bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using evidence-based strategies, including coverage of remote cardiac rehabilitation, to increase cardiac rehabilitation participation - a community health insurance plan’s experience
Authors: Magdon-Ismail Zainab , Murphy Sheree , Gauthier Vickie , Wyrick Tiana , Rowe Cori , Austin Rachael , Cuevas Pennie , Pickreign Jeremy , Coplin Bruce 
Published: November 2024

AbstractBackgroundBarriers to referral, enrollment, and participation in cardiac rehabilitation (CR) contribute to low rates of completion despite known benefits. Barriers are system, provider and patient related. In this observational cohort quality improvement study, we examined the impact a community-based, not-for-profit health insurance plan had on barriers to CR participation.MethodsThe Capital District Physicians’ Health Plan (CDPHP) in Albany, New York developed and implemented a cardiac rehabilitation initiative (CRI) to increase CR rates using evidence-based strategies. CDPHP: 1) eliminated patient cost-share, 2) covered remote CR (RCR), 3) implemented physician valued-based incentives, 4) presented metrics to providers, 5) educated providers and patients, and 6) dedicated staff to facilitating enrollment. Chi-square tests were used to identify differences among patients who enrolled in facility-based CR (FBCR), RCR and no CR. CR enrollment rate distributions were evaluated between Q1, 2021 and Q2, 2022.ResultsA total of 1,736 patients with varying cardiac conditions were eligible for CR in the study period. Between Q1, 2021 and Q2, 2022, enrollment went from 11.1% (32/286) to 16.2% (50/308) in FBCR; 0.7% (2/286) to 10.7% (33/308) in RCR; and 11.9% (34/286) to 26.9% (83/308) overall (P<.0001). Time to enrollment went from 40 to 47 days for FBCR (P=0.1792), 53 to 20 days for RCR (P<.0001) and 43 to 36 days overall (P=0.3348). Older patients were more likely to enroll in CR as were patients who underwent cardiac procedures.ConclusionsThe CRI created a call-to-action among providers to address CR referral and enrollment. RCR increased CR rates and were additive to FBCR rates, suggesting that the introduction of RCR will not displace FBCR. Time to enrollment improved overall, driven by improvement in those enrolling in RCR. Increasing CR engagement requires coordinated effort from stakeholders—cardiology providers, hospitals, CR providers and health plans.
DeFrND: detergent-free reconstitution into native nanodiscs with designer membrane scaffold peptides
Authors: Ren Qian , Wang Jing , Idikuda Vinay , Zhang Shanwen , Shin Jeehae , Ludlam W. Grant , Real Hernandez Luis M , Levental Ilya , Martemyanov Kirill , Chanda Baron , Bao Huan 
Published: November 2024

AbstractMembrane scaffold proteins-based nanodiscs (NDs) have facilitated unprecedented structural and biophysical analysis of membrane proteins in a near-native lipid environment. However, successful reconstitution of membrane proteins in NDs requires prior solubilization and purification in detergents, which may impact their physiological structure and function. Furthermore, the detergent-mediated reconstitution of NDs is unlikely to recapitulate the precise composition or asymmetry of native membranes. To circumvent this fundamental limitation of traditional ND technology, we herein describe the development of membrane-solubilizing peptides to directly extract membrane proteins from native cell membranes into nanoscale discoids. By systematically protein engineering and screening, we created a new class of chemically modified Apolipoprotein-A1 mimetic peptides to enable the formation of detergent-free NDs (DeFrNDs) with high efficiency. NDs generated with these engineered membrane scaffold peptides are suitable for obtaining high-resolution structures using single-particle cryo-EM with native lipids. To further highlight the versatility of DeFrNDs, we directly extract a sampling of membrane signaling proteins with their surrounding native membranes for biochemical and biophysical interrogations.
The BumbleBox: An open-source platform for quantifying behavior in bumblebee colonies
Authors: Easton-Calabria August , Crall James D. 
Published: November 2024

