bluuebunny/crossref_metadata_2025 huggingface dataset:
Diagnostic test accuracy of artificial intelligence in screening for referable diabetic retinopathy in real-world settings: A systematic review and meta-analysis
Authors: Uy Holijah , Fielding Christopher , Hohlfeld Ameer , Ochodo Eleanor , Opare Abraham , Mukonda Elton , Minnies Deon , Engel Mark E
Published: June 2023

Studies on artificial intelligence (AI) in screening for diabetic retinopathy (DR) have shown promising results in addressing the mismatch between the capacity to implement DR screening and the increasing DR incidence; however, most of these studies were done retrospectively. This review sought to evaluate the diagnostic test accuracy (DTA) of AI in screening for referable diabetic retinopathy (RDR) in real-world settings. We searched CENTRAL, PubMed, CINAHL, Scopus, and Web of Science on 9 February 2023. We included prospective DTA studies assessing AI against trained human graders (HGs) in screening for RDR in patients living with diabetes. synthesis Two reviewers independently extracted data and assessed methodological quality against QUADAS-2 criteria. We used the hierarchical summary receiver operating characteristics (HSROC) model to pool estimates of sensitivity and specificity and, forest plots and SROC plots to visually examine heterogeneity in accuracy estimates. Finally, we conducted sensitivity analyses to explore the effects of studies deemed to possibly affect the quality of the studies. We included 15 studies (17 datasets: 10 patient-level analysis (N=45,785), and 7 eye-level analysis (N=15,390). Meta-analyses revealed a pooled sensitivity of 95.33%(95% CI: 90.60-100%) and specificity of 92.01%(95% CI: 87.61-96.42%) for patient-level analysis; for the eye-level analysis, pooled sensitivity was 91.24% (95% CI: 79.15-100%) and specificity, 93.90% (95% CI: 90.63-97.16%). Subgroup analyses did not provide variations in the diagnostic accuracy of country classification and DR classification criteria; however, a moderate increase was observed in diagnostic accuracy at the primary-level and, a minimal decrease in the tertiary-level healthcare settings. Sensitivity analyses did not show any variations in studies that included diabetic macular edema in the RDR definition, nor in studies with ≥3 HGs. This review provides evidence, for the first time from prospective studies, for the effectiveness of AI in screening for RDR, in real-world settings.
Evaluating the buffering role of perceived social support and coping resources against the adult mental health impacts of COVID-19 psychosocial stress: a cross-sectional study in South Africa
Authors: Kim Andrew Wooyoung , Swana Someleze , Sarma Mallika S.
Published: June 2023

Objectivesw

Growing evidence has highlighted the global mental health impacts of the COVID- 19 pandemic and lockdown, particularly in societies with pre-existing socioeconomic adversities and public health concerns. Despite the sudden and prolonged nature of many psychosocial stressors during the pandemic, recent studies have shown that communities utilized several coping mechanisms to buffer the mental health consequences of COVID-related stress. This paper examines the extent to which coping resources and social support buffered against the mental health effects of COVID-19 psychosocial stress among adults in South Africa.

Materials & Methods

Adult participants (n=117) completed an online survey during the second and third waves of the COVID-19 pandemic in South Africa (January-July 2021), which assessed experiences of stress, coping resources, social support, and four mental health outcomes: depression, anxiety, post-traumatic stress disorder, and bipolar disorder. Moderation analyses examined the potential buffering role of coping resources and social support against the mental health effects of COVID-19 stress.

Results

Adults reported elevated rates of psychiatric symptoms. Coping resources buffered against the poor mental health effects of COVID-19 psychosocial stress, whereas perceived social support did not significantly moderate the association between COVID-19 stress and adult mental health.

Discussion

These results suggest that adults in our sample utilized a variety of coping resources to protect their mental health against psychosocial stress experienced during the COVID-19 lockdown and pandemic in South Africa. Additionally, existing mental health conditions and strained social relationships may have attenuated the potential stress-buffering effect of perceived social support on adult mental health.
Metagenomics for pathogen detection during a wildlife mortality event in songbirds
Authors: Mwakibete Lusajo , Greening Sabrina S. , Kalantar Katrina , Ahyong Vida , Anis Eman , Miller Erica A. , Needle David B. , Oglesbee Michael , Thomas W. Kelley , Sevigny Joseph L. , Gordon Lawrence M. , Nemeth Nicole M. , Ogbunugafor C. Brandon , Ayala Andrea J. , Faith Seth A. , Neff Norma , Detweiler Angela M. , Baillargeon Tessa , Tanguay Stacy , Simpson Stephen D. , Murphy Lisa A. , Ellis Julie C. , Tato Cristina M. , Gagne Roderick B.
Published: June 2023

Mass mortality events in wildlife can be indications of an emerging infectious disease. During the spring and summer of 2021, hundreds of dead passerines were reported across the eastern US. Birds exhibited a range of clinical signs including swollen conjunctiva, ocular discharge, ataxia, and nystagmus. As part of the diagnostic investigation, high-throughput metagenomic next-generation sequencing was performed across three molecular laboratories on samples from affected birds. Many potentially pathogenic microbes were detected, with bacteria comprising the largest proportion; however, no singular agent was consistently identified, with many of the detected microbes also found in unaffected (control) birds, and thus considered to be subclinical infections. Congruent results across laboratories have helped drive further investigation into alternative causes including environmental contaminants and nutritional deficiencies. This work highlights the utility of metagenomic approaches in investigations of emerging diseases and provides a framework for future wildlife mortality events.

