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14 pages, 2426 KiB  
Article
Identifying Hub Genes and miRNAs Associated with Alzheimer’s Disease: A Bioinformatics Pathway to Novel Therapeutic Strategies
by Elisa Gascón, Ana Cristina Calvo, Nora Molina, Pilar Zaragoza and Rosario Osta
Biomolecules 2024, 14(12), 1641; https://doi.org/10.3390/biom14121641 (registering DOI) - 20 Dec 2024
Abstract
Alzheimer’s disease (AD) is a neurodegenerative disorder that mainly affects the elderly population. It is characterized by cognitive impairment and dementia due to abnormal levels of amyloid beta peptide (Aβ) and axonal Tau protein in the brain. However, the complex underlying mechanisms affecting [...] Read more.
Alzheimer’s disease (AD) is a neurodegenerative disorder that mainly affects the elderly population. It is characterized by cognitive impairment and dementia due to abnormal levels of amyloid beta peptide (Aβ) and axonal Tau protein in the brain. However, the complex underlying mechanisms affecting this disease are not yet known, and there is a lack of standardized biomarkers and therapeutic targets. Therefore, in this study, by means of bioinformatics analysis, AD-affected brain tissue was analyzed using the GSE138260 dataset, identifying 612 differentially expressed genes (DEGs). Functional analysis revealed 388 upregulated DEGs associated with sensory perception and 224 downregulated DEGs linked to the regulation and modulation of synaptic processes. Protein–protein interaction network analysis identified 20 hub genes. Furthermore, miRNA target gene networks revealed 1767 miRNAs linked to hub genes, among which hsa-mir-106a-5p, hsa-mir-17-5p, hsa-mir-26a-5p, hsa-mir-27a-3p and hsa-mir-34a-5p were the most relevant. This study presents novel biomarkers and therapeutic targets for AD by analyzing the information obtained with a comprehensive literature review, providing new potential targets to study their role in AD. Full article
(This article belongs to the Special Issue Pathogenesis and Neuropathology of Alzheimer's Disease)
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<p>Volcano plot of differentially expressed genes (DEG) of GSE138260 dataset (LOAD’s and healthy control samples). Red dots represent upregulated genes according to <span class="html-italic">p</span>-value &lt; 0.05 and |logFC| &gt; 0. Blue dots represent downregulated genes according to <span class="html-italic">p</span>-values &lt; 0.05 and |logFC| &lt; 0.</p>
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<p>Analysis of differentially expressed gene (DEG) networks. (<b>a</b>) MCODE-clustered subnetwork of upregulated DEGs. (<b>b</b>) MCODE-clustered subnetwork of downregulated DEGs.</p>
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<p>Enrichment analysis of MCODE-clustered subnetwork of upregulated DEGs by Metascape.</p>
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<p>Enrichment analysis of MCODE-clustered subnetwork of downregulated DEGs by Metascape.</p>
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<p>Hub genes identified by cytoHubba. (<b>a</b>) Hub genes of the PPI network of upregulated DEGs. (<b>b</b>) Hub genes of the PPI network of downregulated DEGs. The descending color from red to yellow represents decreasing interaction intensity between genes.</p>
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<p>High centrality filtered network of miRNAs predicted from hub genes (mRNA). The blue diamond represents the miRNAs, and the red circle represents the mRNA. The dashed lines represent the relationships between them.</p>
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26 pages, 1545 KiB  
Review
Natural Antimicrobial Peptides and Their Synthetic Analogues for Effective Oral Microflora Control and Oral Infection Treatment—The Role of Ceragenins in the Development of New Therapeutic Methods
by Michał Czarnowski, Urszula Wnorowska, Milena Łuckiewicz, Ewelina Dargiewicz, Jakub Spałek, Sławomir Okła, Beata Sawczuk, Paul B. Savage, Robert Bucki and Ewelina Piktel
Pharmaceuticals 2024, 17(12), 1725; https://doi.org/10.3390/ph17121725 - 20 Dec 2024
Abstract
Oral diseases, both acute and chronic, of infectious or non-infectious etiology, represent some of the most serious medical problems in dentistry. Data from the literature increasingly indicate that changes in the oral microbiome, and therefore, the overgrowing of pathological microflora, lead to a [...] Read more.
Oral diseases, both acute and chronic, of infectious or non-infectious etiology, represent some of the most serious medical problems in dentistry. Data from the literature increasingly indicate that changes in the oral microbiome, and therefore, the overgrowing of pathological microflora, lead to a variety of oral-localized medical conditions such as caries, gingivitis, and periodontitis. In recent years, compelling research has been devoted to the use of natural antimicrobial peptides as therapeutic agents in the possible treatment of oral diseases. This review focuses on the potential of ceragenins (CSAs), which are lipid analogs of natural antimicrobial peptides, as molecules for the development of new methods for the prevention and treatment of oral diseases. Studies to date indicate that ceragenins, with their spectrum of multidirectional biological activities, including antimicrobial, tissue regeneration-stimulating, anti-inflammatory, and immunomodulatory properties, are strong candidates for further development of oral formulations. However, many of the beneficial properties of ceragenins require confirmation in experimental conditions reproducing the oral environment to fully determine their application potential. Their transition to practical use also requires more advanced testing of these molecules in clinical trials, which have only been conducted in limited numbers to date. Full article
(This article belongs to the Section Natural Products)
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<p>The biological activities of ceragenins. Details on the molecular mechanisms of reported effects are described in more detail below.</p>
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<p>Potential applications of ceragenins in the treatment of oral diseases.</p>
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<p>The multifaceted activities of ceragenins that make them a favorable candidate for further development of highly efficient formulations for oral hygiene and as therapeutics against oral diseases.</p>
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23 pages, 8712 KiB  
Article
A Tachyplesin Antimicrobial Peptide from Theraphosidae Spiders with Potent Antifungal Activity Against Cryptococcus neoformans
by Brenda B. Michira, Yi Wang, James Mwangi, Kexin Wang, Demeke Asmamaw, Dawit Adisu Tadese, Jinai Gao, Mehwish Khalid, Qiu-Min Lu, Ren Lai and Juan Li
Microorganisms 2024, 12(12), 2648; https://doi.org/10.3390/microorganisms12122648 - 20 Dec 2024
Abstract
The venoms of Theraphosidae spiders have evolved into diverse natural pharmacopeias through selective pressures. Cryptococcus neoformans is a global health threat that frequently causes life-threatening meningitis and fungemia, particularly in immunocompromised patients. In this study, we identify a novel anti-C. neoformans peptide, [...] Read more.
The venoms of Theraphosidae spiders have evolved into diverse natural pharmacopeias through selective pressures. Cryptococcus neoformans is a global health threat that frequently causes life-threatening meningitis and fungemia, particularly in immunocompromised patients. In this study, we identify a novel anti-C. neoformans peptide, QS18 (QCFKVCFRKRCFTKCSRS), from the venom gland of China’s native spider species Chilobrachys liboensis by utilizing bioinformatic tools. QS18 shares over 50% sequence similarity with tachyplesin peptides, previously identified only in horseshoe crab hemocytes, expanding the known repertoire of the tachyplesin family to terrestrial arachnids. The oxidative folding of QS18 notably enhances its antifungal activity and stability, resulting in a minimum inhibitory concentration of 1.4 µM. The antimicrobial mechanism of QS18 involves cell membrane disruption. QS18 exhibits less than 5% hemolysis in human erythrocytes, indicating microbial selectivity and a favorable safety profile for therapeutic use. Furthermore, mouse model studies highlight QS18’s ability as an antifungal agent with notable anti-inflammatory activity. Our study demonstrates QS18 as both a promising template for spider venom peptide research and a novel candidate for the development of peptide antifungals. Full article
(This article belongs to the Special Issue Advances in Antimicrobial Peptides)
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<p>Sequence alignment and phylogenetic analysis for QS18: (<b>A</b>) The complete amino acid sequence of QS18. Color-coded regions represent the three typical sections of a toxin peptide sequence: blue for the signal peptide, red for the mature peptide (QS18), and green for the propeptide; (<b>B</b>) Sequence alignment utilizing Clustal W software (<a href="https://www.genome.jp/tools-bin/clustalw" target="_blank">https://www.genome.jp/tools-bin/clustalw</a>). The amino acid identity is represented in different color codes; (<b>C</b>) Phylogenetic analysis maximum likelihood tree generated using RAxML and visualized in the ITOL website. The branch length and bootstrap replications (branch reliability) are represented in black and blue numbers, respectively. The higher the branch length value, the farther the branch. Gomesin (P82358), an antimicrobial peptide from <span class="html-italic">Acanthoscurria gomesiana</span> [<a href="#B20-microorganisms-12-02648" class="html-bibr">20</a>]; gomesin-like peptide (A0A1D0BZI2), an antibacterial peptide from <span class="html-italic">Hadronyche infensa</span> [<a href="#B17-microorganisms-12-02648" class="html-bibr">17</a>]; Tachyplesin-2 (P14214), from <span class="html-italic">Tachypleus tridentatus</span> [<a href="#B39-microorganisms-12-02648" class="html-bibr">39</a>]; Tachyplesin-1 (P14213), from <span class="html-italic">Tachypleus tridentatus</span> [<a href="#B39-microorganisms-12-02648" class="html-bibr">39</a>,<a href="#B40-microorganisms-12-02648" class="html-bibr">40</a>]; Tachyplesin-1 (P69135) and Tachyplesin-3 (P18252) from <span class="html-italic">Tachypleus gigas</span> [<a href="#B41-microorganisms-12-02648" class="html-bibr">41</a>]; Phosphoinositide phospholipase C 3 (Q56W08), an enzyme involved in signal transduction from <span class="html-italic">Arabidopsis thaliana</span> [<a href="#B42-microorganisms-12-02648" class="html-bibr">42</a>]; the protein associated with UVRAG as autophagy enhancer (protein Rubicon-like) (A7E316.1), a regulator of autophagy from Bos taurus; and Polyphemusin-1 (P14215) and Polyphemusin-2 (P14216), AMPs from <span class="html-italic">Limulus polyphemus</span> [<a href="#B43-microorganisms-12-02648" class="html-bibr">43</a>]; (<b>D</b>) The venom gland of <span class="html-italic">Chilobrachys liboensis;</span> (<b>E</b>) A silhouette image of a horseshoe crab obtained from PhyloPic (<a href="https://www.phylopic.org/" target="_blank">https://www.phylopic.org/</a>); and (<b>F</b>) A photograph of the tarantula species <span class="html-italic">C. liboensis</span>.</p>
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<p>Mass spectrometry analysis: (<b>A</b>) Mass spectra of reduced linear QS18 (QS18red). The spectrum shows the mass-to-charge (m/z) ratio distribution, with the highest peak labeled. (<b>B</b>) Mass spectra of the oxidized QS18 (QS18). These data confirmed molecular mass and purity of the synthesized QS18 peptide before and after the oxidative folding process. Comparison with the linear peptide spectrum allowed the verification of successful folding and formation of disulfide bonds, as indicated by the decrease in molecular mass.</p>
