Spatially Selective Retinal Ganglion Cell Activation Using Low Invasive Extraocular Temporal Interference Stimulation.

Conventional retinal implants involve complex surgical procedures and require invasive implantation. Temporal Interference Stimulation (TIS) has achieved noninvasive and focused stimulation of deep brain regions by delivering high-frequency currents with small frequency differences on multiple electrodes. In this study, we conducted in silico investigations to evaluate extraocular TIS's potential as a novel visual restoration approach. Different from the previously published retinal TIS model, the new model of extraocular TIS incorporated a biophysically detailed retinal ganglion cell (RGC) population, enabling a more accurate simulation of retinal outputs under electrical stimulation. Using this improved model, we made the following major discoveries: (1) the maximum value of TIS envelope electric potential ([Formula: see text] showed a strong correlation with TIS-induced RGC activation; (2) the preferred stimulating/return electrode (SE/RE) locations to achieve focalized TIS were predicted; (3) the performance of extraocular TIS was better than same-frequency sinusoidal stimulation (SSS) in terms of lower RGC threshold and more focused RGC activation; (4) the optimal stimulation parameters to achieve lower threshold and focused activation were identified; and (5) spatial selectivity of TIS could be improved by integrating current steering strategy and reducing electrode size. This study provides insights into the feasibility and effectiveness of a low-invasive stimulation approach in enhancing vision restoration.

Robust Real-time Segmentation of Bio-Morphological Features in Human Cherenkov Imaging during Radiotherapy via Deep Learning.

Cherenkov imaging enables real-time visualization of megavoltage X-ray or electron beam delivery to the patient during Radiation Therapy (RT). Bio-morphological features, such as vasculature, seen in these images are patient-specific signatures that can be used for verification of positioning and motion management that are essential to precise RT treatment. However until now, no concerted analysis of this biological feature-based tracking was utilized because of the slow speed and accuracy of conventional image processing for feature segmentation. This study demonstrated the first deep learning framework for such an application, achieving video frame rate processing. To address the challenge of limited annotation of these features in Cherenkov images, a transfer learning strategy was applied. A fundus photography dataset including 20,529 patch retina images with ground-truth vessel annotation was used to pre-train a ResNet segmentation framework. Subsequently, a small Cherenkov dataset (1,483 images from 212 treatment fractions of 19 breast cancer patients) with known annotated vasculature masks was used to fine-tune the model for accurate segmentation prediction. This deep learning framework achieved consistent and rapid segmentation of Cherenkov-imaged bio-morphological features on another 19 patients, including subcutaneous veins, scars, and pigmented skin. Average segmentation by the model achieved Dice score of 0.85 and required less than 0.7 milliseconds processing time per instance. The model demonstrated outstanding consistency against input image variances and speed compared to conventional manual segmentation methods, laying the foundation for online segmentation in real-time monitoring in a prospective setting.

PPI-hotspotID for detecting protein-protein interaction hot spots from the free protein structure.

Experimental detection of residues critical for protein-protein interactions (PPI) is a time-consuming, costly, and labor-intensive process. Hence, high-throughput PPI-hot spot prediction methods have been developed, but they have been validated using relatively small datasets, which may compromise their predictive reliability. Here, we introduce PPI-hotspotID, a novel method for identifying PPI-hot spots using the free protein structure, and validated it on the largest collection of experimentally confirmed PPI-hot spots to date. We explored the possibility of detecting PPI-hot spots using (i) FTMap in the PPI mode, which identifies hot spots on protein-protein interfaces from the free protein structure, and (ii) the interface residues predicted by AlphaFold-Multimer. PPI-hotspotID yielded better performance than FTMap and SPOTONE, a webserver for predicting PPI-hot spots given the protein sequence. When combined with the AlphaFold-Multimer-predicted interface residues, PPI-hotspotID yielded better performance than either method alone. Furthermore, we experimentally verified several PPI-hotspotID-predicted PPI-hot spots of eukaryotic elongation factor 2. Notably, PPI-hotspotID can reveal PPI-hot spots not obvious from complex structures, including those in indirect contact with binding partners. PPI-hotspotID serves as a valuable tool for understanding PPI mechanisms and aiding drug design. It is available as a web server (https://ppihotspotid.limlab.dnsalias.org/) and open-source code (https://github.com/wrigjz/ppihotspotid/).

