Medical Discoveries Research Articles

Trends of Artificial Intelligence (AI) Use in Drug Targets, Discovery and Development: Current Status and Future Perspectives.

The applications of artificial intelligence (AI) in pharmaceutical sectors have advanced drug discovery and development methods. AI has been applied in virtual drug design, molecule synthesis, advanced research, various screening methods, and decision-making processes. In the fourth industrial revolution, when medical discoveries are happening swiftly, AI technology is essential to reduce the costs, effort, and time in the pharmaceutical industry. Further, it will aid "genome-based medicine" and "drug discovery." AI may prepare proactive databases according to diseases, disorders, and appropriate usage of drugs which will facilitate the required data for the process of drug development. The application of AI has improved clinical trials on patient selection in a population, stratification, and sample assessment such as biomarkers, effectiveness measures, dosage selection, and trial length. Various studies suggest AI could be perform better compared to conventional techniques in drug discovery. The present review focused on the positive impact of AI in drug discovery and development processes in the pharmaceutical industry and beneficial usage in health sectors as well.

Implementation of sodium-glucose co-transporter 2 inhibitors in patients with heart failure through a new digital strategy (EMAIL-HF): a randomised clinical trial study design

Abstract Introduction Delayed implementation of new medical discoveries remains a global healthcare challenge and is mainly due to the complexity of cross-institutional patient care. Sodium-glucose co-transporter-2 (SGLT-2) inhibitors is the latest medical discovery in heart failure (HF) and have recently been added to clinical guidelines as they have proven to reduce the risk of adverse cardiovascular outcomes in patients with HF across the ejection fraction spectrum. Whether a new digital strategy can optimise and accelerate the implementation of SGLT2 inhibitors in patients living with HF is of great importance for public health. Purpose To evaluate whether a new and streamlined digital strategy can optimise and accelerate the implementation of SGLT2 inhibitors in patients with HF. Design and methods: The trial is a multicentre, parallel group, register-based randomised clinical study, evaluating the effect and potential of a new digital strategy to implement new guideline therapies to patients living with a chronic disease, specifically SGLT2 inhibitors to patients with HF (figure 1). The setup employs data from nationwide health registers and official digital letters to inform patients about the new therapy option and invite them to have their eligibility evaluated by a HF specialist and start therapy. A total of ~10,000 patients with HF across the ejection fraction spectrum (with and without diabetes), who have not yet been started on SGLT2 inhibitors, are identified through Danish nationwide health registers, and randomised 1:1 to receive the digital letter (figure 2). The primary outcome is the proportion of patients redeeming a prescription of a SGLT2 inhibitor within six months. Secondary outcome is a composite HF endpoint consisting of all-cause death or HF hospitalisation. Other outcome measures are renal failure, stroke and myocardial infarction, safety outcomes, adherence to therapy and proportion of vulnerable patient groups initiating therapy including immigrants, elderly, frail patients, patients with lower socioeconomic level and lower educational level. A total of 4689 patients have been randomised (February 2024) and data will be presented in 2025. Conclusions The trial will determine the efficacy and safety of a new and streamlined digital strategy to implement SGLT2 inhibitors to patients with chronic HF. The setup has the potential to be used in a broad spectrum of patients living with chronic diseases and is expected to be highly cost-effective.Figure 1.Study hypothesisFigure 2.Study design

Drug and Vaccine Extractive Text Summarization Insights Using Fine-tuned Transformers

Text representation is a key aspect in determining the success of various text summarizing techniques. Summarization using pre-trained transformer models has produced encouraging results. Yet the scope of applying these models in medical and drug discovery is not examined to a proper extent. To address this issue, this article aims to perform extractive summarization based on fine-tuned transformers pertaining to drug and medical domain. This research also aims to enhance sentence representation. Exploring the extractive text summarization aspects of medical and drug discovery is a challenging task as the datasets are limited. Hence, this research concentrates on the collection of abstracts collected from PubMed for various domains of medical and drug discovery such as drug, COVID, etc.with a total capacity of 1,370 abstracts. A detailed experimentation using BART (Bidirectional Autoregressive Transformer), T5(Text-to-Text Transfer Transformer), LexRank and TexRank for the analysis of the dataset is carried out in this research to perform extractive text summarization.

