Spectroscopic Diagnosis Research Articles

Berry curvature in the photoelectron emission delay

Density fluctuation potential induced by a screening of the photohole scatters the photoelectron and generally causes its emission delay from the scattering matrix in the photoemission spectroscopy, where the photoemission delay usually quantifies the extrinsic loss of the photoelectron depending on the atomic orbital. Without the potential scattering, however, the photoemission from the coherent two-state mixture created by the laser driving is found to undergo the unexpected photoemission delay, which originates from the mixed photoemission matrix. Using the Haldane model, we analytically calculate such coherent mixing induced photoemission delay in an angle-resolved mode, which is found to reveal the local Berry curvature structure as long as the coherent mixing is sustained. This finding is confirmed through the streaking computation for the photoemission delay by solving the time-dependent Schrödinger equation and suggests that the photoemission delay be a new spectroscopic diagnosis of the material topology of two-dimensional semiconductors.

Emission Spectroscopic Diagnosis of 2-D Particle Distribution in Vacuum Arcs Under Different Currents

Emission Spectroscopic Diagnosis of 2-D Particle Distribution in Vacuum Arcs Under Different Currents

Spectroscopic diagnosis of nickel and zinc plasmas produced by plasma jet technique

Spectroscopic diagnosis of nickel and zinc plasmas produced by plasma jet technique

Spectroscopic diagnosis and metabolite characterization of cisplatin resistance regulated by FDFT1 in bladder cancer tissue

As is the case for most solid tumours, chemotherapy remains the backbone in the management of metastatic disease. However, the occurrence of chemotherapy resistance is a cause to worry, especially in bladder cancer. Extensive evidence indicates molecular changes in bladder cancer cells to be the underlying cause of chemotherapy resistance, including the reduced expression of farnesyl-diphosphate farnesyltransferase 1 (FDFT1) - a gene involved in cholesterol biosynthesis. This can likely be a hallmark in examining the resistance and sensitivity of chemotherapy drugs. This work performs spectroscopic analysis and metabolite characterization on resistant, sensitive, stable-disease and healthy bladder tissues. Raman spectroscopy has detected peaks at around 1003 cm−1 (squalene), 1178 cm−1 (cholesterol), 1258 cm−1 (cholesteryl ester), 1343 cm−1 (collagen), 1525 cm−1 (carotenoid), 1575 cm−1 (DNA bases) and 1608 cm−1 (cytosine). The peak parameters were examined, and statistical analysis was performed on the peak features, attaining significant differences between the sample groups. Small-angle x-ray scattering (SAXS) measurements observed the triglyceride peak together with 6th, 7th and 8th - order collagen peaks; peak parameters were also determined. Neutron activation analysis (NAA) detected seven trace elements. Carbon (Ca), magnesium (Mg), chlorine (Cl) and sodium (Na) have been found to have the greatest concentration in the sample groups, suggestive of a role as a biomarker for cisplatin resistance studies. Results from the present research are suggested to provide an important insight into understanding the development of drug resistance in bladder cancer, opening up the possibility of novel avenues for treatment through personalised interventions.

Spectroscopic diagnosis of plasma generated from platinum metal using the optical emission method

Spectroscopic diagnosis of plasma generated from platinum metal using the optical emission method

Impact of strong magnetization in cylindrical plasma implosions with applied B-field measured via x-ray emission spectroscopy

Magnetization is a key strategy for enhancing inertial fusion performance, though accurate characterization of magnetized dense plasmas is needed for a better comprehension of the underlying physics. Measured spectra from imploding Ar-doped D2-filled cylinders at the OMEGA laser show distinctive features with and without an imposed magnetic field. A multizone spectroscopic diagnosis leads to quantitative estimates of the plasma conditions, namely revealing a 50% core temperature rise at half mass density when a 30-T seed field is applied. Concurrently, experimental spectra align well with predictions from extended-magnetohydrodynamics simulations, providing strong evidence that the attained core conditions at peak compression are consistent with the impact of a 10-kT compressed field. These results pave the way for the validation of magnetized transport models in dense plasmas and for future magnetized laser implosion experiments at a larger scale. Published by the American Physical Society 2024

Metastasis diagnosis using attenuated total reflection-Fourier transform infra-red (ATR-FTIR) spectroscopy.

