bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of the Performance-Based Financing Project: An Observational Panel Study on Health Workers’ Output in Rural Mezam, Northwest Region, Cameroon
Authors: Dingana Therence Nwana , Azibo Balgah Roland , Ndisang Daniel Agwenig , Ngasa Stewart Ndutard , Fozeu Leo Fosso
Published: November 2024

Performance-Based Financing (PBF) has been implemented in many countries to improve healthcare access, quality, and outcomes while ensuring the efficient and equitable allocation of resources within the healthcare system. However, very little effort is visible in assessing its real impacts. This study evaluates the impact of the PBF project on health workers’ output and healthcare quality in the Mezam division in the North West region of Cameroon between 2012 and 2022. Specifically, the study aims to understand health workers’ perceptions of the PBF project, analyze the effect of PBF on health workers’ output, and examine the impact of PBF on healthcare quality. A structured questionnaire was used to generate panel data among healthcare workers in six beneficiary health districts in the study site. The perception scores were estimated based on the Net Promoter Score (NPS) methodology and variability tested using ANOVA. Health workers’ output and performance indicators were analyzed using the chi-square test, assessing the relation between PBF introduction and changes in health workers’ output, while healthcare quality metrics were analyzed using the Mann-Whitney U test to compare healthcare quality before and after PBF implementation. The results showed that health workers’ perceptions varied but were generally positive, with a Net Promoter Score (NPS) of approximately 48.25. PBF significantly boosted health workers’ output (p = 0.002) and healthcare quality (p < 0.05). It can be concluded that the PBF project in the Mezam division had positive effects on workers’ output and healthcare quality. Given the positive impacts, the study recommends scaling up PBF initiatives in Cameroon and other African countries with precarious health systems. Our study demonstrates the relevance of impact assessments in providing evidence for making informed decisions on efficient resource allocation in the health sector.
Evaluation of an artificial intelligence model for opportunistic calculation of Agatston score on non-gated computed tomography of the chest
Authors: McKinney Suzannah E , Mercaldo Sarah F , Chin John K , Ghatak Ankita , Halle Madeleine A , Hedgire Sandeep S , Meyersohn Nandini M , Ghoshhajra Brian , Dreyer Keith J , Kalra Mannudeep , Bizzo Bernardo C , Hillis James M
Published: November 2024

Importance

The Agatston score is a measure of cardiovascular disease traditionally calculated on cardiac gated computed tomography (CT) of the chest. Cardiac gated CT is resource-intensive, can be hard to access, and involves extra radiation exposure. Artificial intelligence (AI) can be used to opportunistically calculate Agatston score on non-gated CTs performed for other indications.

Objective

This study compared the accuracy of an AI model (Riverain Technologies ClearRead CT CAC) at calculating Agatston scores on non-gated CTs to both consensus radiologist interpretations on the same CTs and Agatston scores from paired cardiac gated CTs.

Design

A retrospective standalone performance assessment was conducted on a dataset of non-contrast CT chest cases acquired between January 2022 and December 2023.

Setting

The study was conducted at five hospitals in the United States.

Participants

The cohort included non-gated CTs from 491 patients. It was enriched to ensure a representation of disease severity by selecting approximately two-thirds of patients using the originally reported Agatston score on a paired cardiac gated CT within the study timeframe.

Main Outcome(s) and Measure(s)

The study compared the agreement of Agatston categories (0, 1-99, 100-399 and ≥400) between the AI model and ground truth radiologists or original radiology reports using the quadratic weighted Kappa coefficient.

Exposure(s)

Each non-gated CT case was interpreted independently by three radiologists to establish consensus interpretations. Each CT was then interpreted by the AI model. The Agatston scores for paired cardiac gated CTs were obtained from original radiology reports.

Results

The agreement between the AI model and ground truth radiologists was 0.959 (95% CI: 0.943-0.975). This result was broadly consistent across sex, age group, race, ethnicity and CT scanner manufacturer subgroups. The agreement between the AI model and paired cardiac gated CT was 0.906 (95% CI: 0.882-0.927).

Conclusions and Relevance

The assessed AI model accurately calculated Agatston scores on non-gated CTs and produced similar scores to paired cardiac gated CTs. Its use could broaden screening for atherosclerotic cardiovascular disease, enabling opportunistic screening on CTs captured for other indications.
RNA Polymerase II subunits overexpressions induce genome instability and deregulate transcription
Authors: Sadurni Martina Muste , Jones Megan Louise , Pavlou Lucas , Radi Mohamed , Kompocholi Smaragda , Passaretti Paolo , Gambus Agnieszka , Gregersen Lea H. , Saponaro Marco
Published: November 2024

