A Metastatic Cancer Expression Generator (MetGen): A Generative Contrastive Learning Framework for Metastatic Cancer Generation.

Despite significant advances in tumor biology and clinical therapeutics, metastasis remains the primary cause of cancer-related deaths. While RNA-seq technology has been used extensively to study metastatic cancer characteristics, challenges persist in acquiring adequate transcriptomic data. To overcome this challenge, we propose MetGen, a generative contrastive learning tool based on a deep learning model. MetGen generates synthetic metastatic cancer expression profiles using primary cancer and normal tissue expression data. Our results demonstrate that MetGen generates comparable samples to actual metastatic cancer samples, and the cancer and tissue classification yields performance rates of 99.8 ± 0.2% and 95.0 ± 2.3%, respectively. A benchmark analysis suggests that the proposed model outperforms traditional generative models such as the variational autoencoder. In metastatic subtype classification, our generated samples show 97.6% predicting power compared to true metastatic samples. Additionally, we demonstrate MetGen's interpretability using metastatic prostate cancer and metastatic breast cancer. MetGen has learned highly relevant signatures in cancer, tissue, and tumor microenvironments, such as immune responses and the metastasis process, which can potentially foster a more comprehensive understanding of metastatic cancer biology. The development of MetGen represents a significant step toward the study of metastatic cancer biology by providing a generative model that identifies candidate therapeutic targets for the treatment of metastatic cancer.

Nanorod-like Bimetallic Oxide for Enhancing the Performance of Supercapacitor Electrodes.

Supercapacitors are widely used in many fields owing to their advantages, such as high power, good cycle performance, and fast charging speed. Among the many metal-oxide cathode materials reported for supercapacitors, NiMoO4 is currently the most promising electrode material for high-specific-energy supercapacitors. We have employed a rational design approach to create a nanorod-like NiMoO4 structure, which serves as a conductive scaffold for supercapacitors; the straightforward layout has led to outstanding results, with nanorod-shaped NiMoO4 exhibiting a remarkable capacity of 424.8 F g-1 at 1 A g-1 and an impressive stability of 80.2% capacity preservation even after 3500 cycles, which surpasses those of the majority of previously reported NiMoO4 materials. NiMoO4//AC supercapacitors demonstrate a remarkable energy density of 46.31 W h kg-1 and a power density of 0.75 kW kg-1. This synthesis strategy provides a facile method for the fabrication of bimetallic oxide materials for high-performance supercapacitors.

Landscape of Epstein-Barr virus gene expression and perturbations in cancer.

Epstein-Barr virus (EBV) is the causative agent for multiple neoplastic diseases of epithelial and lymphocytic origin1-3. The heterogeneity of the viral elements expressed and the mechanisms by which these coding and non-coding genes maintain cancer cell properties in vivo remain elusive4,5. Here we conducted a multi-modal transcriptomic analysis of EBV-associated neoplasms and identified that the ubiquitously expressed RPMS1 non-coding RNAs support cancer cell properties by disruption of the interferon response. Our map of EBV expression shows a variable, but pervasive expression of BNLF2 discerned from the overlapping LMP1 RNA in bulk sequencing data. Using long-read single-molecule sequencing, we identified three new viral elements within the RPMS1 gene. Furthermore, single-cell sequencing datasets allowed for the separation of cancer cells and healthy cells from the same tissue biopsy and the characterization of a microenvironment containing interferon gamma excreted by EBV-stimulated T-lymphocytes. In comparison with healthy epithelium, EBV-transformed cancer cells exhibited increased proliferation and inhibited immune response induced by the RPMS1-encoded microRNAs. Our atlas of EBV expression shows that the EBV-transformed cancer cells express high levels of non-coding RNAs originating from RPMS1 and that the oncogenic properties are maintained by RPMS1 microRNAs. Through bioinformatic disentanglement of single cells from cancer tissues we identified a positive feedback loop where EBV-activated immune cells stimulate cancer cells to proliferate, which in turn undergo viral reactivation and trigger an immune response.

