bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing the impact of land use land cover change on regulatory ecosystem services of subtropical scrub forest, Soan Valley Pakistan
Authors: Ghafoor Gul Zareen , Sharif Faiza , Shahid Memuna Ghafoor , Shahzad Laila , Rasheed Rizwan , Khan Amin Ul Haq 
Published: June 2022

AbstractThis study investigated the effect of land use land cover (LULC) changes on carbon sequestration in the Hayat-ul-Mir subtropical scrub reserve forest, Pakistan. Supervised maximum likelihood classification of Landsat satellite imagery was done to assess spatio-temporal changes in LULC during 2007, 2013 and 2019. The CA–Markov model was used to simulate LULC of 2030. Spatial LULC data and carbon pools data was processed in Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) carbon model to investigate the effect of LULC on future carbon dynamics. The analysis revealed increase in cover of A. modesta and O. ferruginea and decrease in agriculture, built up and barren area of forest during 2007–2019 and 2030. The analysis also showed that the forest would additionally sequester 111 Mg C with an overall Net Present Value of $4112.05 in year 2030. The analysis revealed LULC changes on 25% area with increase and decrease in the value of ecosystem service (at some location) from carbon storage and loss as CO2 emissions respectively depending on the type of LULC converted. The study is helpful in identifying areas of potential carbon sequestration to maximize net benefits from management interventions.
The metaxenia effects of different pollen grains on secondary metabolites enzymes and sugars of ‘Piarom’ date palm fruit
Authors: Shahsavar Ali Reza , Shahhosseini Asma 
Published: June 2022

AbstractIn this research, the characteristics of pollen were studied in eight pollinating cultivars of date palm, namely, ‘Shahani’, ‘Kabkab’, ‘Zahedi’, ‘Beraem’, ‘Faryab’, ‘Sheikhali’, ‘Fard’ and ‘Jarvis’. The characteristics were compared and metaxenia effects were evaluated on secondary metabolites, enzymes and other biochemical compounds of ‘Piarom’ date fruits. The evaluations were carried out during four stages of fruit growth and development. The pollen of these eight pollinating cultivars were compared in terms of carbohydrates, proteins, starch, total phenol, flavonoids, pectin methyl esterase, and amylase enzymes. According to the results, the pollen of ‘Sheikhali’, ‘Fard’, ‘Zahedi’ and ‘Shahani’ cultivars contained more of the above compounds, compared to the other cultivars. Regarding the effects of pollen on the composition of ‘Piarom’ date fruits, ‘Fard’ and ‘Sheikhali’ pollen produced the lowest amount of soluble tannin, which resulted in a better quality of ‘Piarom’ date fruits. Pollen was also obtained from ‘Sheikhali’ and ‘Fard’ cultivars for evaluations, showing that they led to the highest amounts of glucose and fructose in the fruits. Regarding the sucrose amount, ‘Jarvis’ and ‘Shikhali’ produced the best results. Pollen of ‘Sheikhali’ and ‘Fard’ cultivars caused the lowest amount of chlorophyll at the different stages of fruit growth, indicating a better decomposition of fruit chlorophyll and, as a result, better fruit quality. Pollen of ‘Sheikhali’ and ‘Fard’ cultivars produced the highest amounts of secondary metabolites such as total phenol, carotenoids and anthocyanin at the different stages of fruit development. The pollen of ‘Fard’ and ‘Sheikhali’ cultivars produced the highest levels of polygalacturonase, cellulase and invertase enzymes at different growth stages of the ‘Piarom’ date fruit. Regarding cellulase enzyme, fruits of the ‘Zahedi’ cultivar had more cellulase than the fruits of ‘Sheikhali’. In general, the pollen of ‘Fard’ and ‘Sheikhali, in comparison with other cultivars, improved the quantity and quality of ‘Piarom’ date fruits, due to their metaxenia properties.
Predicting driving speed from psychological metrics in a virtual reality car driving simulation
Authors: Ju Uijong , Williamson John , Wallraven Christian 
Published: June 2022

