Biology subjects

Ferrucci, L.

Publications and source records attributed to Ferrucci, L..

At least 19 recordsLinked to original sources

bioRxiv2026

Profiling of Aggregated Amyloid β42-induced Proteomic Alterations in KOLF2.1J Induced Pluripotent Stem Cell-derived Neurons

Amyloid[beta]; (A[beta];) plaques are a hallmark of Alzheimer[prime]s disease (AD). A human cellular neuronal model that recaptures A[beta];-induced pathology is critical for advancing AD research. However, comprehensive proteomic profiling of A[beta];-induced cellular model remains elusive. In this study, we investigated the proteomic changes in induced pluripotent stem cell (iPSC)-derived neurons (iNs) exposed to synthetic A[beta]; (1-42) peptides (A[beta];42A) to improve our understanding of the cellular responses of A[beta]; aggregates and to establish a human-related platform for AD research. A[beta];42A formed extracellular aggregates around neuronal soma and neurites, impaired neurite outgrowth, and induced the expression of multiple AD-associated genes, such as APOE, BACE1, ADAM10. To define the molecular landscape of A[beta];-induced neuronal dysfunction, we performed proteomic analyses of whole-cell lysates as well as soma- and neurite-enriched fractions. Proteomic profiling revealed extensive gene alterations in pathways associated with synaptic function, neuronal maintenance, and AD pathogenesis, such as the upregulation of APOE. Importantly, the A[beta];42A-iNs system recapitulated molecular signatures observed in AD brain tissue and cerebrospinal fluid. Representative protein changes, including APOE upregulation and its colocalization with A[beta]; aggregates, were further validated in postmortem human AD brain tissue. Together, these findings manifest that the A[beta];42A-iNs system reproduces multiple cellular and molecular features of AD and exhibits strongly consensus with clinical observations. It provides a valuable platform for investigating A[beta];-driven neurodegeneration and for the discovery of therapeutic targets for AD.

neuroscience↗

bioRxiv2026

Integration of cell-specific gene expression and chromatin accessibility facilitates localization of neurodegenerative risk in microglia

Genome-wide association studies (GWAS) have identified many loci that contribute to the risk of neurodegenerative diseases. However, a persistent challenge in interpretation of GWAS is to break loci down to specific genes, variants, and cell types, and thus nominate disease mechanisms. Here, we used iPSC-derived cells containing population-level variation to examine GWAS loci across NDDs including Alzheimer's disease, Parkinson's disease and Lewy body dementia. We differentiated a set of 135 iPSC donor lines into two cell types relevant to neurodegeneration, neurons and microglia, and completed single cell gene expression and chromatin accessibility profiling. Meta-analysis of these data with published human brain snRNAseq for QTL mapping identified multiple loci associated with NDDs that are restricted to either neurons or microglia. Colocalization of GWAS and these QTL supports microglia as having a strong contribution to disease risk. We tested peaks nominated at the BIN1 locus for enhancer activity using a perturb-seq-based method in microglia. Our results show one of the nominated peaks controls BIN1 expression in microglia but also modifies expression of other genes at the locus. These results support the hypothesis that common variants affecting gene expression specifically in microglia can contribute directly to NDD risk rather than functioning solely as a secondary response to neurodegeneration. These data also show that iPSC-derived cells are a useful model to experimentally dissect GWAS loci that colocalize with QTL.

genomics↗

bioRxiv2026

SALRR: Scalable Analysis of Long-Read RNA-Seq Enables Comprehensive Transcriptome Profiling in Human Brain