Comparative analysis of the gut microbiome of ungulate species from Qinghai-Xizang plateau.

Several studies have investigated the gut bacterial composition of wild ungulates in the Qinghai-Xizang Plateau. However, the relationship between their gut microbiome dendrograms and their phylogenetic tree remains unclear. In this study, we analyzed 45 amplicons (V3-V4 region of the 16S rRNA gene) from five wild ungulates-Pseudois nayaur, Pantholops hodgsonii, Gazella subgutturosa, Bos grunniens, and Equus kiang-from the Qinghai-Xizang Plateau to clarify the relationship between their phylogenies and gut microbiome dendrograms. The unweighted pair group method with arithmetic mean analysis and hierarchical clustering analysis indicated that G. subgutturosa is closely related to P. nayaur; however, these results were inconsistent with their phylogenetic trees. Additionally, the indicator genera in the microbiome of each wild ungulate showed strong associations with the diets and habitats of their host. Thus, diet and space niche differentiation may primarily account for the differences between the gut microbiome characteristics of these wild ungulates and their phylogeny. In summary, our research provides insights into the evolutionary factors influencing the gut microbiome of wild ungulates in the Qinghai-Xizang Plateau.

Bcl-xL is translocated to the nucleus via CtBP2 to epigenetically promote metastasis.

Nuclear Bcl-xL is found to promote cancer metastasis independently of its mitochondria-based anti-apoptotic activity. How Bcl-xL is translocated into the nucleus and how nuclear Bcl-xL regulates histone H3 trimethyl Lys4 (H3K4me3) modification have yet to be understood. Here, we report that C-terminal Binding Protein 2 (CtBP2) binds to Bcl-xL via its N-terminus and translocates Bcl-xL into the nucleus. Knockdown of CtBP2 by shRNA decreases the nuclear portion of Bcl-xL and reverses Bcl-xL-induced invasion and metastasis in mouse models. Furthermore, knockout of CtBP2 not only reduces the nuclear portion of Bcl-xL but also suppresses Bcl-xL transcription. The binding between Bcl-xL and CtBP2 is required for their interaction with MLL1, a histone H3K4 methyltransferase. Pharmacologic inhibition of the MLL1 enzymatic activity reverses Bcl-xL-induced H3K4me3 and TGFß mRNA upregulation, as well as invasion. Moreover, the cleavage under targets and release using nuclease (CUT&RUN) assay coupled with next-generation sequencing reveals that H3K4me3 modifications are particularly enriched in the promotor regions of genes encoding TGFß and its signaling pathway members in cancer cells overexpressing Bcl-xL. Altogether, the metastatic function of Bcl-xL is mediated by its interaction with CtBP2 and MLL1 and this study offers new therapeutic strategies to treat Bcl-xL-overexpressing cancer.

A modular chemigenetic calcium indicator for multiplexed in vivo functional imaging.

Genetically encoded fluorescent calcium indicators allow cellular-resolution recording of physiology. However, bright, genetically targetable indicators that can be multiplexed with existing tools in vivo are needed for simultaneous imaging of multiple signals. Here we describe WHaloCaMP, a modular chemigenetic calcium indicator built from bright dye-ligands and protein sensor domains. Fluorescence change in WHaloCaMP results from reversible quenching of the bound dye via a strategically placed tryptophan. WHaloCaMP is compatible with rhodamine dye-ligands that fluoresce from green to near-infrared, including several that efficiently label the brain in animals. When bound to a near-infrared dye-ligand, WHaloCaMP shows a 7× increase in fluorescence intensity and a 2.1-ns increase in fluorescence lifetime upon calcium binding. We use WHaloCaMP1a to image Ca2+ responses in vivo in flies and mice, to perform three-color multiplexed functional imaging of hundreds of neurons and astrocytes in zebrafish larvae and to quantify Ca2+ concentration using fluorescence lifetime imaging microscopy (FLIM).

