iLABMED : A Translational Medical Journal Embracing a New Era

The third anniversary of iLABMED will be commemorated in June 2026. The editorial leadership extends sincere appreciation to all authors, reviewers, editors, and readers for their continued support and contributions. Over the past year, the journal has made steady progress across multiple dimensions, reflecting its growing academic influence and sustained commitment to translational medicine. In 2025, iLABMED published 48 peer-reviewed articles encompassing a wide range of experimental and clinical research topics. The journal is currently indexed in several major bibliographic databases, including the Chinese Science Citation Database (CSCD), the Directory of Open Access Journals (DOAJ), and Scopus. Applications for inclusion in the Emerging Sources Citation Index (ESCI) and PubMed Central (PMC) are under active review. Collectively, these developments represent important milestones toward enhancing the journal's global visibility and scientific impact, and they provide a strong foundation for the continued advancement of iLABMED in 2026. Over the past year, iLABMED published a diverse and scientifically rigorous body of work encompassing clinically relevant and methodologically robust studies. Kobialka et al. conducted a systematic comparison of ten commercially available extraction protocols for point-of-need molecular diagnostics, highlighting the critical roles of flexibility, reliability, and sample-specific performance in the selection of diagnostic workflows 1. Ren et al. provided a comprehensive review of recent advances in molecular point-of-care testing systems, identifying intelligent, shared, and cloud-based platforms as key directions for future development 2. Several contributions focused on oncology and immunology. Zhao et al. identified CD48 as a breast cancer–associated gene linked to immune cell infiltration and clinical prognosis, supporting its potential utility as a predictive biomarker 3. Cai et al. reviewed recent progress in flow cytometry, emphasizing ongoing improvements in analytical accuracy and clinical applicability as major trends shaping the field 4. Zhang et al. demonstrated that synaptophysin expression is associated with tumor differentiation and prognosis in gastric cancer, providing clinically meaningful prognostic insights 5. In the areas of infectious diseases and clinical microbiology, Gao et al. analyzed antimicrobial susceptibility patterns of Eggerthella lenta isolates, revealing inconsistencies with conventional therapeutic approaches and underscoring the need for updated clinical treatment guidelines 6. Tang et al. critically reviewed precision diagnostic strategies for Helicobacter pylori infection and antimicrobial resistance, offering clinically actionable guidance to inform diagnostic and therapeutic decision-making 7. Dong et al. reported that the combined assessment of monocytic HLA-DR, procalcitonin, and C-reactive protein enhances the diagnostic and prognostic accuracy in patients with sepsis 8. Notably, iLABMED also featured studies showcasing innovative diagnostic technologies. Hao et al. introduced a reporter phage–based approach for the detection of Escherichia coli in urinary tract infections 9. Tan et al. developed a rapid, visual multiplex recombinase polymerase amplification platform designed for on-site tuberculosis screening 10. Yang et al. reported a complementary nucleic acid detection assay enabling rapid diagnosis of malaria 11. Wang et al. demonstrated the clinical utility of nanopore-targeted sequencing for the rapid diagnosis of myocarditis and infective endocarditis 12. In addition, iLABMED published three representative studies illustrating the expanding role of artificial intelligence (AI) in clinical medicine. Ding et al. developed and validated an AI-assisted diagnostic model that exhibited strong predictive performance and robustness when applied to real-world clinical datasets, highlighting the capacity of machine learning to improve diagnostic accuracy and clinical decision-making 13. Zhu et al. applied advanced AI algorithms to outcome prediction, demonstrating that data-driven models can effectively identify high-risk patients and support early intervention strategies 14. Complementing these findings, Wang et al. integrated AI with clinical laboratory evidence to advance mobile health applications in ophthalmology, using ocular surface disease as a case study 15. Collectively, these studies illustrate the translational potential of AI, bridging computational methodologies and practical clinical implementation in precision diagnosis, risk stratification, and personalized medicine. Beyond diagnostic innovation, the journal published a broad array of studies in experimental and translational medicine. These included comprehensive reviews of rare infectious diseases, the establishment of reference intervals for serum uric acid in the Chinese population, analyses of outbreak response strategies for chikungunya fever 16, investigations of traditional Chinese medicine through network pharmacology 17, studies examining immune responses to SARS-CoV-2 variants 18, implementation of patient-based real-time quality control models in laboratory medicine 19, and the development of machine learning–based prognostic models for neonatal bacterial meningitis 20. Taken together, these publications encompass a wide range of disciplines, including laboratory medicine, infectious diseases, oncology, immunology, neurology, endocrinology, pediatrics, parasitology, and biomedical engineering. Although the visibility of some articles remains constrained by current indexing coverage, the scope, quality, and scientific depth of the published work collectively underscore the strong potential and future promise of iLABMED as a multidisciplinary journal in experimental medicine. Global public health is currently confronted with two major challenges: the increasing burden of aging-related diseases, including Alzheimer's disease, osteoporosis, and other age-associated conditions, and the ongoing threat posed by emerging and re-emerging infectious diseases. Effectively addressing these challenges requires sustained scientific innovation and robust cross-disciplinary collaboration. Within this context, several major trends are reshaping the landscape of modern medicine. First, machine learning and AI are being increasingly integrated into clinical practice across a wide range of disciplines, including mental health 21, nursing administration 22, pathology and oncology 23, endocrinology 24, radiology 25, neurology 26, hepatology 27, and intensive care medicine 28. These technologies are increasingly functioning as clinical decision-support tools, facilitating screening, diagnosis, treatment planning, outcome prediction, and rehabilitation. Second, regenerative medicine—particularly advances in cell therapy, biotherapy, and organoid technologies—has emerged as a transformative approach for the treatment of diseases that were previously considered incurable, such as diabetes and neurodegenerative disorders. Continued progress in this field holds the potential to fundamentally alter prevailing paradigms of disease management. Third, the development of novel broad-spectrum antiviral agents with favorable safety profiles and convenient routes of administration remains a critical priority for preparedness against future viral outbreaks. Fourth, growing attention to aging 29 and frailty 30 related conditions underscores the urgent need for integrated systems of elderly care and rehabilitation. In parallel, emerging rehabilitation strategies, including robot-assisted therapy 31, AI-aided rehabilitation 32, and hydrotherapy 30, are gaining increasing clinical relevance. As a journal dedicated to experimental and translational medicine, iLABMED actively engages with and embraces these emerging trends and welcomes high-quality submissions across these evolving domains. As emphasized previously 33, the enduring mission of iLABMED is to bridge the gap between basic research and clinical practice, from bench to bedside. In alignment with this mission, iLABMED will continue to serve as an open and dynamic platform for advancing translational medical research and for contributing to improved global health outcomes. Tetsuya Asakawa and Yi-Wei Tang wrote the original draft. All authors reviewed and approved the final version of the manuscript. The authors have nothing to report. This work was supported by the Shenzhen Science and Technological Foundation (Grant JSGG20220301090005007) and the Shenzhen High-level Hospital Construction Fund (Grant 23274G1001). The authors have nothing to report. The authors have nothing to report. The authors are the editorial board members of this journal. The authors have nothing to report.