bluuebunny/crossref_metadata_2025 huggingface dataset:
MCNET: Multi-Omics Integration for Gene Regulatory Network Inference from scRNA-seq
Authors: Tiwari Ansh , Trankatwar Sachin
Published: June 2023

Abstract

Deep learning has emerged as a powerful approach in various domains, including biological network analysis. This paper investigates the advancements in computational techniques for inferring gene regulatory networks (GRNs) and introduces MCNET, a state-of-the-art deep learning algorithm. MCNET integrates multi-omics data to infer GRNs and extract biologically significant representations from single-cell RNA sequencing (scRNA-seq) data. By incorporating attention mechanisms and graph convolutional networks, MCNET captures intricate regulatory relationships among genes. Extensive benchmarking on diverse scRNA-seq datasets demonstrates MCNET’s superiority over existing methods in GRN inference, scRNA-seq data visualization, clustering, and simulation. Notably, MCNET accurately predicts gene regulations on cell-type marker genes in the mouse cortex, validated by epigenetic data. The introduction of MCNET paves the way for advanced analysis of scRNA-seq data and provides a powerful tool for inferring GRNs in a multi-omics context. Moreover, this paper addresses the integration of multiomics data in gene regulatory network inference, proposing MCNET as a method that efficiently analyzes and visualizes homogeneous gene regulatory networks derived from diverse omics data. The inference capability of MCNET is evaluated through extensive experiments with simulation data and applied to analyze the biological network of psychiatric disorders using human brain data.
Handling missing values in the analysis of between-hospital differences in ordinal and dichotomous outcomes: a simulation study
Authors: van Linschoten Reinier C.A. , Amini Marzyeh , van Leeuwen Nikki , Eijkenaar Frank , den Hartog Sanne J. , Nederkoorn Paul , Hofmeijer Jeannette , Emmer Bart J. , Postma Alida A. , van Zwam Wim , Roozenbeek Bob , Dippel Diederik W.J. , Lingsma Hester F. ,   MR CLEAN Registry Investigators
Published: June 2023

Missing data are frequently encountered in registries that are used to compare performance across hospitals. The most appropriate method for handling missing data when analysing differences in outcomes between hospitals is unclear. We aimed to compare methods for handling missing data when comparing hospitals on ordinal and dichotomous outcomes. We performed a simulation study using data came from the MR CLEAN registry, a prospective cohort study in 17 hospitals performing endovascular therapy for ischemic stroke in the Netherlands. The investigated methods for handling missing data, both case-mix adjustment variables and outcomes, were complete case analysis (CCA), single imputation, multiple imputation, single imputation with deletion of imputed outcomes and multiple imputation with deletion of imputed outcomes. Data were generated as missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR) in three scenarios: (1) 10% missing data in case-mix and outcome; (2) 40% missing data in case-mix and outcome; and (3) 40% missing data in case-mix and outcome with varying degree of missing data among hospitals. Validity and reliability of the methods were compared on the mean squared error (MSE, a summary measure combining bias and precision) relative to the centre effect estimates from the complete reference dataset. For both the ordinal outcome (i.e. the modified Rankin scale) and a common dichotomized version thereof, the MSE of all methods was on average lowest under MCAR and with fewer missing data, and highest with more missing data and under MNAR. The ‘multiple imputation, then deletion’ method had the lowest MSE for both outcomes under all simulated patterns of missing data. Thus, when estimating centre effects on ordinal and dichotomous outcomes in the presence of missing data, the least biased and most precise method to handle these missing data is ‘multiple imputation, then deletion’.
Tropical butterflies lose central nervous system function in the cold from a spreading depolarization event
Authors: Andersen Mads Kuhlmann , Willot Quentin , MacMillan Heath A.
Published: June 2023

Insects are ectotherms and their physiological functions are therefore directly influenced by the environmental temperature. By extension, their ability to tolerate thermal extremes is directly linked to their thermal niche and distribution. Understanding the physiological mechanisms that limit insect thermal tolerance is therefore crucial for our ability to predict biogeography and range shifts. Recent studies on fruit flies and locusts suggest that the loss of coordinated movements at the critical thermal minimum is due to a loss of central nervous system function via a spreading depolarization. We hypothesized that a similar mechanism limits nervous function in other insect taxa. Here, we use electrophysiology to investigate whether the same spreading depolarization event occurs in the brain of butterflies exposed to stressful cold. Supporting our hypothesis, we find that exposure to stressful cold induced spreading depolarization in all species tested. This reinforces the idea that loss of central nervous function by a spreading depolarization is a common mechanism underlying the critical thermal minimum in insects. Furthermore, our results highlight how central nervous system performance is finely tuned to match species’ environments. Further research into the physiological mechanisms underlying the spreading depolarization event is likely to elucidate key mechanisms determining insect ecology.
Dicarboxylic acid supplementation protects from acute kidney injury via stimulation of renal peroxisomal activity
Authors: Barbosa Anne C. S. , Pfister Katherine E. , Chiba Takuto , Bons Joanna , Rose Jacob P. , Burton Jordan B. , King Christina D. , O’Broin Amy , Young Victoria , Zhang Bob , Sivakama Bharathi , Schmidt Alexandra V. , Uhlean Rebecca , Schilling Birgit , Goetzman Eric S. , Sims-Lucas Sunder
Published: June 2023

