Search results for: delivery of disease data information

Authors: Moslem Taheri Soodejani, Mohammad Hassan Lotfi

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Introduction: The outbreak of Covid-19 disease is an international public health concern. Therefore, the analysis of information related to mortality and disability due to COVID-19 is considered important, so the present study was designed and conducted with the aim of assessing COVID-19 Disability-Adjusted Life Years (DALYs) in Yazd. Methods: In Yazd province, all suspected cases of Covid-19 that would be referred to central hospitals in order to get confirmed through PCR or CT scan tests were recruited to our study. The fatality data of Covid- 19 was gathered from the forensic medicine organization. The Disability-Adjusted Life Years (DALYs) combines in one measure years of life lost (YLL), the loss of healthy life due to premature mortality and years of life lived with disability (YLD), the loss of healthy life because of disease and disability. Results: The total burden of COVID-19 was 23,472 years. The number of years lost due to premature death was 23385 and the number of years of life with disability due to COVID-19 was estimated to be 87 years. The disease burden was 12992 years for men and 10480 years for women. The overall incidence of COVID-19 was 1411 per 100,000, of which 1419 in men and 1402 in women per 100,000. Conclusion: The outbreak of the COVID-19 pandemic affected a large population and the residents of Yazd Province lost many years of their lives due to this disease.

Keywords: DALY, covid- 19, Yazd, Iran

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Authors: Ruzanna Muradyan

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Medical data mining is a crucial field in contemporary healthcare that offers cutting-edge tactics with enormous potential to transform patient care. This abstract examines how sophisticated data mining techniques could transform the healthcare industry, with a special focus on how they might improve patient outcomes. Healthcare data repositories have dynamically evolved, producing a rich tapestry of different, multi-dimensional information that includes genetic profiles, lifestyle markers, electronic health records, and more. By utilizing data mining techniques inside this vast library, a variety of prospects for precision medicine, predictive analytics, and insight production become visible. Predictive modeling for illness prediction, risk stratification, and therapy efficacy evaluations are important points of focus. Healthcare providers may use this abundance of data to tailor treatment plans, identify high-risk patient populations, and forecast disease trajectories by applying machine learning algorithms and predictive analytics. Better patient outcomes, more efficient use of resources, and early treatments are made possible by this proactive strategy. Furthermore, data mining techniques act as catalysts to reveal complex relationships between apparently unrelated data pieces, providing enhanced insights into the cause of disease, genetic susceptibilities, and environmental factors. Healthcare practitioners can get practical insights that guide disease prevention, customized patient counseling, and focused therapies by analyzing these associations. The abstract explores the problems and ethical issues that come with using data mining techniques in the healthcare industry. In order to properly use these approaches, it is essential to find a balance between data privacy, security issues, and the interpretability of complex models. Finally, this abstract demonstrates the revolutionary power of modern data mining methodologies in transforming the healthcare sector. Healthcare practitioners and researchers can uncover unique insights, enhance clinical decision-making, and ultimately elevate patient care to unprecedented levels of precision and efficacy by employing cutting-edge methodologies.

Keywords: data mining, healthcare, patient care, predictive analytics, precision medicine, electronic health records, machine learning, predictive modeling, disease prognosis, risk stratification, treatment efficacy, genetic profiles, precision health

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Authors: Maria Sonto Maputle, Rhulani C. Shihundla, Rachel T. Lebese

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Background: Patients’ information must be complete and accurately documented in order to foster quality and continuity of care. The multidisciplinary health care members use patients’ documentation to communicate about health status, preventive health services, treatment, planning and delivery of care. The purpose of this study was to determine the practice of nursing documentation of patients’ information at selected Primary Health Care (PHC) facilities in Vhembe District, Limpopo Province, South Africa. Methods: The research approach adopted was qualitative while exploratory and descriptive design was used. The study was conducted at selected PHC facilities. Population included twelve professional nurses. Non-probability purposive sampling method was used to sample professional nurses who were willing to participate in the study. The criteria included participants’ whose daily work and activities, involved creating, keeping and updating nursing documentation of patients’ information. Qualitative data collection was through unstructured in-depth interviews until no new information emerged. Data were analysed through open–coding of, Tesch’s eight steps method. Results: Following data analysis, it was found that professional nurses’ had knowledge deficit related to insufficient training on updates and rendering multiple services daily had negative impact on accurate documentation of patients’ information. Conclusion: The study recommended standardization of registers, books and forms used at PHC facilities, and reorganization of PHC services into open day system.

