bluuebunny/crossref_metadata_2025 huggingface dataset:
Interpretable and explainable predictive machine learning models for data-driven protein engineering
Authors: Medina-Ortiz David , Khalifeh Ashkan , Anvari-Kazemabad Hoda , Davari Mehdi D.
Published: February 2024

Protein engineering using directed evolution and (semi)rational design has emerged as a powerful strategy for optimizing and enhancing enzymes or proteins with desired properties. Integrating artificial intelligence methods has further enhanced and accelerated protein engineering through predictive models developed in data-driven strategies. However, the lack of explainability and interpretability in these models poses challenges. Explainable Artificial Intelligence addresses the interpretability and explainability of machine learning models, providing transparency and insights into predictive processes. Nonetheless, there is a growing need to incorporate explainable techniques in predicting protein properties in machine learning-assisted protein engineering. This work explores incorporating explainable artificial intelligence in predicting protein properties, emphasizing its role in trustworthiness and interpretability. It assesses different machine learning approaches, introduces diverse explainable methodologies, and proposes strategies for seamless integration, improving trust-worthiness. Practical cases demonstrate the explainable model’s effectiveness in identifying DNA binding proteins and optimizing Green Fluorescent Protein brightness. The study highlights the utility of explainable artificial intelligence in advancing computationally assisted protein design, fostering confidence in model reliability.
Alcohol drinking is associated with greater calcium activity in mouse central amygdala dynorphin-expressing neurons
Authors: Lebonville Christina L. , Rinker Jennifer A. , O’Hara Krysten , McMahan Christopher S. , Hoffman Michaela , Becker Howard C. , Mulholland Patrick J.
Published: February 2024

Alcohol use disorder (AUD) is a chronic disease that poses significant economic burden and health risks. It is pivotal to better understand brain mechanisms engaged by alcohol that promote misuse. The central amygdala (CeA) has emerged as a key mediator of excessive preclinical alcohol consumption. A dynorphin-expressing subpopulation within the CeA (CeADyn) has been implicated in excessive alcohol drinking, yet how cellular activity of CeADynneurons relates to ongoing alcohol drinking is not well-understood. The current study interrogated the engagement of CeADynneurons in male and female mice during voluntary alcohol consumption using fiber photometry and compared this cellular response with that of other solutions having similar motivational and/or taste characteristics. Activity of a calcium sensor, GCaMP7f, expressed in mouse CeADynneurons was recorded and time-locked to bouts of drinking. Multilevel linear mixed modeling was applied to better resolve focal effects from complex data. These analyses revealed a relatively large increase in CeADynneuron calcium transients after bouts of alcohol drinking compared to water or sucrose drinking, indicating these neurons are uniquely engaged during alcohol consumption. Drinking behavior unique to alcohol (i.e., longer bout durations) did not fully explain signal differences between alcohol and other solutions nor did the relatively increased alcohol response diminish over time. No other conditions or solutions tested reproduced the pronounced change in CeADynactivity associated with alcohol drinking. These findings, collectively, support the presence of a unique functional signature for alcohol in a cell population known to control excessive alcohol drinking.

Highlights

Central amygdala dynorphin cells (CeADyn) are firmly implicated in alcohol misuse.

CeADynneuron activity was higher when mice drank alcohol versus other solutions.

Neither how mice drank alcohol nor motivational states could explain this activity.

CeADynneurons having uniquely high alcohol responses may underlie AUD development.
New, biomechanically sound tendon tissue after injection of uncultured, autologous, adipose derived regenerative cells in partial Achilles tendon defects in rabbits
Authors: Schmitz Christoph , Alt Christopher , Würfel Tobias , Milz Stefan , Dinzey Jacqueline , Hill Ashley , Sikes Katie J. , Burton Lindsey , Easley Jeremiah , Stewart Holly L. , Puttlitz Christian M. , Gadomski Benjamin C. , Labus Kevin , Pearce David A. , Maffulli Nicola , Alt Eckhard U.
Published: February 2024

Background

Current management options for partial tendon tears may not offer future potential to heal tissue and improve clinical results. This study tested the hypothesis that treatment of a partial rabbit common calcaneus tendon (CCT) defect with uncultured, autologous, adipose derived regenerative cells (UA-ADRCs) enables regenerative healing without scar formation, as recently observed in a biopsy of a human supraspinatus tendon.

Methods

A full-thickness hole (diameter, 3 mm) was punched into the midsubstance of the right gastrocnemius tendon (GT; which is a part of the CCT) of adult, female New Zealand white rabbits. Immediately thereafter the rabbits were treated by application of an averaged 28.3×106UA-ADRCs in 0.5 ml lactated Ringer’s solution (RLS) into the GT defect and surrounding tendon tissue, or underwent sham treatment. Rabbits were sacrificed either four weeks (W4) or twelve weeks (W12) post-treatment, and the CCTs were investigated using histology, immunohistochemistry and non-destructive biomechanical testing.

Results

Newly formed connective tissue was consistent with the formation of new tendon tissue after treatment with UA-ADRCs, and with the formation of scar tissue after sham treatment, at both W4 and W12 post-treatment. Biomechanical testing demonstrated a significantly higher mean percent relaxation after treatment with UA-ADRCs than after sham treatment (p < 0.05), and significant, negative correlations between the peak stress as well as the equilibrium stress and the cross-sectional area of the CCT (p < 0.05) after treatment with UA-ADRCs but not after sham treatment.

