Search Results (65)

Docosahexaenoic acid (DHA), the dominant polyunsaturated fatty acid in photoreceptors, neurons, and synapses, is usually described as a passive structural membrane constituent. We propose a different view: DHA is a quantum-electronically active molecule whose conjugated double-bond system creates an electron-rich matrix that couples with proteins to form quantum “clouds” and high-speed signaling central to recognition, recall, and cognition. Integrating evidence from molecular evolution, biophysics, and neuroscience, we argue that, as the original chromophore, DHA’s unique properties enabled the emergence of the nervous system and continue to provide the electronic substrate for cognition. By suggesting that cognition depends not only on protein-based mechanisms but on DHA-mediated electron dynamics at the membrane–protein interface, this perspective reframes DHA as an active, conserved determinant of brain evolution and function. Full article

Integrating artificial intelligence (AI) with the Quantitative Structure-Activity Relationship (QSAR) has transformed modern drug discovery by empowering faster, more accurate, and scalable identification of therapeutic compounds. This review outlines the evolution from classical QSAR methods, such as multiple linear regression and partial least squares, to advanced machine learning and deep learning approaches, including graph neural networks and SMILES-based transformers. Molecular docking and molecular dynamics simulations are presented as cooperative tools that boost the mechanistic consideration and structural insight into the ligand-target interactions. Discussions on using PROTACs and targeted protein degradation, ADMET prediction, and public databases and cloud-based platforms to democratize access to computational modeling are well presented with priority. Challenges related to authentication, interpretability, regulatory standards, and ethical concerns are examined, along with emerging patterns in AI-driven drug development. This review is a guideline for using computational models and databases in explainable, data-rich and profound drug discovery pipelines. Full article

Citrus peel, a significant by-product of fruit processing, represents a rich source of carotenoids with strong antioxidant and health-promoting properties. The present study evaluated two green extraction techniques, cloud point extraction (CPE) and supramolecular solvent (SUPRAS)-based extraction, for carotenoids recovered from citron, orange, and tangerine peels. Whereas SUPRAS methods rely on a supramolecular solvent made of water, ethanol, and octanoic acid, CPE methods use surfactants and water, and both show a high potential to extract lipophilic components. CPE demonstrated superior efficiency in extracting total carotenoids and enhancing antioxidant activity, with orange peel extracts showing the highest concentrations. CPE and SUPRAS extracts were subsequently encapsulated using freeze-drying with chickpea protein isolate, achieving high encapsulation efficiencies (82.40–88.97%). The use of encapsulation technology is an effective strategy to protect carotenoids from environmental stressors. Color, morphological, and FTIR analyses confirmed the successful encapsulation and retention of carotenoids. Environmental impact was assessed using the EcoScale tool, revealing excellent sustainability for CPE (92 points) and satisfactory performance for SUPRAS-based extraction (70 points). The use of Generally Recognized As Safe (GRAS) solvents and plant-derived encapsulation materials makes this method highly suitable for clean-label product development across the food, cosmetic, and nutraceutical industries. In summary, the results point to a practical and sustainable approach to citrus waste valorization into valuable, health-promoting ingredients—supporting both circular economy goals and eco-friendly innovation. Full article

The research introduces a revolutionary Internet of Things (IoT)-based system for fish farming, designed to significantly enhance efficiency and cost-effectiveness. By integrating the NodeMcu12E ESP8266 microcontroller, this system automates the management of critical water quality parameters such as pH, temperature, and oxygen levels, essential for fostering optimal fish growth conditions and minimizing mortality rates. The core of this innovation lies in its intelligent monitoring and control mechanism, which not only supports accelerated fish development but also ensures the robustness of the farming process through automated adjustments whenever the monitored parameters deviate from desired thresholds. This smart fish farming solution features an Arduino IoT cloud-based framework, offering a user-friendly web interface that enables fish farmers to remotely monitor and manage their operations from any global location. This aspect of the system emphasizes the importance of efficient information management and the transformation of sensor data into actionable insights, thereby reducing the need for constant human oversight and significantly increasing operational reliability. The autonomous functionality of the system is a key highlight, designed to persist in adjusting the environmental conditions within the fish farm until the optimal parameters are restored. This capability greatly diminishes the risks associated with manual monitoring and adjustments, allowing even those with limited expertise in aquaculture to achieve high levels of production efficiency and sustainability. By leveraging data-driven technologies and IoT innovations, this study not only addresses the immediate needs of the fish farming industry but also contributes to solving the broader global challenge of protein production. It presents a scalable and accessible approach to modern aquaculture, empowering stakeholders to maximize output and minimize risks associated with fish farming, thereby paving the way for a more sustainable and efficient future in the global food supply. Full article

