Early Clinical and Subclinical Visual Evoked Potential and Humphrey's Visual Field Defects in Cryptococcal Meningitis.

Cryptococcal induced visual loss is a devastating complication in survivors of cryptococcal meningitis (CM). Early detection is paramount in prevention and treatment. Subclinical optic nerve dysfunction in CM has not hitherto been investigated by electrophysiological means. We undertook a prospective study on 90 HIV sero-positive patients with culture confirmed CM. Seventy-four patients underwent visual evoked potential (VEP) testing and 47 patients underwent Humphrey's visual field (HVF) testing. Decreased best corrected visual acuity (BCVA) was detected in 46.5% of patients. VEP was abnormal in 51/74 (68.9%) right eyes and 50/74 (67.6%) left eyes. VEP P100 latency was the main abnormality with mean latency values of 118.9 (±16.5) ms and 119.8 (±15.7) ms for the right and left eyes respectively, mildly prolonged when compared to our laboratory references of 104 (±10) ms (p<0.001). Subclinical VEP abnormality was detected in 56.5% of normal eyes and constituted mostly latency abnormality. VEP amplitude was also significantly reduced in this cohort but minimally so in the visually unimpaired. HVF was abnormal in 36/47 (76.6%) right eyes and 32/45 (71.1%) left eyes. The predominant field defect was peripheral constriction with an enlarged blind spot suggesting the greater impact by raised intracranial pressure over that of optic neuritis. Whether this was due to papilloedema or a compartment syndrome is open to further investigation. Subclinical HVF abnormalities were minimal and therefore a poor screening test for early optic nerve dysfunction. However, early optic nerve dysfunction can be detected by testing of VEP P100 latency, which may precede the onset of visual loss in CM

Discovery of serum biomarkers for pancreatic adenocarcinoma using proteomic analysis

Background and aims:The serum/plasma proteome was explored for biomarkers to improve the diagnostic ability of CA19-9 in pancreatic adenocarcinoma (PC).Methods:A Training Set of serum samples from 20 resectable and 18 stage IV PC patients, 54 disease controls (DCs) and 68 healthy volunteers (HVs) were analysed by surface-enhanced laser desorption and ionisation time-of-flight mass spectrometry (SELDI-TOF MS). The resulting protein panel was validated on 40 resectable PC, 21 DC and 19 HV plasma samples (Validation-1 Set) and further by ELISA on 33 resectable PC, 28 DC and 18 HV serum samples (Validation-2 Set). Diagnostic panels were derived using binary logistic regression incorporating internal cross-validation followed by receiver operating characteristic (ROC) analysis.Results:A seven-protein panel from the training set PC vs DC and from PC vs HV samples gave the ROC area under the curve (AUC) of 0.90 and 0.90 compared with 0.87 and 0.91 for CA19-9. The AUC was greater (0.97 and 0.99, P0.05) when CA19-9 was added to the panels and confirmed on the validation-1 samples. A simplified panel of apolipoprotein C-I (ApoC-I), apolipoprotein A-II (ApoA-II) and CA19-9 was tested on the validation-2 set by ELISA, in which the ROC AUC was greater than that of CA19-9 alone for PC vs DC (0.90 vs 0.84) and for PC vs HV (0.96 vs 0.90).Conclusions:A simplified diagnostic panel of CA19-9, ApoC-I and ApoA-II improves the diagnostic ability of CA19-9 alone and may have clinical utility

Long-Term Sphere Culture Cannot Maintain a High Ratio of Cancer Stem Cells: A Mathematical Model and Experiment

Acquiring abundant and high-purity cancer stem cells (CSCs) is an important prerequisite for CSC research. At present, researchers usually gain high-purity CSCs through flow cytometry sorting and expand them by short-term sphere culture. However, it is still uncertain whether we can amplify high-purity CSCs through long-term sphere culture. We have proposed a mathematical model using ordinary differential equations to derive the continuous variation of the CSC ratio in long-term sphere culture and estimated the model parameters based on a long-term sphere culture of MCF-7 stem cells. We found that the CSC ratio in long-term sphere culture presented as gradually decreased drift and might be stable at a lower level. Furthermore, we found that fitted model parameters could explain the main growth pattern of CSCs and differentiated cancer cells in long-term sphere culture

Socioeconomic disparities in breast cancer survival: relation to stage at diagnosis, treatment and race

