bluuebunny/crossref_metadata_2025 huggingface dataset:
The ancient Z-DNA and Z-RNA specific Zα fold has evolved modern roles in immunity and transcription through the natural selection of flipons
Authors: Herbert Alan
Published: June 2024

The Zα fold specifically binds to both Z-DNA and Z-RNA, left-handed nucleic acid structures that form under physiological conditions and are encoded by flipons. I trace the Zα fold back to unicellular organisms representing all three domains of life and to the realm of giant nucleocytoplasmic DNA viruses (NCVs). The canonical Zα fold is present in the earliest known holozoan unicellular symbiont
Capsaspora owczarzaki
and persists in vertebrates and some invertebrates, but not in plants or fungi. In metazoans, starting with porifera, Zα is incorporated into the double-stranded RNA editing enzyme ADAR and reflects an early symbiont relationship with NCV. In vertebrates, Zα is also present in ZBP1 and PKZ proteins that recognize host-derived Z-RNAs to defend against modern-day viruses. A related Zα fold, also likely to bind Z-DNA, is present in proteins thought to modulate gene expression, including a subset of prokaryote arsR proteins and the p15 (PC4) family present in algae. Other Zα variants that probably play a more general role in the reinitiation of transcription include the archaeal and human transcription factor E and the human RNA polymerase 3 subunit C proteins. The roles in immunity and transcription underlie the natural selection of flipons.
Identifying prey capture events of a free-ranging marine predator using bio-logger data and deep learning
Authors: Schoombie Stefan , Jeantet Lorène , Chimienti Marianna , Sutton Grace J. , Pistorius Pierre A. , Dufourq Emmanuel , Lowther Andrew D. , Oosthuizen W. Chris
Published: June 2024

Marine predators are integral to the functioning of marine ecosystems, and their consumption requirements should be integrated into ecosystem-based management policies. However, estimating prey consumption in diving marine predators requires innovative methods as predator–prey interactions are rarely observable. We developed a novel method, validated by animal-borne video, that uses tri-axial acceleration and depth data to quantify prey capture rates in chinstrap penguins (
Pygoscelis antarctica
). These penguins are important consumers of Antarctic krill (
Euphausia superba
), a commercially harvested crustacean central to the Southern Ocean food web. We collected a large data set (
n
= 41 individuals) comprising overlapping video, accelerometer and depth data from foraging penguins. Prey captures were manually identified in videos, and those observations were used in supervised training of two deep learning neural networks (convolutional neural network (CNN) and V-Net). Although the CNN and V-Net architectures and input data pipelines differed, both trained models were able to predict prey captures from new acceleration and depth data (linear regression slope of predictions against video-observed prey captures = 1.13;
R
2
≈ 0.86). Our results illustrate that deep learning algorithms offer a means to process the large quantities of data generated by contemporary bio-logging sensors to robustly estimate prey capture events in diving marine predators.
Managing disclosure outcomes in intelligence interviews
Authors: Neequaye David A. , Luke Timothy J. , Kollback Kristina
Published: June 2024

We introduce the disclosure-outcomes management model. The model views disclosure in intelligence interviews as a behaviour interviewees use to profitably navigate self-interest dilemmas. We theorized that interviewees compare the potential outcomes of disclosing to their self-interests. They evaluate the extent to which disclosure will facilitate or impede those self-interests: an interviewee’s self-interest dilemma elicits cooperation with respect to some information but not other information. A Preliminary Study (
N
= 300) supported the model’s predictions. We proposed a Replication Study (
N
= 369) to examine the model further. Participants assumed the role of an intelligence source undergoing an interview. They decided what information to disclose, contending the typical dilemma in an intelligence interview wherein disclosure could jeopardize or advance their self-interests. The results from the Preliminary and Replication studies were broadly in line with our proposition: perceived benefits positively influenced the likelihood of disclosing. However, a negative interaction between costs and benefits observed in the Preliminary Study did not replicate. That finding may be due to power constraints, not evidence against the existence of an interaction effect. Our proposal that—generally speaking—interviewees are likelier to disclose information units that seem less versus more risky requires further examination. Individual-level sensitivity to benefits, costs and their co-occurrence varied substantially in our studies. We discuss avenues for future research.
Evolution of reciprocity with limited payoff memory
Authors: Glynatsi Nikoleta E. , McAvoy Alex , Hilbe Christian
Published: June 2024

Direct reciprocity is a mechanism for the evolution of cooperation in repeated social interactions. According to the literature, individuals naturally learn to adopt conditionally cooperative strategies if they have multiple encounters with their partner. Corresponding models have greatly facilitated our understanding of cooperation, yet they often make strong assumptions on how individuals remember and process payoff information. For example, when strategies are updated through social learning, it is commonly assumed that individuals compare their average payoffs. This would require them to compute (or remember) their payoffs against everyone else in the population. To understand how more realistic constraints influence direct reciprocity, we consider the evolution of conditional behaviours when individuals learn based on more recent experiences. Even in the most extreme case that they only take into account their very last interaction, we find that cooperation can still evolve. However, such individuals adopt less generous strategies, and they cooperate less often than in the classical setup with average payoffs. Interestingly, once individuals remember the payoffs of two or three recent interactions, cooperation rates quickly approach the classical limit. These findings contribute to a literature that explores which kind of cognitive capabilities are required for reciprocal cooperation. While our results suggest that some rudimentary form of payoff memory is necessary, it suffices to remember a few interactions.
Mutations in yeast are deleterious on average regardless of the degree of adaptation to the testing environment
Authors: Bao Kevin , Strayer Brant R. , Braker Neil P. , Chan Alexandra A. , Sharp Nathaniel P.
Published: June 2024

