3D Morphological Feature Quantification and Analysis of Corn Leaves.

Marked variations in the 3-dimensional (3D) shape of corn leaves can be discerned as a function of various influences, including genetics, environmental factors, and the management of cultivation processes. However, the causes of these variations remain unclear, primarily due to the absence of quantitative methods to describe the 3D spatial morphology of leaves. To address this issue, this study acquired 3D digitized data of ear-position leaves from 478 corn inbred lines during the grain-filling stage. We propose quantitative calculation methods for 13 3D leaf shape features, such as the leaf length, 3D leaf area, leaf inclination angle, blade-included angle, blade self-twisting, blade planarity, and margin amplitude. Correlation analysis, cluster analysis, and heritability analysis were conducted among the 13 leaf traits. Leaf morphology differences among subpopulations of the inbred lines were also analyzed. The results revealed that the 3D leaf traits are capable of revealing the morphological differences among different leaf surfaces, and the genetic analysis revealed that 84.62% of the 3D phenotypic traits of ear-position leaves had a heritability greater than 0.3. However, the majority of 3D leaf shape traits were strongly affected by environmental conditions. Overall, this study quantitatively investigated 3D leaf shape in corn, providing a reliable basis for further research on the genetic regulation of corn leaf morphology and advancing the understanding of the complex interplay among crop genetics, phenotypes, and the environment.

Confinement controls the directional cell responses to fluid forces.

Our understanding of how fluid forces influence cell migration in confining environments remains limited. By integrating microfluidics with live-cell imaging, we demonstrate that cells in tightly-but not moderately-confined spaces reverse direction and move upstream upon exposure to fluid forces. This fluid force-induced directional change occurs less frequently when cells display diminished mechanosensitivity, experience elevated hydraulic resistance, or sense a chemical gradient. Cell reversal requires actin polymerization to the new cell front, as shown mathematically and experimentally. Actin polymerization is necessary for the fluid force-induced activation of NHE1, which cooperates with calcium to induce upstream migration. Calcium levels increase downstream, mirroring the subcellular distribution of myosin IIA, whose activation enhances upstream migration. Reduced lamin A/C levels promote downstream migration of metastatic tumor cells by preventing cell polarity establishment and intracellular calcium rise. This mechanism could allow cancer cells to evade high-pressure environments, such as the primary tumor.

Predicting the oil content of individual corn kernels combining NIR-HSI and multi-stage parameter optimization techniques.

Predicting the oil content of individual corn kernels using hyperspectral imaging and ML offers the advantages of being rapid and non-destructive. However, traditional methods rely on expert experience for setting parameters. In response to these limitations, this study has designed an innovative multi-stage grid search technique, tailored to the characteristics of spectral data. Initially, the study automatically screening the best model from up to 504 algorithm combinations. Subsequently, multi-stage grid search is utilized for improving precision. We collected 270 kernel samples from different parts of the ear from 15 high oil and regular corn materials, with oil contents ranging from 1.4% to 13.1%. Experimental results show that the combinations SG + NONE+KS + PLSR(R2: 0.8570) and MA + LAR+Random+MLR(R2: 0.8523) performed optimally. After parameter optimization, their R2 values increased to 0.9045 and 0.8730, respectively. Additionally, the ACNNR model achieved an R2 of 0.8878 and an RMSE of 0.2243. The improved algorithm significantly outperforms traditional methods and ACNNR model in prediction accuracy and adaptability, offering an effective method for field applications.

Phenotype identification and genome-wide association study of ear-internode vascular bundles in maize (Zea mays).

The vascular bundle in the ear-internode of maize is a key conduit for transporting photosynthetic materials between "source" and "sink", making it critically important to examine its micro-phenotypes and genetic architecture to identify advantageous characteristics and cultivate high-yielding and high-quality varieties. Unfortunately, the limited observation methods and scope of study precludes any comprehensive and systematic investigations into the microscopic phenotypes and genetic mechanisms of vascular bundle in maize ear-internode. In this study, 47 phenotypic traits were extracted in 495 maize inbred lines using micro computed tomography (Micro-CT) scanning technology and a deep learning-based phenotype acquisition method for stem vascular bundle, which included stem slice-related, epidermis zone-related, periphery zone-related, inner zone-related and vascular bundles-related traits. Phenotypic analysis indicated that there was extensive phenotypic variation of vascular bundle traits in ear-internode, especially that in the inner zone. Of these, 30 phenotypic traits with heritability greater than 0.70 were conducted for GWAS, and a total of 4,225 significant SNPs and 416 candidate genes with detailed functional annotations were identified. Furthermore, 20 genes were highly expressed in stem-related tissues, especially in maize internodes. Functional analysis of candidate genes indicated that the pathways obtained for candidate genes of different trait groups were distinct, mainly involved in vitamin synthesis and metabolism, transport of substances, carbohydrate derivative catabolic process, protein transport and localization, and anatomical structure development. The results of this study will help to further understand the phenotypic traits of stem vascular bundles and provide a reference for revealing the genetic mechanism of maize ear-internode vascular bundles.

