The Skin-Whitening and Antioxidant Effects of Protocatechuic Acid (PCA) Derivatives in Melanoma and Fibroblast Cell Lines.

The skin is the most voluminous organ of the human body and is exposed to the outer environment. Such exposed skin suffers from the effects of various intrinsic and extrinsic aging factors. Skin aging is characterized by features such as wrinkling, loss of elasticity, and skin pigmentation. Skin pigmentation occurs in skin aging and is caused by hyper-melanogenesis and oxidative stress. Protocatechuic acid (PCA) is a natural secondary metabolite from a plant-based source widely used as a cosmetic ingredient. We chemically designed and synthesized PCA derivatives conjugated with alkyl esters to develop effective chemicals that have skin-whitening and antioxidant effects and enhance the pharmacological activities of PCA. We identified that melanin biosynthesis in B16 melanoma cells treated with alpha-melanocyte-stimulating hormone (α-MSH) is decreased by PCA derivatives. We also found that PCA derivatives effectively have antioxidant effects in HS68 fibroblast cells. In this study, we suggest that our PCA derivatives are potent ingredients for developing cosmetics with skin-whitening and antioxidant effects.

Metabolic engineering of Escherichia coli for biological production of 1, 3-Butanediol.

The production of 1,3-butanediol (1,3-BDO) from glucose was investigated using Escherichia coli as the host organism. A pathway was engineered by overexpressing genes phaA (acetyl-CoA acetyltransferase), phaB (acetoacetyl-CoA reductase), bld (CoA-acylating aldehyde dehydrogenase), and yqhD (alcohol dehydrogenase). The expression levels of these genes were optimized to improve 1,3-BDO production and pathways that compete with 1,3-BDO synthesis were disrupted. Culture conditions were also optimized, including the C: N ratio, aeration, induction time, temperature, and supplementation of amino acids, resulting in a strain that could produce 1,3-BDO at 257 mM in 36 h, with a yield of 0.51 mol/mol in a fed-batch bioreactor experiment. To the best of our knowledge, this is the highest titer of 1,3-BDO production ever reported using biological methods, and our findings provide a promising strategy for the development of microbial cell factories for the sustainable synthesis of other acetyl-CoA-derived chemicals.

Metabolic engineering of Escherichia coli for enhanced production of 1,3-butanediol from glucose.

1,3-Butanediol (1,3-BDO) finds versatile applications in the cosmetic, chemical, and food industries. This study focuses on the metabolic engineering of Escherichia coli K12 to achieve efficient production of 1,3-BDO from glucose via acetoacetyl-CoA, 3-hydroxybutyryl-CoA, and 3-hydroxybutyraldehyde. The accumulation of an intermediary metabolite (pyruvate) and a byproduct (3-hydroxybutyric acid) was reduced by disruption of the negative transcription factor (PdhR) for pyruvate dehydrogenase complex (PDHc) and employing an efficient alcohol dehydrogenase (YjgB), respectively. Additionally, to improve NADPH availability, carbon flux was redirected from the Embden-Meyerhof-Parnas (EMP) pathway to the Entner-Doudoroff (ED) pathway. One resulting strain achieved a record-high titer of 790 mM (∼71.1 g/L) with a yield of 0.65 mol/mol for optically pure (R)-1,3-BDO, with an enantiomeric excess (e.e.) value of 98.5 %. These findings are useful in the commercial production of 1,3-BDO and provide valuable insights into the development of an efficient cell factory for other acetyl-CoA derivatives.

Verification of De-Identification Techniques for Personal Information Using Tree-Based Methods with Shapley Values.

With the development of big data and cloud computing technologies, the importance of pseudonym information has grown. However, the tools for verifying whether the de-identification methodology is correctly applied to ensure data confidentiality and usability are insufficient. This paper proposes a verification of de-identification techniques for personal healthcare information by considering data confidentiality and usability. Data are generated and preprocessed by considering the actual statistical data, personal information datasets, and de-identification datasets based on medical data to represent the de-identification technique as a numeric dataset. Five tree-based regression models (i.e., decision tree, random forest, gradient boosting machine, extreme gradient boosting, and light gradient boosting machine) are constructed using the de-identification dataset to effectively discover nonlinear relationships between dependent and independent variables in numerical datasets. Then, the most effective model is selected from personal information data in which pseudonym processing is essential for data utilization. The Shapley additive explanation, an explainable artificial intelligence technique, is applied to the most effective model to establish pseudonym processing policies and machine learning to present a machine-learning process that selects an appropriate de-identification methodology.

