Search Results (19,915)

Background: Di(2-ethylhexyl) phthalate (DEHP) is a high-production-volume plasticizer and ubiquitous environ-mental contaminant with established endocrine-disrupting potential. While zebrafish transcriptomic studies have typically used high concentrations and long exposure windows, less is known about genome-wide responses during late embryogenesis/early larval maturation under environmentally relevant exposures. Here we profiled whole-organism transcriptomic responses to a short DEHP exposure during a developmentally sensitive transition (96–120) hours post-fertilization, hpf) and interpreted responses using differential expression, enrichment analyses, and endocrine-focused protein–protein interaction (PPI) network modeling. Methods: Wild-type AB zebrafish lar-vae (96 hpf) were exposed to DEHP at [10⁻⁹ M] or solvent control for 24 h. Larvae were pooled per replicate (25 lar-vae/pool) and processed for poly(A)-selected RNA-seq. Reads were quality-controlled, aligned to the Danio rerio reference genome, and quantified at gene- level. Differential expression was performed using DESeq2. Functional enrichment used KEGG over-representation analysis (ORA) and gene set enrichment analysis (GSEA). Zebrafish genes were mapped to human orthologs for GO/KEGG and STRING-based endocrine subnetworks, which were visualized and interrogated using STRINGdb and visNetwork. Results: Low-dose, short-term exposure does not produce large gene-level effects but induces coordinated, pathway-level transcriptional remodeling. KEGG ORA showed significant enrichment of MAPK signaling and regulation of actin cytoskeleton with additional enrichment of axon guidance and neuroactive ligand–receptor interaction. GSEA detected coordinated downregulation of KEGG neurodegeneration collections with negative normalized enrichment scores reflecting shared gene sets re-lated to mitochondrial function, proteostasis, cytoskeletal organization, and stress-response pathways. Endo-crine-focused STRING subnetworks indicated consistent downregulation of CYP19A1 within estrogen metabo-lism/biosynthesis modules and downregulation of upstream androgen biosynthetic enzymes HSD3B2 and CYP17A1, alongside upregulation of HSD17B3 and proteostasis-associated factors including DNAJA1. Endocrine network to-pology highlighted regulatory and cofactor nodes affecting receptor-linked transcription, consistent with indirect endocrine modulation rather than large receptor-transcript changes. Conclusions: In summary, this study demon-strates that exposure to low-dose DEHP during a critical period of zebrafish embryonic development is associated with modest but coordinated transcriptomic changes across multiple biological pathways. Pathway enrichment and network-based analyses highlight estrogen- and androgen-associated processes, along with broader signaling, met-abolic, and structural pathways, as transcriptionally responsive during this window. Importantly, these findings reflect molecular-level associations rather than direct evidence of functional or physiological endocrine disruption. Instead, they identify candidate pathways and regulatory networks that may be sensitive to low-level environmen-tal exposure and warrant further investigation. Collectively, this work underscores the value of systems-level tran-scriptomic approaches for detecting subtle, pathway-wide responses to environmentally relevant exposures during development. Full article

Background: Companion participation in medical consultations can influence the well-being of older adults with chronic illness, yet the mechanisms underlying this effect remain unclear. This study aimed (1) to examine how companion-reported value co-creation (coproduction and value-in-use) relates to patient-reported multidimensional well-being (psychological, existential, social, and physical), and (2) to test whether these associations vary according to patient and companion characteristics. Methods: A cross-sectional dyadic study of 907 patient-companion pairs (N = 1814) was conducted in Spain prior to the COVID-19 pandemic. Companions completed the adapted Spanish Value Co-creation Scale, while patients completed the McGill Quality of Life Questionnaire-Revised (MQOL-R). Construct validity was confirmed via confirmatory factor analysis, and structural equation modeling tested hypothesized relationships using robust maximum-likelihood estimation. Results: The model showed good fit (χ²/df = 2.41, CFI = 0.96, RMSEA = 0.041). Companion coproduction was positively associated with patient psychological (β = 0.32), social (β = 0.27), and existential well-being (β = 0.29), but not physical well-being. Value-in-use showed small negative associations (β ≈ −0.10 to −0.15), which may reflect relational strain arising when companions’ involvement is excessive or mismatched with patient needs. Coproduction effects were stronger among patients aged ≤75 years. Conclusions: Companion coproduction enhances key dimensions of patient well-being, highlighting its role as a relational resource in clinical practice. Conversely, higher companion value-in-use may signal potential relational strain. These pre-pandemic findings provide a baseline for post-COVID chronic care models that aim to actively involve companions and tailor support according to patient age. Full article

