bluuebunny/crossref_metadata_2025_split huggingface dataset:
Normalized Dynamic Time Warping Increases Sensitivity In Differentiating Functional Network Connectivity In Schizophrenia
Authors: Wiafe Sir-Lord , Kinsey Spencer , Iraji Armin , Miller Robyn , Calhoun Vince D. 
Published: November 2024

ABSTRACTOur study advances the application of dynamic time warping (DTW) as a functional connectivity measure by introducing a normalization technique which enhances the detection of schizophrenia effects in comparison to both standard DTW and traditional correlation methods. By rigorously examining the statistical validity of DTW and our proposed normalized DTW measure, we show that it effectively captures interdependencies between fMRI signals beyond linear correlation, offering a more robust, complementary and informative approach to functional connectivity analysis. Through comprehensive evaluations, we demonstrate that normalized DTW is more sensitive to differences in functional brain network connections between schizophrenia and controls, highlighting its potential to provide deeper insights into clinical research.
Health benefits of a five-day at-home modified fasting program: a randomised controlled trial
Authors: Grundler Franziska , Ducarmon Quinten R. , Holley Alfred , Knufinke Marie , Strathmeyer Selina , Heelemann Steffen , Geyer Roland , Martinez Tellez Borja , MacArthur Michael R , Zeller Georg , Wilhelmi de Toledo Françoise , Mesnage Robin 
Published: November 2024

ABSTRACTBackgroundFasting has been shown to be one of the most cost-effective methods to improve cardiometabolic health. We studied a 5-day hypocaloric (∼600 kcal/day) and ketogenic, modified fasting program (MFP) for at-home interventions. We hypothesised that this MFP induces metabolic changes comparable to 5 days of prolonged fasting (75-250kcal/day).MethodsWe tested the MFP in a two-arm randomised controlled trial where sixty-four healthy subjects were randomised to MFP or control group. Serum biochemistry analyses and questionnaires allowed for determining effects on cardiometabolic risk factors. Emotional well-being, possible side effects and physical activity were assessed with questionnaires. Biological pathways and metabolic processes were explored with nuclear magnetic resonance blood metabolomics and gut metagenomics analyses.ResultsMFP participants (n=32) experienced weight loss (−3.1 ± 1.1 kg) persisting one month after the intervention. The MFP induced significant, but transient reductions, in systolic (−6.4 ± 11.5 mmHg) and diastolic (−4.4 ± 7.7 mmHg) blood pressure, glucose levels, HbA1c and coagulation factors. The MFP led to greater reductions in BMI (p=0.006), diastolic pressure (p = 0.009), cholesterol (p = 0.02), and LDL (p = 0.02) in individuals at risk of cardiometabolic diseases compared to healthy individuals. Total cholesterol, LDL-C and HDL-C levels continued decreasing during food reintroduction. The MFP also increased emotional and physical well-being. Blood metabolomics revealed a significant decrease in chronic inflammation markers. Shotgun metagenomics of the gut microbiome showed trends in the changes in relative abundance of the majority of bacterial species and their genomic repertoire of carbohydrate-active enzymes (CAZymes). This reflected a decrease in families metabolising dietary fibre substrates and an increase in families metabolising host-derived glycan substrates. Comparing MFP effects with a previous cohort’s 5-day prolonged fasting showed similar metabolic changes.ConclusionThis MFP is safe and effectively improves cardiometabolic health and emotional well-being in healthy individuals. It offers comparable metabolic benefits to those observed during 5-day prolonged fasting in a clinic. It is safe to be practised at home, widely accessible and compatible with individuals’ everyday life.
Development and characterization of bioinks for 3D bioprinting of in vitro skeletal muscle constructs
Authors: Kado Abdalkader Rodi , Yamauchi Kosei , Konishi Satoshi , Fujita Takuya 
Published: November 2024