Independently of the pathways or circuits deregulated in cancer cells, these present altered transcription patterns, often also direct consequence of deregulation of transcription factors. In this sense, also the RNA Polymerase complexes responsible for transcription can be affected in cancers. We find that upregulations of RNA Polymerase II subunits, especially the largest ones, correlates with poor cancer patients’ outcome across a range of tumor types, presenting increased genome instability. Overexpressing the subunits RPB1, RPB3 and RPB4 in cells we find that these induce DNA damage. However, the mechanisms behind this increased genome instability are specific for each subunit, linked to the unique transcription alterations generated by the subunit overexpression. Importantly, we find significant overlap between the genes with more DNA damage in our cell line models and those more affected in cancers with subunit upregulation, indicating that upregulations could be responsible for some of the phenotypes present in these patients.
Design of allosteric modulators that change GPCR G protein subtype selectivity
Authors: Moore Madelyn N. , Person Kelsey L. , Alwin Abigail , Krusemark Campbell , Foster Noah , Ray Caroline , Inoue Asuka , Jackson Michael R. , Sheedlo Michael J. , Barak Lawrence S. , Fernandez de Velasco Ezequiel Marron , Olson Steven H. , Slosky Lauren M.
Published: November 2024

G protein-coupled receptors (GPCRs), the largest family of drug targets, can signal through 16 subtypes of Gα proteins. Biased compounds that selectively activate therapy-relevant pathways promise to be safer, more effective medications. The determinants of bias are poorly understood, however, and rationally-designed, G protein-subtype-selective compounds are lacking. Here, using the prototypical class A GPCR neurotensin receptor 1 (NTSR1), we find that small molecules binding the intracellular GPCR-transducer interface change G protein coupling by subtype-specific and predictable mechanisms, enabling rational drug design. We demonstrate that the compound SBI-553 switches NTSR1 G protein preference by acting both as a molecular bumper and a molecular glue. Structurally, SBI-553 occludes G protein binding determinants on NTSR1, promoting association with select G protein subtypes for which an alternative, shallow-binding conformation is energetically favorable. Minor modifications to the SBI-553 scaffold produce allosteric modulators with distinct G protein subtype selectivity profiles. Selectivity profiles are probe-independent, conserved across species, and translate to differences inin vivoactivity. These studies demonstrate that G protein selectivity can be tailored with small changes to a single chemical scaffold targeting the receptor-transducer interface and, as this pocket is broadly conserved, present a strategy for pathway-selective drug discovery applicable to the diverse GPCR superfamily.
Defining the parameters for sorting of different RNA cargo into Extracellular vesicles
Authors: Abdelgawad Ahmed , Huang Yiyao , Gololobova Olesia , Yu Yanbao , Witwer Kenneth W. , Parashar Vijay , Batish Mona
Published: November 2024

Extracellular vesicles (EVs) are small particles that are released by cells and mediate cell-cell communication by transferring bioactive molecules. RNA cargo of EVs, including coding and non-coding RNAs, can change the behavior of recipient cells, affecting processes like gene expression, proliferation, and apoptosis. Circular RNAs (CircRNA) are a newly appreciated class of regulatory RNAs that are stable, resistant to degradation and have been shown to be enriched in EVs. They play key roles in gene regulation and are also emerging as promising biomarkers for disease diagnosis. While microRNAs (miRNAs) are the most well studied RNA cargo of EVs, very little is known about the mechanisms of enrichment of circRNAs as well as long linear RNAs. Here, we take a comprehensive genome-wide approach to investigate the role of GC%, size, exon count, structuredness and coding potential, in the sorting and enrichment of circular and long linear RNAs into EVs. We found that size and structuredness had a significant role in enriching RNAs into EVs which was consistent across all classes of RNAs. Furthermore, we found that structuredness could explain the relative enrichment of circRNAs over their linear counterparts. These results were validated on existing public databases of circular and linear RNAs in EVs. By identifying and analyzing these factors, we aim to better understand the complex mechanisms behind EV-mediated RNA transfer and its impact on cell communication in both health and disease. This mechanistic understanding of RNA enrichment in EVs is crucial for engineering EVs with selective RNA cargo.
Green Elegance T2T: An upgraded telomere-to-telomere genome assembly and annotation of looseleaf lettuce (Lactuca sativavar.crispa)
Authors: Zhang Bin , Liu Xue , Ding Haifeng , Yang Yesheng , Tang Jinfu , Li Dayong
Published: November 2024

Lettuce (Lactuca sativaL.), a globally important vegetable crop, is cultivated in various horticultural varieties. Looseleaf lettuce is one of the main varieties that are consumed. Here, we report a telomere-to-telomere (T2T) genome assembly of looseleaf lettuce (L. sativavar.crispacv. Green Elegance). By combining the sequencing data of previously reported Green Elegance v1.2, the 42.20 Gb clean ultra-long reads produced by Oxford Nanopore Technology were used to close the gaps and upgrade the genome assembly. After filling 11 gaps in Green Elegance v1.2, the final gapless telomere-to-telomere genome assembly is 2.58 Gb in length with a contig N50 of 282.47 Mb, containing nine centromeres and 18 telomeres. The genome contained 41,375 protein-coding genes, of which 99.10% were functionally annotated. This T2T genome of looseleaf lettuce will be valuable for the identification of genetic variation and the advancement of lettuce breeding.
Broca’s area responsible for speech production is regulated by lung functions
Authors: Cao Siyu , Zhuang Wenwen , Hu Yuqian , Qiu Shijun , Tan Li-Hai
Published: November 2024

