Impact of microorganisms on key processes of organic acid metabolism during the occurrence and disappearance of paocai pellicle.

In vegetable fermentation, pellicle is a common quality deterioration phenomenon. This study investigates the characteristics of glucose, organic acids, amino acids, and biogenic amines during the pellicle occurrence and disappearance of paocai. The results revealed a slight increase in pH of the fermentation system after pellicle occurred, and glucose was the main carbohydrate that microbial activity primary relied on. The microorganisms responsible for pellicle formation consumed organic acids in brine, but the lactic acid in paocai gradually increased and exceeded 25 mg/g. The appearance of pellicle caused a decrease in total free amino acids from 200.390 mg/100 g to 172.079 when pellicle occurred, whereas its impact on biogenic amines was not apparent. Through Kyoto Encyclopedia of Genes and Genomes pathway enrichment of metagenomics sequencing data, screening, and sorting of the key enzymes involved in organic acid metabolism, it was observed that the composition and species of the key microorganisms capable of metabolizing organic acids were more abundant before the appearance of pellicle. When pellicle occurred, lactic acid may be metabolized by Lactobacillus plantarum; in contrast, Lactobacillus and Pichia were associated with citric acid metabolism, and Lactobacillus, Pichia, Saccharomycodes, and Kazachstania were linked to malic acid metabolism. Moreover, Prevotella, Kazachstania, Lactobacillus, Vibrio, and Siphonobacter were implicated in succinic acid metabolism. Additionally, the production of tartaric acid and oxalic acid in paocai and brine resulted from abiotic effects. This knowledge offers a theoretical basis for precise control of paocai fermentation process. PRACTICAL APPLICATION: Our study revealed the specific situation of the metabolites produced by the microorganisms during the pollution and recovery process of pellicle in paocai fermentation, especially the effect of pellicle on the key process of organic acid metabolism. These research results provided theoretical basis for precise control of paocai fermentation.

Quantitative patient graph analysis for transient ischemic attack risk factor distribution based on electronic medical records.

A transient ischemic attack (TIA) affects millions of people worldwide. Although TIA risk factors have been identified individually, a systemic quantitative analysis of all health factors relevant to TIA using electronic medical records (EMR) remains lacking. This study employed a data-driven approach, leveraging hospital EMR data to create a TIA patient health factor graph. This graph consisted of 737 TIA and 737 control patient nodes, 740 health factor nodes, and over 33,000 relations between patients and factors. For all health factors in the graph, the connection delta ratios (CDRs) were determined and ranked, generating a quantitative distribution of TIA health factors. A literature review confirmed 56 risk factors in the distribution and unveiled a potential new risk factor "rhinosinusitis" for future validation. Moreover, the patient graph was visualized together with the TIA knowledge graph in the Unified Medical Language System. This integration enables clinicians to access and visualize patient data and international standard knowledge within a unified graph. In conclusion, graph CDR analysis can effectively quantify the distribution of TIA risk factors. The resulting TIA risk factor distribution might be instrumental in developing new risk prediction machine learning models for screening and early detection of TIA.

Incorporation of cellulose nanocrystals to improve the physicochemical and bioactive properties of pectin-konjac glucomannan composite films containing clove essential oil.

This study aimed to investigate the effectiveness of cellulose nanocrystals (CNC) isolated from cotton in augmenting pectin (PEC)/konjac glucomannan (KGM) composite films containing clove essential oil (CEO) for food packaging application. The effects of CNC dosage on film properties were examined by analyzing the rheology of film-forming solutions and the mechanical, barrier, antimicrobial, and CEO-release properties of the films. Rheological and FTIR analysis revealed the enhanced interactions among the film components after CNC incorporation due to its high aspect ratio and abundant hydroxyl groups, which can also prevent CEO droplet aggregation, contributing to form a compact microstructure as confirmed by SEM and 3D surface topography observations. Consequently, the addition of CNC reinforced the polysaccharide matrix, increasing the tensile strength of the films and improving their barrier properties to water vapor. More importantly, antibacterial, controlled release and kinetic simulation experiments proved that the addition of CNC could further slow down the release rate of CEO, prolonging the antimicrobial properties of the films. PEC/KGM/CEO composite films with 15 wt% CNC was found to have relatively best comprehensive properties, which was also most effective in delaying deterioration of grape quality during the storage of 9 days at 25 °C.

