Applied Biosciences

Review

18 pages, 3879 KB

Open AccessReview

Virtual Brain and Digital Twins in Neurogenetics: From Multimodal Patient Data to Genomically Informed, Clinically Actionable Models

by Lorenzo Cipriano

Appl. Biosci. 2026, 5(2), 37; https://doi.org/10.3390/applbiosci5020037 (registering DOI) - 2 May 2026

Abstract

Molecular diagnosis has advanced rapidly in neurogenetic disorders, yet translating genotype into patient-specific predictions of brain network dysfunction and progression remains limited. Virtual brain models provide a structured solution by embedding individual anatomy and connectomics into biophysical whole-brain simulations. The critical step is [...] Read more.

Molecular diagnosis has advanced rapidly in neurogenetic disorders, yet translating genotype into patient-specific predictions of brain network dysfunction and progression remains limited. Virtual brain models provide a structured solution by embedding individual anatomy and connectomics into biophysical whole-brain simulations. The critical step is to position genetics not as a diagnostic label, but as a constructive input to model design. This review outlines a genetics-centered framework for virtual brain modeling. First, atlas-derived transcriptomic and cell-type maps can define region-specific molecular priors, constraining vulnerability or excitability parameters and reducing model degeneracy. Second, when reproducible genotype-linked network phenotypes exist, mutation groups can inform stratified initialization and progression regimes. Third, at the patient level, exome and CNV data—summarized as pathway burdens and, where appropriate, calibrated polygenic modifiers—can be translated into individualized priors or regularizers, provided that mapping rules are explicit and externally validated. By integrating genetics at multiple levels of evidence, virtual brain models gain mechanistic plausibility, improved calibration, and explicit uncertainty quantification. The most realistic impact over the next few years is likely to be improved stratification, progression-aware forecasting, and scenario-based decision support in rare neurogenetic diseases, especially where longitudinal cohort infrastructure and validated biomarker inputs are already available, rather than deterministic individual prediction. Full article

(This article belongs to the Special Issue Feature Reviews for Applied Biosciences)

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16 pages, 740 KB

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Hormonal and Non-Hormonal Estrus Synchronization in Sheep and Goats: Physiological Basis, Efficacy, and Practical Applications

by Daniel Berean, Liviu Marian Bogdan, Simona Ciupe and Raluca Cimpean

Appl. Biosci. 2026, 5(2), 35; https://doi.org/10.3390/applbiosci5020035 - 1 May 2026

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Abstract

Efficient reproductive management is essential for optimizing productivity and sustainability in sheep and goat production systems. Estrus synchronization (ES) has emerged as a pivotal tool for coordinating mating, enhancing fertility, facilitating artificial insemination (AI), and supporting out-of-season breeding. Hormonal protocols, including progesterone devices, [...] Read more.

Efficient reproductive management is essential for optimizing productivity and sustainability in sheep and goat production systems. Estrus synchronization (ES) has emerged as a pivotal tool for coordinating mating, enhancing fertility, facilitating artificial insemination (AI), and supporting out-of-season breeding. Hormonal protocols, including progesterone devices, prostaglandins, and gonadotropin or gonadoliberine treatments, provide the highest precision in estrus and ovulation timing, with estrus response rates exceeding 90% and conception rates commonly between 65–85%. These methods are particularly effective in intensive or AI-based systems but are constrained by cost, labor, regulatory restrictions, and welfare considerations. Non-hormonal strategies, such as the ram effect, photoperiod manipulation, nutritional flushing, and management-based interventions, exploit natural physiological, socio sexual, and nutritional cues to partially synchronize estrus. While these approaches exhibit greater variability and lower precision than hormonal methods, they offer advantages in low input, organic, and extensive systems by improving reproductive clustering, ovulation, and lambing compactness. Among these, the ram effect is the most effective and widely applicable. Integrated reproductive management, combining hormonal or non-hormonal strategies with optimized nutrition, health, and flock management, is critical for achieving predictable and sustainable reproductive outcomes. Future research should focus on refining hormone-sparing protocols and enhancing the reliability of natural synchronization methods. Full article

(This article belongs to the Special Issue Feature Reviews for Applied Biosciences)

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25 pages, 3787 KB

Open AccessReview

Implementation of Generative AI in Biomedical Research and Healthcare

by Anastasios Nikolopoulos and Vangelis D. Karalis

Appl. Biosci. 2026, 5(2), 34; https://doi.org/10.3390/applbiosci5020034 - 1 May 2026

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Abstract

Artificial intelligence has evolved to generative AI (GenAI), a paradigm shift that has shifted the emphasis away from the evaluation of existing patterns to the generation of novel biological and medical material. This study examines GenAI achievements in biosciences and medical fields the [...] Read more.

Artificial intelligence has evolved to generative AI (GenAI), a paradigm shift that has shifted the emphasis away from the evaluation of existing patterns to the generation of novel biological and medical material. This study examines GenAI achievements in biosciences and medical fields the last five years in these fields using databases such as PubMed and Scopus. The paper highlights the recent evolution in biomedical research from virtual screening to de novo design. It illustrates how models like RFdiffusion and ProteinMPNN leverage “inverse folding” to assemble novel of proteins and drugs. Ultimately, these generative methods yield candidate with enhanced binding affinity and structural stability. For example, exploratory studies suggest GenAI has the potential to address inefficiencies via automatic documentation in the therapeutic sector, and it may enhance research capabilities by using Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) to generate synthetic clinical trial data that preserves confidentiality. In addition, the review argues that though GenAI democratizes medical education through scalable simulations, it raises questions about long-term knowledge retention. Finally, GenAI also offers a transformative “write” capability for biology, but its responsible application will require addressing model “hallucinations” and building Explainable AI (XAI) and robust ethical frameworks. Full article

(This article belongs to the Special Issue Feature Reviews for Applied Biosciences)

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28 pages, 1123 KB

Open AccessReview

Plant Hormone Regulation of Competitive Growth: Implications for Agriculture and Inclusive Fitness

by Jasmina Kurepa and Jan A. Smalle

Appl. Biosci. 2026, 5(2), 24; https://doi.org/10.3390/applbiosci5020024 - 1 Apr 2026

Viewed by 443

Abstract

While “survival of the fittest” implies that competition is the main driver of evolution, cooperation and altruism are also widespread in nature, even among plants. This suggests that natural selection favors regulatory systems that balance competitive growth with restraint, depending on context. We [...] Read more.

While “survival of the fittest” implies that competition is the main driver of evolution, cooperation and altruism are also widespread in nature, even among plants. This suggests that natural selection favors regulatory systems that balance competitive growth with restraint, depending on context. We propose that plant hormones are key mediators of this balance, acting along a spectrum from competition to cooperation. Based on evidence from developmental, ecological, and evolutionary studies, we classify major plant hormones by their roles in competitive behavior: auxin, gibberellins, and brassinosteroids drive competitive foraging and resource acquisition, while cytokinins, abscisic acid, strigolactones, ethylene, salicylic acid, and jasmonate are linked to growth restraint, resource conservation, and communal defense. This functional partitioning reflects a modular hormonal architecture that allows plants to adapt flexibly to their environment and social context. We explore how this classification could inform the use of plant hormones in agriculture and advance research in plant kin selection and inclusive fitness. Full article

(This article belongs to the Special Issue Feature Reviews for Applied Biosciences)

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18 pages, 1057 KB

Open AccessReview

CNS-Specific and Coagulation Biomarkers in Traumatic Brain Injury: Beyond the Reach of the Scalpel—A Scoping Review

by Serban Iancu Papacocea, Ioana Anca Bădărău and Toma Marius Papacocea

Appl. Biosci. 2026, 5(1), 12; https://doi.org/10.3390/applbiosci5010012 - 5 Feb 2026

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Abstract

Despite significant advances in neurosurgical and critical care, traumatic brain injury (TBI) remains a major cause of morbidity and mortality. Surgical treatment of intracranial hemorrhagic lesions can only target the primary mechanical injuries and their immediate consequences but fails to address the biochemical [...] Read more.

