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Circulatory Cathelicidin Levels' Predictive Value for Pediatric Community-Acquired Pneumonia Without COVID-19
Get PDF: Background: Community-acquired pneumonia (CAP), one of the most common infectious diseases, is the third leading cause of death worldwide. To stop the spread of serious sickness and keep the initial infection under control, the innate immune response is crucial. Cathelicidin, a potent antimicrobial peptide that may kill germs directly and alter the immune system's response to infection, is an essential component of this response. The main goal of the study is to investigate the association between CaLL37 and the severity of CAP in young patients. Methodology: 120 CAP cases and 165 controls made comprised the 285 participants in this case-control study, whose ages varied from 1 to 18 months. Calculated and compared cathelicidin levels for CAP and control participants as well as the pneumonia-causing agent. People who were thought to have COVID-19 CAP were excluded. Results: The participants' mean age was 9.7 (range of 1 to 18) months. In 46.2%, 35%, and 18.8% of cases of CAP; bacterial, viral, and mixed causative agents, respectively, were detected. Among the individuals, only 6.8% received mixed feeding, compared to 42.1% who used artificial feeding and 51.1% who exclusively breastfed. The mean total serum contained 8.6 ±6.7 ng\ml of CaLL37. CaLL37 serum levels were comparable between the two study groups (p>0.05). The levels of CaLL37 were comparable (p>0.05) among patients with CAP when compared according to the causative agents, while plasma CaLL37 levels were higher among babies on artificial feeding (p-0.001). The ROC assays revealed that CaLL37 plasma levels were unable to differentiate between bacterial and viral pneumonia or between persons who had pneumonia and healthy subjects. However, the CaLL37 can discriminate between infants who are breastfed and those who are fed by a bottle considerably (p-0.001, AUC=0.748, sensitivity=0.673, specificity=0.637, and 95%CI of o.675 - 0.820). Conclusion: According to the study, CaLL37 is capable of determining the difference between infants who are breastfed and those who are fed artificially. However, it is difficult for cathelicidin to distinguish between various CAP causes as well as between CAP patients and healthy controls
Towards A Design Approach to Achieve Environmental Safety in Diagnostic and Therapeutic Units in Hospitals Using Nanotechnology
Get PDFIn The environmental safety was investigated in this study, with an initial focus on defining the general concept of environmental safety. Subsequently, the study delved into the environmental safety within hospitals, particularly in diagnostic and treatment spaces. Air pollutants and their types were examined, along with permissible levels, emphasizing the adverse effects of increased pollutants on human health. Additionally, attention was given to the physical hazards within these spaces, such as temperature, noise, and lighting. In the context of studying diagnostic and treatment spaces in hospitals, a review was conducted on the currently used traditional finishing materials and an evaluation of their harmful effects. The concept of "sick buildings" and its impact on human safety was also explored. The study placed a particular emphasis on nanotechnology and how nano-materials can be employed to mitigate the detrimental effects of non-compliant "sick buildings" with environmental safety standards. Global examples of nano-applications were analyzed, along with an examination of a hospital in Egypt that utilizes nano-technology in its glass structure. Furthermore, a simulation was performed on a local hospital to measure the difference in carbon dioxide emission within the space. This comparison was conducted between the current state of the building using traditional finishing materials and the scenario where nano-alternatives are employed in the glass and thermal insulation of exterior walls
Analysis Of Stock Prediction Parameters and Their Impact on Effective Selection Of Stock
No full textStock value prediction is a multi-disciplinary field which requires efficient knowledge about the stock’s historic values, its news feeds, twitter sentiments, impact of global stock market(s) on the stock, etc. In order to effectively analyse a stock’s trend for inter-day, intra-day or long term, analysists have to evaluate these values on a continuous basis. Along with these values analysists also have to analyse non-stock data like recent news about the company, management changes in the company, tweets related to the company, global news & global stock market trends which affect the company in any way possible. Each of these data sources have a different effect on the stock’s value change, and it is recommended for a good stock prediction system to analyse the effects of these values before real-time deployment. Neglecting even a single parameter before deployment of the stock prediction system might result into a multitude of prediction errors. For instance, if twitter feeds for a stock are not considered during prediction of a nicely performing stock, and suddenly some news about a product fail comes online, then the stock prices might plummet, and the system will not be able to track it. In order to reduce the effect of these outlier events on predicted value of the stock, this paper analyses different parameters that affect stock prediction, and suggest the impact of these parameters on stock performance. Researchers can use this information in order to improve the accuracy of their deployed systems, and make these systems future proof
