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Abstract Background Cardiometabolic index (CMI) is a comprehensive clinical parameter which integrates overweight and abnormal lipid metabolism. However, its relationship with all-cause, cardiovascular disease (CVD), and cancer mortality is still obscure. Thus, a large-scale cohort study was conducted to illustrate the causal relation between CMI and CVD, cancer, and all-cause mortality among the common American population. Methods Our research was performed on the basis of National Health and Nutrition Examination Survey (NHANES) database, involving 40,275 participants ranging from 1999 to 2018. The formula of CMI is [waist circumference (cm) / height (cm)] × [triglyceride (mg/dL) / high-density lipoprotein cholesterol (mg/dL)]. Outcome variables consisted of CVD, cancer, and all-cause mortality, which were identified by the International Classification of Diseases (ICD)-10. The correlation between CMI and mortality outcomes was analyzed utilizing the Kaplan–Meier survival modeling, univariate/multivariate Cox regression analysis, smooth curve fitting analysis, threshold effect analysis, and subgroup analysis. Stratification factors for subgroups included age, race/ethnicity, sex, smoking behavior, drinking behavior, BMI, hypertension, and diabetes. Results The baseline characteristics table includes 4,569 all-cause-induced death cases, 1,113 CVD-induced death cases, and 1,066 cancer-induced death cases. Without adjustment for potential covariates, significantly positive causal correlation existed between CMI and all-cause mortality (HR = 1.03, 95% CI 1.02,1.04, P-value0.05). Subgroup analysis found no specific subgroups. Under a fully adjusted model, a threshold effect analysis was performed combined with smooth curve fitting, and the findings suggested an L-shaped nonlinear association within CMI and all-cause mortality (the Inflection point was 0.98); in particular, when the baseline CMI was below 0.98, there existed a negative correlation with all-cause mortality with significance (HR 0.59, 95% CI 0.43, 0.82, P-value

This research presents a “flexible support structure between reflective mirrors” through a coupling analysis method to restrain the surface shaping error of reflectors in the optical system of airborne LiDAR bathymetry (ALB) under various working conditions. The flexible structure proposed adjusts the mechanical relationship between the reflectors and the support structure to reduce reflector mirror deformation. The optical system is first modeled using Zemax and exported to SolidWorks to create a 3D model of the optical receiving system. Ansys is then used to conduct stiffness testing and surface analysis on the support structure of the annular thin cylinder. According to the analysis results, the first-order frequency of the support structure using a ring-shaped thin cylinder is as high as 353.64 Hz, which indicates that it has good dynamic characteristics. The PV value of the reflector mirror deformation under the thermal coupling reaches 32.59 nm, and the RMS value reaches 8.62 nm. Additionally, it is discovered that the maximum acceleration response of the reflector mirror under the applied 1 g acceleration excitation reaches 4.22 g when carrying out the dynamics analysis of the support structure. Under random vibration analysis, the maximum acceleration RMS value of the reflector mirror assembly reaches 2.18 g, and the maximum stress of the flexible device of the support structure reaches 2.65 MPa. Especially, five groups of experimental results demonstrated that the proposed coupling analysis method can receive the echo signals, the reflector mirror support structure designed in this paper, and the flexible structure is stable and reliable.

