Pretreatment of UC-MSCs with IFN-α2 improves treatment of liver fibrosis by recruiting neutrophils.

BACKGROUND: The use of umbilical cord mesenchymal stem cells (UC-MSCs) is a burgeoning method for the treatment of liver cirrhosis. However, the secretory phenotype and regulatory ability of UC-MSCs are easily affected by their microenvironment. Ensuring a specific microenvironment to enhance the UC-MSCs phenotype is a potential strategy for improving their therapeutic efficacy. The aim of this study was to explore therapeutic UC-MSCs phenotypes for improving liver fibrosis. METHODS: RNA-sequencing was used to analyze the response pattern of UC-MSCs after exposure to the serum of cirrhotic patients with HBV. Using immunohistochemistry, quantitative polymerase chain reaction, and immunofluorescence techniques, we evaluated the therapeutic effect of UC-MSCs pretreated with interferon alpha 2 (IFN-α2) (pre-MSCs) in an animal model of cirrhosis. Immunoblotting, ELISA, and other techniques were used to analyze the signaling pathways underlying the IFN-induced changes in UC-MSCs. RESULTS: UC-MSCs exposed to the serum of patients with hepatitis B-induced cirrhosis showed an enhanced response to type I IFN. The activated type I IFN signal induced the highest secretion of colony-stimulating factor 3 (CSF-3), interleukin (IL)-8, and chemokine (C-C motif) ligand 20 (CCL20) by the UC-MSCs. Pre-MSCs showed a higher therapeutic efficacy than untreated UC-MSCs in an animal model of liver fibrosis. Immunohistochemical analysis revealed that pre-MSCs could recruit neutrophils resulting in an increase in the secretion of matrix metalloprotease 8 that alleviated fibrosis. When neutrophils in animals were depleted, the therapeutic effect of pre-MSCs on fibrosis was inhibited. IFN-α2 altered the secretory phenotype of UC-MSCs by activating phosphorylated signal transducer and activator of transcription 1 and 2 (p-STAT1 and p-STAT2). CONCLUSIONS: Pre-MSCs exhibited enhanced secretion of CSF-3, IL-8, and CCL20 and recruited neutrophils to alleviate fibrosis. This new strategy can improve cell therapy for liver cirrhosis.

Federated and distributed learning applications for electronic health records and structured medical data: a scoping review.

OBJECTIVES: Federated learning (FL) has gained popularity in clinical research in recent years to facilitate privacy-preserving collaboration. Structured data, one of the most prevalent forms of clinical data, has experienced significant growth in volume concurrently, notably with the widespread adoption of electronic health records in clinical practice. This review examines FL applications on structured medical data, identifies contemporary limitations, and discusses potential innovations. MATERIALS AND METHODS: We searched 5 databases, SCOPUS, MEDLINE, Web of Science, Embase, and CINAHL, to identify articles that applied FL to structured medical data and reported results following the PRISMA guidelines. Each selected publication was evaluated from 3 primary perspectives, including data quality, modeling strategies, and FL frameworks. RESULTS: Out of the 1193 papers screened, 34 met the inclusion criteria, with each article consisting of one or more studies that used FL to handle structured clinical/medical data. Of these, 24 utilized data acquired from electronic health records, with clinical predictions and association studies being the most common clinical research tasks that FL was applied to. Only one article exclusively explored the vertical FL setting, while the remaining 33 explored the horizontal FL setting, with only 14 discussing comparisons between single-site (local) and FL (global) analysis. CONCLUSIONS: The existing FL applications on structured medical data lack sufficient evaluations of clinically meaningful benefits, particularly when compared to single-site analyses. Therefore, it is crucial for future FL applications to prioritize clinical motivations and develop designs and methodologies that can effectively support and aid clinical practice and research.

A role for fibroblast-derived SASP factors in the activation of pyroptotic cell death in mammary epithelial cells.

