bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the specific predictive ability of multiple domains of spatial ability on STEM educational outcomes
Authors: Zhou Quan , Wang Ziye , Rimfeld Kaili , Allegrini Andrea G. , Plomin Robert , Malanchini Margherita
Published: December 2024

Abstract

Research has implicated spatial ability as a robust predictor of aptitude, interest, and choice in STEM education and career pursuits. We address three under-explored questions regarding the role of spatial ability in STEM. First, can spatial ability consistently predict STEM success beyond other cognitive skills? Second, what aspects of spatial ability, if any, can predict success in STEM more accurately? Third, to what extent can genetic and environmental factors account for these predictions?

We addressed these questions by leveraging data from the Twins Early Development Study (N = 3,936; age range = 16-22) and using 16 tests that assessed three domains of spatial ability: navigation, object manipulation, and visualization. Results show that all three domains are highly predictive of STEM educational outcomes, especially STEM degree choice. These associations persisted after accounting for verbal and general cognitive abilities (g), albeit attenuated. Associations were strongest for tests of object manipulation (e.g., 2D and 3D drawing, pattern assembly and mental rotation). Genetic factors accounted for most of the observed associations between spatial ability and STEM outcomes (62% - 86%) —genetic variance was mostly shared withg(∼ 40%) and, to a lesser extent, verbal ability (∼ 25%).

Our findings highlight the potential utility of spatial ability as a specific predictor of success in STEM education and career choice beyond other cognitive abilities. Screening for and training spatial skills is likely useful for identifying potential, fostering talent, and improving outcomes in STEM.

Significance Statement

Leveraging a comprehensive battery of 16 spatial ability tests across multiple domains, we show that spatial ability has specific utility for predicting success in STEM education. Spatial skills predict success in STEM above and beyond other cognitive abilities, particularly when it comes to STEM engagement and pursuing further STEM education. Thus, spatial skills may be a fruitful target for policymakers, stakeholders, and industries looking to develop interventions, identify and foster talent, and reduce outcome disparities.
Sex-dimorphic gene regulation in murine macrophages across niches
Authors: McGill Cassandra J. , White Olivia S. , Lu Ryan J. , Sampathkumar Nirmal K. , Benayoun Bérénice A.
Published: December 2024

Macrophages are a key cell type of the innate immune system and are involved at all steps of inflammation: (i) they present antigens to initiate inflammation, (ii) they clear up foreign bodies through phagocytosis, and (iii) they resolve inflammation by removing or deactivating mediator cells. Many subtypes of macrophages have been identified, classified by their niche and/or embryonic origin. In order to better develop therapies for conditions with macrophage dysfunction, it is crucial to decipher potential sex-differences in key physiological mediators of inflammation so that treatment efficacy can be ensured regardless of biological sex. Here, we conduct a meta-analysis approach of transcriptomics datasets for malevs. female mouse macrophages across 8 niches to characterize conserved sex-dimorphic pathways in macrophages across origins and niches. For this purpose, we leveraged new and publicly available RNA-sequencing datasets from murine macrophages, preprocessed these datasets and filtered them based on objective QC criteria, and performed differential gene expression analysis using sex as the covariate of interest. Differentially expressed (DE) genes were compared across datasets and macrophage subsets, and functional enrichment analysis was performed to identify sex-specific functional differences. Consistent with their presence on the sex chromosomes, three genes were found to be differentially expressed across all datasets (i.e.Xist,Eif2s3y, andDdx3y). More broadly, we found that female-biased pathways across macrophage niches are more consistent than male-biased pathways, specifically relating to components of the extracellular matrix. Our findings increase our understanding of transcriptional similarities across macrophage niches and underscore the importance of including sex as a biological variable in immune-related studies.

Highlights

Across 17 independently transcriptomic macrophage datasets, three genes are always differentially expressed between males and females:Ddx3y,Eif2s3y, andXist.

Jaccard analysis reveals female macrophages have more stereotypical transcriptional profile than male macrophages across niches.

Functional enrichment analyses show that female-biased pathways across macrophage subtypes are enriched for extracellular matrix-related genes.
Protein CREATE enables closed-loop design ofde novosynthetic protein binders
Authors: Lourenço Alec , Subramanian Arjuna , Spencer Ryan , Anaya Michael , Miao Jiapei , Fu William , Chow Eric , Thomson Matt
Published: December 2024

