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Abstract Natural gas hydrate is a promising unconventional natural gas source due to its high energy density and huge global reserves. During exploitation, the drilling fluid may invade the hydrate formation and induce hydrate decomposition, causing reservoir damage. Herein, a novel reservoir protectant made by bio-degradable temporary plugging material (BDTPM) was developed in the form of polymer-ceramic composite microcapsules. As an additive to the drilling fluid, the BDTPM can minimize drilling fluid intrusion by plugging the reservoir during drilling and afterwards maximize permeability recovery by degrading the material. The particle size distribution was in the range of 1–130 μm. The optimal mass ratio between modified ceramic particles, ethyl cellulose and epoxy resin was found to be 4:2:1. The plugging rate was 100% when ethyl cellulose and epoxy resin were mixed to coat the ceramic particles to form BDTPM, and the plugging performance was the best. At a temperature close to the typical hydrate reservoir environment (5 °C), 0.02 wt% low-temperature complex enzyme can degrade BDTPM, and the permeability recovery rate is 64.66%. The efficient reservoir protectant developed in this work could play an important role in the successful drilling of natural gas hydrate reservoirs.

Abstract Background Acute pulmonary thromboembolism (PTE) is a common cardiovascular disease and recognizing low prognosis risk patients with PTE accurately is significant for clinical treatment. This study evaluated the value of federated learning (FL) technology in PTE prognosis risk assessment while ensuring the security of clinical data. Methods A retrospective dataset consisted of PTE patients from 12 hospitals were collected, and 19 physical indicators of patients were included to train the FL-based prognosis assessment model to predict the 30-day death event. Firstly, multiple machine learning methods based on FL were compared to choose the superior model. And then performance of models trained on the independent (IID) and non-independent identical distributed(Non-IID) datasets was calculated and they were tested further on Real-world data. Besides, the optimal model was compared with pulmonary embolism severity index (PESI), simplified PESI (sPESI), Peking Union Medical College Hospital (PUMCH). Results The area under the receiver operating characteristic curve (AUC) of logistic regression(0.842) outperformed convolutional neural network (0.819) and multi layer perceptron (0.784). Under IID, AUC of model trained using FL(Fed) on the training, validation and test sets was 0.852 ± 0.002, 0.867 ± 0.012 and 0.829 ± 0.004. Under Real-world, AUC of Fed was 0.855 ± 0.005, 0.882 ± 0.003 and 0.835 ± 0.005. Under IID and Real-world, AUC of Fed surpassed centralization model(NonFed) (0.847 ± 0.001, 0.841 ± 0.001 and 0.811 ± 0.001). Under Non-IID, although AUC of Fed (0.846 ± 0.047) outperformed NonFed (0.841 ± 0.001) on validation set, it (0.821 ± 0.016 and 0.799 ± 0.031) slightly lagged behind NonFed (0.847 ± 0.001 and 0.811 ± 0.001) on the training and test sets. In practice, AUC of Fed (0.853, 0.884 and 0.842) outshone PESI (0.812, 0.789 and 0.791), sPESI (0.817, 0.770 and 0.786) and PUMCH(0.848, 0.814 and 0.832) on the training, validation and test sets. Additionally, Fed (0.842) exhibited higher AUC values across test sets compared to those trained directly on the clients (0.758, 0.801, 0.783, 0.741, 0.788). Conclusions In this study, the FL based machine learning model demonstrated commendable efficacy on PTE prognostic risk prediction, rendering it well-suited for deployment in hospitals.

Internet Gaming Disorder (IGD) is a behavioural addiction characterised by excessive exposure to addictive stimuli, resulting in reduced sensitivity of the brain's reward system towards everyday rewards. Online game addiction is prevalent among adolescents; however, it remains unclear if there are variations in reward processing patterns among adolescents with online game addiction.We compared differences in sensitivity to two types of rewards between patients with IGD and patients with Recreational Game Use (RGU) using the Monetary Incentive Delay (MID) paradigm and the Social Incentive Delay (SID) paradigm (Experiment 1). Additionally, we used a mixed reward latency paradigm, including both monetary and social rewards, to further explore the processing characteristics of IGD towards a mixture of these two rewards (Experiment 2).There were significant differences in the sensitivity of IGD and RGU to monetary and social rewards. Adolescents with IGD had significantly shorter reaction times to the four mixed rewards compared to RGU, while no significant differences were found between groups regarding sensitivity to specific individual rewards. However, the simultaneous presence of two rewards affected the processing speed and preference of adolescents with IGD.The reward processing characteristics observed in adolescents with online gaming disorder show specificity concerning the type and presentation of rewards, providing a theoretical foundation for diagnosing and treating adolescent online gaming addiction.