The current transition from conventional blast furnaces to electronic arc furnaces is a viable path to reducing CO₂ emissions during steel production. However, this transition of technologies changes the requirements for possible scrap that may be used as a secondary raw material during EAF steel production. Copper is especially challenging, as it remains in the melt, reducing the mechanical properties of the produced crude steel while being lost to any secondary use. Currently, the two main routes to reduce the copper content are X-Ray Fluorescence sorting and manual sorting. We propose a third approach by using computer vision and machine learning methods to detect copper-containing particles in a post-shredder scrap fraction on low-cost and low-powered hardware. Furthermore, this proposed method is robust to environmental factors, such as heavily corroded particles caused by prolonged storage without proper weather protection. This method can effectively reduce the need for expensive XRF equipment or manual sorting. The developed sorting pipeline was examined in an industrial setting through sorting trials and achieved 99.9 wt.% purity in the produced iron fraction at throughputs of over 3 t/h. Full article

Background and Objectives: Soft tissue regeneration in oral surgery has undergone remarkable progress in the last decade, supported by the development of innovative laser technologies, advanced biomaterials, platelet-rich plasma (PRP), mesenchymal stem cells (MSCs), and three-dimensional (3D) printing. Lasers are increasingly used not only for incision and coagulation but also for photobiomodulation, promoting cellular proliferation, angiogenesis, and tissue healing. The purpose of this review is to analyze the current advances in soft tissue regeneration, with a particular focus on the clinical use of lasers and their integration with other regenerative strategies. In parallel, hard tissue regeneration has evolved through the synergistic use of bioactive scaffolds, recombinant human growth factors (rhBMP-2, rhPDGF-BB), MSCs, and 3D-printed constructs. These innovations have enhanced alveolar bone regeneration, implant osseointegration, and periodontal tissue repair, offering predictable clinical outcomes. Materials and Methods: A review of the literature published between 2015 and 2025 was conducted through PubMed, Scopus, Web of Science, Embase, and Google Scholar. Clinical and preclinical studies on the use of CO₂, Nd:YAG, Er:YAG, diode, and 445 nm lasers, biomaterials, PRP, MSCs, growth factors, and 3D-printed scaffolds were included. Results: Laser applications demonstrated significant benefits in epithelialization, biostimulation, and reduction in postoperative discomfort in soft tissues. For hard tissues, the combined use of MSCs, bioactive scaffolds, and growth factors promoted osteogenic differentiation, bone volume preservation, and improved mechanical stability. Photobiomodulation enhanced osteoblastic activity and accelerated bone remodeling, while 3D-printed scaffolds provided personalized architecture for optimal integration. Conclusions: Regenerative approaches integrating lasers, biomaterials, PRP, MSCs, growth factors, and 3D printing represent safe, minimally invasive, and effective strategies for the regeneration of both soft and hard oral tissues. These multidisciplinary techniques improve healing quality, functional recovery, and esthetic outcomes, reflecting the growing trend toward precision and technology-driven regenerative oral surgery. Full article

The policymakers of Bangladesh have been mapping the energy mix to shift its high dependency on fossil fuels to sustainable energy; wind energy is addressed as a highly potential option. A feasible site selection process is essential for wind power plant establishment; thus, this study aims to identify potential areas for the sustainable development of large-scale wind plants by considering socio-economic, safety and environmental factors. In this study, two techniques of multi-criteria analysis (MCA), analytical hierarchy process (AHP) and ratio scale weighting (RSW), were incorporated with geographic information system (GIS) to select the optimal area in Bangladesh. This study considers fifteen sub-criteria under four main criteria, namely, socio-economy, geology, ecology, and climatology. AHP and RSW assign suitable weights to the sub-criteria based on their significant impact on the plant. GIS analyzes spatial data layers and produces suitability maps with the following categories: 5—most suitable, 4—suitable, 3—moderately suitable, 2—unsuitable, 1—completely unsuitable, and 0—excluded area. The final suitability map was generated using suitability maps of AHP and RSW. Finally, a combination of the final suitability map and the wind speed suitability map provide a total suitable area of 1595.8293 km². This could produce 2.96 GW power with 1418 wind turbines and be able to reduce 4,992,346.42 tons of CO₂ emissions annually (calculated using a reference turbine). The study was uniquely carried out at a 150 m hub height, and integration of AHP and RSW for weight cross-validation was performed for the first time in large-scale wind plant siting in Bangladesh. The findings of the study can be helpful for decision-makers in developing large-scale wind power plants. Full article

