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Mir-21 and Mir-125b as theranostic biomarkers for epithelial ovarian cancer in Tunisian women
No full textBackground: Ovarian cancer (OC) is the third most common cancer in women and the leading cause of death associated with gynecologic tumors. Because this disease is asymptomatic in the early stages, most patients are not diagnosed until the late stages. This highlights the need for the development of diagnostic biomarkers. MicroRNAs (miRNAs), small non-coding RNAs, are currently being explored as potential biomarkers for the early detection of various malignancies in humans. However, their expression and diagnostic value in OC have not been well studied. Materials and Methods: the plasma levels of miR-21, miR-200a, miR-200b, miR-200c, miR-205 and miR-125b were determined in epithelial ovarian cancer (EOC) patients and healthy controls by Reverse Transcription Quantitative Realtime Polymerase Chain Reaction (RT-qPCR). The expression levels of the deregulated microRNAs were analysed according to clinical characteristics. Results: It was found that miR-21 and miR-125b were upregulated in EOC compared with healthy controls. Moreover, decreased miR-125b was associated with resistance to platinum-based chemotherapy. Conclusions: Our data suggest that miR-21 and miR-125b in plasma may serve as potential circulating biomarkers for the early detection of EOC. MiR-125b may also be useful for predicting chemosensitivity in EOC patients. © 2023 Habel A et al
Leveraging Adversarial Samples for Enhanced Classification of Malicious and Evasive PDF Files
No full textThe Portable Document Format (PDF) is considered one of the most popular formats due to its flexibility and portability across platforms. Although people have used machine learning techniques to detect malware in PDF files, the problem with these models is their weak resistance against evasion attacks, which constitutes a major security threat. The goal of this study is to introduce three machine learning-based systems that enhance malware detection in the presence of evasion attacks by substantially relying on evasive data to train malware and evasion detection models. To evaluate the robustness of the proposed systems, we used two testing datasets, a real dataset containing around 100,000 PDF samples and an evasive dataset containing 500,000 samples that we generated. We compared the results of the proposed systems to a baseline model that was not adversarially trained. When tested against the evasive dataset, the proposed systems provided an increase of around 80% in the f1-score compared to the baseline. This proves the value of the proposed approaches towards the ability to deal with evasive attacks. © 2023 by the authors
Preparation and Characterization of ZnFe2O4/Mn2O3 Nanocatalysts for the Degradation of Nitrobenzene
Get PDFThis study reports the synthesis of pure ZnFe2O4, pure Mn2O3 nanoparticles and ZnFe2O4/Mn2O3 nanocomposites by a simple coprecipitation method. The prepared samples were characterized by X-ray diffraction, transmission electron microscopy, N2 adsorption/desorption, and photoluminescence spectroscopy (PL). The prepared samples were further applied as photocatalysts for UV-exposed degradation of nitrobenzene at 254 nm. The photocatalytic performance showed that ZnFe2O4/Mn2O3 nanocomposites with various Mn2O3 content exhibited a higher activity compared to that of pure ZnFe2O4 and Mn2O3. Furthermore, among the prepared nanocomposites, the best photocatalytic performance was exhibited by 0.9ZnFe2O4/0.1Mn2O3 nanocomposites. The improved photocatalytic activity was mainly attributed to the separation of electron–hole pairs, as verified by PL analysis. To achieve the highest degradation rate, the photodegradation reaction was carried out in the presence of various catalyst doses, in acidic, neutral, and basic mediums and at different reaction temperatures. Finally, the compounds produced from the photodegradation reaction were determined by applying the optimal experimental conditions. © 2023, The Tunisian Chemical Society and Springer Nature Switzerland AG
Re-conceptualizing medical education in the post-COVID era
Get PDFPurpose: The COVID-19 pandemic has forced changes in the delivery of medical education. We aimed to explore these changes and determine whether they will impact the future of medical education in any way. Methods: We invited leaders in medical education from all accessible US-based medical schools to participate in an online individual semi-structured interview. Results: Representatives of 16 medical schools participated. They commented on the adequacy of online education for knowledge transfer, and the logistical advantages it offered, but decried its negative influence on social learning, interpersonal relationships and professional development of students, and its ineffectiveness for clinical education. Most participants indicated that they would maintain online learning for didactic purposes in the context of flipped classrooms but that a return to in-person education was essential for most other educational goals. Novel content will be introduced, especially in telemedicine and social medicine, and the students’ roles and responsibilities in patient care and in curricular development may evolve in the future. Conclusions: This study is the first to document the practical steps that will be adopted by US medical schools in delivering medical education, which were prompted and reinforced by their experience during the COVID-19 pandemic. © 2023 Informa UK Limited, trading as Taylor & Francis Group
Deadline-constrained RSU-To-vehicle task offloading scheme for vehicular fog networks
