bluuebunny/crossref_metadata_2025 huggingface dataset:
How to improve polygenic prediction from whole-genome sequencing data by leveraging predicted epigenomic features?
Authors: Zeng Wanwen , Guo Hanmin , Liu Qiao , Wong Wing Hung
Published: October 2024

Polygenic risk scores (PRS) are crucial in genetics for predicting individual susceptibility to complex diseases by aggregating the effects of numerous genetic variants. Whole-genome sequencing (WGS) has revolutionized our ability to detect rare and evende novovariants, creating an exciting opportunity for developing new PRS methods that can effectively leverage rare variants and capture the complex relationships among different variants. Furthermore, regulatory mechanisms play a crucial role in gene expression and disease manifestation, offering avenues to further enhance the performance and interpretation of PRS predictions. Through simulation studies, we highlighted aspects where current PRS methods face challenges when applied to WGS data, aiming to shed light on potential opportunities for further improvement. To address these challenges, we developed Epi-PRS, an approach that leverages the power of genomic large language models (LLM) to impute epigenomic signals across diverse cellular contexts, for use as intermediate variables between genotype and phenotype. A pretrained LLM is employed to transform genotypes into epigenomic signals using personal diploid sequences as inputs, and the genetic risk is then estimated based on the imputed personal epigenomic signals. Epi-PRS enhances the assessment of personal variant impacts, enabling a comprehensive and holistic consideration of genotypic and regulatory information within large genomic regions. Our simulation results demonstrated that incorporating the nuanced effects of non-linear models, rare variants, and regulatory information can provide more precise PRS prediction and better understanding of genetic risk. Applying Epi-PRS to real data from the UK Biobank, our results further showed that Epi-PRS significantly outperforms existing PRS methods in two major diseases: breast cancer and diabetes. This study suggests that PRS methods can benefit from incorporating non-linear models, rare variants, and regulatory information, highlighting the potential for significant advancements in disease risk modeling and enhancing the understanding of precision medicine.

Significance Statement

Epi-PRS improves polygenic risk scoring by integrating genomic large language models (LLMs) to impute epigenomic signals as intermediaries between genotype and phenotype. This approach enables a more comprehensive assessment of personal variant impacts by incorporating non-linear models, rare variants, and regulatory mechanisms. By leveraging the power of genomic LLM trained on massive amount of reference epigenomics data, Epi-PRS has demonstrated superior performance over existing PRS methods in predicting genetic risk for breast cancer and diabetes in UK Biobank data. These results highlight the potential of Epi-PRS to improve disease risk modeling and advance the field of precision medicine.
Unravelling the joint genetic architecture between psychiatic and insulin-related traits in the general population
Authors: Sakic Barbara , Erdogan Izel , Fanelli Giuseppe , Arenella Martina , Mota Nina Roth , Bralten Janita
Published: October 2024

Attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are heritable disorders that frequently co-occur with insulin resistance (IR)-related conditions. Traditional genetic case-control comparisons are challenged by the extent of heterogeneity and comorbidity within and across these conditions. In this study we step away from univariate analyses to let biology guide us to the potential genetic links between insulin and psychiatry-related traits.

We used large-scale population-based genetic studies (N= 17,666-697,734) and applied genomic structural equation modeling to identify the factor structure best representing the joint genetic architecture of symptom scores of ADHD, ASD, and OCD, and five IR-related traits: body mass index (BMI), fasting plasma glucose (FPG), fasting plasma insulin, glycated haemoglobin (HbA1c), and homeostatic model assessment for IR. Subsequently we performed multivariate genome-wide association analyses on the psychiatry-IR related factors to explore genetic associations to unravel its biological basis. Factor analyses indicated that a three-factor model fitted the data best (x2(df=9)=18.79, AIC=56.8, CFI=0.99, SRMR=0.068). One factor included ADHD traits and three IR-related traits (BMI, FPG, HbA1c), while another encompassed OCD traits and HbA1c. The last factor included solely IR-related traits. Gene-wide analyses revealed 57 genes significantly associated with the ADHD-IR factor (p< 2.961e-06) and one gene,MTNR1B(p=3.44e-07), with the OCD/OCS-IR factor. Gene-set analyses found associations with neurodevelopmental pathways.

Our findings suggest a shared genetic liability between psychiatric symptoms and IR-related traits in the general population, offering new perspectives on the molecular genetics underlying the overlap between psychiatric and IR-related somatic conditions as well as biologically informed clustering within psychiatry.
SNP rs7549881, near SGIP1 at 1p31.3, is significantly associated with digestive disorders and Parkinsonism in women
Authors: Lehrer Steven , Rheinstein Peter
Published: October 2024

Background

A recent study identified a mutation in the SH3GL Interacting Endocytic Adaptor 1 (SGIP1) gene, located at 1p31.3, linked to early-onset Parkinsonism in 2 sisters in an Arab family with a history of young-onset Parkinson symptoms. SGIP1 had not been previously associated with Parkinsonism, a group of disorders including Parkinson’s disease (PD), characterized by motor dysfunction and cognitive decline. SGIP1 plays a role in endocytosis, particularly clathrin-mediated synaptic vesicle recycling, essential for synaptic proteostasis. In a fruit fly model, SGIP1 deletion resulted in synaptic dysfunction, impaired protein recycling, and brain cell degeneration, which mirrors Parkinsonism. We aimed to explore the genetic association of SGIP1 in Parkinson’s disease using data from the UK Biobank, specifically examining the nearby common intron variant rs7549881 at 1p31.3.

