bluuebunny/crossref_metadata_2025_split huggingface dataset:
NOVEL PS-OME MIRNA130B-3P REDUCES INFLAMMATION AND INJURY AND IMPROVES SURVIVAL AFTER RENAL ISCHEMIA-REPERFUSION INJURY
Authors: Vazquez Gustavo , Sfakianos Maria , Coppa Gene , Jacob Asha , Wang Ping 
Published: August 2023

ABSTRACT

Introduction: Acute kidney injury (AKI) is a prevalent medical disorder characterized by a sudden decline in kidney function, often because of ischemia/reperfusion (I/R) events. It is associated with significant chronic complications, and currently available therapies are limited to supportive measures. Extracellular cold-inducible RNA-binding protein (eCIRP) has been identified as a mediator that potentiates inflammation after I/R injury. However, it has been discovered that miRNA 130b-3p acts as an endogenous inhibitor of eCIRP. To address the inherent instability of miRNA in vivo, a chemically modified miRNA mimic called PS-OME miR130 was developed. We hypothesize that administration of PS-OME miR130 after renal I/R can lead to reduced inflammation and injury in a murine model of AKI. Methods: C57BL/6 male mice underwent renal I/R by clamping of bilateral renal hilum for 30 min or sham operation. Immediately after closure, mice were intravenously administered vehicle (phosphate-buffered saline) or PS-OME miR130 at a dose of 12.5 nmol/mouse. Blood and kidneys were collected after 24 h for further analysis. Separately, mice underwent renal I/R and administered vehicle or treatment and, survival was monitored for 10 days. Results: After renal I/R, mice receiving vehicle showed a significant increase in serum markers of kidney injury and inflammation including blood urea nitrogen, NGAL, KIM-1, and IL-6. After treatment with PS-OME miR130, these markers were significantly decreased. Kidney tissue mRNA expression for injury and inflammation markers including NGAL, KIM-1, KC, and MIP-2 were increased after renal I/R; however, these markers showed a significant reduction with PS-OME miR130 treatment. Histologically, treatment with PS-OME miR130 showed a significant decrease in neutrophil infiltration and injury severity score, and decreased apoptosis. In the 10-day survival study, mice in the treatment group showed a significant reduction in mortality as compared with vehicle group. Conclusion: In a murine renal I/R model, the administration of PS-OME miR130, a direct eCIRP antagonistic miRNA mimic, resulted in the reduction of kidney inflammation and injury, and improved survival. PS-OME miR130 holds promise to be developed as novel therapeutic for AKI as an adjunct to the standard of care.
Overexpressing the IPT gene improves drought tolerance and nutritional value of tropical maize (Zea maysL.)
Authors: Muruo Rose Mweru , Nchore Shem B. , Oduor Richard O. , Ngugi Mathew Piero 
Published: August 2023

AbstractDrought stress poses a significant threat to crop productivity, making the development of drought-tolerant crops a priority. The impact of drought on grain yield loss varies significantly, ranging from 10% to 76%, depending on the specific stage of occurrence and the severity of the drought. In this study, we investigated the effects of introducing the pSARK::IPT transgene on the drought tolerance and nutritional composition of successive generations of tropical maize. Towards this goal, we screened different generations of maize plants by genotyping PCR, exposed them to long term drought stress and analysed several drought stress markers and nutritional profiles of the plants. Our results demonstrated that the pSARK::IPT transgene was present in 4 successive generations of maize plants. Under drought conditions, transgenic maize exhibited higher relative water content, and delayed senescence compared to wild-type plants. Additionally, transgenic plants showed increased levels of total chlorophyll, chlorophyll a, and chlorophyll b, indicating improved photosynthetic activity under water deficit. Our study also showed that IPT-transgenic plants produced substantially higher yields and demonstrated enhanced nutritional value compared to wildtype plants when grown under well-watered conditions. Further research is warranted to investigate the underlying molecular mechanisms involved in these improvements and assess the performance of pSARK::IPT maize under field conditions.
Advancing EDGE Zones: spatial priorities for the conservation of tetrapod evolutionary history
Authors: Pipins Sebastian , Baillie Jonathan E.M. , Bowmer Alex , Pollock Laura J. , Owen Nisha , Gumbs Rikki 
Published: August 2023

