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Repair welding technology is widely used in the manufacturing and maintenance of rail transit equipment to repair welding defects. However, repair welding induces modifications in joint performance, and it is necessary to study the microstructure evolution behavior to reveal the reasons. In this study, the effects of multiple repair welding on the microstructure, mechanical, and fatigue properties of 06Cr19Ni10 stainless steel samples were studied. The surface texture and fracture morphology analyses of the samples were conducted by optical microscopy (OM), scanning electron microscopy (SEM), and its equipped backscattered electron diffraction (EBSD) technique. The mechanical and fatigue properties of the samples with different repair welding times were further obtained by hardness, tensile, and fatigue tests. The results show an increase in the grain size and the substructure content in the heat-affected zone (HAZ), and the austenite orientation is changed, attributable to multiple repair welding. Multiple heat inputs result in a significant increase in hardness from 165 HV to 185 HV, a noticeable decrease in tensile strength and elongation, and an upward trend in yield strength. Under the constant stress level, the heat input of multiple repair welding causes a decrease in the fatigue life and significantly reduces toughness in the instantaneous fracture zone of the secondary repair sample. [ABSTRACT FROM AUTHOR]

Pentatrichomonas hominis is a common intestinal parasitic protozoan that causes abdominal pain and diarrhea, and poses a zoonotic risk. Probiotics, known for enhancing immunity and pathogen resistance, hold promise in combating parasitic infections. This study aimed to evaluate two porcine-derived probiotics, Lactobacillus reuteri LR1 and Lactobacillus plantarum LP1, against P. hominis infections in pigs. Taxonomic identity was confirmed through 16 S rRNA gene sequencing, with L. reuteri LR1 belonging to L. reuteri species and L. plantarum LP1 belonging to L. plantarum species. Both probiotics exhibited robust in vitro growth performance. Co-culturing intestinal porcine epithelial cell line (IPEC-J2) with these probiotics significantly improved cell viability compared with the control group. Pre-incubation probiotics significantly enhanced the mRNA expression of anti-oxidative response genes in IPEC-J2 cells compared with the PHGD group, with L. reuteri LR1 and L. plantarum LP1 significantly up-regulating CuZn-SOD、CAT and Mn-SOD genes expression (p < 0.05). The anti-oxidative stress effect of L. reuteri LR1 was significantly better than that of L. plantarum LP1 (p < 0.05). Furthermore, pre-incubation with the probiotics alleviated the P. hominis-induced inflammatory response. L. reuteri LR1 and L. plantarum LP1 significantly down-regulated IL-6、IL-8 and TNF-α gene expression(p < 0.05) compared with the PHGD group. The probiotics also mitigated P. hominis-induced apoptosis. L. reuteri LR1 and L. plantarum LP1 significantly down-regulated Caspase3 and Bax gene expression (p < 0.05), significantly up-regulated Bcl-2 gene expression (p < 0.05) compared with the PHGD group. Among them, L. plantarum LP1 showed better anti-apoptotic effect. These findings highlight the probiotics for mitigating P. hominis infections in pigs. Their ability to enhance anti-oxidative responses, alleviate inflammation, and inhibit apoptosis holds promise for therapeutic applications. Simultaneously, probiotics can actively contribute to inhibiting trichomonal infections, offering a novel approach for preventing and treating diseases such as P. hominis. Further in vivo studies are required to validate these results and explore their potential in animal and human health. [ABSTRACT FROM AUTHOR]

Aging is a risk factor for human health and quality of life. Screening and development of novel supplements and medications to combat aging and delay the incidence of age-related diseases are of great significance. In this study, salidroside (SA), a primary natural small molecule from Rhodiola rosea, was investigated regarding its effects on life and healthspan and the underlying molecular mechanism(s) of anti-aging and antioxidation. Our results showed that SA effectively prolonged lifespan and exhibited anti-aging and antioxidative properties. Computer-assisted methods, label-free interaction analysis, and in vitro assays showed that SA directly bound heat shock protein 90 (HSP90). Furthermore, SA significantly inhibited the ATPase activity of HSP90, affecting the interaction between HSP90 and its interacting proteins and the expression of downstream genes to regulate lifespan and the oxidative stress response. Our findings provided new insights into the pharmacological properties of SA across multiple species and its potential as an anti-aging drug. [ABSTRACT FROM AUTHOR]

