Skin-brain axis signaling mediates behavioral changes after skin wounding

Inhibiting miR-618 Promotes Keratinocytes Proliferation and Migration to Enhance Wound Healing in Mice

The delay in wound healing caused by chronic wounds or pathological scars is a pressing issue in clinical practice, imposing significant economic and psychological burdens on patients. In particular, with the aging of the population and the increasing incidence of diseases such as diabetes, impaired wound healing is one of the growing health problems. MicroRNA (miRNA) plays a crucial role in wound healing and regulates various biological processes. Our results show that miR-618 was significantly upregulated during the inflammatory phase of wound healing.Subsequently, miR-618 promotes the secretion of pro-inflammatory cytokines and regulates the proliferation and migration of keratinocytes. Mechanistically, miR-618 binds to the target gene-Atp11b and inhibits the PI3K-Akt signaling pathway, inhibiting the epithelial-mesenchymal transition (EMT) of keratinocytes. In addition, the PI3K-Akt signaling pathway induces the enrichment of nuclear miR-618, and miR-618 binds to the promoter of Lin7a to regulate gene transcription. Intradermal injection of miR-618 antagomir around full-thickness wounds in peridermal mice effectively accelerates wound closure compared to control. In conclusion, miR-618 antagomir can be a potential therapeutic agent for wound healing.

Causal associations between psoriasis, eczema, urticaria, and mental illness: A bidirectional Mendelian randomization study of the European population

Observational studies have reported a relationship between multiple common dermatoses and mental illness. To assess the potential bidirectional causality between 3 skin disorders (psoriasis, eczema, and urticaria) and 4 psychiatric disorders (bipolar disorder, schizophrenia, major depressive disorder, and anxiety) in the European population, we used Mendelian randomization (MR) analysis, which provides definitive evidence for causal inference. Eligible single nucleotide polymorphisms were screened for dermatological and psychiatric disorders using a genome-wide association study database. We conducted bidirectional, 2-sample MR analysis using instrumental variables related to psoriasis, eczema, and urticaria as exposure factors, and bipolar disorder, schizophrenia, major depression, and anxiety as outcomes. Reverse MR analysis with bipolar disorder, schizophrenia, major depression, and anxiety as exposure and psoriasis, eczema, and urticaria as outcomes were also performed, and the causality was analyzed using inverse-variance weighting (IVW), MR-Egger, and weighted median methods. To thoroughly assess causality, sensitivity analyses were conducted using the IVW, MR-PRESSO, and MR-Egger methods. The results showed that bipolar disorder increased the incidence of psoriasis (odds ratio = 1.271, 95% confidence interval = 1.003-1.612, P = .047), heterogeneity test with Cochran Q test in the IVW showed P value > .05, (P = .302), the MR-Pleiotropy and MR-PRESSO (outlier methods) in the multiplicity test showed P value > .05, (P = .694; P = .441), and MR-Pleiotropy evidence showed no apparent intercept (intercept = -0.060; SE = 0.139; P = .694). Major depression increased the risk of eczema (odds ratio = 1.002, 95% confidence interval = 1.000-1.004, P = .024), heterogeneity test showed P value > .05, (P = .328), multiplicity detection showed P value > .05, (P = .572; P = .340), and MR-Pleiotropy evidence showed no apparent intercept (intercept = -0.099; SE = 0.162; P = .572). Sensitivity analyses of the above results were reliable, and no heterogeneity or multiplicity was found. This study demonstrated a statistically significant causality between bipolar disorder and psoriasis, major depression, and eczema in a European population, which could provide important information for physicians in the clinical management of common skin conditions.