Abstract Hemoptysis is a frequently encountered manifestation in cases of acute pulmonary thromboembolism (PTE), significantly impacting clinical decision‐making. Despite its clinical relevance, studies focusing on patients with acute PTE and hemoptysis are notably scarce. In this retrospective study, we examined data from hospitalized patients with acute PTE at Peking Union Medical College Hospital (PUMCH) between January 2012 and October 2020. Among the 896 patients analyzed, 105 (11.7%) presented with hemoptysis. Patients with hemoptysis were younger, had higher RRs, and frequently reported chest pain, predominantly showing a negative sPESI score. A significant association with autoimmune diseases was observed (39.0% vs. 16.1%; p

Constructing high-precision subsidence basins is of paramount importance for mining subsidence monitoring. Traditional unmanned aerial vehicle (UAV) photogrammetry techniques typically construct subsidence basins by directly differencing digital elevation models (DEMs) from different monitoring periods. However, this method often neglects the influence of horizontal displacement on the accuracy of the subsidence basin. Taking a mining area in Ordos, Inner Mongolia, as an example, this study employed the normalized cross-correlation (NCC) matching algorithm to extract horizontal displacement information between two epochs of a digital orthophoto map (DOM) and subsequently corrected the horizontal position of the second-epoch DEM. This ensured that the planar positions of ground feature points remained consistent in the DEM before and after subsidence. Based on this, the vertical displacement in the subsidence area (the subsidence basin) was obtained via DEM differencing, and the parameters of the post-correction subsidence basin were inverted using the probability integral method (PIM). The experimental results indicate that (1) the horizontal displacement was influenced by the gully topography, causing the displacement within the working face to be segmented on both sides of the gully; (2) the influence of the terrain on the subsidence basin was significantly reduced after correction; (3) the post-correction surface subsidence curve was smoother than the pre-correction curve, with abrupt error effects markedly diminished; (4) the accuracy of the post-correction subsidence basin increased by 43.12% compared with the total station data; and (5) comparing the measured horizontal displacement curve with that derived using the probability integral method revealed that the horizontal displacement on the side of an old goaf adjacent to the newly excavated working face shifted toward the advancing direction of the new working face as mining progressed. This study provides a novel approach and insights for using low-cost UAVs to construct high-precision subsidence basins.

P2A (Power to ammonia) is one of the important ways of large-scale consumption of renewable energy, and one of the important technological routes for the chemical industry to realize low-carbon and clean development. The new off-grid energy power to hydrogen ammonia system lacks the support of large power grids due to the complex mathematical model of the system, more variables, and cumbersome constraints, which leads to model solving difficulties, and the production simulation results obtained suffer from the problems of low economic efficiency and high new energy power abandonment rate. To address the shortcomings of the algorithm, which converges slowly and easily falls into the local optimum when solving the model, this paper applies the Sparrow Search Algorithm (SSA) to the problem of economic optimization of new energy hydrogen synthesis and ammonia system scheduling. Firstly, based on the characteristics of wind and light, the operating characteristics of an electrolyzer, and the characteristics of an electrochemical energy storage device, and taking the economic optimization of the electric hydrogen synthesis ammonia system as the objective function, the economic optimization scheduling model of an off-grid new energy electric hydrogen synthesis ammonia system is established for 24 h production simulation. Secondly, the model is solved based on the sparrow search algorithm, and the speed of solving and the economic benefits of the system are analyzed in comparison with the conventional algorithm. Finally, the proposed off-grid wind-powered hydrogen synthesis ammonia system based on the sparrow search algorithm is verified to achieve the optimal operation of the 24 h production simulation through an actual example in the Daan area of Baicheng City, Jilin Province, which shows that the optimized system has better economic efficiency and the new energy is completely consumed, thus verifying the reasonableness and validity of the algorithm proposed in this article.

