Signaling Complex Research Articles

Extreme examples of reparative chondrogenesis: molecular mechanisms

Restoring hyaline cartilage integrity remains a significant challenge in regenerative medicine. When damaged, the defect is replaced by fibrosis connective tissue, resulting in a loss of the biomechanical properties of the cartilage. This review examines the intricate molecular mechanisms underlying reparative chondrogenesis and presents examples from a variety of animal species. It provides a comprehensive overview of the signaling pathways and cellular responses that promote cartilage repair, showcasing the regenerative abilities of fish and amphibians, including the little skate and axolotl, and surprising cases of chondrogenesis in mammals like the naked mole-rat and the Acomys mouse. Unraveling the dynamic interplay between growth factors, cytokines, and extracellular matrix components will shed light on the complex signaling pathways controlling reparative chondrogenesis. The comparative analysis presented in this review reveals both conserved and species-specific molecular pathways involved in cartilage regeneration. This provides valuable information for translational studies. By uncovering the genetic and epigenetic determinants governing extreme examples of reparative chondrogenesis, this review provides a comprehensive framework for developing therapeutic strategies to improve cartilage repair in humans.

PH‐Dependent Assembly and Stability of Toll‐Like Receptor 3/dsRNA Signaling Complex: Insights from Constant pH Molecular Dynamics and Metadynamics Simulations

AbstractThe pH‐dependent assembly of Toll‐like receptors (TLRs), which triggers a threshold‐like response, is a key principle in immune signaling. While crystallography has revealed the intricate structure of these assembly complexes, the mechanisms underlying their pH dependency remain unclear. Herein, constant pH simulations and metadynamics are employed to investigate the pH‐dependent assembly and stability of the TLR3/dsRNA signaling complex. The findings demonstrate that system pH regulates complex assembly and stability by modulating the protonation and charge states of histidines. Histidines in TLR3 act as pH‐dependent, positively charged binding sites that capture negatively charged dsRNA. Additionally, these histidines form a [H682⁺]—[E626⁻] dipole, facilitating the assembly of two TLR3 molecules into an antisymmetric dimer through dipole–dipole interactions. Surprisingly, TLR3 can shift the pKa values of key histidines from their model pKa of 6.5, increasing protonation likelihood and enhancing ligand binding. Notably, the aromatic residue Phe84, located within the dsRNA binding site [His39⁺–His60⁺–Phe84–His108⁺], alters the pKa of His60 through cation‐π interactions with its protonated state. This study offers new insights into the molecular mechanisms underlying pH‐dependent immune signaling via higher‐order assemblies and suggests potential applications for histidine in self‐assembling biomaterials.

Endosomes serve as signaling platforms for RIG-I ubiquitination and activation.

RIG-I-like receptors (RLRs) are cytosolic RNA sensors critical for antiviral immunity. RLR activation is regulated by polyubiquitination and oligomerization following RNA binding. Yet, little is known about how RLRs exploit subcellular organelles to facilitate their posttranslational modifications and activation. Endosomal adaptor TAPE regulates the endosomal TLR and cytosolic RLR pathways. The potential interplay between RIG-I signaling and endosomes has been explored. Here, we report that endosomes act as platforms for facilitating RIG-I polyubiquitination and complex formation. RIG-I was translocated onto endosomes to form signaling complexes upon activation. Ablation of endosomes impaired RIG-I signaling to type I IFN activation. TAPE mediates the interaction and polyubiquitination of RIG-I and TRIM25. TAPE-deficient myeloid cells were defective in type I IFN activation upon RNA ligand and virus challenges. Myeloid TAPE deficiency increased the susceptibility to RNA virus infection in vivo. Our work reveals endosomes as signaling platforms for RIG-I activation and antiviral immunity.

In situ cell-surface conformation of the TCR-CD3 signaling complex

In situ cell-surface conformation of the TCR-CD3 signaling complex

Tactile Sensitivity to Missing tones in Complex Vibrotactile Signals.

