bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real-time imaging of glutamate transients in the extracellular space of acute human brain slices using a single-wavelength glutamate fluorescence nanosensor
Authors: Brandner Sebastian , Aicher Simon , Schroeter Sarah , Swierzy Izabela , Kinfe Thomas M. , Buchfelder Michael , Maslarova Anna , Stadlbauer Andreas 
Published: March 2022

AbstractGlutamate is the most important excitatory neurotransmitter in the brain. The ability to assess glutamate release and re-uptake with high spatial and temporal resolution is crucial to understand the involvement of this primary excitatory neurotransmitter in both normal brain function and different neurological disorders. Real-time imaging of glutamate transients by fluorescent nanosensors has been accomplished in rat brain slices. We performed for the first time single-wavelength glutamate nanosensor imaging in human cortical brain slices obtained from patients who underwent epilepsy surgery. The glutamate fluorescence nanosensor signals of the electrically stimulated human cortical brain slices showed steep intensity increase followed by an exponential decrease. The spatial distribution and the time course of the signal were in good agreement with the position of the stimulation electrode and the dynamics of the electrical stimulation, respectively. Pharmacological manipulation of glutamate release and reuptake was associated with corresponding changes in the glutamate fluorescence nanosensor signals. We demonstrated that the recently developed fluorescent nanosensors for glutamate allow to detect neuronal activity in acute human cortical brain slices with high spatiotemporal precision. Future application to tissue samples from different pathologies may provide new insights into pathophysiology without the limitations of an animal model.
Characterization of rice farming systems, production constraints and determinants of adoption of improved varieties by smallholder farmers of the Republic of Benin
Authors: Loko Yêyinou Laura Estelle , Gbemavo Charlemagne D. S. J. , Djedatin Gustave , Ewedje Eben-Ezer , Orobiyi Azize , Toffa Joelle , Tchakpa Cyrille , Sedah Paulin , Sabot François 
Published: March 2022

AbstractThe identification of technological and policy interventions allowing to improve the performance of Beninese rice systems is necessary to reduce the heavy dependence on rice imports. This study characterized the Beninese rice farming systems, identified the production constraints, and determinants of the adoption of improved varieties by farmers. Four hundred eighteen rice farm households were surveyed across 39 villages using participatory research tools and methods. Cluster analysis was used to classify the surveyed farm households and revealed four typologies of rice farming systems differentiated by 8 variables. These are, the intensive rice farming system (cluster 4; 33.7%), semi-intensive rice farming system (cluster 1; 31.8%), integrated rice–livestock farming system (cluster 3; 11.8%), and subsistence rice farming (cluster 2; 22.7%). The integrated rice–livestock farming system was the dominant type practiced in the northern Benin, while, it is the intensive rice farming system in the south. Fifteen production constraints across rice-growing areas were recorded. Our results suggest that to increase adoption of improved rice varieties, agricultural extension services should target landowners’ farmers practicing off-season rice production, and having other sources of income. Initiatives to boost rice production in Benin should prioritize the establishment of formal agricultural credit and mechanization option policies.
Monitoring the impact of COVID-19 in France on cancer care: a differentiated impact
Authors: Le Bihan Benjamin Christine , Simonnet Julien-Aymeric , Rocchi Mathieu , Khati Inès , Ménard Estelle , Houas-Bernat Emilie , Méric Jean-Baptiste , Bousquet Philippe-Jean 
Published: March 2022

AbstractThe COVID-19 pandemic has had a substantial and lasting impact on care provision, particularly in the field of cancer care. National steering has helped monitor the health situation and adapt the provision and organisation of care. Based on data from the French administrative healthcare database (SNDS) on the entire French population (67 million people), screening, diagnostic and therapeutic activity was monitored and compared 2019 on a monthly basis. A noteworthy decline in all activities (with the exception of chemotherapy) was observed during the first lockdown in France. Over the months that followed, this activity returned to normal but did not make up for the shortfall from the first lockdown. Finally, during the lockdown in late 2020, cancer care activity was conserved. In brief, in 2020, the number of mammograms decreased by 10% (− 492,500 procedures), digestive endoscopies by 19% (− 648,500), and cancer-related excision by 6% (− 23,000 surgical procedures). Hospital radiotherapy activity was down 3.8% (− 4400 patients) and that in private practice was down 1.4% (− 1600 patients). Chemotherapy activity increased by 2.2% (7200 patients), however. To summarize, COVID-19 had a very substantial impact during the first lockdown. Safeguarding cancer care activity helped limit this impact over the months that followed, but the situation remains uncertain. Further studies on the medium- and long-term impact on individuals (survival, recurrence, after-effects) will be conducted.
Effects of void nodes on epidemic spreads in networks
Authors: Kuga Kazuki , Tanimoto Jun 
Published: March 2022

