bluuebunny/crossref_metadata_2025_split huggingface dataset:
Towards an advanced neurotechnological system: colorimetric sensing with a novel grism-based spectrometer, functionalized gold nanoparticles and a heterogeneous embedded system
Authors: Lachance Gabriel P. , Boisselier Élodie , Boukadoum Mounir , Miled Amine 
Published: June 2022

Neurotransmitter sensing in the brain is crucial for the understanding of neuro-degenerative diseases. Most modern methods for the purpose rely on bulky instruments or are disruptive to the neurotransmitter medium. In this work, we describe and evaluate the design of a novel, compact and non-invasive instrument for neurotransmitter detection based on the colorimetric sensing method. The instrument includes a grism-based spectrometer that measures the wavelength shift of gold nanoparticles that are functionalized with aptamers to act as neurotransmitter-specific markers. It also includes microfluidic and electronic subsystems for sample preparation and control, and processing of the obtained signal. The instrument is tested with gold nanoparticles and its performance is compared to that of a commercial instrument, showing that the designed prototype matches the commercial instrument in performance while being much smaller, and it can surpass it with further improvements.
This article is part of the theme issue ‘Advanced neurotechnologies: translating innovation for health and well-being’.
Full-hand electrotactile feedback using electronic skin and matrix electrodes for high-bandwidth human–machine interfacing
Authors: Abbass Yahya , Dosen Strahinja , Seminara Lucia , Valle Maurizio 
Published: June 2022

Tactile feedback is relevant in a broad range of human–machine interaction systems (e.g. teleoperation, virtual reality and prosthetics). The available tactile feedback interfaces comprise few sensing and stimulation units, which limits the amount of information conveyed to the user. The present study describes a novel technology that relies on distributed sensing and stimulation to convey comprehensive tactile feedback to the user of a robotic end effector. The system comprises six flexible sensing arrays (57 sensors) integrated on the fingers and palm of a robotic hand, embedded electronics (64 recording channels), a multichannel stimulator and seven flexible electrodes (64 stimulation pads) placed on the volar side of the subject’s hand. The system was tested in seven subjects asked to recognize contact positions and identify contact sliding on the electronic skin, using distributed anode configuration (DAC) and single dedicated anode configuration. The experiments demonstrated that DAC resulted in substantially better performance. Using DAC, the system successfully translated the contact patterns into electrotactile profiles that the subjects could recognize with satisfactory accuracy (i.e. median{IQR} of 88.6{11}%for static and93.3{5}%for dynamic patterns). The proposed system is an important step towards the development of a high-density human–machine interfacing between the user and a robotic hand.This article is part of the theme issue ‘Advanced neurotechnologies: translating innovation for health and well-being’.
Life-history diversity in lakes is associated with ecosystem size
Authors: Rypel Andrew L. 
Published: June 2022

AbstractIn this study, I inspect how ecosystem size drives fish life-history strategies in north temperate lakes. Species were classified as equilibrium, periodic, or opportunistic strategists according to Winemiller and Rose (1992), and species-area curves assembled and compared among strategy types. The smallest lakes were often dominated by only one species, usually an opportunistic strategist. Overall, species richness rose with ecosystem size, but larger ecosystems tended to be dominated by more periodic and equilibrium strategists. Richness of periodic species increased with ecosystem size at a faster rate compared to opportunistic species. Similarly, life-history niche space increased with ecosystem size in accord with species-area relationships, but showed saturation behavior (i.e., life-history niche space became increasingly ‘packed’ in large lakes). As predicted by theory, relative abundances of opportunistic strategists were extremely variable over space and time, whereas abundances of equilibrium and periodic strategists were more stable. Integration of species-area relationships with life-history theory provides insights into community assembly at multiple scales, and has broad conservation applications.
Habitat protection and restoration: win-win opportunities for migratory birds in the Northern Andes
Authors: Gonzalez Ana M. , Espejo Nestor , Armenteras Dolors , Hobson Keith A. , Kardynal Kevin J. , Mitchell Greg W. , Mahony Nancy , Bishop Christine A. , Negret Pablo J. , Wilson Scott 
Published: June 2022