Methods

This study utilized data from the UK Biobank, a large biomedical database with genetic and health information from approximately 500,000 participants. We analyzed the association between rs7549881 and PD. The study included all participants with self-reported or ICD-diagnosed PD and restricted analysis to those with at least seven years of education. Genetic association analysis was performed using PLINK and SPSS, with logistic regression adjusting for covariates such as age, sex, and smoking. Additionally, a Phenome-Wide Association Study (PheWAS) was conducted to examine rs7549881 across a wide range of phenotypes.

Results

The study analyzed data from 385,629 subjects, with PD patients having a mean age of 63 ± 5 years. Among females, 26% of those homozygous for the rs7549881 GG allele had PD, compared to 22.2% who did not have PD (p = 0.004). This effect was not significant in males. Logistic regression revealed that male sex (OR 1.828, p < 0.001), age (OR 1.141 per year, p < 0.001), and constipation (OR 4.726, p = 0.001) increased PD risk, while cigarette smoking decreased it (OR 0.748, p < 0.001). The GG genotype was associated with increased PD risk when compared to the AA phenotype (OR 1.208, p = 0.015). PheWAS identified significant associations of rs7549881 with digestive disorders, including functional digestive disorders and non-infectious gastroenteritis.

Conclusion

The study demonstrated an association between the rs7549881 variant and PD in females, highlighting the potential role of SGIP1 in neurodegeneration. Additionally, the PheWAS findings link this variant to gastrointestinal disorders, supporting the emerging concept of a gut-brain axis in PD. The results suggest that SGIP1 may influence both neuronal and gastrointestinal functions, providing a new avenue for understanding the genetic mechanisms underlying Parkinson’s disease and its non-motor symptoms.
A Study on the Correlation between Adolescents’ Online Social Connections and Anxiety and Depression
Authors: Mengxuan Li , Jiajun Xu , Ying Liu , Jiaqi Xu , Hong Chen
Published: October 2024

OBJECTIVE

To investigate the current status of anxiety and depression among adolescents and to analyze the correlation between adolescents’ online social connections and their depression and anxiety.

METHODS

The study adopted a cross-sectional survey research design, conducted in a middle school located in a city in Sichuan Province. Classes were selected through simple random sampling, with all students in the selected classes serving as study participants. Anxiety, depression, and online social connections were assessed using the Chinese version of the DSM-5 Anxiety Inventory for Children and Adolescents, the DSM-5 Depression Inventory for Children and Adolescents, and the Revised Social Connectedness Scale, respectively.

RESULTS

The prevalence rates of anxiety and depression among the participants were found to be 49.1% and 47.1%, respectively. A significant positive correlation was identified between online social connections and both anxiety and depression.

CONCLUSION

The findings indicate a concerning prevalence of anxiety and depression among adolescents. It is crucial for healthcare professionals to recognize the multifaceted factors contributing to these mental health challenges and to remain vigilant regarding adolescent mental health. Leveraging the impact of online social connections, early psychological intervention strategies should be implemented to promote healthy online relationships and mitigate the risks of anxiety and depression among adolescents.
Advancing patient care: Machine learning models for predicting grade 3+ toxicities in gynecologic cancer patients treated with HDR brachytherapy
Authors: Portocarrero-Bonifaz Andres , Syed Salman , Kassel Maxwell , McKenzie Grant W. , Shah Vishwa M. , Forry Bryce M. , Gaskins Jeremy T. , Sowards Keith T. , Avula Thulasi Babitha , Masters Adrianna , Schneider Jose G. , Silva Scott R.
Published: October 2024

Background

Gynecological cancers are among the most prevalent cancers in women worldwide. Brachytherapy, often used as a boost to external beam radiotherapy, is integral to treatment. Advances in computation, algorithms, and data availability have popularized machine learning.

Objective

To develop and compare machine learning models for predicting grade 3 or higher toxicities in gynecological cancer patients treated with high dose rate (HDR) brachytherapy, aiming to contribute to personalized radiation treatments.

Methods

A retrospective analysis on gynecological cancer patients who underwent HDR brachytherapy with Syed-Neblett or Tandem and Ovoid applicators from 2009 to 2023. After exclusions, 233 patients were included. Dosimetric variables for the high-risk clinical target volume (HR-CTV) and organs at risk, along with tumor, patient, and toxicity data, were collected and compared between groups with and without grade 3 or higher toxicities using statistical tests. Six supervised classification machine learning models (Logistic Regression, Random Forest, K-Nearest Neighbors, Support Vector Machines, Gaussian Naive Bayes, and Multi-Layer Perceptron Neural Networks) were constructed and evaluated. The construction process involved sequential feature selection (SFS) when appropriate, followed by hyperparameter tuning. Final model performance was characterized using a 25% withheld test dataset.

Results

The top three ranking models were Support Vector Machines, Random Forest, and Logistic Regression, with F1 testing scores of 0.63, 0.57, and 0.52; normMCC testing scores of 0.75, 0.77, and 0.71; and accuracy testing scores of 0.80, 0.85, and 0.81, respectively. The SFS algorithm selected 10 features for the highest-ranking model. In traditional statistical analysis, HR-CTV volume, Charlson Comorbidity Index, Length of Follow-Up, and D2cc - Rectum differed significantly between groups with and without grade 3 or higher toxicities.

