No abstract

Location fingerprinting in wireless LAN (WLAN) positioning has received much attention recently. One of the key issues of this technique is generating the database of 'fingerprints'. The conventional method does not utilise the spatial correlation of measurements sampled at adjacent reference points (RPs), and the 'training' process is not an easy task. A new method based on kriging is presented in this paper. An experiment shows that the new method can not only achieve more accurate estimation, but can also greatly reduce the workload and save training time. This can make the fingerprinting technique more flexible and easier to implement.

Blockade of immune‐checkpoint programmed cell death protein 1 (PD‐1) or programmed cell death ligand 1 can enhance effector T‐cell responses. However, the lack of response in many patients to checkpoint‐inhibitor therapies emphasizes the need for combination immunotherapies to pursue maximal antitumor efficacy. We have previously demonstrated that antagonism of C‐X‐C chemokine receptor type 4 (CXCR4) by plerixafor (AMD3100) can decrease regulatory T (Treg)‐cell intratumoral infiltration. Therefore, a combination of these 2 therapies might increase antitumor effects. Here, we evaluated the antitumor efficacy of AMD3100 and anti‐PD‐1 (αPD‐1) antibody alone or in combination in an immunocompetent syngeneic mouse model of ovarian cancer. We found that AMD3100, a highly specific CXCR4 antagonist, directly down‐regulated the expression of both C‐X‐C motif chemokine 12 (CXCL12) and CXCR4 in vitro and in vivo in tumor cells. AMD3100 and αPD‐1 significantly inhibited tumor growth and prolonged the survival of tumor‐bearing mice when given as monotherapy. Combination of these 2 agents significantly enhanced antitumor effects compared with single‐agent administration. Benefits of tumor control and animal survival were associated with immunomodulation mediated by these 2 agents, which were characterized by increased effector T‐cell infiltration, increased effector T‐cell function, and increased memory T cells in tumor microenvironment. Intratumoral Treg cells were decreased, and conversion of Treg cells into T helper cells was increased by AMD3100 treatment. Intratumoral myeloid‐derived suppressor cells were decreased by the combined treatment, which was associated with decreased IL‐10 and IL‐6 in the ascites. Also, the combination therapy decreased suppressive leukocytes and facilitated M2‐to‐M1 macrophage polarization in the tumor. These results suggest that AMD3100 could be used to target the CXCR4‐CXCL12 axis to inhibit tumor growth and prevent multifaceted immunosuppression alone or in combination with αPD‐1 in ovarian cancer, which could be clinically relevant to patients with this disease.—Zeng, Y., Li, B., Liang, Y., Reeves, P. M., Qu, X., Ran, C., Liu, Q., Callahan, M. V., Sluder, A. E., Gelfand, J. A., Chen, H., Poznansky, M. C. Dual blockade of CXCL12‐CXCR4 and PD‐1‐PD‐L1 pathways prolongs survival of ovarian tumor‐bearing mice by prevention of immunosuppression in the tumor microenvironment. FASEB J. 33, 6596–6608 (2019). http://www.fasebj.org

Brief exposure of skin to near-infrared (NIR) laser light has been shown to augment the immune response to intradermal vaccination and thus act as an immunologic adjuvant. Although evidence indicates that the NIR laser adjuvant has capacity to activate innate subsets including dendritic cells (DCs) in skin as conventional adjuvants do, the precise immunological mechanism by which the NIR laser adjuvant acts is largely unknown. Here we sought to identify the cellular target of the NIR laser adjuvant by using an established mouse model of intradermal influenza vaccination and examining the alteration of responses resulting from genetic ablation of specific DC populations. We found that a continuous wave (CW) NIR laser adjuvant broadly modulates migratory DC populations, specifically increasing and activating the Lang+ and CD11b−Lang− subsets in skin, and that the antibody responses augmented by the CW NIR laser are dependent on DC subsets expressing CCR2 and Langerin. In comparison, a pulsed wave (PW) NIR laser adjuvant showed limited effects on the migratory DC subsets. Our vaccination study demonstrated that the efficacy of CW NIR laser is significantly better than that of PW laser, indicating that the CW NIR laser offers a desirable immunostimulatory microenvironment for migratory DCs. These results demonstrate the unique ability of the NIR laser adjuvant to selectively target specific migratory DC populations in skin depending on its parameters, and highlight the importance of optimization of laser parameters for desirable immune protection induced by a NIR laser-adjuvanted vaccine.