Introduction

Lysine succinylation is a post-translational modification associated with the control of several diseases, including acute kidney injury (AKI). It is suggested that hypersuccinylation favors peroxisomal fatty acid oxidation (FAO) instead of mitochondrial. In addition, the medium-chain fatty acids (MCFAs) dodecanedioic acid (DC12) and octanedioic acid (DC8), upon FAO, generate succinyl-CoA, resulting in hypersuccinylation. DC8is convenient, inexpensive, easily administered, and efficient. We believe this study could be translated in the future to clinical settings, which would highly benefit patients at high risk of AKI.

Methods and Results

To test the protective roles of MCFAs during AKI, mice were fed with control, 10% DC12, or 10% DC8diet, then, subjected to either ischemic-AKI, or cisplatin-AKI models. Supplementation was provided until sacrifice. Biochemical, histologic, genetic, and proteomic analysis were performed, the latter involving a lysine-succinylome-based analysis. Both DC8and DC12prevented the rise of AKI markers in mice that underwent renal injury. However, DC8was even more protective against AKI than DC12. Finally, succinylome analysis evidenced that the kidneys of DC8-fed mice showed an extensive succinylation of peroxisomal activity-related proteins, and a decline in mitochondrial FAO, in comparison to control-fed mice.

Conclusion

DC8supplementation drives renal protein hypersuccinylation, promoting a shift from mitochondrial to peroxisomal FAO, and protecting against AKI.

Significance Statement

Lysine succinylation of proteins is shown to control several diseases, including acute kidney injury (AKI). Here we show that mice supplemented with the medium-chain fatty acid octanedioic acid successfully presented a high level of succinylation and were protected from both ischemia-reperfusion- and cisplatin-induced AKI. Moreover, our study demonstrates that peroxisomal activity was increased while mitochondrial activity was preserved, suggesting that the metabolism of diet-obtained medium-chain fatty acids by peroxisomes is renoprotective.
Cell age drives asynchronous transcriptome aging
Authors: Yang Ming , Harrison Benjamin R. , Promislow Daniel E.L.
Published: June 2023

Organs age at different rates within a single individual. Such asynchrony in aging has been widely observed at multiple levels, from functional hallmarks, such as anatomical structures and physiological processes, to molecular endophenotypes, such as the transcriptome and metabolome. However, we lack a conceptual framework to understand why some components age faster than others. Just as demographic models explain why aging evolves, here we test the hypothesis that demographic differences among cell types, determined by cell-specific differences in turnover rate, can explain why the transcriptome shows signs of aging in some cell types but not others. Through analysis of mouse single-cell transcriptome data across diverse organs and ages, we find that cellular age explains a large proportion of the variation in the age-related increase in transcriptome variance. We further show that long-lived cells are characterized by relatively high expression of genes associated with proteostasis, and that the transcriptome of long-lived cells shows greater evolutionary constraint than short-lived cells. In contrast, in short-lived cell types the transcriptome is enriched for genes associated with DNA repair. Based on these observations, we develop a novel heuristic model that explains how and why aging rates differ among cell types.
Intestinal epithelial adaptations to vertical sleeve gastrectomy defined at single-cell resolution
Authors: Koch-Laskowski Kieran , Kim Ki-Suk , Bethea Maigen , Fuller Kelly N. Z. , Sandoval Darleen A. , Sethupathy Praveen
Published: June 2023

The gut plays a key role in regulating metabolic health. Dietary factors disrupt intestinal physiology and contribute to obesity and diabetes, whereas bariatric procedures such as vertical sleeve gastrectomy (VSG) cause gut adaptations that induce robust metabolic improvements. However, our understanding of these adaptations at the cellular and molecular levels remains limited. In a validated murine model, we leverage single-cell transcriptomics to determine how VSG impacts different cell lineages of the small intestinal epithelium. We define cell type-specific genes and pathways that VSG rescues from high-fat diet perturbation and characterize additional rescue-independent changes brought about by VSG. We show that Paneth cells have increased expression of the gut peptide Reg3g after VSG. We also find that VSG restores pathways pertaining to mitochondrial respiration and cellular metabolism, especially within crypt-based cells. Overall, our study provides unprecedented molecular resolution of VSG’s therapeutic effects on the gut epithelium.
Harnessing Deep Learning to Analyze Cryptic Morphological Variability ofMarchantia polymorpha
Authors: Tomizawa Yoko , Minamino Naoki , Shimokawa Eita , Kawamura Shogo , Komatsu Aino , Hiwatashi Takuma , Nishihama Ryuichi , Ueda Takashi , Kohchi Takayuki , Kondo Yohei
Published: June 2023

