Psychosocial adjustment changes and related factors in young and middle-aged patients with first-episode acute myocardial infarction: a longitudinal study.

AIMS: This study aimed to explore the change trend and group heterogeneity of psychosocial adjustment level and to determine its influencing factors among young and middle-aged patients with first-episode acute myocardial infarction (AMI). METHODS AND RESULTS: The Psychosocial Adjustment Scale of Illness was used to assess the psychosocial adjustment level of the patients at 1, 3, and 6 months after discharge, respectively. Data were analyzed using Pearson correlation analysis, generalized estimating equations, and growth mixed models. A total of 233 patients were included, and their psychosocial adjustment scores at the three-time points were 57.18 ± 15.50, 36.17 ± 15.02, and 24.22 ± 12.98, respectively. The trajectories of changes in patients' psychosocial adjustment levels were divided into three latent categories: moderate adjustment improvement group (72.5%), low adjustment improvement group (16.3%), and persistent maladjustment group (11.2%). Among them, predictors of the persistent maladjustment group included no spouse, low monthly family income per capita, normal body mass index, never smoking, never exercising, combined with hyperlipidemia, low social support, submission coping, and high perceived stress. CONCLUSIONS: The psychosocial adjustment level of young and middle-aged patients with first-episode AMI showed an upward trend within 6 months after discharge, and there was group heterogeneity in the change trajectory of psychosocial adjustment level. It is suggested that a multi-center, large-sample longitudinal study should be carried out in the future, and the time of follow-up investigation should be extended to further clarify the change trajectory and influencing factors of psychosocial adjustment of patients with different subtypes, to provide the theoretical basis for formulating targeted intervention programs.

Impact of CYP2C19, CYP2C9, CYP3A4, and FMO3 Genetic Polymorphisms and Sex on the Pharmacokinetics of Voriconazole after Single and Multiple Doses in Healthy Chinese Subjects.

Voriconazole is the first-line treatment for invasive aspergillosis. Its pharmacokinetics exhibit considerable inter- and intra-individual variability. The purpose of this study was to investigate the effects of CYP2C19, CYP2C9, CYP3A4, and FMO3 genetic polymorphisms and sex on the pharmacokinetics of voriconazole in healthy Chinese adults receiving single-dose and multiple-dose voriconazole, to provide a reference for its clinical individualized treatment. A total of 123 healthy adults were enrolled in the study, with 108 individuals and 15 individuals in the single-dose and multiple-dose doses, respectively. Plasma voriconazole concentrations were measured using a validated LC-MS/MS method, and pharmacokinetics parameters were calculated using the non-compartmental method with WinNonlin 8.2. CYP2C19, CYP2C9, CYP3A4, and FMO3 single-nucleotide polymorphisms were sequenced using the Illumina Hiseq X-Ten platform. The results suggested that CYP2C19 genetic polymorphisms significantly affected the pharmacokinetics of voriconazole at single doses of 4, 6, and 8 mg/kg and multiple doses of voriconazole. CYP3A4 rs2242480 had a significant effect on AUC0-∞ (area under the plasma concentration-time curve from time 0 to infinity) and MRT (mean residence time) of voriconazole at a single dose of 4 mg/kg in CYP2C19 extensive metabolizer. Regardless of the CYP2C19 genotype, CYP2C9 rs1057910 and FMO3 rs2266780 were not associated with the pharmacokinetics of voriconazole at three single-dose levels or multiple doses. No significant differences in most voriconazole pharmacokinetics parameters were noted between male and female participants after single and multiple dosing. For patients receiving voriconazole treatment, CYP2C19 genetic polymorphisms should be genotyped for its precision administration. In contrast, based on our study of healthy Chinese adults, it seems unnecessary to consider the effects of CYP2C9, CYP3A4, and FMO3 genetic polymorphisms on voriconazole pharmacokinetics.

ILKAP Promotes the Metastasis of Hepatocellular Carcinoma Cells by Inhibiting ß-Catenin Degradation and Enhancing the WNT Signaling Pathway.

