Optimizing Agronomic Management Practices for Enhanced Radiation Capture and Improved Radiation Use Efficiency in Winter Wheat.

Increased aboveground biomass is contingent on enhanced photosynthetically active radiation intercepted by the canopy (IPAR), improved radiation use efficiency (RUE), or both. We investigated whether and how optimized agronomic management practices promote IPAR and RUE. Four integrated agronomic management treatments, i.e., local traditional practice (LP), improved local traditional practice (ILP), high-yield agronomic management (HY), and improved high-yield agronomic management (IHY), were compared over two wheat (Triticum aestivum L.) growing seasons. The average grain yield obtained with IHY was 96% relative to that of HY and was 7% and 23% higher than that with ILP and LP, respectively. Both HY and IHY consistently supported large values of the leaf area index and IPAR fraction, thereby increasing total IPAR. Treatment HY showed increased pre-anthesis RUE, manifested as a higher specific leaf nitrogen content and whole-plant N nutrition index at anthesis. The highest pre-anthesis aboveground biomass was obtained with HY due to the highest pre-anthesis IPAR and RUE. Along with a higher canopy apparent photosynthetic rate, IHY produced higher post-anthesis aboveground biomass due to its higher post-anthesis IPAR and RUE. Treatment IHY had a slightly lower total IPAR but a similar total RUE and harvest index, thus producing a slightly lower grain yield relative to HY. These results demonstrate that the optimized agronomic management practice used under IHY effectively enhances radiation capture and improves radiation utilization. Additionally, the net profit for IHY was higher than that for HY, ILP, and LP by 8%, 11%, and 88%, respectively. Considering the high grain yield, high RUE and high economic benefits, we recommend IHY as the agronomic management practice in the target region, although further study of improvements in pre-anthesis RUE is required.

CORACLE (COVID-19 liteRAture CompiLEr): A platform for efficient tracking and extraction of SARS-CoV-2 and COVID-19 literature, with examples from post-COVID with respiratory involvement.

Background: During the COVID-19 pandemic a need to process large volumes of publications emerged. As the pandemic is winding down, the clinicians encountered a novel syndrome - Post-acute Sequelae of COVID-19 (PASC) - that affects over 10 % of those who contract SARS-CoV-2 and presents a significant challenge in the medical field. The continuous influx of publications underscores a need for efficient tools for navigating the literature. Objectives: We aimed to develop an application which will allow monitoring and categorizing COVID-19-related literature through building publication networks and medical subject headings (MeSH) maps to identify key publications and networks. Methods: We introduce CORACLE (COVID-19 liteRAture CompiLEr), an innovative web application designed to analyse COVID-19-related scientific articles and to identify research trends. CORACLE features three primary interfaces: The "Search" interface, which displays research trends and citation links; the "Citation Map" interface, allowing users to create tailored citation networks from PubMed Identifiers (PMIDs) to uncover common references among selected articles; and the "MeSH" interface, highlighting current MeSH trends and their associations. Results: CORACLE leverages PubMed data to categorize literature on COVID-19 and PASC, aiding in the identification of relevant research publication hubs. Using lung function in PASC patients as a search example, we demonstrate how to identify and visualize the interactions between the relevant publications. Conclusion: CORACLE is an effective tool for the extraction and analysis of literature. Its functionalities, including the MeSH trends and customizable citation mapping, facilitate the discovery of emerging trends in COVID-19 and PASC research.

Endotypes of severe neutrophilic and eosinophilic asthma from multi-omics integration of U-BIOPRED sputum samples.

