bluuebunny/crossref_metadata_2025_split huggingface dataset:
The amino acid permease Byc1 is involved in calcineurin-dependent thermos-tolerance inCryptococcus neoformans
Authors: Lee Kyung-Tae , Giner Madeline , Bahn Daniel , Cornitius Courtney P. , Lee Soo Chan 
Published: February 2024

AbstractCryptococcosis is one of the most serious infectious fungal diseases. It is known to infect the human respiratory tract and central nervous system and cause meningitis and encephalitis, especially in patients with AIDS. In the sub-Saharan area, cryptococcosis causes more mortality than tuberculosis.Cryptococcus neoformansis the etiological agent. There has been a growing number of reports of antifungal resistance inC. neoformans, and this fungus is also primarily resistant to the newest antifungal drug class, the echinocandins. Despite advances in modern medicine, the morbidity and mortality ofC. neoformansinfections remain unacceptably high. InC. neoformans, calcineurin, a serine/threonine phosphatase, is required for growth at the human host temperature, and calcineurin mutants are not virulent in murine models of cryptococcal meningitis. Therefore, calcineurin has long been considered an antifungal target. However, calcineurin is highly conserved in fungi and humans, and thus direct pharmacological inhibition of calcineurin can risk lowering host immunity as the human calcineurin is required for T-cell responses. A previous study demonstrated that there is a link between calcineurin, an amino acid permease, and protein kinase A’s in Mucorales. In this study, we further reveal the existence of a novel link between calcineurin and an amino acid permease, Byc1, for a thermo-tolerance phenotype in this fungus. We found that calcineurin negatively regulates the expression of theBYC1gene and thatbyc1Δ mutants are partially resistant to FK506. Moreover, we revealed that overexpression of theBYC1gene recapitulates the calcineurin mutants’ thermos-sensitive phenotypes, including FK506 sensitivity and lowered virulence in a murine infection model. We also found that protein kinase A (Pka1) mutants are also partially resistant to FK506. These results support the link between calcineurin, Byc1, and Pka1 inC. neoformansand will serve as a platform for developing novel antifungal drugs against the calcineurin pathway without directly targeting the phosphatase.
Decoding Motor Excitability in TMS using EEG-Features: An Exploratory Machine Learning Approach
Authors: Haxel Lisa , Belardinelli Paolo , Ermolova Maria , Humaidan Dania , Macke Jakob H. , Ziemann Ulf 
Published: February 2024

AbstractBackgroundWith the burgeoning interest in personalized treatments for brain network disorders, closed-loop transcranial magnetic stimulation (TMS) represents a promising frontier. Relying on the real-time adjustment of stimulation parameters based on brain signal decoding, the success of this approach depends on the identification of precise biomarkers for timing the stimulation optimally.ObjectiveWe aimed to develop and validate a supervised machine learning framework for the individualized prediction of motor excitability states, leveraging a broad spectrum of sensor and source space EEG features.MethodsOur approach integrates multi-scale EEG feature extraction and selection within a nested cross-validation scheme, tested on a cohort of 20 healthy participants. We assessed the framework’s performance across different classifiers, feature sets, and experimental protocols to ensure robustness and generalizability.ResultsPersonalized classifiers demonstrated a statistically significant mean predictive accuracy of 72 ± 11%. Consistent performance across various testing conditions highlighted the sufficiency of sensor-derived features for accurate excitability state predictions. Subtype analysis revealed distinct clusters linked to specific brain regions and oscillatory features as well as the need for a more extensive feature set for effective biomarker identification than conventionally considered.ConclusionsOur machine learning framework effectively identifies predictive biomarkers for motor excitability, holding potential to enhance the efficacy of personalized closed-loop TMS interventions. While the clinical applicability of our findings remains to be validated, the consistent performance across diverse testing conditions and the efficacy of sensor-only features suggest promising avenues for clinical research and wider applications in brain signal classification.
A Drug Screening Platform for Protein Expression Levels in Neurological Disorders
Authors: Emran Farida , Kays Ibrahim , Lo Chiu-An , Li Yueyang , Chen Brian E. 
Published: February 2024

