Discriminating extra virgin olive oils from common edible oils: Comparable performance of PLS-DA models trained on low-field and high-field 1H NMR data.

INTRODUCTION: Olive oil, derived from the olive tree (Olea europaea L.), is used in cooking, cosmetics, and soap production. Due to its high value, some producers adulterate olive oil with cheaper edible oils or fraudulently mislabel oils as olive to increase profitability. Adulterated products can cause allergic reactions in sensitive individuals and can lack compounds which contribute to the perceived health benefits of olive oil, and its corresponding premium price. OBJECTIVE: There is a need for robust methods to rapidly authenticate olive oils. By utilising machine learning models trained on the nuclear magnetic resonance (NMR) spectra of known olive oil and edible oils, samples can be classified as olive and authenticated. While high-field NMRs are commonly used for their superior resolution and sensitivity, they are generally prohibitively expensive to purchase and operate for routine screening purposes. Low-field benchtop NMR presents an affordable alternative. METHODS: We compared the predictive performance of partial least squares discrimination analysis (PLS-DA) models trained on low-field 60 MHz benchtop proton (1H) NMR and high-field 400 MHz 1H NMR spectra. The data were acquired from a sample set consisting of 49 extra virgin olive oils (EVOOs) and 45 other edible oils. RESULTS: We demonstrate that PLS-DA models trained on low-field NMR spectra are highly predictive when classifying EVOOs from other oils and perform comparably to those trained on high-field spectra. We demonstrated that variance was primarily driven by regions of the spectra arising from olefinic protons and ester protons from unsaturated fatty acids in models derived from data at both field strengths.

Evaluation of normalization strategies for GC-based metabolomics.

INTRODUCTION: For many samples studied by GC-based metabolomics applications, extensive sample preparation involving extraction followed by a two-step derivatization procedure of methoximation and trimethylsilylation (TMS) is typically required to expand the metabolome coverage. Performing normalization is critical to correct for variations present in samples and any biases added during the sample preparation steps and analytical runs. Addressing the totality of variations with an adequate normalization method increases the reliability of the downstream data analysis and interpretation of the results. OBJECTIVES: Normalizing to sample mass is one of the most commonly employed strategies, while the total peak area (TPA) as a normalization factor is also frequently used as a post-acquisition technique. Here, we present a new normalization approach, total derivatized peak area (TDPA), where data are normalized to the intensity of all derivatized compounds. TDPA relies on the benefits of silylation as a universal derivatization method for GC-based metabolomics studies. METHODS: Two sample classes consisting of systematically incremented sample mass were simulated, with the only difference between the groups being the added amino acid concentrations. The samples were TMS derivatized and analyzed using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-TOFMS). The performance of five normalization strategies (no normalization, normalized to sample mass, TPA, total useful peak area (TUPA), and TDPA) were evaluated on the acquired data. RESULTS: Of the five normalization techniques compared, TUPA and TDPA were the most effective. On PCA score space, they offered a clear separation between the two classes. CONCLUSION: TUPA and TDPA carry different strengths: TUPA requires peak alignment across all samples, which depends upon the completion of the study, while TDPA is free from the requirement of alignment. The findings of the study would enhance the convenient and effective use of data normalization strategies and contribute to overcoming the data normalization challenges that currently exist in the metabolomics community.

Biodiversity patterns of the benthic macrofaunal communities across the intertidal sedimentary shores of two Antarctic islands.

