RESUMEN
Hydrocephalus is often treated with a cerebrospinal fluid shunt (CFS) for excessive amounts of cerebrospinal fluid in the brain. However, it is very difficult to distinguish whether the ventricular enlargement is due to hydrocephalus or other causes, such as brain atrophy after brain damage and surgery. The non-trivial evaluation of the consciousness level, along with a continuous drainage test of the lumbar cistern is thus clinically important before the decision for CFS is made. We studied 32 secondary mild hydrocephalus patients with different consciousness levels, who received T1 and diffusion tensor imaging magnetic resonance scans before and after lumbar cerebrospinal fluid drainage. We applied a novel machine-learning method to find the most discriminative features from the multi-modal neuroimages. Then, we built a regression model to regress the JFK Coma Recovery Scale-Revised (CRS-R) scores to quantify the level of consciousness. The experimental results showed that our method not only approximated the CRS-R scores but also tracked the temporal changes in individual patients. The regression model has high potential for the evaluation of consciousness in clinical practice.
RESUMEN
Hydrocephalus is often treated with a cerebrospinal fluid shunt (CFS) for excessive amounts of cerebrospinal fluid in the brain. However, it is very difficult to distinguish whether the ventricular enlargement is due to hydrocephalus or other causes, such as brain atrophy after brain damage and surgery. The non-trivial evaluation of the consciousness level, along with a continuous drainage test of the lumbar cistern is thus clinically important before the decision for CFS is made. We studied 32 secondary mild hydrocephalus patients with different consciousness levels, who received T1 and diffusion tensor imaging magnetic resonance scans before and after lumbar cerebrospinal fluid drainage. We applied a novel machine-learning method to find the most discriminative features from the multi-modal neuroimages. Then, we built a regression model to regress the JFK Coma Recovery Scale-Revised (CRS-R) scores to quantify the level of consciousness. The experimental results showed that our method not only approximated the CRS-R scores but also tracked the temporal changes in individual patients. The regression model has high potential for the evaluation of consciousness in clinical practice.
RESUMEN
F1-ATPase (F1) is the catalytic sector in F(o)F1-ATP synthase that is responsible for ATP production in living cells. In catalysis, its three catalytic ß-subunits undergo nucleotide occupancy-dependent and concerted open-close conformational changes that are accompanied by rotation of the γ-subunit. Bacterial and chloroplast F1 are inhibited by their own ε-subunit. In the ε-inhibited Escherichia coli F1 structure, the ε-subunit stabilizes the overall conformation (half-closed, closed, open) of the ß-subunits by inserting its C-terminal helix into the α3ß3 cavity. The structure of ε-inhibited thermophilic F1 is similar to that of E. coli F1, showing a similar conformation of the ε-subunit, but the thermophilic ε-subunit stabilizes another unique overall conformation (open, closed, open) of the ß-subunits. The ε-C-terminal helix 2 and hook are conserved between the two structures in interactions with target residues and in their positions. Rest of the ε-C-terminal domains are in quite different conformations and positions, and have different modes of interaction with targets. This region is thought to serve ε-inhibition differently. For inhibition, the ε-subunit contacts the second catches of some of the ß- and α-subunits, the N- and C-terminal helices, and some of the Rossmann fold segments. Those contacts, as a whole, lead to positioning of those ß- and α- second catches in ε-inhibition-specific positions, and prevent rotation of the γ-subunit. Some of the structural features are observed even in IF1 inhibition in mitochondrial F1.