Biology subjects

Price, A.

Publications and source records attributed to Price, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Evasion of Hepatic ILC1 Immunosurveillance Drives Breast Cancer Liver Metastasis

Metastasis, the dissemination of cancer cells to distant organs, is an inefficient process1, yet remains the leading cause of cancer-related mortality2. The cellular barriers and evasion mechanisms governing organ-specific susceptibility remain incompletely understood3-5, hindering the development of effective anti-metastatic therapies6. Here, we show that liver-resident type 1 innate lymphoid cells (ILC1s) constitute an essential immunosurveillance barrier against breast cancer liver metastasis that can be bypassed through either cancer cell intrinsic or host-dependent mechanisms. In a multi-organ metastatic breast cancer patient cohort, liver metastasis occurred later and was associated with poorer survival than lung metastasis, with elevated body mass index emerging as a clinical risk factor. This metabolic vulnerability was recapitulated in mice, where a high-fat diet induced hepatosteatosis and selectively enhanced breast cancer colonization of the liver. Mechanistically, liver and lung colonization were restrained by ILC1s and circulating natural killer (NK) cells, respectively. Following cancer cell challenge, NK cells expanded and activated, employing lytic granule pathways and the death receptor DR5 for clearance, whereas activated ILC1s selectively required high DR5 expression on cancer cells, supported by AP-2a (TFAP2A) mediated transcriptional activation, for effective immunosurveillance. Heterozygous copy number deletion at TNFRSF10B (encoding DR5) in human tumours reduced DR5 expression and predisposed to liver metastasis. Hepatosteatosis further compromised this barrier by reducing IL-15 expression in macrophages, thereby depleting hepatic ILC1s effects reversible with glucagon-like peptide-1 (GLP-1) receptor agonists. Thus, hepatic ILC1s form a critical organ-specific barrier to breast cancer metastasis, vulnerable to both cancer cell-intrinsic DR5 downregulation and host metabolic dysfunction.

immunology↗

bioRxiv2026

Scalable Production of a De Novo SARS-CoV-2 Antiviral miniprotein in Escherichia coli

The rapid emergence of SARS-CoV-2 variants that evade neutralizing antibodies underscores the need for next-generation antiviral biologics that combine molecular precision with scalable, cost-effective manufacturing. Computationally designed miniproteins targeting the receptor-binding domain (RBD) of the spike protein offer a compelling alternative to monoclonal antibodies due to their small size, high thermal stability, and compatibility with microbial expression systems. Here we report the end-to-end development and cGMP production of IPD-52520, a de novo antiviral miniprotein, using an optimized E. coli platform. Two miniprotein candidates, a homotrimeric construct (Trimer is referred to as IPD-52520, 17 kDa) and a tandem fusion (Daisy is referred to as IPD-52521, 25 kDa), were evaluated in parallel through systematic optimization of strain selection, media composition, fed-batch fermentation, inclusion-body solubilization, refolding, and chromatographic purification. The Trimer was downselected as the lead molecule based on superior preclinical efficacy, favorable pharmacokinetic properties, and higher volumetric manufacturing yields. The optimized process delivers approximately 2 g/L of purified protein at greater than 90% purity. Scale-up from 5 L to 50 L under cGMP conditions demonstrated excellent batch-to-batch reproducibility across six independent batches, supporting nonclinical and Phase 1 clinical supply. Comprehensive biophysical characterization confirmed a well-folded, predominantly alpha-helical trimer (Tm = 73.4 {degrees}C; polydispersity = 1.005) with an intact primary structure and strong target-binding affinity (KD < 1 pM). Real-time stability studies indicate that the drug substance is stable at 2-8 {degrees}C for at least 12 months, with ongoing stability studies. These results demonstrate the feasibility of translating computationally designed antiviral miniproteins into manufacturable biologics and provide a platform applicable to rapid-response therapeutics against current and future pandemic threats.

bioengineering↗

bioRxiv2026

Pericentromeric repeat copy number tunes heterochromatin dosage to control chromosome segregation and gene expression in fission yeast

