Applied Biosciences

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

Cervical cancer is associated with persistent human papillomavirus (HPV) infections. The early detection of HPV is one of the key strategies for the effective treatment of cervical cancer. Current HPV molecular detection methods use enzyme-based nucleic acid amplification strategies that, although specific and sensitive, involve extensive workflows. Enzyme-free isothermal amplification detection strategies with the potential to adapt to low-resource settings for HPV oncogenic transcripts remain limited. This study aimed to validate a fluorescence-based branched hybridization chain reaction (bHCR) assay for the targeted detection of HPV 16/35 E6 oncogenic transcripts. Analytical performance was evaluated using a synthetic target and a negative clinical matrix, whereas the diagnostic performance of the bHCR assay was evaluated using clinically characterized samples (n = 67). The study demonstrated assay linearity over an analyte concentration range of 0.625–40 µM, with a statistically significant correlation between the fluorescence signal and target concentration (r² = 0.928, p < 0.0001). Analytical accuracy was assessed by pre-extraction spike recovery; achieved recoveries ranged from 70% to 86%, indicating potential RNA loss during the assay workflow. Analytical sensitivity determined the background signal threshold limit of blank (LoB) as 16,251.6 RFU, with detection and quantification at concentrations of 0.0625 µM (≈2.6 × 10¹¹ copies per reaction, limit of detection (LoD) and 0.125 µM (≈5.3 × 10¹¹ copies per reaction, limit of quantification (LoQ). The assay exhibited high diagnostic performance, with a diagnostic cut-off of 16,481 RFU and an area under the curve (AUC) of 0.9194. Specificity and sensitivity of the assay were 94% and 86%, respectively, with a Negative Predictive Value (NPV) of 85% and a Positive Predictive Value (PPV) of 94%. These findings demonstrate a reliable analytical assay with excellent diagnostic discrimination and warrant further optimization and expanded clinical validation. Full article

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

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 study compared the quality and bioactive composition of cloudy apple juices produced from four traditional and four conventional apple cultivars immediately after harvest and following cold storage of the fruit at 4 °C for three and six months. Apples were harvested at the ripening stage at the same criteria, stored as whole fruit, and processed into cloudy juice after harvest, three, and six months of storage. Physicochemical parameters and sugar composition were determined, while phenolic compounds were quantified by HPLC-PDA. Antioxidant activity, total phenolic, and flavonoid content were measured spectrophotometrically. All analyses were performed in technical triplicate. The results revealed notable differences between traditional and conventional cultivars. Juices produced from traditional apple cultivars exhibited significantly higher total polyphenol and flavonoid contents than those from conventional cultivars. Significant variations in catechin, myricetin, quercetin, and epigallocatechin levels were also observed among cultivars. The traditional apple cultivar ‘Mašanka’ showed higher concentrations of quercetin (0.09 ± 0.01 µg/mL), chlorogenic acid (486.58 ± 5.48 µg/mL), catechin (8.76 ± 0.54 µg/mL), epicatechin (20.22 ± 0.20 µg/mL), and phloridzin (13.48 ± 0.19 µg/mL) compared to the other cultivars. In contrast, conventional cultivars showed higher concentrations of myricetin and procyanidin B1. Moreover, the content of TA, sucrose, and glucose decreased, whereas pH, fructose, TSS (except for ‘Fuji’ and ‘Granny Smith’) increased. The TFC decreased in traditional apple cultivars, while it increased in conventional cultivars; however, the TFC in conventional cultivars remained lower than in traditional ones. Overall, these findings demonstrate that the cold storage of apples significantly affects juice composition and highlight the advantages of traditional apple cultivars for producing juices with enhanced phenolic content and antioxidant activity. Full article

