Pancreatic ductal adenocarcinoma (PDAC) remains lethal due to late-stage diagnosis and limited non-surgical treatment options. Its intratumoral heterogeneity and desmoplastic tumor microenvironment (TME) drive invasion, immune escape, and treatment failure. Patient-derived organoids (PDOs) have emerged as efficient model platforms for simulating the TME and preserving tumor heterogeneity and enabling functional testing in vitro; however, conventional PDO cultures lack defined and controllable microenvironmental components and often exhibited limited reproducibility, physiological fidelity, and observability. This review synthesizes recent bioengineering advances that upgrade pancreatic cancer PDO platforms across three interconnected dimensions: (1) engineered extracellular matrices and biofabrication for reproducible construction; (2) co-culture, microfluidic, and bioreactor systems for physiological fidelity; (3) imaging AI and biosensor pipelines for quantitative monitoring. We highlight practical design principles and remaining bottlenecks for standardization, scalability, and clinical translation.
This study evaluated machine learning (ML) models predicting esophageal cancer (EC) treatment outcomes, focusing on data modalities, feature engineering, model frameworks, and validation. Following PRISMA guidelines (PROSPERO: CRD42024619947), six databases (2015-2024) were systematically searched. Two reviewers independently extracted data on model methodologies and performance. Study quality was assessed using a modified TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) + AI checklist. Among 30 studies (14,342 patients), classical ML models were the most frequently employed approach (n = 43), followed by ensemble methods (n = 34), with deep learning being the least utilized (n = 11); however, the best-performing models across all studies demonstrated mean AUC values of 0.847 for deep learning, 0.835 for ensemble models, and 0.816 for classical approaches. Imaging and clinical data constituted the predominant both unimodal and multimodal modeling inputs, with supervised learning representing the dominant paradigm. Multimodal models achieved a significantly higher AUC (0.84 vs. 0.78) than single-modal models. Model validation primarily relied on k-fold cross-validation and external cohort approaches. Quality assessment showed moderate reporting completeness (64.79% median fulfillment). While ML (particularly deep learning and multimodal approaches) demonstrated potential for EC treatment prediction, key limitations persisted, such as opaque computational methods, poorly justified predictor selection, and unaddressed population heterogeneity/class imbalance. Addressing these challenges would be critical to enhancing the reliability and clinical applicability of ML models in future research.
Morocco, like many low and middle-income countries, is undergoing a rapid nutritional transition marked by the concurrent persistence of stunting and the emergence of overweight and obesity, a phenomenon known as the double burden of malnutrition (DBM). Dairy products are recognized as nutrient-dense foods that support linear growth through their role in insulin-like growth factor-1 (IGF-1) stimulation; however, dairy intake patterns and their relationship with nutritional status among Moroccan schoolchildren remain poorly documented, particularly across urban-peri-urban gradients. This cross-sectional study was conducted as part of the SUPREM-MILK project, Work Package 1 (WP1). A total of 248 schoolchildren aged 7-14 years enrolled in pilot public primary schools located in urban and peri-urban public primary schools in Kenitra province, northwestern Morocco (January-June 2025). Dairy product consumption frequency was assessed using a Food Frequency Questionnaire (FFQ). Nutritional status was evaluated through anthropometric measurements, including height-for-age Z-scores (HAZ), BMI-for-age Z-scores (BAZ), and waist-to-height ratio (WHtR). Liquid milk was the most frequently consumed dairy product among the children surveyed (33.9% reported high consumption; 56.5% moderate), while traditional dairy products such as Lben and Jben were consumed less frequently. Taste preference was the dominant motivation for dairy intake across both residential settings. Urban children showed significantly higher HAZ (0.19 ± 1.23 vs. -0.43 ± 0.96; p < 0.001) and BAZ (0.51 ± 1.14 vs. 0.01 ± 0.97; p < 0.001) than peri-urban peers, yet abdominal obesity was markedly more prevalent in urban areas (16.8% vs. 2.4%; p < 0.001). Household income (p = 0.006) and parental education (p < 0.01) were significant determinants of linear growth. After full covariate adjustment, no independent association was detected between dairy consumption frequency and the risk of overweight, stunting, or abdominal obesity (all p > 0.05). These findings indicate a context-specific nutritional transition in which urbanization is associated with improved linear growth but a higher risk of abdominal obesity. The absence of an independent association between dairy consumption frequency and nutritional outcomes after full covariate adjustment reflects the complexity of the diet growth relationship in this context. Differentiated public health strategies are therefore needed: promoting balanced diets in urban settings and improving dietary diversity in peri-urban areas, to address this dual nutritional burden.
