Meta-analysis of preclinical studies of mesenchymal stromal cells to treat rheumatoid arthritis.

BackgroundThis study aims to evaluate the quality of preclinical data, determine the effect sizes, and identify experimental measures that inform efficacy using mesenchymal stromal (or stem) cells (MSC) therapy in animal models of rheumatoid arthritis (RA).MethodsLiterature searches were performed on MSC preclinical studies to treat RA. MSC treatment effect sizes were determined by the most commonly used outcome measures, including paw thickness, clinical score, and histological score.FindingsA total of 48 studies and 94 treatment arms were included, among which 42 studies and 79 treatment arms reported that MSC improved outcomes. The effect sizes of RA treatments using MSC, when compared to the controls, were: paw thickness was ameliorated by 53.6% (95% confidence interval (CI): 26.7% -80.4%), histological score was decreased by 44.9% (95% CI: 33.3% -56.6%), and clinical score was decreased by 29.9% (95% CI: 16.7% -43.0%). Specifically, our results indicated that human umbilical cord derived MSC led to large improvements of the clinical score (-42.1%) and histological score (-51.4%).InterpretationTo the best of our knowledge, this meta-analysis is to quantitatively answer whether MSC represent a robust RA treatment in animal models. It suggests that in preclinical studies, MSC have consistently exhibited therapeutic benefits. The findings demonstrate a need for considering variations in different animal models and treatment protocols in future studies using MSC to treat RA in humans to maximise the therapeutic gains in the era of precision medicine.FundsNIH [1DP2CA195763], Baylx Inc.: BI-206512, NINDS/NIH Training Grant [Award# NS082174]

Mechano-Responsive Immune Cell System for Cancer Metastasis

Cancer metastasis is the major cause of cancer death and remains mostly incurable. Recently, immunotherapy using chimeric antigen receptor-modified patients’ T cells (CAR-T cells) has shown tremendous promise in cancer treatment. Unfortunately, major toxic effects, such as cytokine release syndrome (CRS) and “on-target off-tumor” (OTOT) attack on normal tissue are frequently associated with CAR-T cell treatments. To overcome these severe side effects, we present a mechano-responsive immune cell system that can improve the targeting specificity and control the activation level of cell therapy. Our novel system utilizes both mechanical properties and tumor antigens that are specific to the metastatic tumor niche to trigger a two-keyed lock switch for CAR expression. Multiple mechanosensitive promoters were synthesized and characterized to induce CAR expression in response to specific mechanical cues in vitro. Our study demonstrates that our mechano-responsive immune cell system is specific and cytotoxic to antigen-associated cancer cells present within the stiffness range of the tumor microenvironment in Jurkat T cells and THP-1 derived macrophages models in vitro. This inducible immune cell system could reduce non-specific activation of immune cells, which lowers the OTOT side effects of current immune cell-based therapeutics. Our mechano-responsive immune cell system serves as a novel approach for immunotherapy to target aberrant tissue stiffness in the treatment of cancer metastases or even other fibrotic diseases

Mechano-Responsive Immune Cell System for Cancer Metastasis

Cancer metastasis is the major cause of cancer death and remains mostly incurable. Recently, immunotherapy using chimeric antigen receptor-modified patients’ T cells (CAR-T cells) has shown tremendous promise in cancer treatment. Unfortunately, major toxic effects, such as cytokine release syndrome (CRS) and “on-target off-tumor” (OTOT) attack on normal tissue are frequently associated with CAR-T cell treatments. To overcome these severe side effects, we present a mechano-responsive immune cell system that can improve the targeting specificity and control the activation level of cell therapy. Our novel system utilizes both mechanical properties and tumor antigens that are specific to the metastatic tumor niche to trigger a two-keyed lock switch for CAR expression. Multiple mechanosensitive promoters were synthesized and characterized to induce CAR expression in response to specific mechanical cues in vitro. Our study demonstrates that our mechano-responsive immune cell system is specific and cytotoxic to antigen-associated cancer cells present within the stiffness range of the tumor microenvironment in Jurkat T cells and THP-1 derived macrophages models in vitro. This inducible immune cell system could reduce non-specific activation of immune cells, which lowers the OTOT side effects of current immune cell-based therapeutics. Our mechano-responsive immune cell system serves as a novel approach for immunotherapy to target aberrant tissue stiffness in the treatment of cancer metastases or even other fibrotic diseases

