bluuebunny/crossref_metadata_2025 huggingface dataset:
Sexual dimorphism of insular cortex function in persistent alcohol drinking despite aversion in mice
Authors: Fornari Claudia , Guerrero-Márquez Carmen , Namburi Praneeth , Couderc Yoni , Nicolas Céline , Beyeler Anna
Published: October 2023

BACKGROUND

One major hallmark of alcohol use disorder (AUD) is the persistence of alcohol drinking despite negative consequences. Among the indicators of AUD vulnerability, binge drinking is a strong risk factor. Although the lifetime prevalence of binge and AUD has been historically higher in men than women, this gap dramatically narrowed in the last decade. Additionally, sex differences in AUD and binge drinking have been shown in clinical and preclinical studies, respectively. The insular cortex plays an important role in AUD, and the anterior (aIC) and posterior (pIC) divisions have dimorphic functions. However, the contributions of the aIC and pIC sections in alcohol binge drinking and alcohol persistent drinking despite aversion, as well as the sexual dimorphism of these contributions, remained to be uncovered.

METHODS

First, by combining the drinking in the dark model with chemogenetics, we studied the causal role of aIC and pIC excitatory neurons in binge and persistent ethanol drinking in C57BL6/J male (n=49) and female (n=49) mice. Second, using calcium fiber photometry, we investigated pIC neuronal activity in both sexes (male n=14, female n=11) during both binge and persistent ethanol drinking.

RESULTS

We identified a higher binge and persistent ethanol consumption in females compared to males. Chemogenetic inhibition of aIC glutamatergic neurons reduced bitter solutions intake independently of the solvent (ethanol or water), in both sexes. In contrast, inhibition of pIC glutamatergic neurons exclusively reduced persistent ethanol drinking in female mice. Finally, using fiber photometry recordings, we uncovered that pIC glutamatergic neuron activity was selectivity increased during ethanol persistent drinking in female mice.

CONCLUSIONS

These findings suggest a sex-dependent function of the pIC in persistent ethanol drinking, providing a starting point in our understanding of the insular cortex function in the neurobiology of AUD in both sexes.
Evolution of hind limb morphology of Titanosauriformes (Dinosauria, Sauropoda) analyzed via 3D Geometric Morphometrics reveals wide-gauge posture as an exaptation for gigantism
Authors: Paramo Blazquez Adrian , Mocho Pedro , Escaso Fernando , Ortega Francisco
Published: October 2023

The sauropod hind limb was the main support that allowed their gigantic body masses and a wide range of dynamic stability adaptations. It was closely related to the position of the centre of masses of their multi-ton barrel-shaped bodies, and experienced one of the most noticeable posture changes during macronarian evolution. Deeply branched macronarians achieved increasingly arched hind limbs in what is known as wide-gauge posture. However, it is not clear if this evolutionary trend is related to the evolutionary cascade toward gigantism even though some titanosaurians were the largest terrestrial vertebrates that ever existed. We tested evolutionary changes in hind limb morphology in the Macronaria phylogenetic tree by 3D geometric morphometrics. The macronarian hind limb does become progressively more arched toward deeply-branched groups, specifically Saltasauridae. However, there is morphological convergence between different macronarian subclades. Wide-gauge posture does not correlate with changes in body size deeper in the macronarian evolutionary tree, and acted as an exaptation to gigantism. Despite some titanosaurian subclades becoming some of the largest vertebrates, there is not a statistically-significant trend toward a particular body size but we identify a phyletic body size decrease in Macronaria.
Novel Cyclic Homogeneous Oscillation Detection Method for High Accuracy and Specific Characterization of Neural Dynamics
Authors: Cho Hohyun , Adamek Markus , Willie Jon T. , Brunner Peter
Published: October 2023

Detecting temporal and spectral features of neural oscillations is essential to understanding dynamic brain function. Traditionally, the presence and frequency of neural oscillations are determined by identifying peaks over 1/f noise within the power spectrum. However, this approach solely operates within the frequency domain and thus cannot adequately distinguish between the fundamental frequency of a non-sinusoidal oscillation and its harmonics. Non-sinusoidal signals generate harmonics, significantly increasing the false-positive detection rate — a confounding factor in the analysis of neural oscillations. To overcome these limitations, we define the fundamental criteria that characterize a neural oscillation and introduce the Cyclic Homogeneous Oscillation (CHO) detection method that implements these criteria based on an auto-correlation approach that determines the oscillation’s periodicity and fundamental frequency. We evaluated CHO by verifying its performance on simulated sinusoidal and non-sinusoidal oscillatory bursts convolved with 1/f noise. Our results demonstrate that CHO outperforms conventional techniques in accurately detecting oscillations. Specifically, we determined the sensitivity and specificity of CHO as a function of signal-to-noise ratio (SNR). We further assessed CHO by testing it on electrocorticographic (ECoG, 8 subjects) and electroencephalographic (EEG, 7 subjects) signals recorded during the pre-stimulus period of an auditory reaction time task and on electrocorticographic signals (6 SEEG subjects and 6 ECoG subjects) collected during resting state. In the reaction time task, the CHO method detected auditory alpha and pre-motor beta oscillations in ECoG signals and occipital alpha and pre-motor beta oscillations in EEG signals. Moreover, CHO determined the fundamental frequency of hippocampal oscillations in the human hippocampus during the resting state (6 SEEG subjects). In summary, CHO demonstrates high precision and specificity in detecting neural oscillations in time and frequency domains. The method’s specificity enables the detailed study of non-sinusoidal characteristics of oscillations, such as the degree of asymmetry and waveform of an oscillation. Furthermore, CHO can be applied to identify how neural oscillations govern interactions throughout the brain and to determine oscillatory biomarkers that index abnormal brain function.
Rapid evolution of pesticide resistance via adaptation and interspecific introgression in a major North American crop pest
Authors: North Henry L. , Fu Zhen , Metz Richard , Stull Matt A. , Johnson Charles D. , Shirley Xanthe , Crumley Kate , Reisig Dominic , Kerns David L. , Gilligan Todd , Walsh Tom , Jiggins Chris D. , Sword Gregory A.
Published: October 2023

