Frontiers in Cell and Developmental Biology最新文献

Introduction: Mesenchymal stem cells/stromal cells from the Decidua Basalis of the human placenta (DBMSCs) express wide range of effector molecules that modulate the functions of their target cells. These properties make them potential candidate for use in cellular therapy. In this study, we have investigated the consequences of interaction between DBMSCs and natural killer (NK) cells for both cell types.

Methods: DBMSCs were cultured with IL-2-activated and resting non-activated NK cells isolated from healthy human peripheral blood and various functional assays were performed including, NK cell proliferation and cytolytic activities. Flow cytometry and microscopic studies were performed to examine the expression of NK cell receptors that mediate these cytolytic activities against DBMSCs. Moreover, the mechanism underlying these effects was also investigated.

Results: Our findings revealed that, co-culture of DBMSCs and NK cells resulted in inhibition of proliferation of resting NK cells, while proliferation of IL-2 activated NK cells was increased. Contrarily, treatment of DBMSC's with comparatively high numbers of IL-2 activated NK cells, resulted in their lysis, whereas treatment with low numbers resulted in reduction in their proliferation. Cytolytic activity of NK cells against DBMSCs was mediated by several activating NK cell receptors. In spite of the expression of HLA class I molecules by DBMSCs, they were still lysed by NK cells, excluding their involvement in cytolytic activity. In addition, preconditioning NK cells by DBMSCs, enhanced their ability to suppress tumor cell proliferation and in severe cases resulted in their partial lysis. Lysis and decrease of tumor cell proliferation is associated with increased expression of important molecules involved in anticancer activities.

Discussion: We conclude that DBMSCs exhibit dualfunctions on NK cells that enhance their anticancer therapeutic potential.

Introduction: Our study aims to provide a comprehensive overview of mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) in drug delivery research, focusing on the period between 2013 and 2023. Given the increasing global interest in this field, we utilized bibliometric tools to explore publication trends, key contributors, and thematic research clusters.

Methods: Data was collected from the Web of Science (WoS) database, and an in-depth bibliometric analysis was conducted using VOSviewer. The analysis encompassed bibliographic coupling, co-citation, co-authorship, and co-occurrence trends, offering a structured insight into global research activity. We also employed Citespace to further analyze thematic clusters in this domain.

Results: Our analysis revealed a total of 1,045 publications related to MSC-EVs in drug delivery over the past decade, showing a steady increase in research output. China led in publication count, H-index, prolific authors, and research funding, while the United States ranked highest in total citations, average citation counts, and H-index performance. Pharmaceutics emerged as the leading journal by publication volume, with the Journal of Controlled Release having the strongest total link strength. Top institutions driving research included Shanghai Jiao Tong University, Zhejiang University, and Harvard University. VOSviewer analysis identified four major research clusters: tissue engineering, cancer, neurological diseases, and targeted delivery. Citespace analysis refined this further into ten thematic areas, including differentiation, tissue regeneration, and drug resistance.

Discussion: This bibliometric assessment provides a holistic visualization of the research landscape for MSC-EVs in drug delivery, underlining the significant contributions of China and the United States. Our findings underscore the increasing global importance of MSC-EV research and highlight emerging themes that will likely guide future research directions. The insights from this study offer a foundational framework for identifying nascent frontiers in MSC-EV-based drug delivery.

Purpose: This study aims to develop a diffusion-based workflow to precisely predict postoperative appearance in blepharoptosis patients.

Methods: We developed PtosisDiffusion, a training-free workflow that combines face mesh with ControlNet for accurate post-operative predictions, and evaluated it using 39 preoperative photos from blepharoptosis patients. The performance of PtosisDiffusion was compared against three other diffusion-based methods: Conditional Diffusion, Repaint, and Dragon Diffusion.

Results: PtosisDiffusion demonstrated superior performance in subjective evaluations, including overall rating, correction, and double eyelid formation. Statistical analyses confirmed that PtosisDiffusion achieved the highest overlap ratio (0.87 $\pm$ 0.07) and an MPLPD ratio close to 1 (1.01 $\pm$ 0.10). The model also showed robustness in extreme cases, and ablation studies confirmed the necessity of each model component.

Conclusion: PtosisDiffusion generates accurate postoperative appearance predictions for ptosis patients using only preoperative photographs. Among the four models tested, PtosisDiffusion consistently outperformed the others in both subjective and statistical evaluation.