0.AbstractBumblebees (Apini:Bombus) are important pollinators globally and an emerging model system for studying the ecology and evolution of social behavior and effects of environmental stressors on bees.Behavioral studies of bumblebees have conventionally relied on labor and time-intensive manual observations. While recent years have seen rapid advances in automated behavioral tracking in social insects, these tracking technologies are often expensive and require extensive programming experience, limiting accessibility and widespread adoption.Here we introduce the BumbleBox, an open-source system for automated tracking and behavioral quantification of individual bumblebees that can be built using low-cost consumer components and DIY fabrication (i.e., 3D-printing and laser-cutting). We provide an integrated pipeline for data collection and analysis, including nest arena design, software for automated collection of video data, and the quantification of individual behavior.The BumbleBox system is designed to be (a)accessible, requiring no prior experience with programming or hardware design to operate; (b)scalable, allowing long-term, automated tracking across many units in parallel at low-cost; and (c)modular, allowing for flexible adoption to unique applications in bumblebees and other systems. We validate the use of this system in a widespread bumblebee species (Bombus impatiens) that is both commercially and ecologically important. Finally, we highlight widespread potential applications in quantifying behavior and pollinator health in bumblebees and other social insects, including screening impacts of pesticides and other environmental stressors on social behavior.
Convolutional neural network models describe the encoding subspace of local circuits in auditory cortex
Authors: Wingert Jereme C. , Parida Satyabrata , Norman-Haignere Sam , David Stephen V. 
Published: November 2024

AbstractAuditory cortex encodes information about nonlinear combinations of spectro-temporal sound features. Convolutional neural networks (CNNs) provide an architecture for generalizable encoding models that can predict time-varying neural activity evoked by natural sounds with substantially greater accuracy than established models. However, the complexity of CNNs makes it difficult to discern the computational properties that support their improved performance. To address this limitation, we developed a method to visualize the tuning subspace captured by a CNN. Single-unit data was recorded using high channel-count microelectrode arrays from primary auditory cortex (A1) of awake, passively listening ferrets during presentation of a large natural sound set. A CNN was fit to the data, replicating approaches from previous work. To measure the tuning subspace, the dynamic spectrotemporal receptive field (dSTRF) was measured as the locally linear filter approximating the input-output relationship of the CNN at each stimulus timepoint. Principal component analysis was then used to reduce this very large set of filters to a smaller subspace, typically requiring 2-10 filters to account for 90% of dSTRF variance. The stimulus was projected into the subspace for each neuron, and a new model was fit using only the projected values. The subspace model was able to predict time-varying spike rate nearly as accurately as the full CNN. Sensory responses could be plotted in the subspace, providing a compact model visualization. This analysis revealed a diversity of nonlinear responses, consistent with contrast gain control and emergent invariance to spectrotemporal modulation phase. Within local populations, neurons formed a sparse representation by tiling the tuning subspace. Narrow spiking, putative inhibitory neurons showed distinct patterns of tuning that may reflect their position in the cortical circuit. These results demonstrate a conceptual link between CNN and subspace models and establish a framework for interpretation of deep learning-based models.Significance statementAuditory cortex mediates the representation and discrimination of complex sound features. Many models have been proposed for cortical sound encoding, varying in their generality, interpretability, and ease of fitting. It has been difficult to determine if/what different functional properties are captured by different models. This study shows that two families of encoding models, convolutional neural networks (CNNs) and tuning subspace models account for the same functional properties, providing an important analytical link between accurate models that are easy to fit (CNNs) and models that are straightforward to interpret (tuning subspace).
Random subsamples of animal populations can reveal intrinsic differences in sociality with key implications in ecology, conservation and disease transmission
Authors: Conteddu Kimberly , Kaur Prabhleen , Brown Michael , Fennessy Julian , Fennessy Stephanie , Hart Emma , Amin Bawan , David Anna , Griffin Laura L. , Faull Jane , Grignolio Stefano , Brivio Francesca , Haigh Amy , Kirwan Liam , Salter-Townshend Michael , Ciuti Simone 
Published: November 2024