Insect crop pests threaten global food security. This threat is amplified through the spread of non-native species and the evolution of pesticide resistance, which can be introduced to a population thoughde novomutation or gene flow. We investigate these processes in an economically important noctuid crop pest,Helicoverpa zea, which has rapidly evolved resistance to several pesticides. Its sister speciesHelicoverpa armigera, first detected as an invasive species in Brazil in 2013, introduced the pyrethroid resistance geneCYP337B3to South AmericanH. zeavia introgression. To understand whether this contributes to pesticide resistance in North America, we sequenced 237H. zeagenomes across 10 sample sites in the US. First, we reportH. armigeraintrogression into the North AmericanH. zeapopulation. Two individuals sampled in Texas in 2019 carryH. armigerahaplotypes in a 4Mbp region containingCYP337B3. Second, we show that the remarkable dispersal ability ofH. zearesults in a panmictic North American population. Third, we detect signatures of selection in non-admixedH. zea, identifying a selective sweep at a second pesticide resistance locus with a similar name:CYP333B3. We estimate that its derived allele conferred a ∼4.9% fitness advantage and show that this estimate explains independently observed rare nonsynonymousCYP333B3mutations approaching fixation over a ∼20-year period. We also detect putative signatures of selection at a kinesin gene associated with Bt resistance. Our results show that pesticide resistance inH. zeaevolved rapidly and recently via two independent mechanisms: interspecific introgression and rapid intraspecific adaptation.
spillR: Spillover Compensation in Mass Cytometry Data
Authors: Guazzini Marco , Reisach Alexander G. , Weichwald Sebastian , Seiler Christof
Published: October 2023

Channel interference in mass cytometry can cause spillover and may result in miscounting of protein markers. Chevrieret al. (2018) introduce an experimental and computational procedure to estimate and compensate for spillover implemented in their R packageCATALYST. They assume spillover can be described by a spillover matrix that encodes the ratio between unstained and stained channels. They estimate the spillover matrix from experiments with beads. We propose to skip the matrix estimation step and work directly with the full bead distributions. We develop a nonparametric finite mixture model, and use the mixture components to estimate the probability of spillover. Spillover correction is often a pre-processing step followed by downstream analyses, choosing a flexible model reduces the chance of introducing biases that can propagate downstream. We implement our method in an R packagespillRusing expectation-maximization to fit the mixture model. We test our method on synthetic and real data fromCATALYST. We find that our method compensates low counts accurately, does not introduce negative counts, avoids overcompensating high counts, and preserves correlations between markers that may be biologically meaningful.
APOE, Immune Factors, Sex, and Diet Interact to Shape Brain Networks in Mouse Models of Aging
Authors: Winter Steven , Mahzarnia Ali , Anderson Robert J , Han Zay Yar , Tremblay Jessica , Stout Jacques , Moon Hae Sol , Marcellino Daniel , Dunson David B. , Badea Alexandra
Published: October 2023

Alzheimer’s disease (AD) presents complex challenges due to its multifactorial nature, poorly understood etiology, and late detection. The mechanisms through which genetic, fixed and modifiable risk factors influence susceptibility to AD are under intense investigation, yet the impact of unique risk factors on brain networks is difficult to disentangle, and their interactions remain unclear. To model multiple risk factors including APOE genotype, age, sex, diet, and immunity we leveraged mice expressing the human APOE and NOS2 genes, conferring a reduced immune response compared to mouse Nos2. Employing graph analyses of brain connectomes derived from accelerated diffusion-weighted MRI, we assessed the global and local impact of risk factors in the absence of AD pathology. Aging and a high-fat diet impacted extensive networks comprising AD-vulnerable regions, including the temporal association cortex, amygdala, and the periaqueductal gray, involved in stress responses. Sex impacted networks including sexually dimorphic regions (thalamus, insula, hypothalamus) and key memory-processing areas (fimbria, septum). APOE genotypes modulated connectivity in memory, sensory, and motor regions, while diet and immunity both impacted the insula and hypothalamus. Notably, these risk factors converged on a circuit comprising 63 of 54,946 total connections (0.11% of the connectome), highlighting shared vulnerability amongst multiple AD risk factors in regions essential for sensory integration, emotional regulation, decision making, motor coordination, memory, homeostasis, and interoception. These network-based biomarkers hold translational value for distinguishing high-risk versus low-risk participants at preclinical AD stages, suggest circuits as potential therapeutic targets, and advance our understanding of network fingerprints associated with AD risk.

