bluuebunny/crossref_metadata_2025_split huggingface dataset:
Constraints on Lanthanide Separation by Selective Biosorption
Authors: Anderson Carter , Medin Sean , Adair James , Demopoulos Bryce , Eneli Emeka , Kuelbs Chloe , Lee Joseph , Sheppard Timothy J. , Şinar Deniz , Thurston Zacharia , Xu Mingyang , Zhang Kang , Barstow Buz 
Published: October 2023

AbstractRare Earth Elements (REE) are essential ingredients of sustainable energy technologies1-5, but separation of lanthanides is considered one of the hardest problems in chemistry today6. Biosorption, where molecules adsorb to the surface of biological materials, offers a sustainable alternative to environmentally harmful solvent extractions currently used for REE separations. The REE-biosorption capabilities of some microorganisms already allow for REE separations that under specialized conditions are competitive with solvent extractions7. Our recent work has discovered the genetic basis for REE biosorption selectivity8. However, it is unclear if the small changes to selectivity produced by changes to single genetic loci could allow biosorption to leapfrog existing REE separation technologies. In this article we present three models of lanthanide separation by biosorption and desorption. The first model shows that if a biosorbing microbe behaves as it if has a single type of binding site with small preference for one lanthanide, then the small changes in selectivity produced by changes to a single genetic locus could reduce the length of a separation process by ≈ 25%. Large multi-locus gene edits could reduce a separation process length by almost 90%. On the other hand, if the microbe contains multiple sites each with a distinct preference for an individual lanthanide, then separations become challenging and larger genetic edits would be needed to enable high purity. However, even if these large genetic edits are not possible, high purity separations could still be possible by combining multiple microbes, each with small increases in selectivity, with the first designed to enrich for the target lanthanide, while subsequent microbes are designed to remove contaminants.
Brain Functional Connectivity Correlates of Anomalous Interaction Between Sensorily Isolated Monozygotic Twins
Authors: Silberstein Richard B. , Bigelow Felicity J. 
Published: October 2023

AbstractThis study examined brain functional connectivity (FC) changes associated with possible anomalous interactions between sensorily isolated monozygotic twins. Brain FC was estimated using the Steady State Visual Evoked Potential-Event Related Partial Coherence (SSVEP-ERPC) methodology. Five twin pairs served twice as participants with an average interval between sessions of 67 days. In each recording session, one twin, the sender, viewed a randomized set of 50 general images and 50 personally relevant images, whilst the other twin, the Receiver, viewed a static personally relevant image for the entire duration of the session. Images appeared on the sender screen for 1.0 sec with the interval between successive images varied randomly between 4.0 and 8.0 sec. Receiver FC changes were calculated from the appearance times of the images as viewed by the Sender. It was hypothesized that anomalous interactions would be indicated by statistically significant Receiver FC changes when those changes are determined using the sender image appearance times. For each twin serving as Receiver, FC components were separately analysed for the 50 general and the 50 personal images, yielding 38 observations (19 twin pairs by 2 conditions). The hypothesis was confirmed in that 12 of the 38 observations, yielded statistically significant receiver FC increases or decreases at the p<0.01 level only when trials were synchronized to the Sender image appearance times. Overall, this effect was significant at the p=4X10-8Df=175. To the best of our knowledge, this is the first study reporting statistically significant FC changes indicative of anomalous interactions between two sensorily isolated individuals.
Bnip3 expression is strongly associated with reelin-positive entorhinal cortex layer II neurons
Authors: Omholt Stig W. , Lejneva Raissa , Lagartos Donate Maria Jose , Fang Evandro Fei , Kobro-Flatmoen Asgeir 
Published: October 2023