The incidence of Hepatocellular carcinoma (HCC) and HCC-related deaths have remarkably increased over the recent decades. It has been reported that ß-catenin activation can be frequently observed in HCC cases. This study identified the integrin-linked kinase-associated phosphatase (ILKAP) as a novel ß-catenin-interacting protein. ILKAP is localized both in the nucleus and cytoplasm and regulates the WNT pathway in different ways. First, it is demonstrated that ILKAP activates the WNT pathway in HCC cells by increasing the protein level of ß-catenin and other proteins associated with the WNT signaling, such as c-Myc and CyclinD1. Next, it is shown that ILKAP promotes the metastasis of HCC both in vitro and in vivo in a zebrafish xenograft model. It is also found that ILKAP dephosphorylates the GSK3ß and CK1, contributing to the reduced ubiquitination of ß-catenin. Furthermore, it is identified that ILKAP functions by mediating binding between TCF4 and ß-catenin to enhance expression of WNT target genes. Taken together, the study demonstrates a critical function of ILKAP in metastasis of HCC, since ILKAP is crucial for the activation of the WNT pathway via stabilization of ß-catenin and increased binding between TCF4 and ß-catenin.

Design, synthesis and biological evaluation of novel 1,2,4a,5-tetrahydro-4H-benzo[b][1,4]oxazino[4,3-d][1,4]oxazine-based AAK1 inhibitors with anti-viral property against SARS-CoV-2.

Coronavirus entry into host cells hinges on the interaction between the spike glycoprotein of the virus and the cell-surface receptor angiotensin-converting enzyme 2 (ACE2), initiating the subsequent clathrin-mediated endocytosis (CME) pathway. AP-2-associated protein kinase 1 (AAK1) holds a pivotal role in this pathway, regulating CME by modulating the phosphorylation of the µ subunit of adaptor protein 2 (AP2M1). Herein, we report a series of novel AAK1 inhibitors based on previously reported 1,2,4a,5-tetrahydro-4H-benzo[b] [1,4]oxazino[4,3-d] [1,4]oxazine scaffold. Among 23 synthesized compounds, compound 12e is the most potent one with an IC50 value of 9.38 ± 0.34 nM against AAK1. The in vitro antiviral activity of 12e against SARS-CoV-2 was evaluated using a model involving SARS-CoV-2 pseudovirus infecting hACE2-HEK293 host cells. The results revealed that 12e was superior in vitro antiviral activity against SARS-CoV-2 entry into host cells when compared to SGC-AAK1-1 and LX9211, and its activity was comparable to that of a related and reference compound 8. Mechanistically, all AAK1 inhibitors attenuated AAK1-induced phosphorylation of AP2M1 threonine 156 and disrupted the direct interaction between AP2M1 and ACE2, ultimately inhibiting SARS-CoV-2 infection. Notably, compounds 8 and 12e exhibited a more potent effect in suppressing the phosphorylation of AP2M1 T156 and the interaction between AP2M1 and ACE2. In conclusion, novel AAK1 inhibitor 12e demonstrates significant efficacy in suppressing SARS-CoV-2 infection, and holds promise as a potential candidate for developing novel antiviral drugs against SARS-CoV-2 and other coronavirus infections.

Sustainable Electrochemical Activation of Self-Generated Persulfate for the Degradation of Endocrine Disruptors: Kinetics, Performances, and Mechanisms.

This study presents an electrolysis system utilizing a novel self-circulation process of sulfate (SO42-) and persulfate (S2O82-) ions based on a boron-doped diamond (BDD) anode and an activated carbon fiber (ACF) cathode, which is designed to enable electrochemical remediation of environmental contaminants with reduced use of chemical reagents and minimized residues. The production of S2O82- and hydrogen peroxide (H2O2) on the BDD anode and ACF cathode, respectively, is identified as the source of active radicals for the contaminant degradation. The initiator, sulfate, is identified by comparing the degradation efficiency in NaSO4 and NaNO3 electrolytes. Quenching experiments and electron paramagnetic resonance (EPR) spectroscopy confirmed that the SO4-· and ·OH generated on the ACF cathode are the main reactive radicals. A comparison of the degradation efficiency and the generated S2O82-/H2O2 of the divided/undivided electrolysis system is used to demonstrate the superiority of the synergistic effect between the BDD anode and ACF cathode. This work provides evidence of the effectiveness of the philosophy of "catalysis in lieu of supplementary chemical agents" and sheds light on the mechanism of the generation and transmission of reactive species in the BDD and ACF electrolysis system, thereby offering new perspectives for the design and optimization of electrolysis systems.

