Miracle-dz/UniFAR-FTUs huggingface dataset:
30-Minute Highly Multiplexed VaxArray Immunoassay for Pneumococcal Vaccine Antigen Characterization

Pneumonia accounts for over 20% of deaths worldwide in children aged 1 to 5 years, disproportionately affecting lower- and middle-income countries. Effective, highly multivalent pneumococcal vaccines are available to decrease disease burden, with numerous new vaccines currently under development to serve a variety of worldwide markets. However, pneumococcal conjugate vaccines are among the hardest biologics to manufacture and characterize due to their complexity and heterogeneity. Current characterization methods are often inherently singleplex, requiring separate tests for each serotype present. In addition, identity and quantity are often determined with separate methods. We have developed the VaxArray Pneumococcal Assay for applications in identity, quantity, and stability testing of pneumococcal polysaccharide and pneumococcal conjugate vaccines. The VaxArray Pneumococcal Assay has a time to result of less than 30 minutes and is an off-the-shelf multiplexed, microarray-based immunoassay kit that can identify and simultaneously quantify 23 pneumococcal polysaccharide serotypes common to many on-market and in-development vaccines. Here, we highlight the potential of the assay for identity testing by showing high reactivity and serotype-specificity to a wide variety of native polysaccharides, CRM197-conjugated polysaccharides, and drug product. The assay also has vaccine-relevant lower limits of quantification in the low to mid ng/mL range and can be used for accurate quantification even in adjuvanted vaccines. Excellent correlation to the anthrone assay is demonstrated, with VaxArray resulting in significantly improved precision over this antiquated chemical method.
Detection of orthologous genes with expression shifts linked to nickel hyperaccumulation across Eudicots

The remarkable capacity of plants to tolerate and accumulate tremendous amount of nickel is a complex adaptative trait that appeared independently in more than 700 species distributed in about fifty families. Nickel hyperaccumulation is thus proposed as a model to investigate the evolution of complex traits in plants. However, the mechanisms involved in nickel hyperaccumulation are still poorly understood in part because comparative transcriptomic analyses struggle to identify genes linked to this trait from a wide diversity of species. In this work, we have implemented a methodology based on the quantification of the expression of orthologous groups and phylogenetic comparative methods to identify genes which expression is correlated to the nickel hyperaccumulation trait. More precisely, we performed de novo transcriptome assembly and reads quantification for each species on its own transcriptome using available RNA-Seq datasets from 15 nickel hyperaccumulator and non-accumulator species. Assembled contigs were associated to orthologous groups built using proteomes predicted from completed plant genome sequences. We then analyzed the transcription profiles of 5953 orthologous groups from distant species using a phylogenetic ANOVA. We identified 31 orthologous groups with an expression shift associated with nickel hyperaccumulation. These orthologous groups correspond to genes that have been previously implicated in nickel accumulation, and to new candidates involved in this trait. We thus believe that this method can be successfully applied to identify genes linked to other complex traits from a wide diversity of species.
The contribution of mutation to variation in temperature-dependent sprint speed in zebrafish, Danio rerio

The contribution of new mutations to phenotypic variation, and the consequences of this variation for individual fitness, are fundamental concepts for understanding genetic variation and adaptation. Here, we investigated how mutation influenced variation in a complex trait in zebrafish, Danio rerio. Typical of many ecologically relevant traits in ectotherms, swimming speed in fish is temperature-dependent, with evidence of adaptive evolution of thermal performance. We chemically induced novel germline point mutations in males, and measured sprint speed in their sons at six temperatures (between 16°C and 34°C). Mutational effects on speed were strongly positively correlated among temperatures, resulting in statistical support for only a single axis of mutational variation, reflecting temperature-independent variation in speed (faster-slower mode). While these results suggest pleiotropic effects on speed across different temperatures, when mutation have consistent directional effects on each trait, spurious correlations arise via linkage, or heterogeneity in mutation number. However, mutation did not change mean speed, indicating no directional bias in mutational effects. The results contribute to emerging evidence that mutations may predominantly have synergistic cross-environment effects, in contrast to conditionally neutral or antagonistic effects which underpin thermal adaptation. However, aspects of experimental design might limit resolution of mutations with non-synergistic effects.
Subpopulation Codes Permit Information Modulation Across Cortical States

