Blockchain-enabled immutable, distributed, and highly available clinical research activity logging system for federated COVID-19 data analysis from multiple institutions.

OBJECTIVE: We aimed to develop a distributed, immutable, and highly available cross-cloud blockchain system to facilitate federated data analysis activities among multiple institutions. MATERIALS AND METHODS: We preprocessed 9166 COVID-19 Structured Query Language (SQL) code, summary statistics, and user activity logs, from the GitHub repository of the Reliable Response Data Discovery for COVID-19 (R2D2) Consortium. The repository collected local summary statistics from participating institutions and aggregated the global result to a COVID-19-related clinical query, previously posted by clinicians on a website. We developed both on-chain and off-chain components to store/query these activity logs and their associated queries/results on a blockchain for immutability, transparency, and high availability of research communication. We measured run-time efficiency of contract deployment, network transactions, and confirmed the accuracy of recorded logs compared to a centralized baseline solution. RESULTS: The smart contract deployment took 4.5 s on an average. The time to record an activity log on blockchain was slightly over 2 s, versus 5-9 s for baseline. For querying, each query took on an average less than 0.4 s on blockchain, versus around 2.1 s for baseline. DISCUSSION: The low deployment, recording, and querying times confirm the feasibility of our cross-cloud, blockchain-based federated data analysis system. We have yet to evaluate the system on a larger network with multiple nodes per cloud, to consider how to accommodate a surge in activities, and to investigate methods to lower querying time as the blockchain grows. CONCLUSION: Blockchain technology can be used to support federated data analysis among multiple institutions.

SARS-CoV-2 spike protein detection using slightly tapered no-core fiber-based optical transducer.

The label-free detection of SARS-CoV-2 spike protein is demonstrated by using slightly tapered no-core fiber (ST-NCF) functionalized with ACE2. In the fabricated sensor head, abrupt changes in the mode-field diameter at the interfaces between single-mode fiber and no-core fiber excite multi-guided modes and facilitate multi-mode interference (MMI). Its slightly tapered region causes the MMI to be more sensitive to the refractive index (RI) modulation of the surrounding medium. The transmission minimum of the MMI spectrum was selected as a sensor indicator. The sensor surface was functionalized with ACE2 bioreceptors through the pretreatment process. The ACE2-immobilized ST-NCF sensor head was exposed to the samples of SARS-CoV-2 spike protein with concentrations ranging from 1 to 104 ng/mL. With increasing sample concentration, we observed that the indicator dip moved towards a longer wavelength region. The observed spectral shifts are attributed to localized RI modulations at the sensor surface, which are induced by selective bioaffinity binding between ACE2 and SARS-CoV-2 spike protein. Also, we confirmed the capability of the sensor head as an effective and simple optical probe for detecting antigen protein samples by applying saliva solution used as a measurement buffer. Moreover, we compared its detection sensitivity to SARS-CoV-2 and MERS-CoV spike protein to examine its cross-reactivity. In particular, we proved the reproducibility of the bioassay protocol adopted here by employing the ST-NCF sensor head reconstructed with ACE2. Our ST-NCF transducer is expected to be beneficially utilized as a low-cost and portable biosensing platform for the rapid detection of SARS-CoV-2 spike protein.

Organoid Studies in COVID-19 Research.

The current COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has completely changed human life for more than two years. Upon the emergence of this new lethal virus, multiple approaches were utilized to gain basic knowledge about its biology. Moreover, modern technologies, such as the organoid model system and next-generation sequencing, enabled us to rapidly establish strategies to tackle the disease, including vaccines and therapeutics. The recently developed organoid technology reflects human physiology more closely than other model systems. Coupled with its rapidness, high efficiency, and outstanding reliability, it has provided an opportunity to develop new drugs and understand the impact of the viral pathogen on the host. Recent findings using organoids have successfully revealed the cellular tropism of the virus in different organs and identified potential drug candidates that impact the disease. This review will summarize current achievements made with organoids in the fight against COVID-19.

Fiber-optic label-free biosensor for SARS-CoV-2 spike protein detection using biofunctionalized long-period fiber grating.

With COVID-19 widespread worldwide, people are still struggling to develop faster and more accurate diagnostic methods. Here we demonstrated the label-free detection of SARS-CoV-2 spike protein by employing a SARS-CoV-2 spike antibody-conjugated phase-shifted long-period fiber grating (PS-LPFG) inscribed with a CO2 laser. At a specific cladding mode, the wavelength separation (λD) between the two split dips of a PS-LPFG varies with the external refractive index, although it is virtually insensitive to ambient temperature variations. To detect SARS-CoV-2 spike protein, SARS-CoV-2 spike antibodies were immobilized on the fiber surface of the fabricated PS-LPFG functionalized through chemical modification. When exposed to SARS-CoV-2 spike protein with different concentrations, the antibody-immobilized PS-LPFG exhibited the variation of λD according to the protein concentration, which was caused by bioaffinity binding-induced local changes in the refractive index at its surface. In particular, we also confirmed the potential of our sensor for clinical application by detecting SARS-CoV-2 spike protein in virus transport medium. Moreover, our sensor could distinguish SARS-CoV-2 spike protein from those of MERS-CoV and offer efficient properties such as reusability and storage stability. Hence, we have successfully fabricated a promising optical transducer for the detection of SARS-CoV-2 spike protein, which can be unperturbed by external temperature disturbances.

Privacy-protecting, reliable response data discovery using COVID-19 patient observations.

OBJECTIVE: To utilize, in an individual and institutional privacy-preserving manner, electronic health record (EHR) data from 202 hospitals by analyzing answers to COVID-19-related questions and posting these answers online. MATERIALS AND METHODS: We developed a distributed, federated network of 12 health systems that harmonized their EHRs and submitted aggregate answers to consortia questions posted at https://www.covid19questions.org. Our consortium developed processes and implemented distributed algorithms to produce answers to a variety of questions. We were able to generate counts, descriptive statistics, and build a multivariate, iterative regression model without centralizing individual-level data. RESULTS: Our public website contains answers to various clinical questions, a web form for users to ask questions in natural language, and a list of items that are currently pending responses. The results show, for example, that patients who were taking angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers, within the year before admission, had lower unadjusted in-hospital mortality rates. We also showed that, when adjusted for, age, sex, and ethnicity were not significantly associated with mortality. We demonstrated that it is possible to answer questions about COVID-19 using EHR data from systems that have different policies and must follow various regulations, without moving data out of their health systems. DISCUSSION AND CONCLUSIONS: We present an alternative or a complement to centralized COVID-19 registries of EHR data. We can use multivariate distributed logistic regression on observations recorded in the process of care to generate results without transferring individual-level data outside the health systems.

Privacy-Protecting, Reliable Response Data Discovery Using COVID-19 Patient Observations.

There is an urgent need to answer questions related to COVID-19's clinical course and associations with underlying conditions and health outcomes. Multi-center data are necessary to generate reliable answers, but centralizing data in a single repository is not always possible. Using a privacy-protecting strategy, we launched a public Questions & Answers web portal (https://covid19questions.org) with analyses of comorbidities, medications and laboratory tests using data from 202 hospitals (59,074 COVID-19 patients) in the USA and Germany. We find, for example, that 8.6% of hospitalizations in which the patient was not admitted to the ICU resulted in the patient returning to the hospital within seven days from discharge and that, when adjusted for age, mortality for hospitalized patients was not significantly different by gender or ethnicity.