Keywords: documentation, knowledge, patient care, patient’s information, training

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Authors: Shiva Shakori Poshteh

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Lung cancer is a highly prevalent and devastating disease, representing a significant global health concern with profound implications for healthcare systems and society. Its high incidence, mortality rates, and late-stage diagnosis contribute to its formidable nature. To address these challenges, nanoparticle-based drug delivery has emerged as a promising therapeutic strategy. Curcumin (CUR), a natural compound derived from turmeric, has garnered attention as a potential nanomedicine for lung cancer treatment. Nanoparticle formulations of CUR offer several advantages, including improved drug delivery efficiency, enhanced stability, controlled release kinetics, and targeted delivery to lung cancer cells. CUR exhibits a diverse array of effects on cancer cells. It induces apoptosis by upregulating pro-apoptotic proteins, such as Bax and Bak, and downregulating anti-apoptotic proteins, such as Bcl-2. Additionally, CUR inhibits cell proliferation by modulating key signaling pathways involved in cancer progression. It suppresses the PI3K/Akt pathway, crucial for cell survival and growth, and attenuates the mTOR pathway, which regulates protein synthesis and cell proliferation. CUR also interferes with the MAPK pathway, which controls cell proliferation and survival, and modulates the Wnt/β-catenin pathway, which plays a role in cell proliferation and tumor development. Moreover, CUR exhibits potent antioxidant activity, reducing oxidative stress and protecting cells from DNA damage. Utilizing CUR as a standalone treatment is limited by poor bioavailability, lack of targeting, and degradation susceptibility. Nanoparticle-based delivery systems can overcome these challenges. They enhance CUR’s bioavailability, protect it from degradation, and improve absorption. Further, Nanoparticles enable targeted delivery to lung cancer cells through surface modifications or ligand-based targeting, ensuring sustained release of CUR to prolong therapeutic effects, reduce administration frequency, and facilitate penetration through the tumor microenvironment, thereby enhancing CUR’s access to cancer cells. Thus, nanoparticle-based CUR delivery systems promise to improve lung cancer treatment outcomes. This article provides an overview of lung cancer, explores CUR nanoparticles as a treatment approach, discusses the benefits and challenges of nanoparticle-based drug delivery, and highlights prospects for CUR nanoparticles in lung cancer treatment. Future research aims to optimize these delivery systems for improved efficacy and patient prognosis in lung cancer.

Keywords: lung cancer, curcumin, nanomedicine, nanoparticle-based drug delivery

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Authors: Angga Hidayah Ramadhan, Luciana Andrawina, M. Azani Hasibuan

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Data will be as a core of the decision if it has a good treatment or process, which is process that data into information, and information into knowledge to make a wisdom or decision. Today, many companies have not realize it include XYZ University Admission Directorate as executor of National Admission called Seleksi Masuk Bersama (SMB) that during the time, the workers only uses their feeling to make a decision. Whereas if it done, then that company can analyze the data to make a right decision to get a pin sales from student candidate or registrant that follow SMB as many as possible. Therefore, needs Knowledge Management System (KMS) with Geographic Information System (GIS) use 5C4C that can process that company data becomes more useful and can help make decisions. This information system can process data into information based on the pin sold data with 5C (Contextualized, Categorize, Calculation, Correction, Condensed) and convert information into knowledge with 4C (Comparing, Consequence, Connection, Conversation) that has been several steps until these data can be useful to make easier to take a decision or wisdom, resolve problems, communicate, and quicker to learn to the employees have not experience and also for ease of viewing/visualization based on spatial data that equipped with GIS functionality that can be used to indicate events in each province with indicator that facilitate in this system. The system also have a function to save the tacit on the system then to be proceed into explicit in expert system based on the problems that will be found from the consequences of information. With the system each team can make a decision with same ways, structured, and the important is based on the actual event/data.

Keywords: 5C4C, data, information, knowledge

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Authors: Meriche Hacene

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Introduction: Celiac disease (CD) is a chronic immune-mediated enteropathy triggered by gluten found in wheat or oats or rye. Celiac disease is associated with the HLA-DQ2 and HLA-DQ8 susceptibility alleles. This association with the HLA DQ2/DQ8 molecules confirmed the responsibility of genetic factors that intervene in the triggering of the autoimmune process of this condition. Objective: To evaluate the results of HLA DQ2 and HLA DQ8 typing of 40 patients suspected of having CD by PCR-SSP (Polymerase Chain Reaction Sequence Specific Primers). Material and method : 40 patients suspected of celiac disease with IgA transglutaminase serology (-) and duodenal biopsy (+). HLADR/DQ PCR-SSP (fluogen-innotrain) typing was carried out. Results : The average age of adults was 40 years, children: 4 years, the sex ratio was 1M/3F. In our patients the HLA DQ2 allele is found with a frequency of 75%, the DQ8 with a frequency of 25%, 17.5% were HLA-DQ2 homozygous and 15% were HLADQ2/HLADQ8. In our series, HLADQ2, DQ8 are found in almost all patients with a frequency of 95%. 30% of patients in our study had associated positivity of HLA-DRB3, DRB4 or DRB5 alleles. Conclusion : A high prevalence of positivity of HLADQ2 alleles at the expense of HLA DQ8 was found, which is consistent with literature data. These molecules constitute an additional marker for screening and diagnosis of CD.

