Systematically analyzed molecular characteristics of lung adenocarcinoma using metabolism-related genes classification.

High heterogeneity of lung adenocarcinoma (LUAD) is a major clinical challenge. This study aims to characterize the molecular features of LUAD through classification based on metabolism-related genes. A total of 500 LUAD samples from The Cancer Genome Atlas (TCGA) and 612 from Gene Expression Omnibus (GEO) were integrated with 2,753 metabolism-related genes to determine the molecular classification. Systematic bioinformatics analysis was used to conduct correlation analysis between metabolism-related classification and molecular characteristics of LUAD. LUAD patients were divided into three molecular clusters (C1-C3). Survival analysis revealed that C1 and C2 showed good and poor prognoses, respectively. Associational analysis of classification and molecular characteristics revealed that C1 was associated with low pathological stage, metabolic pathways, high metabolic process, active immune process and checkpoint, sensitive drug response, as well as a low genetic mutation. Nevertheless, C2 was associated with high pathological stage, carcinogenic pathways, low metabolic process, inactive immune signatures, resistant drug response, and frequent genetic mutation. Eventually, a classifier with 60 metabolic genes was constructed, confirming the robustness of molecular classification on LUAD. Our findings promote the understanding of LUAD molecular characteristics, and the research data may be used for providing information be helpful for clinical diagnosis and treatment.

LncRNA LINC00115 facilitates lung cancer progression through miR-607/ITGB1 pathway.

Dysregulated long noncoding RNAs (lncRNAs) have potential roles in various cancer types. The objective of this study was to investigate the expression and the underlying role of long intergenic nonprotein coding RNA 115 (LINC00115) in lung cancer. The relative expression of LINC00115 and miR-607 in tumor tissues and cells was detected by real-time PCR. After overexpression or knockdown of LINC00115 expression in tumor cells, the changes in the proliferation, migration, and invasion capacities were detected via Counting Kit-8 (CCK-8) assay and transwell assays. The interplay among LINC00115, miR-607, and integrin ß1 (ITGB1) was confirmed by bioinformatics analyses and luciferase reporter assay. In addition, tumor cells with LINC00115 knockdown were injected into nude mice to investigate the effect of LINC00115 on tumorigenesis in vivo. LINC00115 was highly expressed in tumor tissues and cells. LINC00115 promoted the malignant properties of tumor cells. Investigation to its molecular mechanism revealed that LINC00115 functioned as a competitive endogenous RNA (ceRNA), regulating the expression of ITGB1 by sponging miR-607 to affect tumor growth. The LINC00115/miR-607/ITGB1 signaling axis might be a novel therapeutic target in lung cancer.

Candidemia in Adults at a Tertiary Hospital in China: Clinical Characteristics, Species Distribution, Resistance, and Outcomes.

BACKGROUND: Candidemia is one of the most common nosocomial bloodstream infections. Early diagnosis and antifungal treatment improve clinical outcomes in some studies but not all, with diverse data reported from different institutions. Similarly, antifungal resistance is more common in the USA than in Europe, but there is little data regarding the microbiology and clinical course of candidemia in adult patients in Asia. AIMS: (1) To capture species distribution and drug resistance rates among Candida bloodstream isolates, (2) to describe clinical features of candidemia, and (3) to identify factors associated with all-cause mortality, with emphasis on early initiation of antifungal treatment, at a large tertiary University Hospital in China. METHODS: In this single-center retrospective study, we identified all patients with candidemia, between 2008 and 2014. Demographic and clinical characteristics, microbiological information, details of antifungal therapy and clinical outcomes were collected. RESULTS: We studied 166 patients. 71 (42.8%) had cancer. Candida albicans was the most frequent species (37.3%), followed by C. parapsilosis (24.1%), C. tropicalis (22.8%), and C. glabrata (14.5%). Antifungal resistance was more frequent in non-albicans strains and especially C. glabrata. Twenty patients received inappropriate treatment with all-cause mortality of 35%. The remaining 146 patients had significantly lower mortality (21.9%, P = 0.045). Among patients who received antifungal treatment, mortality rate increased with time to appropriate antifungal therapy (AAT): 13.7%, for < 24 h, 21.1% for 24-48 h, 23.1% for > 48 h, and 32.4% among patients who received no AT (χ2 for trend P = 0.039). Initiating AAT more than 24 h after blood culture collection was an independent risk factor for mortality, after adjustment for other confounders (OR 7.1, 95% CI 1.3-39.4, P = 0.024). CONCLUSIONS: Candida albicans was the most frequent cause of candidemia at a large tertiary hospital in China, but antifungal resistance is a growing concern among non-albicans Candida species. The mortality rate of patients treated with ineffective antifungal agents based on in vitro susceptibilities was similar to that of patients who received no treatment at all, and delayed initiation of antifungal treatment was associated with increased risk of death.

