Non-target Samples Research Articles

Authentication of indigenous Brazilian specialty canephora coffees using smartphone image analysis

The prevention of coffee fraud through the use of digital and intelligence-based technologies is an analytical challenge because depending on the adulterant, visual inspection is unreliable in roasted and ground coffee due to the similarity in color and texture of the materials used. In this work, a 3D-printed apparatus for smartphone image acquisiton is proposed. The digital images are used to authenticate the geographical origin of indigenous canephora coffees produced at Amazon region, Brazil, against canephora coffees from Espírito Santo, Brazil, and to capture the adulteration of indigenous samples. The results evidenced that the technology is favorable to identify the geographical origin and adulteration with multiple substances using smartphone technology. Pure coffees were adulterated with arabica coffee, spent coffee ground, low-quality Canephora coffee, coffee husks, açaí, corn, and soybean in increasing proportions of 10, 20, 30, 40, 50, 60, and 70 %. These adulterants were roasted and grounded similarly to Canephora coffees to mimetize a highly-sophisticated fraud. The images were converted into Red-Green-Blue (RGB) fingerprinting and used as analytical response to construct Data-Driven Soft Independent Modeling of Class Analogy (DD-SIMCA) models. A total of 95 % of all target and non-target samples in the test set were correctely identified, aiding producers and consumers in ensuring accurate labeling and supporting traditional communities economically and culturally. Smartphone-based method demonstrated potential to innovate the coffee safety control representing a new analytical tecnology.

Paired competing neurons improving STDP supervised local learning in Spiking Neural Networks.

Direct training of Spiking Neural Networks (SNNs) on neuromorphic hardware has the potential to significantly reduce the energy consumption of artificial neural network training. SNNs trained with Spike Timing-Dependent Plasticity (STDP) benefit from gradient-free and unsupervised local learning, which can be easily implemented on ultra-low-power neuromorphic hardware. However, classification tasks cannot be performed solely with unsupervised STDP. In this paper, we propose Stabilized Supervised STDP (S2-STDP), a supervised STDP learning rule to train the classification layer of an SNN equipped with unsupervised STDP for feature extraction. S2-STDP integrates error-modulated weight updates that align neuron spikes with desired timestamps derived from the average firing time within the layer. Then, we introduce a training architecture called Paired Competing Neurons (PCN) to further enhance the learning capabilities of our classification layer trained with S2-STDP. PCN associates each class with paired neurons and encourages neuron specialization toward target or non-target samples through intra-class competition. We evaluate our methods on image recognition datasets, including MNIST, Fashion-MNIST, and CIFAR-10. Results show that our methods outperform state-of-the-art supervised STDP learning rules, for comparable architectures and numbers of neurons. Further analysis demonstrates that the use of PCN enhances the performance of S2-STDP, regardless of the hyperparameter set and without introducing any additional hyperparameters.

Real-time PCR methods for identification and stability monitoring of Bifidobacterium longum subsp. longum UABl-14 during shelf life.

Bifidobacterium longum subsp. longum UABl-14™ is an important probiotic strain that was found to support digestive health. Here we present the development and validation of real-time PCR methods for strain-specific identification and enumeration of this important strain. The identification method was evaluated for specificity using 22 target samples and 30 non-target samples. All target samples successfully amplified, while no amplification was observed from any non-target samples including other B. longum strains. The identification method was evaluated for sensitivity using three DNA dilution series and the limit of detection was 2 pg. of DNA. Coupled with a viability dye, the method was further validated for quantitative use to enumerate viable cells of UABl-14. The viability dye treatment (PMAxx) was optimized, and a final concentration of 50 μM was found as an effective concentration to inactivate DNA in dead cells from reacting in PCR. The reaction efficiency, linear dynamic range, repeatability, and reproducibility were also evaluated. The reaction efficiency was determined to be 97.2, 95.2, and 95.0% with R2 values of 99%, in three replicates. The linear dynamic range was 1.3 × 102 to 1.3 × 105 genomes. The relative standard deviation (RSD%) for repeatability ranged from 0.03 to 2.80, and for reproducibility ranged from 0.04 to 2.18. The ability of the validated enumeration method to monitor cell counts during shelf life was evaluated by determining the viable counts and total counts of strain UABl-14 in 18 multi-strain finished products. The viable counts were lower than label claims in seven products tested post-expiration and were higher than label claims in products tested pre-expiration, with a slight decrease in viable counts below label claim in three samples that were tested 2-3 months pre-expiration. Interestingly, the total counts of strain UABl-14 were consistently higher than label claims in all 18 products. Thus, the method enables strain-specific stability monitoring in finished products during shelf life, which can be difficult or impossible to achieve using the standard plate count method. The validated methods allow for simultaneous and cost-effective identification and enumeration of strain UABl-14 and represent an advancement in the quality control and quality assurance of probiotics.

