bluuebunny/crossref_metadata_2025_split huggingface dataset:
Binding events through the mutual synchronization of spintronic nano-neurons
Authors: Romera Miguel , Talatchian Philippe , Tsunegi Sumito , Yakushiji Kay , Fukushima Akio , Kubota Hitoshi , Yuasa Shinji , Cros Vincent , Bortolotti Paolo , Ernoult Maxence , Querlioz Damien , Grollier Julie 
Published: February 2022

AbstractThe brain naturally binds events from different sources in unique concepts. It is hypothesized that this process occurs through the transient mutual synchronization of neurons located in different regions of the brain when the stimulus is presented. This mechanism of ‘binding through synchronization’ can be directly implemented in neural networks composed of coupled oscillators. To do so, the oscillators must be able to mutually synchronize for the range of inputs corresponding to a single class, and otherwise remain desynchronized. Here we show that the outstanding ability of spintronic nano-oscillators to mutually synchronize and the possibility to precisely control the occurrence of mutual synchronization by tuning the oscillator frequencies over wide ranges allows pattern recognition. We demonstrate experimentally on a simple task that three spintronic nano-oscillators can bind consecutive events and thus recognize and distinguish temporal sequences. This work is a step forward in the construction of neural networks that exploit the non-linear dynamic properties of their components to perform brain-inspired computations.
Using language in social media posts to study the network dynamics of depression longitudinally
Authors: Kelley Sean W. , Gillan Claire M. 
Published: February 2022

AbstractNetwork theory of mental illness posits that causal interactions between symptoms give rise to mental health disorders. Increasing evidence suggests that depression network connectivity may be a risk factor for transitioning and sustaining a depressive state. Here we analysed social media (Twitter) data from 946 participants who retrospectively self-reported the dates of any depressive episodes in the past 12 months and current depressive symptom severity. We construct personalised, within-subject, networks based on depression-related linguistic features. We show an association existed between current depression severity and 8 out of 9 text features examined. Individuals with greater depression severity had higher overall network connectivity between depression-relevant linguistic features than those with lesser severity. We observed within-subject changes in overall network connectivity associated with the dates of a self-reported depressive episode. The connectivity within personalized networks of depression-associated linguistic features may change dynamically with changes in current depression symptoms.
Data-driven modeling and prediction of non-linearizable dynamics via spectral submanifolds
Authors: Cenedese Mattia , Axås Joar , Bäuerlein Bastian , Avila Kerstin , Haller George 
Published: February 2022

AbstractWe develop a methodology to construct low-dimensional predictive models from data sets representing essentially nonlinear (or non-linearizable) dynamical systems with a hyperbolic linear part that are subject to external forcing with finitely many frequencies. Our data-driven, sparse, nonlinear models are obtained as extended normal forms of the reduced dynamics on low-dimensional, attracting spectral submanifolds (SSMs) of the dynamical system. We illustrate the power of data-driven SSM reduction on high-dimensional numerical data sets and experimental measurements involving beam oscillations, vortex shedding and sloshing in a water tank. We find that SSM reduction trained on unforced data also predicts nonlinear response accurately under additional external forcing.
HSL1 and BAM1/2 impact epidermal cell development by sensing distinct signaling peptides
Authors: Roman Andra-Octavia , Jimenez-Sandoval Pedro , Augustin Sebastian , Broyart Caroline , Hothorn Ludwig A. , Santiago Julia 
Published: February 2022

AbstractThe membrane receptor kinases HAESA and HSL2 recognize a family of IDA/IDL signaling peptides to control cell separation processes in different plant organs. The homologous HSL1 has been reported to regulate epidermal cell patterning by interacting with a different class of signaling peptides from the CLE family. Here we demonstrate that HSL1 binds IDA/IDL peptides with high, and CLE peptides with lower affinity, respectively. Ligand sensing capability and receptor activation of HSL1 require a SERK co-receptor kinase. Crystal structures with IDA/IDLs or with CLE9 reveal that HSL1-SERK1 complex recognizes the entire IDA/IDL signaling peptide, while only parts of CLE9 are bound to the receptor. In contrast, the receptor kinase BAM1 interacts with the entire CLE9 peptide with high affinity and specificity. Furthermore, the receptor tandem BAM1/BAM2 regulates epidermal cell division homeostasis. Consequently, HSL1-IDLs and BAM1/BAM2-CLEs independently regulate cell patterning in the leaf epidermal tissue.
Care-seeking and delay of care during COPD exacerbations
Authors: Locke Emily R. , Young Jessica P. , Battaglia Catherine , Simpson Tracy L. , Trivedi Ranak , Simons Carol , Fortney John C. , Hebert Paul , Swenson Erik R. , Edelman Jeffrey , Fan Vincent S. 
Published: February 2022