This study investigated the effect of a Se-enriched Limosilactobacillus fermentum CGMCC 17434 compound microbial agent synergising with peanut sprouts on the flavor of Se-enriched yogurt. In the synergistic fermentation group, viable counts, titratable acidity, and water-holding capacity reached 8.70 lg CFU/mL, 94.57°T, and 83.82%, respectively. E-noses, e-tongues and rheology indicated that, compared with peanut sprout alone, texture and rheological properties improved, umami and richness enhanced, and astringency and bitterness reduced. Additionally, HS-SPME-GC-MS and GC-IMS indicated that adding peanut sprout enriched anethole and 1-hexanol, imparting grassy, fruity and sweet notes. The compound microbial agent promoted pentanoic acid methyl ester and acetic acid ethyl ester and inhibited off-flavor compounds. Metabolomics revealed that differential metabolites were mainly enriched in TCA cycle and amino acid metabolism pathways, with key metabolites including L-glutamic acid, aspartate, L-arginine, and D-proline significantly upregulated. This study provides a theoretical basis for developing Se-enriched yogurt with excellent flavor.
Aiming at an intelligent point-of-care imaging technology for rheumatology clinics, a fully automatic 3D photoacoustic (PA) and ultrasound (US) dual-modality system driven by a robot and powered by deep learning (DL)-based image processing was developed. Automated scanning of volumetric images from patient joints, plus DL-based tissue segmentation and quantification of imaging biomarkers, ensures that the measurements from this system are objective and reproducible. Clinical validation was conducted via a longitudinal study on 43 finger joints from patients affected by inflammatory arthritis. Using manual segmentations as the gold standard, our DL algorithm utilizing the 3D Deep Attentive Feature (DAF3D) model showed satisfactory performance in automatic segmentation of joint space and synovial region and achieved a Dice score of 0.77±0.03 and an IoU of 0.64±0.03. Based on the tissue segmentations facilitated by the DAF3D model, six volumetric imaging biomarkers reflecting the activity of arthritis and its change in response to the treatment were quantified, including hyperemia, blood oxygenation, US power Doppler, joint space echogenicity, joint space volume, and synovial volume. The imaging biomarkers quantified from DL-based segmentation and manual segmentation showed moderate to strong correlations ( R : 0.41-0.86). Hyperemia quantified from PA imaging has the strongest association with the disease activity indicated by Clinical Assessment Questionnaire (CAQ) scores, with R 2 =0.41. Linear models combining the two biomarkers from PA imaging, the four biomarkers from US imaging, and all six imaging biomarkers rendered moderate to very strong associations with the disease activity scores, with R 2 of 0.41, 0.26, and 0.52, respectively.
Microplastics (MPs) in sewer systems can be transported extensively before entering wastewater treatment plants. Sewer systems harbor complex microbial communities under low-oxygen, sulfide-rich conditions that drive key biogeochemical cycles. These conditions drive microplastic aging, whereas these particles concurrently perturb sewer microbial ecology and metabolic functions. However, the underlying mechanisms of in-sewer microplastic aging and their subsequent impacts on sewer microbiomes remain unclear. Here we show that hydroxyl radicals preferentially attack ester bonds (C-O) in polyethylene terephthalate (PET) and polybutylene adipate terephthalate (PBAT) MPs, increasing surface roughness, reducing particle size, promoting surface oxidation, and ultimately inducing polymer chain scission. Exposure to PET and PBAT MPs at 30-500 particles L-1 intensified oxidative stress, disrupted membrane integrity and permeability, impaired microbial activity, and suppressed sulfide production in a dose-dependent manner. These disruptions coincided with weakened microbial co-occurrence networks and a shift from stochastic toward deterministic community assembly. High doses of PET and PBAT MPs reduced hydrolytic/fermentative bacteria and sulfate-reducing bacteria by up to 63.4% and 49.7%, respectively, while enriching hydrogen-producing acetogenic bacteria and methanogenic archaea by 48.4-67.0%, consistent with reduced sulfidogenic potential and enhanced methanogenic potential. Changes in genes related to antioxidant defense, SOS response, quorum sensing (e.g., sodA, katG, lexA, and luxS), and redox signaling suggested potential mechanisms of microbial metabolic perturbations aggravated by PET and PBAT MPs. Our results indicate that sewer systems are not passive conduits but active reactors that promote MP aging, and that MPs reshape microbial functions. Microplastic control may therefore help reduce downstream particle pollution and limit perturbations to urban sewage biogeochemistry.
