bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cortical lipids containing choline mediate cannabinoid-induced cognitive improvement
Authors: Moreno-Rodríguez Marta , Martínez-Gardeazabal Jonatan , de Tena Iker Bengoetxea , Llorente-Ovejero Alberto , Lombardero Laura , de San Román Estibaliz González , Giménez-Llort Lydia , Manuel Iván , Rodríguez-Puertas Rafael 
Published: March 2024

ABSTRACTRecent research connecting choline-containing lipids to basal forebrain cholinergic neurons (BFCN) degeneration in neuropathological states highlights a challenge for balancing lipid integrity with optimal acetylcholine (ACh) levels. Warranting an adequate choline source to maintain ACh levels in this pathway is crucial for preserving memory. The endocannabinoid (eCB) system plays a role in modulating learning and memory processes controlled by cholinergic neurotransmission. Consequently, we propose that activation of this system is neuroprotective against cholinergic degeneration. In the present study, we investigated the neuroprotective effect of a subchronic treatment with the CB1cannabinoid agonist, WIN55,212-2, using bothex vivoandin vivo192IgG-Saporin models of specific cholinergic damage. Degeneration of baso-cortical cholinergic pathways induced memory deficits and a downregulation of saturated and mono-unsaturated lysophosphatidylcholines (LPC) cortical levels. WIN55,212-2 not only restored memory deficits but also increased cortical ACh levels and modified cortical choline-containing lipids such as sphingomyelins (SM) and LPCs, which are essential for correct memory functioning, in lesioned animals. Given these results, we propose that WIN55,212-2 generates an alternative choline source through the breakdown of SMs, which is enough to increase cortical ACh levels and LPCs. These findings suggest that modification of choline-containing lipids by the activation of CB1receptors is a promising therapy for dementia associated with cholinergic dysfunction, such as in Alzheimer’s disease (AD).
Comparative transcriptomic and lipidomic analysis of fatty acid accumulation in threeCamellia oleiferavarieties during maturation
Authors: Yang Dayu , Wang Rui , Lai Hanggui , Chen Yongzhong , He Yimin , Xun Chengfeng , Zhang Ying , He Zhilong 
Published: March 2024

AbstractCamellia oleiferastands out as one of China’s leading woody oil crops, famed for its tea oil, which boasts a high content of unsaturated fatty acids. Often referred to as "liquid gold" or "Oriental olive oil," this oil is prized for its nutritional benefits and culinary versatility, marking Camellia oleifera as a valuable agricultural and economic resource. This study provides an integrated investigation of the transcriptome and lipidome within seeds at the maturation stage across threeC. oleiferavarieties, revealing a significant relationship between fatty acid production and genes involved in lipid synthesis. Through transcriptomic analysis, 26,344 genes with varied expression were found. Functional enrichment analysis highlighted that pathways related to starch and sucrose metabolism, plant hormone signal transduction, and lipid accumulation were highly enriched among the differentially expressed genes. Additionally, expression variations ofSADandFADsamong different varieties were explored. The analysis suggests that increased expression of genes such asFAD3,FAD7, andFAD8during the maturation stage may enhance the proportion of linolenic acid while reducing oleic acid content. This alteration could potentially stimulate fatty acid synthesis through a feedback regulation mechanism, thereby enhancing seed oil content. These findings provide a novel perspective on the feedback regulation mechanisms underlying lipid biosynthesis inC. oleiferaseeds, offering significant insights to boost oil yield and improve tea oil quality.
Estimating evolutionary and demographic parameters via ARG-derived IBD
Authors: Huang Zhendong , Kelleher Jerome , Chan Yao-ban , Balding David J. 
Published: March 2024

AbstractInference of demographic and evolutionary parameters from a sample of genome sequences often proceeds by first inferring identical-by-descent (IBD) genome segments. By exploiting efficient data encoding based on the ancestral recombination graph (ARG), we obtain three major advantages over current approaches: (i) no need to impose a length threshold on IBD segments, (ii) IBD can be defined without the hard-to-verify requirement of no recombination, and (iii) computation time can be reduced with little loss of statistical efficiency using only the IBD segments from a set of sequence pairs that scales linearly with sample size. We first demonstrate powerful inferences when true IBD information is available from simulated data. For IBD inferred from real data, we propose an approximate Bayesian computation inference algorithm and use it to show that poorly-inferred short IBD segments can improve estimation precision. We show estimation precision similar to a previously-published estimator despite a 4 000-fold reduction in data used for inference. Computational cost limits model complexity in our approach, but we are able to incorporate unknown nuisance parameters and model misspecification, still finding improved parameter inference.Author summarySamples of genome sequences can be informative about the history of the population from which they were drawn, and about mutation and other processes that led to the observed sequences. However, obtaining reliable inferences is challenging, because of the complexity of the underlying processes and the large amounts of sequence data that are often now available. A common approach to simplifying the data is to use only genome segments that are very similar between two sequences, called identical-by-descent (IBD). The longer the IBD segment the more informative about recent shared ancestry, and current approaches restrict attention to IBD segments above a length threshold. We instead are able to use IBD segments of any length, allowing us to extract much more information from the sequence data. To reduce the computation burden we identify subsets of the available sequence pairs that lead to little information loss. Our approach exploits recent advances in inferring aspects of the ancestral recombination graph (ARG) underlying the sample of sequences. Computational cost still limits the size and complexity of problems our method can handle, but where feasible we obtain dramatic improvements in the power of inferences.
SPARTA: Interpretable functional classification of microbiomes and detection of hidden cumulative effects
Authors: Ruiz Baptiste , Belcour Arnaud , Blanquart Samuel , Buffet-Bataillon Sylvie , Hüerou-Luron Isabelle Le , Siegel Anne , Cunff Yann Le 
Published: March 2024

