High-mobility group box 1 increases platelet surface P2Y12 and platelet activation in sickle cell disease.

Thrombosis and inflammation are intimately linked and synergistically contribute to the pathogenesis of numerous thromboinflammatory diseases, including sickle cell disease (SCD). While platelets are central to thrombogenesis and inflammation, the molecular mechanisms of crosstalk between the 2 remain elusive. High-mobility group box 1 (HMGB1) regulates inflammation and stimulates platelet activation through Toll-like receptor 4. However, it remains unclear whether HMGB1 modulates other thrombotic agonists to regulate platelet activation. Herein, using human platelets, we demonstrate that HMGB1 significantly enhanced ADP-mediated platelet activation. Furthermore, inhibition of the purinergic receptor P2Y12 attenuated HMGB1-dependent platelet activation. Mechanistically, we show that HMGB1 stimulated ADP secretion, while concomitantly increasing P2Y12 levels at the platelet membrane. We show that in SCD patients, increased plasma HMGB1 levels were associated with heightened platelet activation and surface P2Y12 expression. Treatment of healthy platelets with plasma from SCD patients enhanced platelet activation and surface P2Y12, and increased sensitivity to ADP-mediated activation, and these effects were linked to plasma HMGB1. We conclude that HMGB1-mediated platelet activation involves ADP-dependent P2Y12 signaling, and HMGB1 primes platelets for ADP signaling. This complementary agonism between ADP and HMGB1 furthers the understanding of thromboinflammatory signaling in conditions such as SCD, and provides insight for therapeutic P2Y12 inhibition.

High Dose of Metformin Decreases Susceptibility to Occlusive Arterial Thrombosis in Diabetic Mice.

Introduction: Metformin is the most prescribed medication in Diabetes Mellitus(DM). Metformin has shown to decrease mean platelet volume, with promising antiplatelet effects. High doses of Metformin have also been associated with hypercoagulation. We hypothesize that Metformin will protect DM mice from occlusive arterial thrombus formation by altering platelet activation and mitochondrial bioenergetics. Methods: DM was developed by low dose of Streptozotocin, non-DM (healthy) mice are controls. Either vehicle or Metformin was administered twice daily via oral gavage for 7-days. Ferric chloride (FeCl3) arterial thrombosis and tail bleeding time were performed. Whole blood aggregometry, platelet activation/adhesion and mitochondrial bioenergetics were evaluated. Results: Metformin decreased susceptibility of DM mice to arterial thrombosis. Platelet bioenergetics show DM mice have increased platelet mitochondrial respiration, but no differences were observed with Metformin treatment. In non-DM (healthy) mice, Metformin modulated ADP-dependent increase in platelet adhesion. Non-DM (healthy) mice, Metformin shortens bleeding time with faster thrombotic occlusion. Metformin also increased platelet mitochondrial maximal respiration and spare respiratory capacity uniquely in non-DM (healthy) mice. Conclusion: Metformin regulates platelet bioenergetics and ADP-mediated platelet function in DM mice which attenuates susceptibility to arterial thrombosis. Future studies will evaluate clinically relevant doses of Metformin that regulates thrombotic function in diabetic platelets.

Chemical applicability and computation of K-Banhatti indices for benzenoid hydrocarbons and triazine-based covalent organic frameworks.

The novel applications in chemistry include the mathematical models of molecular structure of the compounds which has numerous findings in this area that refers to mathematical chemistry. Topological descriptors play a major role in QSAR/QSPR studies that analyses the biological and physicochemical properties of the compounds. In the recent times, a new type of topological descriptors are proposed, called K-Banhatti indices. In this study the chemical applicability of K-Banhatti indices are examined for benzenoid hydrocarbons (derivatives of benzene). These indices have shown remarkable results through the study of statistical analysis. Subsequently, triazine-based covalent organic frameworks (CoF's) are studied for which [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and HB(G) of a graph G are computed.

High Dose of Metformin Decreases Susceptibility to Occlusive Arterial Thrombosis in Diabetic Mice.

