Aleksandra Zielińska

Artificial Intelligence (AI) plays an increasingly significant role in drug research and development, particularly in drug repurposing, which involves identifying new therapeutic indications for existing pharmacological compounds. From classical algorithms-based tools e.g. DrugRep and DrugRepo, to more recent innovations (e.g. RosettaVS, RepurposeDrugs), this paper reviews the latest AI methods (e.g. AlphaFold3, mediKanren, AdaDR, TxGNN) and their design applications in drug repurposing, particularly in machine learning, deep learning, and biological network analysis. It discusses strategies using predictive models, natural language processing, and big data analysis to accelerate the identification of promising candidates for clinical repurposing. Data availability, model interpretability, and results validation challenges are also highlighted. This review suggests that AI represents a groundbreaking tool in drug repurposing, ranging from protein structure prediction to knowledge graph reasoning, which can significantly reduce the time and costs of developing new therapies.

Background/Objectives: Sorghum (Sorghum bicolor Moench) is a globally cultivated cereal and an increasingly important crop in Europe due to its exceptional adaptability to climate change and low input requirements. It represents a rich source of bioactive compounds, including phenolic acids, flavonoids, tannins, and 3-deoxyanthocyanidins, which exhibit strong antioxidant, anti-inflammatory, and metabolic regulatory properties. Methods: This review, as a bibliometric analysis, summarizes and discusses current evidence on the health-promoting effects of sorghum, with particular emphasis on its antioxidant, metabolic, and cardiovascular benefits. Results: The antioxidant potential of sorghum is mainly attributed to its phenolic profile, which varies considerably depending on genotype, environmental factors, and processing methods. Human and animal studies demonstrate that sorghum-derived polyphenols enhance endogenous antioxidant enzyme activity, decrease oxidative stress biomarkers, and beneficially modulate gut microbiota composition. Sorghum-based foods are characterized by low to medium glycemic indices, promoting improved postprandial glucose regulation, insulin sensitivity, and prolonged satiety. Furthermore, sorghum bioactive peptides and phenolic acids contribute to cardiovascular health by lowering serum cholesterol levels, reducing inflammatory markers, and exhibiting angiotensin-converting enzyme (ACE) inhibitory activity. Conclusions: Overall, sorghum constitutes a gluten-free, antioxidant-rich grain with significant potential for mitigating oxidative stress, supporting metabolic balance, and preventing chronic non-communicable diseases.

Nanoparticles (NPs) are widely used in the pharmaceutical field to treat various human disorders. Among these, lipid-based NPs (LNPs), including solid lipid nanoparticles (SLN) and nanostructured lipid carriers (NLC), are favored for drug/bioactive delivery due to their high stability, biocompatibility, encapsulation efficiency, and sustained/controlled release. These properties make them particularly suitable as carriers of compounds derived from plant sources. This study comprehensively explores updated literature knowledge on SLN and NLC, focusing on their composition and production methods for the specific delivery of drug/bioactive compounds derived from plant sources of interest in pharmaceutical and biomedical fields. SLN and NLC facilitate the development of more effective natural product-based therapies, aiming to reduce dosage and minimize side effects. These delivery systems align with the consumer demands for safer and more sustainable products, as there are also based on biocompatible and biodegradable raw materials, thereby posing minimal toxicological risks while also meeting regulatory guidelines.

Numerous purified bioactive compounds, crude extracts, and essential oils have demonstrated potent antioxidant, antimicrobial, anti-inflammatory, and antiviral properties, particularly in vitro or in silico; however, their in vivo applications are hindered by inadequate absorption and distribution in the organism. The incorporation of these phytochemicals into solid lipid nanoparticles (SLN) or nanostructured lipid carriers (NLC) has demonstrated significant advancements and represents a viable approach to improve their bioavailability through different administration routes. This review discusses the potential applications of SLN and NLC, loading bioactive compounds sourced from plants for the treatment of several diseases. An overview of the preclinical developments on the use of these lipid nanoparticles is also provided, as well as the requisites to be launched on the market. Medicinal plants have gained even more value for the pharmaceutical industries and their customers, leading to many studies exploring their therapeutic potential. Several bioactives derived from plants with antiviral, anticancer, neuroprotective, antioxidant and antiaging properties have been proposed and loaded into lipid nanoparticles. In vitro and in vivo studies corroborate the added value of SLN/NLC to improve the bioavailability for several bioactives. Surface modification to increase their stability and target delivery should be considering.