AbstractAnimal populations are under mounting stress from the dual threats of climate change and rapid global human population growth, raising significant concerns about declining wildlife and the rising risk of zoonotic diseases. In many species, social interactions can be a highly plastic suite of behaviours that are responsive to these disturbances and are consequential to other processes like disease transmission and population dynamics. Studying social interactions can be challenging in that researchers often rely on wildlife population subsamples due to practical constraints and costs, which can introduce biases in the reliability of social network metrics. We investigated the extent to which subsamples can depict intrinsic characteristics of wildlife populations using data from three distinct species: peri-urban fallow deer, Alpine ibex and Angolan giraffe. We showed that random subsamples of these populations could still reveal differences in their social behaviour, indicating that, as long as researchers have a reliable estimate of population size, subsampling animal populations can be an effective and precise method to infer their sociality and offer valuable empirical data for management, conservation and zoonotic disease ecology. Furthermore, we demonstrate that non-random sampling, influenced for instance by animal personality and related trappability, can introduce significant biases in social network estimates. These findings underscore the importance of accounting for sampling biases in social network analysis and offer a robust framework for using partial networks in ecological studies and conservation management.
Glycophagy is an ancient bilaterian pathway supporting metabolic adaptation through STBD1 structural evolution
Authors: Ren Liting , Bai Yitian , Shi Chenyu , Tan Ying , Zhao Shuyan , Li Qi , Macqueen Daniel J , Liu Shikai 
Published: November 2024

AbstractThe selective autophagy of glycogen (glycophagy) has recently emerged as being crucial to glucose homeostasis in vertebrates, yet its origins remain elusive. Here, we provide evidence that starch-binding domain-containing protein 1 (STBD1), the key glycophagy receptor in vertebrates, is functionally conserved in the Pacific oyster, revealing its conserved position within ancient autophagy networks. We show that STBD1 in oysters - as seen in other invertebrate groups - possesses an N-terminal carbohydrate binding module family 20 (CBM20) domain, representing the ancestral state for this protein, while a shuffling of CBM20 to the C- terminus occurred during early chordate evolution. Structural modelling and functional studies reveal that the N-terminal CBM20 organization of STBD1 enhances glycogen binding. Functional experiments demonstrate that an STBD1-glycogen complex, anchored by GABARAPL2, facilitates an increased glycogen flux into autophagosomes for lysosomal degradation. We conclude that glycophagy is deeply conserved in bilaterians and that STBD1 structural evolution underlies potentially adaptive variation in metabolic strategies across distinct animal clades.
Aberrant expression of CD14 in breast tumor cells is associated with poor outcome
Authors: Katayama Hiroyuki , Dou Rongzhang , León-Letelier Ricardo A. , Irajizad Ehsan , Sevillano Alejandro , Park Soyoung , Hsiao Fu Chung , Cai Yining , Vykoukal Jody , Fahrmann Johannes , Dennison Jennifer , Barrientos-Toro Elizve , Raso Maria Gabriela , Sahin Aysegul , Hanash Sam 
Published: November 2024

AbstractEmerging evidence suggests that cancer cells can mimic features of immune cells during oncogenic transformation to drive disease progression. We assessed the occurrence of immunological markers in breast cancer cells to determine their expression pattern. We initially analyzed 18 immune protein markers (CCR4, CCR6, CCR7, CD11, CD123, CD14, CD16, CD19, CD24, CD25, CD27, CD3, CD38, CD4, CD45, CD56, CD8 and CXCR3) expressed on the surface of 28 breast cancer cell lines using mass spectrometry. CD14 protein expression in tumor cells and its association with clinical outcomes was subsequently evaluated by tissue microarray (TMA) analysis of 346 breast tumors. Single-cell RNA sequencing data from breast cancer tumors and bulk transcriptomic data of breast cancer cell lines were interrogated for molecular signatures associated with CD14 tumor cell expression. Among the markers interrogated, CD14proteinwas aberrantly expressed on the surface of 13 out of 15 triple-negative breast cancer (TNBC), one of six hormone receptor positive (HR+), one of five hormone receptors negative (HR-)/Her2+ cell lines. Likewise, RNA expression revealed higher levels of CD14 in TNBC cell lines compared to other subtypes. Tumor tissue microarray analysis revealed elevated levels of CD14 membrane expression predominantly in TNBC and was associated with higher tumor grade and increased incidence of disease recurrence compared to CD14-negative tumors. The CD14-positive subgroup exhibited Nuclear Factor Kappa Beta (NFkB) and TGF-β centric networks at both the protein and Single-cell RNA levels. We have uncovered a novel subset of breast cancers characterized by aberrant surface expression of CD14 associated with aggressive disease. CD14 identifies a subset of breast cancers with poor outcome and is a potential therapeutic target.
Perineuronal nets on CA2 pyramidal cells and parvalbumin-expressing cells differentially regulate hippocampal dependent memory
Authors: Alexander Georgia M. , Nikolova Viktoriya D. , Stöber Tristan M. , Gruzdev Artiom , Moy Sheryl S. , Dudek Serena M. 
Published: November 2024

