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Efficient Aqueous Intramolecular Alkyne Hydrofunctionalization Catalyzed by Monodentate Gold(I) Complex of Cocarboxylase
No full textThiamine diphosphate (ThDP), or cocarboxylase, is an enzyme cofactor that catalyzes crucial metabolic reactions via a thiazolium carbene in all living systems. In this study, we successfully exploit this N-heterocyclic carbene ligand for the efficient synthesis of a monodentate gold (I) complex. The resulting ThDP = AuCl complex efficiently catalyzes intramolecular hydroamination, hydroalkoxylation, and hydrocarboxylation of a diverse array of alkyne substrates in water and open air at mild temperatures. This new metal catalyst is environmentally friendly and holds promise for the construction of novel artificial metalloenzymes.</p
Moduli spaces of pentagonal subdivision tilings
No full textPentagonal subdivision gives three families of edge-to-edge tilings of the sphere by congruent pentagons. Each family forms a two real parameter moduli space. We describe these moduli spaces in detail, to complete the classification of such tilings and to facilitate potential applications in physics and other disciplines.</p
A class of COPI cargo receptors regulates processing of transmembrane proteins by reinforcing their Golgi retention
No full textMany transmembrane (TM) signaling receptors undergo essential posttranslational modification in the Golgi prior to their delivery to the plasma membrane (PM). Whether and how the passage and accompanied modification of these proteins across the Golgi is controlled remains unclear. Here, we show that leptin receptor overlapping transcript (LEPROT) and LEPROT-like 1 (LEPROTL1) regulate TM receptor activation by securing their sufficient Golgi retention. LEPROTs localize to cis and medial Golgi in a coat protein complex I (COPI)-dependent manner. LEPROTs interact directly with COPI coats and simultaneously engage a variety of integral membrane proteins with relatively long TM domains at acidic pH. Deletion of LEPROTs in cells causes expedited release of TM receptors transiting through the Golgi. Loss of LEPROTs dysregulates receptor signaling activity, including that of epidermal growth factor receptor (EGFR) and transferrin receptor (TFRC), due to defective modification. Collectively, LEPROTs serve as a class of COPI cargo receptors for TM receptors, ensuring adequate preparation, which is vital for subsequent action on the PM.</p
适应性选才: 融合学科范式下研究生招生录取新机制
No full text融合学科育人范式要求吸纳具备跨学科融通、综合创新和系统思维等知识、能力、素养三位一体的潜在人才，亟待创新招生录取机制。在适应性选才的理念指导下，香港科技大学（广州）探索了融合学科范式下研究生招生录取新机制：建立了优势互补的三类招录通道，从不同背景的学生中筛选出潜在的创新领军人才；创新了各招录通道的内部环节，在各环节针对性地建构了多维评估标准，旨在考察学生的融合学科创新思维和可迁移能力；制定了兼顾公平性和有效性的招生录取制度，保障融合学科适应性选才的同时也破解了传统招生录取机制的困境。在学科规训下，融合学科招生录取须建立全新的标准和前瞻性机制，实现从人才选配到培养的范式创新
Coupling a micro-genetic algorithm with RegCM5 for improving extreme precipitation simulations over Southeast Asia
No full textRegional climate models (RCMs) are essential for producing fine-scale climate information, but their effectiveness is highly sensitive to the combination of physical parameterizations and optimal settings of key parameters. To tackle this problem, this study develops a coupled modeling system that integrates a micro-genetic algorithm (μGA) with the Regional Climate Model version 5 (RegCM5), focusing on optimizing parameters in the Tiedtke convection scheme, crucial for precipitation simulations. Using the benchmarking version of RegCM5 for Southeast Asia, we aim to identify the optimal parameter set that enhances performance for three extreme precipitation events. The evaluation of this parameter set is then conducted by simulating six additional extreme events. Results show that simulations with optimized parameters improve both precipitation and temperature compared to the default model, significantly reducing biases, particularly over ocean regions. Our coupled RegCM5-μGA system will aid the broader RegCM5 community in enhancing model performance in their target regions.</p
Macrocyclic geminal diols: synthesis, structures, stability and photophysical properties
No full textGeminal diols are generally unstable and prone to dehydration, yielding carbonyl compounds and making their isolation as discrete species highly challenging. Herein, we report the synthesis, structural characterization, and stability of a series of crystalline, stable, and rigid macrocyclic gem-diols obtained via acid hydrolysis of macrocyclic ketal precursors at −25 °C. Single-crystal X-ray diffraction analysis of these compounds reveals O–C–O bond angles of approximately 111°, along with extensive hydrogen-bonding networks that contribute to stabilizing the gem-diols. Thermogravimetric and hydrolytic analyses reveal a pronounced size-dependent stability trend. Theoretical calculations indicate that the enhanced stability of smaller gem-diol macrocycles stems from their ability to relieve substantial angle strain via sp3 hybridization at the methylene carbon, an effect that diminishes as ring size increases. Based on our experimental and computational results, the inner angle value of the macrocyclic ketone is proposed as a criterion for evaluating the relative stability of macrocyclic ketones versus their gem-diol forms. The photophysical properties of the macrocyclic geminal diols and macrocyclic diketones are also examined. This work broadens the scope of stable geminal diols and provides fundamental insights into their structure–stability relationships, thereby laying the groundwork for the strategic design and synthesis of structurally diverse macrocyclic geminal diols.</p
Large-scale 3D medical image pre-training with geometric context priors
