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Realistic two-dimensional (2D) and three-dimensional (3D) applications for anatomical studies are being developed from true-colored sectioned images. We generated advanced-sectioned images of the entire male body and verified that anatomical structures of both normal and abnormal shapes could be visualized in them. The cadaver was serially sectioned at constant intervals using a cryomacrotome. The sectioned surfaces were photographed using a digital camera to generate horizontal advanced-sectioned images in which normal and abnormal structures were classified. Advanced-sectioned images of the entire male body were generated. The image resolution was 3.3  3.3 fold better than that of the first sectioned images obtained in 2002. In the advancedsectioned images, normal and abnormal structures ranging from microscopic (≥0.06 mm  0.06 mm; pixel size) to macroscopic (≤473.1 mm  202 mm; body size) could be identified. Furthermore, the real shapes and actual sites of lung cancer and lymph node enlargement were ascertained in them. Such images will be useful because of their true color and high resolution in digital 2D and 3D applications for gross anatomy and clinical anatomy. In future, we plan to generate new advanced-sectioned images of abnormal cadavers with different diseases for clinical anatomy studies.

Knowledge of the lung segment system is essential for understanding human anatomy and has great clinical relevance. The arrangement of 11 segments, including the S* or subsuperior segment, and its individual variations, are considered to be the same in fetal and adult lungs. The present study assessed the topographical anatomy of lower segmental and subsegmental bronchi by computer‐assisted three‐dimensional imaging of serial sagittal sections of both lungs of 22 embryos and fetuses of gestational age 6–7 weeks (crown–rump length 15.0–28.5 mm). Long inferior courses of B8b (basal) and B10c (medial) were observed in sagittal sections of both lungs. B8a (lateral) and B10b (lateral) in the right lungs were consistently underdeveloped, with S9 occupying most of the lateral half of the lower lobe. In some samples, B6b (lateral) did not reach the lateral surface. The lateral dominance of S9 was also seen in the left lungs. Some B* candidates were present, but B7 candidates were absent. Lateral and posterior expansions of S6b, S8a and S10b to cover S9 were observed in additional midterm and near‐term lung sections, indicating that the original S9 dominance was 'corrected' by an increase in lung volume. Delayed growth of the lower lateral subsegments might induce mechanical stress, resulting in aberrant notches or fissures, such as those separating an independent posterior lobe. The segmental arrangement of fetal lungs was not stable, but was altered over a long fetal period after the complete subsegmental division of the bronchi, except for the minor bronchi B* and B7.

Sleep disturbance is common in patients with Alzheimer’s disease (AD), and orexin A is a pivotal neurotransmitter for bidirectionally regulating the amyloid-β (Aβ) deposition of AD brain and poor sleep. In the present study, we examined the characteristic of sleep–wake architecture in APPswe/PSldE9 (APP/PS1) and Aβ-treated mice using electroencephalogram (EEG) and electromyographic (EMG) analysis. We compared the expression of orexin A, distribution, and morphology of the corresponding orexin A-positive neurons using innovative methods including three-dimensional reconstruction and brain tissue clearing between wild type (WT) and APP/PS1 mice. Results from our study demonstrated that increased wakefulness and reduced NREM sleep were seen in APP/PS1 and Aβ treated mice, while the expression of orexin A was significantly upregulated. Higher density and distribution of orexin A-positive neurons were seen in APP/PS1 mice, with a location of 1.06 mm–2.30 mm away from the anterior fontanelle compared to 1.34 mm–2.18 mm away from the anterior fontanelle in WT mice. These results suggested that the population and distribution of orexin A may play an important role in the progression of AD.

Currently, studies on the system-of-systems (SoS) capability evaluation index system generation mechanism are scant, and the indicators are mostly determined by merely qualitative expert experience. This paper tries to explore a quantitative method for constructing the search and rescue system-of-systems (SARSoS) capability evaluation index system based on the SoS network architecture analysis, considering the impact from the SoS activity, organization, equipment, project, technology, and their relationships constraint on the capability generation. The four-layers weighted supernetwork model of the SARSoS is first established to describe the influence of SoS network architecture to the capability. Then, the index system construction method is proposed through the indicator importance sort algorithm (IISA). Finally, a specific case study of the SARSoS capability evaluation index system construction is demonstrated based on the proposed method. This paper provides a viable way to construct the index system based on the SoS architecture, which can select and integrate the indicators from multiple perspectives, and help to discover the SoS weak points and relationships in the future capability evaluation work.INDEX TERMS Search and rescue system-of-systems, capability evaluation, index system construction, weighted supernetwork model, indicator importance sort algorithm.