bluuebunny/crossref_metadata_2025 huggingface dataset:
Uncertainty Quantification in Cost-effectiveness Analysis for Stochastic-based Infectious Disease Models: Insights from Surveillance on Lymphatic Filariasis
Authors: Antony Oliver Mary Chriselda , Graham Matthew , Manolopoulou Ioanna , Medley Graham F. , Pellis Lorenzo , Pouwels Koen B , Thorpe Matthew , Hollingsworth T. Deirdre
Published: August 2024

Cost-effectiveness analyses (CEA) typically involve comparing effectiveness and costs of one or more interventions compared to standard of care, to determine which intervention should be optimally implemented to maximise population health within the constraints of the healthcare budget. Traditionally, cost-effectiveness evaluations are expressed using incremental cost-effectiveness ratios (ICERs), which are compared with a fixed willingness-to-pay (WTP) threshold. Due to the existing uncertainty in costs for interventions and the overall burden of disease, particularly with regard to diseases in populations that are difficult to study, it becomes important to consider uncertainty quantification whilst estimating ICERs.

To tackle the challenges of uncertainty quantification in CEA, we propose an alternative paradigm utilizing the Linear Wasserstein framework combined with Linear Discriminant Analysis (LDA) using a demonstrative example of lymphatic filariasis (LF). This approach uses geometric embeddings of the overall costs for treatment and surveillance, disability-adjusted lifeyears (DALYs) averted for morbidity by quantifying the burden of disease due to the years lived with disability, and probabilities of local elimination over a time-horizon of 20 years to evaluate the cost-effectiveness of lowering the stopping thresholds for post-surveillance determination of LF elimination as a public health problem. Our findings suggest that reducing the stopping threshold from <1% to <0.5% microfilaria (mf) prevalence for adults aged 20 years and above, under various treatment coverages and baseline prevalences, is cost-effective. When validated on 20% of test data, for 65% treatment coverage, a government expenditure of WTP ranging from $500 to $3,000 per 1% increase in local elimination probability justifies the switch to the lower threshold as cost-effective.

Stochastic model simulations often lead to parameter and structural uncertainty in CEA. Uncertainty may impact the decisions taken, and this study underscores the necessity of better uncertainty quantification techniques within CEA for making informed decisions.
Nanopore-based analysis unravels the genetic landscape and phylogenetic placement of human-infectingTrichurisspecies in Côte d’Ivoire, Tanzania, Uganda, and Laos
Authors: Rahman Nurudeen , Bär Max A. , Dommann Julian , Hürlimann Eveline , Coulibaly Jean T. , Ali Said , Sayasone Somphou , Beinamaryo Prudence , Keiser Jennifer , Schneeberger Pierre H.H.
Published: August 2024

Soil-transmitted helminthiases (STH), including trichuriasis, pose a significant global burden, affecting numerous mammalian hosts. Traditional diagnostic methods have struggled to differentiate species within theTrichurisgenus, prompting the use of molecular techniques to understand the diversity and zoonotic transmission ofTrichurisspp. among humans and non-human primates (NHP), dogs, and pigs. In this study, we used nanopore-based full-length ITS2 rDNA sequencing to genetically characterize and confirm the phylogenetic placement of the newly identified human-infectingTrichuris incognitaand the well-knownTrichuris trichiura. Using 670 samples from clinical studies in Côte d’Ivoire, Laos, Tanzania, and Uganda, along with publicly available ITS2 sequences, we confirmed two distinct clusters of human-infectingTrichurisspecies. We found a varying prevalence ofT. incognitaandT. trichiuraacross the four countries and that these were also present in NHP. Our findings demonstrated that ITS2 fragment length accurately differentiates both human-infectingTrichurisspecies and thus makes it a good diagnostic marker for future point-of-care applications in resource-constrained settings.
An updated and expanded characterization of the biological sciences academic job market
Authors: Flynn Brooklynn , Kozik Ariangela J. , Cheng You , Hagan Ada K. , Ng Jennifer , Smith Christopher T. , Haage Amanda , Jadavji Nafisa M.
Published: August 2024

In the biological sciences, many areas of uncertainty exist regarding the factors that contribute to success within the faculty job market. Earlier work from our group reported that beyond certain thresholds, academic and career metrics like the number of publications, fellowships or career transition awards, and years of experience did not separate applicants who received job offers from those who did not. Questions still exist regarding how academic and professional achievements influence job offers and if candidate demographics differentially influence outcomes. To continue addressing these gaps, we initiated surveys collecting data from faculty applicants in the biological sciences field for three hiring cycles in North America (Fall 2019 to the end of May 2022), a total of 449 respondents were included in our analysis. These responses highlight the interplay between various scholarly metrics, extensive demographic information, and hiring outcomes, and for the first time, allowed us to look at persons historically excluded due to ethnicity or race (PEER) status in the context of the faculty job market. Between 2019 and 2022, we found that the number of applications submitted, position seniority, and identifying as a women or transgender were positively correlated with a faculty job offer. Applicant age, residence, first generation status, and number of postdocs, however, were negatively correlated with receiving a faculty job offer. Our data are consistent with other surveys that also highlight the influence of achievements and other factors in hiring processes. Providing baseline comparative data for job seekers can support their informed decision-making in the market and is a first step towards demystifying the faculty job market.
Motor somatotopy impacts imagery strategy success in human intracortical brain-computer interfaces
Authors: Kunigk N.G. , Schone H.R. , Gontier C. , Hockeimer W. , Tortolani A.F. , Hatsopoulos N.G. , Downey J.E. , Chase S.M. , Boninger M.L. , Dekleva B.D. , Collinger J.L.
Published: August 2024

