bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synaptic function and sensory processing in ZDHHC9-associated neurodevelopmental disorder: a mechanistic account
Authors: Ianov Vitanov Rebeca , Achterberg Jascha , Akarca Danyal , Astle Duncan E. , Baker Kate 
Published: March 2024

AbstractLoss-of-functionZDHHC9variants are associated with X-linked intellectual disability (XLID), rolandic epilepsy (RE) and developmental language difficulties. This study integrates human neurophysiological data with a computational model to identify a potential neural mechanism explainingZDHHC9-associated differences in cortical function and cognition. Magnetoencephalography (MEG) data was collected during an auditory roving oddball paradigm from eight individuals with aZDHHC9loss-of-function variant (ZDHHC9 group) and seven age-matched individuals without neurological or neurodevelopmental difficulties (control group). Evoked responses to auditory stimulation were larger in amplitude and showed a later peak latency in the ZDHHC9 group but demonstrated normal stimulus-specific properties. Magnetic mismatch negativity (mMMN) amplitude was also increased in the ZDHHC9 group, reflected by stronger neural activation during deviant processing relative to the standard. A recurrent neural network (RNN) model was trained to mimic recapitulate group-level auditory evoked responses, and subsequently perturbed to test the hypothesised impact ofZDHHC9-driven synaptic dysfunction on neural dynamics. Results of model perturbations showed that reducing inhibition levels by weakening inhibitory weights recapitulates the observed group differences in evoked responses. Stronger reductions in inhibition levels resulted in increased peak amplitude and peak latency of RNN prediction relative to the pre-perturbation predictions. Control experiments in which excitatory connections were strengthened by the same levels did not result in consistently stable activity or AEF-like RNN predictions. Together, these results suggest that reduced inhibition is a plausible mechanism by which loss of ZDHHC9 function alters cortical dynamics during sensory processing.Abstract FigureGraphical AbstractIn the current study, we employed a bottom-up approach to study the impact of synaptic-level alterations associated withZDHHC9variants on cortical function in healthy andZDHHC9-deficient participants. To achieve this, a recurrent neural network model was developed to recapitulate MEG-derived auditory evoked responses and subsequently perturbed in order to determine effects on resulting dynamics. We show that reduced network inhibition recapitulates empirical observations, specifically increased response amplitudes, delayed peak latencies and increased mismatch negativity. These results offered a mechanistic account on the impact ofZDHHC9-associated synaptic alterations on auditory processing.
Elucidating microRNA-34a organisation within Human Argonaute-2 by DNP MAS NMR
Authors: Dasgupta Rubin , Becker Walter , Petzold Katja 
Published: March 2024

AbstractUnderstanding mRNA regulation by microRNA (miR) relies on the structural understanding of the RNA-induced silencing complex (RISC). Here, we elucidate the structural organisation of miR-34a, deregulated in various cancers, in hAgo2, effector protein in RISC, using guanosine-specific isotopic labelling and dynamic nuclear polarisation (DNP)-enhanced solid-state NMR. Homonuclear correlation experiments revealed that the non-A-form helical conformation of miR-34a increases when incorporated into hAgo2 and then bound to SIRT1 mRNA compared to the free hairpin or the free duplex formed with mRNA. Nucleotide-specific information of the of C2’- and C3’-endo sugar puckering can be obtained from the C8 – C1’ correlation with varying distributions, revealing a trapping of different confirmations upon freezing. C3’-endo puckering was predominantly observed for the seed, while C2’-endo for the central region and a mixture of both elsewhere. These observations provide insights into the molecular dynamic basis of miR-based mRNA regulation, while also providing a proof-of-concept that experiments under cryogenic conditions, e.g. at 90K, can trap and with that reveal frozen dynamic states, using methods such as (DNP-enhanced) solid-state NMR or Cryo-EM
Open Educational Resources for distributed hands-on teaching in molecular biology
Authors: Cerda Ariel , Aravena Alejandro , Zapata Valentina , Arce Anibal , Araya Wladimir , Gallardo Domingo , Aviles Javiera , Quero Francisco , Nuñez Isaac , Matute Tamara , Navarro Felipe , Ferrando Valentina , Blanco Marta , Velozo Sebastian , Rodriguez Sebastian , Aguilera Sebastian , Chateau Francisco , Molloy Jennifer C , Aidelberg Guy , Lindner Ariel B. , Castro Fernando , Cremades Pablo , Ramirez-Sarmiento Cesar , Federici Fernan 
Published: March 2024