BACKGROUND: Clustering approaches using single omics platforms are increasingly used to characterise molecular phenotypes of eosinophilic and neutrophilic asthma. Effective integration of multi-omics platforms should lead towards greater refinement of asthma endotypes across molecular dimensions and indicate key targets for intervention or biomarker development. OBJECTIVES: To determine whether multi-omics integration of sputum leads to improved granularity of the molecular classification of severe asthma. METHODS: We analyzed six -omics data blocks-microarray transcriptomics, gene set variation analysis of microarray transcriptomics, SomaSCAN proteomics assay, shotgun proteomics, 16S microbiome sequencing, and shotgun metagenomic sequencing-from induced sputum samples of 57 severe asthma patients, 15 mild-moderate asthma patients, and 13 healthy volunteers in the U-BIOPRED European cohort. We used Monti consensus clustering algorithm for aggregation of clustering results and Similarity Network Fusion to integrate the 6 multi-omics datasets of the 72 asthmatics. RESULTS: Five stable omics-associated clusters were identified (OACs). OAC1 had the best lung function with the least number of severe asthmatics with sputum paucigranulocytic inflammation. OAC5 also had fewer severe asthma patients but the highest incidence of atopy and allergic rhinitis, with paucigranulocytic inflammation. OAC3 comprised only severe asthmatics with the highest sputum eosinophilia. OAC2 had the highest sputum neutrophilia followed by OAC4 with both clusters consisting of mostly severe asthma but with more ex/current smokers in OAC4. Compared to OAC4, there was higher incidence of nasal polyps, allergic rhinitis, and eczema in OAC2. OAC2 had microbial dysbiosis with abundant Moraxella catarrhalis and Haemophilus influenzae. OAC4 was associated with pathways linked to IL-22 cytokine activation, with the prediction of therapeutic response to anti-IL22 antibody therapy. CONCLUSION: Multi-omics analysis of sputum in asthma has defined with greater granularity the asthma endotypes linked to neutrophilic and eosinophilic inflammation. Modelling diverse types of high-dimensional interactions will contribute to a more comprehensive understanding of complex endotypes. KEY POINTS: Unsupervised clustering on sputum multi-omics of asthma subjects identified 3 out of 5 clusters with predominantly severe asthma. One severe asthma cluster was linked to type 2 inflammation and sputum eosinophilia while the other 2 clusters to sputum neutrophilia. One severe neutrophilic asthma cluster was linked to Moraxella catarrhalis and to a lesser extent Haemophilus influenzae while the second cluster to activation of IL-22.

Large airway T cells in adults with former bronchopulmonary dysplasia.

BACKGROUND: Bronchopulmonary Dysplasia (BPD) in infants born prematurely is a risk factor for chronic airway obstruction later in life. The distribution of T cell subtypes in the large airways is largely unknown. OBJECTIVE: To characterize cellular and T cell profiles in the large airways of young adults with a history of BPD. METHODS: Forty-three young adults born prematurely (preterm (n = 20), BPD (n = 23)) and 45 full-term-born (asthma (n = 23), healthy (n = 22)) underwent lung function measurements, and bronchoscopy with large airway bronchial wash (BW). T-cells subsets in BW were analyzed by immunocytochemistry. RESULTS: The proportions of both lymphocytes and CD8 + T cells in BW were significantly higher in BPD (median, 6.6%, and 78.0%) when compared with asthma (3.4% and 67.8%, p = 0.002 and p = 0.040) and healthy (3.8% and 40%, p < 0.001 and p < 0.001). In all adults born prematurely (preterm and BPD), lymphocyte proportion correlated negatively with forced vital capacity (r= -0.324, p = 0.036) and CD8 + T cells correlated with forced expiratory volume in one second, FEV1 (r=-0.448, p = 0.048). Correlation-based network analysis revealed that lung function cluster and BPD-birth cluster were associated with lymphocytes and/or CD4 + and CD8 + T cells. Multivariate regression analysis showed that lymphocyte proportions and BPD severity qualified as independent factors associated with FEV1. CONCLUSIONS: The increased cytotoxic T cells in the large airways in young adults with former BPD, suggest a similar T-cell subset pattern as in the small airways, resembling features of COPD. Our findings strengthen the hypothesis that mechanisms involving adaptive and innate immune responses are involved in the development of airway disease due to preterm birth.

Mucins 3A and 3B Are Expressed in the Epithelium of Human Large Airway.

Aberrant mucus secretion is a hallmark of chronic obstructive pulmonary disease (COPD). Expression of the membrane-tethered mucins 3A and 3B (MUC3A, MUC3B) in human lung is largely unknown. In this observational cross-sectional study, we recruited subjects 45-65 years old from the general population of Stockholm, Sweden, during the years 2007-2011. Bronchial mucosal biopsies, bronchial brushings, and bronchoalveolar lavage fluid (BALF) were retrieved from COPD patients (n = 38), healthy never-smokers (n = 40), and smokers with normal lung function (n = 40). Protein expression of MUC3A and MUC3B in bronchial mucosal biopsies was assessed by immunohistochemical staining. In a subgroup of subjects (n = 28), MUC3A and MUC3B mRNAs were quantified in bronchial brushings using microarray. Non-parametric tests were used to perform correlation and group comparison analyses. A value of p < 0.05 was considered statistically significant. MUC3A and MUC3B immunohistochemical expression was localized to ciliated cells. MUC3B was also expressed in basal cells. MUC3A and MUC3B immunohistochemical expression was equal in all study groups but subjects with emphysema had higher MUC3A expression, compared to those without emphysema. Smokers had higher mRNA levels of MUC3A and MUC3B than non-smokers. MUC3A and MUC3B mRNA were higher in male subjects and correlated negatively with expiratory air flows. MUC3B mRNA correlated positively with total cell concentration and macrophage percentage, and negatively with CD4/CD8 T cell ratio in BALF. We concluded that MUC3A and MUC3B in large airways may be a marker of disease or may play a role in the pathophysiology of airway obstruction.