Introduction: Metformin is the most prescribed medication in Diabetes Mellitus(DM). Metformin has shown to decrease mean platelet volume, with promising antiplatelet effects. High doses of Metformin have also been associated with hypercoagulation. We hypothesize that Metformin will protect DM mice from occlusive arterial thrombus formation by altering platelet activation and mitochondrial bioenergetics. Methods: DM was developed by low dose of Streptozotocin, healthy (non-DM) mice are controls. Either vehicle or Metformin was administered twice daily via oral gavage for 7-days. Ferric chloride (FeCl3) arterial thrombosis and tail bleeding time were performed. Whole blood aggregometry, platelet activation/adhesion and mitochondrial bioenergetics were evaluated. Results: Metformin decreased susceptibility of DM mice to arterial thrombosis. Platelet bioenergetics show DM mice have increased platelet mitochondrial respiration, but no differences were observed with Metformin treatment. In healthy mice, Metformin modulated ADP-dependent increase in platelet adhesion. In healthy mice, Metformin shortens bleeding time with faster thrombotic occlusion. Metformin also increased platelet mitochondrial maximal respiration and spare respiratory capacity uniquely in healthy mice. Conclusion: Metformin regulates platelet bioenergetics and ADP-mediated platelet function in DM mice which attenuates susceptibility to arterial thrombosis. Future studies will evaluate clinically relevant doses of Metformin that regulates thrombotic function in diabetic platelets.

Release of hepatic xanthine oxidase (XO) to the circulation is protective in intravascular hemolytic crisis.

Xanthine oxidase (XO) catalyzes the catabolism of hypoxanthine to xanthine and xanthine to uric acid, generating oxidants as a byproduct. Importantly, XO activity is elevated in numerous hemolytic conditions including sickle cell disease (SCD); however, the role of XO in this context has not been elucidated. Whereas long-standing dogma suggests elevated levels of XO in the vascular compartment contribute to vascular pathology via increased oxidant production, herein, we demonstrate, for the first time, that XO has an unexpected protective role during hemolysis. Using an established hemolysis model, we found that intravascular hemin challenge (40 µmol/kg) resulted in a significant increase in hemolysis and an immense (20-fold) elevation in plasma XO activity in Townes sickle cell phenotype (SS) sickle mice compared to controls. Repeating the hemin challenge model in hepatocyte-specific XO knockout mice transplanted with SS bone marrow confirmed the liver as the source of enhanced circulating XO as these mice demonstrated 100% lethality compared to 40% survival in controls. In addition, studies in murine hepatocytes (AML12) revealed hemin mediates upregulation and release of XO to the medium in a toll like receptor 4 (TLR4)-dependent manner. Furthermore, we demonstrate that XO degrades oxyhemoglobin and releases free hemin and iron in a hydrogen peroxide-dependent manner. Additional biochemical studies revealed purified XO binds free hemin to diminish the potential for deleterious hemin-related redox reactions as well as prevents platelet aggregation. In the aggregate, data herein reveals that intravascular hemin challenge induces XO release by hepatocytes through hemin-TLR4 signaling, resulting in an immense elevation of circulating XO. This increased XO activity in the vascular compartment mediates protection from intravascular hemin crisis by binding and potentially degrading hemin at the apical surface of the endothelium where XO is known to be bound and sequestered by endothelial glycosaminoglycans (GAGs).

Errata: Brain tumor IDH, 1p/19q, and MGMT molecular classification using MRI-based deep learning: an initial study on the effect of motion and motion correction.

[This corrects the article DOI: 10.1117/1.JMI.9.1.016001.].

Corrigendum to: A novel fully automated MRI-based deep-learning method for classification of 1p/19q co-deletion status in brain gliomas.

[This corrects the article DOI: 10.1093/noajnl/vdaa066.].

Fibrinogen Mitigates Prion-Mediated Platelet Activation and Neuronal Cell Toxicity.

Prion peptide (PrP) misfolds to infectious scrapie isoform, the ß pleat-rich insoluble fibrils responsible for neurodegeneration and fatal conformational diseases in humans. The amino acid sequence 106-126 from prion proteins, PrP(106-126), is highly amyloidogenic and implicated in prion-induced pathologies. Here, we report a novel interaction between PrP(106-126) and the thrombogenic plasma protein fibrinogen that can lead to mitigation of prion-mediated pro-thrombotic responses in human platelets as well as significant decline in neuronal toxicity. Thus, prior exposure to fibrinogen-restrained PrP-induced rise in cytosolic calcium, calpain activation, and shedding of extracellular vesicles in platelets while it, too, averted cytotoxicity of neuronal cells triggered by prion peptide. Interestingly, PrP was found to accelerate fibrin-rich clot formation, which was resistant to plasmin-mediated fibrinolysis, consistent with enhanced thrombus stability provoked by PrP. We propose that PrP-fibrinogen interaction can be clinically exploited further for prevention and management of infectious prion related disorders. Small molecules or peptides mimicking PrP-binding sites on fibrinogen can potentially mitigate PrP-induced cellular toxicity while also preventing the negative impact of PrP on fibrin clot formation and lysis.

