Ratiometric array of conjugated polymers–fluorescent protein provides a robust mammalian cell sensor

© 2016 American Chemical Society.Supramolecular complexes of a family of positively charged conjugated polymers (CPs) and green fluorescent protein (GFP) create a fluorescence resonance energy transfer (FRET)-based ratiometric biosensor array. Selective multivalent interactions of the CPs with mammalian cell surfaces caused differential change in FRET signals, providing a fingerprint signature for each cell type. The resulting fluorescence signatures allowed the identification of 16 different cell types and discrimination between healthy, cancerous, and metastatic cells, with the same genetic background. While the CP-GFP sensor array completely differentiated between the cell types, only partial classification was achieved for the CPs alone, validating the effectiveness of the ratiometric sensor. The utility of the biosensor was further demonstrated in the detection of blinded unknown samples, where 121 of 128 samples were correctly identified. Notably, this selectivity-based sensor stratified diverse cell types in minutes, using only 2000 cells, without requiring specific biomarkers or cell labeling

Medical diagnosis using machine learning: a statistical review

Decision making in case of medical diagnosis is a complicated process. A large number of overlapping structures and cases, and distractions, tiredness, and limitations with the human visual system can lead to inappropriate diagnosis. Machine learning (ML) methods have been employed to assist clinicians in overcoming these limitations and in making informed and correct decisions in disease diagnosis. Many academic papers involving the use of machine learning for disease diagnosis have been increasingly getting published. Hence, to determine the use of ML to improve the diagnosis in varied medical disciplines, a systematic review is conducted in this study. To carry out the review, six different databases are selected. Inclusion and exclusion criteria are employed to limit the research. Further, the eligible articles are classified depending on publication year, authors, type of articles, research objective, inputs and outputs, problem and research gaps, and findings and results. Then the selected articles are analyzed to show the impact of ML methods in improving the disease diagnosis. The findings of this study show the most used ML methods and the most common diseases that are focused on by researchers. It also shows the increase in use of machine learning for disease diagnosis over the years. These results will help in focusing on those areas which are neglected and also to determine various ways in which ML methods could be employed to achieve desirable results

Reviewing the use of chitosan and polydopamine for electrochemical sensing

Biopolymers possess highly favorable properties for electrochemical biosensing such as their inherent biocompatibility, inexpensive nature, and strong interfacial adhesion. In this mini-review, we will focus on chitosan and polydopamine, two of the most commonly used biopolymers, for electrochemical sensing applications. Chitosan is a polysaccharide that exhibits high chemical resistance, offers straightforward modification and cross-linking, and possesses antibacterial properties and mucoadhesion. Polydopamine has the benefit of universal adhesion, in addition to the ability to form self-assembled structures. We will demonstrate how the unique structural and electrochemical features of these biopolymers can be used in a range of electrochemical biosensing platforms

Liver Enzyme Abnormalities and Associated Risk Factors in HIV Patients on Efavirenz-Based HAART with or without Tuberculosis Co-Infection in Tanzania.

To investigate the timing, incidence, clinical presentation, pharmacokinetics and pharmacogenetic predictors for antiretroviral and anti-tuberculosis drug induced liver injury (DILI) in HIV patients with or without TB co-infection. A total of 473 treatment naïve HIV patients (253 HIV only and 220 with HIV-TB co-infection) were enrolled prospectively. Plasma efavirenz concentration and CYP2B6*6, CYP3A5*3, *6 and *7, ABCB1 3435C/T and SLCO1B1 genotypes were determined. Demographic, clinical and laboratory data were collected at baseline and up to 48 weeks of antiretroviral therapy. DILI case definition was according to Council for International Organizations of Medical Sciences (CIOMS). Incidence of DILI and identification of predictors was evaluated using Cox Proportional Hazards Model. The overall incidence of DILI was 7.8% (8.3 per 1000 person-week), being non-significantly higher among patients receiving concomitant anti-TB and HAART (10.0%, 10.7 per 1000 person-week) than those receiving HAART alone (5.9%, 6.3 per 1000 person-week). Frequency of CYP2B6*6 allele (p = 0.03) and CYP2B6*6/*6 genotype (p = 0.06) was significantly higher in patients with DILI than those without. Multivariate cox regression model indicated that CYP2B6*6/*6 genotype and anti-HCV IgG antibody positive as significant predictors of DILI. Median time to DILI was 2 weeks after HAART initiation and no DILI onset was observed after 12 weeks. No severe DILI was seen and the gain in CD4 was similar in patients with or without DILI. Antiretroviral and anti-tuberculosis DILI does occur in our setting, presenting early following HAART initiation. DILI seen is mild, transient and may not require treatment interruption. There is good tolerance to HAART and anti-TB with similar immunological outcomes. Genetic make-up mainly CYP2B6 genotype influences the development of efavirenz based HAART liver injury in Tanzanians

