Poly[bis-(µ2-N,N-di-methyl-formamide-κ2 O:O)bis-(µ4-thio-phene-2,5-di-carboxyl-ato-κ4 O:O':O'':O''')dicobalt(II)].

The asymmetric unit of the title three-dimensional metal-organic hybrid compound, [Co2(C6H2O4S)2(C3H7NO)2] n , comprises two cobalt(II) cations, one residing on a twofold axis and the other on a centre of inversion, one thio-phene-2,5-di-carboxyl-ate (tdc2-) ligand and one coordinating di-methyl-formamide (DMF) solvent mol-ecule. Both of the cobalt(II) cations exhibit an octa-hedral coordination environment from the four carboxyl O atoms of the tdc2- anions in a µ 4-κ 1:κ 1:κ 1:κ 1 fashion and two O atoms from DMF. A pair of carboxyl O atoms and one DMF molecule connect the adjacent cobalt(II) cations into an infinite chain, leading to a rod-spacer framework with rhombus-window channels, yet no residual solvent-accessible voids are present because the coordinating DMF molecules are oriented into the potential channels.

Covalent triazine-based frameworks/iron oxide for highly sensitive magnetic solid-phase extraction of phenolic pollutants in water samples.

This study demonstrates for the first time the enrichment potential of covalent triazine-based frameworks/iron oxide for the magnetic solid-phase extraction of seven typical polar phenolic pollutants. Important parameters, such as the eluant and its volume, adsorbent amounts, sample pH, extraction time, and ionic strength, were optimized in detail. Under the optimal conditions, low limits of detection (0.09-0.53 ng/mL), wide linear range (25-2000 ng/mL), good repeatability (1.2-8.3%) and reproducibility (1.5-9.9%) were achieved. The developed method was successfully applied to analyze the target phenols at trace levels in environmental water samples.

Magnetic covalent triazine-based frameworks as magnetic solid-phase extraction adsorbents for sensitive determination of perfluorinated compounds in environmental water samples.

Covalent organic frameworks (COFs), which are a new type of carbonaceous polymeric material, have attracted great interest because of their large surface area and high chemical and thermal stability. However, to the best of our knowledge, no work has reported the use of magnetic COFs as adsorbents for magnetic solid-phase extraction (MSPE) to enrich and determine environmental pollutants. This work aims to investigate the feasibility of using covalent triazine-based framework (CTF)/Fe2O3 composites as MSPE adsorbents to enrich and analyze perfluorinated compounds (PFCs) at trace levels in water samples. Under the optimal conditions, the method developed exhibited low limits of detection (0.62-1.39 ng·L-1), a wide linear range (5-4000 ng L-1), good repeatability (1.12-9.71%), and good reproducibility (2.45-7.74%). The new method was successfully used to determine PFCs in actual environmental water samples. MSPE based on CTF/Fe2O3 composites exhibits potential for analysis of PFCs at trace levels in environmental water samples. Graphical abstract Magnetic covalent triazine-based frameworks (CTFs) were used as magnetic solid-phase extraction adsorbents for the sensitive determination of perfluorinated compounds in environmental water samples. PFBA perfluorobutyric acid, PFBS perfluorobutane sulfonate, PFDA perfluorodecanoic acid, PFDoA perfluorododecanoic acid, PFHpA perfluoroheptanoic acid, PFHxA perfluorohexanoic acid, PFHxS perfluorohexane sulfonate, PFNA perfluorononanoic acid, PFOA perfluorooctanoic acid, PFPeA perfluoropentanoic acid, PFUdA Perfluoroundecanoic acid.

Comparative evaluation of two dose optimization methods for image-guided, highly-conformal, tandem and ovoids cervix brachytherapy planning.

Although the Manchester system is still extensively used to prescribe dose in brachytherapy (BT) for locally advanced cervix cancer, many radiation oncology centers are transitioning to 3D image-guided BT, owing to the excellent anatomy definition offered by modern imaging modalities. As automatic dose optimization is highly desirable for 3D image-based BT, this study comparatively evaluates the performance of two optimization methods used in BT treatment planning--Nelder-Mead simplex (NMS) and simulated annealing (SA)--for a cervix BT computer simulation model incorporating a Manchester-style applicator. Eight model cases were constructed based on anatomical structure data (for high risk-clinical target volume (HR-CTV), bladder, rectum and sigmoid) obtained from measurements on fused MR-CT images for BT patients. D90 and V100 for HR-CTV, D2cc for organs at risk (OARs), dose to point A, conformation index and the sum of dwell times within the tandem and ovoids were calculated for optimized treatment plans designed to treat the HR-CTV in a highly conformal manner. Compared to the NMS algorithm, SA was found to be superior as it could perform optimization starting from a range of initial dwell times, while the performance of NMS was strongly dependent on their initial choice. SA-optimized plans also exhibited lower D2cc to OARs, especially the bladder and sigmoid, and reduced tandem dwell times. For cases with smaller HR-CTV having good separation from adjoining OARs, multiple SA-optimized solutions were found which differed markedly from each other and were associated with different choices for initial dwell times. Finally and importantly, the SA method yielded plans with lower dwell time variability compared with the NMS method.

Novel sparse component analysis approach to free radical EPR spectra decomposition.

Free radicals play important roles in many physiological and pathological pathways in biological systems. These free radicals can be detected and quantified by their EPR spectra. The measured EPR spectra are often mixtures of pure spectra of several different free radicals and other chemicals. Blind source separation can be applied to estimate the pure spectra of interested free radicals. However, since the pure EPR spectra are often not independent of each other, the approach based on independent component analysis (ICA) cannot accurately extract the required spectra. In this paper, a novel sparse component analysis method for blind source separation, which exploits the sparsity of the EPR spectra, is presented to reliably extract the pure source spectra from their mixtures with high accuracy. This method has been applied to the analysis of EPR spectra of superoxide, hydroxyl, and nitric oxide free radicals, for both simulated data and real world ex vivo experiment. Compared to the traditional self-modeling method and our previous ICA-based blind source separation method, the proposed sparse component analysis approach gives much better results and can give perfect separation for mixtures of superoxide spectrum and hydroxyl spectrum in the ideal noise-free case. This method can also be used in other similar applications of quantitative spectroscopy analysis.