Exacerbating effects of circadian rhythm disruption on the systemic lupus erythematosus.

OBJECTIVE: Circadian rhythm disruption (CRD) has been associated with inflammation and immune disorders, but its role in SLE progression is unclear. We aimed to investigate the impact of circadian rhythms on immune function and inflammation and their contribution to SLE progression to lupus nephritis (LN). METHODS: This study retrospectively analysed the clinical characteristics and transcriptional profiles of 373 samples using bioinformatics and machine-learning methods. A flare risk score (FRS) was established to predict overall disease progression for patients with lupus. Mendelian randomisation was used to analyse the causal relationship between CRD and SLE progression. RESULTS: Abnormalities in the circadian pathway were detected in patients with SLE, and lower enrichment levels suggested a disease state (normalised enrichment score=0.6714, p=0.0062). The disruption of circadian rhythms was found to be closely linked to lupus flares, with the FRS showing a strong ability to predict disease progression (area under the curve (AUC) of 5-year prediction: 0.76). The accuracy of disease prediction was improved by using a prognostic nomogram based on FRS (AUC=0.77). Additionally, Mendelian randomisation analysis revealed an inverse causal relationship between CRD and SLE (OR 0.6284 (95% CI 0.3630 to 1.0881), p=0.0485) and a positive causal relationship with glomerular disorders (OR 0.0337 (95% CI 1.634e-3 to 6.934e-1), p=0.0280). CONCLUSION: Our study reveals that genetic characteristics arising from CRD can serve as biomarkers for predicting the exacerbation of SLE. This highlights the crucial impact of CRD on the progression of lupus.

Depressive patient-derived GABA interneurons reveal abnormal neural activity associated with HTR2C.

Major depressive disorder with suicide behavior (sMDD) is a server mood disorder, bringing tremendous burden to family and society. Although reduced gamma amino butyric acid (GABA) level has been observed in postmortem tissues of sMDD patients, the molecular mechanism by which GABA levels are altered remains elusive. In this study, we generated induced pluripotent stem cells (iPSC) from five sMDD patients and differentiated the iPSCs to GABAergic interneurons (GINs) and ventral forebrain organoids. sMDD GINs exhibited altered neuronal morphology and increased neural firing, as well as weakened calcium signaling propagation, compared with controls. Transcriptomic sequencing revealed that a decreased expression of serotoninergic receptor 2C (5-HT2C) may cause the defected neuronal activity in sMDD. Furthermore, targeting 5-HT2C receptor, using a small molecule agonist or genetic approach, restored neuronal activity deficits in sMDD GINs. Our findings provide a human cellular model for studying the molecular mechanisms and drug discoveries for sMDD.

Facile and rapid determination of oxalic acid by fading spectrophotometry based on Fe(III)-sulfosalicylate as colorimetric chemosensor.

Spectrophotometry is an economic and rapid method for detecting oxalic acid (OA), while the reported methods have some drawbacks, such as narrow linear range, long response time, delicate operation and required expensive reagents. Herein, we found that the as-synthesized Fe(III)-sulfosalicylate (FeSSA) could be used as an efficient colorimetric chemosensor to detect OA, and the established FeSSA-based fading spectrophotometry showed prominent advantages over the existing ones in detecting OA. The as-established method has wider linear range of 0.80-160 mg/L with regression coefficient ≥ 0.999, while the widest linear range is just 2.7-54 mg/L among the reported ones. Moreover, the method has low limit of detection (0.74 mg/L), extremely fast response (several seconds), satisfactory selectivity, high accuracy and precision. Most importantly, its reliability was further verified by employing it to determine OA concentration during the degradation process of organic pollutants. The measured OA concentration at any time interval was perfectly consistent with those determined by the well-recognized high performance liquid chromatography (HPLC). These confirmed that the FeSSA-based fading spectrophotometry is an efficient, simple, fast, accurate and economic method to determine OA in a wide concentration range.

Deep Learning-Based Model Significantly Improves Diagnostic Performance for Assessing Renal Histopathology in Lupus Glomerulonephritis.

Background: Assessment of glomerular lesions and structures plays an essential role in understanding the pathological diagnosis of glomerulonephritis and prognostic evaluation of many kidney diseases. Renal pathophysiological assessment requires novel high-throughput tools to conduct quantitative, unbiased, and reproducible analyses representing a central readout. Deep learning may be an effective tool for glomerulonephritis pathological analysis. Methods: We developed a murine renal pathological system (MRPS) model to objectify the pathological evaluation via the deep learning method on whole-slide image (WSI) segmentation and feature extraction. A convolutional neural network model was used for accurate segmentation of glomeruli and glomerular cells of periodic acid-Schiff-stained kidney tissue from healthy and lupus nephritis mice. To achieve a quantitative evaluation, we subsequently filtered five independent predictors as image biomarkers from all features and developed a formula for the scoring model. Results: Perimeter, shape factor, minimum internal diameter, minimum caliper diameter, and number of objects were identified as independent predictors and were included in the establishment of the MRPS. The MRPS showed a positive correlation with renal score (r = 0.480, p < 0.001) and obtained great diagnostic performance in discriminating different score bands (Obuchowski index, 0.842 [95% confidence interval: 0.759, 0.925]), with an area under the curve of 0.78-0.98, sensitivity of 58-93%, specificity of 72-100%, and accuracy of 74-94%. Conclusion: Our MRPS for quantitative assessment of renal WSIs from MRL/lpr lupus nephritis mice enables accurate histopathological analyses with high reproducibility, which may serve as a useful tool for glomerulonephritis diagnosis and prognosis evaluation.

