The prescription of Qidong Yixin oral liquid is derived from the experience of national medical master Ren Jixue in treating viral myocarditis （VMC）. It has the functions of tonifying Qi， nourishing the heart，calming the mind， and relieving palpitations. It is used to treat VMC and angina pectoris of coronary heart disease caused by deficiency of both Qi and Yin. However，the understanding of its efficacy evidence， advantageous aspects， dosage and administration， and medication safety remains insufficient in clinical practice. Therefore，the development of the Expert Consensus on the Clinical Application of Qidong Yixin Oral Liquid （hereinafter referred to as consensus） was initiated. Consensus strictly followed the process and methods of the expert consensus on the clinical application of Chinese patent medicines of the China Association of Chinese Medicine，successively completing multiple tasks such as the consensus project initiation，determination of clinical problems，evidence search and evaluation，formation of recommendation opinions and consensus suggestions，solicitation of opinions，peer review， submission for review and release， and so on. Consensus formed a total of 10 recommendation opinions and 12 consensus suggestions，clarifying the clinical positioning，efficacy advantages，syndrome differentiation，dosage and administration，combination therapy，timing of medication，adverse reactions，contraindications， and precautions of Qidong Yixin oral liquid，indicating that it has good clinical advantages and safety in the treatment of VMC and angina pectoris of coronary heart disease，providing norms and references for physicians to safely and rationally apply Qidong Yixin oral liquid. Consensus was reviewed and approved for release by the Standardization Office of the China Association of Chinese Medicine on December 23， 2024. Standard number：GSCACM-376-2024.

