bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epigenomic profiling of stem cells within the pilosebaceous unit identifies PRDM16 as a regulator of sebaceous gland homeostasis
Authors: Rehimi Rizwan , Crispatzu Giuliano , Chacón-Martínez Carlos Andrés , Bleckwehl Tore , Mantellato Giada , Gözüm Gökcen , Clément-Ziza Mathieu , Wickström Sara A. , Niemann Catherin , Niessen Carien , Rada-Iglesias Alvaro 
Published: April 2021

AbstractThe epidermis consists of different compartments such as the hair follicle (HF), sebaceous gland (SG) and interfollicular epidermis (IFE), each containing distinct stem cell (SC) populations. However, with the exception of the SCs residing within the HF bulge, other epidermal SC populations remain less well understood. Here we used an epigenomic strategy that combines H3K27me3 ChIP-seq and RNA-seq profiling to identify major regulators of pilosebaceous unit (PSU) SC located outside the bulge. When applied to the bulk of PSU SC isolated from mouse skin our approach identified both previously known and potentially novel non-bulge PSU SC regulators. Among the latter, we found that PRDM16 was predominantly enriched within the Junctional Zone (JZ), which harbors SC that contribute to renewal of the upper HF and the SG. To investigate PRDM16 function in the PSU SC, we generated an epidermal-specificPrdm16Knock-out mouse model (K14-Cre-Prdm16fl/fl). Notably, SG homeostasis was disturbed upon loss of PRDM16 resulting in enlarged SGs, and excessive sebum production, resembling some of the features associated with human acne and sebaceous hyperplasia. Importantly, PRDM16 is essential to shut down proliferation in differentiating sebocytes. Overall, our study provides a list of putative novel regulators of PSU SC outside the bulge and identifies PRDM16 as a major regulator of SG homeostasis.
Comparative toxicogenomics of glyphosate and Roundup herbicides by mammalian stem cell-based genotoxicity assays and molecular profiling in Sprague-Dawley rats
Authors: Mesnage Robin , Ibragim Mariam , Mandrioli Daniele , Falcioni Laura , Tibaldi Eva , Belpoggi Fiorella , Brandsma Inger , Bourne Emma , Savage Emanuel , Mein Charles A , Antoniou Michael N 
Published: April 2021

AbstractWhether glyphosate-based herbicides (GBHs) are more potent than glyphosate alone at activating cellular mechanisms, which drive carcinogenesis remains controversial. As GBHs are more cytotoxic that glyphosate, we reasoned they may also be more capable of activating carcinogenic pathways. We tested this hypothesis by comparing the effects of glyphosate with Roundup GBHs bothin vitroandin vivo. First, glyphosate was compared with representative GBHs namely MON 52276 (EU), MON 76473 (UK) and MON 76207 (USA) using the mammalian stem cell-based ToxTracker system. Here, MON 52276 and MON 76473, but not glyphosate and MON 76207, activated oxidative stress and unfolded protein responses. Second, molecular profiling of liver was performed in female Sprague-Dawley rats exposed to glyphosate or MON 52276 (both at 0.5, 50, 175 mg/kg bw/day glyphosate) for 90 days. MON 52276 but not glyphosate increased hepatic steatosis and necrosis. MON 52276 and glyphosate altered the expression of genes in liver reflecting TP53 activation by DNA damage and circadian rhythm regulation. Genes most affected in liver were similarly altered in kidneys. Small RNA profiling in liver showed decreased amounts of miR-22 and miR-17 from MON 52276 ingestion. Glyphosate decreased mir-30 while miR-10 levels were increased. DNA methylation profiling of liver revealed 5,727 and 4,496 differentially methylated CpG sites between the control and glyphosate and MON 52276 exposed animals respectively. Apurinic/apyrimidinic DNA damage formation in liver was increased with glyphosate exposure. Altogether, our results show that Roundup formulations cause more biological changes linked with carcinogenesis than glyphosate.
Revealing intraosseous blood flow in the human tibia with ultrasound
Authors: Salles Sebastien , Shepherd Jami , Vos Hendrik J. , Renaud Guillaume 
Published: April 2021

