Search Results (4,108)

Molecular chaperones, especially heat shock proteins (HSPs) have vital functions in cells’ responses to stress. Here, we cloned and sequenced the complete complementary DNA encoding HSP90 (MjHSP90) from the shrimp Marsupenaeus japonicus. The MjHSP90 cDNA comprised 3162 bp, including a 2172 bp coding region encoding a 724 amino acid-protein (predicted molecular mass = 83.12 kDa). Homology and phylogenetic analyses showed that MjHSP90 was highly conserved and most homologous to Litopenaeus vannamei HSP90. MjHSP90 is expressed in all tested tissues, with high expression in gill tissue and the hepatopancreas. Cold stress significantly upregulated MjHSP90 expression in the gill and hepatopancreas (p < 0.05). Following RNA interference knockdown of MjHSP90, the cold stress-related death rate of the shrimp increased significantly, accompanied by significantly upregulated expression of apoptosis-related genes Mjcaspase-3 and Mjbcl-2 (p < 0.05) and an increase in the number of apoptotic cells. The results indicated that MjHSP90 might play a pivotal role in the shrimp’s immune response to cold stress. Full article

Background/Objectives: Nutraceuticals containing milk fat globule membranes (MFGMs) and extracellular vesicles (EVs) are purported to abate age-related metabolic dysfunction due to their richness in milk sphingolipids. As such, nutraceuticals offer a compelling strategy to improve metabolic health through dietary means, especially for elderly persons who are unable to adhere to common therapeutic interventions. To address this, we examined the effects of supplementing aged sedentary rats with an MFGM/EV-rich concentrate. Methods/Results: In a 25-week study, 89-week-old male rats received either a milk sphingolipid-rich MFGM/EV concentrate or a control supplement. Analysis of metabolic health using a battery of tests, including MS^ALL lipidomics of plasma, liver, and other peripheral tissues, revealed that MFGM/EV supplementation promotes accretion of unique sphingolipid signatures, ameliorates ceramide biomarkers predictive of cardiovascular death, and has a general lipid-lowering effect. At the functional level, we find that these health-promoting effects are linked to increased lipoprotein particle turnover, showcased by reduced levels of triglyceride-rich particles, as well as a metabolically healthier liver, assessed using whole-body lipidomic flux analysis. Conclusions: Altogether, our work unveils that MFGM/EV-containing food holds a potential for ameliorating age-related metabolic dysfunction in elderly individuals. Full article

Hemorrhage is the leading cause of preventable death in trauma care, requiring rapid and accurate detection to guide effective interventions. Hemorrhagic shock can be masked by underlying compensatory mechanisms, which may lead to delayed decision-making that can compromise casualty care. In this proof-of-concept study, we aimed to develop and evaluate machine learning models to predict Percent Estimated Blood Loss from a photoplethysmography waveform, offering non-invasive, field deployable solutions. Different model types were tuned and optimized using data captured during a hemorrhage and resuscitation swine study. Through this optimization process, we evaluated different time-lengths of prediction windows, machine learning model architectures, and data normalization approaches. Models were successful at predicting Percent Estimated Blood Loss in blind swine subjects with coefficient of determination values exceeding 0.8. This provides evidence that Percent Estimated Blood Loss can be accurately derived from non-invasive signals, improving its utility for trauma care and casualty triage in the pre-hospital and emergency medicine environment. Full article

