bluuebunny/crossref_metadata_2025 huggingface dataset:
An ER-resident lipid scramblase is crucial for biogenesis and function of apicomplexan parasite secretory organelles
Authors: Reddy G. Srinivas , Gorde Somesh M. , Saxena Kanika , Behera Manash Kumar , Deshmukh Abhijit S , Sijwali Puran Singh
Published: November 2024

Apicomplexan parasites, includingPlasmodium falciparumandToxoplasma gondii, contain specialized secretory organelles such as micronemes, rhoptries, and dense granules, which are essential for parasite motility, host cell invasion, development, and egress. DedA superfamily proteins are implicated in lipid mobilization, which is a key requirement for organelle biogenesis. Herein, we identified and investigated the vacuole membrane protein 1 (VMP1), a DedA superfamily member, ofP. falciparum(PfVMP1) andT. gondii(TgVMP1). PfVMP1 and TgVMP1 are ER-localized lipid scramblases. TgVMP1 depletion adversely affected parasite development, motility, host cell invasion, and egress. These phenotypes were consistent with impaired rhoptry and dense granule biogenesis, and decreased secretion of micronemes, rhoptries, and dense granules in TgVMP1-depleted parasites, indicating a crucial role for TgVMP1 in the biogenesis and function of these organelles. TgVMP1 depletion impaired lipid droplet homeostasis and ER organization. Restoration of the ER-localized lipid scramblase by complementing TgVMP1-depleted parasites with PfVMP1 or a homolog as distant as human VMP1 rescued the depleted parasites, indicating their functional conservation and a crucial role for ER-resident lipid scramblase activity in the biogenesis and function of secretory organelles. The essentiality of TgVMP1 for parasite development and likely functional conservation of apicomplexan VMP1 proteins highlight their drug-target potential.
Results of a survey of the use of perfusion parameters as a selection tool for pumped deceased donor kidneys in the Organ Procurement Organizations of North America
Authors: Heedfeld Veerle , Jochmans Ina
Published: November 2024

Background

Hypothermic machine perfusion (HMP) has become a standard method for preserving deceased donor kidneys, offering advantages over static cold storage. Perfusion parameters like renal vascular resistance (RR) have been explored as potential decision-making tools for kidney transplantability, but their clinical use remains unclear.

Aim

We aimed to investigate the use of perfusion parameters in decision-making regarding the acceptance of pumped deceased donor kidneys among Organ Procurement Organizations (OPOs) in the USA and Canada.

Methods

An anonymous, internet-based survey was sent to 69 OPOs in the USA and Canada, collecting data on the use of HMP, perfusion parameters, and thresholds for transplantability decisions. Descriptive statistics were used for analysis.

Results

Of the 67 OPOs contacted, 15 (22%) responded, with 13 complete responses (87%). All OPOs used HMP, with 93% perfusing both donation after brain death and circulatory death kidneys. While 97% of OPOs used perfusion parameters in decision-making, none relied solely on these parameters. Two OPOs (15%) did not use them at all, while six OPOs (46%) considered them with other data or on a case-by-case basis. Only one OPO (9%) reported using specific thresholds for perfusion parameters, applying flow ≥100 mL/min, resistance <0.3 mmHg/mL/min, and pressure between 15–35 mmHg.

Conclusion

HMP is widely used, but substantial variability exists in the use of perfusion parameters for transplant decisions. Most OPOs do not rely on these parameters alone and lack standardized thresholds, though specific thresholds are still used.
Willingness of urban formal sector workers to support a community-based health insurance scheme in Ethiopia
Authors: Mebratie Anagaw Derseh , Shamebo Dessalegn , Alemu Getnet , Shigute Zemzem , Bedi Arjun S.
Published: November 2024

Introduction

The Ethiopian health system is primarily financed through household out-of-pocket expenditure and financial support from donors. High user fees lead to catastrophic health spending and limited use of services. To promote healthcare-seeking behavior and provide financial protection through enhanced domestic financing, the Ethiopian government has designed two types of health insurance schemes. These are a Community-Based Health Insurance (CBHI) scheme for the informal sector and the yet to be implemented Social Health Insurance (SHI) scheme for the formal sector. In the short run, these schemes are expected to function independently. However, in the long run it is anticipated that they will be combined, thereby pooling risk. Combining the two schemes requires solidarity across the two groups targeted by each of the schemes. Since it is likely that formal sector employees may have to bear the cost of subsidizing the CBHI scheme, this study aims to assess the extent to which formal sector employees are willing to support the CBHI scheme.

Methods

The paper is based on a survey of 1,919 formal sector employees and pensioners residing in the major administrative regions of the country. A survey experiment was used to elicit support for the CBHI scheme. Respondents were randomly allocated to one of five cases. These cases differed in terms of the information provided regarding the source of the CBHI subsidy and the benefits associated with the CBHI. Support for CBHI was assessed using descriptive statistics, binary and ordered logit models.

Results

There is strong support from urban formal sector employees for the CBHI scheme. Regardless of the scenario presented, and despite some regional variation, the key result is that at least 66% of the surveyed participants, adjusting for non-response, supported the CBHI scheme. Good knowledge of insurance increased support while existing access to health insurance lowered it.

