bluuebunny/crossref_metadata_2025_split huggingface dataset:
How short peptides can disassemble ultra-stable tau fibrils extracted from Alzheimer’s disease brain by a strain-relief mechanism
Authors: Hou Ke , Ge Peng , Sawaya Michael R. , Dolinsky Joshua L. , Yang Yuan , Jiang Yi Xiao , Lutter Liisa , Boyer David R. , Cheng Xinyi , Pi Justin , Zhang Jeffrey , Lu Jiahui , Yang Shixin , Yu Zhiheng , Feigon Juli , Eisenberg David S. 
Published: March 2024

AbstractReducing fibrous aggregates of protein tau is a possible strategy for halting progression of Alzheimer’s disease (AD). Previously we found thatin vitrothe D-peptide D-TLKIVWC disassembles tau fibrils from AD brains (AD-tau) into benign segments with no energy source present beyond ambient thermal agitation. This disassembly by a short peptide was unexpected, given that AD-tau is sufficiently stable to withstand disassembly in boiling SDS detergent. To consider D peptide-mediated disassembly as a potential therapeutic for AD, it is essential to understand the mechanism and energy source of the disassembly action. We find assembly of D-peptides into amyloid-like fibrils is essential for tau fibril disassembly. Cryo-EM and atomic force microscopy reveal that these D-peptide fibrils have a right-handed twist and embrace tau fibrils which have a left-handed twist. In binding to the AD-tau fibril, the oppositely twisted D-peptide fibril produces a strain, which is relieved by disassembly of both fibrils. This strain-relief mechanism appears to operate in other examples of amyloid fibril disassembly and provides a new direction for the development of first-in-class therapeutics for amyloid diseases.
AdjuSST: An Adjustable Surface Stiffness Treadmill
Authors: Price Mark , Locurto Dominic , Abdikadirova Banu , Huber Meghan E. , Hoogkamer Wouter 
Published: March 2024

AbstractHumans have the remarkable ability to manage foot-ground interaction seamlessly across terrain changes despite the high dynamic complexity of the task. Understanding how adaptation in the neuromotor system enables this level of robustness in the face of changing interaction dynamics is critical for developing more effective gait retraining interventions. We developed an adjustable surface stiffness treadmill (AdjuSST) to trigger these adaptation mechanisms and enable studies to better understand human adaptation to changing foot-ground dynamics. The AdjuSST system makes use of fundamental beam-bending principles; it controls surface stiffness by controlling the effective length of a cantilever beam. The beam acts as a spring suspension for the transverse endpoint load applied through the treadmill. The system is capable of enforcing a stiffness range of 15-300kN/m within 340 ms, deflecting linearly downwards up to 10 cm, and comfortably accommodating two full steps of travel along the belt. AdjuSST offers significant enhancements in effective walking surface length compared to similar systems, while also maintaining a useful stiffness range and responsive spring suspension. These improvements enhance our ability to study locomotor control and adaptation to changes in surface stiffness, as well as provide new avenues for gait rehabilitation.
Development of AI-assisted microscopy frameworks through realistic simulation in pySTED
Authors: Bilodeau Anthony , Michaud-Gagnon Albert , Chabbert Julia , Turcotte Benoit , Heine Jörn , Durand Audrey , Lavoie-Cardinal Flavie 
Published: March 2024

AbstractThe integration of artificial intelligence (AI) into microscopy systems significantly enhances performance, optimizing both the image acquisition and analysis phases. Development of AI-assisted super-resolution microscopy is often limited by the access to large biological datasets, as well as by the difficulties to benchmark and compare approaches on heterogeneous samples. We demonstrate the benefits of a realistic STED simulation platform,pySTED, for the development and deployment of AI-strategies for super-resolution microscopy. The simulation environment provided bypySTEDallows the augmentation of data for the training of deep neural networks, the development of online optimization strategies, and the training of reinforcement learning models, that can be deployed successfully on a real microscope.
COCONUT: An analysis of coiled-coil regions in proteins
Authors: Soni Neelesh , Madhusudhan M. S. 
Published: March 2024

