Liposome immunoassay based on bio luminescent detection and its application to on-chip analysis

Luc-encapsulated liposomes were employed to develop on-chip immunoassays. Straight-channel chips were better than microbead for V-cup chips to immobilize several antibodies. Straight-channel chip that has PDMS flat substrate and wider channel (1000 μm) was optimum for this assay. To detect high BL intensity, fast flow rate (300 μl/min) was better than slower flow rate because channel was filled up with substrate quickly. However, substrate volume and lysis buffer didn't affect the detecttion high BL intensity. This implies that a sufficient amount of substrate was delivered to Luc in the liposomes. The LOD of CRP in this assay was 10 ng/mL

A primary thymic adenocarcinoma with two components that traced distinct evolutionary trajectories

Even though it is a rare subtype, identifying the genetic features of thymic adenocarcinoma is valuable for a multifaceted understanding of thymic epithelial tumors. We experienced a female patient with thymic adenocarcinoma associated with thymic cysts. The tumor consisted of a solid whitish lesion (lesion-1) and a large cystic lesion with small papillary nodules (lesion-2). Microscopically, lesion-1 exhibited poorly differentiated adenocarcinoma accompanying numerous inflammatory cell infiltrates, and lesion-2 (the nodules within the cystic lesion) exhibited enteric-type adenocarcinoma. Consistent with the histological difference, whole-exome sequencing revealed that these two components exhibited distinct genetic features, except for only a few shared mutations, including CDKN2A truncation. Lesion-1 exhibited microsatellite instability-high signature with high mutation burden, for which immune checkpoint inhibitors might apply; and lesion-2 exhibited whole-genome doubling with KRAS hotspot mutation. Our case presents novel genetic features of thymic adenocarcinoma and demonstrates that distinct mutational processes can be operative within a single tumor

Onset heart rate of microvolt-level T-wave alternans provides clinical and prognostic value in nonischemic dilated cardiomyopathy

AbstractObjectivesThis study was designed to determine the prognostic value of onset heart rate (OHR) in T-wave alternans (TWA) in patients with nonischemic dilated cardiomyopathy (DCM).BackgroundOne of the current major issues in DCM is to prevent sudden cardiac death (SCD). However, the value of the OHR of TWA as a prognostic indicator in DCM remains to be elucidated.MethodsWe prospectively investigated 104 patients with DCM undergoing TWA testing. The end point of this study was defined as SCD, documented sustained ventricular tachycardia/ventricular fibrillation. Relations between clinical parameters and subsequent outcome were evaluated.ResultsForty-six patients presenting with TWA were assigned to one of the following two subgroups according to OHR for TWA of ≤100 beats/min: group A (n = 24) with OHR ≤100 beats/min and group B (n = 22) with 100 < OHR ≤ 110 beats/min. T-wave alternans was negative in 37 patients (group C) and indeterminate in 21 patients. The follow-up result comprised 83 patients with determined TWA. During a follow-up duration of 21 ± 14 months, there was a total of 12 arrhythmic events, nine of which included three SCDs in group A, two in group B and one in group C. The forward stepwise multivariate Cox hazard analysis revealed that TWA with an OHR ≤100 beats/min and left ventricular ejection fraction were independent predictors of these arrhythmic events (p = 0.0001 and p = 0.0152, respectively).ConclusionsThe OHR of TWA is of additional prognostic value in DCM

Machine learning of brain structural biomarkers for Alzheimer\u27s disease (AD) diagnosis, prediction of disease progression, and amyloid beta deposition in the Japanese population