The role of spontaneous mutations in evolution depends on the distribution of their effects on fitness. Despite a general consensus that new mutations are deleterious on average, a handful of mutation accumulation experiments in diverse organisms instead suggest that beneficial and deleterious mutations can have comparable fitness impacts, i.e. the product of their respective rates and effects can be roughly equal. We currently lack a general framework for predicting when such a pattern will occur. One idea is that beneficial mutations will be more evident in genotypes that are not well adapted to the testing environment. We tested this prediction experimentally in the laboratory yeast
Saccharomyces cerevisiae
by allowing nine replicate populations to adapt to novel environments with complex sets of stressors. After >1000 asexual generations interspersed with 41 rounds of sexual reproduction, we assessed the mean effect of induced mutations on yeast growth in both the environment to which they had been adapting and the alternative novel environment. The mutations were deleterious on average, with the severity depending on the testing environment. However, we found no evidence that the adaptive match between genotype and environment is predictive of mutational fitness effects.
Identification and genetic analysis of a pervasive ‘needle-eye’ sperm phenotype in
Drosophila
sterile hybrid males
Authors: Kanippayoor Rachelle L. , Soeder Charles , Hsiang Tom , Jones Corbin D. , Moehring Amanda J.
Published: June 2024

Interspecies hybrid sterility has been extensively studied, especially in the genus
Drosophila
. Hybrid sterility is more often found in the heterogametic (XY or ZW) sex, a trend called Haldane’s rule. Although this phenomenon is pervasive, identification of a common genetic mechanism remains elusive, with modest support found for a range of potential theories. Here, we identify a single precise morphological phenotype, which we call ‘needle-eye sperm’, that is associated with hybrid sterility in three separate species pairs that span the
Drosophila
genus. The nature of the phenotype indicates a common point of meiotic failure in sterile hybrid males. We used 10 generations of backcross selection paired with whole-genome pooled sequencing to genetically map the regions underlying the needle-eye (NE) sperm phenotype. Surprisingly, the sterility phenotype was present in ~50% of males even after 10 generations of backcrossing, and only a single region of the X chromosome was associated with sterility in one direction of backcross. Owing to the common phenotype among sterile male hybrids
,
and the strong effect of individual loci, further exploration of these findings may identify a universal mechanism for the evolution of hybrid sterility.
Lorenz’s classic ‘baby schema’: a useful biological concept?
Authors: Kawaguchi Yuri , Waller Bridget M.
Published: June 2024

Konrad Lorenz introduced the concept of a ‘baby schema’, suggesting that infants have specific physical features, such as a relatively large head, large eyes and protruding cheeks, which function as an innate releaser to promote caretaking motivation from perceivers. Over the years, a large body of research has been conducted on the baby schema. However, there are two critical problems underpinning the current literature. First, the term ‘baby schema’ lacks consistency among researchers. Some researchers use the term baby schema to refer to infant stimuli (often faces) in comparison with adults (
categorical usage
), while others use the term to refer to the extent that features contribute to cuteness perception (
spectrum usage
). Second, cross-species continuity of the ‘baby schema’ has been assumed despite few empirical demonstrations. The evolutionary and comparative relevance of the concept is, therefore, debatable, and we cannot exclude the possibility that extreme sensitivity to the baby schema is a uniquely human trait. This article critically reviews the state of the existing literature and evaluates the significance of the baby schema from an evolutionary perspective.
Costs of antibiotic resistance genes depend on host strain and environment and can influence community composition
Authors: Lai Huei-Yi , Cooper Tim F.
Published: June 2024

Antibiotic resistance genes (ARGs) benefit host bacteria in environments containing corresponding antibiotics, but it is less clear how they are maintained in environments where antibiotic selection is weak or sporadic. In particular, few studies have measured if the direct effect of ARGs on host fitness is fixed or if it depends on the host strain, perhaps marking some ARG–host combinations as selective refuges that can maintain ARGs in the absence of antibiotic selection. We quantified the fitness effects of six ARGs in 11 diverse
Escherichia
spp. strains. Three ARGs
(bla
TEM-116
,
cat
and
dfrA5
, encoding resistance to β-lactams, chloramphenicol, and trimethoprim, respectively) imposed an overall cost, but all ARGs had an effect in at least one host strain, reflecting a significant strain interaction effect. A simulation predicts these interactions can cause the success of ARGs to depend on available host strains, and, to a lesser extent, can cause host strain success to depend on the ARGs present in a community. These results indicate the importance of considering ARG effects across different host strains, and especially the potential of refuge strains to allow resistance to persist in the absence of direct selection, in efforts to understand resistance dynamics.
Half of global islands have reached critical area thresholds for undergoing rapid increases in biological invasions
Authors: Li Yanxia , Wang Yanping , Liu Xuan
Published: June 2024