AbstractMotivationThe molecular rules determine the strength and orientation (parallel or antiparallel) of interacting coiled-coil helices in protein-protein interactions. Interpreting these rules is crucial for identifying novel protein-protein interactions, designing competitive binders, and constructing large assemblies containing coiled-coil domains. This study establishes the molecular principles that dictate the strength and orientation of coiled-coil interactions, providing insights relevant to these applications.ResultsWe examined how hydrophobic contacts determine structural specificity within coiled-coil dimers. Our analysis revealed that the hydrophobic core densities differ between parallel and antiparallel dimer confirmations, highlighting their importance in stabilizing different structural arrangements. We developedCOiled-COil aNalysisUTility (COCONUT), a computational platform with machine learning models, validated for predictive capabilities in various applications. Using COCONUT’s pipeline for coiled-coil analysis and modeling, we predicted the orientation of substitution-sensitive coiled-coil dimer, identified residue pairings in non-canonical coiled-coil heterodimer, and constructedn-strandedcoiled-coil model. These results demonstrate COCONUT’s utility as a computational framework for interpreting and modeling coiled-coil structures.Availability and implementationCOCONUT is an open-source and free Python package available herehttps://github.com/neeleshsoni21/COCONUT. The documentation is available in the source code and here:https://neeleshsoni21.github.io/COCONUT/
Essential Dynamics of CB1Receptor-Agonist Complexes: Implications for Signalling Bias
Authors: Fellner Daniel M. J. , Glass Michelle , Furkert Daniel P. 
Published: March 2024

AbstractThe CB1cannabinoid receptor is implicated in a broad range of physiological processes and disease states, however CB1-targeting drugs in clinical use remain based on tetrahydrocannabinol (THC). Ligands that exhibit functional selectivity for different intracellular signalling pathways are currently an area of rapid development, and hold significant potential as therapeutic agents. Improved understanding of the exact molecular mechanisms underpinning biased activation of intracellular effector proteins for CB1is necessary to enable drug development of biased CB1ligands into candidates for treatment of human disease. Using molecular dynamics, this study shows that CB1conformations resulting from activation by the orthosteric ligands CP55940, Δ9-THC or 5F-MDMB-PICA exhibit differences in the dynamic organisation of key residues and receptor substructures involved in coupling to G proteins and β-arrestins, that leads to selective activation of downstream signalling pathways. The identification of conformationally distinct CB1-agonist complexes that demonstrate different functional profiles provides an important step in unravelling the molecular determinants for biased signalling, and lays a platform for future rational design of novel therapeutic leads.
Unravelling the glycome in human intervertebral disc degeneration: Aberrant glycosylation modulates inflammation and metabolism
Authors: Joyce Kieran , Scheper Aert F. , Phyo Aung Myat , O’Flaherty Roisin , Drake Richard , Devitt Aiden , Marchetti-Deschmann Martina , Saldova Radka , Pandit Abhay 
Published: March 2024

AbstractIntervertebral disc (IVD) degeneration is one of the major contributing causes of low back pain (LBP), a common health issue that imposes a significant socio-economic burden on society. Previous work has demonstrated a dysregulated glycome in animal models of IVD degeneration; however, the role of glycosylation in pathogenesis is unknown. The objective of this study was to characterise altered glycan expression in IVD degeneration and elucidate the functional role of this response. Glycans in human healthy (n=6) and degenerated IVD (n=6) were examined through UPLC-MS and MALDI-IMS. These findings were correlated with proteomic analysis by LC-MS and functionalin vitrostudies using RNA sequencing. IVD degeneration was associated with a hypersialylatedN-glycome, predominantly α-2,6 linked sialic acid. Confirming hypersialylation, we investigated sialylation’s functional role through mechanistic studies using a sialylation inhibitor (3Fax-peracetyl Neu5Ac). Sialylation inhibitionin vitromodulated inflammatory and metabolic pathways, demonstrating a functional role for glycosylation in IVD degeneration.Brief summaryIVD degeneration is associated with altered glycosylation, a potential target for new therapies.
The homeobox transcription factor Cux1 coordinates postnatal epithelial developmental timing but is dispensable for lung organogenesis and regeneration
Authors: Zhao Barbara , Socha Jacob , Toth Andrea , Fernandes Sharlene , Warheit-Niemi Helen , Ruff Brandy , Khurana Hershey Gurgit K , VanDussen Kelli , Swarr Daniel , Zacharias William J. 
Published: March 2024