Despite significant advances in neurosurgical and critical care, traumatic brain injury (TBI) remains a major cause of morbidity and mortality. Surgical treatment of intracranial hemorrhagic lesions can only target the primary mechanical injuries and their immediate consequences but fails to address the biochemical pathological cascade that unfolds during the second injury. This review synthesizes current knowledge regarding the use of several biomarkers in diagnosis and prognosis assessment. A structured literature search was conducted by querying the PubMed database. Articles evaluating diagnostic and prognostic biomarkers in adult TBI were screened according to Prisma guidelines, and data regarding biomarkers type, cut-off values, and correlations with the outcome were extracted and summarized. Among Central Nervous System (CNS)-Specific markers, S100 calcium-binding protein (S100B) emerged as a remarkably strong negative predictor for Computed Tomography (CT)-visible intracranial lesions (NPV = 97.3–100%), whereas glial fibrillary acidic protein (GFAP) yielded both high NPV and brain specificity. Coagulation parameters such as the international normalized ratio (INR) and fibrinogen were independently correlated with mortality and unfavorable outcomes. Fibrinogen displayed a bidirectional relationship with increased mortality risk at both low (<2 g/L) and high (>4.5 g/L) values. In conclusion, biomarkers quantify the otherwise invisible progression of secondary traumatic brain injury that persists even after successful surgery. Full article

(This article belongs to the Special Issue Feature Reviews for Applied Biosciences)

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14 pages, 896 KB

Open AccessReview

Regulation of NO Synthesis by Caveolin-1: A Review of Its Importance in Blood Vessels, Perivascular Adipose Tissue and in Atherosclerosis

by Abdmajid Saad Hwej, Mohammed Alsharif, Ali Al-Ferjani and Simon Kennedy

Appl. Biosci. 2026, 5(1), 11; https://doi.org/10.3390/applbiosci5010011 - 5 Feb 2026

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Abstract

Background: Caveolin-1 (Cav-1) is a protein found in various forms and locations within cells and tissues throughout the body. Studying its structure and function provides valuable insights into key cellular processes such as growth, death, and cell signaling. This review synthesizes evidence from [...] Read more.

Background: Caveolin-1 (Cav-1) is a protein found in various forms and locations within cells and tissues throughout the body. Studying its structure and function provides valuable insights into key cellular processes such as growth, death, and cell signaling. This review synthesizes evidence from human studies and animal models to elucidate the complex role of Caveolin-1 (Cav-1) in regulating nitric oxide (NO) synthesis within the vasculature and perivascular adipose tissue (PVAT) during atherosclerosis. Cav-1 is a master regulator of endothelial NO synthase (eNOS), a relationship well-defined in rodent endothelial cells and cell lines. In humans, loss-of-function CAV1 mutations are linked to pulmonary arterial hypertension, suggesting a protective vascular role. Paradoxically, Cav-1 is upregulated in atherosclerotic plaques. Whether this represents a pathological process reducing NO bioavailability or a compensatory response remains unclear. Furthermore, the direct translation of the Cav-1/eNOS axis to PVAT—a metabolically active tissue expressing Cav-1—is not fully established outside of preclinical models. PVAT influences vascular tone and inflammation, potentially contributing to the paradoxical, stage-specific roles of Cav-1 in disease. Resolving these questions requires integrating human observational data with mechanistic insights from animal models to evaluate Cav-1 as a therapeutic target in vascular disease. Full article

(This article belongs to the Special Issue Feature Reviews for Applied Biosciences)

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34 pages, 872 KB

Open AccessReview

Bridging the Gap: A Scoping Review of Pre-Analytical Variability in Biofluid Metabolomics

by Yumna Ladha, Sushmita Sanaka, Adam Burke, Royston Goodacre, Karina T. Wright, Jade Perry and Charlotte H. Hulme

Appl. Biosci. 2026, 5(1), 10; https://doi.org/10.3390/applbiosci5010010 - 4 Feb 2026

Cited by 1 | Viewed by 646

Abstract

Metabolic profiling enables comprehensive characterisation of the small molecules that are part of the biochemical composition of biological fluids. The most widely profiled biofluids include serum and plasma. Additionally synovial fluid provides a direct reflection of the metabolomic environment of joints and holds [...] Read more.

