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Background Family medicine plays a central role in strengthening primary healthcare systems and addressing evolving population health needs, particularly in regions undergoing rapid healthcare transformation. Over the past 15 years, the Emirates Health Services (EHS) Family Medicine Residency Program in the United Arab Emirates (UAE) has aimed to develop a competent family medicine workforce capable of delivering comprehensive, community-oriented, and patient-centered care. Methods This sequential mixed-methods study evaluated the evolution and perceived educational outcomes of the EHS Family Medicine Residency Program between 2009 and 2025. Quantitative data were collected using a structured survey administered to program alumni and current fourth-year residents (R4), while qualitative data were obtained through focus group discussions with residents, alumni, and faculty members. Quantitative analyses included descriptive statistics, non-parametric subgroup comparisons, and Spearman correlation analyses. Qualitative data were analyzed using inductive thematic analysis. Findings were integrated during interpretation. Results Of 71 eligible participants, 64 completed the survey (response rate: 90.1%), including 56 alumni and eight current R4 residents. Overall satisfaction with the residency program was high, with a median satisfaction score of 4.55/5.00. Faculty teaching, supervision, and academic day activities received the highest ratings, whereas hospital-based training and work-life balance demonstrated comparatively greater variability. Median perceived competency and preparedness scores were 4.36/5.00 and 4.37/5.00, respectively. Satisfaction demonstrated moderate positive correlations with perceived competency (Spearman ρ = 0.60, p < 0.0001) and preparedness for independent practice (ρ = 0.64, p < 0.0001). Outcome scores differed across post-residency duration groups, with alumni more than 10 years post-residency reporting the highest satisfaction, perceived competency, and preparedness scores. Qualitative findings suggested substantial program evolution toward a more structured, learner-centered, and competency-oriented training model, with strengths in academic-clinical integration, supervision, assessment systems, ambulatory learning, and resident professional development. Persistent challenges included workload pressures, administrative burden, and variability in hospital-based supervision. Conclusion Over the past 15 years, the EHS Family Medicine Residency Program has undergone substantial development toward a more structured and competency-oriented training model. Participants generally perceived the program positively in relation to supervision, educational experiences, preparedness for independent practice, and professional development. Ongoing operational and workload-related challenges warrant continued program refinement and longitudinal evaluation.
The subtribe Asterinae (Asteraceae: Astereae) comprises ∼300 species across 13 genera (including the well-known type genus Aster) with considerable horticultural and ecological importance. The pappus, a key character for dispersal and protection, is highly diverse and taxonomically important in Asterinae. However, the phylogenetic relationships within Asterinae and Aster remain poorly resolved, leading to persistent taxonomic controversies and obscuring the evolutionary history of the pappus morphology. We reconstructed both plastid (using five newly developed markers) and nuclear (using 130,503 SNPs generated from ddRADseq) trees, based on a comprehensive sampling of 119 species representing all 13 genera of Asterinae and allied subtribes. Using these newly obtained trees, we inferred the evolutionary trajectories of pappus morphology across Asterinae. Both plastid and nuclear SNP trees resolved relationships within Asterinae with strong support. The previously defined Asterinae and Aster were revealed to be polyphyletic, splitting into four (plastid tree) or seven (nuclear SNP tree) clades, respectively. Both trees strongly supported a large clade containing most genera and species of the previously circumscribed Asterinae. Within this large clade, four consistent and highly supported subclades were recovered, while three additional clades were resolved outside of it. Incongruent placements of several taxa between the two trees were detected. Ancestral state reconstruction revealed extensive homoplasy in pappus evolution, undermining taxonomic reliability of the pappus morphology. We redefine Asterinae to include only its core clade and recognize a single monophyletic Aster. This revised taxonomy of Asterinae consolidates 16 former genera of Astereae. Additionally, we propose one new subtribe (Chlamyditinae) and four subgenera within Aster-three of which are novel. This framework clarifies the taxonomy of Asterinae and Aster and lays the groundwork for future studies on the evolution of pappus and other characters that may drive the rise of its remarkable species diversity.
