Search Results (4,288)

Live weight is widely used as a reference indicator for growth performance and for evaluating the accuracy of weight measurement technologies in pig production. However, live weight is not a fixed physiological quantity, and finishing pigs naturally experience substantial short-term mass fluctuations due to normal behaviors such as drinking, feeding, urination, and defecation. In this study, we integrated published physiological and behavioral parameters into a stochastic simulation model to quantify within-day live-weight dynamics in finishing pigs weighing approximately 100 kg. The simulation was conducted with 1-min temporal resolution over a 24-h period. The model demonstrated that short-term weight fluctuations of approximately ±3–5 kg can occur within a single day, even when measurement error is minimal. Across 1000 simulated pigs, the mean daily fluctuation range was 4.2 kg, confirming that kilogram-scale variation is physiologically expected under normal conditions. These results provide a plausible physiological basis for understanding the frequently reported discrepancies between camera-based weight estimates and instantaneous floor-scale measurements. Camera systems primarily reflect body mass derived from external morphology, whereas floor scales measure instantaneous total mass that includes transient contributions from gastrointestinal contents, ingested water, and retained waste. Consequently, direct comparisons based on instantaneous scale readings can be misleading when used as ground truth. Our findings indicate that commonly cited accuracy claims of ±2–3 kg for camera weighing systems should be interpreted with caution, as normal physiological weight variation often exceeds this range. Recognizing live weight as a dynamic physiological variable is essential for developing biologically meaningful evaluation frameworks and for the appropriate interpretation and comparison of weight measurement technologies in precision livestock farming. Full article

Despite advances in high-resolution topographic survey technologies, abstracting static 3D data into physically meaningful indicators remains critical for river management. This study introduces a geometric moment technique to reflect river curvature and hydraulic characteristics within an integrated framework. Analysis was conducted on a reach of the Nakdong River using first-, second-, and third-order moments, W/D ratios, asymmetry indicators, and D50 data. Key findings are: First, the moment-based approach precisely quantified asymmetric variations and localized bed changes by utilizing centroid deviation (M1), dispersion (M2), and mass bias (M3), addressing the limitations of traditional average-based indices. This effectively transforms vast 3D datasets into “compressed records” for tracing hydraulic drivers. Second, sinuosity (S) analysis revealed that reaches with higher curvature (S ≥ 1.5) exhibited intensified variability in third-order moments and asymmetry due to imbalanced hydraulic forcing. Specifically, the horizontal misalignment between the velocity core and the thalweg was identified as a key mechanism driving geometric imbalance in curves. Third, a W/D-asymmetry quadrant analysis categorized reach-scale morphological types and identified hydraulically vulnerable zones. By integrating sectional geometry, velocity distribution, and sinuosity into a unified system, this study provides a quantitative framework for scientific river management and decision-making. Full article

Background/Objectives: Propolis is a complex bee product with a composition that varies according to local vegetation, environmental conditions, and bee foraging behaviours. Recently, gas chromatography–mass spectrometry (GC–MS) has been employed in Uganda to analyse its volatile components. This study examined Ugandan propolis non-volatile metabolites to determine chemotypes and identify antibacterial compounds. Methods: Ethanolic extracts were analysed using liquid chromatography–high-resolution quadrupole time-of-flight mass spectrometry (LC-HR-QTOF-MS) in an untargeted MS/MS mode. Data processing was carried out using MZmine, then annotated with Global Natural Products Social Molecular Networking (GNPS) and SIRIUS. Chemometric methods assisted in identifying regional chemical signatures. Metabolites highlighted by the heatmap were evaluated for antibacterial activity using molecular docking against bacterial targets, followed by ADMET (absorption, distribution, metabolism, excretion, and toxicity) assessments. Results: Out of 3252 features, 234 and 52 putative compounds were annotated in GNPS and SIRIUS, respectively, as indicated by molecular networking, suggesting high chemical complexity. The chemical space mainly comprises flavonoids (including glycosides, aglycones, methylated, and prenylated derivatives), phenolic acids, amides, hydroxycinnamate derivatives, lignans, megastigmanes, and various diterpenoid skeletons. Multivariate analyses clearly distinguish geographical chemotypes, separating flavonoid-rich regions from diterpenoid-rich regions. Docking studies revealed flavonoids, diterpenoids, and lignans with strong predicted antibacterial activities and favourable ADMET profiles. Conclusions: This study provides the first LC–MS characterisation of the non-volatile metabolome of Ugandan propolis, thereby expanding its chemical diversity. Metabolomics and computational approaches lay a foundation for future ecological, chemotaxonomic, and pharmacological research. Full article

