Surgical management of avascular necrosis of femoral head in young adults treated with uncemented total hip replacement

Background: Normal hip joint is subjected to many stresses during daily activities performed by an individual. Since it is one of the major weight bearing joints of the body, its normal function is necessary for daily activities. Avascular necrosis (AVN) of the femoral head is one of the common causes of painful hip in a young adult. Core decompression, fibular sturt graft can be considered in early stages, total hip arthroplasty in later stages of AVN of femoral head.Methods: This is a retrospective study of 30 patients following uncemented total hip replacement, who were operated between August 2017 and March 2020 at MNR medical college and hospital, Sangareddy. They were followed up for a minimum period of 1 year and evaluated using Harris hip scoring system. Harris hip score is designed specifically for measuring functional outcomes in hip arthroplasty.Results: There was a significant improvement in function as measured with the Harris hip score. The overall preoperative Harris hip score was 43, which remarkably improved to 89 postoperatively. The results observed, showed that all patients had good to excellent results, (Harris hip score ≥0) thus showing a good degree of pain relief, improvement in function and range of motion.Conclusions: Although the use of total hip arthroplasty in young patients will more likely necessitate future revision surgery, the consistent relief of pain and good functional results have made this procedure an attractive treatment choice for the debilitating arthritis resulting from osteonecrosis of the femoral head.

Low Power and Efficient Re-Configurable Multiplier for Accelerator

Deep learning is a rising topic at the edge of technology, with applications in many areas of our lives, including object detection, speech recognition, natural language processing, and more. Deep learning's advantages of high accuracy, speed, and flexibility are now being used in practically all major sciences and technologies. As a result, any efforts to improve the performance of related techniques are worthwhile. We always have a tendency to generate data faster than we can analyse, comprehend, transfer, and reconstruct it. Demanding data-intensive applications such as Big Data. Deep Learning, Machine Learning (ML), the Internet of Things (IoT), and high- speed computing are driving the demand for "accelerators" to offload work from general-purpose CPUs. An accelerator (a hardware device) works in tandem with the CPU server to improve data processing speed and performance. There are a variety of off-the-shelf accelerator architectures available, including GPU, ASIC, and FPGA architectures. So, this work focus on designing a multiplier unit for the accelerators. This increases the performance of DNN, reduced the area and increasing the training speed of the system

Myxoid degeneration of leiomyoma-a masquerader

Uterine leiomyomas are one of the most common benign lesions in the uterus. The lesion can vary in size from a few millimetres to centimetres, location, its presentation and degeneration. They are easy to diagnose clinically with the help of available imaging techniques. Myxoid degeneration is an uncommon degeneration and has to be kept as a differential diagnosis as it mimics uterine sarcoma. Histopathology and Immunohistochemical analysis help in confirming the diagnosis. Here is a patient in reproductive age group who presented with rapidly growing abdominal mass in a span of 1 year with a prior surgical history of myomectomy. Pre-operative imaging was inconclusive for benign etiology and possibility of uterine leiomyosarcoma could not be ruled out. She was hence counselled for a laparotomy with a frozen section to prevent extensive surgery. Myxoid degeneration is not a common degeneration of leiomyoma with a reported incidence of 10% while the incidence of uterine leiomyosarcoma is less than 1% in reproductive age group. Even though rare, myxoid degeneration should be considered as a differential diagnosis of rapidly growing uterine mass with inconclusive pre-operative imaging

Plant Disease Identification Using Machine Learning Techniques

Plants have become a principle origin of energy and are a basic piece in the complexity to work out the problems of a worldwide temperature alteration. There are various kinds of infections which are available in plants. To identify these sicknesses design are needed to remember them. A symbolic strategy for this situation is the utilization of distant dig-out strategies that explore multi and hyper unearthly picture clutch. The strategy that accepts this methodology regularly utilize advanced picture preparing devices to execute their objective. In this paper, various machine learning techniques are handed-down for automatic detection and categorization of plant leaf diseases. It also covers survey on numerous diseases categorization techniques that can be handed-down for plant leaf disease identification. In the remain work back proliferation and head segment investigation are utilized to distinguish plant sicknesses. These calculations are gained from preparing management in neural organization. There is an issue of exactness in these calculation

Influence of Milling Process Parameters on Machined Surface Quality of Carbon Fibre Reinforced Polymer (CFRP) Composites Using Taguchi Analysis And Grey Relational Analysis

The article presents the milled surface quality of Uni-Directional Carbon Fibre Reinforced Polymer (UD-CFRP) composites from Taguchi’s and grey relational analysis. The novelty is demonstrating the possibility of detecting the surface defects in polymer composites during milling using SEM analysis. The material used for this study is UD-CFRP composite laminates and made by hand-layup process. All the milling operations were carried out using a solid tungsten carbide end milling tool and experiments conducted on CNC milling machine. Taguchi L9, 3-level orthogonal array was considered for experimentation. Analysis of Variance (ANOVA) was conducted to explore the significance of each individual input process parameters on multiple performance characteristics. Optimal process parameters are thoroughly validated by grey relational grade achieved by the grey relational analysis for multi performance characteristics. Finally, experimental results were correlated and analyzed with scanning electron micrographs using Scanning Electron Microscope (SEM)