Multilevel psychometric properties of the AHRQ hospital survey on patient safety culture

<p>Abstract</p> <p>Background</p> <p>The Agency for Healthcare Research and Quality (AHRQ) <it>Hospital Survey on Patient Safety Culture </it>was designed to assess staff views on patient safety culture in hospital settings. The purpose of this study was to examine the multilevel psychometric properties of the survey.</p> <p>Methods</p> <p>Survey data from 331 U.S. hospitals with 2,267 hospital units and 50,513 respondents were analyzed to examine the psychometric properties of the survey's items and composites. Item factor loadings, intraclass correlations (ICCs), design effects, internal consistency reliabilities, and multilevel confirmatory factor analyses (MCFA) were examined as well as intercorrelations among the survey's composites.</p> <p>Results</p> <p>Psychometric analyses confirmed the multilevel nature of the data at the individual, unit and hospital levels of analysis. Results provided overall evidence supporting the 12 dimensions and 42 items included in the AHRQ <it>Hospital Survey on Patient Safety Culture </it>as having acceptable psychometric properties at all levels of analysis, with a few exceptions. The Staffing composite fell slightly below cutoffs in a number of areas, but is conceptually important given its impact on patient safety. In addition, one hospital-level model fit indicator for the Supervisor/Manager Expectations & Actions Promoting Patient Safety composite was low (CFI = .82), but all other psychometrics for this scale were good. Average dimension intercorrelations were moderate at .42 at the individual level, .50 at the unit level, and .56 at the hospital level.</p> <p>Conclusions</p> <p>Psychometric analyses conducted on a very large database of hospitals provided overall support for the patient safety culture dimensions and items included in the AHRQ <it>Hospital Survey on Patient Safety Culture</it>. The survey's items and dimensions overall are psychometrically sound at the individual, unit, and hospital levels of analysis and can be used by researchers and hospitals interested in assessing patient safety culture. Further research is needed to study the criterion-related validity of the survey by analysing the relationship between patient safety culture and patient outcomes and studying how to improve patient safety culture.</p

Topical delivery of tetrahydrocurcumin lipid nanoparticles effectively inhibits skin inflammation: in vitro and in vivo study

Tetrahydrocurcumin (THC) also referred to as "white curcumin", is a stable colourless hydrogenated product of curcumin with superior antioxidant and anti-inflammatory properties. Present study is an attempt to elevate the topical bioavailability of THC, post incorporation into a nano-carrier system with its final dosage as a hydrogel. Lipid nanoparticles of THC (THC-SLNs) prepared by microemulsification technique were ellipsoidal in shape (revealed in TEM) with a mean particle size of 96.6 nm and zeta potential of -22 mV. Total drug content and entrapment efficiency of THC-SLNs was 94.51% ± 2.15% and 69.56% ± 1.35%, respectively. DSC and X-Ray diffraction studies confirmed the formation of THC-SLNs. In vitro drug release studies showed the drug release from THC-SLNs gel to follow Higuchi's equation revealing a Fickian diffusion. Ex-vivo permeation studies indicated a 17 times (approximately) higher skin permeation of THC-SLNs gel as compared with the free THC gel. Skin irritation, occlusion and stability studies indicated the formulation to be non-irritating, and stable with a desired occlusivity. Pharmacodynamic evaluation in an excision wound mice model clearly revealed the enhanced anti-inflammatory activity of THC-SLNs gel and confirmed using biochemical and histopathological studies. It is noteworthy to report here that THC-SLNs gel showed significantly better (p≤0.001) activity than free THC in gel. As inflammation is innate to all the skin disorders, the developed product opens up new therapeutic avenues for several skin diseases. To best of our knowledge, this is the first paper elaborating the therapeutic usefulness of white curcumin loaded lipidic nanoparticles for skin inflammation

