mRNA-Engineered CD5-CAR-γδTCD5- Cells for the Immunotherapy of T-Cell Acute Lymphoblastic Leukemia.

Clinical trials of Chimeric Antigen Receptor T-cell (CAR-T) therapy have demonstrated remarkable success in treating both solid tumors and hematological malignancies. Nanobodies (Nbs) have emerged as promising antigen-targeting domains for CARs, owing to their high specificity, robust stability, and strong affinity, leading to significant advancements in the field of Nb-CAR-T. In the realm of T-cell acute lymphoblastic leukemia (T-ALL) targets, CD5 stands out as a potentially excellent candidate for T-cell-based CAR therapy, due to its distinct expression on the surface of malignant T-ALL cells. To mitigate graft-versus-host disease associated with allogeneic CAR-T, γδT cells are selected and stimulated from peripheral blood mononuclear cells, and γδT cells are engineered via CRISPR/Cas9 to eliminate fratricide, enabling the creation of fratricide-resistant CAR-γδTCD5- cells. In vitro transcribed (IVT) mRNA is used to construct CAR-T, presenting a safer, faster, and cost-effective method compared to traditional viral vector approaches. In this study, a CD5-VHH library is constructed, and specific CD5-nanobodies are screened for subsequent use in CD5-CAR-γδTCD5- therapy. IVT-mRNA-CD5-CAR-γδTCD5- cells exhibited favorable functional characteristics and demonstrated antitumor efficacy against malignant T cell lines, underlining the potential for advancing mRNA-CD5-CAR-γδTCD5- therapy.

Fc receptor-like 5 (FCRL5)-directed CAR-T cells exhibit antitumor activity against multiple myeloma.

Multiple myeloma (MM) remains a challenging hematologic malignancy despite advancements in chimeric antigen receptor T-cell (CAR-T) therapy. Current targets of CAR-T cells used in MM immunotherapy have limitations, with a subset of patients experiencing antigen loss resulting in relapse. Therefore, novel targets for enhancing CAR-T cell therapy in MM remain needed. Fc receptor-like 5 (FCRL5) is a protein marker with considerably upregulated expression in MM and has emerged as a promising target for CAR-T cell therapeutic interventions, offering an alternative treatment for MM. To further explore this option, we designed FCRL5-directed CAR-T cells and assessed their cytotoxicity in vitro using a co-culture system and in vivo using MM cell-derived xenograft models, specifically focusing on MM with gain of chromosome 1q21. Given the challenges in CAR-T therapies arising from limited T cell persistence, our approach incorporates interleukin-15 (IL-15), which enhances the functionality of central memory T (TCM) cells, into the design of FCRL5-directed CAR-T cells, to improve cytotoxicity and reduce T-cell dysfunction, thereby promoting greater CAR-T cell survival and efficacy. Both in vitro and xenograft models displayed that FCRL5 CAR-T cells incorporating IL-15 exhibited potent antitumor efficacy, effectively inhibiting the proliferation of MM cells and leading to remarkable tumor suppression. Our results highlight the capacity of FCRL5-specific CAR-T cells with the integration of IL-15 to improve the therapeutic potency, suggesting a potential novel immunotherapeutic strategy for MM treatment.

Low cholesterol levels are associated with increasing risk of plasma cell neoplasm: A UK biobank cohort study.

BACKGROUND: Plasma cell neoplasms are a group of hematologic neoplasms that often develop in the elderly population. The relationship between cholesterol levels and hematologic malignancy has been identified in population studies. However, it is still unclear if there is a relationship between cholesterol levels and plasma cell neoplasm in European ancestry. METHODS: Prospective cohorts included 502,507 individuals from the UK Biobank who were followed up to 2019 and assessed total cholesterol(TC) levels, low-density lipoprotein (LDL) levels, high-density lipoprotein (HDL) levels, apolipoprotein A (ApoA) and apolipoprotein B (ApoB) as risk factors for plasma cell neoplasms with Cox proportional hazard regression and restricted cubic spline model. We also used two-sample Mendelian randomization to determine if the cholesterol level has a causal effect on developing plasma cell neoplasms. RESULTS: We observed 1819 plasma cell neoplasm cases during 14.2 years of follow-up in the UK Biobank. We found higher blood serum cholesterol levels at baseline were associated with a lower risk of plasma cell neoplasm in our study. All lipid profiles we analyzed in this study were inversely associated with plasma cell neoplasm risk (all ptrend <0.005) but triglycerides did not have such association. However, there was no suggestive association of genetically predicted serum LDL, HDL, and total cholesterol levels with multiple myeloma. CONCLUSION: Low serum total cholesterol, LDL, HDL, ApoA, and ApoB levels were all associated with increasing the risk of plasma cell neoplasm.