AbstractWe present the pair approximation models for susceptible–infected–recovered (SIR) epidemic dynamics in a sparse network based on a regular network. Two processes are considered, namely, a Markovian process with a constant recovery rate and a non-Markovian process with a fixed recovery time. We derive the implicit analytical expression for the final epidemic size and explicitly show the epidemic threshold in both Markovian and non-Markovian processes. As the connection rate decreases from the original network connection, the epidemic threshold in which epidemic phase transits from disease-free to endemic increases, and the final epidemic size decreases. Additionally, for comparison with sparse and heterogeneous networks, the pair approximation models were applied to a heterogeneous network with a degree distribution. The obtained phase diagram reveals that, upon increasing the degree of the original random regular networks and decreasing the effective connections by introducing void nodes accordingly, the final epidemic size of the sparse network is close to that of the random network with average degree of 4. Thus, introducing the void nodes in the network leads to more heterogeneous network and reduces the final epidemic size.
Enhancing the decoding accuracy of EEG signals by the introduction of anchored-STFT and adversarial data augmentation method
Authors: Ali Omair , Saif-ur-Rehman Muhammad , Dyck Susanne , Glasmachers Tobias , Iossifidis Ioannis , Klaes Christian 
Published: March 2022

AbstractBrain-computer interfaces (BCIs) enable communication between humans and machines by translating brain activity into control commands. Electroencephalography (EEG) signals are one of the most used brain signals in non-invasive BCI applications but are often contaminated with noise. Therefore, it is possible that meaningful patterns for classifying EEG signals are deeply hidden. State-of-the-art deep-learning algorithms are successful in learning hidden, meaningful patterns. However, the quality and the quantity of the presented inputs are pivotal. Here, we propose a feature extraction method called anchored Short Time Fourier Transform (anchored-STFT), which is an advanced version of STFT, as it minimizes the trade-off between temporal and spectral resolution presented by STFT. In addition, we propose a data augmentation method derived from l2-norm fast gradient sign method (FGSM), called gradient norm adversarial augmentation (GNAA). GNAA is not only an augmentation method but is also used to harness adversarial inputs in EEG data, which not only improves the classification accuracy but also enhances the robustness of the classifier. In addition, we also propose a CNN architecture, namely Skip-Net, for the classification of EEG signals. The proposed pipeline outperforms the current state-of-the-art methods and yields classification accuracies of 90.7% on BCI competition II dataset III and 89.5%, 81.8%, 76.0% and 85.4%, 69.1%, 80.9% on different data distributions of BCI Competition IV dataset 2b and 2a, respectively.
Uncertainty quantification for basin-scale geothermal conduction models
Authors: Degen Denise , Veroy Karen , Wellmann Florian 
Published: March 2022

AbstractGeothermal energy plays an important role in the energy transition by providing a renewable energy source with a low CO2footprint. For this reason, this paper uses state-of-the-art simulations for geothermal applications, enabling predictions for a responsible usage of this earth’s resource. Especially in complex simulations, it is still common practice to provide a single deterministic outcome although it is widely recognized that the characterization of the subsurface is associated with partly high uncertainties. Therefore, often a probabilistic approach would be preferable, as a way to quantify and communicate uncertainties, but is infeasible due to long simulation times. We present here a method to generate full state predictions based on a reduced basis method that significantly reduces simulation time, thus enabling studies that require a large number of simulations, such as probabilistic simulations and inverse approaches. We implemented this approach in an existing simulation framework and showcase the application in a geothermal study, where we generate 2D and 3D predictive uncertainty maps. These maps allow a detailed model insight, identifying regions with both high temperatures and low uncertainties. Due to the flexible implementation, the methods are transferable to other geophysical simulations, where both the state and the uncertainty are important.
Cellobiose phosphorylase from Caldicellulosiruptor bescii catalyzes reversible phosphorolysis via different kinetic mechanisms
Authors: Bai Shaowei , Yang Liangzhen , Wang Honglei , Yang Chao , Hou Xuechen , Gao Jingjie , Zhang Zuoming 
Published: March 2022

