Data-Driven Soft Independent Modeling of Class Analogy in Paper Spray Ionization Mass Spectrometry-Based Metabolomics for Rapid Detection of Prostate Cancer.

Sensitive, rapid, and meaningful diagnostic tools for prostate cancer (PC) screening are urgently needed. Paper spray ionization mass spectrometry (PSI-MS) is an emerging rapid technology for detecting biomarker and disease diagnoses. Due to lack of chromatography and difficulties in employing tandem MS, PSI-MS-based untargeted metabolomics often suffers from increased ion suppression and subsequent feature detection, affecting chemometric methods for disease classification. This study first evaluated the data-driven soft independent modeling of class analogy (DD-SIMCA) model to analyze PSI-MS-based global metabolomics of a urine data matrix to classify PC. The efficiency of DD-SIMCA was analyzed based on the sensitivity and specificity parameters that showed 100% correct classification of the training set, based on only PC and test set samples, based on normal and PC. This analytical methodology is easy to interpret and efficient and does not require any prior information from the healthy individual. This new application of DD-SIMCA in PSI-MS-based metabolomics for PC disease classification could also be extended to other diseases and opens a rapid strategy to discriminate against health problems.

Rapid Diagnosis of Prostate Cancer Disease Progression Using Paper Spray Ionization Mass Spectrometry.

The limitation of prostate specific antigen (PSA) for prostate cancer (PC) diagnosis is well-recognized. The Gleason score (GS) has been the most widely used grading system for prostate tumor differentiation and represents the best-established prognostic indicator for prostate cancer progression. However, a rapid and sensitive noninvasive diagnostic marker that differentiates GS-based prostate cancer disease progression is needed. As PC is becoming a leading cause of cancer related death for men in the U.S. and worldwide, an immediate need exists for an improved, sensitive, noninvasive, and rapid diagnostic test for PC screening. Here, we employed paper spray ionization-mass spectrometry (PSI MS)-based global metabolomics of urine liquid biopsies to distinguish between healthy (negative for any prostate specific health problems) and progressive PC states (low grade PC such as GS6 and high-grade PC such as GS7, GS8, and GS9). For PSI-MS-based direct untargeted metabolic investigation, a raw urine sample was directly pipetted onto a triangular paper substrate, without any additional sample preparation. Multivariate statistical analysis revealed distinct GS-specific metabolic signatures compared to a healthy control. Variable importance in projection from partial least-squares-discriminant analysis showed distinct metabolic patterns that were correlatively elevated with progressive disease and could serve as biomarkers for diagnosis of prostate cancer risk categorization.

Rapid Prostate Cancer Noninvasive Biomarker Screening Using Segmented Flow Mass Spectrometry-Based Untargeted Metabolomics.

Spectrometric methods with rapid biomarker detection capacity through untargeted metabolomics are becoming essential in the clinical cancer research. Liquid chromatography-mass spectrometry (LC-MS) is a rapidly developing metabolomic-based biomarker technique due to its high sensitivity, reproducibility, and separation efficiency. However, its translation to clinical diagnostics is often limited due to long data acquisition times (∼20 min/sample) and laborious sample extraction procedures when employed for large-scale metabolomics studies. Here, we developed a segmented flow approach coupled with high-resolution mass spectrometry (SF-HRMS) for untargeted metabolomics, which has the capability to acquire data in less than 1.5 min/sample with robustness and reproducibility relative to LC-HRMS. The SF-HRMS results demonstrate the capability for screening metabolite-based urinary biomarkers associated with prostate cancer (PCa). The study shows that SF-HRMS-based global metabolomics has the potential to evolve into a rapid biomarker screening tool for clinical research.

A fast and effective approach for the discrimination of garlic origin using wooden-tip electrospray ionization mass spectrometry and multivariate classification.

This paper presents the combination of wooden-tip electrospray ionization mass spectrometry (WTESI-MS) and multivariate pattern recognition methods (principal component analysis, PCA and partial least squares discriminant analysis, PLS-DA) for the rapid and reliable discrimination, via chemical fingerprints, of garlic origin. A total of 312 garlic samples grown in different countries (Brazil, China, Argentina, Spain, and Chile) were studied. The methodology was based on a direct sampling approach, which relies on loading the sample by penetrating the garlic cloves with a pre-wetted wooden tip, followed by direct prompt analysis by WTESI-MS. Thus, no sample preparation is needed, which prevents the degradation of important metabolites and increases the analytical throughput. Parameters that affects the WTESI were optimized and the best performance in terms of signal stability and intensity was achieved using the positive ion mode. Most of the ions in WTESI mass spectra were assigned to amino acids, sugars, organosulfur compounds, and lipids. The discriminative model showed good performance (accuracy rates between 81.9% and 98.6%) and enabled identifying diagnostic ions for garlic samples from different origins. The differentiation and classification of garlic origin is of major importance as this food flavoring product is widely consumed, with worldwide trade representing billions of dollars every year, and is very often the subject of fraud.

