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Gene expression patterns can be used as prognostic biomarkers in various types of cancers. We aimed to identify a gene expression pattern for individual distant metastatic risk assessment in patients with locoregionally advanced nasopharyngeal carcinoma. In this multicentre, retrospective, cohort analysis, we included 937 patients with locoregionally advanced nasopharyngeal carcinoma from three Chinese hospitals: the Sun Yat-sen University Cancer Center (Guangzhou, China), the Affiliated Hospital of Guilin Medical University (Guilin, China), and the First People's Hospital of Foshan (Foshan, China). Using microarray analysis, we profiled mRNA gene expression between 24 paired locoregionally advanced nasopharyngeal carcinoma tumours from patients at Sun Yat-sen University Cancer Center with or without distant metastasis after radical treatment. Differentially expressed genes were examined using digital expression profiling in a training cohort (Guangzhou training cohort; n=410) to build a gene classifier using a penalised regression model. We validated the prognostic accuracy of this gene classifier in an internal validation cohort (Guangzhou internal validation cohort, n=204) and two external independent cohorts (Guilin cohort, n=165; Foshan cohort, n=158). The primary endpoint was distant metastasis-free survival. Secondary endpoints were disease-free survival and overall survival. We identified 137 differentially expressed genes between metastatic and non-metastatic locoregionally advanced nasopharyngeal carcinoma tissues. A distant metastasis gene signature for locoregionally advanced nasopharyngeal carcinoma (DMGN) that consisted of 13 genes was generated to classify patients into high-risk and low-risk groups in the training cohort. Patients with high-risk scores in the training cohort had shorter distant metastasis-free survival (hazard ratio [HR] 4·93, 95% CI 2·99–8·16; p<0·0001), disease-free survival (HR 3·51, 2·43–5·07; p<0·0001), and overall survival (HR 3·22, 2·18–4·76; p<0·0001) than patients with low-risk scores. The prognostic accuracy of DMGN was validated in the internal and external cohorts. Furthermore, among patients with low-risk scores in the combined training and internal cohorts, concurrent chemotherapy improved distant metastasis-free survival compared with those patients who did not receive concurrent chemotherapy (HR 0·40, 95% CI 0·19–0·83; p=0·011), whereas patients with high-risk scores did not benefit from concurrent chemotherapy (HR 1·03, 0·71–1·50; p=0·876). This was also validated in the two external cohorts combined. We developed a nomogram based on the DMGN and other variables that predicted an individual's risk of distant metastasis, which was strengthened by adding Epstein–Barr virus DNA status. The DMGN is a reliable prognostic tool for distant metastasis in patients with locoregionally advanced nasopharyngeal carcinoma and might be able to predict which patients benefit from concurrent chemotherapy. It has the potential to guide treatment decisions for patients at different risk of distant metastasis. The National Natural Science Foundation of China, the National Science & Technology Pillar Program during the Twelfth Five-year Plan Period, the Natural Science Foundation of Guang Dong Province, the National Key Research and Development Program of China, the Innovation Team Development Plan of the Ministry of Education, the Health & Medical Collaborative Innovation Project of Guangzhou City, China, and the Program of Introducing Talents of Discipline to Universities.

Concrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete mixtures. The concrete mix design methods currently used in engineering practice are joint analytical and laboratory procedures derived from the Three Equation Method and do not perform well enough for the needs of modern concrete technology. This often causes difficulties in predicting the final properties of the designed mix and leads to precautionary oversizing of concrete properties for fear of not providing the required parameters. A new approach that would make it possible to predict the newly designed concrete mix properties is highly desirable. The answer to this challenge can be methods based on machine learning, which have been intensively developed in recent years, especially in predicting concrete compressive strength. Machine learning-based methods have been more or less successful in predicting concrete compressive strength, but they do not reflect well the variability that characterises the currently used concrete mixes. A new adaptive solution that allows estimating concrete compressive strength on the basis of the concrete mix main ingredient composition by including two observations for a given batch of concrete is proposed herein. In presented study, a machine learning model was built with a deep neural network architecture, trained on an extensive database of concrete recipes, and translated into a mathematical formula. Testing on four concrete mix recipes was performed, which were calculated according to contemporary design methods (Bolomey and Fuller method), and a comparative analysis was conducted. It was found out that the new algorithm performs significantly better than that without adaptive features trained on the same dataset. The presented algorithm can be used as a concrete strength checking tool for the concrete mix design process.

