Data_Sheet_1_Analysis of characteristics of movement disorders in patients with anti-N-methyl-D-aspartate receptor encephalitis.docx

ObjectiveMovement disorders (MDs) are common in anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis but are poorly studied. This study aimed to investigate the clinical characteristics of MDs and the clinical differences between patients with and without MDs in anti-NMDAR encephalitis.MethodsA retrospective study was conducted on patients with anti-NMDAR encephalitis who were first diagnosed and treated in the First People’s Hospital of Yunnan Province from January 2017 to September 2022. According to the presence or absence of MDs, all patients were divided into two groups, and the clinical manifestations, auxiliary examinations, and prognosis of the two groups were compared. Patients in the MDs group were further subgrouped by different ages (Results(1) In our study there were 64 patients, of whom 76.6% (49/64) presented with MDs; the median age of onset in patients with MDs was 21 (15,35) years and 65.3% (32/49) were female. The three most common MDs were orofacial dyskinesia (OFLD) (67.3%), dystonia (55.1%), and stereotypies (34.7%). Patients ConclusionMDs associated with anti-NMDAR encephalitis were predominantly hyperkinetic. Chorea occurred more commonly in patients aged <12 years. Patients with MDs were prone to autonomic dysfunction, consciousness disorders, pulmonary infection, and gastrointestinal dysfunction; they had more intense inflammation, more severe disease, and a poorer short-term prognosis.</p

Suzuki-Miyaura Cross-Coupling Reactions of Unprotected Haloimidazoles

An efficient protocol for the palladium-catalyzed Suzuki–Miyaura cross-coupling reaction of unprotected haloimidazoles is reported. The relatively mild reaction conditions allow for ready access to a wide array of functionalized imidazole derivatives in good to excellent yields. The synthetic utility of this method is demonstrated by the total synthesis of nortopsentin D

Morphology-Tuned Synthesis of Nickel Cobalt Selenides as Highly Efficient Pt-Free Counter Electrode Catalysts for Dye-Sensitized Solar Cells

In this work, morphology-tuned ternary nickel cobalt selenides based on different Ni/Co molar ratios have been synthesized via a simple precursor conversion method and used as counter electrode (CE) materials for dye-sensitized solar cells (DSSCs). The experimental facts and mechanism analysis clarified the possible growth process of product. It can be found that the electrochemical performance and structures of ternary nickel cobalt selenides can be optimized by tuning the Ni/Co molar ratio. Benefiting from the unique morphology and tunable composition, among the as-prepared metal selenides, the electrochemical measurements showed that the ternary nickel cobalt selenides exhibited a more superior electrocatalytic activity in comparison with binary Ni and Co selenides. In particular, the three-dimensional dandelion-like Ni_0.33Co_0.67Se microspheres delivered much higher power conversion efficiency (9.01%) than that of Pt catalyst (8.30%) under AM 1.5G irradiation

Direct Determination of Creatinine in Urine and Analysis of Pure Aniline by Extractive Electrospray Ionization Mass Spectrometry

<div><p>The direct mass spectrometric determination of highly concentrated analytes in human urine was demonstrated using extractive electrospray ionization without sample dilution or complex preparation. By increasing the distance between the extractive electrospray source and ion inlet of the mass spectrometer from 5 millimeters to 15 centimeters, the fraction of free analyte ions and charged microdroplets introduced into the mass spectrometer was substantially reduced. Consequently, detector saturation, instrument contamination, and space charge effects were greatly diminished for the analysis of highly concentrated samples. Under the optimized experimental conditions, pure aniline and creatinine (>1 millimolar) in human urine were directly characterized by extractive electrospray ionization without any pretreatment. The urinary creatinine concentrations from two adults were 424 ± 30 and 635 ± 32 micrograms per milliliter and were in good agreement with those obtained by a spectrophotometric method based on the Jaffe reaction. The results show that extractive electrospray ionization is suitable for the direct determination of highly concentrated analytes or even pure compounds, allowing rapid characterization of samples in the chemical industry and clinical studies.</p></div

