eric48:
Viruses are obligate parasites of autonomously replicating organisms... (which lymphocytes are...)

Thanks for the encouraging PMs... I'll answer them and also provide further findings on NVP and ABC

recommended readings (hope you have enjoyed the Zombies!)

Not free, hard copy only: Adaptive Dynamics of infectious diseases (U. Dieckmann 2002)

At page 183: The virus seeks to derive the maximum benefits from the cell's replicative machinery at the least cost to itself

Not free, PDF exists: Handbook of regression and modeling (applications for the clinical and Pharmaceutical industries) by Daryl Paulson 2006 Not my favorite, but has a lot of self learning tables, examples, figures and is ubiquitous in clinical labs. Lowdown: mostly linear regression

very graphical explanation of derivation p. 28 fig 2.5; (use amazon's look inside with search words: steam exposure)

Those not understanding the basics of triphasic cell decay (hence VL decay), see fig 3.5 (scroll down on amazon's look inside). The graph gives a good approx. idea

Let's do derivation as per Delta(R)/Delta(T) = R(t) - R(t-1) / (t) - (t-1), as we have a fairly frequent sampling, and plot dR / dT as a function of R (R defined as CD4/CD8 ratio) and plot vs R (for ease of use I'll use, abusively, d in place of Delta). We can then do a convincing nonlinear, exponential, regression (not covered by Paulson)

(note: this is done on MY specific labs, so don't over interpret) As we can see, when R < 1 the speed (dR/dt) is >0 : R moves up towards 1 When R=1 , the speed is 0 : R stays at 1 When R > 1 , speed is < 0 : R moves back towards 1

So my doc, who made predictions only twice (at month 6 to predict that R will 'normalize' to 1, and when R was 1.9, saying it will go down) did this at very limited risk. He who sees many patients, has 'visually' integrated this basic rule that raises his credibility at minimal statistical cost, as lab tests tends to make him right. In this perspective, then, 1 is an attractor of R; R should converge to 1 and stay around there: this is statistically correct but dynamically wrong

Wrong ? What is wrong ? How do we know it is wrong ? 1 is (interestingly) a magic, pivotal, number for R (being at least the rounded lower value for 'normal' range), but is NOT a universal attractor

Quiz: 1 is NOT a universal attractor for R... Prove it, solve it !

Next post: CD4/CD8 dynamic mystery solved !

Stay tuned : @HIVPharmaCure (pls RT) Cheers ! Eric pointer: http://tinyurl.com/HIVPharmaCure-15 (please do not highjack, thanks!)

eric48:
It's a magical world, Hobbes, ol’ buddy... Let's go exploring!

I did not publish my latest forecast (got my fingers burnt last time); I should have... The labs results are right on. As of Nov. 15 2013: CD4: 983 CD4%: 38 CD8%: 27 ratio: 1.4 VL <20

recommended readings

If you are on V&K and think of ridding of Kivexa (aka Epzicom): Nevirapine-raltegravir combination, a NRTI and PI/r sparing regimen... http://www.ncbi.nlm.nih.gov/pubmed/24145365

And, on the other hand, if you would like kiss good bye to Viramune: Dolutegravir plus abacavir-lamivudine... http://www.ncbi.nlm.nih.gov/pubmed/24195548

Just looking at the graph posted here: http://tinyurl.com/nw65oxq we know that 1 is not an attractor for CD4/CD8 ratio: there are 3 subgroups clustered in 2 groups: those with ratio > 1, who cluster around 1.4 - 1.5 ; we did the maths here: http://tinyurl.com/jwcgptj

For those with ratio < 1, we use Chomont's data and find that they cluster at 0.68 So, statistically there are (at least) 2 statistically stable attractors: 0.7 and 1.4. We will see later one that there may be a transient attractor at 1.0 and may be a stable attractor at 2.8, but we are not yet there

The problem with R (aka CD4/CD8 ratio) lies in its composite nature. If you own stocks labelled in a foreign currency, your portfolio may go up because the stock go up OR that foreign currency goes up and vice versa. And when CD4% goes up significantly, then CD8% is likely a go down at least a bit...This makes R more volatile than the underlying trend is. To correct for this we introduce a mathematically more rugged animal: Ropt, optimized ratio, the calculation of which goes beyond the spirit of this thread. The algorithm is not that complex, but, I assume the reader does not really bother. Any signal processing minded person knows the trick. So it is not so much what Ropt is that matters, but rather that it is a better toy to play with.

Let's plot R and Ropt. As you can see below they are not very different, similar trends, except that Ropt is, thus far, more stable

Next post: Exploring a new territory with Ropt derivation: Ropt goes to the Yukon !

Stay tuned : @HIVPharmaCure (pls RT) Cheers ! Eric pointer : http://tinyurl.com/HIVPharmaCure-16 (please do not copy, do not highjack, thanks!)

eric48:
Things are never quite as scary when you've got a best friend.

recommended readings CD4 and CD8 T Cell ... Roles of Homeostasis (Marta Catalfamo 2011) http://m.jimmunol.org/content/186/4/2106.full

While there is little on CD4 and CD8 dynamics, some recent articles are highlighting the driving forces underneath CD4 and CD8 population dynamics. To make it short, the underlying forces are independent in trend and linked in their maximum (aka carrying capacity): CD4 have an autonomous, self fueled proliferation pattern where CD4 growth is driven by ... CD4s themselves. And CD8 have a proliferation pattern driven by signs of infections (such as free RNA, aka VL and signaling infected cells)

Graph on my previous post is showing one thing of interest: we are now 3 and 1/2 years into a treatment started quite early and we see, on the ratio trend, that the immune restoration is still in progress. This graph is better than a thousand words to show the importance of time in recovery. The median treatment time in the SMART study was 3.5 y... Why would anyone be hopefull that treatment interruption can be successful if the recovery is still in progress ?