The notion of a somatotopically organized motor cortex, with movements of different body parts being controlled by spatially distinct areas of cortex, is well known. However, recent studies have challenged this notion and suggested a more distributed representation of movement control. This shift in perspective has significant implications, particularly when considering the implantation location of electrode arrays for intracortical brain-computer interfaces (iBCIs). We sought to evaluate whether the location of neural recordings from the precentral gyrus, and thus the underlying somatotopy, has any impact on the imagery strategies that can enable successful iBCI control. Three individuals with a spinal cord injury were enrolled in an ongoing clinical trial of an iBCI. Participants had two intracortical microelectrode arrays implanted in the arm and/or hand areas of the precentral gyrus based on presurgical functional imaging. Neural data were recorded while participants attempted to perform movements of the hand, wrist, elbow, and shoulder. We found that electrode arrays that were located more medially recorded significantly more activity during attempted proximal arm movements (elbow, shoulder) than did lateral arrays, which captured more activity related to attempted distal arm movements (hand, wrist). We also evaluated the relative contribution from the two arrays implanted in each participant to decoding accuracy during calibration of an iBCI decoder for translation and grasping tasks. For both task types, imagery strategy (e.g., reaching vs. wrist movements) had a significant impact on the relative contributions of each array to decoding. Overall, we found some evidence of broad tuning to arm and hand movements; however, there was a clear bias in the amount of information accessible about each movement type in spatially distinct areas of cortex. These results demonstrate that classical concepts of somatotopy can have real consequences for iBCI use, and highlight the importance of considering somatotopy when planning iBCI implantation.
Discovering Genetic Signatures Associated with Alzheimer’s Disease in Tiled Whole Genome Sequence Data: Results from the Artificial Intelligence for Alzheimer’s Disease (AI4AD) Consortium
Authors: Zaranek Sarah Wait , Zaranek Alexander Wait , Amstutz Peter , Bao Jingxuan , Chen Jiong , Clegg Tom , Craft Hannah , Jo Taeho , Lee Brian , Nho Kwangsik , Thomopoulos Sophia I. , Davatzikos Christos , Shen Li , Huang Heng , Thompson Paul M. , Saykin Andrew J. ,   the Alzheimer’s Disease Neuroimaging Initiative (as a consortium author) for the AI4AD Initiative
Published: August 2024

Currently, the ability to analyze large-scale whole genome sequence (WGS) data is limited due to both the size of the data and the inability of many existing tools to scale. To address this challenge, we use data “tiling” to efficiently partition whole genome sequences into smaller segments resulting in a simple numeric matrix of small integers. This lossless representation is particularly suitable for machine learning (ML) models. As an example of the benefits of tiling, we showcase results from tiled data as part of the Artificial Intelligence for Alzheimer’s Disease (AI4AD) consortium. AI4AD is a coordinated initiative to develop transformative AI approaches for high throughput analysis of next generation sequencing and related imaging, AD biomarker, and cognitive data. The collective effort integrates imaging, genomic, biomarker, and cognitive data to address fundamental barriers in AD prevention and drug discovery. One of the project’s initial aims is to discover new genetic signatures in WGS data that can be used to understand AD risk and progression in conjunction with imaging, biomarker and cognitive data. We tiled and analyzed 15,000+ genomes from the Alzheimer’s Disease Sequencing Project (ADSP) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We tile 11,762 genomes, a subset of the release which does not include family-based datasets (AD Cases: 4,983, age range: 50-90 years, mean age: 73.8 years). We illustrate the use of tiled data in ML classification methods to predict phenotypes. Specifically, we identify and prioritize tile variants/genetic variants that are possible genetic signatures for AD. The model shows added predictive value from variants of genes previously found to be associated with AD risk, age of onset, neurofibrillary tangle measurements, and other AD-related traits–including the APOE variant (rs429358).
Unveiling the Landscape of Reportable Genetic Secondary Findings in the Spanish Population: A Comprehensive Analysis Using the Collaborative Spanish Variant Server Database
Authors: Carmona Rosario , Pérez-Florido Javier , Roldán Gema , Loucera Carlos , Aquino Virginia , Toro-Barrios Noemí , Fernández-Rueda José L. , Bostlemann Gerrit , López-López Daniel , Ortuño Francisco M. , Morte Beatriz , Peña-Chilet María , Dopazo Joaquín ,   CSVS Crowdsourcing Group
Published: August 2024