AbstractThe use of 3D bioprinting to constructin vitroskeletal muscle models presents a promising approach; however, selecting an optimal bioink remains a common challenge. This study focuses on the development and characterization of bioinks for extrusion-based 3D bioprinting, specifically targeting the creation of accurate skeletal muscle models. By exploring various compositions of alginate, gelatin, fibrinogen, and nanofiber cellulose, we evaluate these formulations based on printability and their support for the growth and differentiation of C2C12 myoblast cells.While alginate provided a strong, stable matrix for printing scaffolds embedded with C2C12 cells, it did not effectively promote cell growth and differentiation. The addition of fibrinogen to alginate enhanced cell growth and differentiation but was limited mainly to the scaffold surfaces, even with the inclusion of gelatin as a sacrificial ink. Notably, replacing alginate with nanofiber cellulose (NFC) alongside fibrinogen significantly improved cell growth and differentiation, leading to the formation of mature myotubes. Cell distribution was observed both inside and on the surfaces of the scaffolds, indicating effective spatial cell distribution. Furthermore, the scaffolds were tailored to form skeletal muscle bundles anchored between PDMS pillars for contractility testing. Upon exposure to electrical stimulation, the cells displayed measurable displacement, demonstrating contractile function.These findings offer valuable insights into optimizing bioink formulations that promote myoblast growth and differentiation into skeletal musclein vitro, with potential applications in future neuromuscular disease modeling.
AlloPool: An Adaptive Graph Neural Network for Dynamic Allosteric Network Prediction in Protein Systems
Authors: Marfoglia M. , Guirardel L. , Barth P. 
Published: November 2024

AbstractAllosteric communication is essential to protein function, facilitating the dynamic regulation of biological responses through the propagation of structural and dynamic changes between regulatory and effector sites in response to stimuli. Traditional approaches to studying protein allostery often rely on static protein structures or abstract representations involving fully connected interaction graphs, which do not capture the temporal and state-dependent nature of these dynamic systems. Here, we introduce AlloPool, a graph neural network (GNN)-based model that iteratively prunes residue interactions to identify minimal, time-dependent interaction networks that govern long-range structural and dynamic responses to chemical or mechanical stimuli. Using temporal attention and graph aggregation, AlloPool accounts for evolving protein conformations in both molecular dynamics (MD) and steered MD (SMD) simulations to predict MD and SMD trajectories. We validate AlloPool on the Pin-1 protein and the ADGRG1 and B1AR receptors, showcasing its ability to accurately recapitulate protein motions, infer allosteric communication pathways, and identify critical allosteric sites. Additionally, AlloPool identifies force-dependent changes in GAIN domain structure and reconstructs directed information flow under mechanical load. Comparative analyses indicate that AlloPool outperforms existing models in MD and SMD trajectory reconstruction, presenting a new framework for analyzing force- and ligand-induced allosteric motions. This work advances the modeling of allosteric systems and offers broad potential for applications in drug discovery, synthetic biology, and protein engineering.
Squeakuences: a portable tool for formatting ‘squeaky-clean’ sequences to eliminate bioinformatic software incompatibilities
Authors: Lane Linnea E , Doerfler Ashley N , L’Argent Luna A , Touchette Emily , Mills Bronson , Bryant Jessika , Roller Savannah N , Forsythe Evan S 
Published: November 2024

AbstractComputational analysis of biological sequences is the cornerstone of modern bioinformatics research. Complex processing and interpretation of data often entails multi-step workflows. The specific requirements and limitations of individual applications can require laborious reformatting and piecemeal ‘data-wrangling’ to produce a satisfactory input for each step in a pipeline. We presentSqueakuences, a command line tool developed to simplify and automate FASTA file preparation for applications such as phylogenetics, gene annotation, and genome analysis. Implemented in a lightweight Python script,Squeakuencesidentifies and removes potentially problematic elements in sequence identifiers, such as non-alphanumeric characters, white space, and excessive character count.Squeakuencesoutputs a new clean version of the sequence file for analysis alongside metadata files to track changes. The user can customizeSqueakuences’ behavior using optional arguments to meet individual processing and formatting requirements. We tested the performance ofSqueakuenceson molecular data from the human reference genome and found that runtime correlates with the number of sequences processed but not with file size. We expectSqueakuencesto save time and manual effort when analyzing sequence data.Squeakuencescode is freely available athttps://github.com/EvanForsythe/Squeakuences.
Dampened α7 nAChR activity contributes to audiogenic seizures and hyperactivity in a mouse model of Fragile X Syndrome
Authors: Goebel Sarah , Cordova-Martinez Dylann , Verselis Vytas K. , Francesconi Anna 
Published: November 2024

