A chronic stress-induced microbiome perturbation, highly enriched in Ruminococcaceae_UCG-014, promotes colorectal cancer growth and metastasis.

Purpose: Mounting evidence indicates that psychological stress adversely affects cancer progression including tumor growth and metastasis. The aim of this study was to investigate the role of chronic stress-induced microbiome perturbation in colorectal cancer (CRC) progression. Methods: Chronic restraint stress (CRS) was used to establish the chronic stress mouse model, behavioral tests were used for the CRS model evaluation. Subcutaneous xenograft model and lung metastasis model were established to investigate the growth and metastasis of CRC promoted by CRS exposure. 16S rRNA gene sequencing and liquid chromatograph-mass spectrometer (LC-MS) were applied to observe the effects of CRS exposure on the alteration of the gut microbiome and microbial metabolites. Bioinformatics analysis and correlation analyses were applied to analyse the changes in the frequency of body mass, tumor volume, inflammatory factors, neuroendocrine hormones and metabolites of the gut microbiota. Results: In this study, we identifed that CRS exposure model was appropriately constructed by achieving expected increases in disease activity index and enhanced depressive-like behaviors. CRS exposure can promote growth and metastasis of CRC. Besides, the data indicated that CRS exposure not only increased the neuro- and immune-inflammation, but also weakened the gut mucosal immunological function. The 16s rRNA gene sequencing data showed that CRS exposure increased the abundance of g_Ruminococcaceae_UCG_014. Furthermore, the LC-MS data indicated that with only 2 exceptions of carpaine and DG (15:0/20:4(5Z,8Z,11Z,14Z)/0:0), the majority of these 24 metabolites were less abundant in CRS-exposed mice. Bioinformatics analysis and correlation analyses indicated that only Ruminoscoccaceae-UCG-014 was significantly associated with inflammation (IL-6), neurotransmission (5-HT), and microbial metabolism (PS). Conclusion: CRS exposure altered diversity, composition and metabolites of the gut microbiome, with Ruminococcaceae_UCG-014 perturbation consistently correlated to inflammatory responses, suggesting a particular role of this bacterial genus in CRC growth and metastasis.

Detection of common EEG phenomena using individual electrodes placed outside the hair.

Many studies over the past decades have provided exciting evidence that electrical signals recorded from the scalp (electroencephalogram, EEG) hold meaningful information about the brain's function or dysfunction. This information is used routinely in research laboratories to test specific hypotheses and in clinical settings to aid in diagnoses (such as during polysomnography evaluations). Unfortunately, with very few exceptions, such meaningful information about brain function has not yet led to valuable solutions that can address the needs of many people outside such research laboratories or clinics. One of the major hurdles to practical application of EEG-based neurotechnologies is the current predominant requirement to use electrodes that are placed in the hair, which greatly reduces practicality and cosmesis. While several studies reported results using one specific combination of signal/reference electrode outside the hair in one specific context (such as a brain-computer interface experiment), it has been unclear what information about brain function can be acquired using different signal/referencing locations placed outside the hair. To address this issue, in this study, we set out to determine to what extent EEG phenomena related to auditory, visual, cognitive, motor, and sleep function can be detected from different combinations of individual signal/referencing electrodes that are placed outside the hair. The results of our study from 15 subjects suggest that only a few EEG electrodes placed in locations on the forehead or around the ear can provide substantial task-related information in 6 of 7 tasks. Thus, the results of our study provide encouraging evidence and guidance that should invigorate and facilitate the translation of laboratory experiments into practical, useful, and valuable EEG-based neurotechnology solutions.

Circulating extracellular vesicle-derived MARCKSL1 is a potential diagnostic non-invasive biomarker in metastatic colorectal cancer patients.

