bluuebunny/crossref_metadata_2025 huggingface dataset:
Emergence of cooperation in the one-shot Prisoner’s dilemma through Discriminatory and Samaritan AIs
Authors: Zimmaro Filippo , Miranda Manuel , Fernández José María Ramos , Moreno López Jesús A. , Reddel Max , Widler Valeria , Antonioni Alberto , Han The Anh
Published: September 2024

As artificial intelligence (AI) systems are increasingly embedded in our lives, their presence leads to interactions that shape our behaviour, decision-making and social interactions. Existing theoretical research on the emergence and stability of cooperation, particularly in the context of social dilemmas, has primarily focused on human-to-human interactions, overlooking the unique dynamics triggered by the presence of AI. Resorting to methods from evolutionary game theory, we study how different forms of AI can influence cooperation in a population of human-like agents playing the one-shot Prisoner’s dilemma game. We found that Samaritan AI agents who help everyone unconditionally, including defectors, can promote higher levels of cooperation in humans than Discriminatory AI that only helps those considered worthy/cooperative, especially in slow-moving societies where change based on payoff difference is moderate (small intensities of selection). Only in fast-moving societies (high intensities of selection), Discriminatory AIs promote higher levels of cooperation than Samaritan AIs. Furthermore, when it is possible to identify whether a co-player is a human or an AI, we found that cooperation is enhanced when human-like agents disregard AI performance. Our findings provide novel insights into the design and implementation of context-dependent AI systems for addressing social dilemmas.
Arterial spin labelling perfusion MRI analysis for the Human Connectome Project Lifespan Ageing and Development studies
Authors: Kirk Thomas F. , Kennedy McConnell Flora A. , Toner Jack , Craig Martin S. , Carone Davide , Li Xiufeng , Suzuki Yuriko , Coalson Timothy S. , Harms Michael P. , Glasser Matthew F. , Chappell Michael A.
Published: September 2024

The Human Connectome Project Lifespan studies cover the Development (5-21) and Aging (36-100+) phases of life. Arterial spin labelling (ASL) was included in the imaging protocol, resulting in one of the largest datasets collected to-date of high spatial resolution multiple delay ASL covering 3,000 subjects. The HCP-ASL minimal processing pipeline was developed specifically for this dataset to pre-process the image data and produce perfusion estimates in both volumetric and surface template space. Applied to the whole dataset, the outputs of the pipeline revealed significant and expected differences in perfusion between the Development and Ageing cohorts. Visual inspection of the group average surface maps showed that cortical perfusion often followed cortical areal boundaries, suggesting differential regulation of cerebral perfusion within brain areas at rest. Group average maps of arterial transit time also showed differential transit times in core and watershed areas of the cerebral cortex, which are useful for interpreting haemodynamics of functional MRI images. The pre-processed dataset will provide a valuable resource for understanding haemodynamics across the human lifespan.
Constitutive expression of IκBζ promotes tumor growth and immunotherapy resistance in melanoma
Authors: Kolb Antonia , Kulis-Mandic Ana-Marija , Klein Matthias , Stastny Anna , Haist Maximilian , Weidenthaler-Barth Beate , Sinnberg Tobias , Sucker Antje , Allies Gabriele , Albrecht Lea Jessica , Tasdogan Alpaslan , Tuettenberg Andrea , Stege Henner , Schadendorf Dirk , Grabbe Stephan , Schulze-Osthoff Klaus , Kramer Daniela
Published: September 2024

Background

IκBζ, a rather unknown co-regulator of NF-κB, is mostly inducibly expressed and can either activate or repress a specific subset of NF-κB target genes. While its role as a transcriptional regulator of various cytokines and chemokines in immune cells has been revealed, IκBζ’s function in solid cancer remains unclear.

Methods

We investigated IκBζ expression in melanoma, and assessed its impact on target gene expression, tumor growth, and response to immunotherapy in melanoma cell lines, mouse models, and patient samples.

Results

Unlike in other cell types, IκBζ protein was found to be constitutively expressed in a subfraction of melanoma cell lines, and around 35% of melanoma cases. This atypical expression pattern of IκBζ did not correlate with its mRNA levels or known driver mutations, but instead seemed to result from changes in its post-transcriptional or post-translational regulation. Deleting constitutively expressed IκBζ abrogated the activity and chromatin association of STAT3 and p65, leading to reduced expression of the pro-proliferative cytokines IL-1β and IL-6 in melanoma cells. Consequently, loss of tumor-derived IκBζ suppressed self-sustained melanoma cell growth bothin vitroandin vivo. Additionally, constitutive IκBζ expression suppressed the induction of the chemokinesCXCL9,CXCL10, andCCL5, which impaired the recruitment of NK and CD8+T-cells to the tumor, causing resistance to α-PD-1 immunotherapy in mice. Furthermore, the expression of tumor-derived IκBζ also correlated with the absence of CD8+T-cells in human melanoma samples and progressive disease during immunotherapy.

Conclusion

We propose that tumor-derived IκBζ could serve as a new therapeutic target and prognostic marker that characterizes melanoma with high tumor cell proliferation, cytotoxic T- and NK-cell exclusion, and unfavorable immunotherapy responses. Targeting IκBζ expression might open up a new therapy option to re-establish the recruitment of cytotoxic cells, thereby resensitizing for immunotherapy.