This dataset presents a real-world lipidomics resource for developing and benchmarking quality control methods, batch effect detection algorithms, and data validation workflows. The data originates from a cross-sectional clinical study of psoriatic arthritis (PsA) patients (n = 81) and healthy controls (n = 26), matched for age, sex, and body mass index, which was collected at a tertiary university rheumatology center. Subtle laboratory irregularities were detected only through advanced unsupervised analysis, after passing conventional quality control and standard analytical methods. Blood samples were processed using standardized protocols and analyzed using high-resolution and tandem mass spectrometry platforms. Both targeted and untargeted lipid assays captured lipids of several classes (including carnitines, ceramides, glycerophospholipids, sphingolipids, glycerolipids, fatty acids, sterols and esters, endocannabinoids). The dataset is organized into four comma-separated value (CSV) files: (1) Box–Cox-transformed and imputed lipidomics values; (2) outlier-cleaned and imputed values on the original scale; (3) metadata including clinical classifications, biological sex, and batch information for all assay types and control sample processing dates; and (4) a variable-level description file (readme.csv). The 292 lipid variables are named according to LIPID MAPS classification and standardized nomenclature. Complete batch documentation and FAIR-compliant data structure make this dataset valuable for testing the robustness of analytical pipelines and quality control in lipidomics and related omics fields. This unique dataset does not compete with larger lipidomics quality control datasets for comparisons of results but provides a unique, real-life lipidomics dataset displaying traces of the laboratory sample processing schedule, which can be used to challenge quality control frameworks. Full article

Accurate identification of road roughness is pivotal for optimizing vehicle suspension control and enhancing passenger comfort. However, existing data-driven methods often struggle to balance classification accuracy with the strict computational constraints of real-time onboard monitoring. To address this challenge, this paper proposes a lightweight and robust road roughness classification framework utilizing a single sprung mass accelerometer. First, to overcome the scarcity of labeled real-world data and the limitations of linear models, a high-fidelity co-simulation platform combining CarSim and Simulink is established. This platform generates physically consistent vibration datasets covering ISO A–F roughness levels, effectively capturing nonlinear suspension dynamics. Second, we introduce DB-MLP, a novel Dual-Branch Multi-Layer Perceptron architecture. In contrast to computationally intensive Transformer or RNN-based models, DB-MLP employs a dual-branch strategy with multi-resolution temporal projection to efficiently capture multi-scale dependencies, and integrates dual-domain (time and position-wise) feature transformation blocks for robust feature extraction. Experimental results demonstrate that DB-MLP achieves a superior accuracy of 98.5% with only 0.58 million parameters. Compared to leading baselines such as TimeMixer and InceptionTime, our model reduces inference latency by approximately 20 times (0.007 ms/sample) while maintaining competitive performance on the specific road classification task. This study provides a cost-effective, high-precision solution suitable for real-time deployment on embedded vehicle systems. Full article

