Abstract: Background: The comparative effects of pharmacological treatment, bariatric surgery, and diet on insulin resistance (IR) remain unclear. Aim: To study the comparative effects of the methods on IR: pharmacologic, bariatric surgery, and very-low-calorie diet (VLCD) in patients with type 2 diabetes mellitus (T2DM) and hypertension. Methods. Design: a 90-day prospective, multicenter, comparative clinical trial including 130 adult patients divided in three groups: Drug, Surgical, and VLCD groups. Endpoints: HOMA-IR; weight loss; HbA1c, systolic/diastolic blood pressure (SBP/DBP). Results. At 90 days, weight lost in Surgery (-19.8%) and VLCD groups (-17.4%) (P< 0.0001), while in Drug group the loss was unsignificant (-6.5%; P=0.06). SBP/DBP in Drug group decreased by -9.5% (P=0.0002) and -4.1% (P=0.09), respectively. SBP/DBP in: Surgical group decreased by -13.6% and -10.6%, respectively (P< 0.001); VLCD group -23.3% and 21.3%, respectively (P< 0.0001). HOMA-IR in Drug, Surgery and VLCD groups decreased by -42.2% (P=0.004), -87.6% (P< 0.0001), and -88.7% (P< 0.0001), respectively. In Drug group HOMA-IR did not reach normal level. Correlation-regression-analysis revealed a direct correlation between weight-loss and a decrease in HOMA-IR (r=0.526; F=33.2, P< 0.0001). HOMA-IR decreases by 65% if weight decreases by 10%; if weight decreases by 25%, then HOMA-IR decreases by 83%. Conclusions. HOMA-IR was associated with weight loss: the greater the weight loss, the lower HOMA-IR. Weight loss leads to reduce the need for antidiabetic/antihypertensive drugs in the patients.

Abstract: ABSTRACT Aim. We aimed to compare patients receiving cyclophosphamide treatment post-transplant with those receiving standard graft versus host disease (GVHD) prophylaxis in terms of GVHD development, disease relapse, overall survival, transplant-related mortality and infection development. Methods: The data of 78 patients who underwent allogeneic stem cell transplantation (AHSCT)at Medicana Izmir Hospital between January 2022 and June 2024 were retrospectively evaluated. Results: Of the patients, 36 (46.2%) were female, and 42 (53.8%) were male. Myeloablative related AHSCT was performed on 38 patients (48.7%), myeloablative unrelated on 26 patients (33.3%), and haploidentical on 14 patients (17.9%). Acute GVHD developed in 42 patients (53.8%),Regarding the clinical and laboratory variables affecting acute GVHD, only ferritin (p=0.016) was found to be significantly lower in the group with acute GVHD, and acute GVHD was significantly less observed in the group that received post-transplant cyclophosphamide (p. 0.032).In 15 patients (19.2%), chronic GVHD developed following acute GVHD. It was found that chronic GVHD developed more frequently in those who did not receive post-transplant cyclophosphamide (p=0.0001), in sibling transplants (p=0.037), in those without febrile neutropenia (p=0.021), and in those with high CMV-DNA levels (p=0.040). The median OS (months) was determined as 79.16 months. Median OS (months) was higher in patients with good AML cytogenetic risk group (p< 0.001) and in patients who underwent transplantation in first remission (p=0.021) has been found. In conclusion; Cyclophosphamide administration after allogeneic bone marrow transplantation can significantly reduce the development of acute and chronic GVHD.

