Self-Assembled PD-L1 Downregulator to Boost Photodynamic Activated Tumor Immunotherapy Through CDK5 Inhibition.

The immunosuppressive characteristics and acquired immune resistance can restrain the therapy-initiated anti-tumor immunity. In this work, an antibody free programmed death receptor ligand 1 (PD-L1) downregulator (designated as CeSe) is fabricated to boost photodynamic activated immunotherapy through cyclin-dependent kinase 5 (CDK5) inhibition. Among which, FDA approved photosensitizer of chlorin e6 (Ce6) and preclinical available CDK5 inhibitor of seliciclib (Se) are utilized to prepare the nanomedicine of CeSe through self-assembly technique without drug excipient. Nanoscale CeSe exhibits an increased stability and drug delivery efficiency, contributing to intracellular production of reactive oxygen species (ROS) for robust photodynamic therapy (PDT). The PDT of CeSe can not only suppress the primary tumor growth, but also induce the immunogenic cell death (ICD) to release tumor associated antigens. More importantly, the CDK5 inhibition by CeSe can downregulate PD-L1 to re-activate the systemic anti-tumor immunity by decreasing the tumor immune escape and therapy-induced acquired immune resistance. This work provides an antibody free strategy to activate systemic immune response for metastatic tumor treatment, which may accelerate the development of translational nanomedicine with sophisticated mechanism.

Health risk assessment and potential sources of metals in riparian soils of the Wujiang River, China.

In order to understand the pollution status of metals in the riparian soils along the Wujiang River, 26 sampling sites in the mainstream and tributary streams were selected for investigation. The geo-accumulation index (Igeo), Nemerow integrated pollution index, and potential ecological risk index were applied to evaluate the contamination status and ecological risks of metals. Results revealed that the average concentrations of As, Cd, Cr, Cu, Mn, Ni, Pb, and Zn were 12.20, 0.51, 84.01, 57.42, 922.57, 38.37, 38.06, and 127.82 mg/kg, respectively. The metal contamination degree and ecological risks in the upper reaches were significantly higher than those in the middle and lower reaches of the Wujiang River. Cd was the dominant contamination metal. Significant non-carcinogenic and carcinogenic risks of metals were found in children based on the hazard index and carcinogenic risk. As was the main non-carcinogenic and carcinogenic pollutant metal in both adults and children. According to principal component analysis, hierarchical clustering analysis, and absolute principal component scores-multiple linear regression, anthropogenic sources (mining and agricultural activities) contributed most to Zn, Pb, Cr, Cd, Cu, and Ni, with contribution rates of 89.14, 82.32, 74.46, 72.12, 68.52, and 61.02%, respectively. Natural sources contributed most to Mn, with a contribution rate of 83.07%. Unidentified sources contributed most to As, with a contribution rate of 47.27%.

Chimeric Peptide-Engineered Self-Delivery Nanomedicine for Photodynamic-Triggered Breast Cancer Immunotherapy by Macrophage Polarization.

A systemic treatment strategy is urgently demanded to suppress the rapid growth and easy metastasis characteristics of breast cancer. In this work, a chimeric peptide-engineered self-delivery nanomedicine (designated as ChiP-CeR) for photodynamic-triggered breast cancer immunotherapy by macrophage polarization. Among these, ChiP-CeR is composed of the photosensitizer of chlorine e6 (Ce6) and the TLR7/8 agonist of lmiquimod (R837), which is further modified with tumor matrix targeting peptide (Fmoc-K(Fmoc)-PEG8 -CREKA. ChiP-CeR is preferred to actively accumulate at the tumor site via specific recognition of fibronectin, which can eradicate primary tumor growth through photodynamic therapy (PDT). Meanwhile, the destruction of primary tumors would trigger immunogenic cell death (ICD) effects to release high-mobility group box-1(HMGB1) and expose calreticulin (CRT). Moreover, ChiP-CeR can also polarize M2-type tumor-associated macrophages (TAMs) into M1-type TAMs, which can activate T cell antitumor immunity in combination with ICD. Overall, ChiP-CeR possesses superior antitumor effects against primary and lung metastatic tumors, which provide an applicable nanomedicine and a feasible strategy for the systemic management of metastatic breast cancer.

