. , Jukes Alistair , Vreugde Sarah , Wormald Peter-John 
Published: September 2021

AbstractBeta-chitin patch has previously been proven to be an effective haemostat, but whether modifying the patch affects its efficacy and safety, remains unanswered. In this study, the patch was modified using polyethylene oxide, Pluronic-F127, calcium, increased thickness or polyphosphate, and their effect on the process of haemostasis and cytotoxicity was tested and compared with standard-of-care, Surgicel and FloSeal. Whole blood collected from volunteers was applied to the patches to test their whole blood clotting and thrombin generation capacities, whilst platelet isolates were used to test their platelet aggregation ability. The fluid absorption capacity of the patches was tested using simulated body fluid. Cytotoxicity of the patches was tested using AlamarBlue assays and PC12 cells and the results were compared with the standard-of-care. In this study, beta-chitin patch modifications failed to improve its whole blood clotting, platelet aggregation and thrombin generation capacity. Compared to non-modified patch, modifications with polyethylene oxide or calcium reduced platelet aggregation and thrombin generation capacity, while increasing the thickness or adding polyphosphate decreased platelet aggregation capacity. The cytotoxicity assays demonstrated that the beta-chitin patches were non-toxic to cells. In vivo research is required to evaluate the safety and efficacy of the beta-chitin patches in a clinical setting.
Blunted emotion judgments of body movements in Parkinson’s disease
Authors: Bellot Emmanuelle , Garnier-Crussard Antoine , Pongan Elodie , Delphin-Combe Floriane , Coste Marie-Hélène , Gentil Claire , Rouch Isabelle , Hénaff Marie-Anne , Schmitz Christina , Tillmann Barbara , Krolak-Salmon Pierre 
Published: September 2021

AbstractSome of the behavioral disorders observed in Parkinson’s disease (PD) may be related to an altered processing of social messages, including emotional expressions. Emotions conveyed by whole body movements may be difficult to generate and be detected by PD patients. The aim of the present study was to compare valence judgments of emotional whole body expressions in individuals with PD and in healthy controls matched for age, gender and education. Twenty-eight participants (13 PD patients and 15 healthy matched control participants) were asked to rate the emotional valence of short movies depicting emotional interactions between two human characters presented with the “Point Light Displays” technique. To ensure understanding of the perceived scene, participants were asked to briefly describe each of the evaluated movies. Patients’ emotional valence evaluations were less intense than those of controls for both positive (p < 0.001) and negative (p < 0.001) emotional expressions, even though patients were able to correctly describe the depicted scene. Our results extend the previously observed impaired processing of emotional facial expressions to impaired processing of emotions expressed by body language. This study may support the hypothesis that PD affects the embodied simulation of emotional expression and the potentially involved mirror neuron system.
Multi GPU parallelization of maximum likelihood expectation maximization method for digital rock tomography data
Authors: Prakash Jaya , Agarwal Umang , Yalavarthy Phaneendra K. 
Published: September 2021

AbstractDigital rock is an emerging area of rock physics, which involves scanning reservoir rocks using X-ray micro computed tomography (XCT) scanners and using it for various petrophysical computations and evaluations. The acquired micro CT projections are used to reconstruct the X-ray attenuation maps of the rock. The image reconstruction problem can be solved by utilization of analytical (such as Feldkamp–Davis–Kress (FDK) algorithm) or iterative methods. Analytical schemes are typically computationally more efficient and hence preferred for large datasets such as digital rocks. Iterative schemes like maximum likelihood expectation maximization (MLEM) are known to generate accurate image representation over analytical scheme in limited data (and/or noisy) situations, however iterative schemes are computationally expensive. In this work, we have parallelized the forward and inverse operators used in the MLEM algorithm on multiple graphics processing units (multi-GPU) platforms. The multi-GPU implementation involves dividing the rock volumes and detector geometry into smaller modules (along with overlap regions). Each of the module was passed onto different GPU to enable computation of forward and inverse operations. We observed an acceleration of $$\sim 30$$

