bluuebunny/crossref_metadata_2025 huggingface dataset:
Age-dependent structural reorganization of utricular ribbon synapses
Authors: Michanski Susann , Henneck Timo , Mukhopadhyay Mohona , Steyer Anna M. , Gonzalez Paola Agüi , Grewe Katharina , Ilgen Peter , Gültas Mehmet , Fornasiero Eugenio F. , Jakobs Stefan , Möbius Wiebke , Vogl Christian , Pangršič Tina , Rizzoli Silvio O. , Wichmann Carolin
Published: December 2022

In mammals, spatial orientation is synaptically-encoded by sensory hair cells of the vestibular labyrinth. Vestibular hair cells (VHCs) harbor synaptic ribbons at their presynaptic active zones (AZs), which play a critical role in molecular scaffolding and facilitate synaptic release and vesicular replenishment. With advancing age, the prevalence of vestibular deficits increases; yet, a direct link to the functional decline of VHC ribbon synapses remains to be demonstrated. To address this issue, we investigated the effects of aging on the ultrastructure of the ribbon-type AZs in murine utricles using various electron microscopic techniques and combined them with confocal and super-resolution light microscopy as well as metabolic imaging up to one year of age. In older animals, we detected predominantly in type I VHCs the formation of floating ribbon clusters. Our findings suggest that VHC ribbon-type AZs undergo dramatic structural alterations upon aging.
Structural characterizations of a unusual peptide CORO1C-47aa encoded by circRNA hsa-circ-0000437 associated with endometrial cancer
Authors: Biswas Sima , Bhagat Gaurav Kumar , Bagchi Angshuman
Published: December 2022

Circular RNAs, which have covalently closed ends, is a special type of non-coding RNAs. Recent studies reveal that they are associated with various biochemical pathways. One such involvements of circular RNAs is in the onset of different types of cancers. Though the circular RNAs are known as non-coding RNAs, however, some of them are found to possess the capacities to code for proteins. One such circular RNA is hsa-circ-0000437 which is known to code for a short peptide referred to as CORO1C-47aa. The peptide has anti-angiogenic activity and are associated with the prevention of endometrial cancer. However, till date only the amino acid sequence of the peptide is known and no structural details of the peptide are available. Therefore, in this work, our aim was to predict how the peptide would fold and what could be its possible ligand binding sites. We used computational tools to determine the structure of the peptide. The structure was refined by molecular dynamics simulations. The possible binding sites and the binding partners of the peptide were also predicted. From this structure function analysis study, we tried to elucidate the possible mechanism of the involvements of the peptide in the onset of endometrial cancer. This is the first report on the structural characterization of the peptide. This study may therefore be useful in determining the structures of new drug candidates for the treatment of endometrial cancer.
Intermittent cocaine self-administration has sex-specific effects on addiction-like behaviors in rats
Authors: Bender Brooke N. , Torregrossa Mary M.
Published: December 2022

Intermittent access (IntA) models of cocaine self-administration were developed to better model in rodents how cocaine is used by human drug users. Compared to traditional continuous access (ContA) models, IntA has been shown to enhance several pharmacological and behavioral effects of cocaine, but few studies have examined sex differences in IntA. Moreover, no one has examined the efficacy of cue extinction to reduce cocaine seeking in the IntA model, which has previously shown to be ineffective in other models that promote habit-like cocaine seeking. Therefore, rats were implanted with jugular vein catheters and dorsolateral striatum (DLS) cannulae and trained to self-administer cocaine paired with an audiovisual cue with ContA or IntA. In subsets of rats, we evaluated: the ability of Pavlovian cue extinction to reduce cue-induced drug seeking; motivation for cocaine using a progressive ratio procedure; compulsive cocaine taking by pairing cocaine infusions with footshocks; and dependence of drug-seeking on DLS dopamine (a measure of habit-like behavior) with the dopamine antagonistcis-flupenthixol. Overall, cue extinction reduced cue-induced drug seeking after ContA or IntA. Compared to ContA, IntA resulted in increased motivation for cocaine exclusively in females, but IntA facilitated more compulsive cocaine taking exclusively in males. After 10 days of IntA training, but not fewer, drug-seeking was dependent on DLS dopamine most notably in males. Our results suggest that IntA may be valuable for identifying sex differences in the early stages of drug use and provide a foundation for the investigation of the mechanisms involved.

Highlights

- IntA promotes increased motivation for cocaine in females

- IntA augments compulsive cocaine self-administration in males

- IntA promotes DLS dopamine-dependent cocaine seeking, most notably in males

- Cue extinction overall reduces cue-induced drug seeking after ContA or IntA

- Under IntA, females self-administer more cocaine when in estrous
The cortico-thalamic loop attunes competitive lateral interactions across retinotopic and orientation preference maps
Authors: Guarino Domenico G. , Davison Andrew P. , Frégnac Yves , Antolík Ján
Published: December 2022

