www.fgks.org   »   [go: up one dir, main page]

You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (74,881)

Search Parameters:
Keywords = therapeutics

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
14 pages, 3258 KiB  
Article
Insights into Halogen-Induced Changes in 4-Anilinoquinazoline EGFR Inhibitors: A Computational Spectroscopic Study
by Sallam Alagawani, Vladislav Vasilyev, Andrew H. A. Clayton and Feng Wang
Molecules 2024, 29(12), 2800; https://doi.org/10.3390/molecules29122800 (registering DOI) - 12 Jun 2024
Abstract
The epidermal growth factor receptor (EGFR) is a pivotal target in cancer therapy due to its significance within the tyrosine kinase family. EGFR inhibitors like AG-1478 and PD153035, featuring a 4-anilinoquinazoline moiety, have garnered global attention for their potent therapeutic activities. While pre-clinical [...] Read more.
The epidermal growth factor receptor (EGFR) is a pivotal target in cancer therapy due to its significance within the tyrosine kinase family. EGFR inhibitors like AG-1478 and PD153035, featuring a 4-anilinoquinazoline moiety, have garnered global attention for their potent therapeutic activities. While pre-clinical studies have highlighted the significant impact of halogen substitution at the C3’-anilino position on drug potency, the underlying mechanism remains unclear. This study investigates the influence of halogen substitution (X = H, F, Cl, Br, I) on the structure, properties, and spectroscopy of halogen-substituted 4-anilinoquinazoline tyrosine kinase inhibitors (TKIs) using time-dependent density functional methods (TD-DFT) with the B3LYP functional. Our calculations revealed that halogen substitution did not induce significant changes in the three-dimensional conformation of the TKIs but led to noticeable alterations in electronic properties, such as dipole moment and spatial extent, impacting interactions at the EGFR binding site. The UV–visible spectra show that more potent TKI-X compounds typically have shorter wavelengths, with bromine’s peak wavelength at 326.71 nm and hydrogen, with the lowest IC50 nM, shifting its lambda max to 333.17 nm, indicating a correlation between potency and spectral characteristics. Further analysis of the four lowest-lying conformers of each TKI-X, along with their crystal structures from the EGFR database, confirms that the most potent conformer is often not the global minimum structure but one of the low-lying conformers. The more potent TKI-Cl and TKI-Br exhibit larger deviations (RMSD > 0.65 Å) from their global minimum structures compared to other TKI-X (RMSD < 0.15 Å), indicating that potency is associated with greater flexibility. Dipole moments of TKI-X correlate with drug potency (ln(IC50 nM)), with TKI-Cl and TKI-Br showing significantly higher dipole moments (>8.0 Debye) in both their global minimum and crystal structures. Additionally, optical spectral shifts correlate with potency, as TKI-Cl and TKI-Br exhibit blue shifts from their global minimum structures, in contrast to other TKI-X. This suggests that optical reporting can effectively probe drug potency and conformation changes. Full article
(This article belongs to the Special Issue Molecular Spectroscopy in Applied Chemistry)
Show Figures

Figure 1

Figure 1
<p>Strain energies (SEs) of the top five low-energy TKIs-X conformers calculated in DMSO solvent. * EGFR-DB structures were obtained by downloading them from the EGFR database (<a href="http://crdd.osdd.net/raghava/egfrindb/" target="_blank">http://crdd.osdd.net/raghava/egfrindb/</a>, accessed on 2 February 2023) (H: EGIN0000732, F: EGIN0000733, Cl: EGIN0000281, Br: EGIN0000010, and I: EGIN0000736) [<a href="#B17-molecules-29-02800" class="html-bibr">17</a>], after which optimization was conducted while maintaining fixed torsion angles. The enclosed structure of TKIs-X presents the IUPAC nomenclature for the compound.</p>
Full article ">Figure 2
<p>The relationship between DM (in Debye) and the inhibitor potency (ln(IC<sub>50</sub> in nM)). Note that the more negative the lnX function, the smaller X, so the more potent.</p>
Full article ">Figure 3
<p>The UV–visible absorbance spectra (nm) of the EGFR* database crystal structures in DMSO solvent were determined through the DFT B3LYP/def2TZVP computational method. The spectral colours corresponding to each structure are as follows: H-EGIN0000732 is represented by an orange spectrum, F-EGIN0000733 by a blue spectrum, Cl-EGIN0000281 by a green spectrum, Br-EGIN0000010 by a red spectrum, and I-EGIN0000736 by a purple spectrum. * EGFR database source is (<a href="http://crdd.osdd.net/raghava/egfrindb/" target="_blank">http://crdd.osdd.net/raghava/egfrindb/</a>, accessed on 2 February 2023) [<a href="#B17-molecules-29-02800" class="html-bibr">17</a>].</p>
Full article ">Figure 4
<p>Correlation between optical shift and the potency of the TKI-X.</p>
Full article ">Figure 5
<p>Comparison of UV-Vis absorption spectra (nm) of the calculated global minimum structure (red) and EGFR-DB [<a href="#B17-molecules-29-02800" class="html-bibr">17</a>] structure (blue) with their UV-Vis differential spectrum produced by (λcal−λEGFR-DB) (green) for (<b>a</b>) TKI-Br, (<b>b</b>) TKI-Cl, using B3LYP/def2TZVP method in DMSO solvent.</p>
Full article ">Figure 6
<p>Natural transition orbitals (NTOs) analysis for the excited state with higher oscillation strength for compounds (<b>a</b>) TKI-Cl for excited state S0 S15 (ƒ = 0.5732), (<b>b</b>) TKI-Br for excited state S0 S17 (ƒ = 0.5542). Calculated using TD-DFT at the B3LYP/def2TZVP level of theory in DMSO solvent.</p>
Full article ">Figure 7
<p>The dominant NTOs (occupied and virtual) pairs for the first four excited states of (<b>a</b>) TKI-Br. The associated eigenvalues λ are 0.982423, 0.990344, 0.730883, and 0.861056, respectively; (<b>b</b>) TKI-Cl. The associated eigenvalues λ are 0.983168, 0.980275, 0.729861, and 0.896348, respectively.</p>
Full article ">
11 pages, 775 KiB  
Article
Preliminary Insights into the Antigenotoxic Potential of Lemon Essential Oil and Olive Oil in Human Peripheral Blood Mononuclear Cells
by Sara Gonçalves, Mafalda Monteiro, Isabel Gaivão and Rita S. Matos
Plants 2024, 13(12), 1623; https://doi.org/10.3390/plants13121623 (registering DOI) - 12 Jun 2024
Abstract
Lemon essential oil, derived from Citrus limon, possesses diverse health-promoting properties, including antioxidant, antimicrobial, and mood-enhancing effects. Despite its traditional use in aromatherapy and complementary medicine, there is a need for comprehensive investigations into its therapeutic potential, particularly in mitigating DNA damage [...] Read more.
Lemon essential oil, derived from Citrus limon, possesses diverse health-promoting properties, including antioxidant, antimicrobial, and mood-enhancing effects. Despite its traditional use in aromatherapy and complementary medicine, there is a need for comprehensive investigations into its therapeutic potential, particularly in mitigating DNA damage and supporting health in palliative care settings. This study aimed to evaluate the antigenotoxic effects of lemon essential oil in human peripheral blood mononuclear cells and to explore its potential applications in palliative care. Treatment with lemon essential oil significantly reduced DNA damage, with 1% w/v with 3.13% DNA in tail demonstrating greater efficacy. Furthermore, lemon essential oil attenuated streptonigrin-induced DNA damage, suggesting a potential protective effect against oxidative stress, especially at 3% w/v, with 11.81% DNA in tail. Compared to olive oil treatment, the DNA damage was significantly lower with streptonigrin treatment alone, which had 47.06% DNA in tail, while the olive oil treatment resulted in 36.88% DNA in tail. These results can be attributed to the main constituents: limonene in lemon essential oil and oleic acid in olive oil. These results suggest a potential role in mitigating oxidative stress and supporting genomic stability. Further research is warranted to elucidate the mechanisms of action and clinical applications in palliative care. Full article
Show Figures