AbstractWhy do some people tend to drive faster than others? Personality characteristics such as the evaluation of risk to oneself or to others, impulsivity, adherence to norms, but also other personal factors such as gender, age, or driving experience all may play a role in determining how fast people drive. Since driving speed is a critical factor underlying accident prevalence, identifying the psychological metrics to predict individual driving speed is an important step that could aid in accident prevention. To investigate this issue, here, we used an immersive virtual reality driving simulation to analyze average driving speed. A total of 124 participants first took a comprehensive set of personality and background questionnaires and a behavioral risk-taking measure. In the virtual reality experiment, participants were required to navigate a difficult driving course in a minimally-restricted, non-urban setting in order to provide baseline results for speed selection. Importantly, we found that sensation seeking and gender significantly predicted the average driving speed, and that sensation seeking and age were able to predict the maximum driving speed.
Biosynthesis of exopolysaccharide from waste molasses using Pantoea sp. BCCS 001 GH: a kinetic and optimization study
Authors: Niknezhad Seyyed Vahid , Kianpour Sedigheh , Jafarzadeh Sina , Alishahi Mohsen , Najafpour Darzi Ghasem , Morowvat Mohammad Hossein , Ghasemi Younes , Shavandi Amin 
Published: June 2022

AbstractThe bacterium Pantoea sp. BCCS 001 GH produces an exopolysaccharide (EPS) named Pantoan through using sugar beet molasses (SBM) as an inexpensive and widely available carbon source. This study aims to investigate the kinetics and optimization of the Pantoan biosynthesis using Pantoea sp. BCCS 001 GH in submerged culture. During kinetics studies, the logistic model and Luedeking–Piret equation are precisely fit with the obtained experimental data. The response surface methodology (RSM)-central composite design (CCD) method is applied to evaluate the effects of four factors (SBM, peptone, Na2HPO4, and Triton X-100) on the concentration of Pantoan in batch culture of Pantoea sp. BCCS 001 GH. The experimental and predicted maximum Pantoan production yields are found 9.9 ± 0.5 and 10.30 g/L, respectively, and the best prediction factor concentrations are achieved at 31.5 g/L SBM, 2.73 g/L peptone, 3 g/L Na2HPO4, and 0.32 g/L Triton X-100 after 48 h of submerged culture fermentation, at 30 °C. The functional groups and major monosaccharides (glucose and galactose) of a purified Pantoan are described and confirmed by 1HNMR and FTIR. The produced Pantoan is also characterized by thermogravimetric analysis and the rheological properties of the biopolymer are investigated. The present work guides the design and optimization of the Pantoea sp. BCCS 001 GH culture media, to be fine-tuned and applied to invaluable EPS, which can be applicable in food and biotechnology applications.
Design of a multi-epitope vaccine candidate against Brucella melitensis
Authors: Li Min , Zhu Yuejie , Niu Ce , Xie Xinru , Haimiti Gulishati , Guo Wenhong , Yu Mingkai , Chen Zhiqiang , Ding Jianbing , Zhang Fengbo 
Published: June 2022

AbstractBrucella is a typical facultative intracellular bacterium that can cause zoonotic infections. For Brucella, it is difficult to eliminate with current medical treatment. Therefore, a multi-epitope vaccine (MEV) should be designed to prevent Brucella infection. For this purpose, we applied the reverse vaccinology approach from Omp10, Omp25, Omp31 and BtpB. Finally, we obtained 13 cytotoxic T lymphocyte (CTL) epitopes, 17 helper T lymphocyte (HTL) epitopes, 9 linear B cell epitopes, and 2 conformational B cell epitopes for further study. To keep the protein folded normally, we linked AAY, GPGPG, and KK to CTL epitopes, HTL epitopes, and B cell epitopes, respectively. The N-terminal of the vaccine peptide is supplemented with appropriate adjuvants to enhance immunogenicity. To evaluate its immunogenicity, stability, safety, and feasibility, a final MEV containing 806 amino acids was constructed by linking linkers and adjuvants. In addition, molecular docking and molecular dynamics simulations were performed to verify the affinity and stability of the MEV-TLR4. Then, codon adaptation and in silico cloning studies were carried out to identify the possible codons for expressing the MEV. In animal experiments, the results demonstrated that the MEV had high immunogenicity. Collectively, this study provided a theoretical basis for the development of a Brucella vaccine.
σ-Aromaticity in planar pentacoordinate aluminium and gallium clusters
Authors: Kalita Amlan J. , Sarmah Kangkan , Yashmin Farnaz , Borah Ritam R. , Baruah Indrani , Deka Rinu P. , Guha Ankur K. 
Published: June 2022

