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Curcumin, a natural polyphenolic compound present in Curcuma longa L. rhizomes, shows potent antioxidant, anti-inflammatory, anti-cancer, and anti-atherosclerotic properties. Atherosclerosis is a comprehensive term for a series of degenerative and hyperplasic lesions such as thickening or sclerosis in large- and medium-sized arteries, causing decreased vascular-wall elasticity and lumen diameter. Atherosclerotic cerebro-cardiovascular disease has become a major concern for human health in recent years due to its clinical sequalae of strokes and heart attacks. Curcumin concoction treatment modulates several important signaling pathways related to cellular migration, proliferation, cholesterol homeostasis, inflammation, and gene transcription, among other relevant actions. Here, we provide an overview of curcumin in atherosclerosis prevention and disclose the underlying mechanisms of action of its anti-atherosclerotic effects.

Bacteria use a variety of defense systems to protect themselves from phage infection. In turn, phages have evolved diverse counter-defense measures to overcome host defenses. Here, we use protein structural similarity and gene co-occurrence analyses to screen >66 million viral protein sequences and >330,000 metagenome-assembled genomes for the identification of anti-phage and counter-defense systems. We predict structures for ~300,000 proteins and perform large-scale, pairwise comparison to known anti-CRISPR (Acr) and anti-phage proteins to identify structural homologs that otherwise may not be uncovered using primary sequence search. This way, we identify a Bacteroidota phage Acr protein that inhibits Cas12a, and an Akkermansia muciniphila anti-phage defense protein, termed BxaP. Gene bxaP is found in loci encoding Bacteriophage Exclusion (BREX) and restriction-modification defense systems, but confers immunity independently. Our work highlights the advantage of combining protein structural features and gene co-localization information in studying host-phage interactions. Bacteria use various defense systems to protect themselves from phage infection, and phages have evolved diverse counter-defense measures to overcome host defenses. Here, the authors use protein structural similarity and gene co-occurrence analyses for identification of new anti-phage and counter-defense systems.

Crohn’s and ulcerative colitis are common inflammatory conditions associated with Inflammatory bowel disease. Owing to the importance of diet based approaches for the prevention of inflammatory gut conditions, the present study was aimed to screen the human isolates of Bifidobacterium strains based on their ability to reduce LPS-induced inflammation in murine macrophage (RAW 264.7) cells and to evaluate prioritized strains for their preventive efficacy against ulcerative colitis in mice. Twelve out of 25 isolated strains reduced the production of LPS-induced nitric oxide and inflammatory cytokines. Furthermore, three strains, B. longum Bif10 , B. breve Bif11 , and B. longum Bif16 conferred protection against dextran sodium sulfate induced colitis in mice. The three strains prevented shortening of colon, spleen weight, percentage body weight change and disease activity index relative to colitis mice. Lower levels of Lipocalin-2, TNF-α, IL-1β and IL-6 and improved SCFA levels were observed in Bifidobacterium supplemented mice relative to DSS counterparts. Bacterial composition of B. longum Bif10 and B. breve Bif11 fed mice was partly similar to the normal mice, while DSS and B. longum Bif16 supplemented mice showed deleterious alterations. At the genus level, Bifidobacterium supplementation inhibited the abundances of pathobionts such as Haemophilus , Klebsiella and Lachnospira there by conferring protection.

Skin diseases frequently cause mental and physical distress and are major global health concern. Because early detection is crucial to successful treatment, accurate diagnosis is challenge for dermatologists as well. Diagnostic accuracy could be significantly enhanced using methods like machine learning (ML) and deep learning (DL). However, substantial datasets are required for these models to make accurate predictions. The healthcare providers frequently encounter data shortages, and privacy regulations restrict data sharing. A privacy-preserving federated transfer learning for diagnosing skin diseases which incorporate four key strategies to enhance effectiveness. The transfer learning is used to train a model with dense neural network (DNN) for skin diseases detection. The feature extraction is performed using pre-trained architectures and DNN is used for classification. The federated learning (FL) replaces the transfer learning to train the model across distributed nodes with the DNN used to disease detection. The FL is combined with transfer learning to build a cohesive ecosystem where data privacy is maintained. The model performance was validated on both IID and non-IID database, with the proposed feature extraction with federated learning model achieving cross validation accuracy of 99.528% and 99.689% for IID and non-IID database, respectively. Results indicate that feature extraction with FL model can produce efficient, lightweight models—well-suited for resource-constrained devices—while ensemble learning enhances edge device performance, offering a powerful and privacy-preserving solution for skin disease diagnosis in modern healthcare.

