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Numerous studies have documented that high-intensity or prolonged exercise is associated with increased oxidative stress and modification of antioxidant status. Polyphenol-rich dietary supplements seem to be the compounds that can upregulate the endogenous antioxidant defense system and consequently prevent muscle damage, support recovery. As berry fruits are at the top of the list of the richest polyphenol food sources, supplements containing berries have become the subject of interest in the context of counteracting exercise-induced oxidative stress and the development of cardiovascular diseases. The purpose of this review is to summarize current knowledge on the effects of berry-derived polyphenol supplementation on exercise-induced oxidative stress and cardiovascular health in physically active individuals. Based on the available literature, blackcurrant supplementation, with its richest version being New Zealand blackcurrant extract, is the most commonly explored berry fruit, followed by chokeberries and blueberries. Although several studies have documented the significant and beneficial influence of berry-derived supplements on redox status and cardiovascular response, some inconsistencies remain. The presented findings should be interpreted with caution due the limited number of available studies, particularly with the participation of physically active individuals. Further research is needed to reveal more comprehensive and accurate data concerning the impact of berry-derived supplements on exercise-induced outcomes taking into account the type of supplement, time of administration, and dosage. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the potential benefits and challenges of integrating oral microbiome research into the clinical management of oral potentially malignant disorders (OPMD) and oral squamous cell carcinoma (OSCC). The oral microbiome has gained significant attention for its role in the pathogenesis and progression of these conditions, with emerging evidence suggesting its value as a diagnostic and prognostic tool. By critically analyzing current evidence and methodological considerations, this manuscript examines whether microbiome analysis in biopsy samples can aid in the early detection, prognosis, and management of OPMD and OSCC. The complexity and dynamic nature of the oral microbiome require a multifaceted approach to fully understand its clinical utility. Based on this review, we conclude that studying the oral microbiome in this context holds significant promise but also faces notable challenges, including methodological variability and the need for standardization. Ultimately, this manuscript addresses the question, "Should such research be undertaken, given the intricate interactions of various factors and the inherent obstacles involved?", and also emphasizes the importance of further research to optimize clinical applications and improve patient outcomes. [ABSTRACT FROM AUTHOR]

Background: Dysregulation in phosphoinositide-3-kinase alpha (PI3Kα) signaling is implicated in the development of various cancers, including triple-negative breast cancer (TNBC). We have previously synthesized a series of N-phenyl-6-chloro-4-hydroxy-2-quinolone-3-carboxamides as targeted inhibitors against PI3Kα. Herein, two drug candidates, R7 and R11, were selected to be further investigated as a nanoparticle (NP) formulation against TNBC. Methods: R7 and R11 were entrapped in D-α-tocopheryl poly(ethylene glycol) 1000 succinate (TPGS) polymeric NPs by nanoprecipitation. Following their physicochemical characterization, the anticancer activity of the compounds and their NP formulations was evaluated in the TNBC cell line MDA-MB-231 by conducting viability, uptake, and apoptosis assays, as well as penetration assays in a multicellular tumor spheroid model. Results: The NPs exhibited a particle size of 100–200 nm, excellent drug loading efficiencies, and sustained release under physiologic conditions. Viability assays revealed superior potency for the NP formulations, with IC50 values of 20 µM and 30 µM for R7- and R11-loaded NPs, respectively, compared to the free compounds, which exhibited IC50 values of 280 µM and 290 µM for R7 and R11, respectively. These results were attributed to the inherent antiproliferative activity of TPGS, as evidenced by the cytotoxicity of the drug-free NPs, as well as the enhanced cellular uptake enabled by the NP vehicle, as demonstrated by fluorescence microscopy imaging and flow cytometry measurements. Further investigations showed that the NPs promoted apoptosis via a mitochondrial-dependent pathway that involved the activation of proapoptotic caspases. Moreover, the NP formulations enhanced the penetration ability of the free compounds in multicellular tumor spheroids, causing a time- and concentration-dependent disruption of the spheroids. Conclusions: Our findings highlight the important role nanotechnology can play in improving the biopharmaceutical properties of new drug candidates and facilitating their in vivo translation. [ABSTRACT FROM AUTHOR]

