Miracle-dz/UniFAR-FTUs huggingface dataset:
Perfusion Quantification in the Human Brain Using DSC MRI – Simulations and Validations at 3T

Gadolinium (Gd) and deoxyhemoglobin (dOHb) are paramagnetic contrast agents capable of inducing changes in T2*-weighted MRI signal, utilized in dynamic susceptibility contrast (DSC) MRI. With multiple contrast agents and analysis choices, there are a variety of questions as to its capability to accurately quantify perfusion values. To address these questions, we developed a novel signal model for DSC MRI that incorporates signal contributions from intravascular and extravascular water proton spins at 3T for arterial, venous, and cerebral tissue voxels. This framework allowed us to model the MRI signal in response to changes in Gd and dOHb concentrations, and the effects that various experimental and tissue parameters have on perfusion quantification. We compared the predictions of the numerical simulations with those obtained from experimental data at 3T on six healthy human subjects using Gd and dOHb boluses as contrast agents. Using standard DSC analysis, we identified perfusion quantification dependencies in the experimental results that were in close agreement with the simulations. We found that a reduced baseline oxygen saturation (base-SaO2), greater susceptibility of applied contrast agent (Gd vs dOHb), and larger magnitude of the hypoxic drop (ΔSaO2) reduces overestimation of the cerebral blood volume (rCBV) and flow (rCBF). Furthermore, shortening the bolus duration increases the accuracy and reduces the calculated values of mean transit time (MTT). This study demonstrates that changes in Gd and dOHb can be described by the same unifying theoretical framework, as validated by the experimental results. Based on our work, we suggest practices in DSC MRI that increase accuracy and reduce inter- and intra-subject variability. In uncovering a wide array of quantification dependencies, we argue that caution must be exercised when comparing perfusion values obtained from a standard DSC MRI analysis when employing different experimental paradigms.
The mutational landscape of single neurons and oligodendrocytes reveals evidence of inflammation-associated DNA damage in multiple sclerosis

Neuroinflammation has been linked to DNA damage in multiple sclerosis (MS), but its impact on neural cell genomes at nucleotide resolution is unknown. To address this question, we performed single nucleus whole genome sequencing to determine the landscape of somatic mutation in 172 neurons and oligodendrocytes (OLs) extracted from post-mortem brain tissue from 5 MS cases and three controls. We identified two cases with a significant excess of somatic single nucleotide variants (sSNV) in neurons and OLs from MS inflammatory demyelinated lesions. For a case with primary progressive MS, this translated to a 68% increase in sSNV frequency and 32-year equivalent increase in biological age of lesion-resident cells. Mutational signature analysis conducted on all cells revealed that defective DNA repair and transcription-associated DNA damage are important mutagenic mechanism in both neurons and OLs in MS. Our findings provide the first evidence that inflammation in the brains of people with MS is associated with DNA damage, which may have implications for other neurodegenerative diseases and future drug development.
Normative decision rules in changing environments

Models based on normative principles have played a major role in our understanding of how the brain forms decisions. However, these models have typically been derived for simple, stable environments, and their relevance to decisions under more naturalistic, dynamic conditions is unclear. We previously derived a normative decision model in which evidence accumulation is adapted to environmental dynamics (Glaze et al., 2015), but the evolution of commitment rules (e.g., thresholds on the accumulated evidence) under such dynamic conditions is not fully understood. Here we derive a normative model for decisions based on changing evidence or reward. In these cases, performance (reward rate) is maximized using adaptive decision thresholds that best account for diverse environmental changes, in contrast to predictions of many previous decision models. These adaptive thresholds exhibit several distinct temporal motifs that depend on the specific, predicted and experienced changes in task conditions. These adaptive decision strategies perform robustly even when implemented imperfectly (noisily) and can account for observed response times on a task with time-varying evidence better than commonly used constant-threshold or urgency-gating models. These results further link normative and neural decision-making while expanding our view of both as dynamic, adaptive processes that update and use expectations to govern both deliberation and commitment.
A translational MRI approach to validate acute axonal damage detection

Axonal degeneration is a central pathological feature of neurodegenerative pathologies and is closely associated with irreversible clinical disability. Current noninvasive methods to detect axonal damage in vivo are limited in their specificity, clinical applicability, and lack of proper validation. We aimed to validate an MRI framework based on multicompartment modeling of the diffusion-weighted signal (AxCaliber) in rats in the presence of axonal pathology, achieved through injection of a neurotoxin damaging the neuronal terminal of axons. We then applied the same MRI protocol to map axonal integrity in the whole brain of multiple sclerosis relapsing-remitting patients and age-matched healthy controls, a pathology associated with a neurodegenerative component. AxCaliber is sensitive to microstructural axonal damage in rats, as demonstrated by a significant increase in the mean axonal caliber along the target tract, which correlated with the neurotoxin neurofilament staining. In humans, we uncovered a diffuse increase in mean axonal caliber in multiple sclerosis lesions and, importantly, in most areas of the normal-appearing white matter. Our results demonstrate that axonal diameter mapping is a sensitive and specific imaging biomarker able to link noninvasive imaging contrasts with the underlying biological substrate, supporting the key role of generalized axonal damage useful in diseases such as multiple sclerosis.
Chemical screen of Arabidopsis zygote and proteomics in tobacco BY-2 cells identify general plant cell division inhibitors

