bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interrelated effects of age and parenthood on whole-brain controllability: protective effects of parenthood in mothers
Authors: Jamalabadi Hamidreza , Hahn Tim , Winter Nils R. , Nozari Erfan , Ernsting Jan , Meinert Susanne , Leehr Elisabeth , Dohm Katharina , Bauer Jochen , Pfarr Julia-Katharina , Stein Frederike , Thomas-Odenthal Florian , Brosch Katharina , Mauritz Marco , Gruber Marius , Repple Jonathan , Kaufmann Tobias , Krug Axel , Nenadić Igor , Kircher Tilo , Dannlowski Udo , Derntl Birgit 
Published: July 2022

AbstractBackgroundControllability is a measure of the brain’s ability to orchestrate neural activity which can be quantified in terms of properties of the brain’s network connectivity. Evidence from the literature suggests that aging can exert a general effect on whole-brain controllability. Mounting evidence, on the other hand, suggests that parenthood and motherhood in particular lead to long-lasting changes in brain architecture that effectively slow down brain aging. We hypothesize that parenthood might preserve brain controllability properties from aging.MethodsIn a sample of 814 healthy individuals (aged 33.9±12.7 years, 522 females), we estimate whole-brain controllability and compare the aging effects in subjects with vs. those without children. We use diffusion tensor imaging (DTI) to estimate the brain structural connectome. The level of brain control is then calculated from the connectomic properties of the brain structure. Specifically, we measure the network control over many low-energy state transitions (average controllability) and the network control over difficult-to-reach states (modal controllability).Results and conclusionIn nulliparous females, whole-brain average controllability increases, and modal controllability decreases with age, a trend that we do not observe in parous females. Statistical comparison of the controllability metrics shows that modal controllability is higher and average controllability is lower in parous females compared to nulliparous females. In men, we observed the same trend, but the difference between nulliparous and parous males do not reach statistical significance. Our results provide strong evidence that parenthood contradicts aging effects on brain controllability and the effect is stronger in mothers.
The Free Lunch is not over yet – Systematic Exploration of Numerical Thresholds in Phylogenetic Inference
Authors: Haag Julia , Hübner Lukas , Kozlov Alexey M. , Stamatakis Alexandros 
Published: July 2022

AbstractMaximum Likelihood (ML) is a widely used phylogenetic inference model. ML implementations heavily rely on numerical optimization routines that use internal numerical thresholds to determine convergence. We systematically analyze the impact of these threshold settings on the log-likelihood and runtimes for ML tree inferences with RAxML-NG, IQ-TREE, and FastTree on empirical datasets. We provide empirical evidence that we can substantially accelerate tree inferences with RAxML-NG and IQ-TREE by changing the default values of two such numerical thresholds. At the same time, altering these settings does not significantly impact the quality of the inferred trees. We further show that increasing both thresholds accelerates the RAxML-NG bootstrap without influencing the resulting support values. For RAxML-NG, increasing the likelihood thresholdsϵLnLandϵbrlento 10 and 103respectively results in an average tree inference speedup of 1.9±0.6 onData collection 1, 1.8±1.1 onData collection 2, and 1.9±0.8 onData collection 2for the RAxML-NG bootstrap. Increasing the likelihood thresholdϵLnLto 10 in IQ-TREE results in an average tree inference speedup of 1.3±0.4 onData collection 1and 1.3±0.9 onData collection 2.
Interactive analysis of single-cell data using flexible workflows with SCTK2.0
Authors: Wang Yichen , Sarfraz Irzam , Hong Rui , Koga Yusuke , Akavoor Vidya , Cao Xinyun , Alabdullatif Salam , Pervaiz Nida , Zaib Syed Ali , Wang Zhe , Jansen Frederick , Yajima Masanao , Johnson W. Evan , Campbell Joshua D. 
Published: July 2022

