回旋加速器制备放射性氯化亚铊(~(201)Tl)注射液

本文叙述制备放射性氯化亚铊(~(201)Tl)注射液的方法。靶子为高纯金属铊片,装于具有水冷、气冷腔的2π靶室内,利用扇形聚焦回旋加速器所产生的30MeV质子进行辐照。靶片溶解后,联合使用液-液萃取和阴离子交换法进行化学处理,可同时获得无载体~(203)Pb。产品~(201)Tl核纯度大于99％(~(200)Tl～0.76％,~(202)Tl～0.04％),放化纯度大于98％,含铊量小于0.27×10~(-7)μg/Bq(1.0μg/mCi)~(201)Tl。化学杂质Fe、Al等均小于1ppm,~(201)Tl厚靶产额约为18.8MBq/μAh。产品经临床前药理试验、药检试验和临床试用,质量良好。     

Aroma volatile compositions of high- and low-aromatic guava varieties

BACKGROUND: The traditional guava variety cultivated in Israel, ‘Ben Dov’, emits a very strong odour, whereas some newly bred varieties have a mild odour. In this study the aroma profile composition of the high‐aromatic ‘Ben Dov’ variety was compared with those of four new low‐aromatic varieties. RESULTS: Overall, using gas chromatography/mass spectrometry, a total of 30 aroma volatiles were detected in fresh ripe guava fruit: 15 of them were specifically detected only in the high‐aromatic ‘Ben Dov’ variety, 13 were detected in both the high‐ and low‐aromatic varieties and two were detected only in the new low‐aromatic varieties. Interestingly, 11 out of the 15 volatiles specifically detected in ‘Ben Dov’ were esters that contribute sweet, tropical and fruity notes. In contrast, ten out of 13 detected terpenes and two detected aldehydes, contributing green, spicy, herbal and woody notes, were common to both the high‐ and low‐aromatic varieties. CONCLUSION: Based on these findings, it is concluded that accumulation of esters is the main reason why the traditional ‘Ben Dov’ guava variety emits such a strong tropical fruity odour. In contrast, the newly bred low‐aromatic guava varieties did not synthesise esters at all and thus lacked fruity aromatic notes. Overall, the results of this study point out the important role of esters in forming tropical fruity guava odours. Copyright © 2011 Society of Chemical Industry     

The effect of surface treatments on the adhesion of electrochemically deposited hydroxyapatite coating to titanium and on its interaction with cells and bacteria

The effect of different mechanical and chemical pre-treatments on the adhesion strength of hydroxyapatite (HAp) coating on a commercially pure titanium (CP-Ti) substrate was studied by means of a standard tensile test followed by microscopic and chemical analysis to determine the locus of fracture. In addition, the effects of either these pre-treatments or post-treatment by low-energy electron irradiation, which allowed tuning the wettability of the surface, on both osteoblast progenitor attachment and S. aureus bacteria attachment were investigated. A dedicated program was developed for unambiguous identification and count of stained cells. A single-phase HAp coating was formed by electrodeposition. A series of surface pre-treatments consisted of grinding down to P1000, etching in HNO₃/HF solution, grit blast, soaking in NaOH and subsequent heat treatment provided the highest adhesion strength to the HAp coating. Osteoblast progenitors derived from rats may be attached preferentially to a hydrophilic surface (post-treatment to θ = 30°), while the bacteria seemed to be less attached to hydrophobic surfaces (post-treatment to θ = 105°). However, the results were not statistically different. The bacteria seemed to be less attached to the smoother, uncoated surfaces.     

Pinpointing biomarkers in proteomic LC/MS data by moving-window discriminant analysis

The identification of differential patterns in data originating from combined measurement techniques such as LC/MS is pivotal to proteomics. Although "shotgun proteomics" has been employed successfully to this end, this method also has severe drawbacks, because of its dependence on largely untargeted MS/MS sequencing and databases for statistical analyses. Alternatively, several MS-signal-based (MS/MS-independent) methods have been published that are mainly based on (univariate) Student's t-tests. Here, we present a more robust multivariate alternative employing linear discriminant analysis. Like the t-test-based methods, it is applied directly to LC/MS data, instead of using MS/MS measurements. We demonstrate the method on a number of simulated data sets, as well as on a spike-in LC/MS data set, and show its superior performance over t-tests.     

Automatic generation of nested,fork-join parallelism

This paper presents an efficient algorithm that automatically generates a parallel program from a dependence-based representation of a sequential program. The resulting parallel program consists of nested fork-join constructs, composed from the loops and statements of the sequential program. Data dependences are handled by two techniques. One technique implicitly satisfies them by sequencing, thereby reducing parallelism. Where increased parallelism results, the other technique eliminates them by privatization: the introduction of process-specific private instances of variables. Additionally, the algorithm determines when copying values of such instances in and out of nested parallel constructs results in greater parallelism. This is the first algorithm for automatically generating parallelism for such a general model. The algorithm generates as much parallelism as is possible in our model while minimizing privatization.An earlier version of this paper was presented at the First Workshop on Languages and Compilers for Vector and Parallel Machines, which was held at Cornell University in August 1988. That same year a select group of these workshop papers were published in two special issues of the journal: volume 2, numbers 2 and 3.