Figure 1

Figure 1
<p>Assessment of the genetic damage indicator (GDI) in human PBMCs. The mean values of DNA damage, quantified as arbitrary units using the in vivo Comet assay, were determined in both the unchallenged and SN-challenged groups. (<b>A</b>) the unchallenged group and (<b>B</b>) the SN-challenged group. The ‘C’ designation corresponds to the control group treated exclusively with PBS. The designation ‘C Oo’ corresponds to the control solely treated with olive oil. The designations ‘C 0.2’, ‘C 0.5’, ‘C 1’, ‘C 2’, and ‘C 3’ correspond to olive oil treatment and the respective lemon essential oil concentrations (0.2: 0.2%, 0.5: 0.5%, 1: 1%, 2: 2% and 3: 3%). ‘SN’ signifies the group subjected solely to SN treatment. The designation ‘SN Oo’ corresponds to the SN treated exclusively with olive oil. The tested groups are distinguished by abbreviations denoting the constituent ingredient (LEO: lemon essential oil) and the respective lemon essential oil concentrations (0.2: 0.2%, 0.5: 0.5%, 1: 1%, 2: 2%, and 15: 15%). The single asterisk stands for significant differences between the olive oil treatment and LEO treatment of 0.2%. The double asterisk stands for significant differences between the olive oil and LEO treatments of 0.5%, 1%, 2% and 3%. The triple asterisk stands for significant differences between the control treatment and all LEO treatments. The error bars represent standard errors.</p>
Full article ">Figure 2
<p>Illustration of the SN treatment process: 14 slides were used in this setup. After collecting a blood sample via finger prick, the gel matrix was treated with various treatments. The first contained only PBS, the second olive oil (OO), and the third to the seventh contained different concentrations of lemon essential oil (LEO) combined with OO. The eighth slide held a combination of PBS and SN, the ninth a combination of OO and SN, and the remaining slides accommodated a blend of OO, SN, and distinct lemon essential oil concentrations (0.2%, 0.5%, 1%, 2%, and 3%). All slides followed conventional procedures involving lysis and electrophoresis.</p>
Full article ">
9 pages, 2382 KiB  
Case Report
Leptomeningeal Carcinomatosis in Early Gastric Cancer: A Case Report and Literature Review
by Alessio Lucarini, Giulia Arrivi, Elena Liotta, Francesco Saverio Li Causi, Leonardo Di Cicco, Federica Mazzuca, Mattia Falchetto Osti, Genoveffa Balducci and Paolo Mercantini
Healthcare 2024, 12(12), 1184; https://doi.org/10.3390/healthcare12121184 (registering DOI) - 12 Jun 2024
Abstract
Leptomeningeal carcinomatosis (LC) is a rare site of metastasis in solid tumors, and it is associated with poor prognosis due to disabling symptoms and a scarcity of treatment options. This condition is an uncommon entity in gastric cancer (GC). We present a case [...] Read more.
Leptomeningeal carcinomatosis (LC) is a rare site of metastasis in solid tumors, and it is associated with poor prognosis due to disabling symptoms and a scarcity of treatment options. This condition is an uncommon entity in gastric cancer (GC). We present a case of primary LC manifestation in a patient with an incidental diagnosis of localized node-negative GC. We additionally perform a literature review and discuss the diagnostic and therapeutic challenges. In conclusion, LC from GC represents a rare condition with a dramatic prognosis. Its diagnosis might be very challenging. A multidisciplinary approach appears to be the best strategy for the management of LC from GC. Full article
Show Figures

Figure 1

Figure 1
<p>Brain MRI.</p>
Full article ">Figure 2
<p>Lumbar MRI.</p>
Full article ">Figure 3
<p>Abdominal CT.</p>
Full article ">
23 pages, 5916 KiB  
Article
Chemical Behavior and Bioactive Properties of Spinorphin Conjugated to 5,5′-Dimethyl- and 5,5′-Diphenylhydantoin Analogs
by Stela Georgieva, Petar Todorov, Jana Tchekalarova, Subaer Subaer, Petia Peneva, Kalin Chakarov, Hartati Hartati and Sitti Faika
Pharmaceuticals 2024, 17(6), 770; https://doi.org/10.3390/ph17060770 (registering DOI) - 12 Jun 2024
Abstract
The discovery of new peptides and their derivatives is an outcome of ongoing efforts to identify a peptide with significant biological activity for effective usage as a possible therapeutic agent. Spinorphin peptides have been documented to exhibit numerous applications and features. In this [...] Read more.
The discovery of new peptides and their derivatives is an outcome of ongoing efforts to identify a peptide with significant biological activity for effective usage as a possible therapeutic agent. Spinorphin peptides have been documented to exhibit numerous applications and features. In this study, biologically active peptide derivatives based on novel peptide analogues of spinorphin conjugated with 5,5′-dimethyl (Dm) and 5,5′-diphenyl (Ph) hydantoin derivatives have been successfully synthesized and characterized. Scanning electron microscopy (SEM) and spectral methods such as UV-Vis, FT-IR (Fourier Transform Infrared Spectroscopy), CD (Circular Dichroism), and fluorimetry were used to characterize the microstructure of the resulting compounds. The results revealed changes in peptide morphology as a result of the restructuring of the aminoacidic sequences and aromatic bonds, which is related to the formation of intermolecular hydrogen bonds between tyrosyl groups and the hydantoin moiety. Electrochemical and fluorescence approaches were used to determine some physicochemical parameters related to the biological behavior of the compounds. The biological properties of the spinorphin derivatives were evaluated in vivo for anticonvulsant activity against the psychomotor seizures at different doses of the studied peptides. Both spinorphin analog peptides with Ph and Dm groups showed activity against all three phases of the seizure in the intravenous Pentylenetetrazole Seizure (ivPTZ) test. This suggests that hydantoin residues do not play a crucial role in the structure of spinorphin compounds and in determining the potency to raise the seizure threshold. On the other hand, analogs with a phenytoin residue are active against the drug-resistant epilepsy test (6-Hz test). In addition, bioactivity analyses revealed that the new peptide analogues have the potential to be used as antimicrobial and antioxidant compounds. These findings suggest promising avenues for further research that may lead to the development of alternative medicines or applications in various fields beyond epilepsy treatment. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>FTIR spectrum of peptides S and its analogous: (<b>A</b>) Ph-S, Ph-S5, and Ph-S6 and (<b>B</b>) Dm-S, Dm-S5, and Dm-S6 showing the bands of amides I, II, and III.</p>
Full article ">Figure 2
<p>CD spectra between 190 and 250 nm of the studied hydantoin ring-conjugated peptide derivatives.</p>
Full article ">Figure 3
<p>SEM images at a scale bar of 5 µm of (<b>a</b>) S, (<b>b</b>) Dm-S, (<b>c</b>) Dm-S5, (<b>d</b>) Dm-S6, (<b>e</b>) Ph-S, and (<b>f</b>) Ph-S5.</p>
Full article ">Figure 4
<p>Plot of pH vs. V<sub>NaOH</sub> of 12 µmol hybrid peptides. Dashed lines are tangent to corresponding sections of titration curves to define corresponding distances relevant to determination of isoelectric points and acid-base constants.</p>
Full article ">Figure 5
<p>UV-Vis spectra of solutions of peptide derivatives at concentrations: S (C<sub>S</sub> = 1.584 × 10<sup>−3</sup> mol L<sup>−1</sup>); Dm-S (C<sub>Dm-S</sub> = 1.353 × 10<sup>−3</sup> mol L<sup>−1</sup> ); Dm-S5 (C<sub>Dm-S5</sub> = 1.335 × 10<sup>−3</sup> mol L<sup>−1</sup>); Dm-S6 (C<sub>Dm-S6</sub> = 1.387 × 10<sup>−3</sup> mol L<sup>−1</sup>); Ph-S (C<sub>Ph-S</sub> = 1.230 × 10<sup>−3</sup> mol L<sup>−1</sup>); Ph-S5 (C<sub>Ph-S5</sub> = 1.469 × 10<sup>−3</sup> mol L<sup>−1</sup>); Ph-S6 (C<sub>Ph-S6</sub> = 1.160 × 10<sup>−3</sup> mol L<sup>−1</sup>); inserted graphic represents the first-derivative spectra of the same peptides.</p>
Full article ">Figure 6
<p>Fluorescence spectra of the studied peptide compounds at different concentrations obtained after distribution in two phases: organic: 1-octanol and aqua: phosphate buffer (NaH<sub>2</sub>PO<sub>4</sub>/Na<sub>2</sub>HPO<sub>4</sub>, pH 7.41 ± 0.01).</p>
Full article ">Figure 7
<p>DPP voltamperograms of the test compounds in phosphate buffer solution and concentrations: S (C<sub>S</sub> = 1.584 × 10<sup>−5</sup> mol L<sup>−1</sup>); Dm-S (C<sub>Dm-S</sub> = 1.353 × 10<sup>−5</sup> mol L<sup>−1</sup> ); Dm-S5(C<sub>Dm-S5</sub> = 1.335 × 10<sup>−5</sup> mol L<sup>−1</sup>); Dm-S6 (C<sub>Dm-S6</sub> = 1.387 × 10<sup>−5</sup>mol L<sup>−1</sup>); Ph-S (C <sub>Ph-S</sub> = 1.230 × 10<sup>−5</sup> mol L<sup>−1</sup>); Ph-S5 (C<sub>Ph-S5</sub> = 1.469 × 10<sup>−5</sup> mol L<sup>−1</sup>); Ph-S6(C <sub>Ph-S6</sub> = 1.160 × 10<sup>−5</sup> mol L<sup>−1</sup>); GC electrode as working electrode, Ag/AgCl as a reference electrode.</p>
Full article ">Figure 8
<p>DPP signals of the studied compounds at 40 °C and different incubation times.</p>
Full article ">Figure 9
<p>Effect of Dm-S, Dm-S5, and Dm-S6 compounds on the threshold for myoclonic (<b>A</b>), clonic (<b>B</b>), and tonic (<b>C</b>) seizures induced by intravenous pentylenetetrazol (ivPTZ) in mice. Each bar represents the mean (mg/kg PTZ) + S.E.M. Statistical analyses were performed using Student’s <span class="html-italic">t</span> test. * <span class="html-italic">p</span> ≤ 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 respectively, compared to control group.</p>
Full article ">Figure 10
<p>Effect of Ph-S, Ph-S5, and Ph-S6 compounds on the threshold for myoclonic (<b>A</b>), clonic (<b>B</b>), and tonic (<b>C</b>) seizures induced by intravenous pentylenetetrazol (ivPTZ) in mice. Each bar represents the mean (mg/kg PTZ) + S.E (standard error). Statistical analyses were performed using Student’s <span class="html-italic">t</span> test. * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001, respectively, compared to control group.</p>
Full article ">Figure 11
<p>Graphic of the diameter of the inhibitory zone of peptides against (<b>A</b>) <span class="html-italic">S. aureus</span> bacteria, (<b>B</b>) <span class="html-italic">E. coli</span> bacteria, and (<b>C</b>) <span class="html-italic">B. cereus</span> bacteria. Each bar represents the mean + S.E (standard error); negative control: 10%DMSO; positive control: 10 g of chloramphenicol on the paper disc.</p>
Full article ">Figure 12
<p>Diameter of the inhibitory zone of peptides against the fungus <span class="html-italic">Candida albicans</span>. Each bar represents the mean + S.E (standard error); negative control: 10% DMSO; positive control: nystatin (0.5 g) on the paper disc.</p>
Full article ">Figure 13
<p>Inhibitory activity of Dm-peptides against test bacteria; negative control: 10% DMSO; positive control: 10 g of chloramphenicol on the paper disc.</p>
Full article ">Figure 14
<p>Antioxidant activity of peptides. Each bar represents the mean + S.E.</p>
Full article ">Scheme 1
<p>Schematic pathway of SPPS–Fmoc strategy in synthesizing new 5,5′-dimethyl- and 5,5′-diphenylhydantoin-conjugated spinorphin derivatives.</p>
Full article ">
10 pages, 225 KiB  
Review
MicroRNA as Sepsis Biomarkers: A Comprehensive Review
by Khalid Bindayna
Int. J. Mol. Sci. 2024, 25(12), 6476; https://doi.org/10.3390/ijms25126476 (registering DOI) - 12 Jun 2024
Abstract
Sepsis, a life-threatening condition caused by the body’s dysregulated response to infection, presents a significant challenge in clinical management. Timely and accurate diagnosis is paramount for initiating appropriate interventions and improving patient outcomes. In recent years, there has been growing interest in identifying [...] Read more.
Sepsis, a life-threatening condition caused by the body’s dysregulated response to infection, presents a significant challenge in clinical management. Timely and accurate diagnosis is paramount for initiating appropriate interventions and improving patient outcomes. In recent years, there has been growing interest in identifying biomarkers that can aid in the early detection and prognostication of sepsis. MicroRNAs (miRNAs) have emerged as potential biomarkers for sepsis due to their involvement in the regulation of gene expression and their stability in various biological fluids, including blood. MiRNAs are small non-coding RNA molecules that play crucial roles in post-transcriptional gene regulation by binding to target messenger RNAs (mRNAs), leading to mRNA degradation or translational repression. The diagnostic and prognostic potential of miRNAs in sepsis stems from their ability to serve as sensitive and specific biomarkers reflective of the underlying pathophysiological processes. Compared to traditional biomarkers such as C-reactive protein (CRP) and procalcitonin (PCT), miRNAs offer several advantages, including their early and sustained elevation during sepsis, as well as their stability in stored samples, making them attractive candidates for clinical use. However, despite their promise, the clinical translation of miRNAs as sepsis biomarkers faces several challenges. These include the need for standardized sample collection and processing methods, the identification of optimal miRNA panels or signatures for differentiating sepsis from other inflammatory conditions, and the validation of findings across diverse patient populations and clinical settings. In conclusion, miRNAs hold great promise as diagnostic and prognostic biomarkers for sepsis, offering insights into the underlying molecular mechanisms and potential therapeutic targets. However, further research is needed to overcome existing challenges and realize the full clinical utility of miRNAs in improving sepsis outcomes. Full article
(This article belongs to the Special Issue Sepsis and Septic Shock: From Molecular Mechanisms to Novel Therapies)
13 pages, 363 KiB  
Article
Accordance of Registered Drug Packages with Guideline-Recommended Treatment Durations for Community-Acquired Pneumonia—A New Antibiotic Stewardship Target?
by Martina Prusac, Maja Ortner Hadziabdic, Doris Rusic and Darko Modun
Antibiotics 2024, 13(6), 546; https://doi.org/10.3390/antibiotics13060546 (registering DOI) - 12 Jun 2024
Abstract
In most countries, antibiotics for oral administration are put on the market in fixed packages. When there is no exact unit dispensing of antimicrobials, drug pack size may influence prescribers’ choice of treatment duration. The aim of this study was to investigate the [...] Read more.
In most countries, antibiotics for oral administration are put on the market in fixed packages. When there is no exact unit dispensing of antimicrobials, drug pack size may influence prescribers’ choice of treatment duration. The aim of this study was to investigate the accordance of approved antibiotic packages with national guidelines for the treatment of community-acquired pneumonia (CAP). For the purpose of this study, criteria were developed to determine the accordance of approved antibiotic packages for treating CAP (criteria), which are based on recommendations from national guidelines for treating CAP. Subsequently, the accordance of approved antibiotic packages with the number of antibiotic doses resulting from the specified criteria was determined. Of 39 identified therapeutic option-package size combinations, 11 were found to be matched (28.2%), meaning there were no leftover medication units after completing therapy, and 28 were mismatched combinations (71.8%), indicating that there were excess doses of antibiotics remaining at the end of therapy. The results of this research showed a significant non-accordance of the approved antibiotic packages with the national guidelines for the treatment of CAP and, consequently, the creation of a large amount of residues of unit doses of antibiotics in the community. Full article
Show Figures