Antarctic benthic ecosystems support a unique fauna characterized by high levels of diversity and endemism. However, our knowledge of the macrofauna communities across the Antarctic intertidal sedimentary shore is limited, and their fundamental ecological features, including spatial variability, remain poorly understood. This study aimed to investigate the abundance, community structure (i.e. taxa-specific abundance), and biodiversity patterns (α-, ß-, and λ-diversity) of benthic macrofauna communities on intertidal sedimentary shores of two Antarctic islands (South Shetland archipelago, N of Antarctic Peninsula): Livingston and Deception. We conducted a quantitative sampling during two Austral summer campaigns (2004 and 2005), studying eleven intertidal sites, with five sites located on Livingston and six on Deception. Our results demonstrated a significantly higher abundance of intertidal benthic macrofauna communities on Livingston than on Deception. Furthermore, significant differences in community structure were observed between the two islands. In terms of biodiversity patterns, there were no significant differences in the number of taxa within communities (α-diversity) between the two islands. However, significant differences in the variation of community composition (determined by the number and identity of taxa) between intertidal sites (ß-diversity) were observed, shedding light on the higher total taxa count (λ-diversity) on Livingston compared to Deception. We suggest that the island-specific characteristics (e.g., granulometric characteristics, ice disturbance, sedimentation rates, and geothermal activity) determine the differences observed in macrofauna communities. However, other ecological processes and factors are operating on different spatial and temporal scales (e.g., population dynamics, biotic interactions, oceanographic conditions, and climate change) that influence the occurrence and abundance of macrofaunal taxa. Our findings contribute to the fundamental understanding of the spatial variability of these communities and provide essential information for better management decisions and conservation practices in Antarctic coastal ecosystems.

CaCO3 Nanoparticles Delivering MicroRNA-200c Suppress Oral Squamous Cell Carcinoma.

MicroRNA (miR)-200c suppresses the initiation and progression of oral squamous cell carcinoma (OSCC), the most prevalent head and neck cancer with high recurrence, metastasis, and mortality rates. However, miR-200c-based gene therapy to inhibit OSCC growth has yet to be reported. To develop an miR-based gene therapy to improve the outcomes of OSCC treatment, this study investigates the feasibility of plasmid DNA (pDNA) encoding miR-200c delivered via nonviral CaCO3-based nanoparticles to inhibit OSCC tumor growth. CaCO3-based nanoparticles with various ratios of CaCO3 and protamine sulfate (PS) were used to transfect pDNA encoding miR-200c into OSCC cells, and the efficiency of these nanoparticles was evaluated. The proliferation, migration, and associated oncogene production, as well as in vivo tumor growth for OSCC cells overexpressing miR-200c, were also quantified. It was observed that, while CaCO3-based nanoparticles improve transfection efficiencies of pDNA miR-200c, the ratio of CaCO3 to PS significantly influences the transfection efficiency. Overexpression of miR-200c significantly reduced proliferation, migration, and oncogene expression of OSCC cells, as well as the tumor size of cell line-derived xenografts (CDX) in mice. In addition, a local administration of pDNA miR-200c using CaCO3 delivery significantly enhanced miR-200c transfection and suppressed tumor growth of CDX in mice. These results strongly indicate that the nanocomplexes of CaCO3/pDNA miR-200c may potentially be used to reduce oral cancer recurrence and improve clinical outcomes in OSCC treatment, while more comprehensive examinations to confirm the safety and efficacy of the CaCO3/pDNA miR-200c system using various preclinical models are needed.

Imaging Cerebral Blood Vessels Using Near-Infrared Optical Tomography: A Simulation Study.

Cerebral veins have received increasing attention due to their importance in preoperational planning and the brain oxygenation measurement. There are different modalities to image those vessels, such as magnetic resonance angiography (MRA) and recently, contrast-enhanced (CE) 3D gradient-echo sequences. However, the current techniques have certain disadvantages, i.e., the long examination time, the requirement of contrast agents or inability to measure oxygenation. Near-infrared optical tomography (NIROT) is emerging as a viable new biomedical imaging modality that employs near infrared light (650-950 nm) to image biological tissue. It was proven to easily penetrate the skull and therefore enables the brain vessels to be assessed. NIROT utilizes safe non-ionizing radiation and can be applied in e.g., early detection of neonatal brain injury and ischemic strokes. The aim is to develop non-invasive label-free dynamic time domain (TD) NIROT to image the brain vessels. A simulation study was performed with the software (NIRFAST) which models light propagation in tissue with the finite element method (FEM). Both a simple shape mesh and a real head mesh including all the segmented vessels from MRI images were simulated using both FEM and a hybrid FEM-U-Net network, we were able to visualize the superficial vessels with NIROT with a Root Mean Square Error (RMSE) lower than 0.079.

Use of reconstituted kefir consortia to determine the impact of microbial composition on kefir metabolite profiles.

