bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transcriptome of rat subcortical white matter and spinal cord after spinal injury and cortical stimulation
Authors: Kondiles Bethany R. , Wei Haichao , Chaboub Lesley S. , Horner Philip J. , Wu Jia Qian , Perlmutter Steve I. 
Published: July 2021

AbstractSpinal cord injury disrupts ascending and descending neural signals causing sensory and motor dysfunction. Neuromodulation with electrical stimulation is used in both clinical and research settings to induce neural plasticity and improve functional recovery following spinal trauma. However, the mechanisms by which electrical stimulation affects recovery remain unclear. In this study we examined the effects of cortical electrical stimulation following injury on transcription at several levels of the central nervous system. We performed a unilateral, incomplete cervical spinal contusion injury in rats and delivered stimulation for one week to the contralesional motor cortex to activate the corticospinal tract and other pathways. RNA was purified from bilateral subcortical white matter and 3 levels of the spinal cord. Here we provide the complete data set in the hope that it will be useful for researchers studying electrical stimulation as a therapy to improve recovery from the deficits associated with spinal cord injury.
A simple microscopy setup for visualizing cellular responses to DNA damage at particle accelerator facilities
Authors: Qian Haibin , Hoebe Ron A. , Faas Michel R. , van Goethem Marc Jan , van der Graaf Emiel R. , Meyer Christoph , Kiewiet Harry , Brandenburg Sytze , Krawczyk Przemek M. 
Published: July 2021

AbstractCellular responses to DNA double-strand breaks (DSBs) not only promote genomic integrity in healthy tissues, but also largely determine the efficacy of many DNA-damaging cancer treatments, including X-ray and particle therapies. A growing body of evidence suggests that activation of the mechanisms that detect, signal and repair DSBs may depend on the complexity of the initiating DNA lesions. Studies focusing on this, as well as on many other radiobiological questions, require reliable methods to induce DSBs of varying complexity, and to visualize the ensuing cellular responses. Accelerated particles of different energies and masses are exceptionally well suited for this task, due to the nature of their physical interactions with the intracellular environment, but visualizing cellular responses to particle-induced damage - especially in their early stages - at particle accelerator facilities, remains challenging. Here we describe a straightforward approach for real-time imaging of early response to particle-induced DNA damage. We rely on a transportable setup with an inverted fluorescence confocal microscope, tilted at a small angle relative to the particle beam, such that cells can be irradiated and imaged without any microscope or beamline modifications. Using this setup, we image and analyze the accumulation of fluorescently-tagged MDC1, RNF168 and 53BP1—key factors involved in DSB signalling—at DNA lesions induced by 254 MeV α-particles. Our results provide a demonstration of technical feasibility and reveal asynchronous initiation of accumulation of these proteins at different individual DSBs.
Tree-aggregated predictive modeling of microbiome data
Authors: Bien Jacob , Yan Xiaohan , Simpson Léo , Müller Christian L. 
Published: July 2021

AbstractModern high-throughput sequencing technologies provide low-cost microbiome survey data across all habitats of life at unprecedented scale. At the most granular level, the primary data consist of sparse counts of amplicon sequence variants or operational taxonomic units that are associated with taxonomic and phylogenetic group information. In this contribution, we leverage the hierarchical structure of amplicon data and propose a data-driven and scalable tree-guided aggregation framework to associate microbial subcompositions with response variables of interest. The excess number of zero or low count measurements at the read level forces traditional microbiome data analysis workflows to remove rare sequencing variants or group them by a fixed taxonomic rank, such as genus or phylum, or by phylogenetic similarity. By contrast, our framework, which we call (ee-ggregation of ompositional data), learns data-adaptive taxon aggregation levels for predictive modeling, greatly reducing the need for user-defined aggregation in preprocessing while simultaneously integrating seamlessly into the compositional data analysis framework. We illustrate the versatility of our framework in the context of large-scale regression problems in human gut, soil, and marine microbial ecosystems. We posit that the inferred aggregation levels provide highly interpretable taxon groupings that can help microbiome researchers gain insights into the structure and functioning of the underlying ecosystem of interest.
Automatic segmentation of skin cells in multiphoton data using multi-stage merging
Authors: Prinke Philipp , Haueisen Jens , Klee Sascha , Rizqie Muhammad Qurhanul , Supriyanto Eko , König Karsten , Breunig Hans Georg , Piątek Łukasz 
Published: July 2021

