Research on IgG4-related disease (IgG4-RD), an autoimmune condition recognized to be a unique disease entity only two decades ago, has processed from describing patients' symptoms and signs to summarizing its critical pathological features, and further to investigating key pathogenic mechanisms. Challenges in gaining a better understanding of the disease, however, stem from its relative rarity-potentially attributed to underrecognition-and the absence of ideal experimental animal models. Recently, with the development of various high-throughput techniques, "omics" studies at different levels (particularly the single-cell omics) have shown promise in providing detailed molecular features of IgG4-RD. While, the application of omics approaches in IgG4-RD is still at an early stage. In this paper, we review the current progress of omics research in IgG4-RD and discuss the value of machine learning methods in analyzing the data with high dimensionality.
Humans ; Immunoglobulin G4-Related Disease/metabolism* ; Immunoglobulin G/metabolism* ; Machine Learning ; Animals ; Proteomics/methods*

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique

[This corrects the article DOI: 10.1016/j.jpha.2023.08.006.].

A major impedance to neuronal regeneration after peripheral nerve injury(PNI)is the activation of various programmed cell death mechanisms in the dorsal root ganglion.Ferroptosis is a form of pro-grammed cell death distinguished by imbalance in iron and thiol metabolism,leading to lethal lipid peroxidation.However,the molecular mechanisms of ferroptosis in the context of PNI and nerve regeneration remain unclear.Ferroportin(Fpn),the only known mammalian nonheme iron export protein,plays a pivotal part in inhibiting ferroptosis by maintaining intracellular iron homeostasis.Here,we explored in vitro and in vivo the involvement of Fpn in neuronal ferroptosis.We first delineated that reactive oxygen species at the injury site induces neuronal ferroptosis by increasing intracellular iron via accelerated UBA52-driven ubiquitination and degradation of Fpn,and stimulation of lipid peroxidation.Early administration of the potent arterial vasodilator,hydralazine(HYD),decreases the ubiquitination of Fpn after PNI by binding to UBA52,leading to suppression of neuronal cell death and significant ac-celeration of axon regeneration and motor function recovery.HYD targeting of ferroptosis is a promising strategy for clinical management of PNI.

Cerebral hemorrhage has a high incidence and numerous complications.Pulmonary in-fection is one of the serious complications of cerebral hemorrhage.Domestic and foreign researchers have developed pulmonary infection prediction models for patients with cerebral hemorrhage,which can provide references for clinical medical staff to identify high-risk groups in the early stage and formulate intervention strategies as soon as possible.This article summarized the risk factors of pulmonary infec-tion,the overview of risk prediction models,the current research status of pulmonary infection predic-tion models,and the significance of prediction,aiming to provide references for the evaluation and pre-vention of pulmonary infection in patients with cerebral hemorrhage.

Objective:Childhood traumatic experiences greatly influenced the brain network activities of patients with depression,and there is an urgent need to explore the temporal dynamics for these changes.This study aims to investigate the abnormalities of resting-state electroencephalogram(EEG)microstates in eye-open state of depressed adolescents and to explore the correlations between their EEG microstates and the childhood traumatic experience. Methods:Using resting-state EEG microstate analysis,we explored the temporal dynamics of brain activity in patients with adolescent depression.This study selected 66 adolescents with depression as a patient group,and 27 healthy adolescents as a healthy control group.A modified k-means clustering algorithm was used to classify the 64-channel resting-state EEG data into different microstates.Independent sample t-tests were used to compare the microstate parameters between the 2 groups and further assciations between these parameters and childhood traumatic experience in patients were explored via using Spearman correlation. Results:In this study,significant differences were observed in the occurrence and transition probabilities of EEG microstates between the healthy control and the patient group.Notably,there was a statistically significant difference(P＜0.05)in the occurrence of microstate A across 2 groups,exhibiting a negative correlation with the emotional abuse component within the childhood trauma scores(Spearman's rho=-0.31,P=0.013).Furthermore,patient-specific,non-random transitions from microstate B to A(Spearman's rho=-0.30,P=0.015)and C to A(Spearman's rho=-0.31,P=0.013)were inversely associated with the scores of emotional abuse factors from childhood trauma in the patient group,showing statistically significant differences when comparing to the healthy controls(P＜0.05).Upon stratification into quartiles based on the emotional abuse factor scores,the occurrence of microstate A,as well as the transition rates from microstates B to A and C to A,retained statistical significance following adjustment for multiple comparisons(all P＜0.05). Conclusion:The abnormal temporal dynamics in brain networks of adolescents with depression are linked to childhood emotional abuse.Those who have suffered severe emotional abuse may show greater impairments in the brain's visual and central executive networks.EEG microstate analysis could be a potential tool for detecting adolescent depression with severe childhood trauma.