Conclusion

The study provides strong evidence of solidarity and the willingness of formal sector employees to support the CBHI scheme. While this bodes well for the sustained expansion of the CBHI, it is ironic, as formal sector employees are resisting the introduction of the SHI. This reluctance stems from concerns about the costs and skepticism of the benefits of the proposed SHI, whereas the positive outcomes associated with the CBHI are widely known.
Time-to-event prediction in ALS using a landmark modeling approach, using the ALS Natural History Consortium Dataset
Authors: Schneck David , Arguedas Andres , Xenopoulos-Oddsson Annette , Arcila-Londono Ximena , Lunetta Christian , Wymer James , Olney Nicholas , Gwathmey Kelly , Ajroud-Driss Senda , Hayat Ghazala , Heiman-Patterson Terry , Cerri Federica , Fournier Christina , Glass Jonathan , Sherman Alex , Fiecas Mark , Walk David
Published: November 2024

Background and Objectives

Times to clinically relevant events are a valuable outcome in observational and interventional studies, complementing linear outcomes such as functional rating scales and biomarkers. In ALS, there are several clinically relevant events. We developed dynamic prediction models for several of these times to events that can be used for clinical trial modeling and personal planning.

Methods

Landmark time-to-event analysis was implemented to determine the effect of patient characteristics on disease progression. Longitudinal data from 1557 participants in the ALS Natural History Consortium dataset were used. Five outcomes in the ALS disease progression were considered: loss of ambulation, loss of speech, gastrostomy, non-invasive ventilation (NIV) use, and continuous NIV use. Covariates in our models include age at diagnosis, sex, onset location, riluzole use, diagnostic delay, ALSFRS-R scores at the landmark time, and ALSFRS-R rates of change from baseline. Internal and external validation techniques were used.

Results

For each of our models and landmark times, we present risk prediction intervals for random sets of patient characteristics. We demonstrate our models’ application for an individual’s personal predicted time-to-event. Our internal and external validation metrics indicate good concordance and overall performance. The time to loss of speech models perform the best for each metric in terms of both internal and external validation.

Discussion

Landmarking is an efficient, individualized risk prediction model that is intuitive for both clinicians and patients. Importantly, landmarking can be used for clinical trial modeling, personal planning, and development of real-world evidence of the impacts of treatment interventions.
Neural synchrony in the pain connectome predicts chronic pain severity and interactions with mental health outcomes: A transdiagnostic study using magnetoencephalography and multivariate modeling
Authors: Saberi Majid , Ventresca Matthew , Zamyadi Rouzbeh , Zhang Jing , Vartanian Oshin , Jetly Rakesh , Bhat Venkat , Rhind Shawn G , Don Richardson J , Dunkley Benjamin T
Published: November 2024

Chronic pain is a pervasive condition that involves complex neurobiological mechanisms and frequently co-occurs with mental health challenges such as anxiety, depression, and posttraumatic stress disorder (PTSD), interacting significantly with psychiatric outcomes. Despite its prevalence, the neural mechanisms of chronic pain and its interactions with mental health remain poorly understood – however, functional brain imaging studies suggest the “pain connectome”, a collection of regions amongst numerous brain networks, plays a role in mediating the subjective perception of pain, and serves aspects of psychopathology. Here, we tested whether neural synchrony, a key mechanism in brain network communication, was predictive of self-reported chronic pain severity in a group of Canadian Armed Forces (CAF) service members and Veterans (n = 99) and examined if brain network functioning within the pain connectome interacts with symptoms of mental health challenges. We applied a 5-minute eyes-open resting-state magnetoencephalography (MEG) paradigm combined with multivariate modelling using partial least squares regression (PLSR). MEG is a powerful electrophysiological technique for imaging neural activity, including synchrony and network interactions, and PLSR allows exploration of complex multivariate data with high dimensionality to extract primary and interacting effects of interest in brain data. Pain severity was moderately correlated with the continuum of depression, anxiety, and PTSD symptoms, with mental health outcomes highly correlated between each other. We identified significant positive and negative associations between neural synchrony in the pain connectome and chronic pain severity. Beta oscillations were primarily related to pain severity and showed little-to-no interaction with mental health outcomes. Similarly, theta band synchrony exhibited a more specific and prominent association with the pain-anxiety interaction. Conversely, high frequency gamma synchrony was associated with chronic pain severity and showed significant effects for pain-anxiety, pain-depression, and pain-PTSD interactions. Additionally, predictive modeling using machine learning revealed that cross-spectral synchrony could reliably predict chronic pain severity in individual cases, suggesting it as a robust neurobiological marker for chronic pain. It also demonstrated moderate predictive accuracy in indexing comorbid interactions between pain and mental health. Our findings show that complex, multidimensional patterns of neural synchrony in the pain connectome mediate both chronic pain intensity and its interaction with mental health, offering new avenues for targeted and personalized therapeutic interventions and objectively tracking treatment efficacy.
Cardiac magnetic resonance markers of pre-clinical hypertrophic and dilated cardiomyopathy in genetic variant carriers
Authors: Croon Philip M , van Vugt Marion , Allaart Cornelis P , Ruijsink Bram , Elliott Perry M , Asselbergs Folkert W , Khera Rohan , Bezzina Connie R , Winter Michiel , Schmidt Amand Floriaan
Published: November 2024

