Hybrid Scan Research Articles

Software-aided efficient identification of the components of compound formulae and their metabolites in rats by UHPLC/IM-QTOF-MS and an in-house high-definition MS2 library: Sishen formula as a case

Identifying the compound formulae-related xenobiotics in bio-samples is full of challenges. Conventional strategies always exhibit the insufficiencies in overall coverage, analytical efficiency, and degree of automation, and the results highly rely on the personal knowledge and experience. The goal of this work was to establish a software-aided approach, by integrating ultra-high performance liquid chromatography/ion-mobility quadrupole time-of-flight mass spectrometry (UHPLC/IM-QTOF-MS) and in-house high-definition MS2 library, to enhance the identification of prototypes and metabolites of the compound formulae in vivo, taking Sishen formula (SSF) as a template. Seven different MS2 acquisition methods were compared, which demonstrated the potency of a hybrid scan approach (namely high-definition data-independent/data-dependent acquisition (HDDIDDA)) in the identification precision, MS1 coverage, and MS2 spectra quality. The HDDIDDA data for 55 reference compounds, four component drugs, and SSF, together with the rat bio-samples (e.g., plasma, urine, feces, liver, and kidney), were acquired. Based on the UNIFI™ platform (Waters), the efficient data processing workflows were established by combining mass defect filtering (MDF)-induced classification, diagnostic product ions (DPIs), and neutral loss filtering (NLF)-dominated structural confirmation. The high-definition MS2 spectral libraries, dubbed in vitro-SSF and in vivo-SSF, were elaborated, enabling the efficient and automatic identification of SSF-associated xenobiotics in diverse rat bio-samples. Consequently, 118 prototypes and 206 metabolites of SSF were identified, with the identification rate reaching 80.51% and 79.61%, respectively. The metabolic pathways mainly involved the oxidation, reduction, hydrolysis, sulfation, methylation, demethylation, acetylation, glucuronidation, and the combined reactions. Conclusively, the proposed strategy can drive the identification of compound formulae-related xenobiotics in vivo in an intelligent manner.

Integration of ion-mobility high-resolution liquid chromatography/mass spectrometry-based untargeted metabolomics and desorption electrospray ionization-mass spectrometry imaging to unveil the ginsenosides variation induced by steaming for Panax ginseng, P. quinquefolius and P. notoginseng

The raw and steamed products of ginseng exhibit different efficacy, and elucidation of the underlying chemical transformation is significant for their rational application and quality control. This work was designed to holistically depict the chemical variation of Panax ginseng (PG), P. quinquefolius (PQ), and P. notoginseng (PN) induced by the steaming, and to unveil the steaming-associated markers diagnostic for differentiating between the raw and processed products, following a three-step strategy: 1) systematic ginsenosides characterization by hybrid scan (namely HDDIDDA) available on the Vion™ ion mobility-quadrupole time-of-flight mass spectrometer coupled with reversed-phase ultra-high performance liquid chromatography; 2) holistic depiction of the chemical variation and discovery of potential markers by the pattern recognition untargeted metabolomics analysis; and 3) construction of steaming-induced transformation network combined with desorption electrospray ionization-mass spectrometry imaging (DESI-MSI). Consequently, 542 ginsenosides were characterized from the raw and processed PG/PQ/PN. Steaming at 1–10 h could cause significant chemical variation, and separately 26, 28, and 18 potential markers were found for the steaming of PG, PQ, and PN. Steaming-induced transformation network mainly involved hydration of the malonyl group, hydrolysis of the glycosyl moiety, and dehydration at C-20. DESI-MSI further revealed spatial distribution of marker saponins in the cork layer, phloem, and xylem, and primarily confirmed the hydrolysis reactions occurring to ginseng steaming. Conclusively, the established strategy is practical to unveil the holistic ginsenosides variation of ginseng induced by the processing, which is useful in the quality control of both the herbal medicines and foods.

Comprehensive metabolome characterization and comparison between two sources of Dragon's blood by integrating liquid chromatography/mass spectrometry and chemometrics.

