Sal-like protein 2 upregulates p16 expression through a proximal promoter element.

Sal-like protein 2 (Sall2), a homeotic transcription factor, is a putative tumor suppressor. We have previously shown that Sall2 activates the transcription of tumor suppressor gene p21 and suppresses tumorigenesis through cell cycle inhibition and induction of apoptosis. To investigate additional Sall2-regulated downstream genes, we analyzed the differences in mRNA expression profiles with and without exogenously expressed Sall2. We identified 1616 Sall2-responsive genes through gene expression arrays. Promoter-reporter assays of p16(INK4A) and several other tumor-related genes indicated that the Sall2 regulation of these promoters was not significantly different between the two major forms of Sall2 with alternative exon 1 or exon 1A. Additional analysis showed that Sall2-induced p16 promoter activation was Sall2 dose-dependent. Deletion and site-directed mutagenesis of the p16 promoter identified a consensus Sall2 binding site (GGGTGGG) proximal to the p16 transcription start site and was critical for p16 promoter activation. Finally, to confirm the significance of Sall2-activated p16 expression in cell cycle regulation, we co-transfected the SKOV3 cells with a Sall2 expression construct and a p16 minigene and also co-transfected the ES-2 cells with a Sall2 expression construct and the siRNA against p16 for flow cytometry analysis. Our results showed that Sall2 enhanced the p16 minigene blocking of cell cycle progression and p16 knockdown with siRNA abolished most of the Sall2 inhibition of cell cycle progression. These findings indicate that Sall2 targets multiple cell cycle regulators, including p16, through their promoters, adding knowledge to the understanding of Sall2 and p16 gene regulation, and how Sall2 deregulation may promote cancer formation.

HAFormer: Unleashing the Power of Hierarchy-Aware Features for Lightweight Semantic Segmentation.

Both Convolutional Neural Networks (CNNs) and Transformers have shown great success in semantic segmentation tasks. Efforts have been made to integrate CNNs with Transformer models to capture both local and global context interactions. However, there is still room for enhancement, particularly when considering constraints on computational resources. In this paper, we introduce HAFormer, a model that combines the hierarchical features extraction ability of CNNs with the global dependency modeling capability of Transformers to tackle lightweight semantic segmentation challenges. Specifically, we design a Hierarchy-Aware Pixel-Excitation (HAPE) module for adaptive multi-scale local feature extraction. During the global perception modeling, we devise an Efficient Transformer (ET) module streamlining the quadratic calculations associated with traditional Transformers. Moreover, a correlation-weighted Fusion (cwF) module selectively merges diverse feature representations, significantly enhancing predictive accuracy. HAFormer achieves high performance with minimal computational overhead and compact model size, achieving 74.2% mIoU on Cityscapes and 71.1% mIoU on CamVid test datasets, with frame rates of 105FPS and 118FPS on a single 2080Ti GPU. The source codes are available at https://github.com/XU-GITHUB-curry/HAFormer.

EWT: Efficient Wavelet-Transformer for single image denoising.

Transformer-based image denoising methods have shown remarkable potential but suffer from high computational cost and large memory footprint due to their linear operations for capturing long-range dependencies. In this work, we aim to develop a more resource-efficient Transformer-based image denoising method that maintains high performance. To this end, we propose an Efficient Wavelet Transformer (EWT), which incorporates a Frequency-domain Conversion Pipeline (FCP) to reduce image resolution without losing critical features, and a Multi-level Feature Aggregation Module (MFAM) with a Dual-stream Feature Extraction Block (DFEB) to harness hierarchical features effectively. EWT achieves a faster processing speed by over 80% and reduces GPU memory usage by more than 60% compared to the original Transformer, while still delivering denoising performance on par with state-of-the-art methods. Extensive experiments show that EWT significantly improves the efficiency of Transformer-based image denoising, providing a more balanced approach between performance and resource consumption.

A fine-grained orthodontics segmentation model for 3D intraoral scan data.