AbstractPlanar hypercoordinate structures are gaining immense attention due to the shift from common paradigm. Herein, our high level ab initio calculations predict that planar pentacoordinate aluminium and gallium centres in Cu5Al2+and Cu5Ga2+clusters are global minima in their singlet ground states. These clusters are thermodynamically and kinetically very stable. Detailed electronic structure analyses reveal the presence of σ-aromaticity which is the driving force for the stability of the planar form.
Data-driven spatiotemporal assessment of the event-size distribution of the Groningen extraction-induced seismicity catalogue
Authors: Muntendam-Bos A. G. , Grobbe N. 
Published: June 2022

AbstractFor induced seismicity, the non-stationary, heterogeneous character of subsurface stress perturbations can be a source of spatiotemporal variations in the scaling of event sizes; one of the critical parameters controlling seismic hazard and risk. We demonstrate and test a systematic, statistical, penalized-likelihood approach to analysing both spatial and temporal variations in event size distributions. The methodology used is transferable to the risk analysis of any subsurface operation, especially for small earthquake catalogues. We explore the whole solution space and circumvent conventional, arbitrary choices that require a priori knowledge of these variations. We assess the effect of possible bias in the derivation, e.g., due to tapering of the earthquake-size distribution, correlation between the b-value and the magnitude of completeness and correlation between the b-value and the largest magnitude observed. We analyse the spatiotemporal variations in the earthquake-size distribution of the Groningen induced seismicity catalogue (December 1991–November 16, 2021). We find statistically significant spatial variations without any compelling, statistical evidence of a temporal variation. Furthermore, we find that the largest magnitudes observed are inconsistent with the sampling statistics of an unconstrained earthquake-size distribution. Current risk assessment models likely overestimate the probability of larger magnitude events (M ≥ 3.0) and thus the risk posed.
A computerized diagnostic model for automatically evaluating placenta accrete spectrum disorders based on the combined MR radiomics-clinical signatures
Authors: Zhu Hao , Yin Xuan , Wang Haijie , Wang Yida , Liu Xuefen , Wang Chenglong , Li Xiaotian , Lu Yuanyuan , Yang Guang , Zhang He 
Published: June 2022

AbstractWe aimed to establish a computerized diagnostic model to predict placenta accrete spectrum (PAS) disorders based on T2-weighted MR imaging. We recruited pregnant women with clinically suspected PAS disorders between January 2015 and December 2018 in our institution. All preoperative T2-weighted imaging (T2WI) MR images were manually outlined on the picture archive communication system terminal server. A nnU-Net network for automatic segmentation and the corresponding radiomics features extracted from the segmented region were applied to build a radiomics-clinical model for PAS disorders identification. Taking the surgical or pathological findings as the reference standard, we compared this computerized model’s diagnostic performance in detecting PAS disorders. In the training cohort, our model combining both radiomics and clinical characteristics yielded an accuracy of 0.771, a sensitivity of 0.854, and a specificity of 0.750 in identifying PAS disorders. In the testing cohort, this model achieved a segmentation mean Dice coefficient of 0.890 and yielded an accuracy of 0.825, a sensitivity of 0.830 and a specificity of 0.822. In the external validation cohort, this computer-aided diagnostic model yielded an accuracy of 0.690, a sensitivity of 0.929 and a specificity of 0.467 in identifying placenta increta. In the present study, a machine learning model based on preoperative T2WI-based imaging had high accuracy in identifying PAS disorders in respect of surgical and histological findings.
Liver-derived cell lines from cavefish Astyanax mexicanus as an in vitro model for studying metabolic adaptation
Authors: Krishnan Jaya , Wang Yan , Kenzior Olga , Hassan Huzaifa , Olsen Luke , Tsuchiya Dai , Kenzior Alexander , Peuß Robert , Xiong Shaolei , Wang Yongfu , Zhao Chongbei , Rohner Nicolas 
Published: June 2022