The hydrophobic effect is the main factor that drives the folding of polypeptide chains. In this study, we have examined the influence of the hydrophobic effect in the context of the main mechanical forces approach, mainly in relation to the establishment of specific interplays, such as hydrophobic and CH–π cloud interactions. By adopting three oligopeptides as model systems to assess folding features, we demonstrate herein that these finely tuned interactions dominate over electrostatic interactions, including H-bonds and electrostatic attractions/repulsions. The folding mechanism analysed here demonstrates cooperation at the single-residue level, for which we propose the terminology of “single residues cooperative folding”. Overall, hydrophobic and CH–π cloud interactions produce the main output of the hydrophobic effect and govern the folding mechanism, as demonstrated in this study with small polypeptide chains, which in turn represent the main secondary structures in proteins. Full article

Predicting protein–ligand binding sites is an integral part of structural biology and drug design. A comprehensive understanding of these binding sites is essential for advancing drug innovation, elucidating mechanisms of biological function, and exploring the nature of disease. However, accurately identifying protein–ligand binding sites remains a challenging task. To address this, we propose PGpocket, a geometric deep learning-based framework to improve protein–ligand binding site prediction. Initially, the protein surface is converted into a point cloud, and then the geometric and chemical properties of each point are calculated. Subsequently, the point cloud graph is constructed based on the inter-point distances, and the point cloud graph neural network (GNN) is applied to extract and analyze the protein surface information to predict potential binding sites. PGpocket is trained on the scPDB dataset, and its performance is verified on two independent test sets, Coach420 and HOLO4K. The results show that PGpocket achieves a 58% success rate on the Coach420 dataset and a 56% success rate on the HOLO4K dataset. These results surpass competing algorithms, demonstrating PGpocket’s advancement and practicality for protein–ligand binding site prediction. Full article

Background: Transcatheter aortic valve replacement (TAVR) was developed for inoperable patients with severe aortic stenosis. However, despite TAVR advancements, some patients remain untreated due to complex comorbidities, necessitating less-invasive approaches. Non-invasive ultrasound therapy (NIUT), a new treatment modality, has the potential to address this treatment gap, delivering short ultrasound pulses that create cavitation bubble clouds, aimed at softening embedded calcification in stiffened valve tissue. Methods: In the prospective Valvosoft^® Serbian first-in-human study, we assessed the safety and efficacy of NIUT and its impact on aortic valve hemodynamics, on the left ventricle, and on systemic inflammation in patients with severe symptomatic aortic stenosis not eligible for TAVR or surgery. Results: Ten patients were included. Significant improvements were observed in hemodynamic parameters from baseline to one month, including a 39% increase in the aortic valve area (from 0.5 cm² to 0.7 cm², p = 0.001) and a 23% decrease in the mean transvalvular gradient (from 54 mmHg to 38 mmHg, p = 0.01). Additionally, left ventricular global longitudinal strain significantly rose, while global wasted work significantly declined at one month. A dose–response relationship was observed between treatment parameters (peak acoustic power, intensity spatial-peak pulse-average, and mean acoustic energy) and hemodynamic outcomes. NIUT was safely applied, with no clinically relevant changes in high-sensitivity troponin T or C-reactive protein and with a numerical, but not statistically significant, reduction in brain natriuretic peptide (from 471 pg/mL at baseline to 251 pg/mL at one month). Conclusions: This first-in-human study demonstrates that NIUT is safe and confers statistically significant hemodynamic benefits both on the valve and ventricle. Full article

Advancing climate change increases the risk of future infectious disease outbreaks, particularly of zoonotic diseases, by affecting the abundance and spread of viral vectors. Concerningly, there are currently no approved drugs for some relevant diseases, such as the arboviral diseases chikungunya, dengue or zika. The development of novel inhibitors takes 10–15 years to reach the market and faces critical challenges in preclinical and clinical trials, with approximately 30% of trials failing due to side effects. As an early response to emerging infectious diseases, CavitOmiX allows for a rapid computational screening of databases containing 3D point-clouds representing binding sites of approved drugs to identify candidates for off-label use. This process, known as drug repurposing, reduces the time and cost of regulatory approval. Here, we present potential approved drug candidates for off-label use, targeting the ADP-ribose binding site of Alphavirus chikungunya non-structural protein 3. Additionally, we demonstrate a novel in silico drug design approach, considering potential side effects at the earliest stages of drug development. We use a genetic algorithm to iteratively refine potential inhibitors for (i) reduced off-target activity and (ii) improved binding to different viral variants or across related viral species, to provide broad-spectrum and safe antivirals for the future. Full article