Dragon's Blood (DB) serves as a precious Chinese medicine facilitating blood circulation and stasis dispersion. Daemonorops draco (D. draco; Qi-Lin-Jie) and Dracaena cochinchinensis (D. cochinchinenesis; Long-Xue-Jie) are two reputable plant sources for preparing DB. This work was designed to comprehensively characterize and compare the metabolome differences between D. draco and D. cochinchinenesis, by integrating liquid chromatography/mass spectrometry and untargeted metabolomics analysis. Offline two-dimensional liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (2D-LC/IM-QTOF-MS), by utilizing a powerful hybrid scan approach, was elaborated for multicomponent characterization. Configuration of an XBridge Amide column and an HSS T3 column in offline mode exhibited high orthogonality (A0 0.80) in separating the complex components in DB. Particularly, the hybrid high-definition MSE-high definition data-dependent acquisition (HDMSE-HDDDA) in both positive and negative ion modes was applied for data acquisition. Streamlined intelligent data processing facilitated by the UNIFI™ (Waters) bioinformatics platform and searching against an in-house chemical library (recording 223 known compounds) enabled efficient structural elucidation. We could characterize 285 components, including 143 from D. draco and 174 from D. cochinchinensis. Holistic comparison of the metabolomes among 21 batches of DB samples by the untargeted metabolomics workflows unveiled 43 significantly differential components. Separately, four and three components were considered as the marker compounds for identifying D. draco and D. cochinchinenesis, respectively. Conclusively, the chemical composition and metabolomic differences of two DB resources were investigated by a dimension-enhanced analytical approach, with the results beingbeneficial to quality control and thedifferentiated clinical application of DB.

Unveiling the chemical components variation of Sishen formula induced by different prescription ratios by the advanced liquid chromatography/mass spectrometry approaches

Compatibility with the varying prescription ratios is a unique feature in the Chinese medicine practice. Sishen formula (SSF; containing Psoraleae Fructus-PF, Myristicae Semen-MyS, Schisandrae Chinensis Fructus-SCF, and Euodiae Fructus-EF) with different proportions has been used to treat the irritable bowel syndrome, however, the underlying chemical difference needs to be clarified, particularly the influence on extracting those known toxic components. To tackle this issue, an integrated strategy was developed: 1) systematic multicomponent characterization by an off-line two-dimensional liquid chromatography/ion mobility time-of-flight mass spectrometry (2D-LC/IM-QTOF-MS) approach with the HDMSE-HDDDA hybrid scan; 2) discovery of potential markers associated with SSF proportion variation by untargeted metabolomics; and 3) quantitative assays of representative markers by multiple reaction monitoring (MRM) to unveil the effects on the dissolution of toxic components. Consequently, orthogonal separation, high sensitivity of detection, and intelligent data interpretation, enabled the characterization of 233 compounds from the SSF decoction. Totally 50 differential components were discovered from SSF with 16 different ratios by high-definition LC-MS profiling and multivariate statistical analysis. An MRM approach was validated offering the absolute content alternation of 18 compounds in SSF. Increasing of SCF, MyS, and EF moderately could reduce the dissolution of the main toxic coumarins of PF, while increasing of SCF promoted dissolution of the main toxic alkaloids of EF, which could be restrained by increasing MyS. Conclusively, the in-depth multicomponent characterization of SSF was achieved, and the disparities in the compatibility of various SSF proportions were exposed, which may bridge to the functions/toxicity variations of SSF in clinic.

Refined DFT＋[formula omitted] method for computation of layered oxide cathode materials

Transition metal oxides are widely used as cathode materials in rechargeable Li-ion batteries. Here we test the performance of the parameter-free DFT＋U method for predicting the structural parameters and electronic configuration of three materials: LiCoO2, LiNiO2 and mixed transition metal Li1.2Ni0.19Co0.19Mn0.42O2 compounds. The obtained lattice parameters and band gaps are consistent with the more computationally demanding hybrid functionals and SCAN methods. We emphasize the importance of using a realistic representation of the d orbitals to obtain the correct occupancy of these states, which are highly overestimated when the widely used atomic orbitals are applied as projectors. The applied here Wannier-type projectors result in correct occupancies, allowing for a decisive assignment of the oxidation states of cations and an improved description of the electronic structure. The applied scheme enhances predictive capabilities of the DFT＋U method for computation of electrochemically active compounds.

