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This study proposed a high-speed precision dual-chamber maize metering device for the dense planting pattern with standard ridge promoted in China. Through theoretical analysis of the sowing process, parameters for the key components have been designed. The metering device is capable of planting two rows in a single pass for high-speed precision seeding. The effect of operating speed and negative pressure on seed metering quality was investigated. A high-speed camera was used to capture the trajectory of maize seed at different operating speeds, and it was found that intra-row shifts were caused by collisions at the mouth of the seed guide tube and rotation of the seed as it fell. Employing a two-factor, five-level orthogonal rotation test, Investigated the optimal operating parameters for the maize metering device. Response surface analysis showed that optimum seed metering quality was achieved at 14.2 km/h and 13.5 kPa. Validation tests showed a qualified rate of 97.93%, with a coefficient variation of 8.97% for this method. Additionally, an energy consumption analysis indicated a reduction in operating energy consumption of approximately 32% compared to conventional air suction seed metering devices for dense planting with large ridges on the same area of farmland. This study provides insights for reducing energy consumption in the seeding process, contributing to the sustainable development of agricultural resources.

Abstract Background Metagenomic next-generation sequencing (mNGS) has become a powerful tool for pathogen detection, but the value of human sequencing reads generated from it is underestimated. Methods A total of 138 patients with pleural effusion (PE) were diagnosed with tuberculous pleurisy (TBP, N = 82), malignant pleural effusion (MPE, N = 35), or non-TB infection (N = 21), whose PE samples all underwent mNGS analysis. Clinical TB tests including culture, Acid-Fast Bacillus (AFB) test, Xpert, and T-SPOT, were performed. To utilize mNGS for MPE identification, 25 non-MPE samples (20 TBP and 5 non-TB infection) were randomly selected to set human chromosome copy number baseline and generalized linear modeling was performed using copy number variant (CNV) features of the rest 113 samples (35 MPE and 78 non-MPE). Results The performance of TB detection was compared among five methods. T-SPOT demonstrated the highest sensitivity (61% vs. culture 32%, AFB 12%, Xpert 35%, and mNGS 49%) but with the highest false-positive rate (10%) as well. In contrast, mNGS was able to detect TB-genome in nearly half (40/82) of the PE samples from TBP subgroup, with 100% specificity. To evaluate the performance of using CNV features of the human genome for MPE prediction, we performed the leave-one-out cross-validation (LOOCV) in the subcohort excluding the 25 non-MPE samples for setting copy number standards, which demonstrated 54.1% sensitivity, 80.8% specificity, 71.7% accuracy, and an AUC of 0.851. Conclusion In summary, we exploited the value of human and non-human sequencing reads generated from mNGS, which showed promising ability in simultaneously detecting TBP and MPE.

Background and objective Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) is the first choice for first-line treatment of advanced patients with EGFR positive non-small cell lung cancer (NSCLC). For advanced NSCLC patients with negative drive gene and positive programmed cell death ligand 1 (PD-L1) or highly expressed NSCLC patients, the first-line treatment recommends immune checkpoint inhibitors (ICIs) monotherapy or ICIs combined chemotherapy. Therefore, the first-line treatment strategy for advanced NSCLC patients with EGFR positive at different PD-L1 expression levels is worth further exploring. Many previous studies have suggested that the expression of PD-L1 is obviously affected by EGFR mutation, and the expression of PD-L1 is likely to be related to the mechanism of EGFR-TKIs resistance. The purpose of this study was to analyze the expression characteristics of PD-L1 in patients with advanced EGFR positive NSCLC and its relationship with the efficacy of EGFR-TKIs. Methods 159 patients with newly diagnosed advanced NSCLC with EGFR positive (including 141 patients with EGFR sensitive mutations) were enrolled to analyze the relationship between clinicopathological characteristics and PD-L1 expression. The factors affecting the therapeutic effect of EGFR-TKIs in 141 patients with EGFR sensitive mutations were also explored. Results The PD-L1 expression of the included patients was classified according to the tumor promotion score (TPS): negative (TPS

