In recent year, there has been increasing concern about the growing amount of plastic waste coming from daily life. Different kinds of synthetic plastics are currently used for an extensive range of needs, but in order to reduce the impact of petroleum-based plastics and material waste, considerable attention has been focused on “green” plastics. In this paper, we present a broad review on the advances in the research and development of bio-based polymers analogous to petroleum-derived ones. The main interest for the development of bio-based materials is the strong public concern about waste, pollution and carbon footprint. The sustainability of those polymers, for general and specific applications, is driven by the great progress in the processing technologies that refine biomass feedstocks in order to obtain bio-based monomers that are used as building blocks. At the same time, thanks to the industrial progress, it is possible to obtain more versatile and specific chemical structures in order to synthetize polymers with ad-hoc tailored properties and functionalities, with engineering applications that include packaging but also durable and electronic goods. In particular, three types of polymers were described in this review: Bio-polyethylene (Bio-PE), bio-polypropylene (Bio-PP) and Bio-poly(ethylene terephthalate) (Bio-PET). The recent advances in their development in terms of processing technologies, product development and applications, as well as their advantages and disadvantages, are reported.
Abstract Microalgae as an environmentally friendly renewable feedstock can be processed into an array of products via conversion technologies such as algal lipid upgrading, liquefaction, pyrolysis, gasification, and bioethanol technology. As a unique chemical reaction, pyrolysis of microalgae yields useful chemicals like light olefins, alkanes, syngas, and biochar, as well as the bio-oils with less oxygen, more hydrocarbons, and higher gross heating values than the bio-oils derived from cellulosic biomass. The article reviews direct pyrolysis and catalytic pyrolysis of microalgae, pyrolytic products, reaction mechanisms, and upgrading of microalgal bio-oils. Based on critical analyses of the state-of-the-art developments in this field, the article provides the following perspectives. The current major bottleneck of microalgal technologies is still the productivity, which makes microalgae less abundant than cellulosic biomass at this stage. Biorefinery of microalgae shall be further developed to produce multiple products from various microalgal species. Determination of high value-added chemicals that can be produced from microalgae, especially from microalgal proteins, might significantly promote the development of the conversion technologies and related catalytic science. Designing novel catalysts for the selective conversion of microalgae into fine chemicals may increase the effective use of microalgae and the economics of the process. With the advancement of science and technology, catalytic pyrolysis technology has the potential to process microalgae into biofuels and fine chemicals.
Abstract This study introduces a bio-inspired AlN-piezoelectric MEMS microphone that showcases a cantilever structure offering adjustable performance, fully emulating the dynamics and tunability observed in the basilar membrane of the mammalian cochlea. Through the incorporation of piezoelectric and converse piezoelectric effects alongside dual parametric modulation mechanisms, the device successfully replicates three crucial aspects of cochlear mechanics: i) sensory transduction characteristic of inner hair cell (IHC); ii) local stiffness modulation enabled by outer hair cell (OHC) somatic motility; and iii) energy redistribution in coupled-system recapitulating the energy transfer of cochlear traveling wave dynamics. The device performance was systematically characterized through electrical characterizations, optical analysis, and acoustic measurements. Experimental results demonstrate a baseline sensitivity of −25.38 dB/Pa and signal-to-noise ratios up to 79.28 dB within an operation bandwidth from 1.755 to 2.261 kHz (3 dB cut-on and cut-off bandwidth), while the quality factor (Q) can be tuned to a value ranging from −55.38% to 180.10% of initial values, representing a 124.72% tuning span. In essence, the critical innovations encompass: i) a MEMS microphone that pioneers the first fully mimicking simultaneous sensing/tuning functionality of the mammalian cochlea, through piezoelectric and converse piezoelectric effects; ii) a combination of two novel tuning mechanisms, i.e., AC (through parametric modulation) and mechanical coupling, are applied without the necessity for mechanical structure modification. It can be envisioned that such a technology enables next-generation hearing aids with bio-inspired auditory adaptation, bridging a critical gap in prosthetic sound processing, while also catering to the ever-increasing demands of intelligent acoustic sensors.
