Prediction of anxious depression using multimodal neuroimaging and machine learning.

Anxious depression is a common subtype of major depressive disorder (MDD) associated with adverse outcomes and severely impaired social function. It is important to clarify the underlying neurobiology of anxious depression to refine the diagnosis and stratify patients for therapy. Here we explored associations between anxiety and brain structure/function in MDD patients. A total of 260 MDD patients and 127 healthy controls underwent three-dimensional T1-weighted structural scanning and resting-state functional magnetic resonance imaging. Demographic data were collected from all participants. Differences in gray matter volume (GMV), (fractional) amplitude of low-frequency fluctuation ((f)ALFF), regional homogeneity (ReHo), and seed point-based functional connectivity were compared between anxious MDD patients, non-anxious MDD patients, and healthy controls. A random forest model was used to predict anxiety in MDD patients using neuroimaging features. Anxious MDD patients showed significant differences in GMV in the left middle temporal gyrus and ReHo in the right superior parietal gyrus and the left precuneus than HCs. Compared with non-anxious MDD patients, patients with anxious MDD showed significantly different GMV in the left inferior temporal gyrus, left superior temporal gyrus, left superior frontal gyrus (orbital part), and left dorsolateral superior frontal gyrus; fALFF in the left middle temporal gyrus; ReHo in the inferior temporal gyrus and the superior frontal gyrus (orbital part); and functional connectivity between the left superior temporal gyrus(temporal pole) and left medial superior frontal gyrus. A diagnostic predictive random forest model built using imaging features and validated by 10-fold cross-validation distinguished anxious from non-anxious MDD with an AUC of 0.802. Patients with anxious depression exhibit dysregulation of brain regions associated with emotion regulation, cognition, and decision-making, and our diagnostic model paves the way for more accurate, objective clinical diagnosis of anxious depression.

Deep Learning Model for Grading and Localization of Lumbar Disc Herniation on Magnetic Resonance Imaging.

BACKGROUND: Methods for grading and localization of lumbar disc herniation (LDH) on MRI are complex, time-consuming, and subjective. Utilizing deep learning (DL) models as assistance would mitigate such complexities. PURPOSE: To develop an interpretable DL model capable of grading and localizing LDH. STUDY TYPE: Retrospective. SUBJECTS: 1496 patients (M/F: 783/713) were evaluated, and randomly divided into training (70%), validation (10%), and test (20%) sets. FIELD STRENGTH/SEQUENCE: 1.5T MRI for axial T2-weighted sequences (spin echo). ASSESSMENT: The training set was annotated by three spinal surgeons using the Michigan State University classification to train the DL model. The test set was annotated by a spinal surgery expert (as ground truth labels), and two spinal surgeons (comparison with the trained model). An external test set was employed to evaluate the generalizability of the DL model. STATISTICAL TESTS: Calculated intersection over union (IoU) for detection consistency, utilized Gwet's AC1 to assess interobserver agreement, and evaluated model performance based on sensitivity and specificity, with statistical significance set at P < 0.05. RESULTS: The DL model achieved high detection consistency in both the internal test dataset (grading: mean IoU 0.84, recall 99.6%; localization: IoU 0.82, recall 99.5%) and external test dataset (grading: 0.72, 98.0%; localization: 0.71, 97.6%). For internal testing, the DL model (grading: 0.81; localization: 0.76), Rater 1 (0.88; 0.82), and Rater 2 (0.86; 0.83) demonstrated results highly consistent with the ground truth labels. The overall sensitivity of the DL model was 87.0% for grading and 84.0% for localization, while the specificity was 95.5% and 94.4%. For external testing, the DL model showed an appreciable decrease in consistency (grading: 0.69; localization: 0.66), sensitivity (77.2%; 76.7%), and specificity (92.3%; 91.8%). DATA CONCLUSION: The classification capabilities of the DL model closely resemble those of spinal surgeons. For future improvement, enriching the diversity of cases could enhance the model's generalization. TECHNICAL EFFICACY: Stage 2.

Portrait stylized rendering for 3D light-field display based on radiation field and example guide.