Cloning and functional mechanism of the dwarf gene gba affecting stem elongation and cellulose biosynthesis in jute (Corchorus olitorius).

Plant height (PH) is an important factor affecting bast fiber yield in jute. Here, we report the mechanism of dwarfism in the 'Guangbaai' (gba) of jute. The mutant gba had shorter internode length and cell length compared to the standard cultivar 'TaiZi 4' (TZ4). Exogenous GA3 treatment indicated that gba is a GA-insensitive dwarf mutant. Quantitative trait locus (QTL) analysis of three PH-related traits via a high-density genetic linkage map according to re-seq showed that a total of 25 QTLs were identified, including 13 QTLs for PH, with phenotypic variation explained ranging from 2.42 to 74.16%. Notably, the functional mechanism of the candidate gene CoGID1a, the gibberellic acid receptor, of the major locus qPHIL5 was evaluated by transgenic analysis and virus-induced gene silencing. A dwarf phenotype-related single nucleotide mutation in CoGID1a was identified in gba, which was also unique to the dwarf phenotype of gba among 57 cultivars. Cogid1a was unable to interact with the growth-repressor DELLA even in the presence of highly accumulated gibberellins in gba. Differentially expressed genes between transcriptomes of gba and TZ4 after GA3 treatment indicated up-regulation of genes involved in gibberellin and cellulose synthesis in gba. Interestingly, it was found that up-regulation of CoMYB46, a key transcription factor in the secondary cell wall, by the highly accumulated gibberellins in gba promoted the expression of cellulose synthase genes CoCesA4 and CoCesA7. These findings provide valuable insights into fiber development affected by endogenous gibberellin accumulation in plants.

Three-Dimensional Modeling of Maize Canopies Based on Computational Intelligence.

The 3-dimensional (3D) modeling of crop canopies is fundamental for studying functional-structural plant models. Existing studies often fail to capture the structural characteristics of crop canopies, such as organ overlapping and resource competition. To address this issue, we propose a 3D maize modeling method based on computational intelligence. An initial 3D maize canopy is created using the t-distribution method to reflect characteristics of the plant architecture. The subsequent model considers the 3D phytomers of maize as intelligent agents. The aim is to maximize the ratio of sunlit leaf area, and by iteratively modifying the azimuth angle of the 3D phytomers, a 3D maize canopy model that maximizes light resource interception can be constructed. Additionally, the method incorporates a reflective approach to optimize the canopy and utilizes a mesh deformation technique for detecting and responding to leaf collisions within the canopy. Six canopy models of 2 varieties plus 3 planting densities was constructed for validation. The average R2 of the difference in azimuth angle between adjacent leaves is 0.71, with a canopy coverage error range of 7% to 17%. Another 3D maize canopy model constructed using 12 distinct density gradients demonstrates the proportion of leaves perpendicular to the row direction increases along with the density. The proportion of these leaves steadily increased after 9 × 104 plants ha-1. This study presents a 3D modeling method for the maize canopy. It is a beneficial exploration of swarm intelligence on crops and generates a new way for exploring efficient resources utilization of crop canopies.

Neurological manifestations of SARS-CoV-2 infection in children in Taiwan: A cross-section, multicenter study.