AbstractThe biodiversity crisis is set to prune the Tree of Life in a way that threatens billions of years of evolutionary history. To secure this evolutionary heritage along with the benefits it provides to humanity, there is a need to understand where in space the greatest losses are predicted to occur. We therefore present threatened evolutionary history mapped for all tetrapod groups, globally and within Biodiversity Hotspots, and identify priority regions of Evolutionarily Distinct and Globally Endangered (EDGE) species at both a grid cell and national level. We find that threatened evolutionary history peaks in Cameroon, whilst EDGE species richness peaks in Madagascar. We refined and advanced the 2013 EDGE Zone concept for spatially prioritising phylogenetic diversity using a novel complementarity procedure with uncertainty incorporated for 33,628 tetrapod species. This involved using extinction risk, phylogenetic, and spatial data to iteratively select areas with the highest accumulated threatened evolutionary history driven by unique species compositions. We identify 25 priority EDGE Zones, which are insufficiently protected and disproportionately exposed to high levels of human pressure. Together, the 25 EDGE Zones occupy 0.723% of the world’s surface but harbour one-third of the world’s threatened evolutionary history, half of which is endemic to these grid cells. They also contain part of the distribution of 918 EDGE tetrapod species, representing near one-third of all EDGE species, with 480 being endemic. Our tetrapod EDGE Zones highlight areas of immediate concern for researchers, practitioners, policymakers, and communicators looking to safeguard the Tree of Life.
Molecular dynamics analyses of CLDN15 pore size and charge selectivity
Authors: McGuinness Sarah , Li Pan , Li Ye , Fuladi Shadi , Konar Sukanya , Sajjadi Samaneh , Sidahmed Mohammed , Li Yueying , Shen Le , Araghi Fatemeh Khalili , Weber Christopher R. 
Published: August 2023

ABSTRACTThe Claudin-15 (CLDN15) channel is important for nutrient, electrolyte, and water transport in the gastrointestinal tract. We used cell culture studies and molecular dynamics simulations to elucidate its structure and permeability mechanisms. We provide a model that underscores the crucial role of the D55 residue in the CLDN15 selectivity filter, which interacts with permeating cations. Our studies demonstrated the mechanisms whereby the size and charge of the D55 residue influence paracellular permeability. By altering D55 to larger, negatively charged glutamic acid (E) or similarly sized neutral asparagine (N), we observed changes in pore size and selectivity, respectively. D55E mutation decreased pore size, favoring small ion permeability without affecting charge selectivity, while D55N mutation led to reduced charge selectivity without markedly altering size selectivity. These findings shed light on the complex interplay of size and charge selectivity of CLDN15 channels. This knowledge can inform the development of strategies to modulate the function of CLDN15 and similar channels, which has implications for tight junction modulation in health and disease.SUMMARYUsing cell culture and molecular dynamics simulations, we have clarified the role of amino acid D55 in the claudin-15 channel function. D55 is important for channel permeability and selectivity in both charge- and size-selective manners. This insight into the structural determinant of claudin cation channel function provides potential insight for designing approaches to alter the claudin channel function to benefit human health.
Trans-Omics analysis of post injury thrombo-inflammation identifies endotypes and trajectories in trauma patients
Authors: Cohen Mitchell J. , Erickson Christopher B. , Lacroix Ian S. , Debot Margot , Dzieciatkowska Monika , Mitra Sanchayita , Schaid Terry R. , Hallas William M. , Thielen Otto N. , Cralley Alexis L. , Banerjee Anirban , Moore Ernest E , Silliman Christopher C. , D’Alessandro Angelo , Hansen Kirk C. 
Published: August 2023