For more than one and a half centuries, Broca’s area, specifically, the pars opercularis and pars triangularis in the left inferior frontal gyrus, has been known to be crucial for human speech production. However, it remains unanswered why this region is recruited for speaking. Speech production involves not only conceptualization and motor planning, but also respiration that provides the airflow necessary for creating sounds. Thus, the role of Broca’s area in speech may be shaped by the functionality and the related brain regions associated with lungs. To test this hypothesis, we recruited the patients suffering from chronic obstructive pulmonary disease (COPD) and required them to speak out words while scanning their brains with functional and quantitative magnetic resonance imaging (fMRI and qMRI). We observed that COPD patients exhibited altered cortical responses in left inferior prefrontal cortex and other regions during speech tasks, with abnormal activation in cortical sites associated with breathing. In addition, using the qMRI to generate longitudinal relaxation time (T1) maps as an index of brain microstructural changes including dendritic maturation and myelination, we discovered that the patients showed significantly higher T1values than the control group in Broca’s area, suggesting reduced myelination and impaired microstructural integrity. Crucially, the data indicated that more severe dyspnea was associated with less well-developed microstructure in Broca’s area and its weaker activation. Our study has demonstrated for the first time that lungs may function to shape Broca’s area as the speaking center, and this is consistent with the recent work of a lung–brain axis.
SPO11 dimerization controls meiotic DNA double-strand break formation
Authors: Oger Cédric , Claeys Bouuaert Corentin
Published: November 2024

SPO11 initiates meiotic recombination through the induction of programmed DNA double-strand breaks (DSBs), but this catalytic activity had never been reconstitutedin vitro. Here, usingMus musculusSPO11, we report a biochemical system that recapitulates all the hallmarks of meiotic DSB formation. We show that SPO11 catalyzes break formation in the absence of any partners and remains covalently attached to the 5′ broken strands. We find that target site selection by SPO11 is influenced by the sequence, bendability and topology of the DNA substrate, and provide evidence that SPO11 can reseal single-strand DNA breaks. In addition, we show that SPO11 is monomeric in solution and that cleavage requires dimerization to reconstitute two hybrid active sites. SPO11 and its partner TOP6BL form a 1:1 complex that catalyzes DNA cleavage with a similar activity to SPO11 alone. However, the complex binds DNA ends with higher affinity, suggesting a potential role post-cleavage. We propose a model where additional partners of SPO11 required for DSB formationin vivoassemble biomolecular condensates that recruit SPO11-TOP6BL, enabling dimerization and cleavage. Our work establishes SPO11 dimerization as the fundamental mechanism that controls the induction of meiotic DSBs.
Unveiling the functional heterogeneity of endogenous tissue extracellular vesicles in skeletal muscle through multi-omics
Authors: Wang Yizhuo , Lou Peng , Zhou Xiyue , Xie Yijing , Zhang Yimeng , Liu Shuyun , Li Lan , Lu Yanrong , Wan Meihua , Cheng Jingqiu , Liu Jingping
Published: November 2024

Extracellular vesicles (EVs) have emerged as promising tools for the development of disease biomarkers and therapeutics because they can transfer various bioactive cargos between cellsin vivo. A better understanding of the heterogeneous properties of EVsin vivomay provide insights into their biological roles and clinical translation potential. As a proof-of-concept, we report that different EV subpopulations from skeletal muscle tissues have distinct composition signatures and diverse biological effects on recipient cells. Multiple cell types (e.g., myoblasts and endothelial cells (ECs)) can contribute to the pool of muscle tissue-derived EVs, and large EVs (L-EVs) are enriched with proteins related to metabolic regulation, whereas small EVs (S-EVs) are enriched with original muscle cell-specific proteins related to muscle function regulation. Compared with L-EVs, S-EVs exhibited abundant surface proteins and higher cell uptake rates. Moreover, L-EVs and S-EVs can induce diverse changes in global gene expression, metabolic patterns and some cellular behaviors (e.g., proliferation and differentiation) in recipient cells. These results suggest that different EV subpopulations might control tissue hemostasis in a coordinated manner and suggest the importance of reconsidering their favorable role in future applications (e.g., S-EVs for biomarker discovery and L-EVs for metabolic intervention). This study highlights the functional heterogeneity of tissue-derived EVsin vivo, and the selection of an ideal EV subset on the basis of its specific biological properties may be a promising strategy for developing more precise biomarkers or tailored EV therapies for regenerative medicine.

Graphic abstract

Significance

Extracellular vesicles (EVs) are emerging as important tools for diagnostics, therapeutics, and prognostics in various diseases. Understanding the inherent heterogeneity of EVs is crucial, as distinct subpopulations function differently. While extensive research focuses on EVs derived from cell supernatants, endogenous tissue EVs can more accurately reflect the pathophysiological characteristics of their originating cells. Here, we propose different tissue-EV subpopulations coordinately regulate tissue homeostasis. Small EVs with tissue-specific signatures show promise for biomarker development, while large EVs with metabolic signatures are suitable for metabolic interventions. Additionally, small EVs with enhanced surface proteins are ideal for targeted delivery. This work highlights the importance of selecting tissue-EV subpopulations based on their unique properties for developing precise biomarkers and tailored therapies in regenerative medicine.
Mechano-sensing role of oncogenic lncRNA NEAT1 on soft vs. stiff substrates and its implications for glioblastoma progression
Authors: Ghosh Arpita , Soundharya R. , Jolly Mohit Kumar , Majumder Abhijit
Published: November 2024

