Evaluation on the Outcome of Management of Infected Non Union and Gap Non Union Fracture of Long Bones by Ilizarov Method

INTRODUCTION: Management of infected non-union and gap non-union fracture of long bones is a great challenge to orthopaedic surgeons. Infected non-union of fractures is not a single problem and it is associated with multiple problems like infections, bone defects, limb length discrepancies, deformities and soft tissue problems like scaring, discharging sinuses, etc. Duration of treatment and cost creates a huge burden to the patient as well as treating institution. Ilizarov address all the problems simultaneously. Distraction osteogenesis following corticotomy helps in filling the bone defects, eradicating the infection and promote fracture healing. MATERIALS AND METHODS: This Prospective study was conducted at The department of Orthopaedics, Stanley medical college, Chennai, Tamil Nadu during the period August 2015 to July 2016. In our study includes 20 cases with 18 males and 2 females admitted with infected non-union fracture of long bones, gap non-union fracture of long bones due to various causes was treated by Ilizarov ring fixation method and were studied for the functional outcome, complications and fracture union. The results were evaluated using the criteria laid down by The Association for The Study and Application of the Methods of Ilizarov (ASAMI) Scoring system. RESULTS: Bone healing was excellent in 75% of cases, good in 20%, fair in 5% and none of cases have poor results. Functional results were excellent in 40% and good in 55% , fair in 5% of cases and none of cases show poor results. Limb length discrepancies and joint stiffness are the common complications. CONCLUSIONS: The goal in treatment of infected non-union and gap non-union is to have a well aligned, painless, healed and functional limb. Ilizarov ring fixation is the better option in treatment of infected non-union and gap non-union. Considering the complexity of problems , it is the treatment of choice as it address the problems associated with infected non-union and gap non-union of fracture. Sound patient selection with realistic treatment goals is the key for successful management

Gene expression data analysis using novel methods: Predicting time delayed correlations and evolutionarily conserved functional modules

Microarray technology enables the study of gene expression on a large scale. One of the main challenges has been to devise methods to cluster genes that share similar expression profiles. In gene expression time courses, a particular gene may encode transcription factor and thus controlling several genes downstream; in this case, the gene expression profiles may be staggered, indicating a time-delayed response in transcription of the later genes. The standard clustering algorithms consider gene expression profiles in a global way, thus often ignoring such local time-delayed correlations. We have developed novel methods to capture time-delayed correlations between expression profiles: (1) A method using dynamic programming and (2) CLARITY, an algorithm that uses a local shape based similarity measure to predict time-delayed correlations and local correlations. We used CLARITY on a dataset describing the change in gene expression during the mitotic cell cycle in Saccharomyces cerevisiae. The obtained clusters were significantly enriched with genes that share similar functions, reflecting the fact that genes with a similar function are often co-regulated and thus co-expressed. Time-shifted as well as local correlations could also be predicted using CLARITY. In datasets, where the expression profiles of independent experiments are compared, the standard clustering algorithms often cluster according to all conditions, considering all genes. This increases the background noise and can lead to the missing of genes that change the expression only under particular conditions. We have employed a genetic algorithm based module predictor that is capable to identify group of genes that change their expression only in a subset of conditions. With the aim of supplementing the Ustilago maydis genome annotation, we have used the module prediction algorithm on various independent datasets from Ustilago maydis. The predicted modules were cross-referenced in various Saccharomyces cerevisiae datasets to check its evolutionarily conservation between these two organisms. The key contributions of this thesis are novel methods that explore biological information from DNA microarray data

Comparing the efficacy of ultra-brief pulse to brief pulse in electroconvulsive therapy for major depression: a systematic review

