Search Results (2,322)

The aim of this study was to investigate the effects of the crop load on the berry and wine composition of Marselan grapes. Thus, the appropriate crop load for Marselan wine grapes in Ningxia was determined based on the shoot density and the number of clusters per shoot. Marselan grapes from the Gezi Mountain vineyard, located at the eastern foot of Helan Mountain in the Qingtongxia region of Ningxia, were selected as the research material to conduct a combination experiment with four levels of shoot density and three levels of cluster density. The analysis of the berry and wine chemical composition was combined with a wine sensory evaluation to determine the optimal crop load levels. Crop load regulation significantly affected both the grape berry composition and the basic physicochemical properties of the resulting wine. Low crop loads improved metrics such as the berry weight and soluble solids content. A low shoot density facilitated the accumulation of organic acids, flavonols, and hydroxybenzoic acids in wine. Moderate crop loads were conducive to anthocyanin synthesis—the total individual anthocyanins content in the 10–20 shoots per meter of the canopy treatment group ranged from 116% to 490% of the control group—whereas excessive crop loads hindered its accumulation. Crop load management significantly influenced the aroma composition of wine by regulating the content of sugars, nitrogen sources, and organic acids in grape berries, thereby promoting the synthesis of esters and the accumulation of key aromatic compounds, such as terpenes. This process optimized pleasant flavors, including fruity and floral aromas. In contrast, wines from the high crop load and control treatments contained lower levels of these aroma compounds. Compounds such as ethyl caprylate and β-damascenone were identified as potential quality markers. Overall, the wine produced from vines with a crop load of 30 clusters (15 shoots per meter of canopy, 2 clusters per shoot) received the highest sensory scores. Appropriate crop load management is therefore critical to improving the chemical composition of Marselan wine. Full article

Madagascar harbors a rich marine biodiversity, yet detailed knowledge of its fish species remains limited. Of the 1689 species listed in 2018, only 22% had accessible cytochrome oxidase I (COI) sequences in public databases. In response to growing pressure on fishery resources, this study aims to strengthen biodiversity monitoring tools. Its objectives were to enrich the COI database for Malagasy marine fishes, create the first 12S reference library, and evaluate the taxonomic resolution of different 12S metabarcodes for eDNA analysis, namely MiFish, Teleo1, AcMDB, Ac12S, and 12SF1/R1. An integrated approach combining morphological, molecular, and phylogenetic analyses was applied for specimen identification of fish captured using various types of fishing gear in Toliara and Ranobe Bays from 2018 to 2023. The Malagasy COI database now includes 2146 sequences grouped into 502 Barcode Index Numbers (BINs) from 82 families, with 14 BINs newly added to BOLD (The Barcode of Life Data Systems), and 133 cryptic species. The 12S library comprises 524 sequences representing 446 species from 78 families. Together, the genetic datasets cover 514 species from 84 families, with the most diverse being Labridae, Apogonidae, Gobiidae, Pomacentridae, and Carangidae. However, the two markers show variable taxonomic resolution: 67 species belonging to 35 families were represented solely in the COI dataset, while 10 species from nine families were identified exclusively in the 12S dataset. For 319 species with complete 12S gene sequences associated with COI BINs (Barcode Index Numbers), 12S primer sets were used to evaluate the taxonomic resolution of five 12S metabarcodes. The MiFish marker proved to be the most effective, with an optimal similarity threshold of 98.5%. This study represents a major step forward in documenting and monitoring Madagascar’s marine biodiversity and provides a valuable genetic reference for future environmental DNA (eDNA) applications. Full article

