An age classification model based on DNA methylation biomarkers of aging in human peripheral blood using random forest and artificial neural network.

Recent epigenetic studies have revealed a strong association between DNA methylation and aging and lifespan, which changes (increases or decreases) with age. Based on these, the construction of age prediction models associated with DNA methylation levels can be used to infer biological ages closer to the functional state of the organism. We downloaded methylation data from the Gene Expression Omnibus (GEO) public database for normal peripheral blood samples from people of different ages. We grouped the samples according to age (18-35 years and >50 years), screened the methylation sites that differed between the two groups, identified 44 differentially methylated sites, and subsequently obtained 11 age-related characteristic methylation sites using the random forest method. Then, we constructed an age classification model with these 11 characteristic methylation sites using an artificial neural network and evaluated its efficacy. The age classification model was constructed by an artificial neural network and its efficacy was evaluated. The model predicted an area under the curve (AUC) of 0.97 in the validation set and accurately distinguished between those aged 18-35 and >50 years. Furthermore, the levels of these 11 characteristic methylation sites also differed significantly between the two sets of samples in the validation set, including six newly identified age-related methylation sites (P<0.001). Finally, we constructed a multifactor regulatory network based on the corresponding genes of age-related methylation sites to reveal the transcriptional and post-transcriptional regulation patterns. As a result of the increasing problem of aging, the age classification model we constructed allows us to accurately distinguish different age groups at the molecular level, which will be more predictive than chronological age for assessing individual aging and future health status.

Development and validation of a nomogram for predicting specific mortality risk: A study of competing risk model based on real endometrial cancer patients.

OBJECTIVE: This study aimed to construct a competing risk prediction model for predicting specific mortality risks in endometrial cancer patients from the SEER database based on their demographic characteristics and tumor information. METHODS: We collected relevant clinical data on patients with histologically confirmed endometrial cancer in the SEER database between 2010 and 2015. Univariate and multivariate competing risk models were used to analyze the risk factors for endometrial cancer-specific death, and a predictive nomogram was constructed. C-index and receiver operating characteristic curve (ROC) at different time points were used to verify the accuracy of the constructed nomogram. RESULTS: There were 26 109 eligible endometrial cancer patients in the training cohort and 11 189 in the validation cohort. Univariate and multivariate analyses revealed that Age, Marriage, Grade, Behav, FIGO, Size, Surgery, SurgOth, Radiation, ParaAortic_Nodes, Peritonea, N positive, DX_liver, and DX_lung were independent prognostic factors for specific mortality in endometrial cancer patients. Based on these factors, a nomogram was constructed. Internal validation showed that the nomogram had a good discriminative ability (C-index = 0.883 [95% confidence interval [CI]: 0.881-0.884]), and the 1-, 3-, and 5-year AUC values were 0.901, 0.886 and 0.874, respectively. External validation indicated similar results (C-index = 0.883 [95%CI: 0.882-0.883]), and the 1-, 3-, and 5- AUC values were 0.908, 0.885 and 0.870, respectively. CONCLUSION: We constructed a competing risk model to predict the specific mortality risk among endometrial cancer patients. This model has favorable accuracy and reliability and can provide a reference for the development and update of endometrial cancer prognostic risk assessment tools.

Separation and Detection of Catechins and Epicatechins in Shanxi Aged Vinegar Using Solid-Phase Extraction and Hydrophobic Deep Eutectic Solvents Combined with HPLC.

