The marine-derived compound TAG alleviates Parkinson's disease by restoring RUBCN-mediated lipid metabolism homeostasis.

Parkinson's disease (PD) is the second most common neurodegenerative disease, and its prevalence is increasing. Currently, no effective therapies for PD exist. Marine-derived natural compounds are considered important resources for the discovery of new drugs due to their distinctive structures and diverse activities. In this study, tetrahydroauroglaucin (TAG), a polyketide isolated from a marine sponge, was found to have notable neuroprotective effects on MPTP/MPP+-induced neurotoxicity. RNA sequencing analysis and metabolomics revealed that TAG significantly improved lipid metabolism disorder in PD models. Further investigation indicated that TAG markedly decreased the accumulation of lipid droplets (LDs), downregulated the expression of RUBCN, and promoted autophagic flux. Moreover, conditional knockdown of Rubcn notably attenuated PD-like symptoms and the accumulation of LDs, accompanied by blockade of the neuroprotective effect of TAG. Collectively, our results first indicated that TAG, a promising PD therapeutic candidate, could suppress the accumulation of LDs through the RUBCN-autophagy pathway, which highlighted a novel and effective strategy for PD treatment.

Asymmetric Dearomatization of Indoles through Cobalt-Catalyzed Enantioselective C-H Functionalization Enabled by Photocatalysis.

Photocatalysis holds a pivotal position in modern organic synthesis, capable of inducing novel reactivities under mild and environmentally friendly reaction conditions. However, the merger of photocatalysis and transition-metal-catalyzed asymmetric C-H activation as an efficient and sustainable method for the construction of chiral molecules remains elusive and challenging. Herein, we develop a cobalt-catalyzed enantioselective C-H activation reaction enabled by visible-light photoredox catalysis, providing a synergistic catalytic strategy for the asymmetric dearomatization of indoles with high levels of enantioselectivity (96% to >99% ee). Mechanistic studies indicate that the excited photocatalyst was quenched by divalent cobalt species in the presence of Salox ligand, leading to the formation of catalytically active chiral Co(III) complex. Moreover, stoichiometric reactions of cobaltacycle intermediate with indole suggest that the irradiation of visible light also play a critical role in the dearomatization step.

Discovering biomarkers in bladder cancer by metabolomics.

It has become increasingly clear that the development of cancer, a multifactorial disease, cannot be explained by a single molecule or gene mutation. As a new discipline, metabolomics focuses on the body's metabolite changes, and attempts to find differences to explain the development of cancer; it has proven to be effective and credible. Metabolic studies of bladder cancer (BCa) lag behind those of other tumors. This review systematically outlines the specific process of metabolomics and the use of metabolomics in BCa studies in recent years. We have reviewed the in vitro cell line, bladder tumor tissue and biofluid (urine, plasma and serum) studies used in metabolomics analyses of BCa. The advantages and drawbacks of the use of different samples were compared. Based on the available studies, we have further described the aberrant metabolic pathways of BCa and have suggested some metabolites that may be potential biomarkers for BCa detection.

Expression of CUL1 correlates with tumour-grade and recurrence in urothelial carcinoma.

BACKGROUND: Urothelial carcinoma (UC) is a major health problem in the general population. We aimed to evaluate the function of Cullin-1 (CUL1) and unravel its underlying molecular mechanism to develop novel treatment options equivalent to UC. METHODS: To evaluate the function of CUL1, a group of 132 pairs of UC patients were recruited for this study. UC tissues and their adjacent noncancerous tissues (NCTs) were collected between 2008 and 2009. We used immunohistochemistry to analyse the correlation between CUL1 expression and clinicopathologic variables and patient survival. RESULTS: CUL1 was dramatically overexpressed in high-grade UC tissues compared with low-grade UC tissues. CUL1 up-regulation in recurrence cases in comparison with the non-recurrence cases. CUL1 expression upregulated in human UC tissues versus NCTs. CUL1 protein expression associated with androgen receptor. CONCLUSIONS: Our results demonstrate that increased CUL1 expression is significantly correlated with poor prognosis of patients with UC. CUL1 might be an important marker and a therapeutic target for UC.

Predictive value of neutrophil-to-lymphocyte ratio in diagnosis of prostate cancer among men who underwent template-guided prostate biopsy: A STROBE-compliant study.

To evaluate the predictive value of neutrophil-to-lymphocyte ratio (NLR) in diagnosis of prostate cancer (PCa). Data of 662 patients who underwent prostate biopsy from January 2012 to June 2016 were retrospectively reviewed. The receiver operating characteristic-derived area under the curve analyses were performed to assess the predictive accuracy. Simultaneously, Youden's index was calculated to determine the optimal NLR cutoff. Furthermore, univariate and multivariate logistic regression analyses were performed to determine the association between NLR value and PCa detection. On account of an NLR value of 2.44 was shown with the maximal Youden's index on the receiver operating characteristic curve, the cutoff value of NLR was set at 2.44. Accordingly, patients were classified into high-NLR or low-NLR group. The patients in high-NLR group might have significant higher risk to be diagnosed with PCa (HR 1.640; P = 0.031), especially in the subgroup with prostate-specific antigen (PSA) ranged from 4 to 10 ng mL (hazard ratio [HR] 4.364; P = 0.003). The high-NLR was independent of age of diagnosis, PSA, prostate volume, abnormal digital rectal examination, and hypoechoic lesion on transrectal ultrasound for positive prostate biopsy. In the so-called gray area, combination of NLR value could raise 4.6% of the accuracy of the multivariate logistic model in PCa prediction, but not in advanced PCa prediction.The patients with high-NLR value may have significant higher risk to be diagnosed with PCa, especially among the patients with PSA ranged from 4 to 10 ng mL. In this subgroup, the adding of NLR value in the multivariate model can improve the accuracy of PCa prediction in a large degree. If validated, the NLR will become a promising, accessible, inexpensive biomarker for PCa prediction.