Objective To systematically evaluate the risk factors for persistent cough after lung resection, providing a theoretical basis for preventing persistent postoperative cough. Methods The Cochrane Library, Web of Science, EMbase, PubMed, Chinese Biomedical Literature Database, Wanfang, CNKI, and VIP databases were searched for studies related to risk factors for persistent cough after lung resection. The search period was from database inception to March 30, 2023. Two researchers independently screened the literature, extracted data, and performed quality assessment. RevMan 5.3 software was used for meta-analysis. Results A total of 17 articles with 3 698 patients were included. Meta-analysis results showed that females [OR=3.10, 95%CI (1.99, 4.81), P<0.001], age [OR=1.72, 95%CI (1.33, 2.21), P<0.001], right-sided lung surgery [OR=2.36, 95%CI (1.80, 3.10), P<0.001], lobectomy [OR=3.40, 95%CI (2.47, 4.68), P<0.001], upper lobectomy [OR=8.19, 95%CI (3.87, 17.36), P<0.001], lymph node dissection [OR=3.59, 95%CI (2.72, 4.72), P<0.001], bronchial stump closure method [OR=5.19, 95%CI (1.79, 16.07), P=0.002], and postoperative gastric acid reflux [OR=6.24, 95%CI (3.27, 11.91), P<0.001] were risk factors for persistent cough after lung resection, while smoking history was a protective factor against postoperative cough [OR=0.59, 95%CI (0.45, 0.77), P<0.001]. In addition, the quality of life score of patients with postoperative cough decreased compared with that before surgery [MD=1.50, 95%CI (0.14, 2.86), P=0.03]. Conclusion Current evidence suggests that females, age, right-sided lung surgery, lobectomy, upper lobectomy, lymph node dissection, bronchial stump closure method (stapler closure), and postoperative gastric acid reflux are independent risk factors for persistent postoperative cough in lung resection patients, while smoking history may be a protective factor against postoperative cough. This provides evidence-based information for clinical medical staff on how to prevent and reduce persistent postoperative cough in patients and improve their quality of life in the future.

Objective To study the relationship between serum visfatin, neutrophil-to-lymphocyte ratio (NLR) and disease severity of coronary heart disease (CHD) in elderly patients (≥90 years old). Methods One hundred and two elderly patients (≥90 years old) with CHD who received coronary CT angiography (CTA) were selected from January 2020 to June 2024. In addition, thirty-five elderly patients (≥90 years old) without CHD who underwent coronary CTA during the same period were included in the control group. The CHD patients were divided into mild group, moderate group and severe group by CT-SYNTAX score. The clinical data and levels of serum visfatin and NLR were compared, and the correlation and diagnostic value of the above levels with disease severity of CHD in elderly patients were analyzed. Results Serum visfatin and NLR were manifested as severe group>moderate group>mild group>control group (P<0.05). Pearson correlation analysis found that serum visfatin and NLR were moderately positively correlated with CT-SYNTAX score (r=0.574, 0.482, P<0.001). Receiver operating characteristics (ROC) curve indicated that the area under the curve (AUC) of combination of serum visfatin and NLR in diagnosing severe lesion in elderly patients (≥90 years old) with CHD was 0.882, which was higher than that of visfatin or NLR alone, and its 95%CI was 0.803-0.938. Conclusion There is a certain correlation between serum visfatin, NLR and disease severity of CHD in elderly patients. The combination of the above indicators has a higher predictive value on severe lesion.

