miR-196a enhances polymerization of neuronal microfilaments through suppressing IMP3 and upregulating IGF2 in Huntington's disease.

Huntington's disease (HD) is one of the inheritable neurodegenerative diseases, and these diseases share several similar pathological characteristics, such as abnormal neuronal morphology. miR-196a is a potential target to provide neuroprotective functions, and has been reported to enhance polymerization of neuronal microtubules in HD. While microtubules and microfilaments are two important components of the neuronal cytoskeleton, whether miR-196a improves neuronal microfilaments is still unknown. Here, we identify insulin-like growth factor 2 mRNA binding protein 3 (IMP3), and show that miR-196a directly suppresses IMP3 to increase neurite outgrowth in neurons. In addition, IMP3 disturbs neurite outgrowth in vitro and in vivo, and worsens the microfilament polymerization. Moreover, insulin-like growth factor-II (IGF2) is identified as the downstream target of IMP3, and miR-196a downregulates IMP3 to upregulate IGF2, which increases microfilamental filopodia numbers and activates Cdc42 to increase neurite outgrowth. Besides, miR-196a increases neurite outgrowth through IGF2 in different HD models. Finally, higher expression of IMP3 and lower expression IGF2 are observed in HD transgenic mice and patients, and increase the formation of aggregates in the HD cell model. Taken together, miR-196a enhances polymerization of neuronal microfilaments through suppressing IMP3 and upregulating IGF2 in HD, supporting the neuroprotective functions of miR-196a through neuronal cytoskeleton in HD.

Increase in Akkermansiaceae in Gut Microbiota of Prostate Cancer-Bearing Mice.

Gut microbiota are reported to be associated with many diseases, including cancers. Several bacterial taxa have been shown to be associated with cancer development or response to treatment. However, longitudinal microbiota alterations during the development of cancers are relatively unexplored. To better understand how microbiota changes, we profiled the gut microbiota composition from prostate cancer-bearing mice and control mice at five different time points. Distinct gut microbiota differences were found between cancer-bearing mice and control mice. Akkermansiaceae was found to be significantly higher in the first three weeks in cancer-bearing mice, which implies its role in the early stage of cancer colonization. We also found that Bifidobacteriaceae and Enterococcaceae were more abundant in the second and last sampling week, respectively. The increments of Akkermansiaceae, Bifidobacteriaceae and Enterococcaceae were previously found to be associated with responses to immunotherapy, which suggests links between these bacteria families and cancers. Additionally, our function analysis showed that the bacterial taxa carrying steroid biosynthesis and butirosin and neomycin biosynthesis were increased, whereas those carrying naphthalene degradation decreased in cancer-bearing mice. Our work identified the bacteria taxa altered during prostate cancer progression and provided a resource of longitudinal microbiota profiles during cancer development in a mouse model.

The regulatory roles of microRNAs toward pathogenesis and treatments in Huntington's disease.

Huntington's disease (HD) is one of neurodegenerative diseases, and is defined as a monogenetic disease due to the mutation of Huntingtin gene. This disease affects several cellular functions in neurons, and further influences motor and cognitive ability, leading to the suffering of devastating symptoms in HD patients. MicroRNA (miRNA) is a non-coding RNA, and is responsible for gene regulation at post-transcriptional levels in cells. Since one miRNA targets to several downstream genes, it may regulate different pathways simultaneously. As a result, it raises a potential therapy for different diseases using miRNAs, especially for inherited diseases. In this review, we will not only introduce the update information of HD and miRNA, but also discuss the development of potential miRNA-based therapy in HD. With the understanding toward the progression of miRNA studies in HD, we anticipate it may provide an insight to treat this devastating disease, even applying to other genetic diseases.

Image reconstruction in phase-contrast tomography exploiting the second-order statistical properties of the projection data.

X-ray phase-contrast tomography (PCT) methods seek to quantitatively reconstruct separate images that depict an object's absorption and refractive contrasts. Most PCT reconstruction algorithms generally operate by explicitly or implicitly performing the decoupling of the projected absorption and phase properties at each tomographic view angle by use of a phase-retrieval formula. However, the presence of zero-frequency singularity in the Fourier-based phase retrieval formulas will lead to a strong noise amplification in the projection estimate and the subsequent refractive image obtained using conventional algorithms like filtered backprojection (FBP). Tomographic reconstruction by use of statistical methods can account for the noise model and a priori information, and thereby can produce images with better quality over conventional filtered backprojection algorithms. In this work, we demonstrate an iterative image reconstruction method that exploits the second-order statistical properties of the projection data can mitigate noise amplification in PCT. The autocovariance function of the reconstructed refractive images was empirically computed and shows smaller and shorter noise correlation compared to those obtained using the FBP and unweighted penalized least-squares methods. Concepts from statistical decision theory are applied to demonstrate that the statistical properties of images produced by our method can improve signal detectability.