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Abstract-We consider the task of automatically predicting spirometry readings from cough and wheeze audio signals for asthma severity monitoring. Spirometry is a pulmonary function test used to measure forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) when a subject exhales in the spirometry sensor after taking a deep breath. FEV1%, FVC% and their ratio are typically used to determine the asthma severity. Accurate prediction of these spirometry readings from cough and wheeze could help patients to non-invasively monitor their asthma severity in the absence of spirometry. We use statistical spectrum description (SSD) as the cue from cough and wheeze signal to predict the spirometry readings using support vector regression (SVR). We perform experiments with cough and wheeze recordings from 16 healthy persons and 12 patients. We find that the coughs are better predictor of spirometry readings compared to the wheeze signal. FEV1%, FVC% and their ratio are predicted with root mean squared error of 11.06%, 10.3% and 0.08 respectively. We also perform a three class asthma severity level classification with predicted FEV1% and obtain an accuracy of 77.77%.

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Context: Hair graying is one of the signs of human aging and is caused by a progressive loss of pigmentation from growing hair shafts. Studies have shown a correlation of early hair graying with osteopenia, indicating that premature graying could serve as an early marker of osteopenia. Aim: To compare the degree of osteopenia in individuals with premature graying of hair (PGH) compared to ordinary individuals. Settings and Design: We conducted an observational, case–control study among 132 healthy individuals between 18 and 30 years of age. Subjects and Methods: Detailed history and examination of PGH was taken. Bone mineral density (BMD) was assessed using Furuno CM-200 ultrasound bone densitometer. Statistical Analysis: SPSS 21 software was used, and the data were summarized in the form of mean ± standard deviation for quantitative values and percentages for qualitative values. Chi–square test, Student's t -test, analysis of variance, and other appropriate tests were applied for comparison, and P < 0.05 was considered statistically significant. Results: PGH was present in 82 (62.1%) cases, whereas osteopenia was present in 56 (42.4%) cases. The mean age of onset of graying of hair among the cases was 20.62 ± 3.74 years. A higher age group of 25–30 years ( P = 0.016) and family history of PGH ( P < 0.001) were significant risk factors for PGH. The mean BMD of the case group was 0.76 ± 1.00 and the control group was 0.68 ± 1.11, but the difference was not statistically significant ( P = 0.649). Conclusion: The study concluded that there is no significant association between osteopenia and PGH.

<p class="abstract"><strong>Background:</strong> Pregnancy can present with various dermatoses which is divided into physiological and pathological dermatoses. These dermatoses have various effects on pregnancy and patient’s life. The objective was to study the various pathological dermatoses.</p><p class="abstract"><strong>Methods:</strong> A total of 1425 pregnant females attending dermatology, obstetrics and gynaecology Out Patient Department of Era’s Lucknow Medical College and Hospital were included, out of this 275 presented with pathological dermatoses. Detailed history, examination and investigations were done. Data was analysed using Statistical Package for Social Sciences version 21.0 (test).<strong></strong></p><p class="abstract"><strong>Results:</strong> Pathological dermatoses was seen in 275 pregnant females ranged between 18 to 45 years. Infections or infestations and STDs (53.5%) were the most common dermatological conditions followed by pregnancy specific dermatoses (24.7%), acne and folliculitis (7.6%), non-specific itching (5.8%) and other conditions (10.9%).</p><p class="abstract"><strong>Conclusions:</strong> Pregnant females suffer from number of pregnancy dermatoses. A knowledge of the profile of dermatoses during pregnancy is essential to plan preventive measures, care of the mother and the child.</p>