bluuebunny/crossref_metadata_2025_split huggingface dataset:
Repeated low-intensity focused ultrasound led to microglial profile changes in TgF344-AD rats
Authors: Abjean Laurene , Novell Anthony , Larrat Benoît , Gueorguiev Boris Rafael , Cailly Thomas , Fossey Christine , Fabis Frédéric , Salomir Rares , Tsartsalis Stergios , Tournier Benjamin B. , Millet Philippe , Ceyzériat Kelly 
Published: September 2024

AbstractAlzheimer’s disease (AD), the most common cause of dementia, represents one of the main clinical challenges of the century as the number of patients is predicted to triple by 2050. Despite the recent approval of three monoclonal antibodies targeting Amyloid β (Aβ) aggregates by the Food and Drug Administration (FDA), immunotherapies still face challenges due to the difficulty of antibodies crossing the blood-brain barrier (BBB). This necessitates administering large doses of drugs to achieve their therapeutic effects, which is associated with significant side effects. In this context, low-intensity focused ultrasound (LiFUS) appears as an innovative and non-invasive method which, in association with intravenous injection of microbubbles (MB), leads to a transient BBB opening. This innovative strategy has been extensively studied in different preclinical models and more recently in human clinical trials, particularly in the context of AD. LiFUS+MB seems to increase the inflammatory response at short term, but the time course of this response is not consistent between studies, certainly due to the discrepancy between LiFUS protocols used. Moreover, the impact at longer term is understudied and the mechanisms underlying this effect are still not well understood. In our study, we therefore used the TgF344-AD rat model of AD, to investigate the effect of a single or multiple exposures to LiFUS+MB in the entire brain, on inflammatory response and amyloid load. The ultrasound attenuation through the skull was corrected to apply a peak negative acoustic pressure of 450 kHz in all treated animals. Single LiFUS+MB exposure induces a slight astrocyte and microglial response 24 hours post-treatment whereas repeated LiFUS treatment seems to induce microglial reprogramming, leading to the adaptation of gene expression related to key functions such as inflammatory response, mitochondrial and energetic metabolism. In our rat model and LiFUS+MB protocol conditions, multiple exposures did not modulate soluble/poorly aggregated forms nor the highly aggregated forms of Aβ40and Aβ42. For therapeutic AD management, LiFUS+MB could be combined with drugs such as immunotherapies. In a proof-of-concept experiment, we validated that LiFUS was also efficient to improve the brain entry of the anti-Aβ antibody, Aducanumab.
Acrylic Acid Modified Poly-ethylene Glycol Microparticles for Affinity-Based release of Insulin-Like Growth Factor-1 in Neural Applications
Authors: Ferrer Pablo Ramos , Sakiyama-Elbert Shelly 
Published: September 2024

AbstractSustained release of bioactive molecules via affinity-based interactions presents a promising approach for controlled delivery of growth factors. Insulin-like growth factor-1 (IGF-1) has gained increased attention due to its ability to promote axonal growth in the central nervous system. In this work, we aimed to evaluate the effect of IGF-1 delivery from polyethylene-glycol diacrylate (PEG-DA) microparticles using affinity-based sustained release on neurons. We developed PEG-DA-based microparticles with varying levels of acrylic acid (AA) as a comonomer to tune their overall charge. The particles were synthesized via precipitation polymerization under UV light, yielding microparticles (MPs) with a relatively low polydispersity index. IGF-1 was incubated with the PEG-DA particles overnight, and formulations with a higher AA content resulted in higher loading efficiency and slower release rates over 4 weeks, suggesting the presence of binding interactions between the positively charged IGF-1 and negatively charged particles containing AA. The released IGF-1 was tested in dorsal root ganglion (DRG) neurite outgrowth assay and found to retain its biological activity for up to two weeks after encapsulation. Furthermore, the trophic effect of IGF-1 was tested with stem cell-derived V2a interneurons and found to have a synergistic effect when combined with neurotrophin-3 (NT3). To assess the potential of a combinatorial approach, IGF-1-releasing MPs were encapsulated within a hyaluronic acid (HA) hydrogel and showed promise as a dual delivery system. Overall, the PEG-DA MPs developed herein deliver bioactive IGF-1 for a period of weeks and hold potential to enable axonal growth of injured neurons via sustained release.
Multiplatform lipid analysis of the brain of aging mice by mass spectrometry
Authors: Panda Punyatoya , Ferreira Christina R. , Cooper Bruce R. , Schaser Allison J. , Aryal Uma K. 
Published: September 2024

