The differences of metabolic profiles, socioeconomic status and diabetic retinopathy in U.S. working-age and elderly adults with diabetes: results from NHANES 1999-2018.

AIMS: Controlled metabolic factors and socioeconomic status (SES) was crucial for prevention of diabetic retinopathy (DR). The study aims to assess the metabolic factors control and SES among working-age adults (18-64 years) with diabetes compared to older adults (65 years and older). METHODS: Totals of 6738 participants with self-reported diagnosed diabetes from National Health and Nutrition Examination Survey were included, of whom 3482 were working-age and 3256 were elderly. The prevalence of DR, metabolic factors control, and the impact of SES and diabetic duration on DR was estimated. Subgroup analysis among working-age adults was employed across different diabetic duration and SES level. RESULTS: The prevalence of DR was 20.8% among working-age adults and 20.6% in elderly adults. Further, working-age adults possessed suboptimal control on glycemia (median HbA1c: 7.0% vs. 6.8%, p < 0.001) and lipids (Low-density lipoprotein < 100 mg/dL: 46.4% vs. 63.5%, p < 0.001), but better blood pressure control (< 130/80 mmHg: 53.5% vs. 37.5%, p < 0.001) compared to the elderly, judging based on age-specific control targets. Prolonged diabetic duration didn't improve glycemic and composite factors control. SES like education and income impacted metabolic factors control and adults with higher SES were more likely to control well. Diabetic duration was a significant risk factor (OR = 4.006, 95%CI= (2.752,5.832), p < 0.001) while higher income (OR = 0.590, 95%CI= (0.421,0.826), p = 0.002) and educational level (OR = 0.637, 95%CI= (0.457,0.889), p = 0.008) were protective against DR. CONCLUSIONS: Working-age adults with diabetes demonstrate suboptimal metabolic profile control, especially glycemia and lipids. Additional efforts are needed to improve metabolic factor control and reduce DR risk, particularly for those with longer diabetes duration, less education, and lower incomes.

A jasmonate-mediated regulatory network modulates diurnal floret opening time in rice.

Diurnal floret opening time (DFOT) is a pivotal trait for successful fertilization and hybrid breeding in rice. However, the molecular mechanism underlying this trait is poorly understood in rice. In this study, we combined the cytological, genetic and molecular studies to demonstrate that jasmonic acid (JA) regulates DFOT in rice through modulating the turgor and osmotic pressure of the lodicules. We show that lodicules undergo dramatic morphologic changes, accompanied by changes in water and sugar contents during the process of floret opening. Consistently, a large set of genes associated with cell osmolality and cell wall remodeling exhibits distinct expression profiles at different time points in our time-course transcriptomes of lodicules. Notably, a group of JA biosynthesis and signaling genes is continuously upregulated, accompanied by a gradual increase in JA accumulation as floret opening approaching. Furthermore, we demonstrate that the JA biosynthesis gene OsAOS1 is required for endogenous JA biosynthesis in lodicules and promoting rice DFOT. Moreover, OsMYC2, a master regulator of JA signaling, regulates rice DFOT by directly activating OsAOS1, OsSWEET4, OsPIP2;2 and OsXTH9. Collectively, our findings establish a core regulatory network mediated by JA for modulating rice DFOT and provide effective gene targets for the genetic improvement of DFOT in rice.

Loneliness and social isolation are associated with an increased risk of glaucoma: a UK Biobank cohort study.

