Soft-sensor development for monitoring the lysine fermentation process.

Monitoring cell growth and target production in working fermentors is important for stabilizing high level production. In this study, we developed a novel soft sensor for estimating the concentration of a target product (lysine), substrate (sucrose), and bacterial cell in commercially working fermentors using machine learning combined with available on-line process data. The lysine concentration was accurately estimated in both linear and nonlinear models; however, the nonlinear models were also suitable for estimating the concentrations of sucrose and bacterial cells. Data enhancement by time interpolation improved the model prediction accuracy and eliminated unnecessary fluctuations. Furthermore, the soft sensor developed based on the dataset of the same process parameters in multiple fermentor tanks successfully estimated the fermentation behavior of each tank. Machine learning-based soft sensors may represent a novel monitoring system for digital transformation in the field of biotechnological processes.

Data science-based modeling of the lysine fermentation process.

Mathematical modeling of the fermentation process is useful for understanding the influence of operating parameters on target production and control performance, depending on the situation, to stabilize the target production at a high-level. However, the previous approaches using physical modeling methods and traditional knowledge-based methods are difficult to apply on working fermentors at a commercial plant scale because they have unknown and unmeasured parameters involved in target production. This study focused on developing an ensemble learning model that can predict the amino acid fermentation process behavior based on observation values, which can be obtained from fermentation tanks and future control input. The results revealed the influence of each control input on lysine production during the culturing period. Furthermore, high-order stability, which achieved the target trajectory for lysine production, was realized using dynamic fermentation controls. Additionally, this study demonstrates that the fermentation behavior on a commercial plant scale is reproduced using the ensemble device. The ensemble learning model will provide novel control system with data-science based model of Industry 4.0 in the field of biotechnological processes.

Low plasma tryptophan is associated with olfactory function in healthy elderly community dwellers in Japan.

BACKGROUND: Decreased circulating tryptophan (Trp) levels are frequently observed in elderly patients with neurodegenerative disease including Alzheimer's disease. Trp may serve as a potential biomarker for monitoring disease risk in elderly people. We aimed to investigate the association between low plasma Trp levels and olfactory function, which is known to predict age-related diseases including dementia in elderly people. METHODS: A total of 144 healthy elderly Japanese community (≥ 65 years old) dwellers from the Health, Aging and Nutritional Improvement study (HANI study) were the subjects of our analysis. Low Trp levels were classified using the lower limit values of the reference interval according to a previous report. Olfactory function was assessed using a card-type test called Open Essence, which includes 12 odour items that are familiar to Japanese people. The elderly subjects with low circulating Trp levels were compared to a control group with normal plasma Trp levels. RESULTS: We conducted the analyses using 144 people aged 65 years or older (mean age 73.7 ± 5.5 years; 36.1% men). The subjects showed normal serum albumin levels (4.4 ± 0.2 g/dL) and no daily living disabilities. Low plasma Trp levels (low Trp group) were found in 11.1% of the study population. The low Trp group showed a significantly lower correct-answer rate for the items india ink, perfume, curry and sweaty smelling socks than control group (P < 0.05). There was also a significant association between low Trp levels and low olfactory ability, after adjusting for age and sex. CONCLUSIONS: Lower plasma Trp levels were associated with a decrease in olfactory function in functionally competent older individuals. Because olfactory dysfunction predicts age-related diseases, low plasma Trp levels may represent a clinical sign of disease risk in elderly people.

A titanium-based oxysulfide photocatalyst: La5Ti2MS5O7 (M = Ag, Cu) for water reduction and oxidation.