Background. Patients with hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM) exhibit structural and functional cardiac abnormalities. We aimed to identify imaging biomarkers for pre-clinical cardiomyopathy in healthy individuals carrying cardiomyopathy-associated variants (G+). Methods. We included 40,169 UK biobank participants without cardiac disease who had cardiac magnetic resonance imaging (CMR) measurements and whole exome sequencing. We first validated 22 CMR measurements by associating them with incident atrial fibrillation (AF) or heart failure (HF). We subsequently assessed associations of these measurements with HCM or DCM G+, or specific genes, utilising generalised linear models conditional on cardiac risk factors. Results. Thirteen CMR measurements were associated with incident AF and fifteen with HF. These included left-ventricular (LV) ejection fraction (EF; hazard ratio [HR] 0.61, 95% confidence interval [95%CI] 0.54; 0.69) for HF and indexed maximum left atrial volume (LA-Vi max; HR1.47, 95%CI 1.29; 1.67) for AF. Five measurements associated with HCM G+, amongst which right ventricular (RV) end-systolic volume (RV-ESV; OR 0.62, 95%CI 0.53; 0.74), RV-EF (OR 1.36, 95%CI 1.19; 1.55), and right atrial EF (OR 1.22, 95%CI 1.08; 1.39). All associations overlapping with incident disease and HCM had opposite effect directions, such as RV-ESV with HF (OR 1.22, 95%CI 1.07; 1.40). Two CMR measurements associated with DCM G+: LV-ESVi (OR 1.35, 95%CI 1.15; 1.58) and LV-EF (OR 0.75, 95%CI 0.64; 0.88). Due to heterogeneity, we explored associations with individual cardiomyopathy genes, finding MAPSE associated withTTNandTNNT2, and LA pump and RA-EF associated withMYH7. Conclusion. We identified right heart CMR measurements associated with HCM G+ in healthy individuals, indicating early compensation of cardiac function. LV measurements were associated with DCM G+, and the CMR associations varied across individual DCM genes, suggesting distinct clinical pathophysiology.
GOOGLE TRENDS IN THE DIAGNOSIS OF METEOSENSITIVITY
Authors: Yarovaya Ksenia , Hnatiuk Iryna , Solodovnikova Yuliia , Son Anatoliy
Published: November 2024

Introduction

Primary headache disorders, including tension-type headaches (TTH) and migraines, are highly prevalent and pose a significant socio-economic burden. Environmental triggers, such as weather changes, are commonly believed to provoke these headaches.

Methods

This study aims to explore the role of geomagnetic activity as a potential trigger for TTH and migraines. Using Google Trends data, we tracked public interest in the search terms “migraine” and “headache” in Ukraine from 2019 to 2023. We analyzed the Ap index, which measures geomagnetic activity, alongside the search data to explore potential correlations.

Results

A total of 261 observations were made. The analysis revealed a negative correlation between the popularity of search queries for “migraine” and “headache” and geomagnetic activity, with increased search interest during periods of low geomagnetic activity. TTH patients were found to be more sensitive to low geomagnetic activity compared to those with migraines, suggesting different pathophysiological mechanisms between these two types of headaches. While the correlation is statistically significant, it remains relatively weak, indicating that geomagnetic fluctuations may contribute to headache triggers but are not the sole factor.

Conclusions

The findings suggest a potential link between geomagnetic activity and the incidence of primary headaches, with TTH being more responsive to these fluctuations than migraines. The study underscores the need for further research into the impact of geomagnetic activity on human health and headache disorders.

What is already known on this topic

Primary headache disorders, such as tension-type headaches (TTH) and migraines, are commonly triggered by environmental factors, but the role of geomagnetic activity remains underexplored despite its known effects on human health, like circadian rhythms and blood pressure.

What this study adds

This study identifies a significant negative correlation between low geomagnetic activity and increased public interest in headache-related terms, suggesting that geomagnetic fluctuations may act as environmental triggers for headaches, particularly TTH. It highlights distinct sensitivities between TTH and migraines to geomagnetic changes and demonstrates the utility of Google Trends as a tool for exploring public health patterns related to environmental factors.

How this study might affect research, practice or policy

This study highlights geomagnetic activity as a potential environmental trigger for primary headaches, encouraging further research into its role and distinct impacts on TTH and migraines. It underscores the utility of tools like Google Trends for public health surveillance, offering insights for healthcare practices and policy development to better address headache prevention.
Determining the role of lifestyle factors in healthy cognitive preservation in SuperAgers: A systematic review
Authors: Watson Philippa , Smith Megan , Koychev Ivan , Gallacher John , Bauermeister Sarah
Published: November 2024

Background

A subset of older adults, known as SuperAgers (SAs), exhibit exceptional resilience to these effects, displaying cognitive abilities at the same level or exceeding those 20-30 years younger. To date however, there is little understanding as to which factors may be responsible for SA enhanced cognitive abilities in old age. This systematic review aimed to identify and evaluate the evidence for an association between lifestyle factors and SA status.

Methods

A systematic literature search in accordance with the PRISMA guidelines was conducted across MedLine, Embase, Ovid, Global Health, APA PsychArticles, and PsycINFO from inception to 06/11/23 of studies investigating the link between SA status and one or more lifestyle factors.

