Miracle-dz/UniFAR-FTUs huggingface dataset:
Age-related degradation of optic radiation white matter predicts visual, but not verbal executive functions

Healthy aging is accompanied by degraded white matter connectivity, which has been suggested to contribute to cognitive dysfunction observed in aging, especially in relation to fluid measures of cognition. Prior research linking white matter microstructure and cognition, however, has largely been limited to major association and heteromodal white matter tracts. The optic radiations (OR), which transfer visual sensory-perceptual information from thalamic lateral geniculate nucleus to primary visual cortex, are generally considered lower-level input-relay white matter tracts. However, the role of this prominent white-matter visual relay system in supporting higher-order cognition is understudied, especially in regard to healthy aging. The present study used deterministic tractography to isolate OR fractional anisotropy (FA) in 130 participants aged 20-94 to assess age effects on OR tract white matter. We also examined associations between age-related differences in the OR and cognitive domains involving visual processing speed, and visual- and non-visual executive function (EF). OR microstructure, as indexed by FA, exhibited a significant linear decrease across age. A significant interaction between age, FA, and cognitive domain on cognitive task performance indicated that in older age, more degraded OR white matter was associated with poorer visual EF, but no age-related association between FA in the OR and visual processing speed or verbal EF was observed. These findings suggest the optic radiations are not merely sensory-perceptual relays, but also influence higher-order visual cognition differentially with age.
Rapid compensatory evolution can rescue low fitness symbioses following partner switching

Partner-switching plays an important role in the evolution of symbiosis, enabling local adaptation and recovery from the breakdown of symbiosis. Because of intergenomic epistasis, partner-switched symbioses may possess novel combinations of phenotypes but may also exhibit low fitness due to their lack of recent coevolutionary history. Here, we examine the structure and mechanisms of intergenomic epistasis in the Paramecium-Chlorella symbiosis and test if compensatory evolution can rescue initially low fitness partner-switched symbioses. Using partner-switch experiments coupled with metabolomics we show evidence for intergenomic epistasis wherein low fitness arose from mismatched photoprotection traits and the resulting light stress experienced by non-native symbionts when in high light environments. Experimental evolution under high light conditions revealed that an initially low fitness partner-switched non-native host-symbiont pairing rapidly adapted, gaining fitness equivalent to the native host symbiont pairing in less than 50 host generations. Compensatory evolution took two alternative routes: Either, hosts evolved higher symbiont loads to mitigate for their new algal symbiont’s poor performance, or the algal symbionts themselves evolved higher investment in photosynthesis and photoprotective traits to better mitigate light stress. These findings suggest that partner-switching combined with rapid compensatory evolution will enable the recovery and local adaptation of symbioses in response to changing environments. Significance statement Symbiosis enables the formation of new organisms through the merger of once independent species. Through symbiosis, species can acquire new functions, driving evolutionary innovation and underpinning important ecosystem processes. Symbioses that breakdown due to changing environmental conditions can reform by acquiring new symbionts in a process called partner-switching but may exhibit low fitness due to their lack of coadaptation. Using a microbial symbiosis between the single-celled eukaryote Paramecium and the green alga Chlorella we show that low fitness in partner-switched host-symbiont pairings arises from mismatched photoprotection traits. However, such low fitness partner-switched pairings can be rapidly rescued by adaptive evolution, regaining high fitness in less than 50 host generations. Partner-switching coupled with rapid compensatory evolution can enable symbioses to recover from breakdown.
The evolution of a placenta is not linked to increased brain size in poeciliid fishes

