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.

Kynurenine pathway (KP) is a major catabolic route of tryptophan, generating a series of bioactive metabolites including kynurenine, kynurenic acid (KA), quinolinic acid, and 3-hydroxykynurenine. Beyond its fundamental role in amino acid metabolism, KP exerts critical regulatory functions in neurodevelopment, synaptic plasticity, and immune modulation. Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition with onset in early childhood, characterized by persistent deficits in social communication and restricted, repetitive behaviors. Despite extensive research, the etiological mechanisms underlying ASD remain highly complex and incompletely understood, involving genetic, environmental, and immunological factors. Emerging clinical evidence has consistently revealed a significant imbalance in KP metabolites in individuals with ASD, often accompanied by altered ratios of neuroprotective versus neurotoxic byproducts. However, the primary drivers of this metabolic dysregulation and its causative contribution to ASD pathogenesis are not yet fully elucidated. In this review, we systematically review the enzymatic steps of KP and the principal physiological functions of its major metabolites, with particular emphasis on their dual roles in neuroprotection and neurotoxicity. We then analyze the potential pathogenic mechanisms through which KP dysfunction may contribute to ASD, focusing on two interconnected etiological dimensions. First, KP imbalance can promote oxidative stress, which in turn triggers chronic inflammatory responses via microglial activation and release of pro-inflammatory cytokines, thereby disrupting neuronal homeostasis. Second, aberrant KP metabolism affects neurotransmitter systems, particularly glutamatergic and dopaminergic signaling, leading to impaired neural circuit development and synaptic pruning. By integrating current findings on the KP-ASD association, this review offers a comprehensive etiological framework and a clinically relevant paradigm. Furthermore, we highlight that specific KP metabolites, such as the KA/quinolinic acid ratio, hold promise as peripheral biomarkers for early diagnosis and disease stratification. Finally, we discuss the therapeutic potential of targeting KP enzymes or receptors for personalized intervention strategies, while acknowledging the challenges in translating these findings into clinical practice.

Consciousness, which underpins human perception, cognition, and behavioural responses, has long been a major focus of neuroscience and medicine. Alterations in consciousness occur not only during reversible processes such as sleep and anaesthesia, but also in pathological conditions, including disorders of consciousness (DOC) and brain injury. With recent advances in the synchronized acquisition and analysis of multimodal physiological signals, such as electroencephalography (EEG) and electrocardiography (ECG), the dynamic interactions between the heart and brain have become increasingly apparent. A growing body of evidence indicates that heart-brain interactions are closely associated with the maintenance and transition of consciousness states, offering a novel perspective for elucidating their underlying mechanisms and supporting relevant clinical assessments. Current approaches to heart-brain interaction analysis for consciousness-state assessment can be broadly grouped into three categories: ECG-based methods, EEG-based methods, and heart-brain coupling analysis. These approaches characterize heart-brain interactions during changes in consciousness from the complementary perspectives of autonomic regulation, cortical interoceptive processing, and cross-system information transfer, respectively. Nevertheless, this field remains at an early stage. Most studies have focused on a single experimental context or a fixed analytical method, with insufficient systematic consideration of the applicability and limitations of different approaches. Moreover, the mechanisms underlying the emergence and alteration of consciousness remain incompletely understood. Accordingly, this review examines heart-brain interaction methods employed in recent consciousness-state assessment studies in accordance with progressively deeper analytical perspectives, and systematically evaluates the advantages and limitations of these methods across distinct consciousness-related conditions. Heart rate variability (HRV) is one of the classical ECG-based indices used to investigate heart-brain interactions. It refers to fluctuations in consecutive interbeat intervals over a specified time period and is regarded as a physiological measure of autonomic nervous system regulation that may indirectly reflect the strength of heart-brain interactions. Depending on the analytical dimension, HRV analysis is commonly divided into time-domain, frequency-domain, and complexity-index analyses. These approaches characterize autonomic activity in terms of temporal fluctuations, the distribution of frequency components, and nonlinear dynamical properties, respectively. Although extensive research supports their physiological interpretation, they cannot characterize directional interactions from the heart to the brain. Among EEG-based methods for heart-brain interaction analysis, EEG activity directly related to cardiac fluctuations has received particular attention. One of the most widely used measures is the heartbeat-evoked potential (HEP). HEP-based approaches are considered to directly reflect the capacity of the cerebral cortex to process cardiac afferent signals and may be especially advantageous for characterizing rapidly changing consciousness levels, such as those observed during sleep. However, they do not comprehensively capture dynamic bidirectional information exchange between the brain and heart and are susceptible to cardiac artefacts, respiration, and variation in preprocessing procedures. Heart-brain coupling analysis quantifies functional associations between ECG and EEG through cross-system interaction measures, thereby assessing dynamic interactions between the heart and brain. It emphasizes information transfer, feedback regulation, and cross-timescale coordination between the two systems, offering a more comprehensive perspective for investigating changes in consciousness during sleep, anaesthesia, and DOC. However, the neurophysiological mechanisms and physiological interpretation of individual computational indices have not yet been fully established, and the robustness of their results and their potential for clinical generalization require further validation. Finally, this review summarizes the commonalities and differences among the three classes of methods across research domains involving different consciousness states. It further argues that heart-brain interaction research requires deeper investigation at both the mechanistic level of consciousness and the level of clinical application. Current challenges and key issues are identified, and future directions and feasible pathways for heart-brain interaction research are discussed, with the aim of providing new perspectives for researchers in related fields.