Metal chalcohalides are a fascinating new class of crystalline solids with a unique chemical bonding hierarchy which combines the notable stability of metal chalcogenides along with the enhanced electronic tunability of metal halides. Metal chalcohalides with their complex structures are promising candidates for thermoelectrics if they can exhibit halide-like low thermal conductivity alongside chalcogenide-like enhanced electrical conductivity. However, most metal chalcohalides mimic a wide band gap electronic structure similar to metal halides, limiting overall electrical transport and thus reducing their applicability in thermoelectrics. Here, we present a metal chalcohalide, Tl5Te2I, with a narrow band gap and degenerate semiconductor-like significant electrical conductivity. We explore the structural and chemical bonding attributes of Tl5Te2I and demonstrate it to be suitable for low thermal conductivity arising from its complex crystal structure with significant bonding hierarchy. Tl5Te2I, in its octahedral Tl sublattice, exhibits a multicentric bonded structural framework. This bonding feature allows delocalization of electrons, which permits symmetry-allowed three-center antibonding pz-s-pz and px/y-s-px/y interactions of I-Tl-I and Te-Tl-Te, respectively. These antibonding interactions at the top of the valence band near the Fermi level make interatomic force constants extremely soft and reduce the lattice thermal conductivity to the glass limit. With the combined effects of these features, Tl5Te2I exhibits an extraordinarily high p-type thermoelectric figure of merit of ∼1.2 at ∼650 K in its pristine form. Our investigations highlight the role of multicentric antibonding features to realize record-high thermoelectric performance in mixed anionic chalcohalides.
Two-dimensional (2D) materials offer promising platforms for water purification, particularly for challenging oil-in-water emulsions. Here, a hybrid membrane combining graphene oxide (GO) and MXene nanosheets was fabricated on a nylon support to explore the relationship between membrane composition and separation performance. Four membranes with varying GO loadings were evaluated, and machine learning models were applied to predict rejection efficiency using key operational parameters. Among the tested models, support vector regression achieved the highest predictive accuracy (R2 = 0.952 for training, 0.936 for testing, and 0.922 for validation), effectively capturing nonlinear relationships between membrane structure and operating conditions. Feature-importance analyses identified membrane composition and pressure as dominant factors governing performance. This study demonstrates how integrating 2D materials with data-driven modeling can enable predictive design of membrane systems, supporting more efficient development of water purification technologies. Future work will expand datasets and hybrid learning approaches to further enhance predictive robustness and generalization.
Electrically tunable soft lenses are essential for emerging applications in soft robotics, adaptive optics, and minimally invasive biomedical imaging. Among various materials, electroactive hydrogels have emerged as ideal candidates for constructing such lenses due to their tissue-like softness and intrinsic electrical actuation capabilities. However, current hydrogel-based actuators often face a fundamental trade-off between high optical transparency and low-voltage responsiveness due to the uncontrolled aggregation of conductive fillers. Herein, we report a transparent, low-voltage-driven electroactive hydrogel lens based on a polyacrylamide (PAM) matrix incorporated with sodium-functionalized multiwalled carbon nanotubes (Na-MWCNTs). By engineering the interfacial chemistry of the nanotubes with surface carboxylate groups (-COONa), uniform dispersion of nanotubes in PAM via electrostatic repulsion at a low loading (≤0.1 mg mL-1) was achieved. Consequently, this well-dispersed state preserves high visible-light transmittance, while the incorporation of Na-functionalized MWCNTs modulates the overall charge transport behavior within the hydrogel matrix, facilitating rapid charge redistribution. Under a 30 V stimulus, the focal length of the hydrogel lens can be tuned from 73.6 mm to 53.7 mm, achieving a 27% tunability. Mechanistically, this focal tuning is realized through the asymmetric modulation of surface curvature, driven by an electric-field-induced osmotic pressure gradient. Ultimately, this PAM/Na-MWCNT hydrogel platform offers a versatile solution for next-generation adaptive biomimetic optical devices, endoscopic probes, and soft robotic vision.