ABSTRACTUnderstanding and managing the complexity of trauma-induced thrombo-inflammation necessitates an innovative, data-driven approach. This study leveraged a trans-omics analysis of longitudinal samples from trauma patients to illuminate molecular endotypes and trajectories that underpin patient outcomes. We hypothesized that trans-omics profiling reveals underlying clinical differences in severely injured patients that may present with similar clinical characteristics but ultimately have different responses to treatment and outcomes. Here we used proteomics and metabolomics to profile 759 of longitudinal plasma samples from 118 patients at 11 time points and 97 control subjects. Patients were stratified by shock and injury severity, revealing a spectrum of responses to trauma and treatment that are fundamentally tied to their unique underlying biology. Ensemble models were employed, demonstrating the predictive power of these molecular signatures with area under the receiver operating curves of 80 to 94% for key outcomes such as death. Then, transomics-based patient states were defined to create a map of unique pathophysiologic states encountered by trauma patients across time. Last, distinct longitudinal patient trajectories were identified that group patients according to their path through trauma transomics state maps. Unsupervised clustering of longitudinal trans-omics data identified specific clinical phenotypes while omics-based trajectories increased resolution on outcome prediction. The molecularly defined endotypes and trajectories provide an unprecedented lens to understand and potentially guide trauma patient management, opening a path towards precision medicine. This strategy presents a transformative framework that aligns with our understanding that trauma patients, despite similar clinical presentations, might harbor vastly different biological responses and outcomes.One-sentence summaryTransomic analyses of longitudinal plasma samples from severely injured patients identifies endotypes and trajectories that predict clinical outcomes.
Replication and Refinement of Brain Age Model for adolescent development
Authors: Ray Bhaskar , Chen Jiayu , Fu Zening , Suresh Pranav , Thapaliya Bishal , Farahdel Britny , Calhoun Vince D. , Liu Jingyu 
Published: August 2023

AbstractThe discrepancy between chronological age and estimated brain age, known as the brain age gap, may serve as a biomarker to reveal brain development and neuropsychiatric problems. This has motivated many studies focusing on the accurate estimation of brain age using different features and models, of which the generalizability is yet to be tested. Our recent study has demonstrated that conventional machine learning models can achieve high accuracy on brain age prediction during development using only a small set of selected features from multimodal brain imaging data. In the current study, we tested the replicability of various brain age models on the Adolescent Brain Cognitive Development (ABCD) cohort. We proposed a new refined model to improve the robustness of brain age prediction. The direct replication test for existing brain age models derived from the age range of 8-22 years onto the ABCD participants at baseline (9 to 10 years old) and year-two follow-up (11 to 12 years old) indicate that pre-trained models could capture the overall mean age failed precisely estimating brain age variation within a narrow range. The refined model, which combined broad prediction of the pre-trained model and granular information with the narrow age range, achieved the best performance with a mean absolute error of 0.49 and 0.48 years on the baseline and year-two data, respectively. The brain age gap yielded by the refined model showed significant associations with the participants’ information processing speed and verbal comprehension ability on baseline data.
A universal preservation protocol for multi-omic and histological analysis of kidney tissue
Authors: Gies Sydney E. , Hänzelmann Sonja , Kylies Dominik , Lagies Simon , Lassé Moritz , Hausmann Fabian , Khatri Robin , Poets Manuela , Zhang Tianran , Lu Shun , Liu Shuya , Chilla Silvia , Edenhofer Ilka , Czogalla Jan , Braun Fabian , Kammerer Bernd , Rinschen Markus M. , Puelles Victor G. , Bonn Stefan , Lindenmeyer Maja T. , Huber Tobias B. 
Published: August 2023

