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Abstract Recent studies have revealed that biotic interactions in ecological communities vary over time, possibly mediating community responses to anthropogenic disturbances. This study investigated the heterogeneity of such variability within a real community and its impact on population stability in the face of pesticide application, particularly focusing on density-dependence of the interaction effect. Using outdoor mesocosms with a freshwater community, we found considerable heterogeneity in density-dependent interaction variability among links in the same community. This variability mediated the stability of recipient populations, with negative density-dependent interaction variability stabilizing whereas positive density-dependence and density-independent interaction variability destabilizing populations. Unexpectedly, the mean interaction strength, which is typically considered crucial for stability, had no significant effect, suggesting that how organisms interact on average is insufficient to predict the ecological impacts of pesticides. Our findings emphasize the multifaceted role of interaction variability in predicting the ecological consequences of anthropogenic disturbances such as pesticide application.

Abstract Background Lung sound analysis parameters have been reported to be useful biomarkers for evaluating airway condition. We developed an automatic lung sound analysis software program for infants and children based on lung sound spectral curves of frequency and power by leveraging machine learning (ML) technology. Methods To put this software program into clinical practice, in Study 1, the reliability and reproducibility of the software program using data from younger children were examined. In Study 2, the relationship between lung sound parameters and respiratory flow (L/s) was evaluated using data from older children. In Study 3, we conducted a survey using the ATS-DLD questionnaire to evaluate the clinical usefulness. The survey focused on the history of wheezing and allergies, among healthy 3-year-old infants, and then measured lung sounds. The clinical usefulness was evaluated by comparing the questionnaire results with the results of the new lung sound parameters. Results In Studies 1 and 2, the parameters of the new software program demonstrated excellent reproducibility and reliability, and were not affected by airflow (L/s). In Study 3, infants with a history of wheezing showed lower FAP0 and RPF75p (p

Abstract In this paper, we study massless/massive vector and p-form field perturbations in AdS spacetime with an end-of-the-world brane. By imposing Υ(1) preserving Neumann boundary condition on the end-of-the-world brane, we study their spectrum and discuss their implications for dual BCFT operators. When the perturbation is massless, the dual BCFT operator is a conserved current and we show that such an operator indeed satisfies the Υ(1) preserving conformal boundary condition. On the other hand, when the perturbation is massive, in general there exists non-vanishing perpendicular components of the dual BCFT operator, even in the massless limit. We explain this difference between massless and massive perturbations from the point of view of the bulk gauge symmetry, or equivalently from different structure of equations of motion. We also find several brane-tension-independent modes in massless perturbations, and these are understood as boundary-condition-independent modes from the dual BCFT point of view.

Abstract Background and Aims Degenerative cervical myelopathy (DCM) is a debilitating condition characterized by compression of the cervical spinal cord, leading to neurological deficits. This study aimed to investigate the association between comorbidities like diabetes mellitus (DM) and obesity and quality of life (QOL) in preoperative patients with DCM, and to examine the distribution of pain and numbness. Methods A cross‐sectional study with 86 preoperative patients with DCM was conducted. Patient‐reported outcome measures (PROMs) including Core Outcome Measure Index for the neck (COMI‐Neck), Neck Disability Index (NDI), EQ‐5D‐3L, SF‐12v2 assessed QOL, and baseline characteristics were collected. Patients were categorized by diabetic and obesity status, resulting in 17 with and 69 without DM, and 27 obese, 59 nonobese patients. In the statistical analysis, we compared PROMs and baseline characteristics, and conducted MANCOVA to investigate the association of DM and obesity with PROMs. Results The study found no significant differences in preoperative QOL between patients with and without DM or obesity. Additionally, the results of MANCOVA indicated that neither DM nor obesity alone, nor their combination, had an association with the total scores of PROMs. In each group, the Symptom‐specific well‐being score on the COMI‐Neck was notably high, implying distressing current symptoms (median: 10). On the NDI, the median score for pain intensity, lifting, work, and recreation subitems was 3. Pain was predominantly reported in the neck and lower back, while numbness was more prevalent in the peripheral regions of the upper and lower limbs. Conclusion Preoperative QOL was not significantly affected by the presence of DM and/or obesity. DCM‐related symptoms may mask the associations with these comorbidities. Regardless of the preoperative condition, it is important to address the PROMs items that posed challenges before surgery.