With the development of three-dimensional (3D) light-field display technology, 3D scenes with correct location information and depth information can be perceived without wearing any external device. Only 2D stylized portrait images can be generated with traditional portrait stylization methods and it is difficult to produce high-quality stylized portrait content for 3D light-field displays. 3D light-field displays require the generation of content with accurate depth and spatial information, which is not achievable with 2D images alone. New and innovative portrait stylization techniques methods should be presented to meet the requirements of 3D light-field displays. A portrait stylization method for 3D light-field displays is proposed, which maintain the consistency of dense views in light-field display when the 3D stylized portrait is generated. Example-based portrait stylization method is used to migrate the designated style image to the portrait image, which can prevent the loss of contour information in 3D light-field portraits. To minimize the diversity in color information and further constrain the contour details of portraits, the Laplacian loss function is introduced in the pre-trained deep learning model. The three-dimensional representation of the stylized portrait scene is reconstructed, and the stylized 3D light field image of the portrait is generated the mask guide based light-field coding method. Experimental results demonstrate the effectiveness of the proposed method, which can use the real portrait photos to generate high quality 3D light-field portrait content.

Hyper-inflammation of astrocytes in patients of major depressive disorder: Evidence from serum astrocyte-derived extracellular vesicles.

Astrocyte-derived extracellular vesicles (ADEs) allow the in vivo probing of the inflammatory status of astrocytes practical. Serum sample and ADEs were used to test the inflammatory hypothesis in 70 patients with major depressive disorder (MDD) and 70 matched healthy controls (HCs). In serum, tumor necrosis factor α (TNF-α) and interleukin (IL)-17A were significantly increased, where as IL-12p70 was significantly reduced in the MDD patients compared with HCs. In ADEs, all inflammatory markers (Interferon-γ, IL-12p70, IL-1ß, IL-2, IL-4, IL-6, TNF-α, and IL-17A) except IL-10 were significantly increased in the MDD patients, the Hedge's g values of elevated inflammatory markers varied from 0.48 to 1.07. However, there were no differences of all inflammatory markers whether in serum or ADEs between MDD-drug free and medicated subgroups. The association of inflammatory biomarkers between ADEs and serum did not reach statistically significance after multi-comparison correction neither in the HCs nor MDD patients. The spearman coefficients between inflammatory factors and clinical characteristics in the MDD patients, such as onset age, disease course, current episode duration, and severity of depression, were nonsignificant after multi-comparison correction. In the receiver operating characteristic curves analysis, the corrected partial area under the curve (pAUC) of each inflammatory markers in ADEs ranged from 0.522 to 0.696, and the combination of these inflammatory factors achieved a high pAUC (>0.9). Our findings support the inflammatory glial hypothesis of depression, and suggests that in human ADEs could be a useful tool to probe the in vivo astrocyte status.

Human in vivo evidence of reduced astrocyte activation and neuroinflammation in patients with treatment-resistant depression following electroconvulsive therapy.

AIM: The current study aimed to investigate the neuroinflammatory hypothesis of depression and the potential anti-inflammatory effect of electroconvulsive therapy (ECT) in vivo, utilizing astrocyte-derived extracellular vesicles (ADEVs) isolated from plasma. METHODS: A total of 40 patients with treatment-resistant depression (TRD) and 35 matched healthy controls were recruited at baseline, and 34 patients with TRD completed the post-ECT visits. Blood samples were collected at baseline and post-ECT. Plasma ADEVs were isolated and confirmed, and the concentrations of two astrocyte markers (glial fibrillary acidic protein [GFAP] and S100ß), an extracellular vesicle marker cluster of differentiation 81 (CD81), and nine inflammatory markers in ADEVs were measured as main analyses. In addition, correlation analysis was conducted between clinical features and ADEV protein levels as exploratory analysis. RESULTS: At baseline, the TRD group exhibited significantly higher levels of two astrocyte markers GFAP and S100ß, as well as CD81 compared with the healthy controls. Inflammatory markers interferon γ (IFN-γ), interleukin (IL) 1ß, IL-4, IL-6, tumor necrosis factor α, IL-10, and IL-17A were also significantly higher in the TRD group. After ECT, there was a significant reduction in the levels of GFAP, S100ß, and CD81, along with a significant decrease in the levels of IFN-γ and IL-4. Furthermore, higher levels of GFAP, S100ß, CD81, and inflammatory cytokines were associated with more severe depressive symptoms and poorer cognitive function. CONCLUSION: This study provides direct insight supporting the astrocyte activation and neuroinflammatory hypothesis of depression using ADEVs. ECT may exert an anti-inflammatory effect through inhibition of such activation of astrocytes.