Centromeres are essential for chromosome segregation, yet in many genomes they are composed entirely of rapidly evolving repetitive DNA, embedded in other repetitive DNA that forms pericentromeric heterochromatin. Due to the difficulties of manipulating these repeat-rich regions, how the relative size of pericentromeric repeat regions influences chromosome segregation remains an open question. Here, we take advantage of the tractable Schizosaccharomyces pombe system by combining population-level analysis, complete long-read assemblies, and engineered near-isogenic strains to test how pericentromeric repeat copy number affects chromosome biology in its native context. We find that pericentromeric dh/dg arrays on chromosome 3 vary almost tenfold in size among natural S. pombe isolates, ranging from 35 to 265 kb. We converted this natural diversity into an experimental system of nearly isogenic strains that primarily differ in pericentromere size (35 to >350 kb). We found that pericentromere size does not alter baseline growth under standard conditions. However, larger pericentromeres alter transcriptional output and sensitize cells to spindle stress. We show that this spindle-stress phenotype depends on heterochromatin: loss of the H3K9 methyltransferase Clr4 abolishes size-dependent differences, whereas artificial targeting of the Chromosomal Passenger Complex to heterochromatin partially rescues the defect. Thus, we find that larger pericentromeres act as sinks for limiting regulatory factors, weakening their effective concentration at centromeres and compromising faithful chromosome segregation under stress. These results establish that naturally occurring copy-number variation within repetitive pericentromeric DNA is not merely noise, but a functional source of variation in chromosome segregation and gene regulation. Our work provides an experimentally tractable framework for understanding how repeat expansion in centromere-proximal heterochromatin influences chromosome behavior across eukaryotes.

genetics↗

bioRxiv2025

Lymphatic Malformations with Activating KRAS Mutations Impair Lymphatic Valve Development Through Matrix Metalloproteinases

BACKGROUNDLymphatic malformations (LMs) are lesions due to inherited or somatic mutations that lead to a defective lymphatic vasculature. Activating KRAS mutations have been identified recently in LM patients with lymphedema, chylous ascites, or life-threatening chylothorax. In a LM mouse model, KRAS mutations are associated with a loss of lymphatic valves, which has been proposed to cause chylothorax via retrograde lymph flow into the pleural space. However, the mechanisms underlying the loss of lymphatic valves are unknown. METHODSTo investigate the mechanisms leading to valve loss, we combined the lymphatic-specific and tamoxifen-inducible Flt4CreERT2 with Kras-loxP-stop-loxP-G12D (Kras+/G12D) mice and Prox1GFP reporter mice to induce the restricted expression of KRAS-G12D and enable valve quantification in postnatal pups. Human dermal lymphatic endothelial cells (hdLECs) expressing KRAS-G12D were probed for changes in mRNA and protein expression with qRT-PCR, western blot, and gel zymography, and mechanistic studies were performed using 3D cell culture in collagen matrices. RESULTSOur data showed that lymphatic-specific expression of KRAS-G12D significantly attenuated valve development in the mesentery, diaphragm, and ear skin. qRT-PCR, western blot, and gel zymography using hdLECs expressing KRAS-G12D revealed the upregulation of the plasminogen activator (PA) pathway and matrix metalloproteinases (MMPs). The MMPs were sufficiently activated by plasmin, the product of the PA pathway, in hdLECs grown in a 3D collagen matrix, indicating a role for MMPs in the degradation of valve ECM core. Furthermore, a broad-spectrum MMP inhibitor given to Flt4CreERT2;Kras+/G12D mice rescued lymphatic valve development. CONCLUSIONSWe conclude that hyperactive KRAS signaling upregulates MMPs that become excessively activated by the upregulation of the PA pathway. MMPs then degrade the lymphatic valve ECM core preventing valve formation.