Body-centred cubic refractory multi-principal element alloys (MPEAs), with several refractory metal elements as constituents and featuring a yield strength greater than one gigapascal, are promising materials to meet the demands of aggressive structural applications1–6. Their low-to-no tensile ductility at room temperature, however, limits their processability and scaled-up application7–10. Here we present a HfNbTiVAl10 alloy that shows remarkable tensile ductility (roughly 20%) and ultrahigh yield strength (roughly 1,390 megapascals). Notably, these are among the best synergies compared with other related alloys. Such superb synergies derive from the addition of aluminium to the HfNbTiV alloy, resulting in a negative mixing enthalpy solid solution, which promotes strength and favours the formation of hierarchical chemical fluctuations (HCFs). The HCFs span many length scales, ranging from submicrometre to atomic scale, and create a high density of diffusive boundaries that act as effective barriers for dislocation motion. Consequently, versatile dislocation configurations are sequentially stimulated, enabling the alloy to accommodate plastic deformation while fostering substantial interactions that give rise to two unusual strain-hardening rate upturns. Thus, plastic instability is significantly delayed, which expands the plastic regime as ultralarge tensile ductility. This study provides valuable insights into achieving a synergistic combination of ultrahigh strength and large tensile ductility in MPEAs.A HfNbTiVAl10 alloy shows tensile ductility and ultrahigh yield strength from the addition of aluminium to a HfNbTiV alloy, resulting in a negative mixing enthalpy solid solution, which promotes strength and favours formation of hierarchical chemical fluctuations. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate and analyze the effect of different application sequences of CO2 fractional laser and triamcinolone acetonide injection on the application effect of hypertrophic scar in one operation. Patients with hypertrophic scars who received CO2 lattice laser combined with triamcinolone acetonide injection from January 2021 to December 2022 were retrospectively analyzed. According to the different initial operations, they were divided into CO2 FL-TA group and TA-CO2 FL group. The Vancouver Scar Scale score and scar thickness of the two groups before and after treatment were analyzed. The complications occurred in the two groups during the treatment period. The clinical efficacy of the two groups before and after the treatment was calculated. Before treatment, there was no difference in scar thickness and VSS score between the two groups (P > 0.05). After treatment, the above indexes in CO2 FL-TA group were significantly better than those in TA-CO2 FL group (P < 0.05); the incidence of adverse reactions in CO2 FL-TA group was 9.38%, which was significantly lower than that in TA-CO2 FL group (18.75%) (P < 0.05); the total effective rate of CO2 FL-TA group was 90.63%, which was significantly higher than that in TA-CO2 FL group (65.63%) (P < 0.05). In the process of combined CO2 fractional laser and triamcinolone acetonide injection in the treatment of hypertrophic scars, CO2 fractional laser treatment first, and then triamcinolone acetonide injection can reduce the number of treatments, reduce the incidence of adverse reactions, and achieve more satisfactory treatment effect. [ABSTRACT FROM AUTHOR]

Bio-degumming was gradually become more attracting strategy for obtaining of biomass fiber from bast of plant, which was considered as green and low-carbon approach compared with conventional chemical degumming. However, the current bio-degumming technology cannot meet the required effect and efficiency on a pilot scale. In this investigation, a novel strategy for improving bio-degumming was proposed by breaking of biomass recalcitrance in flax with clean pretreatment method. It is proved that biomass recalcitrance in bast fibers can be effectively broken by physical pretreatment, especially by cryogenic pretreatment. In process of cryogenic pretreatment, non-cellulose substance in flax was obviously decreased and the connection between cellulose and non-cellulose components of flax was evidently disrupted. This resulted in the increase of specific surface area of the bast fiber and the enhancing of binding sites for enzymes. As a result, bioavailability of flax was improved and the efficiency of bio-degumming can be increased with the breaking of biomass recalcitrance in flax. Thus, a clean strategy was provided by breaking of biomass recalcitrance in flax with cryogenic pretreatment for bio-degumming. [ABSTRACT FROM AUTHOR]

