Quality Of Spectra Research Articles

Analysis of automotive paint layers on plastic substrates using chemical imaging μ-FTIR and O-PTIR microspectroscopy.

Automobile paint chips are a crucial piece of trace evidence for forensic investigators. This is because automotive paints are composed of multiple layers, including the primer, basecoat, and clearcoat, each of which has its own chemical composition that can vary by vehicle make, model, year, and manufacturing plant. Thus, Fourier-transform infrared (FTIR) spectral databases for automobile paint systems have been established to aid law enforcement in, for example, narrowing search parameters for a suspect's vehicle. Recently, car manufacturers have implemented primers on plastic substrates that are much thinner (~5 μm) than those on metal substrates, making it more difficult to manually separate for analyses. Here, we evaluated FTIR microspectroscopy (μ-FTIR) and optical photothermal infrared spectroscopy (O-PTIR) to chemically image cross sections of paint chips without manually separating the layers. For μ-FTIR, transmission and transflection modes provided the highest quality spectra compared to reflection and μ-ATR analyses. Point analysis was preferable to chemical imaging, as peaks were identified in the point (MCT) detector's lower spectral range that was below the imaging (FPA) detector's cutoff, such as those associated with titanium dioxide. Reduced spectral range can lead to a similar issue in O-PTIR analyses depending on instrument configuration. However, its complementary Raman spectra showed strong titanium dioxide peaks, providing an alternate means of identification. Both techniques are likely to become more relevant as they are non-destructive and avoid manual separation of the layers. O-PTIR is particularly well-suited for analysis of the thin primer layer due to its superior spatial resolution.

Electron-Activated Dissociation and Collision-Induced Dissociation Glycopeptide Fragmentation for Improved Glycoproteomics.

Tandem mass spectrometry coupled with liquid chromatography (LC-MS/MS) has proven a versatile tool for the identification and quantification of proteins and their post-translational modifications (PTMs). Protein glycosylation is a critical PTM for the stability and biological function of many proteins, but full characterization of site-specific glycosylation of proteins remains analytically challenging. Collision-induced dissociation (CID) is the most common fragmentation method used in LC-MS/MS workflows, but the loss of labile modifications renders CID inappropriate for detailed characterization of site-specific glycosylation. Electron-based dissociation methods provide alternatives that retain intact glycopeptide fragments for unambiguous site localization, but these methods often underperform CID due to increased reaction times and reduced efficiency. Electron-activated dissociation (EAD) is another strategy for glycopeptide fragmentation. Here, we use a ZenoTOF 7600 SCIEX instrument to compare the performance of various fragmentation techniques for the analysis of a complex mixture of mammalian O- and N-glycopeptides. We found CID fragmentation identified the most glycopeptides and generally produced higher quality spectra, but EAD provided improved confidence in glycosylation site localization. Supplementing EAD with CID fragmentation (EAciD) further increased the number and quality of glycopeptide identifications, while retaining localization confidence. These methods will be useful for glycoproteomics workflows for either optimal glycopeptide identification or characterization.

Indirect 1H-[13C] MRS of the human brain at 7 T using a 13C-birdcage coil and eight transmit-receive 1H-dipole antennas with a 32-channel 1H-receive array.

