Construction of 1,3,4-oxadiazolines bearing CF3-quaternary centers via amino-assisted [3 + 2] cycloadditions.

An amino-assisted [3 + 2] cycloaddition strategy of nitrile imines with o-aminotrifluoroacetophenones has been explored, thus providing functionalized 1,3,4-oxadiazolines bearing CF3-quaternary centers in good to excellent yields in the presence of K2CO3 under mild conditions. The amino groups located at the ortho-position of trifluoroacetophenone might play a crucial role in the present cyclization. The MTT assay shows that the 1,3,4-oxadiazoline derivatives could be potential candidates for the treatment of head and neck cancers.

The influence of sentence focus on motor system activity in language comprehension and its temporal dynamics: Preliminary evidence from sEMG.

Previous research has shown that individual experiences and experimental tasks can influence the occurrence of mental simulation during sentence comprehension. However, little research has focused on the effect of sentence focus on mental simulation and its temporal dynamics. Sentence focus refers to the hierarchical structure of information within a sentence, where focused information represents the most prominent and essential information. In contrast, nonfocused information provides a background for the focused information. The present study investigated whether sentence focus would affect the activity of the motor system in language comprehension and at which stage the effect of sentence focus occurred. We measured spontaneous arm muscle electrical activity by surface electromyography (sEMG) while participants read action-focused, nonaction-focused, and control sentences. We observed greater spontaneous muscle electrical activity in the flexor common muscle of the fingers when participants read action-focused sentences compared to nonaction-focused and control sentences. Additionally, there was an interactive trend between sentence type and time, spontaneous muscle electrical activity while reading action-focused sentences was observed in both early (1 ms to 300 ms after the presentation of the action phrase) and late time windows (901 ms to 1500 ms after the action phrase). The findings suggest that the motor system exhibits flexible engagement during language comprehension and the impact of sentence focus on motor system activity may be throughout both the lexical-semantic retrieval and sentence-meaning integration stages.

Construction of and evaluation of the immune response to two recombinant pseudorabies viruses expressing the B119L and EP364R proteins of African swine fever virus.

African swine fever (ASF) is an infectious disease caused by ASF virus (ASFV), which is characterized by high infectivity, rapid onset of disease, and a high mortality rate. Outbreaks of ASFV have caused great economic losses to the global pig industry, and there is a need to develop safe and effective vaccines. In this study, two recombinant pseudorabies virus (PRV) strains, rGXGG-2016-ΔgI/ΔgE-EP364R and rGXGG-2016-ΔgI/ΔgE-B119L, expressing the EP364R and B119L protein, respectively, of ASFV, were constructed by homologous recombination technology. Western blotting and immunofluorescence analysis showed that these foreign proteins were expressed in cells infected with the recombinant strains. The strains showed good genetic stability and proliferative characteristics for 20 passages in BHK-21 cells. Both of these strains were immunogenic in mice, inducing the production of specific antibodies against the expressed ASFV proteins while providing protection against lethal challenge with PRV. Thus, the recombinant strains rGXGG-2016-ΔgI/ΔgE-EP364R and rGXGG-2016-ΔgI/ΔgE-B119L could be used as candidate vaccines for both ASFV and PRV. In addition, our study identifies two potential target genes for the development of safe and efficient ASFV vaccines, provides a reference for the construction of bivalent ASFV and PRV vaccines, and demonstrates the feasibility of developing a live ASFV vector vaccine.

Genome-wide identification of glutamate receptor-like gene family in soybean.

Glutamate receptor-like genes (GLRs) are essential in the growth and development of plants and many physiological and biochemical processes; however, related information in soybean is lacking. In this study, 105 GLRs, including 67 Glycine soja and 38 Glycine max GLRs, were identified and divided into two clades (Clades II and III) according to their phylogenetic relationships. GLR members in the same branch had a relatively conservative motif composition and genetic structure. Furthermore, the soybean GLR family mainly experienced purification selection during evolution. Cis-acting element analysis, gene ontology, and Kyoto Encyclopedia of Genes and Genomic annotations indicated the complexity of the gene regulation and functional diversity of the soybean GLR. Moreover, transcriptome data analysis showed that these GLRs had different expression profiles in different tissues, and Clade III members had higher and more common expression patterns. Additionally, the expression profiles under jasmonic acid treatment and salt stress indicate that the GLR participated in the jasmonic acid signaling pathway and plays a role in salt treatment. This study provides information for a comprehensive understanding of the soybean GLR family and a reference for further functional research and genetic improvement.

