The dynamics of B-cell reconstitution post allogeneic hematopoietic stem cell transplantation: A real-world study.

BACKGROUND: The immune reconstitution after allogeneic hematopoietic stem cell transplantation (allo-HSCT) is crucial for preventing infections and relapse and enhancing graft-versus-tumor effects. B cells play an important role in humoral immunity and immune regulation, but their reconstitution after allo-HSCT has not been well studied. METHODS: In this study, we analyzed the dynamics of B cells in 252 patients who underwent allo-HSCT for 2 years and assessed the impact of factors on B-cell reconstitution and their correlations with survival outcomes, as well as the development stages of B cells in the bone marrow and the subsets in the peripheral blood. RESULTS: We found that the B-cell reconstitution in the bone marrow was consistent with the peripheral blood (p = 0.232). B-cell reconstitution was delayed by the male gender, age >50, older donor age, the occurrence of chronic and acute graft-versus-host disease, and the infections of fungi and cytomegalovirus. The survival analysis revealed that patients with lower B cells had higher risks of death and relapse. More importantly, we used propensity score matching to obtain the conclusion that post-1-year B-cell reconstitution is better in females. Meanwhile, using mediation analysis, we proposed the age-B cells-survival axis and found that B-cell reconstitution at month 12 posttransplant mediated the effect of age on patient survival (p = 0.013). We also found that younger patients showed more immature B cells in the bone marrow after transplantation (p = 0.037). CONCLUSION: Our findings provide valuable insights for optimizing the management of B-cell reconstitution and improving the efficacy and safety of allo-HSCT.

Multimodal evaluation of the effects of low-intensity ultrasound on cerebral blood flow after traumatic brain injury in mice.

Traumatic brain injury (TBI) is one of the leading causes of death and disability worldwide, and destruction of the cerebrovascular system is a major factor in the cascade of secondary injuries caused by TBI. Laser speckle imaging (LSCI)has high sensitivity in detecting cerebral blood flow. LSCI can visually show that transcranial focused ultrasound stimulation (tFUS) treatment stimulates angiogenesis and increases blood flow. To study the effect of tFUS on promoting angiogenesis in Controlled Cortical impact (CCI) model. tFUS was administered daily for 10 min and for 14 consecutive days after TBI. Cerebral blood flow was measured by LSCI at 1, 3, 7 and 14 days after trauma. Functional outcomes were assessed using LSCI and neurological severity score (NSS). After the last test, Nissl staining and vascular endothelial growth factor (VEGF) were used to assess neuropathology. TBI can cause the destruction of cerebrovascular system. Blood flow was significantly increased in TBI treated with tFUS. LSCI, behavioral and histological findings suggest that tFUS treatment can promote angiogenesis after TBI.

The gut microbiome modulates the transformation of microglial subtypes.

Clinical and animal studies have shown that gut microbiome disturbances can affect neural function and behaviors via the microbiota-gut-brain axis, and may be implicated in the pathogenesis of several brain diseases. However, exactly how the gut microbiome modulates nervous system activity remains obscure. Here, using a single-cell nucleus sequencing approach, we sought to characterize the cell type-specific transcriptomic changes in the prefrontal cortex and hippocampus derived from germ-free (GF), specific pathogen free, and colonized-GF mice. We found that the absence of gut microbiota resulted in cell-specific transcriptomic changes. Furthermore, microglia transcriptomes were preferentially influenced, which could be effectively reversed by microbial colonization. Significantly, the gut microbiome modulated the mutual transformation of microglial subpopulations in the two regions. Cross-species analysis showed that the transcriptome changes of these microglial subpopulations were mainly associated with Alzheimer's disease (AD) and major depressive disorder (MDD), which were further supported by animal behavioral tests. Our findings demonstrate that gut microbiota mainly modulate the mutual transformation of microglial subtypes, which may lead to new insights into the pathogenesis of AD and MDD.

Highly efficient removal of tannic acid from wastewater using biomimetic porous materials.

