Removal of hexavalent chromium has been a focus for studies in recent years due to its prevalence and toxicity. The use of magnetotactic bacteria in treating chromium-containing waters has been gaining interest due to its advantage of being able to be separated from the effluent, among other benefits of biological methods. Magnetospirillum gryphiswaldense (MSR-1) has already been proven to reduce Cr(VI) to less toxic Cr(III), but its resistance to the metal has not been studied. This study aims to elucidate the Cr(VI) resistance of MSR-1 by assessing its resistance limits and evaluating its efflux pump capabilities through heterologous expression in E. coli BL21. The minimum inhibitory concentration (MIC) of MSR-1 was found to be 3 mg Cr(VI)/L, although its magnetosome synthesis was already hindered at 2 mg Cr(VI)/L. MSR-1 was also found to be capable of surviving 14 cycles of 12-hour exposures to 10 mg/L of chromium without a significant impact on its average Cr(VI) reduction capacities, but the growth of magnetosome-deficient strains was observed. The engineered bacteria exhibited higher resistance and lower chromium uptake compared to the control, up to a concentration of 50 mg/L Cr(VI). The engineered strain recorded an 83.67% retention of intracellular chromium, indicating better efflux capabilities compared to the control strain’s 97.89% retention rate. However, increasing the culture concentration and duration led to a decrease in efflux capacities. Molybdate, vanadate, and NADPH inhibited the efflux of the engineered strain by 14.32%, 15.28%, and 23.82%, respectively. Conversely, the addition of valinomycin improved efflux by 34.26%

Near-infrared (NIR) fluorescent materials have attracted considerable interest in bioimaging and biosensing, as physiological components such as water and hemoglobin exhibit weak absorption and low intrinsic autofluorescence in this region. The clinically approved dye indocyanine green (ICG; excitation/emission 789/813 nm) holds valuable potential in photothermal and photoacoustic imaging owing to its high absorption cross-section and environment-responsive optical properties, despite its low quantum yield and short lifetime. To enhance its photostability and control aggregation, ICG has been paired with NIR gold nanostructures. However, most reported ICG–gold assemblies rely on cytotoxic surfactants (e.g., CTAB) and strong reducing agents (e.g., NaBH₄), thereby limiting in vivo applications. Consequently, this study synthesized NIR-resonant gold nanotriangles (AuNTs) via a thiosulfate-mediated, surfactant-free method, stabilized using biocompatible zwitterionic amino acid L-cysteine, and added a silica shell, enabling controlled ICG loading while preventing fluorescence quenching from direct metal contact. The resulting AuNT@SiO₂ nanostructures exhibited plasmon resonance above 800 nm, overlapping with ICG absorption. ICG aggregation, emission, and lifetime were assessed by UV-Vis, steady-state fluorescence, and FLIM, respectively, offering insight into nanostructure–ICG photophysical interaction. Metal-enhanced fluorescence (MEF) of ICG remained limited by the aggregation of the dye in aqueous solution, yielding intensity ratios of only 0.865 on AuNP-Cys@SiO₂ and a negligible value on AuNP-CTAB@SiO₂. In contrast, pairing the fully and partially biocompatible silica-coated AuNPs with the visible-region dye FITC gave maximum enhancement factors of 1.127 ± 0.047 and 1.61 ± 0.16, respectively. These results indicate potential for MEF-based biosensing but warrant further study of ICG immobilization and amino acid–silica growth compatibility.

As the effects of climate change are felt, the country needs to transition to sustainable energy sources. With this goal, the experiment studied the potential of buffalo manure and market fruit and vegetable wastes in biogas production through anaerobic co-digestion, as the combination of these substrates has yet to be explored, and the Philippines is home to millions of buffalo. The study examined how moisture content, the initial pH of the substrate mixture, and buffalo manure content affect the methane production of the different proportions of feedstocks. The results of the experiments showed that the methane generated after 15 days was highest at 64.5 ml/gVS in the mixture of 50% buffalo manure, 94% initial moisture content, and initial pH of 7. A statistical model relating the three parameter (buffalo manure content, initial moisture content and initial pH of the substrate mixture) to methane yield (ml/gVS) was generated. It can be used to estimate the latter given the values of the the said three process parameters. The hydrolysis rate constant, k, values of samples with 25, 50, and 75% buffalo manure content are 0.0440, 0.0297, and 0.0178 day-1, respectively. The ammonium level of all mixtures exceeded 600 mg/l in specific periods which indicates that ammonium inhibits the methanogenesis process, which may have inhibited methane generation. The data gathered from this research can be used as basis for designing larger scale methane production from buffalo manure and fruits and vegetables wastes. The results of this study can be used for encouraging the use of anaerobic co-digestion of the waste to produce methane as clean fuel and as strategy for decarbonization.

As modern vehicles evolve into highly connected and autonomous systems, the need for robust cybersecurity measures, such as intrusion detection systems (IDS), becomes increasingly critical. Traditional IDS approaches, however, face significant challenges in preserving data privacy due to centralized collection and processing, which expose sensitive information to potential breaches. This study addresses these challenges by presenting a novel privacy-preserving vehicle IDS that combines federated learning (FL) and homomorphic encryption (HE). Specifically, the system detects denial-of-service (DoS), fuzzy, and impersonation attacks in vehicular networks to strengthen cybersecurity protections against common vehicular threats. FL enables collaborative model training across distributed vehicles without sharing raw data, ensuring data privacy. HE facilitates
secure computations on encrypted data, enhancing confidentiality during processing. This study leverages the CKKS HE scheme to enable efficient encrypted aggregation of model updates, demonstrating the practical feasibility of deploying privacy-preserving collaborative learning solutions in real-world vehicular cybersecurity systems. However, the system is not intended for real-time detection. Due to the computational and communication overhead of FL and HE, this design is best suited for offline or near-real-time analysis where data privacy and collaborative diagnostics are prioritized.

This study evaluates the Allergen Segregation Wheel (ASW) as a decision-support framework for improving production and operational efficiency in a multi-product food manufacturing environment. Facilities handling multiple allergen categories often experience frequent changeovers, extended cleaning times, and complex production sequencing, leading to increased downtime, higher costs, and reduced throughput. The ASW integrates allergen-based sequencing into production planning while maintaining effective allergen control.
A simulation-based, quasi-experimental design using six months of historical production data from a chocolate manufacturing facility was employed. Performance before and after ASW implementation was assessed using metrics for allergen-related changeover downtime, equipment availability, production output, and operational efficiency. Statistical significance was evaluated using the Wilcoxon Signed-Rank Test.
Results indicate that ASW implementation significantly reduced changeover downtime, improved equipment availability, and increased production output, while also enhancing operational efficiency without compromising allergen control practices.
The study concludes that the ASW is an effective production planning tool for improving efficiency and supporting cost-effective operations in multi-product food manufacturing environments.