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Homosporous lycophytes (Lycopodiaceae) are a deeply diverged lineage in the plant tree of life, having split from heterosporous lycophytes (Selaginella and Isoetes) ~400 Mya. Compared to the heterosporous lineage, Lycopodiaceae has markedly larger genome sizes and remains the last major plant clade for which no chromosome-level assembly has been available. Here, we present chromosomal genome assemblies for two homosporous lycophyte species, the allotetraploid Huperzia asiatica and the diploid Diphasiastrum complanatum. Remarkably, despite that the two species diverged ~350 Mya, around 30% of the genes are still in syntenic blocks. Furthermore, both genomes had undergone independent whole genome duplications, and the resulting intragenomic syntenies have likewise been preserved relatively well. Such slow genome evolution over deep time is in stark contrast to heterosporous lycophytes and is correlated with a decelerated rate of nucleotide substitution. Together, the genomes of H. asiatica and D. complanatum not only fill a crucial gap in the plant genomic landscape but also highlight a potentially meaningful genomic contrast between homosporous and heterosporous species.

Objective To summarize the electrophysiological and muscle pathological characteristics of Lambert - Eaton myasthenic syndrome (LEMS). Methods and Results Twelve LEMS patients referred to China - Japan Friendship Hospital between January 2010 and December 2021 were included. Clinically, they all showed proximal muscle weakness and reduced or disappeared tendon reflexes. Electrophysiologically, all 12 patients showed decreased compound muscle action potential (CMAP) amplitudes, normal distal motor latency (DML), and normal motor and sensory conduction velocities. Ten patients underwent repetitive nerve stimulation (RNS) test: all had amplitude increments of more than 100% at high - frequency RNS, and 8 had amplitude decrements of more than 15% at low - frequency RNS. Three patients completed the post-exercise facilitation (PEF) test: the ulnar nerve CMAP amplitude reached a peak immediately after maximum voluntary contraction of the abductor digiti minimi for 5-10 s and then gradually decreased to near baseline level after contraction for 60 s; the ulnar nerve CMAP amplitude reached a peak immediately after maximum voluntary contraction for 10 s, and then rapidly decreased to near baseline level after 15 s. On needle EMG, 8 patients showed normal motor unit action potential (MUAP), 3 showed short - duration MUAP mimicking myopathy, and one showed long - duration MUAP mimicking neuropathy. Two patients with normal MUAP underwent biceps biopsy, which showed selective type Ⅱ fiber atrophy. Conclusions Electrophysiologically, CMAP amplitudes of LEMS patients are usually diffusely low or borderline. LEMS patients have amplitude increments of more than 100% at high-frequency RNS, and some have amplitude decrements of more than 15% at low-frequency RNS. PEF test shows a transient but significant CMAP amplitude increase after 5-10 s maximum voluntary contraction. Needle EMG is usually normal, but some show myogenic lesions, and some show neurogenic lesions. Muscle biopsy shows selective type Ⅱ fiber atrophy. Needle EMG myogenic lesion may not be associated with pathologically selective type Ⅱ fiber atrophy.

为减少甾醇酯的生产工序，提高大豆油脱臭馏分重相组分中总甾醇得率，采用柱层析法直接分离提取甾醇酯，通过单因素试验考察吸附剂种类、上样量、洗脱剂比例和柱长直比（填料高度与直径比）对甾醇酯产品纯度和得率的影响，确定最佳工艺条件，并对最佳工艺条件下分离提取的甾醇酯产品进行傅里叶红外光谱表征，以及甾醇组成和脂肪酸组成测定。结果表明，柱层析法分离提取甾醇酯的最佳工艺条件为吸附剂为硅胶（粒径50~75 μm），上样量0.5 g，洗脱剂比例为正己烷、乙醚、冰乙酸体积比95∶ 5∶ 1，柱长直比16∶ 1。在最佳工艺条件下，甾醇酯产品纯度为(89.90±0.94)%，得率为(9615±1.49)%；傅里叶红外光谱分析证实提取的产品中含甾醇酯，甾醇酯上的甾醇组成主要为β-谷甾醇、豆甾醇、菜油甾醇，脂肪酸组成主要为亚油酸、油酸、棕榈酸、硬脂酸和亚麻酸。综上，柱层析法无需复杂工序，即可实现大豆油脱臭馏分重相组分中甾醇酯的有效回收。In order to reduce the process of sterol ester production and increase the yield of total sterols in the waste residue of soybean oil deodorizer distillate (WRSODD), column chromatography was used to extract the sterol esters from WRSODD. The influence of absorbent type, sample loading amount, eluent ratio and ratio of column material height to diameter on the recovery rate and purity of sterol esters were examined by single factor experiment, and the optimum process conditions were selected. The sterol esters obtained under the optimum process conditions was analyzed by Fourier-infrared spectroscopy, and its sterols and fatty acid compositions were analyzed. The results showed that the optimum conditions were as follows: with silica gel powder (particle size 50-75 μm) as absorbent, sample loading amount 0.5 g, volume ratio of a mixture of n-hexane, diethyl ether and glacial acetic acid 95∶ 5∶ 1, and ratio of column material height to diameter 16∶ 1. Under these conditions, the purity and recovery rate of sterol esters were (89.90±0.94)% and (96.15±1.49)%, respectively. Fourier-infrared spectroscopy results verified that the product contained sterol esters. The sterol compositions of sterol esters were mainly β-sitosterol, stigmasterol and campesterol. The fatty acid compositions were palmitic acid, stearic acid, oleic acid, linoleic acid and linolenic acid. In conclusion, effective recovery of sterol esters from the waste residue of soybean oil deodorizer distillate can be achieved through column chromatography without complex process.

