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.

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.

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.

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.

Biosafe, self-adhesive, recyclable, tough, and conductive hydrogels for multifunctional sensors.

As a bioelectronic material used in personalized medicine, it is necessary to integrate excellent adhesion and stretchability in hydrogels for ensuring biosafety. Herein, a high-performance multifunctional hydrogel of polyvinyl alcohol-sodium alginate-g-dopamine-silver nanowire-borax (PSAB) is reported. It can not only easily adhere to the surface of various substrates, but also exhibit excellent mechanical properties. Its tensile strength, elongation at break and toughness are 0.286 MPa, 500% and 55.15 MJ m-3, respectively. The excellent mechanical properties and high conductivity guarantee that the PSAB hydrogel can successfully serve as a multifunctional sensor for detecting small activities and large-scale movements of the human body through strain and pressure changes. Meanwhile, the long-lasting potent and broad-spectrum antibacterial activity, combined with good in vitro biocompatibility, guarantees the biological safety and non-toxicity of the PSAB hydrogel. These compelling features, such as high flexibility and elasticity, high adhesion, multi-functional sensing and recyclability, as well as biological safety, pave the way for the application of PSAB hydrogel e-skin in biomedicine.

Black Tea Quality is Highly Affected during Processing by its Leaf Surface Microbiome.

Microbiomes can greatly affect the quality of fermented food and beverages, including tea. In this study, microbial populations were characterized during black and green tea manufacturing, revealing that tea processing steps can drive both the bacterial and fungal community structure. Tea leaves were found to mostly harbor Proteobacteria, Bacteriodetes, Firmicutes, and Actinobacteria among bacteria and Ascomycetes among fungi. During processing, tea microbial populations changed especially between sterilized and unsterilized samples. The surface sterilization of fresh leaves before processing can remove many microbes, especially the bacteria of the genera Sphingomonas and Methylobacteria, indicating that these are mostly phylloplane microbes on tea leaves. The surface sterilization removed most fungi, except the Debaryomyces. We also observed a fluctuation in the content of several tea quality-related metabolites during processing. Caffeine and theanine were found in the same quantities in green tea with or without leaf surface sterilization. However, the sterilization process dramatically decreased the content of total catechins and theanine in black tea, indicating that microbes on the surface of tea leaf may be involved in maintaining the formation of these important metabolites during black tea processing.

The effects of transcutaneous electrical nerve stimulation during the first stage of labor: a randomized controlled trial.

BACKGROUND: Labor pain during childbirth can have devastating effects on the progress of labor, mother, and fetus. Consequently, the management of labor pain is crucial for the well-being of the mother and fetus. Transcutaneous electrical nerve stimulation (TENS) is a non -pharmacological analgesic technique. It uses a low-voltage electrical current to activate descending inhibitory systems in the central nervous system to relieve pain. This study aimed to determine the effects of TENS therapy in the first stage of labor. METHODS: In this single-blind randomized controlled trial, we screened low-risk pregnant women who anticipated spontaneous vaginal delivery. Women were assigned (1:1) to either the experimental group (received TENS therapy in the first stage of labor) or the control group (received routine obstetric care). The women, midwives, and researchers working in the gynecology and obstetric department were aware of the treatment group, but statisticians analysis the data were blinded. The primary outcome was labor pain intensity, assessed by visual analog scale (VAS) immediately after the randomization, at 30, 60, and 120 min after TENS therapy, and 2-24 h post-delivery. We used SPSS 21.0 software in data analysis. An independent sample t-test compared the mean VAS scores and labor duration between groups. A Chi-square test was employed to compare categorical variables between the groups. A significant level of ≤0.05 was statistically significant. RESULTS: A total of 326 pregnant women were eligible: experimental group (n = 161) and control group (n = 165). The experimental group had statistically significantly lower mean VAS scores at a different time (30, 60, and 120 min post-intervention and 2-24 h post-delivery) than the control group (p < 0.001). The experimental group demonstrated a statistically significant shorter duration of the active labor phase than the control group (p < 0.001). CONCLUSION: This study indicates that TENS can be used as a non-pharmacological therapy to reduce pain and shorten the active labor phase. TRIAL REGISTRATION: ISRCTN registry, ISRCTN23857995 . Registered on 11/12/2020, 'retrospectively registered.

Deep Learning-Based Screening Test for Cognitive Impairment Using Basic Blood Test Data for Health Examination.

