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Myocardial ischemia/reperfusion injury (MIRI) is related to ferroptosis and apoptosis elicited by reactive oxygen species (ROS). In this research, we investigated the protective effect of salvianolic acid B (SAB) as a natural antioxidant on ferroptosis and apoptosis in the MIRI process, and discussed the protective mechanism inhibiting ubiquitin-proteasome degradation of glutathione peroxidase 4 (GPX4) and the c-Jun N-terminal kinases (JNK) apoptosis signal pathway. We observed that ferroptosis and apoptosis occurred in the MIRI rat model in vivo and the H9c2 cardiomyocyte hypoxia/reoxygenation (H/R) damage model in vitro. SAB can alleviate tissue damage related to ROS, ferroptosis and apoptosis. Ubiquitin-proteasome degradation of GPX4 occurred in H/R models, and SAB reduced the ubiquitin-proteasome degradation of GPX4. SAB downregulates JNK phosphorylation and the expression of BCL2-Associated X (Bax)/B-cell lymphoma-2 (Bcl-2) and Caspase-3 to inhibit apoptosis. The role of GPX4 in the cardioprotection of SAB was further verified by the elimination effect of the GPX4 inhibitor RAS-selective lethal 3 (RSL3). This research shows that SAB may be used as a myocardial protective agent against oxidative stress, ferroptosis and apoptosis, and has potential clinical application prospects.

Shale oil reservoirs differ from conventional reservoirs in several aspects, including the sedimentary model, accumulation mechanism, and reservoir characteristics, which pose significant challenges to their exploration and development. Therefore, identifying the location of optimal spots is crucial for the successful exploration and development of shale oil reservoirs. Mobility, particularly in low-permeability shale oil reservoirs with nano-scale pores, is a crucial petrophysical property that determines the development plan. However, two-dimensional nuclear magnetic resonance (2D-NMR) is expensive and has limited applicability, although it can estimate shale oil mobility. Hence, it is of great significance to find a precise method for evaluating shale oil mobility using conventional logging. In this paper, we propose a new method for assessing shale oil mobility based on free oil porosity derived from the difference in flowing porosity detected at different ranges of logging, utilizing the Maxwell conductivity model and conductivity efficiency theory. Our study shows that longitudinal-T2 (T1-T2) NMR logging can accurately evaluate the mobility of shale oil. This is demonstrated by comparing the processing results obtained from our proposed method with those from 2D-NMR and laboratory NMR experiments. The predicted results based on conventional well logs also show good agreement with experimental results, confirming the effectiveness and reliability of our new method. Our proposed method carries reference significance for evaluating shale oil reservoir quality.

Molecular organic dyes are classic fluorescent nanoprobes finding tremendous uses in biological and life sciences. Yet, they suffer from low brightness, poor photostability, and lack of functional groups for bioconjugation. Here, we describe a class of biocompatible dye-protein optical nanoprobes, which show long-time photostability, superbrightness, and enriched functional groups. These nanoprobes utilize apoferritin (an intracellular protein for iron stores and release) to encase appropriate molecular organic dyes to produce on-demand fluorescence in aqueous solution. A pH-driven dissociation-reconstitution process of apoferritin subunits allows substantial incorporation of hydrophilic (aggregation caused quenching, ACQ) or hydrophobic (aggregation induced enhancement, AIE) dye molecules into the protein nanocavity (8 nm), producing monodispersed dye-apoferritin nanoparticles (apo-dye-NPs, ∼12 nm). As compared with single dye monomer, single apo-dye-NPs possess hundreds of times larger molar extinction coefficient and 2 orders of magnitude higher absolute luminescence quantum yield (up to 45-fold), multiplying fluorescence brightness up to 2778-fold. We show that varying the type of incorporated dyes entails a precise control over nanoprobe emission profile tunable in a broad spectral range of 370-1300 nm. Mechanical investigations indicate that the diversified microstructures of nanocavity inner surface are able to conform ACQ dyes at reasonable space interval while providing protein-guided-stacking for AIE dyes, thus enhancing fluorescence quantum yield through confining intermolecular quenching and intramolecular rotation. Moreover, apo-dye-NPs are able to emit stable fluorescence (over 13 min) without quenching in confocal imaging of HepG2 cancer cell under ultrahigh laser irradiance (1.3 × 10sup6/supW/cmsup2/sup). These superb properties make them suitable, as demonstrated in this work, for long-term super-resolved structured illumination microscopic cell imaging (spatial resolution, 117 nm) over 48 h, near-infrared (NIR) fluorescence angiography imaging of whole-body blood vessels (spatial resolution, 380 μm), and NIR photoacoustic imaging of liveriin vivo/i.