Pigeon farming for meat has developed into an important economic industry in most countries, especially in China. Trichomoniasis, caused by the protozoan parasite Trichomonas gallinae, is a worldwide disease in pigeons. However, studies of the prevalence and distribution of T. gallinae lineages in domestic pigeons in southern China are limited. In this study, a total of 636 pigeon throat swabs samples from four regions in Guangdong Province were screened for T. gallinae by in vitro culture assays and microscopy. The results revealed an overall prevalence of T. gallinae infection in southern China of 26.6% (169/636). There were significant differences in the infection rate of T. gallinae between the four regions (χ2 = 117.948, df = 4, P = 0.000), with up to 44.6% in the Pearl River Delta region. The infection rate of young pigeons was as high as 70.8%. The rDNA sequences (18S rRNA/ITS1-5.8S rRNA-ITS2) of 153 positive samples were amplified and sequenced. Results identified 58.2% (89/153) overall as ITS-A (18S-VI) (also known as ITS-OBT-Tg-1) and 41.8% (64/153) as ITS-B (18S-IV) (also known as ITS-OBT-Tg-2). Thus, ITS-A (18S-VI) was the dominant T. gallinae genotype in southern China, especially in young pigeon (97.0%, 32/33). In conclusion, a high prevalence of T. gallinae infection in domestic pigeons was identified in southern China, particularly in the Pearl River Delta region. The ITS-A (18S-VI) was the dominant genotype highly pathogenic, which may weaken the immune system of pigeons, and cause a negative impact on the development of the pigeon industry in China. [ABSTRACT FROM AUTHOR]

The growth of flexible sensors has always been challenging since the sensing behavior, mechanic performance and fatigue resistance remain to be improved. In this paper, a wearable pressure sensor with fast response and high sensitivity based on ionogel/textile is fabricated. The ionogel is a double-network (DN) structure composed of polydimethylacrylamide (PDMAAm) skeleton and silica particles, carrying ionic liquids (ILs), which serves as a piezoresistive device. By impregnating and polymerization with the ionogel-prepolymer solution, a conventional cotton knitted fabric is converted into a conductive and piezoresistive composite. The fabric serves as a ductile supporting matrix for the ionogel, supplementing the piezoresistive contribution of the brittle silica network. This ionogel/textile composite has a high sensitivity (S=86.90 kPa−1) and durability, continuously outputting stable electric signal during monitoring the motion states of different joints in human body. Through the impregnation-polymerization approach, the selected areas toward to the specific joints positions in clothing can be fabricated into piezoresistive devices. The incorporation of textile improves the stress loading and sensing behavior of the ionogel to work steadily under the sole of the foot for gait monitoring. This ionogel/textile device provides a potential formula of wearable sensors, stepping toward the burgeoning diversified-technologies assisted intelligence system. [ABSTRACT FROM AUTHOR]

Tent shielding is an effective and flexible method to provide inert protective atmosphere during wire arc additive manufacturing of titanium alloy. In this study, five deposited walls were fabricated by CMT-WAAM process with different oxygen levels in the tent shielding, and the influences of oxygen levels on the microstructure and mechanical properties were analyzed. The results showed that, the oscillated path provided enough time for the molten pool to absorb oxygen out of atmosphere. With the increase in oxygen level, the thickness of α-case with higher micro-hardness became larger, the amount of β phase gradually decreased, the ratio of length to width for α lamellar was increased, and the boundary α phase became coarser. The higher oxygen level in the tent shielding caused an increase in tensile strength and a decrease in elongation. An ultimate tensile strength higher than 900 MPa and an elongation higher than 6% could be obtained when the oxygen level in the tent was lower than 2000 ppm. [ABSTRACT FROM AUTHOR]

