Miracle-dz/UniFAR-FTUs huggingface dataset:
Geometric invariance in computer vision

Part 1 Foundations: algebraic invariants - invariant theory and enumerative combinatorics of young tableaux, Shreeram S. Abhyankar, geometric interpretation of joint conic invariants, Joseph L. Mundy, et al, an experimental evaluation of projective invariants, Christopher Coelho, et al the projection of two non-coplanar conics, Stephen J. Maybank the non-existence of general-case view-invariants, J. Brian Burns, et al invariants of non-algebraic curves - noise resistant invariants of curves, Isaac Weiss, semi-differential invariants, Luc J. Van Gool, et al, projective invariants for curves in two and three dimensions, Michael H. Brill, et al, numerical evaluation of differential and semi-differential invariants, Christopher Brown, recognizing general curved objects efficiently, Andrew Zisserman, et al fitting affine invariant conics to curves, Deepak Kapur and Joseph L. Mundy, projectively invariant decomposition of planar shapes, Stefan Carlsson invariants from multiple views - invariant linear methods in photogrammetry and model-matching, Eamon B. Barrett, et al semi-differential invariants for nonplanar curves, Luc J. Van Gool, et al disambiguating stereo matches with spatio-temporal surfaces, Olivier Faugeras and Theo Papadopoulo. Part 2 Applications: transformation invariant indexing, Haim J. Wolfson and Yehezkel Lamdan affine invariants for model-based recognition, John E. Hopcroft, et al object recognition based on moment (or algebraic) invariants, Gabriel Taubin and David B. Cooper fast recognition using algebraic invariants, Charles A. Rothwell, et al toward 3D curved object recognition from image contours, Jean Ponce and David J. Kriegman relative positioning with uncalibrated cameras, Roger Mohr, et al. Appendix: projective geometry for machine vision, Joseph L. Mundy and Andrew Zisserman.
Evaluating methods for estimating the proportion of adaptive amino acid substitutions

A long-standing debate in molecular evolution concerns the role of adaptation in shaping divergence between species. A number of approaches have been developed to estimate the proportion of amino acid substitutions between species (α) that are driven by adaptive natural selection. These methods vary in the type of data they use and in the modeling strategies they employ in their inference. In this study, we evaluate the accuracy of nine different methods for estimating α, using data simulated in the presence of linked selection. We find that methods that model the distribution of fitness effect (DFE) of both deleterious (as a gamma distribution) and beneficial mutations (as a gamma or exponential distribution) are the most accurate. We applied these methods to whole-genome data, finding that the most accurate methods gave average values of α=0.25 in Arabidopsis thaliana, 0.5 in Drosophila melanogaster, and 0.1 in Homo sapiens. We also applied these methods to analyze subsets of tissue-specific genes in A. thaliana that are believed to be under different selective pressures and on genes found on the X vs. autosomes in D. melanogaster. We find estimates of α to be higher in the seeds than in other specialized organs, supporting inferences of conflict-driven adaptive evolution in genes expressed in the seed; we also find α to be higher on the X chromosome, supporting previous inferences of faster-X evolution. Overall, our results suggest that there are multiple methods that provide accurate estimates of α, providing a guide for future estimates of adaptive evolution.
classLog: Logistic regression for the classification of genetic sequences

Sequencing and phylogenetic classification have become a common task in human and animal diagnostic laboratories. It is routine to sequence pathogens to identify genetic variations of diagnostic significance and to use these data in real-time genomic contact tracing and surveillance. Under this paradigm, unprecedented volumes of data are generated that require rapid analysis to provide meaningful inference. We present a machine learning logistic regression pipeline that can assign classifications to genetic sequence data. The pipeline implements an intuitive and customizable approach to developing a trained prediction model that runs in linear time complexity, generating accurate output more rapidly than other classification methods. Our approach was benchmarked against porcine respiratory and reproductive syndrome virus (PRRSv) and swine H1 influenza A (IAV) datasets. Trained classifiers were tested against sequences and simulated datasets that artificially degraded sequence quality at 0, 10, 20, 30, and 40%. When applied to a poor-quality sequence data, the classifier achieved between >85% to 95% accuracy for the PRRSv and the swine H1 IAV HA dataset and this increased to near perfect accuracy when using the full dataset. The model also identifies amino acid positions used to determine genetic clade identity through a feature selection ranking within the model. These positions can be mapped onto a maximum-likelihood phylogenetic tree, allowing for the inference of clade defining mutations. Our approach is implemented as a python package with code available at https://github.com/flu-crew/classLog.
Dynamics, signals and influencing factors of CD4 T cell activation revealed by single cell RNA-seq