AbstractIn the process of yielding biofuels from cellulose degradation, traditional enzymatic hydrolysis, such as β-glucosidase catalyzing cellobiose, can barely resolve the contradiction between cellulose degradation and bioenergy conservation. However, it has been shown that cellobiose phosphorylase provides energetic advantages for cellobiose degradation through a phosphorolytic pathway, which has attracted wide attention. Here, the cellobiose phosphorylase gene from Caldicellulosiruptor bescii (CbCBP) was cloned, expressed, and purified. Analysis of the enzymatic properties and kinetic mechanisms indicated that CbCBP catalyzed reversible phosphorolysis and had good thermal stability and broad substrate selectivity. In addition, the phosphorolytic reaction of cellobiose by CbCBP proceeded via an ordered Bi Bi mechanism, while the synthetic reaction proceeded via a ping pong Bi Bi mechanism. The present study lays the foundation for optimizing the degradation of cellulose and the synthesis of functional oligosaccharides.
Multi-dimensional-double-spiral (MDDS) inertial microfluidic platform for sperm isolation directly from the raw semen sample
Authors: Jeon Hyungkook , Cremers Claudia , Le Doris , Abell Justin , Han Jongyoon 
Published: March 2022

AbstractHere, we propose a fully-automated platform using a spiral inertial microfluidic device for standardized semen preparation that can process patient-derived semen samples with diverse fluidic conditions without any pre-washing steps. We utilized the multi-dimensional double spiral (MDDS) device to effectively isolate sperm cells from other non-sperm seminal cells (e.g., leukocytes) in the semen sample. The recirculation platform was employed to minimize sample dependency and achieve highly purified and concentrated (up to tenfold) sperm cells in a rapid and fully-automated manner (~ 10 min processing time for 50 mL of diluted semen sample). The clinical (raw) semen samples obtained from healthy donors were directly used without any pre-washing step to evaluate the developed separation platform, which showed excellent performance with ~ 80% of sperm cell recovery, and > 99.95% and > 98% removal of 10-μm beads (a surrogate for leukocytes) from low-viscosity and high-viscosity semen samples, respectively. We expect that the novel platform will be an efficient and automated tool to achieve purified sperm cells directly from raw semen samples for assisted reproductive technologies (ARTs) as an alternative to density centrifugation or swim-up methods, which often suffer from the low recovery of sperm cells and labor-intensive steps.
Selenium supplementation influences mice testicular selenoproteins driven by gut microbiota
Authors: Ramírez-Acosta Sara , Selma-Royo Marta , Collado María Carmen , Navarro-Roldán Francisco , Abril Nieves , García-Barrera Tamara 
Published: March 2022

AbstractSelenium is a well-known essential element with important roles in human reproductive health mainly due to its antioxidant character. This study aimed to investigate the potential role of selenoproteins on gut microbiota and male reproductive health. A new assay for the absolute quantification of selenoproteins in testicular tissue based on two dimensional chromatography with inductively coupled plasma mass spectrometry was performed for the first time. The gut microbiota profile was obtained by 16S rRNA gene sequencing. Numerous associations were found between testicular selenoproteins and gut microbiota (e.g.Mucispirillum, related with sperm activity and testosterone, was associated with glutathione peroxidase (GPx) and selenoalbumin (SeAlb), whileEscherichia/Shigella, related to sex hormones, correlated with GPx, selenoprotein P (SelP) and SeAlb). The effects of Se-supplementation on testicular selenoproteins only occur in conventional mice, suggesting a potential selenoproteins-microbiota interplay that underlies testicular function. The selenoproteins GPx and SelP have been quantified for the first time in the testicles, and the novel identification of SeAlb, a protein with nonspecifically incorporated Se, is also reported. These findings demonstrate the significant impact of Se-supplementation on gut microbiota and male reproductive health. In addition, the analytical methodology applied here in selenoprotein quantification in testicular tissue opens new possibilities to evaluate their role in gut microbiota and reproductive health axis.
Inter-strides variability affects internal foot tissue loadings during running
Authors: Van Waerbeke Coline , Jacques André , Berton Eric , Rao Guillaume 
Published: March 2022

