Identifying the Alteration Patterns of Brain Functional Connectivity in Progressive Mild Cognitive Impairment Patients: A Longitudinal Whole-Brain Voxel-Wise Degree Analysis

Patients with mild cognitive impairment (MCI) are at high risk for developing Alzheimer’s disease (AD), while some of them may remain stable over decades. The underlying mechanism is still not fully understood. In this study, we aimed to explore the connectivity differences between progressive MCI (PMCI) and stable MCI (SMCI) individuals on a whole-brain scale and on a voxel-wise basis, and we also aimed to reveal the differential dynamic alternation patterns between these two disease subtypes. The resting-state functional magnetic resonance images of PMCI and SMCI patients at baseline and year-one were obtained from the Alzheimer’s Disease Neuroimaging Initiative dataset, and the progression was determined based on a three-year follow-up. A whole-brain voxel-wise degree map that was calculated based on graph-theory was constructed for each subject, and then the cross-sectional and longitudinal analyses on the degree maps were performed between PMCI and SMCI patients. In longitudinal analyses, compared with SMCI group, PMCI group showed decreased long-range degree in the left middle occipital/supramarginal gyrus, while the short-range degree was increased in the left supplementary motor area and middle frontal gyrus and decreased in the right middle temporal pole. A significant longitudinal alteration of decreased short-range degree in the right middle occipital was found in PMCI group. Taken together with previous evidence, our current findings may suggest that PMCI, compared with SMCI, might be a severe presentation of disease along the AD continuum, and the rapidly reduced degree in the right middle occipital gyrus may have indicative value for the disease progression. Moreover, the cross-sectional comparison results and corresponding receiver-operator characteristic-curves analyses may indicate that the baseline degree difference is not a good predictor of disease progression in MCI patients. Overall, these findings may provide objective evidence and an indicator to characterize the progression-related brain connectivity changes in MCI patients

Targeting Pancreatic Ductal Adenocarcinoma Acidic Microenvironment

Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer death in the USA, accounting for ~40,000 deaths annually. The dismal prognosis for PDAC is largely due to its late diagnosis. Currently, the most sensitive diagnosis of PDAC requires invasive procedures, such as endoscopic ultrasonography, which has inherent risks and accuracy that is highly operator dependent. Here we took advantage of a general characteristic of solid tumors, the acidic microenvironment that is generated as a by-product of metabolism, to develop a novel approach of using pH (Low) Insertion Peptides (pHLIPs) for imaging of PDAC. We show that fluorescently labeled pHLIPs can localize and specifically detect PDAC in human xenografts as well as PDAC and PanIN lesions in genetically engineered mouse models. This novel approach may improve detection, differential diagnosis and staging of PDAC

Detection of pancreatic cancer tumours and precursor lesions by cathepsin E activity in mouse models.

