ObjectiveTo observe the clinical effectiveness and safety of Qingfei Shenshi Decoction （清肺渗湿汤） combined with western medicine for patients with bronchial asthma of heat wheezing syndrome， and to explore its potential mechanism of action. MethodsEighty-six participants with bronchial asthma of heat wheezing syndrome were randomly divided into treatment group and control group， each group with 43 participants. The control group received conventional western medicine， and the treatment group was additionally administered Qingfei Shenshi Decoction orally on the basis of the control group， 1 dose per day. Both groups were treated for 14 days. The primary outcome measure was clinical effectiveness； secondary outcome measures included traditional Chinese medicine （TCM） syndrome score， asthma control test （ACT） score， pulmonary function indices such as forced expiratory volume in 1 second （FEV₁）， forced vital capacity （FVC）， peak expiratory flow （PEF）， serum inflammatory factor levels including interleukin-4 （IL-4）， tumour necrosis factor-α （TNF-α）， and high-sensitivity C-reactive protein （hs-CRP）， and immune function indices including CD3⁺， CD4⁺， CD8⁺， CD4⁺/CD8⁺. All outcome measures were evaluated before and after treatment. Vital signs were monitored， and electrocardiography， blood routine， urine routine， liver function， and renal function tests were performed before and after treatment. Adverse events and reactions during the study were recorded. ResultsA total of 80 patients completed the trial with 40 in each group. The total clinical effective rate of the treatment group was 97.5% （39/40）， which was significantly higher than that of the control group （85.0%， 34/40， P＜0.05）. After treatment， both groups showed decreased TCM syndrome scores， IL-4， TNF-α， hs-CRP， and CD8⁺ levels， as well as increased ACT scores， CD3⁺， CD4⁺， CD4⁺/CD8⁺， FEV₁， FVC， and PEF levels （P＜0.05 or P＜0.01）. Moreover， the improvements in these indices were more significant in the treatment group than in the control group （P＜0.05 or P＜0.01）. No significant abnormalities in safety indicators were observed in either group， and no adverse events or reactions occurred. ConclusionQingfei Shenshi Decoction combined with conventional western medicine for patients with bronchial asthma of heat wheezing syndrome can effectively improve the clinical symptoms， pulmonary function， and clinical effectiveness， with good safety. Its mechanism may be related to reducing inflammatory factor levels and regulating T lymphocyte subsets to improve immune function.

Achondroplasia (ACH) is a common inherited skeletal dysplasia (inherited dwarfism) that compromises quality of life across the lifespan. In 2021, vosoritide became the first approved precision therapy for ACH and is now available in more than 40 countries. Compared with prior symptomatic measures, vosoritide has demonstrated favorable efficacy and a reassuring safety profile. Nevertheless, existing international ACH guidelines largely emphasize complication management and symptomatic care, and there is no unified consensus on pharmacologic therapy. To address this gap, an international expert group developed the International Consensus Guidelines for the Implementation and Monitoring of Vosoritide Therapy in Patients with Achondroplasia providing systematic recommendations that span the continuum of care - from initial patient contact and pre-treatment assessment to medication counseling, injection training, and long-term outcome monitoring. These recommendations complement and refine current management and nursing protocols for individuals with ACH and offer practical guidance for clinicians across diverse regions. This article highlights key elements of the guideline to provide evidence-based support and clinical direction for healthcare professionals in China treating children with ACH using vosoritide.