This article summarized the preoperative and postoperative nursing process of a patient with giant common bile duct stones accompanied by acute cholangitis who underwent SpyGlassTMDS-guided laser lithotripsy for stones removal. Key issues of nursing included preoperative preparation, intraoperative cooperation, postoperative care, and Traditional Chinese Medicine nursing plan, which make a great contribution to alleviating patient’s discomfort symptoms after surgery and quickly recover from discharge. (本文总结1例胆总管巨大结石伴急性胆管炎患者行SpyGlassTMDS直视下激光碎石取石的围手术期护理经验, 护理重点包括术前准备、术中配合、术后护理及中医护理方案, 旨在帮助患者缓解术后不适症状, 促进康复。)

To retrospectively analyze the clinical data of a patient with confocal laser endomicroscopy, and summarize nursing measures such as preoperative preparation, intraoperative coordination, postoperative care of adverse reaction care, psychological care and other targeted nursing interventions. It is required to carried comprehensive nursing interventions to reduce patient discomfort and ensure the success of confocal laser endomicroscopy. (本文总结1例行共聚焦激光显微内镜检查术患者的护理配合要点, 包括术前准备、术中配合以及术后常规护理、不良反应护理、心理护理等针对性护理措施, 以减轻患者不适症状, 保障患者共聚焦激光显微内镜检查的顺利完成。)

The separation of C2H4 from C2H6/C2H4 mixture is of great importance but difficult and energy intensive. Adsorptive separation provides an alternative approach to ameliorate this situation. Here, we report a microporous metal–organic framework (MOF) BUT-315-a as a C2H6-selective adsorbent for the separation of C2H6/C2H4 gas mixture. BUT-315-a combines good IAST selectivity of 2.35 with high C2H6 uptake of 97.5 cm3 g−1, giving superior high separation potential ΔQ (2226 mmol L−1) for equimolar C2H6/C2H4 at 298 K. Impressively, such excellent performance can be preserved at higher temperatures of 313 and 323 K to accommodate industrial conditions. Efficient dynamic separation performance of BUT-315-a has been demonstrated by column breakthrough experiments under varied temperatures and gas ratios. Theoretical calculations further reveal multiple synergistic interactions between C2H6 and the framework. This work highlights a new benchmark material for C2H6/C2H4 separation and provides guidance for designing adsorbent for separation applications.

The relaxation signals of rapeseed oil, soybean oil, peanut oil, sunflower oil and corn oil were investigated using low-field nuclear magnetic resonance (LF-NMR), and the correlation between the composition of vegetable oils and their NMR relaxation characteristics was analyzed. Furthermore, a classification model for vegetable oils was established based on the echo attenuation information of LF-NMR using principal component analysis-linear discriminant analysis (PCA-LDA), and the effects of discriminant functions and the number of principal components (PC) on the model’s performance were studied. The experimental results showed that the decreasing order of the attenuation rates of the echo curves was peanut oil > rapeseed oil > corn oil > soybean oil > sunflower oil. The types of vegetable oils had significant effects on relaxation properties including T2W, T23, S23 and Stotal (P < 0.05). There existed extremely significant correlations between T2W, T22, T23, S23 and Stotal and the contents of C18:1, C18:2, C20:0, monounsaturated fatty acid (MUFA) and polyunsaturated fatty acid (PUFA) (P < 0.01). The classification precision of the PCA-LDA model developed using linear discriminant function and 10 PCs for the training and prediction sets were 100.0% and 88.2%, respectively. It can be seen that it is feasible to identify vegetable oil species using LF-NMR. This study can provide a theoretical basis and technical support for quality and safety detection of different edible vegetable oils.