AbstractFragile X Syndrome (FXS) is the most common form of inherited intellectual disability and often accompanied with debilitating pathologies including seizures and hyperactivity. FXS arises from a trinucleotide repeat expansion in the 5’ UTR of theFMR1gene that silences expression of the RNA-binding protein FMRP. Despite progress in understanding FMRP functions, the identification of effective therapeutic targets has lagged and at present there are no viable treatment options. Here we identify the α7 nicotinic acetylcholine receptor (nAChR) as candidate target for intervention in FXS. In the early postnatal hippocampus ofFmr1knockout (KO) mice, an established pre-clinical model of FXS, the α7 nAChR accessory protein Ly6H is abnormally enriched at the neuronal surface and mislocalized in dendrites. Ly6H, a GPI-anchored protein, binds α7 nAChRs with high affinity and can limit α7 nAChR surface expression and signaling. We find that α7 nAChR-evoked Ca2+responses are dampened in immature glutamatergic and GABAergicFmr1KOneurons compared to wild type. Knockdown of endogenous Ly6H inFmr1KOneurons is sufficient to rescue dampened α7 nAChR Ca2+responses in vitro, providing evidence of a cell-autonomous role for Ly6H aberrant expression in α7 nAChR hypofunction. In line with intrinsic deficits in α7 nAChR activity inFmr1KOneurons, in vivo administration of the α7 nAChR-selective positive allosteric modulator PNU-120596 reduced hyperactivity and seizure severity in adolescentFmr1KOmice. Our mechanistic studies together with evidence of the in vivo efficacy of α7 nAChR augmentation implicate α7 nAChR hypofunction in FXS pathology.SummaryCorrection of α7 nAChR hypofunction in a preclinical murine model of Fragile X syndrome ameliorates seizure severity and hyperactivity.
Generalized cell phenotyping for spatial proteomics with language-informed vision models
Authors: Wang Xuefei (Julie) , Dilip Rohit , Bussi Yuval , Brown Caitlin , Pradhan Elora , Jain Yashvardhan , Yu Kevin , Li Shenyi , Abt Martin , Börner Katy , Keren Leeat , Yue Yisong , Barnowski Ross , Van Valen David 
Published: November 2024

AbstractWe present a novel approach to cell phenotyping for spatial proteomics that addresses the challenge of generalization across diverse datasets with varying marker panels. Our approach utilizes a transformer with channel-wise attention to create a language-informed vision model; this model’s semantic understanding of the underlying marker panel enables it to learn from and adapt to heterogeneous datasets. Leveraging a curated, diverse dataset with cell type labels spanning the literature and the NIH Human BioMolecular Atlas Program (HuBMAP) consortium, our model demonstrates robust performance across various cell types, tissues, and imaging modalities. Comprehensive benchmarking shows superior accuracy and generalizability of our method compared to existing methods. This work significantly advances automated spatial proteomics analysis, offering a generalizable and scalable solution for cell phenotyping that meets the demands of multiplexed imaging data.
Neuron-astrocyte Coupling in Lateral Habenula Mediates Depressive-like Behaviors
Authors: Xin Qianqian , Wang Junying , Zheng Jinkun , Tan Yi , Jia Xiaoning , Ni Zheyi , Feng Jiesi , Wu Zhaofa , Li Yulong , Li Xiaoming , Ma Huan , Hu Hailan 
Published: November 2024

SummaryThe lateral habenular (LHb) neurons and astrocytes have been strongly implicated in depression etiology but it was not clear how the two dynamically interact during depression onset. Here, using multi-brain-region calcium photometry recording in freely-moving mice, we discover that stress induces a unique, bimodal neuronal response and a most rapid astrocytic response in the LHb. LHb astrocytic calcium requires the α1A-adrenergic receptor, and depends on a recurrent neural network between the LHb and locus coeruleus (LC). Through the gliotransmitter glutamate and ATP/Adenosine, LHb astrocytes mediate the second-wave activation of local LHb neurons as well as release of norepinephrine (NE). Activation or inhibition LHb astrocytic calcium signaling facilitates or prevents stress-induced depressive-like behaviors respectively. These results identify a stress-induced positive feedback loop in the LHb-LC axis, with astrocytes being a critical signaling relay. The identification of this prominent neuron-glia interaction may shed light on stress management and depression prevention.
A Perturbation Cell Atlas of Human Induced Pluripotent Stem Cells
Authors: Nourreddine Sami , Doctor Yesh , Dailamy Amir , Forget Antoine , Lee Yi-Hung , Chinn Becky , Khaliq Hammza , Polacco Benjamin , Muralidharan Monita , Pan Emily , Zhang Yifan , Sigaeva Alina , Hansen Jan Niklas , Gao Jiahao , Parker Jillian A. , Obernier Kirsten , Clark Timothy , Chen Jake Y. , Metallo Christian , Lundberg Emma , Ideker Trey , Krogan Nevan , Mali Prashant 
Published: November 2024