Hospitals in Canada are facing a crisis-level shortage of critical supplies and equipment during the COVID-19 pandemic. This motivates us to create predictive models that can use Canada COVID-19 data and pandemic-related factors to accurately forecast 5 quantities—three related to hospital resource utilization (i.e., the number of hospital beds, ICU beds, and ventilators that will be needed by COVID-19 patients) and two to the pandemic progress (i.e., the number of COVID-19 cases and COVID-19 deaths)—several weeks in advance. We developed a machine learning method that can use information (i.e., resource utilization, pandemic progress, population mobility, weather condition, and public policy) currently known about a region since March 2020, to learn multiple temporal convolutional network (TCN) models every week; each used for forecasting the weekly average of one of these 5 quantities in Canada (respectively, in six specific provinces) for each, in the next 1 (resp., 2,3,4) weeks. To validate the effectiveness of our method, we compared our method, versus other standard models, on the COVID-19 data and hospital resource data, on the tasks of predicting the 116 values (for Canada and its six most populated provinces), every week from Oct 2020 to July 2021, and the 20 values (only for Canada) for four specific times within 9 July to 31 Dec 2021. Experimental results show that our 4640 TCN models (each forecasting a regional target for a specific future time, on a specific date) can produce accurate 1,2,3,4-week forecasts of the utilization of every hospital resource and pandemic progress for each week from 2 Oct 2020 to 2 July 2021, as well as 80 TCN models for each of the four specified times within 9 July and 31 Dec 2021. Compared to other baseline and state-of-the-art predictive models, our TCN models yielded the best forecasts, with the lowest mean absolute percentage error (MAPE). Additional experiments, on the IHME COVID-19 data, demonstrate the effectiveness of our TCN models, in comparison with IHME forecasts. Each of our TCN models used a pre-defined set of features; we experimentally validate the effectiveness of these features by showing that these models perform better than other models that instead used other features. Overall, these experimental results demonstrate that our method can accurately forecast hospital resource utilization and pandemic progress for Canada and for each of the six provinces. [ABSTRACT FROM AUTHOR]

Since it emerged in December of 2019, COVID-19 has placed a huge burden on medical care in countries throughout the world, as it led to a huge number of hospitalizations and mortalities. Many medical centers were overloaded, as their intensive care units and auxiliary protection resources proved insufficient, which made the effective allocation of medical resources an urgent matter. This study describes learned survival prediction models that could help medical professionals make effective decisions regarding patient triage and resource allocation. We created multiple data subsets from a publicly available COVID-19 epidemiological dataset to evaluate the effectiveness of various combinations of covariates—age, sex, geographic location, and chronic disease status—in learning survival models (here, "Individual Survival Distributions"; ISDs) for hospital discharge and also for death events. We then supplemented our datasets with demographic and economic information to obtain potentially more accurate survival models. Our extensive experiments compared several ISD models, using various measures. These results show that the "gradient boosting Cox machine" algorithm outperformed the competing techniques, in terms of these performance evaluation metrics, for predicting both an individual's likelihood of hospital discharge and COVID-19 mortality. Our curated datasets and code base are available at our Github repository for reproducing the results reported in this paper and for supporting future research. [ABSTRACT FROM AUTHOR]

Glioma is the most common and fatal primary brain tumor in humans. Myosin binding protein H (MYBPH), which was first identified as an important myofibrillar constituent of vertebrate skeletal and cardiac muscles, reduces cell motility and metastasis. However, its role in gliomas remains unclear. We evaluated the expression of MYBPH in glioma using Gene Expression Profiling Interactive Analysis (http://gepia.cancer-pku.cn/) and Chinese Glioma Genome Atlas (https://www.cgga.org.cn/). The results showed that MYBPH was highly expressed in glioma tissues. Moreover, MYBPH expression was significantly associated with high tumor aggressiveness and poor outcomes in glioma patients. Mechanistically, the results suggested that MYBPH might promote tumor progression by improving tumor invasion and migration. Our results establish MYBPH as an important prognostic biomarker that could be considered a potential epigenetic and immunotherapeutic target for treatment. We showed that MYBPH is a novel biomarker that is variably expressed in glioblastoma (GBM). The association of high MYBPH expression with poor prognosis in newly diagnosed GBM patients and increased expression in recurrent GBM is indicative of its role in tumor aggressiveness. [ABSTRACT FROM AUTHOR]

As an acoustic metamaterial, Metal–organic frameworks (MOFs) can absorb sound energy abnormally. In this research, a thin and flexible acoustic material was prepared by growing MOF on the fabric. The successful growth of MIL-53(Fe) on the fiber surface was confirmed by SEM, FTIR, XRD and XPS. From the sound absorption and sound insulation test results of MIL-53(Fe)@fabric, the in-situ growth of MIL-53(Fe) greatly improves the sound absorption and sound insulation performance of the fabric, and gives the fabric an abnormal acoustic effect. From the calculation results of the theoretical model, the growth of the sub-wavelength scale MIL-53(Fe) significantly increases the flow resistance of the fabric, which is the root cause of the abnormal sound absorption of the material. It is worth noting that the sound transmission loss of the prepared flexible material doesn't follow the mass law and exhibits excellent sound insulation performance. This is not only related to the increase in the sound energy reflected by the fabric, but also to the abnormal sound absorption of MIL-53(Fe). Here, the sound insulation performance of MOFs@fabric is reported for the first time. This work promotes the research and application of MOFs in the field of acoustics, and provides a method and theoretical basis for the design and preparation of acoustic protection textiles. [ABSTRACT FROM AUTHOR]