Conclusions

Management of partial tendon tears with UA-ADRCs has the potential to be truly “structure-modifying”.
From local seafloor imagery to global patterns in benthic habitat states: contribution of citizen science to habitat classification across latitudes
Authors: Violet Clément , Boyé Aurélien , Dubois Stanislas , Edgar Graham J. , Oh Elizabeth S. , Stuart-Smith Rick D. , Marzloff Martin P.
Published: February 2024

Aim

The aim of this study was to define reef benthic habitat states and explore their spatial and temporal variability at a global scale using an innovative clustering pipeline.

Location

The study uses data on the transects surveyed on shallow (< 20m) reef ecosystems across the globe. Time period: Transects sampled between 2008 and 2021. Major taxa studied: Macroalgae, sessile invertebrates, hydrozoans, seagrass, corals.

Methods

Percentage cover was estimated for 24 functional groups of sessile biota and substratum from annotated underwater photoquadrats taken along 6,554 transects by scuba divers contributing to the Reef Life Survey dataset. A clustering pipeline combining a non-linear dimension-reduction technique (UMAP), with a density-based clustering approach (HDBSCAN), was used to identify benthic habitat states. Spatial and temporal variation in habitat distribution was then explored across ecoregions.

Results

TheUMAP-HDBSCANpipeline identified 17 distinct clusters representing different benthic habitats and gradients of ecological state. Certain habitat states displayed clear biogeographic patterns, predominantly occurring in temperate regions or tropical waters. Notably, some reefs dominated by turf algae were ubiquitous across latitudinal zones. Transition zones between temperate and tropical waters emerged as spatial hotspots of habitat state diversity. Temporal analyses revealed changes in the proportion of certain states over time, notably an increase in turf algae occurrence.

Main Conclusions

TheUMAP-HDBSCANclustering pipeline effectively characterised fine-scale benthic habitat states at a global scale, confirming known broader biogeographic patterns, including the importance of temperate-tropical transition zones as hotspots of habitat state diversity. This fine-scale, yet broadly-scalable habitat classification could be applied as a standardised template for tracking benthic habitat change across space and time at a global scale. TheUMAP-HDBSCANpipeline has proven to be a powerful and versatile approach for analysing complex biological datasets and can be applied in various ecological domains.
Multi-trait multi-environment genomic prediction of preliminary yield trials in pulse crops
Authors: Saludares Rica Amor , Atanda Sikiru Adeniyi , Piche Lisa , Worral Hannah , Dariva Francoise , McPhee Kevin , Bandillo Nonoy
Published: February 2024

Phenotypic selection in preliminary yield trials (PYT) is challenged by limited seeds, resulting in trials with few replications and environments. The emergence of multi-trait multi-environment enabled genomic prediction (MTME-GP) offers opportunity for enhancing prediction accuracy and genetic gain across multiple traits and diverse environments. Using a set of 300 advanced breeding lines in the North Dakota State University (NDSU) pulse crop breeding program, we assessed the efficiency of a MTME-GP model for improving seed yield and protein content in field peas in stress and non-stress environments. MTME-GP significantly improved predictive ability, improving up to 2.5-fold, particularly when a significant number of genotypes overlapped across environments. Heritability of the training environments contributed significantly to the overall prediction of the model. Average predictive ability ranged from 3 to 7-folds when environments with low heritability were excluded from the training set. Overall, the Reproducing Kernel Hilbert Spaces (RKHS) model consistently resulted in improved predictive ability across all breeding scenarios considered in our study. Our results lay the groundwork for further exploration, including integration of diverse traits, incorporation of deep learning techniques, and the utilization of multi-omics data in predictive modeling.

Core ideas

Phenotypic selection in PYT is challenged by limited seeds, resulting to few replications and environments.

MTME-GP offers opportunity for enhancing prediction accuracy of multi-trait and diverse environments in PYT.

MTME-GP enhances prediction by up to 2.5-fold, especially with numerous overlapping genotypes in various tested environments.

RKHS MTME-GP models, excels in low-heritability, negatively correlated traits, like drought-affected conditions.
Adaptive Mating Among Natural Strains ofS. cerevisiae
Authors: Strauss Sivan Kaminski , Liti Gianni , Dahan Orna , Pilpel Yitzhak
Published: February 2024

In evolutionary biology, sexual mating plays a pivotal role in facilitating the combination of beneficial alleles among individuals. Cross-species data suggest that organisms selectively mate with partners based on factors such as genetic distance and partner fitness. Understanding the determinants of pair-specific mating affinity is crucial for unraveling the impact of sex on evolution. However, despite the significance of this phenomenon, the availability of large and consistent datasets is limited, leading to inconsistent conclusions.

To address this gap, we present a comprehensive mating assay enabling the simultaneous quantification of mating affinity among approximately 100 naturalSaccharomyces cerevisiaestrains. Our study demonstrates that mating in anen massemanner, allowing mating based on affinity, enhances the overall fitness of the hybrids offspring population compared to mating that enforces one specific partner at a time. By employing a DNA barcode recombination system integrated into natural isolates’ genomes, we sequence recombined barcode pairs and revealed mating frequencies and affinities among all strains in different environments.