Results

A systematic search identified 13 studies which met the inclusion criteria. Eleven investigated the relationship between two or more lifestyle factors with the most common lifestyle factor examined being mental health followed by physical activity, social engagement and smoking. Mixed results were observed across the included studies while social engagement and mental health emerged as the most likely lifestyle factors to be positively associated with SA status, there was considerable heterogeneity in the measures used to assess different lifestyle factors.

Conclusion

No clear conclusions could be drawn as to which lifestyle factors are associated with SA status due to scarcity of studies and heterogeneity in the measurement of different lifestyle factors.
Machine learning for predicting severe dengue, Puerto Rico
Authors: Madewell Zachary J. , Rodriguez Dania M. , Thayer Maile B. , Rivera-Amill Vanessa , Paz-Bailey Gabriela , Adams Laura E. , Wong Joshua M.
Published: November 2024

Background

Distinguishing between non-severe and severe dengue is crucial for timely intervention and reducing morbidity and mortality. Traditional warning signs recommended by the World Health Organization (WHO) offer a practical approach for clinicians but have limitations in sensitivity and specificity. This study evaluates the performance of machine learning (ML) models compared to WHO- recommended warning signs in predicting severe dengue among laboratory-confirmed cases in Puerto Rico.

Methods

We analyzed data from Puerto Rico’s Sentinel Enhanced Dengue Surveillance System (May 2012–August 2024), using 40 clinical, demographic, and laboratory variables. Nine ML models, including Decision Trees, K-Nearest Neighbors, Naïve Bayes, Support Vector Machines, Artificial Neural Networks, AdaBoost, CatBoost, LightGBM, and XGBoost, were trained using 5-fold cross-validation and evaluated with area under the receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). A subanalysis excluded hemoconcentration and leukopenia to assess performance in resource-limited settings. An AUC-ROC value of 0.5 indicates no discriminative power, while a value closer to 1.0 reflects better performance.

Results

Among the 1,708 laboratory-confirmed dengue cases, 24.3% were classified as severe. Gradient boosting algorithms achieved the highest predictive performance, with AUC-ROC values exceeding 94% for CatBoost, LightGBM, and XGBoost. Feature importance analysis identified hemoconcentration (≥20% increase during illness or ≥20% above baseline for age and sex), leukopenia (white blood cell count <4,000/mm³), and timing of presentation to a healthcare facility at 4–6 days post-symptom onset as key predictors. Excluding hemoconcentration and leukopenia did not significantly affect model performance. Individual warning signs like abdominal pain and restlessness had sensitivities of 79.0% and 64.6%, but lower specificities of 48.4% and 59.1%, respectively. Combining ≥3 warning signs improved specificity (80.9%) while maintaining moderate sensitivity (78.6%), resulting in an AUC-ROC of 74.0%.

Conclusions

ML models, especially gradient boosting algorithms, outperformed traditional warning signs in predicting severe dengue. Integrating these models into clinical decision-support tools could help clinicians better identify high-risk patients, guiding timely interventions like hospitalization, closer monitoring, or the administration of intravenous fluids. The subanalysis excluding hemoconcentration confirmed the models’ applicability in resource-limited settings, where access to laboratory data may be limited.
Multicountry genomic analysis underscores regional cholera spread in Africa
Authors: Mboowa Gerald , Matteson Nathaniel Lucero , Tanui Collins Kipngetich , Kasonde Mpanga , Kamwiziku Guyguy Kusanzangana , Akanbi Olusola Anuoluwapo , Chitio Jucunú Johane Elias , Kagoli Mathews , Essomba René Ghislain , Ayitewala Alisen , Ssewanyana Isaac , Ngo Bitoungui Valentina Josiane , Amuri Adrienne Aziza , Azman Andrew S , Babatunde Olajumoke Atinuke , Akenji Blaise Mboringong , Broban Anaïs , Malembaka Espoir Bwenge , Ongole Francis , Chukwu Chimaobi Emmanuel , Ismael Nália , Kapona Otridah , Laurindo Osvaldo , Mbala Placide Kingebeni , Etoundi Mballa Georges Alain , Miambo Imelda Carlos Zulfa , Mwanyongo Alex Ansaye , Najjuka Grace , Mutale Joseph , Musonda Kunda , Niyonzima Allan Muruta , Nyenje Mirriam Ethel , Popoola Michael , Shempela Doreen Mainza , Medi Sike Christiane , Sitoe Sofião Manjor , Wanjohi Dorcas Waruguru , Welo Placide Okitayemba , Yelewa Mtisunge , Yennan Sebastian , Ziba Lucius ,   CholGEN Consortium, Bitilinyu-Bangoh Joseph Ephram , Chilengi Roma , Hadja Hamsatou , Idris Jide , Langa José Paulo Maurício , Mukadi-Bamuleka Daniel , Nabadda Susan , Debes Amanda K , Sack David A , Kaseya Jean , Tebeje Yenew Kebede , Wohl Shirlee , Tessema Sofonias Kifle
Published: November 2024

