A case of severe erythema nodosum induced by methimazole

Predicting Drugs Suspected of Causing Adverse Drug Reactions Using Graph Features and Attention Mechanisms

BACKGROUND

Adverse drug reactions (ADRs) refer to an unintended harmful reaction that occurs after the administration of a medication for therapeutic purposes, which is unrelated to the intended pharmacological action of the drug. In the United States, ADRs account for 6% of all hospital admissions annually. The cost of ADR-related illnesses in 2016 was estimated at USD 528.4 billion. Increasing the awareness of ADRs is an effective measure to prevent them. Assessing suspected drugs in adverse events helps to enhance the awareness of ADRs.

METHODS

In this study, a suspect drug assisted judgment model (SDAJM) is designed to identify suspected drugs in adverse events. This framework utilizes the graph isomorphism network (GIN) and an attention mechanism to extract features based on patients' demographic information, drug information, and ADR information.

RESULTS

By comparing it with other models, the results of various tests show that this model performs well in predicting the suspected drugs in adverse reaction events. ADR signal detection was conducted on a group of cardiovascular system drugs, and case analyses were performed on two classic drugs, Mexiletine and Captopril, as well as on two classic antithyroid drugs. The results indicate that the model can accomplish the task of predicting drug ADRs. Validation using benchmark datasets from ten drug discovery domains shows that the model is applicable to classification tasks on the Tox21 and SIDER datasets.

CONCLUSIONS

This study applies deep learning methods to construct the SDAJM model for three purposes: (1) identifying drugs suspected to cause adverse drug events (ADEs), (2) predicting the ADRs of drugs, and (3) other drug discovery tasks. The results indicate that this method can offer new directions for research in the field of ADRs.

Fe single atoms encapsulated in N, P-codoped carbon nanosheets with enhanced peroxidase-like activity for colorimetric detection of methimazole

Excessive use of antithyroid drug methimazole (MMI) in pharmaceutical samples can cause hypothyroidism and symptoms of metabolic decline. Hence, it is urgent to develop rapid, low cost and accurate colorimetric method with peroxidase-like nanozymes for determination of MMI in medical, nutrition and pharmaceutical studies. Herein, Fe single atoms were facilely encapsulated into N, P-codoped carbon nanosheets (Fe SAs/NP-CSs) by a simple pyrolysis strategy, as certified by a series of characterizations. UV-vis absorption spectroscopy was employed to illustrate the high peroxidase-mimicking activity of the resultant Fe SAs/NP-CSs nanozyme through the typical catalysis of 3,3',5,5'-tetramethylbenzidine (TMB) oxidation. The catalytic mechanism was scrutionously investigated by the fluorescence spectroscopy and electron paramagnetic resonance (EPR) tests. Additionally, the introduced MMI had the ability to reduce the oxidation of TMB (termed oxTMB) as a peroxidase inhibitor, coupled by fading the blue color. By virtue of the above findings, a visual colorimetric sensor was established for dual detection of methimazole (MMI) with a linear scope of 5-50 mM and a LOD of 1.57 mM, coupled by assay of H2O2 at a linear range of 3-50 mM. According to the irreversible oxidation of the drug, its screening with acceptable results was achieved on the sensing platform even in commercial tablets The Fe SAs/NP-CSs nanozyme holds great potential for clinical diagnosis and drug analysis.

Erythema nodosum

BACKGROUND

Erythema nodosum can be associated with a number of systemic diseases. There is, however, a paucity of information in the pediatric literature on this condition. The purpose of this article is to familiarize pediatricians with the evaluation, diagnosis, and treatment of erythema nodosum.

DATA SOURCES

A PubMed search was completed in Clinical Queries using the key terms "erythema nodosum".

RESULTS

Clinically, erythema nodosum presents with a sudden onset of painful, erythematous, subcutaneous nodules mainly localized to the pretibial areas. Lesions are usually bilateral and symmetrical, ranging from 1 to 5 cm in diameter. Erythema nodosum may be associated with a variety of conditions such as infection, medications, sarcoidosis, pregnancy, inflammatory bowel disease, vaccination, autoimmune disease, malignancy, and miscellaneous causes. The condition is idiopathic in approximately 50% of cases. The diagnosis is mainly clinical with biopsy reserved for atypical cases. To evaluate for the underlying cause, some basic laboratory screening studies are worthwhile in most cases and include a complete blood cell count, erythrocyte sedimentation rate and/or C-reactive protein, throat swab culture, antistreptococcal O titers, and a chest radiograph. Other tests should be individualized, guided by the history and physical examination results. Most cases of erythema nodosum are self-limited and require no treatment. Bed rest and leg elevation are generally recommended to reduce the discomfort. Nonsteroidal anti-inflammatory drugs are the first-line treatment for pain management.

CONCLUSIONS

As erythema nodosum is often a cutaneous manifestation of a systemic disease, a thorough search should be performed to reveal the underlying cause.