pathology↗

bioRxiv2025

NR6A1 is essential for neural crest cell specification, formation and survival

Neural crest cells (NCC) are a migratory progenitor cell population considered unique to vertebrates. Derived from the neuroepithelium during early embryogenesis, NCC contribute to nearly every tissue and organ system throughout the body, and disruptions in NCC development can result in congenital disorders, termed neurocristopathies. Despite decades of research, we have a poor understanding of the cellular mechanisms and signals that govern mammalian NCC formation. We discovered nuclear receptor superfamily 6 group member 1 (NR6A1/GCNF/RTR), is a novel, critical regulator of mammalian NCC specification, formation and survival. Nr6a1 is expressed throughout the neuroepithelium in mouse embryos from E8.0 to E9.5 and briefly in newly delaminated NCC. Nr6a1 loss-of-function perturbs anterior cranial NCC formation and survival, and results in the complete agenesis of migratory NCC caudal to the first pharyngeal arch. Using mouse ESC and human iPSC differentiation into NCC, chromatin immunoprecipitation, and multiomic approaches, we demonstrate that these phenotypes are associated with perturbation of NCC specification (Foxd3, Sox9, Sox10) and epithelial-mesenchymal transition (EMT; Snail1, Zeb2), in concert with persistent expression of pluripotency-associated factors (Oct4 and Nanog) in the neuroepithelium. Conditional deletion revealed that Nr6a1 is required during mid-late gastrulation, demonstrating that murine NCC specification occurs earlier than previously thought. Consistent with these observations, in vivo overexpression of Oct4 in gastrulating mouse embryos disrupts NCC specification and formation. Therefore, Nr6a1 is essential for mammalian NCC formation and moreover, may function as a bimodal switch repressing pluripotency-associated factors in the neuroepithelium, while concomitantly activating NCC specifiers and regulators of EMT.

developmental biology↗

bioRxiv2024

Patterns of crossover distribution in Drosophila mauritiana necessitate a re-thinking of the centromere effect on crossing over

We present a SNP-based crossover map for Drosophila mauritiana. Using females derived by crossing two different strains of D. mauritiana, we analyzed crossing over on all five major chromosome arms. Analysis of 105 male progeny allowed us to identify 327 crossover chromatids bearing single, double, or triple crossover events, representing 398 separate crossover events. We mapped these crossover sites along these five chromosome arms using a genome sequence map that includes the euchromatin-heterochromatin boundary. Confirming previous studies, we show that the overall crossover frequency in D. mauritiana is higher than is seen in D. melanogaster. Much of the increase in exchange frequency in D. mauritiana is due to a greatly diminished centromere effect. Using larval neuroblast metaphases from D. mauritiana -D. melanogaster hybrids we show that the lengths of the pericentromeric heterochromatin do not differ substantially between the two species, and thus cannot explain the observed differences in crossover distribution. Using a new and robust maximum likelihood estimation tool for obtaining Weinstein tetrad distributions, we observed an increase in bivalents with two or more crossovers when compared to D. melanogaster. This increase in crossing over along the arms of D. mauritiana likely reflects an expansion of the crossover-available euchromatin caused by the reduction in the centromere effect. The pattern of crossing over in D. mauritiana conflicts with the commonly accepted view of centromeres as polar suppressors of exchange (whose intensity is buffered by sequence non-specific heterochromatin) and demonstrates the importance of expanding such studies into other species of Drosophila. Article SummaryIn meiosis, homolog segregation is usually ensured by crossovers. The number and distribution of crossovers is in part regulated by cis-acting factors such as the cis- acting centromere effect, a polar suppression of exchange emanating from the vicinity of the centromere. We use SNP-based crossover mapping to show that in Drosophila mauritiana, the centromere effect is greatly reduced on four of the five major chromosome arms. We conclude that the centromere effect differs between Drosophila mauritiana and Drosophila melanogaster and that the ability to attenuate the centromere effect is not a general property of heterochromatin.

genetics↗

bioRxiv2024

A consensus variant-to-function score to functionally prioritize variants for disease

