HLA diversity unveils susceptibility and organ-specific occurrence of second primary cancers: a prospective cohort study.

BACKGROUND: Up to 17% of cancer survivors have been reported to develop second primary cancers (SPC), which cause significant physical and economic distress and often complicate clinical decision-making. However, understanding of SPC remains limited and superficial. Human leukocyte antigen (HLA) is characterized by its polymorphism and has been associated with various diseases. This study aims to explore the role of HLA diversity in SPC incidence. METHODS: We analyzed a cohort of 47,550 cancer patients from the UK Biobank. SNP-derived HLA alleles were used and SPC-related HLA alleles were identified using logistic regression, followed by stepwise filtering based on the Akaike information criterion (AIC) and permutation tests. Additionally, we examined the association between extragenetic factors and the risk of SPC in patients carrying hazardous HLA alleles. RESULTS: During a median follow-up of 3.11 years, a total of 2894 (6.09%) participants developed SPC. We identified three protective HLA alleles (DRB1*04:03 and DPA1*02:02 for males and DRB5*01:01 for females) and two hazardous alleles (A*26:01 for males and DPB1*11:01 for females) about SPC. The presence of the protective alleles was associated with a reduced SPC risk (males: hazard ratio [HR] 0.72, 95% confidence interval [CI] 0.59-0.89; females: HR 0.81, 95% CI 0.70-0.93), while the hazardous alleles were linked to an increased risk (males: HR 1.27, 95% CI 1.03-1.56; females: HR 1.35, 95% CI 1.07-1.70). The hazardous allele A*26:01 indicated skin-lung organ-specific SPC occurrence in males. Animal fat and vitamin C were associated with SPC risk in males carrying the hazardous alleles, while free sugar and vegetable fat were linked to SPC risk in females. CONCLUSIONS: These results suggest that HLA alleles may serve as biomarkers for the susceptibility and organ-specific occurrence of SPC, while dietary modulation may mitigate hazardous alleles-related SPC risk, potentially aiding in the early prediction and prevention of SPC.

Natural variations of heterosis-related allele-specific expression genes in promoter regions lead to allele-specific expression in maize.

BACKGROUND: Heterosis has successfully enhanced maize productivity and quality. Although significant progress has been made in delineating the genetic basis of heterosis, the molecular mechanisms underlying its genetic components remain less explored. Allele-specific expression (ASE), the imbalanced expression between two parental alleles in hybrids, is increasingly being recognized as a factor contributing to heterosis. ASE is a complex process regulated by both epigenetic and genetic variations in response to developmental and environmental conditions. RESULTS: In this study, we explored the differential characteristics of ASE by analyzing the transcriptome data of two maize hybrids and their parents under four light conditions. On the basis of allele expression patterns in different hybrids under various conditions, ASE genes were divided into three categories: bias-consistent genes involved in basal metabolic processes in a functionally complementary manner, bias-reversal genes adapting to the light environment, and bias-specific genes maintaining cell homeostasis. We observed that 758 ASE genes (ASEGs) were significantly overlapped with heterosis quantitative trait loci (QTLs), and high-frequency variations in the promoter regions of heterosis-related ASEGs were identified between parents. In addition, 10 heterosis-related ASEGs participating in yield heterosis were selected during domestication. CONCLUSIONS: The comprehensive analysis of ASEGs offers a distinctive perspective on how light quality influences gene expression patterns and gene-environment interactions, with implications for the identification of heterosis-related ASEGs to enhance maize yield.

Regular Use of Aspirin and Statins Reduces the Risk of Cancer in Individuals with Systemic Inflammatory Diseases.