Chourouk Guettas, Foudil Cherif, Ammar Muthanna
et al.
Vision-based robot control remains a significant challenge due to the sample inefficiency and prolonged training times associated with traditional deep reinforcement learning methods. We propose a novel approach inspired by biological gene regulation, leveraging Gene Regulatory Networks (GRNs) for efficient and robust robot control. In our approach, robot states are encoded as gene expression levels, and evolutionary optimization is used to learn GRN parameters that map raw visual inputs to motor commands. We evaluate this method on the KukaDiverseObjectEnv benchmark, where robots must grasp diverse objects using only RGB images. Our GRN-based controller achieves a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>57.5</mn><mo>%</mo></mrow></semantics></math></inline-formula> success rate while reducing training time by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>13.7</mn><mo>×</mo></mrow></semantics></math></inline-formula> compared to Proximal Policy Optimization baselines. It also outperforms NEAT, standard reinforcement learning algorithms, and deep Q-learning in terms of both efficiency and performance. The controller maintains <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>91.8</mn><mo>%</mo></mrow></semantics></math></inline-formula> performance under noisy visual conditions. This bio-inspired design naturally enables hierarchical control via expression cascades, computational efficiency through bounded dynamics, and temporal reasoning without explicit memory modules.
Abstract
Objective
To explore the causal relationships between plasma total testosterone (TT), bioavailable testosterone (Bio-T) levels and the pathogenesis of aortic aneurysm (AA) using Mendelian randomization (MR).
Methods
Single nucleotide polymorphisms (SNPs) strongly associated with TT and Bio-T (P<5×10-10) and with low bias were selected from the IEU Open GWAS public genome database as instrumental variables, with AA as the outcome. The inverse variance weighted (IVW) method served as the primary analytical approach, complemented by MR-Egger regression, weighted median estimation (WME), simple mode, and weighted mode analyses. Sensitivity analyses were conducted using Cochran’s Q test, MR-Egger intercept test, MR-PRESSO test, leave-one-out analysis, and funnel plot inspection, with statistical significance set at P<0.05.
Results
Two-sample MR analyses revealed causal associations between both TT and Bio-T levels and AA risk, with consistent directional results from MR-Egger regression and WME. MR analysis indicated heterogeneity for the causal association between TT and AA (Cochran’s Q=132.081, P=0.024); MR-PRESSO identified no outlier SNPs, prompting adoption of the random-effects model as the primary result (IVW: OR=0.856, 95%CI: 0.744 to 0.985, P=0.030). The causal effect of Bio-T (IVW: OR=0.551, 95%CI: 0.304 to 0.998, P=0.049) on AA incidence was stronger than that of TT (OR=0.856). Progressive stringent SNP selection thresholds (down to P<5×10-33) and a suite of sensitivity analyses confirmed the robustness of the causal association between Bio-T and AA.
Conclusion
Both plasma TT and Bio-T levels are causally associated with AA occurrence, with Bio-T conferring a stronger and more robust causal effect. Maintaining healthy, adequate plasma testosterone levels, particularly Bio-T levels, markedly reduce AA risk, offering novel targets and insights for AA prevention and treatment strategies.
Paul Richmond, Constantinos Papageorgakis, Vasilis Niarchos
et al.
We present specialized large language models (LLMs) for theoretical high-energy physics, obtained as 20 fine-tuned variants of the 8 billion parameter Llama-3.1 model. Each variant was trained on arXiv abstracts (through August 2024) from different combinations of hep-th, hep-ph and gr-qc. For a comparative study, we also trained models on datasets that contained abstracts from disparate fields such as the q-bio and cs categories. All models were fine-tuned using two distinct low-rank adaptation fine-tuning approaches and varying dataset sizes, and outperformed the base model on hep-th abstract completion tasks. We compare performance against leading commercial LLMs (ChatGPT, Claude, Gemini, DeepSeek) and derive insights for further developing specialized language models for high-energy theoretical physics.