Article Summary Line

The causative agent of a mass mortality event in passerines remains inconclusive after metagenomic high-throughput sequencing with results prompting further investigation into non-pathogenic causes.
Improved characterization of soil organic matter by integrating FTICR-MS, liquid chromatography tandem mass spectrometry and molecular networking: a case study of root litter decay under drought conditions
Authors: DiDonato Nicole , Rivas-Ubach Albert , Kew William , Clendinen Chaevien , Sokol Noah , Kyle Jennifer E. , Martínez Carmen E. , Foley Megan M. , Tolić Nikola , Pett-Ridge Jennifer , Paša-Tolić Ljiljana
Published: June 2023

Knowledge of the type of carbon contained in soils is important for predicting carbon fluxes in a warming climate, yet most soil organic matter (SOM) components are unknown. We used an integrated three-part approach to characterize SOM from decaying root-detritus microcosms subject to either drought or normal conditions. To observe broad differences in SOM compositions we employed direct infusion Fourier transform ion cyclotron resonance mass spectrometry (DI-FTICR-MS). We complemented this with liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify components by library matching. Since libraries contain only a small fraction of SOM components, we also used fragment spectra cosine similarity scores to relate unknowns and library matches through molecular networks. This approach allowed us to corroborate DI-FTICR-MS molecular formulas using library matches and infer structures of unknowns from molecular networks to improve SOM annotation. We found matches to fungal metabolites, and under drought conditions, greater relative amounts of lignin-like vs condensed aromatic polyphenol formulas, and lower average nominal oxidation state of SOM carbon, suggesting reduced decomposition of carbon and/or microbes under stress. We propose this integrated approach as more comprehensive than individual analyses in parallel, with the potential to improve knowledge of the chemical composition and persistence of SOM.

Synopsis

Structural characterization and identifications are lacking for soil organic matter components. This study integrates molecular formula assignments and structural information from fragment ion spectra into molecular networks to better characterize unknown soil organic matter components.

For Table of Contents Only
Bayesian analysis dissects kinetic modulation during non-stationary gene expression
Authors: Wildner Christian , Mehta Gunjan D. , Ball David A. , Karpova Tatiana S. , Koeppl Heinz
Published: June 2023

Labelling of nascent stem loops with fluorescent proteins has fostered the visualization of transcription in living cells. Quantitative analysis of recorded fluorescence traces can shed light on kinetic transcription parameters and regulatory mechanisms. However, existing methods typically focus on steady state dynamics. Here, we combine a stochastic process transcription model with a hierarchical Bayesian method to infer global as well locally shared parameters for groups of cells and recover unobserved quantities such as initiation times and polymerase loading of the gene. We apply our approach to the cyclic response of the yeastCUP1locus to heavy metal stress. Within the previously described slow cycle of transcriptional activity on the scale of minutes, we discover fast time-modulated bursting on the scale of seconds. Model comparison suggests that slow oscillations of transcriptional output are regulated by the amplitude of the bursts. Several polymerases may initiate during a burst.
GeNNius: An ultrafast drug-target interaction inference method based on graph neural networks
Authors: Veleiro Uxía , de la Fuente Jesús , Serrano Guillemo , Pizurica Marija , Casals Mikel , Pineda-Lucena Antonio , Vicent Silve , Ochoa Idoia , Gevaert Olivier , Hernáez Mikel
Published: June 2023

Drug-target interaction (DTI) prediction is a relevant but challenging task in the drug repurposing field. In-silico approaches have drawn particular attention as they can reduce associated costs and time commitment of traditional methodologies. Yet, current state-of-the-art methods present several limitations: existing DTI prediction approaches are computationally expensive, thereby hindering the ability to use large networks and exploit available datasets and, the generalization to unseen datasets of DTI prediction methods remains unexplored, which could potentially improve the development processes of DTI inferring approaches in terms of accuracy and robustness. In this work, we introduce Gennius(Graph Embedding Neural Network Interaction Uncovering System), a Graph Neural Network (GNN)-based method that outperforms state-of-the-art models in terms of both accuracy and time efficiency across a variety of datasets. We also demonstrated its prediction power to uncover new interactions by evaluating not previously known DTIs for each dataset. We further assessed the generalization capability of Genniusby training and testing it on different datasets, showing that this framework can potentially improve the DTI prediction task by training on large datasets and testing on smaller ones. Finally, we investigated qualitatively the embeddings generated by Gennius, revealing that the GNN encoder maintains biological information after the graph convolutions while diffusing this information through nodes, eventually distinguishing protein families in the node embedding space.