Biological invasions are among the threats to global biodiversity and social sustainability, especially on islands. Identifying the threshold of area at which non-native species begin to increase abruptly is crucial for early prevention strategies. The small-island effect (SIE) was proposed to quantify the nonlinear relationship between native species richness and area but has not yet been applied to non-native species and thus to predict the key breakpoints at which established non-native species start to increase rapidly. Based on an extensive global dataset, including 769 species of non-native birds, mammals, amphibians and reptiles established on 4277 islands across 54 archipelagos, we detected a high prevalence of SIEs across 66.7% of archipelagos. Approximately 50% of islands have reached the threshold area and thus may be undergoing a rapid increase in biological invasions. SIEs were more likely to occur in those archipelagos with more non-native species introduction events, more established historical non-native species, lower habitat diversity and larger archipelago area range. Our findings may have important implications not only for targeted surveillance of biological invasions on global islands but also for predicting the responses of both non-native and native species to ongoing habitat fragmentation under sustained land-use modification and climate change.
Novel sex-biased outcomes in neuroblastoma are associated with distinct gene expression and chromosomal loss patterns
Authors: Patel Vishwa , Raleigh Mariya , Benhamou Lorraine-Rana E. , Shen Xin , Espinosa Erika C. , Badi Niharika R. , Sheeter Dennis A. , Powers John T.
Published: June 2024

The worst patient outcomes in neuroblastoma are driven by high-risk disease1,2, which is divided into similarly sizedMYCNamplified andMYCNnon-amplified patient subgroups3. Male patients have been reported to have slightly worse outcomes than females in all-patient analyses of multiple studies3,4. However, we show here that inMYCNnon- amplified high-risk and stage 4s low-risk disease, female patients have significantly worse overall survival than males. FemaleMYCNnon-amplified high-risk patients highly expressH19andDLK1, both of which drive cell growthin vitroand are associated with worse outcomes in females but not males. Further, chromosome-specific expression analysis of these patients reveals broad sex disparities in chromosomal patterning, including female-specific retention of chromosome 11q, a pattern typically reserved forMYCN-amplified disease5,6. Finally, we show thatH19, a knownlet-7microRNA target7, sequesterslet-7in females, providing a rationale for worse female survival and reconciling retention of chromosome 11q. We propose that this novel sex-based outcome disparity is driven bylet-7inhibition, expanding on a model of neuroblastoma development wherelet-7mitigation is central to disease pathology8.
The ecology of potentially pathogenicVibriospp. in a seagrass meadow ecosystem
Authors: Gebbe Rebecca , Kesy Katharina , Hallier Dorothea , Brauer Anne , Bertilsson Stefan , Labrenz Matthias , Bengtsson Mia M.
Published: June 2024

Seagrass meadow ecosystems offer several valuable ecosystem services in coastal regions around the world. Recent studies have suggested that one such important service is reduction of pathogenic bacteria and specificallyVibriospp. in adjacent waters. The specific mechanisms of pathogen reduction remain unclear, although increased sedimentation has been suggested as one likely process for pathogens to be quenched from the water column. WhetherVibriospp. persist in the sediment or in other compartments of the seagrass meadow is currently not known, but it has been shown that marine surface biofilms can function as reservoirs of pathogenic vibrios. This general feature may also apply to seagrass and sediment surfaces. In this study, we investigated the relative abundance and community ecology ofVibriospp. bacteria in Baltic Sea seagrass meadows using both culturing and culture-independent methods. While we did not detect a significant reduction ofVibriospp., the highest relative abundances ofVibriospp. were observed in the water column above unvegetated sites as compared to seagrass meadows. We also detected high relative abundances ofVibriospp. on seagrass roots, supporting previous observations that marine surfaces are selectively colonized byVibriospp., implying that these habitats are important for the persistence and possibly release ofVibriospp. into the water column. Our results emphasize the need to understand the interactions of pathogenic bacteria with coastal habitats, including interactions with host organisms such as seagrasses that provide biofilm microenvironments, in order to understand how diseases associated with these organisms develop.
Automated Dentate Nucleus Segmentation from QSM Images Using Deep Learning
Authors: Shiraishi Diogo H , Saha Susmita , Adanyeguh Isaac M , Cocozza Sirio , Corben Louise A , Deistung Andreas , Delatycki Martin B , Dogan Imis , Gaetz William , Georgiou-Karistianis Nellie , Graf Simon , Grisoli Marina , Henry Pierre-Gilles , Jarola Gustavo M , Joers James M , Langkammer Christian , Lenglet Christophe , Li Jiakun , Lobo Camila C , Lock Eric F , Lynch David R , Mareci Thomas H , Martinez Alberto R M , Monti Serena , Nigri Anna , Pandolfo Massimo , Reetz Kathrin , Roberts Timothy P , Romanzetti Sandro , Rudko David A , Scaravilli Alessandra , Schulz Jörg B , Subramony S H , Timmann Dagmar , França Marcondes C , Harding Ian H , Rezende Thiago J R ,   TRACK-FA Neuroimaging Consortium
Published: June 2024

Purpose

To develop a dentate nucleus (DN) segmentation tool using deep learning (DL) applied to brain quantitative susceptibility mapping (QSM) images.

