Utilizing phosphate more efficiently is crucial for sustainable crop production. Highly efficient rice (Oryza sativa) cultivars have been identified and this study aims to identify metabolic markers associated with P utilization efficiency. P deficiency generally reduced leaf P concentrations and CO2 assimilation rates but efficient cultivars were reducing leaf P concentrations further than inefficient ones while maintaining similar CO2 assimilation rates. Adaptive changes in carbon metabolism were detected but equally in efficient and inefficient cultivar groups. Groups furthermore did not differ with respect to partial substitutions of phospholipids by sulfo- and galactolipids. Metabolites significantly more abundant in the efficient group, such as sinapate, benzoate and glucoronate, were related to antioxidant defense and may help alleviating oxidative stress caused by P deficiency. Sugar alcohols ribitol and threitol were another marker metabolite for higher phosphate efficiency as were several amino acids, especially threonine. Since these metabolites are not known to be associated with P deficiency, they may provide novel clues for the selection of more P efficient genotypes. In conclusion, metabolite signatures detected here were not related to phosphate metabolism but rather helped P efficient lines to keep vital processes functional under the adverse conditions of P starvation.
Soil salinization is a serious restrictive factor of sustainable agricultural development, and its monitoring accuracy is mainly influenced by such factors as mineral composition, organic matter, and Fractional Vegetation Cover (FVC). Previous research mostly focused on the first two factors and the study of FVC is scarce and unsystematic. In order to systematically explore the effect of FVC, we monitored the soil salinization with different vegetation coverage in Jiefangzha Irrigation District in Inner Mongolia using satellite remote sensing. From May to August 2018, we carried out field sampling at different depths (0-20cm, 0-40cm, 0-60cm) in each month, and calculated FVC and spectral covariates using GF-1 satellite images in the corresponding sampling period. Based on the FVC division criteria of Inner Mongolia, we took the following steps: (1) setting up control treatment A (the full data with undivided FVC,TA) and experimental treatment B (bare land, TB), C (mid-low FVC, TC), D (mid FVC, TD) and E (high FVC, TE); (2) conducting the Best Subset Selection (BSS) for all spectral covariates at different depths of each treatment; and (3) constructing the Soil Salt Content (SSC) inversion models by Partial Least Square Regression (PLSR), Cubist, and Extreme Learning Machine (ELM). The results indicated that classifying FVC could improve the stability and predictive ability of the models. The results can provide references for soil salinization prevention and agricultural production in Jiefangzha Irrigation District and other areas with the same vegetation cover.
Genetic tools are increasingly used to identify and discriminate between species. One key transition in this process was the recognition of the potential of the ca 658bp fragment of the organelle cytochrome c oxidase I (COI) as a barcode region, which revolutionised animal bioidentification and lead, among others, to the instigation of the Barcode of Life database (BOLD), containing currently barcodes from >7.9 million specimens. Following this discovery, suggestions for other organellar regions and markers, and the primers with which to amplify them, have been continuously proposed. Most recently, the field has taken the leap from PCR based generation of DNA references into shotgun sequencing-based ‘genome skimming’ alternatives, which the ultimate goal of assembling organellar reference genomes. Unfortunately, in genome skimming approaches, much of the nuclear genome (as much as 99% of the sequence data) is discarded, which is not only wasteful but can also limit the power of discrimination at or below the species level. Here, we advocate that the full shotgun sequence data can be used to assign an identity (that we term for convenience its ‘DNA-mark’) for both voucher and query samples, without requiring any computationally intensive pretreatment (e.g., assembly) of reads. We argue that if reference databases are populated with such ‘DNA-marks’, it will enable future DNA-based taxonomic identification to complement, or even replace PCR of barcodes with genome skimming, and we discuss how such methodology ultimately could enable identification to population, or even individual, level.