The growing demand for sodium-ion batteries (SIBs) in commercial applications has made it imperative to meet the commercial requirements. However, SIBs face significant challenges because of their poor cyclability and low reversible capacity compared with their rival lithium-ion batteries (LIBs). To address these challenges, various techniques, design strategies, surface engineering, and structural modifications have been developed to enhance the electrochemical performance of SIBs. This review focuses on recent developments in improving the electrochemical performance and cyclability of novel promising electrode materials for SIBs. We discuss several unique state-of-the-art research studies of the past five years that demonstrated excellent electrochemical performance through effective methodologies, surface modulations, and substitution of novel elements into the structure, and boosted the efficiency of the materials. Furthermore, we propose that it is important to adopt a nuanced approach when designing SIBs. Rather than copying the designs and methods used for LIBs, ideas should be absorbed from them and approaches should be tailored to meet the specific requirements of SIBs. This will enable the development of SIBs that are optimized for their intended applications and will avoid the challenges that have hindered the commercial success of earlier attempts at constructing SIBs. Thus, the key to creating high-performance SIBs is to draw inspiration from the best practices used in LIBs, while simultaneously innovating and developing new approaches tailored to the unique characteristics of SIBs.

Thermoresponsive polymer gels are a type of intelligent material that can react to changes in temperature. These materials possess excellent innovative properties and find use in various fields. This paper systematically analyzes the methods for testing and regulating phase transition temperatures of thermo-responsive polymer gels based on their response mechanism. The report thoroughly introduces the latest research on thermo-responsive polymer gels in oil and gas extraction, discussing their advantages and challenges across various environments. Additionally, it elucidates how the application limitations of high-temperature and high-salt conditions can be resolved through process optimization and material innovation, ultimately broadening the scope of application of thermo-responsive polymer gels in oil and gas extraction. The article discusses the technological development and potential applications of thermo-responsive polymer gels in oil-based drilling fluids. This analysis aims to offer researchers in the oil and gas industry detailed insights into future possibilities for thermo-responsive polymer gels and to provide helpful guidance for their practical use in oil-based drilling fluids.

Surveillance of the fleas and flea-borne pathogens infecting cats is important for both human and animal health. Multiple zoonotic Bartonella and Rickettsia species are known to infect the most common flea infesting cats and dogs worldwide: Ctenocephalides felis, the cat flea. The ability of other flea species to transmit pathogens is relatively unexplored. We aimed to determine cat host and flea factors independently associated with flea Bartonella and Rickettsia infection. We also assessed flea and cat infection by flea-host pair and location. To accomplish these aims, we performed qPCR for the detection of Bartonella, hemotropic Mycoplasma, Rickettsia, and Wolbachia DNA using paired cat and flea samples obtained from free-roaming cats presenting for spay or neuter across four locations in the United States. A logistic regression model was employed to identify the effect of cat (sex, body weight, geographic location, and Bartonella, hemotropic Mycoplasma, and Rickettsia spp., infection) and flea (clade and Rickettsia and Wolbachia infection) factors on C. felis Bartonella clarridgeiae infection. From 189 free roaming cats, we collected 84 fleas: Ctenocephalides felis (78/84), Cediopsylla simplex (4/84), Orchopeas howardi (1/84), and Nosopsyllus fasciatus (1/84). Ctenocephalides felis were phylogenetically assigned to Clades 1, 4, and 6 by cox1 gene amplification. Rickettsia asembonensis (52/84) and B. clarridgeiae (16/84) were the most common pathogenic bacteria detected in fleas. Our model identified host cat sex and weight as independently associated with B. clarridgeiae infection in fleas. Rickettsia asembonensis (52/84), Rickettsia felis (7/84) and Bartonella henselae (7/84) were detected in specific clades: R. felis was detected only in Clades 1 and 6 while B. henselae and R. asembonensis were detected only in Clade 4. Wolbachia spp., also displayed clade specificity with strains other than Wolbachia wCfeT only infecting fleas from Clade 6. There was poor flea and host agreement for Bartonella spp., infection; however, there was agreement in the Bartonella species detected in cats and fleas by geographic location. These findings reinforce the importance of considering reservoir host attributes and vector phylogenetic diversity in epidemiological studies of flea-borne pathogens. Widespread sampling is necessary to identify the factors driving flea-borne pathogen presence and transmission.

