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Most of the research on driving stability control of distributed drive electric vehicles is based on a yaw motion design controller. The designed controller can improve the lateral stability of the vehicle well but rarely mentions...
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Most of the research on driving stability control of distributed drive electric vehicles is based on a yaw motion design controller. The designed controller can improve the lateral stability of the vehicle well but rarely mentions its changes to the roll and pitch motion of the body, and the uneven distribution of the driving force will also cause instability in the vehicle speed, resulting in wheel transition slip, wheel sideslip, and vehicle stability loss. In order to improve the spatial stability of distributed-driven electric vehicles and resolve the control instability caused by their motion coupling, a decoupled control strategy of yaw, roll, and pitch motion based on multi-objective constraints was proposed. The strategy adopts hierarchical control logic. At the upper level, a yaw motion controller based on robust model predictive control, a roll motion controller, and a pitch motion controller based on feedback optimal control are designed. In the lower level, through the motion coupling analysis of the vehicle yaw control process, based on the coupling analysis, the vehicle yaw, roll, and pitch decoupling controller based on multi-objective constraints is designed. Finally, the effectiveness of the decoupling controller is verified.
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An essential feature of modern high-yielding rice varieties is the production of numerous spikelets, but the physiological mechanism underlying spikelet formation in these varieties remains unclear. In this study, we explored the ...
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An essential feature of modern high-yielding rice varieties is the production of numerous spikelets, but the physiological mechanism underlying spikelet formation in these varieties remains unclear. In this study, we explored the characteristics of spikelet differentiation and degeneration and the relevant physiological characteristics of rice varieties with different panicle sizes. The regulatory effects of alternate wetting and moderate soil drying (AWMD) on spikelet formation were also measured. We determined that the high spikelet number per panicle and grain yields of large-panicle rice varieties were primarily due to a higher number of differentiated and surviving secondary spikelets. Furthermore, shoot dry weight, plant nitrogen (N) uptake, plant N concentration, non-structural carbohydrate (NSC) accumulation in stems, leaf area, and leaf photosynthetic rate from branch differentiation stage (BDS) to spikelet differentiation stage (SDS) were positively correlated with the number of differentiated secondary spikelets per panicle. Plant N concentration, NSC accumulation in stems, and leaf photosynthetic rate at pollen mother cell meiosis (PMC) were negatively correlated with the number of degenerated secondary spikelets. Finally, the number of differentiated secondary spikelets of Huaidao 5 (small panicle size) and Yongyou 2640 (large panicle size) varieties was promoted by 19.2% and 6.6%, and the number of degenerated secondary spikelets was reduced by 14.4% and 6.3%, respectively, under AWMD treatment compared to continuously flooded treatment. Prominent spikelet formation under AWMD resulted from the shoot dry weight, plant N uptake, plant N concentration, NSC accumulation in stems, leaf area, and leaf photosynthetic rate. Collectively, improvements in these key aboveground indices mentioned above during the BDS to SDS and the plant N concentration, NSC accumulation in stems, and leaf photosynthetic rate at the PMC stage would benefit spikelet formation by promoting differentiation and reducing degeneration of secondary spikelets, thereby enhancing yield of large-panicle rice varieties.
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ABSTRACT Wastewater-based surveillance is a valuable approach for monitoring COVID-19 at community level. Monitoring SARS-CoV-2 variants of concern (VOC) in wastewater has become increasingly relevant when clinical testing capacit...
