Distinct resting-state effective connectivity of large-scale networks in first-episode and recurrent major depression disorder: evidence from the REST-meta-MDD consortium.

Introduction: Previous studies have shown disrupted effective connectivity in the large-scale brain networks of individuals with major depressive disorder (MDD). However, it is unclear whether these changes differ between first-episode drug-naive MDD (FEDN-MDD) and recurrent MDD (R-MDD). Methods: This study utilized resting-state fMRI data from 17 sites in the Chinese REST-meta-MDD project, consisting of 839 patients with MDD and 788 normal controls (NCs). All data was preprocessed using a standardized protocol. Then, we performed a granger causality analysis to calculate the effectivity connectivity (EC) within and between brain networks for each participant, and compared the differences between the groups. Results: Our findings revealed that R-MDD exhibited increased EC in the fronto-parietal network (FPN) and decreased EC in the cerebellum network, while FEDN-MDD demonstrated increased EC from the sensorimotor network (SMN) to the FPN compared with the NCs. Importantly, the two MDD subgroups displayed significant differences in EC within the FPN and between the SMN and visual network. Moreover, the EC from the cingulo-opercular network to the SMN showed a significant negative correlation with the Hamilton Rating Scale for Depression (HAMD) score in the FEDN-MDD group. Conclusion: These findings suggest that first-episode and recurrent MDD have distinct effects on the effective connectivity in large-scale brain networks, which could be potential neural mechanisms underlying their different clinical manifestations.

Homeland, emotions, and identity: Constructing the place attachment of young overseas Chinese relatives in the returned Vietnam-Chinese community.

Little attention has been paid to the place attachment and homeland construction for refugees and their descendants in China. This study investigates the process by which the place attachment of Young Overseas Chinese Relatives is shaped in the context of resettlement sites. This qualitative research employed ethnographic fieldwork, and the author collected local literature and materials from February to December 2019 through participatory observation, in-depth interviews, and questionnaires. It is believed that the construction of a new homeland in the community, the emotional experience of the Young in childhood, and the cultural logic of place attachment shape place attachment. The process by which place attachment is shaped is interwoven with homeland construction, which indicates that the living state and mentality of the Young are becoming increasingly stable. The Young developed different mentalities on the basis of traditional Confucian culture in responding to the socio-cultural environments. The resettlement site has become a homeland to which young persons are solidly attached, people give this site meanings and experience certain emotions regarding it, which generates place identity and begins the process of homeland construction.

Diagnostic model optimization method for ADHD based on brain network analysis of resting-state fMRI images and transfer learning neural network.

Introduction: Attention deficit and hyperactivity disorder (ADHD) is a common inherited disease of the nervous system whose cause(s) and pathogenesis remain unclear. Currently, the diagnosis of ADHD is mainly based on clinical experience and guidelines that have laid out some diagnostic standards. Our study aimed to apply a learning-based classification method to assist the ADHD diagnosis based on high-dimensional resting-state fMRI. Methods: Our study selected the ADHD-200 Peking dataset of resting-state fMRI, which has an ADHD patient (n = 142) group and a typically developing control (TDC) healthy control (n = 102) group. We first used Pearson and partial correlation coefficients to perform functional connectivity (FC) analysis between ROIs. Then, the Pearson and partial correlation coefficient matrices were concatenated into a dual-channel feature to build a dual data channel as input to the transfer learning neural network (TLNN) architecture. Finally, we transferred the pretrained model from the auxiliary domain to our target domain and fine-tuned it. Results: Based on the Pearson correlation coefficient, FC between ROIs was detected in 22 brain regions, including the fusiform gyrus, superior frontal gyrus, posterior superior temporal sulcus, inferior parietal lobule, anterior cingulate cortex, and parahippocampal gyrus. Based on the partial correlation coefficient, we found FC in the salient network, default network, sensory-motor network, dorsal attention network, and cerebellum network. With the TLNN architecture, we solved the problem of insufficient training data and improved the sensitivity of the classification method. When the VGG model (fine-tuned transfer strategy, 1,024 fully connected layers) was applied, the accuracy of TLNN classification ultimately reached 82%. Conclusion: Our study suggests that completing the training of the target domain by transferring the prior knowledge of the auxiliary domain is effective in solving the classification problem of small sample datasets. Based on prior knowledge of FC analysis, TLNN classification may assist ADHD diagnosis in a new way.