Abstract Background Coronavirus disease 2019 (COVID-19) is an emerging infectious disease, which has caused numerous deaths and health problems worldwide. This study aims to examine the effects of airborne particulate matter (PM) pollution and population mobility on COVID-19 across China. Methods We obtained daily confirmed cases of COVID-19, air particulate matter (PM2.5, PM10), weather parameters such as ambient temperature (AT) and absolute humidity (AH), and population mobility scale index (MSI) in 63 cities of China on a daily basis (excluding Wuhan) from January 01 to March 02, 2020. Then, the Generalized additive models (GAM) with a quasi-Poisson distribution were fitted to estimate the effects of PM10, PM2.5 and MSI on daily confirmed COVID-19 cases. Results We found each 1 unit increase in daily MSI was significantly positively associated with daily confirmed cases of COVID-19 in all lag days and the strongest estimated RR (1.21, 95% CIs:1.14 ~ 1.28) was observed at lag 014. In PM analysis, we found each 10 μg/m3 increase in the concentration of PM10 and PM2.5 was positively associated with the confirmed cases of COVID-19, and the estimated strongest RRs (both at lag 7) were 1.05 (95% CIs: 1.04, 1.07) and 1.06 (95% CIs: 1.04, 1.07), respectively. A similar trend was also found in all cumulative lag periods (from lag 01 to lag 014). The strongest effects for both PM10 and PM2.5 were at lag 014, and the RRs of each 10 μg/m3 increase were 1.18 (95% CIs:1.14, 1.22) and 1.23 (95% CIs:1.18, 1.29), respectively. Conclusions Population mobility and airborne particulate matter may be associated with an increased risk of COVID-19 transmission.

Character segmentation plays an important role in optical character recognition (OCR). Due to the limitations of feature representation, traditional image analyzing based methods cannot well segment characters with connected or broken strokes, especially for the Chinese characters which usually have complex structures. To solve this issue, this paper proposes a novel segmentation model based on fully convolutional neural networks (FCN). The model first uses convolutional neural networks to extract spatial features, then shares them throughout the whole model. Two FCNs are used to extract character information to form a score map. Finally, character features are reused to adjust the accurate segmentation points in the score map. What's more, to strengthen the ability of feature representation, a novel compound character feature which can well describe the characters' outline is also proposed. The proposed method is validated on two datasets: GBSD and CASIA-HWDB-MT, against the methods proposed in the literature. Experimental results show that the proposed model outperforms state-of-the-art methods.

China has abundant shale gas resources with great potential, which may serve as a significant support for the development of a “low-carbon economy”. Domestic shale gas resources are buried deeply and difficult to exploit due to some prevalent issues, such as long horizontal sections, severe development of reservoir fractures, strong sensitivity to water, borehole instability, etc. Compared to water-based drilling fluids, oil-based drilling fluid exhibits better inhibition and good lubricity and is thus broadly used in shale gas drilling, but it is confronted with the challenge of removing the harmful solid phase. Selective chemical flocculation is one of the most effective methods of removing the harmful solid phase in oil-based drilling fluid. In this study, interactions between the flocculation gel for oil-based drilling fluid and clay minerals were investigated by molecular simulation, which revealed the molecular-scale selectivity of the flocculation gel for rock cuttings with negative charges. Calculations showed that the flocculation gel is highly effective for the flocculation of negatively charged cuttings, but it is ineffective for flocculating neutral cuttings. The flocculation gel is not very effective for cuttings with high hydrophilicity, and it is totally ineffective for flocculating cuttings with poor hydrophilicity. Within a limited concentration range, the flocculation effect can be enhanced by increasing the flocculation gel concentration. The performance of the flocculation gel declined at elevated temperatures.