Nicotinamide reverses deficits in puberty-born neurons and cognitive function after maternal separation.

BACKGROUND: Early life stress (ELS) is associated with the development of schizophrenia later in life. The hippocampus develops significantly during childhood and is extremely reactive to stress. In rodent models, ELS can induce neuroinflammation, hippocampal neuronal loss, and schizophrenia-like behavior. While nicotinamide (NAM) can inhibit microglial inflammation, it is unknown whether NAM treatment during adolescence reduces hippocampal neuronal loss and abnormal behaviors induced by ELS. METHODS: Twenty-four hours of maternal separation (MS) of Wistar rat pups on post-natal day (PND)9 was used as an ELS. On PND35, animals received a single intraperitoneal injection of BrdU to label dividing neurons and were given NAM from PND35 to PND65. Behavioral testing was performed. Western blotting and immunofluorescence staining were used to detect nicotinamide adenine dinucleotide (NAD+)/Sirtuin3 (Sirt3)/superoxide dismutase 2 (SOD2) pathway-related proteins. RESULTS: Compared with controls, only MS animals in the adult stage (PND56-65) but not the adolescent stage (PND31-40) exhibited pre-pulse inhibition deficits and cognitive impairments mimicking schizophrenia symptoms. MS decreased the survival and activity of puberty-born neurons and hippocampal NAD+ and Sirt3 expression in adulthood. These observations were related to an increase in acetylated SOD2, microglial activation, and significant increases in pro-inflammatory IL-1ß, TNF-α, and IL-6 expression. All the effects of MS at PND9 were reversed by administering NAM in adolescence (PND35-65). CONCLUSIONS: MS may lead to schizophrenia-like phenotypes and persistent hippocampal abnormalities. NAM may be a safe and effective treatment in adolescence to restore normal hippocampal function and prevent or ameliorate schizophrenia-like behavior.

3D light-field display with an increased viewing angle and optimized viewpoint distribution based on a ladder compound lenticular lens unit.

Three-dimensional (3D) light-field displays (LFDs) suffer from a narrow viewing angle, limited depth range, and low spatial information capacity, which limit their diversified application. Because the number of pixels used to construct 3D spatial information is limited, increasing the viewing angle reduces the viewpoint density, which degrades the 3D performance. A solution based on a holographic functional screen (HFS) and a ladder-compound lenticular lens unit (LC-LLU) is proposed to increase the viewing angle while optimizing the viewpoint utilization. The LC-LLU and HFS are used to create 160 non-uniformly distributed viewpoints with low crosstalk, which increases the viewpoint density in the middle viewing zone and provides clear monocular depth cues. The corresponding coding method is presented as well. The optimized compound lenticular lens array can balance between suppressing aberration and improving displayed quality. The simulations and experiments show that the proposed 3D LFD can present natural 3D images with the right perception and occlusion relationship within a 65° viewing angle.

Analysis and removal of crosstalk in a time-multiplexed light-field display.

Time-multiplexed light-field displays (TMLFDs) can provide natural and realistic three-dimensional (3D) performance with a wide 120° viewing angle, which provides broad potential applications in 3D electronic sand table (EST) technology. However, current TMLFDs suffer from severe crosstalk, which can lead to image aliasing and the distortion of the depth information. In this paper, the mechanisms underlying the emergence of crosstalk in TMLFD systems are identified and analyzed. The results indicate that the specific structure of the slanted lenticular lens array (LLA) and the non-uniformity of the emergent light distribution in the lens elements are the two main factors responsible for the crosstalk. In order to produce clear depth perception and improve the image quality, a novel ladder-type LCD sub-pixel arrangement and a compound lens with three aspheric surfaces are proposed and introduced into a TMLFD to respectively reduce the two types of crosstalk. Crosstalk simulation experiments demonstrate the validity of the proposed methods. Structural similarity (SSIM) simulation experiments and light-field reconstruction experiments also indicate that aliasing is effectively reduced and the depth quality is significantly improved over the entire viewing range. In addition, a tabletop 3D EST based on the proposed TMLFD is presented. The proposed approaches to crosstalk reduction are also compatible with other lenticular lens-based 3D displays.

