Gelatinous Marrow Transformation Associated with Imatinib: Case Report and Literature Review.

Gelatinous marrow transformation (GMT) is a rare condition observed in severe illness or malnutrition, in which the bone marrow contains amorphous "gelatinous" extracellular material, and histopathology demonstrates varied degrees of fat cell atrophy and loss of hematopoietic elements. An association of GMT with imatinib use in chronic myeloid leukemia (CML) has been reported recently. The objective of this study is to describe a case of GMT associated with imatinib use and review the existing similar cases in the literature to identify epidemiological patterns and potential imatinib-induced mechanisms leading to gelatinous conversion.

Innate immune memory and homeostasis may be conferred through crosstalk between the TLR3 and TLR7 pathways.

Toll-like receptors (TLRs) recognize pathogen-associated molecular patterns (PAMPs) and stimulate the innate immune response through the production of cytokines. The innate immune response depends on the timing of encountering PAMPs, suggesting a short-term "memory." In particular, activation of TLR3 appears to prime macrophages for the subsequent activation of TLR7, which leads to synergistically increased production of cytokines. By developing a calibrated mathematical model for the kinetics of TLR3 and TLR7 pathway crosstalk and providing experimental validation, we demonstrated the involvement of the Janus-activated kinase (JAK)-signal transducer and activator of transcription (STAT) pathway in controlling the synergistic production of cytokines. Signaling through this pathway played a dual role: It mediated the synergistic production of cytokines, thus boosting the immune response, and it also maintained homeostasis to avoid an excessive inflammatory response. Thus, we propose that the JAK-STAT pathway provides a cytokine rheostat mechanism, which enables macrophages to fine-tune their responses to multiple, temporally separated infection events involving the TLR3 and TLR7 pathways.

Hidden leprosy cases in tribal population groups and how to reach them through a collaborative effort.

BACKGROUND: Tribal populations are an underserved population group and access to health services is a major challenge for them. Since leprosy treatment is integrated with the general health services, identifying leprosy cases is not be easy in these settings and they remain as endemic reservoirs, unless greater efforts are made to reach them. METHODOLOGY: An active search operation was conducted in the tribal colonies in four pre-identified Health & Nutrition Clusters, Nellore district, Andhra Pradesh, India, in 2013. After a brief training, village health nurses and selected volunteers covered all the households, showing flash cards with photos of leprosy cases and enquiring if there was any resident with a similar condition. Suspects were listed and examined by the district leprosy supervisor and field coordinators from Damien Foundation. Follow up interviews were done after one year to assess the treatment completion rate. RESULTS: Village health workers covered 47,574 people living in the tribal colonies and identified 325 leprosy suspects. Among them, 70 were confirmed as new leprosy cases. The prevalence of previously undetected leprosy cases was found to be 14.7/10,000. Out of 70 cases, 19 (27%) were children, 35 (50%) were female, 32 (45.7%) were classified as MB leprosy, 6 (8.6%) had a leprosy reaction and 11 (15.7%) persons had Grade 2 disability at the time of diagnosis. The treatment completion rate was found to be 74% at the end of one year. CONCLUSION: The study reveals a very high burden of leprosy among the tribal population and demonstrates how resources can be mobilized from government, NGO and local community sources to promote early case detection among underserved population groups.

The self-limiting dynamics of TGF-ß signaling in silico and in vitro, with negative feedback through PPM1A upregulation.

The TGF-ß/Smad signaling system decreases its activity through strong negative regulation. Several molecular mechanisms of negative regulation have been published, but the relative impact of each mechanism on the overall system is unknown. In this work, we used computational and experimental methods to assess multiple negative regulatory effects on Smad signaling in HaCaT cells. Previously reported negative regulatory effects were classified by time-scale: degradation of phosphorylated R-Smad and I-Smad-induced receptor degradation were slow-mode effects, and dephosphorylation of R-Smad was a fast-mode effect. We modeled combinations of these effects, but found no combination capable of explaining the observed dynamics of TGF-ß/Smad signaling. We then proposed a negative feedback loop with upregulation of the phosphatase PPM1A. The resulting model was able to explain the dynamics of Smad signaling, under both short and long exposures to TGF-ß. Consistent with this model, immuno-blots showed PPM1A levels to be significantly increased within 30 min after TGF-ß stimulation. Lastly, our model was able to resolve an apparent contradiction in the published literature, concerning the dynamics of phosphorylated R-Smad degradation. We conclude that the dynamics of Smad negative regulation cannot be explained by the negative regulatory effects that had previously been modeled, and we provide evidence for a new negative feedback loop through PPM1A upregulation. This work shows that tight coupling of computational and experiments approaches can yield improved understanding of complex pathways.

