Phenol biodegradation by a microbial consortium: application of artificial neural network (ANN) modelling

In this study, an effective microbial consortium for the biodegradation of phenol was grown under different operational conditions, and the effects of phosphate concentration (1.4 g L-1, 2.8 g L-1, 4.2 g L-1), temperature (25 degrees C, 30 degrees C, 35 degrees C), agitation (150 rpm, 200 rpm, 250 rpm) and pH (6, 7, 8) on phenol degradation were investigated, whereupon an artificial neural network (ANN) model was developed in order to predict degradation. The learning, recall and generalization characteristics of neural networks were studied using data from the phenol degradation system. The efficiency of the model generated by the ANN was then tested and compared with the experimental results obtained. In both cases, the results corroborate the idea that aeration and temperature are crucial to increasing the efficiency of biodegradation.

Prognostic factors for lymph node metastasis from advanced squamous cell carcinoma of the skin of the trunk and extremities

Abstract Background Squamous cell carcinoma (SCC) of the skin of the trunk and extremities may present lymph node metastasis with difficult disease control and poor survival. The purpose of this study was to identify risk factors for lymph node metastasis and outcome. Patients/Methods Retrospective review of 57 patients with locally advanced SCC of the trunk and extremities was performed and several clinical variables including age, gender, ethnicity, previously injured skin (burns, scars, ulcers and others), patient origin (rural or urban), anatomic site and treatment were studied. Results Fifteen patients presented with previous skin lesions. Thirty-six were classified as T3 tumors and 21 as T4; 46 were N0, and 11, N1. Eleven N0 patients presented lymph node metastasis during follow up. Univariate analysis identified previous skin lesions (ulcers and scars) as risk factor for lymph node metastasis (p = 0.047). Better survival was demonstrated for T3 (p = 0.018) classification. N0 patients who presented lymph node metastasis during follow up (submitted to lymphadenectomy) had similar survival to patients without lymph node recurrence (p = 0.219). Conclusion Local advanced tumors are at risk of lymph node metastasis. Increased risk is associated to previous lesions at tumor site. T4 classification have worse prognosis. Lymph node recurrences in N0 patients, once treated, did not affect survival. For these patients, we propose close follow up and prompt treatment of lymph node metastasis. These results do not support indication for elective lymphadenectomy or sentinel node mapping. Further prospective studies must address this issue.