Characterizing phenotypes is a fundamental aspect of biological sciences, although it can be challenging due to various factors. For instance, the liverwort (Marchantia polymorpha), a model system for plant biology, exhibits morphological variability, making it difficult to identify and quantify distinct phenotypic features using objective measures. To address this issue, we utilized a deep learning-based image classifier that can handle plant images directly without manual extraction of phenotypic features, and analyzed bright-field images ofM. polymorpha. This dioicous plant species exhibits morphological differences between male and female wild accessions at an early stage of gemmaling growth, although it remains elusive whether the differences are attributable to sexual dimorphism or autosomal genetic variation. To dissect the genomic factors, we established a male and female set of recombinant inbred lines (RILs) from a set of male and female wild accessions. We then trained deep-learning models to classify the sexes of the RILs and the wild accessions. Our results showed that the trained classifiers accurately classified male and female gemmalings of wild accessions in the first week of growth, confirming the intuition of plant researchers in a reproducible and objective manner. In contrast, the RILs were less distinguishable, indicating that the differences between the parental wild accessions arose from autosomal variations instead of sexual dimorphism. Furthermore, we validated our trained models by an “explainable AI” technique that highlights image regions relevant to the classification. Our findings demonstrate that the classifier-based approach provides a powerful tool for analyzing plant species that lack standardized phenotyping metrics.
Comparing neural language models for medical concept representation and patient trajectory prediction
Authors: Bornet Alban , Proios Dimitrios , Yazdani Anthony , Santero Fernando Jaume , Haller Guy , Choi Edward , Teodoro Douglas
Published: June 2023

Effective representation of medical concepts is crucial for secondary analyses of electronic health records. Neural language models have shown promise in automatically deriving medical concept representations from clinical data. However, the comparative performance of different language models for creating these empirical representations, and the extent to which they encode medical semantics, has not been extensively studied. This study aims to address this gap by evaluating the effectiveness of three popular language models – word2vec, fastText, and GloVe – in creating medical concept embeddings that capture their semantic meaning. By using a large dataset of digital health records, we created patient trajectories and used them to train the language models. We then assessed the ability of the learned embeddings to encode semantics through an explicit comparison with biomedical terminologies, and implicitly by predicting patient outcomes and trajectories with different levels of available information. Our qualitative analysis shows that empirical clusters of embeddings learned by fastText exhibit the highest similarity with theoretical clustering patterns obtained from biomedical terminologies, with a similarity score between empirical and theoretical clusters of 0.88, 0.80, and 0.92 for diagnosis, procedure, and medication codes, respectively. Conversely, for outcome prediction, word2vec and GloVe tend to outperform fastText, with the former achieving AUROC as high as 0.78, 0.62, and 0.85 for length-of-stay, readmission, and mortality prediction, respectively. In predicting medical codes in patient trajectories, GloVe achieves the highest performance for diagnosis and medication codes (AUPRC of 0.45 and of 0.81, respectively) at the highest level of the semantic hierarchy, while fastText outperforms the other models for procedure codes (AUPRC of 0.66). Our study demonstrates that subword information is crucial for learning medical concept representations, but global embedding vectors are better suited for more high-level downstream tasks, such as trajectory prediction. Thus, these models can be harnessed to learn representations that convey clinical meaning, and our insights highlight the potential of using machine learning techniques to semantically encode medical data.
Cell-type-specific Alzheimer’s disease polygenic risk scores are associated with distinct disease processes in Alzheimer’s disease
Authors: Yang Hyun-Sik , Teng Ling , Kang Daniel , Menon Vilas , Ge Tian , Finucane Hilary K. , Schultz Aaron P. , Properzi Michael , Klein Hans-Ulrich , Chibnik Lori B. , Schneider Julie A. , Bennett David A. , Hohman Timothy J. , Mayeux Richard P. , Johnson Keith A. , De Jager Philip L. , Sperling Reisa A.
Published: June 2023

Alzheimer’s disease (AD) heritability is enriched in glial genes, but how and when cell-type-specific genetic risk contributes to AD remains unclear. Here, we derive cell-type-specific AD polygenic risk scores (ADPRS) from two extensively characterized datasets. In an autopsy dataset spanning all stages of AD (n=1,457), astrocytic (Ast) ADPRS was associated with both diffuse and neuritic Aβ plaques, while microglial (Mic) ADPRS was associated with neuritic Aβ plaques, microglial activation, tau, and cognitive decline. Causal modeling analyses further clarified these relationships. In an independent neuroimaging dataset of cognitively unimpaired elderly (n=2,921), Ast-ADPRS were associated with Aβ, and Mic-ADPRS was associated with Aβ and tau, showing a consistent pattern with the autopsy dataset. Oligodendrocytic and excitatory neuronal ADPRSs were associated with tau, but only in the autopsy dataset including symptomatic AD cases. Together, our study provides human genetic evidence implicating multiple glial cell types in AD pathophysiology, starting from the preclinical stage.
Revealing the Organ-Specific Expression ofSPTBN1using Single-Cell RNA Sequencing Analysis
Authors: Jung Jongyun , Wu Qing
Published: June 2023

