3D dictionary learning based iterative cone beam CT reconstruction

Purpose: This work is to develop a 3D dictionary learning based cone beam CT (CBCT) reconstruction algorithm on graphic processing units (GPU) to improve the quality of sparse-view CBCT reconstruction with high efficiency. Methods: A 3D dictionary containing 256 small volumes (atoms) of 3 × 3 × 3 was trained from a large number of blocks extracted from a high quality volume image. On the basis, we utilized cholesky decomposition based orthogonal matching pursuit algorithm to find the sparse representation of each block. To accelerate the time-consuming sparse coding in the 3D case, we implemented the sparse coding in a parallel fashion by taking advantage of the tremendous computational power of GPU. Conjugate gradient least square algorithm was adopted to minimize the data fidelity term. Evaluations are performed based on a head-neck patient case. FDK reconstruction with full dataset of 364 projections is used as the reference. We compared the proposed 3D dictionary learning based method with tight frame (TF) by performing reconstructions on a subset data of 121 projections. Results: Compared to TF based CBCT reconstruction that shows good overall performance, our experiments indicated that 3D dictionary learning based CBCT reconstruction is able to recover finer structures, remove more streaking artifacts and also induce less blocky artifacts. Conclusion: 3D dictionary learning based CBCT reconstruction algorithm is able to sense the structural information while suppress the noise, and hence to achieve high quality reconstruction under the case of sparse view. The GPU realization of the whole algorithm offers a significant efficiency enhancement, making this algorithm more feasible for potential clinical application.-------------------------------Cite this article as: Bai T, Yan H, Shi F, Jia X, Lou Y, Xu Q, Jiang S, Mou X. 3D dictionary learning based iterative cone beam CT reconstruction. Int J Cancer Ther Oncol 2014; 2(2):020240. DOI: 10.14319/ijcto.0202.4

Current landscape of fecal microbiota transplantation in treating depression

Depression, projected to be the predominant contributor to the global disease burden, is a complex condition with diverse symptoms including mood disturbances and cognitive impairments. Traditional treatments such as medication and psychotherapy often fall short, prompting the pursuit of alternative interventions. Recent research has highlighted the significant role of gut microbiota in mental health, influencing emotional and neural regulation. Fecal microbiota transplantation (FMT), the infusion of fecal matter from a healthy donor into the gut of a patient, emerges as a promising strategy to ameliorate depressive symptoms by restoring gut microbial balance. The microbial-gut-brain (MGB) axis represents a critical pathway through which to potentially rectify dysbiosis and modulate neuropsychiatric outcomes. Preclinical studies reveal that FMT can enhance neurochemicals and reduce inflammatory markers, thereby alleviating depressive behaviors. Moreover, FMT has shown promise in clinical settings, improving gastrointestinal symptoms and overall quality of life in patients with depression. The review highlights the role of the gut-brain axis in depression and the need for further research to validate the long-term safety and efficacy of FMT, identify specific therapeutic microbial strains, and develop targeted microbial modulation strategies. Advancing our understanding of FMT could revolutionize depression treatment, shifting the paradigm toward microbiome-targeting therapies

Prognostic significance of COX-2 immunohistochemical expression in colorectal cancer: a meta-analysis of the literature.

BACKGROUND: Cyclooxygenase-2 (COX-2) is believed to be an important enzyme in the pathogenesis of colorectal cancer (CRC). Correlations between the expression of COX-2 with tumor growth and distant metastasis have become an issue; thus, attention has been paid to COX-2 as a prognostic factor. Various studies examined the relationship between COX-2 immunohistochemistry (IHC) overexpression with the clinical outcome in patients with colorectal cancer, but yielded conflicting results. The prognostic significance of COX-2 overexpression in colorectal cancer remains controversial. METHODS: Electronic databases updated to October 2012 were searched to find relevant studies. A meta-analysis was conducted with eligible studies which quantitatively evaluated the relationship between COX-2 overexpression and survival of patients with colorectal cancer. Survival data were aggregated and quantitatively analyzed. RESULTS: We performed a meta-analysis of 23 studies (n  =  4567 patients) that evaluated the correlation between COX-2 overexpression detected by IHC and survival in patients with colorectal cancer. Combined hazard ratios suggested that COX-2 overexpression had an unfavorable impact on overall survival (OS) (HR [hazard ratio]  =  1.193, 95% CI [confidence interval]: 1.02 ∼ 1.37), but not disease free survival (DFS) (HR  =  1.25, 95% CI: 0.99 ∼ 1.50) in patients with colorectal cancer. CONCLUSIONS: Cox-2 overexpression in colorectal cancer detected by IHC appears to have slightly worse overall survival. However, the prognostic value of COX-2 on survival in colorectal cancer still needs further large-scale prospective trials to be clarified

Transformer based multiple coupled LC tanks for on-chip VCO design and applications

A transformer based multiple coupled LC tanks model for on-chip VCO design is introduced. The merits of adoption multiple coupled LC tanks can be Q factor enhancement for the equivalent LC tank of VCO, low power consumption, better amplitude swing and broad tuning range can be obtained. As an illustration case two low power Ku band VCOs using dual LC-tanks with/without feedback designed using a 0.18 μm BiCMOS process for low phase noise or wide tuning range are demonstrated