Search Results (10,717)

Factors such as latitude, harvesting stage, and stubble height influence silage quality and harvesting decisions. We aimed to examine how harvest stage and stubble height affect the quality of whole-plant corn silage across different latitudes in Northeast China. Experiments were conducted in five different latitude regions (Shenyang, Changchun, Tongliao, Harbin, and Qiqihar) and assessed three stubble heights (20, 40, and 60 cm) at each harvest maturity stage: milk, initial wax, middle wax, late wax, and full maturity. After fermentation, whole-plant corn silage samples were collected and evaluated for nutritional content, fermentation quality, and toxin levels. Increasing the stubble height increased the dry matter (DM), crude protein, starch, and deoxynivalenol content in the whole-plant corn silage (p < 0.01), but decreased the acid detergent fibre and neutral detergent fibre concentrations (p < 0.01). Delayed harvest increased the DM and vomitoxin content (p < 0.01). The pH decreased initially and then increased as the harvest was delayed (p < 0.01). Meanwhile, NH₃–N and acetic acid content did not differ significantly with delayed harvesting (p > 0.05). At higher latitudes, the optimal harvest period is correspondingly delayed, shortening the harvest time. To maintain silage quality without affecting yield or economics, a 40 cm stubble height is recommended. If delayed, incrementally increasing the stubble height to 60 cm may be warranted to maintain silage quality. We provide data-driven insights to optimise silage production and ruminant nutrition. Full article

Composting chicken manure is a source of significant ammonia (NH₃) emissions, which, because of propagation, contributes to the eutrophication of the environment and decreases in air quality. Therefore, it is reasonable to use methods to limit its emission into the atmosphere. Biofiltration, using the metabolic activity of nitrifying and heterotrophic microorganisms capable of oxidizing ammonia, is an effective method to reduce ammonia emissions. In addition, the performance of the biofiltration process depends on operational parameters such as the humidity of the medium, the temperature, the contact time of the gas with the biofiltering medium, and the chemical composition and structure of the filter material. The aim of the study was to evaluate the effectiveness of biofilter fillings in reducing ammonia emissions from composting chicken manure along with the identification of factors allowing us to determine the proposed design solution as the most advantageous in terms of efficiency. Experiments on reducing odour emissions with biofiltration were carried out in two compact composting reactors, in which a compost mixture with a C:N ratio of 10:1 was used. The mixture was prepared in a ratio of 5:1 of chicken manure to the structuring material, with wheat straw used as the structuring material. Based on the results of the research on the course of the composting process, high values of ammonia concentration were recorded. Ammonia concentrations of 886 ppm (composter 1) and 811 ppm (composter 2) were recorded, which confirms the intensive nature of this gas emissions during the process of stabilizing the chicken manure. As part of the conducted research, the effectiveness of biofiltration in reducing ammonia emissions was evaluated by analysing the influence of the aeration intensity of the biofilter (20 dm³/h and 50 dm³/h), directly determining the time of contact of the gas with the bed (EBCT—Empty Bed Contact Time). Coconut-activated carbon was used as a filter bed, which was an effective carrier for the development of microorganisms responsible for the biological removal of ammonia from waste gases generated during composting. In addition, this material showed the ability to physically adsorb ammonia, thus supporting the process of its elimination. Each of the test stations has been equipped with a biofiltration installation. To determine the effectiveness of biological removal of ammonia and to assess the legitimacy of the use of selected strains of microorganisms in the process of biological removal of ammonia, the bed of one of the biofilters (biofilter 2) was inoculated with a strain of nitrifying bacteria. During the study, the high efficiency of ammonia removal because of biofiltration was noted in each of the configurations. In the case of an aeration intensity of 20 dm³/h, a reduction in emissions of 99% was achieved; with a higher aeration value, i.e., 50 dm³/h, the efficiency was 89%. These results indicate that the intensity of aeration has a significant impact on the efficiency of the biofiltration process. The analysis of a biofilter enriched with a strain of nitrifying bacteria requires long-term testing. This is important to reliably determine the effect of inoculation on the efficiency of the biological removal of ammonia in biofilters. It has been shown that optimizing these factors allows us to achieve a reduction in ammonia emissions of up to 90%, while minimizing the formation of unpleasant odours. The use of biofiltration in composting systems for organic waste of animal origin is an effective, sustainable solution that fits into the idea of sustainable development, combining the efficiency of air purification technology with environmental protection and the responsible management of resources. This study demonstrates that biofiltration using coconut-shell-activated carbon is an effective and economical method for reducing ammonia and odour emissions from composting chicken manure. The results provide valuable theoretical and practical information on emissions management in organic waste composting processes. Data from this study could be useful in developing strategies to minimize odour emissions, including from the agricultural sector. Full article

With the rapid evolution of Generative Adversarial Networks (GANs) and diffusion models (DMs), the detection of synthetic images faces significant challenges due to non-rigid artifacts and complex frequency biases. In this paper, we propose SIDWA, a novel dual-branch detection framework that leverages the synergy between frequency and spatial domains. Within the spatial branch, we design a Deformable Sliding Window Cross-Attention (DSWA) module, which utilizes a learnable offset mechanism to dynamically warp the receptive field, effectively capturing distorted edges and non-linear texture features. Simultaneously, the Discrete Wavelet Transform (DWT) Stem decomposes input images into multi-scale sub-bands to preserve crucial high-frequency residues. Through a Frequency-Semantic Resonance Projector (FSRP) strategy, the semantic priors from the spatial branch act as queries to guide the model toward localized frequency anomalies, achieving a unified “where to look” and “how to analyze” approach. Experimental results for the SIDataset (SIDset) benchmark demonstrate that Synthetic Image Detection based on Discrete Wavelet Transform Stem and Deformable Sliding Window Cross-Attention (SIDWA) achieves superior performance, with an average accuracy exceeding 95% and a competitive inference time of 18.2 ms on an NVIDIA A100 GPU. Ablation studies further validate the critical role of learnable offsets and frequency integration in enhancing robustness and generalization. SIDWA offers an efficient and reliable forensic solution for combating the growing threats of sophisticated generative forgeries. Full article

Background/Objectives: This study evaluated exercise-induced changes in body composition and metabolic biomarkers in women across distinct BMI categories and individuals with Type 2 diabetes. Methods: In this quasi-experimental study, 40 sedentary women were stratified into five groups (n = 8): underweight, normal weight, overweight, obese, and T2DM. The rigorous eight-week supervised program utilized submaximal exercise at 70–85% heart rate reserve, calculated via the Karvonen method and monitored by telemetry. Assessments included anthropometric parameters (BMI, fat mass, visceral fat) and serum biomarkers (irisin, myonectin, HIF-1α, insulin, glucose). Fasting venous samples were collected at baseline and 72 h post-intervention to minimize acute effects, then analyzed using validated ELISA protocols. Statistical data were evaluated using parametric or non-parametric tests with significance set at p < 0.05. Results: Post-intervention, significant reductions in weight, fat mass, and visceral fat occurred in overweight, obese, and T2DM groups (p < 0.05). Muscle mass increased across all cohorts. Fasting insulin and glucose decreased significantly in all except the underweight group, with the most pronounced improvements in T2DM and obese participants. Serum irisin increased significantly across all groups (p < 0.05), indicating a universal exercise-induced myokine response. Conversely, myonectin levels decreased significantly only in the normal-weight group, while HIF-1α increased specifically in the T2DM cohort. These findings suggest that baseline BMI and metabolic status are critical determinants of exercise responsiveness, leading to heterogeneous biomarker patterns despite consistent improvements in body composition and basic glycemic regulation. Conclusions: An eight-week submaximal program effectively improves body composition and glycemic regulation, though specific biomarker responses are highly dependent on baseline BMI and metabolic status. Full article