Graphical Abstract
Cardiovascular Disease-Associated Non-Coding Variants Disrupt GATA4-DNA Binding and Regulatory Functions
Authors: Peña-Martínez Edwin G. , Messon-Bird Jean L. , Rodríguez-Ríos Jessica M. , Velázquez-Roig Rosalba , Pomales-Matos Diego A. , Rivera-Madera Alejandro , Sanabria-Alberto Leandro , Barreiro-Rosario Adriana C. , Valle Jeancarlos Rivera-Del , Muñoz-Páez Nicole E. , Peterson-Peguero Esther A. , Rodríguez-Martínez José A.
Published: September 2024

Genome-wide association studies have mapped over 90% of cardiovascular disease (CVD)-associated variants within the non-coding genome. Non-coding variants in regulatory regions of the genome, such as promoters, enhancers, silencers, and insulators, can alter the function of tissue-specific transcription factors (TFs) proteins and their gene regulatory function. In this work, we used a computational approach to identify and test CVD-associated single nucleotide polymorphisms (SNPs) that alter the DNA binding of the human cardiac transcription factor GATA4. Using a gapped k-mer support vector machine (GKM-SVM) model, we scored CVD-associated SNPs localized in gene regulatory elements in expression quantitative trait loci (eQTL) detected in cardiac tissue to identify variants altering GATA4-DNA binding. We prioritized four variants that resulted in a total loss of GATA4 binding (rs1506537 and rs56992000) or the creation of new GATA4 binding sites (rs2941506 and rs2301249). The identified variants also resulted in significant changes in transcriptional activity proportional to the altered DNA-binding affinities. In summary, we present a comprehensive analysis comprised of in silico, in vitro, and cellular evaluation of CVD-associated SNPs predicted to alter GATA4 function.

Graphical Abstract

Highlights

An integrative computational approach combining functional genomics data and machine learning was implemented to prioritize potential causal genetic variants associated with cardiovascular disease (CVD).

We prioritized and validated CVD-associated SNPs that created or destroyed genomic binding sites of the cardiac transcription factor GATA4.

Changes in GATA4-DNA binding resulted in significant changes in GATA4-dependent transcriptional activity in human cells.

Our results contribute to the mechanistic understanding of cardiovascular disease-associated non-coding variants impacting GATA4 function.
habtools: an R package to calculate 3D metrics for surfaces and objects
Authors: Schiettekatte Nina , Asbury Mollie , Chen Guan-Yan , Dornelas Maria , Reichert Jessica , Torres-Pulliza Damaris , Zawada Kyle J.A. , Madin Joshua S.
Published: September 2024

Technological advances in three-dimensional imaging techniques have opened the door to advanced morphological analyses and habitat mapping for biologists and ecologists.

At the same time, the challenge of translating complex 3D data into meaningful metrics that can be used in conjunction with biological data currently hinders progress and accessibility.

We introducehabtools, an R package that provides R functions to efficiently calculate complexity and shape metrics from DEMs, 3D meshes and 2D shapes as well as some helper functions to facilitate workflow.

We expect the functionality ofhabtoolsto continue to expand as new metrics and faster methods become available, and welcome new contributions and ideas.
Proteomic analysis of papillary thyroid carcinoma in the context of Hashimoto’s thyroiditis
Authors: Zhou Hui , Sun Hui , Iqbal Muhammad Asad , Zhao Ziou , Hou Jie , Wang Xian , Pan Donggang
Published: September 2024

Objective

To analyze the proteomic characteristics of papillary thyroid carcinoma in the context of Hashimoto’s thyroiditis by mass spectrometry and screen the corresponding differential proteins.

Methods

Postoperative paraffin specimens of 3 patients with Hashimoto’s thyroiditis combined with papillary thyroid carcinoma and 3 patients with Hashimoto’s thyroiditis and benign nodules were collected. The differential proteins were obtained by qualitative and quantitative analysis using Q ExactiveTM mass spectrometer. Functional enrichment cluster analysis and protein interaction analysis were then performed on these differential proteins. Finally, key proteins were screened out and immunohistochemical verification was performed.

Results

72 up-regulated differentially expressed proteins and 21 down-regulated differentially expressed proteins were screened out. THBS2 and COL12A1 were further identified by bioinformatics analysis. After immunohistochemical verification, it was concluded that COL12A1 can be used as a specific tumor marker.

Conclusion

There are differentially expressed proteins between the Hashimoto’s thyroiditis combined with papillary thyroid carcinoma group and the Hashimoto’s thyroiditis combined with benign nodules group. The up-regulated expression of COL12A1 can become an auxiliary diagnostic marker for papillary thyroid carcinoma with Hashimoto’s thyroiditis.
AsaruSim: a single-cell and spatial RNA-Seq Nanopore long-reads simulation workflow
Authors: Hamraoui Ali , Jourdren Laurent , Thomas-Chollier Morgane
Published: September 2024

Motivation

The combination of long-read sequencing technologies like Oxford Nanopore with single-cell RNA sequencing (scRNAseq) assays enables the detailed exploration of transcriptomic complexity, including isoform detection and quantification, by capturing full-length cDNAs. However, challenges remain, including the lack of advanced simulation tools that can effectively mimic the unique complexities of scRNAseq long-read datasets. Such tools are essential for the evaluation and optimization of isoform detection methods dedicated to single-cell long read studies.

Results

We developed AsaruSim, a workflow that simulates synthetic single-cell long-read Nanopore datasets, closely mimicking real experimental data. AsaruSim employs a multi-step process that includes the creation of a synthetic UMI count matrix, generation of perfect reads, optional PCR amplification, introduction of sequencing errors, and comprehensive quality control reporting. Applied to a dataset of human peripheral blood mononuclear cells (PBMCs), AsaruSim accurately reproduced experimental read characteristics.