Objective:To explore the correlation between serum NLR and SII levels and postmenopausal osteoporotic vertebral compression fracture (OVCF) and to analyze the short-term prognostic value.Methods:A total of 132 patients with postmenopausal OVCF admitted to our hospital from Dec. 2018 to Dec. 2021 were selected as the study group, and 98 patients with postmenopausal osteoporosis but did not suffer from OVCF were selected as the control group. According to the recurrence of postmenopausal OVCF fractures, the ROC curves of NLR and SII were plotted, and their prognostic value for postmenopausal osteoporosis OVCF was analyzed.Results:NLR level was 2.96±0.41 and STI level was 39.41±23.45 in the control group. The level of NLR was 3.42±0.32 and SII was 431.77±31.14 in the research group ( P<0.05) . Multivariate Logistic regression analysis showed that lumbar bone density ( OR=0.030, 95%CI: 0.001-0.832, P=0.042) , NLR level ( OR=29.43, 95%CI: 9.840-103.6, P=0.001) and SII level ( OR=1.048, 95%CI: 1.034-1.066, P=0.001) were all risk factors affecting postmenopausal OVCF. NLR (3.77±0.22) and SII (441.32±29.68) in the recurrent fracture group were higher than NLR (3.27±0.22) and SII (426.87±30.57) in the non-recurrent fracture group, and the differences were statistically significant (all P<0.05) , multivariate Logistic regression analysis showed lumbar spine bone density ( OR=8.56×10 4, 95% CI: 3.884-2.992×10 10, P=0.045) , NLR level ( OR=1.243×10 -8, 95% CI: 2.911×10 -13-1.072×10 -5, P=0.001) and SII level ( OR=0.938, 95% CI: 0.885-0.976, P=0.008) were all influencing factors affecting the postoperative treatment effect of postmenopausal OVCF, and ROC results showed that both NLR (AUC=0.86, 95% CI: 0.77-0.94, P<0.001) and SII (AUC=0.76, 95% CI: 0.67-0.85, P<0.001) had good prognostic value for postmenopausal OVCF. Conclusion:NLR and SII are risk factors for OVCF in postmenopausal osteoporosis patients, and have good short-term prognostic value.

Proto-Oncogene Proteins c-akt/metabolism* ; Butyrates ; Ligands ; Glucose ; Receptors, G-Protein-Coupled/metabolism* ; Glycogen Synthase Kinases/metabolism* ; Glycogen Synthase Kinase 3 beta ; Phosphorylation

Cerebral hemorrhage has a high incidence and numerous complications.Pulmonary in-fection is one of the serious complications of cerebral hemorrhage.Domestic and foreign researchers have developed pulmonary infection prediction models for patients with cerebral hemorrhage,which can provide references for clinical medical staff to identify high-risk groups in the early stage and formulate intervention strategies as soon as possible.This article summarized the risk factors of pulmonary infec-tion,the overview of risk prediction models,the current research status of pulmonary infection predic-tion models,and the significance of prediction,aiming to provide references for the evaluation and pre-vention of pulmonary infection in patients with cerebral hemorrhage.

Objective: To create a model for early prediction of essential hypertension (EH) based on the TreeNet algorithm, so as to provide a tool for early monitoring of EH. Methods: The health examination data were collected from individuals receiving health examinations in Hangzhou Haiqin Health Examination Center or Shanghai Yibao Health Management Co., Ltd from 2014 to 2016, and a predictive model for EH was created based on the TreeNet algorithm. The effectiveness of the model for early prediction of EH was evaluated using root mean square error (RMSE), mean absolute deviation (MAD), coefficient of determination (R2) and receiver operating characteristic (ROC) curve. Results: A total of 12 variables were included in the model, and the highest contributing variable was body mass index (BMI), followed by BMI difference, two-year BMI difference, two-year triglyceride (TG) difference, two-year total cholesterol (TC) difference, high-density lipoprotein cholesterol (HDL-C) in 2014, TG in 2014, low-density lipoprotein cholesterol (LDL-C) in 2014, body weight in 2015, fasting blood glucose in 2015, TG in 2015, urea nitrogen difference and platelet in 2015. The highest predictive accuracy was 100.00%, and the lowest was 56.89%. The risk of EH significantly increased among individuals with BMI in 2015 of >25 kg/m2, two-year BMI difference of >0.5 kg/m2, two-year TG difference ranging from 1.3 to 3.3 mmol/L, TC in 2015 of 2.0 to 2.4 mmol/L and HDL-C in 2014 of <0.52 mmol/L. The model presented RMSE of 0.082, MAD of 0.064, R2 of 0.811, area under the ROC curve of 0.788 (95%CI: 0.741-0.815), sensitivity of 69.05% and specificity of 66.21% for prediction of EH Conclusion The TreeNet algorithm-based model is effective for early monitoring of high-risk individuals for EH.