Background The neurotrophic parasite Toxoplasma gondii (T. gondii) has been implicated as a risk factor for neurodegenerative diseases. However, there is only limited information concerning its underlying mechanism and therapeutic strategy. Here, we investigated the effects of T. gondii chronic infection on the goal-directed cognitive behavior in mice. Moreover, we evaluated the preventive and therapeutic effect of dimethyl itaconate on the behavior deficits induced by the parasite. Methods The infection model was established by orally infecting the cysts of T. gondii. Dimethyl itaconate was intraperitoneally administered before or after the infection. Y-maze and temporal order memory (TOM) tests were used to evaluate the prefrontal cortex-dependent behavior performance. Golgi staining, transmission electron microscopy, indirect immunofluorescence, western blot, and RNA sequencing were utilized to determine the pathological changes in the prefrontal cortex of mice. Results We showed that T. gondii infection impaired the prefrontal cortex-dependent goal-directed behavior. The infection significantly downregulated the expression of the genes associated with synaptic transmission, plasticity, and cognitive behavior in the prefrontal cortex of mice. On the contrary, the infection robustly upregulated the expression of activation makers of microglia and astrocytes. In addition, the metabolic phenotype of the prefrontal cortex post infection was characterized by the enhancement of glycolysis and fatty acid oxidation, the blockage of the Krebs cycle, and the disorder of aconitate decarboxylase 1 (ACOD1)-itaconate axis. Notably, the administration of dimethyl itaconate significantly prevented and treated the cognitive impairment induced by T. gondii, which was evidenced by the improvement of behavioral deficits, synaptic ultrastructure lesion and neuroinflammation. Conclusion The present study demonstrates that T. gondii infection induces the deficits of the goal-directed behavior, which is associated with neuroinflammation, the impairment of synaptic ultrastructure, and the metabolic shifts in the prefrontal cortex of mice. Moreover, we report that dimethyl itaconate has the potential to prevent and treat the behavior deficits. Author summary Toxoplasma gondii (T. gondii) is a neglected but important risk factor for neurodegenerative diseases. It is necessary to decipher the mechanism of cognitive deficits induced by the parasite and develop intervention therapy. Here, we showed that chronic T. gondii infection induces the deficits of the goal-directed behavior, which is associated with the prefrontal cortex. Moreover, the global expression pattern in the brain area of the infected mice is characterized by the downregulation of the genes associated with synaptic transmission and plasticity, and the upregulation of the genes related to neuroinflammation including the activation makers of microglia and astrocytes. Interestingly, the ACOD1-itaconate axis, a key node modulating immunity and metabolism, is activated post infection. We reported that dimethyl itaconate (the derivative of itaconate) effectively prevents and treats the goal-directed cognitive deficits induced by T. gondii, which was proved by the improvement of the synaptic ultrastructure impairment and neuroinflammation. Overall, these findings provide a novel insight for understanding the mechanism of cognitive deficits induced by T. gondii and developing a therapeutic strategy against the parasite-related neurodegenerative diseases.

Forest field inventory plays a crucial role in forestry management and the estimation of carbon circular economy, as it provides information on forest parameters, assesses carbon storage, and identifies the impact factors of ecological change. Terrestrial Laser Scanning (TLS) and Mobile Mapping Systems (MMS) are commonly used for forest field inventory, but they are unable to verify the inventory results in real time. With real-time forest inventory, forestry workers can immediately verify if all trees have been correctly extracted without requiring expertise in point clouds. The advences of miniaturized, low-cost 3D sensors (such as solid-state laser scanners and Inertial Measurement Units [IMUs]) and edge computing units have made it possible to achieve real-time forest inventory using a compact, low-cost helmet. To this end, this paper presents a real-time automated forest field inventory method, which is validated on a compact, low-cost helmet-based laser scanning system. Firstly, a Fast Candidate Tree Detection (FCTD) approach is proposed to identify individual trees as candidates by utilizing a novel 2D corner detection technique based on point cloud projection, taking into account point density and geometry features. Secondly, a Spatiotemporal Consistency-based Tree Parameter Estimation (SCTPE) method is proposed to estimate the tree parameters by considering both the current submap and submaps that have been scanned in real-time. The proposed method was tested in three typical forest areas in Wuhan, China, where the main tree species present include Sapindaceae, dawn redwoods, and Platycladus. The results showed that the proposed method achieves high accuracy in tree detection (recall=0.97,precision=0.94,F=0.96). The average error and root-mean-square error (RMSE) of DBH are 0.033 m and 0.038 m, which outperforms the existing one-circle fitting model. The average error and RMSE of tree height are 0.231 m and 0.294 m. Overall, these results demonstrate the high potential of the helmet-based laser scanning system for real-time forest field inventory.

2,5-furandicarboxylic acid(FDCA) has the potential to replace terephthalic acid in the synthesis of bio-based resins. The catalytic activity of Co/Mn/Br catalyst and the effect of the fourth metal component for FDCA preparation were investigated. The highest yield of FDCA achieved 76.3% with Co/Mn/Br catalyst. Cu(OAc)2·H2O could greatly reduce the dosage of catalyst without sacrificing the activity, and the highest yield of FDCA with Co/Mn/Br/Cu catalyst was 77.2%. And the reaction processes with Co/Mn/Br catalyst and Co/Mn/Br/Cu catalyst were explored.