Health hazards of particles in additive manufacturing: a cross-disciplinary study on reactivity, toxicity and occupational exposure to two nickel-based alloys.

The increasing use of additive manufacturing (AM) techniques (e.g., 3D-printing) offers many advantages but at the same time presents some challenges. One concern is the possible exposure and health risk related to metal containing particles of different sizes. Using the nickel-based alloys Hastelloy X (HX) and Inconel 939 (IN939) as a case, the aim of this cross-disciplinary study was to increase the understanding on possible health hazards and exposure. This was done by performing in-depth characterization of virgin, reused and condensate powders, testing in vitro toxicity (cytotoxicity, genotoxicity, oxidative stress), and measuring occupational airborne exposure. The results showed limited metal release from both HX and IN939, and slightly different surface composition of reused compared to virgin powders. No or small effects on the cultured lung cells were observed when tested up to 100 µg/mL. Particle background levels in the printing facilities were generally low, but high transient peaks were observed in relation to sieving. Furthermore, during post processing with grinding, high levels of nanoparticles (> 100,000 particles/cm3) were noted. Urine metal levels in AM operators did not exceed biomonitoring action limits. Future studies should focus on understanding the toxicity of the nanoparticles formed during printing and post-processing.

Molecular epidemiological and genetic characterization of pseudorabies virus in Guangxi, China.

Pseudorabies virus (PRV) is an important pathogen that can cause harm to the pig population. Since 2011, there have been a number of large-scale outbreaks of pseudorabies on Chinese farms where animals had been vaccinated with the Bartha-K61 vaccine. In order to understand the epidemiological trend and genetic variations of PRV in Guangxi province, China, 819 tissue samples were collected from swine farms where PRV infection was suspected from 2013 to 2019, and these were tested for infectious wild strains of PRV. The results showed a positive rate of PRV in Guangxi province of 28.21% (231/819). Thirty-six wild-type PRV strains were successfully isolated from PRV-positive tissue samples, and a genetic evolutionary analysis was performed based on the gB, gC, gD, gE, and TK genes. Thirty of the PRV strains were found to be closely related to the Chinese variant strains HeN1-China-2012 and HLJ8-China-2013. In addition, five PRV strains were genetically related to Chinese classical strains, and one isolate was a recombinant of the PRV variant and the vaccine strain Bartha-K61. Amino acid sequence analysis showed that all 36 PRV strains had characteristic variant sites in the amino acid sequences of the gB, gC, gD, and gE proteins. Pathogenicity analysis showed that, compared to classical PRV strains, the PRV variant strains were more pathogenic in mice and had a lower LD50. Taken together, our results show that wild-type PRV infections are common on pig farms in Guangxi province of China and that the dominant prevalent strains were those of the PRV variants. The PRV variant strains also had increased pathogenicity in mice. Our data will provide a useful reference for understanding the prevalence and genetic evolution of PRV in China.

Synergetic roadmap of carbon neutrality and clean air for China.

It is well recognized that carbon dioxide and air pollutants share similar emission sources so that synergetic policies on climate change mitigation and air pollution control can lead to remarkable co-benefits on greenhouse gas reduction, air quality improvement, and improved health. In the context of carbon peak, carbon neutrality, and clean air policies, this perspective tracks and analyzes the process of the synergetic governance of air pollution and climate change in China by developing and monitoring 18 indicators. The 18 indicators cover the following five aspects: air pollution and associated weather-climate conditions, progress in structural transition, sources, inks, and mitigation pathway of atmospheric composition, health impacts and benefits of coordinated control, and synergetic governance system and practices. By tracking the progress in each indicator, this perspective presents the major accomplishment of coordinated control, identifies the emerging challenges toward the synergetic governance, and provides policy recommendations for designing a synergetic roadmap of Carbon Neutrality and Clean Air for China.

Augmentation-Free Graph Contrastive Learning of Invariant-Discriminative Representations.