Maternal investment is considered to have a direct influence on the size of energetically costly organs, including the brain. In placental organisms, offspring are supplied with nutrients during pre-natal development, potentially modulating brain size. However, the coevolution of the placenta and brain size remains largely unknown in non-mammalian taxa. Here, using eight poeciliid fish species, we test if species with placental structures invest more resources into offspring brain development than species without placental structures. We predict that matrotrophy may entail higher nutrient provisioning rates to the developing embryo than lecithotrophy, resulting in larger brain sizes in offspring of matrotrophic species, and that a relatively larger part of the total brain growth would occur at younger ages (leading to a shallower ontogenetic brain size allometry). We took non-invasive brain size measurements during the first four weeks of life, and compared these to somatic growth measurements. Contrary to our expectations, we did not find any differences in brain size between the two maternal strategies. Furthermore, we did not find any differences in how relative brain size changed over ontogenetic development, between placental and non-placental species. In contrast to the marsupial/placental transition, the species investigated here only exhibit pre-natal provisioning, which may reduce the potential for maternal investment into brain size. Consequently, our results suggest that coevolution between placental structures and juvenile brain size is not a general pattern.
PCMD-1 bridges the centrioles and the PCM scaffold in C. elegans

Correct cell division relies on the formation of a bipolar spindle. In animal cells, microtubule nucleation at the spindle poles is facilitated by the pericentriolar material (PCM), which assembles around a pair of centrioles. Although centrioles are essential for PCM assembly, proteins that anchor the PCM to the centrioles are less known. Here we investigate the molecular function of PCMD-1 in bridging the PCM and the centrioles in Caenorhabditis elegans. We demonstrate that centrosomal recruitment of PCMD-1 is dependent on the outer centriolar protein SAS-7. While the most C-terminal part of PCMD-1 is sufficient to target it to the centrosome, the coiled-coil domain promotes its accumulation by facilitating self-interaction. We reveal that PCMD-1 is bridging the centrioles and PCM scaffold through protein-protein interactions with the PCM scaffold protein SPD-5, the mitotic kinase PLK-1 and the centriolar protein SAS-4. Using an ectopic translocation assay, we show that PCMD-1 is able to selectively recruit downstream PCM scaffold components to an ectopic location in the cell, indicating that PCMD-1 is sufficient to anchor the PCM scaffold proteins to the centrioles. Our work suggests that PCMD-1 is an essential functional bridge between the centrioles and the PCM.
Mechanistic analysis of enhancer sequences in the Estrogen Receptor transcriptional program

Background Estrogen Receptor α (ERα) is a major lineage determining transcription factor (TF) in mammary gland development, orchestrating the expression of thousands of genes. Dysregulation of ERα-mediated transcriptional program results in abnormal cell proliferation and cancer. Transcriptomic and epigenomic profiling of breast cancer cell lines has revealed large numbers of enhancers involved in this regulatory program, but how these enhancers encode function in their sequence remains poorly understood. Results A subset of ERα-bound enhancers are transcribed into short bidirectional RNA (enhancer RNA or eRNA), and this property is believed to be a reliable marker of active enhancers. We therefore analyze thousands of ERα-bound enhancers and build quantitative, mechanism-aware models to discriminate eRNAs from non-transcribing enhancers based on their sequence. Our thermodynamics-based models provide insights into the roles of specific TFs in ERα-mediated transcriptional program, many of which are supported by the literature. We use in silico perturbations to predict TF-enhancer regulatory relationships and integrate these findings with experimentally determined enhancer-promoter interactions to construct a gene regulatory network. We also demonstrate that the model can prioritize breast cancer-related sequence variants while providing mechanistic explanations for their function. Finally, we experimentally validate the model-proposed mechanisms underlying three such variants. Conclusions We modeled the sequence-to-expression relationship in ERα-driven enhancers and gained mechanistic insights into the workings of a major transcriptional program. Our model is consistent with the current body of knowledge and its predictions are confirmed by experimental observations. We believe this to be a promising approach to analysis of regulatory sequences and variants.
Signaling-based neural networks for cellular computation