Abstract: Complex networks model the structure and function of critical technological, biological, and communication systems. Network dismantling, the targeted removal of nodes to fragment a network, is essential for analyzing and improving system robustness. Existing dismantling methods suffer from key limitations: they depend on global structural knowledge, exhibit slow running times on large networks, and overlook the network’s latent geometry, a key feature known to govern the dynamics of complex systems. Motivated by these findings, we introduce Latent Geometry-Driven Network Automata (LGD-NA), a novel framework that leverages local network automata rules to approximate effective link distances between interacting nodes. LGD-NA is able to identify critical nodes and capture latent manifold information of a network for effective and efficient dismantling. We show that this latent geometry-driven approach outperforms all existing dismantling algorithms, including spectral Laplacian-based methods and machine learning ones such as graph neural networks and . We also find that a simple common-neighbor-based network automata rule achieves near state-of-the-art performance, highlighting the effectiveness of minimal local information for dismantling. LGD-NA is extensively validated on the largest and most diverse collection of real-world networks to date (1,475 real-world networks across 32 complex systems domains) and scales efficiently to large networks via GPU acceleration. Finally, we leverage the explainability of our common-neighbor approach to engineer network robustness, substantially increasing the resilience of real-world networks. We validate LGD-NA's practical utility on domain-specific functional metrics, spanning neuronal firing rates in the Drosophila Connectome, transport efficiency in flight maps, outbreak sizes in contact networks, and communication pathways in terrorist cells. Our results confirm latent geometry as a fundamental principle for understanding the robustness of real-world systems, adding dismantling to the growing set of processes that network geometry can explain.

Abstract: Promoting the clean energy transition is crucial for environmental sustainability and public health. Utilizing data from the China Health and Nutrition Survey (CHNS) spanning 2006 to 2015, this study employs a Difference-in-Differences (DID) model, treating China's West-East Gas Pipeline Project (WEGT) as a quasi-natural experiment to evaluate the causal impact of natural gas infrastructure expansion on resident health. The empirical results indicate that the WEGT significantly improved public health, with more pronounced effects observed among urban residents and the elderly. Mechanism analysis reveals that the infrastructure improves health primarily by optimizing household energy structures and reducing industrial pollution emissions. Furthermore, the "Coal-to-Gas" policy synergistically enhances these health benefits. Welfare analysis demonstrates that the project reduced medical expenditures and increased local employment. These findings provide empirical evidence for deepening supply-side structural reforms in energy and support the realization of the United Nations Sustainable Development Goals (SDGs) related to good health (SDG 3) and affordable clean energy (SDG 7).

Abstract: Background: Acute physical exercise can influence cognitive performance and neuro-biological processes, but evidence spans diverse modalities, intensities, and adult pop-ulations. Objectives: To map the breadth of acute exercise–cognition research, characterize cog-nitive and biological outcomes, and identify consistent patterns and gaps. Eligibility Criteria: Studies of adults (≥18 years) involving a single exercise session or short microcycle (≤7 days) with pre–post assessment of cognition and/or neurobiological markers across any exercise modality (aerobic, resistance, high-intensity interval train-ing/HIIT, combined, vibration, mind–body) were included. Sources of Evidence: PubMed and CENTRAL were systematically searched, yielding 102 studies. Charting Methods: Data were extracted using a structured framework capturing exercise modality, dose, cognitive domains, biomarkers, neuroimaging outcomes, population characteristics, and study design features. Results: Most studies examined young adults (53%) or older adults (32%). Aerobic exercise predominated (62%), followed by resistance (18%) and combined modalities (12%). Moderate-to-vigorous aerobic exercise consistently improved executive function, pro-cessing speed, and working memory. Resistance exercise also enhanced executive function in several trials. Neurobiological correlates included increases in Brain-Derived Neurotrophic Factor (BDNF), lactate, catecholamines, and prefrontal activation, though variability in sampling limited mechanistic conclusions. Conclusions: Acute exercise reliably enhances executive function and processing speed across modalities. Standardized exercise protocols, biomarker timing, and cognitive as-sessments are needed to strengthen mechanistic synthesis.

