Carcinogenic Role and Clinical Significance of Histone H3-H4 Chaperone Anti-silencing Function 1 B (ASF1B) in Lung Adenocarcinoma.

Histone H3-H4 chaperone anti-silencing function 1 (ASF1) plays an important role in the polymerization, transport, and modification of histones. However, the significance of ASF1B in lung adenocarcinoma (LUAD) is largely overlooked. We investigated the aberrant expression of ASF1B in LUAD and its potential link to patient survival using multiple databases. ASF1B-overexpressing and knockdown cell lines were constructed to explore its effects on the biological behavior of lung cancer cells. ssGSEA, TMB, TIDE and IMvigor210 cohort were used to explore and validate the association of ASF1B to tumor immunity. Our data suggested that ASF1B was overexpressed in LUAD, and was associated with poor prognosis. ASF1B promoted the proliferation, migration, and invasion of lung cancer cells by regulating the phosphorylation of AKT in vitro. ASF1B was associated with tumor immunity. In summary, ASF1B may promote malignant behavior of LUAD cells, and its overexpression correlates with worse prognosis and better immunotherapy effect.

Spectral missing color correction based on an adaptive parameter fitting model.

With the development of remote sensing technology, true-color visualization of hyperspectral LiDAR echo signals has become a hotspot for both academic research and commercial applications. The limitation of the emission power of hyperspectral LiDAR causes the loss of spectral-reflectance information in some channels of the hyperspectral LiDAR echo signal. The color reconstructed based on the hyperspectral LiDAR echo signal is bound to have serious color cast problem. To solve the existing problem, a spectral missing color correction approach based on adaptive parameter fitting model is proposed in this study. Given the known missing spectral-reflectance band intervals, the colors in incomplete spectral integration are corrected to accurately restore target colors. Based on the experimental results, the color difference between color blocks and the hyperspectral image corrected by the proposed color correction model is smaller than that of the ground truth, and the image quality is higher, realizing the accurate reproduction of the target color.

An improved spectral estimation method based on color perception features of mobile phone camera.

We use the mobile phone camera as a new spectral imaging device to obtain raw responses of samples for spectral estimation and propose an improved sequential adaptive weighted spectral estimation method. First, we verify the linearity of the raw response of the cell phone camera and investigate its feasibility for spectral estimation experiments. Then, we propose a sequential adaptive spectral estimation method based on the CIE1976 L*a*b* (CIELAB) uniform color space color perception feature. The first stage of the method is to weight the training samples and perform the first spectral reflectance estimation by considering the Lab color space color perception features differences between samples, and the second stage is to adaptively select the locally optimal training samples and weight them by the first estimated root mean square error (RMSE), and perform the second spectral reconstruction. The novelty of the method is to weight the samples by using the sample in CIELAB uniform color space perception features to more accurately characterize the color difference. By comparing with several existing methods, the results show that the method has the best performance in both spectral error and chromaticity error. Finally, we apply this weighting strategy based on the CIELAB color space color perception feature to the existing method, and the spectral estimation performance is greatly improved compared with that before the application, which proves the effectiveness of this weighting method.

Squamous cell carcinoma predicts worse prognosis than adenocarcinoma in stage IA lung cancer patients: A population-based propensity score matching analysis.

Background: Although numerous studies have reported the association between histological types and the prognosis of IA non-small-cell lung cancer (NSCLC) patients, few studies have deeply investigated the impact of pathology on the outcome of NSCLC patients. In this study, we comprehensively explored whether the type of histology influenced the outcome of IA-stage NSCLC patients. Methods: The study population was obtained from the Surveillance, Epidemiology, and End Results (SEER) program, which is supported by the National Cancer Institute of the United States. To avoid potential bias, the method of propensity score matching (PSM) was used to obtain a balanced cohort for further analysis. Results: The results from univariate and multivariate regression models showed that lung squamous cell carcinoma (LSQCC) patients were at a significantly greater risk of undergoing shorter overall survival (OS) and lung cancer-specific survival (LCSS). After PSM analysis, LSQCC was still closely associated with a reduction in OS and LCSS. All of these suggested that the histological type was an independent prognostic factor for OS and LCSS. Conclusion: Our study demonstrated that squamous cell carcinoma predicted worse OS and LCSS in IA-stage NSCLC patients compared with lung adenocarcinoma (LUAD). We suggest that the outcomes of LSQCC and LUAD are very different and that the two histological types should be differently analyzed.

