Natural products (NPs) including herbal teas are widely consumed in Malaysia but lack stringent regulation. Naturally occurring phytochemicals including estragole (genotoxic), aristolochic acids (AAs; Group 1 carcinogen) and certain pyrrolizidine alkaloids (PAs; Group 2B carcinogen) pose severe hepatotoxic and nephrotoxic risk. An integrated risk assessment using the Margin of Exposure (MOE) and the RISK21 framework was applied to 90 NPs (30 per compound). The samples were identified through National Pharmaceutical Regulatory Agency (NPRA) QUEST3 + database and analyzed using validated UPLC-DAD and LC-MS methods. Estragole, AAs, and PAs were detected in 30% (55.0-418.0 µg/g), 16.7% (8.7-2256.3 µg/g), and 36.7% (0.02-21.1 µg/g) of samples, respectively. Lifetime exposure to estragole and AAs, and eight PA-positive samples, resulted in MOE values < 10 000, indicating high priority for risk management. RISK21 characterization placed AAs in the red zone, representing unacceptable risk. Notably, half of estragole-positive products targeted women's health, raising concerns for vulnerable populations, including potential neonatal exposure via breast milk. Furthermore, simultaneous product use may result in potential cumulative effects. Malaysians face significant long-term health risks from toxic phytochemicals in NPs, particularly AAs. The integrated framework provides a critical decision-support tool to strengthen regulatory oversight and enforce stricter quality control.
The growing demand for sustainable construction materials has accelerated the need for alternatives to natural aggregates in concrete. Although steel slag has been extensively studied, the use of steel sludge as a fine aggregate substitute in concrete paver blocks has not been sufficiently examined, especially regarding durability and microstructural characteristics. This study investigates the performance of steel sludge as a micro-filler and partial replacement of fine aggregate at 10%, 20%, and 30% by mass, maintaining a constant water-cement ratio of 0.38. Mechanical and durability properties were evaluated using compressive strength, water absorption, sorptivity, rapid chloride penetration, and weight loss tests, complemented by SEM, EDX, and XRD analyses. The results indicate a consistent improvement in performance with increasing steel sludge content. The 28-day compressive strength increased from 42.77 MPa for the control mix to 54.13 MPa at 30% replacement, representing an approximate 26.6% increase. Water absorption decreased from 6.12% to 4.20%, the initial absorption rate decreased from 0.0332 to 0.0250 mm/min⁰·⁵. and RCPT values declined from 640 to 552 Coulombs, reflecting reduced permeability. Microstructural analysis demonstrated pore refinement, a lower Ca/Si ratio, and enhanced formation of polymerized C-(A)-S-H gel. XRD analysis confirmed the absence of new crystalline phases. Within the investigated range, steel sludge enhances strength and durability through matrix densification and microstructural refinement. These findings demonstrate its potential as a sustainable industrial waste management to natural sand in paver block applications.
The strawberry tree (Arbutus andrachne L.) is an underutilized Mediterranean fruit species with considerable potential as a source of nutritionally valuable and functionally important bioactive compounds. In the present study, 30 naturally growing genotypes collected from Defne district of Hatay Province, Türkiye, were comprehensively evaluated over two consecutive growing seasons (2024 and 2025) to determine the extent of variation in fruit pomological traits, color parameters, biochemical composition, antioxidant capacity, and mineral content. Fruit width, fruit length, fruit weight, CIELAB color coordinates (L*, a*, and b*), total phenolic content, total flavonoid content, total anthocyanin content, total antioxidant capacity, and 16 mineral elements were assessed. In addition to univariate comparisons, multivariate statistical approaches, including correlation analysis, principal component analysis, heat map analysis, and multiple regression analysis, were applied to reveal trait interrelationships and genotype differentiation. The results demonstrated significant genotype-dependent variation for all evaluated traits, indicating broad phenotypic diversity within the studied germplasm. Fruit weight ranged from 0.29 to 1.81 g, total phenolic content from 321.61 to 507.01 mg GAE 100 g⁻1 FW, total flavonoid content from 125.54 to 288.87 mg CAE 100 g⁻1 FW, total anthocyanin content from 7.22 to 20.07 mg C3G 100 g⁻1 FW, and antioxidant capacity from 31.54% to 64.09% inhibition. Potassium was the predominant mineral, varying between 2867.29 and 8134.66 mg kg⁻1 DW. Genotype 'AA-7' was distinguished by superior fruit size and weight, 'AA-19' by outstanding macro-mineral accumulation, 'AA-14' by the highest antioxidant capacity, 'AA-3' by elevated phenolic content, and 'AA-23' by the highest anthocyanin concentration. Multivariate analyses revealed strong coordination among fruit size traits, structured associations among color parameters, partial coupling among biochemical variables, and an integrated pattern of mineral accumulation. Multivariate analyses further revealed that several genotypes, particularly 'AA-7', 'AA-14', 'AA-19', and 'AA-23', occupied distinct positions in the multivariate space, reflecting unique combinations of pomological, biochemical, and mineral attributes. Overall, the findings highlight the substantial breeding, conservation, and functional food potential of naturally growing strawberry tree germplasm.
