Tight junction (TJ) is a “zippering up” junction structure located at the uppermost portion of adjacent epithelial/endothelial cells in organs and tissues. TJs maintain the relative stability of intracellular substances and functions by closing or opening intercellular pathways, coordinating the entry and exit of molecules of different sizes and charges, and regulating the permeability of paracellular barrier. TJs also prevent microbial invasion, maintain epithelial/endothelial cell polarity, and regulate cell proliferation. TJs are widely present in the skin and mucosal epithelial barriers, intestinal epithelial barrier, glomerular filtration barrier, bladder epithelial barrier, blood-brain barrier, brain-blood tumor barrier, and blood-testis barrier. TJ dysfunction in different organs can lead to a variety of diseases. In addition to signal pathways, transcription factors, DNA methylation, histone modification, TJ proteins can also be regulated by a variety of non-coding RNAs, such as micro-RNAs, long-noncoding RNAs, and circular RNAs, directly or indirectly. This review summarizes the structure of TJs and introduces the functions and regulatory mechanisms of TJs in different organs and tissues. The roles and mechanisms of non-coding RNAs in the regulation of TJs are also highlighted in this review.

Background: Psoriasis is one of the most frequent inflammatory skin conditions and could be treated via tele-dermatology, provided that the current lack of reliable tools for objective severity assessments is overcome. Psoriasis Area and Severity Index (PASI) has a prominent level of subjectivity and is rarely used in real practice, although it is the most widely accepted metric for measuring psoriasis severity currently. Objective: This study aimed to develop an image–artificial intelligence (AI)–based validated system for severity assessment with the explicit intention of facilitating long-term management of patients with psoriasis. Methods: A deep learning system was trained to estimate the PASI score by using 14,096 images from 2367 patients with psoriasis. We used 1962 patients from January 2015 to April 2021 to train the model and the other 405 patients from May 2021 to July 2021 to validate it. A multiview feature enhancement block was designed to combine vision features from different perspectives to better simulate the visual diagnostic method in clinical practice. A classification header along with a regression header was simultaneously applied to generate PASI scores, and an extra cross-teacher header after these 2 headers was designed to revise their output. The mean average error (MAE) was used as the metric to evaluate the accuracy of the predicted PASI score. By making the model minimize the MAE value, the model becomes closer to the target value. Then, the proposed model was compared with 43 experienced dermatologists. Finally, the proposed model was deployed into an app named SkinTeller on the WeChat platform. Results: The proposed image-AI–based PASI-estimating model outperformed the average performance of 43 experienced dermatologists with a 33.2% performance gain in the overall PASI score. The model achieved the smallest MAE of 2.05 at 3 input images by the ablation experiment. In other words, for the task of psoriasis severity assessment, the severity score predicted by our model was close to the PASI score diagnosed by experienced dermatologists. The SkinTeller app has been used 3369 times for PASI scoring in 1497 patients from 18 hospitals, and its excellent performance was confirmed by a feedback survey of 43 dermatologist users. Conclusions: An image-AI–based psoriasis severity assessment model has been proposed to automatically calculate PASI scores in an efficient, objective, and accurate manner. The SkinTeller app may be a promising alternative for dermatologists’ accurate assessment in the real world and chronic disease self-management in patients with psoriasis.

The excessive production of reactive oxygen species (ROS) can lead to single nucleic acid base damage, DNA strand breakage, inter- and intra-strand cross-linking of nucleic acids, and protein-DNA cross-linking involved in the pathogenesis of cancer, neurodegenerative diseases, and aging. G-quadruplex (G4) is a stacked nucleic acid structure that is ubiquitous across regulatory regions of multiple genes. Abnormal formation and destruction of G4s due to multiple factors, including cations, helicases, transcription factors (TFs), G4-binding proteins, and epigenetic modifications, affect gene replication, transcription, translation, and epigenetic regulation. Due to the lower redox potential of G-rich sequences and unique structural characteristics, G4s are highly susceptible to oxidative damage. Additionally, the formation, stability, and biological regulatory role of G4s are affected by ROS. G4s are involved in regulating gene transcription, translation, and telomere length maintenance, and are therefore key players in age-related degeneration. Furthermore, G4s also mediate the antioxidant process by forming stress granules and activating Nrf2, which is suggestive of their involvement in developing ROS-related diseases. In this review, we have summarized the crosstalk between ROS and G4s, and the possible regulatory mechanisms through which G4s play roles in aging and age-related diseases.

Keratinocytes are closely associated with innate immunity and inflammatory responses, and are dysregulated during the development of psoriasis, but the underlying mechanisms are not yet fully understood. This work aims to reveal the effects of long non-coding RNA (lncRNA) UCA1 in psoriatic keratinocytes. UCA1 was identified as a psoriasis-related lncRNA that highly expressed in psoriatic lesions. The transcriptome and proteome data of keratinocyte cell line HaCaT showed that UCA1 could positively regulate inflammatory functions, such as response to cytokine. Furthermore, UCA1 silencing decreased inflammatory cytokine secretion and innate immunity gene expression in HaCaT, its culture supernatant also decreased the migration and tube formation ability of vascular endothelial cells (HUVECs). Mechanistically, UCA1 activated the NF-κB signaling pathway, which is regulated by HIF-1α and STAT3. We also observed a direct interaction between UCA1 and N6-methyladenosine (m⁶A) methyltransferase METTL14. Knocking down METTL14 counteracted the effects of UCA1 silencing, indicating that it can suppress inflammation. In addition, the levels of m⁶A-modified HIF-1α were decreased in psoriatic lesions, indicating that HIF-1α is a potential target of METTL14. Taken together, this work indicates that UCA1 positively regulates keratinocyte-driven inflammation and psoriasis development by binding to METTL14, and activating HIF-1α and NF-κB signaling pathway. Our findings provide new insights into the molecular mechanisms of keratinocyte-driven inflammation in psoriasis.