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Deep Learning–Based Identification of Tissue of Origin for Carcinomas of Unknown Primary Using MicroRNA Expression: Algorithm Development and Validation

Deep Learning–Based Identification of Tissue of Origin for Carcinomas of Unknown Primary Using MicroRNA Expression: Algorithm Development and Validation

We restricted the tissue type to be one of the primary tumors, solid tissue normal, or metastatic. We further restricted the data to micro RNA transcriptome profiling and picked data corresponding to 18 types of cancer each containing a sufficient number of samples, obtaining 9648 files (Figure 2 and Table S1 in Multimedia Appendix 1). To obtain the SRA data, we used the micro RNA tissue expression database portal and restricted the cancer types to 6 types of cancer, seen in further detail in Figure 2.

Ananya Raghu, Anisha Raghu, Jillian F Wise

JMIR Bioinform Biotech 2024;5:e56538

Peer Review of “Dental Tissue Density in Healthy Children Based on Radiological Data: Retrospective Analysis”

Peer Review of “Dental Tissue Density in Healthy Children Based on Radiological Data: Retrospective Analysis”

This is the peer-review report for “Dental Tissue Density in Healthy Children Based on Radiological Data: Retrospective Analysis.” This paper [1] has a very good topic selected by the authors. Based on the study of Hounsfield units in cone-beam computed tomography (CBCT), we can evaluate conditions that are abnormal in patients. There is not much to comment on, but try to include good pictures of the CBCT. 1. The authors did not mention the ideal values of the Hounsfield units for enamel and dentin. 2.

Shanmukha Gorthy

JMIRx Med 2024;5:e60329

Peer Review of “Dental Tissue Density in Healthy Children Based on Radiological Data: Retrospective Analysis”

Peer Review of “Dental Tissue Density in Healthy Children Based on Radiological Data: Retrospective Analysis”

This is the peer-review report for ”Dental Tissue Density in Healthy Children Based on Radiological Data: Retrospective Analysis.” The subject is interesting. The densities of dental hard tissues were determined by cone-beam computed tomography (CBCT), a technique that has been recently used for this purpose. 1. The article [1] specifies the aim and is structured according to the journal’s recommendations. 2.

Anonymous

JMIRx Med 2024;5:e62676

Dental Tissue Density in Healthy Children Based on Radiological Data: Retrospective Analysis

Dental Tissue Density in Healthy Children Based on Radiological Data: Retrospective Analysis

Dynamic monitoring of dental tissue condition is required in trauma, after transplantation, and during therapeutic and preventive procedures [3-5]. It is especially important in children with metabolic diseases, genetic abnormalities, and special needs [6-8]. The emergence of innovative diagnostic methods provides dentists with new opportunities to assess dental health, especially in the early stages of pathological changes that are not visible to the eye.

Aleksey Reshetnikov, Natalia Shaikhattarova, Margarita Mazurok, Nadezhda Kasatkina

JMIRx Med 2024;5:e56759

Periorbital Necrotizing Fasciitis: Case Presentation

Periorbital Necrotizing Fasciitis: Case Presentation

Necrotizing fasciitis (NF) or necrotizing soft tissue infection is a rare and severe infection of the skin, muscle, subcutaneous tissue, and underlying fascia. In the United States, approximately 0.4 in every 100,000 people per year are affected by NF, while it is as common as 1 in every 100,000 people in other countries [1].

Ryan S Huang, Nikhil S Patil, Yasser Khan

Interact J Med Res 2023;12:e52507

Effects of Alternative Offers of Screening Sigmoidoscopy and Colonoscopy on Utilization and Yield of Endoscopic Screening for Colorectal Neoplasms: Protocol of the DARIO Randomized Trial

Effects of Alternative Offers of Screening Sigmoidoscopy and Colonoscopy on Utilization and Yield of Endoscopic Screening for Colorectal Neoplasms: Protocol of the DARIO Randomized Trial

Tissue samples are obtained from the neoplasms removed during endoscopy and will be banked for diagnostics and research purposes at the NCT tissue bank. Part III of the study builds up a liquid biobank from biosamples (blood, urine, stool, saliva) of study part II participants, with samples taken prior to endoscopy.

Petra Schrotz-King, Michael Hoffmeister, Peter Sauer, Anja Schaible, Hermann Brenner

JMIR Res Protoc 2020;9(8):e17516