Physics in Medicine最新文献

Dynamically controlling cell-material interactions has a strong potential for advancing many cell-based technologies, including cell detection and cell sorting systems. To this end, fundamental studies that provide insights into how cells respond biologically to physico-chemical cues are necessary. Studies show that biological responses, such as cytoskeletal reorganization alter the overall viscoelastic properties of cells. Here, we monitored, in real time, and non-invasively, the evolution of the viscoelastic properties of yeast cells as a function of medium ionic strength (IS). Measurements were performed on SiO₂-coated sensor surfaces using the quartz crystal microbalance with dissipation monitoring (QCM-D). Our results indicate that, for every adhesion phase, the cell stiffness decreases with increasing IS. This trend was consistent across the various cell concentrations studied. In terms of cell-substrate interactions, we show that a high IS promotes cell adhesion for all cell concentrations, including ultra-low concentrations. Our results also show that while the adhesion signal decreases with cell concentration for each IS, only temporal and close to noise-level adhesion signals were measured in ion-free medium irrespective of the cell concentration. We also show that cell adhesion rates are higher in physiological ionic strengths compared to cells in higher ionic strengths. Finally, from a cell detection perspective, the results reveal that for very low cell concentrations, large signal enhancements can be achieved by measuring the same concentration in a higher ionic strength. This result also applies for measurements on gold surfaces; thus, we suggest ionic tuning as a strategy for promoting trace-level cell detection in biosensors and cell sorting applications.

PEM (Positron Emission Mammography) imaging is a molecular imaging technique for early diagnosis and staging of breast cancer. So, it is very important to check the performance of the PAM device in order to improve the image quality. The aim of this work was to investigate the effects of Time Of Flight (TOF) and Depth Of Interaction (DOI) corrections in the PEM system's performance. For this purpose, the commercially available clinical PEM scanner (PEM Flex Solo II, Naviscan) was simulated using GATE software. This system consists of two non-rotating detector heads that are positioned in an opposing fashion on each side of the body part. Each detector head contains 12 sensitive PMTs with a 6 × 2 array. Also, each PMT is coupled by a light guide to 169 crystals with a 13 × 13 array of 2 mm × 2 mm × 13 mm LYSO crystals. The sensitivity parameter and the scattering fraction of the system were investigated according to the NEMA NU4-2008 standard's manual. Then to assessment the effect of TOF, the coincidence time resolution was changed from 900ps to 100ps. The maximum of NECR curve increases by 42.3% for considering the TOF in the simulation. Also, the Phoswich detector with BGO and LYSO crystals was used to investigate the effect of DOI. The results also show that in Phoswich detector with LYSO crystal with a thickness of 5 mm and BGO crystal with a thickness of 9 mm, the maximum NECR curve increases by 54%. The spatial resolution of the system improves from 2.4 mm to 1 mm by considering TOF and DOI. According to these results, considering the TOF and DOI have a significant role in improving the performance of the PEM system.

The vibration of the human middle ear shows sharp variations in the amplitude and phase over the audible frequency range. Measurements often differ between subjects, and it is difficult to determine the average response of the human middle ear. However, such an average response curve is of great value in detecting pathological ears. Simply averaging the amplitude and phase for each frequency results in a “washed-out” view due to differences in the locations of the maxima and minima of the curves. Therefore, a method is required to consider each individual curve's shape in the average.

This paper discusses a novel method based on frequency-response transfer functions. Each of the individual measurements is fitted with a rational polynomial. The average frequency response is determined by a weighted averaging of the individual curves' numerator and denominator polynomial coefficients. Such an average preserves the shape of the individual curves. The method is applied to vibrational data of the human stapes. As expected from the literature, two resonance frequencies at 1.14 ± 0.13 kHz and 3.61 ± 0.43 kHz were found. A comparison with other methods is made to discuss the method's advantages and disadvantages.