To effectively remove tannic acid (TA) from wastewater, using green and natural materials has attracted increasing attention. Inspired by Galla Chinensis (GC) with high content of TA, this study synthesized a biomimetic porous adsorbent to mimic the GC structure using dialdehyde tapioca starch (DTS) and gelatin (GL). The TA adsorption performance and mechanism of synthetic porous material were investigated. Results revealed that the porous material exhibited a maximum TA adsorption capacity of 1072.01 mg/g, along with a high removal rate of 95.16% under the conditions of a DTS-GL mass ratio of 1:1, DTS aldehyde content of 48.16%, a solid content of 5%, and a pH of 2 at 25 °C. The adsorption of TA by DTS was not affected by water-soluble cationic and anion. The adsorption kinetics of TA on the porous material followed the pseudo-second-order model, and this Langmuir adsorption model (R2 = 0.9954) which were well described the adsorption of TA by the material, indicating that the adsorption primarily occurred in a monolayer. FTIR, XRD, DSC, TG, XPS, and SEM-EDS were employed to characterize the structure characteristics of the porous material. The cross-linking between DTS and GL by Schiff base reaction imparted a chemical structure could absorb TA by hydrogen bonding. The TA desorption rates of in 30% acetone and 40% ethanol solutions were 88.76% and 91.03%, respectively. The porous material prepared by the GC-inspired approach holds promise as an ideal choice for loading polyphenolic compounds and provides a new perspective for the design and application of bioinspired engineering materials.

Enterogenic metabolomics signatures of depression: what are the possibilities for the future.

INTRODUCTION: An increasing number of studies indicate that the microbiota-gut-brain axis is an important pathway involved in the onset and progression of depression. The responses of the organism (or its microorganisms) to external cues cannot be separated from a key intermediate element: their metabolites. AREAS COVERED: In recent years, with the rapid development of metabolomics, an increasing amount of metabolites has been detected and studied, especially the gut metabolites. Nevertheless, the increasing amount of metabolites described has not been reflected in a better understanding of their functions and metabolic pathways. Moreover, our knowledge of the biological interactions among metabolites is also incomplete, which limits further studies on the connections between the microbial-entero-brain axis and depression. EXPERT OPINION: This paper summarizes the current knowledge on depression-related metabolites and their involvement in the onset and progression of this disease. More importantly, this paper summarized metabolites from the intestine, and defined them as enterogenic metabolites, to further clarify the function of intestinal metabolites and their biochemical cross-talk, providing theoretical support and new research directions for the prevention and treatment of depression.

Preoperative assessment of high-grade endometrial cancer using a radiomic signature and clinical indicators.

Aim: To develop and validate a radiomics-based combined model (ModelRC) to predict the pathological grade of endometrial cancer. Methods: A total of 403 endometrial cancer patients from two independent centers were enrolled as training, internal validation and external validation sets. Radiomic features were extracted from T2-weighted images, apparent diffusion coefficient map and contrast-enhanced 3D volumetric interpolated breath-hold examination images. Results: Compared with the clinical model and radiomics model, ModelRC showed superior performance; the areas under the receiver operating characteristic curves were 0.920 (95% CI: 0.864-0.962), 0.882 (95% CI: 0.779-0.955) and 0.881 (95% CI: 0.815-0.939) for the training, internal validation and external validation sets, respectively. Conclusion: ModelRC, which incorporated clinical and radiomic features, exhibited excellent performance in the prediction of high-grade endometrial cancer.

Accurate preoperative evaluation of the pathological grade of endometrial carcinoma is very important for the selection of treatment and prognosis. This study tried to develop a simple combined model based on radiomic features from endometrial carcinoma MRI and clinical features of patients. Compared with the clinical model and the radiomic model, the combined model showed superior performance. Therefore, this combined model would help patients and clinicians to make more rational decisions when choosing treatment strategies.

Edaravone ameliorates depressive and anxiety-like behaviors via Sirt1/Nrf2/HO-1/Gpx4 pathway.

