Luteolin and triptolide: Potential therapeutic compounds for post-stroke depression via protein STAT.

Post stroke depression (PSD) is a common neuropsychiatric complication following stroke closely associated with the immune system. The development of medications for PSD remains to be a considerable challenge due to the unclear mechanism of PSD. Multiple researches agree that the functions of gene ontology (GO) are efficient for the investigation of disease mechanisms, and DeepPurpose (DP) is extremely valuable for the mining of new drugs. However, GO terms and DP have not yet been applied to explore the pathogenesis and drug treatment of PSD. This study aimed to interpret the mechanism of PSD and discover important drug candidates targeting risk proteins, based on immune-related risk GO functions and informatics algorithms. According to the risk genes of PSD, we identified 335 immune-related risk GO functions and 37 compounds. Based on the construction of the GO function network, we found that STAT protein may be a pivot protein in underlying the mechanism of PSD. Additionally, we also established networks of Protein-Protein Interaction as well as Gene-GO function to facilitate the evaluation of key genes. Based on DP, a total of 37 candidate compounds targeting 7 key proteins were identified with a potential for the therapy of PSD. Furthermore, we noted that the mechanisms by which luteolin and triptolide acting on STAT-related GO function might involve three crucial pathways, including specifically hsa04010 (MAPK signaling pathway), hsa04151 (PI3K-Akt signaling pathway) and hsa04060 (Cytokine-cytokine receptor interaction). Thus, this study provided fresh and powerful information for the mechanism and therapeutic strategies of PSD.

Characterization of volatile metabolites in Pu-erh teas with different storage years by combining GC-E-Nose, GC-MS, and GC-IMS.

Storage time is one of the important factors affecting the aroma quality of Pu-erh tea. In this study, the dynamic changes of volatile profiles of Pu-erh teas stored for different years were investigated by combining gas chromatography electronic nose (GC-E-Nose), gas chromatography-mass spectrometry (GC-MS), and gas chromatography-ion mobility spectrometry (GC-IMS). GC-E-Nose combined with partial least squares-discriminant analysis (PLS-DA) realized the rapid discrimination of Pu-erh tea with different storage time (R2Y = 0.992, Q2 = 0.968). There were 43 and 91 volatile compounds identified by GC-MS and GC-IMS, respectively. A satisfactory discrimination (R2Y = 0.991, and Q2 = 0.966) was achieved by using PLS-DA based on the volatile fingerprints of GC-IMS. Moreover, according to the multivariate analysis of VIP > 1.2 and univariate analysis of p < 0.05, 9 volatile components such as linalool and (E)-2-hexenal were selected as key variables to distinguish Pu-erh teas with different storage years. The results provide theoretical support for the quality control of Pu-erh tea.

Lipid metabolic characteristics and marker compounds of ripened Pu-erh tea during pile fermentation revealed by LC-MS-based lipidomics.

Ripened Pu-erh tea (RPT) is a unique microbial fermented tea. Herein, we investigated the lipid composition of RPT and its metabolic changes during pile fermentation, by nontargeted lipidomics profiling and quantitative analysis using liquid chromatography-mass spectrometry (LC-MS). A total of 485 individual lipid species covering 26 subclasses were detected, and fatty acid ester of hydroxy fatty acid (FAHFA) was detected in tea for the first time. Among them, 362 species were significantly altered during fermentation. Chlorophylls decomposition, phospholipids degradation (especially phosphatidylserine, phosphatidylethanolamine, phosphatidylcholine), formation of free fatty acid (FFA) (especially FFA18:3, FFA18:2), and formation of FAHFA, were annotated as the key pathways. Particularly, FAHFAs were undetected in raw tea and gradually enriched to 227.0 ± 9.6 nmol/g after fermentation (p < 0.001), which could serve as marker compounds of RPT associated with microbial fermentation. This study will advance understanding the lipid metabolic fate in microbial fermentation and its role in RPT quality. Chemical compounds studied in this article: Linolenic acid (PubChem CID: 5280934); Linoleic acid (PubChem CID: 5280450); Oleic acid (PubChem CID: 445639); PS(22:0/18:2) (PubChem CID: 52925820); PS(20:0/18:3) (PubChem CID: 52925629); Pheophytin a (PubChem CID: 135398712); Pheophorbide a (PubChem CID: 253193).