Markov models are extensively used for categorical sequence clustering and classification due to their inherent ability to capture complex chronological dependencies hidden in sequential data. Existing Markov models are based on an implicit assumption that the probability of the next state depends on the preceding context/pattern which is consist of consecutive states. This restriction hampers the models since some patterns, disrupted by noise, may be not frequent enough in a consecutive form, but frequent in a sparse form, which can not make use of the information hidden in the sequential data. A sparse pattern corresponds to a pattern in which one or some of the state(s) between the first and last one in the pattern is/are replaced by wildcard(s) that can be matched by a subset of values in the state set. In this paper, we propose a new model that generalizes the conventional Markov approach making it capable of dealing with the sparse pattern and handling the length of the sparse patterns adaptively, i.e. allowing variable length pattern with variable wildcards. The model, named Dynamic order Markov model (DOMM), allows deriving a new similarity measure between a sequence and a set of sequences/cluster. DOMM builds a sparse pattern from sub-frequent patterns that contain significant statistical information veiled by the noise. To implement DOMM, we propose a sparse pattern detector (SPD) based on the probability suffix tree (PST) capable of discovering both sparse and consecutive patterns, and then we develop a divisive clustering algorithm, named DMSC, for Dynamic order Markov model for categorical sequence clustering. Experimental results on real-world datasets demonstrate the promising performance of the proposed model. [ABSTRACT FROM AUTHOR]

The poor compatibility between a Fe2O3 pigment and a blend of ultrahigh molecular weight polyethylene (UHMWPE)/polyolefin (PO) can result in low spinnability and poor mechanical properties of the resulting fiber. This study modifies the surface of a Fe2O3 pigment with a titanate coupling agent for dope dyeing melt-spun UHMWPE fiber. The effects of the coupling agent dose, reaction temperature and reaction time on the surface properties of the pigments are investigated. In addition, the characteristics of the UHMWPE blend and colored fibers (by dope dyeing with modified and unmodified Fe2O3 pigments) are compared. Notably, 3 wt.% coupling agent in regard to the pigments mass, a coupling agent to toluene mass ratio of 1:5, a reaction time of 30 min, and a reaction temperature of 80 °C achieve the optimal results, which are a 48.4 % lipophilic degree of the modified pigment, a zeta potential of 48.4 mV, and a contact angle of 144.3°. Moreover, SEM images and torque results of the blend melt show that the compatibility between the Fe2O3 pigment and UHMWPE/PO blend is significantly enhanced. With an increasing pigment content, the mechanical properties of the colored fibers decrease, and the K/S values of the colored fibers increase. [ABSTRACT FROM AUTHOR]

Revealing the atomistic mechanisms for the high-temperature mechanical behavior of materials is important for optimizing their properties for service at high-temperatures and their thermomechanical processing. However, due to materials microstructure's dynamic recovery and the absence of available in situ techniques, the high-temperature deformation behavior and atomistic mechanisms of materials are difficult to evaluate. Here, we report the development of a microelectromechanical systems-based thermomechanical testing apparatus that enables mechanical testing at temperatures reaching 1556 K inside a transmission electron microscope for in situ investigation with atomic-resolution. With this unique technique, we first uncovered that tungsten fractures at 973 K in a ductile manner via a strain-induced multi-step body-centered cubic (BCC)-to-face-centered cubic (FCC) transformation and dislocation activities within the strain-induced FCC phase. Both events reduce the stress concentration at the crack tip and retard crack propagation. Our research provides an approach for timely and atomic-resolved high-temperature mechanical investigation of materials at high-temperatures. High-temperature deformation of materials is challenging to evaluate. Here the authors develop a novel device that allows atomic resolved in situ high temperature mechanical tests inside a transmission electron microscope and reveal ductile fracture of a single crystal tungsten deformed at 973 K. [ABSTRACT FROM AUTHOR]