Urban edge trees: Urban form and meteorology drive elemental carbon deposition to canopies and soils.

Urban tree canopies are a significant sink for atmospheric elemental carbon (EC)--an air pollutant that is a powerful climate-forcing agent and threat to human health. Understanding what controls EC deposition to urban trees is therefore important for evaluating the potential role of vegetation in air pollution mitigation strategies. We estimated wet, dry, and throughfall EC deposition for oak trees at 53 sites in Denton, TX. Spatial data and airborne discrete-return LiDAR were used to compute predictors of EC deposition, including urban form characteristics, and meteorologic and topographic factors. Dry and throughfall EC deposition varied 14-fold across this urban ecosystem and exhibited significant variability from spring to fall. Generalized additive modeling and multiple linear regression analyses showed that urban form strongly influenced tree-scale variability in dry EC deposition: traffic count as well as road length and building height within 100-150 m of trees were positively related to leaf-scale dry deposition. Rainfall amount and extreme wind-driven rain from the direction of major pollution sources were significant drivers of throughfall EC. Our findings indicate that complex configurations of roads, buildings, and vegetation produce "urban edge trees" that contribute to heterogeneous EC deposition patterns across urban systems, with implications for greenspace planning.

Forest cover classification by optimal segmentation of high resolution satellite imagery.

This study investigated whether high-resolution satellite imagery is suitable for preparing a detailed digital forest cover map that discriminates forest cover at the tree species level. First, we tried to find an optimal process for segmenting the high-resolution images using a region-growing method with the scale, color and shape factors in Definiens(®) Professional 5.0. The image was classified by a traditional, pixel-based, maximum likelihood classification approach using the spectral information of the pixels. The pixels in each segment were reclassified using a segment-based classification (SBC) with a majority rule. Segmentation with strongly weighted color was less sensitive to the scale parameter and led to optimal forest cover segmentation and classification. The pixel-based classification (PBC) suffered from the "salt-and-pepper effect" and performed poorly in the classification of forest cover types, whereas the SBC helped to attenuate the effect and notably improved the classification accuracy. As a whole, SBC proved to be more suitable for classifying and delineating forest cover using high-resolution satellite images.

Geocoding police collision report data from California: a comprehensive approach.

BACKGROUND: Collision geocoding is the process of assigning geographic descriptors, usually latitude and longitude coordinates, to a traffic collision record. On California police reports, relative collision location is recorded using a highway postmile marker or a street intersection. The objective of this study was to create a geocoded database of all police-reported, fatal and severe injury collisions in the California Statewide Integrated Traffic Records System (SWITRS) for years 1997-2006 for use by public agencies. RESULTS: Geocoding was completed with a multi-step process. First, pre-processing was performed using a scripting language to clean and standardize street name information. A state highway network with postmile values was then created using a custom tool written in Visual Basic for Applications (VBA) in ArcGIS software. Custom VBA functionality was also used to incorporate the offset direction and distance. Intersection and address geocoding was performed using ArcGIS, StreetMap Pro 2003 digital street network, and Google Earth Pro. A total of 142,007 fatal and severe injury collisions were identified in SWITRS. The geocoding match rate was 99.8% for postmile-coded collisions and 86% for intersection-coded collisions. The overall match rate was 91%. CONCLUSIONS: The availability of geocoded collision data will be beneficial to clinicians, researchers, policymakers, and practitioners in the fields of traffic safety and public health. Potential uses of the data include studies of collision clustering on the highway system, examinations of the associations between collision occurrence and a variety of variables on environmental and social characteristics, including housing and personal demographics, alcohol outlets, schools, and parks. The ability to build maps may be useful in research planning and conduct and in the delivery of information to both technical and non-technical audiences.