Laboratories all over the word use syringe pumps every day for a multitude of purposes. The market of syringe pumps is limited, as it does not consider the broad range of specifications required by different researchers. In this work, we present a 3D printed syringe pump designed to be affordable, customizable, and extremely user friendly while still maintaining reliability and precision. The pump, thanks to its flexible design and smartphone-controlled interface, can be used in educational settings as well as in biological and chemical laboratories. The presented syringe-pump is used in this work to run a light catalyzed polymerization of butyl methacrylate using visible light, in a continuous flow setup.

A portable test to rapidly determine levels of levodopa, the drug used to treat Parkinson's disease, can improve clinical management of the disease. In this study, screen-printed electrodes (SPEs) were modified with polymers to facilitate the electrochemical detection of levodopa. Cyclic voltammetry was used to deposit a thin layer of polyaniline on the electrode surface. Scanning electron microscopy revealed high surface coverage, which did not impact the electrode's conductivity. Differential pulse voltammetry measurements with the polyaniline-modified electrodes enabled the measurement of levodopa at physiologically relevant concentrations with discrimination between a common interferent (ascorbic acid) and a structurally similar compound (l-tyrosine). However, the use of the polymer layer did not permit differentiation between levodopa and dopamine; the only difference in these molecules is that levodopa has an amino acid moiety whereas dopamine has a free amine group. Density functional theory calculations demonstrated that aniline formed a hydrogen bond between the amino group of the monomer and the meta-hydroxyl group, which is present in both levodopa and dopamine, with similar binding energies (−53.36 vs −50.08 kJ mol⁻¹). Thus, the polymer-functionalised SPEs are a valuable tool to measure compounds important in Parkinson's disease, but further refinement is needed to achieve selective detection.

Neuro-degenerative diseases influence significantly the gait behavior and the ability to move. To explore the etiology of neuro-degenerative disease, it would be useful to characterize gait dynamics. The purpose of this study is to classify different neuro-degenerative diseases using fractal geometry. We use Gait Dynamics in Neuro-Degenerative Disease Data Base including recordings from patients with Parkinson's disease (n = 15), Huntington's disease (n = 20), or amyotrophic lateral sclerosis (n = 13) and 16 healthy control subjects are also included (Hausdorff JM et al., 2000). The vibration analysis using power spectral densities (PSD) method has been carried out to discover whether some type of power-law scaling exists for various statistical moments at different scales of these databases. Using Discrete Wavelet Transform (DWT) and Wavelet Leader Multifractal (WLM) analysis, we explore the possibility that these recordings belong to the class of multifractal process for which a large number of scaling exponents are required to characterize their scaling structures. A non-linear analysis called the Fractal Dimension (FD) using Higuchi algorithm has been performed to quantify the fractal complexity of recordings. According to our results, we noticed that neither the power spectral densities nor the Higuchi algorithm to find the fractal dimension alone were sufficient to separate different classes of patients and healthy people. In addition, when multifractal analysis and scaling exponent were used as a classifier, the three classes could not be well separated. However, this study revealed that we have a wide range of exponents for some of the gait recordings which indicates they have multifractal structure and they need to be indexed by different exponents as we decompose them into different subsets. In other words, these multifractal subjects require much more exponents to characterize their scaling properties compared to monofractal gait recordings which their spectrum displays a narrow width of scaling exponent. Another important outcome from our multifractal analysis is recognizing obvious changes in the shape of D(h) curves for some of the gait recordings which is crucial in finding the best strategies to better controlling the gait mechanisms in different neuro-degenerative diseases. Although the vibration analysis, fractal dimension and multifractal analysis may not be able to classify gait recordings, however, they can be used as comprehensive frameworks to further analysis, characterize and compare the complexity and fractal behavior of gait recordings and data structures of different neuro-degenerative diseases in clinical database. Likewise, beside the Higuchi algorithm to find the fractal dimension as a complexity measure for the gait recordings, it will require much more efforts and further clinical analysis to find a specific threshold which make the fractal dimension to be considered as a biomarker and di