Rolling bearing fault diagnosis based on fine-grained multi-scale Kolmogorov entropy and WOA-MSVM.

In allusion to solve the issue of fault diagnosis for bearing and other rotatory machinery, a technique based on fined-grained multi-scale Kolmogorov entropy and whale optimized multi-class support vector machine (abbreviated as FGMKE-WOA-MSVM) is proposed. Firstly, vibration signals are decomposed by fine-grained multi-scale decomposition, and the Kolmogorov entropy of the sub-signals at different analysis scales is calculated as the multi-dimension feature vector, which quantitatively characterize the complexity of the signal at multi-scales. Aiming at the problem of sensitive parameters selection for multi-class support vector machine model (abbreviated as MSVM), the whale optimization algorithm (abbreviated as WOA) is introduced to optimize the penalty factor and kernel function parameter, and constructing optimal WOA-MSVM model. Finally, an instance analysis is carried out with Jiangnan University bearing datasets to verify the effectiveness and superiority of this technique. The results show that compared with different feature vectors and models such as K nearest neighbors (abbreviated as KNN) and Decision Tree (abbreviated as RF), the proposed technique is superior with fast computation speed and high diagnostic efficiency.

Rolling bearing fault diagnosis based on RQA with STD and WOA-SVM.

A rolling bearing fault diagnosis method based on Recursive Quantitative Analysis (RQA) combined with time domain feature extraction and Whale Optimization Algorithm Support Vector Machine (WOA-SVM) is proposed. Firstly, the recurrence graph of the vibration signal is drawn, and the nonlinear feature parameters in the recurrence graph combined with Standard Deviation (STD) are extracted by recursive quantitative analysis method to generate feature vectors; after that, in order to construct the optimal support vector machine model, the Whale Optimization Algorithm is used to optimize the c and g parameters. Finally, both Recursive Quantitative Analysis and standard deviation are combined with the WOA-SVM model to perform fault diagnosis of rolling bearings. The rolling bearing datasets from Case Western Reserve University and Jiangnan University were used for example analysis, and the fault identification accuracy reached 100% and 95.00%, respectively. Compared to other methods, the method proposed in this paper has higher diagnostic accuracy and wide practical applicability, and the risk of accidents can be reduced through accurate fault diagnosis, which is also important for safety and environmental policies. This research originated in the field of mechanical fault diagnosis to solve the problem of fault diagnosis of rolling bearings in industrial production, it builds on previous research and explores new methods and techniques to fill some gaps in the field of mechanical fault diagnosis.

[Leptin-mediated ERK Signaling Pathway Promotes the Transformation 
of Rat Alveolar Type II Epithelial Cells Induced by Yunnan Tin Mine Dust].

BACKGROUND: Currently, a significant number of miners are involved in mining operations at the Gejiu tin mine in Yunnan. This occupational setting is associated with exposure to dust particles, heavy metals, polycyclic aromatic hydrocarbons, and radioactive radon, thereby significantly elevating the risk of lung cancer. This study aims to investigate the involvement of leptin-mediated extracellular regulated protein kinase (ERK) signaling pathway in the malignant transformation of rat alveolar type II epithelial cells induced by Yunnan tin mine dust. METHODS: Immortalized rat alveolar cells type II (RLE-6TN) cells were infected with Yunnan tin mine dust at a concentration of 200 µg/mL for nine consecutive generations to establish the infected cell model, which was named R200 cells. The cells were cultured normally, named as R cells. The expression of leptin receptor in both cell groups was detected using the Western blot method. The optimal concentration of leptin and mitogen-activated protein kinase kinase (MEK) inhibitor (U0126) on R200 cells was determined using the MTT method. Starting from the 20th generation, the cells in the R group were co-cultured with leptin, while the cells in the R200 group were co-cultured with the MEK inhibitor U0126. The morphological alterations of the cells in each group were visualized utilizing hematoxylin-eosin staining. Additionally, concanavalin A (ConA) was utilized to detect any morphological differences, and an anchorage-independent growth assay was conducted to assess the malignant transformation of the cells. The changes in the ERK signaling pathway in epithelial cells after the action of leptin were detected using the Western blot method. RESULTS: Both the cells in the R group and R200 group express leptin receptor OB-R. Compared to the R200 group, the concentration of leptin at 100 ng/mL shows the most significant pro-proliferation effect. The proliferation of R200 cells infected with the virus is inhibited by 30 µmol/L U0126, and a statistically significant divergence was seen when compared to the control group (P<0.05). Starting from the 25th generation, the cell morphology of the leptin-induced R200 group (R200L group) underwent changes, leading to malignant transformation observed at the 30th generation. The characteristics of malignant transformation became evident by the 40th generation in the R200L group. In contrast, the other groups showed agglutination of P40 cells, and the speed of cell aggregation increased with an increase in ConA concentration. Notably, the R200L group exhibited faster cell aggregation compared to the U0126-induced R200 (R200LU) group. Additionally, the cells in the R200L group were capable of forming clones starting from P30, with a colony formation rate of 2.25‰±0.5‰. However, no clonal colonies were observed in the R200LU group and R200 group. The expression of phosphorylated extracellular signal-regulated kinase (pERK) was enhanced in cells of the R200L group. However, when the cells in the R200L group were treated with U0126, a blocking agent, the phosphorylation level of pERK decreased. CONCLUSIONS: Leptin can promote the malignant transformation of lung epithelial cells infected by mine dust, and the ERK signaling pathway may be necessary for the transformation of alveolar type II epithelial cells induced by Yunnan tin mine dust.