Isoform-resolved transcriptomics is fundamental to decoding the molecular complexity of the human brain, yet population-scale long-read RNA sequencing has remained inaccessible due to labor-intensive library preparation, sensitivity to RNA degradation in postmortem tissue, and the absence of integrated, reproducible analysis pipelines. Here we present SALRR (Scalable Analysis of Long-Read RNA-seq), an integrated wet-lab and computational platform designed to overcome these barriers. Automated ONT long-read cDNA library preparation on the Hamilton Microlab NGS STAR platform reduces hands-on time by 67% and enables 24 libraries per operator per day while maintaining performance across RNA integrity values. A modular, Snakemake-based pipeline performs end-to-end processing from ONT signal data to isoform-level quantification, incorporating SIRV spike-in calibration, multi-stage quality control, and stringent isoform validation. Applied to 10 postmortem frontal cortex samples from the North American Brain Expression Consortium, SALRR identified 31,607 high-confidence isoforms from 10,075 genes, including 8,532 novel splice variants absent from GENCODE v49, and complex splicing events systematically missed by short-read sequencing at neurodegeneration-relevant loci, including GBA1, CCNF, CHCHD10, and TREM2. All protocols and code are openly available, providing a scalable, community-ready framework for isoform-resolved transcriptomics in neurodegeneration, aging, and complex brain disease.

genomics↗

bioRxiv2026

Reduced LANCL1-AS1 in old human skeletal muscle diminishes mitochondrial activity, shortens mt-mRNA poly(A) tails, and suppresses myogenesis

Regeneration of skeletal muscle preserves muscle mass and function, which decline with age. Here, we sought to identify long noncoding (lnc)RNAs involved in skeletal muscle myogenesis and potentially relevant to muscle aging. Cross-sectional analysis of skeletal muscle transcriptomes from healthy 22-through 89-year-old individuals revealed lncRNA LANCL1-AS1 among the top declining transcripts. Conversely, LANCL1-AS1 increased robustly during skeletal myogenesis and promoted myogenic differentiation in culture. Affinity pulldown by ChIRP followed by mass spectrometry revealed that LANCL1-AS1 associated with the mitochondrial protein LRPPRC, enhancing the formation of the chaperone complex LRPPRC-SLIRP, which maintains longer poly(A) tails of mitochondrial (mt-)mRNAs and stabilizes mt-mRNAs. Importantly, while myoblasts from old rhesus monkey muscle expressed lower levels of LANCL1-AS1 and mt-mRNAs, and displayed lower mitochondrial activity than young monkey myoblasts, overexpressing LANCL1-AS1 in old myoblasts restored mitochondrial activity and myogenesis. We propose that the age-associated reduction in LANCL1-AS1 contributes to impaired mitochondrial function and reduced myogenic capacity in aging skeletal muscle.

molecular biology↗

bioRxiv2026

Charting Cervical Spinal Cord Morphometry Across the Lifespan

Spinal cord morphometry provides essential biomarkers of neurological health, but clinical interpretations are confounded by inter-subject variability and a lack of normative references across the full human lifespan. We address this gap by generating the first comprehensive lifespan charts for cervical spinal cord morphometry. We leveraged 30 population-based brain MRI datasets, aggregating 78,269 scans from 41,042 individuals (ages 0-100) whose imaging protocols included cervical cord coverage. To overcome contrast variability, we employed a state-of-the-art contrast-agnostic deep learning segmentation method, extracting cross-sectional area (CSA), anteroposterior (AP) and right-left (RL/transverse), and shape indices (compression ratio, eccentricity, and solidity) from C1 to C7. Normative trajectories were modeled using Generalized Additive Models for Location, Scale, and Shape (GAMLSS). The resulting charts reveal distinct non-linear lifespan changes: rapid growth through childhood and adolescence, peak maturation occurring in early-to-mid adulthood (e.g., mid-30s for CSA), followed by gradual decreases. Significant regional variations along the cervical cord and consistent sex differences (males > females for size metrics) were quantified. Spinal cord trajectories showed strong temporal coupling with brain white matter and brainstem volumes, suggesting integrated CNS development and aging. These lifespan charts provide a robust normative framework, enabling age- and sex-specific centile scoring of individual spinal cord morphometry. This resource offers a critical tool for differentiating typical variation from pathological changes, enhancing the clinical utility of spinal cord MRI in studies of development and neurodegeneration.

