Wave type fiber SPR sensor for rapid and highly sensitive detection of hyperoside.

The fiber surface plasmon resonance (SPR) sensor used for the detection of active ingredients in traditional Chinese medicine has the problems of low sensitivity and difficult specific recognition. This paper proposed a wave type fiber SPR sensor, which reduced the mode of transmitted light through a periodic wave structure and caused concentrated and total reflection of the transmitted beam at the interface between the bent peak cladding and the air. A 50 nm gold film was coated on the surface of the cladding in the wave structure area to form the SPR sensing area. By controlling the width and height of the wave structure to control the total reflection angle of the transmitted light, i.e., the SPR incidence angle, the sensitivity of the fiber SPR sensor was effectively improved to 4972 nm/RIU. Furthermore, HSP90AA protein was modified on the gold film of the sensor to achieve specific detection of hyperoside. The longest single detection time was only 3 minutes, and the detection sensitivity was 0.53 nm/(µg/ml), with a detection limit as low as 0.68µg/ml, which is comparable to liquid chromatography. The proposed wave type fiber SPR sensor is fast in production and has high structural mechanical strength, providing a new approach for the rapid, highly sensitive, and specific detection of active ingredients in traditional Chinese medicine.

Hand Hygiene Education Components Among First-Year Nursing Students: A Cluster Randomized Clinical Trial.

Importance: Few studies have directly and objectively measured the individual and combined effects of multifaceted hand hygiene education programs. Objective: To evaluate the individual and combined immediate effects of an instructional video and hand scan images on handwashing quality, decontamination, and knowledge improvement. Design, Setting, and Participants: This cluster randomized clinical trial was conducted in June to July 2023 among first-year nursing students at a university in Hong Kong. The study used an intention-to-treat analysis. Intervention: Hand hygiene education sessions featuring an instructional video, hand scan images, or both. Main Outcomes and Measures: The primary outcome was the change in residue from fluorescent lotion remaining on participants' hands after handwashing before and after the intervention. The secondary outcomes included handwashing quality and knowledge of hand hygiene. Results: A total of 270 of 280 students (mean [SD] age, 19 [1] years; 182 [67.4%] female) participated in the trial (96.4% participation rate). Participants were randomized to a control group (66 participants), hand scan image group (68 participants), instructional video group (67 participants), and hand scan image with instructional video group (69 participants). All intervention groups had greater reductions in residue after the intervention compared with the control group, although none reached statistical significance (hand scan image group: 3.9 [95% CI, 2.0-5.8] percentage points; instructional video group: 4.8 [95% CI, 2.9-6.7] percentage points; hand scan image with instructional video: 3.5 [95% CI, 1.6-5.4] percentage points; control group: 3.2 [95% CI, 1.3-5.2] percentage points). The instructional video group showed a significant improvement in their handwashing performance, with a higher percentage of participants correctly performing all 7 steps compared with the control group (22.4% [95% CI, 13.1% to 31.6%] vs 1.5% [-7.9% to 10.9%]; P < .001). Hand scan images revealed that wrists, fingertips, and finger webs were the most commonly ignored areas in handwashing. Conclusions and Relevance: In this cluster randomized clinical trial of an education program for hand hygiene, a handwashing instructional video and hand scan images did not enhance the level of decontamination. The intervention group had improved handwashing techniques compared with the control group, a secondary outcome. Trial Registration: ClinicalTrials.gov Identifier: NCT05872581.

The novel function of an orphan pheromone receptor reveals the sensory specializations of two potential distinct types of sex pheromones in noctuid moth.

Sex pheromones play crucial role in mating behavior of moths, involving intricate recognition mechanisms. While insect chemical biology has extensively studied type I pheromones, type II pheromones remain largely unexplored. This study focused on Helicoverpa armigera, a representative species of noctuid moth, aiming to reassess its sex pheromone composition. Our research unveiled two previously unidentified candidate type II sex pheromones-3Z,6Z,9Z-21:H and 3Z,6Z,9Z-23:H-in H. armigera. Furthermore, we identified HarmOR11 as an orphan pheromone receptor of 3Z,6Z,9Z-21:H. Through AlphaFold2 structural prediction, molecular docking, and molecular dynamics simulations, we elucidated the structural basis and key residues governing the sensory nuances of both type I and type II pheromone receptors, particularly HarmOR11 and HarmOR13. This study not only reveals the presence and recognition of candidate type II pheromones in a noctuid moth, but also establishes a comprehensive structural framework for PRs, contributing to the understanding of connections between evolutionary adaptations and the emergence of new pheromone types.

