In India, tuberculosis is an enormous public health problem. This study provides the first description of molecular diversity of the Mycobacterium tuberculosis complex (MTBC) from Sikkim, India. A total of 399 Acid Fast Bacilli sputum positive samples were cultured on Lőwenstein–Jensen media and genetic characterisation was done by spoligotyping and 24-loci MIRU-VNTR typing. Spoligotyping revealed the occurrence of 58 different spoligotypes. Beijing spoligotype was the most dominant type constituting 62.41% of the total isolates and was associated with Multiple Drug Resistance. Minimum Spanning tree analysis of 249 Beijing strains based on 24-loci MIRU-VNTR analysis identified 12 clonal complexes (Single Locus Variants). The principal component analysis was used to visualise possible grouping of MTBC isolates from Sikkim belonging to major spoligotypes using 24-MIRU VNTR profiles. Artificial intelligence-based machine learning (ML) methods such as Random Forests (RF), Support Vector Machines (SVM) and Artificial Neural Networks (ANN) were used to predict dominant spoligotypes of MTBC using MIRU-VNTR data. K-fold cross-validation and validation using unseen testing data set revealed high accuracy of ANN, RF, and SVM for predicting Beijing, CAS1_Delhi, and T1 Spoligotypes (93–99%). However, prediction using the external new validation data set revealed that the RF model was more accurate than SVM and ANN.
Sporotrichosis caused by the fungus Sporothrix schenckii has been widely reported from the northern Himalayan belt and the north eastern region of India. Three autochthonous cases of lymphocutaneous sporotrichosis from east and south districts of Sikkim are reported. Fluid aspirate from the nodulo-ulcerative lesions were sent for cytology and fungal culture. S. schenckii was isolated on culture and cytological examination in all three cases showed granulomatous reaction. Thermal dimorphism was demonstrated and animal pathogenicity testing was performed. Saturated solution of potassium iodide was used for treatment and the last case was treated with itraconazole and potassium iodide. Awareness of this disease and an extensive environmental study is required to understand the actual burden of this disease.
Cryptococcus neoformans and Cryptococcus gatti both cause infection in immunocompromised patients. We report a case of meningitis with C. gatti in an AIDS patient. This case to our knowledge is the first case of C. gatti being reported from Sikkim (North East India).
Background: Diagnosis and treatment of Latent Tuberculosis Infection (LTBI) remains to be one of the main bottlenecks in eradication of tuberculosis (TB). TB and LTBI risk among the residents of a congregate facility in a monastery, situated in a high-TB burden area, Sikkim, India, may be high due to their frequent travel history and has never been illustrated. Method: A population based cross sectional screening of all the monks and residents of Rumtek Monastery (Sikkim, India) was carried out for diagnosis of active TB and LTBI. TrueNat MTB and GenXpert MTB/Rif systems were utilized for active TB diagnosis, whereas QFT-plus IGRA analysis was carried out for LTBI detection. LTBI positive cases were followed up with TrueNat MTB system to diagnose any progression to active TB.Results: Among the 350 residents of the monastery, no participant was found to be having active TB infection; however, ~45% of residents were LTBI positive showing high exposure of disease to the monks belonging to various age groups (9-73 yrs). Participants with frequent travel history, family history of TB or having contacts with TB patients, showed higher percentage of LTBI. Similarly, abnormal BMI showed significant positive correlation with LTBI.Conclusion: This study provides status of high prevalence of LTBI among the residence of a congregate facility in a monastery. These results can be useful to design strategies to treat LTBI in the high TB burden area to achieve the goal of TB elimination.
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