Nutritional Status Indices and Monoclonal Gammopathy of Undetermined Significance Risk in the Elderly Population: Findings from the National Health and Nutrition Examination Survey.

OBJECTIVE: Although several studies have found dietary intake is related to multiple myeloma (MM) and its precursor status risks, the role of one's nutritional status has been ignored and its role in plasma cell neoplasm development is still unclear. This study aimed to explore the relationship between various clinical indices of nutritional status and the risk of monoclonal gammopathy of undetermined significance (MGUS) in the population. METHODS: We selected 9520 participants from the NHANES III and NHANES 1999-2004 studies. Controlling nutritional status index (CONUT), prognostic nutritional index (PNI), geriatric nutritional risk index (GNRI) and body mass index (BMI) were calculated as indices of nutritional status of the participants. Associations between nutritional indices and MGUS were investigated using multiple logistic regression, subgroup analysis, and an RCS model. RESULTS: In our study, 266 participants had MGUS, with a prevalence of 2.79%. This study found that CONUT and PNI identified populations with poor nutritional status and had a significant positive correlation with the risk of MGUS. In multivariate logistic regression, compared with the lower CONUT score (<3) group, the OR for the group with higher scores (≥3) was 1.805 (95%CI: 1.271, 2.564). Compared with the lowest quartile group, the highest quartile PNI score group had an OR of 0.509 (95%CI: 0.290, 0.896). GNRI had no significant correlation with the risk of MGUS, with an OR of 0.737 (95%CI: 0.443, 1.227). CONCLUSION: This study found that older adults with CONUT and PNI scores indicating poorer nutrition had a higher risk of MGUS.

Characterization and application of a lactate and branched chain amino acid metabolism related gene signature in a prognosis risk model for multiple myeloma.

BACKGROUND: About 10% of hematologic malignancies are multiple myeloma (MM), an untreatable cancer. Although lactate and branched-chain amino acids (BCAA) are involved in supporting various tumor growth, it is unknown whether they have any bearing on MM prognosis. METHODS: MM-related datasets (GSE4581, GSE136337, and TCGA-MM) were acquired from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. Lactate and BCAA metabolism-related subtypes were acquired separately via the R package "ConsensusClusterPlus" in the GSE4281 dataset. The R package "limma" and Venn diagram were both employed to identify lactate-BCAA metabolism-related genes. Subsequently, a lactate-BCAA metabolism-related prognostic risk model for MM patients was constructed by univariate Cox, Least Absolute Shrinkage and Selection Operator (LASSO), and multivariate Cox regression analyses. The gene set enrichment analysis (GSEA) and R package "clusterProfiler"were applied to explore the biological variations between two groups. Moreover, single-sample gene set enrichment analysis (ssGSEA), Microenvironment Cell Populations-counter (MCPcounte), and xCell techniques were applied to assess tumor microenvironment (TME) scores in MM. Finally, the drug's IC50 for treating MM was calculated using the "oncoPredict" package, and further drug identification was performed by molecular docking. RESULTS: Cluster 1 demonstrated a worse prognosis than cluster 2 in both lactate metabolism-related subtypes and BCAA metabolism-related subtypes. 244 genes were determined to be involved in lactate-BCAA metabolism in MM. The prognostic risk model was constructed by CKS2 and LYZ selected from this group of genes for MM, then the prognostic risk model was also stable in external datasets. For the high-risk group, a total of 13 entries were enriched. 16 entries were enriched to the low-risk group. Immune scores, stromal scores, immune infiltrating cells (except Type 17 T helper cells in ssGSEA algorithm), and 168 drugs'IC50 were statistically different between two groups. Alkylating potentially serves as a new agent for MM treatment. CONCLUSIONS: CKS2 and LYZ were identified as lactate-BCAA metabolism-related genes in MM, then a novel prognostic risk model was built by using them. In summary, this research may uncover novel characteristic genes signature for the treatment and prognostic of MM.