Proteins have proven to be useful agents in a variety of fields, from serving as potent therapeutics to enabling complex catalysis for chemical manufacture. However, they remain difficult to design and are instead typically selected for using extensive screens or directed evolution. Recent developments in protein large language models have enabled fast generation of diverse protein sequences in unexplored regions of protein space predicted to fold into varied structures, bind relevant targets, and catalyze novel reactions. Nevertheless, we lack methods to characterize these proteins experimentally at scale and update generative models based on those results. We describe Protein CREATE (Computational Redesign via an Experiment-Augmented Training Engine), an integrated computational and experimental pipeline that incorporates an experimental workflow leveraging next generation sequencing and phage display with single-molecule readouts to collect vast amounts of quantitative binding data for updating protein large language models. We use Protein CREATE to generate and assay thousands of designed binders to IL-7 receptorαand insulin receptor with parallel positive and negative selections to identify on-target binders. We discover not only individual novel binders but also features of ligand-receptor binding, including preservation of the IL7Rα- ligand hydrophobic interface specifically and existence of multiple approaches to contact the insulin receptor. We also demonstrate the importance of structural features, such as the lack of unpaired cysteine residues, toward design fidelity and find computational pre-screening metrics, such as interchain predicted TM scoring (iPTM), while useful, are imperfect predictors as they neither guarantee experimental binding nor rule it out. We use the data collected from Protein CREATE to score designs from the initial generative models. Globally, Protein CREATE will power future closed-loop design-build-test cycles to enable fine-grained design of protein binders.
Location-Dependent Differences in Cardiac and Skeletal Muscle Dysfunction Associated With Truncating Titin (ttn.2) Variants
Authors: Santiago Celine F. , Huttner Inken G , Brien Ailbhe O , Bennett Pauline M. , Cvetkovska Jasmina , Chand Renee , Holt Mark , Trivedi Gunjan , Wang Louis W. , Smith Kelly A. , Gautel Mathias , Fatkin Diane , Hinits Yaniv
Published: December 2024

Background

Truncating variants (TTNtv) in theTTNgene, encoding the giant sarcomeric protein titin, cause a range of human cardiac and skeletal muscle disorders of varying penetrance and severity. The effects of variant location on clinical manifestations are incompletely understood.

Methods

We generated six zebrafish lines carrying tv in thettn.2gene at the Z-disk, I-band, A-band, and M-band titin regions. Expression of titin transcripts was evaluated using qPCR. Phenotype analysis was performed during embryonic development and in adult hearts.

Results

Using location-specific primers, we found a significant reduction of Z-disk and I-bandttn.2transcripts in all homozygous embryos but levels of A-band and M-band transcripts were reduced only in lines with truncations distal to thecronospromoter. Homozygous embryos uniformly died by 7-10 days post fertilization with marked impairment of cardiac morphology and function. Skeletal muscle motility and sarcomere organization were more disrupted in mutants with truncations distal to thecronospromoter compared to those proximal. The most C-terminal line (e232), which lacked only the titin kinase and M-band regions, differed from other lines, with homozygous embryos showing incorporation of truncated Ttn.2/Cronos protein and normal sarcomere assembly, but selective degradation of fast skeletal muscle sarcomeres. Heterozygous embryos were phenotypically indistinguishable from wild-type. High-frequency echocardiography in adult heterozygous fish showed reduced ventricular contraction under resting conditions in A-band mutants. Heterozygous Z-disk and I-band mutants had no significant baseline impairment but were unable to augment ventricular contraction in response to acute adrenaline exposure, indicating a lack of cardiac reserve.

Conclusions

Our data suggest that cardiac and skeletal muscle dysfunction associated with truncatingttn.2variants is influenced by age, variant location, and the amount of functional titin protein. The distinctive phenotype associated with distal C-terminal truncations may reflect different requirement for C-terminal titin for maintenance of fast, slow and cardiac muscle sarcomeres.
Machine learning analysis of population-wide plasma proteins identifies hormonal biomarkers of Parkinson’s Disease
Authors: Chaudhry Fayzan , Kim Tae Wan , Elemento Olivier , Betel Doron
Published: December 2024

As the number of Parkinson’s patients is expected to increase with the growth of the aging population there is a growing need to identify new diagnostic markers that can be used cheaply and routinely to monitor the population, stratify patients towards treatment paths and provide new therapeutic leads. Genetic predisposition and familial forms account for only around 10% of PD cases [1] leaving a large fraction of the population with minimal effective markers for identifying high risk individuals. The establishment of population-wide omics and longitudinal health monitoring studies provides an opportunity to apply machine learning approaches on these unbiased cohorts to identify novel PD markers. Here we present the application of three machine learning models to identify protein plasma biomarkers of PD using plasma proteomics measurements from 43,408 UK Biobank subjects as the training and test set and an additional 103 samples from Parkinson’s Progression Markers Initiative (PPMI) as external validation. We identified a group of highly predictive plasma protein markers including known markers such as DDC and CALB2 as well as new markers involved in the JAK-STAT, PI3K-AKT pathways and hormonal signaling. We further demonstrate that these features are well correlated with UPDRS severity scores and stratify these to protective and adversarial features that potentially contribute to the pathogenesis of PD.
Exploration of post-insertion challenges edentulous patients present to dental practitioners during removable complete denture rehabilitation in Makerere University Dental Hospital in Uganda
Authors: Nono David , Bagenda Godfrey , Okullo Isaac , Rwenyonyi Charles Mugisha
Published: December 2024

Background

Edentulism in a major global burden that contributes to disability and impairment. Globally, edentulous patients frequently receive removable complete dentures (RCDs) and though crucial, effective adaptation is still difficult. RCD remains a preferred treatment modality for edentulous patients worldwide. The frequency of full edentulism varies both within and between countries. In Uganda, 1.8% of people aged 20 years and above are edentulous. Despite advances in dental technology and material science, the successful adaptation of RCDs remains a challenge for both patients and dental professionals. Our present study aimed to explore the post-insertion challenges patients presented to dental practitioners during their rehabilitation with removable complete dentures in Makerere University Dental Hospital.

