Search Results (284)

The growing demand for reliable wearable devices that can continuously monitor vital signs and track health under various conditions imposes challenging constraints on battery life. Wearable devices typically include a Photoplethysmogram (PPG) sensor, which is used for various applications such as monitoring heart rate (HR) and blood oxygenation (${\mathrm{SpO}}_2$). The efficiency of these applications depends on the quality of the PPG sensor, which acquires raw data through the analog front-end and transmits it externally. This paper presents a digital block that evaluates the quality of the PPG signal directly within the ASIC. The proposed Signal Quality Assessment (SQA) module is derived from post-processing algorithms and translated into a real-time, single-sample evaluation approach, providing significant benefits at both the sensor and system levels. The proposed solution achieves performance comparable to state-of-the-art methods, with a sensitivity of 95.2%, a specificity of 88.1%, and an accuracy of 89.52%, while introducing an extremely low energy overhead equal to $5.38$ μ$\mathrm{J}$. Full article

Background: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder marked by memory loss and cognitive decline, reflecting widespread brain dysfunction across multiple neural systems. Early detection of pathological changes is critical for enabling timely intervention, improved management, and better therapeutic outcomes. Methods: Using non-transgenic AD rats (Samaritan) and sham rats (Long–Evans), we explored structural and functional differences with multimodal MRI and multi-unit activity (MUA). Results: Diffusion tensor imaging (DTI) revealed no significant changes in mean diffusivity of water, but AD-related microstructural alterations of fractional anisotropy were confined to subcortical regions with cortical areas and white matter tracts remaining intact. We used functional MRI (fMRI) with blood oxygenation level-dependent (BOLD) contrast in rest-state (R-fMRI) and task-based (T-fMRI) paradigms. R-fMRI revealed much stronger functional connectivity in subcortical vs. cortical areas in AD rats, implicating AD-related functional changes in subcortical areas in agreement with DTI data. T-fMRI with sensory stimulation revealed reproducible fMRI responses in both groups; however, AD rats exhibited reduced BOLD response amplitude and spatial activation extent, which was accompanied by attenuated stimulus-evoked MUA responses. These suggest that attenuated evoked BOLD response reflects diminished neuronal activity in AD, rather than impaired neurovascular and/or neurometabolic coupling. Conclusions: Together these findings suggest that AD-induced anatomical and functional changes in subcortical areas are related to altered cortical responses, highlighting multimodal MRI as a sensitive tool for early AD-related brain changes. Full article

Functional magnetic resonance imaging (fMRI) signals exhibit complex temporal structure arising from multivariate neural dynamics, physiological variability, and measurement uncertainty. In this work, we formulate region-of-interest-level fMRI analysis as a probabilistic multi-step forecasting problem and investigate the predictability of blood-oxygen-level-dependent (BOLD) activity from an information-theoretic perspective. Using the Natural Scenes Dataset, we model multiregional BOLD activity as a stochastic process with finite memory and train multiple forecasting architectures, including linear regression, exponential smoothing, recurrent neural networks, and transformer-based models, to predict future BOLD samples from preceding temporal observations. Forecasting performance is analyzed together with entropy-based quantities, including marginal entropy, conditional entropy, and normalized predictive information measures estimated directly from model-derived predictive distributions without imposing restrictive Gaussian assumptions on the underlying BOLD dynamics. The transformer model achieved significant improvement over a naive persistence baseline ($p=0.001$) while yielding a high predictive information fraction ($\eta =75.49\%$). Post hoc directed information analysis revealed that short-horizon prediction was dominated primarily by autoregressive, within-ROI, temporal structure. Overall, the proposed framework demonstrates how probabilistic forecasting and information-theoretic analysis can be integrated to characterize the predictability, uncertainty structure, and directional organization of large-scale fMRI dynamics and may support future downstream neuroengineering and neural-state inference applications. Full article

