Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature attention graph neural network for estimating brain age and identifying important neural connections in mouse models of genetic risk for Alzheimer’s disease

Alzheimer’s disease (AD) remains one of the most extensively researched neurodegenerative disorders due to its widespread prevalence and complex risk factors. Age is a crucial risk factor for AD, which can be estimated by the disparity between physiological age and estimated brain age. To model AD risk more effectively, integrating biological, genetic, and cognitive markers is essential. Here, we utilized mouse models expressing the major APOE human alleles and human nitric oxide synthase 2 to replicate genetic risk for AD and a humanized innate immune response. We estimated brain age employing a multivariate dataset that includes brain connectomes, APOE genotype, subject traits such as age and sex, and behavioral data. Our methodology used Feature Attention Graph Neural Networks (FAGNN) for integrating different data types. Behavioral data were processed with a 2D Convolutional Neural Network (CNN), subject traits with a 1D CNN, brain connectomes through a Graph Neural Network using quadrant attention module. The model yielded a mean absolute error for age prediction of 31.85 days, with a root mean squared error of 41.84 days, outperforming other, reduced models. In addition, FAGNN identified key brain connections involved in the aging process. The highest weights were assigned to the connections between cingulum and corpus callosum, striatum, hippocampus, thalamus, hypothalamus, cerebellum, and piriform cortex. Our study demonstrates the feasibility of predicting brain age in models of aging and genetic risk for AD. To verify the validity of our findings, we compared Fractional Anisotropy (FA) along the tracts of regions with the highest connectivity, the Return-to-Origin Probability (RTOP), Return-to-Plane Probability (RTPP), and Return-to-Axis Probability (RTAP), which showed significant differences between young, middle-aged, and old age groups. Younger mice exhibited higher FA, RTOP, RTAP, and RTPP compared to older groups in the selected connections, suggesting that degradation of white matter tracts plays a critical role in aging and for FAGNN’s selections. Our analysis suggests a potential neuroprotective role of APOE2, relative to APOE3 and APOE4, where APOE2 appears to mitigate age-related changes. Our findings highlighted a complex interplay of genetics and brain aging in the context of AD risk modeling.
Fine-tuning protein language models boosts predictions across diverse tasks

Prediction methods inputting embeddings from protein Language Models (pLMs) have reached or even surpassed state-of-the-art (SOTA) performance on many protein prediction tasks. In natural language processing (NLP) fine-tuning Language Models has become the de facto standard. In contrast, most pLM-based protein predictions do not back-propagate to the pLM. Here, we compared the fine-tuning of three SOTA pLMs (ESM2, ProtT5, Ankh) on eight different tasks. Two results stood out. Firstly, task-specific supervised fine-tuning almost always improved downstream predictions. Secondly, parameter-efficient fine-tuning could reach similar improvements consuming substantially fewer resources. Put simply: always fine-tune pLMs and you will mostly gain. To help you, we provided easy-to-use notebooks for parameter efficient fine-tuning of ProtT5 for per-protein (pooling) and per-residue prediction tasks at https://github.com/agemagician/ProtTrans/tree/master/Fine-Tuning.
A software tool for at-home measurement of sensorimotor adaptation

Sensorimotor adaptation is traditionally studied in well-controlled laboratory settings with specialized equipment. However, recent public health concerns such as the COVID-19 pandemic, as well as a desire to recruit a more diverse study population, have led the motor control community to consider at-home study designs. At-home motor control experiments are still rare because of the requirement to write software that can be easily used by anyone on any platform. To this end, we developed software that runs locally on a personal computer. The software provides audiovisual instructions and measures the ability of the subject to control the cursor in the context of visuomotor perturbations. We tested the software on a group of at-home participants and asked whether the adaptation principles inferred from in-lab measurements were reproducible in the at-home setting. For example, we manipulated the perturbations to test whether there were changes in adaptation rates (savings and interference), whether adaptation was associated with multiple timescales of memory (spontaneous recovery), and whether we could selectively suppress subconscious learning (delayed feedback, perturbation variability) or explicit strategies (limited reaction time). We found remarkable similarity between in-lab and at-home behaviors across these experimental conditions. Thus, we developed a software tool that can be used by research teams with little or no programming experience to study mechanisms of adaptation in an at-home setting. Significance Sensorimotor learning is traditionally studied in the laboratory, but recent public health emergencies have caused the community to consider at-home data collection. To accelerate this effort, we implemented a software tool that remotely tracks motor learning. Compared with previous remote data collection strategies, our software (1) generates experiments of arbitrary length that (2) run locally on a participant’s laptop which (3) can be modified without any programming expertise in the research laboratory. Here we show a close correspondence between behaviors captured by our tool and those observed in laboratory environments including savings, interference, spontaneous recovery, and variations in implicit and explicit learning due to changes in perturbation variance, reaction time constraints, and feedback delay. Our software and its corresponding manuals are available here: https://osf.io/e8b63/.
Convergent evolution of monocyte differentiation in adult skin instructs Langerhans cell identity

