Description of our integrated mouse poly(A) site database.

<p>(A). Venn diagram shows the overlaps of three sources of our poly(A) site database including PolyA_DB2, polyA-seq, and 3′ ends of UCSC Known Genes. (B). Histogram shows the distribution of the number of poly(A) site per gene in comparison with UCSC annotation alone. The poly(A) sites based on UCSC Known Gene data alone are colored in grey and our integrated poly(A) database is colored in black. (C). Scheme for probeset customization of microarray probes for APA detection. The expression values of the probesets after quantification and normalization were used for differential APA expression analysis within each experiment.</p

Scheme of the workflow.

<p>We generated an integrated poly(A) database and analyzed differential expression of APAs and RBPs in publically available microarrays from GEO aiming to reveal RBP's functions in differential APA regulation. The results of our analysis were highlighted in blue color, which include APA differential expression detection and interpretation in the left panel, RBP-APA co-expression network in the middle panel, and RBP regulation models in APA by combining available CLIP data and microarray gene expression data in the right panel.</p

The genes with most frequent differential APA events.

<p>Number of experiments indicate the number of microarray experiments where the APA event shows differential expression. The biological conditions of the most relevant experiments were listed here.</p

The 10 selected RBPs showing the highest positive or negative associations with the global shift in APA.

<p>The median correlation coefficients between RBPs and gULIs across experiments are indicated within the parenthesises.</p

RBP and APA co-expression network.

<p>The arrow-headed edge pointing from an RBP indicates that the up-regulation of RBP is correlated with 3′ UTR lengthening of the target gene, while T-headed edge indicates that the up-regulation of RBP is correlated with 3′ UTR shortening. RBP gene is colored in blue and non-RBP gene in white. Gene with APA event is in the diamond shape and gene without APA event is in the round shape. Note that some RBP genes such as <i>Cpsf6</i> also contain APA events. The strength of correlation is indicated by thickness of the edges. <i>|r|</i>, absolute value of Pearson's correlation coefficient.</p

The list of biological conditions that most significantly perturb global APA usage.

<p>ΔgULI is the maximal shift of global UTR lengthening indices (gULIs).</p

Examples of global shifts in APA.

<p>Six experiments were selected from the top list to represent global ULI shifts under different biological conditions. UTR shortening was preferred in certain tissues (GSE9441, GSE17478) as well as in carcinoma (GSE9012), developments (GSE20954), differentiations (GSE21749), and hypoxia (GSE15894). Box-whiskers indicate global UTR lengthening indices (gULI) across biological replicates within each condition. Y-axis: global UTR lengthening index; X-axis: experimental conditions. The descriptions for the biological conditions are listed below each boxplot. Grey color outlines the conditions with lengthening of UTRs while white color for the conditions with shortening of UTRs.</p

Differential expression of APA for <i>Cpsf6</i> and <i>Eif4e2</i> in various biological conditions.

<p>(A). Boxplots show the differential expression of <i>Cpsf6</i> APA isoforms (a tandem UTR event) in different tissues and cell lines, as well as different development stages. (B). Boxplots show the differential expression of <i>Eif4e2</i> APA isoforms (an alternative UTR event) in different tissues, development and spermatogenesis. Gene models of the APA isoforms are indicated on top, with microarray probes targeted regions on the 3′ UTRs marked with colors. Blue color represents the common or proximal UTR probeset while red color represents extended or distal UTR probeset. Box-whiskers indicate the expression of probesets across biological replicates within each condition. Y-axis: log2-transformed expression values from microarrays; X-axis: experimental conditions. The descriptions for the biological conditions are listed below each boxplot. <i>cor</i>: Pearson correlation coefficient; <i>p</i>: two-way ANOVA p value.</p

Image_1_Application of FGD-BCEL loss function in segmenting temporal lobes on localized CT images for radiotherapy.pdf

ObjectivesThe aim of this study was to find a new loss function to automatically segment temporal lobes on localized CT images for radiotherapy with more accuracy and a solution to dealing with the classification of class-imbalanced samples in temporal lobe segmentation.MethodsLocalized CT images for radiotherapy of 70 patients with nasopharyngeal carcinoma were selected. Radiation oncologists sketched mask maps. The dataset was randomly divided into the training set (n = 49), the validation set (n = 7), and the test set (n = 14). The training set was expanded by rotation, flipping, zooming, and shearing, and the models were evaluated using Dice similarity coefficient (DSC), Jaccard similarity coefficient (JSC), positive predictive value (PPV), sensitivity (SE), and Hausdorff distance (HD). This study presented an improved loss function, focal generalized Dice-binary cross-entropy loss (FGD-BCEL), and compared it with four other loss functions, Dice loss (DL), generalized Dice loss (GDL), Tversky loss (TL), and focal Tversky loss (FTL), using the U-Net model framework.ResultsWith the U-Net model based on FGD-BCEL, the DSC, JSC, PPV, SE, and HD were 0.87 ± 0.11, 0.78 ± 0.11, 0.90 ± 0.10, 0.87 ± 0.13, and 4.11 ± 0.75, respectively. Except for the SE, all the other evaluation metric values of the temporal lobes segmented by the FGD-BCEL-based U-Net model were improved compared to the DL, GDL, TL, and FTL loss function-based U-Net models. Moreover, the FGD-BCEL-based U-Net model was morphologically more similar to the mask maps. The over- and under-segmentation was lessened, and it effectively segmented the tiny structures in the upper and lower poles of the temporal lobe with a limited number of samples.ConclusionsFor the segmentation of the temporal lobe on localized CT images for radiotherapy, the U-Net model based on the FGD-BCEL can meet the basic clinical requirements and effectively reduce the over- and under-segmentation compared with the U-Net models based on the other four loss functions. However, there still exists some over- and under-segmentation in the results, and further improvement is needed.</p

Phase and Composition Engineering of Self-Intercalated 2D Metallic Tantalum Sulfide for Second-Harmonic Generation

Self-intercalation in two-dimensional (2D) materials is significant, as it offers a versatile approach to modify material properties, enabling the creation of interesting functional materials, which is essential in advancing applications across various fields. Here, we define ic-2D materials as covalently bonded compounds that result from the self-intercalation of a metal into layered 2D compounds. However, precisely growing ic-2D materials with controllable phases and self-intercalation concentrations to fully exploit the applications in the ic-2D family remains a great challenge. Herein, we demonstrated the controlled synthesis of self-intercalated H-phase and T-phase Ta1+xS2 via a temperature-driven chemical vapor deposition (CVD) approach with a viable intercalation concentration spanning from 10% to 58%. Atomic-resolution scanning transmission electron microscopy-annular dark field imaging demonstrated that the self-intercalated Ta atoms occupy the octahedral vacancies located at the van der Waals gap. The nonperiodic Ta atoms break the centrosymmetry structure and Fermi surface properties of intrinsic TaS2. Therefore, ic-2D T-phase Ta1+xS2 consistently exhibit a spontaneous nonlinear optical (NLO) effect regardless of the sample thickness and self-intercalation concentrations. Our results propose an approach to activate the NLO response of centrosymmetric 2D materials, achieving the modulation of a wide range of optoelectronic properties via nonperiodic self-intercalation in the ic-2D family