The advent of single-cell RNA sequencing (scRNA-seq) has fundamentally transformed biological research, converting our understanding of cellular diversity from a purely conceptual idea into a quantifiable, applicable, and observable reality. Early efforts successfully created catalogs of cell types across diverse tissues and species, delivering an effective inventory of the components that make up complex animal systems. Yet the field now stands at a crossroads; rather than bringing clarity, the ever-growing number of cellular atlases threatens to flood and overwhelm it. In this review, we argue that the next evolution of scRNA-seq must integrate three essential pillars: temporal dynamics, spatial information, and evolutionary conservation. We have entered the era of predictive biology, moving beyond simple inventories to build dynamic, multispecies, spatially resolved comparative meta-atlases. This new approach seeks not only to understand the fundamental processes of development, physiology, and disease but also to predict cellular behaviors and their evolutionary trajectories, ultimately achieving a mechanistic understanding of life's complexity.
Despite intensive vaccination efforts, Chicken Infectious Anemia Virus (CIAV) remains a formidable threat to the Egyptian poultry industry, primarily through the emergence of vaccine-escape variants. While most studies have focused on Northern Egypt, there is a critical knowledge gap regarding the viral landscape in the Southern provinces. This study provides the most extensive surveillance to date, spanning 10 diverse Egyptian governorates with a strategic focus on Upper Egypt (2024-2025). Out of 400 collected samples, TaqMan-based qPCR revealed a high prevalence of 30% (120/400). Five representative isolates were selected for whole-genome sequencing and molecular characterization. The isolates were classified as Genotype II by phylogenetic analysis, showing a notable genetic divergence (85-87% amino acid similarity) from traditional Genotype I vaccine strains. Notably, comprehensive recombination analysis identified isolate PX96998 as a mosaic variant, with breakpoints indicating intra-genotypic recombination between closely related genotype II lineages, highlighting complex evolutionary dynamics in the field. Furthermore, 3D homology modeling of the VP1 protein identified critical structural alterations in functional loop regions, potentially hindering the binding affinity of neutralizing antibodies and facilitating immune evasion. In an experimental setting, the genotype II isolate demonstrated hypervirulence in SPF chickens, causing severe development retardation and extensive atrophy of lymphoid organs (p < 0.0001). Pathognomonic pale, fatty bone marrow with a sharp drop in PCV% to 18 ± 0.58% indicated severe aplastic anemia. By the fifth week after infection, there was a complete humoral collapse with undetectable ELISA titers due to the huge systemic replication revealed by viral load measurement, which peaked in the thymus (9.50 ± 0.25 log₁₀) and bone marrow (9.00 ± 0.22 log₁₀). These results were supported by histopathology, which revealed intranuclear inclusion bodies and systemic lymphocyte depletion. These findings support the highly pathogenic genotype II CIAV's dominance and aggressive evolution in Egypt. The emergence of recombinant variants with altered structural epitopes underscores the urgent need to replace outdated vaccination plans with genotype-matched immunogens in order to lessen the severe consequences on Egypt's poultry industry.
In enzyme evolution, structural divergence varies among residues, forming residue-dependent structural divergence profiles. The evolutionary constraints that determine these profiles remain unclear. We build on the mutation-stability-activity (MSA) model, a mechanistic mutation-selection model previously developed for sequence evolution. In the MSA model, mutations become fixed or are lost depending on their effects on stability and activity, with parameters aS and aA controlling selection on stability and activity, respectively. The Linearly Forced Elastic Network Model (LFENM) is used to calculate mutational effects on structure, stability, and activity. As substitutions accumulate, structural changes build up unevenly across residues, producing a structural divergence profile that depends on how each residue responds to mutation and on how strongly selection acts on stability and activity. Applied to 34 enzyme families, the MSA model recapitulates observed structural divergence profiles, and nested model comparisons show that mutation, stability, and activity constraints each contribute. However, the balance among these constraints varies widely across families: mutation always contributes substantially, but stability and activity contributions range from negligible to dominant, so any of the three can prevail in a given family. These variations have distinct origins: the mutation contribution depends on how unevenly the protein's flexibility is distributed across residues, while the stability and activity contributions depend on how strongly selection acts, as quantified by aS and aA. The MSA model thus recovers family-specific selection strengths from structural divergence profiles, suggesting these profiles encode information not only about enzyme architecture but also about the selective regime under which enzymes evolve.