Long non-coding RNAs (lncRNAs) have gained increasing recognition as key regulators of cancer biology, overturning their earlier classification as non-functional genomic elements. Among them, NEAT1 (Nuclear-Enriched Abundant Transcript 1) has emerged as a prominent oncogenic lncRNA involved in multiple solid tumors, including liver, prostate, and gastric cancers, as well as gliomas. Although the role of NEAT1 in cancer has been extensively studied, most of these investigations have focused on biochemical factors, leaving the mechano-sensitivity of NEAT1 to mechanical alterations in the tumor microenvironment (TME) largely unexplored. As tumors progress, the TME undergoes significant mechanical changes, particularly extracellular matrix (ECM) stiffening, which modulates cellular behavior through mechano-transduction pathways. While much research has focused on how these mechanical cues influence protein-coding gene expression, their impact on lncRNAs such as NEAT1 remains understudied. This study aims to address this gap by investigating the mechano-sensitivity of NEAT1 in glioblastoma (GBM) cells cultured on polyacrylamide (PAA) gels that mimic the brain’s physiological stiffness (0.5 kPa) versus conventional, stiff tissue culture plastic (TCP). NEAT1 expression, quantified using qRT-PCR, revealed a significant increase on softer, brain-mimicking substrates compared to stiffer TCP. Overexpression of NEAT1 in brain-mimicking stiffness also showed higher expression levels of cancer progression markers, quantified by qRT-PCR. To further explore NEAT1’s role in oncogenesis due to its mechano-sensing capabilities, siRNA-mediated downregulation of NEAT1 in GBM cells cultured on soft PAA gels was performed to reduce NEAT1 levels to those comparable to TCP. The results showed reduced cancer aggressiveness, characterized by decreased expression of invasion, stemness, and epithelial-mesenchymal transition (EMT) markers, further supported by migration and invasion assays. These findings highlight NEAT1 as a mechanosensitive regulator in response to substrate stiffness, underscoring its role in tumor progression.
Chemostat culturing reduces fecal eukaryotic virus load and delays diarrhea after virome transplantation
Authors: Offersen Simone Margaard , Adamberg Signe , Spiegelhauer Malene Roed , Mao Xiaotian , Rasmussen Torben Sølbeck , Larsen Frej , Zhong Jingren , Nguyen Duc Ninh , Nielsen Dennis Sandris , Aunsholt Lise , Thymann Thomas , Adamberg Kaarel , Brunse Anders
Published: November 2024

Fecal virome transfer (FVT) shows promise in reducing necrotizing enterocolitis (NEC), likely due to donor bacteriophages preventing the gut dysbiosis preceding disease. However, concurrent transfer of eukaryotic viruses may carry a risk of infection for the recipient. To increase safety, we investigated chemostat propagation as a method to eliminate eukaryotic viruses from donor feces while maintaining a diverse and reproducible bacteriophage community. Donor feces was collected from healthy suckling piglets and inoculated into a fermenter containing growth media supplemented with lactose and milk oligosaccharides (MOs). During continuous medium exchange (20% volume/h), dilution significantly reduced eukaryotic viruses. Viral richness was concurrently reduced although still preserving a stable community of 200-250 bacteriophages. Inclusion of MOs in the medium ensured higher bacterial richness and a bacterial community closer resembling donor feces. FecalLactobacillaceaebacteria were lost during cultivation but partially replaced by members of theBacteroidotaphylum in MO-supplemented cultures, accompanied by phages predicted to haveParabacteroidesas host. After cultivation, virus-like particles (VLPs) were isolated, and their ability to reduce NEC incidence testedin vivo. Preterm piglets were delivered by cesarean section and received either the lactose- or MO-propagated viromes by oral route (n= 14-15/group). These were compared with groups receiving the same dose of donor fecal virome (1010VLPs/kg) or vehicle control. The piglets were subsequently fed infant formula for 96 hours followed by euthanasia and tissue sampling. Both chemostat-propagated viromes effectively mitigated diarrhea compared to the donor virome. The donor virome partially engrafted in recipients and led to higher levels ofLactobacillaceaebacteria andLactobacillaceaetargeting phages. However, these signatures were lost in recipients of chemostat-propagated viromes, and only minor microbiome effects and no NEC prevention were observed. To conclude, we providein vivoproof-of-concept for chemostat propagation of fecal viruses as a means to deplete eukaryotic viruses and in turn reduce side effects in newborn virome recipients. However, chemostat culture conditions need further optimization to preserve the donor phageome.
Anillin tunes contractility and regulates barrier function during Rho flare-mediated tight junction remodeling
Authors: Craig Zie , Arnold Torey R. , Walworth Kelsey , Walkon Alexander , Miller Ann L.
Published: November 2024