The neuronal tricarboxylic acid and glutamate/glutamine (Glu/Gln) cycles play important roles in brain function. These processes can be measured in vivo using dynamic 1H-[13C] MRS during administration of 13C-labeled glucose. Proton-observed carbon-edited (POCE) MRS enhances the signal-to-noise ratio (SNR) compared with direct 13C-MRS. Ultra-high field further boosts the SNR and increases spectral dispersion; however, even at 7 T, Glu and Gln 1H-resonances may overlap. Further gain can be obtained with selective POCE (selPOCE). Our aim was to create a setup for indirect dynamic 1H-[13C] MRS in the human brain at 7 T. A home-built non-shielded transmit-receive 13C-birdcage head coil with eight transmit-receive 1H-dipole antennas was used together with a 32-channel 1H-receive array. Electromagnetic simulations were carried out to ensure that acquisitions remained within local and global head SAR limits. POCE-MRS was performed using slice-selective excitation with semi-localization by adiabatic selective refocusing (sLASER) and stimulated echo acquisition mode (STEAM) localization, and selPOCE-MRS using STEAM. Sequences were tested in a phantom containing non-enriched Glu and Gln, and in three healthy volunteers during uniformly labeled 13C-glucose infusions. In one subject the voxel position was alternated between bi-frontal and bi-occipital placement within one session. [4-13C]Glu-H4 and [4-13C]Gln-H4 signals could be separately detected using both STEAM-POCE and STEAM-selPOCE in the phantom. In vivo, [4,5-13C]Glx could be detected using both sLASER-POCE and STEAM-POCE, with similar sensitivities, but [4,5-13C]Glu and [4,5-13C]Gln signals could not be completely resolved. STEAM-POCE was alternately performed bi-frontal and bi-occipital within a single session without repositioning of the subject, yielding similar results. With STEAM-selPOCE, [4,5-13C]Glu and [4,5-13C]Gln could be clearly separated. We have shown that with our setup indirect dynamic 1H-[13C] MRS at 7 T is feasible in different locations in the brain within one session, and by using STEAM-selPOCE it is possible to separate Glu from Gln in vivo while obtaining high quality spectra.

Labeling of methyl groups: a streamlined protocol and guidance for the selection of 2H precursors based on molecular weight.

A streamlined one-day protocol is described to produce isotopically methyl-labeled protein with high levels of deuterium for NMR studies. Using this protocol, the D2O and 2H-glucose content of the media and protonation level of ILV labeling precursors (ketobutyrate and ketovalerate) were varied. The relaxation rate of the multiple-quantum (MQ) state that is present during the HMQC-TROSY pulse sequence was measured for different labeling schemes and this rate was used to predict upper limits of molecular weights for various labeling schemes. The use of deuterated solvents (D2O) or deuterated glucose is not required to obtain 1H-13C correlated NMR spectra of a 50kDa homodimeric protein that are suitable for assignment by mutagenesis. High quality spectra of 100-150kDa proteins, suitable for most applications, can be obtained without the use of deuterated glucose. The proton on the β-position of ketovalerate appears to undergo partial exchange with deuterium under the growth conditions used in this study.

Exploring the Performance of Linear and Nonlinear Models of Time-of-Flight Secondary Ion Mass Spectrometry Spectra.

Multivariate statistical tools and machine learning (ML) techniques can deconvolute hyperspectral data and control the disparity between the number of samples and features in materials science. Nevertheless, the importance of generating sufficient high-quality sample replicates in training data cannot be overlooked, as it fundamentally affects the performance of ML models. Here, we present a quantitative analysis of time-of-flight secondary ion mass spectrometry (ToF-SIMS) spectra of a simple microarray system of two food dyes using partial least-squares (PLS, linear) and random forest (RF, nonlinear) algorithms. This microarray was generated by a high-throughput sample preparation and analysis workflow for fast and efficient acquisition of quality and reproducible spectra via ToF-SIMS. We drew insights from the bias-variance trade-off, investigated the performances of PLS and RF regression models as a function of training data size, and inferred the amount of data needed to construct accurate and reliable regression models. In addition, we found that the spectral concatenation of positive and negative ToF-SIMS spectra improved the model performances. This study provides an empirical basis for future design of high-throughput microarrays and multicomponent systems, for the purpose of analysis with ToF-SIMS and ML.

