Browse Articles

Physical-chemical gradients, CO2 venting dynamics and microbial community composition in a shallow Mediterranean CO2-rich hydrothermal system

Abstract Shallow-water CO 2 -rich hydrothermal systems provide natural laboratories for studying localized ocean acidification under realistic environmental conditions. Here, we present a multidisciplinary characterization of the Calent mound CO 2 -rich system (Columbretes Islands, Western Mediterranean), based on oceanographic surveys conducted in 2020 and 2021. Localized pH anomalies were detected directly above active vents, reaching maximum reductions of 1.12 pH units, whereas water-column temperature anomalies were minimal and subsurface sediment temperatures exceeded ambient seawater by 5.67 °C. Gas analyses indicated high CO 2 concentrations (0.094 ± 0.008 mol L − 1 ), with heterogeneous degassing regimes, ranging from sporadic to continuous emissions and an average flux of 189.4 ± 15.4 kg CO 2 m − 2 yr − 1 at the active vent field. Vent fluids were significantly enriched in dissolved inorganic nutrients, particularly silicate, phosphate, nitrate+nitrite, and ammonium. Benthic microbial mats hosted metabolically diverse prokaryotic and eukaryotic communities, including hydrothermal-associated taxa such as Zetaproteobacteria, Campylobacterota, and Nitrosophaeria, consistent with iron, sulfur, and ammonia oxididation metabolisms. Several microbial core taxa persisted across years despite shifts in relative abundance. These findings demonstrate that Calent mound sustains an intense yet highly localized biogeochemical environment within the photic zone, where CO 2 venting and nutrient inputs jointly influence carbonate chemistry and microbial community structure.

CO ₂ ‐Derived Degradable Polythioester Adhesives From Proton‐Trap‐Assisted S/O Isomerization‐Driven Cationic Ring‐Opening Polymerization

ABSTRACT The development of degradable pressure‐sensitive adhesives (PSAs) holds great promise for enabling the recycling of adhesive‐containing materials. However, existing degradable PSAs are often constrained by insufficient or moderate adhesion strength, reliance on fossil‐based feedstocks, and/or incomplete degradation. Addressing these challenges requires the development of new polymerization strategies and material designs. Herein, we report a proton‐trap‐assisted S/O isomerization‐driven cationic ring‐opening polymerization of the CO 2 ‐derived thionolactone 3,6‐diethyltetrahydro‐2H‐pyran‐2‐thione, which enables the well‐controlled synthesis of high‐molecular‐weight CO 2 ‐based (co)polythioesters. The resulting materials exhibit a unique combination of high and tunable peel strength (up to 16.43 N/cm), excellent optical clarity (over 96% transmittance, low haze and low yellowness index), and the ability to undergo either complete degradation or quantitative depolymerization under mild conditions, delivering the first practical example of polythioester‐based PSAs. This study establishes a sustainable platform for PSA design that integrates robust performance with full life‐cycle management, thereby advancing the utilization of CO 2 ‐derived materials and circular polymer design.

Micronutrient intake and food insecurity among mothers of infants with orofacial clefts: a cross-sectional study in Iran

Unlocking an All‐Anisotropic‐Component Integrated Paradigm Toward Practical Solid‐State Zinc Metal Pouch Cells

ABSTRACT High‐safety and low‐cost Zn metal batteries hold great promise for energy storage, but their limited energy density remains a major bottleneck restricting their practical development. Here, an all‐anisotropic‐component integrated model with full high‐flux characteristic is presented for enabling high‐specific‐energy devices. By utilizing natural and recyclable wood‐based materials, we validate its feasibility in classic Zn–MnO 2 single‐electron reaction system. Among them, lightweight and carbonized wood material was used to serves as a universal current collector for both MnO 2 cathode and Zn anode. Simultaneously, a phosphate‐modified cellulose‐based hydrogel with vertically aligned channels was fabricated to achieve high electrochemical compatibility between electrode and electrolyte interfaces. As a result, this configuration enables the stable cycling of Zn||Ca‐MnO 2 pouch cells at high mass loading (even up to 50.13 mg cm −2 ), with a wide‐temperature operability (−30°C to 60°C). Impressively, a maximum energy density of 173.2 Wh kg −1 is achieved at the current density of 0.1 A g −1 , exceeding the vast majority of previous findings. Such battery structure model can be applied to both vanadium‐ and manganese‐based cathodes, but also expected to other multielectron reaction systems, promoting the fast development of economical nonlithium energy storage batteries.

