CPADS: a web tool for comprehensive pancancer analysis of drug sensitivity.

Drug therapy is vital in cancer treatment. Accurate analysis of drug sensitivity for specific cancers can guide healthcare professionals in prescribing drugs, leading to improved patient survival and quality of life. However, there is a lack of web-based tools that offer comprehensive visualization and analysis of pancancer drug sensitivity. We gathered cancer drug sensitivity data from publicly available databases (GEO, TCGA and GDSC) and developed a web tool called Comprehensive Pancancer Analysis of Drug Sensitivity (CPADS) using Shiny. CPADS currently includes transcriptomic data from over 29 000 samples, encompassing 44 types of cancer, 288 drugs and more than 9000 gene perturbations. It allows easy execution of various analyses related to cancer drug sensitivity. With its large sample size and diverse drug range, CPADS offers a range of analysis methods, such as differential gene expression, gene correlation, pathway analysis, drug analysis and gene perturbation analysis. Additionally, it provides several visualization approaches. CPADS significantly aids physicians and researchers in exploring primary and secondary drug resistance at both gene and pathway levels. The integration of drug resistance and gene perturbation data also presents novel perspectives for identifying pivotal genes influencing drug resistance. Access CPADS at https://smuonco.shinyapps.io/CPADS/ or https://robinl-lab.com/CPADS.

The Holothuria leucospilota genome elucidates sacrificial organ expulsion and bioadhesive trap enriched with amyloid-patterned proteins.

Some tropical sea cucumbers of the family Holothuriidae can efficiently repel or even fatally ensnare predators by sacrificially ejecting a bioadhesive matrix termed the Cuvierian organ (CO), so named by the French zoologist Georges Cuvier who first described it in 1831. Still, the precise mechanisms for how adhesiveness genetically arose in CO and how sea cucumbers perceive and transduce danger signals for CO expulsion during defense have remained unclear. Here, we report the first high-quality, chromosome-level genome assembly of Holothuria leucospilota, an ecologically significant sea cucumber with prototypical CO. The H. leucospilota genome reveals characteristic long-repeat signatures in CO-specific outer-layer proteins, analogous to fibrous proteins of disparate species origins, including spider spidroin and silkworm fibroin. Intriguingly, several CO-specific proteins occur with amyloid-like patterns featuring extensive intramolecular cross-ß structures readily stainable by amyloid indicator dyes. Distinct proteins within the CO connective tissue and outer surface cooperate to give the expelled matrix its apparent tenacity and adhesiveness, respectively. Genomic evidence offers further hints that H. leucospilota directly transduces predator-induced mechanical pressure onto the CO surface through mediation by transient receptor potential channels, which culminates in acetylcholine-triggered CO expulsion in part or in entirety. Evolutionarily, innovative events in two distinct regions of the H. leucospilota genome have apparently spurred CO's differentiation from the respiratory tree to a lethal defensive organ against predators.

High-density stable glasses formed on soft substrates.

Enabled by surface-mediated equilibration, physical vapour deposition can create high-density stable glasses comparable with liquid-quenched glasses aged for millions of years. Deposition is often performed at various rates and temperatures on rigid substrates to control the glass properties. Here we demonstrate that on soft, rubbery substrates, surface-mediated equilibration is enhanced up to 170 nm away from the interface, forming stable glasses with densities up to 2.5% higher than liquid-quenched glasses within 2.5 h of deposition. Gaining similar properties on rigid substrates would require 10 million times slower deposition, taking ~3,000 years. Controlling the modulus of the rubbery substrate provides control over the glass structure and density at constant deposition conditions. These results underscore the significance of substrate elasticity in manipulating the properties of the mobile surface layer and thus the glass structure and properties, allowing access to deeper states of the energy landscape without prohibitively slow deposition rates.

PESSA: A web tool for pathway enrichment score-based survival analysis in cancer.

