Search results for: personalized therapeutics

Authors: Sabah Mohammed, Jinan Fiaidhi, Darien Sawyer

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Data integration of health through connected services can save lives in the event of a medical emergency or provide efficient and effective interventions for the benefit of the patients through the integration of bedside and bench side clinical research. Such integration will support all wind of change in healthcare by being predictive, pre-emptive, personalized, problem-oriented and participatory. Prototyping a healthcare system that enables data integration has been a big challenge for healthcare for a long time. However, an innovative solution started to emerge by focusing on problem lists where everything can connect the problem list forming a growing graph. This notion was introduced by Dr. Lawrence Weed in early 70’s, but the enabling technologies weren’t mature enough to provide a successful implementation prototype. In this article, we are describing our efforts in prototyping Dr. Lawrence Weed's problem-oriented medical record (POMR) and his patient case schema (SOAP) to shape a prototype for connected health. For this, we are using the TypeGraphQL API and our enterprise-based QL4POMR to describe a Web-Based gateway for healthcare services connectivity. Our prototype has reported success in connecting to the HL7 FHIR medical record and the OpenTarget biomedical repositories.

Keywords: connected health, problem-oriented healthcare record, SOAP, QL4POMR, typegraphQL

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Authors: Lamis Naddaf, Yuval Tabach

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We identified missense genetic variants with the potential to enhance resistance against cancer. Such a field has not been widely explored as researchers tend to investigate the mutations that cause diseases, in response to the suffering of patients, rather than those mutations that protect from them. In conjunction with the genomic revolution and the advances in genetic engineering and synthetic biology, identifying the protective variants will increase the power of genotype-phenotype predictions and have significant implications for improved risk estimation, diagnostics, prognosis, and even personalized therapy and drug discovery. To approach our goal, we systematically investigated the sites of the coding genomes and selected the alleles that showed a correlation with the species’ cancer resistance. Interestingly, we found several amino acids that are more generally preferred (like the Proline) or avoided (like the Cysteine) by the resistant species. Furthermore, Cancer resistance in mammals and reptiles is significantly predicted by the number of the predicted protecting variants (PVs) a species has. Moreover, PVs-enriched-genes are enriched in pathways relevant to tumor suppression. For example, they are enriched in the Hedgehog signaling and silencing pathways, which its improper activation is associated with the most common form of cancer malignancy. We also showed that the PVs are mostly more abundant in healthy people compared to cancer patients within different human races.

Keywords: cancer resistance, protecting variant, naked mole rat, comparative genomics

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Authors: Itziar Gonzalez, Pilar Carreras, Alberto Pinto, Roque Ruben Andres

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Acoustophoretic separation of plasma from blood is based on a collection process of the blood cells, driven by an acoustic radiation force. The number of cells, their concentration, and the sample hydrodynamics are involved in these processes. However, their influence on the acoustic blood response has not yet been reported in the literature. Addressing it, this paper presents an experimental study of blood samples exposed to ultrasonic standing waves at different hematocrit levels and hydrodynamic conditions. The experiments were performed in a glass capillary (700µm-square cross section) actuated by a piezoelectric ceramic at 1MHz, hosting 2D orthogonal half-wavelength resonances transverse to the channel length, with a single-pressure-node along its central axis where cells collected driven by the acoustic radiation force. Four blood dilutions in PBS of 1:20, 1:10, 1:5, and 1:2 were tested at eight flow rate conditions Q=0:120µL/min. The 1:5 dilution (H=9%) demonstrated to be optimal for the plasmapheresis at any of the flow rates analyzed, requiring the shortest times to achieve plasma free of cells. The study opens new possibilities to optimize processes of plasmapheresis processes by ultrasounds at different hematocrit conditions in future personalized diagnoses/treatments involving blood samples.

Keywords: ultrasounds, microfluidics, flow rate, acoustophoresis, polymeric resonators

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Authors: Ishak Kamal Baskhayroun

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This study examines consumer attitudes toward mobile marketing, especially toward SMS marketing. Unlike similar studies, this study does not focus on the young, but includes consumers who are in the 18-70 age range to the field research. According to the results, it has been concluded that most participants think SMS marketing is disturbing. Most important problems with SMS marketing are about getting subscribed to message lists without the permission of the receiver; the high number of messages sent; and the irrelevancy of the message content. The emergence of sponsorship as a new marketing communication tool and a source of competitive advantage in the marketplace has changed the entire marketing communication process. Sponsorship has overtaken other marketing communication tools in terms of growth and expenditure. This paper seeks to evaluate the role of sponsorship in marketing communication tools. The study recommends that proper measures be taken before the company embarks into sponsorship programs. This is necessary because investment in sponsorship does not always guarantee sustainable competitive advantage in the marketplace.Mobile phones are one of the direct marketing tools that can be used to reach today’s hard to reach consumers. Mobile phones are very personal devices and they are always carried with the consumer, where ever they go. This creates an opportunity for marketers to create personalized marketing communications messages and send them on the right time and place.