Graph contrastive learning (GCL) is a promising direction toward alleviating the label dependence, poor generalization and weak robustness of graph neural networks, learning representations with invariance, and discriminability by solving pretasks. The pretasks are mainly built on mutual information estimation, which requires data augmentation to construct positive samples with similar semantics to learn invariant signals and negative samples with dissimilar semantics to empower representation discriminability. However, an appropriate data augmentation configuration depends heavily on lots of empirical trials such as choosing the compositions of data augmentation techniques and the corresponding hyperparameter settings. We propose an augmentation-free GCL method, invariant-discriminative GCL (iGCL), that does not intrinsically require negative samples. iGCL designs the invariant-discriminative loss (ID loss) to learn invariant and discriminative representations. On the one hand, ID loss learns invariant signals by directly minimizing the mean square error (MSE) between the target samples and positive samples in the representation space. On the other hand, ID loss ensures that the representations are discriminative by an orthonormal constraint forcing the different dimensions of representations to be independent of each other. This prevents representations from collapsing to a point or subspace. Our theoretical analysis explains the effectiveness of ID loss from the perspectives of the redundancy reduction criterion, canonical correlation analysis (CCA), and information bottleneck (IB) principle. The experimental results demonstrate that iGCL outperforms all baselines on five node classification benchmark datasets. iGCL also shows superior performance for different label ratios and is capable of resisting graph attacks, which indicates that iGCL has excellent generalization and robustness. The source code is available at https://github.com/lehaifeng/ T-GCN/tree/master/iGCL.

The role of dendritic cells in COVID-19 infection.

The persistent pandemic of coronavirus disease in 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) currently poses a major infectious threat to public health around the world. COVID-19 is an infectious disease characterized by strong induction of inflammatory cytokines, progressive lung inflammation, and potential multiple organs dysfunction. SARS-CoV-2 infection is closely related to the innate immune system and adaptive immune system. Dendritic cells (DCs), as a "bridge" connecting innate immunity and adaptive immunity, play many important roles in viral diseases. In this review, we will pay special attention to the possible mechanism of dendritic cells in human viral transmission and clinical progression of diseases, as well as the reduction and dysfunction of DCs in severe SARS-CoV-2 infection, so as to understand the mechanism and immunological characteristics of SARS-CoV-2 infection.

A Novel Nanosafety Approach Using Cell Painting, Metabolomics, and Lipidomics Captures the Cellular and Molecular Phenotypes Induced by the Unintentionally Formed Metal-Based (Nano)Particles.

Additive manufacturing (AM) or industrial 3D printing uses cutting-edge technologies and materials to produce a variety of complex products. However, the effects of the unintentionally emitted AM (nano)particles (AMPs) on human cells following inhalation, require further investigations. The physicochemical characterization of the AMPs, extracted from the filter of a Laser Powder Bed Fusion (L-PBF) 3D printer of iron-based materials, disclosed their complexity, in terms of size, shape, and chemistry. Cell Painting, a high-content screening (HCS) assay, was used to detect the subtle morphological changes elicited by the AMPs at the single cell resolution. The profiling of the cell morphological phenotypes, disclosed prominent concentration-dependent effects on the cytoskeleton, mitochondria, and the membranous structures of the cell. Furthermore, lipidomics confirmed that the AMPs induced the extensive membrane remodeling in the lung epithelial and macrophage co-culture cell model. To further elucidate the biological mechanisms of action, the targeted metabolomics unveiled several inflammation-related metabolites regulating the cell response to the AMP exposure. Overall, the AMP exposure led to the internalization, oxidative stress, cytoskeleton disruption, mitochondrial activation, membrane remodeling, and metabolic reprogramming of the lung epithelial cells and macrophages. We propose the approach of integrating Cell Painting with metabolomics and lipidomics, as an advanced nanosafety methodology, increasing the ability to capture the cellular and molecular phenotypes and the relevant biological mechanisms to the (nano)particle exposure.

An Unsupervised Deep-Transfer-Learning-Based Motor Imagery EEG Classification Scheme for Brain-Computer Interface.