Abstract Recently proposed duality relates the critical level limit $$\widehat{k}\to -2$$ of $${\text{SU}}{\left(2\right)}_{\widehat{k}}$$ WZW models to a classical three-dimensional Einstein gravity on a sphere. In this paper, we propose a dimensional reduced version of this duality. The gravity side is reduced to a Jackiw-Teitelboim (JT) gravity on S 2 with a non-standard boundary term, or a BF theory with SU(2) gauge symmetry. At least in low temperature limit, these two-dimensional gravity theories completely capture the original three-dimensional gravity effect. The CFT side is reduced to a certain complex Liouville quantum mechanics (LQM) with SU(2) gauge symmetry. Our proposal gives an interesting example of a holography without boundary. We also discuss a higher-spin generalization with SU(N) gauge symmetry.

Abstract Microactuators are essential for advances in micro-optics, ultrasonic transducers and microsensors, and there is a growing demand for miniaturization and improved power. Here we demonstrate the actuation of micromechanical structures based on spin-current volume effect using an amorphous magnetic film of TbFeCo with volume magnetostriction. A 2 mm-diameter circular polyimide diaphragm coated with thin TbFeCo/non-magnetic metal films is prepared as the micromechanical structure. When an alternating charge current flows through the TbFeCo/non-magnetic metal films on the diaphragm under an external magnetic field orthogonal to the charge current, an alternating spin-current flows in the non-magnetic metal film due to the spin-Hall effect. In the spin-current volume effect, the spin-current transports angular momentum from the non-magnetic metal to TbFeCo film, and the spin-transfer torque modulates the magnetization fluctuation of the TbFeCo film, causing the diaphragm to vibrate due to spin-lattice coupling. The power density of the TbFeCo/Pt films actuator is larger than 1.17 × 106 W m−3 at 20 mA charge current under 7.2 kOe magnetic field. This value is much higher than that of various existing film-type microactuators. This spin-current volume effect is effective as a new actuation mechanism for microactuators used in micro-optical systems, acoustic diagnostic equipment, and micro-fluidic systems etc.

Abstract Background and Aim This study aimed to clarify the efficacy and safety of 48‐week pemafibrate treatment in patients with metabolic dysfunction‐associated steatotic liver disease (MASLD) complicated by dyslipidemia. Methods A total of 110 patients diagnosed with MASLD complicated by dyslipidemia received pemafibrate at a dose of 0.1 mg twice daily for 48 weeks. Results The participants were 54 males and 37 females, with a median age of 63 (52–71) years. Besides improvement in lipid profile, significant reductions from baseline to 48 weeks of treatment were found in liver‐related enzymes, such as aspartate aminotransferase, alanine aminotransferase (ALT), gamma‐glutamyl transpeptidase, and alkaline phosphatase (P