TO ASSESS THE EFFECTIVENESS OF VIDEO ASSISTED TEACHING PROGRAMME ON KNOWLEDGE REGARDING IMPORTANCE OF UMBILICAL CORD BLOOD PRESERVATION FOR FUTURE TREATMENT MODALITIES AMONG EXPECTANT COUPLES AT SELECTED HOSPITALS

Health is the general condition of a person in all aspects it is also a level of functional and metabolic efficiency of an organism. Nothing is more important than protecting the health of your family. A healthy future starts with saving - or banking - your newborns cord blood stem cells. Its a one-time opportunity that can change or even save a life. After a baby is delivered, the mothers body releases the placenta, the temporary organ that transferred oxygen and nutrients to the baby while in the mothers uterus. Stem cell research holds enormous promise for easing human suffering. We have a lot to gain through furthering stem cell research, but medical breakthroughs should be fundamentally about saving, not destroying, human life. Therefore, support stem cell research that does not destroy the embryo. The aim of this study is to assess the effectiveness of video assisted teaching programme on knowledge regarding importance of umbilical cord blood preservation for future treatment modalities among expectant couples. The main objective of the study was to assess the knowledge regarding importance of umbilical cord blood preservation for future treatment modalities among expectant couples. Methodology: The sample size was 60 expectant couples and the setting of the study was selected hospitals where the couples come for antenatal checkup. Sampling technique was convenient sampling technique. One group pretest posttest design was used. Result: The study shows that in pre-test 81.67% of couples were having inadequate knowledge and 18.33% of them having moderately adequate knowledge and none of them having adequate knowledge. While in post test 55% of expectant couples were having Moderately Adequate knowledge and 45% of them having adequate knowledge and none of them having inadequate knowledge. The result shows that the video assisted teaching was effective in improving the knowledge. There was significant association between selected demographic variables and post test score. Conclusion: The teaching was effective in increasing the knowledge of expectant couples and similar awareness programmes should be given to the public so that they can understand regarding the newer treatment modalities.

Data Commons Platforms: Addressing Challenges and Opportunities in Large-Scale Biomedical Data Integration and Analysis

Abstract: Data Commons Platforms are emerging as transformative tools in the landscape of medical research, offering a centralized, accessible, and scalable infrastructure for managing, analyzing, and sharing vast amounts of biomedical data. This article provides a comprehensive examination of these platforms, exploring their core functionalities, benefits, and challenges in the context of advancing medical discovery. We discuss how Data Commons Platforms accelerate research by facilitating datadriven hypothesis generation, enhancing collaboration among researchers, improving data accessibility, and ensuring data interoperability. The article also presents a reference architecture for these platforms, detailing the key components that enable their powerful capabilities. Furthermore, we address critical challenges such as data privacy, quality standardization, and ethical considerations, while also highlighting opportunities for future development. Through case studies and an analysis of emerging trends, this work demonstrates the potential of Data Commons Platforms to revolutionize biomedical research, paving the way for more efficient, collaborative, and impactful scientific discoveries in the era of big data and precision medicine.

Exploring Generative Adversarial Networks for Augmenting Network Intrusion Detection Tasks

The advent of generative networks and their adoption in numerous domains and communities have led to a wave of innovation and breakthroughs in artificial intelligence and machine learning. Generative Adversarial Networks (GANs) have expanded the scope of what is possible with machine learning, allowing for new applications in areas such as computer vision, natural language processing, and creative AI. GANs, in particular, have been used for a wide range of tasks, including image and video generation, data augmentation, style transfer, and anomaly detection. They have also been used for medical imaging and drug discovery, where they can generate synthetic data to augment small datasets, reduce the need for expensive experiments, and lower the number of real patients that must be included in medical trials. Given these developments, we propose using the power of generative adversarial networks to create and augment flow-based network traffic datasets. We evaluate a series of GAN architectures, including Wasserstein, conditional, energy-based, gradient penalty, and LSTM GANs. We evaluate their performance on a set of flow-based network traffic data collected from 16 subjects who used their computers for home, work, and study purposes. The performance of these GAN architectures is described according to metrics that involve networking principles, data distribution among a collection of flows, and temporal data distribution. Given the tendency of network intrusion detection datasets to have a very imbalanced data distribution, i.e., a large number of samples in the “normal traffic” category and a comparatively low number of samples assigned to the “intrusion” categories, we test our GANs by augmenting the intrusion data and checking whether this helps intrusion detection neural networks in their task. We publish the resulting UPBFlow dataset and code on GitHub 1 .