AIMS Aerobic training (AT) and resistance training (RT) can reduce blood glucose and type 2 diabetes risk, and increase muscle mass for prediabetes patients. However, the impact of long-term AT and RT on cardiovascular disease (CVD) risk remains unclear. The purpose of this study was to investigate the impact of AT and RT on CVD risk reduction in prediabetes patients. MATERIALS AND METHODS 248 prediabetes patients were enrolled in this multi-center randomized controlled trial (RCT). Patients were randomly divided into 3 groups: RT (n = 82), aerobic training (AT (n = 83)), and control group (n = 83). Participants in RT and AT groups had moderate RT or AT 3 times a week (150 min/week) under supervision in 3 research centers for 24 months. Primary outcome was CVD risk measured by Framingham Risk Score (FRS) and The Chinese 10-year ischemic cardiovascular disease (ICVD) risk assessment tool. Secondary outcomes included in HOMA2-IR, HbA1c, blood pressure and serum lipid profile. RESULTS Both RT and AT groups experienced a significant reduction in HOMA2-IR, HbA1c, LDL-C, TC, SBP, and DBP at the end of 12 and 24 months. Compared to the control group, Both RT and AT groups had significant reduction of the Chinese 10-year ICVD risk (P

Ultrahigh-Ni layered oxides have been proposed as promising cathodes to fulfill the range demand of electric vehicles, yet they are still haunted by compromised cyclability and thermal robustness. The state-of-the-art surficial coating is designed to solve the instability via blocking the physical contact between the electrolyte and the highly active Ni

The mechanism of discontinuous transcription for the synthesis of a series of sub-genomic mRNAs to express the porcine reproductive and respiratory syndrome virus (PRRSV) structural proteins potentially allows for the simultaneous expression of multiple foreign genes. This can occur by insertion of multiple novel independent transcription units between ORF sequences of the PRRSV genome. Here, an expression cassette consisting of a red fluorescent protein (RFP) gene flanked at its 3′ end by transcription-regulating sequences (TRS) and an expression cassette consisting of an iLOV gene flanked at its 5′ end by TRS was constructed. The resulting expression cassette containing a RFP gene and containing iLOV gene was introduced between ORF1b and 2, and between ORF7 and 3′UTR, respectively, in an infectious PRRSV cDNA clone. Transfection of the resulting clone (pGX-12RFP-73iLOV) into cells resulted in the recovery of a recombinant virus (rGX-12RFP-73iLOV). Simultaneous expression of RFP and iLOV was observed in MARC-145 cells infected with rGX-RFP-iLOV. To test the ability of the PRRSV genome to express three reporter genes simultaneously, an expression cassette containing the Gluc gene and an expression cassette containing iLOV gene were also inserted in between ORF1b and 2, and between ORF7 and 3′UTR, respectively. This was performed in a recently obtained infectious PRRSV cDNA clone carrying a RFP gene in nsp2. Transfection of the construct (pGX-R-Gluc-iLOV) carrying three reporter genes into cells allowed the rescue of the recombinant reporter virus (rGX-R-Gluc-iLOV) which showed similar growth characteristics to the parental virus and yet yielded 100-fold less infectious viruses. Fluorescence microscopy of cells infected with rGX-R-Gluc-iLOV demonstrated the presence of both GFP and iLOV genes. Gluc activities in supernatants harvested at different time points from cells infected with recombinant viruses carrying Gluc showed the levels of Gluc activity increased as the infection progressed, indicating that the expression of Gluc gene and its activity were parameters for monitoring viral propagation. These results indicate that it is possible to introduce at least three foreign proteins simultaneously in a PRRSV-based vector and this will prove invaluable in our future understanding of these viruses.