With the widespread application of digital orthodontics in the diagnosis and treatment of oral diseases, more and more researchers focus on the accurate segmentation of teeth from intraoral scan data. The accuracy of the segmentation results will directly affect the follow-up diagnosis of dentists. Although the current research on tooth segmentation has achieved promising results, the 3D intraoral scan datasets they use are almost all indirect scans of plaster models, and only contain limited samples of abnormal teeth, so it is difficult to apply them to clinical scenarios under orthodontic treatment. The current issue is the lack of a unified and standardized dataset for analyzing and validating the effectiveness of tooth segmentation. In this work, we focus on deformed teeth segmentation and provide a fine-grained tooth segmentation dataset (3D-IOSSeg). The dataset consists of 3D intraoral scan data from more than 200 patients, with each sample labeled with a fine-grained mesh unit. Meanwhile, 3D-IOSSeg meticulously classified every tooth in the upper and lower jaws. In addition, we propose a fast graph convolutional network for 3D tooth segmentation named Fast-TGCN. In the model, the relationship between adjacent mesh cells is directly established by the naive adjacency matrix to better extract the local geometric features of the tooth. Extensive experiments show that Fast-TGCN can quickly and accurately segment teeth from the mouth with complex structures and outperforms other methods in various evaluation metrics. Moreover, we present the results of multiple classical tooth segmentation methods on this dataset, providing a comprehensive analysis of the field. All code and data will be available at https://github.com/MIVRC/Fast-TGCN.

CTCNet: A CNN-Transformer Cooperation Network for Face Image Super-Resolution.

Recently, deep convolution neural networks (CNNs) steered face super-resolution methods have achieved great progress in restoring degraded facial details by joint training with facial priors. However, these methods have some obvious limitations. On the one hand, multi-task joint learning requires additional marking on the dataset, and the introduced prior network will significantly increase the computational cost of the model. On the other hand, the limited receptive field of CNN will reduce the fidelity and naturalness of the reconstructed facial images, resulting in suboptimal reconstructed images. In this work, we propose an efficient CNN-Transformer Cooperation Network (CTCNet) for face super-resolution tasks, which uses the multi-scale connected encoder-decoder architecture as the backbone. Specifically, we first devise a novel Local-Global Feature Cooperation Module (LGCM), which is composed of a Facial Structure Attention Unit (FSAU) and a Transformer block, to promote the consistency of local facial detail and global facial structure restoration simultaneously. Then, we design an efficient Feature Refinement Module (FRM) to enhance the encoded features. Finally, to further improve the restoration of fine facial details, we present a Multi-scale Feature Fusion Unit (MFFU) to adaptively fuse the features from different stages in the encoder procedure. Extensive evaluations on various datasets have assessed that the proposed CTCNet can outperform other state-of-the-art methods significantly. Source code will be available at https://github.com/IVIPLab/CTCNet.

Identification of Trypanosoma brucei leucyl-tRNA synthetase inhibitors by pharmacophore- and docking-based virtual screening and synthesis.

Human African trypanosomiasis (HAT), caused by the protozoan parasite Trypanosoma brucei, is a neglected fatal disease. Leucyl-tRNA synthetase (LeuRS), which has been successfully applied in the development of antifungal agent, represents a potential antiprotozoal drug target. In this study, a 3D model of T. brucei LeuRS (TbLeuRS) synthetic active site was constructed and subjected to virtual screening using a combination of pharmacophore- and docking-based methods. A new 2-pyrrolinone scaffold was discovered and the structure-activity relationship (SAR) studies aided by the docking model and organic synthesis were carried out. Compounds with various substituents on R(1), R(2) and R(3) were synthesized and their SAR was discussed.

[Research on the quality changes in pre-and-post-processed pieces of Radix Polygalae].

OBJECTIVE: To study the quality changes in pre-and-post-processed pieces of Radix Polygalae. METHODS: The changes of the content of senegenin and polygalacic acid were studied. RESULTS: The content of polygalacic acid in post-processed piece was lower than that in pre-processed piece. The content of senegenin had no obvious difference. CONCLUSION: The processing can make the quality change.

Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression.

