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Abstract Background Psychotic depression (PD) and schizophrenia (SCZ) share overlapping symptoms yet differ in etiology, progression, and treatment approaches. Differentiating these disorders through symptom-based diagnosis is challenging, emphasizing the need for a clearer understanding of their distinct cognitive and neural mechanisms. Aim This study aims to compare cognitive impairments and brain functional activities in PD and SCZ to pinpoint distinguishing characteristics of each disorder. Methods We evaluated cognitive function in 42 PD and 30 SCZ patients using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and resting-state functional magnetic resonance imaging (rs-fMRI). Regional homogeneity (ReHo) values were derived from rs-fMRI data, and group differences in RBANS scores were analyzed. Additionally, Pearson correlation analysis was performed to assess the relationship between cognitive domains and brain functional metrics. Results (1) The SCZ group showed significantly lower RBANS scores than the PD group across all cognitive domains, particularly in visuospatial/constructional ability and delayed memory (p

The physicochemical and structural properties of water soluble dietary fibres (SDF) extracted from navel orange peel modified by superfine grinding were investigated, as well as the immunomodulatory activity in RAW264.7 cells. Results showed that superfine grinding treatment could significantly enhance the extract yield and reduce the particle size of SDF. And the water-holding capacity, swelling capacity, oil-holding capacity, nitrite adsorption capacity and total antioxidant capacity were consequently improved. Modified SDF could significantly decrease the generation of reactive oxygen species (ROS), and promoted the production of NO and some cytokines (IL-1β, TNF-ɑ, MCP-1, and IL-6) in RAW264.7 cells. The expressions of P-P65 and HO-1 in SDF-M200 and SDF-M500 were significantly up-regulated, suggesting that SDF could mildly induce macrophage activation and enhance the immune activity. These indicated that SDF modified by superfine grinding could serve as a promising candidate of immunomodulatory ingredient for functional foods.

AimTo provide a risk prediction for bronchopulmonary dysplasia (BPD) in premature infants under the new diagnostic criteria and establish a prediction model.MethodsIn this study, we retrospectively collected case data on preterm infants admitted to the NICU from August 2015 to August 2018. A lasso analysis was performed to identify the risk factors associated with the development of BPD. A nomogram predictive model was constructed in accordance with the new diagnostic criteria for BPD.ResultA total of 276 preterm infants were included in the study.The incidence of BPD under the 2018 diagnostic criteria was 11.2%. Mortality was significantly higher in the BPD group than the non-BPD group under the 2018 diagnostic criteria (P

Metagenomic shotgun sequencing data can identify microbes and their proportions. But metagenomic shotgun data profiling results obtained from multiple projects using different reference databases are difficult to compare and apply meta-analysis. Our work aims to create a novel collection of human gut prokaryotic genomes, named Microbiome Collection Navigator (MBCN). 2379 human gut metagenomic samples are screened, and 16,785 metagenome-assembled genomes (MAGs) are assembled using a standardized pipeline. In addition, MAGs are combined with the representative genomes from public prokaryotic genomes collections to cluster, and pan-genomes for each cluster's genomes are constructed to build Kraken2 and Bracken databases. The databases built by MBCN are more comprehensive and accurate for profiling metagenomic reads comparing with other collections on simulated reads and virtual bio-projects. We profile 1082 human gut metagenomic samples with MBCN database and organize profiles and metadata on the web program. Meanwhile, using MBCN as a reference database, we also develop a unified, standardized, and systematic metagenomic analysis pipeline and platform, named MicrobiotaCN (http://www.microbiota.cn) and common statistical and visualization tools for microbiome research are integrated into the web program. Taken together, MBCN and MicrobiotaCN can be a valuable resource and a powerful tool that allows researchers to perform metagenomic analysis by a unified pipeline efficiently.

Phenyllactic acid (PhLA), an important natural organic acid, can be used as a biopreservative, monomer of the novel polymeric material poly (phenyllactic acid), and raw material for various medicines. Herein, we achieved a high-level production of PhLA in Escherichia coli through the application of metabolic engineering and fermentation optimization strategies. First, the PhLA biosynthetic pathway was established in E. coli CGSC4510, and the phenylalanine biosynthetic pathway was disrupted to improve the carbon flux toward PhLA biosynthesis. Then, we increased the copy number of the key genes involved in the synthesis of the PhLA precursor phenylpyruvic acid. Concurrently, we disrupted the tryptophan biosynthetic pathway and enhanced the availability of phosphoenolpyruvate and erythrose 4-phosphate, thereby constructing the genetically engineered strain MG-P10. This strain was capable of producing 1.42 ± 0.02 g/L PhLA through shake flask fermentation. Furthermore, after optimizing the dissolved oxygen feedback feeding process and other conditions, the PhLA yield reached 52.89 ± 0.25 g/L in a 6 L fermenter. This study successfully utilized metabolic engineering and fermentation optimization strategies to lay a foundation for efficient PhLA production in E. coli as an industrial application.

Abstract Background Distinguishing untreated major depressive disorder without medication (MDD) from schizophrenia with depressed mood (SZDM) poses a clinical challenge. This study aims to investigate differences in fractional amplitude of low-frequency fluctuations (fALFF) and cognition in untreated MDD and SZDM patients. Methods The study included 42 untreated MDD cases, 30 SZDM patients, and 46 healthy controls (HC). Cognitive assessment utilized the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Resting-state functional magnetic resonance imaging (rs-fMRI) scans were conducted, and data were processed using fALFF in slow-4 and slow-5 bands. Results Significant fALFF changes were observed in four brain regions across MDD, SZDM, and HC groups for both slow-4 and slow-5 fALFF. Compared to SZDM, the MDD group showed increased slow-5 fALFF in the right gyrus rectus (RGR). Relative to HC, SZDM exhibited decreased slow-5 fALFF in the left gyrus rectus (LGR) and increased slow-5 fALFF in the right putamen. Changes in slow-5 fALFF in both RGR and LGR were negatively correlated with RBANS scores. No significant correlations were found between remaining fALFF (slow-4 and slow-5 bands) and RBANS scores in MDD or SZDM groups. Conclusions Alterations in slow-5 fALFF in RGR may serve as potential biomarkers for distinguishing MDD from SZDM, providing preliminary insights into the neural mechanisms of cognitive function in schizophrenia.

IntroductionPine wilt disease spreads rapidly, leading to the death of a large number of pine trees. Exploring the corresponding prevention and control measures for different stages of pine wilt disease is of great significance for its prevention and control.MethodsTo address the issue of rapid detection of pine wilt in a large field of view, we used a drone to collect multiple sets of diseased tree samples at different times of the year, which made the model trained by deep learning more generalizable. This research improved the YOLO v4(You Only Look Once version 4) network for detecting pine wilt disease, and the channel attention mechanism module was used to improve the learning ability of the neural network.ResultsThe ablation experiment found that adding the attention mechanism SENet module combined with the self-designed feature enhancement module based on the feature pyramid had the best improvement effect, and the mAP of the improved model was 79.91%.DiscussionComparing the improved YOLO v4 model with SSD, Faster RCNN, YOLO v3, and YOLO v5, it was found that the mAP of the improved YOLO v4 model was significantly higher than the other four models, which provided an efficient solution for intelligent diagnosis of pine wood nematode disease. The improved YOLO v4 model enables precise location and identification of pine wilt trees under changing light conditions. Deployment of the model on a UAV enables large-scale detection of pine wilt disease and helps to solve the challenges of rapid detection and prevention of pine wilt disease.

