Alterations of Ceramides, Acylcarnitines, GlyceroLPLs, and Amines in NSCLC Tissues.

Abnormal lipid metabolism plays an important role in cancer development. In this study, nontargeted lipidomic study on 230 tissue specimens from 79 nonsmall cell lung cancer (NSCLC) patients was conducted using ultraperformance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS). Downregulation of sphingosine and medium-long-chain ceramides and short-medium-chain acylcarnitine, upregulation of long-chain acylcarnitine C20:0, and enhanced histamine methylation were revealed in NSCLC tissues. Compared with paired noncancerous tissues, adenocarcinoma (AC) tissues had significantly decreased levels of sphingosine, medium-long-chain ceramides (Cer d18:1/12:0 and Cer d16:1/14:0, Cer d18:0/16:0, Cer d18:1/16:0, Cer d18:2/16:0, Cer d18:2/18:0), short-medium-chain (C2-C16) acylcarnitines, LPC 20:0 and LPC 22:1, and significantly increased levels of the long-chain acylcarnitine C20:0, LPC 16:0, LPC P-16:0, LPC 20:1, LPC 20:2, glyceroPC, LPE 16:0, and LPE 18:2. In squamous cell carcinoma (SCC) tissues, sphingosine, Cer d18:2/16:0 and Cer d18:2/18:0, and short-medium-chain acylcarnitines had significantly lower levels, while long-chain acylcarnitines (C20:0, and C22:0 or C22:0 M), LPC 20:1, LPC 20:2, and N1,N12-diacetylspermine had significantly higher levels compared to controls. In AC and SCC tissues, the levels of LPG 18:0, LPG 18:1, and LPS 18:1 were significantly decreased, while the levels of ceramide-1-phosphate (C1P) d18:0/3:0 or LPE P-16:0, N1-acetylspermidine, and 1-methylhistamine were significantly increased than controls. Furthermore, an orthogonal partial least-squares-discriminant analysis (OPLS-DA) model based on a 4-lipid panel was established, showing good discrimination ability between cancerous and noncancerous tissues.

Profiling of phenolic composition in camellia oil and its correlative antioxidant properties analysis.

Less research has been conducted on the association between camellia oil's (CO) phenolic composition and antioxidant capability. In this study, the phenolic profile of CO and its connection to antioxidant capacity were examined utilizing a combination of widely-targeted phenolic metabolomics and multivariate statistical analysis. A total of 751 phenolics were discovered. The WGCNA was used to link phenols to antioxidants, yielding 161 antioxidant-related phenols from the blue module. In response to several antioxidant assays, 59 (FRAP), 59 (DPPH), and 53 (ABTS) phenolics were identified as differential phenolic markers (DPMs). Further stepwise multiple linear regression revealed six DPMs that substantially influenced the antioxidant capacities. Nine metabolic pathways and their associated network mechanisms for the most significant phenolics were developed. This study sheds light on the phenolic content of CO, elucidates their role in antioxidant activity, and lays the groundwork for improving extraction techniques and generating improved product.

Spatial Metabolomic Profiling of Pinelliae Rhizoma from Different Leaf Types Using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging.

Pinelliae Rhizoma (PR), a highly esteemed traditional Chinese medicinal herb, is widely applied in clinical settings due to its diverse pharmacological effects, including antitussive, expectorant, antiemetic, sedative-hypnotic, and antitumor activities. Pinellia ternata exhibits morphological variation in its leaves, with types resembling peach, bamboo, and willow leaves. However, the chemical composition differences among the corresponding rhizomes of these leaf phenotypes remain unelucidated. This pioneering research employed Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) to conduct the in situ identification and spatial profiling of 35 PR metabolites in PR, comprising 12 alkaloids, 4 organic acids, 12 amino acids, 5 flavonoids, 1 sterol, and 1 anthraquinone. Our findings revealed distinct spatial distribution patterns of secondary metabolites within the rhizome tissues of varying leaf types. Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) effectively differentiated between rhizomes associated with different leaf morphologies. Furthermore, this study identified five potential differential biomarkers-methylophiopogonanone B, inosine, cytidine, adenine, and leucine/isoleucine-that elucidate the biochemical distinctions among leaf types. The precise tissue-specific localization of these secondary metabolites offers compelling insights into the specialized accumulation of bioactive compounds in medicinal plants, thereby enhancing our comprehension of PR's therapeutic potential.

