Optimal latent period in a bacteriophage population model structured by infection-age

We study the lysis timing of a bacteriophage population by means of a continuously infection-age-structured population dynamics model. The features of the model are the infection process of bacteria, the natural death process, and the lysis process which means the replication of bacteriophage viruses inside bacteria and the destruction of them. We consider that the length of the lysis timing (or latent period) is distributed according to a general probability distribution function. We have carried out an optimization procedure and we have found the latent period corresponding to the maximal fitness (i.e. maximal growth rate) of the bacteriophage population.

Optimal latent period in a bacteriophage population model structured by infection-age

We study the lysis timing of a bacteriophage population by means of a continuously infection-age-structured population dynamics model. The features of the model are the infection process of bacteria, the death process, and the lysis process which means the replication of bacteriophage viruses inside bacteria and the destruction of them. The time till lysis (or latent period) is assumed to have an arbitrary distribution. We have carried out an optimization procedure, and we have found that the latent period corresponding to maximal fitness (i.e. maximal growth rate of the bacteriophage population) is of fixed length. We also study the dependence of the optimal latent period on the amount of susceptible bacteria and the number of virions released by a single infection. Finally, the evolutionarily stable strategy of the latent period is also determined as a fixed period taking into account that super-infections are not considered

Virus infection speeds: theory versus experiment

In order to explain the speed of Vesicular Stomatitis Virus VSV infections, we develop a simple model that improves previous approaches to the propagation of virus infections. For VSV infections, we find that the delay time elapsed between the adsorption of a viral particle into a cell and the release of its progeny has a veryimportant effect. Moreover, this delay time makes the adsorption rate essentially irrelevant in order to predict VSV infection speeds. Numerical simulations are in agreement with the analytical results. Our model satisfactorily explains the experimentally measured speeds of VSV infections

Hypothalamus transcriptome profile suggests an anorexia-cachexia syndrome in the anx/anx mouse model

The anx/anx mouse displays poor appetite and lean appearance and is considered a good model for the study of anorexia nervosa. To identify new genes involved in feeding behavior and body weight regulation we performed an expression profiling in the hypothalamus of the anx/anx mice. Using commercial microarrays we detected 156 differentially expressed genes and validated 92 of those using TaqMan low-density arrays. The expression of a set of 87 candidate genes selected based on literature evidences was also quantified by TaqMan low-density arrays. Our results showed enrichment in deregulated genes involved in cell death, cell morphology and cancer as well as an alteration of several signaling circuits involved in energy balance including neuropeptide Y and melanocortin signaling. The expression profile along with the phenotype led us to conclude that anx/anx mice resemble the anorexia-cachexia syndrome typically observed in cancer, infection with human immunodeficiency virus or chronic diseases, rather than starvation, and that anx/anx mice could be considered a good model for the treatment and investigation of this condition.

A mouse peritonitis model for the study of glycopeptide efficacy in GISA infections

In recent years, the emergence of Staphylococcus aureus strains with reduced susceptibility to glycopeptides has raised considerable concern. We studied the efficacy of vancomycin and teicoplanin, as well as cloxacillin and cefotaxime, against the infection caused by four S. aureus strains with different glycopeptide and β-lactam susceptibilities (strains A, B, C, and D; MICs for vancomycin of 1, 2, 4, and 8 µg/ml respectively), using a modified model of mouse peritonitis. This optimized model appeared to be straightforward and reproducible, and was able to detect low differences in bacterial killing between antibiotics and also between different S. aureus strains. Bactericidal activities in peritoneal fluid for vancomycin, teicoplanin, cloxacillin, and cefotaxime decreased from -2.98, -2.36, -3.22, and -3.57 log10 cfu/ml, respectively, in infection by strain A (MICs for vancomycin and cloxacillin of 1 and 0.38 µg/ml, respectively) to -1.22, -0.65, -1.04, and +0.24 in peritonitis due to strain D (MICs for vancomycin and cloxacillin of 8 and 1,024 µg/ml). Our data confirm the superiority of β-lactams against methicillin-susceptible S. aureus and show that bactericidal activity of glycopeptides decreases significantly with slight increases in MICs; this finding suggests a reduced efficacy of glycopeptides in the treatment of serious glycopeptide-intermediate S. aureus infections

A mouse peritonitis model for the study of glycopeptide efficacy in GISA infections

In recent years, the emergence of Staphylococcus aureus strains with reduced susceptibility to glycopeptides has raised considerable concern. We studied the efficacy of vancomycin and teicoplanin, as well as cloxacillin and cefotaxime, against the infection caused by four S. aureus strains with different glycopeptide and β-lactam susceptibilities (strains A, B, C, and D; MICs for vancomycin of 1, 2, 4, and 8 µg/ml respectively), using a modified model of mouse peritonitis. This optimized model appeared to be straightforward and reproducible, and was able to detect low differences in bacterial killing between antibiotics and also between different S. aureus strains. Bactericidal activities in peritoneal fluid for vancomycin, teicoplanin, cloxacillin, and cefotaxime decreased from -2.98, -2.36, -3.22, and -3.57 log10 cfu/ml, respectively, in infection by strain A (MICs for vancomycin and cloxacillin of 1 and 0.38 µg/ml, respectively) to -1.22, -0.65, -1.04, and +0.24 in peritonitis due to strain D (MICs for vancomycin and cloxacillin of 8 and 1,024 µg/ml). Our data confirm the superiority of β-lactams against methicillin-susceptible S. aureus and show that bactericidal activity of glycopeptides decreases significantly with slight increases in MICs; this finding suggests a reduced efficacy of glycopeptides in the treatment of serious glycopeptide-intermediate S. aureus infections

Classification models for neurocognitive impairment in HIV infection based on demographic and clinical variables

Objective: We used demographic and clinical data to design practical classification models for prediction of neurocognitive impairment (NCI) in people with HIV infection. Methods: The study population comprised 331 HIV-infected patients with available demographic, clinical, and neurocognitive data collected using a comprehensive battery of neuropsychological tests. Classification and regression trees (CART) were developed to btain detailed and reliable models to predict NCI. Following a practical clinical approach, NCI was considered the main variable for study outcomes, and analyses were performed separately in treatment-naïve and treatment-experienced patients. Results: The study sample comprised 52 treatment-naïve and 279 experienced patients. In the first group, the variables identified as better predictors of NCI were CD4 cell count and age (correct classification [CC]: 79.6%, 3 final nodes). In treatment-experienced patients, the variables most closely related to NCI were years of education, nadir CD4 cell count, central nervous system penetration-effectiveness score, age, employment status, and confounding comorbidities (CC: 82.1%, 7 final nodes). In patients with an undetectable viral load and no comorbidities, we obtained a fairly accurate model in which the main variables were nadir CD4 cell count, current CD4 cell count, time on current treatment, and past highest viral load (CC: 88%, 6 final nodes). Conclusion: Practical classification models to predict NCI in HIV infection can be obtained using demographic and clinical variables. An approach based on CART analyses may facilitate screening for HIV-associated neurocognitive disorders and complement clinical information about risk and protective factors for NCI in HIV-infected patients.