Silencing HOXC13 exerts anti-prostate cancer effects by inducing DNA damage and activating cGAS/STING/IRF3 pathway.

BACKGROUND: Advanced prostate cancer (PCa) will develop into castration-resistant prostate cancer (CRPC) and lead to poor prognosis. As the primary subtype of CRPC, CRPC-AR accounts for the major induction of PCa heterogeneity. CRPC-AR is mainly driven by 25 transcription factors (TFs), which we speculate may be the key factors driving PCa toward CRPC. Therefore, it is necessary to clarify the key regulator and its molecular mechanism mediating PCa progression. METHODS: Firstly, we downloaded transcriptomic data and clinical information from TCGA-PRAD. The characteristic gene cluster was identified by PPI clustering, GO enrichment, co-expression correlation and clinical feature analyses for 25 TFs. Then, the effects of 25 TFs expression on prognosis of PCa patients was analyzed using univariate Cox regression, and the target gene was identified. The expression properties of the target gene in PCa tissues were verified using tissue microarray. Meanwhile, the related mechanistic pathway of the target gene was mined based on its function. Next, the target gene was silenced by small interfering RNAs (siRNAs) for cellular function and mechanistic pathway validation. Finally, CIBERSORT algorithm was used to analyze the infiltration levels of 22 immune cells in PCa patients with low and high expression of target gene, and validated by assaying the expression of related immunomodulatory factor. RESULTS: We found that HOX family existed independently in 25 TFs, among which HOXC10, HOXC12 and HOXC13 had unique clinical features and the PCa patients with high HOXC13 expression had the worst prognosis. In addition, HOXC13 was highly expressed in tumor tissues and correlated with Gleason score and pathological grade. In vitro experiments demonstrated that silencing HOXC13 inhibited 22RV1 and DU145 cell function by inducing cellular DNA damage and activating cGAS/STING/IRF3 pathway. Immune infiltration analysis revealed that high HOXC13 expression suppressed infiltration of γδ T cells and plasma cells and recruited M2 macrophages. Consistent with these results, silencing HOXC13 up-regulated the transcriptional expression of IFN-ß, CCL2, CCL5 and CXCL10. CONCLUSION: HOXC13 regulates PCa progression by mediating the DNA damage-induced cGAS/STING/IRF3 pathway and remodels TIME through regulation of the transcription of the immune factors IFN-ß, CCL2, CCL5 and CXCL10.

Spatio-temporal fusion of meteorological factors for multi-site PM2.5 prediction: A deep learning and time-variant graph approach.

In the field of environmental science, traditional methods for predicting PM2.5 concentrations primarily focus on singular temporal or spatial dimensions. This approach presents certain limitations when it comes to deeply mining the joint influence of multiple monitoring sites and their inherent connections with meteorological factors. To address this issue, we introduce an innovative deep-learning-based multi-graph model using Beijing as the study case. This model consists of two key modules: firstly, the 'Meteorological Factor Spatio-Temporal Feature Extraction Module'. This module deeply integrates spatio-temporal features of hourly meteorological data by employing Graph Convolutional Networks (GCN) and Long Short-Term Memory (LSTM) for spatial and temporal encoding respectively. Subsequently, through an attention mechanism, it retrieves a feature tensor associated with air pollutants. Secondly, these features are amalgamated with PM2.5 concentration values, allowing the 'PM2.5 Concentration Prediction Module' to predict with enhanced accuracy the joint influence across multiple monitoring sites. Our model exhibits significant advantages over traditional methods in processing the joint impact of multiple sites and their associated meteorological factors. By providing new perspectives and tools for the in-depth understanding of urban air pollutant distribution and optimization of air quality management, this model propels us towards a more comprehensive approach in tackling air pollution issues.