Materials and Methods

Brain QSM images from 132 healthy controls and 170 individuals with cerebellar ataxia or multiple sclerosis were collected from nine different datasets worldwide for this retrospective study. Manual delineation of the DN (gray matter and white matter hilus) was first undertaken by experienced raters with a robust quality control process. Performance of automated segmentation was compared following training using several DL architectures. A two-step approach was implemented, composed of a localization model followed by DN segmentation.

Results

The manual tracing protocol produced ground-truth data with high intra-rater (average ICC 0.906) and inter-rater reliability (average ICC 0.776). Initial DL architecture exploration indicated that the nnU-Net framework performed best. The two-step localization plus segmentation pipeline achieved a Dice score of 0.898±0.031 and 0.894±0.036 for left and right DN, respectively. In external validation, our algorithm outperformed the leading existing automated tool (left/right DN Dice 0.863±0.038/0.843±0.066 vs. 0.568±0.222/0.582±0.239). The model demonstrated generalizability across unseen datasets during the training step. The measures showed a superior correlation index with manual annotations and performed well in both isotropic and anisotropic QSM datasets.

Conclusion

We provide a model that accurately and efficiently segments the DN from brain QSM images. The model can be readily deployed for use in observational, natural history, and treatment trials for biomarker discovery.
Optimal mix of differentiated service delivery models for HIV treatment in Zambia: a mathematical modelling study
Authors: Lekodeba Nkgomeleng , Rosen Sydney , Phiri Bevis , Masuku Sithabiso , Govathson Caroline , Kamanga Aniset , Haimbe Prudence , Shakwelele Hilda , Mwansa Muya , Lumano-Mulenga Priscilla , Huber Amy , Pascoe Sophie , Jamieson Lise , Nichols Brooke E
Published: June 2024

Background

Zambia has scaled up differentiated service delivery (DSD) models for antiretroviral treatment (ART) to provide more client-centric care and increase service delivery efficiency. The current DSD landscape includes multiple models of care based on guidelines, resources, partner inputs, and other factors. We used local data to identify cost-effective combinations of DSD models that will maximize benefits and/or minimize costs to guide future DSD expansion.

Methods

We developed a mathematical Excel-based model using retrospective retention and viral suppression data from a national cohort of ART clients (≥15 years) between January 2018-March 2022 stratified by age, sex, setting (urban/rural), and model of ART delivery. Outcomes (viral suppression and retention in care), provider costs, and costs to clients for each model were estimated from the cohort and previously-published data. For different combinations of the nine DSD models in use, we evaluated the incremental cost to the health system per additional ART client virally suppressed on treatment compared to the 2022 base case.

Results

Of the 125 combinations of DSD models evaluated, six were on the cost-effectiveness frontier (CEF): 1) six-month dispensing (6MMD)-only; 2) 6MMD and adherence groups (AGs); 3) AGs-only; 4) fast track refills (FTRs) and AGs; 5) FTRs-only; and 6) AGs and home ART delivery. 6MMD-only was cost-saving compared to the base case, increased the proportion of clients virally suppressed by 1.6%, and decreased costs to clients by 16.6%. The next two scenarios on the CEF, 6MMD+AGs and AGs-only, each cost an additional $245 per person virally suppressed, increased the total number of individuals suppressed on treatment by 2.8% and 4.8%, respectively, and increased costs to clients by 63% and 143%, respectively.

Conclusions

Mathematical modelling using existing data can identify cost-effective mixes of DSD models and allocations of clients to these models, while ensuring that all client sub-populations are explicitly considered. In Zambia, providing 6MMD to all eligible clients is likely to be cost-saving, while health outcomes can be improved by allocating clients to selected models based on sub-population.
The impact on clinical success from the 23andMe cohort
Authors: Wang Xin , Karagounis Sotiris , Shringarpure Suyash S. , Srivas Rohith , Su Qiaojuan Jane ,   23andMe Research Team, Vacic Vladimir , Pitts Steven J. , Auton Adam
Published: June 2024