The evolution of minimal residual disease: key insights based on a bibliometric visualization analysis from 2002 to 2022.

Background: The topic of minimal residual disease (MRD) has emerged as a crucial subject matter in the domain of oncology in recent years. The detection and monitoring of MRD have become essential for the diagnosis, treatment, and prognosis of various types of malignancy. Aims: The purpose of this study is to explore the research trends, hotspots, and frontiers of MRD in the last two decades through bibliometric analysis. Methods: We employed Web of Science databases to carry out a bibliometric visualization analysis of research on 8,913 academic papers about MRD research from 2002 to 2022. VOSviewer, CiteSpace, RStudio, and a bibliometric online analysis platform were mainly used to conduct co-occurrence analysis and cooperative relationship analysis of countries/regions, institutions, journals, and authors in the literature. Furthermore, co-occurrence, co-citation, and burst analyses of keyword and reference were also conducted to generate relevant knowledge maps. Results: In the past 20 years, the number of MRD research papers has presented an overall rising trend, going through three stages: a plateau, development, and an explosion. The output of articles in the United States was notably superior and plays a dominant role in this field, and the Netherlands had the highest average citation per article. The most productive and influential institution was the University of Texas MD Anderson Cancer Center. Blood published the most papers and was the most cited journal. A collection of leading academics has come to the fore in the research field, the most prolific of which is Kantarjian HM. It was found that the application of MRD in "acute myeloid leukemia", "acute lymphoblastic leukemia", "multiple myeloma", as well as the detection technology of MRD, are the research hotspots and frontiers in this domain. Furthermore, we analyzed the co-citation network of references and found that the top 10 co-cited references were all associated with MRD in hematological malignancies. Conclusion: This bibliometric visualization analysis conducted a thorough exploration into the research hotspots and trends in MRD from 2002 to 2022. Our findings can aid researchers in recognizing possible collaborations, guiding future research directions, and fostering the growth of MRD detection and monitoring technologies.

A Novel Optimized iBeacon Localization Algorithm Modeling.

The conventional methods for indoor localization rely on technologies such as RADAR, ultrasonic, laser range localization, beacon technology, and others. Developers in the industry have started utilizing these localization techniques in iBeacon systems that use Bluetooth sensors to measure the object's location. The iBeacon-based system is appealing due to its low cost, ease of setup, signaling, and maintenance; however, with current technology, it is challenging to achieve high accuracy in indoor object localization or tracking. Furthermore, iBeacons' accuracy is unsatisfactory, and they are vulnerable to other radio signal interference and environmental noise. In order to address those challenges, our study focuses on the development of error modeling algorithms for signal calibration, uncertainty reduction, and interfered noise elimination. The new error modeling is developed on the Curve Fitted Kalman Filter (CFKF) algorithms. The reliability, accuracy, and feasibility of the CFKF algorithms are tested in the experiments. The results significantly show the improvement of the accuracy and precision with this novel approach for iBeacon localization.

New perspective on African swine fever: a bibliometrics study and visualization analysis.