The microscopic origin of the de Sitter entropy remains a central puzzle in quantum gravity that is related to the cosmological constant problem. Within the paradigm of $\mathcal{H}$olographic $\mathcal{N}$aturalness, we propose that this entropy is carried by a vast number of light, coherent degrees of freedom—called “hairons”—which emerge as the moduli of gravitational instantons on orbifolds. Starting from the Euclidean de Sitter instanton ($S^4$), we construct a new class of orbifold gravitational instantons, $S^4/{\mathbb{Z}}_N$, where N corresponds to the de Sitter entropy. We demonstrate that the dimension of the moduli space of these instantons scales linearly with N, and we identify these moduli with the hairon fields. A ${\mathbb{Z}}_N$ symmetry, derived from Wilson loops in the instanton background, ensures the distinguishability of these modes, leading to the correct entropy count. The hairons acquire a mass of the order of the Hubble scale and exhibit negligible mutual interactions, suggesting that the de Sitter vacuum is a coherent state, or Bose–Einstein condensate, of these fundamental excitations. Then, we present a novel framework which unifies neutrino mass generation with the cosmological constant through gravitational topology and holography. The small neutrino mass scale emerges naturally from first principles, without requiring new physics beyond the Standard Model and Gravity. The gravitational Chern–Simons structure and its anomaly with neutrinos force a topological Higgs mechanism, leading to neutrino condensation via $S^4/{\mathbb{Z}}_N$ gravitational instantons. The number of topological degrees of freedom $N\sim M_{\mathrm{P}}^2/\mathrm{\Lambda }\sim {10}^{120}$ provides both the holographic counting of the de Sitter entropy and a $1/N$information see-saw mechanism for neutrino masses. Our framework makes the following predictions: (i) a neutrino superfluid condensation forming Cooper pairs below meV energies, as a viable candidate for cold dark matter; (ii) a possible resolution of the strong CP problem through a QCD composite axion state; (iii) time-varying neutrino masses which track the evolution of dark energy; and (iv) several distinctive signatures in astroparticle physics, ultra-high-energy cosmic rays and high magnetic field experiments. Full article

The scorpion family Buthidae, renowned for its neurotoxin-rich venoms, dominates toxinology, while non-buthid venoms remain largely unexplored. Here, we present a comprehensive proteomic and biochemical characterization of the Amazonian chactid scorpion Brotheas amazonicus venom (BamazV), with emphasis on molecular complexity, proteolytic processing, and peptide diversity. Using an integrative venomics approach that combines molecular mass-based fractionation, reversed-phase chromatography, high-resolution mass spectrometry, N-terminal sequencing, and functional and immunological analyses, we reveal an unexpectedly complex venom profile enriched in high-molecular-weight components and extensively processed peptides, with more than 40 venom peptides sequenced by MS/MS and Edman degradation. The data provide evidence for non-canonical proteolytic events, including the generation of peptides from precursor regions not classically associated with mature venom components. In contrast to the venom of Tityus serrulatus, BamazV displays a “hydrolase-rich, neurotoxin-poor” profile, featuring a catalytically active Group III phospholipase A₂ (BamazPLA₂), a highly active hyaluronidase, metalloproteases, low-mass peptides, and potassium channel toxins. Our results suggest a hydrolytic prey-subjugation strategy, and limited cross-reactivity with commercial antivenom highlighted its distinct structural landscape. Overall, this study advances the understanding of venom evolution and proteolytic diversification in underexplored scorpion lineages, positioning B. amazonicus as a valuable model for investigating alternative venom strategies and identifying novel biotechnological scaffolds. Full article