Figure 1

Figure 1
<p>Study flowchart [<a href="#B7-antibiotics-13-00546" class="html-bibr">7</a>].</p>
Full article ">
15 pages, 1654 KiB  
Review
Leveraging Multi-Tissue, Single-Cell Atlases as Tools to Elucidate Shared Mechanisms of Immune-Mediated Inflammatory Diseases
by Anthony K. McLean, Gary Reynolds and Arthur G. Pratt
Biomedicines 2024, 12(6), 1297; https://doi.org/10.3390/biomedicines12061297 (registering DOI) - 12 Jun 2024
Abstract
The observation that certain therapeutic strategies for targeting inflammation benefit patients with distinct immune-mediated inflammatory diseases (IMIDs) is exemplified by the success of TNF blockade in conditions including rheumatoid arthritis, ulcerative colitis, and skin psoriasis, albeit only for subsets of individuals with each [...] Read more.
The observation that certain therapeutic strategies for targeting inflammation benefit patients with distinct immune-mediated inflammatory diseases (IMIDs) is exemplified by the success of TNF blockade in conditions including rheumatoid arthritis, ulcerative colitis, and skin psoriasis, albeit only for subsets of individuals with each condition. This suggests intersecting “nodes” in inflammatory networks at a molecular and cellular level may drive and/or maintain IMIDs, being “shared” between traditionally distinct diagnoses without mapping neatly to a single clinical phenotype. In line with this proposition, integrative tumour tissue analyses in oncology have highlighted novel cell states acting across diverse cancers, with important implications for precision medicine. Drawing upon advances in the oncology field, this narrative review will first summarise learnings from the Human Cell Atlas in health as a platform for interrogating IMID tissues. It will then review cross-disease studies to date that inform this endeavour before considering future directions in the field. Full article
Show Figures

Figure 1

Figure 1
<p>Learnings from Pan-cancer atlases. Summary of technologies, analyses and findings from pan-cancer, single-cell atlases of T cells [<a href="#B62-biomedicines-12-01297" class="html-bibr">62</a>,<a href="#B63-biomedicines-12-01297" class="html-bibr">63</a>], NK cells [<a href="#B64-biomedicines-12-01297" class="html-bibr">64</a>], myeloid cells [<a href="#B66-biomedicines-12-01297" class="html-bibr">66</a>], and stromal cells [<a href="#B67-biomedicines-12-01297" class="html-bibr">67</a>]. Green arrows (↑): upregulation; Red arrows (↓): downregulation. Myeloid cells” section of <a href="#biomedicines-12-01297-f001" class="html-fig">Figure 1</a> was reproduced from Cell, Vol 184, Cheng et al., A pan-cancer single-cell transcriptional atlas of tumour infiltrating myeloid cells, 792–809, Copyright (2021), with permission from Elsevier. Created with BioRender.com.</p>
Full article ">Figure 2
<p>Cross-tissue studies of IMIDs. Summary of shared cell states and pathological features from cross-tissue, single-cell atlases of macrophages [<a href="#B74-biomedicines-12-01297" class="html-bibr">74</a>], T cells [<a href="#B75-biomedicines-12-01297" class="html-bibr">75</a>], and fibroblasts [<a href="#B76-biomedicines-12-01297" class="html-bibr">76</a>] in IMIDs. Black, straight arrows: cell state transitions; Black, curved arrows: cell taxis; Black arrows with molecules: cytokine release; Red arrows: pro-inflammatory effects. Created with BioRender.com.</p>
Full article ">
14 pages, 1973 KiB  
Article
3D Chromatin Alteration by Disrupting β-Catenin/CBP Interaction Is Enriched with Insulin Signaling in Pancreatic Cancer
by Yufan Zhou, Zhijing He, Tian Li, Lavanya Choppavarapu, Xiaohui Hu, Ruifeng Cao, Gustavo W. Leone, Michael Kahn and Victor X. Jin
Cancers 2024, 16(12), 2202; https://doi.org/10.3390/cancers16122202 (registering DOI) - 12 Jun 2024
Abstract
The therapeutic potential of targeting the β-catenin/CBP interaction has been demonstrated in a variety of preclinical tumor models with a small molecule inhibitor, ICG-001, characterized as a β-catenin/CBP antagonist. Despite the high binding specificity of ICG-001 for the N-terminus of CBP, this β-catenin/CBP [...] Read more.
The therapeutic potential of targeting the β-catenin/CBP interaction has been demonstrated in a variety of preclinical tumor models with a small molecule inhibitor, ICG-001, characterized as a β-catenin/CBP antagonist. Despite the high binding specificity of ICG-001 for the N-terminus of CBP, this β-catenin/CBP antagonist exhibits pleiotropic effects. Our recent studies found global changes in three-dimensional (3D) chromatin architecture in response to disruption of the β-catenin/CBP interaction in pancreatic cancer cells. However, an understanding of how the functional crosstalk between the antagonist and the β-catenin/CBP interaction affects changes in 3D chromatin architecture and, thereby, gene expression and downstream effects remains to be elucidated. Here, we perform Hi-C analyses on canonical and patient-derived pancreatic cancer cells before and after treatment with ICG-001. In addition to global alteration of 3D chromatin domains, we unexpectedly identify insulin signaling genes enriched in the altered chromatin domains. We further demonstrate that the chromatin loops associated with insulin signaling genes are significantly weakened after ICG-001 treatment. We finally elicit the deletion of a looping of IRS1—a key insulin signaling gene—significantly impeding pancreatic cancer cell growth, indicating that looping-mediated insulin signaling might act as an oncogenic pathway to promote pancreatic cancer progression. Our work shows that targeting aberrant insulin chromatin looping in pancreatic cancer might provide a therapeutic benefit. Full article
Show Figures