With global warming, high-temperature stress has become a primary abiotic factor limiting maize yield and quality. Exposure to heat stress induces sunscald on maize leaves, which severely impairs photosynthesis and ultimately leads to yield reduction. In this study, we used the heat-tolerant inbred line Zheng58 and the heat-sensitive inbred line HSBN, both of which are cultivated maize (Zea mays L. subsp. mays) inbred lines, as parents to construct F₂ and F_2:3 populations consisting of 257 lines. Phenotyping for sunscald at the flowering stage was performed across three field environments. The F₂ population was genotyped using the Maize 10K SNP array to construct a genetic map containing 1728 single nucleotide polymorphism (SNP) markers. The map spanned 1406.22 cM, with an average marker density of 0.81 cM per marker. Eight quantitative trait loci (QTLs) associated with heat tolerance were identified in the F₂/F_2:3 populations, distributed on chromosomes 1, 4, 5, and 8, collectively explaining 3.43% to 35.44% of the phenotypic variation. Among them, the stable QTL qHT1-2 on chromosome 1 was consistently detected across all three environments, explaining 11.41% to 35.44% of the phenotypic variation. Additionally, a major QTL, qHT1-3, was identified on the same chromosome, accounting for 33.70% of the phenotypic variation. Transcriptome analysis of flowering-stage leaves from both parents revealed 9262 differentially expressed genes (DEGs). Of these, 21 DEGs were co-localized within the eight QTL intervals. The genes Zm00001eb013260, Zm00001eb012720, Zm00001eb013600, and Zm00001eb013100 exhibited highly significant differential expression between the parental lines, these four genes are identified as candidate genes in response to heat stress in maize, and their specific biological functions require further functional validation. Full article

Autonomous driving (AD) has emerged as a transformative technology that holds the potential to free humans from the need for manual driving and provide a safer, more comfortable and efficient driving experience. However, most AD systems make decisions solely based on vehicle dynamics and environmental factors such as road conditions and surrounding vehicles, while the occupant’s mental states, such as subjective feelings and experience, are neglected. As a result, autonomous vehicles (AVs) often fail to meet the occupant’s physical and mental demands, ultimately leading to a compromised driving experience. In this study, we propose an occupant-aware decision-making paradigm (ODP) for AD systems. ODP first perceives the occupant’s physical and physiological states that are closely related to mental states, such as facial expressions and physiological signals, through the occupant monitoring system (OMS). Then, a large vision-language model (VLM) processes the occupant’s physical and physiological states via the chain of thought (CoT) technique to analyze the occupant’s mental states and infer the occupant’s needs. Finally, the VLM makes driving decisions that match the occupant’s demands and preferences. Experimental results show that ODP can make decisions that are significantly better aligned with the occupant’s actual needs than existing methods. Full article

Urbanisation and climate change are intensifying heat risks in cities worldwide through the combined effects of global warming and the urban heat island (UHI) phenomenon. Elevated urban temperatures threaten human health, strain infrastructure, increase energy demand and exacerbate socio-spatial inequalities. While architectural and urban design decisions are central to the formation and mitigation of UHI, moving from UHI mitigation to heat-resilient cities requires linking physical interventions with governance capacity, equity, and adaptive learning over time. This paper, therefore, develops a conceptual framework for resilient and sustainable urban environments that embeds built-environment strategies within a broader resilience-oriented governance context. The study combines a narrative review of UHI mechanisms, impacts and mitigation approaches with a systematic review of local-government strategies implemented between 2015 and 2025. Following preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines and a population, intervention, comparison, and outcome (PICO)-based search strategy, 100 studies were selected from Scopus and Web of Science and analysed thematically. The review identifies four main domains of local action: green infrastructure; cool and permeable materials; water-based and blue–green infrastructure; and policy, governance and technology. Within these domains, the paper highlights architectural and design-relevant interventions, including shade-oriented streetscapes, climate-responsive building envelopes, ventilation-sensitive urban form, and blue–green corridors, while also examining institutional, financial and social factors that shape implementation and effectiveness. The findings show that combinations of green infrastructure, cool materials and blue–green systems can reduce surface and near-surface air temperatures and improve thermal comfort, with co-benefits for public health, energy efficiency, biodiversity and liveability. However, implementation is frequently constrained by limited financial and technical capacity, fragmented institutions, context-specific trade-offs, and insufficient attention to equity. Building on these insights, the paper proposes a conceptual framework comprising ten components that connect context and drivers; assessment and diagnosis; intervention strategies; implementation mechanisms; enablers; barriers; equity operationalisation; outcomes and effectiveness; monitoring and evaluation; and feedback and iteration. The paper concludes that advancing from urban heat islands to resilient cities requires design innovation supported by enabling governance, equity-centred prioritisation, and iterative monitoring and learning. Full article