High Endogenously Synthesized N-3 Polyunsaturated Fatty Acids in Fat-1 Mice Attenuate High-Fat Diet-Induced Insulin Resistance by Inhibiting NLRP3 Inflammasome Activation via Akt/GSK-3ß/TXNIP Pathway.

High-fat (HF) diets and low-grade chronic inflammation contribute to the development of insulin resistance and type 2 diabetes (T2D), whereas n-3 polyunsaturated fatty acids (PUFAs), due to their anti-inflammatory effects, protect against insulin resistance. Interleukin (IL)-1ß is implicated in insulin resistance, yet how n-3 PUFAs modulate IL-1ß secretion and attenuate HF diet-induced insulin resistance remains elusive. In this study, a HF diet activated NLRP3 inflammasome via inducing reactive oxygen species (ROS) generation and promoted IL-1ß production primarily from adipose tissue preadipocytes, but not from adipocytes and induced insulin resistance in wild type (WT) mice. Interestingly, endogenous synthesized n-3 polyunsaturated fatty acids (PUFAs) reversed this process in HF diet-fed fat-1 transgenic mice although the HF diet induced higher weight gain in fat-1 mice, compared with the control diet. Mechanistically, palmitic acid (PA), the main saturated fatty acid in an HF diet inactivated AMPK and led to decreased GSK-3ß phosphorylation, at least partially through reducing Akt activity, which ultimately blocked the Nrf2/Trx1 antioxidant pathway and induced TXNIP cytoplasm translocation and NLRP3 inflammasome activation, whereas docosahexaenoic acid (DHA), the most abundant n-3 PUFA in fat-1 adipose tissue, reversed this process via inducing Akt activation. Our GSK-3ß shRNA knockdown study further revealed that GSK-3ß played a pivot role between the upstream AMPK/Akt pathway and downstream Nrf2/Trx1/TXNIP pathway. Given that NLRP3 inflammasome is implicated in the development of most inflammatory diseases, our results suggest the potential of n-3 PUFAs in the prevention or adjuvant treatment of NLRP3 inflammasome-driven diseases.

Small RNA sequencing reveals various microRNAs involved in piperine biosynthesis in black pepper (Piper nigrum L.).

BACKGROUND: Black pepper (Piper nigrum L.), an important and long-cultivated spice crop, is native to South India and grown in the tropics. Piperine is the main pungent and bioactive alkaloid in the berries of black pepper, but the molecular mechanism for piperine biosynthesis has not been determined. MicroRNAs (miRNAs), which are classical endogenous noncoding small RNAs, play important roles in regulating secondary metabolism in many species, but less is known regarding black pepper or piperine biosynthesis. RESULTS: To dissect the functions of miRNAs in secondary metabolism especially in piperine biosynthesis, 110 known miRNAs, 18 novel miRNAs and 1007 individual targets were identified from different tissues of black pepper by small RNA sequencing. qRT-PCR and 5'-RLM-RACE experiments were conducted to validate the reliability of the sequencing data and predicted targets. We found 3 miRNAs along with their targets including miR166-4CL, miR396-PER and miR397-CCR modules that are involved in piperine biosynthesis. CONCLUSION: MiRNA regulation of secondary metabolism is a common phenomenon in plants. Our study revealed new miRNAs that regulate piperine biosynthesis, which are special alkaloids in the piper genus, and they might be useful for future piperine genetic improvement of black pepper.

An oncolytic vaccinia virus armed with anti-human-PD-1 antibody and anti-human-4-1BB antibody double genes for cancer-targeted therapy.