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<p>Structural analysis of QS18: (<b>A</b>) Helical wheel projections showing QS18’s amphipathic nature. The arrow indicates a hydrophobic moment. Indicated in yellow are the hydrophobic residues, whereas the purple color shows serine and threonine, and blue and pink show the basic residues and glutamine, respectively. C and N are the C- and N-termini represented in red. (<b>B</b>) The secondary α-helix structure of QS18 predicted using PEP-FOLD3 software. (<b>C</b>) The primary structure of the linear QS18 generated by pepSMI software (<a href="https://www.novoprolabs.com/tools/convert-peptide-to-smiles-string" target="_blank">https://www.novoprolabs.com/tools/convert-peptide-to-smiles-string</a>). The structure shows amino acids’ sequence connected by peptide bonds. (<b>D</b>,<b>E</b>) Circular dichroism spectra displaying the secondary helical structure of QS18 and QS18red, respectively, in membrane-mimicking and aqueous solutions: trifluoroethanol (TFE) and sodium dodecyl-sulfate (SDS). [θ]M represents the mean residue ellipticity. Results are expressed as the mean ± standard deviation (SD) of three technical replicates.</p>
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<p>Proteolytic resistance: (<b>A</b>) SDS-PAGE evaluation of the proteolytic stability of QS18, QS18red, LL37, and colistin following incubation with chymotrypsin or trypsin from 0 to 12 h. Besides colistin, LL37 human cathelicidin AMP served as a positive control due to its known susceptibility to serine proteases. L represents the protein ladder, and S represents peptide samples without enzymes. (<b>B</b>) The effect of proteolytic enzymes on the antifungal effect of QS18. Two hours post-incubation, QS18 appeared to maintain its antimicrobial property in chymotrypsin, which corresponds with the SDS-PAGE analysis results, displaying resistance even up to 12 h. Data represent the mean ± SD of three independent experiments, each performed in technical triplicates.</p>
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<p>Antifungal activity of QS18 against <span class="html-italic">C. neoformans</span> BNCC225501 cells: (<b>A</b>) Time-dependent fungicidal activity. QS18 exhibits potent effects with complete growth inhibition at 10× the MIC within 60 min and at 5× the MIC after 120 min. (<b>B</b>) Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) micrographs showing the effect of QS18 treatment at 1× and 10× the MIC. SEM and TEM scale bars are 2 µm and 200 µm, respectively. The arrows highlight key areas of membrane disruption, including visible perforations, thus providing visual evidence of QS18’s membrane-targeting mechanism. (<b>C</b>) The fluorescence intensity of DiSC3(5) in <span class="html-italic">C. neoformans</span> cell suspension. Abbreviations: FCZ represents fluconazole, and AMB represents amphotericin B. The results are expressed as the mean ± SD of three independent experiments, each conducted in technical triplicates.</p>
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<p>Antibiofilm activity of QS18 against <span class="html-italic">C. neoformans</span> BNCC225501 cells: (<b>A</b>) Dose–response inhibition of biofilm formation in 96-well plates. (<b>B</b>) Dose–response eradication of preformed biofilms in 96-well plates. Data expressed as mean OD600 values of solubilized crystal violet dye ± SEM. (<b>C</b>) Quantification of the red (PI) and green (FDA) fluorescence. The percentage area of fluorescence is expressed relative to the negative control (NC). (<b>D</b>) Two-photon laser microscopy analysis of the peptide’s effect on <span class="html-italic">C. neoformans</span> biofilms: Propidium iodide (PI) and Fluorescein diacetate (FDA) dyes were used to stain the dead and live cells, respectively. Imaging of the differential interference contrast (DIC) under white light was also assessed. Abbreviations: FCZ, fluconazole; and AMB, amphotericin B. Treated <span class="html-italic">C. neoformans</span> populations demonstrated a higher proportion of dead cells (red fluorescence) compared to untreated cells (green fluorescence). This color intensity shift indicates significant antibiofilm activity in the presence of QS18. These observations further corroborate the membrane-targeting mechanism of QS18. Scale bar, 50 µm. The data are presented as the mean ± SEM of three independent experiments. A one-way ANOVA was conducted for statistical analysis. Statistical significance: *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>QS18 treatment of mice infected with <span class="html-italic">C. neoformans</span>: (<b>A</b>) Evaluation of the number of colony-forming units (CFUs) (<span class="html-italic">C. neoformans</span>-8 × 10<sup>6</sup> CFU/mouse, n = 4) per gram of tissue and per mL in blood. Results demonstrate a substantial dose-dependent decrease in fungal burden in treated groups across all examined tissues and blood. (<b>B</b>) Histopathological analysis of inflammatory responses. Tissue sections from the lung, liver, spleen and kidney were subjected to hematoxylin and eosin (H&amp;E) staining. Compared to untreated negative controls (NC), QS18-treated sections exhibited dose-dependent reduction in infiltrating inflammatory cells and overall architectural disruption. The 4 mg/kg QS18-treated group shows near-normal tissue morphology, indicating the significant alleviation of infection-induced inflammation. Scale bar, 50 µm. Results are expressed as the mean ± SD of four biological replicates per dose group. A one-way ANOVA was performed. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Quantification of pro-inflammatory cytokines: (<b>A</b>–<b>D</b>) Plasma was analyzed for concentrations of interleukin--1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and monocyte chemoattractant protein-1 (MCP-1), respectively, using the enzyme-linked immunosorbent assay (ELISA). QS18-treated groups demonstrated dose-dependent reductions in these inflammatory markers compared to the untreated group. Data represent the mean ± SD of four biological replicates per dose group. Statistical significance was assessed using one-way ANOVA; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p>
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22 pages, 1150 KiB  
Review
Endosomal Escape and Nuclear Localization: Critical Barriers for Therapeutic Nucleic Acids
by Randall Allen and Toshifumi Yokota
Molecules 2024, 29(24), 5997; https://doi.org/10.3390/molecules29245997 - 19 Dec 2024
Abstract
Therapeutic nucleic acids (TNAs) including antisense oligonucleotides (ASOs) and small interfering RNA (siRNA) have emerged as promising treatment strategies for a wide variety of diseases, offering the potential to modulate gene expression with a high degree of specificity. These small, synthetic nucleic acid-like [...] Read more.
Therapeutic nucleic acids (TNAs) including antisense oligonucleotides (ASOs) and small interfering RNA (siRNA) have emerged as promising treatment strategies for a wide variety of diseases, offering the potential to modulate gene expression with a high degree of specificity. These small, synthetic nucleic acid-like molecules provide unique advantages over traditional pharmacological agents, including the ability to target previously “undruggable” genes. Despite this promise, several biological barriers severely limit their clinical efficacy. Upon administration, TNAs primarily enter cells through endocytosis, becoming trapped inside membrane-bound vesicles known as endosomes. Studies estimate that only 1–2% of TNAs successfully escape endosomal compartments to reach the cytosol, and in some cases the nucleus, where they bind target mRNA and exert their therapeutic effect. Endosomal entrapment and inefficient nuclear localization are therefore critical bottlenecks in the therapeutic application of TNAs. This review explores the current understanding of TNA endosomal escape and nuclear transport along with strategies aimed at overcoming these challenges, including the use of endosomal escape agents, peptide-TNA conjugates, non-viral delivery vehicles, and nuclear localization signals. By improving both endosomal escape and nuclear localization, significant advances in TNA-based therapeutics can be realized, ultimately expanding their clinical utility. Full article
(This article belongs to the Section Chemical Biology)
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<p>Uptake and intracellular trafficking of TNAs. Following endocytosis, TNAs become encapsulated inside early endosomes (EE) which undergo maturation to multivesicular bodies (MVBs) and late endosomes (LEs). Non-productive pathways (red) do not permit TNAs to reach their intracellular targets. Such pathways include recycling to the plasma membrane, retention in depot endosomes, or enzymatic degradation in lysosomes. Productive pathways (green) allow the successful escape of TNAs into the cytosol to interact with mRNA targets, or eventually the nucleus when targeting pre-mRNA. A small portion (1–2%) of freely delivery TNAs escape endosomes during trafficking primarily from MVBs and LEs.</p>
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<p>Traditional endosomal escape strategies. (<b>A</b>) Cationic amphiphilic small molecules (CADs) such as chloroquine enter endosomes buffering changes in pH. The resulting proton-sponge effect induces osmotic swelling and endosomal rupture, allowing TNAs to escape. Other small molecules may directly interact with endosomes causing membrane destabilization. (<b>B</b>) Peptide-mediated endosomal escape can be facilitated by biomimetic or cell-penetrating peptides. Interaction between cationic peptides and the anionic endosomal membrane causes fusion, membrane destabilization, or pore formation. (<b>C</b>) Non-viral delivery vehicle-mediated endosomal escape can be achieved using lipid nanoparticles. Cationic or ionizable lipids facilitate fusion with the endosomal membrane, allowing TNA release.</p>
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<p>Alternative strategies to the endosomal escape problem. (1) Direct cytosolic entry of TNAs which can be facilitated by peptide or nanoparticle-mediated delivery. Avoiding endocytosis and subsequent endosomal entrapment allows free translocation to the nucleus. (2) Inhibition of endosomal recycling can be accomplished through small molecules such as NP3.47. Preventing the exocytosis of internalized TNAs provides increased potential for endosomal escape events. (3) Inhibition of endo-Golgi retrograde transport with small molecules such as Retro-1. The mechanism of action remains unclear but may increase the retention of TNAs in endosomes, increasing the probability for escape. (4) Inhibition of endo-lysosomal fusion with molecules such as SH-BC-893. Preventing the degradation of TNAs entrapped in endosomes increases their cytosolic quantity, improving treatment efficacy.</p>
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<p>Mechanism nuclear localization signal (NLS) internalization. TNA-NLS peptide conjugates interact with importin-α and β in the cytosol which facilitate active transport through the nuclear pore complex (NPC). Following nuclear entry, the binding of RanGTP causes the dissociation of the complex. The free TNA-NLS is now capable of binding to target pre-mRNA in the nucleus.</p>
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21 pages, 5449 KiB  
Article
Rational Design of an Epidermal Growth Factor Receptor Vaccine: Immunogenicity and Antitumor Research
by Yifei Liu, Zehui Liu and Zhongliang Zheng
Biomolecules 2024, 14(12), 1620; https://doi.org/10.3390/biom14121620 - 18 Dec 2024
Viewed by 383
Abstract
The epidermal growth factor receptor (EGFR) is frequently overexpressed in a variety of human epithelial tumors, and its aberrant activation plays a pivotal role in promoting tumor growth, invasion, and metastasis. The clinically approved passive EGFR-related therapies have numerous limitations. Seven EGFR-ECD epitope [...] Read more.