(1) Background: Comparison of clinical outcomes between patients with moderate-severe aortic valve stenosis and those with mild or no aortic valve stenosis undergoing surgical revascularization for critical limb threating ischemia (CLTI). (2) Methods: Single center retrospective analysis of consecutive patients undergoing surgical lower limb revascularization with femoro-distal bypass for critical ischemia between 2016 and 2022. All patients were evaluated preoperatively by echocardiographic examination and divided into two cohorts: group A with moderate-severe aortic valve stenosis (AVA-cm² < or =1.5 cm²) and group B with mild or absent stenosis (AVA-cm² > 1.5 cm²). Primary outcomes were major limb amputation and mortality between the two groups. The rate of major cardiovascular events (stroke, myocardial infarction, sudden cardiac death) and change in “preoperative functional status” were the secondary outcomes. Descriptive statistics for continuous variables were performed by calculating means, standard deviation (SD) medians, and interquartile range (IQR) while, for categorical variables, frequencies and percentages were performed. Intergroup comparison tests, for continuous variables, were performed by t-test or corresponding nonparametric tests (Mann-Whitney test) while, for categorical variables, Chi-square test was used. Evaluation of cut-offs for the variable AVA-fx-cm², in terms of predictive of outcome outcomes, was calculated by ROC curves. Comparison between clinical and outcome variables was performed using logistic regression models. A total of 316 patients were analyzed and divided in two groups: 50 (16%) patients with moderate or severe aortic valve stenosis (group A) and 266 (84%) with no or mild aortic valve stenosis (AVA > 1.5 cm²). Patients in group A were significantly older than those in group B (78 years vs. 74 years, p value = 0.005); no other significant comorbidity differences were found between the two groups. The mean follow-up was 1178 days (SD 991 days; 2–3869 days). There were no statistically significant differences between group A and group B in terms of major amputation rate (20% vs. 16.5%; p = 0.895) and overall mortality (48.0% vs. 40.6%; p = 0.640). In the total cohort, the statistically significant variables associated with the major amputation were systemic perioperative complication (OR 5.83, 95% CI: 2.36, 14.57, p < 0.001), bypass-related complication within 30 days of surgery (OR 2.74, 95% CI: 1.17, 6.45, p = 0.020), surgical revascularization below the knee (OR 7.72, 95% CI: 1.53, 140.68, p = 0.049), and the presence of a previous cardiovascular event (OR 2.65, 95% CI: 1.14, 6.26, p = 0.024). In patients undergoing surgical revascularization for CLTI, no significant difference in major amputation rate and overall mortality was found between subjects with mild or no aortic valve stenosis and those with moderate/severe stenosis. As expected, overall mortality was higher in older patients with worse functional status. A significantly higher rate of limb amputation was found in those subjects undergoing subgenicular revascularization, early bypass failure, or previous cardiovascular event. Full article

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, projected to affect 55% globally by 2040. Up to one-third of NAFLD patients develop non-alcoholic steatohepatitis (NASH), with 40% progressing to fibrosis. However, there are currently few reliable tools to predict disease progression. Impaired mitochondrial dynamics, characterized by dysregulated fission, fusion, and mitophagy, have emerged as key events in NAFLD pathophysiology, contributing to hepatocyte death and inflammation. This study explored the transition from steatosis to NASH through transcriptomic analyses, including data from patients with steatosis and those with NASH at different fibrosis stages. By identifying a transcriptomic signature associated with disease progression, the study revealed increased expression of genes involved in mitochondrial dynamics in NASH compared to steatosis and during NASH-related fibrosis. Histological analyses highlighted the central role of Dynamin-related protein 1 (Drp1), a dynamin GTPase essential for mitochondrial fission and mitophagy. In human liver biopsies, Drp1 expression progressively increased from NAFLD to NASH and NASH-related fibrosis and cirrhosis, predominantly in Kupffer cells. These finding suggest Drp1 is a potential driver of the transition to more severe liver damage, making it a promising biomarker for NASH development and progression and a potential therapeutic target in metabolic disorders. Full article

Objectives: This study sought to echocardiographic manifestations and the related risk factors affecting the prognosis of isolated congenitally corrected transposition of the great arteries (CCTGA). Methods: A total of 143 patients (≥18 years of age) were diagnosed with isolated CCTGA at Anzhen Hospital. The patients were classified as the operation group and the non-operation group depending on whether they had undergone tricuspid valve surgery. The echocardiographic data and follow-up were compared, and the primary outcomes examined were defined as death or heart transplantation. Results: The average age of 143 patients with isolated CCTGA was 39.93 ± 13.50 years. Tricuspid valve surgery was performed in 31 patients with isolated CCTGA, and 112 patients did not undergo tricuspid valve surgery. The incidence of tricuspid valve structural changes in the operation group was 39.1%, and this group had higher numbers of patients with right ventricular diastolic diameter, right ventricular systolic diameter, left atrial dimensions, and regurgitation before surgery compared with the non-operation group (p < 0.05). Follow-up results showed no significant difference in the number of death/heart transplantations, and the incidence of systemic ventricular ejection fraction (SVEF) < 40% between the two groups. The survival rate of the surgery group was higher than that of the non-surgery group, although not statistically significant (p = 0.123). Age, right ventricular end-diastolic diameter, and decreased SVEF at the first diagnosis are independent predictive risk factors for major adverse outcomes. Conclusions: Adult patients with isolated CCTGA may have structural abnormalities in their tricuspid valves. There were no significant differences in the incidence of adverse outcomes, morphological right ventricular systolic dysfunction, and survival between the surgery group and the non-surgery group. However, this study is a retrospective study, and the sample size of the surgical group is relatively small, which may limit the generalizability of the research conclusions. In the future, a prospective, large-scale study will be conducted to evaluate the therapeutic effect of tricuspid valve surgery on such patients. Full article

