Exclusion and Inclusion -- A model agnostic approach to feature importance in DNNs

Deep Neural Networks in NLP have enabled systems to learn complex non-linear relationships. One of the major bottlenecks towards being able to use DNNs for real world applications is their characterization as black boxes. To solve this problem, we introduce a model agnostic algorithm which calculates phrase-wise importance of input features. We contend that our method is generalizable to a diverse set of tasks, by carrying out experiments for both Regression and Classification. We also observe that our approach is robust to outliers, implying that it only captures the essential aspects of the input.Comment: 8 pages, 4 figure

An Interpretable Deep Learning System for Automatically Scoring Request for Proposals

The Managed Care system within Medicaid (US Healthcare) uses Request For Proposals (RFP) to award contracts for various healthcare and related services. RFP responses are very detailed documents (hundreds of pages) submitted by competing organisations to win contracts. Subject matter expertise and domain knowledge play an important role in preparing RFP responses along with analysis of historical submissions. Automated analysis of these responses through Natural Language Processing (NLP) systems can reduce time and effort needed to explore historical responses, and assisting in writing better responses. Our work draws parallels between scoring RFPs and essay scoring models, while highlighting new challenges and the need for interpretability. Typical scoring models focus on word level impacts to grade essays and other short write-ups. We propose a novel Bi-LSTM based regression model, and provide deeper insight into phrases which latently impact scoring of responses. We contend the merits of our proposed methodology using extensive quantitative experiments. We also qualitatively asses the impact of important phrases using human evaluators. Finally, we introduce a novel problem statement that can be used to further improve the state of the art in NLP based automatic scoring systems.Comment: 8 pages, 4 figure

A New Data Structure HC-Expression for Learning from Examples

A new data structure Hierarchical Counterfactual Expression (HC-Expression) is proposed.Its use in the area of learning from examples is studied. HC-Expression is a tree-like structure with alternate levels representing positive and negative exceptions to the rule. It is flexible and powerful enough to describe disjunctive concepts and can be visualised as a decision tree. Expressions to describe a concept can be efficiently generated from a set of examples and counter examples of a concept. The efficacy of the proposed method is examined by applying it to a set of data collected from the Institute of Indian Medicine

Downregulation of mouse intestinal Na(+)-coupled glucose transporter SGLT1 by gum arabic (Acacia Senegal)

Intestinal Na(+)-coupled glucose transporter SGLT1 determines the rate of glucose transport, which in turn influences glucose-induced insulin release and development of obesity. The present study explored effects of Gum Arabic (GA), a dietary polysaccharide from dried exudates of Acacia Senegal, on intestinal glucose transport and body weight in wild-type C57Bl/6 mice. Treatment with GA (100 g/l) in drinking water for four weeks did not affect intestinal SGLT1 transcript levels but decreased SGLT1 protein abundance in jejunal brush border membrane vesicles. Glucose-induced jejunal short-circuit currents revealed that GA treatment decreased electrogenic glucose transport. Drinking a 20% glucose solution for four weeks significantly increased body weight and fasting plasma glucose concentrations, effects significantly blunted by simultaneous treatment with GA. GA further significantly blunted the increase in body weight, fasting plasma glucose and fasting insulin concentrations during high fat diet. In conclusion, the present observations disclose a completely novel effect of gum arabic, i.e. its ability to decrease intestinal SGLT1 expression and activity and thus to counteract glucose-induced obesity

Upregulation of intestinal NHE3 following saline ingestion.

Contains fulltext : 187567.pdf (publisher's version ) (Open Access)BACKGROUND: Little is known about the effect of salt content of ingested fluid on intestinal transport processes. Osmosensitive genes include the serum- and glucocorticoid-inducible kinase SGK1, which is up-regulated by hyperosmolarity and cell shrinkage. SGK1 is in turn a powerful stimulator of the intestinal Na(+)/H(+) exchanger NHE3. The present study was thus performed to elucidate, whether the NaCl content of beverages influences NHE3 activity. METHODS: Mice were offered access to either plain water or isotonic saline ad libitum. NHE3 transcript levels and protein abundance in intestinal tissue were determined by confocal immunofluorescent microscopy, RT-PCR and western blotting, cytosolic pH (pHi) in intestinal cells from 2',7'-bis-(2-carboxyethyl)-5-(and-6)-carboxyfluorescein (BCECF) fluorescence and Na(+)/H(+) exchanger activity from the Na(+) dependent realkalinization following an ammonium pulse. RESULTS: Saline drinking significantly enhanced fluid intake and increased NHE3 transcript levels, NHE3 protein and Na(+)/H(+) exchanger activity. CONCLUSIONS: Salt content of ingested fluid has a profound effect on intestinal Na(+)/H(+) exchanger expression and activity

Decreased bone density and increased phosphaturia in gene-targeted mice lacking functional serum- and glucocorticoid-inducible kinase 3

Insulin and growth factors activate the phosphatidylinositide-3-kinase pathway, leading to stimulation of several kinases including serum- and glucocorticoid-inducible kinase isoform SGK3, a transport regulating kinase. Here, we explored the contribution of SGK3 to the regulation of renal tubular phosphate transport. Coexpression of SGK3 and sodium-phosphate cotransporter IIa significantly enhanced the phosphate-induced current in Xenopus oocytes. In sgk3 knockout and wild-type mice on a standard diet, fluid intake, glomerular filtration and urine flow rates, and urinary calcium ion excretion were similar. However, fractional urinary phosphate excretion was slightly but significantly larger in the knockout than in wild-type mice. Plasma calcium ion, phosphate concentration, and plasma parathyroid hormone levels were not significantly different between the two genotypes, but plasma calcitriol and fibroblast growth factor 23 concentrations were significantly lower in the knockout than in wild-type mice. Moreover, bone density was significantly lower in the knockouts than in wild-type mice. Histological analysis of the femur did not show any differences in cortical bone but there was slightly less prominent trabecular bone in sgk3 knockout mice. Thus, SGK3 has a subtle but significant role in the regulation of renal tubular phosphate transport and bone density.Kidney International advance online publication, 30 March 2011; doi:10.1038/ki.2011.67

Crystal and molecular structure of 1-epi-delphisine and nmr assignments for delphisine, 1-epi-delphisine and delphinine

The crystal and molecular structure of the norditerpenoid alkaloid 1-epi-delphisine (5), C28H43NO8, Mr 521.66, has been confirmed by as X-ray diffraction study using the SIR 88 analysis program. The alkaloid crystallizes in the space group P21 with cell parameters: a = 11.853(1)Å, b = 10.511(1)Å, c = 11.854(1)Å, β= 112.58(1), V = 1363.61(0)Å3, Z = 2, Dcalc = 1.27 g/cm3, λ (Cu Kα) = 1.54184 Å, μ(Cu Kα = 7.2 cm−1, F(000) = 564, temperature 23°C, R = 0.052, for 2907 reflections. Ring A of 1-epi-delphisine exists in a chair conformation. By comparison, delphisine which bears a C-1 α hydroxyl group, has ring A in a boat conformation stabilized by an intramolecular N----H-O hydrogen bond. Ring D of both of these alkaloids exists in a boat form. Unambiguous proton and carbon-13 nmr assignments for delphisine, 1-epi-delphisine and delphinine have been made by a detailed analysis of the DEPT, COSY, HETCOR, COLOC, DIFNOE, and selective INEPT nmr techniques