Identifying and functionally characterizing causal disease variants in genome-wide association studies remains a pressing challenge. Here, we construct a consensus variant-to-function (cV2F) score that assigns a single value to each common single-nucleotide variant in the genome, and helps to predict and characterize causal disease variants. The cV2F score leverages features reflecting variant-level experimentally and computationally predicted function (e.g. allelic imbalance and sequence-based deep learning models) and element-level function (e.g. predicted enhancers), and learns optimal combinations of features by training a gradient boosting model on GWAS fine-mapping results. The cV2F-annotated variants attained an AUPRC of 0.822 at identifying held-out fine-mapped variants. Variants with high cV2F scores are highly enriched for heritability (14.2x, s.e. 0.5) across 66 diseases/traits, are uniquely informative for disease heritability, and are highly predictive of variants implicated by reporter assays; cV2F substantially outperforms previous variant-to-function scores using all of these metrics. GWAS fine-mapping of 110 diseases/traits informed by cV2F identified 14.3% more confidently fine-mapped (PIP > 0.95) variants than non-functionally informed fine-mapping. We further constructed tissue/cell line-specific cV2F scores that prioritize variants based on regulatory potential in specific tissues/cell lines, attaining high heritability enrichment for tissue-related diseases/traits (15.6x, s.e. 2.3) while providing independent information (average correlation of 0.27 with the primary cV2F score). We highlight examples of GWAS loci for which cV2F pinpoints causal variants with high confidence and elucidates their functional role.

genetics↗

bioRxiv2024

Network-based representation learning reveals the impact of time and diet on the gut microbial and metabolomic environment of infants

BackgroundWhile studies have explored differences in gut microbiome development for infant liquid diets (breastmilk, formula), little is known about the impact of complementary foods on infant gut microbiome development. Here, we investigated how different protein-rich foods (i.e., meat vs. dairy) affect fecal metagenomics and metabolomics during early complementary feeding from 5-12 months in U.S. formula-fed infants from a randomized controlled feeding trial. ResultsWe used a novel network representation learning approach to model the time-dependent, complex interactions between microbiome features, metabolite compounds, and diet. We then used the embedded space to detect features associated with age and diet type and found the meat diet group was enriched with microbial genes encoding amino acid, nucleic acid, and carbohydrate metabolism. Compared to a more traditional differential abundance analysis, which analyzes features independently and found no significant diet associations, network node embedding represents the infant samples, microbiome features, and metabolites in a single transformed space revealing otherwise undetected associations between infant diet and the gut microbiome. ConclusionsOur findings generate new hypotheses regarding the interplay between complementary feeding practices, microbial-metabolic interactions, and infant physiological outcomes. This work highlights the impact of complementary foods on infant gut microbiome development and the potential of using network representation learning to integrate multi-omic data, allowing for greater insight into complex diet, microbial, and metabolite interactions.

microbiology↗

bioRxiv2024

CCAFE: Estimating Case and Control Allele Frequencies from GWAS Summary Statistics

Methods involving summary statistics in genetics can be quite powerful but can be limited in utility. For instance, many post-hoc analyses of disease studies require case and control allele frequencies (AFs), which are not always published. We present two frameworks to derive case and control AFs from GWAS summary statistics using the odds ratio, case and control sample sizes, and either the total (case and control aggregated) AF or standard error (SE). In simulations and real data, derivations of case and controls AFs using total AF is highly accurate across all settings (e.g., minor AF, condition prevalence). Conversely, derivations using SE underestimate common variant AFs (e.g. minor allele frequency >0.3) in the presence of covariates. We develop an adjustment using gnomAD AFs as a proxy for true AFs, which reduces the bias when using SE. While estimating case and control AFs using the total AF is preferred due to its high accuracy, estimating from the SE can be used more broadly since SE can be derived from p-values and beta estimates, which are commonly provided. The methods provided here expand the utility of publicly available genetic summary statistics and promote the reusability of genomic data. The R package CCAFE, with implementations of both methods, is freely available on Bioconductor and GitHub.

genomics↗

bioRxiv2024

Verifying the concordance between motion corrected and conventional MPRAGE for pediatric morphometric analysis

