bluuebunny/crossref_metadata_2025 huggingface dataset:
Urbanization of a subtropical island (Okinawa, Japan) alters physicochemical characteristics and disrupts microbial community dynamics in nearshore ecosystems
Authors: Mars Brisbin Margaret , Dudley Kenneth L. , Yonashiro Yoshitaka , Mitarai Satoshi , Ares Angela
Published: January 2024

Subtropical and tropical islands are undergoing rapid urbanization as human populations and tourism expand worldwide. Urbanization disrupts coastal ecosystems by replacing forests and other natural habitats with roads, parking lots, and buildings. These impervious surfaces increase the amount of runoff and pollution that reaches coastal ecosystems. Urbanization also comes with increased industry, waste treatment needs, fishing and aquaculture pressure, and coastline engineering. Despite the major changes to coasts that accompany urbanization, specific impacts on marine ecosystems can be difficult to measure due to missing baselines. Here, we take advantage of a large gradient in urbanization on the subtropical island of Okinawa, Japan, to evaluate the impact of urbanization on nearshore ecosystems. We measured physicochemical parameters and assessed bacterial community composition every two weeks for one year at two nearshore sites adjacent to watersheds with >70% urban land use and two nearshore sites adjacent to watersheds with >70% rural land use. Our results show that urbanization increases freshwater input and nutrient loading to nearshore ecosystems and profoundly alters the microbial community, overriding the natural seasonal succession observed at rural sites. At urban sites, we detected multiple bacterial species that are fecal indicators and human or marine organism pathogens. The altered physicochemical conditions and microbial communities at urban sites can contribute to the degradation of nearby coral reefs. Results highlight the importance of a “ridge-to-reef” management mindset, as restoring natural coastlines could buffer the impact of urbanization on the marine environment.
Acoustic Signatures of the Cerrado: Machine Learning Reveals Unique Soundscapes Across Diverse Phytogeographies
Authors: Daleffi da Silva Bruno , Padovese Linilson
Published: January 2024

This article explores the application of machine learning techniques in acoustic ecology to classify the formations of the Brazilian Cerrado (Forest, Savanna, and Grassland) based on their soundscapes. Considering the Cerrado’s importance for biodiversity and hydrology, as well as the challenges faced by the biome in the face of agricultural expansion, the study seeks more efficient and economical methods for identifying its physiognomies.

Five statistical models were developed and evaluated, using both traditional Machine Learning and Deep Learning, with the use of Mel-Frequency Cepstral Coefficients (MFCCs) and spectrogram images as input variables. The performance of these models was measured by accuracy, precision, and recall metrics, revealing a superiority of the Convolutional Neural Network (CNN), which, despite requiring greater computational cost and training time, provided high precision in the classifications and valuable insights through the application of the LIME explainability technique.

Moreover, the study proposes a majority vote classification methodology for frequently observed events, enabling reliable classifications through models with moderate performance. It is concluded that the choice of the ideal model for the classification of soundscapes of the Cerrado should consider a balance between accuracy, operational complexity, and efficiency. The conclusions of this study offer relevant directions for future research and the application of monitoring technologies in conservation and recovery efforts of biomes.
Differentially polarized macrophages show diverse proangiogenic characteristics under normo- and hyperglycemic conditions
Authors: Shariatzadeh Mahnaz , Payán Gómez César , Dik Willem A. , Leenen Pieter J. M.
Published: January 2024

Purpose

Angiogenesis is a vital process involved in the formation of new blood vessels from existing ones. Macrophages play a crucial role in initiating endothelial activation and inflammation, and are involved in the pathological angiogenesis. Traditionally, macrophages have been classified, with the pro-angiogenic activity attributed to the M2 phenotype. However, recent evidence challenges the notion that only M2 macrophages possess pro-angiogenic properties. This study aims to investigate the pro- and anti-angiogenic properties of human polarized macrophages in normo- and hyper-glycemic conditions, in order to gain a better insight into the angiogenic capacity of M1- and M2-like macrophages in diabetes.

Methods

A comprehensive bioinformatic analysis of pro- and anti-angiogenic gene expression profiles related in M1-vs. M2-polarized macrophages was performed based on a large previously published dataset. The most contributing differentially expressed genes in angiogenesis were selected for further validation. Macrophages were generated and polarized by culturing CD14+monocytes and their stimulation with any of IFN-γ, IL-4, or IL-6 cytokines. Polarized macrophages were immunophenotyped using flow cytometry, and their expression of the selected genes were measured using qPCR. Finally, the proangiogenic capacity of the cells was assessed in anin vitro3-D endothelial tubule formation assay, containing GFP-expressing human retinal endothelial cells, pericytes, and pro-angiogenic growth factors.

Results

IL-4 and IL-6 induce distinct M2-like phenotypes in macrophages with mixed pro- and anti-angiogenic gene expressions. Hyperglycemia has a mild negative effect on the expression of M2-associated markers, however it does not significantly affect the angiogenic properties of macrophages.