AbstractCell lines have become an integral resource and tool for conducting biological experiments ever since the Hela cell line was first developed (Scherer et al. in J Exp Med 97:695–710, 1953). They not only allow detailed investigation of molecular pathways but are faster and more cost-effective than most in vivo approaches. The last decade saw many emerging model systems strengthening basic science research. However, lack of genetic and molecular tools in these newer systems pose many obstacles. Astyanax mexicanus is proving to be an interesting new model system for understanding metabolic adaptation. To further enhance the utility of this system, we developed liver-derived cell lines from both surface-dwelling and cave-dwelling morphotypes. In this study, we provide detailed methodology of the derivation process along with comprehensive biochemical and molecular characterization of the cell lines, which reflect key metabolic traits of cavefish adaptation. We anticipate these cell lines to become a useful resource for the Astyanax community as well as researchers investigating fish biology, comparative physiology, and metabolism.
Perceived facial age and biochemical indicators of glycemia in adult men and women
Authors: Żelaźniewicz Agnieszka , Nowak-Kornicka Judyta , Osochocka Adriana , Pawłowski Bogusław 
Published: June 2022

AbstractGlycemia is linked with one of the key mechanisms underlying the aging process and inter-individual differences in biological age. Previous research showed that glucose level is linked with perceived age in elder individuals. This study aimed to verify if glycemia is related to perceived facial age in healthy adult individuals as interventions in younger and healthy cohorts are crucial for preventing the onset of age-related diseases. The study sample consisted of 116 healthy men of mean age 35.53 ± 3.54 years (29.95–44.29) and 163 healthy women of mean age 28.38 ± 2.40 (24.25–34.17) years. Glycemia was evaluated by fasting glucose, insulin, HOMA-IR, and glycated hemoglobin level. BMI, facial sexual dimorphism, estradiol, testosterone, and hsCRP levels were controlled. Perceived age was evaluated based on standardized facial photos in an online survey. Additionally perceived facial aging was calculated as a difference between perceived age and chronological age. No relationship between the levels of biochemical indicators of glycemia and perceived facial age or aging was found both in men and women, also when controlled for possible confounders. This study shows that perceived facial age in adult individuals is rather linked with body adiposity of sexual dimorphism but not with glycemic markers.
Deep learning-based kcat prediction enables improved enzyme-constrained model reconstruction
Authors: Li Feiran , Yuan Le , Lu Hongzhong , Li Gang , Chen Yu , Engqvist Martin K. M. , Kerkhoven Eduard J. , Nielsen Jens 
Published: June 2022

AbstractEnzyme turnover numbers (kcat) are key to understanding cellular metabolism, proteome allocation and physiological diversity, but experimentally measuredkcatdata are sparse and noisy. Here we provide a deep learning approach (DLKcat) for high-throughputkcatprediction for metabolic enzymes from any organism merely from substrate structures and protein sequences. DLKcat can capturekcatchanges for mutated enzymes and identify amino acid residues with a strong impact onkcatvalues. We applied this approach to predict genome-scalekcatvalues for more than 300 yeast species. Additionally, we designed a Bayesian pipeline to parameterize enzyme-constrained genome-scale metabolic models from predictedkcatvalues. The resulting models outperformed the corresponding original enzyme-constrained genome-scale metabolic models from previous pipelines in predicting phenotypes and proteomes, and enabled us to explain phenotypic differences. DLKcat and the enzyme-constrained genome-scale metabolic model construction pipeline are valuable tools to uncover global trends of enzyme kinetics and physiological diversity, and to further elucidate cellular metabolism on a large scale.
Capturing additional genetic risk from family history for improved polygenic risk prediction
Authors: Lu Tianyuan , Forgetta Vincenzo , Richards J. Brent , Greenwood Celia M. T. 
Published: June 2022

AbstractFamily history of complex traits may reflect transmitted rare pathogenic variants, intra-familial shared exposures to environmental and lifestyle factors, as well as a common genetic predisposition. We developed a latent factor model to quantify trait heritability in excess of that captured by a common variant-based polygenic risk score, but inferable from family history. For 941 children in the Avon Longitudinal Study of Parents and Children cohort, a joint predictor combining a polygenic risk score for height and mid-parental height was able to explain ~55% of the total variance in sex-adjusted adult height z-scores, close to the estimated heritability. Marginal yet consistent risk prediction improvements were also achieved among ~400,000 European ancestry participants for 11 complex diseases in the UK Biobank. Our work showcases a paradigm for risk calculation, and supports incorporation of family history into polygenic risk score-based genetic risk prediction models.
MALAT1-dependent hsa_circ_0076611 regulates translation rate in triple-negative breast cancer
Authors: Turco Chiara , Esposito Gabriella , Iaiza Alessia , Goeman Frauke , Benedetti Anna , Gallo Enzo , Daralioti Theodora , Perracchio Letizia , Sacconi Andrea , Pasanisi Patrizia , Muti Paola , Pulito Claudio , Strano Sabrina , Ianniello Zaira , Fatica Alessandro , Forcato Mattia , Fazi Francesco , Blandino Giovanni , Fontemaggi Giulia 
Published: June 2022

