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Abstract 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.

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.

Drylands are highly vulnerable to climate change and human activities. The drylands of China account for approximately 10.8% of global drylands, and China is the country most severely affected by aridity in Asia. Therefore, studying the spatial variation characteristics in soil multifunctionality (SMF) and investigating the driving factors are critical for elucidating and managing the functions of dryland ecosystems in China. Based on the environmental factors (mean annual precipitation (MAP), mean annual temperature (MAT), solar radiation (Srad), soil acidity (pH), enhanced vegetation index (EVI), and cation exchange capacity (CEC)) and aridity from the Dataset of soil properties for land surface modeling over China, we used non-linear regression, ordinary least square (OLS) regression, structural equation model (SEM), and other analytical methods to investigate the relationships of SMF with environmental factors across different aridity levels in China. SMF in different dryland regions varied significantly and showed a patchy distribution, with SMF index values ranging from −1.21 to 2.42. Regions with SMF index values from −0.20 to 0.51 accounting for 63.0% of dryland area in China. OLS regression results revealed that environmental factors like MAP, MAT, Srad, pH, EVI, and CEC were significantly related to SMF (P ​

Red mud (RM) a solid waste generated by the bauxite smelting industry, is a rich source of metal resources, especially Ti, and its recycling can bring significant environmental and economic benefits. In this study, precious metal Ti was efficiently recovered from red mud using a coupled acid leaching and boiling route for the effective separation of low-value metals. The red mud which contained mainly 10.69% Si, 12.1% Al, 15.2% Ca, 10.99% Fe, and 4.37% Ti, was recovered in five steps. First, a nitric acid solution was used to leach the metals in multiple stages, resulting in an acidic leach solution with high concentrations of Fe, Al, Ti, and Ca ions 2.7 g/L, 4.7 g/L, 5.43 g/L, and 1.8 g/L, respectively. Then, a small amount of sucrose was added as a catalyst to recover Ti from the leach solution under hydrothermal conditions, resulting in the targeted recovery of 98.6% of Ti in the form of high-purity anatase while Fe, Al, and Ca remained in the solution. Next, the Fe in solution was separated as hematite products at a temperature of 110°C and a reaction time of 4 h. Similarly, the Al in the solution was separated and precipitated as boehmite by heating it at 260°C for a reaction time of 20 h. Finally, the remaining Ca in solution was recovered by simple pH regulation. Economic accounting assessment showed that the method yields $101.06 for 1 t of red mud treated, excluding labor costs. This study provides a novel approach to recover precious metals from metal wastes through the whole process resource recovery of solid waste red mud.

Soil nutrient status is a crucial measure of soil fertility, which not only coordinates and provides the nutrients necessary for plant growth, but also stimulates the decomposition of soil humus and biogeochemical cycles. Therefore, understanding the distribution characteristics of soil nutrients in the Kyrgyzstan, while exploring the drivers of their variability, is important for understanding ecological processes and the distribution of soil resources. Simultaneously, the study of the spatial distribution of soil multifunctionality and its drivers across Kyrgyzstan can better elucidate the functions of the entire ecosystem, assist in optimizing the allocation of resources and serve as a reference material for the scientific and rational management of the country’s soil ecosystems. In this paper, We have used field sampling data from Kyrgyzstan, to examined the geographic variability and distribution of soil nutrients and soil multifunctionality within different soil depths, as well as the drivers in the country, using a combination of factor analysis and structural equation modeling (SEM). Findings indicated: (1)The topsoil of Kyrgyzstan (0–30 cm) stores 4.24 ± 0.59 Pg of SOC, 0.33 ± 0.06 Pg of total nitrogen (TN), 0.31 ± 0.03 Pg of total phosphorus (TP), and 5.12 ± 1.84 Pg of total potassium (TK). The nutrient reserves of various land-cover categories vary greatly across the nation, with grasslands accounting for the largest reserves (40%) but urban areas allocating the smallest proportion (0.3%). (2): the analysis revealed that using the linear or nonlinear fitting equations, the majority of soil nutrients exhibited a strong correlation with each other and also environmental parameters; (3): in Kyrgyzstan, soil multifunctionality varied substantially from –0.63 to 2.30 across regions. (4): according to the SEM results, NPP, wind speed (VS), MAP, longitude (Lon), SWC, and pH directly affected soil multifunctionality. In addition, several indirect effects of ST, MAT, Sard, and latitude (Lat) on soil multifunctionality were observed. Lon, map, SWC, and pH also had various direct and indirect impacts on soil multifunctionality. The findings of this study shed light on the functions of the entire soil ecosystem in the Kyrgyz Republic that help better predict the effects of environmental changes on ecosystem multifunctionality in drylands and provide a scientific basis for rational utilization of soil resources, efficient management of dryland soils, and prevention of land productivity decline in the country.