Langerhans cells (LCs) maintain tissue and immunological homeostasis at the epidermal barrier site. They are unique among phagocytes in functioning both as embryo-derived, tissue-resident macrophages that influence skin innervation and repair, and as migrating professional antigen presenting cells, a capability classically assigned to dendritic cells (DCs). Here we report the mechanisms that determine this dual identity. Using ablation of embryo-derived LCs in murine adult skin and tracked differentiation of incoming monocyte-derived replacements, we reveal intrinsic intra-epidermal heterogeneity. We demonstrate that monocyte-dendritic cell progenitor (MDP)-derived monocytes are selected for survival in the skin environment. Within the epidermis, the hair follicle niche subsequently provides an initial site of LC commitment, likely via Notch signaling, prior to metabolic adaptation and survival of differentiated monocyte-derived LCs. In human skin, we show that embryo-derived (e)LCs in newborns retain transcriptional evidence of their macrophage origin, but this is superseded by distinct DC-like immune modules after post-natal expansion of eLCs. Thus, intrinsic and extrinsic adaptations to adult skin niches replicate conditioning of eLC at birth, permitting repair of the unique LC network.
Modulation of cell differentiation and growth dynamics underlie the shift from bud protection to light capture in cauline leaves

Plant organs have evolved into diverse shapes for specialized functions despite emerging as simple protrusions at the shoot apex. Cauline leaves serve both as photosynthetic organs and protective structures for emerging floral buds. However, the growth patterns underlying this dual function remain unknown. Here, we investigate the developmental dynamics shaping cauline leaves underlying their functional diversification from other laminar organs. We show that cauline leaves display a significant delay in overall elongation compared to rosette leaves. Using live imaging, we reveal that their functional divergence hinges on early modulation of the timing of cell differentiation and cellular growth rates. In contrast to rosette leaves and sepals, cell differentiation is delayed in cauline leaves, fostering extended proliferation, prolonged morphogenetic activity, and growth redistribution within the organ. Notably, cauline leaf growth is transiently suppressed during the early stages, keeping the leaf small and unfolded during the initiation of the first flowers. Our findings highlight the unique developmental timing of cauline leaves, underlying their shift from an early protective role to a later photosynthetic function. ONE SENTENCE SUMMARY The dual function of the cauline leaf in protection and light capture is achieved during development through a delay of cell differentiation, growth redistribution, and transient growth decrease.
Characterization of bovine vaginal microbiota and its relationship with host fertility, health, and production

Background Because of its potential influence on the host’s phenotype, increasing attention is paid to organ-specific microbiota in several animal species, including cattle. However, ecosystems other than those related to the digestive tract remain largely understudied. In particular, little is known about the vaginal microbiota of ruminants despite the importance of the reproductive functions of cows in a livestock context, where fertility disorders represent one of the primary reasons for culling. Results In the present study, we aimed at better characterizing the vaginal microbiota of dairy cows through 16S rRNA sequencing, using a large cohort of Holstein cows from Northern France. Our results allowed to define a core microbiota of the dairy cows’ vagina, and highlighted that 90% of the sequences belonged to the Firmicutes, the Proteobacteria, and the Bacteroidetes phyla. The core microbiota was composed of four phyla, 16 families, 14 genera and only one amplicon sequence variant (ASV), supporting the idea of the high diversity of vaginal microbiota within the studied population. This variability was partly explained by various environmental factors such as the herd, the sampling season, the lactation rank and the lactation stage. In addition, we investigated potential associations between the diversity and the composition of the vaginal microbiota and several health-, performance-, and fertility-related phenotypes. Our analyses highlighted significant associations between the α and β- diversities and several traits including the first insemination outcome, the productive longevity, and the culling. Besides, relevant phenotypes were correlated with the abundance of several genera, some of which, such as Leptotrichia, Streptobacillus, Methylobacterium-Methylorubrum, or Negativibacillus, were linked to multiple traits. Conclusion Considering the large number of samples, which were collected in commercial farms, and the diversity of the phenotypes considered, this study represents a first step towards a better understanding of the close relationship between the vaginal and the dairy cow’s phenotypes.
A generative model of the hippocampal formation trained with theta driven local learning rules