Abstract: Since 2014, the Mexican Caribbean has faced an ecological and socio-economic crisis due to massive coastal landings of pelagic sargassum. This study presents a comprehensive methodology for sargassum detection using Machine Learning (ML) models applied to imagery from a coastal video monitoring station (EVMC). Three machine learning techniques were implemented to classify sargassum on sand and water, Support Vector Machines (SVM), Random Forest (RF), and a Multi-Layer Perceptron (MLP) Artificial Neural Network. The performance of these ground-based models was then compared against sargassum detections from Sentinel-2 satellite data using the Floating Algae Index (FAI) and the Normalized Difference Vegetation Index (NDVI). The results demonstrated high efficacy, with the MLP model proving most effective for detecting sargassum on sand with a F1-score > 0.86, whilst the Random Forest model performing best in water with a F1-score > 0.75. A significant positive correlation was found between the video-based detections and indices derived from satellite data, with NDVI showing a consistently stronger correlation in both environments. This study validates coastal video monitoring as a reliable tool for local sargassum quantification and suggests that fusing this high-resolution ground data with wide-area satellite imagery offers a promising path toward a more accurate and comprehensive sargassum monitoring system.

Abstract: Introduction The addition of immunotherapy to neoadjuvant treatment for early triple-negative breast cancer (TNBC) has been adopted in clinical practice in France since March 2022 with little real-world data published on the topic. The aim of this study was to evaluate real world data on treatment feasibility, efficacy and related toxicities, with a specific focus on immune-related adverse events (irAEs). Methods We conducted a retrospective analysis of patients who completed at least the neoadjuvant sequence of pembrolizumab combined with chemotherapy for early-stage TNBC at Montpellier Cancer Institute from April 2022 to July 2024. Adverse events were graded according to the Common Terminology Criteria for Adverse Events (CTCAE) v5.0. The pathological complete response (pCR) was defined as the absence of residual invasive disease in the breast and axillary lymph nodes (ypT0/Tis ypN0) Results We reviewed data from 92 patient records. The median age at diagnosis was 50 years (range: 27–76). The history of autoimmune disease was noted in 3.2%. Grade 3–4 irAEs were observed in 20% of patients and included hepatitis (8.6%), colitis (3.3%), skin toxicity (2.1%), myocarditis (2%), arthralgia (1%), autoimmune hemolytic anemia (1%), hypothyroidism (1%), and adrenal insufficiency (1%). No treatment-related deaths were reported. Immunotherapy was discontinued due to irAEs in 1/3 of patients of the study population. pCR rate was 61,1%, with no significant association between the number of neoadjuvant pembrolizumab cycles and pCR rate (p=0.7). Patients experiencing grade 3–4 irAEs had a pCR rate of 80%, compared to 56.7% in those without such toxicities (p=0.079). Initial positivity of antinuclear antibodies (ANA) was not associated with an increased incidence of irAEs. Conclusion The immune-related adverse events and efficacy data observed in our cohort were broadly comparable to those reported in the KEYNOTE-522 trial with no treatment related deaths. Patients with grade 3–4 irAEs tended to have higher pCR rates.

Abstract: Background/Objectives: Falls are a leading cause of morbidity and mortality in older adults, even among those who are physically active. This study examined the associations of skeletal muscle mass, muscle strength, and muscle power with fall risk in community-dwelling, physically active older adults. Methods: A cross-sectional analysis was conducted with 280 participants (71.9 ± 5.3 years; 75% women) enrolled in the Stay Up–Falls Prevention Project. Assessments included skeletal muscle mass (anthropometric prediction equation), handgrip strength, lower-limb strength and power (Five Times Sit-to-Stand test, 5xSTS), and fall history over the past 12 months. Muscle power was calculated from 5xSTS performance using the equation proposed by Alcazar and colleagues. Logistic regression models and receiver operating characteristic (ROC) curve analyses were performed. Results: Overall, 26.4% of participants reported at least one fall in the previous year, with a higher prevalence among women (28.9%) than men (18.8%). Fallers showed significantly lower handgrip strength (23.1 vs. 25.4 kg, p = 0.022) and poorer lower-limb strength (9.2 vs. 8.7 s, p = 0.007) compared with non-fallers. However, no significant differences were found for skeletal muscle mass or sit-to-stand–derived power. In multivariable models adjusted for age, sex, body mass index, comorbidities, and medications, lower-limb strength remained the only independent predictor of falls (OR = 1.78, 95% CI: 1.11–2.85, p = 0.016). ROC analysis confirmed fair discriminative capacity for 5xSTS performance (AUC = 0.616, p = 0.003), with an optimal cut-off of 8.62 s (sensitivity = 78.4%, specificity = 33.0%). Handgrip strength, muscle mass, and power did not show independent predictive value. Conclusions: These findings indicate that the 5xSTS test provides a simple, cost-effective, and clinically relevant measure for fall-risk screening in active older adults. Clinicians should consider the 5xSTS as a sensitive first-line screening tool, ideally combined with complementary assessments (e.g., balance, gait, cognition) to improve risk stratification and guide preventive interventions in ageing populations.

