Evaluation of dental enamel caries assessment using Quantitative Light Induced Fluorescence and Optical Coherence Tomography

An in vitro study of morphological alterations between sound dental structure and artificially induced white spot lesions in human teeth, was performed through the loss of fluorescence by Quantitative Light‐Induced Fluorescence (QLF) and the alterations of the light attenuation coefficient by Optical Coherence Tomography (OCT). To analyze the OCT images using a commercially available system, a special algorithm was applied, whereas the QLF images were analyzed using the software available in the commercial system employed. When analyzing the sound region against white spot lesions region by QLF, a reduction in the fluorescence intensity was observed, whilst an increase of light attenuation by the OCT system occurred. Comparison of the percentage of alteration between optical properties of sound and artificial enamel caries regions showed that OCT processed images through the attenuation of light enhanced the tooth optical alterations more than fluorescence detected by QLF System.

QLF versus OCT imaging of enamel caries: a photonics assessment     

Detection of long non-coding RNAs in human breastmilk extracellular vesicles: Implications for early child development

Breastmilk has many documented beneficial effects on the developing human infant, but the components of breastmilk that influence these developmental pathways have not been fully elucidated. Increasing evidence suggests that non-coding RNAs encapsulated in extracellular vesicles (EVs) represent an important mechanism of communication between the mother and child. Long non-coding RNAs (lncRNAs) are of particular interest given their key role in gene expression and development. However, it is not known whether breastmilk EVs contain lncRNAs. We used qRT-PCR to determine whether EVs isolated from human breastmilk contain lncRNAs previously reported to be important for developmental processes. We detected 55 of the 87 screened lncRNAs in EVs from the 30 analyzed breastmilk samples, and CRNDE, DANCR, GAS5, SRA1 and ZFAS1 were detected in >90% of the samples. GAS5, SNHG8 and ZFAS1 levels were highly correlated (Spearman's rho > 0.9; P < 0.0001), which may indicate that the loading of these lncRNAs into breastmilk EVs is regulated by the same pathways. The detected lncRNAs are important epigenetic regulators involved in processes such as immune cell regulation and metabolism. They may target a repertoire of recipient cells in offspring and could be essential for child development and health. Further experimental and epidemiological studies are warranted to determine the impact of breastmilk EV-encapsulated lnRNAs in mother to child signaling.     

Specification of neuronal identities by feedforward combinatorial coding

Neuronal specification is often seen as a multistep process: earlier regulators confer broad neuronal identity and are followed by combinatorial codes specifying neuronal properties unique to specific subtypes. However, it is still unclear whether early regulators are re-deployed in subtype-specific combinatorial codes, and whether early patterning events act to restrict the developmental potential of postmitotic cells. Here, we use the differential peptidergic fate of two lineage-related peptidergic neurons in the Drosophila ventral nerve cord to show how, in a feedforward mechanism, earlier determinants become critical players in later combinatorial codes. Amongst the progeny of neuroblast 5–6 are two peptidergic neurons: one expresses FMRFamide and the other one expresses Nplp1 and the dopamine receptor DopR. We show the HLH gene collier functions at three different levels to progressively restrict neuronal identity in the 5–6 lineage. At the final step, collier is the critical combinatorial factor that differentiates two partially overlapping combinatorial codes that define FMRFamide versus Nplp1/DopR identity. Misexpression experiments reveal that both codes can activate neuropeptide gene expression in vast numbers of neurons. Despite their partially overlapping composition, we find that the codes are remarkably specific, with each code activating only the proper neuropeptide gene. These results indicate that a limited number of regulators may constitute a potent combinatorial code that dictates unique neuronal cell fate, and that such codes show a surprising disregard for many global instructive cues.     

Enantiomeric bioanalysis of simendan and levosimendan by chiral high-performance liquid chromatography

rac-Simendan, (±)-(R, S)-[[4-(1,4,5,6-tetrahydro-4-methyl-6-oxo-3-pyridazinyl)-phenyl]hydrazono]propanedinitrile, and the levorotatory enantiomer levosimendan, are drug candidates intended for the treatment of congestive heart failure. An enantiospecific high-performance liquid chromatographic (HPLC) method suitable for determination of the ratio of the enantiomer concentrations in blood plasma samples was developed. Direct resolution of the enantiomers was achieved by using a chiral β-cyclodextrin stationary phase in reversed phase mode. With an eluent containing 24–33% of methanol in a 0.5% (v/v) triethylammonium acetate buffer, pH 6.0, and a flow rate of 1 ml/min, a resolution (1.2–1.6) adequate for the determinations was achieved. By using UV detection, the relative concentration of the enantiomers in plasma was assessed down to 10 ng/ml. For the racemate, the results indicated a slightly enantioselective disposition and plasma protein binding in rat, dog, and man. The pure enantiomer, levosimendan, was found not to isomerize in vivo. © 1996 Wiley-Liss, Inc.     

Personalized pathology test for Cardio-vascular disease: Approximate Bayesian computation with discriminative summary statistics learning

Cardio/cerebrovascular diseases (CVD) have become one of the major health issue in our societies. But recent studies show that the present pathology tests to detect CVD are ineffectual as they do not consider different stages of platelet activation or the molecular dynamics involved in platelet interactions and are incapable to consider inter-individual variability. Here we propose a stochastic platelet deposition model and an inferential scheme to estimate the biologically meaningful model parameters using approximate Bayesian computation with a summary statistic that maximally discriminates between different types of patients. Inferred parameters from data collected on healthy volunteers and different patient types help us to identify specific biological parameters and hence biological reasoning behind the dysfunction for each type of patients. This work opens up an unprecedented opportunity of personalized pathology test for CVD detection and medical treatment.