bluuebunny/crossref_metadata_2025_split huggingface dataset:
gMCSpy: Efficient and accurate computation of Genetic Minimal Cut Sets in Python
Authors: Rodriguez Carlos Javier , Barrena Naroa , Olaverri-Mendizabal Danel , Ochoa Idoia , Valcarcel Luis V. , Planes Francisco J. 
Published: February 2024

ABSTRACTMotivationThe identification of minimal genetic interventions that modulate metabolic processes constitutes one of the most relevant applications of genome-scale metabolic models (GEMs). The concept of Minimal Cut Sets (MCSs) and its extension at the gene level, genetic Minimal Cut Sets (gMCSs), have attracted increasing interest in the field of Systems Biology to address this task. Different computational tools have been developed to calculate MCSs and gMCSs using both commercial and open-source software.ResultsHere, we presentgMCSpy, an efficient Python package to calculate gMCSs in GEMs using both commercial and non-commercial optimization solvers. We show thatgMCSpysubstantially overperforms our previous computational tool GMCS, which exclusively relied on commercial software. Moreover, we comparedgMCSpywith recently published competing algorithms in the literature, finding significant improvements in both accuracy and computation time. All these advances makegMCSpyan attractive tool for researchers in the field of Systems Biology for different applications in health and biotechnology.Availability and ImplementationThe Python packagegMCSpy can be accessed at:https://github.com/PlanesLab/gMCSpyContactfplanes@tecnun.esSupplementary Information
A universal and effective variational method for destriping: application to light-sheet microscopy, FIB-SEM and remote sensing images
Authors: Rottmayer Niklas , Redenbach Claudia , Fahrbach Florian O. 
Published: February 2024

AbstractStripe artifacts are a common problem for various imaging techniques such as light-sheet fluorescence microscopy (LSFM), electron microscopy and remote sensing. These artifacts are characterized by their elongated shapes and compromise image quality and impede further analysis. To address the primary challenge of removing the stripe artifacts while preserving the object structures we present here an improved variational method for stripe removal with intuitive parametrization. Comparison against previously published methods on images from LSFM, FIB-SEM and remote sensing by visual inspection and quantitative metrics demonstrates the superior capability of the approach. Based on synthetic LSFM data obtained by simulation of physical light-propagation we enriched our analysis by the comparison of processed images to ground truth data and quantitatively confirmed that our method outperforms existing solutions in terms of improved removal of artifacts and retention of image structures. The open availability of our solution[1], the flexibility in handling variations in stripe orientation and thickness ensures its broad applicability across diverse imaging scenarios.
Mechanical loading modulates AMPK and mTOR signaling in myblasts
Authors: Zhou Xin , Zhu Shaocun , Li Junhong , Mateus Andre , Backman Ludvig J. 
Published: February 2024

AbstractSkeletal muscle adaptation to exercise involves various phenotypic changes that enhance metabolic and contractile functions. One key regulator of these adaptive responses is the activation of AMPK, influenced by exercise intensity. However, the mechanistic understanding of AMPK activation during exercise remains incomplete. In this study, we utilized an in vitro model to investigate the effects of mechanical loading on AMPK activation and its interplay with the mTOR signaling pathway. Proteomic analysis of myoblasts subjected to static loading (SL) revealed distinct quantitative protein alterations associated with RNA metabolism, with 10% SL inducing the most pronounced response compared to lower intensity of 5% and 2% as well as control. Additionally, 10% SL suppressed RNA and protein synthesis, while activating AMPK and inhibiting the mTOR pathway. Our RNA sequencing analysis further corroborated these findings, revealing numerous differentially regulated genes and signaling pathways influenced by both AMPK and mTOR. Further examination showed that SL induced changes in mitochondrial biogenesis and the ADP/ATP ratio. These findings provide novel insights into the cellular responses to mechanical loading and shed light on the intricate AMPK-mTOR regulatory network in myoblasts.
Optimization of liver graft function using poly-pharmacological drug cocktail CEPT in a simulated transplant model
Authors: Kharga Anil , Mojoudi Mohammadreza , Chen Huyun , Taggart McLean S. , Dinicu Antonia T. , Ozgur Ozge S. , Uygun Basak , Toner Mehmet , Tessier Shannon N. , Yeh Heidi , Markmann James F. , Longchamp Alban , Uygun Korkut 
Published: February 2024