Traumatic injuries represent a significant public health challenge, affecting millions worldwide annually and necessitating acute pain management that frequently involves the use of opioid analgesics to mitigate discomfort and facilitate recovery. Although opioids remain an integral part of post-traumatic injury pain management, their use exposes trauma survivors to the risk of developing persistent use, misuse, or opioid use disorder (OUD). Pre-injury health determinants, such as age, gender, psychiatric conditions, medical conditions, and substance use history, may interact with injury-related factors to acutely escalate the risk for misuse and addiction. Despite the growing recognition of these potential vulnerabilities, there remains a lack of evidence-based clinical decision support on modifiable and non-modifiable risk factors specific to post-traumatic injury opioid risk trajectories. This review summarizes the literature related to the multifactorial contributors to opioid misuse and addiction following traumatic injury such as patient-level (e.g., demographics, behavioral health), injury-related (e.g., severity, type), and system-level (e.g., prescribing patterns) characteristics. A comprehensive literature search, inclusive of the literature from 1995 to November 2025, was performed in PubMed/MEDLINE, Scopus, and Google Scholar using combinations of terms related to “opioids,” “misuse,” “addiction,” “trauma,” and “injury.” Search keywords and operators were developed in collaboration with a university librarian. Reference lists of articles were searched and synthesized. Case reports, case series, editorials, mini-reviews, letters to editor without original data, and qualitative studies were excluded. The findings of the review are expected to provide insight into clinical-decision making as it relates to the management of pain, pain-related distress and functional impact, and co-occurring conditions that may impact injury-related outcomes and the potential likelihood of substance misuse and addiction. Full article

Methotrexate (MTX), an effective immunosuppressive and antiproliferative agent, is clinically restricted by its hepatotoxic potential through oxidative stress, inflammation, and apoptosis. Dapagliflozin (DAPA), a sodium–glucose cotransporter 2 inhibitor, exhibits antioxidant and anti-inflammatory actions. This study investigated the hepatoprotective effects of DAPA against MTX-induced acute liver injury. Thirty-two female Wistar albino rats were divided into four groups (n = 8): Control, MTX (20 mg/kg), MTX + DAPA (MTX + DAPA 10 mg/kg/day for 10 days), and DAPA. Liver samples were examined histologically, immunohistochemically (Nuclear factor NF-kappa-B p65 subunit (NF-κB p65), Tumor necrosis factor alpha (TNF-α), Interleukin 1 beta (IL-1β), Caspase (Cas)-3, Vascular endothelial growth factor (VEGF)), molecularly (Reverse transcription–polymerase chain for Bcl-2-associated X protein (Bax), B-cell lymphoma 2 (Bcl-2), Cytochrome C (Cyt-C), Apoptotic peptidase activating factor 1 (Apaf-1), Cas-9, Cas-3, Cas-12), and biochemically (total oxidant status (TOS), total antioxidant status (TAS) and oxidative stress index (OSI)). MTX induced severe hepatic injury with congestion, sinusoidal dilatation, and inflammatory infiltration, accompanied by upregulation of NF-κB, TNF-α, IL-1β, Bax, Cyt-C, Apaf-1, Cas-9, Cas-3, and Cas-12 and reduced Bcl-2. DAPA co-treatment significantly restored hepatic structure, suppressed inflammatory and apoptotic markers, and normalized VEGF expression, indicating reduced pathological angiogenesis. Although DAPA did not fully reverse MTX-induced weight loss, it effectively mitigated hepatocellular damage. DAPA protects against MTX-induced liver injury by inhibiting NF-κB/TNF-α/IL-1β-mediated inflammation, modulating Bax/Bcl-2–Cyt-C–Cas-dependent apoptosis, and balancing VEGF-driven angiogenesis. DAPA may thus serve as a promising hepatoprotective adjunct in MTX therapy. Full article

