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Background: Immune checkpoint inhibitors (ICIs) extend the survival time in patients with advanced non-small-cell lung cancer (NSCLC), but not all patients respond to the treatment. However, current immune-related biomarkers, such as programmed death receptor ligand 1 (PD-L1) and tumor mutation burden(TMB) are limited. We created a machine learning (ML) based clinical decision support algorithm to evaluate the 2-Year mortality of NSCLC patients treated with ICIs by comprehensively combining the clinical information. Methods: We collected clinical data, including patient characteristics, mutations and laboratory findings, from the electronic medical records of 345 patients with NSCLC treated with ICIs. Through machine learning and statistical analysis, we constructed effective immune risk score models. Twenty-four clinically meaningful features were used in supervised ML algorithms, including decision trees, random forest and XGBoost , to predict the 2-Year mortality. Results: Several factors, including driver gene mutation status, derived neutrophil to lymphocyte ratio (dNLR), prognostic nutrition index (PNI), could independently predict the 2-Year mortality.ML platforms based on the random forest algorithm using 24 clinical features showed more significant prediction performance (area under the curve [AUC] 0.736). Conclusions: Collectively, our machine learning algorithm offers a clinical decision support model to predict the 2-Year mortality in NSCLC treated with ICIs.

Based on the development of teaching in the new era and the requirements of modern teaching, the experiment of chemical principles is integrated with virtual simulation, relying on "Internet+" technology, building a new teaching system, realizing a comprehensive information-based experimental teaching, and improving the teaching effect of chemical practical classes. This project implements online and offline teaching system of chemical principle experiment, builds chemical principle experiment resource library, explores and develops new software of virtual simulation experiment of chemical principle with more practicality, implements open sharing and promotion application, and provides reference for the construction and promotion of practical courses of new engineering majors with important theoretical and practical significance.

The influence of line impedance does not be considered in the traditional droop control strategy. When it is directly applied to the control for inverters, the reactive power cannot be accurately shared according to the rated capacity proportion. In this paper, a new secondary reactive power control strategy was proposed; the adaptive power distributor and PI control compensator were designed in the strategy. The adaptive power distributor was used to provide the reactive power reference, and the compensation was obtained by the PI control compensator. Therefore, the main idea of this strategy was to add compensation in the traditional droop control to make sure that the reactive power could dynamically track the reference to achieve accurate sharing. The simulation of the microgrid system verified the rationality and effectiveness of the strategy.

With the deepening of power market reforms, the emergence of independent users of the distribution network has caused the power system to face multi-layer coordination. Under this background, a collaborative optimization scheduling of the transmission and distribution networks method considering demand response was proposed to realize interaction among transmission network, distribution network and load. It was oriented to a three-layer model including transmission system operator(TSO), distribution system operator(DSO) and load aggregator (LA). TSO and DSO achieved collaborative optimization to meet the consistency constraints of boundary power. DSO and LA formed a Stackelberg game model to interact through electricity price and power. Then, combined with KKT transform and other algorithms to solve the boundary power and the optimal electricity price. Through the simulation example, it was verified that the method can achieve the overall economic operation of the system, which provided a new idea for coordinated energy management of transmission and distribution networks.

Background Cotton (Gossypium spp.) fiber yield is one of the key target traits, and improved fiber yield has always been thought of as an important objective in the breeding programs and production. Although some studies had been reported for the understanding of genetic bases for cotton yield-related traits, the detected quantitative trait loci (QTL) for the traits is still very limited. To uncover the whole-genome QTL controlling three yield-related traits in upland cotton (Gossypium hirsutum L.), phenotypic traits were investigated under four planting environments and 9244 single-nucleotide polymorphism linkage disequilibrium block (SNPLDB) markers were developed in an association panel consisting of 315 accessions. Results A total of 53, 70 and 68 significant SNPLDB loci associated with boll number (BN), boll weight (BW) and lint percentage (LP), were respectively detected through a restricted two-stage multi-locus multi-allele genome-wide association study (RTM-GWAS) procedure in multiple environments. The haplotype/allele effects of the significant SNPLDB loci were estimated and the QTL-allele matrices were organized for offering the abbreviated genetic composition of the population. Among the significant SNPLDB loci, six of them were simultaneously identified in two or more single planting environments and were thought of as the stable SNPLDB loci. Additionally, a total of 115 genes were annotated in the nearby regions of the six stable SNPLDB loci, and 16 common potential candidate genes controlling target traits of them were predicted by two RNA-seq data. One of 16 genes (GH_D06G2161) was mainly expressed in the early ovule-development stages, and the stable SNPLDB locus (LDB_19_62926589) was mapped in its promoter region. Conclusion This study identified the QTL alleles and candidate genes that could provide important insights into the genetic basis of yield-related traits in upland cotton and might facilitate breeding cotton varieties with high yield.

