Waist-worn accelerometer data for the development group showing tradeoff between sensitivity and specificity.

<p>Each circle represents sensitivity (y-axis) and 1 – specificity (x-axis), calculated using ROC analysis for a curve (not shown) of a respective set of cut points. The solid circle [•] in the inset represents the selected optimal cut points (counts/min) for bedtime rest (CP₁) and activity (CP₂). The corresponding values are in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092512#pone-0092512-t002" target="_blank">Table 2</a> (bold). The solid square [▪] represents Sadeh's algorithm (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092512#pone-0092512-t003" target="_blank">Table 3</a>) and the solid triangle [▴] represents the validation set (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092512#pone-0092512-t004" target="_blank">Table 4</a>).</p

Representative data plot for one participant (17 years old male) from a 24-h stay in the room calorimeter.

<p>The solid line represents Actigraph recordings (counts/min), and the thick horizontal dash line represents average counts/hour. The insets are representative periods in which transition from activity to bedtime rest (A) and from bedtime rest to activity (B) occurred.</p

Medians for the area under curve (AUC), sensitivity, and specificity for various cut points (counts/min) tested in the development sample set using Receiver Operating Characteristic (ROC) curves for accelerometer worn a waist or wrist during a ∼24-h stay in a whole-room indirect calorimeter.

<p>Bolded values are optimal cut points for bedtime rest (CP₁) and activity (CP₂).</p>a<p>- Area under the ROC curve calculated as sensitivity multiplied by specificity before data were rounded;</p>b<p>- defined as the probability of correctly classifying bedtime rest period;</p>c<p>- defined as the probability of correctly classifying activity period.</p

Comparison of bedtime rest classification from accelerometer placed on waist or wrist calculated using Sadeh's algorithm and the decision tree with classification obtained using whole- room indirect calorimeter.

a<p>- Area under the ROC curve calculated as sensitivity multiplied by specificity before data was rounded;</p>b<p>- defined as the probability of correctly classifying bedtime rest period;</p>c<p>- defined as a probability of correctly classifying activity period;</p>d<p>- Wilcoxon signed rank test;</p>e<p>- automated computer algorithm;</p>f<p>- cut points were 20 counts/min (bedtime) and 500 counts/min (activity);</p>g<p>- cut points were 250 counts/min (bedtime) and 3000 counts/min (activity).</p

The decision tree for the classification of bedtime rest and activity accelerometer recordings.

<p>The decision tree algorithm was using various sets of cut points for waist and wrist worn accelerometers.</p

Characteristics of study participants.

<p>Values are presented as mean ± standard deviation and (range).</p>a<p>-two-sample t-test,</p>b<p>^-BMI percentile – Body Mass Index (BMI) percentile calculated from the Centers for Disease Control (CDC) BMI-for-age growth charts.</p

Comparison of bedtime rest classification from accelerometer placed on waist or wrist in the development and validation groups with classification obtained using whole- room indirect calorimeter.

a<p>– Area under the ROC curve calculated as sensitivity multiplied by specificity before data was rounded;</p>b<p>- defined as the probability of correctly classifying bedtime rest period;</p>c<p>- defined as a probability of correctly classifying activity period;</p>d<p>- Wilcoxon signed rank test;</p>e<p>- automated computer algorithm;</p>f<p>- cut points were 20 counts/min (bedtime) and 500 counts/min (activity);</p>g<p>- cut points were 250 counts/min (bedtime) and 3000 counts/min (activity).</p

Reduction-Degradable Polymeric Micelles Decorated with PArg for Improving Anticancer Drug Delivery Efficacy

In this study, five kinds of reduction-degradable polyamide amine-<i>g</i>-polyethylene glycol/polyarginine (PAA-<i>g</i>-PEG/PArg) micelles with different proportions of hydrophilic and hydrophobic segments were synthesized as novel drug delivery vehicles. Polyarginine not only acted as a hydrophilic segment but also possessed a cell-penetrating function to carry out a rapid transduction into target cells. Polyamide amine-<i>g</i>-polyethylene glycol (PAA-<i>g</i>-PEG) was prepared for comparison. The characterization and antitumor effect of the DOX-incorporated PAA-<i>g</i>-PEG/PArg cationic polymeric micelles were investigated <i>in vitro</i> and <i>in vivo</i>. The cytotoxicity experiments demonstrated that the PAA-<i>g</i>-PEG/PArg micelles have good biocompatibility. Compared with DOX-incorporated PAA-<i>g</i>-PEG micelles, the DOX-incorporated PAA-<i>g</i>-PEG/PArg micelles were more efficiently internalized into human hepatocellular carcinoma (HepG2) cells and more rapidly released DOX into the cytoplasm to inhibit cell proliferation. In the 4T1-bearing nude mouse tumor models, the DOX-incorporated PAA-<i>g</i>-PEG/PArg micelles could efficiently accumulate in the tumor site and had a longer accumulation time and more significant aggregation concentration than those of PAA-<i>g</i>-PEG micelles. Meanwhile, it excellently inhibited the solid tumor growth and extended the survival period of the tumor-bearing Balb/c mice. These results could be attributed to their appropriate nanosize and the cell-penetrating peculiarity of polyarginine as a surface layer. The PAA-<i>g</i>-PEG/PArg polymeric micelles as a safe and high efficiency drug delivery system were expected to be a promising delivery carrier that targeted hydrophobic chemotherapy drugs to tumors and significantly enhanced antitumor effects