Oncolytic virus can selectively recognize cancer cells, target tumors, and stimulate an oncolytic and immune response. Recombinant armed oncolytic vaccinia virus has emerged as an attractive tool in oncolytic virotherapy because it has tumor-specific cytotoxicity and serves as a vector to express immune genes. A novel thymidine kinase (TK) gene-deleted oncolytic vaccinia virus (named ΔTK-Armed-VACV) armed with anti-human-programed cell death-1 protein (PD-1) antibody and anti-human-tumor necrosis factor receptor superfamily, member 9 (4-1BB) antibody genes was constructed based on Western Reserve in our previous study. The present study evaluated the ability of this virus for cancer-targeted therapy both in vitro and in vivo. A complete morphological structure of ΔTK-Armed-VACV was verified using transmission electron microscopy. The antibody was co-expressed with the replication of ΔTK-Armed-VACV in vitro assessed by Western blot analysis, enzyme-linked immunosorbent assay, and quantitative real-time polymerase chain reaction. The 3-(4,5-dimethylthiazol-2-yl)-5-(3-rboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium, inner salt assay showed that the ΔTK-Armed-VACV exhibited significant tumor-specific cytotoxicity in vitro. The ΔTK-Armed-VACV inhibited the tumor growth in a 4T1 or A549 tumor-bearing mouse model. ELISpot assay showed that ΔTK-Armed-VACV-treated mice induced the expression of interferon-gamma, and lactate dehydrogenase-dependent cytotoxicity assay revealed that the ΔTK-Armed-VACV treatment activated tumor-specific cytotoxic T lymphocytes. The results indicated that oncolytic VACV with Western Reserve-mediated anti-human-PD-1 and anti-human-4-1BB antibody co-expression exerted a significant antitumor effect, indicating that the combination of oncolytic virotherapy and immunotherapy by the oncolytic VACV expressing one or more immune checkpoint genes might have satisfactory clinical expectations.

Development of a novel ssDNA aptamer targeting cardiac troponin I and its clinical applications.

Cardiac troponin I (cTnI) is a specific biomarker of acute myocardial infarction (AMI). However, cTnI detection kits prepared with antibodies have many defects. Nucleic acid aptamers are sequences of single-strand DNA or RNA that can overcome the deficiency of antibodies. Herein, sandwich ELONA methods were established based on aptamers. Two selected ssDNA aptamers (Apt3 and Apt6) showed high binding affinity and sensibility (Apt3: Kd = 1.01 ± 0.07 nM, Apt6: k = 0.68 ± 0.05) and did not bind to the same domain of cTnI. Therefore, these two aptamers can be applied to the ELONA methods. The detection range of cTnI using the dual-aptamer sandwich ELONA method was 0.05-200 ng/mL, and the bioanalytical method verification results can meet the national standard of Chinese Pharmacopoeia (2020 Edition). There was no difference between results of the dual-aptamer sandwich ELONA method and the diagnostic results of serum obtained from 243 people (P = 0.39, P ˃ 0.05). The sensitivity and specificity of the ELONA with cTnI in serum were 96.46% and 93.85%, respectively. Compared with the FICA kit, which is clinically used, the consequences of ELONA method are closer to the diagnostic results. This study suggests that the aptamers Apt3 and Apt6 have high affinity and strong specificity and that the dual-aptamer sandwich ELONA method has a wide detection range and can be used to determine cTnI in serum, with potential applications in the diagnosis of AMIs.

Evaluation of analytic and clinical performance of two immunoassays for detecting thyroid-stimulating receptor antibody in the diagnosis of Graves' disease.