Our findings unveil strain-specific mating affinity among natural yeast strains, with certain parental pairs exhibiting a heightened affinity for each other over other strains, whereas certain strains combinations are avoided. Notably, among the pairs with the highest affinity, there is a preference for lower genetic distances. Intriguingly, multiple strains show a propensity for mating with partners that yield higher-fitness hybrids on average. Collectively, our results provide compelling evidence that yeast actively engages in adaptive mate affinity.
Nodulation Trio inMedicago truncatula:Unveiling the Overlapping Roles of MtLYK2, MtLYK3, and MtLYK2bis
Authors: Li Yaohua , Zhao Yanwen , Yan Ziang , Dong Ru , Yu Haixiang , Zhu Hui , Cao Yangrong
Published: February 2024

The perception of rhizobial nodulation factors (NF) by plant NF receptors is crucial for mediating legume nodulation. In Medicago truncatula nodulation, a proposed two-receptor model designates MtLYK3 as an entry receptor, while other LYK proteins, with unidentified functions, may serve as signaling receptors. Here, we generated the single, double, and triple mutants for M. truncatula MtLYK2, MtLYK3, and MtLYK2bis using CRISPR/Cas technology and examined their roles in nodulation. Our findings suggest that all three LYKs possess redundant functions in Medicago nodulation, with their distinct contributions attributed to varying transcription patterns.Our findings also suggest that a one-receptor model with multiple specificities that mediates both signaling and entry responses is more suitable in M. truncatula.
Modeling Neuromotor Adaptation to Pulsed Torque Assistance During Walking
Authors: Kim GilHwan , Sergi Fabrizio
Published: February 2024

Multiple mechanisms of motor learning contribute to the response of individuals to robot-aided gait training, including error-based learning and use-dependent learning. Previous models described either of these mechanisms, but not both, and their relevance to gait training is unknown. In this paper, we establish the validity of existing models to describe the response of healthy individuals to robot-aided training of propulsion via a robotic exoskeleton, and propose a new model that accounts for both use-dependent and error-based learning.

We formulated five state-space models to describe the stride-by-stride evolution of metrics of propulsion mechanics during and after robot-assisted training, applied by a hip/knee robotic exoskeleton for 200 consecutive strides. The five models included a single-state, a two-state, a two-state fast and slow, a use-dependent learning (UDL), and a newly-developed modified UDL model, requiring 4, 9, 5, 3, and 4 parameters, respectively. The coefficient of determination (R2) and Akaike information criterion (AIC) values were calculated to quantify the goodness of fit of each model. Model fit was conducted both at the group and at the individual participant level.

At the group level, the modified UDL model shows the best goodness-of-fit compared to other models in AIC values in 15/16 conditions. At the participant level, both the modified UDL model and the two-state model have significantly better goodness-of-fit compared to the other models. In summary, the modified UDL model is a simple 4-parameter model that achieves similar goodness-of-fit compared to a two-state model requiring 9 parameters. As such, the modified UDL model is a promising model to describe the effects of robot-aided gait training on propulsion mechanics.
Mating-compatibility genes employed as diagnostic markers to identify novel incursions of the myrtle rust pathogenAustropuccinia psidii
Authors: Feng Jinghang , Bird Austin , Luo Zhenyan , Tam Rita , Shepherd Luc , Murphy Lydia , Singh Lavi , Graetz Abigail , Moeller Mareike , Amorim Lilian , Massola Nelson Sidnei , Prodhan M. Asaduzzaman , Shuey Louise , Beattie Douglas , Gonzalez Alejandro Trujillo , Tobias Peri A. , Padovan Amanda , Kimber Rohan , McTaggart Alistair , Kehoe Monica , Schwessinger Benjamin , Boufleur Thaís R.
Published: February 2024

Austropuccinia psidiiis the causal agent of myrtle rust in over 480 species within the family Myrtaceae. Lineages ofA. psidiiare structured by host in its native range, and some have success on new-encounter hosts. For example, the pandemic biotype has spread beyond South America, and proliferation of other lineages is an additional risk to biodiversity and industries. Efforts to manageA. psidiiincursions, including lineage differentiation, relies on variable microsatellite markers. Testing these markers is time-consuming and complex, particularly on a large scale. We designed a novel diagnostic approach targeting the fungal mating-typeHD(homeodomain) transcription factor locus to address these limitations. TheHDlocus (bW1/2-HD1 andbE1/2-HD2)is highly polymorphic, facilitating clear biological predictions about its inheritance from founding populations. To be considered the same lineage, all fourHDalleles must be identical. Our lineage diagnostics relies on PCR amplification of theHDlocus in different genotypes ofA. psidiifollowed by amplicon sequencing using Oxford Nanopore Technologies (ONT) and comparative analysis. The lineage-specific assay was validated on four isolates with existing genomes, uncharacterized isolates, and directly from infected leaf material. We reconstructedHDalleles from amplicons and confirmed their sequence identity relative to their reference. Genealogies usingHDalleles confirmed the variations at theHDloci among lineages/isolates. Our study establishes a robust diagnostic tool, for differentiating known lineages ofA. psidiibased biological predictions. This tool holds promise for detecting new pathogen incursions and can be refined for broader applications, including air-sample detection and mixed-isolate infections.
Phase delays between mouse globus pallidus neurons entrained by common oscillatory drive arise from their intrinsic properties, not their coupling
Authors: Olivares Erick , Wilson Charles J. , Goldberg Joshua A.
Published: February 2024