Availability and implementation

The source code and full documentation are available at:https://github.com/GenomiqueENS/AsaruSim.

Data availability

The 1,090 Human PBMCs count matrix and cell type annotation files are accessible on zenodo under DOI: 10.5281/zenodo.12731408.
The Role of ATP Synthase Subunit e (ATP5I) in Mediating the Metabolic and Antiproliferative Effects of Biguanides
Authors: Lefrançois Guillaume , Lavallée Emilie , Rowell Marie-Camille , Bourdeau Véronique , Mohebali Farzaneh , Berthomeu Thierry , Tyers Mike , Gravel Simon-Pierre , Schmitzer Andréea R. , Ferbeyre Gerardo
Published: September 2024

Here we identify the subunit e of F1Fo-ATP synthase (ATP5I) as a target of medicinal biguanides. ATP5I maintains the stability of F1Fo-ATP synthase dimers which is crucial for shaping cristae morphology. Although its roles have been mainly studied in yeast models, its function in cellular energy metabolism within the context of cancer remains poorly characterized. In this study, we demonstrate that ATP5I interacts with a biguanide analoguein vitroand disabling its expression by CRISPR-Cas9 in pancreatic cancer cells leads to the same phenotype as biguanide treated cells including a decrease in the levels of some respiratory complex subunits, mitochondrial morphology alterations, inhibition of oxidative phosphorylation (OXPHOS) and a compensatory increase in glycolysis. Moreover, ATP5I knockout (KO) cells exhibit resistance to the antiproliferative effects of biguanides, but reintroduction of ATP5I rescues the metabolic and anti-proliferative effects of metformin and phenformin. These findings highlight ATP5I as a significant antineoplastic mitochondrial target of medicinal biguanides, opening new opportunities for the development of mitochondrial-targeted therapies.
Comparative analysis of protein expression between oesophageal adenocarcinoma and normal adjacent tissue
Authors: Nicholas Ben , Bailey Alistair , McCann Katy J , Walker Robert C. , Johnson Peter , Elliott Tim , Underwood Tim J. , Skipp Paul
Published: September 2024

Oesophageal adenocarcinoma (OAC) is the 7th most common cancer in the United Kingdom and remains a significant health challenge. This study presents a proteomic analysis of seven OAC donors complementing our previous neoantigen identification study of their human leukocyte antigen (HLA) immunopeptidomes. Using label-free mass spectrometry proteomics, we compared OAC tumour tissue to matched normal adjacent tissue (NAT) to identify differentially expressed proteins.

We identified differential expression of a number of proteins previously linked to OAC and other cancers. We observed enrichment of processes and pathways relating RNA processing and the immune system. Our findings also offer insight into the role of the protein stability in the generation of the neoantigen we previously identified. These results provide independent corroboration of existing oesophageal adenocarcinoma biomarker studies that may inform future diagnostic and therapeutic research.
Safeguarding Privacy in Genome Research: A Comprehensive Framework for Authors
Authors: Ghasemian Maryam , Gerido Lynette Hammond , Ayday Erman
Published: September 2024

As genomic research continues to advance, sharing of genomic data and research outcomes has become increasingly important for fostering collaboration and accelerating scientific discovery. However, such data sharing must be balanced with the need to protect the privacy of individuals whose genetic information is being utilized. This paper presents a bidirectional framework for evaluating privacy risks associated with data shared (both in terms of summary statistics and research datasets) in genomic research papers, particularly focusing on re-identification risks such as membership inference attacks (MIA). The framework consists of a structured workflow that begins with a questionnaire designed to capture researchers’ (authors’) self-reported data sharing practices and privacy protection measures. Responses are used to calculate the risk of re-identification for their study (paper) when compared with the National Institutes of Health (NIH) genomic data sharing policy. Any gaps in compliance help us to identify potential vulnerabilities and encourage the researchers to enhance their privacy measures before submitting their research for publication. The paper also demonstrates the application of this framework, using published genomic research as case study scenarios to emphasize the importance of implementing bidirectional frameworks to support trustworthy open science and genomic data sharing practices.
Structural and dynamic consequences of inosine, 2′-O-methylation, and N6-methyladenosine modifications in RNA G-quadruplex: A molecular dynamics study
Authors: Dutta Nivedita , Deb Indrajit , Sarzynska Joanna , Lahiri Ansuman
Published: September 2024

RNA G-quadruplexes (rG4) are stable non-canonical structures, often found to regulate important biological processes such as transcription, translation, splicing, RNA localization, and other steps in gene expression. rG4 structures can also influence DNA-related processes e.g. DNA replication, telomere elongation and homeostasis, and recombination. Due to the involvement of rG4s in such important processes, these structures are potential therapeutic targets against different diseases e.g., viral infection and cancer. Hence, a better understanding of the structure and stability of rG4s and their role in various therapeutically important cellular processes can help in the design of effective therapeutic strategies for targeting such structures. In the present study, we present our findings on the structural and dynamic effect of RNA modifications (inosine; 2′-O-methylation, and m6A-methylation) on RNA G-quadruplex structure from molecular dynamics simulations. Additionally, we also report the dynamic and energetic aspects of inter-quadruplex interactions and the influence of non-G purine tetrads neighboring the inter-quadruplex junction on the interactions.
Efficacy and Safety of Acupuncture for Acute Gouty Arthritis: A Systematic Review and Network Meta-Analysis
Authors: Cai Yuxiao , Liu Yifan , Kang Qinglong , Zhu Shiji , Wang Qianqian , Sun Chunmei , Gu Yin
Published: September 2024