In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous occlusions. However, the recognition performance of nuclear norm-based matrix regression degrades greatly in the face of the small sample size problem. An alternative solution to tackle this problem is performing matrix regression on each patch and then integrating the outputs from all patches. However, it is difficult to set an optimal patch size across different databases. To fully utilize the complementary information from different patch scales for the final decision, we propose a multi-scale patch-based matrix regression scheme based on which the ensemble of multi-scale outputs can be achieved optimally. Extensive experiments on benchmark face databases validate the effectiveness and robustness of our method, which outperforms several state-of-the-art patch-based face recognition algorithms.

A new mouse model for wound healing in hemophilia A.

PURPOSE: To establish a new mouse model for wound healing studies on hemophilia A. METHODS: Total 54 male mice with different genotypes including wild-type nude mice, heterozygous mice (FVIII-/-/Nu) and FVIII deficient mice (FVIII-/-) were generated and verified by PCR. Mice were subjected to wound healing research by making a 5 mm-thickness wound on mice skin and applying recombinant human epidermal growth factor (EGF, 10 µg/g) ointment, FVIII ointment (30 IU) or the ointment base to heal the wounds. Furthermore, keratinocytes were isolated from these newborn mice and subjected to migration assay by stimulation of EGF (ng/ml), insulin (10 µM) or vehicle. RESULTS: A new hemophilic mouse model (FVIII-/-/Nu) was constructed successfully after genotyping verified by PCR. Compared to FVIII-/- mice, FVIII-/-/Nu and Nu mice showed greater degree of wound contraction and loss of the crust. Topical treatment with EGF exhibited faster wound healing than FVIII and ointment base. Insulin treatment showed more increased migration distance than treated with EGF or vehicle. FVIII-/-/Nu mice showed greater migration than FVIII-/- and Nu mice. CONCLUSIONS: A new mouse model (FVIII-/-/Nu) for wound healing in hemophilia A was constructed, and topical treatment of insulin may be a better therapy than EGF for healing wounds in hemophilia A.

A human leucyl-tRNA synthetase as an anticancer target.

Several aminoacyl-tRNA synthetases have been reported to be overexpressed for charging essential aminoacyl-tRNAs in many cancer types. In this study, we aimed to explore the potential role of leucyl-tRNA synthetase (LARS) as an anticancer target. MTT assay was performed to screen inhibitors to human LARS (hsLARS) from compounds AN2690 and its derivatives, compounds 1-6, in U2OS and SKOV3 cells. The compound with the strongest inhibitory ability was further investigated for its inhibitory effect in cancer cell lines and in an animal tumor model. Additionally, a LARS-rescue experiment was performed to explore the potential target in U2OS using Western blot and flow cytometry. Luciferase reporter assay was designed to analyze the effect of of hsLARS inhibitor on p21 activation. We identified an hsLARS inhibitor (compound 2) that suppressed the proliferation of U2OS and SKOV3 cells in vitro. A LARS-rescue experiment demonstrated that the proliferation inhibition was induced by targeting intracellular LARS. In addition, the hsLARS inhibition was shown to activate the p21 early transcription and promote cell apoptosis, as well as reduce implanted EMT6 tumor progression in mice. Our results suggest that LARS might serve as a potential anticancer target through the p21 signaling pathway and that the nutritional signaling pathway may provide a valuable anticancer strategy for further investigation.

Induction of anterior gradient 2 (AGR2) plays a key role in insulin-like growth factor-1 (IGF-1)-induced breast cancer cell proliferation and migration.

Anterior gradient 2 (AGR2) is a promising anti-tumor target associated with estrogen receptor expression and metastatic progression of breast cancer. Insulin-like growth factor-1 (IGF-1) is another potent factor that stimulates breast cancer progression and mediates anti-estrogen drug resistance. However, the precise mechanism and connections between these two factors in breast cancer drug resistance have not been fully elucidated. Here, for the first time, we decipher that IGF-1 remarkably induces AGR2 in the MCF7 cell line, through an estrogen response element (ERE) between -802 and -808 bp and a leucine zipper transcription factor-binding site located between -972 and -982 bp on the AGR2 promoter. We also found that the ERK1/2 and AKT pathways mediate estrogen receptor-α at the upstream of ERE and that the JNK pathway activates the leucine zipper site through the c-Jun/c-Fos complex. Additionally, our data suggest that knockdown of AGR2 reduces IGF-1-induced cell proliferation, migration and cell cycle progression. Therefore, we report that AGR2 is a key modulator involved in IGF-1-induced breast cancer development. We propose that the identification of the mechanism linking the IGF-1/insulin signal and AGR2 promoter activation is important, because it provides insights into the development of anti-breast cancer drugs.

