bluuebunny/crossref_metadata_2025_split huggingface dataset:
High-throughputin vivosynaptic connectivity mapping of neuronal micro-circuits using two-photon holographic optogenetics and compressive sensing
Authors: Chen I-Wen , Chan Chung Yuen , Navarro Phillip , de Sars Vincent , Ronzitti Emiliano , Oweiss Karim , Tanese Dimitrii , Emiliani Valentina 
Published: September 2023

SummaryUnderstanding the intricate synaptic connectivity in living neural circuits is crucial for unraveling the relationship between network structure and function, as well as its evolution during development, learning, and recovery from injury. However, current methodologies for identifying connected neuronsin vivosuffer from limitations, particularly with regards to their throughput. In this study, we introduce a groundbreaking framework forin vivoconnectivity mapping that combines two-photon holographic optogenetics for activating single or multiple potential presynaptic neurons, whole-cell recording of postsynaptic responses, and a compressive sensing strategy for efficiently retrieving individual postsynaptic neurons’ responses when multiple potential presynaptic neurons are simultaneously activated. The approach was validated in the layer 2/3 of the visual cortex in anesthetized mice, enabling rapid probing of up to 100 cells in approximately 5 minutes. By identifying tens of synaptic pairs, including their connection strength, kinetics, and spatial distribution, this method showcases its potential to significantly advance circuit reconstruction in large neuronal networks with minimal invasiveness. Moreover, through simultaneous multi-cell stimulation and compressive sensing, we demonstrate up to a three-fold reduction in the number of required measurements to infer connectivity with limited loss in accuracy, thereby enabling high-throughput connectivity mappingin vivo. These results pave the way for a more efficient and rapid investigation of neuronal circuits, leading to deeper insights into brain function and plasticity.
Invariant natural killer T-cell and CD4+T-cell derived IL22 is a regulator of epithelial-to-mesenchymal transition and extracellular matrix remodelling in perianal fistulas
Authors: Constable Laura E , Iqbal Nusrat , Cozzetto Domenico , Csabai Luca , Anandabaskaran Sulak , Korcsmaros Tamas , Hart Ailsa , Tozer Phillip J , Powell Nick 
Published: September 2023

AbstractBackground and aimsPerianal fistulization is a challenging phenotype of Crohn’s disease (CD). Unravelling the cytokine networks and cellular mediators driving tissue injury in perianal CD (pCD) will help inform much needed novel treatment strategies.MethodsThe phenotype of different T-cell subsets, including unconventional lineages, such as γδ T-cells, MAIT and iNKT-cells in fistula tract tissue and blood samples of patients with pCD or cryptoglandular perianal fistulas was determined using multiparameter flow cytometry. Transcriptomic profiling of fistula tract tissue was performed by RNA-sequencing.ResultsCD161+CD4+T-cells and CD161+CD4-CD8-iNKT-cells significantly accumulated in fistula tissue and produced interleukin-(IL)22 and IL13. Transcripts associated with epithelial-to-mesenchymal transition (EMT), extracellular matrix (ECM) remodelling, interferon-gamma, JAK-STAT and lymphocyte signalling were enriched in pCD, as well as inhibition of pathways associated with wound closure. IL22-responsive transcripts were significantly enriched in fistulas and network analysis identified IL22-mediated regulation of EMT, ECM and other inflammatory pathways.ConclusionThis study provides novel molecular and cellular insights into fistula pathogenesis, identifying IL22 producing lymphocytes as novel immune regulators of EMT and ECM dysregulation in perianal fistulas. Targeting the regulatory networks controlling IL22 producing lymphocytes may offer novel therapeutic strategies in pCD.
Beta bursts question the ruling power for brain-computer interfaces
Authors: Papadopoulos Sotirios , Szul Maciej J , Congedo Marco , Bonaiuto James J , Mattout Jérémie 
Published: September 2023