Abstract:

This study extracted polysaccharides from Adansonia Suarezensis fruit pulp using various methods: hot water (ASP-HW), acid (ASP-AC), alkaline (ASP-AL), ultrasound-assisted hot water (ASP-HWU), ultrasound-assisted acid (ASP-ACU), and ultrasound-assisted alkaline (ASP-ALU). A comparison was conducted on the yield, chemical composition, structural properties, and biological activities. The findings indicated that the extraction solvent significantly influenced various essential properties of the ASPs, such as yield, monosaccharide composition, molecular weight, particle size, and thermal stability. The polysaccharides consisted of galacturonic acid, galactose, xylose, and arabinose.ASP-AL and ASP-ALU exhibited smaller molecular weight and particle size, with molecular weights of 19,813 Da and 19,600 Da, and particle sizes of 146.67 ± 22.46 nm and 140.97 ± 20.38 nm, respectively. The ASPs displayed characteristic polysaccharide structures, with ASP-AC, ASP-ACU, ASP-AL, and ASP-ALU possessing a triple-helix conformation. Bioactivity assays demonstrated that ASP-AL and ASP-ALU had enhanced DPPH radical scavenging activity (IC₅₀ 116.67 ± 0.58 μg/mL and 113.67 ± 2.31 μg/mL, respectively), ABTS radical scavenging activity (IC₅₀ 79.67 ± 0.58 μg/mL and 79.33 ± 1.15 μg/mL, respectively), and α-glucosidase inhibitory activity (IC₅₀ 0.146 ± 0.01 mg/mL and 0.206 ± 0.01 mg/mL, respectively).These findings indicate that ASPs possess significant bioactivity, supporting their potential use in pharmaceuticals and functional foods.

Abstract: This paper reviews research literature on Diamond Open Access (DOA) journals – sometimes also called Platinum Open Access – that was produced after this journal segment started to become a priority in European research policy around 2020. It con-textualizes the current science policy debate, critically examines different understand-ings of DOA, and reviews studies on the role of such journals in scholarly communica-tion. Most existing research consists of quantitative studies focusing on aspects such as the number of DOA journals, their publication output, the diversity of the landscape in terms of subject areas, languages, publishing entities, indexing in major databases, awareness and perception among scholars, cost analyses, as well as insights into the internal operations of DOA journals. The review shows that research on DOA journals is partly influenced by the science policy discourse in at least two ways: first, through the normativity inherent in that discourse, and second, through the temporality of policy-driven research of practical relevance, which leaves important aspects of the phenomenon understudied. Moreover, research on the DOA journal landscape has implications beyond understanding this particular journal segment, as it also challenges established views of the global system of scholarly communication.

Abstract: Peer review of empirical patterns in high-precision, low-dimensionality param- eter spaces relies on implicit evaluation standards. When N = 3 parameters at 2% precision permit thousands of statistically significant formulas, reviewers must distinguish structure from coincidence, but the criteria for doing so remain unar- ticulated. We found no published record of community debate establishing explicit standards, despite decades of informal application. This paper proposes one such articulation: seven criteria emphasizing tempo- ral convergence through timestamped predictions. We offer specific thresholds not because we believe them correct, but because explicit proposals can be calibrated while implicit standards cannot. The need for explicit standards is timely. Lattice QCD has only recently achieved the precision necessary for discriminatory tests of quark mass relations. Historical precedents from lepton phenomenology (Koide, Gell-Mann–Okubo) provide limited guidance: leptons offer ∼35,000× greater discriminatory power than light quarks, in- volve no RG running, and constitute a fundamentally different measurement regime. The historical record is further compromised by survivorship bias: patterns that di- verged are largely unrecorded. Historical cases motivate the problem by illustrating why implicit evaluation proved adequate for leptons but may prove inadequate for quarks. They cannot validate the proposed solution. Validation is prospective by design: starting from this publication, patterns evaluated under this framework will be tracked publicly. The framework succeeds if it proves predictively useful; it fails if it requires constant post-hoc adjustment, judged by its own temporal convergence criterion. If this proposal provokes disagreement that leads to better criteria, it will have served its purpose. If it is ignored, the current system of implicit evaluation contin- ues unchanged. We consider both engagement and refinement to be success.

