Search Results (508)

Micro-fragmented adipose tissue (MFAT) is a promising autologous therapy for knee osteoarthritis. To avoid repeated liposuction procedures for its clinical application, MFAT obtained from patients with knee osteoarthritis was stored at −80 °C in a tissue bank. This study describes the preparation, cryopreservation, thawing, and washing, as well as comprehensive analysis of cell populations in fresh and MFAT thawed after two years. Immunophenotyping of both fresh and thawed MFAT showed a significant presence of endothelial progenitors and pericytes in the stromal vascular fraction. Viability before (59.75%) and after freezing (55.73%) showed no significant difference. However, the average cell count per gram of MFAT was significantly reduced in thawed samples (3.00 × 10⁵) compared to fresh ones (5.64 × 10⁵), likely due to processing steps. Thawed MFAT samples showed increased CD73 expression on the CD31^highCD34^high subset of EP and SA-ASC, as well as increased expression of CD105 on EP, the CD31^lowCD34^low subset of EP, pericytes, and SA-ASC. Microbiological testing confirmed 100% sterility, and double washing efficiently removed DMSO, confirming sample safety. Histological analysis revealed healthy, uniformly shaped adipocytes with intact membranes. This approach allows accurate estimation of cell yield for intra-articular injection, ensuring delivery of the target cell number into the knee. Quality control analysis confirms that cryopreserved MFAT retains high cellular and structural integrity, supporting its safety and suitability for clinical application. Full article

Background/Objectives: Although the nanocomposite of poly(L-lactic acid) with graphene oxide (PLLA-GO) shows promise for tissue engineering, its specific bioactive interactions with diverse cell lineages during early tissue regeneration remain unclear. This study comprehensively investigated the in vitro multifaceted biocompatibility of PLLA-GO using human fibroblasts (FN1 cells), murine mesenchymal stem cells (mBMSCs), and human umbilical vein endothelial cells (HUVECs). Methods: Morphological analyses were performed using optical and scanning electron microscopy, while proliferation dynamics were assessed via CFSE staining. Cell cycle progression was evaluated using flow cytometry, mitochondrial activity was examined through TMRE staining, and inflammatory cytokine profiling was performed via Cytometric Bead Array (CBA). Results: PLLA-GO exhibited primary biocompatibility across all evaluated cell lines, characterized by efficient adhesion and proliferation. However, significant cell-type-dependent modulations were observed. The FN1 cells exhibited proliferative adaptation but induced accelerated scaffold degradation, as evidenced by a substantial increase in cellular debris (5.93% control vs. 34.38% PLLA-GO; p = 0.03). mBMSCs showed a transient initial proliferative response and a significant 21.66% increase in TNF-α production (179.67 pg/mL vs. 147.68 pg/mL in control; p = 0.03). HUVECs demonstrated heightened mitochondrial sensitivity, exhibiting a 32.19% reduction in mitochondrial electrical potential (97.07% control vs. 65.82% PLLA-GO; p ≤ 0.05), alongside reductions in pro-inflammatory cytokines TNF-α (8.73%) and IL-6 (12.47%). Conclusions: The PLLA-GO processing method is crucial for its properties and subsequent cellular interactions. Therefore, rigorous and specific preclinical evaluations—considering both cellular contexts and fabrication—are indispensable to ensure the safety and therapeutic potential of PLLA-GO in tissue engineering and regenerative medicine. Full article