Significance Statement

Current interventions for Alzheimer’s disease (AD) do not provide a cure, and are delivered years after neuropathological onset. Addressing the impact of risk factors on brain networks holds promises for early detection, prevention, and revealing putative therapeutic targets at preclinical stages. We utilized six mouse models to investigate the impact of factors, including APOE genotype, age, sex, immunity, and diet, on brain networks. Large structural connectomes were derived from high resolution compressed sensing diffusion MRI. A highly parallelized graph classification identified subnetworks associated with unique risk factors, revealing their network fingerprints, and a common network composed of 63 connections with shared vulnerability to all risk factors. APOE genotype specific immune signatures support the design of interventions tailored to risk profiles.
The effects of resistance training on denervated myofibers, senescent cells, and associated protein markers in middle-aged adults
Authors: Ruple Bradley A. , Mattingly Madison L. , Godwin Joshua S. , McIntosh Mason C. , Kontos Nicholas J. , Agyin-Birikorang Anthony , Michel J. Max , Plotkin Daniel L. , Chen Shao-Yung , Ziegenfuss Tim. N. , Fruge Andrew D. , Gladden L. Bruce , Robinson Austin T. , Mobley C. Brooks , Mackey Abigail L. , Roberts Michael D.
Published: October 2023

Denervated myofibers and senescent cells are hallmarks of skeletal muscle aging. However, sparse research has examined how resistance training affects these outcomes. We investigated the effects of unilateral leg extensor resistance training on denervated myofibers, senescent cells, and associated protein markers in middle-aged participants (MA, 55±8 years old, 17 females, 9 males). We obtained vastus lateralis (VL) muscle cross-sectional area (mCSA), VL biopsies, and strength assessments before and after training. Fiber cross-sectional area (fCSA), satellite cells (Pax7+), denervated myofibers (NCAM+), senescent cells (p16+ or p21+), senescence-related proteins, and senescence-associated secretory phenotype (SASP) proteins were analyzed from biopsied muscle. Leg extensor peak torque increased after training (p<0.001), while VL mCSA trended upward (p=0.082). No significant changes were observed for fCSA, NCAM+ myofibers, or senescent (p16+ or p21+) cells, albeit satellite cells increased after training (p=0.037). While >90% satellite cells were not p16+ or p21+, most p16+ and p21+ cells were Pax7+ (>90% on average). Training altered 13/46 proteins related to muscle-nerve communication (all upregulated, p<0.05) and 10/19 proteins related to cellular senescence (9 upregulated, p<0.05). Only 1/17 SASP proteins increased with training (IGFBP-3, p=0.031). In conclusion, resistance training upregulates proteins associated with muscle-nerve communication in MA participants but does not alter NCAM+ myofibers. Moreover, while training increases senescence-related proteins in skeletal muscle, this coincided with an increase in satellite cells but not alterations in senescent cell content or SASP proteins. Hence, we interpret these collective findings as resistance training being an unlikely inducer of cellular senescence in humans.
DNA and RNA from the same single nucleus reveals interactions between genomic and transcriptomic landscapes in human tumor samples
Authors: Li Siran , Alexander Joan , Kendall Jude , Andrews Peter , Rose Elizabeth , Orjuela Hope , Park Sarah , Podszus Craig , Shanley Liam , Ranade Nissim , Morris Patrick , Stauder Danielle , Bradford Daniel , Ronemus Michael , Rishi Arvind , Ma Rong , Donoho David L. , Goldberg Gary L. , Wigler Michael , Levy Dan
Published: October 2023

To deepen our understanding of cancer heterogeneity and uncover the dynamic interactions of tumor and host cells, we introduce hybrid BAG-seq: a high-throughput, multi-omic method that simultaneously captures DNA and RNA from tens of thousands of individual single nuclei. This method provides dual molecular layer information: DNA to distinguish tumor from stroma, identify tumor subclones, and detect mutant stromal sub-populations; and RNA to characterize distinct cell types, cell states, and signatures of aberrant expression. Additionally, we developed a suite of analysis tools to illuminate cluster phylogeny and connections between DNA identity and RNA expression. We applied this hybrid protocol to 65,499 single nuclei from samples of five uterine cancer patients, and validated the clustering using RNA-only and DNA-only protocols on 34,651 and 21,432 nuclei, respectively, from the same tissues. Multiple tumor genome or expression clusters were often present within a patient, with different tumor clones projecting into distinct or shared expression states, demonstrating nearly all possible genome-transcriptome correlations across the cohort. While tumor expression profiles were highly unique to each patient, the stromal cell types generally recurred across samples, but certain patients and tissues exhibited unique stromal sub-types characterized by aberrant expression. Moreover, we identified mutant stroma in various cell types from several patients with a significant loss of the X-chromosome. This study reveals the complex landscape of genome and transcriptome interactions at the resolution of single nuclei, providing new insights into mutant stroma and tumor heterogeneity.
Robust CNV detection using single-cell ATAC-seq
Authors: Moore Travis W. , Yardımcı Galip Gürkan
Published: October 2023