Brucellosis poses a persistent threat to livestock health in high-altitude pastoral regions of China, where harsh environments and semi-nomadic grazing increase transmission risk. Existing surveillance systems rely mainly on periodic serological testing and lack effective early warning capability. This study proposes an ensemble learning-based early warning framework integrating veterinary epidemiological indicators with environmental and herd-movement data. A total of 4826 herd-level records collected over five years (2019–2024) were analyzed, with an overall positivity rate of 11.4%. Multi-source data, including serological, clinical, reproductive, vaccination, meteorological, pasture-management, and herd-movement information (from GPS tracking and structured surveys), were integrated through epidemiology-guided feature engineering. To address class imbalance and temporal dynamics, Synthetic Minority Over-sampling Technique (SMOTE) resampling and sliding time-window features were applied. The proposed ensemble model combines Random Forest, XGBoost, and LightGBM using a soft-voting strategy, with logistic regression as a baseline. Results show that the ensemble model outperforms single models, achieving an AUC of 0.86 and a PR-AUC of 0.65. After threshold optimization, sensitivity increased from 0.78 to 0.87. Under field conditions, the system provided herd-level early warnings with an average lead time of approximately 12 days before confirmed outbreaks, demonstrating its feasibility and practical value for proactive brucellosis surveillance in high-altitude pastoral systems. Full article

Castrate-resistant prostate cancer (PCa) is a critical situation in which many patients will relapse. Hormonal androgen deprivation therapy (HADT) is the gold standard of care when a patient relapses, following primary surgical or radiation therapy. Usually, the benefits from HADT are poor and recurrent disease after HADT treatment is termed castrate-resistant prostate cancer (CRPC), which is in most cases fatal. The therapeutic regimens for CRPC include chemotherapy with docetaxel, immunotherapy agent sipuleucel-T, the taxane cabazitaxel, the CYP17 inhibitor abiraterone acetate and the androgen receptor (AR) antagonist enzalutamide. Thus, it is imperative to study the inherent property of prostate cancer cells, to resist therapy and reconsider the therapeutic protocols (continuous v’s intermittent). We make use of a hybrid mathematical model which consists of an extension of a very potent ordinary differential equation (ODE) Baez–Kuang model, combined with two Game Theory components: the Minority Game for adaptive behavior and the Axelrod model for heterogeneity behavior. Our study suggests that increasing tumor adaptability, through Minority Game dynamics, improves short-term prostatic-specific antigen (PSA) control and stabilizes therapy cycles. However, this comes at the cost of driving the tumor to a homogeneous, androgen-independent (AI) state, which is therapy-resistant. Conversely, maintaining heterogeneity, via Axelrod dynamics, sustains a mixed population, with androgen-dependent (AD) cells persisting longer and potentially delaying resistance emergence. Full article

Whey is a major by-product of the dairy industry and represents a valuable source of proteins that can be enzymatically converted into bioactive peptides with diverse health-related functions. In recent years, increasing attention has been given to whey-derived peptides due to their antioxidant, antihypertensive, antimicrobial, anti-inflammatory, antithrombotic, immunomodulatory, and anticancer activities, highlighting their potential use as functional ingredients and nutraceutical compounds. The generation and biological functionality of these peptides are strongly influenced by the protein source, processing conditions, enzymatic or microbial hydrolysis strategies, and peptide structure. Unlike the existing literature, this review provides an analysis of individual peptide sequences, meticulously linking their specific chemical structures to their diverse biological activities, such as antioxidants, antihypertensive, and immunomodulatory effects. By moving beyond general protein hydrolysis, this work offers a unique comparative framework that evaluates how these distinct peptide fractions perform under industrial conditions. Furthermore, it bridges the gap between laboratory discovery and commercial implementation, focusing on critical parameters for large-scale production, stability in functional food matrices, and the regulatory pathways required for market-ready nutraceuticals. This integrated approach provides a strategic roadmap for translating molecular bioactivity into high-value industrial applications. This review provides an applied overview of recent advances in the production of whey bioactive peptides, emphasizing enzymatic generation methods, structure–activity relationships, and underlying mechanisms of action associated with their biological effects. In addition, current and emerging applications of whey-derived peptides in functional foods, nutraceuticals, and health-oriented formulations are critically discussed. Finally, key challenges related to peptide stability, bioavailability, industrial scalability, and regulatory aspects are addressed to identify future perspectives for the effective translation of whey bioactive peptides from research to practical applications. Full article