In the early visual system, corticothalamic feedback projections greatly outnumber thalamocortical feedforward projections. Extensive experimental and modeling work has been devoted to the functional impact of the feedforward pathway, but the role of its denser feedback counterpart remains elusive. Here, we propose a novel unifying framework where thalamic recurrent interactions and corticothalamic feedback act in a closed-loop fashion to attune multiple stimulus representations. At each position of the visual field, the loop puts into competition local representations of the stimulus in thalamus and cortex through direct excitation of narrow topologically-aligned portions of the thalamus, accompanied with peri-geniculate nucleus mediated broad inhibition suppressing the topological surround. We built a detailed conductance-based spiking model incorporating retinal input, lateral geniculate nucleus, peri-geniculate nucleus, primary visual cortex, and all the relevant intra-areal and feedback pathways. For the first time we perform comparative analyses between model configurations with completely or locally inactivated cortico-thalamic feedback, as in the experimental preparations. The model mechanistically explains (i) the existence of intra-thalamic surround suppression, (ii) the sensitivity of thalamic neurons to orientation tuning, (iii) the cortex-dependent center-surround opponency in thalamic cells, (iv) the cortical increase of size and orientation selectivity, (v) the cortically enhanced competition between cross-oriented domains within the hypercolumn, and (vi) the selective suppression of cortical functional connectivity. Our results integrate decades of experimental and theoretical research, supporting the hypothesis that cortico-thalamic loop exerts competitive influence between neighboring regions in the thalamus and cortex, complementing the lateral intra-V1 interactions in center-surround contextual modulation.
Off the shelf: Investigating transfer of learning using commercially available virtual reality equipment
Authors: Markwell Logan Taylor , Cochran Koleton , Porter Jared M.
Published: December 2022

The evolution of virtual reality (VR) has created the opportunity for a relatively low-cost and accessible method to practice motor skills. Previous studies have demonstrated how motor skill practice in non-immersive virtual environments transfers to physical environments. Though minimal research has investigated motor learning and transfer within immersive VR, multiple experiments provide empirical evidence of positive transfer effects. To enhance the similarities between virtual and physical environments, most studies have used software engines and modified hardware. However, many learners and practitioners are currently using commercially available VR with the goal of enhancing real-world performance, though there is very little evidence to support the notion of positive transfer for these systems. Therefore, the purpose of this experiment was to investigate how motor skill practice using a commercially available VR system improved real-world performance and how that compared to physical practice. Participants (n = 68) were randomly selected into one of two groups: virtual reality (VR) practice (n = 33) or real-world (RW) practice (n = 35). The experiment took place over two consecutive days with a pretest, posttest, and practice phase occurring on both days. The pre- and post-testing phases were identical for both groups and consisted of putting a golf ball 10 times on a carpeted surface towards the center of a target. The practice phases consisted of 60 total putts per day in the respective environment (VR or RW). Participants continuously alternated golf putting holes from three different distances until they accrued 60 total putts. Participants in the RW group performed golf putts to three targets. Participants in the VR group also performed golf putts on three different miniature golf putting holes, using the commercially available Oculus Rift and the Cloudlands VR Minigolf game. The VR putting targets were designed to replicate the putting holes in the physical environment. Separate 2 (condition) x 4 (test phase) repeated measures ANOVAs were used to assess accuracy and club head kinematics. The results revealed a significant main effect for test phase, but not for condition. Post hoc analyses revealed both groups significantly improved their putting accuracy and club head kinematics at similar rates. The results from this study indicate that the transfer of learning that occurred from the commercially available VR practice was equally effective when compared to RW practice.
Cold and warmth intensify pain-linked sodium channel gating effects and persistent currents
Authors: Kriegeskorte Sophia , Bott Raya , Hampl Martin , Korngreen Alon , Hausmann Ralf , Lampert Angelika
Published: December 2022

Voltage-gated sodium channels (Nav) are key players in excitable tissues with the capability to generate and propagate action potentials. Mutations in the genes encoding Navs can lead to severe inherited diseases, and some of these so-called channelopathies are showing temperature sensitive phenotypes, for example paramyotonia congenita, Brugada-syndrome, febrile seizure syndromes and inherited pain syndromes like erythromelalgia (IEM) and paroxysmal extreme pain disorder (PEPD). Nevertheless, most investigations of mutation-induced gating effects were conducted at room temperature and thus the role of cooling or warming in channelopathies remains poorly understood. Here, we investigated the temperature sensitivity of four Navsubtypes: Nav1.3, Nav1.5, Nav1.6, and Nav1.7 and two mutations in Nav1.7 causing IEM (Nav1.7/L823R) and PEPD (Nav1.7/I1461T), using an automated patch clamp system. Our experiments at 15 °C, 25 °C and 35 °C revealed a shift of the voltage dependence of activation to more hyperpolarized potentials with increasing temperature for all investigated subtypes. Nav1.3 exhibited strongly slowed inactivation kinetics compared to the other subtypes that resulted in enhanced persistent current especially at 15 °C, indicating a possible role in cold induced hyperexcitability. Impaired fast inactivation of Nav1.7/I1461T was significantly enhanced by cooling temperature to 15 °C. The subtype specific modulation as well as the intensified mutation induced gating changes stress the importance to consider temperature as regulator for channel gating and its impact on cellular excitability as well as disease phenotypes.