SummaryAnalysis of single-cell RNA-seq (scRNA-seq) data can reveal novel insights into heterogeneity of complex biological systems. Many tools and workflows have been developed to perform different types of analysis. However, these tools are spread across different packages or programming environments, rely on different underlying data structures, and can only be utilized by people with knowledge of programming languages. In the Single Cell Toolkit 2.0 (SCTK2.0), we have integrated a variety of popular tools and workflows to perform various aspects of scRNA-seq analysis. All tools and workflows can be run in the R console or using an intuitive graphical user interface built with R/Shiny. HTML reports generated with Rmarkdown can be used to document and recapitulate individual steps or entire analysis workflows. We show that the toolkit offers more features when compared with existing tools and allows for a seamless analysis of scRNA-seq data for non-computational users.Graphical AbstractHighlightsIntuitive graphical user interface for interactive analysis of scRNA-seq dataAllows non-computational users to analyze scRNA-seq data with end-to-end workflowsProvides interoperability between tools across different programming environmentsProduces HTML reports for reproducibility and easy sharing of results
High-throughput and automatic structural and developmental root phenotyping on Arabidopsis seedlings
Authors: Fernandez Romain , Crabos Amandine , Maillard Morgan , Nacry Philippe , Pradal Christophe 
Published: July 2022

AbstractBackgroundHigh-throughput phenotyping is crucial for the genetic and molecular understanding of adaptive root system development. In recent years, imaging automata have been developed to acquire the root system architecture of many genotypes grown in Petri dishes to explore the Genetic x Environment (GxE) interaction. There is now an increasing interest in understanding the dynamics of the adaptive responses, such as the organ apparition or the growth rate. However, due to the increasing complexity of root architectures in development, the accurate description of the topology, geometry, and dynamics of a growing root system remains a challenge.ResultsWe designed a high-throughput phenotyping method, combining an imaging device and an automatic analysis pipeline based on registration and topological tracking, capable of accurately describing the topology and geometry of observed root systems in 2D+t. The method was tested on a challenging Arabidopsis seedling dataset, including numerous root occlusions and crossovers. Static phenes are estimated with high accuracy (R2= 0.996 and 0, 923 for primary and second-order roots length, respectively). These performances are similar to state-of-the-art results obtained on root systems of equal or lower complexity. In addition, our pipeline estimates dynamic phenes accurately between two successive observations (R2= 0. 938 for lateral root growth).ConclusionsWe designed a novel method of root tracking that accurately and automatically measures both static and dynamic RSA parameters from a novel high-throughput root phenotyping platform. It has been used to characterize developing patterns of root systems grown under various environmental conditions. It provides a solid basis to explore the GxE interaction controlling the dynamics of root system architecture adaptive responses. In future work, our approach will be adapted to a wider range of imaging configurations and species.
Metformin Improves Ovarian Function and Increases Egg Production in Broiler Breeder Hens
Authors: Weaver Evelyn A. , Ramachandran Ramesh 
Published: July 2022

ABSTRACTBroiler breeder hens, the parent stock of commercial broiler chickens, have poor reproductive efficiency associated with aberrant and excessive recruitment of ovarian follicles which results in sub-optimal egg production, fertility, and hatchability. The reproductive dysfunction observed in these hens resembles polycystic ovary syndrome in women, a condition wherein metformin is prescribed as a treatment. The main objectives of this study were to determine the effect of metformin on body weight, abdominal fat pad weight, ovarian function, and plasma steroid hormone concentrations. Broiler breeder hens were treated with 0, 25, 50, or 75 mg/kg body weight of metformin mixed in the diet for 40 weeks (n= 45 hens/treatment; 25-65 weeks of age). At 65 weeks of age, hens that received the highest dose of metformin had significantly lower body and abdominal fat pad weights (p < 0.05) than the control. Metformin treatment, at all levels, normalized the preovulatory and prehierarchical ovarian follicular hierarchy. Metformin (50 or 75 mg/kg body weight) significantly increased the total number of eggs laid per hen during the entire production period and these hens had significantly greater fertility and hatchability at 65 weeks of age compared to the control (p < 0.05). Metformin treatment at all levels altered the plasma profile of reproductive hormones, with significantly lower plasma testosterone concentrations and a decreased testosterone to androstenedione ratio in hens that received metformin (p < 0.05). Future studies should focus on the mechanisms underlying the beneficial effects of metformin in improving the reproductive efficiency of broiler breeder hens.In BriefThe pathophysiology of the ovarian dysfunction encountered in broiler breeder hens remains poorly understood but is similar to a condition in women known as PCOS. This study reveals that metformin may provide a cheap and effective method of improving ovarian function in broiler breeder hens.
Pannexin 3 channels regulate architecture, adhesion, barrier function and inflammation in the skin
Authors: O’Donnell Brooke L. , Sanchez-Pupo Rafael E. , Sayedyahossein Samar , Karimi Mehdi , Bahmani Mehrnoosh , Zhang Christopher , Johnston Danielle , Kelly John J. , Wakefield C. Brent , Barr Kevin , Dagnino Lina , Penuela Silvia 
Published: July 2022

