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.

ObjectiveTo assess the therapeutic effectiveness and safety of the traditional Chinese medicine compound Shenlong decoction in addressing the symptoms of pulmonary deficiency and stasis in patients with idiopathic pulmonary fibrosis （IPF）. MethodsSixty eligible patients with lung deficiency and collateral stasis syndrome of IPF were randomly assigned to the observation （30 patients） and control groups （30 patients）. All patients underwent standard Western medical therapy. Additionally，the observation group received Shenlong decoction granules，while the control group received a placebo. Both treatments were packaged in four doses of 10.5 g each，taken twice daily for three months. The indexes of the patients during the treatment cycle were observed，and the main indexes include traditional Chinese medicine （TCM） syndrome scores and 6 min walk test （6MWT）. The secondary indexes include pulmonary function test ［actual value/expected value of total lung volume （TLC%），actual value/expected value of vital capacity（FVC%），actual/predicted diffusing capacity of the lung for carbon monoxide（DLCO%），actual/predicted forced expiratory volume in one second （FEV₁%），and FEV₁/ forced vital capacity （FVC）］，blood gas analysis ［arterial blood diathesis partial pressure of oxygen （PaO₂），partial pressure of carbon dioxide （PaCO₂），and arterial oxygen saturation （SaO₂）］，serum inflammatory factors ［transforming growth factor-β₁ （TGF-β₁），interleukin-4 （IL-4），interleukin-13 （IL-13），interleukin-12 （IL-12），and gamma-interferon （IFN-γ）］，and quality of survival evaluation ［St George's Respiratory Questionnaire （SGRQ） score］. The patients' clinical manifestations were determined at the end of the treatment， and the occurrence of adverse events was recorded. ResultsA total of 53 patients completed the study，comprising 27 in the control group and 26 in the observation group. Upon completion of the treatment period，the control group achieved a total effective rate of 33.33% （9/27），whereas the observation group demonstrated a total effective rate of 53.85% （14/26），which was statistically superior to the control group （χ²=4.034，P<0.05）. After the treatment，the TCM syndrome scores，6MWT，DLCO%，FEV₁%，PaO₂，PaCO₂，TGF-β₁，IL-4，IL-13，IL-12，and IFN-γ in the two groups were all significantly improved （P<0.01）. Compared with those in the control group after treatment at the same period，the TCM syndrome scores，6MWT，PaO₂，and PaCO₂ were significantly improved in the observation group after 60 days and 90 days of medication （P<0.01）. Three months after the end of medication，the SGRQ score in the observation group showed significant improvement when compared to that in the control group （P<0.05），and no severe adverse events were reported during the follow-up period. ConclusionCompound Shenlong decoction can alleviate clinical symptoms such as shortness of breath and wheezing in patients with lung deficiency and collateral stasis syndrome of IPF，enhance exercise tolerance，improve the quality of life，and have certain potential advantages in improving pulmonary function.

ObjectiveTo assess the therapeutic effectiveness and safety of the traditional Chinese medicine compound Shenlong decoction in addressing the symptoms of pulmonary deficiency and stasis in patients with idiopathic pulmonary fibrosis （IPF）. MethodsSixty eligible patients with lung deficiency and collateral stasis syndrome of IPF were randomly assigned to the observation （30 patients） and control groups （30 patients）. All patients underwent standard Western medical therapy. Additionally，the observation group received Shenlong decoction granules，while the control group received a placebo. Both treatments were packaged in four doses of 10.5 g each，taken twice daily for three months. The indexes of the patients during the treatment cycle were observed，and the main indexes include traditional Chinese medicine （TCM） syndrome scores and 6 min walk test （6MWT）. The secondary indexes include pulmonary function test ［actual value/expected value of total lung volume （TLC%），actual value/expected value of vital capacity（FVC%），actual/predicted diffusing capacity of the lung for carbon monoxide（DLCO%），actual/predicted forced expiratory volume in one second （FEV₁%），and FEV₁/ forced vital capacity （FVC）］，blood gas analysis ［arterial blood diathesis partial pressure of oxygen （PaO₂），partial pressure of carbon dioxide （PaCO₂），and arterial oxygen saturation （SaO₂）］，serum inflammatory factors ［transforming growth factor-β₁ （TGF-β₁），interleukin-4 （IL-4），interleukin-13 （IL-13），interleukin-12 （IL-12），and gamma-interferon （IFN-γ）］，and quality of survival evaluation ［St George's Respiratory Questionnaire （SGRQ） score］. The patients' clinical manifestations were determined at the end of the treatment， and the occurrence of adverse events was recorded. ResultsA total of 53 patients completed the study，comprising 27 in the control group and 26 in the observation group. Upon completion of the treatment period，the control group achieved a total effective rate of 33.33% （9/27），whereas the observation group demonstrated a total effective rate of 53.85% （14/26），which was statistically superior to the control group （χ²=4.034，P<0.05）. After the treatment，the TCM syndrome scores，6MWT，DLCO%，FEV₁%，PaO₂，PaCO₂，TGF-β₁，IL-4，IL-13，IL-12，and IFN-γ in the two groups were all significantly improved （P<0.01）. Compared with those in the control group after treatment at the same period，the TCM syndrome scores，6MWT，PaO₂，and PaCO₂ were significantly improved in the observation group after 60 days and 90 days of medication （P<0.01）. Three months after the end of medication，the SGRQ score in the observation group showed significant improvement when compared to that in the control group （P<0.05），and no severe adverse events were reported during the follow-up period. ConclusionCompound Shenlong decoction can alleviate clinical symptoms such as shortness of breath and wheezing in patients with lung deficiency and collateral stasis syndrome of IPF，enhance exercise tolerance，improve the quality of life，and have certain potential advantages in improving pulmonary function.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