Is milk fat globule size correlated with milk fat content in Ruminants?

In milk, fat exists in the form of milk fat globules (MFGs). The average size (average fat globules of different particle sizes) is the most common parameter when describing MFG size. There are different views on whether there is a correlation between MFG size and milk fat content. Is the MFG size correlated with milk fat content in ruminants? To address this question, we conducted two experiments. In experiment Ⅰ, dairy cows (n = 40) and dairy goats (n = 30) were each divided into a normal group and a low-fat group according to the milk fat content. In experiment Ⅱ, dairy cows (n = 16) and dairy goats (n = 12) were each divided into a normal group and a conjugated linoleic acid (CLA)-induced low-fat group. The normal groups were fed a basal diet, and the CLA-induced low-fat groups were fed the basal diet + 300 g/d CLA (cows) or the basal diet + 90 g/d CLA (goats). In both experiments, we determined the correlation between MFG size and milk composition and MFG distribution. The results showed that in the normal and low-fat groups of cows and goats, MFG size was not correlated with milk fat, protein, or lactose content or fat-to-protein ratio. Additionally, there was no difference in the distribution of large, medium, and small MFGs (P > 0.05). However, in the CLA-induced low-fat groups, we found a correlation between MFG size and milk fat content and fat-to-protein ratio (R2 > 0.3). Moreover, there was a significant change in the size distribution of MFGs. Therefore, in natural milk, MFG size was not correlated with milk fat content. Following CLA supplementation, MFG size was correlated with milk fat content. Our findings revealed that CLA and not milk fat affects MFG distribution and size.

Electrically programmable magnetic coupling in an Ising network exploiting solid-state ionic gating.

Two-dimensional arrays of magnetically coupled nanomagnets provide a mesoscopic platform for exploring collective phenomena as well as realizing a broad range of spintronic devices. In particular, the magnetic coupling plays a critical role in determining the nature of the cooperative behavior and providing new functionalities in nanomagnet-based devices. Here, we create coupled Ising-like nanomagnets in which the coupling between adjacent nanomagnetic regions can be reversibly converted between parallel and antiparallel through solid-state ionic gating. This is achieved with the voltage-control of the magnetic anisotropy in a nanosized region where the symmetric exchange interaction favors parallel alignment and the antisymmetric exchange interaction, namely the Dzyaloshinskii-Moriya interaction, favors antiparallel alignment of the nanomagnet magnetizations. Applying this concept to a two-dimensional lattice, we demonstrate a voltage-controlled phase transition in artificial spin ices. Furthermore, we achieve an addressable control of the individual couplings and realize an electrically programmable Ising network, which opens up new avenues to design nanomagnet-based logic devices and neuromorphic computers.

Molecular and immune signatures, and pathological trajectories of fatal COVID-19 lungs defined by in situ spatial single-cell transcriptome analysis.

