Changes in visits to green spaces due to the COVID-19 pandemic: Focusing on the proportion of repeat visitors and the distances between green spaces and visitors' places of residences.

Through a quantitative approach, this study aimed to clarify the changes in the number of visitors and visits to green spaces according to green space type before and after the COVID-19 pandemic. We explored the changes in the proportion of repeat visitors and the distance between green spaces and visitors' places of residence. We used KDDI Location Analyzer, which performs novel analysis using mobile phone GPS and census data. The study area included 10 target sites (urban parks and nature trails in the backcountry) located in the Sapporo metropolitan area in Japan. The survey period included snow-free seasons from 2019 to 2021, and 2019 was considered the period "before the pandemic." The results revealed that the number of visits during the pandemic increased compared with those before the pandemic, except for those of urban parks near the city center. In 2020, the proportion of repeat visitors increased for all 10 target sites. In addition, since the outbreak of the pandemic, distances between all urban parks and visitors' residences decreased. The same trend was observed for nature trails in the backcountry close to the city center. These findings indicate a generally decreasing trend in the number of visits to green spaces as many people have been refraining from visiting the site since the outbreak of the pandemic. Contrastingly, the number of visits by repeat visitors who reside close to the target sites has increased in some cases, which compensated for the general decreases.

DSCR1 upregulation enhances dural meningeal lymphatic drainage to attenuate amyloid pathology of Alzheimer's disease.

Highly developed meningeal lymphatics remove waste products from the brain. Disruption of meningeal lymphatic vessels in a mouse model of amyloid pathology (5XFAD) accelerates the accumulation of amyloid plaques in the meninges and brain, and causes learning and memory deficits, suggesting that clearance of toxic wastes by lymphatic vessels plays a key role in neurodegenerative diseases. Here, we discovered that DSCR1 (Down syndrome critical region 1, known also as RCAN1, regulator of calcineurin 1) facilitates the drainage of waste products by increasing the coverage of dorsal meningeal lymphatic vessels. Furthermore, upregulation of DSCR1 in 5XFAD mice diminishes Aß pathology in the brain and improves memory defects. Surgical ligation of cervical lymphatic vessels afferent to dcLN blocks the beneficial effects of DSCR1 on Aß accumulation and cognitive function. Interestingly, intracerebroventricular delivery of AAV1-DSCR1 to 5XFAD mice is sufficient to rebuild the meningeal lymphatic system and re-establish cognitive performance. Collectively, our data indicate that DSCR1 facilitates the growth of dorsal meningeal lymphatics to improve drainage efficiency and protect against Alzheimer's disease (AD) pathologies, further highlighting that improving meningeal lymphatic function is a feasible treatment strategy for AD. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Differentiation of industrial hemp strains by their cannabinoid and phenolic compounds using LC × LC-HRMS.

Cannabis is an ancient plant that has been used for therapeutic and recreational purposes. Nowadays, industrial hemp, a variety with low concentration of the psychoactive cannabinoid Δ9-tetrahydrocannabinol (THC) and high concentration of non-psychoactive cannabinoids, is getting more and more interest in the food, pharmaceutical, and cosmetic industry. However, cannabis not only contains cannabinoids as bioactive components but also other metabolites like terpenes and phenolic compounds, and the content of these interesting secondary metabolites greatly differs with the genetic variety of the plant. Due to the huge complexity of composition of the cannabis matrix, in this work, a comprehensive two-dimensional liquid chromatography (LC × LC) method has been developed as a very power separation technique coupling a pentafluorophenyl (PFP) and a C18 in the first and second dimensions. Two industrial hemp strains (cookie and gelato) were analyzed to determine the difference in their content of cannabinoids and phenolic compounds. To do this, a new demodulation process was applied for the first time to transform 2D raw data into 1D data which allowed carrying out the chemometric analysis needed to determine the statistical differences between the hemp strains. The cookie strain presented a total of 41 cannabinoid markers, while the gelato strain presented more representative phenolic compounds, in total 24 phenolic compounds were detected as potential markers of this sample. These differences in the chemical composition could determine the industrial destiny of the different hemp strains.

A practical application of generative adversarial networks for RNA-seq analysis to predict the molecular progress of Alzheimer's disease.