Background/Objectives: Down syndrome (DS) is the most common cause of early-onset Alzheimer's disease (AD). Dietary choline has been proposed as a modifiable factor to improve the cognitive and pathological outcomes of AD and DS, especially as many do not reach adequate daily intake levels of choline. While lower circulating choline levels correlate with worse pathological measures in AD patients, choline status and intake in DS is widely understudied. Perinatal choline supplementation (Ch+) in the Ts65Dn mouse model of DS protects offspring against AD-relevant pathology and improves cognition. Further, dietary Ch+ in adult AD models also ameliorates pathology and improves cognition. However, dietary Ch+ in adult Ts65Dn mice has not yet been explored; thus, this study aimed to supply Ch+ throughout adulthood to determine the effects on cognition and DS co-morbidities. Methods: We fed trisomic Ts65Dn mice and disomic littermate controls either a choline normal (ChN; 1.1 g/kg) or a Ch+ (5 g/kg) diet from 4.5 to 14 months of age. Results: We found that Ch+ in adulthood failed to improve genotype-specific deficits in spatial learning. However, in both genotypes of female mice, Ch+ significantly improved cognitive flexibility in a reverse place preference task in the IntelliCage behavioral phenotyping system. Further, Ch+ significantly reduced weight gain and peripheral inflammation in female mice of both genotypes, and significantly improved glucose metabolism in male mice of both genotypes. Conclusions: Our findings suggest that adulthood choline supplementation benefits behavioral and biological factors important for general well-being in DS and related to AD risk. [ABSTRACT FROM AUTHOR]

Simple Summary: CR6 interacting factor 1 (CRIF1) plays an essential role in the regulation of mitochondrial function. We provide important details to demonstrate that CRIF1 deletion-induced mitochondrial damage has an antitumor effect via TIGAR induction in BT549 breast cancer cells. CRIF1 deficiency results in OXPHOS dysfunction, which has been investigated as a potential therapeutic target for the treatment of cancer. Background/Objectives: Mitochondrial oxidative phosphorylation (OXPHOS) has been exploited as a therapeutic target in cancer treatments because of its crucial role in tumorigenesis. CR6-interacting factor 1 (CRIF1), a mitochondrial ribosomal subunit protein, is essential for the regulation of mitochondrial OXPHOS capacity. However, the mechanism of CRIF1 in triple-negative breast cancer (TNBC) cells remains unclear. Methods/Results: We showed that the downregulation of CRIF1 reduced cell proliferation in the TNBC cell lines MDA-MB-468, MDA-MB-231, and, especially, BT549. In addition, wound scratch and Transwell assays showed that CRIF1 deficiency inhibited the migration and invasion of BT549 cells. CRIF1 downregulation resulted in the suppression of mitochondrial bioenergetics in BT549 cells, specifically affecting the inhibition of OXPHOS complexes I and II. This was evidenced by a decrease in the mitochondrial oxygen consumption rate and the depolarization of the mitochondrial membrane potential. Damage to mitochondria resulted in a lower adenosine triphosphate level and an elevated production of mitochondrial reactive oxygen species. In addition, CRIF1 deficiency decreased hypoxia-inducible factor 1α accumulation, NADPH synthesis, and TP53-induced glycolysis and apoptosis regulator (TIGAR) expression in BT549 cells. These events contributed to G0/G1-phase cell cycle inhibition and the upregulation of the cell cycle protein markers p53, p21, and p16. Transfection with a TIGAR overexpression plasmid reversed these effects and prevented CRIF1 downregulation-induced proliferation and migration reduction. Conclusions: These results indicate that blocking mitochondrial OXPHOS synthesis via CRIF1 may have a therapeutic antitumor effect in BT549 TNBC cells. [ABSTRACT FROM AUTHOR]

