Precision Microstate Counting of Small Black Rings

We examine certain two-charge supersymmetric states with spin in five-dimensional string theories which can be viewed as small black rings when the gravitational coupling is large. Using the 4D-5D connection, these small black rings correspond to four-dimensional non-spinning small black holes. Using this correspondence, we compute the degeneracy of the microstates of the small black rings exactly and show that it is in precise agreement with the macroscopic degeneracy to all orders in an asymptotic expansion. Furthermore, we analyze the five-dimensional small black ring geometry and show qualitatively that the Regge bound arises from the requirement that closed time-like curves be absent.Comment: 4 pages, LaTeX, references adde

CP violation in modified bipair neutrino mixing and leptogenesis

We study effects of CP violation in a modified bipair neutrino mixing scheme predicting $\sin^2\theta_{23}$ near both 0.4 and 0.6 currently consistent with experimentally allowed values. The source of CP violation is supplied by charged lepton mixing accompanied by a single phase, whose mixing size is assumed to be less than that of the Wolfenstein parameter for the quark mixing. Including results of leptogenesis, which is based on the minimal seesaw model, we obtain the allowed region of CP-violating Dirac and Majorana phases, which provides the observed baryon asymmetry of the universe in the case of the Dirac neutrino mass matrix subject to one zero texture.Comment: 5 pages, 30 figures, accepted for publication in Physics Letters

Development of AI-driven prediction models to realize real-time tumor tracking during radiotherapy

[Background] In infrared reflective (IR) marker-based hybrid real-time tumor tracking (RTTT), the internal target position is predicted with the positions of IR markers attached on the patient’s body surface using a prediction model. In this work, we developed two artificial intelligence (AI)-driven prediction models to improve RTTT radiotherapy, namely, a convolutional neural network (CNN) and an adaptive neuro-fuzzy inference system (ANFIS) model. The models aim to improve the accuracy in predicting three-dimensional tumor motion. [Methods] From patients whose respiration-induced motion of the tumor, indicated by the fiducial markers, exceeded 8 mm, 1079 logfiles of IR marker-based hybrid RTTT (IR Tracking) with the gimbal-head radiotherapy system were acquired and randomly divided into two datasets. All the included patients were breathing freely with more than four external IR markers. The historical dataset for the CNN model contained 1003 logfiles, while the remaining 76 logfiles complemented the evaluation dataset. The logfiles recorded the external IR marker positions at a frequency of 60 Hz and fiducial markers as surrogates for the detected target positions every 80-640 ms for 20-40 s. For each logfile in the evaluation dataset, the prediction models were trained based on the data in the first three quarters of the recording period. In the last quarter, the performance of the patient-specific prediction models was tested and evaluated. The overall performance of the AI-driven prediction models was ranked by the percentage of predicted target position within 2 mm of the detected target position. Moreover, the performance of the AI-driven models was compared to a regression prediction model currently implemented in gimbal-head radiotherapy systems. [Results] The percentage of the predicted target position within 2 mm of the detected target position was 95.1%, 92.6% and 85.6% for the CNN, ANFIS, and regression model, respectively. In the evaluation dataset, the CNN, ANFIS, and regression model performed best in 43, 28 and 5 logfiles, respectively. [Conclusions] The proposed AI-driven prediction models outperformed the regression prediction model, and the overall performance of the CNN model was slightly better than that of the ANFIS model on the evaluation dataset

Sulfur assimilation using gaseous carbonyl sulfideby the soil fungus Trichoderma harzianum

Fungi have the capacity to assimilate a diverse range of both inorganic and organic sulfur compounds. It has been recognized that all sulfur sources taken up by fungi are in soluble forms. In this study, we present evidence that fungi can utilize gaseous carbonyl sulfide(COS) for the assimilation of a sulfur compound. We found that the filamentousfungus Trichoderma harzianum strain THIF08, which has constitutively high COS-degrading activity, was able to grow with COS as the sole sulfur source. Cultivation with 34S-labeled COS revealed that sulfur atom from COS was incorporated into intracellular metabolites such as glutathione and ergothioneine. COS degradation by strain THIF08, in which as much of the moisture derived from the agar medium as possible was removed, indicated that gaseous COS was taken up directly into the cell. Escherichia coli transformed with a COS hydrolase (COSase) gene, which is clade D of the β-class carbonic anhydrase subfamily enzyme with high specificity for COS but low activity for CO2 hydration, showed that the COSase is involved in COS assimilation. Comparison of sulfur metabolites of strain THIF08 revealed a higher relative abundance of reduced sulfur compounds under the COS-supplemented condition than the sulfate-supplemented condition, suggesting that sulfur assimilation is more energetically efficient with COS than with sulfate because there is no redox change of sulfur. Phylogenetic analysis of the genes encoding COSase, which are distributed in a wide range of fungal taxa, suggests that the common ancestor of Ascomycota, Basidiomycota, and Mucoromycota acquired COSase at about 790-670 Ma. © 2024 Iizuka et al

Neuronal surface antigen-specific immunostaining pattern on a rat brain immunohistochemistry in autoimmune encephalitis