The activation levels of biologically significant gene sets are emerging tumor molecular markers and play an irreplaceable role in the tumor research field; however, web-based tools for prognostic analyses using it as a tumor molecular marker remain scarce. We developed a web-based tool PESSA for survival analysis using gene set activation levels. All data analyses were implemented via R. Activation levels of The Molecular Signatures Database (MSigDB) gene sets were assessed using the single sample gene set enrichment analysis (ssGSEA) method based on data from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), The European Genome-phenome Archive (EGA) and supplementary tables of articles. PESSA was used to perform median and optimal cut-off dichotomous grouping of ssGSEA scores for each dataset, relying on the survival and survminer packages for survival analysis and visualisation. PESSA is an open-access web tool for visualizing the results of tumor prognostic analyses using gene set activation levels. A total of 238 datasets from the GEO, TCGA, EGA, and supplementary tables of articles; covering 51 cancer types and 13 survival outcome types; and 13,434 tumor-related gene sets are obtained from MSigDB for pre-grouping. Users can obtain the results, including Kaplan-Meier analyses based on the median and optimal cut-off values and accompanying visualization plots and the Cox regression analyses of dichotomous and continuous variables, by selecting the gene set markers of interest. PESSA (https://smuonco.shinyapps.io/PESSA/ OR http://robinl-lab.com/PESSA) is a large-scale web-based tumor survival analysis tool covering a large amount of data that creatively uses predefined gene set activation levels as molecular markers of tumors.

Integrated Exploration of Epigenetic Dysregulation Reveals a Stemness/EMT Subtype and MMP12 Linked to the Progression and Prognosis in Hepatocellular Carcinoma.

Epigenetic dysregulation drives aberrant transcriptional programs playing a critical role in hepatocellular carcinoma (HCC), which may provide novel insights into the heterogeneity of HCC. This study performed an integrated exploration on the epigenetic dysregulation of miRNA and methylation. We discovered and validated three patterns endowed with gene-related transcriptional traits and clinical outcomes. Specially, a stemness/epithelial-mesenchymal transition (EMT) subtype was featured by immune exhaustion and the worst prognosis. Besides, MMP12, a characteristic gene, was highly expressed in the stemness/EMT subtype, which was verified as a pivotal regulator linked to the unfavorable prognosis and further proven to promote tumor proliferation, invasion, and metastasis in vitro experiments. Proteomic analysis by mass spectrometry sequencing also indicated that the overexpression of MMP12 was significantly associated with cell proliferation and adhesion. Taken together, this study unveils innovative insights into epigenetic dysregulation and identifies a stemness/EMT subtype-specific gene, MMP12, correlated with the progression and prognosis of HCC.

Cellular Ligand-Receptor Perturbations Unravel MEIS2 as a Key Factor for the Aggressive Progression and Prognosis in Stage II/III Colorectal Cancer.

Approximately 10-15% of stage II and 25-30% of stage III colorectal cancer (CRC) patients experience recurrence within 5 years after surgery, and existing taxonomies are insufficient to meet the needs of clinical precision treatment. Thus, robust biomarkers and precise management were urgently required to stratify stage II and III CRC and identify potential patients who will benefit from postoperative adjuvant therapy. Alongside, interactions of ligand-receptor pairs point to an emerging direction in tumor signaling with far-reaching implications for CRC, while their impact on tumor subtyping has not been elucidated. Herein, based on multiple large-sample multicenter cohorts and perturbations of the ligand-receptor interaction network, four well-characterized ligand-receptor-driven subtypes (LRDS) were established and further validated. These molecular taxonomies perform with unique heterogeneity in terms of molecular characteristics, immune and mutational landscapes, and clinical features. Specifically, MEIS2, a key LRDS4 factor, performs significant associations with proliferation, invasion, migration, and dismal prognosis of stage II/III CRC, revealing promising directions for prognostic assessment and individualized treatment of CRC patients. Overall, our study sheds novel insights into the implications of intercellular communication on stage II/III CRC from a ligand-receptor interactome perspective and revealed MEIS2 as a key factor in the aggressive progression and prognosis for stage II/III CRC.