In vivo tracking of individual stem cells labeled with nanowire lasers using multimodality imaging.

Emerging cell-based regenerative medicine and stem cell therapies have drawn wide attention in medical research and clinical practice to treat tissue damage and numerous incurable diseases. In vivo observation of the distribution, migration, and development of the transplanted cells is important for both understanding the mechanism and evaluating the treatment efficacy and safety. However, tracking the 3D migration trajectories for individual therapeutic cells in clinically relevant pathological environments remains technically challenging. Using a laser photocoagulation model in living rabbit eyes, this study demonstrates a multimodality imaging technology integrating optical coherence tomography (OCT), fluorescence microscopy (FM), and lasing emission for in vivo longitudinal tracking of the 3D migration trajectories of individual human retinal pigment epithelium cells (ARPE-19) labeled with CdS nanowires. With unique lasing spectra generated from the subtle microcavity differences, the surface-modified nanowires perform as distinct spectral identifiers for labeling individual ARPE-19 cells. Meanwhile, with strong optical scattering and natural fluorescence emission, CdS nanowires also served as OCT and FM contrast agents to indicate the spatial locations of the transplanted ARPE-19 cells. A longitudinal study of tracking individual ARPE-19 cells in rabbit eyes over a duration of 28 days was accomplished. This method could potentially promote an understanding of the pharmacodynamics and pharmacokinetics of implanted cells in the development of cell-based therapies.

Measuring variability of local brain volume using improved volume preserved warping.

Measuring local brain volume is clinically important in neuroimaging studies. Voxel preserved warping (VPW) and Jacobian determinant are effective methods for studying local brain volume changes and variations (LBVCV) across multiple brains. However, these LBVCV methods typically depend on the local deformation without using the global deformation, while both deformations are needed in co-registering the brains under examination so that the brains can be compared on a common and fair basis. However, instead of employing a uniformed strategy, different co-registration methods have developed their own unique strategy in performing global and local transformation of the co-registration of the brains, and how the global and local transformations may combine to achieve the final goal of co-registration is not their concern, as long as the final registration may accomplish the co-registering job satisfactorily. The aforementioned inconsistency thus makes the LBVCV measurement that relies on the registration methods for studying local brain volumes totally unstable and actually unreliable. To address the uncertainty in measuring local brain volume variability caused by the un-uniqueness of performing global and local deformations during co-registration, the present study proposes new VPW approaches (VPWα and VPWß), which no longer require the separation of the global and local transformation components but employ only the general deformation concatenating both components, as long as the general registration may achieve the task of co-registering brain images. The new VPW methods are validated in theory and in practice, using both simulated and real-world imaging data, respectively, based on two registration methods popularly in use by the neuroimaging research community, i.e., the Automatic Registration Toolbox (ART) and Symmetric Image Normalization Method (SyN) registration methods. Experiments using simulated data demonstrated that the proposed new VPW methods may reliably measure local brain volume changes and variability. In contrast, traditional methods typically may result in LBVCV maps containing significantly inconsistent even false findings. In the experiments using real neuroimaging datasets from a schizophrenia study, the results based on the proposed new VPW methods were highly consistent, no matter which registration method was employed. Otherwise, the LBVCV results based on traditional approaches would show significant difference, depending on the individual registration method that the analysis employed. LBVCV assessments based on traditional methods appear to be unreliable. The proposed new VPW methods for measuring local volume changes is independent of registration methods, and therefore can serve as alternative approaches for assessing LBVCV reliably.

Optical coherence tomography and fluorescence microscopy dual-modality imaging for in vivo single-cell tracking with nanowire lasers.

