Interactions between overweight/obesity and alcohol dependence impact human brain white matter microstructure: evidence from DTI.

There is inconsistent evidence for an association of obesity with white matter microstructural alterations. Such inconsistent findings may be related to the cumulative effects of obesity and alcohol dependence. This study aimed to investigate the possible interactions between alcohol dependence and overweight/obesity on white matter microstructure in the human brain. A total of 60 inpatients with alcohol dependence during early abstinence (44 normal weight and 16 overweight/obese) and 65 controls (42 normal weight and 23 overweight/obese) were included. The diffusion tensor imaging (DTI) measures [fractional anisotropy (FA) and radial diffusivity (RD)] of the white matter microstructure were compared between groups. We observed significant interactive effects between alcohol dependence and overweight/obesity on DTI measures in several tracts. The DTI measures were not significantly different between the overweight/obese and normal-weight groups (although widespread trends of increased FA and decreased RD were observed) among controls. However, among the alcohol-dependent patients, the overweight/obese group had widespread reductions in FA and widespread increases in RD, most of which significantly differed from the normal-weight group; among those with overweight/obesity, the alcohol-dependent group had widespread reductions in FA and widespread increases in RD, most of which were significantly different from the control group. This study found significant interactive effects between overweight/obesity and alcohol dependence on white matter microstructure, indicating that these two controllable factors may synergistically impact white matter microstructure and disrupt structural connectivity in the human brain.

Aberrant degree centrality profiles during rumination in major depressive disorder.

Rumination is closely linked to the onset and maintenance of major depressive disorder (MDD). Prior neuroimaging studies have identified the association between self-reported rumination trait and the functional coupling among a network of brain regions using resting-state functional magnetic resonance imaging (MRI). However, little is known about the underlying neural circuitry mechanism during active rumination in MDD. Degree centrality (DC) is a simple metric to denote network integration, which is critical for higher-order psychological processes such as rumination. During an MRI scan, individuals with MDD (N = 45) and healthy controls (HC, N = 46) completed a rumination state task. We examined the interaction effect between the group (MDD vs. HC) and condition (rumination vs. distraction) on vertex-wise DC. We further characterized the identified brain region's functional involvement with Neurosynth and BrainMap. Network-wise seed-based functional connectivity (FC) analysis was also conducted for the identified region of interest. Finally, exploratory correlation analysis was conducted between the identified region of interest's network FCs and self-reported in-scanner affect levels. We found that a left superior frontal gyrus (SFG) region, generally overlapped with the frontal eye field, showed a significant interaction effect. Further analysis revealed its involvement with executive functions. FCs between this region, the frontoparietal, and the dorsal attention network (DAN) also showed significant interaction effects. Furthermore, its FC to DAN during distraction showed a marginally significant negative association with in-scanner affect level at the baseline. Our results implicated an essential role of the left SFG in the rumination's underlying neural circuitry mechanism in MDD and provided novel evidence for the conceptualization of rumination in terms of impaired executive control.

An evaluation of cervical maturity for Chinese women with labor induction by machine learning and ultrasound images.

BACKGROUND: To evaluate the improvement of evaluation accuracy of cervical maturity for Chinese women with labor induction by adding objective ultrasound data and machine learning models to the existing traditional Bishop method. METHODS: The machine learning model was trained and tested using 101 sets of data from pregnant women who were examined and had their delivery in Peking University Third Hospital in between December 2019 and January 2021. The inputs of the model included cervical length, Bishop score, angle, age, induced labor time, measurement time (MT), measurement time to induced labor time (MTILT), method of induced labor, and primiparity/multiparity. The output of the model is the predicted time from induced labor to labor. Our experiments analyzed the effectiveness of three machine learning models: XGBoost, CatBoost and RF(Random forest). we consider the root-mean-squared error (RMSE) and the mean absolute error (MAE) as the criterion to evaluate the accuracy of the model. Difference was compared using t-test on RMSE between the machine learning model and the traditional Bishop score. RESULTS: The mean absolute error of the prediction result of Bishop scoring method was 19.45 h, and the RMSE was 24.56 h. The prediction error of machine learning model was lower than the Bishop score method. Among the three machine learning models, the MAE of the model with the best prediction effect was 13.49 h and the RMSE was 16.98 h. After selection of feature the prediction accuracy of the XGBoost and RF was slightly improved. After feature selection and artificially removing the Bishop score, the prediction accuracy of the three models decreased slightly. The best model was XGBoost (p = 0.0017). The p-value of the other two models was < 0.01. CONCLUSION: In the evaluation of cervical maturity, the results of machine learning method are more objective and significantly accurate compared with the traditional Bishop scoring method. The machine learning method is a better predictor of cervical maturity than the traditional Bishop method.

