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Sci

Sci is an international, peer-reviewed, open access journal on all research fields published quarterly online by MDPI.

All Articles (433)

Personalized Prediction of the Time to Loss of Response to Azacytidine in MDS Patients

  • Sotirios Vantarakis,
  • Dimitris Koparanis and
  • Theodoros Spyropoulos
  • + 3 authors

Azacytidine is the only approved treatment for patients with higher-risk myelodysplastic syndromes (MDS); yet less than half of the patients will achieve a response, whereas the duration of response is highly heterogeneous and there are no predictors for response duration. The aim of this study is to estimate the patient’s time to loss of response (LoR) to azacytidine based on clinical measurements during treatment. To this end, a personalized prediction framework is proposed that estimates the LoR of a new patient using a patient similarity-based approach. Namely, the new patient’s clinical data—represented as a multivariate time series—are compared to a reference set of patients. The comparison uses distance metrics that quantify how similar two patients’ time series are, assuming patients with similar trajectories tend to have similar LoR. Then, the LoR of the new patient is predicted by averaging the outcomes of the most similar reference patients. The pipeline includes a data normalization strategy that centers each feature on its baseline value and scales it to highlight relative changes and distance metrics to quantify similarity. Both real-world and simulated data were utilized to evaluate the proposed methodology, employing the leave-one-out validation and the Mean Absolute Percentage Error (MAPE) to assess accuracy. The estimated MAPE was found to be 30.52% and 11.82% in the real-world and simulated dataset, respectively. The best and most robust predictions were achieved using the Euclidean distance metric and setting the number of most similar patients around three to five. This study proposes a personalized predictive approach for the LoR to azacitidine in the MDS clinical setting, demonstrating potential for a serviceable prediction of LoR and forming the foundation for further research.

3 November 2025

The methodological framework of the study in six sequential steps, namely, (1) creation of the reference pool of patients, (2) imputation of the dataset, (3) introduction of a new patient, (4) employ normalization strategy, (5) compute similarity between patients, and (6) estimate the LoR time of the new patient.

The increasing demand for industrial resource optimization has driven the creation of integrated methodologies for the technical assessment of complex operations such as gas oil hydrocracking. This study examines the technical performance of a mass and energy-integrated gas oil hydrocracking process using the Extended Water–Energy–Product (E-WEP) methodology, which enables the quantification of 12 key indicators related to water, energy, and raw material usage. The research addresses the challenge of high demineralized water consumption in conventional hydrocracking processes. The findings show a production yield of 95.77% and a recycled hydrogen reuse rate of 67.99%, expressed as the Index of Reused Unconverted Material (IRUM). In terms of water use, fresh water demand decreased to 26.99 m3/h and wastewater discharge to 21 m3/h, although 77.79% of the total water processed is released as effluent, corresponding to the Wastewater Production Ratio (WPR). From the energy standpoint, total energy consumption increased to 2966.57 MMBTU/h, primarily due to the use of additional electrical equipment for mass integration. The Total Cost of Energy (TCE) reached 3,563,840.10 USD/day, with electricity (1630.82 kWh/t) as the dominant source, negatively influencing the process’s economic efficiency. Despite this energy drawback, the evaluated configuration achieves the most sustainable water use compared to conventional and integrated PVC production schemes, underscoring the importance of adopting holistic evaluations that jointly address technical efficiency, environmental impact, and economic feasibility.

3 November 2025

Process flow diagram of the reaction stage of the mass and energy-integrated gas oil hydrocracking process.

Antimicrobial resistance (AMR) is a major public health threat that urgently requires alternative strategies to address this challenge. Klebsiella spp. are among the most important clinical pathogens and a leading cause of opportunistic nosocomial infections, with high morbidity and mortality associated with strains resistant to last-line antimicrobials such as carbapenems. Bacteriophages are considered a promising therapeutic option for treating infections caused by Klebsiella strains. Hence, the aim of this work was to isolate and characterize a phage capable of infecting carbapenem-resistant Klebsiella strains. The phage KpCCP1 was isolated using the double layer agar method (DLA), from the influent of a wastewater treatment plant, which was characterized through phenotypic and genomic analyses. Morphological characteristics were determined using TEM, and its host range was evaluated against a collection of 133 Klebsiella strains. Its whole genome was sequenced using the Illumina NovaSeq X Plus platform and then assembled and annotated. VICTOR was used for phylogenetic analysis of the isolated phage, and VIRIDIC to compare its genome with those of its closest relatives. KpCCP1 is a tailed dsDNA lytic phage with a genome size of 177,276 bp and a GC content of 41.82%. It encodes 292 ORFs, including two tRNA genes. Phage KpCCP1 is a member of the Slopekvirus genus in the Straboviridae family. It is capable of infecting 22 carbapenem-resistant Klebsiella strains, including K. pneumoniae and K. michiganensis. Notably, it does not contain virulence or antibiotic resistance genes and harbors putative anti-CRISPR genes, therefore representing a promising candidate for phage therapy against clinically critical Klebsiella strains.

2 November 2025

Transmission electron micrograph of phage KpCCP1 (A) and lysis plaques of phage KpCCP1 on the lawn of K. pneumoniae UCO-545 (B).

Citrus fruit processing, mainly for fresh juice production in the food industry, generates significant amounts of residues and by-products enriched with bioactive components. Peels are the primary waste fraction of citrus fruits, along with discarded pulp and seeds. This study aimed to identify the most fast and sustainable extraction process for flavonoids on a laboratory scale by varying the solvent and extraction methodology, and comparing the yields in order to evaluate their influence on total and individual flavonoid content. A chromatographic analysis was also performed using ultrahigh-performance liquid chromatography (UHPLC) with a 10 min run time. Our focus was on selecting the most user-friendly and cost-effective methodology. Ultrasound- and microwave-assisted extraction equipment were used with green solvents (water and ethanol) and compared for their efficiency in recovering flavonoid compounds from a mixture of peel and pulp. For this study, two widely cultivated Mediterranean citrus varieties were selected: ‘Marsh’ seedless grapefruits (Citrus paradisi Macf.) and ‘Comun’ mandarins (C. deliciosa Ten.). Lab-scale extraction results showed that ultrasound-assisted extraction with a simple ultrasonic bath, using an ethanol–water mixture provided the highest total flavonoid recovery and improved the extraction of key flavanones such as hesperidin, narirutin, and naringin. All ethanol–water mixtures tested (1:1, 7:3, and 3:7) yielded higher flavonoid levels in grapefruit (approximately 2500 mg/100 g DW) and mandarin (approximately 1200 mg/100 g DW) wastes compared with water or ethanol alone. This method offers a scalable and green strategy for valorizing citrus residues.

2 November 2025

Overall total flavonoid content (mg/100 g DW) from grapefruit peel and waste under different extraction procedures *: (1) US: ultrasound cleaner; (2) UAE: ultrasound-assisted extraction system; (3) DM: domestic microwave oven; (4) MAE: microwave-assisted extraction. * Data are expressed as average 3 replicates (grapefruit peel: dried peel; grapefruit waste: dried mixture of peel and discarded pulp); different letters in the same sample-type (uppercase for peels and lowercase for wastes) indicate significantly different values among extraction procedures.

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