Pirfenidone inhibits TGF-ß1-induced metabolic reprogramming during epithelial-mesenchymal transition in non-small cell lung cancer.

Metastasis is an important contributor to increased mortality rates in non-small cell lung cancer (NSCLC). The TGF-ß signalling pathway plays a crucial role in facilitating tumour metastasis through epithelial-mesenchymal transition (EMT). Glycolysis, a key metabolic process, is strongly correlated with NSCLC metastasis. Pirfenidone (PFD) has been shown to safely and effectively inhibit TGF-ß1 in patients with lung diseases. Furthermore, TGF-ß1 and glycolysis demonstrate an interdependent relationship within the tumour microenvironment. Our previous study demonstrated that PFD effectively inhibited glycolysis in NSCLC cells, prompting further investigation into its potential antitumour effects in this context. Therefore, the present study aims to investigate the potential antitumour effect of PFD in NSCLC and explore the relationship among TGF-ß1, glycolysis and EMT through further experimentation. The antitumour effects of PFD were evaluated using five different NSCLC cell lines and a xenograft tumour model. Notably, PFD demonstrated a significant antitumour effect specifically in highly glycolytic H1299 cells. To elucidate the underlying mechanism, we compared the efficacy of PFD after pretreatment with either TGF-ß1 or a TGF-ß receptor inhibitor (LY2109761). The energy metabolomics analysis of tumour tissue demonstrated that PFD, a chemosensitizing agent, reduced lactate and ATP production, thereby inhibiting glycolysis and exerting synergistic antineoplastic effects. Additionally, PFD combined with cisplatin targeted TGF-ß1 to inhibit glycolysis during EMT and enhanced the chemosensitization of A549 and H1299 cells. The magnitude of the anticancer effect exhibited by PFD was intricately linked to its metabolic properties.

PC4-mediated Ku complex PARylation facilitates NHEJ-dependent DNA damage repair.

Radiotherapy is one of the mainstay treatments for hepatocellular carcinoma (HCC). However, a substantial number of patients with HCC develop radioresistance and eventually suffer from tumor progression or relapse, which is a major impediment to the use of radiotherapy. Therefore, elucidating the mechanisms underlying radioresistance and identifying novel therapeutic targets to improve patient prognosis are important in HCC management. In this study, using in vitro and in vivo models, laser microirradiation and live cell imaging methods, and coimmunoprecipitation assays, we report that a DNA repair enhancer, human positive cofactor 4 (PC4), promotes nonhomologous end joining-based DNA repair and renders HCC cells resistant to radiation. Mechanistically, PC4 interacts with poly (ADP-ribose) polymerase 1 and directs Ku complex PARylation, resulting in the successful recruitment of the Ku complex to damaged chromatin and increasing the efficiency of nonhomologous end joining repair. Clinically, PC4 is highly expressed in tumor tissues and is correlated with poor prognosis in patients with HCC. Taken together, our data suggest that PC4 is a DNA repair driver that can be targeted to radiosensitize HCC cells.

Regio- and Stereoselective Transfer Hydrogenation of Aryloxy Group-Substituted Unsymmetrical 1,2-Diketones: Synthetic Applications and Mechanistic Studies.

Developing a general method that leads to the formation of different classes of chiral bioactive compounds and their stereoisomers is an attractive but challenging research topic in organic synthesis. Furthermore, despite the great value of asymmetric transfer hydrogenation (ATH) in both organic synthesis and the pharmaceutical industry, the monohydrogenation of unsymmetrical 1,2-diketones remains underdeveloped. Here, we report the aryloxy group-assisted highly regio-, diastereo-, and enantioselective ATH of racemic 1,2-diketones. The work produces a myriad of enantioenriched dihydroxy ketones, and further transformations furnish all eight stereoisomers of diaryl triols, polyphenol, emblirol, and glycerol-type natural products. Mechanistic studies and calculations reveal two working modes of the aryloxy group in switching the regioselectivity from a more reactive carbonyl to a less reactive one, and the potential of ATH on 1,2-diketones in solving challenging synthetic issues has been clearly demonstrated.

