Helwan University

Nanomaterials (NMs) have gained prominence in technological advancements due to their tunable physical, chemical and biological properties with enhanced performance over their bulk counterparts. NMs are categorized depending on their size, composition, shape, and origin. The ability to predict the unique properties of NMs increases the value of each classification. Due to increased growth of production of NMs and their industrial applications, issues relating to toxicity are inevitable. The aim of this review is to compare synthetic (engineered) and naturally occurring nanoparticles (NPs) and nanostructured materials (NSMs) to identify their nanoscale properties and to define the specific knowledge gaps related to the risk assessment of NPs and NSMs in the environment. The review presents an overview of the history and classifications of NMs and gives an overview of the various sources of NPs and NSMs, from natural to synthetic, and their toxic effects towards mammalian cells and tissue. Additionally, the types of toxic reactions associated with NPs and NSMs and the regulations implemented by different countries to reduce the associated risks are also discussed.

The principal limitations of the terms NAFLD and NASH are the reliance on exclusionary confounder terms and the use of potentially stigmatising language. This study set out to determine if content experts and patient advocates were in favor of a change in nomenclature and/or definition. A modified Delphi process was led by three large pan-national liver associations. The consensus was defined a priori as a supermajority (67%) vote. An independent committee of experts external to the nomenclature process made the final recommendation on the acronym and its diagnostic criteria. A total of 236 panelists from 56 countries participated in 4 online surveys and 2 hybrid meetings. Response rates across the 4 survey rounds were 87%, 83%, 83%, and 78%, respectively. Seventy-four percent of respondents felt that the current nomenclature was sufficiently flawed to consider a name change. The terms "nonalcoholic" and "fatty" were felt to be stigmatising by 61% and 66% of respondents, respectively. Steatotic liver disease was chosen as an overarching term to encompass the various aetiologies of steatosis. The term steatohepatitis was felt to be an important pathophysiological concept that should be retained. The name chosen to replace NAFLD was metabolic dysfunction-associated steatotic liver disease. There was consensus to change the definition to include the presence of at least 1 of 5 cardiometabolic risk factors. Those with no metabolic parameters and no known cause were deemed to have cryptogenic steatotic liver disease. A new category, outside pure metabolic dysfunction-associated steatotic liver disease, termed metabolic and alcohol related/associated liver disease (MetALD), was selected to describe those with metabolic dysfunction-associated steatotic liver disease, who consume greater amounts of alcohol per week (140-350 g/wk and 210-420 g/wk for females and males, respectively). The new nomenclature and diagnostic criteria are widely supported and nonstigmatising, and can improve awareness and patient identification.

The principal limitations of the terms NAFLD and NASH are the reliance on exclusionary confounder terms and the use of potentially stigmatising language. This study set out to determine if content experts and patient advocates were in favour of a change in nomenclature and/or definition. A modified Delphi process was led by three large pan-national liver associations. The consensus was defined a priori as a supermajority (67%) vote. An independent committee of experts external to the nomenclature process made the final recommendation on the acronym and its diagnostic criteria. A total of 236 panellists from 56 countries participated in 4 online surveys and 2 hybrid meetings. Response rates across the 4 survey rounds were 87%, 83%, 83%, and 78%, respectively. Seventy-four percent of respondents felt that the current nomenclature was sufficiently flawed to consider a name change. The terms "nonalcoholic" and "fatty" were felt to be stigmatising by 61% and 66% of respondents, respectively. Steatotic liver disease was chosen as an overarching term to encompass the various aetiologies of steatosis. The term steatohepatitis was felt to be an important pathophysiological concept that should be retained. The name chosen to replace NAFLD was metabolic dysfunction-associated steatotic liver disease (MASLD). There was consensus to change the definition to include the presence of at least 1 of 5 cardiometabolic risk factors. Those with no metabolic parameters and no known cause were deemed to have cryptogenic steatotic liver disease. A new category, outside pure metabolic dysfunction-associated steatotic liver disease, termed metabolic and alcohol related/associated liver disease (MetALD), was selected to describe those with metabolic dysfunction-associated steatotic liver disease, who consume greater amounts of alcohol per week (140-350 g/wk and 210-420 g/wk for females and males, respectively). The new nomenclature and diagnostic criteria are widely supported and non-stigmatising, and can improve awareness and patient identification.

