title: RhoA/ROCK2 signalling is enhanced by PDGF-AA in fibro-adipogenic progenitor cells in DMD

abstract: The lack of dystrophin expression in Duchenne muscular dystrophy (DMD) leads to muscle necrosis and replacement of muscle tissue by fibro-adipose tissue. Although the role of some growth factors in the process of fibrogenesis has been previously studied, the pathways that are activated by PDGF-AA in muscular dystrophies have not been described so far. Herein we report the effects of PDGF-AA on the fibrotic process in muscular dystrophies by performing a quantitative proteomic study in DMD isolated fibro-adipogenic precursor cells (FAPs) treated with PDGF-AA. In vitro studies showed that RhoA/ROCK2 pathway is activated by PDGF-AA and induces the activation of FAPs. The inhibition of RhoA/ROCK signalling pathway by C3-exoenzyme or fasudil attenuated the effects of PDGF-AA. The blocking effects of RhoA/ROCK pathway were analysed in the dba/2J-mdx murine model with fasudil. Grip strength test showed an improvement in the muscle function and histological studies demonstrated reduction of the fibrotic area. Our results suggest that blockade of RhoA/ROCK could attenuate the activation of FAPs and could be considered a potential therapeutic approach for muscular dystrophies.


title: The reserve of joint torque determines movement coordination

abstract: Humans coordinate biomechanical degrees of freedom to perform tasks at minimum cost. When reaching a target from a seated position, the trunk-arm-forearm coordination moves the hand to the well-defined spatial goal, while typically minimising hand jerk and trunk motion. However, due to fatigue or stroke, people visibly move the trunk more, and it is unclear what cost can account for this. Here we show that people recruit their trunk when the torque at the shoulder is too close to the maximum. We asked 26 healthy participants to reach a target while seated and we found that the trunk contribution to hand displacement increases from 11% to 27% when an additional load is handled. By flexing and rotating the trunk, participants spontaneously increase the reserve of anti-gravitational torque at the shoulder from 25% to 40% of maximal voluntary torque. Our findings provide hints on how to include the reserve of torque in the cost function of optimal control models of human coordination in healthy fatigued persons or in stroke victims.

category: neuroscience


title: A multifaceted role of progranulin in regulating amyloid-beta dynamics and responses

abstract: Haploinsufficiency of progranulin (PGRN) is a leading cause of frontotemporal lobar degeneration (FTLD). PGRN polymorphisms are associated with Alzheimers disease (AD). PGRN is highly expressed in the microglia near A{beta} plaques and influences plaque dynamics and microglial activation. However, the detailed mechanisms remain elusive. Here we report that PGRN deficiency reduces human APP and A{beta} levels in the young male but not female mice. PGRN deficient microglia exhibit increased expression of markers associated with microglial activation, including CD68, Galectin-3, TREM2 and GPNMB, specifically near A{beta} plaques. In addition, PGRN loss leads to up-regulation of lysosome proteins and an increase in the nuclear localization of TFE3, a transcription factor involved in lysosome biogenesis. Cultured PGRN deficient microglia show enhanced nuclear translocation of TFE3 and inflammation in response to A{beta} fibril treatment. Taken together, our data revealed a sex- and age-dependent effect of PGRN on amyloid metabolism and a role of PGRN in regulating lysosomal activities and inflammation in plaque-associated microglia, which may contribute to the disease mechanism associated with PGRN polymorphisms in AD.


title: Maintenance of Bound or Independent Features in Visual Working Memory is Task-dependent

abstract: Over the last decade, seemingly conflicting results were obtained regarding the question of whether features of an object are stored separately, or bound together, in visual working memory. Many of these studies are based on an implicit assumption about a default, or fixed, mode of working memory storage. In contrast, here we asked whether the anticipated memory probes used in a given experiment might determine the format in which information is maintained in working memory, consistent with its task-oriented function. In order to test this flexible maintenance hypothesis, we recorded EEG while subjects performed a delayed-match-to-sample task with different requirements and load. In Experiment 1, by contrasting conditions with and without the requirement of maintaining bound features, we found significant differences in EEG signals recorded in central-parietal channels while controlling for differences in visual stimulation. Such difference was confirmed by multivariate pattern analysis (MVPA). Moreover, behavior results, topographical distributions and cross-contrast MVPA decoding jointly suggested that this effect is not the same as task load effect. These results were confirmed in Experiment 2 with an independent group of subjects with the same paradigm, providing reliable evidence that the format of object maintenance in visual working memory could be flexibly shaped by the current task.


title: Phase- and State-Dependent Modulation of Breathing Pattern by preBötzinger Complex Somatostatin Expressing Neurons

abstract:
As neuronal subtypes are increasingly categorized, delineating their functional role is paramount. The preBotzinger Complex (preBotC) subpopulation expressing the neuropeptide somatostatin (SST) is classified as mostly excitatory, inspiratory-modulated and not rhythmogenic. We further characterized their phenotypic identity; 87% were glutamatergic and the balance were glycinergic and/or GABAergic. We then used optogenetics to investigate their modulatory role in both anesthetized and freely moving mice. In anesthetized mice, short photostimulation (100 ms) of preBotC SST+ neurons modulated breathing-related variables in a combinatory phase- and state-dependent manner; changes in inspiratory duration, inspiratory peak amplitude (Amp), and phase were different at higher ([≥]2.5 Hz) vs. lower (<2.5 Hz) breathing frequency. Moreover, we observed a biphasic effect of photostimulation during expiration that is probabilistic, i.e., photostimulation given at the same phase in consecutive cycles can evoke opposite responses (lengthening vs. shortening of the phase). This unexpected probabilistic state- and phase-dependent responses to photostimulation exposed properties of the preBotC that were not predicted and cannot be readily accounted for in current models of preBotC pattern generation. In freely moving mice, prolonged photostimulation decreased f in normoxia, hypoxia, or hypercapnia, and increased Amp and produced a phase advance, which was similar to the results in anesthetized mice when f[≥]2.5 Hz. We conclude that preBotC SST+ neurons are a key mediator of the extraordinary and essential lability of breathing pattern.

Key points summaryO_LIWe transfected preBotzinger Complex (preBotC) somatostatin-expressing (SST+) neurons, which modulate respiratory pattern, but are not rhythmogenic, with channelrhodopsin to investigate phase- and state-dependent modulation of breathing pattern in anesthetized and freely behaving mice in normoxia, hypoxia, and hypercapnia.
C_LIO_LIIn anesthetized mice, photostimulation of preBotC SST+ neurons during inspiration increased inspiratory duration and amplitude regardless of baseline breathing frequency, f.
C_LIO_LIIn anesthetized mice with low f (<2.5 Hz), photostimulation of preBotC SST+ neurons during expiration evoked either phase advance or phase delay, whereas in anesthetized mice with high f ([≥]2.5 Hz) and in freely behaving mice in normoxia, hypoxia, or hypercapnia, photostimulation always evoked phase advance.
C_LIO_LIPhase- and state-dependency is a function of overall breathing network excitability.
C_LIO_LIThe f-dependent probabilistic modulation of breathing pattern by preBotC SST+ neurons was unexpected, requiring reconsideration of current models of preBotC function, which neither predict nor can readily account for such responses.
C_LI


title: Evidence provided by high-impact cell culture studies does not support authors' claims

abstract:
BackgroundReliability of preclinical research is of critical concern. Previous studies demonstrate the low reproducibility in research and recommend raising standards to improve reproducibility and robustness. One understudied aspect of this quality issue is the harmony between the hypotheses and the experimental design in published work.

Methods and findingsIn this study we focused on highly cited cell culture studies and investigated whether the claims of the study are backed with sufficient experimental evidence or not. We created an open access database containing all 282 claims asserted by 103 different high-impact articles as well as the results of this study. Our findings revealed that only 64% of all claims were sufficiently supported by evidence and there were concerning misinterpretations such as considering the results of tetrazolium salt reduction assays as indicators of cell death or apoptosis.

ConclusionsOur analysis revealed an alarming discordance between the actual experimental findings and the way that the manuscript is written to discuss them in highly cited cell culture studies. In order to improve quality of pre-clinical research, we require a clear nomenclature by which different cell culture claims are distinctively categorized, materials and methods sections to be written more meticulously and cell culture techniques to be selected and utilized more carefully.

category: cell biology


title: Diagnostic classification based on DNA methylation profiles using sequential machine learning approaches.

abstract:
Aberrant methylation patterns in human DNA have great potential for the discovery of novel diagnostic and disease progression biomarkers. In this paper, we used machine learning algorithms to identify promising methylation sites for diagnosing cancerous tissue and to classify patients based on methylation values at these sites.

We used genome-wide DNA methylation patterns from both cancerous and normal tissue samples, obtained from the Genomic Data Commons consortium and trialled our methods on three types of urological cancer. A decision tree was used to identify the methylation sites most useful for diagnosis.

The identified locations were then used to train a neural network to classify samples as either cancerous or non-cancerous. Using this two-step approach we found strong indicative biomarker panels for each of the three cancer types.

These methods could likely be translated to other cancers and improved by using non-invasive liquid methods such as blood instead of biopsy tissue.

category: bioinformatics


title: Persistence and anti-persistence in treadmill walking

abstract:
BackgroundLong-range persistent correlations in stride time (ST) and length (SL) are the fundamental traits of treadmill gait. Our recent work showed that the ST and SL time series statistical properties originated from the superposition of large-scale trends and small-scale fluctuations (residuals). Trends served as the control manifolds about which ST and SL fluctuated. The scaling exponents of the residuals were slightly smaller than 0.5.

Research questionDo random changes in treadmill belt speed affect the trend properties and scaling exponents of ST/SL residuals?

MethodsWe used Multivariate Adaptive Regression Splines (MARS) to determine gait trends during a walk on a treadmill whose belt speed was perturbed by a strong random noise. Then, we calculated the scaling exponents of MARS residuals with the madogram estimator.