PurposeTo validate a retrospective motion correction technique, Distributed and Incoherent Sample Orders for Reconstruction Deblurring using Encoding Redundancy (DISORDER), for pediatric brain morphometry. MethodsTwo T1-weighted MPRAGE 3D datasets were acquired at 3T in thirty-seven children, median age 7.75 years; one with conventional linear phase encoding and one using DISORDER. MPRAGE images were scored as motion-free or motion-corrupt. Cortical morphometry and regional brain volumes were measured with FreeSurfer, subcortical grey matter (GM) with FSL-FIRST, and hippocampal volumes with HippUnfold. Intraclass correlation coefficient (ICC) was used to determine agreement between the 2 MPRAGE acquisitions. Mann-Whitney U was used to test the difference between measures obtained using DISORDER and (i) motion-free and (ii) motion-corrupt conventional MPRAGE data. ResultsICC measures were good/excellent for most subcortical GM (motion-free, 0.75-0.96; motion-corrupt, 0.62-0.98) and regional brain volumes (motion-free 0.47-0.99; motion-corrupt, 0.54-0.99) between conventional MPRAGE and DISORDER data, except for the amygdala and nucleus accumbens (motion-free, 0.38-0.65; motion- corrupt, 0.1-0.42). However, these values were less consistent for motion-corrupt conventional MPRAGE data for hippocampal volumes (motion-free 0.65-0.99; motion-corrupt, 0.11-0.91) and cortical measures (motion-free 0.76-0.98; motion- corrupt, 0.09-0.74). Mann-Whitney U showed percentage differences in measures obtained with motion-corrupt conventional MPRAGE compared to DISORDER data were significantly greater than in those obtained using motion-free conventional MPRAGE data in 22/58 structures. ConclusionIn the absence of motion, morphometric measures obtained using DISORDER are largely consistent with those from conventional MPRAGE data, whereas improved reliability is obtained by DISORDER for motion-degraded scans. This study validates DISORDER for brain morphometric studies in children.

neuroscience↗

bioRxiv2024

A repeatedly evolved mutation in Cryptochrome-1 of subterranean animals alters behavioral and molecular circadian rhythms

The repeated evolution of similar phenotypes in independent lineages often occurs in response to similar environmental pressures, through similar or different molecular pathways. Recently, a repeatedly occurring mutation R263Q in a conserved domain of the protein Cryptochrome-1 (CRY1) was reported in multiple species inhabiting subterranean environments. Cryptochromes regulate circadian rhythms, and glucose and lipid metabolism. Subterranean species show changes to their circadian rhythm and metabolic pathways, making it likely that this mutation in CRY1 contributes to adaptive phenotypic changes. To identify the functional consequences of the CRY1 R263Q mutation, we generated a mouse model homozygous for this mutation. Indirect calorimetry experiments revealed delayed energy expenditure, locomotor activity and feeding patterns of mutant mice in the dark phase, but no further metabolic phenotypes - unlike a full loss of function of CRY1. Gene expression analyses showed altered expression of several canonical circadian genes in the livers of the mutant mice, fortifying the notion that CRY1 R263Q impacts metabolism. Our data provide the first characterization of a novel mutation that has repeatedly evolved in subterranean environments, supporting the idea that shared environmental constraints can drive the evolution of similar phenotypes through similar genetic changes.

evolutionary biology↗

bioRxiv2024

Chamaeleo calyptratus (veiled chameleon) chromosome-scale genome assembly and annotation provides insights into the evolution of reptiles and developmental mechanisms.

