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Microcomb-driven large-scale fully connected quantum network
Abstract Fully connected quantum networks enable simultaneous connection of every user to every other user and are a highly versatile and robust networking architecture. However, the scalability of such networks remains a great challenge for practical applications. Here we construct a large-scale fully connected quantum network founded on two-photon Hong-Ou-Mandel (HOM) interference, where user-to-user security is guaranteed even with an untrusted network provider. Using integrated soliton microcomb (SMC) and photonic encoding chips, we realize precise, massively parallel frequency generation and locking, high-visibility HOM interference and measurement-device-independent (MDI) quantum key distribution. The proposed architecture enables a fully connected quantum network over 200 kilometers with strict information-theoretic security via an untrusted network provider. The implemented networking architecture paves the way for large-scale fully connected MDI quantum networks across metropolitan and intercity regions.
Mitochondria‐Damaging Self‐Reporting Probe for Cancer Therapy
ABSTRACT Mitochondrial damage induced by chemotherapeutic agents through disruption of the mitochondrial membrane potential (Δ Ψ m ) remains a central challenge in drug development and evaluation. However, the assessment of Δ Ψ m ‐targeting drugs using commercially available fluorescent probes is often unreliable, as these dyes can interfere with, mask, or artificially amplify drug‐induced mitochondrial dysfunction, frequently resulting in misleading conclusions and translational failure. Herein, we report a class of cationic chemotherapeutic small molecules ( DPPs ) possessing intrinsic fluorescence migration‐based self‐reporting capability, which enables direct and non‐invasive monitoring of drug action without the need for external probes. Among them, DPP‐1 and DPP‐2 disrupt mitochondrial function, trigger excessive reactive oxygen species generation, and induce highly selective apoptosis. Remarkably, both compounds exhibit concentration‐dependent mitochondrial‐to‐nuclear translocation, enabling the real‐time visualization of therapeutic progression at the subcellular level. In vivo studies further confirm their potent tumor growth inhibition and negligible systemic toxicity effects. This self‐reporting mitochondria‐targeted chemotherapeutic platform provides a highly promising strategy for integrated cancer diagnosis and precision therapy.
Post-quantum secure blockchain framework for decentralized healthcare identity management and predictive analytics
Mechanism underlying the high regulatory performance of the doxycycline riboswitch G12
Abstract Synthetic riboswitches provide protein-independent, modular control of gene expression, yet selecting aptamers that reliably couple ligand binding to regulatory switching remains challenging. Here, we identify and mechanistically characterise G12, a doxycycline-binding aptamer with remarkably high regulatory performance in yeast and human cells. We provide evidence that RNA Capture-SELEX efficiently enriches aptamers with ligand-responsive conformational switching. We compared conventional SELEX and RNA Capture-SELEX using the same starting library followed by NGS analysis and in vivo screening, which led to the identification of G12. G12 binds doxycycline with low-nanomolar affinity and strict discrimination against close derivatives, thus enabling high-dynamic-range riboswitch control of translation in yeast and splicing in human cells. Single-molecule force spectroscopy with optical tweezers revealed that doxycycline stabilises a folding intermediate independent of the closing stem P1, which primarily acts as a scaffold for correct aptamer folding. Mutational analysis and chemical probing identified tertiary contacts between loops L2 and L3 in this intermediate state. Stopped-flow fluorescence spectroscopy further supported a two-step binding mechanism consistent with efficient regulatory switching. Together, these findings deepen our understanding of regulatory aptamer selection and function and expand the synthetic biology toolbox with a high-performance doxycycline-responsive riboswitch.
Regio‐, Stereo‐, and Enantioselective C(sp <sup>3</sup> )─H Monofluoroalkenylation via Photo‐HAT/Nickel Dual Catalysis
ABSTRACT Stereoselective functionalization of C(sp 3 )─H bonds in hydrocarbons constitutes a revolutionary strategy for accessing high‐value chiral molecules. Despite remarkable advances in this field, enantioselective C(sp 3 )‐H monofluoroalkenylation remains unexplored to date. Herein, we report the first regio‐, stereo‐, and enantioselective benzylic C(sp 3 )─H monofluoroalkenylation, enabled by a decatungstate‐mediated hydrogen atom transfer (HAT)/nickel dual‐catalytic system. This protocol utilizes inexpensive, readily available hydrocarbons and easily accessible gem ‐difluoroalkenes as starting materials, delivering a broad array of structurally diverse ( E )‐monofluoroalkenes bearing stereogenic allylic centers, versatile building blocks in synthetic chemistry.