CircCPSF6 promotes hepatocellular carcinoma cancer progression by regulating MAP4K4 through sponging miR-145-5p.

BACKGROUND: Aberrant expression of circRNAs is involved in the progression of hepatocellular carcinoma (HCC). This study aimed at screening the pro-tumorigenic circular RNAs (circRNAs) in HCC and the mechanisms of circCPSF6 expression influencing HCC characteristics. METHOD: circCPSF6 was identified in HCC tissues using high-throughput sequencing data, and its expression was verified in both HCC tissues and cell lines using quantitative real-time PCR (qRT-PCR). CCK-8 and Transwell assays were used to evaluate the effects of circCPSF6 on HCC proliferation and migration. A xenograft mouse model was used to investigate the effects of circCPSF6 on HCC progression in vivo, and the significance of circCPSF6 in HCC was verified both in vivo and in vitro. circCPSF6-associated miRNAs and mRNAs were identified using bioinformatic analyses. Luciferase reporter, RNA pull-down, Fluorescence in situ hybridization, and RNA immunoprecipitation assays were performed to elucidate the circCPSF6 regulatory axis in HCC. RESULT: CircCPSF6 expression was increased in HCC cell lines and tissues, and the expression of its parental mRNA was positively correlated with tumor severity and negatively correlated with survival. Mechanistic analyses of HCC cell lines showed that tumorigenesis was inhibited by circCPSF6 knockdown and promoted by its overexpression. Functional analyses revealed that circCPSF6 mediated HCC development by sponging miR-145-5p as a competing endogenous RNA. Furthermore, this sponging upregulated the miR-145-5p target gene MAP4K4, a classical pro-tumorigenic gene. CONCLUSION: Our findings reveal a regulatory network that includes the circCPSF6-miR-145-5p-MAP4K4 axis. Elements of this axis are potential HCC biomarkers, as well as targets for HCC treatment.

Diagnostic Prediction of portal vein thrombosis in chronic cirrhosis patients using data-driven precision medicine model.

BACKGROUND: Portal vein thrombosis (PVT) is a significant issue in cirrhotic patients, necessitating early detection. This study aims to develop a data-driven predictive model for PVT diagnosis in chronic hepatitis liver cirrhosis patients. METHODS: We employed data from a total of 816 chronic cirrhosis patients with PVT, divided into the Lanzhou cohort (n = 468) for training and the Jilin cohort (n = 348) for validation. This dataset encompassed a wide range of variables, including general characteristics, blood parameters, ultrasonography findings and cirrhosis grading. To build our predictive model, we employed a sophisticated stacking approach, which included Support Vector Machine (SVM), Naïve Bayes and Quadratic Discriminant Analysis (QDA). RESULTS: In the Lanzhou cohort, SVM and Naïve Bayes classifiers effectively classified PVT cases from non-PVT cases, among the top features of which seven were shared: Portal Velocity (PV), Prothrombin Time (PT), Portal Vein Diameter (PVD), Prothrombin Time Activity (PTA), Activated Partial Thromboplastin Time (APTT), age and Child-Pugh score (CPS). The QDA model, trained based on the seven shared features on the Lanzhou cohort and validated on the Jilin cohort, demonstrated significant differentiation between PVT and non-PVT cases (AUROC = 0.73 and AUROC = 0.86, respectively). Subsequently, comparative analysis showed that our QDA model outperformed several other machine learning methods. CONCLUSION: Our study presents a comprehensive data-driven model for PVT diagnosis in cirrhotic patients, enhancing clinical decision-making. The SVM-Naïve Bayes-QDA model offers a precise approach to managing PVT in this population.