The family Chamaeleonidae comprises 228 species, boasting an extensive geographic spread and an array of evolutionary novelties and adaptations, but a paucity of genetic and molecular analyses. Veiled chameleon (Chamaeleo calyptratus) has emerged as a tractable research organism for the study of squamate early development and evolution. Here we report a chromosomal-level assembly and annotation of the veiled chameleon genome. We note a remarkable chromosomal conservation across squamates, but comparisons to more distant genomes reveal GC peaks correlating with ancestral chromosome fusion events. We subsequently identified the XX/XY region on chromosome 5, confirming environmental-independent sex determination in veiled chameleons. Furthermore, our analysis of the Hox gene family indicates that veiled chameleons possess the most complete set of 41 Hox genes, retained from an amniote ancestor. Lastly, the veiled chameleon genome has retained both ancestral paralogs of the Nodal gene, but is missing Dand5 and several other genes, recently associated with the loss of motile cilia during the establishment of left-right patterning. Thus, a complete veiled chameleon genome provides opportunities for novel insights into the evolution of reptilian genomes and the molecular mechanisms driving phenotypic variation and ecological adaptation.

genomics↗

bioRxiv2024

The developing Human Connectome Project fetal functional MRI release: Methods and data structures

Recent advances in fetal fMRI present a new opportunity for neuroscience to study functional human brain connectivity at the time of its emergence. Progress in the field however has been hampered by the lack of openly available datasets that can be exploited by researchers across disciplines to develop methods that would address the unique challenges associated with imaging and analysing functional brain in utero, such as unconstrained head motion, dynamically evolving geometric distortions, or inherently low signal-to-noise ratio. Here we describe the developing Human Connectome Projects release of the largest open access fetal fMRI dataset to date, containing 275 scans from 255 fetuses and spanning the period of 20.86 to 38.29 post-menstrual weeks. We present a systematic approach to its pre-processing, implementing multi-band soft SENSE reconstruction, dynamic distortion corrections via phase unwrapping method, slice-to-volume reconstruction and a tailored temporal filtering model, with attention to the prominent sources of structured noise in the in utero fMRI. The dataset is accompanied with an advanced registration infrastructure, enabling group-level data fusion, and contains outputs from the main intermediate processing steps. This allows for various levels of data exploration by the imaging and neuroscientific community, starting from the development of robust pipelines for anatomical and temporal corrections to methods for elucidating the development of functional connectivity in utero. By providing a high-quality template for further method development and benchmarking, the release of the dataset will help to advance fetal fMRI to its deserved and timely place at the forefront of the efforts to build a life-long connectome of the human brain.

neuroscience↗

bioRxiv2024

Molecular signatures of cortical expansion in the human fetal brain

The third trimester of human gestation is characterised by rapid increases in brain volume and cortical surface area. A growing catalogue of cells in the prenatal brain has revealed remarkable molecular diversity across cortical areas.1,2 Despite this, little is known about how this translates into the patterns of differential cortical expansion observed in humans during the latter stages of gestation. Here we present a new resource, Brain, to facilitate knowledge translation between molecular and anatomical descriptions of the prenatal developing brain. Built using generative artificial intelligence, Brain is a three-dimensional cellular-resolution digital atlas combining publicly-available serial sections of the postmortem human brain at 21 weeks gestation3 with bulk tissue microarray data, sampled across 29 cortical regions and 5 transient tissue zones.4 Using Brain, we evaluate the molecular signatures of preferentially-expanded cortical regions during human gestation, quantified in utero using magnetic resonance imaging (MRI). We find that differences in the rates of expansion across cortical areas during gestation respect anatomical and evolutionary boundaries between cortical types5 and are founded upon extended periods of upper-layer cortical neuron migration that continue beyond mid-gestation. We identify a set of genes that are upregulated from mid-gestation and highly expressed in rapidly expanding neocortex, which are implicated in genetic disorders with cognitive sequelae. Our findings demonstrate a spatial coupling between areal differences in the timing of neurogenesis and rates of expansion across the neocortical sheet during the prenatal epoch. The Brain atlas is available from: https://garedaba.github.io/micro-brain/ and provides a new tool to comprehensively map early brain development across domains, model systems and resolution scales.

neuroscience↗

bioRxiv2024

Characterizing substructure via mixture modeling of genetic similarity in large-scale summary statistics