AbstractIntraosseous blood circulation is thought to have a critical role in bone growth and remodeling, fracture healing, and bone disorders. However, it is rarely considered in clinical practice due to the absence of a suitable non-invasive in vivo measurement technique. In this work, we assessed blood perfusion in tibial cortical bone simultaneously with blood flow in the superficial femoral artery with ultrasound imaging in 5 healthy volunteers. After suppression of stationary signal with Singular-Value-Decomposition, pulsatile blood flow in cortical bone tissue is revealed, following the heart rate measured in the femoral artery. Using a method combining transverse oscillations and phase-based motion estimation, two-dimensional vector flow was obtained in the cortex of the tibia. After spatial averaging over the cortex, the peak blood velocity along the long axis of the tibia was measured four times larger than the peak blood velocity across the bone cortex. This suggests that blood flow in central (Haversian) canals is larger than in perforating (Volkmann’s) canals, as expected from the intracortical vascular organization in humans. The peak blood velocity indicates a flow from the endosteum to the periosteum and from the heart to the foot for all subjects. Because aging and the development of bone disorders are thought to modify the direction and velocity of intra-cortical blood flow, their quantification is crucial. This work reports for the first time an in vivo quantification of the direction and velocity of blood flow in human cortical bone.
Diagnostic classification based on DNA methylation profiles using sequential machine learning approaches
Authors: Wojewodzic M. W. , Lavender J. P. 
Published: April 2021

AbstractAberrant methylation patterns in human DNA have great potential for the discovery of novel diagnostic and disease progression biomarkers. In this paper, we used machine learning algorithms to identify promising methylation sites for diagnosing cancerous tissue and to classify patients based on methylation values at these sites.We used genome-wide DNA methylation patterns from both cancerous and normal tissue samples, obtained from the Genomic Data Commons consortium and trialled our methods on three types of urological cancer. A decision tree was used to identify the methylation sites most useful for diagnosis.The identified locations were then used to train a neural network to classify samples as either cancerous or non-cancerous. Using this two-step approach we found strong indicative biomarker panels for each of the three cancer types.These methods could likely be translated to other cancers and improved by using non-invasive liquid methods such as blood instead of biopsy tissue.
Filling gaps: fishing, genetics, and conservation of groupers, especially the comb grouper (badejo) (Mycteroperca acutirostris), in SE Brazil (2013-2020)
Authors: Begossi Alpina , Salivonchyk Svetlana , Glamuzina Branko , Alves-Pereira Alessandro , Araújo Batista Carlos Eduardo De , Priolli Regina H. G. 
Published: April 2021

AbstractThere are large gaps in our knowledge of the biology of important fish consumed by people in tropical countries, which makes conservation difficult. Small-scale fisheries are difficult to study and regulate, especially in countries with no systematic species monitoring. It is even more difficult to estimate the influence of these fisheries on vulnerable fish species and to diagnose possible damage to local fish populations. In this study, 490 individuals ofbadejo, or comb grouper (Mycteropeca acutirostris), were observed at the Posto 6 fishery in Copacabana, Rio de Janeiro, for the periods of 2013-2014 and 2018-2020. A pattern of decreasing catches was observed for comb grouper. Therefore, provided that the fishing gear and the number of fish have remained the same, the apparent decrease in comb grouper needs to be further investigated. The results provide information regarding the reproduction of comb grouper, with major spawning season around spring (September-December) and additional spawning during April in SE Brazil. Samples from 96 groupers along the coast of Brazil were obtained, and genetic analyses were conducted. The genetic information obtained for grouper species enabled us to determine the relative genetic proximity ofM. acutirostrisandMycteroperca bonaciand to obtain information that can be useful for aquaculture and conservation.
Axonal CB1 receptors mediate inhibitory bouton formation via cAMP increase
Authors: Liang Jian , Kruijssen Dennis LH , Verschuuren Aniek CJ , Voesenek Bas JB , Benavides Feline , Gonzalez Maria Sáez , Ruiter Marvin , Wierenga Corette J 
Published: April 2021