Cardiovascular diseases (CVDs) remain the leading cause of death globally, underscoring the urgent need for data-driven early diagnostic tools. This study proposes a multilayer artificial neural network (ANN) model for heart disease prediction, developed using a real-world clinical dataset comprising 13,981 patient records. Implemented on the Orange data mining platform, the ANN was trained using backpropagation and validated through 10-fold cross-validation. Dimensionality reduction via principal component analysis (PCA) enhanced computational efficiency, while Shapley additive explanations (SHAP) were used to interpret model outputs. Despite achieving 83.4% accuracy and high specificity, the model exhibited poor sensitivity to disease cases, identifying only 76 of 2233 positive samples, with a Matthews correlation coefficient (MCC) of 0.058. Comparative benchmarks showed that random forest and support vector machines significantly outperformed the ANN in terms of discrimination (AUC up to 91.6%). SHAP analysis revealed serum creatinine, diabetes, and hemoglobin levels to be the dominant predictors. To address the current study’s limitations, future work will explore LIME, Grad-CAM, and ensemble techniques like XGBoost to improve interpretability and balance. This research emphasizes the importance of explainability, data representativeness, and robust evaluation in the development of clinically reliable AI tools for heart disease detection. Full article

Resistance of various bacterial pathogens to the activity of clinically approved drugs currently leads to serious infections, rapid spread of difficult-to-treat diseases, and even death. Taking the threats for human health in mind, researchers are focused on the isolation and characterization of novel natural products, including plant secondary metabolites. These molecules serve as inspiration and a suitable structural platform in the design and development of novel semi-synthetic and synthetic derivatives. All considered compounds have to be adequately evaluated in silico, in vitro, and in vivo using relevant approaches. The current review paper briefly focuses on the chemical and metabolic properties of resveratrol (1), as well as its oligomeric structures, viniferins, and viniferin-based molecules. The core scaffolds of these compounds contain so-called privileged structures, which are also present in many clinically approved drugs, indicating that those natural, properly substituted semi-synthetic, and synthetic molecules can provide a notably broad spectrum of beneficial pharmacological activities, including very impressive antimicrobial efficiency. Except for spectral verification of their structures, these compounds suffer from the determination or prediction of other structural and physicochemical characteristics. Therefore, the structure–activity relationships for specific dihydrodimeric and dimeric viniferins, their bioisosteres, and derivatives with notable efficacy in vitro, especially against chosen Gram-positive bacterial strains, are summarized. In addition, a set of descriptors related to their structural, physicochemical, pharmacokinetic, and toxicological properties is generated using various computational tools. The obtained values are compared to those of clinically approved drugs. The particular relationships between these in silico parameters are also explored. Full article

Peanut (Arachis hypogaea L.) is a globally important oilseed cash crop, yet its limited genetic diversity and unique reproductive biology present persistent challenges for conventional crossbreeding. Traditional breeding approaches are often time-consuming and inadequate, mitigating the pace of cultivar development. Essential for double fertilization and programmed cell death (PCD), DUF679 membrane proteins (DMPs) represent a membrane protein family unique to plants. In the present study, a comprehensive analysis of the DMP gene family in peanuts was conducted, which included the identification of 21 family members. Based on phylogenetic analysis, these genes were segregated into five distinct clades (I–V), with AhDMP8A, AhDMP8B, AhDMP9A, and AhDMP9B in clade IV exhibiting high homology with known haploid induction genes. These four candidates also displayed significantly elevated expression in floral tissues compared to other organs, supporting their candidacy for haploid induction in peanuts. Subcellular localization prediction, confirmed through co-localization assays, demonstrated that AhDMPs primarily localize to the plasma membrane, consistent with their proposed roles in the reproductive signaling process. Furthermore, chromosomal mapping and synteny analyses revealed that the expansion of the AhDMP gene family is largely driven by whole-genome duplication (WGD) and segmental duplication events, reflecting the evolutionary dynamics of the tetraploid peanut genome. Collectively, these findings establish a foundational understanding of the AhDMP gene family and highlight promising targets for future applications in haploid induction-based breeding strategies in peanuts. Full article