AbstractRunning overuse injuries result from an imbalance between repetitive loadings on the anatomical structures and their ability to adapt to these loadings. Unfortunately, the measure of these in-vivo loadings is not easily accessible. An optimal amount of movement variability is thought to decrease the running overuse injury risk, but the influence of movement variability on local tissue loading is still not known. A 3D dynamic finite element foot model driven by extrinsic muscle forces was developed to estimate the stress undergone by the different internal foot structures during the stance phase. The boundary conditions of different trials with similar running speed were used as input. Variability in bone stress (10%) and cartilage pressure (16%) can be expected while keeping the overall running speed constant. Bone and cartilage stress were mainly influenced by the muscle force profiles rather than by ground reaction force. These findings suggest, first, that the analysis of a single trial only is not representative of the internal tissue loadings distribution in the foot and second, that muscle forces must be considered when estimating bone and cartilage loadings at the foot level. This model could be applied to an optimal clinical management of the overuse injury.
Inverting angiogenesis with interstitial flow and chemokine matrix-binding affinity
Authors: Moure Adrian , Vilanova Guillermo , Gomez Hector 
Published: March 2022

AbstractThe molecular signaling pathways that orchestrate angiogenesis have been widely studied, but the role of biophysical cues has received less attention. Interstitial flow is unavoidable in vivo, and has been shown to dramatically change the neovascular patterns, but the mechanisms by which flow regulates angiogenesis remain poorly understood. Here, we study the complex interactions between interstitial flow and the affinity for matrix binding of different chemokine isoforms. Using a computational model, we find that changing the matrix affinity of the chemokine isoform can invert the effect of interstitial flow on angiogenesis—from preferential growth in the direction of the flow when the chemokine is initially matrix-bound to preferential flow against the flow when it is unbound. Although fluid forces signal endothelial cells directly, our data suggests a mechanism for the inversion based on biotransport arguments only, and offers a potential explanation for experimental results in which interstitial flow produced preferential vessel growth with and against the flow. Our results point to a particularly intricate effect of interstitial flow on angiogenesis in the tumor microenvironment, where the vessel network geometry and the interstitial flow patterns are complex.
Design of robust cubature fission particle filter algorithm in multi-source cooperative navigation
Authors: Sun Wei , Liu Jingzhou 
Published: March 2022

AbstractAs a part of the multi-source cooperative navigation scheme, data fusion has a significant impact on the quality of state estimation. Particle filtering has gradually become the focus of many fusion methods due to its unique theoretical advantages in nonlinear non-Gaussian systems. However, the particle degradation and the resulting sample impoverishment restrict its application in complex engineering scenarios. In this paper, a robust cubature fission particle filter (RCFPF) is proposed to deal with these problems. First, in the framework of cubature rule, Huber function is used to combine the L2 norm and L1 norm to improve the importance density function(IDF), suppress the observation noise. Meanwhile, the proposed distribution(PD) is further optimized by combining the Gaussian distribution with Laplace distribution to alleviate particle degradation. Second, the particle swarm is fissioned before resampling, and the particle weight is reconstructed by fission of high weight particles and covering low weight particles to inhibit sample impoverishment. The vehicle experiments of multi-source cooperative navigation show that the proposed algorithm achieves better test results in accuracy and robustness than extended Kalman filter (EKF), strong tracking particle filter (STPF), and cubature particle filter (CPF).
Salmonella Salamae and S. Waycross isolated from Nile perch in Lake Victoria show limited human pathogenic potential
Authors: Hounmanou Yaovi Mahuton Gildas , Baniga Zebedayo , García Vanesa , Dalsgaard Anders 
Published: March 2022

