bluuebunny/crossref_metadata_2025_split huggingface dataset:
Strained two-dimensional tungsten diselenide for mechanically tunable exciton transport
Authors: Kim Jin Myung , Jeong Kwang-Yong , Kwon Soyeong , So Jae-Pil , Wang Michael Cai , Snapp Peter , Park Hong-Gyu , Nam SungWoo 
Published: December 2024

AbstractTightly bound electron-hole pairs (excitons) hosted in atomically-thin semiconductors have emerged as prospective elements in optoelectronic devices for ultrafast and secured information transfer. The controlled exciton transport in such excitonic devices requires manipulating potential energy gradient of charge-neutral excitons, while electrical gating or nanoscale straining have shown limited efficiency of exciton transport at room temperature. Here, we report strain gradient induced exciton transport in monolayer tungsten diselenide (WSe2) across microns at room temperature via steady-state pump-probe measurement. Wrinkle architecture enabled optically-resolvable local strain (2.4%) and energy gradient (49 meV/μm) to WSe2. We observed strain gradient induced flux of high-energy excitons and emission of funneled, low-energy excitons at the 2.5 μm-away pump point with nearly 45% of relative emission intensity compared to that of excited excitons. Our results strongly support the strain-driven manipulation of exciton funneling in two-dimensional semiconductors at room temperature, opening up future opportunities of 2D straintronic exciton devices.
Deep neural networks and humans both benefit from compositional language structure
Authors: Galke Lukas , Ram Yoav , Raviv Limor 
Published: December 2024

AbstractDeep neural networks drive the success of natural language processing. A fundamental property of language is its compositional structure, allowing humans to systematically produce forms for new meanings. For humans, languages with more compositional and transparent structures are typically easier to learn than those with opaque and irregular structures. However, this learnability advantage has not yet been shown for deep neural networks, limiting their use as models for human language learning. Here, we directly test how neural networks compare to humans in learning and generalizing different languages that vary in their degree of compositional structure. We evaluate the memorization and generalization capabilities of a large language model and recurrent neural networks, and show that both deep neural networks exhibit a learnability advantage for more structured linguistic input: neural networks exposed to more compositional languages show more systematic generalization, greater agreement between different agents, and greater similarity to human learners.
MaizeCODE reveals bi-directionally expressed enhancers that harbor molecular signatures of maize domestication
Authors: Cahn Jonathan , Regulski Michael , Lynn Jason , Ernst Evan , de Santis Alves Cristiane , Ramakrishnan Srividya , Chougule Kapeel , Wei Sharon , Lu Zhenyuan , Xu Xiaosa , Ramu Umamaheswari , Drenkow Jorg , Kramer Melissa , Seetharam Arun , Hufford Matthew B. , McCombie W. Richard , Ware Doreen , Jackson David , Schatz Michael C. , Gingeras Thomas R. , Martienssen Robert A. 
Published: December 2024

AbstractModern maize (Zea mays ssp. mays) was domesticated from Teosinte parviglumis (Zea mays ssp. parviglumis), with subsequent introgressions from Teosinte mexicana (Zea mays ssp. mexicana), yielding increased kernel row number, loss of the hard fruit case and dissociation from the cob upon maturity, as well as fewer tillers. Molecular approaches have identified transcription factors controlling these traits, yet revealed that a complex regulatory network is at play. MaizeCODE deploys ENCODE strategies to catalog regulatory regions in the maize genome, generating histone modification and transcription factor ChIP-seq in parallel with transcriptomics datasets in 5 tissues of 3 inbred lines which span the phenotypic diversity of maize, as well as the teosinte inbred TIL11. Transcriptomic analysis reveals that pollen grains share features with endosperm, and express dozens of “proto-miRNAs” potential vestiges of gene drive and hybrid incompatibility. Integrated analysis with chromatin modifications results in the identification of a comprehensive set of regulatory regions in each tissue of each inbred, and notably of distal enhancers expressing non-coding enhancer RNAs bi-directionally, reminiscent of “super enhancers” in animal genomes. Furthermore, the morphological traits selected during domestication are recapitulated, both in gene expression and within regulatory regions containing enhancer RNAs, while highlighting the conflict between enhancer activity and silencing of the neighboring transposable elements.
Distinguishing local isomorphism classes in quasicrystals by high-order harmonic spectroscopy
Authors: Liu Jia-Qi , Bian Xue-Bin 
Published: December 2024

