A fine-grained reversible data hiding in encrypted domain based on the cipher-text redundancy of encryption process.

Considering the granularity of embedded data in the design of reversible data hiding scheme has important research significance for the permission control and management of multi-granularity information. To broaden the application possibilities of encrypted data in cloud environments, the researchers propose a fine-grained reversible data hiding method leveraging the cipher-text redundancy of ElGamal encryption. Initially, prior to the encryption process, pixels are organized into a full binary tree based on fine-grained access permissions. Subsequently, a chaotic sequence generator is employed to assign distinct embedding keys to each layer of the full binary tree according to the access permissions. Following this, an XOR operation is conducted between the embedding key and the corresponding secret information in each layer to derive the target features of the cipher-text, facilitating subsequent fine-grained data hiding. Throughout the ElGamal encryption process, iterative manipulation of the random variable ensures alignment between the cipher-text output and the target feature, enabling the embedding of secret information across different layers. This approach facilitates the fine-grained blind extraction of secret information from an encrypted state, thereby expanding the potential applications of cipher-text by extracting information without revealing the original data. Furthermore, the scheme enhances information security through distributed storage and conceals the presence of information hiding by leveraging the separability of lossless decryption and information extraction. Simulation results demonstrate that secret information of three granularities can be embedded and extracted without interference within a three-layer full binary structure, with a maximum embedding capacity of up to 1.75 bpp.

[Microneedles in diagnosis and treatment: a review].

Microneedles have been developed rapidly in the field of transdermal administration in the past few decades. In recent years, the development of microelectronics technology has expanded the applications of microneedles by combining with microelectronic systems, especially in biological diagnosis and treatment. Different types of microneedles have been designed to extract blood and tissue fluids for detection, or as electrodes to directly detect blood sugar, melanoma and pH in real-time in vivo, both show good prospects for real-time detection applications. In this paper, we review the design of materials and structure of microelectronic-based microneedles, and discuss their advances in biological diagnosis.

Knockdown of UCA1 restrains cell proliferation and metastasis of diffuse large B-cell lymphoma by counteracting miR-331-3p expression.

Long non-coding RNA urothelial cancer associated 1 (UCA1) has been reported to act as a carcinogen in bladder cancer, while its role in diffuse large B-cell lymphoma (DLBCL) remains unclear. The present study was designed to explore the expression pattern and role of UCA1 in DLBCL. The expression pattern of UCA1 and microRNA (miR)-331-3p in DLBCL tissues and cell lines were detected by RT-qPCR. Dual luciferase reporter assay was performed to explore the relationship between UCA1 and miR-331-3p. Cell proliferation was explored by MTT assay. Cell migration and invasion abilities were assessed by Transwell assay. In the present study, it was revealed that the expression of UCA1 was significantly upregulated, while miR-331-3p was downregulated in DLBCL tissues and cell lines. Moreover, UCA1 was revealed to competitively bind with miR-331-3p in DLBCL. Functionally, knockdown of UCA1 was revealed to suppress cell proliferation, migration and invasion in DLBCL cells. Furthermore, upregulation of miR-331-3p prevented cell proliferation, migration and invasion in DLBC cells. In conclusion, the present findings firstly demonstrated that UCA1 silencing restrained DLBCL cell proliferation and metastases viability by suppressing miR-331-3p expression. It is suggested that UCA1 could be a possible medicinal target and biomarker for DLBCL.

The delineation of largely deformed brain midline using regression-based line detection network.