The escalating adoption of Next Generation Sequencing (NGS) in clinical diagnostics reveals genetic variations, termed secondary findings (SFs), with health implications beyond primary diagnoses. The Collaborative Spanish Variant Server (CSVS), a crowdsourced database, contains genomic data from more than 2100 unrelated Spanish individuals. Following the American College of Medical genetics (ACMG) guidelines, CSVS was analyzed, identifying pathogenic or likely pathogenic variants in 78 actionable genes (ACMG list v3.1) to ascertain SF prevalence in the Spanish population. Among 1129 samples, 60 reportable SFs were found in 5% of individuals, impacting 32 ACMG-listed genes, notably associated with cardiovascular disease (59.4%), cancer (25%), inborn errors of metabolism (6.3%), and other miscellaneous phenotypes (9.4%). The study emphasizes utilizing dynamic population databases for periodic SF assessment, aligning with evolving ACMG recommendations. These findings illuminate the prevalence of significant genetic variants, enriching understanding of secondary findings in the Spanish population.
Within-host modelling of primaquine-induced haemolysis in hemizygote glucose-6-phosphate dehydrogenase deficient healthy volunteers
Authors: Watson James A , Mehdipour Parinaz , Moss Robert , Jittamala Podjanee , Zaloumis Sophie , Price David J , Dini Saber , Hanboonkunupakarn Borimas , Leungsinsiri Pawanrat , Poovorawan Kittiyod , Chotivanich Kesinee , Bancone Germana , Commons Robert J , Day Nicholas PJ , Pukrittayakamee Sasithon , Taylor Walter RJ , White Nicholas J , Simpson Julie A
Published: August 2024

Primaquine is the only widely available drug to prevent relapses ofPlasmodium vivaxmalaria. Primaquine is underused because of concerns over oxidant haemolysis in glucose-6-phosphate dehydrogenase (G6PD) deficiency. A pharmacometric trial showed that ascending-dose radical cure primaquine regimens causing ‘slow burn’ haemolysis were safe in G6PD deficient male volunteers. We developed and calibrated a within-host model of primaquine haemolysis in G6PD deficiency, using detailed serial haemoglobin and reticulocyte count data from 23 hemizygote deficient volunteers given ascending-dose primaquine (1,523 individual measurements over 656 unique timepoints). We estimate that primaquine doses of ∼0.75mg base/kg reduce the circulating lifespan of deficient erythrocytes by ∼30 days in individuals with common Southeast AsianG6PDvariants. We predict that 5mg/kg primaquine total dose can be administered safely to G6PD deficient individuals over 14 days with expected haemoglobin drops of 18 to 43% (2.7 to 6.5g/dL drop from a baseline of 15g/dL).
Nanoscale volumetric fluorescence imaging via photochemical sectioning
Authors: Wang Wei , Ruan Xiongtao , Liu Gaoxiang , Milkie Daniel E. , Li Wenping , Betzig Eric , Upadhyayula Srigokul , Gao Ruixuan
Published: August 2024

Optical nanoscopy of intact biological specimens has been transformed by recent advancements in hydrogel-based tissue clearing and expansion, enabling the imaging of cellular and subcellular structures with molecular contrast. However, existing high-resolution fluorescence microscopes have limited imaging depth, which prevents the study of whole-mount specimens without physical sectioning. To address this challenge, we developed “photochemical sectioning,” a spatially precise, light-based sample sectioning process. By combining photochemical sectioning with volumetric lattice light-sheet imaging and petabyte-scale computation, we imaged and reconstructed axons and myelination sheaths across entire mouse olfactory bulbs at nanoscale resolution. An olfactory-bulb-wide analysis of myelinated and unmyelinated axons revealed distinctive patterns of axon degeneration and de-/dysmyelination in the neurodegenerative mouse, highlighting the potential for peta- to exabyte-scale super-resolution studies using this approach.
Withania somnifera root extract (LongeFera-TM) confers beneficial effects on health and lifespan of the model worm Caenorhabditis elegans
Authors: Thakkar Nidhi , Gajera Gemini , Mehta Dilip , Nair Sujit , Kothari Vijay
Published: August 2024

Withania somnifera is among the most widely prescribed medicinal plants in traditional Indian medicine. Hydroalcoholic extract of the roots of this plant was investigated for its effects on the overall health and lifespan of the model worm Caenorhabditis elegans. Extract-exposed worms registered longer lifespan, higher fertility, better motility and metabolic activity. Whole transcriptome analysis of the extract-treated worms revealed the differential expression of the genes associated with lifespan extension, eggshell assembly and integrity, progeny formation, yolk lipoproteins, collagen synthesis, cuticle molting, etc. This extract seems to exert its beneficial effect on C. elegans partly by triggering remodeling of the developmentally programmed apical extracellular matrix (aECM). Differential expression of certain important genes (cpg-2, cpg-3, sqt-1, dpy-4, dpy-13, and col-17) was confirmed through PCR assay too. Some of the differently expressed genes (gfat-2, unc-68, dpy-4, dpy-13, col-109, col-169, and rmd-1) in worms experiencing pro-health effect of the extract were found through cooccurrence analysis to have their homologous counterpart in humans. Our results validate the potential of W. somnifera extract as a phytopharmaceutical.
The effect of parental conflict on imprinted genes inA. lyrata
Authors: Le Veve Audrey , İltaş Ömer , Dutheil Julien Y. , Lafon Placette Clément
Published: August 2024