To preserve barrier function, cell-cell junctions must dynamically remodel during cell shape changes. We have previously described a rapid tight junction repair pathway characterized by local, transient activation of RhoA, termed ‘Rho flares,’ which repair leaks in tight junctions via promoting local actomyosin-mediated junction remodeling. In this pathway, junction elongation is a mechanical trigger that initiates RhoA activation through an influx of intracellular calcium and recruitment of p115RhoGEF. However, mechanisms that tune the level of RhoA activation and Myosin II contractility during the process remain uncharacterized. Here, we show that the scaffolding protein Anillin localizes to Rho flares and regulates RhoA activity and actomyosin contraction at flares. Knocking down Anillin results in Rho flares with increased intensity but shorter duration. These changes in active RhoA dynamics weaken downstream F-actin and Myosin II accumulation at the site of Rho flares, resulting in decreased junction contraction. Consequently, tight junction breaks are not reinforced following Rho flares. We show that Anillin-driven RhoA regulation is necessary for successfully repairing tight junction leaks and protecting junctions from repeated barrier damage. Together, these results uncover a novel regulatory role for Anillin during tight junction repair and barrier function maintenance.

Significance Statement

Barrier function is critical for epithelial tissues. Epithelial cells maintain barrier function via tight junctions, which must be remodeled to allow for cell- and tissue-scale shape changes. How barrier function is maintained and remodeled as epithelial cells change shape remains unclear.

The scaffolding protein Anillin is required for generating effective actomyosin contraction to reinforce damaged tight junctions; lack of reinforcement leads to repeated barrier leaks.

These findings highlight a novel role for Anillin in tight junction remodeling and suggest that Anillin’s ability to tune the level and duration of local Rho activation affects the contractile output.
AI-directed voxel extraction and volume EM identify intrusions as sites of mitochondrial contact
Authors: Padman Benjamin S. , Lindblom Runa , Lazarou Michael
Published: November 2024

Membrane contact sites (MCS) establish organelle interactomes in cells to enable communication and exchange of materials. Volume electron microscopy (vEM) is ideally suited for MCS analyses, but semantic segmentation of large vEM datasets remains challenging. Recent adoption of artificial intelligence (AI) for segmentation has greatly enhanced our analysis capabilities. However, we show that organelle boundaries, which are important for defining MCS, are the least confident predictions made by AI. We outline a segmentation strategy termed AI-directed Voxel Extraction (AIVE), that combines AI predictions with image electron signals to confidently segment membrane boundaries irrespective of the AI model used. We demonstrate the precision conferred by AIVE by applying it to the quantitative analysis of organelle interactomes from multiple FIB-SEM datasets. Through AIVE, we discover a previously unknown category of mitochondrial contact that we term the mitochondrial intrusion. We hypothesise that intrusions serve as anchors that stabilize MCS and promote organelle communication.
ConvCGP: A Convolutional Neural Network to Predict Genotypic Values of Rice Traits from Compressed Genome-Wide Polymorphisms
Authors: Islam Tanzila , Hae Kim Chyon , Shimono Hiroyuki , Kimura Akio , Iwata Hiroyoshi
Published: November 2024

The growing size of genome-wide polymorphism data in animal and plant breeding has raised concerns regarding computational load and time, particularly when predicting genotypic values for target traits using genomic prediction. Although several deep learning and conventional methods, including dimensionality reduction techniques, such as principal component analysis (PCA) and autoencoders, have been proposed to address these challenges by selecting subsets of polymorphisms or compressing high-dimensional data for predictive analysis. However, these methods are often computationally intensive and time-consuming. A major challenge in applying high-dimensional genomic data directly to deep-learning models is the substantial computational cost and time required for hyperparameter tuning and model training. To address these limitations, we propose a novel deep learning approach that combines convolutional neural networks (CNNs) to predict the genotypic data of target traits with autoencoders to compress high-dimensional genome-wide polymorphism data. We tested this framework on high-dimensional rice datasets, focusing on agronomic trait prediction. By combining CNNs with autoencoders, our framework outperformed other machine-learning methods and recently proposed compression methods, demonstrating its potential to efficiently address the computational challenges associated with high-dimensional genomic data.
A composite subunit vaccine confers full protection against Buruli ulcer disease in the mouse footpad model ofMycobacterium ulceransinfection
Authors: Boakye-Appiah Justice Kofi , Tran Andy C. , Paul Matthew J. , Hart Peter , Phillips Richard O. , Harrison Thomas S. , Wansbrough-Jones Mark , Reljic Rajko
Published: November 2024

Buruli ulcer (BU) disease, a neglected necrotizing tropical skin infection caused byMycobacterium ulcerans, is the third most common mycobacterial disease after tuberculosis and leprosy. Infections mostly occur in remote, rural areas of Central and West Africa, but also in Australia, Japan and Papua New Guinea. There is currently no vaccine against Buruli ulcer disease and all previous attempts using closely related bacteria and subunit proteins have been partially successful only.

Here, we tested in mice a composite subunit formulation incorporating theMycobacterium ulceranstoxin mycolactone as the immunomodulator, and the antigens Ag85A and Polyketide Synthase Enzyme Ketoreductase A (KRA), formulated with Quil-A adjuvant (‘Burulivac’). Burulivac induced Ag85A and KRA antigen-specific antibodies, T cells and a mixed pro- and anti-inflammatory cytokine responses, which conferred absolute protection against Buruli ulcer disease in the mouse footpad model over a 14-week period of observation. This was superior to both live attenuated mycobacterial vaccines, that is, BCG and an avirulentM. ulceransstrain that lacks the mycolactone toxin (MuΔ). Interleukin 10 was found to be strongly associated with protection. We suggest that Burulivac is a promising vaccine candidate against Buruli ulcer disease that warrants further exploration.