The epidermal growth factor receptor (EGFR) is frequently overexpressed in a variety of human epithelial tumors, and its aberrant activation plays a pivotal role in promoting tumor growth, invasion, and metastasis. The clinically approved passive EGFR-related therapies have numerous limitations. Seven EGFR-ECD epitope peptides (EG1-7) were selected through bioinformatics epitope prediction tools including NetMHCpan-4.1, NetMHCIIpan-3.2, and IEDB Consensus (v2.18 and v2.22) and fused to the translocation domain of diphtheria toxin (DTT). The A549 tumor model was successfully established in a murine mouse model. The vaccine was formulated by combining the adjuvants Alum and CpG and subsequently assessed for its immunogenicity and anti-tumor efficacy. DTT-EG (3;5;6;7) vaccines elicited specific humoral and cellular immune responses and effectively suppressed tumor growth in both prophylactic and therapeutic mouse tumor models. The selected epitopes EG3 (HGAVRFSNNPALCNV145-159), EG5 (KDSLSINATNIKHFK346-360), EG6 (VKEITGFLLIQAWPE398-412), and EG7 (LCYANTINWKKLFGT469-483) were incorporated into vaccines for active immunization, representing a promising strategy for the treatment of tumors with overexpressed epidermal growth factor receptor (EGFR). The vaccine design and fusion method employed in this study demonstrate a viable approach toward the development of cancer vaccines. Full article
(This article belongs to the Section Molecular Biology)
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<p>Immunization with DTT-EG vaccines in combination with tumor cell injection protocol. (<b>A</b>) Prophylactic tumor model: tumor cell injection and vaccine immunization protocol (mouse diagram by <a href="http://medpeer.cn" target="_blank">medpeer.cn</a>) and (<b>B</b>) therapeutic tumor model: tumor cell injection and vaccine immunization protocol (mouse diagram by <a href="http://medpeer.cn" target="_blank">medpeer.cn</a> (accessed on 9 June 2024)).</p>
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<p>The predicted epitope EG in EGFR-ECD is demonstrated, along with the design and expression purification of DTT-EG utilizing DTT as a vector. (<b>A</b>) Displaying the EG epitope within EGFR-ECD (EGFR PDB id:3njp): EG1 is represented by a yellow sequence, EG2 by a red sequence, EG3 by a green sequence, EG4 by a blue and orange sequence, EG5 by an orange and purple sequence, EG6 by a cyan sequence, and EG7 by a pink sequence. (<b>B</b>) Design of DTT-EG tandem recombinant protein. DTT (202–373) denotes the amino acid fragment spanning from 202 to 373 of the DTT protein. The epitope prediction tool identified seven human-specific epitope peptides in the form of EG1, EG2, EG3, EG4, and E5G5G6G7 consisting of 15 amino acid residues each. GS represents the GS-linker sequence (GGTGGTGGTGGTAGTGGTGGTGGTGGTAGT). (<b>C</b>) Analysis of purified recombinant protein using 12% SDS-PAGE (M: Marker; A: DTT-EG1; B: DTT-EG2; C: DTT-EG3; D: DTT-EG4; E: DTT-EG5; F: DTT-EG6; G: DTT-EG7; H: DTT).</p>
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<p>Serum antibodies were detected using enzyme-linked immunosorbent assay (ELISA) following immunization of mice with the DTT-EG tandem recombinant protein. (Significance levels were denoted as ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, while “ns” indicated no significant difference). (<b>A</b>) Schematic representation of the immunization protocol for mice (mouse diagram by <a href="http://medpeer.cn" target="_blank">medpeer.cn</a> (accessed on 9 June 2024)). (<b>B</b>) ELISA analysis was conducted on the serum of immunized mice, with the coated proteins being DTT or EGFR. (<b>C</b>) The titer of antibodies against EGFR in the mouse serum following vaccination was determined by ELISA.</p>
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<p>The splenic lymphocytes of immunized mice were tested for cell proliferation, toxicity, and interferon-gamma release, and the spleens were tested for CD4 and CD8 immunohistochemistry. (Significance levels were denoted as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, while “ns” indicated no significant difference). (<b>A</b>) Schematic representation of the immunization protocol for mice (mouse diagram by <a href="http://medpeer.cn" target="_blank">medpeer.cn</a> (accessed on 9 June 2024)). (<b>B</b>) Cell proliferation detection experiment by CCK-8 method. (<b>C</b>) Cell cytotoxicity detection experiment by lactate dehydrogenase method. (<b>D</b>) Detection of IFN-γ release by ELISA method. (<b>E</b>) The spleen of immunized mice was stained by immunohistochemistry with anti-CD4 specific antibody. (<b>F</b>) The spleen of immunized mice was stained by immunohistochemistry with anti-CD8 specific antibody. (<b>G</b>) CD4+ T and CD8+ T-cell density was quantified using ImageJ.</p>
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<p>Antitumor effects of the DTT-EG vaccine in a prophylactic and therapeutic mouse A549 tumor model. (Significance levels were denoted as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001, while “ns” indicated no significant difference). (<b>A</b>) prophylactic tumor model tumor growth curve, (<b>B</b>) prophylactic tumor model tumor weight, (<b>C</b>) therapeutic tumor model tumor growth curve, and (<b>D</b>) therapeutic tumor model tumor weight.</p>
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<p>The DTT-EG vaccine modulates the infiltration of CD8+ T cells and induces necrosis within the intratumoral tissue. (Significance levels were denoted as ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001, while “ns” indicated no significant difference). (<b>A</b>) Tumor tissues underwent immunohistochemical staining using an anti-CD4 specific antibody. (<b>B</b>) Tumor tissues underwent immunohistochemical staining using an anti-CD8 specific antibody. (<b>C</b>) CD4+ T and CD8+ T cell density was quantified using ImageJ. (<b>D</b>) Revealing the histopathological features of tumor tissue through hematoxylin and eosin (H&amp;E) staining.</p>
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14 pages, 1523 KiB  
Article
Retrospective Analysis of HLA Class II-Restricted Neoantigen Peptide-Pulsed Dendritic Cell Vaccine for Breast Cancer
by Takafumi Morisaki, Makoto Kubo, Shinji Morisaki, Masayo Umebayashi, Hiroto Tanaka, Norihiro Koya, Shinichiro Nakagawa, Kenta Tsujimura, Sachiko Yoshimura, Kazuma Kiyotani, Yusuke Nakamura, Masafumi Nakamura and Takashi Morisaki
Cancers 2024, 16(24), 4204; https://doi.org/10.3390/cancers16244204 - 17 Dec 2024
Viewed by 263
Abstract
Background/Objectives: Neoantigens have attracted attention as ideal therapeutic targets for anti-tumour immunotherapy because the T cells that respond to neoantigens are not affected by central immune tolerance. Recent findings have revealed that the activation of CD4-positive T cells plays a central role [...] Read more.