Genomic imprinting is a form of gene regulation resulting in the unequal expression of the two parental alleles. A common assumption is that parental conflict over resource allocation to the offspring promotes directional selection on imprinted genes, but so far, most studies addressing this question have focused on autogamous species, whose parental conflict is expected to be low. Moreover, parental conflict is expected to promote antagonistic coevolution between imprinted genes, but this has never been tested so far. To address these knowledge gaps, we searched for signals of selection on imprinted genes across the Brassicaceae family based on phylogenetic approaches. We then investigated and compared footprints of selection on imprinted genes in allogamous and autogamous populations ofArabidopsis lyrata. Finally, we investigated signals of coevolution across imprinted genes based on phylogenetics and genomics approaches. Overall, we did not find specific signals of selection on imprinted genes in the allogamous populations ofA. lyrata. Despite some exceptions, these genes were overall not associated with directional selection in allogamous populations and were poorly affected by the mating system, suggesting a limited role of parental conflict. Nevertheless, non-imprinted endosperm genes presented typical signals of balancing selection across the Brassicaceae, as expected in the case of unresolved intralocus sexual conflict. Finally, we found imprinted genes showing signals of recent coevolution, but not related to specific sites, suggesting that drivers other than protein interactions lead to the coevolution between imprinted genes.
Drug Metabolism and Transport Capacity of Endothelial Cells, Pericytes, and Astrocytes: Implications for CNS Drug Disposition
Authors: Wilkins Hannah N. , Knerler Stephen A. , Warshanna Ahmed , Ortiz Rodnie Colón , Haas Kate , Orsburn Benjamin C. , Williams Dionna W.
Published: August 2024

Therapeutically targeting the brain requires interactions with endothelial cells, pericytes, and astrocytes at the blood brain barrier (BBB). We evaluated regional and cell-type specific drug metabolism and transport mechanisms using rhesus macaques andin vitrotreatment of primary human cells. Here, we report heterogenous distribution of representative drugs, tenofovir (TFV), emtricitabine (FTC), and their active metabolites, which cerebrospinal fluid measures could not reflect. We found that all BBB cell types possessed functional drug metabolizing enzymes and transporters that promoted TFV and FTC uptake and pharmacologic activation. Pericytes and astrocytes emerged as pharmacologically dynamic cells that rivaled hepatocytes and were uniquely susceptible to modulation by disease and treatment. Together, our findings demonstrate the importance of considering the BBB as a unique pharmacologic entity, rather than viewing it as an extension of the liver, as each cell type possesses distinct drug metabolism and transport capacities that contribute to differential brain drug disposition.
Root traits and tree functional groups determine variability in root exudation and N uptake rates in mature temperate trees
Authors: Oh Young E. , Midgley Meghan G. , McCormack M. Luke , Beidler Katilyn V. , McCall Marshall , Henderson Savannah , Braghiere Renato K. , Phillips Richard P.
Published: August 2024

Root exudation and nutrient uptake have profound impacts on soil biogeochemistry, yet quantification of these fluxes in mature trees is rare.

We measured exudation and nitrogen (N) uptake rates of 11 tree species - gymnosperms and angiosperms associating with arbuscular mycorrhizal (AM) or ectomycorrhizal (EcM) fungi – at the Morton Arboretum, USA, to explore relationships between root traits, exudation and nitrogen uptake.

Exudation rates were affected by phylogenetic group and mycorrhizal type, as EcM-gymnosperms exuded more carbon than the other three groups. Exudation correlated positively with specific root area and negatively with root tissue density. Nitrogen uptake did not differ between phylogenetic groups or mycorrhizal types. Root traits predicting N uptake varied with N form: root tissue density and phylogenetic group predicted ammonium uptake, whereas exudation and phylogenetic group predicted nitrate uptake. In root economic space, exudation and uptake aligned weakly with the fast side of the conservation gradient, though the two processes were not correlated.

Our results indicate that exudation and N uptake are dynamic processes not predicted easily by species identity, plant functional groups or root traits. As such, incorporating these processes into trait frameworks and large-scale models may require ancillary information about the soil environment and whole-tree physiology.
The Paleozoic assembly of the holocephalian body plan far preceded post-Cretaceous radiations into the ocean depths
Authors: Brownstein Chase D. , Near Thomas J. , Dearden Richard P.
Published: August 2024

Among cartilaginous fishes,Holocephalirepresents the species-depauperate, morphologically conservative sister to sharks, rays, and skates and the last survivor of a once far greater Paleozoic and Mesozoic diversity. Currently, holocephalian diversity is concentrated in deep-sea species, suggesting this lineage might contain relictual diversity that persisted in the ocean depths. Yet, the relationships of living holocephalians to their extinct relatives and the timescale of diversification of living species remains unclear. Here, we reconstruct the evolutionary history of holocephalians using comprehensive morphological and DNA sequence datasets. Our results suggest that living holocephalians entered and diversified in deep (>1000 m) ocean waters after the Cretaceous-Paleogene mass extinction, contrasting with the hypothesis that this ecosystem has acted as a refugium of ancient cartilaginous fishes. These invasions were decoupled from the evolution of key features of the holocephalian body plan, including crushing dentition, a single frontal clasper, and holostylic jaw suspension, in the Paleozoic Era, and considerably postdated the appearance of the living familes by 150 million years ago during a major period of biotic turnover in oceans termed the Mesozoic Marine Revolution. These results clarify the origins of living holocephalians as the recent diversification of a single surviving clade among numerous Paleozoic lineages.
Assessing the ability of ChatGPT to extract natural product bioactivity and biosynthesis data from publications
Authors: Kalmer Thomas L. , Ancajas Christine Mae F. , Cheng Zihao , Oyedele Abiodun S. , Davis Hunter L. , Walker Allison S.
Published: August 2024

