Background and Purpose— There has been a nonstandard surgical procedure and extensive international controversy in minimally invasive surgery (MIS) for the management of spontaneous supratentorial intracerebral hemorrhage. This meta-analysis assessed the effectiveness of MIS as compared with other treatment options, including conservative medical treatment and conventional craniotomy, in patients with supratentorial intracerebral hemorrhage. Methods— PubMed, Embase, Cochrane Controlled Trials Register (CCTR), Web of Science, European Association for Grey Literature Exploitation (EAGLE), National Technical Information Service (NTIS), Current Controlled Trials, Clinical Trials, International Clinical Trials Registry, Internet Stroke Center, Chinese Biomedical Literature Database (CBM), Chinese National Knowledge Infrastructure (CNKI) (last searched December 2011) were searched. Randomized controlled trials on MIS in patients with computed tomography-confirmed supratentorial intracerebral hemorrhage were included. We excluded low-quality randomized controlled trials. The death or dependence at the end of follow-up was defined as the primary outcome, and the death at the end of follow-up was defined as the secondary outcome. Results— The 313 randomized controlled trials met the included criteria. We only analyzed 12 high-quality randomized controlled trials involving 1955 patients. The quality of the included trials was consistently high. OR of the primary outcome and secondary outcome of MIS both showed significant reductions (OR, 0.54, P <0.00001; OR, 0.53, P <0.00001). Conclusions— Patients with supratentorial intracerebral hemorrhage may benefit more from MIS than other treatment options. The most likely candidates to benefit from MIS are both sexes, age of 30 to 80 years with superficial hematoma, Glasgow Coma Scale score of ≥9, hematoma volume between 25 and 40mL, and within 72 hours after onset of symptoms. Our study could help select appropriate patients for MIS and guide clinicians to optimize treatment strategies in supratentorial intracerebral hemorrhage.

Mounting evidence suggests that gut microbiota can play an important role in pathophysiology of depression, but its specific molecular mechanisms are still unclear. This study was conducted to explore the associations between changes in neurotransmitters and short-chain fatty acids (SCFAs) and altered gut microbiota in depressed mice. Here, the chronic restraint stress (CRS) model of depression was built. The classical behavioral tests were conducted to assess the depressive-like behaviors of mice. The 16S rRNA gene sequence extracted from fecal samples was used to assess the gut microbial composition. Liquid and gas chromatography mass spectroscopy were used to identify neurotransmitters in hypothalamus and SCFAs in fecal samples, respectively. Finally, 29 differential bacteria taxa between depressed mice and control mice were identified, and the most differentially abundant bacteria taxa were genus Allobaculum and family Ruminococcaceae between the two groups. The acetic acid, propionic acid, pentanoic acid, norepinephrine, 5-HIAA and 5-HT were significantly decreased in depressed mice compared to control mice. Genus Allobaculum was found to be significantly positively correlated with acetic acid and 5-HT. Taken together, these results provided novel microbial and metabolic frameworks for understanding the role of microbiota-gut-brain axis in depression, and suggested new insights to pave the way for novel therapeutic methods.

BackgroundBrain derived neurotrophic factor (BDNF) is one of the most important regulatory proteins in the pathophysiology of major depressive disorder (MDD). Increasing numbers of studies have reported the relationship between serum/plasma BDNF and antidepressants (ADs). However, the potential effects of several classes of antidepressants on BDNF concentrations are not well known. Hence, our meta-analyses aims to review the effects of differential antidepressant drugs on peripheral BDNF levels in MDD and make some recommendations for future research.MethodsElectronic databases including PubMed, EMBASE, the Cochrane Library, Web of Science, and PsycINFO were searched from 1980 to June 2016. The change in BDNF levels were compared between baseline and post-antidepressants treatment by use of the standardized mean difference (SMD) with 95% confidence intervals (CIs). All statistical tests were two-sided.ResultsWe identified 20 eligible trials of antidepressants treatments for BDNF in MDD. The overall effect size for all drug classes showed that BDNF levels were elevated following a course of antidepressants use. For between-study heterogeneity by stratification analyses, we detect that length of treatment and blood samples are significant effect modifiers for BDNF levels during antidepressants treatment. While both SSRIs and SNRIs could increase the BDNF levels after a period of antidepressant medication treatment, sertraline was superior to other three drugs (venlafaxine, paroxetine or escitalopram) in the early increase of BDNF concentrations with SMD 0.53(95% CI = 0.13–0.93; P = 0.009).ConclusionsThere is some evidence that treatment of antidepressants appears to be effective in the increase of peripheral BDNF levels. More robust evidence indicates that different types of antidepressants appear to induce differential effects on the BDNF levels. Since sertraline makes a particular effect on BDNF concentration within a short amount of time, there is potential value in exploring its relationship with BDNF and its pharmacological mechanism concerning peripheral blood BDNF. Further confirmatory trials are required for both observations.