XPS guide for insulators: Electron flood gun operation and optimization, surface charging, controlled charging, differential charging, useful FWHMs, problems and solutions, and advice

Current day x-ray photoelectron spectroscopy (XPS) instrument makers have made significant advances in charge compensation systems over the last 20 years, which makes it easier to analyze insulators, but samples still have many differences in chemistry, dielectric properties, sizes, surface roughness, etc. that force instrument operators to tweak flood gun settings if they want or need to obtain high quality chemical state spectra that provide the most information. This guide teaches which flood gun variables to check, and how to optimize electron flood gun settings by presenting high energy resolution, chemical state spectra that show the result of using a poorly aligned flood gun on modern XPS instruments equipped with a monochromatic aluminum Kalpha x-ray source. This guide is focused on the XPS measurement of insulators—nonconductive metal oxides and polymers. This guide shows that by measuring commonly available polymers (polypropylene and polyethylene terephthalate) or ceramic materials (SiO2 and Al2O3), the operator can easily characterize the good and bad effects of XY position settings and other settings provided by modern electron flood gun systems. This guide includes many original, never-before-published XPS peak full width at half maximum (FWHM) that will greatly assist peak-fitting efforts. This guide reveals a direct correlation between electron count-rate and best charge-control settings. This guide discusses sample and instrument issues that affect surface charging and explains how to check the quality of charge control by measuring the FWHM and binding energy of C (1s) or O (1s) spectra produced from the sample currently being analyzed. A list of other charge-control methods is provided, along with advice and a best-known method. The availability of large extensive databases of actual spectra is extremely beneficial to users who need real-world examples of high quality chemical state spectra to guide their in-house efforts to collect high quality spectra and to interpret valuable information from the peak-fits of those spectra.

Triboelectric Nanogenerators for the Masses: A Low-Cost Do-It-Yourself Pulsed Ion Source for Sample-Limited Applications.

Triboelectric nanogenerators (TENG) are useful devices for converting mechanical motion into electric current using readily available materials. Though the applications for these devices span across many fields, TENG can be leveraged for mass spectrometry (MS) as inexpensive and effective power supplies for pulsed nanoelectrospray ionization (nESI). The inherently discontinuous spray provided by TENG is particularly useful in scenarios where high sample economy is imperative, as in the case of ultraprecious samples. Previous work has shown the utility of TENG MS as a highly sensitive technique capable of yielding quality spectra from only a few microliters of sample at low micromolar concentrations. As the field of miniaturized, fieldable mass spectrometers grows, it remains critical to develop advanced ion sources with similarly small power requirements and footprints. Here, we present a redesigned TENG ion source with a sub-1000 USD material cost, lower power consumption, reduced footprint, and improved capabilities. We validate the performance of this new device for a diverse set of applications, including lipid double bond localization and native protein analysis.

A delayed decoupling methyl-TROSY pulse sequence for atomic resolution studies of folded proteins and RNAs in condensates

Solution NMR spectroscopy has tremendous potential for providing atomic resolution insights into the interactions between proteins and nucleic acids partitioned into condensed phases of phase-separated systems. However, the highly viscous nature of the condensed phase challenges applications, and in particular, the extraction of quantitative, site-specific information. Here, we present a delayed decoupling-based HMQC pulse sequence for methyl-TROSY studies of ‘client’ proteins and nucleic acids partitioned into ‘scaffold’ proteinaceous phase-separated solvents. High sensitivity and excellent quality spectra are recorded of a nascent form of superoxide dismutase and of a small RNA fragment partitioned into CAPRIN1 condensates.