Oral mucosal lesions (OMLs) comprise a diverse group of diseases affecting the oral mucosal tissues. Traditional treatments such as medication, surgery, laser therapy, and cryotherapy often produce significant side effects, including high recurrence rates due to drug resistance-associated recurrence and considerable tissue trauma, leading to unsatisfactory clinical outcomes. Photodynamic therapy (PDT), which uses photosensitizers, light at specific wavelengths, and oxygen to generate cytotoxic effects that induce cell apoptosis and necrosis, cause immunogenic cell death and microcirculation damage, and trigger local immune responses, has emerged as a promising minimally invasive alternative. PDT offers advantages including strong selectivity, minimal invasiveness, high targeting capability, and repeatable administration. However, clinical translation remains constrained by pharmacological barriers including restricted tissue penetration depth of therapeutic light, absence of standardized treatment protocols, and insufficient long-term efficacy data. This comprehensive review systematically examines the evolutionary development of photosensitizer generations, explores synergistic combination strategies integrating PDT with complementary therapeutic modalities, and critically evaluates current clinical applications across common OMLs types. By synthesizing current evidence and identifying knowledge gaps regarding drug-target interactions, this review aims to provide a robust foundation for advancing therapeutic agent development and guiding future research directions in PDT-based management of OMLs.
Laurdan (6-dodecanoyl-2-(dimethylamino)-naphthalene) is a solvatochromic fluorescent probe widely used for investigating membrane biophysical properties. Since its first application in phospholipid bilayers, laurdan has become a valuable tool in in this field, owing to its sensitivity to the mobility and dynamics of surrounding lipid carbonyl groups and its ability to report on membrane phase behavior through the generalized polarization (GP) parameter. GP, a ratiometric empirical parameter, is derived from the ratio of emission intensities at approximately 440 and 490 nm, providing a measure of membrane fluidity ranging from rigid gel phases to more hydrated liquid-crystalline states. This review outlines the spectroscopic evolution of laurdan applications, beginning with steady-state fluorescence measurements in model membranes and progressing through more modern methodologies including anisotropy measurements, two-photon excitation microscopy, fluorescence correlation spectroscopy, and spectral phasor analysis. Key developments in laurdan's application to biological systems are discussed, including investigations of lipid raft-like domains, heavy metal-membrane interactions, and cellular membrane organization. Practical considerations for the exogenous incorporation of laurdan into membrane systems are also addressed, including the influence of solvent vehicle on probe aggregation and incorporation kinetics. Laurdan derivatives such as C-laurdan, CAPRYDAA, and organelle-targeted variants have further extended the versatility of this probe family. Together, these advances illustrate how laurdan has evolved from a simple polarity sensor into a multifaceted platform for characterizing membrane structure, lateral heterogeneity, and dynamics across model and biological systems.
Predicting viral evolution and function remains a central challenge in biology, hindered by high sequence divergence and limited knowledge compared to cellular organisms. Here, we introduce LucaVirus, a multi-modal foundation model for viruses, trained on 25.4 billion nucleotide and amino acid tokens covering a vast majority of catalogued viral diversity. LucaVirus learns biologically meaningful representations that reflect relationships between sequences, protein/gene homology, and evolutionary divergence. Using these embeddings, we developed downstream models that address key virology tasks: identifying hidden viruses in genomic 'dark matter', annotating enzymatic activities of uncharacterized proteins, predicting viral evolvability, and identifying antibody candidates for emerging viruses. LucaVirus demonstrates competitive performance in three tasks and matches leading models in the fourth with one-third the parameters. Together, these findings demonstrate the utility of a unified foundation model in analyzing viral sequence data and establish LucaVirus as an efficient and versatile platform for AI-driven virology, from virus discovery to functional and therapeutic predictions.
