Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceptual Image Compression with Block-Level Just Noticeable Difference Prediction

A block-level perceptual image compression framework is proposed in this work, including a block-level just noticeable difference (JND) prediction model and a preprocessing scheme. Specifically speaking, block-level JND values are first deduced by utilizing the OTSU method based on the variation of block-level structural similarity values between two adjacent picture-level JND values in the MCL-JCI dataset. After the JND value for each image block is generated, a convolutional neural network–based prediction model is designed to forecast block-level JND values for a given target image. Then, a preprocessing scheme is devised to modify the discrete cosine transform coefficients during JPEG compression on the basis of the distribution of block-level JND values of the target test image. Finally, the test image is compressed by the max JND value across all of its image blocks in the light of the initial quality factor setting. The experimental results demonstrate that the proposed block-level perceptual image compression method is able to achieve 16.75% bit saving as compared to the state-of-the-art method with similar subjective quality. The project page can be found at https://mic.tongji. edu.cn/43/3f/c9778a148287/page.htm.
Quantitative coupling of cell volume and membrane tension during osmotic shocks

During osmotic changes of their environment, cells actively regulate their volume and plasma membrane tension that can passively change through osmosis. How tension and volume are coupled during osmotic adaptation remains unknown, as a quantitative characterization is lacking. Here, we performed dynamic membrane tension and cell volume measurements during osmotic shocks. During the first few seconds following the shock, cell volume varied to equilibrate osmotic pressures inside and outside the cell, and membrane tension dynamically followed these changes. A theoretical model based on the passive, reversible unfolding of the membrane as it detaches from the actin cortex during volume increase, quantitatively describes our data. After the initial response, tension and volume recovered from hypoosmotic shocks but not from hyperosmotic shocks. During these asymmetric recoveries, tension and volume remained coupled. Pharmacological disruption of the cytoskeleton and functional inhibition of ion channels and mTOR all affected tension and volume responses, proving that a passive mechanism is necessary and critical for the cell to adapt fast. The coupling between them was, nonetheless, maintained for a few exceptions suggesting that volume and tension regulations are independent from the regulation of their coupling.
Modeling post-logging height growth of black spruce forests by combining airborne LiDAR and historical forestry maps in eastern Canadian boreal forest

Increase in forest disturbance due to land use as well as climate change has led to an expansion of young forests worldwide, which affects global carbon dynamics and forest management. In this study, we present a novel method that combines a single airborne LiDAR acquisition and historical harvesting maps to model height growth of post-logged black spruce-dominated forests in a 1700 km2 eastern Canadian boreal landscape. We developed a random forest model where forest height is a function of stand age, combined with environmental variables. Our results highlight the strong predictive power of this model: least-square regression between predicted and observed height of our validation dataset was very close to the 1:1 relation and strongly supported by validation metrics (R2 = 0.75; relative RMSE = 19%). Moreover, our findings indicated an ecological gradient responsible for differences in height growth at the landscape scale, with better growth rates on mesic slopes compared to badly drained soils on flat lands. With the increased availability of LiDAR data, this method is promising since it can be applied to forests across the globe that are affected by stand-replacing disturbances.
Brain connectivity meets reservoir computing

The connectivity of Artificial Neural Networks (ANNs) is different from the one observed in Biological Neural Networks (BNNs). Can the wiring of actual brains help improve ANNs architectures? Can we learn from ANNs about what network features support computation in the brain when solving a task? ANNs’ architectures are carefully engineered and have crucial importance in many recent performance improvements. On the other hand, BNNs’ exhibit complex emergent connectivity patterns. At the individual level, BNNs connectivity results from brain development and plasticity processes, while at the species level, adaptive reconfigurations during evolution also play a major role shaping connectivity. Ubiquitous features of brain connectivity have been identified in recent years, but their role in the brain’s ability to perform concrete computations remains poorly understood. Computational neuroscience studies reveal the influence of specific brain connectivity features only on abstract dynamical properties, although the implications of real brain networks topologies on machine learning or cognitive tasks have been barely explored. Here we present a cross-species study with a hybrid approach integrating real brain connectomes and Bio-Echo State Networks, which we use to solve concrete memory tasks, allowing us to probe the potential computational implications of real brain connectivity patterns on task solving. We find results consistent across species and tasks, showing that biologically inspired networks perform as well as classical echo state networks, provided a minimum level of randomness and diversity of connections is allowed. We also present a framework, bio2art, to map and scale up real connectomes that can be integrated into recurrent ANNs. This approach also allows us to show the crucial importance of the diversity of interareal connectivity patterns, stressing the importance of stochastic processes determining neural networks connectivity in general.
Social prediction modulates activity of macaque superior temporal cortex

