Simultaneous detection of SARS-CoV-2 RNA and host antibodies enabled by a multiplexed electrochemical sensor platform

There continues to be a great need for rapid, accurate, and cost-effective point-of-care devices that can diagnose the presence of SARS-CoV-2 virus and development of IgG and IgM antibody responses in early and late stages of COVID-19 disease. Here, we describe a versatile multiplexed electrochemical (EC) sensor platform modified with an antifouling nanocomposite coating that enables single-molecule CRISPR/Cas-based molecular detection of SARS-CoV-2 viral RNA with on-chip signal validation as well as multiplexed serological detection of antibodies against three SARS-CoV-2 viral antigens. The CRISPR-based EC platform achieved 100% accuracy for detection of viral RNA and showed an excellent correlation with RT-qPCR using 30 clinical saliva samples. The serology EC platform obtained 100% sensitivity and 100% specificity for anti-SARS-CoV-2 IgG, as well as 94% specificity and 82% sensitivity for anti-SARS-CoV-2 IgM with 112 clinical plasma samples. These data demonstrate that integration of CRISPR-based RNA detection and serological assays with antifouling nanocomposite-based EC sensors enables performance as good or better than traditional laboratory-based techniques.

SAEFVIC: Surveillance of adverse events following immunisation (AEFI) in Victoria, Australia, 2018

Background SAEFVIC is the Victorian surveillance system for adverse events following immunisation (AEFI). It enhances passive surveillance by also providing clinical support and education to vaccinees and immunisation providers. This report summarises surveillance, clinical and vaccine pharmacovigilance activities of SAEFVIC in 2018. Methods A retrospective observational cohort study of AEFI reports received by SAEFVIC in 2018, compared with previous years since 2008. Data were categorised by vaccinee demographics of age, sex, pregnancy and Indigenous status, vaccines administered and AEFI reactions reported. Age cohorts were defined as infant (0–12 months); young child (1–4 years); school-aged (5–17 years); adult (18–64 years); and older person (65+ years). Proportional reporting ratios were calculated for signal investigation of serious adverse neurological events with all vaccines and with influenza vaccines. Clinical support services and educational activities are described. Results SAEFVIC received 1730 AEFI reports (26.8 per 100,000 population), with 9.3% considered serious. Nineteen percent (n = 329) attended clinical review. Annual AEFI reporting trends increased for infants, children and older persons, but were stable for school-aged and adult cohorts. Females comprised 55% of all reports and over 80% of reports among adults. There were 17 reports of AEFI in pregnant women and 12 (0.7%) in persons identifying as Indigenous Australians. A possible signal regarding serious adverse neurological events (SANE) was detected, but was not supported by signal validation testing. A clinical investigation is ongoing. Two deaths were reported coincident to immunisation with no evidence of causal association. Conclusion SAEFVIC continues to provide robust AEFI surveillance supporting vaccine safety monitoring in Victoria and Australia, with new signal detection and validation methodologies strengthening capabilities.

pyPhotometry: Open source Python based hardware and software for fiber photometry data acquisition

Fiber photometry is the process of recording bulk neural activity by measuring fluorescence changes in activity sensitive indicators (e.g. GCaMP) through an optical fiber. We present a system of open source hardware and software for fiber photometry data acquisition consisting of a compact, low cost, data acquisition board built around the Micropython microcontroller, and a cross platform graphical user interface (GUI) for controlling acquisition and visualising signals. The system can acquire two analog and two digital signals, and control two external LEDs via built in LED drivers. Time-division multiplexed illumination allows independent readout of fluorescence evoked by different excitation wavelengths from a single photoreceiver signal. Validation experiments indicate this approach offers better signal to noise for a given average excitation light intensity than sinusoidally-modulated illumination. pyPhotometry is substantially cheaper than commercial hardware filling the same role, and we anticipate, as an open source and comparatively simple tool, it will be easily adaptable and therefore of broad interest to a wide range of users.

Performance Investigation of Millimeter Wave Generation Reliant on Stimulated Brillouin Scattering

In this work, photonic method of generating the millimeter waves has been done based on Brillouin scattering effect in optical fiber. Here different approaches are proposed to get maximum frequency shift in mm-wave region using only pumps, radio signals with Mach-Zehnder modulator. Moreover for generated signal validation, signals modulated and send to both wired and wireless medium in optical domain. It is observed that maximum shift of 300 GHz is realized using 60 GHz input sine wave. Basically a frequency doubler is proposed which double shift of input frequency and provide better SNR. For the future generation network system, the generation of millimeter waves makes them well reliable for the transmission of the data.

Validation of In-Core Measurements

Paper describes original methods of signal validation, specially developed for in-core measurements, namely for Self Powered Neutron Flux Detectors (SPND) and for core exit coolant temperature measurements (thermocouples measurements). Some interesting examples of NPP Temelin data validation (SPND) and NPP Dukovany (thermocouple measurements) are presented; precision and sensitivity of methods used are discussed.