Persistence - i.e., the ability to exist in a metabolically inactive form - allows bacteria to accumulate genetic advantages. The evolution of the pathogenic potential of Klebsiella pneumoniae has led to the emergence of strains simultaneously characterized by increased aggressiveness (virulence) and prolonged survival in the host organism. This combination of properties contributes to the emergence of "superbugs," necessitating the search for specific markers that would make it possible to prevent the spread of highly adaptive clones. Hypervirulent K. pneumoniae (hvKp) strains represent a growing global health threat, since they combine high invasiveness and antibiotic resistance. An analysis of 92 K. pneumoniae clinical isolates was conducted to assess the prevalence of the key hypervirulence genes (iroB, peg-344, rmpA, rmpA2, and iucA) and investigate their association with the bacterial persister formation gene ptsH. It was found that 64.1% (59/92) of the isolates carried at least one hvKp gene, iucA being the most frequent one (62.0%). The full set of five hvKp genes was identified in only one case (1%). The strains of sequence types ST23, ST268, ST86, ST534, ST219, ST101, and ST395 accumulated virulence genes, whereas ST512 and ST14 rarely harbored hvKp genes. A key finding was the detection of a significant association between the presence of the ptsH gene (found in 50% of the strains) and the accumulation of hvKp genes: the ptsH-positive strains were statistically more likely to harbor the complete aerobactin operon (iucABCD), in combination with one or more additional hypervirulence genes, compared to the ptsH-negative strains (p < 0.05). Our findings indicate that the ptsH gene is crucial in the formation of polygenically determined hypervirulence, and that its role in controlling bacterial persistence creates evolutionary advantages under stress induced by antibiotics or immune factors, thus promoting evasion of their actions. The phosphotransferase system (PTS), to which the ptsH gene belongs, can potentially become a novel source of molecular targets for the therapy of infections caused by hypervirulent K. pneumoniae strains.
The persistent accumulation of heavy metal(loid)s (HMs) in soils poses a major risk to environmental quality worldwide, while their migration and transformation are strongly regulated by climate change. However, global-scale assessments of soil HMs mobility and its spatiotemporal evolution under climate change remain unexplored. To address these challenges, we constructed a predictive framework for soil HMs mobility by integrating interpretable machine learning with future climate scenario simulations. The optimal Extra Trees (ET) model yielded an R2 of 0.885 on the testing dataset, along with the lowest RMSE (8.76) and MAE (4.91). Model interpretability analysis identified climatic variables, including temperature and precipitation, as important factors affecting soil HMs mobility. By coupling this framework with three Shared Socioeconomic Pathways (SSPs), we projected the spatiotemporal evolution of HMs mobility, including As, Cd, Cr, Cu, Hg, and Pb, from 2025 to 2100. The results revealed pronounced element-dependent responses to future climate change: the mobility of Cd and Pb exhibited overall increasing trends, whereas those of As, Cr, Cu, and Hg showed consistent declines. Spatial analyses further demonstrated that SSP5-8.5 (high-emission scenario) drove a marked expansion of Cd mobilization hotspots in tropical and subtropical regions, while mobilization hotspots for As contracted markedly in the mid- to high-latitude areas of the Eurasian continent. These findings elucidate how future climatic shifts may influence the mobility of soil HMs, while offering a scientific foundation for assessing pollution risks and developing adaptive management approaches at a global scale.
Osimertinib is the standard first-line treatment for patients with non-small cell lung cancer (NSCLC) harboring EGFR-sensitive mutations. However, drug resistance inevitably develops, highlighting the critical need for strategies to overcome this resistance and prolong therapeutic efficacy. Understanding the mechanisms underlying drug resistance is essential, and drug-resistant cell models serve as valuable tools for investigating acquired resistance. In this study, we establish an osimertinib resistance evolution model in vitro by continuous high-dose drug induction and identify cell lines exhibiting "permanent" resistance to osimertinib (osimertinib resistant, OR). Transcriptome sequencing (RNA-seq), gain- and loss-of-function assay, including lentiviral-mediated overexpression and RNAi knockdown, pharmacological inhibition, and protein degradation analysis reveal significant alterations in genes associated with epigenetic regulation, notably a marked upregulation of histone deacetylase 6 (HDAC6) in OR cells. Knockdown of HDAC6 or pharmacological inhibition of HDAC6 restores the sensitivity of OR cells to osimertinib, whereas overexpression of HDAC6 in sensitive cells reduces drug efficacy and accelerates the onset of resistance. Furthermore, we find that HDAC6 upregulation promotes EGFR degradation, thereby contributing to resistance. Collectively, our findings demonstrate the utility of drug resistance evolution models in identifying key resistance factors. HDAC6 plays a pivotal role in osimertinib resistance, and targeting HDAC6 may represent a novel therapeutic strategy to overcome resistance and enhance treatment efficacy.