Antimicrobial Resistance: The Impact from and on Society According to One Health Approach

Antibiotics are drugs that target and destroy bacteria, and they are hailed as one of the most amazing medical breakthroughs of the 20th century. They have completely changed how we treat infections and have saved countless lives. But their usefulness is not limited to just medicine; they have also been used for many years in sectors like farming to prevent infections in animals, especially in less wealthy countries. Antimicrobial resistance (AMR) is the ability of microorganisms such as bacteria, viruses, fungi, and parasites to resist the effects of antimicrobial agents, like antibiotics, antivirals, antifungals, and antiparasitics, that were once effective in treating infections caused by these organisms. AMR presents an intricate challenge that endangers the health of both humans and animals, as well as the global economy, and the security of nations and the world at large. Because resistant bacteria are swiftly appearing and spreading among humans, animals, and the environment worldwide, AMR is acknowledged as a challenge within the framework of One Health. The One Health approach involves cooperation among various fields to attain the best possible health outcomes for humans, animals, and the environment. It acknowledges the interconnectedness of human, animal, and environmental health. AMR is not merely a scientific or medical issue; it is a societal challenge that demands collective action and awareness. In the intricate tapestry of society, every thread contributes to the fabric of AMR, and every individual holds a stake in its resolution.

Institutional care and education: circulation of knowledge about epilepsy in Sweden 1915-40.

This article focuses on the circulation of knowledge about epilepsy in Sweden between 1915 and 1940. During the period medical research on epilepsy increased, which simultaneously brought a new degree of specialisation and distinction between branches of medicine. The aim of this article is to study the impact of new medical knowledge about epilepsy on the treatment and education of children with epilepsy in Sweden. In order to concretise the aim, the study focuses on the asylum Margarethahemmet. The key source material consists of Margarethahemmet's annual reports and yearbooks. The minutes of the meetings of the Swedish General Association for the Care of the Feebleminded and Epileptic for the period 1915-1938 have been used as supplementary material. In order to trace the impact of medical discoveries on Margarethahemmet's operations, contemporary scientific articles, mostly from Germany, have also been used. The article demonstrates how new research and new knowledge was sought internationally and nationally, to provide doctors and special teachers at the asylum with a proper knowledge about education, care and treatment for children with epilepsy. The increased understanding of the disease directly impacted the ability of a stigmatized group - people with epileptic disorder - to actively participate in society on the same terms as others.

Generative artificial intelligence in healthcare: current status and future directions

Generative artificial intelligence (GAI) is rapidly transforming the healthcare landscape, offering innovative solutions in areas such as medical imaging, drug discovery, and clinical decision support. This comprehensive review examines the current role of GAI in healthcare, its potential benefits, drawbacks, challenges, and future research directions. By synthesizing recent literature and expert perspectives, this review provides a critical analysis of GAI’s impact on healthcare delivery, patient outcomes, and ethical considerations. While GAI shows promise in enhancing diagnostic accuracy, accelerating drug development, and improving healthcare efficiency, it also faces significant challenges related to data privacy, regulatory compliance, and ethical implementation. This review aims to inform healthcare professionals, researchers, and policymakers about the current state and future potential of GAI in healthcare, emphasizing the need for responsible development and deployment of these technologies.

User Engagement with the User Manuals of Smart Medical Wearable Technologies and Relevant Questions of User Behavior.

In this paper, engagement with smart medical wearables and with their user manuals, as well as related user behavior are studied. A research questionnaire containing 15 single-choice questions was completed by 1381 test participants to address relevant topics of the investigated area, including trust in measured medical data, device calibration, technical terminologies and function discovery in the documentation, information sources beyond the documentation, and wearing such devices to bed. The questionnaire particularly focused on device functionalities and characteristics that initially led to the purchase of the smart medical wearable.