AbstractIn layer II of the entorhinal cortex, the principal neurons that project to the dentate gyrus and the CA3/2 hippocampal fields express the large glycoprotein reelin (Re+ ECLII-neurons). In rodents, neurons located at the dorsal extreme of the entorhinal cortex that thus border the rhinal fissure, express the highest levels, and the expression gradually decreases at levels successively further away from the rhinal fissure. Here we test two predictions following from the hypothesis that reelin expression is strongly correlated with neuronal metabolic rate. Since mitochondrial turnover rate serves as a proxy for energy expenditure, we predicted that the expression of the canonical promitophagic BCL2 and adenovirus E1B 19-kDa-interacting protein 3 (Bnip3) would be upregulated in Re+ ECLII-neurons, and that the degree of upregulation would strongly correlate with the expression level of reelin in these neurons. We confirm both predictions, which implies that the energy requirement of Re+ ECLII-neurons is generally high, and that there is a systematic decrease in metabolic rate in these neurons as one moves successively away from the rhinal fissure. We tentatively suggest that the reasons for the high energy requirement of these neurons are their high rate of synaptic transmission and the high frequency by which they remold their synaptic contacts. This implies that the systematic variation in energy requirement of the neurons manifesting the observed reelin gradient ties in with the level of spatial and temporal detail by which they encode information about the external environment.
Spies of the deep: an animal-borne active sonar and bioluminescence tag to characterise mesopelagic prey size and behaviour in distinct oceanographic domains
Authors: Chevallay Mathilde , Jeanniard du Dot Tiphaine , Goulet Pauline , Fonvieille Nadège , Craig Cassandra , Picard Baptiste , Guinet Christophe 
Published: October 2023

AbstractMesopelagic fish, a central component of marine trophic networks, play a fundamental role in marine ecosystems. However, as they live in highly inaccessible environments, little information is currently available on their ecology, especially on the influence of oceanographic parameters on their distribution. The emergence of biologging technologies has made it possible to use deep-diving predators as bio-samplers of their environment in under-sampled regions. In this work, we deployed an innovati ve miniaturised sonar tag that combines active acoustics with high-resolution GPS, pressure, movement and light sensors on Southern elephant seals, a deep-diving predator feeding on mesopelagic prey. Seals were also equipped with oceanographic tags, allowing us to explore the functional relationships between oceanographic parameters, distribution and ecology of mesopelagic prey targeted by seals and the seals’ foraging behaviour. We highlighted strong vertical differences in prey characteristics and behaviour, with larger, more evasive and less bioluminescent prey in deeper waters. Moreover, prey encountered in warmer waters were found deeper, were more evasive and displayed a more marked diel vertical migration behaviour compared to prey encountered in colder waters, suggesting that prey accessibility and characteristics differ according to oceanographic domains. This study highlights the usefulness of the sonar-bioluminescence tag to infer mesopelagic prey distribution and habitat when deployed on deep-diving predators such as elephant seals.
Enhancing Open-World Bacterial Raman Spectra Identification by Feature Regularization for Improved Resilience against Unknown Classes
Authors: Balytskyi Yaroslav , Kalashnyk Nataliia , Hubenko Inna , Balytska Alina , McNear Kelly 
Published: October 2023

AbstractThe combination of Deep Learning techniques and Raman spectroscopy shows great potential offering precise and prompt identification of pathogenic bacteria in clinical settings. However, the traditional closed-set classification approaches assume that all test samples belong to one of the known pathogens, and their applicability is limited since the clinical environment is inherently unpredictable and dynamic, unknown or emerging pathogens may not be included in the available catalogs. We demonstrate that the current state-of-the-art Neural Networks identifying pathogens through Raman spectra are vulnerable to unknown inputs, resulting in an uncontrollable false positive rate. To address this issue, first, we developed a novel ensemble of ResNet architectures combined with the attention mechanism which outperforms existing closed-world methods, achieving an accuracy of 87.8±0.1% compared to the best available model’s accuracy of 86.7±0.4%. Second, through the integration of feature regularization by the Objectosphere loss function, our model achieves both high accuracy in identifying known pathogens from the catalog and effectively separates unknown samples drastically reducing the false positive rate. Finally, the proposed feature regularization method during training significantly enhances the performance of out-of-distribution detectors during the inference phase improving the reliability of the detection of unknown classes. Our novel algorithm for Raman spectroscopy enables the detection of unknown, uncatalogued, and emerging pathogens providing the flexibility to adapt to future pathogens that may emerge, and has the potential to improve the reliability of Raman-based solutions in dynamic operating environments where accuracy is critical, such as public safety applications.Our model is publicly available:https://github.com/BalytskyiJaroslaw/PathogensRamanOpenSet.git
Detection of Blood Volume Reduction and Vasoconstriction Following Focused Ultrasound Blood-Brain Barrier Opening Using Ultrasound Flow Imaging
Authors: Bae Sua , Lee Stephen A. , Konofagou Elisa E. 
Published: October 2023