PHYTOCHEMICAL STUDIES AND QUALITATIVE ANALYSIS BY TLC OF MURRAYA KOENIGII BARK EXTRACT

Murraya koenigii is a medium size, ever green plant which has been utilized as a source of food, medicine, and other agricultural purposes in different communities. Thus, the preliminary phytochemical analysis and TLC separation was done using methanol, n-hexane, and ethyl acetate(1:3:1), as solvent system while iodine vapour as spotting agent. The phytochemical screening of diethyl ether extracts of bark revealed the presence of carbohydrates , anthraquinones glycosides ,saponins ,flavanoids, and alkaloids, while chloroform extracts of bark revealed carbohydrates, tannins, saponins, and alkaloids, while acetone extracts of bark revealed the presence of carbohydrates, anthraquinones glycosides, flavanoids and alkaloids,while ethanol extracts of bark revealed the presence of carbohydrates, tannins, anthraquinones glycosides,s aponins, flavanoids and alkaloids.TLC separation showed (3) spots each of Diethyl Ether, Chloroform, Acetone, Ethanol from bark extracts. From our findings, it can be concluded that Murraya Koenigii contains some significant phytochemicals that can exhibit desired therapeutic activities such as Antioxidant, Anti-Microbial, Anti-Fungal, Anti-Diabetic, Anti-Ulcer and Cosmetic use. However, there is a need to conduct further Pharmaceutical Analysis on test extracts in order to establish these biomedical applications. Keywords: Thin Layer Chromatography, Murraya koenigii Bark, Phytochemical screening

Immunoassay Urine Drug Testing among Patients Receiving Opioids at a Safety-Net Palliative Medicine Clinic

BACKGROUND: Few studies have examined the use of immunoassay urine drug testing of cancer patients in palliative care clinics. OBJECTIVES: We examined the frequency of immunoassay urine drug test (UDT) abnormalities and the factors associated with aberrancy at a safety-net hospital palliative medicine clinic. METHODS: A retrospective review of the electronic medical records of consecutive eligible patients seen at the outpatient palliative medicine clinic in a resource-limited safety-net hospital system was conducted between 1 September 2015 and 31 December 2020. We collected longitudinal data on patient demographics, UDT findings, and potential predictors of aberrant results. RESULTS: Of the 913 patients in the study, 500 (55%) underwent UDT testing, with 455 (50%) having the testing within the first three visits. Among those tested within the first three visits, 125 (27%) had aberrant UDT results; 44 (35%) of these 125 patients were positive for cocaine. In a multivariable regression model analysis of predictors for aberrant UDT within the first three visits, non-Hispanic White race (odds ratio (OR) = 2.13; 95% confidence interval (CI): 1.03-4.38; CONCLUSION: Despite limitations of immunoassay UDT, it was able to detect aberrant drug-taking behaviors in a significant number of patients seen at a safety-net hospital palliative care clinic, including cocaine use. These findings support universal UDT monitoring and utility of immunoassay-based UDT in resource-limited settings

Adherence to Opioid Patient Prescriber Agreements at a Safety Net Hospital

Patient prescriber agreements, also known as opioid contracts or opioid treatment agreements, have been recommended as a strategy for mitigating non-medical opioid use (NMOU). The purpose of our study was to characterize the proportion of patients with PPAs, the rate of non-adherence, and clinical predictors for PPA completion and non-adherence. This retrospective study covered consecutive cancer patients seen at a palliative care clinic at a safety net hospital between 1 September 2015 and 31 December 2019. We included patients 18 years or older with cancer diagnoses who received opioids. We collected patient characteristics at consultation and information regarding PPA. The primary purpose was to determine the frequency and predictors of patients with a PPA and non-adherence to PPAs. Descriptive statistics and multivariable logistic regression models were used for the analysis. The survey covered 905 patients having a mean age of 55 (range 18-93), of whom 474 (52%) were female, 423 (47%) were Hispanic, 603 (67%) were single, and 814 (90%) had advanced cancer. Of patients surveyed, 484 (54%) had a PPA, and 50 (10%) of these did not adhere to their PPA. In multivariable analysis, PPAs were associated with younger age (odds ratio [OR] 1.44

Studies on the effect of Polycyclic Aromatic Hydrocarbons in the life and activity of Perna spp

In the present study an endeavour has been made to analyse the acute toxicity of WAFs of Bombay High crude and Light Diesel oil on commercially important bivalve species Perna viridis and Perna indica by static bioassay methods. The toxic effects of chemicals in the WAF on the organisms ; their tissues and eventually on rate functions have been elucidated. Marine oil pollution not only affects productivity and quality of marine organisms but also eventually affects the health of human population due to a possible health risk by way of consumption of oil contaminated seafoodCochin University of Science and TechnologyDept. of Marine Biology, Microbiology and Biochemistry Cochin University of Science and Technolog