Conclusion

Our data support the concept of a spectrum model for macrophage polarization, indicating that the angiogenic status of polarized macrophages is not limited to the M2-phenotype, but is rather mediated by microenvironmental cues, and can result in diverse phenotypic characteristics. The effect of hyperglycemia on the angiogenic capacity of macrophages requires more comprehensive investigation.
Computational Transcriptomic and Comparative Genomic Analysis of dead box RNA Helicase gene AT2G45810 Expressed in Plants Arabidopsis thaliana
Authors: Emon Mohammed , Hosen Akram , Bhajan Sujay Kumar , Jewel Zilhas Ahmed , Ali Md. Sarafat
Published: January 2024

Arabidopsis thalianais a short life cycle, small genome, and Brassicaceae family winter annual small flowering plants. It is popularly used as a model organism in genetics and plant biology research, and it is essential to understanding the molecular biology of many plant features, including light sensing and flower formation. It also plays a key role in the science of agronomy, and plant transcriptomics as well as genomics. When it comes to the development of multicellular creatures, transcriptional programs are crucial. The constantly active growth of different organ systems is supported by transcriptional programs. Arabidopsis embryos possess remarkable transcriptomes compared to other plant tissues comprising somatic embryo differentiation circumstances operating during plant embryogenesis. Here we show that the transcriptomic analysis of the genome dead box RNA helicase gene AT2G45810 ofArabidopsis thalianaAraport11 species which revealed the specific gene expression patterns of Arabidopsis tissue-specific information of developmental map, embryo, single cell, DNA damage, cellular interactions, pathway analysis, etc., throughIn Silicoor computational approaches. In this particular study, we used the TAIR, Phytozome, and plant comparative genomics portal for retrieving and identification of specific genes of interest. Next, we used web-based Bar utoronto tools to visualize other data, including functional genomics. Their protein and gene expression tools facilitate the exploration of promoters, the identification of protein-protein interactions, the viewing of expression patterns as electronic fluorescent pictographs or heatmaps, and more.
IOBR2: Multidimensional Decoding Tumor Microenvironment for Immuno-Oncology Research
Authors: Zeng Dongqiang , Fang Yiran , Luo Peng , Qiu Wenjun , Wang Shixiang , Shen Rongfang , Gu Wenchao , Huang Xiatong , Mao Qianqian , Lai Yonghong , Xu Xi , Shi Min , Yu Guangchuang , Liao Wangjun
Published: January 2024

The use of large transcriptome datasets has greatly improved our understanding of the tumor microenvironment (TME) and helped develop precise immunotherapies. The increasing popularity of multi-omics sequencing, single-cell transcriptome sequencing (scRNA), and spatial transcriptome sequencing has led to numerous new discoveries. However, these findings require clinical phenotypic validation with a large sample size. To enhance the integration of multi-omics in advancing research on the tumor microenvironment, we have developed a systematic and comprehensive analytical tool (Immuno-Oncology Biological Research 2, IOBR2) based on our prior work. IOBR2 offers six modules for TME analysis based on multi-omics data. These modules cover data preprocessing, TME estimation, TME infiltrating patterns, cellular interactions, genome and TME interaction, and visualization for TME relevant features, as well as modelling based on key features. IOBR2 integrates multiple vital microenvironmental analysis algorithms and signature estimation methods, simplifying the analysis and downstream visualization of the TME. In addition to providing a quick and easy way to construct gene signatures from single-cell data, IOBR2 also provides a way to construct a reference matrix for TME deconvolution from single-cell RNAseq. The analysis pipeline and feature visualization are user-friendly and provide a comprehensive description of the complex TME, offering insights into tumor-immune interactions. A comprehensive gitbook (https://iobr.github.io/book/) is available with a user-friendly manual and complete analysis workflow for each module.
FLAb: Benchmarking deep learning methods for antibody fitness prediction
Authors: Chungyoun Michael , Ruffolo Jeffrey , Gray Jeffrey
Published: January 2024

The successful application of machine learning in therapeutic antibody design relies heavily on the ability of models to accurately represent the sequence-structure-function landscape, also known as the fitness landscape. Previous protein bench-marks (including The Critical Assessment of Function Annotation [33], Tasks Assessing Protein Embeddings [23], and FLIP [6]) examine fitness and mutational landscapes across many protein families, but they either exclude antibody data or use very little of it. In light of this, we present the Fitness Landscape for Antibodies (FLAb), the largest therapeutic antibody design benchmark to date. FLAb currently encompasses six properties of therapeutic antibodies: (1) expression, (2) thermosta-bility, (3) immunogenicity, (4) aggregation, (5) polyreactivity, and (6) binding affinity. We use FLAb to assess the performance of various widely adopted, pretrained, deep learning models for proteins (IgLM [28], AntiBERTy [26], ProtGPT2 [11], ProGen2 [21], ProteinMPNN [7], and ESM-IF [13]); and compare them to physics-based Rosetta [1]. Overall, no models are able to correlate with all properties or across multiple datasets of similar properties, indicating that more work is needed in prediction of antibody fitness. Additionally, we elucidate how wild type origin, deep learning architecture, training data composition, parameter size, and evolutionary signal affect performance, and we identify which fitness landscapes are more readily captured by each protein model. To promote an expansion on therapeutic antibody design benchmarking, all FLAb data are freely accessible and open for additional contribution athttps://github.com/Graylab/FLAb.
Thermal Tolerance Plasticity and Dynamics of Thermal Tolerance inEublepharis macularius: Implications for Future Climate-Driven Heat Stress
Authors: White Emma , Kim Solyip , Wegh Garrett , Chiari Ylenia
Published: January 2024

