• MeSH
• Proton Pumps chemistry   MeSH
• Spectrum Analysis MeSH
• Light MeSH

• MeSH
• Cytidine chemistry   MeSH
• Guanosine chemistry   MeSH
• Radiation, Ionizing MeSH
• Spectrum Analysis MeSH
• Binding Sites MeSH

• MeSH
• Electron Transport Complex IV MeSH
• Spectrum Analysis MeSH

• MeSH
• Molecular Biology MeSH
• Spectrum Analysis MeSH
• Publication type
• Abstracts MeSH

• Conspectus
• Biochemie. Molekulární biologie. Biofyzika
• NML Fields
• biologie
• radiologie, nukleární medicína a zobrazovací metody

This study reports on the successful use of a machine learning approach using attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy for the classification and prediction of a donor's sex from the fingernails of 63 individuals. A significant advantage of ATR FT-IR is its ability to provide a specific spectral signature for different samples based on their biochemical composition. The infrared spectrum reveals unique vibrational features of a sample based on the different absorption frequencies of the individual functional groups. This technique is fast, simple, non-destructive, and requires only small quantities of measured material with minimal-to-no sample preparation. However, advanced multivariate techniques are needed to elucidate multiplex spectral information and the small differences caused by donor characteristics. We developed an analytical method using ATR FT-IR spectroscopy advanced with machine learning (ML) based on 63 donors' fingernails (37 males, 26 females). The PLS-DA and ANN models were established, and their generalization abilities were compared. Here, the PLS scores from the PLS-DA model were used for an artificial neural network (ANN) to create a classification model. The proposed ANN model showed a greater potential for predictions, and it was validated against an independent dataset, which resulted in 92% correctly classified spectra. The results of the study are quite impressive, with 100% accuracy achieved in correctly classifying donors as either male or female at the donor level. Here, we underscore the potential of ML algorithms to leverage the selectivity of ATR FT-IR spectroscopy and produce predictions along with information about the level of certainty in a scientifically defensible manner. This proof-of-concept study demonstrates the value of ATR FT-IR spectroscopy as a forensic tool to discriminate between male and female donors, which is significant for forensic applications.

• MeSH
• Algorithms * MeSH
• Humans MeSH
• Nails * MeSH
• Neural Networks, Computer MeSH
• Specimen Handling MeSH
• Spectroscopy, Fourier Transform Infrared methods   MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Fully and partially hydrolyzed poly(vinyl alcohol) (PVA) was modified with zinc sulphate in the concentration range from 0 to 9 wt% of recalculated zinc content using the solvent cast technique. The resulting polymeric films were characterized by optical microscopy, stress-strain analysis, differential scanning calorimetry and Fourier transform infrared spectroscopy (FT-IR-ATR). In addition, agar diffusion test and dilution and spread plate technique were used for determination of antibacterial properties of the films against both Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli, Pseudomonas aeruginosa and Klebsiella pneumoniae) bacterial strains. A mathematical model was applied on the measured data and parameters characterizing the antibacterial efficiency of the material were calculated and discussed. The results revealed that the PVA hydrolysis degree can play an important role in all studied properties, including antibacterial activity of the all PVA-based materials.

• MeSH
• Anti-Bacterial Agents chemistry   pharmacology   MeSH
• Calorimetry, Differential Scanning MeSH
• Escherichia coli drug effects   MeSH
• Hydrolysis MeSH
• Polymers chemistry   pharmacology   MeSH
• Polyvinyl Alcohol chemistry   MeSH
• Pseudomonas aeruginosa drug effects   MeSH
• Zinc Sulfate chemistry   MeSH
• Spectroscopy, Fourier Transform Infrared MeSH
• Staphylococcus aureus drug effects   MeSH
• Models, Theoretical MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH