The Cambridge post-mastectomy radiotherapy (C-PMRT) index : a practical tool for patient selection

BACKGROUND AND PURPOSE: Post mastectomy radiotherapy (PMRT) reduces loco-regional recurrence (LRR) and has been associated with survival benefit. It is recommended for patients with T3/T4 tumours and/or ⩾ 4 positive lymph nodes (LN). The role of PMRT in 1-3 positive LN and LN negative patients is contentious. The C-PMRT index has been designed for selecting PMRT patients, using independent prognostic factors for LRR. This study reports a 10 year experience using this index. MATERIALS AND METHODS: The C-PMRT index was constructed using the following prognostic factors (a) number of positive LN/lymphovascular invasion, (b) tumour size (c) margin status and (d) tumour grade. Patients were categorised as high (H) risk, intermediate (I) risk and low (L) risk. PMRT was recommended for H and I risk patients. The LRR, distant metastasis and overall survival (OS) rates were measured from the day of mastectomy. RESULTS: From 1999 to 2009, 898 invasive breast cancers in 883 patients were treated by mastectomy (H: 323, I: 231 and L: 344). At a median follow up of 5.2 years, 4.7% (42/898) developed LRR. The 5-year actuarial LRR rates were 6%, 2% and 2% for the H, I and L risk groups, respectively. 1.6% (14/898) developed isolated LRR (H risk n = 4, I risk group n = 0 and L risk n = 10). The 5-year actuarial overall survival rates were 67%, 77% and 90% for H, I and L risk groups, respectively. CONCLUSION: Based on published literature, one would have expected a higher LRR rate in the I risk group without adjuvant RT. We hypothesise that the I risk group LRR rates have been reduced to that of the L risk group by the addition of RT. Apart from LN status and tumour size, other prognostic factors should also be considered in selecting patients for PMRT. This pragmatic tool requires further validation

Face Recognition using local Patterns

Deriving an effective face representation is very essential task for automatic face recognition application. In this paper we used a feature descriptor called the Local Directional Number Pattern (LDN), which allows individual’s face recognition under different lightning’s, pose and expressions. Face recognition deals with different challenging problems in the field of image analysis and human computer interface. To deal with attention in our proposed work we use local patterns, a local directional number pattern (LDN) method, a six bit compact code for face recognition and understanding. By using LDN method we encode the directional information of the face images by convolving the face image with the compass mask. This compass mask extracts the edge response values in eight directions in the neighborhood. For each pixel we get the maximum and the minimum directional values which generate a LDN code i.e. generating an LDN image. Later LDN image is divided into number of blocks for each block histogram is computed and finally adds these histogram from each block to form the feature vector which acts as face descriptor to represent the face images. We perform different experiments under various illumination, pose and expression conditions

An Framework for Simple Sequence Repeat Reduction with Information Extraction using Machine Learning

Demand for the agricultural improvements using the advanced computer algorithms have increased in the recent years. The primary focus is on the higher crop production rates with least damage to the crops due to various diseases. In the recent times, a good number of research attempts are observed to formulate multiple computerized algorithms to identify the Amino Acid sequence and further protein sequences, which are responsible for diseases to the plants and crops. However, due to the higher complexity of DNA structure and further the complex process for DNA to Amino Acid extraction, these recent researches have produced unsatisfactory outcomes.  Henceforth, in order to solve the primary challenge of higher time complexity of the DNA processing methods, this work proposes two algorithms to reduce the DNA sequence length without losing vital information using machine learning. Firstly, the use of clustering method to reduce the size ensures least information loss and best processing time. Secondly, the look up based indexed Amino Acid extraction process ensures higher correctness of the extraction and again in best possible time. The proposed framework produced nearly 98% accuracy in 0.107 sec time frame, which is relatively 5% improvement in accuracy and 10% improvement in time complexit

Potential Analgesic & Anti-Pyretic Herbal drugs: A Comparative Review of Marketed Products

Analgesic from the family of the non-steroidal anti-inflammatory drugs (NSAIDs) have probably been used for more than 2000 years. In the 1900 ASA become an established treatment for pain and migraine. The detection of the main mechanism of the clinical effect of ASAs in John R.Vane’s group in 1972(who received the Nobel Prize for medicine in 1982 for his discovery of prostaglandin synthesis inhibition) gave a new and persistent drive to the development of other chemically different NSAID. The currently available analgesic and antipyretic drugs in allopathic system of medicine are not so effective in combating wide variety of complications. The remedial measure may lie in the ayurvedic system of medicine. The various herbal drugs such as Acacia nilotica, Bauhinia racemosa Linn. Cleome viscose, Hippobromus panciflorus etc known for their potential analgesic and antipyretic activity shall be discussed. The various branded herbal formulations like Rumalaya, Charak, Rumartho, Arthrella, and Reosto etc available in the market as analgesic and antipyretic remedies are also discussed along with their clinical merits. It may be concluded that since ayurvedic formulations contain number of ingredients in which one ingredient may act to enhance the action of other ingredient. Also as a result of so many ingredients present in the particular ayurvedic formulation it helps in combating other diseases in addition to analgesic and antipyretic activity.Keywords: Analgesic, Ayurvedic system, Herbal drugs, Antipyretic