90% of therapeutic programs that enter clinical trials ultimately fail. Human genetic variation provides a set of “natural experiments” that can inform successful strategies for therapeutic discovery. Previous work has estimated that drug targets with human genetics supported mechanisms have a 2-3x increased likelihood of succeeding in the clinic compared to those without. 23andMe, Inc. is a direct-to-consumer genetics company that has created a human genetics dataset approximately an order of magnitude larger in sample size than current publically available cohorts. As of 2024, 23andMe has approximately 15 million individuals with genotype and phenotype data, of which ∼80% consent to participation in research. In this work, we explore how both the scale of the genetic data and improved methods to link genetic associations to putative causal genes impact the prediction of clinical success. Comparing the total number of target-indication pairs that have reached at least phase I that are also supported by genetic evidence, the number of target-indication pairs with support from 23andMe is 60% greater than that with support from all GWAS datasets in the public domain. Including 23andMe genetic evidence approximately doubles the number of target-indication pairs in the clinic that are supported by human genetics. Furthermore, we show that genetic associations derived from entirely self-reported phenotypes are 2-3x enriched for clinical success, just as for clinically derived phenotypes. In contrast to conclusions from the recent publication of Minikelet al., we found that minor allele frequencies and effect sizes from GWAS influence the relative success estimates for program approvals, and that drug programs supported by rare and large effect associations have greater (3-4x) likelihood to be approved compared to common variant associations with small effects. Finally, improved gene mapping to identify the likely causal genes underlying genetic associations can result in up to 4-5x enrichment for trial success. With the increased power and scale of the 23andMe genetic dataset, we identify an expansive set of opportunities that may be pursued in the clinic, emphasizing the importance of cohort size and gene mapping confidence in deriving clinical value.
Computational pipeline for targeted integration and variable payload expression for bacteriophage engineering
Authors: Fernbach Jonas , Hegedis Emese , Loessner Martin J. , Kilcher Samuel
Published: June 2024

Bacteriophages offer a promising alternative to conventional antimicrobial treatments, particularly in cases where such treatments have proven ineffective. While naturally occurring phages serve as viable options for phage therapy, advances in synthetic biology and genome engineering enable precise modifications to phages to enhance their therapeutic potential. One such approach is the introduction of antimicrobial genetic payloads into the phage genome. Conventional practice is to integrate such payloads behind genes expressed at very high levels late in the infection cycle, such as the major capsid gene (cps). Nevertheless, phages engineered to contain antimicrobial payloads are often difficult to obtain. For instance, the high expression of toxic payloads can prematurely halt host metabolism, leading to the failure in assembling viable phage progeny. To potentially expand the range of genes viable as genetic payloads, we developed a method to identify intergenic loci with favorable expression levels. We used the machine learning (ML)-based promoter prediction algorithm PhagePromoter to identify these loci. We then used this information to design a computationally-assisted engineering pipeline for the integration of genomic payloads at these locations. We validated our approach experimentally, engineering phages with bioluminescent reporter payloads at various predicted loci. We used the well characterized, strictly lytic,Staphylococcus aureus-infecting bacteriophage, K, as an engineering scaffold and employed homologous recombination to engineer three recombinant phages containing the reporter payload at different predicted loci throughout the genome. The recombinant phages exhibited expression levels consistent with our computational predictions and showed temporal expression patterns corresponding to their genomic locations in early, middle, or late gene clusters. Our study underscores the potential of integrating computational tools with classical sequence analysis to streamline the phage engineering process. This approach not only facilitates the rational design of phages with targeted payload insertions but also paves the way for high-throughput, automated phage engineering, fostering a new era of personalized phage therapy.
How the brain learns to parse images using an attentional, incremental grouping process
Authors: Mollard Sami , Bohte Sander M. , Roelfsema Pieter R.
Published: June 2024

Natural scenes usually contain a vast number of objects that need to be segmented and segregated from each other and from the background to guide behaviour. In the visual brain, object-based attention is the process by which image fragments belonging to the same objects are grouped together. The curve-tracing task is a special case of a perceptual grouping task that tests our ability to group image elements of an elongated curve. The task consists in determining which image elements belong to the same curve, and in the brain, neurons spread an enhanced activity level over the representation of the relevant curve. A previous “growth-cone model of attention” accounted for the scale invariance of tracing by proposing that the enhanced activity propagates at multiple levels of the visual cortical hierarchy. However, the precise neuronal circuitry for learning and implementing scale-invariant tracing remains unknown. We propose a new recurrent architecture for the scale-invariant labelling of curves and objects. The architecture is composed of a feedforward pathway that dynamically selects the right scale and prevents the spilling over of the enhanced activity to other curves, and a recurrent pathway for tag spreading that involves horizontal and feedback interactions, mediated by a disinhibitory loop involving VIP and SOM interneurons. We trained the network with curves up to seven pixels long using reinforcement learning and a learning rule local in time and space and we found that it generalized to curves of any length and to spatially extended objects. The network chose the appropriate scale and switched to higher or lower scales as dictated by the distance between curves, just has as been observed in human psychophysics and in the visual cortex of monkeys. Our work provide a mechanistic account of the learning of scale-invariant perceptual grouping in the brain.