Aim To design and synthesize a series of glycyrrhetinic acid derivatives by using glycyrrhetinic acid as the parent nucleus,screen their antitumor activ-ities,and investigate the in vitro and in vivo antitumor effects and mechanisms of the most active compound.Methods MTT assay was used to screen for the com-pound with the most potent antitumor activity.MTT as-say,wound healing assay,colony formation assay and Transwell migration assay were used to evaluate the effects of the compound on tumor cell viability and mi-gration.Flow cytometry was employed to assess the im-pact of the compound on tumor cell cycle progression and apoptosis.Western blot was conducted to verify the effects on the expression of pro-apoptotic proteins Bax,caspase-3 and cleaved caspase-3.A mouse model of hepatocellular carcinoma ascites tumor was estab-lished to examine the antitumor effects of the compound in vivo.Results Compound C22 was identified as having the most significant inhibitory effect on hepato-cellular carcinoma cells.C22 inhibited the viability and migration of hepatocellular carcinoma cells in a time and concentration-dependent manner.C22 upreg-ulated the expression of pro-apoptotic proteins Bax,caspase-3 and cleaved caspase-3 in hepatocellular car-cinoma cells,induced apoptosis,and arrested the cell cycle in the G0/G1 and S phases.C22 significantly re-duced the growth of mouse hepatocellular carcinoma as-cites tumors and prolonged survival.Conclusion Glycyrrhetinic acid derivative C22 significantly inhibits the viability and migration of hepatocellular carcinoma cells in vitro and in vivo,and induces cell cycle arrest and apoptosis.

Aim To explore the therapeutic effects of resveratrol(Res)on hepatic inflammation and oxida-tive stress in rheumatoid arthritis(RA),and to eluci-date the relationship of the regulatory mechanism of the Nrf2/Keap1 signaling pathway in it.Methods A mouse model of arthritis was induced using chicken type Ⅱ collagen in combination with complete Freund's adjuvant,and Res was administered by tube feeding for treatment.Serum liver function indices and levels of hepatic inflammation and oxidative stress were detected in mice.An in vitro cellular model of hepatic inflam-mation and oxidative stress was established by treating mouse primary hepatocytes(MPHs)with TNF-α(5μg·L-1),cell proliferation inhibition was detected by CCK-8,and inflammation and oxidative stress-relat-ed indices were detected by protein blotting.The in-trinsic mechanisms by which Res attenuated hepatic in-flammation and oxidative stress in rheumatoid arthritis were explored by treating MPHs with Nrf2 inhibitor and Keap1 overexpression plasmid.Results Res signifi-cantly reduced the levels of inflammation and oxidative stress in hepatic tissues of collagen-induced arthritis mice as well as TNF-α-treated MPHs,and activated the Nrf2/Keap1 signaling pathway.Inflammation and oxidative stress levels in MPHs were exacerbated by the use of Nrf2 inhibitors and Keap1 overexpression,which promoted apoptosis.Conclusion Res attenuates he-patic inflammation and oxidative stress in rheumatoid arthritis via the Nrf2/Keap1 pathway.

