First Hitting Times on a Quantum Computer: Tracking vs. Local Monitoring, Topological Effects, and Dark States.

We investigate a quantum walk on a ring represented by a directed triangle graph with complex edge weights and monitored at a constant rate until the quantum walker is detected. To this end, the first hitting time statistics are recorded using unitary dynamics interspersed stroboscopically by measurements, which are implemented on IBM quantum computers with a midcircuit readout option. Unlike classical hitting times, the statistical aspect of the problem depends on the way we construct the measured path, an effect that we quantify experimentally. First, we experimentally verify the theoretical prediction that the mean return time to a target state is quantized, with abrupt discontinuities found for specific sampling times and other control parameters, which has a well-known topological interpretation. Second, depending on the initial state, system parameters, and measurement protocol, the detection probability can be less than one or even zero, which is related to dark-state physics. Both return-time quantization and the appearance of the dark states are related to degeneracies in the eigenvalues of the unitary time evolution operator. We conclude that, for the IBM quantum computer under study, the first hitting times of monitored quantum walks are resilient to noise. However, a finite number of measurements leads to broadening effects, which modify the topological quantization and chiral effects of the asymptotic theory with an infinite number of measurements.

Data-Driven Motion Detection and Event-by-Event Correction for Brain PET: Comparison with Vicra.

Head motion degrades image quality and causes erroneous parameter estimates in tracer kinetic modeling in brain PET studies. Existing motion correction methods include frame-based image registration (FIR) and correction using real-time hardware-based motion tracking (HMT) information. However, FIR cannot correct for motion within 1 predefined scan period, and HMT is not readily available in the clinic since it typically requires attaching a tracking device to the patient. In this study, we propose a motion correction framework with a data-driven algorithm, that is, using the PET raw data itself, to address these limitations. Methods: We propose a data-driven algorithm, centroid of distribution (COD), to detect head motion. In COD, the central coordinates of the line of response of all events are averaged over 1-s intervals to generate a COD trace. A point-to-point change in the COD trace in 1 direction that exceeded a user-defined threshold was defined as a time point of head motion, which was followed by manually adding additional motion time points. All the frames defined by such time points were reconstructed without attenuation correction and rigidly registered to a reference frame. The resulting transformation matrices were then used to perform the final motion-compensated reconstruction. We applied the new COD framework to 23 human dynamic datasets, all containing large head motion, with 18F-FDG (n = 13) and 11C-UCB-J ((R)-1-((3-(11C-methyl-11C)pyridin-4-yl)methyl)-4-(3,4,5-trifluorophenyl)pyrrolidin-2-one) (n = 10) and compared its performance with FIR and with HMT using Vicra (an optical HMT device), which can be considered the gold standard. Results: The COD method yielded a 1.0% ± 3.2% (mean ± SD across all subjects and 12 gray matter regions) SUV difference for 18F-FDG (3.7% ± 5.4% for 11C-UCB-J) compared with HMT, whereas no motion correction (NMC) and FIR yielded -15.7% ± 12.2% (-20.5% ± 15.8%) and -4.7% ± 6.9% (-6.2% ± 11.0%), respectively. For 18F-FDG dynamic studies, COD yielded differences of 3.6% ± 10.9% in Ki value as compared with HMT, whereas NMC and FIR yielded -18.0% ± 39.2% and -2.6% ± 19.8%, respectively. For 11C-UCB-J, COD yielded 3.7% ± 5.2% differences in VT compared with HMT, whereas NMC and FIR yielded -20.0% ± 12.5% and -5.3% ± 9.4%, respectively. Conclusion: The proposed COD-based data-driven motion correction method outperformed FIR and achieved comparable or even better performance than the Vicra HMT method in both static and dynamic studies.

Lysine acetylation contributes to development, aflatoxin biosynthesis and pathogenicity in Aspergillus flavus.

