Patients with inflammatory bowel disease (IBD) require long-term pharmacotherapy. Due to the wide variety of clinically available drugs, medication safety has become increasingly concerning. As an indispensable component of pharmaceutical formulations, drug excipients may induce various adverse reactions, including rash, allergic responses, and gastrointestinal discomfort, and may even lead to severe organic injury. However, they are often overlooked in clinical practice. Therefore, identifying and managing excipient-related adverse reactions is crucial for ensuring medication safety. To address this issue, this article systematically reviews common excipients in IBD therapeutics, the underlying mechanisms of excipient-induced adverse reactions, and corresponding management strategies, aiming to enhance clinicians' awareness of excipient-related issues, improve their ability to recognize and manage such reactions, and ultimately ensure patient safety.

To analyze potential adverse drug events(ADEs) associated with ustekinumab and upadacitinib in the treatment of inflammatory bowel disease(IBD) based on an international authoritative database, thereby providing evidence for clinical medication safety.

Bipolar disorder is a chronic mental disorder with a high rate of relapse, disability and suicide. Safe, effective and rapid onset non-invasive neuromodulation therapy technology is becoming a research hotspot in the treatment of bipolar disorder. In this paper, the latest clinical research progress of the main techniques in this field is summarized and reviewed, and its future prospects is also forecasted.

Bipolar disorder is a chronic mental disorder with a high rate of relapse, disability and suicide. Safe, effective and rapid onset non-invasive neuromodulation therapy technology is becoming a research hotspot in the treatment of bipolar disorder. In this paper, the latest clinical research progress of the main techniques in this field is summarized and reviewed, and its future prospects is also forecasted.

Purpose/Significance To explore the characteristics and clinical significance of differentially expressed genes closely re-lated to HPV E6/E7 by using bioinformatics.Method/Process The cervical tissue and clinical information of cervical cancer in TCGA and GTEx of UCSC are used as the training set.The expression profile chip GSE63514 related to cervical cancer in GEO is used as the validation set.Firstly,the limma package of R software is used to screen DEGs of tumor and normal samples,and Venn map of genes re-lated to E6/E7 protein in MigDB is made.Survival analysis is performed by survival kit and verified by ROC and protein expression lev-els.Secondly,key genes are obtained by copy number variation and methylation correlation.Finally,the specific co-expression network is constructed and enrichment analysis and immune infiltration analysis are performed.Result/Conclusion There are 101 differentially expressed genes related to HPV E6/E7 protein,and three genes are found to have significance after screening,namely E2F1,MCM4 and PCNA.At the same time,it is found that the genes in the specific coexpression network are significantly enriched in the DNA replication and chromosome organization pathways.Immune correlation analysis shows that key genes are significantly associated with CD4 T cells,B cells and neutrophils.DNA replication,chromosome organization,etc.,are the molecular mechanisms and key genes significantly related to the development of cervical squamous cell carcinoma and HPV E6/E7 encoded proteins.

In order to better assist doctors in the diagnosis of dry eye and improve the ability of ophthalmologists to recognize the condition of meibomian gland, a meibomian gland image segmentation and enhancement method based on Mobile-U-Net network was proposed. Firstly, Mobile-Net is used as the coding part of U-Net for down sampling, and then features are extracted and fused with the features in decoder to guide image segmentation. Secondly, the segmentation of meibomian gland region is enhanced to assist doctors to judge the condition. Thirdly, a large number of meibomian gland images are collected to train and verify the semantic segmentation network, and the clarity evaluation index is used to verify the meibomian gland enhancement effect. The experimental results show that the similarity coefficient of the proposed method is stable at 92.71%, and the image clarity index is better than the similar dry eye detection instruments on the market.
Deep Learning ; Diagnostic Imaging ; Dry Eye Syndromes ; Humans ; Image Processing, Computer-Assisted ; Meibomian Glands/diagnostic imaging*