Phytate (myo-inositol hexakisphosphate) is a polyphosphate found in plant-based foods whose intestinal absorption mechanisms are insufficiently understood. Due to its high affinity for calcium, phytate can deplete extracellular calcium and potentially affect tight junction integrity, which could increase paracellular permeability. This study investigated the permeation of phytate across Caco-2 cell monolayers depending on calcium concentration. Differentiated Caco-2 cells were cultured on semi-permeable membranes and incubated with various phytate concentrations (0.17–1.66 mM) in media with low (2.1 µM) or normal (1.8 mM) calcium concentration. Phytate permeability and tight junction integrity were analyzed using HPLC and Lucifer yellow as a paracellular marker. At low calcium concentration, significant permeability was observed starting from 0.55 mM phytate (~60% at 1.66 mM), while at normal calcium concentration, significant permeability was only detectable at 1.66 mM. The increased Lucifer yellow permeation correlated with phytate permeation and confirmed tight junction disruption. Phytate that reached the basolateral side at physiological calcium concentration precipitated completely as insoluble calcium–phytate complex. These results demonstrate that phytate can pass intestinal epithelium via the paracellular pathway and increase the paracellular permeability, especially at low apical concentrations of calcium. Full article

Two spectrin-sensitive relaxations have been reported in the RBC plasma membrane: β_s (1.4 MHz, related to the interface β-relaxation) and γ1_s (9 MHz, rotation alignment of spectrin-bound dipoles by penetrating electric field). Here, a third (α_s) relaxation type is reported within the frequency region of surface (α) relaxation. With low-ion-strength outside media, the adsorption of blood plasma immunoglobulins on RBCs was found to inhibit β_s and γ1_s relaxations, while α_s relaxation was enforced with strong inflammation. The three relaxations are represented by three consecutive segments on the Cole′s plots: Δε_rd″.ω against Δε_r′ and Δε_rd″/ω against Δε_r′. Here, ω is the frequency of the field and Δε_r* = Δε_r′ + j.Δε_rd″ is the change in the relative complex dielectric permittivity of RBC suspension at the denaturation temperature of spectrin. The β_s segment in Δε_rd″.ω against the Δε_r′ plot could be regarded as a vector (complex number) whose projection on the vertical axis (the irreversible loss in energy) could express the ability of the plasma membrane to deform (under the impact of shear stress). Full article

The food industry has a strong interest in lactic acid bacteria (LAB) because of their probiotic potential and health advantages. LAB have been previously isolated from pulque and agave sap, showing antibacterial action. However, their reaction to stress can limit their survivability, and their biological activities are strain-specific. To ascertain the impact of LAB isolated from pulque and agave sap on lifespan, thermal and oxidative stress, and health span parameters, we fed the nematode Caenorhabditis elegans these bacteria. The nematodes fed the Escherichia coli OP50 strain were utilized as a control for each experiment. Animals were fed each strain for four days starting from L4 and either (day 5) exposed to oxidative stress caused by high hydrogen peroxide concentrations (8 mM) or acute heat stress (35 °C) for four hours. The strains Lacticaseibacillus rhamnosus and Lactiplantibacillus plantarum significantly improved lifespan, fertility, movement, and heat shock resistance. Lacticaseibacillus casei enhanced the C. elegans lifespan, and Levilactobacillus brevis only increased its survivability in the heat shock studies. Interestingly, we discovered a harmful impact on animals fed Pediococcus acidilactici. This study highlights that, even when strains come from the same plant source, their biological activity might differ significantly. Full article