Empirical and conditional likelihoods for two‐phase studies

Two‐phase, response‐dependent sampling is often used in regression settings that involve expensive covariate measurements. Conditional maximum likelihood (CML) is an attractive approach in many cases as it avoids modelling of the covariate distribution, unlike full maximum likelihood. Scott & Wild (2011) introduced an augmented CML approach which is semi‐parametric efficient in certain settings with a discrete response variable. We consider general regression models and show the Scott–Wild estimator of covariate effects has the same asymptotic efficiency as two empirical likelihood estimators, and that these estimators dominate the CML estimator. We compare the efficiencies of various estimators in simulation studies and illustrate the methodology in a two‐phase genetics study.RésuméUn échantillonnage en deux phases dépendant de la réponse est couramment utilisé dans les contextes de régression dont les covariables nécessitent des mesures coûteuses. Le maximum de vraisemblance conditionnelle (MVC) constitue une approche intéressante pour de nombreux cas puisqu’il évite de modéliser la distribution des covariables, contrairement au maximum de vraisemblance complète. Scott et Wild (2011) ont proposé une approche de MVC augmentée qui est semi‐paramétriquement efficace dans certains contextes avec une variable réponse discrète. Les auteurs considèrent les modèles de régression en général et montrent que l’estimateur de Scott‐Wild (SW) pour l’effet des covariables offre la même efficacité asymptotique que deux estimateurs issus de la vraisemblance empirique, et que ces estimateurs dominent celui du MVC. Les auteurs comparent l’efficacité de différents estimateurs dans des études de simulation et illustrent la méthodologie dans le cadre d’une étude génétique à deux phases.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/167757/1/cjs11566.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/167757/2/cjs11566_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/167757/3/cjs11566-sup-0001-Supinfo.pd

Empirical and conditional likelihoods for two‐phase studies

Two‐phase, response‐dependent sampling is often used in regression settings that involve expensive covariate measurements. Conditional maximum likelihood (CML) is an attractive approach in many cases as it avoids modelling of the covariate distribution, unlike full maximum likelihood. Scott & Wild (2011) introduced an augmented CML approach which is semi‐parametric efficient in certain settings with a discrete response variable. We consider general regression models and show the Scott–Wild estimator of covariate effects has the same asymptotic efficiency as two empirical likelihood estimators, and that these estimators dominate the CML estimator. We compare the efficiencies of various estimators in simulation studies and illustrate the methodology in a two‐phase genetics study.RésuméUn échantillonnage en deux phases dépendant de la réponse est couramment utilisé dans les contextes de régression dont les covariables nécessitent des mesures coûteuses. Le maximum de vraisemblance conditionnelle (MVC) constitue une approche intéressante pour de nombreux cas puisqu’il évite de modéliser la distribution des covariables, contrairement au maximum de vraisemblance complète. Scott et Wild (2011) ont proposé une approche de MVC augmentée qui est semi‐paramétriquement efficace dans certains contextes avec une variable réponse discrète. Les auteurs considèrent les modèles de régression en général et montrent que l’estimateur de Scott‐Wild (SW) pour l’effet des covariables offre la même efficacité asymptotique que deux estimateurs issus de la vraisemblance empirique, et que ces estimateurs dominent celui du MVC. Les auteurs comparent l’efficacité de différents estimateurs dans des études de simulation et illustrent la méthodologie dans le cadre d’une étude génétique à deux phases.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/167757/1/cjs11566.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/167757/2/cjs11566_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/167757/3/cjs11566-sup-0001-Supinfo.pd

Spatial Contamination and Potential Ecological Risk Assessment of Heavy Metals in Farmland Soil around Nonferrous Metal Smeltery in North China