La(5)Ti(2)MS(5)O(7), which absorb visible light of up to 570 nm (M = Ag) and up to 650 nm (M = Cu), respectively, have photocatalytic activities for both water reduction and oxidation. In this study, structural and optical properties, electronic state distributions, and photocatalytic activity for water reduction and oxidation on La(5)Ti(2)MS(5)O(7) (M = Ag, Cu) were investigated. Density functional theory (DFT) calculations of the electronic band structures and charge densities indicated that hybrid orbitals of Cu 3d and S 3p formed the valence band edge of La(5)Ti(2)CuS(5)O(7) while S 3p orbitals alone for La(5)Ti(2)AgS(5)O(7). On the other hand, Ti 3d orbitals were the major components of the conduction band edges of both La(5)Ti(2)CuS(5)O(7) and La(5)Ti(2)AgS(5)O(7). Importantly, it was found that the paths of photoexcited electrons and holes in La(5)Ti(2)MS(5)O(7) bulk were disassociated, which could be favorable for efficient charge separation. In fact, the activity for H(2) evolution after loading of Pt was significantly high among existing Ti-based oxysulfide photocatalysts. The apparent quantum efficiency of Pt-loaded La(5)Ti(2)AgS(5)O(7) for H(2) evolution under visible light irradiation (at λ = 420 ± 10 nm) reached 1.2%. Moreover, La(5)Ti(2)MS(5)O(7) loaded with IrO(2) were active for photocatalytic O(2) evolution although the valence band maximum was composed of S 3p orbitals. These results suggest that La(5)Ti(2)MS(5)O(7) modified with appropriate cocatalysts are promising photocatalysts for water splitting under visible light irradiation.

Hybrid Cu(x)O/TiO2 nanocomposites as risk-reduction materials in indoor environments.

Photocatalytic TiO(2) powders impart ultraviolet light-induced self-cleaning and antibacterial functions when coated on outdoor building materials. For indoor applications, however, TiO(2) must be modified for visible-light and dark sensitivity. Here we report that the grafting of nanometer-sized Cu(x)O clusters onto TiO(2) generates an excellent risk-reduction material in indoor environments. X-ray absorption near-edge structure using synchrotron radiation and high-resolution transmission electron microscopic analyses revealed that Cu(x)O clusters were composed of Cu(I) and Cu(II) valence states. The Cu(II) species in the Cu(x)O clusters endow TiO(2) with efficient visible-light photooxidation of volatile organic compounds, whereas the Cu(I) species impart antimicrobial properties under dark conditions. By controlling the balance between Cu(I) and Cu(II) in Cu(x)O, efficient decomposition and antipathogenic activity were achieved in the hybrid Cu(x)O/TiO(2) nanocomposites.

DFT Method Estimation of Standard Redox Potential of Metal Ions and Metal Complexes.

The DFT method calculation was carried out to evaluate standard redox potential (SRP) for metal-to-metal cation and metal-to-metal complex systems. With the Born-Haber cycle, standard redox potential was composed of the cohesive energy, ionization energy, and solvation energy. The ligand exchange energy was added in case of metal complex. The solvent effects were incorporated by the self-consistent reaction field theory at the level of the polarized continuum model (PCM). At the highest level of calculations, the geometry optimization and harmonic frequency analysis were evaluated under the PCM. Utilizing experimental values of the cohesive energy of metals, the standard deviations between the calculated and experimental SRP values were 0.20-0.27 V depending on the calculation levels and basis sets used. For three Ag complexes with CN(-), S2O3(2-), and NH3 ligands, the discrepancy was within 0.3 V.

Photophysical properties and photocatalytic activities of bismuth molybdates under visible light irradiation.

Aurivillius structure Bi(2)MoO(6) (BG: 2.70 eV) that is a low-temperature phase showed an intense absorption band in the visible light region and photocatalytic activity for O(2) evolution from an aqueous silver nitrate solution under visible light irradiation, among various bismuth molybdates (Bi(2)MoO(6), Bi(2)Mo(2)O(9), and Bi(2)Mo(3)O(12)) synthesized by solid-state and reflux reactions. Bi(2)Mo(3)O(12) (BG: 2.88 eV) also showed photocatalytic activity for O(2) evolution under full-arc irradiation of a Xe lamp (lambda > 300 nm). The photocatalytic activity of the Aurivillius structure Bi(2)MoO(6) prepared by the reflux method was dependent on the annealing temperature after the preparation. The crystallinity was the important factor for the activity. Calculation by the density functional method indicated that the conduction band of Aurivillius structure Bi(2)MoO(6) was made up of Mo 4d orbitals. It turned out that the visible-light absorption of this photocatalyst was due to the transition from the valence band consisting of O 2p orbitals to the conduction band. The corner-sharing structure of the MoO(6) octahedra contributed to the visible light response and the photocatalytic performance because excitation energy and/or photogenerated electron and hole pairs began to migrate easily in the Aurivillius structure.