Figure 1

Figure 1
<p>Cell growth curves and apoptosis analyses of pancreatic cancer cells during treatment with ICG-001. (<b>A</b>) Schematic view of experiments performed in this project. βcat: β-catenin; CBP: histone acetyltransferase cyclic AMP response element-binding protein-binding protein; P300: histone acetyltransferase P300; TCF: T-cell factor. (<b>B</b>) Time- and dose-dependent growth curves of PANC1 and PATC53 during ICG-001 treatment. (<b>C</b>) Cell migration assay for PANC1 and PATC53 in presence of 10 µM ICG-001. (<b>D</b>) Apoptosis analyses of pancreatic cancer cell lines PANC1 and PATC53 with ICG-001 treatment. *: samples <span class="html-italic">t</span>-test, <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 2
<p>Compartment changes following ICG-001 treatment in pancreatic cancer cells. (<b>A</b>) Heatmaps and C-scores of Hi-C data in PATC53 cells. (<b>B</b>) Illustration of compartment changes. (<b>C</b>) Percentage of compartment changes both in PANC1 and PATC53. (<b>D</b>) Enrichment of insulin signaling pathway with GSEA from genes located at regions with absolute values of C-score difference greater than 1.</p>
Full article ">Figure 3
<p>TADs and differentially expressed genes before and after ICG-001 treatment in pancreatic cancer cells. (<b>A</b>) Number of TADs in individual chromosomes in PANC1 and PATC53. (<b>B</b>) Sizes of TADs in PANC1 and PATC53. (<b>C</b>) Number of differential TADs in various shifted lengths of TAD boundaries upstream to TSS after ICG-001 treatment in PANC1 and PATC53. (<b>D</b>) Differentially expressed genes (DEGs) before and after ICG-001 treatment in PANC1 and PATC53 (n = 5667). (<b>E</b>) Venn diagram of DEGs in PANC1, PATC53, PATC50 and HPNE.</p>
Full article ">Figure 4
<p>Involvement of insulin signaling pathway in changes to 3D chromatin in pancreatic cancer cells. (<b>A</b>) Overview of insulin signaling pathway (ISP). Left: major key molecules in ISP. Right: list of ISP genes—genes with missing looping events after ICG-001 treatment in PANC1/PATC53 are highlighted with red background. (<b>B</b>) Comparison of compartment changes in ISP and Non-ISP in PANC1 and PATC53. Left column: C-score difference. Right column: number of compartment changes. * and **: Wilcoxon rank-sum test. ISP: genes of insulin signaling pathway. Non-ISP: genes not in insulin signaling pathway. (<b>C</b>) Number of differential TADs, in various shifted lengths of TAD boundaries upstream to TSS. *: paired samples <span class="html-italic">t</span>-test. ISP: genes of insulin signaling pathway. Non-ISP: genes not in insulin signaling pathway. (<b>D</b>) Number of genes of insulin signaling pathway with changed loops in PANC1 and PATC53. None to None: no looping events with or without ICG-001 treatment. Loop to Loop: having looping events with or without ICG-001 treatment. None to Loop: looping events gained after ICG-001 treatment. Loop to None: looping events lost after ICG-001 treatment.</p>
Full article ">Figure 5
<p>Loss of looping events after ICG-001 treatment in pancreatic cancer cells. (<b>A</b>) Loss of looping events of insulin signaling genes in PANC1 and PATC53. Loop: with looping events. None: without looping events. (<b>B</b>) Expression of genes with loss of looping events in insulin signaling pathway in PANC1 and PATC53. Red up arrow: up-regulated genes. Green down arrow: down-regulated genes. (<b>C</b>) The relative interaction frequencies of insulin signaling pathway genes in PANC1, identified by 3C-qPCR experiments. * and **: samples <span class="html-italic">t</span>-test, *: <span class="html-italic">p</span> &lt; 0.1, **: <span class="html-italic">p</span> &lt; 0.05. (<b>D</b>) The relative interaction frequencies of insulin signaling pathway genes in PATC53, identified by 3C-qPCR experiments. * and **: samples <span class="html-italic">t</span>-test, *: <span class="html-italic">p</span> &lt; 0.1, **: <span class="html-italic">p</span> &lt; 0.05. (<b>E</b>) Changes in TADs and looping events after ICG-001 treatment in PANC1 and PATC53. Up panel: TADs changes indicated by arrows. Down panel: looping events indicated by arcs. IRS1 gene body is highlighted with yellow. IRS1 30–130 K upstream to TSS is highlighted with blue.</p>
Full article ">Figure 6
<p>Functional characterization of IRS1 promoter–enhancer looping in PATC53 cells. (<b>A</b>) The design of CRISPR/Cas9-mediated deletion of the enhancer of IRS1. The primer pairs (F/R-out and F/R-in) were used to validate the deletion of the enhancer region. (<b>B</b>) Gel images of the PCR amplification of genomic DNA using primers inside or outside the enhancer region show the result of the enhancer deletion. Out of 73 clones, 2 clones show validated enhancer deletions. (<b>C</b>) The PCR products of the two clones (Del-01 and Del-02) were purified and Sanger sequencing was performed. Sequencing results represent the deletions induced by sgSite-01 and sgSite-02. (<b>D</b>) Quantitative PCR was performed to detect the mRNA expression levels of IRS1 in the enhancer deletion clones. (<b>E</b>) Three technical replicates of western blotting show the protein expression levels of IRS1 in the enhancer deletion clones. (<b>F</b>) The quantification of the protein expression of IRS1 in the enhancer deletion clones. (<b>G</b>) Cell growth curves show that the growth of clone Del-02 is significantly decreased compared with clone sgEmpty. *: <span class="html-italic">p</span> &lt; 0.1, **: <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">
22 pages, 11192 KiB  
Article
Identification and Characterization of Critical Processing Parameters in the Fabrication of Double-Emulsion Poly(lactic-co-glycolic) Acid Microparticles
by Elizabeth R. Bentley, Stacia Subick, Michael Pezzillo, Stephen C. Balmert, Aidan Herbert and Steven R. Little
Pharmaceutics 2024, 16(6), 796; https://doi.org/10.3390/pharmaceutics16060796 (registering DOI) - 12 Jun 2024
Abstract
In the past several decades, polymeric microparticles (MPs) have emerged as viable solutions to address the limitations of standard pharmaceuticals and their corresponding delivery methods. While there are many preclinical studies that utilize polymeric MPs as a delivery vehicle, there are limited FDA-approved [...] Read more.
In the past several decades, polymeric microparticles (MPs) have emerged as viable solutions to address the limitations of standard pharmaceuticals and their corresponding delivery methods. While there are many preclinical studies that utilize polymeric MPs as a delivery vehicle, there are limited FDA-approved products. One potential barrier to the clinical translation of these technologies is a lack of understanding with regard to the manufacturing process, hindering batch scale-up. To address this knowledge gap, we sought to first identify critical processing parameters in the manufacturing process of blank (no therapeutic drug) and protein-loaded double-emulsion poly(lactic-co-glycolic) acid MPs through a quality by design approach. We then utilized the design of experiments as a tool to systematically investigate the impact of these parameters on critical quality attributes (e.g., size, surface morphology, release kinetics, inner occlusion size, etc.) of blank and protein-loaded MPs. Our results elucidate that some of the most significant CPPs impacting many CQAs of double-emulsion MPs are those within the primary or single-emulsion process (e.g., inner aqueous phase volume, solvent volume, etc.) and their interactions. Furthermore, our results indicate that microparticle internal structure (e.g., inner occlusion size, interconnectivity, etc.) can heavily influence protein release kinetics from double-emulsion MPs, suggesting it is a crucial CQA to understand. Altogether, this study identifies several important considerations in the manufacturing and characterization of double-emulsion MPs, potentially enhancing their translation. Full article
(This article belongs to the Section Nanomedicine and Nanotechnology)
Show Figures