Fagopyrum Dibotrys Rhizoma regulates pulmonary lipid metabolic homeostasis and the ERK-cPLA2 pathway to alleviate asthma in mice.

BACKGROUND: Asthma is a complex disease with mechanisms involving multiple factors, and there is still a lack of highly effective and low-side-effect drugs. Traditional Chinese medicine Fagopyrum Dibotrys Rhizoma (FDR) has been applied for the treatment of acute and chronic bronchitis as well as bronchial asthma due to its favorable pharmacological activity. However, the exact mechanism of FDR remains unclear. OBJECTIVE: A mouse model of asthma was created using OVA and HDM. To investigate the mechanism of FDR in asthma treatment, a combination of network pharmacology, lipidomics, and molecular biology approaches was employed. METHODS: To evaluate the therapeutic effects of FDR on asthma, we established two distinct models of asthma in C57BL/6 J mice using OVA and HDM, respectively. We then employed LC-MS to analyze the major chemical constituents in FDR. Next, the network pharmacology approach was used to predict the potential targets and mechanisms of FDR in asthma treatment. Additionally, lipidomics analysis of mouse serum was conducted using LC-MS. Finally, the impact of FDR on the ERK -cPLA2 signaling pathway was investigated through Western Blotting assay. RESULTS: FDR treatment has been shown to improve histomorphological changes, lung function and inflammation in models of OVA and HDM-induced asthma. Using UPLC/LTQ-Orbitrap-MS, we were able to identify 12 potential active components. Network pharmacology analysis revealed that FDR shares 75 targets with asthma. Further analysis using GO and KEGG pathways demonstrated the involvement of key pathways such as PI3K-Akt, TNF, and MAPK. Additionally, lipidomics analysis of the serum from OVA and HDM induced asthma mice showed disturbances in lipid metabolism, which were effectively ameliorated by FDR treatment. Mechanistically, FDR inhibits ERK1/2-cPLA2, leading to a reduction in lysophospholipids and restoration of lipid balance, thereby aiding in the treatment of asthma. CONCLUSION: FDR has been shown to improve lipid metabolism disorder in the serum of asthmatic mice, thereby potentially serving as a treatment for asthma. This can be achieved by regulating the activation levels of ERK1/2 and p38MAPK. Consequently, the production of lysophosphatide is reduced, thereby alleviating the disorder of lipid metabolism and achieving the desired therapeutic effect in asthma treatment.

Occurrence and mechanism of sulfamethoxazole in alginate-like extracellular polymers from excess sludge.

The recovery of biopolymers, particularly alginate-like extracellular polymers, from municipal sludge represents a promising step toward sustainable sludge treatment practices. Originating from wastewater plants in complexly polluted environments, alginate-like extracellular polymers carry potential environmental risks concerning their reuse. This study employs ultrahigh-performance liquid chromatography-tandem mass spectrometry to investigate the distribution coefficients and occurrence of alginate-like extracellular polymers and sulfamethoxazole. Results demonstrate a negative distribution coefficient, suggesting an inhibitory effect on sulfamethoxazole dissolution. The ethanol-extracted alginate-like extracellular polymers exhibits higher sulfamethoxazole levels (approximately 52%) than those obtained via dialysis extraction. Three-dimensional excitation-emission matrix analysis and adsorption studies indicate the absence of tyrosine-like substances in the alginate-like extracellular polymers, unlike in other extracellular polymeric substances. This absence diminishes hydrophobic interactions, highlighting that electrostatic interactions play a more important role. These insights are crucial for understanding the adsorption behavior of alginate-like extracellular polymers and optimizing their large-scale extraction processes.

Opioid Nonadherence Risk Prediction of Patients with Cancer-Related Pain Based on Five Machine Learning Algorithms.

