Antiplasmodial and larvicidal flavonoids from Derris trifoliata

From the dichloromethane-methanol (1:1) extract of the seed pods of Derris trifoliata, a new flavanone derivative (S)-lupinifolin 4´-methyl ether was isolated. In addition, the known flavonoids lupinifolin and rotenone were identified. The structures were determined on the basis of spectroscopic evidence. Lupinfolin showed moderate in vitro antiplasmodial activity against the D6 (chloroquine-sensitive) and W2 (chloroquineresistant)strains of Plasmodium falciparum. The different parts of this plant showed larvicidal activities against Aedes aegypti and rotenoids were identified as the active principles

Seizures and Encephalitis in Myelin Oligodendrocyte Glycoprotein IgG Disease vs Aquaporin 4 IgG Disease

Importance: Antibodies to myelin oligodendrocyte glycoprotein IgG (MOG-IgG) are increasingly detected in patients with non–multiple sclerosis–related demyelination, some of whom manifest a neuromyelitis optica (NMO) phenotype. Cortical involvement, encephalopathy, and seizures are rare in aquaporin 4 antibody (AQP4-IgG)–related NMO in the white European population. However, the authors encountered several patients with seizures associated with MOG-IgG disease. Objective: To compare incidence of seizures and encephalitis-like presentation, or both between AQP4-IgG–positive and MOG-IgG–positive patients. Design, Setting, and Participants: Retrospective case series of all patients who were seropositive for MOG-IgG (n = 34) and the last 100 patients with AQP4-IgG disease (NMO spectrum disorder) seen in the NMO service between January 2013 and December 2016, and analysis was completed January 4, 2017. All patients were seen in a tertiary neurological center, The Walton Centre NHS Foundation Trust in Liverpool, England. Main Outcomes and Measures: The difference in seizure frequency between the AQP4-IgG–positive and MOG-IgG–positive patient groups was determined. Results: Thirty-four patients with MOG-IgG disease (20 female) with a median age at analysis of 30.5 years (interquartile range [IQR], 15-69 years), and 100 AQP4-IgG–positive patients (86 female) with a median age at analysis of 54 years (IQR, 12-91 years) were studied. Most patients were of white race. Five of the 34 patients with MOG-IgG (14.7%) had seizures compared with 1 patient with AQP4-IgG (2-sided P < .008, Fisher test). On magnetic resonance imaging, all 5 MOG-IgG–positive patients had inflammatory cortical brain lesions associated with the seizures. In 3 of the 5 MOG-IgG–positive patients, seizures occurred as part of the index event. Four of the 5 presented with encephalopathy and seizures, and disease relapsed in all 5 patients. Four of these patients were receiving immunosuppressant medication at last follow-up, and 3 continued to take antiepileptic medication. In contrast, the only AQP4-IgG–positive patient with seizures had a diagnosis of complex partial epilepsy preceding the onset of NMO by several years and experienced no encephalitic illness; her magnetic resonance imaging results demonstrated no cortical, subcortical, or basal ganglia involvement. Conclusions and Relevance: Patients with MOG-IgG–associated disease were more likely to have seizures and encephalitis-like presentation than patients with AQP4-IgG–associated disease

Optically trapped bacteria pairs reveal discrete motile response to control aggregation upon cell–cell approach

Aggregation of bacteria plays a key role in the formation of many biofilms. The critical first step is cell–cell approach, and yet the ability of bacteria to control the likelihood of aggregation during this primary phase is unknown. Here, we use optical tweezers to measure the force between isolated Bacillus subtilis cells during approach. As we move the bacteria towards each other, cell motility (bacterial swimming) initiates the generation of repulsive forces at bacterial separations of ~3 μm. Moreover, the motile response displays spatial sensitivity with greater cell–cell repulsion evident as inter-bacterial distances decrease. To examine the environmental influence on the inter-bacterial forces, we perform the experiment with bacteria suspended in Tryptic Soy Broth, NaCl solution and deionised water. Our experiments demonstrate that repulsive forces are strongest in systems that inhibit biofilm formation (Tryptic Soy Broth), while attractive forces are weak and rare, even in systems where biofilms develop (NaCl solution). These results reveal that bacteria are able to control the likelihood of aggregation during the approach phase through a discretely modulated motile response. Clearly, the force-generating motility we observe during approach promotes biofilm prevention, rather than biofilm formation

Effect of atorvastatin on glycaemia progression in patients with diabetes:an analysis from the Collaborative Atorvastatin in Diabetes Trial (CARDS)