In normal tissue homeostasis, bidirectional communication between different cell types can shape numerous biological outcomes. Many studies have documented instances of reciprocal communication between fibroblasts and cancer cells that functionally change cancer cell behavior. However, less is known about how these heterotypic interactions shape epithelial cell function in the absence of oncogenic transformation. Furthermore, fibroblasts are prone to undergo senescence, which is typified by an irreversible cell cycle arrest. Senescent fibroblasts are also known to secrete various cytokines into the extracellular space; a phenomenon that is termed the senescence-associated secretory phenotype (SASP). While the role of fibroblast-derived SASP factors on cancer cells has been well studied, the impact of these factors on normal epithelial cells remains poorly understood. We discovered that treatment of normal mammary epithelial cells with conditioned media from senescent fibroblasts (SASP CM) results in a caspase-dependent cell death. This capacity of SASP CM to cause cell death is maintained across multiple senescence-inducing stimuli. However, the activation of oncogenic signaling in mammary epithelial cells mitigates the ability of SASP CM to induce cell death. Despite the reliance of this cell death on caspase activation, we discovered that SASP CM does not cause cell death by the extrinsic or intrinsic apoptotic pathway. Instead, these cells die by an NLRP3, caspase-1, and gasdermin D-dependent induction of pyroptosis. Taken together, our findings reveal that senescent fibroblasts can cause pyroptosis in neighboring mammary epithelial cells, which has implications for therapeutic strategies that perturb the behavior of senescent cells.

Cell Therapy for Androgenetic Alopecia: Elixir or Trick?

Androgenetic alopecia is the most common cause of hair loss aggravated by increased life pressure, tension, and anxiety. Although androgenetic alopecia (AGA) does not significantly effect physical health, it can have serious negative impact on the mental health and quality of life of the patient. Currently, the effect of medical treatment for AGA is not idealistic, stem cell-based regenerative medicine has shown potential for hair regrowth and follicle repair, but the long-term effect and mechanism of stem cell therapy is not quite explicit. In this review, we summarize the methods, efficacy, mechanism, and clinical progress of stem cell therapies for AGA by now, hope it will present a more comprehensive view in this topic.

A scoping review of the clinical application of machine learning in data-driven population segmentation analysis.

OBJECTIVE: Data-driven population segmentation is commonly used in clinical settings to separate the heterogeneous population into multiple relatively homogenous groups with similar healthcare features. In recent years, machine learning (ML) based segmentation algorithms have garnered interest for their potential to speed up and improve algorithm development across many phenotypes and healthcare situations. This study evaluates ML-based segmentation with respect to (1) the populations applied, (2) the segmentation details, and (3) the outcome evaluations. MATERIALS AND METHODS: MEDLINE, Embase, Web of Science, and Scopus were used following the PRISMA-ScR criteria. Peer-reviewed studies in the English language that used data-driven population segmentation analysis on structured data from January 2000 to October 2022 were included. RESULTS: We identified 6077 articles and included 79 for the final analysis. Data-driven population segmentation analysis was employed in various clinical settings. K-means clustering is the most prevalent unsupervised ML paradigm. The most common settings were healthcare institutions. The most common targeted population was the general population. DISCUSSION: Although all the studies did internal validation, only 11 papers (13.9%) did external validation, and 23 papers (29.1%) conducted methods comparison. The existing papers discussed little validating the robustness of ML modeling. CONCLUSION: Existing ML applications on population segmentation need more evaluations regarding giving tailored, efficient integrated healthcare solutions compared to traditional segmentation analysis. Future ML applications in the field should emphasize methods' comparisons and external validation and investigate approaches to evaluate individual consistency using different methods.

A role for fibroblast-derived SASP factors in the activation of pyroptotic cell death in mammary epithelial cells.

