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Mikami, K.

Publications and source records attributed to Mikami, K..

7 recordsLinked to original sources

Altered Motor Awareness in Parkinson's Disease with Progressive Micrographia

Micrographia, characterized by abnormally small handwriting, is a common motor symptom in Parkinsons disease (PD), and has been classified into consistent micrographia (CM) and progressive micrographia (PM), which may reflect different underlying mechanisms. However, the relative contributions of motor execution and sensorimotor processing to these subtypes remain unclear. In this study, forty-five people with Parkinsons disease (PwP) and twenty age-matched healthy controls (HCs) completed a handwriting task and a control detection task (CDT) assessing the ability to distinguish self-generated from externally generated movements. PwP were classified based on handwriting metrics as showing no micrographia, CM, and/or PM. CDT accuracy was significantly lower in PwP than in HCs (p < 0.01) and was particularly reduced in PwP with PM (p < 0.01). These findings indicate that PM is associated with impaired motor awareness, suggesting altered sensorimotor integration as a characteristic feature of this subtype.

neuroscience↗

EC-isHCR: a rapid method for in situ hybridization chain reaction in diverse animal samples

The in situ hybridization chain reaction (isHCR) visualizes RNA across multiple spatial scales, from organs to subcellular structures, in diverse samples. We previously proposed a rapid protocol, EC-isHCR, for Drosophila embryos and ovaries. Whether EC-isHCR retains the features of conventional isHCR, including wide-spatial-scale analyses in various samples, however, has remained unclear. Here, we show that EC-isHCR enables robust RNA detection in a broad range of samples, such as whole-mount fruit fly, parasitoid wasp, and aphid preparations; paraffin sections of trout; frozen mouse sections; and human cultured cells. Moreover, EC-isHCR enabled detection of subcellular RNA localization. EC-isHCR also visualized co-localization of RNA with phase-separated condensates in fruit fly embryos and detected the protrusion-enriched mRNA in HeLa cells. To broaden the applicability of EC-isHCR, we developed an automated probe design tool (https://github.com/ShuntaYorimoto/hcrkit). By combining this tool with EC-isHCR, we provide a fast and versatile framework to visualize mRNAs. This framework will help reduce the barrier to using fast isHCR and thereby facilitate research across diverse areas of the life sciences. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/696653v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1852584org.highwire.dtl.DTLVardef@621682org.highwire.dtl.DTLVardef@1b3bf5corg.highwire.dtl.DTLVardef@1d86841_HPS_FORMAT_FIGEXP M_FIG C_FIG Highlights- EC-isHCR enables rapid acquisition of high-contrast images. - EC-isHCR preserves features of conventional isHCR, including versatile sample compatibility and high-resolution imaging. - An automated probe design tool was developed for EC-isHCR. - EC-isHCR/probe tool framework will help reduce the barrier to using fast isHCR.

bioengineering↗

N-acetylchitohexaose induces immune priming against Pseudomonas aeruginosa infection in the silkworm, Bombyx mori

Lysine Motif (LysM) domain-containing receptors are evolutionarily conserved pattern recognition receptors (PRRs) that serve as key mediators of glycan sensing and innate immune activation in plants and mammals. In invertebrates, however, their role in activating innate immunity remains poorly understood, although some evidence for immunosuppressive functions exists. In this study, we performed in silico structural analyses and identified a putative B. mori LYSMD3 homolog (XP_004933441.1). This protein exhibits high structural similarity in the LysM domain to human LYSMD3, with a root-mean-square deviation (RMSD) of 0.559 [A], indicating close structural alignment. RNA-seq analysis of hemocytes isolated from silkworm larvae injected with N-acetylchitohexaose (GN6), a chitin-derived oligosaccharide and known ligand of human LYSMD3, revealed transcriptional activation of innate immune effectors, including antimicrobial peptide (AMP) genes such as cecropins. GN6 also induced cecropin transcription in isolated hemocytes in vitro, and western blotting of hemolymph confirmed elevated Cecropin B protein levels. Furthermore, GN6 and chitin significantly improved survival against P. aeruginosa infection, with median effective doses (ED) values of 0.62 and 0.48 {micro}g/larva, respectively. In contrast, N-acetylglucosamine (GlcNAc) and shorter oligosaccharides (GN2-GN5) were ineffective. These findings provide the first molecular-level evidence of a putative glycan receptor in silkworms based on structural similarity to known LysM domains. Moreover, GN6-induced antimicrobial peptide expression and enhanced infection resistance demonstrate immune priming in this model, supporting an evolutionarily conserved glycan-sensing pathway in invertebrates.

immunology↗

Leaf Mold Agar Facilitates Recovery of Soil Bacterial Diversity Beyond Bacillus Dominance