ABSTRACTPerineuronal nets (PNNs) are a specialized extracellular matrix that surround certain populations of neurons, including (inhibitory) parvalbumin (PV) expressing-interneurons throughout the brain and (excitatory) CA2 pyramidal neurons in hippocampus. PNNs are thought to regulate synaptic plasticity by stabilizing synapses and as such, could regulate learning and memory. Most often, PNN functions are queried using enzymatic degradation with chondroitinase, but that approach does not differentiate PNNs on CA2 neurons from those on adjacent PV cells. To disentangle the specific roles of PNNs on CA2 pyramidal cells and PV neurons in behavior, we generated conditional knockout mouse strains with the primary protein component of PNNs, aggrecan (Acan), deleted from either CA2 pyramidal cells (Amigo2AcanKO) or from PV cells (PVAcanKO). Male and female animals of each strain were tested for social, fear, and spatial memory, as well as for reversal learning. We found that Amigo2AcanKO animals, but not PVAcanKO animals, had impaired social memory and reversal learning. PVAcanKOs, but not Amigo2AcanKOs had impaired contextual fear memory. These findings demonstrate independent roles for PNNs on each cell type in regulating hippocampal-dependent memory. We further investigated a potential mechanism of impaired social memory in the Amigo2AcanKO animals and found reduced input to CA2 from the supramammillary nucleus (SuM), which signals social novelty. Additionally, Amigo2AcanKOs lacked a social novelty-related local field potential response, suggesting that CA2 PNNs may coordinate functional SuM connections and associated physiological responses to social novelty.SIGNIFICANCE STATEMENTPerineuronal nets (PNNs) surround both inhibitory parvalbumin (PV)-expressing neurons and excitatory CA2 pyramidal neurons, but previous studies using enzymatic degradation cannot differentiate the relative roles of PNNs in the two populations. By conditionally deleting aggrecan (Acan) from CA2 pyramidal neurons without affecting PNNs on PV cells, and vice versa, we discovered distinct roles of PNNs on each cell type in behavior. Social memory, which requires CA2 activity, was impaired in mice lacking CA2 PNNs, but not in those lacking PV PNNs. Cognitive flexibility, assessed by reversal learning was also impaired in mice lacking CA2 PNNs, whereas contextual fear memory was impaired in those lacking PV PNNs. Thus, PNNs on each cell type differentially contribute to different forms of hippocampal-dependent memory.
Interpretable and Robust Machine Learning for Exploring and Classifying Soundscape Data
Authors: Omprakash Arpit , Balakrishnan Rohini , Ewers Robert , Sethi Sarab 
Published: November 2024

AbstractThe adoption of machine learning in Passive Acoustic Monitoring (PAM) has improved prediction accuracy for tasks like species-specific call detection and habitat quality estimation. However, these models often lack interpretability, and PAM generates vast amounts of non-informative data, as soundscapes are typically information sparse.Here, we developed ecologically interpretable methods that accurately predict land use from audio while filtering unwanted data. Audio from habitats in Southern India (evergreen forests, deciduous forests, scrublands, grasslands) was collected and categorised by land use (reference, disturbed, and agriculture). We used Gaussian Mixture Models (GMMs) on top of a Convolutional Neural Network (CNN)-based feature extractor to predict land use.Thresholding based on likelihood values from GMMs improved model accuracy by excluding uninformative data, enabling our method to outperform models such as Random Forests and Support Vector Machines. By analysing areas of acoustic feature space driving predictions, we identified “keystone” soundscape elements for each land use, including both biotic and anthropogenic sources.Our approach provides a novel method for ecologically meaningful interpretation and exploration of large acoustic datasets independent of specific feature extractors. Our study paves the way for soundscape monitoring to deliver robust and trustworthy habitat assessments on scales that would not otherwise be possible.
BLAKORinputs to the BNST regulate social stress-escalated alcohol consumption
Authors: Paliarin Franciely , Duplantis Chelsea , Doré Evan , Basavanhalli Samhita , Weiser Emma , Jones Tameka W. , Maiya Rajani 
Published: November 2024