Design of wafer-bonded structures for near room temperature Geiger-mode operation of germanium on silicon single-photon avalanche photodiode.

We investigate the effect of temperature on the single-photon properties of four germanium/silicon (Ge/Si) single-photon avalanche photodiodes (SPADs), which are fabricated by Ge-on-Si direct epitaxial growth, Ge-on-Si two-step epitaxial growth, Ge/Si direct wafer bonding, and Si/Si hydrophobic bonding, respectively. It is found that the wafer-bonded Ge/Si SPAD exhibits extremely low dark current and dark count rate (DCR) compared with the epitaxial ones at 250 and 300 K. This implies that the wafer-bonding technique is a possible candidate for the fabrication of Ge/Si SPAD, which can be operated at near room temperature. Additionally, due to the low DCR and high operation temperature, the wafer-bonded Ge/Si SPAD shows extremely high pulse repetition rate (∼28 MHz in theory for DCR=108 Hz). That is, the wafer-bonded Ge/Si SPAD can be used in a high-speed field. Finally, the effect of voltage pulse width, number of photons per pulse, and hold-off time on the performance of the wafer-bonded Ge/Si SPAD at different temperatures is also clarified.

Voltage sharing effect and interface state calculation of a wafer-bonding Ge/Si avalanche photodiode with an interfacial GeO2 insulator layer.

The tunneling effect and interface state in the p-Ge/GeO2p-Si structure of a wafer-bonding Ge/Si avalanche photodiode (APD) are investigated. It is found that the thin interfacial GeO2 layer (1-2 nm) formed by the hydrophilic reaction at the wafer-bonding interface significantly affects the performance of the Ge/Si APD. With the increase of the GeO2 thickness, the dark current of the Ge/Si APD decreases enormously due to the blocking effect of this GeO2 layer. Owing to the carrier accumulation in Ge layer under illumination condition, the voltage sharing effect of the GeO2 layer (thicker) becomes serious, leading to the absence of the electric field in Ge layer. The photon-generated electrons at Ge/GeO2 interface can be captured and released by the interface states at certain reverse bias. This can adjust the avalanche current of the Ge/Si APD. The stronger interface recombination induced by the larger interface state density (ISD) results in the decrease of the electric field in Ge layer. This increases the transit time of carriers, which in turn decreases the 3dB-bandwidth. Due to the drastic increase of the dark current (larger ISD), the gain of the Ge/Si APD decreases.

Bioinformatics analysis based on DNA methylation data identified in lung adenocarcinoma subgroups with different immune characteristics and clinical outcomes.