SummaryNeurological and psychiatric diseases and disorders affect more than half of the population. Many of these diseases are caused by the malfunctioning of protein synthesis, where too little or too much production of a protein harms a cell and its functions within the brain. We developed a drug screening platform to identify compounds that target the primary cause of these diseases, namely protein expression amounts. This cellular assay monitors protein expression of a target disease gene along with the protein expression of a control gene using the Protein Quantitation Ratioing (PQR) technique. PQR tracks protein concentration using fluorescence. We used human cells and CRISPR-Cas9 genome editing to insert theProtein Quantitation Reporterinto target genes. These cells are used in high-throughput drug screening measuring the fluorescence as the assay. Drug hits can be validated using the same PQR technique or animal models of the disease.HighlightsThe assay can identify drugs that directly address the molecular cause of a disease.The Protein Quantitation Ratioing (PQR) technique allows for tracking and measuring protein amounts over time in single living cells before, during, and after drug administration.Genome editing to insert thePQRinto the target gene allows tracking of endogenous protein expression.Using human cell lines allow for faster production of knock-in cells.Patient mutations can be replicated using genome editing during the knock-in step.Using induced pluripotent stem cells allow for an unlimited supply of genome edited differentiated cells such as neurons with thePQRknock-in reporter.
Protocol for an individual-level, two arm, superiority RCT within an adaptive platform trial: Enhanced patient counselling and SMS reminder messages to improve access to community-based eye care services in Meru, Kenya
Authors: Allen Luke , Kim Min , Gichangi Michael , Macleod David , Carpenter James , Tlhajoane Malebogo , Karanja Sarah , Bolster Nigel , Burton Matthew , Bastawrous Andrew 
Published: February 2024

AbstractBackgroundThe Vision Impact Project (VIP) is a major community-based eye screening programme running in Kenya with the aim of promoting eye health for all. Previous studies embedded within the programme in Meru County have found that a third of people who are screened require care for an eye problem, however only half of these people manage to access outreach treatment clinics. Access varies between sociodemographic groups, and only 30% of young adults (18-44 years old) were able to access care. In previous mixed-methods work our team conducted interviews and surveys with non-attenders from this ‘left-behind’ group to explore what could be done to improve access.MethodsYounger adults told us that better counselling at the point of referral would be likely to improve attendance rates. Based on their feedback, we have developed a script that will be read to participants in the intervention arm at the point of referral, and then sent as a reminder SMS the following day. We will assess whether attendance rates are higher among those randomised to receive this enhanced counselling compared to those who receive standard care. The primary outcome will be the proportion of people from the left-behind group who attend triage clinic. Our secondary analysis will examine overall mean attendance across all groups. We will calculate Bayesian posterior probabilities of attendance in each arm every seven days and continually recruit participants until one of two stopping rules have been met: there is a >95% probability that one arm is best or there is a >95% probability that the difference between the arms is <1%.DiscussionThis Bayesian RCT will be embedded into the clinical workflow software that is used to manage referrals and clinic attendance. It will test whether a simple, low-cost, service user-derived intervention is able to improve access to services among a population group that is currently being left behind.Trial RegistrationISRCTN11329596, Registered on 02 February 2024Administrative Information
Fast, efficient and accurate prediction of postoperative outcomes using a small set of intraoperative time series
Authors: Shorten David P. , Beckingham Tim , Humphries Melissa , Fischer Roy , Soar Natalie , Wilson Bill , Roughan Matthew 
Published: February 2024