Prevention and Potential Treatment Strategies for Respiratory Syncytial Virus.

Respiratory syncytial virus (RSV) is a significant viral pathogen that causes respiratory infections in infants, the elderly, and immunocompromised individuals. RSV-related illnesses impose a substantial economic burden worldwide annually. The molecular structure, function, and in vivo interaction mechanisms of RSV have received more comprehensive attention in recent times, and significant progress has been made in developing inhibitors targeting various stages of the RSV replication cycle. These include fusion inhibitors, RSV polymerase inhibitors, and nucleoprotein inhibitors, as well as FDA-approved RSV prophylactic drugs palivizumab and nirsevimab. The research community is hopeful that these developments might provide easier access to knowledge and might spark new ideas for research programs.

A method for small-sized wheat seedlings detection: from annotation mode to model construction.

The number of seedlings is an important indicator that reflects the size of the wheat population during the seedling stage. Researchers increasingly use deep learning to detect and count wheat seedlings from unmanned aerial vehicle (UAV) images. However, due to the small size and diverse postures of wheat seedlings, it can be challenging to estimate their numbers accurately during the seedling stage. In most related works in wheat seedling detection, they label the whole plant, often resulting in a higher proportion of soil background within the annotated bounding boxes. This imbalance between wheat seedlings and soil background in the annotated bounding boxes decreases the detection performance. This study proposes a wheat seedling detection method based on a local annotation instead of a global annotation. Moreover, the detection model is also improved by replacing convolutional and pooling layers with the Space-to-depth Conv module and adding a micro-scale detection layer in the YOLOv5 head network to better extract small-scale features in these small annotation boxes. The optimization of the detection model can reduce the number of error detections caused by leaf occlusion between wheat seedlings and the small size of wheat seedlings. The results show that the proposed method achieves a detection accuracy of 90.1%, outperforming other state-of-the-art detection methods. The proposed method provides a reference for future wheat seedling detection and yield prediction.

Hydrogen sulfide regulates arsenic-induced cell death in yeast cells by modulating the antioxidative system.

Arsenic (As) is a metal with potentially toxic effects on different organisms. Hydrogen sulfide (H2S) plays a vital role in mitigating heavy metal toxicity by reducing oxidative stress in plants and animals. However, the role of H2S in alleviating arsenic toxicity in yeast cells remains unclear. In this study, the role of NaHS (exogenous physiological H2S) in alleviating As-induced yeast cell death was investigated. Yeast cells in the logarithmic phase were pretreated with 0.05 mmol/L NaHS for 6 h, and then incubated in the YPD medium with or without 1 mmol/L As. After 12 h of treatment, relative survival rate, H2S content, oxidative stress biomarkers, and antioxidant machinery were measured. Our results showed that sodium arsenite-induced yeast cell death and pretreatment with 0.05 mmol/L NaHS significantly alleviated sodium arsenite-induced cell death. Under sodium arsenite conditions, the levels of intracellular reactive oxygen species (ROS) and malondialdehyde (MDA) increased, accompanied by the inhibition of the catalase (CAT) activity and the downregulation of CTT1 expression. However, the activities of the superoxide dismutase (SOD) and glutathion peroxidase (GPX) increased, and the expression of SOD1 and GPX2 was markedly upregulated in the group treated with sodium arsenite. When yeast cells were pretreated with NaHS, the intracellular ROS and MDA levels decreased significantly, and the activities of SOD, CAT, and GPX increased significantly. This was associated with a significant increase in relative survival rate and H2S content compared to the arsenic treatment alone. Our findings indicate that NaHS alleviates sodium arsenite-induced yeast cell death, mainly by enhancing the antioxidant defense system.

Ciprofol is primarily glucuronidated by UGT1A9 and predicted not to cause drug-drug interactions with typical substrates of CYP1A2, CYP2B6, and CYP2C19.

