Disorders of consciousness (DOC) are pathological conditions characterized by severely suppressed brain function and the persistent interruption or loss of consciousness. Accurate diagnosis and evaluation of DOC are prerequisites for precise treatment. Traditional assessment methods are primarily based on behavioral scales, which are inherently subjective and rely on observable behaviors. Moreover, traditional methods have a high misdiagnosis rate, particularly in distinguishing minimally conscious state (MCS) from vegetative state/unresponsive wakefulness syndrome (VS/UWS). This diagnostic uncertainty has driven the exploration of objective, reliable, and efficient assessment tools. Among these tools, electroencephalography (EEG) has garnered significant attention for its non-invasive nature, portability, and ability to capture real-time neurodynamics. This paper systematically reviews the application of EEG biomarkers in DOC assessment. These biomarkers are categorized into 3 main types: resting-state EEG features, task-related EEG features, and features derived from transcranial magnetic stimulation-EEG (TMS-EEG). Resting-state EEG biomarkers include features based on spectrum, microstates, nonlinear dynamics, and brain network metrics. These biomarkers provide baseline representations of brain activity in DOC patients. Studies have shown their ability to distinguish different levels of consciousness and predict clinical outcomes. However, because they are not task-specific, they are challenging to directly associate with specific brain functions or cognitive processes. Strengthening the correlation between resting-state EEG features and consciousness-related networks could offer more direct evidence for the pathophysiological mechanisms of DOC. Task-related EEG features include event-related potentials, event-related spectral modulations, and phase-related features. These features reveal the brain’s responses to external stimuli and provide dynamic information about residual cognitive functions, reflecting neurophysiological changes associated with specific cognitive, sensory, or behavioral tasks. Although these biomarkers demonstrate substantial value, their effectiveness rely on patient cooperation and task design. Developing experimental paradigms that are more effective at eliciting specific EEG features or creating composite paradigms capable of simultaneously inducing multiple features may more effectively capture the brain activity characteristics of DOC patients, thereby supporting clinical applications. TMS-EEG is a technique for probing the neurodynamics within thalamocortical networks without involving sensory, motor, or cognitive functions. Parameters such as the perturbational complexity index (PCI) have been proposed as reliable indicators of consciousness, providing objective quantification of cortical dynamics. However, despite its high sensitivity and objectivity compared to traditional EEG methods, TMS-EEG is constrained by physiological artifacts, operational complexity, and variability in stimulation parameters and targets across individuals. Future research should aim to standardize experimental protocols, optimize stimulation parameters, and develop automated analysis techniques to improve the feasibility of TMS-EEG in clinical applications. Our analysis suggests that no single EEG biomarker currently achieves an ideal balance between accuracy, robustness, and generalizability. Progress is constrained by inconsistencies in analysis methods, parameter settings, and experimental conditions. Additionally, the heterogeneity of DOC etiologies and dynamic changes in brain function add to the complexity of assessment. Future research should focus on the standardization of EEG biomarker research, integrating features from resting-state, task-related, and TMS-EEG paradigms to construct multimodal diagnostic models that enhance evaluation efficiency and accuracy. Multimodal data integration (e.g., combining EEG with functional near-infrared spectroscopy) and advancements in source localization algorithms can further improve the spatial precision of biomarkers. Leveraging machine learning and artificial intelligence technologies to develop intelligent diagnostic tools will accelerate the clinical adoption of EEG biomarkers in DOC diagnosis and prognosis, allowing for more precise evaluations of consciousness states and personalized treatment strategies.

Myocardial fibrosis （MF）， characterized by decreased cardiac function and myocardial compliance， is a pathological process and a progression factor in various cardiovascular diseases. The nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 （NLRP3） inflammasome is closely related to the development of MF. Recent studies have shown that traditional Chinese medicine （TCM） can regulate the NLRP3 inflammasome to alleviate MF. Based on this， this article systematically summarizes the research progress on the mechanisms by which TCM regulates the NLRP3 inflammasome to improve MF. It is found that active ingredients of TCM， such as alkaloids （lycorine，vincristine，bufalin）， saponins （astragaloside Ⅳ， diosgenin，ginsenoside Rg3）， terpenoids （celastrol，oridonin）， and phenols （polydatin，curcumin，phloridzin） as well as TCM formulas （Zhachong shisanwei pills，Zhilong huoxue tongyu capsules， Luqi formula） can inhibit the activation of the NLRP3 inflammasome， thereby suppressing the release of inflammatory factors such as interleukin-1β and IL-18， reducing inflammatory damage to myocardial tissue， alleviating excessive deposition of the extracellular matrix， and thus exerting the effect of improving MF.