Benchmarking the symptom-checking capabilities of ChatGPT for a broad range of diseases.

OBJECTIVE: This study evaluates ChatGPT's symptom-checking accuracy across a broad range of diseases using the Mayo Clinic Symptom Checker patient service as a benchmark. METHODS: We prompted ChatGPT with symptoms of 194 distinct diseases. By comparing its predictions with expectations, we calculated a relative comparative score (RCS) to gauge accuracy. RESULTS: ChatGPT's GPT-4 model achieved an average RCS of 78.8%, outperforming the GPT-3.5-turbo by 10.5%. Some specialties scored above 90%. DISCUSSION: The test set, although extensive, was not exhaustive. Future studies should include a more comprehensive disease spectrum. CONCLUSION: ChatGPT exhibits high accuracy in symptom checking for a broad range of diseases, showcasing its potential as a medical training tool in learning health systems to enhance care quality and address health disparities.

Changes in the structural and physicochemical characteristics of sonicated potato flour.

Ultrasound has been widely used for physical modifications of starch because of its effectiveness and environment friendliness; however, only a few reports have focused on the effect of varying ultrasonic treatments on the physicochemical properties of potato flour. In the present study, ultrasound at varying power levels (200, 300, 400, 500, and 600 W) and time intervals (20, 40, 60, 80, and 100 min) were used to obtain sonicated flour. Sonicated potato flour exhibited a significant (P < 0.05) decrease in blue value and oil holding capacity but an increase in swelling power, water solubility, syneresis rate, and transparency. Moreover, ultrasound decreased the RDS content while increasing RS and SDS contents. Thermal properties demonstrated significant (P < 0.05) increases in T0 (64.39℃-83.52℃) and TC (144.29℃-146.87℃) but a decrease in ΔH of the sonicated flour. SEM revealed wrinkles, less debris, and larger particle size at the surface of the sonicated flour. FTIR profiles of all samples exhibited similar characteristics peaks, but the sonicated flour had a higher R1047/1022 value. Additionally, ultrasound did not affect crystalline patterns, but it increased the crystallinity of the sonicated flour. Our study contributes to the understanding of physicochemical property changes of sonicated potato flour, which could have industrial applications.

Accuracy of Chatbots in Citing Journal Articles.

This cross-sectional study quantifies the journal article citation error rate of an artificial intelligence chatbot.

Antibiofilm Activity and Mechanism of Linalool against Food Spoilage Bacillus amyloliquefaciens.

Pellicle biofilm-forming bacteria Bacillus amyloliquefaciens are the major spoilage microorganisms of soy products. Due to their inherent resistance to antibiotics and disinfectants, pellicle biofilms formed are difficult to eliminate and represent a threat to food safety. Here, we assessed linalool's ability to prevent the pellicle of two spoilage B. amyloliquefaciens strains. The minimum biofilm inhibitory concentration (MBIC) of linalool against B. amyloliquefaciens DY1a and DY1b was 4 µL/mL and 8 µL/mL, respectively. The MBIC of linalool had a considerable eradication rate of 77.15% and 83.21% on the biofilm of the two strains, respectively. Scanning electron microscopy observations revealed that less wrinkly and thinner pellicle biofilms formed on a medium supplemented with 1/2 MBIC and 1/4 MBIC linalool. Also, linalool inhibited cell motility and the production of extracellular polysaccharides and proteins of the biofilm matrix. Furthermore, linalool exposure reduced the cell surface hydrophobicity, zeta potential, and cell auto-aggregation of B. amyloliquefaciens. Molecular docking analysis demonstrated that linalool interacted strongly with quorum-sensing ComP receptor and biofilm matrix assembly TasA through intermolecular hydrogen bonds, hydrophobic contacts, and van der Waals forces interacting with site residues. Overall, our findings suggest that linalool may be employed as a potential antibiofilm agent to control food spoilage B. amyloliquefaciens.

