Low-dose X-ray computed tomography (CT) simulation from high-dose scan is required in optimizing radiation dose to patients. In this study, we propose a simple low-dose CT simulation strategy in sinogram domain using the raw data from high-dose scan. Specially, a relationship between the incident fluxes of low- and high- dose scans is first determined according to the repeated projection measurements and analysis. Second, the incident flux level of the simulated low-dose scan is generated by properly scaling the incident flux level of high-dose scan via the determined relationship in the first step. Third, the low-dose CT transmission data by energy integrating detection is simulated by adding a statistically independent Poisson noise distribution plus a statistically independent Gaussian noise distribution. Finally, a filtered back-projection (FBP) algorithm is implemented to reconstruct the resultant low-dose CT images. The present low-dose simulation strategy is verified on the simulations and real scans by comparing it with the existing low-dose CT simulation tool. Experimental results demonstrated that the present low-dose CT simulation strategy can generate accurate low-dose CT sinogram data from high-dose scan in terms of qualitative and quantitative measurements.
Restricted by the hardware, the projection number at a single phase for 4D-CBCT imaging is very low or even less than 10, thus the associated reconstruction by using conventional reconstruction algorithms will be constrained by serious streak artifacts and noises. To address this problem, in this paper, we are aiming to develop an approach to reconstruct the 4D-CBCT image with multi-phase projections, which means that when the images at one phase were estimated not only from the projection data of the current phase but also the projections at the other phases. The proposed approach is based on the assumption that the image at one phase can be viewed as the motion-compensated image of another phase. Specifically, in this work, we formulate a cost function using multi-phase projections to construct the fidelity term and the TV regularization method was adopted. The Gradient-Projection-Barzilai-Linesearch (GPBL) method was used to optimize the complex cost function. Physical phantom and real patient data were used to evaluate the proposed algorithm. Results show that the proposed approach can effectively reduce the noise and artifacts, which suggest that the introduction of additional temporal correlation (along the phase direction) can improve the 4D-CBCT image quality.
Serine-rich repeat glycoproteins (SRRPs) are conserved in Gram-positive bacteria. They are crucial for modulating biofilm formation and bacterial-host interactions. Glycosylation of SRRPs plays a pivotal role in the process; thus understanding the glycosyltransferases involved is key to identifying new therapeutic drug targets. The glycosylation of Fap1, an SRRP of Streptococcus parasanguinis, is mediated by a gene cluster consisting of six genes: gtf1, gtf2, gly, gtf3, dGT1, and galT2. Mature Fap1 glycan possesses the sequence of Rha1–3Glc1-(Glc1–3GlcNAc1)-2,6-Glc1–6GlcNAc. Gtf12, Gtf3, and dGT1 are responsible for the first four steps of the Fap1 glycosylation, catalyzing the transfer of GlcNAc, Glc, Glc, and GlcNAc residues to the protein backbone sequentially. The role of GalT2 and Gly in the Fap1 glycosylation is unknown. In the present study, we synthesized the fully modified Fap1 glycan in Escherichia coli by incorporating all six genes from the cluster. This study represents the first reconstitution of an exogenous stepwise O-glycosylation synthetic pathway in E. coli. In addition, we have determined that GalT2 mediates the fifth step of the Fap1 glycosylation by adding a rhamnose residue, and Gly mediates the final glycosylation step by transferring glucosyl residues. Furthermore, inactivation of each glycosyltransferase gene resulted in differentially impaired biofilms of S. parasanguinis, demonstrating the importance of Fap1 glycosylation in the biofilm formation. The Fap1 glycosylation system offers an excellent model to engineer glycans using different permutations of glycosyltransferases and to investigate biosynthetic pathways of SRRPs because SRRP genetic loci are highly conserved. Serine-rich repeat glycoproteins (SRRPs) are conserved in Gram-positive bacteria. They are crucial for modulating biofilm formation and bacterial-host interactions. Glycosylation of SRRPs plays a pivotal role in the process; thus understanding the glycosyltransferases involved is key to identifying new