Keywords: HLA typing, coeliac disease, HLA DQ 2, HLA DQ8

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Authors: Sadegh Marzban, Mohamad Sobhan Sheikh Andalibi, Farnaz Ghassemi, Farzad Towhidkhah

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Parkinson's disease (PD), which is characterized by the tremor at rest, rigidity, akinesia or bradykinesia and postural instability, affects the quality of life of involved individuals. The concept of a fractal is most often associated with irregular geometric objects that display self-similarity. Fractal dimension (FD) can be used to quantify the complexity and the self-similarity of an object such as tremor. In this work, we are aimed to propose a new method for evaluating hyperkinetic movements such as tremor, by using the FD and other correlated parameters in patients who are suffered from PD. In this study, we used 'the tremor data of Physionet'. The database consists of fourteen participants, diagnosed with PD including six patients with high amplitude tremor and eight patients with low amplitude. We tried to extract features from data, which can distinguish between patients before and after medication. We have selected fractal dimensions, including correlation dimension, box dimension, and information dimension. Lilliefors test has been used for normality test. Paired t-test or Wilcoxon signed rank test were also done to find differences between patients before and after medication, depending on whether the normality is detected or not. In addition, two-way ANOVA was used to investigate the possible association between the therapeutic effects and features extracted from the tremor. Just one of the extracted features showed significant differences between patients before and after medication. According to the results, correlation dimension was significantly different before and after the patient's medication (p=0.009). Also, two-way ANOVA demonstrates significant differences just in medication effect (p=0.033), and no significant differences were found between subject's differences (p=0.34) and interaction (p=0.97). The most striking result emerged from the data is that correlation dimension could quantify medication treatment based on tremor. This study has provided a technique to evaluate a non-linear measure for quantifying medication, nominally the correlation dimension. Furthermore, this study supports the idea that fractal dimension analysis yields additional information compared with conventional spectral measures in the detection of poor prognosis patients.

Keywords: correlation dimension, non-linear measure, Parkinson’s disease, tremor

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Authors: Mohammed R. Elkobaisi, Abdelsalam Maatuk

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The search engines are the large scale information retrieval tools from the Web that are currently freely available to all. This paper explains how to convert the raw resulted number of search engines into useful information. This represents a new method for data gathering comparing with traditional methods. When a query is submitted for a multiple numbers of keywords, this take a long time and effort, hence we develop a user interface program to automatic search by taking multi-keywords at the same time and leave this program to collect wanted data automatically. The collected raw data is processed using mathematical and statistical theories to eliminate unwanted data and converting it to usable data.

Keywords: search engines, information extraction, agent system

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Authors: Fakhr Eddin Alnaal, Angela Dahdal, Duaa Aladib, Sabeen Ibrahim, Ibrahim Ghoraibi, Bissan Ahmed

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Dementia is one of the diseases which had several stages and Alzheimer’s term was selected in respect for the first doctor Alzheimer who defined the first symptoms of this diseases in a woman whom was well treated by him. The fact that this is a type of a silent disease on which you have a long-term process of neurological degradation and suddenly gives symptoms which are most often irreversible, on clinical level likely we can consider it as a malignancy, one in terms of that it is sudden shocking irreversible and on the level of behavior and some mortality beside the lack of early detection tools for diagnosis. Therefore, the goal of our project is to test the concept of the ability of Statin in prevention of such disease and we investigated that both on experimental level and most importantly on clinical one, the clinical part was performed in a recognized house of aged people who had accidently a high cholesterol and were for years given Statin to treat that elevation, however after the symptoms of Alzheimer’s appeared and when diagnosed, they were well treated and rapidly recovered compared to Alzheimer’s patients in the same house who did not receive Statin had a mild improvement in their symptoms after the therapy, on the other hand we confirmed such observation by a well-organized experimental work.

Keywords: Alzheimer's, dementia, silent disease, statin

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Authors: Oya Bulut, Oguzhan Avci, Zafer Bulut, Atilla Simsek

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Livestock breeders have focused on the improvement of production traits with little or no attention for improvement of disease resistance traits. In order to determine the association between the genetic structure of the individual gene loci with possibility of the occurrence and the development of diseases, MHC (major histocompatibility complex) are frequently used. Because of their importance in the immune system, MHC locus is considered as candidate genes for resistance/susceptibility against to different diseases. Major histocompatibility complex (MHC) molecules play a critical role in both innate and adaptive immunity and have been considered candidate molecular markers of an association between polymorphisms and resistance/susceptibility to diseases. The purpose of this study is to give some information about MHC genes become an important area of study in recent years in terms of animal husbandry and determine the relation between MHC genes and resistance/susceptibility to disease.

