Abstract: Biodiversity is an essential natural resource providing raw material for evolution by natural selection. Bottleneck and founder effects lead to the lack of genetic variation and, in turn, a decreased adaptive potential and elevated risk of extinction. One of the mechanisms maintaining genetic diversity and phenotypic variation to avoid loss of heterozygosity is the acquiring of new genetic material via gene duplication. It can result from small-scale events like unequal crossing over, retroposition, or large-scale whole genome duplication (WGD). New transcriptomic patterns in polyploids lead to transcriptomic and phenotypic novelty that can facilitate increased adaptability under environmental changes. Despite the great genetic diversity potentially generated by WGD and further genome reorganization, only a few WGD events are evolutionary ‘successful.’ Macrostomum lignano, a free-living marine flatworm, is one of the astonishingly successful neopolyploid species. We uncovered the hidden polyploidy of its genome masked with intensive karyotype reorganization. The M. lignano genome consists of three subgenomes that emerged due to the formation of a large fused chromosome and its variants and maintained their heterozygosity through chromosomal rearrangements. In this study, we sought to unveil differences in gene expression and phenotypic variation among euploid and aneuploid worms of M. lignano, being hidden tetra- and hexaploids, respectively.

Abstract:

This study investigated single nucleotide polymorphisms (SNPs) within the CAPN1 316, CAPN1 4751, and CAST 2959 markers using high-resolution melting (HRM) analysis to predict meat tenderness in crossbred beef cattle. Tenderness was assessed using the Warner-Bratzler shear force (WBSF) test, with results expressed in grams (g), representing the force required to shear muscle fibers. Significant differences in phenotypic data were observed among the genotypic groups. The finding showed that polymorphisms at CAPN1 316, CAPN1 4751, and CAST 2959 exert interactive effects on meat quality traits. Notably, the TT genotype at CAPN1 4751 increased the adjusted WBSF (aWBSF) by approximately 792 g, indicating that TT was an unfavorable variant for tenderness. These results support the use of marker-assisted selection strategies in which the TT genotype is managed to minimize its frequency while other relevant markers are concurrently monitored, thereby enhancing genetic progress in meat tenderness across commercial cattle populations. This study demonstrated that CAPN1 4751 could serve as an effective marker for genetic selection in crossbred beef cattle and confirmed the efficiency of HRM analysis as a molecular tool for SNPs genotyping. In conclusion, the findings provided an alternative approach for SNPs detection in livestock breeding programs and represented an important step toward improving meat quality, meeting consumer expectations, and supporting the long-term sustainability of Thailand’s beef industry. The results highlighted the polygenic nature of meat tenderness and emphasized the importance of integrating multiple SNPs markers to accurately assess the genetic potential for meat quality traits in cattle.

Abstract: Innovative developments of GC-MS over the last two decades made this methodology a powerful tool for profiling a broad range of volatile metabolites and non-volatile ones of non-polar, semi-polar and even polar nature after appropriate derivatization. Indeed, the high potential of GC-MS in the analysis of low molecular weight metabolites involved in essential cellular functions (energy production, metabolic adjustment, signaling) made it the method of choice for the life and plant scientists. However, despite these advances, due to their intrinsic thermal lability, multiple classes of hydrophilic low-molecule weight metabolites (like nucleotides, sugar phosphates, cofactors, CoA esters) are unsuitable under the high temperature conditions of the SSL injection and GC separation, that makes analysis of such compounds by GC-MS challenging. Therefore, to ensure comprehensive coverage of the plant metabolome, the GC-MS-based metabolomics platform needs to be efficiently combined with other metabolomics techniques and instrumental strategies. Moreover, to get a deeper insight into dynamics of plant cell metabolism in response to endogenic and exogenic clues, integration of the metabolomics data with the output obtained from other post-genomics techniques is desired. Therefore, here we overview different strategies for integration of the GC-MS-based metabolite profiling output with the data, acquired by other metabolomics techniques in terms of the multi-platform metabolomics approach. Further, we comprehensively discuss the implementation of the GC-MS-based metabolomics in multi-omics strategies and the data integration strategies behind this. We are convinced that this approach is the strategy of future, as it gives deep and multi-level insight into physiological processes in plants in the systems biology context with consideration of all levels of gene expression. However, multiple challenges may arise in the way of integrating data from different omics technologies, which are comprehensively discussed in this review.

