bluuebunny/crossref_metadata_2025_split huggingface dataset:
RSV pre-fusion F protein enhances the G protein antibody and anti-infectious responses
Authors: Su Caixia , Zhong Yiwei , Zhao Gan , Hou Jiawang , Zhang Shuren , Wang Bin 
Published: December 2022

AbstractRespiratory syncytial virus (RSV) infection in children is the most common viral respiratory infection and can cause severe lung damage or death. There is no licensed vaccine for preventing RSV infection. Previously we demonstrated that an RSV vaccine, BARS13, consisting of recombinant G protein from E. coli plus cyclosporine A (CsA) as an immune-modulator, can protect animals from RSV challenge without inducing vaccine-enhanced disease (VED). To maximize the efficacy of such a vaccine, we introduced RSV pre-fusion F protein (pre-F) to form a new vaccine comprised of the pre-F and G proteins with the CsA. Two intramuscular immunizations with the vaccine induced a higher level of neutralizing antibodies against RSV and protected mice from RSV challenge without incurring VED. Interestingly, the addition of the pre-F to the vaccine facilitated anti-G antibody production and protection from RSV infection mainly via induction of antibodies against the central conserved domain (CCD) of the G protein which correlated with blocking the CX3C-CX3CR1 interaction. A 15 amino acid sequence (FP4) within the F2 region of pre-F served as a CD4+ Th epitope to facilitate the anti-G antibody response. Collectively, such a combination of the FP4 peptide with the G protein and CsA provides a novel strategy for developing a safe and maximally effective recombinant G protein-containing RSV vaccine.
Multimodal chromatin profiling using nanobody-based single-cell CUT&Tag
Authors: Bartosovic Marek , Castelo-Branco Gonçalo 
Published: December 2022

AbstractProbing histone modifications at a single-cell level in thousands of cells has been enabled by technologies such as single-cell CUT&Tag. Here we describe nano-CUT&Tag (nano-CT), which allows simultaneous mapping of up to three epigenomic modalities at single-cell resolution using nanobody-Tn5 fusion proteins. Multimodal nano-CT is compatible with starting materials as low as 25,000–200,000 cells and has significantly higher sensitivity and number of fragments per cell than single-cell CUT&Tag. We use nano-CT to simultaneously profile chromatin accessibility, H3K27ac, and H3K27me3 in juvenile mouse brain, allowing for discrimination of more cell types and states than unimodal single-cell CUT&Tag. We also infer chromatin velocity between assay for transposase-accessible chromatin (ATAC) and H3K27ac in the oligodendrocyte lineage and deconvolute H3K27me3 repressive states, finding two sequential waves of H3K27me3 repression at distinct gene modules during oligodendrocyte lineage progression. Given its high resolution, versatility, and multimodal features, nano-CT allows unique insights in epigenetic landscapes in complex biological systems at the single-cell level.
A study of the influence of current ramp rate on the performance of polymer electrolyte membrane fuel cell
Authors: Chandran Mathan , Palaniswamy Karthikeyan , Karthik Babu N. B. , Das Oisik 
Published: December 2022

AbstractDurability and reliability are the key factors that prevent fuel cells from successful implementation in automotive sector. Dynamic load change is a common and frequent condition that the fuel cell has to undergo in automotive applications. Fuel cells are more sensitive to changes in load conditions and degrade based on load variation representing idling, rated power, and high power operating conditions. To examine the influence of dynamic load step on the fuel cell performance, two similar cells of active 25 cm2 was tested under two different load step for the same dynamic load cycle. The main difference in dynamic load cycle 2 was the ramp rate which was fixed as 0.1, 0.3, and 0.25 A/cm2/s for 0.2, 0.6, and 1.0 A/cm2 respectively. To investigate the degradative effects, polarization curves, electrochemical impedance spectroscopy, and field emission scanning electron microscopy were used. The results indicated that the degradation rate increased in both dynamic load cycles but however the impact of load change was comparatively minimal in dynamic load cycle 2. The total degradation in performance was 20.67% and 10.72% in dynamic load cycles 1 and 2 respectively. Fuel cell performance degraded in a manner that was consistent with the electrochemical impedance spectroscopy and cross-sectional analysis of field emission scanning electron microscopy. The results prove that the degradation rate is dependent on the load step and the number of load cycles. Severe catalyst degradation and delamination were observed in fuel cells operated under dynamic load cycle 1.
Dynamic changes in peripheral lymphocytes and antibody response following a third dose of SARS-CoV-2 mRNA-BNT162b2 vaccine in cancer patients
Authors: Ruggeri Enzo Maria , Nelli Fabrizio , Giannarelli Diana , Fabbri Agnese , Giron Berrios Julio Rodrigo , Virtuoso Antonella , Marrucci Eleonora , Mazzotta Marco , Schirripa Marta , Signorelli Carlo , Chilelli Mario Giovanni , Primi Francesca , Fiore Cristina , Panichi Valentina , Topini Giuseppe , Silvestri Maria Assunta 
Published: December 2022

