Histopathological classification of human prostate cancer (PCA) relies on the morphological assessment of tissue specimens but has limited prognostic value. To address this deficiency, we performed comparative transcriptome analysis of human prostatic acini generated in a three-dimensional basement membrane that recapitulates the differentiated morphological characteristics and gene expression profile of a human prostate glandular epithelial tissue. We then applied an acinar morphogenesis-specific gene profile to two independent cohorts of patients with PCA (total n = 79) and found that those with tumors expressing this profile, which we designated acini-like tumors, had a significantly lower risk of postoperative relapse compared with those tumors with a lower correlation (hazard ratio, 0.078; log-rank test P = 0.009). Multivariate analyses showed superior prognostic prediction performance using this classification system compared with clinical criteria and Gleason scores. We prioritized the genes in this profile and identified programmed cell death protein 4 (PDCD4) and Kruppel-like factor 6 (KLF6) as critical regulators and surrogate markers of prostatic tissue architectures, which form a gene signature that robustly predicts clinical prognosis with a remarkable accuracy in several large series of PCA tumors (total n = 161; concordance index, 0.913 to 0.951). Thus, by exploiting the genomic program associated with prostate glandular differentiation, we identified acini-like PCA and related molecular markers that significantly enhance prognostic prediction of human PCA.

We report a novel approach to generating full-duty-cycle triangular waveforms based on a microwave photonic filter (MPF) with negative coefficient. It is known that the Fourier series expansion of a triangular waveform has only odd-order harmonics. In this work, the undesired even-order harmonics are suppressed by the MPF that has a periodic transmission response. A triangular waveform at fundamental frequency can be generated by setting the bias of a Mach-Zehnder modulator (MZM) at quadrature point. However, it is found that a broadband 90° microwave phase shifter has to be used after photodetection to adjust the phases of odd-order harmonics. Alternatively, a frequency doubling triangular waveform can be generated by setting the bias of the MZM at maximum or minimum transmission point. This approach is more promising because the broadband microwave phase shifter is no longer required in this case but it is more power consuming. The proposed approach is theoretically analyzed and experimentally verified.

We report a new radio-frequency (RF) phase stabilization approach for long-haul optical fiber distribution. The phase drift of an RF signal induced by fiber-length variations can be canceled out automatically via RF mixing without using active phase discrimination and dynamic phase tracking. A key significance of our approach is that no assistant local oscillator (LO) signal is needed. Consequently, frequency estimation of the received RF signal, as well as frequency locking between the LO and the received RF signal, is no longer required, which simplifies the system. A proof-of-concept experiment shows that the phase drift of the received RF signal at 9.6 GHz is significantly reduced using the proposed method. The root mean square (RMS) timing jitter is 0.76 ps when a tunable optical delay line (TODL) inserted between the remote antenna unit (RAU) and local station is changed from 0 to 300 ps.