In normal tissue homeostasis, bidirectional communication between different cell types can shape numerous biological outcomes. Many studies have documented instances of reciprocal communication between fibroblasts and cancer cells that functionally change cancer cell behavior. However, less is known about how these heterotypic interactions shape epithelial cell function in the absence of oncogenic transformation. Furthermore, fibroblasts are prone to undergo senescence, which is typified by an irreversible cell cycle arrest. Senescent fibroblasts are also known to secrete various cytokines into the extracellular space; a phenomenon that is termed the senescence-associated secretory phenotype (SASP). While the role of fibroblast derived SASP factors on cancer cells has been well studied, the impact of these factors on normal epithelial cells remains poorly understood. We discovered that treatment of normal mammary epithelial cells with conditioned media (CM) from senescent fibroblasts (SASP CM) results in a caspase-dependent cell death. This capacity of SASP CM to cause cell death is maintained across multiple senescence-inducing stimuli. However, the activation of oncogenic signaling in mammary epithelial cells mitigates the ability of SASP CM to induce cell death. Despite the reliance of this cell death on caspase activation, we discovered that SASP CM does not cause cell death by the extrinsic or intrinsic apoptotic pathway. Instead, these cells die by an NLRP3, caspase-1, and gasdermin D (GSDMD)-dependent induction of pyroptosis. Taken together, our findings reveal that senescent fibroblasts can cause pyroptosis in neighboring mammary epithelial cells, which has implications for therapeutic strategies that perturb the behavior of senescent cells.

Estimating individualized treatment effects using a risk-modeling approach: an application to epidural steroid injections for lumbar spinal stenosis.

ABSTRACT: Conventional "1-variable-at-a-time" analyses to identify treatment effect modifiers are often underpowered and prone to false-positive results. This study used a "risk-modeling" approach guided by the Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement framework: (1) developing and validating a multivariable model to estimate predicted future back-related functional limitations as measured by the Roland-Morris Disability Questionnaire (RMDQ) and (2) stratifying patients from a randomized controlled trial (RCT) of lumbar epidural steroid injections (LESIs) for the treatment of lumbar spinal stenosis into subgroups with different individualized treatment effects on RMDQ scores at the 3-week follow-up. Model development and validation were conducted in a cohort (n = 3259) randomly split into training and testing sets in a 4:1 ratio. The model was developed in the testing set using linear regression with least absolute shrinkage and selection regularization and 5-fold cross-validation. The model was then applied in the testing set and subsequently in patients receiving the control treatment in the RCT of LESI. R2 values in the training set, testing set, and RCT were 0.38, 0.32, and 0.34, respectively. There was statistically significant modification ( P = 0.03) of the LESI treatment effect according to predicted risk quartile, with clinically relevant LESI treatment effect point estimates in the 2 quartiles with greatest predicted risk (-3.7 and -3.3 RMDQ points) and no effect in the lowest 2 quartiles. A multivariable risk-modeling approach identified subgroups of patients with lumbar spinal stenosis with a clinically relevant treatment effect of LESI on back-related functional limitations.

Heterogeneous matrix stiffness regulates the cancer stem-like cell phenotype in hepatocellular carcinoma.

BACKGROUND: Solid tumors are stiffer than their surrounding normal tissues; however, their interior stiffness is not uniform. Under certain conditions, cancer cells can acquire stem-like phenotypes. However, it remains unclear how the heterogeneous physical microenvironment affects stemness expression in cancer cells. Here, we aimed to evaluate matrix stiffness heterogeneity in hepatocellular carcinoma (HCC) tissues and to explore the regulation effect of the tumor microenvironment on stem-like phenotypic changes through mechanical transduction. METHODS: First, we used atomic force microscopy (AFM) to evaluate the elastic modulus of HCC tissues. We then used hydrogel with adjustable stiffness to investigate the effect of matrix stiffness on the stem-like phenotype expression of HCC cells. Moreover, cells cultured on hydrogel with different stiffness were subjected to morphology, real-time PCR, western blotting, and immunofluorescence analyses to explore the mechanotransduction pathway. Finally, animal models were used to validate in vitro results. RESULTS: AFM results confirmed the heterogenous matrix stiffness in HCC tissue. Cancer cells adhered to hydrogel with varying stiffness (1.10 ± 0.34 kPa, 4.47 ± 1.19 kPa, and 10.61 kPa) exhibited different cellular and cytoskeleton morphology. Higher matrix stiffness promoted the stem-like phenotype expression and reduced sorafenib-induced apoptosis. In contrast, lower stiffness induced the expression of proliferation-related protein Ki67. Moreover, mechanical signals were transmitted into cells through the integrin-yes-associated protein (YAP) pathway. Higher matrix stiffness did not affect YAP expression, however, reduced the proportion of phosphorylated YAP, promoted YAP nuclear translocation, and regulated gene transcription. Finally, application of ATN-161 (integrin inhibitor) and verteporfin (YAP inhibitor) effectively blocked the stem-like phenotype expression regulated by matrix stiffness. CONCLUSIONS: Our experiments provide new insights into the interaction between matrix stiffness, cancer cell stemness, and heterogeneity, while also providing a novel HCC therapeutic strategy.