Keywords: MHC, polymorphism, disease, resistance

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Authors: Oluyemi Christianah Ojo

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This study seeks to investigate the quality of ICT provided in the new Caring Heart schools in Ondo State, Nigeria. The population for the study was all caring Heart Mega Schools in Ondo State, Nigeria. Research questions were generated; two instruments CCCMS and TQCUC were used to elicit information from the schools and the teachers. The study adopts descriptive survey approach. The studies revealed and concluded that ICT components were available and adequate in these schools, Charts showing ICT components and other forms of computer devices used as instructional materials were available but were not adequate; teachers teaching computer studies are competent in the delivery of instructions and in handling computer gadgets in the laboratory. The study recommended the provision of steady electricity, uninterrupted internet facilities and provision of adequate ICT components and charts for effective teaching delivery and learning.

Keywords: facilities, information communication technology, mega primary school, primary education

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Authors: H. Parameshwar Naik, Shripad Kulkarni

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Powdery mildew is a serious disease among the fungal in high humid areas with varied temperature conditions. In recent days disease becomes very severe due to uncertain weather conditions and unique character of the disease is, it produces white mycelia growth on upper and lower leaf surfaces and in severe conditions it leads to defoliation. Results of the experiment revealed that sowing of crop in the I fortnight (FN) of July recorded the minimum mean disease severity (7.96 %) followed by crop sown in II FN of July (13.19 %) as against the crop sown in II FN of August (41.44 %) and I FN of September (33.78 %) and the I fortnight of October (33.77 %). In the first date of sowing infection started at 45 DAS and progressed till 73 DAS and it was up to 14.66 Percent and in second date of sowing disease progressed up to 22.66 percent and in the third date of sowing, it was up to 59.35 percent. Afterward, the disease started earlier and progressed up to 66.15 percent and in sixth and seventh date of sowing disease progressed up to 43.15 percent and 59.85 percent respectively. Disease progress is very fast after 45 days after sowing and highest disease incidence was noticed at 73 DAS irrespective of dates of sowing. From the results of the present study, it is very clear that disease development will be very high if crop sown in between 1st fortnight of August and the 1st fortnight of September.

Keywords: cucumber, India, Karnataka, powdery mildew

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Authors: Shao-Hsuan Chien, Ju-Hui Fu

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Parkinson’s disease (PD) is a degenerative disorder of the central nervous system that is characterized by progressive loss of dopaminergic neurons in the substantia nigra pars compacta and motor impairment. Aggregation of α-synuclein in neuronal cells plays a key role in this disease. At present, therapeutics for PD provides moderate symptomatic benefit but is not able to delay the development of this disease. Current efforts for the treatment of PD are to identify new drugs that show slow or arrest progressive course of PD by interfering with a disease-specific pathogenetic process in PD patients. Maackiain is a bioactive compound isolated from the roots of the Chinese herb Sophora flavescens. The purpose of the present study was to assess the potential for maackiain to ameliorate PD in Caenorhabditis elegans models. Our data reveal that maackiain prevents α-synuclein accumulation in the transgenic Caenorhabditis elegans model and also improves dopaminergic neuron degeneration, food-sensing behavior, and life-span in 6-hydroxydopamine-induced Caenorhabditis elegans model, thus indicating its potential as a candidate antiparkinsonian drug.

Keywords: maackiain, Parkinson’s disease, dopaminergic neurons, α-Synuclein

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Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, speech emotion recognition, longitudinal biomarker, machine learning

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Authors: Le Jiang, Chua Jinxing

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Introduction: The recent outbreak of Ebola virus disease in the west Africa has drawn global concern. With a high fatality rate and direct human-to-human transmission, it has spread between countries and caused great damages for patients and family who are affected. Being the designated hospital to manage epidemic outbreak in Singapore, Tan Tock Seng Hospital (TTSH) is facing great challenges in preparation and managing of potential outbreak of emerging infectious disease such as Ebola virus disease. Aim: We conducted an infection control drill in TTSH emergency department to assess the readiness of healthcare and allied health workers in managing suspected Ebola patients. It also helps to review current Ebola clinical protocol and work instruction to ensure more smooth and safe practice in managing Ebola patients in TTSH emergency department. Result: General preparedness level of staffs involved in managing Ebola virus disease in TTSH emergency department is not adequate. Knowledge deficits of staffs on Ebola personal protective equipment gowning and degowning process increase the risk of potential cross contamination in patient care. Loopholes are also found in current clinical protocol, such as unclear instructions and inaccurate information, which need to be revised to promote better staff performance in patient management. Logistic issues such as equipment dysfunction and inadequate supplies can lead to ineffective communication among teams and causing harm to patients in emergency situation. Conclusion: The infection control drill identified the need for more well-structured and clear clinical protocols to be in place to promote participants performance. In addition to quality protocols and guidelines, systemic training and annual refresher for all staffs in the emergency department are essential to prepare staffs for the outbreak of Ebola virus disease. Collaboration and communication with allied health staffs are also crucial for smooth delivery of patient care and minimising the potential human suffering, properties loss or injuries caused by disease. Therefore, more clinical drills with collaboration among various departments involved are recommended to be conducted in the future to monitor and assess readiness of TTSH emergency department in managing Ebola virus disease.