The ability to attribute thoughts to others, also called theory of mind (TOM), has been extensively studied. Computationally, the basis of TOM in humans has been interpreted within the predictive coding framework and associated with activity in the temporo-parietal junction (TPJ). However, the evolutionary origins of these human mindreading abilities have been challenged since the concept was coined. Here we identify a brain region in the Rhesus macaque that shares computational properties with the human TPJ. We revealed, using a non-linguistic task and functional magnetic resonance imaging, that activity in a region of the macaque middle superior temporal cortex was specifically modulated by the predictability of social interactions. As in human TPJ, this region could be distinguished from other temporal regions involved in face processing. Our result suggests the existence of a precursor for the theory of mind ability in the last common ancestor of human and old-world monkeys.
A Structural Basis for Inhibition of the Complement Initiator Protease C1r by Lyme Disease Spirochetes

Key Points We provide a structural basis for inhibition of complement by a bacterial protein. This study improves our knowledge of how pathogens evade early complement steps. Complement evasion is a hallmark of extracellular microbial pathogens such as Borrelia burgdorferi, the causative agent of Lyme disease. Lyme disease spirochetes express nearly a dozen outer surface lipoproteins that bind complement components and interfere with their native activities. Among these, BBK32 is unique in its selective inhibition of the classical pathway. BBK32 blocks activation of this pathway by selectively binding and inhibiting the C1r serine protease of the first component of complement, C1. To understand the structural basis for BBK32-mediated C1r inhibition, we performed crystallography and size-exclusion chromatography–coupled small angle X-ray scattering experiments, which revealed a molecular model of BBK32-C in complex with activated human C1r. Structure-guided site-directed mutagenesis was combined with surface plasmon resonance binding experiments and assays of complement function to validate the predicted molecular interface. Analysis of the structures shows that BBK32 inhibits activated forms of C1r by occluding substrate interaction subsites (i.e., S1 and S1’) and reveals a surprising role for C1r B loop–interacting residues for full inhibitory activity of BBK32. The studies reported in this article provide for the first time (to our knowledge) a structural basis for classical pathway–specific inhibition by a human pathogen.
Diversity and prevalence of colibactin- and yersiniabactin encoding mobile genetic elements in enterobacterial populations: insights into evolution and co-existence of two bacterial secondary metabolite determinants

The bacterial genotoxin colibactin interferes with the eukaryotic cell cycle by causing double-stranded DNA breaks. It has been linked to bacterially induced colorectal cancer in humans. Colibactin is encoded by a 54-kb genomic region in Enterobacteriaceae. The colibactin genes commonly co-occur with the yersiniabactin biosynthetic determinant. Investigating the prevalence and sequence diversity of the colibactin determinant and its linkage to the yersiniabactin operon in prokaryotic genomes, we discovered mainly species-specific lineages of the colibactin determinant and classified three main structural settings of the colibactin-yersiniabactin genomic region in Enterobacteriaceae. The colibactin gene cluster has a similar but not identical evolutionary track to that of the yersiniabactin operon. Both determinants could have been acquired on several occasions and/or exchanged independently between enterobacteria by horizontal gene transfer. Integrative and conjugative elements play(ed) a central role in the evolution and structural diversity of the colibactin-yersiniabactin genomic region. Addition of an activating and regulating module (clbAR) to the biosynthesis and transport module (clbB-S) represents the most recent step in the evolution of the colibactin determinant. In a first attempt to correlate colibactin expression with individual lineages of colibactin determinants and different bacterial genetic backgrounds, we compared colibactin expression of selected enterobacterial isolates in vitro. Colibactin production in the tested Klebsiella spp. and Citrobacter koseri strains was more homogeneous and generally higher than that in most of the E. coli isolates studied. Our results improve the understanding of the diversity of colibactin determinants and its expression level, and may contribute to risk assessment of colibactin-producing enterobacteria.
Dopamine Transporter Is a Master Regulator of Dopaminergic Neural Network Connectivity