Abstract: An important part of geometry computations for synthetic aperture radar (SAR) carried on a satellite platform is to convert between the instrument-specific coordinate system and a geocentric coordinate system such as Cartesian Earth-centered, Earth-fixed (ECEF) coordinates, geodetic coordinates (latitude/longitude) or a projection of these. The solutions for points on or near ellipsoid height typically involves iteration over geodetic coordinates, which means performing the transformation from geodetic to ECEF and its 6 partial derivatives in every iteration step. We present a method for solving these equations in the satellite’s zero Doppler plane, which is typically used as coordinate plane for SAR systems with small squint angles. Solving the system in this plane means one of the constraints is satisfied implicitly, and allows solution which satisfies the other constraint (correct range from satellite) to be solved using a one-dimensional Newton method. The method is simple to implement, fast and accurate. For targets on the ellipsoid, the solution can be made as accurate as machine precision allows. For high-precision applications with targets at non-zero height above the ellipsoid, a small correction step is necessary, and we describe how to arrive at this step.

Abstract: Classical loop-spaces capture cyclic behaviour in topology but are blind to the auxiliary data that often drives real-world quasi-periodic phenomena. In this paper we introduce decorated loop-spaces, organised into a category $\mathbf{DecLpSpc}$, whose objects are spaces equipped with “decorators” (labelling generators by auxiliary data) and whose morphisms are “connectors” acting on families of functions. We construct a decorated loop functor $$\widehat{\Omega} : \mathbf{DecLpSpc} \to \mathbf{DecLpSpc},$$ define a notion of decorated concatenation, and prove coherence and functoriality results in the spirit of Eckmann–Hilton duality. On the homotopical side, we extend classical Whitehead products and higher homotopy brackets to the decorated setting, obtaining decorated Whitehead products and Jacobiators that refine the quasi-Lie structure on homotopy groups by keeping track of decoration data. We show that $\mathbf{DecLpSpc}$ admits a natural symmetric monoidal structure and support operads acting on decorated loop-spaces, giving a recognition principle for iterated decorated loop functors $\widehat{\Omega}^n$. A worked example on a wedge of spheres illustrates how decorations enrich a nontrivial Whitehead product with additional algebraic labels. Finally, we outline several applications in which decorations encode physically or computationally meaningful structure: string dynamics and vacuum expectation values in background fluxes, evolutionary dynamics where decorations separate epigenetic from phenotypic data, and feedback and signal-processing architectures (including an OCR-inspired case study) where connectors transport function families between different feature spaces. We conclude with directions for an intrinsic homotopy theory of $\mathbf{DecLpSpc}$, computable invariants, and data-driven variants of the framework.