CTLs heterogeneity and plasticity: implications for cancer immunotherapy.

Cytotoxic T lymphocytes (CTLs) play critical antitumor roles, encompassing diverse subsets including CD4+, NK, and γδ T cells beyond conventional CD8+ CTLs. However, definitive CTLs biomarkers remain elusive, as cytotoxicity-molecule expression does not necessarily confer cytotoxic capacity. CTLs differentiation involves transcriptional regulation by factors such as T-bet and Blimp-1, although epigenetic regulation of CTLs is less clear. CTLs promote tumor killing through cytotoxic granules and death receptor pathways, but may also stimulate tumorigenesis in some contexts. Given that CTLs cytotoxicity varies across tumors, enhancing this function is critical. This review summarizes current knowledge on CTLs subsets, biomarkers, differentiation mechanisms, cancer-related functions, and strategies for improving cytotoxicity. Key outstanding questions include refining the CTLs definition, characterizing subtype diversity, elucidating differentiation and senescence pathways, delineating CTL-microbe relationships, and enabling multi-omics profiling. A more comprehensive understanding of CTLs biology will facilitate optimization of their immunotherapy applications. Overall, this review synthesizes the heterogeneity, regulation, functional roles, and enhancement strategies of CTLs in antitumor immunity, highlighting gaps in our knowledge of subtype diversity, definitive biomarkers, epigenetic control, microbial interactions, and multi-omics characterization. Addressing these questions will refine our understanding of CTLs immunology to better leverage cytotoxic functions against cancer.

Development and validation of a radiosensitivity model to evaluate radiotherapy benefits in pan-cancer.

Radiotherapy, one of the most fundamental cancer treatments, is confronted with the dilemma of treatment failure due to radioresistance. To predict the radiosensitivity and improve tumor treatment efficiency in pan-cancer, we developed a model called Radiation Intrinsic Sensitivity Evaluation (RISE). The RISE model was built using cell line-based mRNA sequencing data from five tumor types with varying radiation sensitivity. Through four cell-derived datasets, two public tissue-derived cohorts, and one local cohort of 42 nasopharyngeal carcinoma patients, we demonstrated that RISE could effectively predict the level of radiation sensitivity (area under the ROC curve [AUC] from 0.666 to 1 across different datasets). After the verification by the colony formation assay and flow cytometric analysis of apoptosis, our four well-established radioresistant cell models successfully proved higher RISE values in radioresistant cells by RT-qPCR experiments. We also explored the prognostic value of RISE in five independent TCGA cohorts consisting of 1137 patients who received radiation therapy and found that RISE was an independent adverse prognostic factor (pooled multivariate Cox regression hazard ratio [HR]: 1.84, 95% CI 1.39-2.42; p < 0.01). RISE showed a promising ability to evaluate the radiotherapy benefit while predicting the prognosis of cancer patients, enabling clinicians to make individualized radiotherapy strategies in the future and improve the success rate of radiotherapy.

Oxidative stress is involved in immunosuppression and macrophage regulation in glioblastoma.

Oxidative stress dually affected cancer progression, while its effect on glioblastomas remained unclear. Herein, we clustered the multicenter glioblastoma cohorts based on the oxidative-stress-responsive genes (OSS) expression. We found that cluster 2 with high OSS levels suffered a worse prognosis. Functional analyses and immune-related analyses results exhibited that M2-like pro-tumoral macrophages and neutrophils were enriched in cluster 2, while Natural killer cells' infiltration was decreased. The increased M2-like pro-tumoral macrophages in cluster 2 was confirmed by immunofluorescence. An integrated single-cell analysis validated the malignant features of cluster 2 neoplastic cells and discovered their crosstalk with M2-like pro-tumoral macrophages. Moreover, we observed that SOD3 knockdown might decrease the M2-like pro-tumoral transformation of macrophage in vitro and in vivo. Comprehensively, we revealed oxidative stress' prognostic and immunosuppressive potential in glioblastoma and discovered SOD3's potential role in regulating macrophage M2-like pro-tumoral transformation.