Extracellular vesicle-derived proteins are closely related to colorectal cancer metastasis, and early detection and diagnosis of colorectal cancer metastasis is very important to improve the prognosis. In this study, we evaluated the clinical significance of plasma EV-derived MARCKSL1 in differentiating patients with metastatic and nonmetastatic CRC. This study included 78 patients, including 40 patients with nonmetastatic colorectal cancer, 38 patients with metastatic colorectal cancer, and 15 healthy volunteers. The extracellular vesicles extracted from the participants' plasma were characterized through transmission electron microscopy, nanoparticle tracking analysis and western blotting. MARCKSL1 protein expression in the EVs was detected by ELISA, and the diagnostic efficacy of MARCKSL1 alone or in combination with CA125 and lymphocyte levels was evaluated by receiver operating characteristic curve (ROC) analysis. Pearson's correlation test was performed to detect the correlation between MARCKSL1, CA125, lymphocyte level and clinicopathological characteristics of tumors. The present study demonstrated that the level of circulating EV-derived MARCKSL1 in patients with metastatic colorectal cancer was significantly higher than that in patients with nonmetastatic colorectal cancer and healthy people. Combined with CA125 and lymphocyte levels, the best diagnostic effect was achieved, and the area under the ROC curve was 0.7480. Together, our findings indicated that circulating EV-derived MARCKSL1 could be used as a new potential diagnostic biomarker for metastatic CRC.

A method to establish a chronic restraint stress mouse model with colorectal cancer xenografts.

Colorectal cancer (CRC) remains one of the most common clinical cancers of digestive tract. Recently, a large number of researches have shown that chronic stress can actively participate in the development of CRC. The proposed method successfully established the model of chronic stress mouse model with colorectal cancer.•Chronic restraint stress (CRS) was used to establish chronic stress model.•CRS was combined with a colorectal cancer xenografts model.•Behavioural tests and tumour growth were used to evaluate model construction.

Xiao-Chai-Hu-Tang ameliorates tumor growth in cancer comorbid depressive symptoms via modulating gut microbiota-mediated TLR4/MyD88/NF-κB signaling pathway.

BACKGROUND: Depressive symptoms are thought to promote cancer development and depressive remission has been reported to be effective for defeating cancer. The herbal formula Xiao-Chai-Hu-Tang (XCHT), that has an anti-depressive efficacy, has been widely utilized in China. However, its anti-cancer effect and underlying mechanisms remain unclear. PURPOSE: The present study aims to investigate the effects of XCHT on the depression-associated tumor and its potential mechanisms. METHODS: A placebo-controlled trial was conducted in cancer patients comorbid with depressive symptoms to evaluate the effects of XCHT on depressive scales, tumor-related immune indicators, and gut microbial composition. A xenografted colorectal cancer (CRC) mouse model exposure to chronic restraint stress (CRS) was established to examine XCHT effects on tumorigenesis in vivo. Further, by manipulating gut bacteria with fecal microbial transplantation (FMT) or antibiotics-induced bacterial elimination in CRS-associated xenografted model, gut microbiota-mediated anti-tumor mechanism was explored. RESULTS: In cancer patients comorbid with depressive symptoms, XCHT showed substantial effects on improvement of depressive scales, system inflammatory levels and gut dysbiosis. In vivo, XCHT inhibited tumor growth and prolonged survival time in addition to showing anti-depressive effect. Similarly, in our clinical trial, XCHT partially reversed gut dysbiosis, particularly through reducing abundances of Parabacteroides, Blautia and Ruminococcaceae bacterium. Manipulation of gut bacteria in CRS-associated xenografted model further proved that the inhibition of XCHT on tumor progression was mediated by gut microbiota and that the underlying mechanism involves in downregulation of TLR4/MyD88/NF-κB signaling. CONCLUSIONS: We demonstrated that gut microbiota mediates the anti-tumor action of the formula XCHT in cancer patients and models that were comorbid with depressive symptoms. This study implies a novel clinical significance of anti-depressive herbal medicine in the cancer treatment and clarifies the important role of gut microbiota in treating cancer accompanied by depressive symptoms.

Effects of mild moxibustion on intestinal microbiome and NLRP3 inflammasome in rats with 5-fluorouracil-induced intestinal mucositis.