AbstractCurrent efforts to build reliable brain-computer interfaces (BCI) span multiple axes from hardware, to software, to more sophisticated experimental protocols, and personalized approaches. However, despite these abundant efforts, there is still room for significant improvement. We argue that a rather overlooked direction lies in linking BCI protocols with recent advances in fundamental neuroscience. In light of these advances, and particularly the characterization of the burst-like nature of beta frequency band activity and the diversity of beta bursts, we revisit the role of beta activity in “left vs. right hand” motor imagery tasks. Current decoding approaches for such tasks take advantage of the fact that motor imagery generates time-locked changes in induced power in the sensorimotor cortex, and rely on band-pass filtered power changes or covariance matrices which also describe co-varying power changes in signals recorded from different channels. Although little is known about the dynamics of beta burst activity during motor imagery, we hypothesized that beta bursts should be modulated in a way analogous to their activity during performance of real upper limb movements. We show that classification features based on patterns of beta burst modulations yield decoding results that are equivalent to or better than typically used beta power across multiple open electroencephalography datasets, thus providing insights into the specificity of these bio-markers.
Sub-second Dopamine Signals during Risky Decision-Making in Patients with Impulse Control Disorder
Authors: Liebenow Brittany , Wilson Thomas , Maas Benjamin , Aladnani Emily , Moran Rosalyn J. , White Jason , Lohrenz Terry , Haq Ihtsham ul , Siddiqui Mustafa S. , Laxton Adrian W. , Tatter Stephen B. , Montague P. Read , Kishida Kenneth T. 
Published: September 2023

AbstractBackgroundImpulse Control Disorder (ICD) in Parkinson’s disease is a behavioral addiction arising secondary to dopaminergic therapies, most often dopamine receptor agonists. Prior research implicates changes in striatal function and heightened dopaminergic activity in the dorsal striatum of patients with ICD. However, this prior work does not possess the temporal resolution required to investigate dopaminergic signaling during real-time progression through various stages of decision-making involving anticipation and feedback.MethodsWe recorded high-frequency (10Hz) measurements of extracellular dopamine in the striatum of patients with (N=3) and without (N=3) a history of ICD secondary to dopamine receptor agonist therapy for Parkinson’s disease symptoms. These measurements were made using carbon fiber microelectrodes during awake DBS neurosurgery and while participants performed a sequential decision-making task involving risky investment decisions and real monetary gains and losses. Per clinical standard-of-care, participants withheld all dopaminergic medications prior to the procedure.ResultsPatients with ICD invested significantly more money than patients without ICD. On each trial, patients with ICD made smaller adjustments to their investment levels compared to patients without ICD. In patients with ICD, dopamine levels rose or fell on sub-second timescales in anticipation of investment outcomes consistent with increased or decreased confidence in a positive outcome, respectively; dopamine levels in patients without ICD were significantly more stable during this phase. After outcome revelation, dopamine levels in patients with ICD rose significantly more than in inpatients without ICD for better-than-expected gains. For worse-than-expected losses, dopamine levels in patients with ICD remained level whereas dopamine levels in patients without ICD fell.ConclusionWe report significantly increased risky behavior and exacerbated phasic dopamine signaling, on sub-second timescales, anticipating and following the revelation of the outcomes of risky decisions in patients with ICD. Notably, these results were obtained when patients who had demonstrated ICD in the past but were, at the time of surgery, in an off-medication state. Thus, it is unclear whether observed signals reflect an inherent predisposition for ICD that was revealed when dopamine receptor agonists were introduced or whether these observations were caused by the introduction of dopamine receptor agonists and the patients having experienced ICD symptoms in the past. Regardless, future work investigating dopamine’s role in human cognition, behavior, and disease should consider the signals this system generates on sub-second timescales.
Learning to operate an imagined speech Brain-Computer Interface involves the spatial and frequency tuning of neural activity
Authors: Bhadra Kinkini , Giraud Anne Lise , Marchesotti Silvia 
Published: September 2023