Enterocytozoon bieneusi is one of the most common microsporidian parasites, primarily infecting the intestinal epithelial cells of a broad range of animal species, including humans. To date, no scientific reports have documented Enterocytozoon spp. in animal hosts in Romania. This study aimed to assess the occurrence and genetic characteristics of E. bieneusi in shelter dogs, as well as its potential public health relevance. Between December 2022 and May 2025, a total of 112 freshly voided diarrheal fecal samples were collected from dogs housed in a shelter near Timișoara Municipality, Romania. The samples were subjected to molecular analysis using a two-step nested polymerase chain reaction (PCR) targeting the internal transcribed spacer (ITS) region of the rRNA gene. The resulting sequences were deposited in GenBank^® and analyzed phylogenetically. PCR analysis revealed E. bieneusi DNA in 11 (9.8%) samples, identifying two genotypes, with PtEb IX (n = 10) as the dominant genotype and BEB4 (n = 1), which has zoonotic potential. A significant difference in prevalence was found between juvenile (23.1%) and adult (5.8%) dogs (p = 0.026). Phylogenetic analysis of the ITS sequences showed that the isolates clustered into two distinct clades alongside reference sequences from the GenBank^® database. This is the first report of E. bieneusi infection in animals in Romania, providing essential baseline data and highlighting the need for broader surveillance into its prevalence and genetic diversity in other potential hosts. These results reflect the prevalence and genetic diversity of E. bieneusi exclusively among symptomatic (diarrheic) dogs and should not be generalized to the broader shelter dog population. Full article

Chronobiotics represent a pharmacologically diverse group of substances, encompassing both experimental compounds and those utilized in clinical practice, which possess the capacity to modulate the parameters of circadian rhythms. These substances influence fluctuations in various physiological and biochemical processes, including the expression of core “clock” genes in model organisms and cell cultures, as well as the expression of clock-controlled genes. Despite their chemical heterogeneity, chronobiotics share the common ability to alter circadian dynamics. The concept of chronobiotic drugs has been recognized for over five decades, dating back to the discovery and detailed clinical characterization of the hormone melatonin. However, the field remains fragmented, lacking a unified classification system for these pharmacological agents. The current categorizations include natural chrononutrients, synthetic targeted circadian rhythm modulators, hypnotics, and chronobiotic hormones, yet no comprehensive repository of knowledge on chronobiotics exists. Addressing this gap, the development of the world’s first curated and continuously updated database of chronobiotic drugs—circadian rhythm modulators—accessible via the global Internet, represents a critical and timely objective for the fields of chronobiology, chronomedicine, and pharmacoinformatics/bioinformatics. The primary objective of this study is to construct a relational database, ChronobioticsDB, utilizing the Django framework and PostGreSQL as the database management system. The database will be accessible through a dedicated web interface and will be filled in with data on chronobiotics extracted and manually annotated from PubMed, Google Scholar, Scopus, and Web of Science articles. Each entry in the database will comprise a detailed compound card, featuring links to primary data sources, a molecular structure image, the compound’s chemical formula in machine-readable SMILES format, and its name according to IUPAC nomenclature. To enhance the depth and accuracy of the information, the database will be synchronized with external repositories such as ChemSpider, DrugBank, Chembl, ChEBI, Engage, UniProt, and PubChem. This integration will ensure the inclusion of up-to-date and comprehensive data on each chronobiotic. Furthermore, the biological and pharmacological relevance of the database will be augmented through synchronization with additional resources, including the FDA. In cases of overlapping data, compound cards will highlight the unique properties of each chronobiotic, thereby providing a robust and multifaceted resource for researchers and practitioners in the field. Full article

The impacts of backwater due to large dam construction on flow may lead to navigation or flood control problems in curved rivers. This study conducted flume experiments to investigate the effects of backwater on the velocity distribution characteristics of a 90-degree bend. The experimental results show that the backwater degree (η, defined as the ratio of flow depth under backwater to that under non-backwater conditions) has significant impacts on the three-dimensional velocity distribution in the bend. The depth-averaged velocities decrease with increasing backwater degree, and the deflection degrees of depth-averaged velocities are found to be highly related to the backwater degree and cross-sectional position. In this experimental setup, the mean cross-sectional velocity decreases by 67.2% as η increases from 1.00 to 3.64 for Q = 35 L/s; 63.7% as η increases from 1.00 to 3.26 for Q = 52 L/s; and 60.1% as η increases from 1.00 to 2.80 for Q = 52 L/s. The maximum values of transversal and vertical velocities near the riverbed gradually shift to the inner bank as the backwater degree increases at the 45° cross section. The center of the high transversal velocity area shifts about 0.1 m toward the inner bank as the backwater degree increases from 1.00 to 3.26 for Q = 52 L/s, which can reduce the erosion of the riverbed near the outer bank. In the current study, we also demonstrate that the growth and decay processes of secondary flow cells under backwater conditions are similar to those under non-backwater conditions. However, the scales and positions of the secondary flow cells change continuously with different backwater degrees. From the entrance to the exit of the bend, the secondary flow intensity first increases, and then decreases, with its maximum values occurring at the 45° cross section. The findings detailed in this manuscript provide insights for navigation channel design in reservoir backwater zones. Full article