AbstractThe aim of this study was to evaluate the association of circulating lymphocytes profiling with antibody response in cancer patients receiving the third dose of COVID-19 mRNA-BNT162b2 vaccine. Immunophenotyping of peripheral blood was used to determine absolute counts of lymphocyte subsets, alongside detection of IgG antibodies against receptor-binding-domain (RBD) of the SARS-CoV-2 Spike protein (S1) before booster dosing (timepoint-1) and four weeks afterward (timepoint-2). An IgG titer ≥ 50 AU/mL defined a positive seroconversion response. An IgG titer ≥ 4446 AU/mL was assumed as a correlate of 50% vaccine efficacy against symptomatic infections. A total of 258 patients on active treatment within the previous six months were enrolled between September 23 and October 7, 2021. The third dose resulted in an exponential increase in median anti-RBD-S1 IgG titer (P < 0.001), seroconversion rates (P < 0.001), and 50% vaccine efficacy rates (P < 0.001). According to ROC curve analysis, T helper and B cells were significantly associated with seroconversion responses at timepoint-1, whereas only B cells were relevant to 50% vaccine efficacy rates at timepoint-2. A positive linear correlation was shown between anti-RBD-S1 IgG titers and these lymphocyte subset counts. Multivariate analysis ruled out a potential role of T helper cells but confirmed a significant interaction between higher B cell levels and improved antibody response. These findings suggest that peripheral counts of B cells correlate with humoral response to the third dose of mRNA-BNT162b2 vaccine in actively treated cancer patients and could provide insights into a more comprehensive assessment of vaccination efficacy.
The behaviour of metals in deep fluids of NE Iceland
Authors: Saby Marion , van Hinsberg Vincent , Pinti Daniele L. , Berlo Kim , Gautason Bjarni , Sigurðardóttir Ásgerður , Brown Kevin , Rocher Océane 
Published: December 2022

AbstractIn this contribution, we present some of the first data on the elemental signature of deep crustal fluids in a basalt-hosted, low-chloride magmatic-hydrothermal system. Down-hole fluid samples (850–1600 m) from wells in the Theistareykir and Krafla geothermal fields in the Northern Volcanic Zone of Iceland were combined with well-head samples of condensed vapor, cuttings of altered rock, and fresh basalt (being some of the first concentration data for volatile and semi-volatile elements (Sb, Tl, Bi, Cd and As) for this area of Iceland). Results show that the deep fluids are relatively enriched in base metals and (semi)-volatile metals (in particular Te, Hg, Re and Tl) compared to local basalt. We interpret this enrichment in volatile metals to reflect a significant element input from magma degassing. Boiling of this deep fluid results in a well-head fluid composition that is significantly depleted in most elements. This well-head fluid has a distinct elemental signature, including a depletion in Sb that is mirrored in the altered rocks, and a depletion in the base metals that shows their selective sequestration in scale minerals, likely sulphides. As expected, the element content and patterns in surface fluids can thus not be interpreted to directly reflect that of the deep reservoir fluid. The behaviour of elements in Theistareykir and Krafla fluids is consistent, and largely agrees with similar data obtained for the Reykjanes geothermal system in SW Iceland. We therefore posit that our results are representative for this geological setting and indicate a significant magmatic degassing cation input to deep fluids, variably modified by water–rock interaction.
Massive production of fibroin nano-fibrous biomaterial by turbulent co-flow
Authors: Gañán-Calvo Alfonso M. , Blanco-Trejo Sergio , Ruiz-López Miguel , Guinea Gustavo V. , Modesto-López Luis B. , Pérez-Rigueiro José 
Published: December 2022