In this paper, we propose a Bayesian Deep Learning (BDL) framework to model uncertainty and predict the performance of terahertz (THz) biosensors with a graphene and molybdenum disulfide (MoS<sub>2</sub>) coating for AML biomarker detection. Although there have been studies on the individual advantage of these 2D materials for biosensing, a comparative analysis taking into account predictive uncertainty is still insufficient. To this end, we have generated a high-fidelity simulation dataset from full-wave EM simulations of DSSRR structures over the 0.1–2.5 THz frequency range. Realistic geometrical and dielectric modifications have been incorporated to mimic bio-sensing conditions. An approach based on a Bayesian Neural Network (BNN) with Monte Carlo dropout was employed for predicting sensitivity, Q-factor, resonance shift, and absorption, along with the estimation of aleatoric, as well as epistemic, uncertainty. Our results demonstrated a trade-off between material types: MoS<sub>2</sub> sensors showed higher sensitivity (3548 GHz/RIU) but with a larger prediction uncertainty range of ±118 GHz/RIU; on the other hand, graphene-based sensors exhibited a better spectral resolution (Q = 48.5) and a more reliable QV prediction range of ±42 GHz/RIU. The uncertainty study further revealed that graphene demonstrated a predominance for aleatoric uncertainty (68%), classifying them as predictable physical characteristics, while MoS<sub>2</sub> presents a higher epistemic one (55%), indicating sensitivity towards underrepresented design cases. We present a material selection algorithm based on utility that balances sensitivity, resolution, and uncertainty, demonstrating that MoS<sub>2</sub> is the best choice for early screening, while graphene is more suitable for high-precision diagnostics. This study offers a scalable and reliable AI framework for quick, uncertainty-aware optimization of THz biosensors, which is directly applicable to clinical diagnostics and 2D-material-based photonic design.
Ester Sevillano, Irene Lafuente, Nuria Peña
et al.
Antimicrobial resistance (AMR) poses a significant challenge to animal production due to the widespread use of antibiotics. Therefore, there is an urgent need for alternative antimicrobial strategies to effectively manage bacterial infections, protect animal health, and reduce reliance on antibiotics. This study evaluated the use of emerging approaches and procedures for the isolation, identification, and characterization of bacteriocin-producing bacteria and their bacteriocins, sourced from the gastrointestinal tract (GIT) of meat-producing pigs. Out of 2056 isolates screened against Gram-positive and Gram-negative indicator strains, 20 of the most active antimicrobial isolates were subjected to whole genome sequencing (WGS) for the prediction of coding DNA sequences (CDS) and the identification of bacteriocin gene clusters (BGC) and their functions. The use of an in vitro cell-free protein synthesis (IV-CFPS) protocol and the design of an IV-CFPS coupled to a split-intein mediated ligation (IV-CFPS/SIML) procedure made possible the evaluation of the production and antimicrobial activity of described and putatively novel bacteriocins. A colony MALDI-TOF MS procedure assisted in the identification of class I, II, and III lanthipeptides. MALDI-TOF MS and a targeted proteomics, combined with a massive peptide analysis (LC-MS/MS) approach, has proven valuable for the identification and biochemical characterization of previously described and novel bacteriocins encoded by the isolated bacteriocin-producing strains.
Jihan K. Zaki, Jakub Tomasik, Jade A. McCune
et al.