Aspergillus flavus is a pathogenic fungus that produces carcinogenic aflatoxins, posing a great threat to crops, animals and humans. Lysine acetylation is one of the most important reversible post-translational modifications and plays a vital regulatory role in various cellular processes. However, current information on the extent and function of lysine acetylation and aflatoxin biosynthesis in A. flavus is limited. Here, a global acetylome analysis of A. flavus was performed by peptide pre-fractionation, pan-acetylation antibody enrichment and liquid chromatography-mass spectrometry. A total of 1313 high-confidence acetylation sites in 727 acetylated proteins were identified in A. flavus. These acetylation proteins are widely involved in glycolysis/gluconeogenesis, pentose phosphate pathway, citric acid cycle and aflatoxin biosynthesis. AflO (O-methyltransferase), a key enzyme in aflatoxin biosynthesis, was found to be acetylated at K241 and K384. Deletion of aflO not only impaired conidial and sclerotial developments, but also dramatically suppressed aflatoxin production and pathogenicity of A. flavus. Further site-specific mutations showed that lysine acetylation of AflO could also result in defects in development, aflatoxin production and pathogenicity, suggesting that acetylation plays a vital role in the regulation of the enzymatic activity of AflO in A. flavus. Our findings provide evidence for the involvement of lysine acetylation in various biological processes in A. flavus and facilitating in the elucidation of metabolic networks.

Event-by-event non-rigid data-driven PET respiratory motion correction methods: comparison of principal component analysis and centroid of distribution.

Respiratory motion is a major cause of degradation of PET image quality. Respiratory gating and motion correction can be performed to reduce the effects of respiratory motion; these methods require motion information, typically obtained from external tracking systems. Various groups have studied data-driven (DD) motion estimation methods. Recently, a DD respiratory motion estimation method was established by calculating the centroid of distribution (COD) of listmode events, which was then used with event-by-event respiratory motion correction (EBE-MC) and showed results comparable to those with an external motion tracking device. The EBE-MC method only corrected for rigid motion, so that non-rigid components still contributed to motion-induced blurring. A non-rigid respiratory motion correction (NRMC) was later developed to overcome this problem, but was only evaluated using signals from an external monitor. Thus, it is desirable to further develop DD motion estimation to achieve the best respiratory motion correction results. We evaluated two DD respiratory motion detection methods, COD and principal component analysis (PCA), by comparing the extracted motion trace to that acquired by the Anzai system in dynamic studies with two tracers. PCA was chosen as a preliminary study indicated that it produced stable results than other DD methods. We then developed and performed DD-EBE-NRMC using either COD- or PCA-derived respiratory motion information. DD correction results were compared with Anzai-based results. For all tested studies, both COD and PCA showed a good-to-excellent match with Anzai signals, with PCA showing a higher correlation with Anzai signals. The DD-EBE-NRMC results showed that both COD and PCA provide comparable image quality improvement to the Anzai-based correction. Although COD showed a lower correlation with Anzai than PCA, COD-based NRMC results are comparable to those of PCA, both of which showed great reduction in motion-induced blurring.

Data-driven voluntary body motion detection and non-rigid event-by-event correction for static and dynamic PET.

PET has the potential to perform absolute in vivo radiotracer quantitation. This potential can be compromised by voluntary body motion (BM), which degrades image resolution, alters apparent tracer uptakes, introduces CT-based attenuation correction mismatch artifacts and causes inaccurate parameter estimates in dynamic studies. Existing body motion correction (BMC) methods include frame-based image-registration (FIR) approaches and real-time motion tracking using external measurement devices. FIR does not correct for motion occurring within a pre-defined frame and the device-based method is generally not practical in routine clinical use, since it requires attaching a tracking device to the patient and additional device set up time. In this paper, we proposed a data-driven algorithm, centroid of distribution (COD), to detect BM. In this algorithm, the central coordinate of the time-of-flight (TOF) bin, which can be used as a reasonable surrogate for the annihilation point, is calculated for every event, and averaged over a certain time interval to generate a COD trace. We hypothesized that abrupt changes on the COD trace in lateral direction represent BMs. After detection, BM is estimated using non-rigid image registrations and corrected through list-mode reconstruction. The COD-based BMC approach was validated using a monkey study and was evaluated against FIR using four human and one dog studies with multiple tracers. The proposed approach successfully detected BMs and yielded superior correction results over conventional FIR approaches.

Respiratory Motion Compensation for PET/CT with Motion Information Derived from Matched Attenuation-Corrected Gated PET Data.