AbstractElectron diffraction spectroscopy is a fundamental tool for investigating quasicrystal structures, which unveils the quasiperiodic long-range order. Nevertheless, it falls short in effectively distinguishing separate local isomorphism classes. This is a long outstanding problem. Here, we study the high-order harmonic generation in two-dimensional generalized Penrose quasicrystals to optically resolve different local isomorphism classes. The results reveal that: (i) harmonic spectra from different parts of a quasicrystal are identical, even though their atomic arrangements vary significantly. (ii) The harmonic yields of diverse local isomorphism classes exhibit variations, providing a way to distinguish local isomorphism classes. (iii) The rotational symmetry of harmonic yield can serve as a characteristic of quasicrystal harmonics and is consistent with the orientation order. Our results not only pave the way for confirming the experimental reproducibility of quasicrystal harmonics and identifying quasicrystal local isomorphism classes, but also shed light on comprehending electron dynamics influenced by the vertex environments.
Ampere-level reduction of pure nitrate by electron-deficient Ru with K+ ions repelling effect
Authors: Zhang Shi-Nan , Gao Peng , Liu Qian-Yu , Zhang Zhao , Leng Bing-Liang , Chen Jie-Sheng , Li Xin-Hao 
Published: December 2024

AbstractElectrochemical nitrate reduction reaction offers a sustainable and efficient pathway for ammonia synthesis. Maintaining satisfactory Faradaic efficiency for long-term nitrate reduction under ampere-level current density remains challenging due to the inevitable hydrogen evolution, particularly in pure nitrate solutions. Herein, we present the application of electron deficiency of Ru metals to boost the repelling effect of counter K+ ions via the electric-field-dependent synergy of interfacial water and cations, and thus largely promote nitrate reduction reaction with a high yield and well-maintained Faradaic efficiency under ampere-level current density. The pronounced electron deficiency of Ru metals boosts the repelling effect on hydrated K+ ions, as indicated by the distance of K+ ions to catalyst surface, which can loosen the water layer to depress hydrogen evolution and accelerate nitrate conversion. Consequently, the optimized electrode loaded with electron-deficient Ru atomic layers can directly produce 0.26 M ammonia solution in pure nitrate solution in 6 h, providing a high yield (74.8 mg mgcat–1 h–1) and well-maintained the Faradaic efficiency for over 120 h under ampere-level reduction.
Bayesian modeling of HFC production pipeline suggests growth in unreported CFC by-product and feedstock production
Authors: Bourguet Stephen , Lickley Megan 
Published: December 2024

AbstractObservationally-derived emissions of ozone depleting substances must be scrutinized to maintain the progress made by the Montreal Protocol in protecting the stratospheric ozone layer. Recent observations of three chlorofluorocarbons (CFCs), CFC-113, CFC-114, and CFC-115, suggest that emissions of these compounds have not decreased as expected given global reporting of their production. These emissions have been associated with hydrofluorocarbon (HFC) production, which can require CFCs as feedstocks or generate CFCs as by-products, yet emissions from these pathways have not been rigorously quantified. Here, we develop a Bayesian framework to jointly infer emissions of CFC-113, CFC-114, and CFC-115 during HFC-134a and HFC-125 production. We estimate that feedstock emissions from HFC-134a production accounted for 90% (82–94%) and 65% (47–77%) of CFC-113 and CFC-114 emissions, respectively, from 2015–2019, while by-product emissions during HFC-125 production accounted for 81% (68–92%) of CFC-115 emissions. Our results suggest that unreported feedstock production in low- to middle-income countries may explain the unexpected emissions of CFC-113 and CFC-114, although uncertainties within chemical manufacturing processes call for further investigation and industry transparency. This work motivates tightened feedstock regulations and adds a reduction in CFC emissions to the benefits of the HFC phasedowns scheduled by the Kigali Amendment.
Unsupervised inter-domain transformation for virtually stained high-resolution mid-infrared photoacoustic microscopy using explainable deep learning
Authors: Park Eunwoo , Misra Sampa , Hwang Dong Gyu , Yoon Chiho , Ahn Joongho , Kim Donggyu , Jang Jinah , Kim Chulhong 
Published: December 2024

