ADVERSE DRUG REACTIONS ASSOCIATED WITH FIRST-LINE ANTI TUBERCULAR DRUGS IN A TERTIARY CARE HOSPITAL OF CENTRAL INDIA: A STUDY OF CLINICAL PRESENTATIONS, CAUSALITY, AND SEVERITY

  Objective: The objective was to study the adverse drug reactions (ADRs) associated with first-line anti-tubercular drugs for clinical presentations, causality, and severity.Methods: A retrospective study was undertaken in a 750 bedded tertiary care teaching hospital of central India for the duration of 1 year (May 2013‑May 2014). Patients diagnosed with tuberculosis and under treatment with the first-line anti-tubercular drugs were study subjects. Causality, preventability, and severity were analyzed and other parameters such as male to female ratio, most affected system, most common class of drug, and common types of ADRs, were studied.Results: Nearly 118 patients were started on anti-tubercular treatment of first-line drugs in the study duration. Out of these 45 patients suffered one or more ADRs with a total number of reported ADRs being 91. 57.77% were males. Maximum patients belonged to the age group of 31-40 years (26.66%). The most commonly involved system was hepatic and biliary system (53.33%) followed by gastrointestinal system (51.11%), the most common ADR observed was disturbed liver transaminases (33.33%) followed by nausea and vomiting (28.88%). Causality assessment by Naranjo's scale showed 58.2% ADRs scoring probable, 31.86% were of possible score, whereas 9.8% definite score category. Severity assessment shows 68.88% cases of mild grading, 31.11% of moderate and no case of severe grading was reported in the study duration.Conclusions: Vigilance regarding these ADRs occurrences can result in early diagnosis and thus, proper management can be instituted earliest. This will build confidence of patients and will decrease the dropouts which in turn can result in decrease chances of developing drug-resistant strains.Keywords: Adverse drug reactions, Multidrug resistant tuberculosis, Extensively drug-resistant tuberculosis, Causality, Naranjo's algorith

Altered Neurocircuitry in the Dopamine Transporter Knockout Mouse Brain

The plasma membrane transporters for the monoamine neurotransmitters dopamine, serotonin, and norepinephrine modulate the dynamics of these monoamine neurotransmitters. Thus, activity of these transporters has significant consequences for monoamine activity throughout the brain and for a number of neurological and psychiatric disorders. Gene knockout (KO) mice that reduce or eliminate expression of each of these monoamine transporters have provided a wealth of new information about the function of these proteins at molecular, physiological and behavioral levels. In the present work we use the unique properties of magnetic resonance imaging (MRI) to probe the effects of altered dopaminergic dynamics on meso-scale neuronal circuitry and overall brain morphology, since changes at these levels of organization might help to account for some of the extensive pharmacological and behavioral differences observed in dopamine transporter (DAT) KO mice. Despite the smaller size of these animals, voxel-wise statistical comparison of high resolution structural MR images indicated little morphological change as a consequence of DAT KO. Likewise, proton magnetic resonance spectra recorded in the striatum indicated no significant changes in detectable metabolite concentrations between DAT KO and wild-type (WT) mice. In contrast, alterations in the circuitry from the prefrontal cortex to the mesocortical limbic system, an important brain component intimately tied to function of mesolimbic/mesocortical dopamine reward pathways, were revealed by manganese-enhanced MRI (MEMRI). Analysis of co-registered MEMRI images taken over the 26 hours after introduction of Mn^(2+) into the prefrontal cortex indicated that DAT KO mice have a truncated Mn^(2+) distribution within this circuitry with little accumulation beyond the thalamus or contralateral to the injection site. By contrast, WT littermates exhibit Mn^(2+) transport into more posterior midbrain nuclei and contralateral mesolimbic structures at 26 hr post-injection. Thus, DAT KO mice appear, at this level of anatomic resolution, to have preserved cortico-striatal-thalamic connectivity but diminished robustness of reward-modulating circuitry distal to the thalamus. This is in contradistinction to the state of this circuitry in serotonin transporter KO mice where we observed more robust connectivity in more posterior brain regions using methods identical to those employed here

Pharmacokinetic/pharmacodynamic analysis of adjuvant pegylated interferon α-2b in patients with resected high-risk melanoma

PurposeHigh-dose pegylated interferon α-2b (peginterferon α-2b) significantly decreased disease recurrence in patients with resected stage III melanoma in a clinical study. We investigated the pharmacokinetics (PK) and safety of high-dose peginterferon α-2b in patients with high-risk melanoma.MethodsFor PK analysis, 32 patients received peginterferon α-2b 6 μg/(kg week) subcutaneously for 8 weeks (induction) then 3 μg/(kg week) for 4 weeks (maintenance). PK profiles were determined at weeks 1, 8, and 12. Exposure-response relationships between peginterferon α-2b and absolute neutrophil count (ANC) and alanine aminotransferase (ALT) level were also studied.ResultsPeginterferon α-2b was well-absorbed following SC administration, with a median T (max) of 24 h. Mean half-life estimates ranged from 43 to 51 h. The accumulation factor was 1.69 after induction therapy. PK parameters showed moderate interpatient variability. PK profiles were described by a one-compartmental model with first-order absorption and first-order elimination. Toxicity was profiled and was acceptable; observed side effects were similar to those previously described. Dose reduction produced proportional decreases in exposure and predictable effects on ANC in an Imax model; however, a PK/pharmacodynamic (PK/PD) relationship between peginterferon α-2b and ALT could not be established with high precision.ConclusionsPeginterferon α-2b was well-absorbed and sustained exposure to peginterferon α-2b was achieved with the doses tested. These data confirm and extend previous PK observations of peginterferon α-2b in melanoma and solid tumors. Our PK/PD model of exposure and ANC effect provides useful information for prediction of peginterferon α-2b-related hematologic toxicity

Molecular and cellular mechanisms underlying the evolution of form and function in the amniote jaw.