AbstractOpen Educational Resources (OER), freely accessible learning, teaching and research materials, have been proposed as key enabling tools to achieve inclusive knowledge societies and equitable access to education. Here, we describe novel OER consisting of low cost and locally produced public domain biological reagents, open source hardware and free software collaborative notebooks to teach LAMP DNA amplification, RT-PCR RNA detection, enzyme kinetics and fluorescence imaging. These resources have been distributed nationwide to students’ homes as a lab-in-a-box, i.e. remote teaching during the pandemic lockdowns, as well as in the form of personalized learning environments during in-person teaching after the opening of teaching laboratories. All the protocols and design files are available under open source licenses.
Live Cell Fluorescence Microscopy – An End-to-End Workflow for High-Throughput Image and Data Analysis
Authors: Zahumensky Jakub , Malinsky Jan 
Published: March 2024

AbstractFluorescence microscopy images of biological samples contain valuable information but require rigor-ous analysis for accurate and reliable determination of changes in protein localization, fluorescence intensity and morphology of the studied objects. Traditionally, cells for microscopy are immobilized using chemicals, which can introduce stress. Analysis often focuses only on colocalization and in-volves manual segmentation and measurement, which are time-consuming and can introduce bias. Our new workflow addresses these issues by gently immobilizing cells using a small agarose block on a microscope cover glass. This approach is suitable for cell-walled cells (yeast, fungi, plants, bacteria), facilitates their live imaging under conditions close to their natural environment and enables the addi-tion of chemicals during time-lapse experiments. The primary focus of the protocol is on the presented analysis workflow, which is applicable to virtually any cell type – we describe cell segmentation using the Cellpose software followed by automated analysis of a multitude of parameters using custom-written Fiji (ImageJ) macros. The results can be easily processed using the provided R markdown scripts or available graphing software. Our method facilitates unbiased batch analysis of large datasets, improving the efficiency and accuracy of fluorescence microscopy research.The reported sample preparation protocol and Fiji macros were used in our recent publications:Microbiol Spectr(2022), DOI: 10.1128/spectrum.01961-22;Microbiol Spectr(2022), DOI: 10.1128/spectrum.02489-22;J Cell Sci(2023), DOI: 10.1242/jcs.260554.Graphical overviewFrom fluorescence microscopy to numbers and plots – a generalized workflow
The ER-phagy receptor FAM134B is targeted bySalmonellaTyphimurium to promote infection
Authors: Gatica Damián , Alsaadi Reham M. , Hamra Rayan El , Mueller Rudolf , Miyazaki Makoto , Sad Subash , Russell Ryan C. 
Published: March 2024

ABSTRACTMacroautophagy/autophagy is a key catabolic-recycling pathway that can selectively target damaged organelles or invading pathogens for degradation. The selective autophagic degradation of the endoplasmic reticulum (hereafter referred to as ER-phagy) is a homeostatic mechanism, controlling ER size, the removal of misfolded protein aggregates, and organelle damage. ER-phagy is also stimulated by pathogen infection. However, the link between ER-phagy and bacterial infection remains poorly understood, as are the mechanisms evolved by pathogens to escape the effects of ER-phagy. Here, we show thatSalmonella entericaserovar Typhimurium inhibits ER-phagy by targeting the ER-phagy receptor FAM134B, leading to a pronounced increase inSalmonellaviability after invasion.Salmonellaprevents FAM134B oligomerization, which is required for efficient ER-phagy. FAM134B knock-out raises intracellularSalmonellanumber, while FAM134B activation reducesSalmonellaburden. Additionally, we found thatSalmonellatargets FAM134B through the bacterial effector SopF to enhance intracellular survival through ER-phagy inhibition. Furthermore, FAM134B knock-out mice infected withSalmonellapresented severe intestinal damage and increased bacterial burden. These results provide new mechanistic insight into the interplay between ER-phagy and bacterial infection, highlighting a key role for FAM134B in innate immunity.
An artificial intelligence accelerated virtual screening platform for drug discovery
Authors: Zhou Guangfeng , Rusnac Domnita-Valeria , Park Hahnbeom , Canzani Daniele , Nguyen Hai Minh , Stewart Lance , Bush Matthew F. , Nguyen Phuong Tran , Wulff Heike , Yarov-Yarovoy Vladimir , Zheng Ning , DiMaio Frank 
Published: March 2024

