Wound healing is a recovering process of damaged tissues by replacing dysfunctional injured cellular structures. Natural compounds for wound treatment have been widely used for centuries. Numerous ...published works provided reviews of natural compounds for wound healing applications, which separated the approaches based on different categories such as characteristics, bioactivities, and modes of action. However, current studies provide reviews of natural compounds that originated from only plants or animals. In this work, we provide a comprehensive review of natural compounds sourced from both plants and animals that target the different bioactivities of healing to promote wound resolution. The compounds were classified into four main groups (i.e., anti-inflammation, anti-oxidant, anti-bacterial, and collagen promotion), mostly studied in current literature from 1992 to 2022. Those compounds are listed in tables for readers to search for their origin, bioactivity, and targeting phases in wound healing. We also reviewed the trend in using natural compounds for wound healing.
Antibiotic residues in aquatic products in Vietnam were investigated. A total of 511 fish and shrimp samples were collected from markets in Ho Chi Minh City (HCMC), Thai Binh (TB), and Nha Trang (NT) ...from July 2013 to October 2015. The samples were extracted with 2% formic acid in acetonitrile and washed with dispersive C18 sorbent. Thirty-two antibiotics were analyzed by LC-MS/MS. Of the 362 samples from HCMC, antibiotic residues were found in 53 samples. Enrofloxacin was commonly detected, at a rate of 10.8%. In contrast, samples from TB and NT were less contaminated: only 1 of 118 analyzed samples showed residues in TB and only 1 of 31 showed residues in NT. These differences were attributed to the local manufacturing/distribution systems. To understand the current status of antibiotic use and prevent adverse effects that may be caused by their overuse, continual monitoring is required.
A major cause of the paucity of new starting points for drug discovery is the lack of interaction between academia and industry. Much of the global resource in biology is present in universities, ...whereas the focus of medicinal chemistry is still largely within industry. Open source drug discovery, with sharing of information, is clearly a first step towards overcoming this gap. But the interface could especially be bridged through a scale-up of open sharing of physical compounds, which would accelerate the finding of new starting points for drug discovery. The Medicines for Malaria Venture Malaria Box is a collection of over 400 compounds representing families of structures identified in phenotypic screens of pharmaceutical and academic libraries against the Plasmodium falciparum malaria parasite. The set has now been distributed to almost 200 research groups globally in the last two years, with the only stipulation that information from the screens is deposited in the public domain. This paper reports for the first time on 236 screens that have been carried out against the Malaria Box and compares these results with 55 assays that were previously published, in a format that allows a meta-analysis of the combined dataset. The combined biochemical and cellular assays presented here suggest mechanisms of action for 135 (34%) of the compounds active in killing multiple life-cycle stages of the malaria parasite, including asexual blood, liver, gametocyte, gametes and insect ookinete stages. In addition, many compounds demonstrated activity against other pathogens, showing hits in assays with 16 protozoa, 7 helminths, 9 bacterial and mycobacterial species, the dengue fever mosquito vector, and the NCI60 human cancer cell line panel of 60 human tumor cell lines. Toxicological, pharmacokinetic and metabolic properties were collected on all the compounds, assisting in the selection of the most promising candidates for murine proof-of-concept experiments and medicinal chemistry programs. The data for all of these assays are presented and analyzed to show how outstanding leads for many indications can be selected. These results reveal the immense potential for translating the dispersed expertise in biological assays involving human pathogens into drug discovery starting points, by providing open access to new families of molecules, and emphasize how a small additional investment made to help acquire and distribute compounds, and sharing the data, can catalyze drug discovery for dozens of different indications. Another lesson is that when multiple screens from different groups are run on the same library, results can be integrated quickly to select the most valuable starting points for subsequent medicinal chemistry efforts.
Anaplastic large cell lymphoma (ALCL) is an uncommon type of non-Hodgkin's lymphoma (NHL), as well as one of the subtypes of T cell lymphoma, accounting for 1 to 3% of non-Hodgkin's lymphomas and ...around 15% of T cell lymphomas. In 2016, the World Health Organization (WHO) classified anaplastic large cell lymphoma into four categories: ALK-positive ALCL (ALK+ALCL), ALK-negative ALCL (ALK-ALCL), primary cutaneous ALCL (pcALCL), and breast-implant-associated ALCL (BIA-ALCL), respectively. Clinical symptoms, gene changes, prognoses, and therapy differ among the four types. Large lymphoid cells with copious cytoplasm and pleomorphic characteristics with horseshoe-shaped or reniform nuclei, for example, are found in both ALK+ and ALK-ALCL. However, their epidemiology and pathogenetic origins are distinct. BIA-ALCL is currently recognized as a new provisional entity, which is a noninvasive disease with favorable results. In this review, we focus on molecular pathogenesis and management of anaplastic large cell lymphoma.
