[摘 要] 目的：探讨复发/转移性鼻咽癌（NPC）接受含PD-1单抗免疫治疗的临床特征和预后影响因素。方法：回顾性分析2019年3月至2024年7月期间南部战区总医院确诊的95例NPC患者的临床资料和外周血生化及免疫学指标。预后分析采用Kaplan-Meier曲线，组间比较使用Log-rank检验，采用Cox比例风险模型进行单因素和多因素分析。结果：95例患者中男性81例，女性14例，中位年龄49.72岁（16~74岁），Ⅳ期91例（95.79%），所有患者均采用免疫治疗，联合或不联合化疗方案治疗，中位无进展生存期（mPFS）为10.5个月，客观缓解率（ORR）70.53%，疾病控制率（DCR）89.47%，接受含铂治疗方案患者PFS相对更长，且差异有统计学意义。紫杉醇 + 顺铂 + 氟尿嘧啶（TPF）对比吉西他滨 + 顺铂（GP）和紫杉醇 + 顺铂（TP）显示出更长的PFS，但差异无统计学意义。不同PD-1单抗治疗组间的PFS未显示出有统计学意义的差异。单因素及多因素Cox回归分析结果显示，肿瘤复发状态、初始血浆EBV感染状态、治疗周期数、基线外周血SII是复发/转移性NPC患者接受PD-1抑制剂治疗疗效预测的独立相关因素（均P < 0.05），并且非复发患者、初始血浆EBV DNA阳性、接受 ≥ 4治疗周期、基线外周血SII < 772.81的患者接受PD-1抑制剂治疗预后相对更好。结论：在接受PD-1抑制剂治疗的复发/转移性NPC患者中，非复发患者、初始血浆EBV DNA阳性、≥ 4治疗周期且外周血SII < 772.81者PFS相对更长，可早期识别免疫治疗效果不佳患者并精准干预。

Background As one of the most severe occupational diseases in China, pneumoconiosis is significantly burdened by its complications, which adversely affects patients' quality of life. Objective To identify the influencing factors of complications in pneumoconiosis and to construct an early prediction model for pneumoconiosis complications, providing theoretical guidance for clinical diagnosis, treatment, and rehabilitation. Methods A case-control study was conducted using data from the Chongqing 5G Pneumoconiosis Rehabilitation Management Information Platform. A total of 1872 pneumoconiosis patients with complications, who received rehabilitation at various rehabilitation stations in Chongqing from January 2021 to December 2024, were enrolled as the case group. Concurrently, 2348 patients without complications from the same platform and period were included as the control group. Univariate analysis, LASSO regression, and logistic regression were employed to identify influencing factors for complications. An extreme gradient boosting (XGBoost) model was trained using ten-fold cross-validation to predict pneumoconiosis complications. The SHapley Additive exPlanations (SHAP) method was applied for model visualization. Results The analysis of influencing factors revealed that increased age, silicosis type, advanced stage of pneumoconiosis, dependence in activities of daily living, abnormal muscle strength, increased dyspnea index, presence of cough, viscous sputum, impaired cardiac function, severe abnormality in the 6-minute walk test (6MWT), and increased Borg score were risk factors for complications (P<0.05). The XGBoost model demonstrated an area under the curve (AUC) of receiver operating characteristic of 0.718, and a Brier score of 0.211 for the calibration curve. Decision curve analysis demonstrated a superior net benefit within the threshold probability range of 0.2 to 1.0 compared to "all-patient intervention" and "no-patient intervention" strategies, indicating good predictive performance and significant clinical utility. SHAP visualization identified the top six important features as Borg score, age, 6MWT, muscle strength, pneumoconiosis stage, and cough symptoms. Conclusion Multiple factors influence the occurrence of complications in pneumoconiosis patients. Clinical attention should be focused on elderly patients with decreased cardiopulmonary reserve, pronounced respiratory symptoms, and diminished muscle strength. The XGBoost model demonstrates satisfactory discrimination, calibration, and clinical applicability in predicting pneumoconiosis complications and may serve as a useful reference for clinical decision-making.