Natural products are an excellent source of therapeutics and are often discovered through the process of genome mining, where genomes are analyzed by bioinformatic tools to determine if they have the biosynthetic capacity to produce novel or active compounds. Recently, several tools have been reported for predicting natural product bioactivities from the sequence of the biosynthetic gene clusters that produce them. These tools have the potential to accelerate the rate of natural product drug discovery by enabling the prioritization of novel biosynthetic gene clusters that are more likely to produce compounds with therapeutically relevant bioactivities. However, these tools are severely limited by a lack of training data, specifically data pairing biosynthetic gene clusters with activity labels for their products. There are many reports of natural product biosynthetic gene clusters and bioactivities in the literature that are not included in existing databases. Manual curation of these data is time consuming and inefficient. Recent developments in large language models and the chatbot interfaces built on top of them have enabled automatic data extraction from text, including scientific publications. We investigated how accurate ChatGPT is at extracting the necessary data for training models that predict natural product activity from biosynthetic gene clusters. We found that ChatGPT did well at determining if a paper described discovery of a natural product and extracting information about the product’s bioactivity. ChatGPT did not perform as well at extracting accession numbers for the biosynthetic gene cluster or producer’s genome although using an altered prompt improved accuracy.
BRACE: A novel Bayesian-based imputation approach for dimension reduction analysis of alternative splicing at single-cell resolution
Authors: Wen Sean
Published: August 2024

Bayesian approach is a powerful tool to solve challenging questions in life sciences. One such area of life sciences in which Bayesian approach has seen an increased utility in the recent years is single-cell biology. Alternative splicing represents an additional layer of complexity underlying gene expression profile that has the potential to reveal insights into the biological mechanisms underpinning heath and disease states. Dimension reduction analysis is the cornerstone of RNA-sequencing analysis and has the ability to guide selection of candidate biomarkers based on segregation of sample groups. Nevertheless, dimension reduction analysis at single- cell resolution remains a significant challenge for alternative splicing datasets, and therefore hitherto preclude the assessment of candidate isoforms. Here, we introduce BRACE (a Bayesian-based imputation approach for dimension Reduction Analysis of alternative splicing at single-CEll resolution). We demonstrated our Bayesian approach represents an improvement over existing methods for imputing missing percent spliced-in values, and subsequently applied our approach for the dimension reduction analysis of alternative splicing events at single-cell resolution. We further demonstrated the application of our Bayesian approach over a range of single-cell datasets with increasing complexity, namely cell populations that are transcriptomically distinct, similar, and heterogenous. We anticipate our approach to enable assessment and selection of cell state- or disease-specific biomarkers for downstream experimental validation.
Increased listening effort and cochlear neural degeneration underlie behavioral deficits in speech perception in noise in normal hearing middle-aged adults
Authors: Zink Maggie E. , Zhen Leslie , McHaney Jacie R. , Klara Jennifer , Yurasits Kimberly , Cancel Victoria , Flemm Olivia , Mitchell Claire , Datta Jyotishka , Chandrasekaran Bharath , Parthasarathy Aravindakshan
Published: August 2024

Middle-age is a critical period of rapid changes in brain function that presents an opportunity for early diagnostics and intervention for neurodegenerative conditions later in life. Hearing loss is one such early indicator linked to many comorbidities later in life. However, current clinical tests fail to capture hearing difficulties for ∼10% of middle-aged adults seeking help at hearing clinics. Cochlear neural degeneration (CND) could play a role in these hearing deficits, but our current understanding is limited by the lack of objective diagnostics and uncertainty regarding its perceptual consequences. Here, using a cross-species approach, we measured envelope following responses (EFRs) – neural ensemble responses to sound originating from the peripheral auditory pathway – in young and middle-aged adults with normal audiometric thresholds, and compared these responses to young and middle-aged Mongolian gerbils, where CND was histologically confirmed. We observed near identical changes in EFRs across species that were associated with CND. Perceptual effects measured as behavioral readouts showed deficits in the most challenging listening conditions and were associated with CND. Additionally, pupil-indexed listening effort increased even at moderate task difficulties where behavioral outcomes were matched. Our results reveal perceptual deficits in middle-aged adults driven by CND and increases in listening effort, which may result in increased listening fatigue and conversational disengagement.
Interferon-γ driven differentiation of monocytes into PD-L1+and MHC II+macrophages and the frequency of Tim-3+tumor-reactive CD8+T cells within the tumor microenvironment predict a positive response to anti-PD-1-based therapy in tumor-bearing mice
Authors: Gabrilo Jelena , Velde Sylvie Vande , Henin Coralie , Denanglaire Sébastien , Azouz Abdulkader , Boon Louis , Van den Eynde Benoit J. , Moser Muriel , Goriely Stanislas , Leo Oberdan
Published: August 2024

