TEMGYM Advanced - NanoMi lens characterisation.

A complete analysis including finite element method (FEM) calculation, focal length properties, and thirdorder geometric aberrations of the open-source electrostatic lens from the NanoMi project is presented. The analysis is carried out by the software TEMGYM Advanced, a free package developed to carry out ray-tracing and lens characterisation in Python. Previously TEMGYM Advanced has shown how to analyse the aberrations of analytical lens fields; this paper expands upon this work to demonstrate how to apply a suitable fitting method to discrete lens fields obtained via FEM methods so that the aberrations of real lens designs can be calculated. Each software platform used in this paper is freely available in the community and creates a free and viable alternative to commercial lens design packages.

Pure Curcumin Spherulites from Impure Solutions via Nonclassical Crystallization.

Crystallization experiments performed with highly supercooled solutions produced highly pure (>99 wt %) and highly crystalline mesocrystals of curcumin from impure solutions (∼22% of two structurally similar impurities) in one step. These mesocrystals exhibited a crystallographic hierarchy and were composed of perfectly or imperfectly aligned nanometer-thick crystallites. X-ray diffraction and spectroscopic analysis confirmed that the spherulites are a new solid form of curcumin. A theoretical hypothesis based on particle aggregation, double nucleation, and repeated secondary nucleation is proposed to explain the spherulite formation mechanism. The experimental results provide, for the first time, evidence for an organic molecule to naturally form spherulites without the presence of any stabilizing agents. Control experiments performed with highly supercooled pure solutions produced spherulites, confirming that the formation of spherulites is attributed to the high degree of supercooling and not due to the presence of impurities. Likewise, control experiments performed with a lower degree of supercooling produced impure crystals of curcumin via classical molecular addition mechanisms. Collectively, these experimental observations provide, for the first time, evidence for particle-mediated crystallization as an alternate and efficient method to purify organic compounds.

The importance of greater speed in drug development for advanced malignancies.

It takes on average 6-12 years to develop new anticancer drugs from discovery to approval. Effective new agents prolong survival. To demonstrate the importance of rapid drug approval, we calculated life-years potentially saved if selected agents were approved more rapidly. As illustrative examples, we used 27 trials documenting improvements in survival. We multiplied improvement in median survival by numbers of patients dying annually and multiplied this by number of years from drug discovery until approval. For every year by which time to drug approval could have been shortened, there would have been a median number of life-years potentially saved of 79,920 worldwide per drug. Median number of life-years lost between time of drug discovery and approval was 1,020,900 per example. If we were able to use available opportunities to decrease the time required to take a drug from discovery to approval to 5 years, the median number of life-years saved per example would have been 523,890 worldwide. Various publications have identified opportunities to speed drug development without sacrificing patient safety. While many investigational drugs prove to be ineffective, some significantly prolong survival and/or reduce suffering. These illustrative examples suggest that a substantial number of life-years could potentially be saved by increasing the efficiency of development of new drugs for advanced malignancies.

Application of clustering techniques to electron-diffraction data: determination of unit-cell parameters.

A new approach to determining the unit-cell vectors from single-crystal diffraction data based on clustering analysis is proposed. The method uses the density-based clustering algorithm DBSCAN. Unit-cell determination through the clustering procedure is particularly useful for limited tilt sequences and noisy data, and therefore is optimal for single-crystal electron-diffraction automated diffraction tomography (ADT) data. The unit-cell determination of various materials from ADT data as well as single-crystal X-ray data is demonstrated.