The current study presents a novel method to prepare high-purity V2O5 from Na3VO4 solution. This process characterizes Na3VO4 calcification separation, Ca10V6O25 ammoniation and solubilization, NH4VO3 crystallization, and vanadium precipitation, which achieves elemental V migration from the Na3VO4–Ca10V6O25–NH4VO3–V2O5 phase, finally obtaining high-purity V2O5. The influencing factors of the preparation process were investigated, and the results showed that vanadium was released from Na3VO4 solution to synthesize Ca10V6O25 in the first stage under the most suitable conditions (Ca/V molar ratio of 1.8, and a concentration of NaOH less than 160 g/L). In the second stage, the leaching efficiency of vanadium reached 95% at optimal conditions (NH4+/V molar ratio was 1.2, reaction temperature and time were 90 °C and 30 min, respectively). In the third stage, NH4VO3 yield and crystal size reached maximum values under optimal conditions (feed rate, crystallization temperature, and the power factor of the circulating pump were 6 m3/h, 30 °C, and 80% respectively). Finally, high-purity V2O5 was prepared via a series of large particle NH4VO3 post-treatments. In addition, the ICP analysis confirmed that the purity of the generated V2O5 was more than 99.5%.

China’s power industry is a major energy consumer, with the carbon dioxide (CO2) generated by coal consumption making the power industry one of the key emission sectors. Therefore, it is crucial to explore energy conservation and emissions reduction strategies suitable for China’s current situation. Taking a typical cogeneration enterprise in North China as an example, this paper aims to establish a generalized regression prediction model for carbon emissions of coal-fired power plants, which will provide a reference for China to seek strategies for carbon peaking and carbon neutralization in the future. Firstly, in terms of the selection of influencing factors, this paper uses objective index screening methods, simulation means, and the eXtreme Gradient Boosting algorithm (XG-Boost) to analyze the feature importance of various influencing factors. It is concluded that the relevant influencing factors of the boiler feed water system have a strong correlation and characteristic importance with the carbon emissions results of coal-fired power plants. Therefore, this paper proposes to introduce these factors into the regression prediction model as auxiliary variables to more scientifically reflect the carbon emissions results of coal-fired power plants. Secondly, in the aspect of regression prediction model establishment, inspired by the sparrow’s foraging behavior and anti-predation behavior, this paper selects the sparrow search algorithm (SSA) with strong optimization ability and fast convergence speed to optimize the super parameters of the long short-term memory network algorithm (LSTM). It is proposed to use the SSA-LSTM algorithm to establish the carbon emissions regression prediction model of coal-fired power plants. The advantage of the SSA-LSTM algorithm is that it can effectively simplify the super parameter selection process of the LSTM algorithm, effectively solve the global optimization problem, prevent the model from falling into overfitting and local optimization, and make the carbon emissions regression prediction model of coal-fired power plants achieve a better fitting effect. By comparing the performance indicators of the model before and after the improvement, it is found that the regression prediction effect of the SSA-LSTM coal-fired power plant carbon emissions regression prediction model, which introduces boiler feed water influencing factors, has been effectively improved. Therefore, the model proposed in this paper can be used to conduct a comprehensive impact factor analysis and regression prediction analysis on the carbon emissions intensity of China’s coal-fired power plants, formulate targeted carbon emissions reduction countermeasures, and provide a theoretical basis for energy conservation and emissions reduction of China’s coal-fired power plants.

Aiming at the problem of “dynamic” accurate determination of rates in UBI auto insurance pricing, this paper proposes a UBI auto insurance pricing model based on fuzzy controller and optimizes it with a parameter adaptive SASPO. On the basis of the SASPO algorithm, the movement direction of the particles can be mutated and the direction can be dynamically controlled, the inertia weight value is given by the distance between the particle and the global optimal particle, and the learning factor is calculated according to the change of the fitness value, which realizes the parameter in the running process. Effective self-adjustment. A five-dimensional fuzzy controller is constructed by selecting the monthly driving mileage, the number of violations, and the driving time at night in the UBI auto insurance data. The weights are used to form fuzzy rules, and a variety of algorithms are used to optimize the membership function and fuzzy rules and compare them. The research results show that, compared with other algorithms, the parameter adaptive SAPAO algorithm can calculate more reasonable, accurate and high-quality fuzzy rules and membership functions when processing UBI auto insurance data. The accuracy and robustness of UBI auto insurance rate determination can realize dynamic and accurate determination of UBI auto insurance rates.

