Optimization strategy of power control for C+L+S band transmission using a simulated annealing algorithm.

To increase the transmission capacity, ultra-wideband wavelength-division multiplexing (UWB WDM) has been exploited to enlarge the spectral range. However, inter-channel stimulated Raman scattering (ISRS) results in power transition from high-frequency channels to low-frequency channels in wideband scenarios, which degrades the Q-factor of signals. Hence, we modify the optimization method of power control by applying the simulated annealing (SA) algorithm to search for the optimal power slopes and offsets of three bands to construct an optimum distribution of launch powers over channels. High transmission capacity can be reached by carrying 384 channels (96+96+192) in the C+L+S band with the consideration of dynamic Raman gain and channel-dependent parameters. We show that compared to using brute-force searching (BFS), a comparable and even higher transmission capacity can be achieved by the SA algorithm. Meanwhile, the searching speed of the SA algorithm is much faster. Also, different optimizing strategies can be selected to balance the trade-off between capacity and spectral flatness. This method can be used for designing arbitrary optical fiber UWB WDM systems before practical testing.

Random forest assisted vector displacement sensor based on a multicore fiber.

We proposed a two-dimensional vector displacement sensor with the capability of distinguishing the direction and amplitude of the displacement simultaneously, with improved performance assisted by random forest, a powerful machine learning algorithm. The sensor was designed based on a seven-core multi-core fiber inscribed with Bragg gratings, with a displacement direction range of 0-360° and the amplitude range related to the length of the sensor body. The displacement information was obtained under a random circumstance, where the performances with theoretical model and random forest model were studied. With the theoretical model, the sensor performed well over a shorter linear range (from 0 to 9 mm). Whereas the sensor assisted with random forest algorithm exhibits better performance in two aspects, a wider measurement range (from 0 to 45 mm) and a reduced measurement error of displacement. Mean absolute errors of direction and amplitude reconstruction were decreased by 60% and 98%, respectively. The proposed displacement sensor shows the possibility of machine learning methods to be applied in point-based optical systems for multi-parameter sensing.

Identification and development of an independent immune-related genes prognostic model for breast cancer.

BACKGROUND: Breast cancer is one of the main malignant tumors that threaten the lives of women, which has received more and more clinical attention worldwide. There are increasing evidences showing that the immune micro-environment of breast cancer (BC) seriously affects the clinical outcome. This study aims to explore the role of tumor immune genes in the prognosis of BC patients and construct an immune-related genes prognostic index. METHODS: The list of 2498 immune genes was obtained from ImmPort database. In addition, gene expression data and clinical characteristics data of BC patients were also obtained from the TCGA database. The prognostic correlation of the differential genes was analyzed through Survival package. Cox regression analysis was performed to analyze the prognostic effect of immune genes. According to the regression coefficients of prognostic immune genes in regression analysis, an immune risk scores model was established. Gene set enrichment analysis (GSEA) was performed to probe the biological correlation of immune gene scores. P < 0.05 was considered to be statistically significant. RESULTS: In total, 556 immune genes were differentially expressed between normal tissues and BC tissues (p < 0. 05). According to the univariate cox regression analysis, a total of 66 immune genes were statistically significant for survival risk, of which 30 were associated with overall survival (P < 0.05). Finally, a 15 immune genes risk scores model was established. All patients were divided into high- and low-groups. KM survival analysis revealed that high immune risk scores represented worse survival (p < 0.001). ROC curve indicated that the immune genes risk scores model had a good reliability in predicting prognosis (5-year OS, AUC = 0.752). The established risk model showed splendid AUC value in the validation dataset (3-year over survival (OS) AUC = 0.685, 5-year OS AUC = 0.717, P = 0.00048). Moreover, the immune risk signature was proved to be an independent prognostic factor for BC patients. Finally, it was found that 15 immune genes and risk scores had significant clinical correlations, and were involved in a variety of carcinogenic pathways. CONCLUSION: In conclusion, our study provides a new perspective for the expression of immune genes in BC. The constructed model has potential value for the prognostic prediction of BC patients and may provide some references for the clinical precision immunotherapy of patients.

Dataset Construction to Explore Chemical Space with 3D Geometry and Deep Learning.