AbstractCanine individual identification and parentage testing are essential in various fields, including forensics and breeding programs. This study aimed to develop and validate the Canine 25 A kit, a multiplex polymerase chain reaction (PCR) system designed to address these critical requirements. This novel system enables the simultaneous amplification of 24 canine autosomal short tandem repeat (STR) loci and one sex-determining marker. Validation of the Canine 25 A kit was conducted following the Scientific Working Group on DNA Analysis Methods (SWGDAM) guidelines, demonstrating significant sensitivity, high inhibitor tolerance, canine specificity within a mixture, species specificity, and precision in genotype determination. The Canine 25 A kit was crucial in resolving several forensic cases, such as casework samples from a dog attack incident and parentage determination. Its effectiveness in genotyping these samples highlights its significance in forensic applications. Population genetic parameter analysis revealed a high discriminatory power, as indicated by the calculated combined discrimination power (CDP) values for each breed exceeding 0.999 999 999 999, while the combined power of exclusion (CPE) surpassed 0.9999. Overall, the Canine 25 A kit offers a precise and dependable tool for canine individual identification and parentage determination.

A highly hydrophobic metal mesh has great potential for its application in oil/water separation due to its special wettability. However, most current oil/water separation devices are simple with limited separation capacity. A separation device based on a highly hydrophobic metal mesh was constructed for different types of oil/water mixtures. Experimental results show that the device not only can be used for the continuous separation of binary oil/water mixtures of any density ratios but also can realize the simultaneous separation of heavy oil/water/light oil ternary mixtures. This achievement is meaningful for practical applications, which will gain great interest in the future. HIGHLIGHTS A universal oil/water separation device based on a highly hydrophobic metal mesh was constructed.; The device can be used for sustainable separation of binary oil/water mixtures and heavy oil/water/light oil ternary mixtures.; The constructed device allows simultaneous recovery of light and heavy oils in different channels.;

The cutter of the hand-held tea picker is the key cutting component in the efficient tea harvesting process. In order to solve the problems of large cutting resistance and uneven incision during tea picking, this study fully applied the bionics principle to combine the excellent cutting performance of Aeolesthes induta Newman’s mandibles with the tea cutter, which extracted and fitted the tooth profile structure curve of the upper edge of the Aeolesthes induta Newman’s mandibles. The trapezoidal teeth on the reciprocating cutter of ordinary hand-held tea-picking harvesters were optimized by the fitted curve, and a new tea cutter with the shape of Aeolesthes induta Newman teeth was obtained, which included four kinds of bionic tea-harvesting cutters. The multi-body system software ADAMS 2020 and finite element analysis software ANSYS 2024R1 were used to compare the kinematics, statics and explicit dynamics of cutting properties of the four bionic cutters and common cutters with ordinary trapezoidal teeth and saw teeth. The simulation results showed that the maximum equivalent elastic strain and the maximum cutting force during the cutting operation were reduced by 36.7% and 42.89%, respectively, for the cutting teeth of the bionic tea-harvesting cutter #4 compared with that of the cutter with ordinary trapezoidal teeth. The bionic tea-harvesting cutter designed in this study has better cutting performance than the cutter with traditional cutting teeth, which can effectively reduce the cutting force and improve the flatness and cutting quality of the cutting surface.

Fruit- and vegetable-harvesting robots are a great addition to Agriculture 4.0 since they are gradually replacing human labor in challenging activities. In order to achieve the harvesting process accurately and efficiently, the picking robot’s end-effector should be the first part to come into close contact with the crops. The design and performance requirements of the end-effectors are affected by the fruit and vegetable variety as well as the complexity of unstructured surroundings. This paper summarizes the latest research status of end-effectors for fruit- and vegetable-picking robots. It analyzes the characteristics and functions of end-effectors according to their structural principles and usage, which are classified into clamp, air suction, suction holding, and envelope types. The development and application of advanced technologies, such as the structural design of end-effectors, additional sensors, new materials, and artificial intelligence, were discussed. The typical applications of end-effectors for the picking of different kinds of fruit and vegetables were described, and the advantages, disadvantages, and performance indexes of different end-effectors were given and comparatively analyzed. Finally, challenges and potential future trends of end-effectors for picking robots were reported. This work can be considered a valuable guide to the latest end-effector technology for the design and selection of suitable end-effectors for harvesting different categories of fruit and vegetable crops.

Accurately detecting tea bud leaves is crucial for the automation of tea picking robots. However, challenges arise due to tea stem occlusion and overlapping of buds and leaves, presenting varied shapes of one bud–one leaf targets in the field of view, making precise segmentation of tea bud leaves challenging. To improve the segmentation accuracy of one bud–one leaf targets with different shapes and fine granularity, this study proposes a novel semantic segmentation model for tea bud leaves. The method designs a hierarchical Transformer block based on a self-attention mechanism in the encoding network, which is beneficial for capturing long-range dependencies between features and enhancing the representation of common features. Then, a multi-path feature aggregation module is designed to effectively merge the feature outputs of encoder blocks with decoder outputs, thereby alleviating the loss of fine-grained features caused by downsampling. Furthermore, a refined polarized attention mechanism is employed after the aggregation module to perform polarized filtering on features in channel and spatial dimensions, enhancing the output of fine-grained features. The experimental results demonstrate that the proposed Unet-Enhanced model achieves segmentation performance well on one bud–one leaf targets with different shapes, with a mean intersection over union (mIoU) of 91.18% and a mean pixel accuracy (mPA) of 95.10%. The semantic segmentation network can accurately segment tea bud leaves, providing a decision-making basis for the spatial positioning of tea picking robots.

Abstract In order to solve the problems of difficult control, poor stability, and low control precision in complex autonomous non‐linear systems, and some sensors have non‐linear errors in special environments. Based on the PSO (Particle Swarm Optimization) algorithm, an PSO‐BP‐PID (Particle Swarm Optimization Back Propagation neural network PID) control method and a sensor error compensation algorithm based on BP (Back Propagation) neural network are designed for optimal temperature and humidity control and sensor error compensation in the autonomous greenhouse system. The error between the average temperature value and the target value after steady state is 0.5°C, and the error between the average humidity value and the target value is 1% RH. The results show that the control method can effectively compensate the non‐linear error of the sensor and improve the performance of the control system in a complex environment, which is suitable for the stable and control of actuators in autonomous systems. The error of temperature and humidity sensor is compensated by BP neural network; PSO (Particle Swarm Optimization) was used to optimize the BP‐PID parameters of the automatic greenhouse system.

In order to improve the efficiency of fine segmentation and obstacle removal in the road of tea plantation in hilly areas, a lightweight and high-precision DR-YOLO instance segmentation algorithm is proposed to realize environment awareness. Firstly, the road data of tea gardens in hilly areas were collected under different road conditions and light conditions, and data sets were generated. YOLOv8n-seg, which has the highest operating efficiency, was selected as the basic model. The MSDA-CBAM and DR-Neck feature fusion network were added to the YOLOv8-seg model to improve the feature extraction capability of the network and the feature fusion capability and efficiency of the model. Experimental results show that, compared with the YOLOv8-seg model, the DR-YOLO model proposed in this study has 2.0% improvement in AP@0.5 and 1.1% improvement in Precision. In this study, the DR-YOLO model is pruned and quantitatively compressed, which greatly improves the model inference speed with little reduction in AP. After deploying on Jetson, compared with the YOLOv8n-seg model, the Precision of DR-YOLO is increased by 0.6%, the AP@0.5 is increased by 1.6%, and the inference time is reduced by 17.1%, which can effectively improve the level of agricultural intelligent automation and realize the efficient operation of the instance segmentation model at the edge.

