bluuebunny/crossref_metadata_2025_split huggingface dataset:
Towards Interpretable Cryo-EM: Disentangling Latent Spaces of Molecular Conformations
Authors: Klindt David A. , Hyvärinen Aapo , Levy Axel , Miolane Nina , Poitevin Frédéric 
Published: March 2024

ABSTRACTMolecules are essential building blocks of life and their different conformations (i.e., shapes) crucially determine the functional role that they play in living organisms. Cryogenic Electron Microscopy (cryo-EM) allows for acquisition of large image datasets of individual molecules. Recent advances in computational cryo-EM have made it possible to learn latent variable models of conformation landscapes. However, interpreting these latent spaces remains a challenge as their individual dimensions are often arbitrary. The key message of our work is that this interpretation challenge can be viewed as an Independent Component Analysis (ICA) problem where we seek models that have the property of identifiability. That means, they have an essentially unique solution, representing a conformational latent space that separates the different degrees of freedom a molecule is equipped with in nature. Thus, we aim to advance the computational field of cryo-EM beyond visualizations as we connect it with the theoretical framework of (nonlinear) ICA and discuss the need for identifiable models, improved metrics, and benchmarks. Moving forward, we propose future directions for enhancing the disentanglement of latent spaces in cryo-EM, refining evaluation metrics and exploring techniques that leverage physics-based decoders of biomolecular systems. Moreover, we discuss how future technological developments in time-resolved single particle imaging may enable the application of nonlinear ICA models that can discover the true conformation changes of molecules in nature. The pursuit of interpretable conformational latent spaces will empower researchers to unravel complex biological processes and facilitate targeted interventions. This has significant implications for drug discovery and structural biology more broadly. More generally, latent variable models are deployed widely across many scientific disciplines. Thus, the argument we present in this work has much broader applications in AI for science if we want to move from impressive nonlinear neural network models to mathematically grounded methods that can help us learn something new about nature.
Light-gated Integrator for Highlighting Kinase Activity in Living Cells
Authors: Lin Wei , Phatarphekar Abhishek , Zhong Yanghao , Liu Longwei , Kwon Hyung-Bae , Gerwick William H. , Wang Yingxiao , Mehta Sohum , Zhang Jin 
Published: March 2024

AbstractProtein kinases are key signaling nodes that regulate fundamental biological and disease processes. Illuminating kinase signaling from multiple angles can provide deeper insights into disease mechanisms and improve therapeutic targeting. While fluorescent biosensors are powerful tools for visualizing live-cell kinase activity dynamics in real time, new molecular tools are needed that enable recording of transient signaling activities for post hoc analysis and targeted manipulation. Here, we develop a light-gated kinase activity coupled transcriptional integrator (KINACT) that converts dynamic kinase signals into “permanent” fluorescent marks. KINACT enables robust monitoring of kinase activity across scales, accurately recording subcellular PKA activity, highlighting PKA signaling heterogeneity in 3D cultures, and identifying PKA activators and inhibitors in high-throughput screens. We further leverage the ability of KINACT to drive signaling effector expression to allow feedback manipulation of the balance of GαsR201C-induced PKA and ERK activation and dissect the mechanisms of oncogenic G protein signaling.
Incretin hormones and pharmacomimetics rapidly inhibit AgRP neuron activity to suppress appetite
Authors: McMorrow Hayley E. , Lorch Carolyn M. , Hayes Nikolas W. , Fleps Stefan W. , Frydman Joshua A. , Xia Jessica L. , Samms Ricardo J. , Beutler Lisa R. 
Published: March 2024