AbstractStructure-based virtual screening is a key tool in early drug discovery, with growing interest in the screening of multi-billion chemical compound libraries. However, the success of virtual screening crucially depends on the accuracy of the binding pose and binding affinity predicted by computational docking. Here we developed a highly accurate structure-based virtual screen method, RosettaVS, for predicting docking poses and binding affinities. Our approach outperforms other state-of-the-art methods on a wide range of benchmarks, partially due to our ability to model receptor flexibility. We incorporate this into a new open-source artificial intelligence accelerated virtual screening platform for drug discovery. Using this platform, we screened multi-billion compound libraries against two unrelated targets, a novel ubiquitin ligase target KLHDC2 and the human voltage-gated sodium channel NaV1.7. On both targets, we discover hits, including seven novel hits (14% hit rate) to KLHDC2 and four novel hits (44% hit rate) to NaV1.7 with single digit micromolar binding affinities. Screening in both cases was completed in less than seven days. Finally, a high resolution X-ray crystallographic structure validates the predicted docking pose for the KLHDC2 ligand complex, demonstrating the effectiveness of our method in lead discovery.
Three Modes of Viral Adaption by the Heart
Authors: Griffiths Cameron D. , Shah Millie , Shao William , Borgman Cheryl A. , Janes Kevin A. 
Published: March 2024

AbstractViruses elicit long-term adaptive responses in the tissues they infect. Understanding viral adaptions in humans is difficult in organs such as the heart, where primary infected material is not routinely collected. In search of asymptomatic infections with accompanying host adaptions, we mined for cardio-pathogenic viruses in the unaligned reads of nearly one thousand human hearts profiled by RNA sequencing. Among virus-positive cases (∼20%), we identified three robust adaptions in the host transcriptome related to inflammatory NFκB signaling and post-transcriptional regulation by the p38–MK2 pathway. The adaptions are not determined by the infecting virus, and they recur in infections of human or animal hearts and cultured cardiomyocytes. Adaptions switch states when NFκB or p38–MK2 are perturbed in cells engineered for chronic infection by the cardio-pathogenic virus, coxsackievirus B3. Stratifying viral responses into reversible adaptions adds a targetable systems-level simplification for infections of the heart and perhaps other organs.
Repurposing Clinical MRI Archives for Multiple Sclerosis Research with a Flexible, Single-Modality Approach: New Insights from Old Scans
Authors: Goebl Philipp , Wingrove Jed , Abdelmannan Omar , Vega Barbara Brito , Stutters Jonathan , Graca Ramos Silvia Da , Kenway Owain , Rosoor Thomas , Wassmer Evangeline , Chataway Jeremy , Arnold Douglas , Collins Louis , Hemmingway Cheryl , Narayanan Sridar , Chard Declan , Iglesias Juan Eugenio , Barkhof Frederik , Hacohen Yael , Thompson Alan , Alexander Daniel , Ciccarelli Olga , Eshaghi Arman 
Published: March 2024