∼
30

times using our multi-GPU approach compared to the multi-core CPU implementation. Further multi-GPU based MLEM obtained superior reconstruction compared to traditional FDK algorithm.
Searching for metastable particles using graph computing
Authors: Kotwal Ashutosh V. 
Published: September 2021

AbstractThe reconstruction of charged particle trajectories at the Large Hadron Collider and future colliders relies on energy depositions in sensors placed at distances ranging from a centimeter to a meter from the colliding beams. We propose a method of detecting charged particles that decay invisibly after traversing a short distance of about 25 cm inside the experimental apparatus. One of the decay products may constitute the dark matter known to be 84% of all matter at galactic and cosmological distance scales. Our method uses graph computing to cluster spacepoints recorded by two-dimensional silicon pixel sensors into mathematically-defined patterns. The algorithm may be implemented on silicon-based integrated circuits using field-programmable gate array technology to augment or replace traditional computing platforms.
Oxidation-enhanced thermoelectric efficiency in a two-dimensional phosphorene oxide
Authors: Lee Seungjun , Song Jeong-Pil , Kang Seoung-Hun , Kwon Young-Kyun 
Published: September 2021

AbstractWe performed density functional theory calculations to investigate the thermoelectric properties of phosphorene oxide (PO) expected to form by spontaneous oxidation of phosphorene. Since thermoelectric features by nature arise from the consequences of the electron-phonon interaction, we computed the phonon-mediated electron relaxation time, which was fed into the semiclassical Boltzmann transport equation to be solved for various thermoelectric-related quantities. It was found that PO exhibits superior thermoelectric performance compared with its pristine counterpart, which has been proposed to be a candidate for the use of future thermoelectric applications. We revealed that spontaneous oxidation of phosphorene leads to a significant enhancement in the thermoelectric properties of n-doped phosphorene oxide, which is attributed to the considerable reduction of lattice thermal conductivity albeit a small decrease in electrical conductivity. Our results suggest that controlling oxidation may be utilized to improve thermoelectric performance in nanostructures, and PO can be a promising candidate for low-dimensional thermoelectric devices.
Multiscale computational modeling of cancer growth using features derived from microCT images
Authors: Zangooei M. Hossein , Margolis Ryan , Hoyt Kenneth 
Published: September 2021

AbstractAdvances in medical imaging technologies now allow noninvasive image acquisition from individual patients at high spatiotemporal resolutions. A relatively new effort of predictive oncology is to develop a paradigm for forecasting the future status of an individual tumor given initial conditions and an appropriate mathematical model. The objective of this study was to introduce a comprehensive multiscale computational method to predict cancer and microvascular network growth patterns. A rectangular lattice-based model was designed so different evolutionary scenarios could be simulated and for predicting the impact of diffusible factors on tumor morphology and size. Further, the model allows prediction-based simulation of cell and microvascular behavior. Like a single cell, each agent is fully realized within the model and interactions are governed in part by machine learning methods. This multiscale computational model was developed and incorporated input information from in vivo microscale computed tomography (microCT) images acquired from breast cancer-bearing mice. It was found that as the difference between expansion of the cancer cell population and microvascular network increases, cells undergo proliferation and migration with a greater probability compared to other phenotypes. Overall, multiscale computational model agreed with both theoretical expectations and experimental findings (microCT images) not used during model training.
Cognitive control affects motor learning through local variations in GABA within the primary motor cortex
Authors: Maruyama Shuki , Fukunaga Masaki , Sugawara Sho K. , Hamano Yuki H. , Yamamoto Tetsuya , Sadato Norihiro 
Published: September 2021