Haptic interactions with objects induce complex vibrotactile signals that are central to tactile perception. Despite the broad literature on vibrotactile perception, surprisingly little is known about the sensory processing of complex tactile signals made of multiple pure tones. To fill this gap, the study reported here investigated the impact of the constitutive pure tones of a complex vibrotactile signal on its perception. Participants completed a 3-AFC task, in which they were asked to identify an odd signal among two complex references. The odd signal was created by removing one pure tone from the reference, which varied in spectral composition, harmonicity, and inter-frequency intervals. Each reference signal was made of either two, three, or four pure tones. The results revealed that the removed pure tone's value as well as the inter-frequency interval play a significant role on participants' performance whereas changes in harmonicity and complexity have little impact. The smaller the ratio between the removed frequency and the lowest one of the reference signals, the better the participants' capacity to identify the signal with the missing tone. As this ratio correlates with that of pure tone's perceived intensity, participants' performance can be linked to either of them. Analysis of a subset of complex signals made of pure tones perceived with roughly equal intensity showed that the correlation still holds but slightly decreases. Overall, these results suggest that perception of complex vibrations might be mediated by tactile mechanisms related to both frequency selectivity and to pure tones perceived intensity.

A B7-H3–Targeted CD28 Bispecific Antibody Enhances the Activity of Anti–PD-1 and CD3 T-cell Engager Immunotherapies

Abstract T-cell activation is a multistep process requiring T-cell receptor engagement by peptide–MHC complexes (Signal 1) coupled with CD28-mediated costimulation (Signal 2). Tumors typically lack expression of CD28 ligands, so tumor-specific Signal 1 (e.g., neoepitope presentation) without costimulation may be ineffective or even induce T-cell anergy. We designed the bispecific antibody XmAb808 to co-engage the tumor-associated antigen B7-H3 with CD28 to promote T-cell costimulation within the tumor microenvironment. XmAb808 costimulation was measured by its ability to activate and expand T cells and enhance T cell–mediated cancer cell killing in cocultures of human peripheral blood mononuclear cells and cancer cells and in mice engrafted with human peripheral blood mononuclear cells and tumor xenografts. XmAb808 avidly bound cancer cells and stimulated IL2 and IFNγ secretion from T cells cocultured with cancer cells engineered to deliver Signal 1 to T cells via a surface-expressed anti-CD3 antibody. XmAb808 enhanced expression of the antiapoptotic factor Bcl-xL and CD25, promoting survival and IL2-dependent expansion of T cells coupled with increased T cell–mediated cytotoxicity in vitro. XmAb808 combined with an EpCAM×CD3 bispecific antibody to enhance target cell killing through IL2-dependent expansion of CD25+ T cells. This combination also suppressed pancreatic tumor xenograft growth in mice. Furthermore, XmAb808 combined with an anti–programmed cell death protein 1 antibody to suppress breast tumor xenograft growth in mice. XmAb808 as monotherapy and in combination with an anti–programmed cell death protein 1 antibody is currently in clinical development in patients with advanced solid tumors. Our results suggest that XmAb808 may also combine with tumor antigen–targeted anti-CD3 (Signal 1) T-cell engagers.

Research on the Forward Simulation and Intelligent Detection of Defects in Highways Using Ground-Penetrating Radar

The increasing variety and frequency of subgrade defects in operational highways have led to a rise in road safety incidents. This study employed ground-penetrating radar (GPR) detection and forward simulation to analyze the characteristic patterns of common subgrade defects, such as looseness, voids, and cavities. Through the integration of instantaneous feature information from different defect patterns with complex signal techniques, the boundary judgment of structural layers and anomalies in GPR images of various subgrade defects was improved. An intelligent recognition platform was established, and a radar image dataset was created and trained to evaluate the recognition performance of the You Only Look Once (YOLO) v3 and Single-Shot Multi-Box Detector (SSD) algorithms. Evaluation metrics such as precision, recall, F1-score, average precision (AP), and mean average precision (mAP) were used to assess the detection efficiency and accuracy for subgrade defect images. The results showed that YOLO v3 achieved an average detection accuracy of 76.69%, while the SSD achieved 75.07%. This study demonstrates that the reliability of the intelligent recognition and classification of highway subgrade defects can be enhanced by using GPR for non-destructive testing.