Hydrophilic 1T-WS2 Nanosheet Arrays toward Conductive Textiles for High-Efficient and Continuous Hydroelectric Generation and Storage.

Flexible hydroelectric generators (HEGs) are promising self-powered devices that spontaneously derive electrical power from moisture. However, achieving the desired compatibility between a continuous operating voltage and superior current density remains a significant challenge. Herein, a textile-based van der Waals heterostructure is rationally designed between conductive 1T phase tungsten disulfide@carbonized silk (1T-WS2@CSilk) and carbon black@cotton (CB@Cotton) fabrics with an asymmetric distribution of oxygen-containing functional groups, which enhances the proton concentration gradients toward high-performance wearable HEGs. The vertically staggered 1T-WS2 nanosheet arrays on the CSilk fabric provide abundant hydrophilic nanochannels for rapid carrier transport. Furthermore, the moisture-induced primary battery formed between the active aluminum (Al) electrode and the conductive textiles introduces the desired electric field to facilitate charge separation and compensate for the decreased streaming potential. These devices exhibit a power density of 21.6 µW cm-2, an open-circuit voltage (Voc) of 0.65 V sustained for over 10 000 s, and a current density of 0.17 mA cm-2. This performance makes them capable of supplying power to commercial electronics and human respiratory monitoring. This study presents a promising strategy for the refined design of wearable electronics.

CAMOIP: a web server for comprehensive analysis on multi-omics of immunotherapy in pan-cancer.

Immune checkpoint inhibitors (ICIs) have completely changed the approach pertaining to tumor diagnostics and treatment. Similarly, immunotherapy has also provided much needed data about mutation, expression and prognosis, affording an unprecedented opportunity for discovering candidate drug targets and screening for immunotherapy-relevant biomarkers. Although existing web tools enable biologists to analyze the expression, mutation and prognostic data of tumors, they are currently unable to facilitate data mining and mechanism analyses specifically related to immunotherapy. Thus, we effectively developed our own web-based tool, called Comprehensive Analysis on Multi-Omics of Immunotherapy in Pan-cancer (CAMOIP), in which we are able to successfully screen various prognostic markers and analyze the mechanisms involved in biomarker expression and function, as well as immunotherapy. The analyses include information relevant to survival analysis, expression analysis, mutational landscape analysis, immune infiltration analysis, immunogenicity analysis and pathway enrichment analysis. This comprehensive analysis of biomarkers for immunotherapy can be carried out by a click of CAMOIP, and the software should greatly encourage the further development of immunotherapy. CAMOIP provides invaluable evidence that bridges the information between the data of cancer genomics based on immunotherapy, providing comprehensive information to users and assisting in making the value of current ICI-treated data available to all users. CAMOIP is available at https://www.camoip.net.

Machine learning-based tumor-infiltrating immune cell-associated lncRNAs for predicting prognosis and immunotherapy response in patients with glioblastoma.

Long noncoding ribonucleic acids (RNAs; lncRNAs) have been associated with cancer immunity regulation. However, the roles of immune cell-specific lncRNAs in glioblastoma (GBM) remain largely unknown. In this study, a novel computational framework was constructed to screen the tumor-infiltrating immune cell-associated lncRNAs (TIIClnc) for developing TIIClnc signature by integratively analyzing the transcriptome data of purified immune cells, GBM cell lines and bulk GBM tissues using six machine learning algorithms. As a result, TIIClnc signature could distinguish survival outcomes of GBM patients across four independent datasets, including the Xiangya in-house dataset, and more importantly, showed superior performance than 95 previously established signatures in gliomas. TIIClnc signature was revealed to be an indicator of the infiltration level of immune cells and predicted the response outcomes of immunotherapy. The positive correlation between TIIClnc signature and CD8, PD-1 and PD-L1 was verified in the Xiangya in-house dataset. As a newly demonstrated predictive biomarker, the TIIClnc signature enabled a more precise selection of the GBM population who would benefit from immunotherapy and should be validated and applied in the near future.