AbstractThe primary motor cortex (M1) is crucial for motor learning; however, its interaction with other brain areas during motor learning remains unclear. We hypothesized that the fronto-parietal execution network (FPN) provides learning-related information critical for the flexible cognitive control that is required for practice. We assessed network-level changes during sequential finger tapping learning under speed pressure by combining magnetic resonance spectroscopy and task and resting-state functional magnetic resonance imaging. There was a motor learning-related increase in preparatory activity in the fronto-parietal regions, including the right M1, overlapping the FPN and sensorimotor network (SMN). Learning-related increases in M1-seeded functional connectivity with the FPN, but not the SMN, were associated with decreased GABA/glutamate ratio in the M1, which were more prominent in the parietal than the frontal region. A decrease in the GABA/glutamate ratio in the right M1 was positively correlated with improvements in task performance (p = 0.042). Our findings indicate that motor learning driven by cognitive control is associated with local variations in the GABA/glutamate ratio in the M1 that reflects remote connectivity with the FPN, representing network-level motor sequence learning formations.
Emergence of topological superconductivity in doped topological Dirac semimetals under symmetry-lowering lattice distortions
Authors: Cheon Sangmo , Lee Ki Hoon , Chung Suk Bum , Yang Bohm-Jung 
Published: September 2021

AbstractRecently, unconventional superconductivity having a zero-bias conductance peak is reported in doped topological Dirac semimetal (DSM) with lattice distortion. Motivated by the experiments, we theoretically study the possible symmetry-lowering lattice distortions and their effects on the emergence of unconventional superconductivity in doped topological DSM. We find four types of symmetry-lowering lattice distortions that reproduce the crystal symmetries relevant to experiments from the group-theoretical analysis. Considering inter-orbital and intra-orbital electron density-density interactions, we calculate superconducting phase diagrams. We find that the lattice distortions can induce unconventional superconductivity hosting gapless surface Andreev bound states (SABS). Depending on the lattice distortions and superconducting pairing interactions, the unconventional inversion-odd-parity superconductivity can be either topological nodal superconductivity hosting a flat SABS or topological crystalline superconductivity hosting a gapless SABS. Remarkably, the lattice distortions increase the superconducting critical temperature, which is consistent with the experiments. Our work opens a pathway to explore and control pressure-induced topological superconductivity in doped topological semimetals.
Angiotensin converting enzyme inhibitors and incidence of lung cancer in a population based cohort of common data model in Korea
Authors: Lee Seung-Hwa , Chun Kwang Jin , Park Jungchan , Kim Jinseob , Sung Ji Dong , Park Rae Woong , Choi Jinwook , Yang Kwangmo 
Published: September 2021

AbstractContradictory findings exist about association of angiotensin-converting enzyme inhibitor (ACEi) and angiotensin receptor blocker (ARB) with lung cancer development. This was a retrospective observational cohort study that used data from 7 hospitals in Korea, converted to the Observational Medical Outcomes Partnership Common Data Model. The primary outcome was occurrence of lung cancer. A total of 207,794 patients across the 7 databases was included in the final analysis; 33,230 (16%) were prescribed ACEi and 174,564 (84%) were prescribed ARB. Crude analysis adjusted for sex and age showed higher incidence of lung cancer in the ACEi group compared to the ARB group (hazard ratio [HR], 1.46; 95% confidence rate [CI], 1.08–1.97). After propensity-score matching, 30,445 pairs were generated, and there was no difference in incidence of lung cancer between the two groups (HR, 0.93; 95% CI, 0.64–1.35). Patients prescribed ACEi showed no difference in incidence of lung cancer development compared to those using ARB. This finding provides evidence on the association between ACEi and occurrence of lung cancer.
Biopsy bacterial signature can predict patient tissue malignancy
Authors: Hogan Glenn , Eckenberger Julia , Narayanen Neegam , Walker Sidney P. , Claesson Marcus J. , Corrigan Mark , O’Hanlon Deirdre , Tangney Mark 
Published: September 2021