Background: DNA methylation can be used to predict clinical outcomes and improve the classification of tumors. The present study aimed to develop a new lung adenocarcinoma (LUAD) classification system according to the immune cell gene-related methylation sites and to reveal the survival outcomes, clinical characteristics, immune cell infiltration, stem cell characteristics, and genomic variations of each molecular subgroup. Methods: The DNA methylation sites of LUAD samples collected from The Cancer Genome Atlas (TCGA) database were analyzed, and the prognosis-related differential methylation sites (DMS) were screened. Consistent clustering of the samples was conducted using ConsensusClusterPlus, and the classification results were verified by principal component analysis (PCA). The survival and clinical results, immune cell infiltration, stemness, DNA mutation, and copy number variation (CNV) of each molecular subgroup were analyzed. Results: A total of 40 DMS were obtained by difference and univariate COX analyses, and the TCGA LUAD samples were divided into three subgroups: cluster 1 (C1), cluster 2 (C2), and cluster 3 (C3). Among these subgroups, the overall survival (OS) of C3 was significantly higher than that of C1 and C2. Compared with C1 and C3, C2 had the lowest innate immune cell and adaptive immune cell infiltration scores; the lowest stromal score, immune score, and iconic immune checkpoint expression; and the highest expression of messenger RNA (mRNA) expression-based stemness indices (mRNAsi), DNA methylation-based stemness index (mDNAsi), and tumor mutational burden (TMB). Conclusions: In this study, we proposed a LUAD typing system based on DMS, which was closely related to the survival, clinical features, immune characteristics, and genomic variations of LUAD, and may contribute to the development of personalized therapy for new specific subtypes.

Identification of a novel diagnosis model based on 5 hub genes for chronic thromboembolic pulmonary hypertension.

BACKGROUND: As a type of precapillary pulmonary hypertension, chronic thromboembolic pulmonary hypertension (CTEPH) results from incomplete pulmonary embolism resolution. In this study, we aimed to determine biomarker genes for predicting the prognosis of CTEPH. METHOD: RNAseq of CTEPH was collected from the public database, namely Gene Expression Omnibus (GEO), including GSE84538 and GSE188938, which combined a dataset (GSE). Differentially expressed genes (DEG) or miRNA (DEM) were identified by limma package. Functional enrichment analysis was performed by the WebGestaltR package. Then, the miRNA-mRNA network was presented by Cytoscape, and the protein-protein interactions (PPI) network was constructed by STRING. MCODE was mined by mature MCODE algorithm. Immune infiltration analysis was conducted by ESTIMATER and ssGSEA analysis. A diagnosis model was established by SVM algorithm. RESULT: In the GSE dataset, CTEPH samples had a lower GOBP_RESPONSE_TO_OXIDATIVE_STRESS score. A total of 628 DEGs and 31 DEMs were identified between CTEPH and normal samples. Afterward, DEGs were intersected with genes, which correlated with the GOBP_RESPONSE_TO_OXIDATIVE_STRESS score. A 26 DEMs-152 DEGs network was constructed, and a PPI network was established based on 152 DEGs to find 149 target genes. From the above 149 target genes, 3 modules were extracted to obtain 15 core targets. Finally, 5 hub genes were obtained by the intersection of 15 core targets and genes in MCODE2. A total of 5 hub genes were positively correlated with most immune cell scores as well as GOBP_RESPONSE_TO_OXIDATIVE_STRESS. It was found that a diagnosis model based on 5 hub genes had a well diagnostic ability for CTEPH. CONCLUSION: We identified 5 hub genes associated with oxidative stress. It can be concluded that they may be beneficial in diagnosing CTEPH.

Exosomal circSHKBP1 participates in non-small cell lung cancer progression through PKM2-mediated glycolysis.

