The Patient Narrative and the Impositions of Implicit Biases in Health Care

The patient narrative includes the patient’s sentiments about their health condition and how this has affected their lifestyle as opposed to a list of ailments. A large portion of the patient’s diagnosis and treatment plan is rooted in the patient’s narrative. If the health care provider does not listen to the patient’s story, they may miss a vital puzzle piece that could aid them in solving the mystery. The extent to which the health care provider listens to and values the patient narrative could be clouded by implicit biases that the provider holds. Implicit biases are preferential attitudes and associations towards people, which exist subconsciously. In this study, interviews were conducted with physicians, nurses, medical students, and patients to better understand the extent to which health care providers emphasize the patient narrative and the role that implicit biases play in the doctor-patient and nurse-patient relationships. A multitude of biases were identified through the interviews, and it was established that, overall, the interviewed health care providers do not feel that listening to the patient narrative was emphasized in their medical training. Furthermore, all of the patients shared anecdotes of age bias, and they all felt that female physicians are more empathetic than male physicians. After analyzing the qualitative data collected from the interviews, it was established that more courses and training about implicit biases, emotional intelligence, and listening to the patient narrative need to be implemented in medical training

Investigation of the Genetics of Obesity through Single Nucleotide Polymorphisms of the Glucocorticoid Pathway

The stress hormone cortisol is responsible for aspects of metabolism and visceral fat formation that are hypothesized to be linked to obesity. Cortisol directly and indirectly influences metabolism by stimulating lipolysis as well as gluconeogenesis, the breakdown of fat and creation of glucose respectively. By interacting with abdominal organs such as the liver and pancreas, cortisol also increases metabolism through downstream hormones, such as glucagon and epinephrine. Cortisol intersects a variety of pathways that influence the breakdown of sugar, making it an important target for metabolic studies. This study investigates the correlation of mutations in proteins responsible for cortisol action in target tissues, individually and collectively, to clinical measurements of patients with obesity who are seeking or have already sought out bariatric surgery. DNA samples and clinical information were collected from patients of the Ellis Hospital Bariatric Care who were recruited for the study under the supervision of the Ellis Hospital Institutional Review Board. Genotyping of patient samples was done by performing allele specific-polymerase chain reactions (AS_PCR) which were then analyzed through agarose gel electrophoresis to look for single nucleotide polymorphisms (SNPs). It was found that the mutations throughout the glucocorticoid pathway are present at comparable rates in both the bariatric population and general population. Therefore, it cannot be concluded that there is an increase of mutations in the study population compared to the values for the general public found in literature. There are strong correlations between a mutation in the glucocorticoid receptor (GR) and excess body weight. This mutation causes conversion of an aspartic acid to a serine (N363S) in the protein sequence which has previously been shown to cause increased sensitivity to cortisol. As more SNPs are analyzed in combination with each other, more conclusions may be drawn between SNPs and physiological parameters of the patients. High correlations may provide evidence that select bariatric surgeries may be more effective in patients with specific genotypes. If this is the case, bariatric surgery can adopt precision medicine that caters treatment to the patient

Autonomous Soil Assessment System for Planetary Rovers

Planetary rovers face mobility hazards associated with various classes of terrains they traverse, and hence it is desirable to enable remote prediction of terrain trafficability (ability to traverse) properties. For that reason, the development of algorithms for assessing terrain type and mobility properties, as well as for coupling these data in an online learning framework, represent important capabilities for next-generation rovers. This work focuses mainly on 3-way terrain classification (classifying as one of the types: Sand, Bedrock and Gravel) as well as on the correlation of terrain types and their mobility properties in a framework that enables online learning. For terrain classification, visual descriptors are developed, which are primarily based on visual texture and are captured in form of histograms of edge filter responses at various scales and orientations. The descriptors investigated in this work are HOG (Histogram of Oriented Gradients), GIST, MR8 (Maximum Response) Textons and the classification techniques implemented here are nearest and k-nearest neighbors. Further, monochrome image intensity is used as an additional feature to further distinguish bedrock from the other terrain types. No major differences in performance are observed between the three descriptors, leading to the adoption of the HOG approach due to its lower computational complexity (over 3 orders of magnitude difference in complexity between HOG and Textons) and thus higher applicability to planetary missions. Tests demonstrate an accuracy between 70% and 93% (81% average) for the classification using the HOG descriptor, on images taken by NASA’s Mars rovers. To predict terrain trafficability ahead of the rover, exteroceptive data namely terrain type and slope, are correlated with the trafficability metrics namely slip, sinkage and roughness, in a learning framework. A queue based data structure has been implemented for the correlation, which keeps discarding the older data so as to avoid diminishing the effect of newer data samples, when there is a large amount of data. This also ensures that the rover will be able to adapt to changing terrains responses and predict the risk level (low, medium or high) accordingly. Finally, all the algorithms developed in this work were tested and verified in a field test demo at the CSA (Canadian Space Agency) mars yard. The risk metric in combination with the queue based data structure, can achieve stable predictions in consistent terrains, while also being responsive to sudden changes in terrain trafficability