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ABSTRACT Wastewater-based surveillance is a valuable approach for monitoring COVID-19 at community level. Monitoring SARS-CoV-2 variants of concern (VOC) in wastewater has become increasingly relevant when clinical testing capacity and case-based surveillance are limited. In this study, we ascertained the turnover of six VOC in Alberta wastewater from May 2020 to May 2022. Wastewater samples from nine wastewater treatment plants across Alberta were analysed using VOC-specific RT-qPCR assays. The performance of the RT-qPCR assays in identifying VOC in wastewater was evaluated against next generation sequencing. The relative abundance of each VOC in wastewater was compared to positivity rate in COVID-19 testing. VOC-specific RT-qPCR assays performed comparatively well against next generation sequencing; concordance rates ranged from 89% to 98% for detection of Alpha, Beta, Gamma, Omicron BA.1 and Omicron BA.2, with a slightly lower rate of 85% for Delta ( p < 0.01). Elevated relative abundance of Alpha, Delta, Omicron BA.1 and BA.2 were each associated with increased COVID-19 positivity rate. Alpha, Delta and Omicron BA.2 reached 90% relative abundance in wastewater within 80, 111 and 62 days after their initial detection, respectively. Omicron BA.1 increased more rapidly, reaching a 90% relative abundance in wastewater after 35 days. Our results from VOC surveillance in wastewater correspond with clinical observations that Omicron is the VOC with highest disease burden over the shortest period in Alberta to date. The findings suggest that changes in relative abundance of a VOC in wastewater can be used as a supplementary indicator to track and perhaps predict COVID-19 burden in a population.
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Background Protein-energy wasting (PEW) is a common complication in patients with peritoneal dialysis (PD). Few investigations involved risk factors identification and predictive model construction related to PEW. We aimed to deve...
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Background Protein-energy wasting (PEW) is a common complication in patients with peritoneal dialysis (PD). Few investigations involved risk factors identification and predictive model construction related to PEW. We aimed to develop a nomogram to predict PEW risk in patients with peritoneal dialysis. Methods We collected data from end-stage renal disease (ESRD) patients who regularly underwent peritoneal dialysis between January 2011 and November 2022 at two hospitals retrospectively. The outcome of the nomogram was PEW. Multivariate logistic regression screened predictors and established a nomogram. We measured the predictive performance based on discrimination ability, calibration, and clinical utility. Evaluation indicators were receiver operating characteristic (ROC), calibrate curve, and decision curve analysis (DCA). The performance calculation of the internal validation cohort validated the nomogram. Results In this study, 369 enrolled patients were divided into development (n = 210) and validation (n = 159) cohorts according to the proportion of 6:4. The incidence of PEW was 49.86%. Predictors were age, dialysis duration, glucose, C-reactive protein (CRP), creatinine clearance rate (Ccr), serum creatinine (Scr), serum calcium, and triglyceride (TG). These variables showed a good discriminate performance in development and validation cohorts (ROC = 0.769, 95% CI [0.705–0.832], ROC = 0.669, 95% CI [0.585–0.753]). This nomogram was adequately calibrated. The predicted probability was consistent with the observed outcome. Conclusion This nomogram can predict the risk of PEW in patients with PD and provide valuable evidence for PEW prevention and decision-making.
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An imbalance in oxidative and inflammatory regulation is the main contributor to intervertebral disc degeneration (IDD). Hydrogen (H2) therapy is a promising antioxidation and anti-inflammatory approach. However, the key to the tr...
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An imbalance in oxidative and inflammatory regulation is the main contributor to intervertebral disc degeneration (IDD). Hydrogen (H2) therapy is a promising antioxidation and anti-inflammatory approach. However, the key to the treatment is how to maintain the long-term effective H2 concentration in the intervertebral disc (IVD). Therefore, we developed a pH-responsive delivery of H2 through ammonia borane-loaded hollow polydopamine (AB@HPDA) for IDD therapy, which has sufficient capacity to control long-term H2 release in an acid-dependent manner in degenerative IVD. The characterization, toxicity, and pH-responsive H2 release of AB@HPDA was detected in vitro. The metabolization of AB@HPDA in the degenerated IVD was tested by in vivo imaging. The therapeutic effect of AB@HPDA on IDD was tested in vivo by X-ray, MRI, water content of the disc, and histological changes. Nuclear extracellular matrix (ECM) components, oxidative stress, and inflammation were also tested to explore potential therapeutic mechanisms. AB@HPDA has good biocompatibility at concentrations less than 500? μ g/mL. The H2 release of AB@HPDA was pH responsive. Therefore, AB@HPDAs can provide efficient hydrogen therapy with controlled H2 release in response to the acidic degenerated IVD microenvironment. The metabolization of AB@HPDA in IVD was slow and lasted up to 11 days. HPDA and AB@HPDA significantly inhibited IDD, as tested by X-ray, MRI, disc water content, and histology ( ). pH-responsive H2 delivery through AB@HPDAs has the potential to efficiently treat IDD by inhibiting ECM degradation and rebalancing oxidative stress and inflammation in degenerative IVDs.