Comparison of 0.5% Bupivacaine and 0.5% Ropivacaine epidurally in lower limb orthopaedic surgeries

Background: Ropivacaine in equi-potent concentrations with bupivacaine, the degree of motor blockade is less pronounced with ropivacaine, and there is a greater propensity for blocking pain transmitting A-delta and C fibres rather than A-α motor fibres. It appears to have most of the blocking characteristics of bupivacaine. So we have undertaken the study to compare ropivacaine 0.5% (20ml) and bupivacaine 0.5% (20ml) for epidural anaesthesia in patients undergoing lower limb orthopaedic surgeries.Methods: This double-blind, randomized study involves 60 patients who were undergone orthopaedic surgery, having ASA-I or ASA-II physical status. Out of 60, 30 patients received 20 ml of 0.5% ropivacaine and 30 patients received 20 ml of 0.5% bupivacaine at the L3, 4 interspace. Parameters measured were the onset time, duration and spread of sensory block, the onset time, peak time, duration and degree of motor block, the quality of anaesthesia and the heart rate and blood pressure profile during block onset.Results: Epidurally, Ropivacaine in comparison to Bupivacaine provides quicker onset, early peak effect and prolonged duration of sensory block and shorter duration of motor block. Ropivacaine provides prolonged effective analgesia. It reduces requirement of rescue analgesics and related side effects.Conclusions: Ropivacaine 0.5% is safer and effective alternative to Bupivacaine in epidural anaesthesia and post operative pain relief

Systematic transcriptome wide analysis of lncRNA-miRNA interactions.

BACKGROUND: Long noncoding RNAs (lncRNAs) are a recently discovered class of non-protein coding RNAs, which have now increasingly been shown to be involved in a wide variety of biological processes as regulatory molecules. The functional role of many of the members of this class has been an enigma, except a few of them like Malat and HOTAIR. Little is known regarding the regulatory interactions between noncoding RNA classes. Recent reports have suggested that lncRNAs could potentially interact with other classes of non-coding RNAs including microRNAs (miRNAs) and modulate their regulatory role through interactions. We hypothesized that lncRNAs could participate as a layer of regulatory interactions with miRNAs. The availability of genome-scale datasets for Argonaute targets across human transcriptome has prompted us to reconstruct a genome-scale network of interactions between miRNAs and lncRNAs. RESULTS: We used well characterized experimental Photoactivatable-Ribonucleoside-Enhanced Crosslinking and Immunoprecipitation (PAR-CLIP) datasets and the recent genome-wide annotations for lncRNAs in public domain to construct a comprehensive transcriptome-wide map of miRNA regulatory elements. Comparative analysis revealed that in addition to targeting protein-coding transcripts, miRNAs could also potentially target lncRNAs, thus participating in a novel layer of regulatory interactions between noncoding RNA classes. Furthermore, we have modeled one example of miRNA-lncRNA interaction using a zebrafish model. We have also found that the miRNA regulatory elements have a positional preference, clustering towards the mid regions and 3' ends of the long noncoding transcripts. We also further reconstruct a genome-wide map of miRNA interactions with lncRNAs as well as messenger RNAs. CONCLUSIONS: This analysis suggests widespread regulatory interactions between noncoding RNAs classes and suggests a novel functional role for lncRNAs. We also present the first transcriptome scale study on miRNA-lncRNA interactions and the first report of a genome-scale reconstruction of a noncoding RNA regulatory interactome involving lncRNAs

The Influence of Race on Health Status Outcomes One Year After an Acute Coronary Syndrome

ObjectivesThe goal of this study was to compare health status (symptoms, function, and quality of life) outcomes of whites and blacks one year after an acute coronary syndrome (ACS).BackgroundAlthough racial differences in the use of angiography and revascularization after ACS are known to exist, differences in health status outcomes have not been described.MethodsWe conducted a prospective registry of 1,159 consecutive ACS patients treated between February 1, 2000 and October 31, 2001. One-year health status was quantified with the Seattle Angina Questionnaire (SAQ) and Short Form-12 Physical Component Score (SF-12 PCS). Multivariable models were used to adjust for racial differences in sociodemographic, clinical, and treatment characteristics.ResultsMortality rates were similar among the 196 black and 963 white patients (7.1% vs. 7.0%, p = 0.93); 81 died during follow-up, and 199 (17%) could not be interviewed. At one year, blacks had a higher prevalence of angina (43.4% vs. 27.1%), worse quality of life (SAQ score = 70.6 ± 28.3 vs. 83.9 ± 20.8), and poorer physical function (SF-12 PCS = 36.8 ± 12.3 vs. 43.2 ± 11.4; p < 0.0001 for all). Multivariable models, including hospital treatments, revealed a trend for more angina (odds ratio 1.46 [95% confidence interval 0.91 to 2.34]) and significantly worse quality of life (mean difference = −7.7 ± 2.4, p = 0.002) and physical function (−3.6 ± 1.3, p = 0.005).ConclusionsBlacks have more angina, worse quality of life, and worse physical function one year after an ACS than do whites. Closer surveillance of black ACS patients is needed to determine whether additional treatment can improve their outcomes