A dataset is the basis of deep learning model development, and the success of deep learning models heavily relies on the quality and size of the dataset. In this work, we present a new data preparation protocol and build a large fragment-based dataset Frag20, which consists of optimized 3D geometries and calculated molecular properties from Merck molecular force field (MMFF) and DFT at the B3LYP/6-31G* level of theory for more than half a million molecules composed of H, B, C, O, N, F, P, S, Cl, and Br with no larger than 20 heavy atoms. Based on the new dataset, we develop robust molecular energy prediction models using a simplified PhysNet architecture for both DFT-optimized and MMFF-optimized geometries, which achieve better than or close to chemical accuracy (1 kcal/mol) on multiple test sets, including CSD20 and Plati20 based on experimental crystal structures.

Aflatoxin B1 inhibited autophagy flux by inducing lysosomal alkalinization in HepG2 cells.

Aflatoxin B1 (AFB1) is a hazard food pollutant and the most toxic one of all the aflatoxins. It is mainly metabolized in the liver and exerts strong hepatotoxicity and carcinogenesis. Autophagy is an important biological process to maintain the homeostasis of intracellular environment. But the role of autophagy in AFB1-exposured hepatotoxicity remains unclear. The objective of this study was to explore the effect of AFB1 on autophagy flux and its potential mechanisms in HepG2 cells. The data showed AFB1 with no-observed adverse effect level (NOAEL) induced the accumulation of autophagosomes by detecting the level of LC3 and MDC staining. Subsequent findings revealed that autophagosome accumulation was caused by the inhibition of autophagy flux by transfection mRFP-GFP-LC3 adenovirus in the presence of autophagy inhibitor 3-MA and CQ. Further, we investigated lysosomal pH by Acridine orange (AO) and Lysotracker Red (LTR) staining and found that AFB1 exposure caused lysosomal alkalinization. These results indicated AFB1 with NOAEL could inhibit autophagy flux by inducing lysosomal alkalinization. Our study was helpful to further explain early hepatotoxicity mechanism of AFB1.

Joint linear and nonlinear noise monitoring techniques based on spectrum analysis.

As one of the key indicators of signal quality in fiber communication systems, optical signal-to-noise ratio (OSNR) needs to be accurately monitored to ensure reliable network planning, operation, and reconfiguration. OSNR monitoring techniques considering only accumulated amplified spontaneous emission (ASE) noise are no longer suitable for dispersion unmanaged long-haul and dense wavelength division multiplexing (WDM) systems, where the contribution of fiber nonlinearity to total SNR cannot be neglected. In this paper, we propose a modulation-format-transparent, accurate joint linear and nonlinear noise monitoring scheme based on calculation of correlation between two spectral components at the upper and lower sideband of the signal spectrum. Different characteristics of flat linear noise spectrum and non-flat nonlinear noise spectrum are used to distinguish the influences on the correlation value from both noise sources. Simulation results show that the proposed scheme can accurately monitor SNRlinear and SNRnonlinear within a wide launch power range from -5 dBm to 5 dBm per channel for multi-channel WDM systems with a 915-km single mode fiber (SMF) link. The performance of the proposed scheme is further experimentally verified in up-to-7 channel WDM systems over a 915 km SMF link.

Effects of simulated anisometropia and aniseikonia on stereopsis.

PURPOSE: Stereopsis depends on horizontally disparate retinal images but otherwise concordance between eyes. Here we investigate the effect of spherical and meridional simulated anisometropia and aniseikonia on stereopsis thresholds. The aims were to determine effects of meridian, magnitude and the relative effects of the two conditions. METHODS: Ten participants with normal binocular vision viewed McGill modified random dot stereograms through synchronised shutter glasses. Stereoacuities were determined using a four-alternative forced-choice procedure. To induce anisometropia, trial lenses of varying power and axes were placed in front of right eyes. Seventeen combinations were used: zero (no lens) and both positive and negative, 1 and 2 D powers, at 45, 90 and 180 axes; spherical lenses were also tested. To induce aniseikonia 17 magnification power and axis combinations were used. This included zero (no lens), and 3%, 6%, 9% and 12% at axes 45, 90 and 180; overall magnifications were also tested. RESULTS: For induced anisometropia, stereopsis loss increased as cylindrical axis rotated from 180° to 90°, at which the loss was similar to that for spherical blur. For example, for 2 D meridional anisometropia threshold increased from 1.53 log sec arc (i.e. 34 sec arc) for x 180 to 1.89 log sec arc (78 sec arc) for x 90. Anisometropia induced with either positive or negative lenses had similar detrimental effects on stereopsis. Unlike anisometropia, the stereopsis loss with induced meridional aniseikonia was not affected by axis and was about 64% of that for overall aniseikonia of the same amount. Approximately, each 1 D of induced anisometropia had the same effect on threshold as did each 6% of induced aniseikonia. CONCLUSION: The axes of meridional anisometropia but not aniseikonia affected stereopsis. This suggests differences in the way that monocular blur (anisometropia) and interocular shape differences (aniseikonia) are processed during the production of stereopsis.