Cortical state is modulated by myriad cognitive and physiological mechanisms. Yet it is still unclear how changes in cortical state relate to changes in neuronal processing. Previous studies have reported state dependent changes in response gain or population-wide shared variability, motivated by the fact that both are important determinants of the performance of any population code. However, if the state-conditioned cortical regime is well-captured by a linear input-output response (as is often the case), then the linear Fisher information (FI) about a stimulus available to a decoder is invariant to state changes. In this study we show that by contrast, when one restricts a decoder to a subset of a cortical population, information within the subpopulation can increase through a modulation of cortical state. A clear example of such a subpopulation code is one in which decoders only receive projections from excitatory cells in a recurrent excitatory/inhibitory (E/I) network. We demonstrate the counterintuitive fact that when decoding only from E cells, it is exclusively the I cell response gain and connectivity which govern how information changes. Additionally, we propose a parametrically simplified approach to studying the effect of state change on subpopulation codes. Our results reveal the importance of inhibitory circuitry in modulating information flow in recurrent cortical networks, and establish a framework in which to develop deeper mechanistic insight into the impact of cortical state changes on information processing in these circuits.
A high quality chromosome-level genome assembly for the golden mussel (Limnoperna fortunei)

The golden mussel (Limnoperna fortunei) is a highly adaptive species that causes environmental and socioeconomic losses in invaded areas. Reference genomes have proven to be a valuable resource for studying the biology of invasive species. While the current golden mussel genome has been useful for identifying new genes, its high fragmentation hinders some applications. In this Data Note, we provide the first chromosome-level reference genome for the golden mussel. The genome was built using Hi-C, PacBio HiFi and 10X sequencing data. The final assembly contains 99.4% of its total length assembled to the 15 chromosomes of the species and a scaffold N50 of 97.05 Mb. Approximately 47% of the genome was annotated as repetitive sequences. A total of 34 862 protein-coding genes were predicted, of which 84.7% were functionally annotated. This new high quality genome is expected to support both basic and applied research on this invasive species. Species taxonomy Eukaryota; Opisthokonta; Metazoa; Eumetazoa; Bilateria; Protostomia; Spiralia; Lophotrochozoa; Mollusca; Bivalvia; Autobranchia; Pteriomorphia; Mytilida; Mytiloidea; Mytilidae; Arcuatulinae; Limnoperna; Limnoperna fortunei (Dunker, 1857) (NCBI Taxonomy ID: 356393)
A review of two-band superconductivity: materials and effects on the thermodynamic and reversible mixed-state properties

Two-band superconductivity has become an important topic over the past ten years. Extensive experimental and theoretical studies started with MgB2 and are now focused on iron-based and other new superconductors. In this review, I describe how important thermodynamic, reversible mixed-state, and other superconducting properties are changed by two-band superconductivity and, for comparison, by other effects such as anisotropy in a single-band material or an energy-gap structure different from the conventional s-wave symmetry. The work consists of three main parts, in which I review (i) theoretical models and what they predict for experimentally accessible properties in the two-band and other scenarios, (ii) experimental methods applied for investigating superconducting properties and the results obtained in potential two-band materials, and (iii) materials, for which two- or multi-band superconductivity has been suggested. It is shown that two-band effects appear in most of the analyzed properties and that they can be quite significant but usually fade away as interband interactions increase. Anisotropy often leads to similar modifications in single-band superconductors, which is why the distinction of two-band and anisotropy effects is usually difficult, particularly when the temperature dependence of the quantities is examined. In contrast, the field-dependent effects are more often different and thus more often allow a reliable distinction between the models.
Numerical methods for multibody systems