In Vivo Evaluation of an Ivermectin and Allicin Combination Treatment for Eradicating Poultry Red Mite.

A safe and effective method for eradicating poultry red mite (PRM; Dermanyssus gallinae) is urgently needed, as existing treatments show a low efficacy or hazardous effects on chickens. We evaluated the efficacy of a combined treatment with ivermectin and allicin (IA) against PRMs in chickens and drug residues in non-target samples. The efficiency of PRM eradication by IA was compared with those of natural acaricides in vitro. Ivermectin (0.25 mg/mL) + allicin (1 mg/mL) (IA compound) was sprayed on isolator housing hens with PRMs. The PRM mortality rate, clinical symptoms, and ivermectin residue in hens were analyzed. IA showed the highest PRM-eradication efficacy among all tested compounds in vitro. The insecticidal rates of IA were 98.7%, 98.4%, 99.4%, and 99.9% at 7, 14, 21, and 28 days of treatment, respectively. After inoculating PRMs, hypersensitivity, itching, and a pale-colored comb were observed in control animals, which were absent in treated hens. No clinical symptoms from IA and ivermectin residues were found in hens. IA effectively exterminated PRMs, demonstrating its potential for industrial use to treat PRMs.

Development and validation of a multiplex real-time PCR assay for accurate authentication of common buckwheat (Fagopyrum esculentum) and tartary buckwheat (Fagopyrum tataricum) in food

The increased demand for accurate information on ingredients listed on food product labels requires identifying a plant's species of origin. To efficiently and rapidly discriminate between common buckwheat (Fagopyrum esculentum) and tartary buckwheat (Fagopyrum tataricum), here we developed a multiplex real-time PCR assay. This assay included target species-specific and shared primer/probe sets representing the two buckwheat species. Multiplex real-time PCR analyses specifically amplified the target species without detectable cross-reactivity with nontarget plant samples. The detection limit was 1% for common buckwheat in tartary buckwheat and 2% for tartary buckwheat in common buckwheat. The method was verified through application to processed products and was confirmed through comparison with the food label information. The species identified were identical to those declared on the product label. Therefore, this multiplex real-time PCR assay will serve as a sensitive and specific diagnostic tool for detection of buckwheat species in foods.

Nanoparticle-Based Plasmonic Biosensor for the Unamplified Genomic Detection of Carbapenem-Resistant Bacteria.

