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Nanoparticles in Cancer Therapy: Current Progress, Challenges, and Future Perspectives in Clinical Translation
Get PDFCancer treatment is evolving with the advent of nanotechnology, shifting from conventional therapies to precision medicine. Nanoparticles (1–100 nm) which encapsulate drugs and direct them to tumor sites offer unique advantages in cancer therapy, including enhanced drug delivery, reduced toxicity, and improved specificity. This editorial examines various types of nanoparticles, with focus on those that have progressed to clinical trials, while addresses the challenges in translating these innovations from the laboratory to clinical practice. Despite the growing body of researNanoparticlesch, the number of approved nanodrugs remains limited. Hence a deeper understanding of nano formulations and their targeting mechanisms will be crucial to advancing cancer treatment in the future
Leveraging Machine Learning, Cloud Computing, and Artificial Intelligence for Fraud Detection and Prevention in Insurance: A Scalable Approach to Data-Driven Insights
Get PDFThis paper aims to establish an understanding of how developments in technology have affected insurance fraud detection and control. This paper discusses the applicability of combining ML, cloud environment and AI to build flexible and effective fraud discovery systems. The existing strategies for fraud detection and prevention may have a weakness with the amount, variety and real-time nature of data. This paper proposes a detailed framework to improve the effectiveness of fraud detection with the help of ML algorithms for accurate prediction models, AI for decision automation support, and cloud computing for future expansion. It will be clear from the above results that enhanced detection accuracy, operations efficiency and compliance to set legal standards have been attained. This research work’s objective is to present recommendations for insurers interested in preventing fraud while keeping the antidote affordable and easily soluble in large volumes
Toward the Development of a Hybrid Active and Measuring Exoskeleton for Upper Limbs of Heavy-duty Harbor Workers
Get PDFThe paper presents the study of a novel exoskeleton designed for the upper limbs of heavy-duty port operators responsible for lashing containers. This exoskeleton is designed to measure initially its configuration and operational times, once positioned on the workers, to pass to a partial activeness introducing motors for the shoulder, the intra-extra rotation of the forearm, and the elbow. The key concept revolves around the shoulder joint, with particular emphasis on the scapula and its motion. The scapula plays a fundamental role in moving the center of rotation of the humerus, contributing to its exceptional mobility. The fundamental objective is to develop a system that provides support for the vertical motion of the operator's arms, with a specific focus on allowing initially the vertical motion of the scapula to remain unrestricted. This approach aims to collect essential data, which, in a subsequent phase, will likely enable the addition of vertical support to the scapula, possibly with the assistance of AI. Meanwhile, the horizontal motion will consistently be left unrestricted. This exoskeleton design is inspired by previous work that conceptualized a fully measuring exoskeleton, and a corresponding patent application has been presented
Appraisal of Olezarsen for Treatment of Hypertriglyceridemia
Get PDFOlezarsen is antisense antinucleotide under investigation that inhibits synthesis of apolipoprotein C3 (ApoC3) resulting in reduction of plasma triglycerides levels. In a phase 3 clinical trial of patients having familial chylomicronemia syndrome (FCS) with extreme hypertriglyceridemia at baseline (mean plasma triglycerides 2,630 mg/dl), olezarsen 80 mg administered subcutaneously every 4 weeks decreased triglycerides by 43.5 percentage points (95% CI, 69.1 to 17.9; P<0.001) after 6 months compared with placebo. By 53 weeks, 1 episode of acute pancreatitis occurred in olezarsen group versus 11 episodes in the placebo group, rate ratio (RR) 0.12 (95% CI, 0.02 TO 0.66). Two phase 2 trials evaluated olezarsen in patients with moderately elevated triglycerides (<500 mg/dl) and high cardiovascular (CV) risk recorded similar magnitude of reduction of triglycerides. Olezarsen reduced levels of atherogenic lipoproteins such as ApoC3 by 73%, non-high-density lipoprotein cholesterol (non-HDL-C) by 17-23% and increased high-density lipoprotein cholesterol (HDL-C) levels by 30-40%. Meanwhile, olezarsen increased mean values of low-density lipoprotein (LDL-C) from 22.8 to 37.6 mg/dl in patients with FCS but had no significant effects in patients with high CV risk having higher baseline LDL-C levels. Discontinuation rates due to adverse effects of olezarsen were 9-12% versus 0% with placebo. The most common adverse effects of olezarsen were elevation of liver enzymes, mostly below 3 times the upper limit of normal, and injection-site reactions. Platelet count < 140,000/µl occurred in 18% in patients receiving olezarsen versus 3% with placebo (risk ratio 6.8; 95% CI, 0.91 to 51.3; P=0.03). No patient had severe thrombocytopenia with platelet number < 75,000/µl. Overall, olezarsen is a promising new therapy for hypertriglyceridemia and for prevention of hypertriglyceridemia-induced pancreatitis. Long-term randomized trials are urgently needed to examine the effects of olezarsen on CV events and mortality and establish its long-term safety.  
Are the Bones of the Cranial Vault in Newborns Connected to Each Other by Sutures?