Optimized light source spectral power distribution for RGB camera based spectral reflectance recovery.

The accuracy of recovered spectra from camera responses mainly depends on the spectral estimation algorithm used, the camera and filters selected, and the light source used to illuminate the object. We present and compare different light source spectrum optimization methods together with different spectral estimation algorithms applied to reflectance recovery. These optimization methods include the Monte Carlo (MC) method, particle swarm optimization (PSO) and multi-population genetic algorithm (MPGA). Optimized SPDs are compared with D65, D50 A and three LED light sources in simulation and reality. Results obtained show us that MPGA has superior performance, and optimized light source spectra along with better spectral estimation algorithm can provide a more accurate spectral reflectance estimation of an object surface. Meanwhile, it is found that camera spectral sensitivities weighted by optimized SPDs tend to be mutually orthogonal.

A potential endogenous gibberellin-mediated signaling cascade regulated floral transition in Magnolia × soulangeana 'Changchun'.

The floral transition is a critical developmental switch in plants, and has profound effects on the flower production and yield. Magnolia × soulangeana 'Changchun' is known as a woody ornamental plant, which can bloom in spring and summer, respectively. In this study, anatomical observation, physiological measurement, transcriptome, and small RNA sequencing were performed to investigate potential endogenous regulatory mechanisms underlying floral transition in 'Changchun'. Transition of the shoot apical meristem from vegetative to reproductive growth occurred between late April and early May. During this specific developmental process, a total of 161,645 unigenes were identified, of which 73,257 were significantly differentially expressed, while a number of these two categories of miRNAs were 299 and 148, respectively. Further analysis of differentially expressed genes (DEGs) revealed that gibberellin signaling could regulate floral transition in 'Changchun' in a DELLA-dependent manner. In addition, prediction and analysis of miRNA targeted genes suggested that another potential molecular regulatory module was mediated by the miR172 family and other several novel miRNAs (Ms-novel_miR139, Ms-novel_miR229, and Ms-novel_miR232), with the participation of up- or down-regulating genes, including MsSVP, MsAP2, MsTOE3, MsAP1, MsGATA6, MsE2FA, and MsMDS6. Through the integrated analysis of mRNA and miRNA, our research results will facilitate the understanding of the potential molecular mechanism underlying floral transition in 'Changchun', and also provide basic experimental data for the plant germplasm resources innovation in Magnolia.

Sequential adaptive estimation for spectral reflectance based on camera responses.

A sequential weighted nonlinear regression technique from digital camera responses is proposed for spectral reflectance estimation. The method consists of two stages taking colorimetric and spectral errors between training set and target set into accounts successively. Based on polynomial expansion model, local optimal training samples are adaptively employed to recover spectral reflectance as accurately as possible. The performance of the method is compared with several existing methods in the cases of simulated camera responses under three kinds of noise levels and practical camera responses under the self as well as cross test conditions. Results show that the proposed method is able to recover spectral reflectance with a higher accuracy than other methods considered.

The complete chloroplast genome of Magnolia polytepala: Comparative analyses offer implication for genetics and phylogeny of Yulania.