The principal limitations of the terms NAFLD and NASH are the reliance on exclusionary confounder terms and the use of potentially stigmatising language. This study set out to determine if content experts and patient advocates were in favor of a change in nomenclature and/or definition. A modified Delphi process was led by three large pan-national liver associations. The consensus was defined a priori as a supermajority (67%) vote. An independent committee of experts external to the nomenclature process made the final recommendation on the acronym and its diagnostic criteria. A total of 236 panelists from 56 countries participated in 4 online surveys and 2 hybrid meetings. Response rates across the 4 survey rounds were 87%, 83%, 83%, and 78%, respectively. Seventy-four percent of respondents felt that the current nomenclature was sufficiently flawed to consider a name change. The terms "nonalcoholic" and "fatty" were felt to be stigmatising by 61% and 66% of respondents, respectively. Steatotic liver disease was chosen as an overarching term to encompass the various aetiologies of steatosis. The term steatohepatitis was felt to be an important pathophysiological concept that should be retained. The name chosen to replace NAFLD was metabolic dysfunction-associated steatotic liver disease. There was consensus to change the definition to include the presence of at least 1 of 5 cardiometabolic risk factors. Those with no metabolic parameters and no known cause were deemed to have cryptogenic steatotic liver disease. A new category, outside pure metabolic dysfunction-associated steatotic liver disease, termed metabolic and alcohol related/associated liver disease (MetALD), was selected to describe those with metabolic dysfunction-associated steatotic liver disease, who consume greater amounts of alcohol per week (140-350 g/wk and 210-420 g/wk for females and males, respectively). The new nomenclature and diagnostic criteria are widely supported and nonstigmatising, and can improve awareness and patient identification.

Brain tumor classification is a crucial task to evaluate the tumors and make a treatment decision according to their classes. There are many imaging techniques used to detect brain tumors. However, MRI is commonly used due to its superior image quality and the fact of relying on no ionizing radiation. Deep learning (DL) is a subfield of machine learning and recently showed a remarkable performance, especially in classification and segmentation problems. In this paper, a DL model based on a convolutional neural network is proposed to classify different brain tumor types using two publicly available datasets. The former one classifies tumors into (meningioma, glioma, and pituitary tumor). The other one differentiates between the three glioma grades (Grade II, Grade III, and Grade IV). The datasets include 233 and 73 patients with a total of 3064 and 516 images on T1-weighted contrast-enhanced images for the first and second datasets, respectively. The proposed network structure achieves a significant performance with the best overall accuracy of 96.13% and 98.7%, respectively, for the two studies. The results indicate the ability of the model for brain tumor multi-classification purposes.

Non-alcoholic fatty liver disease (NAFLD) is a potentially serious liver disease that affects approximately one-quarter of the global adult population, causing a substantial burden of ill health with wide-ranging social and economic implications. It is a multisystem disease and is considered the hepatic component of metabolic syndrome. Unlike other highly prevalent conditions, NAFLD has received little attention from the global public health community. Health system and public health responses to NAFLD have been weak and fragmented, and, despite its pervasiveness, NAFLD is largely unknown outside hepatology and gastroenterology. There is only a nascent global public health movement addressing NAFLD, and the disease is absent from nearly all national and international strategies and policies for non-communicable diseases, including obesity. In this global Delphi study, a multidisciplinary group of experts developed consensus statements and recommendations, which a larger group of collaborators reviewed over three rounds until consensus was achieved. The resulting consensus statements and recommendations address a broad range of topics - from epidemiology, awareness, care and treatment to public health policies and leadership - that have general relevance for policy-makers, health-care practitioners, civil society groups, research institutions and affected populations. These recommendations should provide a strong foundation for a comprehensive public health response to NAFLD.

Wireless sensor network (WSN) technologies are considered one of the key research areas in computer science and the healthcare application industries for improving the quality of life. The purpose of this paper is to provide a snapshot of current developments and future direction of research on wearable and implantable body area network systems for continuous monitoring of patients. This paper explains the important role of body sensor networks in medicine to minimize the need for caregivers and help the chronically ill and elderly people live an independent life, besides providing people with quality care. The paper provides several examples of state of the art technology together with the design considerations like unobtrusiveness, scalability, energy efficiency, security and also provides a comprehensive analysis of the various benefits and drawbacks of these systems. Although offering significant benefits, the field of wearable and implantable body sensor networks still faces major challenges and open research problems which are investigated and covered, along with some proposed solutions, in this paper.