Respiratory motion degrades the detection and quantification capabilities of PET/CT imaging. Moreover, mismatch between a fast helical CT image and a time-averaged PET image due to respiratory motion results in additional attenuation correction artifacts and inaccurate localization. Current motion compensation approaches typically have 3 limitations: the mismatch among respiration-gated PET images and the CT attenuation correction (CTAC) map can introduce artifacts in the gated PET reconstructions that can subsequently affect the accuracy of the motion estimation; sinogram-based correction approaches do not correct for intragate motion due to intracycle and intercycle breathing variations; and the mismatch between the PET motion compensation reference gate and the CT image can cause an additional CT-mismatch artifact. In this study, we established a motion correction framework to address these limitations. Methods: In the proposed framework, the combined emission-transmission reconstruction algorithm was used for phase-matched gated PET reconstructions to facilitate the motion model building. An event-by-event nonrigid respiratory motion compensation method with correlations between internal organ motion and external respiratory signals was used to correct both intracycle and intercycle breathing variations. The PET reference gate was automatically determined by a newly proposed CT-matching algorithm. We applied the new framework to 13 human datasets with 3 different radiotracers and 323 lesions and compared its performance with CTAC and non-attenuation correction (NAC) approaches. Validation using 4-dimensional CT was performed for one lung cancer dataset. Results: For the 10 18F-FDG studies, the proposed method outperformed (P < 0.006) both the CTAC and the NAC methods in terms of region-of-interest-based SUVmean, SUVmax, and SUV ratio improvements over no motion correction (SUVmean: 19.9% vs. 14.0% vs. 13.2%; SUVmax: 15.5% vs. 10.8% vs. 10.6%; SUV ratio: 24.1% vs. 17.6% vs. 16.2%, for the proposed, CTAC, and NAC methods, respectively). The proposed method increased SUV ratios over no motion correction for 94.4% of lesions, compared with 84.8% and 86.4% using the CTAC and NAC methods, respectively. For the 2 18F-fluoropropyl-(+)-dihydrotetrabenazine studies, the proposed method reduced the CT-mismatch artifacts in the lower lung where the CTAC approach failed and maintained the quantification accuracy of bone marrow where the NAC approach failed. For the 18F-FMISO study, the proposed method outperformed both the CTAC and the NAC methods in terms of motion estimation accuracy at 2 lung lesion locations. Conclusion: The proposed PET/CT respiratory event-by-event motion-correction framework with motion information derived from matched attenuation-corrected PET data provides image quality superior to that of the CTAC and NAC methods for multiple tracers.

Lysine Succinylation Contributes to Aflatoxin Production and Pathogenicity in Aspergillus flavus.

Aspergillus flavus (A. flavus) is a ubiquitous saprophytic and pathogenic fungus that produces the aflatoxin carcinogen, and A. flavus can have tremendous economic and health impacts worldwide. Increasing evidence demonstrates that lysine succinylation plays an important regulatory role in metabolic processes in both bacterial and human cells. However, little is known about the extent and function of lysine succinylation in A. flavus Here, we performed a global succinylome analysis of A. flavus using high accuracy nano-LC-MS/MS in combination with the enrichment of succinylated peptides from digested cell lysates and subsequent peptide identification. In total, 985 succinylation sites on 349 succinylated proteins were identified in this pathogen. Bioinformatics analysis revealed that the succinylated proteins were involved in various biological processes and were particularly enriched in the aflatoxin biosynthesis process. Site-specific mutagenesis and biochemical studies showed that lysine succinylation on the norsolorinic acid reductase NorA (AflE), a key enzyme in aflatoxins biosynthesis, can affect the production of sclerotia and aflatoxins biosynthesis in A. flavus. Together, our findings reveal widespread roles for lysine succinylation in regulating metabolism and aflatoxins biosynthesis in A. flavus Our data provide a rich resource for functional analyses of lysine succinylation and facilitate the dissection of metabolic networks in this pathogen.

FPD: A comprehensive phosphorylation database in fungi.

Protein phosphorylation, one of the most classic post-translational modification, plays a critical role in diverse cellular processes including cell cycle, growth, and signal transduction pathways. However, the available information about phosphorylation in fungi is limited. Here, we provided a Fungi Phosphorylation Database (FPD) that comprises high-confidence in vivo phosphosites identified by MS-based proteomics in various fungal species. This comprehensive phosphorylation database contains 62 272 non-redundant phosphorylation sites in 11 222 proteins across eight organisms, including Aspergillus flavus, Aspergillus nidulans, Fusarium graminearum, Magnaporthe oryzae, Neurospora crassa, Saccharomyces cerevisiae, Schizosaccharomyces pombe, and Cryptococcus neoformans. A fungi-specific phosphothreonine motif and several conserved phosphorylation motifs were discovered by comparatively analysing the pattern of phosphorylation sites in plants, animals, and fungi.

Functional analyses of the versicolorin B synthase gene in Aspergillus flavus.