Dopaminergic neurons of the substantia nigra pars compacta (SNC) and ventral tegmental area (VTA) exhibit spontaneous firing activity. The dopaminergic neurons in these regions have been shown to exhibit differential sensitivity to neuronal loss and psychostimulants targeting dopamine transporter. However, it remains unclear whether these regional differences scale beyond individual neuronal activity to regional neuronal networks. Here, we used live-cell calcium imaging to show that network connectivity greatly differs between SNC and VTA regions with higher incidence of hub-like neurons in the VTA. Specifically, the frequency of hub-like neurons was significantly lower in SNC than in the adjacent VTA, consistent with the interpretation of a lower network resilience to SNC neuronal loss. We tested this hypothesis, in DAT-cre/loxP-GCaMP6f mice of either sex, when activity of an individual dopaminergic neuron is suppressed, through whole-cell patch clamp electrophysiology, in either SNC or VTA networks. Neuronal loss in the SNC increased network clustering, whereas the larger number of hub-neurons in the VTA overcompensated by decreasing network clustering in the VTA. We further show that network properties are regulatable via a dopamine transporter but not a D2 receptor dependent mechanism. Our results demonstrate novel regulatory mechanisms of functional network topology in dopaminergic brain regions. SIGNIFICANCE STATEMENT In this work, we begin to untangle the differences in complex network properties between the substantia nigra pars compacta (SNC) and VTA, that may underlie differential sensitivity between regions. The methods and analysis employed provide a springboard for investigations of network topology in multiple deep brain structures and disorders.
High variation in immune responses and parasite phenotypes in naturally acquired Trypanosoma cruzi infection in a captive non-human primate breeding colony in Texas, USA

Trypanosoma cruzi, the causative agent of human Chagas disease, is endemic to the southern region of the United States where it routinely infects many host species. The indoor/outdoor housing configuration used in many non-human primate research and breeding facilities in the southern U.S. provides the opportunity for infection by T. cruzi and thus provides source material for in-depth investigation of host and parasite dynamics in a natural host species under highly controlled and restricted conditions. For cynomolgus macaques housed at such a facility, we used a combination of serial blood quantitative PCR (qPCR) and hemoculture to confirm infection in >92% of seropositive animals, although each method alone failed to detect infection in >20% of cases. Parasite isolates obtained from 43 of the 64 seropositive macaques were of 2 broad genetic types (discrete typing units, (DTU’s) I and IV); both within and between these DTU groupings, isolates displayed a wide variation in growth characteristics and virulence, elicited host immune responses, and susceptibility to drug treatment in a mouse model. Likewise, the macaques displayed a diversity in T cell and antibody response profiles that rarely correlated with parasite DTU type, length of infection, or age of the primate. This study reveals the complexity of infection dynamics, parasite phenotypes, and immune response patterns that can occur in a primate group, despite being housed in a uniform environment at a single location, and the limited time period over which the T. cruzi infections were established. Author Summary We evaluated naturally occurring infections of Trypanosoma cruzi, the causative agent of human Chagas disease, in an indoor/outdoor primate colony at a breeding facility in Texas, USA. Using serial quantitative PCR and hemoculture, we confirmed infection in 92% of the 64 seropositive animals, but neither of these two methods confirmed more than 80% of the cases. Parasites by hemoculture fell into two genetic groups (discrete typing units I and IV), and displayed large variation in growth characteristics, elicited cellular and humoral immune responses as well as virulence and drug susceptibility when tested in mice. EKG abnormalities were found in 13 out of 51 qPCR-positive macaques. Our results demonstrate the complexity of these infection parameters in this colony in spite of the uniform and geographically constrained housing conditions of the macaques.
Diverse functions associate with trans-species polymorphisms in humans

Long-term balancing selection (LTBS) can maintain allelic variation at a locus over millions of years and through speciation events. Variants shared between species, hereafter “trans-species polymorphisms” (TSPs), often result from LTBS due to host-pathogen interactions. For instance, the major histocompatibility complex (MHC) locus contains TSPs present across primates. Several hundred TSPs have been identified in humans and chimpanzees; however, because many are in non-coding regions of the genome, the functions and adaptive roles for most TSPs remain unknown. We integrated diverse genomic annotations to explore the functions of 125 previously identified non-coding TSPs that are likely under LTBS since the common ancestor of humans and chimpanzees. We analyzed genome-wide functional assays, expression quantitative trait loci (eQTL), genome-wide association studies (GWAS), and phenome-wide association studies (PheWAS). We identify functional annotations for 119 TSP regions, including 71 with evidence of gene regulatory function from GTEx or genome-wide functional genomics data and 21 with evidence of trait association from GWAS and PheWAS. TSPs in humans associate with many immune system phenotypes, including response to pathogens, but we also find associations with a range of other phenotypes, including body mass, alcohol intake, urate levels, chronotype, and risk-taking behavior. The diversity of traits associated with non-coding human TSPs suggest that functions beyond the immune system are often subject to LTBS. Furthermore, several of these trait associations provide support and candidate genetic loci for previous hypothesis about behavioral diversity in great ape populations, such as the importance of variation in sleep cycles and risk sensitivity. Significance statement Most genetic variants present in human populations are young (<100,000 years old); however, a few hundred are millions of years old with origins before the divergence of humans and chimpanzees. These trans-species polymorphisms (TSPs) were likely maintained by balancing selection—evolutionary pressure to maintain genetic diversity at a locus. However, the functions driving this selection, especially for non-coding TSPs, are largely unknown. We integrate genome-wide annotation strategies to demonstrate TSP associations with immune system function, behavior (addition, cognition, risky behavior), uric acid metabolism, and many other phenotypes. These results substantially expand our understanding of functions TSPs and suggest a substantial role for balancing selection beyond the immune system.
Abundant secreted hydrolytic enzymes and secondary metabolite gene clusters in genomes of the Botryosphaeriaceae reflect their role as important plant pathogens