ObjectiveTo construct a large language model （LLM）-based intelligent pre-consultation system for traditional Chinese medicine （TCM） to improve efficacy of clinical practice. MethodsA TCM large language model was fine-tuned using DeepSpeed ZeRO-3 distributed training strategy based on YAYI 2-30B. A weighted undirected graph network was designed and an agent-based syndrome differentiation model was established based on relationship data extracted from TCM literature and clinical records. An agent collaboration framework was developed to integrate the TCM LLM with the syndrome differentiation model. Model performance was comprehensively evaluated by Loss function， BLEU-4， and ROUGE-L metrics， through which training convergence， text generation quality， and language understanding capability were assessed. Professional knowledge test sets were developed to evaluate system proficiency in TCM physician licensure content， TCM pharmacist licensure content， TCM symptom terminology recognition， and meridian identification. Clinical tests were conducted to compare the system with attending physicians in terms of diagnostic accuracy， consultation rounds， and consultation duration. ResultsAfter 100 000 iterations， the training loss value was gradually stabilized at about 0.7±0.08， indicating that the TCM-LLM has been trained and has good generalization ability. The TCM-LLM scored 0.38 in BLEU-4 and 0.62 in ROUGE-L， suggesting that its natural language processing ability meets the standard. We obtained 2715 symptom terms， 505 relationships between diseases and syndromes， 1011 relationships between diseases and main symptoms， and 1 303 600 relationships among different symptoms， and constructed the Agent of syndrome differentiation model. The accuracy rates in the simulated tests for TCM practitioners， licensed pharmacists of Chinese materia medica， recognition of TCM symptom terminology， and meridian recognition were 94.09%， 78.00%， 87.50%， and 68.80%， respectively. In clinical tests， the syndrome differentiation accuracy of the system reached 88.33%， with fewer consultation rounds and shorter consultation time compared to the attending physicians （P＜0.01）， suggesting that the system has a certain pre- consultation ability. ConclusionThe LLM-based intelligent TCM pre-diagnosis system could simulate diagnostic thinking of TCM physicians to a certain extent. After understanding the patients' natural language， it collects all the patient's symptom through guided questioning， thereby enhancing the diagnostic and treatment efficiency of physicians as well as the consultation experience of the patients.

Abstract To explore the mechanism of the impact of small games (SSG) on the physical health of children and adolescents and the reasonable application strategies, the study reviewes the multi-dimensional effects of SSG on the body composition, motor ability, cardiovascular health, musculoskeletal health and metabolic health of children and adolescents, and proposes the strategies for the reasonable application of SSG, which include scientifically designing training programs, emphasizing individualized differences, and strengthening monitoring and feedback. It can provide theoretical support and practical suggestions for the application of SSG in promoting the physical health of children and adolescents.

