Abstract: Deep learning systems have matched dermatologists on curated skin cancer image sets for almost a decade, but evidence from patient care has accumulated slowly and unevenly. This systematic review mapped where that evidence now sits along the translational continuum. A reproducible PubMed search run in August 2026 identified 656 records; after single-screener selection against pre-specified criteria and full-text assessment of 39 reports, 29 clinical-stage studies (prospective, controlled, or real-world evaluations of AI for cutaneous malignancy in patients) were included and staged as prospective standalone accuracy (n = 19), prospective clinician-with-AI use (n = 5), controlled evaluation (n = 1), or real-world deployment (n = 4). Risk of bias, appraised with QUADAS-2, ROBINS-I, or JBI tools, was high or serious in 24 studies, most often because of partial verification and preselected lesion spectra, and the certainty of every principal finding was low or very low (GRADE). No included study was a randomised trial with patient outcomes, and none reported stage at diagnosis, mortality, or overdiagnosis. Across modalities, sensitivity held up in prospective use, commonly above 90% at the pre-set operating point, while specificity fell to between 9% and 85% and was frequently lower than that of the clinicians it was compared against. Performance moved with acquisition hardware, lesion spectrum, and skin type, and one market-approved dermoscopic classifier reached areas under the curve of 0.54 to 0.62 in two Australian primary care studies. One product family progressed from prospective accuracy to national-pathway deployment under a conditional health technology recommendation, with human second reading overturning a large share of automated discharges. We argue that the reported specificity loss reflects safety-first operating points, spectrum preselection, and the choice of comparator rather than model failure alone, and propose readiness criteria linking each translational stage to the evidence needed before autonomous or primary-care use. The review followed PRISMA 2020, was not registered, and received no external funding.

Abstract: Introduction: South Africa’s Broad-Based Black Economic Empowerment (B-BBEE) framework seeks to widen economic participation, yet the supplied evidence indicates that empowerment benefits may remain concentrated among relatively advantaged groups. Concerns therefore persist regarding elite capture, unequal benefit distribution, weak accountability, and limited evidence on how Enterprise and Supplier Development (ESD) screening and targeting operate in practice.Methods: The researcher-selected databases and information sources were Google Scholar, ERIC. The eligibility protocol restricted publication years to 1994–2026. The exact calendar date of search execution was not recorded in the verified identification provenance; this is distinct from the publication-year eligibility range. A systematic review was conducted using Google Scholar and ERIC, with eligibility restricted to English-language peer-reviewed studies published from 1994 to 2026.Results: The synthesis indicates that B-BBEE benefits are reported as insufficiently broad-based and vulnerable to elite concentration. Transparency, accountability, public participation, civil-society involvement, co-production, and partnerships are presented as safeguards, but direct evidence that these mechanisms prevent capture in ESD programmes is limited. Finance, information, training, and skills development may widen participation, although beneficiary experiences and business-performance effects are mixed. Direct evidence on eligibility verification, conflict-of-interest controls, appeals, audits, and procurement-level anti-capture mechanisms is substantially limited.Discussion/Conclusion: The evidence supports a governance and inclusion framework for reducing capture but does not establish that existing ESD screening or targeting practices have demonstrably prevented elite capture. Conclusions are constrained by heterogeneous evidence, limited South African coverage, methodological uncertainty, and a PRISMA identification discrepancy requiring verification.

Abstract: In this paper, we develop a non-Hermitian coupling method for integrating heterogeneous datasets. Using the completeness of the root-vector system of the operator associated with the coupled graph Laplacian, we construct a generalization of a bi-orthogonal basis. Decomposing the trace functional into regular and nilpotent parts, we elaborate an analogue of the gradient ascent and descent method for the extremal trace problem. The central point of the concept is that the extremal values coincide with the trace values and their difference yields an intrinsic characteristic of dataset heterogeneity. The results are illustrated by single-cell multi-omics integration, where the indicators distinguish stable systems from stratified populations.