AbstractBiobanking of tissue from clinically obtained kidney biopsies for later use with multi-omic and imaging techniques is an inevitable step to overcome the need of disease model systems and towards translational medicine. Hence, collection protocols ensuring integration into daily clinical routines using preservation media not requiring liquid nitrogen but instantly preserving kidney tissue for clinical and scientific analyses are of paramount importance. Thus, we modified a robust single nucleus dissociation protocol for kidney tissue stored snap frozen or in the preservation media RNAlaterand CellCover. Using porcine kidney tissue as surrogate for human kidney tissue, we conducted single nucleus RNA sequencing with the Chromium 10X Genomics platform. The resulting data sets from each storage condition were analyzed to identify any potential variations in transcriptomic profiles. Furthermore, we assessed the suitability of the preservation media for additional analysis techniques (proteomics, metabolomics) and the preservation of tissue architecture for histopathological examination including immunofluorescence staining. In this study, we show that in daily clinical routines the RNAlaterfacilitates the collection of highly preserved kidney biopsies and enables further analysis with cutting-edge techniques like single nucleus RNA sequencing, proteomics, and histopathological evaluation. Only metabolome analysis is currently restricted to snap frozen tissue. This work will contribute to build tissue biobanks with well-defined cohorts of the respective kidney disease that can be deeply molecularly characterized, opening new horizons for the identification of unique cells, pathways and biomarkers for the prevention, early identification, and targeted therapy of kidney diseases.
Inferring genetic structure of European beech from observations of spectral phenotypes
Authors: Czyż Ewa A. , Schmid Bernhard , Eppinga Maarten B. , de La Harpe Marylaure , Moradi Aboubakr , Li Cheng , Schaepman Michael E. , Schuman Meredith C. 
Published: August 2023

AbstractBiodiversity loss presents a growing threat to the global environment and requires systematic and spatially contiguous monitoring. Monitoring of within-species genetic variation, a key factor when assessing biodiversity loss, is laborious and could be complemented by observations of phenotypes allowing inferences about genetic variation. We studied genetic and phenotypic variations in the common European beech (Fagus sylvaticaL.) derived from whole-genome sequences and spectral phenotypes of more than 200 individuals at 22 sites across the species’ natural range. The spectral phenotypes were collected under standardized illumination/observation conditions from the same top-of-canopy leaves used for nuclear DNA extraction. We found that spectral and environmental information explains 77.7% of the variance along the first two Principal Coordinates representing genetic structure among sampled individuals. Information from spectral phenotypes contributed 12.1% to predictions of between-site genetic structure. We therefore conclude that future remote observations having sufficient spectral and spatial resolution could improve our ability to rapidly and continuously monitor genetic diversity in trees.HighlightsGenetic diversity underpins biodiversity which loss requires systematic monitoringSpectral phenotypes acquiredin situare indicative of genetic variationIntraspecific spectral and genomic variation correlate across a species rangeSpectral phenotypes improve prediction of the between-site genetic structureRemote observations may contribute to monitoring genetic diversity within species
Generation of “OP7 chimera” defective interfering particle preparations free of infectious influenza A virus that shows antiviral efficacy in mice
Authors: Dogra Tanya , Pelz Lars , Boehme Julia D. , Küchler Jan , Kershaw Olivia , Marichal-Gallardo Pavel , Bälkner Maike , Hein Marc D. , Gruber Achim D. , Benndorf Dirk , Genzel Yvonne , Bruder Dunja , Kupke Sascha Y. , Reichl Udo 
Published: August 2023

AbstractInfluenza A virus (IAV) defective interfering particles (DIPs) are considered as new promising antiviral agents. Conventional DIPs (cDIPs) contain a deletion in the genome and can only replicate upon co-infection with infectious standard virus (STV), during which they suppress STV replication. We previously discovered a new type of IAV DIP “OP7” that entails genomic point mutations and displays higher antiviral efficacy than cDIPs. To avoid safety concerns for the medical use of OP7 preparations, we developed a production system that does not depend on infectious IAV. We reconstituted a mixture of DIPs consisting of cDIPs and OP7 chimera DIPs, in which both harbor a deletion in their genome. To complement the defect, the deleted viral protein is expressed by the suspension cell line used for production in shake flasks. Here, DIP preparations harvested are not contaminated with infectious virions, and the fraction of OP7 chimera DIPs depended on the multiplicity of infection. Intranasal administration of OP7 chimera DIP material was well tolerated. A rescue from an otherwise lethal IAV infection and no signs of disease upon OP7 chimera DIP co-infection demonstrated the remarkable antiviral efficacy. The clinical development of this new class of broad-spectrum antiviral may contribute to pandemic preparedness.
Rapid ionic current phenotyping (RICP) identifies mechanistic underpinnings of iPSC-CM AP heterogeneity
Authors: Clark Alexander P. , Wei Siyu , Fullerton Kristin , Krogh-Madsen Trine , Christini David J. 
Published: August 2023