Non-small cell lung cancer (NSCLC) has a high morbidity and mortality, and it is imperative to explore the latent pathogenesis mechanism of NSCLC progression to find potential prognostic biomarkers and therapeutic targets. The present study aimed to explore the biological function of circSHKBP1 in NSCLC. circSHKBP1 was found to be upregulated in NSCLC tissues and cell lines and was enriched in exosomes derived from NSCLC cells. Exosomal circSHKBP1 enhanced the proliferation, migration, invasion, and stemness of NSCLC cells. miRNA-1294 was identified as a target for circSHKBP1, and circSHKBP1 upregulated PKM2 expression by sponging miR-1294. Exosomal circSHKBP1 regulated glycolysis through PKM2 in a HIF-1α-dependent manner in NSCLC cells and promoted M2 polarization and macrophage recruitment. Moreover, exosomal circSHKBP1 promoted NSCLC cell growth, metastasis, and M2 infiltration in vivo. Thus, exosomal circSHKBP1 participated in the progression of NSCLC via the miR-1294/PKM2 axis. circSHKBP1 may be potential biomarker for the diagnosis and treatment of NSCLC.

Visual question answering model for fruit tree disease decision-making based on multimodal deep learning.

Visual Question Answering (VQA) about diseases is an essential feature of intelligent management in smart agriculture. Currently, research on fruit tree diseases using deep learning mainly uses single-source data information, such as visible images or spectral data, yielding classification and identification results that cannot be directly used in practical agricultural decision-making. In this study, a VQA model for fruit tree diseases based on multimodal feature fusion was designed. Fusing images and Q&A knowledge of disease management, the model obtains the decision-making answer by querying questions about fruit tree disease images to find relevant disease image regions. The main contributions of this study were as follows: (1) a multimodal bilinear factorized pooling model using Tucker decomposition was proposed to fuse the image features with question features: (2) a deep modular co-attention architecture was explored to simultaneously learn the image and question attention to obtain richer graphical features and interactivity. The experiments showed that the proposed unified model combining the bilinear model and co-attentive learning in a new network architecture obtained 86.36% accuracy in decision-making under the condition of limited data (8,450 images and 4,560k Q&A pairs of data), outperforming existing multimodal methods. The data augmentation is adopted on the training set to avoid overfitting. Ten runs of 10-fold cross-validation are used to report the unbiased performance. The proposed multimodal fusion model achieved friendly interaction and fine-grained identification and decision-making performance. Thus, the model can be widely deployed in intelligent agriculture.

Detection Method of Citrus Psyllids With Field High-Definition Camera Based on Improved Cascade Region-Based Convolution Neural Networks.

Citrus psyllid is the only insect vector of citrus Huanglongbing (HLB), which is the most destructive disease in the citrus industry. There is no effective treatment for HLB, so detecting citrus psyllids as soon as possible is the key prevention measure for citrus HLB. It is time-consuming and laborious to search for citrus psyllids through artificial patrol, which is inconvenient for the management of citrus orchards. With the development of artificial intelligence technology, a computer vision method instead of the artificial patrol can be adopted for orchard management to reduce the cost and time. The citrus psyllid is small in shape and gray in color, similar to the stem, stump, and withered part of the leaves, leading to difficulty for the traditional target detection algorithm to achieve a good recognition effect. In this work, in order to make the model have good generalization ability under outdoor light condition, a high-definition camera to collect data set of citrus psyllids and citrus fruit flies under natural light condition was used, a method to increase the number of small target pests in citrus based on semantic segmentation algorithm was proposed, and the cascade region-based convolution neural networks (R-CNN) (convolutional neural network) algorithm was improved to enhance the recognition effect of small target pests using multiscale training, combining CBAM attention mechanism with high-resolution feature retention network high-resoultion network (HRNet) as feature extraction network, adding sawtooth atrous spatial pyramid pooling (ASPP) structure to fully extract high-resolution features from different scales, and adding feature pyramid networks (FPN) structure for feature fusion at different scales. To mine difficult samples more deeply, an online hard sample mining strategy was adopted in the process of model sampling. The results show that the improved cascade R-CNN algorithm after training has an average recognition accuracy of 88.78% for citrus psyllids. Compared with VGG16, ResNet50, and other common networks, the improved small target recognition algorithm obtains the highest recognition performance. Experimental results also show that the improved cascade R-CNN algorithm not only performs well in citrus psylla identification but also in other small targets such as citrus fruit flies, which makes it possible and feasible to detect small target pests with a field high-definition camera.