Distributed acoustic sensing (DAS) is a promising technology for providing dense (metre-scale) sampling of the seismic wavefield. However, harnessing this potential for earthquake detection with accurate phase picking and associated localization remains challenging. Single-channel algorithms are limited by individual channel noise, while machine learning and semblance methods are typically imited to specific geological settings, have no physically constrained phase association and/or require specific fibre geometries. Here, we present a method that seeks to detect seismicity for any geological setting, applicable for any fibre geometry, and combining both fibreoptic and conventional seismometer data to maximize the information used for detection and source localization. This method adapts a proven back-migration detection method to also include DAS observations, migrating energy from many receivers back in time to search for localized peaks in energy, corresponding to seismic sources. The strengths of this method are capitalizing on coherency over many channels to enhance detection sensitivity even in high-noise environments compared to single-channel algorithms, applicability to arbitrary fibre geometries, as well as built-in, physics-informed phase association and source localization. We explore the performance of the method using three geologically and geometrically diverse settings: a glacier, a volcanic eruption and a geothermal borehole. Our results evidence the effect of spatial-sampling extent and non-optimal fibreoptic geometries, accounting for P - and S -wave sensitivity, coupling effects and how the sensitivity of native fibreoptic strain measurements to shallow subsurface heterogeneities can affect detection. Finally, we attempt to also present a method-ambivalent overview of key challenges facing fibreoptic earthquake detection and possible avenues of future work to address them. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has exposed critical weaknesses in the global health system, highlighting the urgent need for a coordinated international approach to pandemic prevention and management. As negotiations for a new WHO pandemic treaty progress, the effective integration of animal welfare is crucial. This paper aims to investigate the perspectives of key civil society organizations on the integration of animal welfare provisions into the pandemic treaty. Through a thematic analysis of documents prepared by FOUR PAWS, Wildlife Conservation Society, and Action for Animal Health between 2020–2023, five major themes are identified: prevention of zoonotic spillover, One Health approach, animal health systems and infrastructure, sustainable and ethical animal management practices, and policy coherence and governance. A comparative analysis of these themes against the April 2024 draft of the pandemic treaty reveals areas of alignment and divergence. Due to the ongoing controversies and the need for further improvements, the WHO's intergovernmental negotiating body was unable to finalize the treaty text for the 77th World Health Assembly in May 2024, leading to an extended mandate until 2025. Based on the findings, the paper proposes recommendations to strengthen the integration of animal welfare into the treaty, arguing that incorporating these recommendations is critical for developing a transformative, equitable, and effective treaty that addresses the systemic drivers of pandemic risk. [ABSTRACT FROM AUTHOR]

LACTB is identified as a tumor suppressor in several tumors. However, preliminary study reveals that LACTB is overexpressed in osteosarcoma and indicates poor prognosis. Two missense mutations (rs34317102 and rs2729835) exist simultaneously in 92.31% of osteosarcoma patients and cause M5L and R469K double mutations in LACTB, suggesting the biologic function of LACTB protein may be altered in osteosarcoma. Moreover, LACTBM5L+R469K overexpression can promote malignant progression in different tumors, which suggests that the M5L and R469K mutations confer oncogene‐like functions to LACTB. Mechanistically, LACTBM5L+R469K not only reduces the wild type p53 via enhancing PSMB7 catalytic activity, but also protects p53R156P protein from lysosomal degradation, which suggesting LACTBM5L+R469K is a dual‐regulator for wt‐p53 and mutant p53, and derive oncogene‐like functions. More importantly, clavulanate potassium, a bacterial β‐lactamase inhibitor, can inhibit osteosarcoma proliferation and sensitize osteosarcoma to cisplatin by binding and blocking LACTBM5L+R469K. These findings revealed that the M5L and R469K double mutations can diminish the tumor suppressive ability of wild type LACTB and provide oncogene‐like functions to LACTB. Inhibiting LACTBM5L+R469K can suppress the progression of osteosarcoma harbouring wild‐type or mutant p53. Clavulanate potassium is a promising drug by targeting LACTBM5L+R469K‐p53 pathway for the treatment of osteosarcoma patients. [ABSTRACT FROM AUTHOR]