Methods

This was a qualitative study using a phenomenological technique and purposive sampling to select 25 participants. After obtaining institutional review board approval and written informed consent, semi-structured in-depth and key informant interviews of dental practitioners were conducted and the data were analyzed thematically.

Results

It was revealed that patients with RCDs commonly reported substantial post-insertion challenges like pain and discomfort, drooling, difficulty speaking, eating, oral hygiene and salivating. Patients’ confidence and self-esteem were severely influenced by their displeasure with the way their dentures looked. Furthermore, patients frequently had denture instability. In addition, patients received helpful post-insertion advice that emphasized the significance of oral health education and support from dental practitioners. This advice included instructions on denture cleaning, maintenance and adaption.

Conclusion

The present study identified several post-insertion challenges faced by patients after receiving RCDs. It is important to provide integrated support for patients and practitioners to enhance effective RCD therapy.
Fetal Growth Disorders Detection During First Trimester Gestation Through Comprehensive Maternal Circulating DNA Profiling
Authors: Cortese Rene , Cataldo Kylie , Hummel Justin , Smith Gracie , Ortega Madison , Richey Madison , Winn Hung , Gozal David , Goodman Jean Ricci
Published: December 2024

STRUCTURED ABSTRACT

BACKGROUND

Early diagnosis, close follow-up and timely delivery constitute the main elements for appropriate detection and management of Fetal Growth Disorders (FGD). We hypothesized that fetoplacental FGD-associated alterations can be detected in circulating DNA (cirDNA) samples isolated from maternal blood, as early as the first gestational trimester. To study whether markers in maternal cirDNA may facilitate FGD early detection, we profiled plasma cirDNA from maternal samples prospectively collected during first gestational trimester.

METHODS

Plasma cirDNA was isolated from samples prospectively collected during first trimester gestation (n=56). Small, Large and Appropriate for Gestational Age (SGA n=11, LGA n=18, and AGA n=29, respectively) status was determined at birth according to weight and gestational age. cirDNA amount, fragmentation, mitochondrial/nuclear ratio and cirDNA methylation profiles were quantified using qPCR-based assays. Machine learning approaches were applied to build a molecular signature for prediction of LGA and SGA. Prediction accuracy was assessed by Receiving-Operating Curve (ROC) analysis, and Positive and Negative Predictive values (PPV and NPV, respectively) were calculated.

RESULTS

Total concentration of plasma cirDNA, cirDNA fragmentation and ratio of mitochondrial/nuclear cirDNA were increased in SGA and LGA compared to AGA pregnancies. DNA methylation profiles also shown distinctive patterns. Out of the 10 selected loci, we detected 5 genes (HSD2,RASSF1,CYP19A1,IL10, andLEP) showing significant differential methylation differences (p<0.05) across the SGA, AGA and LGA samples at first trimester. We combined these molecular and epigenetic cirDNA markers in a signature that reliably discriminates between FGD and AGA pregnancies with high accuracy (AUC>0.95), achieving 88.8% PPV and 85.7% NPV.

CONCLUSIONS

Our findings show that maternal blood cirDNA profiles accurately detects early gestation FGD. The proposed novel marker panel hold great potential for implementation of low invasive approaches for reliable prediction of FGDs, enabling a disruptive path toward precision medicine in FGD.
mHMG-DTI: a drug-target interaction prediction framework combining modified Hierarchical Molecular Graphs and improved Convolutional Block Attention Module
Authors: Yang Zerui , Li Yinqiao , Matsuda Yudai , Song Linqi
Published: December 2024

Drug-target interactions (DTIs) are fundamental to understanding the therapeutic mechanisms of drugs, yet accurately predicting these interactions remains a significant challenge in drug discovery. Current computational approaches often fail to capture essential molecular motifs and spatial information of proteins, limiting their effectiveness, particularly when encountering proteins or compounds absent in the training datasets. To address these limitations, we propose mHMG-DTI, a novel framework that leverages an improved Convolutional Block Attention Module (iCBAM) for enhanced protein feature extraction and modified Hierarchical Molecular Graphs (mHMGs) for comprehensive molecular encoding. This hierarchical approach not only captures detailed local structures and broader connectivity patterns but also incorporates guiding knowledge to improve feature representation. Across a total of 16 experimental evaluations on four benchmark datasets spanning both classification and regression tasks, mHMG-DTI surpasses existing baseline models in 11 cases. These results highlight the potential of mHMG-DTI to enhance DTI prediction accuracy, thereby accelerating the drug discovery process and providing valuable insights into drug resistance and side effect mechanisms.

