bluuebunny/crossref_metadata_2025 huggingface dataset:
Incidence and prevalence of euthanasia in Belgium. A study using administrative data on all cases of euthanasia reported between 2002 and 2023
Authors: Wels Jacques , Hamarat Natasia
Published: October 2024

Background

Reported assisted dying cases have increased in countries with such legislation. In Belgium, where euthanasia was legalized in 2002, cases rose from 236 in 2003 to 3,423 in 2023. While most studies focus on occurrence rates, this study examines the magnitude of increase and the contribution of demographic changes observed over the period.

Methods

We analysed complete data from the Belgian Federal Commission for the Control and Evaluation of Euthanasia (FCCEE) from 2002-2023 (N=33,604). Using Poisson regression, we calculated Rate Ratios (RR) by age, gender, region, and euthanasia characteristics. We compared estimates with a model that included demographic offsets to calculate Prevalence Rates (PR) and explored interaction effects across sub-categories.

Results

The yearly RR is 1.070, while the PR is 1.054, indicating that demographic changes significantly influence the observed increase. The PR for euthanasia among females has slightly risen (PR: 1.034), while psychiatric cases remained a small proportion (PR: 1.002). Cases citing multimorbidity have increased (RR: 1.029), whereas cases related to psychiatric disorders (PR: 0.949) and deaths in care homes (PR: 0.998) have not shown significant increases. Higher prevalence is observed in the Flemish region (PR: 1.983) but the gap has narrowed over the years.

Interpretation

A substantial part of the increase in euthanasia cases is attributed to demographic changes, particularly population ageing. Early increases were mainly due to the regulatory onset, while recent trends reflect a growing influence of demographic factors and regional adjustments. Considering demographic shifts is essential and long-term trends should be monitored.

Funding

ERC (UHealth), FNRS-CQ
Pipeline to explore information on genome editing using large language models and genome editing meta-database
Authors: Suzuki Takayuki , Bono Hidemasa
Published: October 2024

Genome editing (GE) is widely recognized as an effective and valuable technology in life sciences research. However, certain genes are difficult to edit depending on some factors such as the type of species, sequences, and GE tools. Therefore, confirming the presence or absence of GE practices in previous publications is crucial for the effectively design and establishment of research using GE. Although the Genome Editing Meta-database (GEM:https://bonohu.hiroshima-u.ac.jp/gem/) aims to provide as comprehensive GE information as possible, it does not indicate how each registered gene is involved in GE. In this study, we developed a systematic method for extracting essential GE information using large language models from the information based on GEM and GE-related articles. This approach allows for a systematic and efficient investigation of GE information that cannot be achieved using the current GEM alone. In addition, by converting the extracted GE information into metrics, we propose a potential application of this method to prioritize genes for future research. The extracted GE information and novel GE-related scores are expected to facilitate the efficient selection of target genes for GE and support the design of research using GE.

Database Tool URLs:https://github.com/szktkyk/extract_geinfo,https://github.com/szktkyk/visualize_geinfo
Skin Hydration By Natural Moisturizing Factors, A Story Of H-Bond Networking
Authors: Martin Marving , Chantemargue Benjamin , Trouillas Patrick
Published: October 2024

Dry skin is a common condition experienced by many. Besides being particularly present during the cold season, various diseases exist all year round, leading to localized xerosis. To prevent it, the skin is provided with natural moisturizing factors (NMFs). They are small amino acids or derivatives found in the outermost layer of the skin, thestratum corneum(SC). They are often claimed to be highly efficient humectants, increasing the water content to maintain the fluidity of the skin. However, alternative mechanisms have been proposed, suggesting that NMFs themselves may act as lipid mobility amplifiers. This work aims at investigating the role of three NMFs, namely urea (URE), glycerol (GLY) and urocanic acid / urocanate (UCA/UCO) in SCin silicomodels, considering two different levels of humidity. Molecular dynamic simulations showed an increase in the diffusion of different lipid components, mainly free fatty acids (FFAs) and ceramides acyl chain moieties, in the presence of either high water content or NMFs. The membrane properties were modified, as seen by an increased thickness and a greater lateral stiffness. All NMFs exhibited a similar impact, whereas UCA revealed slight differences according to its charged state. By studying NMF-water intermolecular interactions, we highlighted the role of NMF as a regulator of membrane perturbations, while insuring membrane fluidity. This role allows NMFs to prevent destabilization of the skin membrane in the presence of high-water content. This study, performed at an atomistic resolution, highlighted a strong H-bond network between lipids, involving mainly ceramides but also all other components. This network can be modified in the presence of high-water concentration or NMFs, resulting in modifications of membrane properties, rationalizing hydration effects.
ECM-free patient-derived organoids preserve diverse prostate cancer lineages and uncoverin vitro-enriched cell types
Authors: Dolgos Robin , Parmentier Romuald , Wang Jing , Servant Raphaëlle , Templeton Arnoud J. , Zellweger Tobias , Lamb Alastair D. , Mertz Kirsten D. , Subotic Svetozar , Vlajnic Tatjana , Seifert Helge , Mortezavi Ashkan , Rentsch Cyrill A. , Bubendorf Lukas , Le Magnen Clémentine
Published: October 2024

