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.

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.

BackgroundPostpartum depression can affect the physical and mental health of mothers and the quality of parenting. Most Chinese women perform traditional postpartum practices （commonly known as "doing the month"） after giving birth， while the existing findings are inconsistent and inconclusive regarding the potential of traditional Chinese postpartum practices to alleviate or exacerbate postpartum depression. ObjectiveTo explore the relationship between traditional Chinese postpartum practices and postpartum depression， so as to provide references for reducing the risk of postpartum depression. MethodsA total of 240 consecutive women who gave birth in the obstetrics department of the Mianyang Central Hospital and the Third Hospital of Mianyang from January to May 2024 were selected. Data were collected using Self-designed General Information Questionnaire， Chinese version of the Edinburgh Postnatal Depression Scale （EPDS）， the Social Support Rating Scale （SSRS）， the Patient Health Questionnaire-15 （PHQ-15）， the Adherence to Doing-the-Month Practices questionnaire （ADP）， and the Self-compiled Questionnaire on the Cognition of Doing-the-Month. The absolute value （A value） of the difference between scores of ADP and Cognition of Doing-the-Month Questionnaire was calculated to evaluate the degree of cognitive behavioral conflict of postpartum women. Pearson correlation analysis was performed to examine the correlations of EPDS score with SSRS score， PHQ-15 score， ADP total and dimensional scores， Cognition of Doing-the-Month Questionnaire total and dimensional scores， and A value. Logistic regression analysis was conducted to identify the protective and risk factors for developing postpartum depression. ResultsThe postpartum depression was detected in 22.50% of women. The postpartum women had a EPDS score of （6.21±5.00）， ADP score of （70.05±20.57）， SSRS score of （41.96±6.96）， PHQ-15 score of （4.63±3.77）， and Cognition of Doing-the-Month questionnaire score of （40.30±10.13）. The A value was （0.65±0.58）. Correlation analysis revealed that EPDS score was negatively correlated with the total ADP score and the four dimensional scores of the restrictions on social activities， diet， housework， and personal hygiene （r=-0.228， -0.146， -0.184， -0.275， -0.168， P<0.05 or 0.01）， and positively correlated with the A value （r=0.161， P<0.05）. Logistic regression analysis indicated that restriction on housework dimension in ADP was entered into the model （OR=0.930， 95% CI： 0.885~0.978）. ConclusionThe restriction on housework dimension in traditional Chinese postpartum practices may be a protective factor against postpartum depression.

Abstract Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.

ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.

Microorganisms can form biofilms, complex, heterogeneous, multicellular communities that adhere to surfaces. Biofilm formation on the surface of structures in water will accelerate structures’ corrosion, seriously affect their service efficiency and life, and significantly impact the growth of animals, plants, and human life. Hence, clarifying the mechanism of biofilm formation contributes to developing new strategies to control biofilm formation on surface and then reduce infections, biofouling, and contaminations. Biofilm-targeting strategies include the regulation of established biofilms or the modulation of single-cell attachment. In most studies, physicochemical mechanism is frequently applied to explain the initial bacterial adhesion phenomena but rarely to explain other stages of biofilm formation. This review presents a five-step comprehensive description of the physicochemical process from film formation to biofilm maturation: (1) period of film formation; (2) period of bacterial adhesion; (3) period of extracellular-polymeric-substances (EPSs) membrane formation; (4) period of regulating biofilm by quorum sensing (QS); (5) period of biofilm maturation. We first clarify how the film formed by compound molecules affects the surface’s physicochemical properties and initial adhesion, summarizing many factors that affect bacterial adhesion. We then review the types of EPSs and signal molecules secreted by bacteria after irreversible adhesion, as well as their role and QS mechanism in biofilm maturation. Finally, we discuss how bacteria or microcolonies separate from the mature biofilm by physicochemical action and summarize the morphology and adhesion characterization methods after the biofilm matures. This review redefines the role of physicochemical in the whole process of biofilm formation and provides a theoretical basis for the prevention, removal, and utilization of biofilm and other related research fields.

