Abstract: The rapid expansion of high-throughput sequencing technologies and the completion of telomere-to-telomere (T2T) assemblies have transformed genomics into a data-driven discipline, shifting the research focus from data generation to large-scale computational discovery. This literature review synthesizes foundational and emergent pathways in bioinformatics, genomics, and their integration into health applications. We examine the critical role of genomic reproducibility and benchmarking in establishing clinical trust, alongside mathematical models for comparative genomics, such as the Double-Cut-and-Join (DCJ) distance. A significant portion of this review is dedicated to methodological shifts in representation learning, specifically evaluating the impact of Byte-Pair Encoding (BPE) tokenization on genomic language models and the dominance of repetitive elements in sequence vocabularies. Furthermore, we explore the evolution of deep learning architectures, contrasting traditional convolutional and recurrent neural networks with recent advancements in State Space Models (SSMs). These emergent architectures, such as Caduceus and Mamba, demonstrate linear-time complexity and superior performance in capturing long-range regulatory dependencies across ultra-long genomic sequences. Finally, we discuss how these computational innovations converge to support the goals of precision medicine. By mapping these trajectories, this review provides a comprehensive overview of the technical and theoretical challenges inherent in modeling the complexity of the human genome for clinical and biological insights.

Abstract: Food insecurity remains a persistent challenge in South Africa, particularly in rural and township communities constrained by limited resources and environmental degradation. This qualitative study explores the potential of conservation agriculture (CA) as a sustainable farming method to enhance food security among small- to medium-scale farmers within the Nelson Mandela Bay Municipality in the Eastern Cape. Through purposive and snowball sampling, interviews were conducted with CA practitioners to understand their practices, motivations, and perceptions. Thematic analysis revealed diverse adoption patterns, ranging from full implementation to selective integration of CA principles, influenced by contextual, economic, and knowledge-based factors. Participants highlighted CA's role in restoring soil health, reducing dependence on agrochemicals, and fostering long-term resilience against climate variability. However, the high initial costs, delayed yield improvements, and limited institutional support emerged as significant barriers. The study underscores the importance of a multi-stakeholder approach, including government, NGOs, academia, and the private sector, to foster wider adoption of CA. Such collaboration should prioritize tailored support mechanisms, knowledge-sharing platforms, and enabling policies that center on resource-constrained farmers, particularly women and youth. Ultimately, CA presents a viable pathway to achieving both environmental sustainability and household-level food security in vulnerable communities.

Abstract: Genetically encoded biosensors represent a cutting-edge class of biosensors due to real-time monitoring and programmability in living cell. However, the development of eukaryotic genetically encoded biosensors for new analytes is constrained by the shortage of signal–receptor pairs. Bacterial biosensors have been transferred to eukaryote to expand the signal detection space, having achieved remarkable success. However, due to the significant differences between eukaryotic and prokaryotic gene expression systems, optimizing bacterial biosensors has proven challenging. Successful cases indicate that developing orthogonal signal–receptor pairs directly from eukaryotic systems may offer a viable solution. Indeed, the potential of filamentous fungi—a highly diverse group of organisms that share conserved as well as specific signaling and metabolic pathways with yeast or mammalian cells—has been largely overlooked in biosensor development. In this review, we systematically examine sensing systems in filamentous fungi and summarize their signal recognition receptors, signal transduction pathways，responsive transcription factors and describe potential mining strategies for sensing elements from filamentous fungi.

