FLAMES overlaying anti-N-methyl-D-aspartate receptor encephalitis: a case report and literature review.

BACKGROUND: In recent years, simultaneous or sequential occurrence of MOG antibody disease and anti-NMDAR encephalitis in the same patient has been reported with increasing frequency. Scholars refer to the overlapping occurrence of these two disorders as MOG antibody disease and anti-NMDAR encephalitis overlap syndrome (MNOS). Cortical T2-weighted fluid-attenuated inversion recovery (FLAIR) -hyperintense lesions in anti-MOG-associated encephalitis with seizures (FLAMES) is a rare clinical phenotype of MOGAD in which cortical FLAIR high-signal lesions are unilateral, with little spread to the cortex and meninges bilaterally. Although cases of FLAMES have been consistently reported. However, to our knowledge, such cases of FLAMES combined with NMDARE are rare. CASE PRESENTATION: Here, we describe a case of FLAMES combined with anti-NMDARE. The patient was a young male, 29 years old, admitted to our hospital with isolated seizures, whose MRI showed unilateral thalamic and bilateral frontal and parietal leptomeningeal involvement. Since we were unaware of the possibility of bilateral meningo-cortical MOGAD manifestations, the case was initially diagnosed as viral encephalitis and was given antiviral therapy. The diagnosis was not clarified until anti-NMDAR-IgG and MOG-IgG positivity was detected in the cerebrospinal fluid and serum. The patient was then treated with high-dose corticosteroids and his symptoms responded well to the steroids. Therefore, this case expands the clinical spectrum of MNOS overlap syndrome. In addition, we describe the clinical features of MNOS by summarizing the existing literature and exploring the possible mechanisms of its immune response. CONCLUSIONS: Our case serves as a reminder to clinicians that when patients present with atypical clinical manifestations such as seizures, consideration should be given to MNOS and conduct testing for various relevant autoantibodies (including MOG abs) and viruses in both serum and cerebrospinal fluid, as it is easy to misdiagnose the disease as other CNS diseases, such as viral meningoencephalitis. This syndrome exhibits a high responsiveness to steroids, highlighting the critical importance of recognizing the clinical and neuroimaging features of this overlap syndrome for prompt diagnosis and treatment. Furthermore, it enriches the disease spectrum of MNOS.

An Immunochromatographic Test Strip for Rapid Quantitative Control of Monoclonal Antibodies against Programmed Cell Death Protein 1.

Cancer is one of the major public health challenges in the world, which is characterized by rapid progression and high mortality. Immunotherapy, represented by PD-1 monoclonal antibody, has significantly improved the efficacy of malignant tumors and has become one of the most popular immunotherapy methods at present. Therefore, there is an increasing demand for novel detection methods for PD-1 monoclonal antibodies. The aim of this work was to establish a rapid, simple, and sensitive immunochromatographic test strip (ICTS) based on the AuNPs enlargement for both visual and instrumental detection of the PD-1 monoclonal antibody concentration. The mixed solution of NH2OH·HCl and HAuCl4 was used as an enhancement solution to lower the detection limit and achieve higher sensitivity. A test strip reader was used to construct a visualized quantitative detection standard curve for the PD-1 monoclonal antibody concentration. The LOD was 1.58 ng/mL through a triple signal-to-noise ratio. The detection time was within 10 min. The constructed test strips can rapidly, accurately, and efficiently detect the concentration of PD-1 monoclonal antibody in real samples.

Spatial distribution patterns and drivers of above- and below- biomass in Chinese terrestrial ecosystems.

Unraveling the dynamics of the global carbon cycle and assessing the sustainability of terrestrial ecosystems are critically dependent on a comprehensive understanding of vegetation biomass. This exploration delves into the pivotal role of biomass within vegetation communities, emphasizing its impact on ecosystem health, productivity, and community structure development. These insights are invaluable for advancing ecological science and conservation efforts. The synthesis of aboveground (AGB) and belowground (BGB) biomass data from 4485 and 3442 locations across China, respectively, collates a wide range of published sources. Integrating this extensive dataset with environmental parameters and applying advanced machine learning techniques facilitated an in-depth analysis of AGB and BGB spatial patterns within China. Techniques such as variance decomposition analysis and piecewise structural equation modeling were employed to dissect the factors contributing to the spatial variability of vegetation biomass. Significant spatial heterogeneity in biomass distribution was uncovered, with vegetation biomass in the northwest markedly lower than in the southern and northeastern regions. It was observed that AGB consistently surpassed BGB. Climatic conditions, soil characteristics, and soil nutrients were found to significantly explain 53 % and 48 % of the total variance in AGB and BGB, respectively. Specifically, solar radiation and soil total nitrogen were identified as critical factors influencing variations in AGB and BGB. The findings offer profound contributions to the understanding of the global carbon balance and the evaluation of terrestrial ecosystems sustainability. Moreover, they provide essential insights into the ecosystems' response mechanisms to global changes, serving as a fundamental reference for future studies on terrestrial ecosystem carbon cycling and carbon sequestration potentials.

