Yuzhe Zhang

Neuroendocrine prostate cancer (NEPC), a lethal form of the disease, is characterized by loss of androgen receptor (AR) signaling during neuroendocrine transdifferentiation, which results in resistance to AR-targeted therapy. Clinically, genomically and epigenetically, NEPC resembles other types of poorly differentiated neuroendocrine tumors (NETs). Through pan-NET analyses, we identified ONECUT2 as a candidate master transcriptional regulator of poorly differentiated NETs. ONECUT2 ectopic expression in prostate adenocarcinoma synergizes with hypoxia to suppress androgen signaling and induce neuroendocrine plasticity. ONEUCT2 drives tumor aggressiveness in NEPC, partially through regulating hypoxia signaling and tumor hypoxia. Specifically, ONECUT2 activates SMAD3, which regulates hypoxia signaling through modulating HIF1α chromatin-binding, leading NEPC to exhibit higher degrees of hypoxia compared to prostate adenocarcinomas. Treatment with hypoxia-activated prodrug TH-302 potently reduces NEPC tumor growth. Collectively, these results highlight the synergy between ONECUT2 and hypoxia in driving NEPC, and emphasize the potential of hypoxia-directed therapy for NEPC patients.

Hyperspectral imaging provides high-dimensional spatial–temporal–spectral information showing intrinsic matter characteristics1–5. Here we report an on-chip computational hyperspectral imaging framework with high spatial and temporal resolution. By integrating different broadband modulation materials on the image sensor chip, the target spectral information is non-uniformly and intrinsically coupled to each pixel with high light throughput. Using intelligent reconstruction algorithms, multi-channel images can be recovered from each frame, realizing real-time hyperspectral imaging. Following this framework, we fabricated a broadband visible–near-infrared (400–1,700 nm) hyperspectral image sensor using photolithography, with an average light throughput of 74.8% and 96 wavelength channels. The demonstrated resolution is 1,024 × 1,024 pixels at 124 fps. We demonstrated its wide applications, including chlorophyll and sugar quantification for intelligent agriculture, blood oxygen and water quality monitoring for human health, textile classification and apple bruise detection for industrial automation, and remote lunar detection for astronomy. The integrated hyperspectral image sensor weighs only tens of grams and can be assembled on various resource-limited platforms or equipped with off-the-shelf optical systems. The technique transforms the challenge of high-dimensional imaging from a high-cost manufacturing and cumbersome system to one that is solvable through on-chip compression and agile computation. A broadband hyperspectral image sensor fabricated using photolithography maintains high throughput with high spatial–temporal–spectral resolution, and has demonstrated wide applications including chlorophyll and sugar quantification, blood oxygen and water quality monitoring, textile classification, apple bruise detection, and remote lunar detection.

Abstract Background With the increasing fragmentation of landscape induced by rapid urbanization, the construction of ecological networks is of great significance to alleviate the degradation of urban habitats and protect natural environments. However, there is considerable uncertainty when constructing ecological networks, especially the different approaches to selecting ecological sources. We used the southern Chinese city of Shenzhen as a study area to construct and optimize ecological networks using a coupling approach. Ecological source areas were extracted using morphological spatial pattern analysis (MSPA) and the landscape index method. Ecological networks were constructed using the minimal cumulative resistance (MCR) model and the gravity model. Stepping stones and ecological fault points were added in corridors to optimize the ecological network. Results Ten core areas with maximum importance patch values were extracted by the landscape index method as ecological source areas according to MSPA, after which corridors between ecological sources were constructed based on the MCR model. The constructed ecological networks were optimized using 35 stepping stones and 17 ecological fault points. The optimized ecological networks included 11 important corridors, 34 general corridors, and seven potential corridors. The results of corridor landscape-type analysis showed that a suitable ecological corridor is 60 to 200 m wide. Conclusions Overall, our results imply that ecological source areas can be identified virtually, and that ecological networks can be significantly optimized by combining MSPA and MCR models. These results provide a methodological reference for constructing ecological networks, and they will be useful for urban planning and biodiversity protection in Shenzhen and other similar regions around the world.