AbstractAnalogs of the incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP) have become mainstays of obesity and diabetes management. However, both the physiologic role of incretin hormones in the control of appetite and the pharmacologic mechanisms by which incretin-mimetic drugs suppress caloric intake remain incompletely understood. Hunger-promoting AgRP-expressing neurons are an important hypothalamic population that regulates food intake. Therefore, we set out to determine how incretins analogs affect their activityin vivo. Using fiber photometry, we observed that both GIP receptor (GIPR) and GLP-1 receptor (GLP-1R) agonism acutely inhibit AgRP neuron activity in fasted mice and reduce the response of AgRP neurons to food. Moreover, optogenetic stimulation of AgRP neurons partially attenuated incretin-induced feeding suppression, suggesting that AgRP neuron inhibition is necessary for the full appetite-suppressing effects of incretin-based therapeutics. Finally, we found that GIP but not GLP-1 is necessary for nutrient-mediated AgRP neuron inhibition, representing a novel physiologic role for GIP in maintaining energy balance. Taken together, these findings reveal neural mechanisms underlying the efficacy of incretin-mimetic obesity therapies. Understanding these drugs’ mechanisms of action is crucial for the development of next-generation obesity pharmacotherapies with an improved therapeutic profile.
Pro-cognitive Effects of Dual Tacrine Derivatives Acting as Cholinesterase Inhibitors and NMDA Receptor Antagonists
Authors: Chvojkova Marketa , Kolar David , Kovacova Katarina , Cejkova Lada , Misiachna Anna , Hakenova Kristina , Gorecki Lukas , Horak Martin , Korabecny Jan , Soukup Ondrej , Vales Karel 
Published: March 2024

AbstractTherapeutic options for Alzheimer’s disease are limited. Dual compounds targeting two pathophysiological pathways concurrently may enable enhanced effect. The study focuses on tacrine derivatives acting as acetylcholinesterase (AChE) inhibitors and simultaneously as subunit-dependent N-methyl-D-aspartate (NMDA) receptor antagonists. Compounds with balanced inhibitory potencies for target proteins (K1578 and K1599) or with increased inhibitory potency for AChE (K1592 and K1594) were studied. We aimed to identify the most promising pro-cognitive compound.The pro-cognitive effects of the compounds were studied in cholinergic (scopolamine-induced) and glutamatergic (MK-801-induced) rat models of cognitive deficits in the Morris water maze. Moreover, the effect on locomotion in open field and on AChE activity in relevant brain structures were investigated. The effect of the most promising compound on NMDA receptors was explored byin vitroelectrophysiology.The cholinergic antagonist scopolamine induced a deficit of memory acquisition, however was unaffected by the compounds, and a deficit of reversal learning, that was alleviated by K1578 and K1599. K1578 and K1599 significantly inhibited AChE in striatum, potentially explaining the behavioral observations.Glutamatergic antagonist dizocilpine (MK-801) induced a deficit of memory acquisition, which was alleviated by K1599. K1599 also mitigated the MK-801-induced hyperlocomotion in the open field. The electrophysiology study corroborated the K1599-associated NMDA receptor inhibitory effect.K1599 emerged as the most promising compound, demonstrating pro-cognitive efficacy in both models, consistently with intended dual effect. Our findings contributed to elucidation of structural and functional properties of tacrine derivatives associated with optimalin vivopro-cognitive effects, which further research may benefit from.
The role of rat prelimbic cortex in decision making
Authors: Palmer Jensen A. , White Samantha R. , Lopez Kevin Chavez , Laubach Mark 
Published: March 2024

AbstractThe frontal cortex plays a critical role in decision-making. One specific frontal area, the anterior cingulate cortex, has been identified as crucial for setting a threshold for how much evidence is needed before a choice is made (Domenech & Dreher, 2010). Threshold is a key concept in drift diffusion models, a popular framework used to understand decision-making processes. Here, we investigated the role of the prelimbic cortex, part of the rodent cingulate cortex, in decision making. Male and female rats learned to choose between stimuli associated with high and low value rewards. Females learned faster, were more selective in their responses, and integrated information about the stimuli more quickly. By contrast, males learned more slowly and showed a decrease in their decision thresholds during choice learning. Inactivating the prelimbic cortex in female and male rats sped up decision making without affecting choice accuracy. Drift diffusion modeling found selective effects of prelimbic cortex inactivation on the decision threshold, which was reduced with increasing doses of the GABA-A agonist muscimol. Stimulating the prelimbic cortex through mu opioid receptors slowed the animals’ choice latencies and increased the decision threshold. These findings provide the first causal evidence that the prelimbic cortex directly influences decision processes. Additionally, they suggest possible sex-based differences in early choice learning.
Canopy2: tumor phylogeny inference by bulk DNA and single-cell RNA sequencing
Authors: Weideman Ann Marie K. , Wang Rujin , Ibrahim Joseph G. , Jiang Yuchao 
Published: March 2024

