The widespread contamination of aqueous ecosystems by synthetic dyes, discharged from industries such as textiles and printing, poses a severe environmental and health risk due to their toxicity and recalcitrance. Conventional treatment methods often suffer from high operational costs and the generation of secondary pollutants. Addressing this global challenge, this study explores the valorization of agro-industrial Cucurbita pepo peel waste into low-cost, effective bioadsorbents. Embracing a circular economy model, we transformed this abundant by-product into three distinct materials: raw untreated biomass (CPP-R), and two thermally treated versions produced via pyrolysis at 200°C (CPP-200) and 400°C (CPP-400).

Comprehensive physicochemical characterization using FTIR, laser granulometry, and point of zero charge (PZC) analysis was conducted. The results confirmed that thermal treatment significantly modifies the material's surface chemistry, increasing the presence of key functional groups and altering its porous structure. The materials' efficacy in removing Methylene Blue (MB) from aqueous solutions was then assessed in a batch system, systematically optimizing parameters such as pH, contact time, and initial concentration.

Our findings reveal that thermal treatment markedly enhances adsorption capacity, with the biochar produced at 400°C (CPP-400) demonstrating superior performance. Adsorption kinetics were best described by the pseudo-second-order model, indicating that chemisorption is the dominant rate-limiting mechanism. Furthermore, equilibrium data correlated strongly with the Freundlich isotherm, suggesting multilayer adsorption onto a heterogeneous surface with energetically diverse binding sites. This research highlights a viable pathway for converting agricultural by-products into a valuable resource for environmental remediation.

The use of 3D printing in robotics enables the fabrication of lightweight, customized, and geometrically complex structures, such as lattices and compliant mechanisms. While these flexible printed components expand design possibilities, they also introduce challenges in accurately predicting dynamic behavior. Traditional rigid-body models often neglect structural deformations and vibrations, which can critically influence performance, stability, and control.

This work presents initial advances toward a computational framework for the dynamics of flexible multibody 3D-printed robotic structures. A two-link mechanism is adopted as a case study, modeled in MATLAB Simscape Multibody, where both rigid and flexible assumptions are compared. Parametric analyses are performed to investigate the influence of geometric properties, mass distribution, and structural stiffness on system dynamics, highlighting the trade-offs between lightweight design and vibration sensitivity.

Beyond conventional finite-element and multibody approaches, the framework aims to incorporate AI-driven surrogate models and reduced-order techniques to accelerate simulation, enabling real-time predictive tools for design and control. This integration opens the door to optimization studies, where the distribution of mass, topology of the printed structure, and material selection can be tailored to achieve enhanced dynamic performance.

The long-term objective is to establish reliable, computationally efficient methods for the modeling, optimization, and control of 3D-printed flexible robotic mechanisms, contributing to safer, smarter, and more efficient next-generation robotic systems.

Introduction: Salivary biomarkers are increasingly gaining trust as promising candidates for the non-invasive diagnosis of periodontal diseases and the monitoring of periodontal tissue health. This study investigated the analytical capabilities of a multichannel, plasmonic point-of-care (POC) test based on optical fiber technology for detecting and quantifying salivary macrophage inflammatory protein-1 alpha (MIP-1α), using enzyme-linked immunosorbent assay (ELISA) as a comparison.
Methods: Three plastic optical fibers (POFs) were functionalized with a self-assembled monolayer (SAM) containing MIP-1α antibodies. The POFs were placed between a spectrometer and a light source to monitor refractive index shifts at the POF-SAM interface, corresponding to the occurrence of surface plasmon resonance (SPR) during antigen–antibody interaction. A dose–response curve was generated using a range of MIP-1α concentrations. Salivary samples were collected from a cohort of fifty participants and analyzed using both the SPR-based biosensor and ELISA. Spearman’s Rank test assessed the correlation between the two techniques. Differences in MIP-1α expression were further analyzed in relation to clinical variables, including periodontal status, age, and gender (Mann–Whitney U-test).
Results: A significant correlation was observed between the measurements obtained from the biosensor and those from ELISA. The sensitivity of the SPR-POF device allowed for the detection of MIP-1α at lower concentrations than ELISA. Patients with periodontal disease exhibited significantly higher levels of MIP-1α compared to those without the disease, supporting its potential as a diagnostic biomarker.
Conclusions: The developed three-channel plasmonic POCT exhibited comparable accuracy and superior sensitivity to ELISA for detecting salivary MIP-1α. Moreover, the multichannel plasmonic configuration enhanced both measurement efficiency and the reliability of the results.

