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13 pages, 2291 KiB  
Article
Long COVID in ARDS Survivors: Insights from a Two-Year-Follow-Up Study After the First Wave of the Pandemic
by Judit Aranda, Isabel Oriol, Núria Vázquez, Karim Ramos, Romina Concepción Suárez, Lucía Feria, Judith Peñafiel, Ana Coloma, Beatriz Borjabad, Raquel Clivillé, Montserrat Vacas and Jordi Carratalà
J. Clin. Med. 2025, 14(6), 1852; https://doi.org/10.3390/jcm14061852 - 10 Mar 2025
Viewed by 68
Abstract
Objectives: To compare the health status, exercise capacity, and health-related quality of life (HRQoL) in survivors of COVID-19-associated acute respiratory distress syndrome (ARDS) at 8, 12, and 24 months post-diagnosis. Methods: We conducted a prospective, single-center follow-up study embedded within a larger multicenter [...] Read more.
Objectives: To compare the health status, exercise capacity, and health-related quality of life (HRQoL) in survivors of COVID-19-associated acute respiratory distress syndrome (ARDS) at 8, 12, and 24 months post-diagnosis. Methods: We conducted a prospective, single-center follow-up study embedded within a larger multicenter cohort of adults with COVID-19 who required hospital admission. Eligible participants underwent clinical interviews, physical examinations, chest radiography, and the 6-min walk test (6MWT). Standardized scales were used to assess post-traumatic stress disorder (PTSD), anxiety, depression, and HRQoL. Results: Out of 1295 patients with COVID-19, 365 developed ARDS, of whom 166 survived. After excluding deaths and loss to follow-up, 95 patients were monitored for 24 months. Over 60% of patients had persistent symptoms, though significant improvements were recorded in quality of life and physical recovery. More than 70% recovered their previous physical capacity, but 15% did not return to their usual lifestyle habits. Symptoms such as arthralgia and fatigue decreased, but cognitive issues, such as memory loss and insomnia, persisted. Radiological improvements were noted, although pulmonary function remained impaired. The prevalence of PTSD and anxiety decreased, while depression remained stable at around 30%. Conclusions: Long COVID continues to impose significant physical, mental, and social challenges. Symptoms like fatigue and anxiety have a profound impact on daily life. Strategies are urgently needed to help patients regain health and resume their normal lives. Full article
(This article belongs to the Special Issue Post-COVID Symptoms and Causes, 3rd Edition)
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<p>Interventions conducted during 8-, 12- and 24-month follow-up visits.</p>
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<p>Flowchart illustrating the selection process of patients for the study.</p>
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<p>Mean SF36 mental health dimension scores of COVID-19 survivors with ARDS shown by sex in different age groups.</p>
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<p>Mean SF36 physical health dimension scores of COVID-19 survivors with ARDS shown by sex in different age groups.</p>
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15 pages, 3240 KiB  
Article
Therapeutic Effects of TN13 Peptide on Acute Respiratory Distress Syndrome and Sepsis Models In Vivo
by Jae-Eun Byun, Jae-Won Lee, Eun Ji Choi, Juhyun Lee, Seok Han Yun, Chan Ho Park, Hanna Kim, Mi Sun Kim, Suk Ran Yoon, Tae-Don Kim, Ji-Yoon Noh, Sang-Hyun Min, Hyun-A. Seong, Kyung-Seop Ahn, Inpyo Choi and Haiyoung Jung
J. Clin. Med. 2025, 14(6), 1804; https://doi.org/10.3390/jcm14061804 - 7 Mar 2025
Viewed by 221
Abstract
Background/Objectives: Regulation of acute inflammatory responses is crucial for host mortality and morbidity induced by pathogens. The pathogenesis of acute respiratory distress syndrome (ARDS) and sepsis are associated with systemic inflammation. p38 MAPK is a crucial regulator of inflammatory responses and is a [...] Read more.
Background/Objectives: Regulation of acute inflammatory responses is crucial for host mortality and morbidity induced by pathogens. The pathogenesis of acute respiratory distress syndrome (ARDS) and sepsis are associated with systemic inflammation. p38 MAPK is a crucial regulator of inflammatory responses and is a potential target for acute inflammatory diseases, including ARDS and sepsis. We investigated the therapeutic effects of the TAT-TN13 peptide (TN13) on severe inflammatory diseases, including ARDS and sepsis, in vivo. Methods: To establish the ARDS model, C57BL/6 mice were intranasally (i.n.) administered lipopolysaccharide (LPS; 5 mg/kg, 40 µL) to induce lung inflammation. As a positive control, dexamethasone (DEX; 0.2 mg/kg) was administered intraperitoneally (i.n.) 1 h post-LPS exposure. In the experimental groups, TN13 was administered intranasally (i.n.) at doses of 2.5 mg or 5 mg/kg at the same time point. In the LPS-induced sepsis model, mice received an intraperitoneal injection of LPS (20 mg/kg) to induce systemic inflammation. TN13 (25 mg/kg, i.p.) was administered 1 h after LPS treatment. Control mice received phosphate-buffered saline (PBS). Lung histopathology, inflammatory cell infiltration, cytokine levels, and survival rates were assessed to evaluate TN13 efficacy. Results: TN13 significantly reduced inflammatory cell recruitment and cytokine production in the lungs, thereby mitigating LPS-induced ARDS. In the sepsis model, TN13 treatment improved survival rates by suppressing inflammatory responses. Mechanistically, TN13 exerted its effects by inhibiting the p38 MAPK/NF-κB signaling pathway. Conclusions: These results collectively suggested that TN13 could be an effective treatment option for severe inflammatory diseases. Full article
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<p>TN13 Peptide suppresses inflammation in A549 cells. (<b>A</b>,<b>B</b>) A549 cells were treated with various concentrations of LPS (<b>A</b>) or TN13 (<b>B</b>) for 24 h, and cell viability was assessed using the CCK-8 assay to evaluate cytotoxic effects. (<b>C</b>) Flow cytometry analysis was performed to examine the intracellular uptake of FITC-labeled TN13. (<b>D</b>) Western blot analysis was conducted to assess p38 MAPK phosphorylation following LPS treatment. (<b>E</b>) TN13 treatment was evaluated for its effect on LPS-induced phosphorylation of p38 MAPK. (<b>F</b>–<b>H</b>) The mRNA expression levels of key pro-inflammatory cytokines, including TNF-α (<b>F</b>), IL-1β (<b>G</b>), and IL-6 (<b>H</b>), were measured using quantitative real-time PCR. Data are presented as mean ± S.D. Statistical significance was determined using a two-tailed Student’s <span class="html-italic">t</span>-test, with ## <span class="html-italic">p</span> &lt; 0.01 compared to the control group and * <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 compared to the LPS-treated group. n.s: indicates no statistical significance.</p>
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<p>TN13 attenuates lung inflammation by reducing inflammatory cell infiltration in LPS-induced ARDS mice. (<b>A</b>) Experimental design and group composition: C57BL/6 mice (<span class="html-italic">n</span> = 5 per group) were randomly divided into the following five groups: Control: PBS only; LPS: ARDS induction with LPS (5 mg/kg, 40 µL, intranasal) only; Positive Control: LPS + dexamethasone (DEX, 0.2 mg/kg); Low-dose TN13: LPS + TN13 (2.5 mg/kg); and High-dose TN13: LPS + TN13 (5 mg/kg). LPS was administered on day 0, and TN13 or DEX was given intranasally 1 h post-LPS administration on days 0 and 1. Mice were sacrificed on day 2 for BALF collection and lung tissue harvesting. (<b>B</b>) Neutrophil and macrophage counts in BALF of mice were determined using Diff-Quik<sup>®</sup> staining and cell counting (magnification, ×400; scale bar, 25 µM). (<b>C</b>) H&amp;E staining in the lungs of mice (magnification, ×100; scale bar, 100 μm). Data are expressed as the mean ± SD. # <span class="html-italic">p</span> &lt; 0.05 vs. Ctrl; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. ARDS.</p>
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<p>TN13 suppresses pro-inflammatory cytokine production in the lungs of LPS-induced ARDS mice. (<b>A</b>) TNF-α, (<b>B</b>) IL-6, and (<b>C</b>) IL-1β in the BALF of mice were determined using ELISA. (<b>D</b>) The p38/NF-κB pathway-related proteins were determined by Western blot in ARDS lungs. Data are expressed as the mean ± SD. # <span class="html-italic">p</span> &lt; 0.05 vs. Ctrl; * <span class="html-italic">p</span> &lt; 0.05,** <span class="html-italic">p</span> &lt; 0.01 vs. ARDS.</p>