Abstract: For a century, the study of human body weight regulation has been dominated by the Energy Balance Model (EBM) and challenged by the Carbohydrate-Insulin Model (CIM). Both frameworks, however, rely on the indirect conversion of mass to energy, introducing propagated uncertainties and theoretical stalemates. The Eagle Project proposes a paradigm shift: direct mass accounting. By conducting feeding experiments in state-of-the-art whole-room metabolic chambers capable of continuous measurement for up to seven days, we will quantify every gram of mass entering and leaving the human body (food, beverages, O₂, CO₂, urine, feces, sweat). This extended duration eliminates the need for mathematical extrapolations. Furthermore, the project will integrate comprehensive, high-frequency blood sampling to map the full endocrine and metabolic response against physical mass fluxes. Committed to radical transparency, all raw data will be published in near real-time via preprints, free of paywalls and embargoes. The Eagle Project is not merely an experiment – it is a global, collaborative effort to resolve the metabolic stalemate and establish a new, physically rigorous foundation for nutritional science.

Abstract: Extreme endurance exercise offers a field setting for characterizing urinary cellular responses across sexes. This prospective observational study examined paired baseline and immediate post-race urine from 16 women and 16 men completing a 150 km ultramarathon. Automated fluorescence flow-cytometric counts were assessed alongside physicochemical and reagent-strip outputs. Between-sex tests compared individual acute changes; post hoc Bonferroni adjustment retained the original eight-comparison family. Median erythrocyte changes were +1.70 cells/µL in women and +0.60 cells/µL in men, with a between-group distributional difference retained after adjustment (p = 0.032). Corresponding squamous-cell changes were +0.85 and +0.30 cells/µL; this nominal difference did not meet the adjusted threshold (p = 0.056). Leukocyte, bacterial, pH and specific-gravity changes showed no significant between-group contrast. Recorded protein, ketone and male-only 24 h observations provided descriptive context. The findings identify an endpoint-specific urinary phenotype, with the erythrocyte association providing the clearest statistical signal. They establish a focused empirical target for source-specific replication and mechanistic investigation; anatomical origin and clinical significance require additional assessment.

Abstract: This study evaluated the psychometric properties of the Arabic 12-Item General Health Ques-tionnaire (Ar-GHQ-12) among older adults in Saudi Arabia, focusing on its factorial structure, internal consistency, and the feasibility of testing measurement invariance across sex. The sample comprised 221 participants aged 55 years or older, randomly divided into non-overlapping sub-samples for exploratory factor analysis (EFA; n = 110) and confirmatory factor analysis (CFA; n = 111). The Initial EFA used principal axis factoring (PAF) with oblimin rotation, followed by per-mutation-based parallel analysis using polychoric correlations and additional exploratory solu-tions. CFA compared five competing measurement models using robust maximum likelihood es-timation (MLR). Although the initial Kaiser criterion indicated three factors, parallel analysis fa-vored a two-dimensional solution; the exploratory solutions; however, showed suboptimal overall fit. In the CFA subsample, the bifactor model had the most favorable global fit indices (robust CFI = .979, TLI = .968, RMSEA = .041, SRMR = .045), while the wording-based two-factor model also showed favorable fit (robust CFI = .963, RMSEA = .049) and was preferred by BIC. Given the modest CFA subsample size and the differing model-selection criteria, these results do not estab-lish the superiority or stability of either factor structure. Bifactor-specific indices (ECV = .541, ω_H = .642, ω = .874, PUC = .545) did not provide sufficient evidence of essential unidimensionality. In-ternal consistency was acceptable to good for the negative-wording (α = .824; ω = .831) and posi-tive-wording (α = .758; ω = .760) item groups, although these estimates do not establish that the groups represent distinct psychological subscales. Measurement invariance across sex could not be reliably evaluated because the multigroup bifactor model produced an inadmissible solution. These findings provide preliminary, sample-specific psychometric evidence for the Ar-GHQ-12 among older adults but do not establish a definitive factorial structure or essential unidimension-ality. Further validation in larger, independent samples, including assessment of criterion-related validity and measurement invariance, is needed before clinical screening recommendations can be made.

Abstract: The standard cosmological model, Einsteinian spacetime, and the quantum mechanical framework have remained fundamentally deadlocked since the early 20 th century by highly persistent anomalies across diverse spatial scales, stretching from the atomic nucleus to galaxies. Utilizing our previously developed Faster-Than-Light (FTL) unified field framework [1], we demonstrate here that these long-standing mysteries are comprehensively resolved with our overarching FTL field model. We show here that these severe discrepancies are a direct consequence of the constraints imposed by these retarded theories: the speed of light limit c, and geometric misconceptions. Yet clearly also, the lack of the correct fluid-wave-like super-model hierarchy to explain reality. By analyzing about twenty distinctive empirical and experimental case studies, both macro- cosmospheric systems and quantum environments, this work validates beyond a reasonable doubt, our non-linear, hydrodynamic FTL field paradigm and its related waves’ signals: our fluid-wave- model can explain all these anomalies, within the same framework, validating therefore the FTL field foundation for a realistic, continuous, and non-retarded Theory of Everything.