The Botryosphaeriaceae are important plant pathogens, but unique in their ability to establish asymptomatic infections that persist for extended periods in a latent state. In this study, we used comparative analyses to consider elements that might shed light on the genetic basis of the interactions of these fungi with their plant hosts. For this purpose, we characterised secreted hydrolytic enzymes, secondary metabolite biosynthetic gene clusters and considered general trends in genomic architecture using all available Botryosphaeriaceae genomes, and selected Dothideomycetes genomes. The Botryosphaeriaceae genomes were rich in carbohydrate-active enzymes (CAZymes), proteases, lipases and secondary metabolic biosynthetic gene clusters (BGCs) compared to other Dothideomycete genomes. The genomes of Botryosphaeria, Macrophomina, Lasiodiplodia and Neofusicoccum, in particular, had gene expansions of the major constituents of the secretome, notably CAZymes involved in plant cell wall degradation. The Botryosphaeriaceae genomes were shown to have moderate to high GC contents and most had low levels of repetitive DNA. The genomes were not compartmentalized based on gene and repeat densities, but genes of secreted enzymes were slightly more abundant in gene-sparse regions. The abundance of secreted hydrolytic enzymes and secondary metabolite BGCs in the genomes of Botryosphaeria, Macrophomina, Lasiodiplodia, and Neofusicoccum were similar to those in necrotrophic plant pathogens, but also endophytes of woody plants. The results provide a foundation for future comparative genomic analyses and hypothesis to explore the mechanisms underlying Botryosphaeriaceae host-plant interactions.
A new method for determining ribosomal DNA copy number shows differences between Saccharomyces cerevisiae populations

Ribosomal DNA genes (rDNA) encode the major ribosomal RNAs (rRNA) and in eukaryotic genomes are typically present as one or more arrays of tandem repeats. Species have characteristic rDNA copy numbers, ranging from tens to thousands of copies, with the number thought to be redundant for rRNA production. However, the tandem rDNA repeats are prone to recombination-mediated changes in copy number, resulting in substantial intra-species copy number variation. There is growing evidence that these copy number differences can have phenotypic consequences. However, we lack a comprehensive understanding of what determines rDNA copy number, how it evolves, and what the consequences are, in part because of difficulties in quantifying copy number. Here, we developed a genomic sequence read approach that estimates rDNA copy number from the modal coverage of the rDNA and whole genome to help overcome limitations in quantifying copy number with existing mean coverage-based approaches. We validated our method using strains of the yeast Saccharomyces cerevisiae with previously-determined rDNA copy numbers, and then applied our pipeline to investigate rDNA copy number in a global sample of 788 yeast isolates. We found that wild yeast have a mean copy number of 92, consistent with what is reported for other fungi but much lower than in laboratory strains. We show that different populations have different rDNA copy numbers. These differences can partially be explained by phylogeny, but other factors such as environment are also likely to contribute to population differences in copy number. Our results demonstrate the utility of the modal coverage method, and highlight the high level of rDNA copy number variation within and between populations.
Systemic administration of anti-CD20 indirectly reduces B cells in the inflamed meninges in a chronic model of central nervous system autoimmunity

Anti-CD20 B cell depleting therapies have demonstrated that B cells are important drivers of disease progress in Multiple Sclerosis, although the pathogenic mechanisms are not well understood. A population of B cells accumulates in the inflamed meninges in MS and also some chronic animal models of disease, typically adjacent to demyelinating lesions. The role of these meningeal B cells in disease is not known, nor is their susceptibility to anti-CD20 therapy. Here, we administered anti-CD20 to 2D2 IgHMOG spontaneous experimental autoimmune encephalomyelitis mice in the chronic phase of disease, after the establishment of meningeal B cell clusters. Compared to the circulation, lymph nodes, and spleen, B cell depletion from the CNS was delayed and not evident until 7d post administration of anti-CD20. Further, we did not find evidence that anti-CD20 accessed meningeal B cells directly, but rather that depletion was indirect and the result of ongoing turnover of the meningeal population and elimination of the peripheral pool from which it is sustained. The reduction of B cell numbers in the CNS coincided with less demyelination of the spinal cord white matter and also, surprisingly, an increase in the number of T cells recruited to the meninges but not parenchyma.