Get PDFThe skull of a newborn differs from the skull of an adult in many aspects, including the shape of the sutures and the presence of fontanelles. The sutures in an adult's skull that connect adjacent bones are fixed fibrous joints “synarthroses”. The edges of the bones are serrated like sutures. On the other hand, in newborns these joints are flexible and slightly mobile with wide gaps where more than two bones meet. These gaps are called fontanelles, and they close later as the baby grows. Fontanelles are of great clinical importance in monitoring normal growth and checking for diseases that may affect children. Although the joints of the cranial bones are quite different in newborns than in adults, some authors call them sutures in both cases. This may be inaccurate, and a distinction must be made between the terms in both cases, which may express quite different structures. Therefore, we suggest calling them fibrous joints with an interosseous membrane rather than sutures in newborns
Effectiveness of Yoga-Based Interventions on Vascular Health: A Comprehensive Review
Get PDFBackground: Yoga is increasingly recognized as a complementary approach to manage cardiovascular health, particularly in reducing risk factors associated with cardiovascular diseases. While numerous studies suggest that yoga may positively influence vascular health, further synthesis is necessary to understand its efficacy fully.
Objectives: This systematic review aims to evaluate the effectiveness of yoga interventions in managing cardiovascular risk factors, with a focus on hypertension, heart rate variability, lipid profiles, and other related cardiovascular outcomes.
Methods: Various electronic databases were searched for studies assessing the impact of yoga on cardiovascular health. Inclusion criteria encompassed randomized controlled trials and observational studies that analyzed changes in cardiovascular risk factors following yoga interventions. Data were extracted and analyzed for key outcomes related to holistic health changes caused by yoga practice.
Results: Preliminary findings indicate statistically significant improvements in blood pressure, heart rate, and lipid profiles among participants engaged in structured yoga programs compared to control groups. Specific outcomes include a substantial reduction in systolic and diastolic blood pressure, as well as favorable changes in total cholesterol and triglyceride levels.
Conclusion: Yoga interventions demonstrate promise as beneficial adjunct therapies for managing cardiovascular health. Although current evidence supports the positive impact of yoga on key cardiovascular risk factors, further high-quality, large-scale clinical trials are necessary to confirm these outcomes and ascertain the mechanisms underlying yoga's effects on vascular health. Integrating yoga into conventional cardiac rehabilitation programs could enhance overall patient outcomes
Design of ROSES Application to Endocranial Procedures with AI Help
Get PDFThis article presents the application of the ROSES system in intracranial procedures, integrating artificial intelligence (AI) to enhance precision and safety. The system uses advanced robotic actuators and disposable tools to manage microcatheters and guidewires, enabling efficient stent placement while minimizing contact with aneurysms. By leveraging angiographic data to create 3D vascular models, the AI determines optimal pathways, calculates stent dimensions, and identifies critical curvatures. This approach allows for automated or manual intervention based on procedural requirements, reducing the need for physician presence during high-risk stages. The innovation significantly lowers radiation exposure and improves procedural outcomes in complex intracranial surgeries, offering a promising step toward more autonomous endovascular systems. Importantly, this system reduces the necessity for a doctor to be physically present with the patient, as the AI and robotic components can manage much of the procedure remotely. This advancement could greatly enhance the efficiency and safety of medical procedures
Self-Centered Intelligent Care (SCIC) in Patients with Diabetes: A Futuristic Scenario
Get PDFDiabetes is a global epidemic that accounts for about 12% of the world's health costs. Diabetes is the main cause of kidney failure, lower limb disorders and blindness in adulthood and it nearly doubles the risk of heart attack and all-cause mortality, leading to hospitalizations, long-term complications, and high costs. In this way, the value of self-care and especially self-centered health care at the individual, institutional, and social levels, in maintaining and improving the health of patients with diabetes becomes more visible. This manuscript introduces the Self-centered intelligent care (SCIC) scenario, which probably patients with diabetes will benefit from in the future
Building Foundation Models in Biology
Get PDFOver the last three years, Foundation models such as Dall-E and ChatGPT have taken the world by storm and have ushered in the "AI Boom". The next challenge is to build such models in Biology. This article examines the way text-based foundation models were built and the ways in which the approach has to be tweaked to build Foundation models in Biology. More specifically, it looks at the three components of the scaling laws - Data, Architecture and Compute and how they can be adapted to build foundation models in Biology.These Foundation models can then be used for a variety of downstream tasks such as Identification and if possible, prevention of conditions, treatment planning and nutrition planning
Optimizing Travel Insurance Purchase Detection using Predictive Models
Get PDFWhat traveler features should be considered when designing airline travel insurance policies, and can predictive modeling enhance the accuracy of purchase predictions? Motivated by the increased need to safeguard investments due to frequent flight interruptions and cancellations during the COVID-19 pandemic and its travel restrictions, we investigate the uptake of flight travel insurance using predictive models. This study applies various machine learning techniques to a dataset consisting of 1,987 travelers, examining whether they purchased travel insurance (a binary classification problem). Performance metrics such as misclassification rate, precision, recall, F-score, and the area under the receiver operating characteristic curve (AUC) are used to assess model effectiveness. The models were optimized using cross-validation on the training data. Among the models tested, eXtreme Gradient Boosting Machine (XGBoost) achieved the highest accuracy rate of 86%, along with the best AUC, precision, recall, and specificity, indicating a 98% accuracy in predicting who will purchase travel insurance. Other robust models, such as ensemble methods and neural networks, also demonstrated strong performance, with similar AUC and precision scores. Features such as annual income, age, travel history, and education history were found to be the most significant predictors, while chronic disease history had little impact. Parsimonious predictive models, using only the most important variables, yielded better performance. Our findings highlight the critical role of predictive accuracy in helping insurers mitigate the financial risk due to travel interruptions