AbstractLipids are an integral part of brain structure and function and represent about 50% of the dry weight of the brain. Despite their importance, the complexity and variations in the abundance of brain lipids due to aging remain poorly understood. For maximum coverage and multi-platform validation, we applied three complementary mass spectrometry-based analytical approaches: multiple reaction monitoring (MRM) profiling, untargeted liquid chromatography tandem mass spectrometry (LC-MS/MS), and desorption electrospray ionization-MS imaging (DESI-MSI). We used three different age groups of mice, namely adult (3-4 months), middle-aged (10 months) and old (19-21 months). Phospholipids including phosphatidylcholine (PC), phosphatidylethanolamine (PE) and phosphatidylglycerol (PG) showed higher abundance, while phosphatidylinositols (PI) and phosphatidylserines (PS) generally showed lower abundance in the brains of old mice compared to adults or middle-aged mice. Polyunsaturated fatty acids, such as docosahexaenoic acid (DHA) and arachidonic acid (AA), as well as hexosylceramides (HexCer), sulfated hexosylceramides (SHexCer) and sphingomyelins (SM) were among the most abundant lipid species in the brains of old mice. DESI-MSI showed variations in the spatial distribution of many of the lipids confirmed by MRM and LC-MS/MS profiling. Interrogation of lipidomic data with recent proteomics data obtained from the same tissues revealed changes in the abundance and phosphorylation levels of several proteins potentially linked to ceramide (Cer), hexosylceramide (HexCer), fatty acids (FA), phosphatidylinositol (PI), sphingomyelin (SM) and sulfatides (SHexCer) metabolism and correlated well with the multiplatform lipid surveillance. Our findings offer insight into age-dependent changes in brain lipid profiles and their potential contribution to age-related cognitive decline.
Determination of Capsaicin content and pungency levels in Dalle Khursani accessions, a polyploidCapsicumspecies specific to Darjeeling-Sikkim Himalaya, India
Authors: Ghimiray Tulsi Saran , Majumdar Biswajit , Man Sourav 
Published: September 2024

ABSTRACTThe genus Capsicum includes more than 30 species, of which only five are cultivated. The pungency in chillies is primarily due to the accumulation of capsaicinoids such as capsaicin and dihydrocapsaicin, which varies significantly among species and varieties. Dalle Khursani, a unique landrace of Capsicum sp specific to the Darjeeling-Sikkim Himalaya in India, is highly valued for its pungency. However, very limited research exists on the variation of capsaicin content across different accessions of Dalle Khursani.The present study was undertaken to evaluate the capsaicin content and pungency levels of seven accessions collected from diverse altitudinal locations. High-Performance Liquid Chromatography (HPLC) was used to quantify capsaicin content.The concentration of capsaicin varied between 19.05 mg/g to 28.54 mg/g with the corresponding Scoville Heat Units (SHU) ranging from 304,863 to 456,636 revealing the presence of significant variations for pungency within the accessions of Dalle Khursani that may be attributed to genetic or environmental factors. Accessions DK-02 and DK-03 exhibited the highest capsaicin levels despite differing altitudinal growing environments. The results suggest a strong genetic influence on capsaicinoid content, with environmental factors playing a lesser role. For the first time, the capsaicin content and pungency levels in Dalle Khursani accessions are reported in this study.
Spontaneous brain activity and synaptic density in schizophrenia: a combined [11C]UCB-J PET and fMRI study
Authors: Shatalina Ekaterina , Onwordi Ellis Chika , Whitehurst Thomas , Whittington Alexander , Mansur Ayla , Arumuham Atheeshaan , Marques Tiago Reis , Gunn Roger N. , Natesan Sridhar , Rabiner Eugenii A. , Wall Matthew B. , Howes Oliver D 
Published: September 2024