Code Availability

https://github.com/ubioinformat/GeNNius
Modeling Molecular Pathogenesis of Idiopathic Pulmonary Fibrosis-Associated Lung Cancer in Mice
Authors: Barravecchia Ivana , Lee Jennifer M. , Manassa Jason , Magnuson Brian , Cavanaugh Sophia , Steele Nina G. , Espinoza Carlos , Galban Craig J. , Ramnath Nithya , Frankel Timothy L. , di Magliano Marina Pasca , Galban Stefanie
Published: June 2023

Idiopathic Pulmonary Fibrosis (IPF) is characterized by progressive, often fatal loss of lung function due to overactive collagen production and tissue scarring. IPF patients have a sevenfold-increased risk of developing lung cancer. The COVID-19 pandemic has increased the number of patients with lung diseases, and infection can worsen prognoses for those with chronic lung diseases and disease-associated cancer. Understanding the molecular pathogenesis of IPF-associated lung cancer is imperative for identifying diagnostic biomarkers and targeted therapies that will facilitate prevention of IPF and progression to lung cancer. To understand how IPF-associated fibroblast activation, matrix remodeling, epithelial-mesenchymal transition, and immune modulation influences lung cancer predisposition, we developed a mouse model to recapitulate the molecular pathogenesis of pulmonary fibrosis-associated lung cancer using the bleomycin and the Lewis Lung Carcinoma models. Models of pulmonary fibrosis, particularly bleomycin-induced fibrosis, do not recapitulate all aspects of human disease; however, to simplify nomenclature, we refer to our bleomycin-induced fibrosis model as IPF. We demonstrate that development of pulmonary fibrosis-associated lung cancer is linked to increased recruitment or reprogramming of tumor-associated macrophages and a unique gene signature that supports an immune-suppressive microenvironment through secreted factors. Not surprisingly, pre-existing fibrosis provides a pre-metastatic niche and results in augmented tumor growth. Tumors associated with bleomycin-induced fibrosis are characterized by an epithelial-to-mesenchymal transition characterized by dramatic loss of cytokeratin expression.

Implications

We provide new therapeutic targets that may aid the characterization of tumors associated with lung diseases and development of treatment paradigms for lung cancer patients with pre-existing pulmonary diseases.
The increase of Cyclin A/cdk activity and of FAM122A-dependent inhibition of PP2A-B55 are the key events triggering mitosis
Authors: Lacroix Benjamin , Vigneron Suzanne , Labbé Jean Claude , Pintard Lionel , Labesse Gilles , Castro Anna , Lorca Thierry
Published: June 2023

Entry into mitosis has been classically attributed to the activation of cyclin B/cdk1 amplification loop by a partial pool of this kinase that becomes active at the end of G2. However, how this pool is activated is still unknown. Here we discovered a new role of the recently identified PP2A-B55 inhibitor FAM122A in triggering mitotic entry. Accordingly, the depletion of the orthologue of FAM122A inC. elegans, prevents entry into mitosis in germline stem cells. Moreover, our data in Xenopus egg extract strongly supports that FAM122A-dependent inhibition of PP2A-B55 could be the initial event promoting mitotic entry. The inhibition of this phosphatase allows the subsequent phosphorylation of first mitotic substrates by cyclin A/cdk resulting in cyclin B/cdk1 and Greatwall (Gwl) activation. However, interestingly, from Gwl activation, Arpp19/ENSA become phosphorylated and compete with FAM122A promoting its dissociation from PP2A-B55 and taking over its inhibition until the end of mitosis.
ArcheD, a residual neural network for prediction of cerebrospinal fluid amyloid-beta from amyloid PET images
Authors: Tagmazian Arina A. , Schwarz Claudia , Lange Catharina , Pitkänen Esa , Vuoksimaa Eero ,   the Alzheimer’s Disease Neuroimaging Initiative
Published: June 2023

Detection and measurement of amyloid-beta (Aβ) aggregation in the brain is a key factor for early identification and diagnosis of Alzheimer’s disease (AD). We aimed to develop a deep learning model to predict Aβ cerebrospinal fluid (CSF) concentration directly from amyloid PET images, independent of tracers, brain reference regions or preselected regions of interest. We used 1870 Aβ PET images and CSF measurements to train and validate a convolutional neural network (“ArcheD”). We evaluated the ArcheD performance in relation to episodic memory and the standardized uptake value ratio (SUVR) of cortical Aβ. We also compared the brain region’s relevance for the model’s CSF prediction within clinical-based and biological-based classifications. ArcheD-predicted Aβ CSF values correlated strongly with measured Aβ CSF values (r=0.81;p<0.001) and showed correlations with SUVR and episodic memory measures in all participants except in those with AD. For both clinical and biological classifications, cerebral white matter significantly contributed to CSF prediction (q<0.01), specifically in non-symptomatic and early stages of AD. However, in late-stage disease, brain stem, subcortical areas, cortical lobes, limbic lobe, and basal forebrain made more significant contributions (q<0.01). Considering cortical gray matter separately, the parietal lobe was the strongest predictor of CSF amyloid levels in those with prodromal or early AD, while the temporal lobe played a more crucial role for those with AD. In summary, ArcheD reliably predicted Aβ CSF concentration from Aβ PET scans, offering potential clinical utility for Aβ level determination and early AD detection.
Protein evolvability under rewired genetic codes
Authors: Rozhoňová Hana , Martí-Gómez Carlos , McCandlish David M. , Payne Joshua L.
Published: June 2023