AbstractMid-infrared photoacoustic microscopy can capture biochemical information without staining. However, the long mid-infrared optical wavelengths make the spatial resolution of photoacoustic microscopy significantly poorer than that of conventional confocal fluorescence microscopy. Here, we demonstrate an explainable deep learning-based unsupervised inter-domain transformation of low-resolution unlabeled mid-infrared photoacoustic microscopy images into confocal-like virtually fluorescence-stained high-resolution images. The explainable deep learning-based framework is proposed for this transformation, wherein an unsupervised generative adversarial network is primarily employed and then a saliency constraint is added for better explainability. We validate the performance of explainable deep learning-based mid-infrared photoacoustic microscopy by identifying cell nuclei and filamentous actins in cultured human cardiac fibroblasts and matching them with the corresponding CFM images. The XDL ensures similar saliency between the two domains, making the transformation process more stable and more reliable than existing networks. Our XDL-MIR-PAM enables label-free high-resolution duplexed cellular imaging, which can significantly benefit many research avenues in cell biology.
Cerebellar-driven cortical dynamics can enable task acquisition, switching and consolidation
Authors: Pemberton Joseph , Chadderton Paul , Costa Rui Ponte 
Published: December 2024

AbstractThe brain must maintain a stable world model while rapidly adapting to the environment, but the underlying mechanisms are not known. Here, we posit that cortico-cerebellar loops play a key role in this process. We introduce a computational model of cerebellar networks that learn to drive cortical networks with task-outcome predictions. First, using sensorimotor tasks, we show that cerebellar feedback in the presence of stable cortical networks is sufficient for rapid task acquisition and switching. Next, we demonstrate that, when trained in working memory tasks, the cerebellum can also underlie the maintenance of cognitive-specific dynamics in the cortex, explaining a range of optogenetic and behavioural observations. Finally, using our model, we introduce a systems consolidation theory in which task information is gradually transferred from the cerebellum to the cortex. In summary, our findings suggest that cortico-cerebellar loops are an important component of task acquisition, switching, and consolidation in the brain.
Rapid optical determination of salivary cortisol responses in individuals undergoing physiological and psychological stress
Authors: Ahmed Tashfia , Powner Michael B. , Qassem Meha , Kyriacou Panayiotis A. 
Published: December 2024

AbstractTraditional methods for management of mental illnesses in the post-pandemic setting can be inaccessible for many individuals due to a multitude of reasons, including financial stresses and anxieties surrounding face-to-face interventions. The use of a point-of-care tool for self-management of stress levels and mental health status is the natural trajectory towards creating solutions for one of the primary contributors to the global burden of disease. Notably, cortisol is the main stress hormone and a key logical indicator of hypothalamic-pituitary adrenal (HPA) axis activity that governs the activation of the human stress system. Therefore, the measurement of cortisol is imperative to lead the discussion of the relationship between psychological stress and mental health deterioration. The aim of the current study was to determine salivary cortisol concentrations of healthy individuals undergoing the MAST protocol for human stress activation, through optical-colorimetric techniques. The study demonstrates the use of the blue tetrazolium (BT) method as successful means of rapid measurement of cortisol in saliva, comparable to the gold-standard technique i.e., enzyme-linked immunoassays (ELISA) with a coefficient of determination (R2) of 0.997. The results support the future development of a point-of-care optical sensor-based device and mobile application for cortisol monitoring and stress profiling in adults.
Prognostic role of aetiological agent vs. clinical pattern in candidates to lead extraction for cardiac implantable electronic device infections
Authors: Massaro Giulia , Pascale Renato , Biffi Mauro , Martignani Cristian , Ziacchi Matteo , Simeone Andrea , Pittorru Raimondo , De Lazzari Manuel , Migliore Federico , Diemberger Igor 
Published: December 2024