Spatial patterns and drivers of ecosystem multifunctionality in China: Arid vs. humid regions.

Ecosystem multifunctionality (EMF) refers to an ecosystem's capacity to simultaneously uphold multiple ecological functions or services. In terrestrial ecosystems, the potential patterns and processes of EMF remain largely unexplored, limiting our comprehension of how ecosystems react to various driving factors. We collected environmental, soil and plant nutrient data, investigate the spatial distribution characteristics of EMF in China's terrestrial ecosystems, differentiating between arid and humid regions and examining the underlying drivers. Our findings reveal substantial spatial heterogeneity in the distribution of EMF across China's terrestrial ecosystems, with pronounced variations between arid and humid regions. In arid regions, the EMF index predominantly falls within the range of -1 to 1, including approximately 66.8 % of the total area, while in humid regions, the EMF index primarily falls within the range of 0 to 2, covering around 55.2 % of the total area. Climate, soil, and vegetation factors account for 61.4 % and 51.9 % of the total EMF variation in arid and humid regions, respectively. Notably, climate emerges as the dominant factor governing EMF variation in arid regions, whereas soil physicochemical properties take precedence in humid regions. Specifically, mean annual temperature (MAT) emerges as the primary factor influencing EMF variation in arid regions, while the normalized difference vegetation index (NDVI) and soil biodiversity index (SBI) play pivotal roles in regulating EMF variation in humid regions. Indeed, climate can exert both direct and indirect influences on EMF. In summary, our study not only compared the disparities in the spatial distribution of EMF in arid and humid regions but also unveiled the distinct controlling factors that govern EMF changes in these different regions. Our research has contributed novel insights for evaluating the drivers responsible for mediating EMF in diverse ecosystems, shedding light on the adaptability and response mechanisms of ecosystems under varying environmental conditions.

Relationship among Parkinson's disease, constipation, microbes, and microbiological therapy.

This comprehensive review elucidates the complex interplay between gut microbiota and constipation in Parkinson's disease (PD), a prevalent non-motor symptom contributing significantly to patients' morbidity. A marked alteration in the gut microbiota, predominantly an increase in the abundance of Proteobacteria and Bacteroidetes, is observed in PD-related constipation. Conventional treatments, although safe, have failed to effectively alleviate symptoms, thereby necessitating the development of novel therapeutic strategies. Microbiological interventions such as prebiotics, probiotics, and fecal microbiota transplantation (FMT) hold therapeutic potential. While prebiotics improve bowel movements, probiotics are effective in enhancing stool consistency and alleviating abdominal discomfort. FMT shows potential for significantly alleviating constipation symptoms by restoring gut microbiota balance in patients with PD. Despite promising developments, the causal relationship between changes in gut microbiota and PD-related constipation remains elusive, highlighting the need for further research in this expanding field.

Soil organic carbon fractions in China: Spatial distribution, drivers, and future changes.

Soil is the world's largest terrestrial carbon pool and plays an important role in the global carbon cycle, which may be greatly affected by global change. Recently, research frameworks have indicated that division of soil organic carbon (SOC) into two forms particulate organic carbon (POC) and mineral-associated organic carbon (MAOC) can help us better understand SOC cycle. However, there is a lack of the use of meta-analysis combined with machine learning models to explore the spatial distribution of SOC fractions at large scales. Based on 356 studies conducted in Chinese terrestrial ecosystems, we performed a meta-analysis of extracted data and measured data combined with machine learning models to reveal the spatial distribution of soil POC density (POCD) and MAOC density (MAOCD) and the main drivers of variations in POCD and MAOCD. Our study demonstrated that POCD and MAOCD in China's soil were 3.24 and 2.61 kg m-2, with stocks of 31.10 and 25.06 Pg, respectively. Climate, soil, and vegetation properties together explained 44.9 % and 27.2 % of the variation in POCD and MAOCD, respectively. Climate was more important than other variables in controlling the changes in POCD, with mean annual temperature being specifically the main driver. Soil, however, was more important than other variables in controlling changes in MAOCD, with soil clay content being the main driver. Compared to the other climate scenarios, the rate of change in POCD and MAOCD was higher with a 1.5 °C increase in temperature. In the future, we should pay more attention to the impact of climate change on POCD, which provides a theoretical basis for achieving the "dual-carbon" target. Our study contributes to the understanding of the potential mechanisms of the changes in SOC fractions under global change and provides useful information for future prediction models to simulate the impacts of global change.