Application and Evaluation of the Antifungal Activities of Glandular Trichome Secretions from Air/Sun-Cured Tobacco Germplasms against Botrytis cinerea.

The secretions of the glandular trichomes of tobacco leaves and flowers contain abundant secondary metabolites of different compounds, such as cebradanes, labdanes, and saccharide esters. These secondary metabolites have shown interesting biological properties, such as antimicrobial, insecticidal, and antioxidant activity. In this study, 81 air/sun-cured tobacco germplasms were used as experimental materials. Quantitative and qualitative analyses of the glandular secretion components were conducted using ultra-performance liquid chromatography-quadrupole-time of flight-mass spectrometry (UPLC-Q-TOF MS) and gas chromatography-mass spectrometry (GC-MS). The ethanol extracts of glandular trichomes from tobacco leaves and flowers were evaluated for antifungal activity against the fungus Botrytis cinerea using the mycelial growth rate method. Orthogonal Partial Least Squares (OPLS) analysis was then performed to determine the relationship between the trichome secretion components and their anti-fungal activity. The results showed significant differences among the antifungal activities of the tested ethanol extracts of tobacco glandular trichomes. The inhibition rates of the upper leaves and flower extracts against B. cinerea were significantly higher than those of the middle and lower leaves, and 59 germplasms (73.75% of the tested resources) showed antifungal rates higher than 50%, with four germplasms achieving a 95% antifungal rate at the same fresh weight concentration (10 mg/mL). The OPLS analysis revealed that the antifungal activity was primarily associated with alpha-cembratriene-diol (α-CBT-diol (Peak7)) and beta-cembratriene-diol (ß-CBT-diol (Peak8)), followed by sucrose esters III (SE(III)) and cembratriene-diol oxide. These findings help identify excellent tobacco germplasms for the development and utilization of botanical pesticides against fungi and provide a theoretical reference for the multipurpose utilization of tobacco germplasms.

Analysis of characteristic aromas of buckwheat with different germplasm using gas chromatography-mass spectrometry combined with chemometrics and multivariate statistical analysis.

In this study, the volatile components in 40 samples of Tartary buckwheat and common buckwheat from 6 major producing areas in China were analyzed. A total of 77 volatile substances were identified, among which aldehydes and hydrocarbons were the main volatile components. Odor activity value analysis revealed 26 aromatic compounds, with aldehydes making a significant contribution to the aroma of buckwheat. Seven key compounds that could be used to distinguish Tartary buckwheat from common buckwheat were identified. The orthogonal partial least squares-discriminant analysis was effectively used to classify Tartary buckwheat and common buckwheat from different producing areas. This study provides valuable information for evaluating buckwheat quality, breeding high-quality varieties, and enhancing rational resource development.

Insights into the Volatile Flavor Profiles of Two Types of Beef Tallow via Electronic Nose and Gas Chromatography-Ion Mobility Spectrometry Analysis.

In the current study, an electronic nose (E-nose) and gas chromatography-ion mobility spectrometry (GC-IMS) were employed to investigate the volatile flavor compounds (VFCs) of intense flavor beef tallow (L) and ordinary beef tallow (P). The study results indicate that an E-nose combined with an LDA and GC-IMS combined with an OPLS-DA can effectively distinguish between the two types of beef tallow. Compared with ordinary beef tallow, the E-nose sensors of intense flavor beef tallow have stronger response signals to sulfides, terpenes, and nitrogen oxides. A total of 22 compounds contribute to making the flavor of intense flavor beef tallow more typical and richer; in contrast, ethyl acetate was the main aroma-active compound found in the ordinary beef tallow. Sulfur-containing compounds and terpenoids might be the key substances that cause sensory flavor differences between the two types of beef tallow. In conclusion, the results of this study clarify the characteristics and differences of the two types of beef tallow and provide an enhanced understanding of the differences in the flavors of the two types of beef tallow.