BACKGROUND: Loneliness and social isolation have been found to be associated with various health-related outcomes. Our study aimed to evaluate the association of loneliness and social isolation with the risk of glaucoma. METHODS: A total of 373,330 participants from the UK Biobank without glaucoma at recruitment were included in this study. Self-reported questionnaires were used to define loneliness and social isolation. Incident glaucoma events were identified by hospital inpatient admissions and self-reported data. COX proportional hazards models adjusted for sociodemographic, lifestyle, and health-related factors were used to estimate hazard ratios (HRs) and 95% CIs. RESULTS: During a median follow-up of 13.1 (interquartile range: 12.3-13.9) years, 6,489 participants developed glaucoma. After adjusting for confounding factors, loneliness (yes vs. no: adjusted HR: 1.16; 95% CI: 1.04-1.30; P = 0.009) and social isolation (yes vs. no: adjusted HR: 1.08; 95% CI: 1.01-1.16; P = 0.033) were associated with an increased risk of glaucoma. CONCLUSIONS: In this population-based prospective cohort study, loneliness and social isolation were associated with a higher risk of glaucoma.

Gut microbiota: a potential influencer of insomnia occurring after COVID-19 infection.

The prevalence of insomnia has increased in recent years, significantly affecting the lives of many individuals. Coronavirus disease 2019 (COVID-19) infection has been found to have a substantial impact on the human gut microbiota (GM). Clinical studies have shown that the high prevalence, prolonged duration, and refractory treatment of insomnia symptoms following the COVID-19 pandemic may be related to the effect of COVID-19 infection on the GM. Therefore, the GM may be a potential target for the treatment of insomnia following COVID-19 infection. However, relevant studies have not been well-documented, and the GM has not been sufficiently analyzed in the context of insomnia treatment. Herein, we review the interaction between sleep and the GM, summarize the characteristics of COVID-19-induced abnormal changes in the GM and metabolites in patients with insomnia, and discuss potential mechanisms, including metabolic, immune, and neural pathways, by which these abnormal changes in the GM cause insomnia as well as the factors affecting the GM. Finally, we discuss the prospect of modulating the host GM community for the effective treatment of insomnia after COVID-19 infection and the need for further clinical studies.

Effect of Stepwise Exposure to High-Level Erythromycin on Anaerobic Digestion.

High-level erythromycin (ERY) fermentation wastewater will pose serious threats to lake environments. Anaerobic digestion (AD) has advantages in treating high-level antibiotic wastewater. However, the fate of antibiotic resistance genes (ARGs) and microbial communities in AD after stepwise exposure to high-level ERY remains unclear. In this study, an AD reactor was first exposed to 0, 5, 10, 50, 100 and 200 mg/L ERY and then re-exposed to 0, 50, 200 and 500 mg/L ERY to investigate the effect of ERY on AD. The results show that AD could adapt to the presence of high-level ERY (500 mg/L) and could maintain efficient CH4 production after domestication with low-level ERY (50 mg/L). The AD process could achieve higher removal of ERY (>94%), regardless of the initial ERY concentration. ErmB and mefA, conferring resistance through target alteration and efflux pumps, respectively, were dominant in the AD process. The first exposure to ERY stimulated an increase in the total ARG abundance, while the AD process seemed to discourage ARG maintenance following re-exposure to ERY. ERY inhibited the process of acetoclastic methanogenesis, but strengthened the process of hydrogenotrophic methanogenesis. This work provides useful information for treating high-level ERY fermentation wastewater by the AD process.

Caries lesions diagnosis with deep convolutional neural network in intraoral QLF images by handheld device.

OBJECTIVES: This study investigated the effectiveness of a deep convolutional neural network (CNN) in diagnosing and staging caries lesions in quantitative light-induced fluorescence (QLF) images taken by a self-manufactured handheld device. METHODS: A small toothbrush-like device consisting of a 400 nm UV light-emitting lamp with a 470 nm filter was manufactured for intraoral imaging. A total of 133 cases with 9,478 QLF images of teeth were included for caries lesion evaluation using a CNN model. The database was divided into development, validation, and testing cohorts at a 7:2:1 ratio. The accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) were calculated for model performance. RESULTS: The overall caries prevalence was 19.59%. The CNN model achieved an AUC of 0.88, an accuracy of 0.88, a specificity of 0.94, and a sensitivity of 0.64 in the validation cohort. They achieved an overall accuracy of 0.92, a sensitivity of 0.95 and a specificity of 0.55 in the testing cohort. The model can distinguish different stages of caries well, with the best performance in detecting deep caries followed by intermediate and superficial lesions. CONCLUSIONS: Caries lesions have typical characteristics in QLF images and can be detected by CNNs. A QLF-based device with CNNs can assist in caries screening in the clinic or at home. TRIAL REGISTRATION: The clinical trial was registered in the Chinese Clinical Trial Registry (No. ChiCTR2300073487, Date: 12/07/2023).