AbstractPatients who receive earlier treatment for acute exacerbations of chronic obstructive pulmonary disease (COPD) have a better prognosis, including earlier symptom resolution and reduced risk of future emergency-department visits (ED) or hospitalizations. However, many patients delay seeking care or do not report worsening symptoms to their healthcare provider. In this study, we aimed to understand how patients perceived their breathing symptoms and identify factors that led to seeking or delaying care for an acute exacerbation of COPD. We conducted semistructured interviews with 60 individuals following a recent COPD exacerbation. Participants were identified from a larger study of outpatients with COPD by purposive sampling by exacerbation type: 15 untreated, 15 treated with prednisone and/or antibiotics in the outpatient setting, 16 treated in an urgent care or ED setting, and 14 hospitalized. Data were analyzed using inductive content analysis. Participants were primarily male (97%) with a mean age of 69.1 ± 6.9 years, mean FEV1 1.42 (±0.63), and mean mMRC dyspnea of 2.7 (±1.1). We identified 4 primary themes: (i) access and attitudinal barriers contribute to reluctance to seek care, (ii) waiting is a typical response to new exacerbations, (iii) transitioning from waiting to care-seeking: the tipping point, and (iv) learning from and avoiding worse outcomes. Interventions to encourage earlier care-seeking for COPD exacerbations should consider individuals’ existing self-management approaches, address attitudinal barriers to seeking care, and consider health-system changes to increase access to non-emergent outpatient treatment for exacerbations.Clinical Trial Registration NCT02725294
The Digital Brain Tumour Atlas, an open histopathology resource
Authors: Roetzer-Pejrimovsky Thomas , Moser Anna-Christina , Atli Baran , Vogel Clemens Christian , Mercea Petra A. , Prihoda Romana , Gelpi Ellen , Haberler Christine , Höftberger Romana , Hainfellner Johannes A. , Baumann Bernhard , Langs Georg , Woehrer Adelheid 
Published: February 2022

AbstractCurrently, approximately 150 different brain tumour types are defined by the WHO. Recent endeavours to exploit machine learning and deep learning methods for supporting more precise diagnostics based on the histological tumour appearance have been hampered by the relative paucity of accessible digital histopathological datasets. While freely available datasets are relatively common in many medical specialties such as radiology and genomic medicine, there is still an unmet need regarding histopathological data. Thus, we digitized a significant portion of a large dedicated brain tumour bank based at the Division of Neuropathology and Neurochemistry of the Medical University of Vienna, covering brain tumour cases from 1995–2019. A total of 3,115 slides of 126 brain tumour types (including 47 control tissue slides) have been scanned. Additionally, complementary clinical annotations have been collected for each case. In the present manuscript, we thoroughly discuss this unique dataset and make it publicly available for potential use cases in machine learning and digital image analysis, teaching and as a reference for external validation.
E2F1-induced lncRNA, EMSLR regulates lncRNA LncPRESS1
Authors: Priyanka Priyanka , Sharma Madhur , Das Sanjeev , Saxena Sandeep 
Published: February 2022

AbstractE2F1 induces hundreds of protein-coding genes influencing diverse signaling pathways but much less is known about its non-coding RNA targets. For identifying E2F1-dependent oncogenic long non-coding RNAs (lncRNAs), we carried out genome-wide transcriptome analysis and discovered an lncRNA, EMSLR, which is induced both in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). EMSLR depletion blocks the cells in G1 phase and inhibits the clonogenic ability indicating that it is essential for the tumor-related phenotypes. We discovered that EMSLR represses the promoter activity of another lncRNA, LncPRESS1, which is located 6.9 kb upstream of EMSLR and they display an inverse expression pattern in lung cancer cell lines. Depletion of C-MYC results in downregulation of EMSLR and simultaneous upregulation of EMSLR target LncPRESS1, exemplifying how C-MYC and E2F1 signal transduction pathways control the network of lncRNA genes to modulate cell proliferation and differentiation.
Biomechanical duality of fracture healing captured using virtual mechanical testing and validated in ovine bones
Authors: Inglis Brendan , Schwarzenberg Peter , Klein Karina , von Rechenberg Brigitte , Darwiche Salim , Dailey Hannah L. 
Published: February 2022