Isolation, cultivation, and genome analysis of proteorhodopsin-containing SAR116-clade strain Candidatus Puniceispirillum marinum IMCC1322.

Strain IMCC1322 was isolated from a surface water sample from the East Sea of Korea. Based on 16S rRNA analysis, IMCC1322 was found to belong to the OCS28 sub-clade of SAR116. The cells appeared as short vibrioids in logarithmic-phase culture, and elongated spirals during incubation with mitomycin or in aged culture. Growth characteristics of strain IMCC1322 were further evaluated based on genomic information; proteorhodopsin (PR), carbon monoxide dehydrogenase, and dimethylsulfoniopropionate (DMSP)-utilizing enzymes. IMCC1322 PR was characterized as a functional retinylidene protein that acts as a light-driven proton pump in the cytoplasmic membrane. However, the PR-dependent phototrophic potential of strain IMCC1322 was only observed under CO-inhibited and nutrient-limited culture conditions. A DMSP-enhanced growth response was observed in addition to cultures grown on C1 compounds like methanol, formate, and methane sulfonate. Strain IMCC1322 cultivation analysis revealed biogeochemical processes characteristic of the SAR116 group, a dominant member of the microbial community in euphotic regions of the ocean. The polyphasic taxonomy of strain IMCC1322 is given as Candidatus Puniceispirillum marinum, and was confirmed by chemotaxonomic tests, in addition to 16S rRNA phylogeny and cultivation analyses.

Global Electroencephalography Synchronization as a New Indicator for Tracking Emotional Changes of a Group of Individuals during Video Watching.

In the present study, we investigated whether global electroencephalography (EEG) synchronization can be a new promising index for tracking emotional arousal changes of a group of individuals during video watching. Global field synchronization (GFS), an index known to correlate with human cognitive processes, was evaluated; this index quantified the global temporal synchronization among multichannel EEG data recorded from a group of participants (n = 25) during the plays of two short video clips. The two video clips were each about 5 min long and were designed to evoke negative (fearful) or positive (happy) emotion, respectively. Another group of participants (n = 37) was asked to select the two most emotionally arousing (most touching or most fearful) scenes in each clip. The results of these questionnaire surveys were used as the ground-truth to evaluate whether the GFS could detect emotional highlights of both video clips. The emotional highlights estimated using the grand-averaged GFS waveforms of the first group were also compared with those evaluated from galvanic skin response, photoplethysmography, and multimedia content analysis, which are conventional methods used to estimate temporal changes in emotional arousal during video plays. From our results, we found that beta-band GFS values decreased during high emotional arousal, regardless of the type of emotional stimulus. Moreover, the emotional highlights estimated using the GFS waveforms coincided best with those found by the questionnaire surveys. These findings suggest that GFS might be applicable as a new index for tracking emotional arousal changes of a group of individuals during video watching, and is likely to be used to evaluate or edit movies, TV commercials, and other broadcast products.

An emergency call system for patients in locked-in state using an SSVEP-based brain switch.

Patients in a locked-in state (LIS) due to severe neurological disorders such as amyotrophic lateral sclerosis (ALS) require seamless emergency care by their caregivers or guardians. However, it is a difficult job for the guardians to continuously monitor the patients' state, especially when direct communication is not possible. In the present study, we developed an emergency call system for such patients using a steady-state visual evoked potential (SSVEP)-based brain switch. Although there have been previous studies to implement SSVEP-based brain switch system, they have not been applied to patients in LIS, and thus their clinical value has not been validated. In this study, we verified whether the SSVEP-based brain switch system can be practically used as an emergency call system for patients in LIS. The brain switch used for our system adopted a chromatic visual stimulus, which proved to be visually less stimulating than conventional checkerboard-type stimuli but could generate SSVEP responses strong enough to be used for brain-computer interface (BCI) applications. To verify the feasibility of our emergency call system, 14 healthy participants and 3 patients with severe ALS took part in online experiments. All three ALS patients successfully called their guardians to their bedsides in about 6.56 seconds. Furthermore, additional experiments with one of these patients demonstrated that our emergency call system maintains fairly good performance even up to 4 weeks after the first experiment without renewing initial calibration data. Our results suggest that our SSVEP-based emergency call system might be successfully used in practical scenarios.