Integration of a hybrid scan approach and in-house high-resolution MS2 spectral database for charactering the multicomponents of Xuebijing Injection

Xuebijing (XBJ) Injection is a reputable patent Chinese medicine widely used to cure sepsis, among the Chinese ″Three Medicines and Three Prescriptions″ solution to fight against COVID-19. We were aimed to achieve the comprehensive multicomponent characterization from the single drugs to traditional Chinese medicine (TCM) formula, by integrating powerful data acquisition and the in-house MS2 spectral database searching. By ultra-high performance liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (UHPLC/IM-QTOF-MS), a hybrid scan approach (HDMSE-HDDDA) was developed, while the HDMSE data for five component drugs and 56 reference compounds were acquired and processed to establish an in-house MS2 spectral database of XBJ. Good resolution of the XBJ components was accomplished on a Zorbax Eclipse Plus C18 column within 24 min, while a fit-for-purpose HDMSE-HDDDA approach was elaborated in two ionization modes for enhanced MS2 data acquisition. XBJ MS2 spectral library was thus established on the UNIFITM platform involving rich structure-related information for the chemicals from five component drugs. We could identify or tentatively characterize 294 components from XBJ, involving 81 flavonoids, 51 terpenoids, 42 phthalides, 40 organic acids, 13 phenylpropanoids, seven phenanthrenequinones, six alkaloids, and 54 others. In contrast to the application of conventional MS1 library, this newly established strategy could demonstrate superiority in the accuracy of identification results and the characterization of isomers, due to the more restricted filtering/matching criteria. Conclusively, the integration of the HDMSE-HDDDA hybrid scan approach and the in-house MS2 spectral database can favor the efficient and more reliable multicomponent characterization from single drugs to the TCM formula.

Fast Neutron Tomography of Fuel Cells Enabled By Seeded Tomography Reconstruction

Neutron imaging provides high sensitivity to liquid water while being able to penetrate materials typically used to construct fuel cells. Water distribution measurements in operating fuel cells are typically performed using neutron radiography as the neutron fluence rate of the beam requires long acquisition times for high resolution making tomography difficult. Radiography only provides a two-dimensional look at the water distribution with an operating fuel cell making tomography preferable to understand three-dimensional distribution of water. NIST developed a fuel cell hardware design to allow for simultaneous neutron and X-ray tomography and as first reported in 2017 [1], initial efforts for tomography required acquisition times of 18 hours while the cell continuously operated at steady state conditions. Progress was made to improve acquisition settings and reconstruction methods to reduce the time required. These improvements were presented in 2019 [2] and demonstrated that scan times could be reduced to 8 hours and provided ground work for reducing acquisition times down to 1 hour to 2 hours.Since 2019, further progress has been made in applying dose reduction iterative reconstruction algorithms to the fuel cell datasets to allow faster acquisition times. Faster acquisition scans were simulated by reducing the number of projection angles from the high-resolution datasets from the 2019 work. The high-resolution scan was acquired with 851 projections from 0° to 360° and the fast scan consisted of only 51 projections. Reducing the number of projections from 851 to 51 simulates a scan that requires only 29 minutes to acquire, which is close to the typical length of time for acquiring high resolution radiography images. Figure 1 shows the comparison of a single slice from the 3D volumes with (A) representing the 8 hour, 851 projection scan, (C) the iteratively reconstructed 51 projection scan, and (E) the 51 projection scan reconstructed with filtered back projection algorithm used for the 851 projection scan. The iterative reconstruction gives favorable results when compared to the 851 projection reconstruction and shows that flux limitations on speed can be overcome to achieve high-speed tomography at high resolution on a neutron beam.This talk will describe the methodology for acquiring neutron tomography scans of operating fuel cells in under 30 minutes and give insights into how this can be used towards solving water management issues. It will be possible to combine radiography and tomography into a hybrid scan at each operating condition that can be acquired in 1 hour that will provide highly quantifiable water content measurements with 3-dimensional distribution information. The short scan times are beneficial for materials sets that are sensitive to long constant current hold durations such as new non-platinum catalysts. Additionally, new cameras are being commissioned that will improve resolution and push X-ray resolution to the point of resolving the fiber and macropore distribution of the gas diffusion layer (GDL) that can be coupled with the water content information. Figure 1

Integrating Enhanced Profiling and Chemometrics to Unveil the Potential Markers for Differentiating among the Leaves of Panax ginseng, P. quinquefolius, and P. notoginseng by Ultra-High Performance Liquid Chromatography/Ion Mobility-Quadrupole Time-of-Flight Mass Spectrometry.

