Quantitative Assessment of Head Tremor in Patients with Essential Tremor and Cervical Dystonia by Using Inertial Sensors.

Tremor is most common among the movement disabilities that affect older people, having a prevalence rate of 4.6% in the population older than 65 years. Despite this, distinguishing different types of tremors is clinically challenging, often leading to misdiagnosis. However, due to advances in microelectronics and wireless communication, it is now possible to easily monitor tremor in hospitals and even in home environments. In this paper, we propose an architecture of a system for remote health-care and one possible implementation of such system focused on head tremor monitoring. In particular, the aim of the study presented here was to test new tools for differentiating essential tremor from dystonic tremor. To that aim, we propose a number of temporal and spectral features that are calculated from measured gyroscope signals, and identify those that provide optimal differentiation between two groups. The mean signal amplitude feature results in sensitivity = 0.8537 and specificity = 0.8039 in distinguishing patients having cervical dystonia with or without tremor. In addition, mean signal amplitude was shown to be significantly higher in patients with essential tremor than in patients with cervical dystonia, whereas the mean peak frequency is not different between two groups.

Multifractal analysis of tumour microscopic images in the prediction of breast cancer chemotherapy response.

Due to the individual heterogeneity, highly accurate predictors of chemotherapy response in invasive breast cancer are needed for effective chemotherapeutic management. However, predictive molecular determinants for conventional chemotherapy are only emerging and still incorporate a high degree of predictive variability. Based on such pressing need for predictive performance improvement, we explored the value of pre-therapy tumour histology image analysis to predict chemotherapy response. Fractal analysis was applied to hematoxylin/eosin stained archival tissue of diagnostic biopsies derived from 106 patients diagnosed with invasive breast cancer. The tissue was obtained prior to neoadjuvant anthracycline-based chemotherapy and patients were subsequently divided into three groups according to their actual chemotherapy response: partial pathological response (pPR), pathological complete response (pCR) and progressive/stable disease (PD/SD). It was shown that multifractal analysis of breast tumour tissue prior to chemotherapy indeed has the capacity to distinguish between histological images of the different chemotherapy responder groups with accuracies of 91.4% for pPR, 82.9% for pCR and 82.1% for PD/SD. F(α)max was identified as the most important predictive parameter. It represents the maximum of multifractal spectrum f(α), where α is the Hölder's exponent. This is the first study investigating the predictive value of multifractal analysis as a simple and cost-effective tool to predict the chemotherapy response. Improvements in chemotherapy prediction provide clinical benefit by enabling more optimal chemotherapy decisions, thus directly affecting the quality of life and survival.

Application of multifractal analysis on microscopic images in the classification of metastatic bone disease.

The paper considers the method, based on multifractal (MF) analysis, for classifying the shape of tissue cells from microscopis images, identifying the primary cancer in cases of metastasis bone disease. Diagnosis of primary cancer is of great importance, because further treatment depends on how successful and accurate that diagnosis is. This method can be applied as an additional and objective tool in primary cancer diagnosis, as well as in decreasing of the subjective factor and error probability. The method is tested over a large number (1050) of clinical cases from the Institute of Pathology, University of Belgrade. The results of computer-aided analysis of images have been presented and discussed.

Graphitic Carbon Nitride as a New Sustainable Photocatalyst for Textile Functionalization.

As a promising organic semiconducting material, polymeric graphitic carbon nitride (g-C3N4) has attracted much attention due to its excellent optical and photoelectrochemical properties, thermal stability, chemical inertness, nontoxicity, abundance, and low cost. Its advantageous visible light-induced photocatalytic activity has already been beneficially used in the fields of environmental remediation, biological applications, healthcare, energy conversion and storage, and fuel production. Despite the recognized potential of g-C3N4, there is still a knowledge gap in the application of g-C3N4 in the field of textiles, with no published reviews on the g-C3N4-functionalization of textile materials. Therefore, this review article aims to provide a critical overview of recent advances in the surface and bulk modification of textile fibres by g-C3N4 and its composites to tailor photocatalytic self-cleaning, antibacterial, and flame retardant properties as well as to create a textile catalytic platform for water disinfection, the removal of various organic pollutants from water, and selective organic transformations. This paper highlights the possibilities of producing g-C3N4-functionalized textile substrates and suggests some future prospects for this research area.

New Insights into Antibacterial and Antifungal Properties, Cytotoxicity and Aquatic Ecotoxicity of Flame Retardant PA6/DOPO-Derivative Nanocomposite Textile Fibers.