Patient-derived organoids (PDOs) offer new opportunities to model various cancers. However, their application in prostate cancer (PCa) has been hampered by poor success rates and overgrowth of cell types which are not representative of the patient samples. By exploiting a cohort of 164 PCa patient samples and tuning several culture parameters, we show that an extracellular matrix-free (ECM)-free culture system increases the take-rate of PDOs with luminal-like and PCa features. Single-cell RNA sequencing (scRNA-seq) reveals that ECM-free PDOs comprise cell populations associated with known PCa signatures and exhibit transcriptomic resemblance with their respective parental tumors. In addition, we define organoid-associated cell type signatures and identify markers discriminating tumorsversusbenign cellsex vivoandin situ. Furthermore, we generate the first prostate PDO single-cell atlas integrating previously-published scRNA-seq datasets and our newly- generated data. We show that Matrigel-based organoid cultures derived from primary PCa are essentially composed of benign-like epithelial cells, irrespective of the dataset or the malignant nature of the tissue of origin. In contrast, ECM-free conditions maintain heterogenous patient-specific luminal tumor cell populations and enrich in intermediate cell types. Ultimately, our work will significantly enhance the potential of PDOs in basic and translational PCa research.
Load-based divergence in the dynamic allostery of two TCRs recognizing the same pMHC
Authors: Chang-Gonzalez Ana C. , Akitsu Aoi , Mallis Robert J. , Lang Matthew J. , Reinherz Ellis L. , Hwang Wonmuk
Published: October 2024

Increasing evidence suggests that mechanical load on theαβT cell receptor (TCR) is crucial for recognizing the antigenic peptide-loaded major histocompatibility complex (pMHC) molecule. Our recent all-atom molecular dynamics (MD) simulations revealed that the inter-domain motion of the TCR is responsible for the load-induced catch bond behavior of the TCR-pMHC complex and peptide discrimination. To further examine the generality of the mechanism, we perform all-atom MD simulations of the B7 TCR under different conditions for comparison with our previous simulations of the A6 TCR. The two TCRs recognize the same pMHC and have similar interfaces with pMHC in crystal structures. We find that the B7 TCR-pMHC interface stabilizes under ∼15-pN load using a conserved dynamic allostery mechanism that involves the asymmetric motion of the TCR chassis. However, despite forming comparable contacts with pMHC as A6 in the crystal structure, B7 has fewer high-occupancy contacts with pMHC during the simulation. These results suggest that the dynamic allostery common to the TCRαβchassis can amplify slight differences in interfacial contacts into distinctive mechanical responses and potentially nuanced biological outcomes.
The body size and fitness match and its variability in plastic response to temperature
Authors: Żygadło Antoni , Burzawa Agata , Potera Katarzyna , Sierpowski Franek , Walczyńska Aleksandra
Published: October 2024

The ability of organisms to respond plastically to environmental change remains one of the most challenging areas of ecological studies. Reasons for this include the complex nature of environmental cues and responses at the organismal level, the costs that organisms face in performing phenotypic plasticity under different conditions, and the individual capacity to respond, which depends on many internal and external factors. The special case in this regard is an example of the plastic body size response to temperature, known as the Temperature-Size Rule (TSR). We used five clonal and three multiclonal experimental populations of theLecane inermisrotifer. We measured two traits over a wide thermal range: body size and population growth rater. We investigated (i) the thermal conditions under which different experimental populations perform the TSR or canalize (= no plasticity) their body size, (ii) how this response relates to a direct measure of fitness, and (iii) whether this response varies with the thermal preferences of the studied organisms. We found a relationship between body size and fitness, confirming that the TSR is only performed within a certain thermal range, beyond which body size is canalized. We did not find the expected relationship between the strength of the TSR and the range of thermal tolerance, but our results do not allow us to reject the existence of such a relationship. Additionally, we found a relatively high repeatability of thermal tolerance in experimental populations in comparison with the previous studies. Finally, we suggest the role of the level of genetic composition within a population in its ability to respond plastically to temperature. This is the first study to describe in detail the special case of plasticityversuscanalization, for body size response to optimal and suboptimal temperatures, in organisms that differ in their tolerance to temperature.
Exploring the Role of CottonCMFGenes in Salt Stress Tolerance: Insights from Phylogenetic, Expression, and Functional Analyses
Authors: Cui Yupeng , Shi Gongyao , Wang Shuai , Peng Xingyu , Zhou Xue-Rong , Ye Wuwei
Published: October 2024

Salt stress significantly limits cotton growth and development, making the improvement of salt tolerance critical.CMFgenes, containing a single CCT domain, are promising targets for breeding programs. We identified 101CMFgenes from four cotton species. Phylogenetic analysis grouped these genes into six clusters closely related toArabidopsis. Gene structure and motif analysis showed high conservation, while collinear analysis indicated segmental duplication as a key factor inCMFgene family expansion. Promoter analysis predicted involvement in light, abiotic stress, plant hormone responses, and growth. Expression analysis revealed differential expression ofGhCMFgenes across tissues, with some induced by abiotic stress. Co-expression network analysis indicatedGhCMF14interacts with other proteins to resist abiotic stress. Subcellular localization showed GhCMF14 in the nucleus. SilencingGhCMF14enhanced salt tolerance, with higher chlorophyll and proline content, and lower MDA and H2O2levels. This study provides insights intoCMFgene regulation and their role in cotton salt stress tolerance.
Simulation Insights on the Compound Action Potential in Multifascicular Nerves
Authors: Tharayil Joseph , Zinno Ciro , Agnesi Filippo , Lloyd Bryn , Farcito Silvia , Cassara Antonino M. , Kuster Niels , Reimann Michael , Micera Silvestro , Neufeld Esra
Published: October 2024

Objective

Develop an efficient method for simulating evoked compound action potential (eCAP) signals from complex nerves to help optimize and interpret eCAP recordings; validate it through comparison with measured vagus nerve eCAP recordings; elucidate the subtle interplay giving rise to specific eCAP signal shapes and magnitudes.