Surface-enhanced Raman spectroscopy (SERS) is a potential fast and inexpensive method of analyte quantification, which can be combined with deep learning to discover biomarker-disease relationships. This study aims to address present challenges of SERS through a novel SERS bio-quantification framework, including spectral processing, analyte quantification, and model explainability. To this end,serotonin quantification in urine media was assessed as a model task with 682 SERS spectra measured in a micromolar range using cucurbit[8]uril chemical spacers. A denoising autoencoder was utilized for spectral enhancement, and convolutional neural networks (CNN) and vision transformers were utilized for biomarker quantification. Lastly, a novel context representative interpretable model explanations (CRIME) method was developed to suit the current needs of SERS mixture analysis explainability. Serotonin quantification was most efficient in denoised spectra analysed using a convolutional neural network with a three-parameter logistic output layer (mean absolute error = 0.15 μM, mean percentage error = 4.67%). Subsequently, the CRIME method revealed the CNN model to present six prediction contexts, of which three were associated with serotonin. The proposed framework could unlock a novel, untargeted hypothesis generating method of biomarker discovery considering the rapid and inexpensive nature of SERS measurements, and the potential to identify biomarkers from CRIME contexts.
Luis F Seoane, Henry Secaira-Morocho, Ester Lázaro
et al.
Understanding how viral mutant spectra organize and explore genotype space is essential for unraveling the mechanisms driving evolution at the finest scale. Here we use deep-sequencing data of an amplicon in the A2 protein of the RNA bacteriophage Q$β$ to reconstruct genotype networks with tens of thousands of different haplotypes. The study of populations evolved under different temperature regimes uncovers generic topological features conditioned by fundamental structural motifs of genotype networks -- tetrahedrons, triangles, and squares -- that govern their local architecture. Mutant swarms display a hierarchical structure where sequences cluster around a highly connected and abundant sequence core that sustains population diversity. The immediate neighborhood of this core is comprehensively sampled, with no signs of selection, while a few mutations away sampling becomes dynamical and sparse, showing signs of purifying selection. By aggregating genotype networks from populations adapted to different temperatures, we capture the early stages of evolutionary divergence, with overlapping populations that remain connected through short mutational paths. Even at the time scale of these experiments, evolutionary pathways might be multiple, preventing the backward reconstruction of unique trajectories once mutations have been fixed. This analysis provides a detailed view of the local, fine-scale processes shaping viral quasispecies evolution and underscores the usefulness of genotype networks as an enlightening visualization of the organization of mutant swarms.
Andrei Diakonov, Konstantin Khrizman, Eliran Zano
et al.
Abstract The broad and equidistant spectrum of frequency combs has had a profound impact on spectroscopic studies. Particularly, experiments involving the coupling of frequency combs to cavities have already enabled unprecedented broadband and sensitive spectroscopy on a single-molecule level. The emergence of integrated, compact, and broadband Kerr-microcombs holds promise to bring many metrological and spectroscopic studies outside of the lab. However, performing cavity-enhanced direct frequency comb spectroscopy on-chip has remained a challenge. Here, we couple a microcomb source with a microcavity to extend the advantages of cavity-enhanced spectroscopy to photonically integrated circuits. By harnessing the coherent nature of the Kerr-comb and high-Q microcavity enhancement, we obtain a detailed dispersion landscape of the guided-wave mode and comprehensive frequency-dependent cavity lineshapes. Our microcomb-cavity coupling can facilitate photonically integrated cavity-enhanced biochemical spectroscopy by evanescently coupling analytes to the cavity’s guided mode, a mode of operation we analyze numerically and provide guidelines for its potential implementation. Demonstrated detailed dispersion measurements, overperforming state-of-the-art table-top tunable lasers in available bandwidth, show potential for integrated non-linear optics applications, as precise dispersion management is crucial for such processes. Our chip-scale comb-cavity coupled platform suggests an integrated, broadband, cost-effective, and accurate tool for the non-linear optics studies as well as for ultra-compact bio- and chemical-sensing platform.