AbstractConsiderable recent research has indicated the presence of bacteria in a variety of human tumours and matched normal tissue. Rather than focusing on further identification of bacteria within tumour samples, we reversed the hypothesis to query if establishing the bacterial profile of a tissue biopsy could reveal its histology / malignancy status. The aim of the present study was therefore to differentiate between malignant and non-malignant fresh breast biopsy specimens, collected specifically for this purpose, based on bacterial sequence data alone. Fresh tissue biopsies were obtained from breast cancer patients and subjected to 16S rRNA gene sequencing. Progressive microbiological and bioinformatic contamination control practices were imparted at all points of specimen handling and bioinformatic manipulation. Differences in breast tumour and matched normal tissues were probed using a variety of statistical and machine-learning-based strategies. Breast tumour and matched normal tissue microbiome profiles proved sufficiently different to indicate that a classification strategy using bacterial biomarkers could be effective. Leave-one-out cross-validation of the predictive model confirmed the ability to identify malignant breast tissue from its bacterial signature with 84.78% accuracy, with a corresponding area under the receiver operating characteristic curve of 0.888. This study provides proof-of-concept data, from fit-for-purpose study material, on the potential to use the bacterial signature of tissue biopsies to identify their malignancy status.
Combined assessment of the GAP index and body mass index at antifibrotic therapy initiation for prognosis of idiopathic pulmonary fibrosis
Authors: Suzuki Yuzo , Mori Kazutaka , Aono Yuya , Kono Masato , Hasegawa Hirotsugu , Yokomura Koshi , Naoi Hyogo , Hozumi Hironao , Karayama Masato , Furuhashi Kazuki , Enomoto Noriyuki , Fujisawa Tomoyuki , Nakamura Yutaro , Inui Naoki , Nakamura Hidenori , Suda Takafumi 
Published: September 2021

AbstractAntifibrotic therapy (AFT) slows disease progression in patients with idiopathic pulmonary fibrosis (IPF). The Gender-Age-Physiology (GAP) index, was developed based on data at IPF diagnosis before the introduction of AFT and has not been evaluated in the AFT context. Further, recent advances have revealed the importance of body-composition factors in prognosis of IPF treated with AFT. This multi-centre, retrospective study aimed to evaluate the GAP index and body mass index (BMI) at the time of AFT initiation for predicting prognosis in patients with IPF. This study included two patient cohorts of IPF receiving AFT, Hamamatsu cohort (n = 110) and Seirei cohort (n = 119). The distribution of GAP stages I, II, and III was 38.2%, 43.6%, and 18.2%, respectively, in Hamamatsu cohort; in Seirei cohort, it was 41.2%, 50.4%, and 8.4%, respectively. In both cohorts, the GAP index distinctly classified prognosis into three groups (log-rank test). Interestingly, a lower BMI showed prognostic value independent of the GAP index in multivariate analyses. Subsequently, combining the GAP index with BMI at AFT initiation successfully divided the patients with IPF into four distinct prognoses. Assessment of the GAP index and BMI measurement at AFT initiation are important for predicting prognosis in patients with IPF.
Visual exploration dynamics are low-dimensional and driven by intrinsic factors
Authors: Zangrossi Andrea , Cona Giorgia , Celli Miriam , Zorzi Marco , Corbetta Maurizio 
Published: September 2021

AbstractWhen looking at visual images, the eyes move to the most salient and behaviourally relevant objects. Saliency and semantic information significantly explain where people look. Less is known about the spatiotemporal properties of eye movements (i.e., how people look). We show that three latent variables explain 60% of eye movement dynamics of more than a hundred observers looking at hundreds of different natural images. The first component explaining 30% of variability loads on fixation duration, and it does not relate to image saliency or semantics; it approximates a power-law distribution of gaze steps, an intrinsic dynamic measure, and identifies observers with two viewing styles: static and dynamic. Notably, these viewing styles were also identified when observers look at a blank screen. These results support the importance of endogenous processes such as intrinsic dynamics to explain eye movement spatiotemporal properties.
Discovery of a small protein-encoding cis-regulatory overlapping gene of the tumor suppressor gene Scribble in humans
Authors: Nomura Yuhta , Dohmae Naoshi 
Published: September 2021