Comparison of blur and magnification effects on stereopsis: overall and meridional, monocularly- and binocularly-induced.

PURPOSE: To determine whether monocularly- and binocularly-induced spherical and meridional blur and aniseikonia had similar effects on stereopsis thresholds. METHODS: Twelve participants with normal binocular vision viewed McGill modified random dot stereograms to determine stereoacuities in a four-alternative forced-choice procedure. Astigmatism was induced by placing trial lenses in front of the eyes. Twenty-three conditions were used, consisting of zero (no lens), +1 D and +2 D spheres and cylinders at axes 180, 45 and 90 in front of the right eye, and the following binocular combinations of both lens powers: R × 180/L × 180, R × 45/L × 45, R × 90/L × 90, R sphere/L sphere, R × 180/L × 90, R × 45/L × 135, R × 90/L × 180. Aniseikonia was induced by placing magnifying lenses in front of the eyes. Twenty-three conditions were used, consisting of zero, 6% and 12% overall magnification and both magnifications at axes 180, 45 and 90 in front of the right eye only, and the following binocular combinations using 3% and 6% lenses: R × 90/L × 90, R × 45/L × 45, R × 180/L × 180, R overall/L overall, R × 90/L × 180, R × 45/L × 135, and R × 180/L × 90. RESULTS: Stereopsis losses for binocular blur effects with parallel axes (non-anisometropic) were the same as for monocular blur effects of the same axes, and these were strongly dependent on axis (spherical blur and ×90 had the greatest effects). Binocular blur effects with orthogonal axes had greater effects than with parallel axes, with the axis combination of the former having no effect (e.g. R × 90/L × 180 was similar to R × 45/L × 135). For induced aniseikonia, splitting the magnifications between the eyes improved stereopsis slightly, and the effects were not dependent on axis. CONCLUSION: Binocular blur affects stereopsis similarly to monocular meridional blur if axes in the two eyes are parallel, whereas the effect is greater if the axes are orthogonal. In meridional aniseikonia, splitting magnification between the right and left lenses produces a small improvement in stereopsis that is independent of axis direction and right/left combination.

Modulation format identification assisted by sparse-fast-Fourier-transform for hitless flexible coherent transceivers.

For hitless flexible coherent transceivers based next-generation agile optical network, efficient modulation format identification (MFI) is an essential element in digital signal processing (DSP) flow at the receiver-side (Rx). In this paper, we propose a blind and fast MFI scheme with high identification accuracy at low optical signal-to-noise ratio (OSNR) regime. This is achieved by first raising the signal to the 4th power and calculate the peak-to-average power ratio (PAPR) of the corresponding spectra to distinguish 32 quadrature amplitude modulation (QAM) from quadrature phase shift keying (QPSK), 16 and 64QAM signals. Then, followed by iterative partition schemes to remove signals with phase ±π4,±3π4 (or QPSK-like phases) based on the signal amplitudes, the PAPR of the remaining signals is calculated to distinguish the other three formats. Additionally, by frequency offset (FO) pre-compensation, the spectrum can be obtained using sparse-fast-Fourier-transform (S-FFT), which greatly reduces the total complexity. The MFI performance is numerically and experimentally investigated by 28 Gbaud dual-polarization (DP) coherent optical back-to-back (B2B) and up to 1500 km standard single mode fiber (SSMF) transmission system using QPSK, 16QAM, 32QAM, and 64QAM. Results show that high identification accuracy can be achieved, even when OSNR is lower than that required for the 20% forward error correction (FEC) threshold of BER=2×10-2 for each format. Furthermore, fast format switching between 64QAM-32QAM and 32QAM-16QAM are demonstrated experimentally for B2B scenario and 900 km SSMF with the proposed MFI technique, respectively.

Frequency offset drift monitoring: enabling simultaneously optimum performance and minimum cost of frequency offset estimation.