BACKGROUND: The inflammation and oxidative stress (OS) have been considered crucial components of the pathogenesis of depression. Edaravone (EDA), a free radical scavenger, processes strong biological activities including antioxidant, anti-inflammatory and neuroprotective properties. However, its role and potential molecular mechanisms in depression remain unclear. The present study aimed to investigate the antidepressant activity of EDA and its underlying mechanisms. METHODS: A chronic social defeat stress (CSDS) depression model was performed to explore whether EDA could produce antidepressant effects. Behaviors tests were carried out to examine depressive, anxiety-like and cognitive behaviors including social interaction (SI) test, sucrose preference test (SPT), open field test (OFT), elevated plus maze (EPM), novel object recognition (NOR), tail suspension test (TST) and forced swim test (FST). Hippocampal and medial prefrontal cortex (mPFC) tissues were collected for Nissl staining, immunofluorescence, targeted energy metabolomics analysis, enzyme-linked immunosorbent assay (ELISA), measurement of MDA, SOD, GSH, GSH-PX, T-AOC and transmission electron microscopy (TEM). Western blotting (WB) and quantitative real-time polymerase chain reaction (qRT-PCR) detected the Sirt1/Nrf2/HO-1/Gpx4 signaling pathway. EX527, a Sirt1 inhibitor and ML385, a Nrf2 inhibitor were injected intraperitoneally 30 min before EDA injection daily. Knockdown experiments were performed to determine the effects of Gpx4 on CSDS mice with EDA treatment by an adeno-associated virus (AAV) vector containing miRNAi (Gpx4)-EGFP infusion. RESULTS: The administrated of EDA dramatically ameliorated CSDS-induced depressive and anxiety-like behaviors. In addition, EDA notably attenuated neuronal loss, microglial activation, astrocyte dysfunction, oxidative stress damage, energy metabolism and pro-inflammatory cytokines activation in the hippocampus (Hip) and mPFC of CSDS-induced mice. Further examination indicated that the application of EDA after the CSDS model significantly increased the protein expressions of Sirt1, Nrf2, HO-1 and Gpx4 in the Hip. EX527 abolished the antidepressant effect of EDA as well as the protein levels of Nrf2, HO-1 and Gpx4. Similarly, ML385 reversed the antidepressant and anxiolytic effects of EDA via decreased expressions of HO-1 and Gpx4. In addition, Gpx4 knockdown in CSDS mice abolished EDA-generated efficacy on depressive and anxiety-like behaviors. CONCLUSION: These findings suggest that EDA possesses potent antidepressant and anxiolytic properties through Sirt1/Nrf2/HO-1/Gpx4 axis and Gpx4-mediated ferroptosis may play a key role in this effect.

MENDA: a comprehensive curated resource of metabolic characterization in depression.

Depression is a seriously disabling psychiatric disorder with a significant burden of disease. Metabolic abnormalities have been widely reported in depressed patients and animal models. However, there are few systematic efforts that integrate meaningful biological insights from these studies. Herein, available metabolic knowledge in the context of depression was integrated to provide a systematic and panoramic view of metabolic characterization. After screening more than 10 000 citations from five electronic literature databases and five metabolomics databases, we manually curated 5675 metabolite entries from 464 studies, including human, rat, mouse and non-human primate, to develop a new metabolite-disease association database, called MENDA (http://menda.cqmu.edu.cn:8080/index.php). The standardized data extraction process was used for data collection, a multi-faceted annotation scheme was developed, and a user-friendly search engine and web interface were integrated for database access. To facilitate data analysis and interpretation based on MENDA, we also proposed a systematic analytical framework, including data integration and biological function analysis. Case studies were provided that identified the consistently altered metabolites using the vote-counting method, and that captured the underlying molecular mechanism using pathway and network analyses. Collectively, we provided a comprehensive curation of metabolic characterization in depression. Our model of a specific psychiatry disorder may be replicated to study other complex diseases.

An integrated meta-analysis of peripheral blood metabolites and biological functions in major depressive disorder.

Major depressive disorder (MDD) is a serious mental illness, characterized by high morbidity, which has increased in recent decades. However, the molecular mechanisms underlying MDD remain unclear. Previous studies have identified altered metabolic profiles in peripheral tissues associated with MDD. Using curated metabolic characterization data from a large sample of MDD patients, we meta-analyzed the results of metabolites in peripheral blood. Pathway and network analyses were then performed to elucidate the biological themes within these altered metabolites. We identified 23 differentially expressed metabolites between MDD patients and controls from 46 studies. MDD patients were characterized by higher levels of asymmetric dimethylarginine, tyramine, 2-hydroxybutyric acid, phosphatidylcholine (32:1), and taurochenodesoxycholic acid and lower levels of L-acetylcarnitine, creatinine, L-asparagine, L-glutamine, linoleic acid, pyruvic acid, palmitoleic acid, L-serine, oleic acid, myo-inositol, dodecanoic acid, L-methionine, hypoxanthine, palmitic acid, L-tryptophan, kynurenic acid, taurine, and 25-hydroxyvitamin D compared with controls. L-tryptophan and kynurenic acid were consistently downregulated in MDD patients, regardless of antidepressant exposure. Depression rating scores were negatively associated with decreased levels of L-tryptophan. Pathway and network analyses revealed altered amino acid metabolism and lipid metabolism, especially for the tryptophan-kynurenine pathway and fatty acid metabolism, in the peripheral system of MDD patients. Taken together, our integrated results revealed that metabolic changes in the peripheral blood were associated with MDD, particularly decreased L-tryptophan and kynurenic acid levels, and alterations in the tryptophan-kynurenine and fatty acid metabolism pathways. Our findings may facilitate biomarker development and the elucidation of the molecular mechanisms that underly MDD.