AbstractWe propose a novel automatic segmentation algorithm that separates the components of human skin cells from the rest of the tissue in fluorescence data of three-dimensional scans using non-invasive multiphoton tomography. The algorithm encompasses a multi-stage merging on preprocessed superpixel images to ensure independence from a single empirical global threshold. This leads to a high robustness of the segmentation considering the depth-dependent data characteristics, which include variable contrasts and cell sizes. The subsequent classification of cell cytoplasm and nuclei are based on a cell model described by a set of four features. Two novel features, a relationship between outer cell and inner nucleus (OCIN) and a stability index, were derived. The OCIN feature describes the topology of the model, while the stability index indicates segment quality in the multi-stage merging process. These two new features, combined with the local gradient magnitude and compactness, are used for the model-based fuzzy evaluation of the cell segments. We exemplify our approach on an image stack with 200 × 200 × 100 μm3, including the skin layers of the stratum spinosum and the stratum basale of a healthy volunteer. Our image processing pipeline contributes to the fully automated classification of human skin cells in multiphoton data and provides a basis for the detection of skin cancer using non-invasive optical biopsy.
Analysing omics data sets with weighted nodes networks (WNNets)
Authors: Tosadori Gabriele , Di Silvestre Dario , Spoto Fausto , Mauri Pierluigi , Laudanna Carlo , Scardoni Giovanni 
Published: July 2021

AbstractCurrent trends in biomedical research indicate data integration as a fundamental step towards precision medicine. In this context, network models allow representing and analysing complex biological processes. However, although effective in unveiling network properties, these models fail in considering the individual, biochemical variations occurring at molecular level. As a consequence, the analysis of these models partially loses its predictive power. To overcome these limitations, Weighted Nodes Networks (WNNets) were developed. WNNets allow to easily and effectively weigh nodes using experimental information from multiple conditions. In this study, the characteristics of WNNets were described and a proteomics data set was modelled and analysed. Results suggested that degree, an established centrality index, may offer a novel perspective about the functional role of nodes in WNNets. Indeed, degree allowed retrieving significant differences between experimental conditions, highlighting relevant proteins, and provided a novel interpretation for degree itself, opening new perspectives in experimental data modelling and analysis. Overall, WNNets may be used to model any high-throughput experimental data set requiring weighted nodes. Finally, improving the power of the analysis by using centralities such as betweenness may provide further biological insights and unveil novel, interesting characteristics of WNNets.
The association between environmental exposures to chlordanes, adiposity and diabetes-related features: a systematic review and meta-analysis
Authors: Mendes Vânia , Ribeiro Cláudia , Delgado Inês , Peleteiro Bárbara , Aggerbeck Martine , Distel Emilie , Annesi-Maesano Isabella , Sarigiannis Denis , Ramos Elisabete 
Published: July 2021

AbstractChlordane compounds (CHLs) are components of technical chlordane listed in the Stockholm convention on persistent organic pollutants identified as endocrine disrupting chemicals (EDCs) and may interfere with hormone biosynthesis, metabolism or action resulting in an unbalanced hormonal function. There is increasing scientific evidence showing EDCs as risk factors in the pathogenesis and development of obesity and obesity-related metabolic syndromes such as type 2 diabetes, but there is no systematized information on the effect of CHLs in humans. Our aim is to identify the epidemiological data on the association between CHLs with adiposity and diabetes using a systematic approach to identify the available data and summarizing the results through meta-analysis. We searched PubMed and Web of Science from inception up to 15 February 2021, to retrieve original data on the association between chlordanes, and adiposity or diabetes. For adiposity, regression coefficients and Pearson or Spearman correlation coefficients were extracted and converted into standardized regression coefficients. Data were combined using fixed effects meta-analyses to compute summary regression coefficients and corresponding 95% confidence intervals (95% CI). For the association between chlordanes and diabetes, Odds ratios (ORs) were extracted and the DerSimonian and Laird method was used to compute summary estimates and respective 95% CI. For both, adjusted estimates were preferred, whenever available. Among 31 eligible studies, mostly using a cross-sectional approach, the meta-analysis for adiposity was possible only for oxychlordane and transchlordane, none of them were significantly associated with adiposity [(β = 0.04, 95% CI 0.00; 0.07, I2 = 89.7%)] and (β = 0.02, 95% CI − 0.01; 0.06), respectively. For diabetes, the estimates were positive for all compounds but statistically significant for oxychlordane [OR = 1.96 (95% CI 1.19; 3.23)]; for trans-nonachlor [OR = 2.43 (95% CI 1.64; 3.62)] and for heptachlor epoxide [OR = 1.88 (95% CI 1.42; 2.49)]. Our results support that among adults, the odds of having diabetes significantly increase with increasing levels of chlordanes. The data did not allow to reach a clear conclusion regarding the association with adiposity.
Microarray-based selection of a serum biomarker panel that can discriminate between latent and active pulmonary TB
Authors: Li Zhihui , Hu Jianjun , Liu Pengchong , Cui Dan , Di Hongqin , Wu Shucai 
Published: July 2021