Artificial intelligence(AI)is accelerating the digital transformation of the healthcare service system,with policy systems playing an increasingly prominent role in guiding technological innovation and governance reform.However,there is still a lack of systematic theoretical explanation for how AI technologies achieve deep integration under the collaborative effect of diverse policy objectives and policy tools.Drawing on national-level AI healthcare policy texts in China from 2015 to 2025,this study proposes an analytical framework of"policy goals-policy instruments-embedding pathways".It systematically reveals the staged evolution and underlying mechanisms of AI technology integration in healthcare.The findings show:first,China's AI healthcare policy system has progressed from strategic guidance and scenario-driven development to regulatory governance,demonstrating a dynamic adaptability to the integration of complex technologies;second,a dynamic coupling mechanism has formed between policy goals and instruments,achieving a coordinated balance among technological innovation,risk governance,and social value;third,the embedding pathway has evolved from exogenous,relationship-based integration to endogenous,structure-based integration,characterized by a progressive mechanism of"institutional empowerment-structural coupling-regulatory internalization".This research deepens the theoretical understanding of adaptive governance and institutional transformation for complex technologies,offering theoretical insights and practical references for optimizing AI healthcare policies and enhancing digital governance capacity.

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.

OBJECTIVE To investigate the neuroprotective effects of Ditan Decoction(DTD)on ischemic stroke.METHODS A mouse middle cerebral artery occlusion(MCAO)model was used to induce cerebral ischemia and assess the role of DTD in post-stroke NVU injury.DTD was gavaged once a day for 3 days after MCAO.Transwell neutrophil chemotaxis assay was used to explore the role of DTD in the neutrophil chemotaxis.RESULTS In the MCAO model,DTD treatment significantly reduced infarct volume(P<0.01)and attenuated blood-brain barrier disruption,as evidenced by decreased IgG leakage and preserved laminin expression(P<0.05).Furthermore,DTD suppressed neutrophil infiltration into ischemic brain tissue,as demonstrated by reduced neutrophil elastase(P<0.01)and myeloperoxidase(P<0.05)levels.Mechanistically,DTD inhibited neutrophil chemotaxis in a dose-dependent manner and downregulated phosphodiesterase 4B(PDE4B),a key regulator of neutrophil migration(P<0.05).Molecular docking analysis i-dentified four active DTD components-apigenin,vitexin,chlorogenic acid,and orientin-with strong binding affinities to PDE4B(bind-ing energies<-5 kcal·mol-1),suggesting their potential role in mediating DTD's therapeutic effects.CONCLUSION These find-ings highlight DTD as a promising intervention for ischemic stroke,targeting NVU preservation and PDE4B-dependent neutrophil mod-ulation.

