Culture-Independent Raman Spectroscopic Identification of Bacterial Pathogens from Clinical Samples Using Deep Transfer Learning.

The rapid identification of bacterial pathogens in clinical samples like blood, urine, pus, and sputum is the need of the hour. Conventional bacterial identification methods like culturing and nucleic acid-based amplification have limitations like poor sensitivity, high cost, slow turnaround time, etc. Raman spectroscopy, a label-free and noninvasive technique, has overcome these drawbacks by providing rapid biochemical signatures from a single bacterium. Raman spectroscopy combined with chemometric methods has been used effectively to identify pathogens. However, a robust approach is needed to utilize Raman features for accurate classification while dealing with complex data sets such as spectra obtained from clinical isolates, showing high sample-to-sample heterogeneity. In this study, we have used Raman spectroscopy-based identification of pathogens from clinical isolates using a deep transfer learning approach at the single-cell level resolution. We have used the data-augmentation method to increase the volume of spectra needed for deep-learning analysis. Our ResNet model could specifically extract the spectral features of eight different pathogenic bacterial species with a 99.99% classification accuracy. The robustness of our model was validated on a set of blinded data sets, a mix of cultured and noncultured bacterial isolates of various origins and types. Our proposed ResNet model efficiently identified the pathogens from the blinded data set with high accuracy, providing a robust and rapid bacterial identification platform for clinical microbiology.

Ultrasound-Assisted Facile Synthesis of Nanostructured Hybrid Vesicle for the Nasal Delivery of Indomethacin: Response Surface Optimization, Microstructure, and Stability.

This work is devoted to design a novel nanostructured hybrid vesicle (NHV) made of lecithin and an acrylate/C10-C30 alkyl acrylate for the nasal delivery of a model active indomethacin (IND), and further to probe its microstructure, intermolecular interactions, drug release behavior, ex vivo permeation, and stability. NHVs were prepared by cavitation technology employing RSM-based central composite design (CCD). Amount of lecithin (X1), power of ultrasound (X2), and sonication time (X3) were selected as three independent variables while the studied response included Z-Avg (nm), polydispersity index (PDI), and zeta potential (mV). The designed system (NHV) was investigated through dynamic (DLS) and electrophoretic light scattering (ELS), attenuated total reflectance (ATR-FTIR), oscillatory measurement (stress and frequency sweep), and transmission electron microscopy (TEM). CCD was found useful in optimizing NHV. An optimized formulation (S6) had Z-Avg 80 nm, PDI 0.2, and zeta potential of - 43.26 mV. Morphology investigation revealed spherical vesicles with smaller TEM diameters (the largest particle being 52.26 nm). ATR analysis demonstrated significant intermolecular interactions among the drug (IND) and the components of vesicles. The designed vesicles had an elastic predominance and displayed supercase II (n > 1) type of drug release. Besides, the vesicles possessed potential to transport IND across the nasal mucosa with the steady-state flux (µg/cm2/h) and permeability coefficient (cm/h) of 26.61 and 13.30 × 10-3, respectively. NHV exhibited an exceptional stability involving a combination of electrostatic and steric interactions while the histopathology investigation confirmed their safety for nasal administration.

Engineering of a hybrid polymer-lipid nanocarrier for the nasal delivery of tenofovir disoproxil fumarate: physicochemical, molecular, microstructural, and stability evaluation.

PURPOSE: To engineer a hybrid nanocarrier system based on lipid and polymer for the nasal delivery of tenofovir disoproxil fumarate (TDF), and further to investigate its physicochemical, molecular, microstructural, and stability aspects. METHODS: Nanoparticles were prepared by melt emulsification-probe sonication technique. A 3(2) factorial design was used to identify key formulation variables influencing the characteristics of drug-loaded carrier. FT-IR, mass spectroscopy (MS) and (1)H NMR was used to probe molecular interactions among the components of the system, while the surface morphology was imagined through electron microscopy (TEM and SEM). Thermal analysis and powder X-ray diffraction (PXRD) was used to explore melting and crystallization behavior of drug and the carrier lipid. PLN-9 GEL was studied for its rheology, drug release, ex-vivo permeation, histopathology, and stability. RESULTS: Batch PLN-9 had size of 239 nm, drug encapsulation of 87.14% and revealed spherical morphology. MS, FT-IR and (1)H NMR established compatibility between the drug (TDF) and the carrier lipid (Lauric acid), while, a strong H-bonding was identified between the amino (-NH2) group of drug and the carboxyl (-COOH) group of pemulen polymer. Thermal analysis confirmed an amorphous TDF within the carrier matrix. PXRD analysis indicated substantial change in the molecular packing and subcell structure of carrier lipid during the PLN processing. PLN-9 GEL had shear thinning rheology, an anomalous type (n>0.5) of drug release and possessed potential to transport TDF across the nasal mucosa with an average flux of 135.36 µg/cm(2)/h. CONCLUSION: The designed carrier can encapsulate TDF and accentuates its transnasal flux, thus could be used as a carrier for an effective nasal delivery of TDF.