Shotgun metagenomics reveals both taxonomic and tryptophan pathway differences of gut microbiota in major depressive disorder patients.

BACKGROUND: The microbiota-gut-brain axis, especially the microbial tryptophan (Trp) biosynthesis and metabolism pathway (MiTBamp), may play a critical role in the pathogenesis of major depressive disorder (MDD). However, studies on the MiTBamp in MDD are lacking. The aim of the present study was to analyze the gut microbiota composition and the MiTBamp in MDD patients. METHODS: We performed shotgun metagenomic sequencing of stool samples from 26 MDD patients and 29 healthy controls (HCs). In addition to the microbiota community and the MiTBamp analyses, we also built a classification based on the Random Forests (RF) and Boruta algorithm to identify the gut microbiota as biomarkers for MDD. RESULTS: The Bacteroidetes abundance was strongly reduced whereas that of Actinobacteria was significantly increased in the MDD patients compared with the abundance in the HCs. Most noteworthy, the MDD patients had increased levels of Bifidobacterium, which is commonly used as a probiotic. Four Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologies (KOs) (K01817, K11358, K01626, K01667) abundances in the MiTBamp were significantly lower in the MDD group. Furthermore, we found a negative correlation between the K01626 abundance and the HAMD scores in the MDD group. Finally, RF classification at the genus level can achieve an area under the receiver operating characteristic curve of 0.890. CONCLUSIONS: The present findings enabled a better understanding of the changes in gut microbiota and the related Trp pathway in MDD. Alterations of the gut microbiota may have the potential as biomarkers for distinguishing MDD patients form HCs.

The prevalence and independent influencing factors of obesity and underweight in patients with schizophrenia: a multicentre cross-sectional study.

BACKGROUND: Few studies have investigated the weight of patients with schizophrenia in China. OBJECTIVE: The aim of this study was to analyse the prevalence, clinical characteristics and influencing factors of obesity and underweight in patients with chronic schizophrenia in China. METHODS: A total of 325 patients with schizophrenia and 172 sex- and age-matched healthy controls from the community were recruited. Socio-demographic data and laboratory measurements were collected for all subjects. Using the Positive and Negative Syndrome Scale (PANSS), we evaluated the psychiatric symptoms of patients with schizophrenia. According to the body mass index (BMI) criteria in China, BMI ≥ 28 kg/m2 indicates obesity, and BMI < 18.5 kg/m2 indicates underweight. RESULTS: Of the patients with schizophrenia, 16.3% were obese, and 6.8% were underweight; 11.0% of the healthy controls were obese, and 3.5% were underweight. There was no difference between the two groups in the prevalence of obesity and underweight. After controlling for relevant variables, the obesity rate remained non significant, but the underweight rate appeared to be different. The multinomial regression analysis revealed that among the patients with schizophrenia, female sex, triglyceride level and LDL level were independent risk factors for obesity and that HDL level was an independent protective factor against obesity. In contrast, male sex and HDL level were independent risk factors for underweight. CONCLUSION: We found that the patients with schizophrenia had an increased rate of underweight and some factors related to weight. LEVEL OF EVIDENCE: Level V, descriptive study.

Short-term effects of air pollution on cause-specific mental disorders in three subtropical Chinese cities.

