Asymmetric [Dy2] molecules deposited into micro-SQUID susceptometers: characterization of their magnetic integrity.

The controlled integration of magnetic molecules into superconducting circuits is key to developing hybrid quantum devices. Herein, we study [Dy2] molecular dimers deposited into micro-SQUID susceptometers. The results of magnetic, heat capacity and magnetic resonance experiments, backed by theoretical calculations, show that each [Dy2] dimer fulfills the main requisites to encode a two-spin quantum processor.

Identification of epistatic SNP combinations in rheumatoid arthritis using LAMPLINK and Japanese cohorts.

Genome-wide association studies have enabled the identification of important genetic factors in many trait studies. However, only a fraction of the heritability can be explained by known genetic factors, even in the most common diseases. Genetic loci combinations, or epistatic contributions expressed by combinations of single nucleotide polymorphisms (SNPs), have been argued to be one of the critical factors explaining some of the missing heritability, especially in oligogenic/polygenic diseases.

A low-coverage 3' RNA-seq to detect homeolog expression in polyploid wheat.

Although allopolyploid species are common among natural and crop species, it is not easy to distinguish duplicated genes, known as homeologs, during their genomic analysis. Yet, cost-efficient RNA sequencing (RNA-seq) is to be developed for large-scale transcriptomic studies such as time-series analysis and genome-wide association studies in allopolyploids. In this study, we employed a 3' RNA-seq utilizing 3' untranslated regions (UTRs) containing frequent mutations among homeologous genes, compared to coding sequence.

Wearable Sensor and Mobile App-Based mHealth Approach for Investigating Substance Use and Related Factors in Daily Life: Protocol for an Ecological Momentary Assessment Study.

Background: Digital health technologies using mobile apps and wearable devices are a promising approach to the investigation of substance use in the real world and for the analysis of predictive factors or harms from substance use. Moreover, consecutive repeated data collection enables the development of predictive algorithms for substance use by machine learning methods.

Objective: We developed a new self-monitoring mobile app to record daily substance use, triggers, and cravings.

Prediction of the cell-type-specific transcription of non-coding RNAs from genome sequences via machine learning.

Gene transcription is regulated through complex mechanisms involving non-coding RNAs (ncRNAs). As the transcription of ncRNAs, especially of enhancer RNAs, is often low and cell type specific, how the levels of RNA transcription depend on genotype remains largely unexplored. Here we report the development and utility of a machine-learning model (MENTR) that reliably links genome sequence and ncRNA expression at the cell type level.

Volumetric Analysis of Glioblastoma for Determining Which CpG Sites Should Be Tested by Pyrosequencing to Predict Temozolomide Efficacy.

The aim of the present study was to determine which individual or combined CpG sites among O-methylguanine DNA methyltransferase CpG 74-89 in glioblastoma mainly affects the response to temozolomide resulting from CpG methylation using statistical analyses focused on the tumor volume ratio (TVR). We retrospectively examined 44 patients who had postoperative volumetrically measurable residual tumor tissue and received adjuvant temozolomide therapy for at least 6 months after initial chemoradiotherapy. TVR was defined as the tumor volume 6 months after the initial chemoradiotherapy divided by that before the start of chemoradiotherapy.

Estimating Physical/Mental Health Condition Using Heart Rate Data from a Wearable Device.

We propose an estimation method of subjects' physical/mental health condition from their heart rate (HR) and evaluate it on the newly collected data including 25 million points over 97 participants. The accurate health condition estimation is important for an employee's mental health care and an objective understanding of our condition. For the estimation, the heart rate variability (HRV) has been widely used, but there are some technical difficulties with measuring the HRV, such as maintaining a good quality of data for a long period of time.

Preliminary study for developing a navigation system for gastric cancer surgery using artificial intelligence.

Purpose: We are attempting to develop a navigation system for safe and effective peripancreatic lymphadenectomy in gastric cancer surgery. As a preliminary study, we examined whether or not the peripancreatic dissection line could be learned by a machine learning model (MLM).

Methods: Among the 41 patients with gastric cancer who underwent radical gastrectomy between April 2019 and January 2020, we selected 6 in whom the pancreatic contour was relatively easy to trace.

The genome of Shorea leprosula (Dipterocarpaceae) highlights the ecological relevance of drought in aseasonal tropical rainforests.

Hyperdiverse tropical rainforests, such as the aseasonal forests in Southeast Asia, are supported by high annual rainfall. Its canopy is dominated by the species-rich tree family of Dipterocarpaceae (Asian dipterocarps), which has both ecological (e.g.

Assessing Versatile Machine Learning Models for Glioma Radiogenomic Studies across Hospitals.

Radiogenomics use non-invasively obtained imaging data, such as magnetic resonance imaging (MRI), to predict critical biomarkers of patients. Developing an accurate machine learning (ML) technique for MRI requires data from hundreds of patients, which cannot be gathered from any single local hospital. Hence, a model universally applicable to multiple cohorts/hospitals is required.

ARPEGGIO: Automated Reproducible Polyploid EpiGenetic GuIdance workflOw.

