53 research outputs found
Dihydrotestosterone Ameliorates Degeneration in Muscle, Axons and Motoneurons and Improves Motor Function in Amyotrophic Lateral Sclerosis Model Mice
Amyotrophic lateral sclerosis (ALS) is a lethal disease characterized by a progressive loss of motoneurons. The clinical symptoms include skeletal muscle weakness and atrophy, which impairs motor performance and eventually leads to respiratory failure. We tested whether dihydrotestosterone (DHT), which has both anabolic effects on muscle and neuroprotective effects on axons and motoneurons, can ameliorate clinical symptoms in ALS. A silastic tube containing DHT crystals was implanted subcutaneously in SOD1-G93A mice at early symptomatic age when decreases in body weight and grip-strength were observed as compared to wild-type mice. DHT-treated SOD1-G93A mice demonstrated ameliorated muscle atrophy and increased body weight, which was associated with stronger grip-strength. DHT treatment increased the expression of insulin-like growth factor-1 in muscle, which can exert myotrophic as well as neurotrophic effects through retrograde transport. DHT treatment attenuated neuromuscular junction denervation, and axonal and motoneuron loss. DHT-treated SOD1-G93A mice demonstrated improvement in motor behavior as assessed by rota-rod and gait analyses, and an increased lifespan. Application of DHT is a relatively simple and non-invasive procedure, which may be translated into therapy to improve the quality of life for ALS patients
Community acceptability of use of rapid diagnostic tests for malaria by community health workers in Uganda
<p>Abstract</p> <p>Background</p> <p>Many malarious countries plan to introduce artemisinin combination therapy (ACT) at community level using community health workers (CHWs) for treatment of uncomplicated malaria. Use of ACT with reliance on presumptive diagnosis may lead to excessive use, increased costs and rise of drug resistance. Use of rapid diagnostic tests (RDTs) could address these challenges but only if the communities will accept their use by CHWs. This study assessed community acceptability of the use of RDTs by Ugandan CHWs, locally referred to as community medicine distributors (CMDs).</p> <p>Methods</p> <p>The study was conducted in Iganga district using 10 focus group discussions (FGDs) with CMDs and caregivers of children under five years, and 10 key informant interviews (KIIs) with health workers and community leaders. Pre-designed FGD and KII guides were used to collect data. Manifest content analysis was used to explore issues of trust and confidence in CMDs, stigma associated with drawing blood from children, community willingness for CMDs to use RDTs, and challenges anticipated to be faced by the CMDs.</p> <p>Results</p> <p>CMDs are trusted by their communities because of their commitment to voluntary service, access, and the perceived effectiveness of anti-malarial drugs they provide. Some community members expressed fear that the blood collected could be used for HIV testing, the procedure could infect children with HIV, and the blood samples could be used for witchcraft. Education level of CMDs is important in their acceptability by the community, who welcome the use of RDTs given that the CMDs are trained and supported. Anticipated challenges for CMDs included transport for patient follow-up and picking supplies, adults demanding to be tested, and caregivers insisting their children be treated instead of being referred.</p> <p>Conclusion</p> <p>Use of RDTs by CMDs is likely to be acceptable by community members given that CMDs are properly trained, and receive regular technical supervision and logistical support. A well-designed behaviour change communication strategy is needed to address the anticipated programmatic challenges as well as community fears and stigma about drawing blood. Level of formal education may have to be a criterion for CMD selection into programmes deploying RDTs.</p
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
Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential
Modulation of paraoxonases during infectious diseases and its potential impact on atherosclerosis
Hypogonadism in the HIV-Infected Man
Low testosterone levels are frequently observed among men with treated and untreated HIV infection. However, the interpretations of biochemical measurements of testicular function are challenging and need to be considered in the context of the clinical presentation and scenario. The distinction between primary and secondary hypogonadism and determination of the underlying clinical pathophysiology are not always straightforward. Early recognition of clinical hypogonadism and appropriate treatment may improve clinical outcomes and quality of life for affected individuals. A principal aim of testosterone replacement is to maintain serum testosterone concentrations in the normal physiological range and should be considered in clinically symptomatic patients
A comprehensive analysis of the thermodynamic events involved in ligandâreceptor binding using CoRIA and its variants
Quantitative Structure-Activity Relationships(QSAR) are being used since decades for prediction of biological activity, lead optimization, classification, identification and explanation of the mechanisms of drug action, and prediction of novel structural leads in drug discovery. Though the technique has lived up to its expectations in many aspects, much work still needs to be done in relation to problems related to the rational design of peptides. Peptides are the drugs of choice in many situations, however, designing them rationally is a complicated task and the complexity increases with the length of their sequence. In order to deal with the problem of peptide optimization, one of our recently developed QSAR formalisms CoRIA (Comparative Residue Interaction Analysis) is being expanded and modified as: reverse-CoRIA (rCoRIA) and mixed- CoRIA (mCoRIA) approaches. In these methodologies, the peptide is fragmented into individual units and the interaction energies (van der Waals, Coulombic and hydrophobic) of each amino acid in the peptide with the receptor as a whole(rCoRIA) and with individual active site residues in the receptor (mCoRIA) are calculated, which along with other thermodynamic descriptors, are used as independent variables that are correlated to the biological activity by chemometric methods. As a test case, the three CoRIA methodologies have been validated on a dataset of diverse nonamer peptides that bind to the Class I major histocompatibility complex molecule HLA-A*0201, and for which some structure activity relationships have already been reported. The different models developed, and validated both internally as well as externally, were found to be robust with statistically significant values of r2 (correlation coefficient)and r2 pred (predictive r2). These models were able to identify all the structure activity relationships known for this class of peptides, as well uncover some new relationships. This means that these methodologies will perform well for other peptide datasets too. The major advantage of these approaches is that they explicitly utilize the 3D structures of small molecules or peptides as well as their macromolecular targets, to extract position-specific information about important interactions between the ligand and receptor, which can assist the medicinal and computational chemists in designing new molecules, and biologists in studying the influence of mutations in the target receptor on ligand binding
Combined extracts of Garcinia mangostana fruit rind and Cinnamomum tamala leaf supplementation enhances muscle strength and endurance in resistance trained males
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