Articles you may be interested inUltrafast exciton dynamics in free standing 200 nm thin tetracene single crystals were studied at room temperature by femtosecond transient absorption spectroscopy in the visible spectral range. The complex spectrally overlapping transient absorption traces of single crystals were systematically deconvoluted. From this, the ultrafast dynamics of the ground, excited, and transition states were identified including singlet exciton fission into two triplet excitons. Fission is generated through both, direct fission of higher singlet states S n on a sub-picosecond timescale, and thermally activated fission of the singlet exciton S 1 on a 40 ps timescale. The high energy Davydov component of the S 1 exciton is proposed to undergo fission on a sub-picoseconds timescale. At high density of triplet excitons their mutual annihilation (triplet-triplet annihilation) occurs on a <10 ps timescale.
Diabetes is an irreversible condition characterized by elevated blood glucose levels. Currently, there are no predictive biomarkers for this disease and the existing ones such as hemoglobin A1c and fasting blood glucose are used only when diabetes symptoms are noticed. The objective of this work was first to explore the potential of leucine and isoleucine amino acids as diabetes type 2 biomarkers using their Raman spectroscopic signatures. Secondly, we wanted to explore whether Raman spectroscopy can be applied in comparative efficacy studies between commercially available anti-diabetic drug pioglitazone and the locally used anti-diabetic herbal extract Momordica spinosa (Gilg.)Chiov. Sprague Dawley (SD) rat’s blood was used and were pipetted onto Raman substrates prepared from conductive silver paste smeared glass slides. Prominent Raman bands associated with glucose (926, 1302, 1125 cm−1), leucine (1106, 1248, 1302, 1395 cm−1) and isolecucine (1108, 1248, 1437 and 1585 cm−1) were observed. The Raman bands centered at 1125 cm−1, 1395 cm−1 and 1437 cm−1 associated respectively to glucose, leucine and isoleucine were chosen as biomarker Raman peaks for diabetes type 2. These Raman bands displayed decreased intensities in blood from diabetic SD rats administered antidiabetic drugs pioglitazone and herbal extract Momordica spinosa (Gilg.)Chiov. The intensity decrease indicated reduced concentration levels of the respective biomarker molecules: glucose (1125 cm−1), leucine (1395 cm−1) and isoleucine (1437 cm−1) in blood. The results displayed the power and potential of Raman spectroscopy in rapid (10 seconds) diabetes and pre-diabetes screening in blood (human or rat’s) with not only glucose acting as a biomarker but also leucine and isoleucine amino-acids where intensities of respectively assigned bands act as references. It also showed that using Raman spectroscopic signatures of the chosen biomarkers, the method can be an alternative for performing comparative efficacy studies between known and new anti-diabetic drugs. Reports on use of Raman spectroscopy in type 2 diabetes mellitus screening with Raman bands associated with leucine and isoleucine molecules acting as reference is rare in literature. The use of Raman spectroscopy in pre-diabetes screening of blood for changes in levels of leucine and isoleucine amino acids is particularly interesting as once elevated levels are noticed, necessary interventions to prevent diabetes development can be initiated.
We report on application of conductive silver paste smeared glass slides as Raman spectroscopy sample substrates for label-free detection of HIV-1 p24 antigen in blood plasma. We also show that the same substrates can be applied in Raman spectroscopic screening of blood plasma for presence of HIV. The characteristic Raman spectrum of HIV-1 p24 antigen displayed prominent bands that were assigned to ribonucleic acids (RNA) and proteins that constitute the antigen. This spectrum can be used as reference during Raman spectroscopic screening for HIV in plasma within the first few days after exposure (<7 days). The Raman spectra obtained from HIV+ plasma displayed unique peaks centered at wavenumbers 928, 990, 1270, 1397, and 1446 cm attributed to the Raman active vibrations in the virion carbohydrates, lipids, and proteins. Other bands similar to those reported in literature were also seen and assignments made. The attachment of the HIV virions to silver nanoparticles via gp120 glycoprotein knobs was thought to be responsible for the enhanced Raman signals of proteins associated with the virus. The principal component analysis (PCA) applied on the combined spectral data showed that HIV- and HIV+ spectra had differing spectral patterns. This indicated the great power of Raman spectroscopy in HIV detection when plasma samples are deposited onto silver paste smeared glass substrates. The Raman peaks responsible for the segregation of the spectral data in PCA were mainly those assigned to the viral proteins (645, 725, 813, 1270, and 1658 cm). Excellent results were obtained from Artificial Neural Network (ANN) applied on the HIV+ Raman spectral data around the prominent peak centered at 1270 cm with R (coefficient of correlation) and R (coefficient of determination) values of 0.9958 and 0.9895, respectively. The method has the potential of being used as quick blood screening for HIV before blood transfusion with the Raman peaks assigned to the virion proteins acting as reference. Graphical Abstract The HIV type 1 virus particle gets attached to the silver nanoparticle contained in the conductive silver paste smear onto a glass slide. This results in strong Raman signals associated with the components of the virion. The signals are collected, dispersed in a spectrometer and displayed on a computer screen. Method can be used as a label-free and rapid HIV screening in blood plasma.
Most HIV viral load determination techniques available commercially are anchored on direct measurements of either HIV ribonucleic acid (RNA), provirus DNA, or viral antigen. Such techniques often require expensive reagents which makes the process expensive. This study reported the feasibility of label‐free determination of HIV‐1 viral load in plasma based on the consequence of the virus in the components of plasma. The study aimed to provide a relatively cheap and faster HIV‐1 detection and further estimate the concentration of the virus without using any reagent. We subjected 22 HIV‐1‐infected human plasma samples to Raman peak height evaluation to develop a detection and concentration estimation model for HIV‐1. Simultaneously, all the samples were examined for HIV‐1 infection using qualitative polymerase chain reaction (PCR) test. The positive samples were further subjected to quantitative PCR to determine their corresponding viral load. Principal component analysis (PCA) and artificial neural network (ANN) were employed in Raman spectral analysis to enhance label‐free detection of the HIV‐1 in plasma. The quantification model results for HIV‐1 yielded a good correlation with those obtained by the reference quantitative PCR method. HIV‐1 viral load estimation based on the associated Raman spectral peaks centered at 1,270 and 1,446 cm−1 achieved a clinically accepted coefficient of determination (R2 > 0.9). The viral detection sensitivity from the two associated peaks were 95 and 100 copies of the virus per milliliter of plasma, respectively, hence showing that the Raman‐based model can be a potential HIV‐1 diagnostic and viral load estimation tool.
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