The intensity and duration of heat waves, as well as average global temperatures, are expected to increase due to climate change. Heat waves can cause physiological stress and reduce fitness in animals. Species can reduce overheating risk through phenotypic plasticity, which allows them to raise their thermal tolerance limits over time. This mechanism could be important for ectotherms whose body temperatures are directly influenced by available environmental temperatures. Geckos are a large, diverse group of ectotherms that vary in their thermal habitats and times of daily activity, which could affect how they physiologically adjust to heat waves. Data on thermal physiology are scarce for reptiles, with only one study in geckos. Understanding thermal tolerance and plasticity, and their relationship, is essential for understanding how some species are able to adjust or adapt to changing temperatures. In this study, we estimated thermal tolerance and plasticity, and their interaction, in the crepuscular gecko,Eublepharis macularius, a species that is emerging as a model for reptile biology. After estimating basal thermal tolerance for 28 geckos, thermal tolerance was measured for each individual a second time at several timepoints (3, 6, or 24 h) to determine thermal tolerance plasticity. We found that thermal tolerance plasticity (1) does not depend on the basal thermal tolerance of the organism, (2) was highest after 6 hours from initial heat shock, and (3) was negatively influenced by individual body mass. Our findings contribute to the increasing body of work focused on understanding the influence of biological and environmental factors on thermal tolerance plasticity in organisms and provide phenotypic data to further investigate the molecular basis of thermal tolerance plasticity in organisms.
Multi-Source Graph Synthesis (MUGS) for Pediatric Knowledge Graphs from Electronic Health Records
Authors: Li Mengyan , Li Xiaoou , Pan Kevin , Geva Alon , Yang Doris , Sweet Sara Morini , Bonzel Clara-Lea , Panickan Vidul Ayakulangara , Xiong Xin , Mandl Kenneth , Cai Tianxi
Published: January 2024

The wealth of valuable real-world medical data found within Electronic Health Record (EHR) systems is particularly significant in the field of pediatrics, where conventional clinical studies face notably high barriers. However, constructing accurate knowledge graphs from pediatric EHR data is challenging due to its limited content density compared to EHR data for the general population. Additionally, knowledge graphs built from EHR data primarily covering adult patients may not suit the unique biomedical characteristics of pediatric patients. In this research, we introduce a graph transfer learning approach aimed at constructing precise pediatric knowledge graphs. We present MUlti-source Graph Synthesis (MUGS), an algorithm designed to create embeddings for pediatric EHR codes by leveraging information from three distinct sources: (1) pediatric EHR data, (2) EHR data from the general population, and (3) existing hierarchical medical ontology knowledge shared across different patient populations. We break down these code embeddings into shared and unshared components, facilitating the adaptive and robust capture of varying levels of heterogeneity across different medical sites through meticulous hyperparameter tuning. We assessed the quality of these code embeddings in recognizing established relationships among pediatric codes, as curated from credible online sources, pediatric physicians, or GPT. Furthermore, we developed a web API for visualizing pediatric knowledge graphs generated using MUGS embeddings and devised a phenotyping algorithm to identify patients with characteristics similar to a given profile, with a specific focus on pediatric pulmonary hypertension (PH). The MUGS-generated embeddings demonstrated resilience against negative transfer and exhibited superior performance across all three tasks when compared to pediatric-only approaches, multi-site pooling, and semantic-based methods. MUGS embeddings open up new avenues for evidence-based pediatric research utilizing EHR data.
Emotion-related impulsivity is related to orbitofrontal cortical sulcation
Authors: Hastings William L. , Willbrand Ethan H. , Elliott Matthew V. , Johnson Sheri L. , Weiner Kevin S.
Published: January 2024

Background

Emotion-related impulsivity (ERI) describes the trait-like tendency toward poor self-control when experiencing strong emotions. ERI has been shown to be elevated across psychiatric disorders and predictive of the onset and worsening of psychiatric syndromes. Recent work has correlated ERI scores with the neuroanatomy of the orbitofrontal cortex (OFC). Informed by a growing body of research indicating that the morphology of cortical folds (sulci) can produce insights into behavioral outcomes, the present study modeled the association between ERI and the sulcal morphology of OFC at a finer scale than previously conducted.

Methods

Analyses were conducted in a transdiagnostic sample of 118 individuals with a broad range of psychiatric syndromes. We first manually defined over 2000 sulci across the 118 participants. We then implemented a model-based LASSO regression to relate OFC sulcal morphology to ERI and test whether effects were specific to ERI as compared to non-emotion-related impulsivity.

Results

The LASSO regression revealed bilateral associations of ERI with the depth of eight OFC sulci. These effects were specific to ERI and were not observed in non-emotion-related impulsivity. In addition, we identified a new transverse component of the olfactory sulcus in every hemisphere that is dissociable from the longitudinal component based on anatomical features and correlation with behavior, which could serve as a new transdiagnostic biomarker.

