Zhuoling Li

Aim: Youth is a time of a significant rise in depressive symptoms, particularly impacted by anxiety in females. However, the identification of the transition from anxiety to depression in young women remains ambiguous. This study collects data on brain structure and hormone levels in young women, intending to investigate the neurophysiological differences among women with anxiety disorders and comorbid anxiety and depression (CAD). Methods: 53 young women were divided into three groups, namely an anxiety group, a CAD group, and a control group, aiming to explore the differences in brain structure and ovarian hormone levels. Results: The CAD group exhibited significantly reduced gray matter volume (GMV) in the right superior frontal gyrus (SFG; 0.38 ± 0.05) and right middle occipital gyrus (MOG; 0.37 ± 0.04) compared to the anxiety (SFG: 0.41 ± 0.04; MOG: 0.41 ± 0.04) and control groups (SFG: 0.45 ± 0.04; MOG: 0.44 ± 0.03; all p < 0.001). Cortical thickness in the right SFG was also significantly lower in the CAD group (2.81 ± 0.24) than in the anxiety (3.08 ± 0.21) and control groups (3.11 ± 0.19; p < 0.001). Progesterone was negatively correlated with GMV in the right MOG ( r = −0.48, p = 0.042) and SFG ( r = −0.53, p = 0.020) only in the CAD group. Further, no significant associations were observed between estradiol levels and brain structure, nor between anxiety/depression scores and hormone or brain data (all p > 0.070). Conclusions: The change of brain structure in the SFG and MOG may be one of the mechanisms underlying the progression of symptoms from anxiety to CAD, which may also be related to the increase in progesterone, indicating the exacerbation of emotional disorders in young women.

This study was implemented for the evaluation on the circulating endothelial cells’ (CECs) clinical significance in the locally advanced nasopharyngeal carcinoma treatment with endostatin‐combined chemoradiotherapy. This study enrolled 47 patients with locally advanced nasopharyngeal carcinoma who were hospitalized from May 9, 2012 to March 10, 2013. These patients were split up into the observation group (25 patients) and control group (22 patients). Patients in the observation group received the endostatin combined with induction chemotherapy and subsequently with concurrent chemoradiotherapy with endostatin. Patients in the control group were treated with inductive chemotherapy followed by concurrent chemoradiotherapy. CECs in peripheral blood were conducted separately before or after inductive chemotherapy and additionally in the end of concurrent chemoradiotherapy. The CEC values of the observation group showed significant statistical differences (p < 0.05) before or after different therapies, whereas those data in the control group were not statistically different. And, the mostly importantly, the CEC values in the observation group and control group turned out a statistical difference. The combination of endostatin and chemoradiotherapy significantly reduced parameters of peripheral blood CECs in these patients. According to the CEC parameters’ variety that we observed in the combined therapies, this study demonstrated that the CECs might be a clinical clue to evaluate this antiangiogenic chemoradiotherapy. And the clinical value of CECs will be further determined along with increasing comparative studies and clinical long‐term efficacy observation.

Lung metastasis is an important cause for the low 5-year survival rate of colorectal cancer patients. Understanding the metabolic profile of lung metastasis of colorectal cancer is important for developing molecular diagnostic and therapeutic approaches. We carried out the metabonomic profiling of lung tissue samples on a mouse lung metastasis model of colorectal cancer using 1H-nuclear magnetic resonance (1H-NMR). The lung tissues of mice were collected at different intervals after marine colon cancer cell line CT-26 was intravenously injected into BALB/c mice. The distinguishing metabolites of lung tissue were investigated using 1H-NMR-based metabonomic assay, which is a highly sensitive and non-destructive method for biomarker identification. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were applied to analyze 1H-NMR profiling data to seek potential biomarkers. All of the 3 analyses achieved excellent separations between the normal and metastasis groups. A total of 42 metabolites were identified, ~12 of which were closely correlated with the process of metastasis from colon to lung. These altered metabolites indicated the disturbance of metabolism in metastatic tumors including glycolysis, TCA cycle, glutaminolysis, choline metabolism and serine biosynthesis. Our findings firstly identified the distinguishing metabolites in mouse colorectal cancer lung metastasis models, and indicated that the metabolite disturbance may be associated with the progression of lung metastasis from colon cancer. The altered metabolites may be potential biomarkers that provide a promising molecular approach for clinical diagnosis and mechanistic study of colorectal cancer with lung metastasis.