Dynamic Semi-Supervised Federated Learning Fault Diagnosis Method Based on an Attention Mechanism.

In cases where a client suffers from completely unlabeled data, unsupervised learning has difficulty achieving an accurate fault diagnosis. Semi-supervised federated learning with the ability for interaction between a labeled client and an unlabeled client has been developed to overcome this difficulty. However, the existing semi-supervised federated learning methods may lead to a negative transfer problem since they fail to filter out unreliable model information from the unlabeled client. Therefore, in this study, a dynamic semi-supervised federated learning fault diagnosis method with an attention mechanism (SSFL-ATT) is proposed to prevent the federation model from experiencing negative transfer. A federation strategy driven by an attention mechanism was designed to filter out the unreliable information hidden in the local model. SSFL-ATT can ensure the federation model's performance as well as render the unlabeled client capable of fault classification. In cases where there is an unlabeled client, compared to the existing semi-supervised federated learning methods, SSFL-ATT can achieve increments of 9.06% and 12.53% in fault diagnosis accuracy when datasets provided by Case Western Reserve University and Shanghai Maritime University, respectively, are used for verification.

A Multiscale Recursive Attention Gate Federation Method for Multiple Working Conditions Fault Diagnosis.

Federated learning (FL) is an effective method when a single client cannot provide enough samples for multiple condition fault diagnosis of bearings since it can combine the information provided by multiple clients. However, some of the client's working conditions are different; for example, different clients are in different stages of the whole life cycle, and different clients have different loads. At this point, the status of each client is not equal, and the traditional FL approach will lead to some clients' useful information being ignored. The purpose of this paper is to investigate a multiscale recursive FL framework that makes the server more focused on the useful information provided by the clients to ensure the effectiveness of FL. The proposed FL method can build reliable multiple working condition fault diagnosis models due to the increased focus on useful information in the FL process and the full utilization of server information through local multiscale feature fusion. The validity of the proposed method was verified with the Case Western Reserve University benchmark dataset. With less local client training data and complex fault types, the proposed method improves the accuracy of fault diagnosis by 23.21% over the existing FL fault diagnosis.

Sequential multi-parametric MRI in assessment of the histological subtype and features in the malignant pleural mesothelioma xenografts.

Objective: It is still a challenge to find a noninvasive technique to distinguish the histological subtypes of malignant pleural mesothelioma (MPM) and characterize the development of related histological features. We investigated the potential value of multiparametric MRI in the assessment of the histological subtype and development of histologic features in the MPM xenograft model. Methods: MPM xenograft models were developed by injecting tumour cells into the right axillary space of nude mice. The T1, T2, R2*, T2*, apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), and perfusion fraction (f) at 14 d, 28 d, and 42 d were measured and compared between the epithelial and biphasic MPM. Correlations between multiparametric MRI parameters and histologic features, including necrotic fraction (NF) and microvessel density (MVD), were analysed. Results: This study found that T2, T2* and IVIM-DWI parameters can reflect the spatial and temporal heterogeneity of MPM. Compared to the epithelial MPM, T2 and T2* were higher and ADC, D, D*, and f were lower in the biphasic MPM (P < 0.05). MRI parameters were different in different stages of epithelial and biphasic MPM. Moderate correlations were found between ADC and tumor volume and NF in the epithelial MPM, and there was a correlation between f and tumor volume and NF and MVD in the two groups. Conclusion: MRI parameters changed with tumor progression in a xenograft model of MPM. MRI parameters may provide useful biomarkers for evaluating the histological subtype and histological features development of MPM.

