Regulatory effects of tea polysaccharides on hepatic inflammation, gut microbiota dysbiosis, and serum metabolomic signatures in beef cattle under heat stress.

Background: Long-term heat stress (HS) severely restricts the growth performance of beef cattle and causes various health problems. The gut microbiota plays a crucial role in HS-associated inflammation and immune stress involving lymphocyte function. This study investigated the effects of dietary tea polysaccharide (TPS), a natural acidic glycoprotein, on HS-induced anorexia, inflammation, and gut microbiota dysbiosis in Simmental beef cattle. Methods: The cattle were divided into two groups, receiving either normal chow or normal chow plus TPS (8 g/kg, 0.8%). Transcriptome sequencing analysis was used to analysis the differential signaling pathway of liver tissue. 16S rDNA sequencing was performed to analysis gut microbiota of beef cattle. Serum metabolite components were detected by untargeted metabolomics analysis. Results: Hepatic transcriptomics analysis revealed that differentially expressed genes in TPS-fed cattle were primarily enriched in immune processes and lymphocyte activation. TPS administration significantly reduced the expression of the TLR4/NF-κB inflammatory signaling pathway, alleviating HS-induced hepatic inflammation. Gut microbiota analysis revealed that TPS improved intestinal homeostasis in HS-affected cattle by increasing bacterial diversity and increasing the relative abundances of Akkermansia and Alistipes while decreasing the Firmicutes-to-Bacteroidetes ratio and the abundance of Agathobacter. Liquid chromatography-tandem mass spectrometry (LC‒MS/MS) analysis indicated that TPS significantly increased the levels of long-chain fatty acids, including stearic acid, linolenic acid, arachidonic acid, and adrenic acid, in the serum of cattle. Conclusion: These findings suggest that long-term consumption of tea polysaccharides can ameliorate heat stress-induced hepatic inflammation and gut microbiota dysbiosis in beef cattle, suggesting a possible liver-gut axis mechanism to mitigate heat stress.

Estimation of cognitive impairment in chronic pain patients and characteristics of estimated mild cognitive impairment.

Background: Patients with chronic pain suffer from psychological effects such as anxiety due to the pain itself. Pain can not only impair activities of daily living (ADL) and quality of life (QOL), but also impair cognitive function. Therefore, in this study, we aimed to estimate the cognitive function of chronic pain patients using a deep neural network (DNN) model that has already been implemented in society. We investigated the characteristics of patients presumed to have mild cognitive impairment (MCI) and, at the same time, verified the relationship with the questionnaire commonly used in chronic pain research, which is administered by 43 university affiliated hospitals and medical institutions participating in the chronic pain research group of the Ministry of Health, Labor and Welfare in Japan (assessment batteries). Method: The study included 114 outpatients from a multidisciplinary pain clinic, and we estimated their Mini-Mental State Examination (MMSE) scores based on age and basic blood test data (23 items). Furthermore, we classified the estimated MMSE scores of chronic pain patients into two groups based on a cutoff score of 27, which indicates MCI, and compared the blood data and assessment batteries. Additionally, we used a control group of 252 healthy adults aged 45 years or older who visited a dementia prevention outpatient clinic for comparison with the MMSE scores of chronic pain patients. Result: The MMSE scores in chronic pain patients were below the cutoff for MCI. When classified into two groups based on the estimated MMSE score of 27 points, WBC, RBC, Hb, Hct, PLT, UA, BUN, creatinine, Triglyceride, and γ-GT were significantly higher in the blood data. In the MCI group, PDAS values were significantly lower. Furthermore, only in the non-MCI group, a significant correlation was found between the estimated MMSE value and BPI, PDAS, and Locomo. The estimated MMSE scores were significantly lower in chronic pain patients than in healthy adults (p = 0.04). Conclusion: Patients with chronic pain may exhibit cognitive impairment due to systemic metabolic disturbances. This suggests that chronic pain affects activities of daily living, resulting in systemic metabolic disorders.

Relationship Between Cognitive Function, Oral Conditions and Systemic Metabolic Function in the Elderly.