Recently shape constrained classification has gained popularity in the machine learning literature in order to exploit extra model information besides raw data features. In this paper, we present a new Lattice Linear Discriminant Analysis (Lattice-LDA) classifier, which allows to take shape constraints of data inputs, such as monotonicity and convexity/concavity. Lattice-LDA constructs a nonparametric nonlinear discriminant hyperplane for classification, using an additive format of 1-D lattice functions (piecewise linear functions). Moreover, the new classifier features in taking complex shape constraints including combinations of shapes or S-shape. We optimize the model parameters using the Adaptive Moment Estimation (Adam) algorithm embedding stepwise projections which guarantee feasibility of the shape constraints. Through simulation and real-world examples, we demonstrate that the new classifier could accurately recover the nonlinear marginal effect functions and improve classification accuracy when additional shape information is present.

The liquid and gas diffusion layer is a key component of proton exchange membrane water electrolyzer (PEMWE), and its interfacial contact resistance (ICR) and corrosion resistance have a great impact on the performance and durability of PEMWE. In this work, a novel hybrid coating with Au contacts discontinuously embedded in a titanium oxidized layer was constructed on a Ti felt via facile electrochemical metallizing and followed by a pre-oxidization process. The physicochemical characterizations, such as scanning electron microscopy, energy dispersive spectrometer, and X-ray diffraction results confirmed that the distribution and morphology of the Au contacts could be regulated with the electrical pulse time, and a hybrid coating (Au-TiO2/Ti) was eventually achieved after the long-term stability test under anode environment. At the compaction force of 140 N cm−2, the ICR was reduced from 19.7 mΩ cm2 of the P-Ti to 4.2 mΩ cm2 of the Au-TiO2/Ti. The corrosion current density at 1.8 V (RHE) is 0.689 μA cm−2. Both the ICR and corrosion resistance results showed that the prepared protective coating could provide comparable ICR and corrosion resistance to a dense Au coating.

The liquid and gas diffusion layer is a key component of proton exchange membrane water electrolyzer (PEMWE), and its interfacial contact resistance (ICR) and corrosion resistance have a great impact on the performance and durability of PEMWE. In this work, a novel hybrid coating with Au contacts discontinuously embedded in a titanium oxidized layer was constructed on a Ti felt via facile electrochemical metallizing and followed by a pre-oxidization process. The physicochemical characterizations, such as scanning electron microscopy, energy dispersive spectrometer, and X-ray diffraction results confirmed that the distribution and morphology of the Au contacts could be regulated with the electrical pulse time, and a hybrid coating (Au-TiO

With the support of the Internet of Vehicles technology, UBI car insurance premium rate determination has certain guiding significance for realizing accurate pricing of freight vehicle car insurance rates and meeting the individual needs of users. The SSA algorithm is optimized, and the MSNSSA algorithm is proposed, which is used to build a model for determining the UBI rate of freight vehicles. The model first divides the original population into three sub-groups of leader, followers and salp chain evenly according to the fitness value from small to large, and perform different search tasks respectively. By adding a symbiosis strategy to the follower location update process, the development capability of the SSA algorithm can be effectively enhanced. It is proposed to add a non-uniform Gaussian mutation strategy to the chain with poor fitness value to enhance the diversity of the population. By establishing the MSNSSA-FCM algorithm, using the global optimization advantage of the MANSSA algorithm, the clustering center of the FCM algorithm is optimized, and then the sample weight and attribute weight are introduced to design the objective function of the FCM clustering algorithm to improve the clustering of the FCM algorithm performance. The empirical evidence shows that the UBI Freight Vehicle Car insurance rate rating model established based on the MSNSSA-FCM algorithm has reduced visual noise and reduced intra-cluster error variance. In the process of processing UBI Freight Vehicle Car insurance data, compared with FCM algorithm and SSA-FCM algorithm and SAGA-FCM algorithm have higher clustering accuracy, and provide decision-making basis for insurance companies to mine more accurate customer classification information, customer driving risk assessment and customer car insurance rate rating.