This research presents a new, eco-friendly, and swift method combining solid-phase extraction and hydrophobic deep eutectic solvents (DES) with high-performance liquid chromatography (SPE-DES-HPLC) for extracting and quantifying catechin and epicatechin in Shanxi aged vinegar (SAV). The parameters, such as the elution solvent type, the XAD-2 macroporous resin dosage, the DES ratio, the DES volume, the adsorption time, and the desorption time, were optimized via a one-way experiment. A central composite design using the Box-Behnken methodology was employed to investigate the effects of various factors, including 17 experimental runs and the construction of three-dimensional response surface plots to identify the optimal conditions. The results show that the optimal conditions were an HDES (tetraethylammonium chloride and octanoic acid) ratio of 1:3, an XAD-2 macroporous resin dosage of 188 mg, and an adsorption time of 11 min. Under these optimal conditions, the coefficients of determination of the method were greater than or equal to 0.9917, the precision was less than 5%, and the recoveries ranged from 98.8% to 118.8%. The environmentally friendly nature of the analytical process and sample preparation was assessed via the Analytical Eco-Scale and AGREE, demonstrating that this method is a practical and eco-friendly alternative to conventional determination techniques. In summary, this innovative approach offers a solid foundation for the assessment of flavanol compounds present in SAV samples.

Chalcogen bond-assisted syn-locked scaffolds: DFT analysis and biological implications of novel tubulin inhibitors.

A series of new tubulin inhibitors containing chalcogen bonds have been discovered. Density functional theory (DFT) analysis of the O-C-C-S torsion profile shows a preference of 0.8 kcal/mol for the syn-conformer over the anti-conformer. Besides, the O-S natural bond orbital (NBO) analysis reveals that the OLP âˆ¼ C-SBD∗ energy potential is 0.62 kcal/mol. Further pharmacochemical screening of several series of (4-arylthiophen-2-yl)(3,4,5-trimethoxyphenyl)methanones identified IPO-10 as a highly effective tubulin inhibitor with an IC50 of 23 nm for MCF-7.

Spectrally flat mid-infrared supercontinuum pumped by a high power 2 µm noise-like pulse.

We demonstrate spectrally flat high-power mid-infrared supercontinuum (MIR SC) generation with record-breaking power of 33.1 W and power conversion efficiency of 75.06%. It is pumped by a 2 µm master oscillator power amplifier system consisting of a figure-8 mode-locked noise-like pulse seed laser and dual-stage Tm-doped fiber amplifiers with repetition rate of 4.08 MHz. Through cascading a piece of ZBLAN fiber with 13.5 µm large core diameter by direct-low-loss fusion splicing, SCs with spectral ranges of 1.9-3.68 µm, 1.9-3.84 µm, 1.9-4.02 µm and average powers of 33.1 W, 29.8 W, 25.9 W are generated. To the best of our knowledge, all of them have achieved the highest output power under the same condition of MIR spectrum range. This high-power all-fiber MIR SC laser system has relatively simple architecture, high efficiency and flat spectrum, demonstrating the advantages of 2 µm noise-like pulse pump in high-power MIR SC generation.

Effect of atom diffusion on the efficiency of Bragg diffraction in atom interferometers.

The transition efficiency of atomic Bragg diffraction as mirrors and beam splitters in Bragg atom interferometers plays an essential role in impacting the fringe contrast and measurement sensitivity. This can be attributed to the properties of atomic sources, Bragg pulse shapes, the pulse duration, and the relative position deviation of the atoms and Bragg pulses. Here, we investigate the effect of the atomic source's diffusion and velocity width on the efficiency of Bragg diffraction of the moving cold atomic cloud. The transfer efficiency of Bragg mirrors and beam splitters are numerically simulated and experimentally measured, which are well consistent in comparison. We quantify these effects of atomic diffusion and velocity width and precisely compute how Bragg pulses' efficiencies vary as functions of these parameters. Our results and methodology allow us to optimize the Bragg pulses at different atomic sources and will help in the design of large momentum transfer mirrors and beam splitters in atom interferometry experiments.

Unique genetic variants of lean nonalcoholic fatty liver disease: a retrospective cohort study.