Magnoliaceae is a primitive taxon in the angiosperms, comprising approximately 240 species in 2-17 genera. Many of them have been widely cultivated due to their horticultural and medicinal value. However, there are uncertainties and controversies about the delimitation of the genera except Liriodendron L. in this family. The Yulania taxa is also the focus of dispute at the genus and section levels. In this study, we compared ten Yulania plastomes, including the newly sequenced M. polytepala. The plastome-wide comparative analysis demonstrated that 1) Yulania cp genomes were highly conserved, and the majority differences existed in IR regions with the loss/retention of trnV-GAC or ycf15 gene, 2) mutational hotspots with high levels of nucleotide diversity (Pi > 0.02) existed in both coding (rpoA, and ycf1) and no-coding (ccsA-ndhD, ndhE-ndhG, ndhF-rpl32, petA-psbJ, rpl32-trnL, rps3-rps19, and trnH-psbA) regions among the genus Yulania. Combined with other data from Magnoliaceae plastomes, our reconstructed molecular phylogenetic tree revealed that Yulania is monophyletic, separated from the genus Magnolia L. (=Magnolia subg. Magnolia L.), but seems a sister of Michelia L. Moreover, M. polytepala which belongs to the genus Yulania is most closely related to M. liliiflora. All these results indicated that plastome data may contribute to investigating taxonomy, population genetics and phylogeny of Yulania.

A New Insight into Flowering Regulation: Molecular Basis of Flowering Initiation in Magnolia × soulangeana 'Changchun'.

Magnolia × soulangeana 'Changchun' are trees that bloom in spring and summer respectively after flower bud differentiation. Here, we use phenological and morphological observation and RNA-seq technology to study the molecular basis of flowering initiation in 'Changchun'. During the process of flowering initiation in spring and summer, the growth of expanded flower buds increased significantly, and their shape was obviously enlarged, which indicated that flowering was initiated. A total of 168,120 expressed genes were identified in spring and summer dormant and expanded flower buds, of which 11,687 genes showed significantly differential expression between spring and summer dormant and expanded flower buds. These differentially expressed genes (DEGs) were mainly involved in plant hormone signal transduction, metabolic processes, cellular components, binding, and catalytic activity. Analysis of differential gene expression patterns revealed that gibberellin signaling, and some transcription factors were closely involved in the regulation of spring and summer flowering initiation in 'Changchun'. A qRT-PCR (quantitative Real Time Polymerase Chain Reaction) analysis showed that BGISEQ-500 sequencing platform could truly reflect gene expression patterns. It also verified that GID1B (GIBBERELLIN INSENSITIVE DWARF1 B), GID1C, SPL8 (SQUAMOSA PROMOTER BINDING PROTEIN-LIKE 8), and GASA (GIBBERELLIC ACID-STIMULATED ARABIDOPSIS) family genes were expressed at high levels, while the expression of SPY (SPINDLY) was low during spring and summer flowering initiation. Meanwhile, the up- and down-regulated expression of, respectively, AGL6 (AGAMOUS-LIKE 6) and DREB3 (DEHYDRATION-RESPONSIVE ELEMENT-BINDING PROTEIN 3), AG15, and CDF1 (CYCLIC DOF FACTOR 1) might also be involved in the specific regulation of spring and summer flowering initiation. Obviously, flowering initiation is an important stage of the flowering process in woody plants, involving the specific regulation of relevant genes and transcription factors. This study provides a new perspective for the regulation of the flowering process in perennial woody plants.

Reflectance spectra reconstruction from trichromatic camera based on kernel partial least square method.

A novel spectral reflectance reconstruction method based on kernel partial least square (KPLS) regression is proposed. The proposed method integrates the partial least square algorithm and kernel function to estimate the reflectance spectra from 9-channel multispectral imaging system using commercial trichromatic camera. The performance of the proposed method is demonstrated in comparison with the existing methods using simulated and real camera responses from Munsell Matte color and IT8.7/3 dataset. The experimental results show that the proposed method is superior or at least equivalent to its counterparts and satisfactory enough for color management purpose.

Classification and influencing factors analysis of facial skin color in Chinese population.