Residual β-cell secretory function plays a central role in diabetes pathophysiology; however, long-term comparative data describing β-cell trajectories from diagnosis across diabetes phenotypes remain limited. In this prospective observational study, 393 adults with newly diagnosed diabetes underwent assessment of fasting and glucagon-stimulated C-peptide at diagnosis. The cohort included individuals with type 1 diabetes mellitus (T1DM), encompassing both classical adult-onset autoimmune diabetes and latent autoimmune diabetes in adults (LADA), as well as individuals with type 2 diabetes mellitus (T2DM). A subgroup of 89 participants underwent follow-up visit after a mean of seven years. Glucagon stimulation testing was not repeated at follow-up in patients with T1DM and LADA for clinical and safety reasons; therefore, longitudinal analyses in these groups are based on fasting C-peptide measurements. At diagnosis, fasting and glucagon-stimulated C-peptide concentrations differed markedly between phenotypes (median fasting C-peptide: 0.87 ng/mL in T1DM, 1.53 ng/mL in LADA, and 2.64 ng/mL in T2DM; stimulated C-peptide: 1.35, 1.86, and 4.60 ng/mL, respectively; all p < 0.001). During follow-up, patients with T1DM exhibited a pronounced decline in fasting C-peptide (from 0.95 to 0.10 ng/mL), whereas individuals with T2DM showed preserved or increased stimulated responses (from 4.37 to 5.46 ng/mL). Participants with LADA displayed intermediate baseline values and a gradual decline in fasting C-peptide (from 1.41 to 0.31 ng/mL). Higher baseline C-peptide concentrations were associated with more favourable long-term metabolic profiles, including lower insulin resistance and better glycaemic control. These findings demonstrate that the early dynamic assessment of β-cell reserve using the glucagon stimulation test complements fasting C-peptide by revealing biologically meaningful heterogeneity in disease trajectories, thereby refining phenotypic classification and prognostic stratification at the time of diabetes diagnosis. Full article

Background and Objectives: Diabetes mellitus (DM) has been consistently linked to severe coronavirus disease 2019 (COVID-19) and adverse outcomes; however, the extent to which DM independently predicts mortality and cardiovascular complications in real-world hospitalized cohorts remains debated, particularly in Eastern Europe. This study aimed to evaluate the impact of DM on cardiovascular complications and in-hospital outcomes among adults hospitalized with SARS-CoV-2 infection. Materials and Methods: We conducted a single-center retrospective observational cohort study including consecutive adult patients hospitalized with laboratory-confirmed SARS-CoV-2 infection between March 2020 and December 2024 at the “Victor Babeș” Clinical Hospital of Infectious Diseases and Pneumophthisiology, Timișoara, Romania. DM status (type 1, type 2, or newly diagnosed diabetes) was defined using structured dataset fields. The primary outcome was in-hospital all-cause mortality. Secondary outcomes included ICU admission, length of stay, pulmonary embolism (PE) on CT pulmonary angiography (CTPA), and a composite of in-hospital cardiovascular/thromboembolic complications. Multivariable logistic regression models adjusted for clinically relevant covariates (age, sex, BMI, vaccination status, hypertension, ischemic heart disease, atrial fibrillation, prior ischemic stroke, and admission creatinine). Results: A total of 395 patients were included; 98 (24.8%) had DM. Diabetic patients exhibited a high cardiometabolic burden (arterial hypertension: 83.7% vs. 77.4%, p = 0.242) and higher admission renal markers (urea: 55.6 [41.0–79.1] vs. 48.6 [39.2–68.0] mg/dL, p = 0.047; creatinine: 1.04 [0.76–1.52] vs. 0.88 [0.59–1.33] mg/dL, p = 0.008). In-hospital mortality was numerically higher in DM (9.2% vs. 6.7%, p = 0.560), as was ICU admission (7.1% vs. 4.7%, p = 0.503), without statistical significance. PE on CTPA occurred in 13.3% of DM vs. 11.4% of non-DM patients (p = 0.763). In univariable analysis, DM was not significantly associated with mortality (OR 1.40, 95% CI 0.62–3.19; p = 0.422) or ICU admission (OR 1.55, 95% CI 0.61–3.97; p = 0.356). After multivariable adjustment, DM remained not independently associated with mortality (adjusted OR 1.09, 95% CI 0.42–2.83; p = 0.854) or ICU admission (adjusted OR 1.19, 95% CI 0.42–3.36; p = 0.747). Conclusions: In this real-world Eastern European cohort of hospitalized adults with SARS-CoV-2 infection, diabetes mellitus was common and associated with significantly worse renal function at admission, but it was not statistically associated with in-hospital mortality or ICU admission after multivariable adjustment; however, the limited number of events and low events-per-variable raise concerns about model stability and potential false-negative findings. These findings support a risk-marker model in which adverse COVID-19 outcomes in diabetic patients are driven primarily by clustered vulnerability and organ dysfunction rather than diabetes status alone. Full article