Bidirectional communication between the oocyte and surrounding follicular cells coordinates follicle growth, meiotic maturation, and the acquisition of competence. We aimed to identify genes related to follicular crosstalk and the secretory pathway as candidate mediators of cumulus–oocyte complex (COC) crosstalk in cattle. Expressed sequence tags (ESTs) from bovine COCs were retrieved from databases and screened for genes related to secretion and the secretory pathway using SignalP and SecretomeP, and transmembrane proteins were removed, yielding 13 candidate genes. Candidate expression was examined in two GEO RNA-seq datasets to assess enrichment in oocytes versus cumulus cells. RT–qPCR profiling across tissues and reproductive cell types enabled principal component analysis and correlation/network analysis, visualized as heatmaps and Cytoscape, revealing an INBHA-SERPINE2-SDF2L1 co-expression pattern. INHBA and SERPINE2 protein products are secreted, whereas SDF2L1 protein is a secretory pathway-associated, endoplasmic reticulum-resident chaperone. Promoter sequences of INHBA, SERPINE2, and SDF2L1 were scanned with FIMO using JASPAR motifs, identifying shared SMAD-associated motifs and FSH/cAMP-related motif families. The data support a co-regulation model in which endocrine FSH/cAMP and activin/TGF-β–SMAD inputs converge on a shared transcriptional program consistent with a putative INHBA–SERPINE2–SDF2L1 co-regulated module, linking cumulus extracellular matrix remodeling/protease control with oocyte ER protein folding capacity during COC maturation. Full article

Background: Crimean-Congo hemorrhagic fever (CCHF) is a severe tick-borne viral disease with a high fatality rate, and no licensed vaccines are currently available. The nucleoprotein (NP) of the Crimean-Congo hemorrhagic fever virus (CCHFV) plays a critical role in viral replication and immune recognition, making it a promising target for vaccine development. This study aimed to design and evaluate a multiepitope recombinant DNA vaccine targeting the NP of CCHFV. Methods: Cytotoxic T lymphocyte (CTL) epitopes from the NP were predicted via immunoinformatics approaches and systematically assessed for antigenicity, allergenicity, toxicity, hydrophobicity, and global population coverage. The selected epitopes were incorporated into four DNA vaccine constructs driven by a cytomegalovirus promoter, adjuvanted with human β-defensin 3 (hBD3), and fused to the reporter protein mRuby3. The constructs were evaluated in vitro using a fluorescent reporter system designed to provide a readout of TCR signaling upon the co-culture of T lymphocytes with differentiated monocytic cells expressing antigens. In vivo immunogenicity and protective efficacy were assessed in BALB/c (exploratory pilot) and IFNAR^−/− mice, a highly susceptible model for viral infection. Cytokine responses were measured to assess immunogenicity. Results: In vitro assays showed predominantly antigen-independent T-cell activation, suggesting that nonspecific stimulation inherent to the reporter co-culture system likely obscured the detection of antigen-specific TCR signaling. In vivo analyses in BALB/c mice revealed that the constructs elicited only modest systemic cytokine profiles while CCHFV-specific IgG and IFN-γ secretion remained undetectable, indicating that antigen-specific T-cell and antibody responses were limited. In the IFNAR^−/− challenge model, several peptide groups achieved significant 2–3 log reductions in tissue viral RNA and infectious titers (p < 0.05 vs. sham). However, the observed viral modulations were insufficient to reach the protective threshold and did not translate to a survival benefit (0%). Conclusion: Despite a rational in silico foundation, the multiepitope DNA vaccine constructs demonstrated limitations in inducing potent, antigen-specific immunity across both mouse models. The lack of antigen-specific responses indicates limitations in epitope selection, construct design, and delivery strategies, requiring optimization of next-generation epitope-based vaccines. These findings highlight the complexity of translating computational epitope predictions into functional vaccines, and provide benchmark data as a framework to guide future optimizations. Full article