ResultsExcept for the ST at the lowest treadmill speed v = 0.8 m/s, the normalized trend duration was at least three times greater than that for the unperturbed walk. The Cauchy distribution scale parameter, which served as a measure of the width of SL and ST trend slope distributions, was at v = 1.2 m/s, almost 50% and 25% smaller than the unperturbed values. The differences were even greater at v = 1.6 m/s: 73% and 83%. For all speeds, the ST and SL MARS residuals were strongly anti-persistent. At v = 1.2 m/s, the corresponding scaling exponents were equal to 0.37{+/-}0.10 and 0.25{+/-}0.09. Apart from ST at v = 0.8 m/s, the ST/SL scaling indices were close to 0.5.

SignificancePersistence of gait parameters is closely related to the properties of their trends. Longer trends with a gentle slope and strong anti-persistence of ST/SL residuals are the manifestations or tight control required during the perturbed treadmill walk.

category: physiology


title: Plagl1 is part of the mammalian retinal injury response and a critical regulator of Muller glial cell quiescence

abstract: Retinal damage triggers reactive gliosis in Muller glia across vertebrate species, but only in regenerative animals, such as teleost fish, do Muller glia initiate repair; proliferating and undergoing neurogenesis to replace lost cells. By mining scRNA-seq and bulk RNA-seq datasets, we found that Plagl1, a maternally imprinted gene, is dynamically regulated in reactive Muller glia post-insult, with transcript levels transiently increasing before stably declining. To study Plagl1 retinal function, we examined Plagl1+/-pat null mutants postnatally, revealing defects in retinal architecture, visual signal processing and a reactive gliotic phenotype. Plagl1+/-pat Muller glia proliferate ectopically and give rise to inner retinal neurons and photoreceptors. Transcriptomic and ATAC-seq profiles revealed similarities between Plagl1+/-pat retinas and neurodegenerative and injury models, including an upregulation of pro-gliogenic and pro-proliferative pathways, such as Notch, not observed in wild-type retinas Plagl1 is thus an essential component of the transcriptional regulatory networks that retain mammalian Muller glia in quiescence.


title: Adaptive mossy cell circuit plasticity after status epilepticus

abstract: Hilar mossy cells control network function in the hippocampus through both direct excitation and di-synaptic inhibition of dentate granule cells (DGCs). Substantial mossy cell loss occurs after epileptic seizures; however the contribution of surviving mossy cells to network activity in the reorganized dentate gyrus is unknown. To examine functional circuit changes after pilocarpine-induced status epilepticus, we optogenetically stimulated mossy cells in acute hippocampal slices. In control mice, activation of mossy cells produced monosynaptic excitatory and di-synaptic GABAergic currents in DGCs. In pilocarpine-treated mice, mossy cell density and excitation of DGCs were reduced in parallel, with only a minimal reduction in feedforward inhibition, enhancing the inhibition:excitation ratio. Surprisingly, mossy cell-driven excitation of parvalbumin-positive basket cells, the primary mediators of feed-forward inhibition, was maintained, indicating increased connectivity between surviving mossy cells and these targets. Our results suggest that mossy cell outputs reorganize following seizures, increasing their net inhibitory effect in the hippocampus.


title: Axonal CB1 receptors mediate inhibitory bouton formation via cAMP increase

abstract: Experience-dependent formation and removal of synapses are essential throughout life. For instance, GABAergic synapses are removed to facilitate learning, and strong excitatory activity is accompanied by formation of inhibitory synapses. We recently discovered that active dendrites trigger the growth of inhibitory synapses via CB1 receptor-mediated endocannabinoid signaling, but the underlying mechanism remained unclear. Using two-photon microscopy to monitor the formation of individual inhibitory boutons, we found that CB1 receptor activation mediated formation of inhibitory boutons and promoted their subsequent stabilization. Inhibitory bouton formation did not require neuronal activity and was independent of Gi/o protein signaling, but was directly induced by elevating cAMP levels using forskolin and by activating Gs proteins using DREADDs. Our findings reveal that axonal CB1 receptors signal via unconventional downstream pathways and that inhibitory bouton formation is triggered by an increase in axonal cAMP levels. Our results demonstrate a novel role for axonal CB1 receptors in axon-specific, and context-dependent, inhibitory synapse formation.


title: Auditory processing remains sensitive to environmental experience during adolescence

abstract:
Development is a time of great opportunity. A heightened period of neural plasticity contributes to dramatic improvements in perceptual, motor, and cognitive skills. However, developmental plasticity poses a risk: greater malleability of neural circuits exposes them to environmental factors that may impede behavioral maturation. While these risks are well-established prior to sexual maturity (i.e., critical periods), the degree of neural vulnerability during adolescence remains uncertain. To address this question, we induced a transient period of hearing loss (HL) spanning adolescence in the gerbil, confirmed by assessment of circulating sex hormones, and asked whether behavioral and neural deficits are diminished. Wireless recordings were obtained from auditory cortex neurons during perceptual task performance, and within-session behavioral and neural sensitivity were compared. We found that a transient period of adolescent HL caused a significant perceptual deficit (i.e., amplitude modulation detection thresholds) that could be attributed to degraded auditory cortex processing, as confirmed with both single neuron and population-level analyses. In contrast, perceptual deficits did not occur when HL of the same duration was induced in adulthood. To determine whether degraded auditory cortex encoding was attributable to an intrinsic change, we obtained auditory cortex brain slices from adolescent HL animals, and recorded synaptic and discharge properties from auditory cortex pyramidal neurons. There was a clear and novel phenotype, distinct from critical period HL: excitatory postsynaptic potential amplitudes were elevated in adolescent HL animals, whereas inhibitory postsynaptic potentials were unchanged. This is in contrast to critical period deprivation, where there are large changes to synaptic inhibition. Taken together, these results show that diminished adolescent sensory experience can cause long-lasting behavioral deficits that originate, in part, from a dysfunctional cortical circuit.

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=84 SRC="FIGDIR/small/439537v2_ufig1.gif" ALT="Figure 1">
View larger version (18K):
org.highwire.dtl.DTLVardef@50b787org.highwire.dtl.DTLVardef@1410662org.highwire.dtl.DTLVardef@a0fa6org.highwire.dtl.DTLVardef@897b1c_HPS_FORMAT_FIGEXP  M_FIG Summary of experimental design and main findings.

C_FIG


title: Cortico-Fugal Regulation of Predictive Coding.

abstract: Sensory systems must account for both contextual factors and prior experience to adaptively engage with the dynamic external environment. In the central auditory system, neurons modulate their responses to sounds based on statistical context. These response modulations can be understood through a hierarchical predictive coding lens: responses to repeated stimuli are progressively decreased, in a process known as repetition suppression, whereas unexpected stimuli produce a prediction error signal. Prediction error incrementally increases along the auditory hierarchy from the inferior colliculus (IC) to the auditory cortex (AC), suggesting that these regions may engage in hierarchical predictive coding. A potential substrate for top-down predictive cues is the massive set of descending projections from the auditory cortex to subcortical structures, although the role of this system in predictive processing has never been directly assessed. We tested the effect of optogenetic inactivation of the auditory cortico-collicular feedback in awake mice on responses of IC neurons to stimuli designed to test prediction error and repetition suppression. Inactivation of the cortico-collicular pathway led to a decrease in prediction error in IC. Repetition suppression was unaffected by cortico-collicular inactivation, suggesting that this metric may reflect fatigue of bottom-up sensory inputs rather than predictive processing. We also discovered populations of IC neurons that exhibit repetition enhancement, a sequential increase in firing with stimulus repetition. Cortico-collicular inactivation led to a decrease in repetition enhancement in the central nucleus of IC, suggesting that it is a top-down phenomenon. Negative prediction error, a stronger response to a tone in a predictable rather than unpredictable sequence, was suppressed in shell IC units during cortico-collicular inactivation. These changes in predictive coding metrics arose from bidirectional modulations in the response to the standard and deviant contexts, such that neurons in IC responded more similarly to each context in the absence of cortical input. We also investigated how these metrics compare between the anesthetized and awake states by recording from the same neurons under both conditions. We found that metrics of predictive coding and deviance detection differ depending on the anesthetic state of the animal, with negative prediction error emerging in the central IC and repetition enhancement and prediction error being more prevalent in the absence of anesthesia. Overall, our results demonstrate that the auditory cortex provides cues about the statistical context of sound to subcortical brain regions via direct feedback, regulating processing of both prediction and repetition.


title: Influence of Mpv17 on hair-cell mitochondrial homeostasis, synapse integrity, and vulnerability to damage in the zebrafish lateral line

abstract: Noise exposure is particularly stressful to hair-cell mitochondria, which must produce enough energy to meet high metabolic demands as well as regulate local intracellular Ca2+ concentrations. Mitochondrial Inner Membrane Protein 17 (Mpv17) functions as a non-selective channel and plays a role in maintaining mitochondrial homeostasis. In zebrafish, hair cells in mpv17a9/a9 mutants displayed elevated levels of reactive oxygen species (ROS), elevated mitochondrial calcium, hyperpolarized transmembrane potential, and greater vulnerability to neomycin, indicating impaired mitochondrial function. Using a strong water current to overstimulate hair cells in the zebrafish lateral line, we observed mpv17a9/a9 mutant hair cells were more vulnerable to morphological disruption and hair-cell loss than wild type siblings simultaneously exposed to the same stimulus. To determine the role of mitochondrial homeostasis on hair-cell synapse integrity, we surveyed synapse number in mpv17a9/a9 mutants and wild type siblings as well as the sizes of presynaptic dense bodies (ribbons) and postsynaptic densities immediately following stimulus exposure. We observed mechanically injured mpv17a9/a9 neuromasts, while they lost a greater number of hair cells, lost a similar number of synapses per hair cell relative to wild type. Additionally, we quantified the size of hair cell pre- and postsynaptic structures and observed significantly enlarged wild type postsynaptic densities, yet relatively little change in the size of mpv17a9/a9 postsynaptic densities following stimulation. These results suggest impaired hair-cell mitochondrial activity influences synaptic morphology and hair-cell survival but does not exacerbate synapse loss following mechanical injury.


title: Data-driven and interpretable machine-learning modeling to explore the fine-scale environmental determinants of malaria vectors biting rates in rural Burkina Faso

abstract:
BackgroundImproving the knowledge and understanding of the environmental determinants of malaria vectors abundances at fine spatiotemporal scales is essential to design locally tailored vector control intervention. This work aimed at exploring the environmental tenets of human-biting activity in the main malaria vectors (Anopheles gambiae s.s., Anopheles coluzzii and Anopheles funestus) in the health district of Diebougou, rural Burkina Faso.