Federated Learning Based Fault Diagnosis Driven by Intra-Client Imbalance Degree.

Federated learning is an effective means to combine model information from different clients to achieve joint optimization when the model of a single client is insufficient. In the case when there is an inter-client data imbalance, it is significant to design an imbalanced federation aggregation strategy to aggregate model information so that each client can benefit from the federation global model. However, the existing method has failed to achieve an efficient federation strategy in the case when there is an imbalance mode mismatch between clients. This paper aims to design a federated learning method guided by intra-client imbalance degree to ensure that each client can receive the maximum benefit from the federation model. The degree of intra-client imbalance, measured by gain of a class-by-class model update on the federation model based on a small balanced dataset, is used to guide the designing of federation strategy. An experimental validation for the benchmark dataset of rolling bearing shows that a 23.33% improvement of fault diagnosis accuracy can be achieved in the case when the degree of imbalance mode mismatch between clients is prominent.

The Value of Ultra-High-Frequency Ultrasound for the Differentiation between Superficial Basal Cell Carcinoma and Bowen's Disease.

BACKGROUND: The similar visual appearance of superficial basal cell carcinoma (sBCC) and Bowen's disease (BD) may cause confusion for diagnosis. OBJECTIVE: The aim of the study was to investigate the value of ultra-high-frequency ultrasound (uHFUS) in differentiating sBCC from BD. MATERIALS AND METHODS: This prospective study included a pilot cohort of 110 patients (73 BDs and 37 sBCCs) from November 2016 to October 2020 and a validation cohort of 42 patients (30 BDs and 12 sBCCs) from July 2021 to December 2021. Clinical and uHFUS features of pathologically confirmed sBCC and BD were assessed. A predictive model was developed based on the uHFUS features of the pilot cohort. Subsequently, the model was validated and compared with clinical diagnosis in the validation cohort. RESULTS: uHFUS features with significant differences between sBCC and BD included lesion surface, skin layer involvement, hyperkeratosis, and hyperechoic spots (all p < 0.05). A prediction model based on the above features was established to identify sBCC and BD in the pilot and validation cohorts with areas under the curve (AUC) of 0.908 and 0.923, sensitivity of 82.3% and 83.3%, specificity of 91.9% and 91.7%, and accuracy of 85.5% and 85.7%, respectively, which were significantly higher than those obtained by clinical diagnosis based on photographic pictures of lesions, with the AUC of 0.692, sensitivity of 63.3%, specificity of 75.3%, and accuracy of 66.7% (all p < 0.05). CONCLUSION: uHFUS provides detailed internal features of sBCC and BD, which facilitates the differentiation between sBCC and BD, and its diagnostic performance is superior to clinical diagnosis.

Trend Feature Consistency Guided Deep Learning Method for Minor Fault Diagnosis.

Deep learning can be applied in the field of fault diagnosis without an accurate mechanism model. However, the accurate diagnosis of minor faults using deep learning is limited by the training sample size. In the case that only a small number of noise-polluted samples is available, it is crucial to design a new learning mechanism for the training of deep neural networks to make it more powerful in feature representation. The new learning mechanism for deep neural networks model is accomplished by designing a new loss function such that accurate feature representation driven by consistency of trend features and accurate fault classification driven by consistency of fault direction both can be secured. In such a way, a more robust and more reliable fault diagnosis model using deep neural networks can be established to effectively discriminate those faults with equal or similar membership values of fault classifiers, which is unavailable for traditional methods. Validation for gearbox fault diagnosis shows that 100 training samples polluted with strong noise are adequate for the proposed method to successfully train deep neural networks to achieve satisfactory fault diagnosis accuracy, while more than 1500 training samples are required for traditional methods to achieve comparative fault diagnosis accuracy.

Aged bone matrix-derived extracellular vesicles as a messenger for calcification paradox.