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<p>TN13 rescues mice from LPS-induced sepsis. (<b>A</b>) Experimental design of sepsis mouse model. Schematic illustration for routine i.p. of LPS stimulation (20 mg/kg) and treatment of TN13 (25 mg/kg) injection once a day a total of 2 times. (<b>B</b>) Mice body temperature change after LPS + PBS or LPS + TN13 injection (<span class="html-italic">n</span> = 10). Before, −1 h; after, +1 h; and recover, +24 h after TN13 (25 mg/kg) treatment, which was administered 1 h after LPS injection. (<b>C</b>) Mice survival over time LPS + PBS or LPS + TN13 injection (<span class="html-italic">n</span> = 10). Data are expressed as the mean ± SD. *** <span class="html-italic">p</span> &lt; 0.001 vs. before control.</p>
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<p>TN13 inhibits inflammatory responses in the sepsis mouse model. (<b>A</b>–<b>D</b>) Frequencies of neutrophil and macrophage in the spleen and peripheral blood of mice (<span class="html-italic">n</span> = 5). (<b>E</b>,<b>F</b>) Frequencies of activated macrophages (CD80+ cells) in the spleen and peripheral blood. Cells were analyzed by flow cytometry to determine their percentage. Data are mean ± S.D. (Statistical significance was determined using a two-tailed Student’s <span class="html-italic">t</span>-tests. # <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 vs. Ctrl; * <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 vs. LPS + PBS).</p>
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<p>TN13 downregulates inflammatory cytokine levels in lipopolysaccharide-induced sepsis mouse model. Secretions of cytokine TNF-α (<b>A</b>), IL-6 (<b>B</b>), and IL-1β (<b>C</b>) were determined in mice serum using ELISA (<span class="html-italic">n</span> = 10). Data are mean ± S.D. (Statistical significance was determined using a two-tailed Student’s <span class="html-italic">t</span>-tests. ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.001 vs. Ctrl; * <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 vs. LPS + PBS).</p>
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<p>TN13 inhibits the p38/NF-κB pathways in the sepsis mouse model. The expressions of the p38/NF-κB pathway-related protein were determined by Western blot in sepsis lung (<b>A</b>) and spleen (<b>B</b>).</p>
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21 pages, 4825 KiB  
Article
Burn-Related Glycocalyx Derangement and the Emerging Role of MMP8 in Syndecan Shedding
by Hannes Kühtreiber, Daniel Bormann, Melanie Salek, Lisa Auer, Thomas Haider, Caterina Selina Mildner, Marie-Therese Lingitz, Clemens Aigner, Christine Radtke, Daniel Zimpfer, Hendrik Jan Ankersmit and Michael Mildner
Biology 2025, 14(3), 269; https://doi.org/10.3390/biology14030269 - 6 Mar 2025
Viewed by 208
Abstract
Burn injuries often lead to severe complications, including acute respiratory distress syndrome (ARDS), driven in part by systemic inflammation and glycocalyx disruption. In this study, we analyzed the sera of 28 patients after burn trauma and utilized single-cell RNA sequencing (scRNA-seq) along with [...] Read more.
Burn injuries often lead to severe complications, including acute respiratory distress syndrome (ARDS), driven in part by systemic inflammation and glycocalyx disruption. In this study, we analyzed the sera of 28 patients after burn trauma and utilized single-cell RNA sequencing (scRNA-seq) along with microarray transcriptomic analysis to decipher the impact of burn injury on glycocalyx derangement. We observed the significant upregulation of immune cell-derived degrading enzymes, particularly matrix metalloproteinase-8 (MMP8), which correlated with increased immune cell infiltration and glycocalyx derangement. Serum analyses of burn patients revealed significantly elevated levels of shed glycocalyx components and MMP8, both correlating with the presence of inhalation injury. Consequently, the treatment of human in vitro lung tissue models with MMP8 induced significant glycocalyx shedding in alveolar epithelial cells. Together, based on these findings, we propose that MMP8 plays a previously unrecognized role in glycocalyx disruption and subsequent lung injury post-burn, which implies that inhibiting MMP8 may represent a promising therapeutic strategy for alleviating lung injury after burn trauma. Full article
(This article belongs to the Section Biochemistry and Molecular Biology)
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<p>Transcriptomics analysis revealing response of glycocalyx and degrading enzymes post-burn trauma. (<b>A</b>) UMAP of comprehensive scRNA-seq analysis identifying 12 unique cell clusters. (<b>B</b>) Feature Plots showing a glycocalyx module score (GMS), split by condition. (<b>C</b>) Feature Plots illustrating a degrading enzyme module score (DEMS). (<b>D</b>) Dot plot of individual glycocalyx constituents used for the GMS module score. (<b>E</b>) Dot plot of individual glycocalyx-degrading enzymes used for the DEMS module score. Dot size represents the expression percentage for each gene, with color intensity reflecting average gene expression levels. (<b>F</b>) Differentially expressed genes (DEGs) between control and burn groups. Significantly (log2FC &gt; 1, adj. <span class="html-italic">p</span> &lt; 0.05) upregulated genes in the burn group show a positive fold change (red), while those downregulated show a negative fold change (blue). (<b>G</b>) The top 8 ‘GO Biological Process 2023’ terms associated with significantly upregulated and downregulated DEGs. (<b>H</b>) The top 8 terms from a combined query of ‘KEGG 2021 Human’ and ‘Reactome 2022’. Results are displayed as dot plots with their respective combined scores and gene ratios.</p>
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<p>Serum levels of glycocalyx constituents and MMP8 together with SDC1 correlation in burn patients. Systemic levels of SDC1 (<b>A</b>), SDC4 (<b>B</b>), HA (<b>C</b>), HS (<b>D</b>), and MMP8 (<b>E</b>) were quantified in healthy controls and burn patients over a 21-day follow-up. Data analysis was performed using Kruskal–Wallis tests, complemented by Dunn’s multiple comparisons. Data are presented as minimum to maximum boxplots including all data points. Time points with statistical significance (adjusted <span class="html-italic">p</span>-value &lt; 0.05) are marked in red. (<b>F</b>) Pearson’s correlation analysis between MMP8 and SDC1 serum levels in burn patients over various time points, with R<sup>2</sup> values and corresponding <span class="html-italic">p</span>-values provided.</p>
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<p>Effects of MMP8 treatment on pulmonary glycocalyx in vitro. (<b>A</b>) UMAP representation of scRNA-seq analysis from healthy human lung tissue, identifying 14 distinct cell clusters. (<b>B</b>) Feature Plot displaying the glycocalyx module score (GMS) and (<b>C</b>) degrading enzyme module score (DEMS), calculated based on the gene sets outlined in <a href="#app1-biology-14-00269" class="html-app">Supplementary Figure S2 (Figure S2B,C)</a>. (<b>D</b>) Dot plot showing syndecan gene expression, with dot size indicating the percentage of expressing cells and color intensity reflecting average expression levels. (<b>E</b>) Immunofluorescence imaging of untreated and rhMMP8-treated EpiAlveolar™ 3D lung models, incorporating alveolar epithelial cells (EpiCs), fibroblasts (FBs), and endothelial cells (ECs). The 20× magnification images display DAPI-stained nuclei (blue) and SDC1 fluorescence (red). (<b>F</b>) ELISA-based quantitative analysis of SDC1, SDC4, and HA in EpiAlveolar™ model supernatants, with significant differences (<span class="html-italic">p</span> &lt; 0.05) marked in red. (<b>G</b>) SAECs treated with APMA, rhMMP8 alone, and activated rhMMP8, with SDC1, SDC4, and HA levels in supernatants analyzed via ELISA. Statistical significance was assessed using two-tailed unpaired <span class="html-italic">t</span>-tests and the Kruskal–Wallis test followed by Dunn’s multiple comparisons, with significant results (adj. <span class="html-italic">p</span> &lt; 0.05) highlighted in red.</p>
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26 pages, 5846 KiB  
Review
Managing Refractory Hypoxemia in Acute Respiratory Distress Syndrome Obese Patients with Veno-Venous Extra-Corporeal Membrane Oxygenation: A Narrative Review
by Arnaud Robert, Patrick M. Honoré, Pierre Bulpa and Isabelle Michaux
J. Clin. Med. 2025, 14(5), 1653; https://doi.org/10.3390/jcm14051653 - 28 Feb 2025
Viewed by 387
Abstract
Veno-venous extracorporeal membrane oxygenation (vvECMO) is a life-saving intervention for severe respiratory failure unresponsive to conventional therapies. However, managing refractory hypoxemia in morbidly obese patients poses significant challenges due to the unique physiological characteristics of this population, including hyperdynamic circulation, elevated cardiac output, [...] Read more.