Cellular signaling pathways are responsible for decision making that sustains life. Most signaling pathways include post-translational modification cycles, that process multiple inputs and are tightly interconnected. Here we consider a model for phosphorylation/dephosphorylation cycles, and we show that under some assumptions they can operate as molecular neurons or perceptrons, that generate sigmoidal-like activation functions by processing sums of inputs with positive and negative weights. We carry out a steady-state and structural stability analysis for single molecular perceptrons as well as for feedforward interconnections, concluding that interconnected phosphorylation/dephosphorylation cycles may work as multi-layer biomolecular neural networks (BNNs) with the capacity to perform a variety of computations. As an application, we design signaling networks that behave as linear and non-linear classifiers.
The tuning of tuning: how adaptation influences single cell information transfer

Sensory neurons reconstruct the world from action potentials (spikes) impinging on them. To effectively transfer information about the stimulus to the next processing level, a neuron needs to be able to adapt its working range to the properties of the stimulus. Here, we focus on the intrinsic neural properties that influence information transfer in cortical neurons and how tightly their properties need to be tuned to the stimulus statistics for them to be effective. We start by measuring the intrinsic information encoding properties of putative excitatory and inhibitory neurons in L2/3 of the mouse barrel cortex. Excitatory neurons show high thresholds and strong adaptation, making them fire sparsely and resulting in a strong compression of information, whereas inhibitory neurons that favour fast spiking transfer more information. Next, we turn to computational modelling and ask how two properties influence information transfer: 1) spike-frequency adaptation and 2) the shape of the IV-curve. We find that a subthreshold (but not threshold) adaptation, the ‘h-current’, and a properly tuned leak conductance can increase the information transfer of a neuron, whereas threshold adaptation can increase its working range. Finally, we verify the effect of the IV-curve slope in our experimental recordings and show that excitatory neurons form a more heterogeneous population than inhibitory neurons. These relationships between intrinsic neural features and neural coding that had not been quantified before will aid computational, theoretical and systems neuroscientists in understanding how neuronal populations can alter their coding properties, such as through the impact of neuromodulators. Why the variability of intrinsic properties of excitatory neurons is larger than that of inhibitory ones is an exciting question, for which future research is needed. Author summary Intracellular information transfer from synaptic input to output spike train is necessarily lossy. Here, we explicitly measure the mutual information between a neuron’s input and spike output and show that information transfer is more lossy and heterogeneous for excitatory than for inhibitory neurons. By using computational modelling we show that the shape of the input-output curve as well as how fast a neuron adapts to its input collectively determine the rate of information loss. These insights will help both experimentalists and modellers in designing and simulating experiments that investigate how network coding properties can adapt to the environment, for instance through the effects of neuromodulators.
CoaTran: Coalescent tree simulation along a transmission network

Motivation The ability to simulate coalescent viral phylogenies constrained by a given transmission network can enable the benchmarking of computational tools used in molecular epidemiology as well as the ability to gain insights into unobservable aspects of the virology of a novel pathogen. However, such simulation experiments require generating a large number of technical simulation replicates, and existing tools for coalescent simulations along a transmission network are too slow to conduct such experiments at the scale of the global population. Results CoaTran is a massively scalable tool that simulates a coalescent viral phylogeny constrained by a user-provided transmission network. CoaTran is written in highly-optimized C++ code and can generate global population scale phylogenetic coalescent simulations in seconds to minutes. Availability CoaTran is freely available at https://github.com/niemasd/CoaTran as an open-source software project. Contact niema@ucsd.edu Supplementary information Supplementary data are available online.
Enrichment of neurodegenerative microglia signature in brain-derived extracellular vesicles isolated from Alzheimer’s disease mouse model