OpenComet: an automated tool for comet assay image analysis.

Reactive species such as free radicals are constantly generated in vivo and DNA is the most important target of oxidative stress. Oxidative DNA damage is used as a predictive biomarker to monitor the risk of development of many diseases. The comet assay is widely used for measuring oxidative DNA damage at a single cell level. The analysis of comet assay output images, however, poses considerable challenges. Commercial software is costly and restrictive, while free software generally requires laborious manual tagging of cells. This paper presents OpenComet, an open-source software tool providing automated analysis of comet assay images. It uses a novel and robust method for finding comets based on geometric shape attributes and segmenting the comet heads through image intensity profile analysis. Due to automation, OpenComet is more accurate, less prone to human bias, and faster than manual analysis. A live analysis functionality also allows users to analyze images captured directly from a microscope. We have validated OpenComet on both alkaline and neutral comet assay images as well as sample images from existing software packages. Our results show that OpenComet achieves high accuracy with significantly reduced analysis time.

Modeling and analysis of biopathways dynamics.

Cellular processes are governed and coordinated by a multitude of biopathways. A pathway can be viewed as a complex network of biochemical reactions. The dynamics of this network largely determines the functioning of the pathway. Hence the modeling and analysis of biochemical networks dynamics is an important problem and is an active area of research. Here we review quantitative models of biochemical networks based on ordinary differential equations (ODEs). We mainly focus on the parameter estimation and sensitivity analysis problems and survey the current methods for tackling them. In this context we also highlight a recently developed probabilistic approximation technique using which these two problems can be considerably simplified.

Approximate probabilistic analysis of biopathway dynamics.

MOTIVATION: Biopathways are often modeled as systems of ordinary differential equations (ODEs). Such systems will usually have many unknown parameters and hence will be difficult to calibrate. Since the data available for calibration will have limited precision, an approximate representation of the ODEs dynamics should suffice. One must, however, be able to efficiently construct such approximations for large models and perform model calibration and subsequent analysis. RESULTS: We present a graphical processing unit (GPU) based scheme by which a system of ODEs is approximated as a dynamic Bayesian network (DBN). We then construct a model checking procedure for DBNs based on a simple probabilistic linear time temporal logic. The GPU implementation considerably extends the reach of our previous PC-cluster-based implementation (Liu et al., 2011b). Further, the key components of our algorithm can serve as the GPU kernel for other Monte Carlo simulations-based analysis of biopathway dynamics. Similarly, our model checking framework is a generic one and can be applied in other systems biology settings. We have tested our methods on three ODE models of bio-pathways: the epidermal growth factor-nerve growth factor pathway, the segmentation clock network and the MLC-phosphorylation pathway models. The GPU implementation shows significant gains in performance and scalability whereas the model checking framework turns out to be convenient and efficient for specifying and verifying interesting pathways properties. AVAILABILITY: The source code is freely available at http://www.comp.nus.edu.sg/~rpsysbio/pada-gpu/

A hybrid Factored Frontier algorithm for Dynamic Bayesian Networks with a biopathways application.

Dynamic Bayesian Networks (DBNs) can serve as succinct probabilistic dynamic models of biochemical networks. To analyze these models, one must compute the probability distribution over system states at a given time point. Doing this exactly is infeasible for large models; hence one must use approximate algorithms. The Factored Frontier algorithm (FF) is one such algorithm. However FF as well as the earlier Boyen-Koller (BK) algorithm can incur large errors. To address this, we present a new approximate algorithm called the Hybrid Factored Frontier (HFF) algorithm. At each time slice, in addition to maintaining probability distributions over local states-as FF does-HFF explicitly maintains the probabilities of a number of global states called spikes. When the number of spikes is 0, we get FF and with all global states as spikes, we get the exact inference algorithm. We show that by increasing the number of spikes one can reduce errors while the additional computational effort required is only quadratic in the number of spikes. We validated the performance of HFF on large DBN models of biopathways. Each pathway has more than 30 species and the corresponding DBN has more than 3,000 nodes. Comparisons with FF and BK show that HFF is a useful and powerful approximate inferencing algorithm for DBNs.