Chromatin-modifying enzymes (CMEs) have traditionally been studied in their nuclear context for regulating gene expression. However, recent evidence points to the significant non-canonical functions that they perform in the cytoplasm, mitochondria, and plasma membrane, which can contribute to disease progression and alter cell phenotypes. This review surveys emerging engineering approaches to control protein localization, which could be applied to CMEs, particularly histone-modifying enzymes. Natural regulatory mechanisms include nuclear import/export signals and mechanical force-mediated translocation. Engineering strategies encompass diverse approaches: synthetic localization signals for directional transport, RNA editing systems like SNAP-ADAR, and small molecule platforms including bifunctional compounds, self-localizing ligands, and nanobody-mediated translocation. Optogenetic tools provide spatiotemporal control through light-inducible trapping, while inducible condensates enable reversible protein sequestration. Additional tools provide extra control via protease-based cleavage mechanisms and endogenous secondary messenger coupling. Despite significant advances in protein relocalization technologies, their application to CMEs remains largely unexplored, which would allow us to decode mechanisms of disease and develop targeted therapeutic interventions for those diseases. Future applications of these tools to CMEs will elucidate our understanding of epigenetic regulation and expand how we conceptualize CMEs.
Liver diseases remain a major global contributor to disability-adjusted life years (DALYs). Using Global Burden of Disease 2021 data, we applied a three-tier framework linking total liver diseases to acute hepatitis, cirrhosis, liver cancer, and their main etiologies. In 2021, liver diseases caused 309.72 million new cases, 1.98 million deaths, and 63.53 million DALYs worldwide. Although global age-standardized rates declined, death and DALY rates increased in High-income North America and Australasia, with steatosis- and alcohol-related liver diseases accounting for a growing share of the burden. Independent datasets, including the World Health Organization and Global Cancer Observatory sources, supported these regional patterns. Disease burden showed marked age, sex, and etiological disparities, with metabolic factors rising rapidly. Although overall mortality is projected to decline, liver cancer due to steatohepatitis and hepatoblastoma is projected to rise. These findings highlight persistent regional, demographic, and etiological disparities and the need for targeted public health action.
Kombucha production has increased significantly in recent years, and analog beverages (fermented with extracts other than C. sinensis tea) are also gaining market share. Brazil, one of the largest fruit-producing countries with vast fruit diversity, has expanded their research fields to develop new products, including kombucha. This literature review aims to present studies being conducted in Brazil on the production of traditional kombucha (with green or black tea) and analog extracts. Based on the results, it was observed that a large part of the analog beverage production is carried out with fruits mainly from the Northeast and South regions of Brazil. However, it is also done with other types of extracts, such as coffee, yerba mate, and yams. In addition, some studies have used byproducts from cocoa (Theobroma cacao), acerola, guava, tamarind, as well as mango and grape peel. It was also observed that during fermentation, regardless of the type of extract, both total phenolic compounds and antioxidant activity tend to increase. Although regulations for kombucha production in Brazil have already been established, some challenges remain regarding the use of tea and SCOBY, demystifying probiotic effects (since this is not yet regulated), uncontrolled ethanol production, and the need for specific legislation for secondary fermentation. Overall, Brazil shows great potential for developing new products, such as kombucha-type beverages, where the fermentation process is similar to that of traditional kombucha; however, regulating the process using alternative extracts and SCOBY (which may present a consortium of different microorganisms according to regions) remains a challenge for achieving homogeneous, feasible results.
Inspired by the friction-reducing structure of pangolin scales, biomimetic conical textures were designed on bearing roller-raceway surfaces to improve tribological performance and service life. Computational fluid dynamics (CFD) based on hydrodynamic lubrication and cavitation theory was used to simulate the effects of cavitation, inflow direction, and texture parameters (depth, area ratio, and angle) on oil film load capacity. Femtosecond laser fabrication and oil-lubricated friction tests were conducted for validation. The results demonstrate that the load-carrying capacity of the oil film is significantly improved under cavitation conditions. An increased textured area fraction reduces the coefficient of friction, and improves the wear resistance of the contact pairs, whereas an increased texture orientation angle leads to deteriorated lubrication performance. This study provides an effective strategy for optimizing the lubrication of rolling bearing contact pairs and extending bearing service life.