AIMS/HYPOTHESIS: In an individual-level analysis we examined the effect of atorvastatin on glycaemia progression in type 2 diabetes and whether glycaemia effects reduce the prevention of cardiovascular disease (CVD) with atorvastatin. METHODS: The study population comprised 2,739 people taking part in the Collaborative Atorvastatin Diabetes Study (CARDS) who were randomised to receive atorvastatin 10 mg or placebo and who had post-randomisation HbA(1c) data. This secondary analysis used Cox regression to estimate the effect of atorvastatin on glycaemia progression, defined as an increase in HbA(1c) of ≥0.5% (5.5 mmol/mol) or intensification of diabetes therapy. Mixed models were used to estimate the effect of atorvastatin on HbA(1c) as a continuous endpoint. RESULTS: Glycaemia progression occurred in 73.6% of participants allocated placebo and 78.1% of those allocated atorvastatin (HR 1.18 [95% CI 1.08, 1.29], p < 0.001) by the end of follow-up. The HR was 1.22 (95% CI 1.19, 1.35) in men and 1.11 (95% CI 0.95, 1.29) in women (p = 0.098 for the sex interaction). A similar effect was seen in on-treatment analyses: HR 1.20 (95% CI 1.07, 1.35), p = 0.001. The net mean treatment effect on HbA(1c) was 0.14% (95% CI 0.08, 0.21) (1.5 mmol/mol). The effect did not increase through time. Diabetes treatment intensification alone did not differ with statin allocation. Neither baseline nor 1-year-attained HbA(1c) predicted subsequent CVD, and the atorvastatin effect on CVD did not vary by HbA(1c) change (interaction p value 0.229). CONCLUSIONS/INTERPRETATION: The effect of atorvastatin 10 mg on glycaemia progression among those with diabetes is statistically significant but very small, is not significantly different between sexes, does not increase with duration of statin and does not have an impact on the magnitude of CVD risk reduction with atorvastatin. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00125-015-3802-6) contains peer-reviewed but unedited supplementary material, which is available to authorised users

Identification and validation of oncologic miRNA biomarkers for Luminal A-like breast cancer

Introduction: Breast cancer is a common disease with distinct tumor subtypes phenotypically characterized by ER and HER2/neu receptor status. MiRNAs play regulatory roles in tumor initiation and progression, and altered miRNA expression has been demonstrated in a variety of cancer states presenting the potential for exploitation as cancer biomarkers. Blood provides an excellent medium for biomarker discovery. This study investigated systemic miRNAs differentially expressed in Luminal A-like (ER+PR+HER2/neu-) breast cancer and their effectiveness as oncologic biomarkers in the clinical setting. Methods: Blood samples were prospectively collected from patients with Luminal A-like breast cancer (n=54) and controls (n=56). RNA was extracted, reverse transcribed and subjected to microarray analysis (n=10 Luminal A-like; n=10 Control). Differentially expressed miRNAs were identified by artificial neural network (ANN) data-mining algorithms. Expression of specific miRNAs was validated by RQ-PCR (n=44 Luminal A; n=46 Control) and potential relationships between circulating miRNA levels and clinicopathological features of breast cancer were investigated. Results: Microarray analysis identified 76 differentially expressed miRNAs. ANN revealed 10 miRNAs for further analysis ( miR-19b, miR-29a, miR-93, miR-181a, miR-182, miR-223, miR-301a, miR-423-5p, miR-486-5 and miR-652 ). The biomarker potential of 4 miRNAs ( miR-29a, miR-181a , miR-223 and miR-652 ) was confirmed by RQ-PCR, with significantly reduced expression in blood of women with Luminal A-like breast tumors compared to healthy controls (p=0.001, 0.004, 0.009 and 0.004 respectively). Binary logistic regression confirmed that combination of 3 of these miRNAs ( miR-29a, miR-181a and miR-652 ) could reliably differentiate between cancers and controls with an AUC of 0.80. Conclusion: This study provides insight into the underlying molecular portrait of Luminal A-like breast cancer subtype. From an initial 76 miRNAs, 4 were validated with altered expression in the blood of women with Luminal A-like breast cancer. The expression profiles of these 3 miRNAs, in combination with mammography, has potential to facilitate accurate subtype- specific breast tumor detection

The effect of statin therapy on heart failure events: a collaborative meta-analysis of unpublished data from major randomized trials

The effect of statins on risk of heart failure (HF) hospitalization and HF death remains uncertain. We aimed to establish whether statins reduce major HF events.We searched Medline, EMBASE, and the Cochrane Central Register of Controlled Trials for randomized controlled endpoint statin trials from 1994 to 2014. Collaborating trialists provided unpublished data from adverse event reports. We included primary- and secondary-prevention statin trials with >1000 participants followed for >1 year. Outcomes consisted of first non-fatal HF hospitalization, HF death and a composite of first non-fatal HF hospitalization or HF death. HF events occurring <30 days after within-trial myocardial infarction (MI) were excluded. We calculated risk ratios (RR) with fixed-effects meta-analyses. In up to 17 trials with 132 538 participants conducted over 4.3 [weighted standard deviation (SD) 1.4] years, statin therapy reduced LDL-cholesterol by 0.97 mmol/L (weighted SD 0.38 mmol/L). Statins reduced the numbers of patients experiencing non-fatal HF hospitalization (1344/66 238 vs. 1498/66 330; RR 0.90, 95% confidence interval, CI 0.84-0.97) and the composite HF outcome (1234/57 734 vs. 1344/57 836; RR 0.92, 95% CI 0.85-0.99) but not HF death (213/57 734 vs. 220/57 836; RR 0.97, 95% CI 0.80-1.17). The effect of statins on first non-fatal HF hospitalization was similar whether this was preceded by MI (RR 0.87, 95% CI 0.68-1.11) or not (RR 0.91, 95% CI 0.84-0.98).In primary- and secondary-prevention trials, statins modestly reduced the risks of non-fatal HF hospitalization and a composite of non-fatal HF hospitalization and HF death with no demonstrable difference in risk reduction between those who suffered an MI or not