Keywords: ebola, emergency department, infection control drill, Tan Tock Seng Hospital

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Authors: Saeedeh Ahmadi Basir, Mohammad Mahdavi Mazdeh, Mohammad Namakshenas

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Manufacturers often dispatch jobs in batches to reduce delivery costs. However, sending several jobs in batches can have a negative effect on other scheduling-related objective functions such as minimizing the number of tardy jobs which is often used to rate managers’ performance in many manufacturing environments. This paper aims to minimize the number of weighted tardy jobs and the sum of delivery costs of a two-stage assembly flow-shop problem in a batch delivery system. We present a mixed-integer linear programming (MILP) model to solve the problem. As this is an MILP model, the commercial solver (the CPLEX solver) is not guaranteed to find the optimal solution for large-size problems at a reasonable amount of time. We present several numerical examples to confirm the accuracy of the model.

Keywords: scheduling, two-stage assembly flow-shop, tardy jobs, batched delivery system

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Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

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Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, S. Meenakshi Sundaram

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Alzheimer’s disease is one of the prevalent kind of ailment, expected for impudent reconciliation or an effectual therapy is to be accredited hitherto. Probable detonation of patients in the upcoming years, and consequently an enormous deal of apprehension in early discovery of the disorder, this will conceivably chaperon to enhanced healing outcomes. Complex impetuosity of the brain is an observant symbolic of the disease and a unique recognition of genetic sign of the disease. Machine learning alongside deep learning and decision tree reinforces the aptitude to absorb characteristics from multi-dimensional data’s and thus simplifies automatic classification of Alzheimer’s disease. Susceptible testing was prophesied and realized in training the prospect of Alzheimer’s disease classification built on machine learning advances. It was shrewd that the decision trees trained with deep neural network fashioned the excellent results parallel to related pattern classification.

Keywords: Alzheimer's diagnosis, decision trees, deep neural network, machine learning, pattern classification

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Authors: Marinna Madrid, Nabiha Saklayen, Marinus Huber, Nicolas Vogel, Christos Boutopoulos, Michel Meunier, Eric Mazur

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Delivering material into cells is important for a diverse range of biological applications, including gene therapy, cellular engineering and imaging. We present a plasmonic substrate for delivering membrane-impermeable material into cells at high throughput and high efficiency while maintaining cell viability. The substrate fabrication is based on an affordable and fast colloidal self-assembly process. When illuminated with a femtosecond laser, the light interacts with the electrons at the surface of the metal substrate, creating localized surface plasmons that form bubbles via energy dissipation in the surrounding medium. These bubbles come into close contact with the cell membrane to form transient pores and enable entry of membrane-impermeable material via diffusion. We use fluorescence microscopy and flow cytometry to verify delivery of membrane-impermeable material into HeLa CCL-2 cells. We show delivery efficiency and cell viability data for a range of membrane-impermeable cargo, including dyes and biologically relevant material such as siRNA. We estimate the effective pore size by determining delivery efficiency for hard fluorescent spheres with diameters ranging from 20 nm to 2 um. To provide insight to the cell poration mechanism, we relate the poration data to pump-probe measurements of micro- and nano-bubble formation on the plasmonic substrate. Finally, we investigate substrate stability and reusability by using scanning electron microscopy (SEM) to inspect for damage on the substrate after laser treatment. SEM images show no visible damage. Our findings indicate that self-assembled plasmonic substrates are an affordable tool for high-throughput, high-efficiency delivery of material into mammalian cells.

Keywords: femtosecond laser, intracellular delivery, plasmonic, self-assembly

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Authors: Agi Sunday

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A descriptive analysis of reported cases of sickle cell disease and the level of awareness about genetic counselling in 30 hospitals were carried out. Additionally, 150 individuals between ages 16-45 were randomly selected for evaluation of genetic counselling awareness. The main tools for this study were questionnaires which were taken to hospitals, and individuals completed the others. The numbers of reported cases of sickle cell disease recorded in private, public and teaching hospitals were 14 and 57; 143 and 89; 272 and 57 for the periods of 1995-2000 and 2001-2005, respectively. A general informal genetic counselling took place mostly in the hospitals visited. 122 (86%) individuals had the knowledge of genetic disease and only 43 (30.3%) individuals have been exposed to genetic counselling. 64% of individuals agreed that genetic counselling would help in the prevention of genetic disease.

Keywords: sickle disease, genetic counseling, genetic testing, advocacy

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Authors: Melkamu A., Woldu B., Sitotaw C., Seyoum M., Aynalem M.