Significance Statement

Objects are labelled and grouped in the visual cortex via a tag of enhanced activity. If the scale-invariant dynamics of propagations of this tag are well characterised, it remains unknown what neural architectures and learning rules can produce those dynamics. This work is the first to propose a neural architecture trained with reward that give rises to the same dynamics observed in monkeys’ visual cortex or human reaction times, shedding light on the mechanisms of multiscale object-based attention in the visual cortex.
Myogenic dedifferentiation involves a p53-dependent reorganization of PLK4 localization during centrosome regeneration
Authors: Subramanian Elaiyaraja , Brito Gonçalo , Kumar Anoop , Kirkham Matthew , Simon András
Published: June 2024

Multinucleated skeletal muscle cells are stably withdrawn from the cell cycle in most vertebrates. Muscle dedifferentiation is however naturally occurring during limb regeneration in newts and can be artificially induced in mammalian myotubes. Dedifferentiation involves fragmentation of myofibers and myotubes into mononucleate cells which subsequently reenter the cell cycle, and give rise to proliferative progeny. Here we addressed the dynamics of centrosomes, which are key organelles for cell proliferation during myogenic differentiation and dedifferentiation. We show that, in contrast to their mammalian counterparts, newt muscle cells retain centrosomes during differentiation and demonstrate that regeneration of centrosomes in dedifferentiated mouse muscle cells depends on inhibition of the tumor suppressor p53. We also find that regulation of the subcellular localization of Polo-Like Kinase 4 rather than its expression level is a hallmark of myogenic differentiation and dedifferentiation, identifying a novel cellular process underlying the plasticity of the differentiated state.
The spatial layout of antagonistic brain regions is explicable based on geometric principles
Authors: Leech Robert , Braga Rodrigo M , Haydock David , Vowles Nicholas , Jefferies Elizabeth , Bernhardt Boris , Turkheimer Federico , Alberti Francesco , Margulies Daniel , Sherwood Oliver , Jones Emily JH , Smallwood Jonathan , Váša František
Published: June 2024

Brain activity emerges in a dynamic landscape of regional increases and decreases that span the cortex. Increases in activity during a cognitive task are often assumed to reflect the processing of task-relevant information, while reductions can be interpreted as suppression of irrelevant activity to facilitate task goals. Here, we explore the relationship between task-induced increases and decreases in activity from a geometric perspective. Using a technique known as kriging, developed in earth sciences, we examined whether the spatial organisation of brain regions showing positive activity could be predicted based on the spatial layout of regions showing activity decreases (and vice versa). Consistent with this hypothesis we established the spatial distribution of regions showing reductions in activity could predict (i) regions showing task-relevant increases in activity in both groups of humans and single individuals; (ii) patterns of neural activity captured by calcium imaging in mice; and, (iii) showed a high degree of generalisability across task contexts. Our analysis, therefore, establishes that antagonistic relationships between brain regions are topographically determined, a spatial analog for the well documented anti-correlation between brain systems over time.

Significance Statement

It is well documented that brain activity changes in response to the demands of different situations, although what gives rise to the observed cortical activity patterns remains poorly understood. Using analytic tools from earth sciences, we examined whether the landscape of regional changes in activity emerge from a set of common topographical causes. Using only regions showing decreases in activity, we could predict the landscape of regions showing increases in activity using fMRI in humans and calcium imaging in mice. Our results suggest topographical principles determine the landscape of peaks and valleys in brain activity -- a spatial analog for the well documented anti-correlation between sets of brain regions over time.
Lack of an atypical PDR transporter generates an immunogenicCryptococcus neoformansstrain that drives a dysregulated and lethal immune response in murine lungs
Authors: Winski Christopher J. , Stuckey Peter V. , Marrufo Armando M. , Ross Robbi L. , Agyei Georgina , Chapman Sarah , Santiago-Tirado Felipe H.
Published: June 2024

Cryptococcus neoformansis an opportunistic fungal pathogen responsible for >150,000 deaths every year with a mortality rate as high as 81%. This high medical burden is due, in part, to an incomplete understanding of its pathogenesis. In a previous study, we identified a cryptococcal atypical pleiotropic drug resistance (PDR) transporter,PDR6, that regulated antifungal resistance and host interactions. Here, we follow-up on the role ofPDR6in cryptococcal virulence.In vivo, mice infected with thepdr6Δ strain display altered symptomatology and disease progression. Specifically, we observed a significant increase in the innate immune cell populations in thepdr6Δ-infected mice when compared to their WT-infected littermates. Furthermore, quantification of pulmonary cytokines/chemokines revealed a robust increase of pro-inflammatory cytokines in mice infected with thepdr6Δ mutant strain. Whereas antifungal treatment ofpdr6Δ-infected animals did not affect survival, treatment with a corticosteroid significantly extended survival, highlighting the importance of a balanced/controlled host immune response. We determined that the hyper-inflammatory immune response occurs, in part, because the loss of the Pdr6 transporter indirectly alters the cryptococcal cell wall architecture and results in the increased exposure of chitin, β-glucan, and other cryptococcal-specific pathogen associated molecular patterns. Taken together, this study provides clinical insights regarding cryptococcal pathogenesis while also providing additional functions of PDR-type ATP-binding cassette (ABC) transporters in pathogenic fungi.

