35 research outputs found
Effect of vitamin C on N,N′-dimethyl-4,4′-bipyridinium dichloride-induced hepatic and renal toxicity in Swiss albino mice
Purpose: To evaluate the effectiveness of vitamin C on paraquat-induced hepatic and renal toxicity in Swiss albino mice.Methods: Three groups of Swiss albino mice (n = 10), i.e., control, paraquat (15 mg/kg) and paraquat (15 mg/kg) + vitamin C (20 mg/kg) were used in the study. The drugs were administered intraperitoneally for four days. Blood samples were collected on day 5 for determination of serum levels of liver and renal biomarkers. Thereafter, the animals were sacrificed; liver and kidney were excised and preserved in neutral formalin for histopathological analysis.Results: The paraquat-treated animals showed higher levels of aspartate transaminase (AST), alanine transaminase (ALT), serum urea and creatinine, relative to values for control. Histopathological examination of the paraquat-treated animals showed cytoplasmic vacuolar degeneration and congestion of central vein in the liver, and glomerular necrosis in the kidneys. Control and vitamin C-treated mice showed normal architecture of liver and kidney.Conclusion: These results indicate that vitamin C modulated the paraquat-induced liver and renal abnormalities in the experimental animals. Thus vitamin C exerts hepatoprotective and renoprotective effects against paraquat poisoning.Keywords: Paraquat poisoning, Liver, Kidney, Vitamin C, Toxicity, Histopatholog
SnapShare: AI Trained Mobile App to Share Snaps Automatically
These days people take more than 1 million group or selfie photos per day. This goes very hectic for a mobile owner to identify photos of each individual and send them their photos separately. Sharing photos create extra burden for mobile owners. There are fewer applications available (i.e., 23Snaps, Cluster, Path, letmesee) to share photos with small circle of friends. Unfortunately, these developed apps require user’s interaction to identify individuals in the photo. This study proposes a SnapShare mobile application that uses Face Recognition Algorithms to classify individuals in the photos and automatically shares photos with recognized individuals. SnapShare basically uses Deep learning (DL) and Machine Learning (ML) techniques for Face Recognition from the captured images. Based on the results, the developed system achieves the standard performance accuracy (i.e., >90%). The aim of the SnapShare is to create comfort for mobile owners and people visible in-group photo to share and access photo automatically. Furthermore, SnapShare also facilitates user to back up their photo gallery on server storage
Occupational radiation exposure to nursing staff during cardiovascular fluoroscopic procedures:A review of the literature
Fluoroscopy is a method used to provide real time x‐ray imaging of the body during medical procedures to assist with medical diagnosis and treatment. Recent technological advances have seen an increase in the number of fluoroscopic examinations being performed. Nurses are an integral part of the team conducting fluoroscopic investigations and are often located close to the patient resulting in an occupational exposure to radiation. The purpose of this review was to examine recent literature which investigates occupational exposure received by nursing staff during cardiovascular fluoroscopic procedures. Articles published between 2011 and 2017 have been searched and comprehensively reviewed on the referenced medical search engines. Twenty‐four relevant studies were identified among which seventeen investigated nursing dose comparative to operator dose. Seven researched the effectiveness of interventions in reducing occupational exposure to nursing staff. While doctors remain at the highest risk of exposure during procedures, evidence suggests that nursing staff may be at risk of exceeding recommended dose limits in some circumstances. There is also evidence of inconsistent use of personal protection such as lead glasses and skull caps by nursing staff to minimize radiation exposure. Conclusions: The review has highlighted a lack of published literature focussing on dose to nurses. There is a need for future research in this area to inform nursing staff of factors which may contribute to high occupational doses and of methods for minimizing the risk of exposure, particularly regarding the importance of utilizing radiation protective equipment
Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.
Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability
A Unique Case of an Aggressive Gangliocytic Paraganglioma of the Filum Terminale
Paragangliomas are rare neuroendocrine tumors that are mostly found in the head and neck. Even less common are gangliocytic variant paragangliomas of the spine for which there are only 7 other documented cases in the literature. We report a case of gangliocytic paraganglioma of the sacral spine in a 68-year-old man. The growth pattern is documented over three years, which to our knowledge has not previously been reported in the literature and is different from the natural history. Clinical, radiological, and pathological characteristics of the tumor are discussed in light of available reports of this rare tumor
In vitro cytotoxic, antibacterial, antifungal and urease inhibitory activities of some N
High-Speed Real-Time Resting State fMRI using Multi-Slab Echo-Volumar Imaging
We recently demonstrated that ultra-high-speed real-time fMRI using multi-slab echo-volumar imaging (MEVI) significantly increases sensitivity for mapping task-related activation and resting state networks (RSNs) compared to echo-planar imaging (Posse et al. 2012). In the present study we characterize the sensitivity of MEVI for mapping RSN connectivity dynamics, comparing independent component analysis (ICA) and a novel seed-based connectivity analysis (SBCA) that combines sliding-window correlation analysis with meta-statistics. This SBCA approach is shown to minimize the effects of confounds, such as movement, and CSF and white matter signal changes, and enables real-time monitoring of RSN dynamics at time scales of tens of seconds. We demonstrate highly sensitive mapping of eloquent cortex in the vicinity of brain tumors and arteriovenous malformations, and detection of abnormal resting state connectivity in epilepsy. In patients with motor impairment, resting state fMRI provided focal localization of sensorimotor cortex compared with more diffuse activation in task-based fMRI. The fast acquisition speed of MEVI enabled segregation of cardiac-related signal pulsation using ICA, which revealed distinct regional differences in pulsation amplitude and waveform, elevated signal pulsation in patients with arteriovenous malformations and a trend towards reduced pulsatility in gray matter of patients compared with healthy controls. Mapping cardiac pulsation in cortical gray matter may carry important functional information that distinguishes healthy from diseased tissue vasculature. This novel fMRI methodology is particularly promising for mapping eloquent cortex in patients with neurological disease, having variable degree of cooperation in task-based fMRI. In conclusion, ultra-high-real-time speed fMRI enhances the sensitivity of mapping the dynamics of resting state connectivity and cerebrovascular pulsatility for clinical and neuroscience research applications