Abstract
Lymphedema is a disease that refers to tissue swelling caused by an accumulation of protein-rich fluid that is usually drained through the lymphatic system. Detection of lymphedema is often ...based on expensive diagnoses such as bioimpedance spectroscopy, shear wave elastography, computed tomography, etc. In current machine learning models for lymphedema prediction, reliance on observable symptoms reported by patients introduces the possibility of errors in patient-input data. Moreover, these symptoms are often absent during the initial stages of lymphedema, creating challenges in its early detection. Identifying lymphedema before these observable symptoms manifest would greatly benefit patients by potentially minimizing the discomfort caused by these symptoms. In this study, we propose to use new data, such as complete blood count, serum, and therapy data, to develop predictive models for lymphedema. This approach aims to compensate for the limitations of using only observable symptoms data. We collected data from 2137 patients, including 356 patients with lymphedema and 1781 patients without lymphedema, with the lymphedema status of each patient confirmed by clinicians. The data for each patient included: (1) a complete blood count (CBC) test, (2) a serum test, and (3) therapy information. We used various machine learning algorithms (i.e. random forest, gradient boosting, decision tree, logistic regression, and artificial neural network) to develop predictive models on the training dataset (i.e. 80% of the data) and evaluated the models on the external validation dataset (i.e. 20% of the data). After selecting the best predictive models, we created a web application to aid medical doctors and clinicians in the rapid screening of lymphedema patients. A dataset of 2137 patients was assembled from Seoul National University Bundang Hospital. Predictive models based on the random forest algorithm exhibited satisfactory performance (balanced accuracy = 87.0 ± 0.7%, sensitivity = 84.3 ± 0.6%, specificity = 89.1 ± 1.5%, precision = 97.4 ± 0.7%, F1 score = 90.4 ± 0.4%, and AUC = 0.931 ± 0.007). We developed a web application to facilitate the swift screening of lymphedema among medical practitioners:
https://snubhtxt.shinyapps.io/SNUBH_Lymphedema
. Our study introduces a novel tool for the early detection of lymphedema and establishes the foundation for future investigations into predicting different stages of the condition.
Silicone implants are widely used biomaterials in surgeries owing to their physiological inertness and low toxicity. However, capsular contracture is a severe complication caused by the insertion of ...breast implants, which can endanger the health of patients. In this study, twelve different silicone breast implants were tested to determine which could lead to a lower incidence of capsular contracture.
For in vivo experiments, these silicone implants were implanted into 60 rats (i.e., five implants per rat). The implants were explanted eight weeks after the operation. Samples were analyzed and measured by using hematoxylin and eosin staining, Masson's trichrome staining, and immunofluorescence staining methods. We compared twelve samples for their differences in the thickness of capsular formation, number of inflammatory cells, collagen expression, fibroblast intensity (i.e., Vimentin and α-SMA), and inflammatory cytokines (i.e., IL-8, CD68, MCP-1, and F4/80).
Different surface textures of breast implants gave different effects on capsular thickness, collagen formation, fibroblast formation, and potential inflammation. Samples that had smooth textures such as SEBBIN, HANS, and Mentor showed higher collagen formation than other samples. SEBBIN Texture, Motiva Micro, HANS Smooth I, and HANS Micro exhibited higher fibroblast formation (i.e., α-SMA, Vimentin). SEBBIN Smooth and samples in HANS group displayed lower expression of inflammation cytokines (IL-8, CD68, MCP-1, and F4/80).
These findings provide preliminary reports on the surface texture effect and support a selection of breast silicone implants in breast reconstruction to avoid the formation of capsular contracture after implantation.