The effect of statin therapy on heart failure events: a collaborative meta-analysis of unpublished data from major randomized trials

The effect of statins on risk of heart failure (HF) hospitalization and HF death remains uncertain. We aimed to establish whether statins reduce major HF events.We searched Medline, EMBASE, and the Cochrane Central Register of Controlled Trials for randomized controlled endpoint statin trials from 1994 to 2014. Collaborating trialists provided unpublished data from adverse event reports. We included primary- and secondary-prevention statin trials with >1000 participants followed for >1 year. Outcomes consisted of first non-fatal HF hospitalization, HF death and a composite of first non-fatal HF hospitalization or HF death. HF events occurring <30 days after within-trial myocardial infarction (MI) were excluded. We calculated risk ratios (RR) with fixed-effects meta-analyses. In up to 17 trials with 132 538 participants conducted over 4.3 [weighted standard deviation (SD) 1.4] years, statin therapy reduced LDL-cholesterol by 0.97 mmol/L (weighted SD 0.38 mmol/L). Statins reduced the numbers of patients experiencing non-fatal HF hospitalization (1344/66 238 vs. 1498/66 330; RR 0.90, 95% confidence interval, CI 0.84-0.97) and the composite HF outcome (1234/57 734 vs. 1344/57 836; RR 0.92, 95% CI 0.85-0.99) but not HF death (213/57 734 vs. 220/57 836; RR 0.97, 95% CI 0.80-1.17). The effect of statins on first non-fatal HF hospitalization was similar whether this was preceded by MI (RR 0.87, 95% CI 0.68-1.11) or not (RR 0.91, 95% CI 0.84-0.98).In primary- and secondary-prevention trials, statins modestly reduced the risks of non-fatal HF hospitalization and a composite of non-fatal HF hospitalization and HF death with no demonstrable difference in risk reduction between those who suffered an MI or not

MPHASYS: a mouse phenotype analysis system

<p>Abstract</p> <p>Background</p> <p>Systematic, high-throughput studies of mouse phenotypes have been hampered by the inability to analyze individual animal data from a multitude of sources in an integrated manner. Studies generally make comparisons at the level of genotype or treatment thereby excluding associations that may be subtle or involve compound phenotypes. Additionally, the lack of integrated, standardized ontologies and methodologies for data exchange has inhibited scientific collaboration and discovery.</p> <p>Results</p> <p>Here we introduce a Mouse Phenotype Analysis System (MPHASYS), a platform for integrating data generated by studies of mouse models of human biology and disease such as aging and cancer. This computational platform is designed to provide a standardized methodology for working with animal data; a framework for data entry, analysis and sharing; and ontologies and methodologies for ensuring accurate data capture. We describe the tools that currently comprise MPHASYS, primarily ones related to mouse pathology, and outline its use in a study of individual animal-specific patterns of multiple pathology in mice harboring a specific germline mutation in the DNA repair and transcription-specific gene Xpd.</p> <p>Conclusion</p> <p>MPHASYS is a system for analyzing multiple data types from individual animals. It provides a framework for developing data analysis applications, and tools for collecting and distributing high-quality data. The software is platform independent and freely available under an open-source license <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>.</p

Testing the cognitive-behavioural maintenance models across DSM-5 bulimic-type eating disorder diagnostic groups: A multi-centre study

The original cognitive-behavioural (CB) model of bulimia nervosa, which provided the basis for the widely used CB therapy, proposed that specific dysfunctional cognitions and behaviours maintain the disorder. However, amongst treatment completers, only 40–50 % have a full and lasting response. The enhanced CB model (CB-E), upon which the enhanced version of the CB treatment was based, extended the original approach by including four additional maintenance factors. This study evaluated and compared both CB models in a large clinical treatment seeking sample (N = 679), applying both DSM-IV and DSM-5 criteria for bulimic-type eating disorders. Application of the DSM-5 criteria reduced the number of cases of DSM-IV bulimic-type eating disorders not otherwise specified to 29.6 %. Structural equation modelling analysis indicated that (a) although both models provided a good fit to the data, the CB-E model accounted for a greater proportion of variance in eating-disordered behaviours than the original one, (b) interpersonal problems, clinical perfectionism and low self-esteem were indirectly associated with dietary restraint through over-evaluation of shape and weight, (c) interpersonal problems and mood intolerance were directly linked to binge eating, whereas restraint only indirectly affected binge eating through mood intolerance, suggesting that factors other than restraint may play a more critical role in the maintenance of binge eating. In terms of strength of the associations, differences across DSM-5 bulimic-type eating disorder diagnostic groups were not observed. The results are discussed with reference to theory and research, including neurobiological findings and recent hypotheses