A Comprehensive Analysis of Fel Ursi and Its Common Adulterants Based on UHPLC-QTOF-MSE and Chemometrics.

BACKGROUND: As one of the four most valuable animal medicines, Fel Ursi, named Xiong Dan (XD) in China, has the effect of clearing heat, calming the liver, and brightening the eyes. However, due to the special source of XD and its high price, other animals' bile is often sold as XD or mixed with XD on the market, seriously affecting its clinical efficacy and consumers' rights and interests. In order to realize identification and adulteration analysis of XD, UHPLC-QTOF-MSE and multivariate statistical analysis were used to explore the differences in XD and six other animals' bile. METHODS: XD, pig gall (Zhu Dan, ZD), cow gall (Niu Dan, ND), rabbit gallbladder (Tu Dan, TD), duck gall (Yan Dan, YD), sheep gall (Yang Dan, YND), and chicken gall (Ji Dan, JD) were analyzed by UHPLC-QTOF-MSE, and the MS data, combined with multivariate analysis methods, were used to distinguish between them. Meanwhile, the potential chemical composition markers that contribute to their differences were further explored. RESULTS: The results showed that XD and six other animals' bile can be distinguished from each other obviously, with 27 ions with VIP > 1.0. We preliminarily identified 10 different bile acid-like components in XD and the other animals' bile with significant differences (p < 0.01) and VIP > 1.0, such as tauroursodeoxycholic acid, Glycohyodeoxycholic acid, and Glycodeoxycholic acid. CONCLUSIONS: The developed method was efficient and rapid in accurately distinguishing between XD and six other animals' bile. Based on the obtained chemical composition markers, it is beneficial to strengthen quality control for bile medicines.

Plasma Ionomic Profile and Interaction Patterns in Coronary Artery Disease Patients.

Humans are exposed to various chemical elements that have been associated with the development and progression of diseases such as coronary artery disease (CAD). Unlike previous research, we employed a multi-element approach to investigate CAD patients and those with comorbid conditions such as diabetes (CAD-DM2), high blood pressure (CAD-HBP), or high blood lipids (CAD-HBL). Plasma concentrations of 21 elements, including lithium (Li), boron (B), aluminum (Al), calcium (Ca), titanium (Ti), vanadium (V), chromium (Cr), manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), selenium (Se), strontium (Sr), cadmium (Cd), tin (Sn), stibium (Sb), barium (Ba), and lead (Pb), were measured in CAD patients (n = 201) and healthy subjects (n = 110) using inductively coupled plasma-mass spectrometry (ICP-MS). Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models were utilized to analyze the ionomic profiles. Spearman correlation analysis was employed to identify the interaction patterns among individual elements. We found that levels of Ba, Li, Ni, Zn and Pb were elevated in the CAD group compared to the healthy group, while Sb, Ca, Cu, Ti, Fe, and Se were lower. Furthermore, the CAD-DM2 group exhibited higher levels of Ni and Cd, while the CAD-HBP group showed lower levels of Co and Mn. In the CAD-HBL group, Ti was increased, whereas Ba, Cr, Cu, Co, Mn, and Ni were reduced. In conclusion, ionomic profiles can be utilized to differentiate CAD patients from healthy individuals, potentially providing insights for future treatment or dietary interventions.

Chemical Profile and Aroma Effects of Major Volatile Compounds in New Mulberry Leaf Fu Brick Tea and Traditional Fu Brick Tea.

This study aimed to investigate the aroma effects of key volatile compounds in a new type of mulberry leaf Fu brick teas (MTs) and traditional Fu brick teas (FTs). Headspace solid-phase microextraction (HS-SPME), gas chromatography-mass spectrometry (GC-MS), sensory evaluation, and chemometrics were used to determine the differences in key flavour qualities between the two. The results showed that a total of 139 volatile components were identified, with aldehydes, ketones, and alcohols dominating. Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) combined with the odour activity value (OAV) showed that seven aroma compounds had an OAV > 10, including 2-(4-methylcyclohex-3-en-1-yl) propan-2-ol with floral and fruity aroma and green attributes, 6-methylhept-5-en-2-one, (E)-6,10-dimethyl-5,9-Undecadien-2-one, (3E,5E)-octa-3,5-dien-2-one, Benzaldehyde, and (E)-3,7,11,15-tetramethylhexadec-2-en-1-ol, which were more abundant in MTs than FTs; Cedrol with sweet aroma attributes was more consistent in MTs than FTs, and we suggest that these odour compounds are important aroma contributors to MTs. Taken together, these findings will provide new insights into the mechanism of formation of the characteristic attributes of aroma in MTs.