BACKGROUND: The SARS-CoV-2 virus has been a global public health threat since December 2019. This study aims to investigate the neurological characteristics and risk factors of coronavirus disease 2019 (COVID-19) in Taiwanese children, using data from a collaborative registry. METHODS: A retrospective, cross-sectional, multi-center study was done using an online network of pediatric neurological COVID-19 cohort collaborative registry. RESULTS: A total of 11160 COVID-19-associated emergency department (ED) visits and 1079 hospitalizations were analyzed. Seizures were the most common specific neurological symptom, while encephalitis and acute disseminated encephalomyelitis (ADEM) was the most prevalent severe involvement. In ED patients with neurological manifestations, severe neurological diagnosis was associated with visual hallucination, seizure with/without fever, behavior change, decreased GCS, myoclonic jerk, decreased activity/fatigue, and lethargy. In hospitalized patients with neurological manifestations, severe neurological diagnosis was associated with behavior change, visual hallucination, decreased GCS, seizure with/without fever, myoclonic jerk, fatigue, and hypoglycemia at admission. Encephalitis/ADEM was the only risk factor for poor neurological outcomes at discharge in hospitalized patients. CONCLUSION: Neurological complications are common in pediatric COVID-19. Visual hallucination, seizure, behavior change, myoclonic jerk, decreased GCS, and hypoglycemia at admission are the most important warning signs of severe neurological involvement such as encephalitis/ADEM.

Clinical value of oral contrast-enhanced ultrasonography in diagnosis of gastric tumors.

BACKGROUND: The incidence of gastric cancer remains high, and it is the sixth most common cancer and the fourth leading cause of cancer deaths worldwide. Oral contrast-enhanced ultrasonography is a simple, non-invasive, and painless method for the diagnosis of gastric tumors. AIM: To explore the diagnostic value of oral contrast-enhanced ultrasonography for the detection of gastric tumors. METHODS: The screening results based on oral contrast-enhanced ultrasonography and electronic gastroscopy were compared with those of the postoperative pathological examination. RESULTS: Among 42 patients with gastric tumors enrolled in the study, the diagnostic accordance rate was 95.2% for oral contrast-enhanced ultrasonography (n = 40) and 90.5% for electronic gastroscopy (n = 38) compared with postoperative pathological examination. The Kappa value of consistency test with pathological findings was 0.812 for oral contrast-enhanced ultrasonography and 0.718 for electronic gastroscopy, and there was no significant difference between them (P = 0.397). For the TNM staging of gastric tumors, the accuracy rate of oral contrast-enhanced ultrasonography was 81.9% for the overall T staging and 50%, 77.8%, 100%, and 100% for T1, T2, T3, and T4 staging, respectively. The sensitivity and specificity were both 100% for stages T3 and T4. The diagnostic accuracy rate of oral contrast-enhanced ultrasonography was 93.8%, 80%, 100%, and 100% for stages N0, N1-N3, M0, and M1, respectively. CONCLUSION: The accordance rate of qualitative diagnosis by oral contrast-enhanced ultrasonography is comparable to that of gastroscopy, and it could be used as the preferred method for the early screening of gastric tumors.

Calligraphy of Nanoplasmonic Bioink-Based Multiplex Immunosensor for Precision Immune Monitoring and Modulation.

Immunomodulation therapies have attracted immense interest recently for the treatment of immune-related diseases, such as cancer and viral infections. This new wave of enthusiasm for immunomodulators, predominantly revolving around cytokines, has spurred emerging needs and opportunities for novel immune monitoring and diagnostic tools. Considering the highly dynamic immune status and limited window for therapeutic intervention, precise real-time detection of cytokines is critical to effectively monitor and manage the immune system and optimize the therapeutic outcome. The clinical success of such a rapid, sensitive, multiplex immunoanalytical platform further requires the system to have ease of integration and fabrication for sample sparing and large-scale production toward massive parallel analysis. In this article, we developed a nanoplasmonic bioink-based, label-free, multiplex immunosensor that can be readily "written" onto a glass substrate via one-step calligraphy patterning. This facile nanolithography technique allows programmable patterning of a minimum of 3 µL of nanoplasmonic bioink in 1 min and thus enables fabrication of a nanoplasmonic microarray immunosensor with 2 h simple incubation. The developed immunosensor was successfully applied for real-time, parallel detection of multiple cytokines (e.g., interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and transforming growth factor-beta (TGF-ß)) in immunomodulated macrophage samples. This integrated platform synergistically incorporates the concepts of nanosynthesis, nanofabrication, and nanobiosensing, showing great potential in the scalable production of label-free multiplex immunosensing devices with superior analytical performance for clinical applications in immunodiagnostics and immunotherapy.

Nocturnal Bladder Function and Sleep in the Children with Refractory Nocturnal Enuresis: A Prospective Study.