BACKGROUND: The effects of ambient air pollution on specific mental disorders are rarely studied, and the reported results are inconsistent. OBJECTIVE: To assess the short-term effect of ambient air pollution on the morbidity of mental disorders in three subtropical Chinese cities. METHODS: Daily concentrations of air pollution were averaged from 19 fixed monitoring stations across each city, and data on patients were collected from three psychiatric specialty hospitals. A time-series study combined with a generalized additive Poisson model was conducted to investigate the association between air pollution and mental disorders. The exposure-response relationships were explored and stratified analyses by age and sex were conducted. RESULTS: A total of 1,133,220 outpatient visits were recorded in three subtropical cities (Huizhou, Shenzhen, and Zhaoqing). The number of daily outpatient visits for mental disorders increased with higher air pollutant (PM2.5, PM10, SO2 and NO2) concentrations, and the effect of NO2 appeared to be consistently significant across the three cities, with excess risk (ER) of 4.45% (95% CI: 2.90%, 6.04%) in Huizhou, 7.94% (95% CI: 6.28%, 9.62%) in Shenzhen, and 2.19% (95% CI: 0.51%, 3.89%) in Zhaoqing, respectively, at lag03. We also observed significant effect of PM2.5 at lag0 (ER = 1.20%, 95% CI: 0.28%, 2.13%), PM10 at lag0 (ER = 0.99%, 95% CI: 0.36%, 1.62%), and SO2 at lag0 (ER = 10.74%, 95% CI: 3.20%, 18.84%) in Shenzhen. For specific mental disorders, significant associations were found in all the air pollutants except between SO2 and affective disorder and between PM2.5 and schizophrenia. In addition, we found that air pollution exhibited stronger effects for males and adults (≥18 years). CONCLUSION: Acute exposure to air pollution, especially NO2, might be an important trigger of mental disorders.

Study protocol for a parallel-group, double-blinded, randomized, controlled, noninferiority trial: the effect and safety of hybrid electroconvulsive therapy (Hybrid-ECT) compared with routine electroconvulsive therapy in patients with depression.

BACKGROUND: Electroconvulsive therapy (ECT) is the most rapid and effective treatment for patients with depression, ECT can achieve remarkable antidepressant effects in the initial 3-4 sessions, but significant side effects limit its use. However, recent low-charge electrotherapy (LCE) studies have demonstrated antidepressant or antipsychotic effects with significantly fewer side effects. The aim of this study is to propose a novel two-step charge set strategy for ECT treatment, referred to as Hybrid-ECT, to decrease side effects by using a low charge while preserving treatment efficacy. METHODS/DESIGN: A randomized, double-blinded, standard-controlled, parallel-group design will be carried out. We plan to enroll 112 inpatients diagnosed with depression (unipolar or bipolar) and randomly assign them to conventional ECT (control group) or to Hybrid-ECT (treatment group, 3 ECT sessions followed by LCE sessions (approximately 2.8 joules per session)). We will evaluate participants across a wide variety of domains including clinical symptoms, cognitive, psychological and functional metrics. We will also perform magnetic resonance imaging (MRI) and event-related potential (ERPs) assessments during treatment to explore brain function differences between ECT and LCE. DISCUSSION: This research proposes a simple but completely novel ECT strategy that aims to rapidly relieve depressive symptoms and minimize side effects. The mechanism of ECT and LCE will be further discussed. TRIAL REGISTRATION: Chinese Clinical Trial Registry, Number: ChiCTR1900022905 (Registration date: April 30, 2019).

Survival analysis of patients with spinal chordomas.

This study was aimed to analyze the survival of patients with spinal chordomas. Patients' data in the Surveillance, Epidemiology, and End Results (SEER) database were retrieved and analyzed statistically. There were 765 patients with spinal chordomas between 1974 and 2013. The overall survival did not improve significantly over decades for patients receiving surgery and radiotherapy (SR) (P = 0.221). There were significant differences in overall survival among subgroups of patients receiving surgery (S), radiotherapy (R), and neither S nor R (NSR) (P = 0.031, 0.037, and 0.031, respectively). Cancer-specific survival did not change significantly among subgroups of patients receiving R (P = 0.411), while it increased steadily among subgroups of patients receiving S, SR, and NSR (P < 0.001, 0.001, and 0.049, respectively). In the multivariate Cox regression model, younger onset age (hazard ratio [HR] 1.052, P < 0.001), surgery (HR 0.291, P = 0.001), and tumor location of the sacrum (HR 0.401, P = 0.002) were associated with a better overall survival. Similarly, younger onset age (HR 1.036, P = 0.029), surgery (HR 0.221, P = 0.009), and tumor location of the sacrum (HR 0.287, P = 0.002) were also associated with a higher cancer-specific survival. The changes in overall and cancer-specific survival over time differ among different treatment groups. Younger onset age, surgical strategy, and tumor location of the sacrum may be correlated with a higher overall and cancer-specific survival.

