Silver nanoparticles (SNPs) are widely used in the field of biomedicine, but a comprehensive understanding of how SNPs distribute in the body and the induced toxicity remains largely unknown. The present study was designed to investigate the distribution and accumulation of SNPs in rats with subcutaneous injection. Rats were injected with either SNPs or silver microparticles (SMPs) at 62.8 mg/kg, and then sacrificed at predetermined time points. The main organs of the experimental animals were harvested for ultrastructural analysis by transmission electron microscopy (TEM) and for silver content analysis by inductively coupled plasma mass spectrometry (ICP-MS). Results indicated that SNPs translocated to the blood circulation and distributed throughout the main organs, especially in the kidney, liver, spleen, brain and lung in the form of particles. SMPs, however, could not invade the blood stream, or organ tissues. Ultrastructural observations indicate that those SNPs that had accumulated in organs could enter different kinds of cells, such as renal tubular epithelial cells and hepatic cells. Moreover, SNPs also induced blood-brain barrier (BBB) destruction and astrocyte swelling, and caused neuronal degeneration. The results suggest more cautions needed in biomedical applications of SNPs, in particular, the long-term uses.

We have examined the reduction of cyanide by using the purified component proteins of nitrogenase (Av1 and Av2). The previously reported self-inhibition phenomenon was found to be an artifact. One of the two species present in cyanide solutions, CN-, was shown to be a potent reversible inhibitor (Ki = 27 microM) of total electron flow, apparently uncoupling MgATP hydrolysis and electron transfer. There appears to be no differential effect of CN- on the specific activities of Av1 and Av2 nor is there any apparent irreversible physical damage to Av2. CN- inhibition is completely reversed by low levels of CO, implying a common binding site. Azide partially relieves the inhibitory effect, but other substrates and inhibitors (N2, C2H2, N2O, H2) have no effect. The other species present in cyanide solutions, HCN, was shown to be the substrate (Km = 4.5 mM at Av2/Av1 = 8), and extrapolation of the data indicates that at high enough HCN concentration H2 evolution can be eliminated. The products are methane plus ammonia (six electrons), and methylamine (four electrons). There is an excess (relative to methane) of ammonia formed, which, according to electron balance studies, may arise from a two-electron intermediate. Both nitrous oxide and acetylene (but not N2) influence the distribution of cyanide reduction products, implying simultaneous binding. HCN appears to bind to and be reduced at an enzyme state more oxidized than the one responsible for either H2 evolution or N2 reduction.

Silver nanoparticles (SNPs) translocate to the brain through the blood stream after they are implanted in vivo. The aim of this study was to investigate the distribution of SNPs that crossed through the blood-brain barrier (BBB). An in vitro BBB model established by co-cultures of rat brain microvessel vascular endothelial cells (BMVECs) with astrocytes (ACs) was cultured with cell culture medium containing 100 microg/mL of either SNPs or silver microparticles (SMPs). After 4 hours of culture, the ultrastructure and its silver content of BBB was evaluated with transmission electronic microscopy (TEM) and inductively-coupled plasma mass spectrometry (ICP-MS) respectively. Results demonstrated that SNPs crossed the BBB and accumulated inside BMVECs, while the SMPs did not. The data indicated a special distribution of SNPs in the BBB and suggested that SNPs pass the BBB mainly by transcytosis of capillary endothelial cells. Further study would be necessary to evaluate the actual biological effects of SNPs on the brain.

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Objective. To explore a centralized approach to build test sets and assess the performance of an artificial intelligence medical device (AIMD) which is intended for computer-aided diagnosis of diabetic retinopathy (DR). Method. A framework was proposed to conduct data collection, data curation, and annotation. Deidentified colour fundus photographs were collected from 11 partner hospitals with raw labels. Photographs with sensitive information or authenticity issues were excluded during vetting. A team of annotators was recruited through qualification examinations and trained. The annotation process included three steps: initial annotation, review, and arbitration. The annotated data then composed a standardized test set, which was further imported to algorithms under test (AUT) from different developers. The algorithm outputs were compared with the final annotation results (reference standard). Result. The test set consists of 6327 digital colour fundus photographs. The final labels include 5 stages of DR and non-DR, as well as other ocular diseases and photographs with unacceptable quality. The Fleiss Kappa was 0.75 among the annotators. The Cohen’s kappa between raw labels and final labels is 0.5. Using this test set, five AUTs were tested and compared quantitatively. The metrics include accuracy, sensitivity, and specificity. The AUTs showed inhomogeneous capabilities to classify different types of fundus photographs. Conclusions. This article demonstrated a workflow to build standardized test sets and conduct algorithm testing of the AIMD for computer-aided diagnosis of diabetic retinopathy. It may provide a reference to develop technical standards that promote product verification and quality control, improving the comparability of products.