Abstract: Background/Objectives: Cardiovascular disease is the leading cause of morbidity and mortality worldwide, of which the myocardial Infarction is the most prevalent. However, the underlying pathophysiological mechanisms remain incompletely understood, but are tightly regulated by several cellular mechanisms, including long-non-coding. This study aimed to determine if MEG3 and ATF4 are involved in this pathology. Methods: A cross-section study was conducted at the Instituto Nacional de Cardiología Ignacio Chávez, patients with first time diagnosis STEMI and hemodynamic stability were categorized into with and without major adverse cardiovascular events, the most important clinical and biochemical parameters were collected, which were analyzed and subsequently correlated with MEG3 and ATF4. Results: Forty-two patients with a median age of 54 years (86% men) were included and classified with and without MACE. The expression of MEG3 in MACE group and No MACE (0.8974, 0.4186–1.4131 vs. 1.2259, 0.5516–2.3964; p = 0.0342), and ATF4 in MACE group and No MACE (2.8950, 0.7559–4.3287 vs. 2.3498, 1.0821–3.6903; p = 0.0396), ROC curve MEG3 showed an AUC of 0.6490 (0.4760 to 0.8221; p = 0.0924), in contrast ATF4 demonstrated an AUC of 0.7127 (0.5862 to 0.8393; p = 0.0107). Finally, correlation analyses revealed MEG3 was associated with CK-MB (r = 0.3978, 0.0630 to 0.6520; p = 0.0219), and ATF4 was correlated cTnT (r = 0.3328, 0.0284 to 0.5810; p = 0.0335) and with LVEF (r = –0.4283, –0.6503 to –0.1390; p = 0.0052). Conclusions: The dysregulation of MEG3 and transcription factor ATF4 are involved in pathophysiological mechanisms.

Abstract: This study investigated whether ambient biogenic volatile organic compounds (bVOCs) scent profiles emitted by botanic glasshouse vegetation influence quantifiable human health and wellbeing outcomes, extending evidence previously obtained in clinical settings. Over 11 months in 2024 (January–December), human participant trials were conducted at the Oxford Botanic Garden to compare the physiological and psychological impacts of 30-minute exposures in five different vegetation-rich glasshouses, each characterised by a distinct and complex bVOCs profile, with those of a plant-free control room containing minimal bVOCs. Pre- and post-intervention assessments were conducted on 43 participants using the State-Trait Anxiety Inventory (STAI), heart-beat rate (beats per minute), and heart rate variability (HRV), a widely used index of autonomic regulation. Glasshouse exposure produced significant reductions in STAI anxiety scores and decreases in heart-beat rate, while HRV indices remained stable relative to the control condition. Distinct scent profiles in the glasshouses included volatiles previously associated with therapeutic effects in clinical settings, suggesting that such vegetated environments may deliver meaningful physiological and psychological benefits. Overall, these findings highlight the potential public health value of aromatic plant species and the importance of incorporating them into urban green space planning and policy.

Abstract: Motivation: Molecular maps are graphical representations of the molecular mechanisms underlying biological systems. They are a valuable tool for curating, exchanging, and understanding biological knowledge, and may serve as a backbone for data analysis and modelling. Molecular maps are supported by a rich software ecosystem. However, there are currently no tools that support advanced programmatic analysis and processing of maps, in particular the extraction of the biological concepts they represent or their comparison. Results: We introduce momapy, a generic Python library to work with molecular maps efficiently. At its core, momapy allows users to extract and separate the data model of a map from its graphical representation, and perform a variety of base operations on them, including their manipulation and comparison. momapy currently supports the SBGN and CellDesigner formats, two of the main standards to represent molecular maps graphically, and can be easily extended to support additional formats and functionalities.

Abstract: Background: Epigenetic regulation must preserve stable functional states under molecular stochasticity and changing environments, yet an operational model linking context-level signals to measurable chromatin remodeling is limited. Method: This study proposes Epigenetic Teleonomy, a stochastic control framework in which epigenomic observables relax toward an empirically estimated within-subject baseline regime (reference distribution) with lagged mediator-driven inputs and feedback. Results: A local approximation yields mean-reverting dynamics. Simulations illustrate that without effective feedback, diffusion-like drift leads to increasing dispersion, whereas sufficient regulation gain yields bounded fluctuations and recovery. In the isotropic local Ornstein–Uhlenbeck (OU) regime, stationary fluctuations scale with effective diffusion and inversely with return rate (gain). Conclusion: The framework is testable in longitudinal designs by (i) estimating a subject-specific baseline from a stable run-in window, (ii) quantifying deviation using reduced-dimensional proxies, and (iii) fitting gain and diffusion from return-to-baseline statistics.