AbstractBrain-Computer Interfaces (BCI) will revolutionize the way people with impaired speech production can communicate. While recent studies confirm the possibility of decoding imagined speech based on pre-recorded intracranial neurophysiological signals, current efforts focus on collecting vast amounts of data to train classifiers, rather than exploring how the individual’s brain adapts to improve BCI control, an important aspect given the known problem of “BCI illiteracy”, the inability of some individuals to operate a BCI. This issue can be investigated by providing real-time feedback to allow users to identify the best control strategy. In this study, we trained 15 healthy participants to operate a simple binary BCI system based on electroencephalography (EEG) signals through syllable imagery for five consecutive days. We explored whether BCI-control improves with training and characterized the underlying neural dynamics, both in terms of EEG power changes and of the neural features contributing to real-time classification. Despite considerable interindividual variability in performance and learning, a significant improvement in BCI control was observed from day 1 to 5. Performance improvement was associated with a global EEG power increase in frontal theta and a focal increase in temporal low-gamma, showing that learning to operate an imagined-speech BCI involves global and local dynamical changes involving low- and high-frequency neural features, respectively. These findings indicate that both machine and human learning must be considered to reach optimal controllability of imagined-speech BCI, and that non-invasive BCI-learning can help predict the individual benefit from an invasive speech BCI and guide both the electrode implantation and decoding strategies.
A brain circuit and neuronal mechanism for decoding and adapting to change in daylength
Authors: Maddaloni G , Chang YJ , Senft RA , Dymecki SM 
Published: September 2023

AbstractChanges in daylight amount (photoperiod) drive pronounced alterations in physiology and behaviour1,2. Adaptive responses to seasonal photoperiods are vital to all organisms – dysregulation is associated with disease, from affective disorders3to metabolic syndromes4. Circadian rhythm circuitry has been implicated5,6yet little is known about the precise neural and cellular substrates that underlie phase synchronization to photoperiod change. Here we present a previously unknown brain circuit and novel system of axon branch-specific and reversible neurotransmitter deployment that together prove critical for behavioural and sleep adaptation to photoperiod change. We found that the recently defined neuron type called mrEn1-Pet17located in the mouse brainstem Median Raphe Nucleus (MRN) segregates serotonin versus VGLUT3 (here proxy for the neurotransmitter glutamate) to different axonal branches innervating specific brain regions involved in circadian rhythm and sleep/wake timing8,9. We found that whether measured during the light or dark phase of the day this branch-specific neurotransmitter deployment in mrEn1-Pet1neurons was indistinguishable; however, it strikingly reorganizes on photoperiod change. Specifically, axonal boutons but not cell soma show a shift in neurochemical phenotype upon change away from equinox light/dark conditions that reverses upon return to equinox. When we genetically disabled the deployment of VGLUT3 in mrEn1-Pet1neurons, we found that sleep/wake periods and voluntary activity failed to synchronize to the new photoperiod or was significantly delayed. Combining intersectional rabies virus tracing and projection-specific neuronal silencingin vivo, we delineated a Preoptic Area-to-mrEn1Pet1connection responsible for decoding the photoperiodic inputs, driving the neurochemical shift and promoting behavioural synchronization. Our results reveal a previously unrecognized brain circuit along with a novel form of periodic, branch-specific neurotransmitter deployment that together regulate organismal adaptation to photoperiod changes.
Dynamic categorization rules alter representations in human visual cortex
Authors: Henderson Margaret M. , Serences John T. , Rungratsameetaweemana Nuttida 
Published: September 2023

AbstractEveryday perceptual tasks require sensory stimuli to be dynamically encoded and analyzed according to changing behavioral goals. For example, when searching for an apple at the supermarket, one might first find the Granny Smith apples by separating all visible apples into the categories “green” and “non-green”. However, suddenly remembering that your family actually likes Fuji apples would necessitate reconfiguring the boundary to separate “red” from “red-yellow” objects. This flexible processing enables identical sensory stimuli to elicit varied behaviors based on the current task context. While this phenomenon is ubiquitous in nature, little is known about the neural mechanisms that underlie such flexible computation. Traditionally, sensory regions have been viewed as mainly devoted to processing inputs, with limited involvement in adapting to varying task contexts. However, from the standpoint of efficient computation, it is plausible that sensory regions integrate inputs with current task goals, facilitating more effective information relay to higher-level cortical areas. Here we test this possibility by asking human participants to visually categorize novel shape stimuli based on different linear and non-linear boundaries. Using fMRI and multivariate analyses of retinotopically-defined visual areas, we found that shape representations in visual cortex became more distinct across relevant decision boundaries in a context-dependent manner, with the largest changes in discriminability observed for stimuli near the decision boundary. Importantly, these context-driven modulations were associated with improved categorization performance. Together, these findings demonstrate that codes in visual cortex are adaptively modulated to optimize object separability based on currently relevant decision boundaries.
Proteonano™: a novel deep proteomics platform with 1000-plex profiling capacity and picogram sensitivity and its application in diabetic kidney disease
Authors: Zhao Ban , Gao Xuechun , Ouyang Xiehua , Fang Jiakai , Deng Zihao , Wu Hao , Mao Yonghui 
Published: September 2023