Background/Objectives: Prognostication in ICU patients with documented coma or unresponsiveness is a high-stakes task that informs escalation of care, goals-of-care discussions, and family counselling. Conventional scores are often based on static snapshots and may not reflect early physiological evolution in heterogeneous real-world ICU populations. Routine arterial blood gases (ABG) and SpO₂ are repeatedly measured during early ICU care and may capture clinically meaningful trajectories that can be leveraged by explainable machine learning. To develop and internally validate exploratory, time-updated explainable machine-learning models for ICU outcome in ICU patients with clinically documented coma or unresponsiveness using routine ABG/SpO₂ measurements and physiological trajectories available at admission, 24 h, and 72 h, and to evaluate whether trajectory information adds prognostic information within a staged internal-validation framework. Methods: We conducted a retrospective single-centre study of 108 adult ICU patients with clinically documented coma or unresponsiveness. Predictors included demographics, comorbidity burden, COVID-19 status, baseline ABG/SpO₂ at ICU admission, inflammatory and coagulation biomarkers, and derived ABG/SpO₂ trajectory variables at 24 h and 72 h. Trajectory variables were defined as changes from admission to 24 h and to 72 h and were retained as missing when follow-up measurements were unavailable. The primary ICU-course outcome was ICU death versus transfer to ward. Three staged models were evaluated: Model A using baseline variables, Model B adding 24 h trajectory features, and Model C adding 72 h trajectory features. For each stage, models were analyzed with and without the derived respiratory_support index; models excluding respiratory_support were treated as the main interpretive analyses. Logistic regression, random forest, and gradient boosting (XGBoost) classifiers were assessed using repeated stratified 5-fold cross-validation with 20 repeats and aligned out-of-fold predictions. Performance was reported using AUC-ROC, precision–recall AUC, Brier score, and operating-point metrics; clinical utility was examined with decision-curve analysis. Model interpretation used SHAP and partial dependence plots. Robustness analyses included feature-exclusion sensitivity analysis for respiratory_support and a label-permutation sanity check. Results: ICU mortality was 65.7% (71/108). Follow-up ABG completeness was 75.9% at 24 h and 61.1% at 72 h. Because respiratory_support summarized the highest support level during the first 72 h and strongly separated outcome groups, models excluding respiratory_support were treated as the primary interpretive analyses. In the primary NoRS logistic-regression models, discrimination was moderate-to-strong, with AUC-ROC 0.822 for Model A_noRS, 0.848 for Model B_noRS, and 0.895 for Model C_noRS; bootstrap 95% confidence intervals were 0.739–0.897, 0.766–0.919, and 0.830–0.951, respectively. Measurement-availability sensitivity analyses and simple benchmark models were added to contextualize trajectory-related performance. Respiratory_support-enriched models were retained only as secondary severity-aware analyses, not as admission-only prediction models. Label permutation reduced discrimination toward chance (AUC ≈ 0.55). SHAP and partial-dependence analyses identified oxygenation variables, inflammatory burden, acid–base status, and ΔPaO₂ at 72 h as clinically coherent contributors to predicted risk; when included, respiratory_support dominated feature attribution, consistent with its role as an organ-support intensity marker. Conclusions: In ICU patients with clinically documented coma or unresponsiveness, explainable machine-learning models using routine ABG/SpO₂ trajectories within the first 72 h are feasible and may provide time-updated prognostic information, but the incremental value of trajectory-enriched models over simpler admission-only benchmarks remains unproven. Trajectory-enriched NoRS models retained meaningful discrimination after removing organ-support severity, suggesting a possible physiologically meaningful signal beyond support intensity alone, although definitive incremental value over parsimonious admission-only benchmarks was not established. These findings should be interpreted as exploratory and internally validated only; they do not establish a deployable ICU mortality score, do not demonstrate superiority over established ICU severity scores, and require external validation in larger multicentre cohorts before clinical deployment. Full article