Dominance of Bacillus species on conventional agar media often hampers the isolation of taxonomically diverse soil bacteria (i.e., "Bacillus dominance"). To overcome this Bacillus dominance, we developed a novel agar medium containing leaf mold extract (LME) and assessed its utility for isolating microorganisms from soil samples. For comparison, conventional yeast malt extract agar (YME agar) was used as a control. 16S rRNA gene sequencing revealed that colonies cultured on YME agar predominantly consisted of Bacillus-related bacteria, whereas LME agar enabled the growth of a wider variety of taxa, particularly actinomycetes such as Streptomyces. Notably, LME agar supported a higher diversity of soil bacterial isolates even from samples with a low abundance of Bacillus-related species. Among the 138 isolates recovered from LME agar, some either exhibited very low 16S rRNA gene sequence identity to known species in public databases, or failed to yield 16S rRNA amplicons with conventional universal primers, suggesting the presence of previously uncharacterized or novel taxa. Furthermore, one unidentified isolate failed to grow on standard nutrient media (YME, BHI, LB10, or TSB), but proliferated in liquid leaf mold extract, indicating a specific nutrient dependency. These findings demonstrate that LME agar can facilitate the isolation of a broader spectrum of soil microorganisms (including rare and previously uncultured species) not readily recoverable on common basal media. Incorporation of ecosystem-derived substrates into culture media may greatly enhance the discovery and study of novel microbial diversity from environmental samples. ImportanceSoil contains a vast number of microorganisms, many of which remain undiscovered due to limitations in standard laboratory methods. A major issue is the overgrowth of Bacillus species on conventional media, which suppresses the growth of other bacteria. To address this, we developed a new agar medium using leaf mold extract (LME) and found it successfully supported the growth of a much wider variety of soil bacteria, including rare species. Some of the isolated microbes could not be identified using standard genetic tools, and one unique strain only grew in LME-based media, indicating a special nutrient requirement. These findings show that using natural environmental components like leaf mold can help scientists grow and study bacteria that were previously missed. This approach can expand our understanding of microbial diversity and may lead to the discovery of new microbes with potential applications in agriculture, medicine, or environmental science.

microbiology↗

Advancing microbial isolation: The impact of leaf mold extract agar on soil samples

In this study, we developed a new agar medium using leaf mold extract and evaluated its microbial cultivation performance with soil samples. As a control for performance evaluation, the general-purpose nutrient medium YME agar was used. For YME agar, isolated microbes were confirmed to belong mainly to the Bacillus genus through 16S rRNA gene sequencing. In contrast, for the leaf mold agar, bacteria belonging to either Streptomyces or Rhizobium were frequently isolated. Also, of the 51 sequenced isolates on the leaf mold agar medium, an unidentified species (i.e., not listed in databases) with 16S rRNA sequence identity below 98.7% was found. The unidentified species did not grow in standard nutrient media (YME, BHI, LB10, or TSB) but grew in 10% leaf mold extract. The findings of this study suggest that the use of leaf mold agar medium can effectively isolate soil microbes that are difficult to culture in general-purpose nutrient media such as YME. Moreover, this approach indicates a viable method for discovering unknown, previously-uncultured microbial species from soil samples.

microbiology↗

Wistar rats raised in an affectionate environment display lifesaving-like behaviors while distinguishing life from death

It is generally believed that humans are the only species that values life. However, it is not well understood whether animals have a nature that values life. In this study, we attempted to determine whether male Wistar rats have this nature. Normally-reared rats did not show lifesaving-like actions towards anesthesia-induced comatose rats, although they seemed to distinguish life from death. Considering the possibility that different rearing conditions may foster a life-valuing nature, male Wistar rat pups were reared in several ways: normal rearing, loving rearing (LR; rats reared as if they were cute pets), rearing in an enriched environment, reared with gentle stroking of the back, and normal rearing of offspring of rats raised under LR conditions. When placed in an anxiety-producing environment, only LR rats escaped into the hands of the person who reared them, indicating attachment. Only the LR rats displayed lifesaving-like actions towards unknown comatose rats or drowning pups. LR rats also stopped attacks by biting ICR mice that were attacking C57BL/6 mice. Thus, rearing in an affectionate environment may foster a life-valuing nature, even in rats, suggesting that the valuing of life may be neither innate nor human-specific.

animal behavior and cognition↗

Prediction of prostate cancer by deep learning with multilayer artificial neural network.

ObjectivesTo predict the rate of prostate cancer detection on prostate biopsy more accurately, the performance of deep learning utilizing a multilayer artificial neural network was investigated.\n\nMaterials and methodsA total of 334 patients who underwent multiparametric magnetic resonance imaging before ultrasonography-guided transrectal 12-core prostate biopsy were enrolled in the analysis. Twenty-two non-selected variables as well as selected ones by least absolute shrinkage and selection operator (Lasso) regression analysis and by stepwise logistic regression analysis were input into the constructed multilayer artificial neural network (ANN) programs. 232 patients were used as training cases of ANN programs, and the remaining 102 patients were for the test to output the probability of prostate cancer existence, accuracy of prostate cancer prediction, and area under the receiver operating characteristic (ROC) curve with the learned model.\n\nResultsWith any prostate cancer objective variable, Lasso and stepwise regression analyses selected 12 and 9 explanatory variables from 22, respectively. In common between them, age at biopsy, findings on digital rectal examination, findings in the peripheral zone on MRI diffusion-weighted imaging, and body mass index were positively influential variables, while numbers of previous prostatic biopsy and prostate volume were negatively influential. Using trained ANNs with multiple hidden layers, the accuracy of predicting any prostate cancer in test samples was about 5-10% higher compared with that with logistic regression analysis (LR). The AUCs with multilayer ANN were significantly larger on inputting variables that were selected by the stepwise logistic regression compared with the AUC with LR. The ANN had a higher net-benefit than LR between prostate cancer probability cut-off values of 0.38 and 0.6.\n\nConclusionANN accurately predicted prostate cancer without biopsy marginally better than LR. However, for clinical application, ANN performance may still need improvement.

bioinformatics↗