Two-dimensional displacement estimation of one-dimensional laser speckle images for detection of acoustic vibration.

Detection and recovery of audio signals using optical methods is an appealing topic. Observing the movement of secondary speckle patterns is a convenient method for such a purpose. In order to have less computational cost and faster processing, one-dimensional laser speckle images are captured by an imaging device, while it sacrifices the ability to detect speckle movement along one axis. This paper proposes a laser microphone system to estimate the two-dimensional displacement from one-dimensional laser speckle images. Hence, we can regenerate audio signals in real time even as the sound source is rotating. Experimental results show that our system is capable of reconstructing audio signals under complex conditions.

Disrupted intrinsic functional brain topology in patients with major depressive disorder.

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.

Impaired robust interhemispheric function integration of depressive brain from REST-meta-MDD database in China.

BACKGROUND: Recently, functional homotopy (FH) architecture, defined as robust functional connectivity (FC) between homotopic regions, has been frequently reported to be altered in MDD patients (MDDs) but with divergent locations. METHODS: In this study, we obtained resting-state functional magnetic resonance imaging (R-fMRI) data from 1004 MDDs (mean age, 33.88 years; age range, 18-60 years) and 898 matched healthy controls (HCs) from an aggregated dataset from 20 centers in China. We focused on interhemispheric function integration in MDDs and its correlation with clinical characteristics using voxel-mirrored homotopic connectivity (VMHC) devised to inquire about FH patterns. RESULTS: As compared with HCs, MDDs showed decreased VMHC in visual, motor, somatosensory, limbic, angular gyrus, and cerebellum, particularly in posterior cingulate gyrus/precuneus (PCC/PCu) (false discovery rate [FDR] q < 0.002, z = -7.07). Further analysis observed that the reduction in SMG and insula was more prominent with age, of which SMG reflected such age-related change in males instead of females. Besides, the reduction in MTG was found to be a male-special abnormal pattern in MDDs. VMHC alterations were markedly related to episode type and illness severity. The higher Hamilton Depression Rating Scale score, the more apparent VMHC reduction in the primary visual cortex. First-episode MDDs revealed stronger VMHC reduction in PCu relative to recurrent MDDs. CONCLUSIONS: We confirmed a significant VMHC reduction in MDDs in broad areas, especially in PCC/PCu. This reduction was affected by gender, age, episode type, and illness severity. These findings suggest that the depressive brain tends to disconnect information exchange across hemispheres.

Data-driven study on resting-state functional magnetic resonance imaging during early abstinence of alcohol dependence in male patients and its predictive value for relapse.

BACKGROUND: Alcohol dependence is a mental disorder with a high relapse rate. However, specific neuroimaging biomarkers have not been determined for alcohol dependence and its relapse. We conducted data-driven research to investigate resting-state functional magnetic resonance imaging (rs-fMRI) during early abstinence from alcohol dependence and its potential ability to predict relapse. METHODS: Participants included 68 alcohol-dependent patients and 68 healthy controls (HCs). The regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF) were compared between the alcohol dependence group and the HCs and between the relapse group and the nonrelapse group. The brain regions that presented significantly different ReHo and/or fALFF between the alcohol-dependent patients and HCs and/or between the relapsed and nonrelapsed patients were selected as the seeds to calculate the functional connectivities (FCs). RESULTS: During a 6-month follow-up period, 52.24% of alcohol-dependent patients relapsed. A regression model for differentiating alcohol-dependent patients and HCs showed that reductions in ReHo in the left postcentral region, fALFF in the right fusiform region, and FC in the right fusiform region to the right middle cingulum were independently associated with alcohol dependence, with an area under the receiver operating characteristic curve (AUC) of 0.841. The baseline FC of the left precentral to the left cerebellum of the relapse group was significantly lower than that of the nonrelapse group. The AUC of this FC to predict relapse was 0.774. CONCLUSIONS: Our findings contribute to advancing research on the neurobiological etiology and predictive biomarkers for relapse associated with alcohol dependence.

