Digital research data: from analysis of existing standards to a scientific foundation for a modular metadata schema in nanosafety

Background Assessing the safety of engineered nanomaterials (ENMs) is an interdisciplinary and complex process producing huge amounts of information and data. To make such data and metadata reusable for researchers, manufacturers, and regulatory authorities, there is an urgent need to record and provide this information in a structured, harmonized, and digitized way. Results This study aimed to identify appropriate description standards and quality criteria for the special use in nanosafety. There are many existing standards and guidelines designed for collecting data and metadata, ranging from regulatory guidelines to specific databases. Most of them are incomplete or not specifically designed for ENM research. However, by merging the content of several existing standards and guidelines, a basic catalogue of descriptive information and quality criteria was generated. In an iterative process, our interdisciplinary team identified deficits and added missing information into a comprehensive schema. Subsequently, this overview was externally evaluated by a panel of experts during a workshop. This whole process resulted in a minimum information table (MIT), specifying necessary minimum information to be provided along with experimental results on effects of ENMs in the biological context in a flexible and modular manner. The MIT is divided into six modules: general information, material information, biological model information, exposure information, endpoint read out information and analysis and statistics. These modules are further partitioned into module subdivisions serving to include more detailed information. A comparison with existing ontologies, which also aim to electronically collect data and metadata on nanosafety studies, showed that the newly developed MIT exhibits a higher level of detail compared to those existing schemas, making it more usable to prevent gaps in the communication of information. Conclusion Implementing the requirements of the MIT into e.g., electronic lab notebooks (ELNs) would make the collection of all necessary data and metadata a daily routine and thereby would improve the reproducibility and reusability of experiments. Furthermore, this approach is particularly beneficial regarding the rapidly expanding developments and applications of novel non-animal alternative testing methods.

Mechanisms of Silver Nanoparticle Uptake by Embryonic Zebrafish Cells

Evaluation of the uptake pathways in cells during exposure to nanoparticles (NPs) is key for risk assessment and the development of safer nanomaterials, as the internalisation and fate of NPs is linked to their toxicity and mode of action. Here, we determined the uptake mechanisms activated during the internalisation of 10, 30, and 100 nm AgNPs by embryonic zebrafish cells (ZF4). The uptake results demonstrated an NP size- and time-dependent uptake, showing the highest total silver uptake for the smallest AgNP (10 nm) at the lowest exposure concentration (2.5 μg/mL) after 2 h, while after 24 h, the highest exposure concentration (10 μg/mL) of the 10 nm AgNPs revealed the highest cellular load at 8 pg/cell. Inhibition of the caveolae, clathrin, and macropinocytosis endocytic pathways by pharmaceutical inhibitors (genistein, chlorpromazine, and wortmannin respectively) revealed that uptake was mainly via macropinocytosis for the 10 nm AgNPs and via the caveolae-mediated pathway for the 30 and 100 nm AgNPs. The induction of autophagy was also strongly related to the NP size, showing the highest percentage of induction for the 10 nm (around 3%) compared to naive cells, suggesting that autophagy can be activated along with endocytosis to deal with exposure to NPs. TEM imaging revealed the distribution of NPs across the cytoplasm inside intracellular vesicles. An increase in Early Endosome formation (EE) was observed for the 30 and 100 nm sizes, whereas the 10 nm AgNPs disrupted the activity of EE. The data supports the establishment of adverse outcome pathways by increasing knowledge on the link between a molecular initiating event such as receptor-mediated endocytosis and an adverse outcome, as well as supporting the reduction of animal testing by using alternative testing models, such as fish cell lines.

Detection of Salmonella typhimurium ATCC 14028 in Powder Prepared Traditional Medicines Using Real-Time PCR

The detection of Salmonella typhimurium ATCC 14028 using real-time PCR on powdered traditional medicinal products was carried out in the microbiology and molecular biology testing laboratory of the Food and Drug Administration in Gorontalo. This research aims to provide a reference for alternative testing methods in testing the products of traditional powder preparations on the market. The sample consisted of 10 traditional powder preparations spiked with positive control of S. typhimurium ATCC 14028 phase 2. The method used in the study was real-time PCR analysis using the SYBR® Green method, while DNA isolation using the direct PCR method. Data analysis was performed by analyzing the sample's melting temperature (Tm) curve and comparing it with positive control. The results showed that S. typhimurium ATCC 14028 was detected in samples at an average Tm value of 84.18°C, with ranges of 84.0-84.5°C. For positive control, the Tm value was at 85.2°C, while for the negative control, the Tm value was not detected. Based on these data, it can be concluded that S. typhimurium ATCC 14028 in traditional medicine products powder preparations can be detected using real-time PCR.

Penerapan Convolutional Neural Network pada Citra Rontgen Paru-Paru untuk Deteksi SARS-CoV-2

COVID-19 was officially declared as a pandemic by the WHO on March 11, 2020. For COVID-19, the testing methods commonly used are the Antibody Testing and RT-PCR Testing. Both methods are considered to be the most effective in determining whether a person has been suffered from COVID-19 or not. However, alternative testing methods need to be tried. One of them is using the Convolutional Neural Network. This study aims to measure the performance of CNN in classifying x-ray image of a person’s chest to determine whether the person is suffered from COVID-19 or not. The CNN model that was built consists of 1 convolutional 2D layer, 2 activation layers, 1 maxpooling layer, 1 dropout layer, 1 flatten layer, and 1 dense layer. Meanwhile, the chest x-ray image dataset used is the COVID-19 Radiography Database. This dataset consists of 3 classes, i.e. COVID-19 class, NORMAL class, and VIRAL_PNEUMONIA. The experiments consisted of 4 scenarios and were carried out using Google Colab. Based on the experiments, the CNN model can achieve an accuracy of 98.69%, a sensitivity of 97.71%, and a specificity of 98.90%. Thus, CNN has a very good performance to classify the disease based on a person’s chest x-ray.

