Functional disruptions of the brain network in low back pain: a graph-theoretical study.

PURPOSE: The aim of this study was to investigate alterations in the topological organization of whole-brain functional networks in patients with chronic low back pain (CLBP) and characterize the relationship of these alterations with pain characteristics. METHODS: Thirty-three CLBP patients and 34 matched healthy controls (HCs) underwent fMRI scans. A graph-theoretical approach was applied to identify brain network changes in patients suffering from chronic low back pain given its nonspecific etiology and complexity. Graph theory-based analysis was used to construct functional connectivity matrices and extract the features of small-world networks of the brain in both groups. Then, the whole-brain functional connectivity differences were characterized by network-based statistics (NBS) analysis, and the relationship between the altered brain features and clinical measures was explored. RESULTS: At the global level, patients with CLBP showed significantly decreased gamma, sigma, global efficiency, and local efficiency and increased lambda and shortest path length compared with HCs. At the regional level, there were deficits in nodal efficiency within the default mode network and salience network. NBS analysis demonstrated that decreased functional connectivity was present in the CLBP patients, mainly in the frontolimbic circuit and temporal regions. Furthermore, aspects of topological dysfunctions in CLBP were correlated with pain severity. CONCLUSION: This study highlighted the aberrant topological organization of functional brain networks in CLBP, which may shed light on the pathophysiology of CLBP and support the development of pain management approaches.

Altered habenular connectivity in chronic low back pain: An fMRI and machine learning study.

The habenula has been implicated in the pathogenesis of pain and analgesia, while evidence concerning its function in chronic low back pain (cLBP) is sparse. This study aims to investigate the resting-state functional connectivity (rsFC) and effective connectivity of the habenula in 52 patients with cLBP and 52 healthy controls (HCs) and assess the feasibility of distinguishing cLBP from HCs based on connectivity by machine learning methods. Our results indicated significantly enhanced rsFC of the habenula-left superior frontal cortex (SFC), habenula-right thalamus, and habenula-bilateral insular pathways as well as decreased rsFC of the habenula-pons pathway in cLBP patients compared to HCs. Dynamic causal modelling revealed significantly enhanced effective connectivity from the right thalamus to right habenula in cLBP patients compared with HCs. RsFC of the habenula-SFC was positively correlated with pain intensities and Hamilton Depression scores in the cLBP group. RsFC of the habenula-right insula was negatively correlated with pain duration in the cLBP group. Additionally, the combination of the rsFC of the habenula-SFC, habenula-thalamus, and habenula-pons pathways could reliably distinguish cLBP patients from HCs with an accuracy of 75.9% by support vector machine, which was validated in an independent cohort (N = 68, accuracy = 68.8%, p = .001). Linear regression and random forest could also distinguish cLBP and HCs in the independent cohort (accuracy = 73.9 and 55.9%, respectively). Overall, these findings provide evidence that cLBP may be associated with abnormal rsFC and effective connectivity of the habenula, and highlight the promise of machine learning in chronic pain discrimination.

An induced pluripotent stem cell line (SHEHi002-A (5426))from a patient of long QT syndrome type 8 with c.2573G>A mutation in the gene CACNA1C.

Long QT syndrome type 8 is an uncommon inherited condition .An induced pluripotent stem cell (iPSC) line was generated from Peripheral blood mononuclear cells (PBMCs) of a 10-year-old patient with heterozygous mutation of p.R858H(c.2573G > A)in the CACNA1C gene. This iPSC model offers a very valuable resource to study the disease pathophysiology and to develop therapeutics for treatment of Long QT syndrome type 8 patients.

GPNMB silencing suppresses the proliferation and metastasis of osteosarcoma cells by blocking the PI3K/Akt/mTOR signaling pathway.

