Bin Shi

Osteosarcoma is an aggressive malignancy characterized by inherent chemoresistance, a high propensity for pulmonary metastasis, and dismal survival rates in patients with advanced or refractory disease. While immunotherapy has revolutionized cancer treatment, its efficacy in osteosarcoma remains severely limited by an immunologically “cold” and profoundly immunosuppressive tumor microenvironment (TME). This TME is defined by pervasive infiltrates of tumor-associated macrophages (TAMs) and myeloid-derived suppressor cells (MDSCs), cancer-associated fibroblasts (CAFs), and a dense mineralized extracellular matrix (ECM) barrier that collectively exclude or exhaust cytotoxic T cells. We examine the intricate mechanisms driving this immunotherapy resistance at the cellular and molecular levels. We then explore how rationally designed nanotechnology platforms can overcome these barriers. Specifically, we review targeted nanomedicine delivery systems engineered to home to bone tissue and reshape the TME landscape via strategies including TAM reprogramming, MDSC depletion, ECM clearance to relieve physical resistance, and activation of innate immune pathways. Unlike general immunotherapy reviews, the main contribution of this mini-review is strictly focused on innovative nanomedicine delivery platforms—specifically biomimetic, stimuli-responsive, and bone-targeted systems. We dissect how these rationally engineered platforms overcome the unique physical and cellular barriers of the osteosarcoma TME, with a critical emphasis on the severe translational hurdles, such as protein corona formation and in vivo stability, that limit clinical progression. In conclusion, multi-targeted nanomedicine delivery systems hold strong preclinical potential to provide a novel framework for advancing osteosarcoma treatment by precisely modulating the TME and eliciting durable antitumor immune responses.

Fracture healing is an energetically demanding, highly orchestrated process in which inflammation, angiogenesis, callus formation and remodelling must be t

Objective: To evaluate the predictive value of the systemic immune‐inflammation index (SII) for clinical efficacy of acupuncture combined with exercise rehabilitation in patients with knee osteoarthritis (KOA). Methods: In this retrospective observational study, 151 patients with radiographically confirmed Kellgren–Lawrence Grade II or III KOA who completed an 8‐week standardized protocol of acupuncture and exercise rehabilitation were enrolled. Clinical efficacy was defined as the attainment of minimal clinically important improvement (MCII) in both the 11‐point Numeric Rating Scale (NRS) for pain (≥ 2‐point reduction) and the 68‐point WOMAC function subscale (≥ 6‐point improvement, Likert version 3.1). Baseline demographic, clinical, and hematological data were collected, and SII was subsequently calculated from baseline hematological parameters. Uni‐ and multivariate logistic regression analyses were used to identify independent predictors of treatment response. Receiver operating characteristic (ROC) curves were constructed to assess the discriminative ability of SII, body mass index (BMI), and lymphocyte count, individually and in combination. Results: Of the 151 patients, 73 were classified as responders and 78 as nonresponders. Baseline BMI and SII were significantly lower, while lymphocyte count was higher in the effective group (all p < 0.001). Multivariate logistic regression identified BMI (OR = 0.596, 95% CI: 0.472–0.753), lymphocyte count (OR = 34.597, 95% CI: 3.234–370.131), and SII (OR = 0.912, 95% CI: 0.873–0.953) as independent predictors of treatment response. ROC analysis showed that SII demonstrated only moderate predictive power (AUC = 0.749, 95% CI: 0.670–0.828), with improved but still moderate accuracy when combined with BMI and lymphocyte count (AUC = 0.858, 95% CI: 0.799–0.917). Conclusion: Although SII is an independent and accessible biomarker for predicting clinical efficacy, its discriminative ability is moderate. A combined model incorporating SII, BMI, and lymphocyte count may provide better, though not strong, predictive performance and could support clinical decision‐making and individualized treatment planning. However, the retrospective single‐center design may introduce selection bias and limit generalizability. Residual confounding from unmeasured variables cannot be excluded, and the absence of longitudinal SII measurements limits evaluation of temporal changes. Future multicenter prospective studies are warranted to validate these findings.

Conventional triaxial MEMS gyroscope calibration relies on strict mounting constraints, specialized apparatus, and elaborate laboratory procedures that hinder field deployment; this work presents a field-deployable method enabling efficient and accurate in-field calibration. The core strategy is to utilize the criterion that the dot product of the measured gravity and the rotation speed in a fixed frame remains constant. To eliminate the impact of external acceleration, the calibration process involves separate procedures for measuring local gravity and rotation speed. Moreover, unlike existing approaches for auto calibration of triaxial sensors that often result in nonlinear optimization problems, the proposed method simplifies the estimation of the gyroscope scale factor by employing a linear least squares algorithm. Extensive numerical simulations have been conducted to analyze the proposed method’s performance in calibrating the six-parameter triaxial gyroscope model, taking into consideration measurements corrupted by simulated noise. Experimental validation was also carried out using two commercially available MEMS inertial measurement units (LSM9DS1) and a servo motor. The experimental results effectively demonstrate the efficacy of the proposed calibration approach.