Intelligent identification of picking periods of Lu'an Guapian tea by an indicator displacement colorimetric sensor array combined with machine learning.

Lu'an Gua Pian (LAGP) tea is one of the most famous green teas in China. The quality of green tea is related to its picking periods, especially the green tea before Qingming Festival (usually April 6th) is highly praised as precious in the market. In this work, a simple and cheap indicator displacement colorimetric sensor array combined with smartphone was developed to rapidly identify LAGP picked during different picking periods. First, the chemical component contents of LAGP picked before and after Qingming Festival were analyzed. Second, a well-designed colorimetric sensor array was proposed based on the tea component contents differences. Finally, machine learning was used to process the array data taken by a smartphone. By comparison, the accuracy of the best model for the prediction set was 97%. Meanwhile, the multi-channel advantages of the sensing array were demonstrated by an ablation experiment. In addition, the method achieved an AGREE analysis score of 0.88, indicating that it was environmental-friendly.

Role of Enterococcus mundtii in gut of the tomato leaf miner (Tuta absoluta) to detoxification of Chlorantraniliprole.

Chlorantraniliprole (CAP) is applied worldwide for the control of caterpillars (Lepidoptera). However, with the overuse of CAP, the resistance problem in pest control is becoming increasingly serious. Recent studies have indicated a central role of the gut symbiont in insect pest resistance to pesticides and these may apply to the tomato leaf miner Tuta absoluta, is one of the most destructive insects worldwide. Here, we successfully isolated seven strains of tolerant CAP bacterium from the CAP-resistant T. absoluta gut, of which Enterococcus mundtii E14 showed the highest CAP tolerance, with a minimum inhibitory concentration (MIC) of 1.6 g/L and CAP degradation rate of 42.4%. Through transcriptomics and metabolism analysis, we studied the detoxification process of CAP by the E. mundtii E14, and found that CAP can be degraded by E. mundtii E14 into non-toxic compounds, such as 3,4-dihydroxy-2-(5-hydroxy-3,7-dimethylocta-2,6-dien-1-yl) benzoic acid and 2-pyridylacetic acid. Additionally, 2-pyridylacetic acid was detected both intracellular and extracellular in E. mundtii E14 treated with CAP. Meanwhile, we identified 52 up-regulated genes, including those associated with CAP degradation, such as RS11670 and RS19130. Transcriptome results annotated using KEGG indicated significant enrichment in up-regulated genes related to the glyoxylate cycle, nitrogen metabolism, and biosynthesis of secondary metabolites. Additionally, we observed that reinfection with E. mundtii E14 may effectively enhance resistance of T. absoluta to CAP. The LC50 values of the antibiotic treatment population of T. absoluta reinfection with E. mundtii E14 is 0.6122 mg/L, which was 18.27 folds higher than before reinfection. These findings offer new insights into T. absoluta resistance to CAP and contribute to a better understanding of the relationship between insecticide resistance and gut symbionts of T. absoluta, which may play a pivotal role in pest management.

Damage and Recovery Behavior of Low-Replacement-Rate Fly Ash Concrete after Different High-Temperature Exposures.

This study focuses on investigating the strength recovery of fire-damaged fly ash concrete (FAC) with a low substitution rate of 10% through post-fire curing. The chemical and microstructural changes were analyzed using X-ray diffraction (XRD), derivative thermogravimetry (DTG), scanning electron microscopy (SEM), energy dispersive X-ray spectrometry (EDS), and nitrogen adsorption. The findings indicate that the incorporation of fly ash slightly enhanced the strength after exposure to 400 °C; this was attributed to improved pozzolanic reactions, which were not observed at higher temperatures of 600 °C and 800 °C. Moreover, a positive effect on the recovery of compressive strength was observed due to the pozzolanic reaction. However, due to the relatively low fly ash content, depletion occurred at a later age, resulting in the inability to inhibit microstructural damage caused by the production of portlandite, thereby weakening the compressive strength. Interestingly, fly ash influenced the morphology of calcium carbonate and calcium silicate hydrate crystals, which is potentially ascribed to the role of high aluminum content acting as a crystallization-guiding agent.