The leaves of Panax species (e.g., Panax ginseng-PGL, P. quinquefolius-PQL, and P. notoginseng-PNL) can serve as a source for healthcare products. Comprehensive characterization and unveiling of the metabolomic difference among PGL, PQL, and PNL are critical to ensure their correct use. For this purpose, enhanced profiling and chemometrics were integrated to probe into the ginsenoside markers for PGL/PQL/PNL by ultra-high performance liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (UHPLC/IM-QTOF-MS). A hybrid scan approach (HDMSE-HDDDA) was established achieving the dimension-enhanced metabolic profiling, with 342 saponins identified or tentatively characterized from PGL/PQL/PNL. Multivariate statistical analysis (33 batches of leaf samples) could unveil 42 marker saponins, and the characteristic ginsenosides diagnostic for differentiating among PGL/PQL/PNL were primarily established. Compared with the single DDA or DIA, the HDMSE-HDDDA hybrid scan approach could balance between the metabolome coverage and spectral reliability, leading to high-definition MS spectra and the additional collision-cross section (CCS) useful to differentiate isomers.

Systematic Qualitative and Quantitative Analyses of Wenxin Granule via Ultra-High Performance Liquid Chromatography Coupled with Ion Mobility Quadrupole Time-of-Flight Mass Spectrometry and Triple Quadrupole-Linear Ion Trap Mass Spectrometry.

Wenxin granule (WXG) is a popular traditional Chinese medicine (TCM) preparation for the treatment of arrhythmia disease. Potent analytical technologies are needed to elucidate its chemical composition and assess the quality differences among multibatch samples. In this work, both a multicomponent characterization and quantitative assay of WXG were conducted using two liquid chromatography–mass spectrometry (LC-MS) approaches. An ultra-high performance liquid chromatography–ion mobility quadrupole time-of-flight mass spectrometry (UHPLC/IM-QTOF-MS) approach combined with intelligent peak annotation workflows was developed to characterize the multicomponents of WXG. A hybrid scan approach enabling alternative data-independent and data-dependent acquisitions was established. We characterized 205 components, including 92 ginsenosides, 53 steroidal saponins, 14 alkaloids, and 46 others. Moreover, an optimized scheduled multiple reaction monitoring (sMRM) method was elaborated, targeting 24 compounds of WXG via ultra-high performance liquid chromatography–triple quadrupole linear ion trap mass spectrometry (UHPLC/QTrap-MS), which was validated based on its selectivity, precision, stability, repeatability, linearity, sensitivity, recovery, and matrix effect. By applying this method to 27 batches of WXG samples, the content variations of multiple markers from Notoginseng Radix et Rhizoma (21) and Codonopsis Radix (3) were depicted. Conclusively, we achieved the comprehensive multicomponent characterization and holistic quality assessment of WXG by targeting the non-volatile components.

An ion mobility-enabled and high-efficiency hybrid scan approach in combination with ultra-high performance liquid chromatography enabling the comprehensive characterization of the multicomponents from Carthamus tinctorius

