Supplementary data for "Pathological role of Th17 cells in Graves' disease."

Supplementary data for "Pathological role of Th17 cells in Graves' disease.

Supplementary Tables S1-S2, Supplementary Figures S1-S5 from PDCD4 Is an Androgen-Repressed Tumor Suppressor that Regulates Prostate Cancer Growth and Castration Resistance

Supplementary Table S1: siRNA and shRNA Vectors Supplementary Table S2: The sequence of primers used in this study Supplementary Figure S1. miR-21 suppresses PDCD4 expression in normal prostate epithelial cells. Supplementary Figure S2. Androgen signaling and miR-21 suppresses PDCD4 mRNA expression. Supplementary Figure S3. Transient PDCD4 over-expression and PDCD4 knockdown. Supplementary Figure S4. Transient PDCD4-overexpression induces apoptosis of LAPC4, but not LNCaP, cells. Supplementary Figure S5. PDCD4 expression regulates cell proliferation and apoptosis.</p

Protocol of a Prospective Observational Study on the Relationship Between Glucose Fluctuation and Cardiovascular Events in Patients with Type 2 Diabetes

Provide enhanced digital features for this article If you are an author of this publication and would like to provide additional enhanced digital features for your article then please contact [email protected]. The journal offers a range of additional features designed to increase visibility and readership. All features will be thoroughly peer reviewed to ensure the content is of the highest scientific standard and all features are marked as ‘peer reviewed’ to ensure readers are aware that the content has been reviewed to the same level as the articles they are being presented alongside. Moreover, all sponsorship and disclosure information is included to provide complete transparency and adherence to good publication practices. This ensures that however the content is reached the reader has a full understanding of its origin. No fees are charged for hosting additional open access content. Other enhanced features include, but are not limited to: • Slide decks • Videos and animations • Audio abstracts • Audio slides</p

Yoshii et al supplementary data_Figshare.docx

Supplementary data for the manuscript "The importance of continuous glucose monitoring-derived metrics beyond HbA1c for optimal individualized glycemic control"</p

Dataset for Fig 4.

A number of restricted diffusion (RD) imaging techniques, such as diffusion kurtosis (DK) imaging and Q space imaging, have been developed and proven to be useful for the diagnosis of diseases, including cerebral gliomas and cerebrovascular infarction. In particular, apparent diffusion coefficient (ADC) subtraction method (ASM) imaging has become available recently as a novel RD imaging technique. ASM is based on the difference between the ADC values in an image pair of two ADC maps, ADC basic (ADCb) and ADC modify (ADCm), which are created from diffusion-weighted images taken using short and long effective diffusion times, respectively. The present study aimed to assess the potential of different types of ASM imaging by comparing them with DK imaging which is the gold-standard RD imaging technique. In the present basic study using both polyethylene glycol phantom and cell-containing bio-phantom, three different types of ASM images were created using different calculation processes. ASM/A is an image calculated by dividing the absolute difference between ADCb and ADCm by ADCb several times. By contrast, ASM/S is an image created by dividing the absolute difference between ADCb and ADCm by the standard deviation of ADCb several times. As for positive ASM/A image (PASM/A), the positive image, which was resultant after subtracting ADCb from ADCm, was divided by ADCb several times. A comparison was made between the types of ASM and DK images. The results showed the same tendency between ASM/A in addition to both ASM/S and PASM/A. By increasing the number of divisions by ADCb from three to five times, ASM/A images transformed from DK-mimicking to more RD-sensitive images compared with DK images. These observations suggest that ASM/A images may prove useful for future clinical applications in RD imaging protocols for the diagnosis of diseases.</div

Relationship between ADC values and their SD.

(A) SD image of the ADCb values of different phantoms. High-cellularity bio-phantom, physiological saline phantom and 120 mM polyethylene glycol phantom were indicated from left to right. (B) Scatter graph indicating the correlation between the values of ADCb and SD of ADCb. The dotted line indicates a positive correlation as a result of linear regression. ADC, apparent diffusion coefficient; ADCb, ADC basic; SD, standard deviation.</p

Comparison of the relative values for various phantoms among the DK image and ASM images.

(A) ASM/A images. (B) ASM/S images. (C) ASM/A3, PASM/A3 and ASM/S3 images. Phantoms used were bio-phantoms of Jurkat cells and polyethylene glycol phantoms. Vertical bar represents relative values of DK image and ASM images, which were modified for their PS values to become 5,000. Error bar represents standard deviation for each value. +P‡Px, ASM division by ADC x times; ASM/Sx, ASM division by standard deviation x times; PASM/A3, positive ASM division by ADC three times.</p

ADC values of different phantoms.

(A) ADCb values of bio-phantoms of Jurkat cells. (B) ADCb values of polyethylene glycol phantoms. Error bar represents standard deviation for each value. **Pb, ADC basic.</p

Imaging characteristics of diffusion-weighted images for diffusion kurtosis imaging and apparent diffusion coefficient subtraction method.

Imaging characteristics of diffusion-weighted images for diffusion kurtosis imaging and apparent diffusion coefficient subtraction method.</p

Dataset for Fig 5.

A number of restricted diffusion (RD) imaging techniques, such as diffusion kurtosis (DK) imaging and Q space imaging, have been developed and proven to be useful for the diagnosis of diseases, including cerebral gliomas and cerebrovascular infarction. In particular, apparent diffusion coefficient (ADC) subtraction method (ASM) imaging has become available recently as a novel RD imaging technique. ASM is based on the difference between the ADC values in an image pair of two ADC maps, ADC basic (ADCb) and ADC modify (ADCm), which are created from diffusion-weighted images taken using short and long effective diffusion times, respectively. The present study aimed to assess the potential of different types of ASM imaging by comparing them with DK imaging which is the gold-standard RD imaging technique. In the present basic study using both polyethylene glycol phantom and cell-containing bio-phantom, three different types of ASM images were created using different calculation processes. ASM/A is an image calculated by dividing the absolute difference between ADCb and ADCm by ADCb several times. By contrast, ASM/S is an image created by dividing the absolute difference between ADCb and ADCm by the standard deviation of ADCb several times. As for positive ASM/A image (PASM/A), the positive image, which was resultant after subtracting ADCb from ADCm, was divided by ADCb several times. A comparison was made between the types of ASM and DK images. The results showed the same tendency between ASM/A in addition to both ASM/S and PASM/A. By increasing the number of divisions by ADCb from three to five times, ASM/A images transformed from DK-mimicking to more RD-sensitive images compared with DK images. These observations suggest that ASM/A images may prove useful for future clinical applications in RD imaging protocols for the diagnosis of diseases.</div