Keywords: employee organizational performance, internal marketing, internal customer, direct marketing, mobile phones mobile marketing, sms advertising, marketing sponsorship, marketing communication theories, marketing communication tools corporate responsibility

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Authors: Omer Ibrahim Abdallh Omer

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Cancer patients often face complex medication regimens, leading to challenges in treatment adherence and clinical outcomes. Pharmacist-led medication therapy management (MTM) has emerged as a potential solution to optimize medication use and improve patient outcomes in oncology settings. In this prospective intervention study, we aimed to evaluate the impact of pharmacist-led MTM on treatment adherence and clinical outcomes among cancer patients. Participants were randomized to receive either pharmacist-led MTM or standard care, with assessments conducted at baseline and follow-up visits. Pharmacist interventions included medication reconciliation, adherence counseling, and personalized care plans. Our findings reveal that pharmacist-led MTM significantly improved medication adherence rates and clinical outcomes compared to standard care. Patients receiving pharmacist interventions reported higher satisfaction levels and perceived value in pharmacist involvement in their cancer care. These results underscore the critical role of pharmacists in optimizing medication therapy and enhancing patient-centered care in oncology settings. Integration of pharmacist-led MTM into routine cancer care pathways holds promise for improving treatment outcomes and quality of life for cancer patients.

Keywords: cancer, medications adherence, medication therapy management, pharmacist

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Authors: Waleed Afandi

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Artificial intelligence (AI) has rapidly transformed various sectors, including education. This paper explores the integration of AI in education, emphasizing its potential to revolutionize learning processes, enhance teaching methodologies, and personalize education. We examine the historical context of AI in education, current applications, and the potential challenges and ethical considerations associated with its implementation. By reviewing a wide range of literature, this study aims to provide a comprehensive understanding of how AI can be leveraged to improve educational outcomes and the future directions of AI-driven educational innovations. Additionally, the paper discusses the impact of AI on student engagement, teacher support, and administrative efficiency. Case studies highlighting successful AI applications in diverse educational settings are presented, showcasing the practical benefits and real-world implications. The analysis also addresses potential disparities in access to AI technologies and suggests strategies to ensure equitable implementation. Through a balanced examination of the promises and pitfalls of AI in education, this study seeks to inform educators, policymakers, and technologists about the optimal pathways for integrating AI to foster an inclusive, effective, and innovative educational environment.

Keywords: artificial intelligence, education, personalized learning, teaching methodologies, educational outcomes, AI applications, student engagement, teacher support, administrative efficiency, equity in education

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Authors: Khushbu Priyadarshi, Chandramani Pathak

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Cancer cells can develop resistance to conventional therapies especially chemotherapeutic drugs. Resistance to chemotherapy is another challenge in cancer therapeutics. Therefore, it is important to address this issue. Gallic acid (GA) is a natural plant compound that exhibits various biological properties including anti-proliferative, anti-inflammatory, anti-oxidant and anti-bacterial. Despite of the wide spectrum biological properties GA has cytotoxic response and low bioavailability. To overcome this problem, GA was conjugated with the Polyamidoamine(PAMAM) dendrimer for improving the bioavailability and efficient delivery in drug-resistant HCT-116 Colon Cancer cells. Gallic acid was covalently linked to 4.0 G PAMAM dendrimer. PAMAM dendrimer is well established nanocarrier but has cytotoxicity due to presence of amphiphilic nature of amino group. In our study we have modified surface of PAMAM dendrimer with Gallic acid and examine their anti-proliferative effects in drug-resistant HCT-116 cells. Further, drug-resistant colon cancer cells were established and thereafter treated with different concentration of PAMAM-GA to examine their anti-proliferative potential. Our results show that PAMAM-GA conjugate induces apoptotic cell death in HCT-116 and drug-resistant cells observed by Annexin-PI staining. In addition, it also shows that multidrug-resistant drug transporter P-gp protein expression was downregulated with increasing the concentration of GA conjugate. After that we also observed the significant difference in Rh123 efflux and accumulation in drug sensitive and drug-resistant cancer cells. Thus, our study suggests that conjugation of anti-cancer agents with PAMAM could improve drug resistant property and cytotoxic response to treatment of cancer.

Keywords: drug resistance, gallic acid, PAMAM dendrimer, P-glycoprotein

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Authors: Sameen Tariq, Saira Bano, Sayyada Ghufrana Nadeem

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The Ocean, which covers over 70% of the world's surface, is wealthy in biodiversity as well as a rich wellspring of microorganisms with huge potential. The oceanic climate is home to an expansive scope of plants, creatures, and microorganisms. Marine microbial networks, which incorporate microscopic organisms, infections, and different microorganisms, enjoy different benefits in biotechnological processes. Samples were collected from marine environments, including soil and water samples, to cultivate the uncultured marine organisms by using Zobell’s medium, Sabouraud’s dextrose agar, and casein media for this purpose. Following isolation, we conduct microscopy and biochemical tests, including gelatin, starch, glucose, casein, catalase, and carbohydrate hydrolysis for further identification. The results show that more gram-positive and gram-negative bacteria. The isolation process of marine organisms is essential for understanding their ecological roles, unraveling their biological secrets, and harnessing their potential for various applications. Marine organisms exhibit remarkable adaptations to thrive in the diverse and challenging marine environment, offering vast potential for scientific, medical, and industrial applications. The isolation process plays a crucial role in unlocking the secrets of marine organisms, understanding their biological functions, and harnessing their valuable properties. They offer a rich source of bioactive compounds with pharmaceutical potential, including antibiotics, anticancer agents, and novel therapeutics. This study is an attempt to explore the diversity and dynamics related to marine microflora and their role in biofilm formation.