The accumulation of senescent cells is a major contributor to aging and various age-related diseases, making developing senolytic compounds that are capable of clearing these cells an important area of research. However, progress has been hampered by the limited number of known senolytics and the incomplete understanding of their mechanisms. This study presents a powerful senolytic predictor built using phenotypic data and machine learning techniques to identify compounds with potential senolytic activity. A comprehensive training dataset consisting of 111 positive and 3951 negative compounds was curated from the literature. The dataset was used to train machine learning models, incorporating traditional molecular fingerprints, molecular descriptors, and MoLFormer molecular embeddings. By applying MoLFormer-based oversampling and testing different algorithms, it was found that the Support Vector Machine (SVM) and Multilayer Perceptron (MLP) models with MoLFormer embeddings exhibited the best performance, achieving Area Under the Curve (AUC) scores of 0.998 and 0.997, and F1 scores of 0.948 and 0.941, respectively. This senolytic predictor was then used to perform virtual screening of compounds from the DrugBank and TCMbank databases. In the DrugBank database, 98 structurally novel candidate compounds with potential senolytic activity were identified. For TCMbank, 714 potential senolytic compounds were predicted and 81 medicinal herbs with possible senolytic properties were identified. Moreover, pathway enrichment analysis revealed key targets and potential mechanisms underlying senolytic activity. In an experimental screening of predicted compounds, panaxatriol was found to exhibit senolytic activity on the etoposide-induced senescence of the IMR-90 cell line. Additionally, voclosporin was found to extend the lifespan of C. elegans more effectively than metformin, demonstrating the value of our model for drug repurposing. This study not only provides an efficient framework for discovering novel senolytic agents, but also highlights the predicted novel senolytic compounds and herbs as valuable starting points for future research into senolytic drug development. Full article

The fungus Alternaria alternata, which causes tobacco brown spot disease, poses a serious threat to the tobacco industry. Beneficial microorganisms and their secondary metabolites have emerged as a promising green strategy for disease management. This study recovered 16 endophytic bacterial strains from Mentha haplocalyx Briq., a therapeutic herb. The study revealed that strain B5, with an inhibition rate of 82.76%, exhibited the highest antifungal activity against A. alternata. This strain exhibited broad-spectrum antifungal activity, with inhibition rates ranging from 66.34% to 87.23%. Phylogenetic analysis of 16S rDNA and gyrA gene sequences identified it as Bacillus velezensis (GenBank: PV168970 and PV173738). Further characterization revealed that strain B5 can secrete cell wall-degrading enzymes, produce IAA, and synthesize siderophores. The growth of mycelium in A. alternata was greatly reduced by both the ethyl acetate extract and the filtered liquid from the sterile fermentation, resulting in marked morphological abnormalities. Multiple antifungal active substances were identified through liquid LC-MS analysis. Greenhouse experiments demonstrated that the B5 fermentation broth effectively suppressed the occurrence of tobacco brown spot disease, achieving a relative control efficacy of 60.66%, comparable to that of 10% difenoconazole water dispersible granule (WDG). Additionally, strain B5 enhances plant disease resistance by activating the activities of key defense enzymes. B. velezensis B5 serves as a safe alternative to chemical fungicides and is highly effective at controlling tobacco brown spot disease. Full article