Some drugs undergo gelation during the formulation development process, which not only poses significant challenges to the manufacturing process of solid dosage forms but also significantly restricts the drug dissolution and absorption. Could such gelation be utilized by designing the prescription to overcome the adverse effects and water solubility defect of drugs? Herein, this study attempted to design the self-gelation tablets of indomethacin (IND) by introducing small-molecule ligands and to explore the self-gelation mechanism. As a result, the designed tablets occurred to have spontaneous gelation with a typical 3D structure and viscoelasticity upon contact with a small amount of water, accompanied by amorphization transformation. Such a self-gelation behavior was significantly influenced by the composition ratios, storage temperatures, and medium pH values. In comparison to pure IND tablet, the designed IND-ligand tablets performed significantly increased apparent solubility (>200-fold) and intrinsic dissolution rate (>6000-fold) and maintained the long-term supersaturated dissolution with acid-base interactions, which was revealed by nucleation inhibition, fluorescence quenching, and phase solubility tests. Moreover, the self-gelled tablets significantly enhanced the membrane permeability of IND, demonstrating the potential for promoting oral absorption. Thus, this study revealed the self-gelation mechanism of the tablet combination and confirmed such prescription design involving self-gelation as an efficient solubilization strategy.
Phyllanthus fraternus G.L. Webster is an important medicinal plant known for its hepatoprotective activity since ancient times. Our previous study resulted in the identification of hepatoprotective lead compounds through in-silico approach from the aqueous extract of P. fraternus leaves. This finding instigated us to know the potential of identified lead compounds against the fatal liver disease hepatocellular carcinoma (HCC). In the present study, hinokitiol identified from Phyllanthus fraternus has been subjected to a network pharmacology-based study to know the possible targets of HCC and elucidate their mechanism of action. The protein-protein interaction analysis of the target genes of HCC and hinokitiol resulted in the identification of the five hub genes AKT1, EGFR, CASP3, TNF and SRC. These genes exhibited the best docking scores with hinokitiol, demonstrating strong binding affinities: AKT1 (- 6.3), EGFR (- 6.8), CASP3 (- 4.5), TNF (- 4.4), and SRC (- 6.0), which were further validated by molecular dynamics simulations that provided insights into the stability and flexibility of the protein-ligand complexes. The hub genes analysis predicts the involvement of two genes, AKT1, and EGFR, in HCC through MAPK, PI3K-Akt, and calcium signaling pathways. Although three other hub genes CASP3, TNF and SRC could also play a role in developing HCC by prognosis of Hepatitis B, and C and apoptosis. This finding was further validated by the Gepia2 and human protein atlas, confirming the usefulness of hinokitiol against HCC. The online version contains supplementary material available at 10.1007/s40203-026-00698-1.
Calf diarrhea is a common and severe disease in the livestock industry, leading to poor growth and high mortality rates in calves, thereby causing significant economic losses. With increasing concerns over antibiotic resistance, traditional Chinese medicine (TCM) and natural products have garnered widespread attention as alternative therapeutic options for managing calf diarrhea. This review systematically summarizes recent advances in the utilization of TCM, natural products, and plant extracts for the prevention and treatment of calf diarrhea. The mechanisms underlying their antibacterial, anti-inflammatory, immunomodulatory, and intestinal protective effects are critically analyzed in this review. Additionally, the safety profiles and potential applications of these natural agents are evaluated to provide a comprehensive understanding of their roles in the control of diseases. By integrating the latest research findings, this review aims to offer theoretical support and practical guidance for the green and sustainable prevention and control of calf diarrhea, addressing the urgent need for effective, safe, and environmentally friendly therapeutic strategies in modern animal husbandry.
Metal-organic frameworks (MOFs) with intrinsic dual proton-electron conductivity are highly desirable for energy conversion devices and chemical separation, yet merging these properties within a single crystalline phase remains a challenge. Here, we report two novel Mn(II)-based conjugated MOFs that share similar building blocks, but diverge into distinct topologies: a kagome lattice (kgm) and an unprecedented pseudo bex-d topology (Mn-HHTP-bex-d). These frameworks exhibit sharply contrasting conduction profile: Mn-HHTP-kgm demonstrates excellent electronic conductivity (8.4 × 10-1 S cm-1 at room temperature), but limited proton transport (3.6 × 10-7 S cm-1) at 98% relative humidity (RH), whereas the pseudo bex-d topology exhibits more balanced electronic conductivity (2.4 × 10-5 S cm-1) and proton conductivity (4.5 × 10-5 S cm-1 at 98% RH). Crystallographic and computational studies indicate that the efficient π-π stacking in kgm topology promotes charge delocalization and through-space charge transport for electrical conduction, while the pseudo bex-d topology leverages framework-incorporated water molecules and acetate moieties to establish efficient hydrogen-bonding networks for proton transport. This work highlights the critical role of topological control in modulating mixed-conduction properties and offers valuable insights for designing multifunctional MOFs for ambipolar devices, bioelectronics, and energy systems.
