bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding multiple sclerosis as a disease spectrum: above and below the clinical threshold
Authors: Krieger Stephen , Cook Karin , Hersh Carrie M. 
Published: March 2024

Purpose of review
Research in multiple sclerosis (MS) has long been predicated on clinical groupings that do not reflect the underlying biologic heterogeneity apparent within patient populations. This review explicates the various levels of explanation through which the spectrum of disease is described and investigated both above and below the clinical threshold of detection, as framed by the topographical model of MS, to help advance a cogent mechanistic framework.

Recent findings
Contemporary evidence has amended the view of MS as consisting of sequential disease phases in favor of a spectrum of disease with an admixture of interdependent and dynamic pathobiological axes driving tissue injury and progression. Recent studies have shown the presence of acute and compartmentalized inflammation and mechanisms of neurodegeneration beginning early and evolving throughout the disease continuum. Still, the gap between the understanding of immunopathologic processes in MS and the tools used to measure relevant molecular, laboratory, radiologic, and clinical metrics needs attention to enable better prognostication of disease and monitoring for changes along specific pathologic axes and variable treatment outcomes.

Summary
Aligning on a consistently-applied mechanistic framework at distinct levels of explanation will enable greater precision across bench and clinical research, and inform discourse on drivers of disability progression and delivery of care for individuals with MS.
Bruton tyrosine kinase inhibitors in multiple sclerosis: evidence and expectations
Authors: Krämer Julia , Wiendl Heinz 
Published: March 2024

Purpose of review
Despite availability of high-efficacy therapies for multiple sclerosis (MS), many patients experience significant disability worsening due to limited effects of currently available drugs on central nervous system (CNS)-compartmentalized inflammation. Bruton tyrosine kinase (BTK) is an intracellular signaling molecule involved in regulation of maturation, survival, migration, and activation of B cells and microglia, which are central players in the immunopathogenesis of progressive MS. Therefore, CNS-penetrant BTK inhibitors may better prevent disease progression by targeting immune cells on both sides of the blood–brain barrier. This review gives an overview on the preliminary results of clinical trials.

Recent findings
Currently, the efficacy and safety of six BTK inhibitors are being evaluated in clinical trials in patients with relapsing and progressive MS. Evobrutinib, tolebrutinib and fenebrutinib have shown efficacy and safety in relapsing MS in phase 2 studies, and evobrutinib and tolebrutinib in their extension studies up to 3–5 years. However, evobrutinib failed to distinguish itself from the comparator drug teriflunomide in reduction of relapse rate (primary end point) in two phase 3 studies in relapsing MS.

Summary
Inhibition of BTK has emerged as a promising therapeutic approach to target the CNS-compartmentalized inflammation. Results from phase 3 clinical trials will shed light on differences in efficacy and safety of BTK inhibitors and its potential role in the future MS landscape.
Structural identifiability analysis of linear reaction–advection–diffusion processes in mathematical biology
Authors: Browning Alexander P. , Taşcă Maria , Falcó Carles , Baker Ruth E. 
Published: March 2024

Effective application of mathematical models to interpret biological data and make accurate predictions often requires that model parameters are identifiable. Approaches to assess the so-called structural identifiability of models are well established for ordinary differential equation models, yet there are no commonly adopted approaches that can be applied to assess the structural identifiability of the partial differential equation (PDE) models that are requisite to capture spatial features inherent to many phenomena. The differential algebra approach to structural identifiability has recently been demonstrated to be applicable to several specific PDE models. In this brief article, we present general methodology for performing structural identifiability analysis on partially observed reaction–advection–diffusion PDE models that are linear in the unobserved quantities. We show that the differential algebra approach can always, in theory, be applied to such models. Moreover, despite the perceived complexity introduced by the addition of advection and diffusion terms, consideration of spatial analogues of non-spatial models cannot exacerbate structural identifiability. We conclude by discussing future possibilities and the computational cost of performing structural identifiability analysis on more general PDE models.
Pseudomonas hefeiensis sp. nov., isolated from the rhizosphere of multiple cash crops in China
Authors: Liao Kaiji , Li Qiang , Li Jun-Zhou , Wei Hai-Lei 
Published: March 2024