Presence-absence variations (PAVs) are important structural variations, wherein a genomic segment containing one or more genes is present in some individuals but absent in others. While PAVs have been extensively studied in plants, research in cattle remains limited. This study identified PAVs in 173 Holstein bulls using whole-genome sequencing data and assessed their associations with 46 economically important traits. Out of 28,772 cattle genes (from the longest transcripts), a total of 26,979 (93.77%) core genes were identified (present in all individuals), while variable genes included 928 softcore (present in 95–99% of individuals), 494 shell (present in 5–94%), and 371 cloud genes (present in <5%). Cloud genes were enriched in functions associated with hormonal and antimicrobial activities, while shell genes were enriched in immune functions. PAV-based genome-wide association studies identified associations between gene PAVs and 16 traits including milk, fat, and protein yields, as well as traits related to health and reproduction. Associations were found on multiple chromosomes, illustrating important associations on cattle chromosomes 7 and 15, involving olfactory receptor and immune-related genes, respectively. By examining the PAVs at the population level, the results of this research provided crucial insights into the genetic structures underlying the complex traits of Holstein cattle. Full article

Purine stretches, sequences of adenine (A) and guanine (G) in DNA, play critical roles in binding regulatory protein factors and influence gene expression by affecting DNA folding. Both purines can exist in the enol-amine form (often referred to as the imidazole form) and keto-imine forms. The enol-amine form is more stable and biologically significant than the keto-imine form. This enhanced stability is attributed to the fully conjugated ring system in the enol-amine form, which adheres to Hückel’s rule and becomes aromatic. The presence of a delocalized pi-electron cloud within this fully conjugated ring system results in an aromatic molecule. In contrast, the keto-imine form lacks full conjugation in its ring system due to a broken double bond between the nitrogen and carbon atoms, rendering it non-aromatic. This study investigates the relationship between purine stretches and cancer development, which makes mechanistic sense considering the aromaticity of purines in the purine stretches flanking each mutation. A pronounced avoidance of typical cancer mutations of long purine stretches in typical types of cancer was observed in the public data of patients in intergenic regions, suggesting the role of intergenic sequences in chromatin reorganization and gene regulation. A statistically significant shortening of purine stretches in cancerous tumors (p-value 0.0001) was found. The insights into the aromatic nature of purines and their stacking energies explain the role of purine stretches in DNA structure, contributing to their role in cancer progression. This research lays the groundwork for understanding the nature of purine stretches, emphasizing their importance in gene regulation and chromatin restructuring, and offers potential avenues for novel cancer therapies and insights into cancer etiology. Full article

This paper presents a cost-effective, quantitative, point-of-care solution for urinalysis screening, specifically targeting nitrite, protein, creatinine, and pH in urine samples. Detecting nitrite is crucial for the early identification of urinary tract infections (UTIs), while regularly measuring urinary protein-to-creatinine (UPC) ratios aids in managing kidney health. To address these needs, we developed a portable, transmission-based colorimeter using readily available components, controllable via a smartphone application through Bluetooth. Multiple colorimetric detection strategies for each analyte were identified and tested for sensitivity, specificity, and stability in a salt buffer, artificial urine, and human urine. The colorimeter successfully detected all analytes within their clinically relevant ranges: nitrite (6.25–200 µM), protein (2–1024 mg/dL), creatinine (2–1024 mg/dL), and pH (5.0–8.0). The introduction of quantitative protein and creatinine detection, and a calculated urinary protein-to-creatinine (UPC) ratio at the point-of-care, represents a significant advancement, allowing patients with proteinuria to monitor their condition without frequent lab visits. Furthermore, the colorimeter provides versatile data storage options, facilitating local storage on mobile devices or in the cloud. The paper further details the setup of the colorimeter’s secure connection to a cloud-based environment, and the visualization of time-series analyte measurements in a web-based dashboard. Full article

As a substance present in organisms, nitrite is a metabolite of nitric oxide and can also be ingested. Nitrate is the metabolite of nitrite. Therefore, it is necessary to measure it quickly, easily and accurately to evaluate the health status of humans. Although there have been several reviews on analytical methods for non-biological samples, there have been no reviews focused on both sample preparation and analytical methods for biological samples. First, rapid and accurate nitrite measurement has significant effects on human health. Second, the detection of nitrite in biological samples is problematic due to its very low concentration and matrix interferences. Therefore, the pretreatment plus measuring methods for nitrite and nitrate obtained from biological samples since 2010 are summarized in the present review, and their prospects for the future are proposed. The treatment methods include liquid–liquid microextraction, various derivatization reactions, liquid–liquid extraction, protein precipitation, solid phase extraction, and cloud point extraction. Analytical methods include spectroscopic methods, paper-based analytical devices, ion chromatography, liquid chromatography, gas chromatography–mass spectrometry, electrochemical methods, liquid chromatography–mass spectrometry and capillary electrophoresis. Derivatization reagents with rapid quantitative reactions and advanced extraction methods with high enrichment efficiency are also included. Nitrate and nitrate should be determined at the same time by the same analytical method. In addition, much exploration has been performed on formulating fast testing through microfluidic technology. In this review, the newest developments in nitrite and nitrate processing are a focus in addition to novel techniques employed in such analyses. Full article