Copy number variation (CNV) is a widely studied type of structural variation seen in the genomes of cancerous and other dysfunctional cells. CNVs can have direct and indirect effects on gene dosage, and are thought to drive cancer progression and other disorders. Advancements in single-cell assays such as sc-ATAC-seq and sc-RNA-seq, along with their ubiquitous use, allows for the identification of CNVs at single cell resolution. While there are a variety of available tools for CNV detection in sc-RNA-seq, development of sc-ATAC-seq based accurate and reliable CNV callers is in the early stages, with only two available algorithms so far. We present RIDDLER, a single-cell ATAC-seq CNV detection algorithm based on outlier aware generalized linear modeling. By utilizing tools from robust statistics, we developed an extensible model that is able to identify single-cell CNVs from sc-ATAC-seq data in an unsupervised fashion, while providing probabilistic justification for results. Our statistical approach also allows us to estimate when loss of signal is likely caused by drop-out or a true genome deletion event, as well as predict reliable CNVs without the need for normative reference cells. We demonstrate the effectiveness of our algorithm on cancer cell line models where it achieves better agreement with bulk WGS derived CNVs than competing methods. We also compare our approach on 10x multimone data, where it shows better agreement and integration with RNA derived CNV estimates.
Correlation of ECG and Cardiac MRI for Assessment of Ventricular Hypertrophy and Dilatation in Adults with Repaired Tetralogy of Fallot
Authors: Brar Shanjot , Kang Mehima , Sodhi Amit , Deyell Marc W. , Laksman Zachary , Andrade Jason G. , Bennett Matthew T. , Krahn Andrew D. , Yeung-Lai-Wah John , Bennett Richard G. , Barlow Amanda , Grewal Jasmine , Sathananthan Gnalini , Chakrabarti Santabhanu
Published: October 2023

Background

Surgically repaired Tetralogy of Fallot (rTOF) is associated with progressive right ventricular hypertrophy (RVH) and dilation (RVD). Accurate estimation of RVH/ RVD is vital for the ongoing management of this patient population. The utility of the ECG in evaluating patients with rTOF with pre-existing right bundle branch block (RBBB) has not been studied. We aimed to determine the sensitivity/specificity of currently established ECG criteria in detecting RVH/RVD in this patient population.

Methods

We included consecutive patients diagnosed with rTOF who underwent CMR performed at our regional referral centre between January 2012 and December 2019. Each CMR was assessed for LVH, LVD, RVH or RVD diagnosis. The ECG corresponding to the CMR was then used to determine RVH/LVH for specificity and sensitivity analysis.

Results

Our study included 163 consecutive rTOF patients. The specificity for ECG-based criteria for LVH was 100.00% (95% C.I. (87.75, 100.00)), and the sensitivity was 7.19% (95% C.I. (3.15, 12.83)). When RBBB was present, specificity for RVH was 100.00% (95% C.I. (84.56, 100.00)), and sensitivity was 7.69% (95% C.I. (3.75, 13.69)). When RBBB was absent, specificity for RVH was 100.00% (95% C.I. (15.81, 100.00)), and sensitivity was 0.00% (95% C.I. (0.00, 33.63)). A regression model with the entire group of 163 ToF patients, based on the Sokolow-Lyon criterion (sum of R in V1 + S in V5/V6), produced a new suggested criterion for the diagnosis of RVH in patients with rTOF, which was a sum of R in V1 + S in V5/V6 greater than 13.25 mm. This model’s sensitivity for RVH detection was 69.1%, and specificity was 36.8%.

Conclusions

Standard ECG voltage criteria have poor sensitivity for detecting right and left ventricular chamber hypertrophy and dilatation in patients with rTOF, so current ECG criteria should not be used to monitor RVH/RVD in this patient population.
Microenvironment changes in basal ganglia region correlates with hypertension at 7T MRI
Authors: Liang Hongqin , Meng Shan , Li Yue , Yi Xiaoqi , Zhang Haipeng , Wang Jian , Lv Fajin
Published: October 2023

BACKGROUND

Hypertension, a major risk factor for stroke, is associated with the changes of microenvironment in basal ganglia region, including microstructural characteristics and mapping relationship of blood flow and peripheral nerve tissue.

MATERIALS AND METHODS

The morphological characteristics of the lenticulostriate arteries (LSA) and peripheral nerve nuclei were compared by 7T time-of-Flight MRA between 32 hypertensive patients (mean age: 47.1±9.6 years) and 48 age-matched healthy subjects (mean age: 47.7±8.1 years) from September 2022 to February 2023. The ITK-SNAP software was used to measure the morphological characteristics of the LSA and the volume of the nuclei.

RESULTS

The average stems number and length of LSA was significantly higher in healthy people than those in hypertension patients (p<0.05). The volumes of the peripheral nerve nuclei in healthy subjects were significantly larger than those in hypertensive patients (p<0.05). There was a positive correlation between the volume of putamen and the length of LSA in the left hemisphere (r = 0.23, p < 0.05). The number of stems was found to be positively correlated with Globus pallidus volume (r = 0.27, p < 0.05) and internal capsule volume (r = 0.25, p < 0.05) in the right hemisphere. For older adults (>45 year old), the average stems number of LSA and the volume of nuclei were significantly different (P <0.05).