The standard genetic code defines the rules of translation for nearly every life form on Earth. It also determines the amino acid changes accessible via single-nucleotide mutations, thus influencing protein evolvability — the ability of mutation to bring forth adaptive variation in protein function. One of the most striking features of the standard genetic code is its robustness to mutation, yet it remains an open question whether this robustness facilitates or frustrates protein evolvability. To answer this question, we use data from massively-parallel sequence-to-function assays to construct and analyze empirical adaptive landscapes under hundreds of thousands of rewired genetic codes, including those of codon compression schemes relevant to protein engineering and synthetic biology. We find that robust genetic codes tend to enhance protein evolvability by rendering smooth adaptive landscapes with few peaks, which are readily accessible from throughout sequence space. By constructing low-dimensional visualizations of these landscapes, which each comprise more than 16 million mRNA sequences, we demonstrate that alternative genetic codes can radically alter the topological features of the network of high-fitness genotypes. Whereas the genetic codes that optimize evolvability depend to some extent on the detailed relationship between amino acid sequence and protein function, we also uncover general design principles for engineering non-standard genetic codes for enhanced and diminished evolvability, which may facilitate directed protein evolution experiments and the biocontainment of synthetic organisms, respectively. Our findings demonstrate that the standard genetic code, a critical and near-universal cellular information processing system, not only mitigates replication and translation errors as compared to most alternative genetic codes, but also facilitates predictable and directional adaptive evolution by enabling evolving populations to readily find mutational paths to adaptation.
Functional Implications of the Exon 9 Splice Insert in GluK1 Kainate Receptors
Authors: Dhingra Surbhi , Chopade Prachi M. , Vinnakota Rajesh , Kumar Janesh
Published: June 2023

Kainate receptors are key modulators of synaptic transmission and plasticity in the central nervous system. Different kainate receptor isoforms with distinct spatiotemporal expressions have been identified in the brain. The GluK1-1 splice variant receptors, which are abundant in the adult brain, have an extra fifteen amino acids inserted in the amino-terminal domain (ATD) of the receptor resulting from alternative splicing of exon 9. However, the functional implications of this post-transcriptional modification are not yet clear. We employed a multi-pronged approach using cryogenic electron microscopy, electrophysiology, and other biophysical and biochemical tools to understand the structural and functional impact of this splice insert in the extracellular domain of GluK1 receptors. Our study reveals that the splice insert alters the key gating properties of GluK1 receptors and their modulation by the cognate auxiliary Neuropilin and tolloid-like (Neto) proteins 1 and 2. Mutational analysis identified the role of crucial splice residues that influence receptor properties and their modulation. Furthermore, the cryoEM structure of the variant shows that the presence of exon 9 in GluK1 does not affect the receptor architecture or domain arrangement in the desensitized state. Our study thus provides the first detailed structural and functional characterization of GluK1-1a receptors, highlighting the role of the splice insert in modulating receptor properties and their modulation.
ParSe 2.0: A web application that enables proteome-scale searches for sequences that drive protein-mediated phase separation
Authors: Wilson Colorado , Lewis Karen A. , Fitzkee Nicholas C. , Hough Loren E. , Whitten Steven T.
Published: June 2023

We have developed an algorithm, ParSe, that accurately identifies from the primary sequence those protein regions likely to exhibit physiological phase separation behavior. Originally, ParSe was designed to test the hypothesis that, for flexible proteins, phase separation potential is correlated to hydrodynamic size. While our results were consistent with that idea, we also found that many different descriptors could successfully differentiate between three classes of protein regions: folded, intrinsically disordered, and phase-separating intrinsically disordered. Consequently, numerous combinations of amino acid property scales can be used to make robust predictions of protein phase separation. Built from that finding, ParSe 2.0 uses an optimal set of property scales to predict domain-level organization and compute a sequence-based prediction of phase separation potential. The algorithm is fast enough to scan the whole of the human proteome in minutes on a single computer and is equally or more accurate than other published predictors in identifying proteins and regions within proteins that drive phase separation. Here, we describe a web application for ParSe 2.0 that may be accessed through a browser by visitinghttps://stevewhitten.github.io/Parse_v2_FASTAto quickly identify phase-separating proteins within large sequence sets, or by visitinghttps://stevewhitten.github.io/Parse_v2_webto evaluate individual protein sequences.
Starvation reduces thermal limits of the widespread copepodAcartia tonsa
Authors: Rueda Moreno Gaia A. , Sasaki Matthew C.
Published: June 2023