Considering the taxonomic uncertainties of Neotropical deer species, as well as the threat status of many of them, new studies and strategies for their maintenance are urgently needed. Obtaining live cells is of great importance for the conservation of wild species in order to allow cytogenetic and molecular studies to be carried out and for the construction of genomic resource banks. In order to increase the genetic diversity stored in these banks, the possibility of collecting skin fragments from dead animals (e.g., run over, hunted, deaths related to disease or natural causes) becomes a valuable source and a last alternative for obtaining material from these individuals. However, the interval between the death of the animal and the collection of tissue can directly interfere with the quality of the sample obtained and it is therefore essential to identify the maximum time during which viable cells are still found. Thus, this study sought to establish a protocol for the collection, storage, cryopreservation, and cultivation of skin obtained postmortem from individuals of the species Subulo gouazoubira (gray brocket deer) and Mazama rufa (red brocket deer). The collection of tissue fragments at different postmortem intervals (0 h, 1 h, 2 h, 3 h, 4 h, 5 h, 6 h, 7 h, 8 h, 9 h, 10 h, and 11 h) was evaluated. The tissues were analyzed for fibroblast cell viability immediately after collection. Their ability to undergo cryopreservation was evaluated based on techniques that can be directly applied to samples obtained in the field and their subsequent thawing and success of cell cultures was performed in the laboratory. Regarding the genetic integrity of the cells, the number of metaphases was observed by the mitotic index. The cell viability presented by the samples always remained above 60%. It was possible to establish cell cultures even with the tissues obtained 11 h after the death of the individuals; however, they required twice as many days to reach bottle confluence compared to the cultures performed with the tissues obtained 0 h after the death of the individuals. The results suggest that the best rates of cell viability, time to reach confluence, and number of metaphases per cell (mitotic index) are found in skin fragments collected up to 5 h after the death of individuals when their carcasses are kept at room temperature. Full article

The existence of s-DAPK-1, an alternatively spliced variant of DAPK-1, adds complexity to our understanding of the proteins involved in the regulation of cell survival, apoptosis, and autophagy. DAPK-1 has been implicated in the regulation of these processes; however, it remains unclear whether s-DAPK-1 also plays a similar role or a separate function; thus, determining its involvement in these processes is challenging due to the limited understanding of its regulation, interacting partners, function, and three-dimensional (3D) structure. Hence, this study was aimed at (1) understanding the regulation of s-DAPK-1 by predicting its microRNA targets, (2) predicting the 3D structure of s-DAPK-1, (3) its physicochemical and thermodynamic properties, (4) its interacting partners, and (5) molecular functions using computational methods. To achieve this aim, various bioinformatics tools and in silico webservers, such as ProteinPrompt, ProtParam, ProtScale, ScooP, Hawkdock, Phyre2, I-TASSER, PSIPRED, SAVES, and PROCHECK, along with user-friendly databases, such as NCBI, TarBase, and Protein Data Bank (PDB), were employed. For miRNA prediction, we used TarBase, and identified the specific microRNAs targeting s-DAPK-1. Furthermore, the Phyre2 database demonstrated that s-DAPK-1 possesses 40% alpha helices and 4% beta strands, forming a stable 3D structure. Additionally, s-DAPK-1 demonstrated stability to withstand high temperatures, suggesting that it is a thermostable protein. Moreover, s-DAPK-1 was found to interact with a variety of proteins involved in tumor progression and gene regulation, including a prion protein and histone H2B type 2-E (H2B2E). This suggests that s-DAPK-1 may perform diverse molecular functions such as regulation of metabolic processes, nucleic acid binding, and mRNA splicing by interacting with different proteins. Full article