Land degradation destroys human habitats, and vegetation is a marker reflecting land degradation. In this article, the Balochistan Province of Pakistan, which has a fragile ecological environment, was selected as a typical case to analyze its land degradation over 21 years. Relevant studies that used the NDVI and remote sensing data to monitor land degradation already existed. Based on the data product of MODIS, this study obtained the spatio-temporal trends of the normalized difference vegetation index (NDVI) changes from 2000 to 2020 using the sen+ Mann–Kendall (MK) test and Hurst index and analyzed the driving factors of land degradation and restoration by employing the multiple stepwise regression method. The residual analysis method was an effective tool for distinguishing between anthropogenic and climatic impacts, given that not all regions have a significant correlation between the NDVI and rainfall. The main climatic drivers of the NDVI were derived based on the Geodetector analysis and stripped of the main climatic factors by residual analysis to explore the influence of anthropogenic factors on the NDVI. The results show the following: (1) Balochistan is dominated by land restoration. Land restoration is mainly dominated by climate as well as both climate and human factors, and land degradation is mainly dominated by climate and human factors. (2) The Geodetector-based study found high correlations between the NDVI and TMP, MAP, AET and PET, complementing most previous residual analyses that considered only precipitation and temperature. In Balochistan, TMP, AET, PET and MAP were the dominant climatic factors affecting the spatial distribution of the NDVI; TMP with MAP and TMP with AET were the main interactive factors in the spatial distribution of the NDVI. (3) The article quantifies the impact of the anthropogenic drivers on land degradation. Human activities positively influenced the NDVI in 91.02% of the area and negatively influenced it in 8.98% of the area. (4) The overall trend of the NDVI was mainly stable, with stronger improvement than degradation, and showed strong persistence. The above findings enrich our understanding of the climatic impacts of land degradation and human impacts in arid or semi-arid regions and provide a scientific basis for ecological engineering to achieve ecological conservation and quality development in Balochistan, Pakistan.

Potential evapotranspiration (PET) is the capacity of the sub-surface evapotranspiration process, which is determined by weather and climate conditions. As an important component of the surface energy balance and hydrological cycle, PET determines hydrothermal transport in surface ecosystems and is an important factor in regional water resource evaluation, water use efficiency, and drought prediction. Most of the existing studies have focused on the impact of PET on the ecological environment and regional climate, providing limited information on the characteristics of the regional distribution of potential evapotranspiration itself and the associated drivers. In this study, we use the Penman-Monteith (P–M) model to calculate the PET in Akmola Oblast, combined with relevant climate data, partial correlation analysis, and structural equation modelling (SEM) to investigate the spatial and temporal distribution characteristics of PET in the study area and its driving factors, as well as the influence of meteorological activity on PET after the implementation of the Green Ring Project in the capital area of Kazakhstan. The results of the study show that: (1) The PET in Akmola State presented a decreasing trend from 1991 to 2021, with a multi-year average value of 835.87 mm. There is large heterogeneity in the spatial distribution of PET, being significantly higher in the southwestern and northeastern regions of the study area than in the central region. (2) Simple and partial correlation analyses indicate that most of the correlations between meteorological and PET were significant, with strong spatial heterogeneity in the number of biased relationships between different meteorological activity and PET. The spatial characteristics of the correlations between PET and Srad (Solar radiation), VS (wind speed), and MAT (Mean annual temperature) were similar, with the strongest correlations observed in the southwestern part of Akmola State. Furthermore, the spatial distribution of the correlations between PET and SWC (soil water content) and ST (soil temperature) was similar, with stronger correlations in the central part of the study area than elsewhere. (3) The SEM demonstrated that the main drivers of PET change across the study area are Srad (0.59) and VS (0.37). In the metropolitan area, MAP (mean annual precipitation) is also a major driver of PET change, due to the implementation of the Green Ring Project, which has increased vegetation cover and improved the local environment. The results of this study highlight the impact of climate change on PET in Akmola Oblast, Kazakhstan, contributing to a better understanding of PET evolution and providing guidance for water management planning.