Approach

We developed an extended reciprocity theorem approach to model neuron signals in heterogeneous environments, and use it to study analytically the single fibre action potential. We then established a semi-analytic model that also uses hybrid electromagnetic-electrophysiological simulations to model eCAP signals from complex nerves populated with heterogeneous fiber populations of fibers. A cuff electrode was used to measure activity induced by vagus nerve stimulation inin vivoporcine experiments; these measurements were compared with signals produced by the model.

Main Results

The semi-analytic model produces signals that approximate the shape and amplitude ofin vivomeasurements. Partially activated fascicles contribute substantially to the signal, as eCAP contributions from smoothly varying fiber calibers in fully activated ones partially cancel. As a result, eCAP magnitude does not depend monotonically on the stimulation current and recruitment level. Because the eCAP is sensitive to the degree of activation in individual fascicles, and to the location of the recording electrodes with respect to individual fascicles, the contributions of different fascicles to the recorded eCAP signals vary significantly with changes in the shape and placement of the stimulus and the recording electrodes.

Significance

Our method can be used to rapidly assess new stimulation and recording setups involving complex nerves and neurovascular bundles, e.g., to maximize signal information content, for closed-loop control in bioelectronic medicine applications, and potentially to non-destructively reconstruct structural and functional nerve topologies through inverse problem solving.
BioStructNet: Structure-Based Network with Transfer Learning for Predicting Biocatalyst Functions
Authors: Wang Xiangwen , Zhou Jiahui , Mueller Jane , Quinn Derek , Moody Thomas S. , Huang Meilan
Published: October 2024

Enzyme-substrate interactions are essential to both biological processes and industrial applications. Advanced machine learning techniques have significantly accelerated biocatalysis research, revolutionizing the prediction of biocatalytic activities and facilitating the discovery of novel biocatalysts. However, the limited availability of data for specific enzyme functions, such as conversion efficiency and stereoselectivity, presents challenges for prediction accuracy. In this study, we developed BioStructNet, a structure-based deep learning network that integrates both protein and ligand structural data to capture the complexity of enzyme-substrate interactions. Benchmarking studies with the different algorithms showed the enhanced predictive accuracy of BioStructNet. To further optimize the prediction accuracy for the small dataset, we implemented transfer learning in the framework, training a source model on a large dataset and fine-tuning it on a small, function-specific dataset, using the CalB dataset as a case study. The model performance was validated by comparing the attention heat maps generated by the BioStructNet interaction module, with the enzyme substrate interactions revealed by enzyme-substrate complexes revealed from molecular simulations. BioStructNet would accelerate the discovery of functional enzymes for industrial use, particularly in cases where the training datasets for machine learning are small.
Astrocytic Ryk signaling coordinates scarring and wound healing after spinal cord injury
Authors: Shen Zhe , Feng Bo , Lim Wei Ling , Woo Timothy , Liu Yanlin , Vicenzi Silvia , Wang Jingyi , Kwon Brian K. , Zou Yimin
Published: October 2024

Wound healing after spinal cord injury involves highly coordinated interactions among multiple cell types, which is poorly understood. Astrocytes play a central role in creating a border against the non-neural lesion core. To do so, astrocytes undergo dramatic morphological changes by first thickening the processes and then elongating and overlap them. We show here show that the expression of a cell-surface receptor, Ryk, is induced in astrocytes after injury in both rodent and human spinal cord. Astrocyte-specific knockout of Ryk dramatically elongated the reactive astrocytes and accelerated the formation of the border and reduced the size of the scar. Astrocyte-specific knockout of Ryk also accelerated the injury responses of multiple cell types, including the resolution of neuroinflammation. Single cell transcriptomics analyses revealed a broad range of changes cell signaling among astrocytes, microglia, fibroblasts, endothelial cell, etc, after astrocyte-specific Ryk knockout, suggesting that Ryk not only regulates the injury response of astrocytes but may also regulate signals which coordinate the responses of multiple cell types. The elongation is mediated by NrCAM, a cell adhesion molecule induced by astrocyte-specific conditional knockout of Ryk after spinal cord injury. Our findings suggest a promising therapeutic target to accelerate wound healing and promote neuronal survival and enhance functional recovery.
BBATProt : A Framework Predicting Biological Function with Enhanced Feature Extraction via Explainable Deep Learning
Authors: Wang Youqing , Ye Xukai , Feng Yue , Wang Haoqian , Lin Xiaofan , Ma Xin , Zhang Yifei
Published: October 2024

