Table_1_Identification of Two Subtypes and Prognostic Characteristics of Lung Adenocarcinoma Based on Pentose Phosphate Metabolic Pathway-Related Long Non-coding RNAs.xlsx

This study analyzed the differences in subtypes and characteristics of advanced lung adenocarcinoma (LUAD) patients based on the pentose phosphate metabolic pathway-related long non-coding RNAs (lncRNAs), along with their potential regulatory mechanisms. Using the expression profiling and corresponding clinical information of LUAD patients from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). Differential pathway scores between normal and tumor samples from TCGA were identified by rank-sum tests. Pearson correlation coefficients between pentose phosphate scores of the pentose phosphate samples and lncRNAs of the corresponding datasets were calculated. Next, the clusterProfiler software package was used for functional annotation. Clustering of pentose phosphate-related lncRNAs from LUAD samples categorized two molecular subtypes (C1, and C2). C1 was associated with a lower pentose phosphate score and a good prognosis; the C2 showed a higher pentose phosphate score and was related to poorer prognoses. The C2 was markedly associated with energy metabolic pathways. The expression of most immune cells were markedly higher in C1 subtype. Some crucial immune checkpoints, including CTLA4, CD274, and CD47, were also significantly upregulated in C1 subtype, leading to a higher score of clinical effect on the C1 subtype. Finally, one TF, BACH1, was found to be significantly upregulated in C1 subtypes; the pathways activated by this TF may be associated with tumor progression and poor prognoses. LUAD typing based on pentose phosphate metabolic pathway-related lncRNAs was confirmed. Differences in characteristics between C1 and C2 subtypes improved the current LUAD detection and treatment.</p

Image_2_Identification of Two Subtypes and Prognostic Characteristics of Lung Adenocarcinoma Based on Pentose Phosphate Metabolic Pathway-Related Long Non-coding RNAs.JPEG

This study analyzed the differences in subtypes and characteristics of advanced lung adenocarcinoma (LUAD) patients based on the pentose phosphate metabolic pathway-related long non-coding RNAs (lncRNAs), along with their potential regulatory mechanisms. Using the expression profiling and corresponding clinical information of LUAD patients from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). Differential pathway scores between normal and tumor samples from TCGA were identified by rank-sum tests. Pearson correlation coefficients between pentose phosphate scores of the pentose phosphate samples and lncRNAs of the corresponding datasets were calculated. Next, the clusterProfiler software package was used for functional annotation. Clustering of pentose phosphate-related lncRNAs from LUAD samples categorized two molecular subtypes (C1, and C2). C1 was associated with a lower pentose phosphate score and a good prognosis; the C2 showed a higher pentose phosphate score and was related to poorer prognoses. The C2 was markedly associated with energy metabolic pathways. The expression of most immune cells were markedly higher in C1 subtype. Some crucial immune checkpoints, including CTLA4, CD274, and CD47, were also significantly upregulated in C1 subtype, leading to a higher score of clinical effect on the C1 subtype. Finally, one TF, BACH1, was found to be significantly upregulated in C1 subtypes; the pathways activated by this TF may be associated with tumor progression and poor prognoses. LUAD typing based on pentose phosphate metabolic pathway-related lncRNAs was confirmed. Differences in characteristics between C1 and C2 subtypes improved the current LUAD detection and treatment.</p

Image_1_Identification of Two Subtypes and Prognostic Characteristics of Lung Adenocarcinoma Based on Pentose Phosphate Metabolic Pathway-Related Long Non-coding RNAs.JPEG

This study analyzed the differences in subtypes and characteristics of advanced lung adenocarcinoma (LUAD) patients based on the pentose phosphate metabolic pathway-related long non-coding RNAs (lncRNAs), along with their potential regulatory mechanisms. Using the expression profiling and corresponding clinical information of LUAD patients from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). Differential pathway scores between normal and tumor samples from TCGA were identified by rank-sum tests. Pearson correlation coefficients between pentose phosphate scores of the pentose phosphate samples and lncRNAs of the corresponding datasets were calculated. Next, the clusterProfiler software package was used for functional annotation. Clustering of pentose phosphate-related lncRNAs from LUAD samples categorized two molecular subtypes (C1, and C2). C1 was associated with a lower pentose phosphate score and a good prognosis; the C2 showed a higher pentose phosphate score and was related to poorer prognoses. The C2 was markedly associated with energy metabolic pathways. The expression of most immune cells were markedly higher in C1 subtype. Some crucial immune checkpoints, including CTLA4, CD274, and CD47, were also significantly upregulated in C1 subtype, leading to a higher score of clinical effect on the C1 subtype. Finally, one TF, BACH1, was found to be significantly upregulated in C1 subtypes; the pathways activated by this TF may be associated with tumor progression and poor prognoses. LUAD typing based on pentose phosphate metabolic pathway-related lncRNAs was confirmed. Differences in characteristics between C1 and C2 subtypes improved the current LUAD detection and treatment.</p