Figure 1

Figure 1
<p>Process diagram illustrating emulsion process and potential critical processing parameters in double-emulsion solvent evaporation microparticle fabrication. Critical processing parameters can exist in all steps of fabrication, including the primary emulsion (W/O), secondary emulsion (W/O/W), and solvent evaporation steps.</p>
Full article ">Figure 2
<p>Single-factor plots demonstrating the significant relationship between microparticle size and significant critical processing parameters (<span class="html-italic">p</span> &lt; 0.05), including (Parameter A) inner aqueous phase volume (<span class="html-italic">n</span> = 200), (Parameter B) solvent volume (<span class="html-italic">n</span> = 200), (Parameter C) PLGA amount (<span class="html-italic">n</span> = 200), (Parameter E) homogenization time (<span class="html-italic">n</span> = 200), and (Parameter F) concentration of surfactant in the outer aqueous phase (<span class="html-italic">n</span> = 200). The black solid line represents the expected trend, and the blue dotted line illustrates the confidence bands for that trend, as predicted by the RSM.</p>
Full article ">Figure 3
<p>Aqueous phase volume (μL) and solvent volume (mL) interact to impact microparticle size. (<b>A</b>) A 3D surface (left) and contour plot (right) illustrating the overall trends of the impact of aqueous phase volume and solvent volume on microparticle size. (<b>B</b>) Model and experimental data examining size trends at specific levels of aqueous phase volume and solvent volume. Other preparation conditions for these batches are as follows: 200 mg of polymer, 3000 rpm homogenization speed, 1 min homogenization time, 600 rpm stirring speed, 55% sonication amplitude, 2% outer aqueous phase concentration, and 3 h solvent evaporation. * Indicates significant difference in microparticle size (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 4
<p>Solvent volume (mL) and polymer amount (mg) interact to impact microparticle size. (<b>A</b>) A 3D surface (<b>left</b>) and contour plot (<b>right</b>) illustrating overall trends of the impact of polymer and solvent volume on microparticle size. (<b>B</b>) Model and experimental data examining size trends at specific levels of polymer amount and solvent volume. Other preparation conditions for these batches are as follows: 200 μL inner aqueous phase volume, 3000 rpm homogenization speed, 1 min homogenization time, 600 rpm stirring speed, 55% sonication amplitude, 2% outer aqueous phase concentration, and 3 h solvent evaporation. * Indicates significant difference in microparticle size (<span class="html-italic">p</span> &lt; 0.05). ns indicates non-significant difference in microparticle size.</p>
Full article ">Figure 5
<p>Interaction between inner aqueous phase volume and solvent volume impacts release and internal structure of rhCCL22-MPs. (<b>A</b>) Cumulative release (ng rhCCL22/mg MP) profiles of rhCCL22-MPs formulated with each inner aqueous phase volume (200, 500, and 800 μL) at each solvent volume (2, 4, and 8 mL) (<span class="html-italic">n</span> = 3). (<b>B</b>) Scanning electron microscopy (SEM) images of microparticle cross-sections. SEM images taken at 1.5 kx. Scale bar = 10 μm. (<b>C</b>) Diagram depicting features of microparticle internal structure and associated measurements. (<b>D</b>) Microparticle inner occlusion diameter (μm) and polymer matrix composition (% polymer) measurements (<span class="html-italic">n</span> = 3–4). Other preparation conditions for these batches are as follows: 200 mg of PLGA, 3000 rpm homogenization speed, 1 min homogenization time, 55% sonication amplitude, 600 rpm stirring speed, 2% outer aqueous phase concentration, and 3 h solvent evaporation. * <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, ns indicates non-significant difference.</p>
Full article ">Figure 6
<p>Interaction between polymer amount and solvent volume impacts release kinetics and internal structure of rhCCL22-MPs. (<b>A</b>) Cumulative release (%) profiles of rhCCL22-MPs formulated with each polymer amount (200, 400, and 600 mg) at each solvent volume (2, 4, and 8 mL) (<span class="html-italic">n</span> = 3). (<b>B</b>) Scanning electron microscopy (SEM) images of microparticle cross-sections. SEM images taken at 1.5 kx. Scale bar = 10 μm. (<b>C</b>) Microparticle inner occlusion diameter (μm) and polymer matrix composition (% polymer) measurements (<span class="html-italic">n</span> = 3–4). Other preparation conditions for these batches are as follows: 200 μL IA phase volume, 3000 rpm homogenization speed, 1 min homogenization time, 55% sonication amplitude, 600 rpm stirring speed, 2% outer aqueous phase concentration, and 3 h solvent evaporation. * <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, ns indicates non-significant difference.</p>
Full article ">Figure 7
<p>Interaction between solvent volume and polymer amount impacts rhCCL22 release kinetics. Cumulative rhCCL22 release (ng rhCCL22/mg MP) from microparticles formulated with (<b>A</b>) 2 mL and (<b>B</b>) 4 mL of solvent. Other preparation conditions for these batches are as follows: 3000 rpm homogenization speed, 1 min homogenization time, 55% sonication amplitude, 600 rpm stirring speed, 2% outer aqueous phase concentration, and 3 h solvent evaporation.</p>
Full article ">Figure 8
<p>Formulations A, B, and C exhibit some similarities and differences in CQAs. (<b>A</b>) Cumulative release curves (ng rhCCL22/mg MP) for formulations A, B, and C. (<b>B</b>) Scanning electron microscopy images demonstrating spherical surface morphology. Images were taken at 1.2 kx. Scale bars = 10 μm. (<b>C</b>) Volume-weighted size distributions of formulations A, B, and C. <span class="html-italic">n</span> = 10,000 particles. Data from formulation A (control) adapted from Fisher et al., <span class="html-italic">Sci. Adv</span>. (2019). [<a href="#B22-pharmaceutics-16-00796" class="html-bibr">22</a>].</p>
Full article ">
15 pages, 1963 KiB  
Review
Unraveling the Immune Regulatory Functions of USP5: Implications for Disease Therapy
by Jinyi Gu, Changshun Chen, Pu He, Yunjie Du and Bingdong Zhu
Biomolecules 2024, 14(6), 683; https://doi.org/10.3390/biom14060683 (registering DOI) - 12 Jun 2024
Abstract
Ubiquitin-specific protease 5 (USP5) belongs to the ubiquitin-specific protease (USP) family, which uniquely recognizes unanchored polyubiquitin chains to maintain the homeostasis of monoubiquitin chains. USP5 participates in a wide range of cellular processes by specifically cleaving isopeptide bonds between ubiquitin and substrate proteins [...] Read more.
Ubiquitin-specific protease 5 (USP5) belongs to the ubiquitin-specific protease (USP) family, which uniquely recognizes unanchored polyubiquitin chains to maintain the homeostasis of monoubiquitin chains. USP5 participates in a wide range of cellular processes by specifically cleaving isopeptide bonds between ubiquitin and substrate proteins or ubiquitin itself. In the process of immune regulation, USP5 affects important cellular signaling pathways, such as NF-κB, Wnt/β-catenin, and IFN, by regulating ubiquitin-dependent protein degradation. These pathways play important roles in immune regulation and inflammatory responses. In addition, USP5 regulates the activity and function of immunomodulatory signaling pathways via the deubiquitination of key proteins, thereby affecting the activity of immune cells and the regulation of immune responses. In the present review, the structure and function of USP5, its role in immune regulation, and the mechanism by which USP5 affects the development of diseases by regulating immune signaling pathways are comprehensively overviewed. In addition, we also introduce the latest research progress of targeting USP5 in the treatment of related diseases, calling for an interdisciplinary approach to explore the therapeutic potential of targeting USP5 in immune regulation. Full article
(This article belongs to the Special Issue Immune-Related Biomarkers II)
Show Figures

Figure 1

Figure 1
<p>Structure and function of USP5. (<b>A</b>): 3D structure schematic of USP5 (PDB ID: 3ihp) [<a href="#B2-biomolecules-14-00683" class="html-bibr">2</a>]. (<b>B</b>): deubiquitination function of USP5. a: USP5 specifically recognizes unanchored ubiquitin chains to maintain the homeostasis of the free ubiquitin pool. b: USP5 specifically removes target protein ubiquitin modification to maintain protein homeostasis and signal transduction in cells. (<b>C</b>): ubiquitin-binding domains of USP5. (<b>D</b>): four ubiquitin-binding sites of USP5. Created using Figdraw.com (<a href="https://www.figdraw.com" target="_blank">https://www.figdraw.com</a>, accessed on 8 June 2004).</p>
Full article ">Figure 2
<p>USP5 participates in immune regulation through a variety of signaling pathways. (<b>A</b>): knockdown of USP5, which allows the competitive binding of accumulated unanchored polyubiquitin and inhibits proteasomal recognition sites on P53, thereby inhibiting the proteasomal-mediated degradation of p53 and increasing its transcriptional activity to negatively regulate p53-related pathways. (<b>B</b>): Smurf1 interacts with USP5, promotes the degradation of USP5 through the ubiquitin protease pathway, and reduces the protein expression of USP5, thereby inhibiting the production of TNF-α. On the other hand, USP5 physically interacts with Smurf1 and inhibits the expression of IFN-activated antiviral genes by decreasing the level of polyubiquitination of Smurf1 and enhancing the stability and turnover capacity of Smurf1. (<b>C</b>): USP5 bridges STUB1 to RIG-I and promotes the formation of the K48-linked ubiquitin chains on RIG-I, thus facilitating the degradation of RIG-I and inhibiting type I IFN signaling. (<b>D</b>): USP5 selectively promotes K48-linked NLRP3 polyubiquitination by recruiting the E3 ligases MARCHF7 and mediates its degradation via the autophagy lysosome pathway. (<b>E</b>): USP5 enhances the stability of MLL5, HIF2α, β-catenin, FoxM1, PD-L1, and other proteins via deubiquitination. (<b>F</b>): On the one hand, USP5 interacts with IKKβ and prevents IKKβ ubiquitination, which in turn inhibits the NF-κB signaling pathway; on the other hand, USP5 promotes the NF-κB signaling pathway by deubiquitinating TRAF6. Created using Figdraw.com (<a href="https://www.figdraw.com" target="_blank">https://www.figdraw.com</a>, accessed on 8 June 2004).</p>
Full article ">
25 pages, 2633 KiB  
Review
Emerging Roles of Xanthine Oxidoreductase in Chronic Kidney Disease
by Hunter W. Korsmo, Ubong S. Ekperikpe and Ilse S. Daehn
Antioxidants 2024, 13(6), 712; https://doi.org/10.3390/antiox13060712 (registering DOI) - 12 Jun 2024
Abstract
Xanthine Oxidoreductase (XOR) is a ubiquitous, essential enzyme responsible for the terminal steps of purine catabolism, ultimately producing uric acid that is eliminated by the kidneys. XOR is also a physiological source of superoxide ion, hydrogen peroxide, and nitric oxide, which can function [...] Read more.
Xanthine Oxidoreductase (XOR) is a ubiquitous, essential enzyme responsible for the terminal steps of purine catabolism, ultimately producing uric acid that is eliminated by the kidneys. XOR is also a physiological source of superoxide ion, hydrogen peroxide, and nitric oxide, which can function as second messengers in the activation of various physiological pathways, as well as contribute to the development and the progression of chronic conditions including kidney diseases, which are increasing in prevalence worldwide. XOR activity can promote oxidative distress, endothelial dysfunction, and inflammation through the biological effects of reactive oxygen species; nitric oxide and uric acid are the major products of XOR activity. However, the complex relationship of these reactions in disease settings has long been debated, and the environmental influences and genetics remain largely unknown. In this review, we give an overview of the biochemistry, biology, environmental, and current clinical impact of XOR in the kidney. Finally, we highlight recent genetic studies linking XOR and risk for kidney disease, igniting enthusiasm for future biomarker development and novel therapeutic approaches targeting XOR. Full article
Show Figures