Ciprofol is a novel intravenous anesthetic agent. Its major glucuronide metabolite, M4, is found in plasma and urine. However, the specific isoforms of UDP-glucuronosyltransferases (UGTs) that metabolize ciprofol to M4 remain unknown. This study systematically characterized UGTs that contribute to the formation of M4 using human liver microsomes (HLM), human intestinal microsomes (HIM), and human recombinant UGTs. The inhibitory potential of ciprofol and M4 against major human UGTs and cytochrome P450 enzymes (P450s) was also explored. In vitro-in vivo extrapolation (IVIVE) and physiologically-based pharmacokinetic (PBPK) simulations were performed to predict potential in vivo drug-drug interactions (DDIs) caused by ciprofol. Glucuronidation of ciprofol followed Michaelis-Menten kinetics in both HLM and HIM with apparent Km values of 345 and 412 µM, Vmax values of 2214 and 444 nmol min-1·mg protein-1, respectively. The in vitro intrinsic clearances (CLint = Vmax/Km) for ciprofol glucuronidation by HLM and HIM were 6.4 and 1.1 µL min-1·mg protein-1, respectively. Human recombinant UGT studies revealed that UGT1A9 is the predominant isoform mediating M4 formation, followed by UGT1A7, with UGT1A8 playing a minor role. Ciprofol competitively inhibited CYP1A2 (Ki = 12 µM) and CYP2B6 (Ki = 4.7 µM), and noncompetitively inhibited CYP2C19 (Ki = 29 µM). No time-dependent inhibition by ciprofol was noted for CYP1A2, CYP2B6, or CYP2C19. In contrast, M4 showed limited or no inhibitory effects against selected P450s. Neither ciprofol nor M4 inhibited UGTs significantly. Initial IVIVE suggested potential ciprofol-mediated inhibition of CYP1A2, CYP2B6, and CYP2C19 inhibition in vivo. However, PBPK simulations showed no significant effect on phenacetin, bupropion, and S-mephenytoin exposure or peak plasma concentration. Our findings are pertinent for future DDI studies of ciprofol as either a perpetrator or victim drug.

Psychosocial adaptation profiles in young and middle-aged patients with acute myocardial infarction: a latent profile analysis.

AIMS: We sought to explore the latent classifications of psychosocial adaptation in young and middle-aged patients with acute myocardial infarction (AMI) and analyse the characteristics of different profiles of AMI patients. METHODS AND RESULTS: A cross-sectional study was performed in 438 Chinese young and middle-aged patients with AMI. The investigation time was 1 month after discharge. Three different self-report instruments were distributed to the participants, including the Psychosocial Adjustment to Illness Scale, the Perceived Stress Scale, and the Social Support Rating Scale. The seven dimensions of the Psychosocial Adjustment to Illness Scale were then used to perform a latent profile analysis. All participants signed informed consent forms in accordance with the ethical principles of the Declaration of Helsinki. Finally, a total of 411 young and middle-aged AMI patients were enrolled. Three distinct profiles were identified, including the 'well-adapted group' (44.8%), 'highlight in psychological burdens group' (25.5%), and 'poorly adapted group' (29.7%). The influencing factors included stress perception, social support, occupational type, and marital status (P < 0.05). CONCLUSION: The psychosocial adaptation of young and middle-aged AMI patients can be divided into three profiles. Clinical nurses can carry out individualized psychological interventions according to the characteristics of patients in different potential profiles to improve the psychosocial adaptation of patients and the prognosis of their disease.

Structural biology of voltage-gated calcium channels.

Voltage-gated calcium (Cav) channels mediate Ca2+ influx in response to membrane depolarization, playing critical roles in diverse physiological processes. Dysfunction or aberrant regulation of Cav channels can lead to life-threatening consequences. Cav-targeting drugs have been clinically used to treat cardiovascular and neuronal disorders for several decades. This review aims to provide an account of recent developments in the structural dissection of Cav channels. High-resolution structures have significantly advanced our understanding of the working and disease mechanisms of Cav channels, shed light on the molecular basis for their modulation, and elucidated the modes of actions (MOAs) of representative drugs and toxins. The progress in structural studies of Cav channels lays the foundation for future drug discovery efforts targeting Cav channelopathies.

Comparison of two novel methods for counting wheat ears in the field with terrestrial LiDAR.