Metal Uptake by Mitochondrial Carrier Family Proteins Using Lactococcus lactis.

Metal ion homeostasis in mitochondria is essential to maintaining proper cellular physiology. However, the ability of metals to bind off target or form complexes with multiple metabolites presents major challenges to understanding the mechanisms that govern this homeostasis. Adding further to the complexity, some of the major mitochondrial transporters have shown substrate promiscuity. In many cases, mitochondrial metals are found in the matrix compartment that is surrounded by the impermeable inner membrane. Four major classes of transporters facilitate the movement of solute across the inner membrane. These are mitochondrial carrier family, ATP-binding cassette transporters, mitochondrial pyruvate carriers, and sideroflexins. For iron, the matrix is the site of iron-sulfur clusters and heme synthesis and therefore transport must occur in a coordinated fashion with the cellular needs for these critical cofactors. Iron could be transported in numerous forms as it has been shown to form complexes with abundant metabolites such as citrate, nucleotides, or glutathione. Here, we describe assays to study iron (or any metal) transport by mitochondrial carrier family proteins expressed in Lactococcus lactis using a nisin-controlled expression system.

Generalization of cut-in pre-crash scenarios for autonomous vehicles based on accident data.

The utilization of high-risk test cases constitutes an effective approach to enhance the safety testing of autonomous vehicles (AVs) and enhance their efficiency. This research paper presents a derivation of 2052 high-hazard pre-crash scenarios for testing autonomous driving, which were based on 23 high-hazard cut-in accident scenarios from the National Automobile Accident In-Depth Investigation System (NAIS) through combining importance sampling and combined testing methods. Compared to the direct combination of the original distribution after sampling, the proposed method has a 2.92 times higher crash rate of 69.32% for the test case set in this paper. It also has a 5.8 times higher rate of triggering Automatic Emergency Braking (AEB), improving hazardous scenario coverage. Using the proposed method, the generated parameters of the cut-in accident scenario test set were compared with those of the cut-in test scenarios included in existing Chinese autonomous driving test protocols and standards. The velocity of the ego-vehicle obtained using the proposed method matched those in the existing protocols, whereas the velocity, time gap, and time to collision of the target vehicle were significantly lower than those existing protocols indicating scenarios obtained from accident data can enrich the selection of testing scenarios for autonomous driving.

Spermacoce alata Aubl. Essential Oil: Chemical Composition, In Vitro Antioxidant Activity, and Inhibitory Effects of Acetylcholinesterase, α-Glucosidase and ß-Lactamase.

Spermacoce alata Aubl. is widely available in the market as traditional Chinese medicine and animal feed, due to its properties of clearing heat and treating malaria and its high-protein and crude fiber content. In this study, the essential oil of S. alata was obtained through hydrodistillation. GC-MS and GC-FID methods were used to identify the chemical components and their relative abundance. Furthermore, the antioxidant capacity was measured using DPPH, ABTS, and FRAP assays, and the inhibitory effects of acetylcholinesterase, α-glucosidase, and ß-lactamase were also evaluated. A total of 67 compounds were identified, with the major constituents being palmitic acid (30.74%), linoleic acid (16.13%), and phenylheptatriyne (8.07%). The essential oil exhibited moderate antioxidant activity against DPPH (IC50 > 10 mg/mL), while the IC50 value for the ABTS assay was 3.84 ± 2.12 mg/mL and the FRAP assay value was 87.22 ± 12.22 µM/g. Additionally, the essential oil showed moderate anti-acetylcholinesterase activity (IC50 = 286.0 ± 79.04 µg/mL), significant anti-α-glucosidase activity (IC50 = 174.7 ± 13.12 µg/mL), and potent anti-ß-lactamase activity (IC50 = 37.56 ± 3.48 µg/mL). The results suggest that S. alata has the potential for application in pharmacology, warranting further exploration and investigation.