Reduced default mode network functional connectivity in patients with recurrent major depressive disorder.

Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol before aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor, and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. All R-fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.

The interactions between childhood adversities and recent stress were associated with early-adulthood depression among Chinese undergraduate students.

BACKGROUND: It is widely acknowledged that childhood adversities (CAs) and recent stress are potential risk factors for adult depression. However, the mechanism(s) by which interactions of CAs with recent stress affect adult depression remain unclear. AIMS: To investigate the predictive association of the interaction among CAs and recent stress with early-adult depression. METHOD: We conducted an annual survey of all freshmen for the period of 2016-2018 in a Chinese comprehensive university, with a sample size of 23,206. An online questionnaire including standardized self-report instruments was used to assess sociodemographic factors, childhood experiences of left-behind (CELB), and maltreatments (CEMTs) including beating (CEB), neglect (CEN), sexual abuse (CESA), recent stress, and current depression (measured by the 9-item Patient Health Questionnaire). RESULTS: The correlation of Individual CAs and recent stress was significant. In addition to their significant independent/direct incremental effects, all surveyed CAs were associated with increased severity of early-adult depression, and increased frequency of clinically significant depression (CSD), through significant associations with recent stress (mediation effect). History of CEMTs including CEB, CEN, and CESA significantly increased the effects of recent stress on depression (moderation effect). CONCLUSIONS: Chinese undergraduate students reported frequent history of exposure to CAs, which increased the likelihood of depression in early adulthood, not only directly but also through the increasing the likelihood (mediation effect) and impact (moderation effect) of recent stress on depression. These novel findings may help to extend our understanding of environmental determinants of depression, and to guide further research, clinical practice, and policy in this context.

Manganese and IL-12 treatment alters the ovarian tumor microenvironment.

Metal immunotherapy is a novel adjuvant immunotherapy. Mn2+ can activate STING-a type I IFN response protein-that promotes innate immunity and increases anti-tumor activity by promoting macrophage phagocytosis. IL-12, a cytokine that increases the antigen-presenting ability to promote effector T-cell activation, has potent antitumor activity, albeit with severe adverse effects. In this study, we observed that the combination of Mn2+ and IL-12 has a better antitumor effect and possibly reflects a better safety profile, providing a novel approach and theoretical basis for safe and rapid cancer treatment.

[Analysis of clinicopathological factors associated with false-negative rate of sentinel lymph node biopsy in breast cancer patients: experience of a single center].

OBJECTIVE: The purpose of this study was to investigate the clinicopathologic factors associated with false-negative rate of sentinel lymph node biopsy (SLNB) in breast cancer, and to explore how to reduce the false-negative rate of SLNB. METHODS: The clinicopathological data of 2265 patients with invasive breast carcinoma who underwent sentinel lymph nodes biopsy (SLNB) in Shandong Cancer Hospital between November 1999 and December 2011 were retrospectively analyzed. We screened 1228 patients who received axillary lymph node dissection after SLNB, and studied the clinicopathological factors that could be associated with false-negative rate of SLNB. RESULTS: The false negative rate of this group was 10.7% (73/683), accuracy rate was 94.1% (1155/1228), and negative predictive value was 88.2% (545/618). Clinical tumor size (all P < 0.05), calendar year of surgery (all P < 0.05) and numbers of detected SLNs (all P < 0.05) were significantly related with false negative rate and accuracy rate of SLNB, determined by single factor analysis. Logistic regression model analysis showed that calendar year of surgery (P = 0.034) and numbers of detected SLNs (P = 0.012) were independent predictive factors for the false negative rate of SLNB. CONCLUSIONS: False negative rate and accuracy rate of SLNB are significantly related to the calendar year of surgery and number of detected SLNs. Strict case selection, standard operation procedure, increaseing numbers of detected SLNs, and improvement of the skill of operators are effective measures to reduce the false negative rate of SLNB.

Multivariate classification based on large-scale brain networks during early abstinence predicted lapse among male detoxified alcohol-dependent patients.