Kefir is fermented traditionally with kefir grains, but commercial kefir production often relies on fermentation with planktonic cultures. Kefir has been associated with many health benefits, however, the utilization of kefir grains to facilitate large industrial production of kefir is challenging and makes to difficult to ensure consistent product quality and consistency. Notably, the microbial composition of kefir fermentations has been shown to impact kefir associated health benefits. This study aimed to compare volatile compounds, organic acids, and sugar composition of kefir produced through a traditional grain fermentation and through a reconstituted kefir consortium fermentation. Additionally, the impact of two key microbial communities on metabolite production in kefir was assessed using two modified versions of the consortium, with either yeasts or lactobacilli removed. We hypothesized that the complete kefir consortium would closely resemble traditional kefir, while the consortia without yeasts or lactobacilli would differ significantly from both traditional kefir and the complete consortium fermentation. Kefir fermentations were examined after 12 and 18 h using two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS) to identify volatile compounds and high performance liquid chromatography (HPLC) to identify organic acid and sugar composition. The traditional kefir differed significantly from the kefir consortium fermentation with the traditional kefir having 15-20 log2(fold change) higher levels of esters and the consortium fermented kefir having between 1 and 3 log2(fold change) higher organic acids including lactate and acetate. The use of a version of kefir consortium that lacked lactobacilli resulted in between 2 and 20 log2(fold change) lower levels of organic acids, ethanol, and butanoic acid ethyl ester, while the absence of yeast from the consortium resulted in minimal change. In summary, the kefir consortium fermentation is significantly different from traditional grain fermented kefir with respect to the profile of metabolites present, and seems to be driven by lactobacilli, as evidenced by the significant decrease in multiple metabolites when the lactobacilli were removed from the fermentation and minimal differences observed upon the removal of yeast.

Optimization of fecal sample homogenization for untargeted metabolomics.

INTRODUCTION: Fecal samples are highly complex and heterogeneous, containing materials at various stages of digestion. The heterogeneity and complexity of feces make stool metabolomics inherently challenging. The level of homogenization influences the outcome of the study, affecting the metabolite profiles and reproducibility; however, there is no consensus on how fecal samples should be prepared to overcome the topographical discrepancy and obtain data representative of the stool as a whole. OBJECTIVES: Various combinations of homogenization conditions were compared to investigate the effects of bead size, addition of solvents and the differences between wet-frozen and lyophilized feces. METHODS: The homogenization parameters were systematically altered to evaluate the solvent usage, bead size, and whether lyophilization is required in homogenization. The metabolic coverage and reproducibility were compared among the different conditions. RESULTS: The current work revealed that a combination of mechanical and chemical lysis obtained by bead-beating with a mixture of big and small sizes of beads in an organic solvent is an effective way to homogenize fecal samples with adequate reproducibility and metabolic coverage. Lyophilization is required when bead-beating is not available. CONCLUSIONS: A comprehensive and systematical evaluation of various fecal matter homogenization conditions provides a profound understanding for the effects of different homogenization methods. Our findings would be beneficial to assist with standardization of fecal sample homogenization protocol.

Untargeted Metabolomic Profiling of Aqueous and Lyophilized Pooled Human Feces from Two Diet Cohorts Using Two-Dimensional Gas Chromatography Coupled with Time-of-Flight Mass Spectrometry.

The metabolic profiles of human feces are influenced by various genetic and environmental factors, which makes feces an attractive biosample for numerous applications, including the early detection of gut diseases. However, feces is complex, heterogeneous, and dynamic with a significant live bacterial biomass. With such challenges, stool metabolomics has been understudied compared to other biospecimens, and there is a current lack of consensus on methods to collect, prepare, and analyze feces. One of the critical steps required to accelerate the field is having a metabolomics stool reference material available. Fecal samples are generally presented in two major forms: fecal water and lyophilized feces. In this study, two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS) was used as an analytical platform to characterize pooled human feces, provided by the National Institute of Standards and Technology (NIST) as Research-Grade Test Materials. The collected fecal samples were derived from eight healthy individuals with two different diets: vegans and omnivores, matched by age, sex, and body mass index (BMI), and stored as fecal water and lyophilized feces. Various data analysis strategies were presented to determine the differences in the fecal metabolomic profiles. The results indicate that the sample storage condition has a major influence on the metabolic profiles of feces such that the impact from storage surpasses the metabolic differences from the diet types. The findings of the current study would contribute towards the development of a stool reference material.