MethodsAnopheles human-biting activity was monitored in 27 villages during 15 months (in 2017-2018), and environmental variables (meteorological and landscape) were extracted from high resolution satellite imagery. A two-step data-driven modeling study was then carried-out. Correlation coefficients between the biting rates of each vector species and the environmental variables taken at various temporal lags and spatial distances from the biting events were first calculated. Then, multivariate machine-learning models were generated and interpreted to i) pinpoint primary and secondary environmental drivers of variation in the biting rates of each species and ii) identify complex associations between the environmental conditions and the biting rates.

ResultsMeteorological and landscape variables were often significantly correlated with the vectors biting rates. Many nonlinear associations and thresholds were unveiled by the multivariate models, both for meteorological and landscape variables. From these results, several aspects of the bio-ecology of the main malaria vectors were precised or hypothesized for the Diebougou area, including breeding sites typologies, development and survival rates in relation to weather, flight ranges from breeding sites, dispersal related to landscape openness.

ConclusionsUsing high resolution data in an interpretable machine-learning modeling framework proved to be an efficient way to enhance the knowledge of the complex links between the environment and the malaria vectors at a local scale. More broadly, the emerging field of interpretable machine-learning has significant potential to help improving our understanding of the complex processes leading to malaria transmission.

category: ecology


title: Spotted lanternfly nymphs use multiple righting behaviors during landing

abstract: Unlike large animals, insects and other very small animals are so unsusceptible to impact-related injuries that they can use falling for dispersal and predator evasion. Reorienting to land upright can mitigate lost access to resources and predation risk. Such behaviors are critical for the spotted lanternfly (SLF) (Lycorma delicatula), an invasive, destructive insect pest spreading rapidly in the US. High-speed video of SLF nymphs released under different conditions showed that these insects self-right using both active midair righting motions previously reported for other insects, and novel post-impact mechanisms that take advantage of their ability to experience near-total energy loss on impact. Unlike during terrestrial self-righting, in which an animal initially at rest on its back uses appendage motions to flip over, SLF nymphs impacted the surface at varying angles and then self-righted during the rebound using coordinated body rotations, foot-substrate adhesion, and active leg motions. These previously-unreported strategies were found to promote disproportionately upright, secure landings on both hard, flat surfaces and tilted, compliant host plant leaves. Our results highlight the importance of examining biomechanical phenomena in ecologically-relevant contexts, and show that, for small animals, the post-impact bounce period can be critical for achieving an upright landing.


title: Many ways to stick the landing: novel righting strategies allow spotted lanternfly nymphs to land on diverse substrates


title: Multi-Trait Machine and Deep Learning Models for Genomic Selection using Spectral Information in a Wheat Breeding Program

abstract:
Prediction of breeding values and phenotypes is central to plant breeding and has been revolutionized by the adoption of genomic selection (GS). Use of machine and deep learning algorithms applied to complex traits in plants can improve prediction accuracies in the context of GS. Spectral reflectance indices further provide information about various physiological parameters previously undetectable in plants. This research explores the potential of multi-trait (MT) machine and deep learning models for predicting grain yield and grain protein content in wheat using spectral information in GS models. This study compares the performance of four machine and deep learning-based uni-trait (UT) and MT models with traditional GBLUP and Bayesian models. The dataset consisted of 650 recombinant inbred lines from a spring wheat breeding program, grown for three years (2014-2016), and spectral data were collected at heading and grain filling stages. MT-GS models performed 0-28.5% and -0.04-15% superior to the UT-GS models for predicting grain yield and grain protein content. Random forest and multilayer perceptron were the best performing machine and deep learning models to predict both traits. These two models performed similarly under UT and MT-GS models. Four explored Bayesian models gave similar accuracies, which were less than machine and deep learning-based models, and required increased computational time. Green normalized difference vegetation index best predicted grain protein content in seven out of the nine MT-GS models. Overall, this study concluded that machine and deep learning-based MT-GS models increased prediction accuracy and should be employed in large-scale breeding programs.

Core IdeasO_LIPotential for combining high throughput phenotyping, machine and deep learning in breeding.
C_LIO_LIMulti-trait models exploit information from secondary correlated traits efficiently.
C_LIO_LISpectral information improves genomic selection models.
C_LIO_LIDeep learning can aid plant breeders owing to increased data generated in breeding programs
C_LI

category: genetics


title: De novo genome assembly and functional annotation for Fusarium langsethiae

abstract:
MotivationFusarium langsethiae is a T-2 and HT-2 mycotoxins producing Fusarium species firstly characterised in 2004. It is commonly isolated from oats in Northern Europe. T-2 and HT-2 mycotoxins exhibit immunological and haemotological effects in animal health mainly through inhibition of protein, RNA and DNA synthesis. The development of a high-quality and comprehensively annotated assembly for this species is therefore essential in providing the molecular understanding and the mechanism of T-2 and HT-2 biosynthesis in F. langsethiae to help develop effective control strategies.

ResultsThe F. langsethiae assembly was produced using PacBio long reads, which were then assembled independently using Canu, SMARTdenovo and Flye; producing a genome assembly total length of 59Mb and N50 of 3.51Mb. A total of 19,336 coding genes were identified using RNA-Seq informed ab-initio gene prediction. Finally, predicting genes were annotated using the basic local alignment search tool (BLAST) against the NCBI non-redundant (NR) genome database and protein hits were annotated using InterProScan. Genes with blast hits were functionally annotated with Gene Ontology.

Contactf.mohareb@cranfield.ac.uk

Data availabilityRaw sequence reads and assembled genome can be downloaded from: GenBank under the accession JAFFKB000000000

category: genomics


title: Optofluidic Fiber Component for Separation and counting of Micron-Sized Particles

abstract: An all-fiber separation component capable of sorting and counting micron-sized particles based on size is presented. A sequence of silica fiber capillaries with various diameters and longitudinal cavities were used to fabricate the component for separation and detection in an uninterrupted flow. Fluorescence microparticles of 1 m and 10 m sizes are mixed in a visco-elastic fluid and infused into the all-fiber separation component. Elasto-inertial forces focus the larger particle to the center of the silica capillary, while the smaller microparticles exit from a side capillary. Analysis of the separated particles at the output showed a separation efficiency of 100% for the 10 m and 97% for the 1 m particles. In addition, the counting of the larger particles is demonstrated in the same flow. The separated 10 m particles are further routed through another all-fiber component for counting. A counting speed of ~1400 particles/min and with the variation in amplitude of 10% is achived. A combination of separation and counting can be powerful tool may find several applications in biology and medicine, such as separation and analysis of exosomes, bacteria, and blood cell sub-populations.

category: bioengineering


title: A3D 2.0 update for the prediction and optimization of protein solubility

abstract: Protein aggregation propensity is a property imprinted in protein sequences and structures, being associated with the onset of human diseases and limiting the implementation of protein-based biotherapies. Computational approaches stand as cost-effective alternatives for reducing protein aggregation and increasing protein solubility. AGGRESCAN 3D (A3D) is a structure-based predictor of aggregation that takes into account the conformational context of a protein, aiming to identify aggregation-prone regions exposed in protein surfaces. Here we inspect the updated 2.0 version of the algorithm, which extends the application of A3D to previously inaccessible proteins and incorporates new modules to assist protein redesign. Among these features, the new server includes stability calculations and the possibility to optimize protein solubility using an experimentally validated computational pipeline. Finally, we employ defined examples to navigate the A3D RESTful service, a routine to handle extensive protein collections. Altogether, this work is conceived to train and assist A3D non-experts in the study of aggregation-prone regions and protein solubility redesign.


title: PhosIDP: a web tool to visualize the location of phosphorylation sites in disordered regions

abstract: Charge is a key determinant of intrinsically disordered protein (IDP) and intrinsically disordered region (IDR) properties. IDPs and IDRs are enriched in sites of phosphorylation, which alters charge. Visualizing the degree to which phosphorylation modulates the charge profile of a sequence would assist in the functional interpretation of IDPs and IDRs. PhosIDP is a web tool that shows variation of charge and fold propensity upon phosphorylation. In combination with the displayed location of protein domains, the information provided by the web tool can lead to functional inferences for the consequences of phosphorylation. IDRs are components of many proteins that form biological condensates. It is shown that IDR charge, and its modulation by phosphorylation, is more tightly controlled for proteins that are essential for condensate formation than for those present in condensates but inessential.


title: Clustering single-cell RNA-seq data by rank constrained similarity learning

abstract:
MotivationRecent breakthroughs of single-cell RNA sequencing (scRNA-seq) technologies offer an exciting opportunity to identify heterogeneous cell types in complex tissues. However, the unavoidable biological noise and technical artifacts in scRNA-seq data as well as the high dimensionality of expression vectors make the problem highly challenging. Consequently, although numerous tools have been developed, their accuracy remains to be improved.

ResultsHere, we introduce a novel clustering algorithm and tool RCSL (Rank Constrained Similarity Learning) to accurately identify various cell types using scRNA-seq data from a complex tissue. RCSL considers both local similarity and global similarity among the cells to discern the subtle differences among cells of the same type as well as larger differences among cells of different types. RCSL uses Spearmans rank correlations of a cells expression vector with those of other cells to measure its global similarity, and adaptively learns neighbour representation of a cell as its local similarity. The overall similarity of a cell to other cells is a linear combination of its global similarity and local similarity. RCSL automatically estimates the number of cell types defined in the similarity matrix, and identifies them by constructing a block-diagonal matrix, such that its distance to the similarity matrix is minimized. Each block-diagonal submatrix is a cell cluster/type, corresponding to a connected component in the cognate similarity graph. When tested on 16 benchmark scRNA-seq datasets in which the cell types are well-annotated, RCSL substantially outperformed six state-of-the-art methods in accuracy and robustness as measured by three metrics.

AvailabilityThe RCSL algorithm is implemented in R and can be freely downloaded at https://github.com/QinglinMei/RCSL.