Conclusions

The results of this data-driven investigation provide greater neuroanatomical and neurodevelopmental specificity on how OFC is related to ERI. As such, findings link neuroanatomical characteristics to a trait that is highly predictive of psychopathology.
Recombinant venom proteins in insect seminal fluid reduces female lifespan
Authors: Beach Samuel J. , Maselko Maciej
Published: January 2024

The emergence of insecticide resistance has increased the need for alternative pest management tools1,2Numerous genetic biocontrol approaches, which involve the release of genetically modified organisms to control pest populations, are in various stages of development to provide highly targeted pest control3-7. However, all current mating-based genetic biocontrol technologies function by releasing engineered males which skew sex-ratios or reduce offspring viability in subsequent generations. This allows mated females continue to cause harm (e.g. transmit disease). Here, we demonstrate the first example ofintragenerational genetic biocontrol, wherein mating with engineered males reduces female lifespan. The toxic male technique (TMT) involves the heterologous expression of insecticidal proteins within the male reproductive tract that are transferred to females via mating. We demonstrate TMT inDrosophila melanogastermales, which reduce the median lifespan of mated females by 37 - 59% compared to controls mated to wild type males. Agent-based models ofAedes aegyptipredict that compared to existing genetic biocontrol technologies, even modest levels of mated female mortality could allow TMT to suppress a female population substantially faster, which is likely to result in reduced disease burdens. TMT presents a novel approach for combatting outbreaks of disease vectors and agricultural pests.

Graphical Abstract
OmniNA: A foundation model for nucleotide sequences
Authors: Shen Xilin , Li Xiangchun
Published: January 2024

Foundation models have demonstrated exceptional efficacy across diverse downstream tasks. However, within the realms of genomics and transcriptomics, a notable gap persists in the availability of models that afford a comprehensive understanding of nucleotide sequence principles across various species. Here, we present OmniNA, a foundation generative model designed for comprehensive nucleotide sequence learning. The model was pre-trained on 91.7 million nucleotide sequences and the corresponding annotations encompassing 1076.2 billion bases and 197 million words spanning a multitude of species. We demonstrated OmniNA gains the capacity to understand the semantics of the nucleotide sequence and textual annotations by analyzing the learned representation of the pre-trained model. OmniNA can be fine-tuned to align multiple nucleotide learning tasks with natural language paradigms. We demonstrate OmniNA-1.7B surpasses or rivals state-of-the art methods in 17 nucleotide tasks, encompassing nucleotide sequences detection and species classification. The model’s understanding of nucleotide grammars enhances its capability to reveal the mutation effect of nucleotide sequence on DNA and RNA processing. We hereby release the OmniNA-1.7B model as an open-source contribution to the research community. This foundation model signifies a step toward advancing our comprehension of nucleotide sequences across diverse species and holds substantial promise to facilitating genomics and transcriptomics research.
The Alzheimer’s Aβ peptide forms biomolecular condensates that trigger amyloid aggregation
Authors: Šneiderienė Greta , Díaz Alicia González , Adhikari Sourav Das , Wei Jiapeng , Michaels Thomas , Šneideris Tomas , Linse Sara , Vendruscolo Michele , Garai Kanchan , Knowles Tuomas P. J.
Published: January 2024

The onset and development of Alzheimer’s disease (AD) is linked to the accumulation of pathological aggregates formed from the normally monomeric amyloid-β peptide within the central nervous system. These Aβ aggregates are increasingly successfully targeted with clinical therapies, but the fundamental molecular steps that trigger the initial nucleation event leading to the conversion of monomeric Aβ peptide into pathological aggregates remain unknown. Here we show that the Aβ peptide can form biomolecular condensates on lipid bilayers both in molecular assays and in living cells. Our results reveal that these Aβ condensates can significantly accelerate the primary nucleation step in the amyloid conversion cascade that leads to the formation of amyloid aggregates and plaque. We show that Aβ condensates contain phospholipids, are intrinsically heterogenous, and are prone to undergo a liquid-to-solid transition leading to the formation amyloid fibrils. These findings uncover the liquid-liquid phase separation behaviour of the Aβ peptide, and reveal a new molecular step very early in the amyloid-β aggregation cascade that can form the basis for novel therapeutic intervention strategies.

Significance statement

The hallmark of Alzheimer’s disease is the abnormal buildup of the normally soluble amyloid β protein aggregates in the central nervous system. While the molecular mechanisms at the late stages of the amyloid β aggregation cascade are well understood, the initial steps remained elusive until now. Our current study demonstrates that amyloid β undergoes liquid-liquid phase separation on lipid surfaces, which triggers primary nucleation and initiates the amyloid β aggregation cascade. This newly identified step in the molecular mechanism of Alzheimer’s disease represents a promising target for the development of alternative innovative therapeutic strategies.
Comparative pangenome analysis of major pneumococcal genotypes from India
Authors: Murthy Peela Sreeram Chandra , Sistla Sujatha
Published: January 2024

Background

Pneumococcal genomes are highly dynamic with varying core genome sizes. The genotype classification system, Global Pneumococcal Sequence Clusters, identified patterns within genotype and antibiotic resistance. Few genotypes like GPSC10 are frequently associated with antimicrobial resistance and high rates of non-vaccine serotypes.

Objective

To identify and annotate the differences in the core genomes of major GPSC in India, and construct and analyse the Indian Pneumococcal Pangenome (IPPG).

Methods

Using existing dataset from the Global Pneumococcal Sequencing Project, 618 strains were included. The most frequent GPSCs: GPSC1, GOSC2, GPSC8, GPSC9 and GPSC10 were analyzed separately. Pangenomes were constructed using Panaroo with tuning the family threshold parameter. Differences in protein clusters were identified using Orthovenn3 webserver. Functional annotations were performed by eggNOG, Uniprot and STRING database searches.