Objectives: Opioid nonadherence represents a significant barrier to cancer pain treatment efficacy. However, there is currently no effective prediction method for opioid adherence in patients with cancer pain. We aimed to develop and validate a machine learning (ML) model and evaluate its feasibility to predict opioid nonadherence in patients with cancer pain. Methods: This was a secondary analysis from a cross-sectional study that included 1195 patients from March 1, 2018, to October 31, 2019. Five ML algorithms, such as logistic regression (LR), random forest, eXtreme Gradient Boosting, multilayer perceptron, and support vector machine, were used to predict opioid nonadherence in patients with cancer pain using 43 demographic and clinical factors as predictors. The predictive effects of the models were compared by the area under the receiver operating characteristic curve (AUC_ROC), accuracy, precision, sensitivity, specificity, and F1 scores. The value of the best model for clinical application was assessed using decision curve analysis (DCA). Results: The best model obtained in this study, the LR model, had an AUC_ROC of 0.82, accuracy of 0.82, and specificity of 0.71. The DCA showed that clinical interventions for patients at high risk of opioid nonadherence based on the LR model can benefit patients. The strongest predictors for adherence were, in order of importance, beliefs about medicines questionnaire (BMQ)-harm, time since the start of opioid, and BMQ-necessity. Discussion. ML algorithms can be used as an effective means of predicting adherence to opioids in patients with cancer pain, which allows for proactive clinical intervention to optimize cancer pain management. This trial is registered with ChiCTR2000033576.

2 × 4†kW near-single-mode laser output assisted by an optimized bidirectional oscillating-amplifying integrated fiber laser configuration.

Bidirectional output oscillating-amplifying integrated fiber laser (B-OAIFL) can achieve the two-ports laser amplification based on a single cavity, showcasing a promising prospect. In order to improve both the laser power and beam quality, we first simulate and optimize the stimulated Raman scattering (SRS) effect in the B-OAIFL. The simulation results show the SRS effect can be suppressed by optimizing the diameter as well as the length of the active fiber at different locations. With the guidance of theoretical and experimental analysis for the combined suppression of SRS and transverse mode instability (TMI), a near-single-mode B-OAIFL with 2 × 4 kW was demonstrated. Based on this foundation, we further devoted ourselves to the pursuit of the optimization of the structure and performance. The necessity of the configuration of side pump, which was initially introduced for its exceptional performance in stabilizing temporal chaos, was reevaluated in detail. With its negative impacts on efficiency improvement and SRS suppression were analyzed and verified, we removed this configuration and finally demonstrated a more simplified design with superior performance. A total bidirectional output of 8105 W was achieved, with an O-O efficiency of 79.6% and a near-single-mode beam quality of M A 2∼1.36,M B 2∼1.63. No signs of TMI were observed, and the signal-to-SRS suppression ratio was over 38 dB. The results still demonstrate a promising potential for power scaling based on this configuration and parameters.

Large detection range and high strain sensitivity fiber SPR sensor based on wave structure.

To achieve a fiber strain sensor with a large detection range and high sensitivity, this paper proposes a wave structured fiber SPR strain sensor. When subjected to axial strain, the wave structured fiber is stretched axially, increasing the stretchability of the sensor and achieving a large detection range strain sensing. Meanwhile, axial strain reduces the longitudinal amplitude of the fiber wave structure, effectively changing the total reflection angle of the transmitted beam at the peak and valley (SPR incidence angle) to achieve high sensitivity SPR strain sensing. The experiment indicates that the strain detection range of the sensor can reach 0-1800µÎµ, with a maximum strain sensitivity of 36.25pm/µÎµ. The wave structured fiber SPR strain sensor designed in this article provides a new approach to improve the range and sensitivity of strain detection.

Spiral cone fiber SPR sensor for detecting ginsenoside Rg1.

The conical fiber SPR sensor is easy to manufacture and has been used in biochemical detection research, but it has the problem of structural fragility. This article proposes a spiral cone fiber SPR sensor, which introduces a spiral structure on the 76µm fiber coarse cone, achieving good coupling of the core mode into the cladding mode, and improving the physical strength and practicality of the cone-shaped fiber SPR sensor. By modifying the target protein on the surface of the sensor gold film, specific detection of ginsenoside Rg1, an active ingredient of traditional Chinese medicine ginseng, was achieved. The detection sensitivity was 0.138 nm/(µm/ml) and the detection limit was 0.22µm/ml. The proposed spiral cone fiber SPR sensor provides a new scheme for the specific detection of active ingredients in traditional Chinese medicine, which is structurally stable and physically strong.

Prevalence and Genetic Characterization of Giardia duodenalis and Blastocystis spp. in Black Goats in Shanxi Province, North China: From a Public Health Perspective.