Acute gouty arthritis (AGA) severely affects the quality of life of patients due to its persistent, recurrent, and debilitating characteristics. Acupuncture holds a pivotal role as a classical alternative therapy in managing gouty arthritis. This study aimed to assess the clinical effectiveness of various acupuncture methods used in conjunction with conventional medications for treating acute gouty arthritis. We conducted a search of seven English and Chinese databases up to February 10, 2024, and analyzed the data using R software version 4.4.0.The study included a total of 37 randomized controlled trials(RCT), encompassing 2,801 patients. The network meta-analysis (NMA) results are as follows: Fire acupuncture demonstrated the highest effectiveness in improving cure rates. Acupuncture combined with conventional medication was found to be the most effective for reducing VAS scores. Additionally, Acupuncture combined with conventional medication proved most effective in lowering uric acid levels. For reducing ESR, the combination of blood-letting therapy and conventional drugs showed the greatest efficacy. No statistically significant differences were found among the different interventions regarding the reduction of TCMSS and CRP levels. In conclusion, fire acupuncture showed the greatest overall effectiveness. Acupuncture with conventional medication best reduced VAS scores and uric acid levels, while blood-letting therapy combined with conventional drugs was most effective in lowering ESR.
Prediction and design of transcriptional repressor domains with large-scale mutational scans and deep learning
Authors: Valbuena Raeline , Nigam AkshatKumar , Tycko Josh , Suzuki Peter , Spees Kaitlyn , Aradhana  , Arana Sophia , Du Peter , Patel Roshni A. , Bintu Lacramiora , Kundaje Anshul , Bassik Michael C.
Published: September 2024

Regulatory proteins have evolved diverse repressor domains (RDs) to enable precise context-specific repression of transcription. However, our understanding of how sequence variation impacts the functional activity of RDs is limited. To address this gap, we generated a high-throughput mutational scanning dataset measuring the repressor activity of 115,000 variant sequences spanning more than 50 RDs in human cells. We identified thousands of clinical variants with loss or gain of repressor function, including TWIST1 HLH variants associated with Saethre-Chotzen syndrome and MECP2 domain variants associated with Rett syndrome. We also leveraged these data to annotate short linear interacting motifs (SLiMs) that are critical for repression in disordered RDs. Then, we designed a deep learning model called TENet (TranscriptionalEffectorNetwork) that integrates sequence, structure and biochemical representations of sequence variants to accurately predict repressor activity. We systematically tested generalization within and across domains with varying homology using the mutational scanning dataset. Finally, we employed TENet within a directed evolution sequence editing framework to tune the activity of both structured and disordered RDs and experimentally test thousands of designs. Our work highlights critical considerations for future dataset design and model training strategies to improve functional variant prioritization and precision design of synthetic regulatory proteins.
MAX inactivation deregulates the MYC network and induces neuroendocrine neoplasia in multiple tissues
Authors: Freie Brian , Ibrahim Ali H. , Carroll Patrick A. , Bronson Roderick T , Augert Arnaud , MacPherson David , Eisenman Robert N.
Published: September 2024

The MYC transcription factor requires MAX for DNA binding and widespread activation of gene expression in both normal and neoplastic cells. Surprisingly, inactivating mutations inMAXare associated with a subset of neuroendocrine cancers including pheochromocytoma, pituitary adenoma and small cell lung cancer. Neither the extent nor the mechanisms of MAX tumor suppression are well understood. DeletingMaxacross multiple mouse neuroendocrine tissues, we findMaxinactivation alone produces pituitary adenomas whileMaxloss cooperates withRb1/Trp53loss to accelerate medullary thyroid C-cell and pituitary adenoma development. In the thyroid tumor cell lines, MAX loss triggers a striking shift in genomic occupancy by other members of the MYC network (MNT, MLX, MondoA) supporting metabolism, survival and proliferation of neoplastic neuroendocrine cells. Our work reveals MAX as a broad suppressor of neuroendocrine tumorigenesis through its ability to maintain a balance of genomic occupancies among the diverse transcription factors in the MYC network.

Teaser

MAXinactivation deregulates multiple transcription factors to induce neuroendocrine cancers
Assessment of the relationship between synaptic density and metabotropic glutamate receptors in early Alzheimer’s disease: a multi-tracer PET study
Authors: Salardini Elaheh , O’Dell Ryan S. , Tchorz Em , Nabulsi Nabeel B. , Huang Yiyun , Carson Richard E. , van Dyck Christopher H. , Mecca Adam P.
Published: September 2024

Background

The pathological effects of amyloid β oligomers (Aβo) may be mediated through the metabotropic glutamate receptor subtype 5 (mGluR5), leading to synaptic loss in Alzheimer’s disease (AD). Positron emission tomography (PET) studies of mGluR5 using [18F]FPEB indicate a reduction of receptor binding that is focused in the medial temporal lobe in AD. Synaptic loss due to AD measured through synaptic vesicle glycoprotein 2A (SV2A) quantification with [11C]UCB-J PET is also focused in the medial temporal lobe, but with clear widespread reductions is commonly AD-affected neocortical regions. In this study, we used [18F]FPEB and [11C]UCB-J PET to investigate the relationship between mGluR5 and synaptic density in early AD.

Methods

Fifteen amyloid positive participants with early AD and 12 amyloid negative, cognitively normal (CN) participants underwent PET scans with both [18F]FPEB to measure mGluR5 and [11C]UCB-J to measure synaptic density. ParametricDVRimages using equilibrium methods were generated from dynamic. For [18F]FPEB PET,DVRwas calculated using equilibrium methods and a cerebellum reference region. For [11C]UCB-J PET,DVRwas calculated with a simplified reference tissue model – 2 and a whole cerebellum reference region.

