Comparison of hydrothermal,hydrotropic and organosolv pretreatment for improving the enzymatic digestibility of bamboo

Pretreatment is the crucial step to disrupt the recalcitrant structure of lignocellulosic biomass for improving the enzymatic hydrolysis efficiency. Typically, hydrothermal, organosolv and hydrotropic pretreatments are environmentally benign and effective methods. In this work, effects of hydrothermal, organosolv and hydrotropic pretreatments on improving enzymatic hydrolysis of bamboo were comprehensively compared. Hydrotropic pretreatment was more effective in removal lignin and xylose from bamboo fiber cell wall. However, the surface coverage by lignin and extractives were dramatically displaced during organosolv pretreatment as investigation by X-ray photoelectron spectroscopy. After pretreatments, the crystallinity of cellulose in pretreated substrates has a significant reduction, and pores were exposed on fiber surface. The residual content of acetyl and phenolic groups in hydrotropic pretreated substrates is lower than organosolv pretreated substrates. In order to deeply assess the delignification of pretreatments, the isolated lignins obtaining from pretreatments process were characterized by Fourier transform infrared spectroscopy also. It was revealed that hydrotropic lignin contained more phenolic hydroxyl group and syringyl units than organosolv lignin. Compared to hydrothermal and organosolv pretreatment, cellulase adsorption capacity of pretreated substrates was notably improved by hydrotropic pretreatment, which indicating the better enzyme accessibility of cellulose. Eventually, the maximum glucose yield was obtained from hydrotropic pretreated substrates.     

电感耦合等离子体原子发射光谱测定铬矿中的铅、锌、镍、钛、磷

提出了电感耦合等离子体原子原子发射光谱测定铬矿中的铅、锌、镍、钛、磷含量的方法,选择各元素的分析谱线,采用正交试验的方法确定仪器的工作参数,方法的检出限0.22 ~1.50ug·L-1 ,方法的回收率在89%~112%,测定值的相对标准偏差（n=5）小于1.45%,方法用于铬矿杂元素的分析结果与现有的国标检验方法测定值一致。填补无铬矿中铅、锌、钛元素检测方法的空白。     

Nb∶KTiOPO4晶体的生长和倍频性能

通过研究晶体生长工艺参数对Nb∶KTiOPO4(Nb∶KTP)晶体生长的影响,用熔盐顶部籽晶法获得尺寸为55mm×25mm×5mm的Nb∶KTP透明单晶.研究中发现熔体的温度梯度、籽晶和降温速率将严重影响Nb∶KTP晶体的生长.Nb离子的引入不利于Nb∶KTP晶体的生长,尤其是造成晶体易开裂,且沿a轴方向生长速度非常缓慢.同时,Nb的引入大大改变Nb∶KTP晶体的倍频性能.掺杂Nb浓度的摩尔分数为13;时,Nb∶KTP晶体的倍频的Ⅱ型相位匹配的截止波长缩短至937nm,且有效产生469nm倍频蓝光;掺杂Nb浓度的摩尔分数为3;时,Nb∶KTP晶体对Nd∶YAG的1.0642μm激光倍频的最佳相位匹配角为θ=88.32°,()=0°,非常接近90°非临界相位匹配方向.     

多工况多约束下离散变量桁架结构的拓扑优化设计

提出了一个多工况下受应力、位移约束的离散变量桁架结构的拓扑优化方法，给出了结构拓扑形式变更时的约束处理方法及杆件删除策略，使基结构设计空间的维数不断降低，达到最优拓扑，避免了奇异解的出现，在算例中指出了截面离散集和位移约束对最优拓扑的影响；算例给出了满意的拓扑优化解。     

Fermat型复微分-差分方程的整函数解北大核心CSCD

利用值分布理论,研究了一类Fermat型复微分-差分方程与复微分-差分方程组,得到有限级超越整函数解的存在条件与具体形式,推广改进了高凌云、刘凯、曾翠萍等人的结果.     

基于$q$-差分Painlev\'e方程的几类$q$-差分方程解的性质

文章讨论了几类$q$-差分Painlev\''e方程的亚纯解性质,获得了方程亚纯解的存在性条件、增长级的估计,以及亚纯解$f$的$q$-差分$\Delta_qf(z):= f(qz)-f(z)$的极点收敛指数的估计等结果,进一步推广了Qi-Yang的结果.     

