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.

This paper focuses on the application of health big data in cancer screening. Firstly, the sources and characteristics of health big data are introduced, then the commonly used epidemiological designs and analytical techniques in hospital-based cancer screening studies are summarized and the application scenarios of such studies are described. Finally, the challenges and future development in the application of health big data are analyzed to provide reference for the future studies.

Objective:Exploring the role and mechanism of CHMP4C in regulating necroptosis during gastric can-cer development and progression.Method:The expression of CHMP4C in pan-cancer was analyzed by bioinformatics methods,and the expression of CHMP4C was detected in human normal gastric epithelial cells and GC cell lines by RT-qPCR and Western blot.Overexpression or knockdown of CHMP4C was performed in GC cell lines,and the effects of CHMP4C on the growth and proliferation of GC cells were detected using CCK-8 and clone formation assays.The CCK-8 experiment and Hoechst/PI double staining experiment were used to detect the changes in GC cell mortality and PI positive cell ratio after treatment with the necroptsis inducer TSZ or inhibitor necrostatin-1(Nec-1).Western blot assay was used to detect the protein and phosphorylation levels of RIPK1,RIPK3,and MLKL in GC cells.Result:CHMP4C was upregulated in GC tissues and cells.The CCK-8 and clone formation experiments showed that overex-pression of CHMP4C significantly improved the proliferation ability and colony formation efficiency of GC cells,while knockdown of CHMP4C significantly weakened GC cells.Moreover,the results of CCK-8 and Hoechst 33342/PI double staining experiments showed that upregulated CHMP4C could inhibit TSZ induced GC cell death;Nec-1 can reverse the decrease in GC cell viability caused by CHMP4C knockdown.Western blot experiment showed that the levels of p-RIPK1,p-RIPK3,and p-MLKL were significantly decreased in overexpressing cells,while they were increased in knockdown cells.After treatment with Nec-1,the expression levels of these three proteins decreased in knockdown cells.Conclusion:CHMP4C may promote GC progression by negatively regulating necroptosis through inhibiting the phosphorylation of the RIPK1/RIPK3/MLKL signaling pathway,suggesting that it is expected to be a potential target for GC therapy.

Objective:To investigate the prevalence and risk factors of overweight and obesity among Chinese children aged 3-18 years from 11 provinces, antonomous regions, or municipalities.Methods:This national cross-sectional community health survey utilized a multistage stratified cluster-random sampling method to recruit 193 997 nationally representative participants from 11 provinces, autonomous regions, or municipalities between January 2017 and December 2019. All participants underwent physical examinations, and their caregivers completed questionnaires assessing participants′ dietary, lifestyle, familial, and perinatal information. Multilevel multinomial logistic regression models were employed to identify the potential risk factors.Results:The cohort comprised 193 997 children (102 178 boys, 91 819 girls),aged (10±4) years. Overall prevalence rates were 30 574(15.8%)overweight children and 17 217(8.9%) obesity children. Boys exhibited higher overweight and obesity rates than girls (17.0% (17 368/102 178) vs. 14.4% (13 206/102 178), 11.3% (11 553/91 819) vs. 6.2% (5 664/91 819), χ2=249.12,1 578.69,both P<0.001). The detection rates of obesity in Tanner stage 2 and 3 were the highest in boys and girls, with 13.4%(2 231/16 665) and 8.6%(880/10 221) respectively. Risk factors for obesity included parental overweight (paternal OR=2.34 and maternal OR=2.29), annual household income of 100 000-200 000 yuan (compared with<100 000 yuan, OR=1.04), higher paternal education (compared with below high school,high school and a college education OR=1.09,1.14), birth weight >4.0 kg (≤5 and>5 years old OR=1.74, 1.44,respectively), and western food consumption≥1 time/month (compared with<1, 1-2, 3-4,>4 times/month OR=1.36, 1.30, 1.67(≤5 years), 1.19, 1.16, 1.15 (>5 years), respectively) (all P<0.05). Conversely, coarse grain intake≥1 times/week (compared with<1 times/week, every day, 3-4, 1-2 times/week OR=0.74, 0.80, 0.71 (≤5 years), 0.75, 0.87, 0.90(>5 years), respectively, all P<0.05) was associated with reduced obesity risk. Conclusions:Obesity epidemiology in children demonstrates significant heterogeneity across age, gender, geographic regions, and pubertal stages. It is necessary to establish a personalized prevention and control strategy.

Objective To analyze the correlation between right atrial strain at various stages and various influencing factors in patients with pulmonary hypertension,and to explore the role of right atrial strain in the assessment of pulmonary hypertension.Methods A total of 239 cases diagnosed with pulmonary hypertension who underwent echocardiography and complete right heart catheterization at hospital from October 2021 to December 2023 were included.Conventional ultrasound parameters such as right heart strain,right atrial area(RA area),inferior vena cava diameter(IVC diameter),and collapse rate of the inferior vena cava(IVC diameter changes)were measured.The heart rate(HR)corresponding to the ultrasound images were recorded.General information such as age and gender,as well as catheter data including mean right atrial pressure(mRAP),mean pulmonary artery pressure(mPAP),and pulmonary vascular resistance(PVR),were collected.The relationship between right atrial strain and its influencing factors was analyzed,and further analysis was conducted by dividing into shunt group and non-shunt group based on the presence or absence of left-to-right shunt disease.Results The correlation with RA reservoir strain(RASr)from high to low is RV global strain(RV4CSL),RV free wall strain(RVFWSL),RA area,IVC diameter,mRAP,age,HR,and PVR;the correlation with RAconduit strain(RAScd)from high to low is RV4CSL,RVFWSL,RA area,IVC diameter,mRAP,age,PVR,and HR;the correlation with RA contraction strain(RASct)from high to low is RA area,RV4CSL,RVFWSL,mRAP,IVC diameter,and HR.The collapse rate of the inferior vena cava is correlated with strain at various stages of the right atrium;gender is correlated with RASr and RASct.Conclusions Right atrial strain can reflect changes in right atrial function,with the highest correlation to right ventricular strain and right atrial area.Right atrial strain can indicate the severity of right ventricular function and right atrial remodeling,serving as an evaluative index for the condition and treatment outcomes of pulmonary arterial hypertension.

