[Identification of Nitrate Source and Transformation Process in Shallow Groundwater Around Dianchi Lake].

Elucidating the main sources and transformation process of nitrate for the prevention and control of groundwater nitrogen pollution and the development and utilization of groundwater resources has great significance. To explore the current situation and source of nitrate pollution in shallow groundwater around the Dianchi Lake, 73 shallow groundwater samples were collected in the rainy season in 2020(October) and dry season in 2021(April). Using the hydrochemistry and nitrogen and oxygen isotopes(δ15N-NO3- and δ18O-NO3-), the spatial distribution, source, and transformation process of nitrate in shallow groundwater were identified. The contribution of nitrogen from different sources to nitrate in shallow groundwater was quantitatively evaluated using the isotope mixing model(SIAR). The results showed that in nearly 40.5% of sampling points in the shallow groundwater in the dry season, ρ(NO3--N) exceeded the 20 mg·L-1 specified in the Class Ⅲ water quality standard for groundwater(GB/T 14848), and in more than 47.2% of sampling points in the rainy season, ρ (NO3--N) exceeded 20 mg·L-1. The analysis results of nitrogen and oxygen isotopes and SIAR model showed that soil organic nitrogen, chemical fertilizer nitrogen, and manure and sewage nitrogen were the main sources of nitrate in shallow groundwater; these nitrogen sources contributed 13.9%, 11.8%, and 66.5% to nitrate in shallow groundwater in the dry season and 33.7%, 31.1%, and 25.9% in the rainy season, respectively. However, the contribution rate of atmospheric nitrogen deposition was only 8.5%, which contributed little to the source of nitrate in shallow groundwater in the study area. Nitrification was the leading process of nitrate transformation in shallow groundwater in the dry season, denitrification was the dominant process in the rainy season, and denitrification was more noticeable in the rainy season than that in the dry season.

Advances in Neuroimaging and Multiple Post-Processing Techniques for Epileptogenic Zone Detection of Drug-Resistant Epilepsy.

Among the approximately 20 million patients with drug-resistant epilepsy (DRE) worldwide, the vast majority can benefit from surgery to minimize seizure reduction and neurological impairment. Precise preoperative localization of epileptogenic zone (EZ) and complete resection of the lesions can influence the postoperative prognosis. However, precise localization of EZ is difficult, and the structural and functional alterations in the brain caused by DRE vary by etiology. Neuroimaging has emerged as an approach to identify the seizure-inducing structural and functional changes in the brain, and magnetic resonance imaging (MRI) and positron emission tomography (PET) have become routine noninvasive imaging tools for preoperative evaluation of DRE in many epilepsy treatment centers. Multimodal neuroimaging offers unique advantages in detecting EZ, especially in improving the detection rate of patients with negative MRI or PET findings. This approach can characterize the brain imaging characteristics of patients with DRE caused by different etiologies, serving as a bridge between clinical and pathological findings and providing a basis for individualized clinical treatment plans. In addition to the integration of multimodal imaging modalities and the development of special scanning sequences and image post-processing techniques for early and precise localization of EZ, the application of deep machine learning for extracting image features and deep learning-based artificial intelligence have gradually improved diagnostic efficiency and accuracy. These improvements can provide clinical assistance for precisely outlining the scope of EZ and indicating the relationship between EZ and functional brain areas, thereby enabling standardized and precise surgery and ensuring good prognosis. However, most existing studies have limitations imposed by factors such as their small sample sizes or hypothesis-based study designs. Therefore, we believe that the application of neuroimaging and post-processing techniques in DRE requires further development and that more efficient and accurate imaging techniques are urgently needed in clinical practice. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Application value of multimodal MRI combined with PET metabolic parameters in temporal lobe epilepsy with dual pathology.

OBJECTIVES: To investigate the application value of multimodal MRI combined with PET metabolic parameters in detecting temporal lobe epilepsy (TLE) with dual pathology (DP) and the prediction effect of post-surgical outcomes in these patients. METHODS: We retrospectively reviewed 50 patients with TLE-DP who underwent surgery at our hospital between January 2016 and December 2021 and collected the demographics, clinical characteristics, video-electroencephalography (v-EEG), neuroimaging, and surgical data. Seizure outcome data were collected during a regular follow-up of at least 12 months and were graded using Engel scores. Fisher's exact test was used to compare the differences in DP detection rates of various diagnostic modalities. Univariate and multivariate analyses were performed to explore the prognostic factors for predicting seizure outcomes post-surgery. RESULTS: Of the 50 patients, 20 were males. The median age was 30, the median age at first seizure was 14, and the median duration was ten years. Voxel-based morphometry-PET statistical parametric mapping-PET/MRI (VBM-PSPM-PET/MRI) had the highest detection rate, followed by PET/MRI, VBM analysis, and PET-SPM. Regardless of follow-up duration, v-EEG, PET, image post-processing methods, and VBM-PSPM-PET/MRI statistically correlated with seizure outcomes using the log-rank test in the Kaplan-Meier analysis. Multivariate analysis showed that VBM-PSPM-PET/MRI was an independent predictor of TLE-DP (hazard ratio (HR) = 15.674, 95 % CI = 0.002-0.122, P < 0.00 1). CONCLUSIONS: Our study illustrates that VBM-PSPM-PET/MRI has the highest detection value in patients with TLE-DP and can provide independent prognostic information for patients who undergo surgery. This approach has the most substantial potential for the selection of candidates for patients who undergo surgical treatment and for prognostic stratification.