Despite intensive studies during the last 3 years, the pathology and underlying molecular mechanism of coronavirus disease 2019 (COVID-19) remain poorly defined. In this study, we investigated the spatial single-cell molecular and cellular features of postmortem COVID-19 lung tissues using in situ sequencing (ISS). We detected 10 414 863 transcripts of 221 genes in whole-slide tissues and segmented them into 1 719 459 cells that were mapped to 18 major parenchymal and immune cell types, all of which were infected by SARS-CoV-2. Compared with the non-COVID-19 control, COVID-19 lungs exhibited reduced alveolar cells (ACs) and increased innate and adaptive immune cells. We also identified 19 differentially expressed genes in both infected and uninfected cells across the tissues, which reflected the altered cellular compositions. Spatial analysis of local infection rates revealed regions with high infection rates that were correlated with high cell densities (HIHD). The HIHD regions expressed high levels of SARS-CoV-2 entry-related factors including ACE2, FURIN, TMPRSS2 and NRP1, and co-localized with organizing pneumonia (OP) and lymphocytic and immune infiltration, which exhibited increased ACs and fibroblasts but decreased vascular endothelial cells and epithelial cells, mirroring the tissue damage and wound healing processes. Sparse nonnegative matrix factorization (SNMF) analysis of niche features identified seven signatures that captured structure and immune niches in COVID-19 tissues. Trajectory inference based on immune niche signatures defined two pathological routes. Trajectory A primarily progressed with increased NK cells and granulocytes, likely reflecting the complication of microbial infections. Trajectory B was marked by increased HIHD and OP, possibly accounting for the increased immune infiltration. The OP regions were marked by high numbers of fibroblasts expressing extremely high levels of COL1A1 and COL1A2. Examination of single-cell RNA-seq data (scRNA-seq) from COVID-19 lung tissues and idiopathic pulmonary fibrosis (IPF) identified similar cell populations consisting mainly of myofibroblasts. Immunofluorescence staining revealed the activation of IL6-STAT3 and TGF-ß-SMAD2/3 pathways in these cells, likely mediating the upregulation of COL1A1 and COL1A2 and excessive fibrosis in the lung tissues. Together, this study provides a spatial single-cell atlas of cellular and molecular signatures of fatal COVID-19 lungs, which reveals the complex spatial cellular heterogeneity, organization, and interactions that characterized the COVID-19 lung pathology.

Utilizing ANN for Predicting the Cauchy Stress and Lateral Stretch of Random Elastomeric Foams under Uniaxial Loading.

As a result of their cell structures, elastomeric foams exhibit high compressibility and are frequently used as buffer cushions in energy absorption. Foam pads between two surfaces typically withstand uniaxial loads. In this paper, we considered the effects of porosity and cell size on the mechanical behavior of random elastomeric foams, and proposed a constitutive model based on an artificial neural network (ANN). Uniform cell size distribution was used to represent monodisperse foam. The constitutive relationship between Cauchy stress and the four input variables of axial stretch λU, lateral stretch λL, porosity φ, and cell size θ was given by con-ANN. The mechanical responses of 500 different foam structures (20% < φ < 60%, 0.1 mm < θ < 0.5 mm) under compression and tension loads (0.4 < λU < 3) were simulated, and a dataset containing 100,000 samples was constructed. We also introduced a pre-ANN to predict lateral stretch to address the issue of missing lateral strain data in practical applications. By combining physical experience, we chose appropriate input forms and activation functions to improve ANN's extrapolation capability. The results showed that pre-ANN and con-ANN could provide reasonable predictions for λU outside the dataset. We can obtain accurate lateral stretch and axial stress predictions from two ANNs. The porosity affects the stress and λL, while the cell size only affects the stress during foam compression.

Imaging and positioning through scattering media with double-helix point spread function engineering.

Significance: Double-helix point spread function (DH-PSF) microscopy has been developed for three-dimensional (3D) localization and imaging at super-resolution but usually in environments with no or weak scattering. To date, super-resolution imaging through turbid media has not been reported. Aim: We aim to explore the potential of DH-PSF microscopy in the imaging and localization of targets in scattering environments for improved 3D localization accuracy and imaging quality. Approach: The conventional DH-PSF method was modified to accommodate the scanning strategy combined with a deconvolution algorithm. The localization of a fluorescent microsphere is determined by the center of the corresponding double spot, and the image is reconstructed from the scanned data by deconvoluting the DH-PSF. Results: The resolution, i.e., the localization accuracy, was calibrated to 13 nm in the transverse plane and 51 nm in the axial direction. Penetration thickness could reach an optical thickness (OT) of 5. Proof-of-concept imaging and the 3D localization of fluorescent microspheres through an eggshell membrane and an inner epidermal membrane of an onion are presented to demonstrate the super-resolution and optical sectioning capabilities. Conclusions: Modified DH-PSF microscopy can image and localize targets buried in scattering media using super-resolution. Combining fluorescent dyes, nanoparticles, and quantum dots, among other fluorescent probes, the proposed method may provide a simple solution for visualizing deeper and clearer in/through scattering media, making in situ super-resolution microscopy possible for various demanding applications.

