bluuebunny/crossref_metadata_2025 huggingface dataset:
Rapid evolution of genes with anti-cancer functions during the origins of large bodies and cancer resistance in elephants
Authors: Bowman Jacob , Lynch Vincent J.
Published: February 2024

Elephants have emerged as a model system to study the evolution of body size and cancer resistance because, despite their immense size, they have a very low prevalence of cancer. Previous studies have found that duplication of tumor suppressors at least partly contributes to the evolution of anti-cancer cellular phenotypes in elephants. Still, many other mechanisms must have contributed to their augmented cancer resistance. Here, we use a suite of codon-based maximum-likelihood methods and a dataset of 13,310 protein-coding gene alignments from 261Eutherianmammals to identify positively selected and rapidly evolving elephant genes. We found 496 genes (3.73% of alignments tested) with statistically significant evidence for positive selection and 660 genes (4.96% of alignments tested) that likely evolved rapidly in elephants. Positively selected and rapidly evolving genes are statistically enriched in gene ontology terms and biological pathways related to regulated cell death mechanisms, DNA damage repair, cell cycle regulation, epidermal growth factor receptor (EGFR) signaling, and immune functions, particularly neutrophil granules and degranulation. All of these biological factors are plausibly related to the evolution of cancer resistance. Thus, these positively selected and rapidly evolving genes are promising candidates for genes contributing to elephant-specific traits, including the evolution of molecular and cellular characteristics that enhance cancer resistance.
Inhibition of SARS-CoV-2 infection byPorphyromonas gingivalisand the oral microbiome
Authors: Bontempo Alexander , Chirino Alexandra , Heidari Alireza , Lugo Alexandra , Shindo Satoru , Pastore Maria R. , Antonson Sibel A. , Godoy Cristina , Nichols Frank C. , Potempa Jan , Davey Mary Ellen , Kawai Toshihisa , Cayabyab Mark J.
Published: February 2024

The COVID-19 pandemic persists despite the availability of vaccines, and it is therefore crucial to develop new therapeutic and preventive approaches. In this study, we investigated the potential role of the oral microbiome in SARS-CoV-2 infection. Using anin vitroSARS-CoV-2 pseudovirus infection assay, we found a potent inhibitory effect exerted byPorphyromonas gingivalison SARS-CoV-2 infection mediated by knownP. gingivaliscompounds such as phosphoglycerol dihydroceramide (PGDHC) and gingipains as well as by unknown bacterial factors. We found that the gingipain-mediated inhibition of infection is likely due to cytotoxicity, while PGDHC inhibited virus infection by an unknown mechanism. Unidentified factors present inP. gingivalissupernatant inhibited SARS-CoV-2 likely via the fusion step of the virus life cycle. We addressed the role of other oral bacteria and found certain periodontal pathogens capable of inhibiting SARS-CoV-2 pseudovirus infection by inducing cytotoxicity on target cells. In the human oral cavity, we observed the modulatory activity of oral microbial communities varied among individuals in that some saliva-based cultures were capable of inhibiting while others were enhancing infection. These findings contribute to our understanding of the complex relationship between the oral microbiome and viral infections, offering potential avenues for innovative therapeutic strategies in combating COVID-19.
Absence seizures and sleep abnormalities in a rat model ofGRIN2Bneurodevelopmental disorder
Authors: Hristova Katerina , Fasol Melissa C. , McLaughlin Niamh , Nawaz Sarfaraz , Taskiran Mehmet , Buller-Peralta Ingrid , Bassi Alejandro , Ocampo-Garces Adrian , Escudero Javier , Kind Peter C. , Gonzalez-Sulser Alfredo
Published: February 2024