Advances in generative models have recently revolutionised machine learning. Meanwhile, in neuroscience, generative models have long been thought fundamental to animal intelligence. Understanding the biological mechanisms that support these processes promises to shed light on the relationship between biological and artificial intelligence. In animals, the hippocampal formation is thought to learn and use a generative model to support its role in spatial and non-spatial memory. Here we introduce a biologically plausible model of the hippocampal formation tantamount to a Helmholtz machine that we apply to a temporal stream of inputs. A novel component of our model is that fast theta-band oscillations (5-10 Hz) gate the direction of information flow throughout the network, training it akin to a high-frequency wake-sleep algorithm. Our model accurately infers the latent state of high-dimensional sensory environments and generates realistic sensory predictions. Furthermore, it can learn to path integrate by developing a ring attractor connectivity structure matching previous theoretical proposals and flexibly transfer this structure between environments. Whereas many models trade-off biological plausibility with generality, our model captures a variety of hippocampal cognitive functions under one biologically plausible local learning rule.
Characterization of carotenoid-producing Muricauda sp. strains isolated from the reef-building coral Galaxea fascicularis and subtropical seawater

Bacterial symbionts in corals and coral-associated zooxanthellae are attracting increasing attention as potential probiotics. Some members of the family Flavobacteriaceae are zooxanthellae-associated bacteria, which are known to protect zooxanthellae from stresses such as heat and light by producing carotenoids that reduce reactive oxygen species production. This study characterized two Flavobacteriaceae bacteria, Muricauda sp. strains ORYM1 (NBRC115792) and ORYM2 (NBRC115793), isolated from the reef-building coral Galaxea fascicularis and its surrounding seawater in Okinawa, Japan, respectively. The Muricauda sp. strain ORYM2 was isolated from subtropical seawater, and carotenoid production was assessed using ORYM2 as well as ORYM1, which was previously isolated from G. fascicularis. De novo genome sequencing revealed that both strains contain complete sets of zeaxanthin biosynthesis genes, similar to those found in other Muricauda spp. Thin-layer chromatography and high-performance liquid chromatography analyses demonstrated that ORYM1 and ORYM2 produce several carotenoids. The bacterial strains and carotenoids identified in this study provide insights into the biological roles of zooxanthellae-associated bacteria in protecting zooxanthellae and reef-building corals from environmental stresses. Statements and declarations Competing interests: The authors declare no competing interests.
Sperm quality and function deteriorate in old males of the naturally short-lived turquoise killifish

Most of the variation in male reproductive aging observed in nature may be explained by different life-history strategies, which reflect trade-offs between growth, reproduction and survival. The disposable soma theory predicts that the energy allocated in reproductive functions is traded-off with soma maintenance. In particular, males are expected to maximise the investment in reproduction at the expense of soma maintenance, due to the strong selection for reproduction. Therefore, according to the disposable soma theory, species showing rapid somatic aging and high actuarial senescence are expected to have evolved high allocation in reproduction, with limited if any reproductive aging. We tested this prediction in turquoise killifish (Nothobranchius furzeri), a vertebrate of extremely short natural lifespan. We analysed age-related changes in sperm traits, the proportion of fertilized eggs, as well as embryo survival. Surprisingly, we found that, similar to their extensive actuarial senescence, turquoise killifish males also undergo spontaneous reproductive aging, consisting in the age-dependent decline of sperm quality, decreased proportion of fertilized eggs and lower embryo survival. Our results suggest that male reproductive aging may result from processes that are not necessarily dependent on the adaptive resource allocation between reproduction and somatic maintenance.
Molecular definition of the BAK:VDAC2 interaction as a target to manipulate apoptosis

BAK and BAX execute intrinsic apoptosis by permeabilising the mitochondrial outer membrane. Their activity is regulated through interactions with pro-survival BCL-2 family proteins and with non-BCL-2 proteins including the mitochondrial porin VDAC2. VDAC2 is important for bringing both BAK and BAX to mitochondria where they execute their apoptotic function. Despite this important function in apoptosis, whilst interactions with pro-survival family members are well characterised and have culminated in the development of drugs that target these interfaces to induce cancer cell apoptosis, the interaction between BAK and VDAC2 remains largely undefined. Deep scanning mutagenesis coupled with cysteine linkage identified key residues in the interaction between BAK and VDAC2. Obstructive labelling of specific residues in the BH3 domain or hydrophobic groove of BAK disrupted this interaction. Conversely, mutating specific residues in a cytosol-exposed region of VDAC2 stabilised the interaction with BAK, and inhibited BAK apoptotic activity. Thus, this VDAC2–BAK interaction site can potentially be targeted to either inhibit BAK-mediated apoptosis in scenarios where excessive apoptosis contributes to disease, or to promote BAK-mediated apoptosis for cancer therapy.
‘Are you even listening?’ - EEG-based detection of absolute auditory attention to natural speech with application to neuro-steered hearing devices