Carbon emission transfers and the allocation of associated responsibilities are core issues in carbon system analysis. This study investigates the structural evolution and equity implications of China's multi-scale carbon emission transfer networks. We construct province-sector networks and identify pronounced scale-free and core-periphery topologies. Key carbon flows are highly concentrated in the power and heating sectors of resource-rich provinces and in the construction sector across provinces, indicating marked sectoral concentration effects. The spatial pattern of the carbon transfer network has shifted from a single-pole radiation centered on the eastern coast toward a multi-polar linkage pattern. This transition has enhanced the hub status of central and western provinces. Using Carbon Emissions Terms of Trade, Carbon Gini coefficients, and improved network centrality metrics, our analysis confirms the ongoing intensification of inter-provincial carbon inequality. We further identify a significant spatial mismatch between carbon responsibilities and economic benefits from both production-based and consumption-based perspectives. This mismatch constitutes the structural root of inter-provincial carbon inequality and reflects a systemic imbalance between responsibility and benefit in inter-regional industrial transfers. Integrating these findings with a macro-level fairness assessment, this study identifies key transmission pathways and structural hubs. It also provides policy implications for carbon responsibility allocation and more equitable regional emission reduction mechanisms.
Traditional-method sparkling wines undergo a slow aromatic evolution during bottle aging, typically from 12 months to over 10 years, developing toasted, nutty, and mineral notes. This review examines the biochemical, physicochemical, and sensory bases of these attributes, focusing on yeast autolysis, Maillard-derived products, volatile sulfur compounds, and the debated concept of minerality. Maillard-related reactions, although classically linked to high-temperature foods, can also proceed under the 10-15 °C, pH 2.9-3.2, and 5-6 bar conditions of sparkling wine aging, generating aroma-active compounds occurring at 0.5-40 μg/L. Minerality is discussed as a multifactorial, matrix-dependent perception shaped by acidity, ionic composition, and sulfur compounds. The convergence between toasted and mineral descriptors reflects shared precursors and reaction pathways, supporting a continuum rather than discrete sensory categories. Remaining knowledge gaps and priorities for future research under realistic aging conditions are outlined.
Brain-computer interface (BCI) technology represents a critical frontier in neurorehabilitation. This study aims to systematically analyze the global research landscape, hotspot distribution, and evolving trends of BCI interventions for upper limb rehabilitation in stroke survivors between 2016 and 2025. Bibliometric analysis and systematic mapping were conducted using data from the Web of Science Core Collection and PubMed. Literature was retrieved using terms related to "stroke," "brain-computer interface," and "upper limb rehabilitation." Screening followed the PRISMA guidelines. Visualization and quantitative mapping were performed using CiteSpace (v.6.4.R2) and VOSviewer (v.1.6.20) to evaluate publication volume, international collaboration, and keyword co-occurrence clusters. Annual publications increased steadily from 37 in 2016 to 104 in 2025, with 65.6% published since 2020. The United States (n = 144), China (n = 83), and Italy were the most productive countries. Keyword analysis revealed a paradigm shift from functional electrical stimulation toward robotics-assisted therapy, motor imagery, and AI-driven decoding. Significant burst strengths were observed for "closed-loop systems," "generative AI," and "multi-modal feedback," indicating these as the current primary frontiers. BCI research for post-stroke recovery is transitioning from experimental signal processing to intelligent, multi-modal, and personalized clinical systems. Bibliometric evidence confirms that integrating BCI with robotic-assisted rehabilitation or functional electrical stimulation (FES) has become the mainstream clinical trend. Future efforts must focus on improving EEG signal stability and developing user-friendly hardware to facilitate the transition of BCI from research settings to daily clinical practice. China has emerged as the second most productive country, though international cooperation with European institutions remains an area for further growth.