ABSTRACTThe development of blood-based multi-biomarker panels for screening diabetic patients, and as an easy-to-access tool for identifying individuals at greatest risk of developing diabetic kidney disease (DKD) and its progression, is essential. However, conventional blood biomarker-based methodologies (e.g. clinical tests and ELISA) are unable to predict DKD progression with high sensitivity and specificity. To overcome these challenges, we developed a deep, untargeted plasma proteome profiling technology (Proteonano™ platform) to identify potential multiple protein biomarkers involved in DKD progression. The Proteonano™ technology is an affinity selective mass spectrometric platform that comprises nanoparticle-based affinity binders (nanobinders) for low abundant protein enrichment, automated workflow for parallel sample preparation, and machine learning empowered bioinformatic software for data analysis.Using the Proteonano™ platform, we performed untargeted proteomics on 75 subjects (DKD progressors, n = 30; DKD non-progressors, n = 45) and identified an average of 953 ± 80 (AVG ± SD) protein groups, with a wide dynamic range of 8 orders of magnitude (with the lowest concentration down to 3.00 pg/mL). Among these, 38 proteins were differentially expressed between DKD progressors relative to non-progressors, and the predictive power for these proteins were assessed. Further, we performed random forest and LASSO analyses for additional variable selection. Variables selected by these approaches were assessed by Akaike information criterion method followed by ROC analysis, which identified a combination of multiple proteins (including VWF, PTGDS, B2M, BT3A2, and LCAT) that showed excellent predictive power over current methods, with an area under the curve value up to 0.97. Some of these plasma proteins are not previously recognized in the context of DKD progression, suggesting they are novel biomarkers. Our studies pave the way to develop multi-biomarker panels for DKD progression management. This study suggests that the Proteonano™ technology platform reported here can be employed as an established workflow enabling untargeted deep proteomic analysis to identify highly discriminative biomarkers for precise medicine.
Inhibiting Stromal Class I HDACs Curbs Pancreatic Cancer Progression
Authors: Liang Gaoyang , Oh Tae Gyu , Hah Nasun , Tiriac Hervé , Shi Yu , Truitt Morgan L. , Antal Corina E. , Atkins Annette R. , Li Yuwenbin , Fraser Cory , Ng Serina , Pinto Antonio F. M. , Nelson Dylan C. , Estepa Gabriela , Bashi Senada , Banayo Ester , Dai Yang , Liddle Christopher , Yu Ruth T. , Hunter Tony , Engle Dannielle D. , Han Haiyong , Von Hoff Daniel D. , Downes Michael , Evans Ronald M. 
Published: September 2023