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.

Pseudo-Siamese network combined with label-free Raman spectroscopy for the quantification of mixed trace amounts of antibiotics in human milk: A feasibility study.

The utilization of antibiotics is prevalent among lactating mothers. Hence, the rapid determination of trace amounts of antibiotics in human milk is crucial for ensuring the healthy development of infants. In this study, we constructed a human milk system containing residual doxycycline (DXC) and/or tetracycline (TC). Machine learning models and clustering algorithms were applied to classify and predict deficient concentrations of single and mixed antibiotics via label-free SERS spectra. The experimental results demonstrate that the CNN model has a recognition accuracy of 98.85% across optimal hyperparameter combinations. Furthermore, we employed Independent Component Analysis (ICA) and the pseudo-Siamese Convolutional Neural Network (pSCNN) to quantify the ratios of individual antibiotics in mixed human milk samples. Integrating the SERS technique with machine learning algorithms shows significant potential for rapid discrimination and precise quantification of single and mixed antibiotics at deficient concentrations in human milk.

Combining multivariate statistical analysis to characterize changes in amino acids and volatiles during growth of Lou onion pseudostems.

BACKGROUND: The main edible part of the Lou onion is the pseudostem, which is highly valued for its distinctive flavour. However, harvesting decisions for the pseudostem are often based on size and market price, with little consideration given to flavour. By clarifying the growth of flavour in pseudostems, farmers and consumers may benefit from evidence-based insights that help optimize harvesting time and maximize flavour quality. RESULTS: This study employed amino acid analysis and gas chromatography-ion migration spectroscopy (GC-IMS) to elucidate the compounds of the pseudostem across different growth phases, and 17 amino acids and 61 volatile substances. Subsequently, analysis revealed that 18 compounds, including arginine (Arg), aspartic acid (Asp), glutamic acid (Glu), valine (Val), (E)-2-nonenal, decanal, 2,4-nonadienal, 2-octenal, (Z)-4-decenal, 2,4-decadienal benzeneacetaldehyde, linalool, eugenol, (Z)-6-nonen-1-ol, methyl anthranilate, 2-acetylpyridine, 3-sec-butyl-2-methoxypyrazine, and 2,6-dichlorophenol, were the key compounds in determining the flavour characteristics of the pseudostems, as assessed by taste activity value and relative odour activity value calculations. In addition, correlation analysis, focusing on five amino acids and 38 volatile compounds with variable importance for predictive components scores of >1, identified anisaldehyde, eugenol, (Z)-6-nonen-1-ol, 2,4-decadienal, 3-sec-butyl-2-methoxypyrazine, Arg, Asp, and Val as the key differentiators and contributors to the pseudostems flavour profile. CONCLUSION: During the rapid growth of Lou onions just before the emergence of flower stems, the pseudostem exhibited the most prominent flavour, making this stage most suitable for harvesting compared to the regreening growth stage and the rapid growth period of the aerial bulbs. © 2024 Society of Chemical Industry.

Unraveling the complex nexus: Interplay of volatile compounds, free amino acids, and metabolites in oat solid state fermentation.

This study delves into the dynamic interplay of volatile compounds, free amino acids, and metabolites, meticulously exploring their transformations during oat fermentation. Analysis via gas chromatography-mass spectrometry (GC-MS) unveiled significant alterations: 72 volatile compounds in unfermented oats (NFO) and 60 in fermented oats (FO), reflecting the profound impact of Saccharomyces cerevisiae TU11 and Lactobacillus plantarum Heal19 on oat constituents. A marked increase in Heptane (5.7-fold) and specific alcohol compounds, like 2-methyl-1-propanol, 3-methyl-1-butanol, and Phenylethyl alcohol in FO samples, while reductions in Hexanal, Hexanoic acid, and Acetic acid were observed. Notably, 4 phenolic compounds emerged post-fermentation, revealing diverse microbial actions in flavor modulation. Orthogonal-partial least squares discriminant analysis (OPLS-DA) indicated a clear separation between NFO and FO, demonstrating distinct volatile compound profiles. Further analysis revealed a noteworthy decrease in all free amino acids except for a significant increase in serine during fermentation. Differential metabolite screening identified 354 metabolites with 219 upregulated and 135 down-regulated, uncovering critical markers like isophenoxazine and imidazole lactic acid. Correlation analyses unveiled intricate relationships between volatile compounds and diverse metabolites, illuminating underlying biochemical mechanisms shaping oat flavor profiles during fermentation.