OBJECTIVE: To evaluate the analytical and clinical performance of two immunoassays for diagnosis of Graves' disease (GD), the Immulite thyroid-stimulating immunoglobulin (TSI), and Elecsys Anti-TSH receptor (TSHR) assay. METHODS: Precision and analytical measurement range were assessed using pooled samples of patients. The comparison between the two methods was evaluated using 579 clinical samples, and receiver operating characteristic (ROC) curves were drawn using the final diagnosis as reference. Clinical sensitivity and specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were calculated for the two tests. RESULTS: The repeatability and intermediate imprecision coefficient of variation (CV%) of the TSI assay were 3.8% and 4.1% at 0.95 IU/L, and 3.5% and3.6% at 19.5 IU/L, respectively. The assays were linear over a range 0.27-38.5 IU/L. There was a high correlation between the quantitative results of the two methods (correlation coefficient r = 0.930). The cut-off value obtained by ROC analysis for TSI assay was 0.7 IU/L with sensitivity of 93.7% and specificity of 85.1%. An overall qualitative agreement of 91.5% between two methods was observed. Among 44 patients with discordant qualitative results, the TSI assay provided more satisfactory results consistent with clinical diagnoses. CONCLUSION: The TSI assay showed excellent analytical performance and provided a high PPV for GD.

Double-Scale Adaptive Transmission in Time-Varying Channel for Underwater Acoustic Sensor Networks.

The communication channel in underwater acoustic sensor networks (UASNs) is time-varying due to the dynamic environmental factors, such as ocean current, wind speed, and temperature profile. Generally, these phenomena occur with a certain regularity, resulting in a similar variation pattern inherited in the communication channels. Based on these observations, the energy efficiency of data transmission can be improved by controlling the modulation method, coding rate, and transmission power according to the channel dynamics. Given the limited computational capacity and energy in underwater nodes, we propose a double-scale adaptive transmission mechanism for the UASNs, where the transmission configuration will be determined by the predicted channel states adaptively. In particular, the historical channel state series will first be decomposed into large-scale and small-scale series and then be predicted by a novel k-nearest neighbor search algorithm with sliding window. Next, an energy-efficient transmission algorithm is designed to solve the problem of long-term modulation and coding optimization. In particular, a quantitative model is constructed to describe the relationship between data transmission and the buffer threshold used in this mechanism, which can then analyze the influence of buffer threshold under different channel states or data arrival rates theoretically. Finally, numerical simulations are conducted to verify the proposed schemes, and results show that they can achieve good performance in terms of channel prediction and energy consumption with moderate buffer length.

Advances in the treatment of neuropathic pain with hyperbaric oxygen.

Neuropathic pain (NPP) refers to the pain caused by primary or secondary injury or dysfunction of the peripheral or central nervous system, and usually requires multidisciplinary treatment. However, most pharmacological and non-pharmacological interventions can only temporarily and/or moderately improve pain-related symptoms, and they often produce unbearable adverse reactions or cause drug resistance. Hyperbaric oxygen (HBO2) therapy has been widely used in the clinical treatment of some diseases due to its advantages of safety, few side effects, no resistance, and non-invasiveness. In recent years, increasing numbers of basic and clinical studies have been conducted to investigate the efficacy and mechanism of HBO2 in the treatment of NPP, and great progress has been made in this field. In this paper, we briefly introduce the pathogenesis of NPP and therapeutic effects of HBO2 and summarize the mechanisms underlying the effects of HBO2 in treating NPP, which may provide reference for the clinical treatment of pain with HBO2.

[Regulatory roles of microRNAs in sarcopenia and exercise intervention].

Sarcopenia is an age-related degenerative disease, in which skeletal muscle mass and function are reduced during aging process. Physical intervention is one of the most effective strategies available for the treatment of sarcopenia. Studies have shown that microRNAs (miRNAs), as important regulators of gene expression, play an important role in maintaining the homeostasis of senescent skeletal muscle cells by regulating skeletal muscle cell development (proliferation and differentiation), mitochondrial biogenesis, protein synthesis and degradation, inflammatory response and metabolic pathways. Furthermore, exercise can combat age-related changes in muscle mass, composition and function, which is associated with the changes in the expression and biological functions of miRNAs in skeletal muscle cells. In this article, we systematically review the regulatory mechanisms of miRNAs in skeletal muscle aging, and discuss the regulatory roles and molecular targets of exercise-mediated miRNAs in muscular atrophy during aging process, which may provide novel insights into the prevention and treatment of sarcopenia.