Cholera remains a significant public health burden in many countries in sub-Saharan Africa, though the exact mechanisms of bacterial emergence and spread remain largely undefined. We generated genomic data from 728Vibrio choleraeO1 isolates predominantly collected between 2019-2024 to create the largest dataset ofV. choleraegenomes sequenced locally in Africa. This dataset enabled us to interrogate recent patterns of spread, including the rapid circulation of the AFR15 lineage associated with unusually large outbreaks in Southern Africa. We provide evidence for the movement of the AFR15 lineage into new African Member States and confirm previously observed differences inV. choleraetransmission dynamics in West versus East Africa, though cross-border transmission is prevalent on both sides of the continent. Despite observed differences, evolutionary processes are similar across lineages and we find no evidence for significant changes in antimicrobial resistance genotypes. Overall, our findings emphasize the importance of regionally coordinated cross-border surveillance and interventions, while also demonstrating the critical role of locally generated genomic data in understanding the spread of cholera in Africa.
Ethnic Inequalities in Palliative Care Prescribing – A Rapid Systematic Review
Authors: Kunonga Tafadzwa Patience , Johnson Eugenie Evelynne , Din Usvah , Westhead Elizabeth , Dewhurst Felicity , Hanratty Barbara
Published: November 2024

Context

Effective palliative care involves managing the many symptoms commonly experienced towards the end-of-life. Appropriate prescribing is key to this care, and ethnic inequalities may lead to unequal treatment and poorer outcomes for minority groups. Understanding these disparities is critical to ensuring equitable care.

Objectives

To investigate ethnic inequalities in palliative care prescribing amongst adults residing in high-income countries.

Methods

The review was registered with the International Prospective Register of Systematic Reviews (PROSPERO) under registration number CRD42023476977. We conducted searches across three electronic databases (MEDLINE, Embase, and CINAHL) from January 2000 to November 2023. Screening, data extraction and quality assessment were conducted independently by two reviewers. Quality was assessed using various JBI Critical Appraisal tools. Due to the heterogeneity of included studies, a narrative review was undertaken without a meta-analysis.

Results

Out of 7880 references identified, 10 studies met the inclusion criteria, all conducted in the United States. Overall, five studies were deemed to be high quality and five were fair quality. The studies highlighted ethnic disparities in palliative care prescribing. Minority populations were less likely to receive pain management medications, particularly opioids, compared to non-Hispanic whites. Increased age, female gender, lower socioeconomic status, and place of residence were also related to differences in prescribing practices.

Conclusions

This rapid systematic review suggests that there are ethnic inequalities in palliative care symptom management prescribing, highlighting a possible gap in care for ethnic minority patients. Research beyond the USA is needed to understand if there are international disparities in palliative care prescribing.

Key message

This article reports a rapid systematic review on ethnic inequalities in palliative care prescribing for symptom control in high-income countries. Findings highlight a gap in care for ethnic minority patients. Further investigation is needed to understand how widespread disparities in palliative care prescribing are, across the world.
Clickable PEG-norbornene microgels support suspension bioprinting and microvascular assembly
Authors: Zhang Irene W. , Choi Lucia S. , Friend Nicole E. , McCoy Atticus J. , Midekssa Firaol S. , Alsberg Eben , Lesher-Pérez Sasha Cai , Stegemann Jan P. , Baker Brendon M. , Putnam Andrew J.
Published: November 2024

The development of perfusable and multiscale vascular networks remains one of the largest challenges in tissue engineering. As such, there is a need for the creation of customizable and facile methods to produce robustly vascularized constructs. In this study, secondarily crosslinkable (clickable) poly(ethylene glycol)-norbornene (PEGNB) microbeads were produced and evaluated for their ability to sequentially support suspension bioprinting and microvascular self-assembly towards the aim of engineering hierarchical vasculature. The clickable PEGNB microbead slurry exhibited mechanical behavior suitable for suspension bioprinting of sacrificial bioinks, could be UV crosslinked into a granular construct post-print, and withstood evacuation of the bioink and subsequent perfusion of the patterned void space. Endothelial and stromal cells co-embedded within jammed RGD-modified PEGNB microbead slurries assembled into capillary-scale vasculature after secondary crosslinking of the beads into granular constructs, with endothelial tubules forming within the interstitial space between microbeads and supported by the perivascular association of the stromal cells. Microvascular self-assembly was not impacted by printing sacrificial bioinks into the cell-laden microbead support bath before UV crosslinking. Collectively, these results demonstrate that clickable PEGNB microbeads are a versatile substrate for both suspension printing and microvascular culture and may be the foundation for a promising methodology to engineer hierarchical vasculature.
Peroxidasin expression is increased in intratumoural capillaries and in proximal tubular cells adjacent to clear cell renal cell carcinoma
Authors: Silva Roberto , Almeida Jorge Reis , Coelho Ana Rita , Brandão Isabel , Gomes Bárbara , Alencastre Inês Soares , Oliveira João Paulo
Published: November 2024

Peroxidasin (PXDN), is a heme peroxidase with a critical role in the crosslinking of type IV collagen, being essential for basement membrane integrity. In many cancers, PXDN overexpression has been linked with processes associated with poor disease outcomes, namely the impairment of endothelial functions, pathogenesis of vascular diseases, vascular remodelling, apoptosis, and tissue fibrosis. In RCC, almost nothing is so far known. In this work we characterized the expression of PXDN in tumour and non-neoplastic adjacent tissue from clear cell renal cell carcinoma (ccRCC) and renal oncocytoma by immunohistochemistry. Results showed a significant increase of PXDN expression in intratumoural capillaries of ccRCC in comparison with oncocytoma, and an increase in the proximal tubular epithelial cells of non-neoplastic adjacent parenchyma from ccRCC cases, in comparison with the same area from oncocytomas. Overall, our results suggest, for the first time, that PXDN may have a role in tumour angiogenesis that may favour metastases and tumour malignity, being also enrolled in the crosstalk between the tumour and adjacent tissue, that deserves further investigation.