A novel nomogram predicting cancer-specific survival in small cell lung cancer patients with brain metastasis.

Background: Brain metastasis (BM) is one of the most common metastatic sites in patients with small cell lung cancer (SCLC), and the prognosis remains very poor. This study aimed to establish a novel nomogram for predicting the cancer-specific survival (CSS) in SCLC patients with BM. Methods: SCLC patients with BM from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015 were retrospectively collected. Univariate and multivariate Cox regression analyses were performed to identify independent prognostic factors, which were further used to construct the prognostic nomogram. The discrimination and calibration of nomogram were evaluated by concordance index (C-index), receiver operating characteristic (ROC) curve, the area under ROC curve (AUC) and calibration plot. Decision curve analysis (DCA) was used to assess the clinical usefulness. Kaplan-Meier survival curve was applied to analyze the survival outcome. Results: A total of 2,462 patients were enrolled in this study, and randomly assigned into training cohort (n=1,723) and validation cohort (n=739). Age, N stage, surgery, radiation, chemotherapy, bone metastasis, liver metastasis and lung metastasis were identified as independent prognostic factors of CSS. The C-indexes of nomogram was 0.683 [95% confidence interval (CI): 0.667-0.699] in the training cohort, and 0.659 (95% CI: 0.634-0.684) in the validation cohort. The AUC values of 6-, 9- and 12-month CSS were 0.723, 0.742 and 0.737 respectively in the training cohort, while 0.715, 0.737 and 0.739 in the validation cohort. The ROC, calibration and DCA curves showed good discrimination, calibration and clinical applicability of this nomogram in predicting prognosis. Moreover, patients in high-risk group had a worse survival outcome than patients in medium-risk and low-risk groups. Conclusions: A novel nomogram was constructed and validated for predicting individual prognosis in SCLC patients with BM. This nomogram could help clinicians make effective treatment strategies for patients.

Rapid characterization of the volatile profiles in Pu-erh tea by gas phase electronic nose and microchamber/thermal extractor combined with TD-GC-MS.

Aroma plays an important role in the quality of Pu-erh tea. However, the quality evaluation of Pu-erh tea aroma is heavily relied on the experience of sensory evaluation, and the theoretical research is relatively scarce. In the present work, the volatile compounds in Pu-erh tea were characterized by using gas phase electronic nose (e-nose) and microchamber/thermal extractor (µ-CTE) combined with thermal desorption coupled to gas chromatography-mass spectrometry (TD-GC-MS). A satisfactory discrimination model (R2 Y = 0.95, Q2  = 0.807) was obtained by using orthogonal partial least squares discriminant analysis (OPLS-DA) based on the odor fingerprint of different brands of Pu-erh tea. In addition, based on the double criterion of multivariate analysis with VIP >1.0 and univariate analysis with p ≤ 0.001, 39 volatile components were identified to contribute greatly to the discrimination of five brands of Pu-erh tea. The results suggested that gas phase e-nose and µ-CTE combined with TD-GC/MS were simple, rapid techniques to characterize the volatile compounds in Pu-erh tea and were allowed to effectively distinguish different brands of Pu-erh tea, which would provide an important reference on the quality assessment of Pu-erh tea. PRACTICAL APPLICATION: This work demonstrates that the volatile compounds in Pu-erh tea are simply and rapidly characterized by using µ-CTE/TD-GC/MS and gas phase e-nose, allowing to effectively distinguish different brands of Pu-erh tea, which can provide an important reference for the quality assessment and authentication of Pu-erh tea.