Licorice is a frequently applied herb with potential edible and medicinal value based on various flavonoids and triterpenes. However, studies on detailed flavonoid and triterpene metabolism and the molecular basis of their biosynthesis in licorice are very limited, especially under drought conditions. In the present study, we carried out transcriptome, proteome, and metabolome experiments. To ultimately combine three omics for analysis, we performed a bioinformatics comparison, integrating transcriptome data and proteome data through a Cloud platform, along with a simplified biosynthesis of primary flavonoids and triterpenoids in the KEGG pathway based on metabolomic results. The biosynthesis pathways of triterpenes and flavonoids are enriched at both gene and protein levels. Key flavonoid-related genes (PAL, 4CL, CHS, CHI, CYP93C, HIDH, HI4OMT, and CYP81E1_7) and representative proteins (HIDH, CYP81E1_7, CYP93C, and VR) were obtained, which all showed high levels after drought treatment. Notably, one R2R3-MYB transcription factor (Glyur000237s00014382.1), a critical regulator of flavonoid biosynthesis, achieved a significant upregulated expression as well. In the biosynthesis of glycyrrhizin, both gene and protein levels of bAS and CYP88D6 have been found with upregulated expression under drought conditions. Most of the differentially expressed genes (DEGs) and proteins (DEPs) showed similar expression patterns and positively related to metabolic profiles of flavonoid and saponin. We believe that suitable drought stress may contribute to the accumulation of bioactive constituents in licorice, and our research provides an insight into the genetic study and quality breeding in this plant. Full article

Background: Oxidative stress-induced retinal degeneration is among the main contributing factors of serious ocular pathologies that can lead to irreversible blindness. αB-crystallin (cry) is an abundant component of the visual pathway in the vitreous humor, which modulates protein and cellular homeostasis. Within this protein exists a 20 amino acid fragment (mini-cry) with both chaperone and antiapoptotic activity. This study fuses this mini-cry peptide to two temperature-sensitive elastin-like polypeptides (ELP) with the goal of prolonging its activity in the retina. Methods: The biophysical properties and chaperone activity of cry-ELPs were confirmed by mass spectrometry, cloud-point determination, and dynamic light scattering ’DLS’. For the first time, this work compares a simpler ELP architecture, cry-V96, with a previously reported ELP diblock copolymer, cry-SI. Their relative mechanisms of cellular uptake and antiapoptotic potential were tested using retinal pigment epithelial cells (ARPE-19). Oxidative stress was induced with H₂O₂ and comparative internalization of both cry-ELPs was made using 2D and 3D culture models. We also explored the role of lysosomal membrane permeabilization by confocal microscopy. Results: The results indicated successful ELP fusion, cellular association with both 2D and 3D cultures, which were enhanced by oxidative stress. Both constructs suppressed apoptotic signaling (cleaved caspase-3); however, cry-V96 exhibited greater lysosomal escape. Conclusions: ELP architecture is a critical factor to optimize delivery of therapeutic peptides, such as the anti-apoptotic mini-cry peptide; furthermore, the protection of mini-cry via ELPs is enhanced by lysosomal membrane permeabilization. Full article

To explore the temporal profile of retinal proteomes specific to primary and secondary retinal ganglion cell (RGC) loss. Unilateral partial optic nerve transection (pONT) was performed on the temporal side of the rat optic nerve. Temporal and nasal retinal samples were collected at 1, 4 and 8 weeks after pONT (n = 4 each) for non-biased profiling with a high-resolution hybrid quadrupole time-of-flight mass spectrometry running on label-free SWATH^TM acquisition (SCIEX). An information-dependent acquisition ion library was generated using ProteinPilot 5.0 and OneOmics cloud bioinformatics. Combined proteome analysis detected 2531 proteins with a false discovery rate of <1%. Compared to the nasal retina, 10, 25 and 61 significantly regulated proteins were found in the temporal retina at 1, 4, and 8 weeks, respectively (p < 0.05, FC ≥ 1.4 or ≤0.7). Eight proteins (ALDH1A1, TRY10, GFAP, HBB-B1, ALB, CDC42, SNCG, NEFL) were differentially expressed for at least two time points. The expressions of ALDH1A1 and SNCG at nerve fibers were decreased along with axonal loss. Increased ALDH1A1 localization in the inner nuclear layer suggested stress response. Increased GFAP expression demonstrated regional reactivity of astrocytes and Muller cells. Meta-analysis of gene ontology showed a pronounced difference in endopeptidase and peptidase inhibitor activity. Temporal proteomic profiling demonstrates established and novel protein targets associated with RGC damage. Full article