CONCLUSION

The microstructure of the basal ganglia has changed obviously in patients with hypertension compared to healthy individuals when observed by 7T MRA.

NOVELTY AND RELEVANCE

What Is New?

Previously studies on basal ganglia of hypertension using 7T MRI mainly focused on the imaging of LSA, but have not identified significant associations between the LSA and peripheral nerve tissue. However, the occurrence of hypertension adverse events such as intracerebral hemorrhage is closely related to the microenvironment formed by the lenticular artery and peripheral nerve tissue. Once the potential correlation is taken into account, the treatment and follow-up plan related to hypertension may be changed to effectively reduce the adverse.

What Is Relevant?

The rupture of LSA is a recognized cause of stroke in the basal ganglia of hypertensive patients, and the change of the microenvironment of peripheral nerve tissue is closely related to the rupture of LSA. The current findings confirm this notion and identify a potential association between the LSA and peripheral nerve nuclei in hypertensive patients, reinforcing the causal relationship between changes in follow-up strategies for lifelong hypertension and disease risk.

Clinical/Pathophysiological Implications?

Consider early and active assessment of basal ganglia blood flow and peripheral nerve tissue changes in all hypertensive patients to help reduce the risk of adverse events (such as cerebral hemorrhage, cerebral infarction, cognitive impairment, etc.) in individuals.
Multi-donor human cortical Chimeroids reveal individual susceptibility to neurotoxic triggers
Authors: Bolaños Noelia Antón , Faravelli Irene , Faits Tyler , Andreadis Sophia , Trattaro Sebastiano , Kastli Rahel , Adiconis Xian , Di Bella Daniela J. , Tegtmeyer Matthew , Nehme Ralda , Levin Joshua Z. , Regev Aviv , Arlotta Paola
Published: October 2023

Inter-individual genetic variation affects the susceptibility to and progression of many diseases. Efforts to study the molecular mechanisms mediating the impact of human genetic variation on normal development and disease phenotypes are limited, however, by the paucity of faithful cellular human models, and the difficulty of scaling current systems to represent multiple individuals. Here, we present human brain “Chimeroids”, a highly reproducible, multi-donor human brain cortical organoid model generated by the co-development of cells from a panel of individual donors in a single organoid, while maintaining fidelity to endogenous tissue. By reaggregating cells from multiple single-donor organoids at the neural stem or committed progenitor cell stage, we generate Chimeroids in which each donor produces all cell lineages of the cerebral cortex, even when using pluripotent stem cell lines with notable growth biases. We leveraged Chimeroids to investigate inter-individual variation in susceptibility to neurotoxic stressors that exhibit high clinical phenotypic variability: ethanol and the anti-epileptic drug valproic acid. Individual donors varied in both the penetrance of the effect on target cell types, and the molecular phenotype within each affected cell type. Our results show that human genetic background may be an important mediator of neurotoxin susceptibility and introduce Chimeroids as a scalable system for high-throughput investigation of the contribution of human genetic variation to brain development and disease.
A topographical atlas of αSyn dosage and cell-type expression in the mouse brain and periphery
Authors: Geertsma Haley M. , Fisk Zoe A. , Sauline Lillian , Prigent Alice , Kurgat Kevin , Callaghan Steve M. ,   aSCENT-PD consortium, Henderson Michael X. , Rousseaux Maxime W.C.
Published: October 2023

Parkinson’s disease (PD) is the second most common neurodegenerative disease worldwide and presents pathologically with Lewy pathology and dopaminergic neuron loss. Lewy pathology contains aggregated αSynuclein (αSyn), a protein encoded by theSNCAgene which is also mutated or duplicated in a subset of familial PD cases. Due to its predominant presynaptic localization, immunostaining for the protein results in diffuse signal, providing little insight into the types of cells expressing αSyn. As a result, insight into αSyn expression-driven cellular vulnerability has been difficult to ascertain. Using a combination of knock-in mice that target αSyn to the nucleus of cells (SncaNLS) andin situhybridization ofSncain wild-type mice, we systematically map the topography and cell types expressing αSyn in the mouse brain, spinal cord, retina, and gut. We find a high degree of correlation between αSyn protein and RNA levels across multiple brain regions and further identify cell types with low and high αSyn. We found that αSyn is highly expressed in neurons, particularly those involved in PD and to a lower extent in non-neuronal cell types, notably those of oligodendrocyte lineage. We also find that αSyn is devoid in certain neuron types (e.g. ChAT-positive motor neurons), and that all enteric neurons express αSyn to a certain degree. Taken together, this atlas provides much-needed insight into the cellular topography of αSyn, and provides a quantitative map to test assumptions about the role of αSyn in network vulnerability in PD and other αSynucleinopathies.
Beyond human-likeness: Socialness is more influential when attributing mental states to robots
Authors: Jastrzab Laura E. , Chaudhury Bishakha , Ashley Sarah A. , Koldewyn Kami , Cross Emily S.
Published: October 2023