Blastocystis spp. and Giardia duodenalis are two prevalent zoonotic intestinal parasites that can cause severe diarrhea and intestinal diseases in humans and many animals. Black goat (Capra hircus) farming is increasingly important in China due to the remarkable adaptability, high reproductive performance, rapid growth rate, and significant economic value of black goats. A number of studies have indicated that black goats are the potential reservoir of multiple zoonotic protozoans in China; however, the prevalence and zoonotic status of G. duodenalis and Blastocystis spp. in black goats in Shanxi Province is still unknown. Thus, a total of 1200 fecal samples of black goats were collected from several representative regions at different altitudes in Shanxi Province and were examined for the presence and genotypes of G. duodenallis and Blastocystis spp. by amplifying the beta-giardin (bg), glutamate dehydrogenase (gdh), and triosephosphate isomerase (tpi) loci of G. duodenalis and SSU rRNA of Blastocystis spp. using PCR and sequence analysis methods, respectively. The overall prevalence of G. duodenalis and Blastocystis spp. in black goats in Shanxi Province were 7.5% and 3.5%, respectively. Two assemblages (B and E) of G. duodenalis and four subtypes (ST5, ST10, ST14, and ST30) of Blastocystis spp. were identified, with assemblage E and ST10 as the prevalent genotype and subtype in black goats, respectively. One novel multilocus genotype (MLG) was identified in MLG-E and was designated as MLG-E12. For both G. duodenalis and Blastocystis spp., the prevalence was significantly related to the region and age groups (p < 0.05). This is the first report on the prevalence of G. duodenalis and Blastocystis spp. in black goats in Shanxi Province. These results not only provide baseline data for the prevention and control of both parasites in black goats in Shanxi Province, but also enhance our understanding of the genetic composition and zoonotic potential of these two parasites.

Hi-C guided many-polymer model to decipher 3D genome organization.

We propose a Hi-C data-based many-polymer model which allows us to generate an ensemble of multi-scale genome structures. We demonstrate the efficacy of our model by validating the generated structures against experimental measurements and employ them to address key questions regarding genome organization. Our model first confirms a significant correlation between the chromosome size and the nuclear positioning. Specifically, smaller chromosomes are distributed at the core region, whereas the larger chromosomes are at the periphery interacting with the nuclear envelope. The spatial distribution of A- and B-type compartments, which is non-trivial to infer from the corresponding Hi-C maps alone, can also be elucidated using our model, accounting for an issue such as the effect of chromatin-lamina interaction on the compartmentalization of conventional and inverted nuclei. In accordance with imaging data, the overall shape of the 3D genome structures generated from our model displays significant variation. As a case study, we apply our method to the yellow fever mosquito genome, finding that the predicted morphology displays, on average, more globular shape than the previously suggested spindle-like organization, and that our prediction better aligns with the FISH data. Our model has a great potential to be extended to investigate many outstanding issues concerning the 3D genome organization.

Semi-crystalline polymers with supramolecular synergistic interactions: from mechanical toughening to dynamic smart materials.

Semi-crystalline polymers (SCPs) with anisotropic amorphous and crystalline domains as the basic skeleton are ubiquitous from natural products to synthetic polymers. The combination of chemically incompatible hard and soft phases contributes to unique thermal and mechanical properties. The further introduction of supramolecular interactions as noncovalently interacting crystal phases and soft dynamic crosslinking sites can synergize with covalent polymer chains, thereby enabling effective energy dissipation and dynamic rearrangement in hierarchical superstructures. Therefore, this review will focus on the design principles of SCPs by discussing supramolecular construction strategies and state-of-the-art functional applications from mechanical toughening to sophisticated functions such as dynamic adaptivity, shape memory, ion transport, etc. Current challenges and further opportunities are discussed to provide an overview of possible future directions and potential material applications.

Treg-Derived Extracellular Vesicles: Roles in Diseases and Theranostics.

Regulatory T cells (Tregs), a subset of CD4+ T cells, are indispensable in maintaining immune self-tolerance and have been utilized in various diseases. Treg-derived extracellular vesicles (Treg-EVs) have been discovered to play an important role in the mechanism of Treg functions. As cell-derived membranous particles, EVs carry multiple bioactive substances that possess tremendous potential for theranostics. Treg-EVs are involved in numerous physiological and pathological processes, carrying proteins and miRNAs inherited from the parental cells. To comprehensively understand the function of Treg-EVs, here we reviewed the classification of Treg-EVs, the active molecules in Treg-EVs, their various applications in diseases, and the existing challenges for Treg-EVs based theranostics. This Review aims to clarify the feasibility and potential of Treg-EVs in diseases and theranostics, facilitating further research and application of Treg-EVs.

Interpretable baseflow segmentation and prediction based on numerical experiments and deep learning.