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.

Differentiation of Polygonatum Cyrtonema Hua from Different Geographical Origins by near-Infrared Spectroscopy with Chemometrics.

BACKGROUND: The identification of the geographical origin of Polygonatum cyrtonema Hua is of particular importance because the quality and market value of Polygonatum cyrtonema Hua from different production areas are highly variable due to differences in the growing environment and climatic conditions. OBJECTIVE: This study utilized near-infrared spectra (NIR) of Polygonatum cyrtonema Hua (n = 400) to develop qualitative models for effective differentiation of Polygonatum cyrtonema Hua from various regions. METHODS: The models were produced under different conditions to distinguish the origins distinctly. Ten pre-processing methods have been used to pre-process the original spectra (OS) and to select the most optimal spectral pre-processing method. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were employed to determine appropriate models. For simplicity, the pretreated full spectrum was calculated by different wavelength selection methods, and the four most significant variables were selected as discriminant indicator variables. RESULTS: The results show that Polygonatum cyrtonema Hua from different regions can be effectively distinguished using spectra from a series of samples analyzed by OPLS-DA. The accuracy of the OPLS-DA model is also satisfactory, with a good differentiation rate. CONCLUSION: The study findings indicate the feasibility of using spectroscopy in combination with multivariate analysis to identify the geographical origins of Polygonatum cyrtonema Hua. HIGHLIGHTS: The utilization of near-infrared spectroscopy combined with chemometrics exhibits high efficacy in discerning the provenance of herbal medicines and foods, thereby facilitating quality assurance measures.

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 flavor characteristics of cold brew coffee with GC-MS, electronic nose and tongue: effect of roasting degrees and freeze-drying.

BACKGROUND: Roasting is an important process in the formation of coffee flavor characteristics, which determines the quality of coffee and consumer acceptance. However, the influence of roasting degree on the flavor characteristics of cold brew coffee has not been fully described. RESULTS: In the present study, the flavor characteristics of cold brew coffee with different roasting degrees were compared in detail by using chromatographic and electronic sensory approaches, and the flavor changes induced by freeze-drying were investigated. Pyrazine and heterocyclic compounds were the main aroma compounds in coffee, and gradually dominated with the increase of roasting. Pyridine was consistently present in cold brew coffees of different roasting degrees and showed significant gradient of quantity accumulation. Aroma compounds such as pyrazine, linalool and furfuryl acetate were the main contributors to coffee roasting, floral and fruity flavor. Freeze-drying preserved the fruity and floral aromas of medium-roasted cold brew coffee, whereas reducing the bitterness, astringency and acidity properties that are off-putting to consumers. CONCLUSION: The higher consumer acceptance and enjoyment in medium roast cold brew coffee may be related to its stronger floral and fruity aroma. The aroma profile qualities of freeze-drying processed medium roasted cold brewed coffee were more dominant and more suitable for freeze-drying processing than medium dark roasting. Application of freeze-drying for cold brew coffee will promote the convenience of drinking. The present study provides valuable technical guidance in improving the flavor and quality of cold brew coffee, and also promotes its commercialization process. © 2024 Society of Chemical Industry.

Metabolomics and Lipidomics Analyses Aid Model Classification of Type 2 Diabetes in Non-Human Primates.