BACKGROUND: Electroconvulsive therapy (ECT) is an effective intervention for major depressive disorder, especially for subsets of depression that resist more common therapies. However, ECT use is limited by its significant risk for adverse cognitive side effects. Shortening the pulse width of the current used has been demonstrated to lower this risk; however, the shorter pulse may not sufficiently elicit therapeutic effects. A systematic review was performed to determine if UBP ECT is as efficacious as BP ECT, and therefore would be a valid treatment for managing depression. METHODS: We conducted a literature search of MedLine/PubMed, Embase, Cochrane CENTRAL, and Google Scholars databases in October 2017 with the terms “depression”, “major depressive disorder”, “electroconvulsive therapy”, “ECT”, “brief”, “ultrabrief”, and “sine wave”. Studies were selected using inclusion criteria and exclusion criteria. Effects sizes were calculated from formalized mood rating pre-ECT and post-ECT, response rates and remission rates. Heterogeneity and reporting bias of the articles were also assessed. Data were analyzed using meta-analysis tools provided by the Erasmus Research Institute of Management. RESULTS: Data from 9 studies resulted in a pooled Cohen’s d = 0.16 (CI = -0.08 to 0.43, p = 0.149). The effect size alone favors BP ECT over UBP ECT in improving mood as per MADRS/HRSD ratings, but if given p > 0.05, results were non-significant. BP ECT was determined to be more efficacious then UBP ECT in terms of both achieving response and achieving remission, with a pooled ORresponse = 0.72 (CI – 0.49 to 1.05, p = 0.027) and pooled ORremission = 0.65 (CI = 0.42 to 0.98, p = 0.011). CONCLUSION: The choice to use BP ECT or UBP ECT is a balance between the burden of side effects and efficacy. These data suggest that patients with a lower risk of developing cognitive side effect and/or need urgent intervention receive BP ECT. Conversely, patients with a higher risk of developing adverse cognitive side effects and/or are not in need of urgent intervention may benefit UBP ECT. Additional studies are recommended to confirm these findings and clarify the optimal use of these two modalities of ECT

A Folklore Litigation in the Novel Agnaadi by Poomani

Nadar is a term used to describe the primitive manner of life of the human race. People's daily routines and customs are considered to be customs. An ethnic civilization is thought to have developed when customs alter over time and transform into cultural symbols. Every race still retains elements of its traditional dialects even after civilization has advanced. Poomani is regarded as one of the regional authors. He allows the writing to take on its own qualities by combining the aroma of the soil with the free-flowing energies of life. Through the short story ‘Aruppu’, he was introduced to the world of Tamil short stories. Poomani has the ability to write about rural life and aspects of ethnic culture. He wrote a book titled "Agnaadi" in 2012 after researching the history of the residents of Kalingal hamlet in Kovilpatti district. The book won the Sahitya Akademi Award in the year 2014 for its inventive ethnographic history and narrative.  The word Agngnaadi means' mother'. It is a term used by certain ethnic groups. In that way, Poomani’s Agnaadi which has recorded rural life has also recorded folk liturgies. This article examines the novel Agnaadi as a case of folklore litigation

Evolving Role of Women in Terror Groups: Progression or Regression?

Historically, women have been victims to a much greater degree than perpetrators of violence. However, the 1970s witnessed the emergence of women as important protagonists in the conflicts across the world. Recent years have witnessed suicide attacks perpetrated by women suicide bombers. This growing trend of women bombers has the general public and counterterrorism specialists concerned because of its implication that women will be key players in future terrorist attacks. Women’s role in terrorist organisations have also transformed since 1970s.Women across the ideological spectrum played different roles at different times. The use of women for “soft tasks” like logistics and recruitment gradually started to change in the mid-1980s when they started playing a much more visible frontline role. A woman taking up a suicide bombing role diverges significantly and is far more dangerous than their traditional activity of playing logisticians, recruiters or even a frontline role. This paper scrutinizes this change. There are multi causal issues which drive women to join terrorism and more so as suicide bombers. Psychological, economic, political, religious and sociological factors can act as contributors to understanding the causes that drive women towards terrorism. This paper attempts to highlight the role played by women in various terrorist organisations around the world. It also tries to bring out the factors which influence women to participate in terrorist acts. It aims to bring out the above facts by analysing various groups which have women cadre. Previous studies in the same realm have focused on a particular group or a conflict whereas this paper attempts to examine female participation across multiple conflicts in different groups driven by different ideology, which provides a clear insight into the multi causal factors which are responsible for this trend. The methodology followed is a descriptive one wherein the analysis is conducted on information derived from published secondary data