AbstractSchizophrenia is associated with altered Amplitude of Low Frequency Fluctuations (ALFF), a functional Magnetic Resonance Imaging (fMRI) measure of spontaneous brain activity at rest. ALFF in healthy controls has been linked with presynaptic density levels measured by [11C]UCB-J positron emission tomography (PET). Given the growing body of evidence for low presynaptic density levels in schizophrenia, we set out to test if altered [11C]UCB-J binding may be associated with changes in ALFF in schizophrenia, and secondly to test whether the relationships between ALFF and [11C]UCB-J binding differ at the group level.Subjects with schizophrenia had higher ALFF in the medial prefrontal cortex and other regions, in line with published meta-analyses. In control subjects, there was a significant positive relationship between [11C]UCB-J distribution volume ratio (DVRcs) and ALFF in the medial prefrontal cortex (r=0.54, p=0.0365, n=16), but not in subjects with schizophrenia (r=–0.14, p=0.5564, n=22); r-coefficients significantly differed between groups (Zobserved=2.07, p=0.019). At the whole brain level, there were significant positive correlations between [11C]UCB-J DVRcs and ALFF in control subjects in the putamen, insular cortex, precentral gyrus and occipital regions, while in the schizophrenia group, there were significant positive correlations in the bilateral dorsolateral prefrontal cortex and negative correlations in the cuneus, parietal lobule and supramarginal gurus. Correlation coefficients were significantly different between groups across all cortical and subcortical regions with both higher and lower correlation coefficients in the control group.Our results suggest a link between spontaneous brain activity and presynaptic density in control subjects and that this relationship may be disrupted in schizophrenia patients, despite higher ALFF in this group, indicating altered neurobiological mechanisms. Widespread significant differences in ALFF-[11C]UCB-J DVRcs correlation coefficients between controls and schizophrenia subjects highlight the complexity of synaptic dysfunction in schizophrenia and underscore the need for further research to explore the underlying biological mechanisms.
Causality Mapping Using Resting-state fMRI Reveals Hyperactivity and Hypoconnectivity in Schizophrenia Patients
Authors: Tahir Alishba , Abdullah Wajiha , Azeem Wjeeh ul , Khalid Muhammad Farhan , Abualait Turki , Shakil Sadia , Ahmed Fayyaz , Bashir Shahid , Chaudhary Safee Ullah 
Published: September 2024

AbstractSchizophrenia (SZ) is a debilitating disorder in which patients exhibit psychotic behavior due to aberrant connectivity between different regions of the brain. Advances in neuroimaging have now enabled the diagnosis and analysis of SZ in order to elucidate the whole brain functional connectivity networks. In the present study, we have used resting-state functional magnetic resonance imaging (rs-fMRI) to elucidate the causal relationships amongst the differentially activated brain regions between SZ patients (n=10) and healthy controls (n=10). Vector auto-regression (VAR) model and Granger causality (GC) were then applied to construct a functional connectivity network and analyze the causal effects in SZ patients. Our results revealed that the average voxel activation in the frontal lobe (FL), basal ganglia (BG), and ventricular system (VS) was significantly higher in patients indicating hyper-activity as compared to controls. Conversely, cerebellum white matter (CBWM) showed higher activation in the controls as compared to patients. A higher Pearson correlation was observed between the controls as compared to patients while VAR and GC showed higher functional connectivity among all the regions of interest (ROIs) along with more causal relations in the controls. Finally, mediation analysis showed that right middle superior frontal gyrus acts as a strong partial mediator between left accumbens area and left middle superior frontal gyrus. Taken together, this study decodes the dysregulated brain activity in schizophrenia showing hyperactivation in patients when compared with the healthy controls which leads to alterations in neural connections resulting in hypoconnectivity.
Evolution under competition increases phytoplankton production by reducing the density-dependence of net energy fluxes and growth
Authors: Briddon Charlotte L. , Estevens Ricardo , Ghedini Giulia 
Published: September 2024