Multiple and spectrally robust photonic magic angles in reconfigurable α-MoO3 trilayers.

The emergence of a topological transition of the polaritonic dispersion in twisted bilayers of anisotropic van der Waals materials at a given twist angle-the photonic magic angle-results in the diffractionless propagation of polaritons with deep-subwavelength resolution. This type of propagation, generally referred to as canalization, holds promise for the control of light at the nanoscale. However, the existence of a single photonic magic angle hinders such control since the canalization direction in twisted bilayers is unique and fixed for each incident frequency. Here we overcome this limitation by demonstrating multiple spectrally robust photonic magic angles in reconfigurable twisted α-phase molybdenum trioxide (α-MoO3) trilayers. We show that canalization of polaritons can be programmed at will along any desired in-plane direction in a single device with broad spectral ranges. These findings open the door for nanophotonics applications where on-demand control is crucial, such as thermal management, nanoimaging or entanglement of quantum emitters.

PARAFAC2×N: Coupled decomposition of multi-modal data with drift in N modes.

Analysis of GC×GC-TOFMS data for large numbers of poorly-resolved peaks, and for large numbers of samples remains an enduring problem that hinders the widespread application of the technique. For multiple samples, GC×GC-TOFMS data for specific chromatographic regions manifests as a 4th order tensor of I mass spectral acquisitions, J mass channels, K modulations, and L samples. Chromatographic drift is common along both the first-dimension (modulations), and along the second-dimension (mass spectral acquisitions), while drift along the mass channel is for all practical purposes nonexistent. A number of solutions to handling GC×GC-TOFMS data have been proposed: these involve reshaping the data to make it amenable to either 2nd order decomposition techniques based on Multivariate Curve Resolution (MCR), or 3rd order decomposition techniques such as Parallel Factor Analysis 2 (PARAFAC2). PARAFAC2 has been utilised to model chromatographic drift along one mode, which has enabled its use for robust decomposition of multiple GC-MS experiments. Although extensible, it is not straightforward to implement a PARAFAC2 model that accounts for drift along multiple modes. In this submission, we demonstrate a new approach and a general theory for modelling data with drift along multiple modes, for applications in multidimensional chromatography with multivariate detection. The proposed model captures over 99.9% of variance for a synthetic data set, presenting an extreme example of peak drift and co-elution across two modes of separation.

Twist-tunable polaritonic nanoresonators in a van der Waals crystal.

Optical nanoresonators are key building blocks in various nanotechnological applications (e.g., spectroscopy) due to their ability to effectively confine light at the nanoscale. Recently, nanoresonators based on phonon polaritons (PhPs)-light coupled to lattice vibrations-in polar crystals (e.g., SiC, or h-BN) have attracted much attention due to their strong field confinement, high quality factors, and their potential to enhance the photonic density of states at mid-infrared (mid-IR) frequencies, where numerous molecular vibrations reside. Here, we introduce a new class of mid-IR nanoresonators that not only exhibit the extraordinary properties previously reported, but also incorporate a new degree of freedom: twist tuning, i.e., the possibility of controlling their spectral response by simply rotating the constituent material. To achieve this result, we place a pristine slab of the van der Waals (vdW) α-MoO3 crystal, which supports in-plane hyperbolic PhPs, on an array of metallic ribbons. This sample design based on electromagnetic engineering, not only allows the definition of α-MoO3 nanoresonators with low losses (quality factors, Q, up to 200), but also enables a broad spectral tuning of the polaritonic resonances (up to 32 cm-1, i.e., up to ~6 times their full width at half maximum, FWHM ~5 cm-1) by a simple in-plane rotation of the same slab (from 0 to 45°). These results open the door to the development of tunable and low-loss IR nanotechnologies, fundamental requirements for their implementation in molecular sensing, emission or photodetection applications.

