Prediction of Biological Activity Spectra for Few Anticancer Drugs Derived from Plant Sources

Over the past decade plants have become an interesting source of new classes of pharmacologically active natural products. Some secondary metabolites are also well known for their effectiveness on living species. The PASS (Prediction of Activity Spectra for Substances) computer program, which is able to simultaneously predict more than one thousand biological and toxicological activities from only the structural formulas of the chemicals, was used to predict the biological activity profile of 7 secondary metabolites. PASS predictions were successfully compared to the available information on the pharmacological and toxicological activity of these compounds

Effect of PSI-697, a novel P-selectin inhibitor, on platelet-monocyte aggregate formation in humans

Background: Platelet activation is central to the pathogenesis of acute coronary syndromes. Surface expression of P‐selectin on activated platelets induces formation of platelet–monocyte aggregates and promotes vascular inflammation and thrombosis. P‐selectin antagonism may represent a novel therapeutic strategy in vascular disease. We aimed to investigate the effects of the novel P‐selectin antagonist PSI‐697 on platelet–monocyte aggregate formation in humans. Methods and Results: In a double‐blind, randomized, placebo‐controlled crossover study, healthy smokers were randomized to receive either oral PSI‐697 600 mg or matched placebo. The sequence of treatment was also randomized, with all subjects receiving both PSI‐697 and placebo. Platelet–monocyte aggregates were measured by flow cytometry at 4 and 24 hours in the presence and absence of thrombin receptor‐activating peptide (TRAP; 0.1 to 1.0 μm/L). The ex vivo addition of TRAP caused a concentration‐dependent increase in platelet–monocyte aggregates from 8.2% to 94.8% (P<0.001). At 4 and 24 hours, plasma concentrations of PSI‐697 increased to 1906 and 83 ng/mL, respectively (P<0.001). PSI‐697 had no demonstrable effect on either stimulated or unstimulated platelet–monocyte aggregates at 4 or 24 hours (P>0.05). P‐selectin‐blocking antibody (CLB‐Thromb6), but not PSI‐697, inhibited both stimulated and unstimulated platelet–monocyte aggregate formation in vitro (P<0.001). Conclusions: The novel small‐molecule P‐selectin antagonist PSI‐697 did not inhibit basal or stimulated platelet–monocyte aggregate formation in humans at the dose tested. Its clinical efficacy remains to be established

Solidification Processing of Magnesium Based In-Situ Metal Matrix Composites by Precursor Approach

In-situ magnesium based metal matrix composites (MMCs) belong to the category of advanced light weight metallic composites by which ceramic dispersoids are produced by a chemical reaction within the metal matrix itself. In-situ MMCs comprised uniform distribution of thermodynamically stable ceramic dispersoids, clean and unoxidized ceramic-metal interfaces having high interfacial strength. In last two decades, investigators have been collaborating to explore the possibility of enhancing the high temperature creep resistance performance in polymer-derived metal matrix composites (P-MMCs) by utilizing polymer precursor approach. A unique feature of the P-MMC process is that since all constituents of the ceramic phase are built into the polymer molecules itself, there is no need for a separate chemical reaction between the host metal and polymer precursor in order to form in-situ ceramic particles within the molten metal. Among the different polymer precursors commercially available in the market, the silicon-based polymers convert into the ceramic phase in the temperature range of 800–1000°C. Therefore, these Si-based polymers can be infused into molten Mg or Mg-alloys easily by simple stir-casting method. This chapter mainly focuses on understanding the structure–property correlation in both the Mg-based and Mg-alloy based in-situ P-MMCs fabricated by solidification processing via polymer precursor approach

Cardiogoniometry compared to fractional flow reserve at identifying physiologically significant coronary stenosis: The Cardioflow Study