A frequency-Hankel transform method to extract multimodal Rayleigh wave dispersion spectra from active and passive source surface wave data

Rayleigh wave dispersion energy spectra have been widely used to extract dispersion curves and invert underground S-wave velocity structures for engineering geophysics and seismology. We develop a frequency-Hankel (F-H) transform method to extract high-quality multimodal Rayleigh wave dispersion energy spectra from active and passive source Rayleigh wave data. The F-H transform method is inspired by the frequency-Bessel (F-J) transform method and considers the physical meaning of Green’s functions for Rayleigh wave dispersion analysis. The F-H transform method can naturally avoid crossed artifacts caused by converging waves on F-J spectrograms and obtain more multimodal dispersion spectra of the same quality with fewer Rayleigh wave data than the F-J transform method. Synthetic and field Rayleigh wave data from active and passive sources for near-surface exploration and ambient noise tomography are used to demonstrate the validity, accuracy, and applicability of the F-H transform method. The F-H transform method unifies the formulas of the F-J transform method and its modifications for active and passive sources of Rayleigh wave data. The F-H transform method is a robust and efficient multimodal Rayleigh wave dispersion analysis method for active and passive source Rayleigh wave data.

Developing a compact coal quality rapid detection integrated machine based on laser‐induced breakdown spectroscopy

AbstractCoal's calorific value and carbon content are crucial in calculating carbon emissions. Accurately detecting these two indicators is of great significance for carbon accounting. In this study, we developed a compact coal quality rapid detection integrated machine based on laser‐induced breakdown spectroscopy (LIBS), which can directly measure coal particle flow. A partial least squares model, based on data set selection according to cluster analysis results, was applied to establish the relationship between coal quality and plasma spectra. The R2 of the calorific value is .93, the root mean square error of prediction (RMSEP) is 0.41 MJ/kg, and the mean absolute error (MAE) is 0.33 MJ/kg. The R2 of carbon content is .94, the RMSEP is 0.97%, and the MAE is 0.91%. These results indicated that the developed compact coal quality rapid detection integrated machine could conduct precise coal quality analysis in real time.

Measuring black hole spins through X-ray reflection spectroscopy and the relativistic precession model: the case of XTE J1859+226

ABSTRACT The development of techniques to measure accurately black hole spins is crucial to study the physics and astrophysics of these objects. X-ray reflection spectroscopy is currently the most popular method to estimate the spins of accreting black holes; so far it has provided a spin measurement of about 40 stellar-mass black holes in X-ray binaries and 40 supermassive black holes in active galactic nuclei. The relativistic precession model (RPM) is another method to measure the spins of stellar-mass black holes: it requires the measurement of the frequencies of three simultaneous quasi-periodic oscillations and can potentially provide precise estimates of the black hole mass and spin. However, the two methods do not seem to provide consistent results when applied to the same sources, which questions the reliability and accuracy of these measurements. Recently, the RPM has been applied to infer the spin of the black hole in XTE J1859+226. The authors found a* = 0.149 ± 0.005 (68 per cent CL). There are no other spin measurements of this source. We looked for archived RXTE observations of XTE J1859+226 with blurred reflection features and found 23 spectra suitable for measuring the spin. We employed two different models with relxill and relxillD and obtained a higher spin value from all these fits. From simultaneous fitting of seven spectra of higher quality, we found $a_* = 0.986^{+0.001}_{-0.004}$ and a* = 0.987 ± 0.003 (90 per cent CL, statistical) with relxill and relxillD, respectively. Our results confirm the discrepancy between the spin measurements inferred from the two techniques.

