title: From shallow to deep: exploiting feature-based classifiers for domain adaptation in semantic segmentation

abstract: The remarkable performance of Convolutional Neural Networks on image segmentation tasks comes at the cost of a large amount of pixelwise annotated images that have to be segmented for training. In contrast, feature-based learning methods, such as the Random Forest, require little training data, but never reach the segmentation accuracy of CNNs. This work bridges the two approaches in a transfer learning setting. We show that a CNN can be trained to correct the errors of the Random Forest in the source domain and then be applied to correct such errors in the target domain without retraining, as the domain shift between the Random Forest predictions is much smaller than between the raw data. By leveraging a few brushstrokes as annotations in the target domain, the method can deliver segmentations that are sufficiently accurate to act as pseudo-labels for target-domain CNN training. We demonstrate the performance of the method on several datasets with the challenging tasks of mitochondria, membrane and nuclear segmentation. It yields excellent performance compared to microscopy domain adaptation baselines, especially when a significant domain shift is involved.


title: Robust and generalizable segmentation of human functional tissue units

abstract: The Human BioMolecular Atlas Program aims to compile a reference atlas for the healthy human adult body at the cellular level. Functional tissue units (FTU, e.g., renal glomeruli and colonic crypts) are of pathobiological significance and relevant for modeling and understanding disease progression. Yet, annotation of FTUs is time consuming and expensive when done manually and existing algorithms achieve low accuracy and do not generalize well. This paper compares the five winning algorithms from the "Hacking the Kidney" Kaggle competition to which more than a thousand teams from sixty countries contributed. We compare the accuracy and performance of the algorithms on a large-scale renal glomerulus Periodic acid-Schiff stain dataset and their generalizability to a colonic crypts hematoxylin and eosin stain dataset. Results help to characterize how the number of FTUs per unit area differs in relationship to their position in kidney and colon with respect to age, sex, body mass index (BMI), and other clinical data and are relevant for advancing pathology, anatomy, and surgery.

category: bioinformatics


title: scHiCSRS: A Self-Representation Smoothing Method with Gaussian Mixture Model for Imputing single-cell Hi-C Data

abstract:
MotivationSingle cell Hi-C techniques make it possible to study cell-to-cell variability in genomic features. However, excess zeros are commonly seen in single cell Hi-C (scHi-C) data, making scHi-C matrices extremely sparse and bringing extra difficulties in downstream analysis. The observed zeros are a combination of two events: structural zeros for which the loci never interact due to underlying biological mechanisms, and dropouts or sampling zeros where the two loci interact but are not captured due to insufficient sequencing depth. Although quality improvement approaches have been proposed as an intermediate step for analyzing scHi-C data, little has been done to address these two types of zeros. We believe that differentiating between structural zeros and dropouts would benefit downstream analysis such as clustering.

ResultsWe propose scHiCSRS, a self-representation smoothing method that improves the data quality, and a Gaussian mixture model that identifies structural zeros among observed zeros. scHiC-SRS not only takes spatial dependencies of a scHi-C 2D data structure into account but also borrows information from similar single cells. Through an extensive set of simulation studies, we demonstrate the ability of scHiCSRS for identifying structural zeros with high sensitivity and for accurate imputation of dropout values in sampling zeros. Downstream analysis for three real datasets show that data improved from scHiCSRS yield more accurate clustering of cells than simply using observed data or improved data from several comparison methods.

Availability and ImplementationThe scHiCSRS R package, together with the processed real and simulated data used in this study, are available on Github at https://github.com/sl-lin/scHiCSRS.git.

Contactshili@stat.osu.edu

Supplementary informationSupplementary data are available online.


title: A small molecule stabilises the disordered native state of the Alzheimer's Aβ peptide

abstract: The stabilisation of native states of proteins is a powerful drug discovery strategy. It is still unclear, however, whether this approach can be applied to intrinsically disordered proteins. Here we report a small molecule that stabilises the native state of the A{beta}42 peptide, an intrinsically disordered protein fragment associated with Alzheimers disease. We show that this stabilisation takes place by a dynamic binding mechanism, in which both the small molecule and the A{beta}42 peptide remain disordered. This disordered binding mechanism involves enthalpically favourable local {pi}-stacking interactions coupled with entropically advantageous global effects. These results indicate that small molecules can stabilise disordered proteins in their native states through transient non-specific interactions that provide enthalpic gain while simultaneously increasing the conformational entropy of the proteins.

category: biophysics


title: A Machine Learning Approach to Identify Specific Small Molecule Inhibitors of Secondary Nucleation in alpha-Synuclein Aggregation

abstract: Drug development is an increasingly active area of application of machine learning methods, due to the need to overcome the high attrition rates of conventional drug discovery pipelines. This issue is especially pressing for neurodegenerative diseases where very few disease-modifying drugs have been approved. To address this problem, we describe a machine learning approach to identify specific inhibitors of the proliferation of -synuclein aggregates through secondary nucleation, a process that has been implicated in Parkinsons disease and related synucleinopathies. We use a combination of docking simulations followed by machine learning to first identify initial hit compounds and then explore the chemical space around these compounds. Our results demonstrate that this approach leads to the identification of novel chemical matter with an improved hit rate and potency over conventional similarity search approaches.


title: A Machine Learning Approach to Identify Small Molecule Inhibitors of Secondary Nucleation inalpha-Synuclein Aggregation


title: A novel cryo-electron microscopy support film based on 2D crystal of HFBI protein

abstract: Cryo-electron microscopy (cryo-EM) has become the most powerful tool to resolve the high-resolution structures of biomacromolecules in solution. However, the air-water interface induced preferred orientation, dissociation or denaturation of biomacromolecules during cryo-vitrification is still a major limitation factor for many specimens. To solve this bottleneck, we developed a new type of cryo-EM support film using the 2D crystal of hydrophobin I (HFBI) protein. The HFBI-film utilizes its hydrophilic side to adsorb protein particles via electrostatic interactions and keep air-water interface away, allowing thin-enough ice and high-quality data collection. The particle orientation distribution can be optimized by changing the buffer pH. We, for the first time, solved the cryo-EM structure of catalase (2.28-[A]) that exhibited strong preferred orientation using conventional cryo-vitrification protocol. We further proved the HFBI-film is suitable to solve the high-resolution structures of small proteins including aldolase (150 kDa, 3.34-[A]) and hemoglobin (64 kDa, 3.6-[A]). Our work implied that the HFBI-film will have a wide application in the future to increase the successful rate and efficiency of cryo-EM.


title: The Role of Extended Range of Interactions in the Dynamics of Interacting Molecular Motors

abstract: Motor proteins, also known as biological molecular motors, play important roles in various intracellular processes. Experimental investigations suggest that molecular motors interact with each other during the cellular transport, but the nature of such interactions remains not well understood. Stimulated by these observations, we present a theoretical study aimed to understand the effect of the range of interactions on dynamics of interacting molecular motors. For this purpose, we develop a new version of the totally asymmetric simple exclusion processes in which nearest-neighbor as well as the next nearest-neighbor interactions are taken into account in a thermodynamically consistent way. A theoretical framework based on a cluster mean-field approximation, which partially takes correlations into account, is developed to evaluate the stationary properties of the system. It is found that fundamental current-density relations in the system strongly depend on the strength and the sign of interactions, as well as on the range of interactions. For repulsive interactions stronger than some critical value, increasing the range of interactions leads to a change from unimodal to trimodal dependence in the flux-density fundamental diagram. Theoretical calculations are tested with extensive Monte Carlo computer simulations. Although in most ranges of parameters excellent agreement between theoretical predictions and computer simulations is observed, there are situations when the cluster mean-field approach fails to describe properly the dynamics in the system. Theoretical arguments to explain these observations are presented. Our theoretical analysis clarifies the microscopic picture of how the range of interactions influences the dynamics of interacting molecular motors.


title: Resonant Learning in Scale-free Networks

abstract:
Over the last decades, analyses of the connectivity of large biological and artificial networks have identified a common scale-free topology, where few of the network elements, called hubs, control many other network elements. In monitoring the dynamics of networks hubs, recent experiments have revealed that they can show behaviors oscillating between  on and  off states of activation. Prompted by these observations, we ask whether the existence of oscillatory hubs states could contribute to the emergence of specific network dynamical behaviors. Here, we use Boolean threshold networks with scale-free architecture as representative models to demonstrate how periodic activation of the network hub can provide a network-level advantage in learning specific new dynamical behaviors. First, we find that hub oscillations with distinct periods can induce robust and distinct attractors whose lengths depend upon the hub oscillation period. Second, we determine that a given network can exhibit series of different attractors when we sequentially change the period of hub pulses. Using rounds of evolution and selection, these different attractors could independently learn distinct target functions. We term this network-based learning strategy resonant learning, as the emergence of new learned dynamical behaviors depends on the choice of the period of the hub oscillations. Finally, we find that resonant learning leads to convergence towards target behaviors over an order of magnitude faster than standard learning procedures. While it is already known that modular network architecture contributes to learning separate tasks, our results reveal an alternative design principle based on forced oscillations of the network hub.