Clinical feasibility of brain-computer interface based on steady-state visual evoked potential in patients with locked-in syndrome: Case studies.

Although the feasibility of brain-computer interface (BCI) systems based on steady-state visual evoked potential (SSVEP) has been extensively investigated, only a few studies have evaluated its clinical feasibility in patients with locked-in syndrome (LIS), who are the main targets of BCI technology. The main objective of this case report was to share our experiences of SSVEP-based BCI experiments involving five patients with LIS, thereby providing researchers with useful information that can potentially help them to design BCI experiments for patients with LIS. In our experiments, a four-class online SSVEP-based BCI system was implemented and applied to four of five patients repeatedly on multiple days to investigate its test-retest reliability. In the last experiments with two of the four patients, the practical usability of our BCI system was tested using a questionnaire survey. All five patients showed clear and distinct SSVEP responses at all four fundamental stimulation frequencies (6, 6.66, 7.5, 10 Hz), and responses at harmonic frequencies were also observed in three patients. Mean classification accuracy was 76.99% (chance level = 25%). The test-retest reliability experiments demonstrated stable performance of our BCI system over different days even when the initial experimental settings (e.g., electrode configuration, fixation time, visual angle) used in the first experiment were used without significant modifications. Our results suggest that SSVEP-based BCI paradigms might be successfully used to implement clinically feasible BCI systems for severely paralyzed patients.

Data-Driven User Feedback: An Improved Neurofeedback Strategy considering the Interindividual Variability of EEG Features.

It has frequently been reported that some users of conventional neurofeedback systems can experience only a small portion of the total feedback range due to the large interindividual variability of EEG features. In this study, we proposed a data-driven neurofeedback strategy considering the individual variability of electroencephalography (EEG) features to permit users of the neurofeedback system to experience a wider range of auditory or visual feedback without a customization process. The main idea of the proposed strategy is to adjust the ranges of each feedback level using the density in the offline EEG database acquired from a group of individuals. Twenty-two healthy subjects participated in offline experiments to construct an EEG database, and five subjects participated in online experiments to validate the performance of the proposed data-driven user feedback strategy. Using the optimized bin sizes, the number of feedback levels that each individual experienced was significantly increased to 139% and 144% of the original results with uniform bin sizes in the offline and online experiments, respectively. Our results demonstrated that the use of our data-driven neurofeedback strategy could effectively increase the overall range of feedback levels that each individual experienced during neurofeedback training.

Development of a hybrid mental speller combining EEG-based brain-computer interface and webcam-based eye-tracking.

The main goal of this study was to develop a hybrid mental spelling system combining a steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) technology and a webcam-based eye-tracker, which utilizes information from the brain electrical activity and eye gaze direction at the same time. In the hybrid mental spelling system, a character decoded using SSVEP was not typed if the position of the selected character was not matched with the eye direction information ('left' or 'right') obtained from the eye-tracker. Thus, the users did not need to correct a misspelled character using a 'BACKSPACE' key. To verify the feasibility of the developed hybrid mental spelling system, we conducted online experiments with ten healthy participants. Each participant was asked to type 15 English words consisting of 68 characters. As a result, 16.6 typing errors could be prevented on average, demonstrating that the implemented hybrid mental spelling system could enhance the practicality of our mental spelling system.

Improvement of enzymatic biodiesel production by controlled substrate feeding using silica gel in solvent free system.

A silica gel-based substrate feeding system was developed to prevent methanol inhibiting the catalyst during enzymatic biodiesel synthesis. In the system, silica gel swelled upon methanol addition and subsequently released it in a controlled manner to prevent excess methanol affecting the enzyme. Biodiesel was synthesized by the enzymatic transesterification of canola oil with methanol. For this reaction, enzyme loading, methanol/oil molar ratio, silica gel dosage, glycerol content, and methanol feeding method were tested using commercial immobilized enzymes (Novozym 435 and Lipozyme RM IM from Novozymes). The results showed that conversion was highest with controlled substrate feeding rather than direct methanol addition, suggesting that the method developed here can easily prevent enzyme inhibition by limiting methanol concentration to an acceptable level.