AbstractBacterial culture of M. tuberculosis (MTB), the causative agent of tuberculosis (TB), from clinical specimens is the gold standard for laboratory diagnosis of TB, but is slow and culture-negative TB cases are common. Alternative immune-based and molecular approaches have been developed, but cannot discriminate between active TB (ATB) and latent TB (LTBI). Here, to identify biomarkers that can discriminate between ATB and LTBI/healthy individuals (HC), we profiled 116 serum samples (HC, LTBI and ATB) using a protein microarray containing 257 MTB secreted proteins, identifying 23 antibodies against MTB antigens that were present at significantly higher levels in patients with ATB than in those with LTBI and HC (Fold change > 1.2; p < 0.05). A 4-protein biomarker panel (Rv0934, Rv3881c, Rv1860 and Rv1827), optimized using SAM and ROC analysis, had a sensitivity of 67.3% and specificity of 91.2% for distinguishing ATB from LTBI, and 71.2% sensitivity and 96.3% specificity for distinguishing ATB from HC. Validation of the four candidate biomarkers in ELISA assays using 440 serum samples gave consistent results. The promising sensitivity and specificity of this biomarker panel suggest it merits further investigation for its potential as a diagnostic for discriminating between latent and active TB.
Impact of quality of life related to foot problems: a case–control study
Authors: López-López Daniel , Pérez-Ríos Mónica , Ruano-Ravina Alberto , Losa-Iglesias Marta Elena , Becerro-de-Bengoa-Vallejo Ricardo , Romero-Morales Carlos , Calvo-Lobo Cesar , Navarro-Flores Emmanuel 
Published: July 2021

AbstractFoot problems are highly prevalent conditions, being a frequent reason for medical and podiatric consultation. The aim of this study was to compare the differences of quality of life (QoL) related to foot health in people with and without the presence of foot problems. A case–control study was carried out in an outpatient centre, where a clinician recorded data related to sociodemographic and clinical characteristics. In addition, self-reported data on foot health-related quality of life were recorded using the Spanish version of the Foot Health Status Questionnaire. The sample consisted of 498 participants (249 cases and 249 controls), with a median age of 30 years and an interquartile range of 23 years. The differences between the groups were statistically significant for gender, age, footwear, general health, foot health, and physical activity. Cases showed lower scores for the domain of footwear, physical activity and vitality compared to controls. Foot pathologies have a negative impact on quality of life related to foot health, and the domains of footwear, general health and physical activity seem to be the factors that are associated with the presence of alterations and foot deformities.
Improved optical properties of perovskite solar cells by introducing Ag nanopartices and ITO AR layers
Authors: Chen Yangxi , Du Chaoling , Sun Lu , Fu Tianyi , Zhang Ruxin , Rong Wangxu , Cao Shuiyan , Li Xiang , Shen Honglie , Shi Daning 
Published: July 2021