Pectin mediates the mechanism of host blood glucose regulation through intestinal flora.

Pectin is a complex polysaccharide found in plant cell walls and interlayers. As a food component, pectin is benefit for regulating intestinal flora. Metabolites of intestinal flora, including short-chain fatty acids (SCFAs), bile acids (BAs) and lipopolysaccharides (LPS), are involved in blood glucose regulation. SCFAs promote insulin synthesis through the intestine-GPCRs-derived pathway and hepatic adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK) pathway to promote hepatic glycogen synthesis. On the one hand, BAs stimulate intestinal L cells and pancreatic α cells to secrete Glucagon-like peptide-1 (GLP-1) and peptide YY (PYY) through receptors G protein-coupled receptor (TGR5) and farnesoid X receptor (FXR). On the other hand, BAs promote hepatic glycogen synthesis through AMPK pathway. LPS inhibits the release of inflammatory cytokines through Toll-like receptors (TLRs)-myeloid differentiation factor 88 (MYD88) pathway and mitogen-activated protein kinase (MAPK) pathway, thereby alleviating insulin resistance (IR). In brief, both SCFAs and BAs promote GLP-1 secretion through different pathways, employing strategies of increasing glucose consumption and decreasing glucose production to maintain normal glucose levels. Notably, pectin can also directly inhibit the release of inflammatory cytokines through the -TLRs-MYD88 pathway. These data provide valuable information for further elucidating the relationship between pectin-intestinal flora-glucose metabolism.

Building Practical Risk Prediction Models for Nasopharyngeal Carcinoma Screening with Patient Graph Analysis and Machine Learning.

BACKGROUND: To expand nasopharyngeal carcinoma (NPC) screening to larger populations, more practical NPC risk prediction models independent of Epstein-Barr virus (EBV) and other lab tests are necessary. METHODS: Patient data before diagnosis of NPC were collected from hospital electronic medical records (EMR) and used to develop machine learning (ML) models for NPC risk prediction using XGBoost. NPC risk factor distributions were generated through connection delta ratio (CDR) analysis of patient graphs. By combining EMR-wide ML with patient graph analysis, the number of variables in these risk models was reduced, allowing for more practical NPC risk prediction ML models. RESULTS: Using data collected from 1,357 patients with NPC and 1,448 patients with control, an optimal set of 100 variables (ov100) was determined for building NPC risk prediction ML models that had, the following performance metrics: 0.93-0.96 recall, 0.80-0.92 precision, and 0.83-0.94 AUC. Aided by the analysis of top CDR-ranked risk factors, the models were further refined to contain only 20 practical variables (pv20), excluding EBV. The pv20 NPC risk XGBoost model achieved 0.79 recall, 0.94 precision, 0.96 specificity, and 0.87 AUC. CONCLUSIONS: This study demonstrated the feasibility of developing practical NPC risk prediction models using EMR-wide ML and patient graph CDR analysis, without requiring EBV data. These models could enable broader implementation of NPC risk evaluation and screening recommendations for larger populations in urban community health centers and rural clinics. IMPACT: These more practical NPC risk models could help increase NPC screening rate and identify more patients with early-stage NPC.

The Generation of a Lung Cancer Health Factor Distribution Using Patient Graphs Constructed From Electronic Medical Records: Retrospective Study.