The Skin-Brain Axis: From UV and Pigmentation to Behaviour Modulation

The skin-brain axis has been suggested to play a role in several pathophysiological conditions, including opioid addiction, Parkinson's disease and many others. Recent evidence suggests that pathways regulating skin pigmentation may directly and indirectly regulate behaviour. Conversely, CNS-driven neural and hormonal responses have been demonstrated to regulate pigmentation, e.g., under stress. Additionally, due to the shared neuroectodermal origins of the melanocytes and neurons in the CNS, certain CNS diseases may be linked to pigmentation-related changes due to common regulators, e.g., MC1R variations. Furthermore, the HPA analogue of the skin connects skin pigmentation to the endocrine system, thereby allowing the skin to index possible hormonal abnormalities visibly. In this review, insight is provided into skin pigment production and neuromelanin synthesis in the brain and recent findings are summarised on how signalling pathways in the skin, with a particular focus on pigmentation, are interconnected with the central nervous system. Thus, this review may supply a better understanding of the mechanism of several skin-brain associations in health and disease.

A pro-reparative bioelectronic device for controlled delivery of ions and biomolecules

Wound healing is a complex physiological process that requires precise control and modulation of many parameters. Therapeutic ion and biomolecule delivery has the capability to regulate the wound healing process beneficially. However, achieving controlled delivery through a compact device with the ability to deliver multiple therapeutic species can be a challenge. Bioelectronic devices have emerged as a promising approach for therapeutic delivery. Here, we present a pro-reparative bioelectronic device designed to deliver ions and biomolecules for wound healing applications. The device incorporates ion pumps for the targeted delivery of H+ and zolmitriptan to the wound site. In vivo studies using a mouse model further validated the device's potential for modulating the wound environment via H+ delivery that decreased M1/M2 macrophage ratios. Overall, this bioelectronic ion pump demonstrates potential for accelerating wound healing via targeted and controlled delivery of therapeutic agents to wounds. Continued optimization and development of this device could not only lead to significant advancements in tissue repair and wound healing strategies but also reveal new physiological information about the dynamic wound environment.

Role of stress in skin diseases: A neuroendocrine-immune interaction view

Psychological stress is a crucial factor in the development of many skin diseases, and the stigma caused by skin disorders may further increase the psychological burden, forming a vicious cycle of psychological stress leading to skin diseases. Therefore, understanding the relationship between stress and skin diseases is necessary. The skin, as the vital interface with the external environment, possesses its own complex immune system, and the neuroendocrine system plays a central role in the stress response of the body. Stress-induced alterations in the immune system can also disrupt the delicate balance of immune cells and inflammatory mediators in the skin, leading to immune dysregulation and increased susceptibility to various skin diseases. Stress can also affect the skin barrier function, impair wound healing, and promote the release of pro-inflammatory cytokines, thereby exacerbating existing skin diseases such as psoriasis, atopic dermatitis, acne, and urticaria. In the present review, we explored the intricate relationship between stress and skin diseases from a neuroendocrine-immune interaction perspective. We explored the occurrence and development of skin diseases in the context of stress, the stress models for skin diseases, the impact of stress on skin function and diseases, and relevant epidemiological studies and clinical trials. Understanding the relationship between stress and skin diseases from a neuroendocrine-immune interaction perspective provides a comprehensive framework for targeted interventions and new insights into the diagnosis and treatment of skin diseases.

Interorgan communication networks in the kidney-lung axis

The homeostasis and health of an organism depend on the coordinated interaction of specialized organs, which is regulated by interorgan communication networks of circulating soluble molecules and neuronal connections. Many diseases that seemingly affect one primary organ are really multiorgan diseases, with substantial secondary remote organ complications that underlie a large part of their morbidity and mortality. Acute kidney injury (AKI) frequently occurs in critically ill patients with multiorgan failure and is associated with high mortality, particularly when it occurs together with respiratory failure. Inflammatory lung lesions in patients with kidney failure that could be distinguished from pulmonary oedema due to volume overload were first reported in the 1930s, but have been largely overlooked in clinical settings. A series of studies over the past two decades have elucidated acute and chronic kidney-lung and lung-kidney interorgan communication networks involving various circulating inflammatory cytokines and chemokines, metabolites, uraemic toxins, immune cells and neuro-immune pathways. Further investigations are warranted to understand these clinical entities of high morbidity and mortality, and to develop effective treatments.

