Aug
13
Tue
2013
Invited Talk: The system of PAS proteins (HIF and AhR) as an interface between environment and skin homeostasis @ Acharya Hall
Aug 13 @ 2:33 pm – 2:50 pm

andreyAndrey Panteleyev, Ph.D.
Vice Chair, Division of Molecular Biology, NBICS Centre-Kurchatov Institute, Moscow, Russia


The system of PAS proteins (HIF and AhR) as an interface between environment and skin homeostasis

Regulation of normal skin functions as well as etiology of many skin diseases are both tightly linked to the environmental impact. Nevertheless, molecular aspects of skin-environment communication and mechanisms coordinating skin response to a plurality of environmental stressors remain poorly understood.

Our studies along with the work of other groups have identified the family of PAS dimeric transcription factors as an essential sensory and regulatory component of communication between skin and the environment. This protein family comprises a number of hypoxia-induced factors (HIF-alpha proteins), aryl hydrocarbon receptor (AhR), AhR nuclear translocator (ARNT), and several proteins implicated in control of rhythmic processes (Clock, Period, and Bmal proteins). Together, various PAS proteins (and first of all ARNT – as the central dimerization partner in the family) control such pivotal aspects of cell physiology as drug/xenobiotic metabolism, hypoxic and UV light response, ROS activity, pathogen defense, overall energy balance and breathing pathways.

In his presentation Dr. Panteleyev will focus on the role of ARNT activity and local hypoxia in control of keratinocyte differentiation and cornification. His recent work revealed that ARNT negatively regulates expression of late differentiation genes through modulation of amphiregulin expression and downstream alterations in activity of EGFR pathway. All these effects are highly dependent on epigenetic mechanisms such as histone deacetylation. Characterisation of hypoxia as a key microenvironmental factor in the skin and the role of HIF pathway in control of dermal vasculature and epidermal functions is another major focus of Dr. Panteleyev’s presentation.

In general, the studies of Dr. Panteleyev’s laboratory provide an insight into the PAS-dependent maintenance of skin homeostasis and point to the potential role of these proteins in pathogenesis of environmentally-modulated skin diseases such as barrier defects, desquamation abnormalities, psoriasis, etc.

 

Invited Talk: Applying Machine learning for Automated Identification of Patient Cohorts @ Sathyam Hall
Aug 13 @ 2:40 pm – 3:05 pm

SriSairamSrisairam Achuthan, Ph.D.
Senior Scientific Programmer, Research Informatics Division, Department of Information Sciences, City of Hope, CA, USA


Applying Machine learning for Automated Identification of Patient Cohorts

Srisairam Achuthan, Mike Chang, Ajay Shah, Joyce Niland

Patient cohorts for a clinical study are typically identified based on specific selection criteria. In most cases considerable time and effort are spent in finding the most relevant criteria that could potentially lead to a successful study. For complex diseases, this process can be more difficult and error prone since relevant features may not be easily identifiable. Additionally, the information captured in clinical notes is in non-coded text format. Our goal is to discover patterns within the coded and non-coded fields and thereby reveal complex relationships between clinical characteristics across different patients that would be difficult to accomplish manually. Towards this, we have applied machine learning techniques such as artificial neural networks and decision trees to determine patients sharing similar characteristics from available medical records. For this proof of concept study, we used coded and non-coded (i.e., clinical notes) patient data from a clinical database. Coded clinical information such as diagnoses, labs, medications and demographics recorded within the database were pooled together with non-coded information from clinical notes including, smoking status, life style (active / inactive) status derived from clinical notes. The non-coded textual information was identified and interpreted using a Natural Language Processing (NLP) tool I2E from Linguamatics.

Delegate Talk: A Mobile Phone Application for Daily Physical Activity Monitoring in Chronic Obstructive Pulmonary Disease @ Amriteshwari Hall
Aug 13 @ 2:45 pm – 3:05 pm
Delegate Talk: A Mobile Phone Application for Daily Physical Activity Monitoring in Chronic Obstructive Pulmonary Disease @ Amriteshwari Hall | Vallikavu | Kerala | India

H S M Kort, J-W J Lammers, S N W Vorrink, T Troosters


Introduction
Chronic Obstructive Pulmonary Disease (COPD) is a disabling airway disease with variable extrapulmonary effects that may contribute to disease severity in individual patients (Rabe et al. 2007). The world health organization predicts that COPD will become the third leading cause of death worldwide by 2030. Patients with COPD demonstrate reduced levels of spontaneous daily physical activity (DPA) compared with healthy controls (Pitta et al. 2005). This results in a higher risk of hospital admission and shorter survival (Pitta et al. 2006). Pulmonary rehabilitation can help to improve the DPA level, however, obtained benefits decline after 1–2 years (Foglio et al. 2007).

Purpose
In order to maintain DPA in COPD patients after rehabilitation, we developed a mobile phone application. This application measures DPA as steps per day, measured by the accelerometer of the smartphone, and shows the information to the patient via the display of the mobile phone. A physiotherapist can monitor the patient via a secure website where DPA measurements are visible for all patients. Here, DPA goals can be adjusted and text messages sent.

Method
Three pilot studies were performed with healthy students and COPD patients to test the application for usability, user friendliness and reliability with questionnaires and focus groups. Subjects also wore a validated accelerometer. For the Randomized Controlled Trial (RCT) 140 COPD patients will be recruited in Dutch physiotherapy practises. They will be randomised in an intervention group that receives the smartphone for 6 months and a control group. Measurements include lungfunction, dyspnea, and exercise capacity and are held at 0, 3, 6 and 12 months.

Results and Discussion
The application was found to be useful, easy to learn and use. Subjects had no problems with health care professionals seeing information on their physical activity performance. They do find it important to be able to determine who can see the information. Correlations between the accelerometer and the measurements on DPA of the smartphone for steps per hour were 0.69 and 0.70 for pilot studies 1 (students) and 2 (COPD patients) respectively. The version of the application in pilot study 3 contained an error, which made correlations with the accelerometer unusable. The RCT study is now being executed.