Dwarfs in nearby voids: results of SALT spectroscopy

ABSTRACT In the framework of the ongoing project, aimed at the systematical studying galaxies in nearby voids, we conducted spectroscopy with the Southern African Large Telescope (SALT) of 62 objects from the Nearby Void Galaxy (NVG) sample. They include 8 remaining objects of the 60 pre-selected candidates to eXtremely Metal-Poor (XMP) dwarfs, two known void XMP dwarfs and 52 void dwarfs residing within the Local Volume. For 47 galaxies residing in the nearby voids, we obtained spectra of the diverse quality. For 42 of them, we detected the Hydrogen and Oxygen lines that allowed us to get estimates of O/H in the observed H ii regions. For 12 of the 42 objects, we detected the faint line [O iii]λ4363, that allowed us to directly derive the electron temperature Te and obtain their gas O/H by the direct method. 14 objects with the undetected [O iii]λ4363 line fall to the lowest metallicities range (12+log(O/H) ≲ 7.5 dex). For them, we use a carefully checked new empirical ‘Strong line’ method of Izotov et al. For 14 other objects with only strong lines detected and with 12+log(O/H) of ∼7.5–8.0 dex, we used the modified version of ‘semi-empirical’ method of Izotov and Thuan. It accounts for effect of the excitation parameter O32 on Te. 16 new galaxies are found with parameter 12+log(O/H) ≲ 7.39 dex. Of them, four have 12+log(O/H) = 7.07–7.20 dex. Of the 60 observed NVG objects, 15 have mistaken radial velocities in HyperLEDA. They do not reside in the nearby voids.

Lentil grain quality and segregation opportunities in‐field using remote sensing

AbstractFor broad‐acre crops grown in Mediterranean‐type environments, variation in lentil (Lens culinaris) yield and quality occurs due to seasonal abiotic and biotic stresses. Because grain quality affects the price paid to growers, in‐season assessment of likely final quality using remote sensing technologies could limit economic losses by informing spatial management at harvest. For a survey of lentil crops grown in southern Australia, in 2019 and 2020, Moran's I analysis identified significant field spatial autocorrelation for the grain quality traits of grain protein concentration (GPC), grain size, and grain brightness (CIE L*, where CIE is International Commission on Illumination), indicating an opportunity for zoning at harvest. Partial least squares calibration models of observed grain quality and proximal reflectance spectra were successfully derived for grain weight (R2 = 0.80), GPC (R2 = 0.80), and CIE L* (R2 = 0.86). For late senescence, Sentinel‐2 satellite canopy reflectance, grain size was best predicted (R2 = 0.79) and GPC was poorer (R2 = 0.42). Spatial maps of fields for grain size, informed by models, could be derived and determined that for the market critical threshold (38 mg), field area that exceeded this threshold ranged between 30% and 94%. Overall, we determined that sensing technologies had utility for mapping lentil grain quality across fields, providing a potential tool for growers to selectively harvest to achieve best aggregate price based on grain quality targets. Further calibration and validation with multiple years and locations is also needed to test model stability and application to varying environments.

A Concise Review on Time of Flight (TOF) Mass Spectrum

Time of Flight Mass Spectrum is a method of mass spectrometer depending on the time which has been taking to reach the detector (usually located between 1 to 2 min from the source to separate ions) where the Sample is taken and mixed with matrix {the matrix is made up by chemical compound (2,4 Benzoic acid and cinamic acid) and they act as chemical cross link to produce matrix}. The energy source of this procedure is laser. Never the less, the ratio between sample and the matrix is 1:10,000 in order to prevent hampering the. However, TOF has some advantages such as unlimited upper ( mass /charge ) values to be detect, high resolution, good definition of narrow chromatographic peaks , good sensitivity and high quality spectra, High accurate mass measurement to the nearest 0.1 millimass unit for determining the elemental composition for ions less than 500 Da and It can perform tandem MS. Never the less, it has some drawbacks as requiring higher vacuum, Resolution changes with m/z value and high cost equipment. We conclude from this paper that: TOF is considered as one of the best mass filters because of unlimited upper (mass / charge) values to be detected as well as the capability of acquiring rapidly for averaging and good definition of narrow chromatographic peaks.