Design, synthesis and biological evaluation of N-alkyl or aryl substituted isoindigo derivatives as potential dual cyclin-dependent kinase 2 (CDK2)/glycogen synthase kinase 3ß (GSK-3ß) phosphorylation inhibitors.

A series of N-alkyl or aryl substituted isoindigo derivatives have been synthesized and their anti-proliferative activity was evaluated by Sulforhodamine B (SRB) assay. Some of the target compounds exhibited significant antitumor activity, including compounds 6h and 6k (against K562 cells), 6i (against HeLa cells) and 6j (against A549 cells). N-(p-methoxy-phenyl)-isoindigo (6k) exhibited a high and selective anti-proliferative activity against K562 cells (IC50 7.8 µM) and induced the apoptosis of K562 cells in a dose-dependent manner. Compound 6k arrested the cell cycle at S phase in K562 cells by decreasing the expression of cyclin A and CDK2, which played critical roles in DNA replication and passage through G2 phase. Moreover, compound 6k down-regulated the expression of p-GSK-3ß (Ser9), ß-catenin and c-myc proteins, up-regulated the expression of GSK-3ß, consequently, suppressed Wnt/ß-catenin signaling pathway and induced the apoptosis of K562 cells. The binding mode of compound 6k with GSK-3ß was simulated using molecular docking tools. All of these studies gave a better understanding to the molecular mechanisms of this class of agents and clues to develop dual CDK2/GSK-3ß (Ser9) phosphorylation inhibitors applied in cancer chemotherapy.

Reconstruction based finger-knuckle-print verification with score level adaptive binary fusion.

Recently, a new biometrics identifier, namely finger knuckle print (FKP), has been proposed for personal authentication with very interesting results. One of the advantages of FKP verification lies in its user friendliness in data collection. However, the user flexibility in positioning fingers also leads to a certain degree of pose variations in the collected query FKP images. The widely used Gabor filtering based competitive coding scheme is sensitive to such variations, resulting in many false rejections. We propose to alleviate this problem by reconstructing the query sample with a dictionary learned from the template samples in the gallery set. The reconstructed FKP image can reduce much the enlarged matching distance caused by finger pose variations; however, both the intra-class and inter-class distances will be reduced. We then propose a score level adaptive binary fusion rule to adaptively fuse the matching distances before and after reconstruction, aiming to reduce the false rejections without increasing much the false acceptances. Experimental results on the benchmark PolyU FKP database show that the proposed method significantly improves the FKP verification accuracy.

Examining the interactome of huperzine A by magnetic biopanning.

Huperzine A is a bioactive compound derived from traditional Chinese medicine plant Qian Ceng Ta (Huperzia serrata), and was found to have multiple neuroprotective effects. In addition to being a potent acetylcholinesterase inhibitor, it was thought to act through other mechanisms such as antioxidation, antiapoptosis, etc. However, the molecular targets involved with these mechanisms were not identified. In this study, we attempted to exam the interactome of Huperzine A using a cDNA phage display library and also mammalian brain tissue extracts. The drugs were chemically linked on the surface of magnetic particles and the interactive phages or proteins were collected and analyzed. Among the various cDNA expressing phages selected, one was identified to encode the mitochondria NADH dehydrogenase subunit 1. Specific bindings between the drug and the target phages and target proteins were confirmed. Another enriched phage clone was identified as mitochondria ATP synthase, which was also panned out from the proteome of mouse brain tissue lysate. These data indicated the possible involvement of mitochondrial respiratory chain matrix enzymes in Huperzine A's pharmacological effects. Such involvement had been suggested by previous studies based on enzyme activity changes. Our data supported the new mechanism. Overall we demonstrated the feasibility of using magnetic biopanning as a simple and viable method for investigating the complex molecular mechanisms of bioactive molecules.