Background: Chronic low back pain (CLBP) is characterized by persistent neuroinflammation and metabolic dysregulation, extending beyond local tissue injury to central neural maladaptation. While manual therapy (MT) is a clinically validated intervention, its capacity to modulate the neuro‐immune‐metabolic axis remains poorly understood. Methods: We established a complete Freund’s adjuvant (CFA)–induced CLBP rat model and used a combination of in vivo behavioral and molecular techniques to study MT intervention mechanisms. The therapeutic effects were evaluated via multidimensional approaches combining behavioral assays, histology, and high‐throughput dual‐tissue (prefrontal cortex and multifidus muscle) proteomics and metabolomics. Results: MT intervention significantly attenuated mechanical hyperalgesia and suppressed pro‐inflammatory cytokines (IL‐6, IL‐1β, and TNF‐α) in muscle tissues. Integrated omics revealed distinct reprogramming of metabolic pathways, including GABAergic synapses and oxidative phosphorylation. Crucially, the CLBP model exhibited aberrant upregulation of autophagy initiation markers (AMPK, ULK1, and LC3B) coupled with substrate accumulation (p62), indicative of pathological autophagic stress. MT partially normalized the altered expression of autophagy‐related proteins. Conclusion: Our findings from a CFA‐induced inflammatory multifidus injury rat model suggest that AMPK/ULK1‐linked autophagy signaling may correlate with the therapeutic effects of MT on inflammatory muscle‐type low back pain; these preclinical observations require further verification in heterogeneous clinical CLBP cohorts and multiple animal models.

Spinal cord injury (SCI), a highly disabling injury to the central nervous system, has a complex and sequential pathogenesis. Traditional multiple‐delivery systems rely on a physical mix of nanoparticles or drugs in hydrogels, which lacks the controllability of the drug. To solve these problems, an integrative hydrogel system cross‐linked with a Per‐g‐PSB nanogel is designed. Dendritic macromolecular nanogels (Per‐g‐PSB) could not only act as cross‐linkers to adjust the hydrogel mechanical properties but also form a dynamic network (Dex/Per‐g‐PSB hydrogel). Most importantly, a large amount of charge could lead to a significant sustained release via electrostatic interactions. The hydrogel platform (Mel/Ibu@D/P‐g‐PSB) realizes the sequential release of melatonin and ibuprofen by different mechanisms. Melatonin is first released by diffusion and exhibits significant neuroprotective effects during the acute phase by downregulating the expression of inflammatory cytokines. Ibuprofen is released in the second stage due to strong electrostatic interactions, and it reduces RhoA signaling activation by blocking the ROCK pathway in the subacute phase, which reduces the deleterious cascade reaction after spinal cord injury. These results show that the ion‐sensitive hydrogel platform with sequentially releasing drug effects, combining anti‐inflammatory effects and blocking the ROCK pathway, shows excellent repair of SCI.

The etiology of rheumatoid arthritis (RA) is still unclear, but it has been shown to be genetically related. While previous studies have shown a causal relationship between immune cells and RA, there has been no systematic evaluation of the causal relationship between immune cell characteristics and RA in terms of genetic variation. For this study, a comprehensive Mendelian randomization analysis was performed to determine the causal relationship between immune cell characteristics and RA. On the basis of publicly available genetic data, we examined the causal relationship between 731 immune cell characteristics and the risk of RA. In addition to 118 absolute cell (AC) counts, 389 median fluorescence intensities reflecting surface antigen levels, and 32 morphologic parameters, 192 relative counts were collected. We validated the robustness, heterogeneity, and horizontal pleiotropy of our results by carrying out comprehensive sensitivity analyses. False discovery rate-corrected, 12 immune cell phenotypes had a causal effect on RA, and the ratio of ratios for risk of RA using the inverse variance weighting method IgD-CD27-B cell % B cell, CD27 on memory B cell, CD27 on IgD-CD38dim, and CD27 on IgD-% of CD27-lymphocyte. In the TBNK group, HLA DR + NK%CD3-lymphocyte. In the Treg panel, CD28 on resting Treg, while in the cDC panel, CD86 + myeloid DC %DC, CD62L-DC %DC, CD62L-CD86 + myeloid DC %DC, CD86 + myeloid DC AC, CD62L-CD86 + myeloid DC AC, and HLA DR on plasmacytoid DC. There was a causal effect of RA on 2 immune characteristics, including CD38 on plasma blast-plasma cell, and HLA DR on CD33-HLA DR+. Our study demonstrates an intrinsic link between immune cells and RA from a genetic perspective, providing guidance for future clinical studies.