Background/Objectives: Neoantigens have attracted attention as ideal therapeutic targets for anti-tumour immunotherapy because the T cells that respond to neoantigens are not affected by central immune tolerance. Recent findings have revealed that the activation of CD4-positive T cells plays a central role in antitumor immunity, and thus targeting human leukocyte antigen (HLA) class II-restricted neoantigens, which are targets of CD4-positive T cells, is of significance. However, there are very few detailed reports of neoantigen vaccine therapies that use an HLA class II-restricted long peptide. In the present study, we retrospectively analysed the ability of HLA class II-restricted neoantigen-pulsed dendritic cell vaccines to induce immune response in five breast cancer patients. Methods: We performed whole exome and RNA sequencing of breast cancer tissues and neoantigen prediction using an in silico pipeline. We then administered dendritic cells pulsed with synthesized an HLA class II-restricted long peptide containing an epitope with high affinity to HLA class I in the lymph node. Results: ELISPOT analysis confirmed that a T-cell response specific for the HLA class II-restricted neoantigen was induced in all cases. TCR repertoire analysis of peripheral blood mononuclear cells before and after treatment in three patients showed increases of specific T-cell clones in two of the three patients. Importantly, no recurrence was observed in all patients. Conclusions: Our analysis demonstrated the immunological efficacy of the HLA class II-restricted neoantigen peptide dendritic cell vaccine against breast cancer and provides useful information for the development of neoantigen vaccine therapy for breast cancer. Full article
(This article belongs to the Collection Cancers Precision Immunotherapy)
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<p>Protocol of intranodal neoantigen peptide-pulsed dendritic cell (Neo-P DC) vaccine therapy. (<b>a</b>) Tumour sampling (formalin-fixed paraffin-embedded tissue), genetic testing for neoantigen prediction using whole exome sequencing (WES) by next-generation sequencing (NGS) combined with in silico analysis, leukapheresis, and the synthesis of predicted neoantigens were performed. (<b>b</b>) For vaccine treatment, monocyte-derived DCs were cultured with neoantigen peptides and administered to patients via ultrasound (US)-guided intranodal injection. After the administration of six cycles of Neo-P DC at 2-week intervals, IFN-γ ELISpot analysis was performed. Peripheral blood mononuclear cell (PBMCs) and plasma obtained by leukapheresis and cryopreserved before and after treatment were used for analyses. T-cell receptor (TCR) analyses were performed for three patients.</p>
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<p>Immune responses of peripheral blood lymphocytes to neoantigen peptides after Neo-P DC vaccine treatment. (<b>a</b>) IFN-γ ELISpot responses to neoantigen peptides in peripheral blood lymphocytes from each patient after six cycles of vaccine treatment. The intensity and size of each spot were multiplied, and values of all spots were summed; the results were divided by 1000 to obtain the activity values. All measurements were performed in duplicate. Data are represented as mean ± SD. I and II indicate HLA class I or II neoantigen peptide derived from the mutated genes, respectively. Ly, lymphocytes; mDC+Ly, mature dendritic cells + lymphocytes; PBMC, peripheral blood mononuclear cell. The dotted blue horizontal line indicates the control level; the control is mDC + Ly in BC1, BC2, and BC3 and PBMC in BC4 and BC5. Each peptide is added to the control (PBMC or mDc+Ly). The red bars indicate positive activity. (<b>b</b>) Number of neoantigen peptides that evoked a positive or negative reaction in peripheral lymphocytes after Neo-P DC vaccine treatment.</p>
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<p>Immune responses of peripheral CD4-positive and CD8-positive T cells to neoantigen peptides after Neo-P DC vaccine treatment. IFN-γ ELISpot responses to the HLA class II-restricted mutant long peptide (TTN-II) in peripheral blood lymphocytes from each patient after six cycles of vaccine treatment. Spot activity values were calculated. All measurements were performed in triplicate. Data are represented as mean ± SD. In the evaluation of both CD4-positive and CD8-positive T cells, 3.5 × 10<sup>4</sup> cells each were added to each well.</p>
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<p>TCR repertoire analysis before and after Neo-P DC vaccine treatment. TCRβ repertoire analysis was performed in three patients from samples before and after vaccine treatment. CDR3β clonotypes accounting for more than 0.5% are shown in the pie chart. DI: diversity index.</p>
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32 pages, 9784 KiB  
Article
Discovery of Non-Peptide GLP-1 Positive Allosteric Modulators from Natural Products: Virtual Screening, Molecular Dynamics, ADMET Profiling, Repurposing, and Chemical Scaffolds Identification
by Mohamed S. Gomaa, Mansour S. Alturki, Nada Tawfeeq, Dania A. Hussein, Faheem H. Pottoo, Abdulaziz H. Al Khzem, Mohammad Sarafroz and Samar Abubshait
Pharmaceutics 2024, 16(12), 1607; https://doi.org/10.3390/pharmaceutics16121607 - 17 Dec 2024
Viewed by 236
Abstract
Background/Objectives: Glucagon-like peptide-1 (GLP-1) receptor is currently one of the most explored targets exploited for the management of diabetes and obesity, with many aspects of its mechanisms behind cardiovascular protection yet to be fully elucidated. Research dedicated towards the development of oral GLP-1 [...] Read more.
Background/Objectives: Glucagon-like peptide-1 (GLP-1) receptor is currently one of the most explored targets exploited for the management of diabetes and obesity, with many aspects of its mechanisms behind cardiovascular protection yet to be fully elucidated. Research dedicated towards the development of oral GLP-1 therapy and non-peptide ligands with broader clinical applications is crucial towards unveiling the full therapeutic capacity of this potent class of medicines. Methods: This study describes the virtual screening of a natural product database consisting of 695,133 compounds for positive GLP-1 allosteric modulation. The database, obtained from the Coconut website, was filtered according to a set of physicochemical descriptors, then was shape screened against the crystal ligand conformation. This filtered database consisting of 26,325 compounds was used for virtual screening against the GLP-1 allosteric site. Results: The results identified ten best hits with the XP score ranging from −9.6 to −7.6 and MM-GBSA scores ranging from −50.8 to −32.4 and another 58 hits from docked pose filter and a second round of XP docking and MM-GBSA calculation followed by molecular dynamics. The analysis of results identified hits from various natural products (NPs) classes, to whom attributed antidiabetic and anti-obesity effects have been previously reported. The results also pointed to β-lactam antibiotics that may be evaluated in drug repurposing studies for off-target effects. The calculated ADMET properties for those hits revealed suitable profiles for further development in terms of bioavailability and toxicity. Conclusions: The current study identified several NPs as potential GLP-1 positive allosteric modulators and revealed common structural scaffolds including peptidomimetics, lactams, coumarins, and sulfonamides with peptidomimetics being the most prominent especially in indole and coumarin cores. Full article
(This article belongs to the Special Issue Computer-Aided Development: Recent Advances and Expectations)
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<p>Filtration protocol for the Coconut natural products database.</p>
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<p>Chemical structure of GLP-1 co-crystallized ligands positive allosteric modulator used in the shape screening.</p>
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<p>Hit identification protocol.</p>
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<p>Surface representation of the overlay of the top 10 hits (magenta sticks) and the crystal ligand (red stick) in GLP-1 allosteric site (PDB ID: 6VCB). GLP-1 receptor is represented in gray surface and GLP-1 peptide in green surface.</p>
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<p>(<b>a</b>) Three-dimensional representation of the binding interactions between hit <b>1</b> and GLP-1 receptor allosteric site and GLP-1 peptide (PDB ID: 6VCB). Ligand atoms are shown as sticks (carbon atoms colored in magenta) and the key residues are shown as sticks (carbon atoms colored in green). Potential electrostatic interactions are represented as yellow dotted lines and are measured in Angstrom. (<b>b</b>) Two-dimensional ligand–protein binding interactions between hit <b>1</b> and GLP-1 receptor allosteric site and GLP-1 peptide (PDB ID: 6VCB). H bond is represented as a purple arrow and salt bridge as a blue line.</p>
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<p>(<b>a</b>) Three-dimensional representation of the binding interactions between hit <b>12</b> and GLP-1 receptor allosteric site and GLP-1 peptide (PDB ID: 6VCB). Ligand atoms are shown as sticks (carbon atoms colored in magenta) and the key residues are shown as sticks (carbon atoms colored in green). Potential electrostatic interactions are represented as yellow dotted lines and are measured in Angstrom. (<b>b</b>) Two-dimensional ligand–protein binding interactions between hit <b>12</b> and GLP-1 receptor allosteric site and GLP-1 peptide (PDB ID: 6VCB). H bond is represented as a purple arrow, salt bridge as a blue line, and π-π stacking as a green line.</p>
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<p>(<b>a</b>) Three-dimensional representation of the binding interactions between hit <b>44</b> (Ampicillin) and GLP-1 receptor allosteric site and GLP-1 peptide (PDB ID: 6VCB). Ligand atoms are shown as sticks (carbon atoms colored in magenta) and the key residues are shown as sticks (carbon atoms colored in green). Potential electrostatic interactions are represented as yellow dotted lines and are measured in Angstrom. (<b>b</b>) Two-dimensional ligand–protein binding interactions between hit <b>44</b> (Ampicillin) and GLP-1 receptor allosteric site and GLP-1 peptide (PDB ID: 6VCB). H bond is represented as a purple arrow, and salt bridge as a blue line.</p>
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<p>Root mean square deviation (RMSD) graphs for the hit compounds (<b>A</b>): compound <b>3</b> (CNP0086660.2), (<b>B</b>): compound <b>5</b> (CNP0039190.2), (<b>C</b>): compound <b>2</b> (CNP0549010.1). The green graph shows fluctuations in the protein backbone from the initial reference point while the red shows the ligand fluctuations. The RMSD profile of the ligand with respect to its initial fit to the protein binding pocket indicates that all ligands did not fluctuate beyond a 2–7 Å range.</p>
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<p>Interaction diagram of hit compound <b>3</b> (CNP0086660.2) with the GLP-1 allosteric binding pocket. (<b>A</b>) Interaction of compound <b>3</b> with residues in each trajectory frame. The depth of color indicating the higher the interaction with contact residues; (<b>B</b>) the protein–ligand contacts showing the bonding interactions fraction and the nature of the interactions; (<b>C</b>) graphical 2D illustration of compound <b>3</b> interacting with the protein residues during MD simulation.</p>
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<p>Interaction diagram of hit compound <b>5</b> (CNP0039190.2) with the GLP-1 allosteric binding pocket. (<b>A</b>) Interaction of compound <b>5</b> with residues in each trajectory frame. The depth of color indicating the higher the interaction with contact residues; (<b>B</b>) the protein–ligand contacts showing the bonding interactions fraction and the nature of the interactions; (<b>C</b>) graphical 2D illustration of compound <b>5</b> interacting with the protein residues during MD simulation.</p>
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<p>Interaction diagram of hit compound <b>2</b> (CNP0549010.1) with the GLP-1 allosteric binding pocket. (<b>A</b>) Interaction of compound <b>2</b> with residues in each trajectory frame. The depth of color indicating the higher the interaction with contact residues; (<b>B</b>) the protein–ligand contacts showing the bonding interactions fraction and the nature of the interactions; (<b>C</b>) graphical 2D illustration of compound <b>2</b> interacting with the protein residues during MD simulation.</p>
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<p>Chemical structures of identified novel scaffolds for GLP-1 positive allosteric modulation with their hit no (hits are arranged according to their XP/Docking score), Coconut ID, and XP/Docking score.</p>
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<p>Chemical structures of identified novel scaffolds for GLP-1 positive allosteric modulation with their hit no (hits are arranged according to their XP/Docking score), Coconut ID, and XP/Docking score.</p>
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<p>Chemical structures of identified novel scaffolds for GLP-1 positive allosteric modulation with their hit no (hits are arranged according to their XP/Docking score), Coconut ID, and XP/Docking score.</p>
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<p>Chemical structures of identified novel scaffolds for GLP-1 positive allosteric modulation with their hit no (hits are arranged according to their XP/Docking score), Coconut ID, and XP/Docking score.</p>
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<p>Chemical structures of identified novel scaffolds for GLP-1 positive allosteric modulation with their hit no (hits are arranged according to their XP/Docking score), Coconut ID, and XP/Docking score.</p>
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19 pages, 1095 KiB  
Review
Role of the Unique Secreted Peptide Adropin in Various Physiological and Disease States
by Zahra Hasanpour-Segherlou, Andrew A. Butler, Eduardo Candelario-Jalil and Brian L. Hoh
Biomolecules 2024, 14(12), 1613; https://doi.org/10.3390/biom14121613 - 17 Dec 2024
Viewed by 353
Abstract
Adropin, a secreted peptide hormone identified in 2008, plays a significant role in regulating energy homeostasis, glucose metabolism, and lipid metabolism. Its expression is linked to dietary macronutrient intake and is influenced by metabolic syndrome, obesity, diabetes, and cardiovascular diseases. Emerging evidence suggests [...] Read more.