Brain computer interface technology represents a highly growing field of research with application systems. Its contributions in medical fields range from prevention to neuronal rehabilitation for serious injuries. Mind reading and remote communication have their unique fingerprint in numerous fields such as educational, self-regulation, production, marketing, security as well as games and entertainment. It creates a mutual understanding between users and the surrounding systems. This paper shows the application areas that could benefit from brain waves in facilitating or achieving their goals. We also discuss major usability and technical challenges that face brain signals utilization in various components of BCI system. Different solutions that aim to limit and decrease their effects have also been reviewed.

These molecules or classes of natural substances are characterized by two phenyl rings at least and one or more hydroxyl substituents. This description comprehends a large number of heterogeneous compounds with reference to their complexity. Therefore, polyphenols can be simply classified into flavonoids and non-flavonoids, or be subdivided in many sub-classes depending on the number of phenol units within their molecular structure, substituent groups, and/or the linkage type between phenol units. Polyphenols are widely distributed in plant tissues where they mainly exist in form of glycosides or aglycones. The structural diversity of flavonoid molecules arises from variations in hydroxylation pattern and oxidation state resulting in a wide range of compounds: flavanols, anthocyanidins, anthocyanins, isoflavones, flavones, flavonols, flavanones, and flavanonols.

Optic disc (OD) detection is a main step while developing automated screening systems for diabetic retinopathy. We present in this paper a method to automatically detect the position of the OD in digital retinal fundus images. The method starts by normalizing luminosity and contrast through out the image using illumination equalization and adaptive histogram equalization methods respectively. The OD detection algorithm is based on matching the expected directional pattern of the retinal blood vessels. Hence, a simple matched filter is proposed to roughly match the direction of the vessels at the OD vicinity. The retinal vessels are segmented using a simple and standard 2-D Gaussian matched filter. Consequently, a vessels direction map of the segmented retinal vessels is obtained using the same segmentation algorithm. The segmented vessels are then thinned, and filtered using local intensity, to represent finally the OD-center candidates. The difference between the proposed matched filter resized into four different sizes, and the vessels' directions at the surrounding area of each of the OD-center candidates is measured. The minimum difference provides an estimate of the OD-center coordinates. The proposed method was evaluated using a subset of the STARE project's dataset, containing 81 fundus images of both normal and diseased retinas, and initially used by literature OD detection methods. The OD-center was detected correctly in 80 out of the 81 images (98.77%). In addition, the OD-center was detected correctly in all of the 40 images (100%) using the publicly available DRIVE dataset.

microbes and plants for the green preparation of metal and metal oxide nanoparticles and provides insights into the molecular aspects of the synthesis mechanisms and biomedical applications. The use of agriculture waste as a potential bioresource for nanoparticle synthesis and biomedical applications of biosynthesized nanoparticles is also discussed.

The increasing demand for orthopedic implants has driven the search for materials that combine strength, biocompatibility, and long lifetime. Compared to stainless steel and Co-Cr-based alloys, titanium (Ti) and its alloys are favored for biomedical implants because of their high strength, corrosion resistance, and biocompatibility. This comprehensive review delivers a wide overview of the field of titanium-based biomaterials for orthopedic implants applications, focusing on their types, mechanical and chemical resistance, surface modifications, innovations in fabrication techniques, titanium matrix composites, and machine learning advancements. Titanium alloys of different crystalline phases, including α, near-α, (α + β), β, and shape memory alloys, offer diverse options for orthopedic applications. Strengthening properties, wear, fatigue, and corrosion resistance are crucial factors influencing the performance and reliability of titanium implants. Moreover, this review discussed the challenges to titanium-based biomaterial durability through surface modifications to enhance their biofunction, wear resistance, corrosion resistance, and antibacterial properties. Recent developments in fabrication techniques for titanium-based biomaterials are also discussed. Eventually, this review investigated how machine learning (ML) revolutionized titanium orthopedic implants by providing insights into the behavior of new alloys, aiding in manufacturing optimization, allowing for real-time quality control, and advancing the development of personalized, biocompatible, and reliable implants.