AbstractLung epithelial progenitors use a complex network of known and predicted transcriptional regulators to influence early lung development. Here, we evaluate the function of one predicted regulator, Cux1, that we identified from transcriptional regulatory analysis of the SOX9+distal lung progenitor network. We generated a new Cux1-floxed mouse model and created an epithelial-specific knockout of Cux1 using Shh-Cre (Cux1ShhCre-LOF). Postnatal Cux1ShhCre-LOFanimals recapitulate key skin phenotypic features found in prior constitutive Cux1 knockout animals, confirming functionality of the new floxed model. Postnatal Cux1ShhCre-LOFmice displayed subtle alveolar simplification and a transient delay in alveologenesis without persistent lung phenotypes or alterations in lung epithelial cell allocation. Cux1ShhCre-LOFmice developed failure to thrive in their second and third weeks of life due to delayed ileal maturation, which similarly resolves by postnatal day 35. Finally, we challenged Cux1ShhCre-LOFwith influenza-mediated lung injury to demonstrate that Cux1ShhCre-LOFmice undergo productive alveolar regeneration that is indistinguishable from WT animals. Together, these findings indicate that epithelial-specific loss of Cux1 leads to transient developmental delays in the skin, lung, and intestine without defects in definitive organogenesis.One-Sentence SummaryDeletion of key DNA binding domains leads to loss of Cux1 function in the lung, intestine, and skin characterized by transient failure to thrive without significant adult disease.
Effects of early life adversity and adolescent basolateral amygdala activity on corticolimbic connectivity and anxiety behaviors
Authors: Cody Caitlyn R. , Artur de la Villarmois Emilce , Miguelez Fernandez Anabel , Lardizabal Janelle , McKnight Chaney , Tseng Kuei , Brenhouse Heather C. 
Published: March 2024

AbstractEarly postnatal development of corticolimbic circuitry is shaped by the environment and is vulnerable to early life challenges. Prior work has shown that early life adversity (ELA) leads to hyperinnervation of glutamatergic basolateral amygdala (BLA) projections to the prefrontal cortex (PFC) in adolescence. While hyperinnervation is associated with later-life anxiety behaviors, the physiological changes underpinning corticolimbic and behavioral impacts of ELA are not understood. We tested whether postsynaptic BLA-driven PFC activity is enhanced in ELA-exposed animals, using the maternal separation (MS) model of ELA. PFC local-field potential following BLA stimulation was facilitated in MS-exposed adolescents. Since ELA increases activity of the early-developing BLA, while the PFC exhibits protracted development, we further examined impacts of glutamatergic BLA activity during early adolescence on later-life PFC innervation and heightened anxiety. In early adolescence, MS-exposed animals exhibited decreased anxiety-like behavior, and acute adolescent BLA inhibition induced behaviors that resembled those of MS animals. To examine long-lasting impacts of adolescent BLA activity on innervation, BLA-originating axonal boutons in the PFC were quantified in late adolescence after early adolescent BLA inhibition. We further tested whether late adolescent BLA-PFC changes were associated with anxious reactivity expressed as heightened acoustic startle responses. MS rearing increased BLA-PFC innervation and threat reactivity in late adolescence, however early adolescent BLA inhibition was insufficient to prevent MS effects, suggesting that earlier BLA activity or post-synaptic receptor rearrangement in the PFC drives altered innervation. Taken together, these findings highlight both pre- and postsynaptic changes in the adolescent BLA-PFC circuit following ELA.
Mapping the genomic landscape of peach and almond with PrunusMap
Authors: Ksouri Najla , Moreno María Ángeles , Contreras-Moreira Bruno , Gogorcena Yolanda 
Published: March 2024