While immune checkpoint inhibitors have demonstrated durable responses in various cancer types, a significant proportion of patients do not exhibit favourable responses to these interventions. To uncover potential factors associated with a positive response to immunotherapy, we established a bilateral tumor model using P815 mastocytoma implanted in DBA/2 mice. In this model, only a fraction of tumor-bearing mice responds favourably to anti-PD-1 treatment, thus providing a valuable model to explore the influence of the tumor microenvironment (TME) in determining the efficacy of immune checkpoint blockade (ICB)-based immunotherapies. Moreover, this model allows for the analysis of a pretreatment tumor and inference of its treatment outcome based on the response observed in the contralateral tumor. Here, we demonstrated that tumor-reactive CD8+T cell clones expressing high levels of Tim-3 were associated to a positive anti-tumor response following anti-PD-1 administration. Our study also revealed distinct differentiation dynamics in tumor-infiltrating myeloid cells in responding and non-responding mice. An IFNγ-enriched TME appeared to promote the differentiation of monocytes into PD-L1posMHC IIhighcells in mice responding to immunotherapy. Monocytes present in the TME of non-responding mice failed to reach the same final stage of differentiation trajectory, suggesting that an altered monocyte to macrophage route may hamper the response to ICB. These insights will direct future research towards a temporal analysis of TAMs, aiming to identify factors responsible for transitions between differentiation states within the TME. This approach may potentially pave the way to novel strategies to enhance the efficacy of PD-1 blockade.
PixelPrint4D: A 3D printing method of fabricating patient-specific deformable CT phantoms for respiratory motion applications
Authors: Im Jessica Y. , Micah Neghemi , Perkins Amy E. , Mei Kai , Geagan Michael , Noël Peter B.
Published: August 2024

All in-vivo medical imaging is impacted by patient motion, especially respiratory motion, which has a significant influence on clinical workflows in diagnostic imaging and radiation therapy. Many technologies such as motion artifact reduction and tumor tracking algorithms have been developed to compensate for respiratory motion during imaging. To assess these technologies, respiratory motion phantoms (RMPs) are required as preclinical testing environments, for instance, in computed tomography (CT). However, current RMPs are highly simplified and do not exhibit realistic tissue structures or deformation patterns. With the rise of more complex motion compensation technologies such as deep learning-based algorithms, there is a need for more realistic RMPs. This work introduces PixelPrint4D, a 3D printing method designed to fabricate lifelike, patient-specific deformable lung phantoms for CT imaging. The phantom demonstrated accurate replication of patient lung structures, textures, and attenuation profiles. Furthermore, it exhibited accurate nonrigid deformations, volume changes, and attenuation changes under compression. PixelPrint4Denables the production of highly realistic RMPs, surpassing existing models to offer more robust testing environments for a diverse array of novel CT technologies.
The Cognitive, Age, Functioning, and Apolipoprotein E4 (CAFE) Scorecard to Predict the Development of Alzheimer’s Disease: A White-Box Approach
Authors: Wiranto Yumiko , Setiawan Devin R , Watts Amber , Ashourvan Arian ,   the Alzheimer’s Disease Neuroimaging Initiative
Published: August 2024

Objective

This study aimed to bridge the gap between the costliness and complexity of diagnosing Alzheimer’s disease by developing a scoring system with interpretable machine learning to predict the risk of Alzheimer’s using obtainable variables to promote accessibility and early detection.

Participants and Methods

We analyzed 713 participants with normal cognition or mild cognitive impairment from the Alzheimer’s Disease Neuroimaging Initiative. We integrated cognitive test scores from various domains, informant-reported daily functioning,APOEgenotype, and demographics to generate the scorecards using the FasterRisk algorithm.

Results

Various combinations of 5 features were selected to generate ten scorecards with a test area under the curve ranging from 0.867 to 0.893. The best performance scorecard generated the following point assignments: age < 76 (-2 points); noAPOEε4alleles (-3 points); Rey Auditory Verbal Learning Test <= 36 items (4 points); Logical Memory delayed recall <= 3 items (5 points); and Functional Assessment Questionnaire <= 2 (-5 points). The probable Alzheimer’s development risk was 4.3% for a score of -10, 31.5% for a score of -3, 50% for a score of -1, 76.3% for a score of 1, and greater than 95% for a score of > 6.

Conclusions

Our findings highlight the potential of these interpretable scorecards to predict the likelihood of developing Alzheimer’s disease using obtainable information, allowing for applicability across diverse healthcare environments. While our initial scope centers on Alzheimer’s disease, the foundation we have established paves the way for similar methodologies to be applied to other types of dementia.
The Use of Wastewater Surveillance to Estimate SARS-CoV-2 Fecal Viral Shedding Pattern and Identify Time Periods with Intensified Transmission
Authors: Yang Wan , Omoregie Enoma , Olsen Aaron , Watts Elizabeth A. , Parton Hilary , Lee Ellen
Published: August 2024

Background

Wastewater-based surveillance is an important tool for monitoring the COVID-19 pandemic. However, it remains challenging to translate wastewater SARS-CoV-2 viral load to infection number, due to unclear shedding patterns in wastewater and potential differences between variants.