Phytochemical composition of Lagenaria siceraria fruits from KwaZulu-Natal and Limpopo, South Africa.

Lagenaria siceraria (Molina) Standley is a food and medicinal source with anti-proliferative, anti-fertility, anti-HIV and anti-cancerous properties. The current study investigated the phytochemical constituents of L. siceraria fruits using gas chromatography/mass spectrometry (GC-MS). Five isoprenoids present in all investigated landraces were 1-Dodecene, 2,3-Dimethyldodecane, E-15-Heptadecenal, Eicosane, and Tridecane, 6-propyl. Lighter metabolites such as 1-Dodecene and 2,3-Dimethyldodecane were recorded at a shorter retention time range of 9.08-16.29 min over a lower relative peak area ranging from 1.09 to 6.97%. However, heavier compounds (E-15-Heptadecenal, Eicosane and Tridecane, 6-propyl) had a longer retention time range of 13.42-18.00 mins over a higher relative peak area range of 2.25-11.41%. Cluster analysis grouped landraces into 5 clusters (I -V) according to their fruit and seed attributes, and isoprenoid units significant to each cluster. Terpenoids were the prominent phytochemicals present in fruits. This is the most comprehensive study on the fruit phytochemical constituents of different L. siceraria landraces to date.

Profiling of Volatile Compounds in 'Muscat Hamburg' Contaminated with Aspergillus carbonarius before OTA Biosynthesis Based on HS-SPME-GC-MS and DLLME-GC-MS.

Aspergillus carbonarius is known to produce the carcinogenic ochratoxin A (OTA) in grapes. The metabolism process before OTA biosynthesis influences the content and composition of the volatile compounds in grapes. In this study, a self-established method based on QuEChERS coupled with high-performance liquid chromatography-fluorescence detection (HPLC-FLD) was used to determine the OTA levels during a seven-day contamination period. The results showed that OTA was detected on the second day after contamination with A. carbonarius. Thus, the first day was considered as the critical sampling timepoint for analyzing the volatiles in grapes before OTA biosynthesis. Additionally, the volatile compounds in grapes were analyzed using headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) and dispersive liquid-liquid microextraction gas chromatography-mass spectrometry (DLLME-GC-MS). The corresponding data were evaluated via multivariate data analysis using projection methods, including PCA and OPLS-DA. The results indicated significant differences in the nine volatile compounds in grapes contaminated with A. carbonarius before OTA biosynthesis. The results of the Pearson correlation analysis showed positive correlations between ethyl acetate, styrene, 1-hexanol and OTA; (E)-2-hexenal and nerolic acid were negatively correlated with OTA. Overall, these findings provide a theoretical basis for the early prediction of OTA formation in grape and grape products using GC-MS technology.

Portable Mid-Infrared Spectroscopy Combined with Chemometrics to Diagnose Fibromyalgia and Other Rheumatologic Syndromes Using Rapid Volumetric Absorptive Microsampling.

The diagnostic criteria for fibromyalgia (FM) have relied heavily on subjective reports of experienced symptoms coupled with examination-based evidence of diffuse tenderness due to the lack of reliable biomarkers. Rheumatic disorders that are common causes of chronic pain such as rheumatoid arthritis, systemic lupus erythematosus, osteoarthritis, and chronic low back pain are frequently found to be comorbid with FM. As a result, this can make the diagnosis of FM more challenging. We aim to develop a reliable classification algorithm using unique spectral profiles of portable FT-MIR that can be used as a real-time point-of-care device for the screening of FM. A novel volumetric absorptive microsampling (VAMS) technique ensured sample volume accuracies and minimized the variation introduced due to hematocrit-based bias. Blood samples from 337 subjects with different disorders (179 FM, 158 non-FM) collected with VAMS were analyzed. A semi-permeable membrane filtration approach was used to extract the blood samples, and spectral data were collected using a portable FT-MIR spectrometer. The OPLS-DA algorithm enabled the classification of the spectra into their corresponding classes with 84% accuracy, 83% sensitivity, and 85% specificity. The OPLS-DA regression plot indicated that spectral regions associated with amide bands and amino acids were responsible for discrimination patterns and can be potentially used as spectral biomarkers to differentiate FM and other rheumatic diseases.