Depression is commonly accompanied by sleep disturbances and low self-esteem. Saffron (Crocus sativus L.) has demonstrated antidepressant and sleep-enhancing effects in previous clinical trials; however, its efficacy in women experiencing both low mood and poor sleep has not been specifically examined. Furthermore, the effects of saffron on self-esteem and skin health remain largely unexplored. To examine the effects of supplementation with a saffron extract (Affron®) on mood, sleep, self-esteem, and skin health in women aged 50-70 years experiencing low mood and self-reported poor sleep. In this randomised, double-blind, placebo-controlled trial, 86 women were allocated in a 1:1 ratio to receive either 28 mg/day of a saffron extract or placebo for 12 weeks. The primary outcome was the Depression, Anxiety and Stress Scale-21 (DASS-21) depression subscale. Secondary outcomes included the PROMIS Sleep Disturbance and Sleep-Related Impairment scales, the Rosenberg Self-Esteem Scale, a self-report measure of physical appearance, and facial skin age estimated using an artificial intelligence-based application. Compared with placebo, saffron resulted in greater reductions in DASS-21 depression scores (adjusted mean difference: 2.37; 95% CI: 0.23, 4.51; d = 0.48, p = 0.030). A clinically meaningful improvement in depressive symptoms (≥7-point reduction) was achieved by 48.8% of participants receiving saffron compared with 25.6% receiving placebo (p = 0.026). Saffron was also associated with greater improvements in self-esteem (adjusted mean difference: 1.43; 95% CI: 0.22, 2.64; d = 0.51; p = 0.022) and sleep-related impairment (adjusted mean difference: 2.99; 95% CI: 0.12, 5.86; d = 0.45; p = 0.041). No significant between-group differences were observed for sleep disturbance (p = 0.786), self-rated physical appearance (p = 0.964), or estimated facial skin age (p = 0.473). Saffron was well tolerated, with no serious adverse events reported. Supplementation with a saffron extract (Affron®) for 12 weeks was associated with improvements in depressive symptoms. Improvements were also observed in self-esteem and sleep-related impairment; however, these secondary findings should be considered exploratory and require confirmation in adequately powered studies. No significant group differences were observed for sleep disturbance, perceived physical appearance, or estimated facial skin age. https://anzctr.org.au/ACTRN12625000638437p.aspx, ACTRN (registration number): ACTRN12625000638437p.
Sodium-sulfur (Na-S) batteries have become a major focus of research because they can supply large amounts of energy at a minimal cost, depending on the natural abundance of sodium and sulfur. Despite these benefits, their widespread application remains limited because of several persistent issues, particularly brought on by the significant capacity loss caused by the dissolution of sodium polysulfides (NaPs) and the intrinsically sluggish reaction kinetics connected to their electrochemical conversion. In this work, we systematically analyzed the impact of vacancy-induced modifications in hexagonal boron nitride (h-BN) that enhance its catalytic performance and its ability to anchor sulfur species. Density functional theory calculations indicate that pristine h-BN interacts weakly with NaPs. On the other hand, introducing vacancies significantly enhances the interaction strength. Single nitrogen and single boron vacancies substantially boost the adsorption, and even stronger binding is attained when double nitrogen or double boron vacancies are created, thus lowering the polysulfide shuttle. The promise of vacancy-engineered h-BN as an efficient anchoring material is further demonstrated by the polysulfides' stronger binding to vacancy-engineered sheets compared to electrolyte molecules. The density of state calculations demonstrate that the h-BN lattice's electrical characteristics are much improved by the creation of vacancies, changing it from an insulating material to one with semiconducting or even semimetallic behavior. Overall, our results provide fundamental insights and demonstrate that vacancy-engineered h-BN is an excellent host material for reducing the shuttle effect in Na-S batteries because of its favorable electronic properties, structural robustness, and strong affinity for NaPs species.
Amphiregulin (AREG) is an EGF-like ligand that binds EGFR to activate signaling pathways governing cellular proliferation, differentiation, tissue repair, and immune responses. This review integrates AREG's structural characteristics and signaling mechanisms with its biological functions derived from cell-based and animal models. We critically evaluate AREG's mechanistic involvement in cardiovascular, respiratory, intestinal, neoplastic, and infectious diseases, highlighting its dual roles in tissue protection and pathogenesis. The broader significance lies in discussing AREG's translational potential and associated therapeutic challenges for these diseases.