Author summary

Buruli ulcer is a neglected tropical disease caused by skin infections byMycobacterium ulcerans, an organism related to causative pathogens of tuberculosis and leprosy. The disease is endemic to parts of Central and West Africa but is also found in Australia, Japan and some other countries. While mortality is low, morbidity caused by extensive and unsightly ulceration of the skin is high. There currently is no vaccine against Buruli ulcer and all previous attempts to develop one have been unsuccessful.

Here we developed a vaccine formulation termed ‘Burulivac’ that incorporates threeM. ulceransantigens, two of which are proteins and the third the mycolactone toxin, much responsible for the pathology of the BU disease. Our rationale was that in a vaccine setting and using a controlled dose of the toxin, we could calibrate the immune responses to selected antigens, so that they mimic those induced during natural infection. Using an experimental mouse footpad model of infection, we demonstrate that immunisation with Burulivac completely prevented ulceration in the mouse footpad over an extended 14-weeks period of observation, and that this correlated with elevated levels of anti-inflammatory cytokine Interleukin-10. We propose that Burulivac is a promising vaccine candidate that merits further testing and development.
Identification of transcriptome-wide cobalt chloride-induced hypoxia-responsive long noncoding RNAs regulated by cytoplasmic mRNA capping enzyme
Authors: Ghosh Pinaki , Islam Safirul , Mukherjee Chandrama
Published: November 2024

Long non-coding RNAs (lncRNAs) are key regulators of gene expression in human cancers, influencing tumor microenvironment (TME). Hypoxia, a hallmark of solid tumors, elevates hypoxia-inducible factor 1α (HIF-1α), which regulates hypoxia-responsive lncRNAs (HRLs). These HRLs are essential in regulating gene expression under hypoxic conditions at both transcriptional and post-transcriptional levels. However, the mechanisms governing the post-transcriptional regulation of lncRNAs are not fully understood. It has been shown that the cytoplasmic pool of mRNA capping enzyme (cCE) can post-transcriptionally regulate its substrate uncapped mRNAs and lncRNAs in the cytoplasm, thereby preventing their degradation. Our previous study showed elevated expression of cCE under hypoxic conditions. This study aimed to determine whether cCE influences the transcriptome-wide HRLs in CoCl2-induced hypoxia in osteosarcoma U2OS cells. We identified 306 known lncRNAs with significant differential expression under hypoxic conditions, including 137 upregulated and 169 downregulated by RNA sequencing. Gene Ontology enrichment analysis revealed their distinct association with various cancers. Our investigation aimed to ascertain whether the cCE post-transcriptionally regulates these HRLs. Overexpression of a dominant negative form of cCE suggested cCE might post-transcriptionally regulate these HRLs. Future research should focus on understanding how cCE influences substrate HRLs, which play a crucial role in the bidirectional signaling circuit between TME and cancer cells under hypoxic stress as well as establishing cCE as a key factor that may alter cellular responses to hypoxia by stabilizing cCE-targeted lncRNAs.
Identifying spatially variable genes by projecting to morphologically relevant curves
Authors: Nicol Phillip B. , Ma Rong , Xu Rosalind J. , Moffitt Jeffrey R. , Irizarry Rafael A.
Published: November 2024

Spatial transcriptomics enables high-resolution gene expression measurements while preserving the two-dimensional spatial organization of the sample. A common objective in spatial transcriptomics data analysis is to identify spatially variable genes within predefined cell types or regions within the tissue. However, these regions are often implicitly one-dimensional, making standard two-dimensional coordinate-based methods less effective as they overlook the underlying tissue organization. Here we introduce a methodology grounded in spectral graph theory to elucidate a one-dimensional curve that effectively approximates the spatial coordinates of the examined sample. This curve is then used to establish a new coordinate system that better reflects tissue morphology. We then develop a generalized additive model (GAM) to detect genes with variable expression in the newmorphologically relevantcoordinate system. Our approach directly models gene counts, thereby eliminating the need for normalization or transformations to satisfy normality assumptions. We demonstrate improved performance relative to current methods based on hypothesis testing, while also accurately estimating gene expression patterns and precisely identifying spatial loci where deviations from constant expression are observed. We validate our approach through extensive simulations and by analyzing experimental data from multiple platforms such as Slide-seq and MERFISH.
Spatial organization of mediated-macrophage chemoprotective niches in solid tumors: A mathematical analysis
Authors: Dangelser William , Stéphanou Angélique , Millet Arnaud
Published: November 2024