[Shallow Groundwater Around Plateau Lakes: Spatiotemporal Distribution of Phosphorus and Its Driving Factors].

The extensive application of phosphorus fertilizers to croplands and the aggregation of towns and villages around plateau lakes has resulted in the continuous accumulation of phosphorus in the soil profile and the discharge of phosphorus pollutants, which causes phosphorus pollution in shallow groundwater around the lakes. The phosphorus entering the lake with shallow underground runoff in the region around the lake also affects the water quality safety of plateau lakes. The spatiotemporal differences in phosphorus concentrations in 452 shallow groundwater samples and the driving factors were analyzed by monitoring wells in croplands and residential areas around the eight lakes in Yunnan province during the rainy and dry seasons from 2019 to 2021. The results showed that seasonal changes and land use influenced phosphorus concentrations and their composition in shallow groundwater. The concentration of phosphorus in shallow groundwater in the rainy season was higher than that in the dry season, and it was also greater in cropland than that in residential areas. DTP was the dominant form of TP, accounting for 75%-81%, and DIP was the dominant form of DTP, accounting for 74%-80%. Nearly 30% of the samples around the eight lakes had TP concentrations exceeding the surface water Class Ⅲ standard (GB 3838); the exceeded rates of phosphorus in groundwater around the Erhai Lake (52%), Qiluhu Lake (45%), Xingyun Lake (42%), and Dianchi Lake (29%) were far higher than those of Yangzonghai Lake (16%), Fuxianhu Lake (13%), Chenghai Lake (6%), and Yilonghu Lake (5%). The key driving factors of phosphorus concentrations in shallow groundwater were water-soluble phosphorus (WEP), water content (MWC), soil organic matter (SOM), total nitrogen (TN), pH in the soil profile, and pH and groundwater level in the shallow groundwater (P<0.05). The increases in WEP, SOM, TN, and MWC in the soil and pH in groundwater significantly increased the concentrations of DIP and DTP in shallow groundwater, whereas the decrease in groundwater level significantly reduced the concentrations of DTP and DIP in the groundwater.

[Shallow Groundwater Around Plateau Lakes: Spatiotemporal Distribution of Nitrogen and Its Driving Factors].

Shallow groundwater around plateau lakes is one of the important sources of production and potable water. Shallow groundwater NO3--N pollution driven by factors such as surface nitrogen input load, rainfall, and irrigation is serious and threatens the water quality of plateau lakes. In order to identify the characteristics of nitrogen pollution and its driving factors in shallow groundwater, 463 shallow groundwater samples were collected from wells in farmland and residential areas around eight plateau lakes of Yunnan in the rainy and dry seasons in 2020 and 2021. The results showed that the average values of ρ(TN), ρ(NO3--N), ρ(ON), and ρ(NH4+-N) in shallow groundwater were 24.35, 15.15, 8.41, and 0.79 mg·L-1, respectively. Nearly 32% of the shallow groundwater samples around the eight lakes failed to meet the groundwater Class Ⅲ water quality requirements (GB/T 14848) of 20 mg·L-1 for NO3--N. Among them, the NO3--N concentration in the shallow groundwater around Erhai Lake, Qiluhu Lake, and Dianchi Lake had the highest rate of exceeding the standard, followed by that around Xingyunhu Lake, Yangzonghai Lake, Yilonghu Lake, Fuxianhu Lake, and Chenghai Lake as the smallest. Land use and seasonal changes affected the concentration and composition of various forms of nitrogen in shallow groundwater. The concentration of various forms of nitrogen in shallow groundwater in the farmland area was higher than that in the residential area. The nitrogen concentration in shallow groundwater in farmland was higher than that in residential areas. Except for NH4+-N, the concentration of various forms of nitrogen in shallow groundwater in the rainy season was higher than that in the dry season. NO3--N was the main nitrogen form in shallow groundwater; the fraction of TN was 57%-68%, and the fraction of ON was 27%-38%. The EC, DO, ORP, and T in shallow groundwater were the key factors reflecting or affecting the concentration of various forms of nitrogen in shallow groundwater, whereas soil factors had a weak impact on the concentration of various forms of nitrogen in shallow groundwater.

Expression and significance of CD4(+)CD25(+)CD127(-) regulatory T cells in peripheral blood of patients with different phenotypes of Guillain-Barré syndrome.

OBJECTIVE: This study aims to investigate the changes of immune status and significance in patients with Guillain-Barré syndrome (GBS). METHODS: The proportion of CD4(+)CD25(+)CD127(-) regulatory T cells in peripheral blood before immunotherapy for 41 patients with GBS (including 29 classic type and 12 variant type) and 42 normal control patients (healthy volunteers) were evaluated by flow cytometry. And molybdenum three phenol red method was used to detect cerebrospinal fluid protein content of 28 patients with GBS (including 19 with classic type and 9 with variant type). RESULTS: Compared with healthy control group, the CD4(+)CD25(+)CD127(-) of GBS group had obvious difference (P<0.05). Of which, the CD4(+)CD25(+)CD127(-) regulatory T cells of the classic GBS group had no significant changes compared with the variant group (P>0.05), as well as the cerebrospinal fluid protein content between classic and variant GBS groups. The decrease of the proportion of CD4(+)CD25(+)CD127(-) regulatory T cells suggested abnormal expression of immune function in GBS patients. CONCLUSION: The decrease of GBS regulatory T cell number or function indicated that the immune regulatory T cells mediated imbalance of immune regulation involved in the pathogenesis of GBS.