Abstract: Background: TNXB-related classical-like Ehlers-Danlos syndrome (clEDS) is caused by biallelic pathogenic variants in TNXB, encoding the extracellular matrix glycoprotein tenascin-X. Although traditionally classified as a connective tissue disorder based on joint hypermobility and skin findings, accumulating clinical, electrophysiological, and imaging data indicate prominent neuromuscular involvement that likely reflects a central disease mechanism. Methods: A qualitative evidence synthesis was conducted following PRISMA 2020 guidelines. A comprehensive search of PubMed, OMIM, and GeneReviews was performed on January 5, 2026. Data from 18 studies representing 56 individuals with biallelic TNXB variants were synthesized narratively, with findings stratified by assessment method and zygosity. Due to heterogeneity in study designs, assessment methods, and outcome definitions, quantitative meta-analysis was not feasible. Results: Among 56 individuals with biallelic TNXB variants, subjective muscle weakness was reported in only 37% of cases. However, systematic neuromuscular assessment demonstrated objective muscle weakness in 85% of patients examined. Electromyography revealed mixed neurogenic-myopathic patterns in 60%, and muscle imaging abnormalities were present in approximately 50%. A clear dose-effect relationship was observed, with heterozygous individuals exhibiting milder phenotypes correlating with reduced serum tenascin-X levels. Conclusion: Neuromuscular involvement in TNXB-related disorders is frequent, progressive, and mechanistically linked to dysfunction at the muscle-extracellular matrix interface. These findings support the reclassification of TNXB-related disease alongside myopathic Ehlers-Danlos syndrome as a muscle-ECM interface disorder.

Abstract:

The increasing population of mesopredators in Central Europe necessitates precise monitoring for effective game management. This study aimed to estimate the minimum population and reproduction of the European badger (Meles meles), red fox (Vulpes vulpes), and golden jackal (Canis aureus) in two hunting grounds in southwestern Hungary (Drávaszentes and Darány). Methods included a total burrow count conducted in early 2025, followed by the deployment of wildlife cameras at inhabited setts to record adults and cubs. Results indicated an inhabited burrow density of 1.05/100 ha for badgers and 0.38/100 ha for foxes in Drávaszentes, with average litter sizes of 1.13 and 2.33 cubs, respectively. In Darány, badger density was 1.43/100 ha, while jackals were present at 0.2/100 ha. Additionally, habitat composition preference was analyzed using QGIS by comparing Corine Land Cover categories within 400 m buffers around burrows against random points. Habitat analysis suggested local preferences for non-irrigated arable land and mixed forests. These findings provide essential baseline data on predator population dynamics to support conscious management decisions.

Abstract:

Background and Objectives: This study aimed to investigate the effects of explaining the perioperative process to pediatric patients scheduled for adenotonsillectomy using pictures on their anxiety levels. Materials and Methods: A prospective, randomized controlled trial was conducted, enrolling 58 patients. The patients were divided into two groups: Group 1 (n=29), where the perioperative process was explained using pictures, and Group 2 (n=29), the control group, where no pictures were used. Child anxiety was assessed using the modified Yale Preoperative Anxiety Scale Short Form (mYPAS-SF) at five observation time points before anesthesia induction. Parents’ anxiety was measured using the Visual Analog Scale for Anxiety. Results: Patients in Group 1 had significantly lower heart rates during induction and the intraoperative period compared to Group 2 (p = 0.031, p = 0.025, respectively). In terms of anxiety and RSAS scores, patients in Group 1 had significantly lower mYPAS-SF scores at time points t2, t3, t4, and t5 compared to Group 2 (t2: p = 0.001; t3-t5: p < 0.001). No significant difference was observed at t1 (p = 0.068). The mean RSAS scores were also significantly lower in Group 1 (p = 0.029). Parents’ anxiety was significantly lower in Group 1 at all three time points (t1: p = 0.017; t2: p = 0.006; t3: p = 0.036). Conclusion: Our study results demonstrate that illustrating the perioperative process in children undergoing adenotonsillectomy can significantly reduce preoperative anxiety and prevent awakening agitation. Given its ease of implementation, we believe that using visual aids to explain the perioperative process to pediatric patients can facilitate process management for patients, parents, and physicians.