Conclusions

Machine learning models were developed to predict grade 3 or higher toxicities, achieving satisfactory performance. Machine learning presents a novel solution to creating multivariable models for personalized radiation therapy care.
Association between longitudinal changes in left ventricular structure and function and 24-hour urinary free cortisol in essential hypertension
Authors: Cao Gao-Zhen , Huang Jia-Yi , Lin Qing-Shan , Wang Run , Wu Min , Chen Cong , Xiu Jian-Cheng , Yiu Kai-Hang
Published: October 2024

Objective:This study aimed to examine the relationships between 24-hour urinary cortisol levels (24h-UFC) and alterations in left ventricular (LV) structure and function in patients with essential hypertension.Methods:A prospective cohort study was conducted at the Hypertension Center of the University of Hong Kong-Shenzhen Hospital, including 315 patients with essential hypertension. Baseline 24h-UFC levels were measured, and echocardiographic assessments were performed to evaluate left ventricular mass (LVM), left ventricular ejection fraction (LVEF), and the E/e’ ratio (early diastolic trans-mitral flow velocity to early diastolic mitral annular velocity). Patients were divided into tertiles based on their 24h-UFC levels for comparative analysis. Statistical analyses were employed to examine the relationships between UFC levels and changes in cardiac parameters over the follow-up period.Results:Higher baseline 24h-UFC levels were significantly associated with greater increases in LVM and E/e’ during follow-up, indicating adverse LV remodeling and diastolic dysfunction. This correlation remained significant after adjusting for confounding factors such as age, gender, baseline systolic and diastolic blood pressure, heart rate, and their changes. Patients in the highest 24h-UFC tertile exhibited an increase in left ventricular hypertrophy (LVH) prevalence, whereas those in the lower tertiles showed a reduction.Conclusion:Elevated 24h-UFC levels are independently associated with adverse changes in LV structure and diastolic function in patients with essential hypertension.

Novelty and Relevance

What Is New?

This is the first study to elucidate the association between longitudinal changes in left ventricular structure and function and 24-hour urinary free cortisol (24h-UFC) in essential hypertension.

What Is Relevant?

This cohort study indicates that higher baseline 24h-UFC levels are significantly associated with greater increases in left ventricular mass (LVM) and the E/e’ ratio during the follow-up period, suggesting adverse left ventricular (LV) remodeling and diastolic dysfunction.

Clinical/Pathophysiological Implications?

This study provides novel insights into the role of cortisol in cardiovascular remodeling in hypertensive patients and may have significant implications for understanding the mechanisms underlying hypertensive heart disease.
Mid-life association between cardiovascular risk factors and cerebral blood flow in a multi-ethnic population
Authors: Vriend Esther M.C. , Dijsselhof Mathijs B.J. , Bouwmeester Thomas A. , Franco Oscar H. , Galenkamp Henrike , Collard Didier , Nederveen Aart J. , van den Born Bert-Jan H. , Mutsaerts Henk J.M.M.
Published: October 2024

Background

Cardiovascular (CV) risk factors are associated with cerebrovascular damage and cognitive decline in late life. However, it is unknown how different ethnic CV risk profiles are related to cerebral haemodynamics in mid-life. We aimed to investigate associations of CV risk factors with cerebral haemodynamics at two timepoints and examine the impact of ethnicity on these measures.

Methods

From the HELIUS study (53.0 years, 44.8% female), participants of Dutch (n=236), Moroccan (n=122), or South-Asian Surinamese (n=173) descent were included. Cerebral blood flow (CBF) and its spatial coefficient of variation (sCoV, marker of macrovascular efficiency) were obtained in both grey (GM) and white matter (WM). Associations of CV risk factors, WM hyperintensities (WMH), and carotid plaques with cerebral haemodynamics were investigated using linear regressions.

Results

CBF and sCoV differed per ethnicity. Only at the second visit associations were found, without an interaction with ethnicity; history of CV disease with lower GM CBF and higher WM sCoV, higher total cholesterol and lower WMH volume with lower WM CBF, smoking with higher WM sCoV, and higher SBP with lower GM sCoV.

Conclusions

These findings emphasise the need to further explore the longitudinal effects of midlife risk factors and cerebrovascular health, and its interaction with ethnicity.
Machine Learning Algorithms for Neurosurgical Preoperative Planning: A Comprehensive Scoping Review of the Literature
Authors: Bocanegra-Becerra Jhon E. , Sader Neves Ferreira Julia , Simoni Gabriel , Hong Anthony , Rios-Garcia Wagner , Mirahmadi Eraghi Mohammad , Castilla-Encinas Adriam M. , Colan Jhair Alejandro , Rojas-Apaza Rolando , Pariasca Trevejo Emanuel Eduardo Franco , Bertani Raphael , Lopez-Gonzalez Miguel Angel
Published: October 2024

Introduction

Preoperative neurosurgical planning is a keen step to avoiding surgical complications, reducing morbidity, and improving patient safety. The incursion of machine learning (ML) in this domain has recently gained attention, given the notable advantages in processing large data sets and potentially generating efficient and accurate algorithms in patient care.

Objective

To evaluate the evolving applications of ML algorithms in the preoperative planning of brain and spine surgery.

Methods

In accordance with the Arksey and O’Malley framework, a scoping review was conducted using three databases (Pubmed, Embase, and Web of Science). Articles that described the use of ML for preoperative planning in brain and spine surgery were included. Relevant data were collected regarding the neurosurgical field of application, patient baseline features, disease description, type of ML technology, study’s aim, preoperative ML algorithm description, and advantages and limitations of ML algorithms.

