从西藏金发藓科植物初步研究兼论青藏高原的隆起

西藏金发藓科植物,已知有7属,30种,4变种;其中新种5个,新变种3个。从水平分布看,大多集中雅鲁藏布江流域附近,因该流域是印度板块北缘与欧亚大陆南缘的缝合线,因而金发藓科植物得以高度集中。本文讨论了该科在本区的地理分布和区系成份的分析等问题,并讨论了青藏高原的隆起对该群藓类的影响。     

训练与β－内啡肽对急性运动反应关系的研究

用放射免疫法测定训练和非训练大鼠运动前、运动到５０％耐力时间（Ｔ１／２）和衰竭时丘脑下部和血浆β－内啡肽（β－ＥＰ）的含量,探索了训练与β－ＥＰ对急性运动反应的关系。结果表明：训练组大鼠丘脑下部β－ＥＰ含量在运动到Ｔ１／２和衰竭时分别较安静时提高了４％和１５％;对照组大鼠在Ｔ１／２时,β－ＥＰ的变化趋势同训练组,以后随运动生理负荷的增强而迅速降低,衰竭时较Ｔ１／２时降低了２６％,较训练组降低了３２％（Ｐ＜０．０５）。训练组大鼠血浆β－ＥＰ含量随运动开始迅速上升,Ｔ１／２时较运动前增加了５．７倍（Ｐ＜０．０１）,以后上升的幅度减小;非训练组大鼠血浆β－ＥＰ也随运动开始迅速提高（Ｐ＜０．０１）,Ｔ１／２后趋于稳定,在Ｔ１／２和衰竭时分别比训练组低２２％和２６％。表明非训练组大鼠丘脑下部β－Ｅｐ对急性运动呈明显的双相变化,训练提高了大鼠丘脑下部和血浆β－ＥＰ对衰竭运动的反应。     

色氨酸阻遏物与其操纵基因复合物的圆二色性研究

用圆二色性谱来确定色氨酸阻遏物与其操纵基因复合物在溶液中的构象变化。色氨酸阻遏物的圆二色性图谱表明它是一种富含α螺旋的蛋白质,通过比较加入Ｌ－Ｔｒｐ前和后的圆二色性谱,发现活性的与非活性的色酸阻遏物二级结构变化很小,ｔｒｐ Ｐ／Ｏ的圆二色性谱与它的单健、双链理论计算曲线对比,可近拟推测操纵基因在溶液中的存在状态。用色氨酸阻遏物对ｔｒｐ Ｐ／Ｏ进行确定,可以从中找出蛋白质与核酸结合的平衡点。从平衡时     

阿加曲班抗凝对连续血液净化患儿凝血功能及单核细胞TLR2rMnX、TLR4rMnX表达水平的影响

目的:探讨阿加曲班抗凝治疗连续血液净化患儿的疗效及对凝血功能及单核细胞TLR2rMnX、TLR4rMnX表达水平的影响。方法:选取从2017年3月至2018年10月于我院儿童重症医学科接受连续血液净化治疗的患儿86例进行研究,将其按照随机抽签法分成研究组与对照组。对照组予以普通肝素抗凝治疗,研究组予以阿加曲班抗凝治疗。分别比较两组的28 d死亡率、治疗前后凝血功能血小板计数(PLT)、活化部分凝血活酶时间(APTT)、纤维蛋白原(FIB)和单核细胞TLR2rMnX、TLR4rMnX表达水平、治疗过程中滤器与管路凝血程度、使用寿命以及穿刺部位出血情况的差异。结果:研究组28d死亡率(2.33%)比对照组(9.30%)低,但差异无统计学意义(x2=0.849,P=0.357)。治疗后研究组APTT(31.61±1.26)s、FIB水平(6.61±1.80)g/L较对照组的(27.92±1.44)s、(5.58±1.72)g/L明显更高(t=12.646、2.713,P=0.000、0.008)。研究组治疗过程中滤器与管路凝血程度0级人数占比(93.02%)相比对照组(76.74%)较高,而Ⅱ级人数占比(0.00%)相比对照组(9.30%)较低(x2=4.440、4.195,P=0.035,0.041)。研究组穿刺部位出血等级为0级人数占比(93.02%)高于对照组(74.42%),而Ⅱ级人数占比(0.00%)低于对照组(9.30%)(x2=5.460,4.195;P=0.019,0.041)。研究组管路、滤器使用寿命(18.73±7.74)h、(20.84±8.01)h相比对照组的(14.57±6.88)h、(16.20±7.15)h均较长(t=2.634、2.834,P=0.010,0.006)。治疗后研究组单核细胞TLR2rMnX、TLR4rMnX表达水平为(4.72±1.39)、(3.22±0.82),均低于对照组的(8.30±1.44)、(5.11±0.94)(t=11.729、9.936,P=0.000、0.000)。结论:阿加曲班抗凝应用于连续血液净化患儿中的疗效相比普通肝素抗凝更佳,且有利于改善凝血功能和单核细胞TLR2rMnX、TLR4rMnX表达水平,能够降低滤器或管路凝血发生风险,同时有效降低穿刺部位出血风险,增加管路、滤器使用寿命。     