Background/Objectives: Hypertension (HTN) continues to be a leading cause of death and disability in older adults, especially in the southeastern United States. A cross-sectional study was conducted to evaluate the relationships among measured, diagnosed, and treated (HTN) in community-dwelling adults participating in student-led health screenings in eastern Alabama. Methods: Between 2017 and 2019, students from health-related disciplines facilitated screenings at 23 community and independent living sites to conduct health assessments, including measuring blood pressure (BP), obtaining medical history, and evaluating current prescriptions. Statistical analyses including chi-square tests, t-tests, and backward stepwise linear regression were performed. Results: The current sample includes data from 357 adults aged 60 to 99 years (mean age 74.6 ± 8.7), who were 70.9% females, 60.8% identifying as Black/African American (BA), and 36.8% residing in rural areas. The majority of clients had a prior HTN diagnosis (71.1%) and/or currently measured HTN (78.7%). Forty-three percent of adults screened had measured, diagnosed, and pharmaceutically treated HTN, while 31% had measured but untreated HTN. Black clients had higher measured systolic and diastolic BP and were more likely to also have been diagnosed with HTN (p < 0.05 for all). Linear regression indicated that lower systolic BP was predicted by not living alone (p = 0.003), White race (p = 0.004), and previous HTN diagnosis (p = 0.012), while female gender (p = 0.079) and decreasing body mass index (p = 0.053) had marginal predictive value. Conclusions: These results indicate that awareness and screening of HTN in this population are noteworthy, though management of the disease through ongoing screening and referrals is essential to reduce disparities. Full article

Background/Objectives: Artificial intelligence (AI)-enabled electrocardiogram (ECG) analysis may assist in objective and reproducible risk stratification. However, the prognostic utility of serial ECGs, particularly the follow-up ECG prior to discharge, has not been extensively studied. This study aimed to evaluate whether dynamic changes in AI-predicted ECG risk scores could enhance prediction of post-discharge outcomes. Methods: This retrospective cohort study included 11,508 ED visits from a single medical center where patients underwent two ECGs and were directly discharged. We stratified the mortality risk of patients as low risk, medium risk, and high risk based on the first and follow-up ECG prior to discharge using AI-enabled ECG models. The Area Under the Curve (AUC) was calculated for the predictive performance of the two ECGs. Kaplan–Meier (KM) curves were used for 90-day mortality analysis, and the Cox proportional hazards model was utilized to compare the risk of death across categories. Results: The AI-enabled ECG risk prediction model, based on the initial and follow-up ECGs prior to discharge, indicated risk transitions among different groups. The AUC for mortality risk was 78.6% for the first ECG and 83.3% for the follow-up ECG. KM curves revealed a significant increase in 90-day mortality for patients transitioning from low to medium/high risk upon discharge (Hazard Ratio: 6.01; Confidence Interval: 1.70–21.27). Conclusions: AI-enabled ECGs obtained prior to discharge provide superior mortality risk stratification for ED patients compared to initial ECGs. Patients classified as medium- or high-risk at discharge require careful consideration, whereas those at low risk can generally be discharged safely. Although AI-ECG alone does not replace comprehensive risk assessment, it offers a practical tool to support clinical judgment, particularly in the dynamic ED environment, by aiding safer discharge decisions. Full article

Background/Objectives: Clinical stability within 24 h prior to discharge is a key metric for safe care transitions in hospitalised patients with community-acquired pneumonia (CAP). However, its association with post-discharge outcomes, particularly readmissions, remains underexplored. This study assessed whether clinical instability before discharge is associated with 30-day mortality, readmissions, or a composite of both in hospitalised CAP patients. Methods: This retrospective cohort study included adults (≥18 years) admitted with CAP to two tertiary Australian hospitals between 1 January 2020 and 31 December 2023. Clinical instability was defined as abnormal vital signs (temperature, heart rate, respiratory rate, blood pressure, or oxygen saturation) within 24 h before discharge. Pneumonia severity was assessed using the CURB-65 score and frailty using the Hospital Frailty Risk Score. Multilevel logistic regression models were used to evaluate associations with outcomes, adjusting for age, sex, comorbidities, frailty, disease severity, microbiological aetiology, antibiotics prescribed during admission, and prior healthcare use. Competing risk regression accounted for death when analysing readmissions. Results: Of 3984 patients, 20.4% had clinical instability within 24 h before discharge. The composite outcome occurred in 21.9% patients, with 15.8% readmitted and 6.1% dying within 30 days. Clinical instability was significantly associated with the composite outcome (adjusted odds ratio [aOR] 1.73, 95% CI 1.42–2.09, p < 0.001), primarily driven by increased mortality risk (aOR 3.70, 95% CI 2.73–5.00, p < 0.001). However, no significant association was found between clinical instability and readmissions (aOR 1.16, 95% CI 0.93–1.44, p > 0.05). Conclusions: Clinical instability within 24 h before discharge predicts worse outcomes in CAP patients, driven by increased mortality risk rather than readmissions. Full article

