This study investigated the effect of reactive carbonyl species (RCS)-trapping agents on the formation of protein carbonyls during depletion of brain glutathione (GSH). To this end, rat brain slices were incubated with the GSH-depletor diethyl maleate in the absence or presence of chemically different RCS scavengers (hydralazine, methoxylamine, aminoguanidine, pyridoxamine, carnosine, taurine and z-histidine hydrazide). Despite their strong reactivity towards the most common RCS, none of the scavengers tested, with the exception of hydralazine, prevented protein carbonylation. These findings suggest that the majority of protein-associated carbonyl groups in this oxidative stress paradigm do not derive from stable lipid peroxidation products like malondialdehyde (MDA), acrolein and 4-hydroxynonenal (4-HNE). This conclusion was confirmed by the observation that the amount of MDA-, acrolein- and 4-HNE-protein adducts does not increase upon GSH depletion. Additional studies revealed that the efficacy of hydralazine at preventing carbonylation was due to its ability to reduce oxidative stress, most likely by inhibiting mitochondrial production of superoxide and/or by scavenging lipid free radicals.

We focus on the problem of estimating human hand-tremor frequency from input RGB video data. Estimating tremors from video is important for non-invasive monitoring, analyzing and diagnosing patients suffering from motor-disorders such as Parkinson's disease. We consider two approaches for hand-tremor frequency estimation: (a) a Lagrangian approach where we detect the hand at every frame in the video, and estimate the tremor frequency along the trajectory; and (b) an Eulerian approach where we first localize the hand, we subsequently remove the large motion along the movement trajectory of the hand, and we use the video information over time encoded as intensity values or phase information to estimate the tremor frequency. We estimate hand tremors on a new human tremor dataset, TIM-Tremor, containing static tasks as well as a multitude of more dynamic tasks, involving larger motion of the hands. The dataset has 55 tremor patient recordings together with: associated ground truth accelerometer data from the most affected hand, RGB video data, and aligned depth data.

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