Acquired resistance is one of the major causes of failure of standard therapies in cancer patients. Chemotherapeutic agents are still widely used and the understanding of the mechanisms leading to secondary resistance to these molecules are still puzzling. Recently, the role of the tumor immune microenvironment has been recognized. Among the cells potentially involved, macrophages seem to be the perfect culprits. In a previous work, we have shown that hypoxic macrophages are able to provide strong protection against 5-fluorouracil, a first-line chemotherapeutic agent in digestive cancers. In the present work, we use mathematical modeling to explore the spatiotemporal aspects of the treatment-induced organization of the tumor environment. Based on analytical and numerical analysis, we propose that macrophage-driven protection against chemotherapy under treatment does not rely solely on biochemical degradation, but is enhanced by the emergence of spatially structured chemotherapeutic protective niches. This work paves the way for the development of new therapeutic strategies that rely on targeting the spatial organization of tumors as a way to control treatment resistance.
Conserved moiety fluxomics
Authors: Fleming Ronan M.T. , Haraldsdottir Hulda S. , Preciat German , Huang Luojiao , Thiele Ines , Harms Amy , Hankemeier Thomas
Published: November 2024

Fluxomics seeks to infer reaction fluxes at genome-scale by introducing isotopically labelled metabolites into a living system and measuring the enrichment of isotopic tracers in downstream metabolites. This approach has the potential to quantify fluxes at genome-scale but current approaches to infer steady-state metabolic reaction fluxes are either not tractable or not efficient at genome-scale as the corresponding computational models are high-dimensional, involve nonlinear constraints and lack mathematical guarantees of convergence to a global optimum. Herein, we introduce conserved moiety fluxomics, which is a novel, efficient, mathematically transparent, and computationally efficient method to infer metabolic reaction flux at genome-scale. We demonstrate how identification of the set of conserved moieties for a given metabolic network leads to a novel moiety graph decomposition of a stoichiometric matrix that can be used to linearly relate metabolic reaction fluxes to the rate at which conserved moieties transition between metabolites. This linear formulation avoids combinatorial explosion because the number of conserved moieties is bounded, most reactions correspond to a small number of conserved moiety transitions, it is sufficient to represent the flow of moieties that have the potential to be labelled, and it is sufficient to represent constraints from those isotopologues that are actually measured. A non-linear yet strictly convex objective is used to ensure that inferred fluxes satisfy energy conservation and the second law of thermodynamics. Numerical results demonstrate the computational tractability of conserved moiety fluxomics at genome-scale, given liquid chromatography-mass spectrometry derived stationary mass isotopologue distribution data from an in vitro dopaminergic neuronal culture fed13Clabelled glucose. Conserved moiety fluxomics unites the strengths of constraint-based modelling and metabolic flux analysis and has the potential to be further enhanced to enable inference of fluxes in whole-body metabolic models, including from non-stationary isotopic labelling data.
Self-organized cell patterning via mechanical feedback in hindbrain neuropore morphogenesis
Authors: Pérez-Verdugo Fernanda , Maniou Eirini , Galea Gabriel L. , Banerjee Shiladitya
Published: November 2024

Cell patterning is essential for organized tissue development, enabling precise geometric arrangement of cells, body axis establishment and developmental timing. Here we investigate the role of physical forces and mechanical cues in organizing and maintaining cell morphological patterns during hindbrain neuropore closure, a critical morphogenetic event in vertebrate development. Through live-imaging in mouse embryos and cell-based biophysical modeling, we demonstrate that active cell crawling and actomyosin purse-string contraction at the neuropore border are insufficient to account for the observed cellular arrangements in space and time. Instead, mechanosensitive feedback between cellular stress, shape, and nematic alignment is required to establish and maintain cell morphological patterns and their spatial order. This feedback-driven model generates persistent shape memory in cells, stalls cell rearrangements, and promotes local tissue solidification to preserve the spatial organization during the closure process. We validate this model experimentally, establishing the critical role of mechanical feedback in guiding tissue-level morphogenesis through active, force-driven patterning.
Full quantum determination of the quasiequilibrium constant involved in the formation of ozone
Authors: Guillon G. , Honvault P.
Published: November 2024

Forty years ago, measurements of enrichments in O18 in stratospheric ozone O3 revealed a value significantly greater than statistically expected and roughly equal in heavy isotopes O17 and O18. Despite numerous experimental and theoretical studies, this mass-independent fractionation (MIF) still remains unexplained. However, it is now accepted that its origin comes from isotopic effects found in the recombination reaction O+O2+M→O3 + M where M is a stabilizer, even if the theoretical origin of the isotope effects found in this reaction is still not known. Here we study the first of the two steps involved in this reaction, namely, the rapid quasiequilibrium O+O2 ⇌ O3* process where O3* is metastable ozone. The quasiequilibrium constant for this process is obtained from a full quantum dynamical approach. These high-level calculations yield the most accurate value of this quantity to date for O348 and O350. These reference results constitute a crucial stage for a better understanding of the ozone formation reaction, and could therefore help to unravel the mystery of MIF.