Application of surface-enhanced Raman spectroscopy to human serum for diagnosing liver cancer.

This study investigates the application of surface-enhanced Raman spectroscopy (SERS) in the diagnosis of liver cancer using Ag@SiO2 nanoparticles as SERS substrates. A SERS test was conducted on serum samples obtained from patients with liver cancer and healthy individuals. After repeated several times experiments, it was found that the best SERS spectrum was obtained when the volume ratio of serum to deionized water was 1:2. Moreover, data preprocessing was performed on the tested SERS spectrum, and the preprocessed spectral data were combined with principal component analysis (PCA), partial least-squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) for further analysis to classify the serum samples of patients with liver cancer and healthy individuals. The results showed that the classification effect of standard normal variate spectral data combined with the OPLS-DA was the best for the serum samples, with a classification accuracy of 97.98%, sensitivity of 97.14%, and specificity of 98.44%. Therefore, the SERS technology can be developed as a favorable method for the accurate diagnosis of liver cancer in the future.

Comparing Different Chemometric Approaches to Detect Adulteration of Cold-Pressed Flaxseed Oil with Refined Rapeseed Oil Using Differential Scanning Calorimetry.

Flaxseed oil is one of the best sources of n-3 fatty acids, thus its adulteration with refined oils can lead to a reduction in its nutritional value and overall quality. The purpose of this study was to compare different chemometric models to detect adulteration of flaxseed oil with refined rapeseed oil (RP) using differential scanning calorimetry (DSC). Based on the melting phase transition curve, parameters such as peak temperature (T), peak height (h), and percentage of area (P) were determined for pure and adulterated flaxseed oils with an RP concentration of 5, 10, 20, 30, and 50% (w/w). Significant linear correlations (p ≤ 0.05) between the RP concentration and all DSC parameters were observed, except for parameter h1 for the first peak. In order to assess the usefulness of the DSC technique for detecting adulterations, three chemometric approaches were compared: (1) classification models (linear discriminant analysis-LDA, adaptive regression splines-MARS, support vector machine-SVM, and artificial neural networks-ANNs); (2) regression models (multiple linear regression-MLR, MARS, SVM, ANNs, and PLS); and (3) a combined model of orthogonal partial least squares discriminant analysis (OPLS-DA). With the LDA model, the highest accuracy of 99.5% in classifying the samples, followed by ANN > SVM > MARS, was achieved. Among the regression models, the ANN model showed the highest correlation between observed and predicted values (R = 0.996), while other models showed goodness of fit as following MARS > SVM > MLR. Comparing OPLS-DA and PLS methods, higher values of R2X(cum) = 0.986 and Q2 = 0.973 were observed with the PLS model than OPLS-DA. This study demonstrates the usefulness of the DSC technique and importance of an appropriate chemometric model for predicting the adulteration of cold-pressed flaxseed oil with refined rapeseed oil.

Circulating bile acid profile characteristics in PCOS patients and the role of bile acids in predicting the pathogenesis of PCOS.

Background: The metabolic profile of bile acids and their potential role as biomarkers in the pathogenesis of polycystic ovary syndrome (PCOS) have not been thoroughly characterized. Assessing their predictive value for PCOS is of significant importance. Methods: In this study, we enrolled 408 women with PCOS and 204 non-PCOS controls. The serum bile acid profile was measured using high-performance liquid chromatography-tandem mass spectrometry (LC/MS). We analyzed the differences in serum bile acid profiles between PCOS patients using the OPLS-DA model. Additionally, we examined the relationship between bile acid profiles and parameters related to glucose metabolism and hyperandrogenism. ROC analysis was employed to identify potential biomarkers for PCOS pathogenesis. XGboost was utilized for cross-validation. Results: The bile acid profile was found to be altered in PCOS patients. Specifically, the primary and secondary unconjugated bile acid fractions were significantly higher in the PCOS population. We identified five bile acid metabolite candidates that exhibited the most significant differences between PCOS and non-PCOS controls. DCA was associated with deposition index, fasting and postprandial insulin but was influenced by testosterone. CDCA and LCA combined with testosterone showed potential as biomarkers for the pathogenesis of PCOS. Conclusion: The circulating bile acid profile undergoes changes in PCOS. DCA is associated with deposition index, fasting and postprandial insulin and its level is influenced by testosterone. CDCA and LCA combined with testosterone have the potential to serve as biomarkers for the pathogenesis of PCOS.