A hallmark of Parkinson’s disease is the appearance of correlated oscillatory discharge throughout the cortico-basal ganglia (BG) circuits. In the primate globus pallidus (GP), where the discharge of GP neurons is normally uncorrelated, pairs of GP neurons exhibit oscillatory spike correlations with a broad distribution of pairwise phase delays in experimental parkinsonism. The transition to oscillatory correlations is thought to indicate the collapse of the normally segregated information channels traversing the BG. The large phase delays are thought to reflect pathological changes in synaptic connectivity in the BG. Here we study the structure and phase delays of spike correlations measured from neurons in the mouse external GP (GPe) subjected to identical 1-100 Hz sinusoidal drive but recorded in separate experiments. First, we find that spectral modes of a GPe neuron’s empirical instantaneous phase response curve (iPRC), elucidate at what phases of the oscillatory drive the GPe neuron locks when it is entrained, and the distribution of phases at which it spikes when it is not. Then, we show that in this case the pairwise spike cross-correlation equals the cross-correlation function of these spike phase distributions. Finally, we show that the distribution of GPe phase delays arises from the diversity of iPRCs, and is broadened when the neurons become entrained. Modeling GPe networks with realistic intranuclear connectivity demonstrates that the connectivity decorrelates GPe neurons without affecting phase delays. Thus, common oscillatory input gives rise to GPe correlations whose structure and pairwise phase delays reflect their intrinsic properties captured by their iPRCs.

Significance Statement

The external globus pallidus (GPe) is a hub in the basal ganglia, whose neurons impose a barrage of inhibitory synaptic currents on neurons of the subthalamic nucleus, substantia nigra and internal globus pallidus. GPe neurons normally fire independently, but in experimental parkinsonism, they become correlated in the frequency range associated with the pathological rhythms seen in human Parkinson’s disease, raising the possibility that they may be generators of the pathological oscillation. We drove individual pallidal neurons with an oscillatory input over a wide range of frequencies. Cross-correlations of these neurons reproduced many of the features seen in parkinsonism, suggesting that their correlated oscillations might derive from a shared input rather than internal interconnections.
A deep learning-based toolkit for 3D nuclei segmentation and quantitative analysis in cellular and tissue context
Authors: Vijayan Athul , Mody Tejasvinee Atul , Yu Qin , Wolny Adrian , Cerrone Lorenzo , Strauss Soeren , Tsiantis Miltos , Smith Richard S. , Hamprecht Fred A. , Kreshuk Anna , Schneitz Kay
Published: February 2024

We present a new set of computational tools that enable accurate and widely applicable 3D segmentation of nuclei in various 3D digital organs. We developed a novel approach for ground truth generation and iterative training of 3D nuclear segmentation models, which we applied to popular CellPose, PlantSeg, and StarDist algorithms. We provide two high-quality models trained on plant nuclei that enable 3D segmentation of nuclei in datasets obtained from fixed or live samples, acquired from different plant and animal tissues, and stained with various nuclear stains or fluorescent protein-based nuclear reporters. We also share a diverse high-quality training dataset of about 10,000 nuclei. Furthermore, we advanced the MorphoGraphX analysis and visualization software by, among other things, providing a method for linking 3D segmented nuclei to their surrounding cells in 3D digital organs. We found that the nuclear-to-cell volume ratio varies between different ovule tissues and during the development of a tissue. Finally, we extended the PlantSeg 3D segmentation pipeline with a proofreading script that uses 3D segmented nuclei as seeds to correct cell segmentation errors in difficult-to-segment tissues.

Summary Statement

We present computational tools that allow versatile and accurate 3D nuclear segmentation in plant organs, enable the analysis of cell-nucleus geometric relationships, and improve the accuracy of 3D cell segmentation.
Cryogenic non-invasive 3D X-ray phase-contrast imaging of unfixed, intact mouse joints reveals shifting chondrocyte hypertrophy across the endochondral interface
Authors: Evans L. A. E. , Vezeleva D. , Bodey A.J. , Lee P. D. , Poologasundarampillai G. , Pitsillides A. A.
Published: February 2024

Objectives

i) develop and use a new cryogenically-enhanced phase contrast method to visualise hyaline articular cartilage (HAC); ii) to measure HAC, articular calcified cartilage (ACC) and total articular cartilage thicknesses in male STR/Ort (osteoarthritis, OA) and CBA (healthy) mouse tibial epiphyses, reflecting divergent OA predisposition, at three age timepoints chosen to reflect pre-OA, OA onset and late-progression; iii) to compare HAC, trans-zonal and ACC 3D chondrocyte anatomy in tibial epiphyses.

Methods

STR/Ort and CBA mouse knees (n=4 per age and strain group) were synchrotron-CT scanned at high-resolution while fresh frozen, without staining, fixation, dissection or dehydration of the joint capsule. Both cartilage thickness and cellular characteristics (chondrocyte n=420) were manually measured and statistically compared (SPSS).

Results

Cryo-enhanced phase contrast allowed cartilage to be seen in full thickness with cellular detail. HAC was thicker in STR/Ort than age-matched CBA mice in 16/24 knee joint compartments and timepoints (all p<0.04). In contrast, HAC was thicker only in the posterior lateral femur of CBA mice at 10weeks (p<0.001, Table 1). ACC and total cartilage were also thicker in STR/Orts. Trans-zonal chondrocytes were smaller than ACC and HAC chondrocytes (p-values<0.001, volumes 878, 1,567μm3and 1,348μm3respectively).