Emerging cell-based therapies such as stem cell therapy and immunotherapy have attracted broad attention in both biological research and clinical practice. However, a long-standing technical gap of cell-based therapies is the difficulty of directly assessing treatment efficacy via tracking therapeutically administered cells. Therefore, imaging techniques to follow the in vivo distribution and migration of cells are greatly needed. Optical coherence tomography (OCT) is a clinically available imaging technology with ultrahigh-resolution and excellent imaging depth. It also shows great potential for in vivo cellular imaging. However, due to the homogeneity of current OCT cell labeling contrast agents (such as gold and polymer nanoparticles), only the distribution of entire cell populations can be observed. Precise tracking of the trajectory of individual single cells is not possible with such conventional contrast agents. Microlasers may provide a route to track unique cell identifiers given their small size, high emission intensities, rich emission spectra, and narrow linewidths. Here, we demonstrate that nanowire lasers internalized by cells provide both OCT and fluorescence signal. In addition, cells can be individually identified by the unique lasing emission spectra of the nanowires that they carry. Furthermore, single cell migration trajectories can be monitored both in vitro and in vivo with OCT and fluorescence microscopy dual-modality imaging system. Our study demonstrates the feasibility of nanowire lasers combined with the dual-modality imaging system for in vivo single cell tracking with a high spatial resolution and identity verification, an approach with great utility for stem cell and immunomodulatory therapies.

Rapid and quantitative detection of SARS-CoV-2 specific IgG for convalescent serum evaluation.

Convalescent serum with a high abundance of neutralization IgG is a promising therapeutic agent for rescuing COVID-19 patients in the critical stage. Knowing the concentration of SARS-CoV-2 S1-specific IgG is crucial in selecting appropriate convalescent serum donors. Here, we present a portable microfluidic ELISA technology for rapid (15 min), quantitative, and sensitive detection of anti-SARS-CoV-2 S1 IgG in human serum with only 8 µL sample volume. We first identified a humanized monoclonal IgG that has a high binding affinity and a relatively high specificity towards SARS-CoV-2 S1 protein, which can subsequently serve as the calibration standard of anti-SARS-CoV-2 S1 IgG in serological analyses. We then measured the abundance of anti-SARS-CoV-2 S1 IgG in 16 convalescent COVID-19 patients. Due to the availability of the calibration standard and the large dynamic range of our assay, we were able to identify "qualified donors" for convalescent serum therapy with only one fixed dilution factor (200 ×). Finally, we demonstrated that our technology can sensitively detect SARS-CoV-2 antigens (S1 and N proteins) with pg/mL level sensitivities in 40 min. Overall, our technology can greatly facilitate rapid, sensitive, and quantitative analysis of COVID-19 related markers for therapeutic, diagnostic, epidemiologic, and prognostic purposes.

The Effect of Auditory Verbal Hallucinations on the Relationship between Spontaneous Brain Activity and intraventricular Brain Temperature in Patients with Drug-Naïve Schizophrenia.

Our recent study reported that adolescent-onset schizophrenia showed an uncoupling between intraventricular brain temperature (iBT) and local spontaneous brain activity (SBA). While auditory verbal hallucinations (AVH) are common in schizophrenia, the role of AVH in the iBT-SBA relationship is unclear. The current study recruited 24 drug-naïve schizophrenia patients with AVH, 20 patients without AVH and 30 matched healthy controls (HC). We used a diffusion-weighted imaging (DWI) based thermometry method to calculate the iBT for each participant and used both regional homogeneity and amplitude of low-frequency fluctuation methods to assess the SBA. One-way ANOVA was used to detect group differences in iBT, and a partial correlation analysis controlling for lateral ventricles volume, sex and age was applied to detect the relationships between iBT and SBA across the three groups. The results demonstrated that the AVH group showed a significant coupling between iBT and SBA in the bilateral lingual gyrus, left superior occipital gyrus and caudate compared with the other two groups, and no uncoupling was found in the two patients groups relative to HCs. These findings suggest that AVH may modulate the relationship between iBT and SBA in schizophrenia-related regions.

Fast and Reproducible ELISA Laser Platform for Ultrasensitive Protein Quantification.