Pathogenic mutations inGRIN2Bare an important cause of severe neurodevelopmental disorders resulting in epilepsy, autism and intellectual disability.GRIN2Bencodes the GluN2B subunit of N-methyl-D-aspartate receptors (NMDARs), which are ionotropic glutamate receptors critical for normal development of the nervous system and synaptic plasticity. Here, we characterized a novelGRIN2Bheterozygous knockout rat model with 24-hour EEG recordings. We found rats heterozygous for the deletion (Grin2b+/-) had a higher incidence of spontaneous absence seizures than wild-type rats (Grin2b+/+). Spike and wave discharges, the electrographic correlate of absences seizures, were longer in duration and displayed increased higher overall spectral power inGrin2b+/-animals than those inGrin2b+/+. Heterozygous mutant rats also had abnormal sleep-wake brain state dynamics over the circadian cycle. Specifically, we identified a reduction in total rapid eye movement sleep and, altered distributions of non-rapid eye movement sleep and wake epochs, when compared to controls. This was accompanied by an increase in overall spectral power during non-rapid eye movement sleep inGrin2b+/-. The sleep-wake phenotypes were largely uncorrelated to the incidence of spike and wave discharges. We then tested the antiseizure efficacy of ethosuximide, a T-type voltage-gated calcium channel blocker used in the treatment of absence seizures, and memantine, a noncompetitive NMDAR antagonist currently explored as a mono or adjunctive treatment option in NMDAR related neurodevelopmental disorders. Ethosuximide reduced the number and duration of spike and wave discharges, while memantine did not affect the number of spike and wave discharges but reduced their duration. These results highlight two potential therapeutic options forGRIN2Brelated epilepsy. Our data shows the new ratGRIN2Bhaploinsufficiency model exhibits clinically relevant phenotypes. As such, it could prove crucial in deciphering underlying pathological mechanisms and developing new therapeutically translatable strategies forGRIN2Bneurodevelopmental disorders.
Distinct Dendritic Morphological Changes in the Nucleus Accumbens of Microbiota-deficient Male Mice
Authors: García-Cabrerizo Rubén , Viola Maria Francesca , Luczynski Pauline , Clarke Gerard , Cryan John F.
Published: February 2024

The gut microbiota has been shown to be an important regulator of brain and behaviour. Germ-free rodents are a key model to study the microbiome-gut-brain axis to reveal the microbial underpinnings of diseases, including those related to psychiatric illnesses. The present study evaluated whether the absence of gut microbiota could alter the morphological development of the nucleus accumbens, a brain region located in the ventral striatum involved in stress, mood and addiction. In germ-free mice, there was dendritic hypertrophy of medium spiny neurons in the shell and dendritic elongation in the core. This led to an increase in the number of stubby dendritic spines within the shell and an increase in both stubby and thin spines in the core. Taken together, these results indicate that the gut microbiota is essential for the normal development of the dendritic structure of medium spiny neurons in the nucleus accumbens and that altered remodelling may contribute to maladaptive psychiatric disorders.
The Douglas Bell Canada Brain Bank Post-mortem Brain Imaging Protocol
Authors: Dadar Mahsa , Sanches Liana , Fouqouet Jeremie , Moqadam Roqaie , Alasmar Zaki , Miraut Dominique , Maranzano Josefina , Mechawar Naguib , Chakravarty M. Mallar , Zeighami Yashar
Published: February 2024

Magnetic resonance imaging (MRI) is a valuable non-invasive tool that has been widely used for in vivo investigations of brain morphometry and microstructural characteristics. Postmortem MRIs can provide complementary anatomical and microstructural information to in vivo imaging and ex vivo neuropathological assessments without compromising the sample for future investigations. We have developed a postmortem MRI protocol for the brain specimens of the Douglas-Bell Canada Brain Bank (DBCBB), the largest brain bank in Canada housing over 3000 neurotypical and diseased brain specimens, that allows for acquisition of high-resolution 3T and 7T MRIs. Our protocol can be used to scan DBCBB specimens with minimal tissue manipulation, allowing for feasibly scanning large numbers of postmortem specimens while retaining the quality of the tissue for downstream histology and immunohistochemistry assessments. We demonstrate the robustness of this protocol in spite of the dependency of image quality on fixation by acquiring data on the first day of extraction and fixation, to over twenty years post fixation. The acquired images can be used to perform volumetric segmentations, cortical thickness measurements, and quantitative analyses which can be potentially used to link MRI-derived and ex vivo histological measures, assaying both the normative organization of the brain and ex vivo measures of pathology.
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

Cryptococcosis 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

Background

With 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.

Objective

We 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.

Methods

Our 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.

Results

Personalized 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.