Brain tumor IDH, 1p/19q, and MGMT molecular classification using MRI-based deep learning: an initial study on the effect of motion and motion correction.

Purpose: Deep learning has shown promise for predicting the molecular profiles of gliomas using MR images. Prior to clinical implementation, ensuring robustness to real-world problems, such as patient motion, is crucial. The purpose of this study is to perform a preliminary evaluation on the effects of simulated motion artifact on glioma marker classifier performance and determine if motion correction can restore classification accuracies. Approach: T2w images and molecular information were retrieved from the TCIA and TCGA databases. Simulated motion was added in the k-space domain along the phase encoding direction. Classifier performance for IDH mutation, 1p/19q co-deletion, and MGMT methylation was assessed over the range of 0% to 100% corrupted k-space lines. Rudimentary motion correction networks were trained on the motion-corrupted images. The performance of the three glioma marker classifiers was then evaluated on the motion-corrected images. Results: Glioma marker classifier performance decreased markedly with increasing motion corruption. Applying motion correction effectively restored classification accuracy for even the most motion-corrupted images. For isocitrate dehydrogenase (IDH) classification, 99% accuracy was achieved, exceeding the original performance of the network and representing a new benchmark in non-invasive MRI-based IDH classification. Conclusions: Robust motion correction can facilitate highly accurate deep learning MRI-based molecular marker classification, rivaling invasive tissue-based characterization methods. Motion correction may be able to increase classification accuracy even in the absence of a visible artifact, representing a new strategy for boosting classifier performance.

Heme stimulates platelet mitochondrial oxidant production to induce targeted granule secretion.

Hemolysis, a pathological component of many diseases, is associated with thrombosis and vascular dysfunction. Hemolytic products, including cell-free hemoglobin and free heme directly activate platelets. However, the effect of hemolysis on platelet degranulation, a central process in not only thrombosis, but also inflammatory and mitogenic signaling, remains less clear. Our group showed that hemoglobin-induced platelet activation involved the production of mitochondrial reactive oxygen species (mtROS). However, the molecular mechanism by which extracellular hemolysis induces platelet mtROS production, and whether these mtROS regulate platelet degranulation remains unknown. Here, we demonstrate using isolated human platelets that cell free heme is a more potent agonist for platelet activation than hemoglobin, and stimulates the release of a specific set of molecules, including the glycoprotein thrombospondin-1 (TSP-1), from the α-granule of platelets. We uncover the mechanism of heme-mediated platelet mtROS production which is dependent on the activation of platelet toll-like receptor 4 (TLR4) signaling and leads to the downstream phosphorylation and inhibition of complex-V by the serine kinase Akt. Notably, inhibition of platelet TLR4 or Akt, or scavenging of mtROS prevents heme-induced granule release in vitro. Further, heme-dependent granule release is significantly attenuated in vivo in mice lacking TLR4 or those treated with the mtROS scavenger MitoTEMPO. These data elucidate a novel mechanism of TLR4-mediated mitochondrial regulation, establish the mechanistic link between hemolysis and platelet degranulation, and begin to define the heme and mtROS-dependent platelet secretome. These data have implications for hemolysis-induced thrombo-inflammatory signaling and for the consideration of platelet mitochondria as a therapeutic target in hemolytic disorders.

Mitochondrial reactive oxygen species scavenging attenuates thrombus formation in a murine model of sickle cell disease.

BACKGROUND: Sickle cell disease (SCD) is characterized by hemolysis-associated platelet dysfunction that leads to increased risk of thrombosis and plays a role in the high morbidity and mortality of the disease. The mechanisms by which hemolysis induces platelet activation remain unclear. We recently demonstrated that patients with SCD showed increased platelet mitochondrial reactive oxygen species (mtROS) production that correlates with markers of hemolysis and platelet activation. Experiments in isolated platelets demonstrated that mtROS stimulated platelet activation. However, the role of hemolysis-induced mtROS in thrombus formation in vivo remains unclear. OBJECTIVES: Here, we hypothesize that scavenging of mtROS attenuates the propensity for thrombosis in mouse models of hemolysis. METHODS: We used models of hemolysate infusion into wildtype mice as well as the Berkley transgenic mouse model of SCD, a chronic mode of hemolysis, to test the effect of hemolysis on platelet mtROS production and thrombosis. RESULTS: We show that infusion of hemolysate in wildtype mice induces platelet mtROS production and decreases time to vessel occlusion in a model of ferric chloride-induced carotid artery thrombosis. Increased mtROS and propensity for thrombosis was also observed in the Berkley transgenic mouse model of SCD. Notably, treatment with mtROS scavengers decreased platelet mtROS levels and attenuated the propensity for thrombus formation in both models. CONCLUSIONS: These data demonstrate that mtROS significantly contribute to the mechanism of hemolysis-induced thrombosis in vivo and suggest a potential role for mitochondrially targeted antioxidant therapy in hemolysis and SCD-related thrombosis.