Stent placement effectively relieves venous pulsatile tinnitus caused by transverse sinus stenosis with sigmoid sinus wall dehiscence. However, the spectrum of temporal bone remodeling remains poorly characterized. This retrospective cohort study included consecutive patients who underwent transverse sinus stenting for venous pulsatile tinnitus with ipsilateral sigmoid sinus wall dehiscence, with or without a diverticulum. Clinical outcomes were recorded. Preoperative and postoperative CT were obtained (median follow-up 7 months; 18 patients had serial scans). Bone regeneration (graded as complete, major >50%, minor <50%, or absent) and new dehiscence were evaluated bilaterally. Ipsilateral bone regeneration occurred in 47/50 patients (94.0%): complete in 20.0%, major in 46.0%, minor in 28.0%, and absent in 6.0%. Contralateral bone regeneration was observed in 16/17 patients (94.1%). Among 18 patients with serial postoperative scans, 13 (72.2%) showed progressive regeneration. Follow-up duration correlated positively with regeneration degree (r = 0.51, P < 0.001). New bone dehiscence on the symptomatic side developed in 7 patients (14.0%): 3 adjacent to original sigmoid sinus wall dehiscence, 4 at jugular bulb. Complete resolution was achieved in 9/10 of complete regeneration (90.0%), 22/37 of partial regeneration (59.5%). Recurrence was observed in 5 of 37 patients (13.5%) with partial regeneration; notably, 3 of these 5 recurrences occurred among the 4 patients who had new jugular bulb dehiscence. Bone remodeling after stenting for venous pulsatile tinnitus is a dynamic, time-dependent process encompassing bilateral temporal bone regeneration and ipsilateral new dehiscence formation and correlates with clinical outcomes.
Malaria is a devastating disease that resulted in an estimated 610,000 deaths in 2024, the majority being children under the age of five. Here, we use KNX-115 to illustrate multistage antiparasitic activity upon targeting the cytoskeletal enzyme Plasmodium falciparum myosin A (PfMyoA). KNX-115 inhibits purified actin-activated ATPase with a potency in the low nanomolar range and >50-fold selectivity against cardiac, skeletal, and smooth muscle myosins. KNX-115 traps PfMyoA in a state that binds weakly to actin. A 2.35 Å resolution structure of KNX-115 bound to PfMyoA reveals critical interactions contributing to its mechanism of action. Importantly, in vitro evolution data reveal that KNX-115 engages PfMyoA as a sole cellular target. Inhibiting PfMyoA blocks the development of the blood and liver stages of laboratory strains of P. falciparum, with no liver cell toxicity, sporozoite cell traversal and motility, and sporozoite development in the mosquito. Inhibiting PfMyoA completely kills parasites after 96 h of treatment. Furthermore, KNX-115 is equally effective at inhibiting a panel of Plasmodium strains resistant to experimental and marketed antimalarials and shows inhibitory activity against P. falciparum circulating isolates from the Brazilian Amazon. Inhibiting PfMyoA with KNX-115 also blocks the blood stage of a laboratory strain of Plasmodium vivax. In line with the evolutionary identity of MyoA among various apicomplexan parasites, KNX-115 also inhibits Cryptosporidium and Eimeria MyoA in vitro and is an effective inhibitor of Cryptosporidium, Toxoplasma, and Eimeria cellular growth, with EC50s similar to those found for blood and liver stage Plasmodium.
The pyripyropenes A-X represent a family of 24 alkaloids isolated from fungi, mainly Aspergillus and Penicillium species, over the past 30 years. Numerous analogues have been isolated from fungi or (hemi)synthesized to investigate structure-activity relationships. The leader product in the series remains the first identified natural product pyripyropene A (Pyri-A), known as a highly potent and selective inhibitor of acyl CoA:cholesterol acyltransferase 2 (ACAT2). The present review retraces the products history, from their discovery to the characterization of the target engagement, the cellular mechanism of action and bioactivities. In parallel to the identification of naturally occurring pyripyropenes and the synthesis of derivatives, studies have progressed in three directions. First, the development of agricultural insecticides from Pyri-A led to discovery and worldwide commercialization of afidopyropen (Inscalis®) to protect crops against sucking insects. Second, the highly potent and selective targeting of ACAT2, largely expressed in human liver cells notably, drove the design of analogues aimed at regulating cholesterol metabolism for the treatment of metabolic and cardiovascular diseases. Third, the emerging roles of ACAT2 as a regulator of tumor cell proliferation and anticancer immune response call for the development of the pyripyropenes in oncology. A few tumor-active pyripyropene derivatives targeting ACAT2 have been identified recently. The review underlines the evolution of research in this domain, from the fungal production to the insecticidal action, and from the treatment of atherosclerosis to cancers. The pyripyropene saga is alive and well.