Contactguojunsdu@gmail.com, zcsu@uncc.edu

Supplementary informationSupplementary data are available at Bioinformatics online.


title: Borf: Improved ORF prediction in de-novo assembled transcriptome annotation

abstract: ORF prediction in de-novo assembled transcriptomes is a critical step for RNA-Seq analysis and transcriptome annotation. However, current approaches do not appropriately account for factors such as strand-specificity and incompletely assembled transcripts. Strand-specific RNA-Seq libraries should produce assembled transcripts in the correct orientation, and therefore ORFs should only be annotated on the sense strand. Additionally, start site selection is more complex than appreciated as sequences upstream of the first start codon need to be correctly annotated as 5 UTR in completely assembled transcripts, or part of the main ORF in incomplete transcripts. Both of these factors influence the accurate annotation of ORFs and therefore the transcriptome as a whole. We generated four de-novo transcriptome assemblies of well annotated species as a gold-standard dataset to test the impact strand specificity and start site selection have on ORF prediction in real data. Our results show that prediction of ORFs on the antisense strand in data from stranded RNA libraries results in false-positive ORFs with no or very low similarity to known proteins. In addition, we found that up to 23% of assembled transcripts had no stop codon upstream and in-frame of the first start codon, instead comprising a sequence of upstream codons. We found the optimal length cutoff of these upstream sequences to accurately classify these transcripts as either complete (upstream sequence is 5 UTR) or 5 incomplete (transcript is incompletely assembled and upstream sequence is part of the ORF). Here, we present Borf, the better ORF finder, specifically designed to minimise false-positive ORF prediction in stranded RNA-Seq data and improve annotation of ORF start-site prediction accuracy. Borf is written in Python3 and freely available at https://github.com/betsig/borf.


title: Plasticity of the gastrocnemius elastic system in response to decreased work and power demand during growth

abstract: Elastic energy storage and release can enhance performance that would otherwise be limited by the force-velocity constraints of muscle. While functional influence of a biological spring depends on tuning between components of an elastic system (the muscle, spring, driven mass, and lever system), we do not know whether elastic systems systematically adapt to functional demand. To test whether altering work and power generation during maturation alters the morphology of an elastic system, we prevented growing guinea fowl (Numida Meleagris) from jumping. At maturity, we compared the jump performance of our treatment group to that of controls and measured the morphology of the gastrocnemius elastic system. We found that restricted birds jumped with lower jump power and work, yet there were no significant between-group differences in the components of the elastic system. Further, subject-specific models revealed no difference in energy storage capacity between groups, though energy storage was most sensitive to variations in muscle properties (most significantly operating length and least dependent on tendon stiffness). We conclude that the gastrocnemius elastic system in the guinea fowl displays little to no plastic response to decreased demand during growth and hypothesize that neural plasticity may explain performance variation.


title: Integration of computational modeling and quantitative cell physiology reveals central parameters for the brassinosteroid-regulated elongation growth along the axis of the Arabidopsis root

abstract: Brassinosteroids (BR) are key hormonal regulators of plant development. However, whereas the individual components of BR perception and signaling are well characterized experimentally, the question of how they can act and whether they are sufficient to carry out the critical function of cellular elongation remains open. Here, we combined computational modeling with quantitative cell physiology to understand the dynamics of the plasma membrane (PM)-localized BR response pathway during the initiation of cell elongation in the epidermis of the Arabidopsis root tip. The model, consisting of ordinary differential equations, comprises the BR induced hyperpolarization of the PM, the acidification of the apoplast and subsequent cell wall swelling. We demonstrated that the competence of the root epidermal cells for the BR response predominantly depends on the amount and activity of H+-ATPases in the PM. The model further predicted that an influx of cations is required to compensate for the shift of positive charges caused by the apoplastic acidification. A potassium channel was subsequently identified and experimentally characterized, fulfilling this function. Thus, we established the landscape of components and parameters capable of triggering and guiding cellular elongation through the fast response to BRs, a central process in plant development.

category: plant biology


title: Computational modeling and quantitative cell physiology reveal central parameters for the brassinosteroid-regulated cell growth of the Arabidopsis root


title: An enhanced Bouma model fits a hundred people's visual crowding

abstract: Crowding is the failure to recognize an object due to surrounding clutter. Its strength varies across the visual field and individuals. To characterize the statistics of crowding--ultimately to relate psychophysics of crowding to physiology--we measured radial crowding distance and acuity of 105 observers along the four cardinal meridians of the visual field. Fitting the well-known Bouma law -- crowding distance depends linearly on radial eccentricity -- explains 52% of the variance in log crowding distance, cross-validated. Our enhanced Bourma model, with factors for observer, meridian, and target kind, explains 72% of the variance, again cross-validated. The meridional factors confirm previously reported asymmetries. We find a 0.62 horizontal:vertical advantage, a 0.92 lower:upper advantage, and a 0.82 right:left advantage. Crowding distance and acuity have a correlation of 0.41 at the fovea, which drops to 0.23 at {+/-}5 deg along the horizontal midline. Acuity and crowding represent the size and spacing limits of perception. Since they are dissociated in clinical populations (Song et al., 2014; Strappini et al., 2017) and shown here to be only moderately correlated in our sample of mostly university students, clinical testing to predict real-world performance should consider measuring both. In sum, enhancing the Bouma law with terms for meridian, observer, and target kind provides an excellent fit to our 105-person survey of crowding.


title: Intermittent Fasting Enhances Hippocampal Npy Expression to Promote Neurogenesis Following Traumatic Brain Injury

abstract: Interventions for preventing cognitive dysfunction post traumatic brain injury (TBI) is limited. Given that adult hippocampal neurogenesis (AHN) after brain injury contributes to cognitive recovery, and that the AHN is potentially affected by nutritional factors, we asked whether fasting could promote AHN and thus ameliorates cognitive defects after TBI. Here we show that a one-month intermittent fasting (IF) regimen enhanced proliferation of neural stem cells (NSCs) in the subgranular zone (SGZ) of hippocampus 3 days post TBI, as well as improved cognitive performance in Morris water maze (MWM) test. Furthermore, an increase in hippocampal Npy expression was detected in IF group after injury, compared to the mice fed ad libitum (AL), and locally knock-down of Npy in vivo attenuated the aforementioned effects of IF in TBI. These findings suggest that IF promotes AHN following TBI by a mechanism involving enhancement of Npy expression, which may offer novel interventions that might prevent cognitive dysfunction caused by injury.


title: The Effects of Unilateral Transcranial Direct Current Stimulation on Unimanual Laparoscopic Peg-Transfer Task

abstract:
IntroductionEfficient training methods are required for laparoscopic surgical skills training to reduce the time needed for proficiency. Transcranial direct current stimulation (tDCS) is widely used to enhance motor skill acquisition and can be used to supplement the training of laparoscopic surgical skill acquisition. The aim of this study was to investigate the effect of anodal tDCS over the primary motor cortex (M1) on the performance of a unimanual variant of the laparoscopic peg-transfer task.

MethodsFifteen healthy subjects participated in this randomized, double-blinded crossover study involving an anodal tDCS and a sham tDCS intervention separated by 48 hours. On each intervention day, subjects performed a unimanual variant of laparoscopic peg-transfer task in three sessions (baseline, tDCS, post-tDCS). The tDCS session consisted of 10 minutes of offline tDCS followed by 10 minutes of online tDCS. The scores based on the task completion time and the number of errors in each session were used as a primary outcome measure. A linear mixed-effects model was used for the analysis.

ResultsWe found that the scores increased over sessions (p<0.001). However, we found no effects of stimulation (anodal tDCS vs. sham tDCS) and no interaction of stimulation and sessions.

ConclusionThis study suggests that irrespective of the type of current stimulation (anodal and sham) over M1, there was an improvement in the performance of the unimanual peg-transfer task, implying that there was motor learning over time. The results would be useful in designing efficient training paradigms and further investigating the effects of tDCS on laparoscopic peg-transfer tasks.


title: Perineuronal nets affect memory and learning after synapse withdrawal

abstract: Perineuronal nets (PNNs) enwrap mature neurons, playing a role in the control of plasticity and synapse dynamics. PNNs have been shown to have effects on memory formation, retention and extinction in a variety of animal models. It has been proposed that the cavities in PNNs which contain synapses can act as a memory store, which remains stable after events that cause synaptic withdrawal such as anoxia or hibernation. We examine this idea by monitoring positional memory before and after synaptic withdrawal caused by acute hibernation-like state (HLS). Animals lacking hippocampal PNNs due to enzymatic digestion by chondroitinase ABC or knockout of the PNN component aggrecan were compared with wild type controls. HLS-induced synapse withdrawal caused a memory deficit, but not to the level of naive animals and not worsened by PNN attenuation. After HLS, animals lacking PNNs showed faster relearning. Absence of PNNs affected the restoration of inhibitory and excitatory synapses on PNN-bearing neurons. The results support a role for hippocampal PNNs in learning, but not in long-term memory storage.


title: Cross-dataset reproducibility of population receptive field (pRF) estimates and cortical magnification asymmetries

abstract: Population receptive field (pRF) models fit to fMRI data are used to non-invasively measure retinotopic maps in human visual cortex, and these maps are a fundamental component of visual neuroscience experiments. Here, we examined the reproducibility of retinotopic maps across two datasets: a newly acquired retinotopy dataset from New York University (NYU) (n=44) and a public dataset from the Human Connectome Project (HCP) (n=181). Our goal was to assess the degree to which pRF properties are similar across datasets, despite substantial differences in their experimental protocols. The two datasets simultaneously differ in their stimulus apertures, participant pool, fMRI protocol, MRI field strength, and preprocessing pipeline. We assessed the cross-dataset reproducibility of the two datasets in terms of the similarity of vertex-wise pRF estimates and in terms of large-scale polar angle asymmetries in cortical magnification. Within V1, V2, V3, and hV4, the group-median NYU and HCP vertex-wise polar angle estimates were nearly identical. Both eccentricity and pRF size estimates were also strongly correlated between the two datasets, but with a slope different from 1; the eccentricity and pRF size estimates were systematically greater in the NYU data. Next, to compare large-scale map properties, we quantified two polar angle asymmetries in V1 cortical magnification previously identified in the HCP data. The NYU dataset confirms earlier reports that more cortical surface area represents horizontal than vertical visual field meridian, and lower than upper vertical visual field meridian. Together, our findings show that the retinotopic properties of V1, V2, V3, and hV4 can be reliably measured across two datasets, despite numerous differences in their experimental design. fMRI-derived retinotopic maps are reproducible because they rely on an explicit computational model of the fMRI response. In the case of pRF mapping, the model is grounded in physiological evidence of how visual receptive fields are organized, allowing one to quantitatively characterize the BOLD signal in terms of stimulus properties (i.e., location and size). The new NYU Retinotopy Dataset will serve as a useful benchmark for testing hypotheses about the organization of visual areas and for comparison to the HCP 7T Retinotopy Dataset.


