The experts at University College London (UCL) have created a new model for HIV progression. From this model they noticed that HIV spreads through the body using two methods:
- Via the bloodstream
- Directly between cells.
This method is similar to how computer worms spread through both the Internet and local networks to infect as many computers as possible.
The new HIV progression model for this “hybrid spreading” accurately predicts patients’ progression from HIV to AIDS in a major clinical trial.
Detailed sample data from 17 London-based patients were used to verify the model, indicating that “hybrid spreading” provides the most suitable explanation for HIV progression and highlights the benefits of early treatment.
HIV infects CD4+ T cells – the cells that play a vital role in the immune system and protect us from diseases. As HIV advances, the number of active T cells in the body reduces until the immune system can no longer function properly – a state known as “acquired immune deficiency syndrome” or AIDS.
The World Health Organization (WHO) guidelines recommend that HIV treatment should only commence once the number of T cells in the bloodstream fall below a certain level. However, UCL’s model forecasts that treatment should begin as soon as possible after infection to prevent AIDS from developing in the long term.
“The number of HIV cells in the bloodstream is always relatively low, and our model shows that HIV spread through the bloodstream alone would not be enough to cause AIDS,” explains co-senior author Prof. Benny Chain, UCL Infection and Immunity. “It is likely that when HIV gains a foothold somewhere with a high T cell population, such as the gut, it uses a cell-to-cell transfer mechanism to efficiently spread directly between them.” He continues:
“As such, if HIV has already spread to an area rich in T cells by the time treatment begins, preventing its spread through the bloodstream will not stop AIDS. Our model suggests that completely blocking cell-to-cell transfer would prevent progression to AIDS, highlighting the need to develop new treatments.”
HIV model inspired by 2008 damaging Conficker computer worm
The inspiration for the HIV progression model came from similarities between HIV and computer worms such as the highly destructive ‘Conficker’ worm. The Conficker worm was first detected in 2008, which infected military and police computer networks across Europe and is still active today.
Lead author Changwang Zhang, UCL Computer Science, says:
“HIV and Conficker have a lot in common. They both use hybrid-spreading mechanisms, persist for a very long time and are incredibly difficult to eradicate. Our model enables us to explain these important properties and to predict the infection process.”
Changwang’s supervisor, co-author Dr. Shi Zhou, UCL Computer Science, comments, “Although the cybersecurity community organized an unprecedented collaboration to tackle Conficker, they still failed to eliminate Conficker from the Internet. HIV researchers face a similar problem. We hope that our new understanding of hybrid epidemics will help us to fight against Conficker and HIV.”
Previous laboratory research led by co-senior author Dr. Clare Jolly, UCL Infection and Immunity has shown that shown that some drugs are better than others at stopping HIV from spreading directly between cells. However, as the spread occurs inside internal organs, it is unfeasible to measure cell-to-cell spread in patients directly.
“With this new model, we should be able to assess the effectiveness of drugs against different modes of HIV spread in real patients,” explains Dr. Jolly. She concludes:
“This could prove invaluable when interpreting the results of drug trials to understand what works and why. Using computer models to understand processes that we cannot directly observe is common in the physical sciences and supports many fundamental theories. Our model provides strong evidence that cell-to-cell spread is an important part of HIV spread, and we hope to show this directly in future animal studies.”
Contributed by HivPositiveDatingSites.net