In recent years, teaching machines to ask meaningful and coherent questions has attracted considerable attention in natural language processing. Question generation has found wide applications in areas such as education (testing knowledge) and chatbots (enhancing interaction). Following previous studies on conversational question generation, we propose a pretrained, encoder–decoder model that can incorporate the semantic information from both passage and hidden conversation representations. We adopt BERT as the encoder to combine external text and dialogue history, and we design a multi-head attention-based decoder to incorporate the semantic information from both text and hidden dialogue representations into the decoding process, thereby generating coherent questions. Experiments with conversational question generation and document-grounded dialogue response generation tasks indicate that the proposed model is superior to baseline models in terms of both standard metrics and human evaluations. [ABSTRACT FROM AUTHOR]

Time-to-event prediction has been an important practical task for longitudinal studies in many fields such as manufacturing, medicine, and healthcare. While most of the conventional survival analysis approaches suffer from the presence of censored failures and statistically circumscribed assumptions, few attempts have been made to develop survival learning machines that explore the underlying relationship between repeated measures of covariates and failure-free survival probability. This requires a purely dynamic-data-driven prediction approach, free of survival models or statistical assumptions. To this end, we propose two real-time survival networks: a time-dependent survival neural network (TSNN) with a feed-forward architecture and a recurrent survival neural network (RSNN) incorporating long short-term memory units. The TSNN additively estimates a latent failure risk arising from the repeated measures and performs multiple binary classifications to generate prognostics of survival probability, while the RSNN with time-dependent input covariates implicitly estimates the relation between these covariates and the survival probability. We propose a novel survival learning criterion to train the neural networks by minimizing the censoring Kullback–Leibler divergence, which guarantees monotonicity of the resulting probability. Besides the failure-event AUC, C-index, and censoring Brier score, we redefine a survival time estimate to evaluate the performance of the competing models. Experiments on four datasets demonstrate the great promise of our approach in real applications. [ABSTRACT FROM AUTHOR]

The lowest-energy structures and low-lying isomers of double impurity atoms, Ga and Mn, doped Li ( n = 1-12) clusters have been systematically investigated using density functional theory. The trimetallic clusters show larger relative binding energies compared with the bare Li partners, indicating doping with Ga and Mn atoms could enhance the stabilities of Li clusters. The HOMO-LUMO gaps, the vertical ionization potentials and the vertical electron affinities have also been analyzed and compared with the pure lithium clusters. The magnetism calculations demonstrate that the magnetic moments of GaMnLi clusters show a tunable magnetic properties with the increasing number of Li atoms. [ABSTRACT FROM AUTHOR]

The presence of complex distributions of samples concealed in high-dimensional, massive sample-size data challenges all of the current classification methods for data mining. Samples within a class usually do not uniformly fill a certain (sub)space but are individually concentrated in certain regions of diverse feature subspaces, revealing the class dispersion. Current classifiers applied to such complex data inherently suffer from either high complexity or weak classification ability, due to the imbalance between flexibility and generalization ability of the discriminant functions used by these classifiers. To address this concern, we propose a novel representation of discriminant functions in Bayesian inference, which allows multiple Bayesian decision boundaries per class, each in its individual subspace. For this purpose, we design a learning algorithm that incorporates the naive Bayes and feature weighting approaches into structural risk minimization to learn multiple Bayesian discriminant functions for each class, thus combining the simplicity and effectiveness of naive Bayes and the benefits of feature weighting in handling high-dimensional data. The proposed learning scheme affords a recursive algorithm for exploring class density distribution for Bayesian estimation, and an automated approach for selecting powerful discriminant functions while keeping the complexity of the classifier low. Experimental results on real-world data characterized by millions of samples and features demonstrate the promising performance of our approach. [ABSTRACT FROM AUTHOR]

Hexokinase (HK) is one of the key enzymes in the glycolytic pathway that catalyzes the phosphorylation of glucose. In the present study, we cloned the HK gene from the coccidian Eimeria tenella ( EtHK), expressed EtHK as a His-tagged fusion protein, and characterized its primary biochemical features. Mutagenesis confirmed that residues S159, N216, and D217 are essential or important to the EtHK catalytic activity. EtHK exhibited high affinity for d-glucose ( Km = 0.67 to 0.79 mM), but was also able to utilize 2-deoxy- d-glucose ( Km = 5.66 mM), d-fructose ( Km = 13.76 mM), and d-mannose ( Km = 25.41 mM). We also observed that quercetin and mangiferin could inhibit the EtHK enzyme activity (IC values = 6.52 and 85.82 μM, respectively). Among the two inhibitors, mangiferin also inhibited the growth of E. tenella in vitro (MIC = 0.12 μM). These observations suggest that EtHK may be explored as potential drug target, and mangiferin and its analogs may be explored for developing anti-coccidial therapeutics. [ABSTRACT FROM AUTHOR]

