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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.

BackgroundThe 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.MethodsThe 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.ResultsWe 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.ConclusionThe 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.

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.

Plant pathogens pose major threats on agriculture and horticulture, causing significant economic loss worldwide. Due to the continuous and excessive use of synthetic pesticides, emergence of pesticide resistant pathogens has become more frequent. Thus, there is a growing needs for environmentally-friendly and selective antimicrobial agents with a novel mode of action, which may be used in combination with conventional pesticides to delay development of pesticide resistance. In this study, we evaluated the potentials of lichen substances as novel biopesticides against eight bacterial and twelve fungal plant pathogens that have historically caused significant phytopathological problems in South Korea. Eight lichen substances of diverse chemical origins were extracted from axenic culture or dried specimen, and further purified for comparative analysis of their antimicrobial properties. Usnic acid and vulpinic acid exhibited strong antibacterial activities against Clavibacter michiganensis subsp. michiganensis. In addition, usnic acid and vulpinic acid were highly effective in the growth inhibition of fungal pathogens, such as Diaporthe eres, D. actinidiae, and Sclerotinia sclerotiorum. Intriguingly, the growth of Rhizoctonia solani was specifically inhibited by lecanoric acid, indicating that lichen substances exhibit some degrees of selectivity to plant pathogens. These results suggested that lichen substance can be used as a selective biopesticide for controlling plant disease of agricultural and horticultural significance, minimizing possible emergence of pesticide resistant pathogens in fields.

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.

This study examined the neuroprotective properties of resveratrol (Res) and its target sirtuin1 (SIRT1) against lead (Pb)-mediated toxicity and discovered that both resveratrol treatment and SIRT1 overexpression restored blocked autophagic flux as well as reduced β-amyloid (Aβ) contents. Four-week-old male C57BL/6 mice were employed to consumed 0.2% Pb(Ac)2 solution or deionized water for 3 months followed by 12 months of Res (50 mg/kg BW) or vehicle gavage. In in vitro study, SH-SY5Y cells were pretreated with the SIRT1 activator SRT1720 (2 μM) or the inhibitor EX527 (2 μM) for 2 h, then 25 μM of Pb(Ac)2 was added and incubated for 48 h. Western blotting, RT-qPCR, enzyme-linked immunosorbent assay (ELISA), and Lyso-Tracker Red Staining were next used to estimate the potential alterations of the autophagic pathway as well as BACE1-mediated amyloid processing in response to Pb exposure, respectively. Our data revealed that Res treatment or SIRT1 activation resisted the induction of autophagy by Pb exposure through inhibition of LC3 and Beclin-1 expression and promoted the degradation of Aβ and Tau phosphorylation. Besides, the SIRT1 activator (SRT1720) downregulated the expression of BACE1, the rate-limiting enzyme for Aβ production, by inhibiting the activation of nuclear factor-κB (NF-κB) in Pb-treated SH-SY5Y cells, which resulted in reduced Aβ production. Collectively, we verified the role of Res-SIRT1-autophagy as well as the SIRT1-NF-κB-BACE1 pathway in Pb-induced neuronal cell injury by in vivo or in vitro models. Our findings further elucidate the important role of SIRT1 and Res in counteracting Pb neurotoxicity, which may provide new interventions and targets for the subsequent treatment of neurodegenerative diseases.

A modulated model-free predictive control with minimum switching losses (MSL-MMFPC) is proposed to improve the steady-state performance and reduce the switching losses for a permanent magnet synchronous motor (PMSM) drive system. Firstly, two adjacent current vectors are determined based on the predefined first-level cost function, and then, make the current vector at the next control period equal to the reference current vector by modulating the selected current vectors properly. Additionally, in order to keep optimal control performance also in the over-modulation region, a new rotating coordinate frame is used to adjust the optimal voltage vector. Then, the second-level cost function is designed to select the optimal voltage vector sequence, so that the switching of a VSI leg does not happen during the phase-current maximum, which can reduce the switching losses of the inverter. The simulation and experimental results verify the effectiveness of the proposed control method.