SUMMARYTowards comprehensively investigating the genotype-phenotype relationships governing the human pluripotent stem cell state, we generated an expressed genome-scale CRISPRi Perturbation Cell Atlas in KOLF2.1J human induced pluripotent stem cells (hiPSCs) mapping transcriptional and fitness phenotypes associated with 11,739 targeted genes. Using the transcriptional phenotypes, we created a minimum distortion embedding map of the pluripotent state, demonstrating rich recapitulation of protein complexes, such as strong co-clustering of MRPL, BAF, SAGA, and Ragulator family members. Additionally, we uncovered transcriptional regulators that are uncoupled from cell fitness, discovering potential novel pluripotency (JOSD1, RNF7) and metabolic factors (ZBTB41). We validated these findings via phenotypic, protein-interaction, and metabolic tracing assays. Finally, we propose a contrastive human-cell engineering framework (CHEF), a machine learning architecture that learns from perturbation cell atlases to predict perturbation recipes that achieve desired transcriptional states. Taken together, our study presents a comprehensive resource for interrogating the regulatory networks governing pluripotency.
Molecular Signatures of Resilience to Alzheimer’s Disease in Neocortical Layer 4 Neurons
Authors: Dharshini S Akila Parvathy , Sanz-Ros Jorge , Pan Jie , Tang Weijing , Vallejo Kristen , Otero-Garcia Marcos , Cobos Inma 
Published: November 2024

ABSTRACTSingle-cell omics is advancing our understanding of selective neuronal vulnerability in Alzheimer’s disease (AD), revealing specific subtypes that are either susceptible or resilient to neurodegeneration. Using single-nucleus and spatial transcriptomics to compare neocortical regions affected early (prefrontal cortex and precuneus) or late (primary visual cortex) in AD, we identified a resilient excitatory population in layer 4 of the primary visual cortex expressingRORB,CUX2, andEYA4. Layer 4 neurons in association neocortex also remained relatively preserved as AD progressed and shared overlapping molecular signatures of resilience. Early in the disease, resilient neurons upregulated genes associated with synapse maintenance, synaptic plasticity, calcium homeostasis, and neuroprotective factors, includingGRIN2A, RORA, NRXN1, NLGN1, NCAM2, FGF14, NRG3, NEGR1, andCSMD1. We also identifiedKCNIP4, which encodes a voltage-gated potassium (Kv) channel-interacting protein that interacts with Kv4.2 channels and presenilins, as a key factor linked to resilience.KCNIP4was consistently upregulated in the early stages of pathology. Furthermore, AAV-mediated overexpression ofKcnip4in a humanized AD mouse model reduced the expression of the activity-dependent genesArcandc-Fos, suggesting compensatory mechanisms against neuronal hyperexcitability. Our dataset provides a valuable resource for investigating mechanisms underlying resilience to neurodegeneration.
Phase transitions of ice VIII-VII-X: A potential energy landscape perspective
Authors: Li Lu , Gao Pengyue , Zhang Wei , Liu Guoji , Lv Jian , Wang Yanchao 
Published: November 2024

Water ice, an archetypal molecular system, exhibits a complex phase diagram characterized by numerous phase transitions under varying pressure-temperature conditions. However, it remains a significant challenge to theoretical modeling of these transitions owing to the high dimensionality in representing the potential energy landscapes (PEL) of ice crystalline phases. In an attempt to deeply understand the mechanisms of phase transitions between ice VII, VIII, and X, a graph-based stationary-point network was employed to simplify the representation of the PEL and locally constructed the PEL of ice at different pressures by our developed high-index saddle dynamic scheme. The stationary-point networks at 40 and 80 GPa indicate a pronounced flattened PEL of ice over a wide range of pressure (up to at least 80 GPa), where multiple structures (i.e., local minima) are energetically degenerate with phase VIII and separated by low-energy barriers (∼10 meV/atom at 40 GPa). These features indicate the disordered VII phase is more favorable at finite temperatures, in agreement with previous experimental observations. Additionally, we demonstrated that the PEL topology undergoes a fundamental alteration at higher pressures, with a single funnel emerging at 120 GPa, facilitating the crystallization of phase X. This work serves as a proof of concept for using the stationary-point network to explicitly represent the PEL, highlighting their potential in elucidating complex phase transitions.