Multi-omics analysis of tumor mutation burden combined with immune infiltrates in bladder urothelial carcinoma.

To explore the prognosis of tumor mutation burden (TMB) and underlying relationships with tumor-infiltrating immune cells in bladder cancer (BLCA). Transcriptome profiles and somatic mutation data from The Cancer Genome Atlas database by the GDC tool. A total of 437 samples were included, consisted of 412 BLCA patients and matched 25 normal samples. Specific mutation information was summarized and illustrated in waterfall plot. Higher TMB levels revealed improved overall survival (OS) and lower tumor recurrence. We found 68 differentially expressed genes in two TMB groups and identified eight independent hub TMB-related signature. Pathway analysis suggested that differential TMB-related signature correlated with multiple cancer-related crosstalk, including cell cycle, DNA replication, cellular senescence, and p53 signaling pathway. Besides, the tumor mutation burden related signature (TMBRS) model based on eight signature possessed well predictive value with area under curve (AUC) = 0.753, and patients with higher TMBRS scores showed worse OS outcomes (p < .001). Moreover, we exhibited the inferred immune cell fractions in box plot and differential abundance of immune cells were shown in the heatmap. The Wilcoxon rank-sum test suggested that CD8+ T cell (p = .001) and memory activated CD4+ T cell (p = .004) showed higher infiltrating levels in high-TMB group, while the density of resting mast cells showed lower infiltrating level in high-TMB group (p = .016). Finally, it is significant to note that CD8+ T cell and memory activated CD4+ T cell subsets not only revealed higher infiltrating abundance in high-TMB group but correlated with prolonged OS and lower risk of tumor recurrence, respectively.

The telomerase inhibitor AZT enhances differentiation and prevents overgrowth of human pluripotent stem cell-derived neural progenitors.

Human pluripotent stem cell (hPSC)-based cell-replacement therapy has emerged as a promising approach for addressing numerous neurological diseases. However, hPSC transplantation has the potential to cause human cell overgrowth and cancer, which represents a major obstacle to implementing hPSC-based therapies. Inhibition of the overgrowth of transplanted cells could help reduce the risk for hPSC transplantation-induced tumorigenesis. In this study, we report that the telomerase inhibitor azidothymidine (3'-azido-3'-deoxythymidine; AZT) enhances the differentiation of cortical neurons and significantly suppresses the proliferation of hPSC-derived cortical progenitors. Using human embryonic stem cells and induced pluripotent stem cells in culture, we found that AZT effectively reduces the number of dividing progenitors without inducing cell death. Furthermore, AZT promoted differentiation of cortical progenitors and maturation of cortical neurons. Of note, AZT-pretreated, hPSC-derived neural progenitors exhibited decreased proliferation and increased differentiation into cortical neurons when transplanted into the mouse brain. In summary, our findings indicate that AZT prevents the overgrowth of hPSC-derived neural precursors and enhances the differentiation of cortical neurons in both cell cultures and hPSC-transplanted mouse brain. We propose that our work could inform clinical applications of hPSC-based cell therapy.

Detection of viral infection and gene expression in clinical tissue specimens using branched DNA (bDNA) in situ hybridization.

In situ hybridization (ISH) methods for detection of nucleic acid sequences have proved especially powerful for revealing genetic markers and gene expression in a morphological context. Although target and signal amplification technologies have enabled researchers to detect relatively low-abundance molecules in cell extracts, the sensitive detection of nucleic acid sequences in tissue specimens has proved more challenging. We recently reported the development of a branched DNA (bDNA) ISH method for detection of DNA and mRNA in whole cells. Based on bDNA signal amplification technology, bDNA ISH is highly sensitive and can detect one or two copies of DNA per cell. In this study we evaluated bDNA ISH for detection of nucleic acid sequences in tissue specimens. Using normal and human papillomavirus (HPV)-infected cervical biopsy specimens, we explored the cell type-specific distribution of HPV DNA and mRNA by bDNA ISH. We found that bDNA ISH allowed rapid, sensitive detection of nucleic acids with high specificity while preserving tissue morphology. As an adjunct to conventional histopathology, bDNA ISH may improve diagnostic accuracy and prognosis for viral and neoplastic diseases.