AbstractExperience-dependent formation and removal of synapses are essential throughout life. For instance, GABAergic synapses are removed to facilitate learning, and strong excitatory activity is accompanied by formation of inhibitory synapses. We recently discovered that active dendrites trigger the growth of inhibitory synapses via CB1 receptor-mediated endocannabinoid signaling, but the underlying mechanism remained unclear. Using two-photon microscopy to monitor the formation of individual inhibitory boutons, we found that CB1 receptor activation mediated formation of inhibitory boutons and promoted their subsequent stabilization. Inhibitory bouton formation did not require neuronal activity and was independent of Gi/oprotein signaling, but was directly induced by elevating cAMP levels using forskolin and by activating Gsproteins using DREADDs. Our findings reveal that axonal CB1 receptors signal via unconventional downstream pathways and that inhibitory bouton formation is triggered by an increase in axonal cAMP levels. Our results demonstrate a novel role for axonal CB1 receptors in axon-specific, and context-dependent, inhibitory synapse formation.
A multifaceted role of progranulin in regulating amyloid-beta dynamics and responses
Authors: Du Huan , Wong Man Ying , Zhang Tingting , Santos Mariela Nunez , Hsu Charlene , Zhang Junke , Yu Haiyuan , Luo Wenjie , Hu Fenghua 
Published: April 2021

AbstractHaploinsufficiency of progranulin (PGRN) is a leading cause of frontotemporal lobar degeneration (FTLD). PGRN polymorphisms are associated with Alzheimer’s disease (AD). PGRN is highly expressed in the microglia near Aβ plaques and influences plaque dynamics and microglial activation. However, the detailed mechanisms remain elusive. Here we report that PGRN deficiency reduces human APP and Aβ levels in the young male but not female mice. PGRN deficient microglia exhibit increased expression of markers associated with microglial activation, including CD68, Galectin-3, TREM2 and GPNMB, specifically near Aβ plaques. In addition, PGRN loss leads to up-regulation of lysosome proteins and an increase in the nuclear localization of TFE3, a transcription factor involved in lysosome biogenesis. Cultured PGRN deficient microglia show enhanced nuclear translocation of TFE3 and inflammation in response to Aβ fibril treatment. Taken together, our data revealed a sex- and age-dependent effect of PGRN on amyloid metabolism and a role of PGRN in regulating lysosomal activities and inflammation in plaque-associated microglia, which may contribute to the disease mechanism associated with PGRN polymorphisms in AD.
Longitudinal characterization of neuroanatomical changes in the Fischer 344 rat brain during normal aging and between sexes
Authors: Fowler Caitlin , Goerzen Dana , Madularu Dan , Devenyi Gabriel A. , Chakravarty M. Mallar , Near Jamie 
Published: April 2021

ABSTRACTAnimal models are widely used to study the pathophysiology of disease and to evaluate the efficacy of novel interventions, crucial steps towards improving disease outcomes in humans. The Fischer 344 (F344) wildtype rat is a common experimental background strain for transgenic models of disease and is also one of the most frequently used models in aging research. Despite frequency of use, characterization of neuroanatomical change with age has not been performed in the F344 rat. To this end, we present a comprehensive longitudinal examination of morphometric change in 73 brain regions and at a voxel-wise level during normative aging in a mixed-sex cohort of F344 rats. We identified age- and sex-related changes in regions such as the cortex, hippocampus, cingulum, caudoputamen, and nucleus accumbens, which are implicated in memory and motor control circuits frequently affected by aging and neurodegenerative disease. These findings provide a baseline for neuroanatomical changes associated with aging in male and female F344 rats, to which data from transgenic models or other background strains can be compared.HIGHLIGHTSIn vivomagnetic resonance imaging reveals altered neuroanatomy in aging Fischer ratsLinear and curvilinear age effects exist in both grey and white matter structuresSex differences are primarily seen in grey matter structuresThis study clarifies normal aging trajectories across 73 brain regions in both sexesImproved understanding of normal aging will inform future pathological aging studies
Target enrichment improves phylogenetic resolution in the genusZanthoxylum(Rutaceae) and indicates both incomplete lineage sorting and hybridization events
Authors: Reichelt Niklas , Wen Jun , Pätzold Claudia , Appelhans Marc S 
Published: April 2021