We sought to replicate and expand previous work showing that the more human-like a robot appears, the more willing people are to attribute mind-like capabilities and socially engage with it. Forty-two participants played games against a human, a humanoid robot, a mechanoid robot, and a computer algorithm while undergoing functional neuroimaging. Replicating previous studies, we confirmed that the more human-like the agent, the more participants attributed a mind to them. However, exploratory analyses revealed that beyond humanness, the perceivedsocialnessof an agent appeared to be as important, if not more so, for mind attribution. Our findings suggest that top-down knowledge cues are just as important, if not more so, than bottom-up stimulus cues when exploring mind attribution in non-human agents. While further work is now required to test this hypothesis directly, these preliminary findings hold important implications for robotic design and to understand and test the flexibility of human social cognition when people engage with artificial agents.
Integrating microbial abundance time series with fermentation dynamics of the rumen microbiomeviamathematical modelling
Authors: Davoudkhani Mohsen , Rubino Francesco , Creevey Christopher J. , Ahvenjärvi Seppo , Bayat Ali R. , Tapio Ilma , Belanche Alejandro , Muñoz-Tamayo Rafael
Published: October 2023

The rumen represents a dynamic microbial ecosystem where fermentation metabolites and microbial concentrations change over time in response to dietary changes. The integration of microbial genomic knowledge and dynamic modelling can enhance our system-level understanding of rumen ecosystem’s function. However, such an integration between dynamic models and rumen microbiota data is lacking. The objective of this work was to integrate rumen microbiota time series determined by 16S rRNA gene amplicon sequencing into a dynamic modelling framework to link microbial data to the dynamics of the volatile fatty acids (VFA) production during fermentation. For that, we used the theory of state observers to develop a model that estimates the dynamics of VFA from the data of microbial functional proxies associated with the specific production of each VFA. We determined the microbial proxies using CowPi to infer the functional potential of the rumen microbiota and extrapolate their functional modules from KEGG (Kyoto Encyclopedia of Genes and Genomes). The approach was challenged using data from anin vitroRUSITEC experiment and from anin vivoexperiment with four cows. The model performance was evaluated by the coefficient of variation of the root mean square error (CRMSE). For thein vitrocase study, the mean CVRMSE were 9.8% for acetate, 14% for butyrate and 14.5% for propionate. For thein vivocase study, the mean CVRMSE were 16.4% for acetate, 15.8% for butyrate and 19.8% for propionate. The mean CVRMSE for the VFA molar fractions were 3.1% for acetate, 3.8% for butyrate and 8.9% for propionate. Ours results show the promising application of state observers integrated with microbiota time series data for predicting rumen microbial metabolism.
Characterizing cell-type spatial relationships across length scales in spatially resolved omics data
Authors: dos Santos Peixoto Rafael , Miller Brendan F. , Brusko Maigan A. , Aihara Gohta , Atta Lyla , Anant Manjari , Atkinson Mark A. , Brusko Todd M. , Wasserfall Clive H. , Fan Jean
Published: October 2023

Spatially resolved omics (SRO) technologies enable the identification of cell types while preserving their organization within tissues. Application of such technologies offers the opportunity to delineate cell-type spatial relationships, particularly across different length scales, and enhance our understanding of tissue organization and function. To quantify such multi-scale cell-type spatial relationships, we developed CRAWDAD, Cell-type Relationship Analysis Workflow Done Across Distances, as an open-source R package with source code and additional documentation athttps://jef.works/CRAWDAD/.

To demonstrate the utility of such multi-scale characterization, recapitulate expected cell-type spatial relationships, and evaluate against other cell-type spatial analyses, we applied CRAWDAD to various simulated and real SRO datasets of diverse tissues assayed by diverse SRO technologies. We further demonstrate how such multi-scale characterization enabled by CRAWDAD can be used to compare cell-type spatial relationships across multiple samples. Finally, we applied CRAWDAD to SRO datasets of the human spleen to identify consistent as well as patient and sample-specific cell-type spatial relationships. In general, we anticipate such multi-scale analysis of SRO data enabled by CRAWDAD will provide useful quantitative metrics to facilitate the identification, characterization, and comparison of cell-type spatial relationships across axes of interest.
A highly resolved network reveals the role of terrestrial herbivory in structuring aboveground food webs
Authors: Hale Kayla R. S. , Curlis John David , Auteri Giorgia G. , Bishop Sasha , French Rowan L. K. , Jones Lance E. , Mills Kirby L. , Scholtens Brian G. , Simons Meagan , Thompson Cody , Tourville Jordon , Valdovinos Fernanda S.
Published: October 2023

Comparative studies suggest remarkable similarities among food webs across habitats, including systematic changes in their structure with diversity and complexity (scale-dependence). However, historic aboveground terrestrial food webs (ATFWs) have coarsely grouped plants and insects such that these webs are generally small, and herbivory is disproportionately underrepresented compared to vertebrate predator-prey interactions. Furthermore, terrestrial herbivory is thought to be structured by unique processes compared to size-structured feeding in other systems. Here, we present the richest ATFW to date, including ∼580,000 feeding links among ∼3,800 taxonomic species, sourced from ∼27,000 expert-vetted interaction records annotated as feeding upon one of six different resource types: leaves, flowers, seeds, wood, prey, and carrion. By comparison to historical ATFWs and null ecological hypotheses, we show that our temperate forest web displays a potentially unique structure characterized by two properties: a) a large fraction of carnivory interactions dominated by a small number of hyper-generalist, opportunistic bird and bat predators, and b) a smaller fraction of herbivory interactions dominated by a hyper-rich community of insects with variably-sized but highly-specific diets. We attribute our findings to the large-scale, even resolution of vertebrate, insect, and plant guilds in our food web.
AngoraPy: A Python Toolkit for Modelling Anthropomorphic Goal-Driven Sensorimotor Systems
Authors: Weidler Tonio , Goebel Rainer , Senden Mario
Published: October 2023

