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RNA binding proteins (RBPs) regulate nearly all post-transcriptional processes within cells. To fully understand RBP function, it is essential to identify their in vivo targets. Standard techniques for profiling RBP targets, such as crosslinking immunoprecipitation (CLIP) and its variants, are limited or suboptimal in some situations, e.g. when compatible antibodies are not available and when dealing with small cell populations such as neuronal subtypes and primary stem cells. This review summarizes and compares several genetic approaches recently designed to identify RBP targets in such circumstances. TRIBE (targets of RNA binding proteins identified by editing), RNA tagging, and STAMP (surveying targets by APOBEC-mediated profiling) are new genetic tools useful for the study of post-transcriptional regulation and RBP identification. We describe the underlying RNA base editing technology, recent applications, and therapeutic implications.

Vessel segmentation is critical for disease diagnosis and surgical planning. Recently, the vessel segmentation method based on deep learning has achieved outstanding performance. However, vessel segmentation remains challenging due to thin vessels with low contrast that easily lose spatial information in the traditional U-shaped segmentation network. To alleviate this problem, we propose a novel and straightforward full-resolution network (FR-UNet) that expands horizontally and vertically through a multiresolution convolution interactive mechanism while retaining full image resolution. In FR-UNet, the feature aggregation module integrates multiscale feature maps from adjacent stages to supplement high-level contextual information. The modified residual blocks continuously learn multiresolution representations to obtain a pixel-level accuracy prediction map. Moreover, we propose the dual-threshold iterative algorithm (DTI) to extract weak vessel pixels for improving vessel connectivity. The proposed method was evaluated on retinal vessel datasets (DRIVE, CHASE_DB1, and STARE) and coronary angiography datasets (DCA1 and CHUAC). The results demonstrate that FR-UNet outperforms state-of-the-art methods by achieving the highest Sen, AUC, F1, and IOU on most of the above-mentioned datasets with fewer parameters, and that DTI enhances vessel connectivity while greatly improving sensitivity. The code is available at: https://github.com/lseventeen/FR-UNet.

Background A variety of diabetes self-management instruments have been developed but few of them consist of the preparedness for diabetes self-management behavior. The novel psychometric evaluation tool “the LMC Skills, Confidence & Preparedness Index (SCPI)” measures three key aspects of a patient’s diabetes self-management: knowledge of the skill, confidence in being able to perform skill and preparedness to implement the skill. The objective of this study was to translate, adapt and validate the SCPI for use in Chinese adult patients with type 2 diabetes. Methods This study followed the guideline recommended by the American Academy of Orthopaedic Surgeons Evidence Based Medicine Committee (AAOS) to indigenize the scale. Forward and back translation, and cross-cultural language debugging were completed according to the recommended steps. A convenience sample of Chinese patients with type 2 diabetes (n = 375) were recruited from a university-affiliated hospital in Shanghai. The validity (criterion, discriminant validity, and construct validity), reliability (internal consistency and test–retest reliability) and the interpretability of the instrument were examined. The content validity was calculated by experts’ evaluation. Results The Chinese version of SCPI (C-SCPI) has good internal consistency with a Cronbach’s alpha of 0.92. The ceiling effects of the preparedness subscales is 21%. The criterion validity of three dimensions of C-SCPI was established with significantly moderate correlations between the DKT, DES-SF and SDSCA (p 2/df = 2.775, RMSEA = 0.069, CFI = 0.903, GFI = 0.873, TLI = 0.889, IFI = 0.904. The test–retest reliability coefficient was 0.61 (p Conclusion We established a Chinese version of SCPI through translation and cross-cultural adaptation. The C-SCPI is reliable and valid for assessment of the level of self-management in Chinese patients with type 2 diabetes.

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are two related neurodegenerative diseases that present with similar TDP-43 pathology in patient tissue. TDP-43 is an RNA-binding protein which forms aggregates in neurons of ALS and FTD patients as well as in a subset of patients diagnosed with other neurodegenerative diseases. Despite our understanding that TDP-43 is essential for many aspects of RNA metabolism, it remains obscure how TDP-43 dysfunction contributes to neurodegeneration. Interestingly, altered neuronal dendritic morphology is a common theme among several neurological disorders and is thought to precede neurodegeneration. We previously found that both TDP-43 overexpression (OE) and knockdown (KD) result in reduced dendritic branching of cortical neurons. In this study, we used TRIBE (targets of RNA-binding proteins identified by editing) as an approach to identify signaling pathways that regulate dendritic branching downstream of TDP-43. We found that TDP-43 RNA targets are enriched for pathways that signal to the CREB transcription factor. We further found that TDP-43 dysfunction inhibits CREB activation and CREB transcriptional output, and restoring CREB signaling rescues defects in dendritic branching. Finally, we demonstrate, using RNA sequencing, that TDP-43 OE and KD cause similar changes in the abundance of specific messenger RNAs, consistent with their ability to produce similar morphological defects. Our data therefore provide a mechanism by which TDP-43 dysfunction interferes with dendritic branching, and may define pathways for therapeutic intervention in neurodegenerative diseases.

With the development of e-commerce, delivery time is regarded as a key competitive advantage in an oligopoly market, as shortening the delivery time can stimulate demand for products. Many firms adopt a variety of strategies to shorten delivery time, and holding sufficient inventory is reported as an effective way. This study integrates a market share attraction model based on delivery time competition with the traditional inventory model to determine the optimal delivery time and order quantity. With the use of supermodular game method, we investigate the effect of changes in marketing and operations factors on the equilibrium delivery time and order quantity in non-dominated and dominated oligopolistic markets. The results reveal that the equilibrium delivery time and order quantity exhibit a directional response to changes in marketing and operations factors, and the response differs between the non-dominated oligopoly and the dominated oligopoly. Furthermore, under a cooperative oligopolistic market with asymmetry, it is beneficial for the firms with high competitive strength to adopt the delivery time strategy, but it fails to do so for the firm with the low competitive strength. Lastly, numerical analysis suggests that marketing factors play a more important role in affecting equilibrium measures than operations factors.

Hepatocellular carcinoma (HCC) is among the commonest kind of malignant tumors, which accounts for more than 500,000 cases of newly diagnosed cancer annually. Many microarray studies for identifying differentially expressed genes (DEGs) in HCC have been conducted, but results have varied across different studies. Here, we performed a meta-analysis of publicly available microarray Gene Expression Omnibus datasets, which covers five independent studies, containing 753 HCC samples and 638 non-tumor liver samples. We identified 192 DEGs that were consistently up-regulated in HCC vs. normal liver tissue. For the 192 up-regulated genes, we performed Kyoto Encyclopedia of Genes and Genomes pathway analysis. To our surprise, besides several cell growth-related pathways, spliceosome pathway was also up-regulated in HCC. For further exploring the relationship between spliceosome pathway and HCC, we investigated the expression data of spliceosome pathway genes in 15 independent studies in Nextbio database ( https://www.nextbio.com/b/nextbioCorp.nb ). It was found that many genes of spliceosome pathway such as HSPA1A, SNRPE, SF3B2, SF3B4 and TRA2A genes which we identified to be up-regulated in our meta-analysis were generally overexpressed in HCC. At last, using real-time PCR, we also found that BUD31, SF3B2, SF3B4, SNRPE, SPINK1, TPA2A and HSPA1A genes are significantly up-regulated in clinical HCC samples when compared to the corresponding non-tumorous liver tissues. Our study for the first time indicates that many genes of spliceosome pathway are up-regulated in HCC. This finding might put new insights for people's understanding about the relationship of spliceosome pathway and HCC.