AbstractIdentifying strategies that offer co-benefits for biodiversity protection, forest restoration and human well-being are important for successful conservation outcomes. In this study, we identified opportunities where forest restoration and rehabilitation programs in Colombia also align with priority areas for the conservation of Neotropical migratory birds. We used citizen science eBird-based abundance estimates to define regions with the highest richness of Neotropical migratory birds of conservation concern at montane elevations in Colombia and aligned these high richness areas with domestic initiatives for forest protection (Forest Areas), restoration (Restoration Areas) and rehabilitation (Rehabilitation Areas). We quantified the location and amounts of these three areas as well as the type of land protection and designation within them, specifically, National Protected Areas, Indigenous Reserves, Afro-descendent territories, and regions affected by poverty and violence that are prioritized for rural development by the Colombian government in Post-conflict Territorially Focused Development Programs (PDET). Almost half of Forest Areas overlapped with PDETs where goals for economic development present a risk of forest loss if not done sustainably. There was a 20% overlap between Forest Areas and Afro-descendant territories and indigenous reserves; most of this overlap was outside of established protected areas thus presenting an opportunity for community forest conservation that benefits migratory birds. We found an alignment of less than 6% between migrant bird focal areas and the priority Restoration and Rehabilitation Planning Areas identified by the Colombian National Restoration Plan indicating less opportunity for these programs to simultaneously benefit Neotropical migrant species. Our approach highlights that timely and efficient conservation of declining migrants depends on identifying the regions and strategies that incorporate local communities as part of the solution to forest loss and degradation in Colombia.HighlightsColombia covers over half of key wintering areas for migratory birds in South AmericaMost of the migrants’ overwinter range overlaps with working landscapesPriority national restoration/rehabilitation areas are ineffective to benefit migrantsForest conservation needs actions involving vulnerable and minority groups
Intracranial Aneurysm Wall Displacement Predicts Instability
Authors: Pionteck A. , Abderezaei J. , Fillingham P. , Chuang Y.-C. , Sakai Y. , Belani P. , Rigney B. , De Leacy R. , Fifi J. , Chien A. , Villablanca P. , Colby G. , Jahan R. , Duckwiler G. , Sayre J. , Holdsworth S. , Levitt M. , Mocco J. , Kurt M. , Nael K. 
Published: June 2022

AbstractRuptured intracranial aneurysms (IAs) are catastrophic events associated with a high mortality rate. An estimation of 6 million people in the United States have reported IAs, raising a pressing need for diagnostic tools to assess IAs rupture risks. Current population-based guidelines are imperfect, hence the need for new quantifiable variables and imaging markers. Aneurysm wall motion has been identified as a potential marker of high risk aneurysms, but conventional imaging techniques are challenged by small IAs sizes and limited spatial resolution. Recently, amplified Flow (aFlow) has been introduced as an algorithm which allows visualization and quantification of aneurysm wall motion based on amplification of 4D flow MRI data. In this work, we used aFlow to assess IAs wall motion in patients with growing aneurysms. The results were compared with a patient cohort with stable aneurysms. Among 118 patients with unruptured IAs who underwent sequential surveillance imaging, 10 patients with growing IAs who had baseline 3D TOF-MRA and 4D flow MR imaging were identified and matched with another cohort of patients with stable IAs based on IAs size and location. aFlow was then applied to the 4D flow MR data to amplify the aneurysm wall displacement. Voxel-based values of displacement were extracted for each aneurysm and normalized with respect to the reference parent artery. Following histogram analysis, the highest and lowest IAs displacements were calculated, together with their standard deviation and interquartile ranges. A paired-wise analysis was adopted to assess the differences among clinical variables, demographic data, morphological features, and aFlow parameters between patients with stable versus growing aneurysm. Results demonstrated higher wall motion and higher variability of deformation for the growing aneurysms, possibly due to inhomogeneities of the mechanical characteristics of the vessels walls or to underlying hemodynamics. Computational Fluid Dynamic simulation was also conducted for a subset of 6 stable and 6 growing aneurysms to examine the correlation between hemodynamic parameters, wall motion, and aneurysm stability. The magnitude and variance of directional wall shear stress gradient, in addition to area of colocation of elevated oscillatory shear stress and high variance in pressure, were highly correlated with both wall motion and aneurysm stability. We demonstrated here that the measurement and amplification of the aneurysm wall motion achieved with our method has the potential to differentiate stable from growing aneurysms, and potentially act as a substitute for in depth computational fluid dynamic analysis.
CREWdb 1.0: Optimizing Chromatin Readers, Erasers, and Writers Database using Machine Learning-Based Approach
Authors: Natesan Maya , Ghag Reetika , Kong Mitchell , Shi Min , Mollah Shamim 
Published: June 2022