Background: Heart failure (HF) is frequently associated with skeletal muscle wasting, reduced functional capacity, and malnutrition. High-protein diets offer a promising nutritional intervention to improve these outcomes in individuals with HF. Objective: This systematic review evaluated randomized controlled trials of high-protein dietary interventions in HF populations, with emphasis on intervention characteristics, quantitative benefits, and risk of bias. Methods: We conducted a comprehensive search in PubMed, MEDLINE, Embase, and Cochrane CENTRAL from inception to June 2025. Eligible studies enrolled adults (≥18 years) with HF, implemented high-protein regimens (≥1.1 g/kg/day or ~25–30% of energy), and reported on functional capacity, body composition, muscle strength, clinical outcomes, or biochemical markers. Two reviewers independently screened, extracted data, and assessed bias (Cochrane RoB 2). Heterogeneity in dosing, duration, and outcomes precluded meta-analysis; we therefore provide a narrative synthesis. Results: Ten trials (nine randomized controlled trials, one pilot) involving 1080 patients (median n = 38; range 21–652) were included. High-protein interventions yielded mean improvements in six-minute walk distance of +32 ± 14 m, lean body mass gain of +1.6 ± 0.9 kg, and 9 ± 4% enhancement in quality-of-life scores; muscle strength effects varied from −2% to +11%. Two studies reported an 18% reduction in HF readmissions (p < 0.05). The risk-of-bias assessment identified two low-risk, three moderate-risk, and one high-risk study. Key limitations include small sample sizes, varied protein dosing (1.1–1.5 g/kg/day), short follow-up (2–6 months), and outcome heterogeneity. Conclusions: High-protein dietary strategies appear to confer modest, clinically relevant gains in functional capacity, nutritional status, and HF readmission risk. Larger, well-powered trials with standardized dosing and longer follow-up are necessary to establish optimal protein targets, long-term efficacy, and safety. Full article

Hotpot dishes are widely favored by consumers for their flavor profiles developed during the cooking process. This study investigated the quality characteristics and volatile compounds (VOCs) of donkey meat slices across varying boiling durations (0–42 s) using gas chromatography–ion mobility spectrometry (GC-IMS). The results demonstrated that donkey meat boiled for 12–18 s exhibited optimal characteristics in terms of meat retention, color parameters, shear force values, and pH measurements. Forty-eight distinct VOCs were identified in the samples, with aldehydes, alcohols, ketones, acids, furans, and esters representing the predominant categories. Among these compounds, 18 were identified as characteristic aroma compounds, including 3-hexanone, 2, 3-butanedione, and oct-1-en-3-ol. Samples subjected to different boiling durations were successfully differentiated through topographic plots, fingerprint mapping, and multivariate analysis. The abundance and diversity of VOCs reached peak values in samples boiled for 12–18 s. Furthermore, 28 VOCs were identified as potential markers for distinguishing between different boiling durations, including 2-butoxyethanol D, benzaldehyde D, and (E)-2-pentenal D. This study concludes that a boiling duration of 12–18 s for donkey meat during hotpot preparation yields optimal quality characteristics and volatile flavor compound profiles and provides valuable insights for standardizing cooking parameters in hotpot preparations of other meat products. It is necessary to confirm this finding with sensory evaluations in further research. Full article

The design of materials with programmable degradation profiles presents a fundamental challenge in pattern recognition across molecular space, requiring the identification of complex structure–property relationships within an exponentially large chemical domain. This paper introduces a novel physics-informed deep learning framework that integrates multi-scale molecular sensing data with reinforcement learning algorithms to enable intelligent characterization and prediction of polymer degradation dynamics. Our method combines three key innovations: (1) a dual-channel sensing architecture that fuses spectroscopic signatures from Graph Isomorphism Networks with temporal degradation patterns captured by transformer-based models, enabling comprehensive molecular state detection across multiple scales; (2) a physics-constrained policy network that ensures sensor measurements adhere to thermodynamic principles while optimizing the exploration of degradation pathways; and (3) a hierarchical signal processing system that balances multiple sensing modalities through adaptive weighting schemes learned from experimental feedback. The framework employs curriculum-based training that progressively increases molecular complexity, enabling robust detection of degradation markers linking polymer architectures to enzymatic breakdown kinetics. Experimental validation through automated synthesis and in situ characterization of 847 novel polymers demonstrates the framework’s sensing capabilities, achieving a 73.2% synthesis success rate and identifying 42 structures with precisely monitored degradation profiles spanning 6 to 24 months. Learned molecular patterns reveal previously undetected correlations between specific spectroscopic signatures and degradation susceptibility, validated through accelerated aging studies with continuous sensor monitoring. Our results establish that physics-informed constraints significantly improve both the validity (94.7%) and diversity (0.82 Tanimoto distance) of generated molecular structures compared with unconstrained baselines. This work advances the convergence of intelligent sensing technologies and materials science, demonstrating how physics-informed machine learning can enhance real-time monitoring capabilities for next-generation sustainable materials. Full article