Introduction: African swine fever (ASF) is a contagious viral disease that can have devastating effects on domestic pigs and wild boars. Over the past decade, there has been a new wave of this ancient disease spreading around the world, prompting many scholars to dedicate themselves to researching this disease. This research aims to use bibliometric methods to organize, analyze and summarize the scientific publications on ASF that have been amassed in the past two decades. Methods: This paper used VOSviewer, CiteSpace, and a bibliometric online analysis platform to conduct performance analysis and visualization studies on 1,885 academic papers about ASF in the Web of Science from January 2003 to December 2022. Results: The amount of literature published on ASF has increased exponentially in recent years, and the development trend of related research is good. A group of representative scholars have appeared in this research field, and some cooperative networks have been formed. Transboundary and Emerging Diseases is the journal with the most publications in this field, while Virus Research is the journal with the most citation per article. High-productivity countries are led by China in terms of the number of articles published followed by the United States and Spain. In regard to the average number of citations, the scholars in the UK are in the lead. The institution with the most articles was the Chinese Academy of Agricultural Sciences. The analysis of high-frequency keywords showed that the pathogens and epidemiology of ASF were the research hotspots in this field, and the research content was closely related to molecular biology and immunology. The burst keywords "transmission", "identification", "virulence", "replication", and "gene" reflects the research frontier. In addition, by collating and analyzing highly cited journals and highly co-cited references, we explored the knowledge structure and theoretical basis of this field. Discussion: This is the first bibliometric analysis report on ASF research, which highlights the key characteristics of ASF research and presents the research status and evolution trend in this field from a new perspective. It provides a valuable reference for further research.

Impacts of Random Atomic Defects on Critical Buckling Stress of Graphene under Different Boundary Conditions.

Buckled graphene has potential applications in energy harvest, storage, conversion, and hydrogen storage. The investigation and quantification analysis of the random porosity in buckled graphene not only contributes to the performance reliability evaluation, but it also provides important references for artificial functionalization. This paper proposes a stochastic finite element model to quantify the randomly distributed porosities in pristine graphene. The Monte Carlo stochastic sampling process is combined with finite element computation to simulate the mechanical property of buckled graphene. Different boundary conditions are considered, and the corresponding results are compared. The impacts of random porosities on the buckling patterns are recorded and analyzed. Based on the large sampling space provided by the stochastic finite element model, the discrepancies caused by the number of random porosities are discussed. The possibility of strengthening effects in critical buckling stress is tracked in the large sampling space. The distinguishable interval ranges of probability density distribution for the relative variation of the critical buckling stress prove the promising potential of artificial control by the atomic vacancy amounts. In addition, the approximated Gaussian density distribution of critical buckling stress demonstrates the stochastic sampling efficiency by the Monte Carlo method and the artificial controllability of porous graphene. The results of this work provide new ideas for understanding the random porosities in buckled graphene and provide a basis for artificial functionalization through porosity controlling.

Establishment and Application of Indirect ELISAs for Detecting Antibodies against Goose Astrovirus Genotype 1 and 2.

Goose astrovirus (GAstV) was classified into GAstV-1 and GAstV-2, and both caused gosling viral gout. Recently, there has been no effective commercial vaccine to control the infection. It is important to establish serological methods to distinguish between the two genotypes. In this study, we reported the development and application of two indirect enzyme-linked immunosorbent assays (ELISAs) using the GAstV-1 virus and a recombinant GAstV-2 capsid protein as specific antigens to detect antibodies against GAstV-1 and GAstV-2, respectively. The optimal coating antigen concentration of indirect GAstV-1-ELISA and GAstV-2-Cap-ELISA was 1.2 µg/well and 125 ng/well, respectively. In addition, the antigen coating temperature and time, sera dilution and reaction time, and the dilution and reaction time of HRP-conjugated secondary antibody were optimized. The cut-off values were 0.315 and 0.305, and the analytical sensitivity was 1:6400 and 1:3200 for indirect GAstV-1-ELISA and GAstV-2-Cap-ELISA, respectively. The assays were able to differentiate specific sera against GAstVs, TUMV, GPV, and H9N2-AIV. The intra- and inter-plate variabilities of indirect ELISAs were less than 10%. The coincidence rate of positive sera was higher than 90%. The indirect ELISAs were further applied to test 595 goose serum samples. The results showed that the detection rates were 33.3% and 71.4% in GAstV-1-ELISA and GAstV-2-Cap-ELISA, respectively, and the co-detection rate was 31.1%, which indicates that the seroprevalence rate of GAstv-2 was higher than that of GastV-1, and the co-infection existed between GAstV-1 and GAstV-2. In summary, the developed GAstV-1-ELISA and GAstV-2-Cap-ELISA have high specificity, sensitivity, and reproducibility and can be used in the clinical detection of the antibody against GAstV-1 and GAstV-2.

A systematic review on performance analysis of critical time points in multiple myeloma treated by CAR-T cell immunotherapy.