Published by the American Physical Society
2024
Impact of electron correlations on two-particle charge response in electron- and hole-doped cuprates
Authors: Nag Abhishek , Zinni Luciano , Choi Jaewon , Li J. , Tu Sijia , Walters A. C. , Agrestini S. , Hayden S. M. , Bejas Matías , Lin Zefeng , Yamase H. , Jin Kui , García-Fernández M. , Fink J. , Greco Andrés , Zhou Ke-Jin
Published: November 2024

Estimating many-body effects that deviate from an independent particle approach has long been a key research interest in condensed matter physics. Layered cuprates are prototypical systems, where electron-electron interactions are found to strongly affect the dynamics of single-particle excitations. It is, however, still unclear how the electron correlations influence charge excitations, such as plasmons, which have been variously treated with either weak or strong correlation models. In this work, we demonstrate the hybridized nature of collective valence charge fluctuations leading to dispersing acoustic-like plasmons in hole-doped La1.84Sr0.16CuO4 and electron-doped La1.84Ce0.16CuO4 using the two-particle probe, resonant inelastic x-ray scattering. We then describe the plasmon dispersions in both systems, within both the weak-coupling mean-field random phase approximation (RPA) and strong-coupling t−J−V model in a large-N scheme. The t−J−V model, which includes the correlation effects implicitly, accurately describes the plasmon dispersions as resonant excitations outside the single-particle intraband continuum. In comparison, a quantitative description of the plasmon dispersion in the RPA approach is obtained only upon explicit consideration of renormalized electronic band parameters. Our comparative analysis shows that electron correlations significantly impact the low-energy plasmon excitations across the cuprate doping phase diagram, even at long wavelengths. Thus, complementary information on the evolution of electron correlations, influenced by the rich electronic phases in condensed matter systems, can be extracted through the study of two-particle charge response.

Published by the American Physical Society
2024
Combined first-principles and Boltzmann transport theory methodology for studying magnetotransport in magnetic materials
Authors: Liu Zhihao , Zhang Shengnan , Fang Zhong , Weng Hongming , Wu Quansheng
Published: November 2024

Unusual magnetotransport behaviors, such as temperature-dependent negative magnetoresistance (MR) and bowtie-shaped MR, have puzzled us for a long time. Although several mechanisms have been proposed to explain these phenomena, the absence of comprehensive quantitative calculations has made these explanations less convincing. In our work, we introduce a methodology to study magnetotransport behaviors in magnetic materials. This approach integrates the anomalous Hall conductivity induced by the Berry curvature, with a multiband ordinary conductivity tensor, employing a combination of first-principles calculations and semiclassical Boltzmann transport theory. Our method also incorporates the temperature dependence of the relaxation time and the anomalous Hall conductivity, as well as the field dependence of the anomalous Hall conductivity. We initially test this approach on models, obtaining distinct behaviors of magnetoresistance and Hall resistivity across several types of magnetic materials, and then apply it to a Weyl semimetal Co3Sn2S2. The results, which align well with experimental observations in terms of magnetic field and temperature dependencies, demonstrate the efficacy of our approach. This methodology provides a comprehensive and efficient means to understand the underlying mechanisms of the unusual complex behaviors observed in magnetotransport measurements in magnetic materials.

Published by the American Physical Society
2024
Collective quantum stochastic resonance in Rydberg atoms
Authors: Li Haowei , Sun Konghao , Yi Wei
Published: November 2024

We study the collective response of a group of dissipative Rydberg atoms to a periodic modulation of the Rydberg excitation laser. Focusing on the emergent collective-jump dynamics, where the system stochastically switches between states with distinct Rydberg excitations, we show that the counting statistics of the state switching is qualitatively changed by the periodic drive. The impact is most prominent when the driving frequency is comparable to the emergent collective-jump rate, as the jumps tend to synchronize with the external drive, and their counting statistics exhibits a series of suppressed subharmonics of the driving frequency. These phenomena are manifestations of a novel type of stochastic resonance, where a cooperative collective state switching is facilitated by quantum fluctuations in a many-body open system. Such a collective quantum stochastic resonance further leads to an enhanced signal-to-noise ratio in the power spectrum of the Rydberg excitations, for which the synchronized collective jumps are viewed as the output signal. We confirm the many-body quantum nature of the resonance by devising a cluster model, under which the role of many-body correlations is analyzed by changing the size of the atom clusters.

Published by the American Physical Society
2024
Understanding strategies employed by seniors in identifying deepfakes
Authors: Tang Zhong , Goh Dion Hoe-Lian , Lee Chei Sian , Yang Yihao
Published: November 2024

Purpose

This paper aims to confront the rising threat of deepfake videos, focusing on the limited research on deepfake detection strategies among seniors. The study thus investigates seniors’ video credibility conceptualizations and identifies their deepfake detection strategies.

Design/methodology/approach

This study employed semi-structured interviews with 20 seniors aged 55 to 70. Areas covered include their perceptions of video information credibility and identification strategies undertaken. Qualitative content analysis was conducted to interpret interview responses.

Findings

Seniors emphasized the importance of objectivity, trustworthiness, believability, reliability and truthfulness in terms of video credibility. Regarding strategies for assessing video credibility, seniors employed five categories: character appearance, non-human visuals, audio, personal knowledge and external sources.

Originality/value

This study contributes to the literature on human-oriented deepfake detection strategies by uncovering diverse methods employed by seniors. It enhances the understanding of how individuals assess video credibility in the context of deepfakes. Furthermore, this study offers practical and applicable strategies for real-world deepfake detection.