AbstractHigh throughput sequencing is accelerating plant breeding. Genotyping, quantitative trait locus or genome-wide association analyses are essential to locate alleles of interest in germplasm collections. These applications require accurately mapping nucleotide markers within growing collections of reference genome sequences. PrunusMap (https://prunusmap.eead.csic.es) is a user-friendly Web application designed to facilitate these tasks toPrunusbreeders. It efficiently aligns markers and locates SNPs on peach and almond genomes, providing lists of nearby genes and curated proteins. It can align all markers from a genetic map in one step, producing their physical positions. By searching multiple maps, it can also solve the problem of finding equivalent gene identifiers across different annotations. Three intuitive tools, “Find markers”, “Align sequences” and “Locate by position”, are available to accelerate mapping analyses, particularly for users with limited bioinformatics expertise. New genomes, annotations or marker sets will be added based on their interest to the community.
Exploring dynamic brain oscillations in motor imagery and low-frequency sound
Authors: Dupont W. , Poulin-Charronnat B. , Madden-Lombardi C. , Jacquet T. , Pfister P. , Dos Anjos T. , Lebon F. 
Published: March 2024

AbstractWhile both motor imagery (MI) and low-frequency sound listening have independently demonstrated the ability to modulate brain activity, there remains an unexplored frontier regarding the potential synergistic effects that may arise from their combined application. Any further modulation derived from this combination may be relevant for motor learning and/or rehabilitation. We conducted an experiment probing the electrophysiological activity of brain during these processes. By means of EEG, we recorded alpha and beta band power amplitude, which serve as markers of brain activity. Twenty volunteers were instructed to i) explicitly imagine finger flexion/extension movements in a kinaesthetic modality, ii) listen to low-frequency sounds, iii) imagine finger flexion while listening to low-frequency sounds, and iv) stay at rest. We observed a bimodal distribution, suggesting the presence of variability in brain activity across participants during both MI and low-frequency sound listening. One group of participants (12 individuals) displayed increased alpha power within contralateral sensorimotor and ipsilateral medial parieto-occipital regions during MI. Another group (8 individuals) exhibited a decrease in alpha and beta band power within sensorimotor areas. Interestingly, low-frequency sound listening elicited a similar pattern of brain activity within both groups. Surprisingly, the combination of MI and sound listening did not result in additional changes in alpha and beta power amplitudes compared to these processes in isolation, regardless of group. Altogether, these findings shed significant insight into the brain activity and its variability generated during MI and low-frequency sound listening. Nevertheless, it appears that the simultaneous engagement of MI and low-frequency sound listening could not further modulate alpha power amplitude, possibly due to concurrent cortical activations. This prompts us to inquire whether administering these interventions sequentially could uncover any additional modulation.
Multitasking practice eliminates modality-based interference by separating task representations in sensory brain regions
Authors: Mueckstein Marie , Görgen Kai , Heinzel Stephan , Granacher Urs , Rapp Michael A. , Stelzel Christine 
Published: March 2024

AbstractThe debate on the neural basis of multitasking costs evolves around neural overlap between concurrently performed tasks. Recent evidence suggests that training-related reductions in representational overlap in fronto-parietal brain regions predict multitasking improvements. Cognitive theories assume that overlap of task representations may lead to unintended information exchange between tasks (i.e., crosstalk). Modality-based crosstalk was suggested as a source for multitasking costs in multisensory settings. Robust findings of increased costs for certain modality mappings may be explained by crosstalk between the stimulus modality in one task and sensory action consequences in the concurrently performed task. Whether modality-based crosstalk emerges from representational overlap in general fronto-parietal multitasking regions or modality-specific regions is not known yet. In this functional neuroimaging study, we investigate neural overlap in multitasking performance, focusing on modality compatibility by employing multivariate pattern analysis and modality-specific practice interventions in three groups (total N = 54). We observed significant differences between modality compatible and modality incompatible single-task representations, specifically in the auditory cortex but not in fronto-parietal regions. Notably, improved auditory decoding accuracy related to modality incompatible tasks was predictive of performance gains in the corresponding dual task along with complete elimination of modality-specific dual-task costs. This predictive relationship was evident only in the group practicing modality incompatible mappings, suggesting that specific practice on task sets with modality overlap influenced both neural representations and subsequent multitasking performance. This study contributes to the integration of cognitive theory and neuroscience and the role of task representations in dual-task interference.SignificanceIn a society dominated by multitasking, understanding its neurocognitive basis and plasticity is crucial for key aspects of work-related and everyday tasks. We investigate the neural mechanisms behind multitasking limitations, offering insights for targeted cognitive interventions. The study builds upon established theories of cognitive multitasking and imaging research, addressing the concept of modality-based crosstalk - the unintended exchange of modality-based information between tasks. Through functional brain imaging and pattern analysis, we examined how neural task representations contribute to performance costs in dual tasks with varying degrees of modality overlap. Notably, our findings demonstrate a practice-related decrease in neural overlap which is associated with substantial multitasking improvements, specifically in the auditory cortex, emphasizing the contribution of sensory regions to flexible multidimensional task representations.
HIPI: Spatially Resolved Multiplexed Protein Expression Inferred from H&E WSIs
Authors: Zeira Ron , Anavy Leon , Yakhini Zohar , Rivlin Ehud , Freedman Daniel 
Published: March 2024

