Miracle-dz/UniFAR-FTUs huggingface dataset:
Hippocampal and caudate network specificity is altered in older adults

The hippocampal and the caudate networks, defined by their intrinsic resting state functional connectivity (FC), exhibit strong network specificity. This is reflected as strong within-network and weak between-network FC, as well as their dissociable roles in cognition. Aging typically reduces the specificity of brain networks. However, whether the hippocampal and caudate networks show age-related decreases in network specificity is unclear. Further, whether any age-related decreases in network specificity are due to reduced within-network FC, increased between-network FC, or some combination of both, is also unclear. Using a large-scale fMRI data set acquired from healthy younger (n = 101, aged 18–40 years) and older (n = 101, 55–75 years) adults, networks centered on the left anterior hippocampus and the head of the right caudate nucleus were compared. These sub-regions were chosen based on their distinct contributions to cognition, their known interactions, and their susceptibility to age-related changes. A mixed effect model was used to identify brain regions where network specificity differed between groups. For younger adults, hippocampal network specificity was strong in the medial frontal gyrus (MFG), while caudate network specificity was strong in the basal nuclei. However, network specificity in these same regions was significantly reduced in older adults. Reduced specificity in each network was due to a weakening of within-network connectivity rather than an increase in between-network connectivity. These results indicate that hippocampal and caudate network specificity decreases with advancing age, raising the possibility that these reductions may contribute to age-related changes in memory. Impact Statement Older adults represent an increasing proportion of the population, thus increasing the urgency for us to understand the neurological changes that contribute to age-related memory loss. Aging is associated with a loss of network specificity, reflected as reduced within-network, and increased between-network, connectivity. My work shows that this phenomenon is not restricted to the hippocampal and caudate networks, which are critical for learning facts and skills, respectively: Both networks decreased in network functional connectivity. These results raise the possibility that “blurring” between these networks relates to age-related memory loss, possibly as a compensatory mechanism to protect memory in old age.
Dual-stream cortical feedbacks mediate sensory prediction

Predictions are constantly generated from diverse sources to optimize cognitive functions in the ever-changing environment. However, the neural origin and generation process of top-down induced prediction remain elusive. We hypothesized that motor-based and memory-based predictions are mediated by distinct feedback networks from motor and memory systems to the sensory cortices. Using fMRI and a dual imagery paradigm, we showed that motor and memory upstream systems excited the auditory cortex in a content-specific manner. Moreover, the inferior and posterior parts of the parietal lobe differentially relayed predictive signals in motor-to-sensory and memory-to-sensory networks. Our results reveal the functionally distinct neural networks that mediate top-down sensory prediction and ground the neurocomputational basis of predictive processing.
High-performing neural network models of visual cortex benefit from high latent dimensionality

Geometric descriptions of deep neural networks (DNNs) have the potential to uncover core representational principles of computational models in neuroscience. Here we examined the geometry of DNN models of visual cortex by quantifying the latent dimensionality of their natural image representations. A popular view holds that optimal DNNs compress their representations onto low-dimensional subspaces to achieve invariance and robustness, which suggests that better models of visual cortex should have lower dimensional geometries. Surprisingly, we found a strong trend in the opposite direction—neural networks with high-dimensional image subspaces tended to have better generalization performance when predicting cortical responses to held-out stimuli in both monkey electrophysiology and human fMRI data. Moreover, we found that high dimensionality was associated with better performance when learning new categories of stimuli, suggesting that higher dimensional representations are better suited to generalize beyond their training domains. These findings suggest a general principle whereby high-dimensional geometry confers computational benefits to DNN models of visual cortex.
Depletion of ALMS1 affects TGF-β signalling pathway and downstream processes such as cell migration and adhesion capacity