SIGNIFICANCELarge networks of interconnected components such as genes or machines can coordinate complex behavioral dyamics. One outstanding question has been to identify the design principles that allow networks to learn new behaviors. Here, in simulating learning cycles, we randomly modify the interactions between components and select networks that exhibit a desired behavior. Surprisingly, we find that networks can learn new behaviors faster when the state of the most connected network component is forced to oscillate during learning. Remarkably, using distinct periods of oscillations allows a given network to learn distinct behaviors. While it is known that modular network architecture contributes to learning separate tasks, our results reveal an alternative design principle for which modules are not needed.


title: DNA Self-Assembled Plasmonic Nanodiamonds for Biological Sensing

abstract: Nitrogen-vacancy (NV) centers in diamonds are promising solid-state quantum emitters for developing superior biological imaging modalities. They possess desired bio-compatibility, photostability and electronic spin-related photophysical properties that are optically accessible at room temperature. Yet, bare nanodiamond-based imaging modalities are limited by the brightness and temporal resolution due to the intrinsically long lifetime of NV centers. Moreover, it remains a technological challenge using top-down fabrication to create freestanding hybrid nanodiamond imaging probes with enhanced performance. In this study, we leverage the bottom-up DNA self-assembly to develop a hybrid plasmonic nanodiamond construct, which we coin as the plasmon-enhanced nanodiamond (PEN), for biological imaging. The PEN nano-assembly features a closed plasmonic nanocavity that completely encapsulates a single nanodiamond, thus enabling the largest possible plasmonic enhancement to accelerate the emission dynamics of NV centers. Creation of the PEN nano-assembly is size-independent, so is its broadband scattering spectrum that is optimally overlapped with the emission spectrum of NV centers. Study of the structure-property correlation reveals that the optimal condition for emission dynamics modification is causally linked to that for a plasmonic nanocavity. The cellular internalization and cytotoxicity studies further confirm the delivery efficiency and biological safety of PEN nano-assemblies. Collectively, the PEN nano-assembly provides a promising approach for manipulating photophysical properties of solid-state quantum emitters and could serve as a versatile platform to uncover non-trivial quantum effects in biological systems.


title: Photochemical pre-bleaching of formalin-fixed archival prostate tissues significantly reduces autofluorescence to facilitate multiplex immunofluorescence staining

abstract: The characterization of tissues using multiple different primary antibodies detected by secondary antibodies, each possessing a different colored fluorophore (multiplex immunofluorescence), is a powerful technique but often impaired by endogenous autofluorescence present in the specimen. Our current research involves the use of multiplex immunofluorescence to identify specific cell phenotypes within the tumor microenvironment in archival formalin-fixed paraffin-embedded human prostate cancer tissue specimens. These specimens frequently possess high levels of autofluorescence, in part due to the biological age of the tissues and long storage times. This autofluorescence interferes with and, in the worst cases, completely obscures the desired immunofluorescent signals, thus impeding analyses by decreasing signal-to-noise. Here, we demonstrate that a recently published protocol for photochemical bleaching significantly decreases autofluorescence (80% average decrease of the brightest autofluorescent signals), across the visible spectrum, in fixed, archival prostate tissue specimens from aged men, that have been sectioned onto glass slides and stored for several months. Importantly, the method is compatible with subsequent immunofluorescence staining and yields markedly improved signal-to-noise. Inclusion of this method should facilitate studies employing multiplex immunofluorescence in sections cut from archival fixed human prostate tissues.

category: pathology


title: Quantitative effects of environmental variation on stomatal anatomy and gas exchange in a grass model

abstract: Stomata are cellular pores on the leaf epidermis that allow plants to regulate carbon assimilation and water loss. Stomata integrate environmental signals to regulate pore apertures and optimize gas exchange to fluctuating conditions. Here, we quantified intraspecific plasticity of stomatal gas exchange and anatomy in response to seasonal variation in Brachypodium distachyon. Over the course of two years we (i) used infrared gas analysis to assess light response kinetics of 120 Bd21-3 wild-type individuals in an environmentally fluctuating greenhouse and (ii) microscopically determined the seasonal variability of stomatal anatomy in a subset of these plants. We observed systemic environmental effects on gas exchange measurements and remarkable intraspecific plasticity of stomatal anatomical traits. To reliably link anatomical variation to gas exchange, we adjusted anatomical gsmax calculations for grass stomatal morphology. We propose that systemic effects and variability in stomatal anatomy should be accounted for in long-term gas exchange studies.

category: plant biology


title: Real-time motion monitoring improves functional MRI data quality in infants

abstract: Imaging the infant brain with MRI has improved our understanding of early stages of neurodevelopment. However, head motion during MRI acquisition is detrimental to both functional and structural MRI scan quality. Though infants are commonly scanned while asleep, they commonly exhibit motion during scanning, causing data loss. Our group has shown that providing MRI technicians with real-time motion estimates via Framewise Integrated Real-Time MRI Monitoring (FIRMM) software helps obtain high-quality, low motion fMRI data. By estimating head motion in real time and displaying motion metrics to the MR technician during an fMRI scan, FIRMM can improve scanning efficiency. Hence, we compared average framewise displacement (FD), a proxy for head motion, and the amount of usable fMRI data (FD [≤] 0.2mm) in infants scanned with (n = 407) and without FIRMM (n = 295). Using a mixed-effects model, we found that the addition of FIRMM to current state-of-the-art infant scanning protocols significantly increased the amount of usable fMRI data acquired per infant, demonstrating its value for research and clinical infant neuroimaging.

category: neuroscience


title: Real-time computation of transcranial magnetic stimulation electric fields using self-supervised deep learning

abstract:
BackgroundElectric fields (E-fields) induced by transcranial magnetic stimulation (TMS) can be modeled using partial differential equations (PDEs) with boundary conditions. However, existing numerical methods to solve PDEs for computing E-fields are usually computationally expensive. It often takes minutes to compute a high-resolution E-field using state-of-the-art finite-element methods (FEM).

MethodsWe developed a self-supervised deep learning (DL) method to compute precise TMS E-fields in real-time. Given a head model and the primary E-field generated by TMS coils, a self-supervised DL model was built to generate a E-field by minimizing a loss function that measures how well the generated E-field fits the governing PDE and Neumann boundary condition. The DL model was trained in a self-supervised manner, which does not require any external supervision. We evaluated the DL model using both a simulated sphere head model and realistic head models of 125 individuals and compared the accuracy and computational efficiency of the DL model with a state-of-the-art FEM.

ResultsIn realistic head models, the DL model obtained accurate E-fields with significantly smaller PDE residual and boundary condition residual than the FEM (p<0.002, Wilcoxon signed-rank test). The DL model was computationally efficient, which took about 0.30 seconds on average to compute the E-field for one testing individual. The DL model built for the simulated sphere head model also obtained an accurate E-field whose difference from the analytical E-fields was 0.004, more accurate than the solution obtained using the FEM.

ConclusionsWe have developed a self-supervised DL model to directly learn a mapping from the magnetic vector potential of a TMS coil and a realistic head model to the TMS induced E-fields, facilitating real-time, precise TMS E-field modeling.


title: Reliability of quantitative multiparameter maps is high for MT and PD but attenuated for R1 and R2* in healthy young adults

abstract: We investigate the reliability of individual differences of four quantities measured by magnetic resonance imaging based multiparameter mapping (MPM): magnetization transfer (MT), proton density (PD), longitudinal relaxation rate (R1), and effective transverse relaxation rate (R2*). A total of four MPM datasets, two on each of two consecutive days, were acquired in healthy young adults. On Day 1, no repositioning occurred; on Day 2, participants were repositioned between MPM datasets. Using intra-class correlation effect decomposition (ICED), we assessed the contributions of session-specific, day-specific, and residual sources of measurement error. For whole-brain gray and white matter, all four MPM parameters showed high reproducibility and high reliability, as indexed by the coefficient of variation (CoV) and the intra-class correlation (ICC). However, MT, PD, R1, and R2* differed markedly in the extent to which reliability varied across brain regions. MT and PD showed high reliability in almost all regions. In contrast, R1 and R2* showed low reliability in some regions outside the basal ganglia, such that the sum of the measurement error estimates in our structural equation model was higher than estimates of between-person differences. In sum, in this sample of healthy young adults, the four MPM parameters showed very little variability over four measurements over two days but differed in how well they could assess between-person differences. We conclude that R1 and R2* might carry only limited person-specific information in samples of healthy young adults, and, by implication, might be of restricted utility for studying associations to between-person differences in behavior.


title: Necroptosis inhibition counteracts axonal degeneration, cognitive decline and key hallmarks of aging, promoting brain rejuvenation.

abstract: Age is the main risk factor for the development of neurodegenerative diseases. In the aged brain, axonal degeneration is an early pathological event, preceding neuronal dysfunction, and cognitive disabilities. Necroptosis activation mediates degeneration of injured axons, but whether necroptosis triggers neurodegeneration and cognitive impairment along aging is unknown. Here we show necroptosis activation in hippocampal axons during aging. Loss of the necroptotic effector Mlkl was sufficient to delay age-associated axonal degeneration, protecting against decreased synaptic transmission and memory decline in aged mice. Moreover, short-term pharmacologic inhibition of necroptosis in aged mice reverted structural and functional hippocampal impairment. Finally, a quantitative proteomic analysis revealed that necroptosis inhibition leads to an overall improvement of the aged hippocampal proteome, including molecular biofunctions associated with brain rejuvenation. Our results demonstrate that necroptosis contributes to the functional decline of the aged brain, and necroptosis inhibition constitute a potential geroprotective strategy to treat age-related disabilities.


title: Lipophorin receptors regulate mushroom bodies development and participate in learning, memory, and sleep in flies

abstract:
BackgroundDrosophila melanogaster Lipophorin Receptors (LpRs), LpR1 and LpR2, mediate lipid uptake. The orthologs of these receptors in vertebrates, ApoER2 and VLDL-R, bind Reelin, a glycoprotein not present in flies. These receptors are associated with the development and function of the hippocampus and cerebral cortex, important association areas in the mammalian brain. It is currently unknown whether LpRs play similar roles in the Drosophila brain.

ResultsWe report that LpR-deficient flies exhibit impaired olfactory memory and sleep patterns, which seem to reflect anatomical defects found in a critical brain association area, the Mushroom Bodies (MB). Moreover, cultured MB neurons respond to mammalian Reelin by increasing the complexity of their neurites. This effect depends on LpRs and Dab, the Drosophila ortholog of the reelin signaling adaptor protein Dab1. In vitro, two of the long isoforms of LpRs allow the internalization of Reelin.