A novel fully automated MRI-based deep-learning method for classification of 1p/19q co-deletion status in brain gliomas.

BACKGROUND: One of the most important recent discoveries in brain glioma biology has been the identification of the isocitrate dehydrogenase (IDH) mutation and 1p/19q co-deletion status as markers for therapy and prognosis. 1p/19q co-deletion is the defining genomic marker for oligodendrogliomas and confers a better prognosis and treatment response than gliomas without it. Our group has previously developed a highly accurate deep-learning network for determining IDH mutation status using T2-weighted (T2w) MRI only. The purpose of this study was to develop a similar 1p/19q deep-learning classification network. METHODS: Multiparametric brain MRI and corresponding genomic information were obtained for 368 subjects from The Cancer Imaging Archive and The Cancer Genome Atlas. 1p/19 co-deletions were present in 130 subjects. Two-hundred and thirty-eight subjects were non-co-deleted. A T2w image-only network (1p/19q-net) was developed to perform 1p/19q co-deletion status classification and simultaneous single-label tumor segmentation using 3D-Dense-UNets. Three-fold cross-validation was performed to generalize the network performance. Receiver operating characteristic analysis was also performed. Dice scores were computed to determine tumor segmentation accuracy. RESULTS: 1p/19q-net demonstrated a mean cross-validation accuracy of 93.46% across the 3 folds (93.4%, 94.35%, and 92.62%, SD = 0.8) in predicting 1p/19q co-deletion status with a sensitivity and specificity of 0.90 ± 0.003 and 0.95 ± 0.01, respectively and a mean area under the curve of 0.95 ± 0.01. The whole tumor segmentation mean Dice score was 0.80 ± 0.007. CONCLUSION: We demonstrate high 1p/19q co-deletion classification accuracy using only T2w MR images. This represents an important milestone toward using MRI to predict glioma histology, prognosis, and response to treatment.

A Fully Automated Deep Learning Network for Brain Tumor Segmentation.

We developed a fully automated method for brain tumor segmentation using deep learning; 285 brain tumor cases with multiparametric magnetic resonance images from the BraTS2018 data set were used. We designed 3 separate 3D-Dense-UNets to simplify the complex multiclass segmentation problem into individual binary-segmentation problems for each subcomponent. We implemented a 3-fold cross-validation to generalize the network's performance. The mean cross-validation Dice-scores for whole tumor (WT), tumor core (TC), and enhancing tumor (ET) segmentations were 0.92, 0.84, and 0.80, respectively. We then retrained the individual binary-segmentation networks using 265 of the 285 cases, with 20 cases held-out for testing. We also tested the network on 46 cases from the BraTS2017 validation data set, 66 cases from the BraTS2018 validation data set, and 52 cases from an independent clinical data set. The average Dice-scores for WT, TC, and ET were 0.90, 0.84, and 0.80, respectively, on the 20 held-out testing cases. The average Dice-scores for WT, TC, and ET on the BraTS2017 validation data set, the BraTS2018 validation data set, and the clinical data set were as follows: 0.90, 0.80, and 0.78; 0.90, 0.82, and 0.80; and 0.85, 0.80, and 0.77, respectively. A fully automated deep learning method was developed to segment brain tumors into their subcomponents, which achieved high prediction accuracy on the BraTS data set and on the independent clinical data set. This method is promising for implementation into a clinical workflow.

A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas.