Adipocyte differentiation of bone marrow mesenchymal stem/stromal cells (BMSCs) instead of osteoblast formation contributes to age- and menopause-related marrow adiposity and osteoporosis. Vascular calcification often occurs with osteoporosis, a contradictory association called "calcification paradox". Here we show that extracellular vesicles derived from aged bone matrix (AB-EVs) during bone resorption favor BMSC adipogenesis rather than osteogenesis and augment calcification of vascular smooth muscle cells. Intravenous or intramedullary injection of AB-EVs promotes bone-fat imbalance and exacerbates Vitamin D3 (VD3)-induced vascular calcification in young or old mice. Alendronate (ALE), a bone resorption inhibitor, down-regulates AB-EVs release and attenuates aging- and ovariectomy-induced bone-fat imbalance. In the VD3-treated aged mice, ALE suppresses the ovariectomy-induced aggravation of vascular calcification. MiR-483-5p and miR-2861 are enriched in AB-EVs and essential for the AB-EVs-induced bone-fat imbalance and exacerbation of vascular calcification. Our study uncovers the role of AB-EVs as a messenger for calcification paradox by transferring miR-483-5p and miR-2861.

Multifunctional exosome-mimetics for targeted anti-glioblastoma therapy by manipulating protein corona.

Targeted drug delivery to the glioblastoma (GBM) overcoming blood-brain barrier (BBB) has been challenging. Exosomes are promising vehicles for brain tumor drug delivery, but the production and purification hinder its application for nanomedicine. Besides, the formation of protein corona (PC) may affect the behaviour of nanocarriers. Here, multifunctional exosomes-mimetics (EM) are developed and decorated with angiopep-2 (Ang) for enhancing GBM drug delivery by manipulating PC. Docetaxel (DTX)-loaded EM with Ang modification (DTX@Ang-EM) show less absorption of serum proteins and phagocytosis by macrophages. Ang-EM show enhanced BBB penetration ability and targeting ability to the GBM. Ang-EM-mediated delivery increase the concentration of DTX in the tumor area. The multifunctional DTX@Ang-EM exhibits significant inhibition effects on orthotopic GBM growth with reduced side effects of the chemotherapeutic. Findings from this study indicate that the developed DTX@Ang-EM provide a new strategy for targeted brain drug delivery and GBM therapy.

Neuronal Induction of Bone-Fat Imbalance through Osteocyte Neuropeptide Y.

A differentiation switch of bone marrow mesenchymal stem/stromal cells (BMSCs) from osteoblasts to adipocytes contributes to age- and menopause-associated bone loss and marrow adiposity. Here it is found that osteocytes, the most abundant bone cells, promote adipogenesis and inhibit osteogenesis of BMSCs by secreting neuropeptide Y (NPY), whose expression increases with aging and osteoporosis. Deletion of NPY in osteocytes generates a high bone mass phenotype, and attenuates aging- and ovariectomy (OVX)-induced bone-fat imbalance in mice. Osteocyte NPY production is under the control of autonomic nervous system (ANS) and osteocyte NPY deletion blocks the ANS-induced regulation of BMSC fate and bone-fat balance. γ-Oryzanol, a clinically used ANS regulator, significantly increases bone formation and reverses aging- and OVX-induced osteocyte NPY overproduction and marrow adiposity in control mice, but not in mice lacking osteocyte NPY. The study suggests a new mode of neuronal control of bone metabolism through the ANS-induced regulation of osteocyte NPY.

Erratum: Inhibition of miR-331-3p and miR-9-5p ameliorates Alzheimer's disease by enhancing autophagy: Erratum.

[This corrects the article DOI: 10.7150/thno.47408.].

Fructose-coated Ångstrom silver prevents sepsis by killing bacteria and attenuating bacterial toxin-induced injuries.