Keywords: marine microorganisms, ecosystem, fungi, biofilm, gram-positive, gram-negative

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Authors: Crin N. Marcean, Mihaela A. Alexandru, Eugenia S. Cristescu

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By definition, nursing means caring. It is a profession within the health care sector focused on the care of individuals, families, and communities so they may attain, maintain or recover optimal health and quality of life. However, there is a subtle difference between the two: nursing is widely considered as an art and a science, wherein caring forms the theoretical framework of nursing. Nursing and caring are grounded in a relational understanding, unity, and connection between the professional nurse and the patient. Task-oriented approaches challenge nurses in keeping care in nursing. This challenge is on-going as professional nurses strive to maintain the concept, art, and act of caring as the moral centre of the nursing profession. Keeping the care in nursing involves the application of art and science through theoretical concepts, scientific research, conscious commitment to the art of caring as an identity of nursing, and purposeful efforts to include caring behaviours during each nurse-patient interaction. The competencies, abilities, as well as the psycho-motor, cognitive, and relational skills necessary for the nursing practice are conveyed and improved by the nursing teachers’ art of teaching. They must select and use the teaching methods which shape the personalities of the trainers or students, enabling them to provide individualized, personalized care in real-world context of health problems. They have the ultimate responsibility of shaping the future health care system by educating skilful nurses.

Keywords: art of nursing, health care, teacher-student relationship, teaching innovations

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Authors: Raymond Feng, Shadi Ghiasi

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An electroencephalogram (EEG) is a non-invasive technique that records electrical activity in the brain using scalp electrodes. Researchers have studied the use of EEG to detect emotions and moods by collecting signals from participants and analyzing how those signals correlate with their activities. In this study, researchers investigated the relationship between EEG signals and music enjoyment. Participants listened to music while data was collected. During the signal-processing phase, power spectral densities (PSDs) were computed from the signals, and dominant brainwave frequencies were extracted from the PSDs to form a comprehensive feature matrix. A machine learning approach was then taken to find correlations between the processed data and the music enjoyment level indicated by the participants. To improve on previous research, multiple machine learning models were employed, including K-Nearest Neighbors Classifier, Support Vector Classifier, and Decision Tree Classifier. Hyperparameters were used to fine-tune each model to further increase its performance. The experiments showed that a strong correlation exists, with the Decision Tree Classifier with hyperparameters yielding 85% accuracy. This study proves that EEG is a reliable means to detect music enjoyment and has future applications, including personalized music recommendation, mood adjustment, and mental health therapy.

Keywords: EEG, electroencephalogram, machine learning, mood, music enjoyment, physiological signals

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Authors: Yutong An

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Premature babies in the Neonatal Intensive Care Unit (NICU) are usually protected in individual incubators to ensure a constant temperature and humidity. Accompanied by 24-hour monitoring by medical equipment, this provides a considerable degree of protection for the growth of preterm babies. However, preterm babies are still continuously exposed to noise at excessively high decibels (>45dB). Such noise has a highly damaging effect on the growth and development of preterm babies. For example, in the short term, it can lead to sleep deprivation, stress reactions, and difficulty calming emotions, while in the long term, it can trigger endocrine disorders, metabolic disorders, and hearing impairment. Fortunately, musical interventions in the NICU have been shown to provide calmness to newborns. This article integrates existing research on three types of music that are beneficial for preterm infants and their respective advantages and disadvantages. This paper aims to present a possibility, based on existing NICU equipment and experimental data related to musical interventions, to reduce the impact of noise on preterm babies in the NICU through a system design approach that incorporates a personalized adjustable music system in the incubator and an overall music enhancement in the open bay of the NICU.

Keywords: music interventions, neonatal intensive care unit (NICU), premature babies, neonatal nursing

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Authors: Walaa H. Salama, Azza M. Abdel-Aty, Afaf S. Fahmy

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Background: Egyptian Cobra; Naja haje (Elapidae) is one of most common snakes, widely distributed in Egypt and its envenomation causes multi-organ failure leading to rapid death. Thus, Different medicinal plants showed a protective effect against venom toxicity and may complement the conventional antivenom therapy. Aim: The present study was designed to assess both the antioxidant capacity of methanolic extract of rosemary leaves and evaluate the neutralizing ability of the extract against hepatotoxicity induced by Naja haje venom. Methods: The total phenolic and flavonoid contents and the antioxidant capacity of the methanolic rosemary extract were estimated by DPPH and ABTS Scavenging methods. In addition, the rosemary extract were assessed for anti-venom properties under in vitro and in vivo standard assays. Results: The rosemary extract had high total phenolic and flavonoid content as 12 ± 2 g of gallic acid equivalent per 100 gram of dry weight (g GAE/100g dw) and 5.5 ± 0.8 g of catechin equivalent per 100 grams of dry weight (g CE/100g dw), respectively. In addition, the rosemary extract showed high antioxidant capacity. Furthermore, The rosemary extract were inhibited in vitro the enzymatic activities of phospholipase A₂, L-amino acid oxidase, and hyaluronidase of the venom in a dose-dependent manner. Moreover, indirect hemolytic activity, hepatotoxicity induced by venom were completely neutralized as shown by histological studies. Conclusion: The phenolic compounds of rosemary extract with potential antioxidant activity may be considered as a promising candidate for future therapeutics in snakebite therapy.