Additional file 1: Figure S1. QTL-allele matrices of the significant SNPLDBs associated with BN (A), BW(B) and LP(C), respectively.

Fulvic acid–poly(methylmethacrylate) graft copolymers were synthesized by surface-initiated atom transfer radical polymerization with fulvic acid. The result demonstrated that the hydrophobicity of fulvic acid–poly(methylmethacrylate) was improved after modification by surface-initiated atom transfer radical polymerization. Furthermore, poly(lactic acid)/fulvic acid–poly(methylmethacrylate) composites were prepared to improve the performances of poly(lactic acid) by blend melting. Compared to poly(lactic acid) with Xc of 5.38%, the Xc of poly(lactic acid)/fulvic acid–poly(methylmethacrylate) composites was 19.94%. Moreover, the impact strength of poly(lactic acid)/fulvic acid–poly(methylmethacrylate) composites was increased by 5.19% compared to poly(lactic acid). In all, this study provided an effective and feasible method for optimizing interface performance and enhancing the thermal stability of poly(lactic acid).

In this study, trends in synonymous codons usage of Volvariella volvecea have been first examined by analysis of complete coding sequences and gene chip data. The results showed that GC content at three codon positions are obviously different and there were several factors shaping the codon usage of V. volvacea genes, including base composition. The comparison of codon usage among four edible fungi such as V. volvacea, Agaricus bisporus, Coprinopsis cinerea, and Pleurotus ostreatus indicated that the similar codon usage pattern was used among V. volvacea, A. bisporus and P. ostreatus, but there was significantly different codon usage pattern of C. cinerea. Two arrays of optimal codons were determined by effective number of codons (ENC) values and gene chip database separately, resulting that most of the ENC-predicted optimal codons were included in the array of gene chip resulted optimal codons. This study can provide useful information for codon usage pattern analysis and gene transformation of V. volvacea.

Background The aim of the study was to investigate whether simulation education (SE) and case management had any effect on glycemic control in type 2 diabetes (T2DM) patients. Methods In this single center pilot trial, 100 T2DM patients who received medication and basic diabetes self‐management education (DSME) were randomly divided into a control group (n = 50) and an experimental group (n = 50), who received SE and a case management program. Evaluation of biochemical indices was conducted at baseline and after 6 months. DSME consisted of 2‐hour group trainings weekly for 2 consecutive weeks followed by 2 × 30 minute education sessions after 3 and 6 months. The SE program comprised additional 50‐minute video sessions 3 times in the first week and twice in the second week. The experimental group was supervised by a nurse case manager, who followed up participants at least once a month, and who conducted group sessions once every 3 months, focusing on realistic aspects of physical activity and nutrition, with open discussions about setting goals and strategies to overcome barriers. Results After 6 months, HbA1c, fasting plasma glucose, and postprandial blood glucose level improvements were superior in the experimental group compared with the control group (P

To understand the genetic basis of crop economic characteristics, identifying whole-genome quantitative trait loci (QTLs) in breeding resources via genome-wide association studies (GWASs) is important, but conventional GWAS procedures have mainly concentrated on identifying regions of major QTLs. In this study, to reveal whole-genome QTLs controlling cotton fibre quality traits, a total of 1,236,418 single-nucleotide polymorphism (SNP) markers were explored in a natural population of 315 upland cotton accessions using the specific-locus amplified fragment sequencing (SLAF-seq) method, and 13,391 high-quality SNPs were organized into 9244 SNP linkage disequilibrium blocks (SNPLDBs) to develop molecular markers with multiple haplotypes/alleles. A relatively novel procedure for restricted two-stage multi-locus multi-allele GWAS (RTM-GWAS) involving two methods was applied, including multiple environments and four single environments. In total, 75, 77, 66, 66, and 60 significant SNPLDBs associated with the upper half mean length (UHML), fibre strength (FS), fibre micronaire (FM), fibre uniformity index (FUI), and fibre elongation (FE), respectively, were identified via the multiple-environment RTM-GWAS method. Based on these results, the haplotype/allele effects of the significant SNPLDB loci were estimated, and QTL-allele matrices were established to provide the abbreviated genetic composition of the population. Most importantly, nine stable SNPLDB loci were simultaneously detected in multiple environments and two or more single test environments with large –lg(P) values and percentages of explained phenotypic variation. Furthermore, favourable haplotypes/alleles of the nine stable SNPLDB loci were identified, and 79 potential candidate genes related to UHML and FS traits were predicted from RNA-seq data. Favourable haplotypes/alleles, potential candidate genes and QTL-allele matrices can offer important insights into the genetic basis of fibre quality traits in upland cotton and may facilitate the breeding of cotton varieties with excellent fibre quality properties.

