First experience with cluster

I have been thinking about using our cluster but had been so far procrastinating until now. So this past week I thought I should submit a job myself instead of asking others to do this. Even if others submit jobs for me, I need to know some basics of working with clusters … and I mean real basics….

So, I borrowed a completely written script from a smart colleague in which I had to change few words only, basically location of files – input files and output files. And then I took that step … step of submitting a job to a computer cluster.

Result: complete failure; I have been so far unable to run that one… and I am talking about one only … job. Every time when I submit I get error “Requeued job is waiting for rescheduling”. I have still not figured out what and where the problem is. I have been asking friends and colleagues and they have been very forth coming but despite their best efforts and my repeated attempts (and prayers) I have gotten nothing but failure.

However, in the process I have learned few shell commands which I would probably have never learned … at least not this soon.

sh : submit your script

bjobs : submit your job

bjobs –lp : see why your job is still pending- this is the command that told me that my job was waiting for rescheduling or something… whatever!

bkill : get rid of the job that you have submitted

bkill –q <queue name> –u all 0 : this will kill all jobs in that queue

bhosts : shows hosts and load on them

busers : shows your submitted work/jobs

busers all : shows submitted jobs by everyone

bqueues : shows different queues

Alright, so this is enough learning so far. I have to get back to trying again and again and see if repetition of same silly things changes anything ……..

WOW! Interesting spin……

So I get these several newsletters in my email everyday …. Often I delete them without reading and sometimes I eyeball them. Today I got one from ‘MedPage Today’ (www.medpagetoday.com). The headline says “AHA: Drug-eluting stent safe in large artery disease” and then it goes on to say ...

“CHICAGO -- Among patients with coronary disease in large arteries, treatment with a drug-eluting stent was as safe as treatment with a bare-metal one, results of a large international study showed.”

The correct and realistic headline should be that “bare-metal stents are as good as drug-eluting stents (DES) in large artery disease”. In fact, this study is a win for bare-metal stent (BMS) proving that BMS can be used without any hesitation in large vessel disease. Headline on the other hand, tries to portray that it’s safe to continue using DES for large vessel disease.

Platelets and Apoptosis

Platelet Lifespan

Various in vivo and in vitro methods can be used to determine platelet lifespan. One often recommended is the use of 111indium-labelled platelets. In this method, labeled platelets are injected into the patient and samples are collected at various time intervals (at 45 min, 2, 3, 4 hours) after injection and then daily for up to 10 days. Recovered platelets are calculated from each sample, data is plotted on an arithmetic graph paper and survival time is calculated.

What Determines Platelet Lifespan?

The lifespan of a platelet in circulation is about 8-10 days and dying platelets are continuously replaced by new platelets formed in the bone marrow. Platelets are removed from circulation either by consumption during hemostasis or through uptake by reticuloendothelial (RE) system. For the later process, initially, it was thought that platelets die due to usual ‘wear and tear’ while they are in circulation. Various lines of evidence suggested this possibility. For example, older platelets are less responsive to physiological agonists as compared to younger platelets. More recently, there is increasing evidence that platelets undergo programmed cell death through apoptosis and during this process express certain receptors on their surface that lead to uptake by RE system.

Apoptosis

There are two pathways through which apoptosis can be triggered; extrinsic and intrinsic. Extrinsic pathway is activated by the stimulation of cell-surface receptors (death receptors) which leads to the formation of Death Inducing Signaling Complex (DISC) and ultimately of caspases. On the other hand, intrinsic pathway is activated when the intracellular balance of pro-apoptotic and anti-apoptotic proteins tilt in the favor of the pro-apoptotic proteins. The pro-apoptotic proteins then trigger mitochondrial damage, which initiates the apoptosis cascade.

BCL-2 Family of Proteins

BCL-2 family of proteins is mainly responsible for intrinsic pathway of apoptosis (also called programmed cell death). There are about 25 proteins in this family. Some of these are pro-apoptotic while others are anti-apoptotic. A third subgroup within this family (BH3-only) may be involved in sensing signals that trigger programmed cell death. Anti-apoptotic proteins include Bcl-2, Bcl-w, Bcl-XL, Mcl-1 and A1 while pro-apoptotic proteins are mainly Bak and Bax. . BH3-only proteins include Bim, Bad, Bmf, Hrk, Bik, Noxa, and Puma. Together these proteins regulate programmed cell death.

Platelet Apoptosis

In a series of elegant experiments Mason et al has shown that the main anti-apoptotic protein in platelets is Bcl-XL [17382885]. They showed that mutations in Bcl-XL gene resulted in dose dependent reductions in platelet lifespan. The found that the major pro-apoptotic protein in platelets is Bak and to a minor extent Bax. Experiments in which the genes for these proteins were deleted result in doubling of the platelet lifespan. BH3-only proteins also appear to play important pro-apoptotic role in platelet lifespan as BH3-only mimetic compounds trigger apoptosis and rapid development of thrombocytopenia. In contrast, platelets from double-null mice (mice knocked out for both Bak and bax) are refractory to BH3-only mimetic compounds suggesting that the effect of BH3-only proteins is mediated through Bak and Bax.

In a study recently published study Kelly et al [19936621] showed that Bad-deficient mice had elevated platelets in their blood. They further showed that Bad is present in platelets and that bone marrow of Bad deficient mice showed normal number of megakaryocytic. They further studied the half life of platelets from Bad-deficient mice and found it to be modestly increased. To be certain that this was the intrinsic property of the platelets and not due to other host factors, they injected platelets from Bad-deficient mice into wild-type mice and found increased platelet lifespan. These series of experiments suggest that Bad acts by increasing the lifespan of platelets. On the other hand, mice deficient of another BH3-only protein, Bim, has mild thrombocytopenia. Bim appears to be involved in platelet formation by megakaryocytic and therefore, its deficiency is associated with impaired platelet formation. Interestingly, mice deficient in both Bad and Bim have normal number of platelets in their blood.