ABSTRACTThe channel-forming glycoprotein Pannexin 3 (PANX3) functions in cutaneous wound healing and keratinocyte differentiation, but its role in skin homeostasis through aging is not yet understood. We found that PANX3 is absent in newborn skin but becomes upregulated with age. We characterized the skin of globalPanx3knockout mice (KO) and found that KO dorsal skin showed sex-differences at different ages, but generally had reduced dermal and hypodermal areas compared to aged-matched controls. Transcriptomic analysis of KO epidermis revealed reduced E-cadherin stabilization and Wnt signaling compared to WT, consistent with the inability of primary KO keratinocytes to adhere in culture, and diminished epidermal barrier function in KO mice. We also observed increased inflammatory signaling in KO epidermis and higher incidence of dermatitis in aged KO mice compared to wildtype controls. These findings suggest that during skin aging, PANX3 is critical in the maintenance of dorsal skin architecture, keratinocyte cell-cell and cell-matrix adhesion and inflammatory skin responses.
Fast Local Alignment of Protein Pockets (FLAPP): A system-compiled program for large-scale binding site alignment
Authors: Sankar Santhosh , Sakthivel Naren Chandran , Chandra Nagasuma 
Published: July 2022

AbstractProtein function is a direct consequence of its sequence, structure and the arrangement at the binding site. Bioinformatics using sequence analysis is typically used to gain a first insight into protein function. Protein structures, on the other hand, provide a higher resolution platform into understanding functions. As the protein structural information is increasingly becoming available through experimental structure determination and through advances in computational methods for structure prediction, the opportunity to utilize this data is also increasing. Structural analysis of small molecule ligand binding sites in particular provide a direct and more accurate window to infer protein function. However it remains a poorly utilized resource due to the huge computational cost of existing methods that make large scale structural comparisons of binding sites prohibitive. Here we present an algorithm called FLAPP that produces very rapid atomic level alignments. By combining clique matching in graphs and the power of modern CPU architectures, FLAPP aligns a typical pair of binding site binding sites at ~12.5 milliseconds using a single CPU core, ~ 1 millisecond using 12 cores on a standard desktop machine, and performs a PDB-wide scan in 1-2 minutes. We perform rigorous validation of the algorithm at multiple levels of complexity and show that FLAPP provides accurate alignments. We also present a case study involving vitamin B12 binding sites to showcase the usefulness of FLAPP for performing an exhaustive alignment based PDB-wide scan. We expect this tool will be invaluable to the scientific community to quickly align millions of site pairs on a normal desktop machine to gain insights into protein function and drug discovery for drug target and off-target identification, and polypharmacology.
Postnatal protein intake as a determinant of skeletal muscle structure and function in mice – a pilot study
Authors: Giakoumaki Ifigeneia , Pollock Natalie , Aljuaid Turki , Sanicandro Anthony J. , Alameddine Moussira , Owen Euan , Myrtziou Ioanna , Ozanne Susan E. , Kanakis Ioannis , Goljanek-Whysall Katarzyna , Vasilaki Aphrodite 
Published: July 2022

