Identification of potential FAK inhibitors using mol2vec molecular descriptor-based QSAR, molecular docking, ADMET study, and molecular dynamics simulation.

This study aims to identify potential focal adhesion kinase (FAK) inhibitors through an integrated computational approach, combining mol2vec descriptor-based QSAR, molecular docking, ADMET study, and molecular dynamics simulation. A dataset of 437 compounds with known FAK inhibitory activities was used to develop QSAR models using machine learning algorithms combined with mol2vec descriptors. Subsequently, the most promising compounds were subjected to molecular docking against FAK to evaluate their binding affinities and key interactions. ADMET study and molecular dynamics simulation were also employed to investigate the pharmacokinetic, drug-like properties, and the stability of the protein-ligand complexes. The results showed that the mol2vec descriptor-based QSAR model established by support vector regression demonstrated good predictive performance (R2 = 0.813, RMSE = 0.453, MAE = 0.263 in case of training set, and R2 = 0.729, RMSE = 0.635, MAE = 0.477 in case of test set), indicating their reliability in identifying potent FAK inhibitors. Using this QSAR model and molecular docking, compound 21 (ZINC000004523722) was identified as the most potential compound, with predicted logIC50 value and binding energy of 2.59 and - 9.3 kcal/mol, respectively. The results of molecular dynamics simulation and ADMET study also further suggested its potential as a promising drug candidate. However, because our research was merely theoretical, additional in vitro and in vivo studies are required for the verification of these results.

Zirconium-Based Metal-Organic Framework Capable of Binding Proinflammatory Mediators in Hydrogel Form Promotes Wound Healing Process through a Multiscale Adsorption Mechanism.

The regulation of proinflammatory mediators has been explored to promote natural healing without abnormal inflammation or autoimmune response induced by their overproduction. However, most efforts to control these mediators have relied on pharmacological substances that are directly engaged in biological cycles. It is believed that functional porous materials removing target mediators provide a new way to promote the healing process using their adsorption mechanisms. In this study, the Zr-based metal-organic frameworks (MOF)-808 (Zr6 O4 (OH)4 (BTC)2 (HCOO)6 ) crystals are found to be effective at removing proinflammatory mediators, such as nitric oxide (NO), cytokines, and reactive oxygen species (ROS) in vitro and in vivo, because of their porous structure and surface affinity. The MOF-808 crystals are applied to an in vivo skin wound model as a hydrogel dispersion. Hydrogel containing 0.2 wt% MOF-808 crystals shows significant improvement in terms of wound healing efficacy and quality over the corresponding control. It is also proven that the mode of action is to remove the proinflammatory mediators in vivo. Moreover, the application of MOF-808-containing hydrogels promotes cell activation, proliferation and inhibits chronic inflammation, leading to increased wound healing quality. These findings suggest that Zr-based MOFs may be a promising drug-free solution for skin problems related to proinflammatory mediators.

Development of predictive models for lymphedema by using blood tests and therapy data.

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.

Enhancement of Wound Healing Efficacy by Chitosan-based Hydrocolloid on Sprague Dawley Rats.

BACKGROUND/AIM: Chitosan-based functional materials have attracted considerable attention worldwide for applications in wound healing, especially in skin wound healing, due to their efficiency in hemostasis, anti-bacterial, and skin regeneration. Various chitosan-based products have been developed for skin wound healing applications, but most of these face limitations in either efficacy or cost-effectiveness. Therefore, there is a need to develop a unique material that can handle all of these concerns and be utilized for acute and chronic wounds. This study investigated mechanisms of new chitosan-based hydrocolloid patches in inflammatory reduction and skin formation by using wound-induced Sprague Dawley Rats. MATERIALS AND METHODS: Our study combined a hydrocolloid patch with chitosan to achieve a practical and accessible medical patch that would enhance skin wound healing. Our chitosan-embedded patch has shown a significant influence by preventing wound expansion and inflammation increment on Sprague Dawley rat models. RESULTS: The chitosan patch significantly increased the wound healing rate and accelerated the inflammatory stage by suppressing pro-inflammatory cytokines activity (e.g., TNF-α, IL-6, MCP-1, and IL-1ß). Moreover, the product was effective in promoting skin regeneration, demonstrated by the increase in the number of fibroblasts through specific biomarkers (e.g., vimentin, α-SMA, Ki-67, collagen I, and TGF-ß1). CONCLUSION: Our study on the chitosan-based hydrocolloid patches not only elucidated mechanisms of reducing inflammation and enhancing proliferation, but also provided a cost-effective method for skin wound dressing.