Background ALMS1 is a ubiquitous gene associated with Alström syndrome (ALMS). The main symptoms of ALMS affect multiple organs and tissues, generating at last, multi-organic fibrosis in the lungs, kidneys and liver. TGF-β is one of the main pathways implicated in fibrosis, controlling the cell cycle, apoptosis, cell migration, cell adhesion and epithelial-mesenchymal transition (EMT). Nevertheless, the role of ALMS1 gene in fibrosis generation and other implicated processes such as cell migration or cell adhesion via the TGF-β pathway has not been elucidated yet. Methods Initially, we evaluated how depletion of ALMS1 affects different processes like apoptosis, cell cycle and mitochondrial activity in HeLa cells. Then, we performed proteomic profiling with TGF-β stimuli in HeLa ALMS1 −/− cells and validated the results by examining different EMT biomarkers using qPCR. The expression of these EMT biomarkers were also studied in hTERT-BJ-5ta ALMS1 −/−. Finally, we also evaluated the SMAD3 and SMAD2 phosphorylation and cell migration capacity in both models. Results Depletion of ALMS1 generated apoptosis resistance to thapsigargin (THAP) and C2-Ceramide (C2-C), and G2/M cell cycle arrest in HeLa cells. For mitochondrial activity, results did not show significant differences between ALMS1 +/+ and ALMS1 −/−. Proteomic results showed inhibition of downstream pathways regulated by TGF-β. The protein-coding genes (PCG) were associated with processes like focal adhesion or cell-substrate adherens junction in HeLa. SNAI1 showed an opposite pattern to what would be expected when activating the EMT in HeLa and BJ-5ta. Finally, in BJ-5ta model a reduced activation of SMAD3 but not SMAD2 were also observed. In HeLa models no alterations in the canonical TGF-β pathway were observed but both cell lines showed a reduction in migration capacity. Conclusion ALMS1 has a role in controlling the cell cycle and the apoptosis processes. Moreover, the depletion of ALMS1 affects the signal transduction through the TGF-β and other processes like the cell migration and adhesion capacity.
Optimised Non-Coding Regions of mRNA SARS-CoV-2 Vaccine CV2CoV Improves Homologous and Heterologous Neutralising Antibody Responses

More than two years after the emergence of SARS-CoV-2, 33 COVID-19 vaccines, based on different platforms, have been approved in 197 countries. Novel variants that are less efficiently neutralised by antibodies raised against ancestral SARS-CoV-2 are circulating, highlighting the need to adapt vaccination strategies. Here, we compare the immunogenicity of a first-generation mRNA vaccine candidate, CVnCoV, with a second-generation mRNA vaccine candidate, CV2CoV, in rats. Higher levels of spike (S) protein expression were observed in cell culture with the CV2CoV mRNA than with the CVnCoV mRNA. Vaccination with CV2CoV also induced higher titres of virus neutralising antibodies with accelerated kinetics in rats compared with CVnCoV. Significant cross-neutralisation of the SARS-CoV-2 variants, Alpha (B.1.1.7), Beta (B.1.351), and the ‘mink’ variant (B1.1.298) that were circulating at the time in early 2021 were also demonstrated. In addition, CV2CoV induced higher levels of antibodies at lower doses than CVnCoV, suggesting that dose-sparing could be possible with the next-generation SARS-CoV-2 vaccine, which could improve worldwide vaccine supply.
The functional form of value normalization in human reinforcement learning

Reinforcement learning research in humans and other species indicates that rewards are represented in a context-dependent manner. More specifically, reward representations seem to be normalized as a function of the value of the alternative options. The dominant view postulates that value context-dependence is achieved via a divisive normalization rule, inspired by perceptual decision-making research. However, behavioral and neural evidence points to another plausible mechanism: range normalization. Critically, previous experimental designs were ill-suited to disentangle the divisive and the range normalization accounts, which generate similar behavioral predictions in many circumstances. To address this question, we designed a new learning task where we manipulated, across learning contexts, the number of options and the value ranges. Behavioral and computational analyses falsify the divisive normalization account and rather provide support for the range normalization rule. Together, these results shed new light on the computational mechanisms underlying context-dependence in learning and decision-making.
Discovering functionally important sites in proteins