Aspirin has shown potential for cancer prevention, but a recent large randomized controlled trial found no evidence for a reduction in cancer risk. Given the anti-inflammatory effects of aspirin, systemic inflammatory diseases (SID), such as osteoporosis, cardiovascular diseases, and metabolic diseases, could potentially modify the aspirin-cancer link. To investigate the impact of aspirin in people with SIDs, we conducted an observational study on a prospective cohort of 478,615 UK Biobank participants. Individuals with at least one of the 41 SIDs displayed a higher cancer risk than those without SIDs. Regular aspirin use showed protective effects exclusively in patients with SID, contrasting an elevated risk among their non-SID counterparts. Nonetheless, aspirin use demonstrated preventative potential only for 9 of 21 SID-associated cancer subtypes. Cholesterol emerged as another key mediator linking SIDs to cancer risk. Notably, regular statin use displayed protective properties in patients with SID but not in their non-SID counterparts. Concurrent use of aspirin and statins exhibited a stronger protective association in patients with SID, covering 14 common cancer subtypes. In summary, patients with SIDs may represent a population particularly responsive to regular aspirin and statin use. Promoting either combined or individual use of these medications within the context of SIDs could offer a promising chemoprevention strategy. SIGNIFICANCE: Individuals with systemic inflammatory diseases derive chemoprotective benefits from aspirin and statins, providing a precision cancer prevention approach to address the personal and public challenges posed by cancer.

CDK4/6 inhibition triggers ICAM1-driven immune response and sensitizes LKB1 mutant lung cancer to immunotherapy.

Liver kinase B1 (LKB1) mutation is prevalent and a driver of resistance to immune checkpoint blockade (ICB) therapy for lung adenocarcinoma. Here leveraging single cell RNA sequencing data, we demonstrate that trafficking and adhesion process of activated T cells are defected in genetically engineered Kras-driven mouse model with Lkb1 conditional knockout. LKB1 mutant cancer cells result in marked suppression of intercellular adhesion molecule-1 (ICAM1). Ectopic expression of Icam1 in Lkb1-deficient tumor increases homing and activation of adoptively transferred SIINFEKL-specific CD8+ T cells, reactivates tumor-effector cell interactions and re-sensitises tumors to ICB. Further discovery proves that CDK4/6 inhibitors upregulate ICAM1 transcription by inhibiting phosphorylation of retinoblastoma protein RB in LKB1 deficient cancer cells. Finally, a tailored combination strategy using CDK4/6 inhibitors and anti-PD-1 antibodies promotes ICAM1-triggered immune response in multiple Lkb1-deficient murine models. Our findings renovate that ICAM1 on tumor cells orchestrates anti-tumor immune response, especially for adaptive immunity.

Combined transcriptome and metabolome analysis reveals the effects of light quality on maize hybrids.

BACKGROUND: Heterosis, or hybrid vigor, refers to the phenotypic superiority of an F1 hybrid relative to its parents in terms of growth rate, biomass production, grain yield, and stress tolerance. Light is an energy source and main environmental cue with marked impacts on heterosis in plants. Research into the production applications and mechanism of heterosis has been conducted for over a century and a half, but little is known about the effect of light on plant heterosis. RESULTS: In this study, an integrated transcriptome and metabolome analysis was performed using maize (Zea mays L.) inbred parents, B73 and Mo17, and their hybrids, B73 × Mo17 (BM) and Mo17 × B73 (MB), grown in darkness or under far-red, red, or blue light. Most differentially expressed genes (73.72-92.50%) and differentially accumulated metabolites (84.74-94.32%) exhibited non-additive effects in BM and MB hybrids. Gene Ontology analysis revealed that differential genes and metabolites were involved in glutathione transfer, carbohydrate transport, terpenoid biosynthesis, and photosynthesis. The darkness, far-red, red, and blue light treatments were all associated with phenylpropanoid-flavonoid biosynthesis by Weighted Gene Co-expression Network Analysis and Kyoto Encyclopedia of Genes and Genomes enrichment analysis. Five genes and seven metabolites related to phenylpropanoid-flavonoid biosynthesis pathway were identified as potential contributors to the interactions between maize heterosis and light conditions. Consistent with the strong mid-parent heterosis observed for metabolites, significant increases in both fresh and dry weights were found in the MB and BM hybrids compared with their inbred parents. Unexpectedly, increasing light intensity resulted in higher biomass heterosis in MB, but lower biomass heterosis in BM. CONCLUSIONS: The transcriptomic and metabolomic results provide unique insights into the effects of light quality on gene expression patterns and genotype-environment interactions, and have implications for gene mining of heterotic loci to improve maize production.

Mechanistic insight into gel formation of co-amorphous resveratrol and piperine during dissolution process.

