Abnormal brain structure in atopic dermatitis: Evidence from Mendelian randomization study

Feline atopic syndrome: An insight into its effects on the central nervous system through vestibular disease

A 2-year-old male Abyssinian cat was presented with a left head tilt, lethargy, compulsive walking with a left-circling tendency, medial strabismus, a delayed pupillary light reflex, abdominal papules, and severe pruritus that began at 4 mo of age. Imaging revealed mineral opacity foci in the left ear, and magnetic resonance imaging confirmed heterogeneous signal changes, suggesting a diagnosis of otitis interna. No abnormal findings were observed on cerebrospinal fluid tests. Treatment with prednisolone, antibiotics, a hypoallergenic diet, and probiotics led to the resolution of skin issues and neurological improvement. Despite a persistent head tilt after more than 5 mo, there was no recurrence of severe neurological symptoms during the tapering off of prednisolone treatment. Key clinical message: This is the first case report illustrating the potential impact of feline atopic syndrome on the central nervous system. It emphasizes the importance of viewing feline atopic syndrome as more than just a skin disorder.

Genetic landscape of atopic dermatitis

PURPOSE OF REVIEW

This review summarizes recent advances in identifying genetic risk factors for atopic dermatitis and how these genetic associations are being used to explore the causal relationships between atopic dermatitis and potential risk factors and downstream outcomes.

RECENT FINDINGS

A recent large-scale GWAS meta-analysis has identified 91 genetic loci associated with atopic dermatitis. Rare variant studies have also identified new gain-of-function or loss-of-function variants implicated in atopic dermatitis, particularly for FLG and STAT6/JAK1 . Finally, there has been a surge in utilizing genetic association data to investigate the causal relationships between atopic dermatitis and other traits. Mendelian randomization studies have found that various metabolites and gut microbiota are causal for atopic dermatitis and have causally implicate atopic dermatitis in the development of alopecia areata, diabetes, vascular dementia and some cancers.

SUMMARY

The past year has seen a huge increase in the genes implicated for atopic dermatitis and in the use of genetics to explore causal relationships. The latter requires caution in implementation and interpretation, but is a promising area of research. In the coming years, increasing the ethnic diversity of atopic dermatitis genetic studies would be very welcome and the translation of current genetic findings into new drugs will be an exciting area of development.

Recent advances in artificial intelligent strategies for tissue engineering and regenerative medicine

BACKGROUND

Tissue engineering and regenerative medicine (TERM) aim to repair or replace damaged or lost tissues or organs due to accidents, diseases, or aging, by applying different sciences. For this purpose, an essential part of TERM is the designing, manufacturing, and evaluating of scaffolds, cells, tissues, and organs. Artificial intelligence (AI) or the intelligence of machines or software can be effective in all areas where computers play a role.

METHODS

The "artificial intelligence," "machine learning," "tissue engineering," "clinical evaluation," and "scaffold" keywords used for searching in various databases and articles published from 2000 to 2024 were evaluated.

RESULTS

The combination of tissue engineering and AI has created a new generation of technological advancement in the biomedical industry. Experience in TERM has been refined using advanced design and manufacturing techniques. Advances in AI, particularly deep learning, offer an opportunity to improve scientific understanding and clinical outcomes in TERM.

CONCLUSION

The findings of this research show the high potential of AI, machine learning, and robots in the selection, design, and fabrication of scaffolds, cells, tissues, or organs, and their analysis, characterization, and evaluation after their implantation. AI can be a tool to accelerate the introduction of tissue engineering products to the bedside.

HIGHLIGHTS

The capabilities of artificial intelligence (AI) can be used in different ways in all the different stages of TERM and not only solve the existing limitations, but also accelerate the processes, increase efficiency and precision, reduce costs, and complications after transplantation. ML predicts which technologies have the most efficient and easiest path to enter the market and clinic. The use of AI along with these imaging techniques can lead to the improvement of diagnostic information, the reduction of operator errors when reading images, and the improvement of image analysis (such as classification, localization, regression, and segmentation).

The causal relationship between atopic dermatitis and brain cancer: A bidirectional Mendelian randomization study

BACKGROUND

Atopic dermatitis ranks among the prevalent skin disorders. Research has indicated a potential association with brain cancer. Yet, establishing a direct causal relationship between atopic dermatitis and brain cancer continues to be challenging.

MATERIALS AND METHODS

We extracted single nucleotide polymorphisms (SNPs) significantly associated with atopic dermatitis (sample size = 382 254) at a genome-wide level from a large Finnish Genome-Wide Association Study (GWAS) dataset (n cases = 15 208, n controls = 367 046). Summary data for 372 622 cases of brain cancer (n cases = 606, n controls = 372 016) were obtained via the IEU Open GWAS database. We employed the Inverse Variance Weighted (IVW) method as our primary analytical approach for Mendelian Randomization (MR) analysis. Additionally, heterogeneity was measured using Cochran's Q value, and horizontal pleiotropy was evaluated using MR-Egger 、Mendelian Randomization Pleiotropy RESidual Sum and Outlier and leave-one-out analyses.

RESULTS

The risk of brain cancer increases with the presence of atopic dermatitis, as evidenced by the odds ratios (ORs) and 95% confidence intervals (CIs),(OR = 1.0005; 95% CI = 1.0001, 1.0009; p = 0.0096). However, when conducting the analysis in reverse, no significant link was observed.

CONCLUSION

The findings from our study indicate a causative link between atopic dermatitis and brain cancer, highlighting the importance of conducting broader clinical investigations into their potential association going forward.

Skin ultrasonography and magnetic resonance; new clinical applications and instrumentation

BACKGROUND

Technological advances in skin ultrasonography and magnetic resonance are discussed.

METHODS

Literature review.

RESULTS

40 publications cited.

CONCLUSION

This article illustrates crucial contributions made by the Editors, the Editorial Board and this Journal to these fields.