Real-time semi-quantitative PCR (qPCR) is extensively used to assess variations in gene expressions resulting from pathological conditions or biological responses. Normalization of qPCR data is required to control innate variations that occur during experimental procedures. Endogenous control genes (ECs), used for normalization of the data should be expressed constitutively and consistently across treatments groups. The aim of the present study was to identify the most suitable endogenous control genes for qPCR based analyses to study responses in breast cancer cell lines following exposure to Progesterone (P4). The expression and validity of five candidate ECs (PUM1, RPS13, RPL13A, TBCA and PSMB) were determined in three breast cancer cell lines following exposure to Progesterone. Gene expression data was analyzed using three methods, Normfinder, Bestkeeper, and Comparative delta Ct method. A significant difference in variance of expression levels of individual ECs under different growth conditions was observed. Expression of PUM1 and PSMB was minimally affected in breast cancer cell lines under the experimental conditions. Indeed, in the progesterone treated cells,PUM1 and PSMB were identified as the most stable EC genes by all three methods while TBCAand RPS13 were least stable. In breast cancer cell lines, our results highlight PSMB as another stably expressed endogenous control gene besides the previously identified PUM1. PSMB gene expression may thus provide an additional parameter for studies in breast cancers.

Periodic Influenza epidemics are a cause of concern world-wide due to heavy burden of disease consequently leading to economic distress mortality. In modern era, rapid international travel between populations makes the impact of air-borne diseases like Influenza more dramatic, as observed in the last pandemic due to Swine origin Influenza A/H1N1 2009. Though transmission of Influenza in humans has been studied in various settings, studies on ship outbreaks are sparse. The current research aims to analyze the historical Influenza outbreaks on sailing ships. Study revealed the pattern of transmission in isolated population and estimates the epidemiological parameters viz. basic reproduction number (R⁰), epidemic growth rate (r), transmission rate (β). High clustering lead to intense transmission with 0 high value of basic reproductive number, R⁰. Also, the study brought to light the limitations of analyzing 0 historical data.

A novel, rapid, and precise stability-indicating gradient reverse-phase high performance liquid chromatographic method for the quantitative determination of primaquine diphosphate and its impurities was developed and validated. Efficient chromatographic separation was achieved on an Inertsil ODS-3V column (150 mm × 4.6 mm, 5.0 μm) with mobile phase containing phosphate buffer (0.05 M KH²PO⁴, pH 4.5) in gradient combination with acetonitrile at a flow rate of 1 mL/min and the analyte was monitored using a photo-diode array detector at a wavelength of 254 nm. The forced-degradation of primaquine diphosphate was carried out by exposing it to acidic, basic, neutral, thermal, photolytic, and oxidative stress conditions. The peaks of the degradation products obtained were well resolved from that of primaquine diphosphate, indicating that the method developed was specific and stability-indicating. Further, the method was validated according to the International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use guidelines, with respect to parameters such as specificity, precision, linearity, accuracy and robustness. The developed method could also be used for the quantification of primaquine diphosphate encapsulated in niosome formulation.