Three bacterial strains, FP250T, FP821, and FP53, were isolated from the rhizosphere soil of oilseed rape, licorice, and habanero pepper in Anhui Province, Xinjiang Uygur Autonomous Region, and Jiangsu Province, PR China, respectively. All strains were shown to grow at 4–37 °C and pH 6.0–9.0, and in the presence of 0–4.0 % (w/v) NaCl. Phylogenetic analyses based on 16S rRNA gene sequences or housekeeping genes (16S rRNA, gyrB, rpoB, and rpoD) and phylogenomic analysis showed that strains FP250T, FP821, and FP53 belong to the genus Pseudomonas, and are closely related to Pseudomonas kilonensis DSM 13647T, Pseudomonas brassicacearum JCM 11938T, Pseudomonas viciae 11K1T, and Pseudomonas thivervalensis DSM 13194T. The DNA G+C content of strain FP205T was 59.8 mol%. The average nucleotide identity and digital DNA–DNA hybridization values of strain FP205T with the most closely related strain were 93.2 % and 51.4 %, respectively, which is well below the threshold for species differentiation. Strain FP205T contained summed feature 3 (C16 : 1
ω6c and/or C16 : 1
ω7c), summed feature 8 (C18 : 1
ω7c and/or C18 : 1
ω6c) as major fatty acids, and diphosphatidylglycerol along with phosphatidylethanolamine and aminophospholipid as major polar lipids. The predominant isoprenoid quinone was ubiquinone-9. Based on these phenotypic, phylogenetic, and chemotaxonomic results, strain FP205T represents a novel species of the genus Pseudomonas, for which the name Pseudomonas hefeiensis sp. nov. is proposed. The type strain is FP205T (=ACCC 62447T=JCM 35687T).
Alpha Traveling Waves during Working Memory: Disentangling Bottom-up Gating and Top-down Gain Control
Authors: Zeng Yifan , Sauseng Paul , Alamia Andrea 
Published: March 2024

AbstractWhile previous works established the inhibitory role of alpha oscillations during working memory maintenance, it remains an open question whether such an inhibitory control is a top-down process. Here, we attempted to disentangle this issue by considering the spatio-temporal component of waves in the alpha band, i.e., alpha traveling waves. We reanalyzed two pre-existing and open-access EEG datasets where participants performed lateralized delayed match-to-sample working memory tasks. In the first dataset, the distractor load was manipulated (2, 4, or 6), whereas in the second dataset, the memory span varied between 1, 3, and 6 items. In both datasets, we focused on the propagation of alpha waves on the anterior-posterior axis during the retention period. Our results reveal an increase in alpha-band forward waves as the distractor load increased, but also an increase in forward waves and a decrease in backward waves as the memory set size increased. Notably, our results also showed a lateralization effect: alpha forward waves exhibited a more pronounced increase in the hemisphere contralateral to the distractors, whereas the reduction in backward waves was stronger in the hemisphere contralateral to the targets. In short, the forward waves were regulated by distractors, whereas targets inversely modulated backward waves. Such a dissociation of goal-related and goal-irrelevant physiological signals suggests the co-existence of bottom-up and top-down inhibitory processes: alpha forward waves might convey a gating effect driven by distractor load, while backward waves may represent direct top-down gain control of downstream visual areas.Significance StatementWhen exploring the functional role of alpha band neural oscillations during working memory, significant attention has been directed towards its amplitude modulation, with relatively limited exploration of spatial-temporal dynamics of this rather global brain oscillatory signature. The present study seeks to address this gap by examining the directionality of alpha wave propagation during working memory retention. Our findings offer novel insights into the well-established inhibitory role of alpha waves, demonstrating that this function is manifested differently according to their propagation directions: forward waves seem to facilitate bottom-up gating, while backward waves might mediate top-down gain control.
The technical-reasoning network is recruited when people observe others make or teach how to make tools: An fMRI study
Authors: Bluet Alexandre , Reynaud Emanuelle , Federico Giovanni , Bryche Chloé , Lesourd Mathieu , Fournel Arnaud , Lamberton Franck , Ibarrola Danielle , Rossetti Yves , Osiurak François 
Published: March 2024