ABSTRACTIn multiple sclerosis (MS), magnetic resonance imaging (MRI) biomarkers are critical for research in diagnosis, prognosis and assessing treatment efficacy. Traditionally, extracting relevant biomarkers of disease activity and neurodegeneration requires multimodal MRI protocols, limiting the use of the already existing vast amount of incomplete or single-modality MRI data which are acquired in clinical settings. We developed MindGlide, a deep learning model that extracts volums of brain regions and lesion from a single MRI modality, simplifying analysis and enabling the use of heterogeneous clinical archives. We trained MindGlide on a dataset of 4,247 brain MRI scans from 2,934 MS patients across 592 MRI scanners and validated it on 14,952 brain MRI scans from 1001 patients from three unseen external validation cohorts including 161 adolescent patients. Using dice scores, we demonstrated that MindGlide accurately estimated white matter lesion, cortical, and deep grey matter volumes. These volumes correlated with disability (Expanded Disability Status Scale, absolute correlation coefficients 0.1-0.2, p<0.05), and MindGlide outperformed an established tool in this regard. MindGlide robustly detected treatment effects across clinical trials, including disease activity and neurodegeneration (as shown by lesion accrual and brain tissue loss, respectively), even when analysing MRI modalities not traditionally used for such detailed measurements. Our results indicate the potential to indirectly reduce scan time and drug development costs in clinical trials while directly transforming the utility of retrospective analysis of real-world data acquired in clinical settings. As a consequence, scan time will be reduced and, in turn, the cost of trials.
THE USE OF BOTULINUM TOXIN FOR SPASTICITY IN PEOPLE AFFECTED BY SPINAL CORD INJURY: A SCOPING REVIEW PROTOCOL
Authors: Alessandro Zadra , Daniel Feller , Irene Maini , Michele Zarbo , Jacopo Bonavita 
Published: March 2024

ABSTRACTIntroductionUp to 80% of individuals affected by Spinal Cord Injury (SCI) develops spasticity, both in the acute and chronic phases. Botulinum NeuroToxin (BoNT) injections have been proven to be an effective intervention to treat focal spasticity in Stroke, Cerebral Palsy and Multiple Sclerosis. However, to the best of our knowledge, only one systematic review published in 2015 evaluated the efficacy of BoNT in treating spasticity in patients affected by SCI.ObjectiveWe formulated the following research question: “What is known from the existing literature about the use of BoNT for treating spasticity in patients affected by SCI?”.Material and methodsWe will include studies focusing on using BoNT to treat spasticity in patients with SCI due to any cause. We will search the following databases: MEDLINE (via PubMed), Embase, CENTRAL, Scopus, and PEDro. In addition, grey literature and the reference lists of all relevant studies will be searched. Two authors will independently perform the study selection and data extraction phases. Results from the scoping review will be summarized descriptively through tables and diagrams.
Scaffolded cooperative problem-based approach in entrepreneurship education for vocational preservice teacher
Authors: Widiastuti Indah , Budiyanto Cucuk Wawan , Towip Towip , Estriyanto Yuyun , Hassan Syed Ahmad Helmi Syed , Pratami Devi 
Published: March 2024

PurposeThis study aims to comprehend vocational preservice teachers' recalled experiences with the Cooperative Problem-based Learning (CPBL) pedagogical approach in an entrepreneurship course and to reveal how these experiences will impact their future teaching practice. The course under study intends to improve preservice teachers' entrepreneurial attitudes while equipping them with the skills necessary to create a comparable teaching strategy at school after graduation.Design/methodology/approachThis study used the semi-structured interview data to triangulate the qualitative data collected from the students' reflection journals. The data were thematically analyzed whereas the codes with comparable elements were combined, resulting in themes that describe the relevance of scaffolding used with each component of the MUSIC motivational model.FindingsThe results revealed that the student teachers who took part in the research stated in their comments how the scaffolds used in the CPBL sessions impacted their learning. Additionally, they could articulate the experiences that strengthened their perceptions regarding entrepreneurs and entrepreneurship education.Practical implicationsBy implementing scaffolded CPBL in entrepreneurship course during the teacher preparation program, the preservice teachers would be able to put a similar approach into the practice of their future teaching profession in guiding students to accomplish instructional outcomes.Originality/valueThis study highlights the importance of providing more innovative practices for entrepreneurship education across teacher preparation curricula to help develop the skills necessary for entering the future profession. The findings also emphasize the value of scaffolding in PBL, including expert, peer and activity design scaffolding. It also completes the body of research indicating that PBL-based entrepreneur education instruction can help students develop their entrepreneurial skills and attitudes while also providing a great chance to improve their teaching abilities.
Digital twins for smart building at the facility management stage: a systematic review of enablers, applications and challenges
Authors: Ghansah Frank Ato 
Published: March 2024