AbstractTumors are comprised of a mixture of distinct cell populations that differ in terms of genetic makeup and function. Such heterogeneity plays a role in the development of drug resistance and the ineffectiveness of targeted cancer therapies. Insight into this complexity can be obtained through the construction of a phylogenetic tree, which illustrates the evolutionary lineage of tumor cells as they acquire mutations over time. We propose Canopy2, a Bayesian framework that uses single nucleotide variants derived from bulk DNA and single-cell RNA sequencing to infer tumor phylogeny and conduct mutational profiling of tumor subpopulations. Canopy2 uses Markov chain Monte Carlo methods to sample from a joint probability distribution involving a mixture of binomial and beta-binomial distributions, specifically chosen to account for the sparsity and stochasticity of the single-cell data. Canopy2 demystifies the sources of zeros in the single-cell data and separates zeros categorized as non-cancerous (cells without mutations), stochastic (mutations not expressed due to bursting), and technical (expressed mutations not picked up by sequencing). Simulations demonstrate that Canopy2 consistently outperforms competing methods and reconstructs the clonal tree with high fidelity, even in situations involving low sequencing depth, poor single-cell yield, and highly-advanced and polyclonal tumors. We further assess the performance of Canopy2 through application to breast cancer and glioblastoma data, benchmarking against existing methods. Canopy2 is an open-sourceRpackage available athttps://github.com/annweideman/canopy2.
Pollination services to crops of watermelon (Citrullus lanatus) and green tomato (Physalis ixocarpa) in the coastal region of Jalisco, Mexico
Authors: Delgado-Carrillo Oliverio , Martén-Rodríguez Silvana , Ramírez-Mejía Diana , Novais Samuel , Quevedo Alexander , Ghilardi Adrian , Sayago Roberto , Lopezaraiza-Mikel Martha , Pérez-Trujillo Erika , Quesada Mauricio 
Published: March 2024

AbstractBees play a pivotal role as pollinators in crops crucial for human consumption. However, the global decline in bee populations poses a significant threat to pollination services and food security worldwide. The loss and fragmentation of habitats due to land-use change are primary factors contributing to bee declines, particularly in tropical forests facing high deforestation rates. Here we evaluate the pollination services on crops of watermelon (Citrullus lanatus) and green tomato (Physalis ixocarpa) in the Tropical Dry Forest of Jalisco, Mexico during 2008, and 2014 to 2017. We describe pollinator community composition and visitation frequency and evaluate pollinator contribution to plant reproductive success and degree of pollinator dependence for each crop species. We also assess how landscape configuration influences the abundance and richness of pollinators, and we use the model Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) to map and value the pollination service in both crops. Our findings reveal that the main pollinator of both crops wasApis mellifera, one of the few abundant pollinators in the study region during the dry season, when watermelon and green tomato are cultivated. Results revealed that in the absence of pollinators, watermelon yielded no fruits, while green tomato experienced a 65% reduction in production. For green tomato, fruit set was positively correlated with pollinator abundance. A positive association between forest cover and total pollinator abundance was observed in green tomato in 2008, but not in watermelon. We also found a positive relationship between the abundance of bees predicted by the InVEST model and the abundance of bees observed in green tomato flowers in 2008. In the study region, green tomato and watermelon rely on pollinators for fruit production, with honeybees (from feral and managed colonies) acting as the most importante provider of pollination services for these crops. Consequently, the conservation of natural protected areas is crucial for sustaining pollinators and ensuring food security.
Evaluating the position of the uncal apex as a predictor of episodic memory across the adult lifespan
Authors: Bahrd Philip , Andersson Micael , Kalpouzos Grégoria , Salami Alireza , Nordin Kristin 
Published: March 2024