Metabolic profiling enables comprehensive characterisation of the small molecules that are part of the biochemical composition of biological fluids. The most widely profiled biofluids include serum and plasma. Additionally synovial fluid provides a direct reflection of the metabolomic environment of joints and holds promise for biomarker discovery in arthropathies. However, the reproducibility of metabolomics data is highly sensitive to pre-analytical variation, and at the present time, standardised protocols for synovial fluid remain underdeveloped. This review aims to identify and evaluate the existing literature on effects of biofluid pre-analytical handling treatments on metabolic profiles. This review was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. A search was carried out to identify studies employing LC-MS, GC-MS, and NMR spectroscopy for the investigation of factors including sample collection variables, pre-centrifugation conditions, centrifugation parameters, post-centrifugations conditions, sample storage conditions, and freeze/thaw cycling. Best practice recommendations emerging from this review include the use of additive free serum and heparin plasma tubes, the centrifugation of samples within two hours of collection, immediate storage of samples at −80 °C, and avoidance of repeated freeze/thaw cycling. However, while pre-analytical influences have been extensively characterised for plasma and serum, evidence for synovial fluid remains limited. Overall, the findings highlight the existing recommendations for plasma and serum and demonstrate the need for standardised pre-analytical protocols and validation of quality control markers to advance synovial fluid metabolomics. Full article

(This article belongs to the Special Issue Feature Reviews for Applied Biosciences)

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13 pages, 421 KB

Open AccessReview

Urinary Markers for Prostate Cancer: State of the Art

by Carlo Giorgio Costi, Serena Sartori, Riccardo Danuso, Andrea Piasentin, Paolo Umari and Giovanni Liguori

Appl. Biosci. 2025, 4(2), 24; https://doi.org/10.3390/applbiosci4020024 - 8 May 2025

Cited by 6 | Viewed by 5082

Abstract

Prostate cancer (PCa) is one of the most common malignancies in men, where early and accurate detection is crucial. While PSA testing has been the diagnostic standard, its limited specificity leads to unnecessary biopsies and missed significant cancers. Urinary biomarkers such as PCA3 [...] Read more.

Prostate cancer (PCa) is one of the most common malignancies in men, where early and accurate detection is crucial. While PSA testing has been the diagnostic standard, its limited specificity leads to unnecessary biopsies and missed significant cancers. Urinary biomarkers such as PCA3 and TMPRSS2-ERG and multi-marker assays (MyProstateScore, SelectMDx, and ExoDx) offer a promising alternative. This narrative review examines their diagnostic performance and clinical utility with the aim of understanding whether they can be integrated with the established tests and exams already in use. A literature search of PubMed, Scopus, and Medline identified some relevant recent studies (2010–2025). The findings show that PCA3 and TMPRSS2-ERG improve specificity over PSA, while multi-marker tests enhance risk stratification and reduce unnecessary procedures. MPS integrates urinary biomarkers with PSA, achieving over 95% sensitivity and negative predictive value for clinically significant cancers. SelectMDx demonstrates ~90% negative predictive value, and ExoDx assesses urinary exosomes to predict aggressive disease. Despite their advantages, challenges persist, including variability in performance, cost, and accessibility. Urinary biomarkers represent a major step toward more precise, less invasive diagnostics, with future research needed to optimize clinical integration and cost-effectiveness. Full article

(This article belongs to the Special Issue Feature Reviews for Applied Biosciences)

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