Nano-antimony trioxide (Nano-Sb₂O₃) is extensively utilized in industrial production and consumer products, leading to widespread environmental contamination and human exposure. Accumulating evidence has demonstrated that Nano-Sb₂O₃ induces male reproductive toxicity, yet the underlying molecular mechanisms remain poorly understood. In this study, male C57BL/6 mice were exposed to Nano-Sb₂O₃ (2.5, 5.0, and 7.5 mg/kg/day). Exposure to Nano-Sb₂O₃ induced dose-dependent reproductive toxicity, evidenced by dose-dependent reductions in sperm motility (56.70% to 36.10%) and sperm density (15.76 × 10⁶/mL to 2.79 × 10⁶/mL) and a marked elevation in sperm malformation rates (4.56% to 44.36%), as well as severe histopathological alterations, testicular Sb accumulation, and elevated reactive oxygen species (ROS) levels. Transcriptomic analysis revealed significant enrichment of the PPAR and PI3K-Akt signaling pathways and identified SPP1 as one of the most significantly differentially expressed genes. Computational pathway perturbation analyses further yielded hypothesis-generating evidence supporting the potential involvement of PPAR signaling suppression and PI3K-Akt and inflammatory pathway activation following Nano-Sb₂O₃ exposure. Both mRNA and protein levels of SPP1 were significantly upregulated in a dose-dependent manner in mouse testes and TM4 Sertoli cells. In vitro experiments further demonstrated that Nano-Sb₂O₃ increased the expression of pro-inflammatory cytokines IL-1β and IL-6 by up to 5.6-fold and 4.7-fold, respectively, while impairing Sertoli cell viability and wound-healing capacity. Importantly, Spp1 silencing attenuated inflammatory responses and restored the expression of blood–testis barrier (BTB)-associated proteins, including ZO-1, Claudin-11, and N-cadherin. These findings suggest that SPP1 may contribute to Nano-Sb₂O₃-induced inflammatory responses and alterations in BTB-associated proteins, thereby potentially participating in male reproductive injury. Full article

Background: The differential diagnosis of respiratory distress syndrome (RDS) and congenital pneumonia (CP) in newborns remains a complex clinical challenge due to the similarity in their clinical manifestations and their potential to coexist. Objective: We aimed to determine differential diagnostic predictors of RDS and CP in newborns by using mathematical modeling and machine learning methods. Methods: A retrospective cohort study was conducted; de-identified medical records of 244 newborns (97 with RDS and 143 with CP) were collected to assess clinical, anamnestic, laboratory, and instrumental data by applying multiple regression analysis, ROC analysis, logistic regression models, and Random Forest. Results: Patients with CP presented with a more severe condition at admission (57.1% vs. 23.3%; p = 0.023), required mechanical ventilation (MV) more frequently (22.4% vs. 8.2%; p = 0.004), and were more often transferred to the intensive care unit (ICU) (77.3% vs. 55.7%; p = 0.001). They further had lower hemoglobin levels (151 ± 28 g/L vs. 164 ± 31 g/L; p = 0.001) and red blood cell counts (p = 0.021). Regression analysis demonstrated that the severity of the condition and the presence of cerebral ischemia were dependent on hemoglobin levels in the case of CP, while gestational age played a determining role in RDS. The machine learning models achieved an accuracy of 0.69 and an area under the curve (AUC) of 0.82 (Random Forest). The key predictors for differential diagnosis of RDS were low gestational age, hyperbilirubinemia, and congenital heart defects, while for CP, they were hemoglobin < 151 g/L, lymphocytes < 4.8 × 10³/μL, oxygen saturation < 90–91%, and cerebral ischemia. Conclusions: The use of mathematical modeling methods made it possible to identify prognostically significant predictors for the differential diagnosis of RDS and CP. The resulting models are best viewed as proof-of-concept tools for hypothesis generation and future research, as external validation is necessary before they can be considered for clinical use. Full article

