Mechanistic and statistical models of total Vibrio abundance in the Neuse River Estuary

Bacteria in the genus Vibrio are ubiquitous to estuarine waters worldwide and are often the dominant genus recovered from these environments. This genus contains several potentially pathogenic species, including Vibrio vulnificus, Vibrio cholerae, Vibrio parahaemolyticus, and Vibrio alginolyticus. These bacteria have short generation times, as low as 20–30 min, and can thus respond rapidly to changing environmental conditions. A five-parameter mechanistic model was generated based on environmental processes including hydrodynamics, growth, and death rates of Vibrio bacteria to predict total Vibrio abundance in the Neuse River Estuary of eastern North Carolina. Additionally an improved statistical model was developed using the easily monitored parameters of temperature and salinity. This updated model includes data that covers more than eight years of constant bacterial monitoring, and incorporates extreme weather events such as droughts, storms, and floods. These models can be used to identify days in which bacterial abundance might coincide with increased health risks.     

Use of computer dynamic simulation for indoor exposure assessment based on chronogram incident as air pollution source characterization

Determination of the level of exposure due to a chemical incident is crucial for the assessment of public health risks and environmental impact. This kind of information is also useful for the subsequent legal responsibilities. If the air contaminant concentrations are not quantified during the incident, then its air concentration may fall below detectable levels shortly after the incident has passed. In case of smelly compounds, usually the incident chronogram indicates the time when the smell was detected and when the smell was gone. Unfortunately, an objective and analytical measure of odour is impossible. The present study shows that it is possible to computer simulate the concentration evolution in time for a defined indoor scenario. Comparing the odour detection in the chronogram with the computer simulations, it is feasible to determine the maximum gas contaminant exposure during the incident and its evolution in time. Once the pollution source indoor concentration is characterized, considering the overall air renewal time and a plume model, the effects on the environment around the building can be estimated.     

Absolute quantification of the alleles in somatic point mutations by bioluminometric methods based on competitive polymerase chain reaction in the presence of a locked nucleic acid blocker or an allele-specific primer

In somatic (acquired) point mutations, the challenge is to quantify minute amounts of the mutant allele in the presence of a large excess of the normal allele that differs only in a single base pair. We report two bioluminometric methods that enable absolute quantification of the alleles. The first method exploits the ability of a locked nucleic acid (LNA) oligonucleotide to bind to and inhibit effectively the polymerase chain reaction (PCR) amplification of the normal allele while the amplification of the mutant allele remains unaffected. The second method employs allele-specific PCR primers, thereby allowing the amplification of the corresponding allele only. DNA internal standards (competitors) are added to the PCR mixture to compensate for any sample-to-sample variation in the amplification efficiency. The amplification products from the two alleles and the internal standards are quantified by a microtiter well-based bioluminometric hybridization assay using the photoprotein aequorin as a reporter. The methods allow absolute quantification of less than 300 copies of the mutant allele even in samples containing less than 1% of the mutant allele.     

Coexisting difficulties and couple therapy outcomes: Psychopathology and intimate partner violence.

Couples presenting for treatment of relationship distress often experience additional problems, including individual psychopathology and intimate partner violence (IPV). Both issues are associated with current and future poor relationship functioning in nontreatment samples, but relatively little is understood about their association with initial presentation and outcomes in couple therapy. The current study examined these associations in a sample of 177 heterosexual couples who received therapy at two Veteran's Affairs clinics. Unlike most studies of couple therapy outcomes, couples were not excluded from treatment specifically because of high levels of psychopathology or IPV. Results of Actor Partner Interdependence Model (APIM) analyses revealed actor and partner effects of depression, actor effects of anxiety, and partner effects of IPV on initial relationship satisfaction, such that greater coexisting difficulties were associated with poorer initial satisfaction. However, improvement in relationship satisfaction over the course of therapy was not associated with psychopathology, and, contrary to hypothesis, was positively associated with men's IPV prior to treatment, even when initial level of satisfaction was controlled. The results suggest that coexisting symptoms of psychopathology or IPV may not necessarily interfere with therapy outcomes and, indeed, therapy may have positive effects for couples with these problems. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Transient and asymptotic dispersion in confined sphere packings with cylindrical and non-cylindrical conduit geometries