OBJECTIVE: The present study investigated how mild moxibustion treatment affects the intestinal microbiome and expression of NLRP3-related immune factors in a rat model of intestinal mucositis (IM) induced with 5-fluorouracil (5-Fu). METHODS: Forty male Sprague-Dawley rats were randomly divided into control, chemotherapy, moxibustion and probiotics groups. The IM rat model was established by intraperitoneal injection of 5-Fu. Mild moxibustion treatment and intragastric probiotic administration were provided once daily for 15 days. Tissue morphology, serum levels of inflammatory factors and the expression levels of tight junction proteins, caspase-1, gasdermin D and NLRP3 were evaluated in colon tissue, through hematoxylin and eosin staining, electron microscopy, enzyme-linked immunosorbent assay, Western blotting, quantitative real-time reverse transcription polymerase chain reaction and immunofluorescence. Gut microbiome profiling was conducted through 16S rRNA amplicon sequencing. RESULTS: Moxibustion and probiotic treatments significantly increased the expression levels of tight junction proteins, reduced cell apoptosis and the expression levels of caspase-1, gasdermin D and NLRP3; they also decreased the serum levels of tumor necrosis factor-α, interleukin (IL)-6, IL-1ß and IL-18, while increasing serum levels of IL-10. Moxibustion and probiotic treatments also corrected the reduction in α-diversity and ß-diversity in IM rats, greatly increased the proportion of the dominant bacterial genus Lactobacillus and reduced the abundance of the genera Roseburia and Escherichia in chemotherapy-treated rats to levels observed in healthy animals. We also found that these dominant genera were firmly correlated with the regulation of pyroptosis-associated proteins and inflammatory factors. Finally, moxibustion and probiotic treatments elicited similar effects in regulating intestinal host-microbial homeostasis and the expression of NLRP3 inflammasome-related factors. CONCLUSION: Moxibustion exerts its therapeutic effect on IM by ameliorating mucosal damage and reducing inflammation. Moreover, moxibustion modulates the gut microbiota, likely via decreasing the expression levels of the NLRP3 inflammasome.

Xiaoyaosan slows cancer progression and ameliorates gut dysbiosis in mice with chronic restraint stress and colorectal cancer xenografts.

Depression is a risk factor for colorectal cancer (CRC) progression. Xiaoyaosan (XYS) is a traditional Chinese medicine prescription for treating depression. Our present study aimed to investigate the effect of XYS on chronic restraint stress (CRS) in mice with CRC xenografts and explore its underlying mechanisms. XYS treatment for 21 consecutive days successfully reduced the tumour volume and tumour weight in mice and prolonged the overall survival time. In addition, the intestinal permeability in the XYS group was significantly improved after administration. The 16S rRNA high-throughput sequencing method was used to sequence stool samples to check the structure and changes of gut bacteria. XYS mainly regulated the abundance of Bacteroides, Lactobacillus, Desulfovibrio and Rikenellaceae. Taken together, these results provide direct strong evidence that XYS effectively improves the progression of CRC in CRS-handled mice, and its efficacy is associated with the modulation of gut dysbiosis. The application of XYS can be a novel therapeutic strategy for CRC patients with depression.

Comparison of combined anterior-posterior approach versus posterior-only approach in neuromuscular scoliosis: a systematic review and meta-analysis.

PURPOSE: Neuromuscular scoliosis (NS) is a complicated spinal disorder, and it could be treated through posterior-only approach (POA) or combined anterior-posterior approach (APA), which one is better and how to choose the surgical tactic is still in controversy. So comparing POA with APA parameters in the treatment of NS is meaningful. METHODS: Database of PubMed, Embase and Cochrane Library was systematically searched, and the studies, which focus on the comparisons of POA and APA in the treatment of NS, were included. The meta-analysis was performed by RevMan 5.3. RESULTS: Seven retrospective studies with 602 patients were included in meta-analysis. In previous analysis, statistically significant differences were observed in the major parameters between APA and POA. However, the results of subgroup meta-analysis, which focused on the correction angle and loss angle to eliminate the influence of different preoperative angles, were tend to no difference between two groups, except loss angle of scoliosis (MD, 6.4; 95% CI - 0.19 to 13) and correction angle of pelvic obliquity (MD, - 3.44; 95% CI - 6.71 to - 0.17). CONCLUSIONS: Our meta-analysis suggested that POA was similar to APA in the correction of scoliosis in coronal and sagittal planes. However, APA had advantages in the correction of pelvic obliquity and decreasing the loss of angle between postoperation and follow-up in main scoliosis, whereas POA had advantages in operative time, blood loss, duration of hospital stay and complications. LEVEL OF EVIDENCE: Level II. These slides can be retrieved under Electronic Supplementary Material.