The environmental repercussions of extensive carbon dioxide (CO2) emissions on the environment are crucial for policymakers and scholars. The repercussions of and connection between economic growth (ECG), tourism (TOUR), and foreign direct investment (FDI) on CO2 emission mitigation have been measured and argued from empirical and theoretical perspectives by scholars. Notwithstanding, the extant body of knowledge has failed to incorporate and investigate the function of governance in decarbonizing tourism activities and FDI from CO2 emissions to attain a healthy and quality environment in Africa. Hence, this current research investigates governance’s role in the reduction processes of CO2 emissions grounded in environmental Kuznets curve (EKC) conceptual assumptions for panel data spanning 2000 through 2020 for 27 African countries. This research utilized the Westerlund panel cointegration approach for the investigation of the cointegration of the selected variables. This study applied the Driscoll–Kraay regression approach for the long-term estimation. In addition, the dynamic ordinary least squares (DOLS) and the pooled mean group (PMG) were used for robustness checks. The findings of this research indicated that the governance (GOV) indicators employed have a statistically significant effect on the CO2 emission reduction. Besides, this study found that the appreciation of the income of the nations gives credence to the formation of the EKC theory and contributes to the decline in CO2 emissions within the selected African nations. The findings revealed that tourism, FDI, ECG, and GOV are positive and significant factors leading to increased CO2 emissions in Africa. Furthermore, the results showed that effective governance and control of FDI inflows and tourism activities can support decarbonization. These findings suggest the merits of governance in ensuring effective decarbonization policies of the environment, and policy suggestions are accordingly put forward.

Ocean gas hydrate is a potentially efficient and clean oil and gas alternative energy resource. Wells with complex structure, such as horizontal wells, can improve the extraction efficiency; however, drilling operations face challenges such as wellbore instability and reservoir damage due to the complex interaction between drilling fluids and hydrate reservoirs. This work presents a ceramsite temporary plugging microcapsule that uses ceramsite modified by 3-aminopropyltriethoxysilane as the core material and chitosan and sodium alginate as shell materials. It exhibits high strength during drilling and excellent plugging effects. After the action of bioenzymes, it can easily be dissolved, leading to high permeability post-drilling. The analysis and performance evaluation of ceramsite microcapsules show that their particle size is generally 40 µm, which can match the pore size of the hydrate reservoir depending on the number of encapsulation layers. Bioenzyme optimization at 15 °C yields the best permeability recovery of 74.5% for the low-temperature composite enzyme. As the temperature rises, the permeability recovery rate of ceramic microcapsules gradually increases and the difference in permeability recovery rate between 5 and 25 °C becomes more significant. With a longer degradation time, the permeability recovery rate of ceramsite microcapsules gradually enhances and the difference in permeability recovery rate becomes smaller after 12 h. The microcapsules exhibit a specific inhibitory effect on the decomposition of hydrates. Utilizing bioenzymeresponsive ceramsite microcapsules as temporary plugging materials can establish an "isolation barrier" around the wellbore, effectively sealing off the interaction between the wellbore and the gas hydrate reservoir during the drilling process. Re-opening the flow path around the well by bio-enzymatic unblocking at the end of drilling proves to be effective in solving the problem of balancing the stability of the well wall and protecting the reservoir. [ABSTRACT FROM AUTHOR]

Objective: The aim of the study is to estimate inpatient asthma hospital visit rates among impacted Texans in Public Health Region 6/5S during the year of and after Hurricane Harvey. Methods: Asthma inpatient hospitalization discharges were collected from the Texas Health Care Information Collection database (2016-2019). Results: Females (age-adjusted rates [AARs] = 4.8-5.0) and Black Texans (AARs = 5.0-8.1) experienced significantly higher AARs compared with males and White Texans during the year of and after Harvey. During the year of Hurricane Harvey, females were 1.49 times as likely to have an inpatient asthma visit compared with males, while Black Texans were 2.78 times as likely to have an inpatient asthma hospitalization compared with White Texans. Conclusions: Findings from this study may assist public health professionals and local officials to allocate future resources to the most impacted subgroups as well as establish effective processes to mitigate consequences. [ABSTRACT FROM AUTHOR]

