Centre Hospitalo-Universitaire Bab El Oued

Cucurbita maxima (pumpkin) leaves have been traditionally used in folk medicine for the treatment of inflammation, fever, and oxidative stress-related disorders. However, scientific validation of these claims remains limited. This study aimed to evaluate the anti-inflammatory, antioxidant, and protective effects of C. maxima leaf aqueous extract and to elucidate its phytochemical composition and molecular mechanisms of action. The phytochemical profile of the aqueous extract was determined using UPLC-ESI-MS/MS analysis. In vivo anti-inflammatory activity was assessed in a benzylthiouracil-induced inflammation model by measuring white blood cell (WBC) counts, C-reactive protein (CRP) levels, and histopathological changes in liver and kidney tissues. In vitro anti-inflammatory potential was evaluated through the protein denaturation inhibition assay, using diclofenac as a reference. Pharmacokinetic and toxicity properties of major compounds were predicted using ADMET tools, while molecular docking studies were performed to evaluate interactions with COX-1 and COX-2 enzymes. UPLC-ESI-MS/MS analysis revealed a complex mixture of polyphenols, with caffeic acid (56.04%), rutin (9.25%), ferulic acid (8.79%), and myricetin-3-rhamnose (8.62%) as the main constituents. The extract significantly reduced inflammation by normalizing WBC counts (from 7.2 to 4.5×109/L), lowering CRP levels (from 630 to 220mg/L), and protecting liver and kidney tissues. The extract also inhibited protein denaturation in vitro (IC50=2.976mg/mL) compared to diclofenac (IC50=0.718mg/mL). Molecular docking revealed that major flavonoids exhibited strong binding affinities toward COX-1 and COX-2, often surpassing diclofenac, supported by stable hydrogen bonding and hydrophobic interactions. ADMET and toxicity predictions indicated good intestinal absorption for several major compounds, absence of predicted hepatotoxicity or skin sensitization, and generally low acute toxicity, with high predicted LD50 values and no mutagenic risk for most constituents. These findings support the traditional use of C. maxima leaves in folk medicine for the management of inflammation-related conditions, fever, and associated oxidative stress. Further isolation of the key active constituents and clinical evaluation are recommended to confirm their therapeutic efficacy.

Process mining analyzes business processes using event logs. Existing tools generate models to facilitate this task and improve the original business process, but the results are often unsatisfactory due to the complexity of the obtained models. Among the challenges faced in this context, we identify the misalignment with specific business requirements, preventing managers from accessing key data and making effective decisions. In this paper, we propose a requirement-driven approach centered on meta-modeling, which can help the development of process mining tools specially tailored to organizational needs. Thus, we introduce a requirement-driven method to address the critical challenge of model misalignment with required information. The method employs Model-Driven Engineering to simplify how process mining results are formulated, analyzed, and interpreted. The proposed method is iterative and involves several steps. First, a service manager defines a specific business question. Second, service managers and developers collaboratively establish a meta-model representing the target data. Third, developers extract relevant data using appropriate analysis techniques and visualize it. Finally, service managers and developers jointly interpret these visualizations to inform strategic decisions. This requirement-driven methodology empowers developers to concentrate on relevant information. Unlike general-purpose frameworks (e.g., ProM, Disco), this method emphasizes specificity, iterative refinement, and close stakeholder collaboration. By reducing cognitive overload through focused modeling and filtering of irrelevant data, organizations adopting this approach can achieve faster response times to business questions and develop specialized in-house analytical tools. This requirement-driven methodology, therefore, improves decision-making capabilities within process mining and across related analytical domains. We illustrate our methodology through a real business process taken from the literature owned by the VOLVO group. We use several examples of process mining to illustrate the benefits of the proposed methodology compared to existing tools which are unable to provide the required information. • A requirement-driven meta-model method for standardized process-mining assessment. • An iterative approach for low-cost development of tailored in-house tools. • Improves decisions through focused data extraction and need-aligned analysis.

The Sandfish lizard (Scincus scincus) is well adapted to the harsh desert environment of the Algerian Sahara. This study investigated the effects of season and sex on the morphometric measurements and selected blood biochemical parameters of the Sandfish lizard, including 29 females and 31 males from the El Oued region in the southeastern Algerian Sahara. Morphometric and biochemical parameters were assessed across winter, spring, and summer (2024). The results indicated that males had significantly larger total length (TBL), snout-vent length (SVL), vent-to-tail length (TL), trunk length (TRL), forelimb length (FL), and hindlimb length (HL) compared to females (P < 0.05). However, no significant sex-related differences were found in the blood biochemical parameters. Significant seasonal variations (P < 0.05) were observed in body weight (Wt), hindlimb length (HL), forelimb length (FL), head width (HW), mouth length (ML), and body width (BW). Additionally, highly significant seasonal variations (P < 0.005) were found in all blood parameters except for calcium. These findings suggest that while morphometric characteristics vary significantly by sex, certain physiological parameters are more influenced by seasonal changes, highlighting the Sandfish lizard's adaptability to its environment.