The role of matrix stiffness in cancer stromal cell fate and targeting therapeutic strategies.

The tumor microenvironment (TME) is a complex macromolecular network filled with a series of stromal cells. It plays an important role in tumorigenesis, development, immune escape, drug resistance, and other processes and has received increasing attention in recent years. Currently, tumor cell-centered treatments are insufficient to eradicate malignancies, and researchers are constantly searching for better treatments. Over the past decade, the TME has been recognized as a rich resource for anti-cancer drug development. As a significant mechanical feature in the microenvironment of solid tumors, matrix stiffness is increased owing to stromal deposition and remodeling. The effect of matrix stiffness on cancer cells has been described in many studies, whereas its effect on cancer stromal cell fate has rarely been summarized. Therefore, this review discusses the relevant content and drug treatment studies targeting matrix stiffness. STATEMENT OF SIGNIFICANCE: Biochemical and biophysical interactions between tumor cells, stromal cells, and the extracellular matrix (ECM) co-create a distinct tumor microenvironment (TME), which impacts disease outcome. In recent years, there has been a greater emphasis on the physical properties of the ECM, with matrix stiffness being one of the most thoroughly investigated. The matrix stiffness of solid tumors is now commonly acknowledged to be greater than that of normal tissues. Cancer-associated fibroblasts (CAFs), tumor-associated macrophages (TAMs), and endothelial cells (ECs) can all respond to matrix stiffness. At the same time, our current understanding of the TME is insufficient, and an in-depth examination of interactions between ECM and cells could lead to the development of more efficient and specialized treatments.

Stem cells for treatment of liver fibrosis/cirrhosis: clinical progress and therapeutic potential.

Cost-effective treatment strategies for liver fibrosis or cirrhosis are limited. Many clinical trials of stem cells for liver disease shown that stem cells might be a potential therapeutic approach. This review will summarize the published clinical trials of stem cells for the treatment of liver fibrosis/cirrhosis and provide the latest overview of various cell sources, cell doses, and delivery methods. We also describe the limitations and strengths of various stem cells in clinical applications. Furthermore, to clarify how stem cells play a therapeutic role in liver fibrosis, we discuss the molecular mechanisms of stem cells for treatment of liver fibrosis, including liver regeneration, immunoregulation, resistance to injury, myofibroblast repression, and extracellular matrix degradation. We provide a perspective for the prospects of future clinical implementation of stem cells.

A pancreas tumor derived organoid study: from drug screen to precision medicine.

Pancreatic ductal adenocarcinoma (PDAC) one of the deadliest malignant tumor. Despite considerable progress in pancreatic cancer treatment in the past 10 years, PDAC mortality has shown no appreciable change, and systemic therapies for PDAC generally lack efficacy. Thus, developing biomarkers for treatment guidance is urgently required. This review focuses on pancreatic tumor organoids (PTOs), which can mimic the characteristics of the original tumor in vitro. As a powerful tool with several applications, PTOs represent a new strategy for targeted therapy in pancreatic cancer and contribute to the advancement of the field of personalized medicine.