Six compounds were isolated from the roots of Ephedra sinica Stapf using various chromatographic techniques such as silica gel column chromatography, thin layer chromatography and semi-preparative HPLC. Their chemical structures were identified by analysis of physicochemical properties and spectral data, and determined as (Z)-docosanylferulate (1), (E)-docosanylferulate (2), bis (2-ethylheptyl) phythalate (3), 2,2′-oxybis (1,4-di-tert-butylbenzene) (4), diisobutyl phthalate (5), bis (2-ethylhexyl) phthalate (6). Among them, compound 1 is a new compound, compounds 2-4 were first isolated from Ephedra. A corticosterone-induced PC-12 cell injury model was used for compound activity screening. The results showed that compounds 1 and 5 significantly improved corticosterone-induced PC-12 cell injury and significantly increased 5-HT₇ receptor protein expression in the cells, indicating potential antidepressant activity.

The coronavirus disease 2019 (COVID-19) is an acute infectious disease caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, which has led to serious worldwide economic burden. Due to the continuous emergence of variants, vaccines and monoclonal antibodies are only partial effective against infections caused by distinct strains of SARS-CoV-2. Therefore, it is still of great importance to call for the development of broad-spectrum and effective small molecule drugs to combat both current and future outbreaks triggered by SARS-CoV-2. Cathepsin L (CatL) cleaves the spike glycoprotein (S) of SARS-CoV-2, playing an indispensable role in enhancing virus entry into host cells. Therefore CatL is one of the ideal targets for the development of pan-coronavirus inhibitor-based drugs. In this study, a CatL enzyme inhibitor screening model was established based on fluorescein labeled substrate. Two CatL inhibitors IMB 6290 and IMB 8014 with low cytotoxicity were obtained through high-throughput screening, the half inhibition concentrations (IC₅₀) of which were 11.53 ± 0.68 and 1.56 ± 1.10 μmol·L^-1, respectively. SDS-PAGE and cell-cell fusion experiments confirmed that the compounds inhibited the hydrolysis of S protein by CatL in a concentration-dependent manner. Surface plasmon resonance (SPR) detection showed that both compounds exhibited moderate binding affinity with CatL. Molecular docking revealed the binding mode between the compound and the CatL active pocket. The pseudovirus experiment further confirmed the inhibitory effects of IMB 8014 on the S protein mediated entry process. In vitro pharmacokinetic evaluation indicated that the compounds had relatively good drug-likeness properties. Our research suggested that these two compounds have the potential to be further developed as antiviral drugs for COVID-19 treatment.

Breastfeeding is the best natural food for infants. In infants with congenital heart disease(CHD), breast milk can reduce the incidence of necrotizing enterocolitis, feeding intolerance and growth failure, and improve the overall prognosis. However, there are many obstacles to breastfeeding in infants with CHD as well as lack of related domestic research. This study mainly focuses on breastfeeding status, influencing factors, assessment, implementation and solutions for the infants with CHD, and proposed the future research recommendations on clinical practices, in order to provide reference for the breastfeeding management of infants with CHD in China.