Contact

zeruiyang2-c@my.cityu.edu.hk
Genetic ancestry and population structure in the All of Us Research Program cohort
Authors: Sharma Shivam , Nagar Shashwat Deepali , Pemu Priscilla , Zuchner Stephan ,   SEEC Consortium, Mariño-Ramírez Leonardo , Meller Robert , Jordan I. King
Published: December 2024

The NIH All of Us Research Program (All of Us) aims to build one of the world’s most diverse population biomedical datasets in support of equitable precision medicine. For this study, we analyzed participant genomic variant data to assess the extent of population structure and to characterize patterns of genetic ancestry for theAll of Uscohort (n=297,549). Unsupervised clustering of genomic principal component analysis (PCA) data revealed a non-uniform distribution of genetic diversity and substantial population structure in theAll of Uscohort, with dense clusters of closely related participants interspersed among less dense regions of genomic PC space. Supervised genetic ancestry inference was performed using genetic similarity betweenAll of Usparticipants and global reference population samples. Participants show diverse genetic ancestry, with major contributions from European (66.4%), African (19.5%), Asian (7.6%), and American (6.3%) continental ancestry components. Participant genetic similarity clusters show group-specific genetic ancestry patterns, with distinct patterns of continental and subcontinental ancestry among groups. We also explored how genetic ancestry changes over space and time in the United States (US). African and American ancestry are enriched in the southeast and southwest regions of the country, respectively, whereas European ancestry is more evenly distributed across the US. The diversity ofAll of Usparticipants’ genetic ancestry is negatively correlated with age; younger participants show higher levels of genetic admixture compared to older participants. Our results underscore the ancestral genetic diversity of theAll of Uscohort, a crucial prerequisite for genomic health equity.
Integrative multiomics analysis of metabolic dysregulation induced by occupational benzene exposure in mice
Authors: Scofield Sydney , Koshko Lisa , Stilgenbauer Lukas , Booms Alix , Berube Roxanne , Kassotis Christopher , Lin Chung-Ho , Jang Hyejeong , Kim Seongho , Stemmer Paul , Lempradl Adelheid , Sadagurski Marianna
Published: December 2024

Background

Type 2 Diabetes Mellitus (T2DM) is a significant public health burden. Emerging evidence links volatile organic compounds (VOCs), such as benzene to endocrine disruption and metabolic dysfunction. However, the effects of chronic environmentally relevant VOC exposures on metabolic health are still emerging.

Objective

Building on our previous findings that benzene exposure at smoking levels (50 ppm) induces metabolic impairments in male mice, we investigated the effects of occupationally relevant, below OSHA approved, benzene exposure on metabolic health.

Methods

Adult male C57BL/6 mice were exposed to 0.9ppm benzene 8 hours a day for 9 weeks. We assessed measures of metabolic homeostasis and conducted RNA and proteome sequencing on insulin-sensitive organs (liver, skeletal muscle, adipose tissue).

Results

This low-dose exposure caused significant metabolic disruptions, including hyperglycemia, hyperinsulinemia, and insulin resistance. Transcriptomic analysis of liver, skeletal muscle, and adipose tissue identified key changes in metabolic and immune pathways especially in liver. Proteomic analysis of the liver revealed mitochondrial dysfunction as a shared feature, with disruptions in oxidative phosphorylation, mitophagy, and immune activation. Comparative analysis with high-dose (50 ppm) exposure showed both conserved and dose-specific transcriptomic changes in liver, particularly in metabolic and immune responses.

Conclusions

Our study is the first to comprehensively assess the impacts of occupational benzene exposure on metabolic health, highlighting mitochondrial dysfunction as a central mechanism and the dose-dependent molecular pathways in insulin-sensitive organs driving benzene-induced metabolic imbalance. Our data indicate that current OSHA occupational exposure limits for benzene are insufficient, as they could result in adverse metabolic health in exposed workers, particularly men, following chronic exposure.
Distinct Nuclear and Cytoplasmic Transcriptomic Signatures Reveal Transcription Alone Is Insufficient to Determine Glucose-Induced Transcriptomic Dynamics
Authors: Bagheri Atefeh , Kim Jinsil , Jiang Peng
Published: December 2024

Glucose profoundly influences cellular transcriptomes, but whether these changes are primarily driven by transcription remains unclear. Traditional bulk RNA sequencing, which interrogates total mRNA from whole cells, obscures distinct dynamics of nuclear and cytoplasmic transcriptomes. Nuclear RNA levels primarily reflect transcriptional activity, whereas cytoplasmic RNA levels are shaped by both transcription and post-transcriptional processes, such as RNA export, stability, and degradation. In this study, we systematically investigate glucose-induced transcriptomic responses in a subcellular location- and cell type-specific manner using three cell lines: FHC (normal colonic epithelial cells), MCF10A (normal breast epithelial cells), and MCF7 (metastatic breast cancer cells). Our findings reveal that, although nuclear and cytoplasmic mRNA levels show strong global correlations, glucose-induced changes in mRNA abundance exhibit minimal concordance between the nucleus and cytoplasm. Additionally, glucose-induced changes in exon inclusion levels often diverge between the nucleus and cytoplasm, underscoring the importance of post-transcriptional processes in shaping the cytoplasmic transcriptome response to glucose level changes. Glucose-induced differentially expressed genes (DEGs) and differentially spliced exons (ΔPSI) are enriched in distinct pathways exhibiting unique enrichment patterns depending on the subcellular location and cell line. These findings underscore the complexity of glucose-induced transcriptomic regulation, demonstrating that transcription alone is insufficient to explain the observed dynamics.
Impact of dopaminergic modulation on the state transitions of striatal medium spiny neuron sub-types – a computational study
Authors: Anisetty Nitin , Manchanda Rohit
Published: December 2024