OBJECTIVE: To prospectively investigate the nocturnal bladder function and sleep in children with refractory primary monosymptomatic nocturnal enuresis (RPMNE). MATERIALS AND METHODS: Fifty-three children diagnosed with RPMNE and 30 controls who had upper urinary tract abnormality but without any voiding problems were included in the study. RPMNE patients underwent a standardized investigation protocol, including the Pittsburgh Sleep Quality Index (PSQI) questionnaire, a 7-day bladder diary, and the simultaneous ambulatory urodynamic monitoring and polysomnography (PSG); controls were evaluated using the PSQI questionnaire and PSG. RESULTS: The children with RPMNE were subdivided into the nocturnal detrusor overactivity (NDO) case group and the non-NDO case group. The children in the NDO case group had a higher percentage of total sleep time in light sleep and a lower percentage in the N3 sleep stage than those in the non-NDO case group and control group (P <.05). The cortical arousal index and PSQI scores of both RPMNE subgroups were higher compared to the control group (P <.05). The incidences of reduced nocturnal bladder capacity (NBC) in the NDO case group were higher than in the non-NDO case group (P <.05). The frequency of involuntary detrusor contractions during sleep was positively correlated with cortical arousal index in the NDO case group (r = 0.811, P <.0001). CONCLUSION: In addition to the reduced NBC, the RPMNE is related to abnormal NDO, increased light sleep period, and cortical arousal dysfunction. Moreover, there is a certain correlation between the abnormal degrees of NDO and cortical arousal dysfunction.

Investigating the genetic basis of maize ear characteristics: a comprehensive genome-wide study utilizing high-throughput phenotypic measurement method and system.

The morphology of maize ears plays a critical role in the breeding of new varieties and increasing yield. However, the study of traditional ear-related traits alone can no longer meet the requirements of breeding. In this study, 20 ear-related traits, including size, shape, number, and color, were obtained in 407 maize inbred lines at two sites using a high-throughput phenotypic measurement method and system. Significant correlations were found among these traits, particularly the novel trait ear shape (ES), which was correlated with traditional traits: kernel number per row and kernel number per ear. Pairwise comparison tests revealed that the inbred lines of tropical-subtropical were significantly different from other subpopulations in row numbers per ear, kernel numbers per ear, and ear color. A genome-wide association study identified 275, 434, and 362 Single nucleotide polymorphisms (SNPs) for Beijing, Sanya, and best linear unbiased prediction scenarios, respectively, explaining 3.78% to 24.17% of the phenotypic variance. Furthermore, 58 candidate genes with detailed functional descriptions common to more than two scenarios were discovered, with 40 genes being associated with color traits on chromosome 1. After analysis of haplotypes, gene expression, and annotated information, several candidate genes with high reliability were identified, including Zm00001d051328 for ear perimeter and width, zma-MIR159f for ear shape, Zm00001d053080 for kernel width and row number per ear, and Zm00001d048373 for the blue color channel of maize kernels in the red-green-blue color model. This study emphasizes the importance of researching novel phenotypic traits in maize by utilizing high-throughput phenotypic measurements. The identified genetic loci enrich the existing genetic studies related to maize ears.

Three-dimensional branch segmentation and phenotype extraction of maize tassel based on deep learning.

BACKGROUND: The morphological structure phenotype of maize tassel plays an important role in plant growth, reproduction, and yield formation. It is an important step in the distinctness, uniformity, and stability (DUS) testing to obtain maize tassel phenotype traits. Plant organ segmentation can be achieved with high-precision and automated acquisition of maize tassel phenotype traits because of the advances in the point cloud deep learning method. However, this method requires a large number of data sets and is not robust to automatic segmentation of highly adherent organ components; thus, it should be combined with point cloud processing technology. RESULTS: An innovative method of incomplete annotation of point cloud data was proposed for easy development of the dataset of maize tassels,and an automatic maize tassel phenotype analysis system: MaizeTasselSeg was developed. The tip feature of point cloud is trained and learned based on PointNet + + network, and the tip point cloud of tassel branch was automatically segmented. Complete branch segmentation was realized based on the shortest path algorithm. The Intersection over Union (IoU), precision, and recall of the segmentation results were 96.29, 96.36, and 93.01, respectively. Six phenotypic traits related to morphological structure (branch count, branch length, branch angle, branch curvature, tassel volume, and dispersion) were automatically extracted from the segmentation point cloud. The squared correlation coefficients (R2) for branch length, branch angle, and branch count were 0.9897, 0.9317, and 0.9587, respectively. The root mean squared error (RMSE) for branch length, branch angle, and branch count were 0.529 cm, 4.516, and 0.875, respectively. CONCLUSION: The proposed method provides an efficient scheme for high-throughput organ segmentation of maize tassels and can be used for the automatic extraction of phenotypic traits of maize tassel. In addition, the incomplete annotation approach provides a new idea for morphology-based plant segmentation.