Compared with traditional pipe networks, the complexity of air conditioning water systems (ACWSs) and the alternation of cooling and heating are more likely to cause pipe network leakage. Pipe leakage failure seriously affects the reliability of the air conditioning system, and can cause energy waste or reduce human comfort. In this study, a two-stage leakage fault diagnosis (LFD) method based on an Adam optimization BP neural network algorithm, which locates leakage faults based on the change values of monitoring data from flow meters and pressure sensors in air conditioning water systems, is proposed. In the proposed LFD method, firstly, the ACWS network’s hydraulic model is built on the Dymola platform. At the same time, a cuckoo algorithm is used to identify the pipe network’s characteristics to modify the model, and the experimental results show that the relative error between the model-simulated value and the actual values is no more than 1.5%. Secondly, all possible leakage conditions in the network are simulated by the model, and the dataset is formed according to the change rate of the observed data, and is then used to train the LFD model. The proposed LFD method is verified in a practical project, where the average accuracy of the first-stage LFD model in locating the leaking pipe is 86.96%; The average R2 of the second-stage LFD model is 0.9028, and the average error between the predicted location and its exact location with the second-stage LFD model is 6.3% of the total length of the leaking pipe. The results show that the proposed method provides a feasible and convenient solution for timely and accurate detection of pipe network leakage faults in air conditioning water systems.

An endophytic fungus, Phoma sp. NG-25, produces a set of structurally related polyketides including cercosporamide, phomodione, and usnic acid, among which, cercosporamide has been reported to have strong antifungal and anticancer activities. In this study, Phoma sp. NG-25 was grown in seven growth media to determine the optimal culture condition conducive for cercosporamide production. Cercosporamide production peaked on the eighteenth day of incubation in beef peptone dextrose (BPD) broth media. The cercosporamide titer reached to an average of 77.5 µg/mL in BPD. Paper disk diffusion assay revealed that culture filtrate containing cercosporamide as a major constituent inhibited the growth of taxonomically diverse plant pathogens, including ascomycetous, basidiomycetous, and oomycete fungi. Cercosporamide exhibited strong antifungal activities against two pepper anthracnose pathogens, Colletotrichum gloeosporioides and C. scovillei with EC50 values of 3.8 and 7.0 µg/mL, respectively. This study suggests the potential application of cercosporamide as an effective antifungal agent in controlling anthracnose in pepper. [ABSTRACT FROM AUTHOR]

Preparing 2-methoxy-4-methylphenol (MMP) through the vanillin (VAN) route is a crucial step in the high-value utilization of lignin (VTM). In this study, a series of Ni/PB catalysts were synthesized using pseudoboehmite (PB) as a carrier. Changes in the valence states of Ni were induced through H2 activation, while the impacts of reaction temperature, initial pressure, and catalyst addition were investigated based on the VTM process. The results revealed that PB exhibited a distinct mesoporous structure (average pore size of 5.8 nm), with Ni loaded in small particles size (3.88 nm). Ni species on the catalyst existed in a + 2-valence state, undergoing a change after H2 activation, with an increase in Ni0 promoting enhanced activity. The Ni/PB-450 catalyst exhibited excellent activity at 250&#176C for 3 hours (VAN conversion and MMP selectivity > 99%), and the catalyst demonstrated good durability, maintaining 99.1% VAN conversion and 80% MMP selectivity after two cycles. Combining the characterization and experimental results, the etherification and hydrogenation of VAN were identified as the primary reaction pathways. This study aimed to provide a new avenue for the high-value utilization of lignin and its derivatives through controlled catalyst preparation [ABSTRACT FROM AUTHOR]

Effects of the emulsifier type, hydrophilic-lipophilic balance (HLB) value, bio-oil ratio, ultrasonic power density, and ultrasonic time were tested relative to the physicochemical properties and stability of emulsified oils to broaden the use of bio-oil and overcome its defects. The results showed that the turbidity and stabilization times of the emulsified oils reached the maximum values of 184 NTU and 84 min (Span 80 and Tween 80), 191 NTU and 92 min (HLB value of 5), 280 NTU and 92 min (bio-oil ratio of 5%), 191 NTU and 81 min (ultrasonic power density of 0.96 w/mL), 273 NTU and 97 min (ultrasonic time of 20 min), respectively. When the bio-oil to methanol ratio was 1:1, the turbidity value of the emulsified oil reached a maximum value of 664 NTU and the stability time was greater than 24 h. The Fourier transform infrared (FTIR) analysis indicated that the emulsified oil did not delaminate after 30 d, and the uniformity and stability of the emulsified oil were improved. [ABSTRACT FROM AUTHOR]