Characterizing the mechanical and thermal properties of heterogeneous natural building materials, including traditional stones and earth-based composites, presents significant engineering challenges. This study proposes an exploratory non-destructive analytical framework to examine potential proxy relationships among physical, mechanical, and hygrothermal properties of traditional heritage materials. Because the dataset consists of seven aggregated material classes, the results should be interpreted as preliminary trends rather than validated predictive laws. Using a dataset covering seven aggregated material classes, the analysis suggests that porosity may serve as an exploratory indicator of compressive strength (R² = 0.62), while density shows a strong association with thermal conductivity (R² = 0.85). These relationships should be interpreted as dataset-specific trends rather than externally validated predictive models. Furthermore, Principal Component Analysis (PCA) was used as an exploratory dimensional-reduction tool to visualize broad material groupings associated with density, porosity, moisture absorption, and strength. PC1 accounted for 82.7% of the variance within the analyzed dataset; however, this result should not be interpreted as a validated classification model because of the limited number of material classes. The present study does not implement a full HBIM or digital twin system. Instead, it proposes a conceptual pathway for future integration: (1) non-destructive measurement of porosity/density, (2) input into a material-property database, (3) assignment of material parameters to HBIM elements, (4) risk classification using PCA/clustering, and (5) visualization of vulnerable elements for conservation decision-making.
This study involves an integrated approach to predict the mechanical properties of luffa fiber and marble dust- based concrete. It employs Artificial Neural Network (ANN) for mechanical properties prediction aiming for a higher accuracy than currently available models. The composite material used marble dust in the proportion 0-40% as fine aggregate replacement and luffa fiber in the proportion 0-2% as the natural reinforcement. Experimental results implied that the composite containing 20% marble dust and 1% luffa fiber exhibited greatest mechanical characteristics- Compressive strength of 34.5 MPa, flexural strength of 6.2 MPa and split tensile strength of 4.25 MPa. This improvement was attributed to enhanced particle packing by marble dust and effective crack bridging by treated luffa fiber. A single multi-output feedforward multilayer perceptron (MLP) ANN consisting of two hidden layers of 64 and 32 neurons with ReLU activation functions and a three-neuron linear output layer was developed for simultaneously modelling the nonlinear interactions between the input variables and strength outputs. The model was trained on 70% of the dataset, with 15% for validation and 15% for testing. The ANN model was able to predict all three mechanical strength properties simultaneously with a high degree of accuracy as demonstrated by R² values of 0.89 (compressive strength), 0.94 (flexural strength), and 0.96 (split tensile strength) for the training data sets and small root mean square error (RMSE) values and negligible bias. The 100% a20 score indicated that all the samples from the predictions fell within ± 20% of the actual experimental values, demonstrating good robustness or generality. This research basically aims to address a major gap in the existing works by exploring the limited application of ANN in predicting the performance of hybrid sustainable concrete mixes incorporating both marble dust and plant-based fibers by developing a predictive model which is capable of capturing the complex interactions between multiple factors and enhancing the prediction efficiency, minimizing the dependency on extensive experimental investigations thereby promoting data driven evaluation of strength characteristics in sustainable concrete composites.
