Background:Melasma is an acquired increased pigmentation of the skin, characterized by gray-brown symmetrical patches, mostly in the sun-exposed areas of the skin. The pathogenesis is unknown, but genetic or hormonal influences with UV radiation are important.Aims:Our present research aims to study the clinico-epidemiological pattern and the precipitating or provocation factors in melasma.Materials and Methods:A total of 312 patients were enrolled for the study over a period of one year.Results:The mean age of patients with melasma was 33.45 years, ranging from 14 to 54 years. There was female preponderance with a female to male ratio of approximately 4 : 1. The mean age of onset was 29.99 years, with the youngest and oldest being 11 and 49 years, respectively. The patients sought medical treatment on an average of 3.59 years after appearance of melasma. About 55.12% of our patients reported that their disease exacerbated during sun exposure. Among 250 female patients, 56 reported pregnancy and 46 reported oral contraceptive as the precipitating factors. Only 34 patients had given history of exacerbation of melasma during pregnancy. A positive family history of melasma was observed in 104 (33.33%) patients. Centrofacial was the most common pattern (55.44%) observed in the present study. Wood light examination showed the dermal type being the most common in 54.48% and epidermal and mixed were seen in 21.47% and 24.03% of the cases, respectively. We tried to find an association with endocrinal diseases and observed that 20 of them had hypothyroidism.Conclusion:The exact cause of melasma is unknown. However, many factors have been implicated in the etiopathogenesis of this disorder. Here we try to identify the causative factors and provocation to develop melasma.

The aim of this paper was to develop a computer assisted tissue classification (granulation, necrotic, and slough) scheme for chronic wound (CW) evaluation using medical image processing and statistical machine learning techniques. The red-green-blue (RGB) wound images grabbed by normal digital camera were first transformed into HSI (hue, saturation, and intensity) color space and subsequently the “S” component of HSI color channels was selected as it provided higher contrast. Wound areas from 6 different types of CW were segmented from whole images using fuzzy divergence based thresholding by minimizing edge ambiguity. A set of color and textural features describing granulation, necrotic, and slough tissues in the segmented wound area were extracted using various mathematical techniques. Finally, statistical learning algorithms, namely, Bayesian classification and support vector machine (SVM), were trained and tested for wound tissue classification in different CW images. The performance of the wound area segmentation protocol was further validated by ground truth images labeled by clinical experts. It was observed that SVM with 3rd order polynomial kernel provided the highest accuracies, that is, 86.94%, 90.47%, and 75.53%, for classifying granulation, slough, and necrotic tissues, respectively. The proposed automated tissue classification technique achieved the highest overall accuracy, that is, 87.61%, with highest kappa statistic value (0.793).

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Xanthogranuloma is a benign, asymptomatic, and self-healing disorder of non-Langerhans cell histiocytosis, affecting mostly infants, children, and rarely adults. Diagnosis is easy in typical cases but become more complex in unusual forms. We report a case of a 28-year-old male patient who presented with multiple diffuse brown-to-yellowish papulonodular eruptions over extremities, ears, face, trunk, and extensors of joints with almost bilaterally symmetrical distribution for a period of one month. Histopathological examination of the skin biopsy specimen revealed features of xanthogranuloma. The patient was put on isotretinoin 20 mg once daily. Most of the lesions subsided or flattened within two months of isotretinoin therapy. This case is interesting because of the severity and atypical nature of the disease and also, the patient responded with isotretinoin therapy. But further study is required to observe the effectiveness of isotretinoin in xanthogranuloma.

Development of an intrinsically fluorescent nanofibrous scaffold of polycaprolactone–gelatin for skin tissue regeneration and noninvasive monitoring of scaffold activity in vivo.