Different from previous co-amorphous systems, co-amorphous resveratrol and piperine (namely RES-PIP CM) showed much lower dissolution in comparison to the original two crystalline drugs owing to its gel formation during dissolution. The purpose of this study is to investigate the mechanism of gel formation and seek strategies to eliminate such gelation. It was found that the dissolution performance of RES-PIP CM and the properties of formed gels were significantly affected by the medium temperature and stoichiometric ratio of components. Multiple characterization results confirmed that the gelation process underwent the decrease of Tg caused by water plasticization, and then entered into its supercooled liquid state with high viscosity, accompanied by self-assembly of molecules. Furthermore, the study answered the question that whether such gelation of RES-PIP CM could be eliminated by porous carrier materials. The materials, mesoporous silica (MES) and attapulgite (ATT), provided barrier and well separation between molecules and particles of RES-PIP CM by the pore steric hindrance, and impeded the self-assembly and aggregation, hence achieving the degelation and dissolution improvement. The present study highlights the importance of recognizing gelation potential of some co-amorphous formulations, and provides an effective strategy to eliminate gelation in developing high quality co-amorphous drug products.

Interstitial pneumonitis associated with combined regimen of immunotherapy and conventional therapies-pharmacovigilance database analysis with real-world data validation.

BACKGROUND: Immune checkpoint inhibitor (ICI) therapy combined with conventional therapies is being broadly applied in non-small cell lung cancer (NSCLC) patients. However, the risk of interstitial pneumonitis (IP) following a combined regimen is incompletely characterized. METHODS: A total of 46,127 NSCLC patients were extracted for disproportionality analyses of IP from the Food and Drug Administration's Adverse Event Reporting System (FAERS) database. A total of 1108 NSCLC patients who received ICI treatment at Nanfang Hospital of Southern Medical University were collected and utilized for real-world validation. RESULTS: Of the 46,127 patients with NSCLC, 3830 cases (8.3%; 95% confidence interval [CI], 8.05-8.56) developed IP. Multivariable logistic regression analyses revealed that the adjusted ROR of ICI combined with radiation (RT) was the highest (121.69; 95% CI, 83.60-184.96; P < 0.0001) among all therapies, while that of ICI combined with chemotherapy (CHEMO) or targeted therapy (TARGET) was 0.90 (95% CI, 0.78-1.04; P = 0.160) and 1.49 (95% CI, 0.95-2.23; P = 0.065), respectively, using ICI monotherapy as reference. Furthermore, analyses from our validation cohort of 1108 cases showed that the adjusted odds ratio of ICI combined with RT was the highest (12.25; 95% CI, 3.34-50.22; P < 0.01) among all the therapies, while that of ICI combined with CHEMO or TARGET was 2.32 (95% CI, 0.89-7.92; P = 0.12) and 0.66 (95% CI, 0.03-4.55; P = 0.71), respectively, using ICI monotherapy as reference. CONCLUSIONS: Compared with ICI monotherapy, ICI combined with RT, rather than with CHEMO or TARGET, is associated with a higher risk of IP in NSCLC patients. Hence, patients receiving these treatments should be carefully monitored for IP.

Genome-wide identification and functional analysis of the TCP gene family in rye (Secale cereale L.).

TEOSINTE BRANCHED1/CYCLOIDEA/PCF (TCP) proteins are plant-specific transcription factors that play significant roles in plant growth, development, and stress response. Rye is a high-value crop with strong resistance to adverse environments. However, the functions of TCP proteins in rye are rarely reported. Based on a genome-wide analysis, the present study identified 26 TCP genes (ScTCPs) in rye. Mapping showed an uneven distribution of the ScTCP genes on the seven rye chromosomes and detected three pairs of tandem duplication genes. Phylogenetic analysis divided these genes into PCF (Proliferrating Cell Factors), CIN (CINCINNATA), and CYC (CYCLOIDEA)/TB1 (Teosinte Branched1) classes, which showed the highest homology between rye and wheat genes. Analysis of miRNA targeting sites indicated that five ScTCP genes were identified as potential targets of miRNA319. Promoter cis-acting elements analysis indicated that ScTCPs were regulated by light signals. Further analysis of the gene expression patterns and functional annotations suggested the role of a few ScTCPs in grain development and stress response. In addition, two TB1 homologous genes (ScTCP9 and ScTCP10) were identified in the ScTCP family. Synteny analysis showed that TB1 orthologous gene pairs existed before the ancestral divergence. Finally, the yeast two-hybrid assay and luciferase complementation imaging assay proved that ScTCP9, localized in the nucleus, interacts with ScFT (Flowering locus T), indicating their role in regulating flowering time. Taken together, this comprehensive study of ScTCPs provides important information for further research on gene function and crop improvement.