Background: The emergence of generative adversarial networks has laid the groundwork for data augmentation, addressing challenges of missing training data in various research scenarios. However, simulating functional magnetic resonance imaging (fMRI) data remains particularly challenging, especially for populations with varying degrees of mild cognitive impairment (MCI). Effectively characterizing and capturing the mechanisms of brain function variations poses a critical issue in cognitive neuroscience. This study aims to simulate and analyze synthetic fMRI blood-oxygen-level-dependent (BOLD) signals across four cognitive stages: healthy control (HC), early MCI (EMCI), late MCI (LMCI), and Alzheimer’s disease (AD). Methods: We propose WGTMM, an innovative method that integrates the Vision Transformer for fMRI (VTFF) into a generative adversarial network architecture. Crucially, WGTMM directly generates fMRI time-series data from pink noise rather than modeling in a latent space, thereby preserving rich temporal dynamics. The framework incorporates a Wasserstein GAN (WGAN) with feature matching to enhance generation quality and mitigate mode collapse. Results: demonstrate that WGTMM-generated fMRI data exhibit lower Kullback-Leibler (KL) divergence compared to traditional GAN and WGAN models, indicating a closer resemblance to real datasets from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Furthermore, when applied to data augmentation, the synthetic data substantially improve multi-class classification performance. Conclusions: WGTMM not only enriches training datasets but also provides new insights into spatial biomarkers of cognitive decline. By leveraging VTFF to investigate class token attention patterns across 360 brain regions, this study reveals monotonic weight variations along disease stages in key cortical areas, including the rostral Area 6, the primary sensory cortex, and PFm near Wernicke’s area, offering a fine-grained exploration of disease progression. Full article

Systemic hypoxia influences the state of the intestinal epithelial barrier and the microbiome; however, the role of the initial tolerance of the organism to oxygen deficiency in the development of these changes remains poorly studied. The aim of the study was to evaluate the colon histophysiological features and the gut microbiome in rats that were tolerant and susceptible to hypoxia under intermittent hypoxic exposure of varying severity. In male Wistar rats, tolerance to oxygen deficiency was determined according to the Hif1a, Epas1, and Hif3a expression levels in peripheral blood leukocytes, after which they were subjected to intermittent hypoxic exposure at an “altitude” of 5000 m or 7000 m for 1 h daily for 21 days. Subsequently, the state of the intestinal epithelial barrier was assessed using histological, histochemical, and immunohistochemical methods, and the microbiota composition was analyzed by PCR. Under normoxic conditions, in comparison with rats that are tolerant to hypoxia, susceptible animals demonstrated a greater volume fraction of goblet cells and a low abundance of Parabacteroides spp. Intermittent hypoxic exposure induced multidirectional changes depending on the initial tolerance and the severity of the regimen. In tolerant-to-hypoxia animals, an increase in the goblet cells volume fraction was detected after the exposure at the 5000 m “altitude”, while at an “altitude” of 7000 m, a decrease in the number of cells in the lamina propria of the mucosa and Clostridium perfringens gr. abundance, as well as a reduction in the Firmicutes/Bacteroidetes ratio, was observed. In susceptible-to-hypoxia animals, a higher abundance of Clostridium perfringens gr. in comparison with tolerant rats was revealed after the exposure at an “altitude” of 7000 m, with no structural changes in the intestinal wall. Thus, intermittent hypoxic exposure led to a rearrangement of the gut microbiome and the morphofunctional characteristics of the intestinal barrier, and the severity of these changes depended on the initial tolerance of the organism to oxygen deficiency and the severity of the hypoxic regime, which should be taken into account when conducting biomedical research. Full article

Background/Objectives: Renal ischemia–reperfusion injury (IRI) is a major cause of acute kidney injury and delayed graft function after kidney transplantation. Oxidative stress, mitochondrial dysfunction, and tubular epithelial cell apoptosis are central events in renal IRI. Sophocarpine (SOP), a quinolizidine alkaloid derived from Sophora species, has reported antioxidant and anti-apoptotic activities, but its effects in renal IRI remain unclear. This study investigated the role and function of SOP in renal IRI. Methods: A bilateral renal IRI mouse model and a hypoxia/reoxygenation (H/R) model in HK-2 human proximal tubular epithelial cells were used. Renal function, histological injury, apoptosis, reactive oxygen species, malondialdehyde, superoxide dismutase activity, glutathione, mitochondrial morphology, mitochondrial membrane potential, and mitochondrial dynamics-related proteins were evaluated. SIRT1 dependency was examined using Sirt1 small interfering RNA in HK-2 cells and EX527-mediated SIRT1 inhibition in mice. Results: SOP pretreatment reduced serum creatinine and blood urea nitrogen levels, attenuated tubular injury and apoptosis, decreased oxidative stress, and preserved mitochondrial morphology and function after renal IRI. Similar protective effects were observed in HK-2 cells exposed to H/R. SOP increased SIRT1 and PGC-1α expression, whereas Sirt1 knockdown or pharmacological SIRT1 inhibition weakened the antioxidant and mitochondrial protective effects of SOP. Conclusions: SOP attenuates renal IRI-associated oxidative stress and mitochondrial dysfunction, at least in part through the SIRT1/PGC-1α axis. These findings support further investigation of SOP as a candidate renoprotective compound for ischemic kidney injury. Full article