Lichens play significant roles in ecosystem function and comprise about 20% of all known fungi. Polyketide-derived natural products accumulate in the cortical and medullary layers of lichen thalli, some of which play key roles in protection from biotic and abiotic stresses (e.g., herbivore attacks and UV irradiation).

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.

Canopy cover is an important indicator and commonly used in forest management applications. Unmanned-Aerial-Vehicle (UAV)—Borne Laser Scanning (ULS) has drawn increasing attention as a new alternative source for forest field inventory due to its spatial resolution comparable to that of Terrestrial Laser Scanning (TLS). In this study, the performance of plot canopy cover estimations from ULS and TLS is investigated. The experiment was conducted in 16 plots from two Pinus massoniana forests with different stand conditions in Guangxi, China. Both the Canopy Height Model (CHM)-based and Individual Tree Delineation (ITD)-based methods were used to estimate the canopy cover. The influence of CHM pixel sizes on the estimations was also analyzed. Our results demonstrated that the accuracies of ULS (R2: 0.992–0.996, RMSE: 0.591–0.820%) were better than those of TLS (R2: 0.541–0.846, RMSE: 3.642–6.297%) when compared against the reference. The average difference between the ULS and TLS estimations was 6.91%, and the disagreement increased as the forest complexity increased. The reasonable CHM pixel sizes for the canopy cover estimations were 0.07–1.2 m for ULS and 0.07–1.5 m for TLS. This study can provide useful information for the selection of data sources and estimation methods in plot canopy cover mapping.

Despite the fascinating biology of lichens, such as the symbiotic association of lichen-forming fungi (mycobiont) with their photosynthetic partners and their ability to grow in harsh habitats, lack of genetic tools manipulating mycobiont has hindered studies on genetic mechanisms underpinning lichen biology. Thus, we established an Agrobacterium tumefaciens-mediated transformation (ATMT) system for genetic transformation of a mycobiont isolated from Cladonia macilenta. A set of combinations of ATMT conditions, such as input biomass of mycobiont, co-cultivation period with Agrobacterium cells, and incubation temperature, were tested to identify an optimized ATMT condition for the C. macilenta mycobiont. As a result, more than 10 days of co-cultivation period and at least 2 mg of input biomass of the mycobiont were recommended for an efficient ATMT, owing to extremely slow growth rate of mycobionts in general. Moreover, we examined T-DNA copy number variation in a total of 180 transformants and found that 88% of the transformants had a single copy T-DNA insertion. To identify precise T-DNA insertion sites that interrupt gene function in C. macilenta, we performed TAIL-PCR analyses for selected transformants. A hypothetical gene encoding ankyrin repeats at its C-terminus was interrupted by T-DNA insertion in a transformant producing dark-brown colored pigment. Although the identification of the pigment awaits further investigation, this proof-of-concept study demonstrated the feasibility of use of ATMT in construction of a random T-DNA insertion mutant library in mycobionts for studying genetic mechanisms behind the lichen symbiosis, stress tolerance, and secondary metabolite biosynthesis.

Real-time optimal control of air conditioning (AC) is important, and should respond to the condition changes for an energy efficient operation. The traditional optimal control triggering mechanism is based on the “time clock” (called time-driven), and has certain drawbacks (e.g., delayed or unnecessary actions). Thus, an event-driven optimal control (EDOC) was proposed. In previous studies, the part-load ratio (PLR) of chiller plants was used as events to trigger optimal control actions. However, PLR is an indirect indicator of operation efficiency, which could misrepresent the system coefficient of performance (SCOP). This study thus proposes to directly monitor the SCOP deviations from the desired SCOP values. Two events are defined based on transient and cumulative SCOP deviations, which are systematically investigated in terms of energy performance and robustness. The PLR-based and SCOP-based EDOC are compared, in which energy saving and optimal control triggering time are analyzed. Results suggest that SCOP-based EDOC has better energy performance compared with PLR-based EDOC, but the frequent event triggering might happen due to the parameter uncertainty. For actual applications, the SCOP-based EDOC can be recommended when the ideal SCOP model is available with the properly-handled uncertainty. Nevertheless, the PLR-based EDOC could still be a more practical option to replace the traditional TDOC considering its acceptable energy performance and better robustness.