ABSTRACTArchaea, bacteria, and fungi in the soil are increasingly recognized as determinants of agricultural productivity and sustainability. A crucial step for exploring soil microbiomes with important ecosystem functions is to perform statistical analyses on the potential relationship between microbiome structure and functions based on comparisons of hundreds or thousands of environmental samples collected across broad geographic ranges. In this study, we integrated agricultural field metadata with microbial community analyses by targeting 2,903 bulk soil samples collected along a latitudinal gradient from cool-temperate to subtropical regions in Japan (26.1–42.8 °N). The data involving 632 archaeal, 26,868 bacterial, and 4,889 fungal operational taxonomic units detected across the fields of 19 crop plant species allowed us to conduct statistical analyses (permutational analyses of variance, generalized linear mixed models, randomization analyses, and network analyses) on the relationship among edaphic factors, microbiome compositions, and crop disease prevalence. We then examined whether the diverse microbes form species sets varying in potential ecological impacts on crop plants. A network analysis suggested that the observed prokaryotes and fungi were classified into several species sets (network modules), which differed substantially in association with crop disease prevalence. Within the network of microbe-to-microbe coexistence, ecologically diverse microbes, such as an ammonium-oxidizing archaeon, an antibiotics-producing bacterium, and a potentially mycoparasitic fungus, were inferred to play key roles in shifts between crop-disease-promotive and crop-disease-suppressive states of soil microbiomes. The bird’s-eye view of soil microbiome structure will provide a basis for designing and managing agroecosystems with high disease-suppressive functions.IMPORTANCEUnderstanding how microbiome structure and functions are organized in soil ecosystems is one of the major challenges in both basic ecology and applied microbiology. Given the ongoing worldwide degradation of agroecosystems, building frameworks for exploring structural diversity and functional profiles of soil microbiomes is an essential task. Our study provides an overview of cropland microbiome states in light of potential crop-disease-suppressive functions. The large data set allowed us to explore highly functional species sets that may be stably managed in agroecosystems. Furthermore, an analysis of network architecture highlighted species that are potentially used to cause shifts from disease-prevalent states of agroecosystems to disease-suppressive states. By extending the approach of comparative analyses toward broader geographic ranges and diverse agricultural practices, agroecosystem with maximized biological functions will be further explored.

Abstract Recent studies have shown that D-allose, a rare sugar, elicits antitumor effects on different types of solid cancers, such as hepatocellular carcinoma, non-small-cell lung cancer, and squamous cell carcinoma of the head and neck. In this study, we examined the effects of D-allose on the proliferation of human glioblastoma (GBM) cell lines (i.e., U251MG and U87MG) in vitro and in vivo and the underlying mechanisms. D-allose treatment inhibited the proliferation of U251MG and U87MG cells in a dose-dependent manner (3–50 mM). However, D-allose treatment did not affect cell cycles or apoptosis in these cells but significantly decreased the cell division frequency in both GBM cell lines. In a subcutaneous U87MG cell xenograft model, intraperitoneal injection of D-allose (100 mg/kg/day) significantly reduced the tumor volume in 28 days. These data indicate that D-allose-induced reduction in cell proliferation is associated with a subsequent decrease in the number of cell divisions, independent of cell-cycle arrest and apoptosis. Thus, D-allose could be an attractive additive to therapeutic strategies for GBM.

Abstract In this paper, we study one-loop contributions in the double-scaling limit of the SYK model from the chord diagrams and Liouville type effective action. We compute and clarify the meaning of each component consisting of the one-loop corrections for the two- and time-ordered four-point functions of light operators. We also reproduce the exact expression of the out-of-time-ordered four-point function at arbitrary temperatures within the one-loop level, which were previously computed from different methods.

Abstract The information metric on the space of boundary coupling constants in two-dimensional conformal field theories is studied. Such a metric is related to the Casimir energy difference of the theory defined on an interval. We concretely compute the information metric on the boundary conformal manifold of free boson CFT as well as SU(2) k WZW theory, obtaining the result expected from the symmetry of the systems. We also compute the information metric on the space of non-conformal boundary states produced by boundary mass perturbations in the theory of a real free scalar. The holographic dual of the boundary information metric in the context of AdS3/BCFT2 is also discussed. We argue that it corresponds to the area of the minimal cross section of the end-of-the-world brane connecting two boundaries of the asymptotic BCFTs.

Abstract Reducing antibiotic usage among livestock animals to prevent antimicrobial resistance has become an urgent issue worldwide. This study evaluated the effects of administering chlortetracycline (CTC), a versatile antibacterial agent, on the performance, blood components, fecal microbiota, and organic acid concentrations of calves. Japanese Black calves were fed with milk replacers containing CTC at 10 g/kg (CON group) or 0 g/kg (EXP group). Growth performance was not affected by CTC administration. However, CTC administration altered the correlation between fecal organic acids and bacterial genera. Machine learning (ML) methods such as association analysis, linear discriminant analysis, and energy landscape analysis revealed that CTC administration affected populations of various types of fecal bacteria. Interestingly, the abundance of several methane-producing bacteria at 60 days of age was high in the CON group, and the abundance of Lachnospiraceae, a butyrate-producing bacterium, was high in the EXP group. Furthermore, statistical causal inference based on ML data estimated that CTC treatment affected the entire intestinal environment, potentially suppressing butyrate production, which may be attributed to methanogens in feces. Thus, these observations highlight the multiple harmful impacts of antibiotics on the intestinal health of calves and the potential production of greenhouse gases by calves.