Organismal thermal limits affect a wide range of biogeographical and ecological processes. Copepods are some of the most abundant animals on the planet, and play key roles in aquatic habitats. Despite their abundance and ecological importance, there is limited data on the factors that affect copepod thermal limits, impeding our ability to predict how aquatic ecosystems will be affected by anthropogenic climate change. In a warming ocean, one factor that may have particularly important effects on thermal limits is the availability of food. A recently proposed feedback loop known as “metabolic meltdown” suggests that starvation and exposure to high temperatures interact to drastically reduce organismal thermal limits, increasing vulnerability to warming. To investigate one component of this feedback loop, we examined how starvation affects thermal limits (critical thermal maxima: CTmax) ofAcartia tonsa, a widespread estuarine copepod. We found that there was no effect of short duration exposure to starvation (up to two days). However, after three days, there was a significant decrease in the CTmax of starved copepods relative to the fed controls. Our results provide empirical evidence that extended periods of starvation reduce thermal limits, potentially initiating “metabolic meltdown” in this key species of coastal copepod. This suggests that changes in food availability may increase vulnerability of copepods to increasing temperatures, amplifying the effects of climate change on coastal systems.
Blood flow directionality establishes the SCN as source and OVLT as target within a new vascular portal pathway
Authors: Roy Ranjan K. , Yao Yifan , Green Isabella K. , Silver Rae , Stern Javier E.
Published: June 2023

The suprachiasmatic nucleus (SCN) is the locus of a brain clock that sets the phase of oscillation in cells throughout the brain and body. Anatomical evidence reveals a portal system linking the SCN and the OVLT (here termed SCN-OVLTp). This discovery begs the question of the direction of blood flow and the nature of diffusible signals that flow in this specialized vasculature. Here we show unequivocally that the direction of blood flow is from the SCN to the OVLT, that the rate of flow is under circadian regulation, and that vasopressin (AVP) is present in portal vessels following systemic injection. These findings highlight a previously unknown CNS communication pathway. It is well established that the SCN is required for circadian regulation of AVP in the CSF and that the OVLT bears AVP receptors. Specifically, SCN neurons are necessary for time-stamped signals such as the peptide AVP, that can travel via portal veins to a target in the OVLT. The OVLT, a circumventricular organ offering a “window to the brain,” can relay neural and diffusible signals to broad brain areas via its efferent connections and via the CSF. We conclude that the SCN-OVLTp, like that of the pituitary portal system, discovered almost a century ago, allows neurosecretions to reach nearby specialized target sites, thereby avoiding dilution in the systemic blood. In both of these brain portal pathways, the target site, namely the pituitary and OVLT respectively, relay signals broadly, to both the brain and the rest of the body.
ShinyMultiome.UiO: An interactive open-source framework utilizing Seurat Objects for visualizing single-cell Multiomes
Authors: Akshay Akshay , Sharma Ankush , Eskeland Ragnhild
Published: June 2023

Motivation

Single-cell genomics has been revolutionized by the advent of single-cell Multiome sequencing which allows for simultaneous profiling of chromatin accessibility and gene expression in individual nuclei. The analysis and interpretation of large and often complex scMultiome datasets requires in-depth knowledge of computational programming.

Results

We present ShinyMultiome.UiO, a user-friendly, integrative, and opensource web-based tool that supports Seurat objects for visualization of single-cell Multiome. The ShinyMultiome.UiO facilitates interactive reporting and comprehensive characterization of cellular heterogeneity and regulatory landscapes. With ShinyMultiome.UiO, users can facilitate collaborative efforts for interpre-tation of single-cell Multiome data and make it available to the public.

Availability and implementation

https://github.com/EskelandLab/ShinyMultiomeUiOand demo server,https://cancell.medisin.uio.no/ShinyMultiome.UiO/set up with a PBMC reference dataset.

Contact

Ankush.Sharma@medisin.uio.no&Ragnhild.Eskeland@medisin.uio.no
Maintaining task performance levels under cognitive load while walking requires widespread reallocation of neural resources: A Mobile Brain-Body Imaging (MoBI) study
Authors: Patelaki Eleni , Foxe John J. , McFerren Amber L. , Freedman Edward G.
Published: June 2023

The neural underpinnings of increasing cognitive load during walking, despite being ubiquitous in everyday life, is still not fully understood. This study elucidates the neural mechanisms underlying increased cognitive load while walking, by employing 2 versions of a Go/NoGo response inhibition task, namely the 1-back Go/NoGo task and the more cognitively demanding 2-back Go/NoGo task, during sitting or walking on a treadmill. By using the Mobile Brain/Body Imaging (MoBI) modality, electroencephalographic (EEG) activity, three-dimensional (3D) gait kinematics and task-related behavioral responses were collected from 34 young adults for the 1-back Go/NoGo task and 34 young adults for the 2-back Go/NoGo task. Interestingly, increasing cognitive-inhibitory load from 1-back to 2-back Go/NoGo during walking was not associated with any detectable costs in response accuracy, response speed, or gait consistency; however, it came with attenuations in walking-related EEG amplitude changes during both successful inhibitions (correct rejections) and successful executions (hits) of the ‘Go’ motor response. During correct rejections, such attenuations were detected over frontal regions, during latencies related to sensory gain control, conflict monitoring and working memory storage and processing. During hits, attenuations were found over left-parietal regions, during latencies related to orienting attention to and selecting the ‘Go’ motor plan, as well as over central regions, during latencies linked to executing the ‘Go’ motor response. The pattern of attenuation in walking-related EEG amplitude changes, manifested by the 2-back Go/NoGo group, is thought to reflect more effortful recalibration of the above neural processes, a mechanism which might be a key driver of performance maintenance in the face of increased cognitive demands while walking. Overall, the present findings shed light on the extent of the neurocognitive capacity of young adults, thus revealing the employed methodology as promising for better understanding how factors such as aging or neurological disorders could impinge on this capacity.
Assembly archetypes in ecological communities
Authors: Flores-Arguedas Hugo , Antolin-Camarena Omar , Saavedra Serguei , Angulo Marco Tulio
Published: June 2023