ObjectiveAlthough expression of the TEAD1 protein in preadipocytes has been established, its function remains unclear. In this study, we sought to detect transcripts of TEAD1 in chicken and to examine the effects of this protein on the proliferation, migration, apoptosis, and differentiation of immortalized chicken preadipocyte cell lines (ICP1). MethodsThe full-length sequence of the TEAD1 gene was cloned and the two transcripts were subjected to bioinformatics analysis. The subcellsular localization of TEAD1 transcripts was determined based on indirect immunofluorescence. The effects of TEAD1 transcripts overexpression on the proliferation of ICP1 cells were examined by RT-qPCR, CCK-8, and EdU assays; the effects of TEAD1 transcripts on ICP1 cells migration were examined based on the scratch test; and the effects of TEAD1 transcripts overexpression on ICP1 cells apoptosis were analyzed using apoptosis-Hoechst staining and RT-qPCR. The expression of TEAD1 transcripts in different tissues, cells lines, and ICP1 at different periods of differentiation was analyzed by RT-qPCR. The effects of TEAD1 transcripts overexpression on lipid droplet accumulation and adipogenic-related gene expression in ICP1 cells were analyzed based on Oil Red O and BODIPY staining, RT-qPCR, Western blot, and dual-luciferase reporter gene assays. Finally, the content of triglyceride (TG) was measured in TEAD1 overexpressed ICP1 cells. ResultsThe full-length TEAD1 was cloned and two TEAD1 transcripts were identified. The TEAD1-V1 protein was found to be localized primarily in the cell nucleus, whereas the TEAD1-V2 protein is localized in the cell cytoplasm and nucleus. The overexpression of both TEAD1-V1 and TEAD1-V2 significantly inhibited the proliferation of ICP1 cells. Whereas the overexpression of TEAD1-V1 promoted ICP1 cell migration, the overexpression of TEAD1-V2 had no significant effects on ICP1 migration; the overexpression of both TEAD1-V1 and TEAD1-V2 significantly promoted the apoptosis of ICP1 cells. We found that the different transcripts of TEAD1 have similar expression pattern in different tissues and cells lines. During induced preadipocyte differentiation, the expression of these genes initially declined, although subsequently increased. Overexpression of TEAD1-V1 promoted a significant reduction in lipid droplet formation and inhibited C/EBPα expression during the differentiation of ICP1 cells (P<0.05). However, the overexpression of TEAD1-V2 had no significant effect on lipid droplet accumulation or the expression of adipogenic-related proteins (P>0.05). Overexpression of TEAD1-V1 significantly decreased triglyceride content in ICP1 cells (P<0.05), while overexpression of TEAD1-V2 had no effect on triglyceride content in ICP1 cells (P>0.05). ConclusionIn this study, for the first time, identified two TEAD1 transcripts. Overexpressed transcripts TEAD1-V1 and TEAD1-V2 both inhibited the proliferation of chicken preadipocytes and promoted apoptosis of chicken preadipocytes. TEAD1-V1 inhibited the differentiation of preadipocytes and promoted the migration of preadipocytes, while TEAD1-V2 had no effect on the differentiation and migration of preadipocytes.

Anti-tumor traditional Chinese medicine has a long history of clinic application, in which the star molecules have always been the hotspot of modern drug research, but they are limited by the solubility, stability, targeting, bioactivity or toxicity of the monomer components of traditional Chinese medicine anti-tumor star molecules and other pharmacokinetic problems, which hinders the traditional Chinese medicine anti-tumor star molecules for further clinical translation and application. Currently, the nanosystems prepared by supramolecular technologies such as molecular self-assembly and nanomaterial encapsulation have broader application prospects in improving the anti-tumor effect of active components of traditional Chinese medicine, which has attracted extensive attention from scholars at home and abroad. In this paper, we systematically review the research progress in preparation of supramolecular nano-systems from anti-tumor star molecule of traditional Chinese medicine, and summarize the two major categories and ten small classes of carrier-free and carrier-based supramolecular nanosystems and their research cases, and the future development direction is put forward. The purpose of this paper is to provide reference for the research and clinical transformation of using supramolecular technology to improve the clinical application of anti-tumor star molecule of traditional Chinese medicine.