Species utilizing the same resources often fail to coexist for extended periods of time. Such competitive exclusion mechanisms potentially underly microbiome dynamics, causing breakdowns of communities composed of species with similar genetic backgrounds of resource utilization. Although genes responsible for competitive exclusion among a small number of species have been investigated in pioneering studies, it remains a major challenge to integrate genomics and ecology for understanding stable coexistence in species-rich communities. Here, we examine whether community-scale analyses of functional gene redundancy can provide a useful platform for interpreting and predicting collapse of bacterial communities. Through 110-day time-series of experimental microbiome dynamics, we analyzed the metagenome-assembled genomes of co-occurring bacterial species. We then inferred ecological niche space based on the multivariate analysis of the genome compositions. The analysis allowed us to evaluate potential shifts in the level of niche overlap between species through time. We hypothesized that community-scale pressure of competitive exclusion could be evaluated by quantifying overlap of genetically determined resource-use profiles (metabolic pathway profiles) among coexisting species. We found that the degree of community compositional changes observed in the experimental microbiome was correlated with the magnitude of gene-repertoire overlaps among bacterial species, although the causation between the two variables deserves future extensive research. The metagenome-based analysis of genetic potential for competitive exclusion will help us forecast major events in microbiome dynamics such as sudden community collapse (i.e., dysbiosis).

Abstract Background Microbiome dynamics are both crucial indicators and potential drivers of human health, agricultural output, and industrial bio-applications. However, predicting microbiome dynamics is notoriously difficult because communities often show abrupt structural changes, such as “dysbiosis” in human microbiomes. Methods We integrated theoretical frameworks and empirical analyses with the aim of anticipating drastic shifts of microbial communities. We monitored 48 experimental microbiomes for 110 days and observed that various community-level events, including collapse and gradual compositional changes, occurred according to a defined set of environmental conditions. We analyzed the time-series data based on statistical physics and non-linear mechanics to describe the characteristics of the microbiome dynamics and to examine the predictability of major shifts in microbial community structure. Results We confirmed that the abrupt community changes observed through the time-series could be described as shifts between “alternative stable states“ or dynamics around complex attractors. Furthermore, collapses of microbiome structure were successfully anticipated by means of the diagnostic threshold defined with the “energy landscape” analysis of statistical physics or that of a stability index of nonlinear mechanics. Conclusions The results indicate that abrupt microbiome events in complex microbial communities can be forecasted by extending classic ecological concepts to the scale of species-rich microbial systems. Video Abstract

Abstract Background In aquatic ecosystems, the health and performance of fish depend greatly on the dynamics of microbial community structure in the background environment. Nonetheless, finding microbes with profound impacts on fish’s performance out of thousands of candidate species remains a major challenge. Methods We examined whether time-series analyses of microbial population dynamics could illuminate core components and structure of fish-associated microbiomes in the background (environmental) water. By targeting eel-aquaculture-tank microbiomes as model systems, we reconstructed the population dynamics of the 9605 bacterial and 303 archaeal species/strains across 128 days. Results Due to the remarkable increase/decrease of constituent microbial population densities, the taxonomic compositions of the microbiome changed drastically through time. We then found that some specific microbial taxa showed a positive relationship with eels’ activity levels even after excluding confounding effects of environmental parameters (pH and dissolved oxygen level) on population dynamics. In particular, a vitamin-B12-producing bacteria, Cetobacterium somerae, consistently showed strong positive associations with eels’ activity levels across the replicate time series of the five aquaculture tanks analyzed. Network theoretical and metabolic modeling analyses further suggested that the highlighted bacterium and some other closely-associated bacteria formed “core microbiomes” with potentially positive impacts on eels. Conclusions Overall, these results suggest that the integration of microbiology, ecological theory, and network science allows us to explore core species and interactions embedded within complex dynamics of fish-associated microbiomes. Video Abstract