Figure 1

Figure 1
<p><b>Terminal Steps of Purine Catabolism Mediated by XOR.</b> Purines are predominantly metabolized to hypoxanthine, which is subsequently oxidized to xanthine and further to UA. Inhibitors at various steps are indicated (Blue), and purine mimetics have off-target effects (Blue, thin print). The pseudogenized human UOX previously produced allantoin (Grey). Uricase therapy (Green) can promote this pathway in humans. XOR, xanthine oxidoreductase; XDH, xanthine dehydrogenase; XO, xanthine oxidase; UA, uric acid; ASL, adenine succinate lyase; ASS, adenine succinate synthase; NAD(H), nicotinamide adenine dinucleotide; PP<sub>i</sub>, inorganic pyrophosphate; UOX, urate oxidase.</p>
Full article ">Figure 2
<p><b>XOR Impacts Endothelial Structure &amp; Function.</b> XOR is released by multiple sources, predominantly the liver. Upon release, XOR enters the vasculature and binds to the extracellular GAG-rich glycocalyx produced by endothelial cells. Inset: XOR can contribute to the breakdown of the glycocalyx initiate endothelial activation and promote intracellular ROS production. XOR can also be endocytosed following glycocalyx binding, which may impact endothelial cell function. Additionally, XOR functions to uncouple eNOS, inhibiting NO production, and instigating ONOO- formation. eNOS, endothelial nitric oxide synthase; GAG, glycosaminoglycan; ROS, reactive oxygen species; XOR, xanthine oxidoreductase; ONOO-, peroxynitrite.</p>
Full article ">Figure 3
<p><b>XOR’s Influence on Driving CKD.</b> XOR directly contributes to CKD by increasing oxidative distress and the production of UA. Subsequently, XOR contributes to glomerular endothelial cell dysfunction, inflammation, and fibrosis. Genetic predisposition, environmental factors such as diet and heat, and aging can also contribute to total circulating XOR and renal pathogeneses. CVD, cardiovascular disease; GFR, glomerular filtration rate; MAFLD, metabolic-associated fatty liver disease; PKD, polycystic kidney disease; ROS, reactive oxygen species; UA, uric acid.</p>
Full article ">
20 pages, 1694 KiB  
Review
Dynamic Changes in Ion Channels during Myocardial Infarction and Therapeutic Challenges
by Tongtong Song, Wenting Hui, Min Huang, Yan Guo, Meiyi Yu, Xiaoyu Yang, Yanqing Liu and Xia Chen
Int. J. Mol. Sci. 2024, 25(12), 6467; https://doi.org/10.3390/ijms25126467 (registering DOI) - 12 Jun 2024
Abstract
In different areas of the heart, action potential waveforms differ due to differences in the expressions of sodium, calcium, and potassium channels. One of the characteristics of myocardial infarction (MI) is an imbalance in oxygen supply and demand, leading to ion imbalance. After [...] Read more.
In different areas of the heart, action potential waveforms differ due to differences in the expressions of sodium, calcium, and potassium channels. One of the characteristics of myocardial infarction (MI) is an imbalance in oxygen supply and demand, leading to ion imbalance. After MI, the regulation and expression levels of K+, Ca2+, and Na+ ion channels in cardiomyocytes are altered, which affects the regularity of cardiac rhythm and leads to myocardial injury. Myocardial fibroblasts are the main effector cells in the process of MI repair. The ion channels of myocardial fibroblasts play an important role in the process of MI. At the same time, a large number of ion channels are expressed in immune cells, which play an important role by regulating the in- and outflow of ions to complete intracellular signal transduction. Ion channels are widely distributed in a variety of cells and are attractive targets for drug development. This article reviews the changes in different ion channels after MI and the therapeutic drugs for these channels. We analyze the complex molecular mechanisms behind myocardial ion channel regulation and the challenges in ion channel drug therapy. Full article
(This article belongs to the Special Issue Research Progress on the Mechanism and Treatment of Cardiomyopathy)
Show Figures

Figure 1

Figure 1
<p>Voltage-gated Ca<sup>2+</sup> channel structure. The subunit consists of four homologous domains (I–IV) [<a href="#B35-ijms-25-06467" class="html-bibr">35</a>,<a href="#B36-ijms-25-06467" class="html-bibr">36</a>,<a href="#B37-ijms-25-06467" class="html-bibr">37</a>,<a href="#B38-ijms-25-06467" class="html-bibr">38</a>,<a href="#B39-ijms-25-06467" class="html-bibr">39</a>]. The five-subunit complex that forms high-voltage-activated Ca<sup>2+</sup> channels is illustrated with a central pore-forming α1 subunit, a disulfide-linked glycoprotein dimer of α2 and δ subunits, an intracellular β subunit, and a transmembrane glycoprotein γ subunit [<a href="#B40-ijms-25-06467" class="html-bibr">40</a>]. Each domain contains six transmembrane helices (S1–S6) [<a href="#B41-ijms-25-06467" class="html-bibr">41</a>].</p>
Full article ">Figure 2
<p>Ion channel subtypes involved in ion current remodeling after myocardial infarction. LTCC: L-type Ca<sup>2+</sup> channel, Cav1.4: Ca<sup>2+</sup> voltage-gated channel 1.4, TREK-1: TWIK-related K<sup>+</sup> channel 1, BKCa: large-conductance Ca<sup>2+</sup>-activated K<sup>+</sup> channel, KATP: ATP-sensitive K<sup>+</sup> channel, Kv1.3: voltage-gated K<sup>+</sup> channels 1.3, IKCa: intermedia-conductance Ca<sup>2+</sup>-activated K<sup>+</sup> channel, AP: action potential, APD: action potential duration, Nav1.5: Na<sup>+</sup> voltage-gated channel 1.5, TRPC6: transient receptor potential cation channel 6, TRPM4: transient receptor potential cation channel subfamily M member 4, TRPM7: transient receptor potential cation channel subfamily M member 7, TRPM8: transient receptor potential cation channel subfamily M member 8, TRPV1: transient receptor potential cation channel subfamily V member 1, TRPV4: transient receptor potential cation channel subfamily V member 4, PIEZO1: piezo-type mechanosensitive ion channel component 1.</p>
Full article ">Figure 3
<p>Drugs for ion channel therapy after MI. DHP: dihydropyridine; non-DHP: non-dihydropyridine.</p>
Full article ">
23 pages, 7876 KiB  
Article
Deciphering Early and Progressive Molecular Signatures in Alzheimer’s Disease through Integrated Longitudinal Proteomic and Pathway Analysis in a Rodent Model
by Hamad Yadikar, Mubeen A. Ansari, Mohamed Abu-Farha, Shibu Joseph, Betty T. Thomas and Fahd Al-Mulla
Int. J. Mol. Sci. 2024, 25(12), 6469; https://doi.org/10.3390/ijms25126469 (registering DOI) - 12 Jun 2024
Abstract
Alzheimer’s disease (AD), the leading cause of dementia worldwide, remains a challenge due to its complex origin and degenerative character. The need for accurate biomarkers and treatment targets hinders early identification and intervention. To fill this gap, we used a novel longitudinal proteome [...] Read more.
Alzheimer’s disease (AD), the leading cause of dementia worldwide, remains a challenge due to its complex origin and degenerative character. The need for accurate biomarkers and treatment targets hinders early identification and intervention. To fill this gap, we used a novel longitudinal proteome methodology to examine the temporal development of molecular alterations in the cortex of an intracerebroventricular streptozotocin (ICV-STZ)-induced AD mouse model for disease initiation and progression at one, three-, and six-weeks post-treatment. Week 1 revealed metabolic protein downregulation, such as Aldoa and Pgk1. Week 3 showed increased Synapsin-1, and week 6 showed cytoskeletal protein alterations like Vimentin. The biological pathways, upstream regulators, and functional effects of proteome alterations were dissected using advanced bioinformatics methods, including Ingenuity Pathway Analysis (IPA) and machine learning algorithms. We identified Mitochondrial Dysfunction, Synaptic Vesicle Pathway, and Neuroinflammation Signaling as disease-causing pathways. Huntington’s Disease Signaling and Synaptogenesis Signaling were stimulated while Glutamate Receptor and Calcium Signaling were repressed. IPA also found molecular connections between PPARGC1B and AGT, which are involved in myelination and possible neoplastic processes, and MTOR and AR, which imply mechanistic involvements beyond neurodegeneration. These results help us comprehend AD’s molecular foundation and demonstrate the promise of focused proteomic techniques to uncover new biomarkers and therapeutic targets for AD, enabling personalized medicine. Full article
(This article belongs to the Section Molecular Neurobiology)
Show Figures

