Upinder S. Bhalla, Ph.D.
Professor & Dean, NCBS, Bengaluru, India
Watching the network change during the formation of associative memory
The process of learning is measured through behavioural changes, but it is of enormous interest to understand its cellular and network basis. We used 2-photon imaging of hippocampal CA1 pyramidal neuron activity in mice to monitor such changes during the acquisition of a trace conditioning task. One of the questions in such learning is how the network retains a trace of a brief conditioned stimulus (a sound), until the arrival of a delayed unconditioned stimulus (a puff of air to the eye). During learning, the mice learn to blink when the tone is presented, well before the arrival of the air puff.
The mice learnt this task in 20-50 trials. We observed that in this time-frame the cells in the network changed the time of their peak activity, such that their firing times tiled the interval between sound and air puff. Thus the cells seem to form a relay of activity. We also observed an evolution in functional connectivity in the network, as measured by groupings of correlated cells. These groupings were stable till the learning protocol commenced, and then changed. Thus we have been able to observe two aspects of network learning: changes in activity (relay firing), and changes in connectivity (correlation groups).
Aditya Murthy, Ph.D.
Associate Professor, Centre For Neuroscience, Indian Institute of Science, Bangalore, India
Since Karl Lashley’s seminal work on the formulation of serial order, numerous models assume simultaneous representation of competitive elements of a sequence, to account for serial order effects in different types of behavior like typing, speech, etc. Such models follow two basic assumptions: (1) more than one plan representation can be simultaneously active in a planning layer; (2) the most active plan is chosen in another layer called the competitive choice layer. Using the oculomotor system I will describe behavioral and neurophysiological experiments that tests the two critical predictions of such queuing models, providing evidence that basal ganglia in monkeys and humans instantiate a form of queuing that transforms parallel movement representations into more serial representations, allowing for the expression of sequential saccadic eye movements.
Nader Pourmand, Ph.D.
Director, UCSC Genome Technology Center,University of California, Santa Cruz
Biosensor and Single Cell Manipulation using Nanopipettes
Approaching sub-cellular biological problems from an engineering perspective begs for the incorporation of electronic readouts. With their high sensitivity and low invasiveness, nanotechnology-based tools hold great promise for biochemical sensing and single-cell manipulation. During my talk I will discuss the incorporation of electrical measurements into nanopipette technology and present results showing the rapid and reversible response of these subcellular sensors to different analytes such as antigens, ions and carbohydrates. In addition, I will present the development of a single-cell manipulation platform that uses a nanopipette in a scanning ion-conductive microscopy technique. We use this newly developed technology to position the nanopipette with nanoscale precision, and to inject and/or aspirate a minute amount of material to and from individual cells or organelle without comprising cell viability. Furthermore, if time permits, I will show our strategy for a new, single-cell DNA/ RNA sequencing technology that will potentially use nanopipette technology to analyze the minute amount of aspirated cellular material.
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.
Bodo Eickhoff, Ph.D.
Senior Vice-President, Head of Sales and Marketing for Roche Applied Science, Germany
New paths for treatment of complex diseases: target combinatorial drug therapy
Several types of diseases show a complex pathogenesis and require targeted as well as combinatorial drug treatment. A classical example, Tuberculosis, was thought for decades to be managable by triple therapy, however now requiring new therapeutic approaches due to multi drug resistant strains. HIV and AIDS can only be kept under control by combinations of specific, virus-protein targeted drugs, requiring constant monitoring of resistance patterns and modulation of drug combinations during life-long therapy. As a third example, Cancer in all its different variations, requires detailled molecular understanding to enable targeted therapy. New technologies provide more and in depths molecular insights into pathomechanisms and resulting treatment options. However, is there an alternative way to approach complex diseases by holistic models? Can restoring of apoptosis-capabilities of transformed cells be an example of such an alternative path? How do we in future adress major unresolved topics like increasing drug resistance in bacterial infections, lack of anti-viral drugs, treatment of parasite diseases like Malaria, and newly emerging infectious diseases in research and fast translation of these results into diagnosis and treatment?
Akhilesh Pandey, Ph.D.
Professor, Johns Hopkins University School of Medicine, Baltimore, USA
A draft map of the human proteome
We have generated a draft map of the human proteome through a systematic and comprehensive analysis of normal human adult tissues, fetal tissues and hematopoietic cells as an India-US initiative. This unique dataset was generated from 30 histologically normal adult tissues, fetal tissues and purified primary hematopoietic cells that were analyzed at high resolution in the MS mode and by HCD fragmentation in the MS/MS mode on LTQ-Orbitrap Velos/Elite mass spectrometers. This dataset was searched against a 6-frame translation of the human genome and RNA-Seq transcripts in addition to standard protein databases. In addition to confirming a large majority (>16,000) of the annotated protein-coding genes in humans, we obtained novel information at multiple levels: novel protein-coding genes, unannotated exons, novel splice sites, proof of translation of pseudogenes (i.e. genes incorrectly annotated as pseudogenes), fused genes, SNPs encoded in proteins and novel N-termini to name a few. Many proteins identified in this study were identified by proteomic methods for the first time (e.g. hypothetical proteins or proteins annotated based solely on their chromosomal location). We have generated a catalog of proteins that show a more tissue-restricted pattern of expression, which should serve as the basis for pursuing biomarkers for diseases pertaining to specific organs. This study also provides one of the largest sets of proteotypic peptides for use in developing MRM assays for human proteins. Identification of several novel protein-coding regions in the human genome underscores the importance of systematic characterization of the human proteome and accurate annotation of protein-coding genes. This comprehensive dataset will complement other global HUPO initiatives using antibody-based as well as MRM mass spectrometry-based strategies. Finally, we believe that this dataset will become a reference set for use as a spectral library as well as for interesting interrogations pertaining to biomedical as well as bioinformatics questions.