AbstractThe composition of the gut microbiota is a known factor in various diseases, and has proven to be a strong basis for automatic classification of disease state. A need for a better understanding of this community on the functional scale has since been voiced, as it would enhance these approaches’ biological interpretability. In this paper, we have developed a computational pipeline for integrating the functional annotation of the gut microbiota to an automatic classification process, and facilitating downstream interpretation of its results. The process takes as input taxonomic composition data (such as tables of Operational Taxonomic Unit (OTU) or Amplicon Sequence Variant (ASV) abundances), and links each component to its functional annotations through interrogation of the UniProt database. A functional profile of the gut microbiota is built from this basis. Both profiles, microbial and functional, are used to train Random Forest classifiers to discern unhealthy from control samples. An automatic variable selection is then performed on the basis of variable importance, and the method can be iterated until classification performances diminish. This process shows that the translation of the microbiota into functional profiles gives comparable, albeit slightly inferior performances when compared to microbial profiles. Through repetition, it also outputs a robust subset of discriminant variables. These selections were shown to be more reliable than those obtained by a state of the art method, and its contents were validated through a manual bibliographic research. The interconnections between selected OTUs and functional annotations were also analyzed, and revealed that important annotations emerge from the cumulated influence of non-selected OTUs.
Prioritizing the Valorization Strategies of an Invasive Fern (Azolla) in a Wetland
Authors: Nikkhah Farima , Ramezanian Mohammad Rahim , Rosentrater Kurt A. 
Published: March 2024

AbstractWetlands play a vital role as one of the most important natural habitats on our planet. However, the survival of these natural wetlands is threatened by various factors. The arrival of invasive and non-native aquatic ferns is one of these challenges. In this regard, Azolla filiculoides has become a severe problem for the Anzali wetland. Azolla, as an aquatic fern, has created numerous issues in aquatic habitats and paddy fields in recent decades. However, the valorization of Azolla can contribute to the establishment of a collection system for this invasive fern, which can consequently reduce the negative impact of this fern on the wetland, and it can serve as a free and available source of biomass. In this respect, a fuzzy multi-criteria decision-making approach was used to rank the valorization strategies of this invasive fern. Initially, through an in-depth literature review and expert opinions, four criteria were designated as indicators for research evaluation: 1) technical, 2) economic, 3) social, and 4) environmental. Six management options for Azolla were considered: 1) no collection, 2) collection and landfilling, 3) direct use as livestock and poultry feed, 4) composting, 5) biogas generation, and 6) biodiesel generation. The results revealed that “biodiesel generation,” “biogas generation,” and “composting” were ranked as the most effective management strategies for Azolla in the investigated wetland. This study suggests that bioenergy generation and compost production from Azolla are promising strategies towards mitigating the negative impact of this fern on the Anzali wetland.
Enhancing viscosity control in antibody formulations: A framework for the biophysical screening of mutations targeting solvent-accessible hydrophobic and electrostatic patches
Authors: Armstrong Georgina B , Shah Vidhi , Sanches Paula , Patel Mitul , Casey Ricky , Jamieson Craig J , Burley Glenn A , Lewis William J , Rattray Zahra 
Published: March 2024

AbstractThe formulation of high-concentration monoclonal antibody (mAb) solutions in low dose volumes for autoinjector devices poses challenges in manufacturability and patient administration due to elevated solution viscosity. In the current study, we present a systematic experimental framework for the computational screening of molecular descriptors to guide the design of mutants with modified viscosity profiles accompanied by experimental evaluation. Our observations using a model anti-IL8 antibody reveal that the reduction in viscosity is influenced by the location of hydrophobic interactions, while targeting positively charged patches in mAb1 leads to the most significant viscosity increase compared to the wild-type mAb. We conclude that existingin silicopredictions of physicochemical properties exhibit poor correlation with experimental parameters for antibodies with suboptimal developability characteristics, emphasizing the necessity for comprehensive case-by-case evaluations of mAbs. This approach aids in the rational design of mAbs with tailored solution viscosities, ensuring improved manufacturability and patient convenience in self-administration scenarios.
Sustained neurotrophic factor cotreatment enhances donor and host retinal ganglion cell survival in mice
Authors: Soucy Jonathan R. , Kriukov Emil , Oswald Julia , Phay Monichan , Masland John , Pernstich Christian , Baranov Petr 
Published: March 2024