Extracellular vesicles (EVs) are secreted by any neuronal cells in the central nervous system (CNS) for molecular clearance, cellular communications and disease spread in multiple neurodegenerative diseases, including Alzheimer’s disease (AD), although their exact molecular mechanism is poorly understood. We hypothesize that high-resolution proteomic profiling of EVs separated from animal models of AD would determine the composition of EV contents and their cellular origin. Here, we examined recently developed transgenic mice (CAST.APP/PS1), which express familial AD-linked mutations of amyloid precursor protein (APP) and presenilin-1 (PS1) in the CAST/EiJ mouse strain and develop hippocampal neurodegeneration. Quantitative proteomics analysis of EVs separated from CAST.APP/PS1 and age-matched control mice by tandem mass tag-mass spectrometry identified a total of 3,444 unique proteins, which are enriched in neuron, astrocyte, oligodendrocyte and microglia-specific molecules. CAST.APP/PS1-derived EVs show significant enrichment of Psen1, APP, Itgax, and reduction of Wdr61, Pmpca, Aldh1a2, Calu, Anp32b, Actn4 and Ndufv2 compared to WT-derived EVs, suggesting the involvement of Aβ-processing complex and disease-associated / neurodegenerative microglia (DAM/MGnD) in EV secretion. In addition, Itgax and Apoe, the DAM/MGnD markers, in EV show a positive correlation with Itgax and Apoe mRNA expression from brain tissue in CAST.APP/PS1 mice. These datasets indicate the significant contribution of Aβ plaque and neurodegeneration-induced DAM/MGnD microglia for EV secretion in CAST.APP/PS1 mice and shed light on understanding the AD pathogenesis.
Resting state brain signal complexity of young healthy adults reflects genetic risk for developing Alzheimer’s Disease

The e4 allele of the APOE gene is strongly associated with impaired brain functionality and cognitive decline in humans at older age. It is controversial whether and how the APOE e4 allele is affecting brain activity among young healthy individuals and how such effects may contribute to individual differences in cognitive performance. Signal complexity is a critical aspect of brain activity that has been shown to be associated with brain function. In this study, we analyzed multiscale entropy (MSE) of EEG signals among young healthy adults as an indicator of brain signal complexity and investigated how MSE is predicted by APOE genotype groups. Furthermore, by means of structural equation modeling, we investigated whether MSE predicts fluid intelligence. Results indicate larger MSE in young healthy e4 carriers across all time scales. Moreover, better fluid intelligence (gf) is associated with smaller MSE at low time scales and larger MSE at higher scales. However, MSE does not account for better cognitive performance among APOE e4 carriers by mediating the APOE genotype effect on fluid intelligence. The present results shed further light on the neural mechanisms underlying gene-behavior association relevant for Alzheimer’s Disease risk.
EFL learners’ cultural available lexicon: The effect of ELT textbooks

This research compares the cultural types elicited by twenty-nine EFL undergraduate students in response to two prompts from a lexical availability task (i.e. food and drink and countryside) and the cultural input provided by four last year High School ELT textbooks used in La Rioja . Cultural words were classified in terms of their frequency of appearance by means of Range and listed according to a framework of cultural topics (Risager, 1991; Byram, 1993; Byram & Morgan, 1994; Common European Framework of Reference (CEF, 2001). Finally, the words produced by the learners as well the input provided by the textbooks were associated with the culture they represented i.e. source, target, and international culture. Our findings reveal that the number of words related to culture either elicited by students or included in the ELT textbooks is low. Most of the words students and textbooks provided belong to everyday living, and international is the most representative culture in the study.
Genetic Evidence for Selective Transfer of Microbes Between the International Space Station and an Astronaut

Microbial transfer of both pathogenic and non-pathogenic strains from the environment can influence a person’s health, but such studies are rare and the phenomenon is difficult to study. Here, we use the unique, isolated environment of the International Space Station (ISS) to track environmental movement of microbes in an astronaut’s body. We identified several microbial taxa, including Serratia proteamaculans and Rickettsia australis, which appear to have been transferred from the environment of to the gut and oral microbiomes of the on-board astronaut, and also observed an exchange of genetic elements between the microbial species. Strains were matched at the SNP and haplotype-level, and notably some strains persisted even after the astronaut’s return to Earth. Finally, some transferred taxa correspond to secondary strains in the ISS environment, suggesting that this process may be mediated by evolutionary selection, and thus, continual microbial monitoring can be important to future spaceflight mission planning and habitat design.
Phenotypic and environmental predictors of reproductive success in painted turtles