Background/Objectives: Sepsis-induced cardiomyopathy (SIC) is a serious clinical disorder with a high death rate. Qifu decoction (QFD) is a renowned traditional Chinese medicine with documented pharmacological actions, such as anti-inflammatory, anti-oxidant and anti-apoptosis activities, and it has good therapeutic effects on cardiovascular diseases. This study aimed to reveal the cardioprotective effects and underlying mechanisms of QFD against SIC. Methods: Electrocardiography, histopathological examination, and biochemical indicator determination were carried out to investigate the cardioprotective effects of QFD in the treatment of LPS-induced SIC mice. Metabolomics and network pharmacology strategies were employed to preliminarily analyze and predict the mechanisms of QFD against SIC. Molecular docking and Western blot were further applied to validate the core targets and potential pathways for the treatment of SIC in in vitro and in vivo models. Results: It was found that QFD considerably enhanced cardiac function; attenuated myocardial injury; and reduced the serum levels of LDH, CK-MB, IL-1β, and TNF-α by 28.7%, 32.3%, 38.6%, and 36.7%, respectively. Metabolomic analysis showed that QFD could regulate seven metabolic pathways, namely, glutathione metabolism; alanine, aspartate, and glutamate metabolism; arachidonic acid metabolism; glycerophospholipid metabolism; purine metabolism; sphingolipid metabolism; and fatty acid metabolism. Network pharmacology suggested that the anti-SIC effect of QFD may be mediated through the TNF, toll-like receptor, NOD-like receptor, NF-κB, and PPAR signaling pathways. Additionally, 26 core targets were obtained. Molecular docking revealed that active ingredients such as formononetin, kaempferol, quercetin, and (R)-norcoclaurine in QFD had a high affinity for binding to PPARα and TLR4. Further Western blot validation indicated that QFD could regulate the protein levels of NLRP3, TLR4, NF-κB, IL-6, TNF-α, COX2, sPLA2, PPARα, CPT1B, and CPT2. Conclusions: This study demonstrates that QFD can alleviate SIC by suppressing the TLR4/NF-κB/NLRP3 inflammatory pathway and modulating impaired FAO through the activation of the PPARα/CPT pathway, highlighting QFD as a promising candidate drug for SIC treatment. Full article

Monkeypox virus (MPXV) has caused 148,892 confirmed cases and 341 deaths from 137 countries worldwide, as reported by the World Health Organization (WHO), highlighting the urgent need for effective vaccines to prevent the spread of MPXV. Traditional vaccine development is low-throughput, expensive, time consuming, and susceptible to reversion to virulence. Alternatively, a reverse vaccinology approach offers a rapid, efficient, and safer alternative for MPXV vaccine design. Here, MPXV proteins associated with viral infection were analyzed for immunogenic epitopes to design multi-epitope vaccines based on B-cell, CD4+, and CD8+ epitopes. Epitopes were selected based on allergenicity, antigenicity, and toxicity parameters. The prioritized epitopes were then combined via peptide linkers and N-terminally fused to various protein adjuvants, including PADRE, beta-defensin 3, 50S ribosomal protein L7/12, RS-09, and the cholera toxin B subunit (CTB). All vaccine constructs were computationally validated for physicochemical properties, antigenicity, allergenicity, safety, solubility, and structural stability. The three-dimensional structure of the selected construct was also predicted. Moreover, molecular docking and molecular dynamics (MD) simulations between the vaccine and the TLR-4 immune receptor demonstrated a strong and stable interaction. The vaccine construct was codon-optimized for high expression in the E. coli and was finally cloned in silico into the pET21a (+) vector. Collectively, these results could represent innovative tools for vaccine formulation against MPXV and be transformative for other infectious diseases. Full article

Ferroptosis, an iron-dependent form of regulated cell death, plays a critical role in various diseases. Accurate identification of ferroptosis-related proteins (FRPs) is essential for understanding their underlying mechanisms and developing targeted therapeutic strategies. Existing computational methods for FRP prediction often exhibit limited accuracy and suboptimal performance. In this study, we harnessed the power of pre-trained protein language models (PLMs) to develop a novel machine learning framework, termed PLM-FRP, which utilizes deep learning-derived features for FRP identification. By integrating ESM2 embeddings with traditional sequence-based features, PLM-FRP effectively captures complex evolutionary relationships and structural patterns within protein sequences, achieving a remarkable accuracy of 96.09% on the benchmark dataset and significantly outperforming previous state-of-the-art methods. We anticipate that PLM-FRP will serve as a powerful computational tool for FRP annotation and facilitate deeper insights into ferroptosis mechanisms, ultimately advancing the development of ferroptosis-targeted therapeutics. Full article