Get PDFIn Vehicular Fog Computing (VFC), the RSU-To-Vehicle (R2V) task offloading process is highly affected by undesirable yet sometimes inevitable events (e.g., buffer exhaustion, task HoL blocking and deadline expiry), the occurrence of which will notably alter the RSU's performance in terms of crucial Quality-of-Service (QoS) metrics such as the average system response time, the blocking and deadline expiry probabilities. This article proposes a novel R2V Deadline-Constrained Task Offload (R2V-DCTO) scheduling scheme with the objective of improving the RSU's performance in terms of the above-mentioned metrics; hence, filling an important literature gap. For this purpose, a stochastic modelling framework is established to capture the RSU's functional dynamics and assess its performance as it operates under R2V-DCTO. Extensive simulations are conducted to confirm the model's validity and accuracy and then compare R2V-DCTO's performance to that of the often adopted FIFO scheme. Results indicate that, on average, R2V-DCTO outperforms FIFO by 33.4% in terms of the probability of deadline mismatch and by 83.3% in terms of mean system response time; those being critical QoS performance metrics. © 1967-2012 IEEE
Predicting missed delirium diagnosis in a tertiary care center: the Consultation-Liaison at the American University of Beirut (CLAUB) analysis
Get PDFBackground: Delirium is a very common occurrence in hospital settings and is frequently missed by the primary care team. It remains, however, poorly studied in the Middle East despite abundant global reports. In this study, we aimed to estimate the prevalence of missed delirium diagnosis in a tertiary care center in Lebanon and investigate potential predictors of this missed diagnosis. This was a retrospective study of adult patients admitted to the American University of Beirut Medical Center between March 2019 and December 2019 and assessed by the consultation-liaison psychiatry (CLP) team. The primary endpoint was the rate of missed delirium diagnosis among CLP consultations. Relevant statistical tests were performed to assess the association between the missed diagnosis of delirium and characteristics of patients. Results: Five hundred fifty-three patients were included with a mean age of 69.19 ± 14.79 years. 86.13% of the patients received a delirium diagnosis by the CLP team that had been missed prior to the CLP referral. A missed delirium diagnosis was more likely to be found in patients with a history of depression (OR = 24, p < 0.01) and a longer hospital stay [in days] (OR = 1.04, p = 0.04). Conclusion: The alarmingly high prevalence of missed delirium diagnosis is the first evidence of its kind in the Middle East. This urges the implementation of educational interventions to increase the detection of delirium among healthcare providers and ultimately improve patient outcomes. © 2023, The Author(s)
Nerve growth factor and burn wound healing: Update of molecular interactions with skin cells
Get PDFBurn wound healing is a very intricate and complex process that conventionally includes three interrelated and overlapping stages of hemostasis/inflammation, proliferation and remodeling. This review aims to explore the molecular interactions of NGF with the most prominent cell types in the skin and their respective secretory products during wound healing, particularly burn wound healing. Different types of cells such as, nerve cells, endothelial cells, mast cells, macrophages, neutrophils, keratinocytes and fibroblasts all come into play through a plethora of cytokines and growth factors including nerve growth factor (NGF). NGF is a pleiotropic molecule that exerts its effects on all the aforementioned cells using two types of receptors (TrkA and p75) and affects wound healing by decreasing healing time and improving the quality of the scar. Both receptors mediate cellular proliferation, survival and apoptosis through complex signaling molecules. During the inflammatory phase, macrophages and mast cells secrete ample cytokines and growth factors, including NGF, which participate in the inflammatory reaction and induction of other cells targeting a homeostatic state. The proliferative phase follows, and NGF promotes angiogenesis through VEGF and FGF expression in endothelial cells. NGF also stimulates keratinocyte proliferation and neurite extension through the TrkA-PI3K/Akt pathway. Other molecules such as TGF-β1, IL-1β and TNF-α increase NGF expression in fibroblasts through dynamic interactions with Smads and MAPK molecules. Stimulated fibroblasts induce new collagen production to form the granulation tissue. In the remodeling phase, NGF regulates fibroblasts and induces their differentiation into myofibroblasts ultimately leading to wound contracture. In addition, NGF stimulates melanocytes and enhances hair growth and pigmentation. Such data depict the mechanisms of action of NGF implicated in the various stages of the healing process and support its applicability as a new targeted therapeutic molecule effective in burn wound healing but with some limitations. © 2022 Elsevier Ltd and International Society of Burns Injurie
Vision-based Autonomous Navigation of UAVs
No full textAutonomous Drone Racing (ADR) has recently become the going-to-the-moon milestone for many roboticists. A challenging problem that advances the development of vision-based perception and navigation algorithms to perform fast, agile maneuvers while working on constrained onboard computing resources and dealing with imperfect sensing of the Unmanned Aerial Vehicles (UAVs). Due to such constraints, traditional navigation methods of map-localize-plan are infeasible. However, mapless navigation algorithms using Machine Learning approaches are showing promising results. In this thesis, we present an approach for vision-based navigation for quadrotors in an autonomous drone racing configuration. We propose the use of short-trajectory segments as control commands inferred directly from a deep-learning model and tracked by a high-level controller in a receding-horizon fashion. The direct use of short-trajectory segments eliminates the role of a path-planning module, thus, reducing the overall latency of the system, and as a result, allowing higher flight speeds. Furthermore, short-trajectory segments permit the use of deeper neural network models thanks to their relaxed update rate, compared with low-level commands, such as thrust and angular-body rates, that require high and fixed update rates. In addition, we train our policy network to predict short-trajectory segments that jointly traverse a racing gate and maintain it in the field of view of the camera. Keeping the racing