Natural killer (NK) cells frequently exhibit an exhausted state, which facilitates immune escape of circulating tumor cells (CTCs). However, the underlying mechanisms of NK cell dysfunction remain elusive. In this study, we identified a novel immune evasion mechanism whereby tumor cells deliver Vimentin to NK cells via NKp46-dependent trogocytosis, thereby impairing NK cell cytotoxicity. We observed the expression of nonendogenous proteins in NK cells isolated from CTCs from oral cancer patients but not in those from nondetectable patients. High-throughput proteomic analysis, flow cytometry, and confocal microscopy revealed that vimentin, a protein that is not endogenously expressed in NK cells, was significantly enriched in NK cells via NKp46-dependent trogocytosis. The tail domain of trogocytosed vimentin competed with CDC42 for binding to ARHGEF7 and inhibited its exchange activity. This disruption impaired CDC42-mediated actin polymerization, thus suppressing NK cell cytotoxicity. By delivering vimentin to NK cells, CTCs can suppress and evade attacks from NK cells. Crucially, pharmacological inhibition of vimentin trogocytosis increased the efficacy of NK cells in clearing CTCs in vivo and that of NK cell-based adoptive immunotherapies. Clinically, the frequency of vimentin (+) NK cells is correlated with the CTC burden and tumor recurrence in cancer patients. Our study reveals that trogocytosis acts as a conduit for the tumor-induced exhaustion of NK cells and proposes targeting Vimentin transfer as a therapeutic strategy to counteract tumor recurrence.
Night vision goggles (NVGs) enhance vision under scotopic conditions by amplifying near-infrared light and converting it to a wavelength that can be seen by the human visual system. Although significantly more expensive than monocular systems, binocular NVGs provide the user with independent inputs to each eye, and therefore facilitate stereopsis, the ability to discriminate differences in depth from binocular cues. Past work examining stereopsis through NVGs has been mixed, with early-generation systems showing no evidence for stereopsis while more-modern systems show some evidence for (and others against) stereopsis, albeit at levels below that observed under natural photopic viewing conditions. These studies have examined stereopsis through NVGs under ideal conditions that isolate binocular contributions to depth perception. In the present study, stereopsis through NVGs was examined under more realistic conditions and for more operationally relevant tasks. The results show that stereopsis through NVGs persists even under degraded viewing conditions and provides a binocular advantage for real-world tasks where the perception of depth plays an important role. These results show that limitations in stereoacuity through NVGs are not driven by visual acuity limits, as has been previously argued, and more generally a dissociation between visual acuity and stereoacuity.
Polycystic ovary syndrome (PCOS) implicates hormonal imbalance, ovulation disorders, metabolic disturbances, and chronic low-grade inflammation. In this study, we investigated the inflammation driven by 12-lipoxygenase (12-LOX)-mediated conversion of arachidonic acid to pro-inflammatory 12-hydroxyeicosatetraenoic acid (12-HETE) and the therapeutic potential of avenanthramide (AVA)-enriched oat extract and trans-resveratrol (RSV) as natural 12-LOX inhibitors. AVA-enriched extract was obtained from oats using 80% methanol, dried, and analyzed by HPLC. Fifty-six rats (3-week-old females) were divided into 8 groups: four received letrozole 1 mg/kg in 0.5% carboxymethyl cellulose (CMC) for 21 days to induce PCOS, while four received only CMC. Each pair (PCOS and non-PCOS) was treated for 2 weeks with either AVA (100 and 300 mg/kg), trans-resveratrol (20 mg/kg), or left untreated. Serum hormonal profile and 12-HETE levels were assessed via ELISA. Ovarian 12-LOX expression was evaluated by Western blotting. Histopathological analysis was performed on the liver and reproductive organs. Treating PCOS-induced rats with 100 mg/kg AVA, 300 mg/kg AVA, and 20 mg/kg RSV significantly restored their hormonal profile to normal levels and significantly reduced ovarian 12-LOX expression and subsequently their serum 12-HETE levels compared to the untreated PCOS rats (P < 0.001, P < 0.0001, and P < 0.0001, respectively). The 300 mg/kg AVA and 20 mg/kg RSV treatments restored normal ovarian and uterine architecture compared to the untreated PCOS group. No histopathological alterations were observed in the liver or oviduct. Avenanthramides from Avena sativa (oats) restore endocrine and ovarian function in letrozole-induced PCOS by directly inhibiting the redox-sensitive 12-lipoxygenase-12-HETE lipid signaling pathway. These findings suggest that avenanthramides may represent a promising therapeutic approach for restoring endocrine balance and ovarian function in PCOS.