Plant growth regulation by seed coating with films of alginate and auxin-intercalated layered double hydroxides.

Auxins are a class of organic substances known as plant-growth regulators, which act on plant physiology, promoting its full development. However, due to the great instability of these substances among the diversity of crops and cultivation environments, it is necessary to seek more efficient modes of application, which lead to a homogeneous distribution and promote a sustained release according to the plants demand. Seed coating, using films containing a biodegradable polymer and auxins intercalated into layered compounds, emerges as a very promising approach to a new form of growth regulator application. Thus, the presented work had three aims: (i) the synthesis and characterization of an organic-inorganic hybrid material containing a layered double hydroxide (LDH) of zinc and aluminum and the synthetic auxin 1-naphthalenoacetic acid (ZnAl-NAA-LDH), (ii) the coating of bean seeds (Phaseolus vulgaris L.) with composite films produced from mixtures of alginate polymer and ZnAl-NAA-LDH, and (iii) the evaluation of the plant response by bioassays. The hybrid ZnAl-NAA-LDH was characterized by a set of analytical techniques, including powder X-ray diffraction, thermogravimetric analysis coupled to differential scanning calorimetry and mass spectrometry, specific surface area measurement, and scanning electron microscopy. Bioassays were performed with the seeds coated with the composite film to assess the germination rate and germination speed index of the seeds, as well as biometric analyses including measurements of root area, root fresh matter, and shoot length of the plants. The bioassay performed in soil pots showed that the alginate film containing ZnAl-NAA-LDH yields an enhancement regarding root area, fresh root matter and shoot length of plants. Thus, films produced from a mixture of alginate and the hybrid material containing the growth regulator intercalated into LDH can be a viable alternative to enhance plant development, which can be included in seed management.

Toxicity to, oviposition and population growth impairments of Callosobruchus maculatus exposed to clove and cinnamon essential oils.

The use of plant essential oils has been shown to efficiently control insect pests of stored beans, significantly reducing the threats associated with synthetic insecticides. Here, we evaluated the potential of applications of essential oils of clove, Syzygium aromaticum L., and cinnamon, Cinnamomum zeylanicum L., to control Callosobruchus maculatus, considered as one of the most cosmopolitan pests of stored beans. Using four combinations of couples (i.e., unexposed couples, exposed females, exposed males, and exposed couples), we also evaluated how sublethal exposure to these essential oils impacted C. maculatus oviposition. Bioassays results revealed that both essential oils exhibited insecticidal activities similar to the synthetic pyrethroid insecticide deltamethrin. Furthermore, oil dosage increments proportionately decreased the growth rate and reduced the losses in bean weight caused by cowpea weevils, and offspring emergence was almost abolished when parents were exposed to the LD20 of each essential oil. Finally, significant oviposition impairments were perceived only in couples where females were exposed (i.e., females exposed and exposed couples) to the LD20 of cinnamon and clove essential oils. Thus, by exhibiting similar insecticidal activities as synthetic insecticides and by significantly affecting the oviposition of sublethally exposed C. maculatus females, the cinnamon and clove essential oils represent valuable tools with potential of integration into the management of C. maculatus infestations.

A flow injection procedure using Layered Double Hydroxide for on line pre-concentration of fluoride.

This work showed a flow system designed with solenoid valves for preconcentration of fluoride using SPADNS method in water samples. The analyte was preconcentrated in a mini-column coated with Layered Double Hydroxides (LDH) used as adsorbent. Then, the fluoride ions were eluted with 0.5molL-1 sodium hydroxide and determined by spectrophotometry. The variables that affect the system such adsorbent mass, type of eluent, solutions flow rate, reagent concentration and pH effect were critically evaluated. Under optimized conditions, the detection limit, coefficient of variation, linear range and preconcentration factor were estimated at 15µgL-1 (99.7% confidence level), 0.8% (500µgL-1, n = 10), 50-500µgL-1 and 10, respectively. The accuracy of the method was evaluated by analysis of ALPHA APS 1076 (Simulated Rain Water) certified material, the values were not significantly different at a 95% level of confidence. The method was applied for fluoride determination in water samples and the levels found were below the maximum values established by Brazilian environmental and health legislations.