ABSTRACT Background and Aims Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer death in the USA. Surgical resection is the only effective treatment; however, only 20% of patients are candidates for surgery. The ability to detect early PDAC would increase the availability of surgery and improve patient survival. This study assessed the feasibility of using the enzymatic activity of cathepsin E (Cath E), a protease highly and specifically expressed in PDAC, as a novel biomarker for the detection of pancreas-bearing pancreatic intraepithelial neoplasia (PanIN) lesions and PDAC. Methods Pancreas from normal, chronic pancreatitis and PDAC patients was assessed for Cath E expression by quantitative real-time PCR and immunohistochemistry. Human PDAC xenografts and genetically engineered mouse models (GEMM) of PDAC were injected with a Cath E activity selective fluorescent probe and imaged using an optical imaging system. Results The specificity of Cath E expression in PDAC patients and GEMM of pancreatic cancer was confirmed by quantitative real-time PCR and immunohistochemistry. The novel probe for Cath E activity specifically detected PDAC in both human xenografts and GEMM in vivo. The Cath E sensitive probe was also able to detect pancreas with PanIN lesions in GEMM before tumour formation. Conclusions The elevated Cath E expression in PanIN and pancreatic tumours allowed in-vivo detection of human PDAC xenografts and imaging of pancreas with PanIN and PDAC tumours in GEMM. Our results support the usefulness of Cath E activity as a potential molecular target for PDAC and early detection imaging. Despite great efforts to help patients with pancreatic ductal adenocarcinoma (PDAC) in the past few years, this disease remains devastating with the worst outcome of all major cancers. In the USA, PDAC ranks 10th in terms of incidence, but for both men and women, it is fourth in terms of cancer deaths. Although many molecular biomarker candidates of PDAC have been identified, 3 biomarkers with the necessary sensitivity and specificity for early detection are still lacking. 4e6 The most widely utilised blood-based biomarker is CA 19-9, which is not expressed in all patients, is not highly specific as it is elevated in other gastrointestinal cancers, and is not useful for the detection of early disease. 7 8 Furthermore, CA 19-9 levels do not provide information about the localisation of the disease nor the existence of metastases. The most sensitive diagnosis of PDAC currently requires invasive imaging procedures such as endoscopic ultrasonography, which Significance of this study What is already known about this subject? < No highly specific and sensitive biomarkers are clinically available for the detection of PDAC at an early stage. < Cath E is highly overexpressed in many cancers including PDAC. < A Cath E selective peptide was recently identified that specifically detects its enzymatic activity. What are the new findings? < We demonstrate that the elevated levels of Cath E expression in early pancreatic cancer lesions and pancreatic tumours could be exploited for PDAC detection. < We illustrate that the detection and localisation of PDAC in mouse xenografts and GEMM was possible utilising the outstanding specificity of a novel Cath E-activatable imaging probe. How might it impact on clinical practice in the foreseeable future? < The ability to detect and visualise pancreatic tumours and PanIN in PDAC by virtue of Cath E activity sensitive probes in preclinical mouse models suggests that modifications of this approach will be useful for the early detection and management of this deadly cancer in patients. < The specificity of Cath E activity for PDAC suggests that this enzymatic activity will be useful in the future for the development of novel therapeutics or theranostics. Cruz-Monserrate Z, Abd-Elgaliel WR, Grote T, et al. Gut (2011)

The association risk of male subfertility and testicular cancer: a systematic review.

BACKGROUND: An association between male subfertility and an increased risk of testicular cancer has been proposed, but conflicting results of research on this topic have rendered this theory equivocal. To more precisely assess the association between subfertility and the risk of testicular cancer, we performed a systematic review of international epidemiologic evidence. PRINCIPAL FINDINGS: We searched the Medline database for records from January 1966 to March 2008 complemented with manual searches of the literature and then identified studies that met our inclusion criteria. Study design, sample size, exposure to subfertility and risk estimates of testicular cancer incidence were abstracted. Summary relative risks (RRs) with 95% confidence intervals (CIs) were calculated using the DerSimonian and Laird model. All statistical tests were two-sided. We identified seven case-control studies and two cohort studies published between 1987 and 2005. Analysis of the seven case-control studies that included 4,954 participants revealed an overall statistically significant association between subfertility and increased risk of testicular cancer (summary RR = 1.68, 95% CI: 1.22 to 2.31), without heterogeneity between studies (Q = 8.46, P heterogeneity = 0.21, I(2) statistics = 0.29). The association between subfertility and testicular cancer was somewhat stronger in the United States (summary RR = 1.75, 95% CI: 1.01 to 3.02) than it was in Europe (summary RR = 1.53, 95% CI: 1.22 to 1.92). The source of the control subjects had a statistically significant effect on the magnitude of the association (population-based summary-RR = 2.15, 95% CI: 1.11 to 4.17; hospital-based summary--RR = 1.56, 95% CI: 0.93 to 2.61). After excluding possible cryptorchidism, an important confounding factor, we also found a positive association between subfertility and increased risk of testicular cancer (summary RR = 1.59, 95% CI: 1.28 to 1.98). These results were consistent between studies conducted in the United States and in Europe (Q = 0.20, P heterogeneity = 0.66). Of the two cohort studies that reported standardized incidence ratios, both reported a statistically significant positive association between subfertility and increased risk of testicular cancer. CONCLUSIONS: Our findings support a relationship between subfertility and increased risk of testicular cancer and apply to the management of men with subfertility, and prevention and diagnosis of testicular cancer

An integrated mRNA and microRNA expression signature for glioblastoma multiforme prognosis.