Screening of an epigenetic compound library identifies BRD4 as a potential antiviral target for hepatitis B virus covalently closed circular DNA transcription.

HBV cccDNA is the persistent form of viral genome, which exists in host cell nucleus as an episomal minichromosome decorated with histone and non-histone proteins. cccDNA is the authentic viral transcription template and resistant to current antivirals. Growing evidence shows that the transcriptional activity of cccDNA minichromosome undergoes epigenetic regulations, suggesting a new perspective for anti-cccDNA drug development through targeting histone modifications. In this study, we screened an epigenetic compound library in the cccDNA reporter cell line HepBHAe82, which produces the HA-tagged HBeAg in a cccDNA-dependent manner. Among the obtained hits, a bromodomain-containing protein 4 (BRD4) inhibitor MS436 exhibited marked inhibition of cccDNA transcription in both HBV stable cell line HepAD38 and HepG2-NTCP or primary human hepatocyte infection system under noncytotoxic concentrations. Chromatin immunoprecipitation (ChIP) assay demonstrated that MS436 dramatically reduced the enrichment of H3K27ac, an activating histone modification pattern, on cccDNA minichromosome. RNAseq differential analysis showed that MS436 does not drastically change host transcriptome or induce any known anti-HBV factors/pathways, indicating a direct antiviral effect of MS436 on cccDNA minichromosome. Interestingly, the MS436-mediated inhibition of cccDNA transcription is accompanied by cccDNA destabilization in HBV infection and a recombinant cccDNA system, indicating that BRD4 activity may also play a role in cccDNA maintenance. Furthermore, depletion of BRD4 by siRNA knockdown or PROTAC degrader resulted in cccDNA inhibition in HBV-infected HepG2-NTCP cells, further validating BRD4 as an antiviral target. Taken together, our study has demonstrated the practicability of HepBHAe82-based anti-HBV drug screening system and provided a proof-of-concept for targeting HBV cccDNA with epigenetic compounds.

Unmasking the biological function and regulatory mechanism of NOC2L: a novel inhibitor of histone acetyltransferase.

NOC2 like nucleolar associated transcriptional repressor (NOC2L) was recently identified as a novel inhibitor of histone acetyltransferase (INHAT). NOC2L is found to have two INHAT function domains and regulates histone acetylation in a histone deacetylases (HDAC) independent manner, which is distinct from other INHATs. In this review, we summarize the biological function of NOC2L in histone acetylation regulation, P53-mediated transcription, ribosome RNA processing, certain development events and carcinogenesis. We propose that NOC2L may be explored as a potential biomarker and a therapeutic target in clinical practice.

Suppression of Packet Losses and Disturbances in Networked Control Systems Based on Equivalent-Input-Disturbance Approach.

This article presents a method of suppressing packet losses and exogenous disturbances for a networked control system (NCS) subject to network-introduced delays. The NCS has two feedback loops: 1) a local one and 2) a main one. The local feedback loop contains a state observer, an equivalent-input-disturbance (EID) estimator, and state feedback. It is used to ensure prompt disturbance suppression. The controller in the main feedback loop contains an internal model to track a reference input. The system is divided into two subsystems for the design of controllers. The state-observer gain is designed for one subsystem using the concept of perfect regulation to ensure disturbance estimation performance. The state-feedback gains of the other subsystem are designed based on a stability condition in the form of a linear matrix inequality (LMI). A tracking specification is embedded in the LMI-based stability condition to ensure satisfactory tracking performance. A case study on a two-finger robot hand control system and a comparison with a Smith-EID and H∞ controller approach validate the effectiveness and superiority of the presented method.

4D label-free quantitative proteomics analysis to screen potential drug targets of Jiangu Granules treatment for postmenopausal osteoporotic rats.