ConclusionsThese findings demonstrate that LpRs contribute to MB development and function, supporting the existence of LpR-dependent signaling in Drosophila.


title: What happened when? Brain and behavioral responses to violated expectations about the structure and content of episodic memories

abstract: Episodic memories are not static but can be modified on the basis of new experiences, potentially allowing us to make valid predictions in the face of an ever-changing environment. Recent research has identified prediction errors during retrieval as a possible trigger for such changes. In the present study, we used modified episodic cues to investigate whether different types of mnemonic prediction errors modulate brain activity and subsequent memory performance. Participants encoded different episodes which consisted of short toy stories. During a subsequent functional magnetic resonance imaging (fMRI) session, participants were then presented videos showing the original episodes, or modified versions thereof. In modified videos, either the order of two subsequent action steps was changed or an object was exchanged for another. Content modifications recruited inferior frontal, parietal, and temporo-occipital areas reflecting the processing of the new object information, while brain responses to structure modifications in right dorsal premotor and inferior frontal areas remained subthreshold. In a post-fMRI memory test, the participants tendency to accept modified episodes as originally encoded increased significantly when they had been presented modified versions already during the fMRI session. Our study provides valuable initial insights into the neural processing of different types of episodic prediction errors and their influence on subsequent memory.


title: What happened when? Brain and behavioral responses to modified structure and content in episodic cueing


title: NIfTI-MRS: A standard format for magnetic resonance spectroscopic data

abstract:
PurposeThe use of multiple data formats in the MRS community currently hinders data sharing and integration. NIfTI-MRS is proposed as a standard MR spectroscopy data format, which is implemented as an extension to the neuroimaging informatics technology initiative (NIfTI) format.

Using this standardised format will facilitate data sharing, ease algorithm development, and encourage the integration of MRS analysis with other imaging modalities.

MethodsA file format based on the NIfTI header extension framework was designed to incorporate essential spectroscopic metadata and additional encoding dimensions. A detailed description of the specification is provided. An open-source command-line conversion program is implemented to enable conversion of single-voxel and spectroscopic imaging data to NIfTI-MRS. To provide visualisation of data in NIfTI-MRS, a dedicated plugin is implemented for FSLeyes, the FSL image viewer.

ResultsAlongside online documentation, ten example datasets are provided in the proposed format. In addition, minimal examples of NIfTI-MRS readers have been implemented. The conversion software, spec2nii, currently converts fourteen formats to NIfTI-MRS, including DICOM and vendor proprietary formats.

ConclusionThe proposed format aims to solve the issue of multiple data formats being used in the MRS community. By providing a single conversion point, it aims to simplify the processing and analysis of MRS data, thereby lowering the barrier to use of MRS. Furthermore, it can serve as the basis for open data sharing, collaboration, and interoperability of analysis programs. It also opens possibility of greater standardisation and harmonisation. By aligning with the dominant format in neuroimaging, NIfTI-MRS enables the use of mature tools present in the imaging community, demonstrated in this work by using a dedicated imaging tool, FSLeyes, as a viewer.


title: Semantic relation priming is not constituent-specific: Evidence from ERP

abstract: It is humankinds unique wisdom to compose a limited number of words together through specific rules to convey endless information. Researchers have found that this composition process also plays a vital role in the comprehension of compounds. The specific manifestation is relation priming; that is, the previously used relation will promote subsequent word processing using the same relation. This priming phenomenon is bound to morpheme repetition (modifier or head). This study combines a self-paced priming paradigm with electrophysiological technology to explore whether relation priming will occur without sharing morphemes and its time course. We found that relation priming can occur independently of morpheme-repetition, which shows an independent representation of relation information. And it has been activated at a very early stage (about 200ms). As the word processing progresses, this activation gradually strengthens, indicating that the relations role is slowly increasing in the process of compound word recognition. It may first be used as a kind of context information to help determine the constituent morphemes meaning. After the meaning access of the constituent morphemes, they begin to play a role in the semantic composition process. This study uses electrophysiological technology to precisely describe the representation of relation and its time course for the first time. Which gives us a deeper understanding of the relation priming process, and at the same time, shed light on the meaning construction process of compounds.


title: Neurons derived from individual early Alzheimer's disease patients reflect clinical vulnerability

abstract: Establishing preclinical models of Alzheimers disease that predict clinical outcomes remains a critically important, yet to date not fully realised, goal. Models derived from human cells offer considerable advantages over non-human models, including the potential to reflect some of the inter-individual differences that are apparent in patients. Here we report an approach using induced pluripotent stem cell-derived cortical neurons from people with early symptomatic Alzheimers disease where we sought a match between individual disease characteristics in cells with analogous characteristics in the people from whom they were derived. We show that the response to amyloid-{beta} burden in life, as measured by cognitive decline and brain activity levels, varies between individuals and this vulnerability rating correlates with the individual cellular vulnerability to extrinsic amyloid-{beta} in vitro as measured by synapse loss and function. Our findings indicate that patient induced pluripotent stem cell-derived cortical neurons not only present key aspects of Alzheimers disease pathology, but also reflect key aspects of the clinical phenotypes of the same patients. Cellular models that reflect an individuals in-life clinical vulnerability thus represent a tractable method of Alzheimers disease modelling using clinical data in combination with cellular phenotypes.


title: Neurons from individual early Alzheimer's disease patients reflect clinical vulnerability


title: Depth-targeted intracortical microstroke by two-photon photothrombosis in rodent brain

abstract:
SignificancePhotothrombosis is a widely used model of ischemic stroke in rodent experiments. In the photothromboris model, the photosensitizer Rose Bengal is systemically introduced to the blood stream and activated by green light to induce aggregation of platelets that eventually cause vessel occlusion. Since the activation of Rose Bengal is a one-photon phenomenon and the molecules in the illuminated area (light path) are subject to excitation, targeting of thrombosis is unspecific especially in the depth dimension. We have developed a photothrombosis protocol that can target a single vessel in the cortical parenchyma by two-photon excitation.

AimWe aim to induce a thrombotic stroke in the cortical parenchyma by two-photon activation of Rose Bengal so that we confine photothrombosis within a vessel of a target depth.

ApproachFITC-dextran is injected into the blood stream to visualize the cerebral blood flow in anesthetized adult mice with a cranial window. After a target vessel is chosen by two-photon imaging (950 nm), Rose Bengal is injected into the blood stream. The scanning wavelength is changed to 720 nm and photothrombosis was induced by scanning the target vessel.

ResultsTwo-photon depth-targeted single vessel photothrombosis was achieved with a success rate of 84.9{+/-}1.7% within 80 s. Attempts without Rose Bengal (i.e., only with FITC) did not result in photothrombosis at the excitation wavelength of 720 nm.

ConclusionsWe described a protocol that achieves depth-targeted single vessel photothrombosis by two-photon excitation. Simultaneous imaging of blood flow in the targeted vessel using FITC dextran enabled the confirmation of vessel occlusion and prevention of excess irradiation that possibly induces unintended photodamage.


title: Cortico-striatal activity characterizes human safety learning via Pavlovian conditioned inhibition

abstract:
Safety learning generates associative links between neutral stimuli and the absence of threat, promoting the inhibition of fear and security-seeking behaviours. Precisely how safety learning is mediated at the level of underlying brain systems, particularly in humans, remains unclear. Here, we integrated a novel Pavlovian conditioned inhibition task with ultra-high field (UHF) fMRI to examine the neural basis of inhibitory safety learning in 49 healthy participants. In our task, participants were conditioned to two safety signals: a conditioned inhibitor that predicted threat-omission when paired with a known threat signal (A+/AX-), and a standard safety signal that generally predicted threat-omission (BC-). Both safety signals evoked equivalent autonomic and subjective learning responses but diverged strongly in terms of underlying brain activation. The conditioned inhibitor was characterized by more prominent activation of the dorsal striatum, anterior insular and dorsolateral prefrontal cortex compared to the standard safety signal, whereas the latter evoked greater activation of the ventromedial prefrontal cortex, posterior cingulate and hippocampus, among other regions. Further analyses of the conditioned inhibitor indicated that its initial learning was characterized by consistent engagement of dorsal striatal, midbrain, thalamic, premotor, and prefrontal subregions. These findings suggest that safety learning via conditioned inhibition involves a distributed cortico-striatal circuitry, separable from broader cortical regions involved with processing standard safety signals (e.g., CS-). This cortico-striatal system could represent a novel neural substrate of safety learning, underlying the initial generation of  stimulus-safety associations, distinct from wider cortical correlates of safety processing, which facilitate the behavioral outcomes of learning.

Significance statementIdentifying safety is critical for maintaining adaptive levels of anxiety, but the neural mechanisms of human safety learning remain unclear. Using ultra-high field fMRI, we compared learning-related brain activity for a conditioned inhibitor, which actively predicted threat-omission, and a standard safety signal (CS-), which was passively unpaired with threat. The inhibitor engaged an extended circuitry primarily featuring the dorsal striatum, along with thalamic, midbrain, and premotor/prefrontal cortex regions. The CS-exclusively involved cortical safety-related regions observed in basic safety conditioning, such as the vmPFC. These findings extend current models to include learning-specific mechanisms for encoding stimulus-safety associations, which might be distinguished from expression-related cortical mechanisms. These insights may suggest novel avenues for targeting dysfunctional safety learning in psychopathology.


title: Functional but not obligatory link between microsaccades and neural modulation by covert spatial attention

abstract: Covert spatial attention is associated with spatially specific modulation of neural activity as well as with directional biases in fixational eye-movements known as microsaccades. Recently, this link has been suggested to be obligatory, such that modulation of neural activity by covert spatial attention occurs only when paired with microsaccades toward the attended location. Here we revisited this link between microsaccades and neural modulation by covert spatial attention in humans. We investigated spatial modulation of 8-12 Hz EEG alpha activity and microsaccades in a context with no incentive for overt gaze behaviour: when attention is directed internally within the spatial layout of visual working memory. In line with a common attentional origin, we show that spatial modulations of alpha activity and microsaccades co-vary: alpha lateralisation is stronger in trials with microsaccades toward compared to away from the memorised location of the to-be-attended item and occurs earlier in trials with earlier microsaccades toward this item. Critically, however, trials without attention-driven microsaccades nevertheless showed clear spatial modulation of alpha activity - comparable to the neural modulation observed in trials with attention-driven microsaccades. Thus, directional biases in microsaccades are correlated with neural signatures of covert spatial attention, but they are not a prerequisite for neural modulation by covert spatial attention to be manifest.