Visual simultaneous localization and mapping (VSLAM) is a foundational technology that enables robots to achieve fully autonomous locomotion, exploration, inspection, and more within complex environments. Its applicability also extends significantly to agricultural settings. While numerous impressive VSLAM systems have emerged, a majority of them rely on static world assumptions. This reliance constrains their use in real dynamic scenarios and leads to increased instability when applied to agricultural contexts. To address the problem of detecting and eliminating slow dynamic objects in outdoor forest and tea garden agricultural scenarios, this paper presents a dynamic VSLAM innovation called MOLO-SLAM (mask ORB label optimization SLAM). MOLO-SLAM merges the ORBSLAM2 framework with the Mask-RCNN instance segmentation network, utilizing masks and bounding boxes to enhance the accuracy and cleanliness of 3D point clouds. Additionally, we used the BundleFusion reconstruction algorithm for 3D mesh model reconstruction. By comparing our algorithm with various dynamic VSLAM algorithms on the TUM and KITTI datasets, the results demonstrate significant improvements, with enhancements of up to 97.72%, 98.51%, and 28.07% relative to the original ORBSLAM2 on the three datasets. This showcases the outstanding advantages of our algorithm.

The mechanism of the combined process of ion beam sputtering (IBS) and HF acid etching on the chemical structure defects of fused silica and its laser damage resistance performance were investigated in this paper. During the removal process of surface material, the sputtering effect causes lattice atoms to flee their native space locations, and a large amount of unsaturated chemical structures are produced on the silica surface, which improves the chemical activity of Si and O atoms, accelerates the chemical reaction process between surface atoms and water molecules, increases the content of hydroxyl groups (OH-) in the shallow layer, and enhances the photothermal weak absorption intensity. However, the increase in hydroxyl content weakens the binding strength of silicon–oxygen bonds, destroys the spatial network structure of silica bulk, and reduces its mechanical strength, resulting in a decrease in its laser damage resistance performance. The paper reveals for the first time the mechanism by which IBS changes the structure characteristics of silica material, accelerates the surface hydroxylation process, and thereby reduces the laser damage resistance performance. This work provides technical guidance for effectively suppressing chemical structure defects on silica surfaces and improving the laser damage resistance performance of optical components under high-flux laser irradiation.

Water-lubricated material is the fundamental ingredient of a water-lubricated bearing (WLB), of which the friction and wear properties directly affect the working performance and service life of a WLB. We designed a micron-scale stripe texture and fabricated a negative microtexture mold by femtosecond laser etching. The microtextures were fabricated onto the surface of Thordon and polyurethane water-lubricated materials by a precision thermoforming machine. Tribological tests showed that the microstripe texture on water-lubricated materials had lower friction and wear properties than that on pristine surface materials. The results demonstrated that the presence of the microstripe texture effectively improved the friction and anti-wear properties of the water-lubricated materials. This study provides a new idea for the design and preparation of water-lubricated materials with good water-lubricating and anti-wear properties.

In order to precisely reproduce the precise seeding process of the population in the air-suction seed-metering device, it is necessary to execute accurate modeling of seed particles using the bonded-particle model, in combination with the discrete element method (DEM) and computational fluid dynamics (CFD). Through the repose angle, slope screening, rotating container, and particle sedimentation experiments, in this paper, the influence of the filling accuracy of the bonded-particle model on the flow behavior and mixing characteristics of the seed population was first explored based on EDEM software. The viability of the suggested modeling approach for pelleted vegetable seeds, as described in this study, was confirmed by comparing experimental and simulation outcomes. The surface roughness values obtained from the studies above were utilized to assess the accuracy of the bonded-particle model in filling. Additionally, a mathematical technique for determining the surface roughness was provided. Furthermore, an analysis of the multiple contacts in the bonded-particle model was also performed. The results indicated that the simulation results closely matched the experimental data when the number of sub-spheres in the bonded-particle model was equal to or more than 70, as measured by the standard deviation. In addition, the most optimal modeling scheme for the pelletized vegetable seed bonded-particles, based on the cost of coupling simulation, was found to be the bonded-particle surface roughness (BS) with a value of 0.1. Ultimately, a practical example was utilized to demonstrate the utilization of the pelleted vegetable seed bonded-particle model and the DEM-CFD coupling approach in analyzing the accuracy of the seeding process in the air-suction seed-metering device. This example will serve as a valuable reference point for future field studies.

Oil spill cleanup in water remains a critical challenge due to the harmful secondary pollution from conventional methods such as burning or chemical degradation. Herein, we present a facile method to fabricate a superhydrophobic and superoleophilic polyurethane (PU) foil for efficient and environmentally friendly oil/water separation. More specifically, micropillar arrays were embedded onto the foil surface through a nanoimprinting process. Microporous structures were generated at the foil cross-section by a supercritical carbon dioxide (CO2) saturation method. The dimensions of pillar and pore structures were optimized with the aim of boosting selective wetting (i.e., water repellency and oil attraction) properties. As a result, the developed PU foil shows an oil absorption efficiency nearly 4 times higher than a pristine reference. Moreover, the structured PU foil stably retains the absorbed oil for over a week, demonstrating an absorption capacity of nearly 400%, which is also much superior than the unstructured sample. Our concept of combining both topographical micropillars and cross-sectional micropores onto PU foil provides a novel approach for achieving efficient and environmental friendly oil/water separation.

The main purpose of this work is to develop a transient analytical model of an industrial tea dryer based on the theory of heat and mass balance, and provide the variation characteristics in tea moisture content and drying air temperature throughout the whole drying process in the drying chamber. A numerical simulation focusing on the established transient analytical model was conducted, and the simulation results show that the moisture content of tea in the drying chamber performs a descend trend along the flow direction over drying time, while the temperature of the dry air performs an ascend trend along the flow direction of tea. The variations coefficient for the tea moisture content and the dry air temperature in the whole drying chamber were determined to be 0.009–0.09 and 0.065–0.126, respectively, indicating that the overall drying process is relatively stable. An actual production drying test was conducted to validate the analytical model, the test results showed that under dynamic drying conditions, the dynamic changes in tea moisture content and dry air temperature in the drying warehouse are consistent with the corresponding trends predicted by the model. Besides, the determination coefficient of tea moisture content is greater than 0.99, the determination coefficient of dry air in the initial drying period is 0.8027, while it is determined to be 0.9872 in the redrying period. The predicted results of the model are in good agreement with the experimental results, which confirms the effectiveness and reliability of the model. The developed transient analytical model can provide a certain reference for the anaphase development of energy optimization, dynamic state monitoring, and parameter matching systems for tea dryer.

Abstract Sarcopenia has become a leading cause of disability and mortality in the elderly. It has been reported that programmed cell death (PCD) is associated with the development of sarcopenia that is characterized by reduction of muscle fiber size and number. TNF-α is also validated to play a prominent role in sarcopenia through its complex signaling pathways including cell death signaling. However, it is still unclear whether TNF-α contributes to sarcopenia by mediating pyroptosis, one type of PCD. Here, we first established naturally aged mice with sarcopenia model and confirmed an inflammatory state represented by TNF-α in aged mice. Evidence of GSDME-mediated pyroptosis and activation of apoptotic caspase-8/-3 were also found in skeletal muscle cells of aged mice with sarcopenia. We demonstrated that TNF-α triggered GSDME-mediated pyroptosis in myotubes through activating caspase-8 and caspase-3 by using caspase-8 and caspase-3 inhibitors. Comparing the activation of caspase-8 and GSDME expression between TNF Complex IIa and TNF Complex IIb, TNF-α was found to be more inclined to assemble TNF Complex IIb in activating caspase-8 and triggering pyroptosis. Moreover, pyroptotic myotubes were validated to result in decreased expression of MHC1 and finally loss of myotubes by knockdown of GSDME. Our work reveals a novel mechanism that TNF-ɑ/caspase-8/caspase-3/GSDME signaling-mediated pyroptosis contributes to the development of sarcopenia. Caspase-3/GSDME signaling-mediated pyroptosis may be a promising therapeutic target for sarcopenia.