AbstractRetinal ganglion cells (RGCs) lack regenerative capacity in mammals, and their degeneration in glaucoma leads to irreversible blindness. The transplantation of stem cell-derived RGCs lacks clinically relevant effect due to insufficient survival and integration of donor cells. We hypothesize that the retinal microenvironment plays a critical role in this process, and we can engineer a more acceptable setting for transplantation. Since the adult mammalian retina does not have regenerative capacity, we turned to the developing human retina to reconstruct cell-cell interactions at a single-cell level. We established a human fetal retina atlas by integrating currently available single-cell RNA sequencing datasets of human fetal retinas into a unified resource. We align RGC transcriptomes in pseudotime to map RGC developmental fate trajectories against the broader timeline of retinal development. Through this analysis, we identified brain-derived neurotrophic factor (BDNF) and glial-derived neurotrophic factor (GDNF) as key factors in RGC survival, highly expressed during fetal development but significantly reduced in adulthood despite the persistence of their receptors. To demonstrate the practical application of these findings, we show that using a slow-release formulation of BDNF and GDNF enhances RGC differentiation, survival, and function in vitro and improves RGC transplantation outcomes in a mouse model. BNDF/GDNF co-treatment not only increased survival and coverage of donor RGCs within the retina but also showed neuroprotective effects on host RGCs, preserving retinal function in a model of optic neuropathy. Altogether, our findings suggest that manipulating the retinal microenvironment with slow-release neurotrophic factors holds promise in regenerative medicine for treating glaucoma and other optic neuropathies. This approach not only improves donor cell survival and integration but also provides a neuroprotective benefit to host cells, indicating a significant advancement for glaucoma therapies.
Second language learning in older adults modulates Stroop task performance and brain activation
Authors: Schultz DH , Gansemer A , Allgood K , Gentz M , Secilmis L , Deldar Z , Savage CR , Ghazi Saidi L 
Published: March 2024

AbstractNumerous studies have highlighted cognitive benefits in lifelong bilinguals during aging, manifesting as superior performance on cognitive tasks compared to monolingual counterparts. Yet, the cognitive impacts of acquiring a new language in older adulthood remain unexplored. In this study, we assessed both behavioral and fMRI responses during a Stroop task in older adults, pre- and post language-learning intervention.A group of 41 participants (age:60-80) from a predominantly monolingual environment underwent a four-month online language course, selecting a new language of their preference. This intervention mandated engagement for 90 minutes a day, five days a week. Daily tracking was employed to monitor progress and retention. All participants completed a color-word Stroop task inside the scanner before and after the language instruction period.We found that performance on the Stroop task, as evidenced by accuracy and reaction time, improved following the language learning intervention. With the neuroimaging data, we observed significant differences in activity between congruent and incongruent trials in key regions in the prefrontal and parietal cortex. These results are consistent with previous reports using the Stroop paradigm. We also found that the amount of time participants spent with the language learning program was related to differential activity in these brain areas. Specifically, we found that people who spent more time with the language learning program showed a greater increase in differential activity between congruent and incongruent trials after the intervention relative to before.Future research is needed to determine the optimal parameters for language learning as an effective cognitive intervention for aging populations. We propose that with sufficient engagement, language learning can enhance specific domains of cognition such as the executive functions. These results extend the understanding of cognitive reserve and its augmentation through targeted interventions, setting a foundation for future investigations.
Brain-Penetrant NF-κB and NLRP3 Targeting Nanoligomers are Therapeutic in Amyotrophic Lateral Sclerosis (ALS) and Alzheimer’s Disease (AD) Human Organoid and Mouse Models
Authors: Sharma Sadhana , Wahl Devin , Risen Sydney , Gilberto Vincenzo S. , Chatterjee Anushree , Moreno Julie A. , LaRocca Thomas J. , Nagpal Prashant 
Published: March 2024