Background: Whole genome duplication (WGD) events are common in the evolutionary history of many living organisms. For decades, researchers have been trying to understand the genetic and epigenetic impact of WGD and its underlying molecular mechanisms. Particular attention was given to allopolyploid study systems, species resulting from an hybridization event accompanied by WGD.

Evaluation of repair activity by quantification of ribonucleotides in the genome.

Ribonucleotides incorporated in the genome are a source of endogenous DNA damage and also serve as signals for repair. Although recent advances of ribonucleotide detection by sequencing, the balance between incorporation and repair of ribonucleotides has not been elucidated. Here, we describe a competitive sequencing method, Ribonucleotide Scanning Quantification sequencing (RiSQ-seq), which enables absolute quantification of misincorporated ribonucleotides throughout the genome by background normalization and standard adjustment within a single sample.

Fine-Tuning Approach for Segmentation of Gliomas in Brain Magnetic Resonance Images with a Machine Learning Method to Normalize Image Differences among Facilities.

Machine learning models for automated magnetic resonance image segmentation may be useful in aiding glioma detection. However, the image differences among facilities cause performance degradation and impede detection. This study proposes a method to solve this issue.

Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine.

In recent years, advances in artificial intelligence (AI) technology have led to the rapid clinical implementation of devices with AI technology in the medical field. More than 60 AI-equipped medical devices have already been approved by the Food and Drug Administration (FDA) in the United States, and the active introduction of AI technology is considered to be an inevitable trend in the future of medicine. In the field of oncology, clinical applications of medical devices using AI technology are already underway, mainly in radiology, and AI technology is expected to be positioned as an important core technology.

De Novo Genome Assembly of the Japanese Wheat Cultivar Norin 61 Highlights Functional Variation in Flowering Time and Fusarium-Resistant Genes in East Asian Genotypes.

Bread wheat is a major crop that has long been the focus of basic and breeding research. Assembly of its genome has been difficult because of its large size and allohexaploid nature (AABBDD genome). Following the first reported assembly of the genome of the experimental strain Chinese Spring (CS), the 10+ Wheat Genomes Project was launched to produce multiple assemblies of worldwide modern cultivars.

Multiple wheat genomes reveal global variation in modern breeding.

Advances in genomics have expedited the improvement of several agriculturally important crops but similar efforts in wheat (Triticum spp.) have been more challenging. This is largely owing to the size and complexity of the wheat genome, and the lack of genome-assembly data for multiple wheat lines.

Fine-scale empirical data on niche divergence and homeolog expression patterns in an allopolyploid and its diploid progenitor species.

Polyploidization is pervasive in plants, but little is known about the niche divergence of wild allopolyploids (species that harbor polyploid genomes originating from different diploid species) relative to their diploid progenitor species and the gene expression patterns that may underlie such ecological divergence. We conducted a fine-scale empirical study on habitat and gene expression of an allopolyploid and its diploid progenitors. We quantified soil properties and light availability of habitats of an allotetraploid Cardamine flexuosa and its diploid progenitors Cardamine amara and Cardamine hirsuta in two seasons.

A Recently Formed Triploid Inherits Leaf Vivipary and Submergence Tolerance Traits of Parents.

Contemporary speciation provides a unique opportunity to directly observe the traits and environmental responses of a new species. is an allotriploid species that appeared within the past 150 years in a Swiss village, Urnerboden. In contrast to its two progenitor species, and that live in wet and open habitats, respectively, is found in-between their habitats with temporal water level fluctuation.

Isolation of exosomes from whole blood by a new microfluidic device: proof of concept application in the diagnosis and monitoring of pancreatic cancer.

Background: Exosomes are endocytic-extracellular vesicles with a diameter around 100 nm that play an essential role on the communication between cells. In fact, they have been proposed as candidates for the diagnosis and the monitoring of different pathologies (such as Parkinson, Alzheimer, diabetes, cardiac damage, infection diseases or cancer).

Results: In this study, magnetic nanoparticles (FeONPs) were successfully functionalized with an exosome-binding antibody (anti-CD9) to mediate the magnetic capture in a microdevice.

Predicting Deep Learning Based Multi-Omics Parallel Integration Survival Subtypes in Lung Cancer Using Reverse Phase Protein Array Data.

Mortality attributed to lung cancer accounts for a large fraction of cancer deaths worldwide. With increasing mortality figures, the accurate prediction of prognosis has become essential. In recent years, multi-omics analysis has emerged as a useful survival prediction tool.

Uncovering Prognosis-Related Genes and Pathways by Multi-Omics Analysis in Lung Cancer.

Lung cancer is one of the leading causes of death worldwide. Therefore, understanding the factors linked to patient survival is essential. Recently, multi-omics analysis has emerged, allowing for patient groups to be classified according to prognosis and at a more individual level, to support the use of precision medicine.

Genet assignment and population structure analysis in a clonal forest-floor herb, , using RAD-seq.

To study the genetic structure of clonal plant populations, genotyping and genet detection using genetic markers are necessary to assign ramets to corresponding genets. Assignment is difficult as it involves setting a robust threshold of genetic distance for genet distinction as neighbouring genets in a plant population are often genetically related. Here, we used restriction site-associated DNA sequencing (RAD-seq) for a rhizomatous clonal herb, [Brassicaceae] to accurately determine genet structure in a natural population.