Major depressive disorder (MDD) imposes a heavy global disease burden. However, current etiology, diagnosis and treatment remain unsatisfactory and no previous study has resolved this problem. Building on the strengths and limitations of previous cohort studies of MDD, the prospective cohort study of depression (PROUD) is a 3-year large-scale cohort study designed to collect multidimensional data with a flexible follow-up schedule and strategy. The goal is to establish a nationally representative, high-quality, standardized depression cohort to support precise diagnosis and treatment of MDD and address the gap in current research.
PROUD is a patient-based, nationally representative multicenter prospective cohort study with baseline and 3-year follow-up assessments. It will be carried out from January 2022 to December 2026 in 52 qualified tertiary hospitals in China. A total of 14,000 patients diagnosed with MDD, according to the DSM-5 criteria, and aged ≥ 16 years, will be recruited to PROUD. Participants aged 18-65 years who have not received any treatment during a depressive episode will be included in the precision medicine cohort (PMC) of PROUD (n=4,000). Patients who meet the general eligibility criteria but not the PMC criteria will be included in the naturalistic observation cohort (NOC) of PROUD (n=10,000). A multiple follow-up strategy, including scheduled, remote, telephone, external visits and patient self-reports, will be implemented to collect comprehensive sociodemographic, clinical information, biospecimens, neuroimaging, cognitive function and electrophysiology data and digital phenotypes according to strict standard operating procedures implemented across centers. Trial registration: ChiCTR2200059053, registered on 23 April 2022, http://www.chictr.org.cn/showproj.aspx?proj=165790.
PROUD is a prospective cohort study of MDD patients in China. It will provide a comprehensive database facilitating further analyses and aiding the development of homeostatic and precision medicine in China.
This study aims to develop an insulin dosage adjustment model using machine learning of high quality electronic health records (EHRs) notes and then to form an artificial intelligence-based insulin clinical decision support workflow (iNCDSS) implemented in the HIS system to give a real-time recommendation of insulin dosage titration. The efficacy and safety in clinical practice is evaluated in this proof-of-concept study.
We extracted patient-specific and time-varying features from the original EHRs data and performed machine learning analysis through 5-fold cross validation. In the patient-blind, single-arm interventional study, insulin dosage was titrated according to iNCDSS in type 2 diabetic inpatients for up to 7 d or until hospital discharge. The primary end point of the trial was the difference in glycemic control as measured by mean daily blood glucose concentration during the intervention period.
A total of 3275 type 2 diabetic patients with 38,406 insulin counts were included for the model analysis. The XGBoost model presented the best performance with root mean square error (RMSE) of 1.06 unit and mean absolute relative difference (MARD) of 6.0% in the training dataset, and RMSE of 1.30 unit and MARD of 6.9% in the testing dataset. Twenty-three patients with T2DM (male 14, 60.9%; age 58.8 ± 10.7 years; duration of diabetes 11.8 ± 8.8 years, HbA1c 9.1 ± 1.1%) were enrolled in the proof of concept trial. The duration of iNCDSS intervention was 7.0 ± 0.1 d. The insulin dose recommended by iNCDSS was accepted by physicians in 97.8%. The mean daily capillary blood glucose was markedly improved during the intervention period, with a reduction of mean daily capillary BG from 11.3(8.0, 13.9) mmol/L in the first 24 h to 7.9(6.5,8.9) mmol/L in the last 24 h of the trial (P < 0.001). In addition, the time range below 3.9 mmol/L was decreased from 1.1% to 0.5%.
The clinical decision support system of insulin dosage titration developed using a machine learning algorithm based on the EHRs data was effective and safe in glycemic control in in type 2 diabetic inpatients.
ClinicalTrials.gov Identifier: NCT04053959.
Chordoma is a rare bone tumor often present in the skull base and spine. In addition, it is not sensitive to radiotherapy that surgical resection is of great significance for the treatment of chordoma. Residual tumors that cannot be surgically removed usually lead to tumor recurrence. Studies have shown that chordoma will be accompanied by multiple gene mutations, such as PDGFR, EGFR, HER2, VEGFR, and mTOR, and interact with the host immune system to promote tumor progression. Targeted therapy and immunotherapy can improve the prognosis of chordoma patients to some extent. This review focuses on the clinical trials related to targeted therapy, immunotherapy, and chemotherapy of chordoma.
Retinal homeostasis is maintained through a network of the nervous, circulatory, endocrine and immune systems. The integrity of the blood-retinal barrier, immune-inflammatory responses, and metabolic changes all significantly affect the maintenance of normal visual function. Retinal degenerative diseases, which include age-related macular degeneration, retinitis pigmentosa, diabetic retinopathy, and other disorders, are a group of heterogeneous and multi-etiological diseases resulting in an irreversible visual impairment. Whether these disorders are inherited, acquired, or from systemic origins, the gradual loss of the retinal pigment epithelium (RPE) and/or retinal neurons is a common feat. This process often begins with compromised retinal integrity, followed by a disruption in the equilibrium of inflammation, immune response, metabolism, and other aspects, resulting in retinal dyshomeostasis that affects not only disease progression but also the effect of therapeutic intervention. Therefore, a comprehensive understanding of the retinal homeostasis and dyshomeostasis will assist the development of treatment strategies for retinal degenerative diseases and open new avenues for clinical translation.