Medium spiny neurons (MSN) of the striatum are known for their bistable membrane potential leading to two states – a hyperpolarized down-state and relatively depolarized up-state. Glutamatergic inputs from the hippocampus play a key role in switching the cell to up-state. This gating is known to play a key role in regulating when other synaptic inputs, such as from the cortex, should generate action potentials and when they should be considered as noise. Therefore, it is crucial for the transition between states to occur normally as abnormal gating has implications in conditions such as Schizophrenia. Although dopamine is reported to modulate ion channels of MSN sub-types – dMSN and iMSN, it’s influence on the state transition times and up-state dwell times are being reported here. This was done using biophysically constrained spiny models of dMSN and iMSN with explicit dopamine receptors. Additionally, strong correlation between state transition times and spiking frequencies of MSN sub-types was observed.
FGF21 Analogue PF-05231023 on Alcohol Consumption and Neuronal Activity in the Nucleus Accumbens
Authors: Cooley Bart J. , Hanbury-Brown Cassandra V. Occelli , Choi Eun A. , Heller Willow A. , Lim Alyssa W. , Lawrence Andrew J. , Haber Paul S. , McNally Gavan P. , Millan E. Zayra
Published: December 2024

Fibroblast growth factor 21 (FGF21) is a liver-derived hormone known to suppress alcohol consumption in mice and non-human primates. However, the role of FGF21 in modulating environmental and behavioural factors driving alcohol consumption—such as cue-driven responses and effortful actions to obtain alcohol—and its effects on neural activity related to consumption, remain unclear. Here, we evaluated the impact of PF-05231023, a long-acting FGF21 analogue, across multiple dimensions of alcohol consumption and motivation. PF-05231023 reduced alcohol intake and preference in a dose-and sex-specific manner; diminished approach behaviours following an alcohol but not sucrose cue; and decreased lever-pressing under a progressive-ratio schedule, both alone and when combined with the GLP-1 agonist Exendin-4. Additionally, PF-05231023 altered the microstructure of alcohol consumption by shortening drinking bouts and increased the recruitment of nucleus accumbens (Acb) neurons associated with bout termination. These findings demonstrate that PF-05231023 broadly suppresses alcohol-motivated behaviours and that targeting FGF21 signaling in combination with GLP-1 agonists may enhance therapeutic efficacy. Mechanistically, the observed reductions in alcohol consumption following PF-05231023 appear to involve diminished alcohol palatability and modulation of neuronal activity from distinct subsets of Acb neurons.
Non-Canonical Cytochrome P450 Enzymes in Nature
Authors: Nguy Andy K. L. , Ireland Kendra A. , Kayrouz Chase M. , Cáceres Juan Carlos , Greene Brandon L. , Davis Katherine M. , Seyedsayamdost Mohammad R.
Published: December 2024

Cytochrome P450s (CYPs) are a superfamily of thiolate-ligated heme metalloenzymes principally responsible for the hydroxylation of unactivated C–H bonds. The lower-axial cysteine is an obligatory and universally conserved residue for the CYP enzyme class. Herein, we challenge this paradigm by systematically identifying non-canonical CYPs (ncCYPs) that do not harbor a cysteine ligand. Our bioinformatic search reveals 20 distinct ncCYP families with diverse ligands encoded in microbial genomes. We characterize a native serine-ligated CYP with a high-spin ferric resting state. Its crystal structure clearly shows a typical CYP fold and a serine alkoxide as a lower axial heme ligand. In addition, we report the discovery and characterization of the first native selenocysteine-ligated CYP in nature. Our findings radically expand the CYP metalloenzyme family.
Geography is a stronger predictor of diversification of monogenean parasites (Platyhelminthes) than host relatedness in characid fishes of Middle America
Authors: Alda Fernando , Mendoza-Franco Edgar F. , Hanson-Regan William , Reina Ruth G. , Bermingham Eldredge , Torchin Mark
Published: December 2024

Host-parasite associations have historically been considered compelling examples of coevolution and useful in examining cospeciation. However, modern molecular methods have revealed more complex dynamics than previously assumed, with host-switching events appearing commonly across taxa and challenging traditional views of strict coevolution in host-parasite relationships. Monogenean parasites are considered highly host-specific and have long served as models for probing evolution of host-parasite associations, particularly in differentiating geographic and phylogenetic patterns of parasite diversification. We investigated the phylogeographic patterns of monogenean ectoparasites associated with four species of characid fishes across Panama, Nicaragua, and Mexico. Our hypothesis posited that parasite diversity and community structure would be more strongly correlated with host species (suggesting cospeciation) than with geographic location (indicative of allopatric speciation). We found high genetic differentiation among parasites and their hosts across different locations. However, while geography explained the genetic structure of both host fishes and parasites, the observed patterns were neither congruent nor parallel. Parasite community structure and genetic similarity were consistently better explained by geographic location than by host species, although both factors played a significant role. Contrary to our predictions, we found no evidence of cospeciation. Instead, the diversification of these monogenean parasites appears to be primarily driven by their ability to switch hosts. At this taxonomical scale, host-switching is mediated by the geographical proximity of potential hosts, underscoring the importance of spatial factors in parasite evolution.
Collecting, detecting and handling non-wear intervals in longitudinal light exposure data
Authors: Guidolin Carolina , Zauner Johannes , Hartmeyer Steffen Lutz , Spitschan Manuel
Published: December 2024