AbstractIntensive gene annotation has revealed many functional and regulatory elements in the human genome. Although eukaryotic protein-coding genes are generally transcribed into monocistronic mRNAs, recent studies have discovered additional short open reading frames (sORFs) in mRNAs. Here, we performed proteogenomic data mining for hidden proteins categorized into sORF-encoded polypeptides (SEPs) in human cancers. We identified a new SEP-encoding overlapping sORF (oORF) on the cell polarity determinant Scribble (SCRIB) that is considered a proto-oncogene with tumor suppressor function in Hippo-YAP/TAZ, MAPK/ERK, and PI3K/Akt/mTOR signaling. Reanalysis of clinical human proteomic data revealed translational dysregulation of both SCRIB and its oORF, oSCRIB, during carcinogenesis. Biochemical analyses suggested that the translatable oSCRIB constitutively limits the capacity of eukaryotic ribosomes to translate the downstream SCRIB. These findings provide a new example of cis-regulatory oORFs that function as a ribosomal roadblock and potentially serve as a fail-safe mechanism to normal cells for non-excessive downstream gene expression, which is hijacked in cancer.
Nuclear-driven production of renewable fuel additives from waste organics
Authors: Plant Arran George , Kos Bor , Jazbec Anže , Snoj Luka , Najdanovic-Visak Vesna , Joyce Malcolm John 
Published: September 2021

AbstractNon-intermittent, low-carbon energy from nuclear or biofuels is integral to many strategies to achieve Carbon Budget Reduction targets. However, nuclear plants have high, upfront costs and biodiesel manufacture produces waste glycerol with few secondary uses. Combining these technologies, to precipitate valuable feedstocks from waste glycerol using ionizing radiation, could diversify nuclear energy use whilst valorizing biodiesel waste. Here, we demonstrate solketal (2,2-dimethyl-1,3-dioxolane-4-yl) and acetol (1-hydroxypropan-2-one) production is enhanced in selected aqueous glycerol-acetone mixtures with γ radiation with yields of 1.5 ± 0.2 µmol J−1 and 1.8 ± 0.2 µmol J−1, respectively. This is consistent with the generation of either the stabilized, protonated glycerol cation (CH2OH-CHOH-CH2OH2+ ) from the direct action of glycerol, or the hydronium species, H3O+, via water radiolysis, and their role in the subsequent acid-catalyzed mechanisms for acetol and solketal production. Scaled to a hypothetically compatible range of nuclear facilities in Europe (i.e., contemporary Pressurised Water Reactor designs or spent nuclear fuel stores), we estimate annual solketal production at approximately (1.0 ± 0.1) × 104 t year−1. Given a forecast increase of 5% to 20% v/v% in the renewable proportion of commercial petroleum blends by 2030, nuclear-driven, biomass-derived solketal could contribute towards net-zero emissions targets, combining low-carbon co-generation and co-production.
Viscoelastic behavior of chemically fueled supramolecular hydrogels under load and influence of reaction side products
Authors: Kretschmer Martin , Winkeljann Benjamin , Kriebisch Brigitte A. K. , Boekhoven Job , Lieleg Oliver 
Published: September 2021

AbstractAbout ten years ago, chemically fueled systems have emerged as a new class of synthetic materials with tunable properties. Yet, applications of these materials are still scarce. In part, this is due to an incomplete characterization of the viscoelastic properties of those materials, which has – so far – mostly been limited to assessing their linear response under shear load. Here, we fill some of these gaps by comparing the viscoelastic behavior of two different, carbodiimide fueled Fmoc-peptide systems. We find that both, the linear and non-linear response of the hydrogels formed by those Fmoc-peptides depends on the amount of fuel driving the self-assembly process – but hardly on the direction of force application. In addition, we identify the concentration of accumulated waste products as a novel, so far neglected parameter that crucially affects the behavior of such chemically fueled hydrogels. With the mechanistic insights gained here, it should be possible to engineer a new generation of dynamic hydrogels with finely tunable material properties that can be tailored precisely for such applications, where they are challenged by mechanical forces.