Life-Basel最新文献

Retinal ischemia-reperfusion (I/R) injury is a critical pathogenic mechanism in various eye diseases, and an effective therapeutic strategy remains unresolved. Natural derivatives have recently reemerged; therefore, in our present study, we examined the potential therapeutic effects of a stilbenoid that is chemically related to resveratrol. Pterostilbene, recognized for its anti-inflammatory, anti-carcinogenic, anti-diabetic, and neuroprotective properties, counteracts oxidative stress during I/R injury through various mechanisms. This study explored pterostilbene as a retinoprotective agent. Male Sprague Dawley rats underwent retinal I/R injury and one-week reperfusion and were treated with either vehicle or pterostilbene. After this functional electroretinographical (ERG) measurement, Western blot and histological analyses were performed. Pterostilbene treatment significantly improved retinal function, as evidenced by increased b-wave amplitude on ERG. Histological studies showed reduced retinal thinning and preserved the retinal structure in the pterostilbene-treated groups. Moreover, Western blot analysis revealed a decreased expression of glial fibrillary acidic protein (GFAP) and heat shock protein 70 (HSP70), indicating reduced glial activation and cellular stress. Additionally, the expression of pro-apoptotic and inflammatory markers, poly(ADP-ribose) polymerase 1 (PARP1) and nuclear factor kappa B (NFκB) was significantly reduced in the pterostilbene-treated group. These findings suggest that pterostilbene offers protective effects on the retina by diminishing oxidative stress, inflammation, and apoptosis, thus preserving retinal function and structure following I/R injury. This study underscores pterostilbene's potential as a neuroprotective therapeutic agent for treating retinal ischemic injury and related disorders.

Salt-alkaline stress is one of the most stressful occurrences, causing negative effects on plant development and agricultural yield. Identifying and utilizing genes that affect alkaline tolerance is an excellent approach to accelerate breeding processes and meet the needs for remediating saline-alkaline soil. Here, we employed a mapping population of 176 recombinant inbred lines (RILs) produced from a cross between alkali-tolerant Longdao5 and alkali-sensitive Zhongyouzao8 to identify the quantitative trait loci (QTLs) determining alkali tolerance at the seedling stage. For the evaluation of alkali tolerance, the recovered seedling's average alkali tolerance index (ATI), root number (RN), root length (RL), seedling dry weight (SW), root dry weight (RW), and seedling height (SH) were assessed, together with their relative alkaline damage rate. Under alkaline stress, the ATI was substantially negative connected with the root number, seedling height, seedling dry weight, and root dry weight; however, it was considerably positive correlated with the relative alkaline damage rate of the root number and root dry weight. A total of 13 QTLs for the root number, root length, seedling height, seedling dry weight, root dry weight, and alkali tolerance index under alkaline stress were identified, which were distributed across chromosomes 1, 2, 3, 4, 5, 7, and 8. All of these QTLs formed two QTL clusters for alkali tolerance on chromosome 5 and chromosome 7, designated AT5 and AT7, respectively. Nine QTLs were identified for the relative alkaline damage rate of the root number, root length, seedling height, seedling dry weight, and root dry weight under alkali stress. These QTLs were located on chromosome 2, 4, 6, 7, 8, 9, and 12. In conclusion, these findings further strengthen our knowledge about rice's genetic mechanisms for alkaline tolerance. This research offers clues to accelerate breeding programs for new alkaline-tolerance rice varieties.

Treating cartilage damage is challenging as its ability for self-regeneration is limited. Left untreated, it can progress to osteoarthritis (OA), a joint disorder characterized by the deterioration of articular cartilage and other joint tissues. Surgical options, such as microfracture and cell/tissue transplantation, have shown promise as techniques to harness the body's endogenous regenerative capabilities to promote cartilage repair. Nonetheless, these techniques have been scrutinized due to reported inconsistencies in long-term outcomes and the tendency for the defects to regenerate as fibrocartilage instead of the smooth hyaline cartilage native to joint surfaces. Orthobiologics are medical therapies that utilize biologically derived substances to augment musculoskeletal healing. These treatments are rising in popularity because of their potential to enhance surgical standards of care. More recent developments in orthobiologics have focused on the role of exosomes in articular cartilage repair. Exosomes are nano-sized extracellular vesicles containing cargo such as proteins, lipids, and nucleic acids, and are known to facilitate intercellular communication, though their regenerative potential still needs to be fully understood. This review aims to demonstrate the advancements in cartilage regeneration, highlight surgical and biological treatment options, and discuss the recent strides in understanding the precise mechanisms of action involved.