PARP Inhibition Induces Synthetic Lethality and Adaptive Immunity in LKB1-Mutant Lung Cancer.

Contradictory characteristics of elevated mutational burden and a "cold" tumor microenvironment (TME) coexist in liver kinase B1 (LKB1)-mutant non-small cell lung cancers (NSCLC). The molecular basis underlying this paradox and strategies tailored to these historically difficult to treat cancers are lacking. Here, by mapping the single-cell transcriptomic landscape of genetically engineered mouse models with Kras versus Kras/Lkb1-driven lung tumors, we detected impaired tumor-intrinsic IFNγ signaling in Kras/Lkb1-driven tumors that explains the inert immune context. Mechanistic analysis showed that mutant LKB1 led to deficiency in the DNA damage repair process and abnormally activated PARP1. Hyperactivated PARP1 attenuated the IFNγ pathway by physically interacting with and enhancing the poly(ADP-ribosyl)ation of STAT1, compromising its phosphorylation and activation. Abrogation of the PARP1-driven program triggered synthetic lethality in NSCLC on the basis of the LKB1 mutation-mediated DNA repair defect, while also restoring phosphorylated STAT1 to favor an immunologically "hot" TME. Accordingly, PARP1 inhibition restored the disrupted IFNγ signaling and thus mounted an adaptive immune response to synergize with PD-1 blockade in multiple LKB1-deficient murine tumor models. Overall, this study reveals an unexplored interplay between the DNA repair process and adaptive immune response, providing a molecular basis for dual PARP1 and PD-1 inhibition in treating LKB1-mutant NSCLC. SIGNIFICANCE: Targeting PARP exerts dual effects to overcome LKB1 loss-driven immunotherapy resistance through triggering DNA damage and adaptive immunity, providing a rationale for dual PARP and PD-1 inhibition in treating LKB1-mutant lung cancers.

Organ-specific metastatic landscape dissects PD-(L)1 blockade efficacy in advanced non-small cell lung cancer: applicability from clinical trials to real-world practice.

BACKGROUND: Organ-specific metastatic context has not been incorporated into the clinical practice of guiding programmed death-(ligand) 1 [PD-(L)1] blockade, due to a lack of understanding of its predictive versus prognostic value. We aim at delineating and then incorporating both the predictive and prognostic effects of the metastatic-organ landscape to dissect PD-(L)1 blockade efficacy in non-small cell lung cancer (NSCLC). METHODS: A total of 2062 NSCLC patients from a double-arm randomized trial (OAK), two immunotherapy trials (FIR, BIRCH), and a real-world cohort (NFyy) were included. The metastatic organs were stratified into two categories based on their treatment-dependent predictive significance versus treatment-independent prognosis. A metastasis-based scoring system (METscore) was developed and validated for guiding PD-(L)1 blockade in clinical trials and real-world practice. RESULTS: Patients harboring various organ-specific metastases presented significantly different responses to immunotherapy, and those with brain and adrenal gland metastases survived longer than others [overall survival (OS), p = 0.0105; progression-free survival (PFS), p = 0.0167]. In contrast, survival outcomes were similar in chemotherapy-treated patients regardless of metastatic sites (OS, p = 0.3742; PFS, p = 0.8242). Intriguingly, the immunotherapeutic predictive significance of the metastatic-organ landscape was specifically presented in PD-L1-positive populations (PD-L1 > 1%). Among them, a paradoxical coexistence of a favorable predictive effect coupled with an unfavorable prognostic effect was observed in metastases to adrenal glands, brain, and liver (category I organs), whereas metastases to bone, pleura, pleural effusion, and mediastinum yielded consistent unfavorable predictive and prognostic effects (category II organs). METscore was capable of integrating both predictive and prognostic effects of the entire landscape and dissected OS outcome of NSCLC patients received PD-(L)1 blockade (p < 0.0001) but not chemotherapy (p = 0.0805) in the OAK training cohort. Meanwhile, general performance of METscore was first validated in FIR (p = 0.0350) and BIRCH (p < 0.0001), and then in the real-world NFyy cohort (p = 0.0181). Notably, METscore was also applicable to patients received PD-(L)1 blockade as first-line treatment both in the clinical trials (OS, p = 0.0087; PFS, p = 0.0290) and in the real-world practice (OS, p = 0.0182; PFS, p = 0.0045). CONCLUSIONS: Organ-specific metastatic landscape served as a potential predictor of immunotherapy, and METscore might enable noninvasive forecast of PD-(L)1 blockade efficacy using baseline radiologic assessments in advanced NSCLC.