Result

A strong positive correlation between mGluR5 and synaptic density was present in the hippocampus for participants with AD (r= 0.81,p< 0.001) and in the CN group (r= 0.74,p= 0.005). In the entorhinal cortex, there was a strong positive correlation between mGluR5 and synaptic in the AD group (r= 0.85,p<0.001), but a weaker non-significant correlation in the CN group (r= 0.36,p= 0.245). Exploratory analyses within and between other brain regions suggested significant positive correlations between mGluR5 in the medial temporal lobe and synaptic density in a broader set of commonly AD-affected regions.

Conclusion

Medial temporal loss of mGluR5 in AD is associated with synaptic loss in both medial temporal regions and more broadly in association cortical regions, indicating that mGluR5 mediated Aβo toxicity may lead to early synaptic loss more broadly in AD-affected networks. In CN individuals, an isolated strong association between lower mGluR5 and lower synaptic density may indicate non-AD related synaptic loss.
Multiband EEG signature decoded using machine learning for predicting rTMS treatment response in major depression
Authors: Arteaga Alexander , Tong Xiaoyu , Zhao Kanhao , Carlisle Nancy B. , Oathes Desmond J. , Fonzo Gregory A. , Keller Corey J. , Zhang Yu
Published: September 2024

Major depressive disorder (MDD) is a global health challenge with high prevalence. Further, many diagnosed with MDD are treatment resistant to traditional antidepressants. Repetitive transcranial magnetic stimulation (rTMS) offers promise as an alternative solution, but identifying objective biomarkers for predicting treatment response remains underexplored. Electroencephalographic (EEG) recordings are a cost-effective neuroimaging approach, but traditional EEG analysis methods often do not consider patient-specific variations and fail to capture complex neuronal dynamics. To address this, we propose a data-driven approach combining iterated masking empirical mode decomposition (itEMD) and sparse Bayesian learning (SBL). Our results demonstrated significant prediction of rTMS outcomes using this approach (Protocol 1: r=0.40, p<0.01; Protocol 2: r=0.26, p<0.05). From the decomposition, we obtained three key oscillations: IMF-Alpha, IMF-Beta, and the remaining residue. We also identified key spatial patterns associated with treatment outcomes for two rTMS protocols: for Protocol 1 (10Hz left DLPFC), important areas include the left frontal and parietal regions, while for Protocol 2 (1Hz right DLPFC), the left and frontal, left parietal regions are crucial. Additionally, our exploratory analysis found few significant correlations between oscillation specific predictive features and personality measures. This study highlights the potential of machine learning-driven EEG analysis for personalized MDD treatment prediction, offering a pathway for improved patient outcomes.
Building a literature knowledge base towards transparent biomedical AI
Authors: Huang Yuanhao , Han Zhaowei , Luo Xin , Luo Xuteng , Gao Yijia , Zhao Meiqi , Tang Feitong , Wang Yiqun , Chen Jiyu , Li Chengfan , Lu Xinyu , Jiao Tiancheng , Qiu Jiahao , Deng Feiyang , Guan Lingxiao , Shang Haohong , Feng Fan , Vu Thi Hong Ha , Bate Thomas , Xue Dongxiang , Cartailler Jean-Philippe , Stitzel Michael , Chen Shuibing , Brissova Marcela , Parker Stephen , Liu Jie
Published: September 2024

As artificial intelligence (AI) continues to advance and scale up in biomedical research, concerns about AI’s trustworthiness and transparency have grown. There is a critical need to systematically bring accurate and relevant biomedical knowledge into AI applications for transparency and provenance. Knowledge graphs have emerged as a powerful tool that integrates heterogeneous knowledge by explicitly describing biomedical knowledge as entities and relationships between entities. However, PubMed, the largest and most comprehensive repository of biomedical knowledge, exists primarily as unstructured text and is under utilized for advanced machine learning tasks. To address the challenge, we developed LiteralGraph, a computational framework to extract biomedical terms and relationships from PubMed literature into a unified knowledge graph. Using this framework, we established the Genomic Literature Knowledge Base (GLKB), which consolidates 14,634,427 biomedical relationships between 3,276,336 biomedical terms from over 33 million PubMed abstracts and nine well-established biomedical repositories. The database is coupled with RESTful APIs and a user-friendly web interface that makes it accessible to researchers for various usages. We demonstrated the broad utility of GLKB towards transparent AI in three distinct application scenarios. In the LLM grounding scenario, we developed a Retrieval Augmented Generation (RAG) agent to reduce LLM hallucination in biomedical question answering. In the hypothesis generation scenario, we elucidated the potential functions of RFX6 in type 2 diabetes (T2D) using the vast evidence from PubMed articles. In the machine learning scenario, we utilized GLKB to provide semantic knowledge in predictive tasks and scientific fact-checking.
ALMS1KO rat: a new model of metabolic syndrome with spontaneous hypertension
Authors: Jaykumar Ankita B. , Monu Sumit R. , Mendez Mariela , Rhaleb Nour-Eddine , Ortiz Pablo A.
Published: September 2024