ABSTRACTSarcopenia is characterised by an age-related decrease in the number of muscle fibres and additional weakening of the remaining fibres, resulting in a reduction in muscle mass and function. Many studies associate poor maternal nutrition during gestation and/or lactation with altered skeletal muscle homeostasis in the offspring and the development of sarcopenia. The aim of this study was to determine whether the musculoskeletal physiology in offspring born to mouse dams fed a low-protein diet during pregnancy was altered and whether any physiological changes could be modulated by the nutritional protein content in early postnatal stages. Thy1-YFP female mice were fed ad libitum on either a normal (20%) or a low-protein (5%) diet. Newborn pups were cross-fostered to different lactating dams (maintained on 20% or 5% diet) to generate 3 groups analysed at weaning (21 days): Normal-to-Normal (NN), Normal-to-Low (NL) and Low-to-Normal (LN). Further offspring were maintained ad libitum on the same diet as during lactation until 12 weeks of age creating another 3 groups (NNN, NLL, LNN). Mice on a low protein diet postnatally (NL, NLL) exhibited a significant reduction in body and muscle weight persisting up to 12 weeks, unlike mice on a low protein diet only prenatally (LN, LNN). Muscle fibre size was reduced in mice from the NL but not LN group, showing recovery at 12 weeks of age. Muscle force was reduced in NLL mice, concomitant with changes in the NMJ site and changes in atrophy-related and myosin genes. In addition, μCT scans of mouse tibiae at 12 weeks of age revealed changes in bone mass and morphology, resulting in a higher bone mass in the NLL group than the control NNN group. Finally, changes in the expression of miR-133 in the muscle of NLL mice suggest a regulatory role for this microRNA in muscle development in response to postnatal diet changes. Overall, this data shows that a low maternal protein diet and early postnatal life low-protein intake in mice can impact skeletal muscle physiology and function in early life while postnatal low protein diet favors bone integrity in adulthood.
Modular automated microfluidic cell culture platform reduces glycolytic stress in cerebral cortex organoids
Authors: Seiler Spencer T. , Mantalas Gary L. , Selberg John , Cordero Sergio , Torres-Montoya Sebastian , Baudin Pierre V. , Ly Victoria T. , Amend Finn , Tran Liam , Hoffman Ryan N. , Rolandi Marco , Green Richard E. , Haussler David , Salama Sofie R. , Teodorescu Mircea 
Published: July 2022

ABSTRACTOrgan-on-a-chip systems combine microfluidics, cell biology, and tissue engineering to culture 3D organ-specific in vitro models that recapitulate the biology and physiology of their in vivo counterparts. Here, we have developed a multiplex platform that automates the culture of individual organoids in isolated microenvironments at user-defined media flow rates. Programmable workflows allow the use of multiple reagent reservoirs that may be applied to direct differentiation, study temporal variables, and grow cultures long term. Novel techniques in polydimethylsiloxane (PDMS) chip fabrication are described here that enable features on the upper and lower planes of a single PDMS substrate. RNA sequencing (RNA-seq) analysis of automated cerebral cortex organoid cultures shows benefits in reducing glycolytic and endoplasmic reticulum stress compared to conventional in vitro cell cultures.
SARS-CoV-2 causes brain inflammation via impaired neuro-immune interactions
Authors: Oka Naomi , Shimada Kazuya , Ishii Azusa , Kobayashi Nobuyuki , Kondo Kazuhiro 
Published: July 2022

AbstractThe brain inflammation that frequently occurs in SARS-CoV-2 is the cause of neurological complications1,2 and long COVID 3,4,5. However, many aspects of its pathogenesis mechanism remain unknown 6, 7 and no method of treatment has been established 8. By administering a non-proliferating adenovirus vector expressing SARS-CoV-2 S1 protein into the nasal cavity of mice, we developed a mouse model (S1 mouse) reproducing brain inflammation, fatigue, depressive symptoms, and lung inflammation. Having intracellular calcium elevating activity, S1 protein increased olfactory bulb apoptosis, and reduced the number of acetylcholine producing cells in the medial septal and the diagonal band of Broca as well as the amount of acetylcholine in the brain. This resulted in disrupting the cholinergic anti-inflammatory pathway (CAP) 9 and enhancing inflammation in the brain. Previously, nothing was known about anti-inflammatory factors in the CAP but we discovered that, in the inflammation occurring in the S1 mouse brain, the action of the RNA binding protein ZFP36 10 in degrading inflammatory cytokine mRNA was impaired.The symptoms exhibited by the S1 mouse were improved by administering donepezil, a drug with a cholinergic action used in the treatment of dementia. These findings clarify the mechanism of brain inflammation in COVID-19 and indicate the possibility of applying donepezil in the treatment of neurological complications in COVID-19 and long COVID.
RAV1 mediates cytokinin signalling for regulating primary root growth in Arabidopsis
Authors: Mandal Drishti , Datta Saptarshi , Ravindra Giridhar , Mondal Pranab Kumar , Chaudhuri Ronita Nag 
Published: July 2022