Systemic metabolic disorders, including lifestyle-related diseases, are known risk factors for dementia. Furthermore, oral diseases such as periodontal disease and tooth decay are also associated with systemic metabolic disorders such as lifestyle-related diseases, and have also been reported to be indicators of risk factors for developing dementia. In this study, we investigated the relationship between cognitive function, oral conditions and systemic metabolic function in the elderly. We investigated the number of healthy teeth, the number of prosthetic teeth fitted, the number of missing prosthetic teeth, etc., in 41 elderly patients (69.7 ± 5.6 years old). Cognitive function was evaluated by the Mini Mental State Examination (MMSE). We also estimated MMSE scores for each subject using deep learning-based assessment of MMSE scores. This deep learning method enables the estimation of the MMSE score based on basic blood test data from medical examinations and reflects the systemic metabolic state including lifestyle-related diseases. The estimated MMSE score correlated negatively with age (r = -0.381), correlated positively with the number of healthy teeth (r = 0.37), and correlated negatively with the number of missing prosthetic teeth (r = -0.39). This relationship was not found in the measured MMSE scores. A negative correlation (r = -0.36) was found between age and the current number of teeth and a positive correlation (r = 0.37) was found between age and the number of missing prosthetic teeth. A positive correlation was found between the number of teeth requiring prosthesis and lifestyle-related diseases. The deep learning-based estimation method of cognitive function clearly demonstrated the close relationship between oral health condition, systemic metabolic function and the risk of cognitive impairment. It was determined that the smaller the number of existing teeth and the larger the number of missing prosthetic teeth, the higher is the risk of cognitive impairment. Systemic metabolic function is presumed to affect oral health and cognitive function. Interestingly, no such relationship was found in the measured MMSE scores. There are two possible reasons for this. The first is that MMSE is a subjective test and is less accurate in assessing cognitive function. The second is that because the MMSE estimated based on blood data using deep learning is calculated based on the metabolic function, it has a stronger correlation with the oral health condition affected by the metabolic function. In conclusion, oral health condition may predict cognitive impairment in the elderly.

Single-cell RNA-seq of Lotus japonicus provide insights into identification and function of root cell types of legume.

The roots of legume plant play a crucial role in nitrogen fixation. However, the transcriptomes of different cell types of legume root and their functions remain largely unknown. Here, we performed single-cell RNA sequencing and profiled more than 22,000 single cells from root tips of Lotus japonicus, a model species of legume. We identified seven clusters corresponding to seven major cell types, which were validated by in situ hybridization. Further analysis revealed regulatory programs including phytohormone and nodulation associated with specific cell types, and revealed conserved and diverged features for the cell types. Our results represent the first single-cell resolution transcriptome for legume root tips and a valuable resource for studying the developmental and physiological functions of various cell types in legumes.

Turning C1-gases to isobutanol towards great environmental and economic sustainability via innovative biological routes: two birds with one stone.

BACKGROUND: The dramatic increase in greenhouse gas (GHG) emissions, which causes serious global environmental issues and severe climate changes, has become a global problem of concern in recent decades. Currently, native and/or non-native C1-utilizing microbes have been modified to be able to effectively convert C1-gases (biogas, natural gas, and CO2) into isobutanol via biological routes. Even though the current experimental results are satisfactory in lab-scale research, the techno-economic feasibility of C1 gas-derived isobutanol production at the industrial scale still needs to be analyzed and evaluated, which will be essential for the future industrialization of C1-gas bioconversion. Therefore, techno-economic analyses were conducted in this study with comparisons of capital cost (CAPEX), operating cost (OPEX), and minimum isobutanol selling price (MISP) derived from biogas (scenario #1), natural gas (scenario #2), and CO2 (scenario #3) with systematic economic assessment. RESULTS: By calculating capital investments and necessary expenses, the highest CAPEX ($317 MM) and OPEX ($67 MM) were projected in scenario #1 and scenario #2, respectively. Because of the lower CAPEX and OPEX from scenario #3, the results revealed that bioconversion of CO2 into isobutanol temporally exhibited the best economic performance with an MISP of $1.38/kg isobutanol. Furthermore, a single sensitivity analysis with nine different parameters was carried out for the production of CO2-derived isobutanol. The annual plant capacity, gas utilization rate, and substrate cost are the three most important economic-driving forces on the MISP of CO2-derived isobutanol. Finally, a multiple-point sensitivity analysis considering all five parameters simultaneously was performed using ideal targets, which presented the lowest MISP of $0.99/kg in a long-term case study. CONCLUSIONS: This study provides a comprehensive assessment of the bioconversion of C1-gases into isobutanol in terms of the bioprocess design, mass/energy calculation, capital investment, operating expense, sensitivity analysis, and minimum selling price. Compared with isobutanol derived from biogas and natural gas, the CO2-based isobutanol showed better economic feasibility. A market competitive isobutanol derived from CO2 is predicable with lower CO2 cost, better isobutanol titer, and higher annual capacity. This study will help researchers and decision-makers explore innovative and effective approaches to neutralizing GHGs and focus on key economic-driving forces to improve techno-economic performance.