AbstractAberration in heterochromatin and euchromatin states contributes to various disease phenotypes. The transcriptional regulation between these two states is significantly governed by post-translational modifications made by three functional types of chromatin regulators: readers, writers, and erasers. Writers introduce a chemical modification to DNA and histone tails, readers bind the modification to histone tails using specialized domains, and erasers remove the modification introduced by writers. Altered regulation of these chromatin regulators results in complex diseases such as cancer, neurodevelopmental diseases, myocardial diseases, kidney diseases, and embryonic development. Due to the reversible nature of chromatin modifications, we can develop therapeutic approaches targeting these chromatin regulators. However, a limited number of chromatin regulators have been identified thus far, and a subset of them are ambiguously classified as multiple chromatin regulator functional types. Thus, we have developed machine learning-based approaches to predict and classify the functional roles of chromatin regulator proteins, thereby optimizing the accuracy of the first comprehensive database of chromatin regulators known asCREWdb.GitHub URLCREWdb source code is available athttps://github.com/smollahlab/CREWdbDatabase URLCREWdb webtool is available athttp://mollahlab.wustl.edu/crewdb
Spectral performance evaluation of a second-generation spectral detector CT
Authors: Liu Leening P. , Shapira Nadav , Halliburton Sandra S. , Meyer Sebastian , Perkins Amy , Litt Harold I. , Kauczor Hans Ulrich , Leiner Tim , Stiller Wolfram , Noël Peter B. 
Published: June 2022

AbstractObjectiveTo characterize a second-generation wide-detector dual-layer spectral computed tomography system for material quantification accuracy, acquisition parameter and patient size dependencies, and tissue characterization capabilities.MethodsA phantom with multiple tissue-mimicking and material inserts was scanned with a dual-layer spectral detector CT using different tube voltages, collimation widths, radiation dose levels, and size configurations. Accuracy of iodine density maps and virtual monoenergetic images (MonoE) were investigated. Additionally, differences between conventional and MonoE 70 keV images were calculated to evaluate acquisition parameter and patient size dependencies. To demonstrate material quantification and differentiation, liver-mimicking inserts with adipose and iron were analyzed with a two-base decomposition utilizing MonoE 50 and 150 keV, and root mean square error (RMSE) for adipose and iron content was reported.ResultsSpectral accuracy was high for the measured inserts across a wide range of MonoE levels. MonoE 70 keV demonstrated reduced dependence compared to conventional image for phantom size (3 vs. 29 HU) and acquisition parameters, particularly tube voltage (5 vs. 43 HU) and noise-dose (9 vs. 11 HU). Iodine density quantification was successful with errors ranging from 0.25 to 0.5 mg/mL. Similarly, inserts with different amounts of adipose and iron were easily differentiated, and the small deviation in values within inserts corresponded to a RMSE of 1.78 ± 0.37% and 0.87 ± 0.37 mg/mL for adipose and iron content, respectively.ConclusionThe second-generation dual-layer CT enables acquisition of quantitatively accurate spectral data without compromises from differences in patient size and acquisition parameters.Key Points-With second-generation wide-detector dual-layer computed tomography, spectral quantification is further improved.-Spectral performance is independent of acquisition parameters such as tube voltage (100 kVp versus 120 kVp) and z-coverage (10 versus 80 mm).-Spectral performance is not significantly impacted by patient habitus.
Protein profiling of breast carcinomas reveals expression of immune-suppressive factors and signatures relevant to patient outcome
Authors: Ruoff Felix , Kersten Nicolas , Anderle Nicole , Jerbi Sandra , Stahl Aaron , Koch André , Staebler Anette , Hartkopf Andreas , Brucker Sara Y. , Hahn Markus , Schenke-Layland Katja , Schmees Christian , Templin Markus F. 
Published: June 2022