In this study, we use electroencephalography (EEG) recordings to perform absolute auditory attention detection (aAAD), i.e., determine whether a subject is actively listening to a presented speech stimulus or not. More precisely, we aim to discriminate between an active listening condition, and a distractor condition where subjects passively listen to the speech stimulus while performing another cognitive task. To this end, we re-use an existing EEG dataset where the subjects watch a silent movie as a distractor condition, and introduce a new EEG dataset with two other distractor conditions (silently reading a text and performing arithmetic exercises). We focus on two EEG features, namely neural envelope tracking (NET) and spectral entropy (SE). We find significantly higher NET and lower SE in the active listening condition compared to the distractor conditions, which for the SE is the reverse of what was previously found for an active listening versus passive listening condition (without any distractors). In addition, aAAD is used in the context of a selective auditory attention decoding (sAAD) task, where the goal is to decode to which of two competing speakers the subject is attending, which is a core task in the context of so-called neuro-steered hearing devices. We show that evaluating sAAD performance only on segments of active listening improves sAAD performance when detecting these active listening segments as having higher NET, whereas the reverse trend is observed when detecting these segments as having lower SE. We conclude that NET is a more reliable metric for aAAD as it is consistently higher for the active listening condition, whereas the relation of the SE between the active listening and passive listening conditions seems to depend on the nature of the distractor task. Consequently, NET shows the most promise for aAAD and to detect auditory inattentive segments in neuro-steered hearing devices.
Personalized Pangenome References

Pangenomes, by including genetic diversity, should reduce reference bias by better representing new samples compared to them. Yet when comparing a new sample to a pangenome, variants in the pangenome that are not part of the sample can be misleading, for example, causing false read mappings. These irrelevant variants are generally rarer in terms of allele frequency, and have previously been dealt with using allele frequency filters. However, this is a blunt heuristic that both fails to remove some irrelevant variants and removes many relevant variants. We propose a new approach, inspired by local ancestry inference methods, that imputes a personalized pangenome subgraph based on sampling local haplotypes according to k-mer counts in the reads. Our approach is tailored for the Giraffe short read aligner, as the indexes it needs for read mapping can be built quickly. We compare the accuracy of our approach to state-of-the-art methods using graphs from the Human Pangenome Reference Consortium. The resulting personalized pangenome pipelines provide faster pangenome read mapping than comparable pipelines that use a linear reference, reduce small variant genotyping errors by 4x relative to the Genome Analysis Toolkit (GATK) best-practice pipeline, and for the first time make short-read structural variant genotyping competitive with long-read discovery methods.
Stable Cortical Body Maps Before and After Arm Amputation

Neuroscientists have long debated the adult brain’s capacity to reorganize itself in response to injury. A driving model for studying plasticity has been limb amputation. For decades, it was believed that amputation triggers large-scale reorganization of cortical body resources. However, these studies have relied on cross-sectional observations post-amputation, without directly tracking neural changes. Here, we longitudinally followed adult patients with planned arm amputations and measured hand and face representations, before and after amputation. By interrogating the representational structure elicited from movements of the hand (pre-amputation) and phantom hand (post-amputation), we demonstrate that hand representation is unaltered. Further, we observed no evidence for lower face (lip) reorganization into the deprived hand region. Collectively, our findings provide direct and decisive evidence that amputation does not trigger large-scale cortical reorganization.
Role of diffusion and reaction of the constituents in spreading of histone modification marks

Cells switch genes ON or OFF by altering the state of chromatin via histone modifications at specific regulatory locations along the chromatin polymer. These gene regulation processes are carried out by a network of reactions in which the histone marks spread to neighboring regions with the help of enzymes. In the literature, this spreading has been studied as a purely kinetic, non-diffusive process considering the interactions between neighboring nucleosomes. In this work, we go beyond this framework and study the spreading of modifications using a reaction-diffusion (RD) model accounting for the diffusion of the constituents. We quantitatively segregate the modification profiles generated from kinetic and RD models. The diffusion and degradation of enzymes set a natural length scale for limiting the domain size of modification spreading, and the resulting enzyme limitation is inherent in our model. We also demonstrate the emergence of confined modification domains without the explicit requirement of a nucleation site. We explore polymer compaction effects on spreading and show that single-cell domains may differ from averaged profiles. We find that the modification profiles from our model are comparable with existing H3K9me3 data of S. pombe.