Background: Melioidosis is a potentially fatal infectious disease caused by Burkholderia pseudomallei and is highly prevalent in tropical regions. Diabetes mellitus (DM) is the most common comorbidity among patients with melioidosis and is a well-established risk factor for acquiring the infection. However, the impact of diabetes on disease severity and mortality remains uncertain. Methods: We conducted a systematic review and meta-analysis of observational studies to evaluate the association between diabetes mellitus and severe clinical outcomes in patients with melioidosis. PubMed, Embase, and Scopus were searched from database inception to 6 January 2026. Outcomes of interest included bacteremia, septic shock, intensive care unit (ICU) admission, and mortality. Pooled odds ratios with 95% confidence intervals (CIs) were calculated using random-effects models. Heterogeneity was assessed using the I² statistic. The review was registered in PROSPERO (CRD420251237028). Results: Twelve studies comprising patients from Southeast Asia, Australia, and South Asia were included. Diabetes prevalence among patients with melioidosis ranged from 31% to 76%. Meta-analysis showed no significant association between diabetes mellitus and bacteremia (OR 1.48, 95% CI 0.97–2.27), ICU admission (OR 1.31, 95% CI 0.43–3.99), septic shock (OR 0.67, 95% CI 0.39–1.16), or mortality (OR 0.82, 95% CI 0.66–1.03). Subgroup analysis revealed lower mortality among patients with diabetes in Southeast Asia (OR 0.74, 95% CI 0.61–0.91), while no significant association was observed in Australia. Heterogeneity varied across outcomes and regions. Conclusions: Although diabetes mellitus is a major risk factor for acquiring melioidosis, our findings suggest that it is not consistently associated with increased disease severity or mortality once infection occurs. These results should be interpreted cautiously given the limited number of included studies, heterogeneity across outcomes, and potential residual confounding. Further prospective studies are required to better define the underlying biological and healthcare-related mechanisms. Full article

As the global urban economy accelerates its transition from an “industrial economy” to a “service economy”, consumption has replaced investment as the core engine driving economic development. Commercial land serves as the physical foundation for consumer activities and plays a vital role in boosting urban economic vitality, enhancing residents’ quality of life, and promoting regional sustainable development when appropriately allocated. This study constructs a technical framework for analyzing the mismatch between commercial land supply and residential consumption demand, along with its impact mechanism, based on the integrated application of the multidisciplinary quantitative models such as the Boston Consulting Group Matrix (BCGM), Exploratory Spatial Data Analysis (ESDA), Decoupling Model (DM), and Explainable Machine Learning (EML). It conducts empirical research across 87 county-level cities in Gansu Province. The findings reveal that commercial land supply and consumption demand exhibit dynamic diversification, with prominent regional disparities and spatial autocorrelation characteristics. Commercial land in Gansu faces a severe mismatch, with demand exceeding supply and supply exceeding demand occurring simultaneously, and the former holding absolute dominance. The formation of mismatched relationships is influenced by many factors, exhibiting significant path nonlinearity, spatial non-stationarity, and relational interactivity. It is suggested that strategies of planning zoning and regional coordination be developed for mismatch governance, and differentiated management measures be implemented based on local conditions. This will provide a scientific basis for commercial territorial space planning and consumption policy design. Full article