Background: In order to develop a new screening test of cognitive impairment, we studied whether cognitive function can be estimated from basic blood test data by applying deep learning models. This model was constructed based on the effects of systemic metabolic disorders on cognitive function. Methods: We employed a deep neural network (DNN) to predict cognitive function based on subject's age and blood test items (23 items). We included 202 patients (73.48 ± 13.1 years) with various systemic metabolic disorders for training of the DNN model, and the following groups for validation of the model: (1) Patient group, 65 patients (73.6 ± 11.0 years) who were hospitalized for rehabilitation after stroke; (2) Healthy group, 37 subjects (62.0 ± 8.6 years); (3) Health examination group, 165 subjects (54.0 ± 8.6 years) admitted for a health examination. The subjects underwent the Mini-Mental State Examination (MMSE). Results: There were significant positive correlations between the predicted MMSE scores and ground truth scores in the Patient and Healthy groups (r = 0.66, p < 0.001). There were no significant differences between the predicted MMSE scores and ground truth scores in the Patient group (p > 0.05); however, in the Healthy group, the predicted MMSE scores were slightly, but significantly, lower than the ground truth scores (p < 0.05). In the Health examination group, the DNN model classified 94 subjects as normal (MMSE = 27-30), 67 subjects as having mild cognitive impairment (24-26), and four subjects as having dementia (≤ 23). In 37 subjects in the Health examination group, the predicted MMSE scores were slightly lower than the ground truth MMSE (p < 0.05). In contrast, in the subjects with neurological disorders, such as subarachnoid hemorrhage, the ground truth MMSE scores were lower than the predicted scores. Conclusions: The DNN model could predict cognitive function accurately. The predicted MMSE scores were significantly lower than the ground truth scores in the Healthy and Health examination groups, while there was no significant difference in the Patient group. We suggest that the difference between the predicted and ground truth MMSE scores was caused by changes in atherosclerosis with aging, and that applying the DNN model to younger subjects may predict future cognitive impairment after the onset of atherosclerosis.

Molecular Mechanism Associated With the Impact of Methane/Oxygen Gas Supply Ratios on Cell Growth of Methylomicrobium buryatense 5GB1 Through RNA-Seq.

The methane (CH4)/oxygen (O2) gas supply ratios significantly affect the cell growth and metabolic pathways of aerobic obligate methanotrophs. However, few studies have explored the CH4/O2 ratios of the inlet gas, especially for the CH4 concentrations within the explosion range (5∼15% of CH4 in air). This study thoroughly investigated the molecular mechanisms associated with the impact of different CH4/O2 ratios on cell growth of a model type I methanotroph Methylomicrobium buryatense 5GB1 cultured at five different CH4/O2 supply molar ratios from 0.28 to 5.24, corresponding to CH4 content in gas mixture from 5% to 50%, using RNA-Seq transcriptomics approach. In the batch cultivation, the highest growth rate of 0.287 h-1 was achieved when the CH4/O2 supply molar ratio was 0.93 (15% CH4 in air), and it is crucial to keep the availability of carbon and oxygen levels balanced for optimal growth. At this ratio, genes related to methane metabolism, phosphate uptake system, and nitrogen fixation were significantly upregulated. The results indicated that the optimal CH4/O2 ratio prompted cell growth by increasing genes involved in metabolic pathways of carbon, nitrogen and phosphate utilization in M. buryatense 5GB1. Our findings provided an effective gas supply strategy for methanotrophs, which could enhance the production of key intermediates and enzymes to improve the performance of bioconversion processes using CH4 as the only carbon and energy source. This research also helps identify genes associated with the optimal CH4/O2 ratio for balancing energy metabolism and carbon flux, which could be candidate targets for future metabolic engineering practice.

The Crosstalk between lncRNA-SNHG7/miRNA-181/cbx7 Modulates Malignant Character in Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) is a malignant tumor with poor patient survival and high patient mortality. Long noncoding RNA is profoundly involved in the tumorigenesis of LUAD. The present study explores the effect of small nucleolar RNA host gene 7 (SNHG7) on the progression of LUAD and its underlying mechanisms. SNHG7 was found to be down-regulated in LUAD tissues compared with normal tissues. Altered SNHG7 expression induced changes in cell proliferation and migration both in vitro and in vivo. Mechanistically, it was found that SNHG7 interacted with microRNA mir-181 and sequentially up-regulated cbx7. cbx7, which suppresses the Wnt/ß-catenin pathway in LUAD, was found to be a direct target of mir-181. Taken together, loss of SNHG7 in LUAD up-regulated mir-181 and then down-regulated the tumor suppressor cbx7.

Green tea polyphenols and epigallocatechin-3-gallate protect against perfluorodecanoic acid induced liver damage and inflammation in mice by inhibiting NLRP3 inflammasome activation.

Perfluorodecanoic acid (PFDA) is a highly toxic food contaminant that is extensively used in food applications as surface antifouling agent. In this present study, we aimed to assess whether green tea polyphenols (GTPs) and epigallocatechin-3-gallate (EGCG) exert protective effects against PFDA-induced liver damage and inflammation in mice. A mouse model to evaluate liver toxicity was established by giving mice drinking water containing different concentrations of PFDA. GTPs or EGCG (0.32%, w/v) were co-administered to mice exposed to PFDA in drinking water. Overall, GTPs and EGCG extended the survival time and inhibited weight loss among mice who received a lower dose of PFDA. Moreover, GTPs and EGCG ameliorated hepatic oxidative stress, cell apoptosis, necrosis, steatosis, edema, and degeneration, reduced hepatic inflammation and NLRP3 inflammasome activation caused by a moderate dose of PFDA. Taken together, these results show that GTPs or EGCG (or green tea intake) supplements can be beneficial for people exposed to PFDA.