Conclusions

Our 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.
One Hundred Years of Influenza A Evolution
Authors: Nielsen Bjarke Frost , Berrig Christian , Grenfell Bryan T. , Andreasen Viggo
Published: February 2024

Leveraging the simplicity of raw nucleotide distances, we provide an intuitive window into the evolution of the human influenza A ‘nonstructural’ (NS) gene. In an analysis suggested by the eminent Danish biologist Freddy B. Christiansen, we illustrate the existence of a continuous genetic “backbone” of influenza A NS genes, steadily increasing in distance to the 1918 root over more than a century. Interestingly, the 2009 influenza pandemic represents a clear departure from this enduring genetic backbone. Utilizing nucleotide distance maps and phylogenetic analyses, we illustrate remaining uncertainties regarding the origin of the 2009 pandemic, highlighting the complexity of influenza evolution. The NS gene is interesting precisely because it experiences neutral genetic drift over long periods of time time, while sudden deviations from this drift pattern can indicate changes in other genes via the hitchhiking effect. Our approach employs two measures based on genotypic distance — the rooted temporal Hamming map and the unrooted temporal Hamming distribution — to analyze the evolutionary dynamics of the NS gene. The rooted Hamming map elucidates distances between a reference sequence and all other sequences over time. In contrast, the unrooted temporal Hamming distribution captures the distribution of genotypic distances between simultaneously circulating viruses, thereby revealing patterns of sequence diversity and epi-evolutionary dynamics. Our study aims to supplement traditional tree-based phylogenetic inference with these direct temporal distance-based measures, offering transparent insights into the evolution of the influenza NS gene.
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

Neurological 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.

Highlights

The 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

Background

The 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.

Methods

Younger 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%.

Discussion

This 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 Registration

ISRCTN11329596, Registered on 02 February 2024

Administrative 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

In 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

Background

Seed amplification assay (SAA) testing has become an important biomarker in the diagnosis of alpha-synuclein related neurodegenerative disorders.

Objectives

To 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.

Methods

106 CSF samples from clinically diagnosed PSP (n=59), CBS (n=37) and indeterminate parkinsonism cases (n=10) were analysed using alpha-synuclein SAA.

Results

Three 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.

Conclusions

Our 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

Retinal 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

Neuronal 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

Cells 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

Tourette 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

Bacterial 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

Abstract

Dynamic 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.
Constitutive upregulation of transcription factors underlies permissive bradyzoite differentiation in a natural isolate ofToxoplasma gondii
Authors: Xia Jing , Fu Yong , Huang Wanyi , Sibley L. David
Published: February 2024

Toxoplasma gondiibradyzoites play a critical role in pathology due to their long-term persistence in intermediate hosts and their potential to reactivate, resulting in severe diseases in immunocompromised individuals. Currently there is no effective treatment for eliminating bradyzoites. Hence, betterin vitromodels ofT. gondiicyst development would facilitate identification of therapeutic targets for bradyzoites. Herein we characterized a natural isolate ofT. gondii, called Tg68, which showed slowerin vitroreplication of tachyzoites, and permissive bradyzoite development under stress conditionsin vitro. Transcriptional analysis revealed constitutive expression in Tg68 tachyzoites of the key regulators of bradyzoite development includingBFD1,BFD2, and several AP2 factors. Consistent with this finding, Tg68 tachyzoites expressed high levels of bradyzoite-specific genes includingBAG1,ENO1, andLDH2. Moreover, after stress induced differentiation, Tg68 bradyzoites exhibited gene expression profiles of mature bradyzoites, even at early time points. These data suggest that Tg68 tachyzoites exist in a pre-bradyzoite stage primed to readily develop into mature bradyzoites under stress conditionsin vitro. Tg68 presents a novel model for differentiationin vitrothat will serve as a useful tool for investigation of bradyzoite biology and development of therapeutics.

Significance

Toxoplasma gondiiis a widespread protozoan that chronically infects ∼30% of the world’s population.T. gondiican differentiate between the fast-growing life stage that causes acute infection and the slow-growing stage that persists in the host for extended periods of time. The slow-growing stage cannot be eliminated by the host immune response or currently known antiparasitic drugs. Studies on the slow-growing stage have been limited due to the limitations ofin vivoexperiments and the challenges ofin vitromanipulation. Here, we characterize a natural isolate ofT. gondii, which constitutively expresses factors that drive development and that is permissive to convert to the slow-growing stage under stress conditionsin vitro. The strain presents a novelin vitromodel for studying the chronic phase of toxoplasmosis and identifying new therapeutic treatments for chronic infections.
Monkey Prefrontal Cortex Learns to Minimize Sequence Prediction Error
Authors: Cheng Huzi , Chafee Matthew V. , Blackman Rachael K. , Brown Joshua W.
Published: February 2024