An investigation into the biological mechanisms initiated in wounded skin following the application of mesenchymal stem cells (MSCs) and nanoparticles (NPs) (Ag, ZnO), either alone or combined, was performed in mice, with the aim of determining the optimal approach to accelerate the healing process. This combined treatment was hypothesized to be beneficial, as it is associated with the production of molecules supporting the healing process and antimicrobial activity. The samples were collected seven days after injury. When compared with untreated wounded animals (controls), the combined (MSCs+NPs) treatment induced the expression of Sprr2b, encoding small proline-rich protein 2B, which is involved in keratinocyte differentiation, the response to tissue injury, and inflammation. Pathways associated with keratinocyte differentiation were also affected. Ag NP treatment (alone or combined) modulated DNA methylation changes in genes involved in desmosome organization. The percentage of activated regulatory macrophages at the wound site was increased by MSC-alone and Ag-alone treatments, while the production of nitric oxide, an inflammatory marker, by stimulated macrophages was decreased by both MSC/Ag-alone and MSCs+Ag treatments. Ag induced the expression of Col1, encoding collagen-1, at the injury site. The results of the MSC and NP treatment of skin wounds (alone or combined) suggest an induction of processes accelerating the proliferative phase of healing. Thus, MSC-NP interactions are a key factor affecting global mRNA expression changes in the wound. Full article

Colorectal cancer (CRC) is characterized by complex interactions between inflammation, oxidative stress, and extracellular matrix remodeling. Recent studies have highlighted the significance of the reactive oxygen species (ROS)–nuclear factor kappa B (NF-κB)–matrix metalloproteinase-9 (MMP-9) axis in promoting tumor invasion and metastasis in CRC, linking oxidative stress with inflammatory signaling and extracellular matrix degradation. In this study, we analyzed the concentration of advanced oxidation protein products (AOPPs), expression of NF-κB, and the activity of MMP-9 in tumor tissue, adjacent tissue, and healthy control colon tissue. Tissue specimens were collected from 50 patients with primary CRC following surgical resection. The analyses were performed using appropriate and validated biochemical methods, including ELISA, spectrophotometry, and indirect immunofluorescence. Significantly higher levels of all three markers were observed in tumor tissue compared to controls. Additionally, adjacent tissue exhibited elevated NF-κB expression and MMP-9 activity when compared to healthy colon tissue. AOPP levels correlated strongly with MMP-9 activity, highlighting the role of oxidative stress in the activation of MMP-9. MMP-9 demonstrated the highest predictive value for CRC, emphasizing its potential as a diagnostic and theranostic marker. Our findings support the hypothesis that the ROS–NF-κB–MMP-9 axis plays an important role in CRC progression, particularly during stages T2 and T3. Targeting this pathway may offer new therapeutic strategies for limiting tumor invasion and recurrence. Moreover, ensuring adequate surgical resection margins is crucial to optimizing treatment outcomes. Full article

Tumor-associated macrophages (TAMs) are pivotal immune cells within the tumor stroma, whose dynamic alterations significantly impact tumor progression and therapeutic responses. Conventional methods for TAM detection, such as biopsy, are invasive and incapable of whole-body dynamic monitoring. In contrast, positron emission tomography (PET) and single-photon emission computed tomography (SPECT) offer a non-invasive imaging approach by targeting TAM-specific biomarkers like CD206, TSPO, and CCR2. This review comprehensively summarizes the advancements in TAM-targeted imaging probes, including cell surface markers, metabolic/functional markers, and multifunctional nanoprobe, while assessing their potential in tumor immune surveillance and tumor targeting therapeutic applications. While current probes, including ⁶⁸Ga-NOTA-anti-CD206 and ⁶⁴Cu-Macrin, have exhibited high specificity and theragnostic potential in preclinical and early clinical trials, challenges such as target heterogeneity, off-target effects, and clinical translation persist. Moving forward, the advancement of multi-target probes, optimization of pharmacokinetics, and incorporation of multimodal imaging technologies are anticipated to further enhance the impact of TAM-targeted imaging in precision medicine and tumor immunotherapy, fostering the refinement of personalized treatment strategies and improving patient outcomes. Full article

Background/Objectives: Carnitine deficiency is common in hemodialysis patients and may contribute to anemia, inflammation, dyslipidemia, and muscle symptoms. This review explores the potential benefits of L-carnitine supplementation in this population. Methods: A thorough literature search of the PubMed database was conducted to identify clinical trials and studies assessing the effects of L-carnitine supplementation on adult hemodialysis patients. Key outcomes included the effects on inflammation, lipid profile, anemia, glycemic control, and muscle function. Results: Evidence suggests that L-carnitine may reduce inflammatory markers and improve lipid profiles by lowering triglycerides and increasing high-density lipoprotein (HDL). Several studies reported reduced erythropoietin need and improved hemoglobin levels. However, some studies did not find benefits of carnitine supplementation on the mentioned parameters. Results for muscle cramps, glycemic control, and cardiac function remain inconsistent. Conclusions: L-carnitine supplementation shows potential benefits in the management of hemodialysis complications. However, further well-designed trials are needed to confirm efficacy and optimize treatment protocols. Full article

