Wheat gluten intake increases weight gain and adiposity associated with reduced thermogenesis and energy expenditure in an animal model of obesity.

BACKGROUND/OBJECTIVES: The association between gluten and body weight is inconsistent. Previously, we showed that a gluten-free diet reduces weight gain without changing food intake in mice fed high-fat diets. In the present study, we investigated the effects of gluten intake on fat metabolism, thermogenesis and energy expenditure in mice fed a standard or high-fat diet. METHODS: Mice were fed four different experimental diets during 8 weeks: a control-standard diet (CD), a CD added with 4.5% of wheat gluten (CD-G), a high-fat diet (HFD) and a HFD added with 4.5% of wheat gluten (HFD-G). After 8 weeks, the mice received (99m)Tc-radiolabeled gluten orally to study gluten absorption and biodistribution or they underwent indirect calorimetry. After killing, subcutaneous and brown adipose tissues (SAT and BAT) were collected to assess thermogenesis-related protein expression. Lipid metabolism was studied in adipocyte cultures from the four groups. RESULTS: Despite having had the same energy intake, CD-G and HFD-G mice exhibited increased body weight and fat deposits compared with their respective controls. (99m)Tc-GLU or its peptides were detected in the blood, liver and visceral adipose tissue, suggesting that gluten can even reach extraintestinal organs. Uncoupling protein-1 expression was reduced in the BAT of HFD-G and in the SAT of CD-G and HFD-G mice. Indirect calorimetry showed lower oxygen volume consumption in CD-G and HFD-G groups compared with their controls. In HFD mice, daily energy expenditure was reduced with gluten intake. Gluten also reduced adiponectin, peroxisome proliferator-activated receptor (PPAR)-α and PPARγ and hormone-sensitive lipase in cultures of isolated adipocytes from HFD mice, whereas in the CD-G group, gluten intake increased interleukin-6 expression and tended to increase that of tumor necrosis factor. CONCLUSIONS: Wheat gluten promotes weight gain in animals on both HFD and CD, partly by reducing the thermogenic capacity of adipose tissues.

Potential biomarkers as a predictive factor of response to primary chemotherapy in breast cancer patients.

In this study, we identified miRNAs and their potential mRNA targets that are intricately linked to primary chemotherapy response in patients with invasive ductal carcinomas. A cohort of individuals diagnosed with advanced invasive breast ductal carcinoma who underwent primary chemotherapy served as the cornerstone of our study. We conducted a comparative analysis of microRNA expression among patients who either responded or did not respond to primary systemic therapy. To analyze the correlation between the expression of the whole transcriptome and the 24 differentially expressed (DE) miRNAs, we harnessed the extensive repository of The Cancer Genome Atlas (TCGA) database. We mapped molecular mechanisms associated with these miRNAs and their targets from TCGA breast carcinomas. The resultant expression profile of the 24 DE miRNAs emerged as a potent and promising predictive model, offering insights into the intricate dynamics of chemotherapy responsiveness of advanced breast tumors. The discriminative analysis based on the principal component analysis identified the most representative miRNAs across breast cancer samples (miR-210, miR-197, miR-328, miR-519a, and miR-628). Moreover, the consensus clustering generated four possible clusters of TCGA patients. Further studies should be conducted to advance these findings.

Objective chemical fingerprinting of oil spills by partial least-squares discriminant analysis.

An objective method based on partial least-squares discriminant analysis (PLS-DA) was used to assign an oil lump collected on the coastline to a suspected source. The approach is an add-on to current US and European oil fingerprinting standard procedures that are based on lengthy and rather subjective visual comparison of chromatograms. The procedure required an initial variable selection step using the selectivity ratio index (SRI) followed by a PLS-DA model. From the model, a "matching decision diagram" was established that yielded the four possible decisions that may arise from standard procedures (i.e., match, non-match, probable match, and inconclusive). The decision diagram included two limits, one derived from the Q-residuals of the samples of the target class and the other derived from the predicted y of the PLS model. The method was used classify 45 oil lumps collected on the Galician coast after the Prestige wreckage. The results compared satisfactorily with those from the standard methods.

Rosmarinic and chlorogenic acid, isolated from ferns, suppress stem cell damage induced by hydrogen peroxide.