A Multi-Layered Approach for Detecting Alzheimer's Disease (AD) Using Deep Learning Model
No full textAlzheimer's disease (AD) is a chronic brain disorder that affects the brain cells finally. The common cause of AD is dementia which reduces memory, thinking, behavior, and social skills. All these changes affect a person's ability to function. It is challenging to detect the disease in the early stages. Some of the most common diagnosing techniques are Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), and Single Photon Emission Computed Tomography (SPECT). These techniques provide information regarding the external and internal regions of the brain activities for diagnosing AD. Sometimes with the above methods, it is impossible to analyze AD accurately. The retina is a significant part of the eye which provides the vision to humans. Several studies made that the retina reveals that AD patients have some variations in the retina layers in addition to brain changes. Therefore, the retina becomes a biomarker for diagnosing AD. There are different techniques available for an eye examination. Most noticeable are Fundus Imaging and Optical Coherence Tomography (OCT). This paper introduces multi-layered Deep Learning (MLDL) to diagnose AD in the early stages from retinal abnormalities. Results show that the proposed approach achieved 98.7% accuracy in detecting AD
Amyotrophic Lateral Sclerosis – A Comprehensive Review
Get PDFAmyotrophic Lateral Sclerosis (ALS), also known as Lou Gehrig’s disease, generally said to affect people with an age between 50 years and 70 years. Signs of upper motor neuron and lower motor neuron damage, which are not explained by any other disease process, and are the reasons behind ALS. It attacks the neurons in the brain and spinal cord. These neurons transmit messages from brain and spinal cord to the voluntary muscles. At first, it causes mild muscle problems. Some people show symptoms like difficulty in walking, running, writing and speech. Eventually, the patient may lose the strength and cannot move. Due to the depletion of neuronal transmission to muscles in the chest, the patient may report difficulty to breath. The loss of lower motor neurons leads to flaccid paralysis, decreased muscle tone, decreased reflexes, muscle weakness, muscle atrophy. The defining feature of ALS is the death of both upper and lower motor neurons in the motor cortex of the brain, the brain stem, and the spinal cord. There are small eosinophilic, hyaline intra-cytoplasmic inclusions that stain positive for cystatin and transferring and are present in 70–100% of cases. Environmental and lifestyle factors play a major role in the development of ALS, but no conclusive evidence is available to support making specific changes to decrease the risk of the disease, Genetic mutations can lead to inherited ALS, which appears nearly identical to the non-inherited form. Patients with ALS generally have higher levels of glutamate in the brain, around the nerve cells in their spinal fluid. ALS patients may experience pain involving more than one type, no rigid treatment program that involves the sole use of a single agent should be employed to treat ALS-associated pain conditions. Opioids have proven to be effective in providing pain relief in advanced disease. Nevertheless, these therapies lack the ability to induce long-term lasting effects without constant administration. Over the last decade awareness of ALS has significantly increased, diagnosis is being achieved in a more timely fashion, and overall care is better. This review gives a comprehensive information about the symptoms, pathophysiology common causes, drugs currently used in the treatment
Role Of Intellectual Property Theories in Addressing Anomalies Created By The Intersection of Artificial Intelligence and Intellectual Property Rights: An Analysis
No full textGlobally, the use of artificial intelligence (AI) is expanding exponentially. The issue of managing intellectual property in AI is raised by this surge. Discussions and moderating have taken place, but no resolution has been reached. The issue of whether the work created by an AI should get a special status still exists. When it comes to the control of IPR in artificial intelligence, there are a few oddities. The ownership of patents and copyrights is in doubt, and there are serious worries about the consequences of violation. With the development of technology, there is no certainty on the law, despite existing international accords and conventions. In the absence of artificial intelligence (AI), intellectual property (IP) rules have, up to this point, treated IP as a product of human cognition. The current boom in AI, which has seen the development of IP from the "intelligence" of software, has upended this base. But the non availability of law on works created by artificial intelligence the law is left far behind to deal with the anomalies created by the intersection of “Artificial intelligence and intellectual property rights”. This research paper examines the role of intellectual property theories in addressing AI anomalies, focusing on copyright, patent, and trademark laws. It analyzes utilitarianism, labour theory and personality theory, examining authorship and ownership in AI-generated works and potential conflicts between human creators and machine-generated content. In this research paper researcher(s) will- Analyse various theories of Intellectual properties to tackle the anomolities created by the intersection of IPR and AI. Criticize and suggest changes in the theories to make them helpful for emerging frameworks on AI and IPR