Type 2 diabetes (T2D) is a global public health issue characterized by excess weight, abdominal obesity, dyslipidemia, hyperglycemia, and a progressive increase in insulin resistance. Human population studies of T2D development and its effects on systemic metabolism are confounded by many factors that cannot be controlled, complicating the interpretation of results and the identification of early biomarkers. Aged, sedentary, and overweight/obese non-human primates (NHPs) are one of the best animal models to mimic spontaneous T2D development in humans. We sought to identify and distinguish a set of plasma and/or fecal metabolite biomarkers, that have earlier disease onset predictability, and that could be evaluated for their predictability in subsequent T2D studies in human cohorts. In this study, a single plasma and fecal sample was collected from each animal in a colony of 57 healthy and dysmetabolic NHPs and analyzed for metabolomics and lipidomics. The samples were comprehensively analyzed using untargeted and targeted LC/MS/MS. The changes in each animal's disease phenotype were monitored using IVGTT, HbA1c, and other clinical metrics, and correlated with their metabolic profile. The plasma and fecal lipids, as well as bile acid profiles, from Healthy, Dysmetabolic (Dys), and Diabetic (Dia) animals were compared. Following univariate and multivariate analyses, including adjustments for weight, age, and sex, several plasma lipid species were identified to be significantly different between these animal groups. Medium and long-chain plasma phosphatidylcholines (PCs) ranked highest at distinguishing Healthy from Dys animals, whereas plasma triglycerides (TG) primarily distinguished Dia from Dys animals. Random Forest (RF) analysis of fecal bile acids showed a reduction in the secondary bile acid glycoconjugate, GCDCA, in diseased animals (AUC 0.76[0.64, 0.89]). Moreover, metagenomics results revealed several bacterial species, belonging to the genera Roseburia, Ruminococcus, Clostridium, and Streptococcus, to be both significantly enriched in non-healthy animals and associated with secondary bile acid levels. In summary, our results highlight the detection of several elevated circulating plasma PCs and microbial species associated with fecal secondary bile acids in NHP dysmetabolic states. The lipids and metabolites we have identified may help researchers to differentiate individual NHPs more precisely between dysmetabolic and overtly diabetic states. This could help assign animals to study groups that are more likely to respond to potential therapies where a difference in efficacy might be anticipated between early vs. advanced disease.

Characterization of the effect of different cooking methods on volatile compounds in fish cakes using a combination of GC-MS and GC-IMS.

In this study, gas chromatography-mass spectrometry (GC-MS) and gas chromatography-ion mobility spectrometry (GC-IMS) were used to analyze the volatiles of fish cakes obtained using five cooking methods, namely, steaming, baking, air frying, pan frying and deep frying. The odor activity value (OAV) and relative odor activity value (ROAV) were used to screen for the major aroma compounds. Orthogonal partial least squares discriminant analysis (OPLS-DA) and the variable influence on projection (VIP) were used to determine the characteristic flavor compounds in the fish cakes. A total of 72 volatile compounds were identified by GC-MS, and 41 volatile compounds were detected by GC-IMS. 3-ethyl-2,5-dimethylpyrazine and 2,5-dimethylpyrazine were not detected in either CK or SS. The OPLS-DA models for GC-MS and GC-IMS analyses were constructed based on VIP values, and 8 and 7 compounds, respectively, were screened as characteristic aroma compounds. The results of this study provide new insights into the dynamics of flavor formation in reheated fish cakes and provide a theoretical basis for the optimization of the production process of this food product.

Analysis of differences in aroma and sensory characteristics of the mainstream smoke of six cigars.

Cigars have unique aroma and style characteristics. In order to clarify the differences of aroma components between domestic and imported cigars and the material basis of the stylistic characteristics of different cigars, gas chromatography-mass spectrometry (GC-MS) and sensory evaluation were used to compare and analyze the aroma components in the mainstream smoke of four domestic cigars and two imported cigars. The GC-MS results showed that a total of 97 aroma components were measured in the smoke of the six cigars, and the types of aroma components were similar, but there were differences in their contents. In comparison with those of domestic cigars, imported cigars had suitable nicotine content, and higher contents of phytol, neophytadiene, 3-methylpentanoic acid, and (+)-δ-cadinene. To further explore the differences in the aroma components of the six cigars, GC-MS data combined with chemometrics were used to screen out 14 key aroma components based on P-value (P) < 0.05, Variable Importance Projection (VIP) > 1, and Aroma Activity Values (OAV) > 1. The key aroma components of each cigar were obtained, Snow Dream No. 5: cedrol; Wangguan Guocui: 6-methyl-5-hepten-2-one, pyridine, 2-ethyl-6-methylpyrazine; General Achileus No. 3: p-cresol, 2-methylbutyraldehyde, methyl cyclopentenolone; Montecristo No. 4: cedrol, 2-methylbutyraldehyde, guaiacol, 4-vinylguaiacol, methyl cyclopentenolone; Romeo y Julieta Wide Churchills: cedrol, 2,6-dimethylpyrazine, 2-ethyl-6-methylpyrazine, 2-heptanone, phenethyl alcohol; Great Wall No. 2: p-cresol, phenethyl alcohol, geranylacetone, methyl cyclopentenolone, dihydroactinidiolide. The odor descriptors of these compounds were consistent with the aroma profiles that were prominent in the senses of each cigar. This experiment initially explored the differences in aroma composition and style characteristics of cigars and provided data to support the quality improvement of domestic cigars.