Consensus clustering with missing labels (ccml): a consensus clustering tool for multi-omics integrative prediction in cohorts with unequal sample coverage.

Multi-omics data integration is a complex and challenging task in biomedical research. Consensus clustering, also known as meta-clustering or cluster ensembles, has become an increasingly popular downstream tool for phenotyping and endotyping using multiple omics and clinical data. However, current consensus clustering methods typically rely on ensembling clustering outputs with similar sample coverages (mathematical replicates), which may not reflect real-world data with varying sample coverages (biological replicates). To address this issue, we propose a new consensus clustering with missing labels (ccml) strategy termed ccml, an R protocol for two-step consensus clustering that can handle unequal missing labels (i.e. multiple predictive labels with different sample coverages). Initially, the regular consensus weights are adjusted (normalized) by sample coverage, then a regular consensus clustering is performed to predict the optimal final cluster. We applied the ccml method to predict molecularly distinct groups based on 9-omics integration in the Karolinska COSMIC cohort, which investigates chronic obstructive pulmonary disease, and 24-omics handprint integrative subgrouping of adult asthma patients of the U-BIOPRED cohort. We propose ccml as a downstream toolkit for multi-omics integration analysis algorithms such as Similarity Network Fusion and robust clustering of clinical data to overcome the limitations posed by missing data, which is inevitable in human cohorts consisting of multiple data modalities. The ccml tool is available in the R language (https://CRAN.R-project.org/package=ccml, https://github.com/pulmonomics-lab/ccml, or https://github.com/ZhoulabCPH/ccml).

Multiomics integration-based molecular characterizations of COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), rapidly became a global health challenge, leading to unprecedented social and economic consequences. The mechanisms behind the pathogenesis of SARS-CoV-2 are both unique and complex. Omics-scale studies are emerging rapidly and offer a tremendous potential to unravel the puzzle of SARS-CoV-2 pathobiology, as well as moving forward with diagnostics, potential drug targets, risk stratification, therapeutic responses, vaccine development and therapeutic innovation. This review summarizes various aspects of understanding multiomics integration-based molecular characterizations of COVID-19, which to date include the integration of transcriptomics, proteomics, genomics, lipidomics, immunomics and metabolomics to explore virus targets and developing suitable therapeutic solutions through systems biology tools. Furthermore, this review also covers an abridgment of omics investigations related to disease pathogenesis and virulence, the role of host genetic variation and a broad array of immune and inflammatory phenotypes contributing to understanding COVID-19 traits. Insights into this review, which combines existing strategies and multiomics integration profiling, may help further advance our knowledge of COVID-19.

Baseline characteristics and survival of patients of idiopathic pulmonary fibrosis: a longitudinal analysis of the Swedish IPF Registry.

BACKGROUND: Observational data under real-life conditions in idiopathic pulmonary fibrosis (IPF) is scarce. We explored anti-fibrotic treatment, disease severity and phenotypes in patients with IPF from the Swedish IPF Registry (SIPFR). METHODS: Patients enrolled between September 2014 and April 2020 and followed ≥ 6 months were investigated. Demographics, comorbidities, lung function, composite variables, six-minute walking test (6MWT), quality of life, and anti-fibrotic therapy were evaluated. Agreements between classification of mild physiological impairment (defined as gender-age-physiology (GAP) stage 1) with physiological and composite measures of severity was assessed using kappa values and their impact on mortality with hazard ratios. The factor analysis and the two-step cluster analysis were used to identify phenotypes. Univariate and multivariable survival analyses were performed between variables or groups. RESULTS: Among 662 patients with baseline data (median age 72.7 years, 74.0% males), 480 had a follow up ≥ 6 months with a 5 year survival rate of 48%. Lung function, 6MWT, age, and BMI were predictors of survival. Patients who received anti-fibrotic treatment ≥ 6 months had better survival compared to untreated patients [p = 0.007, HR (95% CI): 1.797 (1.173-2.753)] after adjustment of age, gender, BMI, smoking status, forced vital capacity (FVC) and diffusion capacity of carbon monoxide (DLCO). Patients with mild physiological impairment (GAP stage 1, composite physiological index (CPI) ≤ 45, DLCO ≥ 55%, FVC ≥ 75%, and total lung capacity (TLC) ≥ 65%, respectively) had better survival, after adjustment for age, gender, BMI and smoking status and treatment. Patients in cluster 1 had the worst survival and consisted mainly of male patients with moderate-severe disease and an increased prevalence of heart diseases at baseline; Cluster 2 was characterized by mild disease with more than 50% females and few comorbidities, and had the best survival; Cluster 3 were younger, with moderate-severe disease and had few comorbidities. CONCLUSION: Disease severity, phenotypes, and anti-fibrotic treatment are closely associated with the outcome in IPF, with treated patients surviving longer. Phenotypes may contribute to predicting outcomes of patients with IPF and suggest the patients' need for special management, whereas single or composite variables have some limitations as disease predictors.