BACKGROUND: The metrics for assessing the yield of crops in the field include the number of ears per unit area, the grain number per ear, and the thousand-grain weight. Typically, the ear number per unit area contributes the most to the yield. However, calculation of the ear number tends to rely on traditional manual counting, which is inefficient, labour intensive, inaccurate, and lacking in objectivity. In this study, two novel extraction algorithms for the estimation of the wheat ear number were developed based on the use of terrestrial laser scanning (TLS) in conjunction with the density-based spatial clustering (DBSC) algorithm based on the normal and the voxel-based regional growth (VBRG) algorithm. The DBSC involves two steps: (1) segmentation of the point clouds using differences in the normal vectors and (2) clustering of the segmented point clouds using a density clustering algorithm to calculate the ear number. The VBRG involves three steps: (1) voxelization of the point clouds, (2) construction of the topological relationships between the voxels as a connected region using the k-dimensional tree, and (3) detection of the wheat ears in the connected areas using a regional growth algorithm. RESULTS: The results demonstrated that DBSC and VBRG were promising in estimating the number of ears for different cultivars, planting densities, N fertilization rates, and growth stages of wheat (RMSE = 76 ~ 114 ears/m2, rRMSE = 18.62 ~ 27.96%, r = 0.76 ~ 0.84). Comparing the performance of the two algorithms, the overall accuracy of the DBSC (RMSE = 76 ears/m2, rRMSE = 18.62%, r = 0.84) was better than that of the VBRG (RMSE = 114 ears/m2, rRMSE = 27.96%, r = 0.76). It was found that with the DBSC, the calculation in points as units permitted more detailed information to be retained, and this method was more suitable for estimation of the wheat ear number in the field. CONCLUSIONS: The algorithms adopted in this study provide new approaches for non-destructive measurement and efficient acquisition of the ear number in the assessment of the wheat yield phenotype.

Structural basis for human Cav1.2 inhibition by multiple drugs and the neurotoxin calciseptine.

Cav1.2 channels play crucial roles in various neuronal and physiological processes. Here, we present cryo-EM structures of human Cav1.2, both in its apo form and in complex with several drugs, as well as the peptide neurotoxin calciseptine. Most structures, apo or bound to calciseptine, amlodipine, or a combination of amiodarone and sofosbuvir, exhibit a consistent inactivated conformation with a sealed gate, three up voltage-sensing domains (VSDs), and a down VSDII. Calciseptine sits on the shoulder of the pore domain, away from the permeation path. In contrast, when pinaverium bromide, an antispasmodic drug, is inserted into a cavity reminiscent of the IFM-binding site in Nav channels, a series of structural changes occur, including upward movement of VSDII coupled with dilation of the selectivity filter and its surrounding segments in repeat III. Meanwhile, S4-5III merges with S5III to become a single helix, resulting in a widened but still non-conductive intracellular gate.

Small and Oriented Wheat Spike Detection at the Filling and Maturity Stages Based on WheatNet.

Accurate wheat spike detection is crucial in wheat field phenotyping for precision farming. Advances in artificial intelligence have enabled deep learning models to improve the accuracy of detecting wheat spikes. However, wheat growth is a dynamic process characterized by important changes in the color feature of wheat spikes and the background. Existing models for wheat spike detection are typically designed for a specific growth stage. Their adaptability to other growth stages or field scenes is limited. Such models cannot detect wheat spikes accurately caused by the difference in color, size, and morphological features between growth stages. This paper proposes WheatNet to detect small and oriented wheat spikes from the filling to the maturity stage. WheatNet constructs a Transform Network to reduce the effect of differences in the color features of spikes at the filling and maturity stages on detection accuracy. Moreover, a Detection Network is designed to improve wheat spike detection capability. A Circle Smooth Label is proposed to classify wheat spike angles in drone imagery. A new micro-scale detection layer is added to the network to extract the features of small spikes. Localization loss is improved by Complete Intersection over Union to reduce the impact of the background. The results show that WheatNet can achieve greater accuracy than classical detection methods. The detection accuracy with average precision of spike detection at the filling stage is 90.1%, while it is 88.6% at the maturity stage. It suggests that WheatNet is a promising tool for detection of wheat spikes.