Metabolomic changes in animal models of depression: a systematic analysis.

Extensive research has been carried out on the metabolomic changes in animal models of depression; however, there is no general agreement about which metabolites exhibit constant changes. Therefore, the aim of this study was to identify consistently altered metabolites in large-scale metabolomics studies of depression models. We performed vote counting analyses to identify consistently upregulated or downregulated metabolites in the brain, blood, and urine of animal models of depression based on 3743 differential metabolites from 241 animal metabolomics studies. We found that serotonin, dopamine, gamma-aminobutyric acid, norepinephrine, N-acetyl-L-aspartic acid, anandamide, and tryptophan were downregulated in the brain, while kynurenine, myo-inositol, hydroxykynurenine, and the kynurenine to tryptophan ratio were upregulated. Regarding blood metabolites, tryptophan, leucine, tyrosine, valine, trimethylamine N-oxide, proline, oleamide, pyruvic acid, and serotonin were downregulated, while N-acetyl glycoprotein, corticosterone, and glutamine were upregulated. Moreover, citric acid, oxoglutaric acid, proline, tryptophan, creatine, betaine, L-dopa, palmitic acid, and pimelic acid were downregulated, and hippuric acid was upregulated in urine. We also identified consistently altered metabolites in the hippocampus, prefrontal cortex, serum, and plasma. These findings suggested that metabolomic changes in depression models are characterized by decreased neurotransmitter and increased kynurenine metabolite levels in the brain, decreased amino acid and increased corticosterone levels in blood, and imbalanced energy metabolism and microbial metabolites in urine. This study contributes to existing knowledge of metabolomic changes in depression and revealed that the reproducibility of candidate metabolites was inadequate in previous studies.

MRI Texture-Based Models for Predicting Mitotic Index and Risk Classification of Gastrointestinal Stromal Tumors.

BACKGROUND: Treatment regimens and prognoses of gastrointestinal stromal tumors (GIST) are quite different for tumors in different risk categories. Accurate preoperative grading of tumors is important for avoiding under- or overtreatment. PURPOSE: To develop and validate an MRI texture-based model to predict the mitotic index and its risk classification. STUDY TYPE: Retrospective. POPULATION: Ninety-one patients with histologically-confirmed GIST; 64 patients in a training cohort, and 27 patients in a test cohort. FIELD STRENGTH/SEQUENCE: T2 -weighted imaging (T2 WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced three-dimensional volumetric interpolated breath-hold examination (3D-VIBE) at 1.5T. ASSESSMENT: GIST images were manually segmented by two independent radiologists using ITK-SNAP software and MRI features were extracted using Pyradiomics. Two pathologists reviewed the tissue specimens of the tumors to identify the mitotic index and risk classification in consensus. STATISTICAL TESTS: The least absolute shrinkage and selection operator (LASSO) regression method was used to select texture features. A logistic regression model was established based on the radiomic score (radscore), tumor location, and maximum diameter to predict tumor classification and develop a nomogram. Receiver operator characteristic (ROC) curves were used to evaluate the ability of the nomogram to distinguish between two tumors with different risk classifications, and a calibration curve was used to evaluate the consistency between the predicted risk and the actual risk. RESULTS: The texture signature achieved high efficacy in predicting the mitotic index area under the curve ([AUC], 0.906; 95% confidence interval [CI]: 0.813, 0.961). A nomogram for prediction of the risk classification of GIST, which incorporated this texture signature together with maximum tumor diameter and location, allowed good discrimination in the training cohort (AUC, 0.878; 95% CI: 0.769, 0.960) and the validation cohort (AUC, 0.903; 95% CI: 0.732, 0.922). DATA CONCLUSION: The texture-based model can be used to predict GIST mitotic index and risk classification preoperatively. LEVEL OF EVIDENCE: 2. TECHNICAL EFFICACY STAGE: 3.