This article gives a brief summary of some results obtained by Nasser on modeling and simulation of inequality problems in multibody dynamics. In particular, the augmented Lagrangian method discussed here is applied to a constrained motion problem with impulsive inequality constraints. A fundamental characteristic of the multibody dynamics problem is the lack of global convexity of its Lagrangian. The problem is transformed into a convex analysis problem by localization (piecewise linearization), where the augmented Lagrangian has been successfully used. A model test problem is considered and a set of numerical experiments is presented.
Solution of linear gyroscopic systems

HE solution of gyroscopic system equations requires solution of an eigenvalue problem which by present methods is accomplished via a transformation to a standard non-gyroscopic eigenvalue problem on two symmetric matrices with its associated computational advantages. However this is done at the expense of doubling the dimension and simultaneously doubling the multiplicities of the eigenfrequencies. In this paper a method is presented which, for most practical problems eliminates these difficulties. The method takes advantage of special phase relationships satisfied in many practical systems.
Rapid evolutionary diversification of the flamenco locus across simulans clade Drosophila species

Effective suppression of transposable elements (TEs) is paramount to maintain genomic integrity and organismal fitness. In D. melanogaster, flamenco is a master suppressor of TEs, preventing their movement from somatic ovarian support cells to the germline. It is transcribed by Pol II as a long (100s of kb), single-stranded, primary transcript, that is metabolized into Piwi-interacting RNAs (piRNAs) that target active TEs via antisense complementarity. flamenco is thought to operate as a trap, owing to its high content of recent horizontally transferred TEs that are enriched in antisense orientation. Using newly-generated long read genome data, which is critical for accurate assembly of repetitive sequences, we find that flamenco has undergone radical transformations in sequence content and even copy number across simulans clade Drosophilid species. D. simulans flamenco has duplicated and diverged, and neither copy exhibits synteny with D. melanogaster beyond the core promoter. Moreover, flamenco organization is highly variable across D. simulans individuals. Next, we find that D. simulans and D. mauritiana flamenco display signatures of a dual-stranded cluster, with ping-pong signals in the testis and/or embryo. This is accompanied by increased copy numbers of germline TEs, consistent with these regions operating as functional dual stranded clusters. Overall, the physical and functional diversity of flamenco orthologs is testament to the extremely dynamic consequences of TE arms races on genome organization, not only amongst highly related species, but even amongst individuals.
Value-Based Neural Representations Predict Social Decision Preferences

Social decision-making is omnipresent in everyday life, carrying the potential for both positive and negative consequences for the decision-maker and those closest to them. While evidence suggests that decision makers use value-based heuristics to guide choice behavior, very little is known about how decision makers’ representations of other agents influence social choice behavior. We used multivariate pattern expression analyses on fMRI data to understand how value-based processes shape neural representations of those affected by one’s social decisions and whether value-based encoding is associated with social decision preferences. We found that stronger value-based encoding of a given close other (e.g., parent) relative to a second close other (e.g., friend) was associated with a greater propensity to favor the former during subsequent social decision-making. These results are the first to our knowledge to explicitly show that value-based processes affect decision behavior via representations of close others.
YOUNG STELLAR OBJECTS IN THE MASSIVE STAR-FORMING REGION W49

We present the initial results of our investigation of the star-forming complex W49, one of the youngest and most luminous massive star-forming regions in our Galaxy. We used Spitzer/Infrared Array Camera (IRAC) data to investigate massive star formation with the primary objective of locating a representative set of protostars and the clusters of young stars that are forming around them. We present our source catalog with the mosaics from the IRAC data. In this study we used a combination of IRAC, MIPS, Two Micron All Sky Survey, and UKIRT Deep Infrared Sky Survey (UKIDSS) data to identify and classify the young stellar objects (YSOs). We identified 232 Class 0/I YSOs, 907 Class II YSOs, and 74 transition disk candidate objects using color–color and color–magnitude diagrams. In addition, to understand the evolution of star formation in W49, we analyzed the distribution of YSOs in the region to identify clusters using a minimal spanning tree method. The fraction of YSOs that belong to clusters with ≥7 members is found to be 52% for a cutoff distance of 96″, and the ratio of Class II/I objects is 2.1. We compared the W49 region to the G305 and G333 star-forming regions and concluded that W49 has the richest population, with seven subclusters of YSOs.
Predicting enzyme substrate chemical structure with protein language models