Monoclonal antibodies (mAbs) have revolutionized the landscape of cancer therapy, offering unprecedented specificity and diverse mechanisms to combat malignant cells. These biologic agents have emerged as a cornerstone in targeted cancer treatment, binding to specific antigens on cancer cells and exerting their therapeutic effects through various mechanisms, including inhibition of signaling pathways, antibody-dependent cellular cytotoxicity (ADCC), complement-dependent cytotoxicity (CDC), and antibody-dependent cellular phagocytosis (ADCP). The unique ability of mAbs to engage the immune system and directly interfere with cancer cell function has significantly enhanced the therapeutic armamentarium against a broad spectrum of malignancies. mAbs were initially studied in oncology; however, today, treatments have been developed for eye diseases. This review discusses the current applications of mAbs for the treatment of ocular diseases, discussing the specificity and the variety of mechanisms by which these molecules exhibit their therapeutic effects. The benefits, drawbacks, effectiveness, and risks associated with using mAbs in ophthalmology are highlighted, focusing on the most relevant ocular diseases and mAbs currently in use. Technological advances have led to in vitro production methods and recombinant engineering techniques, allowing the development of chimeric, humanized, and fully human mAbs. Nowadays, many humanized mAbs have several applications, e.g., for the treatment of age-related macular disease, diabetic retinopathy, and uveitis, while studies about new applications of mAbs, such as for SARS-CoV-2 infection, are also currently ongoing to seek more efficient and safe approaches to treat this new ocular disease.

Artificial intelligence (AI) technology is advancing significantly, with many applications already in medicine, healthcare, and biomedical research. Among these fields, the area that AI is remarkably reshaping is biomedical scientific writing. Thousands of AI-based tools can be applied at every step of the writing process, improving time effectiveness, and streamlining authors’ workflow. Out of this variety, choosing the best software for a particular task may pose a challenge. While ChatGPT receives the necessary attention, other AI software should be addressed. In this review, we draw attention to a broad spectrum of AI tools to provide users with a perspective on which steps of their work can be improved. Several medical journals developed policies toward the usage of AI in writing. Even though they refer to the same technology, they differ, leaving a substantially gray area prone to abuse. To address this issue, we comprehensively discuss common ambiguities regarding AI in biomedical scientific writing, such as plagiarism, copyrights, and the obligation of reporting its implementation. In addition, this article aims to raise awareness about misconduct due to insufficient detection, lack of reporting, and unethical practices revolving around AI that might threaten unaware authors and medical society. We provide advice for authors who wish to implement AI in their daily work, emphasizing the need for transparency and the obligation together with the responsibility to maintain biomedical research credibility in the age of artificially enhanced science.

Aim: This study aimed to identify and analyze the top 100 most cited digital health and mobile health (m-health) publications. It could aid researchers in the identification of promising new research avenues, additionally supporting the establishment of international scientific collaboration between interdisciplinary research groups with demonstrated achievements in the area of interest. Methods: On 30th August, 2023, the Web of Science Core Collection (WOSCC) electronic database was queried to identify the top 100 most cited digital health papers with a comprehensive search string. From the initial search, 106 papers were identified. After screening for relevance, six papers were excluded, resulting in the final list of the top 100 papers. The basic bibliographic data was directly extracted from WOSCC using its “Analyze” and “Create Citation Report” functions. The complete records of the top 100 papers were downloaded and imported into a bibliometric software called VOSviewer (version 1.6.19) to generate an author keyword map and author collaboration map. Results: The top 100 papers on digital health received a total of 49,653 citations. Over half of them (n = 55) were published during 2013–2017. Among these 100 papers, 59 were original articles, 36 were reviews, 4 were editorial materials, and 1 was a proceeding paper. All papers were written in English. The University of London and the University of California system were the most represented affiliations. The USA and the UK were the most represented countries. The Journal of Medical Internet Research was the most represented journal. Several diseases and health conditions were identified as a focus of these works, including anxiety, depression, diabetes mellitus, cardiovascular diseases, and coronavirus disease 2019 (COVID-19). Conclusions: The findings underscore key areas of focus in the field and prominent contributors, providing a roadmap for future research in digital and m-health.