Aflatoxin is a toxic, carcinogenic mycotoxin primarily produced by Aspergillus parasiticus and Aspergillus flavus. Previous studies have predicted the existence of more than 20 genes in the gene cluster involved in aflatoxin biosynthesis. Among these genes, aflK encodes versicolorin B synthase, which converts versiconal to versicolorin B. Past research has investigated aflK in A. parasiticus, but few studies have characterized aflK in the animal, plant, and human pathogen A. flavus. To understand the potential role of aflK in A. flavus, its function was investigated here for the first time using gene replacement and gene complementation strategies. The aflK deletion-mutant ΔaflK exhibited a significant decrease in sclerotial production and aflatoxin biosynthesis compared with wild-type and the complementation strain ΔaflK::aflK. ΔaflK did not affect the ability of A. flavus to infect seeds, but downregulated aflatoxin production after seed infection. This is the first report of a relationship between aflK and sclerotial production in A. flavus, and our findings indicate that aflK regulates aflatoxin formation.

Data-driven event-by-event respiratory motion correction using TOF PET list-mode centroid of distribution.

Data-driven respiratory gating techniques were developed to correct for respiratory motion in PET studies, without the help of external motion tracking systems. Due to the greatly increased image noise in gated reconstructions, it is desirable to develop a data-driven event-by-event respiratory motion correction method. In this study, using the Centroid-of-distribution (COD) algorithm, we established a data-driven event-by-event respiratory motion correction technique using TOF PET list-mode data, and investigated its performance by comparing with an external system-based correction method. Ten human scans with the pancreatic ß-cell tracer 18F-FP-(+)-DTBZ were employed. Data-driven respiratory motions in superior-inferior (SI) and anterior-posterior (AP) directions were first determined by computing the centroid of all radioactive events during each short time frame with further processing. The Anzai belt system was employed to record respiratory motion in all studies. COD traces in both SI and AP directions were first compared with Anzai traces by computing the Pearson correlation coefficients. Then, respiratory gated reconstructions based on either COD or Anzai traces were performed to evaluate their relative performance in capturing respiratory motion. Finally, based on correlations of displacements of organ locations in all directions and COD information, continuous 3D internal organ motion in SI and AP directions was calculated based on COD traces to guide event-by-event respiratory motion correction in the MOLAR reconstruction framework. Continuous respiratory correction results based on COD were compared with that based on Anzai, and without motion correction. Data-driven COD traces showed a good correlation with Anzai in both SI and AP directions for the majority of studies, with correlation coefficients ranging from 63% to 89%. Based on the determined respiratory displacements of pancreas between end-expiration and end-inspiration from gated reconstructions, there was no significant difference between COD-based and Anzai-based methods. Finally, data-driven COD-based event-by-event respiratory motion correction yielded comparable results to that based on Anzai respiratory traces, in terms of contrast recovery and reduced motion-induced blur. Data-driven event-by-event respiratory motion correction using COD showed significant image quality improvement compared with reconstructions with no motion correction, and gave comparable results to the Anzai-based method.

Fully automatic multi-atlas segmentation of CTA for partial volume correction in cardiac SPECT/CT.

Anatomical-based partial volume correction (PVC) has been shown to improve image quality and quantitative accuracy in cardiac SPECT/CT. However, this method requires manual segmentation of various organs from contrast-enhanced computed tomography angiography (CTA) data. In order to achieve fully automatic CTA segmentation for clinical translation, we investigated the most common multi-atlas segmentation methods. We also modified the multi-atlas segmentation method by introducing a novel label fusion algorithm for multiple organ segmentation to eliminate overlap and gap voxels. To evaluate our proposed automatic segmentation, eight canine 99mTc-labeled red blood cell SPECT/CT datasets that incorporated PVC were analyzed, using the leave-one-out approach. The Dice similarity coefficient of each organ was computed. Compared to the conventional label fusion method, our proposed label fusion method effectively eliminated gaps and overlaps and improved the CTA segmentation accuracy. The anatomical-based PVC of cardiac SPECT images with automatic multi-atlas segmentation provided consistent image quality and quantitative estimation of intramyocardial blood volume, as compared to those derived using manual segmentation. In conclusion, our proposed automatic multi-atlas segmentation method of CTAs is feasible, practical, and facilitates anatomical-based PVC of cardiac SPECT/CT images.

Functional Analysis of the Nitrogen Metabolite Repression Regulator Gene nmrA in Aspergillus flavus.