Humans ; Achondroplasia/drug therapy* ; Consensus ; Practice Guidelines as Topic ; Child

Olfactory receptors (ORs) form the largest superfamily of G protein-coupled receptors (GPCRs). Traditionally recognized for their role in the nasal olfactory epithelium, where they mediate the sense of smell, accumulating evidence has firmly established their ectopic expression in non-olfactory tissues, including the intestine, lungs, and kidneys. The intestine, as the primary site for nutrient digestion and absorption, harbors a highly complex chemical environment. To adapt to this environment, the gut employs a sophisticated network of “chemosensors” to monitor luminal contents and maintain homeostasis. Among these sensors, intestinal ORs have emerged as crucial functional components, serving as a molecular bridge that connects environmental chemical signals—such as food-derived odorants—to specific physiological responses. This discovery has significantly deepened our understanding of how dietary flavors and compounds influence intestinal physiology at the molecular level. This review systematically summarizes the expression profiles, ligand classification, and biological functions of ORs within the gastrointestinal tract. Studies indicate that intestinal ORs exhibit distinct spatial distribution patterns across different gut segments and display cell-type specificity, particularly within enterocytes and enteroendocrine cells. These receptors function as versatile sensors capable of recognizing a wide variety of ligands, including exogenous dietary components, gut microbiota metabolites such as short-chain fatty acids, and endogenous small molecules like azelaic acid. Upon activation by specific ligands, intestinal ORs trigger intracellular signaling cascades, primarily involving the AC-cAMP-PKA pathway or calcium influx channels. A major focus of this review is to elucidate the molecular mechanisms by which these receptors regulate the secretion of gut hormones. Activation of specific ORs in enteroendocrine cells has been shown to stimulate the release of hormones such as glucagon-like peptide-1 (GLP-1), peptide YY (PYY), and serotonin (5-HT), thereby modulating systemic energy metabolism, glucose homeostasis, and gastrointestinal motility. Furthermore, the review addresses the critical roles of ORs in immune regulation and pathology. Evidence suggests that specific ORs contribute to the maintenance of intestinal immune homeostasis and may offer protection against inflammation. Beyond their involvement in inflammatory responses, ORs such as Olfr78 have been shown to regulate the differentiation and function of intestinal endocrine cells. Similarly, Olfr544 has been demonstrated to alleviate intestinal inflammation by remodeling the gut microbiome and metabolome. These findings collectively suggest that specific ORs hold promise as therapeutic targets for mitigating intestinal inflammation and maintaining gut homeostasis. Additionally, the review explores the emerging role of ORs in cancer. Although OR expression is often downregulated in tumor tissues compared to normal mucosa, activation of specific ORs by certain ligands can inhibit tumor cell proliferation and migration and induce apoptosis via pathways such as MEK/ERK and p38 MAPK. Conversely, other receptors, such as OR7C1, may serve as biomarkers for cancer-initiating cells. In conclusion, intestinal ORs represent a vital component of the gut’s sensory network. The review also discusses the translational potential of these findings. By elucidating the precise pairing relationships between dietary components and specific ORs, novel therapeutic strategies could be developed. Intestinal ORs may thus emerge as promising targets for nutritional and pharmacological interventions in metabolic diseases, inflammatory bowel diseases, and malignancies.

Objective:To assess the status of undernutrition and appropriate catch-up growth in extremely preterm infants within 24 months of corrected age (CA).Methods:A retrospective cohort study was conducted. A total of 422 extremely preterm infants born at Shenzhen Maternity and Child Healthcare Hospital, Women and Children's Medical Center, Southern Medical University from January 2017 to December 2022 and followed up until 24 months of CA were enrolled. The extremely preterm infants were grouped by gestational age at birth (<25, 25-26, 27 weeks), birth weight (<500, 500-749, 750-999,≥1 000 g), weight for gestational age (large for gestational age (LGA), appropriate for gestational age (AGA), small for gestational age (SGA)) and sex. Weight data within 24 months of CA were collected every 3 months. Nutritional insufficiency, growth rate, and achievement of adequate catch-up growth were analyzed during the period from 0 to 24 months of CA. Z-score method was used to analyze data. Fenton 2013 preterm growth charts (Fenton 2013) were used before 40 weeks of