ObjectiveTo investigate the therapeutic mechanism of Xuefu Zhuyutang （XFZYT） for metabolic-associated fatty liver disease （MAFLD） through integrated network pharmacology and animal experiments. MethodsNetwork pharmacology was utilized to predict the core components， key therapeutic targets， and signaling pathways of XFZYT in the treatment of MAFLD. For animal experiments， a rat model of MAFLD was established by feeding a high-cholesterol diet for 4 weeks. Intervention was then administered with low-dose （2 g·kg^-1） and high-dose （4 g·kg^-1） XFZYT for 2 weeks. Biochemical assays were performed to measure the serum levels of aspartate aminotransferase （AST）， alanine aminotransferase （ALT）， total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein （HDL）， and low-density lipoprotein （LDL）. In addition， the activities of superoxide dismutase （SOD） and catalase （CAT） and levels of malondialdehyde （MDA） and glutathione （GSH） in the serum were measured. The same way was adopted to measure the levels of TC and TG in the liver tissue. Enzyme-linked immunosorbent assay （ELISA） was employed to quantify the serum levels of interleukin （IL）-6， IL-1β， and tumor necrosis factor-alpha （TNF-α）. Histopathological evaluations included hematoxylin and eosin （HE） staining for liver tissue morphology， Oil Red O staining for lipid deposition， and dihydroethidium （DHE） probe staining for reactive oxygen species （ROS） levels. Western blot analysis was conducted to assess the protein levels of AMP-activated protein kinase （AMPK）， phosphorylated （p）-AMPK， nuclear factor erythroid 2-related factor 2 （Nrf2）， heme oxygenase-1 （HO-1）， nuclear factor-kappa B （NF-κB）， and p-NF-κB in the liver tissue. Untargeted metabolomics analysis of the serum was performed by liquid chromatography-tandem mass spectrometry （LC-MS/MS）. ResultsNetwork pharmacology analysis predicted 155 potential targets of XFZYT for MAFLD treatment， with core targets including signal transducer and activator of transcription 3 （STAT3）， protein kinase B1 （Akt1）， TNF， and IL-6. Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment primarily implicated the AMPK signaling pathway. Animal experiments demonstrated that compared with the normal group， the model group exhibited dyslipidemia， hepatic function impairment， pronounced hepatic lipid deposition， and inflammatory manifestations， with elevated serum levels of AST， ALT， TC， TG， LDL， and MDA （P<0.05）， reduced HDL and GSH levels plus decreased SOD and CAT activities （P<0.05）， downregulated protein levels of Nrf2， HO-1， and p-AMPK （P<0.05）， and upregulated protein level of p-NF-κB （P<0.05） in the liver tissue. Compared with the model group， XFZYT intervention groups showed significant amelioration of dyslipidemia and hepatic function impairment， markedly reduced hepatic lipid deposition and inflammatory cell infiltration， decreased serum levels of AST， ALT， TC， TG， LDL， and MDA （P<0.05）， increased HDL and GSH levels plus enhanced SOD and CAT activities （P<0.05）， upregulated protein levels of Nrf2， HO-1， and p-AMPK （P<0.05）， and downregulated protein level of p-NF-κB （P<0.05）. Serum metabolomics revealed 511 differentially expressed metabolites （231 upregulated and 280 downregulated） between normal and model groups， while XFZYT groups versus model group showed 94 differential metabolites （51 upregulated and 43 downregulated）. Among them， 11 metabolites displayed the most significant alterations， with enriched pathways including glycerolipid metabolism， cholesterol metabolism， and insulin resistance， multiple of which demonstrated AMPK association. ConclusionXFZYT alleviates MAFLD by regulating the AMPK signaling pathway and associated metabolic networks.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Objective:To explore the therapeutic strategy for laryngeal cysts in infants. Methods:A retrospective analysis of the clinical data of 19 children with laryngeal cysts treated in Kunming Children's Hospital from January 2020 to January 2023. All patients were diagnosed through electronic laryngoscopy examination. Twelve neonates were admitted to the neonatal intensive care unit. Five of them received mechanical ventilation with tracheal intubation before surgery due to severe respiratory distress, and seven received oxygen therapy with a head mask. The remaining seven children were admitted to Department of Otolaryngology Head and Neck Surgery, of which three cases were treated with oxygen therapy through a mask during sleep due to frequent shortness of breath during sleep. All patients underwent low-temperature plasma radiofrequency ablation under general anesthesia to remove the cysts. Results:Three newborns were unable to have their tracheal tubes removed due to complications with pneumonia after surgery, while the rest of the children were able to have their tubes successfully removed after complete anesthesia, and no gastric tubes were placed. All postoperative respiratory difficulties in the children disappeared, and there were no complications such as bleeding, hoarseness, or laryngeal stenosis. Five pediatric patients had incomplete relief of laryngeal ringing symptoms one month after surgery, and electronic laryngoscopy diagnosed laryngeal softening. Regular follow-up is recommended. One child relapsed 4 months after surgery and underwent a follow-up surgery six months later without recurrence. Conclusion:Endoscopic low-temperature plasma radiofrequency ablation is an effective surgical method for treating laryngeal cysts, with a low postoperative recurrence rate. Laryngeal cysts may be accompanied by laryngeal softening, which may be a possible reason for the postoperative symptoms not improving.
Humans ; Retrospective Studies ; Cysts/surgery* ; Laryngeal Diseases/surgery* ; Infant ; Laryngoscopy ; Infant, Newborn ; Male ; Female ; Radiofrequency Ablation

Addressing the enduring challenge of evaluating traditional Chinese medicines (TCMs), the integrated evidence chain-based effectiveness evaluation of TCMs (Eff-iEC) has emerged. This paper explored its capacity through a demonstration study that evaluated the effectiveness evidence of six commonly used anti-hepatic fibrosis Chinese patent medicines (CPMs), including Biejiajian Pill (BP), Dahuang Zhechong Pill (DZP), Biejia Ruangan Compound (BRC), Fuzheng Huayu Capsule (FHC), Anluo Huaxian Pill (AHP), and Heluo Shugan Capsule (HSC), using both Eff-iEC and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system. The recognition of these CPMs within the TCM academic community was also assessed through their inclusion in relevant medical documents. Results showed that the evidence of BRC and FHC received higher assessments in both Eff-iEC and GRADE system, while the assessments for others varied. Analysis of community recognition revealed that Eff-iEC more accurately reflects the clinical value of these CPMs, exhibiting superior evaluative capabilities. By breaking through the conventional pattern of TCMs effectiveness evaluation, Eff-iEC offers a novel epistemology that better aligns with the clinical realities and reasoning of TCMs, providing a coherent methodology for clinical decision-making, new drug evaluations, and health policy formulation.