<p>Abstract</p> <p>Background</p> <p>Previous studies have documented lower breast cancer survival among women with lower socioeconomic status (SES) in the United States. In this study, I examined the extent to which socioeconomic disparity in breast cancer survival was explained by stage at diagnosis, treatment, race and rural/urban residence using the Surveillance, Epidemiology, and End Results (SEER) data.</p> <p>Methods</p> <p>Women diagnosed with breast cancer during 1998-2002 in the 13 SEER cancer registry areas were followed-up to the end of 2005. The association between an area-based measure of SES and cause-specific five-year survival was estimated using Cox regression models. Six models were used to assess the extent to which SES differences in survival were explained by clinical and demographical factors. The base model estimated the hazard ratio (HR) by SES only and then additional adjustments were made sequentially for: 1) age and year of diagnosis; 2) stage at diagnosis; 3) first course treatment; 4) race; and 5) rural/urban residence.</p> <p>Results</p> <p>An inverse association was found between SES and risk of dying from breast cancer (p < 0.0001). As area-level SES falls, HR rises (1.00 → 1.05 → 1.23 → 1.31) with the two lowest SES groups having statistically higher HRs. This SES differential completely disappeared after full adjustment for clinical and demographical factors (p = 0.20).</p> <p>Conclusion</p> <p>Stage at diagnosis, first course treatment and race explained most of the socioeconomic disparity in breast cancer survival. Targeted interventions to increase breast cancer screening and treatment coverage in patients with lower SES could reduce much of socioeconomic disparity.</p

Integrating Statistical Predictions and Experimental Verifications for Enhancing Protein-Chemical Interaction Predictions in Virtual Screening

Predictions of interactions between target proteins and potential leads are of great benefit in the drug discovery process. We present a comprehensively applicable statistical prediction method for interactions between any proteins and chemical compounds, which requires only protein sequence data and chemical structure data and utilizes the statistical learning method of support vector machines. In order to realize reasonable comprehensive predictions which can involve many false positives, we propose two approaches for reduction of false positives: (i) efficient use of multiple statistical prediction models in the framework of two-layer SVM and (ii) reasonable design of the negative data to construct statistical prediction models. In two-layer SVM, outputs produced by the first-layer SVM models, which are constructed with different negative samples and reflect different aspects of classifications, are utilized as inputs to the second-layer SVM. In order to design negative data which produce fewer false positive predictions, we iteratively construct SVM models or classification boundaries from positive and tentative negative samples and select additional negative sample candidates according to pre-determined rules. Moreover, in order to fully utilize the advantages of statistical learning methods, we propose a strategy to effectively feedback experimental results to computational predictions with consideration of biological effects of interest. We show the usefulness of our approach in predicting potential ligands binding to human androgen receptors from more than 19 million chemical compounds and verifying these predictions by in vitro binding. Moreover, we utilize this experimental validation as feedback to enhance subsequent computational predictions, and experimentally validate these predictions again. This efficient procedure of the iteration of the in silico prediction and in vitro or in vivo experimental verifications with the sufficient feedback enabled us to identify novel ligand candidates which were distant from known ligands in the chemical space

Epidermal Growth Factor Gene Polymorphism and Risk of Hepatocellular Carcinoma: A Meta-Analysis

BACKGROUND: Hepatocarcinogenesis is a complex process that may be influenced by many factors, including polymorphism in the epidermal growth factor (EGF) gene. Previous work suggests an association between the EGF 61*A/G polymorphism (rs4444903) and susceptibility to hepatocellular carcinoma (HCC), but the results have been inconsistent. Therefore, we performed a meta-analysis of several studies covering a large population to address this controversy. METHODS: PubMed, EMBASE, Google Scholar and the Chinese National Knowledge Infrastructure databases were systematically searched to identify relevant studies. Data were abstracted independently by two reviewers. A meta-analysis was performed to examine the association between EGF 61*A/G polymorphism and susceptibility to HCC. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. RESULTS: Eight studies were chosen in this meta-analysis, involving 1,304 HCC cases (1135 Chinese, 44 Caucasian and 125 mixed) and 2,613 controls (1638 Chinese, 77 Caucasian and 898 mixed). The EGF 61*G allele was significantly associated with increased risk of HCC based on allelic contrast (OR = 1.29, 95% CI = 1.16-1.44, p<0.001), homozygote comparison (OR = 1.79, 95% CI = 1.39-2.29, p<0.001) and a recessive genetic model (OR = 1.34, 95% CI = 1.16-1.54, p<0.001), while patients carrying the EGF 61*A/A genotype had significantly lower risk of HCC than those with the G/A or G/G genotype (A/A vs. G/A+G/G, OR = 0.66, 95% CI = 0.53-0.83, p<0.001). CONCLUSION: The 61*G polymorphism in EGF is a risk factor for hepatocarcinogenesis while the EGF 61*A allele is a protective factor. Further large and well-designed studies are needed to confirm this conclusion