A cohort study comparing the serum levels of pro- or anti-inflammatory cytokines in patients with lumbar radicular pain and healthy subjects.

PURPOSE: The factors influencing the presence or absence of pain in sciatica secondary to disc herniation remain incompletely understood. We hypothesized that the imbalance in inflammatory cytokines is implicated in the generation of pain. In our study, serum levels of pro-inflammatory and anti-inflammatory cytokines were investigated among patients with severe sciatica; the serum levels were compared with those of patients with mild sciatica and healthy subjects. METHODS: In this prospective study, blood protein levels of the pro-inflammatory cytokines, namely, interleukin-6 (IL-6), interleukin-8 (IL-8),and tumor necrosis factor-α (TNF-α), and the anti-inflammatory cytokines, namely, interleukin-4 (IL-4) and interleukin-10 (IL-10), of 58 patients with severe sciatica, 50 patients with mild sciatica, and 30 healthy control subjects were analyzed through ELISA. Physical and mental health symptoms were determined using the Oswestry Disability Index (ODI) and short form-36 (SF-36) questionnaire. Spearman rank correlation coefficient was also determined to calculate the correlation between the scores obtained from the questionnaires and the serum levels of cytokines. RESULTS: IL-6 protein was detected in the three groups and median levels were about 1.5 times higher in patients with severe sciatica than the mild sciatica group (p = 0.02) and the controls (p = 0.03). Median levels of IL-8 in sciatica patients were higher than those of the healthy controls (p = 0.001 for severe sciatica, p = 0.02 for mild sciatica). The TNF-α protein values were approximately twofold higher in the severe sciatica group than in the mild sciatica group (p < 0.01) and in the healthy control group (p < 0.01). Median levels of IL-4 were about 2.5-fold higher in mild sciatica (p < 0.01) and about twofold higher in patients with severe sciatica (p = 0.012) when compared with controls. Median protein levels of IL-10 showed a trend to be higher in patients with mild sciatica compared with severe sciatica (p < 0.01) and with healthy controls (p < 0.01). ODI was significantly correlated with IL-6 (r = 0.394, p = 0.013), TNF-α (r = 0.629, p < 0.001), and IL-10 (r = -0.415, p = 0.009). ODI was not significantly correlated with IL-4 (r = -0.174, p = 0.29) and IL-8 (r = -0.133, p = 0.418). CONCLUSIONS: These findings support our hypothesis that sciatica pain is accompanied by the imbalance in inflammatory cytokines.

Evaluation of transforaminal endoscopic lumbar discectomy in the treatment of lumbar disc herniation.