Conventional methods for isolating extracellular vesicles (EVs) are often limited by long processing times, a low purity, and a reliance on specialized equipment. To overcome these challenges, we developed the DeSEI (amine-functionalized Diatomaceous earth-based Syringe platform for EV Isolation), a novel platform employing low-cost, amine-functionalized diatomaceous earth (ADe) within a simple syringe–filter system. The capture mechanism leverages the electrostatic interaction between the positively charged ADe and the negatively charged EV surface, enabling a rapid and efficient isolation. The optimized 30 min protocol yields intact EVs with morphology, size, and protein markers comparable to those from ultracentrifugation, ensuring minimal cellular contamination. Notably, DeSEI exhibited a nearly 60-fold higher recovery efficiency of EV-derived miRNA compared to ultracentrifugation. The platform further proved its versatility with a rapid one-step miRNA extraction protocol and a user-friendly cartridge format. The direct miRNA extraction capability is particularly advantageous for a streamlined biomarker analysis, while the cartridge design illustrates a clear pathway toward developing point-of-care diagnostic tools. The DeSEI offers a promising alternative to existing methods for EV-based research by providing a combination of speed, simplicity, and procedural flexibility that does not require specialized equipment. Full article

Objectives: Our objective was to investigate the clinical characteristics, complications, and treatment outcomes of Epstein–Barr virus (EBV)-related infectious mononucleosis (IM) in children and to identify risk factors associated with prolonged fever and abnormal liver function. Methods: This retrospective study included 3006 children admitted to Shenzhen Children’s Hospital from May 2009 to April 2024 with suspected EBV-related IM. After excluding cases without etiological evidence and those with underlying diseases, 2660 cases were analyzed. Data on demographics, clinical manifestations, laboratory findings, complications, and treatment outcomes were collected. Logistic regression was used to identify risk factors for prolonged fever and abnormal liver function. Results: Among the 2660 confirmed cases, patients ranged from 8 months to 17 years of age, with a median age of 4 years and a male-to-female ratio of 1.46:1. Co-infections were identified in 369 (13.9%) patients, predominantly with Group A Streptococcus. Complications occurred in 560 (24.46%) of the 2289 patients without co-infections, with bronchitis being the most common (42.68%). Elevated ferritin and atypical lymphocyte percentage were associated with prolonged fever (p < 0.001), while elevated lactate dehydrogenase (LDH) and a lower CD4% predicted abnormal liver function (p < 0.001). Antiviral therapy did not shorten fever duration or hospital stay but prolonged both when combined with corticosteroids or intravenous immunoglobulin (IVIG) (p < 0.001). Conclusions: Specific laboratory markers such as ferritin, atypical lymphocyte percentage, LDH, and CD4% are important predictors of prolonged fever or liver dysfunction in EBV-IM. Our findings suggest that antiviral therapy may not be beneficial in uncomplicated cases and highlight the need for tailored treatment strategies to optimize patient outcomes. Full article

The prognosis of sarcopenia is poor in cancer patients. Recently, urinary titin, a biomarker of muscle damage, has been suggested as a potential marker for sarcopenia. However, its utility in patients with unresectable digestive malignancies remains unclear. In addition, sex differences have been reported in the association between sarcopenia and urinary titin levels. This study aimed to evaluate urinary titin as a diagnostic marker for unresectable digestive malignancies, focusing on sex differences. This retrospective study enrolled 96 patients (58 males, 38 females; median age 70), and urinary titin was evaluated as a diagnostic biomarker in relation to clinical factors (e.g., age, Eastern Cooperative Oncology Group performance status [ECOG PS], albumin [Alb]) and muscle indicators (e.g., psoas muscle index [PMI], handgrip strength). In male patients, urinary titin levels were significantly higher in the sarcopenia subgroup (5.78 vs. 2.79 pmol/mgCr, p = 0.008), and multivariate analyses identified urinary titin as an independent predictor of sarcopenia (odds ratio 13.4, p = 0.028). The receiver operating characteristic (ROC) analysis demonstrated fair diagnostic performance (area under the curve [AUC] 0.729), with an optimal cutoff value of 3.676 pmol/mgCr. Urinary titin may serve as a useful non-invasive diagnostic biomarker for sarcopenia in patients with unresectable digestive malignancies, particularly in males. These findings suggest that sex-specific approaches are required for sarcopenia assessment with urinary titin. Full article