T cell activation is a key event in adaptive immunity. However, factors affecting T cell activation have not been systematically analyzed. Here, we analyzed stimulated CD4 T cells with anti-CD3/CD28 under several conditions to explore the factors affecting T cell activation. We defined stimulated T overlapped with resting T on UMAP as inert T. Inert T expressed activated T specific genes and cytokines, indicating it is a special functional state. Stimulated T derived from peripheral CD4 T has higher fraction of effector T (TEFF) while stimulated T derived from CD4 TN has higher fraction of proliferation T and interferon highly expressed T (IFNhi T). CD4 T was more likely to differentiate into TEFF and less likely to differentiate into heat shock protein specific T (HSPhi T) and IFNhi T in the presence of CD8 T. Interestingly, CXCR4low T responded to stimulation more efficiently than CXCR4hi T. These information facilitates we design stimulation to obtain ideal activated T.
Structural and dynamic basis of DNA capture and translocation by mitochondrial Twinkle helicase

Twinkle is the sole helicase responsible for mitochondrial DNA replication. Twinkle can selfload onto and unwind mitochondrial DNA. Nearly 60 mutations on Twinkle have been linked to human mitochondrial diseases. Using cryo-electron microscopy (cryo-EM) and High-speed atomic force microscope (HS-AFM), we obtained the atomic-resolution structure of a vertebrate Twinkle homolog with DNA and captured in real-time how Twinkle is self-loaded onto DNA. Our data highlight the essential role of the non-catalytic N-terminal domain of Twinkle. The N-terminal domain interacts with the helicase domain to stabilize Twinkle hexamers during translocation and the new domain-domain interface is a hotspot for disease-related mutations. The N-terminal domains can protrude approximately 5 nm to capture nearby DNA and initialize Twinkle loading onto DNA. Moreover, structural analysis and subunit doping experiments suggest that Twinkle hydrolyzes ATP stochastically, which explains the low efficiency of Twinkle DNA unwinding and implicates additional regulations of Twinkle during mitochondrial DNA replication.
Identification, characterization of Apyrase (APY) gene family in rice (Oryza sativa) and analysis of the expression pattern under various stress conditions

Apyrase (APY) is a nucleoside triphosphate (NTP) diphosphohydrolase (NTPDase) which is a member of the superfamily of guanosine diphosphatase 1 (GDA1) - cluster of differentiation 39 (CD39) nucleoside phosphatase. Under various circumstances like stress, cell growth, the extracellular adenosine triphosphate (eATP) level increases, causing a detrimental influence on cells such as cell growth retardation, ROS production, NO burst, and apoptosis. Apyrase hydrolyses eATP accumulated in the extracellular membrane during stress, wounds, into adenosine diphosphate (ADP) and adenosine monophosphate (AMP) and regulates the stress- responsive pathway in plants. This study was designed for the identification, characterization, and for analysis of APY gene expression in Oryza sativa. This investigation discovered nine APYs in rice, including both endo- and ecto-apyrase. According to duplication event analysis, in the evolution of OsAPYs, a significant role is performed by segmental duplication. Their role in stress control, hormonal responsiveness, and the development of cells is supported by the corresponding cis-elements present in their promoter regions. According to expression profiling by RNA-seq data, the genes were expressed in various tissues. Upon exposure to a variety of biotic as well as abiotic stimuli, including anoxia, drought, submergence, alkali, heat, dehydration, salt, and cold, they showed a differential expression pattern. The expression analysis from the RT-qPCR data also showed expression under various abiotic stress conditions, comprising cold, salinity, cadmium, drought, submergence, and especially heat stress. This finding will pave the way for future in-vivo analysis, unveil the molecular mechanisms of APY genes in stress response, and contribute to the development of stress- tolerant rice varieties.
Growth Arrest of Staphylococcus aureus Induces Daptomycin Tolerance via Cell Wall Remodelling

