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An active search for Mycobacterium leprae drug resistance was carried out, 243 multibacillary patients from endemic regions of Colombia were included from 2004 to 2013 in a surveillance program. This program was a World Health Organization initiative for drug resistance surveillance in leprosy, where Colombia is a sentinel country. M. leprae DNA from slit skin smear and/or skin biopsy samples was amplified and sequenced to identify mutations in the drug resistance determining region (DRDR) in rpoB, folP1, gyrA, and gyrB, the genes responsible for rifampicin, dapsone and ofloxacin drug-resistance, respectively. Three isolates exhibited mutations in the DRDR rpoB gene (Asp441Tyr, Ser456Leu, Ser458Met), two in the DRDR folP1 gene (Thr53Ala, Pro55Leu), and one isolate exhibited mutations in both DRDR rpoB (Ser456Met) and DRDR folP1 (Pro55Leu), suggesting multidrug resistance. One isolate had a double mutation in folP1 (Thr53Ala and Thr88Pro). Also, we detected mutations outside of DRDR that required in vivo evaluation of their association or not with drug resistance: rpoB Arg505Trp, folP1 Asp91His, Arg94Trp, and Thr88Pro, and gyrA Ala107Leu. Seventy percent of M. leprae mutations were related to drug resistance and were isolated from relapsed patients; the likelihood of relapse was significantly associated with the presence of confirmed resistance mutations (OR range 20.1-88.7, p < 0.05). Five of these relapsed patients received dapsone monotherapy as a primary treatment. In summary, the current study calls attention to M. leprae resistance in Colombia, especially the significant association between confirmed resistance mutations and relapse in leprosy patients. A high frequency of DRDR mutations for rifampicin was seen in a region where dapsone monotherapy was used extensively.

MATERIALS AND METHODS:In this paper, we propose a theoretical model based upon previous studies about personal and social network dynamics of job performance. We provide empirical support for this model using real-world data within the context of the Australian radiology profession. An examination of radiologists' professional network topology through structural-positional and relational dimensions and radiologists' personal characteristics in terms of knowledge, experience and self-esteem is provided. Thirty one breast imaging radiologists completed a purpose designed questionnaire regarding their network characteristics and personal attributes. These radiologists also independently read a test set of 60 mammographic cases: 20 cases with cancer and 40 normal cases. A Jackknife free response operating characteristic (JAFROC) method was used to measure the performance of the radiologists' in detecting breast cancers. RESULTS:Correlational analyses showed that reader performance was positively correlated with the social network variables of degree centrality and effective size, but negatively correlated with constraint and hierarchy. For personal characteristics, the number of mammograms read per year and self-esteem (self-evaluation) positively correlated with reader performance. Hierarchical multiple regression analysis indicated that the combination of number of mammograms read per year and network's effective size, hierarchy and tie strength was the best fitting model, explaining 63.4% of the variance in reader performance. The results from this study indicate the positive relationship between reading high volumes of cases by radiologists and expertise development, but also strongly emphasise the association between effective social/professional interactions and informal knowledge sharing with high performance.