Publications by authors named "Guangzhong Yang"

Triple-negative breast cancer (TNBC), characterized by its aggressive metastatic propensity and lack of effective targeted therapeutic options, poses a major challenge in oncological management. A proof-of-concept neoadjuvant strategy aimed at inhibiting TNBC tumor growth and mitigating metastasis through a localized delivery of chemotherapeutics is reported in this paper. This approach addresses the limitations in payload capacity and stimuli responsiveness commonly associated with microrobotics in oncology.

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Photoacoustic microscopy (PAM) has gained increasing popularity in biomedical imaging, providing new opportunities for tissue monitoring and characterization. With the development of deep learning techniques, convolutional neural networks have been used for PAM image resolution enhancement and denoising. However, there exist several inherent challenges for this approach.

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Article Synopsis
  • Endoluminal and endocavitary interventions are gaining popularity for early intervention and precision surgery, pushing the need for advanced robotic technology.
  • A new submillimeter-scale fiber robot (~1 mm) is designed for both macro and micro manipulations, using thin optical fibers for actuation and light transmission.
  • This robot can perform precise movements across different scales, achieving accuracy in micro operations during in vivo animal studies.
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Seven undescribed iridoids, identified as valeriridoids A-E (compounds 1, 5, 18, 19a, 19b, 20a, and 20b), were isolated from the roots and rhizomes of Valeriana officinalis L., along with sixteen known iridoids and nine known lignans. The structures were elucidated using NMR and MS spectroscopy, and the absolute configurations of the undescribed iridoids were determined through ECD calculations.

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Purposes: To enhance the functional capability of MRI, this study aims to develop a novel MR elastography (MRE) sequence that achieves rapid acquisition without distortion artifacts.

Methods: A displacement-encoded stimulated echo (DENSE) with multiphase acquisition scheme was used to capture wave images. A center-out golden-angle stack-of-stars sampling pattern was introduced for improved SNR and data incoherence.

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  • * Magnetic resonance imaging (MRI) is a promising radiation-free option for cardiovascular interventions but currently lacks compatible instruments for effective use.
  • * The introduction of a new thermal drawing platform allows for the rapid development of affordable MRI-compatible catheter systems, demonstrating similar mechanical properties to existing devices and paving the way for innovation in catheter technologies for cardiovascular interventions.
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Background: Chromosome 1q21 aberrations are one of the most common cytogenetic abnormalities in patients with multiple myeloma (MM). However, the prognostic value remains controversial. This study aimed to determine the prognostic value of numerical abnormalities of chromosome 1q21 for newly diagnosed patients with MM patients in Chinese population.

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  • Implantable devices for brain-machine interfaces and neurological disorders are growing rapidly, but concerns exist about trauma and long-term safety.
  • This study introduces titanium oxynitride (TiNO) nanofilm as a biosensor that can detect acute inflammatory responses in the brain during micro-neuro-implantation.
  • The TiNO-SPR biosensor is highly sensitive to the inflammatory cytokine interleukin-6, allowing for quick assessments of inflammation during surgeries, which helps improve the safety of invasive procedures.
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Piperine, a natural amide isolated from the genus of , serves as a pharmacophore in medicinal chemistry. In this study, we synthesised and evaluated 18 novel piperine-acylhydrazone hybrids (-) for their antiproliferative activities . The structures of these hybrids were validated using H,C NMR, and HR-ESI-MS data.

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Background And Purpose: Preoperative assessment of meningioma consistency is beneficial for optimizing surgical strategy and prognosis of patients. We aim to develop a noninvasive prediction model for meningioma consistency utilizing MR elastography and DTI.

Materials And Methods: Ninety-four patients (52 ± 22 years old, 69 women, 25 men) diagnosed with meningioma were recruited in the study.

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Unlabelled: Magnetic resonance elastography (MRE) of brain relies on inducing and measuring shear waves in the brain. However, studies have shown vibration could induce changes in cerebral blood flow (CBF), which has a modulation effect and can affect the biomechanical properties measured.

Objective: This work demonstrates the initial prototype of the indirect excitation method, which can generate shear waves in the brain with minimal changes in CBF.

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Six undescribed triterpenoid saponins, namely aescuchinosides A-F, along with seven known triterpenoid saponins, were isolated from the seeds of Aesculus chinensis. Barrigenol-like triterpenoids (BATs) constitute these saponins. Protoaescigenin serves as their aglycone, with various oxygen-containing groups, including acetyl, isobutyryl, tigloyl, and angeloyl groups situated at C-21, C-22, and C-28.