Intratumoral heterogeneity is the main cause of tumor treatment failure, varying across disease sites (spatial heterogeneity) and polyclonal properties of tumors that evolve over time (temporal heterogeneity). As our understanding of intratumoral heterogeneity, the formation of which is mainly related to the genomic instability, epigenetic modifications, plastic gene expression, and different microenvironments, plays a substantial role in drug-resistant as far as tumor metastasis and recurrence. Understanding the role of intratumoral heterogeneity, it becomes clear that a single therapeutic agent or regimen may only be effective for subsets of cells with certain features, but not for others. This necessitates a shift from our current, unchanging treatment approach to one that is tailored against the killing patterns of cancer cells in different clones. In this review, we discuss recent evidence concerning global perturbations of intratumoral heterogeneity, associations of specific intratumoral heterogeneity in lung cancer, the underlying mechanisms of intratumoral heterogeneity potentially leading to formation, and how it drives drug resistance. Our findings highlight the most up-to-date progress in intratumoral heterogeneity and its role in mediating tumor drug resistance, which could support the development of future treatment strategies.

Although various types of drugs and therapies are available to treat atherosclerosis, it remains a major cause of mortality throughout the world. Macrophages are the major source of foam cells, which are hallmarks of atherosclerotic lesions. Consequently, the roles of macrophages in the pathophysiology of atherosclerosis are increasingly investigated. Autophagy is a self-protecting cellular catabolic pathway. Since its discovery, autophagy has been found to be associated with a variety of diseases, including cardiovascular diseases, malignant tumors, neurodegenerative diseases, and immune system disorders. Accumulating evidence demonstrates that autophagy plays an important role in inhibiting inflammation and apoptosis, and in promoting efferocytosis and cholesterol efflux. These facts sug- gest the induction of autophagy may be exploited as a potential strategy for the treatment of atherosclerosis. In this review we mainly discuss the relationship between macrophage autophagy and atherosclerosis and the molecular mechanisms, as well as the recent advances in targeting the process of autophagy to treat atherosclerosis.

Diabetic retinopathy (DR) is a common complication of diabetes and has been recognized as a vascular dysfunction leading to blindness in working-age adults. It becomes increasingly clear that neural cells in retina play an important role in the pathogenesis of DR. Neural retina located at the back of the eye is part of the brain and a representative of the central nervous system. The neurosensory deficits seen in DR are related to inflammation and occur prior to the clinically identifiable vascular complications. The neural deficits are associated with abnormal reactions of retina glial cells and neurons in response to hyperglycemia. Improper activation of the innate immune system may also be an important contributor to the pathophysiology of DR. Therefore, DR manifests characteristics of both vasculopathy and chronic neuroinflammatory diseases. In this article, we attempt to provide an overview of the current understanding of inflammation in neural retina abnormalities in diabetes. Inhibition of neuroinflammation may represent a novel therapeutic strategy to the prevention of the progression of DR.

Inflammasomes are newly recognized, vital players in innate immunity. The best characterized is the NLRP3 inflammasome, so-called because the NLRP3 protein in the complex belongs to the family of nucleotide-binding and oligomerization domain-like receptors (NLRs) and is also known as \"pyrin domain-containing protein 3\". The NLRP3 inflammasome is associated with onset and progression of various diseases, including metabolic disorders, multiple sclerosis, inflammatory bowel disease, cryopyrin-associated periodic fever syndrome, as well as other auto-immune and auto-inflammatory diseases. Several NLRP3 inflammasome inhibitors have been described, some of which show promise in the clinic. The present review will describe the structure and mechanisms of activation of the NLRP3 inflammasome, its association with various auto-immune and auto-inflammatory diseases, and the state of research into NLRP3 inflammasome inhibitors.