Oral treatment with a zinc complex of acetylsalicylic acid prevents diabetic cardiomyopathy in a rat model of type-2 diabetes: activation of the Akt pathway.

BACKGROUND: Type-2 diabetics have an increased risk of cardiomyopathy, and heart failure is a major cause of death among these patients. Growing evidence indicates that proinflammatory cytokines may induce the development of insulin resistance, and that anti-inflammatory medications may reverse this process. We investigated the effects of the oral administration of zinc and acetylsalicylic acid, in the form of bis(aspirinato)zinc(II)-complex Zn(ASA)2, on different aspects of cardiac damage in Zucker diabetic fatty (ZDF) rats, an experimental model of type-2 diabetic cardiomyopathy. METHODS: Nondiabetic control (ZL) and ZDF rats were treated orally with vehicle or Zn(ASA)2 for 24 days. At the age of 29-30 weeks, the electrical activities, left-ventricular functional parameters and left-ventricular wall thicknesses were assessed. Nitrotyrosine immunohistochemistry, TUNEL-assay, and hematoxylin-eosin staining were performed. The protein expression of the insulin-receptor and PI3K/AKT pathway were quantified by Western blot. RESULTS: Zn(ASA)2-treatment significantly decreased plasma glucose concentration in ZDF rats (39.0 +/- 3.6 vs 49.4 +/- 2.8 mM, P < 0.05) while serum insulin-levels were similar among the groups. Data from cardiac catheterization showed that Zn(ASA)2 normalized the increased left-ventricular diastolic stiffness (end-diastolic pressure-volume relationship: 0.064 +/- 0.008 vs 0.084 +/- 0.014 mmHg/microl; end-diastolic pressure: 6.5 +/- 0.6 vs 7.9 +/- 0.7 mmHg, P < 0.05). Furthermore, ECG-recordings revealed a restoration of prolonged QT-intervals (63 +/- 3 vs 83 +/- 4 ms, P < 0.05) with Zn(ASA)2. Left-ventricular wall thickness, assessed by echocardiography, did not differ among the groups. However histological examination revealed an increase in the cardiomyocytes' transverse cross-section area in ZDF compared to the ZL rats, which was significantly decreased after Zn(ASA)2-treatment. Additionally, a significant fibrotic remodeling was observed in the diabetic rats compared to ZL rats, and Zn(ASA)2-administered ZDF rats showed a similar collagen content as ZL animals. In diabetic hearts Zn(ASA)2 significantly decreased DNA-fragmentation, and nitro-oxidative stress, and up-regulated myocardial phosphorylated-AKT/AKT protein expression. Zn(ASA)2 reduced cardiomyocyte death in a cellular model of oxidative stress. Zn(ASA)2 had no effects on altered myocardial CD36, GLUT-4, and PI3K protein expression. CONCLUSIONS: We demonstrated that treatment of type-2 diabetic rats with Zn(ASA)2 reduced plasma glucose-levels and prevented diabetic cardiomyopathy. The increased myocardial AKT activation could, in part, help to explain the cardioprotective effects of Zn(ASA)2. The oral administration of Zn(ASA)2 may have therapeutic potential, aiming to prevent/treat cardiac complications in type-2 diabetic patients