Nonferrous metallurgy is an important source of heavy metal in the environment and consequently poses potential risks to ecosystems. The impact of smelting on the surrounding envi-ronment is a concern. In this work, the content levels of selected heavy metals—chromium (Cr), nickel (Ni), copper (Cu), zinc (Zn), lead (Pb), cadmium (Cd), and arsenic (As)—were investigated separately in soil samples collected around two nonferrous metal smelteries using inductively coupled plasma mass spectrometry (ICP-MS). The spatial distribution characteristics of soil metal pollutants was studied by ArcGIS methods and the potential ecological risks were assessed by the Hakanson potential eco-logical hazard index. The results show that soils were heavily polluted by Cr, Ni, Cu, Zn, Cd, Pb, and As. Their mean contents in soil around Smeltery A were 88, 62, 103, 1200, 1.4, 146, and 69 mg/kg, respectively, and those around Smeltery B were 86, 59, 83, 117, 0.53, 57, and 65 mg/kg, respectively. Their contents were obviously higher than the background values of soil Cr (68 mg/kg), Ni (31 mg/kg), Cu (22 mg/kg), Zn (78 mg/kg), Cd (0.09 mg/kg), Pb (22 mg/kg), and As (14 mg/kg). The distribution pattern in soil and risk assessment results show that the pollution surrounding the two smelteries reached intense and moderate ecological hazard and that the contribution of Cd and As was up to 87.05% and 82.59%, respectively. These results suggest that metal smelting makes a considerable contribution to soil pollution

Spatial Contamination and Potential Ecological Risk Assessment of Heavy Metals in Farmland Soil around Nonferrous Metal Smeltery in North China

Nonferrous metallurgy is an important source of heavy metal in the environment and consequently poses potential risks to ecosystems. The impact of smelting on the surrounding envi-ronment is a concern. In this work, the content levels of selected heavy metals—chromium (Cr), nickel (Ni), copper (Cu), zinc (Zn), lead (Pb), cadmium (Cd), and arsenic (As)—were investigated separately in soil samples collected around two nonferrous metal smelteries using inductively coupled plasma mass spectrometry (ICP-MS). The spatial distribution characteristics of soil metal pollutants was studied by ArcGIS methods and the potential ecological risks were assessed by the Hakanson potential eco-logical hazard index. The results show that soils were heavily polluted by Cr, Ni, Cu, Zn, Cd, Pb, and As. Their mean contents in soil around Smeltery A were 88, 62, 103, 1200, 1.4, 146, and 69 mg/kg, respectively, and those around Smeltery B were 86, 59, 83, 117, 0.53, 57, and 65 mg/kg, respectively. Their contents were obviously higher than the background values of soil Cr (68 mg/kg), Ni (31 mg/kg), Cu (22 mg/kg), Zn (78 mg/kg), Cd (0.09 mg/kg), Pb (22 mg/kg), and As (14 mg/kg). The distribution pattern in soil and risk assessment results show that the pollution surrounding the two smelteries reached intense and moderate ecological hazard and that the contribution of Cd and As was up to 87.05% and 82.59%, respectively. These results suggest that metal smelting makes a considerable contribution to soil pollution

Meta-analysis of preclinical studies of mesenchymal stromal cells to treat rheumatoid arthritis.

BACKGROUND: This study aims to evaluate the quality of preclinical data, determine the effect sizes, and identify experimental measures that inform efficacy using mesenchymal stromal (or stem) cells (MSC) therapy in animal models of rheumatoid arthritis (RA). METHODS: Literature searches were performed on MSC preclinical studies to treat RA. MSC treatment effect sizes were determined by the most commonly used outcome measures, including paw thickness, clinical score, and histological score. FINDINGS: A total of 48 studies and 94 treatment arms were included, among which 42 studies and 79 treatment arms reported that MSC improved outcomes. The effect sizes of RA treatments using MSC, when compared to the controls, were: paw thickness was ameliorated by 53.6% (95% confidence interval (CI): 26.7% -80.4%), histological score was decreased by 44.9% (95% CI: 33.3% -56.6%), and clinical score was decreased by 29.9% (95% CI: 16.7% -43.0%). Specifically, our results indicated that human umbilical cord derived MSC led to large improvements of the clinical score (-42.1%) and histological score (-51.4%). INTERPRETATION: To the best of our knowledge, this meta-analysis is to quantitatively answer whether MSC represent a robust RA treatment in animal models. It suggests that in preclinical studies, MSC have consistently exhibited therapeutic benefits. The findings demonstrate a need for considering variations in different animal models and treatment protocols in future studies using MSC to treat RA in humans to maximise the therapeutic gains in the era of precision medicine. FUNDS: NIH [1DP2CA195763], Baylx Inc.: BI-206512, NINDS/NIH Training Grant [Award# NS082174]