AbstractBackgroundThe number of patients in need of a liver transplant far exceeds the supply of available organs. This imbalance could be dramatically reduced should the donor organ pool be expanded by rendering marginal cases transplantable rather than discarded. The poly-pharmacological drug cocktail CEPT (Chroman-1, Emricasan, Polyamine, and Trans-ISRIB (integrated stress inhibitor)) has been found to improve the in-vitro viability of human pluripotent stem cells (hPSCs) following cryopreservation. It is worth exploring CEPT’s ability to inhibit various apoptotic pathways and preserve cellular function for potentially mitigating warm ischemic stress of the anhepatic phase of graft implantation and promoting more rapid graft recovery following reperfusion with continuous treatment.MethodsRat livers without warm ischemia and CEPT supplementation are the healthy control: fresh (n=3) group. Room-temperature warm ischemia was used to replicate the anhepatic phase of graft implantation in the control (n=6) group and the experimental CEPT group (n=6) without and with CEPT supplementation, respectively. Transplantation was modeled by ex-vivo reperfusion at 37°C for six hours with William’s E-based hepatocyte culture media and with CEPT supplementation in the CEPT group.ResultsLivers treated with CEPT during warm ischemia and subsequent reperfusion have improved hepatocellular function as indicated by increased oxygen O2utilization, stable pH, and improved cholangiocyte function indicated by the increased hourly rate of bile production. Furthermore, resistance, an endothelial injury marker, and caspase 3/7, an apoptotic marker, were lower.ConclusionTo improve the utilization of available donor livers, different stages of the organ transplantation process can be optimized. The anhepatic phase, which includes the period from the removal of the native liver from the recipient to the reperfusion of the donor’s graft liver through the portal vein during graft implantation, can be targeted using CEPT for mitigating warm ischemia-induced injury that occurs during vascular anastomosis.(S1 Fig: Graphical abstract)
Spatial transcriptomics of healthy and fibrotic human liver at single-cell resolution
Authors: Watson Brianna , Paul Biplab , Amir-Zilberstein Liat , Segerstolpe Asa , Rahman Raza Ur , Shih Angela , Deguine Jacques , Xavier Ramnik J. , Moffitt Jeffrey R. , Mullen Alan C. 
Published: February 2024

AbstractSingle-cell RNA sequencing (scRNA-seq) has advanced our understanding of cell types and their heterogeneity within the human liver, but the spatial organization at single-cell resolution has not yet been described. Here we apply multiplexed error robust fluorescent in situ hybridization (MERFISH) to map the zonal distribution of hepatocytes, resolve subsets of macrophage and mesenchymal populations, and investigate the relationship between hepatocyte ploidy and gene expression within the healthy human liver. We next integrated spatial information from MERFISH with the more complete transcriptome produced by single-nucleus RNA sequencing (snRNA-seq), revealing zonally enriched receptor-ligand interactions. Finally, analysis of fibrotic liver samples identified two hepatocyte populations that are not restricted to zonal distribution and expand with injury. Together these spatial maps of the healthy and fibrotic liver provide a deeper understanding of the cellular and spatial remodeling that drives disease which, in turn, could provide new avenues for intervention and further study.
Mutualism provides the basis for biodiversity in eco-evolutionary community assembly
Authors: Araujo Gui , Lurgi Miguel 
Published: February 2024