BACKGROUND: Electronic medical records (EMRs) of patients with lung cancer (LC) capture a variety of health factors. Understanding the distribution of these factors will help identify key factors for risk prediction in preventive screening for LC. OBJECTIVE: We aimed to generate an integrated biomedical graph from EMR data and Unified Medical Language System (UMLS) ontology for LC, and to generate an LC health factor distribution from a hospital EMR of approximately 1 million patients. METHODS: The data were collected from 2 sets of 1397 patients with and those without LC. A patient-centered health factor graph was plotted with 108,000 standardized data, and a graph database was generated to integrate the graphs of patient health factors and the UMLS ontology. With the patient graph, we calculated the connection delta ratio (CDR) for each of the health factors to measure the relative strength of the factor's relationship to LC. RESULTS: The patient graph had 93,000 relations between the 2794 patient nodes and 650 factor nodes. An LC graph with 187 related biomedical concepts and 188 horizontal biomedical relations was plotted and linked to the patient graph. Searching the integrated biomedical graph with any number or category of health factors resulted in graphical representations of relationships between patients and factors, while searches using any patient presented the patient's health factors from the EMR and the LC knowledge graph (KG) from the UMLS in the same graph. Sorting the health factors by CDR in descending order generated a distribution of health factors for LC. The top 70 CDR-ranked factors of disease, symptom, medical history, observation, and laboratory test categories were verified to be concordant with those found in the literature. CONCLUSIONS: By collecting standardized data of thousands of patients with and those without LC from the EMR, it was possible to generate a hospital-wide patient-centered health factor graph for graph search and presentation. The patient graph could be integrated with the UMLS KG for LC and thus enable hospitals to bring continuously updated international standard biomedical KGs from the UMLS for clinical use in hospitals. CDR analysis of the graph of patients with LC generated a CDR-sorted distribution of health factors, in which the top CDR-ranked health factors were concordant with the literature. The resulting distribution of LC health factors can be used to help personalize risk evaluation and preventive screening recommendations.

Simulation of a machine learning enabled learning health system for risk prediction using synthetic patient data.

When enabled by machine learning (ML), Learning Health Systems (LHS) hold promise for improving the effectiveness of healthcare delivery to patients. One major barrier to LHS research and development is the lack of access to EHR patient data. To overcome this challenge, this study demonstrated the feasibility of developing a simulated ML-enabled LHS using synthetic patient data. The ML-enabled LHS was initialized using a dataset of 30,000 synthetic Synthea patients and a risk prediction XGBoost base model for lung cancer. 4 additional datasets of 30,000 patients were generated and added to the previous updated dataset sequentially to simulate addition of new patients, resulting in datasets of 60,000, 90,000, 120,000 and 150,000 patients. New XGBoost models were built in each instance, and performance improved with data size increase, attaining 0.936 recall and 0.962 AUC (area under curve) in the 150,000 patients dataset. The effectiveness of the new ML-enabled LHS process was verified by implementing XGBoost models for stroke risk prediction on the same Synthea patient populations. By making the ML code and synthetic patient data publicly available for testing and training, this first synthetic LHS process paves the way for more researchers to start developing LHS with real patient data.

Identification of pellicle formation related microorganisms in traditional Sichuan paocai through metagenomic sequence and the effects of Baijiu/Salt on pellicle and volatile components.

The occurrence of pellicle on the surface of paocai brine is a common undesirable phenomenon during the multi-rounds of paocai fermentation, which is mainly caused by the growth of microorganisms related to pellicle formation. But the detailed information on these microorganisms and volatile components produced by them, as well as the changes of the microorganisms during the process of paocai recovery, are still rare in the literature. Therefore, the purpose of this study was (1) to analyze the pellicle formation related microorganisms by comparing the differential microorganisms in initial brine and the brine when pellicle occurred through metagenomic sequencing technology, (2) to explore the changes of microorganisms in the fermentation system after addition Baijiu and/or salt, and (3) to further detect the VOCs in paocai samples by gas chromatography-mass spectrometry (GC-MS). The relationship between VOCs and the selected marker microorganisms was also determined. The results showed that the diversity of fungi was increased when pellicle formed, the pellicle formation related microorganisms mainly belonged to six genus, including Kazachstania, Lactobacillus, Pichia, Candida, Lachancea, and Saccharomyces. Apart from the unknown function and basic life activities of microorganisms, the metabolic activities of these pellicle formation related microorganisms were mainly carbohydrate transport and metabolism, and amino acid transport and metabolism. The growth of pellicle formation related microorganisms could be inhibited by adding Baijiu (1.5% v/v), but the addition of salt (7% salt (w/v) did not promote this inhibitory effect. Through PCA analysis, it was found that the VOCs of paocai were significantly affected by adding Baijiu and Baijiu and salt. The undesirable smell at the beginning of pellicle formation may be related to Propanoic acid, hexyl ester, 1,3-Dimethyl-1-cyclohexene, Oxime-, methoxy-phenyl- and Phenylethyl Alcohol.