Central nervous system (CNS) is one of the largest killers of people's health all over the world. The overactivation of the immune and inflammatory responses is considered as an important factor, contributing to the pathogenesis and progression of CNS disorders. Among all kinds of immune and inflammatory reaction, the inflammasome, a complex of proteins, has been drawn increasingly attention to by researchers. The initiation and activation of the inflammasome is involved in the onset of various kinds of diseases. The NLRP3 inflammasome, the most studied member of the inflammasome, is closely associated with many kinds of CNS disorders. Here in this review, the roles of the NLRP3 inflammasome in the pathogenesis and progression of several well-known CNS diseases would be discussed, including cerebrovascular diseases, neurodegenerative diseases, multiple sclerosis, depression as well as other CNS disorders. In addition, several therapeutic strategies targeting on the NLRP3 inflammasome for the treatment of CNS disorders would be described in this review.

Proline accumulation is a common response to salt stress in many plants. Salt stress also increased proline concentration in roots, stems, and leaves of Kosteletzkya virginica seedling treated with 300 mM NaCl for 24 h and reached 3.75-, 4.76-, and 6.83-fold higher than controls. Further study on proline content in leaves under salt stress showed that proline content increased with increasing NaCl concentrations or time. The proline level peaked at 300 mM NaCl for 24 h and reached more than sixfold higher than control, but at 400 mM NaCl for 24 h proline content fell back slightly along with wilting symptom. To explore the cause behind proline accumulation, we first cloned full length genes related to proline metabolism including KvP5CS1, KvOAT, KvPDH, and KvProT from K. virginica and investigated their expression profiles. The results revealed that the expressions of KvP5CS1 and KvProT were sharply up-regulated by salt stress and the expression of KvOAT showed a slight increase with increasing salt concentrations or time, while the expression of KvPDH was not changed much and slightly decreased before 12 h and then returned to the original level. As the key enzyme genes for proline biosynthesis, the up-regulated expression of KvP5CS1 played a more important role than KvOAT for proline accumulation in leaves under salt stress. The low expression of KvPDH for proline catabolism also made a contribution to proline accumulation before 12 h.

Heterohelicenes are of increasing importance in the fields of materials science, molecular recognition, and asymmetric catalysis. However, enantioselective construction of these molecules, especially by organocatalytic methods, is challenging, and few methods are available. In this study, we synthesize enantioenriched 1-(3-indol)-quino[n]helicenes through chiral phosphoric acid-catalyzed Povarov reaction followed by oxidative aromatization. The method has a broad substrate scope and offers rapid access to an array of chiral quinohelicenes with enantioselectivities up to 99%. Additionally, the photochemical and electrochemical properties of selected quinohelicenes are explored. Heterohelicenes are of increasing importance in materials science but organocatalytic enantioselective synthesis of these molecules remains challenging. Here, the authors synthesize enantioenriched 1-(3-indol)-quino[n]helicenes through chiral phosphoric acid-catalyzed Povarov reaction followed by oxidative aromatization and explore the photochemical and electrochemical properties of these compounds.

Background Mitochondrial dynamics is the result of a dynamic balance between fusion and fission events, which are driven via a set of mitochondria-shaping proteins. These proteins are generally considered to be binary components of either the fission or fusion machinery, but potential crosstalk between the fission and fusion machineries remains less explored. In the present work, we analyzed the roles of mitochondrial elongation factors 1 and 2 (MIEF1/2), core components of the fission machinery in mammals. Results We show that MIEFs (MIEF1/2), besides their action in the fission machinery, regulate mitochondrial fusion through direct interaction with the fusion proteins Mfn1 and Mfn2, suggesting that MIEFs participate in not only fission but also fusion. Elevated levels of MIEFs enhance mitochondrial fusion in an Mfn1/2- and OPA1-dependent but Drp1-independent manner. Moreover, mitochondrial localization and self-association of MIEFs are crucial for their fusion-promoting ability. In addition, we show that MIEF1/2 can competitively decrease the interaction of hFis1 with Mfn1 and Mfn2, alleviating hFis1-induced mitochondrial fragmentation and contributing to mitochondrial fusion. Conclusions Our study suggests that MIEFs serve as a central hub that interacts with and regulates both the fission and fusion machineries, which uncovers a novel mechanism for balancing these opposing forces of mitochondrial dynamics in mammals.