PCAS: An Integrated Tool for Multi-Dimensional Cancer Research Utilizing Clinical Proteomic Tumor Analysis Consortium Data.

Proteomics offers a robust method for quantifying proteins and elucidating their roles in cellular functions, surpassing the insights provided by transcriptomics. The Clinical Proteomic Tumor Analysis Consortium database, enriched with comprehensive cancer proteomics data including phosphorylation and ubiquitination profiles, alongside transcriptomics data from the Genomic Data Commons, allow for integrative molecular studies of cancer. The ProteoCancer Analysis Suite (PCAS), our newly developed R package and Shinyapp, leverages these resources to facilitate in-depth analyses of proteomics, phosphoproteomics, and transcriptomics, enhancing our understanding of the tumor microenvironment through features like immune infiltration and drug sensitivity analysis. This tool aids in identifying critical signaling pathways and therapeutic targets, particularly through its detailed phosphoproteomic analysis. To demonstrate the functionality of the PCAS, we conducted an analysis of GAPDH across multiple cancer types, revealing a significant upregulation of protein levels, which is consistent with its important biological and clinical significance in tumors, as indicated in our prior research. Further experiments were used to validate the findings performed using the tool. In conclusion, the PCAS is a powerful and valuable tool for conducting comprehensive proteomic analyses, significantly enhancing our ability to uncover oncogenic mechanisms and identify potential therapeutic targets in cancer research.

Walnut-Derived Peptides Alleviate Learning and Memory Impairments in a Mice Model via Inhibition of Microglia Phagocytose Synapses.

Microglia phagocytose synapses have an important effect on the pathogenesis of neurological disorders. Here, we investigated the neuroprotective effects of the walnut-derived peptide, TWLPLPR(TW-7), against LPS-induced cognitive deficits in mice and explored the underlying C1q-mediated microglia phagocytose synapses mechanisms in LPS-treated HT22 cells. The MWM showed that TW-7 improved the learning and memory capacity of the LPS-injured mice. Both transmission electron microscopy and immunofluorescence analysis illustrated that synaptic density and morphology were increased while associated with the decreased colocalized synapses with C1q. Immunohistochemistry and immunofluorescence demonstrated that TW-7 effectively reduced the microglia phagocytosis of synapses. Subsequently, overexpression of C1q gene plasmid was used to verify the contribution of the TW-7 via the classical complement pathway-regulated mitochondrial function-mediated microglia phagocytose synapses in LPS-treated HT22 cells. These data suggested that TW-7 improved the learning and memory capability of LPS-induced cognitively impaired mice through a mechanism associated with the classical complement pathway-mediated microglia phagocytose synapse.

Metabolite analysis reveals flavonoids accumulation during flower development in Rhododendron pulchrum sweet (Ericaceae).

