Combined Mutual Learning Net for Raman Spectral Microbial Strain Identification.

Infectious diseases pose a significant threat to global health, yet traditional microbiological identification methods suffer from drawbacks, such as high costs and long processing times. Raman spectroscopy, a label-free and noninvasive technique, provides rich chemical information and has tremendous potential in fast microbial diagnoses. Here, we propose a novel Combined Mutual Learning Net that precisely identifies microbial subspecies. It demonstrated an average identification accuracy of 87.96% in an open-access data set with thirty microbial strains, representing a 5.76% improvement. 50% of the microbial subspecies accuracies were elevated by 1% to 46%, especially for E. coli 2 improved from 31% to 77%. Furthermore, it achieved a remarkable subspecies accuracy of 92.4% in the custom-built fiber-optical tweezers Raman spectroscopy system, which collects Raman spectra at a single-cell level. This advancement demonstrates the effectiveness of this method in microbial subspecies identification, offering a promising solution for microbiology diagnosis.

N-Nitrosodimethylamine formation in metformin hydrochloride sustained-release tablets: Effects of metformin and hypromellose used in drug product formulation.

In recent years, nitrosamines have been discovered in some types of drug products that becomes a current regulatory hotspot, and have attracted a lot attention from both regulatory authorities and industry. This manuscript provided an industry perspective on the nitrosamines research. A liquid chromatography coupled with tandem mass spectrometry（LC-MS/MS）method was developed and applied for the quantification of N-nitrosodimethylamine (NDMA) in metformin hydrochloride sustained-release tablets (MET). The key factors resulting in the NDMA formation in MET were identified through forced degradation and drug-excipient studies, which included high temperature, dimethylamine, strong alkali and oxidation conditions, peroxide and alkaline components contained in the formulation as well as the nitrite and nitrate impurities that might be presented in certain excipients. Further, API particle size and water content of the drug product would also affect the growth rate of NDMA. Therefore, the following mitigation strategies to reduce the risk of nitrosamines in the finished drug product are proposed in this manuscript: 1) avoid the use of excipients containing nitrite, nitrate and peroxide impurities; 2) avoid high temperature and strong alkaline environment in the production and storage condition; 3) maintain an appropriate water content level in the formulation. Based on the above principles, it was recommended to add antioxidant or incorporate excipient such as Na2CO3 to modify the formulation pH to weak basic environment in the formulation of MET, which can could effectively prevent formation of NDMA in the stability process.