In field studies using wearable light loggers, participants often need to remove the devices, resulting in non-wear intervals of varying and unknown duration. Accurate detection of these intervals is an essential step during data pre-processing. Here, we deployed a multi-modal approach to collect non-wear time during a longitudinal light exposure campaign and systematically compare non-wear detection strategies. Healthy participants (n=26; mean age 28±5 years, 14F) wore a near-corneal plane light logger for one week and reported non-wear events in three ways: pressing an “event marker” button on the light logger, placing it in a black bag, and using an app-based Wear log. Wear log entries, checked twice daily, served as ground truth for non-wear detection, showing that non-wear time constituted 5.4±3.8% (mean±SD) of total participation time. Button presses at the start and end of non-wear intervals were identified in >85.4% of cases when considering time windows beyond one minute for detection. To detect non-wear intervals based on black bag use and lack of motion, we employed an algorithm detecting clusters of low illuminance and clusters of low activity. Performance was higher for illuminance (F1=0.76) than activity (F1=0.52). Light exposure metrics derived from the full dataset, a dataset filtered for non-wear based on self-reports, and a dataset filtered for non-wear using the low illuminance clusters detection algorithm showed minimal differences. Our results highlight that while non-wear detection may be less critical in high-compliance cohorts, systematically collecting and detecting non-wear intervals is feasible and important for ensuring robust data pre-processing.
Reactivation of reward representations associated with the reinforcement of behavior
Authors: Tong Ai Phuong S. , Sreekumar Vishnu , Inati Sara K. , Zaghloul Kareem A. , Woolrich Mark W.
Published: December 2024

Reward-related representations are found distributed throughout many human subcortical and neocortical regions that support different neural processes. These representations get reinstated for different but related tasks. There is rising evidence that representations reactivate during learning to reinforce prior rewarding choices. However, there remains a critical lack of understanding for whether and how reactivations in humans can facilitate behavioral reinforcement. To investigate this, we recorded from the temporal lobe and prefrontal cortex with intracranial electrocorticography while human subjects learnt two-choice decisions across two different scenes. Crucially, subjects were able to straightforwardly reactivate knowledge gained in a prior scene to make decisions in the current scene, but only when the reward contingencies stayed the same between the two scenes. Using a Bayesian learner, we inferred reward expectation from choice behavior, and measured representations of these reward expectations in electrocorticography data. We found that the representations of reward expectation in the medial temporal lobe and orbitofrontal cortex were reactivated, only when the subjects could straightforwardly transfer knowledge between the two scenes. In the anterior temporal lobe, the reactivation of reward representations increased as learning increased, suggesting an area of plasticity during learning. This work presents a novel framework for measuring the reinforcement, or reactivation, of representations from human electrophysiology during the reinforcement of behavior.

Significance statement

This study provides a framework for how the brain processes and reinstates reward-related information during the reinforcement of behavior. Using intracranial electrocorticography, the researchers found that reward information is encoded in distant brain regions, the medial temporal lobe and orbitofrontal cortex. These representations are dynamically reinstated across scenes when reward contingencies align and when knowledge can be transferred. Additionally, reward-related representations in the anterior temporal lobe become increasingly reinforced or reinstated as learning progresses, revealing an area of plasticity during learning. These findings offer new insights into the neural mechanisms underlying decision-making and highlight potential avenues for addressing conditions like addiction or depression, where reward processing and decision-making are disrupted.
Computationally reconstructing the evolution of cancer progression risk
Authors: Cao Kefan , Schwartz Russell
Published: December 2024

Understanding the evolution of cancer in its early stages is critical to identifying key drivers of cancer progression and developing better early diagnostics or prophylactic treatments. Early cancer is difficult to observe, though, since it is generally asymptomatic until extensive genetic damage has accumulated. In this study, we develop a computational approach to infer how once-healthy cells enter into and become committed to a pathway of aggressive cancer. We accomplish this through a strategy of using tumor phylogenetics to look backwards in time to earlier stages of tumor development combined with machine learning to infer how progression risk changes over those stages. We apply this paradigm to point mutation data from a set of cohorts from the Cancer Genome Atlas (TCGA) to formulate models of how progression risk evolves from the earliest stages of tumor growth, as well as how this evolution varies within and between cohorts. The results suggest general mechanisms by which risk develops as a cell population commits to aggressive cancer, but with significant variability between cohorts and individuals. These results imply limits to the potential for earlier diagnosis and intervention while also providing grounds for hope in extending these beyond current practice.