A variety of neuronal surface (NS) antibodies (NS-Ab) have been identified in autoimmune encephalitis (AE). Tissue-based assay (TBA) using a rodent brain immunohistochemistry (IHC) is used to screen NS-Ab, while cell-based assay (CBA) to determine NS antigens. Commercial rat brain IHC is currently available but its clinical relevance remains unclear. Immunostaining patterns of NS antigens have not been extensively studied yet. To address these issues, we assessed a predictive value of “neuropil pattern” and “GFAP pattern” on commercial IHC in 261 patients, and characterized an immunostaining pattern of 7 NS antigens (NMDAR, LGI1, GABAaR, GABAbR, AMPAR, Caspr2, GluK2). Sensitivity and specificity of “neuropil pattern” for predicting NS-Ab were 66.0% (95% CI 55.7-75.3), and 98.2% (95% CI 94.8-99.6), respectively. False-positive rate was 1.8% (3/164) while false-negative rate was 34.0% (33/97). In all 3 false-positive patients, neuropil-like staining was attributed to high titers of GAD65-Ab. In 33 false-negative patients, NMDAR was most frequently identified (n=18 [54.5%], 16/18 [88.9%] had low titers [< 1:32]), followed by GABAaR (n=5). Of 261 patients, 25 (9.6%) had either GFAP (n=21) or GFAP-mimicking pattern (n=4). GFAP-Ab were identified in 21 of 31 patients examined with CBA (20 with GFAP pattern, 1 with GFAP-mimicking pattern). Immunostaining pattern of each NS antigen was as follows: 1) NMDAR revealed homogenous reactivity in the dentate gyrus molecular layer (DG-ML) with less intense dot-like reactivity in the cerebellar granular layer (CB-GL); 2) both GABAaR and GluK2 revealed intense dot-like reactivity in the CB-GL, but GABAaR revealed homogenous reactivity in the DG-ML while GluK2 revealed intense reactivity along the inner layer of the DG-ML; and 3) LGI1, Caspr2, GABAbR, and AMPAR revealed intense reactivity in the cerebellar ML (CB-ML) but LGI1 revealed intense reactivity along the middle layer of the DG-ML. Whereas, Caspr2, GABAbR, and AMPAR revealed similar reactivity in the DG-ML but some difference in other regions. TBA is useful not only for screening NS- or GFAP-Ab but also for estimating NS antigens; however, negative results should be interpreted cautiously because “neuropil pattern” may be missed on commercial IHC when antibody titers are low. Antigen-specific immunoreactivity is a useful biomarker of AE

Irregular atrial flutter following pulmonary vein isolation for persistent atrial fibrillation

AbstractA 65-year-old man with a history of refractory paroxysmal atrial fibrillation (AF) underwent catheter ablation for persistent AF lasting 2 months. AF was not terminated after complete isolation of the 4 pulmonary veins (PV). Instead, it was transformed to a sustained atrial tachyarrhythmia with beat-to-beat variability in the atrial cycle length. A 12-lead electrocardiogram during tachycardia showed negative flutter-like waves in the inferior leads. Entrainment pacing along the tricuspid annulus confirmed the diagnosis of irregular cavotricuspid isthmus (CTI)-dependent typical atrial flutter (AFL). Linear ablation of the CTI terminated AFL and restored sinus rhythm

Advantages and Disadvantages of Hyperbaric Oxygen Treatment in Mice with Obesity Hyperlipidemia and Steatohepatitis

The effect of hyperbaric oxygen treatment (HBOT) was examined using MSG mice, which are an animal model of obesity, hyperlipidemia, diabetes, and nonalcoholic fatty liver disease. Nineteen MSG male mice were divided into HBOT treated and control groups at 12 weeks of ages. The HBOT group was treated with hyperbaric oxygen from 12 to 14 weeks (first phase) and then from 16 to 18 weeks (second phase). Interestingly, the body weight of the HBOT group was significantly lower (P < 0.01) than that of the control group. In contrast, the serum lipid level did not show significant changes between the two groups. As for the effects of increasing oxidative stress, the liver histology of the HBOT group showed severer cellular damage and aberrant TNF-α expression. HBOT has the advantage of improving obesity in patients with metabolic syndrome, but the fault of causing organ damage by increasing oxidative stress

Preventive Effects of Salacia reticulata on Obesity and Metabolic Disorders in TSOD Mice

The extracts of Salacia reticulata (Salacia extract), a plant that has been used for the treatment of early diabetes, rheumatism and gonorrhea in Ayurveda, have been shown to have an anti-obesity effect and suppress hyperglycemia. In this study, the effects of Salacia extract on various symptoms of metabolic disorder were investigated and compared using these TSOD mice and non-obese TSNO mice. Body weight, food intake, plasma biochemistry, visceral and subcutaneous fat (X-ray and CT), glucose tolerance, blood pressure and pain tolerance were measured, and histopathological examination of the liver was carried out. A significant dose-dependent decline in the gain in body weight, accumulation of visceral and subcutaneous fat and an improvement of abnormal glucose tolerance, hypertension and peripheral neuropathy were noticed in TSOD mice. In addition, hepatocellular swelling, fatty degeneration of hepatocytes, inflammatory cell infiltration and single-cell necrosis were observed on histopathological examination of the liver in TSOD mice. Salacia extract markedly improved these symptoms upon treatment. Based on the above results, it is concluded that Salacia extract has remarkable potential to prevent obesity and associated metabolic disorders including the development of metabolic syndrome