AbstractMicrobubble-mediated focused ultrasound (FUS) offers a non-invasive treatment for transient and localized blood-brain barrier (BBB) opening for drug delivery or immunostimulation. It is known that FUS-induced BBB opening is accompanied by blood flow changes, vasoconstriction, and vasodilation, as validated by optical microscopy through a cranial window. In this study, we introduce a novel method for quantifying vascular changes after FUS-induced BBB opening by employing ultrasound flow imaging in mice. We acquired pre-FUS and post-FUS ultrasound flow images with the same microbubble concentration in the brain. Contrast-enhanced power Doppler (CEPD) images and ultrasound localization microscopy images were obtained to evaluate changes in cerebral blood volume and vessel diameter at the sonicated region of the brain. Our findings demonstrate that FUS leads to a reduction in blood volume at the treated region, with vasoconstriction being more dominant than vasodilation. Furthermore, we show that transcranial CEPD can detect local blood reduction following FUS, which spatially coincides with the edema region identified in T2-weighted MRI. Our findings suggest that ultrasound flow imaging has the potential to serve as a cost-effective and immediate monitoring tool for evaluating the safety and efficacy of FUS-induced BBB opening.
Synthesis of pyrazole-based macrocycles leads to a highly selective inhibitor for MST3
Authors: Amrhein Jennifer A. , Berger Lena M. , Balourdas Dimitrios-Ilias , Joerger Andreas C. , Menge Amelie , Krämer Andreas , Frischkorn Julia M. , Berger Benedict-Tilman , Elson Lewis , Kaiser Astrid , Schubert-Zsilavecz Manfred , Müller Susanne , Knapp Stefan , Hanke Thomas 
Published: October 2023

AbstractMST1, MST2, MST3, MST4, and YSK1 are conserved members of the mammalian sterile 20 kinase (MST) family. MSTs regulate key cellular functions such as cell proliferation, cell migration, metabolic regulation, and cell polarity. The MST3 isozyme plays a role in regulation of cell growth, autophagy and apoptosis, and its dysregulation has been linked to the occurrence of high-grade tumors with poor survival prognosis. To date, there are no isoform-selective inhibitors available that could be used for validating the role of MST3 in tumorigenesis and to assess its potential as an anti-cancer target for drug development. To this end, we have designed a new series of 3-aminopyrazole-based macrocycles based on the structure of an acyclic promiscuous kinase inhibitor. By varying moieties targeting the solvent-exposed region and optimizing the linker, macrocycle JA310 (21c) was synthesized. JA310 exhibited high cellular potency for MST3 with an EC50= 106 nM and excellent kinome-wide selectivity with significantly lower cellular activity on the closely related kinase MST4 (EC50= 1.4 µM). The high-resolution crystal structure of the MST3-JA310 complex provided intriguing insights into the distinct binding mode of the macrocycle, which was associated with large-scale structural rearrangements, including concerted induced-fit movements of the glycine-rich loop, the αC helix, and the activation loop. In summary, the developed macrocyclic MST3 inhibitor, JA310, demonstrates the utility of macrocyclization for the design of highly selective inhibitors and presents a first chemical probe for MST3.
Systematic optimization of siRNA productive uptake into resting and activated T cellsex vivo
Authors: Kremer A , Ryaykenen T , Haraszti RA 
Published: October 2023

