bluuebunny/crossref_metadata_2025_split huggingface dataset:
A transcriptome atlas of leg muscles from healthy human volunteers reveals molecular and cellular signatures associated with muscle location
Authors: Abbassi-Daloii Tooba , el Abdellaoui Salma , Voortman Lenard M. , Veeger Thom , Cats Davy , Mei Hailiang , Meuffels Duncan E. , van Arkel Ewoud , ’t Hoen Peter A.C , Kan Hermien E. , Raz Vered 
Published: June 2022

AbstractSkeletal muscles support the stability and mobility of the skeleton but differ in biomechanical properties and physiological functions. The intrinsic factors that regulate muscle-specific characteristics are poorly understood. To study these, we constructed a large atlas of RNA-seq profiles from six leg muscles and two locations from one muscle, using biopsies from 20 healthy young males. We identified differential expression patterns and cellular composition across the seven tissues using three bioinformatics approaches confirmed by large-scale newly developed quantitative immune-histology procedures. With all three procedures, the muscle samples clustered into three groups congruent with their anatomical location. Concomitant with genes marking oxidative metabolism, genes marking fast- or slow-twitch myofibers differed between the three groups. The groups of muscles with higher expression of slow-twitch genes were enriched in endothelial cells and showed higher capillary content. In addition, expression profiles of Homeobox (HOX) transcription factors differed between the three groups and were confirmed by spatial RNA hybridization. We created an open-source graphical interface to explore and visualize the leg muscle atlas (https://tabbassidaloii.shinyapps.io/muscleAtlasShinyApp/). Our study reveals molecular specialization of human leg muscles and provides a novel resource to study muscle-specific molecular features, which could be linked with (patho)physiological processes.
PPIX-binding Proteins Reveal Porphyrin Synthesis and Ferroptosis Link
Authors: Lynch John , Wang Yao , Li Yuxin , Kavdia Kanisha , Fukuda Yu , Ranjit Sabina , Robinson Camenzind G. , Grace Christy R. , Xia Youlin , Peng Junmin , Schuetz John D. 
Published: June 2022

AbstractAll aerobic organisms require the cofactor heme to survive, but its synthesis requires formation of a potentially toxic intermediate protoporphyrin IX (PPIX). Little is known about the extent of PPIX’s cellular interactions. Here, we report the development of PPB, a biotin-conjugated, PPIX-probe that captures proteins capable of interacting with PPIX. Quantitative proteomics with PPB identified common proteins among a diverse panel of mammalian cell lineages. Pathway and quantitative difference analysis revealed PPB-bound proteins related to iron and heme metabolism and suggested that these processes might be altered by heme/porphyrin synthesis. We show that increased heme/porphyrin synthesis in cells promotes ferroptosis that is pharmacologically distinct from canonical ferroptosis driven by erastin, an inhibitor of the cystine/glutamate antiporter. Proteomic data derived from PPB revealed an interactor, PRDX3, a mitochondrial peroxidase, that modulated heme/porphyrin biosynthesis driven ferroptosis. Consistent with a role in porphyrin-induced ferroptotic death targeted gene knockdown of PRDX3, but not peroxidases, PRDX1 or 2, enhanced porphyrin-induced ferroptotic death. The relationship between increased heme/porphyrin synthesis and ferroptosis was also found in a ferrochelatase-deficient T-lymphoblastoid leukemia cell line, suggesting potential strategy for treating certain cancers. We demonstrate that when the PPB probe is coupled with unbiased proteomics a previously unreported relationship between heme/porphyrin synthesis, and ferroptosis was discovered.
Radiation therapy promotes unsaturated fatty acids to maintain survival of glioblastoma
Authors: De Martino Mara , Daviaud Camille , Minns Hanna E. , Attarwala Nabeel , Chen Qiuying , Dephoure Noah , Choi Seung-Won , Rabadàn Raùl , Gartrell Robyn D. , Laiakis Evagelia C. , Vanpouille-Box Claire 
Published: June 2022

