Opposing roles of HDAC6 in liver regeneration and hepatocarcinogenesis.

Histone deacetylase 6 (HDAC6), a deacetylase of p53, has emerged as a privileged inhibitory target for cancer therapy because of its deacetylating activity for p53 at K120 and K373/382. However, intricate roles of HDAC6 in hepatocellular carcinogenesis have been suggested by recent evidence, namely that HDAC6 ablation suppresses innate immunity, which plays critical roles in tumor immunosurveillance and antitumor immune responses. Therefore, it is valuable to determine whether HDAC6 ablation inhibits hepatocellular carcinogenesis using in vivo animal models. Here, we firstly showed that HDAC6 ablation increased K320 acetylation of p53, known as pro-survival acetylation, in all tested animal models but did not always increase K120 and K373/382 acetylation of p53, known as pro-apoptotic acetylation. HDAC6 ablation induced cellular senescence in primary MEFs and inhibited cell proliferation in HepG2 cells and liver regeneration after two-thirds partial hepatectomy. However, the genetic ablation of HDAC6 did not inhibit hepatocarcinogenesis, but instead slightly enhanced it in two independent mouse models (DEN + HFD and DEN + TAA). Notably, HDAC6 ablation significantly promoted hepatocarcinogenesis in a multiple DEN treatment hepatocellular carcinoma (HCC) mouse model, mimicking chronic DNA damage in the liver, which correlated with hyperacetylation at K320 of p53 and a decrease in inflammatory cytokines and chemokines. Our data from three independent in vivo animal HCC models emphasize the importance of the complex roles of HDAC6 ablation in hepatocellular carcinogenesis, highlighting its immunosuppressive effects.

Machine learning-enhanced gesture recognition through impedance signal analysis.

Gesture recognition is a crucial aspect in the advancement of virtual reality, healthcare, and human-computer interaction, and requires innovative methodologies to meet the increasing demands for precision. This paper presents a novel approach that combines Impedance Signal Spectrum Analysis (ISSA) with machine learning to improve gesture recognition precision. A diverse dataset that included participants from various demographic backgrounds (five individuals) who were each executing a range of predefined gestures. The predefined gestures were designed to encompass a broad spectrum of hand movements, including intricate and subtle variations, to challenge the robustness of the proposed methodology. The machine learning model using the K-Nearest Neighbors (KNN), Gradient Boosting Machine (GBM), Naive Bayes (NB), Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM) algorithms demonstrated notable precision in performance evaluations. The individual accuracy values for each algorithm are as follows: KNN, 86%; GBM, 86%; NB, 84%; LR, 89%; RF, 87%; and SVM, 87%. These results emphasize the importance of impedance features in the refinement of gesture recognition. The adaptability of the model was confirmed under different conditions, highlighting its broad applicability.

Three-dimensional imaging through turbid media using deep learning: NIR transillumination imaging of animal bodies.

Using near-infrared (NIR) light with 700-1200 nm wavelength, transillumination images of small animals and thin parts of a human body such as a hand or foot can be obtained. They are two-dimensional (2D) images of internal absorbing structures in a turbid medium. A three-dimensional (3D) see-through image is obtainable if one can identify the depth of each part of the structure in the 2D image. Nevertheless, the obtained transillumination images are blurred severely because of the strong scattering in the turbid medium. Moreover, ascertaining the structure depth from a 2D transillumination image is difficult. To overcome these shortcomings, we have developed a new technique using deep learning principles. A fully convolutional network (FCN) was trained with 5,000 training pairs of clear and blurred images. Also, a convolutional neural network (CNN) was trained with 42,000 training pairs of blurred images and corresponding depths in a turbid medium. Numerous training images were provided by the convolution with a point spread function derived from diffusion approximation to the radiative transport equation. The validity of the proposed technique was confirmed through simulation. Experiments demonstrated its applicability. This technique can provide a new tool for the NIR imaging of animal bodies and biometric authentication of a human body.

Three-dimensional transillumination image reconstruction for small animal with new scattering suppression technique.

To realize three-dimensional (3D) optical imaging of the internal structure of an animal body, we have developed a new technique to reconstruct optical computed tomography (optical CT) images from two-dimensional (2D) transillumination images. In transillumination imaging of an animal body using near-infrared light, the image is blurred because of the strong scattering in the tissue. To overcome this problem, we propose a novel technique to apply the point spread function (PSF) for a light source located inside the medium to the transilluminated image of light-absorbing structure. The problem of the depth-dependence of PSF was solved in the calculation of the projection image in the filtered back-projection method. The effectiveness of the proposed technique was assessed in the experiments with a model phantom and a mouse. These analyses verified the feasibility of the practical 3D imaging of the internal light-absorbing structure of a small animal.

Application of fluorescent PSF for 3D reconstruction of absorbing structure using slab transillumination images.

In transillumination imaging of an animal body using near-infrared light, the image is blurred due to the strong scattering in the tissue. We have devised the depth-dependent point spread function (PSF) to suppress the scattering effect in fluorescent imaging. In this study, we applied this principle and developed a technique to reconstruct the absorbing structure in turbid medium without using fluorescent material. In experiments, the feasibility and effectiveness of the proposed technique were verified.