Understanding the structural organization of organs and organisms at the cellular level is a fundamental challenge in biology. This task has been approached by reconstructing three-dimensional structure from images taken from serially sectioned tissues, which is not only labor-intensive and time-consuming but also error-prone. Recent advances in tissue clearing techniques allow visualization of cellular structures and neural networks inside of unsectioned whole tissues or the entire body. However, currently available protocols require long process times. Here, we present the rapid and highly reproducible ACT-PRESTO (active clarity technique-pressure related efficient and stable transfer of macromolecules into organs) method that clears tissues or the whole body within 1 day while preserving tissue architecture and protein-based signals derived from endogenous fluorescent proteins. Moreover, ACT-PRESTO is compatible with conventional immunolabeling methods and expedites antibody penetration into thick specimens by applying pressure. The speed and consistency of this method will allow high-content mapping and analysis of normal and pathological features in intact organs and bodies.

Tissue-clearing techniques have received great attention for volume imaging and for the potential to be applied in optical diagnosis. In principle, tissue clearing is achieved by reducing light scattering through a combination of lipid removal, size change, and matching of the refractive index (RI) between the imaging solution and the tissue. However, the contributions of these major factors in tissue clearing have not been systematically evaluated yet. In this study, we experimentally measured and mathematically calculated the contribution of these factors to the clearing of four organs (brain, liver, kidney, and lung). We found that these factors differentially influence the maximal clearing efficacy of tissues and the diffusivity of materials inside the tissue. We propose that these physical properties of organs can be utilized for the quality control (Q/C) process during tissue clearing, as well as for the monitoring of the pathological changes of tissues.

Background Both genetic and lifestyle factors play an etiologic role in colorectal cancer (CRC). Objectives We evaluated potential gene–environment interactions in CRC risk. Methods We used data from 346,297 participants in the UK Biobank cohort. Healthy lifestyle scores (HLSs) were constructed using 8 lifestyle factors, primarily according to the American Cancer Society guidelines, and were categorized into unhealthy, intermediate, and healthy groups. A polygenic risk score (PRS) was created using 95 genetic risk variants identified by genome-wide association studies of CRC and was categorized by tertile. Cox models were used to estimate the HRs and 95% CIs of CRC risk associated with the HLS and PRS. Results During a median follow-up of 5.8 y, 2066 incident cases of CRC were identified. Healthier HLSs were associated with reduced risk of CRC in a dose–response manner. The risk reduction was more apparent among those with high PRS (HRhealthy vs. unhealthy HLS1: 0.58; 95% CI: 0.43, 0.79 for men and 0.71; 0.58, 0.85 for men and women combined) than those with low PRS. Although no multiplicative interactions were identified, the HLS1 and PRS showed a significant additive interaction (P = 0.02 for all participants combined, 0.04 for men). In analyses including all participants, the adjusted CRC cumulative risk from age 40 to 75 y was 6.40% for those with high PRS/unhealthy HLS1, with a relative excess risk due to interaction of 0.58 (95% CI: 0.06, 1.10), compared with 2.09% among those with low PRS/healthy HLS1. This pattern was more apparent among those who reported not having received any bowel screening before baseline. Conclusions Although the observational nature of the study precludes proof of causality, our findings suggest that individuals with a high genetic susceptibility could benefit more substantially than those with a low genetic risk from lifestyle modification in reducing CRC risk.

This study of the Korean version of the CDRS-R provides initial promising data regarding its criterion validity, discriminant validity, internal consistency, and factor structures. These properties were significantly strong, which suggests that the Korean version of the CDRS-R is a valid and reliable instrument for the assessment of depressive symptoms in youth.

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We developed an automatic slow-wave sleep (SWS) detection algorithm that can be applied to groups of healthy subjects and patients with obstructive sleep apnea (OSA). This algorithm detected SWS based on autonomic activations derived from the heart rate variations of a single sensor. An autonomic stability, which is an SWS characteristic, was evaluated and quantified using R-R intervals from an electrocardiogram (ECG). The thresholds and the heuristic rule to determine SWS were designed based on the physiological backgrounds for sleep process and distribution across the night. The automatic algorithm was evaluated based on a fivefold cross validation using data from 21 healthy subjects and 24 patients with OSA. An epoch-by-epoch (30 s) analysis showed that the overall Cohen's kappa, accuracy, sensitivity, and specificity of our method were 0.56, 89.97%, 68.71%, and 93.75%, respectively. SWS-related information, including SWS duration (min) and percentage (%), were also calculated. A significant correlation in these parameters was found between automatic and polysomnography scorings. Compared with similar methods, the proposed algorithm convincingly discriminated SWS from non-SWS. The simple method using only R-R intervals has the potential to be utilized in mobile and wearable devices that can easily measure this information. Moreover, when combined with other sleep staging methods, the proposed method is expected to be applicable to long-term sleep monitoring at home and ambulatory environments.

Purpose: This study investigated the prevalence and correlates of problematic internet use (PIU) in a large sample of adolescents based on the type of internet service used. Materials and Methods: The study was conducted from 2008 to 2010, and 223,542 adolescents aged 12 to 18 years participated in the study. The participants responded to a self-report questionnaire including items for demographic factors, internet usage time, most used internet service and mental health. The PIU was assessed with the Internet Addiction Proneness Scale for Youth-Short Form. Results: The overall prevalence rate of PIU was 5.2%, and the prevalence rates stratified by sex were 7.7% in boys and 3.8% in girls. The distribution of most used internet services was significantly different across sexes. The most commonly used internet services were gaming (58.1%) in boys and blogging (22.1%) and messenger/chatting (20.3%) in girls. The odds ratio for PIU was significantly different according to the most used internet service; using the internet mostly for pornography compared to information searching had the highest odds ratio (4.526-fold higher). Depressive episodes, suicidal ideation, and suicidal attempts were significantly associated with higher odds ratios for PIU (1.725-, 1.747-and 1.361-fold, respectively). Conclusion: The present study identified clinically important information about PIU in adolescents. The distribution of PIU has different patterns based on sex and specific internet services. Studies of PIU with well-defined methodology and assessment tools for PIU of each specific internet service are needed.