C-C Bond Cleavage Mediated Reaction for Constructing 3-Carbonyl Imidazo[1,5-a] Pyridines from 1,3-Dicarbonyl Compounds and Pyridin-2-ylmethanamines.

A [4 + 1] cyclization and C-C bond cleavage process mediated reaction for constructing 3-carbonyl imidazo[1,5-a] pyridines from 1,3-dicarbonyl compounds and pyridin-2-ylmethanamines has been developed. Various 1,3-dicarbonyl compounds are applicable, and selectivity could be achieved. Importantly, this strategy could be extended to an atom economy method by employing a cyclic 1,3-dicarbonyl compound, and it provided a new view for C-C bond cleavage reactions.

SPSI: A Novel Composite Index for Estimating Panicle Number in Winter Wheat before Heading from UAV Multispectral Imagery.

Rapid and accurate estimation of panicle number per unit ground area (PNPA) in winter wheat before heading is crucial to evaluate yield potential and regulate crop growth for increasing the final yield. The accuracies of existing methods were low for estimating PNPA with remotely sensed data acquired before heading since the spectral saturation and background effects were ignored. This study proposed a spectral-textural PNPA sensitive index (SPSI) from unmanned aerial vehicle (UAV) multispectral imagery for reducing the spectral saturation and improving PNPA estimation in winter wheat before heading. The effect of background materials on PNPA estimated by textural indices (TIs) was examined, and the composite index SPSI was constructed by integrating the optimal spectral index (SI) and TI. Subsequently, the performance of SPSI was evaluated in comparison with other indices (SI and TIs). The results demonstrated that green-pixel TIs yielded better performances than all-pixel TIs apart from TI[HOM], TI[ENT], and TI[SEM] among all indices from 8 types of textural features. SPSI, which was calculated by the formula DATT[850,730,675] + NDTICOR[850,730], exhibited the highest overall accuracies for any date in any dataset in comparison with DATT[850,730,675], TINDRE[MEA], and NDTICOR[850,730]. For the unified models assembling 2 experimental datasets, the RV2 values of SPSI increased by 0.11 to 0.23, and both RMSE and RRMSE decreased by 16.43% to 38.79% as compared to the suboptimal index on each date. These findings indicated that the SPSI is valuable in reducing the spectral saturation and has great potential to better estimate PNPA using high-resolution satellite imagery.

HIB/SPOP inhibits Ci/Gli-mediated tumorigenesis by modulating the RNA Polymerase II components stabilities.

Hedgehog (Hh) signaling mediated by transcription factor Ci/Gli plays a vital role in embryonic development and adult tissue homeostasis in invertebrates and vertebrates, whose dysregulation leads to many human disorders, including cancer. However, till now, cofactors of Ci/Gli which can affect tumorigenesis are not well known. Here, through genetic screen, we find overexpression of active Ci alone is not sufficient to generate tumor-like eye phenotype in Drosophila, however, its overexpression combined with knockdown of hib causes a striking tumor-like big eye phenotype. Mechanistically, HIB/SPOP inhibits Ci/Gli-mediated tumorigenesis by modulating the RNA polymerase II (RNAPII) components Rpb3/Rpb7 stabilities in E3 ligase dependent manner. In addition, Ci/Gli can promote HIB/SPOP-mediated Rpb7/Rpb3 degradation. Taken together, our results indicate Ci/Gli needs to hook up with suitable RNAPII together to achieve the tumor-like eye phenotype and HIB/SPOP plays dual roles through controlling Ci/Gli and Rpb3/Rpb7 protein stabilities to temper Ci/Gli/RNAPII-mediated tumorigenesis.

Interaction of Genotype, Environment, and Management on Organ-Specific Critical Nitrogen Dilution Curve in Wheat.