Cell division is essential for growth and development and involves events such as spindle assembly, chromosome separation, and cell plate formation. In plants, the tools used to control these events at the desired time are still poor because the genetic approach is ineffective owing to a high redundancy and lethality, as well as harmful side effects. Accordingly, we screened cell division-affecting compounds, with a focus on Arabidopsis thaliana zygotes, which individually develop in maternal ovules; the cell division was reliably traceable without time-lapse observations. We then identified the target events of the identified compounds using tobacco BY-2 cells for live-cell imaging and proteomics. As a result, we isolated two compounds, PD-180970 and PP2. PD-180970 disrupts microtubule (MT) organization and, thus, nuclear separation, presumably by inhibiting MT-associated proteins (MAP70). PP2 affected class II Kinesin-12 localization at the phragmoplast emerging site and impaired cytokinesis. Moreover, neither chemical caused irreversible damage to viability but they were effective in multiple plant species such as cucumber (Cucumis sativus) and moss (Physcomitrium patens). We propose that the combination of chemical screening based on Arabidopsis zygotes and target event specification focusing on tobacco BY-2 cells can be used to effectively identify novel tools and transiently control specific cell division events that are conserved in diverse plant species.
Molecular Determinants of Tissue Specificity of Flavivirus Nonstructural Protein 1 Interaction with Endothelial Cells

Flavivirus NS1 is secreted into the bloodstream from infected cells during a viral infection. Dengue virus NS1 contributes to severe dengue pathology such as endothelial dysfunction and vascular leak independently of the virus. ABSTRACT Members of the mosquito-borne flavivirus genus such as dengue (DENV), West Nile (WNV), and Zika (ZIKV) viruses cause distinct diseases and affect different tissues. We previously found that the secreted flaviviral nonstructural protein 1 (NS1) interacts with endothelial cells and disrupts endothelial barrier function in a tissue-specific manner consistent with the disease tropism of the respective viruses. However, the underlying molecular mechanism of this tissue-specific NS1-endothelial cell interaction is not well understood. To elucidate the distinct role(s) that the wing and β-ladder domains of NS1 play in NS1 interactions with endothelial cells, we constructed flavivirus NS1 chimeras that exchanged the wing and β-ladder domains in a pairwise manner between DENV, WNV, and ZIKV NS1. We found that both the NS1 wing and β-ladder domains conferred NS1 tissue-specific endothelial dysfunction, with the wing conferring cell binding and the β-ladder involved in inducing endothelial hyperpermeability as measured by transendothelial electrical resistance. To narrow down the amino acids dictating cell binding specificity, we utilized the DENV-WNV NS1 chimera and identified residues 91 to 93 (GDI) of DENV NS1 as a molecular motif determining binding specificity. Further, using an in vivo mouse model of localized leak, we found that the GDI motif of the wing domain was essential for triggering DENV NS1-induced vascular leak in mouse dermis. Taken together, we identify molecular determinants of flavivirus NS1 that confer NS1 binding and vascular leak and highlight the importance of the NS1 wing domain for flavivirus pathogenesis. IMPORTANCE Flavivirus NS1 is secreted into the bloodstream from infected cells during a viral infection. Dengue virus NS1 contributes to severe dengue pathology such as endothelial dysfunction and vascular leak independently of the virus. We have shown that multiple flavivirus NS1 proteins result in endothelial dysfunction in a tissue-specific manner consistent with their respective viral tropism. Here, we aimed to identify the molecular determinants that make some, but not other, flavivirus NS1 proteins bind to select endothelial cells in vitro and cause vascular leak in a mouse model. We identified the wing domain of NS1 as a primary determinant conferring differential endothelial dysfunction and vascular leak and narrowed the contributing amino acid residues to a three-residue motif within the wing domain. The insights from this study pave the way for future studies on the effects of flavivirus NS1 on viral dissemination and pathogenesis and offer potential new avenues for antiviral therapies.
Dispersal between interconnected patches can reduce the total population size