An instrumental discovery in comparative and developmental biology is the existence of assembly archetypes that synthesize the vast diversity of organisms’ body plans—from legs and wings to human arms—into simple, interpretable, and general design principles. Here we combine a novel mathematical formalism based on Category Theory with experimental data to show that similar “assembly archetypes” exist at the larger organization scale of ecological communities when assembling a species pool across diverse environmental contexts, particularly when species interactions are highly structured. We applied our formalism to clinical data discovering two assembly archetypes that differentiate between healthy and unhealthy human gut microbiota. The concept of assembly archetypes and the methods to synthesize them can pave the way to discovering the general assembly principles of the ecological communities we observe in nature.
Recombinase-Independent AAV for Anterograde Transsynaptic Tracing
Authors: Faress Islam , Khalil Valentina , Yamamoto Haruka , Sajgo Szilard , Yonehara Keisuke , Nabavi Sadegh
Published: June 2023

Viral transsynaptic labeling has become indispensable for investigating the functional connectivity of neural circuits. Adeno-associated virus serotype 1 (AAV1) allows for anterograde transneuronal labeling and manipulation of postsynaptic neurons. However, it is limited to delivering an AAV1 expressing a recombinase which relies on using transgenic animals or genetic access to postsynaptic neurons. We reasoned that a strong expression level could overcome this limitation. To this end, we used a self-complementary AAV1 (scAAV1) under a strong promoter (CAG). We demonstrated the anterograde transneuronal efficiency of scAAV1 by delivering a fluorescent marker in mouse retina-superior colliculus and thalamic-amygdala pathways in a recombinase-independent manner. In addition to investigating neuronal connectivity, scAAV1.CAG may be suitable for functional manipulation and imaging.
Rat Deconvolution as Knowledge Miner for Immune Cell Trafficking from Toxicogenomics Databases
Authors: Morita Katsuhisa , Mizuno Tadahaya , Azuma Iori , Suzuki Yutaka , Kusuhara Hiroyuki
Published: June 2023

Toxicogenomics databases are useful for understanding biological responses in individuals because they include a diverse spectrum of biological responses. Although these databases contain no information regarding immune cells in the liver, which are important in the progression of liver injury, deconvolution that estimates cell-type proportions from bulk transcriptome could extend immune information. However, deconvolution has been mainly applied to humans and mice and less often to rats, which are the main target of toxicogenomics databases. Here, we developed a deconvolution method for rats to retrieve information regarding immune cells from toxicogenomics databases. The rat-specific deconvolution showed high correlations for several types of immune cells between spleen and blood, and between liver treated with toxicants compared with those based on human and mouse data. Additionally, we found 4 clusters of compounds in Open TG-GATEs database based on estimated immune cell trafficking, which are different from those based on transcriptome data itself. The contributions of this work are three-fold. First, we obtained the gene expression profiles of 6 rat immune cells necessary for deconvolution. Second, we clarified the importance of species differences on deconvolution. Third, we retrieved immune cell trafficking from toxicogenomics databases. Accumulated and comparable immune cell profiles of massive data of immune cell trafficking in rats could deepen our understanding of enable us to clarify the relationship between the order and the contribution rate of immune cells, chemokines and cytokines, and pathologies. Ultimately, these findings will lead to the evaluation of organ responses in Adverse Outcome Pathway.
Direct quantification of unicellular algae sinking velocities reveals cell size, light, and nutrient-dependence
Authors: Miettinen Teemu P. , Gomez Annika L. , Wu Yanqi , Wu Weida , Usherwood Thomas R. , Hwang Yejin , Roller Benjamin R.K. , Polz Martin F. , Manalis Scott R.
Published: June 2023