OBJECTIVES: Evaluating the effects of rosmarinic (RA) and cryptochlorogenic (CGA) acids isolated from Blechnum binervatum extract on stem cell viability, toxicity and the protective effect on oxidative cell damage. METHODS: MTT and LDH methods were employed, using stem cells from teeth. RA and CGA were evaluated at 100, 250 and 500 µM. The negative effect of hydrogen peroxide (H2O2) (200-2200 µM) and the capacity of RA and CGA (10-100 µM) as protective agents were also evaluated. DAPI followed by fluorescent microscopy was employed to photograph the treated and untreated cells. KEY FINDINGS: At all tested concentrations, RA and CGA demonstrated the ability to maintain cell viability, and with no cytotoxic effects on the treated stem cells. RA also induced an increase of the cell viability and a reduction in cytotoxicity. H2O2 (1400 µM) induced >50% of cytotoxicity, and both compounds were capable of suppressing H2O2 damage, even at the lowest concentration. At 100 µM, in H2O2 presence, total cell viability was observed through microscope imaging. CONCLUSIONS: These findings contribute to the continued research into natural substances with the potential for protecting cells against oxidative injury, with the consideration that RA and CGA are useful in the regeneration of damaged stem cells.

Validation of the online PREDICT tool in a cohort of early breast cancer in Brazil.

PREDICT is a tool designed to estimate the benefits of adjuvant therapy and the overall survival of women with early breast cancer. The model uses clinical, histological, and immunohistochemical variables. This study aimed to evaluate the model's performance in a Brazilian population. We assessed the discrimination and calibration of the PREDICT model to estimate overall survival (OS) in five and ten years of follow-up in a cohort of 873 women with early breast cancer diagnosed from January 2001 to December 2016. A total of 743 patients had estrogen receptor (ER)-positive and 130 had ER-negative tumors. The area under the receiver operating characteristic (ROC) curve (AUC) for discrimination was 0.72 (95%CI: 0.66-0.78) at five years and 0.67 (95%CI: 0.61-0.72) at ten years for women with ER-positive tumors. The AUC was 0.72 (95%CI: 0.62-0.81) at five years and 0.67 (95%CI: 0.54-0.77) at ten years for women with ER-negative tumors. The predicted survival in ER-positive tumors was 91.0% (95%CI: 90.2-91.6%) at five years and 79.3% (95%CI: 77.7-81.0%) at ten years, and the observed survival 90.7% (95%CI: 88.6-92.9%) and 77.2% (95%CI: 73.4-81.4%), respectively. The predicted survival in ER-negative tumors was 84.5% (95%CI: 82.5-86.6%) at five years and 75.0% (95%CI: 71.6-78.5%) at ten years, and the observed survival 76.3% (95%CI: 69.1-84.3%) and 67.9% (95%CI: 58.6-78.6%), respectively. In conclusion, PREDICT was accurate to estimate OS in women with ER-positive tumors and overestimated the OS in women with ER-negative tumors.

Obesity and high neutrophil-to-lymphocyte ratio are prognostic factors in non-metastatic breast cancer patients.

Obesity has been associated with an increased risk of breast cancer recurrence and death. Some readily available biomarkers associated with systemic inflammation have been receiving attention as potential prognostic indicators in cancer, including neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR). This study aimed to explore the correlation between body mass index (BMI) and invasive breast cancer and the association of NLR, PLR, and BMI with breast cancer outcomes. We undertook a retrospective study to evaluate patients treated for breast cancer over 14 years. Clinicopathological data was obtained before receiving any treatment. Of the 1664 patients included with stage I-III, 567 (34%) were obese (BMI≥30 kg/m2). Obese patients had larger tumors compared to non-obese patients. Higher BMI was associated with recurrence and worse survival only in patients with stage I disease. NLR and PLR were classified into high and low level groups. The NLRhigh (NLR>4) was found to be an independent prognostic factor for recurrence and mortality, while the PLRhigh (PLR>150) group had no impact on survival. A subgroup of patients with NLRhigh and BMIhigh had the worst disease-free survival (P=0.046), breast cancer-specific survival (P<0.001), and overall survival (P=0.006), compared to the other groups. Patients with early-stage breast cancer bearing NLRhigh and BMIhigh had worse outcomes, and this might be explained by the dysfunctional milieu of obesity in adipose tissue and its effects on the immune system. This study highlights the importance of lifestyle measures and the immune system interference with clinical outcomes in the early breast cancer setting.