AbstractAmong the different polymers (proteins, polysaccharides, etc.) that make up natural fibers, fibroin is a protein produced by silk spinning animals, which have developed an optimized system for the conversion of a highly concentrated solution of this protein into high-performance solid fibers. This protein undergoes a self-assembly process in the silk glands that result from chemical gradients and by the application of mechanical stresses during the last step of the process. In the quest for a process that could mimic natural spinning at massive scales, we have discovered that turbulence offers a novel and promising solution: a turbulent liquid jet can be formed by a chemically green and simple coagulating liquid (a diluted solution of acetic acid in etanol) co-flowing with a concentrated solution of fibroin in water by the use of a Flow Blurring nebulizer. In this system, (a) the co-flowing coagulant liquid extracts water from the original protein solution and, simultaneously, (b) the self-assembled proteins are subjected to mechanical actions, including splitting and stretching. Given the non-negligible produced content with the size and appearance of natural silk, the stochastic distribution of those effects in our process should contain the range of natural ones found in animals. The resulting easily functionalizable and tunable one-step material is 100% biocompatible, and our method a perfect candidate to large-scale, low-cost, green and sustainable processing of fibroin for fibres and textiles.
Comparability of automated drusen volume measurements in age-related macular degeneration: a MACUSTAR study report
Authors: Garzone Davide , Terheyden Jan Henrik , Morelle Olivier , Wintergerst Maximilian W. M. , Saßmannshausen Marlene , Schmitz-Valckenberg Steffen , Pfau Maximilian , Thiele Sarah , Poor Stephen , Leal Sergio , Holz Frank G. , Finger Robert P. ,   MACUSTAR Consortium, Agostini H. , Altay L. , Atia R. , Bandello F. , Basile P. G. , Behning C. , Belmouhand M. , Berger M. , Binns A. , Boon C. J. F. , Böttger M. , Bouchet C. , Brazier J. E. , Butt T. , Carapezzi C. , Carlton J. , Carneiro A. , Charil A. , Coimbra R. , Cozzi M. , Crabb D. P. , Cunha-Vaz J. , Dahlke C. , de Sisternes L. , Dunbar H. , Fletcher E. , Francisco C. , Gutfleisch M. , Hogg R. , Hoyng C. B. , Kilani A. , Krätzschmar J. , Kühlewein L. , Larsen M. , Lechanteur Y. T. E. , Luhmann U. F. O. , Lüning A. , Marques I. , Martinho C. , Montesano G. , Mulyukov Z. , Paques M. , Parodi B. , Parravano M. , Penas S. , Peters T. , Peto T. , Priglinger S. , Rowen D. , Rubin G. S. , Sahel J. , Sánchez C. , Sander O. , Schmid M. , Schrinner-Fenske H. , Siedlecki J. , Silva R. , Skelly A. , Souied E. , Staurenghi G. , Stöhr L. , Taylor D. J. , Tufail A. , Varano M. , Vieweg L. , Wintergerst L. , Wolf A. , Zakaria N. 
Published: December 2022

AbstractDrusen are hallmarks of early and intermediate age-related macular degeneration (AMD) but their quantification remains a challenge. We compared automated drusen volume measurements between different OCT devices. We included 380 eyes from 200 individuals with bilateral intermediate (iAMD, n = 126), early (eAMD, n = 25) or no AMD (n = 49) from the MACUSTAR study. We assessed OCT scans from Cirrus (200 × 200 macular cube, 6 × 6 mm; Zeiss Meditec, CA) and Spectralis (20° × 20°, 25 B-scans; 30° × 25°, 241 B-scans; Heidelberg Engineering, Germany) devices. Sensitivity and specificity for drusen detection and differences between modalities were assessed with intra-class correlation coefficients (ICCs) and mean difference in a 5 mm diameter fovea-centered circle. Specificity was > 90% in the three modalities. In eAMD, we observed highest sensitivity in the denser Spectralis scan (68.1). The two different Spectralis modalities showed a significantly higher agreement in quantifying drusen volume in iAMD (ICC 0.993 [0.991–0.994]) than the dense Spectralis with Cirrus scan (ICC 0.807 [0.757–0.847]). Formulae for drusen volume conversion in iAMD between the two devices are provided. Automated drusen volume measures are not interchangeable between devices and softwares and need to be interpreted with the used imaging devices and software in mind. Accounting for systematic difference between methods increases comparability and conversion formulae are provided. Less dense scans did not affect drusen volume measurements in iAMD but decreased sensitivity for medium drusen in eAMD.Trial registration: ClinicalTrials.gov NCT03349801. Registered on 22 November 2017.
Prebiopsy bpMRI and hematological parameter-based risk scoring model for predicting outcomes in biopsy-naive men with PSA 4–20 ng/mL
Authors: Zheng Yuxin , Li Wang , Zhang Yang , Zhang Chi , Wang Junqi , Ge Peng 
Published: December 2022