Brain-computer interface (BCI) research has attracted worldwide attention and has been rapidly developed. As one well-known non-invasive BCI technique, electroencephalography (EEG) records the brain's electrical signals from the scalp surface area. However, due to the non-stationary nature of the EEG signal, the distribution of the data collected at different times or from different subjects may be different. These problems affect the performance of the BCI system and limit the scope of its practical application. In this study, an unsupervised deep-transfer-learning-based method was proposed to deal with the current limitations of BCI systems by applying the idea of transfer learning to the classification of motor imagery EEG signals. The Euclidean space data alignment (EA) approach was adopted to align the covariance matrix of source and target domain EEG data in Euclidean space. Then, the common spatial pattern (CSP) was used to extract features from the aligned data matrix, and the deep convolutional neural network (CNN) was applied for EEG classification. The effectiveness of the proposed method has been verified through the experiment results based on public EEG datasets by comparing with the other four methods.

Reproductive toxicity investigation of silica nanoparticles in male pubertal mice.

Silica nanoparticles (SiNPs), one of the most produced nanoparticles (NPs) in the world, are used in all aspects of life. The increased application of SiNPs, especially in medicine, has raised considerable concern regarding their toxicological impact. Previous studies have shown that SiNPs can pass through the reproductive barrier and cause reproductive organ dysfunction by destroying Sertoli cells, Leydig cells, and germ cells. However, little is known about the mechanism of SiNPs-induced reproductive toxicity. In the present study, 5-week-old male mice were intraperitoneally administered SiNPs per day for 1 week at a dose of 0.2 mg per mouse. The results showed that SiNPs could cause damage to the structure of the testis and the epididymis and change the reproductive organ coefficients, leading to decreases of 56.1% and 55.3% in the rates of sperm concentration and motility and an increase of 168.8% in the rate of sperm abnormality. Moreover, the serum testosterone level obviously decreased from 18.77 to 5.23 µg/ml after exposure, and the transcription statuses of some key genes involved in the synthesis and transport of testosterone in the testis were also affected. Additional experiments showed that SiNPs exposure during puberty induced oxidative stress and an inflammatory response, as shown by the changed activity of superoxide dismutase (SOD), increased contents of malondialdehyde (MDA), and excess expression of proinflammatory factors, including TNF-α and IL-1ß. Furthermore, the administration of SiNPs caused DNA damage and cell apoptosis, which were presented by the increased apoptotic cells in the sections of testis and epididymis and activation of the TNF-α/TNFR I-mediated pro-apoptotic pathway. In conclusion, these results indicate that SiNPs exposure during puberty significantly damaged the structure and function of the testis and epididymis by inducing oxidative stress and cell apoptosis. This study provides novel insight into SiNPs-induced reproductive toxicity during puberty, which warrants a more careful assessment of SiNPs before their application in juvenile supplies.

Silica nanoparticles cause spermatogenesis dysfunction in mice via inducing cell cycle arrest and apoptosis.

The widespread use of silica nanoparticles (SiNPs) has increased the risk of human exposure, which raised concerns about their adverse effects on human health, especially the reproductive system. Previous studies have shown that SiNPs could cause damage to reproductive organs, but the specific mechanism is still unclear. In this study, to investigate the underlying mechanism of male reproductive toxicity induced by SiNPs, 40 male mice at the age of 8 weeks were divided into two groups and then intraperitoneally injected with vehicle control or 10 mg/kg SiNPs per day for one week. The results showed that SiNPs could damage testicular structure, perturb spermatogenesis and reduce serum testosterone levels, leading to a decrease in sperm quality and quantity. In addition, the ROS level in the testis of exposed mice was significantly increased, followed by imbalance of the oxidative redox status. Further study revealed that exposure to SiNPs led to cell cycle arrest and apoptosis, as shown by downregulation of the expression of positive cell cycle regulators and the activation of TNF-α/TNFR Ⅰ-mediated apoptotic pathway. The results demonstrated that SiNPs could cause testicles injure via inducing oxidative stress and DNA damage which led to cell cycle arrest and apoptosis, and thereby resulting in spermatogenic dysfunction.

[Effect of Vitamin D3 to Platelet Activation Mediated by Tumor Cell Culture Medium].

