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We report a case of a 36-year-old lady who presented with a huge fungating tumour that involved the entire right breast. The tumour was diagnosed histologically as undifferentiated primary stromal tumour of the breast with axillary lymph node metastasis. We review the literature of this rare malignant tumour. Stromal sarcomas of the breast lack epithelial participation, and diagnosis of these tumours can be difficult. Genome-wide expression profiling is currently used to determine the cell of origin of most sarcomas. Surgery offers the best therapeutic option. Adjuvant radiotherapy is not very beneficial, while chemotherapy has, to date, no established role in the management of this disease. The prognosis is dismal for patients with lymph node involvement. The size of the tumour has a lesser bearing on outcome.

Arterial injuries present the most challenging conditions in surgical practice. Many fail to reach the specialist in time and end up losing limbs or lives. Though well addressed elsewhere, it has received less attention in developing countries like India. There is a need to study these injuries from the perspective of countries like India. The aims of the study are to (1) analyze the epidemiology, presentation, and outcomes of arterial injuries operated by the author in Indian settings; (2) identify factors associated with adverse outcomes; and (3) discuss the critical issues with relevance to our country. Retrospective analysis of arterial injuries operated by the author between July 2010 and February 2014 at our institution was performed. Patients with feasibility of revascularization were included and nonviable limbs requiring primary amputations were excluded. Sixty-one patients fulfilled the criteria of which 55 (90.1 %) were males and 6 (9.8 %) females aged between 5 and 70 years. The mean duration of presentation was 21 h. Majority were resultant of road traffic accidents (62.7 %). Among 49 (80.3 %) noniatrogenic injuries, the mechanism was blunt in 46 (93.8 %, n=49) and penetrating in 3 (6.1 %) cases. Iatrogenic injuries were seen in 12 (19.6 %) cases. Lower limbs accounted for 37 (60.6 %) cases, popliteal segment being common, 22 (36 %) cases. Bony injuries were associated in 39 (63.9 %) cases. The most common procedure was interposition graft (49.1 %). Six (9.8 %) patients required an amputation resulting in 55 (90.1 %) salvaged limbs.Reaching a specialist center in appropriate time can result in good limb salvage rates and functional outcomes. Creating awareness and training the personnel are the critical issues in the management of arterial injuries in India.

Medical data mining has great potential for exploring the hidden patterns in the data sets of the medical domain. These patterns can be utilized for the classification of various diseases. Data mining technology provides a user-oriented approach to novel and hidden patterns in the data. The present study consisted of records of 746 patients collected from ADRC, ISTAART, USA. Around eight hundred and ninety patients were recruited to ADRC and diagnosed for Alzheimer's disease (65%), vascular dementia (38%) and Parkinson's disease (40%), according to the established criteria. In our study we concentrated particularly on the major risk factors which are responsible for Alzheimer's disease, vascular dementia and Parkinson's disease. This paper proposes a new model for the classification of Alzheimer's disease, vascular disease and Parkinson's disease by considering the most influencing risk factors. The main focus was on the selection of most influencing risk factors for both AD and PD using various attribute evaluation scheme with ranker search method. Different models for the classification of AD, VD and PD using various classification techniques such as Neural Networks (NN) and Machine Learning (ML) methods were also developed. It is observed that increase in the vascular risk factors increases the risk of Alzheimer's disease. It was found that some specific genetic factors, diabetes, age and smoking were the strongest risk factors for Alzheimer's disease. Similarly, for the classification of Parkinson's disease, the risk factors such as stroke, diabetes, genes and age were the vital factors.