Over the last decade, distributed acoustic sensing (DAS) has received growing attention in the field of seismic acquisition and monitoring due to its potential high spatial sampling rate, low maintenance cost and high resistance to temperature and pressure. Despite its undeniable advantages, DAS faces some challenges, including a low signal-to-noise ratio, which partly results from the instrument-specific noise generated by DAS interrogators. We present a comparison between two deep learning approaches to address DAS hardware noise and enhance the quality of DAS data. These approaches have the advantage of including real instrumental noise in the neural network training dataset. For the supervised learning (SL) approach, real DAS instrumental noise measured on an acoustically isolated coil is added to synthetic data to generate training pairs of clean/noisy data. For the second method, the Noise2Noise (N2N) approach, the training is performed on noisy/noisy data pairs recorded simultaneously on the downgoing and upgoing parts of a downhole fiber-optic cable. Both approaches allow for the removal of unwanted noise that lies within the same frequency band of the useful signal, a result that cannot be achieved by conventional denoising techniques employing frequency filtering. [ABSTRACT FROM AUTHOR]

The growing energy demand and the need for climate mitigation strategies have spurred interest in the application of CO2–enhanced oil recovery (CO2–EOR) and carbon capture, utilization, and storage (CCUS). Furthermore, natural hydrogen (H2) production and underground hydrogen storage (UHS) in geological media have emerged as promising technologies for cleaner energy and achieving net–zero emissions. However, selecting a suitable geological storage medium is complex, as it depends on the physicochemical and petrophysical characteristics of the host rock. Solubility is a key factor affecting the above–mentioned processes, and it is critical to understand phase distribution and estimating trapping capacities. This paper conducts a succinct review of predictive techniques and present novel simple and non–iterative predictive models for swift and reliable prediction of solubility behaviors in CO2–brine and H2–brine systems under varying conditions of pressure, temperature, and salinity (T–P–m salts), which are crucial for many geological and energy–related applications. The proposed models predict CO2 solubility in CO2 + H2O and CO2 + brine systems containing mixed salts and various single salt systems (Na+, K+, Ca2+, Mg2+, Cl−, SO42−) under typical geological conditions (273.15–523.15 K, 0–71 MPa), as well as H2 solubility in H2 + H2O and H2 + brine systems containing NaCl (273.15–630 K, 0–101 MPa). The proposed models are validated against experimental data, with average absolute errors for CO2 solubility in pure water and brine ranging between 8.19 and 8.80% and for H2 solubility in pure water and brine between 4.03 and 9.91%, respectively. These results demonstrate that the models can accurately predict solubility over a wide range of conditions while remaining computationally efficient compared to traditional models. Importantly, the proposed models can reproduce abrupt variations in phase composition during phase transitions and account for the influence of different ions on CO2 solubility. The solubility models accurately capture the salting–out (SO) characteristics of CO2 and H2 gas in various types of salt systems which are consistent with previous studies. The simplified solubility models for CO2 and H2 presented in this study offer significant advantages over conventional approaches, including computational efficiency and accuracy across a wide range of geological conditions. The explicit, derivative–continuous nature of these models eliminates the need for iterative algorithms, making them suitable for integration into large–scale multiphase flow simulations. This work contributes to the field by offering reliable tools for modeling solubility in various subsurface energy and environmental–related applications, facilitating their application in energy transition strategies aimed at reducing carbon emissions. [ABSTRACT FROM AUTHOR]

Blueberries (Vaccinium corymbosum) undergo significant texture changes during development and ripening, notably a consistent decrease in firmness, which affects fruit quality, consumer preference, transportability, and shelf life. This study examined the composition and structural modifications of the cell wall in five commercially available blueberry varieties with differing firmness levels at harvest. Our approach integrated various biochemical techniques for a comprehensive analysis of cell wall components to elucidate firmness differences at the harvest stage. One of the conclusions was the relationship between a low degree of pectin methylesterification and the presence of increased egg-box structures, which correlated with increased firmness. The data suggest that low-abundance pectins in blueberry cell walls, such as rhamnogalacturonan-I participate in firmness modulation through their side branches or by linking to arabinogalactan proteins. Additionally, the xyloglucan structure can be one of the determinants of fruit firmness. Although, this work provides a broad insight into the relationship between cell wall composition and firmness in blueberry, a more detailed analysis, specifically focusing on pectin and hemicelluloses, would be of significant value. [ABSTRACT FROM AUTHOR]