ObjectiveTo explore the therapeutic effect of Xuebijing injection （XBJ） on severe acute pancreatitis induced acute lung injury （SAP-ALI） by regulating formyl peptide receptors （FPRs）/nucleotide-binding oligomerization domain-like receptor 3 （NLRP3） inflammatory pathway. MethodsSixty rats were randomly divided into a sham group， a SAP-ALI model group， low-， medium-， and high-dose XBJ groups （4， 8， and 12 mL·kg^-1）， and a positive drug （BOC2， 0.2 mg·kg^-1） group. For the sham group， the pancreas of rats was only gently flipped after laparotomy， and then the abdomen was closed， while for the remaining five groups， SAP-ALI rat models were established by retrograde injection of 5% sodium taurocholate （Na-Tc） via the biliopancreatic duct. XBJ and BOC2 were administered via intraperitoneal injection once daily for 3 d prior to modeling and 0.5 h after modeling. Blood was collected from the abdominal aorta 6 h after the completion of modeling， and the expression of interleukin （IL）-1β， IL-6， and tumor necrosis factor-α （TNF-α） in plasma was measured by enzyme-linked immunosorbent assay （ELISA）. The amount of ascites was measured， and the dry-wet weight ratios of pancreatic and lung tissue were determined. Pancreatic and lung tissue was taken for hematoxylin-eosin （HE） staining to observe pathological changes and then scored. The protein expression levels of FPR1， FPR2， and NLRP3 in lung tissue were detected by the immunohistochemical method. Western blot was used to detect the expression of FPR1， FPR2， and NLRP3 in lung tissue. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of FPR1， FPR2， and NLRP3 in lung tissue. ResultsCompared with the sham group， the SAP-ALI model group showed significantly decreased dry-wet weight ratio of lung tissue （P<0.01）， serious pathological changes of lung tissue， a significantly increased pathological score （P<0.01）， and significantly increased protein and mRNA expression levels of FPR1， FPR2， and NLRP3 in lung tissue （P<0.01）. After BOC2 intervention， the above detection indicators were significantly reversed （P<0.01）. After treatment with XBJ， the groups of different XBJ doses achieved results consistent with BOC2 intervention. ConclusionXBJ can effectively improve the inflammatory response of the lungs in SAP-ALI rats and reduce damage. The mechanism may be related to inhibiting the expression of FPRs and NLRP3 in lung tissue， which thereby reduces IL-1β and simultaneously antagonize the release of inflammatory factors IL-6 and TNF-α.

Atopic dermatitis （AD） is a common pruritic and chronic inflammatory dermatosis in clinical practice and is one of the diseases responding specifically to traditional Chinese medicine （TCM）. With the launch of biological agents and small molecule drugs and the development and implementation of guidelines of diagnosis and treatment， clinical pathways of treatment of moderate to severe AD， and consensus on the whole-process management of AD， the clinical efficacy of moderate to severe AD has been significantly improved. However， there are still many unmet clinical needs that require more effective methods to meet. In response to the Opinions of the CPC Central Committee and the State Council on Facilitating the Inheritance， Innovation， and Development of Traditional Chinese Medicine and the spirit of the National Conference on TCM， the China Association of Chinese Medicine organized more than 20 experts in TCM dermatology， Western medicine dermatology， interdisciplinary fields， and industries to discuss the difficulties and advantages of TCM in the treatment of AD. TCM treatment for AD can not only improve rash and relieve itching but also solve many concomitant syndromes. The abundant external treatment methods of TCM have advantages for different special populations and rash characteristics. The concept of treating disease before its onset in TCM is in line with the chronic disease management mode of prevention and treatment of atopic march and prevention of recurrence. In addition， TCM therapy can reduce the use of topical glucocorticoids and has good safety. Regarding the comorbidity of AD， equal emphasis on TCM and Western medicine and multidisciplinary joint treatment should be advocated to achieve maximum benefit for patients. The exchange of TCM and Western medicine has clarified the positioning and advantages of TCM intervention in AD， providing guidance for clinical and scientific research.

ObjectiveTo establish the fingerprints of 15 batches of Hengzhi Kechuan capsules， to quantitatively analyze 10 index components， and to evaluate the quality uniformity of samples from different batches. MethodsThe fingerprints and quantitative analysis of Hengzhi Kechuan capsules were established by a combination method of high performance liquid chromatography coupled with diode array detector and charged aerosol detector（HPLC-DAD-CAD）， adenosine， guanosine， vanillic acid， safflomin A， agarotetrol， naringin， hesperidin， militarine， ginsenoside Rb₁， and glycyrrhizic acid were selected as quality attribute indexes. A total of 15 batches of Hengzhi Kechuan capsules from 2022 to 2024（3 boxes per batch） were qualitatively and quantitatively analyzed， and the quality uniformity level of the manufacturers was characterized by parameters of intra-batch consistency（P_A） and inter-batch consistency（P_B）. The homogeneity and difference of quality attribute indexes of samples from different years were analyzed by heatmap clustering analysis. ResultsHPLC fingerprints and quantitative method of Hengzhi Kechuan capsules were established， and the methods could be used for qualitative and quantitative analysis of this preparation， which was found to be stable and reliable by method validation. The similarity of fingerprints of 15 batches of samples was 0.887-0.975， a total of 13 common peaks were calibrated， and 10 common peaks were designated， all of which were quality attribute index components. The results of quantitative analysis showed that the contents of the above 10 ingredients in the samples were 0.038-0.078， 0.115-0.251， 0.007-0.018， 0.291-0.673， 0.122-0.257， 0.887-1.905， 1.841-3.364， 1.412-2.450， 2.207-3.112， 0.650-1.161， respectively. And the contents of ginsenoside Rb₁ and glycyrrhizic acid met the limit requirements in the 2020 edition of Chinese Pharmacopoeia. For the samples from 15 batches， the P_A values of the 10 index components were all <10%， indicating good intra-batch homogeneity， and the P_B values ranged from 33.86% to 92.97%， suggesting that the inter-batch homogeneity was poor. Heatmap clustering analysis showed that the samples from different years were clustered into separate categories， and adenosine， guanosine， safflomin A， naringin， hesperidin and agarotetrol were the main differential components. ConclusionThe intra-annual quality uniformity of Hengzhi Kechuan capsules is good and the inter-annual quality uniformity is insufficient， which may be related to the quality difference of Pinellinae Rhizoma Praeparatum， Carthami Flos， Citri Sarcodactylis Fructus， Citri Reticulatae Pericarpium， Aquilariae Lignum Resinatum， Citri Fructus， etc. In this study， the fingerprint and multi-indicator determination method of Hengzhi Kechuan capsules was established， which can be used for more accurate and efficient quality control and standardization enhancement.