Abstract: Autonomic regulation has traditionally been described using branch-based models that emphasize linear relationships between sympathetic and parasympathetic activity. While these approaches have contributed substantially to physiological research, they often struggle to account for the nonlinear, multiscale, and state-dependent organization observed in complex biological systems.This manuscript presents the Expanded Polyvagal Theory (TPE) as an interpretative and non-diagnostic theoretical model designed to integrate concepts from autonomic physiology, heart rate variability, complexity science, and entropy-oriented analysis. Rather than introducing new physiological mechanisms or reporting experimental findings, the framework reorganizes existing knowledge through a state-based perspective, emphasizing emergent patterns, metastability, and subsystem coupling across multiple temporal and organizational scales.Within this framework, General States are conceptualized as emergent configurations arising from coordinated interactions among autonomic subsystems, while Autonomic Subtypes are described as recurrent structural–functional motifs within these states. The enteric nervous system is explicitly incorporated as a structural component of autonomic organization, addressing a longstanding gap in conventional autonomic models. An interpretative protocol, OSIRIS, is introduced as a conceptual scaffold for the structured interpretation of multiscale heart rate variability patterns, without proposing diagnostic thresholds, predictive claims, or clinical decision-support functions.This manuscript is presented as a conceptual and hypothesis-generating preprint, intended to stimulate interdisciplinary discussion and theoretical refinement rather than to serve as a clinical or experimental report. By situating autonomic regulation within a complex systems and entropy-oriented framework, the Expanded Polyvagal Theory provides a coherent interpretative lens that may inform future empirical research, model development, and integrative approaches to autonomic physiology.

Abstract: Background/Objectives: This study assessed the clinical effects of preoperative neoadjuvant bevacizumab (neoBev) on newly diagnosed glioblastoma (GB) and investigated imaging-based predictors of outcome. Methods: We retrospectively reviewed 33 patients who received neoBev (10 mg/kg) between 2015 and 2024. Surgery was performed 21–30 days after treatment. Controls comprised 33 patients treated with standard chemoradiotherapy (radiation plus temozolomide) selected through propensity score matching. We assessed changes in performance status, extent of resection (EOR), and volumetric alterations on gadolinium-enhanced T1-weighted imaging (T1Gd) and fluid-attenuated inversion recovery (FLAIR). Median progression-free survival (mPFS) and median overall survival (mOS) were compared. Imaging responders were defined using receiver operating characteristic-derived thresholds. Results: All patients had GB (31 with isocitrate dehydrogenase (IDH)1 wild-type, 2 with IDH-mutant). Median Karnofsky Performance Status improved significantly after treatment in the NeoBev group (from 71 to 83), but remained unchanged in Controls. After matching, mPFS and mOS were 10.2 and 17.9 months with neoBev, and 13.3 and 18.2 months in Controls, respectively. Within the neoBev cohort, T1Gd responders (&gt;37% reduction) achieved longer mPFS and mOS than non-responders. EOR-stratified analysis showed that outcomes favored standard therapy in cases with gross total resection, while subtotal resection cases demonstrated comparable or slightly better OS with neoBev. Conclusions: Preoperative neoBev improved functional status and identified an imaging-defined subgroup with favorable prognosis, although survival was not superior to that with standard therapy. NeoBev may benefit selected patients with limited resectability of newly diagnosed GB.

Abstract:

The main objective of this work is assessing the potential negative impact of organic farming on the thyroid gland and comparing it with the negative impact of conventional farming on this organ. Conventional farming practices deploy synthetic agrochemicals to maximize yields, many of which have endocrine-disrupting properties, like pesticides, while organic farming practices use natural alternative substances, favoring environmental sustainability and health protection. Studies suggest that organic farming yield can be contaminated with pesticide residues. Thyroid disruption underlies some of the most common endocrine pathologies worldwide. Previous studies have linked exposure to conventional farming with thyroid disruption; relatively less is known about effects of exposure to organic farming on the thyroid. Wild mice were selected as bioindicators, captured in a conventional farm (CF); an organic farm (OF), and two reference areas (RF’) without agriculture. Histomorphometric and histomorphological measurements of the thyroid were performed. Hypothyroidism signs were observed in mice exposed to either farming system, being less pronounced in organic farming-exposed mice: epithelium thickness, and the area and volume of epithelial cells were lower than in non-exposed mice [epithelium thickness (µm): 4.1617 ± 0.50860 (CF); 6.2825 ± 0.19308 (OF); 7.4605 ± 0.25412 (RF’)]. Histomorphologic alterations included lower follicular sphericity, irregularly-delimited epithelium, increased exfoliation into the colloid, and increased inflammation of thyroid tissue. Results suggest that, while organic farming might be a better alternative to conventional farming, it is not completely free of health hazards. Exposure to organic farming can cause thyroid disruption, with less pronounced effects. Although there are risks to be considered, results support the benefit of transitioning from conventional farming systems towards organic farming systems.