RGN1 controls grain number and shapes panicle architecture in rice.

Yield in rice is determined mainly by panicle architecture. Using map-based cloning, we identified an R2R3 MYB transcription factor REGULATOR OF GRAIN NUMBER1 (RGN1) affecting grain number and panicle architecture. Mutation of RGN1 caused an absence of lateral grains on secondary branches. We demonstrated that RGN1 controls lateral grain formation by regulation of LONELY GUY (LOG) expression, thus controlling grain number and shaping panicle architecture. A novel favourable allele, RGN1C , derived from the Or-I group in wild rice affected panicle architecture by means longer panicles. Identification of RGN1 provides a theoretical basis for understanding the molecular mechanism of lateral grain formation in rice; RGN1 will be an important gene resource for molecular breeding for higher yield.

Agmatine and glycolipid metabolism. / 胍丁胺与糖脂代谢.

The prevalence of abnormal glucose and lipid metabolism and its relevant diseases has increased year by year, and it has become a problem that threatens human health. Therefore, finding a more effective way to prevent and treat diseases related to abnormal glucose and lipid metabolism has become an urgent public problem. Agmatine is a polyamine substance which widely presents in mammals.It is a metabolite produced by decarboxylation of L-arginine under the action of arginine decarboxylase, hence also known as decarboxylated arginine. Its biological effects have been confirmed. Previous studies have shown that agmatine possesses anti-diabetic effects in diabetic animals. Agmatine not only increases the insulin secretion form ß-pancreatic cells to inhibit the hyperglycemia, but also attenuates insulin resistance in rats. Agmatine also plays a positive role in lipid metabolism disorders and related diseases by modulating lipid metabolism and fatty acid oxidation.

De Novo Mutation in Non-Tyrosine Kinase Domain of ROS1 as a Potential Predictor of Immune Checkpoint Inhibitors in Melanoma.

PURPOSE: Despite the success of targeted therapy in c-ros oncogene 1 (ROS1)-rearranged cancers, especially non-small cell lung cancer (NSCLC), the clinical significance of ROS1 de novo mutation has not yet been understood. We sought to elucidate the predictive effect of ROS1 mutation for immune checkpoint inhibitor (ICI) therapy in melanoma. METHODS: The Cancer Genome Atlas [TCGA (n = 10967)] and Memorial Sloan Kettering Cancer Center [MSK (n = 10,945)] datasets, as well as two clinical cohorts of melanoma received ICI [CA209-038 (n = 73) and MEL-IPI (n = 110)], were included to explore the prevalence, prognostic effect, and immunotherapeutic predictive effect of ROS1 mutation in melanoma. Overall survival (OS) was defined as the primary outcome. RESULTS: Overall, melanoma accounted for the highest proportion of ROS1 mutation (~20%) which made up the majority (~95%) of the ROS1-alterated cases. Remarkably, ROS1 mutation yielded longer OS from ICI than the wild-type counterpart in the MSK melanoma population [hazard ratio (HR) 0.47, 95% confidence interval (CI) 0.30-0.74], and two external melanoma cohorts (CA209-038: HR 0.42, 95% CI 0.20-0.89; MEL-IPI: HR 0.55, 95% CI 0.34-0.91), without affecting the prognosis of patients. Elevated tumor mutational burden and enrichment of DNA damage repair was observed in ROS1 mutated patients, providing an explanation for the favorable responses to ICI therapy. Precisely, ROS1 mutation in non-protein tyrosine kinase (PTK) domain but not PTK mutation was responsible for the immunotherapy-specific responses of the ROS1 mutated patients in melanoma. CONCLUSIONS: Collectively, ROS1 mutation, specifically the non-PTK mutation, is a potential predictor of ICI therapy in melanoma, which is distinct from the well-established role of ROS1 rearrangement for targeted therapy in NSCLC.