Availability

The code used to conduct the analysis is available at:https://github.com/kefanc2/CancerRisk
Gait Adaptations Under Functional Asymmetry: Exploring the Role of Step Width, Step Length, and CoM in Lateral Stability
Authors: Baček Tomislav , Oetomo Denny , Tan Ying
Published: December 2024

Bipedal gait is inherently unstable, requiring a complex interplay between foot placement and centre of mass (CoM) movement to maintain balance. While various factors are known to impact walking balance, few studies have explored the specific effects of functional asymmetry on lateral stability. This study investigates how step length, step width, and CoM adaptations impact lateral gait stability in healthy young adults walking with and without a functional asymmetry induced by fully extending the left knee. The results show that step length remains unaffected by functional asymmetry regardless of speed, while step width increases under the constraint. This adjustment increases the base of support; however, the concurrent increase in lateral CoM movement reduces overall lateral stability. These findings offer valuable insights into fundamental gait adaptation and stability mechanisms, with potential implications for designing rehabilitation strategies for individuals with gait asymmetry.
PRISM: A Python Package for Interactive and Integrated Analysis of Multiplexed Tissue Microarrays
Authors: Tubelleza Rafael , Kilgallon Aaron , Tan Chin Wee , Monkman James , Fraser John , Kulasinghe Arutha
Published: December 2024

Tissue microarrays (TMAs) enable researchers to analyse hundreds of tissue samples simultaneously by embedding multiple samples into single arrays, enabling conservation of valuable tissue samples and experimental reagents. Moreover, profiling TMAs allows efficient screening of tissue samples for translational and clinical applications. Multiplexed imaging technologies allow for spatial profiling of proteins at single cell resolution, providing insights into tumour microenvironments (TMEs) and disease mechanisms. High-plex spatial single cell protein profiling is a powerful tool for biomarker discovery and translational cancer research, however, there remain limited options for end-to-end computational analysis of this type of data. Here, we introduce PRISM, a Python package for interactive, end-to-end analyses of TMAs with a focus on translational and clinical research using multiplexed proteomic data from the CODEX, Phenocycler Fusion (Akoya Biosciences), Comet (Lunaphore), MACSima (Miltenyi Biotec), CosMx and Cellscape (Bruker Spatial Biology) platforms. PRISM leverages the SpatialData framework to standardise data storage and ensure interoperability with single cell and spatial analysis tools. It consists of two main components: TMA Image Analysis for marker-based tissue masking, TMA dearraying, cell segmentation, and single cell feature extraction; and AnnData Analysis for quality control, clustering, iterative cell-type annotation, and spatial analysis. Integrated as a plugin within napari, PRISM provides an intuitive and purely interactive graphical interface for real-time and human-in-the-loop analyses. PRISM supports efficient multi-resolution image processing and accelerates bioinformatics workflows using efficient scalable data structures, parallelisation and GPU acceleration. By combining modular flexibility, computational efficiency, and a completely interactive interface, PRISM simplifies the translation of raw multiplexed images to actionable clinical insights, empowering researchers to explore and interact effectively with spatial omics data.
Decoding transcriptional identity during Neuron-Astroglia Cell Fate driven by RAR-specific agonists
Authors: Galindo-Albarrán Ariel , Koshy Aysis , Mendoza-Ferri Maria Grazia , Mendoza-Parra Marco Antonio
Published: December 2024

How cells respond to different signals leading to defined lineages is an open question to understand physiological differentiation leading to the formation of organs and tissues. Among the various morphogens, retinoic acid signaling, via the RXR/RAR nuclear receptors activation, is a key morphogen of nervous system development and brain homeostasis. Here we analyze gene expression in ∼80,000 cells covering 16 days of monolayer mouse stem cell differentiation driven by the pan-RAR agonist all-trans retinoic acid, the RARα agonist BMS753 or the activation of both RARβ and RARγ receptors (BMS641+BMS961). Furthermore, we have elucidated the role of these retinoids for driving nervous tissue formation within 90 days of brain organoid cultures, by analyzing > 8,000 distinct spatial regions over 28 brain organoids.

Despite a delayed progression in BMS641+BMS961, RAR-specific agonists led to a variety of neuronal subtypes, astrocytes and oligodendrocyte precursors. Spatially-resolved transcriptomics performed in organoids revealed spatially distinct RAR isotype expression leading to specialization signatures associated to matured tissues, including a variety of neuronal subtypes, retina-like tissue structure signatures and even the presence of microglia.
TRF1 and TRF2 form distinct shelterin subcomplexes at telomeres
Authors: Janovič Tomáš , Perez Gloria I. , Schmidt Jens C.
Published: December 2024

The shelterin complex protects chromosome ends from the DNA damage repair machinery and regulates telomerase access to telomeres. Shelterin is composed of six proteins (TRF1, TRF2, TIN2, TPP1, POT1 and RAP1) that can assemble into various subcomplexesin vitro. However, the stoichiometry of the shelterin complex and its dynamic association with telomeres in cells is poorly defined. To quantitatively analyze the shelterin function in living cells we generated a panel of cancer cell lines expressing HaloTagged shelterin proteins from their endogenous loci. We systematically determined the total cellular abundance and telomeric copy number of each shelterin subunit, demonstrating that the shelterin proteins are present at telomeres in equal numbers. In addition, we used single-molecule live-cell imaging to analyze the dynamics of shelterin protein association with telomeres. Our results demonstrate that TRF1-TIN2-TPP1-POT1 and TRF2-RAP1 form distinct subcomplexes that occupy non-overlapping binding sites on telomeric chromatin. TRF1-TIN2-TPP1-POT1 tightly associates with chromatin, while TRF2-RAP1 binding to telomeres is more dynamic, allowing it to recruit a variety of co-factors to chromatin to protect chromosome ends from DNA repair factors. In total, our work provides critical mechanistic insight into how the shelterin proteins carry out multiple essential functions in telomere maintenance and significantly advances our understanding of macromolecular structure of telomeric chromatin.
Accurate sequence-to-affinity models for SH2 domains from multi-round peptide binding assays coupled with free-energy regression
Authors: Gagoski Dejan , Rube H. Tomas , Rastogi Chaitanya , Melo Lucas A. N. , Li Xiaoting , Voleti Rashmi , Shah Neel H. , Bussemaker Harmen J.
Published: December 2024