Background: Postmenopausal osteoporosis (PMOP) is a disease with a high prevalence in postmenopausal women and is characterized by an imbalance in bone metabolism, reduced bone mass, and increased risk of fracture due to estrogen deficiency. Jiangu granules (JG) is a compound prescription used in traditional Chinese medicine to treat PMOP. However, its definitive mechanism in PMOP is unclear. This study used a 4D label-free quantitative proteomics method to explore the potential therapeutic mechanism of JG in an ovariectomy (OVX) rats' model. Materials and methods: A rat model of PMOP was established by removing the ovaries bilaterally. Nine 3-month-old specific-pathogen-free female SD rats. The nine rats were randomly divided into 3 groups (n = 3 in each group): the sham-operated group (J), the ovariectomy group (NC), and the JG treatment (ZY) group. Proteins extracted from the bone tissue of the lumbar spine (L3, L4) of three groups of rats were analyzed by 4D label-free quantitative proteomics, and proteins differentially expressed after JG treatment and proteins differentially expressed after de-ovulation were intersected to identify proteins associated with the mechanism of PMOP by JG treatment. Result: There were 104 up-regulated and 153 down-regulated differentially expressed proteins (DEPs) in the J group vs. NC group, 107 up-regulated and 113 down-regulated DEPs in the J group vs. ZY group, and 15 up-regulated and 32 down-regulated DEPs in the NC group vs. ZY group. Six potential target proteins for JG regulation of osteoblast differentiation in OVX rats were identified by taking intersections of differential proteins in the J group vs. NC group and NC group vs. ZY group. Conclusion: JG may exert therapeutic effects by modulating the expression levels of target proteins associated with osteoblast differentiation to enhance osteoblast differentiation in OVX rats. These results further uncovered the target proteins and specific mechanisms of JG in treating PMOP, providing an experimental basis for the clinical application of JG in treating PMOP.

The effect of high altitude environment on diesel engine performance: Comparison of engine operations in Hangzhou, Kunming and Lhasa cities.

The all-area operating performance of the vehicles requires the development of diesel engines that can operate at high altitudes without significant performance deterioration. Prior to optimizing the efficiency and emissions of highland engines, there is a necessity to investigate the underlying causes of engine performance degradation. The purpose of this paper was to study the in-cylinder activities occurring in the combustion chamber of diesel engines at high altitudes, which can help explain the effect of altitude on engine efficiency and emissions of concern to the customer. Specifically, a turbocharged direct injection compression ignition engine was operated at a constant engine speed and load, but at different altitudes. The theoretical analyses based on experimental data suggested that the mismatch between air and diesel quantities caused by the high altitude atmosphere led to the engine combustion deterioration. Specifically, the lower gas density at high altitudes during fuel injection resulted in a reduction of the injection angle and an enhancement of the penetration capability. In addition, the rise in altitude extended the ignition delay, which increased the fuel fraction mixed with air in the premixed combustion stage and raised the pressure rise rate. Moreover, at high altitudes, the reduction in excess air ratio and increased possibility of wall impingement of the fuel droplets resulted in uneven mixture concentration distribution and reduced air utility. Accordingly, combustion deterioration occurred in the combustion chamber of the plateau engines, which reduced energy release during main mixing-controlled combustion, lowered combustion efficiency, increased exhaust energy, and raised engine-out incomplete combustion emissions. All these effects resulted in a decrease in engine thermal efficiency of ∼6.5% and an increase in soot emissions of ∼4.2 times from Hangzhou to Lhasa city for the engine and operating conditions investigated in this study. Consequently, engines operating in highland areas need to be optimized in terms of efficiency and emissions.

Isoandrographolide from Andrographis paniculata ameliorates tubulointerstitial fibrosis in ureteral obstruction-induced mice, associated with negatively regulating AKT/GSK-3ß/ß-cat signaling pathway.