Keywords: antioxidant activity, neutralization, phospholipase A₂ enzyme, snake venom

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Authors: Gayathri Sadanala, Shibam Pokhrel, Owen Murphy

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In the ever-evolving landscape of education, Virtual Reality (VR) environments offer a promising avenue for enhancing student engagement and learning experiences. However, understanding and predicting student behavior within these immersive settings remain challenging tasks. This paper presents a comprehensive study on the predictive modeling of student behavior in VR using machine learning techniques. We introduce a rich data set capturing student interactions, movements, and progress within a VR orientation program. The dataset is divided into training and testing sets, allowing us to develop and evaluate predictive models for various aspects of student behavior, including engagement levels, task completion, and performance. Our machine learning approach leverages a combination of feature engineering and model selection to reveal hidden patterns in the data. We employ regression and classification models to predict student outcomes, and the results showcase promising accuracy in forecasting behavior within VR environments. Furthermore, we demonstrate the practical implications of our predictive models for personalized VR-based learning experiences and early intervention strategies. By uncovering the intricate relationship between student behavior and VR interactions, we provide valuable insights for educators, designers, and developers seeking to optimize virtual learning environments.

Keywords: interaction, machine learning, predictive modeling, virtual reality

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Authors: Diogo Ribeiro, Teresa Neto, Ricardo Santos, Maria Portela, Alexandra Trincão

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This article describes a set of innovating student recruitment strategies in a 1st cycle course of Civil Engineering, in particular the Civil Engineering Degree from the School of Engineering - Polytechnic of Porto (ISEP-PP). The strategies described were two-fold, targeting, for one, the increment on the number of admissions for the degree’s first year and two, promoting the re-entry of students who, for whatever reason, interrupted their studies. For the first objective, teacher-student binomials were set, whilst for the second, personalized contacts and assistance were provided. The main initiatives were promoted by the team of degree directors and were upheld with the participation and in consonance with the School’s external relations office. These initiatives were put forward as an attempt to minimize the impact of a national and international crisis on the AEC industry when the sustainability of the course was at risk. The implementation of these strategies was assessed on basis of a statistical analysis of the data collected from official sources and by surveys promoted. The results showed that the re-entry boost of former students, attending classes scattered on the three curricular years, secured registrations on some Curricular Units (UC’s) which more than doubled their numbers. Accompanied by a still incipient but regained interest on Civil Engineering it was possible in the short span of three years to reset the number of new students from less than 10 to the currently maximum allowed of 75, and so invert the tendency of an abrupt decline on the total number of students enrolled on the degree.

Keywords: civil engineering, monitoring, performance indicators, strategies, student recruitment

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Authors: Alex Kiselyov, Suehyun Cho, Darrell Harrington; Florent Cros, Olin Palmer, John Caputo, Michael Kardosh, Eran Oren, William Loudon, Michael Shpigelmacher

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Despite the most aggressive surgical and adjuvant therapeutic strategies, treatment of both pediatric and adult brainstem tumors remains problematic. Novel strategies, including targeted biologics, immunotherapy, and specialized delivery systems such as convection-enhanced delivery (CED), have been proposed. While some of these novel treatments are entering phase I trials, the field is still in need of treatment(s) that exhibits dramatically enhanced potency with optimal therapeutic ratio. Bionaut Labs has developed a modular microrobotic platform for performing localized delivery of diverse therapeutics in vivo. Our biocompatible particles (Bionauts™) are externally propelled and visualized in real-time. Bionauts™ are specifically designed to enhance the effect of radiation therapy via anatomically precise delivery of a radiosensitizing agent, as exemplified by temozolomide (TMZ) and Avastin™ to the brainstem gliomas of diverse origin. The treatment protocol is designed to furnish a better therapeutic outcome due to the localized (vs systemic) delivery of the drug to the neoplastic lesion(s) for use as a synergistic combination of radiation and radiosensitizing agent. In addition, the procedure is minimally invasive and is expected to be appropriate for both adult and pediatric patients. Current progress, including platform optimization, selection of the lead radiosensitizer as well as in vivo safety studies of the Bionauts™ in large animals, specifically the spine and the brain of porcine and ovine models, will be discussed.