Another recent study shed some more light on the role of Bad in platelet lifespan. Catani et al [19936621] showed that activation of type-1 cannabinoid receptor by either endocannabinoid anandamide or methanandamide result in prolongation of platelet lifespan. This effect appears to be mediated though activation of Akt which, in turn, phosphorylates Bad (a BH3-only protein). A phosphorylated Bad cannot enter mitochondria and thus unable to bind and inactivate the anti-apoptotic Bcl-XL protein. Thus cytosolic sequestration of Bad results in prolongation of platelet lifespan in this model.

Vitamin D and Arterial Pulse Wave Velocity

Ok, so here is a study that continues the discussion of vitamin D supplementation to enhance health (or a surrogate of health). In this randomized trial, authors took 49 Black teens with mean age of 16.3 years and gave one group 2000 IU of vitamin D while control group was given 400 IU daily. Investigators measured carotid-femoral pulse-wave velocity (PWV) before and after 16 weeks of therapy in both groups. Investigators noticed a significant decrease in PWV in subjects taking higher dose of vitamin D (experimental group) as compared to the control group (group that was given 400 IU/day). In fact, in the control group PWV increased during the 16 week period.

This was despite the fact that both groups received vitamin D. To be sure that oral vitamin D was enough to raise serum vitamin D levels, investigators checked serum levels of vitamin D. Interestingly, serum levels increased in both groups.

Let’s see experimental group first (in nmol/L):
Baseline: 33.1
4 weeks: 55.0
8 weeks: 70.9
16 weeks: 85.7

Now PWV at baseline in the experimental group was
Baseline: 5.41 m/s
16 weeks: 5.33 m/s
p-value: 0.03

Ok, so this is relatively straightforward story so far, vitamin D was given, serum levels increased, and there was decrease in PWV. But lets see what happens with the control group; serum vitamin D levels were as below (in nmol/L):
Baseline: 34
4 weeks: 44.9
8 weeks: 51.2
16 weeks: 59.8

There is a rise in vitamin levels although not as pronounced as with 2000 IU but there is a considerable increase which is statistically significant as well. Now, if vitamin D is really effective then there should be some decrease in PWV although it might not be as much as with the high dose group, right? Lets see what was the PWV in the control group:
Baseline: 5.38 m/s
16 weeks: 5.71 m/s
p-value: 0.02

Oops! There is an increase in PWV and this is despite the fact that the serum levels of vitamin D almost doubled. In other words, this group was better off without any vitamin D supplementation. Hum! How can we interpret these findings? Is it possible that there is a cut-off after which vitamin D is effective? We know that is not the case; there is no consensus about what is the optimum level of vitamin D but it is much closer to 35 than to 60 and certainly not 80 nmol/L. Is it possible that very high vitamin D acts differently? Or is it possible that this is simply a result that happened by chance alone, that because the effect was in the correct direction and that it was consistent with the currently accepted wisdom. We don’t know but this is likely as the sample size was small. It is possible that blinding was not adequate enough and an investigator with a belief that vitamin D is effective may have interpreted PWV studies differently. We don’t know and while we don't know it is difficult to understand these results.

Intra-individual Variability in Platelet Responsiveness to Clopidogrel

Clopidogrel, in combination with aspirin, is a commonly used anti-platelet agents after PCI (percutaneous coronary intervention) in CHD patients. In one study, about 70% of the inter-individual variability in platelet response to clopidogrel is due to hereditary factors. A polymorphism in the CYP2C19 has been shown to be significantly associated with poor platelet response to clopidogrel. Even more important, poor platelet responsiveness to clopidogrel in patients with PCI has been shown to be associated with increased MACE (major adverse cardiac events).

While focus has been generally on inter-individual variation, it is possible that there is a significant intra-individual variability. This difference can't be explained by stable factors such as genetics or gender but is likely to be due to factors that vary over a short period of time. These include inflammatory state.

In recently published study, Armero et al examined patients on two different occasions after they had clopidogrel 600 mg loading dose. Platelet reactivity was measured using VASP (vasodilator-stimulated phosphoprotein). Interestingly, they found that there was a poor intra-individual correlation between the two occasions (kappa 0.33). In 65% of patients, platelet inhibition increased on the second evaluation while in 35% of the patients, platelet inhibition decreased.

The implications of this finding are worthy of notice. This mean that there are some rapidly varying factors that can alter platelet responsiveness to clopidogrel. On potential candidate is inflammation, although this was not measured and tested as such in this study. Investigators did measure leukocyte count and fibrinogen (and there was no difference) but both are rather crude measures of low-grade inflammation. Other possibilities include poor glycemic control in diabetics; in fact, investigators did find a relationship between the presence of diabetes and poor clopidogrel responsiveness.

Mutation T@Ster: Evaluation For Disease-Causing DNA Sequence Alterations

This is a web-based bioinformatics tool for rapid evaluation for the disease-causing DNA sequence alterations. MutationT@ster integrates information from different biomedical databases and analyses evolutionary conservation, splice-site changes, loss of protein features and changes that might affect the amount of mRNA to predict consequences of a polymorphism. The test is quite fast and a typical query takes less than 0.3 seconds to complete.

Its limitations include 1) inability to analyze insertion-deletions greater than 12 base pairs, 2) inability to analyze alterations spanning an intron-exon border, and 3) analysis of non-exonic alterations is restricted to Kozak consensus sequence, splice sites and poly(A) signal.

Other software with similar capability are: 1) Panther, 2) Pmut, 3) PolyPhen and PolyPhen-2, and 4) SNAP (screening for non-acceptable polymorphisms).