ALMS1 is a protein initially associated with Alström syndrome. This is a rare human disorder characterized by metabolic dysfunction, hypertension, obesity and hyperinsulinemia. In addition,ALMS1gene was linked to hypertension status in a multipoint linkage population analysis. However, the mechanisms by which ALMS1 contributes to the development of obesity, insulin resistance and other metabolic disturbances are unknown. To study the role of ALMS1 in blood pressure regulation and renal function we previously generated an ALMS1 knockout rat model, where we found these rats are hypertensive. In this study, we further characterized theALMS1knockout rat, and found that they exhibit most characteristics of metabolic syndrome including hypertension and higher body weight by 10-12 weeks of age. In contrast, obesity, hyperinsulinemia and vascular dysfunction manifested at around 14-16 weeks of age. Interestingly,ALMS1KO rats developed hyperleptinemia prior to the development of obesity rapidly after weaning by 7 weeks of age, suggesting an early role for ALMS1 in the hormonal control of leptin. We also found that femaleALMS1KO rats develop severe metabolic syndrome with hypertension similar to their male counterparts, lacking any protection often associated with better cardiovascular outcomes. Therefore, ALMS1 is an essential gene for sex-and age-dependent metabolic function. TheALMS1knockout rat provides an invaluable pre-clinical animal model that recapitulates most symptoms present in patients and allows the study of new drugs and mechanisms that cause metabolic syndrome.
A Novel Machine Learning Based Framework for Developing Composite Digital Biomarkers of Disease Progression
Authors: Zhai Song , Liaw Andy , Shen Judong , Xu Yuting , Svetnik Vladimir , FitzGerald James J. , Antoniades Chrystalina A. , Holder Dan , Dockendorf Marissa F. , Ren Jie , Baumgartner Richard
Published: September 2024

Background

Current methods of measuring disease progression of neurodegenerative disorders, including Parkinson’s disease (PD), largely rely on composite clinical rating scales, which are prone to subjective biases and lack the sensitivity to detect progression signals in a timely manner. Digital health technology (DHT)-derived measures offer potential solutions to provide objective, precise, and sensitive measures that address these limitations. However, the complexity of DHT datasets and the potential to derive numerous digital features that were not previously possible to measure pose challenges, including in selection of the most important digital features and construction of composite digital biomarkers.

Methods

We present a comprehensive machine learning based framework to construct composite digital biomarkers for progression tracking. This framework consists of a marginal (univariate) digital feature screening, a univariate association test, digital feature selection, and subsequent construction of composite (multivariate) digital disease progression biomarkers using Penalized Generalized Estimating Equations (PGEE). As an illustrative example, we applied this framework to data collected from a PD longitudinal observational study. The data consisted of OpalTMsensor-based movement measurements and MDS-UPDRS Part III scores collected at 3-month intervals for 2 years in 30 PD and 10 healthy control participants.

Results

In our illustrative example, 77 out of 235 digital features from the study passed univariate feature screening, with 11 features selected by PGEE to include in construction of the composite digital measure. Compared to MDS-UPDRS Part III, the composite digital measure exhibited a smoother and more significant increasing trend over time in PD groups with less variability, indicating improved ability for tracking disease progression. This digital composite measure also demonstrated the ability to classify between de novo PD and healthy control groups.

Conclusion

Measures from DHTs show promise in tracking neurodegenerative disease progression with increased sensitivity and reduced variability as compared to traditional clinical scores. Herein, we present a novel framework and methodology to construct composite digital measure of disease progression from high-dimensional DHT datasets, which may have utility in accelerating the development and application of composite digital biomarkers in drug development.
A Novel Adhesin ofB. pertussisis Key to Colonisation of Epithelial Cells
Authors: Gollan Michael , Gestal Monica C , Parrish Katelyn M , Harvill Eric T , Preston Andrew , MacArthur Iain
Published: September 2024

Despite effective vaccines to protect against Whooping cough, or pertussis, the disease is resurgent in many countries. A switch from acellular to whole-cell vaccines has resulted in waning protective immunity, likely contributing to increases in infection prevalence, underlining the need to better understandB. pertussisvirulence. As a respiratory pathogen,B. pertussiscolonises the upper respiratory tract utilising an array of adhesins, four of which (FHA, pertactin, Fim2/3) are included in the acellular vaccine. In this study, we identified two Bvg regulated genes that are upregulated during virulence conditions and thus potentially involved in pathogenesis.bp1251andbp1252encode orphan toxin B subunits, with homology to AB toxin B subunits. Mutation ofbp1251andbp1252reduced thein vitroadherence ofB. pertussisto A549 and BEAS-2B alveolar and bronchial epithelial-like cells. In a murine model of infection,bp1251andbp1252 mutant strains were recovered from the nasal cavity and lungs at lower levels than WT.In vitrono effect of mutation ofbp1251orbp1252on cell invasion or toxicity was found suggesting that these proteins do not form part of a toxin. Given their homology to B subunits of AB toxins, and their role in colonisation, we propose that BP1251 and BP1252 are novel adhesins. Our data suggests that these proteins play a significant role inBordetellainfection and have the potential to further the understanding ofB. pertussispathogenesis.
Genetic and microbial analysis of invasiveness forEscherichia colistrains associated with inflammatory bowel disease
Authors: Kim Jungyeon , Zhang Jing , Kinch Lisa , Shen Jinhui , Field Sydney , Klapproth Jan-Michael , Forsberg Kevin J. , Harris-Tryon Tamia , Orth Kim , Cong Qian , Ni Josephine
Published: September 2024

Background & Aims

The adherent-invasiveEscherichia coli(AIEC) pathotype is implicated in inflammatory bowel disease (IBD) pathogenesis. AIEC strains are currently defined by phenotypic measurement of their pathogenicity, including invasion of epithelial cells. This broad definition, combined with the genetic diversity of AIEC across IBD patients, has complicated the identification of virulence determinants. We sought to quantify the invasion phenotype of clinical isolates from IBD patients and identify the genetic basis for their invasion into epithelial cells.