PURPOSE: The human brain has two cerebral hemispheres that are roughly symmetric and separated by a midline, which is nearly a straight line shown in axial computed tomography (CT) images in healthy subjects. However, brain diseases such as hematoma and tumors often cause midline shift, where the degree of shift can be regarded as a quantitative indication in clinical practice. To facilitate clinical evaluation, we need computer-aided methods to automate this quantification. Nevertheless, most existing studies focused on the landmark- or symmetry-based methods that provide only the existence of shift or its maximum distance, which could be easily affected by anatomical variability and large brain deformations. Intuitive results such as midline delineation or measurement are lacking. In this study, we focus on developing an automated and robust method based on the fully convolutional neural network for the delineation of midline in largely deformed brains. METHODS: We propose a novel regression-based line detection network (RLDN) for the robust midline delineation, especially in largely deformed brains. Specifically, to improve the robustness of delineation in largely deformed brains, we regard the delineation of the midline as the skeleton extraction task and then use the multiscale bidirectional integration module to acquire more representative features. Based on the skeleton extraction, we incorporate the regression task into it to delineate more accurate and continuous midline, especially in largely deformed brains. Our study utilized the public CQ 500 dataset (128 subjects) for training with hold-out validation on 61 subjects from a private cohort accrued from a local hospital. RESULTS: The mean line distance error and F1-score were 1.17 ± 0.72 mm with 0.78 on CQ 500 test set, and 4.15 ± 3.97 mm with 0.61 on the private dataset. Besides, significant differences (P < 0.05) were observed between our method and other comparative ones on these two datasets. CONCLUSIONS: This work provides a novel solution to acquire robust delineation of the midline, especially in largely deformed brains, and achieves state-of-the-art performance on the public and our private dataset, which makes it possible for automated diagnosis of relevant brain diseases in the future.

Polyinosinic-polycytidylic acid accelerates intestinal stem cell proliferation via modulating Myc expression.

It is well known that exposure of double-stranded RNA (dsRNA) to intestine immediately induces villus damage with severe diarrhea, which is mediated by toll-like receptor 3 signaling activation. However, the role of intestinal stem cells (ISCs) remains obscure during the pathology. In the present study, polyinosinic-polycytidylic acid (poly[I:C]), mimicking viral dsRNA, was used to establish intestinal damage model. Mice were acutely and chronically exposed to poly(I:C), and ISCs in jejunum were analyzed. The results showed that the height of villus was shorter 48 hr after acute poly(I:C) exposure compared with that of controls, while chronic poly(I:C) treatment increased both villus height and crypt depth in jejunum compared with control animals. The numbers of ISCs in jejunum were significantly increased after acute and chronic poly(I:C) exposure. Poly (I:C)-stimulated ISCs have stronger capacities to differentiate into intestine endocrine cells. Mechanistically, poly(I:C) treatment increased expression of Stat1 and Axin2 in the intestinal crypt, which was along with increased expression of Myc, Bcl2, and ISC proliferation. These findings suggest that dsRNA exposure could induce ISC proliferation to ameliorate dsRNA-induced intestinal injury.

[Preparation and quantitative analysis of methyl phenyl carbonate standard sample].

The preparation and quantitative analytical method for high-purity methyl phenyl carbonate (MPC) was developed. Dimethyl carbonate (DMC) and diphenyl carbonate (DPC) were firstly used as reactants to synthesize MPC catalyzed by TiO2/SiO2 because the disproportionation of MPC is reversible and the reverse reaction is thermodynamically favorable. The high-purity MPC standard sample was obtained by reduced pressure distillation and the removal of minor phenol with dilute sodium hydroxide solution. The qualitative analysis by gas chromatography-mass spectrometry (GC-MS) showed there were minor phenol and diphenyl carbonate in the MPC sample. The mass percent concentration of water in the MPC sample was 0.26%, which was determined by Karl Fischer titration. A gas chromatographic method with an OV-101 capillary column was established for quantifying the minor phenol and DPC in the MPC sample. The quantitative results showed the mass concentrations of phenol and DPC were 2.04% and 1.59%, respectively. The difficulty to analyze MPC, the intermediate product of the transesterification of DMC and phenol, was solved with the self-made MPC standard sample.

Development and optimization of a method for analysis of the products from the transesterification of dimethyl carbonate and phenol.

A high-purity sample of methyl phenyl carbonate (MPC) was obtained by developing a novel reaction route followed by a series of separation and purification procedures. Identification and quantification of the MPC sample (98.32%) was performed by a gas chromatography-mass spectrometry and Karl Fisher titration. The laboratory-prepared MPC was then used as a standard to optimize quantitative analysis of the products synthesized by transesterification of dimethyl carbonate and phenol. The advantage of the improved method was that MPC can be quantified directly rather than being calculated by subtracting the yield of diphenyl carbonate (DPC) and by-product anisole from the conversion of dimethyl carbonate (DMC). The resulting method was validated for linearity, precision, accuracy, detection limit, and quantification limit. With the improved method, simultaneous accurate quantification of DMC, MPC, DPC, phenol, and anisole in the transesterification products can be achieved. This enables evaluation of the activity and selectivity of different catalysts and control of the reaction processes.