Baseflow is a crucial water source in the inland river basins of high-cold mountainous region, playing a significant role in maintaining runoff stability. It is challenging to select the most suitable baseflow separation method in data-scarce high-cold mountainous region and to evaluate effects of climate factors and underlying surface changes on baseflow variability and seasonal distribution characteristics. Here we attempt to address how meteorological factors and underlying surface changes affect baseflow using the Grey Wolf Optimizer Digital Filter Method (GWO-DFM) for rapid baseflow separation and the Long Short-Term Memory (LSTM) neural network model for baseflow prediction, clarifying interpretability of the LSTM model in baseflow forecasting. The proposed method was successfully implemented using a 63-year time series (1958-2020) of flow data from the Tai Lan River (TLR) basin in the high-cold mountainous region, along with 21 years of ERA5-land meteorological data and MODIS data (2000-2020). The results indicate that: (1) GWO-DFM can rapidly identify the optimal filtering parameters. It employs the arithmetic average of three methods, namely Chapman, Chapman-Maxwell and Eckhardt filter, as the best baseflow separation approach for the TLR basin. Additionally, the baseflow significantly increases after the second mutation of the baseflow rate. (2) Baseflow sources are mainly influenced by precipitation infiltration, glacier frozen soil layers, and seasonal ponding. (3) Solar radiation, temperature, precipitation, and NDVI are the primary factors influencing baseflow changes, with Nash-Sutcliffe efficiency coefficients exceeding 0.78 in both the LSTM model training and prediction periods. (4) Changes in baseflow are most influenced by solar radiation, temperature, and NDVI. This study systematically analyzes the changes in baseflow and response mechanisms in high-cold mountainous region, contributing to the management of water resources in mountainous basins under changing environmental conditions.

V4RIN: visual analysis of regional industry network with domain knowledge.

The regional industry network (RIN) is a type of financial network derived from industry networks that possess the capability to describe the connections between specific industries within a particular region. For most investors and financial analysts lacking extensive experience, the decision-support information provided by industry networks may be too vague. Conversely, RINs express more detailed and specific industry connections both within and outside the region. As RIN analysis is domain-specific and current financial network analysis tools are designed for generalized analytical tasks and cannot be directly applied to RINs, new visual analysis approaches are needed to enhance information exploration efficiency. In this study, we collaborated with domain experts and proposed V4RIN, an interactive visualization analysis system that integrates predefined domain knowledge and data processing methods to support users in uploading custom data. Through multiple views in the system panel, users can comprehensively explore the structure, geographical distribution, and spatiotemporal variations of the RIN. Two case studies were conducted and a set of expert interviews with five domain experts to validate the usability and reliability of our system.

Mineralization, degradation and osteogenic property of polylactide multicomponent porous composites for bone repair: In vitro and in vivo study.

Gelatin and hydroxyapatite were assembled into polylactide porous matrix to prepare multicomponent porous composites for bone repair (PLA-gH). PLA-gH possessed a superior ability of mineralization. During simulated body fluids (SBF), the spherical Ca-P depositions on surface of PLA-gH became bulk as Ca/P decreased, while they locally turned into the rod with different variation in Ca/P during SBF containing bovine serum albumin (SBF-BSA), indicating that the mineralization of PLA-gH could be regulated by BSA. Meanwhile, PLA-gH possessed good degradation behaviour, especially in SBF-BSA, the degradation of PLA porous matrix was higher than that in SBF after 14-day immersion, whose crystallinity (Xc) decreased to a slightly lower level. Gelatin and hydroxyapatite endowed PLA-gH with good osteogenic property, characterized by obvious osteogenic differentiation and bone regeneration. In terms of predicting the cytocompatibility, osteogenic differentiation and new bone mineralization of PLA-gH by in vitro methods, applying SBF-BSA may be more reliable than SBF.

Proficiency Development and Learning Curve in Robot-Assisted Spine Surgery Using the ExcelsiusGPS® System: Experience From a Single Institution.