Genetic summary data are broadly accessible and highly useful including for risk prediction, causal inference, fine mapping, and incorporation of external controls. However, collapsing individual-level data into groups masks intra- and inter-sample heterogeneity, leading to confounding, reduced power, and bias. Ultimately, unaccounted substructure limits summary data usability, especially for understudied or admixed populations. Here, we present Summix2, a comprehensive set of methods and software based on a computationally efficient mixture model to estimate and adjust for substructure in genetic summary data. In extensive simulations and application to public data, Summix2 characterizes finer-scale population structure, identifies ascertainment bias, and identifies potential regions of selection due to local substructure deviation. Summix2 increases the robust use of diverse publicly available summary data resulting in improved and more equitable research.

genomics↗

bioRxiv2023

Dynamic changes in subplate and cortical plate microstructure precede the onset of cortical folding in vivo

Cortical gyrification takes place predominantly during the second to third trimester, alongside other fundamental developmental processes, such as the development of white matter connections, lamination of the cortex and formation of neural circuits. The mechanistic biology that drives the formation cortical folding patterns remains an open question in neuroscience. In our previous work, we modelled the in utero diffusion signal to quantify the maturation of microstructure in transient fetal compartments, identifying patterns of change in diffusion metrics that reflect critical neurobiological transitions occurring in the second to third trimester. In this work, we apply the same modelling approach to explore whether microstructural maturation of these compartments is correlated with the process of gyrification. We quantify the relationship between sulcal depth and tissue anisotropy within the cortical plate (CP) and underlying subplate (SP), key transient fetal compartments often implicated in mechanistic hypotheses about the onset of gyrification. Using in utero high angular resolution multi-shell diffusion-weighted imaging (HARDI) from the Developing Human Connectome Project (dHCP), our analysis reveals that the anisotropic, tissue component of the diffusion signal in the SP and CP decreases immediately prior to the formation of sulcal pits in the fetal brain. By back-projecting a map of folded brain regions onto the unfolded brain, we find evidence for cytoarchitectural differences between gyral and sulcal areas in the late second trimester, suggesting that regional variation in the microstructure of transient fetal compartments precedes, and thus may have a mechanistic function, in the onset of cortical folding in the developing human brain.

neuroscience↗

bioRxiv2023

Afanc: a Metagenomics Tool for Variant Level Disambiguation of NGS Datasets

Genomics is amongst the most powerful tools available for mounting a clinical response to infectious disease. The accurate and precise taxonomic evaluation of pathogens is essential when building a picture of pathogenicity, virulence, transmission, and drug resistance. Carrying out such profiling in a high throughput manner necessitates the development of reliable bioinformatic tools. Here we present Afanc, a novel metagenomic profiler which is sensitive down to species and strain level taxa, and capable of elucidating the complex pathogen profile of compound datasets. We compared Afanc against currently available cutting edge profilers using 3 datasets: single species read sets simulated from the full Mycobacteriaceae taxonomic landscape; compound read sets containing multiple Mycobacteriaceae species and variants; and real data covering the majority of the M. tuberculosis lineage taxonomic space. Afanc outperformed all profilers, both generic and Mycobacteriaceae specific, across all tested fields. As a species agnostic profiler, we predict that Afanc will be of great utility when carrying out highly specific and sensitive pathogen profiling of clinical datasets. Such analyses are essential in advising both the clinical response to an individual disease case, and in forming the foundation of epidemiological surveys.

bioinformatics↗

bioRxiv2023

A shared linguistic space for transmitting our thoughts from brain to brain in natural conversations

Effective communication hinges on a mutual understanding of word meaning in different contexts. The embedding space learned by large language models can serve as an explicit model of the shared, context-rich meaning space humans use to communicate their thoughts. We recorded brain activity using electrocorticography during spontaneous, face-to-face conversations in five pairs of epilepsy patients. We demonstrate that the linguistic embedding space can capture the linguistic content of word-by-word neural alignment between speaker and listener. Linguistic content emerged in the speakers brain before word articulation, and the same linguistic content rapidly reemerged in the listeners brain after word articulation. These findings establish a computational framework to study how human brains transmit their thoughts to one another in real-world contexts.

neuroscience↗