Self organizing maps for analysis of polycyclic aromatic hydrocarbons 3-way data from spilled oils.

In this paper, the application of a new method based on self-organizing maps (SOM; termed MOLMAP, molecular map of atom-level properties) to handle 3-way data generated in a monitoring environmental study is presented. The study comprised 50 polycyclic aromatic hydrocarbons (PAHs) analyzed in samples derived from the weathering of six oil products (four crude oils and two fuel oils) spilled under controlled conditions for about 4 months. MOLMAP yielded useful information on each mode of the data cube: weathering samples, spilled oil products, and PAHs. Thus, the different behaviors of the six oils were ascertained, along with their particular evolution on time, and their weathering patterns were studied in terms of the original PAHs. Thus, the two heaviest products (two fuel oils) were characterized by two neurons whose more relevant weights were associated to heavy PAHs, as C(1)-fluoranthene, C(2)-fluoranthene, benzo(ghi)perylene, and dibenz(ah)anthracene. The six spilled products were projected on different regions on both the MOLMAP-SOM and a subsequent principal components analysis (PCA) scatter plot, developed using the so-called MOLMAP-scores. Besides, it was possible to further differentiate between unweathered, or slightly weathered, samples and the most weathered ones. The more relevant PAHs characterizing those samples were assessed studying the weights of the neurons in which the samples got projected.

Fighting COVID-19.

The current COVID-19 pandemic caused by the novel coronavirus (SARS-CoV2) poses a threat to global health owing to its high rate of spread and severe forms of respiratory infection. The lack of vaccines and antivirals prevents clinical strategies against the disease, creating an emerging need for the development of safe and effective treatments. Strategies for vaccine development include complete vaccines against viruses, subunits, and nucleic acids, but are still in their early stages. Studies carried out to date on possible SARS-CoV2 drug targets highlight glycoprotein S, Mpro (main protease or protease type 3C), and a member of the transmembrane serine protease II families (TMPRSS2). However, due to the pandemic state, priority is given to marketed drugs. These include chloroquine (CQ), hydroxychloroquine (HCQ), nitazoxanide, remdesivir, Lopinavir/ritonavir (LPV / r), in addition to treatment with convalescent plasma. But, therapeutic specific effects against SARS-CoV2 have not yet been verified. Most of the information obtained about treatment is based on preliminary and limited studies. We conclude that, at this time of emergency, the search for new therapies is more urgent due to the need to save lives. Thus, we point out as interesting targets for future more specific research: glycoprotein S, Mpro, and TMPRSS2.

Oral resveratrol supplementation improves Metabolic Syndrome features in obese patients submitted to a lifestyle-changing program.

AIMS: The aim of the present study was to evaluate the oral resveratrol effects associated with diet and physical training changes on anthropometric and biochemical parameters. MAIN METHODS: 25 individuals aged from 30 to 60 years old; with Body Mass Index (BMI) ≥ 30 kg/m2 were included in the study. Following the primary evaluation (anthropometric and clinical), the patients were randomly divided into 2 groups: (1) Placebo: Physical activity program + Diet + Placebo; (2) Resveratrol: Physical activity program + Diet + Resveratrol (RVS) (250 mg/day) for three months. Anthropometric and biochemical parameters were evaluated at baseline and after the treatment period. KEY FINDINGS: The main findings showed that the resveratrol supplementation improved total cholesterol (TC), High-density Lipoprotein cholesterol (HDL-c), Very-low density Lipoprotein cholesterol (VLDL-c), urea, creatinine and albumin serum levels. SIGNIFICANCE: These findings indicate that this polyphenol may be an option to potentiate the beneficial effects induced by dietary and physical activity programs in the Metabolic Syndrome (MetS) treatment.

Comparison of single-reflection near-infrared and attenuated total reflection mid-infrared spectroscopies to identify and monitor hydrocarbons spilled in the marine environment.