BackgroundAversive social experiences can lead to escalated drug consumption and increase the risk of relapse to drug seeking. Individuals who consume alcohol to alleviate the effects of social stress are more likely to develop an alcohol use disorder (AUD). Repeated social defeat stress (SDS) enhances the rewarding and reinforcing effects of alcohol. However, the neural mechanisms that underlie social stress-escalated alcohol drinking are not well understood. Here we explored the role of the dynorphin/kappa opioid receptor (Dyn/KOR) system in regulating social stress-escalated alcohol consumption.MethodsMale and female mice were subjected to repeated SDS for 10 days following which they were left undisturbed in their home cages. They were then subject to intermittent access (IA) two-bottle choice alcohol consumption procedure. The effects of systemic and BNST-specific KOR antagonism using the selective KOR antagonist NorBNI on stress-escalated drinking were evaluated. Using chemogenetic approaches inOprk1-Cremice, we examined the role of KOR expressing cells in the basolateral amygdala (BLAKORs) and BLAKOR-BNST pathway in social stress-escalated alcohol consumption.ResultsRepeated SDS increased alcohol consumption and preference in both males and females. Systemic KOR antagonism attenuated SDS-escalated alcohol consumption in both males and females. BNST -specific KOR antagonism also attenuated stress-escalated drinking in males. Finally, selective chemogenetic activation of BLAKORsand BKAKOR-BNST pathway attenuated social stress-escalated alcohol consumption in both sexes.ConclusionOur results suggest a significant role for BLAKORprojections to the BNST in regulating social stress-escalated alcohol consumption. Our results provide further evidence that the Dyn/KOR system maybe a viable target for medications development to tareat comorbid stress and AUD.
Sudden sensory events trigger modality-independent responses across layers in the mouse neocortex
Authors: Benusiglio Diego , Asari Hiroki 
Published: November 2024

AbstractSudden sensory events trigger widespread electrocortical responses and noticeable changes in an animal’s behavior. It remains unclear, though, how this “surprise” signal is generated via afferent sensory input and represented by neuronal ensembles. Using in vivo electrophysiology, here we recorded the activity of different cortical areas across layers in awake head-fixed mice, while presenting sensory stimuli of different modalities and saliencies. When brief, salient stimuli were delivered at long intervals, we found prominent responses across cortical areas regardless of the stimulus modalities, resembling those observed in human electroencephalography. These responses were larger and emerged earlier in the infragranular layer than in the granular layer of the primary sensory cortex. At short inter-stimulus intervals, in contrast, only modality-specific responses were observed in the corresponding primary sensory cortex. These results indicate that sensory information travels through multiple ascending pathways, in particular, supra-modal surprise signals via non-classical sensory pathways to the cortex.
Critical role of Spatio-Temporally Regulated Maternal RNAs in Zebrafish Embryogenesis
Authors: Kushawah Gopal , Amaral Danielson Baia , Hassan Huzaifa , Gogol Madelaine , Nowotarski Stephanie H. , Bazzini Ariel A. 
Published: November 2024

SummaryThe maternal-to-zygotic transition shifts regulatory control from maternal to zygotic messenger RNAs (mRNA) through maternal mRNA degradation. While temporal aspects of maternal mRNA decay are known, spatial mechanisms remain underexplored. Using CRISPR-Cas9 and CRISPR-Cas13d systems, we functionally dissected the contribution of maternal versus zygotic fractions and overcame challenges of studying embryonic lethal genes. We identified differentially distributed maternal mRNAs in specific cells and evidenced the critical role of five maternal mRNAs,cth1, arl4d, abi1b, foxaandlhx1a,in embryogenesis. Further, we focused on the functionally uncharacterizedcth1gene, revealing its essential role in gametogenesis and embryogenesis.Cth1acts as a spatio-temporal RNA decay factor regulating mRNA stability and accumulation of its targets in a spatio-temporal manner through 3’UTR recognition during early development. Furthermore,Cth13’UTR drives its spatio-temporal RNA localization. Our findings provide new insights into spatio-temporal RNA decay mechanisms and highlight dual CRISPR-Cas strategies in studying embryonic development.HighlightsDifferentially distributed marginal maternal RNAs have a critical role in early embryogenesis.Cas13d complements the Cas9 limitation to study the functions of embryonic lethal genes.Cth1is essential for gametogenesis and early embryonic development.Cth1is a maternal RNA decay factor required for spatio-temporal RNA regulation.3’UTR ofCth1drives its spatio-temporal RNA dynamics.