Terpyridines are well-known ligands in coordination chemistry, are valued for their conformational flexibility and strong metal-binding properties, and are also of interest as fluorophores. This study focused on the synthesis and comprehensive investigation of a new class of bis-oxazolo[5,4-b]pyridine derivatives, designed based on their structural similarity to terpyridines. Four novel compounds, 4a–d, were synthesized by cyclization of amide derivatives of 3-aminopyridin-2(1H)-ones using pyridine-2,6-dicarboxylic acid and its dichloride as key acidic components. Their structures and purity were confirmed by melting point analysis, high-resolution mass spectrometry, and ¹H, ¹³C NMR spectroscopy. Compounds 4a–c exhibit UV absorption at 323–357 nm and intense blue to deep-blue fluorescence (357–474 nm, цi ≈ 0.32–0.84) in chloroform, dichloromethane, and acetonitrile, attributed to p–p* transitions within the conjugated ring system. These findings suggest their potential as phosphors for organic electronics. Computational modeling of 4a–c molecules provided insight into their electronic structures, conformational stability, and predicted optical behavior. The most stable conformers (4a–II, 4b–II, 4c–II′) exhibited a progressive decrease in the HOMO–LUMO gap from 4a to 4c, correlated with the enhancement of photoactivity. Among them, compound 4a stands out as the most promising luminophore, displaying the most intense and narrow luminescence band, owing to its high molecular symmetry and stable emission characteristics. Overall, this study lays the foundation for future studies of bis(oxazolo[5,4-b]pyridine) derivatives in coordination chemistry and optoelectronic materials development. Full article

The main characteristics of the large number of coffee species are differences in aroma and caffeine content. Labeled blends of Coffea arabica (C. arabica) and Coffea canephora (C. canephora) are common to broaden the flavor profile or enhance the stimulating effect of the beverage. New emerging species such as Coffea liberica (C. liberica) further increase the variability in blends. However, significant price differences between coffee species increase the risk of unlabeled blends and thus influence food quality and safety for consumers. In this study, a prototypic hyphenation of trapped headspace-gas chromatography-ion mobility spectrometry-quadrupole mass spectrometry (THS-GC-IMS-QMS) was used for the detection of characteristic compounds of C. arabica, C. canephora, and C. liberica in green and roasted coffee samples. For the discrimination of coffee species with IMS data, multivariate resolution with multivariate curve resolution–alternating least squares (MCR-ALS) prior to partial least squares–discriminant analysis (PLS-DA) was evaluated. With this approach, the classification accuracy, as well as sensitivity and specificity, of the PLS-DA model was significantly improved from an overall accuracy of 87% without prior feature selection to 92%. As MCR-ALS preserves the physical and chemical properties of the original data, characteristic features were determined for subsequent substance identification. The simultaneously generated QMS data allowed for partial annotation of the characteristic volatile organic compounds (VOC) of roasted coffee. Full article

Detection of hazardous substances in feed is important for ensuring human health. A method based on liquid chromatography-high-resolution mass spectrometry (LC-HRMS) was developed and validated for the screening and confirmation of 420 hazardous substances, including pesticides, veterinary drugs, and mycotoxins commonly found in feed. The screening phase employed less stringent criteria to minimize false negatives caused by matrix effects. Subsequently, stricter identification criteria were applied for confirmation to avoid false positives from interfering compounds. The performance of the proposed method was verified by limit of detection (LOD, 5~500 μg/L), screening detection limits (SDL, 50~500 μg/L), matrix effect (ME, 36.12~121.16%), precision (0.02~14.98%), stability, and accuracy. The method was successfully applied to real feed samples, demonstrating its capability to detect the presence of the 420 target hazardous substances. We believe our method provides strong technical support for ensuring the quality and safety of feed. Full article