Multi-Walled Carbon Nanotubes Accelerate Leukaemia Development in a Mouse Model.

Inflammation is associated with an increased risk of developing various cancers in both animals and humans, primarily solid tumors but also myeloproliferative neoplasms (MPNs), myelodysplastic syndromes (MDS), and acute myeloid leukemia (AML). Multi-walled carbon nanotubes (MWCNTs), a type of carbon nanotubes (CNTs) increasingly used in medical research and other fields, are leading to a rising human exposure. Our study demonstrated that exposing mice to MWCNTs accelerated the progression of spontaneous MOL4070LTR virus-induced leukemia. Additionally, similar exposures elevated pro-inflammatory cytokines such as interleukin (IL)-1ß, IL-6, and tumor necrosis factor (TNF)-α and induced reactive oxygen species (ROS) in a murine macrophage cell line. These effects were significantly reduced in immunodeficient mice and when mice were treated with methoxypolyethylene glycol amine (PEG)-modified MWCNTs. These findings underscore the necessity of evaluating the safety of MWCNTs, particularly for those with hematologic cancers.

A Precision Mixture Risk Model to Identify Adverse Drug Events in Subpopulations Using a Case-Crossover Design.

Despite the success of pharmacovigilance studies in detecting signals of adverse drug events (ADEs) from real-world data, the risks of ADEs in subpopulations warrant increased scrutiny to prevent them in vulnerable individuals. Recently, the case-crossover design has been implemented to leverage large-scale administrative claims data for ADE detection, while controlling both observed confounding effects and short-term fixed unobserved confounding effects. Additionally, as the case-crossover design only includes cases, subpopulations can be conveniently derived. In this manuscript, we propose a precision mixture risk model (PMRM) to identify ADE signals from subpopulations under the case-crossover design. The proposed model is able to identify signals from all ADE-subpopulation-drug combinations, while controlling for false discovery rate (FDR) and confounding effects. We applied the PMRM to an administrative claims data. We identified ADE signals in subpopulations defined by demographic variables, comorbidities, and detailed diagnosis codes. Interestingly, certain drugs were associated with a higher risk of ADE only in subpopulations, while these drugs had a neutral association with ADE in the general population. Additionally, the PMRM could control FDR at a desired level and had a higher probability to detect true ADE signals than the widely used McNemar's test. In conclusion, the PMRM is able to identify subpopulation-specific ADE signals from a tremendous number of ADE-subpopulation-drug combinations, while controlling for both FDR and confounding effects.

Fenitrothion induces glucose metabolism disorders in rat liver BRL cells by inhibiting AMPKα and IRS1/PI3K/AKT signaling pathway.

Fenitrothion (FNT) is a common organophosphorus pesticide that is widely used in both agricultural and domestic pest control. FNT has been frequently detected in various environmental media, including the human body, and is a notable contaminant. Epidemiological investigations have recently shown the implications of exposure to FNT in the incidence of various metabolic diseases, such as diabetes mellitus in humans, indicating that FNT may be a potential endocrine disruptor. However, the effects of FNT exposure on glucose homeostasis and their underlying mechanisms in model organisms remain largely unknown, which may limit our understanding of the health risks of FNT. In this study, FNT (4 5, 90, 180, and 4 50 µM) exposure model of rat hepatocytes (Buffalo Rat Liver, BRL cells) was established to investigate the effects and potential mechanisms of its toxicity on glucose metabolism. Several key processes of glucose metabolism were detected in this study. The results showed significantly increased glucose levels in the culture medium and decreased glycogen content in the FNT-exposed BRL cells. The results of quantitative real-time PCR and enzymology showed the abnormal expression of genes and activity/content of glucose metabolic enzymes involved in glucose metabolism, which might promote gluconeogenesis and inhibit glucose uptake, glycolysis, and glycogenesis. Furthermore, gluconeogenesis and glycolytic were carried out in the mitochondrial membrane. The abnormal of mitochondrial membrane potential may be a potential mechanism underlying FNT-induced glucose metabolism disorder. In addition, the mRNA and protein expression implicated that FNT may disrupt glucose metabolism by inhibiting the AMPKα and IRS1/PI3K/AKT signaling pathways. In conclusion, results provide in vitro evidence that FNT can cause glucose metabolism disorder, which emphasizes the potential health risks of exposure to FNT in inducing diabetes mellitus.