OBJECTIVES: Aortic dissection with aberrant right subclavian artery (ARSA) is rare but fatal, with its optimal treatment remaining controversial. In this retrospective study, we presented the outcome of endovascular repair for these patients, aiming to evaluate the efficacy and safety of this technique. MATERIALS AND METHODS: From January 2016 to January 2022, seven patients diagnosed with aortic dissection with ARSA in the First Affiliated Hospital of Sun Yat-sen University were enrolled. All these seven patients received thoracic endovascular aortic repair (TEVAR) within 1 week after their admission to our center. The data of baseline characteristics, imaging parameters, perioperative information, and follow-up were collected till March 2023. RESULTS: The mean age was 48.57 ± 9.41 years. Kommerell diverticulum was found in 2 (28.6%) patients. Among these seven patients, 4 (57.1%) were treated by TEVAR + branched stent graft + chimney technique, 2 (28.6%) were treated by TEVAR + chimney technique, and 1 (14.3%) was treated by TEVAR + chimney and periscope techniques. The mean time of procedures was 196.67 ± 31.18 min. Clinical success was achieved in 6 (85.7%) patients, while 1 (14.3%) patient died of nonaortic related cause. Bird beak configuration was discovered in 4 (57.1%) patients with an average length of 17.87 ± 3.93 mm and angle of 21.9° ±3.70°. One early type I endoleak and one mild cerebral ischemia were discovered, and recovered spontaneously before discharge. The diameter of the aorta remained stable, and no complication was found during the follow-up of the six patients. CONCLUSION: Endovascular repair of aortic dissection with ARSA was feasible and safe, with a favorable early to mid-term outcome.

Abstract Background Pulmonary arterial hypertension (PAH) is characterized by a progressive increase in pulmonary vascular resistance and pulmonary arterial pressure, with complex etiology, difficult treatment and poor prognosis. The objective of this study was to investigate the potential biomarkers for PAH based on bioinformatics analysis. Methods The GSE117261 datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified by screening PAH patients and controls. Then the DEGs were analyzed using a Weighted Gene Co-expression Network Analysis (WGCNA) and the key modules were determined, and to further explore their potential biological functions via Gene Ontology analysis (GO), Kyoto Encyclopedia of Genes and Genomes Pathway analysis (KEGG), and Gene Set Enrichment Analysis (GSEA). Moreover, Protein–protein interaction (PPI) networks were constructed to identify hub gene candidates in the key modules. Finally, real-time quantitative polymerase chain reaction was supplied to detect the expressions of hub genes in human pulmonary arterial smooth cells treated with cobalt chloride (COCl2) which was used to mimic hypoxia. Results There were 2299 DEGs identified. WGCNA indicated that yellow module was the key one correlated with PAH. GO and KEGG analysis demonstrated that genes in the yellow module were mainly enriched in ‘Pathways in cancer’. GSEA revealed that ‘HALLMARK_MYC_TARGETS_V1’ was remarkably enriched in PAH. Based on the PPI network, vascular endothelial growth factor A, proto-oncogene receptor tyrosine kinase (KIT), PNN interacting serine and arginine rich protein (PNISR) and heterogeneous nuclear ribonucleoprotein H1 (HNRNPH1) were identified as the hub genes. Additionally, the PCR indicated that the elevated expressions of PNISR and HNRNPH1 were in line with the bioinformatics analysis. ROC analysis determined that PNISR and HNRNPH1 may be potential biomarkers to provide better diagnosis of PAH. Conclusion PNISR and HNRNPH1 were potential biomarkers to diagnosis PAH. In summary, the identified DEGs, modules, pathways, and hub genes provide clues and shed light on the potential molecular mechanisms of PAH.

Idiopathic pulmonary arterial hypertension (IPAH) is a life-threatening disease with a poor prognosis and high heritability, characterized by elevated pulmonary vascular resistance (PVR) and pulmonary artery pressure. N6-methyladenosine (m6A) RNA modification influences many RNA metabolism pathways. However, the position of m6A methylation regulators in IPAH remains unknown. Therefore, the study aims to disclose the function m6A regulators exert in the pathological mechanisms of IPAH and the immune microenvironment involved. The GSE117261 dataset was downloaded from the Gene Expression Omnibus (GEO) to screen the differentially expressed genes (DEGs) between normal and IPAH samples. Functional and pathway enrichment analyses of DEGs were then conducted by Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG). We also identified the differentially-expressed m6A (DEm6A) regulators between normal and IPAH samples. Key m6A regulators related to the prediction of IPAH were selected using the random forest model. The results showed that FMR1, RBM15, HNRNPA2B1 and IGFBP3 were upregulated in IPAH. In contrast, LRPPRC was downregulated. The single sample gene set enrichment analysis (ssGSEA) method was then adopted to estimate the immune microenvironment in distinct m6A clusters and m6A phenotype-related genes (PRGs) clusters, respectively. Furthermore, we calculated the m6A score via principal component analysis (PCA), and the Sankey diagram was selected to present the correlation among the m6A clusters, m6A PRGs clusters and m6A score. Finally, quantitative RT-PCR and Western blotting were used to validate the key genes in human pulmonary artery smooth muscle cells (HPASMCs) treated by human platelet-derived growth factor-BB (PDGF-BB). The relative mRNA and protein expression levels of FMR1 were significantly elevated, however, the relative mRNA and protein expression levels of LRPPRC were downregulated. Besides, the relative mRNA level of HNRNPA2B1 was increased. Generally, this bioinformatics analysis might provoke more insights into diagnosing and treating IPAH.

ObjectivePrevious studies have established significant differences in the neuroimaging characteristics between healthy controls (HCs) and patients with schizophrenia (SCZ). However, the relationship between homotopic connectivity and clinical features in patients with SCZ is not yet fully understood. Furthermore, there are currently no established neuroimaging biomarkers available for the diagnosis of SCZ or for predicting early treatment response. The aim of this study is to investigate the association between regional homogeneity and specific clinical features in SCZ patients.MethodsWe conducted a longitudinal investigation involving 56 patients with SCZ and 51 HCs. The SCZ patients underwent a 3-month antipsychotic treatment. Resting-state functional magnetic resonance imaging (fMRI), regional homogeneity (ReHo), support vector machine (SVM), and support vector regression (SVR) were used for data acquisition and analysis.ResultsIn comparison to HCs, individuals with SCZ demonstrated reduced ReHo values in the right postcentral/precentral gyrus, left postcentral/inferior parietal gyrus, left middle/inferior occipital gyrus, and right middle temporal/inferior occipital gyrus, and increased ReHo values in the right putamen. It is noteworthy that there was decreased ReHo values in the right inferior parietal gyrus after treatment compared to baseline data.ConclusionThe observed decrease in ReHo values in the sensorimotor network and increase in ReHo values in the right putamen may represent distinctive neurobiological characteristics of patients with SCZ, as well as a potential neuroimaging biomarker for distinguishing between patients with SCZ and HCs. Furthermore, ReHo values in the sensorimotor network and right putamen may serve as predictive indicators for early treatment response in patients with SCZ.