Human respiratory syncytial virus (RSV) is the predominant etiological agent responsible for lower respiratory tract infections in young children. Recurrent infections throughout an individual's lifespan can lead to significant morbidity, particularly in the elderly and in adults with underlying cardiac, pulmonary, or immunocompromised conditions. The trends in hospitalization rates and risk factors for severe bronchiolitis and pneumonia in children younger than two years old are significantly influenced by RSV. Consequently, it is imperative to develop technologies that can sanitize environments from this pathogen while being compatible with human presence. Structure Resonant Energy Transfer (SRET) is the scientific principle underlying a sanitation technology that has demonstrated efficacy against several enveloped viruses, including SARS-CoV-2 and Influenza A viruses (H1N1, H5N1, and H1N2). SRET employs specific frequencies of electromagnetic waves to effectively disrupt the structural integrity of viral envelopes through dipole coupling. This disruption leads to the inactivation of the virus, rendering it non-infectious. The objective of this study is to analyse the effect of a specific SRET non-thermal sanitation method on RSV. The sanitation test was conducted in aerosol form within a BSL-3 laboratory, exploring the X band frequency range from 8 to 16 GHz. An optimal sub-band was identified, giving an inactivation efficiency up to 99.5%, and an optimal protocol was subsequently implemented. In conclusion, it has been demonstrated that the microwave non-thermal sanitation method is effective against RSV. The sanitation process yielded significant results, confirming its potential as a viable approach for environmental decontamination.

Polyhydroxybutyrate (PHB) is a biodegradable polyester that has drawn increasing attention as a sustainable alternative to conventional plastics. Although PHB is widely recognized for its biodegradability, its persistence in certain environments has raised concerns about its actual environmental impact. In particular, the role of plasticizers commonly added to bioplastic formulations remains poorly understood regarding biodegradation.

In this study, we examined the effect of phthalate esters and glycols on PHB degradation using Ralstonia sp. C1. The bacterium was cultivated in LB medium at 30°C for 18 hours, washed to remove residual nutrients, and transferred to a defined medium containing 0.5% (w/v) PHB. Plasticizers were applied at concentrations ranging from 50 to 2000 μg/L.

Cultures were incubated aerobically at 30°C for 96 hours with shaking, and samples were collected every 24 hours. Residual PHB was measured using HPLC.

Under all tested conditions, over 50 percent of the PHB was degraded within the first 24 hours, and more than 98 percent degradation was observed by the end of the incubation period. The degradation rates were comparable regardless of the presence or absence of additives.

Additionally, no evidence was found that Ralstonia sp. C1 metabolized the additives. These results suggest that phthalate and glycol plasticizers do not inhibit the microbial degradation of PHB or alter its availability to degrading bacteria.

This study provides the first clear evidence that environmental isolates can effectively degrade PHB containing such additives. The findings offer valuable insights into the environmental behavior of bioplastics and support the continued development of additive-containing biodegradable materials for commercial use.

Biofilms are one of the most resilient and adaptive strategies that microorganisms use to survive under difficult conditions. Their ability to form protective matrices makes them a critical threat in healthcare, as they often cause persistent infections. While established techniques exist to characterize biofilms, they face several challenges, primarily due to labor intensity, time consumption, complex sample preparation, and the high cost of imaging equipment. In developing countries, costs are particularly high due to limited detection infrastructure, highlighting the need for a complementary characterization technique that enables standardized, cheap, and rapid characterization of biofilm composition and metabolic activity.

In this study, we developed and optimized a short-term potentiometric method to investigate early biofilm formation by measuring in real-time the charge and discharge of bacterial membrane potentials. When grown on a polarized surface, the bacterial attachment generates microscale currents that can be correlated to cell concentration, nutrients, and environmental conditions, among other factors. By analyzing the bacterial current output, we were able to detect early biofilm formation within 4–6 hours, a significant improvement over conventional methods, which typically require 18–24 hours and at lower costs (~1 USD per sample). The results obtained were validated against a control experiment (open-circuit potentiometry) with established biofilm characterization methods to verify the non-destructive capability of the developed technique.

The proposed technique can be effectively used to detect early biofilms without the need for redox mediators, thereby extending its application to the bioelectrochemical analysis of microorganisms of clinical importance, which are often weak electricigens.

The exploitation of lignocellulosic biomass, driven by cellulolytic enzymes, offers a sustainable route for converting plant-based waste into biofuels, biochemicals, and other value-added products.

