SURFACE MODIFICATION OF TPR SOLE: AN APPROACH TO IMPROVE SLIP RESISTANCE ON QUARRY AND CERAMIC TILES

Human slip on smooth surfaces is a common accident, even though the footwear soling materials are designed with cleats and treads to provide more friction with the floor. About 20% of footwear is made with thermoplastic rubber (TPR; styrene-butadiene-styrene) soles. The slip resistance property under wet-flooring conditions of this kind of sole is poor because of the nonionic nature of the polymer. Chemical surface modification can be exploited to improve the slip-resistance property of TPR soles. The surface is chemically modified with trichloroisocyanuric acid in a methyl ethyl ketone medium (TCI/MEK; at 1, 2, and 3%) to introduce chlorinated and oxidized moieties to the rubber surface. The extent of surface modification produced in TPR with this change can be tested using attenuated total reflectance–Fourier transform infrared spectroscopy, scanning electron microscopy, and contact angle and surface roughness measurements. The improvement in slip resistance can be evaluated by measuring the coefficient of friction using a dynamic slip-resistance tester. The extent of the change in the functional physical properties, such as surface roughness, contact angle, work adhesion, in slip resistance can be improved by optimizing the concentration of trichloroisocyanuric acid. Physicomechanical properties of unmodified and modified soles that are essential for wear performance can be tested and compared. Quantitative changes on the surface of modified rubber soles increases surface roughness, reduces contact angles, and increases work energy, so there is a considerable increase in the coefficient of friction, especially under wet floor conditions. The chemical surface treatment tends to reduce the bulk mechanical properties, such as tensile strength, elongation at break, and abrasion resistance, because cyanuric acid attacks the sole. The coefficient of friction produces a positive trend at 1 and 2% TCI/MEK treatments, but the trend is negative at a 3% concentration. The optimum surface treatment level for surface modification to enhance the slip resistance of TPR is 2% TCI/MEK.

Targeting the motor end plates in the mouse hindlimb gives access to a greater number of spinal cord motor neurons: an approach to maximize retrograde transport

Lower motor neuron dysfunction is one of the most debilitating neurological conditions and, as such, significantly impacts on the quality of life of affected individuals. Within the last decade, the engineering of mouse models of lower motor neuron diseases has facilitated the development of new therapeutic scenarios aimed at delaying or reversing the progression of these conditions. In this context, motor end plates (MEPs) are highly specialized regions on the skeletal musculature that offer minimally invasive access to the pre-synaptic nerve terminals, henceforth to the spinal cord motor neurons. Transgenic technologies can take advantage of the relationship between the MEP regions on the skeletal muscles and the corresponding motor neurons to shuttle therapeutic genes into specific compartments within the ventral horn of the spinal cord. The first aim of this neuroanatomical investigation was to map the details of the organization of the MEP zones for the main muscles of the mouse hindlimb. The hindlimb was selected for the present work, as it is currently a common target to challenge the efficacy of therapies aimed at alleviating neuromuscular dysfunction. This MEP map was then used to guide series of intramuscular injections of Fluoro-Gold (FG) along the muscles' MEP zones, therefore revealing the distribution of the motor neurons that supply them. Targeting the entire MEP regions with FG increased the somatic availability of the retrograde tracer and, consequently, gave rise to FG-positive motor neurons that are organized into rostro-caudal columns spanning more spinal cord segments than previously reported. The results of this investigation will have positive implications for future studies involving the somatic delivery and retrograde transport of therapeutic transgenes into affected motor neurons. These data will also provide a framework for transgenic technologies aiming at maintaining the integrity of the neuromuscular junction for the treatment of lower motor neuron dysfunctions.

2-Amino-6-methyl-pyridinium 4-methyl-benzene-sulfonate

In the asymmetric unit of the title salt, C₆H₉N₂⁺·C₇H₇O₃S⁻, there are two independent 2-amino-6-methyl­pyridinium cations and two independent 4-methyl­benzene­sulfonate anions. Both cations are protonated at their pyridine N atoms and their geometries reveal amine–imine tautomerism. In the 4-methyl­benzene­sulfonate anions, the carboxyl­ate groups are twisted out of the benzene ring planes by 88.4 (1) and 86.2 (2)°. In the crystal, the sulfonate O atoms of an anion inter­act with the protonated N atoms and the 2-amino groups of a cation via a pair of N—H⋯O hydrogen bonds, forming an R₂²(8) ring motif. These motifs are connected via N—H⋯O hydrogen bonds, forming chains running along the a-axis direction. Within the chains there are weak C—H⋯O hydrogen bonds present. In addition, aromatic π–π stacking inter­actions [centroid–centroid distances = 3.771 (2), 3.599 (2), 3.599 (2) and 3.497 (2) Å] involving neighbouring chains are also observed.

2-Amino-6-methyl-pyridinium 2,2,2-tri-chloro-acetate

In the asymmetric unit of the title mol­ecular salt, C₆H₉N₂⁺·C₂Cl₃O₂⁻, there are two independent 2-amino-6-methyl­pyridinium cations and two independent tri­chloro­acetate anions. The pyridine N atom of the 2-amino-6-methyl­pyridine mol­ecule is protonated and the geometries of these cations reveal amine–imine tautomerism. Both protonated 2-amino-6-methyl­pyridinium cations are essentially planar [maximum deviations = 0.026 (2) and 0.012 (2) Å]. In the crystal, the protonated N atom and the 2-amino group of the cation are hydrogen bonded to the carboxyl­ate O atoms of the anion via a pair of N—H⋯O hydrogen bonds, forming an R₂²(8) ring motif. These motifs are connected via N—H⋯O and C—H⋯O hydrogen bonds to form slabs parallel to (101).

catena-Poly[[bis-(nitrato-κ(2) O,O')barium]-bis-(μ-l-histidine-κ(3) O,O':O]

In the polymeric title compound, [Ba(NO₃)₂(C₆H₉N₃O₂)₂]_n, the Ba^II atom is located on a crystallographic twofold axis and is coordinated by ten O atoms. Six are derived from two zwitterionic l-histidine mol­ecules that simultaneously chelate one Ba^II atom and bridge to another. The remaining four O atoms are derived from two chelating nitrates. The mol­ecules assemble to form a chain along [010]. In the crystal, chains are linked via N—H⋯O and N—H⋯N hydrogen bonds, generating a three-dimensional network.