Tubulointerstitial fibrosis (TIF) is a prominent pathological manifestation for the progression of almost all chronic kidney diseases (CKDs) to end-stage renal failure. However, there exist few efficient therapies to cure TIF. Our recent results showed that (8R, 12S)-isoandrographolide (ISA), a diterpenoid lactone ingredient of traditional Chinese herbal Andrographis paniculata (Burm.f.) Nees, exhibited anti-pulmonary fibrosis in silica-induced mice. Herein, we investigated the therapeutic effect of ISA on TIF, using mice subjected to unilateral ureteral obstruction (UUO) and human kidney proximal tubular epithelial (HK-2) cells treated with transforming growth factor-ß1 (TGF-ß1) or tumor necrosis factor-α (TNF-α). The pathological changes and collagen deposition results displayed that ISA administration significantly attenuated inflammatory response, ameliorated TIF, and protected the kidney injury. Interestingly, ISA revealed much lower cytotoxicity on HK-2 cells, but exhibited stronger inhibitory effect on tubular epithelial mesenchymal transformation (EMT) and inflammation, as compared to andrographolide (AD), the major ingredient of A. paniculata extract that has been reported to ameliorate TIF in diabetic nephropathy mice. It was further clarified that the amelioration of TIF by ISA was associated with suppressing the aberrant activation of AKT/GSK-3ß/ß-catenin pathway through network pharmacology analysis and experimental validation. Taken together, these findings indicate that ISA is a promising lead compound for development of anti-TIF, and even broad-spectrum anti-fibrotic drugs.

Neutralizing antibodies to SARS-CoV-2 variants of concern including Delta and Omicron in subjects receiving mRNA-1273, BNT162b2, and Ad26.COV2.S vaccines.

SARS-CoV-2 vaccines have contributed to the control of COVID-19 in some parts of the world. However, the constant emergence of variants of concern (VOCs) challenges the effectiveness of SARS-CoV-2 vaccines over time. In particular, Omicron contains a high number of mutations in the spike (S) protein gene, on which most vaccines were developed. In this study, we quantitated neutralizing antibodies in vaccine recipients at various times postvaccination using S protein-based pseudoviruses derived from wild type (WT) SARS-CoV-2 and five VOCs including Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (B.1.1.529). We found that two-dose mRNA-1273 and BNT162b2 vaccines elicited robust neutralizing antibodies against WT, Alpha, Beta, Gamma, and Delta, but wanned after 6 months with a faster decline observed for BNT162b2. Both mRNA-1273 and BNT162b2 elicited weak neutralizing antibodies against Omicron. One dose of Ad26.COV2.S vaccine induced weaker neutralizing antibodies against WT and most VOCs than mRNA-1273 and BNT162b2 did but moderate neutralizing antibodies against Delta and Omicron, which lasted for 6 months. These results support current recommendations of the Centers for Disease Control and Prevention for a booster 5 months after full immunization with an mRNA-based vaccine and the use of an mRNA-based vaccine 2 months after Ad26.COV2.S vaccination.

Toward Top-Down Just Noticeable Difference Estimation of Natural Images.

Just noticeable difference (JND) of natural images refers to the maximum pixel intensity change magnitude that typical human visual system (HVS) cannot perceive. Existing efforts on JND estimation mainly dedicate to modeling the diverse masking effects in either/both spatial or/and frequency domains, and then fusing them into an overall JND estimate. In this work, we turn to a dramatically different way to address this problem with a top-down design philosophy. Instead of explicitly formulating and fusing different masking effects in a bottom-up way, the proposed JND estimation model dedicates to first predicting a critical perceptual lossless (CPL) counterpart of the original image and then calculating the difference map between the original image and the predicted CPL image as the JND map. We conduct subjective experiments to determine the critical points of 500 images and find that the distribution of cumulative normalized KLT coefficient energy values over all 500 images at these critical points can be well characterized by a Weibull distribution. Given a testing image, its corresponding critical point is determined by a simple weighted average scheme where the weights are determined by a fitted Weibull distribution function. The performance of the proposed JND model is evaluated explicitly with direct JND prediction and implicitly with two applications including JND-guided noise injection and JND-guided image compression. Experimental results have demonstrated that our proposed JND model can achieve better performance than several latest JND models. In addition, we also compare the proposed JND model with existing visual difference predicator (VDP) metrics in terms of the capability in distortion detection and discrimination. The results indicate that our JND model also has a good performance in this task. The code of this work are available at https://github.com/Zhentao-Liu/KLT-JND.