Impact on physical and mental health among medical personnel in Wuhan during COVID-19 outbreak: a cluster analysis.

Background: Increased stress among medical personnel had been reported in previous virus outbreaks. The novel coronavirus disease (COVID-19) emerged in December 2019, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). No qualitative assessment has yet described the physical and mental health conditions of frontline medical personnel in the COVID-19 outbreaks. Methods: Here, 251 frontline medical personnel involved in COVID-19 missions completed electronic questionnaires, consisting of 31 categorical variables related to their physical and mental health status, medical history and environmental conditions. We constructed a correlation amongst these variables through pairwise Kendall rank correlation coefficient test. Then, clusters of highly correlated variables were identified using the leading eigenvector. Finally, we used the network and clusters to clarify the correlations amongst variables. Results: This qualitative study identified the six clusters. Cluster 1 was characterized by skin allergy. Cluster 2 was predominantly associated with anxiety. Cluster 3 consisted mostly of respiratory symptoms. The participants in cluster 4 had medical history. Cluster 5 and cluster 6 were characterized by disinfection and demography, respectively. Finally, we revealed three major findings. First, more than 80% of medical personnel worry about COVID-19-related infection and experience newly appearing anxiety (56.2%), airway or heart symptoms (34.3%) and skin allergies (20.3%). Second, COVID-19-related worry significantly associates with all variables in the anxiety and respiratory symptom clusters. Third, new-onset skin allergies did not associate with either disinfection or anxiety, but did associate with a previous history of allergies. Conclusions: COVID-19-related worry leads to physical and mental health problems amongst medical personnel. Effective responses and interventions could relieve a series of new-onset physical and mental health problems.

MicroRNA miR-24-3p reduces DNA damage responses, apoptosis, and susceptibility to chronic obstructive pulmonary disease.

The pathogenesis of chronic obstructive pulmonary disease (COPD) involves aberrant responses to cellular stress caused by chronic cigarette smoke (CS) exposure. However, not all smokers develop COPD and the critical mechanisms that regulate cellular stress responses to increase COPD susceptibility are not understood. Because microRNAs are well-known regulators of cellular stress responses, we evaluated microRNA expression arrays performed on distal parenchymal lung tissue samples from 172 subjects with and without COPD. We identified miR-24-3p as the microRNA that best correlated with radiographic emphysema and validated this finding in multiple cohorts. In a CS exposure mouse model, inhibition of miR-24-3p increased susceptibility to apoptosis, including alveolar type II epithelial cell apoptosis, and emphysema severity. In lung epithelial cells, miR-24-3p suppressed apoptosis through the BH3-only protein BIM and suppressed homology-directed DNA repair and the DNA repair protein BRCA1. Finally, we found BIM and BRCA1 were increased in COPD lung tissue, and BIM and BRCA1 expression inversely correlated with miR-24-3p. We concluded that miR-24-3p, a regulator of the cellular response to DNA damage, is decreased in COPD, and decreased miR-24-3p increases susceptibility to emphysema through increased BIM and apoptosis.

Smoking-associated increase in mucins 1 and 4 in human airways.

RATIONALE: Smoking-related chronic obstructive pulmonary disease (COPD) is associated with dysregulated production of mucus. Mucins (MUC) are important both for mucus secretion and epithelial defense. We have examined the distribution of MUC1 and MUC4 in the airway epithelial cells of never-smokers and smokers with and without COPD. METHODS: Mucosal biopsies and bronchial wash samples were obtained by bronchoscopy from age- and sex-matched COPD-patients (n = 38; GOLD I-II/A-B), healthy never-smokers (n = 40) and current smokers with normal lung function (n = 40) from the Karolinska COSMIC cohort (NCT02627872). Cell-specific expressions of MUC1, MUC4 and regulating factors, i.e., epithelial growth factor receptor (EGFR) 1 and 2, were analyzed by immunohistochemistry. Soluble MUC1 was measured by quantitative immunodetection on slot blot. RESULTS: The levels of cell-bound MUC1 expression in basal cells and in soluble MUC1 in bronchial wash were increased in smokers, regardless of airway obstruction. Patients with chronic bronchitis had higher MUC1 expression. The expression of MUC4 in cells with goblet cell phenotype was increased in smokers. The expression of EGFR2, but not that of EGFR1, was higher in never-smokers than in smokers. CONCLUSIONS: Smoking history and the presence of chronic bronchitis, regardless of airway obstruction, affect both cellular and soluble MUC1 in human airways. Therefore, MUC1 may be a novel marker for smoking- associated airway disease.

