Syntheses of fused pyrroloheterocycles, isatins, approach towards the indole fragment of nosiheptide and a base-mediated formation of 3-hydroxycarbazoles

The nitro group has been and still is one of the few functional groups widely studied in synthetic organic chemistry. The reactivity of the nitro group has had important applications in the syntheses of many complex organic molecules, either through its assistance in the formation of new carbon-carbon bonds or in the formation of carbon-heteroatom bonds. Of late, the nitro group has become an important source of nitrogen in organic molecules, thus spawning the syntheses of a range of nitrogen heterocycles.;This dissertation is one such work, wherein the reactivity of the nitro group has been exploited with respect to the syntheses of nitrogen heterocycles. The palladium-catalyzed reductive N-heteroannulation reaction discovered in our laboratories a decade ago, has been utilized to synthesize a group of fused pyrroloheterocycles from the corresponding nitro-alkenylarenes. Also, these annulation conditions, when applied to 1-(2-haloethynyl)-2-nitrobenzenes, led to the formation of isatins. The isolation of a few stable 2-haloisatogens en route to the isatins is an important aspect in this conversion.;In addition, the possibility of executing an intramolecular nucleophillic attack on 3-(2-nitrophenyl)-2-cyclohexenone derivatives to afford hydroxy-carbazoles was investigated. A short synthetic approach to a model indole fragment of the natural product nosiheptide was also designed and attempted

Therapeutic potential of enoxaparin in lichen planus: Exploring reasons for inconsistent reports

Lichen planus (LP) is an uncommon mucocutaneous inflammatory condition, that is immunologically mediated, typically pruritic and often recurs. The currently advocated therapies are either not highly effective or associated with severe side effects. Enoxaparin, a widely used anticoagulant, is composed of both anticoagulant and non-anticoagulant fragments. Enoxaparin is reported to have anti-inflammatory properties and it was found to be effective in LP. However, the results from clinical studies have varied substantially and, therefore, the clinical role of enoxaparin in LP remains uncertain. This review focuses on potential reasons for the reported inconsistent outcomes, as well as proposing solutions; these include identifying batch-to-batch inconsistency in the composition of enoxaparin. The potential therapeutic value of enoxaparin in LP must be explored using well-designed clinical trials, combined with experimental studies that focus on identifying the anti-inflammatory fragments of enoxaparin and elucidating the mechanism of action of these non-anticoagulant fragments

Burning Mouth Syndrome Questionnaire

Thesis (Master's)--University of Washington, 2013Burning mouth syndrome (BMS) is considered to be a chronic neuropathic condition in the mouth, presenting with burning symptoms affecting the tip and lateral borders of anterior 2/3rds of the tongue, followed by anterior hard palate and labial mucosa. There are other neuropathic conditions in the mouth hat can have similar pathophysiological mechanism and clinical presentation as BMS, these are atypical odontalgia (AO), neuralgias and trigeminal neuropathic pain. However, there are no diagnostic tools available to differentiate there different neuropathic conditions in the mouth. So, the main objective of this study was to develop a questionnaire, which can be used as a screening tool, to help identify and differentiate BMS from the other oral neuropathies. So, we included 2 grops of human subjects: Group1 - patients with a diagnosis of BMS(either primary or secondary); Group2 - patients with a diagnosis of other neuropathic pain conditions in the mouth. We developed a questionnaire with 12questions. It was given to all the participants after the written informed consent was obtained. The responses of the participants to the questions were assessed using descriptive and chi-square analyses, to look for the differences between groups. We found that the majority of patients in Gr1 complained of having both the pain and burning in their mouth at the time of their visit; no known identifiable etiology at the time of onset compared to a known dental treatment at the time of onset of symptoms in Gr2; eating and chewing made the symptoms better in Gr1 whereas they made the symptoms worse in Gr2; salt and acidic foods made the symptoms worse in Gr1 whereas they had no effect on the symptoms in Gr2; dental treatment made the symptoms worse in Gr2 whereas it had no effect on the symptoms in Gr1; Gr1 patients also complained of feeling of dry mouth whereas this was not observed in Gr2 patients. Though there were no significant changes in the sense of taste, but overall Gr1 reported a decrease in the taste whereas Gr2 reported a mix of decrease and increase in taste. We did not assess the changes in saliva, taste and smell changes objectively, only the subjective evaluations were performed

A New Randomized Binary Prior Model for Hydraulic Tomography in Fractured Aquifers