Deep learning model for real time moisture content detection and prediction in white tea withering using near infrared spectroscopy

Synergistic Interaction Between N‐Heterocyclic Carbene (NHC)‐Anchored Cu(I) Atom and In Situ‐Generated Cu Nanoparticles in a Post‐Modified MOF‐808 Framework Promoting C─C Coupling in CO ₂ Reduction

ABSTRACT The electrochemical reduction of CO 2 to high‐value chemicals like C 2 H 4 represents a promising route for sustainable energy and CO 2 mitigation. However, its efficiency remains constrained by the high energy barrier for C─C bond formation and the competing hydrogen evolution reaction (HER). Herein, we report a synergistic catalyst for electrochemical CO 2 reduction reaction (eCO 2 RR), which comprises an N‐heterocyclic carbene (NHC)‐anchored Cu(I) atom and in situ electrogenerated Cu nanoparticles in a MOF‐808 framework. The catalyst exhibits outstanding performance in a neutral electrolyte, achieving a high Faradaic efficiency (FE) of 61.0% for C 2 H 4 and 79.5% for total C 2+ products. Experimental and theoretical studies reveal a dual role of the NHC ligand in eCO 2 RR: (i) promoting proton transfer and *CO hydrogenation via a robust hydrogen‐bonding network with interfacial water and (ii) stabilizing key intermediates such as *CHO and *COCHO through its strong electron‐donating ability. The synergy between a molecular NHC‐Cu(I) atom and adjacent Cu nanoparticles in a tailored microenvironment suppresses HER and lowers the energy barrier for asymmetric C─C coupling. This work offers a strategic design concept for constructing molecular‐nanostructured synergistic active sites in metal‐organic frameworks (MOFs) to advance electrocatalytic CO 2 conversion.

Development of surfactin-based nanocarrier for targeted doxorubicin delivery

Abstract Surfactin, one of the most powerful lipopeptide biosurfactants produced by Bacillus subtilis, has great potential for biomedical applications. Isolation, purification, and characterization of surfactin from Bacillus subtilis 6633 to be used as a doxorubicin (Dox) nanocarrier. Purified surfactin using different chromatographic columns was used to prepare a self-assembled nanocarrier for Dox, which was characterized for size, charge, and drug-loading efficiency. Biological activity against normal fibroblast (FB) and liver cancer (HepG2) cells was assessed. The hybrid nanoparticles showed a remarkable drug loading; 36%, a pH-responsive release profile with enhanced cytotoxicity toward HepG2 cells (IC₅₀ = 5.40 µg/mL), and a reduced toxicity to FB cells (IC₅₀ = 12.78 µg/mL). The nanoparticles were spherical in shape (100 ± 2 nm) with a polydisperse index of (0.019 ± 0.01) and a narrow size distribution pattern. The results support the potential of surfactin-based nanoparticles to act as a selective platform for anticancer drug delivery and underscore their relevance towards the Sustainable Development Goal 3 (Good Health and Well-being) through the development of safer and effective therapeutic strategies.