The capability of single-reflection near-IR (NIR) spectroscopy to differentiate, characterize and monitor the fate of a set of hydrocarbons spilled in the marine environment was compared with that of multiple-reflection horizontal attenuated total reflection mid-IR (ATR-MIR) spectroscopy. Multivariate pattern recognition techniques [principal component analysis (PCA), multivariate polynomial regression, cluster analysis and potential curves] were applied to unravel the major trends of the weathering processes of four generic types of crude oils and two heavy fuel oils spilled under controlled conditions for almost 4 months. A chemical interpretation of the NIR spectra related the weathering processes and the PCA loadings, which had not already been done in the literature. Weathering for both light and heavy products was characterized by a contrast among the linear aliphatic structures (more volatile and easy to degrade) and the branched and aromatic structures (more recalcitrant). Potential curves were applied to model each product and determine objectively whether unknown samples could be classified correctly. Polynomial regression on the PCA scores was employed to evaluate the time elapsed from the oil spillage to its sampling; this represents a new approach to assess the age of a hydrocarbon lump. In general, NIR spectroscopy yielded good results when light crude oils were studied, whereas ATR-MIR spectroscopy led to satisfactory results for both light and heavy products.

The comparison of two heavy fuel oils in composition and weathering pattern, based on IR, GC-FID and GC-MS analyses: application to the Prestige wreackage.

This paper compares the weathering patterns of two similar fuel oils: a fuel oil spilled after a ship accident (Prestige-Nassau, off the Galician coast -NW Spain-) and a fuel designed to cope with the numerous quests for samples to carry out scientific studies (IFO). Comparative studies were made to evaluate the capability of common fingerprinting analytical techniques to differentiate the fuels, as well as their capabilities to monitor their weathering. The two products were spilled under controlled conditions during ca. four months to assess how they evolved on time. Mid-IR spectrometry and gas chromatography (flame ionization and mass spectrometry detectors) were used. IR indexes related to total aromaticity, type of substituents (branched or linear chains) and degree of aromatic substitution reflected well the differences between the fuels during weathering. Regarding the chromatographic measurements, the n-alkanes became highly reduced for both fuel oils and it was found that the PAHs of the synthetic fuel (IFO) were more resistant to weathering. Regarding biomarkers, the different profiles of the steranes, diasteranes and triaromatic steroids allowed for a simple differentiation amongst the two products. The %D2/P2 ratio differentiated both products whereas the %N3/P2 one ordered the samples according to the extent of their weathering.

Primary adenocarcinoma of the fallopian tube as an incidental finding during surgery in a postmenopausal patient with unspecific pelvic pain.

Primary fallopian tube carcinoma (PFTC) is a rare gynecologic neoplasm and is usually diagnosed late and presents classically with a characteristic group of symptoms. We describe a case of a 76-year-old woman who underwent TVS requested by the family physician due to unspecific pelvic pain. An adnexal mass was found with morphology associated with high levels of CA125 suggestive of a malignant tumor. During laparotomy, a mass located in the left tube was found. Histopathology confirmed PFTC. Total hysterectomy, salpingo-oophorectomy and adjuvant chemotherapy with carboplatin/paclitaxel were performed. The patient has not yet presented any signs of recurrence.

Identification of fuel samples from the Prestige wreckage by pattern recognition methods.

A set of 34 worldwide crude oils, 12 distilled products (kerosene, gas oils, and fuel oils) and 45 oil samples taken from several Galician beaches (NW Spain) after the wreckage of the Prestige tanker off the Galician coast was studied. Gas chromatography with flame ionization detection was combined with chemometric multivariate pattern recognition methods (principal components analysis, cluster analysis and Kohonen neural networks) to differentiate and characterize the Prestige fuel oil. All multivariate studies differentiated between several groups of crude oils, fuel oils, distilled products, and samples belonging to the Prestige's wreck and samples from other illegal discharges. In addition, a reduced set of 13 n-alkanes out of 36, were statistically selected by Procrustes Rotation to cope with the main patterns in the datasets. These variables retained the most important characteristics of the data set and lead to a fast and cheap analytical screening methodology.

Chemically driven variable selection by focused multimodal genetic algorithms in mid-IR spectra.

Four genetic-algorithm-based approaches to variable selection in spectral data sets are presented. They range from a pure black-box approach to a chemically driven one. The latter uses a fitness function that takes into account not only typical parameters like the number of errors when classifying a training set but also the chemical interpretability of the selected variables. In order to cope with the fact that multiple solutions may be acceptable, a multimodal genetic algorithm (GA) is employed and the most satisfactory solution selected. The multimodal GA uses two populations (denominated "hybrid two populations" GA or HTP-GA): a classical population, from which potential solutions emerge, and a new population, which maintains diversity in the search space (as required by multimodal problems). Results show that the HTP-GA approach improves the chemical understanding of the selected solution (compared to other GA approaches) and that the classification capabilities of the approach are still good. All of the GA strategies for variable selection were compared with a classical parametric technique, Procrustes rotation, which does not consider interpretability.

