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The volume-specific surface area (VSSA) of a particulate material is one of two apparently very different metrics recommended by the European Commission for a definition of “nanomaterial” for regulatory purposes: specifically, the VSSA metric may classify nanomaterials and non-nanomaterials differently than the median size in number metrics, depending on the chemical composition, size, polydispersity, shape, porosity, and aggregation of the particles in the powder. Here we evaluate the extent of agreement between classification by electron microscopy (EM) and classification by VSSA on a large set of diverse particulate substances that represent all the anticipated challenges except mixtures of different substances. EM and VSSA are determined in multiple labs to assess also the level of reproducibility. Based on the results obtained on highly characterized benchmark materials from the NanoDefine EU FP7 project, we derive a tiered screening strategy for the purpose of implementing the definition of nanomaterials. We finally apply the screening strategy to further industrial materials, which were classified correctly and left only borderline cases for EM. On platelet-shaped nanomaterials, VSSA is essential to prevent false-negative classification by EM. On porous materials, approaches involving extended adsorption isotherms prevent false positive classification by VSSA. We find no false negatives by VSSA, neither in Tier 1 nor in Tier 2, despite real-world industrial polydispersity and diverse composition, shape, and coatings. The VSSA screening strategy is recommended for inclusion in a technical guidance for the implementation of the definition. Graphical abstract We evaluate the extent of agreement between classification by electron microscopy (EM) and classification by Volume-Specific Surface Area (VSSA) on a large set of diverse particulate substances. These represent the challenges anticipated for identification of nanomaterials by the European Commission recommendation for a definition of nanomaterials for regulatory purposes.

Background Staphylococcus aureus clinical isolates with vancomycin MICs of 2 µg/ml have been associated with vancomycin therapeutic failure and the heterogenous vancomycin-intermediate S. aureus (hVISA) phenotype. While carriage of van genes has usually been associated with higher level of MIC and frank vancomycin resistance, the unrecognized risk of hetero-resistance is frequently underestimated. Methods used for assessing vancomycin susceptibility have also shown different concordance and variable performance and accessibility in routine clinical diagnostics posing a challenge to inform treatment selection in hospital settings. Methods A total of 195 clinical samples were obtained among which 100 S. aureus isolates were identified. Ninety-six MRSA isolates have been identified using cefoxitin disc and mec A gene detection. The van A and van B genes have been screened for in the studied isolates using conventional PCR amplification. Examination of reduced vancomycin susceptibility has been performed using vancomycin screen agar, Broth Micro Dilution method (BMD), and VITEK2. Blood isolates were screened for hVISA using PAP-AUC method. Results Vancomycin screening agar applied to 96 MRSA isolates revealed 16 isolates with reduced vancomycin susceptibility. Further MIC testing revealed that 7 isolates were VISA and only 1 isolate was identified as VRSA using both BMD MIC method and VITEK2. Among 24 tested blood isolates, 4 isolates (16.7%) revealed the hVISA phenotype as identified using PAP-AUC method. Using PCR, van A gene was identified in 5 S. aureus isolates (5%). Three of them were VSSA while the other two isolates were VISA. Conclusion In this study, we report the very low prevalence of VRSA among the tested S. aureus clinical isolates (1%) and the existence of hVISA phenotype among studied S. aureus blood isolates at the rate of 16.7% in our setting. Fifty percent (8/16) of isolates that demonstrated reduced vancomycin susceptibility using vancomycin agar screen tested susceptible using both broth dilution method and VITEK2. These finding together with the concerning silent carriage of van A gene among VSSA and VISA (5%) may underly hidden and uninvestigated factors contributing to vancomycin treatment failure that warrant cautious vancomycin prescription.

With the advancement of science and technology, the relationship between vocal singing training methods and big data technology is getting closer and closer. The application of training methods is a means of expressing vocal compositions. Emotional expression is the ultimate purpose and meaning of method optimization. Training methods and emotional expression are equally important in vocal singing, and both are indispensable. In this paper, a VSSA-separation model is established based on the Vocal Signal Separation Algorithm (VSSA). Focus on optimizing the training method of vocal singing. Through in-depth discussion of existing works, I try to find its inner influence and outer connection. In order to better understand the grasp and application of vocal singing method and emotional expression balance. It can be seen from the calculation that the image shaping in the song language accounts for 83% of the optimization of the training method. Inverse word processing in song language has a different proportion of the optimization of the training method. It accounts for 71% of English operas. It accounts for only 13% of Chinese operas. Artistic effects have the highest average optimization difficulty among the training methods. Its optimization difficulty is as high as 89%.

Prolonged vancomycin usage may cause methicillin-resistant to become vancomycin-intermediate (VISA) and heterogeneous VISA (hVISA). Mechanisms of vancomycin resistance of VISA and hVISA are still unclear. In this study, analyses of nucleotide sequence variations in 30 vancomycin-sensitive (VSSA), 41 hVISA and 16 VISA isolates revealed 29 single-nucleotide variations in 12 genes ( , , , , , , , , , , and ) that are related to cell wall synthesis or the two-component system. Six of these 29 single-nucleotide variations were novel and resulted in the following amino acid changes: Q692E in FmtC; T278I, P306L and I311T in HtrA; and I63V and K101E in Upps. Since P306L and I311T in HtrA and I63V in Upps were present in the majority (76.7%-86.7%) of VSSA isolates, these three amino acid variations may not be associated with vancomycin resistance. The other three amino acid variations (T278I in HtrA, K101E in Upps and Q692E in FmtC) were present in the majority (87.5%-93.8%) of hVISA and VISA isolates, but only in a small number (22.9%-25.7%) of VSSA isolates, suggesting that they are associated with vancomycin resistance.