title: Audiovisual task switching rapidly modulates sound encoding in mouse auditory cortex

abstract: In everyday behavior, sensory systems are in constant competition for attentional resources, but the cellular and circuit-level mechanisms of modality-selective attention remain largely uninvestigated. We conducted translaminar recordings in mouse auditory cortex (AC) during an audiovisual (AV) attention shifting task. Attending to sound elements in an AV stream reduced both pre-stimulus and stimulus-evoked spiking activity, primarily in deep layer neurons. Despite reduced spiking, stimulus decoder accuracy was preserved, suggesting improved sound encoding efficiency. Similarly, task-irrelevant probe stimuli during intertrial intervals evoked fewer spikes without impairing stimulus encoding, indicating that these attention influences generalized beyond training stimuli. Importantly, these spiking reductions predicted trial-to-trial behavioral accuracy during auditory attention, but not visual attention. Together, these findings suggest auditory attention facilitates sound discrimination by filtering sound-irrelevant spiking in AC, and that the deepest cortical layers may serve as a hub for integrating extramodal contextual information.


title: Structural Basis for pH-Gating of the K+ Channel TWIK1 at the Selectivity Filter

abstract: TWIK1 is a widely expressed pH-gated two-pore domain K+ channel (K2P) that contributes to cardiac rhythm generation and insulin release from pancreatic beta cells. TWIK1 displays unique properties among K2Ps including low basal activity and inhibition by extracellular protons through incompletely understood mechanisms. Here, we present cryo-EM structures of TWIK1 in lipid nanodiscs at high and low pH that reveal a novel gating mechanism at the K+ selectivity filter. At high pH, TWIK1 adopts an open conformation. At low pH, protonation of an extracellular histidine results in a cascade of conformational changes that close the channel by sealing the top of the selectivity filter, displacing the helical cap to block extracellular ion access pathways, and opening gaps for lipid block of the intracellular cavity. These data provide a mechanistic understanding for extracellular pH-gating of TWIK1 and show how diverse mechanisms have evolved to gate the selectivity filter of K+ channels.


title: Age-dependent formation of TMEM106B amyloid filaments in human brain

abstract: Many age-dependent neurodegenerative diseases, like Alzheimers and Parkinsons, are characterised by abundant inclusions of amyloid filaments. Filamentous inclusions of the proteins tau, amyloid-{beta} (A{beta}), -synuclein and TDP-43 are the most common. Here, we used electron cryo-microscopy (cryo-EM) structure determination to show that residues 120-254 of the lysosomal type II transmembrane protein 106B (TMEM106B) also form amyloid filaments in the human brain. We solved cryo-EM structures of TMEM106B filaments from the brains of 22 individuals with neurodegenerative conditions, including sporadic and inherited tauopathies, A{beta}-amyloidoses, synucleinopathies and TDP-43opathies, as well as from the brains of two neurologically normal individuals. We observed three different TMEM106B folds, with no clear relationship between folds and diseases. The presence of TMEM106B filaments correlated with that of a 29 kDa sarkosyl-insoluble fragment of the protein on Western blots. The presence of TMEM106B filaments in the brains of older, but not younger, neurologically normal individuals indicates that they form in an age-dependent manner.


title: Prehension kinematics in humans and macaques

abstract:
AO_SCPLOWBSTRACTC_SCPLOWNon-human primates, especially rhesus macaques, have been a dominant model to study sensorimotor control of the upper limbs. Indeed, human and macaques have similar hands and homologous neural circuits to mediate manual behavior. However, few studies have systematically and quantitatively compared the manual behaviors of the two species. Such comparison is critical for assessing the validity of using the macaque sensorimotor system as a model of its human counterpart. In this study, we systematically compared the prehensile behaviors of humans and rhesus macaques using an identical experimental setup. We found human and macaque prehension kinematics to be generally similar with a few subtle differences. While the structure of the preshaping postures is similar in humans and macaques, human postures are more object-specific and human joints are less intercorrelated. Conversely, monkeys demonstrate more stereotypical grasping behaviors that are common across all grasp conditions and more variability in their postures across repeated grasps of the same object. Despite these subtle differences in manual behavior between humans and monkeys, our results bolster the use of the macaque model to understand the neural mechanisms of manual dexterity in humans.

NO_SCPLOWEWC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWANDC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWNEWSWORTHYC_SCPLOWMacaques have been a dominant animal model to study the neural mechanisms of human dexterity because they exhibit complex manual behavior. We show that the kinematics of prehension - a critical dexterous behavior - are largely similar in humans and macaques. However, human preshaping postures are more object-specific and the movement of human digits are less correlated with each other. The thumb, index, and wrist are major driver of these interspecies differences.


title: Increased frequency of CD4+ and CD8+ follicular helper T cells in human lymph node biopsies during the earliest stages of rheumatoid arthritis

abstract:
ObjectivesFollicular helper T cells (Tfh cells) provide key B cell help, and are essential in germinal center (GC) formation and (auto) antibody generation. To gain more insight into their role during the earliest phase of rheumatoid arthritis (RA) we analyzed their frequencies, phenotype and cytokine profile in peripheral blood and lymphoid tissues.

MethodsUsing flow cytometry, we studied the frequency of Tfh and B cells in peripheral blood and lymph node (LN) needle biopsies. Three donor groups were included and compared: healthy controls (HCs), autoantibody positive individuals at risk for developing RA (RA-risk individuals), and early RA patients. Ex vivo stimulation of lymphocytes with PMA/ionomycin was performed to assess cytokine secretion by Tfh cells.

ResultsIn blood, the frequency of circular Tfh cells (cTfh) did not differ between study groups. In lymphoid tissue, the frequency of Tfh cells correlated strongly with the frequency of CD19+ B cells. Compared to healthy controls, LN samples of RA patients and RA-risk individuals showed more CD19+ B cells and more CD4+CXCR5+ and CD8+CXCR5+ Tfh cells. These Tfh cells from LNs expressed less IL-21 upon ex vivo stimulation.

ConclusionLN tissue of early RA patients as well as part of RA-risk individuals exhibit increased frequencies of Tfh cells correlating with increased numbers of B cells. Interestingly, IL-21 production is already aberrant in the very early at risk phase of the disease. This suggests that Tfh cells may present a novel rationale for therapeutic targeting during the preclinical stage of the disease to prevent further disease progression.

category: immunology


title: 8 A structure of the cytoplasmic ring of the Xenopus laevis nuclear pore complex solved by cryo-EM and AI

abstract: As one of the largest protein complexes in eukaryotes, the nuclear pore complex (NPC) forms a conduit regulating nucleocytoplasmic transport. Here, we determined 8 [A] resolution cryo-electron microscopic (cryo-EM) structure of the cytoplasmic ring (CR) from the Xenopus laevis NPC. With the aid of AlphaFold2, we managed to build a most comprehensive and accurate pseudoatomic model of the CR to date, including the Y complexes and flanking components of Nup358, Nup214 complexes, Nup205 and Nup93. Comparing with previously reported CR model, the Y complex structure in our model exhibits much tighter interactions in the hub region mediated by -solenoid domain in Nup160 C-terminus. Five copies of Nup358 are identified in each CR subunit to provide rich interactions with other Nups in stem regions of Y complexes. Two copies of Nup214 complexes lay in a parallel pattern and attach to the short arm region of Y complexes towards the central channel of NPC. Besides, the structural details of two copies of Nup205 on the side of the short arm region and one copy of Nup93 on the stem region of Y complexes in each CR subunit are also revealed. These in-depth novel structural features represent a great advance in understanding the assembly of NPCs.

category: molecular biology


title: Determining the architecture of nuclear ring of Xenopus laevis nuclear pore complex using integrated approaches

abstract: The nuclear pore complexes (NPCs) are large protein assemblies as a physical gate to regulate nucleocytoplasmic transport. Here, using integrated approaches including cryo-electron microscopy, hybrid homology modeling and cell experiment, we determined the architecture of the nuclear ring (NR) from Xenopus laevis oocytes NPC at subnanometer resolution. In addition to the improvement of the Y complex model, eight copies of Nup205 and ELYS were assigned in NR. Nup205 connects the inner and outer Y complexes and contributes to the assembly and stability of the NR. By interacting with both the inner Nup160 and the nuclear envelope (NE), the N-terminal {beta}-propeller and -solenoid domains of ELYS were found to be essential for accurate assembly of the NPC on the NE.


title: 8 A structure of the nuclear ring of the Xenopus laevis nuclear pore complex solved by cryo-EM and AI

abstract: The nuclear pore complex (NPC), one of the largest protein complexes in eukaryotes, serves as a physical gate to regulate nucleocytoplasmic transport. Here, we determined the 8 [A] resolution cryo-electron microscopic (cryo-EM) structure of the nuclear ring (NR) from the Xenopus laevis NPC, with local resolutions reaching 4.9 [A]. With the aid of AlphaFold2, we managed to build a pseudoatomic model of the NR, including the Y complexes and flanking components. In this most comprehensive and accurate model to date, the almost complete Y complex structure exhibits much tighter interaction in the hub region. Each NR asymmetric subunit contains two copies of Y complexes, one copy of Nup205 that connects the Y complexes to the neighbouring complex, one copy of ELYS that stabilizes the long arm region of the inner Y complex, and one copy of newly identified Nup93 that forms a bridge across the stems of Y complexes. These in-depth structural features represent a great advance in understanding the assembly of NPCs.


