Increasing experience in laparoscopic staging of early ovarian cancer

We assessed the effect of increasing experience of a single surgeon (learning curve) in the laparoscopic staging procedure for women with early ovarian cancer and compared the results with the literature. We retrospectively analysed a total of 25 women with apparent early-stage ovarian cancer who underwent a laparoscopic staging procedure by the same surgeon. Three time periods, based on date of surgery, were compared with respect to operating time, amount of lymph nodes harvested and surgical outcome. There was no significant difference in operation time, estimated blood loss and hospital stay between the three periods. There was, however, a significant increase in the median number of pelvic and para-aortal lymph nodes harvested (group1 = 6.5, group 2 = 8.0 and group 3 = 21.0; P < 0.005). For the total period, median operation time was 235 min and median estimated blood loss was 100 ml. The median length of hospital stay was 4.0 days. Two intraoperative and two postoperative complications occurred. The upstaging rate was 32%. The mean interval between initial surgery and laparoscopic staging was 51.2 days. Mean duration of follow-up was 43 months, range (1–116 months). Five (20%) patients had recurrences, and two (8%) patients died of the disease. In conclusion, there is a significant learning curve for the laparoscopic full staging procedure in ovarian cancer. In our study this is mainly reflected in the amount of lymph nodes harvested and not in the total operating time

Interrogation of the perturbed gut microbiota in gouty arthritis patients through in silico metabolic modeling

Recent studies have shown perturbed gut microbiota associated with gouty arthritis, a metabolic disease characterized by an imbalance between uric acid production and excretion. To mechanistically investigate altered microbiota metabolism associated with gout disease, 16S rRNA gene amplicon sequence data from stool samples of gout patients and healthy controls were computationally analyzed through bacterial community metabolic models. Patient-specific community models constructed with the metagenomics modeling pipeline, mgPipe, were used to perform k-means clustering of samples according to their metabolic capabilities. The clustering analysis generated statistically significant partitioning of samples into a Bacteroides-dominated, high gout cluster and a Faecalibacterium-elevated, low gout cluster. The high gout cluster was predicted to allow elevated synthesis of the amino acids D-alanine and L-alanine and byproducts of branched-chain amino acid catabolism, while the low gout cluster allowed higher production of butyrate, the sulfur-containing amino acids L-cysteine and L-methionine, and the L-cysteine catabolic product H2S. By expanding the capabilities of mgPipe to provide taxa-level resolution of metabolite exchange rates, acetate, D-lactate and succinate exchanged from Bacteroides to Faecalibacterium were predicted to enhance butyrate production in the low gout cluster. Model predictions suggested that sulfur-containing amino acid metabolism generally and H2S more specifically could be novel gout disease markers

Synthesis, properties and applications of helical carbon nanotubes

Helical carbon nanotubes were produced on silica-supported Co catalysts by chemical vapour decomposition of acetylene. Coiled nanotubes were examined. They have been found to be of various shapes, diameter, and pitch. Some of them are extremely long, up to 5 mu m, with regular helices. The average outer diameter of coils are about 30-50 nm, the pitch is in the range 50-200 nm and the length about 1- 1.4 mu m. The helix-shaped windings of the helical carbon nanotubes reveal characteristic mechanical resonances, which are determined by the elastic modulus, mass, shape, and dimensions

Regularly curved carbon nanotubes

The increasing number of reports on regularly curved carbon nanotube-type architectures makes it increasingly important to understand the structure of these nano-objects, to predict their properties, and to get insight in the way they form. The present work attempts to explore some properties of regularly curved carbon nanotube by combining structural modeling, mechanical calculations, and experimental high-resolution transmission electron microscopy (HRTEM) data