Background: Mild cognitive impairment (MCI) is a major risk factor for delirium. Few studies with mid- to long-term follow-up periods have examined delirium, MCI, and the conversion of MCI to dementia. This prospective, longitudinal cohort study aims to assess the incidence of dementia after delirium onset in patients with MCI and to develop an artificial intelligence algorithm for predicting the conversion of MCI to dementia. Methods: A 30-day evaluation for delirium will be performed for adults aged ≥ 65 years diagnosed with MCI who score 18–23 on the Korean Mini-Mental State Exam. Individuals exhibiting delirium at least once will be classified into the delirium group and the remainder into the non-delirium group. Over 3 years, patients will undergo follow-ups for survival and conversion to dementia at 30-day intervals to analyze risk factors for delirium and clinical outcomes. Differences between the two groups will be analyzed using the chi-square and independent t-tests. Kaplan-Meier survival and Cox proportional hazard regression will be used to assess the effects on 30-day, 60-day, 12-month, 24-month, and 36-month mortality, whereas linear regression will be used to assess the length of stay at long-term care facilities and medical costs. Discussion: The results will emphasize the importance of preventing delirium in MCI patients, and preventive interventions can be strengthened. Trial Registration: NCT05113446 (ClinicalTrials.gov). Registered 9 November 2021 - Retrospectively registered. [ABSTRACT FROM AUTHOR]

Introduction: Obesity is a disease characterized by the excessive accumulation of fat. Concurrently, thyroid carcinoma (THCA) stands as the foremost endocrine malignancy. Despite the observed escalation in concurrent prevalence of both conditions, the underlying interconnections remain elusive. This indicates the need to identify potential biomarkers to predict the pathways through which obesity and THCA coexist. Methods: The study employed a variety of methods, including differential gene expression analysis, Weighted Gene Co-expression Network Analysis (WGCNA), and gene enrichment analysis. It was also supplemented with immunohistochemical data from the Human Protein Atlas (HPA), advanced machine learning techniques, and related experiments such as qPCR, to identify important pathways and key genes shared between obesity and THCA. Results: Through differential gene expression analysis, WGCNA, and machine learning methods, we identified three biomarkers (IL6R, GZMB, and MSR1) associated with obesity. After validation analysis using THCA-related datasets and biological experiments, we selected Macrophage Scavenger Receptor 1 (MSR1) as a key gene for THCA analysis. The final analysis revealed that MSR1 is closely related to the degree of immune cell infiltration in patients with obesity and THCA, suggesting that this gene may be a potential intervention target for both obesity and THCA. Discussion: Our research indicates that MSR1 may influence the occurrence and development of obesity and THCA by regulating the infiltration level of immune cells. This lays the foundation for future research on targeted therapies based on their shared mechanisms. [ABSTRACT FROM AUTHOR]

Background: Inflammatory bowel disease (IBD) is a chronic, inflammatory, and autoimmune disorder, and its incidence of comorbid with major depressive disorder (MDD) is significantly higher than the general population. However, many patients lack proper recognition and necessary psychological health treatments. We aimed to identify potential biomarkers and mechanisms involved in the development of IBD comorbid with MDD (IBD-MDD). Methods: We utilized IBD and MDD-related datasets from the GEO database for differential gene expression analysis, protein-protein interaction (PPI) and pathway enrichment analysis, random forest algorithm, LASSO regression analysis, and construction of a disease prediction model. We assessed the accuracy of the model using ROC curve, explored potential mechanisms through immune infiltration analysis, and validated candidate biomarkers using peripheral blood samples from patients in our center's cohort. Results: We identified 484 IBD-related secreted proteins and 142 key module genes associated with MDD. PPI analysis revealed two crucial modules primarily involved in inflammation and immune regulation. We identified four diagnostic genes (HGF, SPARC, ADAM12, and MMP8) from the 21 shared genes between IBD-related secreted proteins and MDD key module genes, constructed a nomogram model and confirmed its accuracy using ROC curve from an external independent dataset. Immune infiltration analysis revealed significant associations between the four diagnostic genes, and cellular immune dysregulation in MDD. Finally, we validated the expression patterns of the four diagnostic genes in our cohort. Conclusions: Our study discovered four candidate biomarkers for IBD-MDD, providing new insights for the diagnosis and therapeutic intervention of serum-based IBD comorbid with MDD. [ABSTRACT FROM AUTHOR]