BACKGROUND: Multiple myeloma (MM) is the second most common hematological malignancy without cure, and Chimeric Antigen Receptor T Cell (CAR-T) therapy has been shown great promising in MM. Unlike previous published studies mainly focusing on efficacy and safety, this study aims to summarize time points in the process of CAR-T therapy in MM and establish a standardized time-related CAR-T therapy platform to provide a reference for CAR-T treatment in MM. METHODS: All the literatures were retrieved from PubMed, Web of Science, Embase, American Society of Hematology (ASH), American Society of Clinical Oncology (ASCO) and European Hematology Association (EHA). Relevant median detection time of efficacy and safety-related indicators of CAR-T therapy in MM were extracted from included literatures, and median values were applied to represent detection time points of indicators. Notably, the median values were not the certain and optimal detection time points, while the significance is that indicators could be detected more frequently around the median values to obtain the ideal results. RESULTS: This review presented the median detection time points of efficacy and safety-related indicators of CAR-T therapy in MM according to the chronological order. For short-term effects on inflammation status within 1 month after CAR-T initiation, the median time points of cytokine release syndrome onset, immune effector cell-associated neurotoxicity syndrome onset, neutrophils recovery and CAR-T expansion peak were 4.5, 8, 10 and 12 days, respectively. For medium-term effects on clinical response in MM beyond 1 month and up to 3 months following CAR-T infusion, the median time points of minimal residual disease negativity, the reduction of serum light chain to minimum, platelet recovery and the reduction of M protein to minimum were 30, 30, 44 and 90 days, respectively. CONCLUSIONS: This systematic review summarized the median detection time points of efficacy and safety-related indicators of CAR-T therapy in MM and constructed the time-related CAR-T therapy platform, providing an evidence-based standard for establishment of CAR-T treatment regimen in MM.

A Machine Learning Applied Diagnosis Method for Subcutaneous Cyst by Ultrasonography.

For decades, ultrasound images have been widely used in the detection of various diseases due to their high security and efficiency. However, reading ultrasound images requires years of experience and training. In order to support the diagnosis of clinicians and reduce the workload of doctors, many ultrasonic computer aided diagnostic systems have been proposed. In recent years, the success of deep learning in image classification and segmentation has made more and more scholars realize the potential performance improvement brought by the application of deep learning in ultrasonic computer-aided diagnosis systems. This study is aimed at applying several machine learning algorithms and develop a machine learning method to diagnose subcutaneous cyst. Clinical features are extracted from datasets and images of ultrasonography of 132 patients from Hunan Provincial People's Hospital in China. All datasets are separated into 70% training and 30% testing. Four kinds of machine learning algorithms including decision tree (DT), support vector machine (SVM), K-nearest neighbors (KNN), and neural networks (NN) had been approached to determine the best performance. Compared with all the results from each feature, SVM achieved the best performance from 91.7% to 100%. Results show that SVM performed the highest accuracy in the diagnosis of subcutaneous cyst by ultrasonography, which provide a good reference in further application to clinical practice of ultrasonography of subcutaneous cyst.

An emerging prognosis prediction model for multiple myeloma: Hypoxia-immune related microenvironmental gene signature.

Multiple myeloma (MM), a hematologic malignancy, is characterized by malignant plasma cells clonal proliferation. Many evidences indicated the indirect interaction between hypoxic environment and immune state in MM tumorigenesis, but the underlying mechanism remains unclear. MM-related datasets were downloaded from the Gene Expression Omnibus (GEO) database. The R packages were applied for screening protective differentially expressed genes (DEGs) and risk DEGs. The signature was constructed based the most prognostic gene signature in the training and assessed in the validation cohorts. The immune cell infiltration, the expression of the HLA family and immune checkpoint genes inside the low- and high-risk groups were compared to determine the differences in immune infiltration and immunotherapy responses. Moreover, the expression of HLA families and immune checkpoints inside the low- and high-risk groups was markedly disordered. The results indicated hypoxia- and immune-related genes, including CHRDL1, DDIT4, DNTT, FAM133A, MYB, PRR15, QTRT1, and ZNF275, were identified and used to construct a prognostic signature. Role of DDIT4 in multiple myeloma was confirmed in vivo and in vitro. DDIT4 knockdown inhibited MM cell viability, migration and invasion potential as well as promoted myeloma cells apoptosis under hypoxia. Taken together, our study may contribute to the treatment and prognosis prediction of MM.