Eukaryotic phytoplankton, also known as algae, form the basis of marine food webs and drive marine carbon sequestration when their biomass sinks to the ocean floor. Algae must regulate their vertical movement, as determined by motility and gravitational sinking, to balance access to light at the surface and nutrients in deeper layers. However, the regulation of gravitational sinking velocities remains largely unknown, especially in motile species. Here, we directly quantify single-cell masses and volumes to calculate sinking velocities according to Stokes’ law in diverse clades of unicellular marine microalgae. Our results reveal the cell size, light, and nutrient-dependency of sinking velocities. We identify motile dinoflagellate and green algal species that increase their sinking velocity in response to starvation. Mechanistically, this increased cell sinking is achieved by photosynthesis-driven accumulation of carbohydrates, which increases cell mass and density. Moreover, cell sinking velocities correlate inversely with proliferation rates, and the mechanism regulating cell sinking velocities integrates signals from multiple nutrients. Our findings suggest that the regulation of cell composition according to environmental conditions contributes to the vertical movement of motile cells in the oceans. More broadly, our approach for sinking velocity measurements expands the study of gravitational sinking to motile cells and supports the modeling of marine carbon pump and nutrient cycles.
Study protocol for a cluster randomized controlled trial for 16 weeks to assess the effect of almond consumption on glycemic control and gut health in prediabetes adults in rural settings of India
Authors: Vaidya Ruchi , Chaudhury Nayanjeet , Kalra Pramila , Nair Sreekumaran , Prabhakar Bellur S.
Published: June 2023

Introduction

Almonds have prebiotic potential to maintain gut health and regulate glycemia. Western studies have shown their positive effects in preventing non-communicable diseases like diabetes and CVDs. However, there is a lack of well-designed studies involving Asian Indians, who have a higher predisposition to diabetes due to their unique ‘Asian phenotype’. Therefore, this study aims to evaluate the impact of almond supplementation on glycemic control and gut health in prediabetic adults in rural India through a randomized clinical trial.

Methods and Analysis

A parallel cluster randomized controlled trial with 178 prediabetic participants aged 20-50, both genders, with a BMI of 18.9-25 kg/m2, will be conducted in rural areas of Chikkaballapur, Kolar, and rural Bangalore districts in India. The intervention group will receive 56g of almonds as mid-morning snacks for 16 weeks, while the control group will receive cereal pulse based traditional isocaloric snacks under the closed supervision of the study investigators. Anthropometry, clinical, and biochemical parameters will be measured at 0, 8th, and 16th weeks, and a subgroup of 120 participants will undergo gut health analysis. GLP 1 analysis will be conducted on 30 participants at 0 and 16th week. Statistical analysis will be performed using SPSS for Windows V 27.0, and both ITT and per-protocol analyses will be conducted.

Ethics and Dissemination

Ethics approval was obtained from the Institutional Ethics Committee at Ramaiah Medical College, Bangalore, Karnataka, India (DRPEFP7672021). Results from this trial will be disseminated through publication in peer-reviewed journals, national and international presentations.

Trial Registration Number

The trial is registered in the clinical trial registry of India (CTRI/2023/03/050421).

ARTICLE SUMMARY

Strengths and Limitations:

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The study is the first field-based trial in rural settings to assess the effect of almond consumption versus traditional cereal pulse-based snacks on prediabetes adults’ glycemic control and gut health.

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The compliance management is crucially designed by performing an intervention on one-to-one closed supervision, assessment of serum tocopherol levels, and regular follow up of any adverse events.

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The upcoming metagenomic analysis and the gut metabolites like short chain fatty acids (SCFA) and GLP 1 will significantly advance our understanding of the impact of almonds on the gut health of prediabetes adults.

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A potential limitation of the study is that it will not be feasible to follow the participants after the post intervention period.
A case study ofWhirly1(WHY1) evolution in the angiosperms: altered sequence, splicing, and expression in a clade of early-transitional mycoheterotrophic orchids
Authors: Muti Rachel M. , Barrett Craig F. , Sinn Brandon T.
Published: June 2023

The plastid-targeted transcription factorWhirly1(WHY1) has been implicated in chloroplast biogenesis, plastid genome stability, and fungal defense response, which together represent characteristics of interest for the study of autotrophic losses across the angiosperms. While gene loss in the plastid and nuclear genomes has been well studied in mycoheterotrophic plants, the evolution of the molecular mechanisms impacting genome stability are completely unknown. Here we characterize the evolution ofWHY1in four early-transitional mycoheterotrophic orchid species in the genusCorallorhizaby synthesizing the results of phylogenetic, transcriptomic, and comparative genomic analyses withWHY1genomic sequences sampled from 21 orders of angiosperms. We found an increased number of non-canonicalWHY1isoforms assembled from all but the greenestCorallorhizaspecies, including intron retention in some isoforms. WithinCorallorhiza, phylotranscriptomic analyses revealed the presence of tissue-specific differential expression ofWHY1in only the most photosynthetically capable species and a coincident increase in the number of non-canonicalWHY1isoforms assembled from fully mycoheterotrophic species. Gene- and codon-level tests ofWHY1selective regimes did not infer significant signal of either relaxed selection or episodic diversifying selection inCorallorhiza, but did so for relaxed selection in the late-stage full mycoheterotrophic orchidsEpipogium aphyllumandGastrodia elata. Taken together, this study provides the most comprehensive view ofWHY1evolution in angiosperms to date. Our analyses reveal that splicing alteration and decreased expression ofWHY1are coincident with deceased plastome stability in a group of early-transitional mycoheterotrophic orchids and that these changes may precede the selective shifts observed in late-stage mycoheterotrophic species.
Bioorthogonal caging-group-free photoactivatable probes for minimal-linkage-error nanoscopy
Authors: Aktalay Ayse , Lincoln Richard , Heynck Lukas , Lima Maria Augusta do R. B. F. , Butkevich Alexey N. , Bossi Mariano L. , Hell Stefan W.
Published: June 2023