Despite the recent technological advances in single-cell RNA sequencing, it is still unknown how three marker genes (SPTBN1,EPDR1, andPKDCC), which are associated with bone fractures and highly expressed in the muscle tissue, are contributing to the development of other tissues and organs at the cellular level. This study aims to analyze three marker genes at the single-cell level using 15 organ tissue types of adult human cell atlas (AHCA). The single-cell RNA sequencing analysis used three marker genes and a publicly available AHCA data set. AHCA data set contains more than 84,000 cells from 15 organ tissue types. Quality control filtering, dimensionality reduction, clustering for cells, and data visualization were performed using the Seurat package. A total of 15 organ types are included in the downloaded data sets: Bladder, Blood, Common Bile Duct, Esophagus, Heart, Liver, Lymph Node, Marrow, Muscle, Rectum, Skin, Small Intestine, Spleen, Stomach, and Trachea. In total, 84,363 cells and 228,508 genes were included in the integrated analysis. A marker gene ofSPTBN1is highly expressed across all 15 organ types, particularly in the Fibroblasts, Smooth muscle cells, and Tissue stem cells of the Bladder, Esophagus, Heart, Muscle, Rectum, Skin, and Trachea. In contrast,EPDR1is highly expressed in the Muscle, Heart, and Trachea, andPKDCCis only expressed in Heart. In conclusion,SPTBN1is an essential protein gene in physiological development and plays a critical role in the high expression of fibroblasts in multiple organ types. TargetingSPTBN1may prove beneficial for fracture healing and drug discovery.

Author Summary

Three marker genes (SPTBN1,EPDR1, andPKDCC) are playing a critical role in the shared genetic mechanisms between bone and muscle. However, how these marker genes contribute to developing other tissues and organs at the cellular level is unknown. Here, we build on prior work to study an unappreciated degree of heterogeneity of three marker genes in 15 adult human organs by using single-cell RNA sequencing technology. Our analysis included 15 organ types: Bladder, Blood, Common Bile Duct, Esophagus, Heart, Liver, Lymph Node, Marrow, Muscle, Rectum, Skin, Small Intestine, Spleen, Stomach, and Trachea. In total, 84,363 cells from 15 different organ types were included. In all 15 organ types,SPTBN1is highly expressed, including fibroblasts, smooth muscle cells, and skin stem cells of the bladder, esophagus, heart, muscles, and rectum. The first-time discovery of the high expression ofSPTBN1in 15 organ types suggests that it may play a critical role in physiological development. Our study concludes that targetingSPTBN1may benefit fracture healing and drug discovery.
Evolution and diversity of biomineralized columnar architecture in early Cambrian phosphatic-shelled brachiopods
Authors: Zhang Zhiliang , Zhang Zhifei , Holmer Lars E. , Topper Timothy P. , Pan Bing , Li Guoxiang
Published: June 2023

Biologically-controlled mineralization producing organic-inorganic composites (hard skeletons) by metazoan biomineralizers has been an evolutionary innovation since the earliest Cambrian. Among them, linguliform brachiopods are one of the key invertebrates that secrete calcium phosphate minerals to build their shells. One of the most distinct shell structures is the organo-phosphatic cylindrical column exclusive to phosphatic-shelled brachiopods, including both crown and stem groups. However, the complexity, diversity and biomineralization processes of these microscopic columns are far from clear in brachiopod ancestors. Here, exquisitely well-preserved columnar shell ultrastructures are reported for the first time in the earliest eoobolidsLatusobolus xiaoyangbaensisgen. et sp. nov. andEoobolus acutulussp. nov from the Cambrian Series 2 Shuijingtuo Formation of South China. The hierarchical shell architectures, epithelial cell moulds, and the shape and size of cylindrical columns are scrutinised in these new species. Their calcium phosphate-based biomineralized shells are mainly composed of stacked sandwich columnar units. The secretion and construction of the stacked sandwich model of columnar architecture, which played a significant role in the evolution of linguliforms, is highly biologically controlled and organic-matrix mediated. Furthermore, a continuous transformation of anatomic features resulting from the growth of diverse columnar shells is revealed between Eoobolidae, Lingulellotretidae and Acrotretida, shedding new light on the evolutionary growth and adaptive innovation of biomineralized columnar architecture among early phosphatic-shelled brachiopods during the Cambrian explosion.
Enhanced 5mC-Methylation-Site Recognition in DNA Sequences using Token Classification and a Domain-specific Loss Function
Authors: Zeng Wenhuan , Huson Daniel
Published: June 2023

DNA 5-methylcytosine modification has been widely studied in mammals and plays an important role in epigenetics. Several computational methods exist that determine the methylation state of a DNA sequence centered at a possible methylation site. Here, we introduce a novel deep-learning framework, MR-DNA, that predicts the methylation state of a single nucleotide located in a gene promoter region. The idea is to adapt the named-entity recognition approach to methylation-site prediction and to incorporate biological rules during model construction. MR-DNA has a stacked model architecture consisting of a pre-trained MuLan-Methyl-DistilBERT language model and a conditional random field algorithm, trained with a self-defined methyl loss function. The resulting fine-tuned model achieves an accuracy of 97.9% on an independent test dataset of samples. An advantage of this formulation of the methylation-site identification task is that it predicts on every nucleotide of a sequence of a given length, unlike previous methods that the predict methylation state of DNA sequences of a short fixed length. For training and testing purposes, we provide a database of DNA sequences containing verified 5mC-methylation sites, calculated from data for eight human cell lines downloaded from the ENCODE database.
Assessing the predictive ability of computational epitope prediction methods on Fel d 1 and other allergens
Authors: Kwon Hyeji , Ko Soobon , Ha Kyungsoo , Lee Jungjoon K. , Choi Yoonjoo
Published: June 2023