Nanomaterials are becoming important materials in several fields and industries thanks to their very reduced size and shape-related features. Scientists think that nanoparticles and nanostructured materials originated during the Big Bang process from meteorites leading to the formation of the universe and Earth. Since 1990, the term nanotechnology became very popular due to advances in imaging technologies that paved the way to specific industrial applications. Currently, nanoparticles and nanostructured materials are synthesized on a large scale and are indispensable for many industries. This fact fosters and supports research in biochemistry, biophysics, and biochemical engineering applications. Recently, nanotechnology has been combined with other sciences to fabricate new forms of nanomaterials that could be used, for instance, for diagnostic tools, drug delivery systems, energy generation/storage, environmental remediation as well as agriculture and food processing. In contrast with traditional materials, specific features can be integrated into nanoparticles, nanostructures, and nanosystems by simply modifying their scale, shape, and composition. This article first summarizes the history of nanomaterials and nanotechnology. Followed by the progress that led to improved synthesis processes to produce different nanoparticles and nanostructures characterized by specific features. The content finally presents various origins and sources of nanomaterials, synthesis strategies, their toxicity, risks, regulations, and self-aggregation.

In this paper, we will review both past and recent progresses in the generation, detection and application of intense terahertz (THz) radiation. We will restrict the review to laser based intense few-cycle THz sources, and thus will not include sources such as synchrotron-based or narrowband sources. We will first review the various methods used for generating intense THz radiation, including photoconductive antennas (PCAs), optical rectification sources (especially the tilted-pulse-front lithium niobate source and the DAST source, but also those using other crystals), air plasma THz sources and relativistic laser–plasma sources. Next, we will give a brief introduction on the common methods for coherent THz detection techniques (namely the PCA technique and the electro-optic sampling), and point out the limitations of these techniques for measuring intense THz radiation. We will then review three techniques that are highly suited for detecting intense THz radiation, namely the air breakdown coherent detection technique, various single-shot THz detection techniques, and the spectral-domain interferometry technique. Finally, we will give an overview of the various applications that have been made possible with such intense THz sources, including nonlinear THz spectroscopy of condensed matter (optical-pump/THz-probe, THz-pump/THz-probe, THz-pump/optical-probe), nonlinear THz optics, resonant and non-resonant control of material (such as switching of superconductivity, magnetic and polarization switching) and controlling the nonlinear response of metamaterials. We will also provide a short perspective on the future of intense THz sources and their applications.

BACKGROUND: Emerging data indicate that gut-derived endotoxin may contribute to low-grade systemic inflammation in insulin resistant states. This study aimed to examine the importance of serum endotoxin and inflammatory markers in non-alcoholic fatty liver disease (NAFLD) patients, with and without type 2 diabetes mellitus (T2DM), and to explore the effect of treatment with a lipase inhibitor, Orlistat, on their inflammatory status. METHODS: Fasted serum from 155 patients with biopsy proven NAFLD and 23 control subjects were analysed for endotoxin, soluble CD14 (sCD14), soluble tumour necrosis factor receptor II (sTNFRII) and various metabolic parameters. A subgroup of NAFLD patients were re-assessed 6 and 12 months after treatment with diet alone (n = 6) or diet plus Orlistat (n = 8). RESULTS: Endotoxin levels were significantly higher in patients with NAFLD compared with controls (NAFLD: 10.6(7.8, 14.8) EU/mL; controls: 3.9(3.2, 5.2) EU/mL, p < 0.001); NAFLD alone produced comparable endotoxin levels to T2DM (NAFLD: T2DM: 10.6(5.6, 14.2) EU/mL; non-diabetic: 10.6(8.5, 15.2) EU/mL), whilst a significant correlation between insulin resistance and serum endotoxin was observed (r = 0.27, p = 0.008). Both sCD14 (p < 0.01) and sTNFRII (p < 0.001) increased with severity of fibrosis. A positive correlation was also noted between sTNFRII and sCD14 in the NAFLD subjects (r = 0.29, p = 0.004).Sub-cohort treatment with Orlistat in patients with NAFLD showed significant decreases in ALT (p = 0.006), weight (p = 0.005) and endotoxin (p = 0.004) compared with the NAFLD, non-Orlistat treated control cohort at 6 and 12 months post therapy, respectively. CONCLUSIONS: Endotoxin levels were considerably increased in NAFLD patients, with marked increases noted in early stage fibrosis compared with controls. These results suggest elevated endotoxin may serve as an early indicator of potential liver damage, perhaps negating the need for invasive liver biopsy. As endotoxin may promote insulin resistance and inflammation, interventions aimed at reducing endotoxin levels in NAFLD patients may prove beneficial in reducing inflammatory burden.