Results

Our search strategy yielded 7,407 articles, of which 8 studies (5 retrospective, 2 prospective, and 1 experimental study) satisfied the inclusion criteria. Clinical information from 518 patients (62.7% female; mean age: 44.8 years) was used for generating ML algorithms, including convolutional neural network (14.3%), logistic regression (14.3%), random forest (14.3%), and other algorithms (Table 1). Neurosurgical fields of applications included functional neurosurgery (37.5%), tumor surgery (37.5%), and spine surgery (25%). The main advantages of ML included automated processing of clinical and imaging information, selection of an individualized patient surgical approach and data-driven support for treatment decision-making. All studies reported technical limitations, such as long processing time, algorithmic bias, limited generalizability, and the need for database updating and maintenance.

Conclusion

ML algorithms for preoperative neurosurgical planning are being developed for efficient, automated, and safe treatment decision-making. Enhancing the robustness, transparency, and understanding of ML applications will be crucial for their successful integration into neurosurgical practice.
Developing policy to support sustainable diets in Aotearoa New Zealand with contributors
Authors: Kidd Bruce , Enright Hemi , McKerchar Christina , Cleghorn Christine
Published: October 2024

Aotearoa New Zealand (Aotearoa NZ) is an example of a high-income country with high environmental impacts and health consequences associated with its food system. These impacts can be partially addressed by enabling dietary transitions to healthy and sustainable diets. The EAT-Lancet Commission proposed an internationally acceptable reference diet to promote planetary health. We aimed to work with contributors to develop policy actions to support New Zealanders to transition to healthy sustainable diets. These policies were further examined according to the World Cancer Research Fund, NOURISHING and High Level Panel of Experts (HLPE) on Food Security and Nutrition Food System frameworks. Semi-structured interviews (13) and focus groups (6) were conducted with contributors from government agencies, industry, academics, community and rural and urban tangata whenua communities. All interviews and focus groups were first transcribed using Otter.aI then reviewed by the research team. Thematic analysis was used to identify and summarise each policy. 111 policies were suggested across the NOURISHING framework policy domains: 11 (10%) in behaviour change communication; 35 (32%) in the food environment; and 65 (59%) addressing the food system. Participants spoke of behaviour change communication policies of education, awareness campaigns, and workshops such as cooking classes. Food environment policies targeted supermarkets and food retail, local food environments, and government standards and regulations including food taxes and subsidies. Policies in the food system area looked at food waste, supporting local food production and government structures and support. Contributors identified policies that advocate and support planetary health.

Key policy insights

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The majority of policies identified by contributors focused on food systems and specifically food production

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Many contributors highlighted existing policies or initiatives already implemented locally and nationally but needed further support

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There is limited research demonstrating the effectiveness of policies and initiatives addressing sustainable food systems in Aotearoa New Zealand

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Funding, resources and research of existing local initiatives and policies supporting sustainable food systems in Aotearoa New Zealand and globally are urgently required
Outbreak ofLeishmania tropicaamongst militia members in a non-endemic district under conflict in the lowlands of Somali Region in Ethiopia
Authors: Abera Adugna , Tadesse Henok , Beyene Dereje , Geleta Desalegn , Abose Ebise , Kinde Solomon , Abdosh Mussie , Difabachew Hailemariam , Belachew Mahlet , Gire Abdulahi , Bishaw Tesfahun , Habtetsion Medhanye , Olani Zelalem , Eyelachew Endawoke , Birhanu Worku , Choukri Kaoutar , Coppens Jasmine , Tadese Gemechu , Haile Kebron , Bekele Henok , Abte Melkamu , Tollera Getachew , Hailu Mesay , Kebede Zeyede , van der Auwera Gert , Seife Fikre , Dujardin Jean-Claude , van Griensven Johan , Wolday Dawit , Embiale Wendemagegn , Pareyn Myrthe , Tasew Geremew
Published: October 2024

Following the emergence of a conflict, an outbreak of cutaneous leishmaniasis (CL) occurred in a non- endemic lowland area in the Somali Region in Ethiopia, raising public health concerns. All 1050 patients were militia members, immunologically naïve and displaced into a conflict area with a likely sylvatic transmission cycle. We identifiedLeishmania tropicaas the causative species, challenging the previous assumption thatL. aethiopicawas Ethiopia’s primary agent of CL. Notably, over 77% of patients had more than 10 lesions, a presentation atypical forL. tropicaelsewhere.Phlebotomus orientalisandP. sergenti, vectors for visceral leishmaniasis (VL) and CL in North Africa respectively, were captured. Further research is needed to explore the eco-epidemiology of the outbreak and the patient’s treatment responses. Insights will help develop management strategies to control this newly emerging form of CL, prevent its spread to other regions, and hybridize with Leishmania strains causing VL endemic.
The brain's "dark energy" puzzleupgraded: [18F]FDG uptake, delivery and phosphorylation, and their coupling with resting-state brain activity
Authors: Volpi Tommaso , Lee John J. , Vlassenko Andrei G. , Goyal Manu S , Corbetta Maurizio , Bertoldo Alessandra
Published: October 2024