Few phylogeographical studies exist for taxa inhabiting the Colorado Plateau province. We combined mitochondrial and genomic data with species distribution modeling to test Pleistocene hypotheses for Aphonopelma marxi, a large tarantula endemic to the plateau region. Mitochondrial and genomic analyses revealed that the species comprises at least three main clades that diverged in the Pleistocene. A clade distributed along the Mogollon Rim appears to have persisted in place during the last glacial maximum, whereas the other two clades probably colonized the central and northeastern portion of the species’ range from small refugial areas along river-carved canyons. Climate models support this hypothesis for the Mogollon Rim, but late glacial climate data appear too coarse to detect suitable areas in canyons. Locations of canyon refugia could not be inferred from genomic analyses due to missing data, encouraging us to explore the effect of missing loci in phylogeographical inferences using RADseq. In phylogenetic analyses, node support for major clades decreased with the addition of samples with significant amounts of missing data (more than 30%). Population genomic structure was greatly influenced by missing data, with the group membership of many taxa changing as samples with missing loci were added. Results from DAPC, a distance-based method, did not change as samples with significant amounts missing data were added. We conclude that the specific loci that are missing matters more than the number of missing loci, and that samples with missing data can still add information to RADseq-based analyses as long as results are interpreted cautiously.
Rationale aims and objectives Potentially preventable hospitalizations (PPH) are a challenge. What happens before hospital admission? Are there crucial tipping points before admissions in at-risk cohorts’ trajectories? HealthLinksChronicCare (HLCC) hospital risk-prediction algorithms using admission, diagnosis, and lifestyle data identifies at-patients. MW monitors HLCC patients with outbound phone calls using telehealth – the Patient Journey Record System with alerts representing a real-time anticipated risk of PPH. Health Coaches triage and intervene to optimize GP, hospital and community service utilization to reduce the risk of PPH. Aims To describe a time series of telehealth phone calls related to an acute admission ( 10 days) to investigate tipping points in self-reported biopsychosocial environmental concerns (total alerts) and or condition symptoms of concern (red alerts). Methods MW participants had an acute (non-surgical) admission and >44 calls between 23/12/16 - 11/10/17. The Patient Journey Record System (PaJR) and Victorian Admitted Episode Data/ Emergency Minimum Dataset provided longitudinal data. Descriptive time series analysis employed Pettitt’s homogeneity test to detect ‘tipping points’ using XLSTAT package. Findings One hundred three patients aged 74 ± 15.4 years, with 59% male and 61% female, provided 764 call records around admission(s) and 22,715 records over 10 months. Total alerts and red alerts were higher in the 10 days before and after admission. Total alerts significantly increased (tipped) at day 3 before hospitalisation persisting until 10 days. Red alerts increased (tipped) 1 day before admission and remained high following discharge. Discussion and Conclusion Self-report in phone calls describe a pre-hospital phase of ‘post-hospital syndrome’ (PHS), which began at least 10 days before admission and persisted after discharge. Wide-ranging health, psychosocial, and environmental concerns preceded a tipping point into acute symptoms. Telehealth monitoring of biopsychosocial, as well as disease, concerns require further investigation.
Norway spruce is a conifer storing large amounts of terpenoids in resin ducts of various tissues. Parts of the terpenoids stored in needles can be emitted together with de novo synthesized terpenoids. Since previous studies provided hints on xylem transported terpenoids as a third emission source, we tested if terpenoids are transported in xylem sap of Norway spruce. We further aimed at understanding if they might contribute to terpenoid emission from needles. We determined terpenoid content and composition in xylem sap, needles, bark, wood and roots of field grown trees, as well as terpenoid emissions from needles. We found considerable amounts of terpenoids – mainly oxygenated compounds - in xylem sap. The terpenoid concentration in xylem sap was relatively low compared to the content in other tissues where terpenoids are stored in resin ducts. Importantly, the terpenoid composition in the xylem sap greatly differed from the composition in wood, bark or roots suggesting that an internal transport of terpenoids takes place at the sites of xylem loading. Our work gives hints that plant internal transport of terpenoids exists within conifers; studies on their functions should be a focus of future research.
Protein-protein interactions (PPIs) are ubiquitous and functionally of great importance in biological systems. Hence, the ac-curate prediction of PPIs by protein-protein docking and scoring tools is highly desirable in order to characterize their structure and biological function. Ab initio docking protocols are divided into the sampling of docking poses to produce at least one near-native structure, then to evaluate the vast candidate structures by scoring. Concurrent development in both sampling and scoring is crucial for the deployment of protein-protein docking software. In the present work, we apply a machine learning model on pairwise potentials to refine the task of protein quaternary structure native structure detection among decoys. A decoy set was featurized using the Knowledge and Empirical Combined Scoring Algorithm 2 (KECSA2) pairwise potential. The highly unbalanced decoy set was then balanced using a comparison concept between native and decoy structures. The resultant comparison descriptors were used to train a logistic regression (LR) classifier. The LR model yielded the optimal performance for native detection among decoys compared to conventional scoring functions, while exhibiting lesser performance for the detection of low root mean square deviation (RMSD) decoy structures. Its deployment on an independent benchmark set confirms that the scoring function performs competitively relative to other scoring functions. All data and scripts used are available at: https://github.com/TanemuraKiyoto/PPI-native-detection-via-LR .