The Metabolomic Profile of the Essential Oil from Zanthoxylum caribaeum (syn. chiloperone) Growing in Guadeloupe FWI using GC × GC-TOFMS.

The essential oil (EO) from the leaves of Zanthoxylum caribaeum (syn. Chiloperone) (Rutaceae) was studied previously for its acaricidal, antimicrobial, antioxidant, and insecticidal properties. In prior studies, the most abundant compound class found in leaf oils from Brazil, Costa Rica, and Paraguay was terpenoids. Herein, essential oil from the leaves of Zanthoxylum caribaeum (prickly yellow, bois chandelle blanc (FWI), peñas Blancas (Costa Rica), and tembetary hu (Paraguay)) growing in Guadeloupe was analyzed with comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-TOFMS), and thirty molecules were identified. A comparison with previously published leaf EO compositions of the same species growing in Brazil, Costa Rica, and Paraguay revealed a number of molecules in common such as ß-myrcene, limonene, ß-caryophyllene, α-humulene, and spathulenol. Some molecules identified in Zanthoxylum caribaeum from Guadeloupe showed some antimetabolic effects on enzymes; the in-depth study of this plant and its essential oil with regard to metabolic diseases merits further exploration.

Development and Validation of Robust and Cost-Effective Liquid Heterogeneous Phantom for Time Domain Near-Infrared Optical Tomography.

Diffused light imaging techniques, such as near-infrared optical tomography (NIROT), require a stable platform for testing and validation that imitates tissue optical properties. The aim of this work was to build a robust, but flexible liquid phantom for BORL time-domain NIROT system Pioneer. The phantom was designed to assess penetration depth and resolution of the system, and to provide a heterogeneous inner structure that can be changed in controllable manner with adjustable optical properties. We used only in-house produced 3D-printed elements and mechanics of a budget 3D-printer to build the phantom, and managed to keep the overall costs below $500. We achieved stable and repeatable movement of an arbitrary structure in 3+1 degree of freedom inside the phantom and demonstrated its performance in a series of tests. Thus, we presented a universal and cost-effective solution for testing NIROT, that can be easily customised to various systems or testing paradigms.

Untargeted region of interest selection for gas chromatography - mass spectrometry data using a pseudo F-ratio moving window.

There are many challenges associated with analysing gas chromatography - mass spectrometry (GC-MS) data. Many of these challenges stem from the fact that electron ionization (EI) can make it difficult to recover molecular information due to the high degree of fragmentation with concomitant loss of molecular ion signal. With GC-MS data there are often many common fragment ions shared among closely-eluting peaks, necessitating sophisticated methods for analysis. Some of these methods are fully automated, but make some assumptions about the data which can introduce artifacts during the analysis. Chemometric methods such as Multivariate Curve Resolution (MCR), or Parallel Factor Analysis (PARAFAC/PARAFAC2) are particularly attractive, since they are flexible and make relatively few assumptions about the data - ideally resulting in fewer artifacts. These methods do require expert user intervention to determine the most relevant regions of interest and an appropriate number of components, k, for each region. Automated region of interest selection is needed to permit automated batch processing of chromatographic data with advanced signal deconvolution. Here, we propose a new method for automated, untargeted region of interest selection that accounts for the multivariate information present in GC-MS data to select regions of interest based on the ratio of the squared first, and second singular values from the Singular Value Decomposition (SVD) of a window that moves across the chromatogram. Assuming that the first singular value accounts largely for signal, and that the second singular value accounts largely for noise, it is possible to interpret the relationship between these two values as a probabilistic distribution of Fisher Ratios. The sensitivity of the algorithm was tested by investigating the concentration at which the algorithm can no longer pick out chromatographic regions known to contain signal. The algorithm achieved detection of features in a GC-MS chromatogram at concentrations below 10 pg on-column. The resultant probabilities can be interpreted as regions that contain features of interest.

Validation of a Portuguese version of the Groningen radiotherapy-induced xerostomia questionnaire.