This article aimed to summarize the clinical experience of treating sjögren's syndrome of yin-deficiency and heat-toxin type based on the theory of exuberance of shaoyang ministerial fire accumulating to heat toxin. It is believed that sjögren's syndrome of yin-deficiency and heat-toxin type is attributed to dysfunction of shaoyang gallbladder， disruption in the circulation of sanjiao， stagnation of qi leading to fire， and prolonged accumulation of toxins causing damage. The core disease mechanism involves shaoyang dysfunction， hyperactivity of ministerial fire， and accumulation of heat toxins. In clinical practice， the therapeutic principles focus on regulating shaoyang， stabilizing and subduing ministerial fire， enriching yin and resolving toxins. For shaoyang dysfunction with internal stagnation of heat toxins， treatment should aim to unblock shaoyang， clear fire and expel toxins， using modified Sangchai Decoction （桑柴饮）； for shaoyang transformation into fire with symptoms of wood （the gallbladder） disease， the approach involves soothing and regulating gallbladder， clearing heat and resolving toxins， using modified Chaihu Shaoyao Decoction （柴胡芍药汤）； for disordered ministerial fire with excessive heat toxins， the strategy is to rescue the sovereign fire and stabilize the ministerial fire， employing modified Xinshen Liangjiao Decoction （心肾两交汤）； for unregulated ministerial fire with disordered distribution， treatment focuses on increasing body fluids and nourishing yin， stabilizing the ministerial fire， using modified Buyin Decoction （补阴汤）.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

Brain’s neural activities encompass both periodic rhythmic oscillations and aperiodic neural fluctuations. Rhythmic oscillations manifest as spectral peaks of neural signals, directly reflecting the synchronized activities of neural populations and closely tied to cognitive and behavioral states. In contrast, aperiodic fluctuations exhibit a power-law decaying spectral trend, revealing the multiscale dynamics of brain neural activity. In recent years, researchers have made notable progress in studying brain aperiodic dynamics. These studies demonstrate that aperiodic activity holds significant physiological relevance, correlating with various physiological states such as external stimuli, drug induction, sleep states, and aging. Aperiodic activity serves as a reflection of the brain’s sensory capacity, consciousness level, and cognitive ability. In clinical research, the aperiodic exponent has emerged as a significant potential biomarker, capable of reflecting the progression and trends of brain diseases while being intricately intertwined with the excitation-inhibition balance of neural system. The physiological mechanisms underlying aperiodic dynamics span multiple neural scales, with activities at the levels of individual neurons, neuronal ensembles, and neural networks collectively influencing the frequency, oscillatory patterns, and spatiotemporal characteristics of aperiodic signals. Aperiodic dynamics currently boasts broad application prospects. It not only provides a novel perspective for investigating brain neural dynamics but also holds immense potential as a neural marker in neuromodulation or brain-computer interface technologies. This paper summarizes methods for extracting characteristic parameters of aperiodic activity, analyzes its physiological relevance and potential as a biomarker in brain diseases, summarizes its physiological mechanisms, and based on these findings, elaborates on the research prospects of aperiodic dynamics.