Journal of Biomedical Science最新文献

Over the past decade, organoids have emerged as a prevalent and promising research tool, mirroring the physiological architecture of the human body. However, as the field advances, the traditional use of animal or tumor-derived extracellular matrix (ECM) as scaffolds has become increasingly inadequate. This shift has led to a focus on developing synthetic scaffolds, particularly hydrogels, that more accurately mimic three-dimensional (3D) tissue structures and dynamics in vitro. The ECM-cell interaction is crucial for organoid growth, necessitating hydrogels that meet organoid-specific requirements through modifiable physical and compositional properties. Advanced composite hydrogels have been engineered to more effectively replicate in vivo conditions, offering a more accurate representation of human organs compared to traditional matrices. This review explores the evolution and current uses of decellularized ECM scaffolds, emphasizing the application of decellularized ECM hydrogels in organoid culture. It also explores the fabrication of composite hydrogels and the prospects for their future use in organoid systems.

Background: The burgeoning field of regenerative medicine has significantly advanced with recent findings on biotherapies using human platelet lysates (HPLs), derived from clinical-grade platelet concentrates (PCs), for treating brain disorders. These developments have opened new translational research avenues to explore the neuroprotective effects of platelet-extracellular vesicles (PEVs). Their potential in managing neurodegenerative conditions like traumatic brain injury (TBI) and Parkinson's disease (PD) warrants further exploration. We aimed here to characterize the composition of a PEV preparation isolated from platelet concentrate (PC) supernatant, and determine its neuroprotective potential and neurorestorative effects in cellular and animal models of TBI and PD.

Methods: We isolated PEVs from the supernatant of clinical-grade PC collected from healthy blood donors utilizing high-speed centrifugation. PEVs were characterized by biophysical, biochemical, microscopic, and LC-MS/MS proteomics methods to unveil biological functions. Their functionality was assessed in vitro using SH-SY5Y neuronal cells, LUHMES dopaminergic neurons, and BV-2 microglial cells, and in vivo by intranasal administration in a controlled cortical impact (CCI)-TBI model using 8-weeks-old male C57/BL6 mice, and in a PD model induced by MPTP in 5-month-old male C57/BL6 mice.

Results: PEVs varied in size from 50 to 350 nm, predominantly around 200 nm, with concentrations ranging between 10¹⁰ and 10¹¹/mL. They expressed specific platelet membrane markers, exhibited a lipid bilayer by cryo-electron microscopy and, importantly, showed low expression of pro-coagulant phosphatidylserine. LC-MS/MS indicated a rich composition of trophic factors, including neurotrophins, anti-inflammatory agents, neurotransmitters, and antioxidants, unveiling their multifaceted biological functions. PEVs aided in the restoration of neuronal functions in SH-SY5Y cells and demonstrated remarkable neuroprotective capabilities against erastin-induced ferroptosis in dopaminergic neurons. In microglial cells, they promoted anti-inflammatory responses, particularly under inflammatory conditions. In vivo, intranasally delivered PEVs showed strong anti-inflammatory effects in a TBI mouse model and conserved tyrosine hydroxylase expression of dopaminergic neurons of the substantia nigra in a PD model, leading to improved motor function.

Conclusions: The potential of PEV-based therapies in neuroprotection opens new therapeutic avenues for neurodegenerative disorders. The study advocates for clinical trials to establish the efficacy of PEV-based biotherapies in neuroregenerative medicine.

Background: Dysregulation of vascular homeostasis can induce cardiovascular diseases and increase global mortality rates. Although lineage tracing studies have confirmed the pivotal role of modulated vascular smooth muscle cells (VSMCs) in the progression of pathological vascular remodeling, the underlying mechanisms are still unclear.

Methods: The expression of Tudor-SN was determined in VSMCs of artery stenosis, PDGF-BB-treated VSMCs and atherosclerotic plaque. Loss- and gain-of-function approaches were used to explore the role of Tudor-SN in the modulation of VSMCs phenotype both in vivo and in vitro.

Results: In this study, we demonstrate that Tudor-SN expression is significantly elevated in injury-induced arteries, atherosclerotic plaques, and PDGF-BB-stimulated VSMCs. Tudor-SN deficiency attenuates, but overexpression aggravates the synthetic phenotypic switching of VSMCs and pathological vascular remodeling. Loss of Tudor-SN also reduces atherosclerotic plaque formation and increases plaque stability. Mechanistically, PTEN, the major regulator of the MAPK and PI3K-AKT signaling pathways, plays a vital role in Tudor-SN-mediated regulation on proliferation and migration of VSMCs. Tudor-SN facilitates the polyubiquitination and degradation of PTEN via NEDD4-1, thus exacerbating vascular remodeling under pathological conditions. BpV (HOpic), a specific inhibitor of PTEN, not only counteracts the protective effect of Tudor-SN deficiency on proliferation and migration of VSMCs, but also abrogates the negative effect of carotid artery injury-induced vascular remodeling in mice.

Conclusions: Our findings reveal that Tudor-SN deficiency significantly ameliorated pathological vascular remodeling by reducing NEDD4-1-dependent PTEN polyubiquitination, suggesting that Tudor-SN may be a novel target for preventing vascular diseases.

Background: While dengue NS1 antigen has been shown to be associated with disease pathogenesis in some studies, it has not been linked in other studies, with the reasons remaining unclear. NS1 antigen levels in acute dengue are often associated with increased disease severity, but there has been a wide variation in results based on past dengue infection and infecting dengue virus (DENV) serotype. As NS1 engages with many host lipids, we hypothesize that the type of NS1-lipid interactions alters its pathogenicity.