neuroscience↗

bioRxiv2026

DeepBranchAI: A Novel Cascade Workflow Enabling Accessible 3D Branching Network Segmentation

Three-dimensional branching networks exist throughout biological, natural, and man-made systems as pathways through volumetric space. Segmentation is required to correctly reconstruct the networks in whole or in part for analysis. This presents a unique challenge as minor voxel misclassifications can cause sporadic connectivity shifts, whereby connected elements appear to disconnect (false negatives) or to even become amplified (false positives). Addressing this topological vulnerability requires the generation of 3D models since 2D slice-by-slice approaches cannot maintain connectivity across x, y, and z axes. Yet tracking 3D architecture demands substantially more analytical resources than using a 2D strategy as generating volumetric annotations requires extraordinary amounts of expert time to manually annotate. This creates a fundamental annotation bottleneck: with sparse training data available, deep learning models tend to overfit available volumes and fail to generalize to novel volumes. We present a cascade training workflow that overcomes this bottleneck through a positive feedback loop in which trained models become annotation aids for subsequent volumes. The workflow begins with random forests that generate initial drafts from minimal labels, followed by expert refinement that cycle ever closer to the ground truth. As refined data accumulates, training transitions from 2D to 3D architectures, which systematically expand sparse datasets into comprehensive training sets. The outcome is a 3D nnU-Net model optimized for topology-preserving segmentation. We dub our resulting model DeepBranchAI. Training validation on heavily branching mitochondrial networks, generated by focused ion beam scanning electron microscopy (FIB-SEM, 15nm voxel resolution) achieved Dice Similarity Coefficient (DSC) = 0.942 across 5-fold cross-validation. Transfer learning to vascular networks (VESSEL12 dataset, CT volumes, 30,000-fold voxel size difference) achieved 97.05% accuracy against ground truth, validating that learned features represent domain-general topological principles. This workflow reduces annotation time from months to weeks while transforming sparse initial labels into robust training sets. Complete implementation, trained weights, and validation code are provided open source.

bioinformatics↗

bioRxiv2025

The blood proteome predicts the impact of circulating factors on age-related mitochondrial health

Circulating non-cellular factors, such as plasma proteins, contribute to various features of aging. To determine the impacts of endogenous circulating factors on human age-related bioenergetic decline, we treated primary human fibroblasts with serum samples representing the adult life-course. Our results demonstrate that the maximal mitochondrial bioenergetic capacity of fibroblasts treated with serum is negatively correlated with the chronological and epigenetic age of the serum donor. Using targeted proteomics, we identified plasma proteins associated with the bioenergetic effects of serum. We then utilized elastic net, a linear regression modeling technique, to derive a novel proteomic signature of age-related mitochondrial differences. MitoAge is a 25-protein signature of age-related mitochondrial health that predicts the systemic bioenergetic effects of circulating factors and is related to differences in physical function across human aging. Signatures that report on cellular hallmarks of aging, such as mitochondrial function, represent a new generation of mechanistically-informed biomarkers of biological aging. GRAPHICAL ABSTRACTIn this study, we describe the development of a novel proteomic signature, MitoAge. This signature was developed by utilizing human primary fibroblasts treated with serum samples representing the adult human life-course and analyzing how resulting respirometry correlated with chronological age, epigenetic age, and abundance of serum proteins. Utilizing machine learning techniques, we derived a 25-protein signature which can predict bioenergetics and physical features related to aging. Application and utility of this signature may be used to identify novel drivers of health and longevity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/687483v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@905c12org.highwire.dtl.DTLVardef@18ca82forg.highwire.dtl.DTLVardef@175d397org.highwire.dtl.DTLVardef@966faa_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2025