Refined Feature-based Multi-frame and Multi-scale Fusing Gate network for accurate segmentation of plaques in ultrasound videos.

The accurate segmentation of carotid plaques in ultrasound videos will provide evidence for clinicians to evaluate the properties of plaques and treat patients effectively. However, the confusing background, blurry boundaries and plaque movement in ultrasound videos make accurate plaque segmentation challenging. To address the above challenges, we propose the Refined Feature-based Multi-frame and Multi-scale Fusing Gate Network (RMFG_Net), which captures spatial and temporal features in consecutive video frames for high-quality segmentation results and no manual annotation of the first frame. A spatial-temporal feature filter is proposed to suppress the noise of low-level CNN features and promote the detailed target area. To obtain a more accurate plaque position, we propose a transformer-based cross-scale spatial location algorithm, which models the relationship between adjacent layers of consecutive video frames to achieve stable positioning. To make full use of more detailed and semantic information, multi-layer gated computing is applied to fuse features of different layers, ensuring sufficient useful feature map aggregation for segmentation. Experiments on two clinical datasets demonstrate that the proposed method outperforms other state-of-the-art methods under different evaluation metrics, and it processes images with a speed of 68 frames per second which is suitable for real-time segmentation. A large number of ablation experiments were conducted to demonstrate the effectiveness of each component and experimental setting, as well as the potential of the proposed method in ultrasound video plaque segmentation tasks. The codes can be publicly available from https://github.com/xifengHuu/RMFG_Net.git.

Targeting ß-catenin using XAV939 nanoparticle promotes immunogenic cell death and suppresses conjunctival melanoma progression.

Many tumors dysregulate Wnt/ß-catenin pathway to promote stem-cell-like phenotype, tumorigenesis, immunosuppression, and resistance to targeted cancer immunotherapies. Therefore, targeting this pathway is a promising therapeutic approach to suppress tumor progression and elicit robust anti-tumor immunity. In this study, using a nanoparticle formulation for XAV939 (XAV-Np), a tankyrase inhibitor that promotes ß-catenin degradation, we investigated the effect of ß-catenin inhibition on melanoma cell viability, migration, and tumor progression using a mouse model of conjunctival melanoma. XAV-Nps were uniform and displayed near-spherical morphology with size stability for upto 5 days. We show that XAV-Np treatment of mouse melanoma cells significantly suppresses cell viability, tumor cell migration, and tumor spheroid formation compared to control nanoparticle (Con-Np) or free XAV939-treated groups. Further, we demonstrate that XAV-Np promotes immunogenic cell death (ICD) of tumor cells with a significant extracellular release or expression of ICD molecules, including high mobility group box 1 protein (HMGB1), calreticulin (CRT), and adenosine triphosphate (ATP). Finally, we show that local intra-tumoral delivery of XAV-Nps during conjunctival melanoma progression significantly suppresses tumor size and conjunctival melanoma progression compared to Con-Nps-treated animals. Collectively, our data suggest that selective inhibition of ß-catenin in tumor cells using nanoparticle-based targeted delivery represents a novel approach to suppress tumor progression through increased tumor cell ICD.

Liposomal DQ in Combination with Copper Inhibits ARID1A Mutant Ovarian Cancer Growth.

Therapeutic strategies for ARID1A-mutant ovarian cancers are limited. Higher basal reactive oxygen species (ROS) and lower basal glutathione (GSH) empower the aggressive proliferation ability and strong metastatic property of OCCCs, indicated by the increased marker of epithelial-mesenchymal transition (EMT) and serving the immunosuppressive microenvironment. However, the aberrant redox homeostasis also empowers the sensitivity of DQ-Lipo/Cu in a mutant cell line. DQ, a carbamodithioic acid derivative, generates dithiocarbamate (DDC) in response to ROS, and the chelation of Cu and DDC further generates ROS and provides a ROS cascade. Besides, quinone methide (QM) released by DQ targets the vulnerability of GSH; this effect, plus the increase of ROS, destroys the redox homeostasis and causes cancer cell death. Also importantly, the formed Cu(DDC)2 is a potent cytotoxic anti-cancer drug that successfully induces immunogenic cell death (ICD). The synergistic effect of EMT regulation and ICD will contribute to managing cancer metastasis and possible drug resistance. In summary, our DQ-Lipo/Cu shows promising inhibitory effects in cancer proliferation, EMT markers, and "heat" the immune response.