Veno-venous extracorporeal membrane oxygenation (vvECMO) is a life-saving intervention for severe respiratory failure unresponsive to conventional therapies. However, managing refractory hypoxemia in morbidly obese patients poses significant challenges due to the unique physiological characteristics of this population, including hyperdynamic circulation, elevated cardiac output, and increased oxygen consumption. These factors can limit the effectiveness of vvECMO by diluting arterial oxygen content and complicating oxygen delivery. Refractory hypoxemia in obese patients supported by vvECMO often stems from an imbalance between ECMO blood flow and cardiac output. Hyperdynamic circulation exacerbates the recirculation of oxygenated blood and impairs the efficiency of oxygen transfer. To address these challenges, a stepwise, individualized approach is essential. Strategies to reduce oxygen consumption include deep sedation, neuromuscular blockade, and temperature control. Cardiac output modulation can be achieved through beta-blockers and cautious therapeutic hypothermia. Optimizing oxygen delivery involves improving residual lung function; high positive end-expiratory pressure ventilation guided by esophageal pressure monitoring; prone positioning; and adjustments to the ECMO circuit, such as using dual oxygenators, larger membranes, or additional drainage cannulas. This review highlights the interplay of physiological adaptations and technical innovations required to overcome the challenges of managing refractory hypoxemia in obese patients during vvECMO. By addressing the complexities of high cardiac output and obesity, clinicians can enhance the effectiveness of vvECMO and improve outcomes for this high-risk population. Full article
(This article belongs to the Special Issue Clinical Advances in Extracorporeal Membrane Oxygenation (ECMO))
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<p>Flowchart of stepwise management for refractory hypoxemia in ARDS vvECMO among obese patients.</p>
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19 pages, 1868 KiB  
Review
Patient-Self Inflicted Lung Injury (P-SILI): An Insight into the Pathophysiology of Lung Injury and Management
by Himanshu Deshwal, Ahmed Elkhapery, Rudra Ramanathan, Deepak Nair, Isha Singh, Ankur Sinha, Rishik Vashisht and Vikramjit Mukherjee
J. Clin. Med. 2025, 14(5), 1632; https://doi.org/10.3390/jcm14051632 - 27 Feb 2025
Viewed by 1180
Abstract
Acute respiratory distress syndrome (ARDS) is a heterogeneous group of disease entities that are associated with acute hypoxic respiratory failure and significant morbidity and mortality. With a better understanding and phenotyping of lung injury, novel pathophysiologic mechanisms demonstrate the impact of a patient’s [...] Read more.
Acute respiratory distress syndrome (ARDS) is a heterogeneous group of disease entities that are associated with acute hypoxic respiratory failure and significant morbidity and mortality. With a better understanding and phenotyping of lung injury, novel pathophysiologic mechanisms demonstrate the impact of a patient’s excessive spontaneous breathing effort on perpetuating lung injury. Patient self-inflicted lung injury (P-SILI) is a recently identified phenomenon that delves into the impact of spontaneous breathing on respiratory mechanics in patients with lung injury. While the studies are hypothesis-generating and have been demonstrated in animal and human studies, further clinical trials are needed to identify its impact on ARDS management. The purpose of this review article is to highlight the physiologic mechanisms of P-SILI, novel tools and methods to detect P-SILI, and to review the current literature on non-invasive and invasive respiratory management in patients with ARDS. Full article
(This article belongs to the Special Issue Acute Respiratory Failure: Innovations and Clinical Insights)
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<p>The pathophysiologic mechanism of P-SILI. (Created in BioRender. Hashem, A. (2025) <a href="https://BioRender.com/v70d189" target="_blank">https://BioRender.com/v70d189</a>, accessed on 20 February 2025).</p>
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<p>Management approach to acute hypoxic respiratory failure and P-SILI.</p>
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17 pages, 1233 KiB  
Article
Genetic Variants in Genes Related to Lung Function and Interstitial Lung Diseases Are Associated with Worse Outcomes in Severe COVID-19 and Lung Performance in the Post-COVID-19 Condition
by Ingrid Fricke-Galindo, Salvador García-Carmona, Brandon Bautista-Becerril, Gloria Pérez-Rubio, Ivette Buendia-Roldan, Leslie Chávez-Galán, Karol J. Nava-Quiroz, Jesús Alanis-Ponce, Juan M. Reséndiz-Hernández, Esther Blanco-Aguilar, Jessica I. Erives-Sedano, Yashohara Méndez-Velasco, Grecia E. Osuna-Espinoza, Fidel Salvador-Hernández, Rubén Segura-Castañeda, Uriel N. Solano-Candia and Ramcés Falfán-Valencia
Int. J. Mol. Sci. 2025, 26(5), 2046; https://doi.org/10.3390/ijms26052046 - 26 Feb 2025
Viewed by 421
Abstract
Genetic variants related to susceptibility to chronic respiratory conditions such as interstitial lung disease (ILD) could share critical pathways in the pathogenesis of COVID-19 and be implicated in COVID-19 outcomes and post-COVID-19. We aimed to identify the participation of genetic variants in lung [...] Read more.
Genetic variants related to susceptibility to chronic respiratory conditions such as interstitial lung disease (ILD) could share critical pathways in the pathogenesis of COVID-19 and be implicated in COVID-19 outcomes and post-COVID-19. We aimed to identify the participation of genetic variants in lung function and ILD genes in severe COVID-19 outcomes and post-COVID-19 condition. We studied 936 hospitalized patients with COVID-19. The requirement of invasive mechanical ventilation (IMV) and the acute respiratory distress syndrome (ARDS) classification were considered. The mortality was assessed as the in-hospital death. The post-COVID-19 group included 102 patients evaluated for pulmonary function tests four times during the year after discharge. Five variants (FAM13A rs2609255, DSP rs2076295, TOLLIP rs111521887, TERT rs2736100, and THSD4 rs872471) were genotyped using TaqMan assays. A multifactor dimensionality reduction method (MDR) was performed for epistasis estimation. The TERT rs2736100 and THSD4 rs872471 variants were associated with differential risk for ARDS severity (moderate vs. severe, CC + CA, p = 0.044, OR = 0.66, 95% CI = 0.44–0.99; and GG p = 0.034, OR = 2.22, 95% CI = 1.04–4.72, respectively). These variants and FAM13A rs2609255 were also related to pulmonary function post-COVID-19. The MDR analysis showed differential epistasis and correlation of the genetic variants included in this study. The well-known variants in recognized genes related to pulmonary function worsening and interstitial disorders are related to the severity and mortality of COVID-19 and lung performance in the post-COVID-19 condition. Full article
(This article belongs to the Special Issue Molecular Research and Insights into COVID-19: 2nd Edition)
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<p>Multifactor dimensionality reduction analysis for mortality in COVID-19. (<b>a</b>) Bar charts showing the distributions of the genotypes’ combinations, including the <span class="html-italic">DSP</span> rs2076295, <span class="html-italic">FAM13A</span> rs2609255, and <span class="html-italic">THSD4</span> rs872471 variants (for each graph, the left bars correspond to cases, and right bars to controls. 0, homozygous for the common allele; 1, heterozygous; 2, homozygous for the uncommon allele). High-risk genotypes can be observed in dark grey, and low-risk genotypes in light grey. (<b>b</b>) Gene–gene interaction graph. The red and orange colors indicate strong and moderate synergism; gold denotes no association or independence of selected loci effects; and blue indicates strong antagonism [<a href="#B29-ijms-26-02046" class="html-bibr">29</a>,<a href="#B30-ijms-26-02046" class="html-bibr">30</a>].</p>
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<p>Multifactor dimensionality reduction analysis for invasive mechanical ventilation requirement. (<b>a</b>) Bar charts showing the distributions of the genotypes’ combinations of the genetic variants included in this study (for each graph, the left bars correspond to cases, and the right bars to controls. 0, homozygous for the common allele; 1, heterozygous; 2, homozygous for the uncommon allele). High-risk genotypes can be observed in dark grey, and low-risk genotypes in light grey. (<b>b</b>) Gene–gene interaction graph. The red and orange colors indicate strong and moderate synergism; gold denotes no association or independence of selected loci effects [<a href="#B29-ijms-26-02046" class="html-bibr">29</a>,<a href="#B30-ijms-26-02046" class="html-bibr">30</a>].</p>
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<p>Multifactor dimensionality reduction analysis for acute respiratory distress syndrome severity in COVID-19 (moderate vs. severe). (<b>a</b>) Bar charts showing the distributions of the genotype combinations of the genetic variants included in this study (for each graph, the left bars correspond to cases, and the right bars to controls. 0, homozygous for the common allele; 1, heterozygous; 2, homozygous for the uncommon allele). High-risk genotypes can be observed in dark grey, and low-risk genotypes in light grey. (<b>b</b>) Gene–gene interaction graph. The red color indicates strong and moderate synergism; gold denotes no association or independence of selected loci effects; and green indicates moderate antagonism [<a href="#B29-ijms-26-02046" class="html-bibr">29</a>,<a href="#B30-ijms-26-02046" class="html-bibr">30</a>].</p>
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16 pages, 785 KiB  
Review
Exploring the Utility of Renal Resistive Index in Critical Care: Insights into ARDS and Cardiac Failure
by Giuseppe Cuttone, Giulio Geraci, Luigi La Via, Massimiliano Sorbello, Federico Pappalardo and Caterina Carollo
Biomedicines 2025, 13(2), 519; https://doi.org/10.3390/biomedicines13020519 - 19 Feb 2025
Viewed by 381
Abstract
The renal resistive index (RRI), a Doppler ultrasound-derived parameter measuring renal vascular resistance, has emerged as a promising non-invasive tool to evaluate renal hemodynamics in critically ill patients, particularly those with acute respiratory distress syndrome (ARDS) and heart failure (HF). This narrative review [...] Read more.