Optofluidic lasers are currently of high interest for sensitive intracavity biochemical analysis. In comparison with conventional methods such as fluorescence and colorimetric detection, optofluidic lasers provide a method for amplifying small concentration differences in the gain medium, thus achieving high sensitivity. Here, we report the development of an on-chip ELISA (enzyme-linked immunosorbent assay) laser platform that is able to complete an assay in a short amount of time with small sample/reagent volumes, large dynamic range, and high sensitivity. The arrayed microscale reaction wells in the ELISA lasers can be microfabricated directly on dielectric mirrors, thus significantly improving the quality of the reaction wells and detection reproducibility. The details of the fabrication and characterization of those reaction wells on the mirror are described and the ELISA laser assay protocols are developed. Finally, we applied the ELISA laser to detecting IL-6, showing that a detection limit of about 0.1 pg/mL can be achieved in 1.5 h with 15 µL of sample/reagents per well. This work pushes the ELISA laser a step closer to solving problems in real-world biochemical analysis.

Altered coupling of spontaneous brain activities and brain temperature in patients with adolescent-onset, first-episode, drug-naïve schizophrenia.

PURPOSE: A recent study has reported that schizophrenia patients show an uncoupled association between intraventricular brain temperature (BT) and cerebral blood flow (CBF). CBF has been found to be closely coupled with spontaneous brain activities (SBAs) derived from resting-state BOLD fMRI metrics. Yet, it is unclear so far whether the relationship between the intraventricular BT and the SBAs may change in patients with adolescent-onset schizophrenia (AOS) compared with that in healthy controls (HCs). METHODS: The present study recruited 28 first-episode, drug-naïve AOS patients and 22 matched HCs. We measured the temperature of the lateral ventricles (LV) using diffusion-weighted imaging thermometry and measured SBAs using both regional homogeneity and amplitude of low-frequency fluctuation methods. A nonparametric Wilcoxon rank sum test was used to detect the difference in intraventricular BT between AOS patients and HCs with LV volume, age, and sex as covariates. We also evaluated the relationship between the intraventricular BT and the SBAs using partial correlation analysis controlling for LV volume, age, and sex. RESULTS: We found that HCs showed a significant negative correlation between the intraventricular BT and the local SBAs in the bilateral putamina and left superior temporal gyrus, while such a correlation was absent in AOS patients. Additionally, no significant difference between the two groups was found in the intraventricular BT. CONCLUSION: These findings suggest that AOS patients may experience an uncoupling between intraventricular BT and SBAs in several schizophrenia-related brain areas, which may be associated with the altered relationships among intraventricular BT, CBF, and metabolism.

A diffusion tensor imaging study of brain microstructural changes related to religion and spirituality in families at high risk for depression.

INTRODUCTION: Previously in a three-generation study of families at high risk for depression, we found that belief in the importance of religion/spirituality (R/S) was associated with thicker cortex in bilateral parietal and occipital regions. In the same sample using functional magnetic resonance imaging and electroencephalograph (EEG), we found that offspring at high familial risk had thinner cortices, increased default mode network connectivity, and reduced EEG power. These group differences were significantly diminished in offspring at high risk who reported high importance of R/S beliefs, suggesting a protective effect. METHODS: This study extends previous work examining brain microstructural differences associated with risk for major depressive disorder (MDD) and tests whether these are normalized in at-risk offspring who report high importance of R/S beliefs. Diffusion tensor imaging (DTI) data were selected from 99 2nd and 3rd generation offspring of 1st generation depressed (high-risk, HR) or nondepressed (low-risk, LR) parents. Whole-brain and region-of-interest analyses were performed, using ellipsoidal area ratio (EAR, an alternative diffusion anisotropy index comparable to fractional anisotropy). We examined microstructural differences associated with familial risk for depression within the groups of high and low importance of R/S beliefs (HI, LI). RESULTS: In the LI group, HR individuals showed significantly decreased EAR in white matter regions neighboring the precuneus, superior parietal lobe, superior and middle frontal gyrus, and bilateral insula, supplementary motor area, and postcentral gyrus. In the HI group, HR individuals showed reduced EAR in white matter surrounding the left superior, and middle frontal gyrus, left superior parietal lobule, and right supplementary motor area. Microstructural differences associated with familial risk for depression in precuneus, frontal lobe, and temporal lobe were nonsignificant or less significant in the HI group. CONCLUSION: R/S beliefs may affect microstructure in brain regions associated with R/S, potentially conferring resilience to depression among HR individuals.

Altered Effective Connectivity in the Default Network of the Brains of First-Episode, Drug-Naïve Schizophrenia Patients With Auditory Verbal Hallucinations.