BACKGROUND: Subjective evaluation and quantitative analysis of skin color are very important both in dermatology and in cosmetology, but results of existing objective classifications tend to be incompatible to visual perception of skin color among females and males in China. METHODS: Skin color at four facial skin sites was measured in 409 volunteers with 219 males and 190 females aged 20-79 years. Ten observers with normal color vision assessed facial skin color of 205 subjects. The relationship between visual scores and Chardon's individual typology angle (ITA°) values was investigated. Then, the variations of color in different sub-groups were comprehensively discussed by skin color data of 409 volunteers. RESULTS: In order to better characterize Chinese skin color, the redness parameter must be added into the ITA formula. By comparing skin color of Chinese living in different environments or with different lifestyles, some factors not conducive to brightening skin have been identified. CONCLUSION: This study indicated the different influence of skin color components on perceived brightness between Caucasian and Chinese. And skin color was significantly affected by related variables such as gender, age, working environment, and lifestyles. Therefore, this study suggests how to brighten skin color in daily life.

Spectra estimation from raw camera responses based on adaptive local-weighted linear regression.

An improved spectral reflectance estimation method is developed to transform raw camera RGB responses to spectral reflectance. The novelty of our method is to apply a local weighted linear regression model for spectral reflectance estimation and construct the weighting matrix using a Gaussian function in CIELAB uniform color space. The proposed method was tested using both a standard color chart and a set of textile samples, with a digital RGB camera and by ten times ten-fold cross-validation. The results demonstrate that our method gives the best accuracy in estimating both the spectral reflectance and the colorimetric values in comparison with existing methods.

Superpixel segmentation and pigment identification of colored relics based on visible spectral image.

To enrich the contents of digital archive and to guide the copy and restoration of colored relics, non-invasive methods for extraction of painting boundary and identification of pigment composition are proposed in this study based on the visible spectral images of colored relics. Superpixel concept is applied for the first time to the field of oversegmentation of visible spectral images and implemented on the visible spectral images of colored relics to extract their painting boundary. Since different pigments are characterized by their own spectrum and the same kind of pigment has the similar geometric profile in spectrum, an automatic identification method is established by comparing the proximity between the geometric profiles of the unknown spectrum from each superpixel and the pre-known spectrum from a deliberately prepared database. The methods are validated using the visible spectral images of the ancient wall paintings in Mogao Grottoes. By the way, the visible spectral images are captured by a multispectral imaging system consisting of two broadband filters and a RGB camera with high spatial resolution.

[Research on Visual Perception-Referenced Compression Method for Multi-Spectral Data with High-Fidelity].

Aim In order to maintain the chromaticity precision in the process of linear compression of the multispectral data, a visual perception-referenced compression method (VPCM) based on the chroma gradient (refer to the partial derivative of chroma to wavelength) is proposed. Method The method firstly successfully developed the transfer functions which could synchronously fusion the spectral features and chromaticity characteristics of human visuals based on the nonlinear analytic feature of human visual system. For further improvement the transfer function, a modified optimizing function was developed to help find out the optimal transfer direction for different sample sets. If the transfer function was finally settled, it will be applied to transforming the spectral data of the sample set (Γ(S)=C). Then the transformed spectral data of the sample set will be compressed with high chromatic accuracy by the principle components analysis method. After that, the compressed data will be reconstructed through inverse transformation (Γ(-1)(C)=), while the reconstructed spectral data will be using to evaluate the effective of the proposed VPCM method. Result Four groups typical and representative sample sets were chosen to test the effective of the proposed method. The CIELab color difference in the D50/2° calculates condition and a proposed mean metamerism index (MMI) calculated with 75 groups typical light sources (including tungsten, fluorescent and LED lamp) was adopted as evaluating metrics. Eventually, the comparative experiment involving several existing methods Lab-PQR and 2-XYZ indicates that the proposed VPCM hold the best chromatic accuracy both for metric MMI and the average color difference ΔE(ab) when compared with Lab-PQR and 2-XYZ, and the spectral accuracy was calculated between Lab-PQR and 2-XYZ with Lab-PQR maintained the highest spectral accuracy. Conclusion The proposed VPCM can preserve high compression chromatic precision at the price of small loss of spectral precision and possess good colorimetric stability under variable reference conditions. It is very applicable for some application fields which require compressing of the multi-spectral data with high chromatic accuracy.