The amniote jaw complex is a remarkable amalgamation of derivatives from distinct embryonic cell lineages. During development, the cells in these lineages experience concerted movements, migrations, and signaling interactions that take them from their initial origins to their final destinations and imbue their derivatives with aspects of form including their axial orientation, anatomical identity, size, and shape. Perturbations along the way can produce defects and disease, but also generate the variation necessary for jaw evolution and adaptation. We focus on molecular and cellular mechanisms that regulate form in the amniote jaw complex, and that enable structural and functional integration. Special emphasis is placed on the role of cranial neural crest mesenchyme (NCM) during the species-specific patterning of bone, cartilage, tendon, muscle, and other jaw tissues. We also address the effects of biomechanical forces during jaw development and discuss ways in which certain molecular and cellular responses add adaptive and evolutionary plasticity to jaw morphology. Overall, we highlight how variation in molecular and cellular programs can promote the phenomenal diversity and functional morphology achieved during amniote jaw evolution or lead to the range of jaw defects and disease that affect the human condition

Analysis and prediction of cancerlectins using evolutionary and domain information

<p>Abstract</p> <p>Background</p> <p>Predicting the function of a protein is one of the major challenges in the post-genomic era where a large number of protein sequences of unknown function are accumulating rapidly. Lectins are the proteins that specifically recognize and bind to carbohydrate moieties present on either proteins or lipids. Cancerlectins are those lectins that play various important roles in tumor cell differentiation and metastasis. Although the two types of proteins are linked, still there is no computational method available that can distinguish cancerlectins from the large pool of non-cancerlectins. Hence, it is imperative to develop a method that can distinguish between cancer and non-cancerlectins.</p> <p>Results</p> <p>All the models developed in this study are based on a non-redundant dataset containing 178 cancerlectins and 226 non-cancerlectins in which no two sequences have more than 50% sequence similarity. We have applied the similarity search based technique, i.e. BLAST, and achieved a maximum accuracy of 43.25%. The amino acids compositional analysis have shown that certain residues (e.g. Leucine, Proline) were preferred in cancerlectins whereas some other (e.g. Asparatic acid, Asparagine) were preferred in non-cancerlectins. It has been found that the PROSITE domain "Crystalline beta gamma" was abundant in cancerlectins whereas domains like "SUEL-type lectin domain" were found mainly in non-cancerlectins. An SVM-based model has been developed to differentiate between the cancer and non-cancerlectins which achieved a maximum Matthew's correlation coefficient (MCC) value of 0.32 with an accuracy of 64.84%, using amino acid compositions. We have developed a model based on dipeptide compositions which achieved an MCC value of 0.30 with an accuracy of 64.84%. Thereafter, we have developed models based on split compositions (2 and 4 parts) and achieved an MCC value of 0.31, 0.32 with accuracies of 65.10% and 66.09%, respectively. An SVM model based on Position Specific Scoring Matrix (PSSM), generated by PSI-BLAST, was developed and achieved an MCC value of 0.36 with an accuracy of 68.34%. Finally, we have integrated the PROSITE domain information with PSSM and developed an SVM model that has achieved an MCC value of 0.38 with 69.09% accuracy.</p> <p>Conclusion</p> <p>BLAST has been found inefficient to distinguish between cancer and non-cancerlectins. We analyzed the protein sequences of cancer and non-cancerlectins and identified interesting patterns. We have been able to identify PROSITE domains that are preferred in cancer and non-cancerlectins and thus provided interesting insights into the two types of proteins. The method developed in this study will be useful for researchers studying cancerlectins, lectins and cancer biology. The web-server based on the above study, is available at <url>http://www.imtech.res.in/raghava/cancer_pred/</url></p

The use of microbubbles to target drug delivery

Ultrasound-mediated microbubbles destruction has been proposed as an innovative method for noninvasive delivering of drugs and genes to different tissues. Microbubbles are used to carry a drug or gene until a specific area of interest is reached, and then ultrasound is used to burst the microbubbles, causing site-specific delivery of the bioactive materials. Furthermore, the ability of albumin-coated microbubbles to adhere to vascular regions with glycocalix damage or endothelial dysfunction is another possible mechanism to deliver drugs even in the absence of ultrasound. This review focuses on the characteristics of microbubbles that give them therapeutic properties and some important aspects of ultrasound parameters that are known to influence microbubble-mediated drug delivery. In addition, current studies involving this novel therapeutical application of microbubbles will be discussed

A network-based target overlap score for characterizing drug combinations: High correlation with cancer clinical trial results

Drug combinations are highly efficient in systemic treatment of complex multigene diseases such as cancer, diabetes, arthritis and hypertension. Most currently used combinations were found in empirical ways, which limits the speed of discovery for new and more effective combinations. Therefore, there is a substantial need for efficient and fast computational methods. Here, we present a principle that is based on the assumption that perturbations generated by multiple pharmaceutical agents propagate through an interaction network and can cause unexpected amplification at targets not immediately affected by the original drugs. In order to capture this phenomenon, we introduce a novel Target Overlap Score (TOS) that is defined for two pharmaceutical agents as the number of jointly perturbed targets divided by the number of all targets potentially affected by the two agents. We show that this measure is correlated with the known effects of beneficial and deleterious drug combinations taken from the DCDB, TTD and Drugs.com databases. We demonstrate the utility of TOS by correlating the score to the outcome of recent clinical trials evaluating trastuzumab, an effective anticancer agent utilized in combination with anthracycline- and taxane-based systemic chemotherapy in HER2-receptor (erb-b2 receptor tyrosine kinase 2) positive breast cancer. © 2015 Ligeti et al