38 research outputs found
Using Model Explanations to Guide Deep Learning Models Towards Consistent Explanations for EHR Data
It has been shown that identical Deep Learning (DL) architectures will produce distinct explanations when trained with different hyperparameters that are orthogonal to the task (e.g. random seed, training set order). In domains such as healthcare and finance, where transparency and explainability is paramount, this can be a significant barrier to DL adoption. In this study we present a further analysis of explanation (in)consistency on 6 tabular datasets/tasks, with a focus on Electronic Health Records data. We propose a novel deep learning ensemble architecture that trains its sub-models to produce consistent explanations, improving explanation consistency by as much as 315% (e.g. from 0.02433 to 0.1011 on MIMIC-IV), and on average by 124% (e.g. from 0.12282 to 0.4450 on the BCW dataset). We evaluate the effectiveness of our proposed technique and discuss the implications our results have for both industrial applications of DL and explainability as well as future methodological work
Involvement of heparanase in the pathogenesis of acute kidney injury: Nephroprotective effect of PG545
Despite the high prevalence of acute kidney injury (AKI) and its association with increased morbidity and mortality, therapeutic approaches for AKI are disappointing. This is largely attributed to poor understanding of the pathogenesis of AKI. Heparanase, an endoglycosidase that cleaves heparan sulfate, is involved in extracellular matrix turnover, inflammation, kidney dysfunction, diabetes, fibrosis, angiogenesis and cancer progression. The current study examined the involvement of heparanase in the pathogenesis of ischemic reperfusion (I/R) AKI in a mouse model and the protective effect of PG545, a potent heparanase inhibitor. I/R induced tubular damage and elevation in serum creatinine and blood urea nitrogen to a higher extent in heparanase over-expressing transgenic mice vs. wild type mice. Moreover, TGF-\u3b2, vimentin, fibronectin and \u3b1-smooth muscle actin, biomarkers of fibrosis, and TNF\u3b1, IL6 and endothelin-1, biomarkers of inflammation, were upregulated in I/R induced AKI, primarily in heparanase transgenic mice, suggesting an adverse role of heparanase in the pathogenesis of AKI. Remarkably, pretreatment of mice with PG545 abolished kidney dysfunction and the up-regulation of heparanase, pro-inflammatory (i.e., IL-6) and pro-fibrotic (i.e., TGF-\u3b2) genes induced by I/R. The present study provides new insights into the involvement of heparanase in the pathogenesis of ischemic AKI.Our results demonstrate that heparanase plays a deleterious role in the development of renal injury and kidney dysfunction,attesting heparanase inhibition as a promising therapeutic approach for AKI
C151 in KEAP1 is the main cysteine sensor for the cyanoenone class of NRF2 activators, irrespective of molecular size or shape
Additional Power Generation From Waste Energy of Diesel Engine Using Parallel Flow Shell and Tube Heat Exchanger
RADIATION ABSORPTION, GROWTH AND YIELD OF PIGEONPEA CULTIVARS AS INFLUENCED BY SOWING DATES
Electrospun nano silver embedded polystyrene composite nanofiber as a possible water disinfectant
288-293Nano silver (Ag) embedded polystyrene (PS) composite nanofibers have been prepared by electrospinning technique using N,N-dimethylformamide (DMF) as solvent. Nanofibers have been characterized by Fourier transform infrared spectroscopy. Thermal properties of the fibers have been studied using thermogravimetric analysis (TGA). X-ray diffraction study showed silver nanoparticles to be of the size of 19 nm with a cubic structure. The size of silver nanoparticles have also been deduced from TEM analysis and found to be between 11–14 nm. The morphology of PS nanofiber has been demonstrated by scanning electron microscopy (SEM). Antibacterial activity of PS nanofiber and nano Ag embedded PS composite nanofiber against Gram-negative Escherichia coli (E. coli) and Gram-positive Bacillus subtilis (B. subtilis) microorganisms has been evaluated by well diffusion method and viable cell count method
Valnoctamide and sec-butyl-propylacetamide SPD for acute seizures and status epilepticus
sec-Butyl-propylacetamide (SPD) is a one-carbon homologue of valnoctamide (VCD), a chiral constitutional isomer of valproic acid’s (VPA) corresponding amide valpromide. VCD has a potential in epilepsy including status epilepticus (SE) and neuropathic pain, and is currently being developed for the treatment of bipolar disorder. Both VCD and SPD possess two stereogenic carbons in their chemical structure.