Renal Fanconi syndrome (FS) is a rare renal manifestation of primary Sjögren's syndrome (pSS). This study aims to analyze the clinical and prognostic characteristics of patients with pSS-associated renal FS (pSS-FS) and provide insights for clinical management.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

Objective To assess the accuracy of pN staging prediction in papillary thyroid carcinoma (PTC) using ultrasound radiomics and deep neural networks (DNN). Methods A retrospective analysis was conducted on 375 patients with pathologically confirmed PTC, comprising 261 cases in the training set and 114 in the test set. Staging was categorized as pN0 (no cervical lymph node metastasis), pN1a (central neck lymph node metastasis), and pN1b (lateral neck lymph node metastasis). An ultrasound physician manually segmented the regions of interest (ROIs) for PTC, extracting 1899 radiomic features. Dimensionality reduction was performed using the least absolute shrinkage and selection operator (LASSO) regression. A DNN model for predicting PTC pN staging was developed using the H2O deep learning platform, trained on the training set, and validated on the test set to assess the accuracy of the optimal model. Results A total of 153 patients were in the pN0 stage, 131 patients in the pN1a stage, and 91 patients in the pN1b stage. LASSO regression selected 15 radiomic features for each PTC. The optimal DNN model, constructed using these 15 features, achieved accuracies of 85.82% on the training set and 81.57% on the test set. Conclusion Ultrasound radiomics of PTC demonstrates high accuracy in predicting pN staging and shows potential for automating N staging in patients.

ObjectiveTo observe the clinical efficacy of tonifying kidney and replenishing essence on asthenozoospermia patients with the syndrome of kidney essence deficiency and the effects of this method on the adenosine 5′-monophosphate-activated protein kinase （AMPK）/mammalian target of rapamycin complex 1 （mTORC1） signaling pathway. MethodsSeventy-two eligible asthenozoospermia patients with the syndrome of kidney essence deficiency treated in the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine from February 2023 to January 2024 were selected and randomly assigned into an observation group and a control group， with 36 patients in each group. The observation group received oral administration of Guilu Tianjing capsules， while the control group received oral administration of L-carnitine oral solution. The treatment course lasted for 4 weeks in both groups. The observed indicators included sperm progressive motility rate （PR）， total sperm motility （PR+NP）， percentage of normal mitochondrial membrane potential （MMP）， and traditional Chinese medicine （TCM） symptom scores before and after treatment in both groups. A three-month follow-up was instituted to record the conception status of the patients’ spouses. Additionally， eight patients were randomly selected from the eligible patients in the observation group， and four healthy males with normal semen routine examination results were included as the control group for the determination of protein expression. Western blotting was conducted to assess the expression of AMPK， phosphorylated （p）-AMPK， regulatory-associated protein of mTOR （RAPTOR） and p-RAPTOR， and PTEN-induced putative kinase 1 （PINK1） in sperms from the observation group before and after treatment， as well as in the sperms of the control group. ResultsThe pregnancy rate of spouses in the observation group was 9.09% （3/33）， which was higher than that （3.33%， 1/30） in the control group. The total response rate was 84.8% （28/33） in the observation group and 66.7% （20/30） in the control group， with no statistically significant difference. After treatment， both groups were improved considering PR， PR+NP， MMP， and TCM symptom scores （P<0.01）. Moreover， the observation group exhibited more pronounced decreases in TCM symptom scores than the control group （P<0.05）， while the changes in PR， PR+NP， and MMP showed no statistical significance between groups. Compared with the control group， the asthenozoospermia group exhibited upregulations in phosphorylation levels of AMPK and RAPTOR and protein level of PINK （P<0.01）. The administration of Guilu Tianjing Capsules led to downregulations in the phosphorylation levels of AMPK and RAPTOR and protein level of PINK1 （P<0.01）. However， the protein levels of AMPK and RAPTOR demonstrated no significant difference between before and after treatment. During the study period， neither group of patients exhibited any notable adverse reactions. ConclusionGuilu Tianjing capsules can enhance the sperm motility and percentage of normal mitochondrial membrane potential in asthenozoospermia patients with the syndrome of kidney essence deficiency by downregulating the AMPK/mTORC1 signaling pathway， lowering the protein level of PINK1， and inhibiting excessive activation of mitophagy.

