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In recent years, semiconducting polymer dots (Pdots) have attracted much attention due to their excellent photophysical properties and applicability, such as large absorption cross section, high brightness, tunable fluorescence emission, excellent photostability, good biocompatibility, facile modification and regulation. Therefore, Pdots have been widely used in various types of sensing and imaging in biological medicine. More importantly, the recent development of Pdots for point-of-care biosensing and in vivo imaging has emerged as a promising class of optical diagnostic technologies for clinical applications. In this review, we briefly outline strategies for the preparation and modification of Pdots and summarize the recent progress in the development of Pdots-based optical probes for analytical detection and biomedical imaging. Finally, challenges and future developments of Pdots for biomedical applications are given.

Magnetic nanoparticles (MNPs) can be quantified based on their magnetic relaxation properties by volumetric magnetic biosensing strategies, for example, alternating current susceptometry. Volume-amplified magnetic nanoparticle detection assays (VAMNDAs) employ analyte-initiated nucleic acid amplification (NAA) reactions to increase the hydrodynamic size of MNP labels for magnetic sensing, achieving attomolar to picomolar detection limits. VAMNDAs offer rapid and user-friendly analysis of nucleic acid targets but present inherence defects determined by the chosen amplification reactions and sensing principles. In this mini-review, we summarize more than 30 VAMNDA publications and classify their detection models for NAA-induced MNP size increases, highlighting the performances of different linear, cascade, and exponential NAA strategies. For some NAA strategies that have not yet been reported in VAMNDA, we predicted their performances based on the reaction kinetics and feasible detection models. Finally, challenges and perspectives are given, which may hopefully inspire and guide future VAMNDA studies.

Major depressive disorder (MDD) is a serious and widespread psychiatric disorder. Previous studies mainly focused on cerebrum functional connectivity, and the sample size was relatively small. However, functional connectivity is undirected. And, there is increasing evidence that the cerebellum is also involved in emotion and cognitive processing and makes outstanding contributions to the symptomology and pathology of depression. Therefore, we used a large sample size of resting-state functional magnetic resonance imaging (rs-fMRI) data to investigate the altered effective connectivity (EC) among the cerebellum and other cerebral cortex in patients with MDD. Here, from the perspective of data-driven analysis, we used two different atlases to divide the whole brain into different regions and analyzed the alterations of EC and EC networks in the MDD group compared with healthy controls group (HCs). The results showed that compared with HCs, there were significantly altered EC in the cerebellum-neocortex and cerebellum-basal ganglia circuits in MDD patients, which implied that the cerebellum may be a potential biomarker of depressive disorders. And, the alterations of EC brain networks in MDD patients may provide new insights into the pathophysiological mechanisms of depression.

The current diagnosis of major depressive disorder (MDD) primarily relies on the patient's self-reported symptoms and a clinical evaluation. The functional connectivity (FC) feature of resting-state functional magnetic resonance imaging (rs-fMRI) is widely used for the classification of MDD. However, the performance of FC features on the large-scale cross-site dataset is not good enough, which is a bottleneck in the application of classification methods in the clinical diagnosis of MDD. As it can reflect the directed connections between brain regions compared to FC, effective connectivity (EC) has the potential to improve the classification performance on large-scale, multi-site MDD datasets. Granger causality analysis was used to extract EC from a large multi-site MDD dataset. ComBat algorithm and multivariate linear regression were used to harmonize site difference and to remove age and sex covariates, respectably. Two-sample t-test and model-based feature selection methods were used to screen highly discriminative EC for MDD. At last, LightGBM was used to classify MDD. In the REST-Meta-MDD Consortium dataset, 97 EC with highly discriminative for MDD were screened. In the nested five-fold cross-validation, the best classification model using 97 EC achieved the accuracy, sensitivity, and specificity of 94.35%, 93.52%, and 95.25%, respectively. In the DecNef Project Brain Data Repository dataset, which tests the generalization performance of 97 EC, the best classification models achieved 94.74%, 90.59%, and 96.75% accuracy, sensitivity, and specificity, respectively.

Ground temperature (GT) variation significantly affects the energy performance of ground source heat pump (GSHP) systems. Both long-term thermal accumulation and short-term dynamic responses contribute to the degradation of the coefficient of performance (COP), especially under cooling-dominated conditions. This study develops a mechanism-based TRNSYS simulation that integrates building loads, subsurface heat transfer, and dynamic heat pump operation. A 20-year case study in Shanghai reveals long-term performance degradation driven by thermal boundary shifts. Results show that GT increases by over 12 °C during the simulation period, accompanied by a progressive increase in ΔT by approximately 0.20 K and a consistent decline in COP. A near-linear inverse relationship is observed, with COP decreasing by approximately 0.038 for every 1 °C increase in GT. In addition, ΔT is identified as a key intermediary linking subsurface thermal disturbance to efficiency loss. A multi-scale response framework is established to capture both annual degradation and daily operational shifts along the Load–GT–ΔT–COP pathway. This study provides a quantitative explanation of the thermal degradation process and offers theoretical guidance for performance forecasting, operational threshold design, and thermal regulation in GSHP systems.