The number of unannotated or orphan enzymes vastly outnumber those for which the chemical structure of the substrates are known. While a number of enzyme function prediction algorithms exist, these often predict Enzyme Commission (EC) numbers or enzyme family, which limits their ability to generate experimentally testable hypotheses. Here, we harness protein language models, cheminformatics, and machine learning classification techniques to accelerate the annotation of orphan enzymes by predicting their substrate’s chemical structural class. We use the orphan enzymes of Mycobacterium tuberculosis as a case study, focusing on two protein families that are highly abundant in its proteome: the short-chain dehydrogenase/reductases (SDRs) and the S-adenosylmethionine (SAM)-dependent methyltransferases. Training machine learning classification models that take as input the protein sequence embeddings obtained from a pre-trained, self-supervised protein language model results in excellent accuracy for a wide variety of prediction tasks. These include redox cofactor preference for SDRs; small-molecule vs. polymer (i.e. protein, DNA or RNA) substrate preference for SAM-dependent methyltransferases; as well as more detailed chemical structural predictions for the preferred substrates of both enzyme families. We then use these trained classifiers to generate predictions for the full set of unannotated SDRs and SAM-methyltransferases in the proteomes of M. tuberculosis and other mycobacteria, generating a set of biochemically testable hypotheses. Our approach can be extended and generalized to other enzyme families and organisms, and we envision it will help accelerate the annotation of a large number of orphan enzymes. Graphical abstract
Scattering of evanescent wave by two cylinders near a flat boundary

The two-dimensional problem of the evanescent wave scattering by dielectric or metallic cylinders near the interface between two dielectric media is solved. A semianalytical method involving a special Green function and a numerical solution of the boundary integral equations is proposed. A configuration with a circular and a prolate elliptic cylinders is suggested to simulate the sample and the probe in near-field optical microscopy. The far-field energy flux through the probe is calculated as a function of its position. The oscillations of the signal are interpreted as a result of the interference between evanescent and cylindrical waves.
An Intersectional Approach to Sex Therapy: Centering the Lives of Black, Indigenous, Racialized, and People of Color

case studies are deep, moving, and accessible. Her writing is clear, intelligent, and personal. It is not difficult to see how the unspoken traumas of our ancestors find their way into the psyche of future generations resulting in a succession of painful and problematic relationships, both sexual and non-sexual. Atlas skillfully guides the reader through an understanding of the legacy of intergenerational trauma and the process of finding a path toward breaking the cycle of transmission and finding emotional solace. This is Atlas’ most accessible book. Her earlier books, while similarly insightful and clinically wise, were much more heavily steeped in psychological theory and conceptualization. The writing in her earlier texts rendered them appealing primarily to a professional audience with a psychodynamic bent. Atlas, however, has the atypical ability to write lucidly for both professional and lay audiences. In addition to receiving wide-ranging praise for her earlier, theoretically weighty texts, she has received numerous accolades for her inviting, tender, reader-friendly New York Times columns. Her current book follows a style much like those columns. Rich with clinical wisdom, this book is highly readable and welcoming to professional and nonprofessional audiences. Therapists will find this book of great interest and value, while also being able to comfortably recommend it to their patients struggling with the traumatic inheritance from their parents and grandparents. I recommend this book highly and have already begun suggesting it to my patients.
A deterministic iterative algorithm for HMRF-textured image segmentation