Large-scale genome-wide association studies reveal the genetic causal etiology between air pollutants and autoimmune diseases.

BACKGROUND: Epidemiological evidence links a close correlation between long-term exposure to air pollutants and autoimmune diseases, while the causality remained unknown. METHODS: Two-sample Mendelian randomization (TSMR) was used to investigate the role of PM10, PM2.5, NO2, and NOX (N = 423,796-456,380) in 15 autoimmune diseases (N = 14,890-314,995) using data from large European GWASs including UKB, FINNGEN, IMSGC, and IPSCSG. Multivariable Mendelian randomization (MVMR) was conducted to investigate the direct effect of each air pollutant and the mediating role of common factors, including body mass index (BMI), alcohol consumption, smoking status, and household income. Transcriptome-wide association studies (TWAS), two-step MR, and colocalization analyses were performed to explore underlying mechanisms between air pollution and autoimmune diseases. RESULTS: In TSMR, after correction of multiple testing, hypothyroidism was causally associated with higher exposure to NO2 [odds ratio (OR): 1.37, p = 9.08 × 10-4] and NOX [OR: 1.34, p = 2.86 × 10-3], ulcerative colitis (UC) was causally associated with higher exposure to NOX [OR: 2.24, p = 1.23 × 10-2] and PM2.5 [OR: 2.60, p = 5.96 × 10-3], rheumatoid arthritis was causally associated with higher exposure to NOX [OR: 1.72, p = 1.50 × 10-2], systemic lupus erythematosus was causally associated with higher exposure to NOX [OR: 4.92, p = 6.89 × 10-3], celiac disease was causally associated with lower exposure to NOX [OR: 0.14, p = 6.74 × 10-4] and PM2.5 [OR: 0.17, p = 3.18 × 10-3]. The risky effects of PM2.5 on UC remained significant in MVMR analyses after adjusting for other air pollutants. MVMR revealed several common mediators between air pollutants and autoimmune diseases. Transcriptional analysis identified specific gene transcripts and pathways interconnecting air pollutants and autoimmune diseases. Two-step MR revealed that POR, HSPA1B, and BRD2 might mediate from air pollutants to autoimmune diseases. POR pQTL (rs59882870, PPH4=1.00) strongly colocalized with autoimmune diseases. CONCLUSION: This research underscores the necessity of rigorous air pollutant surveillance within public health studies to curb the prevalence of autoimmune diseases.

OralExplorer: a web server for exploring the mechanisms of oral inflammatory diseases.

BACKGROUND: Oral inflammatory diseases are localized infectious diseases primarily caused by oral pathogens with the potential for serious systemic complications. However, publicly available datasets for these diseases are underutilized. To address this issue, a web tool called OralExplorer was developed. This tool integrates the available data and provides comprehensive online bioinformatic analysis. METHODS: Human oral inflammatory disease-related datasets were obtained from the GEO database and normalized using a standardized process. Transcriptome data were then subjected to differential gene expression analysis, immune infiltration analysis, correlation analysis, pathway enrichment analysis, and visualization. The single-cell sequencing data was visualized as cluster plot, feature plot, and heatmaps. The web platform was primarily built using Shiny. The biomarkers identified in OralExplorer were validated using local clinical samples through qPCR and IHC. RESULTS: A total of 35 human oral inflammatory disease-related datasets, covering 6 main disease types and 901 samples, were included in the study to identify potential molecular signatures of the mechanisms of oral diseases. OralExplorer consists of 5 main analysis modules (differential gene expression analysis, immune infiltration analysis, correlation analysis, pathway enrichment analysis and single-cell analysis), with multiple visualization options. The platform offers a simple and intuitive interface, high-quality images for visualization, and detailed analysis results tables for easy access by users. Six markers (IL1ß, SRGN, CXCR1, FGR, ARHGEF2, and PTAFR) were identified by OralExplorer. qPCR- and IHC-based experimental validation showed significantly higher levels of these genes in the periodontitis group. CONCLUSIONS: OralExplorer is a comprehensive analytical platform for oral inflammatory diseases. It allows users to interactively explore the molecular mechanisms underlying the action and regression of these diseases. It also aids dental researchers in unlocking the potential value of transcriptomics data related to oral diseases. OralExplorer can be accessed at https://smuonco.shinyapps.io/OralExplorer/  (Alternate URL: http://robinl-lab.com/OralExplorer ).