We investigated the prevalence and clinical metabolic characteristics of lean nonalcoholic fatty liver disease (NAFLD) in an elderly Chinese population and assessed the relevance of lipid markers and genetic variation. All 5,338 community subjects underwent detailed clinical and laboratory examinations and were divided into three groups: lean (Body mass index (BMI) < 23 kg/m2, n = 2,012), overweight (BMI = 23-24.9 kg/m2, n = 1,354), and obese (BMI ≥ 25 kg/m2, n = 1,972). Single nucleotide polymorphisms were selected based on those reported in previous NAFLD or obesity genome-wide association studies. The frequencies of alleles and genotypes were calculated and statistically analyzed with Pearson's χ2 tests. One-way ANCOVA was used to test the association between positive SNPs and metabolic parameters in lean NAFLD individuals. Our results showed that the C allele frequency of rs2279026, the G allele of rs2279028, the C allele of rs780093, and the C allele frequency of rs1260326 were higher in obese NAFLD than in lean NAFLD (P < 0.05). In addition, we observed an association between the CC of rs1421085, TT of rs3751812, AA of rs8050136, and AA of rs9939609 genotypes in the FTO gene and low-density lipoprotein levels (P < 0.05). In conclusion, our findings provide a unique perspective on the prevalence, genetic characteristics, and metabolic profile of NAFLD in older lean individuals in China. This is the first study to examine the association between genetic variants in the FTO, TFAP2B and GCKR genes and NAFLD in a cohort of lean individuals.

A novel technique of penetrating keratoplasty to prevent intraocular contents extrusion for infectious keratitis.

PURPOSE: To evaluate the safety and the effectiveness of our novel penetrating keratoplasty for infectious keratitis. METHODS: Retrospective, noncomparative, interventional case series of patients with infectious keratitis who received the novel penetrating keratoplasty technique were analyzed. A prepared plastic sheet was located between the diseased cornea and iris-lens diaphragm. After the diseased lesions were removed, the graft was positioned on the plastic sheet and sutured to the recipient bed. The plastic sheet was pulled out from the anterior chamber before the all interrupted sutures were placed. The intra- and post-operative complications, the outcome of the graft and the number of corneal endothelial cells were analyzed. RESULTS: A total of 82 eyes of 82 patients was included. The mean follow-up period was 29 ± 16 months (range from 13 to 45 months). No intraocular content extrusion, simultaneous cataract extraction and suprachoroidal hemorrhage occurred. Direct contact between the infectious cornea and the graft was successfully avoided. Greater than expected endothelial cell reduction or complications were not found. CONCLUSIONS: This modified technique effectively prevents the extrusion of intraocular contents while avoiding the direct contact with donor endothelium during the procedure. The occurrence rate of complications such as endothelial cell loss is not higher than the conventional methods.

A novel pupilloplasty in crescent-shaped suturing pattern for coloboma and traumatic iris defects.

OBJECTIVE: PURPOSE: To observe the safety and effect of the C-pupilloplasty for the treatment of iris coloboma and traumatic iris defects. METHODS: A total of 21 cases (21 eyes) with iris coloboma or traumatic iris defects who underwent C-pupilloplasty (a single-pass three-throw technique) from Feb. 2016 to Mar. 2020 were analyzed retrospectively. Uncorrected visual acuity, refraction, corneal topographic keratometry and endothelial cell density were examined. RESULTS: All the patients were successfully treated, and a central and round pupil was restored. The mean follow-up duration was 8.76 ± 3.58 months (ranging from 2 to 14 months). All patients had round or round-like pupils with a diameter less than or equal to 3 mm after the C-pupilloplasty. Very slightly endothelial loss, negligible symptoms such as glare, distortion, dizziness and photophobia were observed. CONCLUSION: We introduced a new technique of pupilloplasty (C-pupilloplasty) which could be a more straight forward and more effective treatment for iris coloboma and traumatic iris defect.

The Separation, Purification, Structure Identification, and Antioxidant Activity of Elaeagnus umbellata Polysaccharides.