ABSTRACTCompetition can drive rapid evolution but forecasting how species evolve in communities remains difficult. Life history theory predicts that evolution in crowded environments should maximise population production, with intra- and inter-specific competition producing similar outcomes if species compete for similar resources. Despite its appeal, this prediction has rarely been tested in communities. To test its generality and identify its physiological basis, we experimentally evolved four species of marine phytoplankton (spanning three orders of magnitude in cell size) alone or together in a community for 4.5 months. We then quantified changes in their metabolism, demography, and competitive ability at two timepoints (∼60 and 120 generations) in common garden experiments. One species was outcompeted during the evolution experiment. For the other three, we found the same evolutionary outcome: species evolved greater biovolume production regardless of competition treatment but did so either by increasing max. population size or individual cell size. Biovolume production increased because of the differential evolution of photosynthesis and respiration under intense competition. These metabolic changes meant that intraspecific competition decreased and cells maintained higher rates of net energy production and growth as populations neared the stationary phase. Overall, these results show that intra- and inter-specific competition influence physiological and population parameters similarly in species that compete for essential resources. Life history theory thus provides a valuable base for predicting how species evolve in communities, and our results show how these predictions connect with the evolution of metabolism and competitive ability.
The representation of visual motion and landmark position aligns with heading direction in the zebrafish interpeduncular nucleus
Authors: Lavian Hagar , Prat Ot , Petrucco Luigi , Štih Vilim , Portugues Ruben 
Published: September 2024

AbstractSensory information is fundamental for navigation. Visual motion is used by animals to estimate their traveling distance and direction, and visual landmarks allow animals to tether their location and orientation to their environment. How such signals are integrated in the vertebrate brain is poorly understood. Here we investigate the representation of directional whole field visual motion and landmark position in a circuit in the larval zebrafish consisting of the habenula, interpeduncular nucleus (IPN) and anterior hindbrain (aHB). This circuit has been recently implicated in the representation of heading direction. Using calcium imaging we show that these stimuli are represented in the habenula, IPN and aHB. We further show that their representation in the IPN of both these stimuli is topographically arranged in a way that aligns itself with the representation of the heading signal in this region. We use neuronal ablations to show that the landmark responses, but not the whole field motion responses, require intact habenula input to the IPN. Overall our findings suggest the IPN as a site for integration of the heading signal from the aHB with visual information, shedding light on how different types of navigational signals are processed in the vertebrate brain.
Local Mean Suppression Filter for Effective Background Identification in Fluorescence Images
Authors: Kochetov Bogdan , Uttam Shikhar 
Published: September 2024

AbstractWe present an easy-to-use, nonlinear filter for effective background identification in fluorescence microscopy images with dense and low-contrast foreground. The pixel-wise filtering is based on comparison of the pixel intensity with the mean intensity of pixels in its local neighborhood. The pixel is given a background or foreground label depending on whether its intensity is less than or greater than the mean respectively. Multiple labels are generated for the same pixel by computing mean expression values by varying neighborhood size. These labels are accumulated to decide the final pixel label. We demonstrate that the performance of our filter favorably compares with state-of-the-art image processing, machine learning, and deep learning methods. We present three use cases that demonstrate its effectiveness, and also show how it can be used in multiplexed fluorescence imaging contexts and as a denoising step in image segmentation. A fast implementation of the filter is available in Python 3 onGitHub.
Foundry-fabricated dual-color nanophotonic neural probes for photostimulation and electrophysiological recording
Authors: Roszko David A. , Chen Fu-Der , Straguzzi John , Wahn Hannes , Xu Alec , McLaughlin Blaine , Yin Xinxin , Chua Hongyao , Luo Xianshu , Lo Guo-Qiang , Siegle Joshua H. , Poon Joyce K. S. , Sacher Wesley D. 
Published: September 2024