The suitability of Fourier transform infrared spectroscopy as a metastasis prognostic tool has not been reported for some cancer types. Our main aim was to show spectroscopic differences between live un-preprocessed cancer cells of different metastatic levels. Spectra of four cancer cell pairs, including colon cancer (SW480, SW620); human melanoma (WM115, WM266.4); murine melanoma (B16F01, B16F10); and breast cancer (MCF7, MDA-MB-231); each pair having the same genetic background, but different metastatic level were analyzed in the regions 1400-1700 cm-1 and 3100-3500 cm-1 using Principal Component Analysis, curve fitting, multifractal dimension and receiver operating characteristic (ROC) curves. The results show spectral markers I1540/I1473, I1652/I1473, [Formula: see text], and multifractal dimension of the spectral images are significantly different for the cells based on their metastatic levels. ROC curve analysis showed good diagnostic performance of the spectral markers in separating cells based on metastatic degree, with areas under the ROC curves having 95% confidence interval lower limits greater than 0.5 for most instances. These spectral features can be important in predicting the probability of metastasis in primary tumors, providing useful guidance for treatment planning. Our markers are effective in differentiating metastatic levels without sample fixation or drying and therefore could be compactible for future use in in-vivo procedures involving spectroscopic cancer diagnosis.

Distinctions in molecular composition of the dental biofilm in a dependence of method of exo/endogeneous caries prevention and cariogenic condition of a patient

Comparative study of changes in the secondary structure of dental biofilm proteins in people with cariesogenic and cariesoprotective status using synchrotron IR microspectroscopy. Dental biofilm samples from 50 patients without caries (group 1) and with carious lesions of tooth enamel (group 2) were studied. The molecular composition of biofilms was studied using IR microspectroscopy. Changes in the secondary structure of dental biofilm proteins were evaluated based on deconvolution of Amide I or Amide II amide bands. using the analysis of variance. Patients of both groups took tablets containing a mineral complex with calcium glycerophosphate. Based on the deconvolution of the IR spectral profile of the Amide I and Amide II bands, the changes occurring in the secondary structure of dental biofilm proteins have been studied. Using a large set of spectra, it was shown that the prediction of the secondary structure of the biofilm protein network is influenced by both the cariesogenic situation in the oral cavity (with initial carious lesions of the enamel) and the fact that patients use a modulator - calcium glycerophosphate (a tableted mineral complex with calcium glycerophosphate). Significant intra-group and intergroup differences in the secondary structure of dental biofilm proteins were established for patients in normal and carisogenic situations in the mouth, including after the use of a tableted mineral complex with calcium glycerophosphate. This allowed us to give a mathematical assessment of shifts in the secondary structure of proteins depending on the activity of caries and external modulation. The results obtained can form the basis of a technique for spectroscopic diagnosis of changes (shifts) in the oral microbiome leading to the development of the carious process, as well as become the basis for choosing the optimal therapeutic ways to treat enamel caries, including through preventive measures aimed at restoring the microflora of the patient's oral cavity.

Spectroscopic Diagnostics of Radiation Reabsorption in Dense He Arc Plasmas

Observing the light emission from plasmas spectroscopically allows for the determination of key plasma parameters like electron temperature, density and external field. This method, known as plasma spectroscopy, serves as a non-intrusive diagnostic tool to study plasma dynamics. However, overlooking the impact of radiation reabsorption in the typical analytic model may compromise the accuracy of observed plasma behavior. This study addresses the influence of radiation reabsorption on plasma spectroscopic diagnosis, focusing on linear divertor simulators and plasma spectrometers designed for high-density Large Helical Device (LHD) plasmas, where optical thickness cannot be disregarded. The discussion delves into understanding the effects of radiation reabsorption in these observations.

A prospective study: Advances in chaotic characteristics of serum Raman spectroscopy in the field of assisted diagnosis of disease

Chaos theory is an important branch of mathematics and its theory has been widely applied in many fields such as physics and medicine. Based on existing spectroscopic techniques, this paper used chaos theory as a research method for nonlinear time series to analyze Raman spectral time domain curves in order to improve the performance of disease diagnostic models and explore a new paradigm of spectroscopic technology for intelligent assisted disease diagnosis. We quantitatively identified the chaotic characteristics of time domain Raman spectra by three methods, extracted chaotic features such as correlation dimension and Kolmogorov entropy, and used the chaotic features as input to Extreme Learning Machine (ELM), Back Propagation Neural Network (BPNN), K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) to diagnose patients with lung cancer (LC), glioma, renal cell carcinoma (RCC) and esophageal cancer (EC). The Raman spectra were also analyzed by traditional spectral feature extraction & modelling method, and the results of traditional spectral feature extraction & modelling method and chaotic feature modelling method were compared. The experimental results showed that the extraction of effective chaotic features in the full spectral range could achieve comparable diagnostic results with the traditional spectral feature extraction & modelling method. To further validate the effectiveness of chaos theory in Raman spectral data, the full spectrum was divided into three consecutive subsequences of 500–1000, 1000–1500, and 1500–2000 cm−1, and the above experimental steps were repeated respectively, and the results of the traditional spectral feature extraction & modelling method and chaotic feature modelling were compared. The results showed that as the spectral range was split into consecutive subsequences, the diagnostic performance of the chaotic features in each subsequence performed better than that of conventional spectral analysis techniques. In this study, the technique bridges the gap in the application of chaotic signals to Raman spectroscopy techniques, focuses on global features in the time domain profile of Raman spectra, and demonstrates the significant value of chaos theory in artificial intelligence-assisted spectroscopic medical diagnosis.