AbstractCardiac implantable electronic devices infections (CIEDI) are associated with poor survival despite the improvement in transvenous lead extraction (TLE). Aetiology and systemic involvement are driving factors of clinical outcomes. The aim of this study was to explore their contribute on overall mortality. A prospective study was performed between 2011 and 2021, including all TLE candidates at our regional referral University hospital for CIEDI with microbiological confirmed aetiology. Considering significant predictors of mortality at multivariate Cox regression analyses, a 5-point BOP2D score was developed, and it was validated with a prospective cohort from the Padua University. 157 patients were enrolled (mean age 71.3 ± 12.3 years, 81.5% male). S. aureus was isolated in 32.5% of patients, and it was more associated with valvular heart disease, systemic infection, and chronic kidney disease. CIEDI pattern was associated with 1-year mortality, with a significantly worse outcome in patients with “cold closed pocket” (CCP). The developed BOP2D score presented a 0.807 AUC (95%CI 0.703–0.910, p < 0.001) and a good predictive value (OR 2.355, 95%CI 1.754–3.162; p < 0.001), and was associated with a progressive increase in mortality with a score > 2. The score validation with the registry from the Padua University (135 patients) retrieved a C-statistic of 0.746 (95%CI 0.613–0.879; p = 0.002). Both CCP and S. aureus were confirmed as risk factors for mortality in CIEDI patients. This study supports the hypothesis that the infectious process may occur through different mechanisms associated with different infection patterns, and high-risk patients should be considered for specific and aggressive approaches.
Real-time monitoring by interferometric light microscopy of phage suspensions for personalised phage therapy
Authors: Lapras Benjamine , Merienne Camille , Eynaud Emma , Usseglio Léa , Marchand Chloé , Médina Mathieu , Kolenda Camille , Briot Thomas , Laurent Frédéric , Pirot Fabrice ,   PHAGEinLYON, Lapras Benjamine , Merienne Camille , Eynaud Emma , Usseglio Léa , Marchand Chloé , Médina Mathieu , Kolenda Camille , Briot Thomas , Laurent Frédéric , Pirot Fabrice 
Published: December 2024

AbstractPhage therapy uses viruses (phages) against antibiotic resistance. Tailoring treatments to specific patient strains requires stocks of various highly concentrated purified phages. It, therefore, faces challenges: titration duration and specificity to a phage/bacteria couple; purification affecting stability; and highly concentrated suspensions tending to aggregate. To address these challenges, interferometric light microscopy (ILM), characterising particles (size, concentration, and visual homogeneity) within minutes, was applied herein to anti-Staphylococcus aureus myovirus phage suspensions. Particle concentration was linearly correlated with phage infectious titre (R2 > 0.97, slope: 3 particles/plaque forming units (PFU)) at various degrees of purification, allowing to approximate the infectious titre for suspensions ≥ 3 × 108 PFU/mL, thereby encompassing most therapeutic doses. Purification narrowed and homogenised particle distribution while maintaining therapeutic concentrations. When compared to dynamic light scattering, electrophoretic mobility, and UV/Visible-spectroscopy, ILM best detected aggregates according to our homemade scoring. Although ILM has certain limitations, such as the inability to detect podoviruses (hydrodynamic diameter < 80 nm), or to measure particles in low-concentrated suspensions (< 108 particles/mL), the present proof-of-concept positions this technique as a valuable quality control tool, as a complement to titration rather than a replacement for this technique, for phage suspensions, paving the way for further investigations.
Microplastic hotspots mapped across the Southern Ocean reveal areas of potential ecological impact
Authors: Hunter Aidan , Thorpe Sally E. , McCarthy Arlie H. , Manno Clara 
Published: December 2024

AbstractMarine microplastic is pervasive, polluting the remotest ecosystems including the Southern Ocean. Since this region is already undergoing climatic changes, the additional stress of microplastic pollution on the ecosystem should not be considered in isolation. We identify potential hotspot areas of ecological impact from a spatial overlap analysis of multiple data sets to understand where marine biota are likely to interact with local microplastic emissions (from ship traffic and human populations associated with scientific research and tourism). Then we account for cumulative effects by identifying which areas with potential elevated microplastic-biota interaction are already subject to climate change related stresses (ocean warming and acidification). Our analysis indicates that biologically productive coastal areas in proximity to populated facilities are where microplastics pose most risk to the ecosystem, and that the northern Antarctic Peninsula is likely to be the main risk hotspot. This study is the first to map the threat of microplastics to the Southern Ocean ecosystem in a multi-stressor context, locating where microplastic monitoring programmes and mitigation measures may be considered a matter of urgency.
Modulating the human gut microbiome and health markers through kombucha consumption: a controlled clinical study
Authors: Ecklu-Mensah Gertrude , Miller Rachel , Maseng Maria Gjerstad , Hawes Vienna , Hinz Denise , Kim Cheryl , Gilbert Jack A. 
Published: December 2024