Proteins play important roles in biology, biotechnology and pharmacology, and missense variants are a common cause of disease. Discovering functionally important sites in proteins is a central but difficult problem because of the lack of large, systematic data sets. Sequence conservation can highlight residues that are functionally important but is often convoluted with a signal for preserving structural stability. We here present a machine learning method to predict functional sites by combining statistical models for protein sequences with biophysical models of stability. We train the model using multiplexed experimental data on variant effects and validate it broadly. We show how the model can be used to discover active sites, as well as regulatory and binding sites. We illustrate the utility of the model by prospective prediction and subsequent experimental validation on the functional consequences of missense variants in HPRT1 which may cause Lesch-Nyhan syndrome, and pinpoint the molecular mechanisms by which they cause disease.
The neural determinants of abstract beauty

We have enquired into the neural activity which correlates with the experience of beauty aroused by abstract paintings consisting of arbitrary assemblies of lines and colours. During the brain imaging experiments, subjects rated abstract paintings according to aesthetic appeal. There was low agreement on the aesthetic classification of these paintings among participants. Univariate analyses revealed higher activity with higher declared aesthetic appeal in both the visual areas and the medial frontal cortex. Additionally, representational similarity analysis (RSA) revealed that the experience of beauty correlated with decodable patterns of activity in visual areas. These results are broadly similar to those obtained in previous studies on facial beauty. With abstract art, it was the involvement of visual areas implicated in the processing of lines and colours while with faces it was of visual areas implicated in the processing of faces. Both categories of aesthetic experience correlated with increased activity in medial frontal cortex. We conclude that the sensory areas participate in the selection of stimuli according to aesthetic appeal and that it is the co-operative activity between the sensory areas and the medial frontal cortex that is the basis for the experience of abstract visual beauty. Further, this co-operation is enabled by “experience dependent” functional connections, in the sense that currently the existence and high specificity of these connections can only be demonstrated during certain experiences.
Kinematics of individual muscle units in natural contractions measured in vivo using ultrafast ultrasound

Objective. The study of human neuromechanical control at the motor unit (MU) level has predominantly focussed on electrical activity and force generation, whilst the link between these, i.e. the muscle deformation, has not been widely studied. To address this gap, we analysed the kinematics of muscle units in natural contractions. Approach. We combined high-density surface electromyography (HDsEMG) and ultrafast ultrasound (US) recordings, at 1000 frames per second, from the tibialis anterior muscle to measure the motion of the muscular tissue caused by individual MU contractions. The MU discharge times were identified online by decomposition of the HDsEMG and provided as biofeedback to 12 subjects who were instructed to keep the MU active at the minimum discharge rate (9.8 ± 4.7 pulses per second; force less than 10% of the maximum). The series of discharge times were used to identify the velocity maps associated with 51 single muscle unit movements with high spatio-temporal precision, by a novel processing method on the concurrently recorded US images. From the individual MU velocity maps, we estimated the region of movement, the duration of the motion, the contraction time, and the excitation–contraction (E–C) coupling delay. Main results. Individual muscle unit motions could be reliably identified from the velocity maps in 10 out of 12 subjects. The duration of the motion, total contraction time, and E–C coupling were 17.9 ± 5.3 ms, 56.6 ± 8.4 ms, and 3.8 ± 3.0 ms (n = 390 across ten participants). The experimental measures also provided the first evidence of muscle unit twisting during voluntary contractions and MU territories with distinct split regions. Significance. The proposed method allows for the study of kinematics of individual MU twitches during natural contractions. The described measurements and characterisations open new avenues for the study of neuromechanics in healthy and pathological conditions.
Epistasis reduces fitness costs of influenza A virus escape from stem-binding antibodies