The trade-off between impartiality and freedom in the 21st Century Cures Act

Randomized controlled trials test new drugs using various debiasing devices to prevent participantsfrom manipulating the trials. But participants often dislike controls, arguing that they impose apaternalist constraint on their legitimate preferences. The 21st Century Cures Act, passed by USCongress in 2016, encourages the Food and Drug Administration to use alternative testing methods,incorporating participants’ preferences, for regulatory purposes. We discuss, from a historicalperspective, the trade-off between trial impartiality and participants’ freedom. We argue that the onlyway out is considering which methods improve upon the performance of conventional trials inkeeping dangerous or inefficacious compounds out of pharmaceutical markets.

SARS-CoV-2 detection by a clinical diagnostic RT-LAMP assay

The ongoing pandemic of SARS-CoV-2 calls for rapid and cost-effective methods to accurately identify infected individuals. The vast majority of patient samples is assessed for viral RNA presence by RT-qPCR. Our biomedical research institute, in collaboration between partner hospitals and an accredited clinical diagnostic laboratory, established a diagnostic testing pipeline that has reported on more than 252,000 RT-qPCR results since its commencement at the beginning of April 2020. However, due to ongoing demand and competition for critical resources, alternative testing strategies were sought. In this work, we present a clinically-validated procedure for high-throughput SARS-CoV-2 detection by RT-LAMP that is robust, reliable, repeatable, specific, and inexpensive.

Physiologically based kinetic modelling based prediction of in vivo rat and human acetylcholinesterase (AChE) inhibition upon exposure to diazinon

The present study predicts in vivo human and rat red blood cell (RBC) acetylcholinesterase (AChE) inhibition upon diazinon (DZN) exposure using physiological based kinetic (PBK) modelling-facilitated reverse dosimetry. Due to the fact that both DZN and its oxon metabolite diazoxon (DZO) can inhibit AChE, a toxic equivalency factor (TEF) was included in the PBK model to combine the effect of DZN and DZO when predicting in vivo AChE inhibition. The PBK models were defined based on kinetic constants derived from in vitro incubations with liver fractions or plasma of rat and human, and were used to translate in vitro concentration–response curves for AChE inhibition obtained in the current study to predicted in vivo dose–response curves. The predicted dose–response curves for rat matched available in vivo data on AChE inhibition, and the benchmark dose lower confidence limits for 10% inhibition (BMDL10 values) were in line with the reported BMDL10 values. Humans were predicted to be 6-fold more sensitive than rats in terms of AChE inhibition, mainly because of inter-species differences in toxicokinetics. It is concluded that the TEF-coded DZN PBK model combined with quantitative in vitro to in vivo extrapolation (QIVIVE) provides an adequate approach to predict RBC AChE inhibition upon acute oral DZN exposure, and can provide an alternative testing strategy for derivation of a point of departure (POD) in risk assessment.

Monobloc Facial Advancement in the World of COVID-19 Testing: A New Potential Risk for Iatrogenic Injury

Background: Monobloc advancement with distraction is a holistic approach to treat the sequelae of syndromic craniosynostosis. These osteotomies create a communication between the nasal cavity and anterior cranial fossa that must be surgically obliterated to limit the infectious risks. In light of mandatory COVID-19 testing protocols amidst the pandemic, we aim to identify the specific challenges in management and present our strategy to overcome them. Case presentation: We report 2 cases of syndromic craniosynostosis treated with monobloc distraction during the COVID-19 pandemic and highlight safety concerns and our approach to managing these patients by avoiding nasopharyngeal swabs that may potentially penetrate the cranial base and place the patient as risk for iatrogenic injury. Discussion/conclusion: In patients undergoing surgical procedures that create a cranial base defect, caution must be exercised when attempting to test for COVID-19 which may be a source of potential iatrogenic injury. We propose a new algorithm for COVID-19 screening/surveillance following frontofacial advancement. Patients must be screened via alternative testing methods or treated as potential asymptomatic carriers of COVID-19 until postoperative imaging demonstrates complete ossification of the cranial base.

SARS-CoV-2 detection by a clinical diagnostic RT-LAMP assay

The ongoing pandemic of SARS-CoV-2 calls for rapid and cost-effective methods to accurately identify infected individuals. The vast majority of patient samples is assessed for viral RNA presence by RT-qPCR. Our biomedical research institute, in collaboration between partner hospitals and an accredited clinical diagnostic laboratory, established a diagnostic testing pipeline that has reported on more than 252,000 RT-qPCR results since its commencement at the beginning of April 2020. However, due to ongoing demand and competition for critical resources, alternative testing strategies were sought. In this work, we present a clinically-validated procedure for high-throughput SARS-CoV-2 detection by RT-LAMP in 25 minutes that is robust, reliable, repeatable, sensitive, specific, and inexpensive.