title: Robust and unbiased estimation of the background distribution for automated quantitative imaging

abstract: Quantitative analysis of high-throughput microscopy images requires robust automated algorithms. Background estimation is usually the first step and has an impact on all subsequent analysis, in particular for foreground detection and calculation of ratiometric quantities. Most methods recover only a single background value, such as the median. Those that aim to retrieve a background distribution by dividing the intensity histogram yield a biased estimation in images in non-trivial cases. In this work, we present the first method to recover an unbiased estimation of the background distribution directly from an image and without any additional input. Through a robust statistical test, our method leverages the lack of local spatial correlation in background pixels to select a subset of pixels that accurately represent the background distribution. This method is both fast and simple to implement, as it only uses standard mathematical operations and an averaging filter. Additionally, the only parameter, the size of the averaging filter, does not require fine tuning. The obtained background distribution can be used to test for foreground membership of individual pixels, or to estimate confidence intervals in derived quantities. We expect that the concepts described in this work can help to develop a novel family of robust segmentation methods.

category: cell biology


title: The roles of distinct Ca2+ signaling mediated by Piezo and inositol triphosphate receptor (IP3R) in the remodeling of E-cadherin during cell dissemination

abstract: Given the role of E-cadherin (E-cad) in holding epithelial cells together, the inverse relationship between E-cad levels and cell invasion has been perceived as a principle underlying the invasiveness of tumor cells. In contrast, our study employing the Drosophila model of cell dissemination demonstrates that E-cad is necessary for the invasiveness of Rasv12-transformed cells in vivo. Drosophila E-cad/{beta}-catenin disassembles at adherens junctions and assembles at invasive protrusions--the actin- and cortactin-rich invadopodia-like protrusions associated with breach of the extracellular matrix (ECM)--during cell dissemination. Loss of E-cad attenuates dissemination of Rasv12-transformed cells by impairing their ability to compromise the ECM. Strikingly, the remodeling of E-cad/{beta}-catenin subcellular distribution is controlled by two discrete intracellular calcium signaling pathways: Ca2+ release from endoplasmic reticulum via the inositol triphosphate receptor (IP3R) disassembles E-cad at adherens junctions while Ca2+ entry via the mechanosensitive channel Piezo assembles E-cad at invasive protrusions. Thus, our study provides molecular insights into the unconventional role of E-cad in cell invasion during cell dissemination in vivo and describes the discrete roles of intracellular calcium signaling in the remodeling of E-cad/{beta}-catenin subcellular localization.


title: Club cells are the primary source of pIgR in small airways

abstract:
BackgroundLoss of secretory immunoglobulin A (SIgA) is common in COPD small airways and likely contributes to disease progression. We hypothesized loss of SIgA results from reduced expression of pIgR, a chaperone protein needed for SIgA transcytosis, in the COPD small airway epithelium.

MethodspIgR-expressing cells were defined and quantified at single-cell resolution in human airways using RNA in-situ hybridization, immunostaining, and single-cell RNA sequencing. Complementary studies in mice utilized immunostaining, primary murine tracheal epithelial cell (MTEC) culture, and transgenic mice with secretory or ciliated cell-specific knockout of pIgR. SIgA degradation by human neutrophil elastase or secreted bacterial proteases from non-typeable Haemophilus influenzae (NTHi) was evaluated in vitro.

ResultsWe found that secretory cells are the predominant cell type responsible for pIgR expression in human and murine airways. Loss of SIgA in small airways was not associated with a reduction in secretory cells but rather a reduction in pIgR protein expression despite intact PIGR mRNA expression. Neutrophil elastase and NTHi-secreted proteases are both capable of degrading SIgA in vitro and may also contribute to a deficient SIgA immunobarrier in COPD.

InterpretationLoss of the SIgA immunobarrier in small airways of patients severe COPD is complex and likely results from both pIgR-dependent defects in IgA transcytosis and SIgA degradation.

Key MessagesWhat is the key question? Localized SIgA deficiency in small airways is an established driver of COPD pathogenesis, but the mechanism of loss remains unclear. We hypothesized loss of SIgA is due to reduced numbers of pIgR-expressing cells in SIgA-deficient small airways.

What is the bottom line? pIgR is primarily expressed by secretory cells in human and murine airways. Although numbers of secretory cells are similar between SIgA-deficient and SIgA-replete airways in COPD, there is reduced expression of pIgR protein, but not mRNA, in SIgA-deficient airways. Additionally, host and bacterial proteases degrade SIgA in vitro, suggesting loss of SIgA may relate to both impaired transcytosis and increased degradation.

Why read on? This study highlights the complexity of SIgA immunobarrier maintenance and suggests that strategies aimed at restoring the SIgA immunobarrier will need to account for both impaired transcytosis and degradation by host and/or bacterial proteases.


title: Secretory cells are the primary source of pIgR in small airways


title: Pluripotency-Independent Induction of Human Trophoblast Stem Cells from Fibroblasts

abstract:
Recent studies demonstrated that human trophoblast stem-like cells (hTS-like cells) can be derived from naive embryonic stem cells or be induced from somatic cells by the pluripotency factors, OSKM. This raises two main questions; (i) whether human induced TSCs (hiTSCs) can be generated independently to pluripotent state or factors and (ii) what are the mechanisms by which hTSC state is established during reprogramming. Here, we identify GATA3, OCT4, KLF4 and MYC (GOKM) as a pluripotency-independent combination of factors that can generate stable and functional hiTSCs, from both male and female fibroblasts. By using single and double knockout (KO) fibroblasts for major pluripotency genes (i.e. SOX2 or NANOG/PRDM14) we show that GOKM not only is capable of generating hiTSCs from the KO cells, but rather that the efficiency of the process is increased. Through H3K4me2 and chromatin accessibility profiling we demonstrate that GOKM target different loci and genes than OSKM, and that a significant fraction of them is related to placenta and trophoblast function. Moreover, we show that GOKM exert a greater pioneer activity compared to OSKM. While GOKM target many specific hTSC loci, OSKM mainly target hTSC loci that are shared with hESCs. Finally, we reveal a gene signature of trophoblast-related genes, consisting of 172 genes which are highly expressed in blastocyst-derived TSCs and GOKM-hiTSCs but absent or mildly expressed in OSKM-hiTSCs.

Taken together, these results imply that not only is the pluripotent state, and SOX2 specifically, not required to produce functional hiTSCs, but that pluripotency-specific factors actually interfere with the acquisition of the hTSC state during reprogramming.


title: Transgenerational impact of aberrant inflammation in rat pregnancy

abstract: Children of women with pre-eclampsia have increased risk of cardiovascular (CV) and metabolic disease in adult life. Furthermore, the risk of pregnancy complications is higher in daughters born to women affected by pre-eclampsia than in daughters born after uncomplicated pregnancies. While aberrant inflammation contributes to the pathophysiology of pregnancy complications, including pre-eclampsia, the contribution of maternal inflammation to subsequent risk of CV and metabolic disease as well as pregnancy complications in the offspring remains unclear. Here we demonstrate that 24-week-old female rats (F1) born to dams (F0) exposed to lipopolysaccharide (LPS) during pregnancy (to induce inflammation) exhibited mild systolic dysfunction, increased cardiac growth-related gene expression, abnormal glucose tolerance and coagulopathy; whereas male F1 offspring exhibited abnormal glucose tolerance and increased visceral fat accumulation compared with F1 sex-matched offspring born to saline-treated dams. Both male and female F1 offspring born to LPS-treated dams had evidence of anemia. Fetuses (F2) from F1 females born to LPS-treated dams were growth restricted, and this reduction in fetal growth was associated with increased CD68 positivity and decreased expression of glucose transporter-1 in their utero-placental units. These results indicate that abnormal maternal inflammation can contribute to increased risk of CV and metabolic disease in offspring, and that the effects of inflammation may be transgenerational. This study provides evidence in support of early screening for CV and metabolic disease, as well as pregnancy complications in offspring affected by pre-eclampsia or other pregnancy complications associated with aberrant inflammation.

category: developmental biology


title: Divergent phenotypic plasticity of a convergent Mendelian trait in Drosophila

abstract: In Drosophila, comparisons of the thermal plasticity of pigmentation across serially homologous abdominal segments have been conducted in two species, namely Drosophila melanogaster and D. kikkawai. Pigmentation variation has different genetic architecture in the two species, being oligogenic in the former and monogenic in the later. Here, we analyze the thermal plasticity of abdominal pigmentation in a third species, D. erecta, which is phylogenetically close to D. melanogaster but like D. kikkawai has a monogenic basis for pigmentation variation. However, the underlying locus differs between D. erecta and D. kikkawai, being the X-linked melanin-synthesis gene tan in the former and the autosomal transcription factor pdm3 in the later. We found that in spite of a low overall plasticity in monogenic species compared to D. melanogaster, the two monogenic species showed divergent plasticity patterns in respect to the response to temperature and to the degree of dominance in heterozygotes. Those results provide new insights on the dependence of the degree of plasticity on the genetic architecture as well as on the extent of phenotypic convergence.

category: evolutionary biology


title: Chromosome scale assembly of allopolyploid genome of the diatom Fistulifera solaris

abstract: Microalgae including diatoms are of interest for environmentally-friendly manufacturing such as biofuel production. However, only a very few of their genomes have been elucidated owing to their diversified and complex evolutionary history. The genome of the marine oleaginous diatom Fistulifera solaris, an allopolyploid diatom possessing two subgenomes, has been analyzed previously by pyrosequencing. However, many unsolved regions and unconnected scaffolds remained. Here we report the entire chromosomal structure of the genome of F. solaris strain JPCC DA0580 using a long-read nanopore sequencing platform. From just one single run using a MinION flow-cell, the chromosome scale assembly with telomere-to-telomere resolution was achieved for 41 out of 44 chromosomes. Centromere regions were also predicted from the chromosomes, and we discovered conserved motifs in the predicted regions. The function of the motifs was experimentally confirmed by successful transformation of the diatom via bacterial conjugation. This discovery provides insights into chromosome replication, facilitating the rational design of artificial chromosomes for large-scale metabolic engineering of diatoms. The chromosome scale assembly also suggests the potential existence of multi-copy mini-chromosomes and tandemly repeated lipogenesis genes related to the oleaginous phenotype of F. solaris. The nanopore sequencing also solved the sequential arrangement of the repeat region in the F. solaris mitochondrial genome. Findings of this study will be useful to understand and further engineer the oleaginous phenotype of F. solaris.

category: genomics


title: ODGI: understanding pangenome graphs

abstract:
MotivationPangenome graphs provide a complete representation of the mutual alignment of collections of genomes. These models offer the opportunity to study the entire genomic diversity of a population, including structurally complex regions. Nevertheless, analyzing hundreds of gigabase-scale genomes using pangenome graphs is difficult as it is not well-supported by existing tools. Hence, fast and versatile software is required to ask advanced questions to such data in an efficient way.