AbstractBackgroundIn cancerous tissue, a complex interplay of tumour cells with different cell types from the tumour microenvironment is causing modulations in signalling processes. By directly assessing expression of a multitude of proteins and protein variants, extensive information on signalling pathways, their activation status and the effect of the immunological landscape can be obtained providing viable information for treatment response.MethodsProtein extracted from archived breast cancer tissue from patients without adjuvant therapy was subjected to high-throughput Western blotting using the DigiWest technology. Expression of 150 proteins and protein variants covering cell cycle control, apoptosis, Jak/Stat, MAPK-, Pi3K/Akt-, Wnt-, and, autophagic signalling as well as general tumour markers was monitored in a cohort of 84 patient samples. The degree of immune cell infiltration was investigated and set against treatment outcome by integrating patient specific follow-up data.ResultsCharacterization of the tumour microenvironment by monitoring CD8α, CD11c, CD16 and CD68 expression revealed a strong correlation of event-free patient survival with immune cell infiltration. Furthermore, the presence of tumour infiltrating lymphocytes was linked to a pronounced activation of the Jak/Stat signalling pathway and apoptotic processes. Elevated phosphorylation of peroxisome proliferator-activated receptor gamma (PPARγ, pS112) in non-immune infiltrated tumour tissue suggests a novel immune evasion mechanism in breast cancer characterized by increased PPARγ activation.ConclusionMultiplexed immune cell marker assessment and protein profiling of tumour tissue provides functional signalling data facilitating breast cancer patient stratification.
A Multi-scale, Multiomic Atlas of Human Normal and Follicular Lymphoma Lymph Nodes
Authors: Radtke Andrea J. , Postovalova Ekaterina , Varlamova Arina , Bagaev Alexander , Sorokina Maria , Kudryashova Olga , Meerson Mark , Polyakova Margarita , Galkin Ilia , Svekolkin Viktor , Isaev Sergey , Perelman Grigory , Lozinsky Yaroslav , Yaniv Ziv , Lowekamp Bradley C. , Speranza Emily , Yao Li , Pittaluga Stefania , Shaffer Arthur L. , Jonigk Danny , Phelan James D. , Davies-Hill Theresa , Huang Da Wei , Ovcharov Pavel , Nomie Krystle , Nuzhdina Ekaterina , Kotlov Nikita , Ataullakhanov Ravshan , Fowler Nathan , Kelly Michael , Muppidi Jagan , Davis Jeremy , Hernandez Jonathan M. , Wilson Wyndham H. , Jaffe Elaine S. , Staudt Louis M. , Roschewski Mark , Germain Ronald N. 
Published: June 2022

SUMMARYReference atlases, molecular and spatial maps of mammalian tissues, are critical resources for discovery efforts and translational research. Their utility is dependent on operationalizing the resulting data by identifying cell types, histological patterns, and predictive biomarkers underlying health and disease. The human lymph node (LN) offers a compelling use case because of its importance in immunity, structural and cellular diversity, and neoplastic involvement. One hematological malignancy, follicular lymphoma (FL), evolves from developmentally blocked germinal center B cells residing in and trafficking through these tissues. To promote survival and immune escape, tumor B cells undergo significant genetic changes and extensively remodel the lymphoid microenvironment. Here, we present an integrated portrait of healthy and FL LNs using multiple genomic and advanced imaging technologies. By leveraging the strengths of each platform, we identified several tumor-specific features and microenvironmental patterns enriched in individuals who experience early relapse, the most high-risk of FL patients.
Epigenome-wide association study analysis of calorie restriction in humans, CALERIE™ Trial analysis
Authors: Ramaker Megan E. , Corcoran David L. , Apsley Abner T. , Kobor Michael S. , Kraus Virginia B. , Kraus William E. , Lin David T. S. , Orenduff Melissa C. , Pieper Carl F. , Waziry Reem , Huffman Kim M. , Belsky Daniel W. 
Published: June 2022