Due to the challenges of pest detection in complex environments, this research introduces a lightweight network for tobacco pest identification leveraging enhancements in YOLOv8 technology. Using YOLOv8 large (YOLOv8l) as the base, the neck layer of the original network is replaced with an asymptotic feature pyramid network (AFPN) network to reduce model parameters. A SimAM attention mechanism, which does not require additional parameters, is incorporated to improve the model’s ability to extract features. The backbone network’s C2f model is replaced with the VoV-GSCSP module to reduce the model’s computational requirements. Experiments show the improved YOLOv8 model achieves high overall performance. Compared to the original model, model parameters and GFLOPs are reduced by 52.66% and 19.9%, respectively, while mAP@0.5 is improved by 1%, recall by 2.7%, and precision by 2.4%. Further comparison with popular detection models YOLOv5 medium (YOLOv5m), YOLOv6 medium (YOLOv6m), and YOLOv8 medium (YOLOv8m) shows the improved model has the highest detection accuracy and lightest parameters for detecting four common tobacco pests, with optimal overall performance. The improved YOLOv8 detection model proposed facilitates precise, instantaneous pest detection and recognition for tobacco and other crops, securing high-accuracy, comprehensive pest identification.

Abstract Background: Bipolar disorder (BD) and schizophrenia (SC) have many similarities in clinical manifestations. The acute phase of BD has psychotic symptoms, while SC also has emotional symptoms during the onset, which suggests that there is some uncertainty in distinguishing BD and SC through clinical symptoms. Aim: To explore the characteristics of brain functional activities and cognitive impairment between BD and SC. Methods: Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) test was performed on patients in drug-naïve BD and SC (50 subjects in each group), and resting-state functional magnetic resonance imaging (rs-fMRI) scanning was performed meanwhile. Rs-fMRI data were routinely preprocessed, and the value of the fractional amplitude of low-frequency fluctuation (fALFF) was calculated. Then each part of the scores of the RBANS and the characteristics of brain function activities were compared between the two groups. Finally used Pearson correlation to analyze the correlation between cognition and brain function. Results: (1) Compared with BD group, all parts of RBANS scores in SC group decreased; (2) The left inferior occipital gyrus (IOG, peak coordinates − 30, -87, -15; t = 4.78, voxel size = 31, Alphasim correction) and the right superior temporal gyrus (STG, peak coordinates 51, -12, 0; t = 5.08, voxel size = 17, AlphaSim correction) were the brain areas with significant difference in fALFF values between BD and SC. Compared with SC group, the fALFF values of the left IOG and the right STG in BD group were increased (p

Fused deposition modeling and sintering (FDMS) is a novel 3D printing technique that combines fused deposition modeling with catalytic debinding and sintering processes to enable the rapid production of metal parts with low energy consumption and costs. Firstly, a 316L/POM composite filament is prepared. Subsequently, test specimens are printed using a fused deposition modeling (FDM) printer, followed by catalytic debinding and sintering processes to create dense metal parts. The process parameters show an influence on the part structure and, subsequently, the properties, and this study examines the microstructural characteristics of the 316L/POM composite filament at each process stage. Using tensile strength as the indicator, an orthogonal experiment is designed to identify suitable combinations of process parameters. Experimental results demonstrate that the FDMS process can manufacture 316L stainless steel parts; moreover, they influence the structure and, consequently, the mechanical behavior, as these are strongly related. By appropriately adjusting the process parameters, this method can be suitable for applications requiring functional parts with less stringent strength requirements.

As the raw material for tea making, the quality of tea leaves directly affects the quality of finished tea. The quality of fresh tea leaves is mainly assessed by manual judgment or physical and chemical testing of the content of internal components. Physical and chemical methods are more mature, and the test results are more accurate and objective, but traditional chemical methods for measuring the biochemical indexes of tea leaves are time-consuming, labor-costly, complicated, and destructive. With the rapid development of imaging and spectroscopic technology, spectroscopic technology as an emerging technology has been widely used in rapid non-destructive testing of the quality and safety of agricultural products. Due to the existence of spectral information with a low signal-to-noise ratio, high information redundancy, and strong autocorrelation, scholars have conducted a series of studies on spectral data preprocessing. The correlation between spectral data and target data is improved by smoothing noise reduction, correction, extraction of feature bands, and so on, to construct a stable, highly accurate estimation or discrimination model with strong generalization ability. There have been more research papers published on spectroscopic techniques to detect the quality of tea fresh leaves. This study summarizes the principles, analytical methods, and applications of Hyperspectral imaging (HSI) in the nondestructive testing of the quality and safety of fresh tea leaves for the purpose of tracking the latest research advances at home and abroad. At the same time, the principles and applications of other spectroscopic techniques including Near-infrared spectroscopy (NIRS), Mid-infrared spectroscopy (MIRS), Raman spectroscopy (RS), and other spectroscopic techniques for non-destructive testing of quality and safety of fresh tea leaves are also briefly introduced. Finally, in terms of technical obstacles and practical applications, the challenges and development trends of spectral analysis technology in the nondestructive assessment of tea leaf quality are examined.

Obstacle avoidance control and navigation in unstructured agricultural environments are key to the safe operation of autonomous robots, especially for agricultural machinery, where cost and stability should be taken into account. In this paper, we designed a navigation and obstacle avoidance system for agricultural robots based on LiDAR and a vision camera. The improved clustering algorithm is used to quickly and accurately analyze the obstacle information collected by LiDAR in real time. Also, the convex hull algorithm is combined with the rotating calipers algorithm to obtain the maximum diameter of the convex polygon of the clustered data. Obstacle avoidance paths and course control methods are developed based on the danger zones of obstacles. Moreover, by performing color space analysis and feature analysis on the complex orchard environment images, the optimal H-component of HSV color space is selected to obtain the ideal vision-guided trajectory images based on mean filtering and corrosion treatment. Finally, the proposed algorithm is integrated into the Three-Wheeled Mobile Differential Robot (TWMDR) platform to carry out obstacle avoidance experiments, and the results show the effectiveness and robustness of the proposed algorithm. The research conclusion can achieve satisfactory results in precise obstacle avoidance and intelligent navigation control of agricultural robots.

BackgroundGlioblastoma multiforme (GBM) is the most lethal brain cancer in adults, characterized by rapid growth, extensive invasiveness, and poor prognosis, and there is still a lack of effective treatments. Here, we aimed to explore the role of triptolide (TPL), purified from Tripterygium wilfordii Hook F, on glioblastoma cell growth, apoptosis, proliferation, migration and invasion, as well as potential underlying mechanisms.MethodsThe publicly available clinical data of Brain Lower Grade Glioma (LGG) from The Cancer Genome Atlas (TCGA) had been screened to observe PROX1 expression. The Kaplan-Meier analysis was used to analyze the relationship between PROX1 expression and GBM prognosis. CCK8, cell cycle, EDU, apoptosis, wound healing, and transwell assays were performed to detect the effects of TPL on glioblastoma U251 cell viability, cell cycle, proliferation, apoptosis, migration and invasion, respectively. Further, a soft agar colony assay was used to calculate the growth of glioblastoma cells. The qRT-PCR and western blot were conducted to quantify PROX1 mRNA and protein levels. The transcriptional regulation of TPL was detected by Dual luciferase reporter assay.ResultsWe found that TPL inhibited glioblastoma cell viability, proliferation, cell cycle, migration and invasion, but enhanced apoptosis in a dose-dependent manner. The expression of cell cycle inhibitor, P21, and pro-apoptosis factor, Bax was increased, while invasion-related factors MMP2 and MMP9 were silenced after TPL treatments. Mechanistically, TPL showed transcriptional inhibition of PROX1 appearance. Moreover, ectopic expression of PROX1 partially rescued the effects of TPL on glioblastoma cell viability, proliferation, apoptosis, migration and invasion, and on the expression of cell function-related genes.ConclusionThis study verified that TPL inhibited the progression of glioblastoma cells by transcriptionally depressing the expression of PROX1.

