1,691 research outputs found
Antibacterial biohybrid nanofibers for wound dressings
Globally, chronic wounds impose a notable burden to patients and healthcare systems. Such skin wounds are readily subjected to bacteria that provoke inflammation and hence challenge the healing process. Furthermore, bacteria induce infection impeding re-epithelialization and collagen synthesis. With an estimated global market of 20.4 billion by 2021, skin wound dressings are a crucial segment of the wound care industry. As an advanced class of bioactive wound dressing materials, natural polymeric nanofibers loaded with antibacterial agents, e.g. antimicrobial nanoparticles/ions, nature-derived compounds and biofunctional agents, have shown a remarkable potential for replacement of their classic counterparts. Also, given the expanding concern regarding antibiotic resistant bacteria, such biohybrid nanofibrous wound dressings can outperform classical drug delivery systems. Here, an updated overview of the most recent (since 2015) developments of antibacterial biopolymeric nanofibrous wound dressings is presented. In this review, while discussing about the antibacterial efficiency of such systems, the prospects and challenges are highlighted to draw a roadmap for further progresses in this area.</p
High-frequency Oscillations in Small Magnetic Elements Observed with Sunrise/SuFI
We characterize waves in small magnetic elements and investigate their
propagation in the lower solar atmosphere from observations at high spatial and
temporal resolution. We use the wavelet transform to analyze oscillations of
both horizontal displacement and intensity in magnetic bright points found in
the 300 nm and the Ca II H 396.8 nm passbands of the filter imager on board the
Sunrise balloon-borne solar observatory. Phase differences between the
oscillations at the two atmospheric layers corresponding to the two passbands
reveal upward propagating waves at high frequencies (up to 30 mHz). Weak
signatures of standing as well as downward propagating waves are also obtained.
Both compressible and incompressible (kink) waves are found in the small-scale
magnetic features. The two types of waves have different, though overlapping,
period distributions. Two independent estimates give a height difference of
approximately 450+-100 km between the two atmospheric layers sampled by the
employed spectral bands. This value, together with the determined short travel
times of the transverse and longitudinal waves provide us with phase speeds of
29+-2 km/s and 31+-2 km/s, respectively. We speculate that these phase speeds
may not reflect the true propagation speeds of the waves. Thus, effects such as
the refraction of fast longitudinal waves may contribute to an overestimate of
the phase speed.Comment: 14 pages, 7 figure
Nature-Derived and Synthetic Additives to poly(É›-Caprolactone) Nanofibrous Systems for Biomedicine; an Updated Overview
As a low cost, biocompatible, and bioresorbable synthetic polymer, poly (É›-caprolactone) (PCL) is widely used for different biomedical applications including drug delivery, wound dressing, and tissue engineering. An extensive range of in vitro and in vivo tests has proven the favourable applicability of PCL in biomedicine, bringing about the FDA approval for a plethora of PCL made medical or drug delivery systems. This popular polymer, widely researched since the 1970s, can be readily processed through various techniques such as 3D printing and electrospinning to create biomimetic and customized medical products. However, low mechanical strength, insufficient number of cellular recognition sites, poor bioactivity, and hydrophobicity are main shortcomings of PCL limiting its broader use for biomedical applications. To maintain and benefit from the high potential of PCL, yet addressing its physicochemical and biological challenges, blending with nature-derived (bio)polymers and incorporation of nanofillers have been extensively investigated. Here, we discuss novel additives that have been meant for enhancement of PCL nanofiber properties and thus for further extension of the PCL nanofiber application domain. The most recent researches (since 2017) have been covered and an updated overview about hybrid PCL nanofibers is presented with focus on those including nature-derived additives, e.g., polysaccharides and proteins, and synthetic additives, e.g., inorganic and carbon nanomaterials
Emerging technologies for the non-invasive characterization of physical-mechanical properties of tablets
The density, porosity, breaking force, viscoelastic properties, and the presence or absence of any structural defects or irregularities are important physical-mechanical quality attributes of popular solid dosage forms like tablets. The irregularities associated with these attributes may influence the drug product functionality. Thus, an accurate and efficient characterization of these properties is critical for successful development and manufacturing of a robust tablets. These properties are mainly analyzed and monitored with traditional pharmacopeial and non-pharmacopeial methods. Such methods are associated with several challenges such as lack of spatial resolution, efficiency, or sample-sparing attributes. Recent advances in technology, design, instrumentation, and software have led to the emergence of newer techniques for non-invasive characterization of physical-mechanical properties of tablets. These techniques include near infrared spectroscopy, Raman spectroscopy, X-ray microtomography, nuclear magnetic resonance (NMR) imaging, terahertz pulsed imaging, laser-induced breakdown spectroscopy, and various acoustic- and thermal-based techniques. Such state-of-the-art techniques are currently applied at various stages of development and manufacturing of tablets at industrial scale. Each technique has specific advantages or challenges with respect to operational efficiency and cost, compared to traditional analytical methods. Currently, most of these techniques are used as secondary analytical tools to support the traditional methods in characterizing or monitoring tablet quality attributes. Therefore, further development in the instrumentation and software, and studies on the applications are necessary for their adoption in routine analysis and monitoring of tablet physical-mechanical properties