Figure 1

Figure 1
<p>Schematic overview of the experimental workflow for the longitudinal proteomic analysis in an Alzheimer’s disease rodent model. (<b>A</b>) Schematic timeline of the experimental setup. Rats were divided into two groups: one receiving intracerebroventricular (ICV) administration of vehicle (ICVV) and the other receiving streptozotocin (ICV-STZ) to induce Alzheimer ’s-like pathology. The timeline includes three key time points: the start, week 1, week 3, and week 6 post-administration. At each time point, rats were sacrificed, and prefrontal cortex (PFC) tissues were collected. Each group consisted of 10 rats (n = 10 for ICVV and ICV-STZ). (<b>B</b>) workflow of sample processing and analysis. Post-cortex isolation using a stereotaxic apparatus, tissues were homogenized and lysed. The proteins were then digested into peptides through trypsinization. Peptides underwent cleanup using C<sub>18</sub> columns and were concentrated. The prepared samples were analyzed using two mass spectrometry techniques: label-free quantification data-dependent acquisition (LFQ-DDA-MS/MS) for broad proteomic profiling and label-free data-independent acquisition (LFQ-DIA-MS/MS) for targeted quantification. The bioinformatics analysis included generating volcano plots to identify significantly altered proteins, hierarchical clustering for pattern recognition, and pathway analysis to elucidate the molecular mechanisms underlying observed proteomic changes. This approach facilitates the identification of temporal proteomic alterations and the discovery of potential biomarkers and therapeutic targets for Alzheimer’s disease.</p>
Full article ">Figure 2
<p>Differential proteomic profiling across time points in an ICV-STZ AD rodent model. Panels (<b>A</b>–<b>C</b>) represent volcano plots displaying the log2 fold change of protein expressions in the cortex of rats induced with Alzheimer’s pathology using intracerebroventricular streptozotocin (ICV-STZ) at weeks 1, 3, and 6, respectively, against their corresponding controls (ICVV). The x-axis shows log2 fold change between groups, and the y-axis represents the negative log10 of the adjusted <span class="html-italic">p</span>-value, indicating the significance of the change. Red dots indicate proteins with a statistically significant increase in expression, blue dots represent a significant decrease, and gray dots denote proteins with no significant change. Panels (<b>D</b>–<b>F</b>) juxtapose the same time points (weeks 1, 3, and 6 post-ICV-STZ administration) directly against each other to highlight the temporal progression of proteomic alterations. Panels (<b>G</b>–<b>I</b>) are scatter plots comparing the log2 fold changes between two time points, illustrating the correlation of proteomic changes for the disease model. In all scatter plots, the red line indicates the unity line, where equal expression changes between the time points would lie. Green dots above the line indicate a more significant fold change at the later time point (e.g., week 3 vs. week 1), while blue dots below the line indicate a more significant fold change at the earlier time point. Each dot in the volcano plot is annotated with the protein identifier and the fold change value where space allows. Proteins were considered significantly altered with a fold change threshold set at two and an adjusted <span class="html-italic">p</span>-value of less than 0.05.</p>
Full article ">Figure 3
<p>Dynamic Proteomic Patterns in a Streptozotocin-Induced Alzheimer’s Disease Rodent Model Over Time. Panel (<b>A</b>) displays an UpSet plot for proteins with enriched abundance, indicating the number and intersections of proteins upregulated at weeks 1, 3, and 6 post-ICV-STZ administration. Panel (<b>B</b>) shows an UpSet plot for proteins with reduced abundance, highlighting the count and intersection points of downregulated proteins at the corresponding time points. Panel (<b>C</b>) presents a Venn diagram detailing the overlap and unique counts of significantly altered proteins at each time point, illustrating the study’s progression and changes in protein expression. Panel (<b>D</b>) demonstrates a protein rank abundance plot, ranking proteins by their abundance in the study and annotating those of particular interest.</p>
Full article ">Figure 4
<p>Violin plots representing the distribution of log2-transformed intensity values for selected proteins. Each plot corresponds to a specific protein, with individual points denoting replicate measurements—colored as red for replicate 1, orange for replicate 2, and blue for replicate 3. Gray shapes indicate the overall distribution of values, while colored points reflect observed data; the absence of a colored dot indicates imputed data points for missing values. Asterisks (*) in the figure indicate statistical significance between the conditions compared (<span class="html-italic">p</span> &lt; 0.05). Statistical significance was determined using ANOVA followed by post-hoc analysis for multiple comparisons.</p>
Full article ">Figure 5
<p>Hierarchical Clustering and Differential Expression Analysis in an STZ-Induced Alzheimer’s Model. Panel (<b>A</b>) presents a heatmap coupled with hierarchical clustering, showing proteins’ z-score normalized expression levels across six experimental groups, denoted by color coding at the top: ICV-STZ treated (1, 3, and 6 weeks) and their corresponding controls. Each row represents a different protein, while each column represents an experimental replicate—the clustering dendrograms on axes group proteins and replicates based on expression similarities. Panel (<b>B</b>) details a dot plot showing selected proteins’ log2 fold change (Log2FC) at each time point. Circle size indicates the relative fold change in abundance, and color coding signifies the adjusted <span class="html-italic">p</span>-value, with a smaller <span class="html-italic">p</span>-value represented by a darker shade. The statistical significance cutoff was set at an adjusted <span class="html-italic">p</span>-value of &lt;0.05.</p>
Full article ">Figure 6
<p>Gene Ontology and Pathway Enrichment Analysis in STZ-Induced Alzheimer’s Disease Model. Panel (<b>A</b>) represents the enriched Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in the 1-week post-treatment group. The x-axis displays the −log10 (<span class="html-italic">p</span>-value) for the most significant GO terms in the categories of molecular function (GO: MF, blue), cellular component (GO: CC, red), and biological process (GO: BP, green), along with KEGG pathway analysis (purple). Panel (<b>B</b>) shows similar enrichment analysis results for the 3-week post-treatment group. Panel (<b>C</b>) depicts the analysis for the 6-week post-treatment group, highlighting the most significant terms and pathways at this later stage. Bars extend rightward from the y-axis corresponding to their −log10 (<span class="html-italic">p</span>-value), indicating the significant level of enrichment for each term or pathway, with longer bars representing higher significance. The analyses elucidate the evolving biological context of the disease model over time, identifying critical molecular and cellular processes affected during the progression of Alzheimer’s-like pathology induced by STZ.</p>
Full article ">Figure 7
<p>Ingenuity Pathway Analysis (IPA) of Molecular and Cellular Functions Altered in an STZ-Induced Alzheimer’s Disease Model Utilizing Machine Learning. Panels (<b>A</b>–<b>C</b>) illustrate the IPA-derived network analyses at 1, 3, and 6 weeks post-intracerebroventricular STZ administration, highlighting vital biological functions and diseases with the predicted activation (orange) or inhibition (blue) states based on the expression data. The graphical summary legend details the nature of the molecular relationships, including direct and indirect interactions and predicted activations and inhibitions, inferred through machine learning algorithms from IPA. Panel (<b>D</b>) shows a histogram of the z-scores for the top disease and function annotations across the time points, with orange representing a positive z-score, blue a negative z-score, and gray indicating no activity pattern available. Panel (<b>E</b>) displays a heat map of the disease and function annotations, with the intensity of the color representing the degree of association as determined by IPA’s machine-learning analysis. This multifaceted approach elucidates the complex biological landscape of the disease model, predicting the activation state of various pathways and functions implicated in the disease’s progression.</p>
Full article ">
17 pages, 4695 KiB  
Article
Solid Lipid Nanoparticles Based on Babassu Oil and Copaiba Oleoresin: A Promising Approach for Prostate Cancer Therapy
by Michael Jackson Ferreira da Silva, Alisson Mendes Rodrigues, Maria Célia Pires Costa, Adriana Leandro Camara, Lucio Mendes Cabral, Eduardo Ricci Junior, Daniel Figueiredo Vanzan, Ana Paula dos Santos Matos, Thiago da Silva Honorio and Antonio Carlos Romão Borges
Nanomaterials 2024, 14(12), 1014; https://doi.org/10.3390/nano14121014 (registering DOI) - 12 Jun 2024
Abstract
Solid lipid nanoparticles (SLNs) represent promising nanostructures for drug delivery systems. This study successfully synthesized SLNs containing different proportions of babassu oil (BBS) and copaiba oleoresin (COPA) via the emulsification–ultrasonication method. Before SLN synthesis, the identification and quantification of methyl esters, such as [...] Read more.
Solid lipid nanoparticles (SLNs) represent promising nanostructures for drug delivery systems. This study successfully synthesized SLNs containing different proportions of babassu oil (BBS) and copaiba oleoresin (COPA) via the emulsification–ultrasonication method. Before SLN synthesis, the identification and quantification of methyl esters, such as lauric acid and β-caryophyllene, were performed via GC-MS analysis. These methyl esters were used as chemical markers and assisted in encapsulation efficiency experiments. A 22 factorial design with a center point was employed to assess the impact of stearic acid and Tween 80 on particle hydrodynamic diameter (HD) and polydispersity index (PDI). Additionally, the effects of temperature (8 ± 0.5 °C and 25 ± 1.0 °C) and time (0, 7, 15, 30, 40, and 60 days) on HD and PDI values were investigated. Zeta potential (ZP) measurements were utilized to evaluate nanoparticle stability, while transmission electron microscopy provided insights into the morphology and nanometric dimensions of the SLNs. The in vitro cytotoxic activity of the SLNs (10 µg/mL, 30 µg/mL, 40 µg/mL, and 80 µg/mL) was evaluated using the MTT assay with PC-3 and DU-145 prostate cancer cell lines. Results demonstrated that SLNs containing BBS and COPA in a 1:1 ratio exhibited a promising cytotoxic effect against prostate cancer cells, with a percentage of viable cells of 68.5% for PC-3 at a concentration of 30 µg/mL and 48% for DU-145 at a concentration of 80 µg/mL. These findings underscore the potential therapeutic applications of SLNs loaded with BBS and COPA for prostate cancer treatment. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>(<b>A</b>) babassu oil and (<b>B</b>) copaiba oleoresin.</p>
Full article ">Figure 2
<p>Schematic of the experimental procedure used to prepare the SLNs studied in this work.</p>
Full article ">Figure 3
<p>GC-MS spectra obtained from (<b>a</b>) BBS and (<b>b</b>) COPA.</p>
Full article ">Figure 4
<p>2D response surface graphs obtained from the experimental design applied to the (<b>A</b>) HD and (<b>B</b>) PDI.</p>
Full article ">Figure 5
<p>Effect of time and temperature on HD values of SLNs with (SLN-BBS-COPA-RT, SLN-BBS-COPA-UR) and without (SLN-W-RT and SLN-W-UR) natural bioactives.</p>
Full article ">Figure 6
<p>Effect of time and temperature on PDI values of SLN with (SLN-BBS-COPA-RT, SLN-BBS-COPA-UR) and without natural bioactives (SLN-W-RT and SLN-W-UR).</p>
Full article ">Figure 7
<p><math display="inline"><semantics> <mrow> <mi>ξ</mi> </mrow> </semantics></math> measurements of the SLN-BBS-COPA-UR at different times (0, 7, and 30 days).</p>
Full article ">Figure 8
<p>TEM images acquired from (<b>A</b>) SLN-BBS-COPA and (<b>B</b>) SLN-W samples.</p>
Full article ">Figure 9
<p>GC-MS spectrum of SLN-BBS-COPA.</p>
Full article ">Figure 10
<p>Cell viability of the PC-3 line in different concentrations of SLN-BBS-COPA, SLN-BBS, SLN-COPA, SLN-W, BBS, COPA, BBS + COPA, and free drug (flutamide) after 24 h of exposure. The red line indicates 70% cell viability according to ISO:10993-5 [<a href="#B57-nanomaterials-14-01014" class="html-bibr">57</a>].</p>
Full article ">Figure 11
<p>Cell viability of the DU-145 line in different concentrations of SLN-BBS-COPA, SLN-BBS, SLN-COPA, SLN-W, BBS, COPA, BBS + COPA and free drug (flutamide) after 24 h of exposure. The red line indicates 70% cell viability according to ISO:10993-5 [<a href="#B57-nanomaterials-14-01014" class="html-bibr">57</a>].</p>
Full article ">
12 pages, 3160 KiB  
Review
Nano-Delivery of Immunogenic Cell Death Inducers and Immune Checkpoint Blockade Agents: Single-Nanostructure Strategies for Enhancing Immunotherapy
by Yujeong Moon, Hanhee Cho and Kwangmeyung Kim
Pharmaceutics 2024, 16(6), 795; https://doi.org/10.3390/pharmaceutics16060795 (registering DOI) - 12 Jun 2024
Abstract
Cancer immunotherapy has revolutionized oncology by harnessing the patient’s immune system to target and eliminate cancer cells. However, immune checkpoint blockades (ICBs) face limitations such as low response rates, particularly in immunologically ‘cold’ tumors. Enhancing tumor immunogenicity through immunogenic cell death (ICD) inducers [...] Read more.
Cancer immunotherapy has revolutionized oncology by harnessing the patient’s immune system to target and eliminate cancer cells. However, immune checkpoint blockades (ICBs) face limitations such as low response rates, particularly in immunologically ‘cold’ tumors. Enhancing tumor immunogenicity through immunogenic cell death (ICD) inducers and advanced drug delivery systems represents a promising solution. This review discusses the development and application of various nanocarriers, including polymeric nanoparticles, liposomes, peptide-based nanoparticles, and inorganic nanoparticles, designed to deliver ICD inducers and ICBs effectively. These nanocarriers improve therapeutic outcomes by converting cold tumors into hot tumors, thus enhancing immune responses and reducing systemic toxicity. By focusing on single-nanoparticle systems that co-deliver both ICD inducers and ICBs, this review highlights their potential in achieving higher drug concentrations at tumor sites, improving pharmacokinetics and pharmacodynamics, and facilitating clinical translation. Future research should aim to optimize these nanocarrier systems for better in vivo performance and clinical applications, ultimately advancing cancer immunotherapy. Full article
(This article belongs to the Special Issue Nanomedicines in Cancer Therapy)
Show Figures