Human activities increasingly result in a fragmentation of natural ecosystems. However, the ecological consequences of fragmentation remain poorly understood. While some studies report that fragmentation may enhance population growth, others suggest the opposite pattern. Here we investigated how habitat connectivity affects the population size of a single species when habitat patches differ in quality. We combined dispersal experiments, in which bacterial populations of Escherichia coli were repeatedly transferred between two qualitatively different environments, with a process-based mathematical model. Both experiments and model consistently revealed that increased dispersal between patches reduced the total population size, thus demonstrating a detrimental effect of habitat connectivity on population size. This observation could be explained with a net loss of individuals upon migration from a productive to an overcrowded patch. Our findings suggest that conservation measures, which promote movement between fragmented habitats, such as dispersal corridors or stepping stones, are potentially detrimental for some species.
Local field potentials and single unit dynamics in motor cortex of unconstrained macaques during different behavioral states

Different sleep states have been shown to be vital for a variety of brain function, including learning, memory, and skill consolidation. However, our understanding of neural dynamics during sleep and the role of prominent LFP frequency bands remain incomplete. To discern changes between different behavioral states we collected multichannel LFP and spike data in primary motor cortex of unconstrained macaques for up to 24 hours using the Neurochip3. Each 8 second bin of time was classified into awake and moving (Move), awake and at rest (Rest), REM sleep (REM), or non-REM sleep (NREM) by using dimensionality reduction and clustering on the average spectral density and the acceleration of the head. LFP power showed high delta during NREM, high theta during REM, and high beta when the animal was awake. Cross-frequency phase-amplitude coupling typically showed higher coupling for deeper sleep between all pairs of frequency bands except for high delta-high gamma and theta-high gamma coupling during Move, and high theta-beta coupling during REM. Sorted single units showed decreased firing rate with deeper sleep, though with higher “bursty” patterns during NREM compared to other states. Spike-LFP synchrony showed high delta synchrony during Move, and higher coupling with all other frequency bands during NREM. These results altogether are consistent with previous findings showing reactivation of cortical circuitry activated during the day, which may be driven by the delta band LFP.
Partial refuges from biological control due to intraspecific variation in protective host traits: a case study with the egg parasitoid Trissolcus japonicus

Predicting how much of a host or prey population may be attacked by their natural enemies is fundamental to several subfields of applied ecology, particularly biological control of pest organisms. Hosts or prey can occupy refuges from natural enemy attack, but habitat or ecological refuges are challenging or impossible to predict in a laboratory setting – which is often where efficacy and specificity testing of candidate biological control agents is done. Here we explore how intraspecific variation in continuous traits that confers some protection from natural enemy attack – even after the natural enemy has encountered the prey – could provide partial refuges. The size of these trait-based refuges should depend on the relationship between trait values and host/prey susceptibility to natural enemy attack, and on how common different trait values are within a host/prey population. These can be readily estimated in laboratory testing of natural enemy impact on target or non-target prey or hosts as long as sufficient host material is available. We provide a general framework for how intraspecific variation in protective host traits could be integrated into biological control research, specifically with reference to non-target testing as part of classical biological control programs. As a case study, we exposed different host clutch sizes of target (pest) and non-target (native species) stink bug (Hemiptera: Pentatomidae) species to a well-studied exotic biocontrol agent, the egg parasitoid Trissolcus japonicus (Hymenoptera: Scelionidae). Although we observed several behavioural and reproductive responses to variation in host egg mass size by T. japonicus, they did not translate to increases in predicted refuge size (proportion host survival) large enough to change the conclusions of non-target testing. We encourage researchers to investigate intraspecific variation in a wider variety of protective host and prey traits and their consequences for refuge size.
Touch receptor end-organ innervation and function require sensory neuron expression of the transcription factor Meis2

Touch sensation is primarily encoded by mechanoreceptors, called Low-Threshold Mechanoreceptors (LTMRs), with their cell bodies in the Dorsal Root Ganglia (DRG). Because of their great diversity in terms of molecular signature, terminal endings morphology and electrophysiological properties, mirroring the complexity of tactile experience, LTMRs are a model of choice to study the molecular cues differentially controlling neuronal diversification. While the transcriptional codes that define different LTMR subtypes have been extensively studied, the molecular players that participate in their late maturation and in particular in the striking diversity of their end-organ morphological specialization are largely unknown. Here we identified the TALE homeodomain transcription factor Meis2 as a key regulator of LTMRs target-field innervation. Meis2 is specifically expressed in cutaneous LTMRs and its expression depends on target-derived signals. While LTMRs lacking Meis2 survived and are normally specified, their end-organ innervations, electrophysiological properties and transcriptome are differentially and markedly affected, resulting in impaired sensory-evoked behavioral responses. These data establish Meis2 as a major transcriptional regulator controlling the orderly formation of sensory neurons innervating peripheral end-organs required for light touch.
On learning sparse vectors from mixture of responses

