Energy harvesting from the beating heart by a mass imbalance oscillation generator

Energy-harvesting devices attract wide interest as power supplies of today's medical implants. Their long lifetime will spare patients from repeated surgical interventions. They also offer the opportunity to further miniaturize existing implants such as pacemakers, defibrillators or recorders of bio signals. A mass imbalance oscillation generator, which consists of a clockwork from a commercially available automatic wrist watch, was used as energy harvesting device to convert the kinetic energy from the cardiac wall motion to electrical energy. An MRI-based motion analysis of the left ventricle revealed basal regions to be energetically most favorable for the rotating unbalance of our harvester. A mathematical model was developed as a tool for optimizing the device's configuration. The model was validated by an in vitro experiment where an arm robot accelerated the harvesting device by reproducing the cardiac motion. Furthermore, in an in vivo experiment, the device was affixed onto a sheep heart for 1 h. The generated power in both experiments-in vitro (30 μW) and in vivo (16.7 μW)-is sufficient to power modern pacemakers.

Modelling and Validation of a Mass Imbalance Oscillation Generator to Harvest Heart Motion Energy

An autonomous energy source within a human body is of key importance in the development of medical implants. This work deals with the modelling and the validation of an energy harvesting device which converts the myocardial contractions into electrical energy. The mechanism consists of a clockwork from a commercially available wrist watch. We developed a physical model which is able to predict the total amount of energy generated when applying an external excitation. For the validation of the model, a custom-made hexapod robot was used to accelerate the harvesting device along a given trajectory. We applied forward kinematics to determine the actual motion experienced by the harvesting device. The motion provides translational as well as rotational motion information for accurate simulations in three-dimensional space. The physical model could be successfully validated.

Melting of Northern Greenland during the last interglaciation

Using simulated climate data from the comprehensive coupled climate model IPSL CM4, we simulate the Greenland ice sheet (GrIS) during the Eemian interglaciation with the three-dimensional ice sheet model SICOPOLIS. The Eemian is a period 126 000 yr before present (126 ka) with Arctic temperatures comparable to projections for the end of this century. In our simulation, the northeastern part of the GrIS is unstable and retreats significantly, despite moderate melt rates. This result is found to be robust to perturbations within a wide parameter space of key parameters of the ice sheet model, the choice of initial ice temperature, and has been reproduced with climate forcing from a second coupled climate model, the CCSM3. It is shown that the northeast GrIS is the most vulnerable. Even a small increase in melt removes many years of ice accumulation, giving a large mass imbalance and triggering the strong ice-elevation feedback. Unlike the south and west, melting in the northeast is not compensated by high accumulation. The analogy with modern warming suggests that in coming decades, positive feedbacks could increase the rate of mass loss of the northeastern GrIS, exceeding the recent observed thinning rates in the south.

A 600 kb deletion syndrome at 16p11.2 leads to energy imbalance and neuropsychiatric disorders

BACKGROUND: The recurrent ~600 kb 16p11.2 BP4-BP5 deletion is among the most frequent known genetic aetiologies of autism spectrum disorder (ASD) and related neurodevelopmental disorders. OBJECTIVE: To define the medical, neuropsychological, and behavioural phenotypes in carriers of this deletion. METHODS: We collected clinical data on 285 deletion carriers and performed detailed evaluations on 72 carriers and 68 intrafamilial non-carrier controls. RESULTS: When compared to intrafamilial controls, full scale intelligence quotient (FSIQ) is two standard deviations lower in carriers, and there is no difference between carriers referred for neurodevelopmental disorders and carriers identified through cascade family testing. Verbal IQ (mean 74) is lower than non-verbal IQ (mean 83) and a majority of carriers require speech therapy. Over 80% of individuals exhibit psychiatric disorders including ASD, which is present in 15% of the paediatric carriers. Increase in head circumference (HC) during infancy is similar to the HC and brain growth patterns observed in idiopathic ASD. Obesity, a major comorbidity present in 50% of the carriers by the age of 7 years, does not correlate with FSIQ or any behavioural trait. Seizures are present in 24% of carriers and occur independently of other symptoms. Malformations are infrequently found, confirming only a few of the previously reported associations. CONCLUSIONS: The 16p11.2 deletion impacts in a quantitative and independent manner FSIQ, behaviour and body mass index, possibly through direct influences on neural circuitry. Although non-specific, these features are clinically significant and reproducible. Lastly, this study demonstrates the necessity of studying large patient cohorts ascertained through multiple methods to characterise the clinical consequences of rare variants involved in common diseases.