Explaining the UTAUT Model to Understand Individuals' Attitude to Adopt M-Commerce Applications in Developing Countries like Pakistan
Get PDFM-commerce and E-commerce are gaining widespread acceptance among consumers and business communities alike in the shape of online buying and selling products and services interactions in developing countries like Pakistan. Purpose: This study intends to utilize the UTAUT model to investigate the factors influencing individuals' attitudes to adopt M-commerce application and understand the individuals' perceptions and expectations regarding M-commerce usage. Methodology: The research model and suggested hypotheses were addressed using a quantitative approach to achieve the research objective. Data was gathered total of 196 respondents from individuals especially those who spend time and money on M-commerce applications in developing countries like Pakistan was examined using the PLS-SEM approach. Findings: This research found that all significant predictors influence the individuals' attitude toward M-commerce adoption, and the study concluded using PLS-SEM techniques that all the constructs have a greater impact. This research study can help IT experts and online business stakeholders decide on implementing the M-commerce application successfully in Pakistan
Tuning Colossal Magnetoresistance Effect Through Chemical Substitution In Perovskite Manganites
Get PDFObjective: This research is focused on the colossal magnetoresistance (CMR) effect tunability via chemical substitution in perovskite manganites. The objective is to learn how changing the chemical structure of these compounds affect their magnetic and electronic characteristics particularly the CMR effect. Methods: Perovskite manganite materials were prepared by the chemical substitution method to tune the composition of transition metal ions and rare-earth elements. The structural, magnetic, and electronic characterizations were done by the means of X-ray diffraction, magnetization measurements, and electrical transport measurements. Results: The study showed that the selective chemical substitution within the perovskite structure could be used to modulate the CMR effect in manganite materials. Due to the differences in chemical structure the magnetic ordering, charge carrier concentration and electronic band structure are altered which in turn influence the magnitude of the CMR effect. For example, specific chemical substitutions were shown to remarkably strengthen the CMR effect, leading to better magnetoresistance characteristics. Conclusion: This study demonstrates the possibility of tuning the CMR effect by the chemical substitution of Mn perovskite materials. By manipulating the chemical composition, it is achievable to fine-tune the magnetic and electronic characteristics for various spintronics, magnetic sensors and other devices that need high magnetoresistance effects. The results help to gain more knowledge about CMR in manganite systems and provide the guidance for the research on improving their performance
An Intelligent Model for Co-Extraction of Opinion Words and Targets from Online Reviews Using Expectation Maximization
Get PDFThe vital tasks of opinion mining is Mining opinion targets and words from the web reviews. The main aim is to notice opinion relations between words. During this paper, a novel Expectation Maximization (EM) is projected for opinion relations within the sort of alignment method. Subsequently graph-based co-ranking algorithm is studied. And at the last, a candidate who has higher con?dence is extracted. As compared with different strategies, this model is creating the task of opinion relations, for large-span relations additionally. As Compared with the syntax technique, the word alignment model is appearance for negative effects of when yearning for on-line texts. The experimental results show that this model obtains higher precision as Compared to the part supervised alignment model. Once projected system searches for candidate con?dence, it gets to understand that higher-degree vertices within the EM algorithm are decreasing the probability of the generation of erro
Nanostructured Lipid Carriers in Drug Delivery: A Review
No full textOver the past 20 years, lipid-based colloidal systems have gained attention as a means of delivering medications that are not readily soluble in water. The research that has been done has centred on creating various formulations with a broad range of active molecules and excipients. On the particle structure of these colloidal systems, there is disagreement, though. This is partially because there haven't been many studies focused on understanding the drug's preferred location within the particle as well as the arrangement of lipids and stabilising agents during particle formation. This review presents the most widely used materials and preparation techniques for obtaining lipid particles as a contribution in this regard. Additionally, scientometrics tools are used in the synthesis and analysis of the particle characteristics, such as shape, size and distribution, zeta potential, drug loading capacity, and drug entrapment efficiency. A simulation of particle framework based on the creation of the various polymorphic forms of the solid lipid due to the initial ingredients and processing circumstances is proposed in along with the existing evidence. In general, the significance of gaining a thorough understanding of the lipid nanoparticles' structure is emphasised, as this is helpful for the logical design of these nanocarriers