While computational epitope prediction methods have found broad application, their use, specifically in allergy-related contexts, remains relatively less explored. This study benchmarks several publicly available epitope prediction tools, focusing on the allergenic IgE and T-cell epitopes of Fel d 1, an extensively studied allergen. Using a variety of tools accessible via the Immune Epitope Database (IEDB) and other resources, we evaluate their ability to identify the known linear IgE and T-cell epitopes of Fel d 1. Our results show a limited effectiveness for B-cell epitope prediction methods, with most performing only marginally better than random selection. We also explored the general predictive abilities on other allergens, and the results were largely random. When predicting T-cell epitopes, ProPred successfully identified all known Fel d 1 T-cell epitopes, whereas the IEDB approach missed two known epitopes and demonstrated a tendency to over-predict. However, when applied to a larger test set, both methods performed only slightly better than random selection. Our findings show the limitations of current computational epitope prediction methods in accurately identifying allergenic epitopes, emphasizing the need for methodological advancements in allergen research.
IL-1R signaling drives enteric glia-macrophage interactions in colorectal cancer
Authors: van Baarle Lies , Simone Veronica De , Schneider Linda , Santhosh Sneha , Abdurahiman Saeed , Biscu Francesca , Schneider Reiner , Zanoletti Lisa , Verbandt Sara , Hu Zedong , Stakenborg Michelle , Ke Bo-Jun , García-Reyes Balbina , Henn Jonas , Toma Marieta , Vanmechelen Maxime , Smet Frederik De , Ibiza Sales , Tejpar Sabine , Wehner Sven , Matteoli Gianluca
Published: June 2023

Enteric glial cells (EGCs) have been implicated in colorectal cancer (CRC) pathogenesis. However, their precise mechanisms of interaction with the CRC immune cell compartment and pro-tumorigenic role remain unclear. This study aimed to investigate the immunomodulatory effects of EGCs on tumor-associated macrophages (TAMs) and their involvement in CRC progression. Using EGC depletion and supplementation models, we assessed the impact of EGCs on the immunomodulation of orthotopic murine CRC. Furthermore, by making use of Bulk RNA-sequencing of CRC EGCs and single-cell sequencing of the tumor microenvironment, we identified the factors involved in the EGC-TAM crosstalk. Findings demonstrate that EGCs acquire a reactive and immunomodulatory phenotype in both murine CRC models and patients, influencing TAM differentiation. Mechanistically, secretion of IL-1 by tumor-infiltrating monocytes and macrophages triggers the phenotypic and functional switch of CRC EGCs via IL-1R. Consequently, tumor EGCs secrete IL-6, promoting the differentiation of monocytes into pro-tumorigenic SPP1+TAMs. Importantly, the reactive tumor EGCs phenotype correlates with worse disease outcomes in preclinical models and CRC patients. Here we uncover a previously unexplored neuroimmune interaction between EGCs and TAMs within the colorectal tumor microenvironment, informing potential therapeutic strategies and enhancing our understanding of CRC progression.

eTOC Summary

Our study unveils a novel neuroimmune interaction between enteric glia and TAMs in colon carcinoma. Monocyte/Macrophage-derived IL-1 activates enteric glia, leading to the differentiation of pro-tumorigenic SPP1+TAMs via glial-derived IL-6. Blocking glial IL-1R-signaling reduces colonic tumor lesions, highlighting IL-1R as a potential therapeutic target.
A novel method for tracking nitrogen kineticsin vivoandex vivousing radioactive nitrogen-13 gas and Positron Emission Tomography
Authors: Ashworth Edward T , Ogawa Ryotaro , Vera David , Lindholm Peter
Published: June 2023

Rationale

Decompression sickness (DCS) is caused by gaseous nitrogen dissolved in tissues forming bubbles during decompression. To date no method exists to identify nitrogen within tissues, but with advances in PET technology it may be possible to track gaseous radionuclides into tissues. We aimed to develop a method to track nitrogen movementin vivothat could then be used to further our understanding of DCS using nitrogen-13 (13N2) – a radioactive isotope of nitrogen that emits β+ radiation.

Methods

A single anesthetized and ventilated Sprague Dawley rat lay supine inside a PET scanner for 30 min. The rat breathed oxygen for the first 2 min, then was switched to a bag containing13N2gas mixed with oxygen for 20 min, then breathed oxygen alone for the final 8 min. Gas samples were drawn from the inspiratory line at 5, 15 and 25 min. The PET scanner recorded13N2with energy windows of 250-750 keV. Following the scan, a mixed blood sample was taken from the heart, while the brain, liver, femur and thigh muscle were removed to determine organ radioactivity using a gamma counter.