Charge‐Directed Photothermal Methane Dry Reforming Enabled by Interfacial TiO <i> _x </i> Nanodomains

ABSTRACT Photothermal dry reforming of methane (DRM) enables solar‐driven upgrading of CH 4 and CO 2 , yet its efficiency and durability are hindered by carbon deposition and poorly defined photochemical contributions. Here, we demonstrate a charge‐directed photothermal DRM catalyst composed of Rh nanoparticles supported on TiO x ‐functionalized TiC, where interfacial TiO x domains play a critical role by coupling directional photocarrier flow with adaptive oxygen chemistry. Upon illumination, metallic TiC generates charge carriers that transfer electrons to Rh sites while steering holes to TiO x surface oxygens. This charge‐directed interfacial chemistry selectively lowers the barrier for *OCH 3 formation, the potential‐determining step, thus suppressing *CH 3 over‐dehydrogenation and mitigating carbon formation. Concurrently, CO 2 activation at oxygen vacancies within TiO x regions restocks surface oxygens, closing a regenerative photothermal Mars–van Krevelen cycle. As a result, the catalyst delivers high syngas production rates (CO: 17.5 mol g Rh −1 h −1 , H 2 : 10.5 mol g Rh −1 h −1 ), attains a light‐to‐chemical energy efficiency of 29%, and operates stably for over 100 h without coking. This work highlights the mechanistic importance of amorphous TiO x interface in charge‐directed photothermal DRM and provides design insights for developing coking‐resistant reforming catalysts.

A cancelable ear recognition system via optimized deep feature fusion

Abstract The rapid expansion of biometric authentication technologies worldwide has heightened the need for highly reliable and secure identification methods. This research explores the human ear as a distinctive biometric trait, capitalizing on its stable and person-specific anatomical structure. Although ear biometrics offer notable advantages, their practical use is hindered by image variations arising from changes in pose, scale, rotation, illumination, and contrast. To overcome these challenges, this paper presents an innovative deep learning-based ear recognition framework. The proposed approach employs a dual-stream feature extraction strategy that integrates two advanced Convolutional Neural Network (CNN) models MobileNetV3 and DenseNet-121 to derive rich and complementary feature representations, which are subsequently fused. The resulting high-dimensional feature space is then optimized using a Multi-Learning Strategy Golden Eagle Optimization (MLSGEO) algorithm to retain only the most discriminative features. To strengthen security and privacy, the refined feature vector is transformed into a non-invertible, cancelable biometric template using a Comb-filter–based protection mechanism. Data augmentation techniques are further applied to compensate for dataset size limitations. The framework was evaluated on five benchmark ear datasets: AMI, AWE, IITD-I, IITD-II, and UERC, achieving recognition accuracies of 99.90%, 99.64%, 99.78%, 99.32%, and 93.31%, respectively. Experimental findings show that the proposed system outperforms existing state-of-the-art methods. Overall, the integration of robust feature learning with a resilient template protection scheme demonstrates strong potential for secure and high-accuracy biometric authentication applications.

Combined impact of diabetes mellitus and substance use on injury risk: a nationwide population-based cohort study in Taiwan

Predictive Registry Optimization of Molecular Adsorbates on Solid Surfaces

ABSTRACT Understanding and predicting how large organic molecules adsorb on crystalline substrates is essential for designing functional surfaces in electronics, catalysis, and supramolecular chemistry. Standard quantum‐chemical approaches often fail for large π‐conjugated molecules due to size and conformational diversity. We present a physically intuitive, generalizable registry analysis that overcomes this by maximizing the overlap between surface‐oriented hydrogen atoms (“spikes”) and the periodic graphite hexagon centers (“pockets”) in a Monte Carlo‐like approach. Inspired by the alkane‐on‐graphite model, the framework extends to structurally complex architectures to assign adsorption geometries with high resolution, without costly computations. Registry scoring applied to STM data enabled determining the absolute conformation of atropisomers, demonstrating geometric registry as an applicable measure for predicting large‐molecule arrangements on surfaces.