Oral cancer is a significant global health challenge, ranking as the sixth most prevalent cancer worldwide, with approximately 377,000 new cases diagnosed annually. The high morbidity and mortality rates are largely attributed to tobacco and alcohol use. While conventional treatments such as surgery, radiation, and chemotherapy have improved survival rates, they often lead to unfavourable aesthetic and functional outcomes. Tissue engineering offers a promising alternative, providing regenerative solutions aimed at restoring both oral function and appearance. By integrating biomaterials, biological systems, and engineering principles, tissue engineering enables the creation of functional tissue replacements. The current review examines different t pathways the potential applications of autologous tissue, oral cancer cell lines, CRISPR, gene-editing technologies, and epigenetic modifications for tissue regeneration. Advanced scaffold technologies that mimic the natural extracellular matrix, along with stem cell-based therapies and bioactive molecules, are employed to support tissue growth and differentiation. Mesenchymal stem cells (MSCs) and induced pluripotent stem cells (iPSCs) show significant potential in regenerating hard and soft oral tissues, while also targeting cancer stem cells (CSCs) to prevent recurrence. Furthermore, innovative technologies like 3D bio printing, combined with vascularization strategies, hold promise for developing patient-specific tissue constructs for reconstructive procedures. In conclusion, tissue engineering offers transformative potential for oral cancer treatment, presenting regenerative therapies that can significantly enhance patient outcomes and quality of life.
Vitiligo is a chronic autoimmune depigmenting disorder affecting 0.5%-2% of the global population, characterized by bidirectional interplay between psychological stress and disease progression, with accumulating evidence highlighting the central role and translational relevance of the neuro-endocrine-immune-cutaneous axis in its pathogenesis. Epidemiological data indicate over half of patients experience significant psychological stress prior to disease onset, while visible depigmentation markedly elevates the burden of depression and anxiety, establishing a self-amplifying pathogenic loop. Mechanistically, neural crest-derived melanocytes form functional "neuro-pigment units" with intraepidermal nerve endings, enabling bidirectional communication via neuropeptides including calcitonin gene-related peptide (CGRP) and substance P. Dynamic crosstalk among keratinocytes, sensory neurons, and melanocytes integrates neurotrophic and inflammatory signals to tightly regulate melanocyte survival and biological function. Sympathetic activation drives melanocyte injury via norepinephrine-mediated β2-adrenergic receptor signaling, while dopamine metabolites exacerbate apoptosis via the oxidative stress-Akt-Bad axis; context-dependent hypothalamic-pituitary-adrenal axis effects and light-melatonin-circadian clock disruption further promote immune dysregulation and melanocyte loss. Notably, neuromodulatory approaches like transcutaneous auricular vagus nerve stimulation show therapeutic promise by attenuating oxidative stress and limiting pathogenic CD8⁺ T-cell infiltration. These insights have fostered targeted strategies including CGRP receptor antagonists and dual antioxidant-neuroprotective natural compounds. Integrating neuroimmunological modulation with psychological and circadian interventions represents a promising precision medicine framework for vitiligo management.