The organ-specific critical nitrogen (Nc) dilution curves are widely thought to represent a new approach for crop nitrogen (N) nutrition diagnosis, N management, and crop modeling. The Nc dilution curve can be described by a power function (Nc = A1·W-A2), while parameters A1 and A2 control the starting point and slope. This study aimed to investigate the uncertainty and drivers of organ-specific curves under different conditions. By using hierarchical Bayesian theory, parameters A1 and A2 of the organ-specific Nc dilution curves for wheat were derived and evaluated under 14 different genotype × environment × management (G × E × M) N fertilizer experiments. Our results show that parameters A1 and A2 are highly correlated. Although the variation of parameter A1 was less than that of A2, the values of both parameters can change significantly in response to G × E × M. Nitrogen nutrition index (NNI) calculated using organ-specific Nc is in general consistent with NNI estimated with overall shoot Nc, indicating that a simple organ-specific Nc dilution curve may be used for wheat N diagnosis to assist N management. However, the significant differences in organ-specific Nc dilution curves across G × E × M conditions imply potential errors in Nc and crop N demand estimated using a general Nc dilution curve in crop models, highlighting a clear need for improvement in Nc calculations in such models. Our results provide new insights into how to improve modeling of crop nitrogen-biomass relations and N management practices under G × E × M.

[Relationship Between Urban Spatial Pattern and Thermal Environment Response in Summer: A Case Study of Hefei City].

With the continuous expansion of cities, the land cover type of the region is transformed, a large number of natural landscapes are replaced by man-made landscapes, and the environmental temperature rises. The study of the response relationship between urban spatial pattern and thermal environment provides some guidance for improving the ecological environment and optimizing the urban spatial layout. Based on the Landsat 8 series remote sensing image data of Hefei City in 2020 and analysis platforms such as ENVI and ARCGIS, Pearson correlation and profile lines were used to reflect the correlation between the two. Then, the three spatial pattern components with the greatest correlation were selected to construct multiple regression functions to investigate the influence of urban spatial pattern on urban thermal environment and its mechanism of action. The results showed that:① the high temperature area of Hefei City increased significantly with the advance of time during 2013-2020. For different seasons, the urban heat island effect showed that summer>autumn>spring>winter. ② In the central urban area, the building occupancy, building height, imperviousness occupancy, and population density were significantly higher than those in the suburbs, whereas fractional vegetation coverage presented a higher suburban than urban area and mainly showed a point distribution in the urban area and an irregular distribution of water bodies. ③ The urban high-temperature zone was mainly distributed in various development zones in urban areas, whereas other places in urban areas were dominated by medium-high temperature and above-temperature zoning, and suburban areas were dominated by medium-low temperature. ④ The Pearson coefficients between the spatial pattern of each element and the thermal environment were positively correlated with the building occupancy (0.395), impervious surface occupancy (0.333), population density (0.481), and building height (0.188) and negatively correlated with fractional vegetation coverage (-0.577) and water occupancy (-0.384). The coefficients of the constructed multiple regression functions, including building occupancy, population density, and fractional vegetation coverage, were 8.372, 0.295, and -5.639 respectively, with a constant of 38.555. The results of this study can provide a reference basis for optimizing urban spatial layouts and improving urban living quality.

Improving multi-scale detection layers in the deep learning network for wheat spike detection based on interpretive analysis.

BACKGROUND: Detecting and counting wheat spikes is essential for predicting and measuring wheat yield. However, current wheat spike detection researches often directly apply the new network structure. There are few studies that can combine the prior knowledge of wheat spike size characteristics to design a suitable wheat spike detection model. It remains unclear whether the complex detection layers of the network play their intended role. RESULTS: This study proposes an interpretive analysis method for quantitatively evaluating the role of three-scale detection layers in a deep learning-based wheat spike detection model. The attention scores in each detection layer of the YOLOv5 network are calculated using the Gradient-weighted Class Activation Mapping (Grad-CAM) algorithm, which compares the prior labeled wheat spike bounding boxes with the attention areas of the network. By refining the multi-scale detection layers using the attention scores, a better wheat spike detection network is obtained. The experiments on the Global Wheat Head Detection (GWHD) dataset show that the large-scale detection layer performs poorly, while the medium-scale detection layer performs best among the three-scale detection layers. Consequently, the large-scale detection layer is removed, a micro-scale detection layer is added, and the feature extraction ability in the medium-scale detection layer is enhanced. The refined model increases the detection accuracy and reduces the network complexity by decreasing the network parameters. CONCLUSION: The proposed interpretive analysis method to evaluate the contribution of different detection layers in the wheat spike detection network and provide a correct network improvement scheme. The findings of this study will offer a useful reference for future applications of deep network refinement in this field.