Antimicrobial resistance (AMR) is a global public health issue, and the rise of carbapenem-resistant bacteria needs attention. While progress is being made in the rapid detection of resistant bacteria, affordability and simplicity of detection still need to be addressed. This paper presents a nanoparticle-based plasmonic biosensor for detecting the carbapenemase-producing bacteria, particularly the beta-lactam Klebsiella pneumoniae carbapenemase (blaKPC) gene. The biosensor used dextrin-coated gold nanoparticles (GNPs) and an oligonucleotide probe specific to blaKPC to detect the target DNA in the sample within 30 min. The GNP-based plasmonic biosensor was tested in 47 bacterial isolates: 14 KPC-producing target bacteria and 33 non-target bacteria. The stability of GNPs, confirmed by the maintenance of their red appearance, indicated the presence of target DNA due to probe-binding and GNP protection. The absence of target DNA was indicated by the agglomeration of GNPs, corresponding to a color change from red to blue or purple. The plasmonic detection was quantified with absorbance spectra measurements. The biosensor successfully detected and differentiated the target from non-target samples with a detection limit of 2.5 ng/μL, equivalent to ~103 CFU/mL. The diagnostic sensitivity and specificity were found to be 79% and 97%, respectively. The GNP plasmonic biosensor is simple, rapid, and cost-effective in detecting blaKPC-positive bacteria.

Validation of a Real-Time PCR Assay for Identification of Fresh and Processed Carica papaya Botanical Material: Using Synthetic DNA to Supplement Specificity Evaluation.

Several commercially important botanicals have a lack of diagnostic testing options that can quickly and unambiguously identify materials of different matrices. Real-time PCR can be a useful, orthogonal approach to identification for its exceptional specificity and sensitivity. Carica papaya L. is a species with a lack of available identification methods, and one which features two distinct commercially relevant matrices: fresh fruit and powdered fruit extract. In this study, we demonstrate the successful design and validation of a real-time PCR assay for detection of papaya DNA extracted from the two matrices. We also propose a technique that can be used during exclusivity panel construction, when genuine botanical samples are not available for certain species: substitution with synthetic DNA. We demonstrate the use of this material to complete a comprehensive specificity evaluation and confidently determine suitable Ct cutoff values. Further, we demonstrate how ddPCR can be used to determine the copy number of the target sequence in a set amount of genomic DNA, to which synthetic DNA samples can be corrected, and how it can verify specificity of the primers and probe. Through the presentation of successful assay validation for papaya detection, this work serves as a guideline for how to approach specificity evaluation when non-target botanical samples are difficult to obtain and otherwise may not have been included in the exclusivity panel.

Rapid PCR-lateral flow assay for the onsite detection of Atlantic white shrimp

The Atlantic white shrimp (Litopenaeus setiferus) is of great economic importance to the United States and risk being substituted with imported species due to a shortage in domestic production. To improve the current methods used for the identification of the Atlantic white shrimp species, we designed and validated a robust multiplex PCR-lateral flow assay for the onsite identification of L. setiferus. The standardized assay was validated using a miniaturized, low-cost PCR instrument with 68 shrimp, prawn, and fish samples, spread over fourteen seafood species. L. setiferus was simultaneously amplified by the multiplex assay to give three visual bands, which distinguished it from other species having either one or two bands on the dipstick. The standardized assay showed 100% inclusivity for target L. setiferus samples, 100% exclusivity for non-target samples and can be completed in less than two hours. The assay standardized in this study can be used for onsite testing of L. setiferus samples at processing facilities, restaurants, and wholesalers' facilities.

Corrigendum for PM 7/149 (1) Anoplophora glabripennis and Anoplophora chinensis

Corrigendum for <scp>PM</scp> 7/149 (1) <i>Anoplophora glabripennis</i> and <i>Anoplophora chinensis</i>

Enhanced Specificity in Loop-Mediated Isothermal Amplification with Poly(ethylene glycol)-Engrafted Graphene Oxide for Detection of Viral Genes.