Raman spectroscopic diagnosis of blast-induced traumatic brain injury in rats combined with machine learning

Blast-induced traumatic brain injury (bTBI) is a kind of nervous system disease, which results in a major health and economic problem to society. However, the rapid and label-free detection method with high sensitivity is still in great demand for the diagnosis of bTBI, especially for mild bTBI. In this paper, we report a new strategy for bTBI diagnosis through hippocampus and hypothalamus tissues based on Raman spectroscopy. The spectral characteristics of hippocampus and hypothalamus tissues of experimental bTBI in rats have been investigated for mild and moderate degrees at 3 h, 6 h, 24 h, 48 h, 72 h after blast exposure. The results show that the Raman spectra of mild and moderate bTBIs in 300–1700 cm−1 and 2800–3000 cm−1 regions exhibit significant differences at different time points compared with the control group. The main reason is the content change of proteins and lipids in hippocampus and hypothalamus tissues after bTBI. Moreover, four machine learning algorithms are used to automatically identify mild and moderate bTBIs at different time points (a total of 11 groups). The highest diagnostic accuracies are up to 95.3% and 88.5% based on Raman spectra of hippocampus and hypothalamus tissue, respectively. In addition, the classification performance of linear discriminant analysis classifier has been improved after data fusion. It is suggested that there has great potential as an alternative method for high-sensitive, rapid, label-free, economical diagnosis of bTBI.

Spectroscopic diagnosis and simulation analysis of tungsten cathode erosion during the start-up process for a magnetoplasmadynamic thruster

Measurement of tungsten density during the start-up process plays a vital role in monitoring real-time cathode mass loss in the study of plasma discharge instrument structure optimization. The relative intensity of the W II 239.71 nm spectral line, collected at the exit by the monochromator, is used to estimate the W II density in combination with the collision radiative model. The model of a small amount of tungsten in high-density plasma takes into account the main kinetic processes including the electron impact excitation process, electron impact de-excitation process, and electron impact ionization process. Additionally, A two-dimensional axisymmetric quasi-neutral fluid model, coupled with a thermal model of the cathode into a self-consistent model, is also constructed to analyze the mass loss mechanism of tungsten cathode during the start-up process. In the initial stage, the cold-state cathode has a large potential drop in the sheath region to accelerate the ion bombardment of the cathode for the requirement of electron emission, and a large number of tungsten atoms removal from the cathode surface due to sputtering and evaporation. In the steady-state operating phase, the primary reason for the mass loss of tungsten cathodes is attributed to thermal evaporation. Both experimental and simulation results indicate that the mass loss rate during the start-up phase is higher than that during steady-state operation phase by 1 to 2 orders of magnitude.

Serum-based Raman spectroscopic diagnosis of blast-induced brain injury in a rat model.

The diagnosis of blast-induced traumatic brain injury (bTBI) is of paramount importance for early care and clinical therapy. Therefore, the rapid diagnosis of bTBI is vital to the treatment and prognosis in clinic. In this paper, we reported a new strategy for label-free bTBI diagnosis through serum-based Raman spectroscopy. The Raman spectral characteristics of serum in rat were investigated at 3 h, 24 h, 48 h and 72 h after mild and moderate bTBIs. It has been demonstrated that both the position and intensity of Raman characteristic peaks exhibited apparent differences in the range of 800-3000cm-1 compared with control group. It could be inferred that the content, structure and interaction of biomolecules in the serum were changed after blast exposure, which might help to understand the neurological syndromes caused by bTBI. Furthermore, the control group, mild and moderate bTBIs at different times (a total of 9 groups) were automatically classified by combining principal component analysis and four machine learning algorithms (quadratic discriminant analysis, support vector machine, k-nearest neighbor, neural network). The highest classification accuracy, sensitivity and precision were up to 95.4%, 95.9% and 95.7%. It is suggested that this method has great potential for high-sensitive, rapid, and label-free diagnosis of bTBI.