Tracing the geographical origin of tobacco at two spatial scales by stable isotope and element analyses with chemometrics.

Tobacco is a widely cultivated cash crop, but it is often smuggled and sold illegally. Unfortunately, there is currently no way to verify the origin of tobacco in China. In an effort to address this issue, we conducted a study using stable isotopes and elements from 176 tobacco samples at both provincial and municipal scales. Our findings revealed significant differences in δ13C, K, Cs, and 208/206Pb at the provincial-level, and Sr, Se, and Pb at the municipal level. We created a heat map at the municipal level, which showed a similar cluster classification to geographic grouping and provided an initial assessment of tobacco origins. Using OPLS-DA modeling, we achieved a 98.3% accuracy rate for the provincial scale and 97.6% for the municipal scale. It is worth noting that the importance of rankings of variables varied depending on the spatial scale of the evaluation. This study offers the first traceability fingerprint dataset of tobacco and has the potential to combat mislabeling and fraudulent conduct by identifying the geographical origin of tobacco.

Phenolic Profile, Antioxidant Activity, and Chemometric Classification of Carob Pulp and Products.

In recent years, carob and its derived products have gained wide attention due to their health-promoting effects, which are mainly attributed to their phenolic compounds. Carob samples (carob pulps, powders, and syrups) were analyzed to investigate their phenolic profile using high-performance liquid chromatography (HPLC), with gallic acid and rutin being the most abundant compounds. Moreover, the antioxidant capacity and total phenolic content of the samples were estimated through DPPH (IC50 98.83-488.47 mg extract/mL), FRAP (48.58-144.32 µmol TE/g product), and Folin-Ciocalteu (7.20-23.18 mg GAE/g product) spectrophotometric assays. The effect of thermal treatment and geographical origin of carobs and carob-derived products on their phenolic composition was assessed. Both factors significantly affect the concentrations of secondary metabolites and, therefore, samples' antioxidant activity (p-value < 10-7). The obtained results (antioxidant activity and phenolic profile) were evaluated via chemometrics, through a preliminary principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA). The OPLS-DA model performed satisfactorily, differentiating all samples according to their matrix. Our results indicate that polyphenols and antioxidant capacity can be chemical markers for the classification of carob and its derived products.

Targeted metabolomics analysis for serum Helicobacter pylori-positive based on liquid chromatography-tandem mass spectrometry.

Helicobacter pylori (H. pylori), as a harmful bacteria associated with gastric cancer, can have adverse effects on human normal flora and metabolism. However, the effects of H. pylori on human metabolism have not been fully elucidated. The 13 C breathing test was used as the basis for distinguishing negative and positive groups. Serum samples were collected from the two groups for targeted quantitative metabolomics detection; multidimensional statistics were used, including partial least squares discriminant analysis (PLS-DA), principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), and differential metabolites were screened. Unidimensional statistics combined with multidimensional statistics were used to further screen potential biomarkers, and finally pathway analysis was performed. SPSS 21.0 software package was used for statistical analysis of experimental data. Multivariate statistical analysis such as PLS-DA, PCA, and OPLS-DA was performed using Simca-P 13.0 to search for differential metabolites. This study confirmed that H. pylori caused significant changes in human metabolism. In this experiment, 211 metabolites were detected in the serum of the two groups. Multivariate statistical analysis showed that PCA of metabolites was not significantly different between the two groups. PLS-DA indicated that the serum of the two groups was well clustered. There were significant differences in metabolites between OPLS-DA groups. By setting the variable importance in projection (VIP) threshold as one and the corresponding P-value <0.05, a total of 40 metabolites were screened in this study. P <0.05 and ∣log2FC∣>0 (where FC is the fold change) were used together as a unidimensional statistical filter condition. The analysis found that the expression of 15 metabolites such as propionic acid, acetic acid, adipic acid increased, and the metabolism of six products such as deoxycholic acid (DCA), 4-hydroxyphenylpyruvic acid, pyruvic acid decreased. P <0.05, false discovery rate <0.5, ∣log2FC∣>1, and OPLSDA_VIP>1 were used together as a condition for filter screening potential biomarkers. Four potential biomarkers were screened, which were sebacic acid, isovaleric acid, DCA, and indole-3-carboxylic acid. Finally, the different metabolites were added to the pathway-associated metabolite sets (SMPDB) library for the corresponding pathway enrichment analysis. The significant abnormal metabolic pathways were taurine and subtaurine metabolism, tyrosine metabolism, glycolysis or gluconeogenesis, pyruvate metabolism, etc. This study shows that H. pylori has an impact on human metabolism. Not only a variety of metabolites have significant changes, but also metabolic pathways are abnormal, which may be the reason for the high risk of H. pylori causing gastric cancer.