Rolling Bearing Fault Diagnosis Model Based on External Attention Integrated Convolutional Neural Network under Imbalanced Data Conditions

Abstract Rolling bearings are essential components in numerous mechanical systems, and their failure can result in considerable downtime and expensive repairs. Therefore, accurate and timely fault diagnosis is vital for effective predictive maintenance and overall reliability. Traditional diagnostic methods often struggle with complex and non-stationary signals, compounded by issues of data imbalance in 
 realworld scenarios. A method for diagnosing rolling bearing faults has been developed in this paper utilizing External Attention (EA), Convolutional Neural Networks (CNN), and Continuous Wavelet Transform (CWT), specifically addressing the challenge of imbalanced sample data. This approach offers significant advantages, including a reduction in complexity by eliminating the need for data augmentation and leveraging external attention for enhanced feature extraction from samples. Compared to other attention mechanisms, this method demonstrates outstanding performance on both training and testing sets with imbalanced samples, exhibiting minimal overfitting tendencies. The proposed CWT-EACNN method effectively addresses the challenge of imbalanced sample data in rolling bearing fault diagnosis, demonstrating exceptional performance and reduced complexity.

OPTIMIZATION OF THE PARAMETERS OF SYNTHESIZED SIGNALS USING LINEAR APPROXIMATIONS BY THE NELDER-MEAD METHOD

Context. The article presents the results of a study of the effectiveness of using the Nelder-Mead method to optimize the parameters of linear approximations of synthesized signals. Algorithms have been developed and tested that integrate spectral, temporal, and statistical analyzes and provide reasonable optimization. The effectiveness of the application of the Nelder-Mead method was proven by experiment. The obtained results substantiate the improvement of the properties of the mutual correlation of signals and the reduction of the maximum deviations of the side lobes, which opens up prospects for the further application of the method in complex scenarios of signal synthesis. Objective. The purpose of the work is to evaluate the effectiveness of the application of the Nelder-Mead method when adjusting the parameters of linear approximations to optimize the mutual correlation and minimize side deviations of complex synthesized signals. Method. The main research method is the comparison of various optimization algorithms for the selection of the most effective approaches in linear approximations of synthesized signals, taking into account such criteria as accuracy, speed and minimization of deviations. Scientific works [1, 2, 4–6, 8, 9] present algorithms, including the Nelder-Mead method and differential evolution. The effectiveness of these methods is achieved due to adaptive optimization procedures that improve the characteristics of signals. It is worth noting that the methods have disadvantages associated with high requirements for computing resources, especially when processing large data. This can be minimized using combined optimization methods that take into account the interaction of signal parameters. Another important direction of improvement is the optimization of methods for adaptation to dynamic changes in the characteristics of complex signals, which allows to achieve high adaptability and reliability of real-time systems. Results. As a result of the experiment using the Nelder-Mead method, an increase in the similarity of spectral densities was achieved from 0.52 in the first iteration to 0.90 in the fourth, with a significant decrease in the distance between the peaks of the spectrum from 1.2 to 0.4, which indicates high adaptability and the accuracy of the method in adjusting the parameters of the synthesizedsignals. Conclusions. The effectiveness of the Nelder-Mead method for adjusting the specified parameters of the synthesized signals was experimentally proven, which is confirmed by a significant improvement in the similarity of the spectra with each iteration. This opens the way for additional optimizations and application of the method in various technological areas.

Single-molecule imaging and molecular dynamics simulations reveal early activation of the MET receptor in cells

Embedding of cell-surface receptors into a membrane defines their dynamics but also complicates experimental characterization of their signaling complexes. The hepatocyte growth factor receptor MET is a receptor tyrosine kinase involved in cellular processes such as proliferation, migration, and survival. It is also targeted by the pathogen Listeria monocytogenes, whose invasion protein, internalin B (InlB), binds to MET, forming a signaling dimer that triggers pathogen internalization. Here we use an integrative structural biology approach, combining molecular dynamics simulations and single-molecule Förster resonance energy transfer (smFRET) in cells, to investigate the early stages of MET activation. Our simulations show that InlB binding stabilizes MET in a conformation that promotes dimer formation. smFRET reveals that the in situ dimer structure closely resembles one of two previously published crystal structures, though with key differences. This study refines our understanding of MET activation and provides a methodological framework for studying other plasma membrane receptors.