Conclusions

Cryogenically-enhanced phase-contrast imaging allowed cellular detail to be seen in 3D as never before in HAC in this (or any other) model. Our findings challenge current understanding by associating STR/Ort OA vulnerability with regions of thick, rather than thinning-with-age, cartilage. Our data affirm an association between excessively hypertrophic chondrocytes and OA is present in STR/Ort mice.
DNAH3 deficiency causes flagellar inner dynein arm loss and male infertility in humans and mice
Authors: Wang Xiang , Shen Gan , Yang Yihong , Jiang Chuan , Ruan Tiechao , Yang Xue , Zhuo Liangchai , Zhang Yingteng , Ou Yangdi , Zhao Xinya , Long Shunhua , Tang Xiangrong , Lin Tingting , Shen Ying
Published: February 2024

Axonemal protein complexes, including the outer and inner dynein arms (ODA/IDA), are highly ordered structures of the sperm flagella that drive sperm motility. Deficiencies in several axonemal proteins have been associated with male infertility, which is characterized by asthenozoospermia or asthenoteratozoospermia. Dynein axonemal heavy chain 3 (DNAH3) resides in the IDA and is highly expressed in the testis. However, the relationship between DNAH3 and male infertility is still unclear. Herein, we identified biallelic variants ofDNAH3in four unrelated Han Chinese infertile men with asthenoteratozoospermia through whole-exome sequencing (WES). These variants contributed to deficient DNAH3 expression in the patients' sperm flagella. Importantly, the patients represented the anomalous sperm flagellar morphology, and the flagellar ultrastructure was severely disrupted. Intriguingly,Dnah3knockout (KO) male mice were also infertile, especially showing the severe reduction in sperm movement with the abnormal IDA and mitochondrion structure. Mechanically, nonfunctional DNAH3 expression resulted in decreased expression of IDA-associated proteins in the spermatozoa flagella of patients and KO mice, including DNAH1, DNAH6, and DNALI1, the deletion of which has been involved in disruption of sperm motility. Moreover, the infertility of patients withDNAH3variants andDnah3KO mice could be rescued by intracytoplasmic sperm injection (ICSI) treatment. Our findings indicated thatDNAH3is a novel pathogenic gene for asthenoteratozoospermia and may further contribute to the diagnosis, genetic counseling, and prognosis of male infertility.
Predicting cell type-specific extracellular vesicle biology using an organism-wide single cell transcriptomic atlas – insights from theTabula Muris
Authors: LaRocca Thomas J. , Lark Daniel S.
Published: February 2024

Extracellular vesicles (EVs) like exosomes are functional nanoparticles trafficked between cells and found in every biofluid. An incomplete understanding of which cells, from which tissues, are trafficking EVsin vivohas limited our ability to use EVs as biomarkers and therapeutics. However, recent discoveries have linked EV secretion to expression of genes and proteins responsible for EV biogenesis and found as cargo, which suggests that emerging “cell atlas” datasets could be used to begin understanding EV biology at the level of the organism and possibly in rare cell populations. To explore this possibility, here we analyzed 67 genes that are directly implicated in EV biogenesis and secretion, or carried as cargo, in ∼44,000 cells obtained from 117 cell populations of theTabula Muris. We found that the most abundant proteins found as EV cargo (tetraspanins and syndecans) were also the most abundant EV genes expressed across all cell populations, but the expression of these genes varied greatly among cell populations. Expression variance analysis also identified dynamic and constitutively expressed genes with implications for EV secretion. Finally, we used EV gene co-expression analysis to define cell population-specific transcriptional networks. Our analysis is the first, to our knowledge, to predict tissue- and cell type-specific EV biology at the level of the organism and in rare cell populations. As such, we expect this resource to be the first of many valuable tools for predicting the endogenous impact of specific cell populations on EV function in health and disease.
Can we predict the predation pressure of owned domestic cats on all birds in the United States?
Authors: Philippe-Lesaffre Martin
Published: February 2024

Domestic cats (Felis catus) have shared a common history with humans since their domestication 10,000 years ago and today they are one of the world’s most widespread predatory mammals. Different populations of domestic cats around the world show a high degree of variability in terms of their autonomy from humans for feeding or moving about, with common descriptions ranging from owned domestic cats to feral domestic cats on the spectrum from the most dependent to the most autonomous about humans. Distinguishing between owned and other domestic cats, I proposed a framework based on machine learning and citizen science data to predict the annual predation pressure on bird species per domestic cat considering traits, phylogeny and geographical distribution. Leveraging the Random Forest model and data from Mori et al. (2019), I assessed the predation pressure for each native continental bird species of the United States.

Findings revealed that geographical distribution, phylogeny and traits influenced the predictive value of predation pressure, while a specific trait combination was also associated with high predation pressure. Furthermore, 35% of species experienced high predation pressure from owned domestic cats regardless of the existing threats. The results are consistent with former empirical evidence of predation by domestic cats in the United States and highlight the urgency of understanding the ecological impact of domestic cats. By producing a quantitative value for predation pressure, the framework allows the development of more reliable models of species extinction risk, including for the effects of domestic cat predation, and thus the use of more specific management strategies to sensitive populations. Although the study requires further refinement, the framework offers promising insights. With expanded citizen science protocols, it could help improve the extinction risk models and guide precise management strategies, which are crucial for mitigating the impact of domestic cats on native wildlife.
Bayesian Workflow for Generative Modeling in Computational Psychiatry
Authors: Hess Alexander J. , Iglesias Sandra , Köchli Laura , Marino Stephanie , Müller-Schrader Matthias , Rigoux Lionel , Mathys Christoph , Harrison Olivia K. , Heinzle Jakob , Frässle Stefan , Stephan Klaas Enno
Published: February 2024

Computational (generative) modelling of behaviour has considerable potential for clinical applications. In order to unlock the potential of generative models, reliable statistical inference is crucial. For this, Bayesian workflow has been suggested which, however, has rarely been applied in Translational Neuromodeling and Computational Psychiatry (TN/CP) so far. Here, we present a worked example of Bayesian workflow in the context of a typical application scenario for TN/CP.