Antibacterial Peptide NP-6 Affects Staphylococcus aureus by Multiple Modes of Action.

Our previous study extracted and identified an antibacterial peptide that was named NP-6. Herein, we investigated the physicochemical properties of NP-6, and elucidated the mechanisms underlying its antimicrobial activity against Staphylococcus aureus. The results showed that the hemolysis activity of NP-6 was 2.39 ± 0.13%, lower than Nisin A (3.91 ± 0.43%) at the same concentration (512 µg/mL). Negligible cytotoxicity towards RAW264.7 cells was found when the concentration of NP-6 was lower than 512 µg/mL. In addition, it could keep most of its activity in fetal bovine serum. Moreover, transmission electron microscopy, confocal laser scanning microscopy, and flow cytometry results showed that NP-6 can destroy the integrity of the bacterial cell membrane and increase the membrane permeability. Meanwhile, NP-6 had binding activity with bacterial DNA and RNA in vitro and strongly inhibited the intracellular ß-galactosidase activity of S. aureus. Our findings suggest that NP-6 could be a promising candidate against S. aureus.

Exploring the differential stages of the pigment metabolism by pre-harvest bagging and post-harvest ethylene de-greening of Eureka lemon peel.

Pre-harvest bagging or post-harvest ethylene treatments on lemons are commonly applied to change the surface color from green to favorable yellow. In this study, the differential mechanisms of the pigment metabolism by the two treatments were investigated by pigments contents and related genetic expression. The results showed that both treatments reduced the number of chloroplasts and the content of chlorophyll. The differential expression of PSY1 and PSY2 were observed, causing the different accumulation of the main carotenoid phytoene content. The differential expression of NYC resulted in altered contents of chlorophyll a and chlorophyll b, and further led to the difference in a* value. More interestingly, the degradation of chlorophyll uncovered the color of carotenoids, leading to the color changed from green to yellow.

Incorporation of Lipids into Wheat Bran Cellulose/Wheat Gluten Composite Film Improves Its Water Resistance Properties.

This work evaluated the improvement effects of lipids incorporation on water resistance of composite biodegradable film prepared with wheat bran cellulose/wheat gluten (WBC/WG) using an alkaline-ethanol film forming system. Four types of lipids, paraffin wax (PW), beeswax (BW), paraffin oil (PO), and oleic acid (OA), were tested. We found that PW, BW, and PO incorporation at 5-20% improved water vapor permeability (WVP) and surface hydrophobicity of prepared films. Particularly, incorporation of 15% BW could best improve the water resistance properties of the film, with the lowest WVP of 0.76 × 10-12 g/cm·s·Pa and largest water contact angle (WCA) of 86.18°. Incorporation of OA led to the decline in moisture barrier properties. SEM images revealed that different lipids incorporation changed the morphology and of the composite film, and cross-sectional morphology indicated BW-incorporated film obtained more uniform and compact structures compared to other films. Moreover, Fourier transform infrared spectra indicated that the incorporation of PW or BW enhanced the molecular interactions between the film components, confirmed by the chemical shift of characteristic peaks at 3277 and 1026 cm-1. Differential scanning calorimetry results revealed that incorporation of PW, BW, and PO increased films' melting point, decomposition temperatures, and enthalpy values. Furthermore, the presence of most lipids decreased tensile strength and elongation at the break of the film. Overall, the composite film containing 15% BW obtained the most promising water resistance performance and acceptable mechanical properties, and it thus most suitable as a hydrophobic biodegradable material for food packaging.

Metagenomic Study on Chinese Homemade Paocai: The Effects of Raw Materials and Fermentation Periods on the Microbial Ecology and Volatile Components.