ObjectiveTo observe the clinical efficacy of tonifying kidney and replenishing essence on asthenozoospermia patients with the syndrome of kidney essence deficiency and the effects of this method on the adenosine 5′-monophosphate-activated protein kinase （AMPK）/mammalian target of rapamycin complex 1 （mTORC1） signaling pathway. MethodsSeventy-two eligible asthenozoospermia patients with the syndrome of kidney essence deficiency treated in the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine from February 2023 to January 2024 were selected and randomly assigned into an observation group and a control group， with 36 patients in each group. The observation group received oral administration of Guilu Tianjing capsules， while the control group received oral administration of L-carnitine oral solution. The treatment course lasted for 4 weeks in both groups. The observed indicators included sperm progressive motility rate （PR）， total sperm motility （PR+NP）， percentage of normal mitochondrial membrane potential （MMP）， and traditional Chinese medicine （TCM） symptom scores before and after treatment in both groups. A three-month follow-up was instituted to record the conception status of the patients’ spouses. Additionally， eight patients were randomly selected from the eligible patients in the observation group， and four healthy males with normal semen routine examination results were included as the control group for the determination of protein expression. Western blotting was conducted to assess the expression of AMPK， phosphorylated （p）-AMPK， regulatory-associated protein of mTOR （RAPTOR） and p-RAPTOR， and PTEN-induced putative kinase 1 （PINK1） in sperms from the observation group before and after treatment， as well as in the sperms of the control group. ResultsThe pregnancy rate of spouses in the observation group was 9.09% （3/33）， which was higher than that （3.33%， 1/30） in the control group. The total response rate was 84.8% （28/33） in the observation group and 66.7% （20/30） in the control group， with no statistically significant difference. After treatment， both groups were improved considering PR， PR+NP， MMP， and TCM symptom scores （P<0.01）. Moreover， the observation group exhibited more pronounced decreases in TCM symptom scores than the control group （P<0.05）， while the changes in PR， PR+NP， and MMP showed no statistical significance between groups. Compared with the control group， the asthenozoospermia group exhibited upregulations in phosphorylation levels of AMPK and RAPTOR and protein level of PINK （P<0.01）. The administration of Guilu Tianjing Capsules led to downregulations in the phosphorylation levels of AMPK and RAPTOR and protein level of PINK1 （P<0.01）. However， the protein levels of AMPK and RAPTOR demonstrated no significant difference between before and after treatment. During the study period， neither group of patients exhibited any notable adverse reactions. ConclusionGuilu Tianjing capsules can enhance the sperm motility and percentage of normal mitochondrial membrane potential in asthenozoospermia patients with the syndrome of kidney essence deficiency by downregulating the AMPK/mTORC1 signaling pathway， lowering the protein level of PINK1， and inhibiting excessive activation of mitophagy.

BACKGROUND:Our previous research found that Panax notoginseng can repair the morphological structure of bone cells,which has a good application prospect in the treatment of osteoarthritis,but the specific mechanism of Panax notoginseng is still unclear. OBJECTIVE:To identify the main components of Panax notoginseng using ultra-high performance liquid chromatography-Q exactive-mass spectrometry(UHPLC-QE-MS),and to explore the mechanism of Panax notoginseng in the treatment of osteoarthritis by combining network pharmacology,molecular docking and molecular dynamics simulation. METHODS:After identifying the main components of Panax notoginseng by UHPLC-QE-MS technology,the active components were screened by TCMSP database,and the targets of active components were found by TCMSP and Uniprot database.Osteoarthritis targets were screened out through disease databases.After the intersection of drug targets and disease targets,the protein-protein interaction network was constructed by importing STRING database and Cytoscape software,and the"active ingredient-action target"network was constructed to screen key active ingredients.Then the key targets were enriched and analyzed,and the key active components and key targets were verified by molecular docking.Finally,the results with the lowest binding energy were selected for molecular dynamics simulation. RESULTS AND CONCLUSION:A total of 57 active components were identified in the solution of Panax Notoginseng,including 50 intersection targets of components and disease targets,5 key active components(quercetin,ursodeoxycholic acid,kaempferol,naringenin and erythrocyanine),and 5 key targets(interleukin 6,matrix metalloproteinase 9,interleukin 1β,albumin and recombinant chemokine c-motif ligand 2).Gene ontology enriched 642 entries,among which 620 entries represent biological processes,21 entries represent molecular functions,and 1 entry represents cellular components.Kyoto encyclopedia of genes and genomes analysis indicated 63 pathways,mainly including estrogen signaling pathway,interleukin 17 signaling pathway and hyperglycosylation end product-hyperglycosylation end product receptor signaling pathway.Molecular docking showed good binding activity of key active components and key targets.Molecular dynamics simulation indicated that the stable interaction between quercetin and matrix metalloproteinase 9.The composition of Panax notoginseng was comprehensively studied,and the material basis of its efficacy was preliminarily clarified.It was predicted that Panax notoginseng could play an anti-inflammatory,cartilage-protective,and immunomodulatory role in treating osteoarthritis through multiple components,targets,approaches and pathways.

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.

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.