PURPOSE: The purpose of this study was to evaluate the efficacy of transforaminal endoscopic lumbar discectomy (TELD) in the treatment of lumbar disc herniation (LDH) and to identify the relationship between TELD efficacy and age. METHODS: A total of 207 consecutive LDH patients who had undergone TELD with the THESSYS system from January 2013 to September 2014 were divided into two groups on the basis of their age, with 108 cases in the ≤ 45-year-old age group and 99 cases in the >45-year-old group. The Oswestry Disability Index (ODI) was used to quantify the pain relief. The degree of pain and disability were measured on the basis of the visual analog scale (VAS) and the modified MacNab criteria. Complications, duration of hospital stay, surgical costs, and operation time were recorded and compared between the two groups. Spearman's coefficient of rank correlation was used to assess the learning curves for TELD. RESULTS: The mean pre-operative and postoperative VAS and ODI scores significantly improved in both age ≤ 45 group and age >45 group, with no significant differences between them. In age ≤45 group, 56 % had excellent outcomes, 28 % good, 14 % fair, and 3 % poor. In the age >45 group, 51 % had excellent outcomes, 20 % good, 25 % fair, and 4 % poor. The average lengths of hospital stay for the age ≤ 45 group and age >45 group were 6.8 and 8.4 days, respectively. The mean time to return to work or normal activities was ten days for the age ≤ 45 group and 15 days for the age >45 group. The mean operative time for the age ≤ 45 group was 94 minutes and that for age >45 group was 97 minutes. The surgical cost of age ≤ 45 group was 15,480 RMB, which was lower than the 16,381 RMB of age >45 group. A total of 14 patients in the age ≤ 45 group and 13 patients in age >45 group used analgesic medications. Three and five recurrences were reported in the age ≤ 45 group and age >45, respectively. The steep learning curves of operative time plotted against the number of surgeries conducted suggest that the TELD technique can be mastered quickly in terms of reducing the duration of operation. CONCLUSIONS: The efficacy of TELD is relatively good for the selected young and elderly patients in this study. Therefore, age is not a predictor of TELD surgery-related outcomes.

Evaluation of intervertebral disc regeneration with implantation of bone marrow mesenchymal stem cells (BMSCs) using quantitative T2 mapping: a study in rabbits.

PURPOSE: The aim of the study was to investigate the curative effects of transplantation of bone marrow mesenchymal stem cells (BMSCs) on intervertebral disc regeneration and to investigate the feasibility of the quantitative T2 mapping method for evaluating repair of the nucleus pulposus after implantation of BMSCs. METHODS: Forty-eight New Zealand white rabbits were used to establish the lumber disc degenerative model by stabbing the annulus fibrosus and then randomly divided into four groups, i.e. two weeks afterwards, BMSCs or phosphate-buffered saline (PBS) were transplanted into degenerative discs (BMSCs group and PBS group), while the operated rabbits without implantation of BMSCs or PBS served as the sham group and the rabbits without operation were used as the control group. At weeks two, six and ten after operation, the T2 values and disc height indices (DHI) were calculated by magnetic resonance imaging (MRI 3.0 T), and the gene expressions of type II collagen (COL2) and aggrecan (ACAN) in degenerative discs were evaluated by real-time reverse transcription polymerase chain reaction (RT-PCR). T2 values for the nucleus pulposus were correlated with ACAN or COL2 expression by regression analysis. RESULTS: Cell clusters, disorganised fibres, interlamellar glycosaminoglycan (GAG) matrix and vascularisation were observed in lumber degenerative discs. BMSCs could be found to survive in intervertebral discs and differentiate into nucleus pulposus-like cells expressing COL2 and ACAN. The gene expression of COL2 and ACAN increased during ten weeks after transplantation as well as the T2 signal intensity and T2 value. The DHI in the BMSCs group decreased more slowly than that in PBS and sham groups. The T2 value correlated significantly with the gene expression of ACAN and COL2 in the nucleus pulposus. CONCLUSIONS: Transplantation of BMSCs was able to promote the regeneration of degenerative discs. Quantitative and non-invasive T2 mapping could be used to evaluate the regeneration of the nucleus pulposus with good sensitivity.

Study on Vertical Bearing Capacity of Pile Foundation with Distributed Geopolymer Post-Grouting on Pile Side.