The problem of textured image segmentation is considered. A textured image is modeled by a hierarchical Markov random field (HMRF). The image segmentation is realized as the maximum a posteriori (MAP) estimate of the textured regions. Following an argument based on the mean field approximation, a deterministic iterative algorithm is proposed which searches for the MAP segmentation of the textured image.
Pomeranchuk instability and Bose condensation of scalar quanta in a Fermi liquid

We study excitations in a normal Fermi liquid with a local scalar interaction. Spectrum of bosonic scalar-mode excitations is investigated for various values and momentum dependence of the scalar Landau parameter $f_0$ in the particle-hole channel. For $f_0 >0$ the conditions are found when the phase velocity on the spectrum of the zero sound acquires a minimum at a non-zero momentum. For $-1 0$.
Monopoles in ferromagnetic metals

The aim of this short review is to give an introduction to monopoles and to present theoretical derivation of two particular monopoles in ferromagnetic metals, a hedgehog monopole and a spin-damping monopole. In electromagnetism in the vacuum, described by Maxwell’s equations, the magnetic field and the electric field are not symmetric, because there is no monopole, a particle having a finite magnetic charge. Still the monopole has been an exciting object for a long time and was discussed on phenomenological grounds by Dirac in 1931. A theoretical possibility of monopole generation was first given by’ t Hooft and Polyakov in 1974 in the context of symmetry breaking in a grand unified theory (GUT), but a GUT monopole has not been discovered in experiments so far. In contrast to in the vacuum, several kinds of monopoles are expected to emerge in solids associated with various symmetry-breaking mechanisms. Of particular interest is metallic ferromagnetic systems, because a breaking of the symmetry of conduction electron spin, described by an SU(2) algebra, can give rise to monopoles. Indeed, two monopoles are theoretically predicted in ferromagnets; one is a hedgehog monopole arising from a topological spin structure, and the other is a spin-damping monopole arising from spin damping in the presence of the spin-orbit interaction. In this paper, we focus on these monopoles, while other objects similar to monopoles, but not coupled to effective electromagnetic fields, such as spin ice monopoles, are touched only briefly in the introduction. These monopoles are extended objects coupled to effective electromagnetic fields that are described by Maxwell’s equations with a monopole contribution. The effective fields are the ones coupled to the spin of a particle such as an electron, muon and neutron; the two monopoles are, thus, detectable by electric measurements. Spin-damping monopoles can be generated in simple systems such as junctions of ferromagnets and heavy elements with strong spin-orbit interaction such as Pt. The spin-damping monopole is essential in coupling electronics with magnetism and is, thus, expected to play an essential role in spintronics.
Visualizing Cooper pair formation on the atomic scale in high temperature superconductors

In the quest for a microscopic theory for the superconductivity in cuprates, one hotly debated issue is the temperature at which Cooper pairs first form. Do pairs form at the critical temperature Tc or do they form at higher temperatures lacking phase rigidity? To answer the question, we have developed new techniques, based on scanning tunneling microscopy, to visualize the process of the pair formation on the atomic scale. The magnitude of the low-temperature superconducting gap measured in Bi2Sr2CaCu2O8+δ shows a large nanoscale spatial variation. These superconducting gaps evolve smoothly with temperature and close locally over a range of temperatures above the superconducting transition temperature Tc. Our results provide evidence that pairing first occurs in nanoscale regions above the bulk superconducting transition temperature. Using the ability to track the same atomic position while changing the temperature, we have examined the evolution of the electronic states from well below Tc to above the temperature at which the pairs first form. Our technique allows us to investigate another fundamental question on the pairing mechanism: Is pairing mediated by a bosonic excitation, as in conventional BCS superconductors, or is pairing an unavoidable consequence of the strong Coulomb repulsion in these compounds? We quantitatively analyze the temperature evolution of the gap and the local electron-boson coupling for various atomic sites with different pairing strengths. We observe that the gap magnitude variation is not determined by the electron-boson coupling but instead it is strongly correlated to variations present in the normal (ungapped) electronic states.