Abstract: TRISIKON (tiga situasi dan kondisi, three situations and conditions) is a directorial principle from Indonesian expanded cinema that composes three visual modes, documentation footage, animation, and live action, into one work and reads their collision as a dialectic between creative uncertainty and compositional order. Developed through practice-based studies, it has had no quantitative formalization. Here the three modes are placed on the cyclically symmetric axes of the Thomas flow, and the dialectic is identified with a single dissipation parameter that carries the flow between an ordered regime and a chaotic one. The structure is fixed by exact results proved here: the flow is dissipative, with a bounded absorbing set and a compact global attractor; it is equivariant under cyclic permutation of its axes; it has a saddle at the origin; and it contracts phase-space volume at a constant rate. Consequently its Lyapunov exponents sum to that contraction rate for every invariant measure, which also serves as an internal check of the computation. Each regime is characterized by the Lyapunov spectrum with its dimension and entropy rate, by a Gaussian and a nonparametric differential entropy, by the permutation entropy with its statistical complexity, and by an order parameter that provably vanishes when the symmetry holds. Four cases, an ordered baseline, a balanced breathing, a deconstructive regime, and a symmetry-broken mode-dominance regime, are separated consistently by every diagnostic. The formalization is a shared language between weak-chaos theory and the aesthetics of expanded cinema, not an empirical claim about film practice.

Abstract: Intellectual disability (ID) characterizes numerous neurodevelopmental disorders, many of which also show increased obesity and metabolic comorbidities. Traditionally investigated independently, their coexistence suggests potentially shared pathogenic mechanisms, whose molecular and neural bases remain poorly understood. Down syndrome (DS), caused by trisomy 21, offers a genetically defined model for examining how altered gene dosage may affect cognition, feeding behavior, and energy homeostasis. Understanding these relationships could illuminate both the heterogeneous DS phenotype and metabolic vulnerability across ID-associated disorders. The locus coeruleus (LC), a major noradrenergic nucleus, regulates learning, memory, and energy balance. LC abnormalities have been reported in individuals with DS and corresponding mouse models, suggesting a potential contribution to both cognitive and metabolic phenotypes. Among chromosome 21 genes, dual-specificity tyrosine-phosphorylation-regulated kinase 1A (DYRK1A) is a compelling candidate. DYRK1A influences pancreatic β-cell mass and metabolic pathways while regulating neuronal development, synaptic function, and cognitive processes. Moreover, DYRK1A has been implicated in LC alterations in DS, although their functional consequences have primarily been investigated in cognition. Here, we review evidence connecting intellectual disability, obesity, LC function, and chromosome 21 gene dosage. We propose that DYRK1A-dependent changes in LC-noradrenergic signaling may contribute to cognitive impairment and potentially modify metabolic regulation in DS. Rather than assuming a single established causal pathway, this framework highlights a testable interaction between genetic dosage, neural circuitry, and environmental challenges that could explain divergent outcomes across physiological domains. Importantly, current experimental evidence more strongly supports a cognitive contribution than a direct causal role in metabolic and energy balance dysfunction.

Abstract: Under the Ecodesign for Sustainable Products Regulation, the Digital Product Passport (DPP) is set at model, batch or item level in line with the traceability practice of each value chain. Emerging value chains, such as those of agro-waste-based construction products, connect actors from different sectors and require upstream data to be checked and transferred to the product passport. This study proposes a multi-level passport architecture in which a Digital Material Passport (DMP), associated with each residue batch, records origin, legal status, handling and measured properties, and is linked to the product DPP. The architecture was applied in Emilia-Romagna, Italy, to six agricultural residues, three of which feed five lime-based product models at Technology Readiness Level 3–4: a screed, two blocks and two panels. Screening identified seven batch parameters to verify before production. For the three residues used, producers documented 15 of 42 attributes, the laboratory 11, and 16 remain to be supplied; legal status was documented for one batch, as biomass fuel. Half of the DMP data remained within factory production control as acceptance checks; the other half were transmitted to the batch-level DPP as composition, bio-based content, origin and legal status of inputs, and embodied carbon.