Remote quantification of the trophic status of Chinese lakes

Abstract. Assessing eutrophication in lakes is of key importance, as this parameter constitutes a major aquatic ecosystem integrity indicator. The trophic state index (TSI), which is widely used to quantify eutrophication, is a universal paradigm in the scientific literature. In this study, a methodological framework is proposed for quantifying and mapping TSI using the Sentinel Multispectral Imager sensor and fieldwork samples. The first step of the methodology involves the implementation of stepwise multiple regression analysis of the available TSI dataset to find some band ratios, such as blue/red, green/red and red/red, which are sensitive to lake TSI. Trained with in situ measured TSI and match-up Sentinel images, we established the XGBoost of machine learning approaches to estimate TSI, with good agreement (R2= 0.87, slope = 0.85) and fewer errors (MAE = 3.15 and RMSE = 4.11). Additionally, we discussed the transferability and applications of XGBoost in three lake classifications: water quality, absorption contribution and reflectance spectra types. We selected XGBoost to map TSI in 2019–2020 with good-quality Sentinel-2 Level-1C images embedded in the ESA to examine the spatiotemporal variations of the lake trophic state. In a large-scale observation, 10 m TSI products from 555 lakes in China facing eutrophication and unbalanced spatial patterns associated with lake basin characteristics, climate and anthropogenic activities were investigated. The methodological framework proposed herein could serve as a useful resource for continuous, long-term and large-scale monitoring of lake aquatic ecosystems, supporting sustainable water resource management.

Ornithodoros sonrai Soft Ticks and Associated Bacteria in Senegal.

The soft ticks, Ornithodoros sonrai, are known as vectors of the tick-borne relapsing fever caused by Borrelia spp. and have also been reported to carry other micro-organisms. The objective of this study was to collect and to identify O. sonrai ticks and to investigate the micro-organisms associated with them. In 2019, an investigation of burrows within human dwellings was conducted in 17 villages in the Niakhar area and in 15 villages in the Sine-Saloum area in the Fatick region of Senegal. Ticks collected from the burrows were identified morphologically and by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Micro-organism screening was performed by bacteria-specific qPCR and some identifications were made by standard PCR and gene sequencing. O. sonrai ticks were found in 100% (17/17) of the villages surveyed in the Niakhar area and in 66% (10/15) of the villages in the Sine-Saloum area. A total of 1275 soft tick specimens were collected from small mammal burrows. The ticks collected were morphologically identified as O. sonrai. About 20% (259/1275) of the specimens were also submitted to MALDI-TOF MS for identification. Among the resulting MS profiles, 87% (139/159) and 95% (95/100) were considered good quality specimens, preserved in alcohol and silica gel, respectively. All spectra of good quality were tested against our MALDI-TOF MS arthropod spectra database and identified as O. sonrai species, corroborating the morphological classification. The carriage of four micro-organisms was detected in the ticks with a high prevalence of Bartonella spp., Anaplasmataceae, and Borrelia spp. of 35, 28, and 26%, respectively, and low carriage of Coxiella burnetii (2%). This study highlights the level of tick infestation in domestic burrows, the inventory of pathogens associated with the O. sonrai tick, and the concern about the potential risk of tick involvement in the transmission of these pathogens in Senegal.

A quality spectra-based SVDD method for multi-dimensional quality fluctuation evaluation in complex industrial process

To address the problem that fluctuation caused by multi-dimensional quality-related process variables is difficult to evaluate, this paper proposes a quality spectra-based support vector data description (SVDD) method for multi-dimensional quality fluctuation evaluation in complex industrial process. Firstly, based on quality spectra modelling, a multi-dimensional state feature vector of quality fluctuation is constructed from the perspective of quality spectra and statistical distribution, which is used to characterize the difference between normal and abnormal fluctuation. Then the quality fluctuation evaluation model is established based on SVDD algorithm. On this basis, the spherical distance between the sample to be evaluated and the quality evaluation model is calculated to measure the quality fluctuation degree. Finally, a case for TE process data sets is used to verify the quality fluctuation evaluation approach, it reveals that the proposed method could evaluate the degree of quality fluctuation, which could provide some theoretical guides for quality stability control.