Keywords: Bionaut, brainstem, glioma, local delivery, micro-robot, radiosensitizer

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Authors: N. Ipiña, R. Basagoiti, O. Jimenez, I. Arriaran

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Higher education students are increasingly enrolling in online courses, they are, at the same time, generating data about their learning process in the courses. Data collected in those technology enhanced learning spaces can be used to identify patterns and therefore, offer recommendations/personalized courses to future online students. Moreover, recommendations are considered key aspects for personalization in online learning. Taking into account the above mentioned context, the aim of this paper is to explore the perception of higher education students and teachers towards receiving recommendations in online courses. The study was carried out with 322 students and 10 teachers from two different faculties (Engineering and Education) from Mondragon University. Online questionnaires and face to face interviews were used to gather data from the participants. Results from the questionnaires show that most of the students would like to receive recommendations in their online courses as a guide in their learning process. Findings from the interviews also show that teachers see recommendations useful for their students’ learning process. However, teachers believe that specific pedagogical training is required. Conclusions can also be drawn as regards the importance of personalization in technology enhanced learning. These findings have significant implications for those who train online teachers due to the fact that pedagogy should be the driven force and further training on the topic could be required. Therefore, further research is needed to better understand the impact of recommendations on online students’ learning process and draw some conclusion on pedagogical concerns.

Keywords: higher education, perceptions, recommendations, online courses

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Authors: Xin Zhao

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3D printing is used in creating bone grafts of various architectures by printing materials in a layer-by-layer manner. Traditionally, to make materials printable, heating up or dissolving materials in organic solvents have been used, compromising their capability in loading biomolecules. Photocrosslinkable materials which are initially liquid and printable, and solidified upon light exposure are therefore developed. However, the existing photocrosslinkable materials are either too soft to bear load or non-degradable with potential long-term biocompatibility problems. Here, photocrosslinkable nanocomposite ink is developed composed of poly (lactide-co-propylene glycol-co-lactide) dimethacrylate (PmLnDMA) and hydroxyethyl methacrylate-functionalized hydroxyapatite nanoparticles (nHAMA) mimicking the hairy setae of gecko that can strongly interact with its surroundings to bear high load. Incorporation of nHAMA into PmLnDMA endows the nanocomposite ink with several advantages in (1) improved organic/inorganic interfacial compatibility to increase mechanical strength, (2) readily modulated rheological behaviors, wettability, and biodegradation, (3) enhanced osteoconductivity and osteoinductivity. Moreover, the ink can be rapidly crosslinked upon light exposure, load, and long-term release growth factors, and be printed into 3D bone scaffolds of various shapes and structures according to the patients’ needs. Altogether, this innovation will benefit patients all over the world who suffer from bone fractures, tumors, infections.

Keywords: photocrosslinkable nanocomposite, 3D printing, bone ink, personalized medicine

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Authors: Tero Huhtala, Minna Pikkarainen, Saila Saraniemi

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Information technology has long been used as an enabler of exchange for goods and services. Services are evolving from generic to personalized, and the reverse use of customer data has been discussed in both academia and industry for the past few years. This article presents the results of an empirical case study in the area of preventive health care services. The primary data were gathered in workshops, in which future personal data-based services were conceptualized by analyzing future scenarios from a business perspective. The aim of this study is to understand business model transformation in emerging personal data ecosystems. The work was done as a case study in the context of occupational healthcare. The results have implications to theory and practice, indicating that adopting personal data management principles requires transformation of the business model, which, if successfully managed, may provide access to more resources, potential to offer better value, and additional customer channels. These advantages correlate with the broadening of the business ecosystem. Expanding the scope of this study to include more actors would improve the validity of the research. The results draw from existing literature and are based on findings from a case study and the economic properties of the healthcare industry in Finland.

Keywords: ecosystem, business model, personal data, preventive healthcare

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Authors: Cigdem Karaaslan, Yalcin Duydu, Aylin Ustundag, Can Ozgur Yalcın, Hakan Goker

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Benzazole nucleus is found in the structure of many compounds as anticancer agents. Bendamustine (Alkylating agent), Nocodazole (Mitotic inhibitor), Veliparib (PARP inhibitor), Glasdegib (SMO inhibitor) are clinically used as anticancer therapeutics which bearing benzimidazole moiety. Based on the principle of bioisosterism in the present work, 23 compounds belonging to 2-(3,4-dimethoxy-phenyl) benzazoles and imidazopyridine series were synthesized and evaluated for their anticancer activities. N-(5-Chloro-2-hydroxyphenyl)-3,4-dimethoxybenzamide, was obtained by the amidation of 2-hydroxy-5-chloroaniline with 3,4-dimethoxybenzoic acid by using 1,1'-carbonyldiimidazole. Cyclization of benzamide derivative to benzoxazole, was achieved by p-toluenesulfonic acid. Other 1H-benz (or pyrido) azoles were prepared by the reaction between 2-aminothiophenol, o-phenylenediamine, o-pyridinediamine with sodium metabisulfite adduct of 3,4-dimethoxybenzaldehyde. The NMR assignments of the dimethoxy groups were established by the Nuclear Overhauser Effect Spectroscopy. A compound named, 5(4),7(6)-Dichloro-2-(3,4-dimethoxy) phenyl-1H-benzimidazole, bearing two chlorine atoms at the 5(4) and 7(6) positions of the benzene moiety of benzimidazole was found the most potent analogue, against A549 cells with the GI50 value of 1.5 µg/mL. In addition, 2-(3,4-Dimethoxyphenyl)-5,6-dimethyl-1H-benzimi-dazole showed remarkable cell growth inhibition against MCF-7 and HeLa cells with the GI₅₀ values of 7 and 5.5 µg/mL, respectively. It could be concluded that introduction of di-chloro atoms at the phenyl ring of 2-(3,4-dimethoxyphenyl)-1H-benzimidazoles increase significant cytotoxicity to selected human tumor cell lines in comparison to other all benzazoles synthesized in this study. Unsubstituted 2-(3,4-dimethoxyphenyl) imidazopyridines also gave the good inhibitory profile against A549 and HeLa cells.

