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Background: Although several pharmacological treatment options for depression are currently available, a large proportion of patients still do not achieve a complete remission or respond adequately to the initial antidepressant prescribed for reasons that remain relatively unknown. This study explored the application of serum biomarkers to the predict the efficacy of escitalopram for treating depression, to guide clinical drug selection., Method: In this study, 306 patients suffering from depression were treated with escitalopram (10 mg) for 6 weeks. After 6 weeks of treatment, the patients were divided into an escitalopram-sensitive group (ES, n = 172) and an escitalopram-insensitive group (EIS, n = 134) according their HAMD-24 scores after 6 weeks of treatment. Serum samples from all participants were collected on the first day, and 10 different serum biomarkers were analysed. Data from 100 patients in the ES group and 100 patients in the EIS group were then used to build a logistic regression model, and a receiver operating characteristic (ROC) curve was drawn. To validate the accuracy of our model, another 72 patients in the ES group and 34 patients in the EIS group were studied., Results: Of the 10 selected serum biomarkers, 4 were screened to build the regression model. BDNF, FGF-2, TNF-α and 5-HT. The regression equation was Z = 1/[1 + e -(-5.065+0.145 (BDNF)+0.029 (FGF-2)-0.368 (TNF-α)+0.813 (5-HT)) ], and the 4 biomarkers-combined detection achieved an AUC (area under the ROC curve) of 0.929 and a predictive accuracy of 88.70%., Limitation: Decision support tools based on our combined biomarker prediction models hold comparatively great promises; however, they need to be validated on a much larger scales than current studies provide., Conclusion: The logistic regression model and ROC curves based of the serum biomarkers used in this study provide a more reliable means to predict the efficacy of escitalopram in patients with depression, and provide clinical evidence for drug selection., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Quantitative molecular detection based on surface-enhanced Raman spectroscopy (SERS) is still a great challenge because of the highly nonuniform distribution of the SERS hot spots and the nondeterministic spatial and spectral overlap of the analyte with the hot spot. Here, we report a nanoparticle-on-mirror plasmonic sensor excited by surface plasmon polaritons for quantitative SERS detection of alpha fetoprotein in serum with ultrahigh sensitivity. The uniform gaps between the nanoparticles and gold film and the alignment of the gap modes relative to the excitation electric field endow this substrate with a uniform and strong SERS enhancement. The limit of detection reaches 1.45 fM, 697 times higher than that under normal excitation and 7800 times higher than a commercial enzyme-linked immunosorbent assay kit. This approach offers a potential solution to overcome the bottleneck in the field of SERS-based biosensing.

CORRIGENDUM Serum miR-128 Serves as a Potential Diagnostic Biomarker for Alzheimer's Disease [Corrigendum] Zhang M, Han W, Xu Y, Li D, Xue Q. Neuropsychiatr Dis Treat. Submit your manuscript here: https://www.dovepress.com/neuropsychiatric-disease-and-treatment-journal Neuropsychiatric Disease and Treatment Dovepress open access to scientific and medical research Open Access Full T ext Article submit your manuscript | www.dovepress.com Neuropsychiatric Disease and Treatment 2021:17 513 513 http://doi.org/10.2147/NDT .S306151 DovePress © 2021 Zhang et al. Neuropsychiatric Disease and Treatment Dovepress Publish your work in this journal Neuropsychiatric Disease and Treatment is an international, peer- reviewed journal of clinical therapeutics and pharmacology focusing on concise rapid reporting of clinical or pre-clinical studies on a range of neuropsychiatric and neurological disorders. [Extracted from the article]

The aim of the present study was to investigate the expression levels of microRNA(miR)-4722-5p and miR-615-3p in Alzheimer's disease (AD) and their diagnostic value. Blood samples were collected from 33 patients with AD and 33 healthy controls, and an β-amyloid (Aβ)25-35-induced PC12 cell model was also established. The relative mRNA expression levels of miR-4722-5p and miR-615-3p were detected using reverse transcription-quantitative PCR. The correlations between the mRNA expression levels of the two miRNAs and the mini-mental state examination (MMSE) scores were analyzed, and the receiver operating characteristic curve was used to assess the diagnostic value of miR-4722-5p and miR-615-3p in AD. Functional enrichment analysis of the miRNA target genes was performed using The Database for Annotation, Visualization and Integrated Discovery database and the R language analysis package. The mRNA expression levels of miR-4722-5p and miR-615-3p were increased in patients with AD and the Aβ25-35-induced PC12 cell model. The mRNA expression levels of miR-4722-5p and miR-615-3p were negatively correlated with MMSE scores, and the combination of the two miRNAs for AD had an improved diagnostic value than that of each miRNA alone. The results of Gene Ontology (GO) enrichment analysis showed that the target genes of miR-4722-5p were found in the cytoplasm and cytosol, and were mainly involved in protein folding and cell division. The molecular functions included protein binding and GTPase activator activity. The results of Kyoto Encyclopedia of Genes and Genomes analysis showed that miR-4722-5p was associated with the regulation of dopaminergic synapses and mTOR signaling pathways. GO enrichment analysis also revealed that the target genes of miR-615-3p were located in the nucleus and cytoplasm, were involved in the regulation of transcription and protein phosphorylation, and were associated with protein binding, metal ion binding and transcription factor activity. The target genes of miR-615-3p played important roles in the regulation of the Ras and FoxO signaling pathways. In conclusion, miR-4722-5p and miR-615-3p may be potential biomarkers in the early diagnosis of AD. [ABSTRACT FROM AUTHOR]