AbstractUnveiling the ecological and evolutionary mechanisms underpinning the assembly of stable and complex ecosystems is a main focus of community ecology. Ecological theory predicts the necessity of structural constraints on the network of species interactions to allow for growth of complexity in assembling multispecies communities. A promising research avenue is the search for an understanding of how the coexistence of diverse species interaction types could influence the development of complexity and how an ideal composition could arise in nature. We propose an ecological model with mixed interaction types incorporating evolutionary assembly by speciation. This framework allows to investigate the eco-evolutionary assembly on complex species interaction networks with multiple interaction types and its consequences for ecosystem stability. Our results show that highly mutualistic communities are conducive of complexity and promote the emergence of consumer-resource interactions. Furthermore, we show that an evolutionary process is required to produce such condition. Moreover, this evolutionary assembly generates a diversity of outcomes and promotes two distinct types of complexity depending on speciation constraints. Assembled communities are thus either larger (more species) or more connected, in agreement with patterns previously observed in microbial communities. Our results produce invaluable theoretical insight into the mechanisms behind the emergence of ecological complexity and into the roles of mutualism and speciation on community formation.
Predicting Depression in Canadians with or at Risk of Diabetes: A Cross-Sectional Machine Learning Analysis
Authors: Samsel Konrad , Noaeen Mohammad , Tiwana Amrit , Ali Sarra , Guergachi Aziz , Keshavjee Karim , Shakeri Zahra 
Published: February 2024

AbstractDepression often goes unrecognized in individuals at risk or living with diabetes, presenting considerable challenges for primary care clinicians. Although large language models and other foundation model approaches are drawing significant attention, we systematically compared six established machine learning algorithms-Logistic Regression, Random Forest, AdaBoost, XGBoost, Naive Bayes, and Artificial Neural Networks-chosen for their reliability, interpretability, and feasibility in everyday clinical settings. By benchmarking their performance under real-world constraints, we identified key factors linked to depression risk in diabetes care, including patient sex, age, osteoarthritis, hemoglobin A1c, and body mass index. Although incomplete demographic information and potential label bias limited predictive power, our results demonstrate that a diverse set of clinical features might help pinpoint high-risk patients. They also indicate a need for longitudinal follow-up and richer clinical data to enhance model accuracy. As a practical benchmark for both clinicians and data scientists, this work suggests that machine learning–based risk stratification can improve early detection of depression and inform targeted interventions in diabetic populations.
Predictive processing in biological motion perception: Evidence from human behavior
Authors: Elmas Hüseyin O. , Er Sena , Rezaki Ada D. , Izgi Aysesu , Urgen Buse M. , Boyaci Huseyin , Urgen Burcu A. 
Published: February 2024

AbstractBiological motion perception plays a crucial role in understanding the actions of other animals, facilitating effective social interactions. While foundation of biological motion perception is rooted in bottom-up processes, as evidenced by point-light display studies, real-world complexities necessitate the involvement of top-down processes, such as attention and expectation. This study investigates the impact of expectations on biological motion perception using a cued individuation task with point-light display stimuli. We conducted three experiments, each providing advance information about distinct aspects of the subsequent biological motion stimuli – specifically information about action, emotion, and gender. Our results revealed a pattern in the action experiment, where participants demonstrated significantly slower response times for incongruent trials than congruent ones, but only under the 75% cue validity condition. This effect was notably absent in the emotion and gender experiments. Our exploration underscores the multi-faceted nature of biological motion perception, highlighting that while the brain adeptly harnesses prior cues to anticipate and interpret stimuli, the nature and reliability of these cues play a pivotal role on their effects. Specifically, action-related information stands out as an important modulator, possibly due to its evolutionary significance and unique neural processing pathway. These findings not only agree with the principles of predictive processing but also pave the way for future research, emphasizing the need to utilize naturalistic, complex stimuli together with neuroimaging methods to create more comprehensive models of biological motion perception.
Non-cell autonomous OTX2 in the piriform cortex regulates parvalbumin cell maturation states and olfactory-driven behavior
Authors: Gibel-Russo Rachel , Di Nardo Ariel A. 
Published: February 2024