The aim of this study was to evaluate the antibacterial and antifungal activity, cytotoxicity, leaching, and ecotoxicity of novel flame retardant polyamide 6 (PA6) textile fibers developed by our research group. The textile fibers were produced by the incorporation of flame-retardant bridged 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide (DOPO) derivative (PHED) in the PA6 matrix during the in situ polymerization process at concentrations equal to 10 and 15 wt% (PA6/10PHED and PA6/15PHED, respectively). Whilst the nanodispersed PHED provided highly efficient flame retardancy, its biological activity led to excellent antibacterial activity against Escherichia coli and Staphylococcus aureus, as well as excellent antifungal activity against Aspergillus niger and Candida albicans. The results confirmed leaching of the PHED, but the tested leachates did not cause any measurable toxic effect to the duckweed Lemna minor. The in vitro cytotoxicity of the leached PHED from the PA6/15PHED sample was confirmed for human cells from adipose tissue in direct and prolonged contact. The targeted biological activity of the organophosphinate flame retardant could be beneficial for the development of PA6 textile materials with multifunctional properties and the low ecotoxicity profile, while the PHED's leaching and cytotoxicity limit their application involving the washing processes and direct contact with the skin.

Effect of Different Flame-Retardant Bridged DOPO Derivatives on Properties of in Situ Produced Fiber-Forming Polyamide 6.

The production of sustainable and effective flame retardant (FR) polyamide 6 (PA6) fibrous materials requires the establishment of a novel approach for the production of polyamide 6/FR nanodispersed systems. This research work explores the influence of three different flame-retardant bridged 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide (DOPO) derivatives on the comprehensive properties of in situ produced PA6/FR systems. To this end, in situ water-catalyzed ring-opening polymerization of ε-caprolactam was conducted in the presence of three different bridged DOPO derivatives, e.g., one P-N bond phosphonamidate derivative and two P-C bond phosphinate derivatives. The selected bridged DOPO derivatives mainly act in the gas phase at the temperatures that relatively match the PA6 pyrolysis specifics. The effects of the FRs on the dispersion state, morphological, molecular, structural, melt-rheological, and thermal properties of the in situ synthesized PA6 were evaluated. The specific advantage of this approach is one-step production of PA6 with uniformly distributed nanodispersed FR, which was obtained in the case of all three applied FRs. However, the applied FRs differently interacted with monomer and polymer during the polymerization, which was reflected in the length of PA6 chains, crystalline structure, and melt-rheological properties. The applied FRs provided a comparable effect on the thermal stability of PA6 and stabilization of the PA6/FR systems above 450 °C in the oxygen-assisted pyrolysis. However, only with the specifically designed FR molecule were the comprehensive properties of the fiber-forming PA6 satisfied for the continuous conduction of the melt-spinning process.

Characterization of Polyamide 6/Multilayer Graphene Nanoplatelet Composite Textile Filaments Obtained Via In Situ Polymerization and Melt Spinning.

Studies of the production of fiber-forming polyamide 6 (PA6)/graphene composite material and melt-spun textile fibers are scarce, but research to date reveals that achieving the high dispersion state of graphene is the main challenge to nanocomposite production. Considering the significant progress made in the industrial mass production of graphene nanoplatelets (GnPs), this study explored the feasibility of production of PA6/GnPs composite fibers using the commercially available few-layer GnPs. To this aim, the GnPs were pre-dispersed in molten ε-caprolactam at concentrations equal to 1 and 2 wt %, and incorporated into the PA6 matrix by the in situ water-catalyzed ring-opening polymerization of ε-caprolactam, which was followed by melt spinning. The results showed that the incorporated GnPs did not markedly influence the melting temperature of PA6 but affected the crystallization temperature, fiber bulk structure, crystallinity, and mechanical properties. Furthermore, GnPs increased the PA6 complex viscosity, which resulted in the need to adjust the parameters of melt spinning to enable continuous filament production. Although the incorporation of GnPs did not provide a reinforcing effect of PA6 fibers and reduced fiber tensile properties, the thermal stability of the PA6 fiber increased. The increased melt viscosity and graphene anti-dripping properties postponed melt dripping in the vertical flame spread test, which consequently prolonged burning within the samples.

Fractal dimension and lacunarity of tumor microscopic images as prognostic indicators of clinical outcome in early breast cancer.

AIM: Research in the field of breast cancer outcome prognosis has been focused on molecular biomarkers, while neglecting the discovery of novel tumor histology structural clues. We thus aimed to improve breast cancer prognosis by fractal analysis of tumor histomorphology. PATIENTS & METHODS: This retrospective study included 92 breast cancer patients without systemic treatment. RESULTS: Fractal dimension and lacunarity of the breast tumor microscopic histology possess prognostic value comparable to the major clinicopathological prognostic parameters. CONCLUSION: Fractal analysis was performed for the first time on routinely produced archived pan-tissue stained primary breast tumor sections, indicating its potential for clinical use as a simple and cost-effective prognostic indicator of distant metastasis risk to complement the molecular approaches for cancer risk prognosis.