Sputum Vitamin D Binding Protein (VDBP) GC1S/1S Genotype Predicts Airway Obstruction: A Prospective Study in Smokers with COPD.

Introduction: The vitamin D binding protein (VDBP, also known as GC-globulin) and vitamin D deficiency have been associated with chronic obstructive pulmonary disease (COPD). rs7041 and rs4588 are two single nucleotide polymorphisms of the VDBP gene, including three common allelic variants (GC1S, GC1F and GC2). Previous studies primarily assessed the serum levels of vitamin D and VDBP in COPD. However, less is known regarding the impact of the local release of VDBP on COPD lung function. Thus, we examined the association of sputum and plasma VDBP with lung function at baseline and at four years, and examined potential genetic polymorphism interactions. Methods: The baseline levels of sputum VDBP, plasma VDBP and plasma 25-OH vitamin D, as well as the GC rs4588 and rs7041 genotypes, were assessed in a 4-year Finnish follow-up cohort (n = 233) of non-smokers, and smokers with and without COPD. The associations between the VDBP levels and the longitudinal decline of lung function were further analysed. Results: High frequencies of the haplotypes in rs7041/rs4588 were homozygous GC1S/1S (42.5%). Higher sputum VDBP levels in stage I and stage II COPD were observed only in carriers with GC1S/1S genotype when compared with non-smokers (p = 0.034 and p = 0.002, respectively). Genotype multivariate regression analysis indicated that the baseline sputum VDBP and FEV1/FVC ratio at baseline independently predicted FEV1% at follow-up. Discussion and Conclusion: The baseline sputum VDBP expression was elevated in smokers with COPD among individuals with the GC1S/1S genotype, and predicted follow-up airway obstruction. Our results suggest that the GC polymorphism should be considered when exploring the potential of VDBP as a biomarker for COPD.

The unsynchronized changes of CT image and nucleic acid detection in COVID-19: reports the two cases from Gansu, China.

The novel coronavirus disease (COVID-19) outbreak started in December 2019 in Wuhan, China, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The CT image is used to assess the disease progress, whereas the continued two times of negative results from SARS-CoV-2 nucleic acid detection had been considered as a criterion for ending antiviral treatment. We compared the two COVID-19 cases with similar backgrounds and CT image repeated intervals under treatment. Our report highlighted the unsynchronized expression in the changes of CT image and nucleic acid detection in COVID-19, and lasting positive nucleic acid test result in patients recovered from pneumonia. It may be contributed to recognize the disease and improve prevention.

Integration of multi-omics datasets enables molecular classification of COPD.

Chronic obstructive pulmonary disease (COPD) is an umbrella diagnosis caused by a multitude of underlying mechanisms, and molecular sub-phenotyping is needed to develop molecular diagnostic/prognostic tools and efficacious treatments.The objective of these studies was to investigate whether multi-omics integration improves the accuracy of molecular classification of COPD in small cohorts.Nine omics data blocks (comprising mRNA, micro RNA, proteomes and metabolomes) collected from several anatomical locations from 52 female subjects were integrated by similarity network fusion (SNF). Multi-omics integration significantly improved the accuracy of group classification of COPD patients from healthy never-smokers and from smokers with normal spirometry, reducing required group sizes from n=30 to n=6 at 95% power. Seven different combinations of four to seven omics platforms achieved >95% accuracy.For the first time, a quantitative relationship between multi-omics data integration and accuracy of data-driven classification power has been demonstrated across nine omics data blocks. Integrating five to seven omics data blocks enabled 100% correct classification of COPD diagnosis with groups as small as n=6 individuals, despite strong confounding effects of current smoking. These results can serve as guidelines for the design of future systems-based multi-omics investigations, with indications that integrating five to six data blocks from several molecular levels and anatomical locations suffices to facilitate unsupervised molecular classification in small cohorts.