Background/Objectives: The increase in incidences of multidrug resistance exacerbates tuberculosis-related global health challenges and underscores a call for more efforts for development of new antitubercular drugs, including the use of medicinal plants, especially those that have been used for generations by traditional healers. Despite reports of antimicrobial activity and chemical profiling of Kirkia wilmsii (K. wilmsii) extracts, chemical structures of the bioactive agents have not been elucidated. Here, we used a combination of bioactivity-guided fractionation, mass spectrometry, and nuclear magnetic resonance to purify and elucidate the chemical structure of antimycobacterial agents contained in leaf and twig extracts for K. wilmsii. Results: After overnight extraction with acetone and 90 g of dry twigs and leaves produced 5.38 g (6%) and 4.56 g (5%) of product, which displayed moderate antimycobacterial activity of 0.5 and 1 mg/mL, respectively. The antimycobacterial activity was increased six- and three-fold, respectively, after the crude extracts were subjected to solvent–solvent partitioning. Due to many bioactive fractions being obtained after silica gel chromatography purification, fraction 5 of twig extract was prioritized for further purification due to its low minimum inhibitory concentration (MIC) (0.25 mg/mL) and cytotoxicity (20%, in THP-1 cells). Sequential purification of the fraction 5 (twig extract) extracts through the C18 cartridge and high-performance liquid chromatography (HPLC) produced four fractions, which were subjected to structural elucidation. The high-resolution mass spectrometric analyses revealed that the first two eluting peaks had the same mass ion of 441.0822 m/z (M − H⁻), which corresponded to catechin monogallate, and so were the last two eluting peaks, which had a mass ion of 539.0932 m/z (M − H⁻), corresponding to catechin digallate. Further analyses by ¹H, ¹³C, and 2D NMR confirmed the chemical structures of compounds eluting in the first two peaks on HPLC as structural isomers of catechin 3′-monogallate and catechin 4′-monogallate (MIC not determined). Similarly, compounds eluting in the last two peaks were identified as structural isomers catechin 3′-digallate and catechin 4′-digallate, with an MIC of 250 µg/mL against Mycobacterium smegmatis and Mycobacterium tuberculosis H37Rv and an MBC of 500 μg/mL against M. smegmatis. Conclusions: To the best of our knowledge, this study is the first to report the structure of catechin 3′- and 4′-digallate, their antimycobacterial activity, and the existence of acyl migration involving galloyl 3′ and 4′-hydroxyl groups of catechin ring B. Full article

Osteoporosis is a prevalent metabolic bone disorder characterized by reduced bone mass, compromised microarchitecture, and increased fracture risk. Its pathogenesis extends beyond simple bone mineral density (BMD) loss and reflects complex disruptions in bone remodeling governed by osteoblast–osteoclast coupling and systemic metabolic factors. This review lays particular emphasis on diabetes mellitus-related osteoporosis (DOP) and estrogen deficiency-induced osteoporosis (EDOP), discussing bone remodeling between osteoclastogenesis and osteoblast differentiation regulated by key signaling pathways, including the RANKL/RANK/OPG, Wnt/β-catenin, BMP–Smad, Hedgehog, and inflammatory cytokine networks. This review then explores how chronic hyperglycemia, insulin deficiency or resistance, oxidative stress, ferroptosis, advanced glycation end products, and low-grade inflammation disrupt bone homeostasis in diabetes, resulting in impaired bone quality and elevated fracture risk, particularly in type 2 diabetes. In parallel, we discuss the genomic and non-genomic actions of estrogen in maintaining skeletal integrity and elucidate how estrogen deficiency accelerates bone resorption and suppresses bone formation through altered cytokine signaling, oxidative stress, and impaired mechanotransduction. Advances in diagnostic strategies beyond BMD, including trabecular bone score, high-resolution peripheral quantitative computed tomography, and emerging biomarkers, are reviewed. Finally, this review summarizes current and emerging therapeutic approaches tailored to DOP and EDOP, emphasizing the need for mechanism-based, individualized management. A deeper understanding of these shared and distinct pathways may facilitate improved risk stratification and the development of targeted interventions for osteoporosis. Full article