Accurately predicting the functions of peptides and proteins from their amino acid sequences is essential for understanding life processes and advancing biomolecule engineering. Due to the time-consuming and resource-intensive nature of experimental procedures, computational approaches, especially those based on machine learning frameworks, have garnered significant interest. However, many existing machine learning tools are limited to specific tasks and lack adaptability across different predictions. Here we propose a versatile framework BBATProt for the prediction of various protein and peptide functions. BBATProt employs transfer learning with a pre-trained Bidirectional Encoder Representations from Transformers (BERT) model, to effectively capture high-dimensional features from amino acid sequences. The whole custom-designed network, integrating Bidirectional Long Short-Term Memory (Bi-LSTM) and Temporal Convolutional Networks (TCN), can align with the spatial characteristics of proteins. It combines local and global feature extraction through attention mechanisms for precise functional prediction. This approach ensures that key features are adaptively extracted and balanced across diverse tasks. Comprehensive evaluations show BBATProt outperforms state-of-the-art models in predicting functions like hydrolytic catalysis, activity of peptides, and post-translational modification sites. Visualizations of feature evolution and refinement via attention mechanisms validate the framework’s interpretability, providing transparency into the evolutional process and offering deeper insights into function prediction.
Guided assembly of multispecies positive biofilms targeting undesirable bacteria
Authors: Guéneau Virgile , Guillier Laurent , Berdous Cécile , Noirot-Gros Marie-Françoise , Jiménez Guillermo , Plateau-Gonthier Julia , Serror Pascale , Castex Mathieu , Briandet Romain
Published: October 2024

The use of synthetic microbial communities (SynComs) engineered to form positive biofilms that prevent the settlement of harmful bacteria is emerging as a promising strategy in biotechnology, particularly in reducing reliance on chemical antimicrobials. Despite this potential, the rationale for selecting specific strains in SynComs and the mechanisms underlying their antagonistic effects remains insufficiently understood. In this study, we present a bottom-up approach integrating live-cell imaging with high-throughput analysis of multi-strain biofilms across diverse scenarios. Through this method, we identified beneficial strains based on their superior ability to exclude undesirable bacteria and form mixed biofilms. Notably, our findings revealed that competitive strains against undesirable bacteria could also exclude other beneficial strains, emphasising the need for compatibility control in SynComs design. SynComs composed ofB. velezensisandPediococcusspp. demonstrated enhanced pathogen exclusion compared to single strains. Temporal analysis of biofilm interactions, supported by mathematical models, showed that pathogen exclusion was primarily driven by nutritional competition (Jameson effect) with additional specific interference mechanisms (prey-predator Lotka-Volterra model). Furthermore, pre-establishing SynComs to surfaces significantly increased pathogen inhibition, indicating a distinct biofilm-associated exclusion effect. These insights offer a framework for rational SynCom design and deepen our understanding of the mechanisms underpinning positive biofilm applications.

Abstract Figure
Coarse-Grained Dynamic Simulation of Cytoskeletal Microtubule Twist
Authors: Zhu Renjie , Zhang Yuwei , Xia Fei
Published: October 2024

Microtubule, a key component of the cytoskeleton, plays a crucial role in cell mitosis. Modeling and dynamic simulation of microtubules at the micrometer scale remain a significant challenge. In this study, we developed the helix-based ultra-coarse-grained (HB-UCG) model for the dynamic simulation of microtubules, based on the helical characteristics obtained from electron microscopy density data. We constructed microtubules up to 35 μm in length and investigated the relationship between persistence length and contour length. By comparing our results with experimental data, we validated the potential of the HB-UCG model in simulating microtubule functions. We also simulated the twist process of microtubules driven by motor proteins, successfully demonstrating the model’s effectiveness in simulating biological processes. This study can provide the foundation for theoretical simulations of microtubule functions during mitosis.
Identification of Shared and Unique Key Biomarkers of Alcohol Liver Cirrhosis and Non-Alcoholic Steatohepatitis Through Machine Learning Network-Based Algorithms
Authors: Hajihosseini Morteza , Talarico Fernanda , Zhao Caroline , Campbell Scott , Udenze Daniel , Hajizadeh Bastani Nastaran , Ahmed Marawan , Ghasemi Erfan , Tonoyan Lusine , Guirguis Micheal , Mayo Patrick , Campanella Corinne
Published: October 2024

Introduction

Liver fibrosis can progress to cirrhosis, liver failure, or hepatocellular carcinoma, which often requires transplantation and burdens healthcare systems around the world. Advances in single-cell RNA sequencing and machine learning have enhanced the understanding of immune responses in many liver diseases particularly alcohol liver cirrhosis (ALC) and non-alcoholic steatohepatitis (NASH). This study aims to identify key biomarkers involved in these conditions and assess their potential as non-invasive diagnostic tools.

Methods

Two gene expression profiles GSE136103 and GSE115469 were used to conduct differential gene expression (DEG) analysis. Using the results from DEG analysis, we then applied two machine learning network-based algorithms, master regulator analysis (MRA) and weighted key driver analysis (wKDA), to identify potential biomarker genes for NASH and ALC.