AbstractBone fractures commonly repair by forming a bridging structure called callus, which begins as soft tissue and gradually ossifies to restore rigidity to the bone. Virtual mechanical testing is a promising technique for image-based assessment of structural bone healing in both preclinical and clinical settings, but its accuracy depends on the validity of the material model used to assign tissue mechanical properties. The goal of this study was to develop a constitutive model for callus that captures the heterogeneity and biomechanical duality of the callus, which contains both soft tissue and woven bone. To achieve this, a large-scale optimization analysis was performed on 2363 variations of 3D finite element models derived from computed tomography (CT) scans of 33 osteotomized sheep under normal and delayed healing conditions. A piecewise material model was identified that produced high absolute agreement between virtual and physical tests by differentiating between soft and hard callus based on radiodensity. The results showed that the structural integrity of a healing long bone is conferred by an internal architecture of mineralized hard callus that is supported by interstitial soft tissue. These findings suggest that with appropriate material modeling, virtual mechanical testing is a reliable surrogate for physical biomechanical testing.
A prospective cohort study about the effect of repeated living high and working higher on cerebral autoregulation in unacclimatized lowlanders
Authors: Graf Laura C. , Hartmann Sara E. , Lichtblau Mona , Muralt Lara , Bader Patrick R. , Lopez Ivan , Rawling Jean M. , Ulrich Silvia , Bloch Konrad E. , Poulin Marc J. , Furian Michael 
Published: February 2022

AbstractCerebral autoregulation (CA) is impaired during acute high-altitude (HA) exposure, however, effects of temporarily living high and working higher on CA require further investigation. In 18 healthy lowlanders (11 women), we hypothesized that the cerebral autoregulation index (ARI) assessed by the percentage change in middle cerebral artery peak blood velocity (Δ%MCAv)/percentage change in mean arterial blood pressure (Δ%MAP) induced by a sit-to-stand maneuver, is (i) reduced on Day1 at 5050 m compared to 520 m, (ii) is improved after 6 days at 5050 m, and (iii) is less impaired during re-exposure to 5050 m after 7 days at 520 m compared to Cycle1. Participants spent 4-8 h/day at 5050 m and slept at 2900 m similar to real-life working shifts. High/low ARI indicate impaired/intact CA, respectively. With the sit-to-stand at 520 m, mean (95% CI) in ΔMAP and ΔMCAv were − 26% (− 41 to − 10) and − 13% (− 19 to − 7), P < 0.001 both comparisons; mean ± SD in ARI was 0.58 ± 2.44Δ%/Δ%, respectively. On Day1 at 5050 m, ARI worsened compared to 520 m (3.29 ± 2.42Δ%/Δ%), P = 0.006 but improved with acclimatization (1.44 ± 2.43Δ%/Δ%, P = 0.039). ARI was less affected during re-exposure to 5050 m (1.22 ± 2.52Δ%/Δ%, P = 0.027 altitude-induced change between sojourns). This study showed that CA (i) is impaired during acute HA exposure, (ii) improves with living high, working higher and (iii) is ameliorated during re-exposure to HA.
Development of behavioral patterns in young C57BL/6J mice: a home cage-based study
Authors: Reiber Maria , Koska Ines , Pace Claudia , Schönhoff Katharina , von Schumann Lara , Palme Rupert , Potschka Heidrun 
Published: February 2022