Introduction:We developed machine learning (ML) designed to analyze structural brain magnetic resonance imaging (MRI), and trained it on the Alzheimer\u27s Disease Neuroimaging Initiative (ADNI) database. In this study, we verified its utility in the Japanese population.Methods:A total of 535 participants were enrolled from the Japanese ADNI database, including 148 AD, 152 normal, and 235 mild cognitive impairment (MCI). Probability of AD was expressed as AD likelihood scores (ADLS).Results:The accuracy of AD diagnosis was 88.0% to 91.2%. The accuracy of predicting the disease progression in non-dementia participants over a 3-year observation was 76.0% to 79.3%. More than 90% of the participants with low ADLS did not progress to AD within 3 years. In the amyloid positron emission tomography (PET)-positive MCI, the hazard ratio of progression was 2.39 with low ADLS, and 5.77 with high ADLS. When high ADLS was defined as N+ and Pittsburgh compound B (PiB) PET positivity was defined as A+, the time to disease progression for 50% of MCI participants was 23.7 months in A+N+, whereas it was 52.3 months in A+N-.Conclusion:These results support the feasibility of our ML for the diagnosis of AD and prediction of the disease progression

Dynamics of dissolved and bubbled methane in Lake Youngrang and HwaJlnPO, Korea

Article信州大学山地水環境教育研究センター研究報告 6: 69-72(2010)departmental bulletin pape

Severe Hypomyelination and Developmental Defects Are Caused in Mice Lacking Protein Arginine Methyltransferase 1 (PRMT1) in the Central Nervous System

Protein arginine methyltransferase 1 (PRMT1) is involved in cell proliferation, DNA damage response, and transcriptional regulation. While PRMT1 is extensively expressed in the central nervous system (CNS) at embryonic and perinatal stages, the physiological role of PRMT1 was poorly understood. Here, to investigate the primary function of PRMT1 in the CNS, we generated CNS-specific PRMT1 knockout mice by Cre-loxP system. These mice exhibited post-natal growth retardation with tremors and most of them died in two weeks after birth. Brain histological analyses revealed the prominent cell reduction in the white matter tracts of the mutant mice. Furthermore, ultrastructural analysis demonstrated that myelin sheath was almost completely ablated in the CNS of these animals. In agreement with hypomyelination, we also observed that most major myelin proteins including MBP, CNPase, and MAG were dramatically decreased, although neuronal and astrocytic markers were preserved in the brain of CNS-specific PRMT1 knockout mice. These animals had reduced number of OLIG2+ oligodendrocyte lineage cells in the white matter. We found that expressions of transcription factors essential for oligodendrocyte specification and further maturation were significantly suppressed in the brain of the mutant mice. Our findings provide evidence that PRMT1 is required for CNS development, especially for oligodendrocyte maturation processes

Spin dynamics and spin freezing behavior in the two-dimensional antiferromagnet NiGa2_{2}S4_{4} revealed by Ga-NMR, NQR and μ\muSR measurements

We have performed $^{69,71}$Ga nuclear magnetic resonance (NMR) and nuclear quadrupole resonance (NQR) and muon spin rotation/resonance on the quasi two-dimensional antiferromagnet (AFM) NiGa$_2$S$_4$, in order to investigate its spin dynamics and magnetic state at low temperatures. Although there exists only one crystallographic site for Ga in NiGa$_2$S$_4$, we found two distinct Ga signals by NMR and NQR. The origin of the two Ga signals is not fully understood, but possibly due to stacking faults along the c axis which induce additional broad Ga NMR and NQR signals with different local symmetries. We found the novel spin freezing occurring at $T_{\rm f}$, at which the specific heat shows a maximum, from a clear divergent behavior of the nuclear spin-lattice relaxation rate $1/T_{1}$ and nuclear spin-spin relaxation rate $1/T_{2}$ measured by Ga-NQR as well as the muon spin relaxation rate $\lambda$. The main sharp NQR peaks exhibit a stronger tendency of divergence, compared with the weak broader spectral peaks, indicating that the spin freezing is intrinsic in NiGa$_2$S$_4$. The behavior of these relaxation rates strongly suggests that the Ni spin fluctuations slow down towards $T_{\rm f}$, and the temperature range of the divergence is anomalously wider than that in a conventional magnetic ordering. A broad structureless spectrum and multi-component $T_1$ were observed below 2 K, indicating that a static magnetic state with incommensurate magnetic correlations or inhomogeneously distributed moments is realized at low temperatures. However, the wide temperature region between 2 K and $T_{\rm f}$, where the NQR signal was not observed, suggests that the Ni spins do not freeze immediately below $T_{\rm f}$, but keep fluctuating down to 2 K with the MHz frequency range.Comment: 14 pages, 14 figures. To appear in Phys. Rev.