Although patients with Glioblastoma multiforme (GBM) have grave prognosis, significant variability in patient outcome is observed. The objective of this study is to identify a molecular signature for GBM prognosis. We subjected 355 mRNA and microRNA expression profiles to elastic net-regulated Cox regression for identification of an integrated RNA signature for GBM prognosis. A prognostic index (PI) was generated for patient stratification. Survival comparison was conducted by Kaplan-Meier method and a general multivariate Cox regression procedure was applied to evaluate the independence of the PI. The abilities and efficiencies of signatures to predict GBM patient outcome was assessed and compared by the area under the curve (AUC) of the receiver-operator characteristic (ROC). An integrated RNA prognostic signature consisted by 4 protective mRNAs, 12 risky mRNAs, and 1 risky microRNA was identified. Decreased survival was associated with being in the high-risk group (hazard ratio = 2.864, P<0.0001). The prognostic value of the integrated signature was validated in five independent GBM expression datasets (n = 201, hazard ratio = 2.453, P<0.0001). The PI outperformed the known clinical factors, mRNA-only, and miRNA-only prognostic signatures for GBM prognosis (area under the ROC curve for the integrated RNA, mRNA-only, and miRNA-only signatures were 0.828, 0.742, and 0.757 at 3 years of overall survival, respectively, P<0.0001 by permutation test). We describe the first, to our knowledge, robust transcriptome-based integrated RNA signature that improves the current GBM prognosis based on clinical variables, mRNA-only, and miRNA-only signatures

Unusual spectroscopic properties of PPE/TiO2 composite and its sensor response to TNT

A composite from a broad bandgap polymer, poly(phenylene ethylene) (PPE), and nano-sized TiO2 particles was found to be able to sense 2,4,6-trinitrotoluene (TNT) for TNT sensor. Fluorescence quenching induced by charge transfer from PPE to nano-sized TiO2 was observed in toluene solution. At high TiO2 composition, a strong exciplex band occurred at 550 nm. Under prolonged light irradiation at 400 nm, unusual fluorescence gains took place at 460 nm, companied with a very small change in the UV&ndash;vis absorbance. After 30 min light irradiation, the fluorescence at 460 nm reached a maximum, but the peak at 550 nm disappeared. This composite showed amplified sensor response to TNT compared to the pristine PPE film, which can be potentially used as sensing material for detecting TNT based explosives.<br /

Highly fluorescent TPA-PBPV nanofibers with amplified sensory response to TNT

Well-aligned nanofibers were prepared from a conjugated polymer, poly(triphenylamine-alt-biphenylene vinylene) (TPA-PBPV), using a solution-assisted template wetting technique. TPA-PBPV was also coated on the surface of electrospun polyacrylonitrile (PAN) nanofiber nonwoven membrane. The extremely large surface area, highly porous fibrous structure, optical scattering and evanescent-wave guiding effect imparted these one-dimensional (1D) nanofibrous materials with highly improved sensory ability to 2,4,6-trinitrotoluene (TNT) vapors and higher quenching efficiency than that of the neat TPA-PBPV films. The results suggest that nanofibrous structures could be a promising strategy to improve the sensory efficiency of fluorescent chemosensors.<br /

Multivariate Cox stepwise regression of PI and demographic and clinical variables.

<p>The PI based on the integrated 17-RNA signature was an independent prognostic predictor for GBM patients relative to the demographic and clinical variables, and it was superior to clinical variables in predicting GBM patient survival. The significance of the regression model was evaluated by Wald test (<i>P</i> = 8.88e-16).</p

Kaplan-Meier curves and ROC curves for the integrated RNA signature.

<p>Kaplan-Meier plots for GBM patients in high-risk and low-risk groups segregated by the integrated RNA signature in the TCGA GBM cohort (A) and the validation cohort (C). The significance of survival difference between groups was evaluated by log-rank test (<i>P</i> = 1.02e-09 and 3.76e-08, respectively). The respective ROC curves had AUCs of 0.828 (B) and 0.780 (D). The permutation <i>P</i> value was computed to test the null hypothesis (AUC = 0.5) using 10,000 permutations.</p

WPI distribution and AUC histogram of the TCGA GBM cohort.

<p>A, WPI distribution in the TCGA GBM cohort (n = 355). The point at which the distribution changed the most abruptly, which corresponded to (WPI = −0.7), served as the distribution cutoff. Patients were categorized as high risk (n = 294, left double-headed arrow) or low risk (n = 61, right double-headed arrow). B, Histogram of the empirical distribution of AUC generated from 10,000 permutations. The vertical dashed line is the observed AUC in the TCGA GBM cohort.</p