ABSTRACTPurposeRadiation therapy (RT) is essential for the management of glioblastoma (GBM). However, GBM frequently relapses within the irradiated margins, thus suggesting that RT might stimulate mechanisms of resistance that limits its efficacy. GBM is recognized for its metabolic plasticity, but whether RT-induced resistance relies on metabolic adaptation remains unclear.MethodsWe analyzedin vitroextracellular flux and profiled targeted metabolites as well as free fatty acids in two syngenic models of glioblastomas 24hrs post RT. Metabolic adaptation of irradiated GBM were confirmedin vivoby mass spectrometry imaging. The role of the fatty acid synthase (FASN) in RT-induced lipid metabolites was assessed by genetical and pharmacological inhibition ofFasnin irradiated GBM cells. The impact of FASN-mediated lipids on endoplasmic reticulum (ER) stress and apoptosis of irradiated GBM cells were performed by transmission electronic microscopy, western blot, clonogenic assay and flow cytometry. Inhibition of FASN combined with focal RT was assessed in mice. Analysis of a public dataset of GBM patients was performed to correlate preclinical findings.ResultsHere, we showin vitroandin vivothat irradiated GBM tumors switch their metabolic program to accumulate lipids, especially unsaturated fatty acids. This resulted in an increase formation of lipid droplets to prevent ER stress. We uncovered that FASN is critical for lipid accumulation of irradiated GBM and demonstrate that genetic suppression and pharmacological inhibition of FASN lead to mitochondrial dysfunction and apoptosis. Combination of FASN inhibition with focal RT improved the median survival of GBM-bearing mice. Supporting the translational value of these findings, retrospective analysis of the GLASS consortium dataset of matched GBM patients revealed an enrichment in lipid metabolism signature in recurrent GBM compared to primary.ConclusionsOverall, these results demonstrate that RT drives GBM resistance by generating a lipogenic environment permissive to GBM survival. Targeting lipid metabolism might be required to develop more effective anti-GBM strategies.
Metagenomic classification with KrakenUniq on low-memory computers
Authors: Pockrandt Christopher , Zimin Aleksey V. , Salzberg Steven L. 
Published: June 2022

AbstractKraken and KrakenUniq are widely-used tools for classifying metagenomics sequences. A key requirement for these systems is a database containing all k-mers from all genomes that the users want to be able to detect, where k = 31 by default. This database can be very large, easily exceeding 100 gigabytes (GB) and sometimes 400 GB. Previously, Kraken and KrakenUniq required loading the entire database into main memory (RAM), and if RAM was insufficient, they used memory mapping, which significantly increased the running time for large datasets. We have implemented a new algorithm in KrakenUniq that allows it to load and process the database in chunks, with only a modest increase in running time. This enhancement now makes it feasible to run KrakenUniq on very large datasets and huge databases on virtually any computer, even a laptop, while providing the same very high classification accuracy as the previous system.
High emotional reactivity is associated with activation of a molecularly distinct hippocampal-amygdala circuit modulated by the glucocorticoid receptor
Authors: Wei Qiang , Kumar Vivek , Moore Shannon , Li Fei , Murphy Geoffrey G. , Watson Stanley J. , Akil Huda 
Published: June 2022