Activation of the pentose phosphate pathway in macrophages is crucial for granuloma formation in sarcoidosis

肉芽腫形成に特異的な代謝経路の発見 --ペントースリン酸回路の制御による新規治療--. 京都大学プレスリリース. 2023-12-01.More than skin-deep: Kyoto researchers discover metabolic pathway specific to granuloma formation in patients. 京都大学プレスリリース. 2023-12-07.Sarcoidosis is a disease of unknown etiology in which granulomas form throughout the body and is typically treated with glucocorticoids, but there are no approved steroid-sparing alternatives. Here, we investigated the mechanism of granuloma formation using single-cell RNA-Seq in sarcoidosis patients. We observed that the percentages of triggering receptor expressed on myeloid cells 2–positive (TREM2-positive) macrophages expressing angiotensin-converting enzyme (ACE) and lysozyme, diagnostic makers of sarcoidosis, were increased in cutaneous sarcoidosis granulomas. Macrophages in the sarcoidosis lesion were hypermetabolic, especially in the pentose phosphate pathway (PPP). Expression of the PPP enzymes, such as fructose-1, 6-bisphosphatase 1 (FBP1), was elevated in both systemic granuloma lesions and serum of sarcoidosis patients. Granuloma formation was attenuated by the PPP inhibitors in in vitro giant cell and in vivo murine granuloma models. These results suggest that the PPP may be a promising target for developing therapeutics for sarcoidosis

Machine Learning for Diagnosis of AD and Prediction of MCI Progression From Brain MRI Using Brain Anatomical Analysis Using Diffeomorphic Deformation.

Background:With the growing momentum for the adoption of machine learning (ML) in medical field, it is likely that reliance on ML for imaging will become routine over the next few years. We have developed a software named BAAD, which uses ML algorithms for the diagnosis of Alzheimer\u27s disease (AD) and prediction of mild cognitive impairment (MCI) progression.Methods:We constructed an algorithm by combining a support vector machine (SVM) to classify and a voxel-based morphometry (VBM) to reduce concerned variables. We grouped progressive MCI and AD as an AD spectrum and trained SVM according to this classification. We randomly selected half from the total 1,314 subjects of AD neuroimaging Initiative (ADNI) from North America for SVM training, and the remaining half were used for validation to fine-tune the model hyperparameters. We created two types of SVMs, one based solely on the brain structure (SVMst), and the other based on both the brain structure and Mini-Mental State Examination score (SVMcog). We compared the model performance with two expert neuroradiologists, and further evaluated it in test datasets involving 519, 592, 69, and 128 subjects from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Aging (AIBL), Japanese ADNI, the Minimal Interval Resonance Imaging in AD (MIDIAD) and the Open Access Series of Imaging Studies (OASIS), respectively.Results:BAAD\u27s SVMs outperformed radiologists for AD diagnosis in a structural magnetic resonance imaging review. The accuracy of the two radiologists was 57.5 and 70.0%, respectively, whereas, that of the SVMst was 90.5%. The diagnostic accuracy of the SVMst and SVMcog in the test datasets ranged from 88.0 to 97.1% and 92.5 to 100%, respectively. The prediction accuracy for MCI progression was 83.0% in SVMst and 85.0% in SVMcog. In the AD spectrum classified by SVMst, 87.1% of the subjects were Aβ positive according to an AV-45 positron emission tomography. Similarly, among MCI patients classified for the AD spectrum, 89.5% of the subjects progressed to AD.Conclusion:Our ML has shown high performance in AD diagnosis and prediction of MCI progression. It outperformed expert radiologists, and is expected to provide support in clinical practice