The brain's resting-state energy consumption is expected to be mainly driven by spontaneous activity. In our previous work, we extracted a wide range of features from resting-state fMRI (rs-fMRI), and used them to predict [18F]FDG PET SUVR as a proxy of glucose metabolism. Here, we expanded upon our previous effort by estimating [18F]FDG kinetic parameters according to Sokoloff's model, i.e., Ki (irreversible uptake rate), K1 (delivery), k3 (phosphorylation), in a large healthy control group. The parameters' spatial distribution was described at a high spatial resolution. We showed that while K1 is the least redundant, there are relevant differences between Ki and k3 (occipital cortices, cerebellum and thalamus). Using multilevel modeling, we investigated how much of the regional variability of [18F]FDG parameters could be explained by a combination of rs-fMRI variables only, or with the addition of cerebral blood flow (CBF) and metabolic rate of oxygen (CMRO2), estimated from 15O PET data. We found that combining rs-fMRI and CMRO2 led to satisfactory prediction of individual Ki variance (45%). Although more difficult to describe, Ki and k3 were both most sensitive to local rs-fMRI variables, while K1 was sensitive to CMRO2. This work represents the most comprehensive assessment to date of the complex functional and metabolic underpinnings of brain glucose consumption.
Land-use changes impact root-fungal network connectivity in a global biodiversity hotspot
Authors: Carneiro de Melo Moura Carina , Guerrero-Ramirez Nathaly R. , Krashevska Valentyna , Polle Andrea , Siregar Iskandar Z. , Ballauff Johannes , Siregar Ulfah J. , Encinas-Viso Francisco , Bell Karen , Nevill Paul , Gailing Oliver
Published: October 2024

Cross-kingdom associations play a fundamental role in ecological processes. Yet our understanding of plant-fungal co-occurrences in tropical rainforests and the potential impacts of land-use change shaping species connections remains limited.

By using amplicon sequencing on DNA from roots and their associated fungal communities, we aim to understand the impact of rainforest transformation on the composition and structure of root-fungal ecological networks in human-modified landscapes in Sumatra, Indonesia.

Each land-use type supports a distinctive set of indicator species, which are organisms that reflect specific environmental conditions and can signal changes in ecosystem health. We observed a decline in the richness of plant species indicators and plant-fungal associations with increasing land-use intensification. Additionally, there is a turnover in root communities, shifting from native and endemic species in rainforests to non-native, generalist herbaceous species in rubber and oil palm plantations.

Plant-fungal connectivity significantly declined with increasing land-use intensification, suggesting that managed ecosystems may have weakened root-fungal interactions. Network analysis highlights the distinct responses of various fungal groups. For instance, arbuscular mycorrhizal fungi (AMF) showed fewer connections with modules linked to oil palm and rubber roots, indicating weakened root-fungal associations in monocultures. This aligns with the observed reduction in AMF diversity in converted land-use areas compared to forests, further reinforcing the negative impact of land-use practices in oil palm and rubber monocultures on AMF diversity.

Synthesis. Dimensioning the impacts of rainforest transformations belowground is constrained by our understanding of fungal functional guilds. Highly modified systems exhibited fewer connections, suggesting a dynamic restructuring of root-fungal relationships in response to land-use changes. Understanding the intricate interplay between plants and fungi in the face of land-use change can provide valuable information for conservation efforts, agricultural practices, and ecosystem management strategies aimed at promoting biodiversity, soil health, and ecosystem resilience in the context of changing environmental conditions. Moreover, it underscores the importance of communities’ networks in land-use planning and management decisions to support plant and fungal diversity in terrestrial ecosystems.
Tau accelerates tubulin exchange in the microtubule lattice
Authors: Biswas Subham , Grover Rahul , Reuther Cordula , Poojari Chetan S. , Shaebani M. Reza , Grünewald Mona , Zablotsky Amir , Hub Jochen S. , Diez Stefan , John Karin , Schaedel Laura
Published: October 2024

Microtubules are cytoskeletal filaments that exhibit dynamic tip instability and, as recent discoveries reveal, possess a dynamic lattice undergoing continuous tubulin loss and incorporation. In this study, we investigate the role of tau, a neuronal microtubule-associated protein (MAP) known for its stabilizing effects on microtubules, in modulating lattice dynamics. Using in vitro reconstitution, kinetic Monte Carlo modeling, and molecular dynamics simulations, we reveal that tau, despite lacking enzymatic activity, accelerates tubulin exchange within the lattice, particularly at topological defect sites. Tau appears to stabilize longitudinal tubulin–tubulin interactions while destabilizing lateral ones, thereby enhancing the mobility and repair of lattice defects. These results challenge the traditional view of tau as merely a stabilizer, uncovering its active role in dynamically modulating microtubule lattice structure.
Prediction and discovery of protein-protein direct interactions and stable complexes based on gene co-expression and co-evolution
Authors: Miglionico P. , Nemati Fard Lorenzo Amir , Gloeckner C.J. , Raimondi F.
Published: October 2024

In this study we employed a data-driven approach to explore the evolutionary and genetic determinants of protein direct interactions and stable complex formation in the human proteome. We found that simple co-evolutionary and co-expression metrics are highly informative of direct interactions and stable complexes. We used this information to train supervised binary classifiers to predict interactions either directly involved in the formation of a complex (as annotated in IntAct) or forming stable complexes (from Complex Portal). In the former task, our model was able to discriminate direct interactions with an AUROC=0.813, while in the latter it discriminated interaction forming stable complexes with an AUROC=0.964. In both cases, our approach outperformed String, that we employed as a baseline. Feature importance analysis revealed different contributions to the prediction of these distinct interaction types. Co-evolutionary features, in particular those referred to protein domains involved in interaction interfaces, are more important to discriminate direct interactions. On the other hand, co-expression features contributed more to the prediction of stable complexes. From these pairwise predictions we generated a proteome-wide network that we clustered to assess the recovery of known complexes from Complex Portal within network communities. We were able to recover known complexes at a higher accuracy compared to other approaches.