Cardiogoniometry (CGM) is method of 3-dimensional electrocardiographic assessment which has been shown to identify patients with angiographically defined, stable coronary artery disease (CAD). However, angiographic evidence of CAD, does not always correlate to physiologically significant disease. The aim of our study was to assess the ability of CGM to detect physiologically significant coronary stenosis defined by fractional flow reserve (FFR). In a tertiary cardiology centre, elective patients with single vessel CAD were enrolled into a prospective double blinded observational study. A baseline CGM recording was performed at rest. A second CGM recording was performed during the FFR procedure, at the time of adenosine induced maximal hyperaemia. A significant CGM result was defined as an automatically calculated ischaemia score < 0 and a significant FFR ratio was defined as < 0.80. Measures of diagnostic performance (including sensitivity and specificity) were calculated for CGM at rest and during maximal hyperaemia. Forty-five patients were included (aged 61.1 ± 11.0; 60.0% male), of which eighteen (40%) were found to have significant CAD when assessed by FFR. At rest, CGM yielded a sensitivity of 33.3% and specificity of 63.0%. At maximal hyperaemia the sensitivity and specificity of CGM was 71.4 and 50.0% respectively. The diagnostic performance of CGM to detect physiologically significant stable CAD is poor at rest. Although, the diagnostic performance of CGM improves substantially during maximal hyperaemia, it does not reach sufficient levels of accuracy to be used routinely in clinical practice

Routine Cerebral Embolic Protection during Transcatheter Aortic-Valve Implantation.

BACKGROUND: Transcatheter aortic-valve implantation (TAVI) is associated with procedure-related stroke. Cerebral embolic protection (CEP) devices may reduce embolization to the cerebral circulation and hence the incidence of stroke. METHODS: We conducted a randomized, controlled trial across 33 centers in the United Kingdom. We randomly assigned 7635 participants with aortic stenosis in a 1:1 ratio to undergo TAVI with a CEP device (CEP group) or TAVI without a CEP device (control group). The primary outcome was stroke within 72 hours after TAVI or before discharge from the hospital (if discharge occurred sooner). RESULTS: A total of 3815 participants were assigned to the CEP group and 3820 to the control group. A primary-outcome event occurred in 81 of 3795 participants (2.1%) in the CEP group and in 82 of 3799 participants (2.2%) in the control group (difference, -0.02 percentage points; 95% confidence interval, -0.68 to 0.63; P = 0.94). Disabling stroke occurred in 47 participants (1.2%) in the CEP group and in 53 (1.4%) in the control group. Death occurred in 29 participants (0.8%) in the CEP group and in 26 (0.7%) in the control group. Overall access-site complications appeared to be similar in the two groups (8.1% in the CEP group and 7.7% in the control group). A total of 24 serious adverse events occurred in 22 of 3798 participants (0.6%) in the CEP group, and 13 serious adverse events occurred in 13 of 3803 participants (0.3%) in the control group. CONCLUSIONS: Among participants undergoing TAVI, routine use of CEP did not decrease the incidence of stroke within 72 hours. (Funded by the British Heart Foundation and Boston Scientific; BHF PROTECT-TAVI ISRCTN Registry number, ISRCTN16665769.)

Envisioning the Paradigm of Service Oriented Hydrology Intelligence (SOHI)