We study the time and length scales of hydrodynamic dispersion in confined monodisperse sphere packings as a function of the conduit geometry. By a modified Jodrey-Tory algorithm, we generated packings at a bed porosity (interstitial void fraction) of ε=0.40 in conduits with circular, rectangular, or semicircular cross section of area 100πd(p)(2) (where d(p) is the sphere diameter) and dimensions of about 20d(p) (cylinder diameter) by 6553.6d(p) (length), 25d(p) by 12.5d(p) (rectangle sides) by 8192d(p) or 14.1d(p) (radius of semicircle) by 8192d(p), respectively. The fluid-flow velocity field in the generated packings was calculated by the lattice Boltzmann method for Péclet numbers of up to 500, and convective-diffusive mass transport of 4×10(6) inert tracers was modelled with a random-walk particle-tracking technique. We present lateral porosity and velocity distributions for all packings and monitor the time evolution of longitudinal dispersion up to the asymptotic (long-time) limit. The characteristic length scales for asymptotic behaviour are explained from the symmetry of each conduit's velocity field. Finally, we quantify the influence of the confinement and of a specific conduit geometry on the velocity dependence of the asymptotic dispersion coefficients.     

A stochastic approach for integrating strain variability in modeling Salmonella enterica growth as a function of pH and water activity

Strain variability of the growth behavior of foodborne pathogens has been acknowledged as an important issue in food safety management. A stochastic model providing predictions of the maximum specific growth rate (μ_max) of Salmonella enterica as a function of pH and water activity (a_w) and integrating intra-species variability data was developed. For this purpose, growth kinetic data of 60 S. enterica isolates, generated during monitoring of growth in tryptone soy broth of different pH (4.0-7.0) and a_w (0.964-0.992) values, were used. The effects of the environmental parameters on μ_max were modeled for each tested S. enterica strain using cardinal type and gamma concept models for pH and a_w, respectively. A multiplicative without interaction-type model, combining the models for pH and a_w, was used to describe the combined effect of these two environmental parameters on μ_max. The strain variability of the growth behavior of S. enterica was incorporated in the modeling procedure by using the cumulative probability distributions of the values of pH_min, pH_opt and a_wmin as inputs to the growth model. The cumulative probability distribution of the observed μ_max values corresponding to growth at pH 7.0-a_w 0.992 was introduced in the place of the model's parameter μ_opt. The introduction of the above distributions into the growth model resulted, using Monte Carlo simulation, in a stochastic model with its predictions being distributions of μ_max values characterizing the strain variability. The developed model was further validated using independent growth kinetic data (μ_max values) generated for the 60 strains of the pathogen at pH 5.0-a_w 0.977, and exhibited a satisfactory performance. The mean, standard deviation, and the 5th and 95th percentiles of the predicted μ_max distribution were 0.83, 0.08, and 0.69 and 0.96 h^− 1, respectively, while the corresponding values of the observed distribution were 0.73, 0.09, and 0.61 and 0.85 h^− 1. The stochastic modeling approach developed in this study can be useful in describing and integrating the strain variability of S. enterica growth kinetic behavior in quantitative microbiology and microbial risk assessment.     