AbstractSignificanceCompact tools capable of delivering multicolor optogenetic stimulation to deep tissue targets with sufficient span, spatiotemporal resolution, and optical power remain challenging to realize. Here, we demonstrate foundry-fabricated nanophotonic neural probes for blue and red photostimulation and electrophysiological recording, which use a combination of spatial multiplexing and on-shank wavelength-demultiplexing to increase the number of on-shank emitters.AimWe demonstrate Si photonic neural probes with 26 photonic channels and 26 recording sites, which were fabricated on 200-mm diameter wafers at a commercial Si photonics foundry. Each photonic channel consists of an on-shank demultiplexer and separate grating coupler emitters for blue and red light, for a total of 52 emitters.ApproachWe evaluate neural probe functionality through bench measurements andin vivoexperiments by photostimulating through 16 of the available 26 emitter pairs.ResultsWe report neural probe electrode impedances, optical transmission, and beam profiles. We validated a packaged neural probe in optogenetic experiments with mice sensitive to blue or red photostimulation.ConclusionsOur foundry-fabricated nanophotonic neural probe demonstrates dense dual-color emitter integration on a single shank for targeted photostimulation. Given its two emission wavelengths, high emitter density, and long site span, this probe will facilitate experiments involving bidirectional circuit manipulations across both shallow and deep structures simultaneously.
Mixture Models for Dating with Confidence
Authors: Darlim Gustavo , Höhna Sebastian 
Published: September 2024

AbstractRobust estimation of divergence times is commonly performed using Bayesian inference with relaxed clock models. The specific choice of relaxed clock model and tree prior model can impact divergence time estimates, thus necessitating model selection among alternative models. The common approach is to select a model based on Bayes factors estimated via computational demanding approaches such as stepping stone sampling. Here we explore an alternative approach: mixture models that analytically integrate over all candidate models. Our mixture model approach only requires one Markov chain Monte Carlo analysis to both estimate the parameters of interest (e.g., the time-calibrated phylogeny) and to compute model posterior probabilities. We demonstrate the application of our mixture model approach using three relaxed clock models (uncorrelated exponential, uncorrelated lognormal and independent gamma rates) combined with three tree prior models (constant-rates pure birth process, constant-rate birth-death process and piecewise-constant birth-death process) and mitochondrial genome dataset of Crocodylia. We calibrate the phylogeny using well-defined fossil node calibrations. Our results show that Bayes factors estimated using stepping stone sampling are unreliable due to noise in repeated analyses while our analytical mixture model approach shows higher precision and robustness. Thus, divergence time estimates under our mixture model are comparably robust as previous relaxed clock approaches but model selection is significantly faster and avoids marginal likelihood estimation. Finally, our time-calibrated phylogeny of Crocodylia presents a robust benchmark for further studies in the group.
A Unified Theory of Response Sparsity and Variability for Energy-Efficient Neural Coding
Authors: Huang Mingyi , Lin Wei , Roe Anna Wang , Yu Yuguo 
Published: September 2024

AbstractUnderstanding how cortical neurons use dynamic firing patterns to represent sensory signals is a central challenge in neuroscience. Decades of research have shown that cortical neuronal activities exhibit high variance, typically quantified by the coefficient of variation (CV), suggesting intrinsic randomness. Conversely, substantial evidence indicates that cortical neurons display high response sparseness, indicative of efficient encoding. The apparent contradiction between these neural coding properties—stochastic yet efficient—has lacked a unified theoretical framework. This study aims to resolve this discrepancy. We conducted a series of analyses to establish a direct relational function between CV and sparseness, proving they are intrinsically correlated or equivalent across different statistical distributions in neural activities. We further derive a function showing that both irregularity and sparsity in neuronal activities are positive functions of energy-efficient coding capacity, quantified by Information-Cost Efficiency (ICE). This suggests that the observed high irregularity and sparsity in cortical activities result from a shared mechanism optimized for maximizing information encoding capacity while minimizing cost. Furthermore, we introduce a CV-maximization algorithm to generate kernel functions replicating the receptive fields of the primary visual cortex. This finding indicates that the neuronal functions in the visual cortex are optimal energy-efficient coding operators for natural images. Hence, this framework unifies the concepts of irregularity and sparsity in neuronal activities by linking them to a common mechanism of coding efficiency, offering deeper insights into neural coding strategies.