The renal resistive index (RRI), a Doppler ultrasound-derived parameter measuring renal vascular resistance, has emerged as a promising non-invasive tool to evaluate renal hemodynamics in critically ill patients, particularly those with acute respiratory distress syndrome (ARDS) and heart failure (HF). This narrative review examines the current evidence for RRI measurement in these conditions, exploring its physiological bases, methodology, clinical applications, and limitations. In ARDS, RRI reflects the complex interactions between positive pressure ventilation, hypoxemia, and systemic inflammation, showing a role in predicting acute kidney injury and monitoring response to interventions. In HF, RRI is able to assess venous congestion and cardiorenal interactions and can also serve as a prognostic indicator. Many studies have shown RRI’s superiority or complementarity to traditional biomarkers in predicting renal dysfunction, although its interpretation requires consideration of multiple patient-related factors. Key challenges include operator dependency, lack of standardization, and complex interpretation in multi-organ dysfunction. Future research should focus on measurement standardization, development of automated techniques, investigation of novel applications like intraparenchymal renal resistive index variation, and validation of RRI-guided management strategies. Despite its limitations, RRI represents a valuable tool that offers bedside and real-time insights into renal hemodynamics and potential guidance for therapeutic interventions. Further research is needed to fully clarify its clinical potential and address current limitations, particularly in critical care settings involving multiple organ dysfunction. Full article
(This article belongs to the Special Issue Kidney Diseases in Critical Ill Patients)
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<p>Evaluation of the renal resistive index using Doppler ultrasound. The transducer is placed in an interlobar artery, and the spectral Doppler examines the peak systolic and end-diastolic velocities.</p>
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13 pages, 1798 KiB  
Review
Circulating Nucleosomes and Histones in the Development of Lung Injury and Sepsis
by Saugata Dutta, Sauradeep Dutta, Payaningal R. Somanath, S. Priya Narayanan, Xiaoyun Wang and Duo Zhang
Curr. Issues Mol. Biol. 2025, 47(2), 133; https://doi.org/10.3390/cimb47020133 - 19 Feb 2025
Viewed by 599
Abstract
Cellular nucleosomes—the structural and functional units of chromatin—are inherently present in cells. During cellular damage or cell death, nucleosomes are released into circulation, either actively or passively. Once released, nucleosomes can become immunogenic entities through various mechanisms. The nucleosomal proteins in nucleosomes, called [...] Read more.
Cellular nucleosomes—the structural and functional units of chromatin—are inherently present in cells. During cellular damage or cell death, nucleosomes are released into circulation, either actively or passively. Once released, nucleosomes can become immunogenic entities through various mechanisms. The nucleosomal proteins in nucleosomes, called histones, play a pivotal role in inducing immunogenicity. However, intact nucleosomes are more immunogenic than the histones alone, as nucleosomal double-stranded deoxyribonucleic acid (dsDNA) enhances its immunogenic potential. Our recent study has shown that circulating histones are predominantly nucleosomal histones rather than free histones. Consequently, circulating histones primarily function as integral parts of circulating nucleosomes rather than acting independently. Circulating nucleosomes and their associated histones are implicated in the pathogenesis of a wide array of diseases. Notably, they are critical in the pathogenesis of lung injury and sepsis. These diseases have high morbidity and mortality rates and lack early diagnostic biomarkers. Further investigation is required to fully elucidate the role of circulating nucleosomes and their associated histones in disease processes. This review aims to discuss the current understanding of circulating nucleosomes and histones in the pathogenesis of lung injury and sepsis, with a focus on the underlying mechanisms. Full article
(This article belongs to the Collection Molecular Mechanisms in Human Diseases)
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<p>Schematic diagram of the structure of a nucleosome and its location in chromatin. Two copies of each histone H2A, H2B, H3, and H4 assemble to form the histone octamer, around which 145–147 bps (~1.7 turns) of DNA are wrapped. Thousands of nucleosomes collectively form chromatin, which appears as a “beads-on-a-string” structure. When further condensed, chromatin forms chromosomes.</p>
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<p>Schematic diagram of how nucleosomes are released from a dying cell. During apoptosis, the morphology of the cell is distorted and the cell membrane is ruptured. As a result, the nuclear and cytoplasmic contents of the dying cell are released. At this step, nucleosomes are released from the cell along with organelles and cellular debris.</p>
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<p>Schematic diagram illustrating how circulating nucleosomes promote inflammation in various organs and contribute to sepsis. The damaged organ releases a large number of nucleosomes into circulation. These circulating nucleosomes spread throughout the body and induce inflammation in vital organs. Ultimately, this cascade of inflammatory responses contributes to the development of sepsis.</p>
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<p>Schematic diagram of the process of NETosis. Pathogen exposure activates neutrophils. After activation, PAD4 citrullinates histones, which decondenses chromatin. As a result, neutrophil releases DNA fibers along with antimicrobial biomolecules including histones. These released DNA fibers form a web-like structure, called a neutrophil extracellular trap (NET). This process is called NETosis.</p>
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15 pages, 10107 KiB  
Article
Clinical Impact of Neutrophil Variation on COVID-19 Complications
by Khadija El Azhary, Bouchra Ghazi, Fadila Kouhen, Jalila El Bakkouri, Hasna Chamlal, Adil El Ghanmi and Abdallah Badou
Diagnostics 2025, 15(4), 457; https://doi.org/10.3390/diagnostics15040457 - 13 Feb 2025
Viewed by 341
Abstract
Background/Objectives: Corona virus disease 2019 (COVID-19) poses a threat to global public health. The early identification of critical cases is crucial to providing timely treatment to patients. Here, we investigated whether the neutrophil levels could predict COVID-19 complications. Methods: We performed [...] Read more.