Long-Read epigenetic clocks identify improved brain aging predictions

Epigenetic clocks are widely used to estimate biological aging, yet most are built from array-based data from peripheral tissues of predominantly European-ancestry individuals, limiting their generalizability. Here, we present aging clocks on DNA methylation from Oxford Nanopore long-read sequencing (LRS), leveraging over 28 million CpG sites from prefrontal cortex samples across individuals of African and European ancestry. These models were developed using GenoML, an automated machine learning platform for multi-omics data that leverages a diverse catalog of existing model architectures. Our long-read-informed clocks were developed using promoter-based and whole-genome window-based features, yielding models for each individual cohort as well as a combined-cohort clock. Each of these models demonstrated favorable performance compared to existing methylation clocks and was externally validated in a cohort of Colombian individuals. We further performed enrichment analyses and nominated both shared and cohort-specific pathways, cell types, and transcription factor binding motifs which may be implicated in aging and were not fully explained by cell type proportions or postmortem interval. Altogether, our findings highlight the power of long-read methylation data for constructing accurate, ancestry-aware aging clocks and emphasize the importance of inclusive training datasets.

bioinformatics↗

bioRxiv2025

METABOLOMIC SIGNATURES OF EXTREME OLD AGE: FINDINGS FROM THE NEW ENGLAND CENTENARIAN STUDY

The New England Centenarian Study (NECS) provides a unique resource for the study of extreme human longevity (EL). To gain insight into biological pathways related to EL, chronological age and survival, we used an untargeted serum metabolomic approach (> 1,400 metabolites) in 213 NECS participants, followed by integration of our findings with metabolomic data from four additional studies. Compared to their offspring and matched controls, EL individuals exhibited a distinct metabolic profile characterized by higher levels of primary and secondary bile acids - most notably chenodeoxycholic acid (CDCA) and lithocholic acid (LCA) - higher levels of biliverdin and bilirubin, and stable levels of selected steroids. Notably, elevated levels of both bile acids and steroids were associated with lower mortality. Several metabolites associated with age and survival were inversely associated with metabolite ratios related to NAD+ production and/or levels (tryptophan/kynurenine, cortisone/cortisol), gut bacterial metabolism (ergothioneine/ trimethylamine N-oxide, aspartate/quinolinate), and oxidative stress (methionine/methionine sulfoxide), implicating these pathways in aging and/or longevity. We further developed a metabolomic clock predictive of biological age, with age deviations significantly associated with mortality risk. Key metabolites predictive of biological aging, such as taurine and citrate, were not captured by traditional age analyses, pointing to their potential role as biomarkers for healthy aging. These results highlight metabolic pathways that may be targeted to promote metabolic resilience and healthy aging.

systems biology↗

bioRxiv2025

SomaModules: a pathway enrichment approach tailored to SomaScan data

Motivated by the lack of adequate tools to perform pathway enrichment analysis, this work presents an approach specifically tailored to SomaScan data. Starting from annotated gene sets, we developed a greedy, top-down procedure to iteratively identify strongly intra-correlated SOMAmer modules, termed "SomaModules", based on 11K SomaScan data. We generated two repositories based on the latest MSigDB and MitoCarta releases, containing more than 40,000 SOMAmer-based gene sets combined. These repositories can be utilized by any unstructured pathway enrichment analysis tool. We validated our results with two case examples: (i) Alzheimers Disease specific pathways in a 7K SomaScan case-control study, and (ii) mitochondrial pathways using 11K SomaScan data linked to physical performance outcomes. Using Gene Set Enrichment Analysis (GSEA), we found that, in both examples, SomaModules had significantly higher enrichment than the original gene set counterparts. These findings were robust and not significantly affected by the choice of enrichment metric or the Kolmogorov enrichment statistic used in the GSEA procedure. We provide users with access to all code, documentation and data needed to reproduce our current repositories, which also will enable them to leverage our framework to analyze SomaModules derived from other sources, including custom, user-generated gene sets.

bioinformatics↗

bioRxiv2025

Temporal dynamics of proteome and phosphorproteome during neuronal differentiation in the reference KOLF2.1J iPSC line