Improved statistical model checking methods for pathway analysis.

Statistical model checking techniques have been shown to be effective for approximate model checking on large stochastic systems, where explicit representation of the state space is impractical. Importantly, these techniques ensure the validity of results with statistical guarantees on errors. There is an increasing interest in these classes of algorithms in computational systems biology since analysis using traditional model checking techniques does not scale well. In this context, we present two improvements to existing statistical model checking algorithms. Firstly, we construct an algorithm which removes the need of the user to define the indifference region, a critical parameter in previous sequential hypothesis testing algorithms. Secondly, we extend the algorithm to account for the case when there may be a limit on the computational resources that can be spent on verifying a property; i.e, if the original algorithm is not able to make a decision even after consuming the available amount of resources, we resort to a p-value based approach to make a decision. We demonstrate the improvements achieved by our algorithms in comparison to current algorithms first with a straightforward yet representative example, followed by a real biological model on cell fate of gustatory neurons with microRNAs.

Erythrocyte membrane sulfatide plays a crucial role in the adhesion of sickle erythrocytes to endothelium.

Enhanced adhesion of sickle erythrocytes to the vascular endothelium and subendothelial matrix is fundamental to the development of vascular occlusion in sickle cell disease. Erythrocyte membrane sulfatide is implicated in the pathogenesis of vasoocclusive crises in sickle cell disease (SCD) patients. Because previous evidence linking sulfatide to cell adhesion has largely been circumstantial due to a lack of reagents that specifically target sulfatide, we used two sulfatide-specific strategies to address the role of erythrocyte membrane sulfatide in sickle cell adhesion to the vascular endothelium: a single-chain fragment variable chain (scFv) antibody against sulfatide as well as cerebroside sulfotransferase-deficient mice incapable of synthesising sulfatide. The sickle erythrocytes from mice and humans adhered at a greater extent and at higher shear stresses to activated endothelium than normal erythrocytes, and approximately 60% of the adhesion was prevented by the anti-sulfatide scFv. Similarly, the extent of adhesion of sulfatide-deficient erythrocytes was lower than normal erythrocytes. These findings suggest an important role for membrane sulfatide in sickle cell disease pathophysiology.

A computational and experimental study of the regulatory mechanisms of the complement system.

The complement system is key to innate immunity and its activation is necessary for the clearance of bacteria and apoptotic cells. However, insufficient or excessive complement activation will lead to immune-related diseases. It is so far unknown how the complement activity is up- or down- regulated and what the associated pathophysiological mechanisms are. To quantitatively understand the modulatory mechanisms of the complement system, we built a computational model involving the enhancement and suppression mechanisms that regulate complement activity. Our model consists of a large system of Ordinary Differential Equations (ODEs) accompanied by a dynamic Bayesian network as a probabilistic approximation of the ODE dynamics. Applying Bayesian inference techniques, this approximation was used to perform parameter estimation and sensitivity analysis. Our combined computational and experimental study showed that the antimicrobial response is sensitive to changes in pH and calcium levels, which determines the strength of the crosstalk between CRP and L-ficolin. Our study also revealed differential regulatory effects of C4BP. While C4BP delays but does not decrease the classical complement activation, it attenuates but does not significantly delay the lectin pathway activation. We also found that the major inhibitory role of C4BP is to facilitate the decay of C3 convertase. In summary, the present work elucidates the regulatory mechanisms of the complement system and demonstrates how the bio-pathway machinery maintains the balance between activation and inhibition. The insights we have gained could contribute to the development of therapies targeting the complement system.

Microvesicle-associated tissue factor and Trousseau's syndrome.