Next-generation sequencing (NGS) technology has become a powerful tool for dissecting the molecular and pathological signatures of a variety of human diseases. However, the limited availability of biological samples from different disease stages is a major hurdle in studying disease progressions and identifying early pathological changes. Deep learning techniques have recently begun to be applied to analyze NGS data and thereby predict the progression of biological processes. In this study, we applied a deep learning technique called generative adversarial networks (GANs) to predict the molecular progress of Alzheimer's disease (AD). We successfully applied GANs to analyze RNA-seq data from a 5xFAD mouse model of AD, which recapitulates major AD features of massive amyloid-ß (Aß) accumulation in the brain. We examined how the generator is featured to have specific-sample generation and biological gene association. Based on the above observations, we suggested virtual disease progress by latent space interpolation to yield the transition curves of various genes with pathological changes from normal to AD state. By performing pathway analysis based on the transition curve patterns, we identified several pathological processes with progressive changes, such as inflammatory systems and synapse functions, which have previously been demonstrated to be involved in the pathogenesis of AD. Interestingly, our analysis indicates that alteration of cholesterol biosynthesis begins at a very early stage of AD, suggesting that it is the first effect to mediate the cholesterol metabolism of AD downstream of Aß accumulation. Here, we suggest that GANs are a useful tool to study disease progression, leading to the identification of early pathological signatures.

MRPrimerW2: an enhanced tool for rapid design of valid high-quality primers with multiple search modes for qPCR experiments.

For the best results in quantitative polymerase chain reaction (qPCR) experiments, it is essential to design high-quality primers considering a multitude of constraints and the purpose of experiments. The constraints include many filtering constraints, homology test on a huge number of off-target sequences, the same constraints for batch design of primers, exon spanning, and avoiding single nucleotide polymorphism (SNP) sites. The target sequences are either in database or given as FASTA sequences, and the experiment is for amplifying either each target sequence with each corresponding primer pairs designed under the same constraints or all target sequences with a single pair of primers. Many websites have been proposed, but none of them including our previous MRPrimerW fulfilled all the above features. Here, we describe the MRPrimerW2, the update version of MRPrimerW, which fulfils all the features by maintaining the advantages of MRPrimerW in terms of the kinds and sizes of databases for valid primers and the number of search modes. To achieve it, we exploited GPU computation and a disk-based key-value store using PCIe SSD. The complete set of 3 509 244 680 valid primers of MRPrimerW2 covers 99% of nine important organisms in an exhaustive manner. Free access: http://MRPrimerW2.com.

Product Inspection Methodology via Deep Learning: An Overview.

In this study, we present a framework for product quality inspection based on deep learning techniques. First, we categorize several deep learning models that can be applied to product inspection systems. In addition, we explain the steps for building a deep-learning-based inspection system in detail. Second, we address connection schemes that efficiently link deep learning models to product inspection systems. Finally, we propose an effective method that can maintain and enhance a product inspection system according to improvement goals of the existing product inspection systems. The proposed system is observed to possess good system maintenance and stability owing to the proposed methods. All the proposed methods are integrated into a unified framework and we provide detailed explanations of each proposed method. In order to verify the effectiveness of the proposed system, we compare and analyze the performance of the methods in various test scenarios. We expect that our study will provide useful guidelines to readers who desire to implement deep-learning-based systems for product inspection.

How social information can improve estimation accuracy in human groups.

In our digital and connected societies, the development of social networks, online shopping, and reputation systems raises the questions of how individuals use social information and how it affects their decisions. We report experiments performed in France and Japan, in which subjects could update their estimates after having received information from other subjects. We measure and model the impact of this social information at individual and collective scales. We observe and justify that, when individuals have little prior knowledge about a quantity, the distribution of the logarithm of their estimates is close to a Cauchy distribution. We find that social influence helps the group improve its properly defined collective accuracy. We quantify the improvement of the group estimation when additional controlled and reliable information is provided, unbeknownst to the subjects. We show that subjects' sensitivity to social influence permits us to define five robust behavioral traits and increases with the difference between personal and group estimates. We then use our data to build and calibrate a model of collective estimation to analyze the impact on the group performance of the quantity and quality of information received by individuals. The model quantitatively reproduces the distributions of estimates and the improvement of collective performance and accuracy observed in our experiments. Finally, our model predicts that providing a moderate amount of incorrect information to individuals can counterbalance the human cognitive bias to systematically underestimate quantities and thereby improve collective performance.