Keywords: 3, 4-Dimethoxyphenyl, 1H-benzimidazole, benzazole, imidazopyridine

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Authors: Ehi E. Aimiuwu

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As of 2017, many online learning professionals, institutions, and journals are still wondering how instructors can keep student engaged in the online learning environment to facilitate active learning effectively. The purpose of this qualitative single-case and narrative research is to explore whether online professors understand their role as mentors and facilitators of students’ academic success by keeping students engaged in active learning based on personalized experience in the field. Data collection tools that were used in the study included an NVivo 12 Plus qualitative software, an interview protocol, a digital audiotape, an observation sheet, and a transcription. Seven online professors in the United States from LinkedIn and residencies were interviewed for this study. Eleven online teaching techniques from previous research were used as the study framework. Data analysis process, member checking, and key themes were used to achieve saturation. About 85.7% of professors agreed on rubric as the preferred online grading technique. About 57.1% agreed on professors logging in daily, students logging in about 2-5 times weekly, knowing students to increase accountability, email as preferred communication tool, and computer access for adequate online learning. About 42.9% agreed on syllabus for clear class expectations, participation to show what has been learned, and energizing students for creativity.

Keywords: class facilitation, class management, online teaching, online education, pedagogy

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Authors: Dong Tran, Thanh Dac Van, Ly Le

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Hemagglutinin (HA) and Neuraminidase (NA) play an important role in host immune evasion across influenza virus evolution process. The correlation between HA and NA evolution in respect to epitopic evolution and drug interaction has yet to be investigated. In this study, combining of sequence to structure evolution and statistical analysis on epitopic/binding site specificity, we identified potential therapeutic features of HA and NA that show specific antibody binding site of HA and specific binding distribution within NA active site of current inhibitors. Our approach introduces the use of sequence variation and molecular interaction to provide an effective strategy in establishing experimental based distributed representations of protein-protein/ligand complexes. The most important advantage of our method is that it does not require complete dataset of complexes but rather directly inferring feature interaction from sequence variation and molecular interaction. Using correlated sequence analysis, we additionally identified co-evolved mutations associated with maintaining HA/NA structural and functional variability toward immunity and therapeutic treatment. Our investigation on the HA binding specificity revealed unique conserved stalk domain interacts with unique loop domain of universal antibodies (CR9114, CT149, CR8043, CR8020, F16v3, CR6261, F10). On the other hand, NA inhibitors (Oseltamivir, Zaninamivir, Laninamivir) showed specific conserved residue contribution and similar to that of NA substrate (sialic acid) which can be exploited for drug design. Our study provides an important insight into rational design and identification of novel therapeutics targeting universally recognized feature of influenza HA/NA.

Keywords: influenza virus, hemagglutinin (HA), neuraminidase (NA), sequence evolution

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Authors: Jumanah S. Alawfi

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Polycystic ovary syndrome (PCOS) is a common endocrinopathy among females in their reproductive years. The incidence cases are nearly 1.55 million among females across the globe, with 0.43 million associated disability-adjusted life-years (DALYs). This syndrome is associated with intricate mechanisms typically characterized by insulin resistance (IR), infertility, overweight and/or obesity. Lifestyle interventions are often prescribed as an adjective treatment. Nonetheless, obesity is a complex disease that encompasses multiple dimensions, such as excessive energy intake and genetics. The melanocortin 4 receptor mutation (MC4R) is an important mediator in appetite. There is emerging evidence that suggests its role in the Body Mass Index (BMI) among PCOS subjects, which poses the question of obesity and/or overweight among the PCOS patients who carry the MC4R variants may be caused by overconsumption. Thereby, using other satiety techniques may be beneficial as a part of personalized nutrition. Therefore, the aim of the current mini-review is to discuss the effect of the vegan low glycemic diet on reducing appetite among PCOS patients. The review shows that there is a gap in the knowledge of the effect of the vegan diet on PCOS patients who carry MC4R variants which need further research.