Complementary combination of biomarkers for diagnosis of sarcopenia in C57BL/6J mice.

AIMS: The objective of this study is to provide a reliable strategy for the diagnosis of sarcopenia based on a complementary combination of biomarkers from various approaches. MATERIAL AND METHODS: A total of 30 C57BL/6J mice were used for the experiment, in which 15 young mice (YM) at 24 weeks old and 15 aged mice (AM) at 88 weeks old. Extracted features-based digital biomarkers from the electromyography activity of tibialis anterior muscles were evaluated by using receiver operating characteristic analysis. Extracted tissular proteins and circulating hormones based chemical biomarkers were investigated by using immunoblotting and enzyme-linked immunosorbent assay. KEY FINDINGS: In terms of digital biomarkers, the feature-based classification of mice groups showed good performance (Feature A: AUC = 0.986, accuracy = 0.928) and (Feature B: AUC = 0.999, accuracy = 0.990). On the other hand, muscle-specific protein levels based chemical biomarkers (e.g. MuRF1, FoxO1, and perilipin2) were observed significantly increase with age. Pro-inflammatory cytokines based biomarkers extracted from muscle tissue and circulating plasma (e.g. TNF-α, IL-6, and IL-8) were significantly higher in case of AM group compared to YM group. Circulating hormone-based chemical biomarkers (e.g. cortisol/DHEA ratio and cathepsin D) presented a significant increase in concentrations with age. Circulating neurotransmitter based biomarkers (e.g. acetylcholine, serotonin, and histamine) also increased significantly in concentrations from YM to AM. SIGNIFICANCE: A complementary combination of digital and chemical biomarkers covers multiple domains of sarcopenia to provide an effective strategy for the early diagnosis of sarcopenia.

A Comprehensive Review of Natural Compounds for Wound Healing: Targeting Bioactivity Perspective.

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.

In Vivo Comparison of Three Human Acellular Dermal Matrices for Breast Reconstruction.

BACKGROUND/AIM: Acellular dermal matrices (ADMs) have become popular in implant-based breast reconstruction. The aim of this study was to compare three commonly used ADM products in vivo in an animal model. MATERIALS AND METHODS: The nucleic acid content (residual double-stranded DNA) and the levels of the remaining growth factors after decellularization were measured for each ADM. Cytocompatibility with ADMs was documented using NIH 3T3 mouse fibroblast cells. In vivo, the implanted ADMs were histologically evaluated at 1, 2, 3, and 6 months (n=5) using male 8-week-old Sprague-Dawley rats. RESULTS: Fibroblasts grew in the SureDerm HD and DermACELL with no cytotoxicity. In a rat model, SureDerm HD and DermACELL incorporated more readily into the surrounding host tissue, as measured by rapid cell influx and collagen deposition, and showed more delayed tissue remodeling with decreased matrix metalloproteinases levels compared to AlloDerm. CONCLUSION: SureDerm HD and DermACELL can be used as biological materials for breast reconstruction.

Silicone Implants Immobilized with Interleukin-4 Promote the M2 Polarization of Macrophages and Inhibit the Formation of Fibrous Capsules.

Breast augmentations with silicone implants can have adverse effects on tissues that, in turn, lead to capsular contracture (CC). One of the potential ways of overcoming CC is to control the implant/host interaction using immunomodulatory agents. Recently, a high ratio of anti-inflammatory (M2) macrophages to pro-inflammatory (M1) macrophages has been reported to be an effective tissue regeneration approach at the implant site. In this study, a biofunctionalized implant was coated with interleukin (IL)-4 to inhibit an adverse immune reaction and promoted tissue regeneration by promoting polarization of macrophages into the M2 pro-healing phenotype in the long term. Surface wettability, nitrogen content, and atomic force microscopy data clearly showed the successful immobilization of IL-4 on the silicone implant. Furthermore, in vitro results revealed that IL-4-coated implants were able to decrease the secretion of inflammatory cytokines (IL-6 and tumor necrosis factor-α) and induced the production of IL-10 and the upregulation of arginase-1 (mannose receptor expressed by M2 macrophage). The efficacy of this immunomodulatory implant was further demonstrated in an in vivo rat model. The animal study showed that the presence of IL-4 diminished the capsule thickness, the amount of collagen, tissue inflammation, and the infiltration of fibroblasts and myofibroblasts. These results suggest that macrophage phenotype modulation can effectively reduce inflammation and fibrous CC on a silicone implant conjugated with IL-4.