therapeutic drug targets. The glycosylation of Fap1, an SRRP of Streptococcus parasanguinis, is mediated by a gene cluster consisting of six genes: gtf1, gtf2, gly, gtf3, dGT1, and galT2. Mature Fap1 glycan possesses the sequence of Rha1–3Glc1-(Glc1–3GlcNAc1)-2,6-Glc1–6GlcNAc. Gtf12, Gtf3, and dGT1 are responsible for the first four steps of the Fap1 glycosylation, catalyzing the transfer of GlcNAc, Glc, Glc, and GlcNAc residues to the protein backbone sequentially. The role of GalT2 and Gly in the Fap1 glycosylation is unknown. In the present study, we synthesized the fully modified Fap1 glycan in Escherichia coli by incorporating all six genes from the cluster. This study represents the first reconstitution of an exogenous stepwise O-glycosylation synthetic pathway in E. coli. In addition, we have determined that GalT2 mediates the fifth step of the Fap1 glycosylation by adding a rhamnose residue, and Gly mediates the final glycosylation step by transferring glucosyl residues. Furthermore, inactivation of each glycosyltransferase gene resulted in differentially impaired biofilms of S. parasanguinis, demonstrating the importance of Fap1 glycosylation in the biofilm formation. The Fap1 glycosylation system offers an excellent model to engineer glycans using different permutations of glycosyltransferases and to investigate biosynthetic pathways of SRRPs because SRRP genetic loci are highly conserved. Engineering and dissecting the glycosylation pathway of a streptococcal serine-rich repeat adhesion.Journal of Biological ChemistryVol. 293Issue 13PreviewVOLUME 291 (2016) PAGES 27354–27363 Full-Text PDF Open Access
Summary Millions of people die from liver diseases annually, and liver failure is one of the three major outcomes of liver disease. The gut microbiota plays a crucial role in liver diseases. This study aimed to explore the effects of Lactobacillus casei strain Shirota (LcS), a probiotics used widely around the world, on acute liver injury (ALI), as well as the underlying mechanism. Sprague Dawley rats were intragastrically administered LcS suspensions or placebo once daily for 7 days before induction of ALI by intraperitoneal injection of D‐galactosamine (D‐GalN). Histopathological examination and assessments of liver biochemical markers, inflammatory cytokines, and the gut microbiota, metabolome and transcriptome were conducted. Our results showed that pretreatment with LcS reduced hepatic and intestinal damage and reduced the elevation of serum gamma‐glutamyltranspeptidase (GGT), total bile acids, IL‐5, IL‐10, G‐CSF and RANTES. The analysis of the gut microbiota, metabolome and transcriptome showed that LcS lowered the ratio of Firmicutes to Bacteroidetes; reduced the enrichment of metabolites such as chenodeoxycholic acid, deoxycholic acid, lithocholic acid, d ‐talose and N ‐acetyl‐glucosamine, reduce the depletion of d ‐glucose and l ‐methionine; and alleviated the downregulation of retinol metabolism and PPAR signalling and the upregulation of the pyruvate metabolism pathway in the liver. These results indicate the promising prospect of using LcS for the treatment of liver diseases, particularly ALI.
Abstract Anti-PD-1 immunotherapy has saved numerous lives of cancer patients; however, it only exerts efficacy in 10-15% of patients with colorectal cancer. Fecal microbiota transplantation (FMT) is a potential approach to improving the efficacy of anti-PD-1 therapy, whereas the detailed mechanisms and the applicability of this combination therapy remain unclear. In this study, we evaluated the synergistic effect of FMT with anti-PD-1 in curing colorectal tumor-bearing mice using a multi-omics approach. Mice treated with the combination therapy showed superior survival rate and tumor control, compared to the mice received anti-PD-1 therapy or FMT alone. Metagenomic analysis showed that composition of gut microbiota in tumor-bearing mice treated with anti-PD-1 therapy was remarkably altered through receiving FMT. Particularly, Bacteroides genus, including FMT-increased B. thetaiotaomicron, B. fragilis , and FMT-decreased B. ovatus might contribute to the enhanced efficacy of anti-PD-1 therapy. Furthermore, metabolomic analysis upon mouse plasma revealed several potential metabolites that upregulated after FMT, including punicic acid and aspirin, might promote the response to anti-PD-1 therapy via their immunomodulatory functions. This work broadens our understanding of the mechanism by which FMT improves the efficacy of anti-PD-1 therapy, which may contribute to the development of novel microbiota-based anti-cancer therapies.