Age,growth and reproductive traits of invasive goby Taenioides cirratus in the Chaohu Lake,China

The eel goby Taenioides cirratus (Blyth, 1,860) is a small fish inhabits muddy bottoms of brackish-water in the Indo-West Pacific. It has invaded many inland freshwater lakes in China, such as the Chaohu Lake, Gaoyou Lake and Nansi Lake, and its population increased rapidly in these freshwater lakes in recent years. The age, growth and reproductive traits of T. cirratus invading the Chaohu Lake were studied. A total of 482 specimens (210 females, 204 males and 68 juveniles) with total length (TL) ranging from 9.4 to 20.6 cm were collected using the benthic fyke nets at monthly intervals from March 2018 to February 2019. The sagittal otolith was used for age determination. Monthly variation of marginal increment ratio indicated that the annual forming of opaque band on sagittal otolith was completed during March and April. For both sexes, only four (from 0+ to 3+ years) age groups were observed and 1+ and 2+ years age individuals dominated the population. Back calculated length at age showed males grew faster than females. Both sexes reached maturity at 1+ year age and the TL at first maturity (TL₅₀) was 12.6 cm for females and 11.9 cm for males. Monthly variation of gonado-somatic index indicated that the spawning occurred from May to August. The fecundity ranged from 967 ova to 5,114 ova, with a mean of 3,205 ova. Our study provides a comprehensive data on the key life history traits of T. cirratus for the first time.     

Development and characterization of a compensating wheat-Thinopyrum intermedium Robertsonian translocation with Sr44 resistance to stem rust (Ug99)

The emergence of the highly virulent Ug99 race complex of the stem rust fungus (Puccinia graminis Pers. f. sp. tritici Eriks. and Henn.) threatens wheat (Triticum aestivum L.) production worldwide. One of the effective genes against the Ug99 race complex is Sr44, which was derived from Thinopyrum intermedium (Host) Barkworth and D.R. Dewey and mapped to the short arm of 7J (designated 7J#1S) present in the noncompensating T7DS-7J#1L?7J#1S translocation. Noncompensating wheat-alien translocations are known to cause genomic duplications and deficiencies leading to poor agronomic performance, precluding their direct use in wheat improvement. The present study was initiated to produce compensating wheat-Th. intermedium Robertsonian translocations with Sr44 resistance. One compensating RobT was identified consisting of the wheat 7DL arm translocated to the Th. intermedium 7J#1S arm resulting in T7DL?7J#1S. The T7DL?7J#1S stock was designated as TA5657. The 7DL?7J#1S stock carries Sr44 and has resistance to the Ug99 race complex. This compensating RobT with Sr44 resistance may be useful in wheat improvement. In addition, we identified an unnamed stem rust resistance gene located on the 7J#1L arm that confers resistance not only to Ug99, but also to race TRTTF, which is virulent to Sr44. However, the action of the second gene can be modified by the presence of suppressors in the recipient wheat cultivars.     