The logic of medical discovery: the case of Jenner’s inquiry on variolae vaccinae

Abstract Jenner (1749–1826) is known as the father of the smallpox vaccine. Through an inferential analysis of Jenner’s report of inquiry, in which medical practice and medical research are intrinsically intertwined, we highlight his use of abductive hypotheses. Our understanding of abduction is based on the Gabbay and Woods (2005, The Reach of Abduction Insight and Trial, 2, 39) model, in which hypotheses can be activated even when they have not been confirmed, as well as Magnani’s Select and Test model (1992, 2017). We discuss the fundamental role of abductive hypotheses in experimental medicine and understood in the sense of Bernard (1865, Introduction à l’étude la médecine expérimentale). We conclude with remarks about mechanistic hypotheses discussed by Jenner, in relation to the thesis advocated by Russo and Williamson (2007, Int. Stud. Philos. Sci., 21, 157–170).

Data sharing in cancer research: A qualitative study exploring community members' preferences.

Advancements in cancer treatment and survivorship rely on participation in research and access to health records. This study explored preferences for data access and sharing in 14 workshops with 42 community members, most of whom were a cancer survivor or carer. Various scenarios for data access and sharing were presented and discussed, with participants' preferences summarized using descriptive statistics. Reasons underlying these preferences were identified through a thematic analysis of workshop transcripts. Most participants indicated a willingness for researchers to use their self-report data and current health records for a specific research project (86%). Many were also willing for their self-report data and current (62%) or all future (44%) health records to be shared with other researchers for use in other studies if made aware of this. Willingness to consent to data access and sharing data in cancer research was influenced by: (i) the potential for data sharing to advance medical discoveries and benefit people impacted by cancer in the future, (ii) transparency around researchers' credibility and their intentions for data sharing, (iii) level of ownership and control over data sharing, and (iv) protocols for privacy and confidentiality in data sharing. Based on these themes, we present practical strategies for optimizing data access and sharing in cancer research.

Navigating the Landscape of Cancer From Ancient Times to Modern Challenges: A Narrative Review.

Cancer, a pervasive and multifaceted disease, has afflicted humanity since ancient times, as evidenced by early references in the Edwin Smith Papyrus and the Ebers Papyrus. Over centuries, our understanding and treatment of cancer have evolved significantly, transitioning from rudimentary remedies to advanced modalities like chemotherapy, radiation therapy, and precision medicine. Despite these advancements, cancer remains a major global health challenge. As of 2022, nearly 20 million new cancer cases and 10 million cancer-related deaths were reported worldwide. In India, the situation is particularly dire, with over 1.41 million new cases and more than 916,827 deaths in 2022, exacerbated by socioeconomic disparities, cultural stigmas, and healthcare barriers. This review traces the historical evolution of cancer treatment from ancient civilizations to modern times, highlighting key medical milestones and breakthroughs. It examines the global and Indian cancer burden, emphasizing the critical barriers to early diagnosis and effective treatment. These barriers include health system deficiencies, socioeconomic challenges, delayed diagnosis, low health literacy, and inadequate screening programs. The review was conducted through a comprehensive literature search using databases such as PubMed, Google Scholar, Journal Storage (JSTOR), and various other sources focusing on historical texts, epidemiological studies, and current medical research. The search aimed to gather a broad spectrum of perspectives and evidence to provide a well-rounded understanding of cancer's historical journey and current landscape.

The Penicillin Pioneer: Alexander Fleming's Journey to a Medical Breakthrough.

Alexander Fleming's discovery of penicillin is one of the most significant breakthroughs in medical history, revolutionizing the treatment of bacterial infections and saving countless lives. This report chronicles Fleming's journey from his early life in rural Scotland to his pioneering work in bacteriology. It delves into his medical education and career, including his formative experiences during World War I that shaped his future research. The serendipitous discovery of penicillin in 1928, followed by the challenges of isolating and producing the antibiotic, is explored in detail. The report also highlights the crucial contributions of Howard Florey, Ernst Boris Chain, and Norman Heatley in developing penicillin into a widely usable therapeutic agent, particularly during World War II. Fleming's achievements were recognized with the Nobel Prize in 1945 and numerous other honors in Physiology/Medicine. His personal life, continued research, and lasting impact on medicine are also discussed, emphasizing the enduring legacy of his work in the ongoing development of antibiotics and the transformation of medical practices. This comprehensive overview underscores the importance of curiosity, perseverance, and collaboration in scientific discovery, inspiring future researchers.