Non‐Benzenoid π‐Electronic Perturbation Enables Frontier‐Orbital Symmetry Reconstruction in Ultra‐Narrowband Organic Luminophores
ABSTRACT Organic luminophores with ultra‐narrow full widths at half‐maximum (FWHMs) are highly demanding for high‐definition displays; however, the current strategies, including bond‐length homogenization and multiple‐resonance effects, often suffer from limited molecular design flexibility. Herein, we present a new series of ultra‐narrow organic luminophores by incorporating an antiaromatic cyclobutadiene motif into nitrogen‐containing polycyclic aromatic hydrocarbons. Theoretical simulations show that the fused four‐membered rings introduce a non‐benzenoid π‐electronic perturbation, which reconstructs the frontier‐orbital symmetry. This reconstruction suppresses intrinsic bonding‐antibonding transition character, affording an exceptionally narrow FWHM of 10.3 nm (in dilute toluene) and a near‐unity photoluminescence quantum yield (PLQY ≈ 100%). In addition, weak‐aromaticity‐mediated two‐dimensional (2D) π‐conjugation extension not only enhances luminescence efficiency but also affords sufficient chemical robustness compatible with vacuum evaporation process. Organic electroluminescent (EL) devices incorporating these CBD‐embedded emitters exhibit high performance, with a maximum current efficiency surpassing 30.0 cd A − 1 , an external quantum efficiency exceeding 20.1%, and minimal efficiency roll‐off, thereby underscoring the substantial potential of antiaromaticity modulation for the development of cutting‐edge narrowband emitters.
The relationshıp between physical examinatıon and radiology in shoulder pseudoparalysis
Abstract Rotator cuff tears, often caused by degeneration, trauma, or repetitive use, can severely affect shoulder function. Pseudoparalysis, characterized by the inability to elevate the arm despite normal passive range of motion, is a challenge in massive tears. This study aimed to evaluate the association between radiological parameters on X-ray and MRI and pseudoparalysis/pseudoparesis in patients with large to massive rotator cuff tears. A retrospective cohort study was conducted on 58 patients who underwent arthroscopic surgery for large to massive rotator cuff tears between 2018 and 2024. Patients were categorized based on shoulder abduction and flexion: Group 1 (0–45°, pseudoparalysis), Group 2 (45–90°, pseudoparesis), and Group 3 (> 90°, near-normal motion). For abduction, Groups 1, 2, and 3 consisted of 14, 27, and 17 patients, respectively, while the corresponding group sizes for flexion were 13, 26, and 19. Preoperative X-rays and MRI assessed the critical shoulder angle (CSA), acromiohumeral distance (AHD), and muscle integrity. Intraoperative findings detailed tendon tears. Higher Patte stages and a greater number of torn tendons were significantly associated with reduced abduction and flexion ROM (p < 0.001). AHD correlated with greater ROM in abduction and flexion (respectively p = 0.006, p = 0.033), while CSA and tangent sign showed no significant association. Subscapularis involvement correlated with reduced abduction (p = 0.021). Comorbidities like diabetes, hyperlipidemia, and smoking had no significant effect on ROM. The number of torn tendons, Patte stage, and reduced acromiohumeral distance were significantly associated with pseudoparalysis. When physical examination is limited, these imaging findings may be more frequently observed in patients with pseudoparalysis or pseudoparesis; however, they should be interpreted in conjunction with clinical evaluation. Level of Evidence: Level 3
Development of an artificial intelligence model for predicting cardiovascular disease in MASLD
HODet:Horizontal-to-Oriented Object Detection with simplified annotation
Abstract The recognition and positioning of characters on the water gauge are important components of artificial intelligence system for reading ship draft weighing. Meanwhile, the manual annotation of oriented objects has a large workload and low accuracy. To address these issues, this paper proposes a novel oriented detection framework. It introduces three additional parameters to refine the horizontally detected bounding boxes from the model and employs two symmetric functions to confine the angles and scales within specified ranges. In the training and testing of the model, only the horizontal annotation information of the object is needed, reducing the workload of annotation of the target in the dataset. A residual network has been added to the backbone of object detector(YOLO) to enhance the feature extraction capability of deep modules and improve the sensitivity to small objects. For more accurate oriented estimation, we utilize improved Intersection over Union(IoU) to the bounding box regression loss.This method is particularly effective for objects with a dominant orientation and approximately rectangular shapes, such as the characters, vehicles, and buildings commonly found in aerial imagery. A simple implementation of our method has achieved state-of-the-art performances on aerial objects datasets, with a negligible reduction to detection speed. After applying the novel oriented detection method to the intelligent system, real-time testing was conducted on 120 drone videos, resulting in a 35.3% improvement in the accuracy of the system’s water gauge readings.
