Visually evaluating drug efficacy in living cells using COF-based fluorescent nanoprobe via CHA amplified detection of miRNA and simultaneous apoptosis imaging.

BACKGROUNDS: Cancer is a highly fatal disease which is close relative of miRNA aberrant expression and apoptosis disorders. Elucidation of the therapeutic efficacy through investigating the changes in miRNA and apoptosis holds immense importance in advancing the development of miRNA-based precision therapy. However, it remains a challenge as how to visually evaluate the efficacy during protocol optimization of miRNA-based anticancer drugs at the cellular level. Therefore, exploring effective and noninvasive methods for real-time monitoring of therapeutic efficacy in living cells is of great significance. RESULTS: Herein, we reported a novel fluorescent nanoprobe COF-H1/H2-Peptide for visually evaluating drug efficacy in living cells through amplified imaging of low-abundant miRNA-221 with catalytic hairpin assembly (CHA) circle amplification, as well as simultaneous caspase-3 imaging. With strong stability and good biocompatibility, this newly fabricated amplified nanoprobe showed high sensitivity and specificity for the detection of miRNA-221 and caspase-3, and the limit of detection (LOD) of miRNA-221 was as low as 2.79 pM. The fluorescent imaging results showed that this amplified nanoprobe could not only detect caspase-3 in living cells, but also effectively detect low levels of miRNA-221 with increasing anticancer drug concentration and treatment time. The smart nanoprobe had effective performance for optimizing miRNA-based drug treatment schedules by dual-color fluorescence imaging. SIGNIFICANCE: This nanoprobe combined CHA amplified detection of intracellular miRNA-221 and synchronous apoptosis imaging, with excellent sensitivity for the detection of cellular low-level miRNA, enabling the realization of real-time assessment of the efficacy of miRNA-based therapy in living cells. This work presents a promising approach for revealing the regulatory mechanisms between miRNAs and apoptosis in cancer occurrence, development, and treatment.

Association between per- and polyfluoroalkyl substances and risk of hypertension: a systematic review and meta-analysis.

Background: Existing evidence indicates that exposure to per- and polyfluoroalkyl substances (PFASs) may increase the risk of hypertension, but the findings are inconsistent. Therefore, we aimed to explore the relationship between PFASs and hypertension through this systematic review and meta-analysis. Methods: We searched PubMed, Embase, and the Web of Science databases for articles published in English that examined the relationship between PFASs and hypertension before 13 August 2022. The random effects model was used to aggregate the evaluation using Stata 15.0 for Windows. We also conducted subgroup analyses by region and hypertension definition. In addition, a sensitivity analysis was carried out to determine the robustness of the findings. Results: The meta-analysis comprised 15 studies in total with 69,949 individuals. The risk of hypertension was substantially and positively correlated with exposure to perfluorooctane sulfonate (PFOS) (OR = 1.31, 95% CI: 1.14, 1.51), perfluorooctanoic acid (PFOA) (OR = 1.16, 95% CI: 1.07, 1.26), and perfluorohexane sulfonate (PFHxS) (OR = 1.04, 95% CI: 1.00, 1.09). However, perfluorononanoic acid (PFNA) exposure and hypertension were not significantly associated (OR = 1.08, 95% CI: 0.99, 1.17). Conclusion: We evaluated the link between PFASs exposure and hypertension and discovered that higher levels of PFOS, PFOA, and PFHxS were correlated with an increased risk of hypertension. However, further high-quality population-based and pathophysiological investigations are required to shed light on the possible mechanism and demonstrate causation because of the considerable variability. Systematic review registration: https://www.crd.york.ac.uk/prospero/ PROSPERO, registration number: CRD 42022358142.

A Highly Pipelined and Highly Parallel VLSI Architecture of CABAC Encoder for UHDTV Applications.