AoUPRS: A Cost-Effective and Versatile PRS Calculator for the All of Us Program.

The All of Us (AoU) Research Program provides a comprehensive genomic dataset to accelerate health research and medical breakthroughs. Despite its potential, researchers face significant challenges, including high costs and inefficiencies associated with data extraction and analysis. AoUPRS addresses these challenges by offering a versatile and cost-effective tool for calculating polygenic risk scores (PRS), enabling both experienced and novice researchers to leverage the AoU dataset for significant genomic discoveries. AoUPRS is implemented in Python and utilizes the Hail framework for genomic data analysis. It offers two distinct approaches for PRS calculation: the Hail MatrixTable (MT) and the Hail Variant Dataset (VDS). The MT approach provides a dense representation of genotype data, while the VDS approach offers a sparse representation, significantly reducing computational costs. In performance evaluations, the VDS approach demonstrated a cost reduction of up to 99.51% for smaller scores and 85% for larger scores compared to the MT approach. Both approaches yielded similar predictive power, as shown by logistic regression analyses of PRS for coronary artery disease, atrial fibrillation, and type 2 diabetes. The empirical cumulative distribution functions (ECDFs) for PRS values further confirmed the consistency between the two methods. AoUPRS is a versatile and cost-effective tool that addresses the high costs and inefficiencies associated with PRS calculations using the AoU dataset. By offering both dense and sparse data processing approaches, AoUPRS allows researchers to choose the approach best suited to their needs, facilitating genomic discoveries. The tool's open-source availability on GitHub, coupled with detailed documentation and tutorials, ensures accessibility and ease of use for the scientific community.

Targeting mycobacterial efflux system to enhance tuberculosis therapy

The worldwide health epidemic of tuberculosis (TB) persists. It still claims millions of lives each year despite medical breakthroughs. Long-term therapies, drug-resistant TB strains, and co-infections with conditions like HIV necessitate novel approaches. The use of Mycobacterium tuberculosis (Mtb) efflux pumps, which actively expel drugs and decrease their effectiveness, is one such approach. EPIs (Efflux Pump Inhibitors) have the potential to treat tuberculosis. This review offers insights into Mtb's immune evasion mechanisms, including its strong cell wall, granuloma formation, immunological modulation, and dormancy, as well as TB epidemiology, worldwide eradication efforts, and those processes. Dissecting Efflux Pumps highlights their significance in drug resistance, particularly against first-line TB medications. Efflux pumps are notorious for causing antibiotic resistance. EPIs may have benefits such as increased drug efficacy, resistance reversal, shortened treatment durations, less toxicity, improved adherence, and targeting of latent TB. The effectiveness of various EPI classes, including phenylalkylamines, protonophores, phenothiazines, and plant-derived derivatives, against Mtb growth and efflux pumps is evaluated. The creation of effective EPIs, a clearer understanding of efflux pump control, and essential clinical trials for validation remain obstacles.

The Problems of Human Embryos Genome Editing from the Position of Islam Denominations

Biomedical technology is one of the most relevant and rapidly developing branches of science. In response to the major problems of bioethics and bio-law, bioethical dilemmas emerge in society, which constrain the abuse of new technologies. Medical discoveries, on the one hand, can greatly facilitate the life of humankind, but, on the other hand, the problem of interference in human nature actualizes the most fundamental questions concerning its ontology, the boundaries of permissible transformations, the responsibility of a scientist and a specialist, applying the latest technologies, for remote and unpredictable consequences, due to the integrity and interconnectedness of various aspects of human nature. This paper presents the experience of generalizing the attitude of the main Islamic confessions and different approaches in the legislation of Islamic countries to the problem of editing the human embryo genome. Based on a review of scientific and religious literature, it is concluded that, although the Islamic world is increasingly using Western models of behavior, in matters of the permissibility of editing the human embryo genome from the point of view of Islamic bioethics, it is necessary to rely on the principles of Sharia and multidisciplinary knowledge.