AbstractStructural decline of the hippocampus follows heterogeneous spatial patterns, and is an important determinant of episodic memory dysfunction in aging. However, evidence indicate that the anatomical landmark uncal apex, used to demarcate anterior and posterior hippocampal subregions, changes position as the hippocampus atrophies. This risks misclassifying gray matter into the incorrect subregion when using standard demarcation methods, potentially contributing to over– and underestimation of age-related anterior and posterior hippocampal volume loss, respectively. Yet, it remains unexplored whether inter-individual differences in uncal apex position itself predict episodic memory performance. Here, we manually identified the uncal apex in anatomical MRI data from a healthy adult-lifespan sample (n=180; 20-79 years), analyzed age differences in its position, and examined associations with word recall performance. Increasing age was linked to a more anteriorly located uncal apex (retracting ∼0.04 mm/year), and this anterior shift was linked to lower memory performance. Using the manually identified uncal apex for subregion segmentation in native space revealed a lower proportion of anterior hippocampal volume compared to segmentation in MNI space (y = –21), with effects of age on volumes differing between methods. Memory performance was not predicted by hippocampal subregion volumes, but the ratio of posterior to anterior volume was significantly linked to memory when accounting for tissue misclassification due to uncal apex variation. These results indicate that uncal apex position may provide an estimate of hippocampal integrity sensitive to inter-individual differences in memory, independent of limitations associated with different segmentation methods.
Changes in rest-activity rhythms in adolescents as they age: associations with brain changes and behavior in the ABCD study
Authors: Zhang Rui , Schwandt Melanie , Vines Leah , Volkow Nora D. 
Published: March 2024

ABSTRACTBackgroundAdolescents with disrupted rest-activity rhythms (RAR) including shorter sleep duration, later sleep timing and low physical activity levels have higher risk for mental and behavioral problems. However, it remains unclear whether the same associations can be observed for within-subject changes in RAR.MethodsOur longitudinal investigation on RAR used Fitbit data from the Adolescent Brain Cognitive Development (ABCD) Study at the 2-year (FL2: aged 10-13 years) and 4-year follow-up (FL4: aged 13-16 years). 963 youths had good-quality Fitbit data at both time points. In this study we examined changes in RAR from FL2 to FL4, their environmental and demographic contributors as well as brain and behavioral correlates.ResultsFrom FL2 to FL4, adolescents showed decreases in sleep duration and physical activity as well as delayed sleep timing (Cohen’s d .44-.75). The contributions of environmental and demographic factors to RAR changes were greatest to sleep timing (explained 10% variance) and least to sleep duration (explained 1% variance). Delays in sleep timing had stronger correlations with behavioral problems including greater impulsivity and poor academic performance than reductions in sleep duration or physical activity. Additionally, the various brain measures differed in their sensitivity to RAR changes. Reductions in sleep duration were associated with decreased brain functional connectivity between subcortical regions and sensorimotor and cingulo-opercular networks and with enhanced functional connectivity between sensorimotor, visual and auditory networks. Delays in sleep timing were mainly associated with grey matter changes in subcortical regions.ConclusionsThe current findings corroborate the role of sleep and physical activity in adolescent’s brain neurodevelopment and behavior problems. RAR might serve as biomarkers for monitoring behavioral problems in adolescents and to serve as potential therapeutic targets for mental disorders.
Transition from Acute to Chronic Low Back Pain in a Community-Based Cohort
Authors: Burke Colleen , Fillipo Rebecca , George Steven Z. , Goode Adam P. 
Published: March 2024

AbstractThe transition from acute to chronic low back pain (LBP) in community settings has yet to be well understood. We recruited n=131 participants with acute LBP from the community and followed them for 3 and 6-month outcomes. Acute LBP was defined by a duration of < 4 weeks, and participants must have reported a 30-day LBP-free period before the current acute episode. Chronic LBP was defined as pain most or every day over the past 3 months. Baseline psychological, social, and demographic factors were examined as predictors of transition to chronic LBP at 3 months or continuation of chronic LBP at 6 months. The transition from acute to chronic LBP at 3 months was 32.2% ( 38/118). At 6 months, 80.7% (25/111) of participants who transitioned at 3 months continued to have chronic LBP. At 6 months, participants who identified as Black or African American were more likely than white participants to transition to chronic LBP (RR=1.76, 95% CI 1.05, 2.95) and more likely to continue to have chronic LBP (RR=2.19, 95% CI 1.14, 4.21). Those classified at baseline by both LBP most or every day and intensity of at least 30/100 were more likely to transition to chronic LBP (RR=3.13, 95% CI 1.84, 5.30) and continue to have chronic LBP at 6 months (RR=2.58, 95% CI 1.43, 4.16). The STarT Back Screening Tool and the OSPRO-YF were associated with the transition to chronic LBP at 3 months and continuation at 6 months. Participants with higher PROMIS General Health and PROMIS Physical Health scores were less likely to transition to chronic LBP or continue to have chronic LBP at 6 months. These findings identify factors of acute LBP in the community that may predict the transition to chronic LBP. Larger studies are needed to confirm these findings and better understand the mechanisms driving the transition to chronic LBP.
Biglycan Promotes Glioma Cell Line Epithelial-Mesenchymal Transition and Temozolomide Resistance in Vitro
Authors: Han Xiangming , Zheng Yan 
Published: March 2024