AbstractRNA-based medicines are ideally suited for precise modulation of T cell phenotypes in anti-cancer immunity, in autoimmune diseases and forex vivomodulation of T-cell-based therapies. Therefore, understanding productive siRNA uptake to T cells is of particular importance.Most studies used unmodified siRNAs or commercially available siRNA with undisclosed chemical modifications patterns to show functionality in T cells. Despite being an active field of research, robust siRNA delivery to T cells still represents a formidable challenge. Therefore, a systematic approach is needed to further optimize and understand productive siRNA uptake pathways to T cells.Here we compared conjugate-mediated and nanoparticle-mediated delivery of siRNAs to T cells in the context of fully chemically modified RNA constructs. We showed that lipid-conjugate-mediated delivery outperforms lipid-nanoparticle-mediated and extracellular-vesicle-mediated delivery in activated T cellsex vivo. Yet, ex vivo manipulation of T cells without the need of activation is of great therapeutic interest for CAR-T, engineered TCR-T and allogeneic donor lymphocyte applications. We are first to report productive siRNA uptake into resting T cells using lipid-conjugate mediated delivery. Interestingly, we observed strong dependence of silencing activity on lipid-conjugate-identity in resting T cells but not in activated T cells. This phenomenon is consistent with our early uptake kinetics data. Lipid-conjugates also enabled delivery of siRNA to all mononuclear immune cell types, including both lymphoid and myeloid lineages. These findings are expected to be broadly applicable forex vivomodulation of immune cell therapies.
Out of Place: Three Eurasian Taxa Shed Light on Origin of Thermopsideae in North America
Authors: Farmer Todd A. , Jansen Robert K. 
Published: October 2023

AbstractThe North American Thermopsideae, a monophyletic group comprising the North American endemicBaptisia, and the paraphyletic Eurasian–North American disjunctThermopsis, is nested within the Sophoreae (Fabaceae: Papilionoideae). Previous phylogenetic studies have identified two East Asian taxa within the North American Thermopsideae, suggesting two independent dispersal events between North America–East Asia. More recent studies have also placed a third taxon,Vuralia turcica, an endemic species from Turkey, among the North American Thermopsideae. The presence of three geographically distant Eurasian taxa within a relatively young clade of North American origin is perplexing, and the biogeographic implications of this observation are not clear. To investigate this matter, 1540 low-copy nuclear genes and complete plastomes were obtained from 36 taxa across the core genistoids, including 26 newly sequenced taxa. Nuclear and plastome based maximum likelihood (ML) and ASTRAL analyses were conducted based on varying degrees of taxon coverage and read mapping consensus threshold values. Additional analyses were performed to estimate divergence times and to reconstruct biogeographic history. The results strongly support a relictual Old World clade, presently composed ofV. turcicaandT. chinensis, which diverged from the ancestor of the North American lineage during the mid to late Miocene. A single and recent North America–East Asia dispersal involvingT. lupinoidesis reported. Furthermore, the traditional inclusion of the genusAmmopiptanthusamong Thermopsideae, and the recent recircumscription ofT. turcicato the monotypicVuralia, are not supported. A relatively high degree of cytonuclear discordance is reported within each sub-clade of the North American Thermopsideae. This finding is likely attributable to the high degree of interspecific hybridization reported within these groups and raises the need for more rigorous genome-scale testing to disentangle their complex phylogenies.Subjects:Biodiversity, Biogeography, Evolutionary Studies, Genetics, Plant Science
GLP-1 enhances beta-cell response to protein ingestion independent of glycemia and bariatric surgery amplifies it
Authors: Rayas Maria , Gastaldelli Amalia , Honka Henri , Pezzica Samantha , Carli Fabrizia , Peterson Richard , DeFronzo Ralph , Salehi Marzieh 
Published: October 2023