Background and Objectives: Head and neck cancers are heterogeneous malignancies with variable biological behavior and treatment response, contributing to high morbidity and mortality. Conventional imaging techniques are limited in their ability to capture tumor biology, highlighting the need for advanced functional imaging. This review aims to evaluate the role of multiparametric magnetic resonance imaging (MRI) in characterizing the tumor microenvironment. Materials and Methods: A narrative review was conducted based on a targeted literature search of databases, including PubMed and Google Scholar. Studies addressing advanced MRI techniques for assessing tumor cellularity, vascularity, molecular features, and oxygenation were selected and analyzed. Results: Perfusion techniques, such as dynamic contrast-enhanced MRI (DCE-MRI) and arterial spin labeling (ASL), provide a quantitative assessment of tumor vascularity and show value in predicting treatment response. Diffusion-based methods, including diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), enable evaluation of tissue cellularity and heterogeneity. Molecular approaches, such as chemical exchange saturation transfer (CEST) and amide proton transfer (APT), offer insights into protein content and proliferation. Oxygenation-sensitive techniques, such as blood oxygenation level dependent MRI (BOLD MRI) and oxygen-enhanced MRI (OE-MRI), allow non-invasive assessment of tumor hypoxia. Conclusions: Multiparametric MRI provides a comprehensive and biologically relevant evaluation of the tumor microenvironment in head and neck cancer, with potential to improve treatment prediction and support personalized therapeutic strategies. Full article

We explored the possibility of antioxidant and antifibrotic effects of panthenol (PL) associated with modulation of coenzyme A (CoA) biosynthesis in the liver in a rat model of chronic obstructive cholestasis induced by bile duct ligation (BDL). We found that PL increased alcohol dehydrogenase (ADH) activity in the liver of BDL rats. PL and its analog pantethine increased pantothenate kinase (PANK) activity, restored hepatic CoA levels reduced by BDL, lowered protein-bound CoA, and normalized impaired mitochondrial functions associated with induced oxidative stress after BDL. These effects were accompanied by decreased collagen deposition and improved morphological features of hepatocytes. In contrast, PANK inhibitor, hopantenic acid (HPA), reduced hepatic CoA levels, aggravated hepatocellular damage, and promoted fibrosis. In the human hepatic stellate cell line LX-2, PL exhibited no cytotoxicity over a wide concentration range, increased intracellular CoA levels, decreased reactive oxygen species (ROS) production, and attenuated collagen accumulation associated with oxidative stress in vitro. Importantly, inhibition of ADH by 4-methylpyrazole completely abolished the protective effects of panthenol, indicating that its activity depends on metabolic pathways involving CoA. Notably, PL did not directly reduce H₂O₂ or superoxide anion radical production in cell-free systems but significantly suppressed lipid peroxidation in liposomes and red blood cells in vitro. Ultimately, these findings indicate that the antioxidant and antifibrotic effects of PL are associated with modulation of CoA metabolism and enhanced resistance of biological membranes to oxidative damage. Full article

