A Novel image processing technique for weighted particle size distribution assessment.

The objective of the study was to create a reliable method that could be used to evaluate the particle size distribution of samples and pre-mixes in real-world situations, particularly those consisting of typical formulation blends. The goal was to use this method to assess the uniformity of the samples and ensure that they met the required quality standards. The researchers aimed to create a method that could be easily incorporated into the manufacturing process, providing a practical and efficient solution. This study demonstrates the use of ImageJ software to analyze the particle size distribution (PSD) of powders. The technique produces qualitative data from microscopy images and quantitative data from analysis of parameters including average diameter, D10, D50, D90, and standard deviation. The method was tested with various treatments, showing differentiating outcomes in all cases. The alternate technique provides a rapid and cost-effective method for PSD analysis, surpassing the limitations of sieve analysis. Extensive testing of the method, using a variety of sample types, including typical formulation blends, was performed. The results suggest that the method can effectively assess the morphology of changing materials during batch manufacturing and characterize uniformity in blends. The methodology has the capability to identify attributes related to PSD that are typically required to be monitored during manufacturing. The technique allows for accurate and reliable quantification of the attributes through image capture technology. The technique has future potential and has important implications for material science, powder rheology, pharmaceutical formulation development, and continual process monitoring.

[Figure: see text]A Novel Image Processing Technique for Weighted Particle Size Distribution Assessment.

The impact of S2 mutations on Omicron SARS-CoV-2 cell surface expression and fusogenicity.

SARS-CoV-2 Omicron subvariants are still emerging and spreading worldwide. These variants contain a high number of polymorphisms in the spike (S) glycoprotein that could potentially impact their pathogenicity and transmission. We have previously shown that the S:655Y and P681H mutations enhance S protein cleavage and syncytia formation. Interestingly, these polymorphisms are present in Omicron S protein. Here, we characterized the cleavage efficiency and fusogenicity of the S protein of different Omicron sublineages. Our results showed that Omicron BA.1 subvariant is efficiently cleaved but it is poorly fusogenic compared to previous SARS-CoV-2 strains. To understand the basis of this phenotype, we generated chimeric S protein using combinations of the S1 and S2 domains from WA1, Delta and Omicron BA.1 variants. We found that the S2 domain of Omicron BA.1 hindered efficient cell-cell fusion. Interestingly, this domain only contains six unique polymorphisms never detected before in ancestral SARS-CoV-2 variants. WA1614G S proteins containing the six individuals S2 Omicron mutations were assessed for their fusogenicity and S surface expression after transfection in cells. Results showed that the S:N856K and N969K substitutions decreased syncytia formation and impacted S protein cell surface levels. However, we observed that "first-generation" Omicron sublineages that emerged subsequently, had convergently evolved to an enhanced fusogenic activity and S expression on the surface of infected cells while "second-generation" Omicron variants have highly diverged and showed lineage-specific fusogenic properties. Importantly, our findings could have potential implications in the improvement and redesign of COVID-19 vaccines.

Early Ultrasound Surveillance of Newly-Created Hemodialysis Arteriovenous Fistula.

Introduction: We assess if ultrasound surveillance of newly-created arteriovenous fistulas (AVFs) can predict nonmaturation sufficiently reliably to justify randomized controlled trial (RCT) evaluation of ultrasound-directed salvage intervention. Methods: Consenting adults underwent blinded fortnightly ultrasound scanning of their AVF after creation, with scan characteristics that predicted AVF nonmaturation identified by logistic regression modeling. Results: Of 333 AVFs created, 65.8% matured by 10 weeks. Serial scanning revealed that maturation occurred rapidly, whereas consistently lower fistula flow rates and venous diameters were observed in those that did not mature. Wrist and elbow AVF nonmaturation could be optimally modeled from week 4 ultrasound parameters alone, but with only moderate positive predictive values (PPVs) (wrist, 60.6% [95% confidence interval, CI: 43.9-77.3]; elbow, 66.7% [48.9-84.4]). Moreover, 40 (70.2%) of the 57 AVFs that thrombosed by week 10 had already failed by the week 4 scan, thus limiting the potential of salvage procedures initiated by that scan's findings to alter overall maturation rates. Modeling of the early ultrasound characteristics could also predict primary patency failure at 6 months; however, that model performed poorly at predicting assisted primary failure (those AVFs that failed despite a salvage attempt), partly because patency of at-risk AVFs was maintained by successful salvage performed without recourse to the early scan data. Conclusion: Early ultrasound surveillance may predict fistula maturation, but is likely, at best, to result in only very modest improvements in fistula patency. Power calculations suggest that an impractically large number of participants (>1700) would be required for formal RCT evaluation.