Adropin, a secreted peptide hormone identified in 2008, plays a significant role in regulating energy homeostasis, glucose metabolism, and lipid metabolism. Its expression is linked to dietary macronutrient intake and is influenced by metabolic syndrome, obesity, diabetes, and cardiovascular diseases. Emerging evidence suggests that adropin might be a biomarker for various conditions, including metabolic syndrome, coronary artery disease, and hypertensive disorders complicating pregnancy. In cerebrovascular diseases, adropin demonstrates protective effects by reducing blood–brain barrier permeability, brain edema, and infarct size while improving cognitive and sensorimotor functions in ischemic stroke models. The protective effects of adropin extend to preventing endothelial damage, promoting angiogenesis, and mitigating inflammation, making it a promising therapeutic target for cardiovascular and neurodegenerative diseases. This review provides a comprehensive overview of adropin’s multifaceted roles in physiological and pathological conditions, as well as our recent work demonstrating adropin’s role in subarachnoid hemorrhage-mediated neural injury and delayed cerebral infarction. Full article
(This article belongs to the Section Biological Factors)
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<p>Adropin protects endothelial cells and promotes angiogenesis by stimulating the phosphorylation of eNOS at Ser1177 through the VEGFR2-phosphatidylinositol 3-kinase-Akt and VEGFR2-extracellular signal-regulated kinase 1/2 pathway.</p>
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<p>Proposed mechanisms of adropin-mediated protection in post-SAH cerebral infarction.</p>
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20 pages, 1263 KiB  
Perspective
Genetically Engineered T Cells and Recombinant Antibodies to Target Intracellular Neoantigens: Current Status and Future Directions
by Ana Maria Waaga-Gasser and Thomas Böldicke
Int. J. Mol. Sci. 2024, 25(24), 13504; https://doi.org/10.3390/ijms252413504 - 17 Dec 2024
Viewed by 271
Abstract
Recombinant antibodies and, more recently, T cell receptor (TCR)-engineered T cell therapies represent two immunological strategies that have come to the forefront of clinical interest for targeting intracellular neoantigens in benign and malignant diseases. T cell-based therapies targeting neoantigens use T cells expressing [...] Read more.
Recombinant antibodies and, more recently, T cell receptor (TCR)-engineered T cell therapies represent two immunological strategies that have come to the forefront of clinical interest for targeting intracellular neoantigens in benign and malignant diseases. T cell-based therapies targeting neoantigens use T cells expressing a recombinant complete TCR (TCR-T cell), a chimeric antigen receptor (CAR) with the variable domains of a neoepitope-reactive TCR as a binding domain (TCR-CAR-T cell) or a TCR-like antibody as a binding domain (TCR-like CAR-T cell). Furthermore, the synthetic T cell receptor and antigen receptor (STAR) and heterodimeric TCR-like CAR (T-CAR) are designed as a double-chain TCRαβ-based receptor with variable regions of immunoglobulin heavy and light chains (VH and VL) fused to TCR-Cα and TCR-Cβ, respectively, resulting in TCR signaling. In contrast to the use of recombinant T cells, anti-neopeptide MHC (pMHC) antibodies and intrabodies neutralizing intracellular neoantigens can be more easily applied to cancer patients. However, different limitations should be considered, such as the loss of neoantigens, the modification of antigen peptide presentation, tumor heterogenicity, and the immunosuppressive activity of the tumor environment. The simultaneous application of immune checkpoint blocking antibodies and of CRISPR/Cas9-based genome editing tools to engineer different recombinant T cells with enhanced therapeutic functions could make T cell therapies more efficient and could pave the way for its routine clinical application. Full article
(This article belongs to the Special Issue Molecular Advances in Cancer Immunotherapy)
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<p>Neoepitope targeting with recombinant T cell receptors and recombinant antibodies. TCR-CARS target the neopeptide/MHC with the variable domains of a TCR, TCR-like CARs and TCR-like antibodies. TCR-engineered T cells express a new complete TCR on the cell surface and STARs express the variable regions of immunoglobulin heavy and light chains (VH and VL) fused to TCR-Cα and TCR-Cβ. Bispecific antibodies can target CD3ε and Neopeptide/MHC in the format soluble TCR × anti-CD3 or TCR-like antibody × CD3. TCR-like antibody can also be applied as a complete IgG antibody. In addition, intrabodies can neutralize the function of a neoantigen inside the cell.</p>
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<p>Transfer of variable regions of the TCR and IgG to TCR CAR, TCR-like CAR, STAR and T-CAR. In TCR-CAR, the TCR variable regions Vα and Vβ are linked with a flexible peptide linker and a transmembrane domain and fused to the chimeric antigen receptor with the costimulatory TCR domains. In STAR, the VH and VL domains of antibodies are fused to Cα and Cβ of a TCR. In T-CAR, a scFv (VH and VL linked with a flexible peptide linker) is fused to Cα or Cβ of TCR. In TCR-like CAR, a scFv is fused to a chimeric antigen receptor. Intrabodies are single-domain antibodies from camels, sharks or human VH or VL domains transferred via mRNA lipid nanoparticles or viral cell transduction into the nucleus or cytoplasm.</p>
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<p>Current methodologies to identify neoepitopes and develop TCR-like CARs, TCR-CARs, TCR-like antibodies and intrabodies. Neoepitopes are identified by comparing whole genome sequencing and RNA sequencing of normal and tumor tissue. Neoepitope-reactive TCRs are then selected by co-culture of tumor-infiltrating lymphocytes (TILs) with APCs expressing identified tandem minigenes (TMGs) or neoantigen peptides. Characterized TCR variable domain (TCRv) or single-chain variable fragment (scFv) specific for neoepitope/MHCs are used in a CAR structure to produce TCR-CARs or TCR-like CARs, respectively. Modified T cells are then expanded and infused into the patient. CAR ICDs represent intracellular domains (ICDs). Furthermore, TCR-like antibodies and intrabodies can be selected with phage display by biopanning with neopeptide/MHCs or neoantigen, respectively. <a href="#ijms-25-13504-f003" class="html-fig">Figure 3</a> is a modification of <a href="#ijms-25-13504-f002" class="html-fig">Figure 2</a> in [<a href="#B17-ijms-25-13504" class="html-bibr">17</a>].</p>
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18 pages, 7089 KiB  
Article
Limonin Exhibits Anti-Inflammatory Effects by Inhibiting mTORC1 and Mitochondrial Reactive Oxygen Species in Psoriatic-like Skin Inflammation
by Seung Taek Lee, Jong Yeong Lee, Ha Eun Kim, Jun-Young Park and Jin Kyeong Choi
Antioxidants 2024, 13(12), 1541; https://doi.org/10.3390/antiox13121541 - 16 Dec 2024
Viewed by 287
Abstract
Psoriasis is a chronic inflammatory skin disorder characterized by abnormal immune responses and keratinocyte hyperproliferation. Limonin, a bioactive compound found in citrus fruits, has anti-inflammatory properties in various models; however, its effects on psoriasis are not fully understood. We investigated the therapeutic potential [...] Read more.