AbstractEmotions are characterized not only by their valence but also by whether they are stable or labile. Yet, we do not understand the molecular or circuit mechanisms that control the dynamic nature of emotionality. We have shown that glucocorticoid receptor overexpression in the forebrain (GRov) leads to a highly reactive mouse with increased anxiety behavior coupled with greater swings in emotional responses. This phenotype is established early in development and persists into adulthood. However, the neural circuitry mediating this lifelong emotional lability remains unknown. In the present study, optogenetic stimulation in ventral dentate gyrus (vDG) of GRov mice led to a greater range and a prolonged duration of anxiety behavior. cFos expression showed that the amplified behavioral response to vDG activation in GRov mice is coupled to increased neuronal activity in specific brain regions. Relative to wild type mice, GRov mice displayed glutamatergic/GABAergic activation imbalance in ventral CA1 (vCA1) and selectively increased glutamatergic activation in the basal posterior amygdaloid complex. Fluorescence in situ hybridization chain reaction studies showed that forebrain GR overexpression led to increased activation of molecularly distinct subpopulations of neurons within the hippocampus and the posterior basolateral amygdala (pBLA). Increased cFos labeling was observed in the Calbindin 1 (Calbn1+) glutamatergic neurons in vCA1 and in the DARPP-32/Ppp1r1b+ glutamatergic neurons in pBLA. We propose that a molecularly distinct hippocampal-amygdala circuit is shaped by stress early in life and tunes the dynamics of emotional responses.
Improving classification and reconstruction of imagined images from EEG signals
Authors: Shimizu Hirokatsu , Srinivasan Ramesh 
Published: June 2022

AbstractDecoding brain activity related to specific tasks, such as imagining something, is important for brain computer interface (BCI) control. While decoding of brain signals, such as functional magnetic resonance imaging (fMRI) signals and electroencephalography (EEG) signals, during observing visual images and while imagining images has been previously reported, further development of methods for improving training, performance, and interpretation of brain data was the goal of this study. We applied a Sinc-EEGNet to decode brain activity during perception and imagination of EEG stimuli, and added an attention module to extract the importance of each electrode or frequency band. We also reconstructed images from brain activity by using a generative adversarial network (GAN). By combining the EEG recorded during a visual task (perception) and imagination task, we have successfully boosted the accuracy of classifying EEG data in the imagination task and improved the quality of reconstruction by GAN. Our result indicates that the brain activity evoked during the visual task is present in the imagination task and can be used for better classification of the imagined image. By using the attention module, we can derive the spatial weights in each frequency band and contrast spatial or frequency importance between tasks from our model. Imagination tasks are classified by low frequency EEG signals over temporal cortex, while perception tasks are classified by high frequency EEG signals over occipital and frontal cortex. Combining data sets in training results in a balanced model improving classification of the imagination task without significantly changing performance in the visual task. Our approach not only improves performance and interpretability but also potentially reduces the burden on training since we can improve the accuracy of classifying a relatively hard task with high variability (imagination) by combining with the data of the relatively easy task, observing visual images.
Structural and functional characterization of TraI from pKM101 reveals basis for DNA processing
Authors: Breidenstein Annika , ter Beek Josy , Berntsson Ronnie P-A 
Published: June 2022

AbstractType 4 Secretion Systems (T4SSs) are large and versatile protein machineries that facilitate the spread of antibiotic resistance and other virulence factors via horizontal gene transfer. Conjugative T4SSs depend on relaxases to process the DNA in preparation for transport. TraI from the well-studied conjugative plasmid pKM101 is one such relaxase. Here, we report the crystal structure of the trans-esterase domain of TraI in complex with its substrateoriTDNA, highlighting the conserved DNA binding mechanism of conjugative relaxases. Additionally, we present an apo structure of the trans-esterase domain of TraI that includes most of the flexible thumb region. This allows us for the first time to visualize the large conformational change of the thumb domain upon DNA binding. We also characterize the DNA binding, nicking and religation activity of the trans-esterase domain, helicase domain and full-length TraI. Unlike previous indications in the literature, our results reveal that the TraI trans-esterase domain from pKM101 behaves in a conserved manner with its homologs from the R388 and F plasmids.
Stability analysis of Mars soft landing under uncertain landing conditions and two landing strategies
Authors: Ding Jianzhong , Liu Xueao , Dong Yang , Wang Chunjie 
Published: June 2022

Purpose
The purpose of this paper is to study the landing performance of the Mars lander considering uncertain landing conditions under two landing modes.