Kinematic lensing inference – I. Characterizing shape noise with simulated analyses

ABSTRACT The unknown intrinsic shape of source galaxies is one of the largest uncertainties of weak gravitational lensing (WL). It results in the so-called shape noise at the level of $\sigma _\epsilon ^{\mathrm{WL}} \approx 0.26$, whereas the shear effect of interest is of the order of per cent. Kinematic lensing (KL) is a new technique that combines photometric shape measurements with resolved spectroscopic observations to infer the intrinsic galaxy shape and directly estimate the gravitational shear. This paper presents a KL inference pipeline that jointly forward-models galaxy imaging and slit spectroscopy to extract the shear signal. We build a set of realistic mock observations and show that the KL inference pipeline can robustly recover the input shear. To quantify the shear measurement uncertainty for KL, we average the shape noise over a population of randomly oriented disc galaxies and estimate it to be $\sigma _\epsilon ^{\mathrm{KL}}\approx 0.022\!-\!0.038$ depending on emission-line signal-to-noise ratio. This order of magnitude improvement over traditional WL makes a KL observational programme feasible with existing spectroscopic instruments. To this end, we characterize the dependence of KL shape noise on observational factors and discuss implications for the survey strategy of future KL observations. In particular, we find that prioritizing quality spectra of low-inclination galaxies is more advantageous than maximizing the overall number density.

TopNEXt: automatic DDA exclusion framework for multi-sample mass spectrometry experiments.

Liquid Chromatography Tandem Mass Spectrometry experiments aim to produce high-quality fragmentation spectra, which can be used to annotate metabolites. However, current Data-Dependent Acquisition approaches may fail to collect spectra of sufficient quality and quantity for experimental outcomes, and extend poorly across multiple samples by failing to share information across samples or by requiring manual expert input. We present TopNEXt, a real-time scan prioritization framework that improves data acquisition in multi-sample Liquid Chromatography Tandem Mass Spectrometry metabolomics experiments. TopNEXt extends traditional Data-Dependent Acquisition exclusion methods across multiple samples by using a Region of Interest and intensity-based scoring system. Through both simulated and lab experiments, we show that methods incorporating these novel concepts acquire fragmentation spectra for an additional 10% of our set of target peaks and with an additional 20% of acquisition intensity. By increasing the quality and quantity of fragmentation spectra, TopNEXt can help improve metabolite identification with a potential impact across a variety of experimental contexts. TopNEXt is implemented as part of the ViMMS framework and the latest version can be found at https://github.com/glasgowcompbio/vimms. A stable version used to produce our results can be found at 10.5281/zenodo.7468914.

Resting-state EEG as a potential indicator to predict sleep quality in depressive patients

ObjectivesTo investigate the changes in sleep quality, heart rate variability (HRV) and resting-state electroencephalogram (rsEEG) in patients with major depressive disorder (MDD), and to explore whether HRV and rsEEG may be served as more convenient tools to assess sleep quality in MDD patients. MethodWe included a total of 91 subjects (46 healthy controls and 45 MDD patients) and compared their sleep quality, HRV and power spectra of rsEEG. Correlation analyses were conducted to discuss the relationship between HRV and seven factors of PSQI. Multiple linear regression model was used to examine whether absolute band power could predict sleep quality in MDD patients. ResultsWe found higher PSQI scores and lower levels of HRV in depressive individuals compared with healthy controls. In MDD patients, sleep latency was negatively correlated with RMSSD and HF. Delta, theta, and alpha band power of rsEEG were higher in MDD patients. Regression analyses showed delta band power of TP8, as well as theta, alpha band power of AF3 predicts PSQI score of MDD patients. ConclusionsThe findings of our study show that some aspects of sleep problems had negative correlations with parasympathetic activity and the regression model supports that the band power of rsEEG may be used as a potential indicator to evaluate the sleep quality in MDD patients. SignificanceCortical hyperarousal may be one of the reasons leading to poor sleep quality of MDD patients. And resting-state EEG can be used as a potential indicator for clinical assessment of MDD patients' sleep quality.