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 evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

OBJECTIVE To construct three-class （insufficient， normal， excessive） and two-class （insufficient， normal） models for predicting plasma concentration of valproic acid （VPA）， and compare the performance of these two models， with the aim of providing a reference for formulating clinical medication strategies. METHODS The clinical data of 480 patients who received VPA treatment and underwent blood concentration test at the Xi’an International Medical Center Hospital were collected from November 2022 to September 2024 （a total of 695 sets of data）. In this study， predictive models were constructed for target variables of three-class and two-class models. Feature ranking and selection were carried out using XGBoost scores. Twelve different machine learning algorithms were used for training and validation， and the performance of the models was evaluated using three indexes: accuracy， F1 score， and the area under the working characteristic curve of the subject （AUC）. RESULTS XGBoost feature importance scores revealed that in the three-class model， the importance ranking of kidney disease and electrolyte disorders was higher. However， in the two-class model， the importance ranking of these features significantly decreased， suggesting a close association with the excessive blood concentration of VPA. In the three-class model， Random Forest method performed best， with F1 score of 0.704 0 and AUC of 0.519 3 on the test set； while in the two-class model， CatBoost method performed optimally， with F1 score of 0.785 7 and AUC of 0.819 5 on the test set. CONCLUSIONS The constructed three-class model has the ability to predict excessive VPA blood concentration， but its prediction and model generalization abilities are poor； the constructed two-class model can only perform classification prediction for insufficient and normal blood concentration cases， but its model performance is stronger.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

ObjectiveTo improve the quality and service performance of community visual health services in Shanghai, and to establish a set of reasonable and effective evaluation index system for community visual health services. MethodsCentered on the national and Shanghai-based visual health policies and based on the current status and development trends of community visual health service program in Shanghai, the candidate indicators were formed through literature review and expert interviews, firstly. The framework of an evaluation index system was formulated through qualitative research successively, which was further revised and perfected using the Delphi method. Coefficient weights were calculated using the analytic hierarchy process (AHP), culminating in the establishment of the community visual health evaluation index system, lastly. ResultsA total of 22 visual health experts from district-level center for disease control, hospital ophthalmology and leaders in charging of visual health service in community health centers participated in the Delphi questionnaire survey, with a questionnaire recovery rate of 100% and an expert authority coefficient of 0.86, indicating high credibility. After a round of correspondence to experts’ importance ratings and discussions, a comprehensive evaluation index system comprising 3 primary indicators, 12 secondary indicators, and 47 tertiary indicators, along with 5 additional indicators, was finalized. ConclusionAn index system tailored to effective evaluation for community visual health initiatives was drawn up in this study, which can promote the capacity building in community eye health services, facilitating the high-quality development of visual health courses, and enhancing residents’ eye health.

The theory of "turbid pathogen harming the clarity" was proposed by YE Tianshi in his book Wenre Lun, which can be applied to clear orifices diseases such as ear, eye, nose, and mouth. Based on the location and characteristics of vitreous opacity, as well as its understanding by medical professionals throughout history, this article points out that the core pathogenesis of vitreous opacity is "turbid pathogen harming the clarity" and the obstruction of the spirit light, and the basic pathogenesis is: unfavorable liver and gallbladder conditions, damp heat accumulation and turbidity; imbalance of middle jiao, qi deficiency leading to turbidity; kidney failure with yang deficiency, stagnant water and fluids; and stagnation entering the collaterals for an extended time, causing blockage and turbidity. And based on the pathogenesis of "turbid pathogen harming the clarity" , corresponding treatment principles are proposed: soothing liver and promoting bile flow, clearing heat and eliminating turbidity; cultivating soil to produce gold, enhancing clarity and reducing turbidity; tonifying kidney and promoting yang, warming and dispelling turbid pathogens; and removing blood stasis and activating collaterals, dispelling turbidity and unblocking the orifices. Based on the theory of "turbid pathogen harming the clarity" , this article summarizes the pathogenesis and treatment of vitreous opacity, in order to provide new ideas for traditional Chinese medicine treatment of this disease.