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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: Owing to changing climatic and environmental conditions, plant diseases are becoming increasingly prevalent, posing a serious threat to global agriculture. Timely and accurate diagnosis remains challenging, especially where scouting still relies on manual inspection. We propose B2-GraftingNet, a deep learning framework for automated detection of grape leaf diseases. B2-GraftingNet is a streamlined variant of our earlier B4-GraftingNet, retaining its strengths while simplifying blocks for faster inference and deployment. The architecture combines a VGG16 backbone with Inception-style blocks inside a custom CNN to extract robust, multi-scale features based on color, size, and shape. To reduce redundancy and improve generalization, Binary Particle Swarm Optimization (BPSO) selects informative features prior to classification. We evaluate Support Vector Machines (SVM) and k-Nearest Neighbors (KNN); a cubic SVM attains 99.56% peak accuracy on the public Kaggle grape-leaf dataset. For context, we also benchmarked standard pretrained CNNs on the same data, observing validation accuracies of 34.04% (VGG16), 34.04% (VGG19), 97.95% (Xception), 94.91% (Darknet), and 98.44% (ResNet-50); B2-GraftingNet matches or exceeds these while remaining lighter and faster to train and deploy. To enhance transparency and actionability, we pair Grad-CAM, LIME, and occlusion-sensitivity visualizations with a local gpt-oss:20b assistant (served via Ollama) that converts evidence into plain, grower-focused guidance and supports interactive chat validated by horticulturists. Results are further checked against expert-annotated ground-truth labels, confirming high accuracy and computational efficiency. Overall, B2-GraftingNet offers a reliable, interpretable, and scalable solution for early grape-leaf disease detection. The complete setup (code, model, web platform, configuration, and assets) is available on Zenodo: https://doi.org/10.5281/zenodo.17353656.

Abstract: Biological systems maintain coherent organization across spatial and temporal scales that cannot be fully explained by classical biochemical or electrophysiological models. Building on the dissipative quantum field theoretical framework introduced by Vitiello and collaborators, this work develops an organism-wide model in which coherence emerges from multiple quantum substrates undergoing spontaneous symmetry breaking (SSB). Each substrate—coherent water domains, microtubular dipole fields, mitochondrial excitons, chromatin vibrational dipoles, ionic phase waves, and large-scale electromagnetic modes—defines a distinct coherent sector represented by macroscopic fields Θ₁–Θ₁₂. These fields are characterized by condensation amplitudes θₖ(t) derived from the vacuum structure.Using operator doubling, Bogoliubov transformations, and projection of the doubled Liouville equation, we obtain macroscopic evolution equations for θₖ(t) and show that their dynamics form a gradient flow on a multi-field free-energy landscape with a global attractor Θ_ref. The Biological Coherence Index (BCI), based on vacuum overlap, provides an experimentally accessible measure of whole-organism coherence.This framework offers a unified quantitative approach to long-range biological coherence, cross-scale coupling, and integrative regulation in living systems.

Abstract:

Background: The search for meaning (Logos) is widely recognized as a primary determinant of resilience. However, current psychological models often fail to account for the metabolic cost of maintaining coherent narratives in high-entropy environments. Objective: This article introduces the Neuro-Existential Architecture System (NEAS), a unified framework synthesizing Viktor Frankl’s Logotherapy with the Free Energy Principle and Spatiotemporal Neuroscience. We aim to demonstrate how the "Spiritual Self-Pattern" functions not as a metaphysical add-on, but as a thermodynamic necessity for optimizing the brain's predictive dynamics. Methods: Integrating the Resonance-Inference Model (RIM) with theories of Affective Criticality (Tucker & Luu) and Population Clocks (Buonomano), we distinguish between two hierarchical modes of regulation: a semantic Master Prior (Logos) that operates via belief updating, and a structural Master Prior (Spirit) that operates via precision control. We operationalize the spiritual dimension using Michael von Brück’s definition: "consciousness becoming aware of itself."(Brück, personal communication). Results: We identify that while Logos provides the vector of resilience (direction), it remains metabolically expensive and falsifiable. The structural integration of Spirit (awareness of awareness) shifts the system into a state of "Affective Criticality," optimizing information processing and minimizing allostatic load. This integration prevents pathological states defined as "Frozen Priors" (fanaticism) or "Decoupled Narratives" (depression). Conclusions: Meaning is a bio-energetic imperative. The NEAS provides a mechanistic grammar for understanding spiritual practices as "technologies of enactment" that train the brain to maintain viability at the edge of chaos.