In this study, we develop a novel recurrent neural network (RNN) model of pre-frontal cortex that predicts sensory inputs, actions, and outcomes at the next time step. Synaptic weights in the model are adjusted to minimize sequence prediction error, adapting a deep learning rule similar to those of large language models. The model, called Sequence Prediction Error Learning (SPEL), is a simple RNN that predicts world state at the next time step, but that differs from standard RNNs by using its own prediction errors from the previous state predictions as inputs to the hidden units of the network. We show that the time course of sequence prediction errors generated by the model closely matched the activity time courses of populations of neurons in macaque prefrontal cortex. Hidden units in the model responded to combinations of task variables and exhibited sensitivity to changing stimulus probability in ways that closely resembled monkey prefrontal neurons. Moreover, the model generated prolonged response times to infrequent, unexpected events as did monkeys. The results suggest that prefrontal cortex may generate internal models of the temporal structure of the world even during tasks that do not explicitly depend on temporal expectation, using a sequence prediction error minimization learning rule to do so. As such, the SPEL model provides a unified, general-purpose theoretical framework for modeling the lateral prefrontal cortex.
Sci-comm “behind the scenes”: Gendered narratives of scientific outreach activities in the life sciences
Authors: Beasley-Hall Perry G. , Papadelos Pam , Hewitt Anne , Lassaline Charlotte R. , Umbers Kate D. L. , Guzik Michelle T.
Published: February 2024

Science communication, orsci-comm, is a broad term describing activities seeking to increase scientific literacy. Sci-comm has a positive impact on perceptions of science, public policy, public scientific literacy, and career choices of future scientists. Yet, sci-comm is often viewed as at odds with, or tangential, to academic achievement, as non-scientific, or as less worthy a time commitment compared to internal communication in academia. In Australia, scientific societies and organisations engage in a range of activities underpinned by communal, or so-called “behind-the-scenes”, sci-comm work by individuals done almost exclusively on a voluntary basis. Given an apparent undervaluing of sci-comm work in academia, we established a pilot study to investigate who does this work, in what capacity, and why. A semi-structured online survey was administered to 88 Australian life sciences organisations for dissemination to their members, and 49 responses were received. Respondents were mostly women in early-career researcher positions at universities. Participants almost universally agreed that their sci-comm contributions to organisations were not beneficial to career progression. Some participants suggested that this perception might stem from it being perceived as feminised or categorised as “care work”, potentially resulting in its undervaluation. However, most also cited a range of personal and professional benefits gained from the work, including giving back to the general public and scientific community, and developing skills relevant to translating scientific research. The majority of survey respondents indicated that they were likely to continue such work in the future. Gaining a deeper understanding of the motivations behind, and perceptions of, behind-the-scenes sci-comm work will aid in overcoming barriers that disproportionately affect women, and promote better acknowledgement and recognition of their contributions in the future.
Dynamic reinforcement learning reveals time-dependent shifts in strategy during reward learning
Authors: Venditto Sarah Jo C , Miller Kevin J , Brody Carlos D , Daw Nathaniel D
Published: February 2024

Different brain systems have been hypothesized to subserve multiple “experts” that compete to generate behavior. In reinforcement learning, two general processes, one model-free (MF) and one model-based (MB), are often modeled as a mixture of agents (MoA) and hypothesized to capture differences between automaticity vs. deliberation. However, shifts in strategy cannot be captured by a static MoA. To investigate such dynamics, we present the mixture-of-agents hidden Markov model (MoA-HMM), which simultaneously learns inferred action values from a set of agents and the temporal dynamics of underlying “hidden” states that capture shifts in agent contributions over time. Applying this model to a multi-step, reward-guided task in rats reveals a progression of within-session strategies: a shift from initial MB exploration to MB exploitation, and finally to reduced engagement. The inferred states predict changes in both response time and OFC neural encoding during the task, suggesting that these states are capturing real shifts in dynamics.
A ventral hippocampal-lateral septum pathway regulates social novelty preference
Authors: Rashid Maha , Thomas Sarah , Isaac Jennifer , Karkare Sonia , Klein Hannah , Murugan Malavika
Published: February 2024