ABSTRACTBACKGROUNDCalorie restriction (CR) increases healthy lifespan and is accompanied by slowing or reversal of aging-associated DNA methylation (DNAm) changes in animal models. In the Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy (CALERIE™) human trial we evaluated associations of CR and changes in whole-blood DNAm.METHODSCALERIE™ randomized 220 healthy, non-obese adults in a 2:1 allocation to two years of CR or ad libitum (AL) diet. The average CR in the treatment group through 24-months of follow-up was 12%. Whole blood (baseline, 12 and 24 month) DNAm profiles were measured. Epigenome-wide association study (EWAS) analysis tested CR-induced changes from baseline to 12- and 24-months in the n=197 participants with available DNAm data.RESULTSNo CpG-site-specific changes with CR reached epigenome-wide significance (FDR<0.05). Secondary analyses of CpG sites identified in published EWAS suggest, we found that CR induced DNAm changes opposite those associated with body mass index (BMI) and smoking (p<0.003 at 12- and 24-month follow-ups). In contrast, CR altered DNAm at chronological-age associated CpG sites in the direction of older age (p<0.003 at 12- and 24-month follow-ups).CONCLUSIONAlthough individual CpG site DNAm changes in response to CR were not identified, analyses of sets CpGs identified in prior EWAS revealed CR-induced changes to blood DNAm. Altered CpG sets were enriched for insulin-production, glucose-tolerance, inflammation, and DNA-binding and -regulation pathways, several of which are known to be modified by CR. DNAm changes may contribute to CR effects on aging.
Increasing information gain in animal research by improving statistical model accuracy
Authors: Waterkamp Christoph , von Kortzfleisch Vanessa Tabea , Neu Christoph , Kitanovski Simo , Richter S. Helene , Hoffmann Daniel 
Published: June 2022

AbstractReduction of the numbers of laboratory animals is one of the three pillars of ethical animal research. Equivalently, information gain per animal should be maximized. A road towards this goal that is barely taken in current animal research is the more accurate statistical modeling of experiments. Here we show for a typical experiment (“open field test”) with outcomes that are non-normally distributed count data, how this can be implemented and what information gain is achieved. We contrast the state of the art – the use of confidence intervals based on null-hypothesis significance testing (NHST) –, with a Bayesian approach with the same underlying normal model, and a Bayesian approach with a more accurate negative binomial model. We find that the more accurate model leads to a marked improvement of knowledge gained with the experiment, especially for small sample sizes. As experimental data that violate assumptions of simple, conventional models are frequent, our findings have wider implications.
Multi-task learning for single-cell multi-modality biology
Authors: Tang Xin , Zhang Jiawei , He Yichun , Zhang Xinhe , Lin Zuwan , Partarrieu Sebastian , Hanna Emma Bou , Ren Zhaolin , Yang Yuhong , Wang Xiao , Li Na , Ding Jie , Liu Jia 
Published: June 2022

AbstractCurrent biotechnologies can simultaneously measure multi-modality high-dimensional information from the same cell and tissue samples. To analyze the multi-modality data, common tasks such as joint data analysis and cross-modal prediction have been developed. However, current analytical methods are generally designed to process multi-modality data for one specific task without considering the underlying connections between tasks. Here, we present UnitedNet, a multi-task deep neural network that integrates the tasks of joint group identification and cross-modal prediction to analyze multi-modality data. We have found that multi-task learning for joint group identification and cross-modal prediction significantly improves the performance of each task. When applied to various single-cell multi-modality datasets, UnitedNet shows superior performance in each task, achieving better unsupervised and supervised joint group identification and cross-modal prediction performances compared with state-of-the-art methods. Furthermore, by considering the spatial information of cells as one modality, UnitedNet substantially improves the accuracy of tissue region identification and enables spatially resolved cross-modal prediction.