Camp-style lifestyle modification program (CAMP) for diabetes prevention among rural women with prior GDM: study protocol for a three-arm cluster hybrid type 2 randomized controlled trial.

BACKGROUND: Intensive lifestyle interventions were effective to reduce the risk of type 2 diabetes mellitus (T2DM) for women with gestational diabetes mellitus (GDM) history. However, reaching these mothers and maintaining participation in lifestyle interventions is suboptimal in real-world settings. Effective, feasible and sustainable new lifestyle interventions are needed. The objectives of this three-arm trial are to (1) compare diabetes risk outcomes of an evidence-based intensive lifestyle modification (ILSM) intervention, a camp-style lifestyle modification program (CAMP) intervention, and usual care among women with GDM history; and (2) evaluate the comparative efficacy of the CAMP versus ILSM intervention on implementation outcomes. METHODS: A three-arm cluster randomized clinical trial (RCT) using a hybrid type 2 implementation design will be conducted in two counties in Hunan province in China. Six towns from each county will be randomly selected and assigned to CAMP, ILSM, and the usual care group (25 women from each of 12 towns, 100 women in each arm). The ILSM includes six biweekly in-person sessions and 3-month telephone health consultations, while the CAMP consists of a 2-day camp-based session and 3-month health consultations via a popular social media platform. Both interventions share the same session content, including six lifestyle skills. Efficacy (T2DM risk score and behavioral, anthropometric, psychosocial, and glycemic variables) and implementation outcomes (recruitment, acceptability, feasibility, fidelity, and cost-effectiveness) will be collected at baseline, 6-month, and 12-month. Pre-planned ANOVA F-test and generalized estimating equations will be included to test time-by-arm interactions. DISCUSSION: The CAMP intervention is expected to have better reach, better attendance, and comparable effectiveness in reducing the risk of T2DM, thus improving postpartum care for GDM in China. The delivery of a concentrated format supplemented with technology-based support may provide an efficient and effective delivery model for implementing maternal health promotion programs in primary care settings. TRIAL REGISTRATION: Registered in the Chinese Clinical Trial Registry (ChiCTR2200058150) on 31st March 2022.

Integrated bioinformatic analysis of protein landscape in gingival crevicular fluid unveils sequential bioprocess in orthodontic tooth movement.

BACKGROUND: The biological mechanisms driving orthodontic tooth movement (OTM) remain incompletely understood. Gingival crevicular fluid (GCF) is an important indicator of the periodontal bioprocess, providing valuable cues for probing the molecular mechanisms of OTM. METHODS: A rigorous review of the clinical studies over the past decade was conducted after registering the protocol with PROSPERO and adhering to inclusion criteria comprising human subjects, specified force magnitudes and force application modes. The thorough screening investigated differentially expressed proteins (DEPs) in GCF associated with OTM. Protein-protein interaction (PPI) analysis was carried out using the STRING database, followed by further refinement through Cytoscape to isolate top hub proteins. RESULTS: A comprehensive summarization of the OTM-related GCF studies was conducted, followed by an in-depth exploration of biomarkers within the GCF. We identified 13 DEPs, including ALP, IL-1ß, IL-6, Leptin, MMP-1, MMP-3, MMP-8, MMP-9, PGE2, TGF-ß1, TNF-α, OPG, RANKL. Bioinformatic analysis spotlighted the top 10 hub proteins and their interactions involved in OTM. Based on these findings, we have proposed a hypothetic diagram for the time-course bioprocess in OTM, which involves three phases containing sequential cellular and molecular components and their interplay network. CONCLUSIONS: This work has further improved our understanding to the bioprocess of OTM, suggesting biomarkers as potential modulating targets to enhance OTM, mitigate adverse effects and support real-time monitoring and personalized orthodontic cycles.