Induced pluripotent stem cell (iPSC)-derived neurons have emerged as a powerful model to investigate both neuronal development and neurodegenerative diseases. Although transcriptomics and imaging have been applied to characterize neuronal development signatures, comprehensive datasets of protein and post-translational modifications (PTMs) are not readily available. Here, we applied quantitative proteomics and phosphoproteomics to profile the differentiation of the KOLF2.1J iPSC line, the first reference line of the iPSC Neurodegenerative Disease Initiative (iNDI) project. We developed an automated workflow enabling high-coverage enrichment of proteins and phosphoproteins. Our results revealed molecular signatures across proteomic and phosphoproteomic landscapes during differentiation of iPSC-derived neurons. Proteomic data highlighted distinct changes in mitochondrial pathways throughout the course of differentiation, while phosphoproteomics revealed specific regulatory dynamics in GTPase signaling pathways and microtubule proteins. Additionally, phosphosite dynamics exhibited discordant trends compared to protein expression, particularly in processes related to axon functions and RNA transport. Furthermore, we mapped the kinase dynamic changes that are critical for neuronal development and maturation. We developed an interactive Web app (https://niacard.shinyapps.io/Phosphoproteome/) to visualize temporal landscape dynamics of protein and phosphosite expression. By establishing baselines of proteomic and phosphoproteomic profiles for neuronal differentiation, this dataset offers a valuable resource for future research into neuronal development and neurodegenerative diseases using this reference iPSC line. HighlightsO_LITemporal dynamics of proteome and phosphoproteome profiles in KOLF2.1J iPSC derived neurons. C_LIO_LIPhosphoproteomics highlights GTPase signaling and microtubule regulation in neuronal differentiation. C_LIO_LIKinome mapping reveals a shift in kinase activity patterns from early to late differentiation. C_LIO_LIShinyapp for visualizing the trajectory of protein and phosphosite expression during neuronal differentiation. C_LI

neuroscience↗

bioRxiv2025

Proteomic Analysis of Endemic Viral Infections in Neuronsoffers Insights into Neurodegenerative Diseases

Endemic viral infections with low pathogenicity are often overlooked due to their mild symptoms, yet they can exert long-term effects on cellular function and contribute to disease pathogenesis. While viral infections have been implicated in neurodegenerative disorders, their impact on the neuronal proteome remains poorly understood. Here, we differentiated human induced pluripotent stem cells (KOLF2.1J) into mature neurons to investigate virus-induced proteomic changes following infection with five neurotropic endemic human viruses: Herpes simplex virus 1 (HSV-1), Human coronavirus 229E (HCoV-229E), Epstein-Barr virus (EBV), Varicella-Zoster virus (VZV), and Influenza A virus (H1N1). Given that these viruses can infect adults and have the potential to cross the placental barrier, their molecular impact on neurons may be relevant across the lifespan. Using mass spectrometry-based proteomics with a customized library for simultaneous detection of human and viral proteins, we confirmed successful infections and identified virus-specific proteomic signatures. Notably, virus-induced protein expression changes converged on key neuronal pathways, including those associated with neurodegeneration. Gene co-expression network analysis identified protein modules correlated with viral proteins. Pathway enrichment analysis of these modules revealed associations with the nervous system, including pathways linked to Alzheimers and Parkinsons disease. Remarkably, several viral-induced proteomic alterations overlapped with changes observed in postmortem Alzheimers patient brains, suggesting a mechanistic connection between viral exposure and neurodegenerative disease progression. These findings provide molecular insights into how common viral infections perturb neuronal homeostasis and may contribute to neurodegenerative pathology, highlighting the need to consider endemic viruses as potential environmental risk factors in neurological disorders.

neuroscience↗

bioRxiv2025

Changes in motor unit conduction velocity after unilateral lower limb suspension and active recovery correlate with muscle ion channel gene expression