Methods: Primary human monocyte derived macrophages (MDMs) were co-cultured with NS1 alone or with HDL, LDL, LPS and/or platelet activating factor (PAF) from individuals with a history of past dengue fever (DF = 8) or dengue haemorrhagic fever (DHF = 8). IL-1β levels were measured in culture supernatants, and gene expression analysis carried out in MDMs. Monocyte subpopulations were assessed by flow cytometry. Hierarchical cluster analysis with Euclidean distance calculations were used to differentiate clusters. Differentially expressed variables were extracted and a classifier model was developed to differentiate between past DF and DHF.

Results: Significantly higher levels of IL-1β were seen in culture supernatants when NS1 was co-cultured with LDL (p = 0.01, median = 45.69 pg/ml), but lower levels when NS1 was co-cultured with HDL (p = 0.05, median = 4.617 pg/ml). MDMs of those with past DHF produced higher levels of IL-1β when NS1 was co-cultured with PAF (p = 0.02). MDMs of individuals with past DHF, were significantly more likely to down-regulate RPLP2 gene expression when macrophages were co-cultured with either PAF alone, or NS1 combined with PAF, or NS1 combined with LDL. When NS1 was co-cultured with PAF, HDL or LDL two clusters were detected based on IL10 expression, but these did not differentiate those with past DF or DHF.

Conclusions: As RPLP2 is important in DENV replication, regulating cellular stress responses and immune responses and IL-10 is associated with severe disease, it would be important to further explore how differential expression of RPLP2 and IL-10 could lead to disease pathogenesis based on NS1 and lipid interactions.

Extracellular vesicles (EVs) are vital for cell-to-cell communication, transferring proteins, lipids, and nucleic acids in various physiological and pathological processes. They play crucial roles in immune modulation and tissue regeneration but are also involved in pathogenic conditions like inflammation and degenerative disorders. EVs have heterogeneous populations and cargo, with numerous subpopulations currently under investigations. EV therapy shows promise in stimulating tissue repair and serving as a drug delivery vehicle, offering advantages over cell therapy, such as ease of engineering and minimal risk of tumorigenesis. However, challenges remain, including inconsistent nomenclature, complex characterization, and underdeveloped large-scale production protocols. This review highlights the recent advances and significance of EVs heterogeneity, emphasizing the need for a better understanding of their roles in disease pathologies to develop tailored EV therapies for clinical applications in neurological disorders.

Background: Identification of lung cancer subtypes is critical for successful treatment in patients, especially those in advanced stages. Many advanced and personal treatments require knowledge of specific mutations, as well as up- and down-regulations of genes, for effective targeting of the cancer cells. While many studies focus on individual cell structures and delve deeper into gene sequencing, the present study proposes a machine learning method for lung cancer classification based on low-magnification cancer outgrowth patterns in a 2D co-culture environment.

Methods: Using a magnetic well plate holder, circular pattern lung cancer cell clusters were generated among fibroblasts, and daily images were captured to monitor cancer outgrowth over a 9-day period. These outgrowth images were then augmented and used to train a convolutional neural network (CNN) model based on the lightweight TinyVGG architecture. The model was trained with pairs of classes representing three subtypes of NSCLC: A549 (adenocarcinoma), H520 (squamous cell carcinoma), and H460 (large cell carcinoma). The objective was to assess whether this lightweight machine learning model could accurately classify the three lung cancer cell lines at different stages of cancer outgrowth. Additionally, cancer outgrowth images of two patient-derived lung cancer cells, one with the KRAS oncogene and the other with the EGFR oncogene, were captured and classified using the CNN model. This demonstration aimed to investigate the translational potential of machine learning-enabled lung cancer classification.

Results: The lightweight CNN model achieved over 93% classification accuracy at 1 day of outgrowth among A549, H460, and H520, and reached 100% classification accuracy at 7 days of outgrowth. Additionally, the model achieved 100% classification accuracy at 4 days for patient-derived lung cancer cells. Although these cells are classified as Adenocarcinoma, their outgrowth patterns vary depending on their oncogene expressions (KRAS or EGFR).

Conclusions: These results demonstrate that the lightweight CNN architecture, operating locally on a laptop without network or cloud connectivity, can effectively create a machine learning-enabled model capable of accurately classifying lung cancer cell subtypes, including those derived from patients, based upon their outgrowth patterns in the presence of surrounding fibroblasts. This advancement underscores the potential of machine learning to enhance early lung cancer subtyping, offering promising avenues for improving treatment outcomes in advanced stage-patients.

Human immunodeficiency virus type 1 (HIV-1) vaccine immunogens capable of inducing broadly neutralizing antibodies (bNAbs) remain obscure. HIV-1 evades immune responses through enormous diversity and hides its conserved vulnerable epitopes on the envelope glycoprotein (Env) by displaying an extensive immunodominant glycan shield. In elite HIV-1 viremic controllers, glycan-dependent bNAbs targeting conserved Env epitopes have been isolated and are utilized as vaccine design templates. However, immunological tolerance mechanisms limit the development of these antibodies in the general population. The well characterized bNAbs monoclonal variants frequently exhibit extensive levels of somatic hypermutation, a long third heavy chain complementary determining region, or a short third light chain complementarity determining region, and some exhibit poly-reactivity to autoantigens. This review elaborates on the obstacles to engaging and manipulating the Env glycoprotein as an effective immunogen and describes an alternative reverse vaccinology approach to develop a novel category of bNAb-epitope-derived non-cognate immunogens for HIV-1 vaccine design.