Glycoprotein non­metastatic melanoma protein B (GPNMB) is a glycoprotein that is highly expressed in various types of cancer, including osteosarcoma. However, its cellular functions and related mechanisms in osteosarcoma remain unclear. In the present study, a higher GPNMB mRNA level was observed in osteosarcoma tissues, than in adjacent non­cancerous tissues. In addition, upregulation of the GPNMB mRNA and protein level was detected in the osteosarcoma cells SaOS2, 143B, MG63 and U2OS using western blot analysis and qPCR. Following transfection with GPNMB siRNA, the proliferation, migration and invasion of MG63 and U2OS cells were assessed using MTT and Transwell assays. The knockdown of GPNMB markedly inhibited the proliferation and metastasis of MG63 and U2OS cells. GPNMB silencing inhibited the activation of PI3K/Akt/mTOR signaling in MG63 and U2OS cells. PI3K/AKT activator insulin­like growth factor­1 (IGF­1) significantly activated the PI3K/Akt/mTOR signaling and reversed the suppressive effects of GPNMB silencing. IGF­1 counteracted the inhibitory effects of GPNMB silencing on the proliferation and metastasis of the MG63 and U2OS cells. In conclusion, we provided evidence that GPNMB silencing regulated the proliferation and metastasis of osteosarcoma cells by suppressing the PI3K/Akt/mTOR signaling pathway. Thus, GPNMB may be a potential therapeutic target for osteosarcoma treatment.

Significant MRI indicators of malignancy for breast non-mass enhancement.

OBJECTIVE: To explore and evaluate new malignant predictors of breast non-mass enhancement lesions using the new BI-RADS MRI lexicon. METHODS: A dataset involving 422 consecutive women underwent breast 3.0 T MRI between January 2014 and July 2016 was assembled for this study. Each case was retrospectively reviewed by 3 radiologists. Eighty-four lesions that present non-mass enhancement in 79 patients were identified in the study. Dynamic contrast-enhanced MRI features were analyzed using univariate and multivariate analyses to identify significant indicators of malignancy. RESULTS: Of 84 non-mass enhancement lesions, 52 (61.9%) were malignant and 32 (38.1%) were benign. Segmental distribution (P = 0.015 from univariate analysis; OR = 4.739, P = 0.008 from multivariate analysis), cluster ring enhancement (P = 0.017 from univariate analysis; OR = 3.601, P = 0.032 from multivariate analysis), time-intensity curve of plateau (P = 0.002 from univariate analysis; OR = 3.525, P = 0.027 from multivariate analysis) and phase to peak (P = 0.06 from univariate analysis; OR = 6.327, P = 0.015 from multivariate analysis) were significantly different between malignant and benign lesions. CONCLUSIONS: This study demonstrated that segmental distribution, clustered ring enhancement, and short time to peak could act as new malignant predictors for breast non-mass enhancement detected on 3.0 T MRI.

RP-HPLC study of resveratrol derivative (BTM-0512) in rat plasma and tissue distribution.

This paper described a rapid and sensitive HPLC method to analyze (E)-3,5,4'-trimethoxystilbene (BTM-0512) in rat plasma and tissues. The analysis used a BDS Hypersil C18 analytical column (250 mm x 4.6 mm ID, 5 microm) and acetonitrile/water as the mobile phase. The UV detection wavelength was 319 nm. Proteins were precipitated with acetonitrile and diethylstilbestrol as internal standard. The method was validated according to State Food and Drug Administration of China and ICH of Technical Requirements for Registration of Pharmaceuticals for Human Use Guidelines. The limit of detection (S/N: 3/1) for BTM-0512 was 0.005 microg x mL(-1) for plasma. The method performances were shown to be selective for BTM-0512 and the linearity of the assay method was up to 10.0 microg x mL(-1) and 40.0 microg x g(-1) for plasma and tissues, respectively. At 0.1, 1 and 5 microg x mL(-1) (n=5), intraday and interday precision values (% RSD) were in the range of 2.6% - 5.1% and 2.4% - 4.8%, respectively. Mean accuracy and absolute recoveries of BTM-0512 ranged from 95.3% - 100.1% and 95.9% - 100.9% for plasma and tissues, respectively. This method can be quite useful for BTM-0512 pharmacokinetic and tissue distribution studies, for purpose which multiple plasma and tissue samples can be analyzed quickly with high reproducibility.