Peptide-based radiopharmaceuticals targeting integrin α5β1 show promise for precise tumor diagnosis and treatment. However, current peptide-based radioligands that target α5β1 demonstrate inadequate in vivo performance owing to limited tumor retention. The use of PEGylation to enhance the tumor retention of radiopharmaceuticals by prolonging blood circulation time poses a risk of increased blood toxicity. Therefore, a PEGylation strategy that boosts tumor retention while minimizing blood circulation time is urgently needed. Here, we developed a PEGylation-enabled peptide multidisplay platform (PEGibody) for PR_b, an α5β1 targeting peptide. PEGibody generation involved PEGylation and self-assembly. [⁶⁴Cu]QM-2303 PEGibodies displayed spherical nanoparticles ranging from 100 to 200 nm in diameter. Compared with non-PEGylated radioligands, [⁶⁴Cu]QM-2303 demonstrated enhanced tumor retention time due to increased binding affinity and stability. Importantly, the biodistribution analysis confirmed rapid clearance of [⁶⁴Cu]QM-2303 from the bloodstream. Administration of a single dose of [¹⁷⁷Lu]QM-2303 led to robust antitumor efficacy. Furthermore, [⁶⁴Cu]/[¹⁷⁷Lu]QM-2303 exhibited low hematological and organ toxicity in both healthy and tumor-bearing mice. Therefore, this study presents a PEGibody-based radiotheranostic approach that enhances tumor retention time and provides long-lasting antitumor effects without prolonging blood circulation lifetime. The PEGibody-based radiopharmaceutical [⁶⁴Cu]/[¹⁷⁷Lu]QM-2303 shows great potential for positron emission tomography imaging-guided targeted radionuclide therapy for α5β1-overexpressing tumors.

Research on IgG4-related disease (IgG4-RD), an autoimmune condition recognized to be a unique disease entity only two decades ago, has processed from describing patients' symptoms and signs to summarizing its critical pathological features, and further to investigating key pathogenic mechanisms. Challenges in gaining a better understanding of the disease, however, stem from its relative rarity-potentially attributed to underrecognition-and the absence of ideal experimental animal models. Recently, with the development of various high-throughput techniques, "omics" studies at different levels (particularly the single-cell omics) have shown promise in providing detailed molecular features of IgG4-RD. While, the application of omics approaches in IgG4-RD is still at an early stage. In this paper, we review the current progress of omics research in IgG4-RD and discuss the value of machine learning methods in analyzing the data with high dimensionality.
Humans ; Immunoglobulin G4-Related Disease/metabolism* ; Immunoglobulin G/metabolism* ; Machine Learning ; Animals ; Proteomics/methods*

Heart failure (HF) is a common end-stage clinical manifestation of cardiovascular diseases, imposing substantial health-related burdens worldwide. With its high mortality rates and poor long-term prognosis, there is a pressing need for novel therapies. SIRT1, a nicotinamide adenine dinucleotide (NAD⁺)-dependent deacetylase, has anti-cardiovascular aging properties and other cardioprotective effects, attracting much research attention in recent years. In addition, SIRT1 plays an important role in HF pathophysiology. This review summarized the roles of SIRT1 and its activators in HF, the changes of SIRT1 gene expression in cardiac tissues from animal models and HF patients, and the current status of clinical trials investigating SIRT1 activators as potential therapies for HF. This will provide new ideas for further exploration of pathological mechanisms and the development of clinical prevention strategies for HF.
Heart Failure/metabolism* ; Sirtuin 1/genetics* ; Humans ; Animals