The effects of muscle disuse on the propagation of action potentials along muscle units, a key process for effective muscle activation and force production, remain poorly understood. This study aimed to investigate changes in action potential propagation and to identify biological factors influencing these changes following unilateral lower limb suspension (ULLS) and active recovery (AR). Eleven young male participants underwent 10 days of ULLS followed by 21 days of AR based on resistance exercise. Maximal force of the knee extensor muscles (MVC), High-Density surface EMG recordings and muscle biopsies of the vastus lateralis muscle were collected before ULLS, after ULLS and after AR. EMG recordings collected during submaximal isometric contractions were decomposed to estimate single motor unit conduction velocity (MU CV). Muscle biopsies were used to measure muscle fibre diameters via histochemical analysis and ion channel transcriptomic profiles via mRNA-sequencing. MVC decreased after ULLS by 29% and fully recovered after AR. MU CV decreased after ULLS and fully recovered, up to exceeding baseline values after AR. Muscle fibre diameters did not change across the interventions and showed no correlation with MU CV. Conversely, a feature importance analysis revealed that mRNA expression levels of specific ion channel genes, particularly those involved in K+ transport, correlate with MU CV at baseline and across the interventions. This study highlights the crucial role of K+ ion channels in influencing MU CV in humans, offering new insights into MU CV modulation and the mechanisms of muscle force changes after disuse and active recovery. Key pointsO_LIMuscle disuse, such as in unilateral lower limb suspension, leads to a decrease in motor unit conduction velocity (MU CV), a critical factor for muscle activation and force production. C_LIO_LIActive recovery through resistance exercise results in the full recovery of MU CV, even exceeding baseline levels. C_LIO_LIMuscle fibre diameters do not change significantly after limb suspension or active recovery and show no correlation with MU CV. C_LIO_LIConversely, ion channel mRNA expression, particularly of those related to K+ transport, correlates with MU CV and its changes following disuse and recovery. C_LIO_LIThese findings highlight K+ ion channels as a key factor in regulating MU CV in humans and provide new molecular determinants of the changes in muscle force after disuse and recovery. C_LI

physiology↗

bioRxiv2024

Compatibility and comparative analysis of chronological and biological aging between the legacy 450K and the EPIC v2.0 arrays

Several different epigenetic clocks built from DNA methylation beadchip arrays, including the Illumina Infinium Human Methylation 450K and EPICv1 BeadChips, have been developed and are used to evaluate biological aging. However, there is still limited information on effectively utilizing the novel EPICv2 arrays and addressing biases in epigenetic clock calculations resulting from missing probes initially present on legacy arrays. We address how the absence of probes on the EPICv2 array, originally present on the 450K array, affects many available epigenetic clock estimates. Using data from the InCHIANTI study of aging, our findings show that while clocks like Hannum and GrimAgeV2 exhibit significant over- or underestimation due to missing probes, the correlations between estimates from all 450K probes (unreduced) and those from shared probes between 450K and EPICv2 (reduced) remain strong. In this cohort, we consider AgeAcceleration from traditional epigenetic clocks to be the most reliable approach. Their values do not significantly change upon probe reduction, with unreduced and reduced values being nearly identical and with stable mean differences across chronological age.

genetics↗

bioRxiv2024

CREB3 gain of function variants protect against ALS

Amyotrophic lateral sclerosis (ALS) is a fatal and rapidly evolving neurodegenerative disease that arises from the loss of glutamatergic corticospinal neurons (CSN) and cholinergic motoneurons (MN). The disease is mostly sporadic, but genetics is expected to highly contribute to disease onset and progression. Genome wide association studies identified a few genetic disease modifiers, mostly associated with a negative outcome, and demonstrated that ALS is primarily a disease of excitatory glutamatergic neurons. Here, we reasoned that at least a subpart of genetic disease modifiers may directly modulate the molecular pathways selectively activated in vulnerable neurons as the disease progresses, and concentrated on CSN for their selective vulnerability and glutamatergic identity. We implemented comparative cross-species transcriptomics using snRNAseq data from postmortem motor cortex of ALS patients and controls, and longitudinal RNAseq data from anatomically defined CSN purified from the Sod1G86R mouse model of ALS. We report that disease vulnerable neuronal populations undergo ER stress and altered mRNA translation, and identify the transcription factor CREB3 and its regulatory network as a resilience marker of neuronal dysfunction in ALS. Using genetic and epidemiologic analyses we further identify the rare variant CREB3R119G (rs11538707) as a new disease modifier in ALS. Through gain of function, CREB3R119G decreases both the risk of developing ALS and the progression rate of ALS patients. This study reveals novel genetic variants that protect against ALS and highlights the benefice of combining transcriptomics and genetics to identify new disease modifiers and therapeutic targets.