OBJECTIVE: To investigate the effect of vitamin D3 to platelet activation by tumor cell culture medium. METHODS: The peripheral blood platelets of BALB/c mice were isolated. The platelets were activated in 4T1 culture fluid for 24 h. The platelets were divided into 7 groups: control group, activation group, 1 nmol/L vitamin D3 group, 10 nmol/L vitamin D3 group, 50 nmol/L vitamin D3 group, 100 nmol/L vitamin D3 group, and positive drug (0.1 µmol/L eptifibatide) group. CCK-8 assay was used to detect the platelet proliferation at 24, 48 and 72 h. Flow cytometry was used to detect the expression of CD61 and CD62p and receptor for advanced glycation end products (RAGE) at 24, 48 and 72 h. ELISA was used to detect the level of platelet-endothelial cell adhesion molecule-1 (PECAM-1) at 24, 48 and 72 h. RESULTS: The CD41+/CD61+ and CD41+/CD62p+ ratio, PECAM-1 content and RAGE expression of platelets in activated group were all significantly increased as compared with those in control group (P<0.05). Compared with the activated group, the platelet proliferation, proportion of CD41+/CD61+ and CD41+/CD62p+, content of PECAM-1 and RAGE expression in vitamin D3 groups were all decreased (P<0.05). CONCLUSION: Vitamin D3 shows antiplatelet effect and can inhibit platelet proliferation and activation.

Analytical survey of tattoo inks-A chemical and legal perspective with focus on sensitizing substances.

BACKGROUND: Tattoo inks have been reported to elicit allergic contact dermatitis. OBJECTIVES: To investigate the labels and the contents of metals and pigments in tattoo inks, considering restrictions within the European Union. METHODS: Seventy-three tattoo inks currently available on the market, either bought or donated (already used), were investigated for trace metals and pigments by inductively coupled plasma mass spectrometry and by matrix-assisted laser desorption/ionization time of flight tandem mass spectrometry. RESULTS: Ninety-three percent of the bought tattoo inks violated European, legal requirements on labeling. Fifty percent of the tattoo inks declared at least one pigment ingredient incorrectly. Sixty-one percent of the inks contained pigments of concern, especially red inks. Iron, aluminium, titanium, and copper (most in green/blue inks) were the main metals detected in the inks. The level of metal impurities exceeded current restriction limits in only a few cases. Total chromium (0.35-139 µg/g) and nickel (0.1-41 µg/g) were found in almost all samples. The levels of iron, chromium, manganese, cobalt, nickel, zinc, lead, and arsenic were found to covary significantly. CONCLUSIONS: To prevent contact allergy and toxic reactions among users it is important for tattoo ink manufacturers to follow the regulations and decrease nickel and chromium impurities.

A novel 1-D densely connected feature selection convolutional neural network for heart sounds classification.

BACKGROUND: Heart sound auscultation, due to it being a non-invasive, convenient, and relatively low-cost technique, remains the dominant method for detection of cardiovascular disease. METHODS: In this paper, we present a method for identifying abnormal heart sounds based on a novel Dense Feature Selection Convolution Network framework (Dense-FSNet). The Dense-FSNet is comprised of multiple, circular dense connectivity modules, called Clique Blocks. These Clique Blocks can allow low-level and high-level features to stimulate each other for cyclic updates, which subsequently enhances the information flow among layers. Inspired by the channel-wise attention mechanism from Squeeze-and-Excitation Networks (SENet), we adopted squeeze-and-excitation block to avoid the progressive growth of parameters. The effect of the model was assessed using the accuracy, specificity, sensitivity, and area under the curve (AUC) values. To improve model performance, in addition to the structures mentioned above, we incorporated a multi-scale attention mechanism into our framework. RESULTS: Using this attention mechanism, our model was able to achieve adaptively spatial feature fusion by adjusting a hyper-feature that contains higher level visual information and lower-level features including edge details and context information. It is worth noting that data balance technology was also used in the process of building the model, and notable results have been achieved. CONCLUSIONS: Experience using the PhysioNet/CinC 2016 dataset shows that our proposed Dense-FSNet models achieve state of the art levels in the classification and detection of abnormal heart sounds.

Development and validation of a risk prediction model and scoring system for post-endoscopic retrograde cholangiopancreatography pancreatitis.