The hemagglutinin (HA) stem region is a major target of universal influenza vaccine efforts owing to the presence of highly conserved epitopes across multiple influenza A virus strains and subtypes. To explore the potential impact of vaccine-induced immunity targeting the HA stem, we examined the fitness effects of viral escape from stem-binding broadly neutralizing antibodies (stem-bnAbs). Recombinant viruses containing each individual antibody escape substitution showed diminished replication compared to wild-type virus, indicating that stem-bnAb escape incurred fitness costs. A second-site mutation in the HA head domain (N133D) reduced the fitness effects observed in primary cell cultures and likely enabled the selection of escape mutations. This putative permissive mutation was not, however, sufficient to ease fitness costs in a ferret transmission model. Taken together, these data suggest that viral escape from stem-bnAbs is costly but highlight the potential for epistatic interactions to enable evolution within the functionally constrained HA stem domain.
Regulation of sleep quantity and intensity by long and short isoforms of SLEEPY kinase

In Sleepy (Sik3Slp) or Sik3S551A mice, deletion or mutation of inhibitory phosphorylation site serine551 (S551) from salt-inducible kinase 3 (SIK3) markedly increases daily non-rapid eye movement sleep (NREMS) amount, accompanied with constitutively elevated NREMS delta power density–a measure of sleep intensity or quality. Multiple SLP/SIK3 isoforms are expressed in mouse brain neurons, however, their respective roles in sleep regulation remain to be elucidated. Here, we identified a new and most abundant short isoform of SLP/SIK3 and examined sleep phenotypes resulted from isoform-specific expression of SLP-short (S) and long (L) isoforms. Adeno-associated virus-mediated adult brain chimeric (ABC)-expression of SLP-S in neurons, but not in astrocytes, significantly and constitutively elevates NREMS delta power, whereas slightly increases NREMS amount. The ability of SLP-S to regulate sleep quantity/intensity is abrogated by kinase-inactivating mutations, suggesting that the sleep-promoting activity of SLP-S is dependent on its kinase activity. In Sik3S551A-L knock-in mice, isoform-specific expression of SIK3S551A-L (or SLP-L) significantly increases NREMS amount with a modest effect on NREMS delta power. ABC-expression of SLP-S complements the sleep phenotypes of heterozygous Sik3S551A-L mice by further increasing NREMS amount and NREMS delta power to levels of Sik3Slp or Sik3S551A mice. Taken together, these results indicate that both SLP-L and SLP-S isoforms contribute critically to the increases of sleep quantity and intensity in Sik3Slp or Sik3S551A mice. Statement of Significance Previous studies have identified SIK3 as a key sleep regulatory kinase, of which gain-of-function mutations markedly increase sleep quantity and intensity in Sleepy mice. Multiple SLEEPY isoforms are expressed in mouse brain neurons, but their respective contributions to the hypersomnia phenotypes of Sleepy mice remain unclear. Here, we identified a new short isoform of SLP/SIK3 and examined sleep phenotypes resulted from specific expression of SLEEPY-short or long isoform. Our results indicate that both long and short isoforms of SLEEPY kinase contribute critically to increases of sleep quantity and intensity in Sleepy mice. Future studies are needed to identify downstream substrates of SLEEPY kinase that mediate regulation of sleep quantity/intensity, which should facilitate development of new treatments for human sleep disorders.
Molecular and anatomical characterization of parabrachial neurons and their axonal projections

The parabrachial nucleus (PBN) is a major hub that receives sensory information from both internal and external environments. Specific populations of PBN neurons are involved in behaviors including food and water intake, pain sensation, breathing regulation, as well as learning and responding appropriately to threatening stimuli. However, it is unclear how many PBN neuron populations exist and how different behaviors may be encoded by unique signaling molecules or receptors. Here we provide a repository of data on the molecular identity, spatial location, and projection patterns on dozens of PBN neuron subclusters. Using single-cell RNA sequencing, we identified 21 subclusters of neurons in the PBN and neighboring regions. Multiplexed in situ hybridization showed many of these subclusters are localized to distinct PBN subregions. We also describe two major ascending pathways that innervate distinct brain regions by analyzing axonal projections in 21 Cre-driver lines of mice. These results are all publicly available for download and provide a foundation for further interrogation of PBN functions and connections.
Brightness illusions evoke pupil constriction and a visual cortex response in rats