Symmetry in Signals: A New Insight

Symmetry is a fundamental property of many natural systems, which is observable through signals. In most out-of-equilibrium complex dynamic systems, the observed signals are asymmetric. However, for certain operating modes, some systems have demonstrated a resurgence of symmetry in their signals. Research has naturally focused on examining time invariance to quantify this symmetry. Measures based on the statistical and harmonic properties of signals have been proposed, but most of them focused on harmonic distortion without explicitly measuring symmetry. This paper introduces a new mathematical framework based on group theory for analyzing signal symmetry beyond time invariance. It presents new indicators to evaluate different types of symmetry in non-stochastic symmetric signals. Both periodic and non-periodic symmetric signals are analyzed to formalize the problem. The study raises critical questions about the completeness of symmetry in signals and proposes a new classification for periodic and non-periodic signals that goes beyond the traditional classification based on Fourier coefficients. Furthermore, new measures such as “symmetrometry” and “distorsymmetry” are introduced to quantify symmetry. These measures outperform traditional indicators like Total Harmonic Distortion (THD) and provide a more accurate measurement of symmetry in complex signals from applications where duty cycle plays a major role.

The MET Oncogene: An Update on Targeting Strategies

The MET receptor, commonly known as HGF (hepatocyte growth factor) receptor, is a focus of extensive scientific research. MET has been linked to embryonic development, tissue regeneration following injury, tumorigenesis, and cancer metastasis. These functions underscore its involvement in numerous cellular processes, including stemness, proliferation, motility, cell dissociation, and survival. However, the enigmatic nature of MET becomes apparent in the context of cancer. When MET remains persistently activated, since its gene undergoes genetic alterations, it initiates a complex signaling cascade setting in motion an aggressive and metastatic program that is characteristic of malignant cells and is known as “invasive growth”. The expanding knowledge of MET signaling has opened up numerous opportunities for therapeutic interventions, particularly in the realm of oncology. Targeting MET presents a promising strategy for developing novel anti-cancer treatments. In this review, we provide an updated overview of drugs designed to modulate MET signaling, highlighting MET kinase inhibitors, degraders, anti-MET/HGF monoclonal antibodies, and MET-targeted antibody–drug conjugates. Through this review, we aim to contribute to the ongoing advancement of therapeutic strategies targeting MET signaling.

A hybrid model based on complementary ensemble empirical mode decomposition, sample entropy and long short-term memory neural network for the prediction of time series signals in NPPs

Accurate and reliable predictions are fundamental for the condition monitoring and maintenance of components and systems in nuclear power plants (NPPs). In this work, we propose a hybrid condition prediction approach based on the combination of complementary ensemble empirical mode decomposition (CEEMD), sample entropy (SampEn) and optimized long short-term memory (LSTM) neural network. Firstly, the CEEMD decomposes the time series signals into multiple subsequences called intrinsic mode functions (IMFs), by doing so, the complexity of the time series signals can be reduced, and this facilitates the accurate prediction of the original signals. Then, in order to reduce the calculation cost of prediction models for subsequences, SampEn is used to measure the complexities of the IMFs, and the IMFs whose values of SampEn are lower than the average are aggregated into a new component. Finally, the LSTM with the hyperparameters optimized by the Bayesian optimization algorithm (BOA) is used to perform the prediction of each component. The prediction results of the original signals are reconstructed by synthesizing the predictions of all components. The proposed hybrid prediction model is utilized on the time series signals collected from an NPP. The results obtained show that the proposed approach can capture the characteristics of the signals and has better performance in prediction accuracy than other models.

Structural and functional studies of the EGF20-27 region reveal new features of the human Notch receptor important for optimal activation.

The Notch receptor is activated by the Delta/Serrate/Lag-2 (DSL) family of ligands. The organization of the extracellular signaling complex is unknown, although structures of Notch/ligand complexes comprising the ligand-binding region (LBR), and negative regulatory region (NRR) region, have been solved. Here, we investigate the human Notch-1 epidermal growth factor-like (EGF) 20-27 region, located between the LBR and NRR, and incorporating the Abruptex (Ax) region, associated with distinctive Drosophila phenotypes. Our analyses, using crystallography, NMR and small angle X-ray scattering (SAXS), support a rigid, elongated organization for EGF20-27 with the EGF20-21 linkage showing Ca2+-dependent flexibility. In functional assays, Notch-1 variants containing Ax substitutions result in reduced ligand-dependent trans-activation. When cis-JAG1 was expressed, Notch activity differences between WT and Ca2+-binding Ax variants were less marked than seen in the trans-activation assays alone, consistent with disruption of cis-inhibition. These data indicate the importance of Ca2+-stabilized structure and suggest the balance of cis- and trans-interactions explains the effects of Drosophila Ax mutations.