Objectives

We utilized comprehensive wastewater surveillance data and estimates of infection prevalence (i.e., the source of the viral shedding) available for New York City (NYC) to characterize SARS-CoV-2 fecal shedding pattern over multiple COVID-19 waves.

Methods

We collected SARS-CoV-2 viral wastewater measurements in NYC during August 31, 2020 – August 29, 2023 (N= 3794 samples). Combining with estimates of infection prevalence (number of infectious individuals including those not detected as cases), we estimated the time-lag, duration, and per-infection fecal shedding rate for the ancestral/Iota, Delta, and Omicron variants, separately. We also developed a procedure to identify occasions with intensified transmission.

Results

Models suggested fecal viral shedding likely starts around the same time as and lasts slightly longer than respiratory tract shedding. Estimated fecal viral shedding rate was highest during the ancestral/Iota variant wave, at 1.44 (95% CI: 1.35 – 1.53) billion RNA copies in wastewater per day per infection (measured by RT-qPCR), and decreased by ∼20% and 50-60% during the Delta wave and Omicron period, respectively. We identified around 200 occasions during which the wastewater SARS-CoV-2 viral load exceeded the expected level in any of 14 sewersheds. These anomalies disproportionally occurred during late January, late April - early May, early August, and from late-November to late-December, with frequencies exceeding the expectation assuming random occurrence (P< 0.05; bootstrapping test).

Discussion

These estimates may be useful in understanding changes in underlying infection rate and help quantify changes in COVID-19 transmission and severity over time. We have also demonstrated that wastewater surveillance data can support the identification of time periods with potentially intensified transmission.
The Impact of Myosteatosis on Cardiac Function in a Healthy Population: Insights from Abdominal CT Imaging
Authors: Kim Myung Jin , Nam Hyo-Jung , Cho Yun Kyung , Kim Eun Hee , Lee Min Jung , Lee Woo Je , Kim Hong-Kyu , Jung Chang Hee
Published: August 2024

Background:

Ectopic fat deposition in skeletal muscle, termed myosteatosis, is a key factor in insulin resistance and contributes to various metabolic disturbances. This study evaluated the association between myosteatosis, assessed via abdominal computed tomography, and cardiac function in an asymptomatic Korean population.

Methods:

This cross-sectional study included 7,716 participants (4,902 [63.5%] men and 2,814 [36.5%] women, mean age 53.2 ± 8.0) who underwent routine health check-ups at Asan Medical Center (Seoul, Korea). Myosteatosis was evaluated by segmenting the total abdominal muscle area (TAMA) at the L3 vertebral level into normal-attenuation muscle area (NAMA), low-attenuation muscle area (LAMA), and inter-/intra-muscular adipose tissue (IMAT). Patients were categorized into quartiles based on the NAMA/TAMA index, calculated by dividing the NAMA by TAMA and multiplying by 100. Cardiac function was assessed by transthoracic echocardiography.

Results:

Higher NAMA/TAMA index levels were associated with decreased absolute values of the E/E’ ratio and increased E/A ratio in both men and women. Multiple linear regression analysis revealed a significant correlation between the NAMA/TAMA index and both the E/A and E/E’ ratios after adjusting for covariates. No significant correlation was found with left ventricular (LV) ejection fraction or LV mass index.

Conclusions:

The degree of myosteatosis was significantly associated with diastolic function in an asymptomatic population, while systolic function remained unaffected.
Nematodes Vector Bacteriophages in Compost and Soil
Authors: van Sluijs Lisa , Dietz Cassidy , van Noort Floris , Helder Johannes , Zwart Mark W. , Mason-Jones Kyle
Published: August 2024

Bacteriophages (phages) infect bacteria to reproduce and are often lethal to their host. To maintain the infection cycle, soil phages must travel from one suitable host to the next. However, traversing the soil matrix presents a dangerous journey for phages, which need to encounter the right hosts in this spatially complex habitat, but are not capable of active motion and can adsorb to soil particles. Here, we tested the hypothesis that bacterial-feeding nematodes (roundworms) present a reliable vehicle of soil transport for phages. First, we demonstrated that the bacterivorous nematodeCaenorhabditis elegansvectored the laboratory model phage T7 as well as the soil phage Φ Ppu-W11 on agar. Sorption assays carried out with paralyzed and non-paralyzed nematodes showed that phage transport can occur via both external cuticular attachment and ingestion, and that the presence of host bacteria is not required for phage vectoring. Finally, we designed a microcosm to test phage transfer in compost and sandy soil usingC. elegansand its sister species,C. remanei, respectively. This experiment confirmed that nematodes also enable phage movement through complex spatial habitats. This novel mechanism of phage vectoring extends our understanding of virus transmission in soil, revealing new multitrophic interactions that may influence soil functioning.
The multi-level effect of chlorpyrifos during clownfish metamorphosis
Authors: Reynaud Mathieu , Vianello Stefano , Lee Shu-Hua , Salis Pauline , Wu Kai , Frederich Bruno , Lecchini David , Besseau Laurence , Roux Natacha , Laudet Vincent
Published: August 2024