Methods

A pangenome with core and accessory genes (genotype) was assembled using whole genome sequencing of 168E. colisamples isolated from 13 IBD patients. A modified assay for invasion of epithelial cells (phenotype) was established with consideration of antibiotic resistance phenotypes. Isolate genotype was correlated to invasiveness phenotype to identify genetic factors that co-segregate with invasion.

Results

Pangenome-wide comparisons ofE. coliclinical isolates identified accessory genes that can co-segregate with invasion phenotype. These correlations found the acquisition of antibiotic resistance genes in clinical isolates compromised the traditional gentamicin protection assays used to quantify invasion. Therefore, an alternate assay, based on amikacin resistance, identified genes co-segregating with invasion. These genes encode an arylsulfatase, a glycoside hydrolase, and genetic islands carrying propanediol utilization and sulfoquinovose metabolism pathways.

Conclusions

This study highlights the importance of incorporating antibiotic resistance screening for invasion assays used in AIEC identification. Accurately screened invasion phenotypes identified accessory genome elements amongE. coliIBD isolates that correlate with their ability to invade epithelial cells. These results help explain why single genetic markers for the AIEC phylotype are challenging to identify.

Synopsis

We established a pangenome ofEscherichia coliisolates from inflammatory bowel disease patients using whole genome sequencing. The genotypes were correlated with a newly developed measurement of invasion phenotype to identify co-segregating genes.
TNFSF13 insufficiency disrupts human colonic epithelial cell-mediated B cell differentiation
Authors: Ma Xianghui , Dawany Noor , Kondo Ayano , Maurer Kelly , Karakasheva Tatiana , Shraim Rawan , Williams Patrick A. , Parham Louis R. , Simon Lauren A. , Danan Charles H. , Conrad Maire A. , Piccoli David A. , Devoto Marcella , Sullivan Kathleen E. , Kaestner Klaus H. , Kelsen Judith R. , Hamilton Kathryn E.
Published: September 2024

Cytokines mediating epithelial and immune cell interactions modulate mucosal healing-a process that goes awry with chronic inflammation as in inflammatory bowel disease. TNFSF13 is a cytokine important for B cell maturation and function, but roles for epithelial TNFSF13 and putative contribution to inflammatory bowel disease are poorly understood. We evaluated functional consequences of a novel monoallelicTNFSF13variant using biopsies, tissue-derived colonoids and induced pluripotent stem cell (iPSC)-derived colon organoids.TNFSF13variant colonoids exhibited a >50% reduction in secreted TNFSF13, increased epithelial proliferation, and reduced apoptosis, which was confirmed in iPSC-derived colon organoids. Single cell RNA-sequencing, flow cytometry, and co-immunoprecipitation identified FAS as the predominant colonic epithelial receptor for TNFSF13. Imaging mass cytometry revealed an increase in epithelial-associated B cells inTNFSF13variant colon tissue sections. Finally,TNFSF13variant colonoids co-cultured with memory B cells demonstrated a reduction in the production of IgA+ plasma cells compared to control colonoid co-cultures. Our findings support a role for epithelial TNFSF13 as a regulator of colonic epithelial growth and epithelial crosstalk with B cells.

Epithelial TNFSF13 regulates colonic epithelial growth and epithelial-B cell interactions.

Graphical Abstract
Environmental sphagnum-associated fungi target thiol homeostasis to compete withMycobacterium tuberculosis
Authors: Malhotra Neha , Oh Sangmi , Finin Peter , Medrano Jessica , Andrews Jenna , Goodwin Michael , Markowitz Tovah E. , Lack Justin , Boshoff Helena I. M. , Barry Clifton Earl
Published: September 2024

Mycobacterial species in nature are found in abundance in sphagnum peat bogs where they compete for nutrients with a variety of microorganisms including fungi. We screened a collection of fungi isolated from sphagnum bogs by co-culture withMycobacterium tuberculosis(Mtb) to look for inducible expression of antitubercular agents and identified five fungi that produced cidal antitubercular agents upon exposure to liveMtb. Whole genome sequencing of these fungi followed by fungal RNAseq afterMtbexposure allowed us to identify biosynthetic gene clusters induced by co-culture. Three of these fungi induced expression of patulin, one induced citrinin expression and one induced the production of nidulalin A. The biosynthetic gene clusters for patulin and citrinin have been previously described but the genes involved in nidulalin A production have not been described before. All three of these potent electrophiles react with thiols and treatment ofMtbcells with these agents followed byMtbRNAseq showed that these natural products all induce profound thiol stress suggesting a rapid depletion of mycothiol. The induction of thiol-reactive mycotoxins through three different systems in response to exposure toMtbsuggests that fungi have identified this as a highly vulnerable target in a similar microenvironment to that of the caseous human lesion.
The Mitochondrial Ubiquitin Ligase MARCHF5 Cooperates with MCL1 to Inhibit Apoptosis in KSHV-Transformed Primary Effusion Lymphoma Cell Lines
Authors: Viswanathan Prasanth , Bersonda Justine R. , Gill Jackson , Navarro Alyssandra , Farrar Allison C. , Dunham Daniel , Boehme Karl W. , Manzano Mark
Published: September 2024