SPT20 Regulates the Hog1-MAPK Pathway and Is Involved in Candida albicans Response to Hyperosmotic Stress.

Candida albicans is the most common fungal pathogen and relies on the Hog1-MAPK pathway to resist osmotic stress posed by the environment or during host invasions. Here, we investigated the role of SPT20 in response to osmotic stress. Testing a C. albicans spt20Δ/Δ mutant, we found it was sensitive to osmotic stress. Using sequence alignment, we identified the conserved functional domains between CaSpt20 and ScSpt20. Reconstitution of the Spt20 function in a spt20Δ/CaSPT20 complemented strain found CaSPT20 can suppress the high sensitivity to hyperosmotic stressors, a cell wall stress agent, and antifungal drugs in the Saccharomyces cerevisiae spt20Δ/Δ mutant background. We measured the cellular glycerol accumulation and found it was significantly lower in the C. albicans spt20Δ/Δ mutant strain, compared to the wild type strain SC5314 (P < 0.001). This result was also supported by quantitative reverse transcription-PCR, which showed the expression levels of gene contributing to glycerol accumulation were reduced in Caspt20Δ/Δ compared to wild type (GPD2 and TGL1, P < 0.001), while ADH7 and AGP2, whose expression can lead to glycerol decrease, were induced when cells were exposed to high osmolarity (ADH7, P < 0.001; AGP2, P = 0.002). In addition, we tested the transcription levels of Hog1-dependent osmotic stress response genes, and found that they were significantly upregulated in wild type cells encountering hyperosmolarity, while the expression of HGT10, SKO1, CAT1, and SLP3 were not induced when SPT20 was deleted. Although the transcript of ORF19.3661 and ORF19.4370 in Caspt20Δ/Δ was induced in the presence of 1 M NaCl, the levels were less than what was observed in the wild type (ORF19.3661, P = 0.007; ORF19.4370, P = 0.011). Moreover, the deletion of CaSPT20 in C. albicans reduced phosphorylation levels of Hog1. These findings suggested that SPT20 is conserved between yeast and C. albicans and plays an important role in adapting to osmotic stress through regulating Hog1-MAPK pathway.

Diffusion-kurtosis imaging predicts early radiotherapy response in nasopharyngeal carcinoma patients.

In this prospective study, we analyzed diffusion kurtosis imaging (DKI) parameters to predict the early response to radiotherapy in 23 nasopharyngeal carcinoma (NPC) patients. All patients underwent conventional magnetic resonance imaging (MRI) and DKI before and after radiotherapy. The patients were divided into response (RG; no residual tumors; 16/23 patients) and no-response (NRG; residual tumors; 7/23 patients) groups, based on MRI and biopsy results 3 months after radiotherapy. The maximum diameter of tumors in RG and NRG patients were similar prior to radiotherapy (p=0.103). The pretreatment diffusion coefficient (D) parameters (Daxis, Dmean and Drad) were higher in RG than NRG patients (p=0.022, p=0.027 and p=0.027). Conversely, the pre-treatment fractional anisotropy (FA) and kurtosis coefficient (K) parameters (Kaxis, Kfa, Kmean, Krad and Mkt) were lower in RG than NRG patients (p=0.015, p=0.022, p=0.008, p=0.004, p=0.001, p=0.002). The Krad coefficient (0.76) was the best parameter to predict the radiotherapy response. Based on receiver operating characteristic curve analysis Krad showed 71.4% sensitivity and 93.7% specificity (AUC: 0.897, 95% CI, 0.756-1). Multivariate analysis indicated DKI parameters were independent prognostic factors for the short-term effect in NPC. Thus, DKI predicts the early response to radiotherapy in NPC patients.