Meta-analysis of preclinical studies of mesenchymal stromal cells to treat rheumatoid arthritis.

BackgroundThis study aims to evaluate the quality of preclinical data, determine the effect sizes, and identify experimental measures that inform efficacy using mesenchymal stromal (or stem) cells (MSC) therapy in animal models of rheumatoid arthritis (RA).MethodsLiterature searches were performed on MSC preclinical studies to treat RA. MSC treatment effect sizes were determined by the most commonly used outcome measures, including paw thickness, clinical score, and histological score.FindingsA total of 48 studies and 94 treatment arms were included, among which 42 studies and 79 treatment arms reported that MSC improved outcomes. The effect sizes of RA treatments using MSC, when compared to the controls, were: paw thickness was ameliorated by 53.6% (95% confidence interval (CI): 26.7% -80.4%), histological score was decreased by 44.9% (95% CI: 33.3% -56.6%), and clinical score was decreased by 29.9% (95% CI: 16.7% -43.0%). Specifically, our results indicated that human umbilical cord derived MSC led to large improvements of the clinical score (-42.1%) and histological score (-51.4%).InterpretationTo the best of our knowledge, this meta-analysis is to quantitatively answer whether MSC represent a robust RA treatment in animal models. It suggests that in preclinical studies, MSC have consistently exhibited therapeutic benefits. The findings demonstrate a need for considering variations in different animal models and treatment protocols in future studies using MSC to treat RA in humans to maximise the therapeutic gains in the era of precision medicine.FundsNIH [1DP2CA195763], Baylx Inc.: BI-206512, NINDS/NIH Training Grant [Award# NS082174]

Preclinical Evaluation of a Single Intravenous Infusion of hUC-MSC (BX-U001) in Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is an inflammatory disease of the joints, which causes severe pain and excessive systemic circulation of harmful inflammatory cytokines. Current treatments are limited, with some patients not responding well, and some experiencing severe and detrimental side effects. Mesenchymal stem cells (MSC) are cell-based therapeutics being evaluated as potent immunomodulators in RA and may provide relief to patients not responding well to drug-based treatments. We evaluated the safety and efficacy of BX-U001 human umbilical cord tissue-derived mesenchymal stem cells (hUC-MSC) to treat RA, in support of a successful investigational new drug application. A collagen-induced arthritis (CIA) mouse model of RA was established in DBA/1 J mice. Mice from the treatment assessment group were given a tail vein infusion of hUC-MSC 24 days after primary RA induction, while control assessment (CA) group mice were given cell-free carrier solution. All animals were evaluated daily for RA symptoms via clinical scoring, blood was taken periodically for cytokine analysis, and mice were dissected at end point for histological analysis. A linear mixed model was used to compare the rate of change among groups. The clinical scores of TA group were significantly reduced compared with CA group (P < 0.01), indicating therapeutic effects. The histological scores of the joints in TA group were significantly lower than those in the CA group (P < 0.05), but had no significant difference compared with Healthy groups (P > 0.05). The concentration of (interleukin) IL-6 in TA group was significantly reduced by 80.0% (P < 0.0001) 2 days after treatment and by 93.4% at the experimental endpoint compared with levels prior to hUC-MSC injection. A single intravenous infusion of hUC-MSC (2 × 106 cells/mouse), to CIA-induced DBA/1 J mice, resulted in significant alleviation of RA symptoms and may provide significant therapeutic benefits in humans