Objective To analyze the clinical efficacy of the Qianyang Fengsui Dan(combined with flying needle therapy)in the treatment of kidney-yang deficiency type of insomnia.Methods A retrospective study was conducted to select 82 patients with insomnia admitted to the Department of Traditional Chinese Medicine of Dezhou Hospital of Traditional Chinese Medicine from November 2020 to November 2021,and they were divided into an observation group and a control group according to whether or not they were treated with Qianyang Fengsui Dan combined with flying needle therapy,with 41 cases in each group.The control group was treated with Estazolam,while the observation group was treated with Qianyang Fengsui Dan combined with flying needle therapy on the basis of the treatment of the control group,and the course of treatment was 1 month.The changes of Pittsburgh Sleep Quality Index(PSQI)scores and Epworth Sleepiness Scale(ESS)scores,as well as polysomnographic parameters were observed before and after treatment in the two groups.The changes of γ-aminobutyric acid(GABA),glutamate(GA),substance P(SP),and neuropeptide Y(NPY)levels were compared before and after treatment between the two groups.And followed up for 1 year to compare the incidence of relapce of the two groups of patients.Results(1)The total effective rate was 95.12%(39/41)in the observation group and 63.41%(26/41)in the control group,and the efficacy of the observation group was superior to that of the control group,and the difference was statistically significant(P＜0.05).(2)After treatment,PSQI scores and ESS scores of patients in the two groups were significantly improved(P＜0.05),and the observation group was significantly superior to the control group in improving PSQI scores and ESS scores,and the differences were statistically significant(P＜0.05).(3)After treatment,sleep efficiency,awakening time,sleep latency,REM,and total sleep time were significantly improved in the two groups(P＜0.05),and the observation group was significantly superior to the control group in improving sleep efficiency,awakening time,sleep latency,REM,and total sleep time,and the differences were statistically significant(P＜0.05).(4)After treatment,the serum GABA,GA,SP,and NPY levels of patients in the two groups were significantly improved(P＜0.05),and the observation group was significantly superior to the control group in improving the serum GABA,GA,SP,and NPY levels,and the differences were all statistically significant(P＜0.05).(5)After treatment,follow-up for 1 year,the recurrence rate of the observation group was 0,and there were 7 cases of recurrence in the control group,and the recurrence rate of the control group was 17.07%(7/41),and the recurrence rate of the observation group was lower than that of the control group,and the difference was statistically significant(P＜0.05).Conclusion The combination of flying needle therapy and Qianyang Fengsui Dan can effectively relieve insomnia and fatigue in patients with insomnia,reduce daytime drowsiness,regulate the release of blood monoamine neurotransmitters,and reduce the relapse rate,and its efficacy is superior to that of simple western medicine treatment.

Objective This study aims to investigate the regulatory effects of Fujiu Patch(composed of Sinapis Semen,Kansui Radix,Corydalis Rhizoma and Asari Radix et Rhizoma)on the CD4+ T helper 17 cell(Th17)/CD4+CD25+ regulatory T cell(Treg)balance in asthmatic rats via the signal pathway of IL-6/signal transducer and activator of transcription 3(STAT3)as well as IL-2/signal transducer and activator of transcription 5(STAT5),and to reveal its anti-asthma mechanisms.Methods An experimental asthma model was constructed by ovalbumin(OVA)combined with aluminum hydroxide sensitization and challenge,and then the rats were administered with Fujiu Patch at Dazhui(DU14),Feishu(BL13)and Shenshu(BL23)points for 4 hours each time,once every other day for 7 times.Immunohistochemistry was used to detect the positive expressions of Th17 specific cytokine(IL-17)and Treg transcription factor(Foxp3)in rat lung tissue.The percentage of Th17 and Treg cells in peripheral blood was examined by flow cytometry analysis,and the expressions of IL-6/STAT3 and IL-2/STAT5 pathway-related proteins in lung tissue were assayed with Western Blot.Results Compared to the model group,IL-17 positive expression in the rat lung showed a significant reduction in the Fujiu Patch group(P＜0.01),while the positive expression of Foxp3 was obviously increased(P＜0.05).Meanwhile,the protein expression levels of IL-6 and phospho-STAT3 were were significantly declined(P＜0.01),and the protein expression levels of IL-2 and phospho-STAT5 were were significantly elevated(P＜0.01).However,there was no significant alteration in the total protein expressions of STAT3 and STAT5(P＞0.05).Furthermore,the proportion of Th17 cells in peripheral blood of rats in the Fujiu Patch group was lower than that in the model group,while the proportion of Treg cells was higher than that in the model group.Statistically-significant differences were observed(all P＜0.01).Conclusion These findings indicate that Th17/Treg immune imbalance occurs in asthmatic rat.Fujiu Patch may exert anti-asthma effects via inhibiting the expression of IL-6,downregulating the expression of phospho-STAT3,diminishing the level of IL-17-producing Th17 cells,as well as increasing the expressions of IL-2-mediated STAT5 phosphorylation,raising the level of Foxp3-expressing Treg cells,promoting Th17/Treg balance and suppressing immune responses in rat with asthma.