Understanding why antibiotics sometimes fail to cure infections is fundamental to improving treatment outcomes. This is a major challenge when it comes to Staphylococcus aureus because this pathogen causes several different chronic or recurrent infections. ABSTRACT Almost all bactericidal drugs require bacterial replication and/or metabolic activity for their killing activity. When these processes are inhibited by bacteriostatic antibiotics, bacterial killing is significantly reduced. One notable exception is the lipopeptide antibiotic daptomycin, which has been reported to efficiently kill growth-arrested bacteria. However, these studies employed only short periods of growth arrest (<1 h), which may not fully represent the duration of growth arrest that can occur in vivo. We found that a growth inhibitory concentration of the protein synthesis inhibitor tetracycline led to a time-dependent induction of daptomycin tolerance in S. aureus, with an approximately 100,000-fold increase in survival after 16 h of growth arrest, relative to exponential-phase bacteria. Daptomycin tolerance required glucose and was associated with increased production of the cell wall polymers peptidoglycan and wall-teichoic acids. However, while the accumulation of peptidoglycan was required for daptomycin tolerance, only a low abundance of wall teichoic acid was necessary. Therefore, whereas tolerance to most antibiotics occurs passively due to a lack of metabolic activity and/or replication, daptomycin tolerance arises via active cell wall remodelling. IMPORTANCE Understanding why antibiotics sometimes fail to cure infections is fundamental to improving treatment outcomes. This is a major challenge when it comes to Staphylococcus aureus because this pathogen causes several different chronic or recurrent infections. Previous work has shown that a lack of replication, as often occurs during infection, makes bacteria tolerant of most bactericidal antibiotics. However, one antibiotic that has been reported to kill nonreplicating bacteria is daptomycin. In this work, we show that the growth arrest of S. aureus does in fact lead to daptomycin tolerance, but it requires time, nutrients, and biosynthetic pathways, making it distinct from other types of antibiotic tolerance that occur in nonreplicating bacteria.
Cellular Mechanisms Underlying Embryonic Retinal Waves

Spontaneous activity is a hallmark of developing neural systems. In the retina, spontaneous activity comes in the form of retinal waves, comprised of three stages persisting from embryonic day 16 (E16) to eye opening at postnatal day 14 (P14). Though postnatal retinal waves have been well characterized, little is known about the spatiotemporal properties or the mechanisms mediating embryonic retinal waves, designated Stage 1 waves. Using a custom-built macroscope to record spontaneous calcium transients from whole embryonic retinas, we show that Stage 1 waves are initiated at several locations across the retina and propagate across finite regions of a broad range of areas. A gap junction antagonist, meclofenamic acid, reduced the frequency and size of Stage 1 waves but did not abolish them. The general nAChR antagonist, hexamethonium blocked Stage 1 waves, while they persisted in the presence of α4β2 nAChR antagonist dihydro-ß-erythroidine, indicating that the spatiotemporal properties of Stage 1 waves are mediated by a complex circuitry involving subtypes of nAChRs and gap junctions. Stage 1 waves in mice lacking the β2 subunit of the nAChRs (β2-nAChR-KO) were reduced, but in contrast to WT mice, they persisted in the hexamethonium and were completely blocked by meclofenamic acid. To assay the impact of Stage 1 waves on retinal development, we compared the spatial distribution of a subtype of retinal ganglion cells, intrinsically photosensitive retinal ganglion cells (ipRGCs) in WT and β2-nAChR-KO mice. We found that the developmental decrease of ipRGC density is preserved between WT and β2-nAChR-KO mice, indicating that processes regulating ipRGC distribution are not influenced by spontaneous activity.
Urotensin II-related peptides, Urp1 and Urp2, control zebrafish spine morphology