Study of obesity research using machine learning methods: A bibliometric and visualization analysis from 2004 to 2023.

BACKGROUND: Obesity, a multifactorial and complex health condition, has emerged as a significant global public health concern. Integrating machine learning techniques into obesity research offers great promise as an interdisciplinary field, particularly in the screening, diagnosis, and analysis of obesity. Nevertheless, the publications on using machine learning methods in obesity research have not been systematically evaluated. Hence, this study aimed to quantitatively examine, visualize, and analyze the publications concerning the use of machine learning methods in obesity research by means of bibliometrics. METHODS: The Web of Science core collection was the primary database source for this study, which collected publications on obesity research using machine learning methods over the last 20 years from January 1, 2004, to December 31, 2023. Only articles and reviews that fit the criteria were selected for bibliometric analysis, and in terms of language, only English was accepted. VOSviewer, CiteSpace, and Excel were the primary software utilized. RESULTS: Between 2004 and 2023, the number of publications on obesity research using machine learning methods increased exponentially. Eventually, 3286 publications that met the eligibility criteria were searched. According to the collaborative network analysis, the United States has the greatest volume of publications, indicating a significant influence on this research. coauthor's analysis showed the authoritative one in this field is Leo Breiman. Scientific Reports is the most widely published journal. The most referenced publication is "R: a language and environment for statistical computing." An analysis of keywords shows that deep learning, support vector machines, predictive models, gut microbiota, energy expenditure, and genome are hot topics in this field. Future research directions may include the relationship between obesity and its consequences, such as diabetic retinopathy, as well as the interaction between obesity and epidemiology, such as COVID-19. CONCLUSION: Utilizing bibliometrics as a research tool and methodology, this study, for the first time, reveals the intrinsic relationship and developmental pattern among obesity research using machine learning methods, which provides academic references for clinicians and researchers in understanding the hotspots and cutting-edge issues as well as the developmental trend in this field to detect patients' obesity problems early and develop personalized treatment plans.

Polysaccharides from Ostrea rivularis alleviate type II diabetes induced-retinopathy and VGEF165-induced angiogenesis via PI3K/AKT signaling pathway.

The purpose of this study was to investigate the role of polysaccharides from Ostrea rivularis Gloud (ORPs) in the progression of diabetic retinopathy (DR) and its anti-angiogenic effect on endothelial cell. Transgenic db/db mice with DR model were used to evaluate the protective effect of ORPs on retinal damage. It was found that ORPs could down-regulated levels of random blood glucose and fasting insulin, and further ameliorate retinal structure abnormalities as well as vascular network structure. Moreover, ORPs could reduce the expression of VEGF in retinal tissue and lessen pathological angiogenesis, thus slowing the progression of DR. In vitro, the proliferation, migration and tube formation of VGEF165-induced EA.hy926 cells were inhibited with ORPs administration. Furthermore, the expression of related proteins in the PI3K/AKT pathway and angiogenesis related factors were improved after ORPs intervention. Overall, these findings suggested that ORPs could effectively control the development of DR, and inhibit VGEF165-induced EA.hy926 cells proliferation, migration and tube formation, which effects might work through blocking the activation of PI3K/AKT signaling pathway.

Migrating pseudolipoma of Glisson's capsule: A case report.

Pseudolipoma of Glisson's capsule is a rare, benign subcapsular liver lesion that typically occurs in older adult men. It comprises degenerated fat tissue that likely originates from detached mesothelial appendages or degenerated liver lipomas. We report the case of a 58-year-old female patient with a gastric malignant tumor after admission. No lesions were found in the liver capsule before surgery. During postoperative reviews from 2015 to 2018, new dense, fatty lesions were found under the liver capsule, and highly unusually, the lesions moved under the liver capsule over time. To the best of our knowledge, only 1 other case has been reported of a pseudolipoma of Glisson's capsule that migrated over time. This supports the hypothesis that migrating mesothelial attachments form Glisson capsule pseudolipomas. This case report aims to review liver capsule anatomy, explain why the liver is particularly susceptible to this phenomenon, and present information to aid the diagnosis of fat-containing hepatic lesions by providing a unique perspective on certain pathologies affecting the liver.