Results

The IPPG core genome size (1615 genes) was similar to those reported previously, with similar distribution of metabolic categories across the five GPSC types. The GPSC10 (1619 genes) and GPSC1 (1909 genes) had the lowest and highest core genome sizes respectively, and these core genomes possessed genes encoding for macrolide and tetracycline resistance. Virulence genes ply, psaA, pce (cbpE), pavA, nanB, lytA, and hysA are detected among all the core genomes.

Conclusions

There is a genotype specific variation within the core genomes of major GPSCs in India. The presence of antibiotic resistance genes among GPSC1 and GPSC10 core genomes explain widespread drug resistance due to these genotypes. The core virulence genes identified among all the genotypes indicate conserved pathogenesis mechanisms, and can be targets for vaccine development or therapy.
Different vaccine platforms result in distinct antibody responses to the same antigen in haemodialysis patients
Authors: Wall Nadya , Lamerton Rachel , Ashford Fiona , Perez-Toledo Marisol , Jasiulewicz Aleksandra , Banham Gemma D , Newby Maddy L , Faustini Sian , Richter Alex , Selvaskandan Haresh , Billany Roseanne E , Adenwalla Sherna , Henderson Ian R , Crispin Max , Graham-Brown Matthew , Harper Lorraine , Cunningham Adam F
Published: January 2024

Generalised immune dysfunction in chronic kidney disease, especially in patients requiring haemodialysis (HD), significantly enhances the risk of severe infections. Moreover, vaccine-induced immunity is typically reduced in HD populations, but the full mechanisms behind this remain unclear. The SARS-CoV-2 pandemic provided an opportunity to examine the magnitude and functionality of antibody responses in HD patients to a previously unencountered antigen, Spike (S)-glycoprotein, after vaccination with different vaccine platforms (viral vector (VV); mRNA (mRV)). Here, we compared total and functional anti-S antibody responses (cross-variant neutralisation and complement binding) in 187 HD patients and 43 healthy controls 21-28 days after serial immunisation. After 2 doses of the same vaccine, HD patients had anti-S antibody levels and complement binding capacity comparable to controls. However, 2 doses of mRV induced greater polyfunctional antibody responses than VV, yet previous SARS-CoV-2 infection or an mRV boost after 2 doses of VV significantly enhanced antibody functionality in HD patients. Therefore, HD patients can generate near-normal, functional antigen-specific antibody responses following serial vaccination to a novel antigen, suggesting largely intact B cell memory. Encouragingly, exploiting immunological memory by using mRNA vaccines and boosting may improve the success of vaccination strategies in this vulnerable patient population.
Targeted CRISPR-Cas9 screening identifies transcription factor network controlling murine haemato-endothelial fate commitment
Authors: Teske Michael , Wertheimer Tobias , Butz Stefan , Zwicky Pascale , Mallona Izaskun , Elling Ulrich , Lancrin Christophe , Becher Burkhard , Grosso Ana Rita , Baubec Tuncay , Schmolka Nina
Published: January 2024

Haematopoiesis is a tightly coordinated process that forms and maintains all blood cells. During development blood generation begins in the yolk sac with the differentiation of haemato-endothelial mesoderm giving rise to haematopoietic progenitors. Which molecular regulators are crucial for haemato-endothelial mesoderm formation remains unclear and has not been studied in an unbiased way. Here we employ a mouse embryonic stem cell model that recapitulates embryonic blood development and perform targeted CRISPR-Cas9 knock out screens focusing on transcription factors and chromatin regulators. Focusing on the transition of primitive towards haematoendothelial mesoderm we identified the known master regulator Etv2 and novel transcription factors including Smad1, Ldb1, Six4 and Zbtb7b acting as crucial drivers or repressors of mesodermal commitment. Our transcriptome analysis highlights that each factor has a precise impact on the gene expression signature of the developing mesoderm resulting in the formation of mesodermal subsets with a defined lineage differentiation bias. Our study reveals novel molecular pathways governing mesodermal development crucial to allow endothelial and haematopoietic lineage specification.
Mitochondrial ncRNA LDL-805 declines in alveolar epithelial type 2 cells of chronic obstructive pulmonary disease patients
Authors: Mathuram Theodore L. , Su Yafei , Bard Jonathan E. , Perry Noa A. , Chen Chien Wen , Warren Marisa T. , Linden Phillip A. , Perry Yaron , Hatzoglou Maria , Wu Yun , Blumental-Perry Anna
Published: January 2024

Rationale

We showed that levels of a murine mitochondrial noncoding RNA,mito-ncR-LDL805, increase in alveolar epithelial type 2 cells exposed to extracts from cigarette smoke. The transcripts translocate to the nucleus, upregulating nucleus-encoded mitochondrial genes and mitochondrial bioenergetics. This response is lost after chronic exposure to smoke in a mouse model of chronic obstructive pulmonary disease.

Objectives

To determine ifmito-ncR-LDL805plays a role in human disease, this study aimed to (i) identify the human homologue, (ii) test if the smoke-induced response occurs in human cells, (ii) determine causality between the subcellular localization of the transcript and increased mitochondrial bioenergetics, and (iii) analyzemito-ncR-LDL805transcript levels in samples from patients with chronic obstructive pulmonary disease.