AbstractCumulative technological culture is defined as the increase in efficiency and complexity of tools and techniques over generations. While the role of social cognitive skills in cultural transmission has been long acknowledged, recent accounts have emphasized that non-social cognitive skills such as technical reasoning, a form of causal reasoning aimed at understanding the physical world, are also at work during the social transmission of technical content. Here we contribute to this double process approach by reporting an fMRI study about the neurocognitive origins of social learning. Participants were shown videos depicting tool-making episodes in three social-learning conditions: Reverse engineering, Observation and Teaching. Our results showed that the technical-reasoning network, centred around the Area PF of the left inferior parietal cortex, was preferentially activated when watching tool-making episodes. Additionally, the teaching component was related to an activation of the right middle temporal gyrus. We propose that technical reasoning is at the heart of our technological culture and that the role of social cognition and teaching is to improve the learner’s technical reasoning by helping them concentrate on important parts of the technology. Thus, both technical reasoning and social-cognitive skills may play a key role in the cultural evolution of our technologies.
ChemPrint: An AI-Driven Framework for Enhanced Drug Discovery
Authors: Umansky Tyler J. , Woods Virgil A. , Russell Sean M. , Smith Davey M. , Haders Daniel J. 
Published: March 2024

ABSTRACTTraditional High-Throughput Screening (HTS) drug discovery is inefficient. Hit rates for compounds with clinical therapeutic potential are typically 0.5% and only up to 2% maximally. Deep learning models have enriched screening rates to 28%; however, these results include hits with non-therapeutic relevant concentrations, insufficient novelty to their training set, and traverse limited chemical space. This study introduces a novel artificial intelligence (AI)-driven platform, GALILEO, and the Molecular-Geometric Deep Learning (Mol-GDL) model, ChemPrint. This model deploys both t-distributed Stochastic Neighbor Embedding (t-SNE) data splitting to maximize chemical dissimilarity during training and adaptive molecular embeddings to enhance predictive capabilities and navigate uncharted molecular territories. When tested retrospectively, ChemPrint outperformed a panel of five models for the difficult-to-drug oncology targets, AXL and BRD4, achieving an average AUROC score of 0.897 for AXL and 0.876 for BRD4 using the t-SNE split, compared to benchmark model scores ranging from 0.826 to 0.885 for AXL and 0.801 to 0.852 for BRD4. In a zero-shot prospective study,in vitrotesting demonstrated that 19 of 41 compounds nominated by ChemPrint against AXL and BRD4 demonstrated inhibitory activity at concentrations ≤ 20 µM, a 46% hit rate. The 19 hits reported an average-maximum Tanimoto similarity score of 0.36 relative to their training set and scores of 0.13 (AXL) and 0.10 (BRD4) relative to clinical stage compounds for these targets. Our findings demonstrate that increasing test set difficulty through training and testing ChemPrint on datasets with maximal dissimilarity enhances the predictive capabilities of the model. This results in the discovery of compound libraries at high hit rates with low therapeutic concentrations and high chemical novelty. Taken together, the proposed platform sets a new performance standard.
Rapid Homolog Juxtaposition During Meiotic Chromosome Pairing
Authors: Nozaki Tadasu , Weiner Beth , Kleckner Nancy 
Published: March 2024

AbstractA central basic feature of meiosis is pairing of homologous maternal and paternal chromosomes (“homologs”) intimately along their lengths. Recognition between homologs and their juxtaposition in space are mediated by axis-associated DNA recombination complexes. Additional effects ensure that pairing occurs without ultimately giving entanglements among unrelated chromosomes. Here we examine the process of homolog juxtaposition in real time by 4D fluorescence imaging of tagged chromosomal loci at high spatio-temporal resolution in budding yeast. We discover that corresponding loci start coming together from a quite large distance (∼1.8 µm) and progress to completion of pairing in a very short time, usually less than six minutes (thus, “rapid homolog juxtaposition” or “RHJ”). Juxtaposition initiates by motion-mediated extension of a nascent interhomolog DNA linkage, raising the possibility of a tension-mediated trigger. In a first transition, homolog loci move rapidly together (in ∼30 sec, at speeds of up to ∼60 nm/sec) into a discrete intermediate state corresponding to canonical ∼400 nm axis distance coalignment. Then, after a short pause, crossover/noncrossover differentiation (crossover interference) mediates a second short, rapid transition that brings homologs even closer together. If synaptonemal complex (SC) component Zip1 is present, this transition concomitantly gives final close pairing by axis juxtaposition at ∼100 nm, the “SC distance”. We also find that: (i) RHJ occurs after chromosomes acquire their prophase chromosome organization; (ii) is nearly synchronously over thirds (or more) of chromosome lengths; but (iii) is asynchronous throughout the genome. Furthermore, cytoskeleton-mediated movement is important for the timing and distance of RHJ onset and also for ensuring normal progression. Potential implications for local and global aspects of pairing are discussed.
Adaptive chunking improves effective working memory capacity in a prefrontal cortex and basal ganglia circuit
Authors: Soni Aneri V , Frank Michael J. 
Published: March 2024