Activation of the sodium channel subtypes Nav1.3, Nav1.5, Nav1.6, and Nav1.7 and two pain linked mutations is alleviated by warmth. Cooler temperatures, on the other hand, strongly enhance persistent currents of Nav1.3. The impaired fast inactivation of the pain-linked Nav1.7/I1461T mutation is further impaired by cooling, mimicking clinical findings.
Profiling intra- and inter-individual differences in brain development across early adolescence
Authors: Bottenhorn Katherine L. , Cardenas-Iniguez Carlos , Mills Kathryn L. , Laird Angela R. , Herting Megan M.
Published: December 2022

As we move toward population-level developmental neuroscience, understanding intra- and inter-individual variability in brain maturation and sources of neurodevelopmental heterogeneity becomes paramount. Large-scale, longitudinal neuroimaging studies have uncovered group-level neurodevelopmental trajectories, and while recent work has begun to untangle intra- and inter-individual differences, they remain largely unclear. Here, we aim to quantify both intra- and inter-individual variability across facets of neurodevelopment across early adolescence (ages 8.92 to 13.83 years) in the Adolescent Brain Cognitive Development (ABCD) Study and examine inter-individual variability as a function of age, sex, and puberty. Our results provide novel insight into differences in annualized percent change in macrostructure, microstructure, and functional brain development from ages 9-13 years old. These findings reveal moderate age-related intra-individual change, but age-related differences in inter-individual variability only in a few measures of cortical macro- and microstructure development. Greater inter-individual variability in brain development were seen in mid-pubertal individuals, except for a few aspects of white matter development that were more variable between prepubertal individuals in some tracts. Although both sexes contributed to inter-individual differences in macrostructure and functional development in a few regions of the brain, we found limited support for hypotheses regarding greater male-than-female variability. This work highlights pockets of individual variability across facets of early adolescent brain development, while also highlighting regional differences in heterogeneity to facilitate future investigations in quantifying and probing nuances in normative development, and deviations therefrom.
Genes and genome-resolved metagenomics reveal the microbial functional make up of Amazon peatlands under geochemical gradients
Authors: Pavia Michael J. , Finn Damien , Macedo-Tafur Franco , Tello-Espinoza Rodil , Penaccio Christa , Bouskill Nicholas , Cadillo-Quiroz Hinsby
Published: December 2022

The Pastaza-Marañón Foreland Basin (PMFB) holds the most extensive tropical peatland area in South America. PMFB peatlands store 7.07 Gt of organic carbon interacting with multiple microbial heterotrophic, methanogenic, and other oxic/anoxic respirations. Little is understood about the contribution of distinct microbial community members inhabiting tropical peatlands. Here, we studied the metagenomes of three geochemically distinct peatlands spanning minerotrophic, mixed, and ombrotrophic conditions. Using gene- and genome-centric approaches, we evaluate the functional potential of the underlying microbial communities. Abundance analyses shows significant differences in C, N, P, and S acquisition genes. Further, community interactions mediated by Toxin-antitoxin and CRISPR-Cas systems were enriched in oligotrophic soils, suggesting that non-metabolic interactions may exert additional controls in low nutrient environments. Similarly, we reconstructed 519 metagenome-assembled genomes spanning 28 phyla. Our analyses detail key differences across the nutrient gradient in the predicted microbial populations involved in degradation of organic matter, and the cycling of N and S. Notably, we observed differences in the nitrogen oxide (NO) reduction strategies between sites with high and low N2O fluxes and found phyla putatively capable of both NO and sulfate reduction. Our findings detail how gene abundances and microbial populations are influenced by geochemical differences in tropical peatlands.
MTL neurons phase-lock to human hippocampal theta
Authors: Schonhaut Daniel R. , Ramayya Ashwin G. , Solomon Ethan A. , Herweg Nora A. , Fried Itzhak , Kahana Michael J.
Published: December 2022

Memory formation depends on neural activity across a network of regions, including the hippocampus and broader medial temporal lobe (MTL). Interactions between these regions have been studied indirectly using functional MRI, but the bases for inter-regional communication at a cellular level remain poorly understood. Here we evaluate the hypothesis that oscillatory currents in the hippocampus synchronize the firing of neurons both within and outside the hippocampus. We recorded extracellular spikes from 1,854 single- and multi-units simultaneously with hippocampal local field potentials (LFPs) in 28 neurosurgical patients who completed virtual navigation experiments. A majority of hippocampal neurons phase-locked to oscillations in the slow (2-4Hz) or fast (6-10Hz) theta bands, with a significant subset exhibiting nested slow theta × beta frequency (13-20Hz) phase-locking. Outside of the hippocampus, phase-locking to hippocampal oscillations occurred only at theta frequencies and primarily among neurons in the entorhinal cortex and amygdala. Extrahippocampal neurons phase-locked to hippocampal theta even when theta did not appear locally. These results indicate that spike-time synchronization with hippocampal theta is a defining feature of neuronal activity in the hippocampus and structurally-connected MTL regions. Theta phase-locking could mediate flexible communication with the hippocampus to influence the content and quality of memories.
The neurophysiology of closed-loop auditory stimulation in sleep: a magnetoencephalography study
Authors: Jourde Hugo R. , Merlo Raphaëlle , Brooks Mary , Rowe Meredith , Coffey Emily B.J.
Published: December 2022