To study the applicability of the new geopolymer grouting material for super-long and large-diameter post-grouting bored piles in silty fine sand geology, this paper compares the bearing capacity of two grouting materials, geopolymer and normal Portland cement, and different grouting volume pile side-distributed grouting piles in silty fine sand based on field model tests are analyzed through the diffusion forms of the two materials in silty fine sand through the morphology of the grouted body after excavation. The results show that the ultimate bearing capacities of P0 (ungrouted pile), P1 (8 kg cement grouted pile), P2 (6 kg geopolymer-grouted pile), P3 (8 kg geopolymer-grouted pile) and P4 (10 kg geopolymer-grouted pile) are 5400 N, 8820 N, 9450 N, 11,700 N and 12,600 N, respectively, and that the ultimate bearing capacity of the grouted pile is improved compared with that of the ungrouted pile since, under the same grouting amount, the maximum bearing capacity of the pile using geopolymer grouting is increased by 133% compared with that of the pile with cement grouting. This further verifies the applicability of the geopolymer grouting material for the post-grouting of the pile foundation in silty fine sand. Under the action of the ultimate load, the pile side friction resistance of P1, P2, P3 and P4 is increased by 200%, 218%, 284% and 319% compared with that of P0. In addition, the excavation results show that the geopolymer post-grouting pile forms the ellipsoidal consolidation body at the pile side grouting location, which mainly comprises extrusion diffusion with a small amount of infiltration diffusion, and the cement grouting pile forms a sheet-like consolidation body at the lower grouting location, which primarily comprises split diffusion. This study can provide a reference basis for the theoretical and engineering application of post-grouting piles using geopolymers.

Effects of autotaxin and lysophosphatidic acid deficiencies on depression-like behaviors in mice exposed to chronic unpredictable mild stress.

The involvement of lipids in the mechanism of depression has triggered extensive discussions. Earlier studies have identified diminished levels of lysophosphatidic acid (LPA) and autotaxin (ATX) in individuals experiencing depression. However, the exact significance of this phenomenon in relation to depression remains inconclusive. This study seeks to explore the deeper implications of these observations. We assessed alterations in ATX and LPA in both the control group and the chronic unpredictable mild stress (CUMS) model group. Additionally, the impact of ATX adeno-associated virus (AAV-ATX) injection into the hippocampus was validated through behavioral tests in CUMS-exposed mice. Furthermore, we probed the effects of LPA on synapse-associated proteins both in HT22 cells and within the mouse hippocampus. The mechanisms underpinning the LPA-triggered shifts in protein expression were further scrutinized. Hippocampal tissues were augmented with ATX to assess its potential to alleviate depression-like behavior by modulating synaptic-related proteins. Our findings suggest that the decrement in ATX and LPA levels alters the expression of proteins associated with synaptic plasticity in vitro and in vivo, such as synapsin-I (SYN), synaptophysin (SYP), and brain-derived neurotrophic factor (BDNF). Moreover, we discerned a role for the ERK/CREB signaling pathway in mediating the effects of ATX and LPA. Importantly, strategic supplementation of ATX effectively mitigated depression-like behaviors. This study indicates that the ATX-LPA pathway may influence depression-like behaviors by modulating synaptic plasticity in the brains of CUMS-exposed mice. These insights augment our understanding of depression's potential pathogenic mechanism in the context of lipid metabolism and propose promising therapeutic strategies for ameliorating the disease.

A Machine Learning Analysis of Big Metabolomics Data for Classifying Depression: Model Development and Validation.

BACKGROUND: Many metabolomics studies of depression have been performed, but these have been limited by their scale. A comprehensive in silico analysis of global metabolite levels in large populations could provide robust insights into the pathological mechanisms underlying depression and candidate clinical biomarkers. METHODS: Depression-associated metabolomics was studied in 2 datasets from the UK Biobank database: participants with lifetime depression (N = 123,459) and participants with current depression (N = 94,921). The Whitehall II cohort (N = 4744) was used for external validation. CatBoost machine learning was used for modeling, and Shapley additive explanations were used to interpret the model. Fivefold cross-validation was used to validate model performance, training the model on 3 of the 5 sets with the remaining 2 sets for validation and testing, respectively. Diagnostic performance was assessed using the area under the receiver operating characteristic curve. RESULTS: In the lifetime depression and current depression datasets and sex-specific analyses, 24 significantly associated metabolic biomarkers were identified, 12 of which overlapped in the 2 datasets. The addition of metabolic features slightly improved the performance of a diagnostic model using traditional (nonmetabolomics) risk factors alone (lifetime depression: area under the curve 0.655 vs. 0.658 with metabolomics; current depression: area under the curve 0.711 vs. 0.716 with metabolomics). CONCLUSIONS: The machine learning model identified 24 metabolic biomarkers associated with depression. If validated, metabolic biomarkers may have future clinical applications as supplementary information to guide early and population-based depression detection.