AbstractRoot growth dynamics is an outcome of complex hormonal crosstalk. The primary root meristem size for example, is determined by antagonizing actions of cytokinin and auxin. Here we show that RAV1, a member of the AP2/ERF family of transcription factors, mediates cytokinin signalling in roots to regulate meristem size. Therav1mutants have prominently longer primary roots, with a meristem that is significantly enlarged and contain higher cell numbers, compared to wild type. The mutant phenotype could be restored on exogenous cytokinin application or by inhibiting auxin transport. At the transcript level, primary cytokinin-responsive genes likeARR1, ARR12were significantly downregulated in the mutant root, indicating impaired cytokinin signalling. In concurrence, cytokinin induced regulation ofSHY2, an Aux/IAA gene, and auxin efflux carrierPIN1was hindered inrav1, leading to altered auxin transport and distribution. This effectively altered root meristem size in the mutant. Notably, CRF1 another member of the AP2/ERF family implicated in cytokinin signalling, is transcriptionally repressed by RAV1 to promote cytokinin response in roots. Further correlating RAV1 to cytokinin signalling, our results demonstrate that cytokinin upregulateRAV1expression through ARR1, during post-embryonic root development. Regulation ofRAV1expression is a part of secondary cytokinin response that eventually repressesCRF1to augment cytokinin signalling. To conclude, in Arabidopsis, RAV1 functions in a branch pathway downstream to ARR1 that regulatesCRF1expression to enhance cytokinin action during primary root development.
Plasma Metallomics Reveals Potential Biomarkers and Insights into the Ambivalent Associations of Elements with Acute Myocardial Infarction
Authors: Lim Si Ying , Dayal Hiranya , Seah Song Jie , Woon Tan Regina Pei , Low Zhi En , Carrasco Laserna Anna Karen , Tan Sock Hwee , Chan Mark Y. , Yau Li Sam Fong 
Published: July 2022

AbstractAcute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. Using a validated and efficient ICP-MS/MS-based workflow, a total of 30 metallomic features were profiled in a study comprising 101 AMI patients and 66 age-matched healthy controls. The metallomic features include 12 essential elements (Ca, Co, Cu, Fe, K, Mg, Mn, Na, P, S, Se, Zn), 8 non-essential/toxic elements (Al, As, Ba, Cd, Cr, Ni, Rb, Sr, U, V), and 10 clinically relevant element-pair product/ratios (Ca/Mg, Ca×P, Cu/Se, Cu/Zn, Fe/Cu, P/Mg, Na/K, Zn/Se). Preliminary linear regression with feature selection confirmed smoking status as a predominant determinant for the non-essential/toxic elements, and revealed potential routes of action. Univariate assessments with adjustments for covariates revealed insights into the ambivalent relationships of Cu, Fe, and P with AMI, while also confirming cardioprotective associations of Se. Also, beyond their roles as risk factors, Cu and Se may be involved in the response mechanism in AMI onset/intervention, as demonstrated via longitudinal data analysis with 2 additional time-points (1-/6-month follow-up). Finally, based on both univariate tests and multivariate classification modelling, potentially more sensitive markers measured as element-pair ratios were identified (e.g., Cu/Se, Fe/Cu). Overall, metallomics-based biomarkers may have utility for AMI prediction.
Integration of Clinicopathological And Genomic Features To Predict The Risk Stratification of TCGA Lung Adenocarcinoma And Lung Squamous Cell Carcinoma Patients
Authors: Sakman Mehmet Cihan , Zengin Talip , Önal-Süzek Tuğba 
Published: July 2022

AbstractBackgroundPredicting lung adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LUSC) risk cohorts is a crucial step in precision oncology. Currently, clinicians and patients are informed about the patient’s risk group via staging. Recently, several machine learning approaches are reported for the stratification of LUAD and LUSC patients, but there is no study comparatively assessing the integrated modeling of the clinicopathological and genetic data of these two lung cancer types so far.MethodsIn our study based on 1026 patients’ clinicopathological and somatically mutated gene features, a prognostic prediction model is implemented to rank the importance of features according to their impact on risk classification.FindingsBy integrating the clinicopathological features and somatically mutated genes of patients, we achieved the highest accuracy; %93 for LUAD and %89 for LUSC, respectively. Our second finding is that new prognostic genes such as KEAP1 for LUAD and CSMD3 for LUSC and new clinicopathological factors such as site of resection are significantly associated with the risk stratification and can be integrated into clinical decision making.ConclusionsIn current clinical practice, clinicians, and patients are informed about the patient’s risk group only with cancer staging. With the feature set we propose, clinicians and patients can assess the risk group of their patients according to the patient-specific clinical and molecular parameters. Using this machine learning model we are implementing a user-friendly web interface for clinicians and lung cancer patients to predict the risk stratification of individuals and to understand the underlying clinical and molecular mechanisms.