The HERG ion channel belongs to the voltage-gated potassium (Kv) channel family and is involved in potassium efflux during cellular repolarization. Mutations in HERG have been linked to long QT syndrome, which is associated with elevated secretion of glucagon-like peptide-1 (GLP-1). However, the precise contribution of HERG to GLP-1 secretion remains unclear. In this study, we demonstrate the expression of HERG in GLP-1-producing L-cells within the intestinal epithelium of rodents. Using a mouse L-cell model (GLUTag cell line), we observed that downregulation of HERG led to a significant prolongation of action potential duration, an increase in intracellular calcium concentration, and a stimulation of GLP-1 secretion following exposure to nutrients. These findings provide evidence that HERG plays a direct role in regulating GLP-1 secretion in the intestine and may hold promise as a potential target for the treatment of diabetes.
Over the past 15 years, single-cell RNA sequencing (scRNA-seq) technology, in combination with other omics, has revealed the mechanisms of human development, tumors, and complex diseases at the genome, transcriptome, and proteome levels. However, this approach fails to directly reflect relevant spatial information, such as cell location and interactions. This limitation has been addressed with the advancement of the combination of high-resolution scRNA-seq and spatial transcriptomics (ST), which enables the identification of cell composition, intercellular and intermolecular interaction, and unravels the mechanisms of disease phenotypes. This review explores two types of ST - imaging-based ST (iST) and sequencing-based ST (sST) - and demonstrates how ST analysis can follow disease pathogenesis in a spatiotemporal manner, searching for disease-specific biomarkers. ST technology is an effective tool for resolving major biomedical and clinical problems, including tumor research, brain science, embryonic development, organ atlas construction and other pathological analysis. Looking towards the future, despite its limitations, ST has the potential to address these problems in conjunction with “dynamics, multi-omics, and resolution”. Ultimately, the development of ST technology, improvement of algorithms, utilization of deep learning, and refinement of the analysis process and interpretation will determine the key to transforming ST from bench to bedside.
T cell receptor (TCR) usually determines the specificity and unique function of T cells. Recently, the unconventional T cells with a unique TCR have attracted great attentions because of their clinical importance. TCR Vα7.2+ cells, that consist of the CD161+ mucosal associated invariant T (MAIT) cells and CD161− non-MAIT T cells, have been reported to play crucial roles in immune defenses. However, their characterizations in human blood are still obscure. This study aims to investigate the signatures and functions of circulating TCR Vα7.2+CD161+ MAIT and TCR Vα7.2+CD161− cells under steady state.
The TCR Vα7.2+CD161+ and TCR Vα7.2+CD161− cells were separately sorted from healthy donor peripheral blood mononuclear cells (PBMCs) and send for single cell RNA sequencing (scRNA-seq). Flow cytometry analysis was used to verify the findings obtained from scRNA-seq analysis.
Our findings demonstrated that there are more TCR Vα7.2+CD161+ cells than TCR Vα7.2+CD161− cells in healthy donor PBMCs and revealed the differences between them. Under steady state, 4 TCR Vα7.2+CD161+ MAIT clusters existed in peripheral blood. Pseudotime analysis further implied the development trajectory of these MAIT cells, which was ordered from CCR7 + resting cluster to LGALS3 + transitional cluster, followed by KLRG1 + cluster and ending with CX3CR1 + terminally differentiated cytotoxic cluster. In addition, our results revealed that TCR Vα7.2+CD161− cells consist of different kind of conventional T cells. These TCR Vα7.2+CD161− non-MAIT cells showed a higher level of Granzyme B expression and upregulated genes associated with cytotoxicity, which implicated their roles in immune defense.
Our findings advanced the understandings of the evolution of circulating MAIT cells. We also preliminarily defined the TCR Vα7.2+CD161− PBMCs as a combination of versatile CD4+ and CD8+ populations with cytotoxicity.
Cisplatin, an anticancer drug, has limited its clinical application due to its severe nephrotoxicity, such as acute kidney injury (AKI). Damaged or dysfunctional mitochondria caused by cisplatin are toxic to the cell by producing reactive oxygen species and releasing cell death factors. Mitophagy is the mechanism of selective degradation of these damaged mitochondria via autophagy, that is critical to cellular homeostasis and viability. In this study, the protective functions of inorganic nitrate against cisplatin-induced nephrotoxicity are assessed. Our results in vitro show that nitrate significantly reduced the apoptosis of HK2 or NRK52E cells induced by cisplatin treatment. Furthermore, dietary nitrate notably alleviates the tubular and glomerular damages as well as the loss of renal function in cisplatin-induced AKI mice models. These protective effects are closely related to downregulation of cell apoptosis and reduction of reactive oxygen species (ROS) generation. Mechanistically, inorganic nitrate treatment promotes the activation of mitophagy mediated by the PINK1-PRKN/PARK2 pathway, which plays an important role in the maintenance of mitochondrial quality, helping renal tubular cells to survive and recover from cisplatin stress. These novel findings suggest that inorganic nitrate supplementation deserve further exploration as a potential treatment in patients with cisplatin-induced renal injury.
This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1007/s44194-022-00011-0.