Methods

Levels and subcellular localization of the human homologue identified from an RNA transcript library were assessed in human alveolar epithelial type 2 cells exposed to smoke extract. Lipid nanoparticles were used for nucleus-targeted delivery ofmito-ncR-LDL805transcripts. Analyses includedin situhybridization, quantitative PCR, cell growth, and Seahorse mitochondrial bioenergetics assays.

Measurements and Main Results

The levels of human homologue transiently increased and the transcripts translocated to the nuclei in human cells exposed to smoke extract. Targeted nuclear delivery of transcripts increased mitochondrial bioenergetics. Alveolar cells from humans with chronic obstructive pulmonary disease had reduced levels of themito-ncR-LDL805.

Conclusions

mito-ncR-LDL805mediates mitochondrial bioenergetics in murine and human alveolar epithelial type 2 cells in response to cigarette smoke exposure, but this response is likely lost in diseases associated with chronic smoking, such as chronic obstructive pulmonary disease, due to its diminished levels.

Impact

This study describes a novel mechanism by which epithelial cells in the lungs adapt to the mitochondrial stress triggered by exposure to cigarette smoke. We show that a noncoding RNA in mitochondria is upregulated and translocated to the nuclei of alveolar epithelial type 2 cells to trigger expression of genes that restore mitochondrial bioenergetics. Mitochondria function and levels of the noncoding RNA decrease under conditions that lead to chronic obstructive pulmonary disease, suggesting that the mitochondrial noncoding RNA can serve as potential therapeutic target to restore function to halt disease progression.
Quantifying spectral information about source separation in multisource odour plumes
Authors: Tootoonian Sina , True Aaron C. , Crimaldi John P. , Schaefer Andreas T.
Published: January 2024

Odours released by objects in natural environments can contain information about their spatial locations. In particular, the correlation of odour concentration fields produced by two spatially separated sources contains information about the distance between the sources. Mice are able to distinguish correlated and anti-correlated odour fluctuations at frequencies up to 40 Hz. Can this high-frequency acuity support odour source localization? Here we answer this question by quantifying the spatial information about source separation contained in the spectral constituents of correlations. We used computational fluid dynamics simulations of multisource plumes in two-dimensional chaotic flow environments to generate temporally complex, covarying odour concentration fields. By relating the correlation of these fields to the spectral decompositions of the associated odour concentration timeseries, and making simplifying assumptions about the statistics of these decompositions, we derived analytic expressions for the Fisher information contained in the spectral components of the correlations about source separation. We computed the Fisher information for a broad range of frequencies and source separations and found that high frequencies were more informative than low frequencies when sources were close relative to the sizes of the large eddies in the flow. We observed a qualitatively similar effect in an independent set of simulations with different geometry, but not for surrogate data with a similar power spectrum to our simulations but in which all frequencies werea prioriequally informative. Our work suggests that the high-frequency acuity of the murine olfactory system may support high-resolution spatial localization of odour sources. We also provide a model of the distribution of the spectral components of correlations that is accurate over a broad range of frequencies and source separations. More broadly, our work establishes an approach for the quantification of the spatial information in odour concentration timeseries.
Blood immunophenotyping identifies distinct kidney histopathology and outcomes in patients with lupus nephritis
Authors: Horisberger Alice , Griffith Alec , Keegan Joshua , Arazi Arnon , Pulford John , Murzin Ekaterina , Howard Kaitlyn , Hancock Brandon , Fava Andrea , Sasaki Takanori , Ghosh Tusharkanti , Inamo Jun , Beuschel Rebecca , Cao Ye , Preisinger Katie , Gutierrez-Arcelus Maria , Eisenhaure Thomas M. , Guthridge Joel , Hoover Paul J. , Dall’Era Maria , Wofsy David , Kamen Diane L. , Kalunian Kenneth C. , Furie Richard , Belmont Michael , Izmirly Peter , Clancy Robert , Hildeman David , Woodle E. Steve , Apruzzese William , McMahon Maureen A. , Grossman Jennifer , Barnas Jennifer L. , Payan-Schober Fernanda , Ishimori Mariko , Weisman Michael , Kretzler Matthias , Berthier Celine C. , Hodgin Jeffrey B. , Demeke Dawit S. , Putterman Chaim ,   Accelerating Medicines Partnership: RA/SLE Network, Brenner Michael B. , Anolik Jennifer H. , Raychaudhuri Soumya , Hacohen Nir , James Judith A. , Davidson Anne , Petri Michelle A. , Buyon Jill P. , Diamond Betty , Zhang Fan , Lederer James A. , Rao Deepak A.
Published: January 2024