Here we describe highly compact, click compatible, and photoactivatable dyes for super-resolution fluorescence microscopy (nanoscopy). By combining the photoactivatable xanthone (PaX) core with a tetrazine group, we achieve minimally sized and highly sensitive molecular dyads for selective labeling of unnatural amino acids introduced by genetic code expansion. We exploit the excited state quenching properties of the tetrazine group to attenuate the photoactivation rates of the PaX, and further reduce the overall fluorescence emission of the photogenerated fluorophore, providing two mechanisms of selectivity to reduce off-target signal. Coupled with MINFLUX nanoscopy, we demonstrate our dyads in the minimal-linkage-error imaging of vimentin filaments, demonstrating the molecular scale precision in fluorophore positioning.
Zona incerta distributes a broad movement signal that modulates behavior
Authors: Hormigo Sebastian , Zhou Ji , Chabbert Dorian , Sajid Muhammad S. , Busel Natan , Castro-Alamancos Manuel A.
Published: June 2023

The zona incerta is a subthalamic nucleus made up mostly of GABAergic neurons. It has wide- ranging inputs and outputs and is believed to have many integrative functions that link sensory stimuli with motor responses to guide behavior. However, its role is not well established perhaps because few studies have measured the activity of zona incerta neurons in behaving animals under different conditions. To record the activity of zona incerta neurons during exploratory and cue-driven goal-directed behaviors, we used electrophysiology in head-fixed mice moving on a spherical treadmill and fiber photometry in freely moving mice. We found two groups of neurons based on their sensitivity to movement, with a minority of neurons responding to whisker stimuli. Furthermore, zona incerta GABAergic neurons robustly code the occurrence of exploratory and goal-directed movements, but not their direction. To understand the function of these activations, we performed genetically targeted lesions and optogenetic manipulations of zona incerta GABAergic neurons during exploratory and goal-directed behaviors. The results showed that the zona incerta has a role in modulating the movement associated with these behaviors, but this has little impact on overall performance. Zona incerta neurons distribute a broad corollary signal of movement occurrence to their diverse projection sites, which regulates behavior.
Fractional Hitting Sets for Efficient and Lightweight Genomic Data Sketching
Authors: Rouzé Timothé , Martayan Igor , Marchet Camille , Limasset Antoine
Published: June 2023

The exponential increase in publicly available sequencing data and genomic resources necessitates the development of highly efficient methods for data processing and analysis. Locality-sensitive hashing techniques have successfully transformed large datasets into smaller, more manageable sketches while maintaining comparability using metrics such as Jaccard and containment indices. However, fixed-size sketches encounter difficulties when applied to divergent datasets.

Scalable sketching methods, such as Sourmash, provide valuable solutions but still lack resourceefficient, tailored indexing. Our objective is to create lighter sketches with comparable results while enhancing efficiency. We introduce the concept of Fractional Hitting Sets, a generalization of Universal Hitting Sets, which uniformly cover a specified fraction of thek-mer space. In theory and practice, we demonstrate the feasibility of achieving such coverage with simple but highly efficient schemes.

By encoding the coveredk-mers as super-k-mers, we provide a space-efficient exact representation that also enables optimized comparisons. Our novel tool, SuperSampler, implements this scheme, and experimental results with real bacterial collections closely match our theoretical findings.

In comparison to Sourmash, SuperSampler achieves similar outcomes while utilizing an order of magnitude less space and memory and operating several times faster. This highlights the potential of our approach in addressing the challenges presented by the ever-expanding landscape of genomic data.

SuperSampler is an open-source software and can be accessed atgithub.com/TimRouze/supersampler. The data required to reproduce the results presented in this manuscript is available atgithub.com/TimRouze/Expe_SPSP.
FLOP: Tasks for Fitness Landscapes Of Protein wildtypes
Authors: Groth Peter Mørch , Michael Richard , Salomon Jesper , Tian Pengfei , Boomsma Wouter
Published: June 2023

Protein engineering has the potential to create optimized protein variants with improved properties and function. An initial step in the protein optimization process typically consists of a search among natural (wildtype) sequences to find the naturally occurring proteins with the most desirable properties. Promising candidates from this initial discovery phase then form the basis of the second step: a more local optimization procedure, exploring the space of variants separated from this candidate by a number of mutations. While considerable progress has been made on evaluating machine learning methods on single protein datasets, benchmarks of data-driven approaches for global fitness landscape exploration are still lacking. In this paper, we have carefully curated a representative benchmark dataset, which reflects industrially relevant scenarios for the initial wildtype discovery phase of protein engineering. We focus on exploration within a protein family, and investigate the downstream predictive power of various protein representation paradigms, i.e., protein language model-based representations, structure-based representations, and evolution-based representations. Our benchmark highlights the importance of coherent split strategies, and how we can be misled into overly optimistic estimates of the state of the field. The codebase and data can be accessed viahttps://github.com/petergroth/FLOP.