Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process

In a recent study of denitrification dynamics in hyporheic zone sediments, we observed a significant time lag (up to several days) in enzymatic response to the changes in substrate concentration. To explore an underlying mechanism and understand the interactive dynamics between enzymes and nutrients, we developed a trait-based model that associates a community’s traits with functional enzymes, instead of typically used species guilds (or functional guilds). This enzyme-based formulation allows to collectively describe biogeochemical functions of microbial communities without directly parameterizing the dynamics of species guilds, therefore being scalable to complex communities. As a key component of modeling, we accounted for microbial regulation occurring through transcriptional and translational processes, the dynamics of which was parameterized based on the temporal profiles of enzyme concentrations measured using a new signature peptide-based method. The simulation results using the resulting model showed several days of a time lag in enzymatic responses as observed in experiments. Further, the model showed that the delayed enzymatic reactions could be primarily controlled by transcriptional responses and that the dynamics of transcripts and enzymes are closely correlated. The developed model can serve as a useful tool for predicting biogeochemical processes in natural environments, either independently or through integration with hydrologic flow simulators

Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process

In a recent study of denitrification dynamics in hyporheic zone sediments, we observed a significant time lag (up to several days) in enzymatic response to the changes in substrate concentration. To explore an underlying mechanism and understand the interactive dynamics between enzymes and nutrients, we developed a trait-based model that associates a community’s traits with functional enzymes, instead of typically used species guilds (or functional guilds). This enzyme-based formulation allows to collectively describe biogeochemical functions of microbial communities without directly parameterizing the dynamics of species guilds, therefore being scalable to complex communities. As a key component of modeling, we accounted for microbial regulation occurring through transcriptional and translational processes, the dynamics of which was parameterized based on the temporal profiles of enzyme concentrations measured using a new signature peptide-based method. The simulation results using the resulting model showed several days of a time lag in enzymatic responses as observed in experiments. Further, the model showed that the delayed enzymatic reactions could be primarily controlled by transcriptional responses and that the dynamics of transcripts and enzymes are closely correlated. The developed model can serve as a useful tool for predicting biogeochemical processes in natural environments, either independently or through integration with hydrologic flow simulators

The Weighted Aggregation of Ranked Objects by the Arbitrary Totality of Other Objects

The task of distribution of the ranked objects by the smaller number of other objects is set. The first objects are named objects of the first kind, the second objects are the objects of the second kind. The rating of the totality of objects of the first kind, included on the attribute of belonging in the object of the second kind, is suggested to be calculated through the procedure of the weighted aggregation which represents a product of number of the above mentioned objects of the first kind and the average weight coefficient calculated through the average rank (rating) of the totality of the objects of the first kind. An example of such a task is the distribution of ranked universities by the world countries according to one of the global world ratings. The task is extended to the calculation of the integral rank (rating) for an arbitrary number of rankings of different objects of the first kind, distributed on the given number of objects of the second kind

Inhibition of TNF-α Improves the Bladder Dysfunction That Is Associated With Type 2 Diabetes

Diabetic bladder dysfunction (DBD) is common and affects 80% of diabetic patients. However, the molecular mechanisms underlying DBD remain elusive because of a lack of appropriate animal models. We demonstrate DBD in a mouse model that harbors hepatic-specific insulin receptor substrate 1 and 2 deletions (double knockout [DKO]), which develops type 2 diabetes. Bladders of DKO animals exhibited detrusor overactivity at an early stage: increased frequency of nonvoiding contractions during bladder filling, decreased voided volume, and dispersed urine spot patterns. In contrast, older animals with diabetes exhibited detrusor hypoactivity, findings consistent with clinical features of diabetes in humans. The tumor necrosis factor (TNF) superfamily genes were upregulated in DKO bladders. In particular, TNF-α was upregulated in serum and in bladder smooth muscle tissue. TNF-α augmented the contraction of primary cultured bladder smooth muscle cells through upregulating Rho kinase activity and phosphorylating myosin light chain. Systemic treatment of DKO animals with soluble TNF receptor 1 (TNFRI) prevented upregulation of Rho A signaling and reversed the bladder dysfunction, without affecting hyperglycemia. TNFRI combined with the antidiabetic agent, metformin, improved DBD beyond that achieved with metformin alone, suggesting that therapies targeting TNF-α may have utility in reversing the secondary urologic complications of type 2 diabetes

An Analysis Platform for Multiscale Hydrogeologic Modeling with Emphasis on Hybrid Multiscale Methods

One of the most significant challenges faced by hydrogeologic modelers is the disparity between the spatial and temporal scales at which fundamental flow, transport, and reaction processes can best be understood and quantified (e.g., microscopic to pore scales and seconds to days) and at which practical model predictions are needed (e.g., plume to aquifer scales and years to centuries). While the multiscale nature of hydrogeologic problems is widely recognized, technological limitations in computation and characterization restrict most practical modeling efforts to fairly coarse representations of heterogeneous properties and processes. For some modern problems, the necessary level of simplification is such that model parameters may lose physical meaning and model predictive ability is questionable for any conditions other than those to which the model was calibrated. Recently, there has been broad interest across a wide range of scientific and engineering disciplines in simulation approaches that more rigorously account for the multiscale nature of systems of interest. In this article, we review a number of such approaches and propose a classification scheme for defining different types of multiscale simulation methods and those classes of problems to which they are most applicable. Our classification scheme is presented in terms of a flowchart (Multiscale Analysis Platform), and defines several different motifs of multiscale simulation. Within each motif, the member methods are reviewed and example applications are discussed. We focus attention on hybrid multiscale methods, in which two or more models with different physics described at fundamentally different scales are directly coupled within a single simulation. Very recently these methods have begun to be applied to groundwater flow and transport simulations, and we discuss these applications in the context of our classification scheme. As computational and characterization capabilities continue to improve, we envision that hybrid multiscale modeling will become more common and also a viable alternative to conventional single-scale models in the near future