"Chinese paocai" is typically made by fermenting red radish or cabbage with aged brine (6-8 w/w). This study aimed to reveal the effects of paocai raw materials on fermentation microorganisms by metagenomics sequencing technology, and on volatile organic compounds (VOCs) by gas chromatography-mass spectroscopy, using red radish or cabbage fermented for six rounds with aged brine. The results showed that in the same fermentation period, the microbial diversity in cabbage was higher than that in red radish. Secundilactobacillus paracollinoides and Furfurilactobacillus siliginis were the characteristic bacteria in red radish paocai, whereas 15 species of characteristic microbes were found in cabbage. Thirteen kinds of VOCs were different between the two raw materials and the correlation between the microorganisms and VOCs showed that cabbage paocai had stronger correlations than radish paocai for the most significant relationship between 4-isopropylbenzyl alcohol, α-cadinol, terpinolene and isobutyl phenylacetate. The results of this study provide a theoretical basis for understanding the microbiota and their relation to the characteristic flavors of the fermented paocai.

Extraction Optimization and Evaluation of the Antioxidant and α-Glucosidase Inhibitory Activity of Polysaccharides from Chrysanthemum morifolium cv. Hangju.

In order to evaluate the antioxidant and α-glucosidase activities of polysaccharides from Chrysanthemum morifolium cv. Hangju (CMPs), the response surface methodology was applied to optimize the parameters for extraction progress of CMPs by ultrasound, with heat reflex extraction (HRE) performed as the control. The difference in the physicochemical properties of polysaccharides obtained by the two methods were also investigated. The maximum yields (8.29 ± 0.18%) of polysaccharides extracted by ultrasonic assisted extraction (UAE) were obtained under the optimized conditions of ultrasonic power 501 W, extraction time 19 min, and ratio of liquid-to-raw material 41 mL/g. Polysaccharides extracted by UAE possessed lower protein contents (2.56%) and higher uronic acids contents (7.08%) and low molecular weight fractions than that by HRE. No significant differences were found in monosaccharide composition and Fourier transform infrared (FT-IR) spectra of polysaccharides extracted by UAE and HRE, while polysaccharides by UAE possessed stronger antioxidant and α-glucosidase inhibitory activities. Therefore, UAE was an efficient way to obtain CMPs.

Novel liquid fermentation medium of Cordyceps militaris and optimization of hydrothermal reflux extraction of cordycepin.

In this study, we developed a novel liquid fermentation medium of Cordyceps militaris using pupa powder and wheat bran as nitrogen resources instead of the traditionally used peptone. This process not only reduced the cost by approximately 50%, but increased production by over 30%. Then, we explored a method to extract and purify cordycepin by combining hydrothermal reflux extraction with macroporous resin adsorption, which is inexpensive and suitable for the industrial production. The optimum conditions for hydrothermal reflux were extracting three times at 95 °C with 1:10 sample-to-water ratio, and the cordycepin purity with macroporous resin HPD-100 reached 95.23%.[Formula: see text].

Preparation and characterization of indicator films from carboxymethyl-cellulose/starch and purple sweet potato (Ipomoea batatas (L.) lam) anthocyanins for monitoring fish freshness.

A novel indicator film from carboxymethyl-cellulose (CMC)/starch (S) and purple sweet potato anthocyanins (PSPA) was prepared and characterized. The Fourier transform infrared spectroscopic (FT-IR) analysis indicated that new interaction were generated between the components of the film, and the scanning electron microscopic (SEM) and X-ray diffraction spectra (XRD) showed that PSPA was well dispersed in CMC and starch-based film. The results from differential scanning calorimetric (DSC) analysis revealed that the novel film had increased melting temperature. The addition of PSPA into the film resulted in the increase of tensile strength but the decrease of elongation at break and moisture content. The analysis of color change demonstrated that the film color was changed from red to blue and green when exposed to different pH or ammonia. In their application trial, the SCA film was used as labels to monitor the freshness of fish stored at 20 °C, and the results showed that the color of the film was changed from red to blue when the fish became spoiled. The observation was consistent with the TVB-N value, which was higher than the set limit (20 mg/100 g). Hence, the novel indicator film could be used as intelligent food packaging to monitor fish freshness.