Aug
12
Mon
2013
Invited Talk: Osteoarthritis: diagnosis, treatment and challenges @ Acharya Hall
Aug 12 @ 11:42 am – 12:07 pm

hideakiHideaki Nagase, Ph.D.
Kennedy Institute of Rheumatology-Centre for Degenerative Diseases, University of Oxford, UK


Osteoarthritis: diagnosis, treatment and challenges

Hideaki Nagase1, Ngee Han Lim1, George Bou-Gharios1, Ernst Meinjohanns2  and Morten Meldal3

  1. Kennedy Institute of Rheumatology, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, London, W6 8LH  UK
  2. Carlsberg Laboratory, Copenhagen, Denmark,
  3. Nano-Science Center, Department of Chemistry, University of Copenhagen, Denmark

Osteoarthritis (OA) is the most prevalent age-related degenerative joint disease. With the expanding ageing population, it imposes a major socio-economic burden on society.  A key feature of OA is a gradual loss of articular cartilage and deformation of bone, resulting in the impairment of joint function. Currently, there is no effective disease-modifying treatment except joint replacement surgery. There are many possible causes of cartilage loss (e.g. mechanical load, injury, reactive oxygen species, aging, etc.) and etiological factors (obesity, genetics), but the degradation of cartilage is primarily caused by elevated levels of active metalloproteinases.  It is therefore attractive to consider proteinase inhibitors as potential therapeutics. However, there are several hurdles to overcome, namely early diagnosis and continuous monitoring of the efficacy of inhibitor therapeutics. We are therefore aiming at developing non-invasive probes to detect cartilage degrading metalloproteinase activities.

We have designed in vivo imaging probes to detect MMP-13 (collagenase 3) activity that participates in OA by degrade cartilage collagen II and MMP-12 (macrophage elastase) activity involved in inflammatory arthritis. These activity-based probes consist of a peptide that is selectively cleaved by the target proteinase, a near-infrared fluorophore and a quencher. The probe’s signal multiplies upon proteolysis.  They were first used to follow the respective enzyme activity in vivo in the mouse model of collagen-induced arthritis and we found MMP-12 activity probe (MMP12AP) activation peaked at 5 days after onset of the disease, whereas MMP13AP activation was observed at 10-15 days. The in vivo activation of these probes was inhibited by specific low molecule inhibitors.  We proceeded to test both probes in the mouse model of OA induced by the surgical destabilization of medial meniscus of the knee joints.  In this model, degradation of knee cartilage is first detected histologically 6 weeks after surgery with significant erosion detectable at 8 weeks. Little activation of MMP12AP was detected, which was expected, as macrophage migration is not obvious in OA. MMP13AP, on the other hand, was significantly activated in the operated knee at 6 weeks compared with the non-operated contralateral knee, but there were no significant differences between the operated and sham-operated knees.  At 8 weeks, however, the signals in the operated knees were significantly higher than both the contralateral and sham-operated controls. Activation of aggrecanases and MMP-13 are observed before structural changes of cartilage. We are therefore currently improving the MMP-13 probe for earlier detection by attaching it to polymers that are retained in  cartilage.

 

Plenary Talk: Realistic modeling-new insight into the functions of the cerebellar network @ Amriteshwari Hall
Aug 12 @ 1:37 pm – 2:24 pm

egidioEgidio D’Angelo, MD, Ph.D.
Full Professor of Physiology & Director, Brain Connectivity Center, University of Pavia, Italy


Realistic modeling: new insight into the functions of the cerebellar network

Realistic modeling is an approach based on the careful reconstruction of neurons synapses starting from biological details at the molecular and cellular level. This technique, combined with the connection topologies derived from histological measurements, allows the reconstruction of precise neuronal networks. Finally, the advent of specific software platforms (PYTHON-NEURON) and of super-computers allows large-scale network simulation to be performed in reasonable time. This approach inverts the logics of older theoretical models, which anticipated an intuition on how the network might work.  In realistic modeling, network properties “emerge” from the numerous biological properties embedded into the model.

This approach is illustrated here through an outstanding application of realistic modeling to the cerebellar cortex network. The neurons (over 105) are reproduced at a high level of detail generating non-linear network effects like population oscillations and resonance, phase-reset, bursting, rebounds, short-term and long-term plasticity, spatiotemporal redistrbution of input patterns. The model is currently being used in the context of he HUMAN BRAIN PROJECT to investigate the cerebellar network function.

Correspondence should be addressed to

Dr. EgidioD’Angelo,
Laboratory of Neurophysiology
Via Forlanini 6, 27100 Pavia, Italy
Phone: 0039 (0) 382 987606
Fax: 0039 (0) 382 987527
dangelo@unipv.it

Acknowledgments

This work was supported by grants from European Union to ED (CEREBNET FP7-ITN238686, REALNET FP7-ICT270434) and by grants from the Italian Ministry of Health to ED (RF-2009-1475845).

Egidio

Aug
13
Tue
2013
Invited Talk: New paths for treatment of complex diseases: target combinatorial drug therapy @ Acharya Hall
Aug 13 @ 5:06 pm – 5:27 pm

bodoBodo 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?