Loop-mediated isothermal amplification (LAMP) is a nucleic acid amplification method that allows the simple, quick, and low-cost detection of various viral genes. LAMP assays are susceptible to generating non-specific amplicons, as high concentrations of DNA primers can give rise to primer dimerization and mismatched hybridizations, resulting in false-positive signals. Herein, we reported that poly(ethylene glycol)-engrafted nanosized graphene oxide (PEG-nGO) can significantly enhance the specificity of LAMP, owing to its ability to adsorb single-stranded DNA (ssDNA). By adsorbing surplus ssDNA primers, PEG-nGO minimizes the non-specific annealing of ssDNAs, including erroneous priming and primer dimerization, leading to the enhanced specificity of LAMP. The detection of complementary DNAs transcribed from the hepatitis C virus (HCV) RNA was performed by the PEG-nGO-based LAMP. We observed that the inclusion of PEG-nGO significantly enhances the specificity and sensitivity of the LAMP assay through the augmented difference in fluorescence signals between the target and non-target samples. The PEG-nGO-based LAMP assay greatly facilitates the detection of HCV-positive clinical samples, with superior precision to the conventional quantitative real-time PCR (RT-qPCR). Among the 20 clinical samples tested, all 10 HCV-positive samples are detected as positive in the PEG-nGO-based LAMP, while only 7 samples are detected as HCV-positive in the RT-qPCR. In addition, the PEG-nGO-based LAMP method significantly improves the detection precision for the false-positive decision by 1.75-fold as compared to the LAMP without PEG-nGO. Thus, PEG-nGO can significantly improve the performance of LAMP assays by facilitating the specific amplification of target DNA with a decrease in background signal.

Abstract 5414: RNA sequencing reveals that CYP3A5 siRNA treatment induces cell cycle blockade and senescence in MDAPCa2b human prostate cancer cells

Abstract Background: Previously we have demonstrated that CYP3A5 inhibition blocks prostate cancer (PC) cell growth partly by attenuating androgen receptor (AR) activation and downstream signaling. We further investigated whether CYP3A5 inhibition blocks PC cell growth independently of AR signaling. Initially, most PCs respond to androgen deprivation therapy (ADT), but eventually PC becomes castration resistant and does not respond to ADT. With very limited options available for patients with castration resistant prostate cancer (CRPC), there is an urgent need for the development of novel targeted therapies for this subtype of PC. Additionally, understanding the role of CYP3A5 as promoter of PC growth in African Americans (AA) is very relevant as AAs preferentially carry wild type CYP3A5 gene, often present with aggressive disease, and have higher mortality rate versus Caucasian (CA) patients, who typically express the mutant CYP3A5. Method: We used MDAPCa2b PC cell line of AA origin carrying one copy of wild type CYP3A5 for our study. After inhibiting the CYP3A5 using siRNA pool of 3 siRNAs, we performed Illumina RNA sequencing. Differentially expressed genes (DEGs) between non-target and CYP3A5 siRNA triplicate samples were identified using DESeq2, at a false discovery rate of adjusted p &amp;lt; 0.05. Furthermore, KEGG pathway analysis was performed to identify the roles of the differentially expressed genes in regulating prostate cancer growth. Results: We identified 1814 DEGs after inhibiting CYP3A5 using siRNA pool in MDAPCa2b cells, 825 of which increased or decreased expression greater than two-fold. The differentially down-regulated genes associate with several growth regulatory pathways: cell cycle progression (39), cellular senescence (16) DNA replication (18) and base excision repair (9). Additionally, we identified that CYP3A5 siRNA downregulates several genes which are dysregulated (including oncogenes and tumor suppressors) in different cancer type including RAS, c-Met, ERBB2, FGFR2, cyclin E, p53, Myc, PTEN, RARβ and CDK2. The upregulated genes correspond to two pathways, retinol metabolism pathway (arrests proliferation) and steroid hormone biosynthesis. We also identified several unique genes which are down regulated with CYP3A5 siRNA treatment like Glo1, FoxM1 (often upregulated in several cancers) and Tk1 (marker for chemotherapy sensitivity). Conclusion: CYP3A5 siRNA inhibits several genes involved in cell growth and proliferation. Targeting CYP3A5 represents a potential novel therapeutic approach, especially for AAs expressing wild type CYP3A5. Citation Format: Richard L. Tillett, Shirley Shen, Edwin C. Oh, Oscar B. Goodman Jr., Ranjana Mitra. RNA sequencing reveals that CYP3A5 siRNA treatment induces cell cycle blockade and senescence in MDAPCa2b human prostate cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5414.