ResultsWe wrote ODGI, a novel suite of tools that implements scalable algorithms and has an efficient in-memory representation of DNA pangenome graphs in the form of variation graphs. ODGI supports pre-built graphs in the Graphical Fragment Assembly format. ODGI includes tools for detecting complex regions, extracting pangenomic loci, removing artifacts, exploratory analysis, manipulation, validation, and visualization. Its fast parallel execution facilitates routine pangenomic tasks, as well as pipelines that can quickly answer complex biological questions of gigabase-scale pangenome graphs.

AvailabilityODGI is published as free software under the MIT open source license. Source code can be downloaded from https://github.com/pangenome/odgi and documentation is available at https://odgi.readthedocs.io. ODGI can be installed via Bioconda https://bioconda.github.io/recipes/odgi/README.html or GNU Guix https://github.com/pangenome/odgi/blob/master/guix.scm.

Contactegarris5@uthsc.edu


title: Improving Neural Networks for Genotype-Phenotype Prediction Using Published Summary Statistics

abstract: Phenotype prediction is a necessity in numerous applications in genetics. However, when the size of the individual-level data of the cohort of interest is small, statistical learning algorithms, from linear regression to neural networks, usually fail due to insufficient data. Fortunately, summary statistics from genome-wide association studies (GWAS) on other large cohorts are often publicly available. In this work, we propose a new regularization method, namely, main effect prior (MEP), for making use of GWAS summary statistics from external datasets. The main effect prior is generally applicable for machine learning algorithms, such as neural networks and linear regression. With simulation and real-world experiments, we show empirically that MEP improves the prediction performance on both homogeneous and heterogeneous datasets. Moreover, deep neural networks with MEP outperform standard baselines even when the training set is small.


title: Conditional Generative Modeling for De Novo Protein Design with Hierarchical Functions

abstract:
MotivationProtein design has become increasingly important for medical and biotechnological applications. Because of the complex mechanisms underlying protein formation, the creation of a novel protein requires tedious and time-consuming computational or experimental protocols. At the same time, machine learning has enabled the solving of complex problems by leveraging large amounts of available data, more recently with great improvements on the domain of generative modeling. Yet, generative models have mainly been applied to specific sub-problems of protein design.

ResultsHere we approach the problem of general purpose protein design conditioned on functional labels of the hierarchical Gene Ontology. Since a canonical way to evaluate generative models in this domain is missing, we devise an evaluation scheme of several biologically and statistically inspired metrics. We then develop the conditional generative adversarial network ProteoGAN and show that it outperforms several classic and more recent deep learning baselines for protein sequence generation. We further give insights into the model by analysing hyperparameters and ablation baselines. Lastly, we hypothesize that a functionally conditional model could generate proteins with novel functions by combining labels and provide first steps into this direction of research.

AvailabilityCode and data is available at https://github.com/timkucera/proteogan

Contacttim.kucera@bsse.ethz.ch, mt@visium.ch, lpapaxanthos@google.com


title: A graph neural network approach to molecule carcinogenicity prediction

abstract: Molecular carcinogenicity is a preventable cause of cancer, however, most experimental testing of molecular compounds is an expensive and time consuming process, making high throughput experimental approaches infeasible. In recent years, there has been substantial progress in machine learning techniques for molecular property prediction. In this work, we propose a model for carcinogenicity prediction, CONCERTO, which uses a graph transformer in conjunction with a molecular fingerprint representation, trained on multi-round muta-genicity and carcinogenicity objectives. To train and validate CONCERTO, we augment the training dataset with more informative labels and utilize a larger external validation dataset. Extensive experiments demonstrate that our model yields results superior to alternate approaches for molecular carcinogenicity prediction.


title: An in vivo drug repurposing screen and transcriptional analyses reveals the serotonin pathway and GSK3 as major therapeutic targets for NGLY1 deficiency

abstract: NGLY1 deficiency, a rare disease with no effective treatment, is caused by autosomal recessive, loss-of-function mutations in the N-glycanase 1 (NGLY1) gene and is characterized by global developmental delay, hypotonia, alacrima, and seizures. We used an adult Drosophila model of NGLY1 deficiency to conduct an in vivo, unbiased, small molecule, repurposing screen of FDA-approved drugs to identify therapeutic compounds. Seventeen molecules rescued lethality in a patient-specific NGLY1 deficiency model, including multiple serotonin and dopamine modulators. Exclusive dNGLY1 expression in serotonin and dopamine neurons, in an otherwise dNGLY1-null fly, was sufficient to rescue lethality. Further, genetic modifier and transcriptomic data supports the importance of serotonin signaling in NGLY1 deficiency. Connectivity Map analysis identified glycogen synthase kinase 3 (GSK3) inhibition as a potential therapeutic mechanism for NGLY1 deficiency, which we experimentally validated with TWS119 and lithium. Strikingly, GSK3 inhibitors and a serotonin modulator rescued size defects in dNGLY1 deficient larvae upon proteasome inhibition, suggesting that these compounds act through NRF1, a transcription factor that regulates proteasome expression. This study reveals the importance of the serotonin pathway in NGLY1 deficiency, and serotonin modulators or GSK3 inhibitors may be effective therapeutics for this rare disease.

category: pharmacology and toxicology


title: Mitigation of Injury from Myocardial Infarction by TH1834, an Inhibitor of the Acetyltransferase Tip60

abstract: It is estimated that up to one billion cardiomyocytes (CMs) can be lost during myocardial infarction (MI), which results in contractile dysfunction, adverse ventricular remodeling, and systolic heart failure. Pharmacologic strategies that target factors having both pro-apoptotic and anti-proliferative functions in CMs may be useful for the treatment of ischemic heart disease. One such multifunctional candidate for drug targeting is the acetyltransferase Tip60, which is a member of the MYST family of acetyltransferases known to acetylate both histone and non-histone protein targets that have been shown in cultured cancer cells to promote apoptosis and to initiate the DNA damage response (DDR) thereby limiting cellular expansion. Using a murine model, we recently published findings demonstrating that CM-specific disruption of the Kat5 gene encoding Tip60 markedly protected against the damaging effects of MI. In the experiments described here, in lieu of genetic targeting, we administered TH1834, an experimental drug designed to specifically inhibit the acetyltransferase domain of Tip60. We report that, similar to the effect of disrupting the Kat5 gene, daily systemic administration of TH1834 beginning 3 days after induction of MI and continuing for two weeks of a 4-week timeline resulted in improved systolic function assessed by echocardiography, reduced apoptosis and scarring, and increased activation of the CM cell-cycle. Our results support that idea that drugs that inhibit the acetyltransferase activity of Tip60 may be useful agents for the treatment of ischemic heart disease.


title: Children's Species Literacy as Estimated and Desired by Biodiversity Communicators: a Mismatch with the Actual Level

abstract: While biodiversity decline continues and laypeoples knowledge about species is limited, especially in children, high-quality communication is needed to raise awareness. For this, communicators should be aware of current knowledge levels in their target groups. We compared biodiversity communicators' estimates of the average species literacy level in primary school children with the actual level. Moreover, we explored the importance that communicators placed on species literacy and the level that they desired. Estimations of childrens average knowledge level varied widely and differed from the actual level. In particular, communicators overestimated the species literacy level. Although most biodiversity communicators agreed that knowledge about species is important, their view differed as to why species literacy would be important. Moreover, communicators differed with respect to the relative importance attached to different knowledge components. Professionals may thus benefit from a detailed framework of species literacy that illustrates different aspects and values. Most importantly, our findings suggest that to bridge the gap between actual and desired knowledge levels in children effectively, biodiversity communicators first need to become more aware of current perceptions in young audiences.

category: scientific communication and education


title: A synthetic distributed genetic multi-bit counter

abstract:
A design for genetically-encoded counters is proposed via repressor-based circuits. An N -bit counter reads sequences of input pulses and displays the total number of pulses, modulo 2N .

The design is based on distributed computation, with specialized cell types allocated to specific tasks. This allows scalability and bypasses constraints on the maximal number of circuit genes per cell due to toxicity or failures due to resource limitations.

The design starts with a single-bit counter. The N -bit counter is then obtained by interconnecting (using diffusible chemicals) a set of N single-bit counters and connector modules.

An optimization framework is used to determine appropriate gate parameters and to compute bounds on admissible pulse widths and relaxation (inter-pulse) times, as well as to guide the construction of novel gates.

This work can be viewed as a step toward obtaining circuits that are capable of finite-automaton computation, in analogy to digital central processing units.