ObjectivesOsteoporosis may contribute to failure of unicompartmental knee arthroplasty (UKA), yet the prevalence of osteoporosis in the population awaiting UKA has not been adequately studied. The objectives of this study were to report the prevalence of osteoporosis in people awaiting UKA and the rate of anti-osteoporosis treatment, and to explore factors associated with osteoporosis prevalence in people awaiting UKA.MethodsParticipants awaiting UKA from January 2019 to May 2023 were consecutively enrolled. Participants ‘ age, gender, BMI, knee K-L score, VAS score, history of previous DXA testing, history of anti-osteoporosis treatment, and possible underlying risk factors were recorded. All participants were given a dual-energy x-ray absorptiometry (DXA) test after the visit. The diagnosis of osteoporosis was made according to the World Health Organization criteria. Compare the prevalence of osteoporosis between people waiting for UKA and the general population. Risk factors associated with osteoporosis were analyzed using multiple linear regression and binary logistic regression models.ResultsA total of 340 participants were included in the study, 259 in female and 81 in male, with a mean age of 63.53 years (range: 41-84 years), and all participants completed UKA and had DXA prior to UKA. The prevalence of osteoporosis was 40.88% (44.79% in female and 28.40% in male). The prevalence of osteoporosis was higher in female than in male (p

In order to accurately establish a discrete element model for the whole plant flexibility of upright rice during the harvesting period, several physical characteristics, such as geometric features, moisture content, and density, of the entire rice plant were measured, along with frictional properties, such as the static and rolling friction coefficients, and mechanical properties, including the elastic modulus and restitution coefficient. A flexible and upright discrete element model of the rice plant was established using the DEM method based on the Hertz–Mindlin (no slip) and Hertz–Mindlin with bonding mechanical models. The parameters were optimized through Plackett–Burman screening experiments, steepest ascent experiments, and Box–Behnken optimization experiments to accurately determine the discrete element model parameters of each component of the rice plant. The calibration process of the contact parameters between rice grains and steel was analyzed in detail as an example, resulting in a calibration error of 0.68% for the natural repose angle. Taking the calibration of the contact parameters between the main stem and steel as an example, a detailed analysis of the calibration process was conducted. The calibration resulted in a calibration error of 2.76% for the natural repose angle and 2.33% for deflection. This study lays the foundation for understanding the mechanical response of rice and machinery when they are coupled together. Additionally, it provides valuable references for establishing discrete element models of plant species other than rice.

Abstract Cross-modal analysis of the same whole brain is an ideal strategy to uncover brain function and dysfunction. However, it remains challenging due to the slow speed and destructiveness of traditional whole-brain optical imaging techniques. Here we develop a new platform, termed Photoacoustic Tomography with Temporal Encoding Reconstruction (PATTERN), for non-destructive, high-speed, 3D imaging of ex vivo rodent, ferret, and non-human primate brains. Using an optimally designed image acquisition scheme and an accompanying machine-learning algorithm, PATTERN extracts signals of genetically-encoded probes from photobleaching-based temporal modulation and enables reliable visualization of neural projection in the whole central nervous system with 3D isotropic resolution. Without structural and biological perturbation to the sample, PATTERN can be combined with other whole-brain imaging modalities to acquire the whole-brain image with both high resolution and morphological fidelity. Furthermore, cross-modal transcriptome analysis of an individual brain is achieved by PATTERN imaging. Together, PATTERN provides a compatible and versatile strategy for brain-wide cross-modal analysis at the individual level.

A number of pH-sensitive fluorescent proteins exist which enable monitoring of some but not all steps of exocytosis. Here the authors engineer a bright, photostable red pH-sensitive fluorescent protein, pHmScarlet, to allow visualisation of the docking and fusion events of exocytosis.