Background/Objectives: Corona virus disease 2019 (COVID-19) poses a threat to global public health. The early identification of critical cases is crucial to providing timely treatment to patients. Here, we investigated whether the neutrophil levels could predict COVID-19 complications. Methods: We performed a retrospective study of patients with COVID-19, admitted to the Cheikh Khalifa International University Hospital, Casablanca, Morocco. Laboratory test results collected upon admission and during hospitalization were analyzed based on clinical information. Results: Our study revealed that a rise in neutrophil “PNN” levels was associated with respiratory deterioration and intubation. They were positively correlated with the procalcitonin and C-reactive protein levels. Interestingly, PNN (polynuclear neutrophil) levels on day 5 proved to be a better predictor of intubation, acute respiratory distress syndrome (ARDS), and mortality than the initial PNN counts, C-reactive protein, or procalcitonin. Moreover, binary logistic regression with stratified PNN-day 5 data revealed that a PNN level on day 5 > 7.7 (109/L) was an independent risk factor for mortality and ARDS. Finally, the PNN levels on day 5 and proinflammatory cytokine IL-6 were positively correlated. Conclusions: Our data showed that neutrophilia proved to be an excellent predictor of complications and mortality during hospitalization and could be used to improve the management of patients with COVID-19. Full article
(This article belongs to the Section Clinical Laboratory Medicine)
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<p><b>Evolution of blood immune cell counts depending on COVID-19 severity:</b> (<b>A</b>) initial white blood cells counts (<span class="html-italic">n</span> = 83 vs. 36) and(<b>B</b>) evolution of white blood cells (<span class="html-italic">n</span> = day 0 (83 vs. 36), day 5 (50 vs. 33), and day 10 (27 vs. 23)), (<b>C</b>) lymphocyte (<span class="html-italic">n</span> = day 0 (83 vs. 35), day 5 (50 vs. 32), and day 10 (27 vs. 22)), (<b>D</b>) neutrophil “PNN” (<span class="html-italic">n</span> = day 0 (82 vs. 36), day 5 (49 vs. 33), and day 10 (27 vs. 23)), (<b>E</b>) monocyte (<span class="html-italic">n</span> = day 0 (82 vs. 35), day 5 (50 vs. 33), and day 10 (27 vs. 22)), and (<b>F</b>) eosinophil “PNE” counts (<span class="html-italic">n</span> = day 0 (83 vs. 36), day 5 (50 vs. 33), and day 10 (27 vs. 22)) during the first 10 days of hospitalization in patients grouped into the “Mild–Moderate”(“M.M”) and “Severe–Critical”(“S.C”) groups. Data are represented as the median with range. Mann–Whitney U, Kruskal–Wallis, and Dunn’s multiple-comparison tests were performed. * <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. ns, non-significant.</p>
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<p><b>Correlation of variation in global white blood cells count and variation in the count of each cell type.</b> The variation was defined as the change in cell counts obtained between day 0 and day 5 of admission (delta = day 5 − day 0). Spearman rank correlation was performed for the white blood cells (WBCs) and (<b>A</b>) neutrophils (PNNs) (<span class="html-italic">n</span> = 80), (<b>B</b>) eosinophils (PNEs) (<span class="html-italic">n</span> = 81), (<b>C</b>) monocytes (<span class="html-italic">n</span> = 82), and (<b>D</b>) lymphocytes (<span class="html-italic">n</span> = 82).</p>
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<p><b>The increase in neutrophil counts associated with disease severity and the rise in inflammatory biomarkers</b>: (<b>A</b>) evolution of neutrophil(“PNN”) (<span class="html-italic">n</span> = day 0 (82 vs. 25), day 5 (49 vs. 23), day 10 (27 vs. 18), day 1 ((9 vs. 8), and day 20 (6 vs. 5)) count during the first 20 days of hospitalization in patients grouped into ICU and non-ICU categories; (<b>B</b>) variation in PNN (delta-PNN = PNN-day 5 − PNN-day 0) in ICU (<span class="html-italic">n</span> = 23) and non-ICU (<span class="html-italic">n</span> = 47) patients; and (<b>C</b>) correlation of variation in PNN (delta-PNN, <span class="html-italic">n</span> = 80) and variation in CRP (delta-CRP, <span class="html-italic">n</span> = 74) levels and (<b>D</b>) variation in procalcitonin (delta-PCT, <span class="html-italic">n</span> = 21). Data are represented as the median with range. Mann–Whitney U, Kruskal–Wallis, and Dunn’s multiple-comparison tests and Spearman rank correlation were performed. ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001. ns, non-significant.</p>
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<p><b>PNN on day 5 predicted complications during hospitalization.</b> ROC analyses using day 0 of PNN, CRP, PCT, delta-PNN, and the PNN on day 5 were performed: (<b>A</b>) mild–moderate (<span class="html-italic">n</span> = 37) and severe–critical (<span class="html-italic">n</span> = 29); (<b>B</b>) intubation (<span class="html-italic">n</span> = 14) or not (<span class="html-italic">n</span> = 50); (<b>C</b>) ARDS (<span class="html-italic">n</span> = 13) or not (<span class="html-italic">n</span> = 50); (<b>D</b>) hemodialysis (<span class="html-italic">n</span> = 6) or not (<span class="html-italic">n</span> = 58); and (<b>E</b>) area under the curve (AUC) with 95% confidence interval (CI).</p>
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<p><b>Neutrophil counts on day 5 associated with IL-6 levels and patient mortality</b>: (<b>A</b>) survival curves for COVID 19 with normal ((≤7500), <span class="html-italic">n</span> = 49) and high neutrophil counts ((&gt;7500), <span class="html-italic">n</span> = 9) on day 5; (<b>B</b>) ROC analysis using PNN on day 0, delta-PNN, and PNN on day 5 performed for death (<span class="html-italic">n</span> = 11) or not (<span class="html-italic">n</span> = 53); (<b>C</b>) evolution of PNN (<span class="html-italic">n</span> = day 0 (13 vs. 23), day 5 (11 vs. 22), and day 10 (9 vs. 14)) count during the first 10 days of hospitalization in patients grouped into death or non-death categories, respectively (represented as the median with range); (<b>D</b>) survival curves for severe–critical patients with normal ((≤7500), <span class="html-italic">n</span> = 29) and high neutrophil counts ((&gt;7500), <span class="html-italic">n</span> = 8) on day 5; (<b>E</b>) variation in PNN (delta-PNN = PNN-day 5 − PNN-day 0) in patients with mild disease who survived (MM, non-death) (<span class="html-italic">n</span> = 47), those with severe disease who also survived (SC, non-death) (<span class="html-italic">n</span> = 22), and those with severe disease who did not survive(SC, death) (<span class="html-italic">n</span> = 11); (<b>F</b>) PNN count on day 5 in patients with mild disease who survived (MM, non-death) (<span class="html-italic">n</span> = 49), those with severe disease who also survived (SC, non-death) (<span class="html-italic">n</span> = 22), and those with severe disease who did not survive (SC, death) (<span class="html-italic">n</span> = 11) (represented as the median with range); (<b>G</b>) correlation of variation in PNN on day 5 and initial IL-6 (<span class="html-italic">n</span> = 44) levels; and (<b>H</b>) PNN count in patients with IL-6 levels &gt;80 pg/mL on day 0 (<span class="html-italic">n</span> = 15) and on day 5 (<span class="html-italic">n</span> = 13) or &lt;80 pg/mL on day 0 (<span class="html-italic">n</span> = 27) and on day 5 (<span class="html-italic">n</span> = 24) (represented as the mean and standard deviation). Kruskal–Wallis and Dunn’s multiple-comparison tests were performed. * <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. ns, non-significant.</p>
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29 pages, 1367 KiB  
Review
SARS-CoV-2 and Coronaviruses: Understanding Transmission, Impact, and Strategies for Prevention and Treatment
by Seyede Nafise Tabatabaei, Zahra Keykhaee, Saghi Nooraei, Mohammad Amin Ayati, Mohammad Behzadmand, Saba Azimi, Fatemeh Eskati and Gholamreza Ahmadian
Drugs Drug Candidates 2025, 4(1), 5; https://doi.org/10.3390/ddc4010005 - 10 Feb 2025
Viewed by 972
Abstract
COVID-19, first identified in December 2019 in Wuhan, China, is caused by the SARS-CoV-2 virus, a pathogen that primarily targets the respiratory system and can lead to severe conditions such as acute respiratory distress syndrome (ARDS). Among the seven coronaviruses known to infect [...] Read more.