A label-free biosensor based on a tunable MEMS metamaterial structure is proposed in this paper. The adopted structure is a one-dimensional array of metamaterial gratings with movable and fixed fingers. The moving unit of the optical detection system is a component of the MEMS structure, driven by the surface stress effect. Thus, these suspended optical nanoribbons can be moved and change the grating pattern by the biological bonds that happened on the modified cantilever surface. Such structural variations lead to significant changes in the optical response of the metamaterial system under illuminating angled light and subsequently shift its resonance wavelength spectrum. As a result, the proposed biosensor shows appropriate analytical characteristics, including the mechanical sensitivity of S<sub>m</sub> = 11.55 μm/Nm<sup>−1</sup>, the optical sensitivity of S<sub>o</sub> = Δλ/Δd = 0.7 translated to S<sub>o</sub> = Δλ/Δσ = 8.08 μm/Nm<sup>−1</sup>, and the quality factor of Q = 102.7. Also, considering the importance of multi-biomarker detection, a specific design of the proposed topology has been introduced as an array for identifying different biomolecules. Based on the conducted modeling and analyses, the presented device poses the capability of detecting multiple biomarkers of disease at very low concentrations with proper precision in fluidic environments, offering a suitable bio-platform for lab-on-chip structures.
Oxalis corniculate L. (O. corniculate) was used to treat diabetes in Chinese folk as a popular tea drink. In this work, 31 compounds from O. corniculate were screened and identified as potential α-Glucosidase inhibitors (α-GIs). Among them, 6 compounds displayed stronger inhibitory activity than acarbose (IC50 = 212.9 ± 5.98 μg/mL). Especially, the most effective compounds quercetin (Qu, IC50 = 4.70 ± 0.40 μg/mL) and luteolin (Lu, IC50 = 15.72 ± 0.75 μg/mL) inhibited α-Glu in competitive and mixed manners, respectively. Moreover, fluorescence quenching, circular dichroism (CD), and molecular docking study revealed that they can arouse the changes in the secondary structure and hydrophobic micro-environment of the enzyme mainly through a hydrophobic binding. Furthermore, it was observed that oral administration of Qu (20 mg/kg) can significantly reduce postprandial blood glucose (PBG) levels in mice vs. the control group. To sum up, the above research confirmed that O. corniculate could prevent and treat postprandial hyperglycemia as a good tea drink, and the plant was an excellent source to obtain natural α-GIs.
Bianca Op den Brouw, Manuel A. Fernandez-Rojo, Tom Charlton
et al.
Snake venoms constitute a complex, rapidly evolving trait, whose composition varies between and within populations depending on geographical location, age and preys (diets). These factors have determined the adaptive evolution for predatory success and link venom heterogeneity with prey specificity. Moreover, understanding the evolutionary drivers of animal venoms has streamlined the biodiscovery of venom-derived compounds as drug candidates in biomedicine and biotechnology. The king cobra (Ophiophagus hannah; Cantor, 1836) is distributed in diverse habitats, forming independent populations, which confer differing scale markings, including between hatchlings and adults. Furthermore, king cobra venoms possess unique cytotoxic properties that are used as a defensive trait, but their toxins may also have utility as promising anticancer-agent candidates. However, the impact of geographical distribution and age on these potential venom applications has been typically neglected. In this study, we hypothesised that ontogenetic venom variation accompanies the morphological distinction between hatchlings and adults. We used non-transformed neonatal foreskin (NFF) fibroblasts to examine and compare the variability of venom cytotoxicity between adult captive breeding pairs from Malaysian and Chinese lineages, along with that of their progeny upon hatching. In parallel, we assessed the anticancer potential of these venoms in human-melanoma-patient-derived cells (MM96L). We found that in a geographical distribution and gender-independent manner, venoms from hatchlings were significantly less cytotoxic than those from adults (NFF; ~Log EC50: 0.5–0.6 vs. 0.2–0.35 mg/mL). This is consistent with neonates occupying a semifossorial habitat, while adults inhabit more above-ground habitats and are therefore more conspicuous to potential predators. We also observed that Malaysian venoms exhibited a slightly higher cytotoxicity than those from the Chinese cobra cohorts (NFF; Log EC50: 0.1–0.3 vs. 0.3–0.4 mg/mL), which is consistent with Malaysian king cobras being more strongly aposematically marked. These variations are therefore suggestive of differential anti-predator strategies associated with the occupation of distinct niches. However, all cobra venoms were similarly cytotoxic in both melanoma cells and fibroblasts, limiting their potential medical applications in their native forms.