IVSPlat 1.0: an integrated virtual screening platform with a molecular graphical interface

<p>Abstract</p> <p>Background</p> <p>The virtual screening (VS) of lead compounds using molecular docking and pharmacophore detection is now an important tool in drug discovery. VS tasks typically require a combination of several software tools and a molecular graphics system. Thus, the integration of all the requisite tools in a single operating environment could reduce the complexity of running VS experiments. However, only a few freely available integrated software platforms have been developed.</p> <p>Results</p> <p>A free open-source platform, IVSPlat 1.0, was developed in this study for the management and automation of VS tasks. We integrated several VS-related programs into a molecular graphics system to provide a comprehensive platform for the solution of VS tasks based on molecular docking, pharmacophore detection, and a combination of both methods. This tool can be used to visualize intermediate and final results of the VS execution, while also providing a clustering tool for the analysis of VS results. A case study was conducted to demonstrate the applicability of this platform.</p> <p>Conclusions</p> <p>IVSPlat 1.0 provides a plug-in-based solution for the management, automation, and visualization of VS tasks. IVSPlat 1.0 is an open framework that allows the integration of extra software to extend its functionality and modified versions can be freely distributed. The open source code and documentation are available at <url>http://kyc.nenu.edu.cn/IVSPlat/.</url></p

Generation and dietary modulation of anti-inflammatory electrophilic omega-3 fatty acid derivatives

Dietary ω-3 polyunsaturated fatty acids (PUFAs) decrease cardiovascular risk via suppression of inflammation. The generation of electrophilic α,β-unsaturated ketone derivatives of the ω-3 PUFAs docosahexaenoic acid (DHA) and docosapentaenoic acid (DPA) in activated human macrophages is catalyzed by cyclooxygenase-2 (Cox-2). These derivatives are potent pleiotropic anti-inflammatory signaling mediators that act via mechanisms including the activation of Nrf2- dependent phase 2 gene expression and suppression of pro-inflammatory NF-κB-driven gene expression. Herein, the endogenous generation of ω-3 PUFAs electrophilic ketone derivatives and their hydroxy precursors was evaluated in human neutrophils. In addition, their dietary modulation was assessed through a randomized clinical trial. Methods: Endogenous generation of electrophilic omega-3 PUFAs and their hydroxy precursors was evaluated by mass spectrometry in neutrophils isolated from healthy subjects, both at baseline and upon stimulation with calcium ionophore. For the clinical trial, participants were healthy adults 30-55 years of age with a reported EPA+DHA consumption of ≤ 300 mg/day randomly assigned to parallel groups receiving daily oil capsule supplements for a period of 4 months containing either 1.4 g of EPA+DHA (active condition, n = 24) or identical appearing soybean oil (control condition, n = 21). Participants and laboratory technicians remained blinded to treatment assignments. Results: 5-lypoxygenase-dependent endogenous generation of 7-oxo-DHA, 7-oxo-DPA and 5-oxo-EPA and their hydroxy precursors is reported in human neutrophils stimulated with calcium ionophore and phorbol 12-myristate 13-acetate (PMA). Dietary EPA+DHA supplementation significantly increased the formation of 7-oxo-DHA and 5-oxo-EPA, with no significant modulation of arachidonic acid (AA) metabolite levels. Conclusions: The endogenous detection of these electro.©2014 Cipollina et al

Enabling large-scale design, synthesis and validation of small molecule protein-protein antagonists

Although there is no shortage of potential drug targets, there are only a handful known low-molecular-weight inhibitors of protein-protein interactions (PPIs). One problem is that current efforts are dominated by low-yield high-throughput screening, whose rigid framework is not suitable for the diverse chemotypes present in PPIs. Here, we developed a novel pharmacophore-based interactive screening technology that builds on the role anchor residues, or deeply buried hot spots, have in PPIs, and redesigns these entry points with anchor-biased virtual multicomponent reactions, delivering tens of millions of readily synthesizable novel compounds. Application of this approach to the MDM2/p53 cancer target led to high hit rates, resulting in a large and diverse set of confirmed inhibitors, and co-crystal structures validate the designed compounds. Our unique open-access technology promises to expand chemical space and the exploration of the human interactome by leveraging in-house small-scale assays and user-friendly chemistry to rationally design ligands for PPIs with known structure. © 2012 Koes et al