CE has been alive for over two decades now, yet its sensitivity is still regarded as being inferior to that of more traditional methods of separation such as HPLC. As such, it is unsurprising that overcoming this issue still generates much scientific interest. This review continues to update this series of reviews, first published in Electrophoresis in 2007, with updates published in 2009 and 2011 and covers material published through to June 2012. It includes developments in the field of stacking, covering all methods from field amplified sample stacking and large volume sample stacking, through to isotachophoresis, dynamic pH junction and sweeping. Attention is also given to online or inline extraction methods that have been used for electrophoresis.

The worldwide pandemic of COVID-19 has forced higher education institutions to shift from face-to-face to online education. However, many public institutions, especially in developing countries, often do not have access to formal online learning management systems (LMS) for facilitating communication with students and/or among faculty members. This research empirically examines the extent to which social media sites are adopted by faculty members and students for sustaining formal, i.e., sole and official tools, academic communication. For this purpose, online questionnaire surveys, supplemented with in-depth interviews, were undertaken with both faculty members and students. The results showed that students’ personal usage of social media has promoted its effective usage for sustaining formal teaching and learning. However, significant differences were found between faculty members and students regarding social media usage for student support and building an online community. Students used social media for building an online community and supporting each other, whereas faculty members were focused on teaching and learning exclusively. The results confirm that proper usage of social media could promote a new era of social learning, social presence and an alternative platform to foster online learning. Research implications for higher education policymakers, especially in developing countries, and scholars are discussed.

<h3>Objective:</h3> Ki-67 plays an important function in cell division, but its exact role is still unknown. Moreover, few works regarding its overall function were published. The present study evaluated the clinical significance of Ki-67 index as a prognostic marker and predictor of recurrence in different molecular subtypes of breast cancer. The relationship of Ki-67 index with different clinicopathological factors was also analyzed. <h3>Methods:</h3> Ki-67 index was measured in 107 cases of primary breast cancer from 2010-2012. These patients were evaluated for estrogen receptor, progesterone receptor, and HER2. Ki-67 was divided according to percentage levels: &lt; 15% and &gt; 15%. Follow-up ranged from 32 months up to 6 years. <h3>Results:</h3> Approximately 44, 23, 15, and 25 cases were grouped as luminal A, luminal B, HER2 subtype, and triple-negative (TN), respectively. No luminal A patients showed Ki-67 level higher than 15%, and their recurrence was 20%. In luminal B group, Ki-67 level higher than 15% was observed in 69% of patients, and recurrence was 39%. In HER2 subtype, Ki-67 was higher than 15% in 34% of cases, and recurrence was 40%. In triple-negative cases, Ki-67 was higher than 15% in 60% of cases, and recurrence was detected in 32% of patients. Patients with Ki-67 less than 15% displayed better overall survival than those with Ki-67 higher than 15% (<i>P</i> = 0.01). Patients with Ki-67 higher than 15% exhibited higher incidence of metastasis and recurrence than those with Ki-67 less than 15% (<i>P</i> = 0.000). <h3>Conclusions:</h3> Ki-67 may be considered as a valuable biomarker in breast cancer patients.

Objective: To translate and evaluate the psychometric properties of an Arabic-language version of the Depression Anxiety Stress Scales (DASS). Method: The items were translated, back translated, refined, and tested in an Australian immigrant sample ( N = 220). Results: Confirmatory factor analysis showed that the Arabic DASS discriminates between depression, anxiety, and stress but to a lesser degree than the English DASS. The factor loadings for all 42 items were comparable to those of the English DASS, indicating that the items had been appropriately translated and adapted. Analysis of exploratory items suggested by Arabic-speaking mental health professionals failed to reveal any new items that were both psychometrically adequate and theoretically coherent. Analysis of a bilingual sample ( N = 24) indicated that the English norms was appropriate for the Arabic DASS. Conclusion: The results support the universality of depression, anxiety, and stress across cultures and provide initial support for the psychometric properties of the Arabic DASS.

Unique features of nanofibers provide enormous potential in the field of biomedical and healthcare applications. Many studies have proven the extreme potential of nanofibers in front of current challenges in the medical and healthcare field. This review highlights the nanofiber technologies, unique properties, fabrication techniques (i.e., physical, chemical, and biological methods), and emerging applications in biomedical and healthcare fields. It summarizes the recent researches on nanofibers for drug delivery systems and controlled drug release, tissue-engineered scaffolds, dressings for wound healing, biosensors, biomedical devices, medical implants, skin care, as well as air, water, and blood purification systems. Attention is given to different types of fibers (e.g., mesoporous, hollow, core-shell nanofibers) fabricated from various materials and their potential biomedical applications.