Potential anti-tumor effects of regulatory T cells in the tumor microenvironment: a review.

Regulatory T cells (Tregs) expressing the transcription factor FoxP3 are essential for maintaining immunological balance and are a significant component of the immunosuppressive tumor microenvironment (TME). Single-cell RNA sequencing (ScRNA-seq) technology has shown that Tregs exhibit significant plasticity and functional diversity in various tumors within the TME. This results in Tregs playing a dual role in the TME, which is not always centered around supporting tumor progression as typically believed. Abundant data confirms the anti-tumor activities of Tregs and their correlation with enhanced patient prognosis in specific types of malignancies. In this review, we summarize the potential anti-tumor actions of Tregs, including suppressing tumor-promoting inflammatory responses and boosting anti-tumor immunity. In addition, this study outlines the spatial and temporal variations in Tregs function to emphasize that their predictive significance in malignancies may change. It is essential to comprehend the functional diversity and potential anti-tumor effects of Tregs to improve tumor therapy strategies.

Wavelength encoding spectral imaging based on the combination of deeply learned filters and an RGB camera.

Hyperspectral imaging is a critical tool for gathering spatial-spectral information in various scientific research fields. As a result of improvements in spectral reconstruction algorithms, significant progress has been made in reconstructing hyperspectral images from commonly acquired RGB images. However, due to the limited input, reconstructing spectral information from RGB images is ill-posed. Furthermore, conventional camera color filter arrays (CFA) are designed for human perception and are not optimal for spectral reconstruction. To increase the diversity of wavelength encoding, we propose to place broadband encoding filters in front of the RGB camera. In this condition, the spectral sensitivity of the imaging system is determined by the filters and the camera itself. To achieve an optimal encoding scheme, we use an end-to-end optimization framework to automatically design the filters' transmittance functions and optimize the weights of the spectral reconstruction network. Simulation experiments show that our proposed spectral reconstruction network has excellent spectral mapping capabilities. Additionally, our novel joint wavelength encoding imaging framework is superior to traditional RGB imaging systems. We develop the deeply learned filter and conduct actual shooting experiments. The spectral reconstruction results have an attractive spatial resolution and spectral accuracy.

Correlation between second and first primary cancer: systematic review and meta-analysis of 9 million cancer patients.

BACKGROUND: Many survivors of a first primary cancer (FPCs) are at risk of developing a second primary cancer (SPC), with effects on patient prognosis. Primary cancers have different frequencies of specific SPC development and the development of SPCs may be closely related to the FPC. The aim of this study was to explore possible correlations between SPCs and FPCs. METHODS: Relevant literature on SPCs was retrospectively searched and screened from four databases, namely, PubMed, EMBASE, Web of Science, and PMC. Data on the number of patients with SPC in 28 different organ sites were also collected from The Surveillance, Epidemiology, and End Results (SEER) 8 Registry and NHANES database. RESULTS: A total of 9 617 643 patients with an FPC and 677 430 patients with an SPC were included in the meta-analysis. Patients with a first primary gynaecological cancer and thyroid cancer frequently developed a second primary breast cancer and colorectal cancer. Moreover, those with a first primary head and neck cancer, anal cancer and oesophageal cancer developed a second primary lung cancer more frequently. A second primary lung cancer and prostate cancer was also common among patients with first primary bladder cancer and penile cancer. Patients with second primary bladder cancer accounted for 56% of first primary ureteral cancer patients with SPCs. CONCLUSIONS: This study recommends close clinical follow-up, monitoring and appropriate interventions in patients with relevant FPCs for better screening and early diagnosis of SPCs.