Miniaturized microscopes or 'miniscopes' for neuroimaging in freely behaving animals mostly operate over short durations (<2 h) and image either neuronal activity or cerebral hemodynamics. In contrast, central nervous system (CNS) disease models involving seizures, brain tumors etc. necessitate long-term (>24 h) imaging, remote operation and simultaneous characterization of multiple neurophysiological variables such as neuronal activity, blood flow, blood volume, oxygenation and cellular dynamics (a capability that we call 'neurosurveillance'). Thus, we developed the 'CloudScope', a cloud-based multicontrast miniscope for autonomous neurosurveillance in freely behaving animals. Its cloud-based architecture enables global remote operation and continuous acquisition of multicontrast images over CNS disease model life cycles. We demonstrate CloudScope's neurosurveillance capabilities in predicting behavior from 24-h neuroimaging data with deep learning (DL), characterizing neurovascular changes during natural behavior, seizure-induced neurovascular disruptions, and in vivo cellular and microvascular phenotyping of brain tumor microenvironments. Finally, CloudScope's architecture enables 'time-shared' imaging, which potentially reduces animal use. Collectively, CloudScope's neurosurveillance capabilities in conjunction with CNS disease models establish a new paradigm for characterizing their etiology and evolution.
Accurate survival prediction in non-small cell lung cancer (NSCLC) requires integrating clinical, radiological, and histopathological data. Multimodal deep learning (MDL) can improve precision prognosis, but small cohorts and missing modalities limit its clinical applicability, as conventional approaches enforce complete-case filtering or imputation. We present a missing-aware multimodal survival framework that combines computed tomography (CT), whole-slide histopathology images (WSI), and structured clinical variables for overall survival modeling in unresectable stage II-III NSCLC. The framework uses foundation models (FMs) for modality-specific feature extraction and a missing-aware encoding strategy that enables intermediate multimodal fusion under naturally incomplete modality profiles. By design, the architecture processes all available data without dropping patients during training or inference. Intermediate fusion outperforms unimodal baselines and both early and late fusion strategies, with the trimodal configuration reaching a C-index of 74.42. Modality-importance analyses show that the fusion model adapts its reliance on each data stream according to representation informativeness, shaped by the alignment between FM pretraining objectives and the survival task. The learned risk scores produce clinically meaningful stratification of disease progression and metastatic risk, with statistically significant log-rank tests across all modality combinations, supporting the translational relevance of the proposed framework.
The natural antifungal peptide Histatin 5 (Hst 5) is a histidine-rich cationic peptide secreted by human salivary glands and a key component of oral innate immunity, but its moderate activity limits clinical use. Hst 5 enters Candida albicans via the membrane receptor Ssa1/2. Here, we integrated artificial intelligence-assisted and computer-aided drug design to rationally modified the sequence structure of Hst 5. Truncated derivatives of Hst5 were screened for antimicrobial potential using ESM2-AFPpred, and high-probability candidates were docked with Ssa1/2. The Hst 5-22 was identified, then redesigned based on alanine scanning to yield the optimized derivative Hst 5-22-RW. Compared with Hst 5, Hst 5-22-RW has a shorter sequence, stronger Ssa1/2 binding, and improved activity against C. albicans. It also shows superior activity against fluconazole-resistant strains. RT-qPCR and transmembrane tracking confirmed higher cellular transport efficiency in C. albicans. The CADD/AIDD-driven optimization successfully generated the highly active antifungal peptide Hst 5-22-RW, providing a novel strategy for rational modification of antimicrobial peptides.
The recycling of thermal power plant ash and other industrial wastes in ceramic wall products is a promising strategy for reducing natural clay consumption; however, the interaction between ash dosage, multi-waste composition, pressing time, firing temperature, and ceramic performance remains insufficiently clarified. This study evaluates ceramic wall products based on Ekibastuz thermal power plant ash, red brick waste, metallurgical slag, and glass waste, with emphasis on composition-processing-property relationships and microstructural mechanisms. Ceramic mixtures containing 0-30% thermal power plant ash and selected multi-waste combinations were pressure-molded at 15 MPa, pressed for 60-90 s, dried, and fired at 900-1100 °C. Compressive strength, water absorption, density, and microstructure were assessed to identify the optimal balance between waste incorporation and material performance. The highest performance was achieved by the mixture containing 20% thermal power plant ash, which reached 43.5 MPa compressive strength, 6.1% water absorption, and 2.30 g/cm³ density after firing at 1100 °C and pressing for 90 s. Increasing ash content to 30% reduced strength because of increased residual porosity and microstructural heterogeneity. Multi-waste mixtures containing red brick waste, metallurgical slag, and glass waste produced technically acceptable ceramics but did not exceed the optimized ash-only composition, showing that maximum waste replacement does not automatically provide maximum performance. The main innovation of the study is the identification of a controlled composition-processing-property window in which moderate ash incorporation improves densification and pore refinement, whereas excessive ash or multi-waste loading promotes heterogeneity. The findings demonstrate the engineering significance of optimized waste-derived ceramic systems for sustainable wall-product manufacturing.