ABSTRACTMillions of people suffer worldwide from neurodegenerative diseases ranging from rapidly progressing and fatal motor neuron diseases like Amyotrophic Lateral Sclerosis (ALS) to more chronic illnesses such as frontotemporal dementia (FTD) and Alzheimer’s disease (AD). A growing number of studies have implicated neuroinflammation as a key and causative phenomenon and an important target for novel therapeutics for these diseases. Neuroinflammation is characterized by reactive glial cells that produce pro-inflammatory neurotoxic cytokines. Our previous studies have shown a brain-penetrant Nanoligomer cocktail (NI112) inhibiting the neuroinflammation mediators nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and NOD-like receptor family, pyrin domain containing 3 (NLRP3) is a safe, targeted, and effective neurotherapeutic drug. Here, we show that a four-week NI112 treatment is therapeutic using: 1) an ALS-FTD 3D human motor neuron organoid model of tar DNA binding protein 43 (TDP-43, a key contributor to ALS pathology) overexpression (knock-in); 2) an AD model of APOE4/APOE4 (AD risk allele) double mutation in human neurons comprising a 3D human prefrontal cortex (PFC) organoid; and 3) multiplein vivo(mouse models) of the same/related conditions. In 3D organoids made from healthy motor neurons (HMN negative control) and TDP-43 overexpressing (or ALS organoids), we monitored the mean firing rate using calcium signaling as a functional output, while measuring TDP-43 and other key neurodegeneration biomarkers. After 4 weeks, we observed a massive improvement in the mean firing rate of NI112-treated ALS organoids compared to untreated ALS organoids, which was more comparable to healthy HMN organoids. Similarly, we found a significant decrease in neurodegeneration markers like amyloid beta 42 (Aβ42) in NI112-treated AD organoids compared to untreated AD organoids (Aβ42 comparable to healthy PFC organoids). In the mouse ALS (SOD1-G93A) model, we observed behavioral improvements and restoration of motor function (e.g., grip strength) in NI112-treated mice, and in mouse AD model mice (radiation-induced accelerated neuropathology in APP/PS1, and rTg4510 phospho-tau), we observed improved cognition. In both models, we also found an accompanying reduction in neuroinflammation and reduced neuropathology. These results show the promise for further testing and development of neuroinflammation-targeting Nanoligomers to benefit patients suffering from debilitating neurodegenerative diseases like ALS, FTD, and AD.
Demographic history and the efficacy of selection in the globally invasive mosquitoAedes aegypti
Authors: Kent Tyler V. , Schrider Daniel R. , Matute Daniel R. 
Published: March 2024

AbstractAedes aegyptiis the main vector species of yellow fever, dengue, zika and chikungunya. The species is originally from Africa but has experienced a spectacular expansion in its geographic range to a large swath of the world, the demographic effects of which have remained largely understudied. In this report, we examine whole-genome sequences from 6 countries in Africa, North America, and South America to investigate the demographic history of the spread ofAe. aegyptiinto the Americas its impact on genomic diversity. In the Americas, we observe patterns of strong population structure consistent with relatively low (but probably non-zero) levels of gene flow but occasional long-range dispersal and/or recolonization events. We also find evidence that the colonization of the Americas has resulted in introduction bottlenecks. However, while each sampling location shows evidence of a past population contraction and subsequent recovery, our results suggest that the bottlenecks in America have led to a reduction in genetic diversity of only ∼35% relative to African populations, and the American samples have retained high levels of genetic diversity (expected heterozygosity of ∼0.02 at synonymous sites) and have experienced only a minor reduction in the efficacy of selection. These results evoke the image of an invasive species that has expanded its range with remarkable genetic resilience in the face of strong eradication pressure.
Cell Marker Accordion: interpretable single-cell and spatial omics annotation in health and disease
Authors: Busarello Emma , Biancon Giulia , Cimignolo Ilaria , Lauria Fabio , Ibnat Zuhairia , Ramirez Christian , Tomè Gabriele , Ciuffreda Marianna , Bucciarelli Giorgia , Pilli Alessandro , Marino Stefano Maria , Bontempi Vittorio , Aass Kristin R. , VanOudenhove Jennifer , Mione Maria Caterina , Standal Therese , Macchi Paolo , Viero Gabriella , Halene Stephanie , Tebaldi Toma 
Published: March 2024

AbstractSingle-cell technologies offer a unique opportunity to explore cellular heterogeneity in health and disease. However, reliable identification of cell types and states represents a bottleneck. Available databases and analysis tools employ dissimilar markers, leading to inconsistent annotations and poor interpretability. Furthermore, current tools focus mostly on physiological cell types, limiting their applicability to disease.We developed the Cell Marker Accordion, a user-friendly platform providing automatic annotation and unmatched biological interpretation of single-cell populations, based on consistency weighted markers. We validated our approach on multiple single-cell and spatial datasets from different human and murine tissues, improving annotation accuracy in all cases. Moreover, we show that the Cell Marker Accordion can identify disease-critical cells and pathological processes, extracting potential biomarkers in a wide variety of disease contexts.The breadth of these applications elevates the Cell Marker Accordion as a fast, flexible, faithful and standardized tool to annotate and interpret single-cell and spatial populations in studying physiology and disease.