Aiming at the problem of usage-based insurance (UBI) auto insurance pricing, this paper proposes a multi-dimensional pricing model based on fuzzy controllers. In order to comprehensively consider the influencing factors of the rate, an index system of autonomous underwriting coefficient is proposed from four dimensions of driving distance, driving time, driving speed and driving behavior. A sub-fuzzy controller based on dimension index is proposed. The adaptive weight and learning factor are introduced into simulated annealing particle swarm optimization (SAPSO) algorithm, and combined with Metropolis criterion, the adaptive SAPSO algorithm is improved. In order to reduce the subjective defects of fuzzy controller, standard particle swarm optimization (PSO), parameter adaptive PSO and SAPSO algorithms are used for optimization respectively. The fitness function is improved to incorporate stability into the screening criteria. After comparison, it is found that SAPSO algorithm can get the optimal results in fuzzy controllers with lower dimensions, and parameter adaptive PSO algorithm in fuzzy controllers with higher dimensions can get better results. The optimal output result is selected and input into the total fuzzy controller to calculate the autonomous underwriting coefficient. The experimental results show that the multi-dimensional auto insurance pricing model based on fuzzy controller in this paper can better measure the driving risk comprehensively. It has higher accuracy and stability in rate determination.

Recently, nickel phosphides (Ni-P) in an amorphous state have emerged as potential catalysts with high intrinsic activity and excellent electrochemical stability for hydrogen evolution reactions (HER). However, it still lacks a good strategy to prepare amorphous Ni-P with rich surface defects or structural boundaries, and it is also hard to construct a porous Ni-P layer with favorable electron transport and gas–liquid transport. Herein, an integrated porous electrode consisting of amorphous Ni-P and a Ni interlayer was successfully constructed on a 316L stainless steel felt (denoted as Ni-P/Ni-316L). The results demonstrated that the pH of the plating solution significantly affected the grain size, pore size and distribution, and roughness of the cell-like particle surface of the amorphous Ni-P layer. The Ni-P/Ni-316L prepared at pH = 3 presented the richest surface defects or structural boundaries as well as porous structure. As expected, the as-developed Ni-P/Ni-316L demonstrated the best kinetics, with η10 of 73 mV and a Tafel slope of ca. 52 mV dec-1 for the HER among all the electrocatalysts prepared at various pH values. Furthermore, the Ni-P/Ni-316L exhibited comparable electrocatalytic HER performance and better durability than the commercial Pt (20 wt%)/C in a real water electrolysis cell, indicating that the non-precious metal-based Ni-P/Ni-316L is promising for large-scale processing and practical use.

Gastric cancer (GC) is the third leading cause of cancer-associated mortality globally. Although the diagnosis and therapeutic strategies for GC have improved, the prognosis for advanced gastric cancer (AGC) remains poor. Hence, the present study sought to design a zebrafish model established by microinjecting human MGC-803 GC cell line for studying personalized molecular-targeted cancer therapy. Apatinib, a novel molecular-targeted agent, was evaluated for its in vivo efficacy through a comparison among the control groups (no treatment) and subject groups (treatment). Newly formed vessel length and tumor volume were measured in all of the groups for further study. The length of newly formed vessels was obviously shortened after apatinib treatment in the zebrafish model established in this study. Meanwhile, apatinib exhibited the best antitumor growth effect with dose and time dependence by suppressing AKT/GSK3α/β signaling, which may be the mechanism underlying the profound antitumor clinical effect of apatinib. The data indicated that apatinib therapy exerts an anti-angiogenesis effect and it can be recommended as a proper antitumor growth therapy for GC patients. Additionally, zebrafish models could be designed as a potential practical tool to explore new anti-GC cancer drugs.

Currently, the most efficient method of resolving the pollution problem of weed management is by using variable spraying technology. In this study, an improved genetic proportional-integral-derivative control algorithm (IGA-PID) was developed for this technology. It used a trimmed mean operator to optimize the selection operator for an improved searching rate and accuracy. An adaptive crossover operator and mutation operator were constructed for a rapid convergence speed. The weed density detection was performed through an image acquisition and processing subsystem which was capable of determining the spraying quantity. The variable spraying control sub-system completed variable spraying operation. The performance of the system was evaluated by simulations and field tests, and compared with conventional methods. The simulation results indicated that the parameters of the overshoot (1.25%), steady-state error (1.21%) and the adjustment time (0.157s) of IGA-PID were the lowest when compared with the standard algorithms. Furthermore, the field validation results showed that the system with the proposed algorithm achieved the optimal performance with spraying quantity error being 2.59% and the respond time being 3.84s. Overall, the variable spraying system based on an IGA-PID meets the real-time and accuracy requirements for field applications which could be helpful for weed management in precise agriculture.