The integration of artificial intelligence technology into education is an inevitable trend of scientific progress and educational reform, and how to use artificial intelligence technology and ideological and political education reform is called a key research direction in the education sector. Aiming at the problems of cold start in personalized recommendation system, lack of interpretability of recommendation results, and ignoring the implicit features of the course for better acceptance of recommendation results by learners, the BPRMF model based on deep learning is proposed to be applied to the problem of recommendation of Civics and Political Science course, which not only models learners’ preferences and combines with course attribute features to generate recommendation rating ranking list and provide personalized recommendation service. Then the study of Civics education reform is conducted, mainly analyzing the change in teaching methods based on big data, machine learning, and deep learning technologies to promote secondary school students. The performance of the BPRMF model is evaluated in comparison with the BPRMF model under different k values. It is concluded that the accuracy rate of the BPRMF model is 8.9%~12.01% higher than UBCF and 8.07%~10.26% higher than IBCF, but with the increase of k value, the recall rate will gradually pull away from other models and optimize the recommendation system to some extent. This study is beneficial to ideological education in the implementation process to better utilize the opportunities, meet the challenges, and develop efficiently.

This paper summarized the nursing management for an elderly patient with esophageal food impaction during the recovery stage after cerebral infarction. Based on the nursing assessment on hospital admission, gastroscopy-assisted foreign body removal was carried out. Much attention has been paid on the perioperative nursing and health education about functional exercise after discharge from hospital. A systematic and comprehensive support was provided including dietary guidance, swallowing exercise, limb function exercise, language function exercise and psychological care. (本文总结1例老年脑梗死康复患者引起食物嵌塞的护理经验。在完善入院评估的基础上, 加强胃镜下食管异物取出围手术期护理, 开展出院后功能锻炼和延续护理指导, 从饮食、吞咽功能锻炼、肢体功能锻炼、语言功能锻炼及心理方面为患者及家属提供系统全面的护理干预。)

Fragment productions in spallation reactions and projectile fragmentation reactions are important topics in nuclear reaction both theoretically and experimentally, which find important applications in fundamental nuclear physics, radioactive ion beam facilities, nuclear waste disposal, medical isotopes production, etc. Besides the many models to predict the fragment productions, such as the transport model, empirical parametrizations or formula, machine learning models have been constructed to predict fragment cross-sections in proton induced spallation reactions and projectile fragmentation reactions. In this paper, the recently proposed models using Bayesian neural network (BNN) models were introduced for precise prediction of fragments, especially for extreme rare isotopes with large isospins in nuclear spallation and projectile fragmentation reactions. Two types of models were introduced, i.e., the BNN models which were constructed based on massive learning to experimental data, and the physical model guided BNN+ models which were constructed based on massive learning to the differences between measured data and physical model predictions. The simplified EPAX (sEPAX) formula and the FRACS formulas were adopted as the physical model to guide the BNN+ model for spallation reaction (BNN+sEPAX) and projectile fragmentation reaction (BNN+FRACS), respectively. The BNN and BNN+ models have the structure of one input layer with key parameters related to the reaction, one hidden layer with optimized numbers of neural nodes and one output layer. For the numbers of learning data set, it was 15 370 measured fragments in the proton induced nuclear spallation reactions and 6 393 measured fragments in the projectile fragmentation reactions. It is found that the machine learning models provide new type of predictive models for nuclear reactions besides the physical models. The BNN model needs sufficient information to achieve good prediction ability, while the BNN+ model can inherit the advantage of the physical model and make up for the defects of the physical model, which makes it achieve good predictive ability when known data are insufficient. The predicted results show that the BNN and BNN+ models have high predictions to fragments cross-sections in spallation reactions smaller than 136Xe within an incident energy range from tens of MeV/u to a few GeV/u, and projectile fragmentation reactions for projectile from 40Ar to 208Pb within the range of incident energy from tens of MeV/u to 1 GeV/u. Particularly, the BNN model for projectile fragmentation reaction predicts a 0.46 fb compared to the experimental estimation 0.5 fb for 39Na isotope in the 345 MeV/u 48Ca+9Be reaction, indicating it is capable for high quality prediction to near drip-line isotopes.