Abstract

Goal-driven deep learning is increasingly used to supplement classical modeling approaches in computational neuroscience. The strength of deep neural networks lies in their ability to autonomously learn the connectivity required to solve complex and ecologically valid tasks, obviating the need for hand-engineered or hypothesis-driven connectivity patterns. Consequently, goal-driven models can generate hypotheses about the neurocomputations underlying cortical processing. Whereas goal-driven modeling is becoming increasingly common in perception neuroscience, its application to sensorimotor control is currently hampered by the complexity of the methods required to train models comprising the closed sensation-action loop. To mitigate this hurdle, we introduceAngoraPy, a modeling library that provides researchers with the tools to train complex recurrent convolutional neural networks that model sensorimotor systems.
Neither Williston nor Dollo: mandibular complexity from stem tetrapods to modern amphibians
Authors: Watt Emily C. , Felice Ryan N. , Goswami Anjali
Published: October 2023

Directional trends in evolution have long captured the attention of biologists, and are particularly interesting when they reflect fundamental developmental processes that underlie morphological change. Here, we apply deep time data and a phylogenetic comparative framework to assess two fundamental “laws” – Williston’s law of phenotypic simplification and Dollo’s law of irreversibility – in the tetrapod mandible, a structure that has sustained the same primary function of feeding for nearly 400 million years. In spite of this conserved function, the tetrapod mandible has undergone numerous morphological and compositional changes during and since the initial water-to-land transition around 390Ma. To quantify these shifts, we reconstructed the compositional ev olution of the mandible with 31 traits scored in 568 species from early tetrapods through to modern amphibians, thereby capturing immense developmental and ecological diversity as well as an excellent fossil record. Mandibular complexity and jaw disparity are highest at the base of the tetrapod tree and generally decrease through time, with stasis dominating over the last ~160M years. Nonetheless, we find a lack of support for Williston’s and Dollo’s laws, with loss and gain of jaw components equally likely throughout the course of early tetrapod and amphibian evolution. Combined, our results demonstrate that evolutionary patterns of mandibular complexity are more nuanced than either Williston’s or Dollo’s laws allow. Thus, laws of simplification are too crude to capture the evolutionary processes underlying the evolution of even a functionally conserved structure through deep time.

The lower jaw is a key innovation in vertebrate evolution with a unifying primary function: feeding. In spite of this conserved function, the jaw is extremely diverse in shape and composition. In limbed vertebrates (tetrapods), the jaw evolves from a complex structure comprising multiple elements and high numbers of teeth towards a simpler structure comprising few elements and generally fewer teeth. Superficially, this pattern suggests support for both Williston’s and Dollo’s laws of phenotypic simplification and irreversibility, respectively. However, we find a lack of support for either law in the jaw of the earliest tetrapods and amphibians, adding to growing literature refuting overly simplified “laws” governing organismal evolution.
RAS isoform specific activities are disrupted by disease associated mutations during cell differentiation
Authors: Chippalkatti Rohan , Parisi Bianca , Kouzi Farah , Laurini Christina , Ben Fredj Nesrine , Abankwa Daniel Kwaku
Published: October 2023

The Ras-MAPK pathway is aberrantly regulated in cancer and developmental diseases called RASopathies. While typically the impact of Ras on the proliferation of various cancer cell lines is assessed, it is poorly established how Ras affects cellular differentiation.

Here we implement the C2C12 myoblast cell line to systematically study the effect of Ras mutants and Ras-pathway drugs on differentiation. We first provide evidence that a minor pool of Pax7+ progenitors replenishes a major pool of transit amplifying cells that are ready to differentiate. Our data indicate that Ras isoforms have distinct roles in the differentiating culture, where K-Ras is more important than N-Ras to maintain the progenitor pool and H-Ras is significant for terminal differentiation. This assay could therefore provide significant new insights into Ras biology and Ras-driven diseases.

In line with this, we found that all oncogenic Ras mutants block terminal differentiation of transit amplifying cells. Notably, while RASopathy K-Ras variants that are also NF1-GAP resistant also block differentiation, albeit less than their oncogenic counterparts. Profiling of targeted Ras-pathway drugs on oncogenic Ras mutants revealed their distinct abilities to restore normal differentiation as compared to triggering cell death. In particular, the MEK-inhibitor trametinib could broadly restore differentiation, while the mTOR-inhibitor rapamycin broadly suppressed differentiation.