ABSTRACTOncogenic lesions in pancreatic ductal adenocarcinoma (PDAC) hijack the epigenetic machinery in stromal components to establish a desmoplastic and therapeutic resistant tumor microenvironment (TME). Here we identify Class I histone deacetylases (HDACs) as key epigenetic factors facilitating the induction of pro-desmoplastic and pro-tumorigenic transcriptional programs in pancreatic stromal fibroblasts. Mechanistically, HDAC-mediated changes in chromatin architecture enable the activation of pro-desmoplastic programs directed by serum response factor (SRF) and forkhead box M1 (FOXM1). HDACs also coordinate fibroblast pro-inflammatory programs inducing leukemia inhibitory factor (LIF) expression, supporting paracrine pro-tumorigenic crosstalk. HDAC depletion in cancer-associated fibroblasts (CAFs) and treatment with the HDAC inhibitor entinostat (Ent) in PDAC mouse models reduce stromal activation and curb tumor progression. Notably, HDAC inhibition (HDACi) enriches a lipogenic fibroblast subpopulation, a potential precursor for myofibroblasts in the PDAC stroma. Overall, our study reveals the stromal targeting potential of HDACi, highlighting the utility of this epigenetic modulating approach in PDAC therapeutics.
Evolving alterations of structural organization and functional connectivity in feedforward neural networks after induced P301L tau mutation
Authors: Weir Janelle S. , Hanssen Katrine Sjaastad , Winter-Hjelm Nicolai , Sandvig Axel , Sandvig Ioanna 
Published: September 2023

AbstractReciprocal structure–function relationships underlie both healthy and pathological behaviors in complex neural networks. Thus, understanding neuropathology and network dysfunction requires a thorough investigation of the complex interactions between structural and functional network reconfigurations in response to perturbation. Such adaptations are often difficult to studyin vivo. For example, subtle, evolving changes in synaptic connectivity, transmission, and the electrophysiological shift from healthy to pathological states, as for example alterations that may be associated with evolving neurodegenerative disease, such as Alzheimeŕs, are difficult to study in the brain. Engineeredin vitroneural networks are powerful models that enable selective targeting, manipulation, and monitoring of dynamic neural network behavior at the micro- and mesoscale in physiological and pathological conditions. In this study, we engineered feedforward cortical neural networks using two-nodal microfluidic devices with controllable connectivity interfaced with microelectrode arrays (mMEAs). We induced P301L mutated tau protein to the presynaptic node of these networks and monitored network dynamics over three weeks. Induced perturbation resulted in altered structural organization and extensive axonal retraction starting in the perturbed node. Perturbed networks also exhibited functional changes in intranodal activity, which manifested as an overall decline in both firing rate and bursting activity, with a progressive increase in synchrony over time, and decrease in internodal signal propagation between pre- and postsynaptic nodes. These results provide insights into dynamic structural and functional reconfigurations at the micro- and mesoscale as a result of evolving pathology and illustrate the utility of engineered networks as models of network function and dysfunction.
High-resolution double vision of the archetypal protein tyrosine phosphatase
Authors: Sharma Shivani , Mehlman Tamar (Skaist) , Sagabala Reddy Sudheer , Boivin Benoit , Keedy Daniel A. 
Published: September 2023

AbstractProtein tyrosine phosphatase 1B (PTP1B) plays important roles in cellular homeostasis and is a highly validated therapeutic target for multiple human ailments including diabetes, obesity, and breast cancer. However, much remains to be learned about how conformational changes may convey information through the structure of PTP1B to enable allosteric regulation by ligands or functional responses to mutations. High-resolution X-ray crystallography can offer unique windows into protein conformational ensembles, but comparison of even high-resolution structures is often complicated by differences between datasets including non-isomorphism. Here we present the highest-resolution crystal structure of apo wildtype (WT) PTP1B to date, out of ∼350 total PTP1B structures in the PDB. Our structure is in a crystal form that is rare for PTP1B, with two unique copies of the protein that exhibit distinct patterns of conformational heterogeneity, allowing a controlled comparison of local disorder across the two chains within the same asymmetric unit. We interrogate the conformational differences between these chains in our apo structure, and between several recently reported high-resolution ligand-bound structures. We also examine electron density maps in a high-resolution structure of a recently reported activating double mutant, and discover unmodeled alternate conformations in the mutant structure that coincide with regions of enhanced conformational heterogeneity in our new WT structure. Our results validate the notion that these mutations operate by enhancing local dynamics, and suggest a latent susceptibility to such changes in the WT enzyme. Together, our new data and analysis provide a freshly detailed view of the conformational ensemble of PTP1B, and highlight the utility of high-resolution crystallography for elucidating conformational heterogeneity with potential relevance for function.