Adherence to Positive Airway Therapy After Switching From CPAP to ASV: A Big Data Analysis.

STUDY OBJECTIVES: There is a lack of data regarding adherence trajectories when switching from continuous positive airway pressure (CPAP) to adaptive servoventilation (ASV) in the context of persistent or treatment-emergent central sleep apnea (CSA). This study investigated 90-day adherence rates in patients with sleep apnea based on the type of positive airway pressure (PAP) device used and any switching of PAP modality over time. METHODS: Telemonitoring data were obtained from a United States PAP database. Eligible patients were a 30% random sample who started PAP, plus all who started ASV, from January 1, 2015 to October 2, 2015. All received PAP and had at least one session with usage of 1 hour or more. Adherence and device usage were determined in three groups: started on CPAP and stayed on CPAP (CPAP only); started on ASV and stayed on ASV (ASV only); started on CPAP, switched to ASV (Switch). The United States Medicare definition of adherence was used. RESULTS: The study included 198,890 patients; 189,724 (CPAP only), 8,957 (ASV only) and 209 (Switch). In the Switch group, average apnea-hypopnea index decreased significantly on ASV versus CPAP. At 90 days, adherence rates were 73.8% and 73.2% in the CPAP only and ASV only groups. In the Switch group, CPAP adherence was 62.7%, improving to 76.6% after the switch to ASV. Mean device usage at 90 days was 5.27, 5.31, and 5.73 h/d in the CPAP only, ASV only, and Switch groups, respectively. CONCLUSIONS: Treatment-emergent or persistent CSA during CPAP reduced therapy adherence, but adherence improved early after switching from CPAP to ASV.

Trajectories of Emergent Central Sleep Apnea During CPAP Therapy.

BACKGROUND: The emergence of central sleep apnea (CSA) during positive airway pressure (PAP) therapy has been observed clinically in approximately 10% of obstructive sleep apnea titration studies. This study assessed a PAP database to investigate trajectories of treatment-emergent CSA during continuous PAP (CPAP) therapy. METHODS: U.S. telemonitoring device data were analyzed for the presence/absence of emergent CSA at baseline (week 1) and week 13. Defined groups were as follows: obstructive sleep apnea (average central apnea index [CAI] < 5/h in week 1, < 5/h in week 13); transient CSA (CAI ≥ 5/h in week 1, < 5/h in week 13); persistent CSA (CAI ≥ 5/h in week 1, ≥ 5/h in week 13); emergent CSA (CAI < 5/h in week 1, ≥ 5/h in week 13). RESULTS: Patients (133,006) used CPAP for ≥ 90 days and had ≥ 1 day with use of ≥ 1 h in week 1 and week 13. The proportion of patients with CSA in week 1 or week 13 was 3.5%; of these, CSA was transient, persistent, or emergent in 55.1%, 25.2%, and 19.7%, respectively. Patients with vs without treatment-emergent CSA were older, had higher residual apnea-hypopnea index and CAI at week 13, and more leaks (all P < .001). Patients with any treatment-emergent CSA were at higher risk of therapy termination vs those who did not develop CSA (all P < .001). CONCLUSIONS: Our study identified a variety of CSA trajectories during CPAP therapy, identifying several different clinical phenotypes. Identification of treatment-emergent CSA by telemonitoring could facilitate early intervention to reduce the risk of therapy discontinuation and shift to more efficient ventilator modalities.

Frequency-domain EEG source analysis for acute tonic cold pain perception.