No abstract

The poor 5-year survival rate in high-grade osteosarcoma (HOS) has not been increased significantly over the past 30 years. This work aimed to develop a radiomics nomogram for survival prediction at the time of diagnosis in HOS.In this retrospective study, an initial cohort of 102 HOS patients, diagnosed from January 2008 to March 2011, was used as the training cohort. Radiomics features were extracted from the pretreatment diagnostic computed tomography images. A radiomics signature was constructed with the lasso algorithm; then, a radiomics score was calculated to reflect survival probability by using the radiomics signature for each patient. A radiomics nomogram was developed by incorporating the radiomics score and clinical factors. A clinical model was constructed by using clinical factors only. The models were validated in an independent cohort comprising 48 patients diagnosed from April 2011 to April 2012. The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. Kaplan–Meier survival analysis was performed.The radiomics nomogram showed better calibration and classification capacity than the clinical model with AUC 0.86 vs. 0.79 for the training cohort, and 0.84 vs. 0.73 for the validation cohort. Decision curve analysis demonstrated the clinical usefulness of the radiomics nomogram. A significant difference (p-value <.05; log-rank test) was observed between the survival curves of the nomogram-predicted survival and non-survival groups. The radiomics nomogram may assist clinicians in tailoring appropriate therapy.

Even though combining surgery with chemotherapy has significantly improved the prognosis of osteosarcoma patients, advanced, metastatic, or recurrent osteosarcomas are often non-responsive to chemotherapy, making development of novel efficient therapeutic methods an urgent need. Adoptive immunotherapy has the potential to be a useful non-surgical modality for treatment of osteosarcoma. Recently, alternative strategies, including immunotherapies using naturally occurring or genetically modified T cells, have been found to hold promise in the treatment of hematologic malignancies and solid tumors. In this review, we will discuss possible T-cell-based therapies against osteosarcoma with a special emphasis on combination strategies to improve the effectiveness of adoptive T cell transfer and, thus, to provide a rationale for the clinical development of immunotherapies.

Background: The difficulty of assessment of neoadjuvant chemotherapeutic response preoperatively may hinder personalized-medicine strategies that depend on the results from pathological examination. Methods: A total of 191 patients with high-grade osteosarcoma (HOS) were enrolled retrospectively from November 2013 to November 2017 and received neoadjuvant chemotherapy (NCT). A cutoff time of November 2016 was used to divide the training set and validation set. All patients underwent diagnostic CTs before and after chemotherapy. By quantifying the tumor regions on the CT images before and after NCT, 540 delta-radiomic features were calculated. The interclass correlation coefficients for segmentations of inter/intra-observers and feature pair-wise correlation coefficients (Pearson) were used for robust feature selection. A delta-radiomics signature was constructed using the lasso algorithm based on the training set. Radiomics signatures built from single-phase CT were constructed for comparison purpose. A radiomics nomogram was then developed from the multivariate logistic regression model by combining independent clinical factors and the delta-radiomics signature. The prediction performance was assessed using area under the ROC curve (AUC), calibration curves and decision curve analysis (DCA). Results:The delta-radiomics signature showed higher AUC than single-CT based radiomics signatures in both training and validation cohorts. The delta-radiomics signature, consisting of 8 selected features, showed significant differences between the pathologic good response (pGR) (necrosis fraction ≥90%) group and the non-pGR (necrosis fraction < 90%) group (P < 0.0001, in both training and validation sets). The delta-radiomics nomogram, which consisted of the delta-radiomics signature and new pulmonary metastasis during chemotherapy showed good calibration and great discrimination capacity with AUC 0.871 (95% CI, 0.804 to 0.923) in the training cohort, and 0.843 (95% CI, 0.718 to 0.927) in the validation cohort. The DCA confirmed the clinical utility of the radiomics model. Conclusion:The delta-radiomics nomogram incorporating the radiomics signature and clinical factors in this study could be used for individualized pathologic response evaluation after chemotherapy preoperatively and help tailor appropriate chemotherapy and further treatment plans.