CeCaFLUX: the first web server for standardized and visual instationary 13C metabolic flux analysis.

SUMMARY: The number of instationary 13C-metabolic flux (INST-MFA) studies grows every year, making it more important than ever to ensure the clarity, standardization and reproducibility of each study. We proposed CeCaFLUX, the first user-friendly web server that derives metabolic flux distribution from instationary 13C-labeled data. Flux optimization and statistical analysis are achieved through an evolutionary optimization in a parallel manner. It can visualize the flux optimizing process in real-time and the ultimate flux outcome. It will also function as a database to enhance the consistency and to facilitate sharing of flux studies. AVAILABILITY AND IMPLEMENTATION: CeCaFLUX is freely available at https://www.cecaflux.net, the source code can be downloaded at https://github.com/zhzhd82/CeCaFLUX. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

[Clinical Characteristics and Prognosis of 76 Lung Adenocarcinoma Patients 
Harboring EGFR Mutations with Pleural Effusion at Initial Diagnosis: 
A Single-center Retrospective Study].

BACKGROUND: Malignant pleural effusion is one of the common clinical manifestations of patients with lung adenocarcinoma. Patients with pleural effusion at the initial diagnosis of lung adenocarcinoma usually indicate poor prognosis. Epidermal growth factor receptor (EGFR) mutations mainly occur in patients with lung adenocarcinoma. Patients with different mutant subtypes have different prognosis. The clinical characteristics and prognostic factors of patients with EGFR mutated lung adenocarcinoma of different molecular subtypes combined with pleural effusion at initial diagnosis are still unclear. This study was designed to explore the clinical characteristics and prognostic factors of these patients in order to provide management recommendations for them. METHODS: A retrospective analysis of the clinical characteristics, treatment, outcomes and progression-free survival (PFS) of first-line treatment in patients with EGFR mutated lung adenocarcinoma combined with pleural effusion at initial diagnosis admitted to Department of Medical Oncology and Radiation Sickness, Peking University Third Hospital from January 2012 to June 2021 was performed. Pearson's chi-square test or Fisher's exact test were performed for comparison between groups. Kaplan-Meier method was performed for survival analysis and Cox proportional risk regression model was performed for multivariate analysis. RESULTS: 76 patients met the inclusion criteria in this study. The incidences of EGFR classical mutations 19del, 21L858R and non-classical mutations were 46.0%, 38.2% and 15.8%, respectively among these patients. There was no significant difference between the three mutations in terms of gender, age, presence of dyspnea at presentation, whether other distant metastases were combined, site of pleural effusion, volume of pleural effusion, presence of other combined effusions, tumor-node-metastasis (TNM) stage, presence of other gene mutations, and treatment of pleural effusion (P>0.05). In patients with EGFR classical mutations 19del or 21L858R or non-classical mutations subtype, the proportion of chemotherapy in first-line regimens were 17.1%, 20.7% and 58.3%, respectively (P=0.001); and first-line disease control rates were 94.3%, 75.9% and 50%, respectively (P=0.003); pleural effusion control rates were 94.3%, 79.3% and 66.7%, respectively (P=0.04); PFS were 287 d, 327 d and 55 d, respectively (P=0.001). Univariate analysis showed that EGFR mutation subtype, control of pleural effusion, first-line treatment agents, and first-line treatment efficacy were significantly associated with PFS (P<0.05). Cox multifactorial analysis showed that only EGFR mutation subtype and first-line treatment efficacy were independent prognostic factors for PFS (P<0.05). CONCLUSIONS: PFS was significantly better for classical mutations than for non-classical mutations in patients with EGFR mutated lung adenocarcinoma combined with pleural effusion at initial diagnosis. Improving the efficacy of first-line therapy is the key to improve the prognosis of these patients.