Recent studies have demonstrated the high analytical and diagnostic performance of plasma p-tau217 using well-defined cohorts. We aimed to assess the analytical, diagnostic, and prognostic utility of plasma p-tau217 as a routine biomarker in symptomatic patients attending our memory clinic. We also sought to identify optimal cutoff points that align with cerebrospinal fluid (CSF) amyloid beta (Aβ) status. A total of 276 cognitively impaired patients were included, with 81 mild cognitive impairment (MCI) patients followed for a mean of 56 (±15.8) months to evaluate progression to Alzheimer’s disease (AD). CSF and blood biomarkers of AD were quantified using the Lumipulse G platform. Plasma p-tau217 levels showed strong correlations with CSF Aβ42/Aβ40 (r = −0.707), p-tau181/Aβ42 (r = 0.842), and p-tau181 (r = 0.728). Plasma p-tau217 levels were significantly higher in the A + T + group than in A − T +/− (p < 0.001) and outperformed other plasma markers in detecting CSF Aβ pathology (AUC 0.924).Additionally, p-tau217 moderated cognitive changes over time as measured by the Mini-mental state examination (MMSE) (F(2, 70) = 13.995, p < 0.001) and outperformed other plasma biomarkers in predicting progression from MCI to AD (AUC 0.876). Using a dual cutoff strategy, 72% of patients were classified with 94.9% concordance with CSF Aβ status. Plasma p-tau217 shows strong potential as a non-invasive, cost-effective diagnostic and prognostic tool in clinical settings. Full article

In this study, we evaluated the nitrous oxide production potential of denitrifying bacterial strains isolated from sediments of the urban wetland Santa María del Lago under anaerobic and aerobic conditions to determine their potential role in mitigating anthropogenic N₂O emissions, which have increased by approximately 40% since 1980, and if these emissions could be related to the absence of the nitrous oxide reductase gene (nosZ). The results demonstrated that denitrifying bacteria belonging to the genus Bacillus were able to generate nitrous oxide in high concentrations under both aerobic (up to 83 nM/h) and anaerobic (up to 3865.5 nM/h) conditions in cultures with optimal concentrations of nitrate and carbon. The amplification of the nosZ gene as marker of denitrifying microorganisms showed that only 50% of strains possess this gene, and its presence did not correlate with nitrous oxide reduction under anoxic conditions. Interestingly, one strain was able to reduce nitrous oxide in the presence of air, which is promising for its potential use in aerobic bioremediation systems that require microorganisms with a high affinity for this greenhouse gas to reduce emissions into the atmosphere. Full article

The discovery of effective therapeutics against Alzheimer’s disease (AD) and other neurological disorders remains a significant challenge. Artificial intelligence (AI) tools are of considerable interest in modern drug discovery processes and, by exploiting machine learning (ML) algorithms and deep learning (DL) tools, as well as data analytics, can expedite the identification of new drug targets and potential lead molecules. The current study was aimed at assessing the role of AI-based tools in the discovery of new drug targets against AD and other related neurodegenerative diseases and their efficacy in the discovery of new drugs against these diseases. AD represents a multifactorial neurological disease with limited therapeutics available for management and limited efficacy. The discovery of more effective medications is limited by the complicated pathophysiology of the disease, involving amyloid beta (Aβ), neurofibrillary tangles (NFTs), oxidative stress, and inflammation-induced damage in the brain. The integration of AI tools into the traditional drug discovery process against AD can help to find more effective, safe, highly potent compounds, identify new targets of the disease, and help in the optimization of lead molecules. A detailed literature review was performed to gather evidence regarding the most recent AI tools for drug discovery against AD, Parkinson’s disease (PD), multiple sclerosis (MLS), and epilepsy, focusing on biological markers, early diagnoses, and drug discovery using various databases like PubMed, Web of Science, Google Scholar, Scopus, and ScienceDirect to collect relevant literature. We evaluated the role of AI in analyzing multifaceted biological data and the properties of potential drug candidates and in streamlining the design of clinical trials. By exploring the intersection of AI and neuroscience, this review focused on providing insights into the future of AD treatment and the potential of AI to revolutionize the field of drug discovery. Our findings conclude that AI-based tools are not only cost-effective, but the success rate is extremely high compared to traditional drug discovery methods in identifying new therapeutic targets and in the screening of the majority of molecules for clinical trial purposes. Full article