Alteration of lipids and amino acids in plasma distinguish schizophrenia patients from controls: A targeted metabolomics study.

BACKGROUND: Schizophrenia (SCZ) is a serious psychiatric disorder. Metabolite disturbance is an important pathogenic factor in schizophrenic patients. In this study, we aim to identify plasma lipid and amino acid biomarkers for SCZ using targeted metabolomics. METHODS: Plasma from 76 SCZ patients and 50 matched controls were analyzed using the LC/MS-based multiple reaction monitoring (MRM) metabolomics approach. A total of 182 targeted metabolites, including 22 amino acids and 160 lipids or lipid-related metabolites were observed. We used binary logistic regression analysis to determine whether the lipid and amino acid biomarkers could discriminate SCZ patients from controls. The area under the curve (AUC) from receiver operation characteristic (ROC) curve analysis was conducted to evaluate the diagnostic performance of the biomarkers panel. RESULTS: We identified 19 significantly differentially expressed metabolites between the SCZ patients and the controls (false discovery rate < 0.05), including one amino acid and 18 lipids or lipid-related metabolites. The binary logistic regression-selected panel showed good diagnostic performance in the drug-naïve group (AUC = 0.936) and all SCZ patients (AUC = 0.948), especially in the drug-treated group (AUC = 0.963). CONCLUSIONS: Plasma lipids and amino acids showed significant dysregulation in SCZ, which could effectively discriminate SCZ patients from controls. The LC/MS/MS-based approach provides reliable data for the objective diagnosis of SCZ.

Optimisation and evaluation of the random forest model in the efficacy prediction of chemoradiotherapy for advanced cervical cancer based on radiomics signature from high-resolution T2 weighted images.

PURPOSE: Our objective was to establish a random forest model and to evaluate its predictive capability of the treatment effect of neoadjuvant chemotherapy-radiation therapy. METHODS: This retrospective study included 82 patients with locally advanced cervical cancer who underwent scanning from March 2013 to May 2018. The random forest model was established and optimised based on the open source toolkit scikit-learn. Byoptimising of the number of decision trees in the random forest, the criteria for selecting the final partition index and the minimum number of samples partitioned by each node, the performance of random forest in the prediction of the treatment effect of neoadjuvant chemotherapy-radiation therapy on advanced cervical cancer (> IIb) was evaluated. RESULTS: The number of decision trees in the random forests influenced the model performance. When the number of decision trees was set to 10, 25, 40, 55, 70, 85 and 100, the performance of random forest model exhibited an increasing trend first and then a decreasing one. The criteria for the selection of final partition index showed significant effects on the generation of decision trees. The Gini index demonstrated a better effect compared with information gain index. The area under the receiver operating curve for Gini index attained a value of 0.917. CONCLUSION: The random forest model showed potential in predicting the treatment effect of neoadjuvant chemotherapy-radiation therapy based on high-resolution T2WIs for advanced cervical cancer (> IIb).

Effect of aquaporin 4 protein overexpression in nigrostriatal system on development of Parkinson's disease.