In this article, the Ni-46.1Al-7.8Mo (at.%) alloy was directionally solidified at different growth rates ranging from 15 μm/s to 1000 μm/s under a constant temperature gradient (334 K/cm). The dependence of microstructural length scales on the growth rate was investigated. The results show that, with the growth rate increasing, the primary dendritic arm spacings (PDAS) and secondary dendritic arm spacings (SDAS) decreased. There exists a large distribution range in PDAS under directional solidification conditions at a constant temperature gradient. The average PDAS and SDAS as a function of growth rate can be given as λ = 848.8967 V and λ = 64.2196 V, respectively. In addition, a comparison of our results with the current theoretical models and previous experimental results has also been made. [ABSTRACT FROM AUTHOR]

A series of stoichiometric NiAl alloys contain four different concentrations of Mo (7.8, 9, 13, 16 at.%) were directionally solidified in the Bridgman-type directional solidification furnace for four different growth rates ( V = 1.5-6 μm/s) in a constant temperature gradient ( G = 334 K/cm). the microstructures of the alloys produced with the different growth rates at a constant temperature gradient tended to form fully fibrous structures. The fiber spacings λ were measured from transverse section of the specimen. The variation of λ with respect to growth rate ( V) and composition ( C) were determined by linear regression analysis. It has been found that λ decreases with the increasing values of V and C. The results are compared with theoretical models and previous experimental published data. [ABSTRACT FROM AUTHOR]

There is much interest in developing synthetic analogues of biological membrane channels with high efficiency and exquisite selectivity for transporting ions and molecules. Bottom-up and top-down methods can produce nanopores of a size comparable to that of endogenous protein channels, but replicating their affinity and transport properties remains challenging. In principle, carbon nanotubes (CNTs) should be an ideal membrane channel platform: they exhibit excellent transport properties and their narrow hydrophobic inner pores mimic structural motifs typical of biological channels. Moreover, simulations predict that CNTs with a length comparable to the thickness of a lipid bilayer membrane can self-insert into the membrane. Functionalized CNTs have indeed been found to penetrate lipid membranes and cell walls, and short tubes have been forced into membranes to create sensors, yet membrane transport applications of short CNTs remain underexplored. Here we show that short CNTs spontaneously insert into lipid bilayers and live cell membranes to form channels that exhibit a unitary conductance of 70-100 picosiemens under physiological conditions. Despite their structural simplicity, these 'CNT porins' transport water, protons, small ions and DNA, stochastically switch between metastable conductance substates, and display characteristic macromolecule-induced ionic current blockades. We also show that local channel and membrane charges can control the conductance and ion selectivity of the CNT porins, thereby establishing these nanopores as a promising biomimetic platform for developing cell interfaces, studying transport in biological channels, and creating stochastic sensors. [ABSTRACT FROM AUTHOR]

In order to clarify the air temperature distribution and air velocity distribution of a hydroelectric generating powerhouse in the mechanical ventilation mode, detailed ventilation experiments were conducted using a 1:20 small-scale model of a pumped-storage hydroelectric power station. In this model, we arranged fifty-seven circular inlets in double and triple rows to simulate the air supply pattern in a typical powerhouse. Six combinations of the inlets, and three air supply rates (28 m/h, 56 m/h, and 112 m/h) were selected to determine the effect of the inlets' arrangement and the air supply rates on the air distribution in the occupied zone of the powerhouse. A dimensionless method was adopted to process the acquired data of the air temperature and air velocity. The results revealed that the inlets' arrangements and the air supply velocity had a significant influence on the air distribution in the powerhouse. Simultaneously, the ventilation efficiency of four heat sources was studied in the optimum case, i.e. the most effective air supply rate is 112 m/h among the three tested values. The results of the experiments revealed that the air distribution was nearly independent of adjustable heat release rates. Our findings in this work may offer a significant advance in the understanding of ventilation system designs for hydroelectric powerhouses. [ABSTRACT FROM AUTHOR]