Energy-Efficient Nonuniform Content Edge Pre-Caching to Improve Quality of Service in Fog Radio Access Networks.

The fog radio access network (F-RAN) equipped with enhanced remote radio heads (eRRHs), which can pre-store some requested files in the edge cache and support mobile edge computing (MEC). To guarantee the quality-of-service (QoS) and energy efficiency of F-RAN, a proper content caching strategy is necessary to avoid coarse content storing locally in the cache or frequent fetching from a centralized baseband signal processing unit (BBU) pool via backhauls. In this paper we investigate the relationships among eRRH/terminal activities and content requesting in F-RANs, and propose an edge content caching strategy for eRRHs by mining out mobile network behavior information. Especially, to attain the inference for appropriate content caching, we establish a pre-mapping containing content preference information and geographical influence by an efficient non-uniformed accelerated matrix completion algorithm. The energy consumption analysis is given in order to discuss the energy saving properties of the proposed edge content caching strategy. Simulation results demonstrate our theoretical analysis on the inference validity of the pre-mapping construction method in static and dynamic cases, and show the energy efficiency achieved by the proposed edge content pre-caching strategy.

Research on the Impact of Absorption Feature Extraction on Spectral Difference Between Similar Minerals.

Diagnostic absorption features can indicate the existence of specific materials, which is the foundation of mineral analysis with optical remote sensing data. In hyperspectral data processing, the most commonly used method to extract absorption feature, is Continuum Removal (CR). As for multispectral data, Principle Component Analysis and other indirect methods were used to extract absorption information, and little research has been done on full-band absorption feature extraction. Classification of similar minerals is one of the major difficulties in mineral spectral analysis, while there is no valid index for spectral difference between similar mineral groups. Absorption feature extraction may improve the classification accuracy, but there is no research to investigate the impact of absorption feature extraction on spectral difference between similar minerals. This paper summarized the principle of mineral spectral difference, and proposed the concept of Class Separability Ratio (CSR), which was verified to be a valid index for spectral difference between similar mineral categories. Through comparison experiments on alunite and kaolinite spectra, including USGS spectral library spectra and resampled spectra in accordance with the band settings of HYPERION, ASTER and OLI, the impact of absorption feature extraction on spectral difference between similar minerals were investigated. Experimental results show that valid absorption feature extraction can greatly enhance the spectral difference between similar minerals, and the spectral difference is positively correlated with spectral resolution. Besides, the results of CR can be severely affected by spectral resolution and band center positions, and the absorption feature spectra extraction results for multispectral datasets need to be improved. This research laid the foundation of precise identification between similar mineral categories, and provided valuable reference for the band settings of future geology remote sensing sensors.

[Monitor of Cyanobacteria Bloom in Lake Taihu from 2001 to 2013 Based on MODIS Temporal Spectral Data].

Algal bloom highly impacts the ecological balance of inland lakes. Remote sensing provides real-time and large-scale observations, which plays an increasingly significant role in the monitoring of algal bloom. Various Vegetation Indices (VIs) derived from satellite images have been used to monitor algae. With threshold segmentation of VI, the area of algal bloom can be extracted from images. However, the result of threshold segmentation only reflects the condition of algae when images were generated. Compared to separated VI data obtained at a particular moment of time, temporal spectral VI data contains phonological information of algae, which may be used to evaluate algal bloom more accurately and comprehensively. This study chose MODIS NDVI data of the Lake Taihu from 2001 to 2013, and constructed temporal spectral data for each year. Then, we determined the feature temporal spectra of severe cyanobacteria bloom, moderate cyanobacteria bloom, slight cyanobacteria bloom and aquatic plants, and separated these four kinds of objects using SVM (Support Vector Machine) algorithm, getting the spatial distribution and area of them. In order to compare the results of our method with traditional threshold segmentation method, we chose 8 separated NDVI images from the temporal spectral data of 2007. With the threshold 0.2 and 0.4, cyanobacteria bloom was classified into three degrees: severe cyanobacteria bloom, moderate cyanobacteria bloom, and slight cyanobacteria bloom. By comparison, it showed that our method reflected cyanobacteria bloom more comprehensively, and could distinguish cyanobacteria and aquatic plants using the phonological information provided by NDVI temporal spectra. This study provides important information for monitoring the algal bloom trends and degrees of inland lakes, and temporal spectral method may be used in the forecast of algal bloom in the future.