BACKGROUND: Trousseau's syndrome is a prothrombotic state associated with malignancy that is poorly understood pathophysiologically. METHODS AND RESULTS: Here we report studies on the blood of a 55-year-old man with giant-cell lung carcinoma who developed a severe form of Trousseau's syndrome. His clinical course was dominated by an extremely hypercoagulable state. Despite receiving potent antithrombotic therapy, he suffered eleven major arterial and venous thrombotic events over a 5 month period. We examined the patient's blood for tissue factor (TF), the major initiator of coagulation, and found its concentration in his plasma to be forty-one-fold higher than the mean concentration derived from testing of 16 normal individuals. CONCLUSION: Almost all of the TF in the patient's plasma was associated with cell-derived microvesicles, likely shed by the cancer cells.

A decompositional approach to parameter estimation in pathway modeling: a case study of the Akt and MAPK pathways and their crosstalk.

Parameter estimation is a critical problem in modeling biological pathways. It is difficult because of the large number of parameters to be estimated and the limited experimental data available. In this paper, we propose a decompositional approach to parameter estimation. It exploits the structure of a large pathway model to break it into smaller components, whose parameters can then be estimated independently. This leads to significant improvements in computational efficiency. We present our approach in the context of Hybrid Functional Petri Net modeling and evolutionary search for parameter value estimation. However, the approach can be easily extended to other modeling frameworks and is independent of the search method used. We have tested our approach on a detailed model of the Akt and MAPK pathways with two known and one hypothesized crosstalk mechanisms. The entire model contains 84 unknown parameters. Our simulation results exhibit good correlation with experimental data, and they yield positive evidence in support of the hypothesized crosstalk between the two pathways.

P-selectin in arterial thrombosis.

P-selectin is a transmembrane protein present in the alpha granules of platelets and the Weibel-Palade bodies of endothelial cells. Following activation, it is rapidly translocated to the cell surface. P-selectin expression in platelets has been shown to be elevated in disorders associated with arterial thrombosis such as coronary artery disease, acute myocardial infarction, stroke, and peripheral artery disease. P-selectin mediates rolling of platelets and leukocytes on activated endothelial cells as well as interactions of platelets with leukocytes. Platelet P-selectin interacts with P-selectin glycoprotein ligand-1 (PSGL-1) on leukocytes to form platelet-leukocyte aggregates. Furthermore, this interaction of P-selectin with PSGL-1 induces the upregulation of tissue factor, several cytokines in leukocytes and the production of procoagulant microparticles, thereby contributing to a prothrombotic state. P-selectin is also involved in platelet-platelet interactions, i. e. platelet aggregation which is a major factor in arterial thrombosis. P-selectin interacts with platelet sulfatides, thereby stabilizing initial platelet aggregates formed by GPIIb/IIIa-fibrinogen bridges. Inhibtion of the P-selectin-sulfatide interaction leads to a reversal of platelet aggregation. Thus, P-selectin plays a significant role in platelet aggregation and platelet- leukocyte interactions, both important mechanisms in the development of arterial thrombosis.

The incidence of proximal deep vein thrombosis following total knee arthroplasty in an Asian population: a Doppler ultrasound study.

PURPOSE: To investigate the incidence of deep vein thrombosis (DVT) following total knee arthroplasty in an Asian population. METHODS: A prospective study of 149 consecutive cases of total knee arthroplasty done for osteoarthritis was conducted over a 5-year period. All patients underwent duplex ultrasonographic assessment of the lower limbs within the first postoperative week. RESULTS: The incidence of proximal DVT was found to be 4.38% in this study. Symptomology was statistically significant in predicting the presence of proximal DVT in all cases. General anaesthesia was associated with a statistically significant-higher incidence of DVT as compared with regional anaesthesia. There was a significant association between a sedentary lifestyle and the development of DVT. CONCLUSION: The incidence of proximal DVT in Asian patients after total knee arthroplasty is higher than that previously reported for this demographic group.

Sulfatides: targets for anti-phospholipid antibodies.

