Exploration of Drug Science

Open Access

Systematic Review

Utilizing the Ethereum blockchain for retrieving and archiving augmented reality surgical navigation data

Aim: Conventional techniques to share and archive spinal imaging data raise issues with trust and security, with novel approaches being more greatly considered. Ethereum smart contracts present o [...] Read more.

Aim:

Conventional techniques to share and archive spinal imaging data raise issues with trust and security, with novel approaches being more greatly considered. Ethereum smart contracts present one such novel approach. Ethereum is an open-source platform that allows for the use of smart contracts. Smart contracts are packages of code that are self-executing and reside in the Ethereum state, defining conditions for programmed transactions. Though powerful, limited attempts have been made to showcase the clinical utility of such technologies, especially in the pre- and post-operative imaging arenas. Herein, we therefore aim to propose a proof-of-concept smart contract that stores intraoperative three-dimensional (3D) augmented reality surgical navigation (ARSN) data and was tested on a private, proof-of-authority network. To the author’s best knowledge, the present study represents a first-use case of the InterPlanetary File Storage protocol for storing and retrieving spine imaging smart contracts.

Methods:

The content identifier hashes were stored inside the smart contracts while the interplanetary file system (IPFS) was used to efficiently store the image files. Insertion was achieved with four storage mappings, one for each of the following: fictitious patient data, specific diagnosis, patient identity document (ID), and Gertzbein grade. Inserted patient observations were then queried with wildcards. Insertion and retrieval times for different record volumes were collected.

Results:

It took 276 milliseconds to insert 50 records and 713 milliseconds to insert 350 records. Inserting 50 records required 934 Megabyte (MB) of memory per insertion with patient data and imaging, while inserting 350 records required almost the same amount of memory per insertion. In a database of 350 records, the retrieval function needs about 1,026 MB to query a record with all three fields left blank, but only 970 MB to obtain the same observation from a database of 50 records.

Conclusions:

The concept presented in this study exemplifies the clinical utility of smart contracts and off-chain data storage for efficient retrieval/insertion of ARSN data.

Sai Batchu ... Brandon Lucke-Wold

Published: February 28, 2023 Explor Drug Sci. 2023;1:55–63
DOI: https://doi.org/10.37349/eds.2023.00005

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Times Cited: 4

Aim:

Conventional techniques to share and archive spinal imaging data raise issues with trust and security, with novel approaches being more greatly considered. Ethereum smart contracts present one such novel approach. Ethereum is an open-source platform that allows for the use of smart contracts. Smart contracts are packages of code that are self-executing and reside in the Ethereum state, defining conditions for programmed transactions. Though powerful, limited attempts have been made to showcase the clinical utility of such technologies, especially in the pre- and post-operative imaging arenas. Herein, we therefore aim to propose a proof-of-concept smart contract that stores intraoperative three-dimensional (3D) augmented reality surgical navigation (ARSN) data and was tested on a private, proof-of-authority network. To the author’s best knowledge, the present study represents a first-use case of the InterPlanetary File Storage protocol for storing and retrieving spine imaging smart contracts.

Methods:

The content identifier hashes were stored inside the smart contracts while the interplanetary file system (IPFS) was used to efficiently store the image files. Insertion was achieved with four storage mappings, one for each of the following: fictitious patient data, specific diagnosis, patient identity document (ID), and Gertzbein grade. Inserted patient observations were then queried with wildcards. Insertion and retrieval times for different record volumes were collected.

Results:

It took 276 milliseconds to insert 50 records and 713 milliseconds to insert 350 records. Inserting 50 records required 934 Megabyte (MB) of memory per insertion with patient data and imaging, while inserting 350 records required almost the same amount of memory per insertion. In a database of 350 records, the retrieval function needs about 1,026 MB to query a record with all three fields left blank, but only 970 MB to obtain the same observation from a database of 50 records.

Conclusions:

The concept presented in this study exemplifies the clinical utility of smart contracts and off-chain data storage for efficient retrieval/insertion of ARSN data.

Open Access

Review

Essential functions, syntheses and detection of sialyl Lewis X on glycoproteins

It is widely acknowledged that sialyl Lewis X (sLeX), the composition and linkage of which are N-acetylneuraminic acid (Neu5Ac) α2-3 galactose (Gal) β1-4 [fucose (Fuc) α1-3] N-acetylglucosamine, is usually attached to the cell [...] Read more.

Qiushi Chen ... Xuechen Li

Published: February 28, 2023 Explor Drug Sci. 2023;1:31–54
DOI: https://doi.org/10.37349/eds.2023.00004
This article belongs to the special issue Bioactive Peptides discovery and development

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Times Cited: 2

Open Access

Original Article

Surface functionalized mesoporous polydopamine nanocomposites for killing tumor cells through collaborative chemo/photothermal/chemodynamic treatment

Aim: The development of a collaborative strategy with improved efficacy holds great promise in tumor treatment. This study aims to develop an effective collaborative strategy based on functionalized mesoporous polydopamine (MPDA) [...] Read more.

Yi Ouyang ... Hui Liu

Published: February 27, 2023 Explor Drug Sci. 2023;1:18–30
DOI: https://doi.org/10.37349/eds.2023.00003
This article belongs to the special issue Emerging Nanomedicine Technologies for Enhanced Cancer Theranostics

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Times Cited: 0

Open Access

Original Article

Convenient estimation of oxytetracycline and polymyxin B by a novel high-performance liquid chromatography method: development and validation

Aim: The aim of this research work was to develop a validated reversed-phase (RP)-high-performance liquid chromatography (HPLC) method for simultaneous estimation of oxytetracycline (OXY) and pol [...] Read more.