Gene expression data analysis using novel methods: Predicting time delayed correlations and evolutionarily conserved functional modules

Microarray technology enables the study of gene expression on a large scale. One of the main challenges has been to devise methods to cluster genes that share similar expression profiles. In gene expression time courses, a particular gene may encode transcription factor and thus controlling several genes downstream; in this case, the gene expression profiles may be staggered, indicating a time-delayed response in transcription of the later genes. The standard clustering algorithms consider gene expression profiles in a global way, thus often ignoring such local time-delayed correlations. We have developed novel methods to capture time-delayed correlations between expression profiles: (1) A method using dynamic programming and (2) CLARITY, an algorithm that uses a local shape based similarity measure to predict time-delayed correlations and local correlations. We used CLARITY on a dataset describing the change in gene expression during the mitotic cell cycle in Saccharomyces cerevisiae. The obtained clusters were significantly enriched with genes that share similar functions, reflecting the fact that genes with a similar function are often co-regulated and thus co-expressed. Time-shifted as well as local correlations could also be predicted using CLARITY. In datasets, where the expression profiles of independent experiments are compared, the standard clustering algorithms often cluster according to all conditions, considering all genes. This increases the background noise and can lead to the missing of genes that change the expression only under particular conditions. We have employed a genetic algorithm based module predictor that is capable to identify group of genes that change their expression only in a subset of conditions. With the aim of supplementing the Ustilago maydis genome annotation, we have used the module prediction algorithm on various independent datasets from Ustilago maydis. The predicted modules were cross-referenced in various Saccharomyces cerevisiae datasets to check its evolutionarily conservation between these two organisms. The key contributions of this thesis are novel methods that explore biological information from DNA microarray data

Ammonia toxicity: from head to toe?

Ammonia is diffused and transported across all plasma membranes. This entails that hyperammonemia leads to an increase in ammonia in all organs and tissues. It is known that the toxic ramifications of ammonia primarily touch the brain and cause neurological impairment. However, the deleterious effects of ammonia are not specific to the brain, as the direct effect of increased ammonia (change in pH, membrane potential, metabolism) can occur in any type of cell. Therefore, in the setting of chronic liver disease where multi-organ dysfunction is common, the role of ammonia, only as neurotoxin, is challenged. This review provides insights and evidence that increased ammonia can disturb many organ and cell types and hence lead to dysfunction

Testování nové generace LiDARu

The development of autonomous vehicles is heavily dependent on object detection technology. Li- DAR, a remote sensing technology that uses laser beams to measure distances and generate precise 3D representations of objects and their surroundings, plays a critical role in this domain. Object detection is essential for advancing autonomous vehicle technology. This study focuses on utilizing LiDAR data from Next Generation datasets and comparing it with the nuScenes dataset. The main objective is to predict object classes and validate the accuracy of the proposed solution using these two distinct datasets. The test approach employed in this study aims to evaluate the effectiveness of the solution and determine the optimal outcomes through rigorous result evaluation.Vývoj autonomních vozidel je silně závislý na technologii detekce objektů. LiDAR, technologie dálkového průzkumu, která využívá laserové paprsky k měření vzdáleností a generování přesných 3D reprezentací objektů a jejich okolí, hraje v této oblasti klíčovou roli. Detekce objektů je nezbytná pro pokrok v technologii autonomních vozidel. Tato studie se zaměřuje na využití dat LiDAR z datových sad nové generace a jejich porovnání s datovou sadou nuScenes. Hlavním cílem je předpovědět třídy objektů a ověřit přesnost navrhovaného řešení pomocí těchto dvou odlišných datových sad. Testovací přístup použitý v této studii má za cíl vyhodnotit efektivitu řešení a stanovit optimální výsledky prostřednictvím přísného vyhodnocení výsledků.450 - Katedra kybernetiky a biomedicínského inženýrstvídobř