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Life
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From Animal Models to Clinical Innovations: Translating Research into Medicine
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From Animal Models to Clinical Innovations: Translating Research into Medicine

A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Animal Science".

Deadline for manuscript submissions: 22 May 2026 | Viewed by 2920

Special Issue Editors

Prof. Dr. Mihaela-Claudia Spataru

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Guest Editor
Department of Public Health, Faculty of Veterinary Medicine, “Ion Ionescu de la Brad” Iasi University of Life Sciences, 700489 Iasi, Romania
Interests: animal experimentation; comparative anatomy and physiology; animal behavior and psychology; animal-based product testing; implantology
Prof. Dr. Manuela Ciocoiu

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Guest Editor
Department of Pathophysiology, “Grigore T. Popa” University of Medicine and Pharmacy, 16 Universitatii Street, 700115 Iasi, Romania
Interests: cardiovascular diseases; metabolic diseases; diabetes mellitus; antioxidants
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This section is devoted to the promotion and dissemination of scientific findings derived from animal research, encompassing a wide array of organisms ranging from insects and invertebrates to higher vertebrates, and always conducted in accordance with current ethical and legal frameworks. Its primary objective is to provide a rigorous platform for the publication of original experimental studies and comprehensive bibliographic reviews that critically evaluate the relevance, validity, and appropriateness of animal use in biomedical investigations. Emphasis is placed on the translational value of such studies, particularly with regard to their contribution to bridging fundamental research with clinical practice.

An essential aspect addressed in this section concerns the recognition of interspecies differences, which often represent a limiting factor in extrapolating preclinical results to human or veterinary medicine. Advances in genetic engineering, including the development of transgenic and genome-edited animal models, are highlighted as significant tools to mitigate these discrepancies and enhance predictive accuracy. Furthermore, this section welcomes contributions that examine the ethical, societal, and regulatory dimensions of animal experimentation, acknowledging the increasing public scrutiny of research practices and the demand for greater transparency and refinement, reduction, and replacement strategies.

Finally, the section encourages submissions exploring the application of animal models across a broad range of scientific domains in both human and veterinary medicine. These include, but are not limited to, comparative morphology, surgery, parasitic diseases, biochemistry, pharmacology, oncology, cardiovascular and metabolic diseases, neuroscience, infectious diseases, and other specialized research fields, where animal experimentation continues to provide indispensable insights into pathophysiology, therapeutic innovation, and translational outcomes.

Prof. Dr. Mihaela-Claudia Spataru
Prof. Dr. Manuela Ciocoiu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Life is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • animal models
  • animal research
  • biomedical research
  • ethics of animal experimentation
  • experimentation on animals
  • interspecies differences
  • translational medicine
  • human clinical medicine

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Published Papers (3 papers)