Highlights

Peroxidasin is increased in ccRCC microvasculature comparing to oncocytoma.

Peroxidasin is increased in proximal tubules of ccRCC kidney adjacent parenchyma.

Is Peroxidasin a modulator of tumour microenvironment promoting angiogenesis?
Pan-Cancer Drug Sensitivity Prediction from Gene Expression using Deep Learning
Authors: Ocasio Beronica A. , Hu Jiaming , Stathias Vasileios , Martinez Maria J. , Burnstein Kerry L. , Schürer Stephan C.
Published: November 2024

Cancer is a group of complex diseases, with tumor heterogeneity, durable drug efficacy, emerging resistance, and host toxicity presenting major challenges to the development of effective cancer therapeutics. While traditionally used methods have remained limited in their capacity to overcome these challenges in cancer drug development, efforts have been made in recent years toward applying “big data” to cancer research and precision oncology. By curating, standardizing, and integrating data from various databases, we developed deep learning architectures that use perturbation and baseline transcriptional signatures to predict efficacious small molecule compounds and genetic dependencies in cancer. A series of internal validations followed by prospective validation in prostate cancer cell lines were performed to ensure consistent performance and model applicability. We reportSensitivitySeq, a novel bioinformatics tool for prioritizing small molecule compounds and gene dependenciesin silicoto drive the development of targeted therapies for cancer. To the best of our knowledge, this is the first supervised deep learning approach, validatedin vitro, to predict drug sensitivity using baseline cancer cell line gene expression alongside cell line-independent perturbation-response consensus signatures.

GRAPHICAL ABSTRACT
Rapid and In-situ Detection of Biological Agents via Near-Infrared Spectroscopy and Cloud-Powered Neural Networks
Authors: Leseigneur Chloé , Radgen-Morvant Isabelle , Metzger César , Esseiva Pierre , Croll Daniel , Miéville Pascal
Published: November 2024

The contagious nature of certain biological agents and the difficulty in treating infections render them a significant threat to public health and safety. In situations involving chemical, biological, radiological, and nuclear (CBRN) agents, effective detection is of paramount importance to prevent the undetected spread of these agents and enable swift and targeted responses tailored to the specific threat. Although portable detection tools are effective for chemical and nuclear detection, current biological detection methods face several challenges, including limited mobility, extended processing times, and varying accuracy. In the context of biological threats, where agents such as anthrax can be rapidly dispersed due to environmental factors and human activities, rapid detection is of paramount importance. It is imperative to develop field-applicable detection devices that are highly selective, capable of differentiating between biological and non-biological agents, as well as benign and harmful microorganisms. This study examines the potential of near-infrared (NIR) spectroscopy in conjunction with machine learning as a rapid in-situ biological detection method. The objective is to distinguish between biological agents and common white powders that are used as confounding agents in suspect letters. The non-pathogenic surrogates employed are safe and representative of typical biological warfare agents. The near-infrared (NIR) spectra of lyophilized bacterial and fungal surrogates, along with common white powders, were subjected to analysis and processing through the application of principal component analysis (PCA) and hierarchical clustering analysis (HCA). This resulted in the successful classification of the samples into distinct groups. The classification model demonstrated high accuracy in its prediction, thereby emphasizing the potential of the method for field detection of solid biological agents. These promising results suggest that NIR spectroscopy combined with machine learning could be further investigated as a rapid in-situ tool for biological detection in CBRN contexts.
Utilizing protein structure graph embeddings to predict the pathogenicity of missense variants
Authors: Danner Martin , Begemann Matthias , Elbracht Miriam , Kurth Ingo , Krause Jeremias
Published: November 2024

Background

Genetic variants can impact the structure of the corresponding protein, which can have detrimental effects on protein function. While the effect of protein truncating variants is often easier to evaluate, most genetic variants are missense variants. These variants are mostly single nucleotide variants which result in the exchange of a single amino acid. The effect on protein function of these variants can be challenging to deduce. To aid the interpretation of missense variants a variety of bioinformatic algorithms have been developed, yet current algorithms rarely directly use the protein structure as a feature to consider.

Results

We developed a machine learning workflow that utilizes the protein-language-model ESMFold to predict the protein structure of missense variants, which is subsequently embedded using graph autoencoders. The generated embeddings are used in a classifier model which predicts pathogenicity. We provide evidence that the generated graph embeddings improve classification accuracy of a XGBoost pathogenicity predictor, which should lead to a wide applicability for human genetic diseases. Additionally, we explored different levels of abstraction of the graph embeddings and their influence on the classifier. Finally, we compare the utility of graph embeddings from different protein-folding models.
Integrated proteome and lipidome analyses place OCIAD1 at mitochondria-peroxisome intersection balancing lipid metabolism
Authors: Linke Vanessa , Chodkowski Mateusz , Kaszuba Kacper , Radkiewicz Mariusz , Rana Vikas , Stadnik Dorota , Dadlez Michał , Chacinska Agnieszka
Published: November 2024