Pigment epithelial-derived factor (PEDF)-triggered lung cancer cell apoptosis relies on p53 protein-driven Fas ligand (Fas-L) up-regulation and Fas protein cell surface translocation.

Pigment epithelium-derived factor (PEDF), a potent antiangiogenesis agent, has recently attracted attention for targeting tumor cells in several types of tumors. However, less is known about the apoptosis-inducing effect of PEDF on human lung cancer cells and the underlying molecular events. Here we report that PEDF has a growth-suppressive and proapoptotic effect on lung cancer xenografts. Accordingly, in vitro, PEDF apparently induced apoptosis in A549 and Calu-3 cells, predominantly via the Fas-L/Fas death signaling pathway. Interestingly, A549 and Calu-3 cells are insensitive to the Fas-L/Fas apoptosis pathway because of the low level of cell surface Fas. Our results revealed that, in addition to the enhancement of Fas-L expression, PEDF increased the sensitivity of A549 and Calu-3 cells to Fas-L-mediated apoptosis by triggering the translocation of Fas protein to the plasma membrane in a p53- and FAP-1-dependent manner. Similarly, the up-regulation of Fas-L by PEDF was also mediated by p53. Furthermore, peroxisome proliferator-activated receptor γ was determined to be the upstream regulator of p53. Together, these findings uncover a novel mechanism of tumor cell apoptosis induced by PEDF and provide a potential therapeutic strategy for tumors that are insensitive to Fas-L/Fas-dependent apoptosis because of a low level of cell surface Fas.

[Spectral Uncertainty of Terrestrial Objects and the Applicability of Spectral Angle Mapper Algorithm].

The spectral uncertainty of terrestrial objects causes a certain degree of spectral differences among feature spectra, which affects the accuracy of object recognition and also impacts the object recognition of spectral angle mapper algorithm (SAM). The spectral angle mapper algorithm is based on the overall similarity of the spectral curves, which was widely used in the classification of hyperspectral remotely sensed information. The spectral angle mapper algorithm does not take the spectral uncertainty of terrestrial objects into account while calculating the spectral angle between the spectral curves, and therefore does not tend to correctly identify the target objects. The applicability of the spectral angle mapper algorithm is studied for the spectral uncertainty of terrestrial objects and a modified SAM is proposed in this paper. In order to overcome the influence of the spectral uncertainty, the basic idea is to set a spectral difference value for the test spectra and the reference spectra and to calculate the spectral difference value based on derivation method according to the principle of minimum angle between the test spectra and the reference spectra. By considering the impact of the spectral uncertainty of terrestrial objects, this paper uses five kaolinite mineral spectra of USGS to calculate the spectral angle between the five kalinite mineral spectra by using local band combination and all bands to verify the improved algorithm. The calculation results and the applicability of the spectral angle mapper algorithm were analyzed. The results obtained from the experiments based on USGS mineral spectral data indicate that the modified SAM is not only helpful in characterizing and overcoming the impact of the spectral uncertainty but it can also improve the accuracy of object recognition to certain extent especially for selecting local band combination and has better applicability for the spectral uncertainty of terrestrial objects.