BACKGROUND: Isocitrate dehydrogenase (IDH) mutation status has emerged as an important prognostic marker in gliomas. Currently, reliable IDH mutation determination requires invasive surgical procedures. The purpose of this study was to develop a highly accurate, MRI-based, voxelwise deep-learning IDH classification network using T2-weighted (T2w) MR images and compare its performance to a multicontrast network. METHODS: Multiparametric brain MRI data and corresponding genomic information were obtained for 214 subjects (94 IDH-mutated, 120 IDH wild-type) from The Cancer Imaging Archive and The Cancer Genome Atlas. Two separate networks were developed, including a T2w image-only network (T2-net) and a multicontrast (T2w, fluid attenuated inversion recovery, and T1 postcontrast) network (TS-net) to perform IDH classification and simultaneous single label tumor segmentation. The networks were trained using 3D Dense-UNets. Three-fold cross-validation was performed to generalize the networks' performance. Receiver operating characteristic analysis was also performed. Dice scores were computed to determine tumor segmentation accuracy. RESULTS: T2-net demonstrated a mean cross-validation accuracy of 97.14% ± 0.04 in predicting IDH mutation status, with a sensitivity of 0.97 ± 0.03, specificity of 0.98 ± 0.01, and an area under the curve (AUC) of 0.98 ± 0.01. TS-net achieved a mean cross-validation accuracy of 97.12% ± 0.09, with a sensitivity of 0.98 ± 0.02, specificity of 0.97 ± 0.001, and an AUC of 0.99 ± 0.01. The mean whole tumor segmentation Dice scores were 0.85 ± 0.009 for T2-net and 0.89 ± 0.006 for TS-net. CONCLUSION: We demonstrate high IDH classification accuracy using only T2-weighted MR images. This represents an important milestone toward clinical translation.

Blood-based bioenergetics: An emerging translational and clinical tool.

Accumulating studies demonstrate that mitochondrial genetics and function are central to determining the susceptibility to, and prognosis of numerous diseases across all organ systems. Despite this recognition, mitochondrial function remains poorly characterized in humans primarily due to the invasiveness of obtaining viable tissue for mitochondrial studies. Recent studies have begun to test the hypothesis that circulating blood cells, which can be obtained by minimally invasive methodology, can be utilized as a biomarker of systemic bioenergetic function in human populations. Here we present the available methodologies for assessing blood cell bioenergetics and review studies that have applied these techniques to healthy and disease populations. We focus on the validation of this methodology in healthy subjects, as well as studies testing whether blood cell bioenergetics are altered in disease, correlate with clinical parameters, and compare with other methodology for assessing human mitochondrial function. Finally, we present the challenges and goals for the development of this emerging approach into a tool for translational research and personalized medicine.

Classification of brain tumor isocitrate dehydrogenase status using MRI and deep learning.

Isocitrate dehydrogenase (IDH) mutation status is an important marker in glioma diagnosis and therapy. We propose an automated pipeline for noninvasively predicting IDH status using deep learning and T2-weighted (T2w) magnetic resonance (MR) images with minimal preprocessing (N4 bias correction and normalization to zero mean and unit variance). T2w MR images and genomic data were obtained from The Cancer Imaging Archive dataset for 260 subjects (120 high-grade and 140 low-grade gliomas). A fully automated two-dimensional densely connected model was trained to classify IDH mutation status on 208 subjects and tested on another held-out set of 52 subjects using fivefold cross validation. Data leakage was avoided by ensuring subject separation during the slice-wise randomization. Mean classification accuracy of 90.5% was achieved for each axial slice in predicting the three classes of no tumor, IDH mutated, and IDH wild type. Test accuracy of 83.8% was achieved in predicting IDH mutation status for individual subjects on the test dataset of 52 subjects. We demonstrate a deep learning method to predict IDH mutation status using T2w MRI alone. Radiologic imaging studies using deep learning methods must address data leakage (subject duplication) in the randomization process to avoid upward bias in the reported classification accuracy.

A study on the impact of fire crackers on airborne microflora during diwali.

Diwali is celebrated widely in Asian countries, with a custom of firing crackers. Crackers pollute the environment with noise, particulate matter and chemicals. There are reports on the variation of particulates during firing crackers but none on airborne microbes. The present study was conducted to know the impact of fire crackers on airborne microflora. The air samples were collected 3 days prior to Diwali, on Diwali and 3 days after Diwali during the year 2017 at 15 different areas in Chennai, India. Andersen N-6 viable particle air sampler was exposed with petridishes containing nutrient agar and potato dextrose agar for the isolation of bacteria and fungi respectively. An average of 1,904 ± 2.5 CFU/m3 of bacteria recorded prior Diwali was reduced by 53.23% on Diwali and increased by 27.37% after Diwali. This reduction on Diwali is attributed to the exposure of bacteria to chemicals emitted by the crackers. For fungi, an average of 235.57 ± 1.67 CFU/m3 was recorded prior Diwali, with an increase of 78.5% on Diwali. The increase in fungal count might be due to the release of spores by ground crackers. The study shows that bacteria are susceptible to the chemicals emitted by fire crackers when compared with fungi.