OBJECTIVE: To investigate electrocortical responses to tonic cold pain by frequency-domain electroencephalogram (EEG) source analysis, and to identify potential electrocortical indices of acute tonic pain. METHODS: Scalp EEG data were recorded from 26 healthy subjects under tonic cold pain (CP) and no-pain control (NP) conditions. EEG power spectra and the standardized low-resolution brain electromagnetic tomography (sLORETA) localized EEG cortical sources were compared between the two conditions in five frequency bands: 1-4 Hz, 4-8 Hz, 8-12 Hz, 12-18 Hz and 18-30 Hz. RESULTS: In line with the EEG power spectral results, the source power significantly differed between the CP and NP conditions in 8-12 Hz (CPNP) in extensive brain regions. Besides, there were also significantly different 4-8 Hz and 12-18 Hz source activities between the two conditions. Among the significant source activities, the left medial frontal and left superior frontal 4-8 Hz activities, the anterior cingulate 8-12 Hz activity and the posterior cingulate 12-18 Hz activity showed significant negative correlations with subjective pain ratings. CONCLUSIONS: The brain's perception of tonic cold pain was characterized by cortical source power changes across different frequency bands in multiple brain regions. Oscillatory activities that significantly correlated with subjective pain ratings were found in the prefrontal and cingulate regions. SIGNIFICANCE: These findings may offer useful measures for objective pain assessment and provide a basis for pain treatment by modulation of neural oscillations at specific frequencies in specific brain regions.

A spatio-temporal filtering approach to denoising of single-trial ERP in rapid image triage.

Conventional search for images containing points of interest (POI) in large-volume imagery is costly and sometimes even infeasible. The rapid image triage (RIT) system which is a human cognition guided computer vision technique is potentially a promising solution to the problem. In the RIT procedure, images are sequentially presented to a subject at a high speed. At the instant of observing a POI image, unique POI event-related potentials (ERP) characterized by P300 will be elicited and measured on the scalp. With accurate single-trial detection of such unique ERP, RIT can differentiate POI images from non-POI images. However, like other brain-computer interface systems relying on single-trial detection, RIT suffers from the low signal-to-noise ratio (SNR) of the single-trial ERP. This paper presents a spatio-temporal filtering approach tailored for the denoising of single-trial ERP for RIT. The proposed approach is essentially a non-uniformly delayed spatial Gaussian filter that attempts to suppress the non-event related background electroencephalogram (EEG) and other noises without significantly attenuating the useful ERP signals. The efficacy of the proposed approach is illustrated by both simulation tests and real RIT experiments. In particular, the real RIT experiments on 20 subjects show a statistically significant and meaningful average decrease of 9.8% in RIT classification error rate, compared to that without the proposed approach.

Common spatio-temporal pattern for single-trial detection of event-related potential in rapid serial visual presentation triage.

Searching for target images in large volume imagery is a challenging problem and the rapid serial visual presentation (RSVP) triage is potentially a promising solution to the problem. RSVP triage is essentially a cortically-coupled computer vision technique that relies on single-trial detection of event-related potentials (ERP). In RSVP triage, images are shown to a subject in a rapid serial sequence. When a target image is seen by the subject, unique ERP characterized by P300 are elicited. Thus, in RSVP triage, accurate detection of such distinct ERP allows for fast searching of target images in large volume imagery. The accuracy of the distinct ERP detection in RSVP triage depends on the feature extraction method, for which the common spatial pattern analysis (CSP) was used with limited success. This paper presents a novel feature extraction method, termed common spatio-temporal pattern (CSTP), which is critical for robust single-trial detection of ERP. Unlike the conventional CSP, whereby only spatial patterns of ERP are considered, the present proposed method exploits spatial and temporal patterns of ERP separately, providing complementary spatial and temporal features for high accurate single-trial ERP detection. Numerical study using data collected from 20 subjects in RSVP triage experiments demonstrates that the proposed method offers significant performance improvement over the conventional CSP method (corrected p-value < 0.05, Pearson r = 0.64) and other competing methods in the literature. This paper further shows that the main idea of CSTP can be easily applied to other methods.

Effect of pain perception on the heartbeat evoked potential.