In order to investigate the antioxidant activity of Elaeagnus umbellata polysaccharides, the physicochemical characteristics of purified Elaeagnus umbellata polysaccharides (EUP, consisting of two fractions, EUP1 and EUP2) were investigated using UV spectrophotometry, high-performance liquid chromatography (HPLC), high-performance gel permeation chromatography (HPGPC), and Fourier transform infrared spectroscopy (FT-IR). This revealed that EUP1 and EUP2 were acidic polysaccharides with an average molecular weight (MW) of 63 and 38 kDa, respectively. EUP1 mainly consisted of L-rhamnose and D-galactose in a molar ratio of 2.05:1, and EUP2 consisted of D-mannose, L-rhamnose, D-galactose, and D-arabinose in a molar ratio of 2.06:1:2.78:1. Furthermore, EUP exhibited considerable antioxidant potential for scavenging hydroxyl, superoxide anion, DPPH, and ABTS radicals. Therefore, EUP can be developed as a potential antioxidant for the functional food or pharmaceutical field.

Determination of Flavonoid Compounds in Shanxi Aged Vinegars Based on Hydrophobic Deep Eutectic Solvent VALLME-HPLC Method: Assessment of the Environmental Impact of the Developed Method.

This research presents a novel, eco-friendly, vortex-assisted liquid-liquid microextraction (VALLME) approach, integrating hydrophobic deep eutectic solvents (DESs) with HPLC for the identification and quantification of nine specific flavonoids in Shanxi aged vinegar (SAV). The parameters of DES-VALLME, including the ratio of trioctylmethylammonium chloride to 1,4-butanediol (1:6), DES volume (150 µL), vortex duration (5 min), the concentration of NaCl (0.40 g), and centrifugation time (10 min), were optimized to achieve the maximum extraction efficiency of target substances. Under these optimal conditions, quantitative analyses performed via HPLC demonstrated a broad linear range of 0.20-50.00 µg/mL and correlation coefficients (r2) greater than 0.9944 for all nine calibration curves. The limits of detection (LOD) and limits of quantitation (LOQ) were 0.09-0.18 µg/mL and 0.30-0.60 µg/mL, respectively, ensuring high sensitivity. The relative standard deviations for intra-day and inter-day variability were within the acceptable range, 2.34-3.77% and 3.04-4.96%, respectively, demonstrating the method's reliability. The recovery rates ranged from 85.97% to 108.11%, underscoring the method's precision. This technique exhibited a significant enrichment effect (enrichment factor: 43 to 296) on SAV flavonoids. Notably, the eco-friendliness of this procedure was evaluated using the Analytical Eco-Scale, Green Analytical Procedure Index, and Analytical Greenness Metric. The results suggested that this technique is a viable green alternative to traditional flavonoid determination methods in SAV. In summary, this novel method provides a theoretical basis for assessing flavonoid content in SAV samples and tracing SAV products. This contribution has significant implications for enhancing analytical techniques in food chemistry and environmental science and the sustainable development of the food industry.

The antibacterial mechanism of perilla rosmarinic acid.

Rosmarinic acid (RosA) is a phenolic acid compound extracted from perilla. In this experiment, the Oxford cup method was used to verify the antibacterial activity of PerillaRosA against Escherichia coli, Staphylococcus aureus, Salmonella, and Bacillus subtilis. By polyacrylamide gel electrophoresis, the effect of RosA on bacterial nucleic acid and bacterial Na+ /K+ -ATP-ase activity, and scanning electron microscope to exploration of its antibacterial mechanism preliminarily. The results showed that RosA had antibacterial properties against all four bacteria. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of E. coli were 0.8 and 0.9 mg/ml, respectively. The MIC and MBC of Salmonella were 0.9 and 1.0 mg/ml, respectively. The MIC and MBC of S. aureus and B. subtilis were both 1.0 and 1.1 mg/ml. RosA has the bacteriostasis function, which can destroy bacterial cells and cell proteins and inhibit the activity of Na+ /K+ -ATP-ase in cells.