title: Cross-dataset reproducibility of human retinotopic maps


title: Dynamic Causal Modeling of Neural Responses to an Orofacial Pneumotactile Velocity Array

abstract: The effective connectivity of neuronal networks during orofacial pneumotactile stimulation with different velocities is still unknown. The present study aims to characterize the effectivity connectivity elicited by three different saltatory velocities (5, 25, and 65 cm/s) over the lower face using dynamic causal modeling on functional magnetic resonance imaging data of twenty neurotypical adults. Our results revealed the contralateral SI and SII as the most likely sources of the driving inputs within the sensorimotor network for the pneumotactile stimuli, suggesting parallel processing of the orofacial pneumotactile stimuli. The 25 cm/s pneumotactile stimuli modulated forward interhemispheric connection from the contralateral SII to the ipsilateral SII, suggesting a serial interhemispheric connection between the bilateral SII. Moreover, the velocity pneumotactile stimuli influenced the contralateral M1 through both contralateral SI and SII, indicating that passive pneumotactile stimulation may positively impact motor function rehabilitation. Furthermore, the slow velocity 5 cm/s pneumotactile stimuli modulated both forward and backward connections between the right cerebellar lobule VI and the contralateral left SI, SII, and M1, while the medium velocity 25 cm/s pneumotactile stimuli modulated both forward and backward connections between the right cerebellar lobule VI and the contralateral left SI and M1. Our findings suggest that the right cerebellar lobule VI plays a role in the sensorimotor network through feedforward and feedback neuronal pathways.


title: fMRI Informed Montage Selection for Transcranial Electrical Stimulation: Frontoparietal Synchronization for Drug Cue Reactivity

abstract:
BackgroundFrontoparietal network (FPN) with multiple cortical nodes is involved in executive functions. Transcranial electrical stimulation (tES) can potentially modulate interactions between these nodes using frontoparietal synchronization (FPS). Here we used fMRI and computational head models (CHMs) to inform electrode montage and dosage selection in FPS.

MethodsSixty methamphetamine users completed an fMRI drug cue-reactivity task. Two sets of 4x1 HD electrodes with anode over F3 and F4 were simulated and spheres around maximum electric field in each hemisphere were defined as frontal seeds. Using frontal seeds, a task-based functional connectivity analysis was conducted based on a seed-to-whole brain generalized psychophysiological interaction (gPPI). Electrode placement for parietal sites was selected based on gPPI results. Task-based and resting-state connectivity were compared between fMRI-informed and classic F3-P3/F4-P4 montages.

ResultsWhole-brain gPPI showed two significant clusters (left: 506 voxels P=0.006, right: 455 voxels P=0.016), located in the inferior parietal lobule under the CP5 and CP6 electrode location. Pair-wise ROI-based gPPI comparing informed (F3-CP5/F4-CP6) and classic (F3-P3/F4-P4) montages showed significant increased PPI and resting-state connectivity only in the informed montage. Cue-induced craving score was also correlated with left (F3-CP5) frontoparietal connectivity in the fMRI-informed montage.

ConclusionThis study proposes an analytic pipeline to select electrode montage and dosage in dual site tES using CHMs and task-based connectivity. Stimulating F3-F4 can tap into both FPN and saliency network (SN) based on the montage selection. Using CHM and fMRI will be essential to navigating ample parameter space in the stimulation protocols for future tES studies.

HighlightsO_LIWe demonstrated a methodology for montage selection in network-based tES
C_LIO_LITask-based functional connectivity can inform dual-site tES montage selection
C_LIO_LIHead models can help to induce balance tES dose in targeted brain regions
C_LIO_LITargeting DLPFC with tES can tap into both saliency and frontoparietal networks
C_LIO_LILower resting-state frontoparietal connectivity before cue exposure followed by a greater craving
C_LI


title: Within-cycle instantaneous frequency profiles report oscillatory waveform dynamics.

abstract: Non-sinusoidal waveform is emerging as an important feature of neuronal oscillations. However, the role of single cycle shape dynamics in rapidly unfolding brain activity remains unclear. Here, we develop an analytical framework that isolates oscillatory signals from time-series using masked Empirical Mode Decomposition to quantify dynamical changes in the shape of individual cycles (along with amplitude, frequency and phase) using instantaneous frequency. We show how phase-alignment, a process of projecting cycles into a regularly sampled phase-grid space, makes it possible to compare cycles of different durations and shapes.  Normalised shapes can then be constructed with high temporal detail whilst accounting for differences in both duration and amplitude. We find that the instantaneous frequency tracks non-sinusoidal shapes in both simulated and real data. Notably, in local field potential recordings of mouse hippocampal CA1, we find that theta oscillations have a stereotyped slow-descending slope in the cycle-wise average, yet exhibiting high variability on a cycle-by-cycle basis. We show how Principal Components Analysis allows identification of motifs of theta cycle waveform that have distinct associations to cycle amplitude, cycle duration and animal movement speed. By allowing investigation into oscillation shape at high temporal resolution, this analytical framework will open new lines of enquiry into how neuronal oscillations support moment-by-moment information processing and integration in brain networks.


title: Coherent waves of myelin plasticity during motor-skill learning

abstract: Motor skill learning relies on neural plasticity in the motor and limbic systems. However, the spatial and temporal dependencies of these changes--and their microstructural underpinnings--remain unclear. Eighteen healthy males received training in a computer-controlled motion game 4 times a week, for 4 weeks. Performance improvements were observed in all trained participants. Serial myelin-sensitive multiparametric mapping at 3T during this period of intensive motor skill acquisition revealed temporally and spatially distributed, performance-related myelin-sensitive microstructural changes in the grey and white matter across the corticospinal system and hippocampus. Interestingly, analysis of the trajectory of these transient changes revealed a time-shifted choreography across white and grey matter of the corticospinal system as well as with changes in the hippocampus. Crucially, in the cranial corticospinal tracts, myelin-sensitive changes during training in the posterior part of the limb of the internal capsule were of greater magnitude in lower-limb trainees compared to upper limb trainees. Motor skill learning is depended on coherent waves of plasticity within a corticospinal-hippocampal loop.


title: Leishmania major formins are cytosolic actin bundler play an important role in cell physiology

abstract: Formins are a highly conserved eukaryotic family of proteins that regulate actin dynamics. They play important physiological roles in cell adhesion, motility, vesicular trafficking and cytokinesis. Although sequence analysis of Trypanosomatida genomes predicted multiple formin-encoding genes, none of them are functionally characterized yet. We report here experimental identification and functional characterization of two constitutively expressed formins from the trypanosomatid protozoa Leishmania major viz. LmForminA and LmForminB. These formins exhibited irregular cytosolic distribution that co-localized with actin patches. Co-sedimentation assay and surface plasmon resonance confirmed that purified LmForminA and B FH2 domains can bind actin, albeit with differential affinity. Interestingly, both LmForminA and B FH2 domains were found to be actin bundlers as revealed by low-speed co-sedimentation assay and TIRF microscopy. LmForminA and B also had actin-nucleating activities, which was abolished by mutating their conserved Ile residue crucial for actin assembly. The Ile-mutant formins, however, retained their actin binding and bundling properties. Treatment of Leishmania cells with formin inhibitor SMIFH2 severely perturbed parasite growth and morphology indicating that Lmformins are physiologically important and may be considered as novel drug targets.


title: Plasma exosomal miRNA analysis of Alzheimer's disease reveals the dysfunction of a neural network

abstract: Exosomal microRNA (miRNA) is an emerging source for biomarkers of Alzheimers disease (AD). Here, we profiled miRNA expression in AD, mild cognitive impairment (MCI), and controls. The assessment and validation of differentially expressed miRNA represented their potential to be novel biomarkers for AD and MCI. We conducted 13 co-expression networks and a miRNA network module linked to neural function emerged as the most significantly associated with AD diagnosis. The conservation analysis revealed the M1 was highly preserved in controls but dysfunction in AD and MCI. The module pattern between MCI and NC was similar, but significantly differed from AD, suggesting that the neural network regulated by miRNA changed during the mild cognitive stage, and the total miRNA expression altered in AD stage. Additionally, 24 out of 26 M1 hub-miRNAs were derived from brain tissue, and 15 had been reported as AD biomarkers. We consequently proposed the other 11 miRNAs could play important roles in AD. Our study highlights that co-expression network analysis can provide a new path for finding novel biomarkers.


title: Visualization of reactive astrocytes in living brain of Alzheimer's disease patient

abstract: An early appearance of reactive astrocytes is a hallmark of Alzheimers disease (AD)1,2, providing a substrate for early diagnostic neuroimaging targets. However, there is no clinically validated neuroimaging probe to visualize the reactive astrogliosis in the human brain in vivo. Here, we report that PET/CT imaging with 11C-acetate and 18F-fluorodeoxyglucose (18F-FDG) functionally visualizes the reactive astrocyte-mediated neuronal hypometabolism in the brains with neuroinflammation and AD. We demonstrate that reactive astrocytes excessively absorb acetate through elevated monocarboxylate transporter-1 (MCT1), leading to aberrant GABA synthesis and release which suppresses neuronal glucose uptake through decreased glucose transporter-3 (GLUT3) in both animal and human brains. We propose the non-invasive functional PET/CT imaging for astrocytic acetate-hypermetabolism and neuronal glucose-hypometabolism as an advanced diagnostic strategy for early stages of AD.


title: AAV-delivery of diacylglycerol kinase kappa achieves long-term rescue of Fmr1-KO mouse model deficits of fragile X syndrome

abstract:
Fragile X syndrome (FXS) is the most frequent form of familial intellectual disability. It results from the lack of the RNA binding protein FMRP and is associated with the overactivation of signaling pathways downstream of mGluRI receptors and upstream of mRNA translation. We previously found that diacylglycerol kinase kappa (DGKk) is a main mRNA target of FMRP in cortical neurons. Here we show that diacylglycerol kinase kappa (DGKk), when modified as to become FMRP-independent and delivered into the brain of adolescent mice using adeno-associated viral vectors, corrects brain diacylglycerol and phosphatidic acid homeostasis and the main phenotypic behaviors of the Fmr1-KO mouse model of FXS. Thus, DGKk appears as a key triggering factor of FXS pathomechanism while providing a possible means of intervention for FXS gene therapy.