We present a novel pilot-point-based hydraulic tomography (HT) inversion procedure to delineate preferential flow paths and estimate hydraulic properties in a fractured aquifer. Our procedure considers a binary prior model developed using a randomized algorithm. The randomized algorithm involves discretizing the domain into grid cells, assigning a binary label to each cell, traversing the grid randomly, and choosing the optimal grid configuration cell-by-cell. This binary prior model is used to guide the placement of pilot points and to constrain aquifer parameters during pilot-point-based HT inversion. A two-dimensional fractured granite rock block was considered to test our methodology under controlled laboratory conditions. Multiple pumping tests were conducted at selected ports and the pressure responses were monitored. The pumping datasets thus obtained were preprocessed using median filters to remove random noise, and then analyzed using the proposed procedure. The proposed binary prior algorithm was implemented in C++ by supplying the forward groundwater model, HydroGeoSphere (HGS). Pilot-point-assisted HT inversion was performed using the parameter-estimation tool, coupled to HGS. The resulting parameter distributions were assessed by: (1) a visual comparison of the K- and Ss-tomograms with the known topology of the fractures and (2) comparing model predictions with measurements made at two validation ports that were not used in calibration. The performance assessment revealed that HT with the proposed randomized binary prior could be used to recover fracture-connectivity and to predict drawdowns in fractured aquifers with reasonable accuracy, when compared to a conventional pilot-point inversion scheme

Evaluation of aquifer characterization methods using sandbox experiments and numerical studies

In this study, We evaluated the effectiveness of the Hydraulic Tomography combining with Electrical Resistivity Tomography using an inversion technique to estimate the hydraulic and storage properties of a heterogeneous aquifer system. The resistivity tomogram obtained from the ERT inversion was used to distribute the pilot points around the heterogeneity which cross-hole in the subsurface. Also, it was used to constrain the values of hydraulic parameters during HT inversion. The groundwater flow model numerical studies were performed using GMS interface and Modflow-2000 compiler for the forward modeling and Regularized Parameter Estimation algorithm was used for the inversion technique for representing the spatial property variation. We created two aquifer realizations synthetically in which a typical layered system which mostly found in alluvial soils and an embedded system, a representative of weathered granitic aquifers. In both cases, the point estimates were estimated and obtained the spatial distribution of parameters using geostatistical interpolation, which is utilized to perform zones based regularisation. The HT was performed in both the aquifer systems and used the vast time-drawdown data sets in the inversion. The regularized inversion was performed using pilot points. The regularization technique is a two-part optimization technique in which both the data misfit and the structure of the model was preserved. The inversion was performed using three methods in which the first represents the uniform distribution of the pilot points; the second represents the kriging based distribution of pilot points, and the third represents ERT based distribution of pilot points. Independent pumping tests were used to evaluate the performance of the inversion models and the efficiency of the models was statistically analyzed using the model to measurement discrepancies in drawdowns. Our results conclude that using ERT as a priori to HT inversion guiding the pilot points can improve the parameter estimation process and that was represented by using R-Square, RMSE, and NSE efficiency coefficients

Sequential downscaling of GRACE products to map groundwater level changes in Krishna River basin

We propose a deep learning model: long short-term memory (LSTM) networks to spatially downscale Global Recovery and Climate Experiment (GRACE)-derived terrestrial water storage anomalies (TWSA) with an objective to map groundwater level anomalies (GWLA) at 0.25 degrees resolution for basin-scale applications. Monthly TWSA from global spherical harmonic (GSH) and global mascons (GM) during 2002 to 2017 were obtained at 1 degrees scales for the Krishna River. Eleven hydro-climatic variables were considered to observe their dependence on TWSA and further reduced to three principal components. The LSTM's recurrent neural networks, with a 12-month lag to control flow of information in the memory units, were applied to downscale TWSA. At basin scale, downscaled GWLA from the two GRACE solutions have reasonably captured the observed trends (r > 0.6); however, GSH has underestimated the peaks (BIAS = 7.83 cm). The strong signal amplitude resulting from reduced leakage made GM a better choice over GSH in downscaling TWSA, particularly for the land-ocean mixed pixels (r(GM) = 0.74, r(GSH) = 0.62)

Application of random forest and multi-linear regression methods in downscaling GRACE derived groundwater storage changes

The advent of Gravity Recovery and Climate Experiment (GRACE) has opened the doors for remote monitoring of gravitational changes and its derivatives across the globe, but received less attention due to poor spatial and temporal representation. Statistical models of varying complexity are commonly employed to downscale the GRACE datasets for use with local to regional applications. This study presents the application of two commonly employed machine learning models, multi-linear regression (MLR) and random forest (RF), in spatially downscaling (from 1° to 0.25°) the GRACE-derived terrestrial water storage anomalies (TWSA) by establishing a correlation with various land surface and hydroclimatic variables. The downscaled TWSA was further converted into groundwater storage anomalies. Applicability of the proposed methods was tested on four contrasting hydrogeological basins of India. For each basin, the significant predictor variables were considered to establish the relations. Seasonal groundwater levels observed in 236 wells during 2006–2015 were used for method validation and accuracy assessment. We observed a close match between GRACE-derived groundwater levels and the measurements for three of the four basins (r = 0.40–0.92, Root mean square error (RMSE) = 3.6–10.5 cm). Our results indicate that the predictor variables to downscale TWSA should be considered cautiously based on the hydrogeological, topographical, and meteorological characteristics of the basin