Abstract: Implicit knowledge graphs describe knowledge organization within large models as structures of semantic relations that emerge in response to an input. This theoretical account requires a rigorous existence proof. Using Transformer hidden states and multi-head attention, we provide a constructive existence proof under explicit assumptions. Nodes are selected by numerical salience and semantic-probe conditions. Edge weights are aggregated within specified groups of attention heads to construct an input-conditioned, multi-relational, directed weighted graph. Under assumptions of local regularity, semantic separability and positive threshold margins, the graph is well-defined, and its nodes satisfy classification conditions for specified semantic tasks. The node set and each typed edge set remain unchanged when input perturbations stay within the neighborhood where the assumptions hold and satisfy the corresponding margin bounds. We also give sufficient conditions for identical discrete structures under extractors that use common indices and the same thresholds. Aggregated graph edges are traced to single-head carrier edges, yielding a directional-derivative criterion for functional effects. If a non-degenerate carrier edge satisfies this criterion, sufficiently small weakening perturbations along the prescribed path decrease the target output’s unnormalized score, or logit. We further characterize the restoring gradient contribution of an entropy regularizer to mean attention entropy. These results establish the conditional existence of implicit knowledge graphs as a family of input-conditioned internal representations. They provide a mathematical basis for studying local stability and connections to model outputs.

Abstract: Neuromodulation techniques, such as repetitive transcranial magnetic stimulation (rTMS), have demonstrated efficacy across several neuropsychiatric disorders, yet identifying symptom-specific and biologically informed stimulation targets remains a major challenge. Lesion network mapping (LNM) addresses this problem by treating focal brain lesions as natural perturbations and mapping anatomically heterogeneous lesion locations onto normative connectomes to identify convergent symptom-relevant circuits. Since its introduction in 2015, LNM has generated candidate neuromodulation targets across diverse neurological and psychiatric conditions, with several studies showing overlap between lesion-derived networks, independent neuroimaging findings, and therapeutic neuromodulation targets. However, these observations do not establish whether the identified networks connected to lesion sites are causally responsible for symptom expression or how they should be therapeutically modulated. Because LNM relies on correlation-based connectivity measures, it cannot determine which circuit components or pathways causally mediate the relevant symptom, or whether candidate neuromodulation targets should be activated or inhibited. We therefore propose a translational framework in which LNM-derived circuit hypotheses are examined through cross-species anatomical and functional mapping, region-, cell-, and projection-specific perturbation in animal models, and concurrent behavioral and whole-brain functional readouts, before clinical evaluation. This framework positions LNM as a tool for identifying candidate circuits that are first tested in animal models for causal relevance and perturbation direction, and then evaluated clinically for therapeutic relevance.

Abstract: Background: Tuberculosis (TB) remains a major public health problem in sub-Saharan Africa. Although host genetic factors may influence susceptibility to infectious diseases, the relationship between ABO/Rh blood groups and pulmonary TB remains incompletely understood, particularly in African populations. Herein, we characterise the distribution of ABO/Rh blood groups and the demographic profile of patients with pulmonary TB in Luanda, Angola. Methods: This was a cross-sectional study conducted among patients with pulmonary TB treated at Hospital Divina Providência, Luanda, during the second semester of 2020. A total of 110 patients were selected by simple random sampling. Sociodemographic data were collected and ABO/Rh blood groups determined using anti-A, anti-B, and anti-D reagents. Results: Among the 110 participants, O+ was the most prevalent phenotype (51; 46.4%), followed by A+ (29; 26.4%), B+ (25; 22.7%), and AB+ (5; 4.5%). The mean age was 31.5 years, and males accounted for 57.3% of participants. Most participants had non-higher education (89.1%) and resided in Kilamba Kiaxi municipality (75.5%). ABO phenotype was not associated with age (p=0.423) or sex (p=0.522). Also, ABO was not associated with educational level (p=0.125), residence (p=0.769), occupation (p=0.864), alcohol consumption (p=0.748), or associated infections (p=0.365). Conclusion: The O+ blood group was the predominant ABO/Rh phenotype among patients with pulmonary TB in Luanda, followed by A+, B+, and AB+. No associations were identified between ABO phenotype and demographic or clinical characteristics. Larger multicentre studies incorporating appropriate non-TB control groups are warranted to clarify the potential relationship between ABO phenotypes and TB susceptibility in Angola.

