Application of laser capture microdissection combined with two-dimensional electrophoresis for the discovery of differentially regulated proteins in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal of all the common malignancies and markers for early detection or targets for treatment of this disease are urgently required. The disease is characterised by a strong stromal response, with cancer cells usually representing a relatively small proportion of the cells in the tumor mass. We therefore performed laser capture microdissection (LCM) to enrich for both normal and malignant pancreatic ductal epithelial cells. Proteins extracted from these cells were then separated by two-dimensional gel electrophoresis (2-DE). The limited amounts of protein in the LCM procured samples necessitated the detection of 2-DE resolved proteins by silver staining. Consequently, loading equivalent amounts of protein onto gels was essential. However, we found that conventional means of measuring total protein in the samples were not sufficiently accurate. We therefore adopted a strategy in which the samples were first separated by one-dimensional sodium dodecyl sulphate-polyacrylamide gel electrophoresis, stained with silver stain and subjected to densitometry. Evaluation of the staining intensity was then used to normalise the samples. We found that the protein profiles from undissected normal pancreas and LCM-acquired non-malignant ductal epithelial cells from the same tissue block were different, underpinning the value of LCM in our analysis. The comparisons of protein profiles from nonmalignant and malignant ductal epithelial cells revealed nine protein spots that were consistently differentially regulated. Five of these proteins showed increased expression in tumor cells while four showed diminished expression in these cells. One of the proteins displaying enhanced expression in tumor cells was identified as the calcium-binding protein, S100A6. To determine the incidence of S100A6 overexpression in pancreatic cancer, we carried out immunohistochemical analysis on sections from a pancreas cancer tissue array containing 174 duplicate normal and malignant pancreatic tissue samples, from 46 pancreas cancer patients. Normal pancreatic ductal epithelia were either devoid of detectable S100A6 or showed weak expression only. Moderately or poorly differentiated tumors, by contrast, showed a higher incidence and a higher level of S100A6 expression. These observations indicate that the combination of LCM with 2-DE provides an effective strategy to discover proteins that are differentially expressed in PDAC.     

Optimisation of Wavelength Modulated Raman Spectroscopy: Towards High Throughput Cell Screening

In the field of biomedicine, Raman spectroscopy is a powerful technique to discriminate between normal and cancerous cells. However the strong background signal from the sample and the instrumentation affects the efficiency of this discrimination technique. Wavelength Modulated Raman spectroscopy (WMRS) may suppress the background from the Raman spectra. In this study we demonstrate a systematic approach for optimizing the various parameters of WMRS to achieve a reduction in the acquisition time for potential applications such as higher throughput cell screening. The Signal to Noise Ratio (SNR) of the Raman bands depends on the modulation amplitude, time constant and total acquisition time. It was observed that the sampling rate does not influence the signal to noise ratio of the Raman bands if three or more wavelengths are sampled. With these optimised WMRS parameters, we increased the throughput in the binary classification of normal human urothelial cells and bladder cancer cells by reducing the total acquisition time to 6 s which is significantly lower in comparison to previous acquisition times required for the discrimination between similar cell types.     

Rating of perceived exertion as a tool for prescribing and self regulating interval training: a pilot study

The aim of the present study was to analyse the usefulness of the 6-20 rating of perceived exertion (RPE) scale for prescribing and self-regulating high-intensity interval training (HIT) in young individuals. Eight healthy young subjects (age = 27.5±6.7 years) performed maximal graded exercise testing to determine their maximal and reserve heart rate (HR). Subjects then performed two HIT sessions (20 min on a treadmill) prescribed and regulated by their HR (HR: 1 min at 50% alternated with 1 min at 85% of reserve HR) or RPE (RPE: 1 minute at the 9-11 level [very light-fairly light] alternated with 1 minute at the 15-17 level [hard-very hard]) in random order. HR response and walking/running speed during the 20 min of exercise were compared between sessions. No significant difference between sessions was observed in HR during low- (HR: 135±15 bpm; RPE: 138±20 bpm) and high-intensity intervals (HR: 168±15 bpm; RPE: 170±18 bpm). Walking/running speed during low- (HR: 5.7±1.2 km · h⁻¹; RPE: 5.7±1.3 km · h⁻¹) and high-intensity intervals (HR: 7.8±1.9 km · h⁻¹; RPE: 8.2±1.7 km · h⁻¹) was also not different between sessions. No significant differences were observed in HR response and walking/running speed between HIT sessions prescribed and regulated by HR or RPE. This finding suggests that the 6-20 RPE scale may be a useful tool for prescribing and self-regulating HIT in young subjects.     

Between-session reliability of four hop tests and the agility T-test

The purposes of this study were firstly to investigate whether learning affects were present in the administration of 4 hop tests and the Agility T-test and secondly to assess the between-session reliability of these tests. Twenty-two recreational athletes (11 women: age 22.3 ± 3.7 years, height 167.7 ± 6.2 cm, weight 59.2 ± 6.9 kg and 11 men: age 22.8 ± 3.1 years, height 179.8 ± 4 cm, weight 79.6 ± 10 kg) took part in the study. The subjects performed 6 repetitions of each hop test and 4 repetitions of the Agility T-test once a week over a period of 3 weeks. Distances were normalized to leg length and presented as a percentage value for the single, triple and crossover hop. Results showed that there were significant differences in scores between genders and that learning affects were present in all tests. Intraclass correlation coefficients ranged from 0.76 to 0.92 for the hop tests and 0.82 to 0.96 for the Agility T-test. The results indicated that the hop and Agility T-tests are reliable tests for use with subjects in a clinical or team sport environment. The error measurement statistics presented could be of help to practitioners to determine whether changes in individuals' scores in the hop and Agility T-tests are because of a true change in performance or measurement error. Of most importance was the fact that all subjects achieved at least 90% limb symmetry index on all 4 hop tests. Therefore, we recommend that a minimum limb symmetry value of 90%, rather than previously recommended 85%, should be adopted during rehabilitation and conditioning.     

An overview of population genetic data simulation

Simulation studies in population genetics play an important role in helping to better understand the impact of various evolutionary and demographic scenarios on sequence variation and sequence patterns, and they also permit investigators to better assess and design analytical methods in the study of disease-associated genetic factors. To facilitate these studies, it is imperative to develop simulators with the capability to accurately generate complex genomic data under various genetic models. Currently, a number of efficient simulation software packages for large-scale genomic data are available, and new simulation programs with more sophisticated capabilities and features continue to emerge. In this article, we review the three basic simulation frameworks--coalescent, forward, and resampling--and some of the existing simulators that fall under these frameworks, comparing them with respect to their evolutionary and demographic scenarios, their computational complexity, and their specific applications. Additionally, we address some limitations in current simulation algorithms and discuss future challenges in the development of more powerful simulation tools.