Plasma Ephrin-A1 level in a cohort of diabetic retinopathy patients.

BACKGROUND: To determine plasma ephrin-A1 and VEGF165 levels in a cohort of diabetic retinopathy patients. METHODS: Plasma ephrin-A1 and VEGF165 levels in fifty-five subjects including 19 individuals without diabetes (non-DM), 16 patients with diabetes (DM) but without diabetic retinopathy, and 20 patients with diabetic retinopathy (DR), were determined by ELISA. Serum creatinine, total cholesterol, fasting blood glucose and HbA1c were also measured. One-way ANOVA, Kruskal-Wallis Test, Mann-Whitney U Test corrected by Bonferroni, Pearson Correlation Analysis and Spearman Correlation Coefficient Analysis were used for data analysis. RESULTS: Ephrin-A1 expression could be detected in human plasma with an average of 1.52 ± 0.43 (mean ± SEM) ng/ml. In DR subjects, the plasma ephrin-A1concentration was 3.63 ± 4.63 ng/ml, which was significantly higher than that of the other two groups (non-DM: 0.27 ± 0.13 ng/ml, DM: 0.35 ± 0.34 ng/ml). The expression of VEGF165 in human plasma was 34.00 ± 42.55 pg/ml, with no statistical difference among the three groups. There was no correlation between ephrin-A1 and VEGF165 in human plasma, but there was a correlation between plasma ephrin-A1 and duration of diabetes. CONCLUSIONS: Plasma ephrin-A1 was highly expressed in patients with diabetic retinopathy, and there was no difference of plasma VEGF165 expression in patients with diabetic retinopathy compared to the other two groups, suggesting that changes of plasma ephrin-A1 may be a more sensitive biomarker than plasma VEGF165 in detecting diabetic retinopathy.

Fluorometric microplate-based dimethoate assay using CdSe/ZnS quantum dots coated with a molecularly imprinted polymer.

A microplate-based assay is described for the sensitive and selective fluorometric determination of the pesticide dimethoate. Molecularly imprinted polymer (MIP)-coated CdSe/ZnS quantum dots (QDs) are used as the molecular recognition probe. The MIP-coated QDs were synthesized using one-step reversed-phase microemulsion in the presence of hydrophobic CdSe/ZnS QDs. Copolymerization was performed by using 3-aminopropyltriethoxysilane as the functional monomer, tetraethoxysilane as the cross-linker, and dimethoate as the template. The fluorescence of the coated QDs is quenched by dimethoate when dimethoate becomes rebound on the imprinting sites of the MIP. Under the optimal conditions, fluorescence (best measured at excitation/emisison wavelengths of 380/620 nm) drops linearly in the 5.0-150 µg L-1 dimethoate concentration range, and the limit of detection is 2.1 µg L-1 (at S/N = 3). The assay was utilized for dimethoate determination in spiked real samples. Satisfactory recoveries (89.8%-98.0%) with relatively standard deviations of <4.9% are obtained. The method is rapid, cost-effective, sensitive, and selective. The use of microplate allows for the quantitation of a large number of samples simultaneously. Graphical abstract Schematic representation of sensitive and selective fluorometric microplate-based assay for the high-throughput determination of dimethoate (DM) based on recognition of molecularly imprinted polymer (MIP)-coated CdSe/ZnS quantum dots (QDs). DM exerts a quenching effect on the fluorescence of the QDs.

Analysis of Byzantine Attacks for Target Tracking in Wireless Sensor Networks.