Short linear peptide motifs play important roles in cell signaling. They can act as modification sites for enzymes and as recognition sites for peptide binding domains. SH2 domains bind specifically to tyrosine-phosphorylated proteins, with the affinity of the interaction depending strongly on the flanking sequence. Quantifying this sequence specificity is critical for deciphering phosphotyrosine-dependent signaling networks. In recent years, protein display technologies and deep sequencing have allowed researchers to profile SH2 domain binding across thousands of candidate ligands. Here, we present a concerted experimental and computational strategy that improves the predictive power of SH2 specificity profiling. Through multi-round affinity selection and deep sequencing with large randomized phosphopeptide libraries, we produce suitable data to train an additive binding free energy model that covers the full theoretical ligand sequence space. Our models can be used to predict signaling network connectivity and the impact of missense variants in phosphoproteins on SH2 binding.
Biochemical dissection of a fungal highly reducing polyketide synthase condensing region reveals basis for acyl group selection
Authors: Foran Mia E. , Auckloo Nazia B. , Ho Y. T. Candace , Liu Shaonan , Hai Yang , Jenner Matthew
Published: December 2024

Fungal highly reducing polyketide synthases (hrPKSs) are remarkable multidomain enzymes that catalyse the biosynthesis of a diverse range of structurally complex compounds. During biosynthesis, the ketosynthase (KS) and acyltransferase (AT) domains of the condensing region are visited by the acyl carrier protein (ACP) domain during every cycle, catalysing chain priming and elongation reactions. Despite their significance, our comprehension of how these steps contribute to biosynthetic fidelity remains poorly understood. Herein, we report the fullin vitroreconstitution of each catalytic step carried out by a hrPKS condensing region. Application of intact protein mass spectrometry shows that the AT domain operates selective acyl transfer to the ACP domain, ensuring loading of the correct starter / extender units, which is governed by a substrate recycling mechanism and kinetic parameters towards each substrate. The KS domain is shown to select for the correct starter unit for transacylation and subsequent chain elongation, yet harbours flexibility towards the extender unit supplied. This work provides the first comprehensive interrogation of a fungal hrPKS condensing region, which both affirms and expands our understanding of how these systems function, and provides a framework for future bioengineering efforts.
Cerebral perfusion and metabolic response of astrocytes and neurons during locomotion
Authors: Tiaglik Alisa , Morozova Kseniia , Fedotova Anna , Brazhe Alexey , Li Li , Liu Dan , Zhu Ling-Qiang , Bilan Dmitry , Oleinikov Vladimir , Brazhe Nadezda , Semyanov Alexey
Published: December 2024

The hemodynamic response links neural oxidative metabolism changes to increased cerebral blood flow during brain activity1. Although Roy and Sherrington introduced this concept over a century ago (1890), the exact cellular mechanisms remain unclear. This study demonstrates how local blood supply increases correlate with the metabolic response of individual brain cells during locomotion. Using Raman microspectroscopy, we observed an elevation in oxygen saturation levels (sO2) in cortical venules but not in arterioles, which were already near saturation. The increased sO2in the venules was accompanied by vasodilation, indicating blood oversupply in the local brain area, a phenomenon known as functional hyperemia. We then analyzed the metabolic response of individual neurons and astrocytes to locomotion. In neurons, the levels of reduced cytochromes ofcandbtypes [cytc,b(Fe2+)] rapidly decreased at the onset of locomotion. This suggests an increase in the activity of the mitochondrial respiratory chain (electron transport chain, ETC) in response to heightened energy demands in these cells2. In contrast, because astrocytes rely less on oxidative phosphorylation for their energy metabolism than neurons3, we did not observe an initial decrease in reduced cytochromes in these cells. However, as locomotion continued, the cytc,b(Fe2+) levels steadily increased in both cell types. In neurons, this led to a slow recovery from the initial drop, while in astrocytes, the increase exceeded baseline levels. Consequently, we observed an overload of electrons in the astrocytic ETC. The distinct responses of astrocytic and neuronal mitochondria to locomotion may reflect differences in the organization of the ETC in the two cell types4. Furthermore, astrocytes may shift to glycolysis under increased neuronal activity5,6. This difference also resulted in hydrogen peroxide (H202) production in astrocytic mitochondria but not neuronal mitochondria. Since H202is a signaling molecule critical for cognitive function in the brain7, we speculate that astrocytic mitochondria act as signaling hubs during exercise.