MASH Suite Pro: A Comprehensive Software Tool for Top-Down Proteomics

Top-down mass spectrometry (MS)-based proteomics is arguably a disruptive technology for the comprehensive analysis of all proteoforms arising from genetic variation, alternative splicing, and posttranslational modifications (PTMs). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for data analysis in bottom-up proteomics, the data analysis tools in top-down proteomics remain underdeveloped. Moreover, despite recent efforts to develop algorithms and tools for the deconvolution of top-down high-resolution mass spectra and the identification of proteins from complex mixtures, a multifunctional software platform, which allows for the identification, quantitation, and characterization of proteoforms with visual validation, is still lacking. Herein, we have developed MASH Suite Pro, a comprehensive software tool for top-down proteomics with multifaceted functionality. MASH Suite Pro is capable of processing high-resolution MS and tandem MS (MS/MS) data using two deconvolution algorithms to optimize protein identification results. In addition, MASH Suite Pro allows for the characterization of PTMs and sequence variations, as well as the relative quantitation of multiple proteoforms in different experimental conditions. The program also provides visualization components for validation and correction of the computational outputs. Furthermore, MASH Suite Pro facilitates data reporting and presentation via direct output of the graphics. Thus, MASH Suite Pro significantly simplifies and speeds up the interpretation of high-resolution top-down proteomics data by integrating tools for protein identification, quantitation, characterization, and visual validation into a customizable and user-friendly interface. We envision that MASH Suite Pro will play an integral role in advancing the burgeoning field of top-down proteomics.With well-developed algorithms and computational tools for mass spectrometry (MS)¹ data analysis, peptide-based bottom-up proteomics has gained considerable popularity in the field of systems biology (1–9). Nevertheless, the bottom-up approach is suboptimal for the analysis of protein posttranslational modifications (PTMs) and sequence variants as a result of protein digestion (10). Alternatively, the protein-based top-down proteomics approach analyzes intact proteins, which provides a “bird''s eye” view of all proteoforms (11), including those arising from sequence variations, alternative splicing, and diverse PTMs, making it a disruptive technology for the comprehensive analysis of proteoforms (12–24). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for processing data from bottom-up proteomics experiments, the data analysis tools in top-down proteomics remain underdeveloped.The initial step in the analysis of top-down proteomics data is deconvolution of high-resolution mass and tandem mass spectra. Thorough high-resolution analysis of spectra by horn (THRASH), which was the first algorithm developed for the deconvolution of high-resolution mass spectra (25), is still widely used. THRASH automatically detects and evaluates individual isotopomer envelopes by comparing the experimental isotopomer envelope with a theoretical envelope and reporting those that score higher than a user-defined threshold. Another commonly used algorithm, MS-Deconv, utilizes a combinatorial approach to address the difficulty of grouping MS peaks from overlapping isotopomer envelopes (26). Recently, UniDec, which employs a Bayesian approach to separate mass and charge dimensions (27), can also be applied to the deconvolution of high-resolution spectra. Although these algorithms assist in data processing, unfortunately, the deconvolution results often contain a considerable amount of misassigned peaks as a consequence of the complexity of the high-resolution MS and MS/MS data generated in top-down proteomics experiments. Errors such as these can undermine the accuracy of protein identification and PTM localization and, thus, necessitate the implementation of visual components that allow for the validation and manual correction of the computational outputs.Following spectral deconvolution, a typical top-down proteomics workflow incorporates identification, quantitation, and characterization of proteoforms; however, most of the recently developed data analysis tools for top-down proteomics, including ProSightPC (28, 29), Mascot Top Down (also known as Big-Mascot) (30), MS-TopDown (31), and MS-Align+ (32), focus almost exclusively on protein identification. ProSightPC was the first software tool specifically developed for top-down protein identification. This software utilizes “shotgun annotated” databases (33) that include all possible proteoforms containing user-defined modifications. Consequently, ProSightPC is not optimized for identifying PTMs that are not defined by the user(s). Additionally, the inclusion of all possible modified forms within the database dramatically increases the size of the database and, thus, limits the search speed (32). Mascot Top Down (30) is based on standard Mascot but enables database searching using a higher mass limit for the precursor ions (up to 110 kDa), which allows for the identification of intact proteins. Protein identification using Mascot Top Down is fundamentally similar to that used in bottom-up proteomics (34), and, therefore, it is somewhat limited in terms of identifying unexpected PTMs. MS-TopDown (31) employs the spectral alignment algorithm (35), which matches the top-down tandem mass spectra to proteins in the database without prior knowledge of the PTMs. Nevertheless, MS-TopDown lacks statistical evaluation of the search results and performs slowly when searching against large databases. MS-Align+ also utilizes spectral alignment for top-down protein identification (32). It is capable of identifying unexpected PTMs and allows for efficient filtering of candidate proteins when the top-down spectra are searched against a large protein database. MS-Align+ also provides statistical evaluation for the selection of proteoform spectrum match (PrSM) with high confidence. More recently, Top-Down Mass Spectrometry Based Proteoform Identification and Characterization (TopPIC) was developed (http://proteomics.informatics.iupui.edu/software/toppic/index.html). TopPIC is an updated version of MS-Align+ with increased spectral alignment speed and reduced computing requirements. In addition, MSPathFinder, developed by Kim et al., also allows for the rapid identification of proteins from top-down tandem mass spectra (http://omics.pnl.gov/software/mspathfinder) using spectral alignment. Although software tools employing spectral alignment, such as MS-Align+ and MSPathFinder, are particularly useful for top-down protein identification, these programs operate using command line, making them difficult to use for those with limited knowledge of command syntax.Recently, new software tools have been developed for proteoform characterization (36, 37). Our group previously developed MASH Suite, a user-friendly interface for the processing, visualization, and validation of high-resolution MS and MS/MS data (36). Another software tool, ProSight Lite, developed recently by the Kelleher group (37), also allows characterization of protein PTMs. However, both of these software tools require prior knowledge of the protein sequence for the effective localization of PTMs. In addition, both software tools cannot process data from liquid chromatography (LC)-MS and LC-MS/MS experiments, which limits their usefulness in large-scale top-down proteomics. Thus, despite these recent efforts, a multifunctional software platform enabling identification, quantitation, and characterization of proteins from top-down spectra, as well as visual validation and data correction, is still lacking.Herein, we report the development of MASH Suite Pro, an integrated software platform, designed to incorporate tools for protein identification, quantitation, and characterization into a single comprehensive package for the analysis of top-down proteomics data. This program contains a user-friendly customizable interface similar to the previously developed MASH Suite (36) but also has a number of new capabilities, including the ability to handle complex proteomics datasets from LC-MS and LC-MS/MS experiments, as well as the ability to identify unknown proteins and PTMs using MS-Align+ (32). Importantly, MASH Suite Pro also provides visualization components for the validation and correction of the computational outputs, which ensures accurate and reliable deconvolution of the spectra and localization of PTMs and sequence variations.