Frequency offset (FO) is an important impairment in coherent transmission systems induced by wavelength mismatch between a free-running local oscillator (LO) and the transmit laser. A fast-Fourier-transform-based FO estimation (FFT-FOE) scheme is commonly employed. The obtained FOE value can be used to compensate FO of a relatively long duration of the signal. On the other hand, the drift of the laser frequency leads to time-varying FO, and FOE should operate in intervals to track the FO drift (FOD) for the best system performance. However, the complexity of FFT is high, and continuous operation of FFT-FOE results in huge energy consumption since it is unclear when FO drifts to an intolerable value. This Letter aims to solve such a problem: How often should FFT-FOE be operated to guarantee system performance with the lowest complexity? Here, we propose a FOD monitoring scheme based on sparse fast Fourier transform, by which optimum performance and minimum cost of FOE are achieved simultaneously. A downsampling process is further proposed to reduce the complexity of subsequent FFT-FOE. The performance is experimentally verified with 28 Gbaud coherent systems.

Incorporating Explicit Water Molecules and Ligand Conformation Stability in Machine-Learning Scoring Functions.

Structure-based drug design is critically dependent on accuracy of molecular docking scoring functions, and there is of significant interest to advance scoring functions with machine learning approaches. In this work, by judiciously expanding the training set, exploring new features related to explicit mediating water molecules as well as ligand conformation stability, and applying extreme gradient boosting (XGBoost) with Δ-Vina parametrization, we have improved robustness and applicability of machine-learning scoring functions. The new scoring function ΔvinaXGB can not only perform consistently among the top compared to classical scoring functions for the CASF-2016 benchmark but also achieves significantly better prediction accuracy in different types of structures that mimic real docking applications.

Exploring fragment-based target-specific ranking protocol with machine learning on cathepsin S.

Cathepsin S (CatS), a member of cysteine cathepsin proteases, has been well studied due to its significant role in many pathological processes, including arthritis, cancer and cardiovascular diseases. CatS inhibitors have been included in D3R-GC3 for both docking pose prediction and affinity ranking, and in D3R-GC4 for binding affinity ranking. The difficulties posed by CatS inhibitors in D3R mainly come from three aspects: large size, high flexibility and similar chemical structures. We have participated in GC4; our best submitted model, which employs a similarity-based alignment docking and Vina scoring protocol, yielded Kendall's τ of 0.23 for 459 binders in GC4. In our further explorations with machine learning, by curating a CatS specific training set, adopting a similarity-based constrained docking method as well as an arm-based fragmentation strategy which can describe large inhibitors in a locality-sensitive fashion, our best structure-based ranking protocol can achieve Kendall's τ of 0.52 for all binders in GC4. In this exploration process, we have demonstrated the importance of training data, docking approaches and fragmentation strategies in inhibitor-ranking protocol development with machine learning.

Experimental Study of Refraction Effects of Nominally Plano Ophthalmic Prisms and Magnifying Lenses.

SIGNIFICANCE: Nominally plano ophthalmic prisms give autorefraction results similar to those predicted on the basis of how effective powers change with pantoscopic tilt, and magnifying lenses give autorefraction results similar to those predicted on the basis of vergence changes. Without appreciation of the optics involved, these effects might wrongly be considered artifacts. PURPOSE: The purpose of this study was to investigate the interactions of autorefractors with lenses and prisms. METHODS: There were 15 adult participants across three experiments, with a range of ages and refractions. In experiments 1 and 2, participants wore frames containing base-up and base-down nominally plano prisms. In experiment 3, participants wore a lens that produced either 6.3% magnification or 5.9% minification, depending on which surface faced the eye. Autorefracting instruments with different operating principles were used: Shin-Nippon SRW5000 autorefractor, Grand Seiko 5100K autorefractor, Hoya AR-530 autorefractor, a Complete Ophthalmic Analysis System-High Definition wavefront sensor, and Tomey FC-800 autorefractor. A theory on the likely effects of magnifying lenses was presented. RESULTS: For ophthalmic prisms, refractions showed results similar to those predicted on the basis of how effective prism powers change with pantoscopic tilt. As tilt increased, base-up prism gave more positive mean refractions and more negative horizontal/vertical astigmatism and vice versa for base-down prisms. In the presence of 10° tilt, 8Δ base-up prisms and 8Δ base-down prisms had different effects by a mean of 0.36 diopters. Magnifying lenses affected refractions similar to those predicted on the basis of vergence changes, with 6% magnification and minification producing mean changes of -11 and +8%, respectively, in absolute mean refraction. There was no strong evidence that different instruments had different effects. CONCLUSIONS: The results have implications for studies in which prisms and lenses are placed in the front eyes, such as accommodation studies using thick lenses close to the eyes to stimulate accommodation rather than by changing object distance.