In mortgage default modeling, many of the key variables, such as loan age, FICO score, Debt-to-Income ratio (DTI), and Loan-to-House-Value ratio (LTV), have nonlinear relationships with the target default rates. Experienced modelers generally apply a spline transformation with knots to the individual variables. In this article, we introduce the Quantile-based Shape Constrained Maximum Likelihood Estimator (QSC-MLE), which features an automatic spline knot selection in a mortgage default model. QSC-MLE is an enhanced variant of SC-MLE (Chen and Samworth 2016) used in combination with a quantile-based knots set, to effectively process large datasets. QSC-MLE requires generic shape information of the inputs, for example, the monotonicity or convexity of the FICO score, DTI, and LTV, to capture any nonlinear effects. We show that the new default model considerably improves the accuracy of the out-of-sample prediction in comparison with the logistic regression and the Cox proportional hazards model. Moreover, the model conveniently generates component-wise spline functions, which facilitates the interpretation of the default rate response to the input variables. Key Findings ▪ A mortgage default model using the Quantile-based Shape Constrained Maximum Likelihood Estimator (QSC-MLE), which features automatic spline knot selection. ▪ QSC-MLE constructs shape-constrained spline functions to capture nonlinear effects of model inputs. ▪ The new default model considerably improves the accuracy of the out-of-sample prediction.

The effect of electromagnetic stirring at a continuous casting strand on the distribution of inclusions along the thickness of gear steel blooms was investigated. Inclusions in the subsurface of continuous casting blooms were Al2O3·CaO·CaS·MgO, similar to those in the molten steel of continuous casting tundish. Inclusions at 1/4 thickness from the loose side and the center of the bloom were Al2O3·CaS·MgO. The spatial distribution in the number density and composition of inclusions along the thickness from the loose side to the fixed side of the bloom was non-uniform but symmetric. The electromagnetic stirring efficiently improved steel cleanliness by lowering the average number density and area fraction of inclusions in the whole section of the CC bloom from 58.14 #/mm2 and 176.82 ppm to 30.90 #/mm2 and 111.67 ppm, respectively, and by increasing the average size and the maximum size of inclusions from 2.73 and 20.84 μm to 2.99 and 76.02 μm, respectively. More large-size inclusions contained K and Na by the slag entrainment in the mold with electromagnetic stirring were detected than those without electromagnetic stirring. Seven mm of the bloom from the loose side was analyzed for inclusions with size > 1.0 μm every 1 mm depth. The average CaO content of inclusions with size > 1.0 μm within the 7 mm subsurface of the bloom increased from 5.67 wt pct without electromagnetic stirring to 16.12 wt pct with electromagnetic stirring and increased from 10.24 wt pct without electromagnetic stirring to 21.31 wt pct with electromagnetic stirring for > 3.0 μm inclusions, which confirmed that unreasonable current electromagnetic stirring operation parameters will lead to slag entrainment.

The world’s energy system is changing dramatically. Li-ion battery, as a powerful and highly effective energy storage technique, is crucial to the new energy revolution for its continuously expanding application in electric vehicles and grids. Over the entire lifetime of these power batteries, it is essential to monitor their state of health not only for the predicted mileage and safety management of the running electric vehicles, but also for an “end-of-life” evaluation for their repurpose. Electrochemical impedance spectroscopy (EIS) has been widely used to diagnose the health state of batteries quickly and nondestructively. In this review, we have outlined the working principles of several electrochemical impedance techniques and further evaluated their application prospects to achieve the goal of nondestructive testing of battery health. EIS can scientifically and reasonably perform real-time monitoring and evaluation of electric vehicle power batteries in the future and play an important role in vehicle safety and battery gradient utilization.

