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.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Objective To explore the application of plasma 7 microRNA (miR7) testing in the differential diagnosis of very early-stage hepatocellular carcinoma (HCC). Methods This study is a multicenter real-world study. Patients with single hepatic lesion (maximum diameter≤2 cm) who underwent plasma miR7 testing at Zhongshan Hospital, Fudan University, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Anhui Provincial Hospital, and Peking University People’s Hospital between January 2019 and December 2024 were retrospectively enrolled. Patients were divided into very early-stage HCC group and non-HCC group, and the clinical pathological characteristics of the two groups were compared. The value of plasma miR7 levels, alpha-fetoprotein (AFP), and des-gamma-carboxy prothrombin (DCP) in the differential diagnosis of very early-stage HCC was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). In patients with both negative AFP and DCP (AFP＜20 ng/mL, DCP＜40 mAU/mL), the diagnostic value of plasma miR7 for very early-stage HCC was analyzed. Results A total of 64 528 patients from 4 hospitals underwent miR7 testing, and 1 682 were finally included, of which 1 073 were diagnosed with very early-stage HCC and 609 were diagnosed with non-HCC. The positive rate of miR7 in HCC patients was significantly higher than that in non-HCC patients (67.9% vs 24.3%, P＜0.001). ROC curves showed that the AUCs for miR7, AFP, and DCP in distinguishing HCC patients from the non-HCC individuals were 0.718, 0.682, and 0.642, respectively. The sensitivities were 67.85%, 43.71%, and 44.45%, and the specificities were 75.70%, 92.78%, and 83.91%, respectively. The pairwise comparison of AUCs showed that the diagnostic efficacy of plasma miR7 detection was significantly better than that of AFP or DCP (P＜0.05). Although its specificity was slightly lower than AFP and DCP, the sensitivity was significantly higher. Among patients negative for both AFP and DCP, miR7 maintained an AUC of 0.728 for diagnosing very early-stage HCC, with 67.82% sensitivity and 77.73% specificity. Conclusions Plasma miR7 testing is a potential molecular marker with high sensitivity and specificity for the differential diagnosis of small hepatic nodules. In patients with very early-stage HCC lacking effective molecular markers (negative for both AFP and DCP), miR7 can serve as a novel and effective molecular marker to assist diagnosis.

Objective To systematically evaluate the radiation impact of radioactive sources used in online elemental analyzers in cement enterprises on the surrounding environment, and to provide a scientific basis for radiation monitoring and safety management at the application sites of this type of radioactive sources. Methods A statistical analysis was conducted on 15 cement enterprises in Guangxi Province using online elemental analyzers with ²⁵²Cf as the radioactive source. On-site investigation of radiation safety management and on-site monitoring of radiation environment were performed, followed by an evaluation based on the collected data. Results Although the gamma radiation ambient dose equivalent rate and neutron ambient dose equivalent rate increased around the sites using online elemental analyzers with ²⁵²Cf as the radioactive source, they all met the requirements of the Radiological Health Protection Requirements for Instruments with Sealed Sources (GBZ 125—2009). Conclusion Under the current usage and management conditions, the application of this type of radioactive sources has controllable radiation impact on the surrounding environment, and will not pose a threat to public health and environmental safety. However, continuous strengthening of radiation safety management measures and regular radiation monitoring work are still needed to ensure the safe use of radioactive sources, further reducing potential radiation risks and providing strong guarantees for the safe application of radioactive sources in online elemental analyzers in cement enterprises.

Objective: To investigate the cross sectional association between bedroom nocturnal light exposure and objectively measured sleep parameters in college students, so as to provide evidence for promoting sleep health. Methods: From September to October 2019, a convenience sampling method was used to recruit 365 healthy college students from two universities in Hefei, establishing a cohort. Bedroom nocturnal light exposure was measured at the individual level for two consecutive days using a portable illuminometer (TES-1339R; Taishi Corp, Taiwan, China). Sleep parameters were objectively measured over seven consecutive days using wrist worn accelerometers (ActiGraph GT3X-BT, Pensacola, FL). Multiple linear regression models were employed to examine the association between nocturnal light exposure and sleep parameters. Results: Compared to the low nocturnal light exposure (<3 lx) group, the high exposure (≥3 lx) group exhibited significantly lower sleep efficiency[(93.5± 2.7 )%,(92.2±2.9)%, t =3.93], longer wake after sleep onset (WASO)[(24.7±90.3)(29.2±11.2)min, t =-3.66], higher movement index(11.0±3.6, 12.2± 3.8, t =-2.80), and higher sleep fragmentation index(20.5±6.5,23.0±7.0, t =-3.24) (all P <0.01). After adjusting for covariates,multiple linear regression showed that,compared to the low nocturnal light exposure group, the high exposure group had reduced sleep efficiency ( β =-1.15, 95% CI =-1.78 to -0.52), increased WASO [ β (95% CI )=3.94(1.55- 6.33 )], higher movement index[ β (95% CI )=1.05(0.20-1.89)], and elevated sleep fragmentation index[ β (95% CI )=2.35(0.81-3.88)](all P <0.05). Conclusions Light exposure at night negatively impacts college students sleep. Optimizing bedroom lighting management may improve sleep quality in adolescents.

