Chronic post-surgical pain (CPSP) is a common long-term complication following lung surgery. Its high incidence significantly impacts patients’ quality of life and functional recovery, and imposes a substantial socioeconomic burden. This consensus aims to systematically establish a standardized integrated Chinese and Western medicine diagnostic and treatment framework for chronic post-lung surgery pain (CPLSP). Based on the latest domestic and international evidence-based medical research and multidisciplinary clinical experience, the working group comprehensively elaborates on core issues regarding CPLSP, including its definition, epidemiology, pathogenesis, clinical assessment, Western medical treatment, traditional Chinese medicine (TCM) treatment, and integrated strategies. The consensus emphasizes a patient-centered approach, adhering to the principles of multimodality, individualization, and stepwise management, highlighting the synergistic advantages of integrating Chinese and Western medicine throughout the entire perioperative management cycle encompassing "perioperative anti-inflammation, acute analgesia, and chronic rehabilitation." Through systematic literature retrieval and evidence integration, a total of 9 core recommendations were established to provide scientifically sound and clinically practical guidance.

Objective: This prospective study evaluated the feasibility of chemical exchange saturation transfer (CEST) MRI for assessing disease activity in thyroid-associated ophthalmopathy (TAO). Materials and Methods: A total of 88 patients with active TAO, 76 with inactive TAO, and 30 healthy controls were enrolled. CEST MRI-derived magnetization transfer ratio (MTR) and MTR asymmetry (MTRasym) at 1 ppm, 2 ppm, and 3.5 ppm were calculated. Clinical data, MTR, and MTRasym values for the extraocular muscles (one representative muscle per eye, yielding two measurements per participant) were compared among the groups. Spearman’s correlation was used to examine associations between imaging parameters and the clinical activity score (CAS) in patients with TAO. Logistic regression analysis was used to identify independent associations between imaging parameters and disease activity in patients with TAO (active vs. inactive). Receiver operating characteristic (ROC) analysis was conducted to evaluate the diagnostic performance for discriminating active from inactive TAO. Results: Patients with active TAO showed lower MTR values (P < 0.001) and higher MTRasym (1 ppm), MTRasym (2 ppm), and MTRasym (3.5 ppm) (all P < 0.001) compared with those with inactive TAO. MTR was negatively correlated with CAS (r = -0.402; P < 0.001), while MTRasym (1 ppm), MTRasym (2 ppm), and MTRasym (3.5 ppm) were positively correlated with CAS (r = 0.369, 0.350, and 0.349, respectively;all P < 0.001). MTR and MTRasym (1 ppm) were independently associated with TAO activity. The areas under the ROC curve (AUCs) for MTR and MTRasym (1 ppm) in discriminating active from inactive TAO were 0.772 and 0.730, respectively. Combining MTR with MTRasym (1 ppm) significantly improved diagnostic performance compared with either parameter alone, achieving an AUC of 0.805 (P = 0.029 and 0.001). Conclusion MTR and MTRasym (1 ppm) were independently associated with TAO activity. Their combination further enhanced diagnostic performance in distinguishing active from inactive TAO, suggesting their potential as quantitative imaging biomarkers to guide treatment in patients with TAO.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective To analyze the correlation between cardiac function and degree of coronary artery lesion in elderly patients with coronary heart disease. Methods A total of 110 elderly patients with coronary heart disease and 30 elderly people without coronary heart disease (non-coronary heart disease group) in the Third People's Hospital of Chengdu were selected for the study. Based on Gensini score, the patients with coronary heart disease were classified into mild, moderate and severe lesion groups. The echocardiographic indicators and myocardial injury indicators [cardiac troponin I (cTnI), creatine kinase (CK), creatine kinase isoenzyme (CK-MB)] were compared among the groups. The correlation between cardiac function indicators and degree of coronary artery lesion and the evaluation value of various indicators on severe coronary artery lesion were analyzed. Results The left ventricular ejection fraction (LVEF) was represented as severe lesion groupmoderate lesion group>mild lesion group> non-coronary heart disease group (P<0.05). LVEF showed a negative correlation with degree of coronary artery lesion (P<0.05), while LVEDD, LVESD, cTnI, CK and CK-MB all exhibited positive correlations with degree of coronary artery lesion (P<0.05). The combined detection of the above indicators demonstrated superior evaluation efficiency on severe coronary artery lesion compared to any single indicator (P<0.05). Conclusion There is a significant correlation between cardiac function and degree of coronary artery lesion in elderly patients with coronary heart disease. Comprehensive evaluation of these indicators is conducive to clinical disease risk stratification and individualized treatment.