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

Cancer is an alarming health concern and economic burden in both developed and developing countries. Recently, there has been a growing demand for new alternative medications with more effectiveness and fewer harmful effects. During the past decades, a set of chemotherapeutic agents has been developed to fight against a large spectrum of cancer types. Unfortunately, their use is associated with a high level of toxicity; they are expensive, also, and their deployment is restricted by the emergence of cellular resistance. Plant-based components are garnering attention due to their low toxicity, selectivity, efficiency, and ease of accessibility. Alkaloids are one of these targeted compounds. Indeed, they are a highly diverse group with basic heterocyclic nitrogen-containing alkaloids that exhibit potent anticancer effects against a large panel of solid and liquid tumors, such as lung, breast, leukemia, liver, and colon cancer. The main molecular mechanisms involved in alkaloids’ anticancer effect are the induction of apoptosis via the extrinsic and intrinsic pathways, DNA damage, and the inhibition of cell cycle progression. Amazingly, these auspicious compounds exhibited strenuous inhibitory effects against a whole range of key enzymes involved in cancer progression and metastasis, such as Cytochrome P450 (CYP450), Cyclooxygenase-2 (Cox-2), Lysine-Specific Demethylase 1 (LSD1), Poly [ADP-ribose] polymerase (PARP), and topoisomerase, mainly through two action modes, namely irreversible and reversible inhibition. Furthermore, several conventional extraction methods have been developed to extract bioactive compounds from natural matrices, such as Soxhlet and hot water extraction. However, these techniques have many drawbacks, as they require a large amount of organic solvents, which not only affect human health but also generate severe environmental issues. To overcome these limitations, multiple eco-extraction techniques have emerged as potential alternatives to traditional extraction methods such as ultrasonic extraction, microwave-assisted extraction, and supercritical fluid extraction. In fact, they are considered eco-friendly and efficient technologies with less time and solvent consumption. Overall, this review aims to provide an updated overview of the most prominent anticancer alkaloids that have not been well reviewed already, as well as the main green extraction techniques relevant to the extraction of antineoplastic alkaloids. Full article

Musculoskeletal (MSK) diseases present major health and economic challenges globally. Advancing age, diseases like osteoarthritis (OA), osteoporosis (OP), fracture and other conditions significantly reduce the quality of life (QOL) of these patients. Current pharmaceutical approaches are able to manage symptoms for some of these; however, they do not provide long-term solutions. Surgeries which are usually the final resort, present an added layer of challenges with the risk of post-surgical complications. The last couple of decades have observed an increase in the use of tissue engineering and regenerative medicine (TERM) for bone tissue engineering (BTE) applications. With the advent of artificial intelligence (AI), there will inevitably be an intersection of AI with TERM for MSK conditions. As of 2025, AI is already in use for small-scale applications in BTE including data extraction, image analysis, scaffold design and fabrication using three-dimensional (3D) printing techniques. This review outlines the convergence of these three fields and discusses the potential of their intersection. The author describes the need for this convergence, a brief update of TERM in MSK in the last decade, followed by the potential of AI in MSK-TERM. The review concludes on the challenges and future directions of the emerging field and hopes to encourage bold and ambitious collaborations between industry, academia, hospitals and health-care start-ups to realize the potential of this unique intersection. Full article

