Osaka Prefectural Toyonaka Support School

Cellular senescence contributes to aging and disease, and senolytic drugs that selectively eliminate senescent cells hold therapeutic promise. Although over 20 candidates have been reported, their relative efficacies remain unclear. Here we systematically compared 21 senolytic agents using a senolytic specificity index, identifying the Bcl-2 inhibitor ABT263 and the BET inhibitor ARV825 as most effective senolytics across fibroblast and epithelial senescence models. However, even upon extended treatment with these most potent senolytics, a proportion of senescent cells remained viable. We found that senolytic resistance was driven by maintenance of mitochondrial integrity through V-ATPase-mediated clearance of damaged mitochondria. Imposing mitochondrial stress via metabolic workload enhanced the senolytic efficacies of ABT263 and ARV825 in vitro, and in mouse models, ketogenic diet adoption or SGLT2 inhibition similarly potentiated ABT263-induced and ARV825-induced senolysis, reducing metastasis and tumor growth. These findings suggest that mitochondrial quality control is a key determinant of resistance to ABT263-induced and ARV825-induced senolysis, providing a possible framework for rational combination senotherapies.

In this survey article, we first review relations between fibration-like structures and contact and symplectic manifolds. Then we overview recent developments in the study of the topology of those manifolds, including author’s results, via fibration-like structures.

BackgroundAccurate automatic recognition of surgical instruments is important for enhancing the safety and efficiency of transcanal endoscopic ear surgery (TEES). Segment Anything Model 2 (SAM 2) is a state-of-the-art artificial intelligence (AI) model featuring “zero-shot segmentation”, which allows it to identify objects without extensive training data. The purpose of this study was to be the first to apply SAM 2 to TEES videos to evaluate its performance in segmenting and classifying surgical instruments.MethodsFrom videos of three clinical TEES cases (tympanoplasty), we created a 684-frame evaluation video that simulated the sequential use of four types of surgical instruments: cupped forceps, pick, alligator forceps, and circular knife. SAM 2 was instructed to identify the instruments using only 12 reference images. Performance was quantitatively evaluated using four metrics—Precision, Recall, dice similarity coefficient (DSC), and intersection over union (IoU)—as well as a confusion matrix to assess frame-level classification accuracy by comparing the model’s output to manually created ground-truth annotations.ResultsFor segmentation without classification, SAM 2 demonstrated excellent performance, with a mean Precision of 0.98, a mean Recall of 0.89, a mean DSC of 0.93, and a mean IoU of 0.87. When classifying the four specific instrument types, performance varied, with mean Precision ranging from 0.68 to 0.98, mean Recall from 0.79 to 0.86, mean DSC from 0.62 to 0.89, and mean IoU from 0.58 to 0.84. Notably, false-positive detections in non-instrument regions were extremely rare. A trend of lower classification accuracy was observed for articulating instruments with moving parts (cupped forceps and alligator forceps).ConclusionsThis study demonstrated that SAM 2 can accurately identify surgical instruments in TEES videos without the need to prepare large, costly training datasets. This zero-shot segmentation characteristic significantly lowers the barrier to clinical implementation of AI, suggesting it is a promising foundational technology for future surgical navigation and robotic automation. Key future challenges include improving classification accuracy for articulating instruments and accelerating processing speed for practical, real-time use.

Collective cell behavior is fundamental to structure multicellular organisms. There, constituting cells always have heterogeneous properties across cell types (macro-heterogeneity) and within a cell type (micro-heterogeneity). Many studies have described the existence of heterogeneity in various systems at the cellular level, whereas little has investigated its effect on the systems. Unveiling how heterogeneity plays a role in the collective behavior would build a bridge from microscopic to macroscopic biological phenomena. We use the muscle remodeling in Drosophila as a model system, in which drastic reconstruction processes involve the physical interactions of various cells. At the early pupal stages, hundreds of hemocytes vigorously migrate and decompose the larval muscles into fragments called sarcolytes. We used in vivo and in silico approaches to understand how the dynamics of the sarcolyte population are characterized by hemocytes and other cells in the environment. Our in vivo imaging showed that the sarcolyte population gradually reduced the speed while changing the spatial arrangements. We also found that the sarcolyte dynamics involve macro-heterogeneity, namely, the coexistence of fat body cells and hemocytes, as well as micro-heterogeneity within hemocytes. To computationally evaluate the effects of factors determining the speed and arrangement of the sarcolyte population, we built a mathematical model assuming simplified interactions between sarcolytes, hemocytes, and fat body cells. Our simulations showed that, firstly, the efficient spreading and stable pattern formation of sarcolytes were together achieved by a delayed emergence of fat body cells and the micro-heterogeneity in hemocyte motility. Secondly, based on the similarity of observed and simulated network-like arrangements of sarcolytes, spatial confinement was another factor that causes the stabilization of sarcolytes. This study provides a pattern formation mechanism by which macro- and micro-heterogeneous migratory cells generate a 'dual-purpose' collective behavior-quickly spreading particles throughout the field while efficiently organizing them into an orderly arrangement.