The ability to distinguish strangers from familiar individuals is crucial for the survival of most mammalian species. In humans, an inability to recognize kin and familiar individuals and engage in appropriate behaviors is associated with several types of dementia, including Alzheimer’s disease. Mice preferentially spend more time investigating a novel individual relative to a familiar individual. Yet, how social novelty related information drives increased investigation of the novel animal remains poorly understood. Recent evidence has implicated the ventral hippocampus (vHPC) as a key node in encoding information about conspecific identity. Of particular interest are vHPC projections to the lateral septum (LS), a region that has been implicated in driving a wide range of motivated social behaviors. In this study using chemogenetics, optogenetics and monosynaptic rabies tracing, we identified a novel vHPC-LS-ventral tegmental area (VTA) pathway that is necessary for mice to preferentially investigate novel conspecifics. Using monosynaptic rabies tracing, we established that LS neurons make direct monosynaptic connections onto dopaminergic neurons in the VTA. Thus, we have identified a potential pathway via which conspecific identity could be transformed to drive motivated social behaviors.
Unified description of DGLAP, CSS, and BFKL evolution: TMD factorization bridging large and small
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Authors: Mukherjee Swagato , Skokov Vladimir V. , Tarasov Andrey , Tiwari Shaswat
Published: February 2024

This paper introduces a transverse-momentum dependent (TMD) factorization scheme designed to unify both large and small Bjorken-x regimes. We compute the next-to-leading order quantum chromodynamics (QCD) corrections to the gluon TMD operator for an unpolarized hadron within this proposed scheme. This leads to the emergence of a new TMD evolution, incorporating those in transverse momentum, rapidity, and Bjorken-x. When matched to the collinear factorization scheme, our factorization scheme faithfully reproduces the well-established Dokshitzer-Gribov-Lipatov-Altarelli-Parisi and Collins-Soper-Sterman (CSS) evolutions. Conversely, matching with high-energy factorization not only yields the Balitsky-Fadin-Kuraev-Lipatov evolution but also reveals distinctive signatures of CSS logarithms. The development of this novel TMD factorization scheme, capable of seamlessly reconciling disparate Bjorken-x regimes and faithfully reproducing established QCD evolution equations, has the potential to significantly advance our comprehension of high-energy processes and three-dimensional parton structures of hadrons.

Published by the American Physical Society
2024
Effective Field Theory for Extreme Mass Ratio Binaries
Authors: Cheung Clifford , Parra-Martinez Julio , Rothstein Ira Z. , Shah Nabha , Wilson-Gerow Jordan
Published: February 2024

We derive an effective field theory describing a pair of gravitationally interacting point particles in an expansion in their mass ratio, also known as the self-force (SF) expansion. The 0SF dynamics are trivially obtained to all orders in Newton’s constant by the geodesic motion of the light body in a Schwarzschild background encoding the gravitational field of the heavy body. The corrections at 1SF and higher are generated by perturbations about this configuration—that is, the geodesic deviation of the light body and the fluctuation graviton—but crucially supplemented by an operator describing the recoil of the heavy body as it interacts with the smaller companion. Using this formalism we compute new results at third post-Minkowskian order for the conservative dynamics of a system of gravitationally interacting massive particles coupled to a set of additional scalar and vector fields.

Published by the American Physical Society
2024
Automated selection of nanoparticle models for small-angle X-ray scattering data analysis using machine learning
Authors: Monge Nicolas , Deschamps Alexis , Amini Massih-Reza
Published: February 2024

Small-angle X-ray scattering (SAXS) is widely used to analyze the shape and size of nanoparticles in solution. A multitude of models, describing the SAXS intensity resulting from nanoparticles of various shapes, have been developed by the scientific community and are used for data analysis. Choosing the optimal model is a crucial step in data analysis, which can be difficult and time-consuming, especially for non-expert users. An algorithm is proposed, based on machine learning, representation learning and SAXS-specific preprocessing methods, which instantly selects the nanoparticle model best suited to describe SAXS data. The different algorithms compared are trained and evaluated on a simulated database. This database includes 75 000 scattering spectra from nine nanoparticle models, and realistically simulates two distinct device configurations. It will be made freely available to serve as a basis of comparison for future work. Deploying a universal solution for automatic nanoparticle model selection is a challenge made more difficult by the diversity of SAXS instruments and their flexible settings. The poor transferability of classification rules learned on one device configuration to another is highlighted. It is shown that training on several device configurations enables the algorithm to be generalized, without degrading performance compared with configuration-specific training. Finally, the classification algorithm is evaluated on a real data set obtained by performing SAXS experiments on nanoparticles for each of the instrumental configurations, which have been characterized by transmission electron microscopy. This data set, although very limited, allows estimation of the transferability of the classification rules learned on simulated data to real data.