Pediatric patients with SARS-CoV-2 infection are at an increased risk of severe disease and adverse outcomes. Nevertheless, comprehensive data on COVID-19 vaccine effectiveness (VE) in children with diabetes during the post-pandemic period remain limited. This study assessed the VE against severe COVID-19 outcomes during both the pandemic and post-pandemic phases in children with and without diabetes mellitus (DM). A cohort study based on population data was carried out, including all patients under 18 years of age with symptomatic SARS-CoV-2 infection as registered in the Brazilian national surveillance systems from February 2020 to June 2025. The main outcomes were hospitalization due to COVID-19 and severe illness, which included admission to the intensive care unit (ICU), need for invasive ventilation, and death. Utilizing a propensity score-matched cohort, we estimated the VE and the number needed to vaccinate (NNV) for a booster dose against these outcomes by comparing vaccinated and unvaccinated individuals, employing conditional logistic regression adjusted for confounding variables. The cohort comprised 3,730,007 pediatric patients with COVID-19, of whom 7675 (0.2%) had DM. At baseline, children with DM exhibited a significantly higher prevalence of hospitalization (11.2% vs. 2.0%), severe COVID-19 (6.4% vs. 0.6%), and mortality (1.9% vs. 0.1%) than those without DM (all p < 0.001). During the pandemic period, the adjusted VE was consistently higher in children with DM. Against severe disease, the VE was 72.8% (95% CI: 12.3–93.2) in the DM cohort compared with 45.7% (28.1–59.0) in the non-DM cohort. This increased effectiveness corresponded to a more favorable NNV; the NNV to prevent one severe case was 24 (95% CI: 12–232) for children with DM versus 243 (168–440) for those without DM. In the post-pandemic period, the VE remained significantly higher in the DM cohort. Against severe disease, the VE was 76.2% (11.5–93.5) for children with DM and 52.9% (32.7–67.1) for those without. The NNV to prevent one severe case was consistently lower in the DM cohort (8 vs. 591). In conclusion, a complete vaccination regimen, including a booster dose, substantially mitigated severe COVID-19 outcomes in children with DM in the pandemic and post-pandemic periods. Full article

The rising global incidence of Type 1 Diabetes Mellitus (T1DM) necessitates a deeper understanding of the molecular shifts underlying its metabolic complications, specifically the role of protein N-glycosylation. This study utilized a streptozotocin-induced C57Bl/6 mouse model to examine temporal changes in plasma N-glycan profiles at 2, 8, and 20 weeks post-induction using HILIC-UPLC-FLR-MS. Following the successful establishment of persistent hyperglycemia and weight loss, glycomic analysis revealed significant structural remodeling of 20 individual glycan species, with complex, multi-sialylated structures proving most sensitive to disease progression. Notably, bi-antennary structures such as A2G1S1, A2G2S1, and A2G2S2(2) exhibited a marked decrease in relative abundance that strongly correlated with elevated blood glucose levels. In contrast, highly sialylated and fucosylated glycans like FA2G2S3 and FA3G3S3 showed a progressive increase over the 20-week period, suggesting an adaptive response to chronic metabolic stress and altered hepatic processing. Our findings demonstrate that chronic hyperglycemia is accompanied by substantial remodeling of the plasma N-glycome, characterized by increased sialylation and fucosylation. These alterations closely track the progression of metabolic dysregulation, suggesting that while they parallel blood glucose trends, they provide a distinct molecular readout of the systemic glycosylation response to glucotoxicity. This study offers a detailed longitudinal characterization of these glycomic changes, highlighting their potential value as descriptive markers of cumulative metabolic stress in rodent models of type 1 diabetes. Full article