Background and purpose: Savolitinib (AZD6094, HMPL-504, volitinib) is an oral, potent, and highly selective MET receptor tyrosine kinase inhibitor. This series of studies aimed to develop a pharmacokinetic-pharmacodynamic (PK/PD) model to link inhibition of MET phosphorylation (pMET) by savolitinib with anti-tumour activity. Experimental approach: Cell line-derived xenograft (CDX) experiments using human lung cancer (EBC-1) and gastric cancer (MKN-45) cells were conducted in athymic nude mice using a variety of doses and schedules of savolitinib. Tumour pMET changes and growth inhibition were calculated after 28 days. Population PK/PD techniques were used to construct a PK/PD model for savolitinib. Key results: Savolitinib showed dose- and schedule-dependent anti-tumour activity in the CDX models, with more frequent, lower dosing schedules (e.g. twice daily) being more effective than intermittent, higher dosing schedules (e.g. 4 days on/3 days off or 2 days on/5 days off). There was a clear exposure–response relationship, with maximal suppression of pMET of >90%. Data from additional CDX and patient-derived xenograft (PDX) models overlapped, allowing the calculation of a single EC50 of 0.38 ng/mL. Tumour growth modelling demonstrated that prolonged, high levels of pMET inhibition (>90%) were required for tumour stasis and regression in the models. Conclusion and implications: High and durable levels of MET inhibition by savolitinib are needed for optimal monotherapy anti-tumour activity in preclinical models. The modelling framework developed here can be used to translate tumour growth inhibition from the mouse to human, and thus guide choice of clinical dose and schedule.
Coral reef fish larvae are tiny, exceedingly numerous, and hard to track. They are also highly capable, equipped with swimming and sensory abilities that may influence their dispersal trajectories. Despite the importance of larval input to the dynamics of a population, we remain reliant on indirect insights to the processes influencing larval behaviour and transport. Here, we used genetic data (300 independent single nucleotide polymorphisms) derived from a light trap sample of a single recruitment event of Dascyllus abudafur in the Red Sea (N=168 settlers). We analysed the genetic composition of the larvae and assessed whether kinship among these was significantly different from random as evidence for cohesive dispersal during the larval phase. We simulated many iterations of similar-sized recruitment cohorts to compare the expected kinship composition relative to our empirical data. The high number of siblings within the empirical cohort strongly suggests cohesive dispersal among larvae. This work highlights the utility of kinship analysis as a means of inferring dynamics during the pelagic larval phase.
Shewanella oneidensis MR-1, a model strain of exoelectrogenic bacteria (EEB), plays a key role in environmental bioremediation and bioelectrochemical systems because of its unique respiration capacity. However, only a narrow range of substrates can be utilized by S. oneidensis MR-1 as carbon sources, resulting in its limited applications. In this work, a rapid, highly efficient and easily manipulated base editing system pCBEso was developed by fusing a Cas9 nickase (Cas9n (D10A)) with the cytidine deaminase rAPOBEC1 in S. oneidensis MR-1. The C-to-T conversion of suitable C within the base editing window could be readily and efficiently achieved by the pCBEso system without requiring double strand break or repair templates. Moreover, double-locus simultaneous editing was successfully accomplished with an efficiency of 87.5. With this tool, the roles of the key genes involving in N-acetyl-glucosamine (GlcNAc) or glucose metabolism in S. oneidensis MR-1 were identified. Furthermore, an engineered strain with expanded carbon source utilization spectra was constructed and exhibited a higher degradation rate for multiple organic pollutants (i.e., azo dyes and organoarsenic compounds) than the wild type when glucose or GlcNAc was used as the sole carbon source. Such a base editing system could be readily applied to other EEB. This work not only enhances the substrate utilization and pollutant degradation capacities of S. oneidensis MR-1, but also accelerates the robust construction of engineered strains for environmental bioremediation.