Integrative evaluation of primary and metastatic lesion spectrum to guide anti-PD-L1 therapy of non-small cell lung cancer: results from two randomized studies.

Objectives: Clinical benefits of immune-checkpoint blockade (ICB) versus standard chemotherapy have been established in unselected non-small cell lung cancer (NSCLC). However, the response to ICB therapy among patients is heterogeneous in clinical practice. Materials and Methods: We retrospectively assessed the predicitive effect of the primary and metastatic lesion spectrum (baseline sum of the longest diameters [SLD], number of metastatic sites and specific organ metastases) on the efficacy of atezolizumab over docetaxel in OAK and POPLAR trial cohorts. A decision model, termed DSO (Diameter-Site-Organ), based on the spectrum was developed and validated for guiding ICB. Results: Higher SLD (>38 mm) and more metastatic sites (≥2) were characterized with pronounced overall survival (OS) benefits from atezolizumab versus docetaxel. Specifically, adrenal gland and brain metastases were identified as favorable predictors of atezolizumab treatment. The DSO model was developed in the discovery cohort to integrate the directive effect of the primary and metastatic lesion spectrum. Remarkably, a general pattern of enhanced efficacy of atezolizumab versus docetaxel was observed along with the increase of the DSO score. For patients with DSO score > 0, atezolizumab yielded a significantly prolonged OS than docetaxel, whereas OS was generally similar between two treatments in patients with DSO score ≤ 0. Equivalent findings were also seen in the internal and external validation cohorts. Conclusions: The response to anti-PD-L1 therapy among patients varied with the primary and metastatic lesion spectrum. The DSO-based system might provide promising medication guidance for ICB treatment in NSCLC patients.

Clinical Characteristics of Patients With Progressive and Non-progressive Coronavirus Disease 2019: Evidence From 365 Hospitalised Patients in Honghu and Nanchang, China.

Background: Coronavirus disease (COVID-19) has swept around the globe and led to a worldwide catastrophe. Studies examining the disease progression of patients with non-severe disease on admission are scarce but of profound importance in the early identification of patients at a high risk of deterioration. Objectives: To elucidate the differences in clinical characteristics between patients with progressive and non-progressive COVID-19 and to determine the risk factors for disease progression. Study design: Clinical data of 365 patients with non-severe COVID-19 from 1 January 2020 to 18 March 2020 were retrospectively collected. Patients were stratified into progressive and non-progressive disease groups. Univariate and multivariate logistic regression analyses were performed to determine the independent risk factors for disease progression. Results: Compared with patients with non-progressive disease, those who progressed to severe COVID-19 were older and had significantly decreased lymphocyte and eosinophil counts; increased neutrophil and platelet counts; lower albumin levels; higher levels of lactate dehydrogenase, C-reactive protein (CRP), creatinine, creatinine kinase, and urea nitrogen; and longer prothrombin times. Hypertension, fever, fatigue, anorexia, bacterial coinfection, bilateral patchy shadowing, antibiotic and corticosteroid administration, and oxygen support had a significantly higher incidence among patients with progressive disease. A significantly longer duration of hospital stay was also observed in patients with progressive disease. Bilateral patchy shadowing (OR = 4.82, 95% CI: 1.33-17.50; P = 0.017) and elevated levels of creatinine (OR =6.24, 95% CI: 1.42-27.40; P = 0.015), and CRP (OR = 7.28, 95% CI: 2.56-20.74; P < 0.001) were independent predictors for disease progression. Conclusion: The clinical characteristics of patients with progressive and non-progressive COVID-19 were significantly different. Bilateral patchy shadowing and increased levels of creatinine, and CRP were independent predictors of disease progression.