Abstract: Technologies in sustained operational use can yield different productivity outcomes even when adoption, implementation, and organizational complements are comparable. This study develops a testable relational explanation based on binding shortfalls in contributions required by focal activities. A structured integrative Scopus review and a separate theoretical comparison relate the framework to process theory, complementarity, benefits realization, and the Theory of Constraints (TOC). The analytical unit is a directed relation between an activity and a contribution it needs after implementation. An illustrative application to a published Amazon Web Services (AWS) database-contention benchmark shows how a required contribution and lock waits can be identified independently of economic productivity. In comparable post-implementation conditions, binding is expected to reduce the activity’s output–input ratio relative to an unbound condition, although productivity may still exceed its pre-implementation baseline. Criticality and substitutability condition the expected effect, external control can restrict access, and reconfiguration burden may prolong binding.

Abstract: We consider the identification of a Robin coefficient \(R\) defined on a nonaccessible part \(\Gamma_{\text{out}}\) of the boundary, from noisy velocity measurements available on an accessible part \(\Gamma_0\), for the nonstationary Stokes system with mixed Dirichlet, Neumann and Robin boundary conditions. This ill-posed inverse problem is formulated as a nonlinear least-squares problem, which we solve by the Levenberg--Marquardt method. The linearized subproblems are expressed by means of the sensitivity and adjoint problems. Under suitable assumptions, we prove that, for an initial guess close enough to the exact coefficient and a small noise level, the iterates satisfy a quadratic convergence estimate up to a term proportional to the noise level. For the discrete iteration, we further show that, under noise and under an explicit condition, the iterates started close enough to the least-squares solution converge linearly to it, at a rate bounded explicitly in terms of the smallest eigenvalue of the Gauss--Newton matrix, the noise level and the curvature of the forward map, and we derive an a posteriori stopping test. The discrete problem is verified with manufactured solutions and an exact discrete gradient, and the rates predicted from the eigenvalue and the noise level alone are reproduced by the experiments to two digits. On a bifurcation with two outlets, velocity measurements at the inlet determine the equivalent resistance of the outlets well, and the split of the coefficients between them poorly: a network model, in which the inlet velocity depends on the coefficients through the equivalent resistance only, explains the weak direction. When the data are generated by a finer model, the time discretization error of the model used for the inversion exceeds the effect of the coefficients on the data, and the iteration moves away from the exact coefficient; we quantify this limitation and propose a stopping test that accounts for the model error. The approach is motivated by applications to blood flow in cerebral aneurysms and to air flow in the lungs.

Abstract: A Ti–6Al–7Nb–0.3Y spherical powder was produced by ultrasonic atomization (UA), and its < 63 µm (d₅₀ ≈ 53 µm) and 63–125 µm (d₅₀ ≈ 82 µm) fractions were characterized for laser powder-bed fusion (LPBF) of patient–specific biomedical implants. Both fractions show near-ideal sphericity (1.01) with no satellites or internal pores, flow times of 26.8–28.0 s/50 g and bulk densities of 2.35–2.45 g/cm³ (51–53% of true density), matching commercial powder-bed feedstocks. XRD revealed only hexagonal α(α′)-Ti with a microstrain of 0.45–0.55%. Nanoindentation showed a hardness of 4.55–4.90 GPa, exceeding that of laser-powder-bed-fused Ti–6Al–4V (3.66 GPa), and an elastic modulus of 119–148 GPa on rigidly supported particles. Simultaneous thermal analysis showed stability up to 450 °C in all atmospheres, oxidation in air above 720 °C (E_a ≈ 160–170 kJ/mol) and mass gains at 1195 °C of 23.2–25.7% (air), 4.9–6.8% (N₂) and 1.7–2.1% (Ar). The Ti–6Al–7Nb–0.3Y powder contains 0.69–0.74 wt.% Oxygen, far beyond the scavenging capacity of the retained 0.11–0.12 wt.% Yttrium, as well as 0.09–0.12 wt.% Nitrogen and 0.013–0.015 wt.% Hydrogen.