中国股市与汇市的波动溢出效应模型研究与实证分析

选取2009年1月5日-2012年5月22的人民币兑美元汇率和上证综指的日交易数据为对象,采用BEKK—GARCH模型,并结合LR似然比检验,对中国汇市与股市的波动溢出效应进行建模研究与实证分析．实证结果表明,整体样本存在汇率到上证指数的波动溢出,这种溢出是单向的;第二次汇改前,既不存在汇率到上证指数的波动溢出,也不存在上证指数到汇率的波动溢出;第二次汇改后,既存在汇率到上证指数的波动溢出,也存在上证指数到汇率的微弱的波动溢出．     

增敏剂改进超级微波消解-电感耦合等离子体质谱(ICP-MS)法测定食品中硒元素

合适比例增敏剂会对超级微波消解-电感耦合等离子体质谱法(ICP-MS)测定食品中硒元素含量具有一定的优化效果。本文采用超级微波消解仪对1.0 g食品样品进行全消解,采用碰撞池模式规避质谱干扰,内标校正非质谱干扰,选择甲醇、乙醇、乙酸、异丙醇、丙三醇作为增敏剂,并调整测试过程中的添加比例,用电感耦合等离子体质谱法测定。结果表明：2%异丙醇存在时硒元素各同位素响应值最高,其中78Se具有低至0.0003 mg·kg-1的方法检出限;用以上方法对食品标准物质（GSB-8、GSB-9、GSB-24、GSB-30）及实际样品进行分析,标准物质测定值均在其认定值及不确定度范围内,相对误差小于-5.4%;实际样品测定值的相对标准偏差（n=7,RSD）为0.3~1.7%,加标回收率为99.2~105%。本方法操作简便,精密度好,准确度高,可以作为各类食品样品中硒含量测试方法。     

Quantification of Venetoclax for Therapeutic Drug Monitoring in Chinese Acute Myeloid Leukemia Patients by a Validated UPLC-MS/MS Method

Venetoclax has emerged as a breakthrough for treatment of leukemia with a wide interindividual variability in pharmacokinetics. Herein, a rapid, sensitive, and reliable UPLC-MS/MS method for quantification of venetoclax in plasma was developed and validated. The method was operated in the multiple-reaction monitoring (MRM) mode to detect venetoclax at m/z transition 868.5 > 321.0 and IS at 875.5 > 321.0, respectively. Protein precipitation prior to injection into the LC-MS/MS and the analyte was separated on an ACQUITY UPLC BEH C18 column by gradient elution with acetonitrile and 0.1% formic acid in water. Linear calibration curves were obtained in the range of 25–8000 ng/mL. The specificity, recovery, matrix effect, and stability also met the acceptance criteria of FDA guidance. The method was successfully applied to analyze plasma in acute myeloid leukemia (AML) patients. The peak plasma concentration (C_max) of venetoclax in Chinese AML patient was 2966.0 ± 1595.0 ng/mL while the trough concentration (C_min) was 1018.0 ± 729.4 ng/mL. Additionally, C_max and C_min showed a positive correlation with AST levels. Furthermore, C_max was significantly higher in the older patients. The present method can be applied for TDM of venetoclax in treatment of hematological cancers.     

Multiplex metal-detection based assay (MMDA) for COVID-19 diagnosis and identification of disease severity biomarkers

The ongoing COVID-19 pandemic caused by SARS-CoV-2 highlights the urgent need to develop sensitive methods for diagnosis and prognosis. To achieve this, multidimensional detection of SARS-CoV-2 related parameters including virus loads, immune response, and inflammation factors is crucial. Herein, by using metal-tagged antibodies as reporting probes, we developed a multiplex metal-detection based assay (MMDA) method as a general multiplex assay strategy for biofluids. This strategy provides extremely high multiplexing capability (theoretically over 100) compared with other reported biofluid assay methods. As a proof-of-concept, MMDA was used for serologic profiling of anti-SARS-CoV-2 antibodies. The MMDA exhibits significantly higher sensitivity and specificity than ELISA for the detection of anti-SARS-CoV-2 antibodies. By integrating the high dimensional data exploration/visualization tool (tSNE) and machine learning algorithms with in-depth analysis of multiplex data, we classified COVID-19 patients into different subgroups based on their distinct antibody landscape. We unbiasedly identified anti-SARS-CoV-2-nucleocapsid IgG and IgA as the most potently induced types of antibodies for COVID-19 diagnosis, and anti-SARS-CoV-2-spike IgA as a biomarker for disease severity stratification. MMDA represents a more accurate method for the diagnosis and disease severity stratification of the ongoing COVID-19 pandemic, as well as for biomarker discovery of other diseases.

A MMDA platform is developed by using metal-tagged antibodies as reporting probes combined with machine learning algorithms, as a general strategy for highly multiplexed biofluid assay.