OCIAD1 (Ovarian Cancer Immunoreactive Antigen Domain Containing 1) is a membrane protein largely localized to mitochondria, however, its function in health or disease is not well understood. To comprehensively characterize the molecular changes upon lack of OCIAD1, we used mass spectrometry to study the mitochondrial and cellular proteome and lipidome. We find extensive lipidome rearrangement in OCIAD1 KO cells, characterized by two main phenotypes of decreased ether phospholipids and decreased phospholipids with an odd number of carbons. The lipidomic changes suggest alterations in peroxisomal lipid metabolism. At the same time, proteins responsible for mitochondrial fatty acid β oxidation are significantly increased. Together with a global loss in peroxisomal proteins and a meta-analysis of proximity labeling data, this gives a function to the previously observed partial localization of OCIAD1 to peroxisomes. We suggest a role for OCIAD1 in balancing mitochondrial and peroxisomal lipid metabolism, and a direct impact on the key enzymes FAR1 and ACBD3.

Summary Statement

Lipidomics and proteomics of mitochondrial fractions and whole cells lacking the membrane protein OCIAD1 suggest a role as a dually localized protein balancing mitochondrial and peroxisomal lipid metabolism.
Evaluating the Fidelity of Data-Driven Predator-Prey Models: A Dynamical Systems Analysis
Authors: Frank Anna-Simone J. , Zhang Jiawen , Subbey Sam
Published: November 2024

In empirical predator-prey systems, understanding the inherent dynamics typically comes from analyzing a structural model fitted to observation data. However, determining an appropriate model structure and its parameters is often complex and highly uncertain. A promising alternative is to learn the model structure directly from time series data of both predator and prey.

This study explores the capability of a data-driven algorithm, Sparse Identification of Nonlinear Dynamics (SINDy), to accurately capture the dynamics of a predator-prey system. We apply SINDy to derive a Learned Model (LM) from data generated by a Reference Model (RM), whose predator-prey dynamics are well understood. The study compares the dynamics of the LM to the RM using criteria such as equilibrium points, stability, sensitivity, and bifurcation analysis.

Our results demonstrate general consistency between the RM and LM dynamics, though notable differences remain. We discuss the implications of these differences in the broader context of using learned models to uncover the inherent drivers of predator-prey dynamics and ecological implications.

2010 MSC

37M05, 37N25, 92B05, 92D25, 92D40, 65L05, 37G15

Highlights

Evaluates data-driven model’s ability to replication of predator-prey dynamics using SINDy framework

Learned Model captures core dynamics but shows parameter sensitivity and bifurcation differences

Analysis reveals need for extensive data for effective model learning

Suggests combining data-driven methods with biological priors to improve model accuracy
Dynamically arrested condensate fusion creates complex structures with varying material properties
Authors: Erkamp Nadia A. , Sanchez-Burgos Ignacio , Zhou Alexandra , Krug Tommy J. , Qamar Seema , Sneideris Tomas , Zhang Ellie , Nakajima Kichitaro , Chen Anqi , Collepardo-Guevara Rosana , van Hest Jan , St George-Hyslop Peter , Weitz David A. , Espinosa Jorge R. , Knowles Tuomas P. J.
Published: November 2024

The cell nucleus and cytosol contain numerous biomolecular condensates which dynamically reshape, fuse and split to accomplish precise compartmentalization of the cell material. While it has been observed that some condensates rapidly coalesce, some others only attach to each other, or do not establish persistent interactions over time. Here, we explain these observations through optical tweezers and Molecular Dynamics simulations focusing on two condensate-forming, RNA-binding proteins—FUS and G3BP1—strongly involved in RNA metabolism and stress responses. We find that the fusion of pure droplets formed by these proteins can give rise to multiphase single-component condensates exhibiting notably different densities, architectures, and material properties. Such behaviour is dictated by the relative timescales of condensate fusion and protein internal mixing. A critical parameter controlling this interplay is the extent of ageing that condensates display; e.g., their progressive hardening driven by the accumulation of inter-proteinβ-sheet assemblies over time. Strikingly, different degrees of ageing in fusing droplets can lead single-component condensates to form diverse architectures including concentric drops or two-sided condensates. Overall, our results highlight a mechanism, based on the temporal coupling between ageing, fusion, and mixing rate, by which biomolecular condensates form multiphasic structures with markedly different material properties, and hence potentially distinct biological roles.
Schistosome esophageal gland factor MEG-8.2 drives host cell lysis and interacts with host immune proteins
Authors: Yadav Pallavi , Simbassa Sabona B , Sloan Ryan , Newmark Phillip A , Lee Jayhun
Published: November 2024