Abstract: Psychological well-being is associated with favorable cardiovascular health, but its physiological mechanisms remain incompletely understood. We examined associations between psychological well-being and inflammatory, hemodynamic, and neuroendocrine measures in 846 participants from the community-based Health, Environment, and Action in Louisville study. Well-being was assessed with the Warwick-Edinburgh Mental Well-Being Scale; perceived stress, depressive symptoms, and neighborhood social cohesion were evaluated as complementary psychosocial measures. Primary outcomes were high-sensitivity C-reactive protein (hsCRP), systolic blood pressure (SBP), and diastolic blood pressure (DBP). Multivariable models adjusted for demographic, socioeconomic, and smoking-related factors, with false discovery rate correction. Greater well-being was associated with lower hsCRP (β = −0.12, 95% CI: −0.20 to −0.04; p = 0.002), SBP (β = −2.03 mmHg, 95% CI: −3.16 to −0.90; p < 0.001), and DBP (β = −1.56 mmHg, 95% CI: −2.36 to −0.76; p < 0.001). Perceived stress showed reciprocal associations, whereas depressive symptoms and neighborhood social cohesion were less consistent. Selected urinary catecholamines, but not hair cortisol, were associated with well-being. These findings identify inflammatory and hemodynamic correlates of psychological well-being and support further investigation of positive psychological health in cardiovascular disease prevention.

Abstract: Public biomedical repositories contain petabytes of data, yet testing hypotheses against those resources still requires expert effort. I present a four-phase blinded workflow for autonomous computational hypothesis testing: an agent receives a natural-language hypothesis, discovers public datasets with academic publisher domains blocked, executes an analysis pipeline and validates findings against the literature. Published studies serve as calibration rulers, measuring how closely an autonomous workflow approaches known answers before it is trusted on unknown ones. Across five biomedical tasks spanning bacterial genomics, single-cell multiomics, metagenomics, cancer genomics and GWAS functional genomics, the agent scored 5–9 out of 10 on pre-specified rubrics in 20–188 minutes (the single-cell multiomics score was corrected from an initial 8 to 5 after blinded judge review identified over-credited criteria; see Methods). An exploratory comparison across three successive model generations found scores directionally higher for the first generation (claude-opus-4-6) on all five tasks (one-sided Wilcoxon p = 0.031, rank-biserial r = 1.0; n = 5 studies), with newer models completing tasks faster; the benchmark also exposed generation-specific safety policy and schema differences that silently confound cross-generation comparisons if not corrected. Failures fell into three categories, tool-version sensitivity, data-scope limitation and analytical completeness, all self-diagnosed by the validation phase in all five cases examined here without human prompting. These results introduce a calibration framework and failure taxonomy for characterising when autonomous computational science workflows should and should not be trusted.

Abstract: Aquaculture has become an increasingly important industry today, and with rising demand for fish, the sector has been working diligently to enhance production while maintaining quality and improving efficiency. However, excessive use of antibiotics and other chemicals to control diseases in aquaculture has raised concerns about potential impacts on fish consumers and the aquatic environment. As a result, there has been concern about finding alternative methods to maintain fish health and boost productivity. In a recent investigation, it has been discovered that the use of the gastrointestinal commensal microbiome species can control the spread of diseases in aquaculture farming effectively. Therefore, the potential to manipulate the gastrointestinal microbiome to improve health and production is a fascinating prospect that has gained considerable attention in recent years.

Abstract: Rotavirus-associated encephalopathy is a rare, severe complication in infants and young children, but its molecular basis remains unclear. Rotavirus nonstructural protein 4 (NSP4) is secreted from infected cells as a phospholipid-associated oligomer and can disrupt calcium homeostasis, yet its presence in circulation, interactions with the blood-brain barrier (BBB), and central nervous system access remain unproven. This hypothesis article integrates evidence on NSP4 structure and lipoprotein-like behavior, low-density lipoprotein receptor-related protein 1 (LRP1), caveolin-1, and developmental BBB transport. This article proposes that NSP4–lipid complexes could interact with glycosaminoglycans and, potentially, with LRP1- and caveolin-associated uptake in brain endothelial cells. If NSP4 crosses or is retained within the BBB, it might perturb calcium signaling and cellular homeostasis in endothelial and neural cells, including astrocytes, microglia, neurons, and oligodendrocyte precursor cells. These links are hypothesis-generating because NSP4–LRP1 binding, BBB transcytosis, and cell-specific effects in the developing brain remain unproven. This article outlines experiments to test or refute this developmental lipid-transport model.