The representation of arbitrary data in a biological system is one of the most elusive elements of biological information processing. The often logarithmic nature of information in amplitude and frequency presented to biosystems prevents simple encapsulation of the information contained in the input. Criticality Analysis (CA) is a bio-inspired method of information representation within a controlled self-organised critical system that allows scale-free representation. This is based on the concept of a reservoir of dynamic behaviour in which self-similar data will create dynamic nonlinear representations. This unique projection of data preserves the similarity of data within a multidimensional neighbourhood. The input can be reduced dimensionally to a projection output that retains the features of the overall data, yet has much simpler dynamic response. The method depends only on the rate control of chaos applied to the underlying controlled models, that allows the encoding of arbitrary data, and promises optimal encoding of data given biological relevant networks of oscillators. The CA method allows for a biologically relevant encoding mechanism of arbitrary input to biosystems, creating a suitable model for information processing in varying complexity of organisms and scale-free data representation for machine learning.
Akihiko Tanaka,1 Mai Takahashi,2 Ayako Fukui,3 Yoshifumi Arita,3 Masakazu Fujiwara,3 Naoyuki Makita,3 Naoki Tashiro3 1Division of Respiratory Medicine and Allergology, Department of Medicine, School of Medicine, Showa University, Tokyo, Japan; 2Medical, AstraZeneca K.K., Tokyo, Japan; 3Medical, AstraZeneca K.K., Osaka, JapanCorrespondence: Akihiko Tanaka, Division of Respiratory Medicine and Allergology, Department of Medicine, School of Medicine, Showa University, 1-5-8 Hatanodai Shinagawa-ku, Tokyo, 142-8666, Japan, Tel +81 3-3784-8000, Fax +81 3-3784-8517, Email tanakaa@med.showa-u.ac.jpPurpose: The oral corticosteroid (OCS)-sparing effect of several biologics (BIOs) has been shown in clinical trials. To date, no study has evaluated differences in OCS dose reduction between BIO-initiated and BIO-non-initiated patients in real-world clinical practice. We compared dose reductions in maintenance OCS between BIO-initiated and BIO-non-initiated severe asthma patients in a real-world setting.Patients and Methods: This retrospective cohort study used the data from the Diagnosis Procedure Combination database of Medical Data Vision in Japan. Severe asthma patients with continuous use of OCS were selected from December 2015 to February 2020. The primary endpoint was the proportion reduction in daily maintenance OCS dose from Week 0 to Week 24. Analyses were performed using inverse probability treatment weighting.Results: In total, 2927 patients were included (BIO-initiated: 239 patients, BIO-non-initiated: 2688 patients). Adjusted median (quartile [Q] 1–Q3) proportion reduction in daily maintenance OCS dose at Week 24 from the index date was 25.0% (0.0– 100.0%) and 0.0% (0.0– 83.3%) in the BIO-initiated and BIO-non-initiated groups, respectively (Hodges–Lehmann estimate [95% confidence interval], 0.0000% [0.0000– 0.3365%]). Respective proportions of patients in the BIO-initiated and BIO-non-initiated groups achieving dose reductions from the index date in the daily maintenance OCS dose at Week 24 were > 0% reduction, 56.6% and 44.1% (odds ratio [OR] 1.6554); ≥ 25% reduction, 50.5% and 40.6% (OR 1.4888); ≥ 50% reduction, 42.8% and 33.7% (OR 1.4714); and 100% reduction, 26.2% and 24.4% (OR 1.1005).Conclusion: Among severe asthma patients, the daily dose of maintenance OCS was reduced with BIO treatment. Although a higher percentage of patients in the BIO-initiated group had an OCS reduction of ≤ 75% than the BIO-non-initiated group, we found no clear difference in OCS reduction. Our findings will be justified by further research that incorporates a longer observation period and variables excluded from this study.Trial Registration: ClinicalTrials.gov (NCT05136547).Keywords: severe asthma, asthma exacerbation, oral corticosteroid, biologics, retrospective cohort study