AbstractSolid tumors are characterized by complex interactions between the tumor, the immune system and the microenvironment. These interactions and intra-tumor variations have both diagnostic and prognostic significance and implications. However, quantifying the underlying processes in patient samples requires expensive and complicated molecular experiments. In contrast, H&E staining is typically performed as part of the routine standard process, and is very cheap. Here we present HIPI (H&E Image Interpretation and Protein Expression Inference) for predicting cell marker expression from tumor H&E images. We process paired H&E and CyCIF images taken from serial sections of colorectal cancers to train our model. We show that our model accurately predicts the spatial distribution of several important cell markers, on both held-out tumor regions as well as new tumor samples taken from different patients. Moreover, using only the tissue image morphology, HIPI is able to colocalize the interactions between different cell types, further demonstrating its potential clinical significance.
Micron-resolution fiber mapping in histology independent of sample preparation
Authors: Georgiadis Marios , auf der Heiden Franca , Abbasi Hamed , Ettema Loes , Nirschl Jeffrey , Moein Taghavi Hossein , Wakatsuki Moe , Liu Andy , Ho William Hai Dang , Carlson Mackenzie , Doukas Michail , Koppes Sjors A. , Keereweer Stijn , Sobel Raymond A. , Setsompop Kawin , Liao Congyu , Amunts Katrin , Axer Markus , Zeineh Michael , Menzel Miriam 
Published: March 2024

AbstractDetailed knowledge of the brain’s nerve fiber network is crucial for understanding its function in health and disease. However, mapping fibers with high resolution remains prohibitive in most histological sections because state-of-the-art techniques are incompatible with their preparation. Here, we present a micron-resolution light-scattering-based technique that reveals intricate fiber networks independent of sample preparation for extended fields of view. We uncover fiber structures in both label-free and stained, paraffin-embedded and deparaffinized, newly-prepared and archived, animal and human brain tissues – including whole-brain sections from the BigBrain atlas. We identify altered microstructures in demyelination and hippocampal neurodegeneration, and show key advantages over diffusion magnetic resonance imaging, polarization microscopy, and structure tensor analysis. We also reveal structures in non-brain tissues – including muscle, bone, and blood vessels. Our cost-effective, versatile technique enables studies of intricate fiber networks in any type of histological tissue section, offering a new dimension to neuroscientific and biomedical research.
Baselining the Buzz Trastuzumab-HER2 Affinity, and Beyond
Authors: Chinery Lewis , Hummer Alissa M. , Mehta Brij Bhushan , Akbar Rahmad , Rawat Puneet , Slabodkin Andrei , Quy Khang Le , Lund-Johansen Fridtjof , Greiff Victor , Jeliazkov Jeliazko R. , Deane Charlotte M. 
Published: March 2024

1AbstractThere is currently considerable interest in the field ofde novoantibody design, and deep learning techniques are now regularly applied to optimise antibody properties such as binding affinity. However, robust baselines within this field have not kept up with recent developments.In this study, we generate a dataset of over 524,000 Trastuzumab variants and use this to show that standard computational methods such as BLOSUM, AbLang, ESM, and Protein-MPNN can be used to design diverse antibody libraries from just a single starting sequence. These novel libraries are predicted to be enriched in binding variants and experimental validation of 700 of these designs is ongoing. We also demonstrate that, even with only a very small number of experimental data points, simple machine learning classifiers can be trained in seconds to accurately pre-screen future designs. This pre-screening maintains library diversity and saves experimental time and money.