Design/methodology/approach
A dynamics analysis model for the legged Mars lander is established for landing simulation, where the nonlinear large-deformation flexible buffer rods are equivalently modeled with a rigid-body mechanism with external forces and movement limit. Sensitivities of the landing stability to various landing conditions are analyzed using the Quasi–Monte-Carlo-based Sobol’ method and computer-aided landing simulations. Moreover, based on the results of sensitivity analysis, sensitive parameters are selected for estimating the safe boundaries for stability indices of rotation and clearance.

Findings
It can be concluded from this study that the lander has excellent ability against overturning. The shutdown-before-touchdown strategy helps to maintain than landing pose, and the shutdown-at-touchdown strategy helps to prevent the nozzle from colliding with the surface of Mars.

Practical implications
This study provides a theoretical reference to choose the better landing strategies for Mars landers considering uncertain landing conditions.

Originality/value
A parameterized dynamics Mars lander model and a simplification method are proposed to simulate the landing on Mars. Uncertain landing conditions are parameterized and considered in the dynamics model. Sensitivity analysis and safe boundary methods are used to compare the landing performances with two landing strategies.
Forecasting with Bayesian vector autoregressive models: comparison of direct and iterated multistep methods
Authors: Sugita Katsuhiro 
Published: June 2022

PurposeThe paper compares multi-period forecasting performances by direct and iterated method using Bayesian vector autoregressive (VAR) models.Design/methodology/approachThe paper adopts Bayesian VAR models with three different priors – independent Normal-Wishart prior, the Minnesota prior and the stochastic search variable selection (SSVS). Monte Carlo simulations are conducted to compare forecasting performances. An empirical study using US macroeconomic data are shown as an illustration.FindingsIn theory direct forecasts are more efficient asymptotically and more robust to model misspecification than iterated forecasts, and iterated forecasts tend to bias but more efficient if the one-period ahead model is correctly specified. From the results of the Monte Carlo simulations, iterated forecasts tend to outperform direct forecasts, particularly with longer lag model and with longer forecast horizons. Implementing SSVS prior generally improves forecasting performance over unrestricted VAR model for either nonstationary or stationary data.Originality/valueThe paper finds that iterated forecasts using model with the SSVS prior generally best outperform, suggesting that the SSVS restrictions on insignificant parameters alleviates over-parameterized problem of VAR in one-step ahead forecast and thus offers an appreciable improvement in forecast performance of iterated forecasts.
Total quality management in Peruvian goods companies during the COVID-19 pandemic
Authors: Benzaquen Jorge Benny , Narro Juan Pedro 
Published: June 2022

PurposeThe aim of this research is to empirically assess the nine dimensions of the Total Quality Management (TQM) model, which have been categorized into four blocks: the top management block, the supplier block, the process management block and the customer block. The nine dimensions represent key strategic activities of company performance. A comparative analysis of companies with ISO 9001 certification and those without certification in a developing country during the COVID-19 pandemic is carried out.Design/methodology/approachA survey was administered to the management of 259 Peruvian goods companies (in the mining, repair and manufacturing sectors) during the COVID-19 pandemic. The survey consisted of 35 Likert-scale items, which were grouped into the following nine TQM dimensions: Top management (leadership), quality planning, quality audit and assessment, product design, suppliers' quality management, process control and improvement, education and training, quality circles and focus on customer satisfaction. Then, Cronbach's alpha, the Kolmogorov–Smirnov test, the Mann–Whitney U test and means were computed for each of the dimensions. This analysis made it possible to estimate significant differences between ISO 9001 certified and non-certified goods companies in terms of the dimensions.FindingsThe results showed that, for ISO 9001 certified companies, the averages for all of the dimensions were significantly different from those of non-certified companies, except for the education and training dimension. ISO 9001 certified companies scored higher than non-certified companies in the TQM dimensions. For both certified and non-certified companies, the leadership dimension had the highest average and the quality circles dimension had the lowest average.Originality/valueThis study addresses two main gaps highlighted in the research on quality management: the application of Quality Management Systems (QMS) in developing countries like Peru, and the impact of ISO 9001 on the performance of goods companies during the COVID-19 pandemic.
The impact of priority issues for publicly traded companies in corporate governance (CG) rating notes: an empirical study in Turkey
Authors: Kartal Mustafa Tevfik , Kılıç Depren Serpil , Depren Özer 
Published: June 2022