Results

The gas samples at 5 (5.7 kbq.ml-1) and 15 min (5.3 kbq.ml-1) showed radioactivity in the inspired gas that was absent at 25 min (0.1 kbq.ml-1), when the13N2was stopped. The signal intensity in the PET scanner increased from baseline (0.03) to 2-12 min (0.68±0.31), and 12-22 min (0.88±0.06), before reducing slightly from 22-30 min (0.61±0.04). All organs had radioactivity when measured in the gamma counter, with the highest counts in the liver (12593 counts.min-1.g-1) and the lowest in the muscle (2687 counts.min-1.g-1).

Principal Conclusions

This study successfully demonstrated a quantitative 3D imaging method of tracking nitrogen gas through the body bothin vivoandex vivousing PET.
Direct measurement of dynamic attractant gradients reveals breakdown of the Patlak-Keller-Segel chemotaxis model
Authors: Phan Trung V. , Mattingly Henry H. , Vo Lam , Marvin Jonathan S. , Looger Loren L. , Emonet Thierry
Published: June 2023

Chemotactic bacteria not only navigate chemical gradients, but also shape their environments by consuming and secreting attractants. Investigating how these processes influence the dynamics of bacterial populations has been challenging because of a lack of experimental methods for measuring spatial profiles of chemoattractants in real time. Here, we use a fluorescent sensor for aspartate to directly measure bacterially generated chemoattractant gradients during collective migration. Our measurements show that the standard Patlak-Keller-Segel model for collective chemotactic bacterial migration breaks down at high cell densities. To address this, we propose modifications to the model that consider the impact of cell density on bacterial chemotaxis and attractant consumption. With these changes, the model explains our experimental data across all cell densities, offering new insight into chemotactic dynamics. Our findings highlight the significance of considering cell density effects on bacterial behavior, and the potential for fluorescent metabolite sensors to shed light on the complex emergent dynamics of bacterial communities.

SIGNIFICANCE STATEMENT

During collective cellular processes, cells often dynamically shape and respond to their chemical environments. Our understanding of these processes is limited by the ability to measure these chemical profiles in real time. For example, the Patlak-Keller-Segel model has widely been used to describe collective chemotaxis towards self-generated gradients in various systems, albeit without direct verification. Here we used a biocompatible fluorescent protein sensor to directly observe attractant gradients created and chased by collectively-migrating bacteria. Doing so uncovered limitations of the standard chemotaxis model at high cell densities and allowed us to establish an improved model. Our work demonstrates the potential for fluorescent protein sensors to measure the spatiotemporal dynamics of chemical environments in cellular communities.
Molecular Dynamics and Water site bias docking method allows the identification of key amino acids in the Carbohydrate Recognition Domain of a viral protein
Authors: Gamarra Marcelo D. , Dieterle Maria Eugenia , Capurro Juan I. Blanco , Radusky Leandro , Piuri Mariana , Modenutti Carlos P.
Published: June 2023

Carbohydrate-binding modules (CBMs) are protein domains that typically reside near catalytic domains, increasing substrate-protein proximity by constraining the conformational space of carbohydrates. Due to the flexibility and variability of glycans, the molecular details of how these protein regions recognize their target molecules are not always fully understood. Computational methods, including molecular docking and molecular dynamics simulations, have been employed to investigate lectin-carbohydrate interactions. In this study, we introduce a novel approach that integrates multiple computational techniques to identify the critical amino acids involved in the interaction between a CBM located at the tip of bacteriophage J-1’s tail and its carbohydrate counterparts. Our results highlight three amino acids that play a significant role in binding, which we confirmed through in vitro experiments. By presenting this approach, we offer an intriguing alternative for pinpointing amino acids that contribute to protein-sugar interactions, leading to a more thorough comprehension of the molecular determinants of lectin-carbohydrate interactions.
HDAC1-3 inhibition reduces CCR2 expression and immunosuppressive function of myeloid-derived suppressor cells
Authors: Xie Zhiqi , Okada Yoshiaki , Okuzaki Daisuke , Okada Naoki , Tachibana Masashi
Published: June 2023

Myeloid-derived suppressor cells (MDSCs) play a critical role in cancer progression and resistance, making them significant targets for cancer immunotherapy. Although epigenetic regulation by histone deacetylases (HDACs) regulates cell fate and function, the specific roles of HDACs in modulating MDSCs remain poorly understood. We aimed to examine the effects and underlying mechanisms of HDAC on MDSCs using various HDAC inhibitors. HDAC1-3 inhibitors were found to reduce the expression of CCR2, a chemokine receptor that mediates the migration of monocytic (M-)MDSCs to tumors and attenuated the immunosuppressive activity of MDSCs. In an orthotopic hepatocellular carcinoma (HCC) murine model, HDAC1-3 inhibitors reduced the infiltration of M-MDSCs, increased the number of natural killer cells in tumors, and suppressed tumor growth. Our results also suggest that HDAC1-3 inhibitors potentiate the antitumor effects of anti-programmed cell death protein 1 antibodies. To elucidate the molecular mechanisms underlying the inhibition of MDSCs by HDAC1-3 inhibitors, ATAC-seq and RNA-seq analyses were performed. We identified 115 genes that were epigenetically upregulated by HDAC1-3 inhibitors, related to transcriptional regulation and ubiquitination. HDAC1-3 inhibitors further reduced CCR2 protein expression by enhancing ubiquitination-mediated degradation. Our findings reveal a novel mechanism of action of HDAC1-3 inhibitors in MDSCs and suggest a potential combination strategy with immunotherapy for the clinical translation of HCC.
Validity of observation tools for patients hospitalized with osteoporotic vertebral fractures
Authors: Yoshimi Youhei , Matsuura Takanori , Miyazato Kazuaki , Takahashi Shiho , Tanaka Nami , Morinaga Hanae , Hayata Asuka , Onishi Minami , Nagano Yousuke , Ohnishi Hideo
Published: June 2023