This paper focuses on the application of health big data in cancer screening. Firstly, the sources and characteristics of health big data are introduced, then the commonly used epidemiological designs and analytical techniques in hospital-based cancer screening studies are summarized and the application scenarios of such studies are described. Finally, the challenges and future development in the application of health big data are analyzed to provide reference for the future studies.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

This study aims to investigate the therapeutic effect and mechanism of Daotan Xixin Decoction on APP/PS1 mice. Twelve APP/PS1 male mice were randomized into four groups: APP/PS1 and low-, medium-, and high-dose Daotan Xixin Decoction. Three C57BL/6 wild-type mice were used as the control group. The learning and memory abilities of mice in each group were examined by the Morris water maze test. The pathological changes of hippocampal nerve cells were observed by hematoxylin-eosin staining and Nissl staining. Immunohistochemistry was employed to detect the expression of β-amyloid(Aβ)_(1-42) in the hippocampal tissue. The high-dose Daotan Xixin Decoction group with significant therapeutic effects and the model group were selected for high-throughput sequencing. The differentially expressed gene(DEG) analysis, Gene Ontology(GO) analysis, Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis, and Gene Set Variation Analysis(GSVA) were performed on the sequencing results. RT-qPCR and Western blot were conducted to determine the mRNA and protein levels, respectively, of some DEGs. Compared with the APP/PS1 group, Daotan Xixin Decoction at different doses significantly improved the learning and memory abilities of APP/PS1 mice, ameliorated the neuropathological damage in the CA1 region of the hippocampus, increased the number of neurons, and decreased the deposition of Aβ_(1-42) in the brain. A total of 1 240 DEGs were screened out, including 634 genes with up-regulated expression and 606 genes with down-regulated expression. The GO analysis predicted the biological processes including RNA splicing and protein folding, the cellular components including spliceosome complexes and nuclear spots, and the molecular functions including unfolded protein binding and heat shock protein binding. The KEGG pathway enrichment analysis revealed the involvement of neurodegenerative disease pathways, amyotrophic lateral sclerosis, and splicing complexes. Further GSVA pathway enrichment analysis showed that the down-regulated pathways involved nuclear factor-κB(NF-κB)-mediated tumor necrosis factor-α(TNF-α) signaling pathway, UV response, and unfolded protein response, while the up-regulated pathways involved the Wnt/β-catenin signaling pathway. The results of RT-qPCR and Western blot showed that compared with the APP/PS1 group, Daotan Xixin Decoction at different doses down-regulated the mRNA and protein levels of signal transducer and activator of transcription 3(STAT3), NF-κB, and interleukin-6(IL-6) in the hippocampus. In conclusion, Daotan Xixin Decoction can improve the learning and memory abilities of APP/PS1 mice by regulating the STAT3/NF-κB/IL-6 signaling pathway.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Male ; Alzheimer Disease/metabolism* ; Computational Biology ; Mice, Inbred C57BL ; High-Throughput Nucleotide Sequencing ; Amyloid beta-Protein Precursor/metabolism* ; Hippocampus/metabolism* ; Mice, Transgenic ; Presenilin-1/metabolism* ; Humans ; Memory/drug effects* ; Maze Learning/drug effects* ; Amyloid beta-Peptides/genetics* ; Disease Models, Animal

OBJECTIVE: To investigate the association between long-term glycemic control and cerebral infarction risk in patients with diabetes through a large-scale cohort study. METHODS: This prospective, community-based cohort study included 12,054 patients with diabetes. From 2006 to 2012, 38,272 fasting blood glucose (FBG) measurements were obtained from these participants. FBG trajectory patterns were generated using latent mixture modelling. Cox proportional hazards models were applied to assess the subsequent risk of cerebral infarction associated with different FBG trajectory patterns. RESULTS: At baseline, the mean age of the participants was 55.2 years. Four distinct FBG trajectories were identified based on FBG concentrations and their changes over the 6-year follow-up period. After a median follow-up of 6.9 years, 786 cerebral infarction events were recorded. Different trajectory patterns were associated with significantly varied outcome risks (Log-Rank P < 0.001). Compared with the low-stability group, Hazard Ratio ( HR) adjusted for potential confounders were 1.37 for the moderate-increasing group, 1.23 for the elevated-decreasing group, and 2.08 for the elevated-stable group. CONCLUSION Sustained high FBG levels were found to play a critical role in the development of ischemic stroke among patients with diabetes. Controlling FBG levels may reduce the risk of cerebral infarction.
Humans ; Cerebral Infarction/blood* ; Middle Aged ; Male ; Female ; Blood Glucose/analysis* ; Fasting/blood* ; Aged ; Prospective Studies ; Risk Factors ; Diabetes Mellitus/blood* ; Adult ; Proportional Hazards Models