A central aim of neuroethological research is to discover the mechanisms of natural behaviors in controlled laboratory studies. This goal, however, comes with challenges, namely the selection of experimental paradigms that allow full expression of natural behaviors. Here, we explore this problem in echolocating bats that evolved Doppler shift compensation (DSC) of sonar vocalizations to yield close matching between echo frequency and hearing sensitivity. We ask if behavioral tasks influence the precision of DSC in Pratt’s roundleaf bat, Hipposideros pratti, in three classic laboratory paradigms evoking audio-vocal adjustments: Stationary bats listening to echo playbacks, bats transported on a moving pendulum, and bats flying freely. We found that experimental conditions had a strong influence on the expression of the audiovocal frequency adjustments in bats. H. pratti exhibited robust DSC in both free-flying and moving-pendulum experiments but did not exhibit consistent audiovocal adjustments in echo playback experiments. H. pratti featured a maximum compensation magnitude of 87% and a compensation precision of 0.27% in the free flight experiment. Interestingly, in the moving pendulum experiment H. pratti displayed surprisingly high-precision DSC, with an 84% maximum compensation magnitude and a 0.27% compensation precision. Such DSC performance places H. pratti among the bat species exhibiting the most precise audio-vocal control of echo frequency. These data support the emerging view that Hipposiderid bats have a high-precision DSC system and highlight the importance of selecting experimental paradigms that yield the expression of robust natural behaviors.

Since its recent appearance in China, the NADC30-like strains of porcine reproductive and respiratory syndrome virus 2 (PRRSV-2) have caused an expanding epidemic, and this has further expanded the genetic diversity of PRRSV. In this study, three NADC30-like strains—GXFCG20210401, GXQZ20210403 and GXNN20210506—were isolated from pig serum samples obtained in Guangxi, and their genomes were sequenced. A comparative analysis of the whole genomes showed that the three strains were most similar to NADC30 (88.3–88.7%). In particular, the non-structural protein coding regions (nsp1, nsp4-5, nsp7-8 and nsp9) showed the highest similarities to JXA1, and the ORF2a-ORF5 regions showed the highest similarities to NADC34. The three strains had same discontinuous deletions of 111+1+19 amino acids in the nsp2 region, which were similar to the NADC30-like strains. Phylogenetic tree analysis based on the ORF5 gene showed that the three PRRSV isolates were divided into lineage 1.5 along with the representative NADC34-like strains, but they were classified as NADC30-like strains with respect to the whole genome and nsp2 evolutionary trees. Recombinant analysis revealed complex recombination patterns in the genomes of the three strains, which likely originated from multiple recombination events among JXA1-like, NADC30-like and NADC34-like strains. The results from animal experiments showed that the GXQZ20210403 strain was 20% lethal to piglets and caused more severe clinical reactions than GXFCG20210401, and both recombinant strains were similar in terms of pathogenicity to the previously reported NADC34 strains. This study demonstrates that NADC34-like strains of PRRSV have been circulating in the southern provinces of China and have exchanged genomes with several other indigenous strains. In addition, differences in recombination patterns may cause different clinical pathogenicity and indicate the importance of the surveillance and preventive control of recombinant strains.

The incidence of type 2 diabetic osteoporosis (T2DOP), which seriously threatens elderly people's health, is rapidly increasing in recent years. However, the specific mechanism of the T2DOP is still unclear. Studies have shown the relationship between iron overload and T2DOP. Mitochondrial ferritin (FtMt) is a protein that stores iron ions and intercepts toxic ferrous ions in cells mitochondria. Ferroptosis, an iron-dependent cell injured way, may be related to the pathogenesis of T2DOP. In this study, we intend to elucidate the effect of FtMt on ferroptosis in osteoblasts and explain the possible mechanism. We first detected the occurrence of ferroptosis in bone tissue and the expression of FtMt after inducing T2DOP rat model. Then we used hFOB1.19 cells to study the influence of high glucose on FtMt, ferroptosis, and osteogenic function of osteoblasts. Then we observed the effect of FtMt on ferroptosis and osteoblast function by lentiviral silencing and overexpression of FtMt. We found ferroptosis in T2DOP rats bone. Overexpression of FtMt reduced osteoblastic ferroptosis under high glucose condition while silent FtMt induced mitophagy through ROS / PINK1/Parkin pathway. Then we found increased ferroptosis in osteoblasts after activating mitophagy by carbonyl cyanide-m-chlorophenyl-hydrazine (CCCP, a mitophagy agonist). Our study demonstrated that FtMt inhibited the occurrence of ferroptosis in osteoblasts by reducing oxidative stress caused by excess ferrous ions, and FtMt deficiency induced mitophagy in the pathogenesis of T2DOP. This study suggested that FtMt might serve as a potential target for T2DOP therapy.