Chronic Cervicitis and Cervical Cancer Detection Based on Deep Learning of Colposcopy Images Toward Translational Pharmacology.

With the rapid development of deep learning, automatic image recognition is widely used in medical development. In this study, a deep learning convolutional neural network model was developed to recognize and classify chronic cervicitis and cervical cancer. A total of 10,012 colposcopy images of 1,081 patients from Hunan Provincial People's Hospital in China were recorded. Five different colposcopy image features of the cervix including chronic cervicitis, intraepithelial lesions, cancer, polypus, and free hyperplastic squamous epithelial tissue were extracted to be applied in our deep learning network convolutional neural network model. However, the result showed a low accuracy (42.16%) due to computer misrecognition of chronic cervicitis, intraepithelial lesions, and free hyperplastic squamous epithelial tissue with high similarity. To optimize this model, we selected two significant feature images: chronic cervicitis and cervical cancer to input into a deep learning network. The result indicates high accuracy and robustness with an accuracy of 95.19%, which can be applied to detect whether the patient has chronic cervicitis or cervical cancer based on the patient's colposcopy images.

A Supervised ML Applied Classification Model for Brain Tumors MRI.

Brain Tumor originates from abnormal cells, which is developed uncontrollably. Magnetic resonance imaging (MRI) is developed to generate high-quality images and provide extensive medical research information. The machine learning algorithms can improve the diagnostic value of MRI to obtain automation and accurate classification of MRI. In this research, we propose a supervised machine learning applied training and testing model to classify and analyze the features of brain tumors MRI in the performance of accuracy, precision, sensitivity and F1 score. The result presents that more than 95% accuracy is obtained in this model. It can be used to classify features more accurate than other existing methods.

Corrigendum: LYG1 Deficiency Attenuates the Severity of Acute Graft-Versus-Host Disease via Skewing Allogeneic T Cells Polarization Towards Treg Cells.

[This corrects the article DOI: 10.3389/fimmu.2021.647894.].

Controlled Release of Curcumin from HPMC (Hydroxypropyl Methyl Cellulose) Co-Spray-Dried Materials.

In order to achieve the controlled release of curcumin, HPMC (hydroxypropyl methyl cellulose) was spray dried with curcumin and lactose. The spray-dried materials were pressed into tablets with a diameter of 8 mm, and their release characteristics in vitro were measured. In vitro experiments showed that the release of curcumin from the HPMC mixture was significantly slower due to the sustained-release property of HPMC as a typical excipient. The release profile of curcumin from the HPMC mixture was relatively stable for a controlled release. SEM images show that the HPMC co-spray-dried powders have crumpled surfaces due to the large molecular weight of HPMC. DSC, XRD, FTIR, N2 adsorption, and TGA have been measured for the spray-dried curcumin materials. This work indicates that HPMC can be used as a controlled-release excipient for curcumin preparations.

LYG1 Deficiency Attenuates the Severity of Acute Graft-Versus-Host Disease via Skewing Allogeneic T Cells Polarization Towards Treg Cells.

Acute graft-versus-host disease (aGVHD) is a lethal complication after allogeneic hematopoietic stem cell transplantation. The mechanism involves the recognition of host antigens by donor-derived T cells which induces augmented response of alloreactive T cells. In this study, we characterized the role of a previously identified novel classical secretory protein with antitumor function-LYG1 (Lysozyme G-like 1), in aGVHD. LYG1 deficiency reduced the activation of CD4+ T cells and Th1 ratio, but increased Treg ratio in vitro by MLR assay. By using major MHC mismatched aGVHD model, LYG1 deficiency in donor T cells or CD4+ T cells attenuated aGVHD severity, inhibited CD4+ T cells activation and IFN-γ expression, promoted FoxP3 expression, suppressed CXCL9 and CXCL10 expression, restrained allogeneic CD4+ T cells infiltrating in target organs. The function of LYG1 in aGVHD was also confirmed using haploidentical transplant model. Furthermore, administration of recombinant human LYG1 protein intraperitoneally aggravated aGVHD by promoting IFN-γ production and inhibiting FoxP3 expression. The effect of rhLYG1 could partially be abrogated with the absence of IFN-γ. Furthermore, LYG1 deficiency in donor T cells preserved graft-versus-tumor response. In summary, our results indicate LYG1 regulates aGVHD by the alloreactivity of CD4+ T cells and the balance of Th1 and Treg differentiation of allogeneic CD4+ T cells, targeting LYG1 maybe a novel therapeutic strategy for preventing aGVHD.

