Allo-Hemodialysis, a Novel Dialytic Treatment Option for Patients with Kidney Failure: Outcomes of Mathematical Modelling, Prototyping, and Ex Vivo Testing.

It has been estimated that in 2010, over two million patients with end-stage kidney disease may have faced premature death due to a lack of access to affordable renal replacement therapy, mostly dialysis. To address this shortfall in dialytic kidney replacement therapy, we propose a novel, cost-effective, and low-complexity hemodialysis method called allo-hemodialysis (alloHD). With alloHD, instead of conventional hemodialysis, the blood of a patient with kidney failure flows through the dialyzer's dialysate compartment counter-currently to the blood of a healthy subject (referred to as a "buddy") flowing through the blood compartment. Along the concentration and hydrostatic pressure gradients, uremic solutes and excess fluid are transferred from the patient to the buddy and subsequently excreted by the healthy kidneys of the buddy. We developed a mathematical model of alloHD to systematically explore dialysis adequacy in terms of weekly standard urea Kt/V. We showed that in the case of an anuric child (20 kg), four 4 h alloHD sessions are sufficient to attain a weekly standard Kt/V of >2.0. In the case of an anuric adult patient (70 kg), six 4 h alloHD sessions are necessary. As a next step, we designed and built an alloHD machine prototype that comprises off-the-shelf components. We then used this prototype to perform ex vivo experiments to investigate the transport of solutes, including urea, creatinine, and protein-bound uremic retention products, and to quantitate the accuracy and precision of the machine's ultrafiltration control. These experiments showed that alloHD performed as expected, encouraging future in vivo studies in animals with and without kidney failure.

Exploring the Tl 2 H 2 potential energy surface: A comparative analysis with group 13 systems and experiment.

Thallium chemistry is experiencing unprecedented importance. Therefore, it is valuable to characterize some of the simplest thallium compounds. Stationary points along the singlet and triplet Tl 2 H 2 potential energy surface have been characterized. Stationary point geometries were optimized with the CCSD(T)/aug-cc-pwCVQZ-PP method. Harmonic vibrational frequencies were computed at the same level of theory while anharmonic vibrational frequencies were computed at the CCSD(T)/aug-cc-pwCVTZ-PP level of theory. Final energetics were obtained with the CCSDT(Q) method. Basis sets up to augmented quintuple-zeta cardinality (aug-cc-pwCV5Z-PP) were employed to obtain energetics in order to extrapolate to the complete basis set limits using the focal point approach. Zero-point vibrational energy corrections were appended to the extrapolated energies in order to determine relative energies at 0 K. It was found that the planar dibridged isomer lies lowest in energy while the linear structure lies highest in energy. The results were compared to other group 13 M 2 H 2 (M = B, Al, Ga, In, and Tl) theoretical studies and some interesting variations are found. With respect to experiment, incompatibilities exist.

Electrospinning Nanofiber Mats with Magnetite Nanoparticles Using Various Needle-Based Techniques.

Electrospinning can be used to produce nanofiber mats containing diverse nanoparticles for various purposes. Magnetic nanoparticles, such as magnetite (Fe3O4), can be introduced to produce magnetic nanofiber mats, e.g., for hyperthermia applications, but also for basic research of diluted magnetic systems. As the number of nanoparticles increases, however, the morphology and the mechanical properties of the nanofiber mats decrease, so that freestanding composite nanofiber mats with a high content of nanoparticles are hard to produce. Here we report on poly (acrylonitrile) (PAN) composite nanofiber mats, electrospun by a needle-based system, containing 50 wt% magnetite nanoparticles overall or in the shell of core-shell fibers, collected on a flat or a rotating collector. While the first nanofiber mats show an irregular morphology, the latter are quite regular and contain straight fibers without many beads or agglomerations. Scanning electron microscopy (SEM) and atomic force microscopy (AFM) reveal agglomerations around the pure composite nanofibers and even, round core-shell fibers, the latter showing slightly increased fiber diameters. Energy dispersive X-ray spectroscopy (EDS) shows a regular distribution of the embedded magnetic nanoparticles. Dynamic mechanical analysis (DMA) reveals that mechanical properties are reduced as compared to nanofiber mats with smaller amounts of magnetic nanoparticles, but mats with 50 wt% magnetite are still freestanding.

Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEngine): Automation and interoperability among computational chemistry programs.

Community efforts in the computational molecular sciences (CMS) are evolving toward modular, open, and interoperable interfaces that work with existing community codes to provide more functionality and composability than could be achieved with a single program. The Quantum Chemistry Common Driver and Databases (QCDB) project provides such capability through an application programming interface (API) that facilitates interoperability across multiple quantum chemistry software packages. In tandem with the Molecular Sciences Software Institute and their Quantum Chemistry Archive ecosystem, the unique functionalities of several CMS programs are integrated, including CFOUR, GAMESS, NWChem, OpenMM, Psi4, Qcore, TeraChem, and Turbomole, to provide common computational functions, i.e., energy, gradient, and Hessian computations as well as molecular properties such as atomic charges and vibrational frequency analysis. Both standard users and power users benefit from adopting these APIs as they lower the language barrier of input styles and enable a standard layout of variables and data. These designs allow end-to-end interoperable programming of complex computations and provide best practices options by default.

Psi4NumPy: An Interactive Quantum Chemistry Programming Environment for Reference Implementations and Rapid Development.

Psi4NumPy demonstrates the use of efficient computational kernels from the open-source Psi4 program through the popular NumPy library for linear algebra in Python to facilitate the rapid development of clear, understandable Python computer code for new quantum chemical methods, while maintaining a relatively low execution time. Using these tools, reference implementations have been created for a number of methods, including self-consistent field (SCF), SCF response, many-body perturbation theory, coupled-cluster theory, configuration interaction, and symmetry-adapted perturbation theory. Furthermore, several reference codes have been integrated into Jupyter notebooks, allowing background, underlying theory, and formula information to be associated with the implementation. Psi4NumPy tools and associated reference implementations can lower the barrier for future development of quantum chemistry methods. These implementations also demonstrate the power of the hybrid C++/Python programming approach employed by the Psi4 program.