The azalea (Rhododendron simsii Planch.) is an important ornamental woody plant with various medicinal properties due to its phytochemical compositions and components. However little information on the metabolite variation during flower development in Rhododendron has been provided. In our study, a comparative analysis of the flavonoid profile was performed in Rhododendron pulchrum sweet at three stages of flower development, bud (stage 1), partially open flower (stage 2), and full bloom (stage 3). A total of 199 flavonoids, including flavone, flavonol, flavone C-glycosides, flavanone, anthocyanin, and isoflavone were identified. In hierarchical clustering analysis (HCA) and principal component analysis (PCA), the accumulation of flavonoids displayed a clear development stage variation. During flower development, 78 differential accumulated metabolites (DAMs) were identified, and most were enriched to higher levels at the full bloom stage. A total of 11 DAMs including flavone (chrysin, chrysoeriol O-glucuronic acid, and chrysoeriol O-hexosyl-O-pentoside), isoflavone (biochanin A), and flavonol (3,7-di-O-methyl quercetin and isorhamnetin) were significantly altered at three stages. In particular, 3,7-di-O-methyl quercetin was the top increased metabolite during flower development. Furthermore, integrative analyses of metabolomic and transcriptomic were conducted, revealing that the contents of isoflavone, biochanin A, glycitin, and prunetin were correlated with the expression of 2-hydroxyisoflavanone dehydratase (HIDH), which provide insight into the regulatory mechanism that controls isoflavone biosynthesis in R. pulchrum. This study will provide a new reference for increasing desired metabolites effectively by more accurate or appropriate genetic engineering strategies.

Non-pharmaceutical interventions in containing COVID-19 pandemic after the roll-out of coronavirus vaccines: a systematic review.

BACKGROUND: Non-pharmaceutical interventions (NPIs) have been widely utilised to control the COVID-19 pandemic. However, it is unclear what the optimal strategies are for implementing NPIs in the context of coronavirus vaccines. This study aims to systematically identify, describe, and evaluate existing ecological studies on the real-world impact of NPIs in containing COVID-19 pandemic following the roll-out of coronavirus vaccines. METHODS: We conducted a comprehensive search of relevant studies from January 1, 2021, to June 4, 2023 in PubMed, Embase, Web of science and MedRxiv. Two authors independently assessed the eligibility of the studies and extracted the data. A risk of bias assessment tool, derived from a bibliometric review of ecological studies, was applied to evaluate the study design, statistical methodology, and the quality of reporting. Data were collected, synthesised and analysed using qualitative and quantitative methods. The results were presented using summary tables and figures, including information on the target countries and regions of the studies, types of NPIs, and the quality of evidence. RESULTS: The review included a total of 17 studies that examined the real-world impact of NPIs in containing the COVID-19 pandemic after the vaccine roll-out. These studies used five composite indicators that combined multiple NPIs, and examined 14 individual NPIs. The studies had an average quality assessment score of 13 (range: 10-16), indicating moderately high quality. NPIs had a larger impact than vaccination in mitigating the spread of COVID-19 during the early stage of the vaccination implementation and in the context of the Omicron variant. Testing policies, workplace closures, and restrictions on gatherings were the most effective NPIs in containing the COVID-19 pandemic, following the roll-out of vaccines. The impact of NPIs varied across different time frames, countries and regions. CONCLUSION: NPIs had a larger contribution to the control of the pandemic as compared to vaccination during the early stage of vaccine implementation and in the context of the omicron variant. The impact of NPIs in containing the COVID-19 pandemic exhibited variability in diverse contexts. Policy- and decision-makers need to focus on the impact of different NPIs in diverse contexts. Further research is needed to understand the policy mechanisms and address potential future challenges.

The influence of the doping concentration and reverse intersystem crossing on the efficiency of tricomponent organic light-emitting diodes with the thermally activated delayed fluorescence exciplex emitter.

In this work, we fabricate a series of full-fluorescent organic light-emitting diodes (OLEDs) with the thermally activated delayed fluorescence (TADF) exciplex emitter in order to improve the efficiency through the reverse intersystem crossing (RISC) process. The TADF exciplex emitters are made up of a mixture of P-type materials (DMAC-DPS and mCBP) and n-type material (PO-T2T), among which DMAC-DPS also classes as a TADF material. The change in doping concentration will affect the intermolecular distance and the composition of TADF material and two kinds of exciplexes (DMAC-DPS:PO-T2T and mCBP:PO-T2T) in the luminescent layer (EML). Different materials and concentrations of doping not only add new RISC channels but also alter the original RISC channels, thereby affecting the performance of devices. It is beneficial for improving efficiency by increasing the proportion of independent TADF material and reducing the proportion of exciplex (DMAC-DPS:PO-T2T) in the EML, which can be controlled by doping. When the ratio of DMAC-DPS, PO-T2T and mCBP in the EML is 1 : 1 : 2, we achieve the optimal electro-optic performance in device A3, with maximum current efficiency, power efficiency, and luminance of 41.64 cd A-1, 43.42 lm W-1, and 23 080 cd m-2, respectively.

