DENDRIMER: A NOVEL DRUG DELIVERY SYSTEM

Dendrimer as a drug delivery system is based on the approach of sending a nano particle   (10-9) to the body, loaded with drug. The drug might be loaded on its terminal surface or encapsulated within the branches of a dendrimer. It’s very small size and unique properties like polyvalency, monodispersity, stability make it an appropriate carrier for delivering drugs with precision and selectivity. Dendrimers help in achieving increased bioavailability, sustained, controlled as well as targeted release of drug. There is reduction in the amount of drug and systemic toxicity while the therapeutic efficacy increases. It is advancing as a method used for delivery of various drugs like anticancer drugs(methotrexate), drug for prevention of HIV, enhancing bioavailability of pilocarpine for ocular drug delivery, et al. This approach as a drug delivery system certainly promises a reliable, safe, selective and precise method of drug deliver

Neuroprotective Effects of Marine Algae

The marine environment is known as a rich source of chemical structures with numerous beneficial health effects. Among marine organisms, marine algae have been identified as an under-exploited plant resource, although they have long been recognized as valuable sources of structurally diverse bioactive compounds. Presently, several lines of studies have provided insight into biological activities and neuroprotective effects of marine algae including antioxidant, anti-neuroinflammatory, cholinesterase inhibitory activity and the inhibition of neuronal death. Hence, marine algae have great potential to be used for neuroprotection as part of pharmaceuticals, nutraceuticals and functional foods. This contribution presents an overview of marine algal neuroprotective effects and their potential application in neuroprotection

Water T2 as an early, global and practical biomarker for metabolic syndrome: an observational cross-sectional study

Background: Metabolic syndrome (MetS) is a highly prevalent condition that identifies individuals at risk for type 2 diabetes mellitus and atherosclerotic cardiovascular disease. Prevention of these diseases relies on early detection and intervention in order to preserve pancreatic β-cells and arterial wall integrity. Yet, the clinical criteria for MetS are insensitive to the early-stage insulin resistance, inflammation, cholesterol and clotting factor abnormalities that char- acterize the progression toward type 2 diabetes and atherosclerosis. Here we report the discovery and initial charac- terization of an atypical new biomarker that detects these early conditions with just one measurement. Methods: Water T2, measured in a few minutes using benchtop nuclear magnetic resonance relaxometry, is exqui- sitely sensitive to metabolic shifts in the blood proteome. In an observational cross-sectional study of 72 non-diabetic human subjects, the association of plasma and serum water T2 values with over 130 blood biomarkers was analyzed using bivariate, multivariate and logistic regression. Results: Plasma and serum water T2 exhibited strong bivariate correlations with markers of insulin, lipids, inflamma- tion, coagulation and electrolyte balance. After correcting for confounders, low water T2 values were independently and additively associated with fasting hyperinsulinemia, dyslipidemia and subclinical inflammation. Plasma water T2 exhibited 100% sensitivity and 87% specificity for detecting early insulin resistance in normoglycemic subjects, as defined by the McAuley Index. Sixteen normoglycemic subjects with early metabolic abnormalities (22% of the study population) were identified by low water T2 values. Thirteen of the 16 did not meet the harmonized clinical criteria for metabolic syndrome and would have been missed by conventional screening for diabetes risk. Low water T2 values were associated with increases in the mean concentrations of 6 of the 16 most abundant acute phase proteins and lipoproteins in plasma. Conclusions: Water T2 detects a constellation of early abnormalities associated with metabolic syndrome, provid- ing a global view of an individual’s metabolic health. It circumvents the pitfalls associated with fasting glucose and hemoglobin A1c and the limitations of the current clinical criteria for metabolic syndrome. Water T2 shows promise as an early, global and practical screening tool for the identification of individuals at risk for diabetes and atherosclerosis

Ultrahigh-Energy Neutrino Interactions

Cross sections for the interactions of ultrahigh-energy neutrinos with nucleons are evaluated in light of new information about nucleon structure functions. For $10^{20}$--eV neutrinos, the cross section is about 2.4 times previous estimates. We also review the cross sections for neutrino interactions with atomic electrons. Some consequences for interaction rates in the Earth and for event rates from generic astrophysical sources in large-scale detectors are noted.Comment: 51 pages, LaTeX, uses elsart.sty and BoxedEPS for 23 uufiled PostScript figures. Compressed PostScript version is available at http://chrisq.fnal.gov/Papers/GQRS.ps.