Moving Target Detection for Array Antennas in Varying Multipath Environments

Detecting moving targets remains a significant challenge in radar applications, particularly in dense multipath environments where signal complexities present formidable obstacles. However, the application of time reversal (TR) technology offers promising prospects for enhancing target detection capabilities. Utilizing this technology, we propose a detection algorithm tailored specifically for a moving target, designed exclusively for array antennas (AA) operating in dense multipath environments with dynamic channel variations. We establish an AA-TR signal model within this framework and derive the AA-TR likelihood ratio test (AA-TR-LRT) detector. To assess the effectiveness of our proposed approach, we also develop the AA conventional LRT (AA-C-LRT) detector as a comparative benchmark. Comprehensive numerical tests consistently verify the outstanding effectiveness of our detection algorithm, underscoring its precision in detecting moving targets, particularly in highly complex multipath scenarios with varying channels.

Immunometabolism: signaling pathways, homeostasis, and therapeutic targets.

Immunometabolism plays a central role in sustaining immune system functionality and preserving physiological homeostasis within the organism. During the differentiation and activation, immune cells undergo metabolic reprogramming mediated by complex signaling pathways. Immune cells maintain homeostasis and are influenced by metabolic microenvironmental cues. A series of immunometabolic enzymes modulate immune cell function by metabolizing nutrients and accumulating metabolic products. These enzymes reverse immune cells' differentiation, disrupt intracellular signaling pathways, and regulate immune responses, thereby influencing disease progression. The huge population of immune metabolic enzymes, the ubiquity, and the complexity of metabolic regulation have kept the immune metabolic mechanisms related to many diseases from being discovered, and what has been revealed so far is only the tip of the iceberg. This review comprehensively summarized the immune metabolic enzymes' role in multiple immune cells such as T cells, macrophages, natural killer cells, and dendritic cells. By classifying and dissecting the immunometabolism mechanisms and the implications in diseases, summarizing and analyzing advancements in research and clinical applications of the inhibitors targeting these enzymes, this review is intended to provide a new perspective concerning immune metabolic enzymes for understanding the immune system, and offer novel insight into future therapeutic interventions.

The role of STK11/LKB1 in cancer biology: implications for ovarian tumorigenesis and progression

STK11 (serine-threonine kinase 11), also known as LKB1 (liver kinase B1) is a highly conserved master kinase that regulates cellular metabolism and polarity through a complex signaling network involving AMPK and 12 other AMPK-related kinases. Germline mutations in LKB1 have been causatively linked to Peutz-Jeghers Syndrome (PJS), an autosomal dominant hereditary disease with high cancer susceptibility. The identification of inactivating somatic mutations in LKB1 in different types of cancer further supports its tumor suppressive role. Deleterious mutations in LKB1 are frequently observed in patients with epithelial ovarian cancer. However, its inconsistent effects on tumorigenesis and cancer progression suggest that its functional impact is genetic context-dependent, requiring cooperation with other oncogenic lesions. In this review, we summarize the pleiotropic functions of LKB1 and how its altered activity in cancer cells is linked to oncogenic proliferation and growth, metastasis, metabolic reprogramming, genomic instability, and immune modulation. We also review the current mechanistic understandings of this master kinase as well as therapeutic implications with particular focus on the effects of LKB1 deficiency in ovarian cancer pathogenesis. Lastly, we discuss whether LKB1 deficiency can be exploited as an Achilles heel in ovarian cancer.

Differential Localization and Functional Roles of mGluR6 Paralogs in Zebrafish Retina.

To define the location of mglur6 paralogs in the outer zebrafish retina and delineate their contribution to retina light responses across the visual spectrum. In situ hybridization and immunolocalization with custom-made antibodies were used to localize mglur6 transcripts, proteins, and additional components of the mGluR6 signaling complex. Gene editing was used to generate knockout mutants that were analyzed with white light and spectral electroretinography. Both mglur6 paralogs colocalized with known downstream pathway genes, such as trpm1a, nyctalopin, and gnaoβ. All rod photoreceptors contacted mGluR6-positive cells, while cone connectivity presented a more complex situation with no red cones and only a few UV and blue-sensitive cones connecting to mGluR6a-positive bipolar cells. All cone subtypes contacted mGluR6b-positive cells with markedly fewer red-sensitive cones. Retinas of knockout animals displayed no morphologic alterations. While ERG responses were unaffected in mglur6a knockout animals, mglur6b mutants displayed decreased responses over all spectral wavelengths. We demonstrated that mGlurR6 signalplex components are similar in the zebrafish and the mammalian retina. Despite mglur6b knockout animals having significantly impaired ERG b-wave responses, a residual b-wave persists, even in double knockouts, suggesting additional pathway components yet to be identified.