Despite that sleep disturbance and poor neurocognitive performance are common complaints among coronavirus disease 2019 (COVID-19) survivors, few studies have focused on the effect of post-COVID-19 sleep disturbance (PCSD) on cognitive function. This study aimed to identify the impact of PCSD on neurocognitive function and explore the associated risk factors for the worsening of this condition. This cross-sectional study was conducted via the web-based assessment in Chinese mainland. Neurocognitive function was evaluated by the modified online Integrated Cognitive Assessment (ICA) and the Number Ordering Test (NOT). Propensity score matching (PSM) was utilized to match the confounding factors between individuals with and without PCSD. Univariate analyses were performed to evaluate the effect of PCSD on neurocognitive function. The risk factors associated with worsened neurocognitive performance in PCSD individuals were explored using binary logistic regression. A total of 8692 individuals with COVID-19 diagnosis were selected for this study. Nearly half (48.80%) of the COVID-19 survivors reported sleep disturbance. After matching by PSM, a total of 3977 pairs (7954 individuals in total) were obtained. Univariate analyses revealed that PCSD was related to worse ICA and NOT performance (P<0.05). Underlying disease, upper respiratory infection, loss of smell or taste, severe pneumonia, and self-reported cognitive complaints were associated with worsened neurocognitive performance among PCSD individuals (P<0.05). Furthermore, aging, ethnicity (minority), and lower education level were found to be independent risk factors for worsened neurocognitive performance in PCSD individuals (P<0.05). PCSD was related to impaired neurocognitive performance. Therefore, appropriate prevention and intervention measures should be taken to minimize or prevent PCSD and eliminate its potential adverse effect on neurocognitive function.
Humans ; COVID-19/epidemiology* ; Male ; Female ; Sleep Wake Disorders/epidemiology* ; Propensity Score ; Middle Aged ; Cross-Sectional Studies ; Adult ; SARS-CoV-2 ; Aged ; Risk Factors ; China/epidemiology* ; Cognition ; Cognitive Dysfunction/etiology* ; Neuropsychological Tests

Objective:To explore the feasibility of the multiple-choice auditory graphical interactive check（MAGIC） screening module in childhood hearing screening in children aged 3 to 6 years. Methods:A hearing screening was conducted on 366 children（732 ears） aged between 3 and 6 years. The screening methods included MAGIC, DPOAE, and acoustic immittance.The cooperation, screening time, pass rate, and correlation of the three screening methods were compared. Results:There was a statistically significant difference in the degree of cooperation among the three screeningmethods（P=0.004）.The MAGIC pure tone screening method was 98.6%, the screening DPOAE was 99.5%,and the acoustic immittance screening was 100%. For the screening duration, the MAGIC pure tone screening method was（116.3±59.1）s, the screening DPOAE was（27.2±19.7）s, and the acoustic impedance screening was（24.6±14.6）s. There was a significant statistical significance differences among the three or two groups（P<0.01）. The passing rates of MAGIC pure tone screening,screening DPOAE and acoustic immittance screening were 64.7%, 65.4%, and 69.3%, respectively, and there was no significant statistical difference among the three or two groups（P>0.05）. There was no significant difference between MAGIC pure tone screening method and screening DPOAE（P=0.827>0.05）, and acoustic impedance（P=0.653>0.05）, while the difference between screening DPOAE and acoustic impedance was statistically significant（P<0.01）. Conclusion:MAGIC pure sound screening method has good feasibility, can comprehensively reflect the hearing level of screened children, and can be promoted for hearing screening in children aged between 3 and 6 years.
Humans ; Child, Preschool ; Child ; Female ; Male ; Audiometry, Pure-Tone ; Mass Screening/methods* ; Feasibility Studies ; Acoustic Impedance Tests/methods* ; Hearing Loss/diagnosis* ; Hearing Tests/methods*