Modulation format identification enabled by the digital frequency-offset loading technique for hitless coherent transceiver.

We propose a blind and fast modulation format identification (MFI) enabled by the digital frequency-offset (FO) loading technique for hitless coherent transceiver. Since modulation format information is encoded to the FO distribution during digital signal processing (DSP) at the transmitter side (Tx), we can use the fast Fourier transformation based FO estimation (FFT-FOE) method to obtain the FO distribution of individual data block after constant modulus algorithm (CMA) pre-equalization at the receiver side, in order to realize non-data-aided (NDA) and fast MFI. The obtained FO can be also used for subsequent FO compensation (FOC), without additional complexity. We numerically investigate and experimentally verify the proposed MFI with high accuracy and fast format switching among 28 Gbaud dual-polarization (DP)-4/8/16/64QAM, time domain hybrid-4/16QAM, and set partitioning (SP)-128QAM. In particular, the proposed MFI brings no performance degradation, in term of tolerance of amplified spontaneous emission (ASE) noise, laser linewidth, and fiber nonlinearity. Finally, a hitless coherent transceiver enabled by the proposed MFI with switching-block of only 2048 symbols is demonstrated over 1500 km standard single mode fiber (SSMF) transmission.

Directed Chemical Assembly of Single and Clustered Nanoparticles with Silanized Templates.

The assembly of nanoscale materials into arbitrary, organized structures remains a major challenge in nanotechnology. Herein, we report a general method for creating 2D structures by combining top-down lithography with bottom-up chemical assembly. Under optimal conditions, the assembly of gold nanoparticles was achieved in less than 30 min. Single gold nanoparticles, from 10 to 100 nm, can be placed in predetermined patterns with high fidelity, and higher-order structures can be generated consisting of dimers or trimers. It is shown that the nanoparticle arrays can be transferred to, and embedded within, polymer films. This provides a new method for the large-scale fabrication of nanoparticle arrays onto diverse substrates using wet chemistry.

Computational Strategy for Bound State Structure Prediction in Structure-Based Virtual Screening: A Case Study of Protein Tyrosine Phosphatase Receptor Type O Inhibitors.

Accurate protein structure in the ligand-bound state is a prerequisite for successful structure-based virtual screening (SBVS). Therefore, applications of SBVS against targets for which only an apo structure is available may be severely limited. To address this constraint, we developed a computational strategy to explore the ligand-bound state of a target protein, by combined use of molecular dynamics simulation, MM/GBSA binding energy calculation, and fragment-centric topographical mapping. Our computational strategy is validated against low-molecular weight protein tyrosine phosphatase (LMW-PTP) and then successfully employed in the SBVS against protein tyrosine phosphatase receptor type O (PTPRO), a potential therapeutic target for various diseases. The most potent hit compound GP03 showed an IC50 value of 2.89 µM for PTPRO and possessed a certain degree of selectivity toward other protein phosphatases. Importantly, we also found that neglecting the ligand energy penalty upon binding partially accounts for the false positive SBVS hits. The preliminary structure-activity relationships of GP03 analogs are also reported.

Feed-forward frequency offset estimation for 32-QAM optical coherent detection.

Due to the non-rectangular distribution of the constellation points, traditional fast Fourier transform based frequency offset estimation (FFT-FOE) is no longer suitable for 32-QAM signal. Here, we report a modified FFT-FOE technique by selecting and digitally amplifying the inner QPSK ring of 32-QAM after the adaptive equalization, which is defined as QPSK-selection assisted FFT-FOE. Simulation results show that no FOE error occurs with a FFT size of only 512 symbols, when the signal-to-noise ratio (SNR) is above 17.5 dB using our proposed FOE technique. However, the error probability of traditional FFT-FOE scheme for 32-QAM is always intolerant. Finally, our proposed FOE scheme functions well for 10 Gbaud dual polarization (DP)-32-QAM signal to reach 20% forward error correction (FEC) threshold of BER=2×10-2, under the scenario of back-to-back (B2B) transmission.

Joint carrier phase and frequency-offset estimation with parallel implementation for dual-polarization coherent receiver.