A combined AIMD and DFT study of the low-energy radiation responses of GaN.

Although GaN is a promising candidate for semiconductor devices, degradation of GaN-based device performance may occur when the device is bombarded by high-energy charged particles during its application in aerospace, astronomy, and nuclear-related areas. It is thus of great significance to explore the influence of irradiation on the microstructure and electronic properties of GaN and to reveal the internal relationship between the damage mechanisms and physical characteristics. Using a combined density functional theory (DFT) and ab initio molecular dynamics (AIMD) study, we explored the low-energy recoil events in GaN and the effects of point defects on GaN. The threshold displacement energies (Eds) significantly depend on the recoil directions and the primary knock-on atoms. Moreover, the Ed values for nitrogen atoms are smaller than those for gallium atoms, indicating that the displacement of nitrogen dominates under electron irradiation and the created defects are mainly nitrogen vacancies and interstitials. The formation energy of nitrogen vacancies and interstitials is smaller than that for gallium vacancies and interstitials, which is consistent with the AIMD results. Although the created defects improve the elastic compliance of GaN, these radiation damage states deteriorate its ability to resist external compression. Meanwhile, these point defects lead the Debye temperature to decrease and thus increase the thermal expansion coefficients of GaN. As for the electronic properties of defective GaN, the point defects have various effects, i.e., VN (N vacancy), Gaint (Ga interstitial), Nint (N interstitial), and GaN (Ga occupying the N lattice site) defects induce the metallicity, and NGa (N occupying the Ga lattice site) defects decrease the band gap. The presented results provide underlying mechanisms for defect generation in GaN, and advance the fundamental understanding of the radiation resistances of semiconductor materials.

Unraveling pancreatic ductal adenocarcinoma immune prognostic signature through a naive B cell gene set.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC), a leading cause of cancer mortality, has a complex pathogenesis involving various immune cells, including B cells and their subpopulations. Despite emerging research on the role of these cells within the tumor microenvironment (TME), the detailed molecular interactions with tumor-infiltrating immune cells (TIICs) are not fully understood. METHODS: We applied CIBERSORT to quantify TIICs and naive B cells, which are prognostic for PDAC. Marker genes from scRNA-seq and modular genes from weighted gene co-expression network analysis (WGCNA) were integrated to identify naive B cell-related genes. A prognostic signature was constructed utilizing ten machine-learning algorithms, with validation in external cohorts. We further assessed the immune cell diversity, ESTIMATE scores, and immune checkpoint genes (ICGs) between patient groups stratified by risk to clarify the immune landscape in PDAC. RESULTS: Our analysis identified 994 naive B cell-related genes across single-cell and bulk transcriptomes, with 247 linked to overall survival. We developed a 12-gene prognostic signature using Lasso and plsRcox algorithms, which was confirmed by 10-fold cross-validation and showed robust predictive power in training and real-world cohorts. Notably, we observed substantial differences in immune infiltration between patients with high and low risk. CONCLUSION: Our study presents a robust prognostic signature that effectively maps the complex immune interactions in PDAC, emphasizing the critical function of naive B cells and suggesting new avenues for immunotherapeutic interventions. This signature has potential clinical applications in personalizing PDAC treatment, enhancing the understanding of immune dynamics, and guiding immunotherapy strategies.