Genetic cell-lineage tracing studies in mice are crucial for delineating the contribution of stem and progenitor cells to different cell types, both in disease states and after regenerative therapy. He et al. have developed new genetic lineage-tracing systems that provide more definitive results than the commonly used Cre-based system and show that this new technology can resolve current controversies in the field, as demonstrated by lineage-tracing studies in the heart and liver. The Cre– loxP recombination system is the most widely used technology for in vivo tracing of stem or progenitor cell lineages. The precision of this genetic system largely depends on the specificity of Cre recombinase expression in targeted stem or progenitor cells. However, Cre expression in nontargeted cell types can complicate the interpretation of lineage-tracing studies and has caused controversy in many previous studies. Here we describe a new genetic lineage tracing system that incorporates the Dre– rox recombination system to enhance the precision of conventional Cre– loxP -mediated lineage tracing. The Dre– rox system permits rigorous control of Cre– loxP recombination in lineage tracing, effectively circumventing potential uncertainty of the cell-type specificity of Cre expression. Using this new system we investigated two topics of recent debates—the contribution of c-Kit + cardiac stem cells to cardiomyocytes in the heart and the contribution of Sox9 + hepatic progenitor cells to hepatocytes in the liver. By overcoming the technical hurdle of nonspecific Cre– loxP -mediated recombination, this new technology provides more precise analysis of cell lineage and fate decisions and facilitates the in vivo study of stem and progenitor cell plasticity in disease and regeneration.

Periampullary diverticulum (PAD) often increases the difficulty of ERCP operation, and there is no standardized treatment strategy. This study compared the efficacy of “small incision + large balloon dilation (EST + EPBD)” with traditional ERCP. 111 patients with PAD complicated with choledocholithiasis were randomly divided into experimental group ( n  = 55, EST < 5 mm + EPBD) and control group ( n  = 56, conventional EST/EPBD). The primary endpoints were one-time stone clearance and adverse event rate, while secondary endpoints included operative time and common bile duct pressure. One-time stone clearance rate: test group 98.1% vs. control group 87.5% ( P  = 0.029) • Mean operation time: 24 ± 9 min vs. 31 ± 11 min ( P  < 0.001) • CBD pressure 6 days after surgery: 11.5 ± 2.3 vs. 8.5 ± 1.6 cm H₂O ( P  < 0.001) • Incidence of postoperative pancreatitis: 3.6% vs. 10.7% ( P  = 0.206). EST + EPBD can significantly improve stone removal efficiency, shorten operation time, and may improve long-term prognosis by preserving Oddi sphincter function.

Lead-free perovskite is one of the ideal solutions for the toxicity and instability of lead halide perovskite quantum dots. As the most ideal lead-free perovskite at present, bismuth-based perovskite quantum dots still have the problem of a low photoluminescence quantum yield, and its biocompatibility also needs to be explored. In this paper, Ce3+ ions were successfully introduced into the Cs3Bi2Cl9 lattice using a modified antisolvent method. The photoluminescence quantum yield of Cs3Bi2Cl9:Ce is up to 22.12%, which is 71% higher than that of undoped Cs3Bi2Cl9. The two quantum dots show high water-soluble stability and good biocompatibility. Under the excitation of a 750 nm femtosecond laser, high-intensity up-conversion fluorescence images of human liver hepatocellular carcinoma cells cultured with the quantum dots were obtained, and the fluorescence of the two quantum dots was observed in the image of the nucleus. The fluorescence intensity of cells cultured with Cs3Bi2Cl9:Ce was 3.20 times of that of the control group and 4.54 times of the control group for the fluorescence intensity of the nucleus, respectively. This paper provides a new strategy to develop the biocompatibility and water stability of perovskite and expands the application of perovskite in the field.

Achieving large-scale electrochemical CO 2 reduction to multicarbon products with high selectivity using membrane electrode assembly (MEA) electrolyzers in neutral electrolyte is promising for carbon neutrality. However, the unsatisfactory multicarbon products selectivity and unclear reaction mechanisms in an MEA have hindered its further development. Here, we report a strategy that manipulates the interfacial microenvironment of Cu nanoparticles in an MEA to suppress hydrogen evolution reaction and enhance C 2 H 4 conversion. In situ multimodal characterizations consistently reveal well-stabilized Cu δ+ -OH species as active sites during MEA testing. The OH radicals generated in situ from water create a locally oxidative microenvironment on the copper surface, stabilizing the Cu δ+ species and leading to an irreversible and asynchronous change in morphology and valence, yielding high-curvature nanowhiskers. Consequently, we deliver a selective C 2 H 4 production with a Faradaic efficiency of 55.6% ± 2.8 at 316 mA cm −2 in neutral media. The use of membrane electrode assembly electrolyzers in a neutral electrolyte offer potential for large-scale CO2 reduction to multicarbon products, but progress is hindered by low selectivity and unclear reaction mechanisms. Here, the authors regulate the interfacial microenvironment of Cu to stabilize Cuδ + -OH active species for selective C2H4 production.

This paper focuses on the design of vehicle trajectories and their control systems. A method based on quintic polynomials is utilized to develop trajectories for intelligent vehicles, ensuring the smooth continuity of the trajectory and related state curves under varying conditions. The construction of lateral and longitudinal controllers is discussed, which includes a tracking error model derived from the two-degree-of-freedom dynamic model of a two-wheeled vehicle and the application of the Frenet coordinate system transformation. The vehicle tracking performance is regulated by these controllers. Experimental verification on a small intelligent vehicle platform operating on the Ackermann steering principle was conducted. The results confirm the tracking performance of the controllers under different conditions and validate the effectiveness and feasibility of the overall framework of the study.