Detection of Unamplified E. coli O157 DNA Extracted from Large Food Samples Using a Gold Nanoparticle Colorimetric Biosensor.

Rapid detection of foodborne pathogens such as E. coli O157 is essential in reducing the prevalence of foodborne illness and subsequent complications. Due to their unique colorimetric properties, gold nanoparticles (GNPs) can be applied in biosensor development for affordability and accessibility. In this work, a GNP biosensor was designed for visual differentiation between target (E. coli O157:H7) and non-target DNA samples. Results of DNA extracted from pure cultures indicate high specificity and sensitivity to as little as 2.5 ng/µL E. coli O157 DNA. Further, the biosensor successfully identified DNA extracted from flour contaminated with E. coli O157, with no false positives for flour contaminated with non-target bacteria. After genomic extraction, this assay can be performed in as little as 30 min. In addition, food sample testing was successful at detecting approximately 103 CFU/mL of E. coli O157 magnetically extracted from flour after only a 4 h incubation step. As a proof of concept, these results demonstrate the capabilities of this GNP biosensor for low-cost and rapid foodborne pathogen detection.

Learning Target Class Feature Subspace (LTC-FS) Using Eigenspace Analysis and N-ary Search-Based Autonomous Hyperparameter Tuning for OCSVM

Existing dimensionality reduction (DR) techniques such as principal component analysis (PCA) and its variants are not suitable for target class mining due to the negligence of unique statistical properties of class-of-interest (CoI) samples. Conventionally, these approaches utilize higher or lower eigenvalued principal components (PCs) for data transformation; but the higher eigenvalued PCs may split the target class, whereas lower eigenvalued PCs do not contribute significant information and wrong selection of PCs leads to performance degradation. Considering these facts, the present research offers a novel target class-guided feature extraction method. In this approach, initially, the eigendecomposition is performed on variance–covariance matrix of only the target class samples, where the higher- and lower-valued eigenvectors are rejected via statistical analysis, and the selected eigenvectors are utilized to extract the most promising feature subspace. The extracted feature-subset gives a more tighter description of the CoI with enhanced associativity among target class samples and ensures the strong separation from nontarget class samples. One-class support vector machine (OCSVM) is evaluated to validate the performance of learned features. To obtain optimized values of hyperparameters of OCSVM a novel [Formula: see text]-ary search-based autonomous method is also proposed. Exhaustive experiments with a wide variety of datasets are performed in feature-space (original and reduced) and eigenspace (obtained from original and reduced features) to validate the performance of the proposed approach in terms of accuracy, precision, specificity and sensitivity.

Occurrence and distributions of human-associated markers in an impacted urban watershed.

Numerous genetic markers for microbial source tracking (MST) have been evaluated by testing a panel of target and nontarget faecal samples. However, the performance of MST markers may vary between faecal and water samples, thereby resulting in inaccurate water quality assessment. In this study, a 30-day sampling study was conducted in an urban river impacted by human- and sewage-associated pollution to evaluate the performance of different human-associated markers in environmental water. Additionally, marker decay was assessed via a microcosms approach. Overall, Bacteroidales 16sRNA and crAssphage markers exhibited higher prevalence in the study area, and their detection frequencies exceeded 90%. In contrast, Bacteroidales protein markers exhibited poor detection frequencies compared to other markers, with the prevalence of Hum2 and Hum163 reaching only 63% and 84%, respectively. Regarding marker abundance, there was no significant difference in the detection concentrations between Bacteroidales 16sRNA and crAssphage markers (p>0.05); however, the concentrations of Bacteroidales protein markers were nearly 1 order of magnitude lower than those of other MST markers. The microcosm experiments indicated that the decay rate of crAssphage markers was significantly lower than that of other bacterial target markers, which may improve their detectability when the pollution source is located far from the sampling site. Due to the observed differences in performance and decay patterns among Bacteroidales 16sRNA, crAssphage, and Bacteroidales protein markers, we recommend the simultaneous use of multiple markers from different target microorganisms to obtain a more comprehensive understanding of the pollution sources. This approach would also provide an accurate assessment of pollution levels and health risks.