Tumorigenesis and metastasis are highly dependent on the interactions between the tumor and the surrounding microenvironment. In 3D matrix, the fibrous structure of the extracellular matrix (ECM) undergoes dynamic remodeling during tumor progression. In particular, during the late stage of tumor development, the fibers become more aggregated and oriented. However, it remains unclear how cancer cells respond to the organizational change of ECM fibers and exhibit distinct morphology and behavior. Here, we used electrospinning technology to fabricate biomimetic ECM with distinct fiber arrangements, which mimic the structural characteristics of normal or tumor tissues and found that aligned and oriented nanofibers induce cytoskeletal rearrangement to promote directed migration of cancer cells. Mechanistically, caveolin-1(Cav-1)-expressing cancer cells grown on aligned fibers exhibit increased integrin β1 internalization and actin polymerization, which promoted stress fiber formation, focal adhesion dynamics and YAP activity, thereby accelerating the directional cell migration. In general, the linear fibrous structure of the ECM provides convenient tracks on which tumor cells can invade and migrate. Moreover, histological data from both mice and patients with tumors indicates that tumor tissue exhibits a greater abundance of isotropic ECM fibers compared to normal tissue. And Cav-1 downregulation can suppress cancer cells muscle invasion through the inhibition of YAP-dependent mechanotransduction. Taken together, our findings revealed the Cav-1 is indispensable for the cellular response to topological change of ECM, and that the Cav-1/YAP axis is an attractive target for inhibiting cancer cell directional migration which induced by linearization of ECM fibers.

Abstract Background Accurate segmentation of gastric tumors from CT scans provides useful image information for guiding the diagnosis and treatment of gastric cancer. However, automated gastric tumor segmentation from 3D CT images faces several challenges. The large variation of anisotropic spatial resolution limits the ability of 3D convolutional neural networks (CNNs) to learn features from different views. The background texture of gastric tumor is complex, and its size, shape and intensity distribution are highly variable, which makes it more difficult for deep learning methods to capture the boundary. In particular, while multi-center datasets increase sample size and representation ability, they suffer from inter-center heterogeneity. Methods In this study, we propose a new cross-center 3D tumor segmentation method named Hierarchical Class-Aware Domain Adaptive Network (HCA-DAN), which includes a new 3D neural network that efficiently bridges an Anisotropic neural network and a Transformer (AsTr) for extracting multi-scale context features from the CT images with anisotropic resolution, and a hierarchical class-aware domain alignment (HCADA) module for adaptively aligning multi-scale context features across two domains by integrating a class attention map with class-specific information. We evaluate the proposed method on an in-house CT image dataset collected from four medical centers and validate its segmentation performance in both in-center and cross-center test scenarios. Results Our baseline segmentation network (i.e., AsTr) achieves best results compared to other 3D segmentation models, with a mean dice similarity coefficient (DSC) of 59.26%, 55.97%, 48.83% and 67.28% in four in-center test tasks, and with a DSC of 56.42%, 55.94%, 46.54% and 60.62% in four cross-center test tasks. In addition, the proposed cross-center segmentation network (i.e., HCA-DAN) obtains excellent results compared to other unsupervised domain adaptation methods, with a DSC of 58.36%, 56.72%, 49.25%, and 62.20% in four cross-center test tasks. Conclusions Comprehensive experimental results demonstrate that the proposed method outperforms compared methods on this multi-center database and is promising for routine clinical workflows.

Abstract Actomyosin networks constrict cell area and junctions to alter cell and tissue shape. However, during cell expansion under mechanical stress, actomyosin networks are strengthened and polarized to relax stress. Thus, cells face a conflicting situation between the enhanced actomyosin contractile properties and the expansion behaviour of the cell or tissue. To address this paradoxical situation, we study late Drosophila oogenesis and reveal an unusual epithelial expansion wave behaviour. Mechanistically, Rac1 and Rho1 integrate basal pulsatile actomyosin networks with ruffles and focal adhesions to increase and then stabilize basal area of epithelial cells allowing their flattening and elongation. This epithelial expansion behaviour bridges cell changes to oocyte growth and extension, while oocyte growth in turn deforms the epithelium to drive cell spreading. Basal pulsatile actomyosin networks exhibit non-contractile mechanics, non-linear structures and F-actin/Myosin-II spatiotemporal signal separation, implicating unreported expanding properties. Biophysical modelling incorporating these expanding properties well simulates epithelial cell expansion waves. Our work thus highlights actomyosin expanding properties as a key mechanism driving tissue morphogenesis.