Soil organic carbon (C) and soil total nitrogen (N) show different degrees of spatial variability at different scales. Both are important components of soil nutrients and essential elements for plant growth and development, and are closely related to biogeochemical cycles. However, there is limited information on the regional spatial validity of SOC and TN and the associated drivers at the scale of the Central Asian drylands. Therefore, this study uses the ISRIC-WISE (International Soil Reference and Information Centre-Word Inventory of Soil Property Estimates) database to conduct soil sampling at the raster level, combined with relevant climatic and environmental datasets, to investigate the spatial distribution characteristics and drivers of soil C and N in the drylands of Central Asia using classical geostatistical methods and structural equation modelling (SEM). The results of this study show that the distributions of soil C and N contents in the dry zone of Central Asia have greater similarity, with C content mainly concentrated in the ranges of 0–5.5 g/kg and 11.1–15.9 g/kg; soil N content mainly concentrated in the range of 0.4–1.1 g/kg, and the soil C:N ratio mainly concentrated in the range of 12.2–28.9. Structural equation modelling showed that the main driver of soil C change was Aridity (−0.51); the main driver of soil N change was Mean Annual Temperature (MAT) (−0.44); and soil C:N change was most influenced by Aboveground biomass (AGB) (−0.25). An analysis of the relative importance contribution showed that Aridity had the highest relative importance with regard to the change in C (32%); MAT had the highest relative importance with regard to the changes in N and C:N (29% and 40%, respectively). The above findings provide a reference for the use of soil resources in drylands and provide a scientific basis for regional differences in the response of arid ecosystems to climate change.

Epilepsy is characterized by highly abnormal synchronous discharge of brain neurons, and ion channels are fundamental in the generation and modulation of neural excitability. Considering that abnormal methylation can either activate or repress genes, this study was designed to explore the DNA methylation signature of pathogenic genes encoding ion channels in temporal lobe epilepsy (TLE). In total, 38 TLE patients and 38 healthy controls were enrolled in the study, and genomic DNA and total protein of the lymphocytes were extracted from peripheral blood samples to assess methylation and protein levels. The DNA methylation levels of all 12 genes examined were significantly lower in the TLE group than in the control group. After false-positive correction, 83.3% (10/12) of these genes, namely, gamma-aminobutyric acid type A receptor subunit beta1 (GABRB1), gamma-aminobutyric acid type A receptor subunit beta2 (GABRB2), gamma-aminobutyric acid type A receptor subunit beta1 (GABRB3), glutamate ionotropic receptor NMDA type subunit 1 (GRIN1), glutamate ionotropic receptor NMDA type subunit 2A (GRIN2A), glutamate ionotropic receptor NMDA type subunit 2B (GRIN2B), hyperpolarization activated cyclic nucleotide gated potassium channel 1 (HCN1), potassium voltage-gated channel subfamily A member 2 (KCNA2), potassium voltage-gated channel subfamily B member 1 (KCNB1), and potassium sodium-activated channel subfamily T member 1 (KCNT1), were still differentially expressed. Among these ion channels, HCN1 and KCNA2 were selected to evaluate the effects of DNA methylation, and the levels of these proteins were inversely upregulated in the TLE group compared to the control group. As the genes identified as having differential methylation levels are involved in both excitatory and inhibitory ion channels, this study observed by binary logistic regression that hypermethylated GARAB1 was an independent risk factor for TLE, indicating that the overwhelming effect of ion channels on TLE is probably inhibitory from the perspective of DNA methylation. All these findings support the involvement of DNA methylation in TLE pathologies, but the mechanisms need to be further investigated.