Rechargeable zinc-air batteries (ZABs) require efficient electrocatalysts to boost the sluggish oxygen reduction reaction (ORR)/ oxygen evolution reaction (OER) kinetics at the air cathode. However, designing high-activity catalysts faces considerable challenges due to spatial and electronic constraints. Herein, a boron-doped hollow spherical porous carbon (HS-FeNi-BNC) anchored with Fe-B-Ni diatomic sites is prepared via a facile B-bridging strategy, realizing the regulated construction of heteroatom doping and diatomic active sites. HS-FeNi-BNC possesses abundant micropores/mesopores, uniformly dispersed FeNi diatomic centers (0.27 nm spacing) with a Fe-B-Ni bridge structure, and topological carbon defects induced by B/N co-doping. HS-FeNi-BNC exhibits exceptional trifunctional electrocatalytic performance in alkaline electrolytes, with an ORR E1/2 of 0.864 V, an OER overpotential of 308 mV and a hydrogen evolution reaction (HER) overpotential of 301 mV at 10 mA cm-2. HS-FeNi-BNC-based ZABs achieve an outstanding wide-temperature operating range of -10 °C to 60 °C, a specific capacity of 761.51 mAh g-1 and a Zn utilization efficiency of 92.9%, outperforming Pt/C + RuO2-based ZABs. Density functional theory (DFT) calculations reveal that the Fe-B-Ni bridge structure triggers p-d orbital hybridization, regulating metal site electronic structures, optimizing reaction intermediate adsorption and accelerating interfacial electron transfer. This work advances the development of high-efficiency heteroatom-modified non-noble metal multifunctional catalysts.
The development of highly efficient water-splitting technologies relies on the precise control of catalytic environments at the nanoscale, where structural, electronic, and interfacial properties collectively determine catalytic performance. Recent advances in nanoengineered electrocatalysts, including noble-metal nanostructures, single-atom catalysts, defect-rich oxides, heterointerface-engineered systems, and carbon-supported multidimensional architectures, have revealed new opportunities for tailoring catalytic nanoenvironments to enhance hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) kinetics. This review highlights emerging strategies for engineering functional catalytic environments that regulate charge transfer, optimize active-site exposure, facilitate mass transport, and improve structural robustness under practical electrochemical conditions. Particular attention is given to ultrathin oxyhydroxide layers, vacancy-mediated surfaces, lattice-distorted phases, and multicomponent heterostructures that exhibit superior activity and long-term durability. In addition, recent progress in operando characterization, theoretical modeling, and integrated electrode design is discussed to elucidate structure-function relationships governing catalytic performance. Finally, scalable synthesis approaches, engineered porous electrodes, and data-driven catalyst discovery are examined as promising pathways toward practical implementation. By connecting nanoscale materials engineering with functional electrocatalytic performance, this review provides critical insights into the rational design of catalytic nanoenvironments for next-generation water-splitting technologies.
Digital health technologies are increasingly applied in diabetes care, enabling continuous monitoring, personalized support and remote interventions. Meanwhile, artificial intelligence (AI) is enhancing the precision and effectiveness of these tools. This study aims to map global research trends and thematic developments in AI-driven digital health technologies for diabetes management and to explore their future directions. We collected data from the Web of Science Core Collection, including articles and reviews published up to July 12, 2025, using CiteSpace, VOSviewer, and Microsoft Excel to analyze countries/regions, institutions, journals, references, authors, and keywords. A total of 673 publications were included in the analysis. Global publications on AI-driven digital health technologies for diabetes increased steadily, with the USA leading in output. The University of London ranked as the most productive institution. Sensors and diabetes care were the most frequently published and cited journals in this field. Herrero P was among the most prolific authors. The most cited article was "Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs." "diabetes" was the most frequently occurring keyword. Keyword cluster analysis identified 3 primary research hotspots: AI-enabled monitoring, digital health interventions, and AI-based diabetic retinopathy screening. This study summarizes the evolution of AI-driven digital health technologies in diabetes care. Although challenges remain in data security, standardization and validation, these technologies hold increasing potential for accurate diagnosis, real-time monitoring and personalized care.