AbstractThe timing of critical periods of juvenile brain plasticity is driven by the maturation of parvalbumin interneurons in the neocortex, a process regulated in part by non-cell autonomous activity of the OTX2 homeoprotein transcription factor. However, the involvement of critical periods in olfactory paleocortex maturation is unknown. Here, we find that the adult mouse piriform cortex parvalbumin interneurons display particularly low molecular maturation that increases in aged animals. Expression analysis of a large panel of genes reveals that an acute increase in piriform cortex OTX2 levels in young adult mice increasesPvalbexpression as well asAdamts9expression, resulting in increased extracellular perineuronal net levels, while reducing OTX2 transfer decreasesPvalbexpression and increasesMmp9expression, resulting in decreased perineuronal net levels. Reduction in OTX2 also stimulates odor-driven cFos activity in piriform cortex parvalbumin cells and disrupts olfactory-driven behavior. Our findings suggest plasticity in piriform cortex involves OTX2 activity on parvalbumin cells and lacks strictly defined critical periods.
SSRI Use During Acute COVID-19 Infection Associated with Lower Risk of Long COVID Among Patients with Depression
Authors: Butzin-Dozier Zachary , Ji Yunwen , Deshpande Sarang , Hurwitz Eric , Coyle Jeremy , Shi Junming (Seraphina) , Mertens Andrew , van der Laan Mark J. , Colford John M. , Patel Rena C. , Hubbard Alan E. ,   the National COVID Cohort Collaborative (N3C) Consortium
Published: February 2024

ABSTRACTBackgroundLong COVID, also known as post-acute sequelae of COVID-19 (PASC), is a poorly understood condition with symptoms across a range of biological domains that often have debilitating consequences. Some have recently suggested that lingering SARS-CoV-2 virus in the gut may impede serotonin production and that low serotonin may drive many Long COVID symptoms across a range of biological systems. Therefore, selective serotonin reuptake inhibitors (SSRIs), which increase synaptic serotonin availability, may prevent or treat Long COVID. SSRIs are commonly prescribed for depression, therefore restricting a study sample to only include patients with depression can reduce the concern of confounding by indication.MethodsIn an observational sample of electronic health records from patients in the National COVID Cohort Collaborative (N3C) with a COVID-19 diagnosis between September 1, 2021, and December 1, 2022, and pre-existing major depressive disorder, the leading indication for SSRI use, we evaluated the relationship between SSRI use at the time of COVID-19 infection and subsequent 12-month risk of Long COVID (defined by ICD-10 code U09.9). We defined SSRI use as a prescription for SSRI medication beginning at least 30 days before COVID-19 infection and not ending before COVID-19 infection. To minimize bias, we estimated the causal associations of interest using a nonparametric approach, targeted maximum likelihood estimation, to aggressively adjust for high-dimensional covariates.ResultsWe analyzed a sample (n= 506,903) of patients with a diagnosis of major depressive disorder before COVID-19 diagnosis, where 124,928 (25%) were using an SSRI. We found that SSRI users had a significantly lower risk of Long COVID compared to nonusers (adjusted causal relative risk 0.90, 95% CI (0.86, 0.94)).ConclusionThese findings suggest that SSRI use during COVID-19 infection may be protective against Long COVID, supporting the hypothesis that serotonin may be a key mechanistic biomarker of Long COVID.
Evaluating Cochlear Implant Stimulation Strategies Through Wide-field Calcium Imaging of the Auditory Cortex
Authors: Castellaro Bruno , Yip Tony Ka Wing , Peng Fei , Muhammad Zeeshan , Fang Shiyi , Nelken Israel , Schnupp Jan 
Published: February 2024