The spine provides structure and support to the body, yet how it develops its characteristic morphology as the organism grows is little understood. This is underscored by the commonality of conditions in which the spine curves abnormally such as scoliosis, kyphosis and lordosis. Understanding the origin of such spinal curves has been challenging in part due to the lack of appropriate animal models. Recently, zebrafish have emerged as promising tools with which to understand the origin of spinal curves. Using zebrafish, we demonstrate that the Urotensin II-related peptides (URPs), Urp1 and Urp2, are essential for maintaining spine morphology. Urp1 and Urp2 are 10-amino acid cyclic peptides expressed by neurons lining the central canal of the spinal cord. Upon combined genetic loss of Urp1 and Urp2, adolescent-onset planar curves manifested in the caudal region of the spine, akin to a lordosis-like condition. Highly similar curves were caused by mutation of Uts2r3, an URP receptor. Quantitative comparisons revealed that Urotensin-associated curves were distinct from other zebrafish spinal curve mutants that more closely reflected idiopathic scoliosis or kyphosis. Last, we found that the Reissner fiber, a proteinaceous thread that sits in the central canal and has been implicated in the control of spine morphology, breaks down prior to curve formation in an idiopathic scoliosis model but was unperturbed by loss of Uts2r3. This suggests a Reissner fiber-independent mechanism of curvature in Urotensin-deficient mutants. Overall, our results show that Urp1 and Urp2 control zebrafish spine morphology and establish new animal models of lordosis-like curves.
ENVIROME-WIDE ASSOCIATIONS ENHANCE MULTI-YEAR GENOME-BASED PREDICTION OF HISTORICAL WHEAT BREEDING DATA

Linking high-throughput environmental data (enviromics) into genomic prediction (GP) is a cost-effective strategy for increasing selection intensity under genotype-by-environment interactions (G×E). This study developed a data-driven approach based on Environment-Phenotype Associations (EPA) aimed at recycling important G×E information from historical breeding data. EPA was developed in two applications: (1) scanning a secondary source of genetic variation, weighted from the shared reaction-norms of past-evaluated genotypes; (2) pinpointing weights of the similarity among trial-sites (locations), given the historical impact of each envirotyping data variable for a given site. Then, the EPA outcomes were integrated into multi-environment GP models through a new single-step GBLUP. The wheat trial data used included 36 locations, 8 years and 3 target populations of environments (TPE) in India. Four prediction scenarios and 6 kernel-models within/across TPEs were tested. Our results suggest that the conventional GBLUP, without enviromic data or when omitting EPA, is inefficient in predicting the performance of wheat lines in future years. However, when EPA was introduced as an intermediary learning step to reduce the dimensionality of the G×E kernels while connecting phenotypic and environmental-wide variation, a significant enhancement of G×E prediction accuracy was evident. EPA revealed that the effect of seasonality makes strategies such as “covariable selection” unfeasible because G×E is year-germplasm specific. We propose that the EPA effectively serves as a “reinforcement learner” algorithm capable of uncovering the effect of seasonality over the reaction-norms, with the benefits of better forecasting the similarities between past and future trialing sites. EPA combines the benefits of dimensionality reduction while reducing the uncertainty of genotype-by-year predictions and increasing the resolution of GP for the genotype-specific level.
Calculating shades of meaning in semantic spaces

This thesis introduces the problem of conceptual ambiguity, or Shades of Meaning (SoM) that can exist around a term or entity. As an example consider President Ronald Reagan the ex-president of the USA, there are many aspects to him that are captured in text; the Russian missile deal, the Iran-contra deal and others. Simply finding documents with the word “Reagan” in them is going to return results that cover many different shades of meaning related to "Reagan". Instead it may be desirable to retrieve results around a specific shade of meaning of "Reagan", e.g., all documents relating to the Iran-contra scandal. This thesis investigates computational methods for identifying shades of meaning around a word, or concept. This problem is related to word sense ambiguity, but is more subtle and based less on the particular syntactic structures associated with or around an instance of the term and more with the semantic contexts around it. A particularly noteworthy difference from typical word sense disambiguation is that shades of a concept are not known in advance. It is up to the algorithm itself to ascertain these subtleties. It is the key hypothesis of this thesis that reducing the number of dimensions in the representation of concepts is a key part of reducing sparseness and thus also crucial in discovering their SoMwithin a given corpus.
Identification of unique α4 chain structure and conserved anti-angiogenic activity of α3NC1 type IV collagen in zebrafish