Surface modification of starch based biomaterials by oxygen plasma or UV-irradiation

Radiation is widely used in biomaterials science for surface modification and sterilization. Herein, we describe the use of plasma and UV-irradiation to improve the biocompatibility of different starch-based blends in terms of cell adhesion and proliferation. Physical and chemical changes, introduced by the used methods, were evaluated by complementary techniques for surface analysis such as scanning electron microscopy, atomic force microscopy, contact angle analysis and X-ray photoelectron spectroscopy. The effect of the changed surface properties on the adhesion of osteoblast-like cells was studied by a direct contact assay. Generally, both treatments resulted in higher number of cells adhered to the modified surfaces. The importance of the improved biocompatibility resulting from the irradiation methods is further supported by the knowledge that both UV and plasma treatments can be used as cost-effective methods for sterilization of biomedical materials and devices.     

A microRNA Signature for the Diagnosis of Statins Intolerance

Atherosclerotic cardiovascular diseases (ASCVD) are the leading cause of morbidity and mortality in Western societies. Statins are the first-choice therapy for dislipidemias and are considered the cornerstone of ASCVD. Statin-associated muscle symptoms are the main reason for dropout of this treatment. There is an urgent need to identify new biomarkers with discriminative precision for diagnosing intolerance to statins (SI) in patients. MicroRNAs (miRNAs) have emerged as evolutionarily conserved molecules that serve as reliable biomarkers and regulators of multiple cellular events in cardiovascular diseases. In the current study, we evaluated plasma miRNAs as potential biomarkers to discriminate between the SI vs. non-statin intolerant (NSI) population. It is a multicenter, prospective, case-control study. A total of 179 differentially expressed circulating miRNAs were screened in two cardiovascular risk patient cohorts (high and very high risk): (i) NSI (n = 10); (ii) SI (n = 10). Ten miRNAs were identified as being overexpressed in plasma and validated in the plasma of NSI (n = 45) and SI (n = 39). Let-7c-5p, let-7d-5p, let-7f-5p, miR-376a-3p and miR-376c-3p were overexpressed in the plasma of SI patients. The receiver operating characteristic curve analysis supported the discriminative potential of the diagnosis. We propose a three-miRNA predictive fingerprint (let-7f, miR-376a-3p and miR-376c-3p) and several clinical variables (non-HDLc and years of dyslipidemia) for SI discrimination; this model achieves sensitivity, specificity and area under the receiver operating characteristic curve (AUC) of 83.67%, 88.57 and 89.10, respectively. In clinical practice, this set of miRNAs combined with clinical variables may discriminate between SI vs. NSI subjects. This multiparametric model may arise as a potential diagnostic biomarker with clinical value.     

Comprehensive Cytokine Profiling of Patients with COVID-19 Receiving Tocilizumab Therapy

Coronavirus disease 2019 (COVID-19) is characterized by immune activation in response to viral spread, in severe cases leading to the development of cytokine storm syndrome (CSS) and increased mortality. Despite its importance in prognosis, the pathophysiological mechanisms of CSS in COVID-19 remain to be defined. Towards this goal, we analyzed cytokine profiles and their interrelation in regard to anti-cytokine treatment with tocilizumab in 98 hospitalized patients with COVID-19. We performed a multiplex measurement of 41 circulating cytokines in the plasma of patients on admission and 3–5 days after, during the follow-up. Then we analyzed the patient groups separated in two ways: according to the clusterization of their blood cytokines and based on the administration of tocilizumab therapy. Patients with and without CSS formed distinct clusters according to their cytokine concentration changes. However, the tocilizumab therapy, administered based on the standard clinical and laboratory criteria, did not fully correspond to those clusters of CSS. Furthermore, among all cytokines, IL-6, IL-1RA, IL-10, and G-CSF demonstrated the most prominent differences between patients with and without clinical endpoints, while only IL-1RA was prognostically significant in both groups of patients with and without tocilizumab therapy, decreasing in the former and increasing in the latter during the follow-up period. Thus, CSS in COVID-19, characterized by a correlated release of multiple cytokines, does not fully correspond to the standard parameters of disease severity. Analysis of the cytokine signature, including the IL-1RA level in addition to standard clinical and laboratory parameters may be useful to define the onset of a cytokine storm in COVID-19 as well as the indications for anti-cytokine therapy.