Kaposi’s sarcoma-associated herpesvirus (KSHV) causes several malignancies in people with HIV including Kaposi’s sarcoma and primary effusion lymphoma (PEL). We have previously shown that PEL cell lines require myeloid cell leukemia-1 (MCL1) to inhibit apoptosis. MCL1 is an oncogene that is amplified in cancers and causes resistance to chemotherapy regimens. MCL1 is thus an attractive target for drug development. The emerging clinical relevance and therapeutic potential of MCL1 motivated us to study the roles of this oncogene in PEL in depth. Using a systems biology approach, we uncovered an unexpected genetic interaction between MCL1 and MARCHF5 indicating that they function in the same pathway. MARCHF5 is an E3 ubiquitin ligase most known for regulating mitochondrial homeostasis and antiviral signaling, but not apoptosis. We thus investigated how MCL1 and MARCHF5 cooperate to promote PEL cell survival. CRISPR knockout (KO) of MARCHF5 in PEL cell lines resulted in a significant increase in apoptosis despite the presence of MCL1. The anti-apoptotic function of MARCHF5 was dependent on its E3 ligase and dimerization activities. Loss of MARCHF5 or inhibition of the 26S proteasome furthermore stabilized the MCL1 antagonist NOXA without affecting levels of MCL1. Interestingly, NOXA KO provides a fitness advantage to PEL cells suggesting that NOXA is the pro-apoptotic signal that necessitates the anti-apoptotic activities of MCL1 and MARCHF5. Finally, endogenous reciprocal co-immunoprecipitation experiments show that MARCHF5 and NOXA are found in the same protein complex. Our findings thus provide the mechanistic link that underlies the genetic interaction between MCL1 and MARCHF5. We propose that MARCHF5 induces the degradation of the MCL1 antagonist NOXA thus reinforcing the pro-survival role of MCL1 in these tumor cells. This newly appreciated interaction of the MCL1 and MARCHF5 oncogenes may be useful to improve the design of combination therapies for KSHV malignancies.
Mycobacterium abscessuspersistence in the face ofPseudomonas aeruginosaantagonism
Authors: Gupta Rashmi , Schuster Martin , Rohde Kyle H.
Published: September 2024

Chronic bacterial infections are responsible for significant mortality and morbidity in cystic fibrosis (CF) patients.Pseudomonas aeruginosa(Pa), the dominant CF pathogen, andMycobacterium abscessus(Mab) both cause persistent pulmonary infections that are difficult to treat. Co-infection by both bacterial pathogens leads to severe disease and poor clinical outcomes. To explore understudied interactions between these two CF pathogens, we employed culture- and molecular-based approaches. In a planktonic co-culture model, growth ofPacontinued unimpeded, and it exerted a bacteriostatic effect onMab. Strikingly, exposure ofMabgrown in monoculture to cell-free spent supernatant ofParesulted in a dramatic, dose-dependent bactericidal effect. Initial characterization indicated that this potentPa-derived anti-Mabcidal activity was mediated by a heat-sensitive, protease-insensitive soluble factor of >3kDa size. Further analysis demonstrated that expression of this mycobactericidal factor requires LasR, a central regulator ofPaquorum sensing (QS). In contrast, ΔLasRPawas still able to exert a bacteriostatic effect onMabduring co-culture, pointing to additional LasR-independent factors able to antagonizeMabgrowth. However, the ability ofMabto adapt during co-culture to counter the cidal effects of a LasR regulated factor suggested complex interspecies dynamics. Dual RNAseq analysis ofMab-Paco-cultures revealed significant transcriptional remodeling ofMab, with differential expression of 68% ofMabgenes compared to minimal transcriptional changes inPa. Transcriptome analysis reflected slowedMabgrowth and remodeling of carbon and energy metabolism akin to a non-replicating persister-like phase. A tailoredMabresponse toPawas evident by enhanced transcript levels of genes predicted to interfere with alkylquinolone QS signals or provide protection against respiratory toxins and hydrogen cyanide. This is the first study to provide a transcriptome-level view of genetic responses governing the interplay between two important CF pathogens. This will provide insights into interspecies interaction mechanisms which can be targeted to disrupt their communities in a CF lung to improve patient clinical performance. Moreover, identification of a novel antimicrobial natural product with potent cidal activity againstMabwill provide a chemical biology tool for identifying new drug targets inMab.
Rfam 15: RNA families database in 2025
Authors: Ontiveros Nancy , Cooke Emma , Nawrocki Eric P. , Triebel Sandra , Marz Manja , Rivas Elena , Griffiths-Jones Sam , Petrov Anton I. , Bateman Alex , Sweeney Blake
Published: September 2024

The Rfam database, a widely-used repository of non-coding RNA (ncRNA) families, has undergone significant updates in release 15.0. This paper introduces major improvements, including the expansion of Rfamseq to 26, 106 genomes, a 76% increase, incorporating the latest UniProt reference proteomes and additional viral genomes. Sixty-five RNA families were enhanced using experimentally determined 3D structures, improving the accuracy of consensus secondary structures and annotations. R-scape covariation analysis was used to refine structural predictions in 26 families. Gene Ontology and Sequence Ontology annotations were comprehensively updated, increasing GO term coverage to 75% of families. The release adds 14 new Hepatitis C Virus RNA families and completes microRNA family synchronisation with miRBase, resulting in 1, 603 microRNA families. New data types, including FULL alignments, have been implemented. Integration with APICURON for improved curator attribution and multiple website enhancements further improve user experience. These updates significantly expand Rfam’s coverage and improve annotation quality, reinforcing its critical role in RNA research, genome annotation, and the development of machine learning models. Rfam is freely available athttps://rfam.org.

Graphical Abstract

Rfam has undergone a major update with the release of 15.0. We have increased the number of genomes in our sequence database Rfamseq by 75%, completed the synchronisation with miRBase and improved 65 families using 3D structures.