AbstractVascular Endothelial Growth Factor A (VEGFA) is the most commonly expressed angiogenic growth factor in solid tumors and is generated as multiple isoforms through alternative mRNA splicing. Here, we show that lncRNA MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) and ID4 (inhibitor of DNA-binding 4) protein, previously referred to as regulators of linear isoforms of VEGFA, induce back-splicing of VEGFA exon 7, producing circular RNA circ_0076611. Circ_0076611 is detectable in triple-negative breast cancer (TNBC) cells and tissues, in exosomes released from TNBC cells and in the serum of breast cancer patients. Circ_0076611 interacts with a variety of proliferation-related transcripts, included MYC and VEGFA mRNAs, and increases cell proliferation and migration of TNBC cells. Mechanistically, circ_0076611 favors the expression of its target mRNAs by facilitating their interaction with components of the translation initiation machinery. These results add further complexity to the multiple VEGFA isoforms expressed in cancer cells and highlight the relevance of post-transcriptional regulation of VEGFA expression in TNBC cells.
DnaK response to expression of protein mutants is dependent on translation rate and stability
Authors: Christensen Signe , Rämisch Sebastian , André Ingemar 
Published: June 2022

AbstractChaperones play a central part in the quality control system in cells by clearing misfolded and aggregated proteins. The chaperone DnaK acts as a sensor for molecular stress by recognising short hydrophobic stretches of misfolded proteins. As the level of unfolded protein is a function of protein stability, we hypothesised that the level of DnaK response upon overexpression of recombinant proteins would be correlated to stability. Using a set of mutants of the λ-repressor with varying thermal stabilities and a fluorescent reporter system, the effect of stability on DnaK response and protein abundance was investigated. Our results demonstrate that the initial DnaK response is largely dependent on protein synthesis rate but as the recombinantly expressed protein accumulates and homeostasis is approached the response correlates strongly with stability. Furthermore, we observe a large degree of cell-cell variation in protein abundance and DnaK response in more stable proteins.
Anchor-based bisulfite sequencing determines genome-wide DNA methylation
Authors: Chapin Nathaniel , Fernandez Joseph , Poole Jason , Delatte Benjamin 
Published: June 2022

AbstractWhole Genome Bisulfite Sequencing (WGBS) is the current standard for DNA methylation profiling. However, this approach is costly as it requires sequencing coverage over the entire genome. Here we introduce Anchor-Based Bisulfite Sequencing (ABBS). ABBS captures accurate DNA methylation information in Escherichia coli and mammals, while requiring up to 10 times fewer sequencing reads than WGBS. ABBS interrogates the entire genome and is not restricted to the CpG islands assayed by methods like Reduced Representation Bisulfite Sequencing (RRBS). The ABBS protocol is simple and can be performed in a single day.
Meteoritic materials within sulfate aerosol particles in the troposphere are detected with transmission electron microscopy
Authors: Adachi Kouji , Oshima Naga , Takegawa Nobuyuki , Moteki Nobuhiro , Koike Makoto 
Published: June 2022

AbstractWhen meteorites impact the Earth’s atmosphere, they fractionalize and ablate, generating aerosol particles containing extraplanetary materials. Meteoritic materials have been identified among aerosol particles using elemental markers (iron and magnesium); however, their shapes and mixing states are largely unknown. Here we demonstrate the presence of meteoritic materials collected by a research aircraft from the troposphere over the western Pacific using transmission electron microscopy. The distribution of meteoritic elements within individual particles coincided with sulfur, indicating that they were in forms of sulfates, i.e., water-soluble. Enhanced number fractions of sulfate particles with meteoritic materials were observed during tropopause-folding events, suggesting that they originated from the stratosphere. We also estimated the potential contributions of the Chelyabinsk meteorite event, which occurred 5 months prior to the sampling and represents the largest meteorite event in the past century. This study provides unique observational evidence for the linkage between extraplanetary materials and tropospheric aerosols.