Single Image Super-Resolution Quality Assessment: A Real-World Dataset, Subjective Studies, and an Objective Metric.

Numerous single image super-resolution (SISR) algorithms have been proposed during the past years to reconstruct a high-resolution (HR) image from its low-resolution (LR) observation. However, how to fairly compare the performance of different SISR algorithms/results remains a challenging problem. So far, the lack of comprehensive human subjective study on large-scale real-world SISR datasets and accurate objective SISR quality assessment metrics makes it unreliable to truly understand the performance of different SISR algorithms. We in this paper make efforts to tackle these two issues. Firstly, we construct a real-world SISR quality dataset (i.e., RealSRQ) and conduct human subjective studies to compare the performance of the representative SISR algorithms. Secondly, we propose a new objective metric, i.e., KLTSRQA, based on the Karhunen-Loéve Transform (KLT) to evaluate the quality of SISR images in a no-reference (NR) manner. Experiments on our constructed RealSRQ and the latest synthetic SISR quality dataset (i.e., QADS) have demonstrated the superiority of our proposed KLTSRQA metric, achieving higher consistency with human subjective scores than relevant existing NR image quality assessment (NR-IQA) metrics. The dataset and the code will be made available at https://github.com/Zhentao-Liu/RealSRQ-KLTSRQA.

A glycolysis-related two-gene risk model that can effectively predict the prognosis of patients with rectal cancer.

BACKGROUND: Aerobic glycolysis is an emerging hallmark of cancer. Although some studies have constructed glycolysis-related prognostic models of colon adenocarcinoma (COAD) based on The Cancer Genome Atlas (TCGA) database, whether the COAD glycolysis-related prognostic model is appropriate for distinguishing the prognosis of rectal adenocarcinoma (READ) patients remains unknown. Exploring critical and specific glycolytic genes related to READ prognosis may help us discover new potential therapeutic targets for READ patients. RESULTS: Three gene sets, HALLMARK_GLYCOLYSIS, REACTOME_GLYCOLYSIS and REACTOME_REGULATION_OF_GLYCOLYSIS_BY_FRUCTOSE_2_6_BISPHOSPHATE_METABOLISM, were both significantly enriched in both COAD and READ through glycolysis-related gene set enrichment analysis (GSEA). We found that six genes (ANKZF1, STC2, SUCLG2P2, P4HA1, GPC1 and PCK1) were independent prognostic genes in COAD, while TSTA3 and PKP2 were independent prognostic genes in READ. Glycolysis-related prognostic model of COAD and READ was, respectively, constructed and assessed in COAD and READ. We found that the glycolysis-related prognostic model of COAD was not appropriate for READ, while glycolysis-related prognostic model of READ was more appropriate for READ than for COAD. PCA and t-SNE analysis confirmed that READ patients in two groups (high and low risk score groups) were distributed in discrete directions based on the glycolysis-related prognostic model of READ. We found that this model was an independent prognostic indicator through multivariate Cox analysis, and it still showed robust effectiveness in different age, gender, M stage, and TNM stage. A nomogram combining the risk model of READ with clinicopathological characteristics was established to provide oncologists with a practical tool to evaluate the rectal cancer outcomes. GO enrichment and KEGG analyses confirmed that differentially expressed genes (DEGs) were enriched in several glycolysis-related molecular functions or pathways based on glycolysis-related prognostic model of READ. CONCLUSIONS: We found that a glycolysis-related prognostic model of COAD was not appropriate for READ, and we established a novel glycolysis-related two-gene risk model to effectively predict the prognosis of rectal cancer patients.