Prediction of MMSE Score Using Time-Resolved Near-Infrared Spectroscopy.

Time-resolved near-infrared spectroscopy (TRS) enables assessment of baseline concentrations of hemoglobin (Hb) in the prefrontal cortex, which reflects regional cerebral blood flow and neuronal activity at rest. In a previous study, we demonstrated that baseline concentrations of oxy-Hb, deoxy-Hb, total-Hb, and oxygen saturation (SO2) measured by TRS were correlated with mini mental state examination (MMSE) scores. In the present study, we investigated whether Hb concentrations measured with TRS at rest can predict MMSE scores in aged people with various cognitive functions. A total of 202 subjects (87 males, 115 females, age 73.4 ± 13 years) participated. First, MMSE was conducted to assess cognitive function, and then baseline concentrations of oxy-Hb, deoxy-Hb, total-Hb, and SO2 in the bilateral prefrontal cortex were measured by TRS. Then, we employed the deep neural network (DNN) to predict the MMSE score. From the comparison results, the DNN showed 91.5% accuracy by leave-one-out cross validation. We found that not only the baseline concentration of SO2 but also optical path lengths contributed to prediction of the MMSE score. These results suggest that TRS with the DNN is useful as a screening test for cognitive impairment.

Relation Between Prefrontal Cortex Activity and Respiratory Rate During Mental Stress Tasks: A Near-Infrared Spectroscopic Study.

In order to clarify the central mechanism controlling respiratory rate during mental stress, we examined the relation between prefrontal cortex (PFC) activity and respiratory rate during mental arithmetic (MA) tasks. Employing two-channel near-infrared spectroscopy (NIRS), we measured hemoglobin (Hb) concentration changes in the bilateral PFC during MA tasks in normal adults. To evaluate asymmetry of the PFC activity, we calculated the laterality index (LI); (R-L)/(R + L) of oxy-Hb concentration changes (R = right, L = left); positive LI scores indicate right-dominant activity, while negative scores indicate left-dominant activity. For measurements of respiratory rate, we employed a Kinect motion sensor (Microsoft). The MA tasks increased both oxy-Hb in the bilateral PFC and respiratory rate (p < 0.001). In addition, there was a significant correlation between LI and respiratory rate (r = 0.582, p < 0.02). These results indicate that the MA-induced activity in the right PFC was greater than that in the left PFC in subjects with large increases of respiratory rate, suggesting that the right PFC has a greater role in cerebral regulation of respiratory rate during mental stress.

Effects of Antioxidant Supplements (BioPQQ™) on Cerebral Blood Flow and Oxygen Metabolism in the Prefrontal Cortex.

Pyrroloquinoline quinone (PQQ) is a quinone compound originally identified in methanol-utilizing bacteria and is a cofactor for redox enzymes. At the Meeting of the International Society on Oxygen Transport to Tissue (ISOTT) 2014, we reported that PQQ disodium salt (BioPQQ™) improved cognitive function in humans, as assessed by the Stroop test. However, the physiological mechanism of PQQ remains unclear. In the present study, we measured regional cerebral blood flow (rCBF) and oxygen metabolism in prefrontal cortex (PFC), before and after administration of PQQ, using time-resolved near-infrared spectroscopy (tNIRS). A total of 20 healthy subjects between 50 and 70 years of age were administered BioPQQ™ (20 mg) or placebo orally once daily for 12 weeks. Hemoglobin (Hb) concentration and absolute tissue oxygen saturation (SO2) in the bilateral PFC were evaluated under resting conditions using tNIRS. We found that baseline concentrations of hemoglobin and total hemoglobin in the right PFC significantly increased after administration of PQQ (p < 0.05). In addition, decreases in SO2 level in the PFC were more pronounced in the PQQ group than in the placebo group (p < 0.05). These results suggest that PQQ causes increased activity in the right PFC associated with increases in rCBF and oxygen metabolism, resulting in enhanced cognitive function.

In silico identification and functional annotation of yeast E3 ubiquitin ligase Rsp5 substrates.

Rsp5, E3 ligases conserved from yeast to mammals, plays a key role in diverse processes in yeast. However, many of Rsp5 substrates are still unclear. Therefore we proposed an in silico method to recognise new substrates of Rsp5. To investigate the molecular determinants that affect the interaction between Rsp5 and its substrate, we have systematically analysed many features that perhaps correlated with the Rsp5 substrate recognition. It is found that PPxY motif, transmembrane region, disorder region and N-linked glycosylation modification are the most important features for substrate recognition. We have constructed an SVM-based classifier to recognise Rsp5 substrates, obtaining 81.5% sensitivity and 74.1% specificity averagely on ten independent testing dataset. We also applied the model on the whole yeast proteome, and identified -66 new Rsp5 substrates. Functional annotation reveals that half of these novel substrates function in the Rsp5 involved cell processes as Rsp5-interacting proteins.