BACKGROUND/AIMHypertrophic scars (HS) are the result of pathological wound healing characterized by a red, raised scar formation. The goal of this research was development of a new method for ...treatment of HS formation. MATERIALS AND METHODSA tranilast-loaded microneedle (TMN) was developed and applied in a rabbit ear model to treat an induced HS. Scar elevation index, the thickness of dorsal skin by hematoxylin and eosin staining, collagen deposition by Masson trichrome staining and expression of myofibroblast biomarker proteins were evaluated. RESULTSThe 12×12 array of the TMN containing 2.9 μg tranilast per needle released more than 80% of the drug within 30 min. During the procedure, control, non-loaded MN and TMN loaded with three different doses of tranilast (low: 2.5-3, medium: 25-30, and high: 100-150 μg) were applied to the HS in rabbit ears. High-level TMN led to a clear and natural appearance of skin, a decrease in scar elevation index by 47% and decline in the thickness of the epidermis from 69.27 to 15.92 μm when compared to the control group. Moreover, the collagen density also decreased in groups treated with medium- or high-level TMNs, by 10.2% and 9.06%, respectively. Furthermore, the expression of transforming growth factor-β, collagen-1, and α-smooth muscle actin proteins was reduced in TMN-treated HSs compared to the control. CONCLUSIONThe findings show the overall efficacy of TMNs in inhibiting HS. Thus, use of TMN is a simple and cosmetic remedy for HS, with good protection and reliability.
Human skin-derived ECM aids cell functions but can trigger immune reactions; therefore it is addressed through decellularization. Acellular dermal matrices (ADMs), known for their regenerative ...properties, are used in tissue and organ regeneration. ADMs now play a key role in plastic and reconstructive surgery, enhancing aesthetics and reducing capsular contracture risk. Innovative decellularization with supercritical carbon dioxide preserves ECM quality for clinical use. The study investigated the cytotoxicity, biocompatibility, and anti-inflammatory properties of supercritical CO 2 acellular dermal matrix (scADM) in vivo based on Sprague Dawley rat models. Initial experiments in vitro with fibroblast cells confirmed the non-toxic nature of scADM and demonstrated cell infiltration into scADMs after incubation. Subsequent tests in vitro revealed the ability of scADM to suppress inflammation induced by lipopolysaccharides (LPS) presenting by the reduction of pro-inflammatory cytokines TNF-α, IL-6, IL-1β, and MCP-1. In the in vivo model, histological assessment of implanted scADMs in 6 months revealed a decrease in inflammatory cells, confirmed further by the biomarkers of inflammation in immunofluorescence staining. Besides, an increase in fibroblast infiltration and collagen formation was observed in histological staining, which was supported by various biomarkers of fibroblasts. Moreover, the study demonstrated vascularization and macrophage polarization, depicting increased endothelial cell formation. Alteration of matrix metalloproteinases (MMPs) was analyzed by RT-PCR, indicating the reduction of MMP2, MMP3, and MMP9 levels over time. Simultaneously, an increase in collagen deposition of collagen I and collagen III was observed, verified in immunofluorescent staining, RT-PCR, and western blotting. Overall, the findings suggested that scADMs offer significant benefits in improving outcomes in implant-based procedures as well as soft tissue substitution.
We have observed a boom in video streaming over the Internet, especially during the Covid-19 pandemic, that could exceed the network resource availability. In addition to upgrading the network ...infrastructure, finding a way to smartly adapt the streaming system to the network and users’ conditions to satisfy clients’ perceptions is exceptionally critical, too. This paper proposes a new QoE-aware adaptive streaming scheme over HTTP - ABRA - to make flexible adaptations based on the network and the client’s current status. Besides, we propose a technique that can keep the buffer at an average high for more than 10s. We were limiting the phenomena of rebuffering due to unexpected and unpredictable bandwidth changes. The algorithm keeps the quality of subsequent versions’ quality constant even when the average bitrate decreases, increasing the QoE. Experimental results show that our method can improve QoE from 7.86% to 20.41% compared to state-of-the-art methods. ABRA can provide better performance in terms of QoE score in all buffer conditions compared to the existing solutions while maintaining a minimum secured buffer level for the worst case.
The receptor-type protein tyrosine phosphatase PTPσ mediates neural development and regeneration. Early studies on the ligands of PTPσ identified heparan sulfate proteolycan (HSPG) as a ligand. ...Binding of HSPG to PTPσ plays a critical role in axon guidance and synapse formation. PTPσ is also a receptor for chondroitin sulfate proteoglycan (CSPG). CSPG is deposited in high concentration at sites of neural injury. The deposited CSPG inhibits neural regeneration and axonal growth via PTPσ. The crystal structure of N-terminal immunoglobulin-like domains of PTPσ shows that the glycan binding site forms an elliptical surface patch of ∼35 by 24 Å, which interacts with sulfate groups of HSPG and CSPG. In this review, we focus on the structural and functional mechanisms for the neural regeneration regulation by different types of proteoglycans. We also discuss recent results on induction of neural regeneration in the stroke model and neural transplantation. The mechanistic understanding of relationships between proteoglycans and PTPσ provides new therapeutic opportunities against diseases with impaired neural regeneration.
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