Multienergy computed tomography (MECT) has the potential to simultaneously offer multiple sets of energy- selective data belonging to specific energy windows. However, because sufficient photon counts are not available in the specific energy windows compared with that in the whole energy window, the MECT images reconstructed by the analytical approach often suffer from poor signal-to-noise (SNR) and strong streak artifacts. To eliminate this drawback, in this work we present a penalized weighted least-squares (PWLS) scheme by incorporating the new concept of structure tensor total variation (STV) regularization to improve the MECT images quality from low-milliampere-seconds (low-mAs) data acquisitions. Henceforth the present scheme is referred to as `PWLS- STV' for simplicity. Specifically, the STV regularization is derived by penalizing the eigenvalues of the structure tensor of every point in the MECT images. Thus it can provide more robust measures of image variation, which can eliminate the patchy artifacts often observed in total variation regularization. Subsequently, an alternating optimization algorithm was adopted to minimize the objective function. Experiments with a digital XCAT phantom clearly demonstrate that the present PWLS-STV algorithm can achieve more gains than the existing TV-based algorithms and the conventional filtered backpeojection (FBP) algorithm in terms of noise-induced artifacts suppression, resolution preservation, and material decomposition assessment.
Background Acute rejection (AR) remains a life-threatening complication after orthotopic liver transplantation (OLT) and there are few available diagnostic biomarkers clinically for AR. This study aims to identify intestinal microbial profile and explore potential application of microbial profile as a biomarker for AR after OLT. Methods The OLT models in rats were established. Hepatic graft histology, ultrastructure, function, and intestinal barrier function were tested. Ileocecal contents were collected for intestinal microbial analysis. Results Hepatic graft suffered from the ischemia-reperfusion (I/R) injury on day 1, initial AR on day 3, and severe AR on day 7 after OLT. Real-time quantitative polymerase chain reaction results showed that genus Faecalibacterium prausnitzii and Lactobacillus were decreased, whereas Clostridium bolteae was increased during AR. Notably, cluster analysis of denaturing gradient gel electrophoresis (DGGE) profiles showed the 7AR and 3AR groups clustered together with 73.4% similarity, suggesting that intestinal microbiota was more sensitive than hepatic function in responding to AR. Microbial diversity and species richness were decreased during AR. Phylogenetic tree analysis showed that most of the decreased key bacteria belonged to phylum Firmicutes, whereas increased key bacteria belonged to phylum Bacteroidetes. Moreover, intestinal microvilli loss and tight junction damage were noted, and intestinal barrier dysfunction during AR presented a decrease of fecal secretory immunoglobulin A (sIgA) and increase of blood bacteremia, endotoxin, and tumor necrosis factor-α. Conclusion We dynamically detail intestinal microbial characterization and find a high sensitivity of microbial change during AR after OLT, suggesting that intestinal microbial variation may predict AR in early phase and become an assistant therapeutic target to improve rejection after OLT.
Dynamic imaging (such as computed tomography (CT) perfusion, dynamic CT angiography, dynamic positron emission tomography, four-dimensional CT, etc.) is widely used in the clinic. The multiple-scan mechanism of dynamic imaging results in greatly increased radiation dose and prolonged acquisition time. To deal with these problems, low-mAs or sparse-view protocols are usually adopted, which lead to noisy or incomplete data for each frame. To obtain high-quality images from the corrupted data, a popular strategy is to incorporate the composite image that reconstructed using the full dataset into the iterative reconstruction procedure. Previous studies have tried to enforce each frame to approach the composite image in each iteration, which, however, introduces mixed temporal information into each frame. In this paper, we propose an average consistency (AC) model for dynamic CT image reconstruction. The core idea of AC is to enforce the average of all frames to approach the composite image in each iteration, which preserves image edges and noise characteristics while avoids the invasion of mixed temporal information. Experiment on a dynamic phantom and a patient for CT perfusion imaging shows that the proposed method obtains the best qualitative and quantitative results. We conclude that the AC model is a general framework and a superior way of using the composite image for dynamic CT reconstruction.
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