OBJECTIVE: To explore the association between acupuncture during controlled ovarian hyperstimulation (COH) and the live birth rate (LBR) using different propensity score methods. METHODS: In this retrospective cohort study, eligible women who underwent a COH were divided into acupuncture and non-acupuncture groups. The primary outcome was LBR, as determined by propensity score matching (PSM). LBR was defined as the delivery of one or more living infants that reached a gestational age over 28 weeks after embryo transfer. The propensity score model encompassed 16 confounding variables. To validate the results, sensitivity analyses were conducted using three additional propensity score methods: propensity score adjustment, inverse probability weighting (IPW), and IPW with a "doubly robust" estimator. RESULTS: The primary cohort encompassed 9751 patients (1830 [18.76%] in the acupuncture group and 7921 [81.23%] in the non-acupuncture group). Following 1:1 PSM, a higher LBR was found in the acupuncture cohort (41.4% [755/1824] vs 36.4% [664/1824], with an odds ratio of 1.23 [95% confidence interval, 1.08-1.41]). Three additional propensity score methods produced essentially similar results. The risk of serious adverse events did not significantly differ between the two groups. CONCLUSION This retrospective study revealed an association between acupuncture and an increased LBR among patients undergoing COH, and that acupuncture is a safe and valuable treatment option. Please cite this article as: Zheng XY, Jiang ZY, Li YT, Li CL, Zhu H, Yu Z, Yu SY, Yang LL, Tang SY, Lü XY, Liang FR, Yang J. Association between acupuncture and live birth rates after fresh embryo transfer: A cohort study based on different propensity score methods. J Integr Med. 2025; 23(5):528-536.
Humans ; Female ; Propensity Score ; Embryo Transfer ; Adult ; Acupuncture Therapy ; Retrospective Studies ; Pregnancy ; Live Birth ; Birth Rate ; Cohort Studies

BACKGROUND: Acupuncture therapy provides a complementary and alternative approach to treating major depressive disorder (MDD), but its efficacy and safety have still not been comprehensively assessed. Recently published systematic reviews remain confusing and inconclusive. OBJECTIVE: This systematic review evaluated the efficacy and safety of acupuncture therapy alone or combined with antidepressants for adult patients with mild and moderate MDD. SEARCH STRATEGY: Chinese Biomedical Literature Database, China National Knowledge Infrastructure Database, Wanfang Database, Chinese Science and Technology Journal Database, PubMed, Embase, and Cochrane Library were searched from their inceptions to March 2025. INCLUSION CRITERIA: Randomized controlled trials that compared acupuncture therapy with antidepressants, or acupuncture therapy plus antidepressants with acupuncture therapy or antidepressants for adult patients with mild and moderate MDD were included. DATA EXTRACTION AND ANALYSIS: Five reviewers independently extracted data from original literature using a standardized form, and the data were verified by two reviewers to ensure accuracy. Statistical meta-analyses, publication bias analyses, and subgroup analyses were performed by using Review Manager 5.3 software. The Grading of Recommendations Assessment, Development, and Evaluation approach was used to assess the certainty of the evidence. RESULTS: A total of 60 eligible studies including 4675 participants were included. Low-certainty evidence showed that compared with antidepressants, acupuncture therapy (standardized mean difference [SMD] = -0.57; 95% confidence interval [CI] = [-0.87, -0.27]; I² = 86%; P = 0.006) or acupuncture therapy plus antidepressants (SMD = -1.00; 95% CI = [-1.18, -0.81]; I² = 77%; P < 0.00001) may reduce the severity of depression at the end of treatment. Low-certainty evidence indicated that compared with acupuncture therapy alone, acupuncture therapy plus antidepressants slightly reduced the severity of depression at the end of treatment (SMD = -0.38; 95% CI = [-0.61, -0.14]; I² = 18%; P = 0.002). Similar results were also found for acupuncture's relief of insomnia. The reported adverse effects of acupuncture therapy were mild and transient. For most of the subgroup analyses, acupuncture type, scale type, and the course of treatment did not show a significant relative effect. CONCLUSION Acupuncture therapy may provide antidepressant effects and relieve insomnia with mild adverse effects for adult patients with mild and moderate MDD. But the certainty of evidence was very low. More high-quality, well designed, large-scale studies with long-term follow-up are needed in the future. Please cite this article as: Kuang HJ, Yang HS, Feng YX, Tang H, Fan Q, Xu YQ, Cui S, Musil R, Luxenburger H, Zhang YX, Zhao H, Zhang YQ. Efficacy and safety of acupuncture therapies for adult patients with mild and moderate major depressive disorder: A systematic review and meta-analysis. J Integr Med. 2025; 23(5):471-491.
Humans ; Acupuncture Therapy/methods* ; Depressive Disorder, Major/therapy* ; Adult ; Antidepressive Agents/therapeutic use* ; Treatment Outcome ; Randomized Controlled Trials as Topic