Chemical pollution in coastal waters, particularly from agricultural runoff organophosphates, poses a significant threat to marine ecosystems, including coral reefs. Pollutants such as chlorpyrifos (CPF) are widely used in agriculture and have adverse effects on marine life and humans. In this paper, we investigate the impact of CPF on the metamorphosis of a coral reef fish model, the clownfishAmphiprion ocellaris, focusing on the disruption of thyroid hormone (TH) signalling pathways. Our findings reveal that by reducing TH levels, CPF exposure impairs the formation of characteristic white bands in clownfish larvae, indicative of metamorphosis progression. Interestingly, TH treatment can rescue these effects, establishing a direct causal link between CPF effect and TH disruption. The body shape changes occurring during metamorphosis are also impacted by CPF exposure, shape changes are less advanced in CPF-treated larvae than in control conditions. Moreover, transcriptomic analysis elucidates CPF’s effects on all components of the TH signalling pathway. Additionally, CPF induces systemic effects on cholesterol and vitamin D metabolism, DNA repair, and immunity, highlighting its broader TH-independent impacts. Pollutants are often overlooked in marine ecosystems, particularly in coral reefs. Developing and enhancing coral reef fish models, such asAmphiprion ocellaris, offers a more comprehensive understanding of how chemical pollution affects these ecosystems. This approach provides new insights into the complex mechanisms underlying CPF toxicity during fish metamorphosis, shedding light on the broader impact of environmental pollutants on marine organisms.

Highlights

Chlorpyrifos (CPF) is an insecticide widely used in agriculture for the past five decades and has adverse effects on marine life and humans

CPF exposure impairs the formation of characteristic white bands in clownfish larvae, indicative of metamorphosis progression

During metamorphosis, clownfish larvae lose their elongated body shape and transform into miniature ovoid-shaped adults, these shape changes are less advanced in CPF-treated larvae

CPF induces systemic effects on cholesterol and vitamin D metabolism, DNA repair, and immunity, highlighting its broader TH-independent impacts
Activity-dependent synapse elimination requires caspase-3 activation
Authors: Yu Zhou , Gutu Andrian , Kim Namsoo , O’Shea Erin K.
Published: August 2024

During brain development, synapses are initially formed in excess and are later eliminated in an activity-dependent manner. Weak synapses are preferentially removed, but the mechanism linking neuronal activity to synapse removal is unclear. Here we show that, in the developing mouse visual pathway, inhibiting synaptic transmission induces postsynaptic activation of caspase-3. Caspase-3 deficiency results in defects in synapse elimination driven by both spontaneous and experience-dependent neural activity. Notably, caspase-3 deficiency blocks activity-dependent synapse elimination, as evidenced by reduced engulfment of inactive synapses by microglia. Furthermore, in a mouse model of Alzheimer’s disease, caspase-3 deficiency protects against synapse loss induced by amyloid-β deposition. Our results reveal caspase-3 activation as a key step in activity-dependent synapse elimination during development and synapse loss in neurodegeneration.
Reducing maladaptive behavior in neuropsychiatric disorders using network modification
Authors: Timme Nicholas
Published: August 2024

Neuropsychiatric disorders are caused by many factors and produce a wide range of symptomatic maladaptive behaviors in patients. Despite this great variance in causes and resulting behavior, we believe the maladaptive behaviors that characterize neuropsychiatric disorders are most proximally determined by networks of neurons and that this forms a common conceptual link between these disorders. Operating from this premise, it follows that treating neuropsychiatric disorders to reduce maladaptive behavior can be accomplished by modifying the patient’s network of neurons. In this proof-of-concept computational psychiatry study, we tested this approach in a simple neural network model that produces aversion-resistant alcohol drinking – a key maladaptive behavior associated with alcohol use disorder. We demonstrated that it was possible to predict personalized network modifications that substantially reduced maladaptive behavior without inducing side effects. Furthermore, we found that it was possible to predict effective treatments with limited knowledge of the model and that information about neural activity during certain types of trials was more helpful in predicting treatment than information about model parameters. We hypothesize that this is a general feature of developing effective treatment strategies for networks of neurons. This computational study lays the groundwork for future studies utilizing more biologically realistic network models in conjunction within vivodata.
Experience-dependent modulation of collective behavior in larval zebrafish
Authors: Harpaz Roy , Phillips Morgan , Goel Ronan , Fishman Mark C. , Engert Florian
Published: August 2024

Complex group behavior can emerge from simple inter-individual interactions. Commonly, these interactions are considered static and hardwired and little is known about how experience and learning affect collective group behavior. Young larvae use well described visuomotor transformations to guide interindividual interactions and collective group structure. Here, we use naturalistic and virtual-reality (VR) experiments to impose persistent changes in population density and measure their effects on future visually evoked turning behavior and the resulting changes in group structure. We find that neighbor distances decrease after exposure to higher population densities, and increase after the experience of lower densities. These adaptations develop slowly and gradually, over tens of minutes and remain stable over many hours. Mechanistically, we find that larvae estimate their current group density by tracking the frequency of neighbor-evoked looming events on the retina and couple the strength of their future interactions to that estimate. A time-varying state-space model that modulates agents’ social interactions based on their previous visual-social experiences, accurately describes our behavioral observations and predicts novel aspects of behavior. These findings provide concrete evidence that inter-individual interactions are not static, but rather continuously evolve based on past experience and current environmental demands. The underlying neurobiological mechanisms of experience dependent modulation can now be explored in this small and transparent model organism.