AbstractIn the period immediately following surgery, patients are at high risk of various negative outcomes such as Acute Kidney Injury (AKI) and Myocardial Infarction (MI). Identifying patients at increased risk of developing these complications assists in their prevention and management. During surgery, rich time series data of vital signs and ventilator parameters are collected. This data holds enormous potential for the prediction of postoperative outcomes. There is, however, minimal work exploring this potential. Moreover, existing approaches rely on deep learning, which is computationally expensive, often requiring specialized hardware and significant energy consumption. We demonstrate that it is possible to extract substantial value from intraoperative time series using techniques that are extremely computationally efficient. We used recordings from 66 300 procedures at the Lyell McEwin Hospital (Adelaide, South Australia), occurring in 2013 through 2020. The procedures associated with 80% of the patients were used for model training, with the remainder held out for testing. A combination of techniques including MultiRocket, Multitask and logistic regression were used to predict Rapid Response Team (RRT) calls within 48 hours of surgery and mortality, AKI and elevated troponin levels within 30 days of surgery. This approach achieved an Area Under the Receiver Operating Characteristic curve (AUROC) (95% CI) on the test data of 0.96 (0.95-0.97) for mortality, 0.85 (0.84-0.87) for AKI, 0.89 (0.87-0.91) for elevated troponin levels and 0.80 (0.78-0.83) for RRT calls, outperforming the ASA score and Charlson comorbidity index on the test population for all outcomes. These results show that roughly equivalent accuracy to computationally expensive modelling approaches using diverse sources of clinical data can be achieved using highly computationally efficient techniques and only a small set of automatically recorded intraoperative time series. This implies substantial potential in the analysis of these time series for the improvement of perioperative patient care. We also performed an analysis of the measurement sampling rate required to achieve these results, demonstrating the advantage of high-frequency patient vitals monitoring.
Evaluation of cerebrospinal fluid alpha-synuclein seed amplification assay in PSP and CBS
Authors: Vaughan DP , Fumi R , Theilmann Jensen M , Georgiades T , Wu L , Lux D , Obrocki R , Lamoureux J , Ansorge O , Allinson KSJ , Warner TT , Jaunmuktane Z , Misbahuddin A , Leigh PN , Ghosh BCP , Bhatia KP , Church A , Kobylecki C , Hu MTM , Rowe JB , Blauwendraat C , Morris HR , Jabbari E 
Published: February 2024

AbstractBackgroundSeed amplification assay (SAA) testing has become an important biomarker in the diagnosis of alpha-synuclein related neurodegenerative disorders.ObjectivesTo assess the rate of alpha-synuclein SAA positivity in progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS), and analyse the clinical and pathological features of SAA positive and negative cases.Methods106 CSF samples from clinically diagnosed PSP (n=59), CBS (n=37) and indeterminate parkinsonism cases (n=10) were analysed using alpha-synuclein SAA.ResultsThree cases (1 PSP, 2 CBS) were Multiple System Atrophy (MSA)-type SAA positive. 5/59 (8.5%) PSP cases were Parkinson’s disease (PD)-type SAA positive, and these cases were older and had a shorter disease duration compared with SAA negative cases. In contrast, 9/35 (25.7%) CBS cases were PD-type SAA positive.ConclusionsOur results suggest that PD-type seeds can be detected in PSP and CBS using a CSF alpha-synuclein SAA, and in PSP this may impact on clinical course.
WITHDRAWN: Exploring the power of structural brain MRI and clinical measures in predicting AD neuropathology: a machine learning approach
Authors: Kamal Farooq , Morrison Cassandra , Oliver Michael D. , Dadar Mahsa 
Published: February 2024

Withdrawal Statement**The authors have withdrawn their manuscript owing to data access requirements. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.
Stiffness Measurement of Retinal Capillaries and Subendothelial Matrix using Atomic Force Microscopy
Authors: Tierno Irene Santiago , Agarwal Mahesh , Matisioudis Nikolaos , Chandrakumar Sathishkumar , Ghosh Kaustabh 
Published: February 2024

ABSTRACTRetinal capillary degeneration is a clinical hallmark of the early stages of diabetic retinopathy (DR). Our recent studies have revealed that diabetes-induced increase in retinal capillary stiffness plays a crucial and previously unrecognized causal role in inflammation-mediated degeneration of retinal capillaries. Retinal capillary stiffening results from overexpression of lysyl oxidase, an enzyme that crosslinks and stiffens the subendothelial matrix. Since tackling DR at the early stage is expected to prevent or slow down DR progression and associated vision loss, subendothelial matrix and capillary stiffness represent relevant and novel therapeutic targets for early DR management. Further, direct measurement of retinal capillary stiffness can serve as a crucial preclinical validation step for the development of new imaging techniques for non-invasive assessment of retinal capillary stiffness in animal and human subjects. With this view in mind, we here provide a detailed protocol for the isolation and stiffness measurement of mouse retinal capillaries and retinal subendothelial matrix using atomic force microscopy.
GLP1 receptor agonism ameliorates Parkinson’s disease through modulation of neuronal insulin signalling and glial suppression
Authors: Athauda Dilan , Evans James R , Mahoney-Sanchez Laura , Virdi Gurvir S , Lopez-Garcia Patricia , Wernick Anna , Wagen Aaron , D’Sa Karishma , Lachica Joanne , Strohbuecker Stephanie , Vecchi Giulia , Leighton Craig , Saleeb Rebecca S. , O’Shaughnessy Judi , Toomey Christina E. , Vijiaratnam Nirosen , Girges Christine , Li Yazhou , Mustapic Maja , Ismail Khalida , Davies Melanie , Kapogiannis Dimitrios , Choi Minee L , Ryten Mina , Horrocks Mathew H. , Greig Nigel , Foltynie Thomas , Gandhi Sonia 
Published: February 2024