Sustainable aviation fuels (SAFs), produced from waste and renewable sources, are a promising means for reducing net greenhouse gas emissions from air travel while still maintaining the quality of air transportation expected. In this work, the catalytic co-pyrolysis of polystyrene and pine with red mud (bauxite residue) and ZSM-5 catalysts at temperatures of 450 °C, 500 °C, and 550 °C was investigated as a method for producing aromatic hydrocarbons with carbon numbers ranging from 7 to 17 for use as additives to blend with SAF produced through other methods to add the required quantity of aromatic molecules to these blends. The maximum yield of kerosene-range aromatic hydrocarbons was 620 mg per gram of feedstock (62% of feedstock was converted to kerosene-range hydrocarbons) obtained at 550 °C in the presence of ZSM-5. Additionally, it was noted that a positive synergy exists between pine and polystyrene feedstocks during co-pyrolysis that cracks solid and liquid products into gaseous products similarly to that of a catalyst. The co-pyrolysis of pine and polystyrene without a catalyst produced on average 17% or 36.3 mg more kerosene-range hydrocarbons than predicted, with a maximum yield of 266 mg of C7–C17 aromatic hydrocarbons per gram of feedstock (26.6% conversion of initial feedstock) obtained at 550 °C. [ABSTRACT FROM AUTHOR]

Background: Lung adenocarcinoma (LUAD) is a widely occurring cancer with a high death rate. Radiomics, as a high-throughput method, has a wide range of applications in different aspects of the management of multiple cancers. However, the molecular mechanism of LUAD by combining transcriptomics and radiomics in order to probe LUAD remains unclear. Methods: The transcriptome data and radiomics features of LUAD were extracted from the public database. Subsequently, we used weighted gene co-expression network analysis (WGCNA) and a series of machine learning algorithms including Random Forest (RF), Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression, and Support Vector Machines Recursive Feature Elimination (SVM-RFE) to proceed with the screening of diagnostic genes for LUAD. In addition, the CIBERSORT and ESTIMATE algorithms were utilized to assess the association of these genes with immune profiles. The LASSO algorithm further identified the features most relevant to the expression levels of LUAD diagnostic genes and validated the model based on receiver operating characteristic (ROC), precision-recall (PR), calibration curves and decision curve analysis (DCA) curves. Finally, RT-qPCR, transwell and cell counting kit-8 (CCK8) based assays were performed to assess the expression levels and potential functions of the screened genes in LUAD cell lines. Results: We screened a total of 214 modular genes with the highest correlation with LUAD samples based on WGCNA, of which 192 genes were shown to be highly expressed in LUAD patients. Subsequently, three machine learning algorithms identified a total of four genes, including UBE2T, TEDC2, RCC1, and FAM136A, as diagnostic molecules for LUAD, and the ROC curves showed that these diagnostic molecules had good diagnostic performance (AUC values of 0.989, 0.989, 989, and 0.987, respectively). The expression of these diagnostic molecules was significantly higher in tumor samples than in normal para-cancerous tissue samples and also correlated significantly and negatively with stromal and immune scores. Specifically, we also constructed a model based on TEDC2 expression consisting of seven radiomic features. Among them, the ROC and PR curves showed that the model had an AUC value of up to 0.96, respectively. Knockdown of TEDC2 slowed down the proliferation, migration and invasion efficiency of LUAD cell lines. Conclusion: In this study, we screened for diagnostic markers of LUAD and developed a non-invasive radiomics model by innovatively combining transcriptomics and radiomics data. These findings contribute to our understanding of LUAD biology and offer potential avenues for further exploration in clinical practice. [ABSTRACT FROM AUTHOR]