Updated version of an interim connection space LabPQR for spectral color reproduction: LabLab.

In this paper, we propose a new interim connection space (ICS) called LabLab, which is an updated version of LabPQR, to overcome the drawback that the last three dimensions of LabPQR have no definite colorimetric meanings. We extended and improved the method by which the first three dimensions of LabPQR are deduced to obtain an ICS consisting of two sets of CIELAB values under different illuminants, and the reconstructed spectra from LabLab were obtained by minimizing colorimetric errors by means of the computational formula of the CIE-XYZ tristimulus values combined with least-squares best fit. The improvement obtained from the proposed method was tested to compress and reconstruct the reflectance spectra of the 1950 Natural Color System color chips and more than 50,000 ISO SOCS color patches as well as six multispectral images acquired by multispectral image acquisition systems using 1600 glossy Munsell color chips as training samples. The performance was evaluated by the mean values of color differences between the original and reconstructed spectra under the CIE 1931 standard colorimetric observer and the CIE standard illuminants D50, D55, D65, D75, F2, F7, F11, and A as well as five multichip white LED light sources. The mean and maximum values of the root mean square errors between the original and reconstructed spectra were also calculated. The experimental results show that the proposed three LabLab interim connection spaces significantly outperform principal component analysis, LabPQR, XYZLMS, Fairman-Brill, and LabRGB in colorimetric reconstruction accuracy at the cost of slight reduction of spectral reconstruction accuracy and illuminant independence of color differences of the suggested LabLab interim connection spaces outperform other interim connection spaces. In addition, the presented LabLab interim connection spaces could be quite compatible with the extensively used colorimetric management system since each dimension has definite colorimetric meanings and is perceptually uniform.

In Situ Identification of Pigment Composition and Particle Size on Wall Paintings Using Visible Spectroscopy as a Noninvasive Measurement Method.

Noninvasive examination methods of chemical composition and particle size are presented here based on visible spectroscopy to achieve the identification and recording of mineral pigments used on ancient wall paintings. The normalized spectral curve, slope and curvature extracted from visible spectral reflectance are combined with adjustable weighting coefficients to construct the identification feature space, and Euclid distances between spectral reflectance from wall paintings and a reference database are calculated in the feature space as the discriminant criterion to identify the chemical composition of mineral pigments. A parametric relationship between the integral quantity of spectral reflectance and logarithm of mean particle size is established using a quadratic polynomial to accomplish the noninvasive prediction of mineral pigment particle size used on ancient wall paintings. The feasibility of the proposed methods is validated by the in situ nondestructive identification of the wall paintings in the Mogao Grottoes at Dunhuang. Chinese painting styles and historical evolution are then analyzed according to the identification results of 16 different grottoes constructed from the Sixteen Kingdoms to the Yuan Dynasty.

[Iterated Tikhonov Regularization for Spectral Recovery from Tristimulus].

Reflective spectra in a multispectral image can objectively and originally represent color information due to their high dimensionality, illuminant independent and device independent. Aiming to the problem of loss of spectral information when the spectral data reconstructed from three-dimensional colorimetric data in the trichromatic camera-based spectral image acquisition system and its subsequent problem of loss of color information, this work proposes an iterated Tikhonov regularization to reconstruct the reflectance spectra. First of all, according to relationship between the colorimetric value and the reflective spectra in the colorimetric theory, this work constructs a spectral reconstruction equation which can reconstruct high dimensional spectral data from three dimensional colorimetric data acquired by the trichromatic camera. Then, the iterated Tikhonov regularization, inspired by the idea of the pseudo inverse Moore-Penrose, is used to cope with the linear ill-posed inverse problem during solving the equation of reconstructing reflectance spectra. Meanwhile, the work also uses the L-curve method to obtain an optimal regularized parameter of the iterated Tikhonov regularization by training a set of samples. Through these methods, the ill condition of the spectral reconstruction equation can be effectively controlled and improved, and subsequently loss of spectral information of the reconstructed spectral data can be reduced. The verification experiment is performed under another set of training samples. The experimental results show that the proposed method reconstructs the reflective spectra with less spectral information loss in the trichromatic camera-based spectral image acquisition system, which reflects in obvious decreases of spectral errors and colorimetric errors compared with the previous method.