Liquid chromatography/mass spectrometry (LC/MS) is extensively applied for the untargeted/targeted analyses of the herbal components, utilizing data-dependent acquisition (DDA) or data-independent acquisition (DIA) to record the fragmentation information useful for the structural elucidation. A new trend recently has emerged by integrating DDA and DIA to render the hybrid scan, which, unfortunately, has rarely been reported. Herein, by using the Vion™ ion-mobility quadrupole time-of-flight mass spectrometer, a hybrid scan strategy (HDMSE-HDDDA) was presented and validated by the untargeted characterization of the multicomponents from Carthamus tinctorius (safflower), in combination with reversed-phase ultra-high performance liquid chromatography (RP-UHPLC). Good chromatographic separation was achieved on an HSS T3 column within 26 min, while HDMSE-MS/MS was used to acquire the collision-induced dissociation MS2 data in the negative mode. Automatic workflows (e.g., data correction, precursors/product ions matching, and peak annotation) were well established on UNIFI™ (incorporating an in-house library recording 261 known compounds) to process the obtained MS2 data. Compared with single DDA or DIA, the hybrid approach of HDMSE-HDDDA better balanced between the coverage and reliability, led to high-definition MS spectra, offered useful collision cross section (CCS) information, and showed satisfactory identification performance comparable to MSE. A total of 141 components (involving 41 quinochalcones, 66 flavanols/flavones, 11 flavanones, 6 organic acids, 1 polyacetylene, and 16 others) were characterized from safflower. Moreover, CCS prediction could assist isomers characterization, to some extent. Conclusively, this hybrid scan approach enables a dimension-enhanced MS data acquisition strategy providing the complementary structural information, which more suits the chemical characterization of complex samples.

Pure and Hybrid SCAN, rSCAN, and r2SCAN: Which One Is Preferred in KS- and HF-DFT Calculations, and How Does D4 Dispersion Correction Affect This Ranking?

Using the large and chemically diverse GMTKN55 dataset, we have tested the performance of pure and hybrid KS-DFT and HF-DFT functionals constructed from three variants of the SCAN meta-GGA exchange-correlation functional: original SCAN, rSCAN, and r2SCAN. Without any dispersion correction involved, HF-SCANn outperforms the two other HF-DFT functionals. In contrast, among the self-consistent variants, SCANn and r2SCANn offer essentially the same performance at lower percentages of HF-exchange, while at higher percentages, SCANn marginally outperforms r2SCANn and rSCANn. However, with D4 dispersion correction included, all three HF-DFT-D4 variants perform similarly, and among the self-consistent counterparts, r2SCANn-D4 outperforms the other two variants across the board. In view of the much milder grid dependence of r2SCAN vs. SCAN, r2SCAN is to be preferred across the board, also in HF-DFT and hybrid KS-DFT contexts.

A novel hybrid scan approach enabling the ion-mobility separation and the alternate data-dependent and data-independent acquisitions (HDDIDDA): Its combination with off-line two-dimensional liquid chromatography for comprehensively characterizing the multicomponents from Compound Danshen Dripping Pill

Data-dependent acquisition (DDA) and data-independent acquisition (DIA)-based MSn strategies are extensively applied in metabolites characterization. DDA gives accurate MSn information, but receives low coverage, while DIA covers the entire mass range, but the precursor-product ions matching often yields false positives. Currently available MS scan approaches rarely integrate DIA and DDA within a duty circle. Utilizing a Vion™ IM-QTOF (ion mobility-quadrupole time-of-flight) mass spectrometer, we report a novel hybrid scan approach, namely HDDIDDA, which involves three scan events: 1) IM-enabled full scan (MS1), 2) high-definition MSE (HDMSE) of all precursor ions (MS2); and 3) high-definition DDA (HDDDA) of top N precursors (MS2). As a proof-of-concept, the HDDIDDA approach combined with off-line two-dimensional liquid chromatography (2D-LC) was applied to characterize the multiple ingredients from a reputable Chinese patent medicine, Compound Danshen Dripping Pill (CDDP) used for treating the cardiovascular diseases. An off-line 2D-LC system by configuring an XBridge Amide column and an HSS T3 column showed a measurable orthogonality of 0.92 and enhanced the separation of co-eluting components. A fit-for-purpose HDDIDDA methodology was developed in the negative mode to characterize saponins and salvianolic acids, while tanshinones in the positive mode. Computational workflows to efficiently process the acquired HDMSE and HDDDA data were established, and the searching of an in-house CDDP library (recording 712 compounds) eventually characterized 403 components from CDDP, indicating approximate 12-fold improvement compared with the previous report. The HDDIDDA approach can measure collision cross section of each component, and merges the merits of DIA and DDA in MS2 data acquisition.

Integrated Pose Estimation Using 2D Lidar and INS Based on Hybrid Scan Matching.