SPD possess a unique and broad-spectrum antiseizure profile superior to that of VPA and better than that of VCD. In addition SPD blocked behavioral- and electrographic-SE induced by pilocarpine and soman (organophosphate nerve gas) and afforded in vivo neuroprotection that was associated with cognitive sparing. VCD has similar activity as SPD in the pilocarpine-induced-SE although at higher doses. The activity of SPD and VCD against SE is superior to that of diazepam in terms of rapid onset, potency and ability to block SE when given 20 to 60 min after seizure onset. When administered 20 and 40min after SE onset, SPD (100–174mg/kg) produced long-lasting efficacy (e.g., 4–8hr) against soman-induced convulsive- and electrographic-SE in both rats and guinea pigs. SPD activity in the pilocarpine-and soman-induced SE models when administered 20 to 60 min after seizure onset differentiates SPD from benzodiazepines and all other AEDs
Isolation of pathogenic Escherichia coli from buffalo meat sold in Parbhani city, Maharashtra, India
Aim: Isolation, characterization, in-vitro pathogenicity and antibiogram study of E.coli from buffalo meat sold in Parbhani city. Materials and Methods: Meat samples were collected from buffalo immediately after slaughter. Isolation, identification and enumeration of E. coli were done by following standard methods and protocols. Hemolysin test and Congo red binding assay were used to study in-vitro pathogenicity of E. coli isolates. Disc diffusion method was used to study antibiogram of pathogenic E. coli isolates. Results: A total of 250 buffalo meat samples were collected and processed. A total of 22 (8.80 percent) E. coli isolates were isolated with average differential count of 1.231 ± 0.136 log cfu/g on EMB agar. All the E. coli isolates were confirmed by 10 Grams staining, biochemical reactions and sugar fermentation and motility tests. A total of 9 (3.6 percent) E. coli isolates were found to be pathogenic by in-vitro pathogenicity testing. Antibiogram studies of pathogenic E. coli isolates showed that all 9 isolates were sensitive to gentamycin (20 ± 1.49 mm) while 7 isolate showed resistance to enrofloxacin (18.22 ± 3.58 mm) and tetracycline (11.44 ± 2.04 mm). Conclusion: Buffalo meat sold in Parbhani city is an important source of E. coli infection to human population. A total of 9 pathogenic E. coli were isolated from buffalo meat immediately after slaughter. All isolates were characterized and confirmed pathogenic by in-vitro pathogenicity tests. Antibiogram studies of all isolates revealed sensitivity to gentamicin and resistance to tetracycline and enrofloxacin. [Vet World 2013; 6(5.000): 277-279
Fast and effective optimisation of arrays of submerged wave energy converters
A Recombination of the 25th International Conference on Genetic Algorithms (ICGA) and the 21st Annual Genetic Programming Conference (GP)Renewable forms of energy are becoming increasingly important to consider, as the global energy demand continues to grow. Wave energy is one of these widely available forms, but it is largely unexploited. A common design for a wave energy converter is called a point absorber or buoy. The buoy typically oats on the surface or just below the surface of the water, and captures energy from the movement of the waves. It can use the motion of the waves to drive a pump to generate electricity and to create potable water. Since a single buoy can only capture a limited amount of energy, large-scale wave energy production necessitates the deployment of buoys in large numbers called arrays. However, the efficiency of arrays of buoys is affected by highly complex intra-buoy interactions. The contributions of this article are two-fold. First, we present an approximation of the buoy interactions model that results in a 350-fold computational speed-up to enable the use inside of iterative optimisation algorithms, Second, we study arrays of fully submerged three-tether buoys, with and without shared mooring points.Junhua Wu, Slava Shekh, Nataliia Y. Sergiienko, Benjamin S. Cazzolato, Boyin Ding, Frank Neumann, Markus Wagne