gate in the camera’s field of view increases the accuracy of future predictions while permitting more accurate and robust state estimation. We compare the performance of our proposed system against one of the state-of-the-art methods in simulation. Our system flies at nearly double the speed on average reaching speeds up to around 4 m/s while achieving a comparable successful traversing rate (91% compared with 92% for the baseline)
ENHANCEMENT OF THERMOMECHANICAL PROPERTIES OF EPOXY COMPOSITE SYSTEM REINFORCED USING GRAPHITIC CARBON NITRIDE WITH VARIOUS MORPHOLOGIES
No full textTo address the expanding need for improved polymer composites with prospective applications in a wide range of industries, research on polymer matrix improvement utilizing a carbon-based nanomaterial as the high potential filler has drawn great attention. The most stable allotrope of carbon nitrides, graphitic carbon nitride (g-C3N4), is a viable contender in many domains because of its electron-rich characteristics, basic surface functions, and hydrogen bond motifs. The primary goal of this study is to highlight the importance of the different forms of g-C3N4 as a reinforcing material in polymer composites, particularly epoxy resin, by examining the influence of filler concentration and morphology on the mechanical properties of the composite. In this study, g-C3N4 was synthesized in bulk as well as in the form of nanotubes and nanosheets. The objectives of this study are to investigate the effect of different concentrations of G-C3N4: bulk, nanotubes and nanosheets filler on the mechanical properties of epoxy composites. To better understand the effects of g-C3N4 morphology and particle size of the physical and chemical properties of epoxy resin the following characterization techniques scanning electron microscope (SEM), dynamic light scattering (DLS), thermogravimetric analysis (TGA) and fourier-transform infrared spectroscopy (FTIR) were used. An enhancement in the thermal breakdown reached 600 °C due to the strength of the formed covalent bonds between C and N that was also seen in FTIR results.
To assess the mechanical properties, a universal testing machine (UTM) is used to measure the tensile properties and calculate the fracture toughness. SEM is used to examine the morphology of the crack in the samples. The results showed that mechanical properties were optimum when the bulk graphitic carbon nitride was used as a filler with 0.5 wt %. The tensile strength of the resulting epoxy composite improved by 14 %. The geometries of cracks that developed in epoxy composite specimens during tensile testing were examined using SEM. The fracture surface's SEM micrographs revealed a modification in morphology from brittle to rough, indicating an increase in the composites' toughness. TGA showed that the addition of g-C3N4 did not affect the degradation temperature, however dynamic mechanical analysis showed a good improvement of material’s glass transition temperature of up to 17%.
More research is required on how to enhance the interaction between graphitic carbon nitride materials and the epoxy matrix as well as the orientation of the filler in epoxy, either by surface modification or by a curing agent that aids in strengthening the formation of epoxy composites
EXAMINING THE IMPACT OF RURAL-URBAN YOUTH MIGRATION ON SMALLHOLDER FARMERS' DECISIONS: A CASE STUDY OF MATHASKA COMMUNITY, PORT LOKO DISTRICT, SIERRA LEONE
Get PDFRural-urban youth migration is a growing phenomenon in many developing countries, and its impact on smallholder farmers' decisions is a critical issue that policymakers and development practitioners need to address. This study focuses on examining the impact of rural-urban youth migration on smallholder farmers' decisions: A case study of Mathaska community, Port Loko district, Sierra Leone. A qualitative methods approach was used to gather data for this study. The research design included a case study of the Mathaska community, involving interviews and focus group discussions with 80 participants. Purposive sampling techniques were employed to select study participants, and the data was analyzed using descriptive statistics and thematic analysis.
The results revealed that the majority of farming household heads (52.5%) were females, and nearly all respondents (97.5%) reported having migrants within their households. The analysis demonstrated that the size of the household farm and the number of migrants in the household significantly influenced smallholder farmers' decisions regarding land use, agricultural practices, and crop choices. Additionally, the study highlighted the role of education and employment as motivating factors for youth migration in the Mathaska community. Importantly, the study concluded that remittances have a significant impact on smallholder farmers' livelihoods and agricultural activities. Remittances play a crucial role in meeting household expenses, purchasing farm inputs, supporting farm labour, and investing in education, healthcare, and small business ventures.
These findings provide valuable insights for policymakers, practitioners, and researchers to develop strategies that promote sustainable agriculture and address the challenges associated with rural-urban youth migration and evolving agricultural practices. Furthermore, the study lays the foundation for further research and policy development in the field of sustainable agriculture and rural development