Usnic acid (UA) is one of the most extensively studied specialized metabolites of lichens, attracting considerable interest due to its antimicrobial, anti-inflammatory, and cytotoxic properties. The efficiency of UA extraction from lichens depends on multiple interrelated biological and technological factors. This systematic review aims to synthesize and critically evaluate reported strategies for UA extraction from wild-grown lichen biomass, with particular emphasis on extraction efficiency, practicality, and application potential. This systematic literature review, based on the Scopus database was conducted by including original research articles reporting UA extraction from wild-growing lichens. The analysis covered species selection, sample pre-treatment, solvent type, and extraction methodology. A total of 117 studies were included. Due to the predominantly non-polar nature of UA, higher extraction efficiencies were generally achieved using solvents, including acetone, supercritical CO₂, vegetable oils, and lipophilic green solvent systems. Pre-treatment strategies such as grinding or flaking significantly enhanced extraction performance by improving mass transfer. Alongside conventional methods (maceration, reflux, Soxhlet), non-conventional techniques such as Supercritical Fluid Extraction (SFE), Ultrasound- (UAE), and Microwave-Assisted Extraction (MAE) enabled faster and more selective UA extraction with reduced solvent use. Notably, SFE have been reported as particularly promising in terms of selectivity, process control, and potential suitability for scale-up, with commercially available supercritical CO₂ extracts of Usnea species supporting the feasibility of this approach. This review provides a consolidated and application-oriented overview of UA extraction, highlighting strategies that balance efficiency, selectivity, sustainability, and practical implementation. Full article

Background: Obesity is a multifactorial chronic disease resulting from sustained energy imbalance and modulated by environmental and demographic factors, and it is associated with numerous comorbidities. DNA methylation is an epigenetic modification associated with obesity. Modulation of DNA methylation is a viable target for obesity control strategies. The flavanol (-)-epicatechin (EC) exerts beneficial effects in overweight individuals, suggesting that EC may influence gene regulation through signaling pathways and epigenetic mechanisms. We evaluated whether EC modulates obesity-associated DNA methylation changes using complementary in silico, in vitro, and in vivo approaches. Methods. In silico analyses were performed to explore potential EC interactions with the DNA methyltransferases DNMT1, DNMT3A, and DNMT3B. DNMT activity was measured in nuclear extracts of 4T1 cells in the presence of EC. Finally, in a C57BL/6 mouse model of diet- induced obesity, we assessed global DNA methylation and the expression of the DNA methyltransferases, as well as metabolism-related genes; peroxisome proliferator-activated receptor gamma coactivator 1 alpha (Pgc-1α), pyruvate dehydrogenase kinase isozyme 4 (Pdk4), and nuclear factor erythroid 2–related factor 2 (Nrf2) and relative mitochondrial DNA content (mtDNA/nDNA ratio) in visceral adipose tissue (VAT) and skeletal muscle. Results. EC showed stable in silico interactions within catalytic/cofactor-binding regions of DNMTs and inhibited DNMT activity in vitro in a concentration-dependent manner. In vivo, the obesogenic diet reduced global DNA methylation and decreased transcript levels of Dnmt1, Dnmt3a, and Dnmt3b in skeletal muscle and adipose tissue. EC counteracted obesity-associated DNA methylation changes in skeletal muscle, restoring global methylation and Dnmt expression toward control levels, whereas effects in VAT were limited. EC increased mitochondrial DNA content. Discussion. In silico and enzymatic data suggest that EC may bind DNMT active sites and inhibit DNMT activity in a concentration-dependent manner, supporting a role for EC in obesity-related epigenetic remodeling, particularly in skeletal muscle. EC also increased relative mitochondrial DNA content in VAT and skeletal muscle despite no obesogenic diet effect on relative mitochondrial abundance, consistent with favorable mitochondrial modulation. In conclusion, EC is an epigenetic modulator and may have positive effects in obesity related dysfunctional tissues. Full article