No full textThe scarcity of annotations poses a significant challenge in medical image analysis, which demands extensive efforts from radiologists, especially for high-dimension 3D medical images. Large-scale pre-training has emerged as a promising label-efficient solution, owing to the utilization of large-scale data, large models, and advanced pre-training techniques. However, its development in medical images remains underexplored. The primary challenge lies in harnessing large-scale unlabeled data and learning high-level semantics without annotations. We observe that 3D medical images exhibit consistent geometric context, i.e., consistent geometric relations between different organs, which leads to a promising way for learning consistent representations. Motivated by this, we introduce a simple-yet-effective Volume Contrast (VoCo) framework to leverage geometric context priors for self-supervision. Given an input volume, we extract base crops from different regions to construct positive and negative pairs for contrastive learning. Then we predict the contextual position of a random crop by contrasting its similarity to the base crops. In this way, VoCo implicitly encodes the inherent geometric context into model representations, facilitating high-level semantic learning without annotations. To assess effectiveness, we (1) introduce PreCT-160 K, the largest medical image pre-training dataset to date, which comprises 160 K Computed Tomography (CT) volumes covering diverse anatomic structures; (2) investigate scaling laws and propose guidelines for tailoring different model sizes to various medical tasks; (3) build a comprehensive benchmark encompassing 51 medical tasks, including segmentation, classification, registration, and vision-language. Extensive experiments highlight the superiority of VoCo, showcasing promising transferability to unseen modalities and datasets. VoCo notably enhances performance on datasets with limited labeled cases and significantly expedites fine-tuning convergence.</p
Development and assessment of an improved Baldwin-Lomax turbulence model for complex hypersonic flows in two and three dimensions
No full textAccurate prediction of hypersonic turbulent boundary layers is critical for the design of hypersonic vehicles. Traditional turbulence models were originally developed for incompressible flows and are commonly extended to compressible conditions by employing density-weighted averages. In a recent study, Chen et al. (J. Fluid Mech., 2024, vol 987, A7) proposed an improved Baldwin-Lomax (BL) turbulence model by incorporating velocity transformations and the temperature-velocity relation. Their modifications yielded notable improvements for high-speed zero-pressure-gradient flat-plate flows. Building upon this foundation, the present study introduces further enhancements to Chen et al.’s BL model to improve its accuracy and robustness for complex hypersonic configurations. The improved BL turbulence model is implemented into a standard computational fluid dynamics (CFD) solver and validated against direct numerical simulation results and experimental data across two- and three-dimensional hypersonic cases involving pressure gradients, cold walls, and shock/boundary-layer interactions. The results show that the improved BL turbulence model generally achieves superior accuracy in attached flow regions compared to the baseline BL, Spalart-Allmaras and k–ω SST turbulence models. These findings highlight the model's potential for practical use in hypersonic flow simulations, offering a valuable tool for aerospace engineering applications.</p
Nanobubble-enabled wetting control in membrane distillation via interfacial modulation
No full textSurfactant-induced membrane wetting critically undermines membrane distillation (MD), yet its nanoscale origins remain elusive. Here, we investigate the role of nanobubbles (NBs) as dynamic interfacial modulators that disrupt wetting pathways at the membrane–liquid interface. By coupling real-time impedance spectroscopy with molecular dynamics simulations and contact angle kinetics, we demonstrate that NBs form metastable gaseous domains on hydrophobic membranes, physically and chemically impeding the adsorption of sodium dodecyl sulfate (SDS) and pore intrusion. NB pretreatment extends wetting resistance by up to 3×, while NB-mediated cleaning re-establishes interfacial exclusion zones, sustaining salt rejection under surfactant stress. Our findings reveal a dual-function mechanism in which NBs modulate interfacial thermodynamics and surfactant transport, offering a scalable, non-invasive paradigm for engineering wetting-resilient MD systems.</p
Up-scaling of a photoelectrochemical system with regulated chloride activation for negative-emission saline sewage treatment and disinfection byproduct mitigation
No full textConventional wastewater treatment plants (WWTPs) are carbon- and energy-intensive, inefficient in degrading emerging pollutants (EPs), and require additional chemicals. The photoelectrochemical (PEC) system offers a sustainable approach for saline sewage treatment; however, effective regulation of chloride activation and demonstration of scalability remain critical challenges. Herein, a bismuth- and oxygen-vacancies modified BiVO4 (BvOv-BVO) photoanode is developed to regulate chloride activation, efficiently removing chemical oxygen demand (including EP), ammonia-N, and bacteria from simulated saline sewage coupled with substantial H2 evolution, while suppressing 76.6% of disinfection byproduct (DBP) formation compared to BVO. Importantly, it achieves negative emissions through restrained greenhouse gas (GHG) generation and carbon offsets from green H2 evolution. Mechanistic investigations reveal that BvOv-BVO regulates chloride activation to generate ClO• as the dominant reactive chlorine species, which simultaneously accelerates contaminant removal, suppresses DBP formation, and mitigates GHG emissions to enable negative emissions. To validate scalability, a continuous-flow prototypical PEC reactor with enlarged light absorption area, optimized light exposure, enhanced mass transfer, and improved hydrodynamics is established. This prototype exhibits exceptional performance in treating real saline sewage under natural sunlight, meeting discharge standards within 2 h, sustaining negative emissions and DBP control, and demonstrating excellent long-term stability. This study pioneers a scalable, negative-emission PEC system as a powerful and sustainable substitute for activated sludge and disinfection processes.</p