Many classification problems contain shape information from input features, such as monotonic, convex, and concave. In this research, we propose a new classifier, called Shape-Restricted Support Vector Machine (SR-SVM), which takes the component-wise shape information to enhance classification accuracy. There exists vast research literature on monotonic classification covering monotonic or ordinal shapes. Our proposed classifier extends to handle convex and concave types of features, and combinations of these types. While standard SVM uses linear separating hyperplanes, our novel SR-SVM essentially constructs non-parametric and nonlinear separating planes subject to component-wise shape restrictions. We formulate SR-SVM classifier as a convex optimization problem and solve it using an active-set algorithm. The approach applies basis function expansions on the input and effectively utilizes the standard SVM solver. We illustrate our methodology using simulation and real world examples, and show that SR-SVM improves the classification performance with additional shape information of input.

In order to improve the conductivity of titanium bipolar plate under the premise of ensuring its corrosion resistance for the proton exchange membrane fuel cell (PEMFC), the nitride coatings are deposited on the surface of titanium bipolar plate via a powder immersion reaction assisted coating (PIRAC) method. Both the scanning electron microscopy (SEM) and energy dispersive spectrometer (EDS) show that the dense titanium nitride coatings with the thickness around 1.5–2.5 μm are successfully prepared. Furthermore, the X-ray photoelectron spectroscopy (XPS) results confirm the presence of TiN, TiNxOy and TiO2 phases on the surface of nitride coatings, and the content of these phases is tunable by adjusting the prepared temperatures. Both the microstructure, the thickness and the composition of the nitride coatings could be associated with the corrosion resistance and the interfacial contact resistance of the nitrided samples. We find that the nitrided samples prepared at 1000 °C could be the ideal mixed coating materials with the proper combination of the corrosion resistance and the interfacial contact resistance, which also show the best long-term stability in simulated PEMFC cathode environment.

Objective. To investigate the expression patterns and prognostic characteristics of inflammasome-related genes (IRGs) across cancer types and develop a robust biomarker for the prognosis of KIRC. Methods. The differentially expressed IRGs and prognostic genes among 10 cancers were analyzed based on The Cancer Genome Atlas (TCGA) dataset. Subsequently, an IRGs risk signature was developed in KIRC. Its prognostic accuracy was evaluated by receiver operating characteristic (ROC) analysis. The independent predictive capacity was identified by stratification survival and multivariate Cox analyses. The gene ontology (GO) analysis and principal component analysis (PCA) were performed to explore biological functions of the IRGs signature in KIRC. Results. The expression patterns and prognostic association of IRGs varied from different cancers, while KIRC showed the most abundant survival-related dysregulated IRGs. The IRG signature for KIRC was able to independently predict survival, and the signature genes were mainly involved inimmune-related processes. Conclusions. The pan-cancer analysis provided a comprehensive landscape of IRGs across cancer types and identified a strong association between IRGs and the prognosis of KIRC. Further IRGs signature represented a reliable prognostic predictor for KIRC and verified the prognostic value of inflammasomes in KIRC, contributing to our understanding of therapies targeting inflammasomes for human cancers.

Variations of Libor Market Model (LMM), including Constant Elasticity of Variance-LMM (CEV-LMM) and Stochastic Alpha-Beta-Rho LMM (SABR-LMM), have become popular for modeling interest rate term structure. Nevertheless, the limitation of applying CEV-/SABR-LMM to model negative interest rates still exists. In this paper, we adopt the approach of Free-Boundary SABR (FB-SABR), which is an extension based on standard SABR. The key idea of FB-SABR is to apply absolute value of forward rate $|F_t|$ in the rate dynamic $\mathrm{d} F_t = |F_t|^\beta \sigma_t \mathrm{d} W_{t}$, which naturally allows interest rates to across zero boundary. We focus on introducing FB-SABR into LMM to handle volatility smile under negative rates. This new model, FB-SABR-LMM, can be used to price interest rate instruments with negative strikes as well as to recover implied volatility surface.