Long-Term Existence of SARS-CoV-2 in COVID-19 Patients: Host Immunity,Viral Virulence,and Transmissibility

Virologica Sinica - COVID-19 patients can recover with a median SARS-CoV-2 clearance of 20 days post initial symptoms (PIS). However, we observed some COVID-19 patients with existing...     

响应面法优化类芽胞杆菌HB172198产褐藻胶裂解酶发酵培养基

为了提高类芽胞杆菌新种HB172198产褐藻胶裂解酶活力,本研究采用响应面法对该菌株液体发酵培养基进行了优化实验。在单因素实验和Plackett-Burman试验筛选出海藻酸钠、胰蛋白胨、NaCl、MgSO4·7H2O等4个显著影响产酶因素的基础上,通过Box-Behnken设计及响应面法进行回归分析,得出产褐藻胶裂解酶最佳发酵培养基,其成分为:海藻酸钠7.50 g/L、胰蛋白胨13.57 g/L、NaCl 29.75 g/L、MgSO4·7H2O 0.08 g/L。优化条件下该菌株最大酶活性达14.60 U/mL,是优化前的1.87倍。本研究为菌株HB172198产褐藻胶裂解酶的大规模生产和工业应用提供了重要的理论依据。     

一氧化氮对豆科植物结瘤及固氮的影响机制

豆科植物-根瘤菌共生过程受双方基因复杂且精细的调控, 能够产生特异的根瘤结构并可将大气中的惰性氮气(N₂)转化为可被植物直接利用的氨态氮。结瘤与固氮受多种因素影响, 其中, 一氧化氮(NO)作为一种自由基反应性气体信号分子, 可参与调节植物的许多生长发育过程, 如植物的呼吸、光形态建成、种子萌发、组织和器官发育、衰老以及响应各种生物及非生物胁迫。在豆科植物中, NO不仅影响寄主与菌共生关系的建立, 还参与调控根瘤菌对氮气的固定并提高植株氮素营养利用效率。该文主要从豆科植物及共生菌内NO的产生、降解及其对结瘤、共生固氮的影响和对环境胁迫的响应, 阐述了NO调控豆科植物共生体系中根瘤形成和共生固氮过程的作用机制, 展望了NO信号分子在豆科植物共生固氮体系中的研究前景。     

Leaf size of woody dicots predicts ecosystem primary productivity

A key challenge in ecology is to understand the relationships between organismal traits and ecosystem processes. Here, with a novel dataset of leaf length and width for 10 480 woody dicots in China and 2374 in North America, we show that the variation in community mean leaf size is highly correlated with the variation in climate and ecosystem primary productivity, independent of plant life form. These relationships likely reflect how natural selection modifies leaf size across varying climates in conjunction with how climate influences canopy total leaf area. We find that the leaf size?primary productivity functions based on the Chinese dataset can predict productivity in North America and vice‐versa. In addition to advancing understanding of the relationship between a climate‐driven trait and ecosystem functioning, our findings suggest that leaf size can also be a promising tool in palaeoecology for scaling from fossil leaves to palaeo‐primary productivity of woody ecosystems.     

New insights into small‐cell lung cancer development and therapy

Small‐cell lung cancer (SCLC) accounts for approximately 15% of lung cancer cases; however, it is characterized by easy relapse and low survival rate, leading to one of the most intractable diseases in clinical practice. Despite decades of basic and clinical research, little progress has been made in the management of SCLC. The current standard first‐line regimens of SCLC still remain to be cisplatin or carboplatin combined with etoposide, and the adverse events of chemotherapy are by no means negligible. Besides, the immunotherapy on SCLC is still in an early stage and novel studies are urgently needed. In this review, we describe SCLC development and current therapy, aiming at providing useful advices on basic research and clinical strategy.     

MMS2plot: An R Package for Visualizing Multiple MS/MS Spectra for Groups of Modified and Non‐Modified Peptides

A large number of post‐translational modifications (PTMs) in proteins are buried in the unassigned mass spectrometric (MS) spectra in shot‐gun proteomics datasets. Because the modified peptide fragments are low in abundance relative to the corresponding non‐modified versions, it is critical to develop tools that allow facile evaluation of assignment of PTMs based on the MS/MS spectra. Such tools will preferably have the ability to allow comparison of fragment ion spectra and retention time between the modified and unmodified peptide pairs or group. Herein, MMS2plot, an R package for visualizing peptide‐spectrum matches (PSMs) for multiple peptides, is described. MMS2plot features a batch mode and generates the output images in vector graphics file format that facilitate evaluation and publication of the PSM assignment. MMS2plot is expected to play an important role in PTM discovery from large‐scale proteomics datasets generated by liquid chromatography‐MS/MS. The MMS2plot package is freely available at https://github.com/lileir/MMS2plot under the GPL‐3 license.