Although the default mode network (DMN) is known to be abnormal in schizophrenia (SZ) patients with auditory verbal hallucinations (AVHs), it is still unclear whether AVHs that occur in SZ are associated with certain information flow in the DMN. This study collected resting-state functional magnetic resonance imaging data from 28 first-episode, drug-naïve SZ patients with AVHs, 20 SZ patients without AVHs, and 38 healthy controls. We used Granger causality analysis (GCA) to examine effective connectivity (EC) of two hub regions [posterior cingulate cortex (PCC) and anteromedial prefrontal cortex (aMPFC)] within the DMN. We used two-sample t-tests to compare the difference in EC between the two patient groups, and used Spearman correlation analysis to characterize the relationship between imaging findings and clinical assessments. The GCA revealed that, compared with the non-AVHs group, EC decreased from aMPFC to left inferior temporal gyrus (ITG) and from PCC to left cerebellum posterior lobe, ITG, and right middle frontal gyrus in SZ patients with AVHs. We also found significant correlations between clinical assessments and mean strengths of connectivity from aMPFC to left ITG and from PCC to left ITG. Moreover, receiver operating characteristic analysis revealed that the above-mentioned effective connectivities had a diagnostic value for distinguishing SZ patients with AVHs from non-AVHs patients. These findings suggest that AVHs in SZ patients may be associated with the aberrant information flows of the DMN, and the left ITG may probably serve as a potential biomarker for the neural mechanisms underlying AVHs in SZ patients.

Label-free and real-time monitoring of single cell attachment on template-stripped plasmonic nano-holes.

Leveraging microfluidics and nano-plasmonics, we present in this paper a new method employing a micro-nano-device that is capable of monitoring the dynamic cell-substrate attachment process at single cell level in real time without labeling. The micro-nano-device essentially has a gold thin film as the substrate perforated with periodic, near-cm2-area, template-stripped nano-holes, which generate plasmonic extraordinary optical transmission (EOT) with a high sensitivity to refractive index changes at the metal-dielectric interface. Using this device, we successfully demonstrated label-free and real-time monitoring of the dynamic cell attachment process for single mouse embryonic stem cell (C3H10) and human tumor cell (HeLa) by collecting EOT spectrum data during 3-hour on-chip culture. We further collected the EOT spectral shift data at the start and end points of measurement during 3-hour on-chip culture for 50 C3H10 and 50 HeLa cells, respectively. The experiment results show that the single cell attachment process of both HeLa and C3H10 cells follow the logistic retarded growth model, but with different kinetic parameters. Variations in spectral shift during the same culture period across single cells present new evidence for cell heterogeneity. The micro-nano-device provides a new, label-free, real-time, and sensitive, platform to investigate the cell adhesion kinetics at single cell level.

Deducing magnetic resonance neuroimages based on knowledge from samples.

PURPOSE: Because individual variance always exists, using the same set of predetermined parameters for magnetic resonance imaging (MRI) may not be exactly suitable for each participant. We propose a knowledge-based method that can repair MRI data of undesired contrast as if a new scan were acquired using imaging parameters that had been individually optimized. METHODS: The method employed a strategy called analogical reasoning to deduce voxel-wise relaxation properties using morphological and biological similarity. The proposed framework involves steps of intensity normalization, tissue segmentation, relaxation time deducing, and image deducing. RESULTS: This approach has been preliminarily validated using conventional MRI data at 3T from several examples, including 5 normal and 9 clinical datasets. It can effectively improve the contrast of real MRI data by deducing imaging data using optimized imaging parameters based on deduced relaxation properties. The statistics of deduced images shows a high correlation with real data that were actually collected using the same set of imaging parameters. CONCLUSION: The proposed method of deducing MRI data using knowledge of relaxation times alternatively provides a way of repairing MRI data of less optimal contrast. The method is also capable of optimizing an MRI protocol for individual participants, thereby realizing personalized MR imaging.

Altered Spontaneous Activity in Patients with Persistent Somatoform Pain Disorder Revealed by Regional Homogeneity.