ObjectivePrior researches have identified distinct differences in neuroimaging characteristics between healthy controls (HCs) and patients with major depressive disorder (MDD). However, the correlations between homotopic connectivity and clinical characteristics in patients with MDD have yet to be fully understood. The present study aimed to investigate common and unique patterns of homotopic connectivity and their relationships with clinical characteristics in patients with MDD.MethodsWe recruited 42 patients diagnosed with MDD and 42 HCs. We collected a range of clinical variables, as well as exploratory eye movement (EEM), event-related potentials (ERPs) and resting-state functional magnetic resonance imaging (rs-fMRI) data. The data were analyzed using correlation analysis, support vector machine (SVM), and voxel-mirrored homotopic connectivity (VMHC).ResultsCompared with HCs, patients with MDD showed decreased VMHC in the insula, and increased VMHC in the cerebellum 8/vermis 8/vermis 9 and superior/middle occipital gyrus. SVM analysis using VMHC values in the cerebellum 8/vermis 8/vermis 9 and insula, or VMHC values in the superior/middle occipital gyrus and insula as inputs can distinguish HCs and patients with MDD with high accuracy, sensitivity, and specificity.ConclusionThe study demonstrated that decreased VMHC in the insula and increased VMHC values in the sensory-motor networks may be a distinctive neurobiological feature for patients with MDD, which could potentially serve as imaging markers to discriminate HCs and patients with MDD.

BackgroundThis study aimed to investigate the relationships between regional neural activity and multiple related indicators in patients with major depressive disorder (MDD).MethodsForty-two patients and 42 healthy controls (HCs) were enrolled. Pearson/Spearman correlation analyses were applied to examine the associations between abnormal regional homogeneity (ReHo) and different indicators in the patients.ResultsCompared with HCs, patients with MDD had increased ReHo in the left inferior temporal gyrus (ITG) and decreased ReHo values in the left putamen, anterior cingulate cortex (ACC), and precentral gyrus. The ReHo of the left putamen was positively correlated with the PR interval, Repeatable Battery for the Assessment of Neuropsychological Status 4A, and Discriminant analysis (D), and negatively correlated with Ae (block) and Ae (total) in the patients. The ReHo value of the left ACC was positively correlated with the severity of depression, Stroop Color Word Test of C − 2B + 100 in reaction time, and negatively correlated with Ce (Missay) and Perseverative Responses in the patients. The ReHo of the left ITG was positively correlated with the Neuroticism scores and negatively correlated with the Lie scores in the patients.ConclusionThese results suggested that the decreased ReHo of the salience network might be the underpinning of cognitive impairments in patients with MDD.

Nitrogen content is one of the essential elements in citrus leaves (CL), and many studies have been conducted to determine the nutrient content in CL using hyperspectral technology. To address the key problem that the conventional spectral data-denoising algorithms directly discard high-frequency signals, resulting in missing effective signals, this study proposes a denoising preprocessing algorithm, complete ensemble empirical mode decomposition with adaptive noise joint sparse representation (CEEMDAN–SR), for CL hyperspectral data. For this purpose, 225 sets of fresh CL were collected at the Institute of Fruit Tree Research of the Guangdong Academy of Agricultural Sciences, to measure their elemental nitrogen content and the corresponding hyperspectral data. First, the spectral data were preprocessed using CEEMDAN–SR, Stein’s unbiased risk estimate and the linear expansion of thresholds (SURE–LET), sparse representation (SR), Savitzky–Golay (SG), and the first derivative (FD). Second, feature extraction was carried out using principal component analysis (PCA), uninformative variables elimination (UVE), and the competitive adaptive re-weighted sampling (CARS) algorithm. Finally, partial least squares regression (PLSR), support vector regression (SVR), random forest (RF), and Gaussian process regression (GPR) were used to construct a CL nitrogen prediction model. The results showed that most of the prediction models preprocessed using the CEEMDAN–SR algorithm had better accuracy and robustness. The prediction models based on CEEMDAN–SR preprocessing, PCA feature extraction, and GPR modeling had an R2 of 0.944, NRMSE of 0.057, and RPD of 4.219. The study showed that the CEEMDAN–SR algorithm can be effectively used to denoise CL hyperspectral data and reduce the loss of effective information. The prediction model using the CEEMDAN–SR+PCA+GPR algorithm could accurately obtain the nitrogen content of CL and provide a reference for the accurate fertilization of citrus trees.

Copper, manganese, and iodine are part of a yak’s required trace elements. However, knowledge about their dietary requirements is scarce. Therefore, an experiment was conducted to evaluate rumen fermentation, blood parameters, and growth performance and screen out the optimum levels of trace elements in yaks’ diet. Here, 18 three-year-old castrated yaks were randomly divided into four groups, which fed with diets containing basal (CON: 4.40, 33.82, and 0 mg/kg) and low-level (LL: 10.00, 40.00, and 0.30 mg/kg), middle-level (ML: 15.00, 50.00, and 0.50 mg/kg), and high-level (HL: 20.00, 60.00, and 0.70 mg/kg) copper, manganese, and iodine for 30 days. With the increase in trace elements, yaks’ daily weight gain (DWG), rumen pH, ammonia nitrogen, microbial protein (MCP), and volatile fatty acids levels and serum triglycerides and urea nitrogen levels showed firstly increasing and then decreasing trends and reached the highest values in ML, and serum ceruloplasmin and total superoxide dismutase (T-SOD) activities showed continuously increasing trends. Yaks’ DWG, rumen MCP, butyrate, and valerate levels and serum triglycerides, urea nitrogen, ceruloplasmin, and T-SOD levels in ML were significantly higher than CON. Therefore, the recommended levels of copper, manganese, and iodine in growing yaks’ diet are 15.00, 50.00, and 0.50 mg/kg (ML), respectively.

Abstract Background Bronchiolar adenoma (BA) is a recently proposed diagnostic terminology, which is considered as the expansion of the concept of ciliated muconodular papillary tumors. BA is considered to be a benign neoplasm, but a few previous cases have been reported with the possibility of malignant transformation. Therefore, the genetic and histological nature of BA is controversial so far. We describe a rare case of multiple BAs with malignant transformation and CCNE1 (cyclin E1) mutation to increase the understanding of this disease. Case description A 56-year-old woman was admitted to our hospital due to two ground-glass nodules (GGNs) in the left lung detected by chest CT without symptom. The pure GGN located in the upper lingual segment about 6 mm in diameter and another mixed GGN located in the dorsal segment about 7 mm. The two GGNs have been found a year ago without treatment, and the mixed GGN become larger to 8 mm with vacuole sign in the next year health checkup. We performed a wedge resection of the two nodules completely by video-assisted thoracoscopy (VATS). Postoperative pathology indicated that the pure GGN was atypical bronchial adenoma, while the mixed GGN was atypical bronchial adenoma with malignant transformation which was missed in frozen section. Gene mutations analysis by next-generation sequencing (NGS) showed CCNE1 gene mutation in both lesions, and her-2 mutation was identified in the mixed GGN. The programmed cell death 1 ligand 1 (PD-L1) expression analysis of tumor cells showed 0% and less than 1% in the pure GGN and the mixed GGN, respectively. Conclusion BA is generally considered to be a benign tumor. The present study indicated that BA may be carcinogenic in atypical cases with some driver genes mutation and we should be vigilant for its potentiality of malignant transformation in clinical practice.