BACKGROUND: Disease-modifying therapies have been approved for the treatment of relapsing multiple sclerosis (RMS). The present study aims to examine the safety of teriflunomide in Chinese patients with RMS. METHODS: This non-randomized, multi-center, 24-week, prospective study enrolled RMS patients with variant (c.421C>A) or wild type ABCG2 who received once-daily oral teriflunomide 14 mg. The primary endpoint was the relationship between ABCG2 polymorphisms and teriflunomide exposure over 24 weeks. Safety was assessed over the 24-week treatment with teriflunomide. RESULTS: Eighty-two patients were assigned to variant ( n  = 42) and wild type groups ( n  = 40), respectively. Geometric mean and geometric standard deviation (SD) of pre-dose concentration (variant, 54.9 [38.0] μg/mL; wild type, 49.1 [32.0] μg/mL) and area under plasma concentration-time curve over a dosing interval (AUC tau ) (variant, 1731.3 [769.0] μg∙h/mL; wild type, 1564.5 [1053.0] μg∙h/mL) values at steady state were approximately similar between the two groups. Safety profile was similar and well tolerated across variant and wild type groups in terms of rates of treatment emergent adverse events (TEAE), treatment-related TEAE, grade ≥3 TEAE, and serious adverse events (AEs). No new specific safety concerns or deaths were reported in the study. CONCLUSION: ABCG2 polymorphisms did not affect the steady-state exposure of teriflunomide, suggesting a similar efficacy and safety profile between variant and wild type RMS patients. REGISTRATION NCT04410965, https://clinicaltrials.gov .
Humans ; Crotonates/adverse effects* ; Toluidines/adverse effects* ; Nitriles ; Hydroxybutyrates ; Female ; Male ; Adult ; ATP Binding Cassette Transporter, Subfamily G, Member 2/genetics* ; Middle Aged ; Multiple Sclerosis, Relapsing-Remitting/genetics* ; Prospective Studies ; Young Adult ; Neoplasm Proteins/genetics* ; East Asian People

Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, treatment, and prognosis prediction of PCa. The introduction of the foundation model has revolutionized the application of AI in medical treatment and facilitated its integration into clinical practice. This review emphasizes the clinical application of AI in PCa by discussing recent advancements from both pathological and imaging perspectives. Furthermore, it explores the current challenges faced by AI in clinical applications while also considering future developments, aiming to provide a valuable point of reference for the integration of AI and clinical applications.
Humans ; Prostatic Neoplasms/diagnosis* ; Male ; Artificial Intelligence ; Deep Learning ; Prognosis

Through a comprehensive analysis combining network pharmacology prediction and transcriptomics, this study systematically explained the multi-target mechanism of Cyanotis arachnoidea(CA) Gel in improving melasma. A melasma model was induced in female SD rats by progesterone injection combined with ultraviolet B(UVB) irradiation for 40 consecutive days, while the blank control group was only fed routinely. After successful model establishment, the rats were randomly divided into five groups and administered different doses of CA ethanol extract gel(high, medium, and low doses) or arbutin Gel(positive control), which were applied once daily for 28 consecutive days. Subsequently, the levels of superoxide dismutase(SOD), malondialdehyde(MDA), and tyrosinase(TYR) in the skin, serum, and liver tissues were measured. Hematoxylin-eosin(HE) staining and Masson-Fontana staining were used to observe the pathological changes in the tissues. Network pharmacology combined with transcriptomics was employed to identify core targets and pathways, and the differential gene expression was validated by quantitative real-time PCR(qPCR). Pharmacodynamic experiments showed that CA Gel significantly increased SOD activity and decreased MDA and TYR levels in the skin, serum, and liver of model rats. It also improved epidermal thickening, inflammatory infiltration, collagen loss, and melanin deposition. Network pharmacology analysis showed that CA mainly regulated core targets such as signal transducer and activator of transcription 3(STAT3), epidermal growth factor receptor(EGFR), and interleukin-6(IL-6), and modulated the phosphatidylinositol 3-kinase(PI3K)-protein kinase B(AKT) and interleukin-17(IL-17) signaling pathways. Transcriptomic analysis showed that CA Gel significantly downregulated the gene expression of heat shock protein 90β family member 1(Hsp90b1), heat shock protein 90α family member 1(Hsp90aa1), and the key steroid synthesis enzyme cytochrome P450 family 17 subfamily A member 1(Cyp17a1), while upregulating thioredoxin 1(Txn1). qPCR results confirmed that CA Gel regulated oxidative stress and inflammatory response by inhibiting the IL-17 signaling pathway and steroid hormone synthesis. This study, for the first time, reveals the molecular mechanism of CA Gel in improving melasma through multi-target synergistic regulation of oxidative stress, inflammatory response, and hormone metabolism pathways, providing a scientific basis for the treatment of pigmentation diseases with traditional Chinese medicine.
Animals ; Rats ; Female ; Rats, Sprague-Dawley ; Network Pharmacology ; Drugs, Chinese Herbal/administration & dosage* ; Melanosis/metabolism* ; Transcriptome/drug effects* ; Humans ; Superoxide Dismutase/genetics* ; Signal Transduction/drug effects* ; Malondialdehyde/metabolism*

