No abstract

SUMMARY Antiretroviral therapy (ART) is increasingly being used as an HIV-prevention tool, administered to uninfected people with ongoing HIV exposure as pre-exposure prophylaxis (PrEP) and to infected people to reduce their infectiousness. We used a modelling approach to determine the optimal population-level combination of ART and PrEP allocations required in South Africa to maximize programme effectiveness for four outcome measures: new infections, infection-years, death and cost. We considered two different strategies for allocating treatment, one that selectively allocates drugs to sex workers and one that does not. We found that for low treatment availability, prevention through PrEP to the general population or PrEP and ART to sex workers is key to maximizing effectiveness, while for higher drug availability, ART to the general population is optimal. At South Africa’s current level of treatment availability, using prevention is most effective at reducing new infections, infection-years, and cost, while using the treatment as ART to the general population best reduces deaths. At treatment levels that meet the UNAIDS’s ambitious new 90–90–90 target, using all or almost all treatment as ART to the general population best reduces all four outcome measures considered.

In Africa, the HIV prevalence in rural areas has begun to reach levels estimated within urban settings, where women are also more at risk for both malaria and intestinal parasitic infections. The objective of this review is to assess whether concomitant infections with malaria and/or helminthic diseases have an impact on cervical disease progression in women on HAART. This scoping review was conducted in August 2018. To conduct this scoping review, we searched the relevant studies in electronic databases such as PUBMED, Global Health, EMBASE, CINAHL and SCOPUS published in the year between 1960 and 2018 using the following search terms HAART AND malaria OR Helminth and Female OR women. Eight studies qualified for this review. The literature underscores the need for women on HAART with multiple co-infections to use adjuncts to retain immune recovery and undetectable HIV viral load, to reduce risk of cervical disease progression. A trend for higher risk of CIN3+ in HIV+ women reporting recent malarial infection was observed in one study. Given the public health impact of synergistic interactions between malaria and helminthic infections in HIV/HPV co-infected women on HAART, it is urgent that these interactions are elucidated.

This preprint is the outcome of the “Training Workshop Interdisciplinary Life Sciences”, held in October 2013 in the Lorentz Center, Leiden, The Netherlands. The motivation to organize this event stems from the following considerations: The enormous progress in laboratory techniques and facilities leads to the availability of huge amounts of data at all levels of complexity (molecules, cells, tissues, organs, organisms, populations, ecosystems). Especially data at the cellular level reveal details of life processes we were unconscious of until recently. However, it becomes clear that huge amounts of data alone do not automatically lead to understanding. The data explosion in Life Sciences teaches one lesson: life processes are of a highly intricate and integrative nature. To really understand the dynamic processes in living organisms one must integrate experimental data sets in quantitative and predictive models. Only then one may hope to grasp the functioning of these complex systems and be able to convert information in understanding. In the field of physics, for instance, this strong interaction between experiment and theory is already common practice since centuries, culminating in the 20th century being called the ’Century of Physics’. In contrast to physics, the complex nature of the Life Sciences forces us to work in an interdisciplinary fashion. The necessary expertise is available, but scattered over many scientific disciplines. Only the combined efforts of biologists, chemists, mathematicians, physicists, engineers, and informaticians will lead to progress in tackling the huge challenge of understanding the complexity of life. Researchers in the Life Sciences often focus their research on a rather narrow research field. However, the majority of the upcoming generation of researchers in the Life Sciences should be trained to expand their skills, becoming able to tackle complex, multi-dimensional systems. The knowledge they have to incorporate in their research will stem from a diverse range of disciplines, So, they should be trained to integrate a broad range of modelling approaches in order to deduce quantitative, predictive and often multi-scale models from highly diverse data sets. Present curricula in the Life Sciences hardly offer this kind of training yet. This workshop intends to start filling this gap. Three teams worked on the following open problems: 1) Modeling the influence of temperature on the Regulation of flowering time in Arabidopsis thaliana; 2) Validation of computational models of angiogenesis to experimental data; 3) Reconstructing the gene network that regulates branching in Tomato. This preprint bundles the reports of the three teams.

This preprint is the outcome of the “Training Workshop Interdisciplinary Life Sciences”, held in October 2013 in the Lorentz Center, Leiden, The Netherlands. The motivation to organize this event stems from the following considerations: The enormous progress in laboratory techniques and facilities leads to the availability of huge amounts of data at all levels of complexity (molecules, cells, tissues, organs, organisms, populations, ecosystems). Especially data at the cellular level reveal details of life processes we were unconscious of until recently. However, it becomes clear that huge amounts of data alone do not automatically lead to understanding. The data explosion in Life Sciences teaches one lesson: life processes are of a highly intricate and integrative nature. To really understand the dynamic processes in living organisms one must integrate experimental data sets in quantitative and predictive models. Only then one may hope to grasp the functioning of these complex systems and be able to convert information in understanding. In the field of physics, for instance, this strong interaction between experiment and theory is already common practice since centuries, culminating in the 20th century being called the ’Century of Physics’. In contrast to physics, the complex nature of the Life Sciences forces us to work in an interdisciplinary fashion. The necessary expertise is available, but scattered over many scientific disciplines. Only the combined efforts of biologists, chemists, mathematicians, physicists, engineers, and informaticians will lead to progress in tackling the huge challenge of understanding the complexity of life. Researchers in the Life Sciences often focus their research on a rather narrow research field. However, the majority of the upcoming generation of researchers in the Life Sciences should be trained to expand their skills, becoming able to tackle complex, multi-dimensional systems. The knowledge they have to incorporate in their research will stem from a diverse range of disciplines, So, they should be trained to integrate a broad range of modelling approaches in order to deduce quantitative, predictive and often multi-scale models from highly diverse data sets. Present curricula in the Life Sciences hardly offer this kind of training yet. This workshop intends to start filling this gap. Three teams worked on the following open problems: 1) Modeling the influence of temperature on the Regulation of flowering time in Arabidopsis thaliana; 2) Validation of computational models of angiogenesis to experimental data; 3) Reconstructing the gene network that regulates branching in Tomato. This preprint bundles the reports of the three teams.