Electrokinetic Size-Based Spatial Separation of Micro/Nanospheres Using Paper-Based 3D Origami Preconcentrator.

Sample preparation steps (e.g., preconcentration and separation) are key to enhancing sensitivity and reliability in biomedical and analytical chemistry. However, conventional methods (e.g., ultracentrifugation) cause significant loss of sample as well as their contamination. In this study, we developed a paper-based three-dimensional (3D) origami ion concentration polarization preconcentrator (POP) for highly efficient and facile sample preparation. The unique design of POP enables simultaneous preconcentration and spatial separation of target analytes rapidly and economically. The POP comprises accordion-like multifolded layers with convergent wicking areas that can separate analytes based on their sizes in different layers, which can then be easily isolated by unfolding the POP. We first demonstrated 100-fold preconcentration of albumin and its isolation on the specific layers. Then, we demonstrated the simultaneous preconcentration and spatial separation of microspheres of three different sizes (with diameters of 0.02, 0.2, and 2 µm) on the different layers.

Enhanced paper-based ELISA for simultaneous EVs/exosome isolation and detection using streptavidin agarose-based immobilization.

EVs/exosomes are considered as the next generation of biomarkers, including for liquid biopsies. Consequently, the quantification of EVs/exosomes is crucial for facilitating EV/exosome research and applications. Paper-based enzyme-linked immunosorbent assay (p-ELISA) is a portable diagnostic system with low cost that is simple and easy to use; however, it shows low sensitivity and linearity. In this study, we develop p-ELISA for targeting EVs/exosomes by using streptavidin agarose resin-based immobilization (SARBI). This method reduces assay preparation times, provides strong binding, and retains good sensitivity and linearity. The time required for the total assay, including preparation steps and surface immobilization, was shortened to ∼2 h. We evaluated SARBI p-ELISA systems with/without CD63 capture Ab and then with fetal bovine serum (FBS) and EVs/exosome-depleted fetal bovine serum (dFBS). The results provide evidence supporting the selective capture ability of SARBI p-ELISA. We obtain semiquantitative p-ELISA results using an exosome standard (ES) and human serum (HS), with R2 values of 0.95 and 0.92, respectively.

MRPrimerV: a database of PCR primers for RNA virus detection.

Many infectious diseases are caused by viral infections, and in particular by RNA viruses such as MERS, Ebola and Zika. To understand viral disease, detection and identification of these viruses are essential. Although PCR is widely used for rapid virus identification due to its low cost and high sensitivity and specificity, very few online database resources have compiled PCR primers for RNA viruses. To effectively detect viruses, the MRPrimerV database (http://MRPrimerV.com) contains 152 380 247 PCR primer pairs for detection of 1818 viruses, covering 7144 coding sequences (CDSs), representing 100% of the RNA viruses in the most up-to-date NCBI RefSeq database. Due to rigorous similarity testing against all human and viral sequences, every primer in MRPrimerV is highly target-specific. Because MRPrimerV ranks CDSs by the penalty scores of their best primer, users need only use the first primer pair for a single-phase PCR or the first two primer pairs for two-phase PCR. Moreover, MRPrimerV provides the list of genome neighbors that can be detected using each primer pair, covering 22 192 variants of 532 RefSeq RNA viruses. We believe that the public availability of MRPrimerV will facilitate viral metagenomics studies aimed at evaluating the variability of viruses, as well as other scientific tasks.

MRPrimerW: a tool for rapid design of valid high-quality primers for multiple target qPCR experiments.

Design of high-quality primers for multiple target sequences is essential for qPCR experiments, but is challenging due to the need to consider both homology tests on off-target sequences and the same stringent filtering constraints on the primers. Existing web servers for primer design have major drawbacks, including requiring the use of BLAST-like tools for homology tests, lack of support for ranking of primers, TaqMan probes and simultaneous design of primers against multiple targets. Due to the large-scale computational overhead, the few web servers supporting homology tests use heuristic approaches or perform homology tests within a limited scope. Here, we describe the MRPrimerW, which performs complete homology testing, supports batch design of primers for multi-target qPCR experiments, supports design of TaqMan probes and ranks the resulting primers to return the top-1 best primers to the user. To ensure high accuracy, we adopted the core algorithm of a previously reported MapReduce-based method, MRPrimer, but completely redesigned it to allow users to receive query results quickly in a web interface, without requiring a MapReduce cluster or a long computation. MRPrimerW provides primer design services and a complete set of 341 963 135 in silico validated primers covering 99% of human and mouse genes. Free access: http://MRPrimerW.com.