Cardio-renal metabolic (CRM) syndrome, characterized by insulin resistance and dyslipidemia, disrupts renal insulin signaling, enhances oxidative stress, and activates inflammasome pathways, ultimately promoting renal fibrosis and kidney dysfunction. Aberrant renal gluconeogenesis has emerged as a critical contributor to tubular injury under cardiometabolic stress; however, its mechanistic linkage to inflammatory and fibrotic remodeling remains incompletely defined. In this study, ApoE^−/− mice subjected to streptozotocin administration and a high-fat diet developed pronounced cardiometabolic dysfunction, accompanied by elevated blood urea nitrogen, creatinine, uric acid, and glycated hemoglobin levels, as well as severe renal histopathological alterations. N-Acetylcysteine (NAC) supplementation significantly improved metabolic abnormalities and attenuated tubular dilation, glomerular hypertrophy, and mesangial expansion. Mechanistically, NAC suppressed renal gluconeogenesis by downregulating glucose-6-phosphatase and phosphoenolpyruvate carboxykinase expression and mitigated epithelial–mesenchymal transition by restoring E-cadherin and reducing vimentin expression, thereby limiting fibrotic remodeling. Consistent with in vivo findings, NAC reduced reactive oxygen species production, restored PI3K/Akt-dependent insulin signaling, and inhibited inflammasome activation in NRK-52E renal tubular cells exposed to high glucose and oleic acid, resulting in attenuation of inflammatory signaling and gluconeogenic activity. Collectively, these results demonstrate that NAC mitigates cardiometabolic stress-induced renal injury by modulating inflammasome activation and gluconeogenic reprogramming, highlighting its potential as a mechanistic modulator of renal fibrosis under CRM conditions. Full article

Introduction: Electronic nicotine delivery systems (ENDSs), also known as e-cigarettes or vapes, have shown popularity among the adolescent population. Compared to adults, less is known regarding the impacts of ENDS and nicotine on the adolescent brain. Adolescent research related to nicotine and other illicit substances can be difficult due to the requirement of parent/guardian consent, adolescent hesitancy for disclosure of product use, and the continually evolving vaping and nicotine products on the market. Despite these challenges, further research is needed to explore the impact of ENDS on the developing adolescent brain. The objective of the study was to evaluate reward sensitivity and cognitive flexibility in the adolescent population using functional magnetic resonance imaging (fMRI) through a probabilistic reversal learning task. Methods: This pilot study recruited participants aged 13–19 years old to complete fMRI testing. We specifically adapted a probabilistic reversal learning task that was previously used to measure reward sensitivity and cognitive flexibility in adults (including nicotine users). We were unable to recruit enough ENDS users to complete the planned analysis; therefore, we evaluated non-users as proof of concept for the use of the probabilistic reversal learning task in adolescents to support future research. Participants completed four blocks of a probabilistic reversal learning task, each lasting 6 min. During each block of the task, blood-oxygenation-level-dependent (BOLD) fMRI images were collected. The reward sensitivity and cognitive flexibility contrasts of parameter estimates were entered into a group analysis model. Due to the small sample size and exploratory nature of the study, we were interested in computing population-level estimates of brain activation that could be attributed to reward sensitivity (win-stay minus lose-stay trials) and cognitive flexibility (lose-shift trials minus lose-stay trials). Results: A total of twelve participants completed fMRI testing—ten non-users, one intermittent user, one regular user. Four of these participants (three non-users and one intermittent user) were excluded from the fMRI analysis due to excessive head movement and/or poor task performance. With the seven remaining non-users, we found no evidence of significant BOLD activation when strictly controlling the Type I error rate. Using a more liberal statistical threshold that did not control the Type I error rate, both contrasts resulted in suprathreshold clusters in occipital and posterior parietal regions, and the reward sensitivity contrast also resulted in suprathreshold clusters in the prefrontal cortex (bilateral middle occipital gyrus). Discussion/Conclusions: We did not find statistically significant BOLD activation, which is likely due to the small sample size. Suprathreshold clusters using the liberal statistical threshold may be feasible for use as regions of interest in future studies using this task. Notably, the prefrontal regions where the reward sensitivity contrast exceeded the liberal statistical threshold in our study were similar to those observed in previous studies of reward sensitivity in adults (including nicotine users) and adolescents. This pilot study explores the use of an fMRI reward-learning paradigm in the adolescent population, which can serve as a catalyst for future research related to nicotine use. Full article