Genome-wide meta-analysis for Alzheimer's disease cerebrospinal fluid biomarkers

Amyloid-beta 42 (A beta 42) and phosphorylated tau (pTau) levels in cerebrospinal fluid (CSF) reflect core features of the pathogenesis of Alzheimer's disease (AD) more directly than clinical diagnosis. Initiated by the European Alzheimer & Dementia Biobank (EADB), the largest collaborative effort on genetics underlying CSF biomarkers was established, including 31 cohorts with a total of 13,116 individuals (discovery n = 8074; replication n = 5042 individuals). Besides the APOE locus, novel associations with two other well-established AD risk loci were observed; CR1 was shown a locus for A beta 42 and BIN1 for pTau. GMNC and C16orf95 were further identified as loci for pTau, of which the latter is novel. Clustering methods exploring the influence of all known AD risk loci on the CSF protein levels, revealed 4 biological categories suggesting multiple A beta 42 and pTau related biological pathways involved in the etiology of AD. In functional follow-up analyses, GMNC and C16orf95 both associated with lateral ventricular volume, implying an overlap in genetic etiology for tau levels and brain ventricular volume.Peer reviewe

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.</p

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation

Aptamer-based search for correlates of plasma and serum water T2: implications for early metabolic dysregulation and metabolic syndrome

Abstract Background Metabolic syndrome is a cluster of abnormalities that increases the risk for type 2 diabetes and atherosclerosis. Plasma and serum water T2 from benchtop nuclear magnetic resonance relaxometry are early, global and practical biomarkers for metabolic syndrome and its underlying abnormalities. In a prior study, water T2 was analyzed against ~ 130 strategically selected proteins and metabolites to identify associations with insulin resistance, inflammation and dyslipidemia. In the current study, the analysis was broadened ten-fold using a modified aptamer (SOMAmer) library, enabling an unbiased search for new proteins correlated with water T2 and thus, metabolic health. Methods Water T2 measurements were recorded using fasting plasma and serum from non-diabetic human subjects. In parallel, plasma samples were analyzed using a SOMAscan assay that employed modified DNA aptamers to determine the relative concentrations of 1310 proteins. A multi-step statistical analysis was performed to identify the biomarkers most predictive of water T2. The steps included Spearman rank correlation, followed by principal components analysis with variable clustering, random forests for biomarker selection, and regression trees for biomarker ranking. Results The multi-step analysis unveiled five new proteins most predictive of water T2: hepatocyte growth factor, receptor tyrosine kinase FLT3, bone sialoprotein 2, glucokinase regulatory protein and endothelial cell-specific molecule 1. Three of the five strongest predictors of water T2 have been previously implicated in cardiometabolic diseases. Hepatocyte growth factor has been associated with incident type 2 diabetes, and endothelial cell specific molecule 1, with atherosclerosis in subjects with diabetes. Glucokinase regulatory protein plays a critical role in hepatic glucose uptake and metabolism and is a drug target for type 2 diabetes. By contrast, receptor tyrosine kinase FLT3 and bone sialoprotein 2 have not been previously associated with metabolic conditions. In addition to the five most predictive biomarkers, the analysis unveiled other strong correlates of water T2 that would not have been identified in a hypothesis-driven biomarker search. Conclusions The identification of new proteins associated with water T2 demonstrates the value of this approach to biomarker discovery. It provides new insights into the metabolic significance of water T2 and the pathophysiology of metabolic syndrome

Water T2 as an early, global and practical biomarker for metabolic syndrome: an observational cross-sectional study

Background: Metabolic syndrome (MetS) is a highly prevalent condition that identifies individuals at risk for type2 diabetes mellitus and atherosclerotic cardiovascular disease. Prevention of these diseases relies on early detection and intervention in order to preserve pancreatic β-cells and arterial wall integrity. Yet, the clinical criteria for MetS are insensitive to the early-stage insulin resistance, inflammation, cholesterol and clotting factor abnormalities that char- acterize the progression toward type 2 diabetes and atherosclerosis. Here we report the discovery and initial charac- terization of an atypical new biomarker that detects these early conditions with just one measurement.Methods: Water T2, measured in a few minutes using benchtop nuclear magnetic resonance relaxometry, is exqui- sitely sensitive to metabolic shifts in the blood proteome. In an observational cross-sectional study of 72 non-diabetic human subjects, the association of plasma and serum water T2 values with over 130 blood biomarkers was analyzed using bivariate, multivariate and logistic regression.Results: Plasma and serum water T2 exhibited strong bivariate correlations with markers of insulin, lipids, inflamma- tion, coagulation and electrolyte balance. After correcting for confounders, low water T2 values were independently and additively associated with fasting hyperinsulinemia, dyslipidemia and subclinical inflammation. Plasma water T2 exhibited 100% sensitivity and 87% specificity for detecting early insulin resistance in normoglycemic subjects, as defined by the McAuley Index. Sixteen normoglycemic subjects with early metabolic abnormalities (22% of the study population) were identified by low water T2 values. Thirteen of the 16 did not meet the harmonized clinical criteria for metabolic syndrome and would have been missed by conventional screening for diabetes risk. Low water T2 values were associated with increases in the mean concentrations of 6 of the 16 most abundant acute phase proteins and lipoproteins in plasma.Conclusions: Water T2 detects a constellation of early abnormalities associated with metabolic syndrome, provid- ing a global view of an individual"s metabolic health. It circumvents the pitfalls associated with fasting glucose and hemoglobin A1c and the limitations of the current clinical criteria for metabolic syndrome. Water T2 shows promise as an early, global and practical screening tool for the identification of individuals at risk for diabetes and atherosclerosis