Serious infection caused by multi-drug-resistant bacteria is a major threat to human health. Bacteria can invade the host tissue and produce various toxins to damage or kill host cells, which may induce life-threatening sepsis. Here, we aimed to explore whether fructose-coated Ångstrom-scale silver particles (F-AgÅPs), which were prepared by our self-developed evaporation-condensation system and optimized coating approach, could kill bacteria and sequester bacterial toxins to attenuate fatal bacterial infections. Methods: A series of in vitro assays were conducted to test the anti-bacterial efficacy of F-AgÅPs, and to investigate whether F-AgÅPs could protect against multi-drug resistant Staphylococcus aureus (S. aureus)- and Escherichia coli (E. coli)-induced cell death, and suppress their toxins (S. aureus hemolysin and E. coli lipopolysaccharide)-induced cell injury or inflammation. The mouse models of cecal ligation and puncture (CLP)- or E. coli bloodstream infection-induced lethal sepsis were established to assess whether the intravenous administration of F-AgÅPs could decrease bacterial burden, inhibit inflammation, and improve the survival rates of mice. The levels of silver in urine and feces of mice were examined to evaluate the excretion of F-AgÅPs. Results: F-AgÅPs efficiently killed various bacteria that can cause lethal infections and also competed with host cells to bind with S. aureus α-hemolysin, thus blocking its cytotoxic activity. F-AgÅPs inhibited E. coli lipopolysaccharide-induced endothelial injury and macrophage inflammation, but not by directly binding to lipopolysaccharide. F-AgÅPs potently reduced bacterial burden, reversed dysregulated inflammation, and enhanced survival in mice with CLP- or E. coli bloodstream infection-induced sepsis, either alone or combined with antibiotic therapy. After three times injections within 48 h, 79.18% of F-AgÅPs were excreted via feces at the end of the 14-day observation period. Conclusion: This study suggests the prospect of F-AgÅPs as a promising intravenous agent for treating severe bacterial infections.

Artificial exosomes for translational nanomedicine.

Exosomes are lipid bilayer membrane vesicles and are emerging as competent nanocarriers for drug delivery. The clinical translation of exosomes faces many challenges such as massive production, standard isolation, drug loading, stability and quality control. In recent years, artificial exosomes are emerging based on nanobiotechnology to overcome the limitations of natural exosomes. Major types of artificial exosomes include 'nanovesicles (NVs)', 'exosome-mimetic (EM)' and 'hybrid exosomes (HEs)', which are obtained by top-down, bottom-up and biohybrid strategies, respectively. Artificial exosomes are powerful alternatives to natural exosomes for drug delivery. Here, we outline recent advances in artificial exosomes through nanobiotechnology and discuss their strengths, limitations and future perspectives. The development of artificial exosomes holds great values for translational nanomedicine.

Exosomes and biomimetic nanovesicles-mediated anti-glioblastoma therapy: A head-to-head comparison.

Exosomes (Exos) are promising vehicles for brain drug delivery due to nanosize and the ability to breach the blood-brain barrier (BBB). But the low yield of natural exosomes limits its application for nanomedicine. The generation of bioinspired nanovesicles (BNVs) that mimicking Exos is attractive, but there is a lack of comparative evaluation of Exos and BNVs. Here, we perform the first head-to-head comparison study of Exos and BNVs for brain tumor drug delivery. We show that BNVs derived from brain-derived endothelial cells are competent alternative nanocarrier to natural exosomes. The drug-loading capacity of Exos and BNVs are similar, but the yield of BNVs is substantially higher (500-fold) than Exos. Doxorubicin (DOX)-loaded BNVs (BNV/DOX) and DOX-loaded Exos (Exo/DOX) showed similar pharmacokinetic profiles and prolonged circulation od DOX. Despite inconsistent mechanisms, BNV/DOX can across the BBB, and exhibit suppression effects similar to Exo/DOX on the progress of glioblastoma (GBM) in zebrafish and in vivo subcutaneous and orthotopic xenografts mice models, with minimal systemic toxicity. Findings from this head-to-head comparison study indicate that autologous BNVs is a effective alternative of Exos for brain tumor nanomedicine.

Control system research in wave compensation based on particle swarm optimization.

For the offshore wave compensation control system, its controller setting will directly affect the platform's compensation effect. In order to study the wave compensation control system and optimization strategy, we build and simulate the wave compensation control model by using particle swarm optimization (PSO) to optimize the controller's control parameters and compare the results with other intelligent algorithms. Then we compare the response errors of the wave compensation platform under different PID controllers; and compare the particle swarm algorithm's response results and the genetic algorithm to the system controller optimization. The results show that the particle swarm algorithm is 63.94% lower than the genetic algorithm overshoot, and the peak time is 0.26 s lower, the adjustment time is 1.4 s lower than the genetic algorithm. It shows that the control effect of the wave compensation control system has a great relationship with the controller's parameter selection. Meanwhile, the particle swarm optimization algorithm's optimization can set the wave compensation PID control system, and it has the optimization effect of small overshoot and fast response time. This paper proposes the application of the particle swarm algorithm to the wave compensation system. It verifies the superiority of the method after application, and provides a new research reference for the subsequent research on the wave compensation control systems.