Diabetes-Related Macrovascular Complications Are Associated With an Increased Risk of Diabetic Microvascular Complications: A Prospective Study of 1518 Patients With Type 1 Diabetes and 20 802 Patients With Type 2 Diabetes in the UK Biobank.

BACKGROUND: Diabetic vascular complications share common pathophysiological mechanisms, but the relationship between diabetes-related macrovascular complications (MacroVCs) and incident diabetic microvascular complications remains unclear. We aimed to investigate the impact of MacroVCs on the risk of microvascular complications. METHODS AND RESULTS: There were 1518 participants with type 1 diabetes (T1D) and 20 802 participants with type 2 diabetes from the UK Biobank included in this longitudinal cohort study. MacroVCs were defined by the presence of macrovascular diseases diagnosed after diabetes at recruitment, including coronary heart disease, peripheral artery disease, stroke, and ≥2 MacroVCs. The primary outcome was incident microvascular complications, a composite of diabetic retinopathy, diabetic kidney disease, and diabetic neuropathy. During a median (interquartile range) follow-up of 11.61 (5.84-13.12) years and 12.2 (9.50-13.18) years, 596 (39.3%) and 4113 (19.8%) participants developed a primary outcome in T1D and type 2 diabetes, respectively. After full adjustment for conventional risk factors, Cox regression models showed significant associations between individual as well as cumulative MacroVCs and the primary outcome, except for coronary heart disease in T1D (T1D: diabetes coronary heart disease: 1.25 [0.98-1.60]; diabetes peripheral artery disease: 3.00 [1.86-4.84]; diabetes stroke: 1.71 [1.08-2.72]; ≥2: 2.57 [1.66-3.99]; type 2 diabetes: diabetes coronary heart disease: 1.59 [1.38-1.82]; diabetes peripheral artery disease: 1.60 [1.01-2.54]; diabetes stroke: 1.50 [1.13-1.99]; ≥2: 2.66 [1.92-3.68]). Subgroup analysis showed that strict glycemic (glycated hemoglobin <6.5%) and blood pressure (<140/90 mm Hg) control attenuated the association. CONCLUSIONS: Individual and cumulative MacroVCs confer significant risk of incident microvascular complications in patients with T1D and type 2 diabetes. Our results may facilitate cost-effective high-risk population identification and development of precise prevention strategies.

Microbiome dynamics and products profiles of biowaste fermentation under different organic loads and additives.

Biowaste fermentation is a promising technology for low-carbon print bioenergy and biochemical production. Although it is believed that the microbiome determines both the fermentation efficiency and the product profiles of biowastes, the explicit mechanisms of how microbial activity controls fermentation processes remained to be unexplored. The current study investigated the microbiome dynamics and fermentation product profiles of biowaste fermentation under different organic loads (5, 20, and 40 g-VS/L) and with additives that potentially modulate the fermentation process via methanogenesis inhibition (2-bromoethanesulfonate) or electron transfer promotion (i.e., reduced iron, magnetite iron, and activated carbon). The overall fermentation products yields were 440, 373 and 208 CH4-eq/g-VS for low-, medium- and high-load fermentation. For low- and medium-load fermentation, volatile fatty acids (VFAs) were first accumulated and were gradually converted to methane. For high-load fermentation, VFAs were the main fermentation products during the entire fermentation period, accounting for 62% of all products. 16S rRNA-based analyses showed that both 2-bromoethanesulfonate addition and increase of organic loads inhibited the activity of methanogens and promoted the activity of distinct VFA-producing bacterial microbiomes. Moreover, the addition of activated carbon promoted the activity of H2-producing Bacteroides, homoacetogenic Eubacteriaceae and methanogenic Methanosarcinaceae, whose activity dynamics during the fermentation led to changes in acetate and methane production. The current results unveiled mechanisms of microbiome activity dynamics shaping the biowaste fermentation product profiles and provided the fundamental basis for the development of microbiome-guided engineering approaches to modulate biowaste fermentation toward high-value product recovery.