Bipolar disorder (BD) is a debilitating mental disorder that cannot be diagnosed by objective laboratory-based modalities. Our previous studies have independently used nuclear magnetic resonance (NMR)-based and gas chromatography-mass spectrometry (GC-MS)-based metabonomic methods to characterize the urinary metabolic profiles of BD subjects and healthy controls (HC). However, the combined application of NMR spectroscopy and GC-MS may identify a more comprehensive metabolite panel than any single metabonomic platform alone. Therefore, here we applied a dual platform (NMR spectroscopy and GC-MS) that generated a panel of five metabolite biomarkers for BD-four GC-MS-derived metabolites and one NMR-derived metabolite. This composite biomarker panel could effectively discriminate BD subjects from HC, achieving an area under receiver operating characteristic curve (AUC) values of 0.974 in a training set and 0.964 in a test set. Moreover, the diagnostic performance of this panel was significantly superior to the previous single platform-derived metabolite panels. Thus, the urinary biomarker panel identified here shows promise as an effective diagnostic tool for BD. These findings also demonstrate the complementary nature of NMR spectroscopy and GC-MS for metabonomic analysis, suggesting that the combination of NMR spectroscopy and GC-MS can identify a more comprehensive metabolite panel than applying each platform in isolation.

Emerging evidence has shown the age-related changes in gut microbiota, but few studies were conducted to explore the effects of age on the gut microbiota in patients with major depressive disorder (MDD). This study was performed to identify the age-specific differential gut microbiota in MDD patients. In total, 70 MDD patients and 71 healthy controls (HCs) were recruited and divided into two groups: young group (age 18-29 years) and middle-aged group (age 30-59 years). The 16S rRNA gene sequences were extracted from the collected fecal samples. Finally, we found that the relative abundances of Firmicutes and Bacteroidetes were significantly decreased and increased, respectively, in young MDD patients as compared with young HCs, and the relative abundances of Bacteroidetes and Actinobacteria were significantly decreased and increased, respectively, in middle-aged MDD patients as compared with middle-aged HCs. Meanwhile, six and 25 differentially abundant bacterial taxa responsible for the differences between MDD patients (young and middle-aged, respectively) and their respective HCs were identified. Our results demonstrated that there were age-specific differential changes on gut microbiota composition in patients with MDD. Our findings would provide a novel perspective to uncover the pathogenesis underlying MDD.

Available data indicate that patients with depression and anxiety disorders are likely to be at greater risk for suicide. Therefore, it is important to correctly diagnose patients with depression and anxiety disorders. However, there are still no empirical laboratory methods to objectively diagnose these patients. In this study, the multiple metabolomics platforms were used to profile the urine samples from 32 healthy controls and 32 patients with depression and anxiety disorders for identifying differential metabolites and potential biomarkers. Then, 16 healthy controls and 16 patients with depression and anxiety disorders were used to independently validate the diagnostic performance of the identified biomarkers. Finally, a panel consisting of four biomarkers—N-methylnicotinamide, aminomalonic acid, azelaic acid and hippuric acid—was identified. This panel was capable of distinguishing patients with depression and anxiety disorders from healthy controls with an area under the receiver operating characteristic curve of 0.977 in the training set and 0.934 in the testing set. Meanwhile, we found that these identified differential metabolites were mainly involved in three metabolic pathways and five molecular and cellular functions. Our results could lay the groundwork for future developing a urine-based diagnostic method for patients with depression and anxiety disorders.

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