AbstractGliomas are aggressive brain tumors associated with high mortality and treatment resistance. This study investigates the role of Biglycan (BGN) in glioma progression and its potential as a prognostic marker and therapeutic target. Analysis of data from The Cancer Genome Atlas (TCGA) reveals dysregulated BGN expression in low-grade gliomas (LGG) and glioblastoma (GBM) with positive correlation to tumor grade. High BGN expression is associated with poor prognosis. Functional analysis highlights BGN’s involvement in ECM regulation and EMT, driving glioma invasion and drug resistance. Silencing BGN reduces EMT-related gene expression and invasion capacity. Moreover, BGN expression is upregulated upon TMZ treatment, implicating its role in TMZ resistance. Targeting BGN may be a promising strategy to overcome glioma treatment resistance.
Assembly of mTORC3 involves binding of ETV7 to two separate sequences in the mTOR kinase domain
Authors: Zhan Jun , Harwood Frank , Have Sara Ten , Lamond Angus , Phillips Aaron H. , Kriwacki Richard W. , Halder Priyanka , Cardone Monica , Grosveld Gerard C. 
Published: March 2024

AbstractmTOR plays a crucial role in cell growth by controlling ribosome biogenesis, metabolism, autophagy, mRNA translation, and cytoskeleton organization. It is a serine/threonine kinase that is part of two distinct extensively described protein complexes, mTORC1 and mTORC2. We have identified a rapamycin resistant mTOR complex, called mTORC3, which is different from the canonical mTORC1 and mTORC2 complexes in that it does not contain the Raptor, Rictor, or mLST8 mTORC1 / 2 components. mTORC3 phosphorylates mTORC1 and mTORC2 targets and contains the ETS transcription factor ETV7, which binds to mTOR and is essential for mTORC3 assembly in the cytoplasm. Tumor cells that assemble mTORC3 have a proliferative advantage and become resistant to rapamycin, indicating that inhibiting mTORC3 may have a therapeutic impact on cancer. Here, we investigate which domains or amino acid residues of ETV7 and mTOR are involved in their mutual binding. We found that the mTOR FRB and LBE sequences in the kinase domain interact with the pointed (PNT) and ETS domains of ETV7, respectively. We also found that forced expression of the mTOR FRB domain in the mTORC3 expressing, rapamycin-resistant cell line Karpas-299 out competes mTOR for ETV7 binding and renders these cells rapamycin-sensitive in vivo. Our data provide useful information for the development of molecules that prevent the assembly of mTORC3, which may have therapeutic value in the treatment of mTORC3 positive cancer.
Understanding systems level metabolic adaptation resulting from osmotic stress
Authors: Tremblay Alexandre , Bekiaris Pavlos Stephanos , Klamt Steffen , Mahadevan Radhakrishnan 
Published: March 2024

AbstractAn organism’s survival hinges on maintaining the right thermodynamic conditions. Osmotic constraints limit the concentration range of metabolites, affecting essential cellular pathways. Despite extensive research on osmotic stress and growth, understanding remains limited, especially in hypo-osmotic environments. To delve into this, we developed a novel modeling approach that considers metabolic fluxes and metabolite concentrations along with thermodynamics. Our analysis ofE. coliadaptation reveals insights into growth rates, metabolic pathways, and thermodynamic bottlenecks during transitions between hypo- and hyper-osmotic conditions. Both experimental and computational findings show that cells prioritize pathways that have higher thermodynamic driving force, like the pentose phosphate or the Entner–Doudoroff pathway, under low osmolarity. This work offers a systematic and mechanistic explanation for reduced growth rates in hypo- and hyper-osmotic conditions. The developed framework is the first of its kind to incorporate genome wide constraints that consider both natural logarithm and actual metabolite concentrations.Abstract Figure