One sentence summaryDGKk gene therapy in Fmr1-KO mouse model


title: FAN1 nuclease activity affects CAG expansion and age at onset of Huntington's disease

abstract: The age at onset of motor symptoms in Huntingtons disease (HD) is driven by HTT CAG repeat length but modified by other genes. We used exome sequencing of 683 HD patients with extremes of onset or phenotype relative to CAG length to identify rare variants associated with clinical effect. We identified damaging coding variants in candidate modifier genes from prior genome-wide association studies associated with altered HD onset or severity. Variants in FAN1 clustered in its DNA-binding and nuclease domains and were associated predominantly with earlier onset HD. Nuclease activities of these variants correlated with residual age at motor onset of HD. Mutating endogenous FAN1 to a nuclease-inactive form in an induced pluripotent stem cell model of HD led to rates of CAG expansion comparable to those observed with complete FAN1 knock out. Together, these data implicate FAN1 nuclease activity in slowing somatic repeat expansion and hence onset of HD.


title: α3β4* Nicotinic acetylcholine receptors strongly modulate the excitability of VIP neurons in the mouse inferior colliculus

abstract:
The inferior colliculus (IC), the midbrain hub of the central auditory system, receives extensive cholinergic input from the pontomesencephalic tegmentum. Activation of nicotinic acetylcholine receptors (nAChRs) in the IC can alter acoustic processing and enhance auditory task performance. However, how nAChRs affect the excitability of specific classes of IC neurons remains unknown. Recently, we identified vasoactive intestinal peptide (VIP) neurons as a distinct class of glutamatergic principal neurons in the IC. Here, in experiments using male and female mice, we show that cholinergic terminals are routinely located adjacent to the somas and dendrites of VIP neurons. Using whole-cell electrophysiology in brain slices, we found that acetylcholine drives surprisingly strong and long-lasting excitation and inward currents in VIP neurons. This excitation was unaffected by the muscarinic receptor antagonist atropine. Application of nAChR antagonists revealed that acetylcholine excites VIP neurons mainly via activation of 3{beta}4* nAChRs, a nAChR subtype that is rare in the brain. Furthermore, we show that cholinergic excitation is intrinsic to VIP neurons and does not require activation of presynaptic inputs. Lastly, we found that low frequency trains of acetylcholine puffs elicited temporal summation in VIP neurons, suggesting that in vivo-like patterns of cholinergic input can reshape activity for prolonged periods. These results reveal the first cellular mechanisms of nAChR regulation in the IC, identify a functional role for 3{beta}4* nAChRs in the auditory system, and suggest that cholinergic input can potently influence auditory processing by increasing excitability in VIP neurons and their postsynaptic targets.

Key points summaryO_LIThe inferior colliculus (IC), the midbrain hub of the central auditory system, receives extensive cholinergic input and expresses a variety of nicotinic acetylcholine receptor (nAChR) subunits.
C_LIO_LIIn vivo activation of nAChRs alters the input-output functions of IC neurons and influences performance in auditory tasks. However, how nAChR activation affects the excitability of specific IC neuron classes remains unknown.
C_LIO_LIHere we show in mice that cholinergic terminals are located adjacent to the somas and dendrites of VIP neurons, a class of IC principal neurons.
C_LIO_LIWe find that acetylcholine elicits surprisingly strong, long-lasting excitation of VIP neurons and this is mediated mainly through activation of 3{beta}4* nAChRs, a subtype that is rare in the brain.
C_LIO_LIOur data identify a role for 3{beta}4* nAChRs in the central auditory pathway and reveal a mechanism by which cholinergic input can influence auditory processing in the IC and the postsynaptic targets of VIP neurons.
C_LI


title: Melanocore uptake by keratinocytes occurs through phagocytosis and involves Protease-activated receptor-2 activation

abstract: In the skin epidermis, melanin is produced and stored within melanosomes in melanocytes and then transferred to keratinocytes. Different models have been proposed to explain the melanin transfer mechanism, which differ essentially in how melanin is transferred - either in a membrane-bound melanosome or as a melanosome core, i.e. melanocore. Here we investigated the endocytic route followed by melanocores and melanosomes during internalization by keratinocytes, by comparing the uptake of melanocores isolated from the supernatant of melanocyte cultures with melanosomes isolated from melanocytes. We show that inhibition of actin dynamics impairs the uptake of both melanocores and melanosomes. Moreover, depletion of critical proteins involved in actin-dependent uptake mechanisms, namely Rac1 and CtBP1/BARS, together with inhibition of Rac1-dependent signaling pathways or macropinocytosis suggest that melanocores are internalized by phagocytosis, whereas melanosomes are internalized by macropinocytosis. Furthermore, we confirmed that melanocore, but not melanosome uptake is dependent on the Protease-activated receptor-2 (PAR-2) and found that PAR-2 can be specifically activated by melanocores. As skin pigmentation was shown to be regulated by PAR-2 activation, our results further support the melanocore mechanism of melanin transfer and further refine this model, which can now be described as coupled melanocore exo/phagocytosis.


title: Investigation of Different Free Image Analysis Software for High-Throughput Droplet Detection

abstract: Droplet microfluidics has revealed innovative strategies in biology and chemistry. This advancement has delivered novel quantification methods, such as digital droplet polymerase chain reaction (ddPCR) and antibiotic heteroresistance analysis tool. For droplet analysis, researchers often use imaging techniques. Unfortunately, the analysis of images may require specific tools or programming skills to produce the expected results. In order to address the issue, we explore the potential use of standalone freely available software to detect droplets. We select four most popular software and classify them into instinctive and objective types based on their operation logic. We test and evaluate the softwares i) ability to detect droplets, ii) accuracy and precision, and iii) overall user-friendliness. In our experimental setting we find the objective type of software is better suited for droplet detection. The objective type of software also has simpler workflow or pipeline, especially aimed for non-experienced user. In our case, CellProfiler (CP) offers the most user-friendly experience for both single image and batch processing analysis.


title: β-RA targets mitochondrial metabolism and adipogenesis, leading to therapeutic benefits against CoQ deficiency and age-related overweight

abstract: Primary mitochondrial diseases are caused by mutations in mitochondrial or nuclear genes, leading to abnormal function of specific mitochondrial pathways. Mitochondrial dysfunction is also a secondary event in more common pathophysiological conditions, such as obesity and metabolic syndrome. In both cases, the improvement and management of mitochondrial homeostasis remains challenging. Here, we show that beta-resorcylic acid ({beta}-RA), a natural phenolic compound, competes in vivo with 4-hydroxybenzoic acid, the natural precursor of Coenzyme Q biosynthesis. This leads to a decrease of demethoxyubiquinone, an intermediate metabolite of CoQ biosynthesis that is abnormally accumulated in Coq9R239X mice. As a consequence, {beta}-RA rescues the phenotype of Coq9R239X mice, a model of primary mitochondrial encephalopathy. Moreover, we observe that long-term treatment with {beta}-RA also reduces the size and content of the white adipose tissue (WAT) that is normally accumulated during aging in wild-type mice, leading to a prevention of hepatic steatosis and an increase in survival at the old stage of life. The reduction in WAT content is due to a decrease in adipogenesis, an adaptation of the mitochondrial proteome in the kidneys, and a stimulation of glycolysis and acetyl-CoA metabolism. Therefore, our results demonstrate that {beta}-RA acts through different cellular mechanisms, with effects on mitochondrial metabolism, and it may be used for the treatment of primary Coenzyme Q deficiency, overweight, and hepatic steatosis.


title: Associations between Infant-Mother Physiological Synchrony and 4- to 6-Month-Old Infants' Emotion Regulation

abstract: In this study we assessed whether physiological synchrony between infants and mothers contributes to infants emotion regulation following a mild social stressor. Infants between 4- to 6-months of age and their mothers were tested in the Face-to-Face-Still-Face paradigm, and were assessed for behavioral and physiological self-regulation during and following the stressor. Physiological synchrony was calculated from a continuous measure of respiratory sinus arrhythmia (RSA) enabling us to cross-correlate the infants and mothers RSA responses. Without considering physiological synchrony, the evidence suggested that infants distress followed the prototypical pattern of increasing during the Still Face episode and then decreasing during the Reunion episode. Once physiological synchrony was added to the model, we observed that infants emotion regulation improved if mother-infant synchrony was positive, but not if it was negative. This result was qualified further by whether or not infants suppressed their RSA response during the Still Face episode. In sum, these findings highlight how individual differences in infants physiological responses contribute significantly to their self-regulation abilities.


title: Age-related decreases of cortical visuo-phonological transformation of unheard spectral fine-details

abstract: The integration of visual and auditory cues is crucial for successful processing of speech, especially under adverse conditions. Recent reports have shown that when participants watch muted videos of speakers, the phonological information about the acoustic speech envelope is tracked by the visual cortex. However, the speech signal also carries much richer acoustic details, e.g. about the fundamental frequency and the resonant frequencies, whose visuo-phonological transformation could aid speech processing. Here, we investigated the neural basis of the visuo-phonological transformation processes of these more fine-grained acoustic details and assessed how they change with ageing. We recorded whole-head magnetoencephalography (MEG) data while participants watched silent intelligible and unintelligible videos of a speaker. We found that the visual cortex is able to track the unheard intelligible modulations of resonant frequencies and the pitch linked to lip movements. Importantly, only the processing of intelligible unheard formants decreases significantly with age in the visual and also in the cingulate cortex. This is not the case for the processing of the unheard speech envelope, the fundamental frequency or the purely visual information carried by lip movements. These results show that unheard spectral fine-details (along with the unheard acoustic envelope) are transformed from a mere visual to a phonological representation. Aging affects especially the ability to derive spectral dynamics at formant frequencies. Since listening in noisy environments should capitalize on the ability to track spectral fine-details, our results provide a novel focus on compensatory processes in such challenging situations.