AbstractEmbedded noble metal nanostructures and surface anti-reflection (AR) layers affect the optical properties of methylammonium lead iodide (CH3NH3PbI3) perovskite solar cells significantly. Herein, by employing a combined finite element method and genetic algorithm approach, we report five different types of CH3NH3PbI3 perovskite solar cells by introducing embedded Ag nanoparticles within the CH3NH3PbI3 layer and/or top ITO cylinder grating as an AR layer. The maximum photocurrent was optimized to reach 23.56 mA/cm2, which was 1.09/1.17 times higher than Tran’s report/ flat cases. It is also comparable with values (23.6 mA/cm2) reported in the literature. The calculations of the electric field and charge carrier generation rate of the optimized solar cell further confirms this improvement than flat cases. It attributes to the synergistic effect of the embedded Ag nanoparticles and ITO AR layer. The results obtained herein hold great promise for future boosting the optical efficiency of perovskite solar cells.
Development of custom lead shield and strainer for targeted irradiation for mice in the gamma cell chamber
Authors: Hasan Nurhaslina , Sham Nur Fatihah Ronny , Karim Muhammad Khalis Abdul , Fuad Syed Baharom Syed Ahmad , Hasani Narimah Abdul Hamid , Omar Effat , Ibahim Mohammad Johari 
Published: July 2021

AbstractWe presented a development of a custom lead shield and mouse strainer for targeted irradiation from the gamma-cell chamber. This study was divided into two parts i.e., to (i) fabricate the shield and strainer from a lead (Pb) and (ii) optimize the irradiation to the mice-bearing tumour model with 2 and 8 Gy absorbed doses. The lead shielding was fabricated into a cuboid shape with a canal on the top and a hole on the vertical side for the beam path. Respective deliveries doses of 28 and 75 Gy from gamma-cell were used to achieve 2 and 8 Gy absorbed doses at the tumour sites.
Study on the optimal position of the roof low roadway based on the response surface methodology
Authors: Zhu Hongqing , Fang Shuhao , Huo Yujia , Liao Qi , Hu Lintao , Zhang Yilong , Li Feng 
Published: July 2021

AbstractFor determine the optimum position of the roof low roadway, the optimal solution is derived according to the response surface methodology. The UDEC numerical simulation of the overburden gives the porosity distribution of the strike fractured zone, the upper limit heights of the caving zone and the fractured zone are obtained as 18 m and 65 m, respectively. Based on the porosity distribution, the FLUENT numerical models of the goaf zone, air inlet roadway, air return roadway, working face and roof low roadway were established to simulate the gas concentration in the upper corner and gas drainage volume in roof low roadway during mining. Using the vertical and horizontal distance of the roof low roadway as the influencing factors, the experimental scheme of the position of the roof low roadway was designed according to the response surface method, and the response values were obtained from the FLUENT simulation experiments, predicting that the vertical and horizontal distances of the roof low roadway were 7.7 m and 5.9 m respectively when the interaction between the gas concentration in the upper corner and gas drainage volume in roof low roadway was optimal. Field tests showed that the average gas concentration in the upper corner and the average gas drainage volume in roof low roadway were 0.432% and 40.861 m3/min respectively, both of which were less than 10% of the error from the simulations. The design of the roof low roadway has effectively managed the gas accumulation problem in the upper corner.
Growth and autolysis of the kefir yeast Kluyveromyces marxianus in lactate culture
Authors: Lo Shou-Chen , Yang Chia-Yin , Mathew Dony Chacko , Huang Chieh-Chen 
Published: July 2021

AbstractKluyveromyces marxianus is a yeast that could be identified from kefir and can use a broad range of substrates, such as glucose and lactate, as carbon sources. The lactate produced in kefir culture can be a substrate for K. marxianus. However, the complexity of the kefir microbiota makes the traits of K. marxianus difficult to study. In this research, we focused on K. marxianus cultured with lactate as the sole carbon source. The optimal growth and released protein in lactate culture were determined under different pH conditions, and the LC–MS/MS-identified proteins were associated with the tricarboxylic acid cycle, glycolysis pathway, and cellular stress responses in cells, indicating that autolysis of K. marxianus had occurred under the culture conditions. The abundant glyceraldehyde-3-phosphate dehydrogenase 1 (GAP1) was cocrystallized with other proteins in the cell-free fraction, and the low transcription level of the GAP1 gene indicated that the protein abundance under autolysis conditions was dependent on protein stability. These results suggest that lactate induces the growth and autolysis of K. marxianus, releasing proteins and peptides. These findings can be fundamental for K. marxianus probiotic and kefir studies in the future.
Taxonomic changes in the gut microbiota are associated with cartilage damage independent of adiposity, high fat diet, and joint injury
Authors: Collins Kelsey H. , Schwartz Drew J. , Lenz Kristin L. , Harris Charles A. , Guilak Farshid 
Published: July 2021