Idiosyncratic drug-induced liver injury (IDILI) has long posed a challenging and pivotal concern in pharmaceutical research. The complex composition of traditional Chinese medicine (TCM) has introduced a bottleneck in current research, hindering the elucidation of the component basis associated with IDILI in TCM. Using Epimedii Folium (EF) and Psoraleae Fructus (PF) as illustrative examples, this study endeavors to establish an in vitro evaluation model, providing a high-throughput and preliminary assessment method for screening components related to TCM-induced IDILI. A TNF-α-mediated HepG2 susceptible model was first established in this study, with the focus on the index components present in EF and PF. The release of lactate dehydrogenase (LDH) in the cell supernatant served as the detection index. A concentration-toxicity response curve was constructed, and the hepatotoxic components of EF and PF were identified utilizing the synergistic toxicity index. The LDH results unveiled the hepatotoxic effects of bavachin, backuchiol, isobavachin, neobavaisoflavone, psoralidin, isobavachalcone, icarisid I, and icarisid II on both normal and susceptible cells, categorizing these 8 components as both direct hepatotoxicity components and idiosyncratic hepatotoxicity components. Bavachin and neobavaisoflavone exhibited no hepatotoxicity on normal cells but demonstrated significant effects on susceptible cells, designating them as potential idiosyncratic susceptible hepatotoxicity components. The study further delineated that 10 EF components and 3 PF components were direct immune-promoting hepatotoxicity components. Additionally, 14 idiosyncratic immune-promoting hepatotoxicity components were identified, encompassing 10 EF components and 4 PF components, with neobavaisoflavone, bavachinin, and isobavachin being potential idiosyncratic susceptible immune-promoting hepatotoxicity components. Synergistic toxicity index results indicated that 13 idiosyncratic immune-promoting hepatotoxicity components (except anhydroicaritin) combined with bavachin demonstrated synergistic hepatotoxicity on susceptible cells. Notably, 3 idiosyncratic susceptible immune-promoting hepatotoxicity components combined with bavachin exhibited synergistic hepatotoxicity, with neobavaisoflavone displaying the highest synergistic toxicity index and bavachinin the lowest. In summary, this methodology successfully screens hepatotoxic and immune-promoting hepatotoxic components in EF and PF, distinguishing the types of components inducing hepatotoxicity, evaluating the hepatotoxicity degree of each component, and elucidating the synergistic relationships among them. Importantly, these findings align with the characteristics of IDILI. The method provides an effective model tool for the fundamental research of TCM-related IDILI components.

Objective To summarize the epidemiological and clinical features of infectious diseases of the central nervous system(CNS)by a single-center analysis.Methods A retrospective analysis was conducted on the data of 1247 cases of CNS infectious diseases diagnosed and treated in the First Medical Center of PLA General Hospital from 2001 to 2020.Results The data for this group of CNS infectious diseases by disease type in descending order of number of cases were viruses 743(59.6％),Mycobacterium tuberculosis 249(20.0％),other bacteria 150(12.0％),fungi 68(5.5％),parasites 18(1.4％),Treponema pallidum 18(1.4％)and rickettsia 1(0.1％).The number of cases increased by 177 cases(33.1％)in the latter 10 years compared to the previous 10 years(P<0.05).No significant difference in seasonal distribution pattern of data between disease types(P>0.05).Male to female ratio is 1.87︰1,mostly under 60 years of age.Viruses are more likely to infect students,most often at university/college level and above,farmers are overrepresented among bacteria and Mycobacterium tuberculosis,and more infections of Treponema pallidum in workers.CNS infectious diseases are characterized by fever,headache and signs of meningeal irritation,with the adductor nerve being the more commonly involved cranial nerve.Matagenomic next-generation sequencing improves clinical diagnostic capabilities.The median hospital days for CNS infectious diseases are 18.00(11.00,27.00)and median hospital costs are ￥29,500(￥16,000,￥59,200).The mortality rate from CNS infectious diseases is 1.6％.Conclusions The incidence of CNS infectious diseases is increasing last ten years,with complex clinical presentation,severe symptoms and poor prognosis.Early and accurate diagnosis and standardized clinical treatment can significantly reduce the morbidity and mortality rate and ease the burden of disease.

Objective To study the feasibility on automatic contouring of pelvic intestinal tube based on deep learning for radiotherapy images.Methods A total of 100 patients with diagnosis of rectal cancer,received radiotherapy in Zhongshan Hospital,Fudan University from 2019 to 2021,were randomly selected.Sixty cases were randomly enrolled to train the models,and the other 40 cases were applied to test.Based on the original small intestine model in automatic segmentation software AccuContour,60,40 and 20(2 groups)cases in the model cases were used to train the models Rec60,Rec40,Rec20A and Rec20B with manual contouring as ground truth.Other 40 cases for test were applied to evaluate the Dice similarity coefficient(DSC),95%Hausdorff distance(HD95)and average symmetric surface distance(ASSD)between the manual contouring and original model along with model Rec60.The DSC of the 5 groups of auto-segmentations were compared as well.The paired t tests were performed for each pair of the original model and 4 trained models.Results The small bowel contoured by trained models were more similar to the manual contouring.They could distinguish the boundary of the intestinal tube better and distinguish the small bowel from the colon.The average DSC,HD95 and ASSD of Rec60 were 0.16 higher(P＜0.001),12.4 lower(P＜0.001)and 5.14 lower(P＜0.001)than the original model respectively.According to the paired t tests,there were no statistical differences in DSC between the 4 training models and the original model.No statistical difference was observed between Rec60 and Rec40,while they were both significantly different from the two Rec20 models.There was no statistical difference between Rec20B and Rec20B.Conclusion For radiotherapy images,model training can effectively improve the accuracy of intestinal tube delineation.Forty cases were enough for training an optimal model of automatic segmentation for pelvic intestinal tube in AccuContour software.