title: Cortical tracking of unheard formant modulations derived from silently presented lip movements and its decline with age


title: Characteristic changes in EEG spectral powers of patients with opioid-use disorder as compared with those with methamphetamine- and alcohol-use disorders

abstract: Electroencephalography (EEG) likely reflects activity of cortical neurocircuits, making it an insightful estimation for mental health in patients with substance use disorder (SUD). EEG signals are recorded as sinusoidal waves, containing spectral amplitudes across several frequency bands with high spatio-temporal resolution. Prior work on EEG signal analysis has been made mainly at individual electrodes. These signals can be evaluated from advanced aspects, including sub-regional and hemispheric analyses. Due to limitation of computational techniques, few studies in earlier work could conduct data analyses from these aspects. Therefore, EEG in patients with SUD is not fully understood. In the present retrospective study, spectral powers from a data house containing opioid (OUD), methamphetamine/stimulants (MUD), and alcohol use disorder (AUD) were extracted, and then converted into five distinct topographic data (i.e., electrode-based, cortical subregion-based, left-right hemispheric, anterior-posterior based, and total cortex-based analyses). We found that EEG spectral powers in patients with OUD were significantly different from those with MUD or AUD. Differential changes were observed from multiple perspectives, including individual electrodes, subregions, hemispheres, anterior-posterior cortices, and across the cortex as a whole. Understanding the differential changes in EEG signals may be useful for future work with machine learning and artificial intelligence (AI), not only for diagnostic but also for prognostic purposes in patients with SUD.


title: Emergence and function of cortical offset responses in sound termination detection

abstract: Offset responses in auditory processing appear after a sound terminates. They arise in neuronal circuits within the peripheral auditory system, but their role in the central auditory system remains unknown. Here we ask what the behavioural relevance of cortical offset responses is and what circuit mechanisms drive them. At the perceptual level, our results reveal that experimentally minimizing auditory cortical offset responses decreases the mouse performance to detect sound termination, assigning a behavioural role to offset responses. By combining in vivo electrophysiology in the auditory cortex and thalamus of awake mice, we also demonstrate that cortical offset responses are not only inherited from the periphery but also amplified and generated de novo. Finally, we show that offset responses code more than silence, including relevant changes in sound trajectories. Together, our results reveal the importance of cortical offset responses in encoding sound termination and detecting changes within temporally discontinuous sounds crucial for speech and vocalization.


title: Post-encoding reactivation promotes one-shot learning of episodes in humans

abstract: Prior animal and human work have shown that post-encoding reinstatement plays an important role in organizing the temporal sequence of unfolding episodes in memory. Here, we investigated whether post-encoding reinstatement serves to promote the encoding of  one-shot episodic learning beyond the temporal structure in humans. In experiment 1, participants encoded sequences of pictures depicting unique and meaningful episodic-like events. We used representational similarity analysis on scalp electroencephalography recordings during encoding and found evidence of rapid picture elicited EEG patterns reinstatement at episodic offset (around 500ms post-episode). Memory reinstatement was not observed between successive elements within an episode and the degree of memory reinstatement at episodic offset predicted later recall for that episode. In experiment 2, participants encoded a shuffled version of the picture sequences from experiment 1, rendering each episode meaningless to the participant but temporally structured as in experiment 1, and we found no evidence of memory reinstatement at episodic offset. These results suggest that post-encoding memory reinstatement is akin to the rapid formation of unique and meaningful episodes that unfold over time.


title: Correcting artifacts in ratiometric biosensor imaging; an improved approach for dividing noisy signals

abstract: The accuracy of biosensor ratio imaging is limited by signal/noise. Signals can be weak when biosensor concentrations must be limited to avoid cell perturbation. This can be especially problematic in imaging of low volume regions, e.g., along the cell edge. The cell edge is an important imaging target in studies of cell motility. We show how the division of fluorescence intensities with low signal-to-noise at the cell edge creates specific artifacts due to background subtraction and division by small numbers, and that simply improving the accuracy of background subtraction cannot address these issues. We propose a new approach where, rather than simply subtracting background from the numerator and denominator, we subtract a noise correction factor (NCF) from the numerator only. This NCF can be derived from the analysis of noise distribution in the background near the cell edge or from ratio measurements in the cell regions where signal-to-noise is high. We test the performance of the method first by examining two noninteracting fluorophores distributed evenly in cells. This generated a uniform ratio that could provide a ground truth. We then analyzed actual protein activities reported by a single chain biosensor for the guanine exchange factor Asef, and a dual chain biosensor for the GTPase Cdc42. The reduction of edge artifacts revealed persistent Asef activity in a narrow band ([~]640 nm wide) immediately adjacent to the cell edge. For Cdc42, the NCF method revealed an artefact that would have been obscured by traditional background subtraction approaches.


title: Peptidylarginine deiminase IV (PADI4) is not essential for cell-autonomous HSC maintenance and normal haematopoiesis

abstract:
Peptidylarginine deiminases (PADIs, or PADs) are emerging as key regulators of human physiology and pathophysiology. The nuclear deiminase PADI4 regulates embryonic stem cell pluripotency, however its role in adult stem cells is unknown. PADI4 is expressed most highly in the bone marrow (BM), where it is found as part of a self-renewal-associated gene signature and shown to modulate the function of critical transcriptional regulators such as Tal1 and c-Myc, suggesting that it regulates haematopoietic development or regeneration. We investigated the functional significance of PADI4 in haematopoietic stem cell (HSC) biology and normal haematopoiesis. We employed two conditional mouse models of tissue-specific Padi4 ablation, where Padi4 was completely deleted either after the emergence of HSCs, or acutely in the BM of adult mice. We found that loss of PADI4 does not significantly affect HSC self-renewal or differentiation potential upon injury or serial transplantation, nor does it lead to exhaustion or premature ageing of HSCs. Thus, surprisingly, PADI4 is dispensable for cell-autonomous HSC maintenance, differentiation and haematopoietic regeneration. This work has important implications for the clinical use of PADI4 inhibitors as therapeutic agents in autoimmunity and cancer.

Key PointsO_LIPADI4 is dispensable for steady-state and post-transplantation haematopoiesis
C_LIO_LIHSCs do not require intrinsic PADI4 activity to respond to haematopoietic injury
C_LIO_LIPADI4 deficiency does not lead to premature HSC ageing or exhaustion
C_LI

category: developmental biology


title: Variant calling from scRNA-seq data allows the assessment of cellular identity in patient-derived cell lines

abstract:
AO_SCPLOWBSTRACTC_SCPLOWMatters Arising from: Sharma, A., Cao, E.Y., Kumar, V. et al. Longitudinal single-cell RNA sequencing of patient-derived primary cells reveals drug-induced infidelity in stem cell hierarchy. Nat Commun 9, 4931 (2018). https://doi.org/10.1038/s41467-018-07261-3.

In Sharma, A. et al. Nat Commun 9, 4931 (2018) the authors employ longitudinal single-cell transcriptomic data from patient-derived primary and metastatic oral squamous cell carcinomas cell lines, to investigate possible divergent modes of chemo-resistance in tumor cell subpopulations. We integrated the analyses presented in the manuscript, by performing variant calling from scRNA-seq data via GATK Best Practices. As a main result, we show that an extremely high number of singlenucleotide variants representative of the identity of a specific patient is unexpectedly found in the scRNA-seq data of the cell line derived from a second patient, and vice versa. This finding likely suggests the existence of a sample swap, thus jeopardizing some of the translational conclusions of the article. Our results prove the efficacy of a joint analysis of the genotypic and transcriptomic identity of single-cells.


title: Engineering Insulin Cold Chain Resilience to Improve Global Access

abstract: There are 150 million people with diabetes worldwide who require insulin replacement therapy and the prevalence of diabetes is rising fastest in middle and low-income countries. Current formulations require costly refrigerated transport and storage to prevent loss of insulin integrity. This study shows the development of simple "drop-in" amphiphilic copolymer excipients to maintain formulation integrity, bioactivity, pharmacokinetics and pharmacodynamics for over 6 months when subjected to severe stressed aging conditions that cause current commercial formulation to fail in under 2 weeks. Further, when these copolymers are added to Humulin R (Eli Lilly) in original commercial packaging they prevent insulin aggregation for up to 4 days at 50 {degrees}C compared to less than 1 day for Humulin R alone. These copolymers demonstrate promise as simple formulation additives to increase the cold chain resilience of commercial insulin formulations, thereby expanding global access to these critical drugs for treatment of diabetes.


title: UCell: robust and scalable single-cell gene signature scoring

abstract: UCell is an R package for evaluating gene signatures in single-cell datasets. UCell signature scores, based on the Mann-Whitney U statistic, are robust to dataset size and heterogeneity, and their calculation demands less computing time and memory than other available methods, enabling the processing of large datasets in a few minutes even on machines with limited computing power. UCell can be applied to any single-cell data matrix, and includes functions to directly interact with Seurat objects. The UCell package and documentation are available on GitHub at https://github.com/carmonalab/UCell


title: Effect of imputation on gene network reconstruction from single-cell RNA-seq data

abstract:
Despite the advances in single-cell transcriptomics the reconstruction of gene regulatory networks remains challenging. Both the large amount of zero counts in experimental data and the lack of a consensus preprocessing pipeline for single-cell RNA-seq data make it hard to infer networks from transcriptome data. Data imputation can be applied in order to enhance gene-gene correlations and facilitate downstream data analysis. However, it is unclear what consequences imputation methods have on the reconstruction of gene regulatory networks.