This application example uses Hierarchical Gaussian Filter (HGF) models, a family of computational models for hierarchical Bayesian belief updating. When equipped with a suitable response model, HGF models can be fit to behavioural data from cognitive tasks; these data frequently consist of binary responses and are typically univariate. This poses challenges for statistical inference due to the limited information contained in such data. We present a novel set of response models that allow for simultaneous inference from multivariate (here: two) behavioural data types. Using both simulations and empirical data from a speed-incentivised associative reward learning (SPIRL) task, we show that harnessing information from two different data streams (binary responses and continuous response times) improves the accuracy of inference (specifically, identifiability of parameters and models). Moreover, we find a linear relationship between log-transformed response times in the SPIRL task and participants’ uncertainty about the outcome.

Our analysis illustrates the benefits of Bayesian workflow for a typical use case in TN/CP. We argue that adopting Bayesian workflow for generative modelling helps increase the transparency and robustness of results, which in turn is of fundamental importance for the long-term success of TN/CP.
Temporal characterization of the viral load of psittacine beak and feather disease virus in rosy-faced lovebirds (Agapornis roseicollis)
Authors: Lam Derek Kong , Kei Poon Emily Shui , Sin Simon Yung Wa
Published: February 2024

Psittacine beak and feather disease virus (PBFDV) is a widespread and highly pathogenic virus in parrots (Psittaciformes), threatening both captive and wild populations over the world. The disease typically presents with feather and beak abnormalities, along with possible immune system suppression. No cure or commercialized vaccine is currently available. Our understanding of the Psittacine beak and feather disease often come from infected individuals with visible symptoms. Limited knowledge exists regarding the pathology and role of asymptomatic individuals in disease transmission. Asymptomatic individuals could shed virus in their crop secretion, feces, or feathers. In this study, we investigated the temporal change in viral load in feather and fecal samples from 17 asymptomatic rosy-faced lovebirds (Agapornis roseicollis). We developed a qPCR assay for PBFDV viral load quantification in the studied lovebirds. Our results showed that most of the individuals had very low viral load, while three individuals with high viral load at the beginning of the experiment were observed to exhibit a decreasing trend in viral load in both fecal and feather samples. Surprisingly, the viral load in an individual can drop from a high level to an undetectable level within three months, which is contrary to the prevailing notion that the disease is highly lethal with few reports of complete recovery. We also showed that viral load in feathers was higher than in feces. Our study provides valuable insights into the infection dynamics of PBFDV in asymptomatic individuals and contribute to the understanding of disease transmission in parrots.
Confounding factors in targeted degradation of short-lived proteins
Authors: Vetma Vesna , Casarez-Perez Laura , Eliaš Ján , Stingu Andrea , Kombara Anju , Gmaschitz Teresa , Braun Nina , Ciftci Tuncay , Dahmann Georg , Diers Emelyne , Gerstberger Thomas , Greb Peter , Kidd Giorgia , Kofink Christiane , Puoti Ilaria , Spiteri Valentina , Trainor Nicole , Westermaier Yvonne , Whitworth Claire , Ciulli Alessio , Farnaby William , McAulay Kirsten , Frost Aileen B. , Chessum Nicola , Koegl Manfred
Published: February 2024

Targeted protein degradation has recently emerged as a novel option in drug discovery. Natural protein half-life is expected to affect the efficacy of degrading agents, but to what extent it influences target protein degradation has not been systematically explored. Using mathematical modelling of protein degradation, we demonstrate that the natural half-life of a target protein has a dramatic effect on the level of protein degradation induced by a degrader agent which can pose significant hurdles to screening efforts. Moreover, we show that upon screening for degraders of short-lived proteins, agents that stall protein synthesis, such as GSPT1 degraders and generally cytotoxic compounds, deceptively appear as protein degrading agents. This is exemplified by the disappearance of short-lived proteins such as MCL1 and MDM2 upon GSPT1 degradation and upon treatment with cytotoxic agents such as doxorubicin. These findings have implications for target selection as well as for the type of control experiments required to conclude that a novel agent works as a bona fide targeted protein degrader.
Emergence of neural persistence: Insights from computational modelling
Authors: Verma Vishal
Published: February 2024

The persistent neural activity at a global scale, either stationary or oscillatory, can be explained by the use of the excitatory-inhibitory neural network models. This state of the network, as can be inferred, is crucial for the information processing and the memorizing ability of the brain. Though the goal for persistence to exist is apparent; from where the network achieves its ability to show a rich variety of the persistent dynamical states is unclear. The following study investigates the possible reasons for the persistence of neuronal networks in two parts; numerically and analytically. Presently, it shows that the action of the inhibitory components, among other favourable factors, plays a key role in starting and stabilizing neural activity. The results strongly support previous research conducted with both simpler and more specialized neural network models, as well as neurophysiological experiments.