AbstractExcessive prostate biopsy is a common problem for clinicians. Although some hematological and bi-parametric magnetic resonance imaging (bpMRI) parameters might help increase the rate of positive prostate biopsies, there is a lack of studies on whether their combination can further improve clinical detection efficiency. We retrospectively enrolled 394 patients with PSA levels of 4–20 ng/mL who underwent prebiopsy bpMRI during 2010–2021. Based on bpMRI and hematological indicators, six models and a nomogram were constructed to predict the outcomes of biopsy. Furthermore, we constructed and evaluated a risk scoring model based on the nomogram. Age, prostate-specific antigen (PSA) density (PSAD), systemic immune-inflammation index, cystatin C level, and the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 score were significant predictors of prostate cancer (PCa) on multivariable logistic regression analyses (P < 0.05) and the five parameters were used to construct the XYFY nomogram. The area under the receiver operating characteristic (ROC) curve (AUC) of the nomogram was 0.916. Based on the nomogram, a risk scoring model (XYFY risk model) was constructed and then we divided the patients into low-(XYFY score: < 95), medium-(XYFY score: 95–150), and, high-risk (XYFY score: > 150) groups. The predictive values for diagnosis of PCa and clinically-significant PCa among the three risk groups were 3.0%(6/201), 41.8%(51/122), 91.5%(65/71); 0.5%(1/201), 19.7%(24/122), 60.6%(43/71), respectively. In conclusion, in this study, we used hematological and bpMRI parameters to establish and internally validate a XYFY risk scoring model for predicting the biopsy outcomes for patients with PSA levels of 4–20 ng/mL and this risk model would support clinical decision-making and reduce excessive biopsies.
ANIMAL-SPOT enables animal-independent signal detection and classification using deep learning
Authors: Bergler Christian , Smeele Simeon Q. , Tyndel Stephen A. , Barnhill Alexander , Ortiz Sara T. , Kalan Ammie K. , Cheng Rachael Xi , Brinkløv Signe , Osiecka Anna N. , Tougaard Jakob , Jakobsen Freja , Wahlberg Magnus , Nöth Elmar , Maier Andreas , Klump Barbara C. 
Published: December 2022

AbstractBioacoustic research spans a wide range of biological questions and applications, relying on identification of target species or smaller acoustic units, such as distinct call types. However, manually identifying the signal of interest is time-intensive, error-prone, and becomes unfeasible with large data volumes. Therefore, machine-driven algorithms are increasingly applied to various bioacoustic signal identification challenges. Nevertheless, biologists still have major difficulties trying to transfer existing animal- and/or scenario-related machine learning approaches to their specific animal datasets and scientific questions. This study presents an animal-independent, open-source deep learning framework, along with a detailed user guide. Three signal identification tasks, commonly encountered in bioacoustics research, were investigated: (1) target signal vs. background noise detection, (2) species classification, and (3) call type categorization. ANIMAL-SPOT successfully segmented human-annotated target signals in data volumes representing 10 distinct animal species and 1 additional genus, resulting in a mean test accuracy of 97.9%, together with an average area under the ROC curve (AUC) of 95.9%, when predicting on unseen recordings. Moreover, an average segmentation accuracy and F1-score of 95.4% was achieved on the publicly available BirdVox-Full-Night data corpus. In addition, multi-class species and call type classification resulted in 96.6% and 92.7% accuracy on unseen test data, as well as 95.2% and 88.4% regarding previous animal-specific machine-based detection excerpts. Furthermore, an Unweighted Average Recall (UAR) of 89.3% outperformed the multi-species classification baseline system of the ComParE 2021 Primate Sub-Challenge. Besides animal independence, ANIMAL-SPOT does not rely on expert knowledge or special computing resources, thereby making deep-learning-based bioacoustic signal identification accessible to a broad audience.
Environmentally driven phenotypic convergence and niche conservatism accompany speciation in hoary bats
Authors: Soto-Centeno J. Angel , Simmons Nancy B. 
Published: December 2022