Using a structural equation model (SEM), this paper investigates the response of soil nitrogen content of five typical grasslands in the middle line countries of China’s “Belt and Road” initiative to the changes of climate variables, soil pH value, and normalized vegetation index, and employs the principal component analysis method to determine the spatial variation characteristics and influencing factors of nitrogen reserves in different grasslands. Pontiac grassland (PS), Middle East grassland (MES), Kazakh grassland (KS), Kazakh forest grassland (KFS), and Kazakh semi-desert grassland (KFS) are the five grasslands in the research region (KSD). The results indicated that (1) the nitrogen reserves of the five grassland soils (0–100 cm) in the research area were 7.49 Pg, or approximately 5.7 percent of the total world nitrogen reserves. The sum of the five grasslands’ 0–30 cm and 0–50 cm N reserves accounted for 36.3 percent and 63.1 percent, respectively, of the total 0–100 cm N reserves. The density of nitrogen in the soil (0–100 cm) varied significantly between grasslands, ranging from 1.47 to 3.87 kg/m2, with an average of 3.10 kg/m2. (2) PCA analysis revealed a substantial positive correlation between soil N and MAP (p < 0.01), a negative correlation between soil N and Srad (p < 0.01), and a high degree of similarity between the three grassland samples, KFS, KS, and KSD. (3) The decision tree algorithm determined that MAP had the most relative importance for changes in soil nitrogen content in PS, MES, and KFS, whereas Srad had the greatest relative importance for changes in soil nitrogen content in KS and KSD. The pH showed the least proportional impact for variations in soil N concentration in all five grasslands. (4) Different factors influence the change in soil N content across diverse grasslands. The principal positive driving factor of soil N content in KS and KSD is Srad, with loads of −0.39 and −0.44, respectively. The principal negative driving factor of soil N content in PS and MES is Map, with loads of 0.38 and 0.2, respectively. In the SEM model of soil nitrogen content in KFS, no environmental variables had a significant effect on N content, and the model’s R2 value was 0.08, indicating an average fit.

Background/Aims: Increasing evidence suggests the important role of sirtuin 2 (SIRT2) in the pathology of Parkinson’s disease (PD). However, the association between potential functional polymorphisms in the SIRT2 gene and PD still needs to be identified. Exploring the molecular mechanism underlying this potential association could also provide novel insights into the pathogenesis of this disorder. Methods: Bioinformatics analysis and screening were first performed to find potential microRNAs (miRNAs) that could target the SIRT2 gene, and molecular biology experiments were carried out to further identify the regulation between miRNA and SIRT2 and characterize the pivotal role of miRNA in PD models. Moreover, a clinical case-control study was performed with 304 PD patients and 312 healthy controls from the Chinese Han population to identify the possible association of single nucleotide polymorphisms (SNPs) within the miRNA binding sites of SIRT2 with the risk of PD. Results: Here, we demonstrate that miR-486-3p binds to the 3’ UTR of SIRT2 and influences the translation of SIRT2. MiR-486-3p mimics can decrease the level of SIRT2 and reduce a-synuclein (α-syn)-induced aggregation and toxicity, which may contribute to the progression of PD. Interestingly, we find that a SNP, rs2241703, may disrupt miR-486-3p binding sites in the 3’ UTR of SIRT2, subsequently influencing the translation of SIRT2. Through the clinical case-control study, we further verify that rs2241703 is associated with PD risk in the Chinese Han population. Conclusion: The present study confirms that the rs2241703 polymorphism in the SIRT2 gene is associated with PD in the Chinese Han population, provides the potential mechanism of the susceptibility locus in determining PD risk and reveals a potential target of miRNA for the treatment and prevention of PD.