AbstractBackground and aimsZanthoxylumL. is the only pantropical genus within Rutaceae, with a few species native to temperate eastern Asia and North America. Efforts using Sanger sequencing failed to resolve the backbone phylogeny ofZanthoxylum. In this study, we employed target enrichment high-throughput sequencing to improve resolution. Gene trees were examined for concordance and sectional classifications ofZanthoxylumwere evaluated. Off-target reads were investigated to identify putative single-copy markers for bait refinement, and low-copy markers for evidence of putative hybridization events.MethodsWe developed a custom bait set for target enrichment of 745 exons inZanthoxylumand applied it to 45Zanthoxylumspecies and oneTetradiumspecies as the outgroup. Illumina reads were processed via the HybPhyloMaker pipeline. Phylogenetic inferences were conducted using coalescent and concatenated methods. Concordance was assessed using quartet sampling. Off-target reads were assembled and putative single- and low-copy genes were extracted. Additional phylogenetic analyses were performed based on these alignments.Key resultsFour major clades are supported withinZanthoxylum: the African clade, theZ. asiaticumclade, the Asian-Pacific-Australian clade, and the American-eastern Asian clade. While overall support has improved, regions of conflict are similar to those previously observed. Gene tree discordances indicate a hybridization event in the ancestor of the Hawaiian lineage, and incomplete lineage sorting for the American backbone. Off-target putative single-copy genes largely confirm on-target results, and putative low-copy genes provide additional evidence for hybridization in the Hawaiian lineage. Only two of the five sections ofZanthoxylumare resolved as monophyletic.ConclusionTarget enrichment is suitable to assess phylogenetic relationships inZanthoxylum. Our phylogenetic analyses reveal that current sectional classifications need revision. Quartet tree concordance indicates several instances of reticulate evolution. Off-target reads are proven useful to identify additional phylogenetically informative regions for bait refinement or gene tree based approaches.
Phase- and State-Dependent Modulation of Breathing Pattern by preBötzinger Complex Somatostatin Expressing Neurons
Authors: de Sousa Abreu Raquel P. , Bondarenko Evgeny , Feldman Jack L. 
Published: April 2021

AbstractAs neuronal subtypes are increasingly categorized, delineating their functional role is paramount. The preBötzinger Complex (preBötC) subpopulation expressing the neuropeptide somatostatin (SST) is classified as mostly excitatory, inspiratory-modulated and not rhythmogenic. We further characterized their phenotypic identity; 87% were glutamatergic and the balance were glycinergic and/or GABAergic. We then used optogenetics to investigate their modulatory role in both anesthetized and freely moving mice. In anesthetized mice, short photostimulation (100 ms) of preBötC SST+neurons modulated breathing-related variables in a combinatory phase- and state-dependent manner; changes in inspiratory duration, inspiratory peak amplitude (Amp), and phase were different at higher (≥2.5 Hz) vs. lower (<2.5 Hz) breathing frequency. Moreover, we observed a biphasic effect of photostimulation during expiration that is probabilistic, i.e., photostimulation given at the same phase in consecutive cycles can evoke opposite responses (lengthening vs. shortening of the phase). This unexpected probabilistic state- and phase-dependent responses to photostimulation exposed properties of the preBötC that were not predicted and cannot be readily accounted for in current models of preBötC pattern generation. In freely moving mice, prolonged photostimulation decreasedfin normoxia, hypoxia, or hypercapnia, and increased Amp and produced a phase advance, which was similar to the results in anesthetized mice whenf≥2.5 Hz. We conclude that preBötC SST+neurons are a key mediator of the extraordinary and essential lability of breathing pattern.Key points summaryWe transfected preBötzinger Complex (preBötC) somatostatin-expressing (SST+) neurons, which modulate respiratory pattern, but are not rhythmogenic, with channelrhodopsin to investigate phase- and state-dependent modulation of breathing pattern in anesthetized and freely behaving mice in normoxia, hypoxia, and hypercapnia.In anesthetized mice, photostimulation of preBötC SST+neurons during inspiration increased inspiratory duration and amplitude regardless of baseline breathing frequency,f.In anesthetized mice with lowf(<2.5 Hz), photostimulation of preBötC SST+neurons during expiration evoked either phase advance or phase delay, whereas in anesthetized mice with highf(≥2.5 Hz) and in freely behaving mice in normoxia, hypoxia, or hypercapnia, photostimulation always evoked phase advance.Phase- and state-dependency is a function of overall breathing network excitability.Thef-dependent probabilistic modulation of breathing pattern by preBötC SST+neurons was unexpected, requiring reconsideration of current models of preBötC function, which neither predict nor can readily account for such responses.
Persistence and anti-persistence in treadmill walking
Authors: Kozlowska Klaudia , Latka Miroslaw , West Bruce J. 
Published: April 2021