[Research on the Training Samples Selection for Spectral Reflectance Reconstruction Based on Principal Component Analysis].

The composition of training samples set is an important influence factor of spectral reflectance reconstruction process. Representative color samples selection for learning-based spectral reflectance reconstruction is discussed in this paper. A method based on Principal Component Analysis (PCA) is proposed to perform sample selection. First of all, a part of samples are selected according to the minimum Euclidean distance criteria in terms of camera response value from a large number of samples, which aim to ensure the similarity between training samples and target samples. Then the PCA data processing method is applied to these samples after removing the duplicate samples. The samples with larger principal component loadings are regarded as the representative color samples. Different thresholds for each principal component are used to make decision whether the loading of sample is large enough. In order to validate the proposed method, the selected samples are used as training samples to recover the spectral reflectance of color patches. A real multi-channel imaging system by loading broadband color filters in front of lens is used in the experiment to acquire the multi-channel image dataset. In this paper the pseudo-inverse method is employed to reconstruct spectral reflectance of target color patches. It is shown that the proposed method is superior to the previous methods in spectral reconstruction accuracy and can meet the requirements of high precision color reproduction.

[Research on Developping the Colorimetric Correction Method Based on Wide Gamut Spectral Color Dataset].

In cross-media digital color imaging workflow, the colorimetric information transform among various digital medias always suffers from large transform errors, due to the difference among the lighting illuminants and the digital devices. Colorimetric correction aims at avoiding the colorimetric transform mismatch and thus improving the color transform accuracy comprehensively. Till now, two kinds of colorimetric transform methods have been proposed, which are the chromatic adaptation transform and the regression-based transform. However, since the color gamut of the training samples of such two method are both small, adopting those methods in colorimetric domain always leads to large colorimetric transform errors for the high saturated color regions. In this research, in order to reduce the large correction error in high saturated color regions, a modified colorimetric correction method basing on a wide gamut spectral dataset was proposed. The wide gamut spectral dataset was built by comprehensively collecting and producing typical spectral color samples and could provide optimal training samples for the existing regression based colorimetric correction model, with the help of gamut partition and optimal color purity choosing. By modifying the existing method with such samples, the colorimetric correction performance obviously improved. The experimental result shows that the modified colorimetric correction method performs significantly better than the existing methods and the colorimetric correction errors are successfully reduced by around 15% according to proposed method in form of CIEDE2000 color difference, while as for the high saturated color regions the reduction rate of the colorimetric correction errors approximately grows to 40%. The authors believe that the proposed method will provided effective support for the development of digital color imaging in near future.

[Optimization Study of Non-Contact Color Measurement Parameters].

Spectral data or chrominance data acquired with color measurement device is able to objectively characterize the true color information of the object. As to the measuring target that without direct contact with the measuring instrument, it needs to adopt the non-contact color measurement method to obtain the color information.The spectral irradiance theoretical analysis shows that the changes of the color illumination distance, measuring distance and exposure time have greater impact on the measurement results. However, there is no in-depth study on the influence of the changes of measuring parameters for the measured results. In order to get the most accurate measurement results in the process of non-contact color measurement, parameter optimization study based on orthogonal experiment was proposed. Experiment with different combinations of parameters was conducted to obtain the color information of ColorChecker via PR705 spectroradiometer with range analysis and variance analysis method.Experimental results show that the minimum color difference of measured value and the standard value is 0.878 8ΔE, and the maximum color difference is 1.543 1ΔE. Data results show that the proposed method can effectively select the best combination of parameters, and to analyze the impact of various parameters on the result.