Fangzhu, which has been lost for thousands of years, is an ancient device for water collection from air, its mechanism is unknown yet. Here we elucidate its possible surface-geometric and related physical properties by the oldest the Yin-Yang contradiction. In view of modern nanotechnology, we reveal that Fangzhu’s water-harvesting ability is obtained through a hydrophilic-hydrophobic hierarchy of the surface, mimicking spider web’s water collection, lotus or desert beetle’s water intake. The convex-concave hierarchy of Fangzhu’s textured surface enables it to have low wettability(high geometric potential) to attract water molecules from air through the nano-scale convex surface and transfer the attracted water along the concave surface to the collector. A mathematical model is established to reveal three main factors affecting its effectiveness, i.e., the air velocity, the surface temperature and surface structure. The lost technology can play an extremely important role in modern architecture, ocean engineering, transportation and others to catch water from air for everyday use.
Molecular mechanisms and process kinetics of crystallizing concomitant polymorphs remain poorly understood. Solvent-mediated phase transformation is often mistaken as concomitant crystallization, mainly due to the two processes sharing similar kinetic profiles. Herein, we developed a population balance model to simulate a concomitant crystallization process of two polymorphs of tolfenamic acid (TFA). The kinetic modeling aims to better understand concomitant crystallization and help guide form selection of such a molecular system. Crystallization kinetics of ethanolic TFA solutions were uncovered from induction time measurements, as well as seeded and unseeded crystallization experiments. Both experimental and simulation results demonstrate that the stable form I crystallizes concomitantly with the metastable form II. The faster growing form II results in an intermediate decline in the kinetic profile of form I composition in crystallized samples, a characteristic feature of the concomitantly crystallized system. A four-quadrant scheme of attainable polymorph outcome was simulated under various crystallization conditions.
The interior Dirichlet boundary value problem for the diffusion equation in non-homogeneous media is reduced to a system of Boundary-Domain Integral Equations (BDIEs) employing the parametrix obtained in different from . We further extend the results obtained in for the mixed problem in a smooth domain with L²(Ω) right hand side to Lipschitz domains and PDE right-hand in the Sobolev space H−1(Ω), where neither the classical nor the canonical co-normal derivatives are well defined. Equivalence between the system of BDIEs and the original BVP is proved along with their solvability and solution uniqueness in appropriate Sobolev spaces.
Nanofluid as a special thermal transporting medium has recently received unprecedented attention due to its improved heat transfer performance compared to conventional fluids. Numerous researches have been conducted on the natural convection characteristics of different nanofluids in various configurations of cavities due to the important applications of natural convection in environmental, petrochemical, medical, aviation and space technology, industrial and many more areas. The emergence of a magnetic field as a tool for the manipulation of convective flow and heat transfer behaviours of nanofluids in non-square enclosures has been extensively reviewed. The influence of several variables such as controlling parameters, heat distribution methods, thermal and concentration boundary conditions, magnetic field types, numerical methods, correlation types, nanofluid types, heaters types, numbers and length, and slip conditions, etc., on the magnetohydrodynamic (MHD) natural convection flow and heat transfer behaviours of nanofluid in non-square cavities has been given great attention and brought to the spotlight for discussion. The concepts of bioconvection, micro-polar nanofluid, bio-nanofluid (green nanofluid), ionic nanofluid, and hybrid nanofluid have also been discussed for the first time in relation to natural convection. Special cases of MHD natural convection in non-square cavities involving hybrid nanofluids and micro-polar nanofluids are also presented herein. The application of several numerical methods (which is the major approach studied so far) to investigate the hydromagnetic behaviours of nanofluids in non-square cavities is the focus of this work.
We apply the Bielecki metric on the space C([a, b]), to analyze the different types of stabilities of non-linear fractional integral equation corresponding to fractional boundary value problems. Sufficient conditions are obtained to prove stability results for fractional non-linear Volterra and Fredholm integral equations, given by Ulam, Hyer and Rassias. We extend the respective stability results to the fractional integral equations where the domain of integration is an unbounded interval. We provide numerical examples which asserts our stability results.
We establish nonexistence of nontrivial solutions (including sign-changing ones) for some partial differential inequalities of elliptic and parabolic type containing nonlinear terms that depend on the positive and negative part of the sought function in different ways. Systems of elliptic inequalities with similar structure are also considered. The proofs are based on the test function method.