Tailored Viral-like Particles as Drivers of Medical Breakthroughs.

Despite the recognized potential of nanoparticles, only a few formulations have progressed to clinical trials, and an even smaller number have been approved by the regulatory authorities and marketed. Virus-like particles (VLPs) have emerged as promising alternatives to conventional nanoparticles due to their safety, biocompatibility, immunogenicity, structural stability, scalability, and versatility. Furthermore, VLPs can be surface-functionalized with small molecules to improve circulation half-life and target specificity. Through the functionalization and coating of VLPs, it is possible to optimize the response properties to a given stimulus, such as heat, pH, an alternating magnetic field, or even enzymes. Surface functionalization can also modulate other properties, such as biocompatibility, stability, and specificity, deeming VLPs as potential vaccine candidates or delivery systems. This review aims to address the different types of surface functionalization of VLPs, highlighting the more recent cutting-edge technologies that have been explored for the design of tailored VLPs, their importance, and their consequent applicability in the medical field.

Advancing team science and health equity in clinical oncology using the All of Us Research Program dataset.

e13741 Background: The All of Us Research Program ( All of Us) is one of the largest, most diverse health databases developed to expedite medical breakthroughs and is a resource for cancer researchers. The size and diversity of participants along with data types within the program, coupled with the program’s cloud based data analytics platform, encourage both team science and equitable health research outcomes. All of Us is dedicated to advancing the science of health equity with a focus on populations underrepresented in biomedical research and workforce, and embedding health equity across all aspects of the program. Methods: All of Us uses a centralized protocol where participants may elect to 1) enroll, consent, and authorize EHR, 2) answer surveys, 3) provide physical measurements, 4) provide biosamples, and 5) share data from wearables. High levels of participant diversity was achieved through an Engagement Ecosystem of outreach leaders, participants, and engagement awardees. Outreach, engagement, enrollment, and retention efforts are strategically directed by a Community and Participant Engagement Framework and a Health Equity Strategic Plan. Results: As of January 2024, health data from 413,450+ participants is available, including eight survey types from 337,500+ participants, electronic health records (EHR) from 287,000+ participants, wearable data from 15,600+ participants and whole genome sequencing from 245,350+ participants. Over 75% of participants self-identify as underrepresented in biomedical research, and about 45% self-identify as racial and ethnic minority groups. Cancer data includes history at enrollment as well as incident ascertainment via EHR (N = 26,323 total cancers and 13,067 incident cancers, from 7,544 participants assigned female at birth and 5,264 participants assigned male at birth). As of February 2024, All of Us data has been used in more than 221 publications. Of these, 35% (78) discuss cancer or oncology. More than 10% of active workspaces (921 out of 8000+ as of January 2024) include “cancer” in workspace descriptions. Commonly studied cancer types include breast, prostate, lung, ovarian, and colorectal. Conclusions: All of Us has established itself as a resource for cancer researchers. This database has the potential to provide insights into the development of treatment guidelines and emerging indicators for screening and early detection guided by health equity built on participant engagement, diversity, and broad data availability. Finally, the breadth of All of Us data also offers potential insight into cancer etiology and opportunities for prevention.

Should brain chip implants for memory and cognitive enhancement be banned in competitive national examinations?

In a recent medical breakthrough, Elon Musk's startup company Neuralink implanted the first brain chip in a human patient, purportedly for aiding paralysis. While certainly representing a significant medical milestone for many patients afflicted with debilitating brain and spinal cord injuries, as well as devastating neurodegenerative diseases such as Parkinson's and Alzheimer's, it must be noted that this very same technology can also be manipulated for human memory or cognitive enhancement. What happens if a brain chip were to be developed that can significantly improve either IQ (intelligence quotient) or memory, and these were then implanted in people to enhance their performance in highly competitive national examinations for college entrance or gaining employment in civil service positions? This article therefore discusses the ethical implications of this nascent technology platform, and whether its use in competitive national examinations should be banned.