Osteoporotic vertebral fractures in older patients impair activities of daily living because of low back pain and abnormal posture. Assessing pain using self-reported assessment tools is difficult, especially in patients with moderate-to-severe cognitive impairment. In recent years, observational assessment tools have been used when self-reported assessment tools were difficult to implement. However, no reports have investigated the usefulness of observational assessment tools in patients with acute-phase orthopedic disorders without comorbidities. This study examined the validity of observational tools for pain assessment in patients with lumbar vertebral fractures. Patients admitted to our hospital with acute-phase vertebral fractures were enrolled in this prospective study. Pain was assessed using Japanese versions of the Abbey Pain Scale and Doloplus-2 observational assessment tools, in addition to the Numerical Rating Scale, a self-reported assessment tool. To verify the validity of each pain assessment tool, we examined whether each tool correlated with the activities of daily living and ambulatory status. Activities of daily livings were assessed using the Barthel Index. Ambulatory status was assessed using the Functional Ambulation Categories and the 10-m walking test. Similar to the Numerical Rating Scale scores, assessments with the Abbey Pain Scale and Doloplus-2 showed significant decreases in scores over time. In addition, a significant positive correlation was observed between the self-reported and observational assessment tools. Each pain assessment tool was significantly negatively correlated with activities of daily livings and ambulatory status. Our results indicated when self-reported assessment with the Numerical Rating Scale was difficult for patients with cognitive impairment, pain could be estimated using the Abbey Pain Scale and Doloplus-2 observational assessment tools.
Environment-Wide Association Studies of Anemia in the National Health and Nutrition Examination Surveys
Authors: Zhou Jiayan , Palmiero Nicole , Passero Kristin , McGuigan John R , Zarzar Tomás González , Sandeep Prabhu K. , Hall Molly A.
Published: June 2023

Background

Anemia is a global health problem that can lead to chronic illness in adults and may be fatal in children and the elderly. While some dietary factors and heavy metals are known risk factors for anemia, there are no environment-wide studies of anemia.

Objectives

Our goal was to identify environment-wide risk factors for anemia.

Methods

We evaluated general anemia in children and adults and further classified anemia as a) iron, vitamin B12, or folate deficiency anemia; b) anemia in general chronic diseases; and c) anemia in chronic kidney disease. As well as quantitative measures including level of hemoglobin, serum vitamin B12, red blood cell (RBC) folate, and serum iron. Environment-wide association studies (EWAS) were performed to identify novel environmental risk factors of anemia in discovery and replication subsets of the National Health and Nutrition Examination Surveys (NHANES).

Results

We identified and replicated 106 potential environmental risk factors for anemia. As expected, serum iron was the top exposure associated with general anemia for adults. Cadmium was associated with adult hemoglobin levels, as were vitamin Bs, micronutrients, smoking, and alcohol consumption. Further, decreased levels of multiple vitamins, including vitamin A, vitamin Es and multiple vitamin Bs, were associated with general anemia in adults. Use of tobacco and alcohol was also found to be associated with red blood cell folate and serum iron levels. In children, serum iron level was associated with folic acid supplements and vitamin A supplements.

Discussion

This is the first EWAS of anemia, providing insights into the environmental etiology of anemia risk in children and adults. These results may lead to the development of public health recommendations to mitigate anemia risk factors.
Risk of tuberculosis and uptake rates of latent tuberculosis infection screening among clinical risk groups in South Korea: A nationwide population-based cohort study
Authors: Kim Hyung Woo , Min Jinsoo , Choi Joon Young , Shin Ah Young , Myong Jun-Pyo , Lee Yunhee , Yim Hyeon Woo , Jeong Hyunsuk , Bae Sanghyuk , Hoyong Choi , In Hyekyung , Park Ahyoung , Jang Miri , Koo Hyeon-Kyoung , Lee Sung-Soon , Park Jae Seuk , Kim Ju Sang
Published: June 2023

Background

This study aimed to investigate actual tuberculosis (TB) risk and uptake rates of latent tuberculosis infection (LTBI) screening among eight clinical risk groups specified in Korean guidelines. Proportions of potentially preventable TB in these groups were also calculated.