AbstractLipodystrophic mice are protected from cartilage damage following joint injury. This protection can be reversed by the implantation of a small adipose tissue graft. The purpose of this study was to evaluate the relationship between the gut microbiota and knee cartilage damage while controlling for adiposity, high fat diet, and joint injury using lipodystrophic (LD) mice. LD and littermate control (WT) mice were fed a high fat diet, chow diet, or were rescued with fat implantation, then challenged with destabilization of the medial meniscus surgery to induce osteoarthritis (OA). 16S rRNA sequencing was conducted on feces. MaAslin2 was used to determine associations between taxonomic relative abundance and OA severity. While serum LPS levels between groups were similar, synovial fluid LPS levels were increased in both limbs of HFD WT mice compared to all groups, except for fat transplanted animals. The Bacteroidetes:Firmicutes ratio of the gut microbiota was significantly reduced in HFD and OA-rescued animals when compared to chow. Nine novel significant associations were found between gut microbiota taxa and OA severity. These findings suggest the presence of causal relationships the gut microbiome and cartilage health, independent of diet or adiposity, providing potential therapeutic targets through manipulation of the microbiome.
Forest canopy mitigates soil N2O emission during hot moments
Authors: Mander Ülo , Krasnova Alisa , Escuer-Gatius Jordi , Espenberg Mikk , Schindler Thomas , Machacova Katerina , Pärn Jaan , Maddison Martin , Megonigal J. Patrick , Pihlatie Mari , Kasak Kuno , Niinemets Ülo , Junninen Heikki , Soosaar Kaido 
Published: July 2021

AbstractRiparian forests are known as hot spots of nitrogen cycling in landscapes. Climate warming speeds up the cycle. Here we present results from a multi-annual high temporal-frequency study of soil, stem, and ecosystem (eddy covariance) fluxes of N2O from a typical riparian forest in Europe. Hot moments (extreme events of N2O emission) lasted a quarter of the study period but contributed more than half of soil fluxes. We demonstrate that high soil emissions of N2O do not escape the ecosystem but are processed in the canopy. Rapid water content change across intermediate soil moisture was a major determinant of elevated soil emissions in spring. The freeze-thaw period is another hot moment. However, according to the eddy covariance measurements, the riparian forest is a modest source of N2O. We propose photochemical reactions and dissolution in canopy-space water as reduction mechanisms.
Combined FGFR and Akt pathway inhibition abrogates growth of FGFR1 overexpressing EGFR-TKI-resistant NSCLC cells
Authors: Terp Mikkel G. , Jacobsen Kirstine , Molina Miguel Angel , Karachaliou Niki , Beck Hans C. , Bertran-Alamillo Jordi , Giménez-Capitán Ana , Cardona Andrés F. , Rosell Rafael , Ditzel Henrik J. 
Published: July 2021

AbstractEGFR tyrosine kinase inhibitor (TKI) resistance in non-small cell lung cancer (NSCLC) patients is inevitable. Identification of resistance mechanisms and corresponding targeting strategies can lead to more successful later-line treatment in many patients. Using spectrometry-based proteomics, we identified increased fibroblast growth factor receptor 1 (FGFR1) expression and Akt activation across erlotinib, gefitinib, and osimertinib EGFR-TKI-resistant cell line models. We show that while combined EGFR-TKI and FGFR inhibition showed some efficacy, simultaneous inhibition of FGFR and Akt or PI3K induced superior synergistic growth inhibition of FGFR1-overexpressing EGFR-TKI-resistant NSCLC cells. This effect was confirmed in vivo. Only dual FGFR and Akt inhibition completely blocked the resistance-mediating signaling pathways downstream of Akt. Further, increased FGFR1 expression was associated with significantly lower PFS in EGFR-TKI-treated NSCLC patients, and increased FGFR1 were demonstrated in a few post- vs. pre-EGFR-TKI treatment clinical biopsies. The superior therapeutic benefit of combining FGFR and Akt inhibitors provide the rationale for clinical trials of this strategy.