Results

A total of 1,435 and 5,074 DEGs were identified for ALC and NASH compared to healthy controls, including 1,077 shared DEGs between the two diseases. The MRA showed HLA-DPA1, HLA-DRB1, IFI44L, ISG15, and CD74 as the potential master regulators of ALC and HLA-DPB1, HLA-DQB1, HLA-DRB5, PFN1, and TMSB4X as the potential master regulators of NASH. In addition, wKDA analysis indicated CD300A, FCGR2A, RGS1, HLA-DMB, and C1QA as the key drivers of ALC and INPP5D, NCKAP1L, RAC2, PTPRC, and TYROBP as key drivers of NASH.

Conclusion

This study presented a comprehensive framework for analyzing single-cell RNA-seq data, demonstrating the potential of combining advanced network-based machine-learning techniques with conventional DEG analysis to uncover actionable prognostic markers for ALC and NASH with potential use as target biomarkers in drug development.
The association between alcohol consumption and colorectal carcinogenesis is partially mediated by the gut microbiome
Authors: Kværner Ane Sørlie , Birkeland Einar , Avershina Ekaterina , Botteri Edoardo , Bucher-Johannessen Cecilie , Dines Knudsen Markus , Hjartåker Anette , Page Christian M. , Hov Johannes R. , Song Mingyang , Ranheim Randel Kristin , Hoff Geir , Rounge Trine B. , Berstad Paula
Published: October 2024

Background

Alcohol consumption is one of the major risk factors of colorectal cancer (CRC). However, the mechanisms underlying this relationship are not fully understood, particularly the potential role of gut microbes.

Objective

To study associations of alcohol intake with the gut microbiome and colorectal lesions among CRC screening participants. Of particular interest was the potential role of gut microbes in mediating the association between alcohol intake and colorectal lesions.

Methods

Participants included fecal immunochemical test-positive women and men enrolled in the CRCbiome study, aged 55-77 years at inclusion. Intake of alcohol was assessed using a validated, semi-quantitative food frequency questionnaire. Integrating with shotgun metagenome based taxonomic and functional profiles, we studied associations with screen-detected colorectal lesions. The potential role of alcohol-associated gut microbes in mediating the association between alcohol intake and colorectal lesions was examined using causal mediation analysis.

Results

Of 1,468 participants with dietary data, 414 were diagnosed with advanced lesions (advanced adenoma, advanced serrated lesions or CRC). Alcohol intake was positively associated with advanced lesions in a dose-dependent manner (ptrend= 0.008), with odds ratio of 1.09 (95% confidence interval, 1.00, 1.19) per 10 g/day increase. Compared to non-consumers, those consuming alcohol were characterized by a distinct microbial profile, manifested as modest, but consistent, shifts in α- and β-diversity, and differentially abundant bacteria (Log2 fold change (Log2FC) >0:B. finegoldiiandL. asaccharolyticus; Log2FC <0:S. mutans, B. dentinum,C. symbiosumandE. boltae). A causal mediation analysis showed that 12% of the association between alcohol intake and advanced lesions was mediated by alcohol-associated gut bacteria.

Conclusions

Alcohol consumption was associated with a distinct microbial profile, which partly explained the association between alcohol intake and advanced colorectal lesions.

Trial Registration

The BCSN is registered at clinicaltrials.gov (National clinical trial (NCT) no. 01538550).
Synaptic Vesicle Cycling Disorders: Cross-Sectional Phenotyping Study of a Gene Functional Network
Authors: Eck Josefine , Smith Tess , Kolesnik Anna , Al-jawahiri Reem , Baker Kate
Published: October 2024

Background and objectives

Genes associated with neurodevelopmental disorders (NDDs) can be grouped into networks according to their molecular and cellular functions. However, the links between gene functional networks and neurodevelopmental phenotypes are not well understood. Synaptic vesicle cycling (SVC) is one gene functional network in which rare, high penetrance variants are known to cause NDDs. SVC genes regulate neurotransmitter release and recycling, thus essential for synaptic transmission and plasticity. We investigated whether SVC disorders are associated with a different neurodevelopmental spectrum from other monogenic NDDs, and whether phenotypic variation within SVC disorders can be predicted.

Methods

We included 199 children, young people, and adults with a genetic NDD diagnosis (n=109 with SVC disorders, n=90 with non-SVC disorders). Families were recruited via clinical genetics and neurology services, and support organisations. Parents or carers completed quantitative questionnaire measures previously validated in populations with NDDs. We implemented a PCA-derived K-prototype clustering analysis to assess associations between gene functional network and neurodevelopmental variation.

Results

Cohort-wide K-prototype clustering identified four phenotypic similarity clusters, each having membership from both SVC and non-SVC participants. The clusters differed in phenotype enrichments as follows: 1) behavioural difficulties and sleep problems, 2) less severe neurodevelopmental problems overall, 3) epilepsies, sleep problems, severe adaptive impairments and visual awareness difficulties, 4) sensory-motor problems. The SVC group was over-represented within cluster 3. Cluster memberships within the SVC group cannot be predicted by age, sex, variant type, gene or SVC sub-process.

Discussion

The K-prototype method can be used to describe multi-dimensional phenotypic structure within the heterogeneous genetic NDD population. We found that SVC functional network membership contributes to the likelihood of phenotype cluster memberships, but does not specify a distinct or homogeneous neurodevelopmental profile. Investigating convergent disease mechanisms arising from SVC dysfunction is central to understanding the observed neurodevelopmental spectrum, and may ultimately guide evidence-based prognostication and mechanism-informed management.
The complete blood count and cardiovascular disease: analyses across six cohorts of 23,370 adults
Authors: Goonewardena Sascha N. , Murthy Venkatesh L.
Published: October 2024

Background

The complete blood count (CBC) is one of the most performed laboratory studies. However, the CBC and its components are not commonly used to understand and quantify cardiovascular disease (CVD) risk.