Closed-loop auditory stimulation (CLAS) is a brain modulation technique in which sounds are timed to enhance or disrupt endoge-nous neurophysiological events. CLAS of slow oscillation up-states in sleep is becoming a popular tool to study and enhance sleep’s functions, as it increases slow oscillations, evokes sleep spindles, and enhances memory consolidation of certain tasks. However, few studies have examined the specific neurophysiological mechanisms involved in CLAS, in part because of practical limitations to available tools. To evaluate evidence for possible models of how sound stimulation during brain up-states alters brain activity, we simultaneously recorded electro- and magnetoencephalography in human participants who received auditory stimulation across sleep stages. We conducted a series of analyses that test different models of pathways through which CLAS of slow oscillations may affect widespread neural activity that have been suggested in literature, using spatial information, timing, and phase relationships in the source-localized magnetoencephalography data. The results suggest that auditory information reaches ventral frontal lobe areas via non-lemniscal pathways. From there, a slow oscillation is created and propagated. We demonstrate that while the state of excitability of tissue in auditory cortex and frontal ventral regions shows some synchrony with the EEG-recorded up-states that are commonly used for CLAS, it is the state of ventral frontal regions that is most critical for slow oscillation generation. Our findings advance models of how CLAS leads to enhancement of slow oscillations, sleep spindles, and associated cognitive benefits, and offer insight into how the effectiveness of brain stimulation techniques can be improved.
A Re-evaluation of Phylogenomic Data Reveals that Current Understanding in Wheat Blast Population Biology and Epidemiology is Obfuscated by Oversights in Population Sampling
Authors: Farman Mark L. , Ascari Joao P. , Rahnama Mostafa , Del Ponte Emerson M. , Pedley Kerry F. , Martinez Sebastián , Fernandes José Maurício C. , Valent Barbara
Published: December 2022

Wheat blast, caused by theTriticumlineage ofPyricularia oryzae(PoT), is a serious disease that first emerged in Brazil and quickly spread to neighboring countries. The recent appearance of this disease in Bangladesh and Zambia highlights a need to understand the population biology and epidemiology of the disease so as to mitigate pandemic outbreaks. Current knowledge in these areas is largely based on analyses of wheat blast isolates collected in Brazil, and their comparison with isolates from non-wheat, endemic grasses. Those studies concluded that wheat blast is caused by a highly diverseP. oryzaepopulation that lacks host specificity and, as a result, undergoes extensive gene flow with populations infecting non-wheat hosts. Additionally, based on genetic similarity between wheat blast and isolates infectingUrochloaspecies, it was proposed that the disease originally emerged via a host jump from this grass, and the widespread use ofUrochloaas a pasture grass likely plays a central role in wheat blast epidemiology. Inconsistencies with earlier phylogenetic studies prompted us to re-analyze the Brazilian data in the context of a comprehensive, global, phylogenomic dataset. We now show that the seminal studies failed to sample theP. oryzaepopulations normally found on endemic grasses and, instead, repeatedly sampled PoT andP. oryzae Lolium(PoL) members that happened to be present in these hosts. The resulting lack of accurate and representative information about the grass-infecting populations in Brazil means that current conclusions about wheat blast’s evolution, population biology and epidemiology are unsubstantiated and could be equivocal.
Heritable epigenetic variation facilitates long-term maintenance of epigenetic and genetic variation
Authors: Webster Amy K. , Phillips Patrick C.
Published: December 2022

The maintenance of genetic and phenotypic variation has long been one of the fundamental questions in population and quantitative genetics. A variety of factors have been implicated to explain the maintenance of genetic variation in some contexts (e.g. balancing selection), but the potential role of epigenetic regulation to influence population dynamics has been understudied. It is well recognized that epigenetic regulation, including histone methylation, small RNA expression, and DNA methylation, helps to define differences between cell types and facilitate phenotypic plasticity. In recent years, empirical studies have shown the potential for epigenetic regulation to also be heritable for at least a few generations without selection, raising the possibility that differences in epigenetic regulation can act alongside genetic variation to shape evolutionary trajectories. Like genetic mutation, heritable differences in epigenetic regulation can arise spontaneously; these are termed ‘epimutations’. Epimutations differ from genetic mutations in two key ways – they occur at a higher rate and the loci at which they occur often revert back to their original state within a few generations. Here, we present an extension of the standard population-genetic model with selection to incorporate epigenetic variation arising via epimutation. Our model assumes a diploid, sexually reproducing population with random mating. In addition to spontaneous genetic mutation, we included parameters for spontaneous epimutation and back-epimutation, allowing for four potential epialleles at a single locus (two genetic alleles, each with two epigenetic states), each of which affect fitness. We then analyzed the conditions under which stable epialleles were maintained. Our results show that highly reversible epialleles can be maintained in long-term equilibrium under neutral conditions in a manner that depends on the epimutation and back-epimutation rates, which we term epimutation-back-epimutation equilibrium. On the other hand, epialleles that compensate for deleterious mutations cause deviations from the expectations of mutation-selection balance by a simple factor that depends on the epimutation and back-epimutation rate. We also numerically analyze several sets of fitness parameters for which large deviations from mutation-selection balance occur. Together, these results demonstrate that transient epigenetic regulation may be an important factor in the maintenance of both epigenetic and genetic variation in populations.
High spontaneous integration rates of end-modified linear DNAs upon mammalian cell transfection
Authors: Lim Samuel , Yocum R. Rogers , Silver Pamela A , Way Jeffrey C
Published: December 2022