In Aspergillus nidulans, the nitrogen metabolite repression (NMR) regulator NmrA plays a major role in regulating the activity of the GATA transcription factor AreA during nitrogen metabolism. However, the function of nmrA in A. flavus has not been previously studied. Here, we report the identification and functional analysis of nmrA in A. flavus. Our work showed that the amino acid sequences of NmrA are highly conserved among Aspergillus species and that A. flavus NmrA protein contains a canonical Rossmann fold motif. Deletion of nmrA slowed the growth of A. flavus but significantly increased conidiation and sclerotia production. Moreover, seed infection experiments indicated that nmrA is required for the invasive virulence of A. flavus. In addition, the ΔnmrA mutant showed increased sensitivity to rapamycin and methyl methanesulfonate, suggesting that nmrA could be responsive to target of rapamycin signaling and DNA damage. Furthermore, quantitative real-time reverse transcription polymerase chain reaction analysis suggested that nmrA might interact with other nitrogen regulatory and catabolic genes. Our study provides a better understanding of NMR and the nitrogen metabolism network in fungi.

Global Phosphoproteomic Analysis Reveals the Involvement of Phosphorylation in Aflatoxins Biosynthesis in the Pathogenic Fungus Aspergillus flavus.

Aspergillus flavus is a pathogenic fungus that produces toxic and carcinogenic aflatoxins and is the causative agent of aflatoxicosis. A growing body of evidence indicates that reversible phosphorylation plays important roles in regulating diverse functions in this pathogen. However, only a few phosphoproteins of this fungus have been identified, which hampers our understanding of the roles of phosphorylation in A. flavus. So we performed a global and site-specific phosphoproteomic analysis of A. flavus. A total of 598 high-confidence phosphorylation sites were identified in 283 phosphoproteins. The identified phosphoproteins were involved in various biological processes, including signal transduction and aflatoxins biosynthesis. Five identified phosphoproteins associated with MAPK signal transduction and aflatoxins biosynthesis were validated by immunoblotting using phospho-specific antibodies. Further functional studies revealed that phosphorylation of the MAP kinase kinase kinase Ste11 affected aflatoxins biosynthesis in A. flavus. Our data represent the results of the first global survey of protein phosphorylation in A. flavus and reveal previously unappreciated roles for phosphorylation in the regulation of aflatoxins production. The generated dataset can serve as an important resource for the functional analysis of protein phosphorylation in A. flavus and facilitate the elucidation of phosphorylated signaling networks in this pathogen.

Effects of reflector and crystal surface on the performance of a depth-encoding PET detector with dual-ended readout.

PURPOSE: Depth encoding detectors are required to improve the spatial resolution and spatial resolution uniformity of small animal positron emission tomography (PET) scanners, as well as dedicated breast and brain scanners. Depth of interaction (DOI) can be measured by using dual-ended readout of lutetium oxyorthosilicate (LSO) scintillator arrays with position-sensitive avalanche photodiodes. Inter-crystal reflectors and crystal surface treatments play important roles in determining the performance of dual-ended detectors. In this paper, the authors evaluated five LSO arrays made with three different intercrystal reflectors and with either polished or unpolished crystal surfaces. METHODS: The crystal size in all arrays was 1.5 mm, which is typical of the detector size used in small animal and dedicated breast scanners. The LSO arrays were measured with dual-ended readout and were compared in terms of flood histogram, energy resolution, and DOI resolution performance. RESULTS: The four arrays using enhanced specular reflector (ESR) and Toray reflector provided similar quality flood histograms and the array using Crystal Wrap reflector gave the worst flood histogram. The two arrays using ESR reflector provided the best energy resolution and the array using Crystal Wrap reflector yielded the worst energy resolution. All arrays except the polished ESR array provided good DOI resolution ranging from 1.9 mm to 2.9 mm. DOI resolution improved as the gradient in light collection efficiency with depth (GLCED) increased. The geometric mean energies were also calculated for these dual-ended readout detectors as an alternative to the conventional summed total energy. It was shown that the geometric mean energy is advantageous in that it provides more uniform photopeak amplitude at different depths for arrays with high GLCED, and is beneficial in event selection by allowing a fixed energy window independent of depth. A new method of DOI calculation that improved the linearity of DOI ratio vs depth and simplifies the DOI calibration procedure also was developed and tested. CONCLUSIONS: The results of these studies provide useful guidance in selecting the proper reflectors and crystal surface treatments when LSO arrays are used for high-resolution PET applications in small animal scanners or dedicated breast and brain scanners.