Objective

We sought to define the relationships between the CBC, traditional CVD risk factors, and common CVD biomarkers and their joint association with all-cause mortality and CVD.

Methods

We examined the relationships between the CBC, traditional CVD risk factors, and mortality in NHANES (n=7843). We validated and extended these findings to more refined CVD endpoints in five additional cohorts (n=15,527).

Results

We first examined the variance accounted for by common laboratory studies (lipid panel, HbA1c, hs-CRP, and basic metabolic panel) by traditional risk factors in NHANES. Except for hemoglobin (Hb) components, we found that traditional risk factors accounted for less than 20% of the variance in the CBC, suggesting that the CBC provides unique information beyond traditional risk factors and CVD biomarkers. Additionally, the CBC was strongly associated with all-cause mortality (p<0.0001), even more than traditional CVD biomarkers (lipid panel, HbA1c, and CRP). We validated and extended these findings across five additional cohorts with a mean follow-up of 16 years and more refined CVD endpoints. In the fully adjusted analyses, several CBC components, including the white blood cell (WBC) count, neutrophil (PMN) count, Hb level, and an integrated immune cell score, were associated with individual CVD endpoints (incident stroke, MI, or revascularization) and a composite CV endpoint (MACE3) with standardized hazard ratios of 1.13 (p=0.002), 1.15 (p=0.0006), 0.82 (p<0.0001), and 2.16 (p<0.0001) respectively.

Conclusion

This study represents the first systematic examination of the relationship between the CBC, all-cause mortality, and CVD in a diverse cohort of 23,370 adults. These findings underscore the added value of the CBC over traditional risk factors and common CVD biomarkers for CVD risk assessment. Future studies should explore the integration of CBC parameters into predictive models to enhance our understanding, early identification, and prevention strategies for CVD.
Vector competence for Oropouche virus: a systematic review of pre-2024 experiments
Authors: Gallichotte Emily N. , Ebel Gregory , Carlson Colin J.
Published: October 2024

The 2023-24 epidemic of Oropouche fever in the Americas and the associated ongoing outbreak in Cuba suggests a potential state shift in the epidemiology of the disease, raising questions about which vectors are driving transmission. In this study, we conduct a systematic review of vector competence experiments with Oropouche virus (OROV, Orthobunyavirus) that were published prior to the 2023-24 epidemic season. Only seven studies were published by September 2024, highlighting the chronic neglect that Oropouche virus (like many other orthobunyaviruses) has been subjected to since its discovery in 1954. Two species of midge (Culicoides paraensis and C. sonorensis) consistently demonstrate a high competence to transmit OROV, while mosquitoes (including both Aedes and Culex spp.) exhibited an infection rate consistently below ~20%, and showed limited OROV transmission. Further research is needed to establish which vectors are involved in the ongoing outbreak in Cuba, and whether local vectors create any risk of establishment in regions with frequent travel to Latin America and the Caribbean.
Raman flow cytometry using time delay integration
Authors: Lindley Matthew , Kubo Toshiki , Devineau Stéphanie , Li Menglu , Qiao Jing , Yashiro Takuya , Iwanaga Shiroh , Moro Kazuyo , Fujita Katsumasa
Published: October 2024

Raman flow cytometry offers chemically sensitive, label-free measurement of cells and particles; however, the technique suffers from low cell throughput due to the weak Raman signal. Here, we demonstrate the use of time-delay integration to achieve Raman flow cytometry combined with dual-sided line illumination. The use of line illumination from both sides of the cell flow capillary kept the cell stream in the detection area by balancing optical force from the illumination lines. The time-delay integration allowed accumulation of Raman signals from flowing cells without sacrificing the spectrum readout rate. With the developed system, we achieved Raman flow cytometry at throughputs of 32 and 75 events per second for cell and particle detection, respectively. We applied the technique for analyzing lipid uptake in HepG2 cells and degranulation in bone marrow-derived murine mast cells.
Thermal Proteome Profiling reveals rapid proteomic responses to redox changes in specific cellular compartments
Authors: Revazian Aram , Nesterenko Alexey , Ezeriņa Daria , Luo Ting , Vertommen Didier , Gibhardt Christine S. , Bogeski Ivan , Messens Joris , Belousov Vsevolod V.
Published: October 2024

Hydrogen peroxide (H2O2) functions as a secondary messenger in cellular redox signaling, acting mainly via oxidation of protein thiols. Its spatially and temporally regulated activity within cells is essential for maintaining proper redox balance, and disruptions in these patterns can lead to oxidative stress and various related pathologies. Redox proteomics, which examines the impact of H2O2at the proteome level, typically focuses only on thiol oxidation, overlooking broader proteomic alterations and the significance of subcellular localization in these redox processes. In this study, we address these open questions by combining chemogenetics with Thermal Proteome Profiling (TPP) to map global proteome response to compartmentalized H2O2production. We identified hundreds of proteins with altered thermostability and/or abundance upon localized H2O2generation in the cytosol, nucleus, and the ER lumen, highlighting their roles in cellular responses to localized H2O2. We identified proteins such as MAP2K1, PARK7, TRAP1, and UBA2 to be highly sensitive to localized H2O2production. Furthermore, we validated their altered thermostability and found that these changes are controlled via dysregulated protein-protein interactions. This study provides a valuable resource for researchers exploring redox-mediated signal transduction and offers novel insights that could be harnessed in treating oxidative stress-induced pathologies.
Force-dependent Reorganization and Mechanostability of the Izumo1:Juno Complex Involved in Human Fertilization
Authors: Boult Sean , Pacak Paulina , Yang Byeongseon , Liu Haipei , Vogel Viola , Nash Michael A.
Published: October 2024