Urinary Metabolic Profiling of Liver Fluke-Induced Cholangiocarcinoma-A Follow-Up Study.

Background/Aims: Global liquid chromatography mass spectrometry (LC-MS) profiling in a Thai population has previously identified a urinary metabolic signature in Opisthorchis viverrini-induced cholangiocarcinoma (CCA), primarily characterised by disturbance in acylcarnitine, bile acid, steroid, and purine metabolism. However, the detection of thousands of analytes by LC-MS in a biological sample in a single experiment potentially introduces false discovery errors. To verify these observed metabolic perturbations, a second validation dataset from the same population was profiled in a similar fashion. Methods: Reverse-phase ultra-performance liquid-chromatography mass spectrometry was utilised to acquire the global spectral profile of 98 spot urine samples (from 46 healthy volunteers and 52 CCA patients) recruited from Khon Kaen, northeast Thailand (the highest incidence of CCA globally). Results: Metabolites were differentially expressed in the urinary profiles from CCA patients. High urinary elimination of bile acids was affected by the presence of obstructive jaundice. The urine metabolome associated with non-jaundiced CCA patients showed a distinctive pattern, similar but not identical to published studies. A panel of 10 metabolites achieved a diagnostic accuracy of 93.4% and area under the curve value of 98.8% (CI = 96.3%-100%) for the presence of CCA. Conclusions: Global characterisation of the CCA urinary metabolome identified several metabolites of biological interest in this validation study. Analyses of the diagnostic utility of the discriminant metabolites showed excellent diagnostic potential. Further larger scale studies are required to confirm these findings internationally, particularly in comparison to sporadic CCA, not associated with liver fluke infestation.

LC/MS-based discrimination between plasma and urine metabolomic changes following exposure to ultraviolet radiation by using data modelling.

INTRODUCTION: This study sought to compare between metabolomic changes of human urine and plasma to investigate which one can be used as best tool to identify metabolomic profiling and novel biomarkers associated to the potential effects of ultraviolet (UV) radiation. METHOD: A pilot study of metabolomic patterns of human plasma and urine samples from four adult healthy individuals at before (S1) and after (S2) exposure (UV) and non-exposure (UC) were carried out by using liquid chromatography-mass spectrometry (LC-MS). RESULTS: The best results which were obtained by normalizing the metabolites to their mean output underwent to principal components analysis (PCA) and Orthogonal Partial least squares-discriminant analysis (OPLS-DA) to separate pre-from post-of exposure and non-exposure of UV. This separation by data modeling was clear in urine samples unlike plasma samples. In addition to overview of the scores plots, the variance predicted-Q2 (Cum), variance explained-R2X (Cum) and p-value of the cross-validated ANOVA score of PCA and OPLS-DA models indicated to this clear separation. Q2 (Cum) and R2X (Cum) values of PCA model for urine samples were 0.908 and 0.982, respectively, and OPLS-DA model values were 1.0 and 0.914, respectively. While these values in plasma samples were Q2 = 0.429 and R2X = 0.660 for PCA model and Q2 = 0.983 and R2X = 0.944 for OPLS-DA model. LC-MS metabolomic analysis showed the changes in numerous metabolic pathways including: amino acid, lipids, peptides, xenobiotics biodegradation, carbohydrates, nucleotides, Co-factors and vitamins which may contribute to the evaluation of the effects associated with UV sunlight exposure. CONCLUSIONS: The results of pilot study indicate that pre and post-exposure UV metabolomics screening of urine samples may be the best tool than plasma samples and a potential approach to predict the metabolomic changes due to UV exposure. Additional future work may shed light on the application of available metabolomic approaches to explore potential predictive markers to determine the impacts of UV sunlight.