AbstractHow and why is working memory (WM) capacity limited? Traditional cognitive accounts focus either on limitations on the number or items that can be stored (slots models), or loss of precision with increasing load (resource models). Here we show that a neural network model of prefrontal cortex and basal ganglia can learn to reuse the same prefrontal populations to store multiple items, leading to resource-like constraints within a slot-like system, and inducing a trade-off between quantity and precision of information. Such “chunking” strategies are adapted as a function of reinforcement learning and WM task demands, mimicking human performance and normative models. Moreover, adaptive performance requires a dynamic range of dopaminergic signals to adjust striatal gating policies, providing a new interpretation of WM difficulties in patient populations such as Parkinson’s disease, ADHD and schizophrenia. These simulations also suggest a computational rather than anatomical limit to WM capacity.
Noise schemas aid hearing in noise
Authors: Hicks Jarrod M. , McDermott Josh H. 
Published: March 2024

AbstractHuman hearing is robust to noise, but the basis of this robustness is poorly understood. Several lines of evidence are consistent with the idea that the auditory system adapts to sound components that are stable over time, potentially achieving noise robustness by suppressing noise-like signals. Yet background noise often provides behaviorally relevant information about the environment, and thus seems unlikely to be completely discarded by the auditory system. Motivated by this observation, we explored whether noise robustness might instead be mediated by internal models of noise structure that could facilitate the separation of background noise from other sounds. We found that detection, recognition, and localization in real-world background noise was better for foreground sounds positioned later in a noise excerpt, with performance improving over the initial second of exposure to a noise. These results are consistent with both adaptation-based and model-based accounts, since both explanations require online noise estimation that should benefit from acquiring more samples. However, performance was also robust to interruptions in the background noise and was enhanced for intermittently recurring backgrounds, neither of which would be expected from known forms of adaptation. Additionally, the performance benefit observed for foreground sounds occurring later within a noise excerpt was reduced for recurring noises, suggesting that a noise representation is built up during exposure to a new background noise and then maintained in memory. These findings suggest noise robustness is supported by internal models—“noise schemas”—that are rapidly estimated, stored over time, and used to estimate other concurrent sounds.
Analysis Pipeline to Quantify Uterine Gland Structural Variations
Authors: Khan Sameed , Alessio Adam , Arora Ripla 
Published: March 2024

ABSTRACTTechnical advances in whole tissue imaging and clearing have allowed 3D reconstruction of exocrine uterine glands deep seated in the endometrium. However, there are limited gland structure analysis platforms to analyze these imaging data sets. Here we present a pipeline for segmenting and analyzing uterine gland shape. Using this segmentation methodology, we derive individual metrics to describe gland length, shape, and branching patterns. These metrics are applied to quantify gland behavior with respect to organization around the embryo and proximity of each individual unit to the uterine lumen. Using this image analysis pipeline we evaluate uterine glands at the peri-implantation time points of a mouse pregnancy. Our analysis reveals that upon embryo entry into the uterus glands show changes in length, tortuosity, and proximity to the uterine lumen while gland branch number stays the same. These shape changes aid in reorganization of the glands around the site of embryo implantation. We further apply our analysis pipeline to human and guinea pig uterine glands, extending feasibility to other mammalian species. This work serves as a resource for researchers to extract quantitative, reproducible morphological features from three-dimensional uterine gland images in order to reveal insights about functional and structural patterns.
A portable electrochemical DNA sensor for sensitive and tunable detection of piconewton-scale cellular forces
Authors: Tabrizi Mahmoud Amouzadeh , Ali Ahsan Ausaf , Singuru Murali Mohana Rao , Mi Lan , Bhattacharyya Priyanka , You Mingxu 
Published: March 2024