Considering the major source of plant-derived low/non-calorie steviol glycosides (SGs), comprehensive physiological, biochemical, and deep transcriptional investigations were conducted to explicit deeper insight into multiple abiotic stress responses in Stevia rebaudiana . The physiological indicators including photosynthesis, chlorophyll, relative water content, shoot growth, electrolyte leakage, and SG biosynthesis were negatively impacted under drought (DS), followed by salinity (SS) and waterlogging (WS). Global transcriptional analysis revealed significant upregulated expression of the genes encoding for ROS detoxification (GST, SOD, APX, glutathione peroxidase), osmotic adjustment (alpha-trehalose-phosphate and S-adenosylmethionine decarboxylase), ion transporters (CAX, NHX, CNGS, VPPase, VATPase), water channel (PIP1, TIP) and abiotic stress-responsive candidate genes (LEA, HSPs, and Dehydrins) regulating abiotic stress response in S. rebaudiana . These inferences were complemented with predicted interactome network that revealed regulation of energy metabolism by key stress-responsive genes (GST, HKT1, MAPKs, P5CSs, PIP), transcription factors (HSFA2, DREB1A, DREB2A), and abiotic stress responsive pathways (ABA, ethylene, ion stress). This is the first detailed study to comprehend the molecular regulation of stress response and their interplay under DS, SS, and WS. The key genes and regulators can be functionally validated, and will facilitate targeted gene editing for genetic improvement of crop sustainability under changing environmental conditions in S. rebaudiana.

Large-scale subsurface hydrogen storage is critical for transitioning towards renewable, economically viable, and emission-free energy technologies. Although preliminary studies on geochemical interactions between different minerals, aqueous ions, and other dissolved gasses with H2 have helped partially quantify the degree of hydrogen loss in the subsurface, the long-term changes in abiotic hydrogen–brine–rock interactions are still not well understood due to variable rates of mineral dissolution/precipitation and redox transformations under different conditions of reservoirs. One of the potentially understudied aspects of these complex geochemical interactions is the role of iron on the redox interactions and subsequent impact on long-term (100 years) hydrogen cycling. The theoretical modeling conducted in this study indicates that the evolution of secondary iron-bearing minerals, such as siderite and magnetite, produced after H2-induced reductive dissolution of primary Fe3+-bearing phases can result in different degrees of hydrogen loss. Low dissolved Fe2+ activity (<10−4) in the formation water can govern the transformation of secondary siderite to magnetite within 100 years, eventually accelerating the H2 consumption through reductive dissolution. Quantitative modeling demonstrates that such secondary iron mineral transformations need to be studied to understand the long-term behavior of hydrogen in storage sites.

Since the advent of the coronavirus disease (COVID-19) infection, this highly infectious virus has spread worldwide infecting millions of people. Not only it has affected the pulmonary function of the body, leading to difficulty in breathing, but at the same time, an array of other systemic infections which may or may not be directly due to coronavirus infection, due to an absent established relationship. The mucocutaneous manifestations seen in COVID-19 infection include depapillation of the tongue, lesions seen on alveolar mucosa, gingiva, buccal mucosa, dysgeusia, and dry mouth. This case report highlights the effect of COVID-19 on the tongue also known as COVID tongue seen as depapillation of the tongue surface. Due to the absence of long-term studies and time-limited research, a direct relationship between COVID-19 and the systemic manifestation is not yet established. More research has to be done in this direction, to chart out the exact etiology of these systemic infections.