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19 pages, 1106 KB  
Article
Clinical Prediction of Functional Decline in Multiple Sclerosis Using Volumetry-Based Synthetic Brain Networks
by Alin Ciubotaru, Alexandra Maștaleru, Thomas Gabriel Schreiner, Cristiana Filip, Roxana Covali, Laura Riscanu, Robert-Valentin Bilcu, Laura-Elena Cucu, Sofia Alexandra Socolov-Mihaita, Diana Lăcătușu, Florina Crivoi, Albert Vamanu, Ioana Martu, Lucia Corina Dima-Cozma, Romica Sebastian Cozma and Oana-Roxana Bitere-Popa
Life 2026, 16(3), 459; https://doi.org/10.3390/life16030459 - 11 Mar 2026
Viewed by 480
Abstract
Background: Disability progression in multiple sclerosis (MS) is increasingly recognized as a consequence of large-scale brain network disruption rather than isolated regional damage. Although diffusion tensor imaging (DTI) is the reference method for assessing structural connectivity, its limited availability restricts widespread clinical application. [...] Read more.
Background: Disability progression in multiple sclerosis (MS) is increasingly recognized as a consequence of large-scale brain network disruption rather than isolated regional damage. Although diffusion tensor imaging (DTI) is the reference method for assessing structural connectivity, its limited availability restricts widespread clinical application. There is therefore a critical need for alternative approaches capable of capturing network-level alterations using routinely acquired MRI data. Objective: This study aimed to determine whether synthetic structural connectivity matrices derived from standard regional volumetric MRI can capture clinically meaningful network alterations in MS and predict subsequent functional progression, particularly upper limb decline. Methods: Regional brain volumetry was obtained from routine T1-weighted MRI using an automated, clinically approved volumetric pipeline. Synthetic structural connectivity matrices were generated by integrating principles of structural covariance, distance-dependent connectivity, and disease-specific vulnerability patterns. Graph-theoretical network metrics were extracted to characterize global and regional topology. Machine learning models including logistic regression, support vector machines, random forests, and gradient boosting were trained to predict clinical progression defined by worsening on the 9-Hole Peg Test. Dimensionality reduction was performed using principal component analysis, and model performance was evaluated using balanced accuracy, AUC-ROC, and resampling-based validation. Feature importance analyses were conducted to identify network vulnerability patterns. Results: Synthetic connectivity networks exhibited biologically plausible properties, including preserved but attenuated small-world organization. Global efficiency showed a strong inverse correlation with disability severity (EDSS). Patients with clinical progression demonstrated marked reductions in network integration and segregation, alongside increased characteristic path length. Machine learning models achieved robust prediction of upper limb functional decline, with ensemble-based methods performing best (balanced accuracy > 80%, AUC-ROC up to 0.85). A limited subset of connections accounted for a disproportionate share of predictive power, predominantly involving frontoparietal associative networks, thalamocortical pathways, and inter-hemispheric connections. In a longitudinal subset, network-level alterations preceded measurable clinical deterioration by several months. Conclusions: Synthetic structural connectivity derived from routine volumetric MRI captures clinically relevant network-level disruption in multiple sclerosis and enables accurate prediction of functional progression. By bridging network neuroscience with widely accessible imaging data, this framework provides a pragmatic alternative for connectomic analysis when diffusion imaging is unavailable and supports a network-based understanding of disease evolution in MS. Full article
(This article belongs to the Special Issue From Animal Models to Clinical Innovations: Translating Research into Medicine)
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16 pages, 1370 KB  
Article
Evaluation of Immune Response Dynamics: Analyzing the Parameters of Complete Blood Count (CBC) in Experimental Borreliosis
by Diana Mihaela Alexandru, Diana Larisa Ancuţa and Cristin Coman
Life 2025, 15(11), 1758; https://doi.org/10.3390/life15111758 - 16 Nov 2025
Viewed by 736
Abstract
The spirochete Borrelia is responsible for Lyme disease, a multisystemic infection and growing public health concern. This study aimed to evaluate host response dynamics to Borrelia bavariensis by analyzing hematological parameters as potential immuno-inflammatory markers in a murine model. Forty C3He/HeNCrl mice were [...] Read more.
The spirochete Borrelia is responsible for Lyme disease, a multisystemic infection and growing public health concern. This study aimed to evaluate host response dynamics to Borrelia bavariensis by analyzing hematological parameters as potential immuno-inflammatory markers in a murine model. Forty C3He/HeNCrl mice were inoculated intradermally with B. bavariensis (5 × 105 spirochetes/100 µL/mouse) and monitored for 90 days. Samples were collected at defined intervals for microbiological examination, hematology, and qPCR. Microbiological and qPCR testing revealed infection between days 7–21; results were negative on days 28–42. At later stages (days 60 and 90), Borrelia was only detectable by qPCR, highlighting differences in diagnostic sensitivity. Hematological analysis showed that the neutrophil-to-lymphocyte ratio (NLR) and systemic immuno-inflammatory index (SII) peaked on day 7 (p < 0.0001), followed by gradual normalization until day 35. These markers reflected the intensity of the inflammatory response and defined three distinct phases of host reaction. Overall, results demonstrate the complexity of immune responses in B. bavariensis infection and underscore the value of monitoring hematological indices for understanding host–pathogen interactions. This approach supports the potential use of simple blood markers in diagnostic strategies with translational relevance for clinical practice. Full article
(This article belongs to the Special Issue From Animal Models to Clinical Innovations: Translating Research into Medicine)
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22 pages, 1218 KB  
Systematic Review
Systematic Review: Exploring Inter-Species Variability in Diabetes Mellitus for Translational Medicine
by Luminița Diana Hrițcu, Vasile Boghian, Geta Pavel, Teodor Daniel Hrițcu, Florin Nechifor, Alexandru Spataru, Alexandra Andreea Cherșunaru, Alexandru Munteanu, Manuela Ciocoiu and Mihaela-Claudia Spataru
Life 2026, 16(1), 64; https://doi.org/10.3390/life16010064 - 31 Dec 2025
Viewed by 944
Abstract
Interspecies variability in diabetes mellitus (DM) represents a critical challenge for translational medicine, as metabolic pathways, pancreatic architecture, and therapeutic responses differ substantially across animal models. This systematic review, conducted according to PRISMA 2020 guidelines, synthesized evidence from 86 eligible studies published between [...] Read more.
Interspecies variability in diabetes mellitus (DM) represents a critical challenge for translational medicine, as metabolic pathways, pancreatic architecture, and therapeutic responses differ substantially across animal models. This systematic review, conducted according to PRISMA 2020 guidelines, synthesized evidence from 86 eligible studies published between 2001 and 2025. Comparative data from rodents, dogs, cats, pigs, non-human primates, and humans were analyzed to identify species-specific patterns in insulin secretion, insulin resistance (IR), β-cell dysfunction, microbiota–metabolism interactions, and susceptibility to diabetic complications. Results indicate that spontaneous diabetes in dogs closely mirrors human type 1 diabetes (T1DM), whereas feline obesity-associated diabetes reflects key features of human type 2 diabetes (T2DM). Rodent models remain essential for mechanistic and genetic studies but show limited chronicity and lower predictive fidelity for long-term outcomes. Non-human primates exhibit the highest physiological similarity to humans, especially regarding β-cell structure and incretin response, supporting their role in advanced translational studies. Major limitations included methodological heterogeneity and inconsistent molecular reporting. Integrating spontaneous models with standardized protocols and multi-omics approaches enhances translational relevance and supports more accurate model selection in diabetes research. Full article
(This article belongs to the Special Issue From Animal Models to Clinical Innovations: Translating Research into Medicine)
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