Causal effects of fatty acids on atopic dermatitis: A Mendelian randomization study.

Background: Some evidence suggests abnormalities in fatty acids in patients with atopic dermatitis (AD), and benefits of supplementation with these fatty acids have been reported. However, there is still substantial controversy on the correlation between fatty acids and AD. Therefore, the aim of this study was to determine whether fatty acid levels are causally related to AD using a Mendelian randomization approach. Methods: We evaluated the data about the fatty acids levels and AD with various methods from Genome-Wide Association Study (GWAS). GWAS results were available both from European ancestry. Mendelian randomization methods were used to analysis the casual inference of fatty acids on AD. MR Egger and MR-PRESSO were used to determine pleiotropy and heterogeneity. Further analysis was conducted using instruments associated with the FADS genes to address mechanisms involved. We also used Multivariate MR (MVMR) to show the independent casual inference of omega-3 (n-3) fatty acids on AD. Results: Mendelian randomization (MR) analysis suggests that n-3 fatty acid levels are associated with a lower risk of AD (n-3 ORIVW: 0.92, 95% confidence interval [CI]: 0.87-0.98; p = 0.01). Moreover, docosahexaenoic acids (DHA) levels, which is a kind of long-chain, highly unsaturated omega-3 (n-3) fatty acid, and its higher level was associated with a lower risk of AD (DHA ORIVW: 0.91, 95% CI: 0.84-0.98; p = 0.02). We ran multivariable MR analysis while controlling for variables within the other types of fatty acids. The effect estimates agreed with the preliminary MR analysis indicating the effect of n-3 fatty acids levels on AD was robust. MR-egger suggest no significant pleiotropy and heterogeneity on genetic instrumental variants. Outliers-corrected MR analyses after controlling horizontal pleiotropy were still robust. The single-SNP analyses revealed that n-3 fatty acids are likely linked to a decreased risk of AD through FADS cluster, highlighting the significance of the FADS gene in the fatty acids synthesis pathway in the development of AD. Conclusion: Our studies suggest that n-3 fatty acids may reduce the risk of AD. Risk prediction tools based on n-3 fatty acid levels may be valuable methods for improving AD screening and primary prevention. To reduce the risk of AD, individuals could enhance n-3 fatty acids intake through supplement or diet.

Utilization of Physiologically Based Pharmacokinetic Modeling in Pharmacokinetic Study of Natural Medicine: An Overview.

Natural medicine has been widely used for clinical treatment and health care in many countries and regions. Additionally, extracting active ingredients from traditional Chinese medicine and other natural plants, defining their chemical structure and pharmacological effects, and screening potential druggable candidates are also uprising directions in new drug research and development. Physiologically based pharmacokinetic (PBPK) modeling is a mathematical modeling technique that simulates the absorption, distribution, metabolism, and elimination of drugs in various tissues and organs in vivo based on physiological and anatomical characteristics and physicochemical properties. PBPK modeling in drug research and development has gradually been recognized by regulatory authorities in recent years, including the U.S. Food and Drug Administration. This review summarizes the general situation and shortcomings of the current research on the pharmacokinetics of natural medicine and introduces the concept and the advantages of the PBPK model in the study of pharmacokinetics of natural medicine. Finally, the pharmacokinetic studies of natural medicine using the PBPK models are summed up, followed by discussions on the applications of PBPK modeling to the enzyme-mediated pharmacokinetic changes, special populations, new drug research and development, and new indication adding for natural medicine. This paper aims to provide a novel strategy for the preclinical research and clinical use of natural medicine.

Shining light on chiral inorganic nanomaterials for biological issues.

The rapid development of chiral inorganic nanostructures has greatly expanded from intrinsically chiral nanoparticles to more sophisticated assemblies made by organics, metals, semiconductors, and their hybrids. Among them, lots of studies concerning on hybrid complex of chiral molecules with achiral nanoparticles (NPs) and superstructures with chiral configurations were accordingly conducted due to the great advances such as highly enhanced biocompatibility with low cytotoxicity and enhanced penetration and retention capability, programmable surface functionality with engineerable building blocks, and more importantly tunable chirality in a controlled manner, leading to revolutionary designs of new biomaterials for synergistic cancer therapy, control of enantiomeric enzymatic reactions, integration of metabolism and pathology via bio-to nano or structural chirality. Herein, in this review our objective is to emphasize current research state and clinical applications of chiral nanomaterials in biological systems with special attentions to chiral metal- or semiconductor-based nanostructures in terms of the basic synthesis, related circular dichroism effects at optical frequencies, mechanisms of induced optical chirality and their performances in biomedical applications such as phototherapy, bio-imaging, neurodegenerative diseases, gene editing, cellular activity and sensing of biomarkers so as to provide insights into this fascinating field for peer researchers.

Graphene-based nanomaterials for breast cancer treatment: promising therapeutic strategies.

Breast cancer is the most common malignancy in women, and its incidence increases annually. Traditional therapies have several side effects, leading to the urgent need to explore new smart drug-delivery systems and find new therapeutic strategies. Graphene-based nanomaterials (GBNs) are potential drug carriers due to their target selectivity, easy functionalization, chemosensitization and high drug-loading capacity. Previous studies have revealed that GBNs play an important role in fighting breast cancer. Here, we have summarized the superior properties of GBNs and modifications to shape GBNs for improved function. Then, we focus on the applications of GBNs in breast cancer treatment, including drug delivery, gene therapy, phototherapy, and magnetothermal therapy (MTT), and as a platform to combine multiple therapies. Their advantages in enhancing therapeutic effects, reducing the toxicity of chemotherapeutic drugs, overcoming multidrug resistance (MDR) and inhibiting tumor metastasis are highlighted. This review aims to help evaluate GBNs as therapeutic strategies and provide additional novel ideas for their application in breast cancer therapy.

Artificial intelligence in tongue diagnosis: Using deep convolutional neural network for recognizing unhealthy tongue with tooth-mark.

Tongue diagnosis plays a pivotal role in traditional Chinese medicine (TCM) for thousands of years. As one of the most important tongue characteristics, tooth-marked tongue is related to spleen deficiency and can greatly contribute to the symptoms differentiation and treatment selection. Yet, the tooth-marked tongue recognition for TCM practitioners is subjective and challenging. Most of the previous studies have concentrated on subjectively selected features of the tooth-marked region and gained accuracy under 80%. In the present study, we proposed an artificial intelligence framework using deep convolutional neural network (CNN) for the recognition of tooth-marked tongue. First, we constructed relatively large datasets with 1548 tongue images captured by different equipments. Then, we used ResNet34 CNN architecture to extract features and perform classifications. The overall accuracy of the models was over 90%. Interestingly, the models can be successfully generalized to images captured by other devices with different illuminations. The good effectiveness and generalization of our framework may provide objective and convenient computer-aided tongue diagnostic method on tracking disease progression and evaluating pharmacological effect from a informatics perspective.