PACS numbers (2006 scheme)

05.40.-a, 05.45.-a, 87.00, 89.00
Simulating Colloid Motion in Spinning Suspension: Internal Dynamics in Orbital Shaker
Authors: Zhao Neil , Zheng Diana
Published: February 2024

Colloid suspensions in the form of mammalian or bacterial cell mixtures in orbital shakers are commonly encountered in biomedical research. An understanding of particle motion in these conditions would provide insight into bulk colloid behavior and distribution under short and long timeframes. Such data can be used to supplement and clarify existing concepts of biological phenomena encountered in the laboratory setting. It can also aid biomedical researchers in experiment design and data interpretation. We present a MATLAB based simulation of colloid motion under rotary agitation. Our simulation setup is modular and therefore designed to act as a scaffold that can be customized to simulate different mammalian, bacterial, or particle properties in liquid suspension.
Single-nucleus multiomics reveals the gene-regulatory networks underlying sex determination of murine primordial germ cells
Authors: Alexander Adriana K. , Rodriguez Karina F. , Chen Yu-Ying , Amato Ciro M. , Estermann Martin A. , Nicol Barbara , Xu Xin , Yao Humphrey Hung-Chang
Published: February 2024

Accurate specification of female and male germ cells during embryonic development is critical for sexual reproduction. Primordial germ cells (PGCs) are the bipotential precursors of mature gametes that commit to an oogenic or spermatogenic fate in response to sex-determining cues from the fetal gonad. The critical processes required for PGCs to integrate and respond to signals from the somatic environment in gonads are not understood. In this study, we developed the first single-nucleus multiomics map of chromatin accessibility and gene expression during murine PGC development in both XX and XY embryos. Profiling of cell-type specific transcriptomes and regions of open chromatin from the same cell captured the molecular signatures and gene networks underlying PGC sex determination. Joint RNA and ATAC data for single PGCs resolved previously unreported PGC subpopulations and cataloged a multimodal reference atlas of differentiating PGC clusters. We discovered that regulatory element accessibility precedes gene expression during PGC development, suggesting that changes in chromatin accessibility may prime PGC lineage commitment prior to differentiation. Similarly, we found that sexual dimorphism in chromatin accessibility and gene expression increased temporally in PGCs. Combining single-nucleus sequencing data, we computationally mapped the cohort of transcription factors that regulate the expression of sexually dimorphic genes in PGCs. For example, the gene regulatory networks of XX PGCs are enriched for the transcription factors, TFAP2c, TCFL5, GATA2, MGA, NR6A1, TBX4, and ZFX. Sex-specific enrichment of the forkhead-box and POU6 families of transcription factors was also observed in XY PGCs. Finally, we determined the temporal expression patterns of WNT, BMP, and RA signaling during PGC sex determination, and our discovery analyses identified potentially new cell communication pathways between supporting cells and PGCs. Our results illustrate the diversity of factors involved in programming PGCs towards a sex-specific fate.
CAMKV Kinase Signaling Is a Novel Therapeutic Avenue with Prognostic Relevance in Neuroblastoma
Authors: Yu Yang , Zhao Yanling , Shi Zhongcheng , Cheng Feng , Wang Larry L. , Choi Jong Min , Li Kan , Silverman Daniel , Qi Dan , Wang Jun , Agarwal Saurabh , Rood Brian R , Dome Jeffrey S. , Fabbri Muller , Yi Joanna S. , Wu Erxi , Jung Sung Yun , Zhang Chunchao , Yang Jianhua
Published: February 2024

Neuroblastoma (NB) can be a highly aggressive malignancy in children. However, the precise mechanisms driving NB tumorigenesis remain elusive. This study revealed the critical role of CREB phosphorylation in NB cell proliferation. By employing a CRISPR-Cas9 knockout screen targeting calcium/calmodulin-dependent protein kinase (CaMK) family members, we identified the CaM kinase-like vesicle-associated (CAMKV) protein as a kinase that mediates direct phosphorylation of CREB to promote NB cell proliferation.CAMKVwas found to be a transcriptional target of MYCN/MYC in NB cells. CAMKV knockout and knockdown effectively suppressed NB cell proliferation and tumor growth both in vitro and in vivo. Bioinformatic analysis revealed that high CAMKV expression is significantly correlated with poor patient survival. High-risk NB frequently had high CAMKV protein levels by Immunohistochemical staining. Integrated transcriptomic and proteomic analyses of CAMKV knockdown cells unveiled downstream targets involved in CAMKV-regulated phosphorylation and signaling pathways, many of which are linked to neural development and cancer progression. We identified small molecule inhibitors targeting CAMKV and further demonstrated the efficacy of one inhibitor in suppressing NB tumor growth and prolonging the survival of mice bearing xenografted tumors. These findings reveal a critical role for CAMKV kinase signaling in NB growth and identified CAMKV kinase as a potential therapeutic target and prognostic marker for patients with NB.
Effective Population Size in Field Pea
Authors: Johnson Josephine Princy , Piche Lisa , Worral Hannah , Atanda Sikiru Adeniyi , Coyne Clarice J. , McGee Rebecca , McPhee Kevin , Bandillo Nonoy
Published: February 2024

Background

Effective population size (Ne) is a pivotal parameter in population genetics as it can provide information on the rate of inbreeding and the contemporary status of genetic diversity in breeding populations. The population with smallerNecan lead to faster inbreeding, with little potential for genetic gain making selections ineffective. The importance ofNehas become increasingly recognized in plant breeding, which can help breeders monitor and enhance the genetic variability or redesign their selection protocols. Here, we present the firstNeestimates based on linkage disequilibrium (LD) in the pea genome.

