Rui Zhang’s research while affiliated with Guilin University of Technology and other places

Objectives Super‐resolution ultrasound microvascular imaging (SRUS) has emerged as a noninvasive technology capable of visualizing the microvasculature with exceptional spatial resolution, surpassing the acoustic diffraction limit. This study aims to assess the potential of SRUS in staging liver fibrosis by evaluating its diagnostic performance against ultrasound viscosity imaging. Methods Liver fibrosis was induced by carbon tetrachloride (CCl 4 ) in 30 mice. The mice were evenly distributed across five stages (6 mice per stage), categorized from F0 (no fibrosis) to F4 (cirrhosis) based on the extent of collagen deposition. SRUS microvascular imaging and ultrasound viscosity imaging were compared for their efficacy in detecting liver fibrosis stages. Immunohistochemistry and histopathological analyses were conducted to correlate vessel density and collagen deposition. Results SRUS effectively detected microvascular changes across all fibrosis stages. Significant vessel diameter enlargement was observed at early stages (F1), with further increases in advanced stages (F3–F4). Vessel density significantly decreased in later stages, indicating compromised angiogenesis. Ultrasound viscosity imaging showed marked viscoelastic reductions in fibrosis but lacked sensitivity in early‐stage detection. SRUS parameters exhibited strong correlations with histological findings, underscoring their potential diagnostic value. Receiver operating characteristic (ROC) curve analysis further demonstrated the superior sensitivity of SRUS (89.59% [95% confidence interval (CI): 84.87–92.96%]), particularly in distinguishing early‐stage fibrosis (F0–F1) from advanced stages (F2–F4) (area under the curve [AUC] = 0.9610, 95% CI: 0.9449–0.9771; P < .001). Conclusions SRUS microvascular imaging is a promising adjunct to traditional elastography, offering enhanced sensitivity for early‐stage liver fibrosis detection. It provides critical insights into microcirculatory dysfunction, complementing stiffness measurements and aiding in accurate diagnosis.

This study proposes an innovative two-step synthesis strategy to significantly enhance the performance of sodium-ion batteries by developing low-defect, low water content iron-based Prussian blue (PB) materials. Addressing the limitations of traditional co-precipitation methods—such as rapid reaction rates leading to excessive crystal defects and interstitial water content—the research team introduced a synergistic approach combining non-aqueous phase precursor synthesis and controlled water-concentration secondary crystallization. The process involves preparing a PB precursor in a glycerol system, followed by secondary crystallization in a water-/ethanol-mixed solvent with a precisely regulated water content, achieving the dual objectives of water content reduction and crystal morphology optimization. Systematic characterization revealed that water concentration during secondary synthesis critically influences the material’s crystal structure, morphological features, and water content. The optimized PB50-24 material exhibited a highly regular cubic morphology with a sodium content of 9.2% and a remarkably low interstitial water content of 2.1%. Electrochemical tests demonstrated outstanding performance—an initial charge–discharge capacity of 120 mAh g⁻¹ at a 1C rate, the retention of 105 mAh g⁻¹ after 100 cycles, and a high rate capability of 86 mAh g⁻¹ at 10C, representing significant improvements in cycling stability and rate performance over conventional methods. This work not only establishes a cost-effective, scalable synthesis pathway for Prussian blue materials but also provides theoretical guidance for developing other metal-based Prussian blue analogs, offering substantial value for advancing the industrial application of sodium-ion batteries in next-generation energy storage systems.

Background Acute intermittent porphyria (AIP) is a rare metabolic disorder resulting from defects in the heme biosynthesis pathway, often presenting with non-specific symptoms such as abdominal pain, seizures, and neuropsychiatric disturbances. Diagnosis is challenging due to the overlap of symptoms with other conditions, and early recognition is critical for effective treatment. Case Presentation A 24-year-old female presented with a 6-day history of persistent lower abdominal pain and generalized tonic-clonic seizures, following the consumption of seafood. Neuroimaging revealed white matter hyperintensities, and urine analysis showed dark red discoloration, suggestive of porphyria. Genetic testing confirmed a novel c.499-1_514del mutation in the HMBS gene, diagnosing AIP. The patient was treated with intravenous glucose, heme arginate, and anticonvulsants. Symptom resolution was noted within days, and follow-up MRI showed significant improvement. Conclusion This case underscores the importance of early diagnosis and management in AIP. Genetic testing plays a crucial role in confirming the diagnosis, especially in atypical cases. Timely intervention with glucose and heme arginate, combined with supportive care, led to rapid symptom resolution, reinforcing the reversibility of AIP-associated neuroimaging changes. Clinicians should maintain a high index of suspicion for AIP in patients with unexplained abdominal and neurological symptoms to prevent long-term complications.