Purpose
This paper aims to determine priority issues in the corporate governance (CG) principles to increase CG rating notes of publicly traded companies.

Design/methodology/approach
This study defines the priority issues for publicly traded companies that should be focused to increase the CG rating notes. In this context, this study considers the companies in Borsa Istanbul CG index (XKURY), use data for 2018, 2019, 2020, and applies machine learning algorithms.

Findings
Overall, importance of each CG principle changes for the CG rating notes; first five CG principles in terms of significance have a total of 43.6% importance for the CG rating notes; following a straight-line approach in completing deficiencies of the CG principles cannot help increase the CG rating notes. Hence, empirical results highlight the impact of the most significant CG principles in terms of the CG rating notes that should be focused on by publicly traded companies so that CG ratings can be increased.

Research limitations/implications
This study uses Turkey data and considers publicly traded companies in the XKURY index. The main cause of this condition is that consolidated data of compliance report format for all publicly traded companies cannot be obtained.

Practical implications
The publicly traded companies can increase the CG rating notes by considering the results of this study while focusing on priority issues in the CG principles.

Social implications
The study determines the most important CG principles that companies can focus on, highlights the importance of usage of machine learning algorithms in determining the most influential CG principles in terms of the CG rating notes and reflects on the difficulties for gathering consolidated CG principles compliance reporting data for all publicly traded companies. Hence, societies can have better companies that are ruled more efficiently and corporately by increasing their compliance with the CG principles.

Originality/value
To the best of the authors’ knowledge, this is the first empirical study that determines the priority issues to increase the CG rating notes of publicly traded companies based on the new CG principles compliance reporting scheme in Turkey. Following this aim, machine learning algorithms, which can present better results with regard to most of the econometric models, are used in this study.
The return volatility and shock transmission patterns of chosen S&P and Dow Jones sustainability indices and their conventional counterpart
Authors: Almansour Bashar Yaser , Alshater Muneer M. , Marashdeh Hazem , Dhiaf Mohamed , Atayah Osama F. 
Published: June 2022

Purpose
The purpose of this study is to investigate the dynamic return volatility connectedness among S&P, Dow Jones (DJ) sustainability indices and their conventional counterparts.

Design/methodology/approach
This study uses time-series daily data for 10 S&P and DJ indices over the period of December 1, 2012 to December 8, 2021. The authors divide the data into three periods; over the whole sample, pre and during the Covid-19 pandemic. The study adopts the connectedness approach developed by Diebold and Yilmaz (2014).

Findings
The results reveal a high degree of connectedness between S&P and DJ indices and their relative sustainability indices over the whole sample, pre and during the Covid-19 pandemic, indicating that the sustainability indices converge toward their conventional peers. The results further show that the conventional S&P500, S&P Euro 50 and DJWI are the main transmitters of shocks, whereas the S&P400, S&P500 and S&P50 sustainability indices are the main receivers of shocks.

Originality/value
The study provides novel insights in terms of shock transmission of S&P and DJ sustainability indices and their conventional counterparts, where there is a lack of investigation of the connectedness between indices in this field.

Practical implications
The study has significant implications for investors and portfolio managers to devise portfolio strategies to minimize risk and trace the cause, the direction and the magnitude of risk transmission among different indices. Also, the results help policymakers to manage diverse types of risks associated with S&P and DJ indices. Finally, faith-based and ethical investors would be able to predict the pairwise spillover connectedness between these indices.