Keywords: polycystic ovarian syndrome (PCOS), Appetite, Melanocortin 4 Receptor Mutation (MC4R)., Obesity

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Authors: Isabel Moscol, Carlos J. Díaz, Ciro Rodríguez

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Hip replacement becomes necessary when a person suffers severe pain or considerable functional limitations and the best option to enhance their quality of life is through the replacement of the damaged joint. One of the main components in femoral prostheses is the stem which distributes the loads from the joint to the proximal femur. To preserve more bone stock and avoid weakening of the diaphysis, a short starting stem was selected, generated from the intramedullary morphology of the patient's femur. It ensures the implantability of the design and leads to geometric delimitation for personalized optimization with machine learning (ML) and metaheuristic algorithms. The present study attempts to design a cementless short stem to make the strain deviation before and after implantation close to zero, promoting its fixation and durability. Regression models developed to estimate the percentage change of maximum principal stresses were used as objective optimization functions by the metaheuristic algorithm. The latter evaluated different geometries of the short stem with the modification of certain parameters in oblique sections from the osteotomy plane. The optimized geometry reached a global stress shielding (SS) of 18.37% with a determination factor (R²) of 0.667. The predicted results favour implantability integration in the short stem optimization to effectively reduce SS in the proximal femur.

Keywords: machine learning techniques, metaheuristic algorithms, short-stem design, stress shielding, hip replacement

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Authors: Jesús David Argueta Moreno, Taria Ruiz, Cesar Ortega

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This qualitative investigation represents the first stage of the human capital engineering analysis, along the small and medium textile manufacturing companies, located on the city of Tegucigalpa, Honduras where the symptoms of the local manufacturing industry´s describe a severe gender displacement phenomenon. The evaluation of this phenomena, intends to trigger the Honduran small and medium technology manufactures into a collective performance, analysis through the development of a sectorial diagnose and the creation of a manufacturers guide, personalized. In accordance to the Honduran textile manufacturing needs, in order to strengthen their personnel capacities and thereby smoothen the gender equilibrium on this particular sector. It is worth mentioning, that on the last decade, the female gender has gathered positive statistics upon Central American job market´s, were the local business landscape describes a significant displacement of the Honduran female operators over the male gender workers that has significantly diminished their employment predominance. On the other hand, this study aims to evaluate the main features that impact on the job market local gender supplanting. On the other hand, this document aims to holistically describe the Honduran manufacturing context, as well as the current textile operator qualifications, in order to infer over the most proper human resources enforcement approaches/techniques on the industry.

Keywords: gender predominance, manufacturing, higher education institutions, emerging trends

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Authors: Mirna John Shawky Demian

Abstract:

Mobile phones are now one of the direct marketing tools used to reach hard-to-reach consumers. Cell phones are very personal devices that you can carry with you anytime, anywhere. This gives marketers the ability to create personalized marketing messages and send them at the right time and place. The study examined consumer attitudes towards mobile marketing, particularly SMS marketing. Unlike similar studies, this study does not focus on young people, but the field study included consumers between the ages of 18 and 70.The results showed that the majority of participants found SMS marketing destructive. The biggest problem with SMS marketing is subscribing to message lists without the recipient's consent; large number of messages sent; and the irrelevance of message content. Experiential marketing is an unforgettable experience that remains deeply anchored in the customer's memory. Furthermore, customer satisfaction is defined as the emotional response to the experience provided to the customer in relation to specific products or services purchased. Therefore, experiential marketing activities can influence the level of customer satisfaction and loyalty.In this context, the study aims to examine the relationship between experiential marketing, customer satisfaction and loyalty to beauty products in Konya. The results of this study showed that experiential marketing is an important indicator of customer satisfaction and loyalty and that experiential marketing has a significant positive impact on customer satisfaction and loyalty.

Keywords: direct marketing, mobile phones mobile marketing, sms advertising, marketing sponsorship, marketing communication theories, marketing communication tools

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Authors: Karolis Leonavičius, Dalius Kučiauskas, Dangiras Lukošius, Arnoldas Jasiūnas, Kostas Zdanys, Rokas Stanislovas, Emilis Gegevičius, Žana Kapustina, Juozas Nainys

Abstract:

Screening throughput is a common bottleneck in many research areas, including functional genomics, drug discovery, and directed evolution. High-throughput screening techniques can be classified into two main categories: (i) affinity-based screening and (ii) functional screening. The first one relies on binding assays that provide information about the affinity of a test molecule for a target binding site. Binding assays are relatively easy to establish; however, they reveal no functional activity. In contrast, functional assays show an effect triggered by the interaction of a ligand at a target binding site. Functional assays might be based on a broad range of readouts, such as cell proliferation, reporter gene expression, downstream signaling, and other effects that are a consequence of ligand binding. Screening of large cell or gene libraries based on direct activity rather than binding affinity is now a preferred strategy in many areas of research as functional assays more closely resemble the context where entities of interest are anticipated to act. Droplet sorting is the basis of high-throughput functional biological screening, yet its applicability is limited due to the technical complexity of integrating high-performance droplet analysis and manipulation systems. As a solution, the Droplet Genomics Styx platform enables custom droplet sorting workflows, which are necessary for the development of early-stage or complex biological therapeutics or industrially important biocatalysts. The poster will focus on the technical design considerations of Styx in the context of its application spectra.