AbstractNon-enterica subspecies of Salmonella enterica are rarely associated with human infections. Paradoxically, food safety legislations consider the entire genus Salmonella as pathogenic to humans. Globally, large amounts of seafoods are rejected and wasted due to findings of Salmonella. To inform better food safety decisions, we investigated the pathogenicity of Salmonella Salamae 42:r- and Salmonella Waycross isolated from Nile perch from Lake Victoria. Genome-wide analysis revealed absence of significant virulence determinants including on key Salmonella pathogenicity islands in both serovars. In epithelial cells, S. Salamae showed a weak invasion ability that was lower than the invH mutant of S. Typhimiurium used as negative control. Similarly, S. Salamae could not replicate inside macrophages. Moreover, intracellular replication in S. Waycross strains was significantly lower compared to the wild type S. Typhimurium. Our findings suggest a low pathogenicity of S. Salamae reinforcing the existing literature that non-enterica subspecies are avirulent. We propose that food legislations and actions taken on findings of Salmonella are revisited to avoid wasting valuable sea- and other foods.
The relevance of migraine in the clinical spectrum of mitochondrial disorders
Authors: Terrin Alberto , Bello Luca , Valentino Maria Lucia , Caporali Leonardo , Sorarù Gianni , Carelli Valerio , Maggioni Ferdinando , Zeviani Massimo , Pegoraro Elena 
Published: March 2022

AbstractRecent scientific evidence suggests a link between migraine and brain energy metabolism. In fact, migraine is frequently observed in mitochondrial disorders. We studied 46 patients affected by mitochondrial disorders, through a headache-focused semi-structured interview, to evaluate the prevalence of migraine among patients affected by mitochondrial disorders, the possible correlations between migraine and neuromuscular genotype or phenotype, comorbidities, lactate acid levels and brain magnetic resonance spectroscopy. We explored migraine-related disability, analgesic and prophylactic treatments. Diagnoses were achieved according to International Classification of Headache Disorders, 3rd edition. Lifetime prevalence of migraine was 61% (28/46), with high values in both sexes (68% in females, 52% in males) and higher than the values found in both the general population and previous literature. A maternal inheritance pattern was reported in 57% of cases. MIDAS and HIT6 scores revealed a mild migraine-related disability. The high prevalence of migraine across different neuromuscular phenotypes and genotypes suggests that migraine itself may be a common clinical manifestation of brain energy dysfunction. Our results provide new relevant indications in favour of migraine as the result of brain energy unbalance.
Sarcopenia increases the risk of major organ or vessel invasion in patients with papillary thyroid cancer
Authors: Yoon Ja Kyung , Yoon Jung Hyun , Park Vivian Youngjean , Lee Minah , Kwak Jin Young 
Published: March 2022

AbstractWhile sarcopenia is associated with poor overall survival and cancer-specific survival in solid cancer patients, the impact of sarcopenia on clinicopathologic features that can influence conventional papillary thyroid cancer (PTC) prognosis remains unclear. To investigate the impact of sarcopenia on aggressive clinicopathologic features in PTC patients, prospectively collected data on 305 patients who underwent surgery for PTC with preoperative staging ultrasonography and bioelectrical impedance analysis were retrospectively analyzed. Nine sarcopenia patients with preoperative sarcopenia showed more patients aged 55 or older (p = 0.022), higher male proportion (p < 0.001), lower body-mass index (p = 0.015), higher incidence of major organ or vessel invasion (p = 0.001), higher T stage (p = 0.002), higher TNM stage (p = 0.007), and more tumor recurrence (p = 0.023) compared to the non-sarcopenia patients. Unadjusted and adjusted logistic regression analyses showed that sarcopenia (odds ratio (OR) 9.936, 95% confidence interval (CI) 2.052–48.111, p = 0.004), tumor size (OR 1.048, 95% CI 1.005–1.093, p = 0.027), and tumor multiplicity (OR 3.323, 95% CI 1.048–10.534, p = 0.041) significantly increased the risk of T4 cancer. Sarcopenia patients showed significantly lower disease-free survival probability compared to non-sarcopenia patients. Therefore, preoperative sarcopenia in PTC patients should raise clinical suspicion for a more locally advanced disease and direct appropriate management and careful follow-up.