Figure 1

Figure 1
<p>Schematic illustration of the action mechanism of nanoparticles encapsulating ICD and ICB agents in cancer immunotherapy.</p>
Full article ">Figure 2
<p>(<b>A</b>) Preparation of DOX/P-12-encapsulated cell-penetration peptide octaarginine (R8) conjugated lipid/PLGA nanoparticles and their mechanism of action. (<b>B</b>) TEM images of LPN (<b>top</b>) and LPN-30-R8<sup>2k</sup> (<b>bottom</b>) with hydrodynamic volumes of 100 nm and 125 nm, respectively. (<b>C</b>) Enhanced cellular uptake of LPN-30-R8<sup>2k</sup>@DP in CT26 cells compared to LPN@DP. (<b>D</b>) Expression of CRT as DAMPs due to DOX release from LPN-30-R8<sup>2k</sup>@DP. (<b>E</b>) Improved tumor targeting efficiency of LPN-30-R8<sup>2k</sup>@DP via passive targeting in CT26-tumor bearing mice. The white dashed line indicates the location of the tumor. (<b>F</b>) Enhanced tumor growth suppression using LPN-30-R8<sup>2k</sup>@DP compared to other groups with a dosage of 3 mg dox/kg and 5 mg P-12/kg. (<b>G</b>) CD8<sup>+</sup> T cell staining in excised tumor tissue from the LPN-30-R8<sup>2k</sup>@DP treated group. The student’s <span class="html-italic">t</span>-test was applied for statistical significance. (* <span class="html-italic">p</span> &lt; 0.05). Reproduced with permission [<a href="#B55-pharmaceutics-16-00795" class="html-bibr">55</a>]. Copyright: ACS publications, 2022.</p>
Full article ">Figure 3
<p>(<b>A</b>) Preparation of DOX/IDO1-encapsulated liposomes surface-modified with CD44 and PD-L1 aptamers, and their mode of action. (<b>B</b>) The size of the nanostructures confirmed by DLS and TEM images with an average size of 183 nm. (<b>C</b>) Released DOX from the liposomes induced ATP release as DAMPs in MDA-MB-231 cells. (<b>D</b>) Aptm[DOX/IDO1] demonstrated enhanced tumor targeting in 4T1-tumor-bearing mice compared to Lipm[DOX/IDO1], due to a dual-targeting mechanism via passive and active targeting. (<b>E</b>) Effective tumor suppression was observed in the Aptm[DOX/IDO1]-treated group in the 4T1 tumor xenograft model. (<b>F</b>) Immune activation was evident in the excised tumor tissue from the Aptm[DOX/IDO1]-treated group. One-way analysis of variance (ANOVA) with Dunnett’s test was applied for statistical significance (* <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.005). Reproduced with permission [<a href="#B58-pharmaceutics-16-00795" class="html-bibr">58</a>]. Copyright: Elsevier, 2022.</p>
Full article ">Figure 4
<p>(<b>A</b>) Preparation of self-assembled peptide-derived prodrug nanoparticles capable of releasing DOX in the presence of cathepsin B. (<b>B</b>) The size of the self-assembled nanoparticles was confirmed by DLS and TEM with an average size of 157.4 ± 12.1 nm, while no particle formation was observed in the presence of cathepsin B. (<b>C</b>) CRT expression was observed as DAMPs due to the specific release of DOX in 4T1 cancer cells. (<b>D</b>) Enhanced tumor-targeting efficiency of nanoparticles via the EPR effect in the 4T1 tumor xenograft model at 150–200 mm<sup>3</sup> volume. (<b>E</b>) Improved tumor suppression due to the release of DOX and PD-L1 blockade peptide with a dosage of 3 mg DOX/kg. (<b>F</b>) Immune analysis (CD8<sup>+</sup> cytotoxic T cell, regulatory T cell) of excised tumor tissue following tumor suppression evaluation. Reproduced with permission [<a href="#B61-pharmaceutics-16-00795" class="html-bibr">61</a>]. One-way analysis of variance (ANOVA) with Tukey-Kramer <span class="html-italic">posthoc</span> test was applied for statistical significance (** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.005). Copyright: Ivyspring international Publisher, 2022.</p>
Full article ">
Back to TopTop