AbstractNeuronal insulin resistance is linked to the pathogenesis of Parkinson’s disease through unclear, but potentially targetable, mechanisms. We delineated neuronal and glial mechanisms of insulin resistance and glucagon-like 1 peptide (GLP-1) receptor agonism in human iPSC models of synucleinopathy, and corroborated our findings in patient samples from a Phase 2 trial of a GLP-1R agonist in Parkinson’s (NCT01971242). Human iPSC models of synucleinopathy exhibit neuronal insulin resistance and dysfunctional insulin signalling, which is associated with inhibition of the neuroprotective Akt pathways, and increased expression of the MAPK-associated p38 and JNK stress pathways. Ultimately, this imbalance is associated with cellular stress, impaired proteostasis, accumulation of α-synuclein, and neuronal loss. The GLP-1R agonist exenatide led to restoration of insulin signalling, associated with restoration of Akt signalling and suppression of the MAPK pathways in neurons. GLP-1R agonism reverses the neuronal toxicity associated with the synucleinopathy, through reduction of oxidative stress, improved mitochondrial and lysosomal function, reduced aggregation of α-synuclein, and enhanced neuronal viability. GLP-1R agonism further suppresses synuclein induced inflammatory states in glia, leading to neuroprotection through non cell autonomous effects. In the exenatide-PD2 clinical trial, exenatide treatment was associated with clinical improvement in individuals with higher baseline MAPK expression (and thus insulin resistance). Exenatide treatment led to a reduction of α-synuclein aggregates, and a reduction in inflammatory cytokine IL-6. Taken together, our patient platform defines the mechanisms of GLP-1R action in neurons and astrocytes, identifies the population likely to benefit from GLP-1R agonism, and highlights the utility of GLP-1R agonism as a disease modifying strategy in synucleinopathies.
PhysMAP - interpretablein vivoneuronal cell type identification using multi-modal analysis of electrophysiological data
Authors: Lee Eric Kenji , Gül Asım Emre , Heller Greggory , Lakunina Anna , Jaramillo Santiago , Przytycki Pawel F. , Chandrasekaran Chandramouli 
Published: February 2024

AbstractCells of different types perform diverse computations and coordinate their activity during sensation, perception, and action. While electrophysiological approaches can measure the activity of many neurons simultaneously, assigning cell type labels to these neurons is an open problem. Here, we develop PhysMAP, a framework that weighs multiple electrophysiological modalities simultaneously in an unsupervised manner and obtain an interpretable representation that separates neurons by cell type. PhysMAP is superior to any single electrophysiological modality in identifying neuronal cell types such as excitatory pyramidal, PV+interneurons, and SOM+interneurons with high confidence in both juxtacellular and extracellular recordings and from multiple areas of the mouse brain. PhysMAP built on ground truth data can be used for classifying cell types in new and existing electrophysiological datasets, and thus facilitate simultaneous assessment of the coordinated dynamics of multiple neuronal cell types during behavior.
Interneuron loss and microglia activation by transcriptome analyses in the basal ganglia of Tourette syndrome
Authors: Wang Yifan , Fasching Liana , Wu Feinan , Huttner Anita , Berretta Sabina , Roberts Rosalinda , Leckman James F. , Abyzov Alexej , Vaccarino Flora M. 
Published: February 2024