We expect that this quantitative assessment of the impact of Ras-pathway mutants and drugs on cellular differentiation has great potential to complement cancer cell proliferation data.
Predicting Suitable Habitats Of Critically Endangered Chinese Pangolin In Assam, India
Authors: Sarma Kuladip , Krishna Murali , Boro Barin Kumar , Saikia Malabika Kakati , Sarania Bidyut , Basumatary Himolin , Saikia Bhrigu Prasad , Saikia Prasanta Kumar
Published: October 2023

Chinese pangolin is a least known species in terms of its ecology and population status in India. The present study of Chinese pangolin in Kaziranga-Karbi-Anglong landscape aimed to gather information on species distribution and population status and also an account of threats of the species was investigated. A total of 24 occurrence points were collected from all over Assam and used to get a predictive potential distribution map for the species via Maxent and Random Forest models. To understand the knowledge level of the local people, a total of 13 villages in the north east boundary of North Karbi Anglong Wildlife Sactuary have been surveyed and 160 respondents were interviewed. The AUC values for the two models namely Maxent (0.736) and Random Forest (0.87) were different. Out of the six environmental parameters chosen, the altitude clarified the maximum variation in the model (62 %) followed by the seasonal temperature (bio4; 19.6 %) in the Maxent model. At the same time, these two variables were also found to be of greater significance in the Random Forest model. The species has been least seen by most of the respondents in the last 10 years (43.7%). Most of the respondent of age class 18-24 years never saw a pangolin (82.5%) in the area which depict the population decline of the spcies. Scales were the most used body parts for traditional medicine (58.8%) especially for exceesive saliva secretion in children. The resultant potential habitat in the predictive distribution map in Assam needs to be confirmed with ground verification and accordingly inclusion in the priority conservation zone for Chinese pangolin in Assam should be done.
Ecology and not phylogeny influences sensitivity to climate change in Muscicapidae Flycatchers in Eastern Himalayan and Indo-Burman hotspots
Authors: Dhanda Aavika , Jezierski Michał T. , Coulson Tim , Clegg Sonya
Published: October 2023

Aims

Species’ distributional responses to climate change can depend on ecology and phylogeny. The degree of habitat specialism is potentially important because habitat generalists with wider distributions are assumed to be less sensitive to environmental changes compared to narrowly-distributed habitat specialists. Additionally, predicting which aspects of the changing climate impacts species with different habitat associations may be particularly challenging in complex environments such as those of tropical mountains. We explore the effects of climate change on potential distributions of Muscicapidae Flycatchers in parts of the Eastern Himalayan Mountains and the Indo-Burman range, and relate predictions to the level of ecological habitat specialism, while accounting for phylogenetic relatedness.

Location

Bhutan and Northeast India

Methods

We used Maxent to develop ecological niche models of 60 Muscicapidae Flycatchers under different climatic scenarios by collating presences from Global Biodiversity Information Facility, Bioclimatic variables from WorldClim, and elevation from ASTER. Species were scored as habitat specialists or generalists using the Species Specialism Index. Variables with high contributions to Maxent models were extracted to explore sensitivity to climate change based on habitat specialism while testing for phylogenetic signal using Phylogenetic Generalised Least Squares.

Results

Maxent models had the highest contributions from variable bio8 (mean temperature of wettest quarter) under present climate, and tmax (maximum temperature) under future climatic scenarios. Phylogenetic Generalised Least Squares revealed that habitat generalists had higher sensitivity to climate change than specialists. We did not detect strong phylogenetic signal in sensitivity to abiotic variables under all climate scenarios.

Main conclusions

Potential distributions of Muscicapidae Flycatchers were sensitive to temperature variable in the month of the highest precipitation, and to maximum temperature. Potential distributions of habitat generalists were particularly sensitive to these abiotic variables, and those of habitat specialists less so. Sensitivity to abiotic variables did not show a pattern of phylogenetic niche conservatism. climate change, Muscicapidae Flycatchers, phylogenetic niche conservatism, habitat specialism, tropical mountains, Maxent
Learning modifies attention during bumblebee visual search
Authors: Robert Théo , Tarapata Karolina , Nityananda Vivek
Published: October 2023

The role of visual search during bee foraging is relatively understudied compared to the choices made by bees. As bees learn about rewards, we predicted that visual search would be modified to prioritise rewarding flowers. To test this, we ran an experiment testing how bee search differs in the initial and later part of training as they learn about flowers with either higher-or lower-quality rewards. We then ran an experiment to see how this prior training with reward influences their search on a subsequent task with different flowers. We used the time spent inspecting flowers as a measure of attention and found that learning increased attention to rewards and away from distractors. Higher quality rewards led to decreased attention to non-flower regions, but lower quality rewards did not. Prior experience of lower rewards also led to more attention to higher rewards compared to distractors and non-flower regions. Our results suggest that flowers would elicit differences in bee search behaviour depending on the sugar content of their nectar. They also demonstrate the utility of studying visual search and have important implications for understanding the pollination ecology of flowers with different qualities of reward.

Significance Statement

Studies investigating how foraging bees learn about reward typically focus on the choices made by the bees. How bees deploy attention and visual search during foraging is less well studied. We analysed flight videos to characterise visual search as bees learn which flowers are rewarding. We found that learning increases the focus of bees on flower regions. We also found that the quality of the reward a flower offers influences how much bees search in non-flower areas. This means that a flower with lower reward attracts less focussed foraging compared to one with a higher reward. Since flowers do differ in floral reward, this has important implications for how focussed pollinators will be on different flowers. Our approach of looking at search behaviour and attention thus advances our understanding of the cognitive ecology of pollination.