Schistosomes are blood flukes that ingest large amounts of host blood during their intra-mammalian stage. The ingested blood contains leukocytes that can be harmful, yet the parasites survive inside the host for decades, reflecting superb immune evasion mechanisms that remain poorly understood. Our previous work discovered that FoxA, a forkhead transcription factor, drives the production of the esophageal gland, an anterior digestive organ essential for degrading the ingested leukocytes and for in vivo survival. However, a comprehensive molecular makeup of the esophageal gland remains unclear. Importantly, which of the esophageal gland factors are responsible for degrading the ingested leukocytes, their mechanism of action, and how such a function relates to parasite survival and immune evasion remains unknown. Here, we identify additional esophageal gland genes by taking a comparative transcriptomics approach to identify transcripts altered in foxA knockdown adult schistosomes. A targeted RNAi screen coupled with biochemistry reveals that specific domains of the micro-exon gene MEG-8.2, can drive host cell lysis in a concentration-dependent manner. Using pull-down assays coupled with mass spectrometry, we discover that MEG-8.2 interacts with several host membrane and extracellular proteins that play important roles in activating innate and/or adaptive immunity. Together, our findings suggest a dual role for MEG-8.2 in effectively lysing the ingested cells in the esophageal lumen and interacting with specific host proteins to neutralize or suppress the host immunity. These findings lay an important foundation for exploiting esophageal gland factors to treat schistosomiasis.
Urban tree diversity fosters bird insectivory despite a loss in bird diversity with urbanization
Authors: Schillé Laura , Paquette Alain , Marcotte Gabriel , Ouellet Hugo , Cobus Swane , Barbaro Luc , Castagneyrol Bastien
Published: November 2024

Urbanization is one of the main drivers of biotic homogenization in bird communities worldwide. Yet, only a few studies have addressed its functional consequences on the top-down control birds exert on insect herbivores. We hypothesized that their inconsistent results reflect the overlooked heterogeneity of the urban habitat for birds, and in particular the distribution and diversity of urban trees.

We monitored tree diversity, bird diversity, avian predation attempts on artificial prey, and the effect of bird exclusion on insect herbivory in 97 trees distributed among 24 urban experimental plots in the city of Montreal, Canada. We characterized urbanization levels through a combination of variables related to tree density, impervious surfaces, anthropic noise, and human population density.

Bird diversity decreased with increasing urbanization, whereas the frequency of generalist synurbic species increased. We found no significant relationship between predation and urbanization or between predation and bird diversity. However, tree diversity was positively correlated with predation attempts on artificial prey, irrespective of bird diversity.

We revealed a mismatch between the effects of urbanization on bird diversity and on the regulation service and unraveled the functional importance of tree diversity in shaping the avian predation function in urban ecosystems. Our study advocates for the consideration of intra-urban heterogeneity in the investigation of trophic cascades within cities.
Deletion of epithelial HKDC1 decelerates cellular proliferation and impairs mitochondrial function of tumorous epithelial cells thereby protecting from intestinal carcinogenesis in mice
Authors: Järke Lea , Weber-Stiehl Saskia , Shima Kensuke , Moors Karlis Arturs , Genth Jerome , Schuran Fenja Amrei , Best Lena , Tschurtschenthaler Markus , Flemer Burkhardt , Tholey Andreas , Kaleta Christoph , Rupp Jan , Rosenstiel Philip , Sommer Felix
Published: November 2024

Background

A metabolic switch favoring glycolysis over aerobic oxidative phosphorylation, namely the “Warburg effect”, represents a hallmark of cancer cells. Hexokinases (HK) catalyze the first step of glycolysis, thereby regulating its rate. Dysregulated HKDC1 (HK domain containing 1) expression has been associated with various cancer types and blocking HKDC1 prevents disease progression for hepatic carcinoma T cell lymphoma and lung adenocarcinoma, but its implication for colorectal cancer (CRC) remained unknown. Here, we functionally investigated the role of HKDC1 for intestinal carcinogenesis.

Methods

First, we analyzed HKDC1 expression in the intestinal mucosa of healthy controls (HC) and CRC patients and in different tumor tissues using transcriptomic data from publicly available databases. We then generated HKDC1-deficient human and murine colonic epithelial cell lines as well as intestinal organoids and profiled their phenotypic functions. Next, we screened for proteins interacting with HKDC1 by immunoprecipitation. Finally, we generated tumor-bearingApcMin/+mice with a conditional deletion of HKDC1 in intestinal epithelial cells and also performed a xenograft mouse model to test the role of HKDC1 for intestinal carcinogenesisin vivo.

Results

HKDC1 was found to be overexpressed in tumor compared to normal tissue of CRC patients.In vitro,HKDC1-deficient human Caco-2 and murine CMT-93 cells displayed reduced proliferation, altered susceptibility to cell death induction, and disrupted mitochondrial functions, particularly mitochondrial respiration. These altered cancer hallmarks were then corroborated in HKDC1-deficient normal and tumor-derivedApcMin/+intestinal organoids. Immunoprecipitation and mass spectometry proteomic analyses revealed interactions of HKDC1 with several mitochondria-related proteins.In vivo, two distinct mouse models demonstrated that epithelial deletion of HKDC1 protected from carcinogenesis. First,ApcMin/+-Hkdc1ΔIECmice showed mildly improved disease phenotypes in the colon accompanied with reduced numbers of Ki67-positive proliferating epithelial cells. Finally, HKDC1-deficient Caco-2 cells completely failed to form any tumor mass in a xenograft model when implanted into immunodeficient mice.

Conclusions

We demonstrate that HKDC1 influences cancer cell proliferation and susceptibility to cell death, potentially through interactions with mitochondrial proteins that regulate membrane permeability, ultimately impacting intestinal carcinogenesis. Collectively, these findings highlight the significance of HKDC1 for CRC pathobiology, presenting it as a promising target for further investigation and potential therapeutic interventions.