Izumo1:Juno-mediated adhesion between sperm and egg cells is essential for mammalian sexual reproduction. However, conventional biophysical and structural approaches have provided only limited functional insights. Using atomic force microscopy-based single- molecule force spectroscopy and all-atom steered molecular dynamic simulations, we explored the role of mechanical forces in regulating the human Izumo1:Juno complex. Our findings reveal a multi-state catch bond capable of withstanding forces up to 600 pN- mechanostability rarely observed among eukaryotic protein complexes. We further found that this mechanostability was impaired in the infertility-associated mutant, JunoH177Q. Detailed steered molecular dynamics simulations show how force-dependent reorganization of the Izumo1:Juno complex engages new binding conformations to achieve this state of high mechanostability. Overall, this study significantly enhances our understanding of the mechanical underpinnings that regulate human fertilization.
Multi-omics investigation of spontaneous T2DM macaque reveals gut microbiota promote T2DM by up-regulating the absorption of excess palmitic acid
Authors: Liu Xu , Yang Shengzhi , Xie Yuchen , Jiang Cong , Shang Ke , Luo Jinxia , Zhang Lin , Hu Gang , Liu Qinghua , Yue Bisong , Fan Zhenxin , He Zhanlong , Li Jing
Published: October 2024

Although gut microbiota and lipid metabolites have been suggested to be closely associated with type 2 diabetes mellitus (T2DM), the interactions between gut microbiota, lipid metabolites and the host in T2DM development remains unclear. Rhesus macaques may be the best animal model to investigate these relationships given their spontaneous development of T2DM. We identified eight spontaneous T2DM macaques and conducted a comprehensive study investigating the relationships using multi-omics sequencing technology. Our results from 16S rRNA, metagenome, metabolome and transcriptome analyses identified that gut microbiota imbalance, tryptophan metabolism and fatty acid β oxidation disorders, long-chain fatty acid (LCFA) accumulation, and inflammation occurred in T2DM macaques. We verified the accumulation of palmitic acid (PA) and activation of inflammation in T2DM macaques. Importantly, mice transplanted with spontaneous T2DM macaque fecal microbiota and fed a high PA diet developed prediabetes within 120 days. We determined that gut microbiota mediated the absorption of excess PA in the ileum, resulting in the accumulation of PA in the serum consequently leading to T2DM in mice. In particular, we demonstrated that the specific microbiota composition was probably involved in the process. This study provides new insight into interactions between microbiota and metabolites and confirms causative effect of gut microbiota on T2DM development.
Spectrin coordinates cortical actomyosin organization and differentiation essential for a functional epithelial barrier
Authors: Soffer Arad , Bhosale Aishwarya , Matsui Takeshi , Niessen Carien M. , Luxenburg Chen , Rübsam Matthias
Published: October 2024

Cell shape and cell fate are tightly linked. However, how cortical cytoskeletal organization that controls cell shape connects to signaling and drives cell fate changes is still poorly understood. Here we used the skin epidermis as paradigm for spatiotemporally coordinated cell shape and fate changes. Upon induction of differentiation, epidermal stem cells stratify and increasingly flatten to form a functional barrier. Here, we identify spectrin, an actin-binding membrane cytoskeleton protein, as a major regulator of epidermal cell shape, signaling and differentiation to control the formation of a functional epithelial barrier. Loss of αII-spectrin (encoded bySptan1) in the developing mouse epidermis inhibited suprabasal cell flattening, differentiation, and epidermal barrier function. Spectrin cortical localization required E-cadherin and actomyosin, while spectrin itself controls cortical actomyosin organization. In detail, using high resolution imaging and laser ablation revealed that spectrin was essential to form actin-based honeycomb-like cortical lattices that are essential to maintain cortical tension and structural integrity. We found that spectrin-dependent actomyosin organization controlled the activity and localization of the growth factor receptor EGFR, and the cation channel TRPV3, known to activate the enzyme transglutaminase essential for barrier function. Indeed, loss of spectrin, E-cadherin or actomyosin inhibition reduce TGM1 activity. Together, our results provide novel insights into how cortical organization and mechanics regulate cell shape and spatially activate signals necessary for differentiation and epithelial tissue function.
Exploring the Antifibrotic Potential of the heparan sulfate mimetic OTR4120: Insights from Preclinical Models
Authors: Marega Manuela , Mejdoubi-Charef Najet , Wiegard David , Khan Muzamil Majid , Bartkuhn Marek , Gambs Laura , Procida-Kowalski Tara , Wilhelm Jochem , Vasquez-Pacheco Esmeralda , Noori Afshin , Dong Ying , Zheng Yi , Chu Xuran , Lingampally Arun , Zukowska Joanna , Charef Said , Chiappini Franck , Choppin Agnes , Papy Garcia Dulce , Pepperkok Rainer , Muley Thomas , Winter Hauke , Ruppert Clemens , Seeger Werner , Gunther Andreas , Barritault Denis , Chen Chengshui , Chao Cho-Ming , Rivetti Stefano , Bellusci Saverio
Published: October 2024