In gene therapy, potential integration of therapeutic transgene into host cell genomes is a serious risk that can lead to insertional mutagenesis and tumorigenesis. Viral vectors are often used as the gene delivery vehicle, but they are prone to undergoing integration events. More recently, non-viral delivery of linear DNAs having modified geometry such as closed-end linear duplex DNA (CELiD) have shown promise as an alternative, due to prolonged transgene expression and less cytotoxicity. However, whether such modified-end linear DNAs can also provide a safe, non-integrating gene transfer remains unanswered. Herein, we provide a systematic comparison of genomic integration frequency upon transfection of cells with expression vectors in the forms of circular plasmid, unmodified linear DNA, CELiD, and Streptavidin-conjugated blocked-end linear DNA. All of these forms of linear DNA resulted in a high fraction of the cells being stably transfected – between 10% and 20% of the initially transfected cells, with CELiDs showing the highest rates of integration. These results indicate that blocking the ends of linear DNA is insufficient to prevent integration. Moreover, our analysis suggest that conventional AAV-based gene therapy may be highly susceptible to integration, which is consistent with recent findings from long-term clinical studies.
Larval and adult traits coevolve in response to coastal oceanography to shape marine dispersal kernels
Authors: Peniston James H. , Burgess Scott C.
Published: December 2022

Dispersal emerges as an outcome of organismal traits and external forcings. However, it remains unclear how the emergent dispersal kernel evolves as a by-product of selection on the underlying traits. This question is particularly compelling in coastal marine systems where dispersal is tied to development and reproduction, and where directional currents bias larval dispersal downstream causing selection for retention. We modelled the dynamics of a metapopulation along a finite coastline using an integral projection model and adaptive dynamics to understand how asymmetric coastal currents influence the evolution of larval (pelagic larval duration) and adult (spawning frequency) life history traits, which indirectly shape the evolution of marine dispersal kernels. Selection induced by alongshore currents favors the release of larvae over multiple time periods, allowing long pelagic larval durations and long-distance dispersal to be maintained in marine life cycles in situations where they were previously predicted to be selected against. Two evolutionary stable strategies emerged: one with a long pelagic larval duration and many spawning events resulting in a dispersal kernel with a larger mean and variance, and another with a short pelagic larval duration and few spawning events resulting in a dispersal kernel with a smaller mean and variance. Our theory shows how coastal ocean flows are important agents of selection that can generate multiple, often co-occurring, evolutionary outcomes for marine life history traits that affect dispersal.
Structural characterization of an intrinsically disordered protein complex using integrated small-angle neutron scattering and computing
Authors: Chen Serena H. , Weiss Kevin L. , Stanley Christopher , Bhowmik Debsindhu
Published: December 2022

Characterizing the structural ensembles of intrinsically disordered proteins (IDPs) is essential for studying structure-function relationships as conformational dynamics govern proteins’ biological functions. Due to the notable difference between the neutron scattering lengths of hydrogen and deuterium, selective labeling and contrast matching in small-angle neutron scattering (SANS) becomes an effective tool to study dynamic structures of disordered systems. However, the experimental timescale typically results in measurements averaged over multiple conformations, leaving complex SANS data for disentanglement. We hereby demonstrate an integrated method to elucidate the structural ensemble of a protein complex formed by two IDP domains, the NCBD/ACTR complex, using data from selective labeling SANS experiments, microsecond all-atom molecular dynamics (MD) simulations with four molecular mechanics force fields, and an autoencoder-based deep learning (DL) algorithm. By incorporating structural metrics derived from the SANS experiments as constraints in MD structure classification, we describe a structural ensemble that captures the experimental SANS and, in addition, NMR data better than MD ensembles generated by one single force field. Based on structural similarity, DL reveals three clusters of distinct conformations in the ensemble. Our results demonstrate a new integrated approach for characterizing structural ensembles of IDPs.
Dynamics and maintenance of categorical responses in primary auditory cortex during task engagement
Authors: Chillale Rupesh Kumar , Shamma Shihab , Ostojic Srdjan , Boubenec Yves
Published: December 2022