Skin wound healing is a complex process which involves multiple molecular events and the underlying mechanism is not fully understood. We presented a comparative transcriptomic analysis of skin wound healing in humans and mice to identify shared molecular mechanisms across species. We analyzed transcriptomes from three distinct stages of the healing process and constructed protein-protein interaction networks to elucidate commonalities in the healing process. A substantial number of differentially expressed genes (DEGs) were identified in human transcriptomes, particularly upregulated genes before and after wound injury, and enriched in processes related to extracellular matrix organization and leukocyte migration. Similarly, the mouse transcriptome revealed thousands of DEGs, with shared biological processes and enriched KEGG pathways, highlighting a conserved molecular signature in skin wound healing. A total of 21 common DEGs were found across human comparisons, and 591 in mouse comparisons, with four genes (KRT2, MARCKSL1, MMP1, and TNC) consistently differentially expressed in both species, suggesting critical roles in mammalian skin wound healing. The expression trends of these genes were consistent, indicating their potential as therapeutic targets. The molecular network analysis identified five subnetworks associated with collagen synthesis, immunity, cell-cell adhesion, and extracellular matrix, with hub genes such as COL4A1, TLR7, TJP3, MMP13, and HIF1A exhibited significant expression changes before and after wound injury in humans and mice. In conclusion, our study provided a detailed molecular network for understanding the healing process in humans and mice, revealing conserved mechanisms that could help the development of targeted therapies across species.

CHAC1, an essential regulator of oxidative stress and ferroptosis, is increasingly recognized for its significant roles in these cellular processes and its impact on various human diseases and cancers. This review aims to provide a comprehensive overview of CHAC1's molecular functions, regulatory mechanisms, and effects in different pathological contexts. Specifically, the study objectives are to elucidate the biochemical pathways involving CHAC1, explore its regulatory network, and discuss its implications in disease progression and potential therapeutic strategies. As a γ-glutamyl cyclotransferase, CHAC1 degrades glutathione, affecting calcium signaling and mitochondrial function. Its regulation involves transcription factors like ATF4 and ATF3, which control CHAC1 mRNA expression. CHAC1 is crucial for maintaining redox balance and regulating cell death pathways in cancer. Its elevated levels are associated with poor prognosis in many cancers, indicating its potential as a biomarker and therapeutic target. Additionally, CHAC1 influences non-cancerous diseases such as neurodegenerative and cardiovascular disorders. Therapeutically, targeting CHAC1 could increase cancer cell sensitivity to ferroptosis, aiding in overcoming resistance to standard treatments. This review compiles current knowledge and recent discoveries, emphasizing CHAC1's vital role in human diseases and its potential in diagnostic and therapeutic applications.

Type 2 innate lymphoid cells (ILC2s) have emerged as pivotal regulators in the pathogenesis of diseases, with their roles in inflammation, metabolism, and tissue homeostasis becoming increasingly recognized. This review provides an overview of the current understanding of ILC2s in inflammation and metabolic disorders, including their functional contributions. Moreover, we will discuss how these cells adapt their metabolic processes to support their function and survival and how their metabolic requirements change under different physiological and pathological conditions. Lastly, we will review recent omics studies that have provided insights into the molecular and cellular characteristics of ILC2s. This includes transcriptomic, proteomic, and metabolomic analyses that have elucidated the gene expression profiles, protein interactions, and metabolic networks, respectively, associated with ILC2s. These studies have advanced our understanding of the functional diversity of ILC2s and their involvement in metabolic disease.

Excess cholesterol accumulation induces the accumulation of foam cells, eventually accelerating atherosclerosis progress. Historically, the mechanisms of macrophage-derived foam cells have attracted attention because of their central role in plaque development, which was challenged by lineage tracing in union with single-cell sequencing (sc-seq). Accumulated studies have uncovered how vascular smooth muscle cells (VSMCs) proliferate and migrate to the vascular intima and accumulate, then transform into foam cells induced by surplus lipids, finally accounting for 30% to 70% of the total foam cells within the plaque of both mice and humans. Therefore, the mechanisms of VSMC-derived foam cells have received increasing attention. The review intends to summarize the transformation mechanism of VSMCs into foam cells induced by oxidized low-density lipoproteins (ox-LDL) in atherosclerosis.