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Background: Different MR elastography (MRE) systems may produce different stiffness measurements, making direct comparison difficult in multi-center investigations.

Purpose: To assess the repeatability and reproducibility of liver stiffness measured by three typical MRE systems.

Study Type: Prospective.

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Cerebral aneurysms and brain tumors are leading life-threatening diseases worldwide. By deliberately occluding the target lesion to reduce the blood supply, embolization has been widely used clinically to treat cerebral aneurysms and brain tumors. Conventional embolization is usually performed by threading a catheter through blood vessels to the target lesion, which is often limited by the poor steerability of the catheter in complex neurovascular networks, especially in submillimeter regions.

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One previously undescribed naphthoquinone-benzisochromanquinone dimer berpolydiquinone A (), along with two previously undescribed naphthoquinone-anthraquinone dimers berpolydiquinones B and C (-), and one previously undescribed dimeric naphthalene berpolydinaphthalene A (), were isolated from the stems and leaves of var. leioclada. The chemical structures of these compounds were determined using high-resolution electrospray ionization mass spectroscopy (HR-ESI-MS), spectroscopic data, the exciton chirality method (ECM), and quantum chemical calculation.

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Precise manipulation of flexible surgical tools is crucial in minimally invasive surgical procedures, necessitating a miniature and flexible robotic probe that can precisely direct the surgical instruments. In this work, we developed a polymer-based robotic fiber with a thermal actuation mechanism by local heating along the sides of a single fiber. The fiber robot was fabricated by highly scalable fiber drawing technology using common low-cost materials.

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Drug delivery to the brain is crucial in the treatment for central nervous system disorders. While significant progress has been made in recent years, there are still major challenges in achieving controllable drug delivery to the brain. Unmet clinical needs arise from various factors, including controlled drug transport, handling large drug doses, methods for crossing biological barriers, the use of imaging guidance, and effective models for analyzing drug delivery.

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Three new anthraquinone-benzisochromanquinone dimers polyphylldiquinones A-C (), along with three known analogs floribundiquinone A-B (-) and 7-dehydroxyventiloquinone H (), were isolated from the stems and leaves of . The chemical structures and absolute configurations of these compounds were determined using HR-ESI-MS, spectroscopic data, and electronic circular dichroism. Notably, compounds (-) are dimeric quinones that share the same benzisochromanquinone moiety, specifically identified as 7-dehydroxyventiloquinone H (), which was the first time to report as a natural product.

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Accurate navigation and targeting are critical for neurological interventions including biopsy and deep brain stimulation. Real-time image guidance further improves surgical planning and MRI is ideally suited for both pre- and intra-operative imaging. However, balancing spatial and temporal resolution is a major challenge for real-time interventional MRI (i-MRI).

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Motor Imagery (MI) Electroencephalography (EEG) is one of the most common Brain-Computer Interface (BCI) paradigms that has been widely used in neural rehabilitation and gaming. Although considerable research efforts have been dedicated to developing MI EEG classification algorithms, they are mostly limited in handling scenarios where the training and testing data are not from the same subject or session. Such poor generalization capability significantly limits the realization of BCI in real-world applications.

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Article Synopsis
  • Triterpenoid saponins have shown potential for relieving inflammatory pain, primarily by enhancing inhibitory synaptic responses and affecting capsaicin receptors.
  • The study utilized patch clamp techniques and animal experiments to identify active components and evaluate their analgesic effects.
  • Findings indicate that these saponins can improve pain relief through various mechanisms, highlighting the multi-faceted approach of traditional Chinese medicine in targeting pain management.
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Ethnopharmacological Relevance: Ludwigia hyssopifolia (LH), an ethnopharmacological herb used in Guangxi Zhuang medicine, is known for its extensive therapeutic use in treating throat disorders. The anti-laryngeal-cancer benefits of the ethyl acetate and petroleum ether fractions of the ethanolic extracts of LH have been shown in our prior cell-based research. Nevertheless, the specific impacts and underlying processes by which LH combats throat cancer effects have not been fully understood.

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  • Open international challenges are now the main way to evaluate algorithms for computer vision and image analysis, especially in pulmonary airway segmentation.
  • A new challenge, ATM'22, was organized to provide a large-scale dataset of 500 annotated CT scans to help improve algorithm performance in this area.
  • The results showed that deep learning models that enhanced topological continuity performed best, and the challenge offers an open-call design for accessing data and evaluations.
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