Anti-IgLON5 disease: a novel topic beyond neuroimmunology.

Anti-IgLON5 disease is a recently defined autoimmune disorder of the nervous system associated with autoantibodies against IgLON5. Given its broad clinical spectrum and extremely complex pathogenesis, as well as difficulties in its early diagnosis and treatment, anti-IgLON5 disease has become the subject of considerable research attention in the field of neuroimmunology. Anti-IgLON5 disease has characteristics of both autoimmunity and neurodegeneration due to the unique activity of the anti-IgLON5 antibody. Neuropathologic examination revealed the presence of a tauopathy preferentially affecting the hypothalamus and brainstem tegmentum, potentially broadening our understanding of tauopathies. In contrast to that seen with other autoimmune encephalitis-related antibodies, basic studies have demonstrated that IgLON5 antibody-induced neuronal damage and degeneration are irreversible, indicative of a potential link between autoimmunity and neurodegeneration in anti-IgLON5 disease. Herein, we comprehensively review and discuss basic and clinical studies relating to anti-IgLON5 disease to better understand this complicated disorder.

[Remitting Seronegative Symmetrical Synovitis with Pitting Edema associated with Lung Malignancy:Case Report and Literature Review].

Remitting seronegative symmetrical synovitis with pitting edema(RS3PE),the inflammatory arthritis attacking mainly elderly males,is characterized by symmetrical synovitis with pitting edema of the dorsum of hands and feet and the absence of rheumatoid factor.RS3PE commonly accompanies malignant tumor,infections and other diseases.Here we report a case of RS3PE associated with lung malignancy and review other six cases to summarize the clinical features,treatment and prognosis.

Effectiveness of Combined Immunoglobulin and Glucocorticoid Treatments in a Patient With Stiff Limb Syndrome: Case Report and Review of the Literature.

Stiff limb syndrome (SLS) is a rare autoimmune-related central nervous system disorder, resulting in stiffness and spasms of limbs since onset with rare involvement of the truncal muscles. However, SLS patients will gain notable effects by appropriate therapy focusing on symptomatic treatment and immunotherapy. We reported on a 55-year-old female who showed typical painful spasms in both lower limbs and abduction of the right eyeball that partially responded to low-dose diazepam and had high-titer anti-glutamic acid decarboxylase (anti-GAD) antibody. Electromyography (EMG) only showed continuous motor unit activity (CMUA) in the anterior tibialis and right triceps. Eventually, our patient was diagnosed with SLS and treated with intravenous immunoglobulin (IVIG) and glucocorticoid combined simultaneously. She obtained notable effects. We also review and summarize the current literature on clinical characteristics, coexisting disease, treatment, and outcome of 40 patients with SLS. We hope that this report will provide a basis for further understanding of SLS and promote the formation of more advanced diagnosis and treatment processes.

Multiple genetic factors affecting the pharmacokinetic and pharmacodynamic processes of tacrolimus in Chinese myasthenia gravis patients.

PURPOSE: Tacrolimus is a novel effective immunosuppressant for myasthenia gravis (MG) patients. However, the narrow therapeutic window, and high inter- and intrapatient variation in bioavailability largely limited its clinical application. This article intended to find the SNPs influencing clinical outcome and discover the possible mechanisms. METHODS: Based on the tagSNPs genotyped by Improved Multiple Ligase Detection Reaction, Plink 1.07 was used to find the SNPs having close interaction to tacrolimus serum concentration, QMG score changes or even reasonable drug dose. Then we searched several databases to predict the possible miRNA binding rs15524 sequence. Based on the prediction, dual-luciferase reporter assay and miRNA transfection were used to discover the mechanism of how SNP rs15524 controls tacrolimus serum concentration through influencing CYP3A5 expression. RESULTS: In this article, we found multiple SNPs on CYP3A4, CYP3A5, FKBP1A, NFATC2 genes were predicted closely related to tacrolimus serum concentration, therapeutic effect which reflected by QMG score changes or even reasonable drug dose. After in silico miRNA selection, possible relationship between hsa-miR-500a and rs15524 was found. With the help of dual-luciferase reporter assay, wild-type rs15524 (T allele) was found having a stronger binding affinity for hsa-miR-500a. Higher expression of CYP3A5 may also led by lower hsa-miR-500a level. CONCLUSIONS: SNP rs15524 may control CYP3A5 expression by affecting the binding affinity between CYP3A5 3'UTR and hsa-miR-500a. Wild type (T allele) 3'UTR of CYP3A5 has stronger binding affinity to hsa-miR-500a and cause lower CYP3A5 expression and higher tacrolimus serum concentration.

The Application of Machine Learning Techniques in Clinical Drug Therapy.

INTRODUCTION: The development of a novel drug is an extremely complicated process that includes the target identification, design and manufacture, and proper therapy of the novel drug, as well as drug dose selection, drug efficacy evaluation, and adverse drug reaction control. Due to the limited resources, high costs, long duration, and low hit-to-lead ratio in the development of pharmacogenetics and computer technology, machine learning techniques have assisted novel drug development and have gradually received more attention by researchers. METHODS: According to current research, machine learning techniques are widely applied in the process of the discovery of new drugs and novel drug targets, the decision surrounding proper therapy and drug dose, and the prediction of drug efficacy and adverse drug reactions. RESULTS AND CONCLUSION: In this article, we discussed the history, workflow, and advantages and disadvantages of machine learning techniques in the processes mentioned above. Although the advantages of machine learning techniques are fairly obvious, the application of machine learning techniques is currently limited. With further research, the application of machine techniques in drug development could be much more widespread and could potentially be one of the major methods used in drug development.

SNPs affecting the clinical outcomes of regularly used immunosuppressants.

Recent studies have suggested that genomic diversity may play a key role in different clinical outcomes, and the importance of SNPs is becoming increasingly clear. In this article, we summarize the bioactivity of SNPs that may affect the sensitivity to or possibility of drug reactions that occur among the signaling pathways of regularly used immunosuppressants, such as glucocorticoids, azathioprine, tacrolimus, mycophenolate mofetil, cyclophosphamide and methotrexate. The development of bioinformatics, including machine learning models, has enabled prediction of the proper immunosuppressant dosage with minimal adverse drug reactions for patients after organ transplantation or for those with autoimmune diseases. This article provides a theoretical basis for the personalized use of immunosuppressants in the future.