Image_3_Identification of Two Subtypes and Prognostic Characteristics of Lung Adenocarcinoma Based on Pentose Phosphate Metabolic Pathway-Related Long Non-coding RNAs.JPEG

This study analyzed the differences in subtypes and characteristics of advanced lung adenocarcinoma (LUAD) patients based on the pentose phosphate metabolic pathway-related long non-coding RNAs (lncRNAs), along with their potential regulatory mechanisms. Using the expression profiling and corresponding clinical information of LUAD patients from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). Differential pathway scores between normal and tumor samples from TCGA were identified by rank-sum tests. Pearson correlation coefficients between pentose phosphate scores of the pentose phosphate samples and lncRNAs of the corresponding datasets were calculated. Next, the clusterProfiler software package was used for functional annotation. Clustering of pentose phosphate-related lncRNAs from LUAD samples categorized two molecular subtypes (C1, and C2). C1 was associated with a lower pentose phosphate score and a good prognosis; the C2 showed a higher pentose phosphate score and was related to poorer prognoses. The C2 was markedly associated with energy metabolic pathways. The expression of most immune cells were markedly higher in C1 subtype. Some crucial immune checkpoints, including CTLA4, CD274, and CD47, were also significantly upregulated in C1 subtype, leading to a higher score of clinical effect on the C1 subtype. Finally, one TF, BACH1, was found to be significantly upregulated in C1 subtypes; the pathways activated by this TF may be associated with tumor progression and poor prognoses. LUAD typing based on pentose phosphate metabolic pathway-related lncRNAs was confirmed. Differences in characteristics between C1 and C2 subtypes improved the current LUAD detection and treatment.</p

Image_4_Identification of Two Subtypes and Prognostic Characteristics of Lung Adenocarcinoma Based on Pentose Phosphate Metabolic Pathway-Related Long Non-coding RNAs.JPEG

This study analyzed the differences in subtypes and characteristics of advanced lung adenocarcinoma (LUAD) patients based on the pentose phosphate metabolic pathway-related long non-coding RNAs (lncRNAs), along with their potential regulatory mechanisms. Using the expression profiling and corresponding clinical information of LUAD patients from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). Differential pathway scores between normal and tumor samples from TCGA were identified by rank-sum tests. Pearson correlation coefficients between pentose phosphate scores of the pentose phosphate samples and lncRNAs of the corresponding datasets were calculated. Next, the clusterProfiler software package was used for functional annotation. Clustering of pentose phosphate-related lncRNAs from LUAD samples categorized two molecular subtypes (C1, and C2). C1 was associated with a lower pentose phosphate score and a good prognosis; the C2 showed a higher pentose phosphate score and was related to poorer prognoses. The C2 was markedly associated with energy metabolic pathways. The expression of most immune cells were markedly higher in C1 subtype. Some crucial immune checkpoints, including CTLA4, CD274, and CD47, were also significantly upregulated in C1 subtype, leading to a higher score of clinical effect on the C1 subtype. Finally, one TF, BACH1, was found to be significantly upregulated in C1 subtypes; the pathways activated by this TF may be associated with tumor progression and poor prognoses. LUAD typing based on pentose phosphate metabolic pathway-related lncRNAs was confirmed. Differences in characteristics between C1 and C2 subtypes improved the current LUAD detection and treatment.</p

Panel data cointegration test.

Panel data cointegration test.</p

Determining the Subnanometer Thickness of the Water-Depletion Layer at the Interface between Water and the Hydrophobic Substrate

Surface plasmon resonance (SPR) is one of the most popular and powerful techniques for label-free detecting and quantitatively analyzing the interfacial refractive index (RI). So far, most of the SPR measurements are mainly applied to detect the relative change of RI upon biological and chemical events occurring at the interface, while the determinations on the absolute value of RI remains challenging. However, the absolute value of RI has become increasingly urgent in some cases, such as the existence and physical properties of the water depletion layer (WDL). WDL refers to a subnanometer-thick layer with reduced density between water and the hydrophobic substrate. The detailed explanations of how water meets hydrophobic surface have been studied by several kinds of techniques for decades but it remains under debate. In this work, we successfully established a method to measure the absolute RI at a gold–liquid interface by surface plasmon resonance microscopy (SPRM) and 2D Fourier transformation image processing and further applied this method to study the existence and physical nature of WDL. It was found that a 0.6 nm thick WDL existed at the interface of water and the hydrophobic substrate, leading to a reduced refractive index of 1.3295 ± 0.0006 compared with the standard value of 1.3325. Our results further indicated that the WDL consisted of a uniform layer rather than numerous isolated surface nanobubbles that distributed at the interface with high density

Results of the threshold effect test.

Results of the threshold effect test.</p

Threshold estimates and confidence intervals.

Threshold estimates and confidence intervals.</p

<i>Ulrikezza aspoeckae</i> gen. et sp. nov

<p>Line drawing of complete venation for left forewing (A) and left hindwing (B). Scale bar = 10 mm.</p