In a multimodal public transport network, transfers are inevitable. Planning and managing an efficient transfer connection is thus important and requires an understanding of the factors that influence those transfers. Existing studies on predicting passenger transfer flows have mainly used transit assignment models based on route choice, which need extensive computation and underlying behavioral assumptions. Inspired by studies that use network properties to estimate public transport (PT) demand, this paper proposes to use the network properties of a multimodal PT system to explain transfer flows. A statistical model is estimated to identify the relationship between transfer flow and the network properties in a joint bus and metro network. Apart from transfer time, the number of stops, and bus lines, the most important network property we propose in this study is transfer accessibility. Transfer accessibility is a newly defined indicator for the geographic factors contributing to the possibility of transferring at a station, given its position in a multimodal PT network, based on an adapted gravity-based measure. It assumes that transfer accessibility at each station is proportional to the number of reachable points of interest within the network and dependent on a cost function describing the effect of distance. The R-squared of the regression model we propose is 0.69, based on the smart card data, PT network data, and Points of Interest (POIs) data from the city of Beijing, China. This suggests that the model could offer some decision support for PT planners especially when complex network assignment models are too computationally intensive to calibrate and use.

The main protease (Mpro) of SARS-CoV-2 is an attractive target in anti-COVID-19 therapy for its high conservation and major role in the virus life cycle. The covalent Mpro inhibitor nirmatrelvir (in combination with ritonavir, a pharmacokinetic enhancer) and the non-covalent inhibitor ensitrelvir have shown efficacy in clinical trials and have been approved for therapeutic use. Effective antiviral drugs are needed to fight the pandemic, while non-covalent Mpro inhibitors could be promising alternatives due to their high selectivity and favorable druggability. Numerous non-covalent Mpro inhibitors with desirable properties have been developed based on available crystal structures of Mpro. In this article, we describe medicinal chemistry strategies applied for the discovery and optimization of non-covalent Mpro inhibitors, followed by a general overview and critical analysis of the available information. Prospective viewpoints and insights into current strategies for the development of non-covalent Mpro inhibitors are also discussed.

Indolylarylsulfones (IASs) are classical HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs) with a unique scaffold and possess potent antiviral activity. To address the high cytotoxicity and improve safety profiles of IASs, we introduced various sulfonamide groups linked by alkyl diamine chain to explore the entrance channel of non-nucleoside inhibitors binding pocket. 48 compounds were designed and synthesized to evaluate their anti-HIV-1 activities and reverse transcriptase inhibition activities. Especially, compound R10L4 was endowed with significant inhibitory activity towards wild-type HIV-1 (EC50(WT) = 0.007 μmol/L, SI = 30,930) as well as a panel of single-mutant strains exemplified by L100I (EC50 = 0.017 μmol/L, SI = 13,055), E138K (EC50 = 0.017 μmol/L, SI = 13,123) and Y181C (EC50 = 0.045 μmol/L, SI = 4753) which were superior to Nevirapine and Etravirine. Notably, R10L4 was characterized with significantly reduced cytotoxicity (CC50 = 216.51 μmol/L) and showed no remarkable in vivo toxic effects (acute and subacute toxicity). Moreover, the computer-based docking study was also employed to characterize the binding mode between R10L4 and HIV-1 RT. Additionally, R10L4 presented an acceptable pharmacokinetic profile. Collectively, these results deliver precious insights for next optimization and indicate that the sulfonamide IAS derivatives are promising NNRTIs for further development.