Keywords: functional screening, droplet microfluidics, droplet sorting, dielectrophoresis

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Authors: Syed Asif Hassan, Syed Atif Hassan

Abstract:

Multidrug-resistant Tuberculosis (MDR-TB) is an infection caused by the resistant strains of Mycobacterium tuberculosis that do not respond either to isoniazid or rifampicin, which are the most important anti-TB drugs. The increase in the occurrence of a drug-resistance strain of MTB calls for an intensive search of novel target-based therapeutics. In this context LprG (Rv1411c) a lipoprotein from MTB plays a pivotal role in the immune evasion of Mtb leading to survival and propagation of the bacterium within the host cell. Therefore, a machine learning method will be developed for generating a computational model that could predict for a potential anti LprG activity of the novel antituberculosis compound. The present study will utilize dataset from PubChem database maintained by National Center for Biotechnology Information (NCBI). The dataset involves compounds screened against MTB were categorized as active and inactive based upon PubChem activity score. PowerMV, a molecular descriptor generator, and visualization tool will be used to generate the 2D molecular descriptors for the actives and inactive compounds present in the dataset. The 2D molecular descriptors generated from PowerMV will be used as features. We feed these features into three different classifiers, namely, random forest, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model based on the accuracy of predicting novel antituberculosis compound with an anti LprG activity. Additionally, the efficacy of predicted active compounds will be screened using SMARTS filter to choose molecule with drug-like features.

Keywords: antituberculosis drug, classifier, machine learning, molecular descriptors, prediction

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Authors: Kartik Thakore, Anna-Roza Tamas, Adam Cole

Abstract:

The world health organization (WHO) reports that by 2030 more than 23.7 million deaths annually will be caused by Cardiovascular Diseases (CVDs); with a 2008 economic impact of $3.76 T. Metabolic syndrome is a disorder of multiple metabolic risk factors strongly indicated in the development of cardiovascular diseases. Guided lifestyle intervention driven by live coaching has been shown to have a positive impact on metabolic risk factors. Individuals’ path to improved (decreased) metabolic risk factors are driven by personal motivation and personalized messages delivered by coaches and augmented by technology. Using interactions captured between 400 individuals and 3 coaches over a program period of 500 days, a preliminary model was designed. A novel real time event tracking system was created to track and classify clients based on their genetic profile, baseline questionnaires and usage of a mobile application with live coaching sessions. Classification of clients and coaches was done using a support vector machines application build on Apache Spark, Stanford Natural Language Processing Library (SNLPL) and decision-modeling.

Keywords: guided lifestyle intervention, metabolic risk factors, personal coaching, support vector machines application, Apache Spark, natural language processing

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Authors: Hongquan Zhang

Abstract:

Inspired by endogenous protein motors, researchers have constructed various synthetic DNA motors based on the specificity and predictability of Watson-Crick base pairing. However, the application of DNA motors to signal amplification and biosensing is limited because of low mobility and difficulty in real-time monitoring of the walking process. The objective of our work was to construct a new type of DNA motor termed target-triggered DNA motors that can walk for hundreds of steps in response to a single target binding event. To improve the mobility and processivity of DNA motors, we used gold nanoparticles (AuNPs) as scaffolds to build high-density, three-dimensional tracks. Hundreds of track strands are conjugated to a single AuNP. To enable DNA motors to respond to specific protein and nucleic acid targets, we adapted the binding-induced DNA assembly into the design of the target-triggered DNA motors. In response to the binding of specific target molecules, DNA motors are activated to autonomously walk along AuNP, which is powered by a nicking endonuclease or DNAzyme-catalyzed cleavage of track strands. Each moving step restores the fluorescence of a dye molecule, enabling monitoring of the operation of DNA motors in real time. The motors can translate a single binding event into the generation of hundreds of oligonucleotides from a single nanoparticle. The motors have been applied to amplify the detection of proteins and nucleic acids in test tubes and live cells. The motors were able to detect low pM concentrations of specific protein and nucleic acid targets in homogeneous solutions without the need for separation. Target-triggered DNA motors are significant for broadening applications of DNA motors to molecular sensing, cell imagining, molecular interaction monitoring, and controlled delivery and release of therapeutics.

Keywords: biosensing, DNA motors, gold nanoparticles, signal amplification

Procedia PDF Downloads 79

Authors: Itamir de Morais Barroca Filho, Cephas A. S. Barreto, Ramon Malaquias, Cezar Miranda Paula de Souza, Arthur Costa Gorgônio, João C. Xavier-Júnior, Mateus Firmino, Fellipe Matheus Costa Barbosa

Abstract:

Information and Communication Technologies (ICT) in healthcare are crucial for efficiently delivering medical healthcare services to patients. These ICTs are also known as e-health and comprise technologies such as electronic record systems, telemedicine systems, and personalized devices for diagnosis. The focus of e-health is to improve the quality of health information, strengthen national health systems, and ensure accessible, high-quality health care for all. All the data gathered by these technologies make it possible to help clinical staff with automated decisions using machine learning. In this context, we collected patient data, such as heart rate, oxygen saturation (SpO2), blood pressure, respiration, and others. With this data, we were able to develop machine learning models for patients’ risk of death and estimate the length of stay in ICU beds. Thus, this paper presents the methodology for applying machine learning techniques to develop these models. As a result, although we implemented these models on an IoT healthcare platform, helping clinical staff in healthcare in an ICU, it is essential to create a robust clinical validation process and monitoring of the proposed models.

Keywords: ICT, e-health, machine learning, ICU, healthcare

Procedia PDF Downloads 97