Background: The extracellular matrix (ECM), primarily composed of collagen and elastin synthesized by dermal fibroblasts, is critical for mesenchymal tissue integrity. Fibroblast phenotypes vary significantly with the anatomical location and developmental stage. Fetal skin, particularly prior to 14 weeks of gestation, exhibits a simplified structure compared to adult skin, characterized by a thin, loose dermal matrix and a single-layered epithelium. Objectives: This study aimed to characterize and functionally compare homogenous progenitor fetal fibroblast (PFF) populations derived from 14-week-old fetal skin with fibroblasts isolated from adult burn patients. Methods: We evaluated the proliferative capacity, collagen synthesis, and differentiation potential (adipogenesis and osteogenesis) of PFF and adult burn patient fibroblasts. Furthermore, we assessed their ability to support skin regeneration using a de-epidermized dermis (DED) model seeded with both PFF and patient-derived keratinocytes. The stability of PFF characteristics was monitored across multiple passages (P5–P12). Results: PFF demonstrated a 2–4-fold increase in proliferation rate and a 30–50% enhancement in collagen production in vitro compared to adult fibroblasts. Notably, PFF exhibited a consistent lack of adipogenic and osteogenic differentiation, an attribute distinct from adult fibroblasts. In the DED model, PFF, even at a low fibroblast-to-keratinocyte ratio (1:5), effectively facilitated the formation of well-organized skin structures, including rete ridges, surpassing the performance of adult fibroblasts and adipose-derived cells. These properties remained stable over multiple passages. Conclusions: The unique attributes of PFF, likely attributable to the simplified microenvironment (i.e., collagen organization) of developing fetal tissue, positions them as a promising source for cell-based therapies. Their inherent high collagen synthesis capacity is particularly advantageous for wound healing applications. Consequently, PFF represent a consistent and readily available resource for developing “off-the-freezer” cutaneous cell therapies, potentially enabling accelerated and improved treatment of severe burn injuries. Full article

Background and Objectives: Malaria is a disease that can result in a variety of complications. Diagnosis is carried out by an optical microscope and depends on operator experience. The use of artificial intelligence to identify morphological patterns in erythrocytes would improve our diagnostic capability. The object of this study was therefore to establish computer viewing models able to classify blood cells infected with Plasmodium spp. to support malaria diagnosis by optical microscope. Materials and Methods: A total of 27,558 images of human blood sample extensions were obtained from a public data bank for analysis; half were of parasite-infected red cells (n = 13,779), and the other half were of uninfected erythrocytes (n = 13,779). Six models (five machine learning algorithms and one pre-trained for a convolutional neural network) were assessed, and the performance of each was measured using metrics like accuracy (A), precision (P), recall, F1 score, and area under the curve (AUC). Results: The model with the best performance was VGG-19, with an AUC of 98%, accuracy of 93%, precision of 92%, recall of 94%, and F1 score of 93%. Conclusions: Based on the results, we propose a convolutional neural network model (VGG-19) for malaria diagnosis that can be applied in low-complexity laboratories thanks to its ease of implementation and high predictive performance. Full article

Bacillus cereus poses a persistent challenge for human milk banks (HMBs) due to its ability to survive Holder pasteurization (HoP; 62.5 °C for 30 min). To ensure neonatal safety, any milk found to be contaminated post-HoP must be discarded, which impacts milk supply and adds to the operational demands of HMBs. In this study, we analyzed 688 B. cereus isolates from human milk (pre- and post-HoP), as well as from patient and environmental sources, to investigate human milk contamination by B. cereus at a Canadian HMB. Despite the limited temporal and geographic scope of the collection, the isolates exhibited remarkable genomic diversity, comparable to global B. cereus collections. Phylogenetic analysis at the core genome level revealed no clear clustering by isolate source, suggesting multifactorial pathways of B. cereus contamination. Isolates surviving HoP displayed gene variants linked to sporulation and cell wall integrity, suggesting a potential basis for HoP tolerance. Our findings emphasize that while genomic analyses offer major valuable insights, they alone are insufficient to address the complexities of B. cereus contamination in HMBs. Addressing this challenge will require combining genomic tools with robust monitoring systems, improved human milk-handling protocols, and pasteurization strategies better-suited to countering B. cereus resilience. Full article