Grouping sets of sounds into relevant categories is an important cognitive ability that facilitates the association of stimuli with appropriate goal-directed behavioral responses. In perceptual tasks, a prominent role of primary auditory cortex (A1) is to multiplex the encoding of sound sensory features and task variables. Here we investigated the involvement of A1 in initiating sound categorization. We trained ferrets to discriminate click trains of different rates in a Go/No-Go delayed categorization task and recorded neural activity during both active behavior and passive exposure to the same sounds. Purely categorical response components were extracted and analyzed separately from sensory responses to reveal their contributions to the overall population response throughout the trials. We found that population-level representation of Go/No-Go behavioral categories emerged during sound presentation and was present in both active behavioral and passive states. However, upon task engagement, categorical responses to the No-Go category became suppressed, leading to an asymmetrical representation of the Go stimuli relative to the No-Go sounds and prestimulus baseline. At stimulus offset, the population code changed abruptly but categorical representation was maintained during the delay period. Categorical responses extracted from the stimulus period correlated with the ones found in the delay epoch, suggesting an early contribution of A1 to stimulus categorization.
Microbiome features differentiating unsupervised-stratification based clusters of patients with abnormal glycometabolism
Authors: Xu Ting , Wang Xuejiao , Chen Yu , Li Hui , Zhao Liping , Ding Xiaoying , Zhang Chenhong
Published: December 2022

The alteration of gut microbiota structure plays a pivotal role in the pathogenesis of abnormal glycometabolism. However, the microbiome features identified in patient groups stratified solely based on glucose levels remain controversial among different studies.. In this study, we stratified 258 participants (discovery cohort) into three clusters according to an unsupervised method based on 16 clinical parameters involving the levels of blood glucose, insulin, and lipid. We found 67 cluster-specific microbiome features (i.e., amplicon sequence variants, ASVs) based on 16S rRNA gene V3-V4 region sequencing. Specifically, ASVs belonging toBarnesvilleandAlistipeswere enriched in Cluster 1, in which participants had the lowest blood glucose levels, high insulin sensitivity, and high-fecal short-chain fatty acid concentration. ASVs belonging toPrevotella copriandRuminococcus gnavuswere enriched in Cluster 2, which was characterized by a moderate level of blood glucose, serious insulin resistance, and high levels of cholesterol and triglyceride. Cluster 3 was characterized by a high level of blood glucose and insulin deficiency, enriched with ASVs inP. copriandBacteroides vulgatus. In addition, machine learning classifiers using the 67 cluster-specific ASVs were used to distinguish individuals in one cluster from those in the other two clusters both in discovery and testing cohorts (N = 83). Therefore, microbiome features identified based on the unsupervised stratification of patients with more inclusive clinical parameters may better reflect microbiota alterations associated with the progression of abnormal glycometabolism.

IMPORTANCE

The gut microbiota is altered in patients with type 2 diabetes (T2D) and prediabetes. The association of particular bacteria with T2D, however, varied among studies, which has made it challenging to develop precision medicine approaches for the prevention and alleviation of T2D. Blood glucose level is the only parameter in clustering patients when identifying the T2D-related bacteria in previous studies. This stratification ignores the fact that patients within the same blood glucose range differ in their insulin resistance and dyslipidemia, which also may be related to disordered gut microbiota. In addition to parameters of blood glucose levels, we also used additional parameters involving insulin and lipid levels to stratify participants into three clusters and further identified cluster-specific microbiome features. We further validated the association between these microbiome features and glycometabolism with an independent cohort. This work highlights the importance of stratification of patients with blood glucose, insulin, and lipid levels when identifying the microbiome features associated with the progression of abnormal glycometabolism.
The free energy of an ecosystem: towards a measure of its inner value
Authors: Perillo Gerardo M. E. , Zilio Mariana I. , Tohme Fernando , Piccolo M. Cintia
Published: December 2022

Based on a free energy approach, we propose the estimation of ecosystem Inner Value, which is both non-instrumental and objective, reflecting the ecosystem’s value for itself as a natural entity, abstracted from any human valuation activity. The ecosystem services approach has become the dominant criteria for studying the relationship between humans and nature. Although there is concern about preserving and recuperating damaged ecosystems, we seldom consider how much the ecosystem values itself. Then, we propose that Inner Value could be a tool to evaluate and model ecosystems’ health before any anthropic disturbance, allowing comparison with the impact these disturbances may have in the future. We also suggest that it should be a requirement for any Environmental Impact Assessment.

Significance Statement

Ecosystem are valued for the services they provide to human. Therefore, they are estimated following human (mostly economic) criteria. However, any ecosystem has its own value independent of the services it can give. Therefore, we propose the use of the Inner Value concept as a non-instrumental, objective measure reflecting the ecosystem’s value for itself as a natural entity based on a free-energy approach. Inner Value could be a tool to evaluate and model ecosystems’ health before any anthropic disturbance, allowing comparison with the impact these disturbances may have in the future.
Analyzing postprandial metabolomics data using multiway models: A simulation study
Authors: Li Lu , Yan Shi , Bakker Barbara M. , Hoefsloot Huub , Chawes Bo , Horner David , Rasmussen Morten A. , Smilde Age K. , Acar Evrim
Published: December 2022

Background

Analysis of time-resolved postprandial metabolomics data can improve the understanding of metabolic mechanisms, potentially revealing biomarkers for early diagnosis of metabolic diseases and advancing precision nutrition and medicine. Postprandial metabolomics measurements at several time points from multiple subjects can be arranged as asubjectsbymetabolitesbytime pointsarray. Traditional analysis methods are limited in terms of revealing subject groups, related metabolites, and temporal patterns simultaneously from such three-way data.