Recently, specifically designed video codecs have been preferred due to the expansion of video data in Internet of Things (IoT) devices. Context Adaptive Binary Arithmetic Coding (CABAC) is the entropy coding module widely used in recent video coding standards such as HEVC/H.265 and VVC/H.266. CABAC is a well known throughput bottleneck due to its strong data dependencies. Because the required context model of the current bin often depends on the results of the previous bin, the context model cannot be prefetched early enough and then results in pipeline stalls. To solve this problem, we propose a prediction-based context model prefetching strategy, effectively eliminating the clock consumption of the contextual model for accessing data in memory. Moreover, we offer multi-result context model update (MCMU) to reduce the critical path delay of context model updates in multi-bin/clock architecture. Furthermore, we apply pre-range update and pre-renormalize techniques to reduce the multiplex BAE's route delay due to the incomplete reliance on the encoding process. Moreover, to further speed up the processing, we propose to process four regular and several bypass bins in parallel with a variable bypass bin incorporation (VBBI) technique. Finally, a quad-loop cache is developed to improve the compatibility of data interactions between the entropy encoder and other video encoder modules. As a result, the pipeline architecture based on the context model prefetching strategy can remove up to 45.66% of the coding time due to stalls of the regular bin, and the parallel architecture can also save 29.25% of the coding time due to model update on average under the condition that the Quantization Parameter (QP) is equal to 22. At the same time, the throughput of our proposed parallel architecture can reach 2191 Mbin/s, which is sufficient to meet the requirements of 8 K Ultra High Definition Television (UHDTV). Additionally, the hardware efficiency (Mbins/s per k gates) of the proposed architecture is higher than that of existing advanced pipeline and parallel architectures.

QA-Filter: A QP-Adaptive Convolutional Neural Network Filter for Video Coding.

Convolutional neural network (CNN)-based filters have achieved great success in video coding. However, in most previous works, individual models were needed for each quantization parameter (QP) band, which is impractical due to limited storage resources. To explore this, our work consists of two parts. First, we propose a frequency and spatial QP-adaptive mechanism (FSQAM), which can be directly applied to the (vanilla) convolution to help any CNN filter handle different quantization noise. From the frequency domain, a FQAM that introduces the quantization step (Qstep) into the convolution is proposed. When the quantization noise increases, the ability of the CNN filter to suppress noise improves. Moreover, SQAM is further designed to compensate for the FQAM from the spatial domain. Second, based on FSQAM, a QP-adaptive CNN filter called QA-Filter that can be used under a wide range of QP is proposed. By factorizing the mixed features to high-frequency and low-frequency parts with the pair of pooling and upsampling operations, the QA-Filter and FQAM can promote each other to obtain better performance. Compared to the H.266/VVC baseline, average 5.25% and 3.84% BD-rate reductions for luma are achieved by QA-Filter with default all-intra (AI) and random-access (RA) configurations, respectively. Additionally, an up to 9.16% BD-rate reduction is achieved on the luma of sequence BasketballDrill. Besides, FSQAM achieves measurably better BD-rate performance compared with the previous QP map method.

Integrating analysis of circular RNA and mRNA expression profiles in doxorubicin induced cardiotoxicity mice.

Doxorubicin (DOX)-induced cardiotoxicity impedes its clinical application, but the mechanisms have not been thoroughly elucidated. Based on circRNA and mRNA expression profiles, we illustrated RNA expression signature changes during DOX-induced cardiotoxicity; mechanism exploration and biomarkers screening were also conducted. Twelve mice were randomly divided into two groups, induction group was treated with doxorubicin, and the control group was given an equal quantity of saline. After the confirmation of myocardial injury in induction group, the heart tissues from both groups were isolated for RNA high-throughput sequencing. The expression profiles were compared between the two groups; a total of 295 mRNAs and 11 circRNAs were shown as biased expression in DOX-induced cardiotoxicity mouse hearts. The dysregulation of three circRNAs were validated by quantitative real-time PCR: mmu_circ_0015773, mmu_circ_0002106, and mmu_circ_001606. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the differentially expressed RNAs were performed; the results implied that DOX might cause cardiotoxicity by interfering hemoglobin-based oxygen delivery and DNA-associated signal pathways. We integrated the differential expressed mRNA and validated circRNAs by constructing a competing endogenous RNA (ceRNA) network, which indicated that the alteration of the three circRNAs could activate apoptosis process of myocardial cells. This study provided novel insight into the mechanisms of DOX induced cardiotoxicity, and potential biomarkers or therapeutic targets were also proposed.