AbstractAs a renewable, easily accessible, human-derivedin vitromodel, human induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) are a promising tool for studying arrhythmia-related factors, including cardiotoxicity and congenital proarrhythmia risks. An oft-mentioned limitation of iPSC-CMs is the abundant cell-to-cell variability in recordings of their electrical activity. Here, we develop a new method, rapid ionic current phenotyping (RICP), that utilizes a short (10 s) voltage clamp protocol to quantify cell-to-cell heterogeneity in key ionic currents. We correlate these ionic current dynamics to action potential recordings from the same cells and produce mechanistic insights into cellular heterogeneity. We present evidence that the L-type calcium current is the main determinant of upstroke velocity, rapid delayed rectifier K+current is the main determinant of the maximal diastolic potential, and an outward current in the excitable range of slow delayed rectifier K+is the main determinant of action potential duration. We measure an unidentified outward current in several cells at 6 mV that is not recapitulated by iPSC-CM mathematical models but contributes to determining action potential duration. In this way, our study both quantifies cell-to-cell variability in membrane potential and ionic currents, and demonstrates how the ionic current variability gives rise to action potential heterogeneity. Based on these results, we argue that iPSC-CM heterogeneity should not be viewed simply as a problem to be solved but as a model system to understand the mechanistic underpinnings of cellular variability.New & NoteworthyWe present rapid ionic current phenotyping (RICP), a current quantification approach based on an optimized voltage clamp protocol. The method captures a rich snapshot of ionic currents that provides quantitative information about multiple currents (e.g., ICaL, IKr) in the same cell. The protocol helped to identify key ionic determinants of cellular action potential heterogeneity in iPSC-CMs. This included unexpected results, such as the critical role of IKrin establishing the maximum diastolic potential.
A tryptophan metabolite modulates the host response to bacterial infection via kainate receptors
Authors: Parada-Kusz Margarita , Clatworthy Anne E. , Goering Emily R. , Blackwood Stephanie M. , Salm Elizabeth J. , Choi Catherine , Combs Senya , Lee Jenny S. W. , Rodriguez-Osorio Carlos , Tomita Susumu , Hung Deborah T. 
Published: August 2023

SUMMARYBacterial infection involves a complex interaction between the pathogen and host where the outcome of infection is not solely determined by pathogen eradication. To identify small molecules that promote host survival by altering the host-pathogen dynamic, we conducted anin vivochemical screen using zebrafish embryos and found that treatment with 3-hydroxy-kynurenine protects from lethal gram-negative bacterial infection. 3-hydroxy-kynurenine, a metabolite produced through host tryptophan metabolism, has no direct antibacterial activity but enhances host survival by restricting bacterial expansion in macrophages by targeting kainate-sensitive glutamate receptors. These findings reveal new mechanisms by which tryptophan metabolism and kainate-sensitive glutamate receptors function and interact to modulate immunity, with significant implications for the coordination between the immune and nervous systems in pathological conditions.
From sequences to therapeutics: Machine learning predicts chemically modified siRNA Activity
Authors: Martinelli Dominic D. 
Published: August 2023

AbstractSmall interfering RNAs (siRNAs) exemplify the promise of genetic medicine in the discovery of novel therapeutic modalities. Their ability to selectively suppress gene expression makes them ideal candidates for development as oligonucleotide pharmaceuticals. Recent advancements in machine learning (ML) have facilitated unmodified siRNA design and efficacy prediction, but a model trained to predict the silencing activity of siRNAs with diverse chemical modification patterns has yet to be published, despite the importance of such chemical modifications in designing siRNAs with the potential to advance to the clinic. This study presents the first application of ML to classify efficient chemically modified siRNAs from sequence and chemical modification patterns alone. Three algorithms are evaluated at three classification thresholds and compared according to sensitivity, specificity, consistency of feature weights with empirical knowledge, and performance on an external validation dataset. Finally, possible directions for future research are proposed.