Lupus nephritis (LN) is a frequent manifestation of systemic lupus erythematosus, and fewer than half of patients achieve complete renal response with standard immunosuppressants. Identifying non-invasive, blood-based pathologic immune alterations associated with renal injury could aid therapeutic decisions. Here, we used mass cytometry immunophenotyping of peripheral blood mononuclear cells in 145 patients with biopsy-proven LN and 40 healthy controls to evaluate the heterogeneity of immune activation in patients with LN and to identify correlates of renal parameters and treatment response. Unbiased analysis identified 3 immunologically distinct groups of patients with LN that were associated with different patterns of histopathology, renal cell infiltrates, urine proteomic profiles, and treatment response at one year. Patients with enriched circulating granzyme B+T cells at baseline showed more severe disease and increased numbers of activated CD8 T cells in the kidney, yet they had the highest likelihood of treatment response. A second group characterized primarily by a high type I interferon signature had a lower likelihood of response to therapy, while a third group appeared immunologically inactive by immunophenotyping at enrollment but with chronic renal injuries. Main immune profiles could be distilled down to 5 simple cytometric parameters that recapitulate several of the associations, highlighting the potential for blood immune profiling to translate to clinically useful non-invasive metrics to assess immune-mediated disease in LN.
Management of Central Post-Stroke Pain: Systematic Review and Meta-Analysis
Authors: Tamasauskas Arnas , Marshall Andrew , Silva-Passadouro Barbara , Fallon Nichollas , Frank Bernhard , Laurinaviciute Svajune , Keller Simon
Published: January 2024

Central post stroke pain (CPSP) is a neuropathic pain condition prevalent in 8% to 35% of stroke patients. This systematic review and meta-analysis aimed to provide insight in the effectiveness of available pharmacological, physical, psychological, and neuromodulation intervention in reducing pain in CPSP patients. Secondary outcomes included mood, sleep, global impression of change, and physical responses. Data extraction included participant demographics, stroke aetiology, pain characteristics, pain reduction scores, and secondary outcome metrics. Forty two original studies were included with a total of 1451 participants. Twelve studies met requirements for a random-effects meta-analysis which found: neuromodulation to be the most effective with a moderate effect on pain scores (SMD = -0.60, 95% confidence interval [-0.97, -0.23]), followed by physical interventions with moderate effect (SMD = -0.55, [-1.28, 0.18), and pharmacological interventions with a small effect on pain (SMD = -0.36, [-0.68, -0.03]). Fourteen studies were included in proportional meta-analysis with pharmacological studies having a moderate effect (58.34% mean reduction, [36.50, 80.18]), and neuromodulation studies a small effect (31.70% mean reduction, [21.44, 41.96]). Sixteen studies were included in the narrative review. While the overall medium risk of bias limits generalisation of findings, fluvoxamine and repetitive transcranial magnetic stimulation was found to have consistently good pain alleviation and relatively low risk of side effects. Anticonvulsants were found to have a significant effect on pain reduction, but were found to have the most side effects. Virtual reality and acupuncture show promising results, but lack rigorous methodological investigation to understand their full effect.
Trajectories in county-level Low Birthweight Rates and Associated Contextual Factors in the United States, 2016-2021
Authors: Dwivedi Pallavi , Nguyen Thu T. , He Xin , Nguyen Quynh C.
Published: January 2024

Introduction

Infants with low birthweight (less than 2500 grams) have greater risk of mortality, long-term neurologic disability and chronic diseases such as diabetes and cardiovascular disease as compared to infants with normal birthweight. This study examined the trajectories of low birthweight rate in the U.S. across the metropolitan and non-metropolitan counties over the time period of 2016-2021 and the associated contextual factors.

Methods

This longitudinal study utilized data on 21,759,834 singleton births across 3,108 counties. Data on birthweight and maternal sociodemographic and behavioral characteristics was obtained from the National Center for Health Statistics. A generalized estimating equations model was used to examine the association of county-level contextual variables with low birthweight rates.

Results

A significant increase in low birthweight rates was observed across the counties over the duration of the study. Large metro and small metro counties had significantly higher low birthweight rates as compared to non-metro counties. High percentage of Black women, underweight women, age more than 35 years, lack of prenatal care, uninsured population, and high violent crime rate was associated with an increase in low-birth-weight rates. Other contextual characteristics (percentage of married women, American Indian/Alaskan Native women, and unemployed population) differed in their associations with low birthweight rates depending on county metropolitan status.

Conclusions

Our study findings emphasize the importance of developing interventions to address geographical heterogeneity in low birthweight burden, particularly for metropolitan areas and communities with vulnerable racial/ethnic and socioeconomic groups.
Contrasting methods of measurement of antibiotic exposure in clinical research: a real-world application predicting hospital-associatedClostridioides difficileinfection
Authors: Webster Jessica L. , Eppes Stephen , Lee Brian K , Harrington Nicole S. , Goldstein Neal D.
Published: January 2024

The goal of this article is to summarize common methods of antibiotic measurement used in clinical research and demonstrate analytic methods for selection of exposure variables. Variable selection was demonstrated using three methods for modeling exposure, using data from a case-control study onClostridioides difficileinfection in hospitalized patients: 1) factor analysis of mixed data, 2) multiple logistic regression models, and 3) Least Absolute Shrinkage and Selection Operator (LASSO) regression. The factor analysis identified 9 variables contributing the most variation in the dataset:any antibiotic treatment;number of classes;number of treatments;dose; and classesmonobactam, β-lactamβ-lactamase inhibitors,rifamycin,carbapenem, andcephalosporin. The regression models resulting in the best model fit used predictorsany antibiotic exposureandproportion of hospitalization on antibiotics. The LASSO model selected 22 variables for inclusion in the predictive model, exposure variables including:any antibiotic treatment; classes β-lactamβ-lactamase inhibitors,carbapenem,cephalosporin,fluoroquinolone,monobactam,rifamycin,sulfonamides, andmiscellaneous; andproportion of hospitalization on antibiotics. Investigators studying antibiotic exposure should consider multiple aspects of treatment informed by their research question and the theory on how antibiotics may impact the distribution of the outcome in their target population.
A tripartite organelle platform links growth factor receptor signaling to mitochondrial metabolism
Authors: Mesa Deborah Salvi , Barbieri Elisa , Raimondi Andrea , Freddi Stefano , Miloro Giorgia , Jendrisek Gorana , Caldieri Giusi , Quarto Micaela , Lomoriello Irene Schiano , Malabarba Maria Grazia , Bresci Arianna , Manetti Francesco , Vernuccio Federico , Abdo Hind , Scita Giorgio , Polli Dario , Tacchetti Carlo , Pinton Paolo , Bonora Massimo , Di Fiore Pier Paolo , Sigismund Sara
Published: January 2024