[Research on Accuracy and Stability of Inversing Vegetation Chlorophyll Content by Spectral Index Method].

Spectral index method was widely applied to the inversion of crop chlorophyll content. In the present study, PSR3500 spectrometer and SPAD-502 chlorophyll fluorometer were used to acquire the spectrum and relative chlorophyll content (SPAD value) of winter wheat leaves on May 2nd 2013 when it was at the jointing stage of winter wheat. Then the measured spectra were resampled to simulate TM multispectral data and Hyperion hyperspectral data respectively, using the Gaussian spectral response function. We chose four typical spectral indices including normalized difference vegetation index (NDVD, triangle vegetation index (TVI), the ratio of modified transformed chlorophyll absorption ratio index (MCARI) to optimized soil adjusted vegetation index (OSAVI) (MCARI/OSAVI) and vegetation index based on universal pattern decomposition (VIUPD), which were constructed with the feature bands sensitive to the vegetation chlorophyll. After calculating these spectral indices based on the resampling TM and Hyperion data, the regression equation between spectral indices and chlorophyll content was established. For TM, the result indicates that VIUPD has the best correlation with chlorophyll (R2 = 0.819 7) followed by NDVI (R2 = 0.791 8), while MCARI/OSAVI and TVI also show a good correlation with R2 higher than 0.5. For the simulated Hyperion data, VIUPD again ranks first with R2 = 0.817 1, followed by MCARI/OSAVI (R2 = 0.658 6), while NDVI and TVI show very low values with R2 less than 0.2. It was demonstrated that VIUPD has the best accuracy and stability to estimate chlorophyll of winter wheat whether using simulated TM data or Hyperion data, which reaffirms that VIUPD is comparatively sensor independent. The chlorophyll estimation accuracy and stability of MCARI/OSAVI also works well, partly because OSAVI could reduce the influence of backgrounds. Two broadband spectral indices NDVI and TVI are weak for the chlorophyll estimation of simulated Hyperion data mainly because of their dependence on few bands and the strong influence of atmosphere, solar altitude, viewing angle of sensor, background and so on. In conclusion, the stability and consistency of chlorophyll estimation is equally important to the estimation accuracy by spectral index method. VIUPD introduced in the study has the best performance to estimate winter wheat chlorophyll, which illustrates its potential ability in the area of estimating vegetation biochemical parameters.

Optical controlled and nuclear targeted CECR2 competitor to downregulate CSF-1 for metastatic breast cancer immunotherapy.

The crosstalk between breast cancer cells and tumor associated macrophages (TAMs) greatly contributes to tumor progression and immunosuppression. In this work, cat eye syndrome chromosome region candidate 2 (CECR2) is identified to overexpress in breast cancer patients, which can recognize v-rel avian reticuloendotheliosis viral oncogene homolog A (RelA) and activate nuclear factor κB (NF-κB) to release colony stimulating factor-1 (CSF-1). Pharmacological inhibition of CECR2 by the bromodomain competitor (Bromosporine, Bro) can downregulate CSF-1 to inhibit M2 type TAMs. To amplify the immunotherapeutic effect, a chimeric peptide-based and optical controlled CECR2 competitor (designated as N-PB) is constructed to enhance the nuclear targeted delivery of Bro and initiate an immunogenic cell death (ICD). In vivo results indicate a favorable breast cancer targeting ability and primary tumor suppression effect of N-PB under optical irradiation. Importantly, N-PB downregulates CSF-1 by competitive inhibition of CECR2 and NF-κB(RelA) interactions, thus inhibiting immunosuppressive M2-like TAMs while improving the antitumorigenic M1-like phenotype. Ultimately, the systemic anti-tumor immunity is activated to suppress the metastatic breast cancer in an optical controlled manner. This study provides a promising therapeutic target and reliable strategy for metastatic breast cancer treatment by interrupting immunosuppressive crosstalk between tumor cells and macrophages.