Fast assessment of bioaccessible metallic contamination in marine sediments.

A fast (16min) procedure to assess the bioaccessible metallic fraction of Cd, Cr, Cu, Ni, Pb and Zn simultaneously extracted (SEM) from marine sediments plus an indirect approach to determine acid volatile sulfides (AVS) are presented. For the extraction process magnetic agitation was compared with ultrasonic stirring (using a bath and a probe), and several stirring times were assayed. The proposed SEM procedure uses an ultrasonic probe and 1mL of HCl. It dramatically minimizes the turnaround time and the residues. AVS were evaluated as the difference between the amounts of sulphur in the solid residue after the extraction and total sulphur in the original sample. These procedures are fast, easy to implement and cost-effective to assess the potential risk posed by metals in marine sediments. They were tested using several CRMs and applied to sediments from two Galician Rias (NW Spain); their SEM-AVS differences indicated no biological risk.

Neoadjuvant chemotherapy with trastuzumab in HER2-positive breast cancer: pathologic complete response rate, predictive and prognostic factors.

The purpose of this study was to retrospectively review the pathologic complete response (pCR) rate from patients (n=86) with stage II and III HER2-positive breast cancer treated with neoadjuvant chemotherapy at our institution from 2008 to 2013 and to determine possible predictive and prognostic factors. Immunohistochemistry for hormone receptors and Ki-67 was carried out. Clinical and pathological features were analyzed as predictive factors of response to therapy. For survival analysis, we used Kaplan-Meier curves to estimate 5-year survival rates and the log-rank test to compare the curves. The addition of trastuzumab to neoadjuvant chemotherapy significantly improved pCR rate from 4.8 to 46.8%, regardless of the number of preoperative trastuzumab cycles (P=0.0012). Stage II patients achieved a higher response rate compared to stage III (P=0.03). The disease-free and overall survivals were not significantly different between the group of patients that received trastuzumab in the neoadjuvant setting (56.3 and 70% at 5 years, respectively) and the group that initiated it post-operatively (75.8 and 88.7% at 5 years, respectively). Axillary pCR post neoadjuvant chemotherapy with trastuzumab was associated with reduced risk of recurrence (HR=0.34; P=0.03) and death (HR=0.21; P=0.02). In conclusion, we confirmed that trastuzumab improves pCR rates and verified that this improvement occurs even with less than four cycles of the drug. Hormone receptors and Ki-67 expressions were not predictive of response in this subset of patients. Axillary pCR clearly denotes prognosis after neoadjuvant target therapy and should be considered to be a marker of resistance, providing an opportunity to investigate new strategies for HER2-positive treatment.

Validation of the online PREDICT tool in a cohort of early breast cancer in Brazil

PREDICT is a tool designed to estimate the benefits of adjuvant therapy and the overall survival of women with early breast cancer. The model uses clinical, histological, and immunohistochemical variables. This study aimed to evaluate the model's performance in a Brazilian population. We assessed the discrimination and calibration of the PREDICT model to estimate overall survival (OS) in five and ten years of follow-up in a cohort of 873 women with early breast cancer diagnosed from January 2001 to December 2016. A total of 743 patients had estrogen receptor (ER)-positive and 130 had ER-negative tumors. The area under the receiver operating characteristic (ROC) curve (AUC) for discrimination was 0.72 (95%CI: 0.66-0.78) at five years and 0.67 (95%CI: 0.61-0.72) at ten years for women with ER-positive tumors. The AUC was 0.72 (95%CI: 0.62-0.81) at five years and 0.67 (95%CI: 0.54-0.77) at ten years for women with ER-negative tumors. The predicted survival in ER-positive tumors was 91.0% (95%CI: 90.2-91.6%) at five years and 79.3% (95%CI: 77.7-81.0%) at ten years, and the observed survival 90.7% (95%CI: 88.6-92.9%) and 77.2% (95%CI: 73.4-81.4%), respectively. The predicted survival in ER-negative tumors was 84.5% (95%CI: 82.5-86.6%) at five years and 75.0% (95%CI: 71.6-78.5%) at ten years, and the observed survival 76.3% (95%CI: 69.1-84.3%) and 67.9% (95%CI: 58.6-78.6%), respectively. In conclusion, PREDICT was accurate to estimate OS in women with ER-positive tumors and overestimated the OS in women with ER-negative tumors.