Estimation of Human Cerebral Atrophy Based on Systemic Metabolic Status Using Machine Learning.

Background: Based on the assumption that systemic metabolic disorders affect cognitive function, we have developed a deep neural network (DNN) model that can estimate cognitive function based on basic blood test data that do not contain dementia-specific biomarkers. In this study, we used the same DNN model to assess whether basic blood data can be used to estimate cerebral atrophy. Methods: We used data from 1,310 subjects (58.32 ± 12.91years old) enrolled in the Brain Doc Bank. The average Mini Mental State Examination score was 28.6 ± 1.9. The degree of cerebral atrophy was determined using the MRI-based index (GM-BHQ). First, we evaluated the correlations between the subjects' age, blood data, and GM-BHQ. Next, we developed DNN models to assess the GM-BHQ: one used subjects' age and blood data, while the other used only blood data for input items. Results: There was a negative correlation between age and GM-BHQ scores (r = -0.71). The subjects' age was positively correlated with blood urea nitrogen (BUN) (r = 0.40), alkaline phosphatase (ALP) (r = 0.22), glucose (GLU) (r = 0.22), and negative correlations with red blood cell counts (RBC) (r = -0.29) and platelet counts (PLT) (r = -0.26). GM-BHQ correlated with BUN (r = -0.30), GLU (r = -0.26), PLT (r = 0.26), and ALP (r = 0.22). The GM-BHQ estimated by the DNN model with subject age exhibited a positive correlation with the ground truth GM-BHQ (r = 0.70). Furthermore, even if the DNN model without subject age was used, the estimated GM-BHQ showed a significant positive correlation with ground truth GM-BHQ (r = 0.58). Age was the most important variable for estimating GM-BHQ. Discussion: Aging had the greatest effect on cerebral atrophy. Aging also affects various organs, such as the kidney, and causes changes in systemic metabolic status, which may contribute to cerebral atrophy and cognitive impairment. The DNN model may serve as a new screening test for dementia using basic blood tests for health examinations. Finally, the blood data reflect systemic metabolic disorders in each subject-this method may thus contribute to personalized care.

Simultaneous and Efficient Removal of Oleophilic and Hydrophilic Stains from Polyurethane by the Combination of Easy-Cleaning and Self-Cleaning.

The simultaneous and efficient removal of oleophilic and hydrophilic stains from polyurethane (PU) is realized by combining the easy-cleaning from the hydrophilic thermoresponsive hydrogel coating containing acrylamide (AAm), gum arabic (GA), and (ethylene glycol) methyl ether methacrylate (OEGMA300) P(GA/AAm/OEGMA300) and the self-cleaning from the embedded nonmetallic photocatalyst g-C3N4. Due to the existence of strong hydrogen bonds between the hydroxyl groups in the hybrid hydrogel coating and the hydroxyl/carboxyl groups in the plasma-treated PU, the hybrid hydrogel coating is very stable on PU. Simultaneously, the acrylamide network in the hybrid hydrogel coating enhances its mechanical strength. Because the transition temperature of OEGMA300 is well above the room temperature, the cross-linked coating remains hydrophilic in ambient conditions. Thus, oleophilic stains, such as oil and grease, can be easily removed from the coating surface. In addition, the embedded photocatalyst g-C3N4 in the hybrid hydrogel coating introduces the extra capability of decomposing organic compounds under sunshine, which favors the removal of hydrophilic stains such as dyes and wines. After sunlight illumination and simply rinsing with water, both hydrophilic and oleophilic stains can be easily removed. Moreover, this joint cleaning performance can work for a long time. Even after four consecutive cycles, both the easy-cleaning to oleophilic stains by the hydrophilic hydrogel surface and self-cleaning to the hydrophilic stains by the embedded g-C3N4 remain unchanged.