AbstractCochlear Implants (CI) are an effective neuroprosthesis for humans with profound hearing loss, enabling deaf adults to have phone calls without lipreading and babies to have successful language development. However, CIs have significant limitations in complex hearing situations, motivating the need for further research, including studies in animal models. Here, we demonstrate the usefulness of wide field Ca++ imaging in assessing different CI stimulation strategies. One major challenge in electrophysiology in CI animals lies in excluding the CI electric artifacts from the recording, since they are orders of magnitude larger than the amplitude of action potentials. Also, electrophysiology can rarely sample large areas of neuropil at high spatial resolution. To circumvent these problems, we have set up an imaging system allowing us to monitor neural activity in the auditory cortex (AC) of CI supplied rats using the Ca++ sensitive dye OGB. Here we describe an initial experiment with this setup, in which we recorded cortical responses to 4 different stimulation patterns which were delivered across 3 CI channels to the contralateral ear. We then investigated two parameters that have been shown to affect intelligibility in CI users: pulse rate and relative pulse timing across CI channels. While pulse rate had only a very modest effect on the discriminability of the neural responses, the stimulation mode had a major effect, with simultaneous pulse timing, perhaps surprisingly, allowing much better pattern discrimination than interleaved sampling. The result suggests that allowing collisions of pulses on neighboring channels may not always be detrimental, at least if partial overlaps of pulses, in which anodic and cathodic pulse phases might cancel, are avoided.
The Effect on Speech-in-Noise Perception of Real Faces and Synthetic Faces Generated with either Deep Neural Networks or the Facial Action Coding System
Authors: Yu Yingjia , Lado Anastasia , Zhang Yue , Magnotti John F. , Beauchamp Michael S. 
Published: February 2024

AbstractThe prevalence of synthetic talking faces in both commercial and academic environments is increasing as the technology to generate them grows more powerful and available. While it has long been known that seeing the face of the talker improves human perception of speech-in-noise, recent studies have shown that synthetic talking faces generated by deep neural networks (DNNs) are also able to improve human perception of speech-in-noise. However, in previous studies the benefit provided by DNN synthetic faces was only about half that of real human talkers. We sought to determine whether synthetic talking faces generated by an alternative method would provide a greater perceptual benefit. The facial action coding system (FACS) is a comprehensive system for measuring visually discernible facial movements. Because the action units that comprise FACS are linked to specific muscle groups, synthetic talking faces generated by FACS might have greater verisimilitude than DNN synthetic faces which do not reference an explicit model of the facial musculature. We tested the ability of human observers to identity speech-in-noise accompanied by a blank screen; the real face of the talker; and synthetic talking face generated either by DNN or FACS. We replicated previous findings of a large benefit for seeing the face of a real talker for speech-in-noise perception and a smaller benefit for DNN synthetic faces. FACS faces also improved perception, but only to the same degree as DNN faces. Analysis at the phoneme level showed that the performance of DNN and FACS faces was particularly poor for phonemes that involve interactions between the teeth and lips, such as /f/, /v/, and /th/. Inspection of single video frames revealed that the characteristic visual features for these phonemes were weak or absent in synthetic faces. Modeling the realvs.synthetic difference showed that increasing the realism of a few phonemes could substantially increase the overall perceptual benefit of synthetic faces, providing a roadmap for improving communication in this rapidly developing domain.
Ramping Dynamics in the Frontal Cortex Unfold Over Multiple Timescales During Motor Planning
Authors: Affan R.O. , Bright I.M. , Pemberton L.N. , Cruzado N.A. , Scott B.B. , Howard M.W. 
Published: February 2024

AbstractPlans are formulated and refined over the period leading to their execution, ensuring that the appropriate behavior is enacted at just the right time. While existing evidence suggests that memory circuits convey the passage of time through diverse neuronal responses, it remains unclear whether the neural circuits involved in planning behavior exhibit analogous temporal dynamics. Using publicly available data, we analyzed how activity in the frontal motor cortex evolves during motor planning. Individual neurons exhibited diverse ramping activity throughout a delay interval that preceded a planned movement. The collective activity of these neurons was useful for making temporal predictions that became increasingly precise as the movement time approached. This temporal diversity gave rise to a spectrum of encoding patterns, ranging from stable to dynamic representations of the upcoming movement. Our results indicate that neural activity unfolds over multiple timescales during motor planning, suggesting a shared mechanism in the brain for processing temporal information related to both past memories and future plans.