This work presents a compact microwave sensor for noninvasive blood glucose monitoring based on a substrate-integrated waveguide loaded with a complementary split-ring resonator on RO4350. The sensing principle uses shifts in resonance frequency and changes in S-parameters to track the dielectric dispersion of glucose-containing tissue. The resonator is constructed using Substrate-Integrated Waveguide (SIW) technology, which mimics the propagation characteristics of a conventional rectangular waveguide. To validate its versatility, the sensor implements three practical sample delivery modes: direct liquid contact with the sensing surface, a glass tube holder mounted over the active region, and a non-invasive fingertip interface. Electromagnetic simulations and benchtop measurements confirm clear glucose-dependent frequency shifts with stable matching and insertion levels. Across the physiological range of 20 to 200 mg·dL⁻¹, the sensor exhibits clear glucose-dependent resonance shifts in all configurations. In direct contact mode, the resonance frequency shifts from 10.83 GHz to 10.45 GHz with sensitivities up to 2.47 MHz per mg·dL⁻¹. The tube configuration shows a shift from 10.49 GHz to 10.38 GHz with sensitivity up to 0.80 MHz per mg·dL⁻¹, while reducing contamination. In the non-invasive fingertip mode, the resonance shifts from 2.56 GHz to 2.52 GHz with sensitivities up to 0.25 MHz per mg·dL⁻¹. These results confirm the sensor’s compactness, reliability, and suitability for portable, low-cost glucose monitoring. The results indicate that the proposed sensor can support practical continuous or spot monitoring and offers a clear path toward portable and low-cost glucose assessment. Full article

Cutaneous melanoma is one of the most aggressive skin cancers, and early diagnosis remains essential to reduce mortality. Reflectance Confocal Microscopy (RCM) provides non-invasive, quasi-histological images of the epidermis, dermoepidermal junction (DEJ), and dermis, enabling real-time assessment of melanocytic lesions. However, interpretation still relies on expert visual evaluation, which is time-consuming and subjective. In this context, Artificial Intelligence (AI) and Computer-Assisted Detection (CAD) systems are emerging as valuable tools to improve diagnostic accuracy and reproducibility. This review summarizes research on AI applications in RCM imaging for melanoma, focusing on three major areas: delineation of skin strata, segmentation of tissues and morphological patterns, and classification of benign versus malignant lesions. Early approaches included Bayesian classifiers, wavelet-based decision trees, and logistic regression, while recent studies have employed support vector machines, random forests, and increasingly deep learning architectures such as convolutional and recurrent neural networks. The results demonstrate encouraging accuracy in DEJ localization, the segmentation of diagnostically relevant patterns, and the discrimination of melanoma from benign nevi. We distinguish the maturity of dermoscopy-based AI (AUC (ROC) > 0.80 on large multicenter cohorts) from the still-exploratory evidence for RCM-based AI. Nonetheless, current studies are often limited by small datasets, heterogeneous protocols, and a lack of multicenter validation. Overall, progress in AI applied to RCM supports the development of CAD systems that could assist clinicians during acquisition and diagnosis, reducing unnecessary biopsies and improving early melanoma detection. Future work should address standardization, dataset expansion, and the integration of advanced AI methods to move closer to clinical implementation. Full article

Zoonotic pathogens could persist in their environment and be introduced into the food-chain. With careful screening and selection, lactic acid bacteria (LAB) could be used as direct-fed microbials (DFMs) to control these pathogens in food animals. Previously isolated LAB (n = 250) were evaluated for inhibition against Shiga-toxigenic Escherichia coli (STEC) and Salmonella enterica, using agar spot test. Tests revealed that LAB were more effective against Salmonella than STEC, with 67% showing excellent (>15 mm) inhibition. LAB (n = 65) exhibiting significant pathogen inhibition (zones > 10 mm) were tested for acid (pH: 2, 4, 5, 7) and bile (0, 0.1, 0.3, 0.5%) tolerance, and biofilm-forming capabilities. About half of the tested LAB exhibited excellent to very good tolerance. All LAB formed biofilms, with 33% forming strong biofilms. LAB (n = 59) were also examined for susceptibility to commonly used antibiotics due to their intrinsic or acquired antibiotic resistance (AR), transferrable to pathogens. Only S. thermophilus S-2 showed susceptibility to all the antibiotics. The majority were susceptible to erythromycin (88%), followed by ampicillin (85%), clindamycin (64%), tetracycline (58%), vancomycin (44%), streptomycin (15%), and gentamicin (9%). Overall, LAB showed strong inhibition against pathogens, along with survival capabilities for environmental stress conditions, and could be considered for potential DFM applications. Full article