Background: Prostate cancer (PCa) is a prevalent malignant tumor in males, with a significant incidence of biochemical recurrence (BCR) despite advancements in treatment. Adipose tissue surrounding the prostate, known as periprostatic adipose tissue (PPAT), contributes to PCa invasion through adipocytokine production. However, the relationship between adipocytokine-related genes and PCa prognosis remains understudied. This study was conducted to provide a theoretical basis and serve as a reference for the use of adipocytokine-related genes as prognostic markers in PCa.

Methods: Transcriptome and survival data of PCa patients from The Cancer Genome Atlas (TCGA) database were analyzed. Differential gene expression analysis was conducted using the DESeq2 and limma packages. Prognostic genes were identified through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. A prognostic model was developed and validated utilizing receiver operating characteristic (ROC) and Kaplan-Meier (K-M) curves. Assessments of immune cell infiltration and drug sensitivity were also carried out. Subsequently, the function of BNIP3L gene in PCa was verified.

Results: A total of 47 adipocytokine-related differentially expressed genes (DEGs) were identified. Five genes (PPARGC1A, APOE, BNIP3L, STEAP4, and C1QTNF3) were selected as prognostic markers. The prognostic model demonstrated significant predictive accuracy in both training and validation cohorts. Patients with higher risk scores exhibited poorer survival outcomes. Immune cell infiltration analysis revealed that the high-risk group had increased immune and ESTIMATE scores, while the low-risk group had higher tumor purity. In vitro experiments confirmed the suppressive effects of BNIP3L on PCa cell proliferation, migration, and invasion.

Conclusion: The prognostic model independently predicts the survival of patients with PCa, aiding in prognostic prediction and therapeutic efficacy. It expands the study of adipocytokine-related genes in PCa, presenting novel targets for treatment.

There is a well-established link between abnormal sperm chromatin states and poor motility, however, how these two processes are interdependent is unknown. Here, we identified a possible mechanistic insight by showing that Protamine 2, a nuclear DNA packaging protein in sperm, directly interacts with cytoskeletal protein Septin 12, which is associated with sperm motility. Septin 12 has several isoforms, and we show, that in the Prm2 ^-/- sperm, the short one (Mw 36 kDa) is mis-localized, while two long isoforms (Mw 40 and 41 kDa) are unexpectedly lost in Prm2 ^-/- sperm chromatin-bound protein fractions. Septin 12 co-immunoprecipitated with Protamine 2 in the testicular cell lysate of WT mice and with Lamin B1/2/3 in co-transfected HEK cells despite we did not observe changes in Lamin B2/B3 proteins or SUN4 expression in Prm2 ^-/- testes. Furthermore, the Prm2 ^-/- sperm have on average a smaller sperm nucleus and aberrant acrosome biogenesis. In humans, patients with low sperm motility (asthenozoospermia) have imbalanced histone-protamine 1/2 ratio, modified levels of cytoskeletal proteins and we detected retained Septin 12 isoforms (Mw 40 and 41 kDa) in the sperm membrane, chromatin-bound and tubulin/mitochondria protein fractions. In conclusion, our findings present potential interaction between Septin 12 and Protamine 2 or Lamin B2/3 and describe a new connection between their expression and localization, contributing likely to low sperm motility and morphological abnormalities.

In recent years, artificial intelligence (AI), especially deep learning models, has increasingly been integrated into diagnosing and treating diabetic retinopathy (DR). From delving into the singular realm of ocular fundus photography to the gradual development of proteomics and other molecular approaches, from machine learning (ML) to deep learning (DL), the journey has seen a transition from a binary diagnosis of "presence or absence" to the capability of discerning the progression and severity of DR based on images from various stages of the disease course. Since the FDA approval of IDx-DR in 2018, a plethora of AI models has mushroomed, gradually gaining recognition through a myriad of clinical trials and validations. AI has greatly improved early DR detection, and we're nearing the use of AI in telemedicine to tackle medical resource shortages and health inequities in various areas. This comprehensive review meticulously analyzes the literature and clinical trials of recent years, highlighting key AI models for DR diagnosis and treatment, including their theoretical bases, features, applicability, and addressing current challenges like bias, transparency, and ethics. It also presents a prospective outlook on the future development in this domain.