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Although bone mesenchymal stem cell (BMSC) transplantation has been applied to the treatment of spinal cord injury (SCI), the effect is unsatisfactory due to the specific microenvironment (inflammation and oxidative stress) in the...
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Although bone mesenchymal stem cell (BMSC) transplantation has been applied to the treatment of spinal cord injury (SCI), the effect is unsatisfactory due to the specific microenvironment (inflammation and oxidative stress) in the SCI area, which leads to the low survival rate of transplanted cells. Thus, additional strategies are required to improve the efficacy of transplanted cells in the treatment of SCI. Hydrogen possesses antioxidant and anti-inflammatory properties. However, whether hydrogen can enhance the effect of BMSC transplantation in the treatment of SCI has not yet been reported. This study was aimed at investigating whether hydrogen promotes the therapeutic effect of BMSC transplantation in the treatment of SCI in rats. In vitro, BMSCs were cultured in a normal medium and a hydrogen-rich medium to study the effect of hydrogen on the proliferation and migration of BMSCs. BMSCs were treated with a serum-deprived medium (SDM), and the effects of hydrogen on the apoptosis of BMSCs were studied. In vivo, BMSCs were injected into the rat model of SCI. Hydrogen-rich saline (5?ml/kg) and saline (5?ml/kg) were given once a day via intraperitoneal injection. Neurological function was evaluated using the Basso, Beattie, and Bresnahan (BBB) and CatWalk gait analyses. Histopathological analysis, oxidative stress, inflammatory factors (TNF- α , IL-1 β , and IL-6), and transplanted cell viability were detected at 3 and 28 days after SCI. Hydrogen can significantly enhance BMSC proliferation and migration and tolerance to SDM. Hydrogen and BMSC codelivery can significantly enhance neurological function recovery by improving the transplant cell survival rate and migration. Hydrogen can enhance the migration and proliferation capacity of BMSCs to repair SCI by reducing the inflammatory response and oxidative stress in the injured area. Hydrogen and BMSC codelivery is an effective method to improve BMSC transplantation in the treatment of SCI.
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The real-time polymerase chain reaction (PCR), commonly known as quantitative PCR (qPCR), is increasingly common in environmental microbiology applications. During the COVID-19 pandemic, qPCR combined with reverse transcription (R...
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The real-time polymerase chain reaction (PCR), commonly known as quantitative PCR (qPCR), is increasingly common in environmental microbiology applications. During the COVID-19 pandemic, qPCR combined with reverse transcription (RT-qPCR) has been used to detect and quantify SARS-CoV-2 in clinical diagnoses and wastewater monitoring of local trends. Estimation of concentrations using qPCR often features a log-linear standard curve model calibrating quantification cycle (Cq) values obtained from underlying fluorescence measurements to standard concentrations. This process works well at high concentrations within a linear dynamic range but has diminishing reliability at low concentrations because it cannot explain “non-standard” data such as Cq values reflecting increasing variability at low concentrations or non-detects that do not yield Cq values at all. Here, fundamental probabilistic modeling concepts from classical quantitative microbiology were integrated into standard curve modeling approaches by reflecting well-understood mechanisms for random error in microbial data. This work showed that data diverging from the log-linear regression model at low concentrations as well as non-detects can be seamlessly integrated into enhanced standard curve analysis. The newly developed model provides improved representation of standard curve data at low concentrations while converging asymptotically upon conventional log-linear regression at high concentrations and adding no fitting parameters. Such modeling facilitates exploration of the effects of various random error mechanisms in experiments generating standard curve data, enables quantification of uncertainty in standard curve parameters, and is an important step toward quantifying uncertainty in qPCR-based concentration estimates. Improving understanding of the random error in qPCR data and standard curve modeling is especially important when low concentrations are of particular interest and inappropriate analysis can unduly affect interpretation, conclusions regarding lab performance, reported concentration estimates, and associated decision-making.