A digital nanoplasmonic microarray immunosensor for multiplexed cytokine monitoring during CAR T-cell therapy from a leukemia tumor microenvironment model.

The release of cytokines by chimeric antigen receptor (CAR) T-cells and tumor resident immune cells defines a significant part of CAR T-cell functional activity and patient immune responses during CAR T-cell therapy. However, few studies have so far precisely characterized the cytokine secretion dynamics in the tumor niche during CAR T-cell therapy, which requires multiplexed, and timely biosensing platforms and integration with biomimetic tumor microenvironment. Herein, we implemented a digital nanoplasmonic microarray immunosensor with a microfluidic biomimetic Leukemia-on-a-Chip model to monitor cytokine secretion dynamics during CD19 CAR T-cell therapy against precursor B-cell acute lymphocytic leukemia (B-ALL). The integrated nanoplasmonic biosensors achieved precise multiplexed cytokine measurements with low operating sample volume, short assay time, heightened sensitivity, and negligible sensor crosstalk. Using the digital nanoplasmonic biosensing approach, we measured the concentrations of six cytokines (TNF-α, IFN-γ, MCP-1, GM-CSF, IL-1ß, and IL-6) during first 5 days of CAR T-cell treatment in the microfluidic Leukemia-on-a-Chip model. Our results revealed a heterogeneous secretion profile of various cytokines during CAR T-cell therapy and confirmed a correlation between the cytokine secretion profile and the CAR T-cell cytotoxic activity. The capability to monitor immune cell cytokine secretion dynamics in a biomimetic tumor microenvironment could further help in study of cytokine release syndrome during CAR T-cell therapy and in development of more efficient and safer immunotherapies.

Characterization and genetic dissection of maize ear leaf midrib acquired by 3D digital technology.

The spatial morphological structure of plant leaves is an important index to evaluate crop ideotype. In this study, we characterized the three-dimensional (3D) data of the ear leaf midrib of maize at the grain-filling stage using the 3D digitization technology and obtained the phenotypic values of 15 traits covering four different dimensions of the ear leaf midrib, of which 13 phenotypic traits were firstly proposed for featuring plant leaf spatial structure. Cluster analysis results showed that the 13 traits could be divided into four groups, Group I, -II, -III and -IV. Group I contains HorizontalLength, OutwardGrowthMeasure, LeafAngle and DeviationTip; Group II contains DeviationAngle, MaxCurvature and CurvaturePos; Group III contains LeafLength and ProjectionArea; Group IV contains TipTop, VerticalHeight, UpwardGrowthMeasure, and CurvatureRatio. To investigate the genetic basis of the ear leaf midrib curve, 13 traits with high repeatability were subjected to genome-wide association study (GWAS) analysis. A total of 828 significantly related SNPs were identified and 1365 candidate genes were annotated. Among these, 29 candidate genes with the highest significant and multi-method validation were regarded as the key findings. In addition, pathway enrichment analysis was performed on the candidate genes of traits to explore the potential genetic mechanism of leaf midrib curve phenotype formation. These results not only contribute to further understanding of maize leaf spatial structure traits but also provide new genetic loci for maize leaf spatial structure to improve the plant type of maize varieties.

Enhanced Label-Free Nanoplasmonic Cytokine Detection in SARS-CoV-2 Induced Inflammation Using Rationally Designed Peptide Aptamer.

