Colorectal cancer is the leading cause of cancer-related mortality in the western world. It is also the third most common cancer diagnosed in both men and women in the United States with a recent estimate for new cases of colorectal cancer in the year 2012 being around 103,170. Various risk factors for colorectal cancer include life-style, diet, age, personal and family history, and racial and ethnic background. While a few cancers are certainly preventable but this does not hold true for colon cancer as it is often detected in its advanced stage and generally not diagnosed until symptoms become apparent. Despite the fact that several options are available for treating this cancer through surgery, chemotherapy, radiation therapy, immunotherapy, and nutritional-supplement therapy, but the success rates are not very encouraging when used alone where secondary complications appear in almost all these therapies. To maximize the therapeutic-effects in patients, combinatorial approaches are essential. In this review we have discussed the therapies previously and currently available to patients diagnosed with colorectal-cancer, focus on some recent developments in basic research that has shaded lights on new therapeutic-concepts utilizing macrophages/dendritic cells, natural killer cells, gene delivery, siRNA-, and microRNA-technology, and specific-targeting of tyrosine kinases that are either mutated or over-expressed in the cancerous cell to treat these cancer. Potential strategies are discussed where these concepts could be applied to the existing therapies under a comprehensive approach to enhance the therapeutic effects.
In this paper, we address the text and image matching in crossmodal retrieval of the fashion industry. Different from the matching in the general domain, the fashion matching is required to pay much more aention to the fine-grained information in the fashion images and texts. Pioneer approaches detect the region of interests (i.e., RoIs) from images and use the RoI embeddings as image representations. In general, RoIs tend to represent the "object-level" information in the fashion images, while fashion texts are prone to describe more detailed information, e.g. styles, aributes. RoIs are thus not fine-grained enough for fashion text and image matching. To this end, we propose FashionBERT, which leverages patches as image features. With the pre-trained BERT model as the backbone network, FashionBERT learns high level representations of texts and images. Meanwhile, we propose an adaptive loss to trade off multitask learning in the FashionBERT modeling. Two tasks (i.e., text and image matching and cross-modal retrieval) are incorporated to evaluate FashionBERT. On the public dataset, experiments demonstrate FashionBERT achieves significant improvements in performances than the baseline and state-ofthe-art approaches. In practice, FashionBERT is applied in a concrete cross-modal retrieval application. We provide the detailed matching performance and inference efficiency analysis.
The global pandemic of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV -2) has resulted in widespread social and economic disruption. Effective interventions are urgently needed for the prevention and treatment of COVID-19. Neutralizing monoclonal antibodies (mAbs) have demonstrated their prophylactic and therapeutic efficacy against SARS-CoV-2, and several have been granted authorization for emergency use. Here, we discover and characterize a fully human cross-reactive mAb, MW06, which binds to both SARS-CoV-2 and SARS-CoV spike receptor-binding domain (RBD) and disrupts their interaction with angiotensin-converting enzyme 2 (ACE2) receptors. Potential neutralization activity of MW06 was observed against both SARS-CoV-2 and SARS-CoV in different assays. The complex structure determination and epitope alignment of SARS-CoV-2 RBD/MW06 revealed that the epitope recognized by MW06 is highly conserved among SARS-related coronavirus strains, indicating the potential broad neutralization activity of MW06. In in vitro assays, no antibody-dependent enhancement (ADE) of SARS-CoV-2 infection was observed for MW06. In addition, MW06 recognizes a different epitope from MW05, which shows high neutralization activity and has been in a Phase 2 clinical trial, supporting the development of the cocktail of MW05 and MW06 to prevent against future escaping variants. MW06 alone and the cocktail show good effects in preventing escape mutations, including a series of variants of concern, B.1.1.7, P.1, B.1.351, and B.1.617.1. These findings suggest that MW06 recognizes a conserved epitope on SARS-CoV-2, which provides insights for the development of a universal antibody-based therapy against SARS-related coronavirus and emerging variant strains, and may be an effective anti-SARS-CoV-2 agent.
The Bcl-2 family of proteins is critical to the life and death of malignant B-lymphocytes. Interfering with their activity using small-molecule inhibitors (SMI) is being explored as a new therapeutic strategy for treating B-cell tumors. We evaluated the efficacy of TW-37, a non-peptidic SMI of Bcl-2 against a range spectrum of human B-cell lines, fresh patient samples and animal xenograft models. Multiple cytochemical and molecular approaches such as acridine orange/ethidium bromide assay for apoptosis, co-immunoprecipitation of complexes and western blot analysis, caspase luminescent activity assay and apoptotic DNA fragmentation assay were used to demonstrate the effect of TW-37 on different B-cell lines, patient derived samples, as well as in animal xenograft models. Nanomolar concentrations of TW-37 were able to induce apoptosis in both fresh samples and established cell lines with IC 50 in most cases of 165-320 nM. Apoptosis was independent of proliferative status or pathological classification of B-cell tumor. TW-37 was able to block Bim-Bcl-X L and Bim-Mcl-1 heterodimerization and induced apoptosis via activation of caspases -9, -3, PARP and DNA fragmentation. TW-37 administered to tumor-bearing SCID mice led to significant tumor growth inhibition (T/C), tumor growth delay (T-C) and Log 10 kill, when used at its maximum tolerated dose (40 mg/kg × 3 days) via tail vein. TW-37 failed to induce changes in the Bcl-2 proteins levels suggesting that assessment of baseline Bcl-2 family proteins can be used to predict response to the drug. These findings indicate activity of TW-37 across the spectrum of human Bcell tumors and support the concept of targeting the Bcl-2 system as a therapeutic strategy regardless of the stage of B-cell differentiation.
UTL-5b (GBL-5b) is a novel analog of leflunomide with anti-inflammatory and antiarthritic effects. It has been shown to lower serum tumor necrosis factor-alpha (TNF-α) level induced by lipopolysaccharide (LPS) in an animal model. In this study, the effect of UTL-5b on nitric oxide (NO) and dihydroorotate dehydrogenase (DHODH) was investigated. Our in vitro studies showed that (1) UTL-5b is a stronger inhibitor of NO production as compared to leflunomide and its active metabolite, teriflunomide, and (2) Unlike leflunomide, a potent inhibitor of DHODH, UTL-5b does not inhibit DHODH activity. These findings show that UTL-5b acts in a manner different from that of leflunomide. To further investigate the mode of action of UTL-5b, an ex vivo gene array study was performed. C57BL/6 mice were injected subcutaneously with of UTL-5b 24 hr before injection of E. coli LPS. Mice were sacrificed 90 min later and the whole spleen mRNA was isolated for gene microarray analysis. The results showed that UTL-5b significantly suppressed three genes that are relevant to the TNF- pathway: Janus kinase 3 (JAK3), mitogen-activated protein kinase kinase kinase 2 (MAP3K2) and lipopolysaccharide-induced TNF- factor (LITAF). In summary, our results showed that UTL-5b has a stronger inhibitory effect on NO production than leflunomide; yet, unlike leflunomide, UTL-5b does not inhibit DHODH in vitro. In addition, gene array analysis showed that the biological effects of UTL-5b are attributed at least in part to the suppression of JAK3, MAP3K2 and LITAF gene expression.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.