Abstract: The design of biomaterial scaffolds for bone tissue engineering requires a balance between bioactivity, porosity, mechanical stability, and osteoinductivity. Kappa- (KC) and iota-carrageenan (IC) have been explored for scaffold fabrication due to their biocompatibility and structural similarity to glycosaminoglycans. However, there are limited reports on how their distinct sulfation degree affects the osteogenic differentiation of cells cultured on them. While laponite has been reported as an osteoinductive nanoclay, its combined effect with different carrageenan types and its concentration-dependent effect on scaffold functionality remain unexplored. Therefore, we developed composite scaffolds comprising poly(vinyl alcohol) (PVA) and gelatin (GEL), reinforced with kappa- or iota-carrageenan (KC, IC) and functionalized with two different concentrations of laponite (LAP), 0.5 and 1% w/v, to monitor composition-structure-function relationships. The scaffolds were fabricated via lyophilization and dual crosslinking, and characterized for their physicochemical, structural, mechanical, and biological properties. The incorporation of both carrageenans into scaffolds, maintained high swelling ratios of 600% after 24 h, and increased porosity without altering their apparent density (0.09-0.11 g/cm3), whereas LAP preserved interconnectivity, densified pore walls, raised their compressive modulus at >220 kPa, and improved stability (&gt;60% mass retained after 40 days). In vitro validation using MC3T3-E1 pre-osteoblastic cells demonstrated robust cytocompatibility, with the LAP-containing scaffolds significantly promoting cell adhesion, proliferation, and osteogenic differentiation, evidenced by elevated alkaline phosphatase activity, calcium production and collagen secretion. Direct comparison between KC and IC scaffolds confirmed that differences in sulfate substitution modulated scaffold stiffness, swelling, and degradation, while variation in LAP concentration affected the biological response, with the 0.5 wt% concentration favoring early cell proliferation, whereas the 1 wt% significantly promoted the osteogenic differentiation. This compositional strategy demonstrates how tuning the interplay between carrageenan and laponite can balance scaffold hydration, mechanical and biological properties, thereby guiding the design of scaffolds for bone repair.

Abstract:

Abstract: Well-cited articles identify Google Scholar as a sufficiently lacking database to evaluate it as supplementary regarding the preferred reporting items for systematic reviews and meta-analyses: PRISMA. Subsequent author systematic review searches have accepted this relegation of Google Scholar to supplementary status without examination. This study questions this acceptance by (1) revealing the type of difficulties with Google Scholar identified in these well-cited publications compared with PRISMA guidelines, and (2) examining several PRISMA scoping review primary database searches performed by this author since 2023 for the adequacy of Google Scholar results compared with them. The results reveal that the reasons for considering Google Scholar a supplementary database regarding PRISMA status are not convincing, as they are unrelated to PRISMA guidelines for systematic reviews. Additionally, Google Scholar was the source of the most relevant included studies for the majority of this author’s post-2023 scoping reviews. These results demonstrate that the accepted advice to authors that Google Scholar should be a supplementary database is unsupported. Regarding PRISMA guidelines, based on the results of this original research, there should be immediate reconsideration of Google Scholar's status for acceptance as a primary database.

Abstract: Background/Objectives: To evaluate the incidence, characteristics, and clinical outcomes of intraocular inflammation (IOI) associated with intravitreal faricimab (IVF) in patients with neovascular age-related macular degeneration (nAMD) and diabetic macular edema (DME). Methods: Following PRISMA guidelines, a comprehensive search of PubMed, Web of Science, Scopus, Embase, and CENTRAL databases was performed from their inception to February 2025. Using the random-effects model, weighted proportions, standardized mean differences, and weighted log odds ratios (OR) were pooled and calculated. A two-tailed p-value of &lt;0.05 was considered statistically significant. The χ2 (z) test and the Higgins I2 test were used to assess studies heterogeneity. Results: We conducted a systematic review and meta-analysis of 24 studies (4,761 patients; 5,652 eyes). The most common diagnoses were nAMD (n = 4,782, 94.6%) and DME (n = 845, 37.1%). The pooled proportion for IOI incidence in eyes receiving IVF was 3.0% (95% CI: 1.0 – 6.0). The odds of developing IOI are significantly lower in the DME group compared to the nAMD group (OR: 0.89, p &lt;0.01). Unspecified IOI was the most common sign (n = 210, 2.9% [95% CI: 1.2 – 7.3]), followed by anterior uveitis (n = 80, 1.9% [95% CI: 0.1 – 34.8]), vitritis (n = 63, 2.9% [95% CI: 0.2 – 32.1]), retinal hemorrhage (n = 27, 0.7% [95% CI: 0.0 – 15.3]), and endophthalmitis (n = 8, 0.5% [95% CI: 0.3 – 1.1]). Conclusions: While IVF demonstrates therapeutic efficacy, our findings highlight a clinically relevant risk of IOI. We, therefore, recommend vigilant monitoring for all patients receiving IVF, especially those with nAMD.

