Spectral changes in electrical activity of pylorus due to L-NAME induced hypertrophic pyloric stenosis

OBJECTIVES

To investigate the relation between hypertrophic pyloric stenosis (HPS) and the changes in the myoelectrical activity of the pyloric and gastric areas.

METHODS

Three pregnant females, at 14 days of gestation two of which were named as D14n (NOS inhibitor group) and one was named as D14c (control). From the beginning of the study until the end of gestation, rats in D14n group received nitric oxide synthase inhibitor L-NAME for administrating their pups, and the rat in D14c group was drinking water for 21 days. The pups of each group underwent laparotomy at 42 days of their life and myoelectrical signals of their pyloric and gastric regions were recorded via bipolar electrodes and then evaluated through signal processing.

RESULTS

Signal analysis showed that HPS induced pyloric segment reveals a suppressed spectral component that was detected in normal pyloric segment. The HPS induced pyloric segment also revealed higher power/ min and +/- SD compared to that of normal and gastric areas. In the pyloric segment, while the number of interstitial cells of Cajal (ICC) was lesser, the number of smooth muscle cells was higher than in the pyloric segment of controls.

CONCLUSIONS

The spectral differentials depend on the type, population and condition of locally specialized muscular mechanism which can be affected from HPS. The HPS also has a relation to specific cells, such as ICC that generates NO, provoke the spontaneous pacemakers and biological slow waves (Tab. 1, Fig. 1, Ref. 19).

Combating endometriosis by blocking proteasome and nuclear factor-kappaB pathways

BACKGROUND

The objective of this study is to investigate the effect of pyrrolidine dithiocarbamate [PDTC; a nuclear factor-kappaB (NF-kappaB) inhibitor] and bortezomib (Velcade; a proteasome inhibitor) on the development of experimental endometriotic implants in rats.

METHODS

Endometriosis was surgically induced in 30 rats using the method of Vernon and Wilson. Three weeks later the viability and volume of the implants were recorded and classified. Afterwards, rats were put into three groups with equal numbers. The groups were labelled as the control, the PDTC and the bortezomib groups. Seven days after treatment, a third laparotomy was done and the volume of implants was measured again. The animals were then sacrificed, and the implants were stained with Ki67, proliferating cell nuclear antigen (PCNA), CD34, CD31 and Masson's trichrome histochemical staining.

RESULTS

In 80% of the implanted rats, vesicles at the suture region were observed, and the rats graded according to average vesicle diameter (D) as: Grade 1 (no vesicle, 20% of rats), Grade 2 (D < 2 mm, 33.3% of rats), Grade 3 (2 mm<D > 4.5 mm, 26.7% of rats) and Grade 4 (D > 4.5 mm, 20% of rats). After treatment with PDTC or bortezomib, these percentages were decreased for Grades 3 and 4, and increased in Grade 1. The post-treatment implant volumes were decreased in the PDTC and bortezomib groups (P < 0.002 and P < 0.001), and slightly increased in the control group (P = 0.279). In the PDTC and bortezomib groups, CD34, CD31, PCNA and Ki67 expression levels were similar but were significantly reduced compared with the control group.

CONCLUSIONS

PDTC and bortezomib may represent a novel therapeutic strategy for treatment of endometriosis.

Time-frequency analysis of ECG signals using an image processing technique

To overcome limitations that occur in time-frequency representations (TFR) of signals, a new technique that considers the ambiguity function (AF) is proposed. This work firstly introduces a filtering technique that is based on the processing of the image of the AF of the signal. Secondly it shows the potential of this technique in application to ECG signal analysis by comparing some kernel-based techniques. The analytic form of the ECG is used to eliminate aliasing and the cross terms generated by the negative spectra that appear in TFRs. This work shows that data adaptive time-frequency analysis of the ECG by image processing techniques is possible and potentially useful.