Abstract: Background/Objectives: Schizophrenia is a highly heritable psychiatric disorder that affects approximately 1% of the global population. Genome-wide association studies (GWAS) have mapped most schizophrenia risk variants to noncoding regions, highlighting the role of regulatory processes and noncoding RNAs in schizophrenia pathology. Despite this, and schizophrenia’s association with 5-hydroxytryptamine (serotonin) system dysfunction, HTR5A-AS1, a long noncoding RNA (lncRNA) antisense to the serotonin receptor (HTR, 5-hydroxytryptamine receptor) gene HTR5A, remains virtually unstudied. This study provides the first systematic characterization of HTR5A-AS1, validating its transcript structure and investigating its genetic associations, expression dynamics, developmental regulation, and potential synaptic and GABAergic functions in schizophrenia. Methods: Transcriptome-wide association study (TWAS) summary statistics were integrated with postmortem RNA sequencing (RNA-seq), BrainSpan developmental transcriptomes, UCSC Genome Browser annotations, and functional prediction tools. These complementary approaches enabled validation of the transcript’s structure, quantification of regional and developmental expression, and assessment of potential molecular functions. Results: HTR5A-AS1 showed significant TWAS associations with schizophrenia in the hippocampus and dorsolateral prefrontal cortex (dlPFC). In postmortem schizophrenia donor tissue, expression was significantly reduced in the hippocampus, with a non-significant but directionally similar decrease in the dlPFC; sex-stratified analyses revealed that hippocampal reductions were strongest in male donors. Parallel analyses showed modest hippocampal downregulation of the paired receptor gene HTR5A, again driven primarily by males. Developmental transcriptomes revealed region-specific developmental trajectories, with steep increases during adolescence, aligning with the age range of typical schizophrenia onset. HTR5A-AS1 was strongly co-expressed with HTR5A, and functional predictions implicated involvement in synaptic and GABAergic signaling, consistent with cortico-hippocampal circuit disruption in schizophrenia. Conclusions: These findings provide the first evidence that HTR5A-AS1 is a bona fide antisense transcript with developmental and synaptic roles that may contribute to schizophrenia risk. Future single-cell and functional perturbation studies are needed to test causality and define mechanisms of regulation.

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.

Abstract: Polygonatum odoratum is rich in polysaccharides, which are key bioactive components with significant pharmacological value. To optimize their extraction and utilization, it is crucial to identify the growth stage during which polysaccharides are most abundant. In this study, we investigated the seasonal dynamics of polysaccharide accumulation and protein expression in Polygonatum odoratum rhizomes via wide-targeted metabolomics and proteomics. The total polysaccharide content peaked in spring (13.3%), with the second highest level occurring in winter. A total of 610 differentially expressed proteins (DEPs) were identified, with the highest number of DEPs upregulated in spring. Weighted gene coexpression network analysis (WGCNA) revealed a module highly correlated with polysaccharide accumulation and enriched in pathways such as “starch and sucrose metabolism.” Key enzymes, including invertase (INV) and hexokinase (E2.7.1.4), were significantly upregulated in spring and positively correlated with polysaccharide biosynthesis. These results provide valuable insights into the optimal harvest time (spring) for Polygonatum odoratum and identify potential molecular targets for breeding high-polysaccharide varieties.

Abstract: The 2022 global mpox outbreak represented a turning point in the Monkeypox virus (MPXV) epidemiology, highlighting the incredible capability of this virus to adapt to different conditions also in a non-endemic context. To investigate the genomic dynamics of MPXV 2022 strains, we performed whole-genome sequencing of 40 clinical samples from 16 Italian patients across multiple anatomical sites and timepoints between May and December 2022. Combining single-nucleotide analysis with detailed investigation of short tandem repeats (STRs), we explored inter- and intra-host viral dynamics. We identified 19 STR loci located near or within genes involved in immune modulation and virion morphogenesis. While most STRs remained stable across patients, a subset displayed locus- or matrix-specific variation. Among these, STR-VII—embedded within the coding sequence of OPG153, an envelope-associated protein implicated in viral attachment—showed a 12-nucleotide in-frame deletion, resulting in the loss of four aspartic acid residues (Δ4D variant). Structural modeling indicated that this deletion slightly alters a disordered acidic loop without affecting the global fold, potentially modulating surface charge and immune recognition. Integrating STR profiling into genomic surveillance may enhance resolution in outbreak reconstruction and reveal subtle adaptive processes underlying poxvirus host interaction and immune escape.