Abstract: Ultra-processed food (UPF) consumption has generated a great deal of concern among nutrition scientists and consumers due to its potential relationship with increased risk of adverse health impacts. Evidence from intervention studies comparing UPF-rich and less-processed diets on cardiometabolic health outcomes is limited. Clinical trials that have been published to date focus on comparing more- and less-processed diets, as defined by the Nova system, and their impact on weight-related outcomes. Only one trial compares equally healthful more- and less-processed diets. The Dietary Guidelines for Americans with Ultra-Processed foods (DGA-UP) study will be the first trial to examine whether there is a differential effect to following recommendations from the 2020-2025 Dietary Guidelines for Americans (2020 DGA) including more- or less-processed foods as defined by the Nova classification system on cardiometabolic disease risk factors. A randomized controlled crossover dietary intervention study, DGA-UP will be conducted with 4 week provision of all meals to generally healthy male and female adults at eucaloric levels. The trial will consist of 2 dietary arms: 1) a less-processed 2020 DGA diet and 2) a ultra-processed 2020 DGA diet. The primary outcome is change in blood pressure on each diet from baseline to week 4. Both interventions will have excellent diet quality and contain similar amounts of macronutrients and micronutrients as well as the same types of food. DGA-UP will help to fill a significant research gap regarding potential impact of UPFs on cardiometabolic health markers independent of food type, diet quality, and micronutrient content. ClinicalTrials.gov registration: NCT07252037.

Abstract: Rising numbers of wolf populations make traditional, resource-intensive methods of wolf monitoring increasingly challenging and often insufficient. This study explores how wolf howls can be used as a new monitoring tool fro wolves by applying AI methods to detect and classify wolf howls from acoustic recordings, thereby improving the effectiveness of wolf population monitoring. Three AI approaches are evaluated: BirdNET, Yellowstone's Cry-Wolf project system, and BioLingual. Data were collected using SM4 audio recorders in a known wolf territory in Klelund Dyrehave, Denmark, and manually validated to establish a ground truth of 260 wolf howls. Results demonstrate that while AI solutions currently do not achieve the complete precision or overall accuracy of expert manual analysis, they offer tremendous efficiency gains, significantly reducing processing time. BirdNET achieved the highest recall at 78.5% (204/260 howls detected), though with a low precision of 0.007 (resulting in 28,773 false positives). BioLingual detected 61.5% of howls (160/260) with 0.005 precision (30,163 false positives), and Cry-Wolf detected 59.6% of howls (155/260) with 0.005 precision (30,099 false positives). Crucially, a combined ap-proach utilizing all three models achieved a 96.2% recall (250/260 howls detected). This suggests that while AI solutions primarily function as powerful human-aided data re-duction tools rather than fully autonomous detectors, they represent a valuable, scalable, and non-invasive complement to traditional methods in wolf research and conservation, making large-scale monitoring more feasible.

Abstract: Dosage accuracy is a critical requirement for medical devices based on cannabidiol microemulsions. Some users of NegEnt Micellar Drops, CE Medical Device, reported a shorter-than-expected duration of the bottle equipped with a pipette dropper, suggesting possible variability in drop formation. This study compares the precision and homogeneity of drops delivered by a pipette dropper versus a pharmaceutical-grade gravity dropper. Twenty subjects participated in a controlled drop-weight test, followed by a 30-day longitudinal assessment. Results show significantly lower variability with the gravity dropper (SD ±2 mg) compared to the pipette dropper (SD ±5 mg), with statistical significance (p < 0.05). The second phase confirms the stability of the gravity system over time. We conclude that the gravity dropper ensures more accurate and reproducible dosing, improving the clinical reliability of the medical device.