ABSTRACTBackgroundThe glycemic-independent actions of glucagon-like peptide 1 (GLP-1) in the prandial state in humans are largely unknown. Protein ingestion stimulates beta-cell secretion without changing plasma glucose concentration. We examined the contribution of endogenous GLP-1 to glucose metabolism and beta-cell response to protein ingestion under basal glucose concentrations, and whether these responses are affected by rerouted gut after gastric bypass (GB) or sleeve gastrectomy (SG).MethodsInsulin secretion rate (ISR) and glucose fluxes during a 50-gram oral protein load were compared between 10 non-diabetic individuals with GB, 9 matched subjects with SG and 7 non-operated controls (CN) with and without intravenous infusion of exendin-(9–39) [Ex-9], a specific GLP-1 receptor (GLP-1R) antagonist.ResultsBlocking GLP-1R increased plasma glucose concentration before and after protein ingestion and decreased beta-cell sensitivity to glucose in the first 30 minutes of protein ingestion (p<0.05) in all 3 groups. However, reduction in the premeal ISR by Ex-9 infusion only was observed in CN (p<0.05 for interaction), whereas diminished prandial ISR3hby GLP-1R blockade was observed in GB and SG and not in controls (p<0.05 for interaction). Also, GLP-1R blockade enhanced post-protein insulin action in GB and SG, but not in CN. Endogenous glucose production (EGP) during the first hour after protein ingestion was increased in all 3 groups butEGP3hwas accentuated by Ex-9 infusion only in GB (p<0.05 for interaction).ConclusionThese findings are consistent with both a glucose-independent pancreatic and extra-pancreatic role for GLP-1 during protein ingestion in humans that are exaggerated by bariatric surgery.Trial registrationThis study was registered at Clinical Trials.Gov:NCT02823665
Shortening heart rate variability measurement time to 1 minute using deep learning: Implication of real-time measurement of heart rate variability
Authors: Shin Junghwa , Lee Byung-Chae , Jeong Kee Sam , Kim Kwang Yoon , Kim Bom-Taeck 
Published: October 2023

AbstractHeart rate variability (HRV) is an effective predictor of cardiovascular diseases. The current standard 5-min recording time is lengthy compared with routine clinical examinations such as blood pressure measurement. Previous studies have observed that the indices of 3-min HRV data are as clinically meaningful as those of 5-min HRV data; however, shorter durations are considered unreliable, and there have been no attempts to challenge this notion. This study aimed to validate the outcomes of 1-min HRV recordings reconstructed using deep learning algorithms. Three-minute HRV recordings from 34,885 participants were included in the analysis. Of the recordings, 60% (20,931), 30% (10,465), and 10% (3,489) were allocated to the training, validation, and test sets, respectively. Data from 1-min excerpts of the 3-min recordings were used as the input for the deep learning models to predict the data of the 3-min recordings. Various deep learning models were applied to each indicator, and the model that produced the lowest mean absolute error was selected as that particular indicator’s learning model. There was no statistical difference between the values of the 1-min recordings reconstructed by deep learning and those of the 3-min recordings. The 1-min recordings reconstructed by deep learning demonstrated a higher correlation with the 3-min recordings when compared with the 1-min recordings that were not processed by deep learning. They also strongly agreed with the 3-min recordings in the Bland–Altman analysis. The 1-min HRV recordings reconstructed by deep learning were as reliable as the 3-min HRV recordings, suggesting that a 1-min recording could serve as a proxy for real-time HRV monitoring in the future.
Improved particle swarm optimization based on multi-strategy fusion for UAV path planning
Authors: Ye Zijing , Li Huan , Wei Wenhong 
Published: October 2023

PurposePath planning is an important part of UAV mission planning. The main purpose of this paper is to overcome the shortcomings of the standard particle swarm optimization (PSO) such as easy to fall into the local optimum, so that the improved PSO applied to the UAV path planning can enable the UAV to plan a better quality path.Design/methodology/approachFirstly, the adaptation function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV itself. Secondly, the standard PSO is improved, and the improved particle swarm optimization with multi-strategy fusion (MFIPSO) is proposed. The method introduces class sigmoid inertia weight, adaptively adjusts the learning factors and at the same time incorporates K-means clustering ideas and introduces the Cauchy perturbation factor. Finally, MFIPSO is applied to UAV path planning.FindingsSimulation experiments are conducted in simple and complex scenarios, respectively, and the quality of the path is measured by the fitness value and straight line rate, and the experimental results show that MFIPSO enables the UAV to plan a path with better quality.Originality/valueAiming at the standard PSO is prone to problems such as premature convergence, MFIPSO is proposed, which introduces class sigmoid inertia weight and adaptively adjusts the learning factor, balancing the global search ability and local convergence ability of the algorithm. The idea of K-means clustering algorithm is also incorporated to reduce the complexity of the algorithm while maintaining the diversity of particle swarm. In addition, the Cauchy perturbation is used to avoid the algorithm from falling into local optimum. Finally, the adaptability function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV itself, which improves the accuracy of the evaluation model.