Erectile dysfunction (ED) is one of the most prevalent and disabling complications of diabetes mellitus (DM), thought to arise from the interaction of metabolic, vascular, and neural injury. Recent evidence indicates that diabetic neuropathy, affecting both somatic and autonomic pathways, plays a central role in the development of ED and is strongly associated with increased disease burden. Early neurophysiological studies documented impaired penile sensory conduction and abnormalities of sacral reflex pathways in diabetic men with ED, while more recent investigations have confirmed the contribution of cardiovascular autonomic neuropathy and small-fibre loss. At the molecular level, oxidative stress, advanced glycation end-product signalling, impaired nitric oxide bioavailability, and reduced neurotrophic support, particularly involving brain-derived neurotrophic factor (BDNF), emerge as key mechanisms linking diabetes to neural and neurovascular dysfunction. Although phosphodiesterase type-5 inhibitors remain first-line therapy, reduced responsiveness in patients with significant neuropathy highlights the importance of recognising the role of neurogenic mechanisms. Overall, the available evidence supports the conceptualisation of diabetic ED as a neurovascular manifestation within the broader spectrum of diabetic neuropathy rather than as a purely vasculogenic disorder. This review integrates historical and contemporary literature addressing the epidemiology, neurophysiology, pathophysiology and therapeutic implications of ED in diabetes, with a specific focus on its neuropathic substrate. These findings support a paradigm shift toward an integrated neurovascular approach to diabetic ED, highlighting the importance of early neuropathy-oriented assessment and paving the way for future regenerative and neuroprotective therapeutic strategies. Full article

Background/Objectives: Stress-induced hyperglycemia (SIH) is frequently observed in critically ill patients and has been associated with adverse outcomes in individuals both with and without known diabetes mellitus (DM). However, evidence regarding its prognostic utility for in-hospital mortality in high-acuity emergency department (ED) populations remains limited. Methods: We conducted a retrospective observational cohort study of consecutive adult ED patients classified as Emergency Severity Index (ESI) triage level 1. SIH was defined a priori as an admission serum glucose >140 mg/dL, a pragmatic cutoff widely applied in clinical practice despite ongoing debate regarding optimal pathophysiological thresholds. Associations with in-hospital mortality were assessed using logistic regression in the overall cohort and stratified by DM status. Additional analyses assessed the prognostic performance of admission glucose as a continuous variable. Results: Of 470 included patients, 435 had complete mortality data; 247 (56.8%) died during hospitalization. SIH was present in 258/435 (59.3%)and known DM in 114/435 (26.2%). SIH was associated with higher in-hospital mortality in univariate analysis (OR 2.90, 95% CI 1.91–4.43; p < 0.001) and remained independently associated after adjustment (adjusted OR 2.22, 95% CI 1.41–3.51; p < 0.001). The association between SIH and mortality persisted in both non-DM and DM subgroups, with no significant interaction by DM status. SIH alone showed modest discrimination for mortality (AUC 0.625, 95% CI 0.572–0.669), whereas continuous admission glucose performed better. Discrimination improved in the multivariable model (AUC 0.728, 95% CI 0.677–0.779). Restricted cubic spline analysis demonstrated a strong overall association between admission glucose and mortality without evidence of nonlinearity, indicating an approximately linear risk increase across the observed glucose range. Conclusions: Regarding severely ill ED patients, classified as ESI triage 1, SIH is an independent predictor of in-hospital mortality irrespective of DM status. Admission glucose may improve early risk stratification when incorporated into clinical models.  Full article