A One-Class Classification Method for Human Gait Authentication Using Micro-Doppler Signatures

In this letter, a radar-based gait authentication method is proposed. We focus on the overfitting problem on the target category caused by limited training data in authentication models and propose a one-class classification model to alleviate this problem. The effectiveness of such model is verified by establishing a radar-based gait dataset, which is composed of gait micro-Doppler spectrograms derived from nine human subjects. The experimental results demonstrate that, under the condition of limited training data, the performances of an authentication model degrade because misclassification of the non-target samples easily occurs. The proposed method effectively avoids this risk,performing the other existing authentication and one-class classification \textcolor{red}{methods} on the metric Equal Error Rate.

Assessing the faecal source sensitivity and specificity of ruminant and human genetic microbial source tracking markers in the central Ethiopian highlands

This study tested genetic microbial source tracking (MST) methods for identifying ruminant‐ (BacR) and human‐associated (HF183/BacR287, BacHum) bacterial faecal contaminants in Ethiopia in a newly created regional faecal sample bank (n = 173). BacR performed well, and its marker abundance was high (100% sensitivity (Sens), 95% specificity (Spec), median log10 8·1 marker equivalents (ME) g−1 ruminant faeces). Human‐associated markers tested were less abundant in individual human samples (median: log10 5·4 and 4·2 (ME + 1) g−1) and were not continuously detected (81% Sens, 91% Spec for BacHum; 77% Sens, 91% Spec for HF183/BacR287). Furthermore, the pig‐associated Pig2Bac assay was included and performed excellent (100% Sens, 100% Spec). To evaluate the presence of MST targets in the soil microbiome, representative soil samples were tested during a whole seasonal cycle (n = 60). Only BacR could be detected, but was limited to the dry season and to sites of higher anthropogenic influence (log10 3·0 to 4·9 (ME + 1) g−1 soil). In conclusion, the large differences in marker abundances between target and non‐target faecal samples (median distances between distributions ≥log10 3 to ≥log10 7) and their absence in pristine soil indicate that all tested assays are suitable candidates for diverse MST applications in the Ethiopian area.

A Method to Evaluate In Vivo CD8+ T Cell Cytotoxicity in a Murine Model.

Herein, a method to measure in vivo CD8+ T cell cytotoxicity in a murine model is presented. The activation of a strong CD8+ T cell response is paramount when designing vaccines to tackle intracellular infections and for cancer therapy. CD8+ T cells can directly kill infected and transformed cells and are directly associated with beneficial protection in many disease models. CD8+ T cell cytotoxicity can be measured using multiple methods including measuring IFNγ production by ELISPOT or measuring intracellular cytokines or cytotoxic granules by flow cytometry. However, to determine the ability of CD8+ T cells to kill their target in the context of its cognate receptor and in their native environment, the in vivo cytotoxic T cell assay (in vivo CTL) is ideal. The in vivo CTL assay provides a snapshot of the whole ability of the host to kill "Target" cells by measuring the loss of injected target cells relative to "Non-target" cells. The assay involves isolating splenocytes from donor mice, forming "Target" and "Non-target" cellular samples and injecting them intravenously into naïve and experimental mice at a chosen time-point in the experiment. Mice are humanely sacrificed 20h later, and their spleens are excised and processed for flow cytometric analysis. The extent of "Target" cell killing relative to "Non-target" cells is determined by comparing the surviving proportions of these cells among experimental mice relative to naïve mice. The in vivo CTL assay is a rapid, sensitive, and reliable method to measure the potency of CD8+ T cells in their host to kill their target.

Comparison of the performance of the main real-time and conventional PCR detection tests for ‘Candidatus Liberibacter’ spp., plant pathogenic bacteria causing the Huanglongbing disease in Citrus spp.