Abstract: Schistosomiasis is a neglected tropical disease caused by parasitic trematodes of the genus Schistosoma, affecting millions of people globally. It poses a substantial public health challenge, particularly in low- and middle-income countries, most of which are in sub-Saharan Africa, where defaecating and urinating in or near freshwater bodies is prevalent. Despite decades of control efforts, including mass drug administration, reinfection by the parasites remains a common occurrence, with a vaccine being viewed as a crucial tool for sustainable control and ultimate elimination of the disease. Recent advancements in vaccine developments, particularly through the Vaccine Against Schistosomiasis in Africa initiative, therefore, offer hope of getting an anti-schistosomiasis vaccine soon. Several vaccine candidates, including Glutathione S-transferase, Sm-TSP-2, Sm14, and Sm-p80, are thus being explored currently, with Sm-p80, S. mansoni calcium-activated neutral protease, calpain, involved in tegmental maintenance, promising safety and immunogenicity results in Phase 1b trials conducted in a couple of African countries that pave the way for Phase 2a trials. These efforts, supported by global regulatory engagement and partnerships, aim to streamline the approval of the anti-schistosomiasis vaccine and ensure equitable access, but are not without challenges. This review, therefore, explores the current state of schistosomiasis vaccine development, highlighting key scientific, regulatory, and logistical gains made toward a viable and impactful vaccine solution against the disease.

Abstract: Background/Objectives: Post-COVID-19 pulmonary fibrosis (PCPF) and idiopathic pul-monary fibrosis (IPF) show clinical parallels, suggesting overlapping pathogenesis. This study investigated the dysregulation of key proteases, matrix metalloproteinases-2 and -9 (MMP-2/9), and associated inflammatory and endothelial markers in both conditions. Methods: We analyzed MMP-2 and MMP-9 gene expression in peripheral blood leuko-cytes and corresponding plasma protein levels in patients 6 and 12 months after SARS-CoV-2 infection, stratified by the presence (FB+) or absence (FB-) of post-COVID pulmonary fibrosis. These groups were compared to IPF patients and pre-pandemic healthy controls. Results: Results showed a significant, sustained increase in MMP-2/9 in post-COVID patients versus controls, which was most pronounced in the PCPF group and mirrored the dysregulation in IPF. This proteolytic shift corresponded to a distinct sys-temic profile: patients without fibrosis showed reduced levels of acute-phase cytokines (TNF-α, IL-6), whereas patients with fibrosis exhibited both elevated cytokines and in-creased markers of endothelial dysfunction (Endothelin-1, sICAM-1). Conclusions: The findings demonstrate that sustained MMP-2/9 overexpression is a hallmark of post-COVID fibrosis and is associated with a transition from systemic inflammation to chronic endothelial impairment. The convergence of this molecular profile in PCPF and IPF indicates shared pathophysiological pathways driving fibrosis. This positions MMP-2 and MMP-9 as promising biomarkers and potential therapeutic targets for mitigating progressive fibrotic lung disease.

Abstract:

Surface and subsurface acidity (pH < 4.4) limits nutrient availability and root exploration, whereas a pH range of 5.4–6.4 ensures the availability of most nutrients that are essential for crop productivity. To ameliorate acidity in the surface and subsurface layers and improve soil chemical fertility, different application methodologies (surface, incorporation by soil tillage, or subsurface) for calcium (Ca) compounds (limestone (LS), phosphogypsum (PG), and hydrated lime (HL)) were evaluated in an agropastoral system in an Arenic Hapludalf in Brazil during the 2017–2020 seasons. Two seasons after the last application of Ca compounds, the soil was sampled and analyzed to evaluate the long-term ability of these different application methodologies. In the 0.0–0.2 m layer, the correction of surface acidity via increased pH and base saturation (BS) and reduced total acidity was maintained, but the improvement in acidity in the 0.4–0.8 m layer previously observed after the incorporation of LS and subsurface application of HL in the 2017-2018 season was not. Moreover, the improvements in Ca²⁺ content and Ca²⁺/cation exchange capacity (CEC) after applying LS plus PG and Mg²⁺ content and Mg²⁺/CEC after applying HL plus PG were preserved in the surface layer. The positive effects of these amendments on sulfate-S (S-SO₄^2-) content throughout the soil profile (0.0–0.8 m) were not. Finally, Ca compound application had residual positive effects on P content in the 0.1–0.8 m layer and organic matter (OM) content in the 0.2–0.8 m layer.