AbstractCell-generated forces are a key player in cell biology, especially during cellular shape formation, migration, cancer development, and immune response. A new type of label-free smartphone-based electrochemical DNA sensor is developed here for cellular force measurement. When cells apply tension forces to the DNA sensors, the rapid rupture of DNA duplexes allows multiple redox reporters to reach the electrode and generate highly sensitive electrochemical signals. The sensitivity of these portable sensors can be further enhanced by incorporating a CRISPR-Cas12a system. Meanwhile, the threshold force values of these DNA-based sensors can be rationally tuned based on the force application geometries and also DNA intercalating agents. Overall, these highly sensitive, portable, cost-efficient, and easy-to-use electrochemical sensors can be powerful tools for detecting different cell-generated molecular forces.Graphical Abstract
Glucosylceramides impact cellulose deposition and cellulose synthase complex motility in Arabidopsis
Authors: Villalobos Jose A. , Cahoon Rebecca E. , Cahoon Edgar B. , Wallace Ian S. 
Published: March 2024

AbstractCellulose is an abundant component of plant cell wall matrices, and this para-crystalline polysaccharide is synthesized at the plasma membrane by motile Cellulose Synthase Complexes (CSCs). However, the factors that control CSC activity and motility are not fully resolved. In a targeted chemical screen, we identified the alkylated nojirimycin analogN-Dodecyl Deoxynojirimycin (ND-DNJ) as a small molecule that severely impacts Arabidopsis seedling growth. Previous work suggests that ND-DNJ-related compounds inhibit the biosynthesis of glucosylceramides (GlcCers), a class of glycosphingolipid associated with plant membranes. Our work uncovered major changes in the sphingolipidome of plants treated with ND-DNJ, including reductions in GlcCer abundance and altered acyl chain length distributions. Crystalline cellulose content was also reduced in ND-DNJ-treated plants as well as plants treated with the known GlcCer biosynthesis inhibitor N-[2-hydroxy-1-(4-morpholinylmethyl)-2-phenyl ethyl]-decanamide (PDMP) or plants containing a genetic disruption in GLUCOSYLCERAMIDE SYNTHASE (GCS), the enzyme responsible for sphingolipid glucosylation that results in GlcCer synthesis. Live-cell imaging revealed that CSC speed distributions were reduced upon treatment with ND-DNJ or PDMP, further suggesting an important relationship between glycosylated sphingolipid composition and CSC motility across the plasma membrane. These results indicated that multiple interventions compromising GlcCer biosynthesis disrupt cellulose deposition and CSC motility, suggesting that GlcCers impact cellulose biosynthesis in plants.
Megabase-Scale Transgene De-Duplication to Generate a Functional Single-Copy Full-Length Human DMD Transgenic Mouse Model
Authors: Chey Yu C. J. , Corbett Mark , Arudkumar Jayshen , Piltz Sandra , Thomas Paul Q. , Adikusuma Fatwa 
Published: March 2024

AbstractThe development of sequence-specific precision treatments like CRISPR gene-editing therapies for Duchenne Muscular Dystrophy (DMD) requires sequence humanised animal models to enable the direct clinical translation of tested strategies. The current available integrated transgenic mouse model containing the full-length humanDMDgene, Tg(DMD)72Thoen/J (hDMDTg), has been found to have two copies of the transgene per locus in a tail-to-tail orientation, which does not accurately simulate the true copy number of theDMDgene. This duplication also complicates the analysis when testing CRISPR therapy editing outcomes, as large genetic alterations and rearrangements can occur between the cut sites on the two transgenes. To address this, we performed long read nanopore sequencing on hDMDTg mice to better understand the structure of the duplicated transgenes. Following that, we performed a megabase-scale deletion of one of the transgenes by CRISPR zygotic microinjection to generate a single-copy, full-length, humanised DMD transgenic mouse model (hDMDTgSc). Functional, molecular, and histological characterisation show that the single remaining human transgene retains its function and rescues the dystrophic phenotype caused by endogenous murineDmdknockout. Our unique hDMDTgSc mouse model can potentially be used to further generation of DMD disease models, suited for the pre-clinical assessment of sequence-specific therapies.