Identifying biomarkers to predict lapse of alcohol-dependence (AD) is essential for treatment and prevention strategies, but remains remarkably challenging. With an aim to identify neuroimaging features for predicting AD lapse, 66 male AD patients during early-abstinence (baseline) after hospitalized detoxification underwent resting-state functional magnetic resonance imaging and were then followed-up for 6 months. The relevance-vector-machine (RVM) analysis on baseline large-scale brain networks yielded an elegant model for differentiating relapsing patients (n = 38) from abstainers, with the area under the curve of 0.912 and the accuracy by leave-one-out cross-validation of 0.833. This model captured key information about neuro-connectome biomarkers for predicting AD lapse.

Clinical efficacy of hyperbaric oxygen combined with different timings of right median-nerve electrical stimulation in patients with brain injury-induced disorders of consciousness.

OBJECTIVE: The objective of this study was to investigate the clinical efficacy of hyperbaric oxygen combined with right median-nerve stimulation (RMNES) in patients with disorders of consciousness caused by brain injury. METHODS: A total of 120 patients with consciousness disorders caused by brain injury were selected. They were randomly divided into three groups, a control group, test group 1 (treated with RMNES after hyperbaric oxygen therapy [HBOT]), and test group 2 (treated with RMNES at the same time as HBOT), with 40 patients in each group. Before and after treatment, the Glasgow coma scale (GCS), brainstem auditory-evoked potential (BAEP), electroencephalogram (EEG), and upper-limb sensory-evoked potential (USEP) were evaluated for the three groups of patients. RESULTS: The GCS score of patients in the three groups significantly improved compared with that before treatment (p < .05). There were significant differences in GCS scores among the three groups (p < .05), and the GCS score for the patients was test group 2>test group 1>control group. The EEG, BAEP, and USEP scores were significantly improved compared with those before treatment (p < .05), and the degree of improvement of patients in the three groups was test group 2>test group 1>control group (p < .05). The clinical efficacy of test group 2 was higher than that of test group 1, and the clinical efficacy of test group 1 was higher than that of the control group (p < .05). CONCLUSION: Hyperbaric oxygen combined with RMNES can improve the state of consciousness and promote the recovery of consciousness for patients with consciousness disorders caused by brain injury, and the effect of RMNES combined with HBOT in the chamber on improving the recovery of consciousness is better than after HBOT outside the chamber.

Short-term efficacy of music therapy combined with α binaural beat therapy in disorders of consciousness.

Objective: To investigate the short-term effect of music therapy combined with binaural frequency difference therapy on patients with consciousness disorder. Materials and methods: Ninety patients with definite diagnosis of disorders of consciousness (DOC) were selected. These patients were randomly divided into control group, experiment 1 group and experiment 2 group, with 30 patients in each group. The control group was treated with routine clinical treatment and rehabilitation. In experiment 1 group, music therapy was added to the control group. In experimental group 2, music therapy combined with binaural α frequency difference therapy was added to the control group. All patients were assessed before and after 30 treatments. The assessment items included Glasgow Coma Scale (GCS), Coma Recovery Scale revised (CRS-R), electroencephalogram (EEG), upper somatosensory evoked potential (USEP), and brainstem auditory evoked potential (BAEP). Results: Before treatment, there were no significant differences in GCS score, CRS-R score, USEP, BAEP, and EEG scores among the three groups (P > 0.05). After 30 times of treatment, GCS score, CRS-R score, USEP, BAEP, and EEG scores in 3 groups were significantly higher than those before treatment (P < 0.05), and experimental group 2 >experimental group 1 >control group (P < 0.05). And the consciousness rate of experimental group 2 was better than experimental group 1, experimental group 1 was better than the control group and the difference was statistically significant (P < 0.05). Conclusion: Music therapy combined with binaural α frequency difference therapy is more effective in stimulating DOC patients.

Clinical effect of pulmonary rehabilitation combined with diaphragm pacemaker therapy in the treatment of severely ill patients with mechanical ventilation.