Abstract: The endocannabinoid system is expressed in brain centers involved in a wide variety of functions which makes it an ideal target for disease therapy and prevention. Unlike major excitatory and inhibitory neurotransmitters such as glutamate and GABA, en-dogenously produced cannabinoids have been shown to play a complimentary role as neuromodulators by acting as gain regulators of neural signals. The endocannabinoid system consists of cannabinoid receptors, CB1R and CB2R, and endogenously generat-ed lipid-based neurotransmitters, 2-AG (2-arachidonoylglycerol) and anandamide, the endocannabinoids. In the central nervous system, these signaling molecules are re-leased from postsynaptic cells in an on-demand manner. This retrograde transmission from post- to presynaptic neurons and the binding of endocannabinoids onto the pre-synaptic CB1 receptors modulates the magnitude of release of glutamate and GABA, either enhanced or inhibited, depending on the brain area under study. Research has focused on the role of the endocannabinoid system in the limbic system such as the hippocampus and amygdala. Research is increasing regarding the role that endocan-nabinoids play in other brain centers such as the olfactory system with particular em-phasis on the role of the endocannabinoid system in neural networks of the main ol-factory bulb. This review aims to bring together research within the overlap of the ol-factory system and the endocannabinoid system. By better understanding the unique neuromodulator and neurodevelopmental role of endocannabinoids in the brain, in-sight into understanding how to mitigate disease states that result from aberrant re-lease of glutamate and GABA such as stroke, epilepsy, and schizophrenia is expected to be gained.

Abstract: We propose a generalization of the dissipative quantum field theory (DQFT) as developed by Celeghini, Rasetti, and Vitiello to describe the dynamic informational feedback underlying biological coherence. The new framework, termed the Quantum Blueprint Formalism (QBF), builds on the fact that in DQFT the conjugate field ψ̃ is an active dynamical partner of ψ, representing the time-reversed degrees of freedom that co-generate dissipation, irreversibility, and the selection of inequivalent vacuum states. Rather than functioning as a mere repository of past interactions, ψ̃ participates continuously in the system’s coherent evolution through SU(1,1) Bogoliubov mixing.QBF extends this structure by allowing the ψ–ψ̃ coupling to become explicitly state-dependent, thereby endowing the conjugate field with an informational role that reflects and influences the system’s ongoing coherence pattern. Correlation parameters Θ = {θₖ} quantify the instantaneous coherence relations between the two sectors and evolve in time according to a nonlinear stochastic differential equation derived from the dissipative field dynamics.This extended formalism provides quantitative links between informational coherence and physiological observables such as heart rate variability (HRV), EEG phase synchronization, water-domain ordering, and ultraweak photon emission. It thereby establishes a bridge between dissipative quantum physics, information theory, and experimental biophysics, offering a consistent mathematical and empirical basis for understanding life as an informationally guided, self-organizing process in which ψ and ψ̃ jointly sustain and regenerate coherence.

Abstract: Oncofetal reprogramming has recently emerged as a critical concept in translational cancer research, particu-larly for its role in driving therapeutic resistance across a variety of malignancies. This biological process refers to the pattern of gene expression that is restricted to embryogenesis, but becomes expressed again in a sub-population of cancer cells. These genes are typically suppressed after embryogenesis, and their aberrant re-expression in tumors endows cancer cells with stem-like properties and enhanced adaptability. The GOAL of this review is to: i) Comprehensively examine the multifaceted nature of oncofetal reprogramming, ii) Elucidate its underlying molecular mechanisms, including its regulators and effectors, and iii) Evaluate its consequences on therapeutic response in different cancer types. We comprehensively integrate the latest findings from col-orectal, breast, lung, liver, and other cancers to provide a detailed understanding of how oncofetal programs interfere with tumor response to treatment. Among the candidates, YAP1 and AP-1 have emerged as central transcriptional drivers of this reprogramming process, especially in colorectal and breast cancers. We also ex-plore the distinct expression patterns of oncofetal genes across different tumor types and how these patterns correlate with treatment outcomes and patient survival. Lastly, we propose a dual-targeting therapeutic strategy that simultaneously targets both cancer stem cells and oncofetal-reprogrammed populations as more effectively approach to overcome resistance and limit recurrence.