[Spindle assembly checkpoint complex-related genes TTK and MAD2L1 are over-expressed in lung adenocarcinoma: a big data and bioinformatics analysis].

OBJECTIVE: To screen the key genes related to the prognosis of lung adenocarcinoma through big data analysis and explore their clinical value and potential mechanism. METHODS: We analyzed GSE18842, GSE27262, and GSE33532 gene expression profile data obtained from the Gene Expression Omnibus (GEO). Bioinformatics methods were used to screen the differentially expressed genes in lung adenocarcinoma tissues and KEGG and GO enrichment analysis was performed, followed by PPI interaction network analysis, module analysis, differential expression analysis, and prognosis analysis. The expressions of MAD2L1 and TTK by immunohistochemistry were verified in 35 non-small cell lung cancer specimens and paired adjacent tissues. RESULTS: We identified a total of 256 genes that showed significant differential expressions in lung adenocarcinoma, including 66 up-regulated and 190 down-regulated genes. Thirty-two up-regulated core genes were screened by functional analysis, and among them 29 were shown to significantly correlate with a poor prognosis of patients with lung adenocarcinoma. All the 29 genes were highly expressed in lung adenocarcinoma tissues compared with normal lung tissues and were mainly enriched in cell cycle pathways. Seven of these key genes were closely related to the spindle assembly checkpoint (SAC) complex and responsible for regulating cell behavior in G2/M phase. We selected SAC-related proteins TTK and MAD2L1 to test their expressions in clinical tumor samples, and detected their overexpression in lung adenocarcinoma tissues as compared with the adjacent tissues. CONCLUSIONS: Seven SAC complex-related genes, including TTK and MAD2L1, are overexpressed in lung adenocarcinoma tissues with close correlation with the prognosis of the patients.

Development and Validation of a Deep Learning-Based Model Using Computed Tomography Imaging for Predicting Disease Severity of Coronavirus Disease 2019.

OBJECTIVES: Coronavirus disease 2019 (COVID-19) is sweeping the globe and has resulted in infections in millions of people. Patients with COVID-19 face a high fatality risk once symptoms worsen; therefore, early identification of severely ill patients can enable early intervention, prevent disease progression, and help reduce mortality. This study aims to develop an artificial intelligence-assisted tool using computed tomography (CT) imaging to predict disease severity and further estimate the risk of developing severe disease in patients suffering from COVID-19. MATERIALS AND METHODS: Initial CT images of 408 confirmed COVID-19 patients were retrospectively collected between January 1, 2020 and March 18, 2020 from hospitals in Honghu and Nanchang. The data of 303 patients in the People's Hospital of Honghu were assigned as the training data, and those of 105 patients in The First Affiliated Hospital of Nanchang University were assigned as the test dataset. A deep learning based-model using multiple instance learning and residual convolutional neural network (ResNet34) was developed and validated. The discrimination ability and prediction accuracy of the model were evaluated using the receiver operating characteristic curve and confusion matrix, respectively. RESULTS: The deep learning-based model had an area under the curve (AUC) of 0.987 (95% confidence interval [CI]: 0.968-1.00) and an accuracy of 97.4% in the training set, whereas it had an AUC of 0.892 (0.828-0.955) and an accuracy of 81.9% in the test set. In the subgroup analysis of patients who had non-severe COVID-19 on admission, the model achieved AUCs of 0.955 (0.884-1.00) and 0.923 (0.864-0.983) and accuracies of 97.0 and 81.6% in the Honghu and Nanchang subgroups, respectively. CONCLUSION: Our deep learning-based model can accurately predict disease severity as well as disease progression in COVID-19 patients using CT imaging, offering promise for guiding clinical treatment.

Development and validation of the HNC-LL score for predicting the severity of coronavirus disease 2019.