COVID-19, first identified in December 2019 in Wuhan, China, is caused by the SARS-CoV-2 virus, a pathogen that primarily targets the respiratory system and can lead to severe conditions such as acute respiratory distress syndrome (ARDS). Among the seven coronaviruses known to infect humans, three—SARS-CoV, MERS-CoV, and SARS-CoV-2—are associated with severe illness and significant morbidity. SARS-CoV-2 is an enveloped, single-stranded RNA virus that utilizes the angiotensin-converting enzyme 2 (ACE2) receptor for cellular entry. The genetic sequence of SARS-CoV-2 is highly mutable, leading to the emergence of variants that alter disease pathology and transmission dynamics. The World Health Organization (WHO) has classified these mutations into variants of concern (VOCs), variants of interest (VOIs), and variants under monitoring (VUMs). This review provides an in-depth analysis of both historical and emerging SARS-CoV-2 variants, summarizes recent advancements in diagnostic methods for SARS-CoV-2 detection, and discusses current therapeutic strategies for COVID-19, with a particular focus on virus-like particle (VLP) vaccines developed in recent years. Additionally, we highlight ongoing therapeutic approaches and their implications for managing COVID-19. Full article
(This article belongs to the Special Issue Fighting SARS-CoV-2 and Related Viruses)
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<p>Physical and genome structure of SARS-CoV-2 and its encoded proteins. (<b>a</b>) Diagram of the SARS-CoV-2 virion. (<b>b</b>) Genome organization and proteins. The open reading frame 1a (ORF1a) and ORF1b are shown as red and blue boxes, respectively, that encode 15 non-structural proteins (NSPs). The genes encoding main structural proteins, including spike (S), envelope (E), membrane (M), and nucleocapsid (N), are represented in different color boxes. (<b>c</b>) Schematic diagram of SARS-CoV-VLP vaccine.</p>
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<p>A schematic representation of various medications used to treat SARS-CoV-2. These medications comprise both chemical and biopharmaceutical options. Chemical medications consist of inhibitors, nucleotide and nucleoside analogs, anti-influenza agents, and antiparasitic medications, whereas biopharmaceuticals include antibiotics, antibodies, anti-inflammatory drugs, corticosteroids, and potential targets indicated by CD147.</p>
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15 pages, 1294 KiB  
Article
Outcomes in Atrial Fibrillation Patients with Different Clinical Phenotypes: Insights from the French Population
by Ameenathul M. Fawzy, Arnaud Bisson, Lisa Lochon, Thibault Lenormand, Gregory Y. H. Lip and Laurent Fauchier
J. Clin. Med. 2025, 14(4), 1044; https://doi.org/10.3390/jcm14041044 - 7 Feb 2025
Cited by 1 | Viewed by 683
Abstract
Background: Atrial fibrillation (AF) patients represent a clinically complex, heterogeneous population comprising multiple homogeneous cohorts. Purpose: We aimed to identify the common clinical phenotypes of AF patients and compare clinical outcomes between these subgroups. Methods: A 1% representative sample of all AF [...] Read more.
Background: Atrial fibrillation (AF) patients represent a clinically complex, heterogeneous population comprising multiple homogeneous cohorts. Purpose: We aimed to identify the common clinical phenotypes of AF patients and compare clinical outcomes between these subgroups. Methods: A 1% representative sample of all AF patients hospitalized between 2010 and 2019 was identified from the French national database. Agglomerative hierarchical cluster analysis was performed using Ward’s method and squared Euclidian distance to derive the clusters of patients. Cox regression analyses were used to evaluate outcomes including all-cause death, cardiovascular death, non-cardiovascular death, ischemic stroke, hospitalization for heart failure (HF) and composite of ventricular tachycardia, ventricular fibrillation and cardiac arrest (VT/VF/CA) over a mean follow-up period of 2.0 ± 2.3 years. Results: Four clusters were generated from the 12,688 patients included. Cluster 1 (n = 2375) was younger, low cardiovascular disease (CVD)-risk group with a high cancer prevalence. Clusters 2 (n = 6441) and 3 (n = 1639) depicted moderate-risk groups for CVD. Cluster 3 also had the highest degree of frailty and lung disease while Cluster 4 (n = 2233) represented a high-risk cohort for CVD. After adjusting for confounders, with cluster 1 as the reference, cluster 3 had the highest risk of all-cause death, HR 1.24 (1.09–1.41), ARD (10.3%), cardiovascular death, HR 1.56 (1.19–2.06), ARD (3.3%), non-cardiovascular death, HR 1.20 (1.04–1.38), ARD (6.9%), hospitalization for HF, HR 2.07 (1.71–2.50), ARD (9.1%) and VT/VF/CA, HR 1.74 (1.20–2.53), (ARD 1.3%). Conclusions: Four distinct clusters of AF patients were identified, discriminated by the differential presence of comorbidities. Our findings suggest that hospitalized AF patients with moderate CVD risk may have a poorer prognosis compared to hospitalized AF patients with high CVD risk in the presence of lung pathology and frailty. This subgroup of patients may require more stringent management of existing comorbidities such as chronic obstructive pulmonary disease and sleep apnea, alongside their AF. Full article
(This article belongs to the Section Cardiovascular Medicine)
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<p>Dendrogram generated by hierarchical clustering process showing the 4 AF clusters. The dendrogram graph is the visual representation of the hierarchical clustering process. Vertical lines are clusters that are joined together, and the position of the line on the scale indicates the distance at which clusters were joined.</p>
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<p>Heatmap of the baseline characteristics of AF patients according to the patient clusters. Legend for heat map colors: from blue (low %: represents the lowest values in the dataset) to red (highest %: highlights the maximum values in the dataset).</p>
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<p><b>Cumulative incidences for study outcomes.</b> Cumulative incidences for all-cause death (<b>A</b>), cardiovascular death (<b>B</b>), non-cardiovascular death (<b>C</b>), ischemic stroke (<b>D</b>), rehospitalization for HF (<b>E</b>) or VT/VF/CA (<b>F</b>) during follow-up in patients with AF according to patient clusters.</p>
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37 pages, 2637 KiB  
Review
Septic Cardiomyopathy: Difficult Definition, Challenging Diagnosis, Unclear Treatment
by George E. Zakynthinos, Grigorios Giamouzis, Andrew Xanthopoulos, Evangelos Oikonomou, Konstantinos Kalogeras, Nikitas Karavidas, Ilias E. Dimeas, Ioannis Gialamas, Maria Ioanna Gounaridi, Gerasimos Siasos, Manolis Vavuranakis, Epaminondas Zakynthinos and Vasiliki Tsolaki
J. Clin. Med. 2025, 14(3), 986; https://doi.org/10.3390/jcm14030986 - 4 Feb 2025
Viewed by 1937
Abstract
Sepsis is a systemic inflammatory response syndrome of suspected or confirmed infectious origin, which frequently culminates in multiorgan failure, including cardiac involvement. Septic cardiomyopathy (SCM) remains a poorly defined clinical entity, lacking a formal or consensus definition and representing a significant knowledge gap [...] Read more.