The inhibition of tumor necrosis factor (TNF)-α trimer formation renders it inactive for binding to its receptors, thus mitigating the vicious cycle of inflammation. We designed a peptide (PIYLGGVFQ) that simulates a sequence strand of human TNFα monomer using a series of in silico methods, such as active site finding (Acsite), protein–protein interaction (PPI), docking studies (GOLD and Flex-X) followed by molecular dynamics (MD) simulation studies. The MD studies confirmed the intermolecular interaction of the peptide with the TNFα. Fluorescence-activated cell sorting and fluorescence microscopy revealed that the peptide effectively inhibited the binding of TNF to the cell surface receptors. The cell culture assays showed that the peptide significantly inhibited the TNFα-mediated cell death. In addition, the nuclear translocation of the nuclear factor kappa B (NFκB) was significantly suppressed in the peptide-treated A549 cells, as observed in immunofluorescence and gel mobility-shift assays. Furthermore, the peptide protected against joint damage in the collagen-induced arthritis (CIA) mouse model, as revealed in the micro focal-CT scans. In conclusion, this TNFα antagonist would be helpful for the prevention and repair of inflammatory bone destruction and subsequent loss in the mouse model of CIA as well as human rheumatoid arthritis (RA) patients. This calls upon further clinical investigation to utilize its potential effect as an antiarthritic drug.

Time series experiments were used to explore the fluid redox impact on the corrosion of Q125, 316L, and C276 steels in low-ionic-strength and neutral water at temperature and pressure conditions associated with low-temperature geothermal systems. After exposing polished samples of each steel grade to an oxidizing (H2O2) and a reducing (Zn-doped) fluid for intervals of 24 h, 1 week, and 6 weeks, the atomic force microscopy results revealed general corrosion for Q125, while 316L and C276 exhibited pitting, crevice expansion, and edge attack corrosion. Secondary depositional features are frequently found as topographic highs, adjacent to pitting corrosion. These features may be identified as there is a very strong spatial correlation between the height retrace and phase retrace surface maps. All steels became progressively rougher over time after exposure to both fluids, while the corrosion rates were more complex. Samples exposed to the reducing fluid experienced an increase in the corrosion rate over time, while C276 and 316L experienced a decrease in the corrosion rate. Finally, a novel data validation technique was developed to address the intrinsic scalability of corrosion. The results indicate that the AFM scan area does not affect the measured surface roughness over nearly three orders of magnitude.

Malnutrition affects growth and development in humans and causes socio-economic losses. Normal maize is deficient in essential amino acids, lysine and tryptophan; and vitamin-A. Crop biofortification is a sustainable and economical approach to alleviate micronutrient malnutrition. We combined favorable alleles of crtRB1 and lcyE genes into opaque2 ( o2 )-based four inbreds viz . QLM11, QLM12, QLM13, and QLM14 using marker-assisted backcross breeding. These are parents of quality protein maize versions of two elite hybrids viz . Buland and PMH1, grown in India. Gene-based SSRs for o2 and InDel markers for crtRB1 and lcyE were successfully employed for foreground selection in BC 1 F 1 , BC 2 F 1 , and BC 2 F 2 generations. The recurrent parent genome recovery ranged from 88.9 to 96.0% among introgressed progenies. Kernels of pyramided lines possessed a high concentration of proA (7.14–9.63 ppm), compared to 1.05 to 1.41 ppm in the recurrent parents, while lysine and tryptophan ranged from 0.28–0.44% and 0.07–0.09%, respectively. The reconstituted hybrids (RBuland and RPMH1) showed significant enhancement of endosperm proA (6.97–9.82 ppm), tryptophan (0.07–0.09%), and lysine (0.29–0.43%), while grain yield was at par with their original versions. The dissemination of reconstituted hybrids holds significant promise to alleviate vitamin-A deficiency and protein-energy malnutrition in developing countries.