In conclusion, we propose a new method able to discriminate direct interactions as well as forming stable complexes. This method can be used to stratify molecular interaction networks, as well as to perform discovery of new functional complexes at a proteome-wide scale.
Conservation of mRNA operon formation in the control of the heat shock response in mammalian cells
Authors: Pataki Emese , Gerst Jeffrey E.
Published: October 2024

Prokaryotic organisms rely on polycistronic transcription (i.e.operons) to express multiple mRNAs from a single promoter, enabling rapid and robust responses to stimuli. In yeast, a similar mechanism exists whereby monocistronic mRNAs are selectively assembled into ribonucleoprotein particles, termed RNA operons or transperons, to regulate the expression of genes involved in the same biological process. One example is the heat shock protein (HSP) transperon that confers the eukaryotic heat shock response (HSR), a conserved cellular mechanism that enables organisms to cope with proteotoxic stress. As it was unknown whether transperons exist in higher eukaryotes, we examined whether a similar mechanism operates in mammalian cells. Using both single-molecule fluorescentin situhybridization and RNA pulldown techniques, we show that mammalian HSP mRNAs colocalize and multiplex to form mRNA assemblages during heat stress. These RNP assemblies are dependent on heat shock factor 1 transcriptional regulator and involve both inter- and intrachromosomal interactions among the HSP genes. Bioinformatic analysis identifies a conserved sequence motif within the coding regions of HSP mRNAs and mutational studies in yeast suggest that it is critical for mRNA multiplexing and the HSR. These findings emphasize the evolutionarily conserved nature of heat shock gene regulation across species and suggest that mammalian cells employ RNA operons/transperons in organizing their heat shock response.
White Tea Mitigates Obesity-Related Metabolic Disorders Through Apelin and Insulin Modulation in Rats
Authors: Sümer Ayşegül , Demirtaş Öznur , Pınarbaş Esra , Kutlu Eda Yılmaz , Kılıç Hülya
Published: October 2024

Obesity, a prevalent global health issue, is influenced by genetic, metabolic, environmental, and behavioral factors, often leading to serious complications like type 2 diabetes, cardiovascular diseases, and reduced life expectancy. Recent studies have highlighted apelin, a bioactive peptide, for its significant role in obesity and related metabolic disorders. Apelin, primarily found in adipose tissue, regulates appetite, energy expenditure, and insulin sensitivity, making it a promising target for antiobesity treatments. Concurrently, tea, especially white tea, rich in bioactive compounds, has shown potential health benefits, including antiobesity effects. This study investigates the impact of white tea on weight gain, glucose metabolism, and lipid metabolism by analyzing its effects on apelin-13, apelin-36, and insulin levels in a high-fat diet (HFD)-induced obesity model in rats. Thirty-two male Sprague Dawley rats were divided into four groups: control, HFD, HFD+orlistat, and HFD+white tea. Over 13 weeks, the HFD groups received their respective treatments while being monitored for weight gain and metabolic changes. Results indicated that the HFD group exhibited significant weight gain and elevated cholesterol levels compared to the control. White tea-treated rats showed reduced weight gain and lower cholesterol levels, suggesting its antiobesity properties. Apelin-13 levels were significantly lower in the HFD group, while white tea mitigated this effect, highlighting its potential role in modulating apelin levels and improving insulin sensitivity. The findings support the hypothesis that white tea can be an effective antiobesity agent, offering a safer, natural alternative to conventional treatments. Further research is warranted to elucidate the precise mechanisms underlying these beneficial effects.
Transparent and robust Artificial intelligence-driven Electrocardiogram model for Left Ventricular Systolic Dysfunction
Authors: Lee Min Sung , Jang Jong-Hwan , Kang Sora , Han Ga In , Yoo Ah-Hyun , Jo Yong-Yeon , Son Jeong Min , Kwon Joon-myoung , Lee Sooyeon , Lee Ji Sung , Lee Hak Seung , Kim Kyung-Hee
Published: October 2024

Heart failure (HF) is an escalating global health concern, worsened by an aging population and limitations in traditional diagnostic methods like electrocardiograms (ECG). The advent of deep learning has shown promise for utilizing 12-lead ECG models for the early detection of left ventricular systolic dysfunction (LVSD), a crucial HF indicator. This study validates the AiTiALVSD, an AI/machine learning-enabled Software as a Medical Device, for its effectiveness, transparency, and robustness in detecting LVSD. Conducted at Mediplex Sejong Hospital in the Republic of Korea, this retrospective single-center cohort study involved patients suspected of LVSD. The AiTiALVSD model, which is based on a deep learning algorithm, was assessed against echocardiography findings. To improve model transparency, the study utilized Testing with Concept Activation Vectors (TCAV) and included clustering analysis and robustness tests against ECG noise and lead reversals. The study involved 688 participants and found AiTiALVSD to have a high diagnostic performance, with an AUROC of 0.919. There was a significant correlation between AiTiALVSD scores and left ventricular ejection fraction values, confirming the model’s predictive accuracy. TCAV analysis showed the model’s alignment with medical knowledge, establishing its clinical plausibility. Despite its robustness to ECG artifacts, there was a noted decrease in specificity in the presence of ECG noise. AiTiALVSD’s high diagnostic accuracy, transparency, and resilience to common ECG discrepancies underscore its potential for early LVSD detection in clinical settings. This study highlights the importance of transparency and robustness in AI/ML-based diagnostics, setting a new benchmark in cardiac care.
P450-Catalyzed Biaryl Macrocyclization of Leaderless Ribosomal Peptides
Authors: Liu Runze , Ren Hongyu , Wu Gengfan , He Bei-Bei , Pang Cuiping , Shen Zhuanglin , Liu Jing , Song Zhi-Man , Zhou Jiahai , Li Yong-Xin
Published: October 2024