One open question in the biology of growth factor receptors is how a quantitative input (i.e.,ligand concentration) is decoded by the cell to produce specific response(s). Here, we show that an EGFR endocytic mechanism, non-clathrin endocytosis (NCE), which is activated only at high ligand concentrations and targets receptor to degradation, requires a tripartite organelle platform involving the plasma membrane (PM), endoplasmic reticulum (ER) and mitochondria. At these contact sites, EGFR-dependent, ER-generated Ca2+oscillations are sensed by mitochondria, leading to increased metabolism and ATP production. Locally released ATP is required for cortical actin remodeling and EGFR-NCE vesicle fission. The same biochemical circuitry is also needed for an effector function of EGFR, i.e., collective motility. The multiorganelle signaling platform herein described mediates direct communication between EGFR signaling and mitochondrial metabolism, and is predicted to have a broad impact on cell physiology as it is activated by another growth factor receptor, HGFR/MET.
Targeting ductal-endothelial crosstalk alleviate pancreatitis
Authors: Gao Rong-rong , Ma Lan-yue , Chen Jian-wei , Wang Yu-xiang , Li Yu-yan , Zhou Zi-yuan , Deng Zhao-hua , Zhong Jing , Shu Ya-hai , Liu Yang , Chen Qi
Published: January 2024

Pancreatitis are common gastrointestinal disorders that cause hospitalization with significant morbidity and mortality. The mechanistic pathophysiology of pancreatitis is complicated, which greatly limits the discovery of pharmacological intervention methods. Here, we show that administration of antagonist of Integrin-α5, significantly mitigates the pathological condition of acute pancreatitis. In caerulein-induced acute pancreatitis model, the newly emergent CK19 positive cells are highly vascularized with significant increase of vascular density and endothelial cell number. Single cell RNA sequencing analysis shows ductal and endothelial cells are intimate interacting partners. Pancreatitis dramatically reduce the crosstalk in ductal-endothelial interface but promote the integrin-α5 signaling. Blocking this signaling significantly reduce acinar-to-ductal metaplasia, pathological angiogenesis and restore other abnormal defects induced by caerulein. Our work reveals a therapeutic potential of targeting integrin-α5 as uncharacterized pharmacological method to alleviate the symptom of pancreatitis.
Requirements for the Biogenesis of [2Fe-2S] Proteins in the Human and Yeast Cytosol
Authors: Braymer Joseph J. , Stehling Oliver , Stümpfig Martin , Rösser Ralf , Spantgar Farah , Blinn Catharina M. , Mühlenhoff Ulrich , Pierik Antonio J. , Lill Roland
Published: January 2024

The biogenesis of iron-sulfur (Fe/S) proteins entails the synthesis and trafficking of Fe/S clusters, followed by their insertion into target apoproteins. In eukaryotes, the multiple steps of biogenesis are accomplished by complex protein machineries in both mitochondria (ISC) and cytosol (CIA). The underlying biochemical pathways have been elucidated over the past decades, yet the mechanisms of cytosolic [2Fe-2S] protein assembly have remained ill-defined. Similarly, the precise site of glutathione (GSH) requirement in cytosolic and nuclear Fe/S protein biogenesis is unclear, as is the molecular role of the GSH-dependent cytosolic monothiol glutaredoxins (cGrxs). Here, we investigated these questions in human and yeast cells by variousin vivoapproaches. [2Fe-2S] cluster assembly of cytosolic target apoproteins required the mitochondrial ISC machinery, the ABC transporter Atm1/ABCB7 and GSH, yet occurred independently of both the CIA system and cGrxs. This mechanism was strikingly different from the ISC-, Atm1/ABCB7-, GSH-, and CIA-dependent assembly of cytosolic-nuclear [4Fe-4S] proteins. One notable exception to this newly defined cytosolic [2Fe-2S] protein maturation pathway was the yeast protein Apd1 which used the CIA system via binding to the CIA targeting complex through its C-terminal tryptophan. cGrxs, although attributed as [2Fe-2S] cluster chaperones or trafficking proteins, were not essentialin vivofor deliver ing [2Fe-2S] clusters to either CIA components or apoproteins. Finally, GSH function was assigned to Atm1-dependent export, i.e. a step before GSH-dependent cGrxs function. Our findings extend the general model of eukaryotic Fe/S protein biogenesis by adding the molecular requirements for cytosolic [2Fe-2S] protein maturation.