Breast-cancer detection using blood-based infrared molecular fingerprints

Background Breast cancer screening is currently predominantly based on mammography, tainted with the occurrence of both false positivity and false negativity, urging for innovative strategies, as effective detection of early-stage breast cancer bears the potential to reduce mortality. Here we report the results of a prospective pilot study on breast cancer detection using blood plasma analyzed by Fourier-transform infrared (FTIR) spectroscopy – a rapid, cost-effective technique with minimal sample volume requirements and potential to aid biomedical diagnostics. FTIR has the capacity to probe health phenotypes via the investigation of the full repertoire of molecular species within a sample at once, within a single measurement in a high-throughput manner. In this study, we take advantage of cross-molecular fingerprinting to probe for breast cancer detection. Methods We compare two groups: 26 patients diagnosed with breast cancer to a same-sized group of age-matched healthy, asymptomatic female participants. Training with support-vector machines (SVM), we derive classification models that we test in a repeated 10-fold cross-validation over 10 times. In addition, we investigate spectral information responsible for BC identification using statistical significance testing. Results Our models to detect breast cancer achieve an average overall performance of 0.79 in terms of area under the curve (AUC) of the receiver operating characteristic (ROC). In addition, we uncover a relationship between the effect size of the measured infrared fingerprints and the tumor progression. Conclusion This pilot study provides the foundation for further extending and evaluating blood-based infrared probing approach as a possible cross-molecular fingerprinting modality to tackle breast cancer detection and thus possibly contribute to the future of cancer screening.

Label-Free Surface Enhanced Raman Scattering (SERS) on Centrifugal Silver Plasmonic Paper (CSPP): A Novel Methodology for Unprocessed Biofluids Sampling and Analysis

Label-free SERS is a powerful bio-analytical technique in which molecular fingerprinting is combined with localized surface plasmons (LSPs) on metal surfaces to achieve high sensitivity. Silver and gold colloids are among the most common nanostructured substrates used in SERS, but since protein-rich samples such as serum or plasma can hinder the SERS effect due to protein–substrate interactions, they often require a deproteinization step. Moreover, SERS methods based on metal colloids often suffer from a poor reproducibility. Here, we propose a paper-based SERS sampling method in which unprocessed human serum samples are first soaked on paper strips (0.4 × 2 cm2), and then mixed with colloidal silver nanoparticles by centrifugation to obtain a Centrifugal Silver Plasmonic Paper (CSPP). The CSPP methodology has the potential to become a promising tool in bioanalytical SERS applications: it uses common colloidal substrates but without the need for sample deproteinization, while having a good reproducibility both in terms of overall spectral shape (r > 0.96) and absolute intensity (RSD < 10%). Moreover, this methodology allows SERS analysis more than one month after serum collection on the paper strip, facilitating storage and handling of clinical samples (including shipping from clinical sites to labs).

Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer

Recent omics analyses of human biofluids provide opportunities to probe selected species of biomolecules for disease diagnostics. Fourier-transform infrared (FTIR) spectroscopy investigates the full repertoire of molecular species within a sample at once. Here, we present a multi-institutional study in which we analysed infrared fingerprints of plasma and serum samples from 1639 individuals with different solid tumours and carefully matched symptomatic and non-symptomatic reference individuals. Focusing on breast, bladder, prostate, and lung cancer, we find that infrared molecular fingerprinting is capable of detecting cancer: training a support vector machine algorithm allowed us to obtain binary classification performance in the range of 0.78–0.89 (area under the receiver operating characteristic curve [AUC]), with a clear correlation between AUC and tumour load. Intriguingly, we find that the spectral signatures differ between different cancer types. This study lays the foundation for high-throughput onco-IR-phenotyping of four common cancers, providing a cost-effective, complementary analytical tool for disease recognition.

Molecular Fingerprinting and Hybridity Authentication in Cowpea Using Single Nucleotide Polymorphism Based Kompetitive Allele-Specific PCR Assay