In this paper, we address two learning problems. Suppose a family of (cid:96) unknown sparse vectors is ﬁxed, where each vector has at most k non-zero elements. In the ﬁrst problem, we concentrate on robust learning the supports of all vectors from the family using a sequence of noisy responses. Each response to a query vector shows the sign of the inner product between a randomly chosen vector from the family and the query vector. In the second problem, we aim at designing queries such that all sparse vectors from the family can be approximately reconstructed based on the error-free responses. This learning model was introduced in the work of Gandikota et al., 2020, and these problems can be seen as generalizations of support recovery and approximate recovery problems, well-studied under the framework of 1-bit compressed sensing. As the main contribution of the paper, we prove the existence of learning algorithms for the ﬁrst problem which work without any assumptions. Under a mild structural assumption on the unknown vectors, we also show the existence of learning algorithms for the second problem and rigorously analyze their query complexity.
When is Unsupervised Disentanglement Possible?

A common assumption in many domains is that high dimensional data are a smooth nonlinear function of a small number of independent factors. When is it possible to recover the factors from unlabeled data? In the context of deep models this problem is called “disentanglement” and was recently shown to be impossible without additional strong assumptions [17, 19]. In this paper, we show that the assumption of local isometry together with non-Gaussianity of the factors, is sufﬁcient to provably recover disentangled representations from data. We leverage recent advances in deep generative models to construct manifolds of highly realistic images for which the ground truth latent representation is known, and test whether modern and classical methods succeed in recovering the latent factors. For many different manifolds, we ﬁnd that a spectral method that explicitly optimizes local isometry and non-Gaussianity consistently ﬁnds the correct latent factors, while baseline deep autoencoders do not. We propose how to encourage deep autoencoders to ﬁnd encodings that satisfy local isometry and show that this helps them discover disentangled representations. Overall, our results suggest that in some realistic settings, unsupervised disentanglement is provably possible, without any domain-speciﬁc assumptions. representation found by HLLE+ICA approximately satisﬁes local isometry while the encoding of the baseline autoencoder does not (bottom). In this paper we show that the assumptions of local isometry and non-Gaussianity are sufﬁcient to provably recover disentangled representations.
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization

In practical instances of nonconvex matrix factorization, the rank of the true solution r ⋆ is often unknown, so the rank r of the model can be overspecified as r > r ⋆ . This over-parameterized regime of matrix factorization significantly slows down the convergence of local search algorithms, from a linear rate with r = r ⋆ to a sublinear rate when r > r ⋆ . We propose an inexpensive preconditioner for the matrix sensing variant of nonconvex matrix factorization that restores the convergence rate of gradient descent back to linear, even in the over-parameterized case, while also making it agnostic to possible ill-conditioning in the ground truth. Classical gradient descent in a neighborhood of the solution slows down due to the need for the model matrix factor to become singular. Our key result is that this singularity can be corrected by ℓ 2 regularization with a specific range of values for the damping parameter. In fact, a good damping parameter can be inexpensively estimated from the current iterate. The resulting algorithm, which we call preconditioned gradient descent or PrecGD, is stable under noise, and converges linearly to an information theoretically optimal error bound. Our numerical experiments find that PrecGD works equally well in restoring the linear convergence of other variants of nonconvex matrix factorization in the over-parameterized regime.
Genome-Wide Identification of Wild Soybean Mitochondrial Calcium Uniporter Family Genes and Their Responses to Cold and Carbonate Alkaline Stresses

The mitochondrial calcium uniporter (MCU), as an important component of the Ca2+ channel uniporter complex, plays a regulatory role in intracellular Ca2+ signal transduction. However, only a few studies to date have investigated plant MCU genes. In this study, we identified the MCU family genes in wild soybean and investigated their expression under cold and carbonate alkaline stresses. Eleven Glycine soja MCU genes (GsMCUs) were identified and clustered into two subgroups (subgroups I and II), and subgroup II could be further divided into two branches (MCU5 and MCU6). A total of 21 pairs of GsMCUs were characterized as duplicated genes, and displayed a similar exon-intron architecture. All GsMCU proteins contained one conserved MCU domain, within which two transmembrane domains were found. An analysis of the conserved motifs further supported that the GsMCUs showed high conservation in protein sequence and structure. Moreover, we found that all GsMCUs were expressed ubiquitously in different tissues and organs, and GsMCUs from the same subgroup displayed varied tissue expression profiles. In addition, based on RNA-seq and qRT-PCR assays, six and nine GsMCUs were differentially expressed under cold and carbonate alkaline stress, respectively. Promoter analysis also uncovered the existence of two canonical cold-related cis-acting elements, LTR and DRE/CRT, as well as stress-related phytohormone-responsive elements. Our results provide valuable information about the MCU family in soybean responses to cold and carbonate alkaline stress, which will be helpful in further characterizing their biological roles in response to abiotic stress.