Abstract: Faithful DNA replication is essential for genome stability but is constantly challenged by metabolic and oxidative stresses. Hydroxyurea (HU), a widely used antiproliferative drug, is traditionally known to inhibit ribonucleotide reductase and deplete dNTP pools. Recent studies, especially in Saccharomyces cerevisiae, reveal that HU-induced replication stress also arises from reactive oxygen species (ROS), which oxidize DNA, impair iron–sulfur–dependent replication enzymes, and disrupt replisome function. These combined effects promote helicase–polymerase uncoupling, accumulation of RPA-coated ssDNA, and activation of the Mec1–Rad53 (ATR–CHK1) checkpoint, leading to strand-specific changes such as PCNA unloading and reduced lagging-strand synthesis. When protective pathways are overwhelmed, HU-treated forks collapse, generating chromosome breaks and genome instability. This review summarizes current understanding of how HU remodels replication forks through both ROS-dependent and ROS-independent pathways and highlights emerging insights into how these mechanisms influence genome stability and may be exploited for therapeutic benefit.

Abstract: INTRODUCTION: While the exact cause of Type 1 Diabetes (T1D) remains unclear, it is widely believed that both genetic and environmental factors contribute to the development of the disease. Recent research has explored the potential role of gut microbiota and its metabolites in modulating immune responses and influencing the development of autoimmune diseases like T1D. With this purpose, we designed a study: 1. to compare the levels of different bacterial metabolites in plasma samples of T1D patients and healthy controls (HC). 2. to correlate the levels of these metabolites with different demographic, clinical and analytical variables collected from the T1D patients. METHODS: A total of 91 T1D patients were recruited. Plasma samples were collected and analyzed with gas chromatography coupled to mass spectrometry for the detection of the metabolites: short-chain fatty acids (SCFA: acetate [AA], propionate [PA], isobutyrate [IBA], butyrate [BA], isovalerate [IVA], valerate [VA] and methyl valerate [MVA]), medium-chain fatty acids (MCFA: hexanoate [HxA] and heptanoate [HpA]) and para-cresol (p-cresol). We also calculated the ratios between the different SCFA with AA. RESULTS: 1. AA levels were significantly higher in T1D patients than in HC (p=0.0009). PA/AA and IBA/AA ratios were significantly higher in HC (p=0.0004 and p=0.0001, respectively). 2. Glycated haemoglobin (HbA1c) was positively correlated with AA levels (p=0.0001; r=0.406) and a significant negative correlation with a rSpearman< -0.3 was found for PA/AA, IBA/AA and BA/AA ratios. 3. p-cresol correlated with Ferritin levels (p=0.04; r=0.362); besides, p-cresol levels were lower in T1D patients with a normal liver profile (p=0.002) and in T1D patients without hypertension (p=0.005). CONCLUSIONS: Serum levels of bacterial metabolites were significantly different in T1D patients. AA levels were significantly increased in T1D patients and p-cresol was higher in T1D patients with liver disturbances and hypertension. To develop strategies to restore gut microbiota health and immune balance could be essential for the control of T1D.

Abstract: The Temperature-Size Rule; a widely accepted bio-ecological principle, posits that ectothermic organisms mature at a smaller body size in warmer steady state conditions. However, pelagic cnidarians such as jellyfish and siphonophores consistently present an exception to this rule. This paradox is observed with such cnidarians exhibiting neutral or even positive size responses to warming conditions in both field and laboratory studies. This not only challenges the universality of the Temperature-Size Rule but also conflicts with established endometric scaling models which prioritize body mass as the primary determinant of metabolic rate. This paper seeks to propose a new model that resolves the "jellyfish paradox" with an updated exometric framework, whereby environmental properties, specifically those integrated by the thermohaline regime, act as primary modulators of physiological changes. This perspective positions thermohaline regime density as a quasi-master dial; a physical variable that concurrently determines the effects of temperature and salinity on the degree of development of the aqueous medium. Furthermore, in rooting the framework in thermohaline regime density we are able to integrate established principles of quantum biology, wherein processes such as proton tunneling and coherent energy transfer in mitochondrial electron transport chains are not only temperature-invariant but are also exometrically sensitive to their immediate aqueous environment. We synthesize these concepts into a novel Quantum-Exometric Scaling (QES) model. This QES model predicts that the optimal body size for pelagic cnidarians is not a simple inverse function of temperature but is determined by the synergistic effects of temperature and salinity on water density, viscosity, and ionic strength, which in turn alter the quantum efficiency of core metabolic processes. We hypothesize that the sign and magnitude of the temperature-size relationship in these organisms are conditional upon thermohaline density, providing a predictive framework that reconciles their anomalous responses within a broader biophysical context.