MRPrimer: a MapReduce-based method for the thorough design of valid and ranked primers for PCR.

Primer design is a fundamental technique that is widely used for polymerase chain reaction (PCR). Although many methods have been proposed for primer design, they require a great deal of manual effort to generate feasible and valid primers, including homology tests on off-target sequences using BLAST-like tools. That approach is inconvenient for many target sequences of quantitative PCR (qPCR) due to considering the same stringent and allele-invariant constraints. To address this issue, we propose an entirely new method called MRPrimer that can design all feasible and valid primer pairs existing in a DNA database at once, while simultaneously checking a multitude of filtering constraints and validating primer specificity. Furthermore, MRPrimer suggests the best primer pair for each target sequence, based on a ranking method. Through qPCR analysis using 343 primer pairs and the corresponding sequencing and comparative analyses, we showed that the primer pairs designed by MRPrimer are very stable and effective for qPCR. In addition, MRPrimer is computationally efficient and scalable and therefore useful for quickly constructing an entire collection of feasible and valid primers for frequently updated databases like RefSeq. Furthermore, we suggest that MRPrimer can be utilized conveniently for experiments requiring primer design, especially real-time qPCR.

A cold-adapted tyrosinase with an abnormally high monophenolase/diphenolase activity ratio originating from the marine archaeon Candidatus Nitrosopumilus koreensis.

OBJECTIVES: To obtain an acidic and cold-active tyrosinase, which potentially minimizes unwanted self-oxidation of tyrosinase-catalyzed catechols, including 3,4-dihydroxyphenylalanine at elevated pH and high temperature. RESULTS: A putative psychrophilic tyrosinase (named as tyrosinase-CNK) was identified from the genome information of the marine archaeon Candidatus Nitrosopumilus koreensis. This protein contains key tyrosinase domains, such as copper-binding domains and an O2-binding motif, and phylogenetic analysis revealed that it was distinct from other known bacterial tyrosinases. Functional tyrosinase-CNK was produced by applying a co-expression strategy together with chaperone proteins in Escherichia coli with a yield of approx. 30 mg l(-1) and a purity >95 %. The purified enzyme showed optimal activity at pH 6 and 20 °C and still had 50 % activity at 0 °C. Surprisingly, the enzyme exhibited an abnormally high monophenolase/diphenolase activity ratio. CONCLUSIONS: The acidic and cold-adapted tyrosinase-CNK, as a new type of tyrosinase, could expand potential applications of tyrosinases including the production of catechols through minimizing unwanted self-oxidation and the modification of existing materials at low temperature.

Potential role of shear-wave ultrasound elastography for the differential diagnosis of breast non-mass lesions: preliminary report.

OBJECTIVES: To report our preliminary experience with shear-wave elastography (SWE) for non-mass lesions (NMLs) in the breast and suggest a potential ancillary role of SWE for BI-RADS Category 4a NMLs in reducing the number of unnecessary benign biopsies. METHODS: A total of 310 breast lesions in 286 consecutive women who had been scheduled for US-guided automated gun biopsy or vacuum-assisted biopsy between June and December 2012 were initially included in this study. Finally, 33 women with 34 breast lesions classified as NMLs constituted our study population. Diagnostic performances of each quantitative SWE parameter were calculated. Histological diagnosis was used as a reference standard. RESULTS: Among the 34 breast NMLs, 22 (65%) were benign and 12 (35%) were malignant. Emean value with cut-off set at 41.6 kPa had the highest Az value 0.788 (95% CI, 0.625-0.951), showing sensitivity of 83.3% and specificity of 68.2%. By applying an Emean value of 41.6 kPa or less as a criterion for downgrading soft BI-RADS category 4a NMLs to category 3 NMLs, 15 unnecessary biopsies could have been eliminated from the 19 BI-RADS category 4a lesions (79%). CONCLUSIONS: SWE features could increase positive predictive values and reduce unnecessary benign biopsies of category 4a NMLs. KEY POINTS: • Ultrasound elastography is increasingly used to assess the stiffness of breast lesions • Shear-wave elastography provides useful information about non-mass breast lesions • Shear-wave elastography may render some biopsies of non-mass breast lesions unnecessary.