Single-walled carbon nanohorns (SWNHs) have great potential to enhance thermal and chemotherapeutic drug efficiencies for cancer therapies. Despite their diverse capabilities, minimal research has been conducted so far to study nanoparticle intracellular transport, which is an important step in designing efficient therapies. SWNHs, like many other carbon nanomaterials, do not have inherent fluorescence properties making intracellular transport information difficult to obtain. The goals of this project were to (1) develop a simple reaction scheme to decorate the exohedral surface of SWNHs with fluorescent quantum dots (QDs) and improve conjugate stability, and (2) evaluate SWNH-QD conjugate cellular uptake kinetics and localization in various cancer cell lines of differing origins and morphologies. In this study, SWNHs were conjugated to CdSe/ZnS core/shell QDs using a unique approach to carbodiimide chemistry. Transmission electron microscopy and electron dispersive spectroscopy verified the conjugation of SWNHs and QDs. Cellular uptake kinetics and efficiency were characterized in three malignant cell lines: U-87 MG (glioblastoma), MDA-MB-231 (breast cancer), and AY-27 (bladder transitional cell carcinoma) using flow cytometry. Cellular distribution was verified by confocal microscopy, and cytotoxicity was also evaluated using an alamarBlue assay. Results indicate that cellular uptake kinetics and efficiency are highly dependent on cell type, highlighting the significance of studying nanoparticle transport at the cellular level. Nanoparticle intracellular transport investigations may provide information to optimize treatment parameters (e.g., SWNH concentration, treatment time, etc.) depending on tumor etiology. [ABSTRACT FROM AUTHOR]

OsERF3 is a transcriptional repressor with an ethylene-responsive element-binding factor-associated amphiphilic repression (EAR) motif (F/LDLNxxP), which transcriptionally represses the ethylene emission and drought tolerance in rice. However, its molecular mechanism to explore repression function remains unknown. Here, we first revealed that the expression of OsERF3 was induced by drought, salt, ACC and ABA treatment. In addition, it showed a higher expression level in the root and sheath than that in the leaf. Then, we generated transgenic rice overexpressing full-length OsERF3 (OE) and its mutation of EAR motif with the A/C substitution (mEAR), respectively. The physiological analyses showed that mEAR lines showed better drought tolerance and more ethylene emission compared with those of OE lines and wild type plants. Consistent with our previous research, the expression of ethylene synthesis genes, including ACO2, ACS2, and ACS6 was down-regulated in OE lines. However, the repression of OsERF3 was eliminated in mEAR lines. Specifically, ACS2 was up-regulated in mEAR lines compared with that in OE lines and WT plants, suggesting that the Leu/Ala substitution within the EAR motif resulted in loss of repression of OsERF3. Thus, our data reveal that the EAR motif is required for OsERF3 to transcriptionally regulate the ethylene synthesis and drought tolerance in rice, providing new insight to the roles of ethylene-response factor proteins in regulating ethylene biosynthesis and stress response. [ABSTRACT FROM AUTHOR]

Developing combinatorial treatments involving laser irradiation and nanoparticles require an understanding of the effect of nanoparticle inclusion on tissue thermal properties, such as thermal conductivity. This information will permit a more accurate prediction of temperature distribution and tumor response following therapy, as well as provide additional information to aid in the selection of the appropriate type and concentration of nanoparticles. This study measured the thermal conductivity of tissue representative phantoms containing varying types and concentrations of carbon nanotubes (CNTs). Multi-walled carbon nanotubes (MWNTs, length of 900-1200 nm and diameter of 40-60 nm), single-walled carbon nanotubes (SWNTs, length of 900-1200 nm and diameter <2 nm), and a novel embodiment of SWNTs referred to as single-walled carbon nanohorns (SWNHs, length of 25-50 nm and diameter of 3-5 nm) of varying concentrations (0.1, 0.5, and 1.0 mg/mL) were uniformly dispersed in sodium alginate tissue representative phantoms. The thermal conductivity of phantoms containing CNTs was measured using a hot wire probe method. Increasing CNT concentration from 0 to 1.0 mg/mL caused the thermal conductivity of phantoms containing SWNTs, SWNHs, and MWNTs to increase by 24, 30, and 66%, respectively. For identical CNT concentrations, phantoms containing MWNTs possessed the highest thermal conductivity. [ABSTRACT FROM AUTHOR]