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Background: Liver disease is any condition that affects the liver cells and their function. It is directly linked to coagulation disorders since most coagulation factors are produced by the liver. Therefore, this study aimed to assess the magnitude and associated factors of coagulation abnormalities among liver disease patients. Methods: A cross-sectional study was conducted from August to October 2022 among 307 consecutively selected study participants at the University of Gondar Comprehensive Specialized Hospital. Sociodemographic and clinical data were collected using a structured questionnaire and data extraction sheet, respectively. About 2.7 mL of venous blood was collected and analyzed by the Genrui CA51 coagulation analyzer. Data was entered into Epi-data and exported to STATA version 14 software for analysis. The finding was described in terms of frequencies and proportions. Factors associated with coagulation abnormalities were analyzed by bivariable and multivariable logistic regression. Result: In this study, a total of 307 study participants were included. Of them, the magnitude of prolonged Prothrombin Time (PT) and Activated Partial Thromboplastin Time (APTT) were 68.08% and 63.51%, respectively. The presence of anemia (AOR = 2.97, 95% CI: 1.26, 7.03), a lack of a vegetable feeding habit (AOR = 2.98, 95% CI: 1.42, 6.24), no history of blood transfusion (AOR = 3.72, 95% CI: 1.78, 7.78), and lack of physical exercise (AOR = 3.23, 95% CI: 1.60, 6.52) were significantly associated with prolonged PT. While the presence of anaemia (AOR = 3.02; 95% CI: 1.34, 6.76), lack of vegetable feeding habit (AOR = 2.64; 95% CI: 1.34, 5.20), no history of blood transfusion (AOR = 2.28; 95% CI: 1.09, 4.79), and a lack of physical exercise (AOR = 2.35; 95% CI: 1.16, 4.78) were significantly associated with abnormal APTT. Conclusion: Patients with liver disease had substantial coagulation problems. Being anemic, having a transfusion history, lack of physical activity, and lack of vegetables showed significant association with coagulopathy. Therefore, early detection and management of coagulation abnormalities in liver disease patients are critical.

Keywords: coagulation, liver disease, PT, Aptt

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Authors: Nipun Agarwal, David Paul, Fareed Un Din

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Every organization develops a strategy that needs to be implemented and is undertaken through project delivery. In essence, project requirements should exactly replicate an organization’s strategy. In reality this does not happen, and behavioral factors deviate the project delivery from the strategic objectives. This occurs as project stakeholders can have competing objectives. Resultantly, requirements that are implemented through projects are less aligned to the strategy. This paper develops a game theoretic model to simulate why such deviations occur. That explains the difference between strategy development and implementation.

Keywords: strategy, simulation, project management, game theory

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Authors: Sabine Pau, Sophia Volz, Emanuel Bauer, Amelie De Gregorio, Frank Reister, Wolfgang Janni, Florian Ebner

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Purpose: The umbilical cord pH is a well evaluated contributor for prediction of neonatal outcome. This study correlates nenonatal umbilical cord pH with the weekday of delivery, the time of birth as well as the staff hand over times (midwifes and doctors). Material and Methods: This retrospective study included all deliveries of a 20 year period (1994-2014) at our primary obstetric center. All deliveries with a newborn cord pH under 7,20 were included in this analysis (6929 of 48974 deliveries (14,4%)). Further subgroups were formed according to the pH (< 7,05; 7,05 – 7,09; 7,10 – 7,14; 7,15 – 7,19). The data were then separated in day- and night time (8am-8pm/8pm-8am) for a first analysis. Finally, handover times were defined at 6 am – 6.30 am, 2 pm -2.30 pm, 10 pm- 10.30 pm (midwives) and for the doctors 8-8.30 am, 4 – 4.30 pm (Monday- Thursday); 2 pm -2.30 pm (Friday) and 9 am – 9.30 am (weekend). Routinely a shift consists of at least three doctors as well as three midwives. Results: During the last 20 years, 6929 neonates were born with an umbilical cord ph < 7,20 ( < 7,05 : 7,1%; 7,05 – 7,09 : 10,9%; 7,10 – 7,14 : 30,2%; 7,15 – 7,19:51,8%). There was no significant difference between either night/day delivery (p = 0.408), delivery on different weekdays (p = 0.253), delivery between Monday to Thursday, Friday and the weekend (p = 0.496 ) or delivery during the handover times of the doctors as well as the midwives (p = 0.221). Even the standard deviation showed no differences between the groups. Conclusion: Despite an increased workload over the last 20 years, the standard of care remains high even during the handover times and night shifts. This applies for midwives and doctors. As the neonatal outcome depends on various factors, further studies are necessary to take more factors influencing the fetal outcome into consideration. In order to maintain this high standard of care, an adaption of work-load and changing conditions is necessary.