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Goal-driven top-down mechanism plays important role in the case of object detection and recognition. In this paper, we propose a top-down computational model for goal-driven saliency detection based on the coding-based classificat...
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Goal-driven top-down mechanism plays important role in the case of object detection and recognition. In this paper, we propose a top-down computational model for goal-driven saliency detection based on the coding-based classification framework. It consists of four successive steps: feature extraction, descriptor coding, contextual pooling and saliency prediction. Particularly, we investigate the effect of spatial context information for saliency detection, and propose a block-wise spatial pooling operation to take advantage of contextual cues in multiple neighborhood scales and orientations. The experimental results on three datasets demonstrate that our method can effectively exploit contextual information and achieves the state-of-the-art performance on top-down saliency detection task.
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Mesenchymal stromal cells (MSC) have great potential for cellular therapies as they can be directed to differentiate into certain lineages or to exert paracrine effects at sites of injury. The interactions between stromal cell-der...
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Mesenchymal stromal cells (MSC) have great potential for cellular therapies as they can be directed to differentiate into certain lineages or to exert paracrine effects at sites of injury. The interactions between stromal cell-derived factor (SDF)-1 and its receptors CXCR4 and CXCR7 play pivotal roles in the migration of MSC to injured tissues. We evaluated whether a histone deacetylase inhibitor valproic acid (VPA) modulates the migration of cord blood (CB-) derived MSC towards SDF-1 and their proliferation and differentiation. We found that in MSC, VPA increased (i) the gene and total protein expression of CXCR4 and CXCR7 and primed migration towards a low gradient of SDF-1, (ii) the gene expression of MMP-2 and secretion and activation of proMMP-2, (iii) the proliferation and gene expression of pluripotency markers SOX2 and Oct-4, and exposure to lower concentrations of VPA (≤5 mM) had no effect on their differentiation to osteocytes and chondrocytes. Thus, our study indicates that VPA enhances the migration of CB MSC towards SDF-1 by increasing the expression of CXCR4, CXCR7, and MMP-2. VPA at low concentrations may be used for ex vivo treatment of MSC to increase their recruitment to sites of injury without compromising their ability to proliferate or differentiate.
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Calreticulin, an endoplasmic reticulum (ER) resident protein, affects many critical cellular functions, including protein folding and calcium homeostasis. Using embryonic stem cells and 3T3-L1 preadipocytes, we show that calreticu...
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Calreticulin, an endoplasmic reticulum (ER) resident protein, affects many critical cellular functions, including protein folding and calcium homeostasis. Using embryonic stem cells and 3T3-L1 preadipocytes, we show that calreticulin modulates adipogenesis. We find that calreticulin-deficient cells show increased potency for adipogenesis when compared with wild-type or calreticulin-overexpressing cells. In the highly adipogenic crt ?/? cells, the ER lumenal calcium concentration was reduced. Increasing the ER lumenal calcium concentration led to a decrease in adipogenesis. In calreticulin-deficient cells, the calmodulin–Ca2+/calmodulin-dependent protein kinase II (CaMKII) pathway was up-regulated, and inhibition of CaMKII reduced adipogenesis. Calreticulin inhibits adipogenesis via a negative feedback mechanism whereby the expression of calreticulin is initially up-regulated by peroxisome proliferator–activated receptor γ (PPARγ). This abundance of calreticulin subsequently negatively regulates the expression of PPARγ, lipoprotein lipase, CCAAT enhancer–binding protein α, and aP2. Thus, calreticulin appears to function as a Ca2+-dependent molecular switch that regulates commitment to adipocyte differentiation by preventing the expression and transcriptional activation of critical proadipogenic transcription factors.
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