We present dual-polarization complex-weighted, decision-aided, maximum-likelihood algorithm with superscalar parallelization (SSP-DP-CW-DA-ML) for joint carrier phase and frequency-offset estimation (FOE) in coherent optical receivers. By pre-compensation of the phase offset between signals in dual polarizations, the performance can be substantially improved. Meanwhile, with the help of modified SSP-based parallel implementation, the acquisition time of FO and the required number of training symbols are reduced by transferring the complex weights of the filters between adjacent buffers, where differential coding/decoding is not required. Simulation results show that the laser linewidth tolerance of our proposed algorithm is comparable to traditional blind phase search (BPS), while a complete FOE range of ± symbol rate/2 can be achieved. Finally, performance of our proposed algorithm is experimentally verified under the scenario of back-to-back (B2B) transmission using 10 Gbaud DP-16/32-QAM formats.

Scanning Nanospin Ensemble Microscope for Nanoscale Magnetic and Thermal Imaging.

Quantum sensors based on solid-state spins provide tremendous opportunities in a wide range of fields from basic physics and chemistry to biomedical imaging. However, integrating them into a scanning probe microscope to enable practical, nanoscale quantum imaging is a highly challenging task. Recently, the use of single spins in diamond in conjunction with atomic force microscopy techniques has allowed significant progress toward this goal, but generalization of this approach has so far been impeded by long acquisition times or by the absence of simultaneous topographic information. Here, we report on a scanning quantum probe microscope which solves both issues by employing a nanospin ensemble hosted in a nanodiamond. This approach provides up to an order of magnitude gain in acquisition time while preserving sub-100 nm spatial resolution both for the quantum sensor and topographic images. We demonstrate two applications of this microscope. We first image nanoscale clusters of maghemite particles through both spin resonance spectroscopy and spin relaxometry, under ambient conditions. Our images reveal fast magnetic field fluctuations in addition to a static component, indicating the presence of both superparamagnetic and ferromagnetic particles. We next demonstrate a new imaging modality where the nanospin ensemble is used as a thermometer. We use this technique to map the photoinduced heating generated by laser irradiation of a single gold nanoparticle in a fluid environment. This work paves the way toward new applications of quantum probe microscopy such as thermal/magnetic imaging of operating microelectronic devices and magnetic detection of ion channels in cell membranes.

Therapeutic effect of phycocyanin on chronic obstructive pulmonary disease in mice.

INTRODUCTION: The prevention and treatment of chronic obstructive pulmonary disease (COPD) is closely tied to antioxidation and anti-inflammation. Phycocyanin (PC) has numerous pharmacological effects, such as antioxidation and anti-inflammation. However, it remains unclear whether PC can play a therapeutic role in COPD. OBJECTIVE: As inflammation and oxidative stress can aggravate COPD, this study is to explore the effect of PC on COPD mice and its mechanisms. METHODS: The COPD mice model was established by exposing them to lipopolysaccharide (LPS) and cigarette smoke (CS); PC was administrated in a concentration of 50 mg/kg for 30 days. On the last day, lung function was measured, and bronchoalveolar lavage fluid (BALF) was obtained and classified for cells. Lung tissue pathological change was analyzed, and organ indices statistics were measured. Based on molecular docking, the mechanism was explored with Western blotting, immunohistochemical, and immunofluorescence in vivo and in vitro. RESULTS: PC significantly ameliorated the pulmonary function of COPD mice and reduced inflammation of the lung (p < 0.05), and hematoxylin and eosin (H&E) staining showed PC depressed lung inflammatory cell accumulation and emphysema. Periodic acid Schiff (PAS) and Masson staining revealed that PC retarded goblet cells metaplasia and collagen deposition (p < 0.05). In addition, in vivo PC regulated Heme oxygenase 1 (HO-1) (p < 0.05) and NAD(P)H dehydrogenase quinone 1 (NQO1) level (p < 0.01) in the lung, as well as NOX2 level in pulmonary macrophages. Molecular docking results indicate that phycocyanobilin (PCB) in PC had a good binding site in Keap1 and NOX2 proteins; the phycocyanobilin-bound phycocyanin peptide (PCB-PC-peptide) was obtained for further studies. In vitro, PCB-PC-peptide could depress the phospho-NF-E2-related factor 2 (p-Nrf2) and NQO1 protein expression in RAW264.7 cells induced by cigarette smoke extract (CSE) (p < 0.05). CONCLUSION: PC exerts beneficial effects on COPD via anti-inflammatory and antioxidative stress, which may be achieved through PCB.