This paper focuses on an important task in online courses, which is to estimate student learning ability from students’ answering records. The challenge of this task is to automatically estimate the learning ability for students and infer the true answer for each question without any supervision. Most of the existing methods solve these challenges by designing an optimization objective function. However, these approaches ignore the characteristics of students from different groups. Intuitively, outstanding students always provide correct answers and should be assigned higher weights compared with ordinary students. Based on this intuition, this paper proposes a new optimization framework by dividing students into two groups: an authoritative group and an ordinary group. The losses of the objective are from both authoritative students and ordinary students. Through optimizing both losses simultaneously, the proposed model can automatically estimate learning ability for authoritative students and ordinary students and infer the right answer for each question. Two experiments conducted on two datasets show that the proposed model outperforms state-of-the-art baselines.

With the continuous development of society, human beings are in the midst of profound changes. The new information thinking has penetrated into society, study, work and life. The application of information technology has become an important direction for the teaching reform of chemistry. By analyzing the application status of information education and teaching, this paper concludes that the construction of information teaching resources needs to be improved, and the application of information teaching technology still needs to be strengthened, and proposes the idea of integrating it with innovation and development, using information technology. Improve the teaching concepts of chemistry subjects, improve teaching resources and improve the application of information technology. Due to the introduction of information technology, it can highlight the characteristics of rapid, sensitive and accurate analysis of chemistry. The combination of various teaching methods makes the application of analytical chemistry more extensive and strongly promotes the development of analytical chemistry. Change traditional teaching methods and traditional education models, and innovate teaching concepts and practical concepts. It is believed that the continuous integration of information technology in development and rapid social economy will definitely create an information environment for the whole society

Pear (Pyrus L.) is an important commercial fruit in the world. The fruit size is one of the important characters in fruit quality. The previous research reported that the fruit size of pear was mainly caused by the number of cell in about 40 days after blossom (DAB) in nature. However, studies about the mechanisms underlying cell division in young fruit development are very limited in pear. Two pear accessions codenamed ‘GH59B’ with big fruit and ‘GH81S’ with small fruit in three stages were sampled and the RNA-seq high-throughput sequencing was used to evaluate changes of gene transcription levels in the early stage of fruit development. The difference of cell size among two samples was little in 40 DAB, implying that the difference of the fruit size was caused by the number of the cell. More than 274,517,982 high quality reads from six libraries of fruit development were sequenced. A total of 797 differentially expressed genes (DEGs) were identified. Three cytokinin dehydrogenase genes and two gibberellin 2-beta-dioxygenase gene were identified in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to zeatin and gibberellin. Their expression was upregulated at 20 DAB in ‘GH81S’ and at 30 DAB in ‘GH59B’, suggesting that the small fruit size might be related to the early degradation of cytokinin and gibberellin inducing a short period of cell division. A total of 38 DEGs of transcription factors were found and 23 DEGs including NAC, ERF and bHLH transcription factors were highly related with cytokinin dehydrogenase and gibberellin dioxygenase genes. Altogether, the results of the present study provide information from a comprehensive gene expression analysis and insight into the molecular mechanism underlying the difference of fruit size in Pyrus pyrifolia.

Summary Systemic immunosuppression greatly affects the chemotherapeutic antitumor effect. Here, we showed that CD19+ extracellular vesicles (EVs) from B cells through CD39 and CD73 vesicle-incorporated proteins hydrolyzed ATP from chemotherapy-treated tumor cells into adenosine, thus impairing CD8+ T cell responses. Serum CD19+ EVs were increased in tumor-bearing mice and patients. Patients with fewer serum CD19+ EVs had a better prognosis after chemotherapy. Upregulated hypoxia-inducible factor-1α (HIF-1α) promoted B cells to release CD19+ EVs by inducing Rab27a mRNA transcription. Rab27a or HIF-1α deficiency in B cells inhibited CD19+ EV production and improved the chemotherapeutic antitumor effect. Silencing of Rab27a in B cells by inactivated Epstein-Barr viruses carrying Rab27a siRNA greatly improved chemotherapeutic efficacy in humanized immunocompromised NOD Prkdcscid Il2rg−/− mice. Thus, decreasing CD19+ EVs holds high potential to improve the chemotherapeutic antitumor effect.