STUDY DESIGN: Retrospective Cohort Study Objectives: Robot-assisted spine surgery (RASS) is a rapidly evolving technique with potential benefits for improving surgical outcomes. A number of studies on RASS learning curve have focused on early iterations of the Mazor robot. Limited research exists on the learning curve associated with using the Globus Medical ExcelsiusGPS® system. In this retrospective study, we aimed to evaluate the learning curve of RASS using the ExcelsiusGPS® system at a single institution. METHODS: A total of 95 patients (541 screws) who underwent RASS between 2021 and 2022 were included. Variables including operative time, robot registration time, screw placement time, fluoroscopy utilization, and complications were analyzed. Statistical analysis was performed using descriptive statistics and two-sample t-tests. RESULTS: The average operative time significantly decreased after the first 14 cases, indicating a learning curve. However, no significant improvement was observed in robot registration time. Notably, screw placement time significantly improved after approximately 13 cases. When controlling for the number of levels fused, the trends remained consistent. CONCLUSIONS: Our study confirmed the presence of a learning curve in RASS using the ExcelsiusGPS® system and demonstrated rapid proficiency development. Our findings highlight the relatively quick learning curve of 1 RASS system.

Population genomics analysis reveals footprints of selective breeding in a rapid-growth variety of Paulownia fortunei with apical dominance.

Paulownia fortunei is an ecologically and economically valuable tree cultivated for its rapid growth and high-quality timber. To enhance Paulownia germplasm, we have developed the elite variety QingT with patented advantages in growth rate and apical dominance. To illuminate the genetic basis of QingT's superior traits, here we harness comparative population genomics to analyze genomic variation patterns between QingT and common Paulownia. We performed whole-genome re-sequencing of 30 QingT and 30 common samples, detecting 15.6 million SNPs and 2.6 million indels. Phylogeny and population structure analyses robustly partitioned common and QingT into distinct groups which indicate robust genome stabilization. QingT exhibited reduced heterozygosity and linkage disequilibrium decay compared to common Paulownia, reflecting high recombination, indicating hybridizing effects with common white-flowered string is the source of its patented advantages. Genome selection scans uncovered 25 regions of 169 genes with elevated nucleotide diversity, indicating selection sweeps among groups. Functional analysis of sweep genes revealed upregulation of ribosomal, biosynthesis, and growth pathways in QingT, implicating enhanced protein production and developmental processes in its rapid growth phenotype. This study's insights comprehensively chart genomic variation during Paulownia breeding, localizing candidate loci governing agronomic traits, and underpinnings of future molecular breeding efforts to boost productivity.

The self-designed reactor to achieve efficient degradation of polyvinyl alcohol under high-pressure and high-temperature conditions.

A huge amount of polyvinyl alcohol (PVA) fabric is abandoned from nuclear power plants every year, the traditional treatment process will occupy land resources and pollute the environment; therefore, a lot of research has been carried out on the chemical treatment of PVA fabric. Herein, the performance of degradation of polyvinyl alcohol under high-pressure and high-temperature conditions is investigated. The effects of the initial pH value, reaction temperature, molar ratio of H2O2/Fe2+, and H2O2 dosage on PVA degradation were evaluated. In the tested ranges in this work, the degradation of PVA fabric via high-pressure and high-temperature method was optimum at the initial pH value of 4, reaction temperature of 300℃, molar ratio of H2O2/Fe2+ as 10, and H2O2 dosage of 13 g/L. The PVA removal rate and TOC removal rate were 99.99% and 97.36%, respectively. Meanwhile, the high-pressure and high-temperature methods also had a great effect on the removal of Rhodamine-B and Reactive Red X-3B, the removal rates of Rhodamine-B and Reactive Red X-3B were 99.83% and 99.76%, respectively. The reaction mechanism of high-pressure and high-temperature methods was also discussed in this study.

A distinct "repair" role of regulatory T cells in fracture healing.

Regulatory T cells (Tregs) suppress immune responses and inflammation. Here, we described the distinct nonimmunological role of Tregs in fracture healing. The recruitment from the circulation pool, peripheral induction, and local expansion rapidly enriched Tregs in the injured bone. The Tregs in the injured bone displayed superiority in direct osteogenesis over Tregs from lymphoid organs. Punctual depletion of Tregs compromised the fracture healing process, which leads to increased bone nonunion. In addition, bone callus Tregs showed unique T-cell receptor repertoires. Amphiregulin was the most overexpressed protein in bone callus Tregs, and it can directly facilitate the proliferation and differentiation of osteogenic precursor cells by activation of phosphatidylinositol 3-kinase/protein kinase B signaling pathways. The results of loss- and gain-function studies further evidenced that amphiregulin can reverse the compromised healing caused by Treg dysfunction. Tregs also enriched in patient bone callus and amphiregulin can promote the osteogenesis of human pre-osteoblastic cells. Our findings indicate the distinct and nonredundant role of Tregs in fracture healing, which will provide a new therapeutic target and strategy in the clinical treatment of fractures.