Abstract: Background: This retrospective cohort study created an artificial intelligence (AI) model to predict dementia development and compared the prediction accuracy of the training data. The study participants were 7,384 older adults (age ≥ 75 years) who underwent regional dental checkups in Gifu Prefecture, Japan, in 2018 and 2020. Methods: The National Da-tabase of Health Insurance of Japan (NDB) was integrated with dental checkup data, and the participants were randomly divided into two datasets: training (n = 5,169) and valida-tion (n = 2,215). A data analytics tool was utilized to create the AI model with training da-ta in 2018 and data on the presence or absence of dementia development in 2020. Results: The AI model trained solely on NDB data showed sensitivity of 0.73 and specificity of 0.91 in predicting the presence or absence of dementia development after 2 years. By contrast, the AI model trained on NDB and dental checkup data showed sensitivity of 0.75 and specificity of 0.95, indicating improvement in both metrics. Conclusions: Combining dif-ferent sets of data, such as NDB and dental checkup data, for training may be useful for improving the accuracy of AI models to predict dementia development.

Abstract: Mitogen-activated protein kinase (MAPK) signaling cascade is fundamental in regulating cellular proliferation and differentiation, cell survival as well as cell death via apoptosis. Disruption in MAPK signaling cascade at any point can lead to evasion of apoptosis and unchecked cell growth and proliferation leading to oncogenesis. This narrative review describes MAPK pathway dysregulation, their therapeutic targets, and resistance mechanisms. The therapeutic targeting of MAPK pathway is complex owing to dual context dependent roles of several kinases in the signaling cascade. Despite therapeutic effectiveness of MAPK inhibitors, cancers cells develop chemoresistance that needs to be targeted via bypassing several molecular signaling points, pairing of MAPK inhibitors with multiple immune agents and targeting MAPK pathway downstream of ERK to prevent its reactivation mechanisms using combination therapies, downstream signaling regulators and PROTACs. Additionally, MAPK mediated regulation of ferroptosis is a novel oncological therapeutic targeting strategy for controlling tumor progression. The emerging therapies targeting MAPK pathway should be designed considering these crosstalks, compensatory signaling mechanism activation and the impact of tumor microenvironment.

Abstract: Background: Artificial intelligence is reshaping higher education, yet most institutions still rely on ad-hoc experiments rather than a holistic, evidence-based strategy for curriculum innovation. Purpose: This study develops and proposes a comprehensive framework that helps universities integrate AI ethically and systematically into program and course design, ensuring alignment with learner needs, labour-market skills, and quality standards. Methods: Employing an integrative secondary research design, we conducted a structured review of peer-reviewed articles, policy documents, and institutional case studies published between 2018 and 2025. Forty high-quality sources passed rigorous screening for relevance, credibility, and methodological soundness. Extracted data were coded thematically and synthesised into recurring practices, enablers, challenges, and ethical considerations, which collectively informed framework construction. Results: AI adoption in curriculum design is global but uneven; leading institutions report gains in student retention, skills alignment, and design efficiency, while lagging peers cite insufficient faculty training, unclear policies, and ethical concerns. Synthesised findings yielded a three-layer framework: (1) program-level guidance that uses AI analytics for outcome formulation, skills mapping, and curriculum sequencing; (2) course-level guidance that positions AI as a co-designer for content generation, adaptive assessment, and personalised feedback; and (3) cross-cutting foundations covering governance, responsible AI use, quality assurance, capacity building, and sustainability. Conclusions: The proposed framework offers a scalable pathway for data-driven, learner-centred, and ethically responsible curriculum innovation. Its adoption can enhance institutional agility and graduate employability, though empirical validation across diverse contexts remains a priority for future research.