A noninvasive, in vivo technique to quantitatively measure water concentration of the stratum corneum using attenuated total-reflectance infrared spectroscopy

1985 ◽  
Vol 277 (6) ◽  
pp. 489-495 ◽  
Author(s):  
R. O. Potts ◽  
D. B. Guzek ◽  
R. R. Harris ◽  
J. E. McKie
Keyword(s):  
Infrared Spectroscopy ◽  
Stratum Corneum ◽  
Water Concentration ◽  
Attenuated Total Reflectance ◽  
Total Reflectance

Quick determination and discrimination of commercial hand sanitisers using attenuated total reflectance-Fourier transform infrared spectroscopy and chemometrics

2021 ◽  
Vol 13 (13) ◽  
pp. 1601-1611
Author(s):  
Way Koon Teoh ◽  
Noor Zuhartini Md Muslim ◽  
Md Lukmi Ismail ◽  
Kah Haw Chang ◽  
Ahmad Fahmi Lim Abdullah
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Fourier Transform Infrared Spectroscopy ◽  
Fourier Transform Infrared ◽  
Attenuated Total Reflectance ◽  
Forensic Investigation ◽  
Total Reflectance ◽  
Quick Determination

Quick determination and discrimination of commercial hand sanitisers for forensic investigation.

Discrimination of clinically relevant Candida species by Fourier-transform infrared spectroscopy with attenuated total reflectance (FTIR-ATR)

RSC Advances ◽  
2016 ◽  
Vol 6 (94) ◽  
pp. 92065-92072 ◽  
Author(s):  
Sónia Silva ◽  
Flávia Tobaldini-Valerio ◽  
Sofia Costa-de-Oliveira ◽  
Mariana Henriques ◽  
Joana Azeredo ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Fourier Transform Infrared Spectroscopy ◽  
Species Identification ◽  
Candida Species ◽  
Fourier Transform Infrared ◽  
Attenuated Total Reflectance ◽  
Total Reflectance ◽  
Reflectance Ftir

Accurate Candida species identification remains a challenge due to their phenotypic and genotypic similarity.

scholarly journals Infrared Fiber-Optic Spectroscopy Detects Bovine Articular Cartilage Degeneration

Cartilage ◽  
2021 ◽  
pp. 194760352199322
Author(s):  
Vesa Virtanen ◽  
Ervin Nippolainen ◽  
Rubina Shaikh ◽  
Isaac O. Afara ◽  
Juha Töyräs ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Infrared Spectroscopy ◽  
Articular Cartilage ◽  
Fiber Optic ◽  
Mechanical Damage ◽  
Attenuated Total Reflectance ◽  
Support Vector ◽  
Mid Infrared ◽  
Total Reflectance ◽  
Joint Injuries

Objective Joint injuries may lead to degeneration of cartilage tissue and initiate development of posttraumatic osteoarthritis. Arthroscopic surgeries can be used to treat joint injuries, but arthroscopic evaluation of articular cartilage quality is subjective. Fourier transform infrared spectroscopy combined with fiber optics and attenuated total reflectance crystal could be used for the assessment of tissue quality during arthroscopy. We hypothesize that fiber-optic mid-infrared spectroscopy can detect enzymatically and mechanically induced damage similar to changes occurring during progression of osteoarthritis. Design Bovine patellar cartilage plugs were extracted and degraded enzymatically and mechanically. Adjacent untreated samples were utilized as controls. Enzymatic degradation was done using collagenase and trypsin enzymes. Mechanical damage was induced by (1) dropping a weight impactor on the cartilage plugs and (2) abrading the cartilage surface with a rotating sandpaper. Fiber-optic mid-infrared spectroscopic measurements were conducted before and after treatments, and spectral changes were assessed with random forest, partial least squares discriminant analysis, and support vector machine classifiers. Results All models had excellent classification performance for detecting the different enzymatic and mechanical damage on cartilage matrix. Random forest models achieved accuracies between 90.3% and 77.8%, while partial least squares model accuracies ranged from 95.8% to 84.7%, and support vector machine accuracies from 91.7% to 80.6%. Conclusions The results suggest that fiber-optic Fourier transform infrared spectroscopy attenuated total reflectance spectroscopy is a viable way to detect minor and major degeneration of articular cartilage. Objective measures provided by fiber-optic spectroscopic methods could improve arthroscopic evaluation of cartilage damage.

Detecting antimicrobial resistance in Escherichia coli using benchtop attenuated total reflectance-Fourier transform infrared spectroscopy and machine learning

The Analyst ◽  
2021 ◽  
Vol 146 (20) ◽  
pp. 6211-6219
Author(s):  
Hewa G. S. Wijesinghe ◽  
Dominic J. Hare ◽  
Ahmed Mohamed ◽  
Alok K. Shah ◽  
Patrick N. A. Harris ◽  
...  
Keyword(s):  
Machine Learning ◽  
Escherichia Coli ◽  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Antimicrobial Resistance ◽  
Fourier Transform Infrared Spectroscopy ◽  
Attenuated Total Reflectance ◽  
Total Reflectance ◽  
E Coli ◽  
Machine Learning Model

ATR–FTIR with a machine learning model predicts ESBL genotype of unknown E. coli strains with 86.5% AUC.

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