CRIM1 is localized to the podocyte filtration slit diaphragm of the adult human kidney

Background. CRIM1 is a plasma membrane bound protein containing six cysteine-rich repeats (CRR). Through these, CRIM1 has been shown to interact with a subgroup of the TGF-β superfamily, the bone morphogenic proteins (BMP) isoforms 2, 4 and 7. The probable action is to modulate the signalling properties of these factors. CRIM1 has also been shown to regulate the release of VEGFA by podocytes during renal organogenesis. Knock-out studies in mice have shown that CRIM1 is critically involved in the development of the central nervous system, eye and kidney. Replacement of CRIM1 with a defective version leads to renal dysgenesis and perinatal death. We have analysed the distribution of CRIM1 in adult human renal tissue

Evaluation of Postsurgical Hyperalgesia and Sensitization After Open Inguinal Hernia Repair: A Useful Model for Neuropathic Pain?

Cutaneous mechanical hyperalgesia can be induced in healthy volunteers in early phase analgesic studies to model central sensitization, a key mechanism of persistent pain. However, such hyperalgesia is short-lived (a matter of hours), and is used only for assessing only single drug doses. In contrast, postsurgical peri-incisional hyperalgesia may be more persistent and hence be a more useful model for the assessment of the efficacy of new analgesics. We undertook quantitative sensory testing in 18 patients at peri-incisional and nonoperated sites before open inguinal hernia repair and up to the 24th postsurgical week. The spatial extent of punctate hyperalgesia and brush allodynia at the peri-incisional site were greatest at weeks 2 and 4, but had resolved by week 24. Heat allodynia, suggestive of local inflammation or peripheral sensitization, was not observed; instead, there were deficits in cold and heat sensory detection that persisted until week 24. The findings suggest that central sensitization contributes significantly to mechanical hyperalgesia at the peri-incisional site. The prolonged duration of hyperalgesia would be advantageous as a pain model, but there was considerable variability of mechanical hyperalgesia in the cohort; the challenges of recruitment may limit its use to small, early phase analgesic studies. PERSPECTIVE: Peri-incisional mechanical hyperalgesia persists for ≥4 weeks after open inguinal hernia repair and reflects central sensitization; this may have usefulness as a model of chronic pain to assess the potential of antineuropathic analgesics.Unrestricted educational grant from GlaxoSmithKline U

Disruption prediction with artificial intelligence techniques in tokamak plasmas

In nuclear fusion reactors, plasmas are heated to very high temperatures of more than 100 million kelvin and, in so-called tokamaks, they are confined by magnetic fields in the shape of a torus. Light nuclei, such as deuterium and tritium, undergo a fusion reaction that releases energy, making fusion a promising option for a sustainable and clean energy source. Tokamak plasmas, however, are prone to disruptions as a result of a sudden collapse of the system terminating the fusion reactions. As disruptions lead to an abrupt loss of confinement, they can cause irreversible damage to present-day fusion devices and are expected to have a more devastating effect in future devices. Disruptions expected in the next-generation tokamak, ITER, for example, could cause electromagnetic forces larger than the weight of an Airbus A380. Furthermore, the thermal loads in such an event could exceed the melting threshold of the most resistant state-of-the-art materials by more than an order of magnitude. To prevent disruptions or at least mitigate their detrimental effects, empirical models obtained with artificial intelligence methods, of which an overview is given here, are commonly employed to predict their occurrence—and ideally give enough time to introduce counteracting measures

Global scaling of the heat transport in fusion plasmas

A global heat flux model based on a fractional derivative of plasma pressure is proposed for the heat transport in fusion plasmas. The degree of the fractional derivative of the heat flux, α, is defined through the power balance analysis of the steady state. The model was used to obtain the experimental values of α for a large database of the Joint European Torus (JET) carbon-wall as well as ITER like-wall plasmas. The fractional degrees of the electron heat flux are found to be α<2, for all the selected pulses in the database, suggesting a deviation from the diffusive paradigm. Moreover, the results show that as the volume integrated input power is increased, the fractional degree of the electron heat flux converges to α∼0.8, indicating a global scaling between the net heating and the pressure profile in the high-power JET plasmas. The model is expected to provide insight into the proper kinetic description for the fusion plasmas and improve the accuracy of the heat transport predictions

Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model

The RAPTOR code is a control-oriented core plasma profile simulator with various applications in control design and verification, discharge optimization and real-time plasma simulation. To date, RAPTOR was capable of simulating the evolution of poloidal flux and electron temperature using empirical transport models, and required the user to input assumptions on the other profiles and plasma parameters. We present an extension of the code to simulate the temperature evolution of both ions and electrons, as well as the particle density transport. A proof-of-principle neural-network emulation of the quasilinear gyrokinetic QuaLiKiz transport model is coupled to RAPTOR for the calculation of first-principle-based heat and particle turbulent transport. These extended capabilities are demonstrated in a simulation of a JET discharge. The multi-channel simulation requires ∼0.2 s to simulate 1 second of a JET plasma, corresponding to ∼20 energy confinement times, while predicting experimental profiles within the limits of the transport model. The transport model requires no external inputs except for the boundary condition at the top of the H-mode pedestal. This marks the first time that simultaneous, accurate predictions of Te, Tiand nehave been obtained using a first-principle-based transport code that can run in faster-than-real-time for present-day tokamaks

Runaway electron beam control

Post-disruption runaway electron (RE) beams in tokamaks with large current can cause deep melting of the vessel and are one of the major concerns for ITER operations. Consequently, a considerable effort is provided by the scientific community in order to test RE mitigation strategies. We present an overview of the results obtained at FTU and TCV controlling the current and position of RE beams to improve safety and repeatability of mitigation studies such as massive gas (MGI) and shattered pellet injections (SPI). We show that the proposed RE beam controller (REB-C) implemented at FTU and TCV is effective and that current reduction of the beam can be performed via the central solenoid reducing the energy of REs, providing an alternative/parallel mitigation strategy to MGI/SPI. Experimental results show that, meanwhile deuterium pellets injected on a fully formed RE beam are ablated but do not improve RE energy dissipation rate, heavy metals injected by a laser blow off system on low-density flat-top discharges with a high level of RE seeding seem to induce disruptions expelling REs. Instabilities during the RE beam plateau phase have shown to enhance losses of REs, expelled from the beam core. Then, with the aim of triggering instabilities to increase RE losses, an oscillating loop voltage has been tested on RE beam plateau phase at TCV revealing, for the first time, what seems to be a full conversion from runaway to ohmic current. We finally report progresses in the design of control strategies at JET in view of the incoming SPI mitigation experiments