IMPORTANCE

Yeasts of theCryptococcusgenus, especiallyC. neoformans, can cause disease with unacceptably high mortality. This is due to delays in diagnostics, ineffective treatments, and an incomplete understanding of the interactions between this fungus and our immune system. In this study, we expand our knowledge of the biological function of thePDR6gene, particularly its effect on modulating the host’s immune response. Normally,C. neoformans’s infections are characterized by an anti-inflammatory response that is unable to control the yeast. In the absence ofPDR6, the response to the infection is a dysregulated pro-inflammatory response that initially controls the fungi but eventually results in death of the host due to too much tissue damage. This is due, in part, to an altered fungal surface. Given the dual role ofPDR6in modulating antifungal sensitivity and immune responses, this work provides important insights that may lead to new or improved therapeutics.
In-vitroresensitization of multidrug resistant clinical isolates ofEnterococcus faeciumandfaecalisthrough phage-antibiotic synergy
Authors: Ghatbale Pooja , Sah Govind Prasad , Dunham Sage , Khong Ethan , Blanc Alisha , Monsibais Alisha , Garcia Andrew , Schooley Robert T. , Cobián Güemes Ana G. , Whiteson Katrine , Pride David T.
Published: June 2024

Bacteriophages are an increasingly attractive option for the treatment of antibiotic resistant infections, but their efficacy is difficult to discern due to confounding effects of antibiotics. Phages are generally delivered in conjunction with antibiotics, and thus, when patients improve it’s unclear whether the phages, antibiotics or both are responsible. This question is particularly relevant for enterococcus infections, as limited data suggest phages might restore antibiotic efficacy against resistant strains. Enterococci can develop high-level resistance to vancomycin, a primary treatment. We assessed clinical and laboratory isolates ofEnterococcus faeciumandEnterococcus faecalisto determine whether we could observe synergistic interactions between phages and antibiotics. We identified synergy between multiple phages and antibiotics including linezolid, ampicillin, and vancomycin. Notably, antibiotic susceptibility did not predict synergistic interactions with phages. Vancomycin resistant isolates (n=6) were eradicated by the vancomycin-phage combination as effectively as vancomycin susceptible isolates (n=2). Transcriptome analysis revealed significant gene expression changes under antibiotic-phage conditions, especially for linezolid and vancomycin, with upregulated genes involved in nucleotide and protein biosynthesis and downregulated stress response and prophage-related genes. While our results do not conclusively determine the etiology of the observed synergistic interactions between antibiotics and phages, they do confirm and build upon previous research that observed these synergistic interactions. Our work highlights how using phages can restore the effectiveness of vancomycin against resistant isolates. This finding provides a promising, although unexpected, strategy for moving forward with phage treatments for Vancomycin Resistant Enterococcus infections.
Semi-Inclusive Deep-Inelastic Scattering at Next-to-Next-to-Leading Order in QCD
Authors: Bonino Leonardo , Gehrmann Thomas , Stagnitto Giovanni
Published: June 2024

Semi-inclusive hadron production processes in deep-inelastic lepton-nucleon scattering are important probes of the quark flavor structure of the nucleon and of the fragmentation dynamics of quarks into hadrons. We compute the full next-to-next-to-leading order QCD corrections to the coefficient functions for semi-inclusive deep-inelastic scattering in analytical form. The numerical impact of these corrections for precision physics is illustrated by a detailed comparison with data on single inclusive hadron spectra from the CERN COMPASS experiment.

Published by the American Physical Society
2024
Student understanding of eigenvalue equations in quantum mechanics: Symbolic blending and sensemaking analysis
Authors: Piña A. R. , Topdemir Zeynep , Thompson John R.
Published: June 2024

As part of an effort to examine students’ mathematical sensemaking (MSM) in a spins-first quantum mechanics course during the transition from discrete (spin) to continuous (position) systems, students were asked to construct an eigenvalue equation for a one-dimensional position operator. A subset of responses took the general form of an eigenvalue equation written in Dirac notation. Symbolic blending, a combination of symbolic forms and conceptual blending, as well as a categorical framework for MSM, were used in the analysis. The data suggest two different symbolic forms for an eigenvalue equation that share a symbol template but have distinct conceptual schemata: A transformation that reproduces the original and to operate is to act. These symbolic forms, when blended with two sets of contextual knowledge, form the basis of three different interpretations of eigenvalue equations modeled here as conceptual blends. The analysis in this study serves as a novel example of, and preliminary evidence for, student engagement in sensemaking activities in the transition from discrete to continuous systems in a spins-first quantum mechanics course.

Published by the American Physical Society
2024
Anomalous Fraunhofer-like patterns in quantum anomalous Hall Josephson junctions
Authors: Qi Junjie , Liu Haiwen , Liu Jie , Jiang Hua , Liu Dong E. , Chen Chui-Zhen , He Ke , Xie X. C.
Published: June 2024

The intriguing interplay between topology and superconductivity has attracted significant attention, given its potential for realizing topological superconductivity. In the quantum anomalous Hall insulators (QAHIs)-based junction, the supercurrents are carried by the chiral edge states, characterized by a 2Φ0 magnetic flux periodicity (Φ0=h/2e is the flux quantum, h the Planck constant, and e the electron charge). However, experimental observations indicate the presence of bulk carriers in QAHI samples due to magnetic dopants. In this study, we reveal a systematic transition from edge-state to bulk-state dominant supercurrents as the chemical potential varies from the bulk gap to the conduction band. This results in an evolution from a 2Φ0-periodic oscillation pattern to an asymmetric Fraunhofer pattern. Furthermore, a Fraunhoher-like pattern emerges due to the coexistence of chiral edge states and bulk states caused by magnetic domains, even when the chemical potential resides within the gap. These findings not only advance the theoretical understanding but also pave the way for the experimental discovery of the chiral Josephson effect based on QAHI doped with magnetic impurities.