Prevention in Healthcare: An Explainable AI Approach
Intrusion prevention is a critical aspect of maintaining the security of healthcare systems, especially in the context of sensitive patient data. Explainable AI can provide a way to improve the effectiveness of intrusion prevention by using machine learning algorithms to detect and prevent security breaches in healthcare systems. This approach not only helps ensure the confidentiality, integrity, and availability of patient data but also supports regulatory compliance. By providing clear and interpretable explanations for its decisions, explainable AI can enable healthcare professionals to understand the reasoning behind the intrusion detection system's alerts and take appropriate action. This paper explores the application of explainable AI for intrusion prevention in healthcare and its potential benefits for maintaining the security of healthcare systems
A Machine Learning Model for the Identification of the Holy Quran Reciter Utilizing K-Nearest Neighbor and Artificial Neural Networks
The method of identification of the Holy Quran reciter, which is entered on the various features of the acoustic wave, is referred to as the Holy Quran Reciter Identification. The Muslim communitys Holy Book is the Holy Quran. Listening to or reading the Holy Quran is one of the obligatory activities for Muslims. This research proposes a machine learning model for identifying the Holy Quran reciter using a machine learning language. Here, the presented system comprises the essential phases for a voice recognition system encompassing the processes of classification, extraction of features, preprocessing, and data acquisition. Moreover, the voices of ten known reciters are framed as a dataset in this research. The reciters are leaders of prayers in the Holy masjids of Madinah and Makkah. The analysis of the audio dataset is performed using the mel frequency cepstral coefficients (MFCC). The artificial neural network (ANN) and the k-nearest neighbor (KNN) classifiers are employed for classification. The pitch is utilized as features employed to train the KNN and ANN classifiers. The proposed system is validated using two chapters chosen from the Holy Quran. The results revealed an excellent level of accuracy. With the help of the ANN classifier, the proposed system offered 98.5% accuracy for chapter 7 and 97.2% accuracy for chapter 32. On the other hand, while utilizing KNN, the accuracy for chapter 7 is 97.02% and for chapter 32 is 96.07%. Then, the system’s performance is compared with the utilization of support vector machines (SVM) in recognition of Quranic voice reciter. The comparison results revealed that ANN is a better machine learning algorithm for voice recognition when compared to SVM
Bioactive glass-based fibrous wound dressings
Since the discovery of silicate bioactive glass (BG) by Larry Hench in 1969, different classes of BGs have been researched over decades mainly for bone regeneration. More recently, validating the beneficial influence of BGs with tailored compositions on angiogenesis, immunogenicity and bacterial infection, the applicability of BGs has been extended to soft tissue repair and wound healing. Particularly, fibrous wound dressings comprising BG particle reinforced polymer nanofibers and cotton-candy-like BG fibers have been proven to be successful for wound healing applications. Such fibrous dressing materials imitate the physical structure of skin’s extracellular matrix and release biologically active ions e.g. regenerative, pro-angiogenic and antibacterial ions, e.g. borate, copper, zinc, etc., that can provoke cellular activities to regenerate the lost skin tissue and to induce new vessels formation, while keeping an anti-infection environment. In the current review, we discuss different BG fibrous materials meant for wound healing applications and cover the relevant literature in the past decade. The production methods for BG-containing fibers are explained and as fibrous wound dressing materials, their wound healing and bactericidal mechanisms, depending on the ions they release, are discussed. The present gaps in this research area are highlighted and new strategies to address them are suggested
Bio-cementation of sandy soil using microbially induced carbonate precipitation for marine environments
This study proposes and describes a novel approach for cementing sandy soils in marine environments by modifying the promising technique of microbially induced carbonate precipitation (MICP). In contrast to the usual MICP technique described in the literature, the method proposed herein relies on the calcium ions dissolved in seawater as the sole source of calcium for calcite formation. This proposed method involves flushing high-salinity-tolerant, urease-active bacteria followed by a mixture of urea and seawater through a porous sandy soil, leading to bacterial carbonate release from the urease reaction and precipitation of insoluble and semi-soluble carbonate salts including calcium carbonate and magnesium carbonate trihydrate. This precipitation method resulted in a physical stabilisation of sand that reached an unconfined compressive strength of up to 300 kPa, which is about two-fold higher (with same amount of crystals produced) than that of the MICP treatment in which highly concentrated calcium and urea solutions are used. Permeability was retained at about 30% for all MICP-treated samples, suggesting good drainage ability. This new exploration of MICP technology provides a high potential for using bio-cementation in marine environments, for applications such as mitigation of submarine sediment liquefaction and prevention of beach sand erosion and cliffs scouring
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