Transcription Factor Networks derived from Breast Cancer Stem Cells control the immune response in the Basal subtype.

Breast cancer is the most common cancer in women worldwide and metastatic dissemination is the principal factor related to death by this disease. Breast cancer stem cells (bCSC) are thought to be responsible for metastasis and chemoresistance. In this study, based on whole transcriptome analysis from putative bCSC and reverse engineering of transcription control networks, we identified two networks associated with this phenotype. One controlled by SNAI2, TWIST1, BNC2, PRRX1 and TBX5 drives a mesenchymal or CSC-like phenotype. The second network is controlled by the SCML4, ZNF831, SP140 and IKZF3 transcription factors which correspond to immune response modulators. Immune response network expression is correlated with pathological response to chemotherapy, and in the Basal subtype is related to better recurrence-free survival. In patient-derived xenografts, the expression of these networks in patient tumours is predictive of engraftment success. Our findings point out a potential molecular mechanism underlying the balance between immune surveillance and EMT activation in breast cancer. This molecular mechanism may be useful to the development of new target therapies.

Repeated administration of mazindol reduces spontaneous pain-related behaviors without modifying bone density and microarchitecture in a mouse model of complete Freund's adjuvant-induced knee arthritis.

BACKGROUND: The role of dopaminergic system in the development of rheumatoid arthritis-related pain, a major symptom in this disease, has not been explored. Therefore, the anti-nociceptive effect of mazindol, a dopamine uptake inhibitor, was evaluated in a model of complete Freund's adjuvant (CFA)-induced arthritis. Furthermore, as studies have shown that the dopaminergic system regulates bone metabolism, the effect of mazindol on bone mass and microarchitecture was determined. METHODS: Adult ICR male mice received intra-articular injections of either CFA or saline into the right knee joint every week. Spontaneous pain-like behaviors (flinching and guarding) and locomotor activity were assessed at day 26 post-first CFA, following which, a single intraperitoneally (i.p.) administered dose of mazindol was given (1, 3 and 10 mg/kg). Then, the antinociceptive effect of a repeated administration of 3 mg/kg mazindol (daily, i.p.; day 15-day 26) was evaluated. Additionally, at day 26, the participation of D1-like, D2-like or opioid receptors in the antinociceptive effect of mazindol was evaluated. The effect of mazindol on bone density and microarchitecture was evaluated by micro-computed tomography. RESULTS: Acute administration of mazindol decreased the spontaneous pain-like behaviors in a dose-dependent manner without reducing the knee edema. However, mazindol at 10 mg/kg significantly increased the locomotor activity; therefore, 3 mg/kg mazindol was used for further studies. Repeated administration of 3 mg/kg mazindol significantly decreased the pain-like behaviors without modifying locomotor activity. The antinociceptive effect of mazindol was blocked by administration of a D2-like receptor antagonist (haloperidol), but not by administration of D1-like receptor antagonist (SCH 23390) or an opioid receptor antagonist (naloxone). Repeated administration of mazindol did not significantly modify the density and microarchitecture of periarticular bone of the arthritic and nonarthritic knee joints. CONCLUSION: Results suggest that mazindol via D2-like receptors has an antinociceptive role in mice with CFA-induced knee arthritis without modifying the bone health negatively.

Classification of some heat-treated liver pastes according to container type, using heavy metals content and manufacturer's data, by principal components analysis and potential curves.

A total of 115 pork liver pastes were randomly collected in local markets from different brands, countries and containers. The concentrations of nine heavy metals (Cu, Ni, Cd, Fe, Mn, Pb, Cr, Co and Zn), determined by atomic absorption spectrometry, and some qualitative variables described on the labelling constituted the data set. Chemometrics analysis was performed combining principal components analysis (PCA), factor analysis (FA) and typical classification techniques, such as linear discriminant analysis (LDA) and potential curves (PoCu) to classify pork liver pastes. Origin of the sample, manufacturer and effect of manufacturing process were taken into account to verify traceability, which is an important issue in food safety policies.