To investigate the effect of pulmonary rehabilitation combined with diaphragm pacemaker therapy on the diaphragm function of severely ill patients on mechanical ventilation. Forty patients were randomly divided into the control group (CG; n = 20) and experimental group (EG; n = 20). The CG was given basic ICU nursing and conventional rehabilitation treatment. The EG added a diaphragm pacemaker and pulmonary rehabilitation therapies along with basic ICU nursing and conventional rehabilitation treatment. The relevant indexes were compared at baseline and postintervention, including the Glasgow Coma Scale (GCS), Acute Physiology, Chronic Health Evaluation II (APACHE II) scores, diaphragm mobility and thickness. The indexes of mechanical ventilation time, ICU and total hospital stays were compared between the two groups. There was no difference in the GCS and APACHE II scores, and diaphragm mobility and thickness between the two groups before treatment (P > 0.05). After 30 days of treatment, the GCS scores increased in both groups, the APACHE II scores decreased significantly, and diaphragm mobility and thickness decreased compared with before treatment (P < 0.05), but the improvement of each index in the EG was more evident than in the CG. Compared with the CG, the indexes of the EG, including offline, ICU and total hospitalization times, were significantly shorter (P < 0.05). Additionally, there were no adverse events such as accidental tube detachment or falling out of bed during treatment. Pulmonary rehabilitation combined with a diaphragm pacemaker is safe and effective in treating severely ill mechanically ventilated patients.

UV-light-assisted gas sensor based on PdSe2/InSe heterojunction for ppb-level NO2 sensing at room temperature.

The fabrication of van der Waals (vdWs) heterostructures mainly extends to two-dimensional (2D) materials. Nevertheless, the current processes for obtaining high-quality 2D films are mainly exfoliated from their bulk counterparts or by high-temperature chemical vapor deposition (CVD), which limits industrial production and is often accompanied by defects. Herein, we first fabricated the type-II p-PdSe2/n-InSe vdWs heterostructure using the ultra-high vacuum laser molecular beam epitaxy (LMBE) technique combined with the vertical 2D stacking strategy, which is reproducible and suitable for high-volume manufacturing. This work found that the introduction of 365 nm UV light illumination can significantly improve the electrical transport properties and NO2 sensing performance of the PdSe2/InSe heterojunction-based device at room temperature (RT). The detailed studies confirm that the sensor based on the PdSe2/InSe heterojunction delivers the comparable sensitivity (Ra/Rg = ∼2.6 at 10 ppm), a low limit of detection of 52 ppb, and excellent selectivity for NO2 gas under UV light illumination, indicating great potential for NO2 detection. Notably, the sensor possesses fast response and full recovery properties (275/1078 s) compared to the results in the dark. Furthermore, the mechanism of enhanced gas sensitivity was proposed based on the energy band alignment of the PdSe2/InSe heterojunction with the assistance of investigating the surface potential variations. This work may pave the way for the development of high-performance, room-temperature gas sensors based on 2D vdWs heterostructures through the LMBE technique.

A bidirectional association between internet addiction and depression: A large-sample longitudinal study among Chinese university students.

BACKGROUND: Internet addiction (IA) is associated with adverse consequences, especially for younger people. Evidence indicates that IA is associated with depression, but no studies have yet investigated potential common vulnerability between them. METHODS: IA (measured by the Young's 20-item Internet Addiction Test Scale) and depressive symptoms (measured by the Patient Health Questionnaire-9 Scale) among 12 043 undergraduates were surveyed at baseline and at a respective 12 month follow-up for each participant. Application of a cross-lagged panel model approach (CLPM) revealed an association between IA and depression after adjusting for demographic variables. RESULTS: Rates of baseline IA and depression were 5.47% (95% CI: 5.07%, 5.88%) and 3.85% (95% CI: 3.51%, 4.20%), respectively; increasing to 9.47% (95% CI: 8.94%, 9.99%) and 5.58% (95% CI: 5.17%,5.99%), respectively, at follow-up. Rates of new-incidences of IA and depression over 12 months were 7.43% (95% CI: 6.95%, 7.91%) and 4.47% (95% CI: 4.09%, 4.84%), respectively. Models in the present analysis revealed that baseline depression had a significant net-predictive effect on follow-up IA, and baseline IA had a significant net-predictive effect on follow-up depression. LIMITATIONS: The follow-up survey response rate was moderate (54.69%) in this analysis of university students. Moreover, the IAT-20 scale did not allow differentiate between specific forms of Internet activity. CONCLUSIONS: Common vulnerability and bidirectional cross-causal effects may both contribute to the association between IA and depression, with common vulnerability likely playing a more significant role than cross-causal effects.