Herein, the problem of target tracking in wireless sensor networks (WSNs) is investigated in the presence of Byzantine attacks. More specifically, we analyze the impact of Byzantine attacks on the performance of a tracking system. First, under the condition of jointly estimating the target state and the attack parameters, the posterior Cramer-Rao lower bound (PCRLB) is calculated. Then, from the perspective of attackers, we define the optimal Byzantine attack and theoretically find a way to achieve such an attack with minimal cost. When the attacked nodes are correctly identified by the fusion center (FC), we further define the suboptimal Byzantine attack and also find a way to realize such an attack. Finally, in order to alleviate the negative impact of attackers on the system performance, a modified sampling importance resampling (SIR) filter is proposed. Simulation results show that the tracking results of the modified SIR filter can be close to the true trajectory of the moving target. In addition, when the quantization level increases, both the security performance and the estimation performance of the tracking system are improved.

MicroRNA-33 promotes the replicative senescence of mouse embryonic fibroblasts by suppressing CDK6.

MicroRNAs are a large class of tiny noncoding RNAs, which have emerged as critical regulators of gene expression, and thus are involved in multiple cellular processes, including cellular senescence. MicroRNA-33 has previously been established to exert crucial effect on cell proliferation, lipid metabolism and cholesterol metabolism. Nonetheless, the association between microRNA-33 and cellular senescence and its underlying molecular mechanism are far to be elucidated. The present study has attempted to probe into the effect of microRNA-33 on MEFs senescence. Our data unveiled that microRNA-33 was dramatically down-regulated in senescent MEFs compared to the young MEFs, and ectopic expression of microRNA-33 promoted MEFs senescence, while knock-down of microRNA-33 exhibited a protective effect against senescence phenotype. Moreover, we verified CDK6 as a direct target of microRNA-33 in mouse. Silencing of CDK6 induced the premature senescence phenotype of MEFs similarly as microRNA-33, while enforced expression of CDK6 significantly reverse the senescence-induction effect of microRNA-33. Taken together, our results suggested that microRNA-33 enhanced the replicative senescence of MEFs potentially by suppressing CDK6 expression.

Enhancing Earth data analysis in 5G satellite networks: A novel lightweight approach integrating improved deep learning.

Efficiently handling huge data amounts and enabling processing-intensive applications to run in faraway areas simultaneously is the ultimate objective of 5G networks. Currently, in order to distribute computing tasks, ongoing studies are exploring the incorporation of fog-cloud servers onto satellites, presenting a promising solution to enhance connectivity in remote areas. Nevertheless, analyzing the copious amounts of data produced by scattered sensors remains a challenging endeavor. The conventional strategy of transmitting this data to a central server for analysis can be costly. In contrast to centralized learning methods, distributed machine learning (ML) provides an alternative approach, albeit with notable drawbacks. This paper addresses the comparative learning expenses of centralized and distributed learning systems to tackle these challenges directly. It proposes the creation of an integrated system that harmoniously merges cloud servers with satellite network structures, leveraging the strengths of each system. This integration could represent a major breakthrough in satellite-based networking technology by streamlining data processing from remote nodes and cutting down on expenses. The core of this approach lies in the adaptive tailoring of learning techniques for individual entities based on their specific contextual nuances. The experimental findings underscore the prowess of the innovative lightweight strategy, LMAED2L (Enhanced Deep Learning for Earth Data Analysis), across a spectrum of machine learning assignments, showcasing remarkable and consistent performance under diverse operational conditions. Through a strategic fusion of centralized and distributed learning frameworks, the LMAED2L method emerges as a dynamic and effective remedy for the intricate data analysis challenges encountered within satellite networks interfaced with cloud servers. The empirical findings reveal a significant performance boost of our novel approach over traditional methods, with an average increase in reward (4.1 %), task completion rate (3.9 %), and delivered packets (3.4 %). This report suggests that these advancements will catalyze the integration of cutting-edge machine learning algorithms within future networks, elevating responsiveness, efficiency, and resource utilization to new heights.

Local prediction-learning in high-dimensional spaces enables neural networks to plan.