With the transition from Industry 4.0 to Industry 5.0, human–robot collaborative assembly (HRCA) has progressed from physical copresence to cognitive integration and knowledge sharing. Digital twins (DTs) serve as enabling technologies that connect physical and virtual spaces. Support is provided for dynamic, safe, and human-centered collaboration. This study presents a systematic review of the research progress and practical applications of DT-enabled HRCA. First, conceptual boundaries between HRCA and general human–robot collaboration (HRC) in manufacturing are defined. Core elements of DT-driven state perception, task planning, and constraint modeling are described. Second, four task-allocation paradigms are classified and summarized, including optimization-based, constraint satisfaction-based, data-driven intelligent, and large language model (LLM)-assisted approaches. Applicable scenarios are identified. Third, the effects of collaboration modes and interaction modalities on planning logic are analyzed. Collaboration modes are categorized as parallel, sequential, and tightly coupled. Interaction modalities are grouped into AR-based explicit interaction, implicit intention perception, and multimodal fusion. Fourth, cross-domain application characteristics and engineering bottlenecks are summarized. Target domains include precision assembly, disassembly and remanufacturing, and construction on-site operations. Finally, four core challenges are distilled, including dynamic uncertainty, multi-objective conflicts, human factor adaptation, and system integration. Four future directions are outlined: LLM-enabled adaptive planning, safety–efficiency co-optimization, personalized collaboration, and standardized integration. The proposed technology–application–challenge–outlook framework is intended to provide a theoretical reference and practical guidance for transitioning HRCA from laboratory prototypes to large-scale industrial deployment. Full article

This article presents a comprehensive and analytically explicit study of optimal discrete quantization on spherical geometries equipped with the geodesic metric. Focusing on highly symmetric configurations on the unit sphere ${\mathbb{S}}^2$, we investigate three explicit models of discrete uniform distributions and derive closed-form expressions for their optimal quantizers and corresponding mean square quantization errors. (I) For N equally spaced points on the equator, we obtain exact error formulas for both divisible and non-divisible cases $n\nmid N$, demonstrating that optimal Voronoi cells form contiguous arcs with midpoint representatives. (II) For two antipodally symmetric small circles at latitudes $\pm {\varphi }_0$, each with M longitudes, we prove a no-cross-circle Voronoi phenomenon, establish symmetry-preserving optimality, and derive finite-sum error formulas together with sharp curvature-dependent bounds and asymptotics. (III) For a single small circle at latitude ${\varphi }_0$, we obtain analogous exact error formulas and show that curvature reduces distortion by a factor of ${cos}^2{\varphi }_0$, while preserving the $n^{-2}$ decay rate. Across all models, we rigorously establish the “block midpoint principle”: optimal Voronoi cells on a circle are contiguous azimuthal blocks, and their optimal representatives are the corresponding azimuthal midpoints. Numerical tables and illustrative figures highlight curvature effects and compare divisible and non-divisible cases. An algorithmic appendix provides pseudocode and a small, commented Python implementation to facilitate reproducibility. Written with didactic clarity while maintaining full mathematical rigor, this work bridges geometric intuition and analytic precision, providing explicit benchmark models that illuminate curvature effects and support further developments in quantization on curved manifolds. Full article

The Mar Menor is the second largest coastal lagoon in the Mediterranean Sea, with a surface area of about 136 km². It is restricted from the open sea by a sandy barrier system (La Manga) interrupted by three tidal inlets. As a result of high evaporation, it is hypersaline (42–47 ppt) in parts. This study examines the factors leading to the rise in sea surface temperature in the Mar Menor through an analysis of long-term sea surface temperature using HadSST1.1 data together with shorter-term Moderate-Resolution Imaging Radiometer and Optimum Interpolation Sea Surface Temperature data. A thermal box model has been constructed for the lagoon in an attempt to balance major heat sources and sinks. Additionally, a thermal probe was deployed in 0.3 m of water to evaluate the benthic flux of heat of the shelly fine sand that covers the lagoon seabed. The results show that the vertical thermal gradient in the seabed inverts between the day and night. Prior to circa 1977, there was no clear trend in SST, and variations were strongly associated with the Atlantic Mutidecadal Oscillation and the North Atlantic Oscillation. Post circa 1980, the maximum summertime sea surface temperature showed a steady increase of 0.34 °C/decade. The cross-correlation of SST in the Mar Menor with external drivers showed that it is dominated by the sea surface temperature of the Western Mediterranean, followed by local air temperature, with a minor contribution from the Indian Ocean Dipole. No other significant correlations were evident, suggesting that local temperature was dominated by local drivers. In addition, a Spearman rank order evaluation and principal component analysis showed that the general trends of the Mar Menor SST were also influenced by the Atlantic Multidecadal Oscillation, CO₂, and GDP. Full article