Cardiotocography (CTG) is a non-invasive and important tool for diagnosing fetal distress during pregnancy. To meet the needs of intelligent fetal heart monitoring based on deep learning, this paper proposes a TWD-MOAL deep active learning algorithm based on the three-way decision (TWD) theory and multi-objective optimization Active Learning (MOAL). During the training process of a convolutional neural network (CNN) classification model, the algorithm incorporates the TWD theory to select high-confidence samples as pseudo-labeled samples in a fine-grained batch processing mode, meanwhile low-confidence samples annotated by obstetrics experts were also considered. The TWD-MOAL algorithm proposed in this paper was validated on a dataset of 16 355 prenatal CTG records collected by our group. Experimental results showed that the algorithm proposed in this paper achieved an accuracy of 80.63% using only 40% of the labeled samples, and in terms of various indicators, it performed better than the existing active learning algorithms under other frameworks. The study has shown that the intelligent fetal heart monitoring model based on TWD-MOAL proposed in this paper is reasonable and feasible. The algorithm significantly reduces the time and cost of labeling by obstetric experts and effectively solves the problem of data imbalance in CTG signal data in clinic, which is of great significance for assisting obstetrician in interpretations CTG signals and realizing intelligence fetal monitoring.
Humans ; Pregnancy ; Female ; Cardiotocography/methods* ; Deep Learning ; Neural Networks, Computer ; Algorithms ; Fetal Monitoring/methods* ; Heart Rate, Fetal ; Fetal Distress/diagnosis* ; Fetal Heart/physiology*

Retrieving keyframes most relevant to text from small intestine videos with given labels can efficiently and accurately locate pathological regions. However, training directly on raw video data is extremely slow, while learning visual representations from image-text datasets leads to computational inconsistency. To tackle this challenge, a small bowel video keyframe retrieval based on multi-modal contrastive learning (KRCL) is proposed. This framework fully utilizes textual information from video category labels to learn video features closely related to text, while modeling temporal information within a pretrained image-text model. It transfers knowledge learned from image-text multimodal models to the video domain, enabling interaction among medical videos, images, and text data. Experimental results on the hyper-spectral and Kvasir dataset for gastrointestinal disease detection (Hyper-Kvasir) and the Microsoft Research video-to-text (MSR-VTT) retrieval dataset demonstrate the effectiveness and robustness of KRCL, with the proposed method achieving state-of-the-art performance across nearly all evaluation metrics.
Humans ; Video Recording ; Intestine, Small/diagnostic imaging* ; Machine Learning ; Image Processing, Computer-Assisted/methods* ; Algorithms