To study this question, we evaluate the effect of imputation methods on the performance and structure of the reconstructed networks in different experimental single-cell RNA-seq data sets. We use state-of-the-art algorithms for both imputation and network reconstruction and evaluate the difference in results before and after imputation. We observe an inflation of gene-gene correlations that affects the predicted network structures and may decrease the performance of network reconstruction in general. Yet, within the modest limits of achievable results, we also make a recommendation as to an advisable combination of algorithms, while warning against the indiscriminate use of imputation before network reconstruction in general.


title: Systematic benchmark of state-of-the-art variant calling pipelines identifies major factors affecting accuracy of coding sequence variant discovery

abstract: Accurate variant detection in the coding regions of the human genome is a key requirement for molecular diagnostics of Mendelian disorders. Efficiency of variant discovery from nextgeneration sequencing (NGS) data depends on multiple factors, including reproducible coverage biases of NGS methods and the performance of read alignment and variant calling software. In this work, we systematically evaluated the performance of 4 popular short read aligners (Bowtie2, BWA, Isaac, and Novoalign) and 6 variant calling and filtering methods (based on DeepVariant, Genome Analysis ToolKit (GATK), FreeBayes, and Strelka2) using a set of 10 "gold standard" WES and WGS datasets. Our results suggest that Bowtie2 performs significantly worse than other aligners and should not be used for medical variant calling. When other aligners were used, the accuracy of variant discovery mostly depended on the variant caller and not the read aligner. Among the tested variant callers, DeepVariant consistently showed the best performance and the highest robustness, with other state-of-the-art tools, i.e. Strelka2 and GATK with 1D convolutional neural network variant scoring, also showing high performance on both WES and WGS data. The results show surprisingly large differences in the performance of cutting-edge tools even on high confidence regions of the coding genome. This highlights the importance of regular benchmarking of quickly evolving tools and pipelines. Finally, we discuss the need for a more diverse set of gold standard genomes (e.g. of African, Hispanic, or mixed ancestry) that would allow to control for deep learning model overfitting. For similar reasons there is a need for better variant caller assessment in the repetitive regions of the coding genome.


title: Elasticity of dense actin networks produces nanonewton protrusive forces

abstract: Actin filaments assemble into force-generating systems involved in diverse cellular functions, including cell motility, adhesion, contractility and division. It remains unclear how networks of actin filaments, which individually generate piconewton forces, can produce forces reaching tens of nanonewtons. Here we use in situ cryo-electron tomography to unveil how the nanoscale architecture of macrophage podosomes enables basal membrane protrusion. We show that the sum of the actin polymerization forces at the membrane is not sufficient to explain podosome protrusive forces. Quantitative analysis of podosome organization demonstrates that the core is composed of a dense network of bent actin filaments storing elastic energy. Theoretical modelling of the network as a spring-loaded elastic material reveals that it exerts forces of up to tens of nanonewtons, similar to those evaluated experimentally. Thus, taking into account not only the interface with the membrane but also the bulk of the network, is crucial to understand force generation by actin machineries. Our integrative approach sheds light on the elastic behavior of dense actin networks and opens new avenues to understand force production inside cells.

category: biophysics


title: The transcriptomic landscape of the photoperiodic stress response in Arabidopsis thaliana resembles the response to pathogen infection.

abstract:
Plants are exposed to regular diurnal rhythms of light and dark. Changes in the photoperiod by the prolongation of the light period cause photoperiod stress in short day-adapted Arabidopsis thaliana. Here we report on the transcriptional response to photoperiod stress of wild-type A. thaliana and photoperiod stress-sensitive cytokinin signalling and clock mutants. Transcriptomic changes induced by photoperiod stress included numerous changes in reactive oxygen (ROS)-related transcripts and showed a strong overlap with changes occurring in response to ozone stress and pathogen attack, which have in common the induction of an apoplastic oxidative burst. A core set of photoperiod stress-responsive genes has been identified, including salicylic acid (SA) biosynthesis and signalling genes. Genetic analysis revealed a central role for NPR1 in the photoperiod stress response as npr1-1 mutants were stress-insensitive. Photoperiod stress treatment led to a strong increase in camalexin levels which is consistent with shared photoperiod stress and pathogen response pathways. Photoperiod stress induced resistance of Arabidopsis plants to a subsequent infection by Pseudomonas syringae cv. tomato DC3000 indicating priming of the defence response. Together, photoperiod stress causes transcriptional reprogramming resembling plant pathogen defence responses and induces systemic acquired resistance in the absence of a pathogen.

One sentence summaryPhotoperiod stress results in significant dynamic transcriptomic changes related to oxidative stress similar to those caused by pathogen attack and primes the defence response against a subsequent pathogen infection.


title: Remembering the gist of an event over a lifetime depends on the hippocampus

abstract: A well-accepted view in memory research is that retrieving the gist of a memory over time depends on the cortex, typically the prefrontal cortex, while retrieving its precision relies on the hippocampus. More recent advances indicate that the hippocampal subfield CA1, as opposed to CA3, remains engaged even for retrieving very remote memories and that this engagement coincides with a maximal recruitment of parahippocampal cortical areas (LEC, MEC, PER and POR)1. Using a time-window comparable to that used in human long-term memory studies, here we show that CA1 is necessary for retrieving the gist of a memory independently of its age while memory precision specifically depends on CA3 in a time-dependent manner. The precision for the memory of a context-footshock association was tested in mice after one day or very remotely (i.e. after 6 months or one year) allowing for the natural fading of the memory trace. Retrieving recent memories engaged both CA1 and CA3 in control mice as revealed by high levels of RNA of the immediate-early gene Arc, strongly tied to synaptic plasticity and memory function. Optogenetic inhibition of CA3 cell firing led to the loss of memory precision, i.e. the retrieval of the gist memory selectively supported by CA1. In contrast, CA1 inhibition abolished memory retrieval and reduced both CA1 and CA3s activity. At very remote tests, controls retrieved only the gist of the event by recruiting CA1 and parahippocampal areas. Retrieving this gist was selectively abrogated upon CA1 optogenetic inactivation that dramatically reduced parahippocampal activity. Our findings indicate that the hippocampus, specifically CA1, is required for gist memory retrieval even for very remote memories that were previously reported to be hippocampal-independent, while CA3 is necessary for recalling precise memories in a time-dependent manner.


title: Behavior-dependent spatial maps enable efficient theta phase coding

abstract:
Navigation through space involves learning and representing relationships between past, current and future locations. In mammals, this might rely on the hippocampal theta phase code, where in each cycle of the theta oscillation, spatial representations start behind the animals location and then sweep forward. However, the exact relationship between phase and represented and true positions remains unclear. Developing a quantitative framework for the theta phase code, we formalize two previous notions: in spatial sweeps, different phases of theta encode positions at fixed distances behind or ahead of the animal, whereas in temporal sweeps, they encode positions reached at fixed time intervals into the past or future. These two schemes predict very different position representations during theta depending on the animals running speed. Paradoxically, in some studies sweep length has been shown to increase proportionally with running speed, consistent with temporal sweeps, whereas in other studies individual place field parameters such as field size and phase precession slope were shown to remain constant with speed, consistent with spatial sweeps. Here, we introduce a third option: behavior-dependent sweeps, according to which sweep length and place field properties vary across the environment depending on the running speed characteristic of each location. Analyzing single-cell and population variables in parallel in recordings from rat CA1 place cells and comparing them to model simulations, we show that behavior-dependent sweeps uniquely account for all relevant variables. This coding scheme combines features and advantages of both spatial and temporal sweeps, revealing an efficient hippocampal code.

SignificanceTo learn the structure of the world and the consequences of our actions, information about the past must be carried through to the present and linked to what is currently happening. To plan, desired future states and the predicted outcomes of actions must be represented. In mammals, including humans, hippocampal neurons are thought to encode such representations of past, present and future states at different phases of the theta oscillation. However, the precise hippocampal phase code remains unknown. We show that two previous ideas are incompatible with each other and with rat experimental data. So, we propose a new coding scheme that synthesizes features from both ideas and accounts for all relevant observations.


title: Training Data Distribution Significantly Impacts the Estimation of Tissue Microstructure with Machine Learning

abstract:
PurposeSupervised machine learning (ML) provides a compelling alternative to traditional model fitting for parameter mapping in quantitative MRI. The aim of this work is to demonstrate and quantify the effect of different training strategies on the accuracy and precision of parameter estimates when supervised ML is used for fitting.

MethodsWe fit a two-compartment biophysical model to diffusion measurements from in-vivo human brain, as well as simulated diffusion data, using both traditional model fitting and supervised ML. For supervised ML, we train several artificial neural networks, as well as random forest regressors, on different distributions of ground truth parameters. We compare the accuracy and precision of parameter estimates obtained from the different estimation approaches using synthetic test data.

ResultsWhen the distribution of parameter combinations in the training set matches those observed in similar data sets, we observe high precision, but inaccurate estimates for atypical parameter combinations. In contrast, when training data is sampled uniformly from the entire plausible parameter space, estimates tend to be more accurate for atypical parameter combinations but may have lower precision for typical parameter combinations.

ConclusionThis work highlights the need to consider the choice of training data when deploying supervised ML for estimating microstructural metrics, as performance depends strongly on the training-set distribution. We show that high precision obtained using ML may mask strong bias, and visual assessment of the parameter maps is not sufficient for evaluating the quality of the estimates.


title: Alpha oscillations reflect suppression of distractors with increased perceptual load

abstract: Attention serves an essential role in cognition and behaviour allowing us to focus on behaviourally-relevant objects while ignoring distraction. Perceptual load theory states that attentional resources are allocated according to the requirements of the task, i.e. its  load. The theory predicts that the resources left to process irrelevant, possibly distracting stimuli, are reduced when the perceptual load is high. However, it remains unclear how this allocation of attentional resources specifically relates to neural excitability and suppression mechanisms. In this magnetoencephalography (MEG) study, we show that brain oscillations in the alpha band (8-13Hz) implement the suppression of distracting objects when the perceptual load is high. In parallel, high load increased neuronal excitability for target objects, as reflected by rapid frequency tagging. We suggest that the allocation of resources in tasks with high perceptual load is implemented by a gain increase for targets, complemented by distractor suppression reflected by alpha band oscillations closing the  gate for interference.