AbstractSpecies that are geographically widespread may exist across environmentally heterogeneous landscapes that could influence patterns of occupation and phylogeographic structure. Previous studies have suggested that geographic range size should be positively correlated with niche breadth, allowing widespread species to sustain viable populations over diverse environmental gradients. We examined the congruence of phenotypic and phylogenetic divergence with the environmental factors that help maintain species level diversity in the geographically widespread hoary bats (Lasiurus cinereussensu lato) across their distribution. Genetic sequences were analyzed using multiple phylogenetic and species delimitation methods, and phenotypic data were analyzed using supervised and unsupervised machine learning approaches. Spatial data from environmental, geographic, and topographic features were analyzed in a multiple regression analysis to determine their relative effect on phenotypic diversity. Ecological niches of each hoary bat species were examined in environmental space to quantify niche overlap, equivalency, and the magnitude of niche differentiation. Phylogenetic and species delimitation analyses support existence of three geographically structured species of hoary bat, each of which is phenotypically distinct. However, the Hawaiian hoary bat is morphologically more similar to the South American species than to the North American species despite a closer phylogenetic relationship to the latter. Multiple regression and niche analyses revealed higher environmental similarities between the South American and Hawaiian species. Hoary bats thus exhibit a pattern of phenotypic variation that disagrees with well-supported genetic divergences, instead indicating phenotypic convergence driven by similar environmental features and relatively conserved niches occupied in tropical latitudes.
Human reliability assessment of intelligent coal mine hoist system based on Bayesian network
Authors: Sun Linhui , Wang Liao , Su Chang , Cheng Fangming , Wang Xinping , Jia Yuanrui , Zhang Ziming 
Published: December 2022

AbstractThe human reliability of intelligent coal mine hoist operation system is affected by many factors, in order to reduce the occurrence of human error in the hoist system and improve the reliability of the system. The characteristics of phased-mission task operation of hoists is combined, the phase dependence of human cognitive errors is considered and, a new human reliability evaluation method is proposed with the help of Bayesian network (BN) model in this paper. Firstly, the phase dependence of human cognitive errors was analyzed based on the cognitive behavior model. Then the human error analysis in the hoist system was carried out, and several main performance shaping factors are selected. Secondly, BN was used to build the human reliability model of the hoist system at each stage. Finally, it is found that the phase dependence of cognitive errors has a negative impact on the human reliability of the hoist system through the case analysis. At the same time, several main performance shaping factors (PSFs)were quantitatively analyzed by using the reverse reasoning ability of BN, which proves the effectiveness of the proposed method, and provides a scientific and reasonable theoretical basis for the development of effective human error prevention measures for the operation of intelligent coal mine hoists.
Estimate earth fissure hazard based on machine learning in the Qa’ Jahran Basin, Yemen
Authors: Al-Masnay Yousef A. , Al-Areeq Nabil M. , Ullah Kashif , Al-Aizari Ali R. , Rahman Mahfuzur , Wang Changcheng , Zhang Jiquan , Liu Xingpeng 
Published: December 2022

AbstractEarth fissures are potential hazards that often cause severe damage and affect infrastructure, the environment, and socio-economic development. Owing to the complexity of the causes of earth fissures, the prediction of earth fissures remains a challenging task. In this study, we assess earth fissure hazard susceptibility mapping through four advanced machine learning algorithms, namely random forest (RF), extreme gradient boosting (XGBoost), Naïve Bayes (NB), and K-nearest neighbor (KNN). Using Qa’ Jahran Basin in Yemen as a case study area, 152 fissure locations were recorded via a field survey for the creation of an earth fissure inventory and 11 earth fissure conditioning factors, comprising of topographical, hydrological, geological, and environmental factors, were obtained from various data sources. The outputs of the models were compared and analyzed using statistical indices such as the confusion matrix, overall accuracy, and area under the receiver operating characteristics (AUROC) curve. The obtained results revealed that the RF algorithm, with an overall accuracy of 95.65% and AUROC, 0.99 showed excellent performance for generating hazard maps, followed by XGBoost, with an overall accuracy of 92.39% and AUROC of 0.98, the NB model, with overall accuracy, 88.43% and AUROC, 0.96, and KNN model with general accuracy, 80.43% and AUROC, 0.88), respectively. Such findings can assist land management planners, local authorities, and decision-makers in managing the present and future earth fissures to protect society and the ecosystem and implement suitable protection measures.