Accomplishing High-Performance Organic Solar Sub-Modules (≈55 cm2) with >16% Efficiency by Controlling the Aggregation of an Engineered Non-Fullerene Acceptor.

The fabrication of environmentally benign, solvent-processed, efficient, organic photovoltaic sub-modules remains challenging due to the rapid aggregation of the current high performance non-fullerene acceptors (NFAs). In this regard, design of new NFAs capable of achieving optimal aggregation in large-area organic photovoltaic modules has not been realized. Here, an NFA named BTA-HD-Rh is synthesized with longer (hexyl-decyl) side chains that exhibit good solubility and optimal aggregation. Interestingly, integrating a minute amount of new NFA (BTA-HD-Rh) into the PM6:L8-BO system enables the improved solubility in halogen-free solvents (o-xylene:carbon disulfide (O-XY:CS2)) with controlled aggregation is found. Then solar sub-modules are fabricated at ambient condition (temperature at 25 ± 3 °C and humidity: 30-45%). Ultimately, the champion 55 cm2 sub-modules achieve exciting efficiency of >16% in O-XY:CS2 solvents, which is the highest PCE reported for sub-modules. Notably, the highest efficiency of BTA-HD-Rh doped PM6:L8-BO is very well correlated with high miscibility with low Flory-Huggins parameter (0.372), well-defined nanoscale morphology, and high charge transport. This study demonstrates that a careful choice of side chain engineering for an NFA offers fascinating features that control the overall aggregation of active layer, which results in superior sub-module performance with environmental-friendly solvents.

π-Conjugated Polymer with Pendant Side Chains as a Dopant-Free Hole Transport Material for High-Performance Perovskite Solar Cells.

Dopant-free polymeric hole transport materials (HTMs) have attracted considerable attention in perovskite solar cells (PSCs) due to their high carrier mobilities and excellent hydrophobicity. They are considered promising candidates for HTMs to replace commercial Spiro-OMeTAD to achieve long-term stability and high efficiency in PSCs. In this study, we developed BDT-TA-BTASi, a conjugated donor-π-acceptor polymeric HTM. The donor benzo[1,2-b:4,5-b']dithiophene (BDT) and acceptor benzotriazole (BTA) incorporated pendant siloxane, and alkyl side chains led to high hole mobility and solubility. In addition, BDT-TA-BTASi can effectively passivate the perovskite layer and markedly decrease the trap density. Based on these advantages, dopant-free BDT-TA-BTASi-based PSCs achieved an efficiency of over 21.5%. Furthermore, dopant-free BDT-TA-BTASi-based devices not only exhibited good stability in N2 (retaining 92% of the initial efficiency after 1000 h) but also showed good stability at high-temperature (60 °C) and -humidity conditions (80 ± 10%) (retaining 92 and 82% of the initial efficiency after 400 h). These results demonstrate that BDT-TA-BTASi is a promising HTM, and the study provides guidance on dopant-free polymeric HTMs to achieve high-performance PSCs.

KoNA: Korean Nucleotide Archive as A New Data Repository for Nucleotide Sequence Data.

During the last decade, the generation and accumulation of petabase-scale high-throughput sequencing data have resulted in great challenges, including access to human data, as well as transfer, storage, and sharing of enormous amounts of data. To promote data-driven biological research, the Korean government announced that all biological data generated from government-funded research projects should be deposited at the Korea BioData Station (K-BDS), which consists of multiple databases for individual data types. Here, we introduce the Korean Nucleotide Archive (KoNA), a repository of nucleotide sequence data. As of July 2022, the Korean Read Archive in KoNA has collected over 477 TB of raw next-generation sequencing data from national genome projects. To ensure data quality and prepare for international alignment, a standard operating procedure was adopted, which is similar to that of the International Nucleotide Sequence Database Collaboration. The standard operating procedure includes quality control processes for submitted data and metadata using an automated pipeline, followed by manual examination. To ensure fast and stable data transfer, a high-speed transmission system called GBox is used in KoNA. Furthermore, the data uploaded to or downloaded from KoNA through GBox can be readily processed using a cloud computing service called Bio-Express. This seamless coupling of KoNA, GBox, and Bio-Express enhances the data experience, including submission, access, and analysis of raw nucleotide sequences. KoNA not only satisfies the unmet needs for a national sequence repository in Korea but also provides datasets to researchers globally and contributes to advances in genomics. The KoNA is available at https://www.kobic.re.kr/kona/.