genomics↗

bioRxiv2024

Out of the single-neuron straitjacket: neurons within assemblies change selectivity and their reconfiguration underlies dynamic coding

We investigated cell assemblies in the frontal cortex of macaques during two discrimination tasks. Focusing on the period of goal-action transformation, we extracted spikes fired during assembly activation from the full neural activity and showed that the contribution of a neuron to assembly coding, when it coordinates with other assembly neurons, differs from its coding in isolation. Neurons with their flexible participation to multiple assemblies contributed to the encoding of new information not encoded by the neurons alone. Even non-discriminative neurons acquired selectivity as part of the collective activity of the assemblies. Thus, neurons in their assemblies process distinct information for various purposes as a chess simul master, playing on multiple chessboards. The reconfiguration of the participation of the neurons into different assemblies in the goal-action transformation process translated into a dynamic form of coding, whereas minimal reconfiguration was associated with the static goal coding of the memory period.

neuroscience↗

bioRxiv2024

History bias and its perturbation of the stimulus representation in the macaque prefrontal cortex.

Multiple history biases affect our representation of magnitudes, such as time, distance, and size. It is not clear whether the previous stimuli interfere with the discrimination process from the moment of stimulus presentation, during working memory retention, or even later during the decision-making phase. We used a spatial discrimination task involving two stimuli of different magnitudes, presented sequentially at various distances from the center. The monkeys task was to select the farthest of them. We showed that the previous stimulus magnitude generated a contraction bias effect, but only when its stimulus features differed from those of the current stimulus. In this case, at the neural level we also observed that the decoding of the stimulus magnitude achieved the highest accuracy when it matched the magnitude of the preceding stimulus for which the decoder was trained. This indicates that past stimuli can affect magnitude processing already during the stimulus presentation, even before the decision process. Interestingly, this effect manifested when the trace of the previous stimulus magnitude reactivated in the second part of the stimulus presentation after an "activity-silent" period.

neuroscience↗

bioRxiv2024

Effects of in vitro hemolysis and repeated freeze-thaw cycles in protein abundance quantification using the SomaScan and Olink assays

SomaScan and Olink are affinity-based platforms that aim to estimate the relative abundance of thousands of human proteins with a broad range of endogenous concentrations. In this study, we investigated the effects of in vitro hemolysis and repeated freeze-thaw cycles in protein abundance quantification across 10,776 (11K SomaScan) and 1472 (Olink Explore 1536) analytes, respectively. Using SomaScan, we found two distinct groups, each one consisting of 4% of all aptamers, affected by either hemolysis or freeze-thaw cycles. Using Olink, we found 6% of analytes affected by freeze-thaw cycles and nearly half of all measured probes significantly impacted by hemolysis. Moreover, we observed that Olink probes affected by hemolysis target proteins with a larger number of annotated protein-protein interactions. We found that Olink probes affected by hemolysis were significantly associated with the erythrocyte proteome, whereas SomaScan probes were not. Given the extent of the observed nuisance effects, we propose that unbiased, quantitative methods of evaluating hemolysis, such as the hemolysis index successfully implemented in many clinical laboratories, should be adopted in proteomics studies. We provide detailed results for each SomaScan and Olink probe in the form of extensive Supplementary Data files to be used as resources for the growing user communities of both platforms.

molecular biology↗