BACKGROUND: The aim of this study was to validate and determine at pretest level the reliability of the Portuguese version of the Groningen radiotherapy-induced xerostomia questionnaire. MATERIAL AND METHODS: This study employed 37 head and neck cancer patients. Each patient signed an informed consent and responded to the Portuguese version of the questionnaire in the form of an interview. This was repeated again after 2 weeks. A standard single question provided a validity check. Data were analyzed using Cronbach's α to test its reliability and total and interitem correlation, and intraclass correlation to determine its internal consistency and test-retest reliability. Construct validity supported by objective measurements as salivary secretion was also investigated. Significance was set at .05. RESULTS: Cronbach's α was 0.91 and 0.89 for the first and second test administrations, respectively, which indicates that the internal consistency was excellent. The intraclass correlation coefficient value for the test-retest reliability was 0.70. The correlation between the total score of the questionnaire and standard single dry mouth question was 0.72 for the first round, indicating a good correlation. CONCLUSIONS: Demonstrating very good psychometric properties, the Portuguese version of the Groningen radiotherapy-induced xerostomia questionnaire is a valid tool and can be considered a reliable instrument to measure xerostomia in head and neck cancer patients.

Henry's Law Constants and Indoor Partitioning of Microbial Volatile Organic Compounds.

Microbial volatile organic compounds (MVOCs) play an essential role in many environmental fields, such as indoor air quality. Long-term exposure to odorous and toxic MVOCs can negatively affect the health of occupants. Recently, the involvement of surface reservoirs in indoor chemistry has been realized, which signifies the importance of the phase partitioning of volatile organic pollutants. However, reliable partition coefficients of many MVOCs are currently lacking. Equilibrium partition coefficients, such as Henry's law constant, H, are crucial for understanding the environmental behavior of chemicals. This study aims to experimentally determine the H values and their temperature dependence for key MVOCs under temperature relevant to the indoor environment. The H values were determined with the inert gas-stripping (IGS) method and variable phase ratio headspace (VPR-HS) technique. A two-dimensional partitioning model was applied to predict the indoor phase distribution of MVOCs and potential exposure pathways to the residences. The findings show that the MVOCs are likely distributed between the gas and weakly polar (e.g., organic-rich) reservoirs indoors. Temperature and the volume of reservoirs can sensitively affect indoor partitioning. Our results give a more comprehensive view of indoor chemical partitioning and exposure.

Evaluation of fresh, frozen, and lyophilized fecal samples by SPME and derivatization methods using GC×GC-TOFMS.

INTRODUCTION: Feces is a highly complex matrix containing thousands of metabolites. It also contains live bacteria and enzymes, and does not have a static chemistry. Consequently, proper control of pre-analytical parameters is critical to minimize unwanted variations in the samples. However, no consensus currently exists on how fecal samples should be stored/processed prior to analysis. OBJECTIVE: The effects of sample handling conditions on fecal metabolite profiles and abundances were examined using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC-TOFMS). METHODS: Solid-phase microextraction (SPME) and derivatization via trimethylsilylation (TMS) were employed as complementary techniques to evaluate fresh, frozen, and lyophilized fecal samples with expanded coverage of the fecal metabolome. The total number of detected peaks and the signal intensities were compared among the different handling conditions. RESULTS: Our analysis revealed that the metabolic profiles of fecal samples depend greatly on sample handling and processing conditions, which had a more pronounced effect on results obtained by SPME than by TMS derivatization. Overall, lyophilization resulted in a greater amount of total and class-specific metabolites, which may be attributed to cell lysis and/or membrane disintegration. CONCLUSIONS: A comprehensive comparison of the sample handling conditions provides a deeper understanding of the physicochemical changes that occur within the samples during freezing and lyophilization. Based on our results, snap-freezing at -80 °C would be preferred over lyophilization for handling samples in the field of fecal metabolomics as this imparts the least change from the fresh condition.

Investigation of the protective suitability of a dental fluorinated varnish by means of X Ray fluorescence and Raman spectroscopy.