Abstract Syzygium brachythyrsum is an important folk medicinal and edible plant in Yunnan ethnic minority community of China, however, little is known about the chemical and bio-active properties. The present study is aimed to identify the bioactive constituents with antioxidant and anti-inflammatory properties by an integrating approach. First, two new bergenin derivatives, brachythol A (1) and brachythol B (2), together with eleven known phenolic compounds (3-13) were isolated from bioactive fractions by phytochemical method. Among these isolated chemicals, five bergenin derivatives, along with 3 phenolics were found in Syzygium genus for the first time. Then, a further chemical investigation based on ultra-high-performance liquid chromatography-Q Exactive Orbitrap mass spectrometry resulted in a total of 107 compounds characterized in the bio-active fractions, including 50 bergenin derivatives, among which 14 bergenin derivatives and 14 phenolics were potential new natural chemicals. Most of the isolated compounds showed obvious antioxidant activities, while compounds 11, 12, and 13 had favorable performance. Eight compounds (2-5, 7, and 9-11) showed good inhibitory activity on nitric oxide (NO) production in macrophage RAW 264.7 cells. The structure-activity correlation analysis indicated that the antioxidation and anti-inflammatory activities enhanced when bergenin was esterified with gallic acid, caffeic acid or ferulic acid. This is the first report of bergenins in Syzygium genus and the richness in new bio-active bergenins and gallic acid derivatives indicated that Syzygium brachythyrsum is a promising functional and medicinal resource.
Abstract This study demonstrates a comprehensive and cost-effective one-step rapid bio-fabrication of Eucalyptus globulus leaf extract (ELE) bio-actives functionalized copper oxide nanoparticles (CuONPs); and analyze its apoptotic and toxic effects in human breast cancer (MCF-7) cells and Aspergillus flavus. The state-of-art characterization data confirmed the thermal-stability of (i) ELE-CuONPs and (ii) surface associated ELE bio-active compounds bearing characteristic functional groups (aromatic OH, polymeric OH, C O, and C O) over a range of conventional temperatures (30 °C–80 °C), and microwave (MW) heat (140 °C). The MW accelerated ELE-CuONPs (16.9 nm) treated (25−100 μg/ml) MCF-7 cells showed a significant (p
Abstract Combined steam/dry reforming of bio-oil with blast furnace slag as heat carrier for the syngas production with the H2/CO ratio of 3:1 for further methanation, was investigated. The increase of H2O addition can increase the total yield of H2 and CO, but also increase the critical temperature at which 3:1-H2/CO syngas was obtained, while the increase of CO2 addition can decrease the critical temperature, but the syngas yield was also decreased. When the steam/carbon (S/C) ratio was 3.0 and the CO2/carbon (CO2/C) ratio was 0.5, the critical temperature decreased to 804 °C, with the potential H2 yield of over 90%. Although the addition of slag and how much slag to be added had almost no any thermodynamic effect on the combined reforming of bio-oil under the condition where higher potential H2 yield can be obtained, the slag as heat carrier could supply all heat for the combined reforming process. When the added slag mass was 3.99 times bio-oil mass, the combined reforming at the S/C ratio of 3.0 and the CO2/C ratio of 0.5 can occur spontaneously for the production of 3:1-H2/CO syngas. The present study could offer important guidance toward utilization of this novel process for further methanation.