BsEndo9 is a novel glycoside hydrolase family 9 (GH9) endoglucanase identified in Bacillus safensis ATHUBA63, a soil-derived strain from the Attica region of Greece. The gene encoding BsEndo9 was amplified via PCR and heterologously expressed in E. coli BL21 (DE3) competent cells. The recombinant enzyme was purified using His-Tag-assisted chromatography and its molecular weight (69 kDa) was confirmed via SDS-PAGE. BsEndo9 exhibited optimal activity at 60 °C and pH 6.0, retaining over 85% of activity after 48 hours within the pH range 5.0–8.0. Thermal inactivation studies revealed a half-life of 74.53 min at 60 °C and an inactivation energy (E_(a)d) of 198.51 kJ/mol. Additional thermodynamic parameters (ΔH*, ΔS*, ΔG*) were also determined. Enzyme activity was enhanced by Mg²⁺ and stable in the presence of several metal ions (K⁺, Na⁺, Fe²⁺, Ca²⁺, Ba²⁺, Co²⁺, Mn²⁺, Ni²⁺, Zn²⁺), as well as EDTA and SDS, though inhibited by 5 mM Fe³⁺ and Cu²⁺. Substrate specificity was examined against amorphous cellulose substrates: carboxymethyl cellulose (CMC), β-glucan (barley) and phosphoric acid-swollen cellulose (PASC). Kinetic parameters (K_m and V_max) were determined for carboxymethyl cellulose (CMC). Structural prediction using AlphaFold3 (beta) indicated a modular structure with a GH9 catalytic domain and a CBM3 module, consistent with efficient cellulases.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by severe cognitive decline, for which current therapies are limited in efficacy and have significant adverse effects. In this context, natural compounds with neuroprotective potential are attracting increasing interest. Mansorina (MA), a coumarin derivative extracted from Mansoria gagei, is recognized for its antioxidant and anti-inflammatory properties. The aim of this study was to evaluate the effects of mansorina on cognitive function, using Danio rerio (zebra fish) as a preclinical model for AD. Amnesia was induced by exposing fish to okadaic acid (OKA, 10 nM) for 4 days. Animals were divided into six groups (n = 10/group): control (DMSO), OKA, galantamine (GAL, 1 mg/L), and OKA co-treated with MA at 1, 3, or 6 μg/L. MA was administered for 7 days, every 3 days, during water changes. Fish behavior was monitored using ANY-maze® v6.3 software (Stoelting Co., USA) and a Logitech HD Webcam C922 camera, for automatic analysis of locomotor and exploratory parameters in the Y-maze (spatial memory) and NOR (novel object recognition) tests. Statistical analysis was performed using ANOVA with Tukey’s post hoc test (GraphPad Prism 9, p < 0.05). OKA significantly impaired spatial memory and object recognition (p < 0.0001), effects reversed by GAL. MA at 3 and 6 μg/L improved cognitive performance (p < 0.001–0.00001) and increased exploration of the novel arm and object. MA also enhanced locomotor activity, suggesting a neuroactive effect.

The incidence of skin cancer is rising worldwide, with non-melanoma skin cancer ranked as the fifth most prevalent cancer in 2022, presenting a significant burden on public health. Photothermal therapy has emerged as a promising treatment that employs near-infrared light to selectively destroy cancerous tissue. While the integration of metallic nanoparticles has demonstrated enhanced thermal performance, concerns over their low tissue clearance rate and long-term toxicity have hindered their clinical translation. Polydopamine (PDA) nanoparticles have recently garnered attention as a promising alternative due to their biodegradability and biocompatibility. This study presents a finite element-based multiscale modeling framework to investigate PDA nanoparticle-enhanced photothermal therapy for skin cancer treatment. Numerically characterized optical properties of PDA nanoparticles were incorporated into a three-dimensional, multi-layered skin tissue model that includes a region of squamous cell carcinoma. Heat transfer was simulated by coupling the Pennes’ bioheat transfer equation with the Beer–Lambert law to compute the spatiotemporal temperature distribution during laser irradiation. Model validation against experimental temperature data from PDA suspensions at various concentrations showed strong agreement. Parametric studies explored the effect of PDA nanoparticle size, concentration, laser intensity, and beam profile on temperature profiles. The results demonstrated that PDA nanoparticles increased tumor temperature compared to treatments without nanoparticles. The temperature increased by 6˚C when 1000 μg/mL was irradiated for 10 minutes with a 1.4 W/cm² laser intensity. These findings help to deepen our understanding of the thermal behavior of PDA nanoparticles in biological tissues and support their potential as a biocompatible alternative for enhanced photothermal therapy.

Climate-induced heat stress poses a critical threat to cotton (Gossypium spp.) productivity, especially during the flowering and boll development stages. Elevated temperatures exceeding 35°C disrupt key physiological processes, impair photosynthesis, and alter hormonal homeostasis, ultimately triggering premature boll abscission. Central to this process is the formation of the abscission zone (AZ), driven by the upregulation of ethylene and abscisic acid (ABA) biosynthetic genes, which antagonize auxin transport and compromise cell wall integrity. This disruption results in reduced boll retention and significant yield losses under heat-stressed conditions. This review synthesizes current advances in understanding the molecular and physiological mechanisms underlying heat-induced boll shedding. We highlight the roles of heat shock proteins (HSPs), stress-responsive transcription factors, reactive oxygen species (ROS) signaling, and hormone crosstalk in AZ regulation. Furthermore, we explore integrative breeding approaches combining quantitative trait loci (QTL) mapping, transcriptomics, and CRISPR/Cas9-based gene editing to enhance thermotolerance in cotton. Agronomic interventions—including exogenous application of plant growth regulators and precision irrigation techniques—are also examined as complementary strategies for mitigating heat stress effects. Emerging technologies, such as nanotechnology-enabled delivery systems for stress modulators, offer promising avenues for targeted intervention. Finally, we propose a research framework centered on AZ-specific gene expression profiling, gene–hormone interaction networks, and translational breeding pipelines. These multidisciplinary insights form a robust foundation for the development of climate-resilient cotton cultivars suited to increasingly extreme agro-climatic conditions.