This study evaluated the diagnostic usefulness of surfactant protein D (SP-D), chemokine C-C motif ligand 2/monocyte chemoattractant protein-1 (CCL2/MCP-1), and interleukin 18 (IL-18) in patients with SARS-CoV-2 infection. The authors focused on lung failure assessment, lung parenchyma involvement, and the early assessment of the risk of developing pulmonary fibrosis at the onset of COVID-19. The study group included 87 patients with COVID-19 and 45 healthy subjects. Concentrations of all three markers were measured using the enzyme immunoassay method. The serum SP-D, CCL2/MCP-1, and IL-18 concentrations were significantly higher in the COVID-19 patients before admission to the hospital than those in the controls (p < 0.001 for all comparisons). Differences were only found in the IL-18 levels between the groups categorized according to disease severity (p < 0.001); levels were significantly higher in patients with critical disease severity compared to those with moderate disease severity (p < 0.001). IL-18 also showed a positive correlation with the disease severity (p = 0.025). SP-D and IL-18 levels varied depending on the amount of oxygen administration (p = 0.017 and p < 0.001, respectively). Among the blood gas parameters, SP-D levels were negatively associated with the partial pressure of arterial oxygen (PaO₂) and oxygen saturation (O₂Sat) (p = 0.026 and p = 0.048, respectively), IL-18 with O₂Sat (p = 0.036), and CCL2/MCP-1 with PaO₂ (p = 0.042). SP-D and IL-18 were significantly negatively correlated with oxygen therapy (p = 0.003 and p = 0.014, respectively). Conversely, CCL2/MCP-1 was significantly positively correlated with the pulmonary involvement severity (p = 0.017) and level of hyaluronic acid (HA), a marker of fibrosis (p = 0.042). We also observed a significant correlation between the IL-18 level and the pulmonary involvement severity (p < 0.001), HA (p < 0.001), and other markers of fibrosis. In summary, our study’s results indicate that SP-D, CCL2/MCP-1, and IL-18 may be used to assess lung function in the early stage of COVID-19 infection; additionally, SP-D may serve as an indicator of alveolar injury, while CCL2/MCP-1 and IL-18 may be markers of lung parenchyma involvement and potential predictors of the development of pulmonary fibrosis. Full article

Acute myeloid leukemia (AML) is a complex blood cancer that primarily affects relapsing or refractory patients receiving conventional chemotherapy. Nonsteroidal anti-inflammatory drugs (NSAIDs) have anticancer properties with restricted clinical efficacy attributable to cyclooxygenase (COX)-induced toxicities. To address this issue, a group of benzylamide analogs of the classical NSAIDs (NSI-1–NSI-9) were developed and synthesized to mask the carboxylic acid moiety and minimize COX-induced adverse effects while maintaining anticancer activity. The cytotoxic effect of such substances has been demonstrated in some leukemia cell lines (HL-60, MV4-11, KG1a, and K562). NSI-5 exerted the highest anti-leukemic activity among these sulindac analogs, as determined at a sub-micromolar level in all cell lines studied, by IC50. This mechanistic data also demonstrated that NSI-5 induced apoptosis that was dose-dependent, especially in HL-60 cell lines, and increased the sub-G1 cell fraction. This apoptotic process was also accompanied by a significant decrease in mitochondrial membrane potential, which is characteristic of the induction of the intrinsic apoptotic process. Interestingly, NSI-5 decreased the intracellular reactive oxygen species (ROS) and the expression of most antioxidants (catalase and glutathione synthetase), as well as the redox balance. Gene characterization in vitro also suggested activation of apoptotic pathways, where expression of Bax, Bak1, and Caspase-3 increased, suggesting a potential p53-independent apoptotic pathway, in contrast to control for Bcl-2 expression. Collectively, these findings indicate that NSI-5 is a promising in vitro anti-leukemic lead compound, with activity associated with mitochondrial dysfunction and altered redox regulation. The observed effects are consistent with previously reported COX-independent activity of structurally related NSAID derivatives, and support further investigation of NSI-5 in preclinical models. Full article