Unique case of autoantibody mediated inactivation of ADAMTS13 in an Indian TTP patient.

A young Indian female visited hospital as a suspected case of thrombotic thrombocytopenic purpura (TTP) with relapsed thrombotic complications with low platelet counts, infarct in middle cerebral artery and thrombi in microvessels. We first confirmed the deficiency of ADAMTS13 metalloprotease in this patient showing improper cleavage of vWF multimers by her plasma unlike her parents and brother. Although patient had very less ADAMTS13 antigen in plasma, but it did not appear to be the cause of deficiency of the enzyme, because her father had similarly low antigen level and he never had prothrombotic complications. While investigating the genetic change in ADAMTS13, we observed four homozygous-SNPs (g.420T>C, g.1342C>G, g.1716G>A and g.2280T>C) in exon 5, 12, 15 and 19 respectively in patient and her father unlike the heterozygous form of same SNPs in mother and brother. Further to investigate the cause of ADAMTS13 deficiency, we observed an elevated level of antibody against ADAMTS13 in patient unlike her father and other family members. Our study therefore provides the molecular approach of diagnosis of TTP in this patient and also highlights the use of such techniques in India. More importantly, study provides the clue of alternate treatment such as immunosuppressant therapy to this patient.

Utility of Point-of-Care Ultrasonography in Diagnosing Submassive Pulmonary Thromboembolism in a Trauma Patient and Subsequent Anesthetic Management: Case Report and Literature Review.

Point-of-care ultrasonography is defined as ultrasonography brought to the patient's bedside and performed by the provider in real time. The clinician can use these real-time dynamic images immediately (rather than images recorded by a sonographer and interpreted later), allowing findings to be directly correlated with the patient's presenting signs and symptoms. Point-of-care ultrasonography is easily repeatable if the patient's condition changes. Over the past decade, the use of point-of-care ultrasonography has extended to emergency settings and intensive care units. The role of ultrasound in triage patients is not only limited to the Focused Assessment with Sonography for Trauma which includes assessment for hemoperitoneum and hemopericardium, it has also been used to detect the presence of hemothorax, pneumothorax, and intravascular filling status in a trauma patient. However, the use of ultrasonography in detecting pulmonary thromboembolism in trauma has not been commonly reported. We report a patient in whom submassive pulmonary embolism was detected by lung ultrasound and thereafter operated for bilateral open Grade III lower-limb fractures. The surgery was proceeded under bilateral ultrasound-guided femoral sciatic nerve block.

Platelet factor 4 promotes rapid replication and propagation of Dengue and Japanese encephalitis viruses.

BACKGROUND: Activated platelets release cytokines/proteins including CXCL4 (PF4), CCL5 and fibrinopeptides, which regulate infection of several pathogenic viruses such as HIV, H1N1 and HCV in human. Since platelet activation is the hallmark of Dengue virus (DV) infection, we investigated the role of platelets in DV replication and also in a closely related Japanese Encephalitis virus (JEV). METHODS AND FINDINGS: Microscopy and PCR analysis revealed a 4-fold increase in DV replication in primary monocytes or monocytic THP-1 cells in vitro upon incubation with either DV-activated platelets or supernatant from DV-activated platelets. The mass spectrometry based proteomic data from extra-nuclear fraction of above THP-1 lysate showed the crucial association of PF4 with enhanced DV replication. Our cytokine analysis and immunoblot assay showed significant inhibition of IFN-α production in monocytes via p38MAPK-STAT2-IRF9 axis. Blocking PF4 through antibodies or its receptor CXCR3 through inhibitor i.e. AMG487, significantly rescued production of IFN-α resulting in potent inhibition of DV replication in monocytes. Further, flow cytometry and ELISA data showed the direct correlation between elevated plasma PF4 with increased viral NS1 in circulating monocytes in febrile DV patients at day-3 of fever than day-9. Similarly, PF4 also showed direct effects in promoting the JEV replication in monocytes and microglia cells in vitro. The in vitro results were also validated in mice, where AMG487 treatment significantly improved the survival of JEV infected animals. INTERPRETATION: Our study suggests that PF4-CXCR3-IFN axis is a potential target for developing treatment regimen against viral infections including JEV and DV.