M6A modification and T cells in adipose tissue inflammation.

Adipose tissue in the obese state can lead to low-grade chronic inflammation while inducing or exacerbating obesity-related metabolic diseases and impairing overall health.T cells, which are essential immune cells similar to macrophages, are widely distributed in adipose tissue and perform their immunomodulatory function; they also cross-talk with other cells in the vascular stromal fraction. Based on a large number of studies, it has been found that N6 methyl adenine (m6A) is one of the most representative of epigenetic modifications, which affects the crosstalk between T cells, as well as other immune cells, in several ways and plays an important role in the development of adipose tissue inflammation and related metabolic diseases. In this review, we first provide an overview of the widespread presence of T cells in adipose tissue and summarize the key role of T cells in adipose tissue inflammation. Next, we explored the effects of m6A modifications on T cells in adipose tissue from the perspective of adipose tissue inflammation. Finally, we discuss the impact of m6a-regulated crosstalk between T cells and immune cells on the prospects for improving adipose tissue inflammation research, providing additional new ideas for the treatment of obesity.

A comprehensive quality evaluation strategy of Mailuoning oral liquid based on fingerprint, qualitative and quantitative analyses.

In order to obtain comprehensive quality evaluation of one traditional Chinese patent medicine of Mailuoning oral liquid (MLN), one smart strategy combined by fingerprint, qualitative and quantitative analyses were carried out in this study. Firstly, the fingerprints of MLN were established by HPLC-UV and HPLC-ELSD, and explained the similarity of twenty-seven batches of MLN by similarity analysis (SA). Secondly, qualitative analysis was performed by high performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (HPLC-QTOF-MS/MS). A total of 60 compounds were identified or tentatively identified based on chemical standards and fragmentation information. Finally, the quantitative method based on UPLC combined with triple quadrupole mass spectrometry (UPLC-QqQ-MS/MS) was developed for the simultaneous determination of 40 target compounds. The results showed that MLN samples of different productive year were clearly discriminated and eight compounds (5-hydroxymethyl-2-furaldehyde, neochlorogenic acid, loganic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, isoacteoside, angoroside C) were selected as differential markers for MLN. In a word, this strategy including fingerprint, identification of chemical composition and multiple-component quantification could be well applied to modern quality evaluation of MLN, which could be valuable for the further quality control of more other traditional Chinese patent medicines.

Targeted characterization and guided isolation of chemical components in Scrophulariae Radix based on LC-MS.

How to achieve rapid characterization and efficient isolation of chemical components from traditional Chinese medicines (TCMs) is what the researchers have been exploring. Herein, a strategy integrated diagnostic ion filtering (DIF) and selected ion recording (SIR)-based screen was firstly proposed and successfully applied for targeted characterization and guided isolation of the chemical components from Scrophulariae Radix, one of TCMs. After acquiring the Q-TOF-MS/MS untargeted data, 128 compounds were characterized based on DIF, a self-built database and comparison of the related literatures, in which 38 compounds were reported for the first time. Subsequently, the SIR method of UPLC-QqQ-MS/MS was adopted to guide the isolation of potential new compounds. Finally, three new compounds together with one known compound with the same skeleton were isolated, and unambiguously elucidated by NMR and acid hydrolysis. These results indicated that this integrated analytical approach is effective and reliable in targeted characterizing chemical components and isolating new compounds from the extract of Scrophulariae Radix.

N6-methyladenosine in macrophage function: a novel target for metabolic diseases.

N6-methyladenosine (m6A) is one of the most prevalent internal transcriptional modifications. Evidence has highlighted changes in m6A in metabolic disorders and various metabolic diseases. However, the precise mechanisms of these m6A changes in such conditions are not understood. Macrophages are crucial for the innate immune system and exert either beneficial or harmful roles in metabolic disease. Notably, m6A was found to be closely related to macrophage phenotype and dysfunction. In this review, we summarize m6A in macrophage function from the perspective of macrophage development, activation, and polarization, pyroptosis, and metabolic disorders. Furthermore, we discuss how m6A-mediated macrophage function affects metabolic diseases, including atherosclerosis and nonalcoholic fatty liver disease (NAFLD). Finally, we discuss challenges and prospects for m6A in macrophage and metabolic diseases with the aim of providing guidance for the treatment of metabolic diseases.

AI-Assisted Diagnosis and Decision-Making Method in Developing Countries for Osteosarcoma.

Osteosarcoma is a malignant tumor derived from primitive osteogenic mesenchymal cells, which is extremely harmful to the human body and has a high mortality rate. Early diagnosis and treatment of this disease is necessary to improve the survival rate of patients, and MRI is an effective tool for detecting osteosarcoma. However, due to the complex structure and variable location of osteosarcoma, cancer cells are highly heterogeneous and prone to aggregation and overlap, making it easy for doctors to inaccurately predict the area of the lesion. In addition, in developing countries lacking professional medical systems, doctors need to examine mass of osteosarcoma MRI images of patients, which is time-consuming and inefficient, and may result in misjudgment and omission. For the sake of reducing labor cost and improve detection efficiency, this paper proposes an Attention Condenser-based MRI image segmentation system for osteosarcoma (OMSAS), which can help physicians quickly locate the lesion area and achieve accurate segmentation of the osteosarcoma tumor region. Using the idea of AttendSeg, we constructed an Attention Condenser-based residual structure network (ACRNet), which greatly reduces the complexity of the structure and enables smaller hardware requirements while ensuring the accuracy of image segmentation. The model was tested on more than 4000 samples from two hospitals in China. The experimental results demonstrate that our model has higher efficiency, higher accuracy and lighter structure for osteosarcoma MRI image segmentation compared to other existing models.