Quantitative characterization of the temporal-spatial evolution of RONS in air surface micro-discharge using UV–VIS optical absorption spectroscopic diagnosis and modeling approach

The research of the chemically active species of cold atmospheric pressure plasmas is a essential step for a more in-depth comprehension of the effects of its interaction with the target. In this paper, the temporal and spatial evolution of key species O3, NO2 and NO3 produced by surface micro-discharge in air were investigated. UV–VIS optical absorption spectroscopy at 254 nm, 400 nm and 662 nm were used to measure the concentrations of O3, NO2 and NO3, respectively. The results show that the temporal evolution of O3, NO2 and NO3 are revealed a significant correlation with the surface power density (SPD). The phenomenon of O3 and NO3 quenching occur once the SPD overcomes a critical value of 0.15 W cm−2. An O3-enriched atmosphere (peak concentration around 3000 ppm) is formed when the SPD is below the critical value, and a NO2-enriched atmosphere (maximum NO2 density around 600 ppm) is formed at higher SPD. In addition, the concentration distribution of O3, NO2 and NO3 in the chamber ranging from 10–100 mm of the downstream of the mesh electrode tends to be uniform. Finally, a zero-dimensional model of the afterglow chemistry, validated using the experimental measurements, is developed to determined important reactions affecting O3, NO2 and NO3 respectively, and obtain insight into the evolutionary behavior of the considered reactive species.

Spectroscopic Diagnosis of Cobalt Plasma Produced by OES Technique and Influence of Applied Voltage on Plasma Parameters

In this work, plasma system that operates at vacuum was designed and built using a sheet of cobalt metal for the purpose of diagnosing plasma and measuring its parameters, as it is very important to know the processes that accompany plasma generation and are closely related to them, including the electron density in the plasma and its temperature. The spectroscopic diagnosis was done by optical emission spectroscopy (OES) which relies on the calculation of the optical radiation emitted by the plasma to describe plasma parameters in the chemical, molecular, and ionic radiator's near environment, and applied to cobalt metal at vacuum D.C high voltage power supply. The results showed the rise of spectral lines intensity with increasing the applied voltage. The maximum peak of argon gas (ArI) was at the wavelength (811.5311) nm and the maximum peak of cobalt metal (CoI) was at the wavelength of 242 nm, where argon gas was used at the fifth flow per minute with variable voltages (13-21) kV. The results also achieved that the values ​​of electron temperature rises from (0.2708-0.6649) eV with the increase in the applied voltage, as well as the electron density from (8.108-13.851)x1017cm-3 with the stability of the argon gas flow rate at 5 l/min. The length of the plasma was measured at different gas flow rates (1-5) l/min and different applied voltages (13-21) kV that were used in this diagnosis.

Study the Impact of Laser Energy on Laser-Induced Copper Plasma Parameters By Spectroscopic Analysis Technique

In this paper, spectroscopic analysis (OES) for copper (Cu) plasma was achieved at atmospheric pressure. Q switched Nd: YAG pulsed laser with a fundamental wavelength (1064 nm), energy range (500-800) mJ, frequency (6 Hz), and laser pulses (10-30 pulses) was applied to induce copper plasma. Based on the spectroscopic analysis, plasma parameters like electron temperature (Te), electron density (ne), Debye length (λD), and plasma frequency (fp) have been calculated. The results demonstrated that the laser energy affects all plasma parameters, with an electron temperature (Te) range of (0.6820-0.8949) eV and electron number density (ne) range of (13.667-17.235)×1017 cm−3. Also, the image of the place of laser bombardment of copper (Cu) metal shows three diameters or circles, each circle bears a different color from the other. It can be described as a crater, and the interaction of the laser with copper metal is obvious by laser ablation, and here the effect of the increased energy of the laser appears during the spectroscopic diagnosis and the process of metal bombardment.