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/468063v1_ufig1.gif" ALT="Figure 1">
View larger version (65K):
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category: synthetic biology


title: Cell Wall Biochemistry Drives Pollen Tube Mechanics and Affects Growth Rate

abstract: Pollen tubes live a life on a razors edge. They must maintain cell wall integrity whilst growing towards the ovule at extraordinary speed but explosively burst at just the right moment to release the sperm cells--with fatal consequences for reproduction if things go wrong. The precisely controlled growth of the pollen tube depends on the fine-tuned balance between the expansive force of turgor pressure and the restraining effect of the cell wall. Currently, it is not well understood how the composition of the cell wall affects its mechanical properties. Using Arabidopsis mutants, we have investigated these interactions by combining experimental and simulation techniques to determine instantaneous and time-dependent mechanical parameters. This allowed, for the first time, the quantification of the effects of cell wall biochemistry on turgor pressure and cell wall elasticity and to predict their effects on growth rate. Our systems biology approach is widely applicable to study the implications of mechanical stress on growth.

category: systems biology


title: Attractor Landscapes as a Model Selection Criterion in Data Poor Environments

abstract: Modeling of systems for which data is limited often leads to underdetermined model identification problems, where multiple candidate models are equally adherent to data. In such situations additional optimality criteria are useful in model selection apart from the conventional minimization of error and model complexity. This work presents the attractor landscape as a domain for novel model selection criteria, where the number and location of attractors impact desirability. A set of candidate models describing immune response dynamics to SARS-CoV infection is used as an example for model selection based on features of the attractor landscape. Using this selection criteria, the initial set of 18 models is ranked and reduced to 7 models that have a composite objective value with a p-value < 0.05. Additionally, the impact of pharmacologically induced remolding of the attractor landscape is presented.


title: Non-canonical Function of a Hif-1α Splice Variant Contributes to the Sustained Flight of Locusts

abstract: The hypoxia inducible factor (Hif) pathway is functionally conserved across metazoans in modulating cellular adaptations to hypoxia. However, the functions of this pathway under aerobic physiological conditions are rarely investigated. Here, we show that Hif-12, a locust Hif-1 isoform, does not induce canonical hypoxic responses but functions as a specific regulator of locust flight, which is a completely aerobic physiological process. Two Hif-1 splice variants were identified in locusts, a ubiquitously expressed Hif-11 and a muscle-predominantly expressed Hif-12. Hif-11 that induces typical hypoxic responses upon hypoxia exposure, remains inactive during flight. By contrast, the expression of Hif-12, which lacks C-terminal transactivation domain, is less sensitive to oxygen-tension but induced extensively by flying. Hif-12 sustains flight endurance by promoting glucose oxidation while simultaneously maintaining redox homeostasis by upregulating the production of a reactive oxygen species (ROS) quencher, DJ-1. Overall, this study reveals a novel Hif-mediated mechanism underlying prolonged aerobic physiological activity.

category: zoology


title: Microlitter pollution in the marine environment and preliminary evidences of in vitro cytotoxic effects on two Mediterranean commercial fish species

abstract:
Marine litter is composed mainly of plastics and is recognized as a serious threats to marine ecosystems. Ecotoxicological approaches have started elucidating the potential severity of microplastics (MPs) in controlled laboratory studies with pristine materials but no information exist on marine environmental microlitter as a whole. Here, we characterized the litter in the coastal Northern Tyrrhenian sea and in the stomach of two fish species of socio-economic importance, and exposed primary cell cultures of mucosal and lymphoid organs to marine microlitter for evaluating possible cytotoxic effects. An average of 0.30 {+/-} 0.02 microlitter items m-3 was found in water samples. FT-IR analysis revealed that plastic particles, namely HDPE, polyamide and polypropylene were present in 100% and 83.3% of Merluccius merluccius and Mullus barbatus analyzed, which overall ingested 14.67 {+/-} 4.10 and 5.50 {+/-} 1.97 items/individual, respectively. Moreover, microlitter was confirmed as a vector of microorganisms. Lastly, the apical end-point of viability was found to be significantly reduced in splenic cells exposed in vitro to two microlitter conditions. Considering the role of the spleen in the mounting of adaptive immune responses, our results warrant more in-depth investigations for clarifying the actual susceptibility of these two species to anthropogenic microlitter.

HighlightsO_LI0.30 {+/-} 0.02 microlitter items m-3 were found at the surface of coastal Northern Tyrrhenian sea
C_LIO_LI14.67 {+/-} 4.10 and 5.50 {+/-} 1.97 items/individual were retrieved from the stomach of hakes and mullets
C_LIO_LIThe ingested microlitter contained plastic items
C_LIO_LIMicrolitter was validated as a carrier of bacteria, fungi and flagellates
C_LIO_LISplenic cells exposed to two microlitter conditions for 72 hours suffered cytotoxicity
C_LI


title: First evidence of in vitro cytotoxic effects of marine microlitter on Merluccius merluccius and Mullus barbatus, two Mediterranean commercial fish species


title: Biophysical and Architectural Mechanisms of Subthalamic Theta under Response Conflict

abstract: The cortico-basal ganglia circuit is needed to suppress prepotent actions and to facilitate controlled behavior. Under conditions of response conflict, the frontal cortex and subthalamic nucleus [STN] exhibit increased spiking and theta band power, which are linked to adaptive regulation of behavioral output. The electrophysiological mechanisms underlying these neural signatures of impulse control remain poorly understood. To address this lacuna, we constructed a novel large-scale, biophysically principled model of the subthalamopallidal [STN-Globus Pallidus externus (GPe)] network, and examined the mechanisms that modulate theta power and spiking in response to cortical input. Simulations confirmed that theta power does not emerge from intrinsic network dynamics but is robustly elicited in response to cortical input as burst events representing action selection dynamics. Rhythmic burst events of multiple cortical populations, representing a state of conflict where cortical motor plans vacillate in the theta range, led to prolonged STN theta and increased spiking, consistent with empirical literature. Notably, theta band signaling required NMDA, but not AMPA, currents, which were in turn related to a triphasic STN response characterized by spiking, silence and bursting periods. Finally, theta band resonance was also strongly modulated by architectural connectivity, with maximal theta arising when multiple cortical populations project to individual STN "conflict detector" units, due to an NMDA-dependent supralinear response. Our results provide insights into the biophysical principles and architectural constraints that give rise to STN dynamics during response conflict, and how their disruption can lead to impulsivity and compulsivity.


title: High-frequency changes in single-trial visual evoked potentials for unattended stimuli in chronic schizophrenia

abstract:
BackgroundPatients with schizophrenia reveal changes in information processing associated with external stimuli, which is reflected in the measurements of brain evoked potentials. We discuss actual knowledge on electro- (EEG) and magnetoencephalographic (MEG) changes in schizophrenia.

New methodThe commonly used averaging technique entails the loss of information regarding the generation of evoked responses. We propose a methodology to describe single-trial (non-averaged) visual evoked potentials (VEP) using spectral and statistical analyses. We analysed EEG data registered in the O1-Cz and O2-Cz leads during unattended pattern-reversal stimulation, collected from a group of adult patients with chronic schizophrenia, and compared them to those of healthy individuals. Short-time single-trial VEP were transformed to the frequency domain using the FFT algorithm. Changes of the spectral power were visualized using spectrograms which were created by stacking single-trial spectra across all trials. Measures of the absolute and the relative spectral power were calculated and compared statistically.

ResultsIn schizophrenia, the energy density of VEP oscillations is shifted towards higher (gamma) frequencies, compared to healthy individuals. These differences are statistically significant in all analysed frequency bands for the relative power. This indicates distorted early processing of visual stimuli in schizophrenia.

Comparison with existing methodsThe main advantage of the presented methodology is its simplicity and ease of interpretation of obtained results. The presented observations complement the knowledge on gamma oscillations acquired from computationally more complex methods of time-frequency analysis.

ConclusionsHigh-frequency changes for single-trial VEPs are detected in chronic schizophrenia.


title: Neuroplastin genetically interacts with Cadherin 23 and the encoded isoform Np55 is sufficient for cochlear hair cell function and hearing

abstract:
Mammalian hearing involves the mechanoelectrical transduction (MET) of sound-induced fluid waves in the cochlea. Essential to this process are the specialised sensory cochlear cells, the inner (IHCs) and outer hair cells (OHCs). While genetic hearing loss is highly heterogeneous, understanding the requirement of each gene will lead to a better understanding of the molecular basis of hearing and also to therapeutic opportunities for deafness. The Neuroplastin (Nptn) gene, which encodes two protein isoforms Np55 and Np65, is required for hearing, and homozygous loss-of-function mutations that affect both isoforms lead to profound deafness in mice. Here we have utilised several distinct mouse models to elaborate upon the spatial, temporal, and functional requirement of Nptn for hearing. While we demonstrate that both Np55 and Np65 are present in cochlear cells, characterisation of a Np65-specific mouse knockout shows normal hearing thresholds indicating that Np65 is functionally redundant for hearing. In contrast, we find that Nptn-knockout mice have significantly reduced maximal MET currents and MET channel open probabilities in mature OHCs, with both OHCs and IHCs also failing to develop fully mature basolateral currents. Furthermore, comparing the hearing thresholds and IHC synapse structure of Nptn-knockout mice with those of mice that lack Nptn only in IHCs and OHCs shows that the majority of the auditory deficit is explained by hair cell dysfunction, with abnormal afferent synapses contributing only a small proportion of the hearing loss. Finally, we show that continued expression of NEUROPLASTIN in OHCs of adult mice is required for membrane localisation of Plasma Membrane Ca2+ ATPase 2 (PMCA2), which is essential for hearing function. Moreover, Nptn haploinsufficiency phenocopies Atp2b2 (encodes PMCA2) mutations, with heterozygous Nptn-knockout mice exhibiting hearing loss through genetic interaction with the Cdh23ahl allele. Together, our findings provide further insight to the functional requirement of Neuroplastin for mammalian hearing.