Bio-valorization of C1 gaseous substrates into bioalcohols: Potentials and challenges in reducing carbon emissions.

C1 gaseous substrates (CH4, CO2, and CO) derived from natural gas, biogas, and syngas, are of interest due to their threats to the environment or inefficient utilization. Benefiting from advanced genetic editing tools and bioconversion strategies, metabolically engineered C1-gas-utilizing microorganisms (CGUM), such as methanotrophs, cyanobacteria, and acetogens, are capable of utilizing C1 gaseous feedstocks as the sole substrates for cell growth and synthesis of chemicals and biofuels. In this paper, we critically review metabolic pathways related to the assimilation of C1 gaseous substrates for alcohol biosynthesis in several model CGUM. Metabolic engineering approaches utilized to enhance the carbon conversion efficiency, microbial growth and biosynthesis of desired alcohols are summarized, including the regulation of C1 gaseous substrates activation and electron and energy supply, the accumulation of key intermediates, and the manipulation of target gene expression to optimize carbon flux to bioalcohols. In addition, challenges in the efficient microbial conversion of C1 gaseous substrates are explored and discussed. The strategies of bioalcohol biosynthesis presented here could guide the development of a variety of efficient biological routes for CH4, CO2, and CO utilization in the future.

The key regulator LcERF056 enhances salt tolerance by modulating reactive oxygen species-related genes in Lotus corniculatus.

BACKGROUND: The APETALA2/ethylene response factor (AP2/ERF) family are important regulatory factors involved in plants' response to environmental stimuli. However, their roles in salt tolerance in Lotus corniculatus remain unclear. RESULTS: Here, the key salt-responsive transcription factor LcERF056 was cloned and characterised. LcERF056 belonging to the B3-1 (IX) subfamily of ERFs was considerably upregulated by salt treatment. LcERF056-fused GFP was exclusively localised to nuclei. Furthermore, LcERF056- overexpression (OE) transgenic Arabidopsis and L. corniculatus lines exhibited significantly high tolerance to salt treatment compared with wild-type (WT) or RNA interference expression (RNAi) transgenic lines at the phenotypic and physiological levels. Transcriptome analysis of OE, RNAi, and WT lines showed that LcERF056 regulated the downstream genes involved in several metabolic pathways. Chromatin immunoprecipitation-quantitative polymerase chain reaction (ChIP-qPCR) and yeast one-hybrid (Y1H) assay demonstrated that LcERF056 could bind to cis-element GCC box or DRE of reactive oxygen species (ROS)-related genes such as lipid-transfer protein, peroxidase and ribosomal protein. CONCLUSION: Our results suggested that the key regulator LcERF056 plays important roles in salt tolerance in L. corniculatus by modulating ROS-related genes. Therefore, it may be a useful target for engineering salt-tolerant L. corniculatus or other crops.

Exploration of an Efficient Electroporation System for Heterologous Gene Expression in the Genome of Methanotroph.

One-carbon (C1) substrates such as methane and methanol have been considered as the next-generation carbon source in industrial biotechnology with the characteristics of low cost, availability, and bioconvertibility. Recently, methanotrophic bacteria naturally capable of converting C1 substrates have drawn attractive attention for their promising applications in C1-based biomanufacturing for the production of chemicals or fuels. Although genetic tools have been explored for metabolically engineered methanotroph construction, there is still a lack of efficient methods for heterologous gene expression in methanotrophs. Here, a rapid and efficient electroporation method with a high transformation efficiency was developed for a robust methanotroph of Methylomicrobium buryatense 5GB1. Based on the homologous recombination and high transformation efficiency, gene deletion and heterologous gene expression can be simultaneously achieved by direct electroporation of PCR-generated linear DNA fragments. In this study, the influence of several key parameters (competent cell preparation, electroporation condition, recovery time, and antibiotic concentration) on the transformation efficiency was investigated for optimum conditions. The maximum electroporation efficiency of 719 ± 22.5 CFU/µg DNA was reached, which presents a 10-fold improvement. By employing this method, an engineered M. buryatense 5GB1 was constructed to biosynthesize isobutyraldehyde by replacing an endogenous fadE gene in the genome with a heterologous kivd gene. This study provides a potential and efficient strategy and method to facilitate the cell factory construction of methanotrophs.