Optimization of a breeding program for increased genetic gain requires quality assurance (QA) and quality control (QC) at key phases of the breeding process. One vital phase in a breeding program that requires QC and QA is the choice of parents and successful hybridizations to combine parental attributes and create variations. The objective of this study was to determine parental diversity and confirm hybridity of cowpea F1 progenies using KASP (Kompetitive Allele-Specific PCR)-based single nucleotide polymorphism (SNP) markers. A total of 1,436 F1 plants were derived from crossing 220 cowpea breeding lines and landraces to 2 elite sister lines IT99K-573-1-1 and IT99K-573-2-1 as male parents, constituting 225 cross combinations. The progenies and the parents were genotyped with 17 QC SNP markers via high-throughput KASP genotyping assay. The QC markers differentiated the parents with mean efficiency of 37.90% and a range of 3.4–82.8%, revealing unique fingerprints of the parents. Neighbor-Joining cladogram divided the 222 parents into 3 clusters. Genetic distances between parents ranged from 0 to 3.74 with a mean of 2.41. Principal component analysis (PCA) depicted a considerable overlap between parents and F1 progenies with more scatters among parents than the F1s. The differentiation among parents and F1s was best contributed to by 82% of the markers. As expected, parents and F1s showed a significant contrast in proportion of heterozygous individuals, with mean values of 0.02 and 0.32, respectively. KASP markers detected true hybridity with 100% success rate in 72% of the populations. Overall, 79% of the putative F1 plants were true hybrids, 14% were selfed plants, and 7% were undetermined due to missing data and lack of marker polymorphism between parents. The study demonstrated an effective application of KASP-based SNP assay in fingerprinting, confirmation of hybridity, and early detection of false F1 plants. The results further uncovered the need to deploy markers as a QC step in a breeding program.

Reservoir Architecture and Fluid Connectivity in an Abu Dhabi Oil Accumulation

Summary Developing an understanding of reservoir architecture and fluid connectivity is a challenging, but essential task for well, reservoir and facilities management (WRFM). Insight into fluid connectivity (both static and dynamic) can be obtained from molecular fingerprinting of crude oil samples. Oil fingerprinting is also applied for allocation of commingled fluid streams, and in time-lapse mode it can even help to understand fluid flow in the subsurface. Results from fingerprinting studies are directly used as constraints for static and dynamic reservoir models. A basic requirement for most fingerprinting applications is an understanding of the initial, pre-production fluid distribution. The limited availability of pre-production fluids has until now been a major constraint for the widespread application of oil fingerprinting in the industry. Reservoir rock samples contain enough residual hydrocarbons for fluid fingerprinting. Reservoir core and cuttings samples are widely available and thus provide an excellent opportunity to increase the spatial coverage of fluid fingerprints in a reservoir. A major challenge, however, is the accuracy and reproducibility of existing fingerprinting methods, which are insufficient in the chromatographic range of the ‘heavier’, non-volatile, hydrocarbons remaining in reservoir rock samples. This paper describes the application of a new, high resolution, molecular fingerprinting technology that resolves these limitations. This so-called Compound Class Specific Fingerprinting (CCSF) technique has unprecedented accuracy and reproducibility over the full analytical window, which makes it suitable for fingerprinting of both oils and extracts. An added benefit of this approach is that the additional compound class information may help to resolve why fluids are different, as not all differences are related to reservoir connectivity. As a first test, the new CCSF technology has been applied to fluid samples from an offshore field in Abu Dhabi. Two specific aspects are highlighted in this paper: Assessment of vertical compartmentalization and fault transmissibility of four stacked reservoirs in a highly fractured zone. Even in this highly fractured zone, a barrier to vertical fluid flow was identified between the top reservoir and the three underlying reservoirs, which contain slightly different oil. The improved resolution of the CCSF method, combined with the molecular information it provides, made it possible to demonstrate that the fluids in the lower reservoirs are vertically connected and that gravity segregation has created a compositional gradient. These conclusions could not have been reached with existing fingerprinting technologies. Identify opportunities for production monitoring. Some of the reservoirs in this field show strong compositional gradients related to the complex charge history and incomplete fluid mixing. Fluid surveillance of the mid-flank producers will help identify the efficiency of the gas and water injection schemes that are simultaneously applied to this reservoir. In addition, fluid surveillance will help to predict water and/or gas breakthrough.

Aluminum nitride nanophotonics for beyond-octave soliton microcomb generation and self-referencing

Frequency microcombs, alternative to mode-locked laser and fiber combs, enable miniature rulers of light for applications including precision metrology, molecular fingerprinting and exoplanet discoveries. To enable frequency ruling functions, microcombs must be stabilized by locking their carrier-envelope offset frequency. So far, the microcomb stabilization remains compounded by the elaborate optics external to the chip, thus evading its scaling benefit. To address this challenge, here we demonstrate a nanophotonic chip solution based on aluminum nitride thin films, which simultaneously offer optical Kerr nonlinearity for generating octave soliton combs and quadratic nonlinearity for enabling heterodyne detection of the offset frequency. The agile dispersion control of crystalline aluminum nitride photonics permits high-fidelity generation of solitons with features including 1.5-octave spectral span, dual dispersive waves, and sub-terahertz repetition rates down to 220 gigahertz. These attractive characteristics, aided by on-chip phase-matched aluminum nitride waveguides, allow the full determination of the offset frequency. Our proof-of-principle demonstration represents an important milestone towards fully integrated self-locked microcombs for portable optical atomic clocks and frequency synthesizers.