Results

We introduce an unsupervised multiway analysis approach based on the CANDECOMP/PARAFAC (CP) model for improved analysis of postpran-dial metabolomics data guided by a simulation study. Because of the lack of ground truth in real data, we generate simulated data using a comprehensive human metabolic model. This allows us to assess the performance of CP models in terms of revealing subject groups and underlying metabolic processes. We study three analysis approaches: analysis offasting-statedata using Principal Component Analysis,T0-correcteddata (i.e., data corrected by subtracting fasting-state data) using a CP model andfull-dynamic(i.e., full postprandial) data using CP. Through extensive simulations, we demonstrate that CP models capture meaningful and stable patterns from simulated meal challenge data, revealing underlying mechanisms and differences between diseased vs. healthy groups.

Conclusions

Our experiments show that it is crucial to analyze bothfasting-stateandT0-correcteddata for understanding metabolic differences among subject groups. Depending on the nature of the subject group structure, the best group separation may be achieved by CP models ofT0-correctedorfull-dynamicdata. This study introduces an improved analysis approach for postprandial metabolomics data while also shedding light on the debate about correcting baseline values in longitudinal data analysis.
Aberrant hierarchical prediction errors are associated with transition to psychosis: A computational single-trial analysis of the mismatch negativity
Authors: Hauke Daniel J. , Charlton Colleen E. , Schmidt André , Griffiths John , Woods Scott W. , Ford Judith M. , Srihari Vinod H. , Roth Volker , Diaconescu Andreea O. , Mathalon Daniel H.
Published: December 2022

Background

Mismatch negativity (MMN) reductions are among the most reliable biomarkers for schizophrenia and have been associated with increased risk for conversion to psychosis in individuals at clinical high risk for psychosis (CHR-P). Here, we adopt a computational approach to develop a mechanistic model of MMN reductions in CHR-P individuals and patients early in the course of schizophrenia (ESZ).

Methods

Electroencephalography (EEG) was recorded in 38 CHR-P individuals (15 converters), 19 ESZ patients (≤5 years), and 44 healthy controls (HC) during three different auditory oddball MMN paradigms including 10% duration-, frequency-, or double-deviants, respectively. We modelled sensory learning with the hierarchical Gaussian filter and extracted precision-weighted prediction error trajectories from the model to assess how the expression of hierarchical prediction errors modulated EEG amplitudes over sensor space and time.

Results

Both low-level sensory and high-level volatility precision-weighted prediction errors were altered in CHR-P and ESZ groups compared to HC. Furthermore, low-level precision-weighted prediction errors were significantly different in CHR-P that later converted to psychosis compared to non-converters.

Conclusions

Our results implicate altered processing of hierarchical prediction errors as a computational mechanism in early psychosis consistent with predictive coding accounts of psychosis. This computational model appears to capture pathophysiological mechanisms relevant to early psychosis and the risk for future psychosis in CHR-P individuals, and may serve as a predictive biomarker and mechanistic target for novel treatment development.
Impact of Age, Race, and Family History on COVID-19 Related Changes in Breast Cancer Screening among the Boston Mammography Cohort Study
Authors: Chen Naiyu , Cheng David , Sodipo Michelle O. , Barnard Mollie E. , DuPre Natalie C. , Tamimi Rulla M. , Warner Erica T.
Published: December 2022

Background

We studied women enrolled in the Boston Mammography Cohort Study to investigate whether subgroups defined by age, race, or family history of breast cancer experienced differences in trends of screening or diagnostic imaging rates during the COVID-19 lockdown and had slower rebound in trends of these rates during reopening.

Methods

We compared trends of monthly breast cancer screening and diagnostic imaging rates over time between the pre-COVID-19, lockdown, and reopening periods and tested for differences in the monthly trend within the same period by age (<50 vs ≥50), race (White vs non-White), and first-degree family history of breast cancer (yes vs no).

Results

Overall, we observed a decline in breast cancer screening and diagnostic imaging rates. The monthly trend of breast cancer screening rates for women age ≥50 was 5% higher (p=0.005) in the pre-COVID-19 period but was 19% lower in the reopening phase than that of women aged<50 (p<0.001). White participants had 36% higher monthly trend of breast cancer diagnostic imaging rates than non-White participants (p=0.018).

Discussion

The rebound in screening was lower in women age ≥50 and lower in non-White women for diagnostic imaging. Careful attention must be paid as the COVID-19 recovery continues to ensure equitable resumption of care.

Funding

The project was supported by the Breast Cancer Research Foundation (RT). Researchers were supported by the University of Louisville CIEHS P30 ES030283 (NCD), K01CA188075 (ETW), T32CA09001 (NCD, MOS, MEB) P30 ES000002 (JH, FL), and NIH/NCI K00 CA212222 (MEB). This manuscript is the responsibility of the authors and does not represent the official views of the National Institutes of Health.
Socioeconomic position and the influence of food portion size on daily energy intake in adult females: two randomized control trials
Authors: Langfield Tess , Clarke Katie , Marty Lucile , Jones Andrew , Robinson Eric
Published: December 2022

Background

Large portions of energy-dense foods drive overconsumption and are more readily available in socioeconomically deprived areas. Reducing portion sizes of commercially available foods could be an effective public health strategy to reduce population energy intake, but recent research suggests that the effect portion size has on energy intake may differ based on socioeconomic position (SEP).