BACKGROUND: A few models have been proposed for the prediction of the risk of post-endoscopic retrograde cholangiopancreatography pancreatitis (PEP), but many include factors that are not assessed routinely. Herein, we intend to develop and validate a predictive model for the occurrence of PEP. METHODS: Data of patients who underwent endoscopic retrograde cholangiopancreatography (ERCP) from January 01, 2016 to May 16, 2019 (training set and internal test set) and from May 17, 2019 to December 25, 2019 (external test set) were retrospectively collected. The performance of the model was validated in the two validation cohorts. RESULTS: A total of 342 patients were included for the external test set, and 47 (13.7%) developed PEP. The variables included in the scoring system were gastrectomy history, high direct bilirubin (DBIL), high albumin (ALB), villous type of papillary orifice, nodular type of papillary orifice, pancreatic guidewire passages, precut sphincterotomy, and high operator experience. A total score >5 indicated high risk. In the external test set, the area under the curve (AUC) was 0.718, the sensitivity was 0.723, and the specificity was 0.676. In the external test set, the probability of PEP was 6.1%, 17.0%, and 37.5% in patients with low (<0), moderate (0-5), and high (>5) risk scores, respectively. CONCLUSIONS: This study established a scoring system for predicting the risk of PEP using routinely measured clinical variables. Its application in routine work warrants further investigation.

Adversarial active learning for the identification of medical concepts and annotation inconsistency.

OBJECTIVE: Named entity recognition (NER) is a principal task in the biomedical field and deep learning-based algorithms have been widely applied to biomedical NER. However, all of these methods that are applied to biomedical corpora use only annotated samples to maximize their performances. Thus, (1) large numbers of unannotated samples are relinquished and their values are overlooked. (2) Compared with other types of active learning (AL) algorithms, generative adversarial learning (GAN)-based AL methods have developed slowly. Furthermore, current diversity-based AL methods only compute similarities between a pair of sentences and cannot evaluate distribution similarities between groups of sentences. Annotation inconsistency is one of the significant challenges in the biomedical annotation field. Most existing methods for addressing this challenge are statistics-based or rule-based methods. (3) They require sufficient expert knowledge and complex designs. To address challenges (1), (2), and (3) simultaneously, we propose innovative algorithms. METHODS: GAN is introduced in this paper, and we propose the GAN-bidirectional long short-term memory-conditional random field (GAN-BiLSTM-CRF) and the GAN-bidirectional encoder representations from transformers-conditional random field (GAN-BERT-CRF) models, which can be considered an NER model, an AL model, and a model identifying error labels. BiLSTM-CRF or BERT-CRF is defined as the generator and a convolutional neural network (CNN)-based network is considered the discriminator. (1) The generator employs unannotated samples in addition to annotated samples to maximize NER performance. (2) The outputs of the CRF layer and the discriminator are used to select unlabeled samples for the AL task. (3) The discriminator discriminates the distribution of error labels from that of correct labels, identify error labels, and address the annotation inconsistency challenge. RESULTS: The corpus from the 2010 i2b2/VA NLP challenge and the Chinese CCKS-2017 Task 2 dataset are adopted for experiments. Compared to the baseline BiLSTM-CRF and BERT-CRF, the GAN-BiLSTM-CRF and GAN-BERT-CRF models achieved significant improvements on the precision, recall, and F1 scores in terms of NER performance. Learning curves in AL experiments show the comparative results of the proposed models. Furthermore, the trained discriminator can identify samples with incorrect medical labels in both simulation and real-word experimental environments. CONCLUSION: The idea of introducing GAN contributes significant results in terms of NER, active learning, and the ability to identify incorrect annotated samples. The benefits of GAN will be further studied.

Bioaccessibility of Nickel and Cobalt Released from Occupationally Relevant Alloy and Metal Powders at Simulated Human Exposure Scenarios.

Nickel (Ni) and cobalt (Co) release from chromium-alloy powders (different stainless steels and a nickel-based Inconel alloy) compared with Ni and Co metal powders was investigated at simulated human exposure scenarios (ingestion, skin contact, and inhalation) between 2 and 168 h. All investigated powders consisted of particles sized within the respirable range. The powder particles and their surface reactivity were studied by means of nitrogen adsorption and electrochemical, spectroscopic (X-ray photoelectron spectroscopy and atomic absorption spectroscopy), light scattering, and microscopic techniques. The release of both Ni and Co was highest in the acidic and complexing fluids simulating the gastric environment and an inhalation scenario of small powders (artificial lysosomal fluid). Relatively high corrosion resistance and lower levels of released Ni and Co were observed in all fluids for all alloy powders compared with the corresponding pure metals. The extent of released metals was low for powders with a passive surface oxide. This study strongly emphasizes the importance of considering alloying effects in toxicological classification and/or regulation of Ni and Co in alloys and metals.