OBJECTS: Recent studies indicated that aquaporin 4 (AQP4), as the main water channel in the central nervous system (CNS), participated in the onset and progression of Parkinson's disease (PD). But how the AQP4 influenced the exacerbation of PD has not been described in detail. In this study, the effect of the AQP4 protein overexpression in nigrostriatal system that include substantia nigra (SN) and striatum (CPu) on the development of PD was investigated. METHODS: Forty male Sprague Dawley rats were equally divided into two groups at random: PD group and control group, PD group undergoing surgery and receiving 6-hydroxydopamine (6-OHDA). Using MRI tracer-based method, extracellular space (ECS) diffusion parameters of nigrostriatal system for all rats were measured, including the clearance coefficient (k') and the half-life (t1/2). Immunohistochemistry of AQP4 was performed for 20 rats. RESULTS: The area of dark-stained AQP4 immunoreactivity increased markedly in SN of PD rats, there were significant differences between two groups (SN: t = 5.809, p < 0.0001; CPu: t = 5.943, p < 0.0001). And the diffusion parameters were significantly greater in PD group than that of control group, including k' (SN: t = 5.519, p < 0.0001; CPu: t = 2.149, p = 0.045) and t1/2 (SN: t = 6.131, p < 0.0001; CPu: t = 6.708, p < 0.0001). There was a significant positive correlation between the AQP4 expression level and the k' values (SN: r = 0.827, p = 0.0031; CPu: r = 0.641, p = 0.0046), and a significant negative correlation between AQP4 and the t1/2 values (SN: r=-0.654, p = 0.0403; CPu: r=-0.664, p = 0.0362). CONCLUSIONS: The results indicated that AQP4 expression was increased in nigrostriatal system of PD rats, therefore, the overexpression of AQP4 led to acceleration of the diffusion and drainage process of drugs in ECS, reduced the effect of drugs for the treatment of PD, inhibited the development of PD.

Evaluating the Therapeutic Effect of Low-Intensity Transcranial Ultrasound on Traumatic Brain Injury With Diffusion Kurtosis Imaging.

BACKGROUND: Low-intensity transcranial ultrasound (LITUS) has a therapeutic effect on traumatic brain injury (TBI). Diffusion kurtosis imaging (DKI) might be able to evaluate the effect changes of injured brain microstructure. PURPOSE: To evaluate the therapeutic effect of LITUS in a moderate TBI rat model with DKI parameters. STUDY TYPE: Prospective case-control animal study. ANIMAL MODEL: Forty-five rats were randomly divided into sham control, TBI, and LITUS treatment groups (n = 15). FIELD STRENGTH/SEQUENCE: Single-shot spin echo echo-planar imaging and fast T2 WI sequences at 3.0T. ASSESSMENT: DKI parameters were obtained on days 1, 7, 14, 21, 28, 35, and 42 after TBI. STATISTICAL TESTS: For the mean kurtosis (MK), axial kurtosis (Ka), and radial kurtosis (Kr) values, groups were compared using a two-way analysis of variance (ANOVA). RESULTS: LITUS inhibited TBI and caused MK values to increase significantly during the early stage (LITUS vs. TBI, day 7, adjusted P < 0.0001) and decrease during the late stage (LITUS vs. TBI, day 42, adjusted P = 0.0156) in the damaged cortex. In the thalamus, the MK value of the TBI group began to rise on day 7, with no change observed in the LITUS group. TBI increases Ka value during the early stage in the cortex and decreases during the late stage in the cortex and thalamus. LITUS inhibited these Ka changes (LITUS vs. TBI, day 7, adjusted P = 0.0014; LITUS vs. TBI, day 42, adjusted P = 0.0026 and 0.0478, respectively, for cortex and thalamus). The Kr value increased slightly during the early stage in the cortex (TBI vs. Sham, day 1, adjusted P = 0.0016). DATA CONCLUSION: The DKI parameter, particularly the MK value, evaluates primary cortical injury as well as the secondary brain injury that could not be detected by conventional T2 WI. LEVEL OF EVIDENCE: 1 Technical Efficacy Stage: 4 J. Magn. Reson. Imaging 2020;52:520-531.

Polyunsaturated fatty acids metabolism, purine metabolism and inosine as potential independent diagnostic biomarkers for major depressive disorder in children and adolescents.

Major depressive disorder (MDD) in children and adolescents is a recurrent and disabling condition globally but its pathophysiology remains poorly elucidated and there are limited effective treatments available. We performed metabolic profiling of plasma samples based on ultra-high-performance liquid chromatography equipped with quadrupole time-offlight mass spectrometry to explore the potential biomarkers of depression in children and adolescents with MDD. We identified several perturbed pathways, including fatty acid metabolism-particularly the polyunsaturated fatty acids metabolism, and purine metabolism-that were associated with MDD in these young patients. In addition, inosine was shown as a potential independent diagnostic biomarker for MDD, achieving an area under the ROC curve of 0.999 in discriminating drug-naive MDD patients and 0.866 in discriminating drug-treated MDD from healthy controls. Moreover, we found evidence for differences in the pathophysiology of MDD in children and adolescents to that of adult MDD, specifically with tryptophan metabolism. Through metabolomic analysis, we have identified links between a framework of metabolic perturbations and the pathophysiology and diagnostic biomarker of child and adolescent MDD.

