Age Differences in Stress and Coping: Problem-Focused Strategies Mediate the Relationship between Age and Positive Affect

The present study examined the different types of stressors experienced by adults of different ages, their coping strategies, and positive/negative affect. A mediation hypothesis of coping strategies was tested on the relationships between age and positive/negative affect. One-hundred and ninety-six community-dwelling adults (age range 18-89 years old) reported the most stressful situation they experienced in the past month and coping strategies. Levels of positive and negative affect in the past month were also measured. Content analysis revealed age differences in different types of stressors adults reported. Three types of coping strategies were found: problem-focused, positive emotion-focused, and negative emotion-focused coping. Older adults were less likely than younger adults to use problem-focused coping and reported lower levels of positive affect. Path analysis supported the mediation hypothesis, showing that problem-focused coping mediated the relationship between age and positive affect. Implications are discussed on the importance of promoting problem-focused coping among older adults

Estimation of Recurrence of Colorectal Adenomas with Dependent Censoring Using Weighted Logistic Regression

In colorectal polyp prevention trials, estimation of the rate of recurrence of adenomas at the end of the trial may be complicated by dependent censoring, that is, time to follow-up colonoscopy and dropout may be dependent on time to recurrence. Assuming that the auxiliary variables capture the dependence between recurrence and censoring times, we propose to fit two working models with the auxiliary variables as covariates to define risk groups and then extend an existing weighted logistic regression method for independent censoring to each risk group to accommodate potential dependent censoring. In a simulation study, we show that the proposed method results in both a gain in efficiency and reduction in bias for estimating the recurrence rate. We illustrate the methodology by analyzing a recurrent adenoma dataset from a colorectal polyp prevention trial

Real-time tracking and in vivo visualization of β-galactosidase activity in colorectal tumor with a ratiometric near-infrared fluorescent probe

Development of “smart” noninvasive bioimaging probes for trapping specific enzyme activities is highly desirable for cancer therapy in vivo. Given that β-galactosidase (β-gal) is an important biomarker for cell senescence and primary ovarian cancers, we design an enzyme-activatable ratiometric near-infrared (NIR) probe (DCM-βgal) for the real-time fluorescent quantification and trapping of β-gal activity in vivo and in situ. DCM-βgal manifests significantly ratiometric and turn-on NIR fluorescent signals simultaneously in response to β-gal concentration, which makes it favorable for monitoring dynamic β-gal activity in vivo with self-calibration in fluorescent mode. We exemplify DCM-βgal for the ratiometric tracking of endogenously overexpressed β-gal distribution in living 293T cells via the <i>lacZ</i> gene transfection method and OVCAR-3 cells, and further realize real-time in vivo bioimaging of β-gal activity in colorectal tumor-bearing nude mice. Advantages of our system include light-up ratiometric NIR fluorescence with large Stokes shift, high photostability, and pH independency under the physiological range, allowing for the in vivo real-time evaluation of β-gal activity at the tumor site with high-resolution three-dimensional bioimaging for the first time. Our work provides a potential tool for in vivo real-time tracking enzyme activity in preclinical applications

A Complete Developmental Sequence of a Drosophila Neuronal Lineage as Revealed by Twin-Spot MARCM

Labeling every neuron in a lineage in the fruit fly olfactory system reveals that every cell is born with a pre-determined cell fate that is invariant and dependent upon neuron birth orde

Transcriptional Profiling of the Dose Response: A More Powerful Approach for Characterizing Drug Activities

The dose response curve is the gold standard for measuring the effect of a drug treatment, but is rarely used in genomic scale transcriptional profiling due to perceived obstacles of cost and analysis. One barrier to examining transcriptional dose responses is that existing methods for microarray data analysis can identify patterns, but provide no quantitative pharmacological information. We developed analytical methods that identify transcripts responsive to dose, calculate classical pharmacological parameters such as the EC50, and enable an in-depth analysis of coordinated dose-dependent treatment effects. The approach was applied to a transcriptional profiling study that evaluated four kinase inhibitors (imatinib, nilotinib, dasatinib and PD0325901) across a six-logarithm dose range, using 12 arrays per compound. The transcript responses proved a powerful means to characterize and compare the compounds: the distribution of EC50 values for the transcriptome was linked to specific targets, dose-dependent effects on cellular processes were identified using automated pathway analysis, and a connection was seen between EC50s in standard cellular assays and transcriptional EC50s. Our approach greatly enriches the information that can be obtained from standard transcriptional profiling technology. Moreover, these methods are automated, robust to non-optimized assays, and could be applied to other sources of quantitative data