Rapid and precise serum cytokine quantification provides immense clinical significance in monitoring the immune status of patients in rapidly evolving infectious/inflammatory disorders, examplified by the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. However, real-time information on predictive cytokine biomarkers to guide targetable immune pathways in pathogenic inflammation is critically lacking, because of the insufficient detection range and detection limit in current label-free cytokine immunoassays. In this work, we report a highly sensitive localized surface plasmon resonance imaging (LSPRi) immunoassay for label-free Interleukin 6 (IL-6) detection utilizing rationally designed peptide aptamers as the capture interface. Benefiting from its characteristically smaller dimension and direct functionalization on the sensing surface via Au-S bonding, the peptide-aptamer-based LSPRi immunoassay achieved enhanced label-free serum IL-6 detection with a record-breaking limit of detection down to 4.6 pg/mL, and a wide dynamic range of ∼6 orders of magnitude (values from 4.6 to 1 × 106 pg/mL were observed). The immunoassay was validated in vitro for label-free analysis of SARS-CoV-2 induced inflammation, and further applied in rapid quantification of serum IL-6 profiles in COVID-19 patients. Our peptide aptamer LSPRi immunoassay demonstrates great potency in label-free cytokine detection with unprecedented sensing capability to provide accurate and timely interpretation of the inflammatory status and disease progression, and determination of prognosis.

Dissecting the Genetic Structure of Maize Leaf Sheaths at Seedling Stage by Image-Based High-Throughput Phenotypic Acquisition and Characterization.

The rapid development of high-throughput phenotypic detection techniques makes it possible to obtain a large number of crop phenotypic information quickly, efficiently, and accurately. Among them, image-based phenotypic acquisition method has been widely used in crop phenotypic identification and characteristic research due to its characteristics of automation, non-invasive, non-destructive and high throughput. In this study, we proposed a method to define and analyze the traits related to leaf sheaths including morphology-related, color-related and biomass-related traits at V6 stage. Next, we analyzed the phenotypic variation of leaf sheaths of 418 maize inbred lines based on 87 leaf sheath-related phenotypic traits. In order to further analyze the mechanism of leaf sheath phenotype formation, 25 key traits (2 biomass-related, 19 morphology-related and 4 color-related traits) with heritability greater than 0.3 were analyzed by genome-wide association studies (GWAS). And 1816 candidate genes of 17 whole plant leaf sheath traits and 1,297 candidate genes of 8 sixth leaf sheath traits were obtained, respectively. Among them, 46 genes with clear functional descriptions were annotated by single nucleotide polymorphism (SNPs) that both Top1 and multi-method validated. Functional enrichment analysis results showed that candidate genes of leaf sheath traits were enriched into multiple pathways related to cellular component assembly and organization, cell proliferation and epidermal cell differentiation, and response to hunger, nutrition and extracellular stimulation. The results presented here are helpful to further understand phenotypic traits of maize leaf sheath and provide a reference for revealing the genetic mechanism of maize leaf sheath phenotype formation.

Pd@Pt Nanodendrites as Peroxidase Nanomimics for Enhanced Colorimetric ELISA of Cytokines with Femtomolar Sensitivity.

Colorimetric enzyme-linked immunosorbent assay (ELISA) has been widely applied as the gold-standard method for cytokine detection over decades. However, it has become a critical challenge to further improve the detection sensitivity of ELISA as limited by the catalytic activity of enzymes. Herein, we report an enhanced colorimetric ELISA for ultrasensitive detection of interleukin-6 (IL-6, as a model cytokine for demonstration) using Pd@Pt core@shell nanodendrites (Pd@Pt NDs) as peroxidase nanomimics (named "Pd@Pt ND ELISA"), pushing the sensitivity up to femtomolar level. Specifically, the Pd@Pt NDs are rationally engineered by depositing Pt atoms on Pd nanocubes (NCs) to generate rough dendrite-like Pt skins on the Pd surfaces via Volmer-Weber growth mode. They can be produced on a large scale with highly uniform size, shape, composition, and structure. They exhibit significantly enhanced peroxidase-like catalytic activity with catalytic constants (Kcat) more than 2000-fold higher than those of horseradish peroxidase (HRP, an enzyme commonly used in ELISA). Using Pd@Pt NDs as the signal labels, the Pd@Pt ND ELISA presents strong colorimetric signals for the quantitative determination of IL-6 with a wide dynamic range of 0.05-100 pg mL-1 and an ultralow detection limit of 0.044 pg mL-1 (1.7 fM). This detection limit is 21-fold lower than that of conventional HRP-based ELISA. The reproducibility and specificity of the Pd@Pt ND ELISA are excellent. More significantly, the Pd@Pt ND ELISA was validated for analyzing IL-6 in human serum samples with high accuracy and reliability through recovery tests. Our results demonstrate that the colorimetric Pd@Pt ND ELISA is a promising biosensing tool for ultrasensitive determination of cytokines and thus is expected to be applied in a variety of clinical diagnoses and fundamental biomedical studies.