Methods and Findings

Patients enrolled before January 1st, 2018, were classified into a prevalence cohort whereas those enrolled thereafter were classified into an incidence cohort. Both cohorts were followed up until December 31st, 2020. Sex, age, and calendar year-adjusted standardized incidence ratio (SIR) of tuberculosis was calculated with total population in South Korea as a reference group. The number of TB patients notified in 2018 was investigated for both prevalence and incidence cohorts. SIR of TB in each incidence cohort was higher than that in each corresponding prevalence cohort. Among all incidence cohorts, SIR in people living with human immunodeficiency virus (PLHIV) was the highest (17.41, (95% CI: 14.14-21.43)). Although classified as moderate TB risk diseases in current guideline, end-stage renal disease (ESRD) (8.05, (7.02-9.23)) and uncontrolled diabetes mellitus (DM) (6.31, (5.78-6.99)) showed high SIRs comparable to other high-risk diseases. Among total TB cases notified in 2018, each cohort accounted for less than 1.5% except for patients with DM. The uptake rate of LTBI test was the highest among patients using TNF inhibitors (92.7%), followed by those who underwent organ transplantation (60.4%) and PLHIV (41.3%).

Conclusions

LTBI screening should be reinforced for certain clinical risk groups such as ESRD or uncontrolled DM. Beyond the current guideline, additional high-risk groups should be identified.
Early Psychosis Informatics into Care [EPICare]: A co-designed protocol for implementing and evaluating a national integrated digital registry and clinical decision support system within early intervention in psychosis services
Authors: Lowri Griffiths Siân , Murray Graham K. , Logeswaran Yanakan , Ainsworth John , Allan Sophie M. , Campbell Niyah , Drake Richard , Katshu Mohammad Zia , Machin Matthew , Pope Megan A. , Sullivan Sarah A. , Waring Justin , Bogatsu Tumelo , Kane Julie , Weetman Tyler , Johnson Sonia , Kirkbride James B. , Upthegrove Rachel
Published: June 2023

Introduction

Early Intervention in Psychosis services are nationally mandated in England to provide multidisciplinary care to people experiencing first-episode psychosis, which disproportionately affects deprived and ethnic minority youth. Quality of service provision varies by region, and people from historically underserved populations have unequal access. In other disease areas, including stroke and dementia, national digital registries coupled with clinical decision support systems have revolutionised delivery of equitable, evidence-based interventions to transform patient outcomes and reduce population-level disparities in care and prognosis. Given psychosis is ranked the third most burdensome mental health condition by the World Health Organization, it is essential that we achieve the same parity of health improvements. Here, we provide details of a co-designed protocol to produce an evidence-based, stakeholder-informed framework for the build, implementation, and evaluation of a national integrated digital registry and clinical decision support system for psychosis, known as EPICare (Early Psychosis Informatics for Care).

Methods and Analysis

Using a participatory co-design framework, we engaged key stakeholders (N∼40-50) across four meetings to establish the parameters and essential features of EPICare and identify factors likely to influence adoption and implementation into routine practice. Stakeholders consisted of organisational, clinical, academic, and patient and public contributors. In collaboration with National Health Service (NHS) informatics teams, we identified how to retrieve key data items from Electronic Health Records and subsequently design the software architecture and data model to create an infrastructure plan for future implementation. Guided by Normalisation Process Theory, data synthesised from observations of stakeholder meetings and individual interviews (n=10) were subject to interpretative qualitative analysis. Finally, a co-designed set of guides were produced to allow for the build, implementation, and evaluation of EPICare in a larger, future study. An inclusive, representative stakeholder group, fully engaged with the future co-development of EPICare, was also established.
Cost components of school-based oral health-promoting programs: a systematic review protocol
Authors: Matoso Bárbara da Silva Mourthé , Gomes Viviane Elisângela , Marcenes Wagner , Micaela de Souza Noronha Kênya Valéria , Lima Camilla Aparecida Silva de Oliveira , Ferreira Raquel Conceição
Published: June 2023

Introduction

Oral health-promoting school programs play a crucial role in achieving universal coverage of oral health care by addressing oral diseases and promoting the well-being and quality of life of children and adolescents. However, a lack of studies has evaluated the costs associated with implementing these programs, which hinders decision-makers in adopting them on a large scale. This review aims to assess the cost components involved in school-based oral health-promoting programs.

Methods

This review will include studies that have conducted either partial or full economic evaluations, focusing on describing the cost components of oral health-promoting programs implemented in primary schools involving students aged 6 to 14. A systematic search was conducted across multiple databases: MEDLINE, The Cochrane Library, the Virtual Health Library, the NHS Economic Evaluation Database, Web of Science, Scopus, and EMBASE. Additionally, gray literature was searched using the Health Technology Assessment Database. Two independent reviewers will screen the titles and abstracts, followed by a full-text review based on predefined inclusion criteria. Data extraction and critical appraisal evaluation will also be carried out independently by two reviewers. In case of disagreements, the reviewer team will resolve them through discussion.

Discussion

The systematic review resulting from this protocol aims to provide evidence regarding the cost components and necessary resources for implementing and maintaining oral health-promoting school programs. This information can assist decision-makers in adopting these programs on a larger scale and effectively addressing oral diseases among children and adolescents.

Protocol registration

CRD42022363743.