ObjectiveTo investigate the syndrome evolution patterns， characteristics of the used herbal medicinals， and efficacy variations across different stages of rheumatoid arthritis （RA） progression. MethodsBased on the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine （CERTAIN）， 2,506 RA patients were retrospectively enrolled and categorized into ＜6 months group （166 cases）， 6 months to ＜5 years group （1063 cases）， 5 to ＜20 years group （1067 cases）， and ≥20 years group （210 cases）. Syndromes were differentiated before and after traditional Chinese medicine （TCM） treatment， including damp-heat obstruction， wind-damp obstruction， cold-damp obstruction， blood stasis obstructed in the collaterals， phlegm-stasis obstruction， liver-kidney insufficiency， qi and blood deficiency， and qi-yin deficiency. The syndrome evolution rate was calculated for high-frequency syndromes before and after treatment. Analysis was conducted on top 20 frequently used Chinese herbs at the first diagnosis. Clinical efficacy of the 28-joint disease activity score based on erythrocyte sedimentation rate （DAS28-ESR） and 28-joint disease activity score based on C-reactive protein （DAS28-CRP） before and after treatment were assessed. A multivariate logistic regression analysis was performed to identify factors affecting the efficacy of TCM treatment. ResultsPatients with course of disease shorter than 6 months predominantly presented with cold-dampness obstruction syndrome （49/166， 29.5%）， wind-dampness obstruction syndrome （46/166， 27.7%）， and dampness-heat obstruction syndrome （43/166， 25.9%）. For patients with course of disease logner than 6 months and shorter than 5 years and those within 5 to 20 years， the dominant syndrome was dampness-heat obstruction syndrome （324/1063， 30.5% and 318/1067， 29.8%， respectively）. In patients with disease duration ≥20 years， liver-kidney insufficiency syndrome and dampness-heat obstruction syndrome both predominated， each accounting for 25.24% （53/210）. The syndromes with more than 100 cases before treatment and a syndrome evolution rate greater than 10% after treatment were dampness-heat obstruction （201/738， 27.2%）， liver-kidney insufficiency （119/367， 32.4%）， and phlegm-stasis obstruction syndromes （73/172， 42.4%）. These were classified as high-frequency syndromes. After treatment， damp-heat obstruction syndrome and liver-kidney insufficiency syndrome primarily evolved into wind-damp obstruction syndrome， while phlegm-stasis obstruction syndrome evolved into damp-heat obstruction and cold-damp obstruction syndrome. The top two commonly used Chinese herbs across all groups were Gancao （Radix et Rhizoma Glycyrrhizae） and Baishao （Radix Paeoniae Alba）. In the ＜6 months group and the 6 months to ＜5 years group， high-frequency herbs also included Fangfeng （Radix Saposhnikoviae）， Duhuo （Radix Angelicae Pubescentis）， Chuanxiong （Rhizoma Chuanxiong）， and Qianghuo （Radix et Rhizoma Notopterygii）. In the 5 to ＜20 years group and the ≥20 years group， the usage of Huangqi （Radix Astragali）， Fuling （Poria）， Niuxi （Radix Achyranthis Bidentatae）， and Danggui （Radix Angelicae Sinensis） increased， while the proportion of Fangfeng and Duhuo decreased. After treatment， the DAS28-ESR and DAS28-CRP scores in all groups significantly decreased （P＜0.05）. There were statistically significant differences in clinical efficacy based on DAS28-ESR and DAS28-CRP across all groups （P＜0.01）. Multivariate logistic regression revealed significantly reduced treatment efficacy in the 6 months-5 years group （OR=0.4）， 5~20 years group （OR=0.5）， and ≥20 years group （OR=0.4） compared to the ＜6 months group. ConclusionRA syndromes follow a progression pattern from excess to deficiency， with corresponding transition in herbal usage from pathogen-eliminating to healthy qi-reinforcing approaches. TCM intervention can significantly reduce disease activity of RA， with superior efficacy in patients with disease duration shorter than 6 months.

Ischemic stroke(IS)is a common cerebrovascular disease,and its pathogenesis is closely associated with brain cell death due to insufficiency of cerebral blood supply.In recent years,cell apoptosis has become a research hotspot in the pathogenesis of IS.The B-cell lymphoma-2(Bcl-2)family proteins associated with cell apoptosis are the key regulators for apoptosis and are mainly in-volved in the intrinsic apoptotic pathway,and they regulate cell apoptosis by mediating the two pathways of mitochondrial membrane permeability and Ca2? overload,thereby delaying the progression of IS.Starting from the anti-apoptotic mechanisms of Bcl-2 family proteins,this article summarizes the research advances in traditional Chinese medicine for the prevention and treatment of IS by regu-lating B-cell lymphoma-2 family proteins from the aspects of the structural features of Bcl-2 family proteins,their anti-apoptotic role in IS,and traditional Chinese medicine regulation.The results show that the anti-apoptotic strategies in IS mainly focus on the regula-tion of Bcl-2 and Bax proteins,and monomers of Chinese herbs,traditional Chinese medicine extracts,and compound traditional Chi-nese medicine prescriptions were used for treatment,which further confirms the great potential of traditional Chinese medicine in the prevention and treatment of IS and provides a theoretical basis for future experimental research and clinical treatment.