Psoriasis is a chronic inflammatory skin disorder characterized by abnormal immune responses and keratinocyte hyperproliferation. Limonin, a bioactive compound found in citrus fruits, has anti-inflammatory properties in various models; however, its effects on psoriasis are not fully understood. We investigated the therapeutic potential of limonin in a 12-O-tetradecanoylphorbol-13-acetate (TPA)-induced psoriasis mouse model. Mice were treated with TPA to induce psoriasis-like skin lesions, followed by intraperitoneal administration of limonin (200 or 400 μg/mouse) for six days. The results showed that limonin improved psoriasis-related symptoms in a psoriasis-like mouse model by suppressing the mRNA expression of pro-inflammatory cytokines and inflammation-related antimicrobial peptides and regulating the expansion of myeloid cells and T cells. Specifically, limonin reduced glucose uptake and oxidative phosphorylation to shift the metabolic program in the inflamed skin cells of psoriasis-like mice. Limonin activates AMPK and proteins related to mTOR inhibition, thereby suppressing the mTOR signaling pathway. It also inhibits mitochondrial mass and mitochondrial ROS production, thereby preventing the development of dysfunctional mitochondria in inflamed skin cells. Overall, limonin modulates key immune responses and metabolic pathways related to inflammation and mitochondrial health in psoriasis. Therefore, it is a promising natural candidate for the treatment of psoriasis and various inflammatory skin diseases. Full article
(This article belongs to the Special Issue Antioxidants for Skin Health)
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<p>Limonin alleviates symptoms of TPA induced psoriasis-like mouse model and inhibits amplification of psoriasis-associated genes. (<b>a</b>) Experimental design for the induction of TPA-induced psoriasis-like mouse model. The mice (n = 4–6/group) were divided into five groups. (<b>b</b>) Mouse body weight change calculated as a percentage of the initial weight. (<b>c</b>) Ear thickness was measured 24 h after TPA application using a dial thickness gauge. (<b>d</b>) Representative photographs of mouse ears from each treatment group on day 7. (<b>e</b>) Representative photomicrographs of ear sections stained with hematoxylin and eosin (H&amp;E) (×200 magnification; scale bar = 200 µm). (<b>f</b>) Epidermal and dermal thicknesses were measured using microphotographs of H&amp;E-stained ear tissues. (<b>g</b>,<b>h</b>) Gene expression of pro-inflammatory cytokines (<span class="html-italic">Tnfα</span> and <span class="html-italic">Il1β</span>), and psoriasis-related antibacterial peptides (<span class="html-italic">Defb4</span>, <span class="html-italic">LCN</span>, <span class="html-italic">S100a7</span>, <span class="html-italic">S100a8</span>, and <span class="html-italic">S100a9</span>) in the ear skin of TPA and limonin or rapamycin-treated psoriasis-like mice; the ear skin was excised on day 7. Gene expression was analyzed using qPCR. The gene expression levels were normalized to that of β-actin. All data are presented as the mean ± SEM of four independent experiments. Values were analyzed by Holm–Šídák post-hoc test. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 vs. TPA-induced group. TPA: 12-O-tetradecanoylphorbol-13-acetate; H&amp;E: hematoxylin and eosin; SEM: standard error of the mean; <span class="html-italic">Defb4</span>: defensin β 4; <span class="html-italic">S100a7</span>: S100 calcium-binding protein A7; <span class="html-italic">S100a8</span>: S100 calcium-binding protein A8; <span class="html-italic">S100a9</span>: S100 calcium-binding protein A9.</p>
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<p>Limonin inhibits the innate immune cells in the skin of TPA-induced psoriasis mice. (<b>a</b>) Representative flow cytometry plots showing the percentages of Ly6G<sup>+</sup>CD11b<sup>+</sup> (neutrophils), F4/80<sup>+</sup>CD11b<sup>+</sup> (macrophages), F4/80<sup>+</sup>CD163<sup>-</sup> (M1 macrophages), and F4/80<sup>+</sup>CD163<sup>+</sup> (M2 macrophages) in skin cells. (<b>b</b>) Bar charts showing the percentages (upper panel) and (<b>c</b>) the numbers (lower panel) of Ly6G<sup>+</sup>CD11b<sup>+</sup> (neutrophils), F4/80<sup>+</sup>CD11b<sup>+</sup> (macrophages), F4/80<sup>+</sup>CD163<sup>-</sup> (M1 macrophages), and F4/80<sup>+</sup>CD163<sup>+</sup> (M2 macrophages) in skin cells. All data are presented as the mean ± SEM of four independent experiments. Values were analyzed by Holm–Šídák post-hoc test. *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001 vs. TPA-induced group. TPA: 12-O-tetradecanoylphorbol-13-acetate; Ly6G: lymphocyte antigen 6 complex, locus G.</p>
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<p>Limonin regulates T cell immune responses in the skin of TPA-induced psoriasis mice. (<b>a</b>) Gene expression of Th17-assciated genes (<span class="html-italic">Rorc</span>, <span class="html-italic">Il17a</span>, <span class="html-italic">Il17e</span>, <span class="html-italic">Il17f</span>, and <span class="html-italic">Il22</span>) in ear tissue of TPA and limonin or rapamycin-treated psoriasis-like mice, the back skin were excised on day 7. Gene expression was analyzed using qPCR. The gene expression levels were normalized to that of β-actin. (<b>b</b>–<b>d</b>) Representative flow cytometry plots and bar charts showing the percentage and numbers of CD4<sup>+</sup>IFN-γ<sup>+</sup> (Th1 cells), CD4<sup>+</sup>RORγt<sup>+</sup>IL-17A<sup>+</sup> (Th17 cells), CD4<sup>+</sup>IL-22<sup>+</sup> (Th17 cells), and CD4<sup>+</sup>Foxp3<sup>+</sup> (Treg cells) in the ear skin cells (<span class="html-italic">n</span> = 5/group). All data are presented as mean ± SEM of two independent experiments. Statistical significance was determined using the Holm–Šídák post hoc test. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001 vs. TPA-induced group. TPA: 12-O-tetradecanoylphorbol-13-acetate; Rorc: retinoic acid-related orphan receptor gamma c; IFN-γ: interferon gamma; IL-17A: interleukin-17A; IL-22: interleukin-22; Foxp3: forkhead box P3; Th1: T helper 1; Th17: T helper 17.</p>
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<p>Limonin suppresses glycolysis, oxidative phosphorylation, and mitochondrial ROS in the skin of TPA-induced psoriasis mice. (<b>a</b>) Measurement of ECAR using a seahorse metabolic analyzer in ear skin cells from each group (left panel). Bar graphs show quantification of glycolysis, glycolytic capacity, glycolytic reserve, and non-glycolytic acidification (right panel). (<b>b</b>) Measurement of OCR using a Seahorse metabolic analyzer in ear tissue cells from each group (left panel). Bar graphs show quantification of basal respiration, maximal respiration, proton leak, non-mitochondrial oxygen consumption, and spare respiratory capacity (right panel). (<b>c</b>) Representative histograms of glucose uptake in ear tissue cells measured by using 2-NBDG (left panel) and bar graphs showing quantification of 2-NBDG in percentage and cell numbers (right panel). (<b>d</b>) Representative flow cytometry plots (left panel) showing mitochondrial ROS levels, as measured by MitoSOX Red, and mitochondrial mass, as measured by MitoTracker Green; bar graphs showing quantification of MitoSOX<sup>+</sup> MitoTracker<sup>+</sup> in percentage and cell numbers (right panel). All data are presented as mean ± SEM of four independent experiments. Statistical significance was determined using the Holm–Šídák post-hoc test. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001 vs. TPA-induced group. TPA: 12-O-tetradecanoylphorbol-13-acetate; OCR: oxygen consumption rate; ECAR: extracellular acidification rate; 2-NBDG: 2-[N-(7-Nitrobenz-2-oxa-1,3-diazol-4-yl) Amino]-2-Deoxyglucose.</p>
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<p>Limonin inhibits the mTOR signaling pathway by inducing AMPK activation. (<b>a</b>) Representative Western blot images of phosphorylated and total forms of key proteins involved in the mTOR signaling pathways (left panel) and bar graph of the relative intensities (right panel). (<b>b</b>) Representative Western blot images for p-AMPK, AMPK, and β-actin (left panel) and bar graph of the relative intensities (right panel). All data are presented as mean ± SEM of two independent experiments. Statistical significance was determined using the Holm–Šídák post-hoc test. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and **** <span class="html-italic">p</span> &lt; 0.0001 vs. TPA-induced group. TPA: 12-O-tetradecanoylphorbol-13-acetate; mTOR: mechanistic target of rapamycin; RAPTOR: regulatory-associated protein of mTOR; p70S6K: p70 S6 kinase; 4E-BP1: eukaryotic translation initiation factor 4E-binding protein 1; AMPK: AMP-activated protein kinase.</p>
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<p>Limonin Inhibits mTOR Signaling and Mitochondrial ROS Production via AMPK Activation in IL-17-stimulated HaCaT cells. (<b>a</b>) Human keratinocytes HaCaT cells were stimulated with IL-17A (200 ng/mL) in the presence or absence of limonin (20 μg/mL) or Rapa (100 nM) for 24 h. Protein expression of mTOR and AMPKs was determined by Western blotting. (<b>b</b>–<b>e</b>) HaCaT cells were transfected with Control or AMPKs siRNA for 83 h and then stimulated with IL-17A (200 ng/mL) in the presence or absence of limonin (20 μg/mL) for 24 h (n = 3/group). (<b>c</b>) Cells were transfected either control or AMPK siRNA without stimulation and analyzed using Western blotting. (<b>d</b>) Representative flow cytometry plots (left panel) showing mitochondrial ROS levels, as measured by MitoSOX Red, and mitochondrial mass, as measured by MitoTracker Green; bar graphs showing quantification of MitoSOX<sup>+</sup> MitoTracker<sup>+</sup> in percentage and cell numbers (right panel). (<b>e</b>) Gene expression of pro-inflammatory cytokines (<span class="html-italic">Tnfα</span> and <span class="html-italic">Il1β</span>) and psoriasis-related antibacterial peptides (<span class="html-italic">Defb4</span>, <span class="html-italic">LCN</span>, <span class="html-italic">S100a7</span>, <span class="html-italic">S100a8</span>, and <span class="html-italic">S100a9</span>) were analyzed using qPCR. The gene expression levels were normalized to that of β-actin. All data are presented as mean ± SEM of independent experiments. Statistical significance was determined using the Holm–Šídák post-hoc test. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001 vs. IL-17-stimulated group. mTOR: mechanistic target of rapamycin; AMPK: AMP-activated protein kinase; ROS: reactive oxygen species; <span class="html-italic">Defb4</span>: defensin β 4; <span class="html-italic">S100a7</span>: S100 calcium-binding protein A7; <span class="html-italic">S100a8</span>: S100 calcium-binding protein A8; <span class="html-italic">S100a9</span>: S100 calcium-binding protein A9.</p>
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15 pages, 4209 KiB  
Article
Construction of Nicotinamide Mononucleotide-Loaded Liposomes and Their In Vitro Transport Across the Blood–Brain Barrier
by Tiantian Wang, Qi Wu, Lihong Wang, Tao Lan, Zhenyu Yun, Lin Zhao and Xi Wu
Appl. Sci. 2024, 14(24), 11732; https://doi.org/10.3390/app142411732 - 16 Dec 2024
Viewed by 435
Abstract
Nicotinamide mononucleotide (NMN) possesses a variety of physiological functions and has therapeutic effects on cardio-cerebral diseases, senile degenerative diseases, neurodegenerative diseases, delayed aging, etc. However, its ability to cross the blood–brain barrier (BBB) and the mechanism of its transport have not been reported. [...] Read more.