Published by the American Physical Society
2024
Towards a framework for implementing blockchain technology in the construction industry of Sri Lanka
Authors: Gamage Namal , Ambagala A.P. Krishni Kavindya , Nanayakkara Samudaya , Perera Srinath 
Published: November 2024

PurposeThe construction industry is often criticised due to inherited challenges: poor payment practices, inadequate collaboration, etc. Blockchain has the potential to address these issues with its salient features. Nonetheless, adopting blockchain and smart contracts (B&SC) within the construction industry is a comprehensive endeavour due to its intricate nature. The situation is bleak in Sri Lanka due to numerous barriers such as limited technical expertise, cost implications and many others. Hence, this paper aims to examine these barriers, appropriate strategies to overcome them, explore potential blockchain-applicable areas and formulate a framework to adopt B&SC in the construction industry of Sri Lanka (CISL).Design/methodology/approachThis study employed a mixed research approach. The barriers for the adoption of B&SC to the CISL and their applicable areas were distinguished through a questionnaire survey and analysed using the Relative Importance Index. Strategies to overcome them were identified through expert interviews and analysed utilising manual-content analysis.FindingsThe study identified 15 barriers, 12 strategies and 9 areas for integrating B&SC for the CISL. The analysis indicated that having fewer blockchain-powered applications, the reluctance of the enterprises to bear costs to integrate blockchain and sluggish adaptation to new digital technologies are significant barriers. Further, conducting an industry-wide digitalisation analysis, developing an industry-wide digitalisation strategy and recruiting skilful IT staff were pointed out as the pivotal strategies. Moreover, payment and supply chain management were identified as areas with high potential.Originality/valueThis study unveils an analysis of barriers, strategies and areas in adopting B&SC for CISL and formulates a framework. It can be deployed as a guideline for implementing B&SC in the CISL.
Understanding enablers and inhibitors of digital rupee: a dual-factor theory perspective
Authors: Balasubramanian Senthil Arasu , Thirumaran Pirasad 
Published: November 2024

Purpose
Central banks globally are actively investigating the issuance of central bank digital currencies, a digital form of fiat money. In this light, this study aims to explore and empirically validate the factors that enable or inhibit user behavioral intentions to adopt the digital rupee in India.

Design/methodology/approach
The study employed dual-factor theory (DFT) to capture the users’ perceptions of both enablers and inhibitors of the digital rupee. The authors gathered survey data from 351 individuals in India through online questionnaires. The authors used partial least squares structural equation modeling and multigroup analysis (MGA) to evaluate the proposed conceptual model.

Findings
The findings reveal that enablers such as perceived government support, trialability and similarity positively influence users’ attitudes toward the digital rupee. In contrast, inhibitors such as usage, value and risk barriers increase users’ resistance. Attitude has a significant positive impact on the intention to use the digital rupee, while resistance significantly reduces the intention to adopt it. MGA results highlight the importance of gender and income status in understanding intention to use the digital rupee.

Originality/value
By applying DFT, the study identifies a set of enablers and inhibitors that influence the behavioral intention to use the digital rupee in India. It provides actionable insights for governments and central bankers to devise effective policies, design considerations and targeted interventions, ensuring a sustainable environment for the successful implementation of the digital rupee.
Constrained solutions of generalized coupled discrete-time periodic matrix equations with application in state observer design for linear periodic systems
Authors: Wang Wenli , Song Caiqin 
Published: November 2024

PurposeIt is desired to provide a diversified iterative scheme for solving the constrained solutions of the generalized coupled discrete-time periodic (GCDTP) matrix equations from the perspective of optimization.Design/methodology/approachThe paper considers generalized reflexive solutions of the GCDTP matrix equations by applying the Jacobi gradient-based iterative (JGI) algorithm, which is an extended variant of the gradient-based iterative (GI) algorithm.FindingsThrough numerical simulation, it is verified that the efficiency and accuracy of the JGI algorithm are better than some existing algorithms, such as the GI algorithm in Hajarian, the RGI algorithm in Sheng and the AGI algorithm in Xie and Ma.Originality/valueIt is the first instance in which the GCDTP matrix equations are solved applying the JGI algorithm.