Objective

We tested whether the effect of reducing food portion sizes on daily energy intake differed based on SEP.

Methods

Participants were served either smaller or larger portions of food at lunch and evening meals (N = 50; Study 1) and breakfast, lunch and evening meals (N = 46; Study 2) in the laboratory on two separate days, in repeated-measures designs. The primary outcome was total daily energy intake (kcal). Participant recruitment was stratified by primary indicators of SEP; highest educational qualification (Study 1) and subjective social status (Study 2). Secondary indicators of SEP in both studies included household income, self-reported childhood financial hardship and a measure accounting for total years in education.

Results

In both studies, smaller (vs larger) meal portions led to a reduction in daily energy intake (ps < .02). Smaller portions resulted in a reduction of 235kcal per day (95% CI: 134, 336) in Study 1 and 143kcal per day (95% CI: 24, 263) in Study 2. There was no evidence in either study that effects of portion size on energy intake differed by SEP. Results were consistent when examining effects on portion-manipulated meal (as opposed to daily) energy intake.

Conclusion

Reducing meal portion sizes could be an effective way to reduce overall daily energy intake and contrary to other suggestions it may be a socioeconomically equitable approach to improving diet. These trials were registered atwww.clinicaltrials.govasNCT05173376andNCT05399836.
Biologically-informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post-treatment glioblastoma
Authors: Wang Hairong , Argenziano Michael G , Yoon Hyunsoo , Boyett Deborah , Save Akshay , Petridis Petros , Savage William , Jackson Pamela , Hawkins-Daarud Andrea , Tran Nhan , Hu Leland , Al Dalahmah Osama , Bruce JeffreyN. , Grinband Jack , Swanson Kristin R , Canoll Peter , Li Jing
Published: December 2022

Intratumoral heterogeneity poses a significant challenge to the diagnosis and treatment of glioblastoma (GBM). This heterogeneity is further exacerbated during GBM recurrence, as treatment-induced reactive changes produce additional intratumoral heterogeneity that is ambiguous to differentiate on clinical imaging. There is an urgent need to develop non-invasive approaches to map the heterogeneous landscape of histopathological alterations throughout the entire lesion for each patient. We propose to predictively fuse Magnetic Resonance Imaging (MRI) with the underlying intratumoral heterogeneity in recurrent GBM using machine learning (ML) by leveraging image-localized biopsies with their associated locoregional MRI features. To this end, we develop BioNet, a biologically-informed neural network model, to predict regional distributions of three tissue-specific gene modules: proliferating tumor, reactive/inflammatory cells, and infiltrated brain tissue. BioNet offers valuable insights into the integration of multiple implicit and qualitative biological domain knowledge, which are challenging to describe in mathematical formulations. BioNet performs significantly better than a range of existing methods on cross-validation and blind test datasets. Voxel-level prediction maps of the gene modules by BioNet help reveal intratumoral heterogeneity, which can improve surgical targeting of confirmatory biopsies and evaluation of neuro-oncological treatment effectiveness. The non-invasive nature of the approach can potentially facilitate regular monitoring of the gene modules over time, and making timely therapeutic adjustment. These results also highlight the emerging role of ML in precision medicine.
Myc controls IL-15-driven expansion and translational machinery of NK cells
Authors: Khameneh Hanif J. , Fonta Nicolas , Zenobi Alessandro , Niogret Charlène , Ventura Pedro , Guerra Concetta , Kwee Ivo , Rinaldi Andrea , Pecoraro Matteo , Geiger Roger , Cavalli Andrea , Bertoni Francesco , Vivier Eric , Trumpp Andreas , Guarda Greta
Published: December 2022

Myc is a pleiotropic transcription factor involved in cancer, cell proliferation, and metabolism. Its regulation and function in Natural Killer (NK) cells, which are innate cytotoxic lymphocytes important to control viral infections and cancer, remain poorly defined. Here we show that mice deficient for Myc in NK cells presented a severe reduction in these lymphocytes. Myc was required for NK cell development and expansion in response to the key cytokine interleukin (IL)-15, which induced Myc through transcriptional and posttranslational mechanisms. Mechanistically, Myc ablationin vivolargely impacted NK cells’ ribosomagenesis, reducing their translation and expansion capacities. Similar results were obtained by inhibiting MYC in human NK cells. Impairing translation by pharmacological intervention phenocopied the consequences of deleting or blocking MYCin vitro. Notably, mice lacking Myc in NK cells exhibited defective anticancer immunity, which reflected their decreased numbers of mature NK cells exerting suboptimal cytotoxic functions. These results indicate that MYC is a central node in NK cells, connecting IL-15 to translational fitness, expansion, and anticancer immunity.