Point cloud data is essential measurement information that has facilitated an extended functionality horizon for urban mobility. While 3D lidar and image-depth sensors are superior in implementing mapping and localization, sense and avoidance, and cognitive exploration in an unknown area, applying 2D lidar is inevitable for systems with limited resources of weight and computational power, for instance, in an aerial mobility system. In this paper, we propose a new pose estimation scheme that reflects the characteristics of extracted feature point information from 2D lidar on the NDT framework for exploiting an improved point cloud registration. In the case of the 2D lidar point cloud, vertices and corners can be viewed as representative feature points. Based on this feature point information, a point-to-point relationship is functionalized and reflected on a voxelized map matching process to deploy more efficient and promising matching performance. In order to present the navigation performance of the mobile object to which the proposed algorithm is applied, the matching result is combined with the inertial navigation through an integration filter. Then, the proposed algorithm was verified through a simulation study using a high-fidelity flight simulator and an indoor experiment. For performance validation, both results were compared and analyzed with the previous techniques. In conclusion, it was demonstrated that improved accuracy and computational efficiency could be achieved through the proposed algorithms.

A Hybrid Scan Gibbs Sampler for Bayesian Models with Latent Variables

Gibbs sampling is a widely popular Markov chain Monte Carlo algorithm that can be used to analyze intractable posterior distributions associated with Bayesian hierarchical models. There are two standard versions of the Gibbs sampler: The systematic scan (SS) version, where all variables are updated at each iteration, and the random scan (RS) version, where a single, randomly selected variable is updated at each iteration. The literature comparing the theoretical properties of SS and RS Gibbs samplers is reviewed, and an alternative hybrid scan Gibbs sampler is introduced, which is particularly well suited to Bayesian models with latent variables. The word “hybrid” reflects the fact that the scan used within this algorithm has both systematic and random elements. Indeed, at each iteration, one updates the entire set of latent variables, along with a randomly chosen block of the remaining variables. The hybrid scan (HS) Gibbs sampler has important advantages over the two standard scan Gibbs samplers. First, the HS algorithm is often easier to analyze from a theoretical standpoint. In particular, it can be much easier to establish the geometric ergodicity of a HS Gibbs Markov chain than to do the same for the corresponding SS and RS versions. Second, the sandwich methodology developed in (Ann. Statist. 36 (2008) 532–554), which is also reviewed, can be applied to the HS Gibbs algorithm (but not to the standard scan Gibbs samplers). It is shown that, under weak regularity conditions, adding sandwich steps to the HS Gibbs sampler always results in a theoretically superior algorithm. Three specific Bayesian hierarchical models of varying complexity are used to illustrate the results. One is a simple location-scale model for data from the Student’s t distribution, which is used as a pedagogical tool. The other two are sophisticated, yet practical Bayesian regression models.

Schizophrenia syndrome due to C9ORF72 mutation case report: a cautionary tale and role of hybrid brain imaging!

BackgroundFrontal variant frontotemporal dementia is a common cause of presenile dementia. A hexanucleotide expansion on chromosome 9 has recently been recognized as the most common genetic mutation cause of this illness. This sub-type tends to present psychiatrically with psychosis being a common presenting symptom before the onset of cognitive changes or brain atrophy. A few case series have been published describing the prominence of early psychotic symptoms, and lack of clear brain atrophy on clinical brain imaging imposing a challenge in reaching early accurate diagnosis. In this report, we present a case whereby the diagnosis of Schizophrenia syndrome was made and the patient was treated for years with multiple interventions for that syndrome before reaching the accurate diagnosis of Frontal variant frontotemporal dementia due to hexanucleotide expansion on chromosome 9. This diagnosis was confirmed after genetic testing and findings on a hybrid Positron Emission Tomography/Magnetic Resonance Imaging scanning.Case summaryA 60-year-old female diagnosed with schizophrenia at age 50 after presenting with delusions and hallucinations, which proved to be refractor to several lines of pharmacological and non-pharmacological interventions including electroconvulsive therapy. Patient had a history of post-partum psychosis in her 20s. She was referred to cognitive neurology due to progressive decline in function. While clinical structural brain imaging data were not adequate to support an alternative neurological diagnosis, careful inquiry elicited a history of psychotic illness followed by progressive decline in a sister. Genetic testing confirmed hexanucleotide expansion on chromosome 9 mutation. The patient was offered a state-of-the-art FD-Glucose Positron Emission Tomography/Magnetic Resonance Imaging scan available at our centre. While volumetric Magnetic Resonance Imaging scan did not show volume loss in frontotemporal areas, the hybrid scan showed regionally specific deficit in FD-Glucose Positron Emission Tomography affecting medial superior frontal, insula, inferior temporal, thalamus, and anterior cingulate cortex consistent with behavioral variant frontotemporal dementia.ConclusionsThis case highlights the importance of considering Frontal variant frontotemporal dementia due to hexanucleotide expansion on chromosome 9 when facing relatively late-onset, refractory schizophrenia-like syndrome. Careful history from all available sources to elicit family history of similar presentation is very important. Genetic testing and functional brain imaging can aid in confirming the diagnosis and potentially streamlining the management of these cases.