The study aimed to diagnose of Alzheimer's Disease (AD) and Frontotemporal Dementia (FTD) based on brain functional connectivity features extracted via resting-state Electroencephalographic (EEG) signals, and subsequently developed a convolutional neural network (CNN) model, Coherence-CNN, for classification. First, a publicly available dataset of EEG resting state-closed eye recordings containing 36 AD subjects, 23 FTD subjects, and 29 cognitively normal (CN) subjects was used. Then, coherence metrics were utilized to quantify brain functional connectivity, and the differences in coherence between groups across various frequency bands were investigated. Next, spectral clustering was used to analyze variations and differences in brain functional connectivity related to disease states, revealing distinct connectivity patterns in brain electrode position maps. The results demonstrated that brain functional connectivity between different regions was more robust in the CN group, while the AD and FTD groups exhibited various degrees of connectivity decline, reflecting the pronounced differences in connectivity patterns associated with each condition. Furthermore, Coherence-CNN was developed based on CNN and the feature of coherence for three-class classification, achieving a commendable accuracy of 94.32% through leave-one-out cross-validation. This study revealed that Coherence-CNN demonstrated significant performance for distinguishing AD, FTD, and CN groups, supporting the disorder of brain functional connectivity in AD and FTD.

This study proposes an innovative two-step synthesis strategy to significantly enhance the performance of sodium-ion batteries by developing low-defect, low-water-content iron-based Prussian blue (PB) materials. Addressing the limitations of traditional co-precipitation methods—such as rapid reaction rates leading to excessive crystal defects and interstitial water content—the research team introduced a synergistic approach combining non-aqueous phase precursor synthesis and controlled water-concentration secondary crystallization. The process involves preparing a PB precursor in a glycerol system, followed by secondary crystallization in a water/ethanol mixed solvent with precisely regulated water content, achieving dual objectives of water-content reduction and crystal morphology optimization. Systematic characterization revealed that water concentration during secondary synthesis critically influences the materials crystal structure, morphological features, and water content. The optimized PB50-24 material exhibited a highly regular cubic morphology with a sodium content of 9.2% and a remarkably low interstitial water content of 2.1%. Electrochemical tests demonstrated outstanding performance: an initial charge-discharge capacity of 120 mAh g⁻&sup1; at 1C rate, retention of 105 mAh g⁻&sup1; after 100 cycles, and a high-rate capability of 86 mAh g⁻&sup1; at 10C, representing significant improvements in cycling stability and rate performance over conventional methods. This work not only establishes a cost-effective, scalable synthesis pathway for Prussian blue materials but also provides theoretical guidance for developing other metal-based Prussian blue analogs, offering substantial value for advancing the industrial application of sodium-ion batteries in next-generation energy storage systems.

The electrophysiological findings have shown that epileptiform spikes triggering sleep spindles within 1[Formula: see text]s across multiple channels are commonly observed during sleep in focal epilepsy (FE). Such spatio-temporal couplings of spikes and spindles (STCSSs) are defined as a kind of pathological waves, and frequent emergence of them may cause the degradation of cognitive function for FE patients. However, the neural mechanisms underlying STCSSs are not well understood. To this end, this work first develops a neural mass network model for focal epilepsy (FE-NMNM) with multiple thalamocortical columns being its nodes and the long-range synaptic interactions of thalamocortical columns being its edges, where each thalamocortical column is extended on the basis of Costa model and then they are connected through excitatory synapses between pyramidal cells. Then, how the cortico-cortical connectivity affects the evolution of STCSSs across the network is especially discussed by simulations in two cases, where the inter-ictal state and the ictal state are considered separately. Simulation results demonstrate that: (1) the more STCSSs occur in a more extensive area when the cortico-cortical connectivity becomes stronger, and the significant increase of coupling discharges is attributed to the presence of abundant spikes; (2) when the connectivity is excessively strong, the cortical hyperexcitability will happen, thereby inducing massive spike discharges which may further inhibit the occurrence of spindles, and hence, resulting in the disappearance of STCSSs. The obtained results provide a mechanistic insight into STCSSs, and suggest that such coupling patterns could reflect widespread network dysfunction in FE, thereby potentially advancing therapeutic strategies for FE.