Results

We calculated and comparedNeusing SNP markers from North Dakota State University (NDSU) modern breeding lines and United States Department of Agriculture (USDA) diversity panel. The extent of LD was highly variable not only between populations but also among different regions and chromosomes of the genome. Overall, NDSU had a higher and longer-range LD than the USDA that could extend up to 500Kb, with a genome-wide averager2of 0.57 (vs 0.34), likely due to its lower recombination rates and the selection background. The estimatedNefor the USDA was nearly three-fold higher (Ne=174) than NDSU (Ne=64), which can be confounded by a high degree of population structure due to the selfing nature of pea.

Conclusions

Our results provided insights into the genetic diversity of the germplasm studied, which can guide plant breeders to actively monitorNein successive cycles of breeding to sustain viability of the breeding efforts in the long term.
Polygenic Risk for Alcohol Use Disorder Affects Cellular Responses to Ethanol Exposure in a Human Microglial Cell Model
Authors: Li Xindi , Liu Jiayi , Boreland Andrew J. , Kapadia Sneha , Zhang Siwei , Stillitano Alessandro C. , Abbo Yara , Clark Lorraine , Lai Dongbing , Liu Yunlong , Barr Peter B , Meyers Jacquelyn L. , Kamarajan Chella , Kuang Weipeng , Agrawal Arpana , Slesinger Paul A. , Dick Danielle , Salvatore Jessica , Tischfield Jay , Duan Jubao , Edenberg Howard J. , Kreimer Anat , Hart Ronald P. , Pang Zhiping P.
Published: February 2024

Polygenic risk scores (PRS) assess genetic susceptibility to Alcohol Use Disorder (AUD), yet their molecular implications remain underexplored. Neuroimmune interactions, particularly in microglia, are recognized as significant contributors to AUD pathophysiology. We investigated the interplay between AUD PRS and ethanol in human microglia derived from iPSCs from individuals with high- or low-PRS (HPRS or LPRS) of AUD. Ethanol exposure induced elevated CD68 expression and morphological changes in microglia, with differential responses between HPRS and LPRS microglial cells. Transcriptomic analysis revealed expression differences in MHCII complex and phagocytosis-related genes following ethanol exposure; HPRS microglial cells displayed enhanced phagocytosis and increasedCLEC7Aexpression, unlike LPRS microglial cells. Synapse numbers in co-cultures of induced neurons with microglia after alcohol exposure were lower in HRPS co-cultures, suggesting possible excess synapse pruning. This study provides insights into the intricate relationship between AUD PRS, ethanol, and microglial function, potentially influencing neuronal functions in developing AUD.
Overcoming brain-derived therapeutic resistance in HER2+ breast cancer brain metastasis
Authors: Ippolitov Danyyl , Lin Yi-Han , Spence Jeremy , Glogowska Aleksandra , Thanasupawat Thatchawan , Beiko Jason , Del Bigio Marc R. , Xu Xin , Wang Amy , Calvo Raul , Kapoor Abhijeet , Marugan Juan J , Henderson Mark J , Klonisch Thomas , Hombach-Klonisch Sabine
Published: February 2024

Brain metastasis of HER2+ breast cancer occurs in about 50% of all women with metastatic HER2+ breast cancer and confers poor prognosis for patients. Despite effective HER2-targeted treatments of peripheral HER2+ breast cancer with Trastuzumab +/-HER2 inhibitors, limited brain permeability renders these treatments inefficient for HER2+ breast cancer brain metastasis (BCBM). The scarcity of suitable patient-derived in-vivo models for HER2+ BCBM has compromised the study of molecular mechanisms that promote growth and therapeutic resistance in brain metastasis. We have generated and characterized new HER2+ BCBM cells (BCBM94) isolated from a patient HER2+ brain metastasis. Repeated hematogenic xenografting of BCBM94 consistently generated BCBM in mice. The clinically used receptor tyrosine kinase inhibitor (RTKi) Lapatinib blocked phosphorylation of all ErbB1-4 receptors and induced the intrinsic apoptosis pathway in BCBM94. Neuregulin-1 (NRG1), a ligand for ErbB3 and ErbB4 that is abundantly expressed in the brain, was able to rescue Lapatinib-induced apoptosis and clonogenic ability in BCBM94 and in HER2+ BT474. ErbB3 was essential to mediate the NRG1-induced survival pathway that involved PI3K-AKT signalling and the phosphorylation of BAD at serine 136 to prevent apoptosis. High throughput RTKi screening identified the brain penetrable Poziotinib as highly potent compound to reduce cell viability in HER2+ BCBM in the presence of NRG1. Successful in-vivo ablation of BCBM94- and BT474-derived HER2+ brain tumors was achieved upon two weeks of treatment with Poziotinib. MRI revealed BCBM remission upon poziotinib, but not with Lapatinib treatment. In conclusion, we have established a new patient-derived HER2+ BCBM in-vivo model and identified Poziotinib as highly efficacious RTKi with excellent brain penetrability that abrogated HER2+ BCBM brain tumors in our mouse models.