The human CHCHD4 protein, which is a prototypical family member, carries a coiled–coil–helix–coiled–coil–helix motif that is stabilized by two disulfide bonds. Using its CPC sequence motif, CHCHD4 plays a key role in mitochondrial metabolism, cell survival, and response to stress conditions, controlling the mitochondrial import of diversified protein substrates that are specifically recognized through an interplay between covalent and non-covalent interactions. In the present review, we provide an updated and comprehensive analysis of CHCHD4 substrates controlled by its redox activities. A particular emphasis has been placed on the molecular and structural aspects of these partnerships. The literature survey has been integrated with the mining of structural databases reporting either experimental structures (Protein Data Bank) or structures predicted by AlphaFold, which provide protein three-dimensional models using machine learning-based approaches. In providing an updated view of the thirty-four CHCHD4 substrates that have been experimentally validated, our analyses highlight the notion that this protein can operate on a variety of structurally diversified substrates. Although in most cases, CHCHD4 plays a crucial role in the formation of disulfide bridges that stabilize helix–coil–helix motifs of its substrates, significant variations on this common theme are observed, especially for substrates that have been more recently identified. Full article

The rapid worldwide transmission of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to severe cases of hypoxia, acute respiratory distress syndrome, multi-organ failure, and ultimately death. Small-scale molecular interactions have been analyzed by focusing on several genes/single genes, providing important insights; however, genome-wide multi-omics comprehensive molecular interactions have not yet been well investigated with the exception of GWAS and eQTLm, both of which show genetic risks. From April of 2020 until now, we have created a Japan-wide system, initially named the Japan COVID-19 Task Force. This system has collected more than 6500 COVID-19 patients’ peripheral blood and as much associated clinical information as possible from a network of more than 120 hospitals. DNA, RNA, serum, and plasma were extracted and stored in this bank. This study unravels the interplay of inflammatory gene networks that induce different COVID-19 severity levels (mild, moderate, severe, and critical) by using multi-omics data from the Japan COVID-19 Task Force. We analyze RNA and protein expressions to estimate severity-specific inflammation networks that uncover the interplay between RNA and protein networks via ligand–receptor pairs. Our large-scale RNA/protein expression data analysis reveals that the atypical chemokine receptor 2 (ACKR2) acts as a key broker linking RNA and protein inflammation networks to induce COVID-19 critical severity. ACKR2 emerges in RNA and protein inflammation networks, showing active interplay in high-severity cases and weak interactions in mild cases. The results also show severity-specific molecular interactions between interleukin (IL), cytokine receptor activity, cell adhesion, and interactions involving the CC chemokine ligand (CCL) gene family and ACKR2. Full article

A large number of pineapple (Ananas comosus) fruits are discarded in China every year due to softening. However, the underlying molecular mechanism is still unknown. AcoPG3 (GenBank accession number: XM020243935), a pineapple gene of polygalacturonase, was found to be the major gene responsible for the softening of pineapple fruit. Fruit of AcoPG3-overexpressing tomato (Solanum lycopersicum var. Jingfan 101) begins to soften 9 days earlier than that transformed with a net vector. Fruit of AcoPG3-overexpressing pineapple (APG3-2) begins to soften 6 days earlier than that transformed with a net vector. Fruit of MPG3-1, a pineapple line in which AcoPG3 is mutated, begins to soften 31 days later than that transformed with a net vector. The sequence of polygalacturonase activities in fruit from the highest to the lowest was APG3-2, wild type, MPG3-1. The same sequences were also found in the liquid content of apoplast and the electrolyte leakage of pineapple pulp. The order of methyl-esterified pectin content in the pulp cell wall, from the highest to the lowest, was MPG3-1, wild type, and APG3-2. The same order was also observed for the contents of non-methyl-esterified homogalacturonan and rhamnogalacturonan-I in the pulp cell wall. The AcoPG3 mutation resulted in a decrease in polygalacturonase activity in pineapple fruit, decreasing the degradation of methyl-esterified pectin, non-methyl-esterified homogalacturonan, galactan and rhamnogalacturonan-I in the pulp cell wall. Fruit softening can be deferred, and the shelf life can be extended by mutating the AcoPG3 gene. Full article