Morphology-Tuned Synthesis of Nickel Cobalt Selenides as Highly Efficient Pt-Free Counter Electrode Catalysts for Dye-Sensitized Solar Cells

In this work, morphology-tuned ternary nickel cobalt selenides based on different Ni/Co molar ratios have been synthesized via a simple precursor conversion method and used as counter electrode (CE) materials for dye-sensitized solar cells (DSSCs). The experimental facts and mechanism analysis clarified the possible growth process of product. It can be found that the electrochemical performance and structures of ternary nickel cobalt selenides can be optimized by tuning the Ni/Co molar ratio. Benefiting from the unique morphology and tunable composition, among the as-prepared metal selenides, the electrochemical measurements showed that the ternary nickel cobalt selenides exhibited a more superior electrocatalytic activity in comparison with binary Ni and Co selenides. In particular, the three-dimensional dandelion-like Ni_0.33Co_0.67Se microspheres delivered much higher power conversion efficiency (9.01%) than that of Pt catalyst (8.30%) under AM 1.5G irradiation

A graph-based deep learning framework for field scale wheat yield estimation

Accurate estimation of crop yield at the field scale plays a pivotal role in optimizing agricultural production and food security. Conventional studies have mainly focused on employing data-driven models for crop yield estimation at the regional scale, while large challenges may occur when attempting to apply these methods at the field scale. This is primarily due to the inherent complexity of obtaining reliable ground labels of yield for field validation, and the geographical independence and correlation that exists between fields. To effectively solve this problem, this study couples geographical, crop physiological knowledge and deep learning networks, and builds a graph-based deep learning framework by integrating high-medium spatial resolution active and passive remote sensing data (Sentinel-1, Sentinel-2 and Sentinel-3) and uses it to estimate field scale winter wheat yield. Firstly, a deep learning framework based on graph theory was constructed to achieve accurate estimation of field scale time series winter wheat growth parameter (Leaf Area Index, LAI), and then the growth mechanism of winter wheat and the specific factors affecting wheat yield formation were further considered, so as to improve the yield estimation accuracy of the traditional data-driven yield estimation model. Finally, the yield estimates of the proposed method were compared and analyzed for farmlands under different categories of agricultural disasters. The results showed that the graph-based two-branch network architecture (the Seq_Gra_Gd model) with the optimal meteorological data input strategy (meteorological data of the previous 15 d) had the optimal LAI estimation accuracy, and except for the jointing stage of winter wheat, the Seq_Gra_Gd model had a high and stable LAI estimation accuracy at the other main growth stages. The Seq_Gra_Gd model achieved good accuracy in estimating winter wheat yield (R2 = 0.73, RMSE = 590.43 kg·ha−1), and the introduction of the graph convolution module enabled the model to take into account the spatial distribution characteristics of stripe rust and lodging disasters well, which improved the yield estimation accuracy of affected winter wheat

Forest plot for the expression levels of NF-kB family members and 5-year overall survival in NSCLC patients.

<p>Forest plot for the expression levels of NF-kB family members and 5-year overall survival in NSCLC patients.</p

Sensitivity analyses.

<p>(A) Overall survival in NSCLC patients. (B) Tumor stage. (C) Lymph node metastasis.</p

Forest plot for the association of NF-κB with clinicopathological parameters.

<p>(A) Patients with adenocarcinoma and squamous cell carcinoma. (B) Patients with tumor stage T1/T2 and T3/T4. (C) Patients with or without lymph node metastasis. OR, Odds ratio; CI, confidence interval.</p

Forest plot for the association between NF-κB and overall survival in NSCLC patients.

<p>(A) Overall analysis of all NSCLC patients. (B) Subgroup analysis of Asian and Caucasian NSCLC patients. HR, hazard ratio; CI, confidence interval.</p