125I Brachytherapy in Locally Advanced Nonsmall Cell Lung Cancer After Progression of Concurrent Radiochemotherapy.

To investigate the safety and effectiveness of computed tomography (CT)-guided I seed implantation for locally advanced nonsmall cell lung cancer (NSCLC) after progression of concurrent radiochemotherapy (CCRT).We reviewed 78 locally advanced NSCLC patients who had each one cycle of first-line CCRT but had progressive disease identified from January 2006 to February 2015 at our institution. A total of 37 patients with 44 lesions received CT-guided percutaneous I seed implantation and second-line chemotherapy (group A), while 41 with 41 lesions received second-line chemotherapy (group B).Patients in group A and B received a total of 37 and 41 first cycle of CCRT treatment. The median follow-up was 19 (range 3-36) months. After the second treatment, the total response rate (RR) in tumor response accounted for 63.6% in group A, which was significantly higher than that of group B (41.5%) (P = 0.033). The median progression-free survival time (PFST) was 8.00 ±â€Š1.09 months and 5.00 ±â€Š0.64 months in groups A and B (P = 0.011). The 1-, 2-, and 3-year overall survival (OS) rates for group A were 56.8%, 16.2%, and 2.7%, respectively. For group B, OS rates were 36.6%, 9.8%, and 2.4%, respectively. The median OS time was 14.00 ±â€Š1.82 months and 10.00 ±â€Š1.37 months for groups A and B, respectively (P = 0.059). Similar toxicity reactions were found in both groups. Tumor-related clinical symptoms were significantly reduced and the patients' quality of life was obviously improved.CT-guided I seed implantation proved to be potentially beneficial in treating localized advanced NSCLC; it achieved good local control rates and relieved clinical symptoms without increasing side effects.

Progress in the treatment of pulmonary metastases after liver transplantation for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the fifth most common cancer in the world, and is the third leading cause of cancer-related death. Liver transplantation (LT) has become a curative treatment for patients with HCC. However, recurrence and metastasis after LT are the main factors reducing long-term survival in patients, and the lung is the most common site of metastasis after LT for HCC, although metastasis to liver, para-aortic lymph nodes and renal periphery are observed. Thus, the treatment of pulmonary metastases after LT for HCC has become a hot research topic, the successful treatment of pulmonary metastases can significantly prolong the survival of LT patients. Although single conventional treatment (chemotherapy, surgery and external beam radiation therapy), immunosuppression, image-guided minimally invasive therapy (radiofrequency ablation, microwave ablation, cryoablation, and brachytherapy) and molecular targeted drugs have had a significant effect, patients do not have durable remission and the long-term survival rate is disappointing. Therefore, improving existing treatments and identifying a more effective combination therapy are important research issues in the prevention and treatment of pulmonary metastases after LT for HCC. The paper reviewed single conventional treatments, new treatments, and combination therapy, to provide a basis for the best treatment of these patients.

[Effects of cultivation patterns on the radiation use and grain yield of winter wheat].

Taking winter wheat cultivar 'Tainong 18' as test material, this paper set three treatments, local farmer's traditional cultivation pattern (FP), super high yield pattern (SH) and high yield high efficiency pattern ( HH) to investigate the effects of cultivation patterns on the intercepted photosynthetically active radiation (IPAR), PAR use efficiency (RUE), dry matter (DM) accumulation, harvest index (HI), grain yield and fertilizers' partial factor productivity (PFP) in 2012-2013. The results showed that IPAR, RUE and DM accumulation of the total growth stage and grain yield under SH pattern were significantly higher than those under FP pattern. IPAR of the total growth stage under HH pattern was lower than that under FP pattern, but RUE, DM accumulation and HI were significantly higher than that under FP pattern, so grain yield was higher than that under FP pattern. The grain yields under HH pattern were respectively decreased by 3.8% and 2.8% under high and low fertility levels compared that under SH pattern, while the PFP of N, P and K under HH pattern were averagely 26.4%, 68.5% and 92.6% higher than those under SH pattern, respectively. In conclusion, HH pattern, with the characteristics of 'reducing fertilizer', 'increasing planting density' and 'delaying sowing date', was the recommended cultivation pattern under the condition similar to this experiment balancing the grain yield, radiation use and fertilizer use.