AbstractEvidence exists that behavioral patterns only stabilize once mice reach adulthood. Detailed information about the course of behavioral patterns is of particular relevance for neuroscientific research and for the assessment of cumulative severity in genetically modified mice. The analysis considered five age groups focusing on behavioral assessments in the animals’ familiar home cage environment during the adolescence phase. We confirmed age- and sex-specific differences for several of the behavioral parameters and fecal corticosterone metabolites. Interestingly, an age-dependent decline in saccharin preference was detected in female mice. Regardless of sex, relevant levels of burrowing activity were only observed during later developmental phases. The development of nest complexity following the offer of new material was affected by age in female mice. In female and male mice, an age-dependency was evident for wheel running reaching a peak at P 50. A progressive increase with age was also observed for Open field activity. The data sets provide guidance for behavioral studies and for development of composite measure schemes for evidence-based severity assessment in young mice. Except for the burrowing test, the different behavioral tests can be applied in different age groups during post-weaning development. However, age- and sex-specific characteristics need to be considered.
Neuronal modulation in the mouse superior colliculus during covert visual selective attention
Authors: Wang Lupeng , Herman James P. , Krauzlis Richard J. 
Published: February 2022

AbstractCovert visual attention is accomplished by a cascade of mechanisms distributed across multiple brain regions. Visual cortex is associated with enhanced representations of relevant stimulus features, whereas the contributions of subcortical circuits are less well understood but have been associated with selection of relevant spatial locations and suppression of distracting stimuli. As a step toward understanding these subcortical circuits, here we identified how neuronal activity in the intermediate layers of the superior colliculus (SC) of head-fixed mice is modulated during covert visual attention. We found that spatial cues modulated both firing rate and spike-count correlations. Crucially, the cue-related modulation in firing rate was due to enhancement of activity at the cued spatial location rather than suppression at the uncued location, indicating that SC neurons in our task were modulated by an excitatory or disinhibitory circuit mechanism focused on the relevant location, rather than broad inhibition of irrelevant locations. This modulation improved the neuronal discriminability of visual-change-evoked activity, but only when assessed for neuronal activity between the contralateral and ipsilateral SC. Together, our findings indicate that neurons in the mouse SC can contribute to covert visual selective attention by biasing processing in favor of locations expected to contain task-relevant information.
Mitochondrial DNA diversity of the Sardinian local cattle stock
Authors: Petretto Elena , Dettori Maria Luisa , Pazzola Michele , Manca Fabio , Amills Marcel , Vacca Giuseppe Massimo 
Published: February 2022

AbstractThe aim of this research was to characterize the genetic diversity of the Sarda (Sa, n = 131), Sardo Bruna (SB, n = 44) and Sardo Modicana (SM, n = 26) cattle breeds, reared in the island of Sardinia (Italy). A portion of the mitochondrial DNA hypervariable region was sequenced, in order to identify a potential signature of African introgression. The FST coefficients among populations ranged between 0.056 for Sa vs SB and 0.167 for SB vs SM. AMOVA analysis indicated there was a significant differentiation of the three breeds, although most of diversity was gathered at the within-breed level. The Median Joining Network of the Sardinian sequences showed a potential founder effect signature. A MJ network including Sardinian cattle plus African, Italian, Iberian and Asian sequences, revealed the presence of haplogroup T3, already detected in Sa cattle, and the presence of Hg T1 and Hg T1′2′3, in Sa and SB. The presence of a private haplotype belonging to haplogroup T1, which is characteristic of African taurine breeds, may be due to the introgression of Sardinian breeds with African cattle, either directly (most probable source: North African cattle) or indirectly (through a Mediterranean intermediary already introgressed with African blood).
Evaluation of machine learning algorithms for trabeculectomy outcome prediction in patients with glaucoma
Authors: Banna Hasan Ul , Zanabli Ahmed , McMillan Brian , Lehmann Maria , Gupta Sumeet , Gerbo Michael , Palko Joel 
Published: February 2022

AbstractThe purpose of this study was to evaluate the performance of machine learning algorithms to predict trabeculectomy surgical outcomes. Preoperative systemic, demographic and ocular data from consecutive trabeculectomy surgeries from a single academic institution between January 2014 and December 2018 were incorporated into models using random forest, support vector machine, artificial neural networks and multivariable logistic regression. Mean area under the receiver operating characteristic curve (AUC) and accuracy were used to evaluate the discrimination of each model to predict complete success of trabeculectomy surgery at 1 year. The top performing model was optimized using recursive feature selection and hyperparameter tuning. Calibration and net benefit of the final models were assessed. Among the 230 trabeculectomy surgeries performed on 184 patients, 104 (45.2%) were classified as complete success. Random forest was found to be the top performing model with an accuracy of 0.68 and AUC of 0.74 using 5-fold cross-validation to evaluate the final optimized model. These results provide evidence that machine learning models offer value in predicting trabeculectomy outcomes in patients with refractory glaucoma.
The effect of unexpected rewards on decision making in cuttlefish
Authors: Chung Tzu-Ting , Darmaillacq Anne-Sophie , Dickel Ludovic , Chiao Chuan-Chin 
Published: February 2022