Green synthesis of Ni-doped ZnO nanoparticles using Salvia hispanica and their antibacterial, anticancer and anti-virulence activities
Risk factors for incident chronic kidney disease following unilateral nephrectomy: a systematic review and meta-analysis
A soft-switched, trans-inverse step-up DC-DC converter with minimal components based on built-in transformer
Alignment-free convolutional neural network classification of glycemic states in type 1 diabetes from GC–IMS breath spectra
Abstract Reliable detection of glycemic dysregulation, particularly hypoglycemia, is essential for people with diabetes, yet current approaches rely on capillary blood sampling or require subcutaneous sensor insertion. Breath analysis offers a non-invasive alternative by capturing volatile organic compounds associated with metabolic changes. This study investigated whether a convolutional neural network can classify glycemic states from gas chromatography–ion mobility spectrometry data of exhaled breath. Breath samples from ten individuals with type 1 diabetes were collected under standardized fasting, postprandial, and insulin-induced hypoglycemic conditions. In a proof-of-concept cohort of ten participants, the model trained on minimally preprocessed spectra achieved a mean balanced accuracy of 86.6% (±4.0%) in leave-2-patients-out cross-validation, with specificity exceeding 92% across all classes. Importantly, the network maintained stable performance despite retention time variability caused by instrumental drift, without requiring spectral alignment. In contrast, traditional machine learning models required extensive preprocessing and showed reduced robustness under shifted conditions. Saliency map visualization highlighted physiologically relevant breath markers, including acetone, isoprene, and 2-propanol. To our knowledge, this is the first application of a convolutional neural network to ion mobility spectrometry breath data. The findings establish a methodological foundation for applying neural network-based analysis to complex breathomics datasets and motivate further validation toward scalable digital health tools that complement existing glucose monitoring technologies.
Candidate gene identification and molecular marker development for the small granule starch trait in cassava (Manihot esculenta Crantz)
Abstract Cassava ( Manihot esculenta ) is both a vital staple and industrial cash crop, with growing global demand for specialty starches. Small granule cassava starch is highly valued for industrial uses because its reduced size, high amylose content, and improved processing efficiency make it ideal for specific applications such as bioethanol production. The genetic basis for this trait in cassava is unknown, and no molecular tools are currently available to support breeding. Here, we combine in silico genomic analysis, phenotyping and independent genome-wide association study (GWAS) to identify candidate genomic regions and develop a robust molecular marker. Cassava genome exploration revealed nine α-glucan phosphorylase (PHS1/PHO1) genes, with six clustered in tandem duplication on chromosome 2. Whole-genome sequence analysis of 392 progenitors identified a key single nucleotide polymorphism (SNP) at Chr02:4,238,800 in the 5′ untranslated region (UTR) of Manes.02G052600 that strongly associated with the trait. We designed a Kompetitive Allele Specific PCR (KASP) assay targeting this SNP and validated it in a multi-parental population ( n = 962). The marker explained 48% of the phenotypic variation. This is the first molecular marker for cassava starch granule size, providing a cost-effective high-throughput tool for marker-assisted selection (MAS) to accelerate the development of specialty starch varieties.
A novel gas detector optimisation method combining 2-of-N voting systems, kinetic theory of gases, and exceedance curves to minimise CFD requirements
Controlled-release phosphorus dynamics of urine-derived struvite for nutrient recovery and circular agriculture in tropical soils
Abstract Phosphorus recovery from human waste is a cornerstone of circular nutrient management, yet the behavior of recovered phosphorus minerals in highly weathered tropical soils remains poorly understood. This study evaluated the agronomic performance and phosphorus dynamics of human urine-derived struvite (HU-Struvite) in a tropical Oxisol cultivated with maize (Zea mays). HU-Struvite achieved substantial shoot biomass production under tropical soil conditions, although monoammonium phosphate (NH₄H₂PO₄) generally produced higher shoot dry mass at the highest phosphorus application rates. More importantly, HU-Struvite maintained substantially higher residual Mehlich-1 extractable phosphorus after cultivation, indicating sustained labile phosphorus availability and reduced phosphorus immobilization in the highly weathered soil. By integrating plant response, phosphorus uptake, residual soil phosphorus, and phosphorus fractionation behavior within a single soil–plant system, the study demonstrates how the controlled-release characteristics of urine-derived struvite influence phosphorus retention under tropical conditions. These findings suggest that controlled phosphorus release may mitigate rapid fixation associated with iron and aluminum oxides while sustaining plant-available phosphorus over time. Our results demonstrate that, during the early vegetative growth of maize, urine-derived struvite is a promising strategy for improving phosphorus-use efficiency and advancing circular nutrient management in tropical agricultural systems.