Efficacy and acceptability of psychological interventions for social anxiety disorder in children and adolescents: a meta-analysis of randomized controlled trials.

Social anxiety disorder (SAD) is highly prevalent and persistent in children and adolescents. However, evidence for the efficacy and acceptability of psychological interventions for SAD in children and adolescents remains unclear. Seven electronic databases (PubMed, CENTRAL, Embase, Web of Science, PsycINFO, CINAHL, and ProQuest) were searched. Randomized controlled trials (RCTs) that compared psychological interventions for SAD with control conditions in children and adolescents were included. Primary outcomes were the efficacy (mean change in anxiety symptom scores) and acceptability (dropouts for all reasons). Secondary outcomes were remission, quality of life/functional improvement, and depressive symptoms measures. Seventeen RCTs were included in this meta-analysis. Psychological interventions (including cognitive behavioral therapy and behavioral therapy) were significantly more effective than control conditions, with a standardized mean difference (SMD) of - 1.13, and remission with a risk ratio (RR) of 8.99, the number needed to treat was 3.3. There was no statistically significant difference between psychological interventions and control conditions for all-cause dropouts (RR = 1.00). Psychological interventions were superior to control conditions in improving quality of life/functioning (SMD = 0.79) and reducing depressive symptoms (SMD = - 0.39). Given considerable heterogeneity of primary efficacy outcome, a series of subgroup analyses of different variables were conducted. Psychological interventions are probably efficacious in the treatment of SAD among children and adolescents, and may markedly improve quality of life and functioning in this population. However, this finding should be interpreted with caution because of the high heterogeneity of trials and low literature quality.

Role of the combination of FA and T2* parameters as a new diagnostic method in therapeutic evaluation of parkinson's disease.

BACKGROUND: Simple diffusion delivery (SDD) has attained good effects with only tiny amounts of drugs. Fractional anisotropy (FA) and relaxation time T2* that indicate the integrity of fiber tracts and iron concentration within brain tissue were used to evaluate the therapeutic effect of SDD. PURPOSE: To evaluate therapeutic effect of SDD in the Parkinson's disease (PD) rat model with FA and T2* parameters. STUDY TYPE: Prospective case-control animal study. POPULATION: Thirty-two male Sprague Dawley rats (eight normal, eight PD, eight SDD, and eight subcutaneous injection rats). FIELD STRENGTH/SEQUENCE: Single-shot spin echo echo-planar imaging and fast low-angle shot T2 WI sequences at 3.0T. ASSESSMENT: Parameters of FA and T2* on the treated side of the substantia nigra were measured to evaluate the therapeutic effect of SDD in a PD rat model. STATISTICAL TESTS: The effects of time on FA and T2* values were analyzed by repeated measurement tests. A one-way analysis of variance was conducted, followed by individual comparisons of the mean FA and T2* values at different timepoints. RESULTS: The FA values on the treated side of the substantia nigra in the SDD treatment group and subcutaneous injection treatment group were significantly higher at week 1 and lower at week 6 than that of the PD control group (SDD vs. PD, week 1, adjusted P = 0.012; subcutaneous vs. PD, week 1, adjusted P < 0.001; SDD vs. PD, week 6, adjusted P = 0.004; subcutaneous vs. PD, week 6, adjusted P = 0.024). The T2* parameter in the SDD treatment group and subcutaneous injection treatment group was significantly higher than that in the PD control group at week 6 (SDD vs. PD, adjusted P = 0.032; subcutaneous vs. PD, adjusted P < 0.001). DATA CONCLUSION: The combination of FA and T2* parameters can potentially serve as a new effective evaluation method of the therapeutic effect of SDD. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2017.

Antidepressants for depressive disorder in children and adolescents: a database of randomised controlled trials.