BACKGROUND: Sulfatides are sulfated glycosphingolipids expressed on the surface of erythrocytes, leukocytes, and platelets. Sulfatides interact with several cell adhesion molecules involved in hemostasis. Beta2-glycoprotein I is an anionic phospholipid-binding plasma protein, and the phospholipid-bound form is the target for most anti-phospholipid antibodies that are associated with recurrent thrombosis, miscarriages, and neurological symptoms. In this study, we examined whether beta2-glycoprotein I forms a complex with sulfatides and thereby becomes a target for anti-phospholipid antibodies. METHODS AND RESULTS: Beta2-glycoprotein I binds to surface-bound sulfatides but not to other glycolipids, such as ceramide, cerebrosides, sphingomyelin, or ganglioside. At a sulfatide coating density of 1 microg/well, beta2-glycoprotein I reaches half-maximal binding at 2.5 microg/mL, and the binding is saturated at 10 microg/mL. The binding of beta2-glycoprotein I also depends on the coating density of sulfatides in the well. At a constant beta2-glycoprotein I concentration of 5 microg/mL, maximal binding of beta2-glycoprotein I is observed at a coating density of 1 mug/well. The serum from 14 patients with anti-cardiolipin antibodies, a subset of anti-phospholipid antibodies, bound to sulfatide-bound beta2-glycoprotein I and previous absorption on cardiolipin-coated surfaces decreased the immunoreactivity toward sulfatide-beta2-glycoprotein I complex by >50% in 12 of 14 patients. Furthermore, immunoaffinity-purified anti-cardiolipin antibodies from 4 of 5 patients reacted with sulfatide-bound beta2-glycoprotein I. CONCLUSIONS: These results show that not only anionic phospholipids, as commonly known, but also sulfatides are targets for most anti-phospholipid antibodies. We therefore postulate that interactions of these antibodies with sulfatides may contribute to some of the clinical symptoms of the anti-phospholipid antibody syndrome.

Sulfatides inhibit platelet adhesion to von Willebrand factor in flowing blood.

Sulfatides are sulfated glycosphingolipids present on cell surfaces that bind to adhesive proteins such as von Willebrand factor (VWF), P-selectin, laminin and thrombospondin. Previous studies have localized the sulfatide-binding site of VWF to amino acid residues Gln626-Val646 in the A1 domain. The A1 domain also contains the binding site for platelet glycoprotein Ib (GP Ib), a site that has been reported to be distinct from the sulfatide-binding site. In this study, we analyzed the interaction of sulfatides with VWF and its effect on GP Ib-mediated platelet adhesion under flow conditions. Recombinant VWF A1 domain (rVWF-A1) bound specifically and saturably to sulfatides (half-maximal concentration of approximately 12.5 microg mL(-1)), binding that was blocked by dextran sulfate (IC(50) approximately equal to 100 microg mL(-1)) but not by heparin at concentrations up to 100 U mL(-1). Furthermore, sulfatides (125 microg mL(-1)) prevented the adhesion of platelets or glycocalicin-coupled polystyrene beads to a rVWF-A1-coated surface under high shear stress. In addition, plasma VWF prebound to a sulfatide-coated surface failed to support subsequent platelet adhesion. These results provide firm evidence that sulfatides bind the VWF A1 domain at a site overlapping the GP Ib-binding site.

Role for sulfatides in platelet aggregation.

BACKGROUND: Sulfatides are sulfated glycosphingolipids present on the surface of oligodendrocytes, renal tubular cells, and certain tumor cells. They appear to be involved in nerve conduction and cell adhesion, but their precise physiological function is not known. METHODS AND RESULTS: Here, we show a novel role for sulfatides as a major ligand for P-selectin in platelet adhesion and aggregation. Sulfatides are expressed on the platelet surface, and platelets expressing sulfatides adhere to P-selectin. Both sulfatide micelles and sulfatide-binding recombinant malaria circumsporozoite protein (MCSP) inhibit this adhesion. In parallel, platelets and CHO cells expressing P-selectin adhere to sulfatides, and anti-P-selectin antibodies inhibit this adhesion. Furthermore, both anti-P-selectin antibodies and sulfatide antagonist MCSP significantly reverse platelet aggregation induced by ADP, collagen, or thrombin receptor-activating peptide, suggesting that sulfatide-P-selectin interactions are necessary for the formation of stable platelet aggregates. CONCLUSIONS: These results show that sulfatide interactions with P-selectin are important in platelet adhesion and platelet aggregation. The sulfatide interactions with P-selectin stabilize platelet aggregates, representing a new mechanism of platelet aggregation that may play a significant role in hemostasis and thrombosis.