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

Compounds isolated from Epimedium include the total flavonoids of Epimedium , icariin, and its metabolites (icaritin, icariside I, and icariside II), which have similar molecular structures. Modern pharmacological research and clinical practice have proved that Epimedium and its active components have a wide range of pharmacological effects, especially in improving sexual function, hormone regulation, anti-osteoporosis, immune function regulation, anti-oxidation, and anti-tumor activity. To date, we still need a comprehensive source of knowledge about the pharmacological effects of Epimedium and its bioactive compounds on the male reproductive system. However, their actions in other tissues have been reviewed in recent years. This review critically focuses on the Epimedium , its bioactive compounds, and the biochemical and molecular mechanisms that modulate vital pathways associated with the male reproductive system. Such intrinsic knowledge will significantly further studies on the Epimedium and its bioactive compounds that protect the male reproductive system and provide some guidances for clinical treatment of related male reproductive disorders.
Male ; Epimedium/chemistry* ; Humans ; Genitalia, Male/drug effects* ; Flavonoids/therapeutic use* ; Animals

This study explores whether the current external quality assessment (EQA) level and acceptable bias for basic semen analysis in China are clinically useful. We collected data of semen EQA from Andrology laboratories in the Hunan Province (China) in 2022 and searched for data in the published literature from January 2000 to December 2023 in China. On the basis of these data, we analyzed the coefficients of variation and acceptable biases of different quality control materials for basic semen analysis through robust statistics. We compared these findings with quality specifications based on biological variation from optimal, desirable, and minimum levels of bias to seek a unified and more suitable semen EQA bias evaluation standard for China's national conditions. Different sources of semen quality control material exhibited considerable variation in acceptable biases among laboratories, ranging from 8.2% to 56.9%. A total of 50.0% of the laboratories met the minimum quality specifications for progressive motility (PR), whereas 100.0% and 75.0% of laboratories met only the minimum quality specifications for sperm concentration and total motility (nonprogressive [NP] + PR), respectively. The Z value for sperm concentration and PR+NP was equivalent to the desirable performance specification, whereas the Z value for PR was equivalent only to the minimum performance specification. This study highlights the feasibility of operating external quality assessment schemes for basic semen analysis using quality specifications based on biological variation. These specifications should be unified among external quality control (EQC) centers based on biological variation.
Semen Analysis/standards* ; Humans ; China ; Male ; Quality Control ; Sperm Motility ; Sperm Count/standards*

Eight previously undescribed lanostane triterpenoids, including five nortriterpenoids with 26 carbons, ganothenoids A-E (1-5), and three lanostanoids, ganothenoids F-H (6-8), along with 24 known ones (9-32), were isolated from the fruiting bodies of Ganodrma theaecolum. The structures of the novel compounds were elucidated using comprehensive spectroscopic methods, including electronic circular dichroism (ECD) and nuclear magnetic resonance (NMR) calculations. Compounds 1-32 were assessed for their neuroprotective effects against H₂O₂-induced damage in human neuroblastoma SH-SY5Y cells, as well as their inhibitory activities against protein tyrosine phosphatase 1B (PTP1B) and α-glucosidase. Compound 4 demonstrated the most potent neuroprotective activity against H₂O₂-induced oxidative stress by suppressing G₀/G₁ phase cell cycle arrest, reducing reactive oxygen species (ROS) levels, and inhibiting cell apoptosis through modulation of B-cell lymphoma 2 protein (Bcl-2) and Bcl-2 associated X-protein (Bax) protein expression. Compounds 26, 12, and 28 exhibited PTP1B inhibitory activities with IC₅₀ values ranging from 13.92 to 56.94 μmol·L^-1, while compound 12 alone displayed significant inhibitory effects on α-glucosidase with an IC₅₀ value of 43.56 μmol·L^-1. Additionally, enzyme kinetic analyses and molecular docking simulations were conducted for compounds 26 and 12 with PTP1B and α-glucosidase, respectively.
Humans ; Fruiting Bodies, Fungal/chemistry* ; Triterpenes/isolation & purification* ; Neuroprotective Agents/isolation & purification* ; Protein Tyrosine Phosphatase, Non-Receptor Type 1/metabolism* ; Ganoderma/chemistry* ; Apoptosis/drug effects* ; Hypoglycemic Agents/isolation & purification* ; Molecular Structure ; alpha-Glucosidases/metabolism* ; Cell Line, Tumor ; Reactive Oxygen Species/metabolism* ; Oxidative Stress/drug effects* ; Hydrogen Peroxide/toxicity* ; Molecular Docking Simulation