Tasting the Italian Terroir through Craft Beer: Quality and Sensory Assessment of Cascade Hops Grown in Central Italy and Derived Monovarietal Beers

The present study aimed to chemically and sensorially characterize hop samples, cv Cascade, grown in two different Italian regions (Latium and Tuscany) as well as their derived beers by a multi analytical approach. Significant differences in bitter acid, oil and polyphenol content were observed for hop samples according to their origin. Gas chromatography-olfactometry analysis pointed out floral notes for Tuscany samples, where hops from Latium were characterized by spicy and resinous notes, correlated to the presence of sesquiterpenes. Differences in the molecular fingerprinting were also highlighted by Fourier–Transform Infrared Spectroscopy. The differences found in the hops were reflected in the beers, which were clearly recognized as distinct by a sensory panel. Both beer samples were mainly characterized by six aroma compounds (linalool, geraniol and β-damascenone, citronellol, 2-phenylethyl acetate, and 2-phenylethanol), three of which were potentially responsible for the geographic origin of the hops given their significantly different concentrations.

Key Roles of De-Domestication and Novel Mutation in Origin and Diversification of Global Weedy Rice

Agricultural weeds pose great challenges to sustainable crop production, owing to their complex origins and abundant genetic diversity. Weedy rice (WD) infests rice fields worldwide causing tremendous losses of rice yield/quality. To explore WD origins and evolution, we analyzed DNA sequence polymorphisms of the seed shattering genes (sh4 and qsh1) in weedy, wild, and cultivated rice from a worldwide distribution. We also used microsatellite and insertion/deletion molecular fingerprinting to determine their genetic relationship and structure. Results indicate multiple origins of WD with most samples having evolved from their cultivated progenitors and a few samples from wild rice. WD that evolved from de-domestication showed distinct genetic structures associated with indica and japonica rice differentiation. In addition, the weed-unique haplotypes that were only identified in the WD samples suggest their novel mutations. Findings in this study demonstrate the key role of de-domestication in WD origins, in which indica and japonica cultivars stimulated further evolution and divergence of WD in various agroecosystems. Furthermore, novel mutations promote continued evolution and genetic diversity of WD adapting to different environments. Knowledge generated from this study provides deep insights into the origin and evolution of conspecific weeds, in addition to the design of effective measures to control these weeds.

Molecular fingerprinting by single cell clone analysis in adverse drug reaction (ADR) assessment

: Causality assessment for idiosyncratic ADRs mainly relies on epidemiology, signal detection and less often on proven or plausible mechanistic evidence of the drug at a cellular or organ level. Distinct clones of cells can exist within organs of individual patients, some conferring susceptibility to well recognised adverse drug reactions (ADRs). Recent advances in molecular biology has allowed the development of single cell clonal techniques, including single cell RNA sequencing (scRNA-seq) to molecularly fingerprint ADRs and distinguish between distinct clones of cells within organs in individuals, which may confer differing susceptibilities to ADRs. ScRNA-seq permits molecular fingerprinting of some serious ADRs, mainly in the skin, through identification of directly expressed genes (DEG) of interest within specific clones. Overexpressed DEGs provides an opportunity for targeted treatment strategies to be developed. scRNA-seq could be applied to a number of other ADRs involving tissues that can be biopsied/sampled (including skin, liver, kidney, blood, stem cells) as well as providing a molecular basis for rapid screening of potential therapeutic candidates, which may not otherwise be predictable from class of toxicity/organ involvement. . A framework for putative assessment for ADRs using scRNA-seq is proposed as well as speculating on potential regulatory implications for pharmacovigilance and drug development. Molecular fingerprinting of ADRs using scRNA-seq may allow better targeting for enhanced pharmacovigilance and risk minimisation measures for medicines with appropriate benefit risk profiles, although cost-effectiveness and other factors, such as frequency/severity of individual ADRs and population differences will still be relevant.