We theoretically investigate the electronic structure of monolayer ${\mathrm{BC}}_{3}$ and find that it hosts anisotropic multiple valleys originating from the splitting of the van Hove singularity in graphene. To make use of its favorable electronic structure, we investigate the electronic structure of alkali-metal-intercalated ${\mathrm{BC}}_{3}$, where intercalated atoms not only introduce electron carriers but also suppress interlayer coupling. We find that the interlayer transfer is effectively suppressed by potassium intercalation, by which the favorable electronic structure of monolayer ${\mathrm{BC}}_{3}$ is preserved. Finally, we perform model calculation with the onsite-energy offset, and we verify that the strategy of introducing the splitting to the van Hove singularity works well.

Disaggregated data centers (DDC) enable efficient resource utilization. However, a DDC faces performance degradation due to resource communication latency. Furthermore, workload changes in DDC affect the execution time of service tasks. Therefore, to continually satisfy the performance requirements for service tasks, a dynamic resource management method is required that considers workload changes and the impact of the network on performance. We propose a dynamic resource allocation method considering the workload changes in a DDC (DRA-CWC). We formulate the impact of workload changes on performance and define resource allocation costs based on service demand and resource importance for future service execution. Based on these, we preserve the required resources to satisfy the performance requirements for the future workload increase. By comparing conventional resource allocation methods for a DDC, we demonstrate that DRA-CWC can satisfy service performance requirements for a longer time.

Heterogeneous noble metal catalysts exhibit various functions. Although their redox functions have been extensively studied, we focused on their soft Lewis acid functions. Supported Au, Pt, and Pd catalysts electrophilically attack the π-electrons of soft bases such as alkynes, alkenes, and aromatic compounds to perform addition and substitution reactions. Hydroamination, intramolecular cyclization of alkynyl carboxylic acids, isomerization of allylic esters, vinyl exchange reactions, Wacker oxidation, and oxidative homocoupling of aromatics are introduced based on a discussion of the active species and reaction mechanisms. Furthermore, the adsorption of sulfur compounds, which are soft bases, onto the supported AuNPs is discussed. The adsorption and removal of 1,3-dimethyltrisulfane (DMTS), which is the compound responsible for the stale odor of "hine-ka" in alcoholic beverages, particularly Japanese sake, is described.

Abstract We investigate whether the soft mode that becomes massless at the QCD critical point (CP) causes an enhancement of the dilepton production rate (DPR) and electric conductivity around the CP through modification of the photon self-energy using the two-flavor Nambu–Jona-Lasinio model. The modification is described by the so-called Aslamazov–Larkin, Maki–Thompson, and density of states terms, which have been taken into account in our previous study on the DPR near the color-superconducting phase transition, with a replacement of the diquark modes with the soft mode of the QCD CP. We show that the coupling of photons with the soft modes brings about an enhancement of the DPR in the low-invariant-mass region and the conductivity near the CP, which would be observable in relativistic heavy-ion collisions.

We developed an autocorrelation function to resolve the overtaking problem in a multiturn time-of-flight mass spectrometer (TOF-MS). The function analyzes the characteristic period for one lap of each ion packet and derives a mass spectrum from a signal pulse train composed of multiturn ion packets. To detect the ion pulse train, a new nondestructive ion detector was developed and installed in the multiturn orbit of MULTUM-S II. This detector is composed of an electrostatically induced charge detector, a preamplifier, and a digitizer. The electrostatic noises are smaller than the single-ion signals owing to the accumulation of the multiturn TOF spectrum. The conventional ion detector of TOF-MS is operated after collecting the signal pulse train. The multiturn TOF spectrum was convolved with an autocorrelation function to derive the mass spectrum. The convolved mass spectrum performed a mass resolving power (MRP) of 28,200 at m/z 69 and mass accuracy of 28 ppm for the perfluorotributylamine (PFTBA) gas sample.