Reduced nucleus accumbens functional connectivity in reward network and default mode network in patients with recurrent major depressive disorder.

The nucleus accumbens (NAc) is considered a hub of reward processing and a growing body of evidence has suggested its crucial role in the pathophysiology of major depressive disorder (MDD). However, inconsistent results have been reported by studies on reward network-focused resting-state functional MRI (rs-fMRI). In this study, we examined functional alterations of the NAc-based reward circuits in patients with MDD via meta- and mega-analysis. First, we performed a coordinated-based meta-analysis with a new SDM-PSI method for all up-to-date rs-fMRI studies that focused on the reward circuits of patients with MDD. Then, we tested the meta-analysis results in the REST-meta-MDD database which provided anonymous rs-fMRI data from 186 recurrent MDDs and 465 healthy controls. Decreased functional connectivity (FC) within the reward system in patients with recurrent MDD was the most robust finding in this study. We also found disrupted NAc FCs in the DMN in patients with recurrent MDD compared with healthy controls. Specifically, the combination of disrupted NAc FCs within the reward network could discriminate patients with recurrent MDD from healthy controls with an optimal accuracy of 74.7%. This study confirmed the critical role of decreased FC in the reward network in the neuropathology of MDD. Disrupted inter-network connectivity between the reward network and DMN may also have contributed to the neural mechanisms of MDD. These abnormalities have potential to serve as brain-based biomarkers for individual diagnosis to differentiate patients with recurrent MDD from healthy controls.

The DIRECT consortium and the REST-meta-MDD project: towards neuroimaging biomarkers of major depressive disorder.

Despite a growing neuroimaging literature on the pathophysiology of major depressive disorder (MDD), reproducible findings are lacking, probably reflecting mostly small sample sizes and heterogeneity in analytic approaches. To address these issues, the Depression Imaging REsearch ConsorTium (DIRECT) was launched. The REST-meta-MDD project, pooling 2428 functional brain images processed with a standardized pipeline across all participating sites, has been the first effort from DIRECT. In this review, we present an overview of the motivations, rationale, and principal findings of the studies so far from the REST-meta-MDD project. Findings from the first round of analyses of the pooled repository have included alterations in functional connectivity within the default mode network, in whole-brain topological properties, in dynamic features, and in functional lateralization. These well-powered exploratory observations have also provided the basis for future longitudinal hypothesis-driven research. Following these fruitful explorations, DIRECT has proceeded to its second stage of data sharing that seeks to examine ethnicity in brain alterations in MDD by extending the exclusive Chinese original sample to other ethnic groups through international collaborations. A state-of-the-art, surface-based preprocessing pipeline has also been introduced to improve sensitivity. Functional images from patients with bipolar disorder and schizophrenia will be included to identify shared and unique abnormalities across diagnosis boundaries. In addition, large-scale longitudinal studies targeting brain network alterations following antidepressant treatment, aggregation of diffusion tensor images, and the development of functional magnetic resonance imaging-guided neuromodulation approaches are underway. Through these endeavours, we hope to accelerate the translation of functional neuroimaging findings to clinical use, such as evaluating longitudinal effects of antidepressant medications and developing individualized neuromodulation targets, while building an open repository for the scientific community.

[Use of translational medicine in the early diagnosis of xenobiotic-induced intrauterine growth retardation].

Translational medicine is an emerging idea in current medical research area. Typically, for the purpose of bridging the gap between basic and clinical research, it not only emphasizes the urgency and necessity to break the traditional working formats, including single subject centered research team and limited cooperation among different scientific groups, but also highlights a more close and frequent interaction between basic scientist and clinician. In order to reach this goal, the theory and method of systems biology should be employed. This paper mainly focused on a central issue that how to carry out an investigation on early clinical diagnosis of xenobiotic-induced intrauterine growth retardation (IUGR) by using research concept of translational medicine and method of systems biology. Briefly, a hypothesis of common mechanism of IUGR was first proposed and subsequent validation was performed via integrating--omics (e.g. genomics, proteomics, cytomics, metabonomics/metabolomics) and molecular biology techniques. Metabonomics was further utilized to explore IUGR biomarker and establish preliminary forecasting model by bioinformatics and computational biology, which is available for early diagnosis of IUGR and make a complement to current evaluation criteria.