corrected gestational age, and World Health Organization child growth standards (2009) fitted Z-scores were applied from 40 weeks of CA. Changes in weight Z-scores of extremely preterm infants from 0 to 24 months of CA were observed and compared, the occurrence of moderate to severe malnutrition and growth retardation was determined, nutritional insufficiency was assessed, and growth rate as well as the achievement of appropriate catch-up growth were analyzed. The Lambda-mu-sigma method combined with the Z-score fitting model was used to fit and analyze the distribution characteristics of weight percentiles in extremely preterm infants. The Chi-square test was used to compare differences among groups.Results:A total of 422 extremely preterm infants were included, with a gestational age at birth of 26.3(25.4, 27.2) weeks and a birth weight of (880±177) g. Among them, 238 were males and 184 were females; 36 cases (8.5%) were LGA, and 16 cases (3.8%) were SGA. During follow-up within 24 month of CA, 89 cases (21.1%) developed moderate to severe malnutrition. When compared separately among different birth weight and gestational age at birth groups, there had both statistically differences in the incidence of moderate to severe malnutrition ( χ2=42.94 and 9.17, both P<0.05). The incidence was the highest in the birth weight of CA<500 g group and the <25 weeks gestational age at birth group, while it was the lowest in the birth weight of CA≥1 000 g group and the 27 weeks gestational age at birth group in their respective groups. Growth retardation occurred in 5.2% (22/422). However, there had statistically differences in the incidence of growth retardation among different birth weight and gestational age at birth groups, in each grouped time interval ( χ2=21.61 and 4.30, both P<0.05). The proportions of rapid growth were relatively high in the 0-3 months and 3-6 months of CA groups, which were 96 cases (27.4%) and 98 cases (26.6%), respectively. Overall, appropriate catch-up growth was achieved in 341 cases (80.8%) from 0 to 24 months of CA. There had statistically differences in the completion rate of appropriate catch-up growth among different birth weight and gestational age at birth groups ( χ2=23.65 and 7.08, both P<0.05). The completion rate was the highest in the birth weight of CA<500 g group and the <25 weeks of gestational age at birth group, while it was the lowest in the birth weight of CA≥1 000 g group and the 27 weeks of gestational age at birth group. Conclusions:The lower the birth weight and gestational age of extremely preterm infants, the higher the incidence of moderate to severe malnutrition and the lower the achievement rate of adequate catch-up growth within 24 months of CA. The period of 0-6 months of CA is the critical window for catch-up in extremely preterm infants.

Objective:To assess the status of undernutrition and appropriate catch-up growth in extremely preterm infants within 24 months of corrected age (CA).Methods:A retrospective cohort study was conducted. A total of 422 extremely preterm infants born at Shenzhen Maternity and Child Healthcare Hospital, Women and Children's Medical Center, Southern Medical University from January 2017 to December 2022 and followed up until 24 months of CA were enrolled. The extremely preterm infants were grouped by gestational age at birth (<25, 25-26, 27 weeks), birth weight (<500, 500-749, 750-999,≥1 000 g), weight for gestational age (large for gestational age (LGA), appropriate for gestational age (AGA), small for gestational age (SGA)) and sex. Weight data within 24 months of CA were collected every 3 months. Nutritional insufficiency, growth rate, and achievement of adequate catch-up growth were analyzed during the period from 0 to 24 months of CA. Z-score method was used to analyze data. Fenton 2013 preterm growth charts (Fenton 2013) were used before 40 weeks of corrected gestational age, and World Health Organization child growth standards (2009) fitted Z-scores were applied from 40 weeks of CA. Changes in weight Z-scores of extremely preterm infants from 0 to 24 months of CA were observed and compared, the occurrence of moderate to severe malnutrition and growth retardation was determined, nutritional insufficiency was assessed, and growth rate as well as the achievement of appropriate catch-up growth were analyzed. The Lambda-mu-sigma method combined with the Z-score fitting model was used to fit and analyze the distribution characteristics of weight percentiles in extremely preterm infants. The Chi-square test was used to compare differences among groups.Results:A total of 422 extremely preterm infants were included, with a gestational age at birth of 26.3(25.4, 27.2) weeks and a birth weight of (880±177) g. Among them, 238 were males and 184 were females; 36 cases (8.5%) were LGA, and 16 cases (3.8%) were SGA. During follow-up within 24 month of CA, 89 cases (21.1%) developed moderate to severe malnutrition. When compared separately among different birth weight and gestational age at birth groups, there had both statistically differences in the incidence of moderate to severe malnutrition ( χ2=42.94 and 9.17, both P<0.05). The incidence was the highest in the birth weight of CA<500 g group and the <25 weeks gestational age at birth group, while it was the lowest in the birth weight of CA≥1 000 g group and the 27 weeks gestational age at birth group in their respective groups. Growth retardation occurred in 5.2% (22/422). However, there had statistically differences in the incidence of growth retardation among different birth weight and gestational age at birth groups, in each grouped time interval ( χ2=21.61 and 4.30, both P<0.05). The proportions of rapid growth were relatively high in the 0-3 months and 3-6 months of CA groups, which were 96 cases (27.4%) and 98 cases (26.6%), respectively. Overall, appropriate catch-up growth was achieved in 341 cases (80.8%) from 0 to 24 months of CA. There had statistically differences in the completion rate of appropriate catch-up growth among different birth weight and gestational age at birth groups ( χ2=23.65 and 7.08, both P<0.05). The completion rate was the highest in the birth weight of CA<500 g group and the <25 weeks of gestational age at birth group, while it was the lowest in the birth weight of CA≥1 000 g group and the 27 weeks of gestational age at birth group. Conclusions:The lower the birth weight and gestational age of extremely preterm infants, the higher the incidence of moderate to severe malnutrition and the lower the achievement rate of adequate catch-up growth within 24 months of CA. The period of 0-6 months of CA is the critical window for catch-up in extremely preterm infants.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

The present study employed UPLC-MS/MS to analyze and identify compounds in the raw powder of Tongluo Shenggu capsules. An HPLC method for the determination of vitexin content was established. The analysis of this drug was performed on a 30 ℃ thermostatic Acquity UPLC® BEH C18 (2.1 mm×100 mm,1.7 μm) column, with the mobile phase comprising 0.2% formic acid-methanol flowing at 0.3 mL /min in a gradient elution manner. Mass spectrometry was detected by ESI sources in both positive and negative ion modes for qualitative identification of chemical constituents. 12 flavonoid and 3 stilbenes compounds in the raw powder of Tongluo Shenggu capsules were successfully identified. Additionally, an HPLC method for the determination of vitexin content was established using a XBridge C18 column (4.6 mm × 250 mm, 5 µm) with a mobile phase of 0.05% glacial acetic acid in methanol for gradient elution, at a column temperature of 30 °C, a flow rate of 1.0 mL/min, and an injection volume of 20 μL. The method demonstrated good linearity in the concentration range of 10 µg/mL to 40 µg/mL (R=1.000) with an average recovery rate of 96.7%. The establishment of these methods provides a scientific basis for the quality control and development of the raw powder of Tongluo Shenggu capsules.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

INTRODUCTION: Obstructive sleep apnoea (OSA) is common in Singapore, with moderate to severe OSA affecting around 30% of residents. These consensus statements aim to provide scientifically grounded recommendations for the management of OSA, standar-dise the management of OSA in Singapore and promote multidisciplinary collaboration. METHOD: An expert panel, which was convened in 2024, identified several areas of OSA management that require guidance. The expert panel reviewed the current literature and developed consensus statements, which were later independently voted on using a 3-point Likert scale (agree, neutral or disagree). Consensus (total ratings of agree and neutral) was set a priori at ≥80% agreement. Any statement not reaching consensus was excluded. RESULTS: The final consensus included 49 statements that provide guidance on the screening, diagnosis and management of adults with OSA. Additionally, 23 statements on the screening, diagnosis and management of paediatric OSA achieved consensus. These 72 consensus statements considered not only the latest clinical evidence but also the benefits and harms, resource implications, feasibility, acceptability and equity impact of the recommendations. CONCLUSION The statements presented in this paper aim to guide clinicians based on the most updated evidence and collective expert opinion from sleep specialists in Singapore. These recommendations should augment clinical judgement rather than replace it. Management decisions should be individualised, taking into account the patient's clinical characteristics, as well as patient and caregiver concerns and preferences.
Humans ; Sleep Apnea, Obstructive/diagnosis* ; Singapore ; Consensus ; Adult