Macrocyclic peptides, an intriguing class of molecules, embody promising frameworks for the development of chemical probes and prospective therapeutic agents. However, the lack of an established wide-substrate scope synthesis methodology has made it challenging to achieve both efficiency and selectivity simultaneously. P450-catalyzed ribosomal synthesized and post-translational modification peptides (RiPPs) are a new family of macrocyclic peptides with typical biaryl crosslinks. In this study, we report the discovery of a RiPP-modified P450 macrocyclase, GpeC, which natively catalyzes the biaryl C(sp2)-C(sp2) crosslink of tryptophan-tyrosine in a tetrapeptide module. Unlike most previously documented P450-RiPPs that possess a substantial leader peptide region, hindering biocatalytic applications, our P450 GpeC exhibits catalytic potential with leaderless precursor peptides and a wide substrate tolerance, highlighting its adaptability and potential for creating diverse macrocyclic structures. The crystal structure of GpeC, combined with in silico calculations and site-directed mutagenesis, provides strong evidence for the extreme flexibility of intra-cyclic amino acids within the biaryl-cyclized tetrapeptide. This flexibility enables the substitution of any of the other 19 amino acids, indicating that GpeC is a robust and adaptable catalyst for biaryl cyclization, providing a valuable resource for the biocatalytic synthesis of complex macrocyclic compounds.
Faecalibacterium prausnitziiinduces an anti-inflammatory response and a metabolic reprogramming in human monocytes
Authors: Danne Camille , Creusot Laura , de Oliveira Formiga Rodrigo , Marquet Florian , Sedda Delphine , Hua Laura , Ruffié Pauline , Pham Hang-Phuong , Salgueiro Iria Alonso , Brot Loic , Michel Marie-Laure , Langella Philippe , Lefevre Jérémie H. , Sokol Harry , Rolhion Nathalie
Published: October 2024

Background and aims

Faecalibacterium prausnitzii, a highly abundant bacterium in the human gut microbiota, has been linked to overall health and is decreased in several pathological conditions, such as Inflammatory Bowel Disease (IBD).F. prausnitziihas shown anti-inflammatory properties in human and mouse models, notably through the induction of IL-10 signaling. Here, we investigated which cell types from human blood and intestinal tissue are responsible for producing IL-10 induced byF. prausnitzii, and providing the first mechanistic insights.

Methods

Immune cells isolated from human blood and intestinal lamina propria of patients with IBD and non-inflamed controls, were stimulated with eitherF. prausnitziiEXL01 strain orEscherichia colilipopolysaccharide (LPS) and analysed by Legendplex, ELISA, flow cytometry, RNA-sequencing (RNAseq), and Seahorse technology.

Results

F. prausnitziiEXL01 strain induced the direct and dose-dependent production of IL-10 in CD14+monocytes from the systemic circulation and intestinal tissue of IBD patients and non-inflamed controls, without inducing a pro-inflammatory response as compared to LPS stimulation. RNAseq analysis corroborated these results and revealed thatF. prausnitziiEXL01 strain differentially affects cell energy metabolism compared to LPS. The anti-inflammatory response induced byF. prausnitziiin monocytes was dependent on mitochondrial respiration.

Conclusion

F. prausnitziiinduces an anti-inflammatory response and rewires energy metabolism in human monocytes, which might explain its beneficial impact on intestinal inflammation and human health in general. These results provide new insight into the mechanisms underlying the anti-inflammatory effects ofF. prausnitziiand are crucial for a better understanding of its potential use in the treatment of IBD.
Genomic and evolutionary evidence for drought adaptation of grass allopolyploid Brachypodium hybridum
Authors: Wang Yuanyuan , Chen Guang , Zeng Fanrong , Deng Fenglin , Yang Zujun , Han Zhigang , Xu Shengchun , Nevo Eviatar , Catalán Pilar , Chen Zhong-Hua
Published: October 2024

Climate change increases the frequency and severity of drought worldwide, threatening the environmental resilience of cultivated grasses. However, the genetic diversity in many wild grasses could contribute to the development of climate-adapted varieties. Here, we elucidated the impact of polyploidy on drought response using allotetraploidBrachypodium hybridum(Bh) and its progenitor diploid speciesB. stacei(Bs). Our findings suggest that progenitor species’ genomic legacies resulting from hybridization and whole-genome duplications conferred greater ecological adaptive advantages to Bh over Bs. Genes related to stomatal regulation and immune response from S-subgenomes were under positive selection during speciation, underscoring their evolutionary importance in adapting to environmental stresses. Biased expression in polyploid subgenomes [B. stacei-type (Bhs) andB. distachyon-type (Bhd)] significantly influenced differential gene expression, with the dominant subgenome exhibiting more differential expression.B. hybridumadapted a drought escape strategy characterized by higher photosynthetic capacity and lowerWUEithan Bs, driven by a highly correlated co-expression network involving genes in the circadian rhythm pathway. In summary, our study showed the influence of polyploidy on ecological and environmental adaptation and resilience in modelBrachypodiumgrasses. These insights hold promise for informing the breeding of climate-resilient cereal crops and pasture grasses.
Targeting DNA-PK is a highly conserved poxvirus innate immune evasion mechanism
Authors: Oliveira Marisa , Manna Paul T. , Ribeiro-Rodrigues Damaris , Allport Thomas , Wagner Emma , Brooks Heather , Skinner Michael A. , Giotis Efstathios S. , Chaplin Amanda K. , Guabiraba Rodrigo , Bryant Clare E. , Ferguson Brian J.
Published: October 2024