AbstractBackgroundLong-range persistent correlations in stride time (ST) and length (SL) are the fundamental traits of treadmill gait. Our recent work showed that the ST and SL time series’ statistical properties originated from the superposition of large-scale trends and small-scale fluctuations (residuals). Trends served as the control manifolds about which ST and SL fluctuated. The scaling exponents of the residuals were slightly smaller than 0.5.Research questionDo random changes in treadmill belt speed affect the trend properties and scaling exponents of ST/SL residuals?MethodsWe used Multivariate Adaptive Regression Splines (MARS) to determine gait trends during a walk on a treadmill whose belt speed was perturbed by a strong random noise. Then, we calculated the scaling exponents of MARS residuals with the madogram estimator.ResultsExcept for the ST at the lowest treadmill speedv= 0.8 m/s, the normalized trend duration was at least three times greater than that for the unperturbed walk. The Cauchy distribution scale parameter, which served as a measure of the width of SL and ST trend slope distributions, was atv= 1.2 m/s, almost 50% and 25% smaller than the unperturbed values. The differences were even greater atv= 1.6 m/s: 73% and 83%. For all speeds, the ST and SL MARS residuals were strongly anti-persistent. Atv= 1.2 m/s, the corresponding scaling exponents were equal to 0.37±0.10 and 0.25±0.09. Apart from ST atv= 0.8 m/s, the ST/SL scaling indices were close to 0.5.SignificancePersistence of gait parameters is closely related to the properties of their trends. Longer trends with a gentle slope and strong anti-persistence of ST/SL residuals are the manifestations or tight control required during the perturbed treadmill walk.
Multi-Trait Machine and Deep Learning Models for Genomic Selection using Spectral Information in a Wheat Breeding Program
Authors: Sandhu Karansher S. , Patil Shruti S. , Pumphrey Michael O. , Carter Arron H. 
Published: April 2021

AbstractPrediction of breeding values and phenotypes is central to plant breeding and has been revolutionized by the adoption of genomic selection (GS). Use of machine and deep learning algorithms applied to complex traits in plants can improve prediction accuracies in the context of GS. Spectral reflectance indices further provide information about various physiological parameters previously undetectable in plants. This research explores the potential of multi-trait (MT) machine and deep learning models for predicting grain yield and grain protein content in wheat using spectral information in GS models. This study compares the performance of four machine and deep learning-based uni-trait (UT) and MT models with traditional GBLUP and Bayesian models. The dataset consisted of 650 recombinant inbred lines from a spring wheat breeding program, grown for three years (2014-2016), and spectral data were collected at heading and grain filling stages. MT-GS models performed 0-28.5% and −0.04-15% superior to the UT-GS models for predicting grain yield and grain protein content. Random forest and multilayer perceptron were the best performing machine and deep learning models to predict both traits. These two models performed similarly under UT and MT-GS models. Four explored Bayesian models gave similar accuracies, which were less than machine and deep learning-based models, and required increased computational time. Green normalized difference vegetation index best predicted grain protein content in seven out of the nine MT-GS models. Overall, this study concluded that machine and deep learning-based MT-GS models increased prediction accuracy and should be employed in large-scale breeding programs.Core IdeasPotential for combining high throughput phenotyping, machine and deep learning in breeding.Multi-trait models exploit information from secondary correlated traits efficiently.Spectral information improves genomic selection models.Deep learning can aid plant breeders owing to increased data generated in breeding programs