Hydrology is an increasingly data-intensive discipline and the key contribution of existing and emerging information technologies for the hydrology ecosystem is to smartly transform the water-specific data to information and to knowledge that can be easily picked up and used by various stakeholders and automated decision engines in order to forecast and forewarn the things to unfold. Attaining actionable and realistic insights in real-time dynamically out of both flowing as well as persisting data mountain is the primary goal for the aquatic industry. There are several promising technologies, processes, and products for facilitating this grand yet challenging objective. Business intelligence (BI) is the mainstream IT discipline representing a staggering variety of data transformation and synchronization, information extraction and knowledge engineering techniques. Another paradigm shift is the overwhelming adoption of service oriented architecture (SOA), which is a simplifying mechanism for effectively designing complex and mission-critical enterprise systems. Incidentally there is a cool convergence between the BI and SOA concepts. This is the stimulating foundation for the influential emergence of service oriented business intelligence (SOBI) paradigm, which is aptly recognized as the next-generation BI method. These improvisations deriving out of technological convergence and cluster calmly pervade to the ever-shining water industry too. That is, the bubbling synergy between service orientation and aquatic intelligence empowers the aquatic ecosystem significantly in extracting actionable insights from distributed and diverse data sources in real time through a host of robust and resilient infrastructures and practices. The realisable inputs and information being drawn from water-related data heap contribute enormously in achieving more with less and to guarantee enhanced safety and security for total human society. Especially as the green movement is taking shape across the globe, there is a definite push from different quarters on water and ecology professionals to contribute their mite immensely and immediately in permanently arresting the ecological degradation. In this chapter, we have set the context by incorporating some case studies that detail how SOA has been a tangible enabler of hydroinformatics. Further down, we have proceeded by explaining how SOA-sponsored integration concepts contribute towards integrating different data for creating unified and synchronized views and to put the solid and stimulating base for quickly deriving incisive and decisive insights in the form of hidden patterns, predictions, trends, associations, tips, etc. from the integrated and composite data. This enables real-time planning of appropriate countermeasures, tactics as well as strategies to put the derived in faster activation and actuation modes. Finally the idea is to close this chapter with an overview of how SOA celebrates in establishing adaptive, on-demand and versatile SOHI platforms. SOA is insisted as the chief technique for developing and deploying agile, adaptive, and on-demand hydrology intelligence platforms as a collection of interoperable, reusable, composable, and granular hydrology and technical services. The final section illustrates the reference architecture for the proposed SOHI platform.</jats:p

Envisioning the Paradigm of Service Oriented Hydrology Intelligence (SOHI)

Hydrology is an increasingly data-intensive discipline and the key contribution of existing and emerging information technologies for the hydrology ecosystem is to smartly transform the water-specific data to information and to knowledge that can be easily picked up and used by various stakeholders and automated decision engines in order to forecast and forewarn the things to unfold. Attaining actionable and realistic insights in real-time dynamically out of both flowing as well as persisting data mountain is the primary goal for the aquatic industry. There are several promising technologies, processes, and products for facilitating this grand yet challenging objective. Business intelligence (BI) is the mainstream IT discipline representing a staggering variety of data transformation and synchronization, information extraction and knowledge engineering techniques. Another paradigm shift is the overwhelming adoption of service oriented architecture (SOA), which is a simplifying mechanism for effectively designing complex and mission-critical enterprise systems. Incidentally there is a cool convergence between the BI and SOA concepts. This is the stimulating foundation for the influential emergence of service oriented business intelligence (SOBI) paradigm, which is aptly recognized as the next-generation BI method. These improvisations deriving out of technological convergence and cluster calmly pervade to the ever-shining water industry too. That is, the bubbling synergy between service orientation and aquatic intelligence empowers the aquatic ecosystem significantly in extracting actionable insights from distributed and diverse data sources in real time through a host of robust and resilient infrastructures and practices. The realisable inputs and information being drawn from water-related data heap contribute enormously in achieving more with less and to guarantee enhanced safety and security for total human society. Especially as the green movement is taking shape across the globe, there is a definite push from different quarters on water and ecology professionals to contribute their mite immensely and immediately in permanently arresting the ecological degradation. In this chapter, we have set the context by incorporating some case studies that detail how SOA has been a tangible enabler of hydroinformatics. Further down, we have proceeded by explaining how SOA-sponsored integration concepts contribute towards integrating different data for creating unified and synchronized views and to put the solid and stimulating base for quickly deriving incisive and decisive insights in the form of hidden patterns, predictions, trends, associations, tips, etc. from the integrated and composite data. This enables real-time planning of appropriate countermeasures, tactics as well as strategies to put the derived in faster activation and actuation modes. Finally the idea is to close this chapter with an overview of how SOA celebrates in establishing adaptive, on-demand and versatile SOHI platforms. SOA is insisted as the chief technique for developing and deploying agile, adaptive, and on-demand hydrology intelligence platforms as a collection of interoperable, reusable, composable, and granular hydrology and technical services. The final section illustrates the reference architecture for the proposed SOHI platform.</jats:p