Sepsis is a systemic inflammatory response syndrome of suspected or confirmed infectious origin, which frequently culminates in multiorgan failure, including cardiac involvement. Septic cardiomyopathy (SCM) remains a poorly defined clinical entity, lacking a formal or consensus definition and representing a significant knowledge gap in critical care medicine. It is an often-underdiagnosed complication of sepsis. The only widely accepted aspect of its definition is that SCM is a transient myocardial dysfunction occurring in patients with sepsis, which cannot be attributed to ischemia or pre-existing cardiac disease. The pathogenesis of SCM appears to be multifactorial, involving inflammatory cytokines, overproduction of nitric oxide, mitochondrial dysfunction, calcium homeostasis dysregulation, autonomic imbalance, and myocardial edema. Diagnosis primarily relies on echocardiography, with advanced tools such as tissue Doppler imaging (TDI) and global longitudinal strain (GLS) providing greater sensitivity for detecting subclinical dysfunction and guiding therapeutic decisions. Traditional echocardiographic findings, such as left ventricular ejection fraction measured by 2D echocardiography, often reflect systemic vasoplegia rather than intrinsic myocardial dysfunction, complicating accurate diagnosis. Right ventricular (RV) dysfunction, identified as a critical component of SCM in many studies, has multifactorial pathophysiology. Factors including septic cardiomyopathy itself, mechanical ventilation, hypoxemia, and hypercapnia—particularly in cases complicated by acute respiratory distress syndrome (ARDS)—increase RV afterload and exacerbate RV dysfunction. The prognostic value of cardiac biomarkers, such as troponins and natriuretic peptides, remains uncertain, as these markers primarily reflect illness severity rather than being specific to SCM. Treatment focuses on the early recognition of sepsis, hemodynamic optimization, and etiological interventions, as no targeted therapies currently exist. Emerging therapies, such as levosimendan and VA-ECMO, show potential in severe SCM cases, though further validation is needed. The lack of standardized diagnostic criteria, combined with the heterogeneity of sepsis presentations, poses significant challenges to the effective management of SCM. Future research should focus on developing cluster-based classification systems for septic shock patients by integrating biomarkers, echocardiographic findings, and clinical parameters. These advancements could clarify the underlying pathophysiology and enable tailored therapeutic strategies to improve outcomes for SCM patients. Full article
(This article belongs to the Section Cardiology)
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<p>Echocardiographic markers of left ventricular systolic and diastolic function. (<b>A</b>,<b>B</b>): Left ventricular ejection fraction (EF) estimation through the Simpson’s method in a patients with SCM. LVEF was 27%. (<b>C</b>): Tissue Doppler imaging evaluating the systolic velocity of the lateral mitral annulus (S’) which was very low in the present patient (0.04 m/s) (red arrows). (<b>D</b>,<b>E</b>): Mitral Annular Plane Systolic Excursion (MAPSE) at the septal and lateral mitral annulus which was 0.8 and 1.3 mm, respectively, indicating severe LV systolic dysfunction. (<b>F</b>,<b>G</b>): transmitral flow and tissue Doppler imaging at the mitral annulus to evaluate diastolic LV function. E/e’ was 16.35, severely increased, indicating diastolic dysfunction in a patient with urinary sepsis and previously normal cardiac function. E’ was 0.04 cm/s also indicating severe diastolic dysfunction.</p>
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<p>(<b>A</b>). Speckle-tracking analysis of a patient with normal systolic left ventricular (LV) function. Two-dimensional image showing speckles within the LV being tracked by the ultrasound Machine Software (EchoPAC Software version 203). Graphical representation of the movement of speckles throughout the cardiac cycle (<span class="html-italic">x</span>-axis, longitudinal strain; <span class="html-italic">y</span>-axis, time in msec), with each line representing a different segment of the LV; large negative values represent movement of speckles towards one another during contraction representing normal function. (<b>B</b>). Bullseye map showing global longitudinal strain values throughout the LV. (<b>C</b>). Speckle-tracking analysis of a patient with sepsis and severely reduced left ventricular (LV) systolic function. A 2D image showing speckles within the LV being tracked by the ultrasound machine software. Graphical representation of movement of speckles throughout the cardiac cycle (x-axis, longitudinal strain; y-axis, time in msec) with each line representing a different segment of the LV; note smaller negative values with variable time to peak strain representing reduced LV function with mechanical dyssynchrony. Bullseye map showing global longitudinal strain values throughout the LV; blue zones represent areas of the LV where there is lengthening of the segments during systole rather than shortening (<b>D</b>).</p>
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<p>Speckle-tracking analysis in patients with SCM. (<b>A</b>). A patient with severely decreased LV EF (18%) measured with the Simpson’s method and the (<b>B</b>). corresponding GLS with STE which was also found severely decreased. (<b>C</b>). A patient with septic shock and mildly reduced LVEF (47%). The corresponding GLS (<b>D</b>) was found severely decreased, better depicting the depressed cardiac contractility which was probably masked due to the decreased peripheral vascular resistances. (<b>E</b>,<b>F</b>) present GLS examinations in patients with SCM. Interesting is the difference in the distribution of the affected myocardial regions presenting altered contractility.</p>
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<p>Indices of RV function. (<b>A</b>). Assessment of RV size through the evaluation of RV end diastolic area) (RVEDA) to LVEDA. (<b>B</b>) RV outflow tract velocity Time Integral (RVOT VTI). The ascending part of the RVOT VTI envelop presents a midsystolic notch which is indicative of increased pulmonary vascular resistances (PVRs). (<b>C</b>). D shape of the LV at the parasternal short axis indicating Acute Core Pulmonale (ACP) due to increased RV pressures. In order to conclude that ACP is due to sepsis (SCM) it is essential to exclude all other features that result to RV dusfunction. (<b>D</b>). Tricuspid annular Plane Systolic Excursion (TAPSE) which is borderline. (<b>E</b>). Fractional Area Change quantification through the equation [RVED area − RVESA)/RVESA]. (<b>F</b>). Estimation of RV Systolic pressure through the velocity of the envelope of tricuspid regurgitation. Using the Bernouli equation. Using the above measurements, TAPSE/PASP, a derived variable indicating right ventriculoarterial; coupling, can be evaluated. Moreover, PASP/VTI RVOT can indicate the value of PVRs.</p>
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<p>(<b>A</b>,<b>C</b>): Superior vena cava collapsibility index measured with transesophageal echocardiography. The reported threshold to identify fluid responsiveness varies in the literature between 18 and 36%. Patient (<b>A</b>) is probably not a fluid responder. On the contrary, patient (<b>C</b>) will respond to fluid administration. (<b>B</b>): IVC distensibility index in a fully sedated patient under controlled mechanical ventilation. The value of 31% indicates fluid responsiveness (<b>D</b>): IVC collapsibility index in a spontaneously breathing patient. The value of 100% indicates fluid responsiveness, although it should be considered with caution in a patient with rigorous respiratory efforts.</p>
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14 pages, 1229 KiB  
Article
Intubation Versus Tracheotomy Outcomes in Critically Ill COVID-19 Patients in Low-Resource Settings: What Do We Know?
by Pedja Kovacevic, Goran Baric, Sasa Dragic, Danica Momcicevic, Biljana Zlojutro, Milka Jandric, Tijana Kovacevic, Daniel Lovric, Ivan Palibrk and Jihad Mallat
J. Clin. Med. 2025, 14(3), 978; https://doi.org/10.3390/jcm14030978 - 3 Feb 2025
Viewed by 458
Abstract
Background: Patients undergoing prolonged mechanical ventilation commonly require tracheotomy. The main aim of this study was to evaluate the outcomes of tracheotomy for patients with acute respiratory distress syndrome (ARDS) associated with COVID-19 in low-resource settings. Methods: A retrospective, single-center, observational [...] Read more.
Background: Patients undergoing prolonged mechanical ventilation commonly require tracheotomy. The main aim of this study was to evaluate the outcomes of tracheotomy for patients with acute respiratory distress syndrome (ARDS) associated with COVID-19 in low-resource settings. Methods: A retrospective, single-center, observational cohort study was performed on patients with ARDS associated with COVID-19. Patients who underwent intubation alone were compared with those who received both intubation and subsequent tracheotomy. The analysis included patient demographics, comorbidities, and outcomes. Results: Patients undergoing tracheotomy (n = 89) were compared with intubated patients (n = 622). The median time from intubation to tracheotomy was 10 days (IQR: 6–15 days). Overall, 608 patients (85.5%) died in the hospital. Thirty-seven patients (35.9%) in the survival group had tracheostomy compared with fifty-two patients (8.5%) in the non-survival group (p < 0.001). The Kaplan–Meier curve shows a higher probability of survival in the tracheotomy group compared with the non-tracheotomy group (log-rank test: p < 0.001). Tracheotomy was found to be independently associated with lower in-hospital mortality (HR = 0.16 [95% CI: 0.11–0.23], p < 0.001) in the multivariable Cox proportional hazards regression analysis after adjusting for potential confounding factors. Furthermore, tracheotomy was associated with a higher cumulative incidence of being alive and off the ventilator at day 28 (SHR = 2.87 [95% CI: 1.88–4.38], p < 0.001). Conclusions: Tracheotomy was associated with reduced in-hospital mortality and longer ventilator-free days. Full article
(This article belongs to the Special Issue Key Advances in the Treatment of the Critically Ill: 2nd Edition)
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<p>Kaplan–Meier survival curve shows the tracheotomy group had a significantly better probability of survival compared with the non-tracheotomy group.</p>
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<p>The adjusted Cox proportional hazards model shows lower in-hospital mortality hazards for the tracheostomy group. Adjusted for age, gender, SAPS II score, SOFA score, lactate level, lactic dehydrogenase level, acute kidney injury, tocilizumab, and corticosteroids. HR: hazards ratio.</p>
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<p>Cumulative incidence functions for ventilator-free days in patients with tracheostomy and those without. The probability of being alive and off the mechanical ventilator was significantly higher in the tracheostomy group than in the non-tracheostomy group. SHR: sub-hazards ratio.</p>
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<p>Distribution of ventilator-free days in the non-tracheostomy group (<b>A</b>) and tracheostomy group (<b>B</b>).</p>
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14 pages, 2766 KiB  
Article
Acute Respiratory Distress Identification via Multi-Modality Using Deep Learning
by Wajahat Nawaz, Kevin Albert, Philippe Jouvet and Rita Noumeir
Appl. Sci. 2025, 15(3), 1512; https://doi.org/10.3390/app15031512 - 2 Feb 2025
Viewed by 657
Abstract
Medical instruments are essential in pediatric intensive care units (PICUs) for measuring respiratory parameters to prevent health complications. However, the assessment of acute respiratory distress (ARD) is still conducted through intermittent visual examination. This process is subjective, labor-intensive, and prone to human error, [...] Read more.