Abstract Glioblastoma is characterized by a strong self-renewal potential and poor differentiated state. We have reported previously that the (pro)renin receptor [(P)RR] is a potential target for glioma therapy by silencing the (P)RR gene. Here, we have examined the effects of a monoclonal antibody against (P)RR on gliomagenesis. Human glioma cell lines (U251MG and U87MG) and a glioma stem cell line (MGG23) were used for the in vitro study. The expressions of the Wnt/β-catenin signaling pathway (Wnt signaling pathway) components and stemness markers were measured by Western blotting. The effects of the (P)RR antibody on cell proliferation, sphere formation, apoptosis and migration were also examined. Subcutaneous xenografts were also examined in nude mice. Treatment with the (P)RR antibody reduced expression of Wnt signaling pathway components and stemness markers. Furthermore, the (P)RR antibody reduced cell proliferation and decreased sphere formation significantly. The treatment also suppressed migration and induced apoptosis. In a subcutaneous xenograft model, systemic administration of the (P)RR antibody reduced tumor volume significantly. These data show that treatment with the (P)RR antibody is a potential therapeutic strategy for treating glioblastoma.

Abstract Microbiota are a major component of agroecosystems. Root microbiota, which inhabit the inside and surface of plant roots, play a significant role in plant growth and health. As next-generation sequencing technology allows the capture of microbial profiles without culturing the microbes, profiling of plant microbiota has become a staple tool in plant science and agriculture. Here, we have increased sample handling efficiency in a two-step PCR amplification protocol for 16S rRNA gene sequencing of plant root microbiota, improving DNA extraction using AMPure XP magnetic beads and PCR purification using exonuclease. These modifications reduce sample handling and capture microbial diversity comparable to that obtained by the manual method. We found a buffer with AMPure XP magnetic beads enabled efficient extraction of microbial DNA directly from plant roots. We also demonstrated that purification using exonuclease before the second PCR step enabled the capture of higher degrees of microbial diversity, thus allowing for the detection of minor bacteria compared with the purification using magnetic beads in this step. In addition, our method generated comparable microbiome profile data in plant roots and soils to that of using common commercially available DNA extraction kits, such as DNeasy PowerSoil Pro Kit and FastDNA SPIN Kit for Soil. Our method offers a simple and high-throughput option for maintaining the quality of plant root microbial community profiling.

The rapid growth in the IoT network comes with a huge security threat. Network scanning is considered necessary to identify vulnerable IoT devices connected to IP networks. However, most existing network scanning tools or system do not consider the burden of scan packet traffic on the network, especially in the IoT network where resources are limited. It is necessary to know the status of the communication environment and the reason why network scanning failed. Therefore, this paper proposes a multimodel-based approach which can be utilized to estimate the cause of failure/delay of network scanning over wireless networks where a scan packet or its response may sometimes be dropped or delayed. Specifically, the factors that cause network scanning failure/delay were identified and categorized. Then, using a machine learning algorithm, we introduced a multimodel linear discriminant analysis (MM-LDA) to estimate the cause of scan failure/delay based on the results of network scanning. In addition, a one-to-many model and a training data filtering technique were adopted to ensure that the estimation error was drastically reduced. The goal of our proposed method was to correctly estimate the causes of scan failure/delay in IP-connected devices. The performance of the proposed method was evaluated using computer simulation assuming a cellular (LTE) network as the targeted IoT wireless network and using LTE-connected devices as the targeted IoT devices. The proposed MM-LDA correctly estimates the cause of failure/delay of the network scan at an average probability of 98% in various scenarios. In comparison to other conventional machine learning classifiers, the proposed MM-LDA outperforms various classification methods in the estimation of the cause of scan failure/delay.