BACKGROUND: In recent years, whether, when and how to use antidepressants to treat depressive disorder in children and adolescents has been hotly debated. Relevant evidence on this topic has increased rapidly. In this paper, we present the construction and content of a database of randomised controlled trials of antidepressants to treat depressive disorder in children and adolescents. This database can be freely accessed via our website and will be regularly updated. DESCRIPTION: Major bibliographic databases (PubMed, the Cochrane Library, Web of Science, Embase, CINAHL, PsycINFO and LiLACS), international trial registers and regulatory agencies' websites were systematically searched for published and unpublished studies up to April 30, 2017. We included randomised controlled trials in which the efficacy or tolerability of any oral antidepressant was compared with that of a control group or any other treatment. In total, 7377 citations from bibliographical databases and 3289 from international trial registers and regulatory agencies' websites were identified. Of these, 53 trials were eligible for inclusion in the final database. Selected data were extracted from each study, including characteristics of the participants (the study population, setting, diagnostic criteria, type of depression, age, sex, and comorbidity), characteristics of the treatment conditions (the treatment conditions, general information, and detail of pharmacotherapy and psychotherapy) and study characteristics (the sponsor, country, number of sites, blinding method, sample size, treatment duration, depression scales, other scales, and primary outcome measure used, and side-effect monitoring method). Moreover, the risk of bias for each trial were assessed. CONCLUSION: This database provides information on nearly all randomised controlled trials of antidepressants in children and adolescents. By using this database, researchers can improve research efficiency, avoid inadvertent errors and easily focus on the targeted subgroups in which they are interested. For authors of subsequent reviews, they could only use this database to insure that they have completed a comprehensive review, rather than relied solely on the data from this database. We expect this database could help to promote research on evidence-based practice in the treatment of depressive disorder in children and adolescents. The database could be freely accessed in our website: http://xiepengteam.cn/research/evidence-based-medicine .

Comparative efficacy and tolerability of antidepressants for major depressive disorder in children and adolescents: a network meta-analysis.

BACKGROUND: Major depressive disorder is one of the most common mental disorders in children and adolescents. However, whether to use pharmacological interventions in this population and which drug should be preferred are still matters of controversy. Consequently, we aimed to compare and rank antidepressants and placebo for major depressive disorder in young people. METHODS: We did a network meta-analysis to identify both direct and indirect evidence from relevant trials. We searched PubMed, the Cochrane Library, Web of Science, Embase, CINAHL, PsycINFO, LiLACS, regulatory agencies' websites, and international registers for published and unpublished, double-blind randomised controlled trials up to May 31, 2015, for the acute treatment of major depressive disorder in children and adolescents. We included trials of amitriptyline, citalopram, clomipramine, desipramine, duloxetine, escitalopram, fluoxetine, imipramine, mirtazapine, nefazodone, nortriptyline, paroxetine, sertraline, and venlafaxine. Trials recruiting participants with treatment-resistant depression, treatment duration of less than 4 weeks, or an overall sample size of less than ten patients were excluded. We extracted the relevant information from the published reports with a predefined data extraction sheet, and assessed the risk of bias with the Cochrane risk of bias tool. The primary outcomes were efficacy (change in depressive symptoms) and tolerability (discontinuations due to adverse events). We did pair-wise meta-analyses using the random-effects model and then did a random-effects network meta-analysis within a Bayesian framework. We assessed the quality of evidence contributing to each network estimate using the GRADE framework. This study is registered with PROSPERO, number CRD42015016023. FINDINGS: We deemed 34 trials eligible, including 5260 participants and 14 antidepressant treatments. The quality of evidence was rated as very low in most comparisons. For efficacy, only fluoxetine was statistically significantly more effective than placebo (standardised mean difference -0·51, 95% credible interval [CrI] -0·99 to -0·03). In terms of tolerability, fluoxetine was also better than duloxetine (odds ratio [OR] 0·31, 95% CrI 0·13 to 0·95) and imipramine (0·23, 0·04 to 0·78). Patients given imipramine, venlafaxine, and duloxetine had more discontinuations due to adverse events than did those given placebo (5·49, 1·96 to 20·86; 3·19, 1·01 to 18·70; and 2·80, 1·20 to 9·42, respectively). In terms of heterogeneity, the global I(2) values were 33·21% for efficacy and 0% for tolerability. INTERPRETATION: When considering the risk-benefit profile of antidepressants in the acute treatment of major depressive disorder, these drugs do not seem to offer a clear advantage for children and adolescents. Fluoxetine is probably the best option to consider when a pharmacological treatment is indicated. FUNDING: National Basic Research Program of China (973 Program).