Rationale

Idiopathic pulmonary fibrosis (IPF) is a debilitating lung disease characterized by excessive deposition of extracellular matrix (ECM), resulting in lung function impairment. Heparan sulfate mimetics (HSm) have been suggested to have potential antifibrotic effects by regulating ECM. This study aims to investigate the impact of a specific HSm named OTR4120 on fibrotic processes inex vivo,in vitroandin vivomodels.

Methods

Human Precision Cut Lung Slices (hPCLS) treated with a fibrotic cocktail alone or with OTR4120 were evaluated using second-harmonic imaging microscopy (SHIM) to assess collagen deposition. Human embryonic fibroblast WI-38 cell line and primary fibroblasts obtained from human donors were differentiated into myofibroblasts (MYF) using TGF-β1 and treated with OTR4120 or a control vehicle. Gene expression analysis for MYF markers was performed using quantitative PCR (qPCR). Protein expression of MYF markers was evaluated using immunofluorescence techniques. Bulk-RNA sequencing analysis on WI-38 cells cultured under different experimental conditions was conducted. Finally, the therapeutic effects of OTR4120 on a bleomycin-induced fibrosis mouse model were investigated.

Results

SHIM analysis on OTR4120-treated hPCLS showed a decrease in collagen deposition. OTR4120 treatment of primary fibroblasts and WI-38 cells exposed to TGF-β1 significantly reduced the expression of MYF markers. Bulk-RNA sequencing analysis on OTR4120-treated WI-38 cells showed significant impacts on fibrosis-related processes. Therapeutic application of OTR4120in vivoto bleomycin-induced fibrosis mice resulted in enhanced fibrosis resolution.

Conclusion

OTR4120 has potential therapeutic benefits as an antifibrotic agent in the context of lung fibrosis. Further investigations are necessary to understand the precise mechanism through which OTR4120 exerts its antifibrotic effects.
Development and validation of an open-source Hand Laterality Judgement Task for in-person and online studies
Authors: Moreno-Verdú Marcos , McAteer Siobhán M , Waltzing Baptiste M , Van Caenegem Elise , Hardwick Robert M
Published: October 2024

The Hand Laterality Judgement Task (HLJT) is considered a measure of the ability to manipulate motor images. The ‘biomechanical constraints’ effect (longer reaction times for hand rotations towards anatomically difficult versus biomechanically easier movements) is considered the behavioural hallmark indicating motor imagery is being used. Previous work has used diverse HLJT paradigms, and there is no standardized procedure for the task. We developed an open-source, freely available version of the HLJT in PsychoPy2, which needs no programming skills and is highly customisable. Some studies suggest responding to the HLJT with the hands may interfere with performance, which would limit practical application of the task. We examined this potential issue using in-person and online versions. For the in-person version, 40 right-footed/handed individuals performed the HLJT with their feet or bimanually (N=20 each). For the online version, 60 right-handed individuals performed the task bimanually or unimanually (N=20 each). Bayesian mixed-effect analyses quantified the evidence for and against equivalence within and between the in-person and online versions. Both versions replicated previously described behavioural phenomena, including effects of angle, hand view, and the ‘biomechanical constraints’ effect. While responding with different effectors modified overall reaction times, it did not interact with other factors analysed, and did not affect accuracy or the ‘biomechanical constraints’ effect. There was also evidence for equivalence between in-person and online bimanual groups for all measures. We conclude that this open-source, standardized HLJT protocol (available athttps://osf.io/8h7ec/) can reliably detect previously identified effects and works equally well in-person or online.
A Multi-Modal Genomic Knowledge Distillation Framework for Drug Response Prediction
Authors: Ge Shuang , Sun Shuqing , Xu Huan , Cheng Qiang , Ren Zhixiang
Published: October 2024

Precision oncology utilizes genomic data to tailor treatment to individuals. Cancer drug sensitivity studies can predict the response levels of different drugs for the same cultured cancer cell line, which is beneficial for personalized medicine. Recent studies have demonstrated that integrating multi-modal genomic data, e.g., gene expression, mutation, copy number alteration, methylation, can provide comprehensive knowledge and improve drug response prediction. Although multimodal genomic profiles are generally available from public datasets, only gene expression data is commonly used in clinical settings. In this study, we propose a framework for privileged information knowledge distillation to transfer knowledge from a multi-modal genomic teacher network, using only gene expression for inference. Specifically, we train a teacher network by feature re-weighting based on inter-modality dependencies and align the inter-sample correlations through our proposed relation-aware differentiation distillation. Experiments on the Genomics of Drug Sensitivity in Cancer (GDSC) dataset demonstrate that our framework improves drug response prediction by about 6% compared to the baseline and outperforms state-of-the-art methods. Transferable studies performed on missing GDSC data and clinical datasets further confirm the feasibility of our model for predicting drug responses using only gene expression data.