Nicotinamide mononucleotide (NMN) possesses a variety of physiological functions and has therapeutic effects on cardio-cerebral diseases, senile degenerative diseases, neurodegenerative diseases, delayed aging, etc. However, its ability to cross the blood–brain barrier (BBB) and the mechanism of its transport have not been reported. In this study, we used the immortalized hCMEC/D3 cell line to construct an in vitro monolayer cell BBB model, evaluated its ability to cross the blood–brain barrier, and explored the mechanism by carrying out transport and efflux experiments on NMN. The ability of NMN to cross the BBB was investigated by preparing NMN-loaded liposomes conjugated with ANG peptide and RVG peptide. The results showed that the transmembrane transport ability of NMN was moderate, and the transport mechanism was passive transport relying on the concentration difference. The trans-BBB ability of ANG peptide coupled with NMN could be highly significantly improved. Full article
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<p>Schematic diagram of targeted liposome synthesis.</p>
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<p>Liposome characterization: (<b>a</b>) blank liposomes (KB-lips); (<b>b</b>) results of liposome particle size.</p>
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<p>Time-dependent TEER values of monolayer BBB in vitro.</p>
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<p>MTT method detection results: (<b>a</b>) NMN; (<b>b</b>) KB-lips; (<b>c</b>) NMN-lips; (<b>d</b>) ANG-NMN-lips; (<b>e</b>) RVG-NMN-lips; *: compared with the blank group, there is a significant difference, <span class="html-italic">p</span> &lt; 0.05; **: compared with the blank group, there is a highly significant difference, <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>MTT method detection results: (<b>a</b>) NMN; (<b>b</b>) KB-lips; (<b>c</b>) NMN-lips; (<b>d</b>) ANG-NMN-lips; (<b>e</b>) RVG-NMN-lips; *: compared with the blank group, there is a significant difference, <span class="html-italic">p</span> &lt; 0.05; **: compared with the blank group, there is a highly significant difference, <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>The transport kinetics curve and transport percentage in NMN time-dependency bidirectional transmembrane transport experiment and the MTT method detection results: (<b>a</b>) transport kinetics curve of AP-BL; (<b>b</b>) transport kinetics curve of BL-AP; (<b>c</b>) transport percentage of AP-BL; (<b>d</b>) transport percentage BL-AP.</p>
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<p>The transport kinetics curve and transport percentage in the NMN concentration-dependency bidirectional transmembrane transport experiment: (<b>a</b>) transport kinetics curve of AP-BL; (<b>b</b>) transport kinetics curve of BL-AP; (<b>c</b>) transport percentage of AP-BL; (<b>d</b>) transport percentage BL-AP.</p>
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<p>The transport kinetics curve and transport percentage in the NMN concentration-dependency bidirectional transmembrane transport experiment: (<b>a</b>) transport kinetics curve of AP-BL; (<b>b</b>) transport kinetics curve of BL-AP; (<b>c</b>) transport percentage of AP-BL; (<b>d</b>) transport percentage BL-AP.</p>
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<p>Results of four types of liposome transmembrane transport: (<b>a</b>) AP-BL; (<b>b</b>) BL-AP. #: compared with the NMN group, there is a significant difference, <span class="html-italic">p</span> &lt; 0.05; ##: compared with the NMN group, there is a highly significant difference, <span class="html-italic">p</span> &lt; 0.01.</p>
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19 pages, 6316 KiB  
Article
Protective Effects of Cereal-Based Fermented Beverages Against 5-Fluorouracil-Induced Intestinal Damage in Mice
by Dongze Qin, Wenhui Fu, Yi Sun, Lingda Zhao, Haiwei Liu, Dancai Fan, Dongfei Tan, Xuemeng Ji and Shuo Wang
Nutrients 2024, 16(24), 4332; https://doi.org/10.3390/nu16244332 - 16 Dec 2024
Viewed by 371
Abstract
Background: 5-Fluorouracil (5-FU) is a common chemotherapeutic medication used to treat cancer. However, the intestinal tract may sustain oxidative damage as a result. Objectives: The purpose of this study was to clarify the underlying molecular mechanisms and examine the preventive benefits of cereal-based [...] Read more.
Background: 5-Fluorouracil (5-FU) is a common chemotherapeutic medication used to treat cancer. However, the intestinal tract may sustain oxidative damage as a result. Objectives: The purpose of this study was to clarify the underlying molecular mechanisms and examine the preventive benefits of cereal-based fermented drinks (CFBs) against intestinal injury in mice caused by 5-FU. Methods: The mice were injected intraperitoneally with 5-FU to induce intestinal mucosal and treated with CFB. The factors for intestinal barrier integrity, oxidative stress and inflammation were measured. Results: The findings demonstrated that CFBs had high levels of polyphenol, flavonoids, and peptides and had in vitro high free radical scavenging capacity. Furthermore, CFBs effectively ameliorated 5-FU-induced intestinal epithelium damage, characterized by increasing intestinal tight junctions and reducing apoptosis in intestinal cells. These protective effects may attribute to the increased activity of antioxidant-related enzymes (SOD, CAT, and GSH) as well as decreased amounts of inflammatory and oxidative damage markers (IL-1β, TNF-α, and MDA) in the intestinal tract. Conclusions: Overall, these results show that CFBs can mitigate intestinal damage caused by 5-FU by reducing oxidative stress, suggesting the potential utility of CFBs for therapeutic treatment against intestinal mucositis. Full article
(This article belongs to the Section Nutritional Immunology)
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<p>The scheme of animal experiments: BALB/c mice (<span class="html-italic">n</span> = 10 in each group) were treated with CFB for 15 days. On the 10th day, intestinal injury was induced by intraperitoneal (i.p.) injection of 5-FU (300 mg/kg).</p>
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<p>The quality and chemical antioxidant activity of CFBs. ZLC: the fermentation supernatant of samples without herbal medicines; ZLCM: the fermentation supernatant of samples with herbal medicines; JGJZ: the commercial cereal-based juice; Ascorbate: the positive control group (Vitamin C). (<b>A</b>) pH values; (<b>B</b>) protein content; (<b>C</b>) TPC; (<b>D</b>) TFC; (<b>E</b>) ABTS radical scavenging activity; (<b>F</b>) DPPH radical scavenging activity; (<b>G</b>) molecular weight distribution (The red-circled part is the elution peak of the 12 kDa molecular weight protein). Data are presented as mean ± SEM, and differences were regarded as statistically significant at a <span class="html-italic">p</span>-value &lt; 0.05 (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, or *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Clinical index of mice. (<b>A</b>) The contamination of the hair around the anus and buttocks; (<b>B</b>) The length of the small intestine. Ctrl: the control group; 5-FU: the model group; ZLC: pretreatment with ZLC; ZLCM: pretreatment with ZLCM; JGJZ: the positive control (pretreatment with JGJZ).</p>
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<p>CFB supplementation ameliorated immunosuppression in mice induced by 5-FU. Ctrl: the control group; 5-FU: the model group; ZLC: pretreatment with ZLC; ZLCM: pretreatment with ZLCM; JGJZ: the positive control (pretreatment with JGJZ). (<b>A</b>) White blood cell (WBC); (<b>B</b>) platelet (PLT); (<b>C</b>) spleen index. Data are presented as mean ± SEM, and differences were regarded as statistically significant at a <span class="html-italic">p</span>-value &lt; 0.05 (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, or *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>CFB ameliorated 5-FU-induced intestinal barrier injury and histopathological changes. Ctrl: the control group; 5-FU: the model group; ZLC: pretreatment with ZLC; ZLCM: pretreatment with ZLCM; JGJZ: the positive control (pretreatment with JGJZ). The mRNA expression levels of (<b>A</b>) ZO-1; (<b>B</b>) occludin; (<b>C</b>) DAO; (<b>D</b>) morphometric analysis of villus height; (<b>E</b>) histopathological sections of stained mucosal (5× objective, scale bar = 200 μm). Data are presented as mean ± SEM, and differences were regarded as statistically significant at a <span class="html-italic">p</span>-value &lt; 0.05 (* <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001, or **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Effects of CFBs on the integrity of intestinal mucosal barrier in mice. Ctrl: the control group; 5-FU: the model group; ZLC: pretreatment with ZLC; ZLCM: pretreatment with ZLCM; JGJZ: the positive control (pretreatment with JGJZ). (<b>A</b>) The mRNA expression levels of Mucin-2; (<b>B</b>) number of goblet cells/field for experimental groups; (<b>C</b>) Alcian blue-periodic acid Schiff (AB-PAS) staining of ileum; the purple-magenta particles indicated by the arrow are goblet cells (20× objective, scale bar = 50 μm). Data are presented as mean ± SEM, and differences were regarded as statistically significant at a <span class="html-italic">p</span>-value &lt; 0.05 (* <span class="html-italic">p</span> &lt; 0.05, or **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>CFBs reduced 5-FU-induced apoptosis of intestinal cells. Ctrl: the control group; 5-FU: the model group; ZLC: pretreatment with ZLC; ZLCM: pretreatment with ZLCM; JGJZ: the positive control (pretreatment with JGJZ). (<b>A</b>) The mRNA expression levels of Bcl-2; (<b>B</b>) mRNA expression levels of Bax; (<b>C</b>) TUNEL staining (20× objective, scale bar = 50 μm). Data are presented as mean ± SEM, and differences were regarded as statistically significant at a <span class="html-italic">p</span>-value &lt; 0.05 (* <span class="html-italic">p</span> &lt; 0.05, or ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>CFBs attenuated intestinal oxidative stress injury in mice induced by 5-FU. Ctrl: the control group; 5-FU: the model group; ZLC: pretreatment with ZLC; ZLCM: pretreatment with ZLCM; JGJZ: the positive control (pretreatment with JGJZ). (<b>A</b>) CAT; (<b>B</b>) SOD; (<b>C</b>) GSH; (<b>D</b>) MDA. Data are presented as mean ± SEM, and differences were regarded as statistically significant at a <span class="html-italic">p</span>-value &lt; 0.05 (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, or **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>CFBs inhibited 5-FU-induced intestinal inflammatory response. Ctrl: the control group; 5-FU: the model group; ZLC: pretreatment with ZLC; ZLCM: pretreatment with ZLCM; JGJZ: the positive control (pretreatment with JGJZ). Contents of pro-inflammatory cytokines (<b>A</b>) TNF-α and (<b>B</b>) IL-1β; (<b>C</b>) mRNA expression levels of NF-κB, IKKα, and IKKβ. Data are presented as mean ± SEM, and differences were regarded as statistically significant at a <span class="html-italic">p</span>-value &lt; 0.05 (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, or **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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11 pages, 2439 KiB  
Article
AISMPred: A Machine Learning Approach for Predicting Anti-Inflammatory Small Molecules
by Subathra Selvam, Priya Dharshini Balaji, Honglae Sohn and Thirumurthy Madhavan
Pharmaceuticals 2024, 17(12), 1693; https://doi.org/10.3390/ph17121693 - 15 Dec 2024
Viewed by 587
Abstract
Background/Objectives: Inflammation serves as a vital response to diverse harmful stimuli like infections, toxins, or tissue injuries, aiding in the elimination of pathogens and tissue repair. However, persistent inflammation can lead to chronic diseases. Peptide therapeutics have gained attention for their specificity in [...] Read more.