Mesenchymal stem cells alleviate idiopathic pneumonia syndrome by modulating T cell function through CCR2-CCL2 axis.

BACKGROUND: Idiopathic pneumonia syndrome (IPS) is a non-infectious fatal complication characterized by a massive infiltration of leukocytes in lungs and diffuse pulmonary injury after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Conventional immunosuppressive treatments for IPS have poor therapeutic effects. Safe and effective treatments are not yet available and under explorations. Our previous study demonstrated that mesenchymal stem cells (MSCs) can alleviate IPS, but the mechanisms remain unclear. METHODS: Co-cultured pre-activated T cells and MSCs in vitro to observe the changes in the CCR2-CCL2 axis. By establishing an IPS mouse model and administering MSCs to further verify the results of in vitro experiments. RESULTS: Co-culture of pre-activated T cells with MSCs in vitro modulated the CCR2-CCL2 axis, resulting in quiescent T cells and polarization toward CCR2+CD4+ T cell subsets. Blocking CCR2-CCL2 interaction abolished the immunoregulatory effect of MSCs, leading to re-activation of T cells and partial reversion of polarizing toward CCR2+CD4+ T cells. In IPS mouse model, application of MSCs prolonged the survival and reduced the pathological damage and T cell infiltration into lung tissue. Activation of CCR2-CCL2 axis and production of CCR2+CD4+ T cells were observed in the lungs treated with MSCs. The prophylactic effect of MSCs on IPS was significantly attenuated by the administration of CCR2 or CCL2 antagonist in MSC-treated mice. CONCLUSIONS: We demonstrated an important role of CCR2-CCL2 axis in modulating T cell function which is one of the mechanisms of the prophylactic effect of MSCs on IPS.

The Potential Genes Mediate the Pathogenicity of Allogeneic CD4+T Cell in aGVHD Mouse Model.

Acute graft-versus-host disease (aGVHD) remains a significant and severe complication of allogeneic hematopoietic stem cell transplantation (allo-HSCT). Due to the occurrence of aGVHD, allo-HSCT significantly increases the mortality rate compared with autologous hematopoietic stem cell transplantation (auto-HSCT). In this study, auto-HSCT and allo-HSCT aGVHD mouse models were built to detect the difference in CD4+ lymphocyte in different tissues based on ribonucleic acid sequencing (RNA-Seq) analysis. Clustering analysis, functional annotation, and pathway enrichment analysis were performed on differentially expressed genes (DEGs). The protein-protein interaction (PPI) network was used to find hub genes. CD4+T cells were activated by MLR and cytokine stimulation. Cells were sorted out by a flow cell sorter. The selected genes were verified by qRT-PCR, histology, and immunofluorescence staining. The GSE126518 GEO dataset was used to verify the hub genes. Enrichment analysis revealed four immune-related pathways that play an important role in aGVHD, including immunoregulatory interactions between a lymphoid and a nonlymphoid cell, chemokine receptors binding chemokines, cytokine and cytokine receptor interaction, and the chemokine signaling pathway. At the same time, with the PPI network, 11 novel hub genes that were most likely to participate in immunoregulation in aGVHD were identified, which were further validated by qRT-PCR and the GSE126518 dataset. Besides, the protein expression level of Cxcl7 was consistent with the sequencing results. In summary, this study revealed that immunoregulation-related DEGs and pathways played a vital role in the onset of aGVHD. These findings may provide some new clues for probing the pathogenesis and treatment of aGVHD.