Type IV collagen is an abundant component of basement membranes in all multicellular species and is essential for the extracellular scaffold supporting tissue architecture and function. Lower organisms typically have two type IV collagen genes, encoding α1 and α2 chains, in contrast with the six genes in humans, encoding α1 to α6 chains. The α chains assemble into trimeric protomers, the building blocks of the type IV collagen network. The detailed evolutionary conservation of type IV collagen network remains to be studied. We report on the molecular evolution of type IV collagen genes. The zebrafish α4 non-collagenous (NC1) domain, in contrast with its human ortholog, contains an additional cysteine residue and lacks the M93 and K211 residues involved in sulfilimine bond formation between adjacent protomers. This may alter α4 chain interactions with other α chains, as supported by temporal and anatomic expression patterns of collagen IV chains during zebrafish development. Despite the divergence between zebrafish and human α3 NC1 domain (endogenous angiogenesis inhibitor, Tumstatin), the zebrafish α3 NC1 domain exhibits conserved anti-angiogenic activity in human endothelial cells. Our work supports type IV collagen is largely conserved between zebrafish and humans, with a possible difference involving the α4 chain.
Zebrafish Slit2 and Slit3 Act Together to Regulate Retinal Axon Crossing at the Midline

Slit-Robo signaling regulates midline crossing of commissural axons in different systems. In the zebrafish, all retinofugal axons cross at the optic chiasm to innervate the contralateral tectum. Here, the mutant for the Robo2 receptor presents severe axon guidance defects, which were not completely reproduced by a Slit2 ligand null mutant. Since, in the zebrafish, slit3 is also expressed around this area at the stage of axon crossing, we decided to analyze the possibility that it collaborates with Slit2. We found that slit3 expression disruption by sgRNA-Cas9 injection caused similar, albeit slightly milder, defects than those of the slit2 mutant, while the same treatment in the slit2-/- background caused a much more severe defect, comparable to that observed in robo2 mutants. Tracking analysis of in vivo time-lapse experiments indicated differential but complementary functions of these secreted factors in the correction of axon turn errors around the optic chiasm. Interestingly, qPCR analysis showed a mild slit2 expression increase in slit3 deficient embryos, but not the inverse. Our observations support the previously proposed “repulsive channel” model for Slit-Robo action at the optic chiasm, with both Slits acting through Robo2 in different manners, most probably based on their different spatial expression patterns.
Endocannabinoid-dependent persistent decrease of GABAergic transmission on dopaminergic neurons underlies gene-environment interaction-induced susceptibility to cocaine sensitization

Vulnerability to develop cocaine use disorder depends upon an unpredictable combination of genetic and non-genetic risk factors. Early life adversity and adolescence are critical non-genetic risk factors, and haplotypes of the monoamine oxidase (MAO) genes are among genetic variations increasing the risk of drug-related problems. However, data on the interactions between inheritable risk factors and early life stress (ES) with respect to predisposition to cocaine abuse are limited. Here, we show that a mouse model containing both genetic (low-activity alleles of the MAO A gene; MAOANeo) and environmental (i.e., ES) variables displays a long lasting increased sensitivity to repeated in vivo cocaine psychomotor stimulant actions associated with a reduction of GABAA receptor-mediated inhibition of dopamine neurons of the ventral tegmental area (VTA). Depolarization-induced suppression of inhibition (DSI), a 2-arachidonoylglycerol (2-AG)-dependent form of short-term plasticity, also becomes readily expressed by dopamine neurons from MAOANeoES mice treated repeatedly with cocaine. Activation of either dopamine D2 or CB1 receptors is required for cocaine-induced DSI expression, decreased GABA synaptic efficacy, and hyperlocomotion. Next, in vivo pharmacological enhancement of 2-AG signaling during repeated cocaine exposure occludes its actions both in vivo and ex vivo. This data extends our knowledge of the multifaceted sequelae imposed by this gene by environment interaction in VTA dopamine neurons of male pre-adolescent mice, contributing to our understanding of neural mechanisms of vulnerability for early onset cocaine use disorder.