This study assessed the impact of the dietary inclusion of Prosopis laevigata pods (PLPs) on growth performance, carcass traits, and the metabolomic profiles of liver and meat in finishing lambs. A total of 28 crossbred lambs (38 ± 5 kg body weight) were allocated to one of two treatments: a control diet (0 g PLP/kg dry matter, n = 14; CONT) and a diet supplemented with 300 g PLP/kg dry matter (DM) (n = 14; PS). Growth performance was monitored over 25 days. Animals were assigned to a randomized design, and data were analyzed using the General Linear Model (GLM) procedure. Compared with the control diet, PLP inclusion (300 g/kg DM) reduced total body weight gain (p = 0.04) and worsened feed conversion efficiency. Lambs on the control diet also displayed a significantly greater (p = 0.02) rump perimeter. In contrast, lambs fed the 300 g PLP/kg DM diet showed a marked increase (p < 0.05) in the longissimus thoracis et lumborum (LTL) muscle area. Principal component analysis revealed a distinct separation between treatment groups based on the identified metabolites. Liver metabolomic data accounted for 30.6% of the total variability, while meat samples accounted for 45.7%. A total of 21 and 23 metabolites exhibited positive correlations in liver and meat, respectively. Notably, PLP supplementation influenced several metabolic pathways (p < 0.05), including the biosynthesis of unsaturated fatty acids, fatty acid biosynthesis, and sulfur metabolism in both liver and meat. Additionally, phenylalanine metabolism was specifically affected (p < 0.05) in the liver, while steroid biosynthesis was altered (p < 0.05) in meat. Overall, the inclusion of PLPs in the diet of finishing lambs resulted in notable changes to the liver and meat metabolomes, particularly in pathways associated with fatty acid biosynthesis. Although PLP supplementation reduced overall growth performance, it did not negatively impact carcass quality traits; hence, we recommend the inclusion of 300 g PLP/kg DM in finishing lamb diets. Full article

European bioeconomy policies stress the need for responsible, efficient feedstock use and timely, comprehensive data on ecosystems and bioeconomic activities. This paper addresses the data gap by: (i) providing holistic county-level (sub-NUTS3) biomass maps for the Republic of Ireland (RoI), covering primary feedstocks (PFs) and secondary feedstocks (SFs, i.e., by-products and waste); (ii) identifying feedstock uses during the study period. In total, 221 feedstocks were mapped: 85 solid PFs (approx. 43 million tonnes dry matter (tDM) nationally) and 136 solid SFs (approx. 6 million tDM nationally), plus 6 liquid PFs (approx. 18 thousand million m³ nationally) and 8 liquid SFs (approx. 39 thousand million m³ nationally). The mapping indicates that environmentally sustainable bio-based value chains (BBVCs) requiring large amounts of solid or liquid SF should prioritise processing sites near major feedstock sources in the southeast and southwest of the RoI. The northwest and east coast have the lowest availability, while the west and midlands have the most variety in quantity and type of feedstock. Counties with abundant feedstocks do not necessarily have high feedstock diversity, except for Cork. Granular sub-NUTS3 mapping of quantities and fate provides a powerful foundation for future feedstock strategies and empowers stakeholders to design innovative BBVCs. Full article

Type 2 diabetes mellitus (T2DM) is one of the most prevalent chronic metabolic diseases, and inhibition of α-glucosidase activity represents an effective therapeutic strategy. Chitin is the most abundant renewable polysaccharide in the ocean, with its monosaccharide being N-acetylglucosamine (NAG). To evaluate the potential of NAG glycosides as novel α-glucosidase inhibitors, three common phenolic compounds were modified via NAG glycosylation. Their inhibitory activities were assessed at both the enzymatic and cellular levels. In addition, density functional theory (DFT), molecular dynamics (MD) simulations, and molecular docking analyses were employed to systematically investigate the effects of NAG glycosylation on enzyme inhibition and the underlying mechanisms. Compared with the parent phenolic compounds, NAG glycosides exhibited significantly enhanced α-glucosidase inhibitory activity, with NAG introduction markedly improving their binding affinity to α-glucosidase. Among them, glycoside 3a displayed the optimal inhibitory effect, comparable to acarbose, and at the cellular level, its activity at high concentrations was comparable to or slightly higher than that of metformin. Circular dichroism (CD) and MD analyses indicated that glycoside 3a increased the conformational flexibility of key residues and enhanced the structural looseness of the enzyme, thereby inhibiting its activity. NAG glycosides constitute a promising class of marine-derived α-glucosidase inhibitors, warranting further structural optimization and rational design to enhance their activity and selectivity. Full article