The efficient conversion of lignocellulosic biomass into methane (CH4) remains a major challenge due to its intrinsic structural recalcitrance, primarily governed by lignin complexity. Although numerous pretreatment technologies have been developed, the relationship between lignin reduction and CH4 production is often assumed to be directly proportional, despite limited mechanistic evidence. This study presents a systematic review and multivariate statistical analysis of 283 studies (2005-2025) to elucidate the relationship between lignin modification and CH4 enhancement. A multi-level analytical framework was applied to quantify this relationship, integrating Spearman and Pearson correlation analyses, second-order polynomial regression, and k-means clustering. In addition, a Pretreatment Efficiency Index was proposed to integrate structural and biological responses. The results suggest a partial decoupling between lignin reduction and CH4 production, as indicated by a moderate linear relationship (r = 0.656) and a non-linear regression fit (R2 = 0.4525), showing that higher delignification is not consistently associated with improved methanogenic performance. Solvent-based pretreatments achieved lignin reductions above 80-90%, but CH4 enhancement generally remained below 200%. In contrast, selective pretreatments, particularly ozonation, showed superior performance, reaching up to 658% increase in CH4 yield with moderate lignin reduction (39-71%), owing to its ability to selectively modify lignin while preserving fermentable carbohydrates and minimizing inhibitor formation. Overall, the findings suggest that pretreatment selectivity represents a stronger predictor of CH4 enhancement than process severity, thereby providing a mechanistic and decision-oriented framework for optimizing lignocellulosic biogas production systems.
Trioza erytreae is a vector of Huanglongbing (HLB), a highly damaging citrus disease. Lemon plants (Citrus ×limon) are the preferred host for T. erytreae, although the underlying mechanisms behind this remain to be fully elucidated. A comparative proteomic analysis of T. erytreae nymphs in their fourth and fifth instars that were fed either lemon or sweet orange (SwO) was carried out to investigate the interaction with its hosts. A 24-hour sucrose feeding assay was conducted to understand proteomic responses to a nutrient-poor diet. Proteomic profiling using nanoscale liquid chromatography coupled to tandem mass spectrometry (nanoLC-MS/MS) identified a total of 1,477 psyllid proteins with high confidence. Oviposition and nymphal development were also evaluated across citrus hosts, revealing higher numbers of nymphs developing on lemon than on SwO. Feeding on SwO enriched pathways related to “transmission across chemical synapses” and “metabolism of proteins”. Responses observed under a 24-hour sucrose-only diet enriched the biological processes “response to external stimulus”, “response to stress” and “cytoskeleton organization”. In contrast, these enrichments were absent on lemon host, suggesting that lemon provides a more favourable environment for psyllid development. In addition, nymphs developed on lemon exhibited enhanced energy metabolism and an increase in translation initiation factors. Overall, the results demonstrate that development strongly depends on host plant species, with SwO impairing optimal growth and lemon promoting successful nymphal development.
Liver diseases are a significant global health concern affecting millions worldwide. Prevention, early diagnosis and treatment are crucial in mitigating complications and improving patient quality of life. Machine learning techniques are essential for supporting medical decisions and improving diagnosis precision. In this context, this work presents a collaborative system based on a features selection voting technique that identifies the most important feature to define the disease presence or absence. The most representative features identified through this voting process were employed in the Fuzzy c-means clustering algorithm. Furthermore, a ranking method was developed, which proved to be a valuable tool for measuring the patient risk and analyze anomalous values. In summary, the proposed method demonstrated substantial advantages in a clinical setting, providing diverse information that supports clinical decision-making in terms of liver disease diagnosis.
Microplastics are emerging pollutants that have raised great concerns to the fish community and are present in most freshwater aquatic ecosystems. These pollutants can cause physical damage and accumulate in the gastrointestinal tract, leading to intestinal obstruction. Thus, the objective of this study was to evaluate the presence of microplastics in the gastrointestinal content of the fish community in the Jaguariaíva River, considered an important tributary of the Itararé River, upper Paraná River basin, Brazil. To this end, we tested whether (i) microplastic ingestion varies among fish from different trophic guilds (detritivores, omnivores, herbivores, insectivores, and piscivores) and (ii) whether ingestion is associated with habitat use (demersal, benthopelagic, and pelagic). The fishes were collected from March 2013 to December 2014 at seven points along the Jaguariaíva River and had their gastrointestinal tracts removed and analyzed in the laboratory. Microplastics were analyzed with a micro Fourier transform infrared spectrometer. In general, fibers and fragments were found in 13 fish species, with their composition being polyvinyl alcohol and polydimethylsiloxane. Furthermore, the consumption of these microplastics was not associated with trophic groups or the types of habitats used by the species analyzed. The presence of microplastics in fish provides insights into the current pollution in the Jaguariaíva River. These findings reinforce the need for mitigation measures to reduce plastic pollution and minimize its impact on aquatic biodiversity.
Ion-exchange modification of commercial binder-free zeolites offers a promising strategy to improve adsorption-based CO2 capture from post-combustion flue gases. In this study, the CO2/ N-2 separation performance of ion-exchanged binder-free Linde-Type A (LTA) zeolites-namely 4 A, 5 A, Sr(40)A, and Sr(80)A-was systematically evaluated under post-combustion capture (PCC) conditions. Adsorption isotherms were measured over the temperature range of 306-344 K and pressures up to 350 kPa. The CO2 uptake followed the order: 5 A > Sr(40)A > Sr(80)A > 4 A, with 5 A achieving the highest loading of 5.58 mol center dot kg(-1) at 120 kPa and 306 K, compared to 4.47 mol center dot kg(-1) for Sr(40)A, 4.45 mol center dot kg(-1) for Sr(80)A, and 3.73 mol center dot kg(-1) for 4 A. The presence of divalent cations (Ca2+ and Sr2+) strengthened the electrostatic interactions, thereby enhancing CO2 affinity relative to the Na-exchanged 4 A. Binary CO2/N-2 breakthrough experiments demonstrated that Sr(80)A exhibited the highest selectivity (75 at 10 kPa and 306 K), followed by 5 A (60), 4 A (51), and Sr(40)A (47). Which the developed mathematical model accurately captured the breakthrough behavior and dynamic performance of the fixed-bed system. Finally, a Response Surface Methodology (RSM) was applied to the statistical analysis of selectivity of different studied zeolites and getting the optimum operating conditions.