VPrimer: A Method of Designing and Updating Primer and Probe With High Variant Coverage for RNA Virus Detection.

Fatal infectious diseases caused by RNA viruses, such as COVID-19, have emerged around the world. RT-PCR is widely employed for virus detection, and its accuracy depends on the primers and probes since RT-PCR can detect a virus only when the primers and probes bind to the target gene of the virus. Most of primer design methods are for a single host and so require a great deal of effort to design for RNA virus detection, including homology tests among the host and all the viruses for the host using BLAST-like tools. Furthermore, they do not consider variant sequences, which are very common in viruses. In this study, we describe VPrimer, a method of designing high-quality primer-probe sets for RNA viruses. VPrimer can find primer-probe sets that cover more than 95% of the variants of a target virus but do not cover any sequences of other viruses or the host. With VPrimer, we found 381,698,582 primer-probe sets for 3,104 RNA viruses. Multiplex PCR assays using the top 2 primer-probe sets suggested by VPrimer usually cover 100% of variants. To address the rapid changes in viral genomes, VPrimer finds the best and up-to-date primer-probe sets incrementally against the most recently reported variants.

Investigation of early molecular alterations in tauopathy with generative adversarial networks.

The recent advances in deep learning-based approaches hold great promise for unravelling biological mechanisms, discovering biomarkers, and predicting gene function. Here, we deployed a deep generative model for simulating the molecular progression of tauopathy and dissecting its early features. We applied generative adversarial networks (GANs) for bulk RNA-seq analysis in a mouse model of tauopathy (TPR50-P301S). The union set of differentially expressed genes from four comparisons (two phenotypes with two time points) was used as input training data. We devised four-way transition curves for a virtual simulation of disease progression, clustered and grouped the curves by patterns, and identified eight distinct pattern groups showing different biological features from Gene Ontology enrichment analyses. Genes that were upregulated in early tauopathy were associated with vasculature development, and these changes preceded immune responses. We confirmed significant disease-associated differences in the public human data for the genes of the different pattern groups. Validation with weighted gene co-expression network analysis suggested that our GAN-based approach can be used to detect distinct patterns of early molecular changes during disease progression, which may be extremely difficult in in vivo experiments. The generative model is a valid systematic approach for exploring the sequential cascades of mechanisms and targeting early molecular events related to dementia.

DSCR1 deficiency ameliorates the Aß pathology of Alzheimer's disease by enhancing microglial activity.

Microglial phagocytosis and clearance are important for the removal of amyloid-ß (Aß) plaques in Alzheimer's disease (AD). Chronic exposure of microglia to Aß plaques leads to microglial metabolic dysfunction, and dysregulation of microglia can accelerate the deposition of Aß plaques and cause learning and memory impairment. Thus, regulating microglial Aß clearance is crucial for the development of therapeutics for AD-related dementia. Here, Down syndrome critical region 1 (DSCR1) deficiency ameliorated Aß plaque deposition in the 5xFAD mouse model of AD by altering microglial activity; however, the Aß synthesis pathway was not affected. DSCR1 deficiency improved spatial learning and memory impairment in 5xFAD mice. Furthermore, DSCR1-deficient microglia exhibited accelerated lysosomal degradation of Aß after phagocytosis, and BV2 cells with stable knockdown of DSCR1 demonstrated enhanced lysosomal activity. RNA-sequencing analysis showed that the transcriptional signatures associated with responses to IFN-γ were significantly up-regulated in DSCR1-knockdown BV2 cells treated with Aß. Our data strongly suggest that DSCR1 is a critical mediator of microglial degradation of amyloid plaques and a new potential microglial therapeutic target in AD.