Abstract Introduction Chondroblastoma is a rare, benign locally but aggressive bone tumor. It accounts for

ObjectivePreterm delivery (PTD) is the primary cause of mortality in infants. Mounting evidence indicates that thyroid dysfunction might be associated with an increased risk of PTD, but the dose-dependent association between the continuous spectrum maternal free thyroxine (FT4) and PTD is still not well-defined. This study aimed to further investigate this relationship using a machine learning-based model.MethodsA hospital-based cohort study was conducted from January 2014 to December 2018 in Shanghai, China. Pregnant women who delivered singleton live births and had first-trimester thyroid function data available were included. The generalized additive models with penalized cubic regression spline were applied to explore the non-linear association between maternal FT4 and risk of PTD and also subtypes of PTD. The time-to-event method and multivariable Cox proportional hazard model were further applied to analyze the association of abnormally high and low maternal FT4 concentrations with the timing of PTD.ResultsA total of 65,565 singleton pregnancies with completed medical records and no known thyroid disease before pregnancy were included for final analyses. There was a U-shaped dose-dependent relationship between maternal FT4 in the first trimester and PTD (p 19.7 pmol/L; HR 1.41, 95% CI [1.13–1.76]). The association between isolated hypothyroxinemia and PTD was mainly associated with spontaneous PTD (HR 1.33, 95% CI [1.11–1.59]) while overt hyperthyroidism may be attributable to iatrogenic PTD (HR 1.51, 95% CI [1.18–1.92]) when compared with euthyroid women. Additionally, mediation analysis identified that an estimated 11.80% of the association between overt hyperthyroidism and iatrogenic PTD risk was mediated via the occurrence of hypertensive disorders in pregnancy (p

In order to study the dynamic response of bridge coupling caused by the overlapping of vehicle and railway dynamic loads, by using the time-domain samples of pavement irregularity compiled by MATLAB software and the secondary development function of ANSYS software, the vehicle, bridge, and train models are established in ANSYS software at the same time, and the train supported beam bridge coupling program is compiled with MATLAB software. The model considers the influence of initial conditions and vehicle speed on the system before entering the bridge, the interaction between the coupled large-scale highway and railway bridge system, and the influence of different adverse factors on the system. The influence of a vehicle or train on the bridge structure when the vehicle or train passes through the continuous steel truss bridge under different factors is calculated, respectively, and the displacement and acceleration limits of the bridge are evaluated in combination with the corresponding specifications.

Detection rapidity and model accuracy are the keys to hyperspectral nondestructive testing technology, especially for Pennisetum sinese Roxb (PsR) due to its extremely high adsorptive heavy metal content. The study of the resolution of PsR is conducive to the analysis of the accumulated heavy metal content in its different parts. In this paper, the contents of Cd, Cu and Zn accumulated in the old leaves, young leaves, upper stem, middle stem and lower stem, as well as the hyperspectral data of the corresponding parts, were measured simultaneously in both fresh and dry states. To begin, the spectral data of PsR were preprocessed by using Ensemble Empirical Mode Decomposition-Daubechies3 (EEMD-db3), Savitzky–Golay (SG), Symlet3 (sym3), Symlet5 (sym5), and multiplicative scatter correction (MSC). The 40 samples were divided into 32 training sets and 8 validation sets. The preprocessed spectral data were transformed by the first derivative (FD) and reciprocal logarithm (log(1/R)) to highlight the singularities using binary wavelet decomposition. After screening the significant bands from the correlation curve, the competitive adaptive reweighted sampling (CARS) and successive projection algorithm (SPA) were applied to extract the spectral characteristic variables, which were used to establish the partial least-squares (PLS) regression and multiple stepwise linear regression (MSLR) inversion models of Cd, Cu, and Zn contents. Based on EEMD-db3 pretreatment, the inversion model of Zn in the dry (fresh) state had R2 values of 0.884 (0.880), NRMSE values of 0.179 (0.253) and RPD values of 3.191 (3.221), indicating excellent stability and predictive performance. The findings of this study can not only aid in the rapid nondestructive detection of heavy metal adsorption in various parts of PsR, but can also be applied to guide the development and use of animal feed.

The rhizome of Polygonatum sibiricum is a traditional Chinese medicine material and also a popular functional food consumed in China. Due to the increasing demand and overexploitation, the use of the cultivated plant is growing rapidly. However, the difference in phytochemical profile and health benefit between the cultivated and wild-grown P. sibiricum has not been revealed yet. The objectives of this study are to compare the phytochemical profiles of two types of P. sibiricum, i.e., the cultivated and the wild-grown types, by using UHPLC-Q-Orbitrap-MS based untargeted metabolomics approach. We tentatively identified 190 phytochemicals belonging to alkaloids, flavonoids, phenolic acids, and terpenoids from both two types of samples. In general, there is distinctive difference in phytochemical profiles between these two types of samples. Specifically, 33 phytochemicals showed significant differences. Of these phytochemicals, 22 compounds, such as laetanine, p-coumaroyl-beta-D-glucose, geniposide, medicagenic acid, were significantly higher in cultivated type; 11 compounds, such as vicenin-2, kaempferol 7-neohesperidoside, vanillic acid, and obacunone, were significantly higher in wild-grown type samples. This study will expand our knowledge regarding the cultivated of P. sibiricum and facilitate its further application in pharmaceutical and food industries.

Objective: Autophagy influences a wide range of physiological and pathological processes in the human body. In this study, we aimed to investigate the role of autophagy in early-onset preeclampsia (EOPE); autophagy activation by hypoxia could rescue impaired angiogenesis and apoptosis in preeclampsia, leading by ox-LDL.Methods: Transmission electron microscopy was applied to identify autolysosomes in trophoblast cells of the placenta apical region. Quantitative real-time polymerase chain reaction, Western blot, flow cytometry, and wound-healing assays were adopted to determine autophagy activity, angiogenesis, and apoptosis in placenta tissues or HTR8/SVneo cells.Results: Autophagy activity was inhibited in the placenta of women who experienced EOPE; autophagy activation by hypoxia enhanced the migration ability, rescued ox-LDL–mediated impaired angiogenesis in HTR8/SVneo cells [vascular endothelial growth factor A (VEGFA) downregulation and FMS-like tyrosine kinase-1 (FLT1) upregulation], and protected against cell apoptosis (BAX downregulation).Conclusion: Autophagy could maintain the function of trophoblast cells by differentially regulating the expression of VEGFA and FLT1 and protecting against cell apoptosis at the maternal–fetal interface, potentially related to prevention of preeclampsia.