Huanglongbing disease affects the Rutaceae family and is associated with three phloem-limited bacterium species: Candidatus Liberibacter asiaticus, africanus and americanus. These species are considered quarantine pathogens in the world, and pose major risks for citrus production and industry. Due to the low titer and the uneven distribution of the bacteria within its host plant, conventional PCR detection protocols can lead to false negative results, especially for early detection. Herein, three real-time PCR diagnostic methods recommended by the EPPO and FAO for asiaticus and africanus species detection were evaluated for their performance and compared with a conventional duplex PCR. Assessments were done as part of an international cooperative project under the EUPHRESCO guidance. Intra-laboratory assessment of the analytical specificity and analytical sensitivity was performed on 33 target or non-target DNA samples and seven target DNA samples were used to determine the sensitivity. Thereafter, repeatability, reproducibility, and concordance odds ratio were assessed on 20 target or non-target DNA samples through a collaborative test performance study organized among eight international laboratories. Results showed that the Li protocol proved to be the best method for asiaticus and africanus species detection, along with the conventional duplex PCR; whereas the Morgan protocol showed high performance only for asiaticus species. Interlaboratory reproducibility was high, suggesting that these real-time PCR methods can be readily transferred to diagnostic laboratories.

Efficient differentiation of Nocardia farcinica, Nocardia cyriacigeorgica and Nocardia beijingensis by high-resolution melting analysis using a novel locus

Accurate identification of Nocardia species remains a challenge due to the complexities of taxonomy and insufficient discriminatory power of traditional techniques. We report the development of a molecular technique that utilizes real-time PCR-based high-resolution melting (HRM) analysis for differentiation of the most common Nocardia species. Based on a novel fusA-tuf intergenic region sequence, Nocardia farcinica , Nocardia cyriacigeorgica and Nocardia beijingensis were clearly distinguished from one another by HRM analysis. The limit of detection of the HRM assay for purified Nocardia spp. DNA was at least 10 fg. No false positives were observed for specificity testing of 20 non-target clinical samples. In comparison to established matrix-assisted laser desorption/ionization-time of flight MS, the HRM assay improved the identification of N. beijingensis . Additionally, all the products of PCR were verified by direct sequencing. In conclusion, the developed molecular assay allows simultaneous detection and differentiation of N. farcinica , N. cyriacigeorgica and N. beijingensis with high sensitivity and specificity.

Different strategies for class model optimization. A comparative study

The Class Modelling (CM) approaches like Soft Independent Modelling of Class Analogy (SIMCA) aim at developing a mathematical model for determination of belongingness of new samples to the studied classes. The main feature of CM is that for each target class an individual model is constructed. CM is widely exploited, e.g., in the food and drug quality testing and authenticity or origin verification. It is well known that the most critical stage in construction of a class model is optimization of its parameters. There exist two basic strategies for optimization of class model, i.e., the “compliant” strategy where the target and nontarget class samples are required in the model optimization process, and the “rigorous” strategy where only the target class samples are used. Since the nontarget class samples are usually available, the compliant scenario is more often explored. In the present study, four different resampling methods for optimization of the SIMCA model (applied in both, a compliant and a rigorous fashion) are thoroughly compared. Each method is tested in combination with two distinct decision threshold estimation criteria: i) an a priori fixing it based on a desired statistical significance level and ii) optimizing it through appropriate data-driven procedures. For the sake of a comprehensive assessment of the studied strategies, several real-world datasets are exploited and final results are post-processed by means of ANalysis Of VAriance (ANOVA). The study reveals that both, a compliant approach with an optimized decision threshold and a rigorous approach with a fixed decision threshold can yield satisfactory classification outcomes, no matter which resampling technique is used.Finally, it is shown how unrepresentativeness of the nontarget classes can lead to the biased classification models when a compliant optimization is carried out. Therefore, a rigorous optimization can be considered as a safer option for the SIMCA model parameter tuning.