Medical instruments are essential in pediatric intensive care units (PICUs) for measuring respiratory parameters to prevent health complications. However, the assessment of acute respiratory distress (ARD) is still conducted through intermittent visual examination. This process is subjective, labor-intensive, and prone to human error, making it unsuitable for continuous monitoring and early detection of deterioration. Previous studies have proposed solutions to address these challenges, but their techniques rely on color information, the performance of which can be influenced by variations in skin tone and lighting conditions. We propose leveraging multi-modality data to address these limitations. Our method integrates color and depth data using deep convolutional neural networks with a late feature fusion scheme. We train and evaluate our model on a dataset of 153 patients with respiratory illnesses, 86 of whom have ARD of varying severity levels. Experimental results demonstrate that multi-modality data combined with simple late fusion techniques are more effective with limited data, offering higher confidence scores compared to using color information alone. Our approach achieves an accuracy of 85.2%, a precision of 86.7%, a recall of 85.2%, and an F1 score of 85.8%. These findings suggest that multi-modality data provide a promising solution for improving ARD detection accuracy and confidence in clinical settings. Full article
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<p>Illustration of the proposed network architecture for detecting acute respiratory distress, featuring the integration of RGB and depth temporal visual data through identical 3D convolutional neural networks.</p>
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<p>RGB-D videos’ cropping: (<b>a</b>) RGB and (<b>b</b>) depth.</p>
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<p>Data distribution of ARD and non-ARD patients categorized by age group, retraction type, and overall totals.</p>
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<p>Block diagram illustrating the various types of multi-modality fusion schemes: (<b>a</b>) early fusion, where input modalities are combined at the input level; (<b>b</b>) score averaging, where individual modality predictions are averaged; (<b>c</b>) late fusion, where features are combined after independent processing of each modality w/o base-model freezing.</p>
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<p>Performance comparison of ARD detection (X3D) system using different modality and different modality fusion schemes. The bars represent the average performance, with error bars indicating the min–max range of each metric across five folds.</p>
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15 pages, 3117 KiB  
Article
Selective Catalysis by Complexes Including Ni and Redox-Inactive Alkali Metals (Li, Na, or K) in Oxidation Processes: The Role of Hydrogen Bonds and Supramolecular Structures
by Ludmila I. Matienko, Elena M. Mil, Anastasia A. Albantova and Alexander N. Goloshchapov
Int. J. Mol. Sci. 2025, 26(3), 1166; https://doi.org/10.3390/ijms26031166 - 29 Jan 2025
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Abstract
It is known that the presence of redox-inactive metals in the active center of an enzyme has a significant effect on its activity. In this regard and for other reasons, the effect of redox-inactive metals on redox processes, such as electron transfer, oxygen [...] Read more.
It is known that the presence of redox-inactive metals in the active center of an enzyme has a significant effect on its activity. In this regard and for other reasons, the effect of redox-inactive metals on redox processes, such as electron transfer, oxygen and hydrogen atom transfer, as well as the breaking and formation of O–O bonds in reactions catalyzed by transition metals, has been widely studied. Many questions about the role of redox-inactive metals in the mechanisms of these reactions remain open. In this paper, the mechanism of catalysis by bi- and triple hetero-binuclear heteroligand complexes including Ni and redox-inactive alkali metals ((A) {Ni(acac)2∙L2} and (B) {Ni(acac)2∙L2∙PhOH} (L2 = MSt (M = Li, Na, or K)) in the process of the selective oxidation of ethylbenzene by molecular oxygen into α-phenyl ethyl hydroperoxide is considered. The activity of A and B complexes towards O2, ROOH, and RO2 radicals was studied. Based on kinetic data, we suggest that the high catalytic efficiency of B triple complexes in oxidation processes may be associated with the role of outer-sphere regulatory interactions, with the formation of stable supramolecular structures due to intermolecular H bonds. This assumption was confirmed using the AFM method. Prospects for studying catalysis by complexes ({Ni(acac)2∙L2} and {Ni(acac)2∙L2∙PhOH}) that are models of NiARD (Ni-Acyreductone dioxygenase) are discussed. Full article
(This article belongs to the Section Materials Science)
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<p>The structure of hetero-dinuclear nickel(II)/zinc(II) complex [<a href="#B7-ijms-26-01166" class="html-bibr">7</a>].</p>
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<p>Structure of Fe(<sup>15c5</sup>PDI)(CO)<sub>2</sub> complex with either Na<sup>+</sup> or Li<sup>+</sup> encapsulated.</p>
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<p>The proposed structure of the heteroligand triple complex {Ni(acac)<sub>2</sub>·MSt PhOH}.</p>
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<p>Kinetics of accumulation oxidation products C ([C]—concentration of oxidation products): (1) PEH ([C] = [PEH]), (2) acetophenone (AP) ([C] = [AP]), and (3) methylphenylcarbinol (MPC) ([C] = [MPC]) during oxidation of ethylbenzene catalyzed by the following triple systems: (<b>a</b>) {Ni(acac)<sub>2</sub> + NaSt + PhOH} and (<b>b</b>) {Ni(acac)<sub>2</sub> + LiSt + PhOH}. [Ni(acac)<sub>2</sub>] = 3∙10<sup>−3</sup> mol/L, [NaSt] = [LiSt] = 3∙10<sup>−3</sup> mol/L, and [PhOH] = 3∙10<sup>−3</sup> mol/L; 120 °C.</p>
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<p>The ratio of the concentrations of oxidation products Δ[AP]]/Δ[PEH] (<b>a</b>,<b>c</b>) and Δ[AP]/Δ[MPC] (<b>b</b>) versus time t (h) in ethylbenzene oxidation catalyzed by {Ni(acac)<sub>2</sub>∙LSt∙PhOH} (<b>a</b>,<b>b</b>) and {Ni(acac)<sub>2</sub>∙KSt∙PhOH} (<b>c</b>) complexes at 120 °C.</p>
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<p>An AFM three-dimensional image (30 × 30 (<b>a</b>) and 10 × 10 (<b>b</b>) (µm)) of the structures formed on the surface of modified silicone based on Ni(acac)<sub>2</sub>∙NaSt∙PhOH triple complexes.</p>
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<p>The 3D AFM (2 × 2 (µm)) image of the supramolecular structures based on Ni(acac)<sub>2</sub>∙LiSt∙PhOH (<b>a</b>) triple complexes. The 3D AFM (5 × 5 (µm)) image of the supramolecular structures based on {Ni(acac)<sub>2</sub>∙His∙Tyr} (h~25–30 nm) (<b>b</b>).</p>
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<p>The “latent-radical” mechanism of the decomposition of the intermediate complex {ROO-M} with the formation of AP (R’ = O) and MPC (ROH) (the stage of chain propagation (M + RO<sub>2</sub><sup>▪</sup>→); M = Cat = {Ni(acac)<sub>2</sub>·MSt·PhOH}; R = C<sub>6</sub>H<sub>5</sub> HC(CH<sub>3</sub>); R’ = C<sub>6</sub>H<sub>5</sub>C(CH<sub>3</sub>)).</p>
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