Earlier, we had graphed the derivative of R: a nice but not over exciting exercise. Today, I am posting a graph that I think is quite unique. Let's graph the derivative of R-opt (aka dRopt/dt, or speed, if you want) vs Ropt.

I had to move, very marginally, the X coordinates of 3 data points, to improve clarity. Even marginally edited for educational purposes, this graph is much more exciting. There you go:

Keeping in mind the diagram I posted here: http://tinyurl.com/HIVPharmaCure-10

I hope you are guessing where I am getting at ;-)

Next post: Ropt potential well and recovery progress !

Stay tuned : @HIVPharmaCure (pls RT) Cheers ! Eric pointer : http://tinyurl.com/HIVPharmaCure-17 (please do not copy, do not highjack, thanks!)

eric48:
Most natural systems evolve according to multistep processes. We refer to these dynamics as punctuated evolution

Nonequilibrium systems evolve in time, not according to a smooth or gradual fashion, but by going through periods of stagnation interrupted by fast changes.

I have finally found ways to graph the multistep changes in a very convincing manner, so next posts are going to be exiting!

I am not losing focus: show the 'unfortunate' users of 'low cost' NVP that its very simple structure makes it a very good ally in reservoir lowering strategies.

Yet, non-progress may involve steps forwards and steps backwards, and, I'd like to make sure that progress is sustained. 2013 started with mixed results with ratio flickering around 1. For 6 months now we have repeatedly had a ratio > 1.4

So we can look forward to 2014

In next posts, I'll explain the significance of the above graph, move to another very exiting graph, review my latest tricks against 'brain fog', anxiety and sleep issues and finally explore if our (earlier defined) point G is an extinction point of sorts and see when we can hope to reach a point where we can experiment further.

I remain convinced that remission is possible. It is just a matter of time until we find the keys to the challenging hurdle

This is Xmas time, so no maths for this post. Feel free to throw a marble (or glass sphere) in your cereal bowl, watch the movement, speed, etc. in case you have forgotten about potential wells. We may need that...

I did not like 2013 much. But I have enjoyed the 1400 CD4, and the PMs, and the graphs, and time spent with you guys.

So, I wish you all a Merry Christmas

Looking forward to the Holidays and challenging discussions in 2014

Next post: Ropt potential well and recovery progress !

Stay tuned : @HIVPharmaCure (pls RT) Cheers ! Eric pointer : tinyurl.com/HIVPharmaCure-18 (please do not copy, do not highjack, thanks!)

eric48:
How could they see anything but the shadows if they were never allowed to move their heads -Plato

recommended readings viral load white paper by B. Taiwo http://tinyurl.com/qzlblor A very informative review of VL, blips, and clinical management

Characteristics determinants of T-cell phenotype normalization (not free) http://www.ncbi.nlm.nih.gov/pubmed/24304582 The abstract is all we need, but, for further reading go there (free): http://tinyurl.com/pzrb3fh

T-cell phenotype (TCP) has several definitions and the one, here, is interesting.

We can envision several types of 'cures' (aka HIV cure) -A- treatments coming from the cancer specialists (graft, radiotherapy) -B- Bio treatments (Sangamo, therapeutic vaccine, vaccines...) -C- PharmaCure (FAUCI's concept when he attempted Treatment Interuptions) -D- Non-portable cures (Visconti...)

A : no thanks; B : Somewhere, sometime, most likely the best, but, not in our reach; D : We can learn from them, but if the prerequisite is that you get meds within a few days of infection, then, as far as I am concerned, it's too late C (Pharmacure) is slow progression from one status to another until We reach ultimate favorable factors and see if a remission is possible

Thus we need to define these 'status': the left hand side of our cursor is disease, the right side is 'cured' and there are things in between that are step stones towards the cure itself.

TCP as defined in the above article is : - CD4 T-cell count >532 - T-cell homeostasis (CD3> 65% and < 85%) - CD4:CD8 ratio >1.2

The T-cell homeostasis is unusual, interesting... This is not something we consider much. Yet, at baseline, 32% of patients had lost homeostasis. Not everyone recovers this. If you do not know your CD3%, just add CD4% + CD8% and you are about right. So, if you do not have access to CD3% , per se, substitute with (CD4% + CD8%)

Only 2% of patients meet the 3 criterias. Of note, achieving a normal CD4:CD8 ratio was not associated with better clinical outcome.

Interestingly, 99% exhibited ratio dysregulation at baseline... In other words, in that game, we all start in the same line, pretty much like in a video or role game. Patients initiating meds at CD4 600 have a head start in the CD4 contest, but, not in the ratio marathon. For me, CD4 T-cell count >532 cells took 3 weeks but CD4:CD8 ratio >1.2 took ... 3 years !

Pretty much as in cross country or cycling, how fast you get to the goal depends on the relief or terrain (aka topography). And recording speed tells you about the map ... Revealing the underlying terrain ... This is exactly what my latest graph aims at.

Quiz: are you seing the relief in the speed graph ? It's easy

Next post: Ropt potential well explained !

Labs as of 2014-01-02 : CD4: 1091 (37%) CD8:855 (29%) CD4/CD8: 1.3

Happy New Year !

Stay tuned : @HIVPharmaCure (pls RT) Cheers ! Eric pointer : http://tinyurl.com/HIVPharmaCure-19 (please do not copy, do not highjack, thanks!)