BACKGROUND: Information regarding risk factors associated with severe coronavirus disease (COVID-19) is limited. This study aimed to develop a model for predicting COVID-19 severity. METHODS: Overall, 690 patients with confirmed COVID-19 were recruited between 1 January and 18 March 2020 from hospitals in Honghu and Nanchang; finally, 442 patients were assessed. Data were categorised into the training and test sets to develop and validate the model, respectively. FINDINGS: A predictive HNC-LL (Hypertension, Neutrophil count, C-reactive protein, Lymphocyte count, Lactate dehydrogenase) score was established using multivariate logistic regression analysis. The HNC-LL score accurately predicted disease severity in the Honghu training cohort (area under the curve [AUC]=0.861, 95% confidence interval [CI]: 0.800-0.922; P<0.001); Honghu internal validation cohort (AUC=0.871, 95% CI: 0.769-0.972; P<0.001); and Nanchang external validation cohort (AUC=0.826, 95% CI: 0.746-0.907; P<0.001) and outperformed other models, including CURB-65 (confusion, uraemia, respiratory rate, BP, age ≥65 years) score model, MuLBSTA (multilobular infiltration, hypo-lymphocytosis, bacterial coinfection, smoking history, hypertension, and age) score model, and neutrophil-to-lymphocyte ratio model. The clinical significance of HNC-LL in accurately predicting the risk of future development of severe COVID-19 was confirmed. INTERPRETATION: We developed an accurate tool for predicting disease severity among COVID-19 patients. This model can potentially be used to identify patients at risks of developing severe disease in the early stage and therefore guide treatment decisions. FUNDING: This work was supported by the National Nature Science Foundation of China (grant no. 81972897) and Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2015).

(Fe,N-codoped carbon nanotube)/(Fe-based nanoparticle) nanohybrid derived from Fe-doped g-C3N4: A superior catalyst for oxygen reduction reaction.

Transition metal- and N-codoped carbon nanotubes (CNTs) have superior catalytic activity because the curling surface enhances the bonding ability of atoms within CNTs to other species. However, it is a great challenge to prepare CNTs with transition metal- and N-doped at high level during the growth of CNTs. Here, (Fe,N-codoped CNT)/(Fe-based nanoparticle) (Fe,N-CNT/FeNP) hybrid nanostructures are for the first time prepared through the carbonization of Fe-doped g-C3N4. The doping of Fe and N is simultaneously realized during the formation of CNTs. Meanwhile, the abundant and homogeneous Fe and N in Fe-doped g-C3N4 ensure high-level and uniform doping of Fe and N in CNTs. The Fe,N-CNT/FeNP hybrid nanostructures have several types of active components, including homogeneously distributed coordinating Fe moieties (FeCxNy or FeNx) and CFe15.1 nanoparticles embedded in Fe,N-CNTs, towards oxygen reduction reaction (ORR). A superior ORR electrocatalytic performance is therefore obtained on the Fe,N-CNT/FeNP nanohybrids. Our preparation method opens an avenue to preparation of CNTs with transition metal- and N-doping at high-level, and the superior performance of Fe,N-CNT/FeNP nanostructures for ORR will be very helpful to the development of fuel cells and metal-air batteries.

Control of the emission from electric and magnetic dipoles by gold nanocup antennas.

The control of the emission from electric and magnetic dipoles is highly desired for the development of optic chips. Although the emission of electric dipole has been successfully controlled by plasmonic nanoantenna, the control of magnetic dipole emission is relatively difficult. Here, we systematically study the effect of electric and magnetic modes of Au nanocups on the emission of electric and magnetic dipoles. The emission of electric dipole can be enhanced by both the electric and magnetic mode of the Au nanocup, while the emission of the magnetic dipole is only increased by the magnetic mode. The enhancement exhibits wavelength dependence. The wavelength of the largest enhancement is determined by the resonance wavelength of electric and magnetic modes. The enhancement values for electric and magnetic dipoles are determined by the near-field electric and magnetic field enhancements, respectively. More importantly, the emission pattern of magnetic dipole is greatly modified by the magnetic mode of Au nanocup. The directional emission of magnetic dipole is first time realized by use of the magnetic mode of the Au nanocup. Our findings deepen the understanding of the plasmon-controlled emission of electric and magnetic dipoles and will be very helpful to the development of the nanophotonic chips.