Persistent somatoform pain disorder (PSPD) is a mental disorder un-associated with any somatic injury and can cause severe somatosensory and emotional impairments in patients. However, so far, the neuro-pathophysiological mechanism of the functional impairments in PSPD is still unclear. The present study assesses the difference in regional spontaneous activity between PSPD and healthy controls (HC) during a resting state, in order to elucidate the neural mechanisms underlying PSPD. Resting-state functional Magnetic Resonance Imaging data were obtained from 13 PSPD patients and 23 age- and gender-matched HC subjects in this study. Kendall's coefficient of concordance was used to measure regional homogeneity (ReHo), and a two-sample t-test was subsequently performed to investigate the ReHo difference between PSPD and HC. Additionally, the correlations between the mean ReHo of each survived area and the clinical assessments were further analyzed. Compared with the HC group, patients with PSPD exhibited decreased ReHo in the bilateral primary somatosensory cortex, posterior cerebellum, and occipital lobe, while increased ReHo in the prefrontal cortex (PFC) and default mode network (including the medial PFC, right inferior parietal lobe (IPL), and left supramarginal gyrus). In addition, significant positive correlations were found between the mean ReHo of both right IPL and left supramarginal gyrus and participants' Self-Rating Anxiety Scale (SAS) scores, and between the mean ReHo of the left middle frontal gyrus and Visual Analogue Scale (VAS) scores. Our results suggest that abnormal spontaneous brain activity in specific brain regions during a resting state may be associated with the dysfunctions in pain, memory and emotional processing commonly observed in patients with PSPD. These findings help us to understand the neural mechanisms underlying PSPD and suggest that the ReHo metric could be used as a clinical marker for PSPD.

Study of a Microfluidic Chip Integrating Single Cell Trap and 3D Stable Rotation Manipulation.

Single cell manipulation technology has been widely applied in biological fields, such as cell injection/enucleation, cell physiological measurement, and cell imaging. Recently, a biochip platform with a novel configuration of electrodes for cell 3D rotation has been successfully developed by generating rotating electric fields. However, the rotation platform still has two major shortcomings that need to be improved. The primary problem is that there is no on-chip module to facilitate the placement of a single cell into the rotation chamber, which causes very low efficiency in experiment to manually pipette single 10-micron-scale cells into rotation position. Secondly, the cell in the chamber may suffer from unstable rotation, which includes gravity-induced sinking down to the chamber bottom or electric-force-induced on-plane movement. To solve the two problems, in this paper we propose a new microfluidic chip with manipulation capabilities of single cell trap and single cell 3D stable rotation, both on one chip. The new microfluidic chip consists of two parts. The top capture part is based on the least flow resistance principle and is used to capture a single cell and to transport it to the rotation chamber. The bottom rotation part is based on dielectrophoresis (DEP) and is used to 3D rotate the single cell in the rotation chamber with enhanced stability. The two parts are aligned and bonded together to form closed channels for microfluidic handling. Using COMSOL simulation and preliminary experiments, we have verified, in principle, the concept of on-chip single cell traps and 3D stable rotation, and identified key parameters for chip structures, microfluidic handling, and electrode configurations. The work has laid a solid foundation for on-going chip fabrication and experiment validation.

Automated assessment of the quality of diffusion tensor imaging data using color cast of color-encoded fractional anisotropy images.

Diffusion tensor imaging (DTI) data often suffer from artifacts caused by motion. These artifacts are especially severe in DTI data from infants, and implementing tight quality controls is therefore imperative for DTI studies of infants. Currently, routine procedures for quality assurance of DTI data involve the slice-wise visual inspection of color-encoded, fractional anisotropy (CFA) images. Such procedures often yield inconsistent results across different data sets, across different operators who are examining those data sets, and sometimes even across time when the same operator inspects the same data set on two different occasions. We propose a more consistent, reliable, and effective method to evaluate the quality of CFA images automatically using their color cast, which is calculated on the distribution statistics of the 2D histogram in the color space as defined by the International Commission on Illumination (CIE) on lightness and a and b (LAB) for the color-opponent dimensions (also known as the CIELAB color space) of the images. Experimental results using DTI data acquired from neonates verified that this proposed method is rapid and accurate. The method thus provides a new tool for real-time quality assurance for DTI data.