Exploring metabolic responses and pathway changes in CHO-K1 cells under varied aeration conditions and copper supplementations using 1 H NMR-based metabolomics.

The optimization of bioprocess for CHO cell culture involves careful consideration of factors such as nutrient consumption, metabolic byproduct accumulation, cell growth, and monoclonal antibody (mAb) production. Valuable insights can be obtained by understanding cellular physiology to ensure robust and efficient bioprocess. This study aims to improve our understanding of the CHO-K1 cell metabolism using 1 H NMR-based metabolomics. Initially, the variations in culture performance and metabolic profiles under varied aeration conditions and copper supplementations were thoroughly examined. Furthermore, a comprehensive metabolic pathway analysis was performed to assess the impact of these conditions on the implicated pathways. The results revealed substantial alterations in the pyruvate metabolism, histidine metabolism, as well as phenylalanine, tyrosine and tryptophan biosynthesis, which were especially evident in cultures subjected to copper deficiency conditions. Conclusively, significant metabolites governing cell growth and mAb titer were identified through orthogonal partial least square-discriminant analysis (OPLS-DA). Metabolites, including glycerol, alanine, formate, glutamate, phenylalanine, and valine, exhibited strong associations with distinct cell growth phases. Additionally, glycerol, acetate, lactate, formate, glycine, histidine, and aspartate emerged as metabolites influencing cell productivity. This study demonstrates the potential of employing 1 H NMR-based metabolomics technology in bioprocess research. It provides valuable guidance for feed medium development, feeding strategy design, bioprocess parameter adjustments, and ultimately the enhancement of cell proliferation and mAb yield.

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.

Non-targeted metabolomics identifies biomarkers in milk with high and low milk fat percentage.

Milk is widely recognized as an important food source with health benefits. Different consumer groups have different requirements for the content and proportion of milk fat; therefore, it is necessary to investigate the differential metabolites and their regulatory mechanisms in milk with high and low milk fat percentages (MFP). In this study, untargeted metabolomics was performed on milk samples from 13 cows with high milk fat percentage (HF) and 13 cows with low milk fat percentage (LF) using ultra-high performance liquid chromatography coupled with mass spectrometry (UHPLC-MS/MS). Forty-eight potential differentially labeled compounds were screened using the orthogonal partial least squares-discriminant analysis (OPLS-DA) combined with the weighted gene co-expression network analysis (WGCNA) method. Amino acid metabolism was the key metabolic pathway with significant enrichment of L-histidine, 5-oxoproline, L-aspartic acid, and L-glutamic acid. The negative correlation with MFP differentiated the HF and LF groups. To further determine the potential regulatory role of these amino acids on milk fat metabolism, the expression levels of marker genes in the milk fat synthesis pathway were explored. It was noticed that L-histidine reduced milk fat concentration primarily by inhibiting the triglycerides (TAG) synthesis pathway. L-aspartic acid and L-glutamic acid inhibited milk fat synthesis through the fatty acid de novo and TAG synthesis pathways. This study provides new insights into the mechanism underlying milk fat synthesis and milk quality improvement.

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.

Flavor characteristics of large yellow croaker soup served with different dried edible fungi.

The effects of different edible fungi on the flavor profiles of fish soups were analyzed by sensory evaluation, non-volatile and volatile flavor compounds. The sensory attributes of fish soups were modified by adding edible fungi, with the highest total scores obtained for AAFS and DFS. Compared with pure fish soup, the amounts of free amino acids, nucleotides, organic acids and inorganic ions were increased with fungi addition, especially AAFS. The different mushroom fish soups could be clearly distinguished by E-nose analysis, and a total of 52 flavor compounds, mainly composed of aldehydes (27), ketones (11), alcohols (8), esters (4), and others (2), were then identified by GC-IMS. Eventually, fish soup samples were classified into three groups based on OPLS-DA analysis: Ⅰ (LEFS), Ⅱ (BFS and BEFS) and Ⅲ (ABFS, AAFS and DFS). The results showed that Agrocybe aegerita had high suitability for improving the flavor of Large yellow croaker soups.

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.