From the late Carboniferous to the early Permian, multiple pulses of glaciation and deglaciation have been caused by the LPIA. The Pennsylvanian period experienced phases of recovery, proliferation, and decline, ultimately forming a reef system distinctly different from that of the Mississippian period. During the late Bashkirian to Moscovian, the metazoan reef experienced a limited resurgence, with reef predominantly formed by chaetetid developing in the United States, northern China, and Japan. During the Kasimovian to Gzhelian, the phylloid algal reef dominated the global reef systems. In the late Pennsylvanian, bioconstruction cases and paleoenvironmental proxies in southern Guizhou Province were studied to investigate the composition, recovery, and evolutionary processes of the bioconstructions as well as their response to environmental variations during this period. Several bioconstructions have been reported in the Lumazhai section of Houchang Town, Guizhou Province, southern China, from the Moscovian to the Gzhelian. The upper Carboniferous strata are well-preserved and continuously exposed. The continuous strata, abundant fossils, and diverse bioconstructions provide excellent research materials for exploring the mutual constraints between organisms and their environment. This study identified ten microfacies, whose vertical evolution indicated significant changes in the depositional environment related to relative sea-level fluctuations. Skeletal grains are widely present in these facies. Among them, foraminifera, algae, bryozoans, crinoids, and Tubiphytes are the most common and exhibit distinct distribution characteristics in various environments. Quantitative statistics, CCA and theoretical ecospace have been utilized to examine and interpret environmental impact factors. Quantitative analysis of their relative abundance and distribution patterns provides insights into the complex interactions between organisms and environmental factors. The relative abundances of different organisms and factors controlling their bioconstructions are influenced by relative sea-level changes. CCA analysis reveal that hydrodynamic conditions are the primary influencing factor. Variation trends in average tiering and motility reveal the characteristics of biological communities during environmental changes in phylloid algae and microbial bioconstructions. These bioconstructions are not directly correlated with changes in environmental factors, and the biological communities in phylloid algae mounds and biostromes exhibit similar organism compositions and ecological niches across different environments.

Introduction: A hiatal hernia (HH) can be defined as a condition in which elements from the abdominal cavity herniate through the oesophageal hiatus in the mediastinum and, in the majority of cases, parts of the proximal stomach. Today, the role of HHs within the complex entity of gastroesophageal reflux disease (GERD) is very important with regard to its pathophysiology, severity, and therapeutic and prognostic options. Despite this, the application and stringent use of the worldwide accepted classification (Skinner and Belsey: Types I-IV) are lacking. The aim of this study was to carry out a systematic review of the clinical applications of HH classifications and scientific documentation over time, considering their value in diagnosis and treatment.

Methods: Following the PRISMA concept, all abstracts published on pubmed.gov until 12/2023 (hiatal hernia) were reviewed, and those with a focus and clear description of the application of the current HH classification in the full-text version were analysed to determine the level of classification and its use within the therapeutic context.

Results: In total, 9342 abstracts were screened. In 9199 of the abstracts, the reports had a different focus than HH, or the HH classification was not used or was incompletely applied. After further investigation, 60 papers were used for a detailed analysis, which included more than 12,000 patient datapoints. Among the 8904 patients, 83% had a Type I HH; 4% had Type II; 11% had Type III; and 1% had Type IV. Further subgroup analyses were performed. Overall, the precise application of the HH classification has been insufficient, considering that only 1% of all papers and only 54% of those with a special focus on HH have documented its use.

Conclusions: The application and documentation of a precise HH classification in clinical practice and scientific reports are decreasing, which should be rectified for the purpose of scientific comparability.

The species Lactococcus lactis is a bacterium extensively used in the dairy industry. This bacterium is Generally Recognized as Safe and was added to the European Food Safety Authority's Qualified Presumption of Safety list. The major functions of this species in dairy fermentation are the production of lactic acid from lactose, citric acid fermentation, and the hydrolysis of casein. But, the representatives of this species that produce bacteriocin substances can also exert an inhibitory effect against spoilage bacteria. The aims of this study were to test three lactococcal strains isolated from raw goat milk for their postbiotic activity and to test their stability in goat milk yogurts after their application in encapsulated form for their further application. To achieve these aims, validated methods were used. Three Lactococcus lactis strains (identified by Blastn 16S rRNA analysis) produced bacteriocin substances/postbiotics. These concentrated postbiotics inhibited the growth of enterococci and staphylococci (by up to 97.8%), reaching an inhibitory activity of up to 800 AU/mL. The encapsulated (freeze-dried) lactococci survived in the goat milk yogurts with sufficient stability. Strain MK2/8 fortified the yogurts in the highest amount (8.1 ± 0.0 cfu/g log 10). It did not influence the pH of the yogurt.