Mechanochemical Synthesis of RuCo/MgTiO3 Catalysts for Nonthermal Plasma-Assisted Ammonia Synthesis

The development of robust yet effective catalysts is vital for promoting nonthermal plasma (NTP)-assisted ammonia (NH3) synthesis toward practical applications. Herein, we report a simple mechanochemical synthesis method (via ball milling) for preparing bimetallic RuCo supported on MgTiO3 catalyst (i.e., RuCo/MgTiO3-6-500) to be used in NTP-assisted catalytic NH3 synthesis. The physicochemical properties of the developed catalysts were investigated systematically with respect to the relevant process parameters of ball milling. Catalytic tests showed that, at a low specific energy input of 15 kJ L–1, the developed RuCo/MgTiO3-6-500 catalyst exhibited a high NH3 synthesis rate and an energy efficiency of ∼50 μmol min–1 gcat–1 and 1.54 gNH3kWh–1, respectively, which outperformed the monometallic Ru or Co control catalysts. Additionally, the energy barriers were calculated as a function of N2/H2 ratio for the NTP-catalytic NH3 synthesis over RuCo/MgTiO3-6-500, and the results were interpreted together with the activity data measured during the catalysis. It was found that the energy barrier approach may not be appropriate for discussing the energy required for the dynamics of interest in the NTP-catalytic system. Compared to MgTiO3-packed and plasma-alone systems, results by in situ optical emission spectroscopic (OES) diagnosis of the plasma-catalytic systems showed that the presence of active metal sites (i.e., Ru and/or Co) could intensify the activation and dissociation rates of N2 and H2 molecules, showing the relatively higher peak intensity of NH, N2*, N2+, and Hα species. However, based on the obtained information, the possible roles of Ru and/or Co in NTP-assisted ammonia synthesis system are difficult to be identified.

1040 Metabolite Quantification and Entity and Grade Characterisation of Gliomas via Single-Voxel Spectroscopy for Pre-Operative Radiological Diagnosis

Abstract Aim Brain tumours pose a diagnostic challenge, but single-voxel spectroscopy (SVS) provides a non-invasive tool to quantify brain metabolite variations reflective of neoplasia, such as NAA, choline (Cho), creatinine (Cr), lipids (Lip) and lactate (Lac). Inconsistency in spectroscopic research and time-patient pressures emphasises the need for reviewing SVS characterisation of gliomas for peri-operative decision-making. Method A single-centre, retrospective, observational study, including 93 SVS meaningfully interpretable examinations between 2012 and 2018 (PRESS, TE=35ms, 144ms). Spectroscopic diagnoses were compared to histopathologic reports for overall, entity and grade accuracy analysis. Metabolite ratios to Cr were recorded or obtained from peak area integrals. Results High accuracy of lesions discrimination was observed (83–98%). Significant metabolite variation for Cho/Cr (p=0.021) and Cho/NAA (p=0.013) was observed across grades (WHO Grade I-IV). Spectra of astrocytomas and oligodendrogliomas (grade II) were similarly characterised by high Cho, decreased NAA and Cr, and small-to-moderate Lac-Lip and mIns. In contrast, grade III anaplastic oligodendrogliomas (AO) were distinguished from anaplastic astrocytomas (AA) thanks to smaller Lac-Lip and mIns/Cr. Finally, glioblastoma multiforme (GBM, grade IV) displayed high Cho, decreased Cr, the lowest or virtually absent NAA, and the highest Lac-Lip. High-grade spectroscopy, such as enhanced Lac or Lac-Lip, may be an early indicator of grade transformation prior to reflection in histopathology in tumours, which were follow up prospectively. Conclusion This study enhanced spectral characterisation of gliomas and discrimination amongst low- and high-grade gliomas. Whilst these aid pre-operative radiological diagnoses, further research is required to investigate spectroscopy predictive of tumour genetics, now necessary for diagnosis.

Diagnostic Tools for Rapid Screening and Detection of SARS-CoV-2 Infection.

The novel coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has severely impacted human health and the health management system globally. The ongoing pandemic has required the development of more effective diagnostic strategies for restricting deadly disease. For appropriate disease management, accurate and rapid screening and isolation of the affected population is an efficient means of containment and the decimation of the disease. Therefore, considerable efforts are being directed toward the development of rapid and robust diagnostic techniques for respiratory infections, including SARS-CoV-2. In this article, we have summarized the origin, transmission, and various diagnostic techniques utilized for the detection of the SARS-CoV-2 virus. These higher-end techniques can also detect the virus copy number in asymptomatic samples. Furthermore, emerging rapid, cost-effective, and point-of-care diagnostic devices capable of large-scale population screening for COVID-19 are discussed. Finally, some breakthrough developments based on spectroscopic diagnosis that could revolutionize the field of rapid diagnosis are discussed.

Defect-induced excitonic traps and nonlinear visible photoluminescence: a multiphoton spectroscopic diagnosis

Defect-induced excitonic traps and nonlinear visible photoluminescence: a multiphoton spectroscopic diagnosis