Nitric oxide-releasing biomaterials for promoting wound healing in impaired diabetic wounds: State of the art and recent trends.

Impaired diabetic wounds are serious pathophysiological complications associated with persistent microbial infections including failure in the closure of wounds, and the cause of a high frequency of lower limb amputations. The healing of diabetic wounds is attenuated due to the lack of secretion of growth factors, prolonged inflammation, and/or inhibition of angiogenic activity. Diabetic wound healing can be enhanced by supplying nitric oxide (NO) endogenously or exogenously. NO produced inside the cells by endothelial nitric oxide synthase (eNOS) naturally aids wound healing through its beneficial vasculogenic effects. However, during hyperglycemia, the activity of eNOS is affected, and thus there becomes an utmost need for the topical supply of NO from exogenous sources. Thus, NO-donors that can release NO are loaded into wound healing patches or wound coverage matrices to treat diabetic wounds. The burst release of NO from its donors is prevented by encapsulating them in polymeric hydrogels or nanoparticles for supplying NO for an extended duration of time to the diabetic wounds. In this article, we review the etiology of diabetic wounds, wound healing strategies, and the role of NO in the wound healing process. We further discuss the challenges faced in translating NO-donors as a clinically viable nanomedicine strategy for the treatment of diabetic wounds with a focus on the use of biomaterials for the encapsulation and in vivo controlled delivery of NO-donors.

Single-Cell RNA Sequencing with Spatial Transcriptomics of Cancer Tissues.

Single-cell RNA sequencing (RNA-seq) techniques can perform analysis of transcriptome at the single-cell level and possess an unprecedented potential for exploring signatures involved in tumor development and progression. These techniques can perform sequence analysis of transcripts with a better resolution that could increase understanding of the cellular diversity found in the tumor microenvironment and how the cells interact with each other in complex heterogeneous cancerous tissues. Identifying the changes occurring in the genome and transcriptome in the spatial context is considered to increase knowledge of molecular factors fueling cancers. It may help develop better monitoring strategies and innovative approaches for cancer treatment. Recently, there has been a growing trend in the integration of RNA-seq techniques with contemporary omics technologies to study the tumor microenvironment. There has been a realization that this area of research has a huge scope of application in translational research. This review article presents an overview of various types of single-cell RNA-seq techniques used currently for analysis of cancer tissues, their pros and cons in bulk profiling of transcriptome, and recent advances in the techniques in exploring heterogeneity of various types of cancer tissues. Furthermore, we have highlighted the integration of single-cell RNA-seq techniques with other omics technologies for analysis of transcriptome in their spatial context, which is considered to revolutionize the understanding of tumor microenvironment.

Spatial mapping of cancer tissues by OMICS technologies.

Spatial mapping of heterogeneity in gene expression in cancer tissues can improve our understanding of cancers and help in the rapid detection of cancers with high accuracy and reliability. Significant advancements have been made in recent years in OMICS technologies, which possess the strong potential to be applied in the spatial mapping of biopsy tissue samples and their molecular profiling to a single-cell level. The clinical application of OMICS technologies in spatial profiling of cancer tissues is also advancing. The current review presents recent advancements and prospects of applying OMICS technologies to the spatial mapping of various analytes in cancer tissues. We benchmark the current state of the art in the field to advance existing OMICS technologies for high throughput spatial profiling. The factors taken into consideration include spatial resolution, types of biomolecules, number of different biomolecules that can be detected from the same assay, labeled versus label-free approaches, and approximate time required for each assay. Further advancements are still needed for the widespread application of OMICs technologies in performing fast and high throughput spatial mapping of cancer tissues as well as their effective use in research and clinical applications.

Cytotoxicity screening of Bangladeshi medicinal plant extracts on pancreatic cancer cells.

BACKGROUND: There has been a long standing interest in the identification of medicinal plants and derived natural products for developing cancer therapeutics. Our study focuses upon pancreatic cancer, due to its high mortality rate, that is attributed in part to the lack of an effective chemotherapeutic agent. Previous reports on the use of medicinal plant extracts either alone or alongside conventional anticancer agents in the treatment of this cancer have shown promising results. This work aims to investigate the therapeutic properties of a library of medicinal plants from Bangladesh. METHODS: 56 extracts of 44 unique medicinal plants were studied. The extracts were screened for cytotoxicity against the pancreatic adenocarcinoma cell line Panc-1, using a label-free biosensor assay. The top cytotoxic extracts identified in this screen were tested on two additional pancreatic cancer cell lines (Mia-Paca2 and Capan-1) and a fibroblast cell line (Hs68) using an MTT proliferation assay. Finally, one of the most promising extracts was studied using a caspase-3 colorimetric assay to identify induction of apoptosis. RESULTS: Crude extracts of Petunia punctata, Alternanthera sessilis, and Amoora chittagonga showed cytotoxicity to three cancer cell lines with IC50 values ranging between 20.3 - 31.4 µg/mL, 13.08 - 34.9 µg/mL, and 42.8 - 49.8 µg/mL, respectively. Furthermore, treatment of Panc-1 cells with Petunia punctata was shown to increase caspase-3 activity, indicating that the observed cytotoxicity was mediated via apoptosis. Only Amoora chittagonga showed low cytotoxicity to fibroblast cells with an IC50 value > 100 µg/mL. CONCLUSION: Based upon the initial screening work reported here, further studies aimed at the identification of active components of these three extracts and the elucidation of their mechanisms as cancer therapeutics are warranted.

Color Classifier for Symptomatic Soybean Seeds Using Image Processing.

Symptoms associated with fungal damage, viral diseases, and immature soybean (Glycine max) seeds were characterized using image processing techniques. A Red, Green, Blue (RGB) color feature-based multivariate decision model discriminated between asymptomatic and symptomatic seeds for inspection and grading. The color analysis showed distinct color differences between the asymptomatic and symptomatic seeds. A model comprising six color features including averages, minimums, and variances for RGB pixel values was developed for describing the seed symptoms. The color analysis showed that color alone did not adequately describe some of the differences among symptoms. Overall classification accuracy of 88% was achieved using a linear discriminant function with unequal priors for asymptomatic and symptomatic seeds with highest probability of occurrence. Individual classification accuracies were asymptomatic 97%, Alternaria spp. 30%, Cercospora spp. 83%, Fusarium spp. 62%, green immature seeds 91%, Phomopsis spp. 45%, soybean mosaic potyvirus (black) 81%, and soybean mosaic potyvirus (brown) 87%. The classifier performance was independent of the year the seed was sampled. The study was successful in developing a color classifier and a knowledge domain based on color for future development of intelligent automated grain grading systems.