Design, synthesis, and structure-activity relationship of Trypanosoma brucei leucyl-tRNA synthetase inhibitors as antitrypanosomal agents.

African trypanosomiasis, caused by the proto zoal pathogen Trypanosoma brucei (T. brucei), is one of the most neglected tropical diseases that are in great need of new drugs. We report the design and synthesis of T. brucei leucyl-tRNA synthetase (TbLeuRS) inhibitors and their structure--activity relationship. Benzoxaborole was used as the core structure and C(6) was modified to achieve improved affinity based on docking results that showed further binding space at this position. Indeed, compounds with C(7) substitutions showed diminished activity due to clash with the eukaryote specific I4ae helix while substitutions at C(6) gave enhanced affinity. TbLeuRS inhibitors with IC(50) as low as 1.6 µM were discovered, and the structure-activity relationship was discussed. The most potent enzyme inhibitors also showed excellent T. brucei parasite growth inhibition activity. This is the first time that TbLeuRS inhibitors are reported, and this study suggests that leucyl-tRNA synthetase (LeuRS) could be a potential target for antiparasitic drug development.

[Cloning, expression, purification and activity assay of Trypanosoma brucei phenylalanyl-tRNA synthetase in Escherichia coli].

Phenylalany--tRNA synthetase is a key enzyme for protein synthesis in Trypanosoma. Its validation as an inhibition. target will enable the development of a new generation of anti-Trypanosoma drugs. However, little is known about the isolation of the Trypanosoma Phenylalanyl-tRNA synthetase. Here we report the cloning, expression, purification, and activity assay of Phenylalanyl-tRNA synthetase from Trypanosoma brucei in Escherichia coli host. We co-cloned the alpha-subunit and beta-subunit of Phenylalanyl-tRNA synthetase from Trypanosoma brucei genomic DNA into the co-expression vector pCOLADuet. We successfully expressed the Trypanosoma brucei Phenylalanyl-tRNA synthetase in E. coli host, purified the whole enzyme by Ni-Hind affinity column and verified it by Western blotting. In addition, we tested its enzymatic activity by isotope labeling. The whole work laid a solid foundation for in vitro the screening and optimization of Trypanosoma brucei phenylalanyl-tRNA synthetase inhibitors.

[Preparation, characterization and potential application of monoclonal antibody 18A4 against AGR2].

AIM: To prepare mouse monoclonal antibodies (mAb) against AGR2 (human homolog of xenopus anterior gradient 2), to characterize these antibodies' properties, and to develop potential applications. METHODS: BALB/c mice were immunized with AGR2-MBP (maltose binding protein) fusion protein. The mAb was prepared by hybridoma technique and purified by protein G affinity chromatography. The titer and specificity of the mAb was determined by ELISA and Western blot respectively. The mAb was then further characterized by immunoprecipitation, immunofluorescent staining and tumor cell inhibition assay. RESULTS: One clone of hybridoma, 18A4, secreting specific mAb against AGR2, was obtained. The Ig subclass of the mAb was IgG1 (kappa). The titer of the mAb was 1 x 10(-6);. Western blot analysis showed specific binding of 18A4 with both recombinant and native AGR2 in cell extract. Immunofluorescent staining using 18A4 mAb demonstrated specific staining of AGR2 in the cytoplasma of Breast cancer cell line MCF7. Immunoprecipitation assay confirmed that this mAb could specifically bind and effectively precipitate the native AGR2. mAb 18A4 could also inhibit the growth of breast cancer cell MCF7. CONCLUSION: The mAb anti-AGR2 with high titer and specificity has been obtained. This mAb, 18A4, can be used in most molecular biology studies including Western blot, immunostaining, immunoprecipitation. It also inhibited the growth of cancer cells and therefore is a potential therapeutic starting point. It is a useful tool for the functional study of AGR2 and for the diagnosis and potential treatment of certain cancers.