Correlation of NBME pharmacology subject exam performance with medical school internal pharmacology scores and academic metrics

Direct microbiota profiling of apheresis-associated products for microbiological insights in cell therapy

Incorporation of Organic Counter‐Cations Into Poly(Heptazine Imide) Networks for Promoting Proton‐Coupled Electron Transfer During Photocatalytic H ₂ O ₂ Evolution

ABSTRACT Nitrogen based onium ions such as methylammonium (MA + ), formamidinium (FA + ), and tetramethylammonium (TMA + ) were used as counterions in poly(heptazine imide) (PHI) networks via a protonation‐acid base reaction strategy. This creates all organic PHIs. Chemical composition analysis confirmed the successful accommodation of target species, resulting in a maximum incorporation of 1 cation per ideal PHI unit cell. Structural characterization confirmed crystal phase consistency to that of parent Na‐PHI. Photocatalytic H 2 O 2 evolution was chosen as a model reaction. Under ambient conditions, MA + ‐PHI showed the best performance, producing 7.6 mmol g − 1 H 2 O 2 after 1 h of 427 nm LED irradiation, corresponding to an AQY of 13.9% and a 42% activity enhancement over the Na‐PHI analogue. When an additional oxygen pressure of 3 bars is applied, the H 2 O 2 yield increased to 36.5 mmol g − 1 , while AQY increased proportionally to ∼66.8%, being one of highest outputs reported to date. Photochemical and photo‐charging experiments suggest that methylammonium moieties stabilize photoelectrons though coulombic interaction in an effective manner, while proton conductivity and photocatalytic experiments point out toward a PCET driven mechanism responsible for the recorded H 2 O 2 rate enhancements. These results showcase that counterion replacement, as applied in organic perovskites, also improves carbon nitride photosynthesis.

Combining blast resistance and high yield in F1 aromatic rice through classical hybrid breeding

Polyphenol profiling and multi-target antioxidant, anti-inflammatory and antidiabetic activity of Sorbus commixta Hedl. leaves

Abstract Sorbus commixta , a plant from the Rosaceae family, is native to Asia and cultivated in Europe and North America. Here, we evaluated the potential of S. commixta leaves as a source of biologically active compounds, including rare flavanones. The methanol-water extract (ME) and its bioactive polyphenol-enriched fractions were assessed for phytochemical composition, biological activity, and composition-activity relationships. A total of 78 compounds were identified by UHPLC-PDA-ESI-MS/MS, with a content reaching 589 mg/g of dry weight. Among the tested samples, ME and the n -butanol fraction (BF) exhibited the strongest biological effects. Both significantly protected human plasma components against peroxynitrite-induced oxidative and nitrative stress (ex vivo model) and inhibited the release of pro-inflammatory cytokines (IL-1β, IL-2, TNF-α) from stimulated human peripheral blood mononuclear cells in vitro. The BF fraction also demonstrated pronounced antidiabetic activity, showing approximately 17- to 26-fold stronger effects than acarbose and aminoguanidine in inhibiting α-glucosidase and the formation of advanced glycation end products in vitro. Statistical analysis revealed significant correlation of the observed effects with polymeric proanthocyanidins, flavonol diglycosides, caffeoylquinic acids, and monoglycosides of flavonols and flavanones. These findings support further in vivo investigation of S. commixta leaf extracts and highlight the need for their standardised quality control strategies.

Extended Endocyclic Conjugation and <i>N,N</i> ‐Bidentate Chelation Alleviate the Capacity–Stability Trade‐Off in Organic Magnesium Battery Cathodes