Author SummarySensorineural hearing loss, caused by problems with sensory cells in the cochlea or the auditory nerve, is the most common type of hearing loss. Mutations in Neuroplastin have already been implicated in deafness in mice. We have used mutant mouse models to investigate where Neuroplastin is expressed in the cochlea and its function. When mice do not express a functioning copy of Neuroplastin they have disruptions to the primary sensory synapse. We show that although synaptic disruption contributes to the loss of hearing function it is not the primary cause. Instead, continued expression of Neuroplastin is needed to maintain the localisation of Plasma Membrane Ca2+ ATPase 2 channels which help regulate calcium flow. We have also shown that two types of NEUROPLASTIN protein (isoforms) are both expressed within the cochlea, although only one of these isoforms needs to be expressed for normal hearing. Finally, we also demonstrate that the hearing loss caused by the absence of Neuroplastin is made worse when combined with a common mutation within a gene called Cadherin 23 (Cdh23ahl). This is an important finding as although there are currently no human patients with an identified NEUROPLASTIN mutation, it may be involved in human deafness in combination with other mutations.


title: Sequence learning attenuates cortical responses in both frontal and perceptual cortices in early infancy

abstract: Prior work has found that the frontal lobe is involved in higher-order sequential and statistical learning in young infants. Separate lines of work have found evidence of modulation of posterior sensory cortices during and after learning tasks. How do these processes relate? Here, we build evidence the infant frontal lobe was modulated during sequential learning and ask whether posterior perceptual cortices show corresponding modulation. First, replicating and extending past work, we found evidence of frontal lobe involvement in this task. Second, consistent with our hypotheses, we found that there is a corresponding attenuation of neural responses in the posterior perceptual cortices (temporal and occipital) to predictable compared to unpredictable audiovisual sequences. This study provides convergent evidence that the frontal lobe is crucial for higher-level learning in young infants but that it likely works as part of a large, distributed network of regions to modulate infant neural responses during learning. Overall, this work challenges the view that the infant brain is not dynamic and disconnected, lacking in long-range neural connections. Instead, this paper reveals patterns of a highly dynamic and interconnected infant brain that change rapidly as a result of new, learnable experiences.


title: Realistic alpha oscillations and transient responses in a cortical microcircuit model

abstract:
Neural-mass modeling of neural population data (EEG, ECoG, or LFPs) has shown promise both in elucidating the neural processes underlying cortical rhythms and changes in brain state, as well as offering a framework for testing the interplay between these rhythms and information processing. Models of cortical alpha rhythms (8 - 12 Hz) and their impact in visual sensory processing have been at the forefront of this effort, with the Jansen-Rit being one of the more popular models in this domain. The Jansen-Rit model, however, fails in reproducing key physiological observations including the level of inputs that cortical neurons receive and their responses to visual transients. To address these issues we generated a neural mass model that complies better with synaptic mediated dynamics, intrinsic alpha behavior, and produces realistic responses. The model is robust to many changes in parameter values but critically depends on the ratio of excitation to inhibition, producing response transients whose features are dependent on this ratio and alpha phase and power. The model is sufficiently flexible so as to be able to easily replicate the range of low frequency oscillations observed in different studies. Consistent with experimental observations, we find phase-dependent response dynamics to both visual and electrical stimulation using this model. The model suggests that stimulation facilitates alpha at particular phases and suppresses it in others due to a phase dependent lag in inhibitory responses. Hence, the model generates insight into the physiological parameters responsible for intrinsic oscillations and testable hypotheses regarding the interactions between visual and electrical stimulation on those oscillations.

Author summaryWhile there is increasing evidence of the fundamental role brain states play in shaping information processing in the cerebral cortex, a mechanistic understanding of how those brain states are manifested and alter the signals underlying sensory processing and decision making has proved challenging. To address this issue we have modeled a well established signature of inattention in visual cortex: synchronized low frequency (8 - 12 Hz) oscillations. To allow for inferences regarding the local generation of these rhythms within a cortical microcircuit we used a neural mass model approach that incorporates physiologically realistic interactions between 3 populations of neurons. Our model is able to explain a variety of experimental observations that previous neural mass models have not, including spontaneous rhythms in the absence of input, the faithful transmission of strong input transients, a range of oscillation frequencies, and phase dependent visual responses. The model is robust to a range of parameters, but critically depends on the balance between local excitation and inhibition.


title: An essential role for a discrete parasubthalamic nucleus subpopulation in appetite suppression

abstract: Food intake behavior is regulated by a network of appetite-inducing and appetite-suppressing neuronal populations throughout the brain. The parasubthalamic nucleus (PSTN), a relatively unexplored population of neurons in the posterior hypothalamus, has been hypothesized to regulate appetite due to its connectivity with other anorexigenic neuronal populations and because these neurons express Fos, a marker of neuronal activation, following a meal. However, the individual cell types that make up the PSTN are not well characterized, nor are their functional roles in food intake behavior. Here we identify and distinguish between two discrete PSTN subpopulations, those that express tachykinin-1 (PSTNTac1 neurons) and those that express corticotropin-releasing hormone (PSTNCRH neurons), and use a panel of genetically encoded tools in mice to show that PSTNTac1 neurons play an essential role in appetite suppression. Both subpopulations increase activity following a meal and in response to administration of the anorexigenic hormones amylin, cholecystokinin (CCK), and peptide YY (PYY). Interestingly, chemogenetic inhibition of PSTNTac1, but not PSTNCRH neurons, reduces the appetite-suppressing effects of these hormones. Consistently, optogenetic and chemogenetic stimulation of PSTNTac1 neurons, but not PSTNCRH neurons, is sufficient to reduce food intake in hungry mice. PSTNTac1 and PSTNCRH neurons project to distinct downstream brain regions, and stimulation of PSTNTac1 projections to individual anorexigenic populations reduces food consumption. Taken together, these results reveal the functional properties and projection patterns of distinct PSTN cell types and demonstrate an essential, anorexigenic role for PSTNTac1 neurons in the hormonal and central regulation of appetite.


title: IFN-γ stimulated murine and human neurons mount anti-parasitic defenses against the intracellular parasite Toxoplasma gondii

abstract: Dogma holds that Toxoplasma gondii persists in neurons because neurons cannot clear intracellular parasites, even with IFN-{gamma} stimulation. As several recent studies questioned this idea, we used primary murine neuronal cultures from wild-type and transgenic mice in combination with IFN-{gamma} stimulation and parental and transgenic parasites to reassess IFN-{gamma} dependent neuronal clearance of intracellular parasites. We found that neurons respond to IFN-{gamma} and that a subset of neurons clear intracellular parasites via immunity regulated GTPases. Whole neuron reconstructions from mice infected with parasites that trigger neuron GFP expression only after full invasion revealed that [~]40% of these T. gondii-invaded neurons no longer harbor parasites. Finally, IFN-{gamma} stimulated human stem cell derived neurons showed a [~] 50% decrease in parasite infection rate when compared to unstimulated cultures. This work highlights the capability of human and murine neurons to mount cytokine-dependent anti-T. gondii defense mechanisms in vitro and in vivo.


category: microbiology


title: An Infant Sleep Electroencephalographic Marker of Thalamocortical Connectivity Predicts Behavioral Outcome in Late Infancy

abstract:
Infancy represents a critical period during which thalamocortical brain connections develop and mature. Deviations in the maturation of thalamocortical connectivity are linked to neurodevelopmental disorders. There is a lack of early biomarkers to detect and localize neuromaturational deviations, which can be overcome with mapping through high-density electroencephalography (hdEEG) assessed in sleep. Specifically, slow waves and spindles in non-rapid eye movement (NREM) sleep are generated by the thalamocortical system, and their characteristics, slow wave slope and spindle density, are closely related to neuroplasticity and learning. Recent studies further suggest that information processing during sleep underlying sleep-dependent learning is promoted by the temporal coupling of slow waves and spindles, yet slow wave-spindle coupling remains unexplored in infancy. Thus, we evaluated three potential biomarkers: 1) slow wave slope, 2) spindle density, and 3) the temporal coupling of slow waves with spindles. We use hdEEG to first examine the occurrence and spatial distribution of these three EEG features in healthy infants and second to evaluate a predictive relationship with later behavioral outcomes. We report four key findings: First, infants EEG features appear locally: slow wave slope is maximal in occipital and frontal areas, whereas spindle density is most pronounced frontocentrally. Second, slow waves and spindles are temporally coupled in infancy, with maximal coupling strength in the occipital areas of the brain. Third, slow wave slope, spindle density, and slow wave-spindle coupling are not associated with concurrent behavioral status (6 months). Fourth, spindle density in central and frontocentral regions at age 6 months predicts later behavioral outcomes at 12 and 24 months. Neither slow wave slope nor slow wave-spindle coupling predict behavioral development. Our results propose spindle density as an early EEG biomarker for identifying thalamocortical maturation, which can potentially be used for early diagnosis of neurodevelopmental disorders in infants. These findings are complemented by our companion paper that demonstrates the linkage of spindle density to infant nighttime movement, framing the possible role of spindles in sensorimotor microcircuitry development. Together, our studies suggest that early sleep habits, thalamocortical maturation, and behavioral outcome are closely interwoven. A crucial next step will be to evaluate whether early therapeutic interventions may be effective to reverse deviations in identified individuals at risk.

HighlightsO_LISlow waves and spindles occur in a temporally coupled manner in infancy
C_LIO_LISlow wave slope, spindle density, and slow wave-spindle coupling are not related to concurrent behavioral development
C_LIO_LISpindle density at 6 months predicts behavioral status at 12 and 24 months
C_LIO_LISlow wave slope and slow wave-spindle coupling are not predictive of behavioral development
C_LI


title: Contribution of linear and nonlinear mechanisms to predictive motion estimation

abstract: Successful behavior relies on the ability to use information obtained from past experience to predict what is likely to occur in the future. A salient example of predictive encoding comes from the vertebrate retina, where neural circuits encode information that can be used to estimate the trajectory of a moving object. Predictive computations should be a general property of sensory systems, but the features needed to identify these computations across neural systems are not well understood. Here, we identify several properties of predictive computations in the primate retina that likely generalize across sensory systems. These features include calculating the derivative of incoming signals, sparse signal integration, and delayed response suppression. These findings provide a deeper understanding of how the brain carries out predictive computations and identify features that can be used to recognize these computations throughout the brain.


title: A vaccine targeting the L9 epitope of the malaria circumsporozoite protein confers protection from blood-stage infection in a mouse challenge model

abstract: Pre-erythrocytic malaria vaccines that induce high-titer, durable antibody responses can potentially provide protection from infection. Here, we engineered a virus-like particle (VLP)-based vaccine targeting a recently described vulnerable epitope at the N-terminus of the central repeat region of the Plasmodium falciparum circumsporozoite protein (CSP) that is recognized by the potently inhibitory monoclonal antibody L9 and show that immunization with L9 VLPs induces strong antibody responses that provide protection from blood-stage malaria in a mouse infection model.