Sexual selection is often assumed to elicit sexually dimorphic traits. However, most work on this assumption in tetrapod vertebrates has focused on birds. In this field experiment, we assessed relationships between both sexually dimorphic (body size, claw length) and non-dimorphic traits (forelimb stripe color, baseline corticosterone concentrations) and reproductive success in adult painted turtles to explicate the roles of these phenotypes in mate choice and the evolution of sexual dimorphism. We also modified adult sex ratios in experimental ponds to elucidate the role of biased sex ratios on reproductive success, which is a timely test of the potential threat of biased sex ratios on population persistence in a species with temperature-dependent sex determination. We found no strong influence of male phenotypes on male siring success, but female body size and baseline corticosterone concentrations predicted female clutch sizes. We find weak evidence that adult sex ratio influences male siring success, with a male-biased sex ratio producing lower male siring success than a female-biased sex ratio. This study offers evidence that female mate choice may not be an important selective force on male phenotypes, but that instead selection occurs on female phenotypes, particularly body size and corticosterone concentrations. Further, biased adult sex ratios can influence reproductive success of both sexes. Finally, the use of Kompetitive Allele Specific PCR (KASP) was highly successful in parentage analysis, which adds reptiles to the growing list of taxa successfully genotyped with this new technology. Lay Summary Female painted turtles aren’t choosy about traits of their mates. In a field experiment, we find that male traits do not predict male fitness, but key female traits (body size and stress levels) do predict female reproductive success. Further, we find weak evidence that adult sex ratio influences individual fitness in this species with environmental sex determination. Ultimately, we reject the long-assumed importance of female mate choice in this freshwater turtle.
SARS-CoV-2 infection causes transient olfactory dysfunction in mice

Olfactory dysfunction caused by SARS-CoV-2 infection represents as one of the most predictive and common symptoms in COVID-19 patients. However, the causal link between SARS-CoV-2 infection and olfactory disorders remains lacking. Herein we demonstrate intranasal inoculation of SARS-CoV-2 induces robust viral replication in the olfactory epithelium (OE), resulting in transient olfactory dysfunction in humanized ACE2 mice. The sustentacular cells and Bowman’s gland cells in OE were identified as the major targets of SARS-CoV-2 before the invasion into olfactory sensory neurons. Remarkably, SARS-CoV-2 infection triggers cell death and immune cell infiltration, and impairs the uniformity of OE structure. Combined transcriptomic and proteomic analyses reveal the induction of antiviral and inflammatory responses, as well as the downregulation of olfactory receptors in OE from the infected animals. Overall, our mouse model recapitulates the olfactory dysfunction in COVID-19 patients, and provides critical clues to understand the physiological basis for extrapulmonary manifestations of COVID-19.
Processing of subjectively and objectively invisible stimuli in human visual cortex

The study of unconscious processing requires a measure of conscious awareness. Awareness measures can be either subjective (based on participant’s report) or objective (based on perceptual performance). The preferred awareness measure depends on the theoretical position about consciousness, and may influence conclusions about the extent of unconscious processing and about the neural correlates of consciousness. We obtained fMRI measurements from 43 subjects while they viewed masked faces and houses that were either subjectively or objectively invisible. We show that neural representations of objectively invisible faces and houses are limited to visual (shape-related) object properties, while subjectively invisible stimuli are processed up to more abstract, categorical levels of representation. These results demonstrate that the hypothesized extent of unconscious information processing is determined by the measurement approach. Furthermore, our data show that subjective and objective approaches are associated with different neural correlates of consciousness and thus have implications for neural theories of consciousness.