Quantifying innervation facilitated by deep learning in wound healing

The peripheral nerves (PNs) innervate the dermis and epidermis, and are suggested to play an important role in wound healing. Several methods to quantify skin innervation during wound healing have been reported. Those usually require multiple observers, are complex and labor-intensive, and the noise/background associated with the immunohistochemistry (IHC) images could cause quantification errors/user bias. In this study, we employed the state-of-the-art deep neural network, Denoising Convolutional Neural Network (DnCNN), to perform pre-processing and effectively reduce the noise in the IHC images. Additionally, we utilized an automated image analysis tool, assisted by Matlab, to accurately determine the extent of skin innervation during various stages of wound healing. The 8 mm wound is generated using a circular biopsy punch in the wild-type mouse. Skin samples were collected on days 3, 7, 10 and 15, and sections from paraffin-embedded tissues were stained against pan-neuronal marker- protein-gene-product 9.5 (PGP 9.5) antibody. On day 3 and day 7, negligible nerve fibers were present throughout the wound with few only on the lateral boundaries of the wound. On day 10, a slight increase in nerve fiber density appeared, which significantly increased on day 15. Importantly, we found a positive correlation (R2 = 0.926) between nerve fiber density and re-epithelization, suggesting an association between re-innervation and re-epithelization. These results established a quantitative time course of re-innervation in wound healing, and the automated image analysis method offers a novel and useful tool to facilitate the quantification of innervation in the skin and other tissues.

Quantifying innervation facilitated by deep learning in wound healing

The peripheral nerves (PNs) innervate the dermis and epidermis, which have been suggested to play an important role in wound healing. Several methods to quantify skin innervation during wound healing have been reported. Those usually require multiple observers, are complex and labor-intensive, and noise/background associated with the Immunohistochemistry (IHC) images could cause quantification errors/user bias. In this study, we employed the state-of-the-art deep neural network, DnCNN, to perform pre-processing and effectively reduce the noise in the IHC images. Additionally, we utilized an automated image analysis tool, assisted by Matlab, to accurately determine the extent of skin innervation during various stages of wound healing. The 8mm wound is generated using a circular biopsy punch in the wild-type mouse. Skin samples were collected on days 3,7,10 and 15, and sections from paraffin-embedded tissues were stained against pan-neuronal marker- protein-gene-product 9.5 (PGP 9.5) antibody. On day 3 and day 7, negligible nerve fibers were present throughout the wound with few only on the lateral boundaries of the wound. On day 10, a slight increase in nerve fiber density appeared, which significantly increased on day 15. Importantly we found a positive correlation (R 2  = 0.933) between nerve fiber density and re-epithelization, suggesting an association between re-innervation and re-epithelization. These results established a quantitative time course of re-innervation in wound healing, and the automated image analysis method offers a novel and useful tool to facilitate the quantification of innervation in the skin and other tissues.

Quantifying innervation facilitated by deep learning in wound healing

The peripheral nerves (PNs) innervate the dermis and epidermis, which have been suggested to play an important role in wound healing. Several methods to quantify skin innervation during wound healing have been reported. Those usually require multiple observers, are complex and labor-intensive, and noise/background associated with the Immunohistochemistry (IHC) images could cause quantification errors/user bias. In this study, we employed the state-of-the-art deep neural network, DnCNN, to perform pre-processing and effectively reduce the noise in the IHC images. Additionally, we utilized an automated image analysis tool, assisted by Matlab, to accurately determine the extent of skin innervation during various stages of wound healing. The 8mm wound is generated using a circular biopsy punch in the wild-type mouse. Skin samples were collected on days 3,7,10 and 15, and sections from paraffin-embedded tissues were stained against pan-neuronal marker- protein-gene-product 9.5 (PGP 9.5) antibody. On day 3 and day 7, negligible nerve fibers were present throughout the wound with few only on the lateral boundaries of the wound. On day 10, a slight increase in nerve fiber density appeared, which significantly increased on day 15. Importantly we found a positive correlation (R- 2 = 0.933) between nerve fiber density and re-epithelization, suggesting an association between re-innervation and re-epithelization. These results established a quantitative time course of re-innervation in wound healing, and the automated image analysis method offers a novel and useful tool to facilitate the quantification of innervation in the skin and other tissues.