Carbohydrates are among the most abundant and structurally diverse biomolecules in nature, playing central roles in energy storage, molecular recognition, and cell signaling. Within this domain, C-glycosides1-3, in which the oxygen atom of the glycosidic bond in O-glycosides is replaced by carbon, have emerged as valuable motifs in medicinal chemistry due to their resistance to enzymatic hydrolysis2,4. Of particular importance are C-aryl glycosides, exemplified by the SGLT2 inhibitors dapagliflozin, canagliflozin, and empagliflozin, which are frontline therapies for type 2 diabetes5-7. However, scalable syntheses of C-aryl glycosides have traditionally relied on protected sugar derivatives, lengthy sequences, or conventional cross-couplings that often suffer from poor selectivity, limited scope, and extensive protecting-group manipulation6. Herein, we report a practical approach to C-aryl glycosides using glycosyl sulfonyl hydrazides as redox-neutral radical precursors for cross-coupling. Prepared directly from unprotected native sugars, these reagents generate glycosyl radicals under mild conditions and enable efficient access to diverse C-aryl glycosides, including all approved SGLT2 inhibitors, natural products such as salmochelins and neopetrosins, and medicinally relevant probes. Beyond anomeric functionalization, this platform enables C-C bond formation at multiple positions on carbohydrate scaffolds and supports stereoretentive radical coupling that can override inherent stereochemical biases, expanding practical access to carbohydrate-derived therapeutics and chemical tools.
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Cryptococcosis is a severe invasive fungal infection with limited therapeutic options beyond fluconazole-based regimens. Isavuconazole, a broad-spectrum triazole antifungal, has emerged as a potential alternative, although clinical data supporting its use remain scarce. We aimed to evaluate the real-world effectiveness and safety of isavuconazole in patients with different forms of cryptococcosis. A retrospective observational study was conducted at a tertiary-care hospital, including patients with cryptococcosis who received isavuconazole at any treatment phase. Standard microbiological methods were used for pathogen identification and susceptibility testing. Demographic, clinical, and microbiological data were collected. Clinical and microbiological responses and tolerability were assessed at end of treatment or until death. Eight patients with cryptococcosis received isavuconazole, most of whom were immunocompromised. Clinical presentations included pulmonary and disseminated disease, with Cryptococcus neoformans as the predominant species. Isavuconazole was primarily used during the consolidation and maintenance phases, after induction therapy with amphotericin B and flucytosine for 2 weeks in most cases, and as salvage therapy in two patients. It was well tolerated during prolonged treatment (6-12 months). In the two patients with isavuconazole therapeutic drug monitoring, plasma total trough concentrations were within the therapeutic range (5 and 3.5 µg/mL, respectively), whereas cerebrospinal fluid total concentration levels were undetectable. A favorable clinical response was observed in four patients, while three remain on treatment with ongoing clinical improvement; one patient died early. Microbiological clearance was achieved in all culture-positive cases. Isavuconazole demonstrated clinical effectiveness in this cohort of patients across different presentations of cryptococcosis. Treatment was safe and well tolerated, supporting its role as an alternative antifungal option against Cryptococcus, particularly when fluconazole is limited by adverse effects or drug-drug interactions. However, data on central nervous system penetration were limited, and further studies are needed to better define its role in cryptococcal meningitis management.
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