Planning and problem solving are cornerstones of higher brain function. But we do not know how the brain does that. We show that learning of a suitable cognitive map of the problem space suffices. Furthermore, this can be reduced to learning to predict the next observation through local synaptic plasticity. Importantly, the resulting cognitive map encodes relations between actions and observations, and its emergent high-dimensional geometry provides a sense of direction for reaching distant goals. This quasi-Euclidean sense of direction provides a simple heuristic for online planning that works almost as well as the best offline planning algorithms from AI. If the problem space is a physical space, this method automatically extracts structural regularities from the sequence of observations that it receives so that it can generalize to unseen parts. This speeds up learning of navigation in 2D mazes and the locomotion with complex actuator systems, such as legged bodies. The cognitive map learner that we propose does not require a teacher, similar to self-attention networks (Transformers). But in contrast to Transformers, it does not require backpropagation of errors or very large datasets for learning. Hence it provides a blue-print for future energy-efficient neuromorphic hardware that acquires advanced cognitive capabilities through autonomous on-chip learning.

An all-fiber system biosensor for trace ß-lactam antibiotics detection enhanced by functionalized microfiber and fiber bragg grating.

An all-fiber-optic system for rapid detection of antibiotic concentration, based on an optical enzyme biosensor with microfiber interferometer (MFI) and fiber gratings (FBGs) power variation, is proposed and experimentally validated. During the experiment, ß-lactamase(ß-LS) is fixed on the polyaniline (PANI)-coated optical fiber by cross-linking through glutaraldehyde (GA) covalent bonding. ß-LS can hydrolyze ß-lactam antibiotics to generate acidic by-products that transform polyaniline from the form of the emerald base to emerald salt, which results in the surface refractive index (RI) variation of MFI, to convert MFI wavelength and FBGs power macroscopic change for feedbackingly detecting the concentration of ß-lactam antibiotics. The detection of amoxicillin (AMX) in deionized water at concentrations in the range of 0.01-100 nM resulted in a wavelength change sensitivity of 0.6 nm/nM, and FBGs power difference change sensitivity of 1.3 dB/nM, with a detection limit LOD = 0.04 nM in real food and urine samples. The sensing system by the same calibration technique can detect antibiotic concentrations in different substances (tap water, milk and artificial urine). This developed all-fiber-optic system can be used as a rapid solution for the measurement of ß-lactam antibiotic residues in food and the environment.

Selective Elucidation of Living Microbial Communities in Fermented Grains of Chinese Baijiu: Development of a Technique Integrating Propidium Monoazide Probe Pretreatment and Amplicon Sequencing.

The fermentation process of Chinese Baijiu's fermented grains involves the intricate succession and metabolism of microbial communities, collectively shaping the Baijiu's quality. Understanding the composition and succession of these living microbial communities within fermented grains is crucial for comprehending fermentation and flavor formation mechanisms. However, conducting high-throughput analysis of living microbial communities within the complex microbial system of fermented grains poses significant challenges. Thus, this study addressed this challenge by devising a high-throughput analysis framework using light-flavor Baijiu as a model. This framework combined propidium monoazide (PMA) pretreatment technology with amplicon sequencing techniques. Optimal PMA treatment parameters, including a concentration of 50 µM and incubation in darkness for 5 min followed by an exposure incubation period of 5 min, were identified. Utilizing this protocol, viable microorganism biomass ranging from 8.71 × 106 to 1.47 × 108 copies/µL was successfully detected in fermented grain samples. Subsequent amplicon sequencing analysis revealed distinct microbial community structures between untreated and PMA-treated groups, with notable differences in relative abundance compositions, particularly in dominant species such as Lactobacillus, Bacillus, Pediococcus, Saccharomycopsis, Issatchenkia and Pichia, as identified by LEfSe analysis. The results of this study confirmed the efficacy of PMA-amplicon sequencing technology for analyzing living microbial communities in fermented grains and furnished a methodological framework for investigating living microbial communities in diverse traditional fermented foods. This technical framework holds considerable significance for advancing our understanding of the fermentation mechanisms intrinsic to traditional fermented foods.