Keywords: delivery, fetal umbilical cord pH, day time, hand over times

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Authors: Jonathan Turner, Julie Doyle, Laura O’Philbin, Dympna O’Sullivan

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People living with dementia should be at the centre of decision-making regarding goals for daily living. These goals include basic activities (dressing, hygiene, and mobility), advanced activities (finances, transportation, and shopping), and meaningful activities that promote well-being (pastimes and intellectual pursuits). However, there is limited involvement of people living with dementia in the design of technology to support their goals. A project is described that is co-designing intelligent computer-based support for, and with, people affected by dementia and their carers. The technology will support self-management, empower participation in shared decision-making with carers and help people living with dementia remain healthy and independent in their homes for longer. It includes information from the patient’s care plan, which documents medications, contacts, and the patient's wishes on end-of-life care. Importantly for this work, the plan can outline activities that should be maintained or worked towards, such as exercise or social contact. The authors discuss how to integrate care goal information from such a care plan with data collected from passive sensors in the patient’s home in order to deliver individualized planning and interventions for persons with dementia. A number of scientific challenges are addressed: First, to co-design with dementia patients and their carers computerized support for shared decision-making about their care while allowing the patient to share the care plan. Second, to develop a new and open monitoring framework with which to configure sensor technologies to collect data about whether goals and actions specified for a person in their care plan are being achieved. This is developed top-down by associating care quality types and metrics elicited from the co-design activities with types of data that can be collected within the home, from passive and active sensors, and from the patient’s feedback collected through a simple co-designed interface. These activities and data will be mapped to appropriate sensors and technological infrastructure with which to collect the data. Third, the application of machine learning models to analyze data collected via the sensing devices in order to investigate whether and to what extent activities outlined via the care plan are being achieved. The models will capture longitudinal data to track disease progression over time; as the disease progresses and captured data show that activities outlined in the care plan are not being achieved, the care plan may recommend alternative activities. Disease progression may also require care changes, and a data-driven approach can capture changes in a condition more quickly and allow care plans to evolve and be updated.

Keywords: care goals, decision-making, dementia, self-care, sensors

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Authors: H.C. Chen, S. W. C. Chan, K. Cheng, A. Vathsala, H. K. Sran, H. He

Abstract:

Background: End-stage renal disease (ESRD) is the last stage of chronic kidney disease. The numbers of patients with ESRD have increased worldwide due to the growing number of aging, diabetes and hypertension populations. Patients with ESRD suffer from physical illness and psychological distress due to complex treatment regimens, which often affect the patients’ social and psychological functioning. As a result, the patients may fail to perform daily self-care and self-management, and consequently experience worsening conditions. Aims: The study aims to examine the effectiveness of a self-efficacy psychoeducational programme on primary outcome (self-efficacy) and secondary outcomes (psychological wellbeing, treatment adherence, and quality of life) in patients with ESRD and haemodialysis in Singapore. Methodology: A randomised controlled, two-group pretest and repeated posttests design will be carried out. A total of 154 participants (n=154) will be recruited. The participants in the control group will receive a routine treatment. The participants in the intervention group will receive a self-efficacy psychoeducational programme in addition to the routine treatment. The programme is a two-session of educational intervention in a week. A booklet, two consecutive sessions of face-to-face individual education, and an abdominal breathing exercise are adopted in the programme. Outcome measurements include Dialysis Specific Self-efficacy Scale, Kidney Disease Quality of Life- 36 Hospital Anxiety and Depression Scale, Renal Adherence Attitudes Questionnaire and Renal Adherence Behaviour Questionnaire. The questionnaires will be used to measure at baseline, 1- and 3- and 6-month follow-up periods. Process evaluation will be conducted with a semi-structured face to face interview. Quantitative data will be analysed using SPSS21.0 software. Qualitative data will be analysed by content analysis. Significance of the study: This study will identify a clinically useful and potentially effective approach to help patients with end-stage renal disease and haemodialysis by enhancing their self-efficacy in self-care behaviour, and therefore improving their psychological wellbeing, treatment adherence and quality of life. This study will provide information to develop clinical guidelines to improve patients’ disease self-management and to enhance health-related outcomes. Hopefully it will help reducing disease burden.

Keywords: end-stage renal disease (ESRD), haemodialysis, psychoeducation, self-efficacy

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Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

Abstract:

Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: Harshadkumar Rajgor, Jeff Butterworth

Abstract:

Background: Barretts oesophagus increases the risk of developing oesophageal adenocarcinoma. Over the last 40 years, there has been a 6 fold increase in the incidence of oesophageal adenocarcinoma in the western world and the incidence rates are increasing at a greater rate than cancers of the colon, breast and lung. Endoscopic mucosal resection (EMR) is a relatively new technique being used by 2 centres in the greater midlands cancer network. EMR can be used for curative or staging purposes, for high-grade dysplasia’s and T1 tumours of the oesophagus. EMR is also suitable for those who are deemed high risk for oesophagectomy. EMR has a recurrence rate of 21% according to the Wiesbaden data. Method: A retrospective study of prospectively collected data was carried out involving 24 patients who had EMR for curative or staging purposes. Complications of residual or recurrent disease following EMR that required further treatment were investigated. Results: In 54% of cases residual or recurrent disease was suspected. 96% of patients were given clear and concise information regarding their diagnosis of high-grade dysplasia or T1 tumours. All 24 patients consulted the same specialist healthcare team. Conclusion: EMR is a safe and effective treatment for patients who have high-grade dysplasia and T1NO tumours. In 54% of cases residual or recurrent disease was suspected. Initially, only single resections were undertaken. Multiple resections are now being carried out to reduce the risk of recurrence. Complications from EMR remain low in this series and consisted of a single episode of post procedural bleeding.

Keywords: endoscopic mucosal resection, oesophageal dysplasia, T1 tumours, cancer network

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Authors: Isaac Kofi Mensah

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Governments around the world are adopting Information and Communication Technologies (ICTs) because of the important opportunities it provides through E-government (EG) to modernize government public administration processes and delivery of quality and efficient public services. Almost every country in the world is adopting ICT in its public sector administration (EG) to modernize and change the traditional process of government, increase citizen engagement and participation in governance, as well as the provision of timely information to citizens. This paper, therefore, seeks to present the adoption, development and implementation of EG in regions globally, as well as the ICT indicators around the world, which are making EG initiatives successful. Europe leads the world in its EG adoption and development index, followed by the Americas, Asia, Oceania and Africa. There is a gradual growth in ICT indicators in terms of the increase in Internet access and usage, increase in broadband penetration, an increase of individuals using the Internet at home and a decline in fixed telephone use, while the mobile cellular phone has been on the increase year-on-year. Though the lack of ICT infrastructure is a major challenge to EG adoption and implementation around the world, in Africa it is very pervasive, hampering the expansion of Internet access and provision of broadband, and hence is a barrier to the successful adoption, development, and implementation of EG initiatives in countries on the continent. But with the general improvement and increase in ICT indicators around the world, it provides countries in Europe, Americas, Asia, Arab States, Oceania and Africa with the huge opportunity to enhance public service delivery through the adoption of EG. Countries within these regions cannot fail their citizens who desire to enjoy an enhanced and efficient public service delivery from government and its many state institutions.

Keywords: e-government development index, e-government, indicators, information and communication technologies (ICTs)

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Authors: H. Shola Adeosun, F. Ajoke Adebiyi

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This study appraises the impact of television on the coverage of Lassa Fever disease. The objectives of the study are to find out whether television is an effective tool for raising awareness about Lassa fever shapes the perception of members of the public. The research work was based on the theoretical foundation of Agenda – setting and reinforcement theory. Survey research method was adopted in the study to elicit data from the residents of Obafemi Owode Local Government, area of Ogun state. Questionnaire and oral interview were adopted as a tool for data gathering. Simple random sampling techniques were used to draw a sample for this study. Out of filled 400 questionnaires distributed to the respondents. 37 of them were incorrectly filled and returned at the stipulated time. This is about (92.5% Tables, percentages, and figures were used to analyse and interpret the data and hypothesis formulation for this study revealed that Lassa fever diseases with higher media coverage were considered more serious and more representative of a disease and estimated to have lower incidents, than diseases less frequently found in the media. Thus, 92% of the respondents agree that they have access to television coverage of Lassa fever disease led to exaggerated perceptions of personal vulnerability. It, therefore, concludes that there is a need for relevant stakeholders to ensure better community health education and improved housing conditions in southwestern Nigeria, with an emphasis on slum areas and that Nigeria need to focus on the immediate response, while preparing for the future because a society or community is all about the people who inhabit. Therefore every effort must be geared towards their society and survival.

Keywords: impact, television, coverage, Lassa fever disease

Procedia PDF Downloads 189

Authors: Sanaz Kavianpour, Zuraini Ismail, Bharanidharan Shanmugam

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Social Network Sites (SNSs) can be served as an invaluable platform to transfer the information across a large number of individuals. A substantial component of communicating and managing information is to identify which individual will influence others in propagating information and also whether dissemination of information in the absence of social signals about that information will be occurred or not. Classifying the final audience of social data is difficult as controlling the social contexts which transfers among individuals are not completely possible. Hence, undesirable information diffusion to an unauthorized individual on SNSs can threaten individuals’ privacy. This paper highlights the information diffusion in SNSs and moreover it emphasizes the most significant privacy issues to individuals of SNSs. The goal of this paper is to propose a privacy-preserving model that has urgent regards with individuals’ data in order to control availability of data and improve privacy by providing access to the data for an appropriate third parties without compromising the advantages of information sharing through SNSs.

Keywords: anonymization algorithm, classification algorithm, information diffusion, privacy, social network sites

Procedia PDF Downloads 291