AbstractFermented foods are becoming more popular due to their purported links to metabolic health and the gut microbiome. However, direct clinical evidence for the health claims is lacking. Here, we describe an eight-week clinical trial that explored the effects of a four-week kombucha supplement in healthy individuals consuming a Western diet, randomized into the kombucha (n = 16) or control (n = 8) group. We collected longitudinal stool and blood samples to profile the human microbiome and inflammation markers. We did not observe significant changes in either biochemical parameters or levels of circulating markers of inflammation across the entire cohort. However, paired analysis between baseline and end of intervention time points within kombucha or control groups revealed increases in fasting insulin and in HOMA-IR in the kombucha group whereas reductions in HDL cholesterol were associated with the control group. Shotgun metagenomic analysis revealed the relative abundance of Weizmannia, a kombucha-enriched probiotic and several SCFA producing taxa to be overrepresented in consumers at the end of the intervention. Collectively, in our healthy cohort consuming a Western diet, a short-term kombucha intervention induced modest impacts on human gut microbiome composition and biochemical parameters, which may be attributed to relatively small number of participants and the extensive inter-participant variability.
Revealing connectivity patterns of deep brain stimulation efficacy in Parkinson’s disease
Authors: Výtvarová Eva , Lamoš Martin , Hlinka Jaroslav , Goldemundová Sabina , Rektor Ivan , Bočková Martina 
Published: December 2024

AbstractThe aim of this work was to study the effect of deep brain stimulation of the subthalamic nucleus (STN-DBS) on the subnetwork of subcortical and cortical motor regions and on the whole brain connectivity using the functional connectivity analysis in Parkinson’s disease (PD). The high-density source space EEG was acquired and analyzed in 43 PD subjects in DBS on and DBS off stimulation states (off medication) during a cognitive-motor task. Increased high gamma band (50–100 Hz) connectivity within subcortical regions and between subcortical and cortical motor regions was significantly associated with the Movement Disorders Society – Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) III improvement after DBS. Whole brain neural correlates of cognitive performance were also detected in the high gamma (50–100 Hz) band. A whole brain multifrequency connectivity profile was found to classify optimal and suboptimal responders to DBS with a positive predictive value of 0.77, negative predictive value of 0.55, specificity of 0.73, and sensitivity of 0.60. Specific connectivity patterns related to PD, motor symptoms improvement after DBS, and therapy responsiveness predictive connectivity profiles were uncovered.
Rheological comparison of sputum and reconstituted airway epithelium mucus
Authors: Esteban Enjuto Lydia , Taty Poaty Vassylia , Bouveret Mendy , Song Huang , Constant Samuel , Patarin Jérémy 
Published: December 2024

AbstractPulmonary mucus serves as a crucial protective barrier in the respiratory tract, defending against pathogens and contributing to effective clearance mechanisms. In Muco Obstructive Pulmonary Diseases (MOPD), abnormal rheological properties lead to highly viscous mucus, fostering chronic infections and exacerbations. While prior research has linked mucus viscoelasticity to its mucin content, the variability in MOPD patients implies the involvement of other factors. To isolate these effects, mucus produced by epithelia reconstituted in vitro serves as a powerful versatile model for mucin research. This study characterises the rheology of mucus collected from Air-Liquid Interface (ALI) cultures and compares it to sputum samples from MOPD patients, demonstrating that macrorheology with cone-plate geometries is a reproducible method for analysing small mucus quantities from ALI cultures. While sputum samples exhibit similarities in rigidity with ALI mucus, they also display structural differences and variations in their response to substantial deformations. The study highlights the importance of understanding mucus behaviour under large deformations, emphasising the role of ALI cultures as a controlled environment for conducting detailed studies.