Nanoparticles: Untying the Gordian Knot in Conventional Computed Tomography Imaging

X-ray computed tomography (CT) imaging plays an essential role in disease diagnosis due to its noninvasive, painless mode and superior penetration depth. However, the resolution of the soft tissue ...

Automatic radar antenna scan type recognition based onlimited penetrable visibility graph

To address the problem of the weak anti-noise and macro-trend extraction abilities of the current methods for identifying radar antenna scan type, a recognition method for radar antenna scan types based on limited penetrable visibility graph(LPVG) is proposed. Firstly, seven types of radar antenna scans are analyzed, which include the circular scan, sector scan, helical scan, raster scan, conical scan, electromechanical hybrid scan and two-dimensional electronic scan. Then, the time series of the pulse amplitude in the radar reconnaissance receiver is converted into an LPVG network, and the feature parameters are extracted. Finally, the recognition result is obtained by using a support vector machine (SVM) classifier. The experimental results show that the recognition accuracy and noise resistance of this new method are improved, where the average recognition accuracy for radar antenna type is at least 90% when the signal-to-noise ratio (SNR) is 5 dB and above.

Effect of Shape and Sizes of Crystal Particles on Angular Distributions of Transmitted Solar Radiation in Two Sensing Geometries: Results of Numerical Simulation

The results of statistical simulation of intensity of transmitted solar radiation in the presence of optically thin cirrus clouds for two sensing geometries: in solar almucantar and hybrid scan (AERONET photometric network) are considered. Numerical experiments were performed using ice crystal cloud models: OPAC (hexagonal particles with a smooth surface) and a model proposed by Baum et al. (а mixture of particles with different shapes, hexagonal columns and aggregates of hexagonal columns with a very rough surface). The effects of shape and size of ice crystals on the angular distributions of downward radiation in the wavelength channels of 440 and 870 nm are estimated for background atmospheric situations observed in Tomsk in the summer period.

Comparative study of reliability of inflammatory markers over 18-FDG−PET CT scan in monitoring skull base osteomyelitis

IntroductionThe end point of treatment in skull base osteomyelitis is a matter of debate. A treatment based on symptoms alone is fraught with recurrence. There is a need to restrict imaging though more informative. The inflammatory markers like C-reactive protein and erythrocyte sedimentation rate used commonly need a detailed evaluation to optimize its utility. ObjectivesTo compare the diagnostic accuracy of inflammatory markers with a hybrid PET scan in monitoring skull base osteomyelitis. The secondary objective was to obtain a cut-off value of these markers to decide upon antibiotic termination. MethodsA prospective cohort study was conducted in a tertiary care center with fifty-one patients with skull base osteomyelitis meeting eligibility criteria. Patients diagnosed with skull base osteomyelitis were serially monitored with weekly markers and PET scan after the initiation of treatment. A hybrid scan was taken at 6–8 weeks of treatment and repeated if required. The follow-up period varied from 6 weeks to 15 months. The outcome measures studied were the values of markers and the metabolic activity of PET scan when the patient became asymptomatic and when disease-free. ResultsC-reactive protein and erythrocyte sedimentation rate had a statistically significant correlation to disease activity in PET tomography scan as a prognostic marker. Both showed good clinical correlation. A cut off value of ≤ 3.6mg/L for C-reactive protein and ≤ 35mm/hour for erythrocyte sedimentation rate were taken as normalized values. ConclusionA consistent normalized value of C-reactive protein and erythrocyte sedimentation rate for 8–12 weeks in an asymptomatic patient may be an indicator of disease control, though not cure. So, relying solely on markers alone for antibiotic termination may cause relapse. It may be used cautiously in a peripheral setting without access to more specific hybrid scans. In a tertiary care, follow-up scans may be done based on the titres, thereby limiting the radiation exposure.

The AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2

Abstract. The Aerosol Robotic Network (AERONET) Version 3 (V3) aerosol retrieval algorithm is described, which is based on the Version 2 (V2) algorithm with numerous updates. Comparisons of V3 aerosol retrievals to those of V2 are presented, along with a new approach to estimate uncertainties in many of the retrieved aerosol parameters. Changes in the V3 aerosol retrieval algorithm include (1) a new polarized radiative transfer code (RTC), which replaced the scalar RTC of V2, (2) detailed characterization of gas absorption by adding NO2 and H2O to specify total gas absorption in the atmospheric column, specification of vertical profiles of all the atmospheric species, (3) new bidirectional reflectance distribution function (BRDF) parameters for land sites adopted from the MODIS BRDF/Albedo product, (4) a new version of the extraterrestrial solar flux spectrum, and (5) a new temperature correction procedure of both direct Sun and sky radiance measurements. The potential effect of each change in V3 on single scattering albedo (SSA) retrievals was analyzed. The operational almucantar retrievals of V2 versus V3 were compared for four AERONET sites: GSFC, Mezaira, Mongu, and Kanpur. Analysis showed very good agreement in retrieved parameters of the size distributions. Comparisons of SSA retrievals for dust aerosols (Mezaira) showed a good agreement in 440 nm SSA, while for longer wavelengths V3 SSAs are systematically higher than those of V2, with the largest mean difference at 675 nm due to cumulative effects of both extraterrestrial solar flux and BRDF changes. For non-dust aerosols, the largest SSA deviation is at 675 nm due to differences in extraterrestrial solar flux spectrums used in each version. Further, the SSA 675 nm mean differences are very different for weakly (GSFC) and strongly (Mongu) absorbing aerosols, which is explained by the lower sensitivity to a bias in aerosol scattering optical depth by less absorbing aerosols. A new hybrid (HYB) sky radiance measurement scan is introduced and discussed. The HYB combines features of scans in two different planes to maximize the range of scattering angles and achieve scan symmetry, thereby allowing for cloud screening and spatial averaging, which is an advantage over the principal plane scan that lacks robust symmetry. We show that due to an extended range of scattering angles, HYB SSA retrievals for dust aerosols exhibit smaller variability with solar zenith angles (SZAs) than those of almucantar (ALM), which allows extension of HYB SSA retrievals to SZAs less than 50∘ to as small as 25∘. The comparison of SSA retrievals from closely time-matched HYB and ALM scans in the 50 to 75∘ SZA range showed good agreement with the differences below ∼0.005. We also present an approach to estimate retrieval uncertainties which utilizes the variability in retrieved parameters generated by perturbing both measurements and auxiliary input parameters as a proxy for retrieval uncertainty. The perturbations in measurements and auxiliary inputs are assumed as estimated biases in aerosol optical depth (AOD), radiometric calibration of sky radiances combined with solar spectral irradiance, and surface reflectance. For each set of Level 2 Sun/sky radiometer observations, 27 inputs corresponding to 27 combinations of biases were produced and separately inverted to generate the following statistics of the inversion results: average, standard deviation, minimum and maximum values. From these statistics, standard deviation (labeled U27) is used as a proxy for estimated uncertainty, and a lookup table (LUT) approach was implemented to reduce the computational time. The U27 climatological LUT was generated from the entire AERONET almucantar (1993–2018) and hybrid (2014–2018) scan databases by binning U27s in AOD (440 nm), Angström exponent (AE, 440–870 nm), and SSA (440, 675, 870, 1020 nm). Using this LUT approach, the uncertainty estimates U27 for each individual V3 Level 2 retrieval can be obtained by interpolation using the corresponding measured and inverted combination of AOD, AE, and SSA.