AbstractDespite numerous studies demonstrating the cognitive ability of cephalopods, there is currently no study showing an emotion-like behavior in this group of animals. To examine whether cuttlefish have different internal states, we developed a behavioral paradigm to assess if prior surprised events are able to alter the choice made by cuttlefish. By presenting unexpected food rewards to cuttlefish before the test, we investigated whether the reaction time of choosing between two shrimps, an intuitive response toward the prey without previous learning, at three different levels of discriminative tests (easy, difficult, and ambiguous), are different compared to the one without an unexpected reward. This behavioral paradigm serves to demonstrate whether cuttlefish are aware of ambiguous situations, and their choice outcome and reaction time are dependent of their internal states. The results show that the response latency was significantly shortened in the difficult and ambiguous tests when choosing from two shrimps that are either moderately different in size or similar sizes, respectively, when cuttlefish have received unexpected rewards before the test. These results were compared with tests during which the cuttlefish did not receive any reward in advance. Furthermore, this shortening of latency did not result in a difference in choice outcome during the difficult and ambiguous tests. Interestingly, even when cuttlefish have obtained the expected food rewards or simply made tentacular strike without prey capture each time before test, these prior experiences were sufficient to shorten the response latency in the difficult and ambiguous tests. However, different from the result of unexpected rewards, food consumption alone or prey capture failure did affect the choice outcome during the simple and difficult tests. Taken together, our findings suggest that pre-test treatments of unexpected and expected rewards or simply unsuccessful visual attack seem to induce cuttlefish to adopt different foraging behaviors. This context dependent decision making suggests that cuttlefish’s foraging strategies are influenced by the previously surprised event and their internal states. It also shows a speed-accuracy tradeoff in difficult and ambiguous situations when foraging for prey. This observation may lead to a future investigation of the presence of emotional state in cephalopods.
Dual use of e-cigarettes with conventional tobacco is associated with increased sleep latency in cross-sectional Study
Authors: Advani Ira , Gunge Deepti , Boddu Shreyes , Mehta Sagar , Park Kenneth , Perera Samantha , Pham Josephine , Nilaad Sedtavut , Olay Jarod , Ma Lauren , Masso-Silva Jorge , Sun Xiaoying , Jain Sonia , Malhotra Atul , Crotty Alexander Laura E. 
Published: February 2022

AbstractThe health effects of e-cigarettes remain relatively unknown, including their impact on sleep quality. We previously showed in a pilot study that females who smoke both conventional tobacco and vape e-cigarettes (dual users) had decreased sleep quality (measurement of how well an individual is sleeping) and increased sleep latency (amount of time to fall asleep), suggesting an influence by gender. Cough is also known to adversely impact sleep quality and may be caused by inhalant use. As a result, we undertook this study to assess the impact of e-cigarette, conventional tobacco, and dual use on sleep quality, sleep latency, cough, and drug use. Participants (n = 1198) were recruited through online surveys posted to social media sites with a monetary incentive. Participants were grouped by inhalant use, with 8% e-cigarette users, 12% conventional tobacco users, 30% dual users, and 51% non-smokers/non-vapers. Dual use of e-cigarettes and conventional tobacco was associated with increased sleep latency relative to non-smokers/non-vapers by multivariable linear regression (mean difference of 4.08; 95% CI: 1.12 to 7.05, raw p = 0.007, adjusted p = 0.042); however, dual usage was not significantly associated with sleep quality relative to non-smokers/non-vapers (mean difference 0.22, 95%CI: (−0.36, 0.80), raw p = 0.452, adjust p = 0.542). Dual use was also associated with a higher reporting of cough (p = 0.038), as well as increased marijuana (p < 0.001) and cocaine (p < 0.001) usage. This study demonstrates that dual use is associated with longer sleep latency, and suggests that the shared component of nicotine may be a driver. Because sleep broadly impacts multiple aspects of human health, defining the associations of e-cigarettes and vaping devices on sleep is critical to furthering our understanding of their influence on the body.