Abstract In this paper we study various dynamical aspects of the AdS/BCFT correspondence in higher dimensions. We study properties of holographic stress energy tensor by analyzing the metric perturbation in the gravity dual. We also calculate the stress energy tensor for a locally excited state on a half plane in a free scalar CFT. Both of them satisfy a reflective boundary condition that is expected for any BCFTs. We also study the behavior of the scalar field perturbation in the AdS/BCFT setup and show that they also show complete reflections. Moreover, we find that the entanglement entropy of a BCFT computed from the AdS/BCFT matched with that calculated from the Island formula, which supports the Island/BCFT correspondence in higher dimensions. Finally we show how we can calculate one point functions in a BCFT in our gravity dual.

Abstract In this paper, we introduce a “partially disorder-averaged” SYK model. This model has a real parameter that smoothly interpolates between the ordinary totally disorder-averaged SYK model and the totally fixed-coupling model. For the large N effective description, in addition to the usual bi-local collective fields, we also introduce a new additional set of local collective fields. These local fields can be understood as “half” of the bi-local collective fields, and in the totally fixed-coupling limit, they represent the “half-wormholes” which were found in recent studies. We find that the large N saddles of these local fields vanish in the total-disorder-averaged limit, while they develop nontrivial profiles as we gradually fix the coupling constants. We argue that the bulk picture of these local collective fields represents a correlation between a spacetime brane and the asymptotic AdS boundary. This illuminates how the half-wormhole saddles emerge in the SYK model with fixed couplings.

Facilitative interactions between microbial species are ubiquitous in various types of ecosystems on the Earth. Therefore, inferring how entangled webs of interspecific interactions shift through time in microbial ecosystems is an essential step for understanding ecological processes driving microbiome dynamics. By compiling shotgun metagenomic sequencing data of an experimental microbial community, we examined how the architectural features of facilitative interaction networks could change through time. A metabolic modeling approach for estimating dependence between microbial genomes (species) allowed us to infer the network structure of potential facilitative interactions at 13 time points through the 110-day monitoring of experimental microbiomes. We then found that positive feedback loops, which were theoretically predicted to promote cascade breakdown of ecological communities, existed within the inferred networks of metabolic interactions prior to the drastic community-compositional shift observed in the microbiome time-series. We further applied “directed-graph” analyses to pinpoint potential keystone species located at the “upper stream” positions of such feedback loops. These analyses on facilitative interactions will help us understand key mechanisms causing catastrophic shifts in microbial community structure.

Abstract By combining the AdS/BCFT correspondence and the brane world holography, we expect an equivalence relation between a boundary conformal field theory (BCFT) and a gravitational system coupled to a CFT. However, it still remains unclear how the boundary condition of the BCFT is translated in the gravitational system. We examine this duality relation in a two-dimensional setup by looking at the computation of entanglement entropy and energy flux conservation. We also identify the two-dimensional gravity which is dual to the boundary dynamics of a BCFT. Moreover, we show that by considering a gravity solution with scalar fields turned on, we can reproduce one point functions correctly in the AdS/BCFT.

Abstract In this paper we study a connection between Jackiw-Teitelboim (JT) gravity on two-dimensional anti de-Sitter spaces and a semiclassical limit of c < 1 two-dimensional string theory. The world-sheet theory of the latter consists of a space-like Liouville CFT coupled to a non-rational CFT defined by a time-like Liouville CFT. We show that their actions, disk partition functions and annulus amplitudes perfectly agree with each other, where the presence of boundary terms plays a crucial role. We also reproduce the boundary Schwarzian theory from the Liouville theory description. Then, we identify a matrix model dual of our two-dimensional string theory with a specific time-dependent background in c = 1 matrix quantum mechanics. Finally, we also explain the corresponding relation for the two-dimensional de-Sitter JT gravity.