ABSTRACT Rechargeable Mg batteries represent an appealing post‐lithium energy‐storage technology, yet their advancement is hampered by the scarcity of cathode materials combining high capacity, rapid kinetics, and long‐term cycling stability. In this study, we propose a molecular design strategy integrating extended endocyclic conjugation with polydentate Mg 2+ coordination. Using hexaazatriphenylene (HATN), a rigid planar macrocycle featuring extensive π‐conjugation and N , N ‐bidentate chelating sites, as the Mg‐storage active center, we constructed polymer cathodes through monothioether and dithioether linkages. Theoretical and experimental analyses reveal that the HATN unit enables high‐capacity, multi‐electron reversible Mg 2+ storage while maintaining structural stability via efficient charge buffering through strong electron delocalization, offering a notable advantage in a “capacity‒delocalization” evaluation framework. The thioether linkage suppresses dissolution and yields high surface area with hierarchical porosity, boosting interfacial kinetics and Mg 2+ transport. The resulting polymer cathode delivers a high capacity of 370 mAh g ‒1 at 0.1 A g ‒1 , superior rate capability (94 mAh g ‒1 at 5.0 A g ‒1 ), and exceptional cycling stability (95% capacity retention over 500 cycles at 1.0 A g ‒1 ). This work presents an innovative molecular‐level design strategy for high‐performance organic Mg‐battery cathodes, advances the mechanistic understanding of multivalent‐ion storage, and provides a new paradigm for rational electrode engineering for multivalent battery systems.

Enrichment of mutated DNA enables ultra-sensitive ctDNA detection in NSCLC using shallow targeted sequencing

A Molecular Trimming Strategy for Hypoxia‐Tolerant Photosensitizers With Enhanced cGAS‐STING Activation

ABSTRACT The development of effective photosensitizers for photo‐immunotherapy is highly desirable yet remains challenging, particularly given the prevailing reliance on π‐conjugation extension in conventional molecular design. Herein, we propose a counterintuitive “π‐bridge trimming” strategy to construct high‐performance Ir(III) complexes photosensitizers. Unlike the conventional π‐extension approach, the three‐ring fused TTz‐Ir outperforms its π‐extended five‐ring fused analog TBTz‐Ir in multiple aspects, including molar absorptivity, solubility, photocatalytic activity, and photocytotoxicity. Mechanistic studies revealed that the superior performance of TTz‐Ir stems from its longer triplet‐state lifetime, more efficient charge separation, and transport favoring type I reactive oxygen species (ROS) generation. Upon light irradiation, TTz‐Ir not only produces 1 O 2 via energy transfer, but also efficiently generates type I ROS such as O 2 •− , H 2 O 2 , and •OH, primarily through oxygen reduction reaction (ORR) and water oxidation reaction (WOR) pathways, ensuring robust photocytotoxicity even under hypoxia. These ROS induces mitochondrial and nuclear DNA damage, leading to activation of the cGAS‐STING pathway and robust antitumor immunity. When encapsulated into DSPE‐PEG 2000 ‐Biotin, TTz‐Ir NPs achieve effective tumor accumulation and significant tumor suppression in vivo. This work provides a novel molecular design paradigm and efficient metal complexes for photo‐immunotherapy.

FusionDiff: a dual-path diffusion-based framework for few-shot authenticity analysis of ceramic microstructures

Abstract The authenticity of ceramic components is closely tied to their microscopic structures, making automatic and accurate identification essential for quality control. However, this task is often constrained by the scarcity of labeled samples. This study investigates the potential of large-scale pretrained diffusion models as feature extractors, leveraging the rich visual priors embedded in their generative processes to provide a robust semantic foundation for small-sample learning. To address the limitations of the original U-Net in global representation modeling and the weak local-detail sensitivity of DeiT, we propose a dual-path fusion encoder, FusionDiff. Within a frozen Stable Diffusion V1.4 framework, CNN and adapter-enhanced DeiT paths operate in parallel and are deeply integrated via feature gating. Following a “self-supervised pretraining + supervised fine-tuning” paradigm, classification is performed using a Random Forest classifier. On our custom ceramic dataset, FusionDiff achieves a test accuracy of 99.07%, outperforming SD-CNN (97.44%), DeiT (96.30%), and ResNet50 (97.00%) under a unified self-supervised evaluation protocol. Even under extremely small-sample conditions ( $$n = 50$$ ), the model attains 90.7% validation accuracy, demonstrating competitive data efficiency and cross-domain generalization capability.