Surveillance of the fleas and flea-borne pathogens infecting cats is important for both human and animal health. Multiple zoonotic Bartonella and Rickettsia species are known to infect the most common flea infesting cats and dogs worldwide: Ctenocephalides felis, the cat flea. The ability of other flea species to transmit pathogens is relatively unexplored. We aimed to determine cat host and flea factors independently associated with flea Bartonella and Rickettsia infection. We also assessed flea and cat infection by flea-host pair and location. To accomplish these aims, we performed qPCR for the detection of Bartonella, hemotropic Mycoplasma, Rickettsia, and Wolbachia DNA using paired cat and flea samples obtained from free-roaming cats presenting for spay or neuter across four locations in the United States. A logistic regression model was employed to identify the effect of cat (sex, body weight, geographic location, and Bartonella, hemotropic Mycoplasma, and Rickettsia spp., infection) and flea (clade and Rickettsia and Wolbachia infection) factors on C. felis Bartonella clarridgeiae infection. From 189 free roaming cats, we collected 84 fleas: Ctenocephalides felis (78/84), Cediopsylla simplex (4/84), Orchopeas howardi (1/84), and Nosopsyllus fasciatus (1/84). Ctenocephalides felis were phylogenetically assigned to Clades 1, 4, and 6 by cox1 gene amplification. Rickettsia asembonensis (52/84) and B. clarridgeiae (16/84) were the most common pathogenic bacteria detected in fleas. Our model identified host cat sex and weight as independently associated with B. clarridgeiae infection in fleas. Rickettsia asembonensis (52/84), Rickettsia felis (7/84) and Bartonella henselae (7/84) were detected in specific clades: R. felis was detected only in Clades 1 and 6 while B. henselae and R. asembonensis were detected only in Clade 4. Wolbachia spp., also displayed clade specificity with strains other than Wolbachia wCfeT only infecting fleas from Clade 6. There was poor flea and host agreement for Bartonella spp., infection; however, there was agreement in the Bartonella species detected in cats and fleas by geographic location. These findings reinforce the importance of considering reservoir host attributes and vector phylogenetic diversity in epidemiological studies of fleaborne pathogens. Widespread sampling is necessary to identify the factors driving flea-borne pathogen presence and transmission. [ABSTRACT FROM AUTHOR]

Skeletal muscle aging in rats is a reduction in skeletal muscle mass caused by a decrease in the number or volume of skeletal muscle myofibers. Apoptosis has been recognized to play a key role in accelerating the process of skeletal muscle aging in rats. The thioredoxin (Trx) system is a widely expressed oxidoreductase system that controls the cellular reduction/oxidation state and has both potent anti-free radical damage and important pro-growth and apoptosis inhibitory functions. Previous studies have shown that exercise delays skeletal muscle aging. However, it is unclear whether exercise attenuates skeletal muscle aging via the Trx system. Therefore, the present study used the Trx system as an entry point to explore the effect of aerobic exercise to improve skeletal muscle aging in rats and its possible mechanisms, and to provide a theoretical basis for exercise to delay skeletal muscle aging in rats. It was shown that aerobic exercise in senescent rats resulted in increased gastrocnemius index, decreased body weight, increased endurance, decreased skeletal muscle cell apoptosis, increased activity and protein expression of the Trx system, and decreased expression of p38 and ASK1. Based on these findings, we conclude that 10 weeks of aerobic exercise may enhance the anti-apoptotic effect of Trx by up-regulating Trx and Trx reductase (TR) protein expression, which in turn increases Trx activity in rat skeletal muscle, and ultimately alleviates apoptosis in senescent skeletal muscle cells.