Histophilus somni, a member of the Pasteurellaceae family, causes various diseases, including thrombotic meningoencephalitis and respiratory diseases. Here, 166 isolates recovered from Japanese cattle with various diseases between the late 1970s and the 2010s were subjected to susceptibility testing against 14 antimicrobials (ampicillin, amoxicillin, cefazolin, ceftiofur, kanamycin, streptomycin, nalidixic acid, enrofloxacin, danofloxacin, florfenicol, erythromycin, tylosin, oxytetracycline, and fosfomycin). The proportions of antimicrobial-resistant/intermediate isolates were low in the total isolates, with resistance rates ranging from 0% for ceftiofur and florfenicol to 13.2% for ampicillin. However, relatively high minimum inhibitory concentrations (MICs) and resistance/intermediate rates were observed in the isolates from cattle with respiratory diseases; i.e., 21/53 isolates (39.6%) showed resistance or intermediate to one or more antimicrobials for treatment of respiratory diseases, and the resistance/intermediate rates to oxytetracycline, kanamycin, ampicillin, amoxicillin, nalidixic acid, and danofloxacin were 28.3, 24.5, 24.5, 13.2, 1.9, and 1.9%, respectively. Isolates with high MICs tended to possess antimicrobial resistance genes, which may confer antimicrobial resistance phenotypes. In particular, all isolates with MICs of ampicillin/amoxicillin, kanamycin, and oxytetracycline ≥2 μg/mL, ≥512 μg/mL, and ≥4 μg/mL possessed blaROB − 1, aphA-1, and tetH/tetR, respectively, whereas isolates whose MICs were lower than the above-mentioned values did not possess these resistance genes. These results suggest that the resistance genes detected in this study are primarily responsible for the reduced susceptibility of H. somni strains to these antimicrobials. As integrative and conjugative element (ICEs)-associated genes were detected only in genetically related isolates possessing antimicrobial resistance genes, ICEs may play an important role in the spread of resistance genes in some genetic groups of H. somni strains.

Abstract Background Tumor hypoxia and glycolysis have been recognized as determinant factors characterizing tumor aggressiveness in malignant gliomas. To clarify in vivo hypoxia and glucose metabolism in relation to isocitrate dehydrogenase (IDH) mutation and chromosome 1p and 19q (1p/19q) codeletion status, we retrospectively analyzed hypoxia as assessed by positron emission tomography (PET) with [18F]-fluoromisonidazole (FMISO) and glucose metabolism as assessed by PET with [18F]-fluoro-2-deoxy-d-glucose (FDG) in newly diagnosed malignant gliomas. Methods In total, 87 patients with newly diagnosed supratentorial malignant (WHO grade III and IV) gliomas were enrolled in this study. They underwent PET studies with FMISO and FDG before surgery. The molecular features and histopathological diagnoses based on the 2016 WHO classification were determined using surgical specimens. Maximal tumor-to-normal ratio (TNR) was calculated for FDG PET, and maximal tumor-to-blood SUV ratio (TBR) was calculated for FMISO PET. The PET uptake values in relation to IDH mutation and 1p/19q codeletion status were statistically analyzed. Results In all tumors and malignant astrocytomas, the median FMISO TBR in IDH-wildtype tumors was significantly higher than that in IDH-mutant tumors (P

Abstract We study the theory of Jackiw-Teitelboim gravity with generalized dilaton potential on Euclidean two-dimensional negatively curved backgrounds. The effect of the generalized dilaton potential is to induce a conical defect on the two-dimensional manifold. We show that this theory can be written as the ordinary quantum mechanics of a charged particle on a hyperbolic disk in the presence of a constant background magnetic field plus a pure gauge Aharonov-Bohm field. This picture allows us to exactly calculate the wavefunctions and propagators of the corresponding gravitational dynamics. With this method we are able to reproduce the gravitational density of states as well as compute the Réyni and entanglement entropies for the Hartle-Hawking state. While we reproduce the classical entropy at high temperature, we also find an extra topological contribution that becomes dominant at low temperatures. We then show how the presence of defects modify correlation functions, including the out-of-time-ordered correlation, and decrease the Lyapunov exponent. This is achieved two ways: by directly quantizing the boundary Schwarzian theory and by dimensionally reducing SL(2, ℤ) black holes.