Long non-coding RNAs (lncRNAs) are involved in numerous biological processes and serve crucial regulatory functions in both animals and plants. Nevertheless, there is limited understanding of lncRNAs and their patterns of expression and roles in sharks. In the current study, we systematically identified and characterized lncRNAs in the blue shark (Prionace glauca) from four tissues (liver, spleen, muscle, and kidney) using high-throughput sequencing and bioinformatics tools. A total of 21,932 high-confidence lncRNAs were identified, with 8984 and 3067 stably and tissue-specific expressed lncRNAs, respectively. In addition, a total of 45,007 differentially expressed (DE) lncRNAs were obtained among tissues, with kidney versus muscle having the largest numbers across tissues. DE lncRNAs trans target protein-coding genes were predicted, and functional gene ontology enrichment of these genes showed GO terms such as muscle system processes, cellular/metabolic processes, and stress and immune responses, all of which correspond with the specific biological functions of each tissue analyzed. These results advance our knowledge of lncRNAs in sharks and present novel data on tissue-specific lncRNAs, providing key information to support future functional shark investigations.

Long-term frequent use of acute pain medication for the treatment of headaches has paradoxically been shown to increase the frequency of headaches. So-called medication-overuse headache (MOH) is particularly problematic in patients with migraine who overuse triptans and opioids. Prevention through education remains the most important management strategy. Once established, MOH can be difficult to treat. Although complete or near-complete withdrawal of acute pain medication for 8-12 weeks has been shown to benefit most patients, this can be hard to achieve. The use of OnabotulinumtoxinA and drugs that target the calcitonin gene-related peptide system for the prevention of migraines have been shown to benefit patients with MOH. Furthermore, the use of novel acute pain medication for migraines, including Gepants and Ditans, which do not cause MOH, are likely to improve patient outcomes. In this review article we examine the following: the burden of MOH; who develops MOH; the pathophysiological mechanisms; and the treatment strategies.

The aim of this study was to investigate the influence of executive functioning and cognitive performance on individual experimentally induced pain perception during distractor tasks in an asymptomatic pain-free population. A total of 59 healthy pain-free subjects (59.3% women, mean age: 46.5 ± 24.7 years) completed a battery test that assessed execution functions (cognitive flexibility, working memory, mental inhibition), attention level, and psychological aspects (anxiety/depressive levels-HADS, pain catastrophizing-PCS, pain anxiety symptoms-PASS 20, sleep quality-PSQI) before conducting two n-back distraction tasks. Pain was experimentally induced with a thermal stimulus that was able to induce moderate pain (70/100 points) and applied to the non-dominant forearm. The thermal stimulus was applied before and during both (one-back and two-back) distraction tasks. The analyses consisted of separated repeated-measures ANOVA that considered the functioning on each test (cognitive flexibility, working memory, mental inhibition, selective attention) and controlled for sociodemographic and psychological aspects by comparing the pain intensity at the baseline and during the one-back and two-back distractor tasks. All ANOVAs found a significant effect of the distraction task, which indicates that the perceived pain intensity scores were lower during the one-back and two-back tasks (p < 0.001) as compared with the baseline. No interaction effect between the distractor tasks and working memory (p = 0.546), mental inhibition (p = 0.16), cognitive flexibility (p = 0.069), or selective attention (p = 0.105) was identified. The current study found that a distraction task decreased the perceived intensity of experimentally induced pain in asymptomatic pain-free individuals and that this effect was not related to executive function or attention levels.

In this paper, I present a comprehensive pipeline integrating a Fine-Tuned Convolutional Neural Network (FT-CNN) and a Residual-UNet (RUNet) architecture for the automated analysis of MRI brain scans. The proposed system addresses the dual challenges of brain tumor classification and segmentation, which are crucial tasks in medical image analysis for precise diagnosis and treatment planning. Initially, the pipeline preprocesses the FigShare brain MRI image dataset, comprising 3064 images, by normalizing and resizing them to achieve uniformity and compatibility with the model. The FT-CNN model then classifies the preprocessed images into distinct tumor types: glioma, meningioma, and pituitary tumor. Following classification, the RUNet model performs pixel-level segmentation to delineate tumor regions within the MRI scans. The FT-CNN leverages the VGG19 architecture, pre-trained on large datasets and fine-tuned for specific tumor classification tasks. Features extracted from MRI images are used to train the FT-CNN, demonstrating robust performance in discriminating between tumor types. Subsequently, the RUNet model, inspired by the U-Net design and enhanced with residual blocks, effectively segments tumors by combining high-resolution spatial information from the encoding path with context-rich features from the bottleneck. My experimental results indicate that the integrated pipeline achieves high accuracy in both classification (96%) and segmentation tasks (98%), showcasing its potential for clinical applications in brain tumor diagnosis. For the classification task, the metrics involved are loss, accuracy, confusion matrix, and classification report, while for the segmentation task, the metrics used are loss, accuracy, Dice coefficient, intersection over union, and Jaccard distance. To further validate the generalizability and robustness of the integrated pipeline, I evaluated the model on two additional datasets. The first dataset consists of 7023 images for classification tasks, expanding to a four-class dataset. The second dataset contains approximately 3929 images for both classification and segmentation tasks, including a binary classification scenario. The model demonstrated robust performance, achieving 95% accuracy on the four-class task and high accuracy (96%) in the binary classification and segmentation tasks, with a Dice coefficient of 95%.