PurposeDespite the opportunities of digital twins (DTs) for smart buildings, limited research has been conducted regarding the facility management stage, and this is explained by the high complexity of accurately representing and modelling the physics behind the DTs process. This study thus organises and consolidates the fragmented literature on DTs implementation for smart buildings at the facility management stage by exploring the enablers, applications and challenges and examining the interrelationships amongst them.Design/methodology/approachA systematic literature review approach is adopted to analyse and synthesise the existing literature relating to the subject topic.FindingsThe study revealed six main categories of enablers of DTs for smart building at the facility management stage, namely perception technologies, network technologies, storage technologies, application technologies, knowledge-building and design processes. Three substantial categories of DTs application for smart buildings were revealed at the facility management stage: efficient operation and service monitoring, efficient building energy management and effective smart building maintenance. Subsequently, the top four major challenges were identified as being “lack of a systematic and comprehensive reference model”, “real-time data integration”, “the complexity and uncertainty nature of real-time data” and “real-time data visualisation”. An integrative framework is finally proposed by examining the interactive relationship amongst the enablers, the applications and the challenges.Practical implicationsThe findings could guide facility managers/engineers to fairly understand the enablers, applications and challenges when DTs are being implemented to improve smart building performance and achieve user satisfaction at the facility management stage.Originality/valueThis study contributes to the knowledge body on DTs by extending the scope of the existing studies to identify the enablers and applications of DTs for smart buildings at the facility management stage and the specific challenges.
Intrinsic and extrinsic drivers of organic matter processing along phosphorus and salinity gradients in coastal wetlands
Authors: Anderson Kenneth J. , Kominoski John S. , Sah Jay P. 
Published: March 2024

Abstract

Climate change is accelerating sea‐level rise and saltwater intrusion in coastal regions world‐wide and interacting with large‐scale changes in species composition in coastal wetlands. Quantifying macrophyte litter breakdown along freshwater‐to‐marine coastal gradients is needed to predict how carbon stores will respond to shifts in both macrophyte communities and water chemistry under changing environmental conditions.

To test the interactive drivers of changing species identity and water chemistry, we performed a reciprocal transplant of four macrophyte litter species in seven sites along freshwater‐to‐marine gradients in the Florida Coastal Everglades. We measured surface water chemistry (dissolved organic carbon, total nitrogen and total phosphorus), litter chemistry (% nitrogen, % phosphorus, change in N:P molar ratio, % cellulose and % lignin as proxies for recalcitrance) and litter breakdown rates (k/degree‐day).

Direct effects of salinity and surface water nutrients were the strongest drivers of k, but unexpectedly, litter chemistry did not correlate with litter k. However, salinity strongly correlated with changes in litter chemistry, whereby litter incubated in brackish and marine wetlands was more labile and gained more phosphorus compared with litter in freshwater marshes. Our results suggest that litter k in coastal wetlands is explained by species‐specific interactions among water and litter chemistries. Water nutrient availability was an important predictor of breakdown rates across species, but breakdown rates were only explained by the carbon recalcitrance of litter in the species with the slowest breakdown (Cladium jamaicense), indicating the importance of carbon structure, and species identity on breakdown rates.

Synthesis. In oligotrophic ecosystems, nutrients are often the primary driver of organic matter breakdown. However, we found that variation in macrophyte breakdown rates in oligotrophic coastal wetlands was also explained by salinity and associated seawater chemistry, emphasising the need to understand how saltwater intrusion will alter organic matter processing in wetlands. Our results suggest that marine subsidies associated with sea‐level rise have the potential to accelerate leaf litter breakdown. The increase in breakdown rates could either be buffered or increase further as sea‐level rise also shifts macrophyte community composition to more or less recalcitrant species.