The Influence of Dopaminergic Medication on Regularity and Determinism of Gait and Balance in Parkinson’s Disease: A Pilot Analysis

Background/Objectives: Understanding how dual-tasking and Parkinson’s disease medication affect gait and balance regularity can provide valuable insights to patients, caregivers, and clinicians regarding frailty and fall risk. However, dual-task gait and balance studies in PD most often only employ linear measures to describe movement regularity. Some have used nonlinear techniques to analyze PD performances, but only in the on-medication state. Thus, it is unclear how the nonlinear aspects of gait or standing balance are affected by PD medication. This study aimed to assess how dopaminergic medication influenced the regularity and determinism of joint angle and anterior–posterior (AP) and medial–lateral (ML) center of pressure (COP) path time-series data while single- and dual-tasking in PD. Methods: Sixteen subjects with PD completed single- and dual-task gait and standing balance trials for 3 min off and on dopaminergic medication. Sample entropy and percent determinism were calculated for bilateral hip, knee, and shoulder joints, and the AP and ML COP path. Results: There were no relevant medication X task interactions for either the joint angles series or the balance series. Instead, the results supported independent effects of medication, dual-tasking, or standing with eyes closed. Balance task difficulty (i.e., eyes open vs. eyes closed) was detected by the nonlinear analyses, but the nonlinear measures yielded opposing results such that standing with eyes closed simultaneously yielded less regular and more deterministic signals. Conclusions: When juxtaposed with previous findings, these results suggest that medication-induced functional improvements in people with PD might be accompanied by a shift from lesser to greater signal consistency, and the effects of dual-tasking and standing with eyes closed were mixed. Future studies would benefit from including both linear and nonlinear measures to better describe gait and balance performance and signal complexity in people with PD.

The uremic toxin indoxyl sulfate decreases osteocyte RANKL/OPG and increases wnt inhibitor RNA expression that is reversed by PTH

Abstract Renal osteodystrophy (ROD) leads to increased fractures, potentially due to underlying low bone turnover in chronic kidney disease (CKD). We hypothesized that indoxyl sulfate (IS), a circulating toxin elevated in CKD and ligand for the aryl hydrocarbon receptor (AhR), may target the osteocytes leading to bone cell uncoupling in ROD. The IDG-SW3 osteocytes were cultured for 14 days (early) and 35 days (mature osteocytes) and incubated with 500 μM of indoxyl sulfate after dose finding studies to confirm AhR activation. Long-term incubation of IS for 14 days led to decreased expression of Tnfsf11/Tnfrsf11b ratio (RANKL/OPG), which would increase osteoclast activity, and increased expression of Wnt inhibitors Sost and Dkk1, which would decrease bone formation in addition to decreased mineralization and alkaline phosphatase (ALP) activity. When osteocytes were incubated with IS and the AhR translocation inhibitor CH223191, mineralization and ALP activity were restored. However, the Tnfsf11/Tnfrsf11b ratio and Sost, Dkk1 expression were not altered compared to IS alone, suggesting more complex signaling. In both early and mature osteocytes, co-culture with PTH and IS reversed the IS-induced upregulation of Sost and Dkk1, and IS enhanced the PTH-induced increase of the Tnfsf11/Tnfrsf11b ratio. Co-culture of IS with PTH additively enhanced the AhR activity assessed by Cyp1a1 and Cyp1b1 expression. In summary, IS in the absence of PTH, increased osteocyte mRNA Wnt inhibitor expression in both early and mature osteocytes and decreased mRNA expression ofTnfsf11/Tnfrsf11b ratio and mineralization in early osteocytes. These changes would lead to decreased resorption and formation resulting in low bone remodeling. These data suggest IS may be important in the underlying low turnover bone disease observed in CKD when PTH is not elevated. In addition, when elevated PTH, IS interacts to further increase Tnfsf11/Tnfrsf11b ratio for osteoclast activity in both early and mature osteocytes which would worsen bone resorption.