Narrow Results

Human immunodeficiency virus-1 (HIV-1) integrase appears to be a crucial target for developing new anti-HIV-1 therapeutic agents. Different quantitative structure–activity relationships (QSARs) algorithms have been used in order to develop efficient model(s) to predict the activity of new pyridinone derivatives against HIV-1 integrase. Multiple linear regression (MLR) and combined principal component analysis (PCA) with MLR have been applied to build QSAR models for a set of new pyridinone derivatives as potent anti-HIV-1 therapeutic agents. Four different approaches based on MLR method including; concrete-MLR, stepwise-MLR, concrete PCA–MLR and stepwise PCA–MLR were utilized for this aim. Twenty two different sets of descriptors containing 1613 descriptors were constructed for each optimized molecule. Comparison between predictability of the “concrete” and “stepwise” procedure in two different algorithms of MLR and PCA models indicated the advantage of the stepwise procedure over that of the simple concrete method. Although the PCA was employed for dimension reduction, using stepwise PCA–MLR model showed that the method has higher ability to predict the compounds’ activity. The stepwise PCA–MLR model showed highly validated statistical results both in fitting and prediction processes ($R_{\mathrm{\text{test}}}^2=0.78$ and $Q^2=0.80$). Therefore, using stepwise PCA approach is suitable to remove ineffective descriptors, which results in remaining efficient descriptors for building good predictability stepwise PCA–MLR. The stepwise hybrid approach of PCA–MLR may be useful in derivation of highly predictive and interpretable QSAR models.

This paper presents a nonlinear sex-structured mathematical model to study the spread of HIV/AIDS by considering transmission of disease by heterosexual contact. The epidemic threshold and equilibria for the model are determined, local stability and global stability of both the "Disease-Free Equilibrium" (DFE) and "Endemic Equilibrium" (EE) are discussed in detail. The DFE is shown to be locally and globally stable when the basic reproductive number ℛ₀ is less than unity. We also prove that the EE is locally and globally asymptotically stable under some conditions. Finally, numerical simulations are reported to support the analytical findings.

A class of four linear and nonlinear differential equations models is given to describe the detection of HIV-positive individuals in Cuba through random screening and contact tracing. The basic reproduction number is obtained for each of the four models. Cuban HIV data from 1986 to 2002 are used to fit the models for the purpose of comparison. We also use the models to gauge the difference in detection time through random screening and contact tracing. Remarks on the implications for intervention measures and treatment of people living with HIV in Cuba are also given.

In this paper we develop and analyse a model for the spread of HIV/AIDS amongst a population of injecting drug users. We examine the impact on the spread of disease caused by allowing addicts to progress through three distinct stages of variable infectivity prior to the onset of full blown AIDS. We first state a three stage infectivity model of the transmission of HIV and perform an equilibrium and stability analysis on this model. We find that there is a critical threshold parameter R₀ which determines its behaviour. If R₀≤1 then there is a unique disease-free equilibrium which is globally stable. If R₀>1 then there is a unique endemic equilibrium which is locally stable. Simulations indicate that if R₀>1, then provided disease is initially present it will tend to the endemic equilibrium. We also extend this model to include recruitment and mortality from AIDS, and find that its long-term behaviour is similar to that of the simple model. We then look briefly at a stochastic version of the model and simulations indicate that again the disease dies out if R₀<1 and if R₀>1 the long-term conditional mean prevalence of disease is approximately the same as in the simple model. We examine the implications of our results for the prevention of the spread of HIV and AIDS amongst drug users. A short discussion concludes the paper.

It has been observed that in many cases one infection can partially protect against another infection or it may lead to a co-infection. For instance, the interaction between infections with different strains, like dengue and malaria or tuberculosis and lepra, induces cross immunity. On the other hand, individuals infected with HIV are much more susceptible to other infections, for instance, tuberculosis. We propose a compartmental model to describe the transmission of AIDS and tuberculosis in a closed community as an example of one infection activating the other one. When studying the dynamics of the interactions we obtain basins of attraction where one infection prevails over the other one and where both infections coalesce. Furthermore, we are taking into account an adaptation of the model in order to assess the transmission coefficients for HIV and Mycobacterium tuberculosis infections among women inmates.

Monogamous behavior may have a genetic component, in which case it can be subject to natural selection. The mechanism of selection may be the reduced fertility that correlates with STDs. AIDS is a fatal STD (FSTD) capable (without intervention) of severely reducing the human population. We show how, for any mating species, multiple FSTDs (statistical “runs”) occurring within the characteristic time for population recovery, drive that species exponentially towards extinction. Runs of FSTDs occur on geological time scales, providing a general, quantitative model for background extinction rates, and a simpler alternative to the Red Queen hypothesis. It has been difficult to get people to change their risk behavior even when they have full knowledge of how HIV is spread. If we come to understand monogamy (and perhaps polygamy) as heritable traits, then new approaches for slowing the HIV epidemic become apparent.

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