Background/Objectives: Inflammation serves as a vital response to diverse harmful stimuli like infections, toxins, or tissue injuries, aiding in the elimination of pathogens and tissue repair. However, persistent inflammation can lead to chronic diseases. Peptide therapeutics have gained attention for their specificity in targeting cells, yet their development remains costly and time-consuming. Therefore, small molecules, with their stability, low immunogenicity, and oral bioavailability, have become a focal point for predicting anti-inflammatory small molecules (AISMs). Methods: In this study, we introduce a computational method called AISMPred, designed to classify AISMs and non-AISMs. To develop this approach, we constructed a dataset comprising 1750 AISMs and non-AISMs, each annotated with IC50 values sourced from the PubChem BioAssay database. We computed two distinct types of molecular descriptors using PaDEL and Mordred tools. Subsequently, these descriptors were concatenated to form a hybrid feature set. The SVC-L1 regularization method was implemented for the optimum feature selection to develop robust Machine learning (ML) models. Five different conventional ML classifiers were employed, such as RF, ET, KNN, LR, and Ensemble methods. Results: A total of 15 ML models were developed using 2D, FP, and Hybrid feature sets, with the ET model with hybrid features achieving the highest accuracy of 92% and an AUC of 0.97 on the independent test dataset. Conclusions: This study provides an effective method for screening AISMs, potentially impacting drug discovery and design. Full article
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<p>The chemical space of the compounds in the training set compared with that in the test set. (<b>a</b>) 2D descriptors, (<b>b</b>) fingerprints, (<b>c</b>) hybrid (2D + FP).</p>
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<p>(<b>a</b>) Comparison of receiver operating characteristic curves of the four models on external data using Hybrid dataset. The curve closer to the upper left corner showed better overall discrimination ability. (<b>b</b>) Comparison of precision-recall curves of the four models on external data. The curve closer to the upper right corner also showed the ability to combine precision with sensitivity. (AP: average precision, AUC: area under the receiver operating characteristic curve, ROC: receiver operating characteristic).</p>
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<p>Feature importance plot for the selected ML-based ExtraTree model using hybrid feature set.</p>
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<p>Computational framework of AISMPred. It includes data collection, feature selection, model construction, and performance comparison.</p>
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18 pages, 1909 KiB  
Review
Peptide Lv and Angiogenesis: A Newly Discovered Angiogenic Peptide
by Dylan L. Pham, Kelsey Cox, Michael L. Ko and Gladys Y.-P. Ko
Biomedicines 2024, 12(12), 2851; https://doi.org/10.3390/biomedicines12122851 - 15 Dec 2024
Viewed by 438
Abstract
Peptide Lv is a small endogenous secretory peptide with ~40 amino acids and is highly conserved among certain several species. While it was first discovered that it augments L-type voltage-gated calcium channels (LTCCs) in neurons, thus it was named peptide “Lv”, it can [...] Read more.
Peptide Lv is a small endogenous secretory peptide with ~40 amino acids and is highly conserved among certain several species. While it was first discovered that it augments L-type voltage-gated calcium channels (LTCCs) in neurons, thus it was named peptide “Lv”, it can bind to vascular endothelial growth factor receptor 2 (VEGFR2) and has VEGF-like activities, including eliciting vasodilation and promoting angiogenesis. Not only does peptide Lv augment LTCCs in neurons and cardiomyocytes, but it also promotes the expression of intermediate-conductance KCa channels (KCa3.1) in vascular endothelial cells. Peptide Lv is upregulated in the retinas of patients with early proliferative diabetic retinopathy, a disease involving pathological angiogenesis. This review will provide an overview of peptide Lv, its known bioactivities in vitro and in vivo, and its clinical relevance, with a focus on its role in angiogenesis. As there is more about peptide Lv to be explored, this article serves as a foundation for possible future developments of peptide Lv-related therapeutics to treat or prevent diseases. Full article
(This article belongs to the Section Gene and Cell Therapy)
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<p>Peptide Lv is encoded as a propeptide in the <span class="html-italic">Vstm4</span> gene. Created with Biorender.com.</p>
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<p>Sequence homology of peptide Lv among four different species: mouse, rat, human, and chicken. Created with Biorender.com.</p>
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<p>Stages of vascular endothelial cell-mediated angiogenesis. The first stage of angiogenesis is initiated by the reaction to various factors, including VEGF. Local vasodilation and increased permeability occur in response to VEGF. An increase in MMPs, followed by basement membrane degradation ensues. A sprout then forms, followed by the proliferation and migration of endothelial stalk cells, led by a tip cell. Once the vessel tube is formed, the vessel will then mature through its association with pericytes. Created by Biorender.com.</p>
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<p>Various ion channels are involved in hyperpolarization. Endothelial K<sup>+</sup> channels, such as K<sub>Ca</sub>3.1, K<sub>Ca</sub>2.3, and Kir channels, release K<sup>+</sup>, leading to endothelial hyperpolarization. The electrical signal can be propagated to smooth muscle cells through myoendothelial junctions (MEJs). K<sup>+</sup> efflux into the myoendothelial space can activate smooth muscle Kir channels and Na<sup>+</sup>/K<sup>+</sup> pumps, leading to smooth muscle hyperpolarization. TRPV4 channel opening leads to increased calcium influx that can activate K<sub>Ca</sub> channels. Created with Biorender.com.</p>
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13 pages, 621 KiB  
Article
Clinical Implication of HIF-PH Inhibitor in Patients with Heart Failure, Chronic Kidney Disease, and Renal Anemia
by Yuki Hida, Teruhiko Imamura and Koichiro Kinugawa
J. Clin. Med. 2024, 13(24), 7619; https://doi.org/10.3390/jcm13247619 - 13 Dec 2024
Viewed by 268
Abstract
Background: Hypoxia-inducible factor-prolyl hydroxylase (HIF-PH) inhibitors have been developed as a treatment for renal anemia. However, their therapeutic impact on patients with concomitant heart failure remains uncertain. We investigated the impact of HIF-PH inhibitors on improving renal anemia and associated clinical outcomes in [...] Read more.
Background: Hypoxia-inducible factor-prolyl hydroxylase (HIF-PH) inhibitors have been developed as a treatment for renal anemia. However, their therapeutic impact on patients with concomitant heart failure remains uncertain. We investigated the impact of HIF-PH inhibitors on improving renal anemia and associated clinical outcomes in patients with heart failure. Methods: Patients with both heart failure and renal anemia who received HIF-PH inhibitors were retrospectively analyzed over a six-month follow-up period. Hemoglobin levels and other clinical parameters were compared between the six-month pre-treatment period without HIF-PH inhibitors and the six-month treatment period with HIF-PH inhibitors. Results: A total of 69 patients (median age 82 years, 27 male) were included. Baseline hemoglobin was 9.2 (8.8, 10.3) g/dL, baseline plasma B-type natriuretic peptide level was 264 (156, 372) pg/mL, and baseline estimated glomerular filtration rate was 29.1 (19.0, 35.1) mL/min/1.73 m2. Hemoglobin levels declined during the pre-treatment period from 10.5 (9.4, 11.5) g/dL to 9.2 (8.8, 10.3) g/dL (p < 0.001) but subsequently increased to 10.9 (10.1, 12.0) g/dL following six months of HIF-PH inhibitor treatment (p < 0.001). This increase in hemoglobin was accompanied by a reduction in plasma BNP levels, improved renal function, and reduced systemic inflammation (p < 0.05 for all). Conclusions: HIF-PH inhibitors demonstrated efficacy in this cohort of patients with heart failure, with associated improvements in heart failure severity, renal function, and systemic inflammation. Full article
(This article belongs to the Special Issue Current and Emerging Treatment Perspectives in Heart Failure)
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<p>Trajectory of hemoglobin levels at three time points: six months before the initiation of HIF-PH inhibitors, baseline just before the initiation of HIF-PH inhibitors, and six months after the initiation of HIF-PH inhibitors (on treatment). When the trend analysis using Friedman test reached statistical significance, post hoc Wilcoxon signed-rank test was performed for two different time point data. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Changes in hemoglobin levels during six-month pre-treatment period and six-month on-treatment period. * <span class="html-italic">p</span> &lt; 0.05 by Mann–Whitney U test.</p>
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