Near-Infrared Fluorescent Probe Reveals Elevated Mitochondrial Viscosity during Acute Alcoholic Liver Injury.

Acute alcoholic liver injury (AALI) has become an important cause of liver disease worldwide, and there is an urgent need to develop noninvasive and sensitive methods to detect and evaluate AALI. We report herein three novel but readily available mitochondrial targeting fluorescence probes (ICR, ICJ, and ICQ) for AALI detection. These probes contain different electron-donating groups, among which ICQ exhibits NIR fluorescence (740 nm), a large Stokes shift (110 nm), and a sensitive response to viscosity (73-fold enhancement in fluorescence from water to glycerol), making it suitable for in vivo imaging. ICQ also exhibits an excellent ability to image mitochondrial viscosity changes in cells. More importantly, ICQ can target the liver selectively and image the viscosity changes in the liver noninvasively. Through establishing an AALI mouse model, ICQ was successfully applied to the in situ imaging changes in liver viscosity during the AALI process. The results showed a significant increase in liver viscosity in AALI mice, indicating that viscosity can serve as a marker for AALI, and ICQ is a promising noninvasive and sensitive tool for detecting and evaluating AALI.

Quantitative separation of CEST effect by Rex-line-fit analysis of Z-spectra.

The process of chemical exchange saturation transfer (CEST) is quantified by evaluating a Z-spectra, where CEST signal quantification and Z-spectra fitting have been widely used to distinguish the contributions from multiple origins. Based on the exchange-dependent relaxation rate in the rotating frame (Rex), this paper introduces an additional pathway to quantitative separation of CEST effect. The proposed Rex-line-fit method is solved by a multi-pool model and presents the advantage of only being dependent of the specific parameters (solute concentration, solute-water exchange rate, solute transverse relaxation, and irradiation power). Herein we show that both solute-water exchange rate and solute concentration monotonously vary with Rex for Amide, Guanidino, NOE and MT, which has the potential to assist in solving quantitative separation of CEST effect. Furthermore, we achieve Rex imaging of Amide, Guanidino, NOE and MT, which may provide direct insight into the dependency of measurable CEST effects on underlying parameters such as the exchange rate and solute concentration, as well as the solute transverse relaxation.

Salivary Protein Sfapyrase of Spodoptera frugiperda Stimulates Plant Defence Response.

Plants have developed various resistance mechanisms against herbivorous insects through prolonged coevolution. Plant defence responses can be triggered by specific compounds present in insect saliva. Apyrase, a known enzyme that catalyzes the hydrolysis of adenosine triphosphate (ATP) and adenosine diphosphate (ADP) into adenosine monophosphate (AMP) and inorganic phosphorus, has recently been identified in some herbivorous insects. However, whether insect salivary apyrase induces or inhibits plant responses remains poorly understood. In this study, we identified an apyrase-like protein in the salivary proteome of the fall armyworm, Spodoptera frugiperda, named Sfapyrase. Sfapyrase was primarily expressed in the salivary gland and secreted into plants during insect feeding. Transient expression of Sfapyrase in tobacco and maize enhanced plant resistance and resulted in decreased insect feeding. Knockdown of Sfapyrase through RNA interference led to increased growth and feeding of S. frugiperda. Furthermore, we showed that Sfapyrase activates the jasmonic acid signalling pathway and promotes the synthesis of secondary metabolites, especially benzoxazinoids, thereby enhancing resistance to S. frugiperda. In summary, our findings demonstrated that Sfapyrase acts as a salivary elicitor, inducing maize jasmonic acid defence responses and the production of insect-resistant benzoxazinoids. This study provides valuable insights into plant-insect interactions and offers potential targets for developing innovative insect pest management strategies.