In the present study, a novel multiplex system, AGCU X-InDel 38 kit, was designed to amplify 38 X-InDel markers and amelogenin in a single Polymerase Chain Reaction (PCR). To demonstrate the suitability and efficiency for forensic applications, a series of validation experiments were conducted, including sensitivity, species specificity, reproducibility, stability, case samples, balance of peak height, size precision, as well as allele frequency and forensic parameter analysis. The results showed that AGCU X-InDel 38 kit was capable to get full profiles even with 62.5 pg of template DNA, and full profiles can be obtained when hematin concentration ≤25 μmol/L, or hemoglobin concentration ≤50 μmol/L, showing good tolerance to six common inhibitors. Moreover, the analyzed case samples indicated that AGCU X-InDel 38 kit had better performance for degraded and trace DNA samples. The 200 unrelated males from Guangdong Han population showed that the combined PDMale and PDFemale were both more than 0.999999999, and the combined MECKrüger, MECKishida, and MECDesmarais Duo were 0.999369481, 0.999999917, and 0.999941556, respectively. Robust discrimination capability of this novel multiplex system could be demonstrated through the high values of forensic parameters. In conclusion, AGCU X-InDel 38 kit is sensitive, precise, reproducible, and highly informative and could be used as a complementary tool for complex and challenging kinship cases.

The accuracy of particle shape characterization is the key to the study of particle dynamics. This study proposes two modeling methods, super-ellipsoid approach (SE) and multi-sphere approach (MS), to describe the discrete element method (DEM) model of soybean seeds with the goal of improving the accuracy of the discrete element analysis model of soybean seeds. The accumulation process, flow behavior, and mixing characteristics of soybean seeds were studied through experiments and DEM simulation. Three comparative verification tests were carried out to compare the accuracy and potential similarity of the SE particle model and the MS particle model: (1) angle of repose experiment; (2) slope screening experiment; and (3) horizontal rotating cylinder experiment. The simulation and experimental results indicated that when compared with the MS particle model, the soybean seed model established using the super-ellipsoid approach can make the described particle shape more accurate, and also reproduce the accumulation process, flow behavior, and mixing characteristics of soybean seeds more accurately. For the multi-sphere approach, the calculation cost for approximating the DEM model of soybean seeds can be saved when the number of sub-spheres is less, but the accuracy of the particle model will be reduced at the same time. In this paper, the DEM model established using the super-ellipsoid approach can accurately simulate the real movement of soybean seeds. Therefore, the model can provide a new numerical calculation method for the simulation of the particle system in the structure of agricultural machinery.

Abstract Background Congenital chloride diarrhea (CCD) in a newborn is a rare autosomal recessive disorder with life-threatening complications, requiring early diagnostics and treatment to prevent severe dehydration and infant mortality. SLC26A3 rs386833481 (c.392C>G; p.P131R) gene polymorphism is an important genetic determinant of CCD. Here, we report the influence of the non-synonymous SLC26A3 variant rs386833481 gene polymorphism on the function of the epithelial barrier and the potential mechanisms of these effects. Results We found that P131R-SLC26A3 increased dysfunction of the epithelial barrier compared with wild type SLC26A3 in human colonic Caco-2 and mouse colonic CMT-93 cells. When P131R-SLC26A3 was subsequently reverted to wild type, the epithelial barrier function was restored similar to wild type cells. Further study demonstrated that variant P131R-SLC26A3 disrupts function of epithelial barrier through two distinct molecular mechanisms: (a) decreasing SLC26A3 expression through a ubiquitination pathway and (b) disrupting a key interaction with its partner ZO-1/CFTR, thereby increasing the epithelial permeability. Conclusion Our study provides an important insight of SLC26A3 SNPs in the regulation of the epithelial permeability and indicates that SLC26A3 rs386833481 is likely a causative mutation in the dysfunction of epithelial barrier of CCD, and correction of this SNP or increasing SLC26A3 function could be therapeutically beneficial for chronic diarrhea diseases.

Abstract Graphene enhanced WO3 has recently become a promising material for various applications. The understanding of the transfer of charge carriers during the photocatalytic processes remains unclear because of their complexity. In this study, the characteristics of the deposited WO3/graphene layered materials were investigated by Raman spectroscopy, UV–vis spectroscopy, and SEM. According to the results, p-graphene exhibits and enhances the characteristics of the WO3/graphene film. The photocatalytic activities of WO3/graphene layered materials were assessed by the photocatalytic degradation of oxytetracycline antibiotics as irradiated by UV light. Here, a higher current of cyclic voltammetry and a higher resistance of impedance spectra were obtained with the as-grown WO3/graphene directly synthesized on Cu foils under UV light using an electrochemical method, which was different from traditional WO3 catalysts. Thus, it is urgent to explore the underlying mechanism in depth. In this study, a large layered material WO3/graphene was fabricated on a Si substrate using a modified CVD method, and a WO3/graphene device was developed by depositing a gold electrode material and compared with a WO3 device. Due to photo-induced doping effects, the current-voltage test suggested that the photo-resistance is larger than dark-resistance, and the photo-current is less than the dark current based on WO3/graphene layered materials, which are significantly different from the characteristics of the WO3 layered material. A new pathway was developed here to analyze the transfer properties of carriers in the photocatalytic process.

Aim: To investigate the genetic polymorphisms of 19 STR loci in the Teochew population of Chaozhou. Subjects and methods: Nineteen STR loci of 631 unrelated Teochew people in Chaozhou were detected by using the AGCU Expressmarker 20 kit. Results: The allele frequency ranged from 0.0008–0.5577. The combined power of discrimination and combined probability of excluding paternity is over 0.999,999,999,999,999,999,999,999,999,999 and 0.999,999,992,549,546, respectively. The principal component analysis based on the 11 shared STR loci showed the Teochew population was most genetically related to the Fujian Han population. Conclusion: The results demonstrate the set of 19 autosomal STRs could provide robust genetics information for individual identification, paternity testing and human genetics research in the Teochew population.

The purpose of this research work is to perform detailed exergetic, energetic and techno-economic analysis of the black tea drying process in the gas-type industrial dryer. Exergy–energy and techno-economic methodology was applied to investigate the heat loss, exergetic and energetic performance, exergy efficiency, improvement potential rate, sustainability index and techno-economic performance of a drying system. The results showed that the heat loss of exhaust air in the late drying process played a main contributing role in the heat loss and exergy loss of the whole drying system. Therefore, the exergy efficiency of the initial drying period and the redrying period varied from 38.08% to 65.09% and 24.76% to 26.97%, respectively. In addition, the improvement potential rate and sustainability index of the whole system varied from 6.93 kW to 12.94 kW and 1.33 to 2.86, respectively. The improvement potential obtained in the present work indicated that the drying operation is greatly in need of exergy performance improvement. Finally, the net present value and payback period obtained from techno-economic analysis were 179,442.03 USD and 5.3 years, the result is useful for investors or contractors to refer to and make investment decisions.

This paper investigates a novel Efficient Dual-branch Bottleneck Network (EDBNet) to perform real-time semantic segmentation tasks on mobile robot systems based on CCD camera. To remedy the non-linear connection between the input and the output, a small-scale and shallow module called the Efficient Dual-branch Bottleneck (EDB) module is established. The EDB unit consists of two branches with different dilation rates, and each branch widens the non-linear layers. This module helps to simultaneously extract local and situational information while maintaining a minimal set of parameters. Moreover, the EDBNet, which is built on the EDB unit, is intended to enhance accuracy, inference speed, and parameter flexibility. It employs dilated convolution with a high dilation rate to increase the receptive field and three downsampling procedures to maintain feature maps with superior spatial resolution. Additionally, the EDBNet uses effective convolutions and compresses the network layer to reduce computational complexity, which is an efficient technique to capture a great deal of information while keeping a rapid computing speed. Finally, using the CamVid and Cityscapes datasets, we obtain Mean Intersection over Union (MIoU) results of 68.58 percent and 71.21 percent, respectively, with just 1.03 million parameters and faster performance on a single GTX 1070Ti card. These results also demonstrate the effectiveness of the practical mobile robot system.