Study of clinical profile of childhood extra pulmonary tuberculosis

Background: Tuberculosis is the second most common cause of death from infectious disease at the global level, being second only to AIDS. Good data on the burden of all forms of TB amongst children in India is not available; most surveys conducted have focused on pulmonary TB. The present study was designed to study clinical profile of various forms of childhood EPTB. Objective of current study was to study clinico-epidemiological profile of various forms of childhood EPTB.Methods: Retrospective analysis of clinical profile of 100 patients of childhood EPTB in the age group of 6 months to 12 years.Results: Age distribution in our study showed that 62% cases falling in the age 0-5 years and 38% cases in 5-12 years (P = 0.041) with male to female ratio of 1.9:1. 96% (P = 0.016) of the patients belonged to the lower socio-economic class (P = 0.01). The distribution of EPTB was - TBME (46%), disseminated TB (21%), pleural effusion (12%), abdominal TB (10%), TB lymphadenitis (7%), Osteoarticular (4%). 28% of the patients had mild to moderate malnutrition (PEM Grade-I,II)  and 46% (PEM Grade-III,IV) were severely malnourished. 66% of the patient were BCG vaccinated & history of  Koch’s contact were present in 28% of the all cases. In CNS tuberculosis, fever was present in 97% followed by altered sensorium & convulsion in 80%, tonic posturing in 60% & abnormal movements in 4% and in most common sign was tonic posturing in 60%, crack pot sign positive in 41%. In abdominal tuberculosis - fever (100%), anorexia (90%), weight loss (80%) abdominal pain (50%) & hepatomegaly was common finding seen in 100% of abdominal tuberculosis.Conclusion: Childhood EPTB is commonly seen in children age more than 1 year, lower socioeconomic class & in severely malnourished. CNS tuberculosis commonly present with fever, altered sensorium, convulsion, abnormal movements while abdominal TB present with fever, anorexia, weight loss & abdominal pain

Effects of histatin-1 peptide on human corneal epithelial cells.

Ocular surface and corneal epithelial wounds are common and potentially debilitating problems. Ideal treatments for these injuries would promote epithelial healing without inflammation, infection and scarring. In addition the best treatments would be cost-efficient, effective, non-toxic and easily applied. Histatin-1 peptides have been shown to be safe and effective enhancers of epithelial wound healing in other model systems. We sought to determine whether histatin-1 peptides could enhance human corneal epithelial wound healing in vitro.Histatin-1 peptides were applied to human corneal epithelial cells and compared over useful dose ranges in scratch assays using time-lapse microscopy. In addition, path finding analysis, cell spreading assays, toxicity and proliferation assays were performed to further characterize the effects of histatin-1 peptide on human corneal limbal epithelial (HCLE).Histatin-1 enhanced human corneal epithelial wound healing in typical wound healing models. There was minimal toxicity and no significant enhancement of proliferation of corneal epithelium in response to histatin-1 application. Corneal epithelial spreading and pathfinding appeared to be enhanced by the application of histatin-1 peptides.Histatin -1 peptide may enhance migration of HCLE cells and wound healing in vitro. These peptides may have benefit in corneal epithelial wounds and need to be investigated further