Biomimetic Liposome with Surface-Bound Elastase for Enhanced Tumor Penetration and Chemo-Immumotherapy.

Dense extracellular matrix (ECM) in the tumor stroma has been a challenge for drug penetration and cytotoxic T lymphocyte (CTL) infiltration. Neutrophil elastase (NE), in surface-bound form, can destruct ECM rapidly, may be used for remodeling tumor ECM, and overcoming tumor stromal barrier. Focusing on elastosis in triple-negative breast tumor, biomimetic liposomes with chimeric cell membrane proteins (LMP) are developed and for the first time, it is demonstrated that LMP with surface-bound elastase (NE-LMP) can target and degrade ECM effectively in tumor stroma, with minimal toxicity to normal tissues. The pretreatment of NE-LMP increases the accumulation of chemotherapeutics at the tumor site and enhances antitumor effects. Also, NE-LMP facilitates CTL infiltration in tumors and exhibits enhanced chemo-immunotherapy in combination of PD-1 immune checkpoint blockade treatment in orthotopic 4T1 tumor-bearing mice, with significantly prolonged survival. Moreover, the remodeling of the tumor ECM by NE-LMP shows inhibiting effects on metastasis in the lung. Findings from this study suggest that NE-LMP holds promise for enhancing deep penetration of drug and infiltration of CTL in desmoplastic tumor by effective degrading ECM in the tumor stroma.

Harmine targets inhibitor of DNA binding-2 and activator protein-1 to promote preosteoclast PDGF-BB production.

Osteoporosis is one of the most common metabolic bone diseases affecting millions of people. We previously found that harmine prevents bone loss in ovariectomized mice via increasing preosteoclast platelet-derived growth factor-BB (PDGF-BB) production and type H vessel formation. However, the molecular mechanisms by which harmine promotes preosteoclast PDGF-BB generation are still unclear. In this study, we revealed that inhibitor of DNA binding-2 (Id2) and activator protein-1 (AP-1) were important factors implicated in harmine-enhanced preosteoclast PDGF-BB production. Exposure of RANKL-induced Primary bone marrow macrophages (BMMs), isolated from tibiae and femora of mice, to harmine increased the protein levels of Id2 and AP-1. Knockdown of Id2 by Id2-siRNA reduced the number of preosteoclasts as well as secretion of PDGF-BB in RANKL-stimulated BMMs administrated with harmine. Inhibition of c-Fos or c-Jun (components of AP-1) both reversed the stimulatory effect of harmine on preosteoclast PDGF-BB production. Dual-luciferase reporter assay analyses determined that PDGF-BB was the direct target of AP-1 which was up-regulated by harmine treatment. In conclusion, our data demonstrated a novel mechanism involving in the production of PDGF-BB increased by harmine, which may provide potential therapeutic targets for bone loss diseases.

Extracellular Vesicles from Child Gut Microbiota Enter into Bone to Preserve Bone Mass and Strength.

Recently, the gut microbiota (GM) has been shown to be a regulator of bone homeostasis and the mechanisms by which GM modulates bone mass are still being investigated. Here, it is found that colonization with GM from children (CGM) but not from the elderly (EGM) prevents decreases in bone mass and bone strength in conventionally raised, ovariectomy (OVX)-induced osteoporotic mice. 16S rRNA gene sequencing reveals that CGM reverses the OVX-induced reduction of Akkermansia muciniphila (Akk). Direct replenishment of Akk is sufficient to correct the OVX-induced imbalanced bone metabolism and protect against osteoporosis. Mechanistic studies show that the secretion of extracellular vesicles (EVs) is required for the CGM- and Akk-induced bone protective effects and these nanovesicles can enter and accumulate into bone tissues to attenuate the OVX-induced osteoporotic phenotypes by augmenting osteogenic activity and inhibiting osteoclast formation. The study identifies that gut bacterium Akk mediates the CGM-induced anti-osteoporotic effects and presents a novel mechanism underlying the exchange of signals between GM and host bone.