Abstract: Background/Objectives: The genus Tristerix comprises at least ten species, found from southern Chile to Colombia in South America. In Chile, several species of these hemiparasitic plants are commonly known as quitral or quintral. Traditionally, quitral, mainly T. corymbosus (syn. T. tetrandus), has been used in alternative medicine for its anti-inflammatory, digestive, hemostatic, hypocholesterolemic, wound-healing, and astringent properties. Due to its wide distribution in central and southern Chile and its frequent collection for ethnopharmacological purposes, this study aimed to investigate the phytochemical composition and antimicrobial properties of T. corymbosus. Methods: A hydroalcoholic extract of T. corymbosus was prepared from powdered leaves and small branches. Subsequently, the addition of methanol produced a precipitation to isolate three different fractions: a methanol-soluble fraction that was rotovaped, a brown powder obtained after filtration, and a tar-like residue that remained at the bottom of the flask. These fractions were resuspended in 70% ethanol or water and tested for antimicrobial activity. Results: All fractions showed activity against Streptococcus pyogenes, but not E. coli, with the brown powder exhibiting the strongest potency against S. pyogenes and other Gram-positive bacteria. Qualitative phytochemical characterization, followed by HPLC-MS analysis, revealed the presence of key compounds, including lipidic compounds with surfactant properties. Conclusions: the abundant lipidic molecules present in the analyzed fraction likely account for the antimicrobial effects through affecting membrane structure of Gram-positive bacteria, some Gram-negative and yeast Candida albicans supporting the traditional wound-healing uses of T. corymbosus in ancestral and alternative medicine.

Abstract: The human body consists of multiple joints with many degrees of freedom that open the context for biomechanical interventions in the form of recommendations and feedback, with the purpose of improving performance, reducing the risk of injuries, and so forth. These interventions sometimes involve loading trade-offs between joints or loading redistribution. Removing the load from one joint or segment (“native” joint) and transferring it to another joint (“step” joint) seem to need more consideration. Therefore, the aim of the current paper is to highlight the necessity of scientific communication from data collection to conclusions in the form of recommendations, presentations, and publications. The tendency to focus on specific joints and develop expertise hides the trade-off between joint loads, and sometimes, recommendations or feedback on the basis of biomechanical loading simply shift the risk of injury. To address this concern, several approaches are suggested, including improved marker sets, dataset availability, departmental diversity, research team collaboration, and the sharing of conferences and sessions.

Abstract:

Spectral clustering is a powerful methodology rooted in graph theory, linear algebra, and probability theory, and is highly effective for unsupervised learning in complex, non-linear data. This article serves as a comprehensive tutorial and guide for interdisciplinary researchers, building a clear connection between the rigorous mathematical framework of spectral clustering, beginning with the continuous Laplacian operator, progressing to its discrete, graph-based counterpart, and finally culminating in a real-world application. We detail the theory through practical examples and apply the framework to bulk RNA-seq data analysis in breast cancer cell lines, demonstrating the method's unique ability to uncover both broad trends and nuanced molecular subtypes. By providing intuitive knowledge on both the theory and the application, this work aims to facilitate collaboration across mathematics, computational science, and life sciences to support robust and sound scientific research.

Abstract:

The increasing resistance to antibiotics resulting from their indiscriminate use in humans and animals is a serious public health concern recognized by the WHO and WOAH. In this context, phytotherapy based on medicinal plants represents a promising alternative, particularly due to the presence of bioactive compounds such as flavonoids and alkaloids with antimicrobial potential. The Fabaceae family stands out for its remarkable diversity and pharmacological relevance. This review integrates available information on the 347 species recorded in the state of Tamaulipas, Mexico. Only 64 species have been subjected to phytochemical studies, and 46 are traditionally used in medicine, mainly to treat digestive disorders (32%), dermatological conditions (18%), and parasitic infections (15%). The most frequently reported metabolites are tannins and flavonoids, which support their empirical use and therapeutic potential. The main extraction techniques identified were maceration (47.7%) and Soxhlet (10.8%), employing solvents such as methanol (21.5%), water, ethanol, ethyl acetate, and hexane. Herbaceous and arboreal plants were the most investigated. Phenols and flavonoids exhibited antioxidant properties with antibacterial and antifungal activity, whereas alkaloids showed antibacterial, antifungal, anticancer, and anti-inflammatory effects. The greatest metabolic diversity was found in leaves. Microbiological studies highlight notable activity against Staphylococcus aureus, Escherichia coli, and Candida albicans, mainly evaluated through the disk diffusion method.