AbstractTourette syndrome (TS) is a disorder of high-order integration of sensory, motor, and cognitive functions afflicting as many as 1 in 150 children and characterized by motor hyperactivity and tics. Despite high familial recurrence rates, a few risk genes and no biomarkers have emerged as causative or predisposing factors. The syndrome is believed to originate in basal ganglia, where patterns of motor programs are encoded. Postmortem immunocytochemical analyses of brains with severe TS revealed decreases in cholinergic, fast-spiking parvalbumin, and somatostatin interneurons within the striatum (caudate and putamen nuclei). Here, we performed single cell transcriptomic and chromatin accessibility analyses of the caudate nucleus from 6 adult TS and 6 control post-mortem brains. The data reproduced the known cellular composition of the adult human striatum, including a majority of medium spiny neurons (MSN) and small populations of GABAergic and cholinergic interneurons. Comparative analysis revealed that interneurons were decreased by roughly 50% in TS brains, while no difference was observed for other cell types. Differential gene expression analysis suggested that mitochondrial function, and specifically oxidative metabolism, in MSN and synaptic function in interneurons are both impaired in TS subjects. Furthermore, such an impairment was coupled with activation of immune response pathways in microglia. Also, our data explicitly link gene expression changes to changes in cis-regulatory activity in the corresponding cell types, suggesting de-regulation as a factor for the etiology of TS. These findings expand on previous research and suggest that impaired modulation of striatal function by interneurons may be the origin of TS symptoms.
Transient inhibition of cell division in competent pneumococcal cells results from deceleration of the septal peptidoglycan complex
Authors: Juillot Dimitri , Billaudeau Cyrille , Barbotin Aurélien , Lablaine Armand , Mortier-Barrière Isabelle , Polard Patrice , Campo Nathalie , Carballido-Lopez Rut 
Published: February 2024

AbstractBacterial cells are known to produce inhibitors of cell division in response to stress responses and developmental programs. Knowledge of the underlying molecular mechanisms remains however largely limited. In this study, we investigated the mechanism of transient cell division inhibition observed during the development of competence for transformation in the human pathogenStreptococcus pneumoniae. In this species, ComM, a membrane protein specifically produced during competence, transiently inhibits cell division to preserve genomic integrity during transformation. We show that ComM reduces specifically the dynamics of the septal peptidoglycan synthetic complex FtsW:PBP2x. We also present evidence that ComM interacts with the peptidoglycan precursor synthetic enzyme MurA, and show that overproduction of MurA suppresses FtsW:PBP2x deceleration along the cell division delay in competent cells. Collectively, our data support a model in which ComM interferes with MurA activity to reduce septal peptidoglycan synthesis during competence inS. pneumoniae.
Electrophysiological dynamics of salience, default mode, and frontoparietal networks during episodic memory formation and recall: A multi-experiment iEEG replication
Authors: Das Anup , Menon Vinod 
Published: February 2024

AbstractDynamic interactions between large-scale brain networks underpin human cognitive processes, but their electrophysiological mechanisms remain elusive. The triple network model, encompassing the salience (SN), default mode (DMN), and frontoparietal (FPN) networks, provides a framework for understanding these interactions. We analyzed intracranial EEG recordings from 177 participants across four diverse episodic memory experiments, each involving encoding as well as recall phases. Phase transfer entropy analysis revealed consistently higher directed information flow from the anterior insula (AI), a key SN node, to both DMN and FPN nodes. This directed influence was significantly stronger during memory tasks compared to resting-state, highlighting the AI’s task-specific role in coordinating large-scale network interactions. This pattern persisted across externally-driven memory encoding and internally-governed free recall. Control analyses using the inferior frontal gyrus (IFG) showed an inverse pattern, with DMN and FPN exerting higher influence on IFG, underscoring the AI’s unique role. We observed task-specific suppression of high-gamma power in the posterior cingulate cortex/precuneus node of the DMN during memory encoding, but not recall. Crucially, these results were replicated across all four experiments spanning verbal and spatial memory domains with high Bayes replication factors. Our findings advance understanding of how coordinated neural network interactions support memory processes, highlighting the AI’s critical role in orchestrating large-scale brain network dynamics during both memory encoding and retrieval. By elucidating the electrophysiological basis of triple network interactions in episodic memory, our study provides insights into neural circuit dynamics underlying memory function and offer a framework for investigating network disruptions in memory-related disorders.