Bis(μ-l-arginine-κ(3) N (2),O:O')bis-(l-arginine-κ(2) N (2),O)tetra-μ-chlorido-tetra-chlorido-tetra-copper(II)

The title compound, [Cu₄Cl₈(C₆H₁₄N₄O₂)₄], contains four mol­ecules in the asymmetric unit. In the mol­ecular structure, each of the four Cu²⁺ ions binds to three Cl atoms, one N atom and one O atom, resulting in distorted square-pyramidal coordination environments. The molecular structure is stabilized by weak C—H⋯O and N—H⋯Cl hydrogen bonds. The crystal structure exhibit weak inter­molecular N—H⋯O, C—H⋯O and N—H⋯Cl inter­actions, generating a three-dimensional network.

Commissioning dose computation models for spot scanning proton beams in water for a commercially available treatment planning system

PURPOSE

To present our method and experience in commissioning dose models in water for spot scanning proton therapy in a commercial treatment planning system (TPS).

METHODS

The input data required by the TPS included in-air transverse profiles and integral depth doses (IDDs). All input data were obtained from Monte Carlo (MC) simulations that had been validated by measurements. MC-generated IDDs were converted to units of Gy mm(2)/MU using the measured IDDs at a depth of 2 cm employing the largest commercially available parallel-plate ionization chamber. The sensitive area of the chamber was insufficient to fully encompass the entire lateral dose deposited at depth by a pencil beam (spot). To correct for the detector size, correction factors as a function of proton energy were defined and determined using MC. The fluence of individual spots was initially modeled as a single Gaussian (SG) function and later as a double Gaussian (DG) function. The DG fluence model was introduced to account for the spot fluence due to contributions of large angle scattering from the devices within the scanning nozzle, especially from the spot profile monitor. To validate the DG fluence model, we compared calculations and measurements, including doses at the center of spread out Bragg peaks (SOBPs) as a function of nominal field size, range, and SOBP width, lateral dose profiles, and depth doses for different widths of SOBP. Dose models were validated extensively with patient treatment field-specific measurements.

RESULTS

We demonstrated that the DG fluence model is necessary for predicting the field size dependence of dose distributions. With this model, the calculated doses at the center of SOBPs as a function of nominal field size, range, and SOBP width, lateral dose profiles and depth doses for rectangular target volumes agreed well with respective measured values. With the DG fluence model for our scanning proton beam line, we successfully treated more than 500 patients from March 2010 through June 2012 with acceptable agreement between TPS calculated and measured dose distributions. However, the current dose model still has limitations in predicting field size dependence of doses at some intermediate depths of proton beams with high energies.

CONCLUSIONS

We have commissioned a DG fluence model for clinical use. It is demonstrated that the DG fluence model is significantly more accurate than the SG fluence model. However, some deficiencies in modeling the low-dose envelope in the current dose algorithm still exist. Further improvements to the current dose algorithm are needed. The method presented here should be useful for commissioning pencil beam dose algorithms in new versions of TPS in the future.

Verification of proton range, position, and intensity in IMPT with a 3D liquid scintillator detector system

PURPOSE

Intensity-modulated proton therapy (IMPT) using spot scanned proton beams relies on the delivery of a large number of beamlets to shape the dose distribution in a highly conformal manner. The authors have developed a 3D system based on liquid scintillator to measure the spatial location, intensity, and depth of penetration (energy) of the proton beamlets in near real-time.

METHODS

The detector system consists of a 20 × 20 × 20 cc liquid scintillator (LS) material in a light tight enclosure connected to a CCD camera. This camera has a field of view of 25.7 by 19.3 cm and a pixel size of 0.4 mm. While the LS is irradiated, the camera continuously acquires images of the light distribution produced inside the LS. Irradiations were made with proton pencil beams produced with a spot-scanning nozzle. Pencil beams with nominal ranges in water between 9.5 and 17.6 cm were scanned to irradiate an area of 10 × 10 cm square on the surface of the LS phantom. Image frames were acquired at 50 ms per frame.

RESULTS

The signal to noise ratio of a typical Bragg peak was about 170. Proton range measured from the light distribution produced in the LS was accurate to within 0.3 mm on average. The largest deviation seen between the nominal and measured range was 0.6 mm. Lateral position of the measured pencil beam was accurate to within 0.4 mm on average. The largest deviation seen between the nominal and measured lateral position was 0.8 mm; however, the accuracy of this measurement could be improved by correcting light scattering artifacts. Intensity of single proton spots were measured with precision ranging from 3 % for the smallest spot intensity (0.005 MU) to 0.5 % for the largest spot (0.04 MU).

CONCLUSIONS

Our LS detector system has been shown to be capable of fast, submillimeter spatial localization of proton spots delivered in a 3D volume. This system could be used for beam range, intensity and position verification in IMPT.