A new sandwich-type hybrid complex, Na8{Cu(im)4(H2O)}[Cu(im)4 {Na(H2O)2Co(im)}3(BiW9O33)2] · 11H2O (1) (im = imidazole), has been synthesized and structurally characterized. The polyoxoanion in 1 contains trinuclear Co2+ ions in the central belt and an antennal Cu(II)–imidazole supported complex, which firstly represents a copper(II)-complex mono-supported tungstobismuthate system containing sandwiched trinuclear cobalt(II) ions. Neighboring polyanions further connect each other by disodium ions to yield a dimeric complex. The successful synthesis of 1 opens a new approach to the combination of different kinds of transition–metal ions by virtue of lacunary Keggin-type polyoxoanions, [BiW9O33]9−, as effective linkages. The magnetic investigation for 1 indicate weak antiferromagnetic interactions for trinuclear Co(II) clusters located in the polyanions.

A cryptographic network file system has to guarantee confidentiality and integrity of its files, and also it has to support random access. For this purpose, existing designs mainly rely on(often ad-hoc) combination of Merkle hash tree with a block cipher mode of encryption. In this paper, we propose a new design based on a MAC tree construction which uses a universal-hash based stateful MAC. This new design enables standard model security proof and also better performance compared with Merkle hash tree. We formally define the security notions for file encryption and prove that our scheme provides both confidentiality and integrity. We implement our scheme in coreFS, a user-level network file system, and evaluate the performance in comparison with the standard design. Experimental results confirm that our construction provides integrity protection at a smaller cost.

Rare earth complex Tb(DPC) 2 2H 2 O was synthesized by introducing Pyridine-2,6-dicarboxylic acid(H 2 DPC) as the ligand and characterized by UV, fluorescent and infrared spectra as well as elemental analysis. The complex exhibited ligand-sensitized green emission, and it has the higher sensitized luminescent efficiency and longer lifetime. The effect and mechanism of the ligand (H 2 DPC) on the luminescence properties of terbium complex was discussed. In device ITO/PVK/Tb(DPC) 2 2H 2 O/Al, Tb 3+ may be excited by intramolecular energy transfer from ligand as observed by electroluminescence. The main emitting peak at 545 nm can be attributed to the transition of 5 D 4 → 7 F 5 of Tb 3+ ion and this process results in the enhancement of green emission from electroluminescence device.

There is a huge amount of duplicated or redundant data in current storage systems. So data de-duplication, which uses lossless data compression schemes to minimize the duplicated data at the inter-file level, has been receiving broad attention in recent years. But there are still research challenges in current approaches and storage systems, such as: how to chunking the files more efficiently and better leverage potential similarity and identity among dedicated applications; how to store the chunks effectively and reliably into secondary storage devices. In this paper, we propose ADMAD: an application-driven metadata aware de-duplication archival storage system, which makes use of certain meta-data information of different levels in the I/O path to direct the file partitioning into more meaningful data chunks (MC) to maximally reduce the inter-file level duplications. However, the chunks may be with different lengths and variable sizes, storing them into storage devices may result in a lot of fragments and involve a high percentage of random disk accesses, which is very inefficient. Therefore, in ADMAD, chunks are further packaged into fixed sized objects as the storage units to speed up the I/O performance as well as to ease the data management. Preliminary experiments have demonstrated that the proposed system can further reduce the required storage space when compared with current methods (from 20% to near 50% according to several datasets), and largely improves the writing performance (about 50%-70% in average).

We investigate the robustness of complex communication networks on allocating redundancy links. The protecting key nodes (PKN) strategy is proposed to improve the robustness of complex communication networks against intentional attack. Our numerical simulations show that allocating a few redundant links among key nodes using the PKN strategy will significantly increase the robustness of scale-free complex networks. We have also theoretically proved and demonstrated the effectiveness of the PKN strategy. We expect that our work will help achieve a better understanding of communication networks.