BACKGROUND AND AIM: Evaluating the protective effect in human enamel of a fluorinated varnish after enduring a citric acid erosive challenge. METHODS: An in vitro model was developed considering the intraoral environment, human saliva and acid erosive procedures. The evaluation of the enamel specimens was undertaken through the direct analysis of enamel by means of Raman spectroscopy and Energy Dispersive X Ray Fluorescence (EDXRF). Ten tooth specimens per group were analysed during three stages: 1- before treatment; 2- After varnish (treatment group) or toothpaste (control) application; 3- After citric acid cycle. Additionally, Particle Induced Gamma Ray emission (PIGE) was used to gauge the fluorine uptake by enamel after the application of the varnish (stage 2). Results were presented as mean and standard deviation with ANOVA and Tukey post hoc performed considering a significance level of 0.05. RESULTS: A significant (p < 0.05) higher Ca levels were detected in treatment group at stage 2 (37.4 ± 0.4 w/w%) and 3 (37.1 ± 0.1) when compared to the control group. After varnish application in treatment group, depolarization ratios were significant lower (p < 0.05) and anisotropy were significant higher (p < 0.05), however no differences were detected in FWHM. CONCLUSIONS: The use of a fluorinated dental varnish suggests a protective effect for human enamel against dental erosion demineralization process which was detectable in an in vitro model.

Neuronal Ceroid Lipofuscinosis Type 6 (CLN6) clinical findings and molecular diagnosis: Costa Rica's experience.

BACKGROUND: Commonly known as Batten disease, the neuronal ceroid lipofuscinoses (NCLs) are a genetically heterogeneous group of rare pediatric lysosomal storage disorders characterized by the intracellular accumulation of autofluorescent material (known as lipofuscin), progressive neurodegeneration, and neurological symptoms. In 2002, a disease-causing NCL mutation in the CLN6 gene was identified (c.214G > T) in the Costa Rican population, but the frequency of this mutation among local Batten disease patients remains incompletely characterized, as do clinical and demographic attributes for this rare patient population. OBJECTIVE: To describe the main sociodemographic and clinical characteristics of patients with a clinical diagnosis for Batten Disease treated at the National Children's Hospital in Costa Rica and to characterize via molecular testing their causative mutations. METHODS: DNA extracted from buccal swabs was used for CLN6 gene sequencing. Participants' sociodemographic and clinical characteristics were also obtained from their medical records. RESULTS: Nine patients with a clinical diagnosis of Batten disease were identified. Genetic sequencing determined the presence of the previously described Costa Rican homozygous mutation in 8 of 9 cases. One patient did not have mutations in the CLN6 gene. In all cases where the Costa Rican CLN6 mutation was present, it was accompanied by a substitution in intron 2. Patients were born in 4 of the 7 Costa Rican provinces, with an average onset of symptoms close to 4 years of age. No parental consanguinity was present in pedigrees. Initial clinical manifestations varied between patients but generally included: gait disturbances, language problems, visual impairment, seizures and psychomotor regression. Cortical and cerebellar atrophy was a constant finding when neuroimaging was performed. Seizure medication was a common element of treatment regimens. CONCLUSIONS: This investigation supports that the previously characterized c.214G > T mutation is the most common causative NCL mutation in the Costa Rican population. This mutation is geographically widespread among Costa Rican NCL patients and yields a clinical presentation similar to that observed for CLN6 NCL patients in other geographies.

Global metabolome analysis of Dunaliella tertiolecta, Phaeobacter italicus R11 Co-cultures using thermal desorption - Comprehensive two-dimensional gas chromatography - Time-of-flight mass spectrometry (TD-GC×GC-TOFMS).

Dunaliella tertiolecta is a marine microalgae that has been studied extensively as a potential carbon-neutral biofuel source (Tang et al., 2011). Microalgae oil contains high quantities of energy-rich fatty acids and lipids, but is not yet commercially viable as an alternative fuel. Carefully optimised growth conditions, and more recently, algal-bacterial co-cultures have been explored as a way of improving the yield of D. tertiolecta microalgae oils. The relationship between the host microalgae and bacterial co-cultures is currently poorly understood. Here, a complete workflow is proposed to analyse the global metabolomic profile of co-cultured D. tertiolectra and Phaeobacter italicus R11, which will enable researchers to explore the chemical nature of this relationship in more detail. To the best of the authors' knowledge this study is one of the first of its kind, in which a pipeline for an entirely untargeted analysis of the algal metabolome is proposed using a practical sample preparation, introduction, and data analysis routine.