109 research outputs found
Using Minecraft Education Edition to Enhance 21st Century Skills in the College Classroom: A Mixed Methods Study
Serum zinc deficiency could be associated with dementia conversion in Parkinson’s disease
BackgroundAssociation between heavy metals and Parkinson’s disease (PD) is well noted, but studies regarding heavy metal levels and non-motor symptoms of PD, such as PD’s dementia (PD-D), are lacking.MethodsIn this retrospective cohort study, we compared five serum heavy metal levels (Zn, Cu, Pb, Hg, and Mn) of newly diagnosed PD patients (n = 124). Among 124 patients, 40 patients were later converted to Parkinson’s disease dementia (PD-D), and 84 patients remained without dementia during the follow-up time. We collected clinical parameters of PD and conducted correlation analysis with heavy metal levels. PD-D conversion time was defined as the initiation time of cholinesterase inhibitors. Cox proportional hazard models were used to identify factors associated with dementia conversion in PD subjects.ResultsZn deficiency was significant in the PD-D group than in the PD without dementia group (87.53 ± 13.20 vs. 74.91 ± 14.43, p < 0.01). Lower serum Zn level was significantly correlated with K-MMSE and LEDD at 3 months (r = −0.28, p < 0.01; r = 0.38, p < 0.01). Zn deficiency also contributed to a shorter time to dementia conversion (HR 0.953, 95% CI 0.919 to 0.988, p < 0.01).ConclusionThis clinical study suggests that a low serum Zn level can be a risk factor for developing PD-D and could be used as a biological marker for PD-D conversion
New Constraints on ALP Electron and Photon Couplings from ArgoNeuT and the MiniBooNE Beam Dump
Beam dumps and fixed-target experiments have been very sensitive probes of
such particles and other physics beyond the Standard Model (BSM) by considering
the production of new states from the primary interaction in the beam dump. In
a proton beam dump, there are many secondary interactions taking place in
electromagnetic showers which may be additional production channels for
pseudoscalar bosons or axion-like particles (ALPs). The target-less
configuration of the MiniBooNE experiment, which collected data from protons impinging directly on the steel beam dump, is an
excellent test of sensitivity to these production channels of ALPs in the MeV
mass region. Using the null observation of the MiniBooNE dump mode data, we set
new constraints on ALPs coupling to electrons and photons produced through a
multitude of channels and detected via both scattering and decays in the
MiniBooNE detector volume. We find that the null result rules out parameter
space that was previously unconstrained by laboratory probes in the 10-100 MeV
mass regime for both electron and photon couplings. Lastly, we make the case
for performing a dedicated analysis with 1.25 POT of data
collected by the ArgoNeuT experiment, which we show to have complementary
sensitivity and set the stage for future searches.Comment: 9 pages, 8 figures; updated reference
Ultrasensitive biosensing platform for Mycobacterium tuberculosis detection based on functionalized graphene devices
Tuberculosis (TB) has high morbidity as a chronic infectious disease transmitted mainly through the respiratory tract. However, the conventional diagnosis methods for TB are time-consuming and require specialists, making the diagnosis of TB with point-of-care (POC) detection difficult. Here, we developed a graphene-based field-effect transistor (GFET) biosensor for detecting the MPT64 protein of Mycobacterium tuberculosis with high sensitivity as a POC detection platform for TB. For effective conjugation of antibodies, the graphene channels of the GFET were functionalized by immobilizing 1,5-diaminonaphthalene (1,5-DAN) and glutaraldehyde linker molecules onto the graphene surface. The successful immobilization of linker molecules with spatial uniformity on the graphene surface and subsequent antibody conjugation were confirmed by Raman spectroscopy and X-ray photoelectron spectroscopy. The GFET functionalized with MPT64 antibodies showed MPT64 detection with a detection limit of 1 fg/mL in real-time, indicating that the GFET biosensor is highly sensitive. Compared to rapid detection tests (RDT) and enzyme-linked immunosorbent assays, the GFET biosensor platform developed in this study showed much higher sensitivity but much smaller dynamic range. Due to its high sensitivity, the GFET biosensor platform can bridge the gap between time-consuming molecular diagnostics and low-sensitivity RDT, potentially aiding in early detection or management of relapses in infectious diseases
Combined Analysis of the Time-Resolved Transcriptome and Proteome of Plant Pathogen Xanthomonas oryzae pv. oryzae
Xanthomonas oryzae pv. oryzae (Xoo) is a plant pathogen responsible for causing bacterial blight in rice. The immediate alterations in Xoo upon initial contact with rice are essential for pathogenesis. We studied time-resolved genome-wide gene expression in pathogenicity-activated Xoo cells at the transcriptome and proteome levels. The early response genes of Xoo include genes related to cell motility, inorganic ion transport, and effectors. The alteration of gene expression is initiated as early as few minutes after the initial interaction and changes with time. The time-resolved comparison of the transcriptome and proteome shows the differences between transcriptional and translational expression peaks in many genes, although the overall expression pattern of mRNAs and proteins is conserved. The discrepancy suggests an important role of translational regulation in Xoo at the early stages of pathogenesis. The gene expression analysis using time-resolved transcriptome and proteome provides unprecedented valuable information regarding Xoo pathogenesis
ギジ カアツミツ コウセキ ネンド ノ アッシュク モデル ノ コウチク ト オオサカワン ウメタテ ジバン ノ チョウキ チンカ ヨソク エノ テキヨウセイ ニ カンスル ケンキュウ
京都大学0048新制・課程博士博士(工学)甲第11503号工博第2449号新制||工||1331(附属図書館)23146UT51-2005-D253京都大学大学院工学研究科土木工学専攻(主査)教授 関口 秀雄, 教授 井合 進, 教授 嘉門 雅史学位規則第4条第1項該当Doctor of EngineeringKyoto UniversityDA
An SDRAM-aware router for Networks-on-Chip
In this paper, we present an NoC (Networks-on-Chip) router with an SDRAM-aware flow control. Based on a priority-based arbitration, it schedules packets to improve memory utilization and reduce memory latency. Moreover, our multi-scheduling scheme performed by the multiple SDRAM-aware routers helps to achieve better SDRAM performance and save the hardware cost of NoC platform. Experimental results show that our SDRAM-aware router improves memory latency by 18 % and memory utilization by 4.9 % on average with over 42 % saving of gate count of the NoC platform with dual memory subsystem
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