The sensing of viral nucleic acid by pattern recognition receptors (PRRs) is essential for initiation of a type-I interferon response against infection. Intracellular DNA sensing PRRs are responsible for initiating innate immune responses to poxviruses and other double-stranded DNA viruses. Poxviruses, in turn, encode an armoury of immunomodulators that inhibit this host defence mechanism. DNA-dependent protein kinase (DNA-PK) is an essential component of the cGAS/STING-dependent viral DNA sensing machinery that leads to the initiation of a type-I interferon response during poxvirus infection. Poxviruses counter this host sensing mechanism using the C4/C10 family of proteins that target DNA-PK, interfering with its ability to bind viral DNA. Although the DNA-PK complex, known also for its role in double strand break repair, is conserved across multiple taxa, its function in innate immunity outside mammals is unexplored. Here we analysed the contribution of DNA-PK to poxvirus DNA sensing in chickens, a species that is evolutionarily distant from mammals, but that is also infected by poxviruses. We found that DNA-PK functions as a DNA sensor in chickens, and this process is countered by C4/C10 family members found in fowlpox virus. This host/pathogen interaction is conserved across a broader range of species than other mechanisms of poxvirus antagonism of innate immune sensing, which may reflect the difficulty of the host in evolving escape mechanisms that interfere with a protein that is essential for maintenance of genomic stability.
The TWEAK/Fn14 signaling promotes skeletal muscle wasting during cancer cachexia
Authors: Tomaz da Silva Meiricris , Roy Anirban , Vuong Anh Tuan , Joshi Aniket S. , Josphien Cristeena , Trivedi Meghana V , Hindi Sajedah M , Narkar Vihang , Kumar Ashok
Published: October 2024

Cachexia is an involuntary loss of body weight mostly due to skeletal muscle wasting. The proinflammatory cytokine TWEAK and its receptor Fn14 constitute a major signaling system that regulates skeletal muscle mass in diverse conditions. However, the role of TWEAK/Fn14 system in the regulation of skeletal muscle mass during cancer-induced cachexia remains poorly understood. In this study, we demonstrate that the levels of Fn14, but not TWEAK, are induced in skeletal muscle of multiple mouse models of cancer cachexia. Targeted deletion of Fn14 inhibits muscle wasting and gene expression of multiple components of the ER stress-induced unfolded protein response (UPR) in the KPC mouse model of pancreatic ductal adenocarcinoma (PDAC) cancer cachexia. The TWEAK/Fn14 signaling activates PERK and IRE1α arm of the UPR and inhibits protein synthesis in cultured primary myotubes. Inhibition of PERK using pharmacological or molecular approaches improves protein synthesis and inhibits atrophy in TWEAK-treated cultured myotubes. Silencing of Fn14 in KPC cells prior to their inoculation in pancreas of mice also attenuates tumor growth without having any significant effect on muscle atrophy. The knockdown of Fn14 inhibits proliferation, migration, and invasion of cultured KPC cells. Finally, our results demonstrate that targeted ablation of Fn14 also attenuates muscle atrophy in the Lewis lung carcinoma model of cancer cachexia. Altogether, our study provides initial evidence that the inhibition of TWEAK/Fn14 signaling can prevent tumor growth and skeletal muscle wasting during cancer-induced cachexia.
Neuropeptide-dependent spike time precision and plasticity in circadian output neurons
Authors: Chong Bryan , Kumar Vipin , Nguyen Dieu Linh , Hopkins Makenzie A. , Ferry Faith S. , Spera Lucia K. , Paul Elizabeth M. , Hutson Anelise N. , Tabuchi Masashi
Published: October 2024

Circadian rhythms influence various physiological and behavioral processes such as sleep-wake cycles, hormone secretion, and metabolism. InDrosophila, an important set of circadian output neurons are called pars intercerebralis (PI) neurons, which receive input from specific clock neurons called DN1. These DN1 neurons can further be subdivided into functionally and anatomically distinctive anterior (DN1a) and posterior (DN1p) clusters. The neuropeptide diuretic hormones 31 (Dh31) and 44 (Dh44) are the insect neuropeptides known to activate PI neurons to control activity rhythms. However, the neurophysiological basis of how Dh31 and Dh44 affect circadian clock neural coding mechanisms underlying sleep inDrosophilais not well understood. Here, we identify Dh31/Dh44-dependent spike time precision and plasticity in PI neurons. We first find that a mixture of Dh31 and Dh44 enhanced the firing of PI neurons, compared to the application of Dh31 alone and Dh44 alone. We next find that the application of synthesized Dh31 and Dh44 affects membrane potential dynamics of PI neurons in the precise timing of the neuronal firing through their synergistic interaction, possibly mediated by calcium-activated potassium channel conductance. Further, we characterize that Dh31/Dh44 enhances postsynaptic potentials in PI neurons. Together, these results suggest multiplexed neuropeptide-dependent spike time precision and plasticity as circadian clock neural coding mechanisms underlying sleep inDrosophila.