Luminance causes the pupillary light response (PLR), a constriction of the pupil. Surprisingly, mere illusions of brightness evoke a pupil constriction in humans. Since brightness illusions depend on scene and context, this suggests that high-level visual processing has a top-down influence onto the brainstem neurons controlling the PLR. The influence of high-level vision on this brainstem-mediated reflex is thought to be restricted to primates that perform foveal fixation. Here, we report that the same brightness illusions that evoke a pupil constriction in humans also do so in rats (N = 14). This response occurred only for stimuli that matched the spectral sensitivity of the rat retina. We recorded 32-channel cortex-wide EEG and found that illusory brightness stimuli also evoked a larger primary visual cortex event-related potential. This neural response preceded pupil constriction by ∼335 msec. Thus, primary visual cortex may contribute to the PLR evoked by passive viewing of brightness illusions. Our results resolve whether this phenomenon is confined to primates by showing that it can also be found in rats.
Warmer temperatures favor slower-growing bacteria in natural marine communities

Earth’s life-sustaining oceans harbor diverse bacterial communities that display varying composition across time and space. While particular patterns of variation have been linked to a range of factors, unifying rules are lacking, preventing the prediction of future changes. Here, analyzing the distribution of fast- and slow-growing bacteria in ocean datasets spanning seasons, latitude, and depth, we show that higher seawater temperatures universally favor slower-growing taxa, in agreement with theoretical predictions. Our results explain why slow growers dominate at the ocean surface, during summer, and near the tropics, and provide a framework to understand how bacterial communities will change in a warmer world.
Fate Bias and Transcriptional Memory of human B cells

Lineage tracking offers a direct approach to study cell fate determination. In this work we combined single cell transcriptomics and lineage tracing to better understand fate-choice in human B cells. Using the antibody sequence to trace cell lineage during in vitro differentiation, we identified intrinsic proliferative and cell fate biases of B cell subtypes. Clonal analysis revealed that IgM memory B cells were more proliferative than any other B cell subtype, and that cells from the same clone had highly concordant fates. We found that transcriptional memory within clones varies across genes, with strongest persistence in genes related to cell fate determination. Similar persistent transcriptional programs were observed in human plasma cells from bone marrow, suggesting that these programs maintain long-term cell fate in vivo. These results show that cell-intrinsic fate bias influences human B cell differentiation and reveal molecular programs underpinning cell fate determination in B cells.
The spatial distribution and temporal trends of livestock damages caused by wolves in Europe

Wolf populations are recovering and expanding across Europe, causing conflicts with livestock owners. To mitigate these conflicts and reduce livestock damages, authorities spend considerable resources to compensate damages, support damage prevention measures, and manage wolf populations. However, the effectiveness of these measures remains largely unknown, especially at larger geographic scales. Here we compiled incident-based livestock damage data across 21 countries for the years 2018, 2019 and 2020, during which 39,262 wolf-caused incidents were reported from 470 administrative regions. We found substantial regional variation in all aspects of the data, including the primary target species, the density of damages, their seasonal distribution, and their temporal trend. More than half of the variation in damage densities across regions is explained by the area of extensively cultivated habitats occupied by wolves and namely natural grasslands and broad-leaved forests. Regional variation in husbandry practices and damage prevention, while difficult to quantify at a continental scale, appear important factors to further modulate these incidents. As illustrated with detailed data from Germany, for instance, the relationship between the number of wolf units and damages is diminishing over time, suggesting some adaptation of livestock owners and local authorities to their presence, for example by increasing prevention efforts. As we argue, temporal trends of damage incidents, which are robust to variation in data collection across regions, are thus informative about the local intensity of the wolf-human conflict. We estimated increasing trends for the majority of regions, reflecting the current expansion of wolves across the continent. Nonetheless, many of these increases were moderate and for more than one third of all regions, trends were negative despite growing wolf populations, thus indicating that wolf-livestock conflicts can be successfully mitigated with proper management.