Published by the American Physical Society
2024
Tracking copper nanofiller evolution in polysiloxane during processing into SiOC ceramic
Authors: Loughney Patricia A. , Cuillier Paul , Pruyn Timothy L. , Doan-Nguyen Vicky
Published: June 2024

Polymer-derived ceramics (PDCs) remain at the forefront of research for a variety of applications including ultra-high-temperature ceramics, energy storage and functional coatings. Despite their wide use, questions remain about the complex structural transition from polymer to ceramic and how local structure influences the final microstructure and resulting properties. This is further complicated when nanofillers are introduced to tailor structural and functional properties, as nanoparticle surfaces can interact with the matrix and influence the resulting structure. The inclusion of crystalline nanofiller produces a mixed crystalline–amorphous composite, which poses characterization challenges. With this study, we aim to address these challenges with a local-scale structural study that probes changes in a polysiloxane matrix with incorporated copper nanofiller. Composites were processed at three unique temperatures to capture mixing, pyrolysis and initial crystallization stages for the pre-ceramic polymer. We observed the evolution of the nanofiller with electron microscopy and applied synchrotron X-ray diffraction with differential pair distribution function (d-PDF) analysis to monitor changes in the matrix's local structure and interactions with the nanofiller. The application of the d-PDF to PDC materials is novel and informs future studies to understand interfacial interactions between nanofiller and matrix throughout PDC processing.
Quantitative selection of sample structures in small-angle scattering using Bayesian methods
Authors: Hayashi Yui , Katakami Shun , Kuwamoto Shigeo , Nagata Kenji , Mizumaki Masaichiro , Okada Masato
Published: June 2024

Small-angle scattering (SAS) is a key experimental technique for analyzing nanoscale structures in various materials. In SAS data analysis, selecting an appropriate mathematical model for the scattering intensity is critical, as it generates a hypothesis of the structure of the experimental sample. Traditional model selection methods either rely on qualitative approaches or are prone to overfitting. This paper introduces an analytical method that applies Bayesian model selection to SAS measurement data, enabling a quantitative evaluation of the validity of mathematical models. The performance of the method is assessed through numerical experiments using artificial data for multicomponent spherical materials, demonstrating that this proposed analysis approach yields highly accurate and interpretable results. The ability of the method to analyze a range of mixing ratios and particle size ratios for mixed components is also discussed, along with its precision in model evaluation by the degree of fitting. The proposed method effectively facilitates quantitative analysis of nanoscale sample structures in SAS, which has traditionally been challenging, and is expected to contribute significantly to advancements in a wide range of fields.
Patching-based deep-learning model for the inpainting of Bragg coherent diffraction patterns affected by detector gaps
Authors: Masto Matteo , Favre-Nicolin Vincent , Leake Steven , Schülli Tobias , Richard Marie-Ingrid , Bellec Ewen
Published: June 2024

A deep-learning algorithm is proposed for the inpainting of Bragg coherent diffraction imaging (BCDI) patterns affected by detector gaps. These regions of missing intensity can compromise the accuracy of reconstruction algorithms, inducing artefacts in the final result. It is thus desirable to restore the intensity in these regions in order to ensure more reliable reconstructions. The key aspect of the method lies in the choice of training the neural network with cropped sections of diffraction data and subsequently patching the predictions generated by the model along the gap, thus completing the full diffraction peak. This approach enables access to a greater amount of experimental data for training and offers the ability to average overlapping sections during patching. As a result, it produces robust and dependable predictions for experimental data arrays of any size. It is shown that the method is able to remove gap-induced artefacts on the reconstructed objects for both simulated and experimental data, which becomes essential in the case of high-resolution BCDI experiments.
Synthesis and crystal structure of bis(2-aminobenzimidazolium) catena-[metavanadate(V)]
Authors: Jabborova Kholida , Ashurov Jamshid , Tojiboev Akmaljon , Daminova Shahlo
Published: June 2024

The structure of polymeric catena-poly[2-aminobenzimidazolium [[dioxidovanadium(V)]-μ-oxido]], {(C7H8N3)2[V2O6]}
n
, has monoclinic symmetry. The title compound is of interest with respect to anticancer activity. In the crystal structure, infinite linear zigzag vanadate (V2O6)2− chains, constructed from corner-sharing VO4 tetrahedra and that run parallel to the a axis, are present. Two different protonated 2-aminobenzimidazole molecules are located between the (V2O6)2– chains and form classical N—H...O hydrogen bonds with the vanadate oxygen atoms, which contribute to the cohesion of the structure.