Selection of Anti-Sulfadimidine Specific ScFvs from a Hybridoma Cell by Eukaryotic Ribosome Display

BACKGROUND:Ribosome display technology has provided an alternative platform technology for the development of novel low-cost antibody based on evaluating antibiotics derived residues in food matrixes. METHODOLOGY/PRINCIPAL FINDINGS:In our current studies, the single chain variable fragments (scFvs) were selected from hybridoma cell lines against sulfadimidine (SM(2)) by using a ribosome library technology. A DNA library of scFv antibody fragments was constructed for ribosome display, and then mRNA-ribosome-antibody (MRA) complexes were produced by a rabbit reticulocyte lysate system. The synthetic sulfadimidine-ovalbumin (SM(2)-OVA) was used as an antigen to pan MRA complexes and putative scFv-encoding genes were recovered by RT-PCR in situ following each panning. After four rounds of ribosome display, the expression vector pCANTAB5E containing the selected specific scFv DNA was constructed and transformed into Escherichia coli HB2151. Three positive clones (SAS14, SAS68 and SAS71) were screened from 100 clones and had higher antibody activity and specificity to SM(2) by indirect ELISA. The three specific soluble scFvs were identified to be the same molecular weight (approximately 30 kDa) by Western-blotting analysis using anti-E tag antibodies, but they had different amino acids sequence by sequence analysis. CONCLUSIONS/SIGNIFICANCE:The selection of anti-SM(2) specific scFv by in vitro ribosome display technology will have an important significance for the development of novel immunodetection strategies for residual veterinary drugs

Validity and Reliability of the Integrated Palliative Care Outcome Scale in Asian Heart Failure Patients

BACKGROUND: The Integrated Palliative Care Outcome Scale (IPOS) was developed in the United Kingdom for health assessment in advanced illness. OBJECTIVES: To evaluate the validity and reliability of a culturally adapted IPOS (both patient and staff versions) for heart failure (HF). DESIGN/SETTING: We recruited HF patients and staff from a tertiary hospital in Singapore. We collected patient IPOS, New York Heart Association (NYHA) status, Edmonton Symptom Assessment System (ESAS) and Minnesota Living with Heart Failure (MLHF) scores at baseline, and patient IPOS at follow-up. Each baseline patient IPOS was matched with a staff IPOS. MEASUREMENTS: Pearson correlation coefficient (r) between ESAS, MLHF, and patient IPOS was calculated to assess construct validity. The two-sample T-test assessed difference in patient and staff IPOS scores across NYHA status and care settings for known-group validity. Internal consistency of patient and staff IPOS was assessed using Cronbach's alpha (α). Intraclass correlation coefficient (ICC) was used to assess test-retest reliability of patient IPOS and inter-rater reliability between patient and staff IPOS. RESULTS: Ninety-one patients and 12 staff participated. There was strong convergent validity of total patient IPOS with MLHF (r = 0.78) and ESAS (r = 0.81). There were statistically significant differences in total IPOS across care settings (patient-IPOS: 8.05, staff-IPOS 13.61) and NYHA (patient-IPOS: 7.52, staff-IPOS 12.71).There was high internal consistency of total patient (α = 0.83) and staff IPOS (α = 0.88) and high test-retest reliability of patient IPOS (ICC 0.81). Inter-rater reliability (ICC) ranged between 0.82 and 0.91. CONCLUSION: The IPOS was valid and reliable for HF patients in Singapore.publishedVersionPeer reviewe

Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites

Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use

Stereotaxical Infusion of Rotenone: A Reliable Rodent Model for Parkinson's Disease

A clinically-related animal model of Parkinson's disease (PD) may enable the elucidation of the etiology of the disease and assist the development of medications. However, none of the current neurotoxin-based models recapitulates the main clinical features of the disease or the pathological hallmarks, such as dopamine (DA) neuron specificity of degeneration and Lewy body formation, which limits the use of these models in PD research. To overcome these limitations, we developed a rat model by stereotaxically (ST) infusing small doses of the mitochondrial complex-I inhibitor, rotenone, into two brain sites: the right ventral tegmental area and the substantia nigra. Four weeks after ST rotenone administration, tyrosine hydroxylase (TH) immunoreactivity in the infusion side decreased by 43.7%, in contrast to a 75.8% decrease observed in rats treated systemically with rotenone (SYS). The rotenone infusion also reduced the DA content, the glutathione and superoxide dismutase activities, and induced alpha-synuclein expression, when compared to the contralateral side. This ST model displays neither peripheral toxicity or mortality and has a high success rate. This rotenone-based ST model thus recapitulates the slow and specific loss of DA neurons and better mimics the clinical features of idiopathic PD, representing a reliable and more clinically-related model for PD research