Decades ago, the introduction of GC-MS marked a significant advancement in primary plant metabolite studies. Here, in our review, we will delve into critical aspects of the workflow, spanning the selection of an analytical platform, sample preparation, analytical acquisition, and data processing and interpretation. The exceptional separation capabilities of GC, characterized by remarkable chromatographic resolution, render it ideal for analysis of the complex plant metabolome, including the separation of isomeric compounds. The diversity of analytical platforms allows the investigation of plant metabolomes using targeted and non-targeted approaches. GC-MS, equipped with efficient extraction methods and reliable derivatization protocols for semi- and non-volatile compounds, enables qualitative and quantitative analysis of these molecules. The stability of derivatives forms the foundation for the robustness and reproducibility of GC-MS methods, and their mass spectra provide characteristic fragments for confident identification and sensitive quantification of individual metabolites. There has been key progress in the advancement of GC-MS approaches to studying plant metabolism. However, the presence of artifacts during GC-MS analysis, particularly during derivatization, is a challenge that requires careful validations, which frequently necessitate additional investigations. The feasible solutions that were achieved to overcome the limitations in GC-MS-based studies are a particular focus of the present discussion. Full article

Glycogen synthase kinase-3 beta (GSK-3β) is a multifunctional serine/threonine kinase mediating multiple cellular functions, such as differentiation, apoptosis, and cell proliferation. Because of their ability to alter carcinogenic pathways, GSK-3β inhibitors are being explored for the development of anticancer molecules. In the present study, we synthesized and evaluated the cytotoxic properties of a series of twenty indole–triazole-linked pyrazolone derivatives, 10Aa–Ed. All derivatives were characterized by FTIR, ¹H/¹³C NMR, and high-resolution mass spectrometry (HRMS) methods. All compounds and standards, sunitinib and 5-Fluorouracil (5-FU), were screened against four adherent cell lines, including pancreatic adenocarcinoma (Capan-1), colorectal carcinoma (HCT-116), glioblastoma(LN229), and lung carcinoma (NCI-4460), and four non-adherent cell lines, including acute myeloid leukemia (HL-60), chronic myeloid leukemia (K562), T lymphoblast (MOLT4), and non-Hodgkin lymphoma (Z138). Among the screened derivatives, molecule 10Aa showed cytotoxicity against MOLT 4, Z138, and HL60 with CC₅₀ values of 14.45 μM, 15.34 μM, and 17.56 μM, respectively. GSK-3β kinase inhibition was evaluated with the 10Aa, which is capable of inhibiting GSK-3β in a dose-dependent manner. Additionally, molecular docking was performed to estimate the correlation between invitro data and GSK-3β binding affinity. The outcomes of the invitro experiments demonstrated strong concordance with the insilico data. The discovery yielded compounds 10Aa and 10Cd, which can be modified to create effective anticancer agents that target GSK-3β. Full article

Background/Objectives: Cholangiocarcinoma (CCA) is a very aggressive biliary carcinoma characterised by significant molecular heterogeneity and restricted treatment alternatives. Despite genomic and proteomic investigations revealing recurrent changes, the signalling dynamics influencing tumour behaviour remain inadequately comprehended. Methods: We conducted high-resolution Liquid Chromatography–Tandem Mass Spectrometry (LC–MS/MS)-based phosphoproteomics on paired tumour and surrounding tissues from 13 CCA patients in Northeast Thailand, meticulously sampling four geographically unique tumour areas for each patient. Our analysis concentrated on phosphoproteins consistently identified across all regions, delineating strong tumour-specific and cohort-wide phosphorylation signatures. Results: Notwithstanding considerable inter-patient variability, two conserved signalling modules were identified: an adhesion/Wnt axis regulated by hyperphosphorylated CTNNB1 protein (β-catenin) and a metal-handling module facilitated by metallothionein-1G (MT1G) protein and metallothionein-2A (MT2A) protein. Pathway enrichment identified focal adhesion, ECM-receptor interaction, cytoskeletal modulation, and mineral absorption as critical activities. Conclusions: This study elucidates conserved oncogenic pathways by analysing phosphoproteomic signatures across regional and patient-level variability, emphasising phosphoproteomics as a robust framework for biomarker and therapeutic development in CCA. Full article