OBJECTIVE: To investigate the effect of acute tonic pain on the heartbeat-evoked potential (HEP) and to test whether or not pain perception can be reflected by the HEP. METHODS: Simultaneous electroencephalogram (EEG) and electrocardiogram (ECG) were recorded from 21 healthy young adults in three conditions: passive no-task control, no-pain control and cold pain. The HEP was obtained by using ECG R-peaks as event triggers. RESULTS: Prominent HEP deflection was observed in both control conditions mainly over the frontal and central locations, while it was significantly suppressed in the cold pain condition over the right-frontal, right-central and midline locations. A comparison of the data in the first and last 5 min of cold pain condition showed that lower subjective pain ratings were accompanied by higher HEP magnitudes. A correlation analysis showed that the mean HEP magnitude over the midline locations was significantly negatively correlated with subjective pain ratings. CONCLUSIONS: Cold pain induces significant suppression of the HEP across a number of scalp locations, and the suppression is correlated with self-report of pain. SIGNIFICANCE: The HEP has the potential to serve as an alternative pain measure.

An improved algorithm for the solution of the regularization path of support vector machine.

This paper describes an improved algorithm for the numerical solution to the support vector machine (SVM) classification problem for all values of the regularization parameter C . The algorithm is motivated by the work of Hastie and follows the main idea of tracking the optimality conditions of the SVM solution for ascending value of C . It differs from Hastie's approach in that the tracked path is not assumed to be 1-D. Instead, a multidimensional feasible space for the optimality condition is used to solve the tracking problem. Such a treatment allows the algorithm to properly handle data sets which Hastie's approach fails. These data sets are characterized by the presence of linearly dependent points (in the kernel space), duplicate points, or nearly duplicate points. Such data sets are quite common among many real-world data, especially those with nominal features. Other contributions of this paper include a unifying formulation of the tracking process in the form of a linear programming problem, update formula for the linear programs, considerations that guard against accumulation of errors resulting from the use of incremental updates, and routines to speed up the algorithm. The algorithm is implemented under the Matlab environment and is available for download. Experiments with several data sets including data set having up to several thousand data points are reported.

Automatic EEG artifact removal: a weighted support vector machine approach with error correction.

An automatic electroencephalogram (EEG) artifact removal method is presented in this paper. Compared to past methods, it has two unique features: 1) a weighted version of support vector machine formulation that handles the inherent unbalanced nature of component classification and 2) the ability to accommodate structural information typically found in component classification. The advantages of the proposed method are demonstrated on real-life EEG recordings with comparisons made to several benchmark methods. Results show that the proposed method is preferable to the other methods in the context of artifact removal by achieving a better tradeoff between removing artifacts and preserving inherent brain activities. Qualitative evaluation of the reconstructed EEG epochs also demonstrates that after artifact removal inherent brain activities are largely preserved.

EEG-based mental fatigue measurement using multi-class support vector machines with confidence estimate.

OBJECTIVE: Automatic measurement and monitoring of mental fatigue are invaluable for preventing mental-fatigue related accidents. We test an EEG-based mental-fatigue monitoring system using a probabilistic-based support vector-machines (SVM) method. METHODS: Ten subjects underwent 25-h sleep deprivation experiments with EEG monitoring. EEG data were segmented into 3-s long epochs and manually classified into 5 mental-fatigue levels, based on subjects' performance on an auditory vigilance task (AVT). Probabilistic-based multi-class SVM and standard multi-class SVM were compared as classifiers for distinguishing mental fatigue into the 5 mental-fatigue levels. RESULTS: Accuracy of the probabilistic-based multi-class SVM was 87.2%, compared to 85.4% using the standard multi-class SVM. Using confidence estimates aggregation, accuracy increased to 91.2%. CONCLUSIONS: Probabilistic-based multi-class SVM not only gives superior classification accuracy but also provides a valuable estimate of confidence in the prediction of mental fatigue level in a given 3-s EEG epoch. SIGNIFICANCE: The work demonstrates the feasibility of an automatic EEG method for assessing and monitoring of mental fatigue. Future applications of this include traffic safety and other domains where measurement or monitoring of mental fatigue is crucial.