Oncological and functional impact of adjuvant treatments after open partial laryngeal surgery: a systematic review of the literature and a meta-analysis.

BACKGROUND: The oncological and functional role of postoperative radiotherapy (PORT) after open partial laryngeal surgery (OPLS) remains debatable. METHODS: A systematic review and a meta-analysis of the literature were conducted according to the PRISMA guidelines. Outcomes of patients receiving OPLS with and without PORT for laryngeal cancer were summarized. RESULTS: In the 10 studies that were included in the meta-analysis, no significant difference emerged in terms of pooled overall survival between OPLS patients who did and who did not receive PORT (- 0.3%, 95% CI - 5.4 to 4.9%, p = 0.922). Only one study showed a significantly higher incidence of complications in the PORT cohort. CONCLUSIONS: PORT may apparently be performed after OPLS in face of adverse postoperative features without an increased risk of toxicities affecting the neolarynx. Because of the limitations in the available literature, the oncological and functional effects of PORT in this setting needs to be prospectively assessed to strengthen the evidence of this treatment strategy for laryngeal cancer.

Rapid Identification of Benign Gallbladder Diseases Using Serum Surface-Enhanced Raman Spectroscopy Combined with Multivariate Statistical Analysis.

In this study, we looked at the viability of utilizing serum to differentiate between gallbladder (GB) stones and GB polyps using Surface-enhanced Raman spectroscopy (SERS), which has the potential to be a quick and accurate means of diagnosing benign GB diseases. Rapid and label-free SERS was used to conduct the tests on 148 serum samples, which included those from 51 patients with GB stones, 25 patients with GB polyps and 72 healthy persons. We used an Ag colloid as a Raman spectrum enhancement substrate. In addition, we employed orthogonal partial least squares discriminant analysis (OPLS-DA) and principal component linear discriminant analysis (PCA-LDA) to compare and diagnose the serum SERS spectra of GB stones and GB polyps. The diagnostic results showed that the sensitivity, specificity, and area under curve (AUC) values of the GB stones and GB polyps based on OPLS-DA algorithm reached 90.2%, 97.2%, 0.995 and 92.0%, 100%, 0.995, respectively. This study demonstrated an accurate and rapid means of combining serum SERS spectra with OPLS-DA to identify GB stones and GB polyps.

Decoding the Effect of Age on the Taste Perception of Chicken Breast Soup Based on LC-QTOF-MS/MS Combined with a Chemometric Approach.

A nontargeted fingerprinting approach combined with the chemometrics method and sensory analysis was used to assess the differences in taste-chemical compositions of chicken breast soup with different ages and their sensory qualities. The sensory evaluation results showed that the overall taste as well as the sourness, saltiness, and umami scores of the soup were increased with the age of chicken. Fifty-nine compounds were identified from four soup samples by liquid chromatography-tandem quadrupole time-of-flight mass spectrometry (LC-QTOF-MS/MS), and their total content was the highest in the 90 wk soup samples. Six upregulated compounds (carnosine, hypoxanthine, inosine, inosine 5'-monophosphate (5'-IMP), adenosine 5'-monophosphate (5'-AMP), and lactic acid) were identified as potential contributors to the taste characteristics of the 90 wk soup samples by orthogonal projections to latent structures-discriminant analysis (OPLS-DA). Additional experiments showed that 5'-AMP particularly contributed to the sourness of the soup, while carnosine contributed to the saltiness and umami of the soup.