This work is inspired by the method proposed in [1], where planar G2 interpolants based on seventh-degree PH biarcs were constructed to interpolate prescribed points, tangent directions, and curvature values while enforcing a desired arc length. Our aim is to investigate the possibility of achieving analogous results using quintic PH curves. The construction of the quintic biarc model with prescribed arc length is presented, along with the derivation of the associated equations and the strategies used to reduce the degrees of freedom. Numerical experiments are reported to show the validity, limitations, and general applicability of the proposed quintic approach.
Severe, treatment-resistant obsessive-compulsive disorder (OCD) remains disabling despite optimized pharmacotherapy and exposure and response prevention (ERP). Radiosurgical capsulotomy is an irreversible ablative intervention reserved for highly selected patients. This narrative review examines evidence from structural MRI, diffusion imaging, functional connectivity, electrophysiology, and radiobiology. The search was supplemented by a reproducible PubMed search across eight prespecified modules (856 records before and 739 after deduplication), with an audited 102-record core SRS/OCD set. Structural lesion mapping and a small longitudinal diffusion study support investigating pathway involvement alongside lesion volume, but do not establish a validated network mechanism or individualized targeting biomarker. Functional MRI and EEG findings in OCD and connectivity studies of other interventions provide complementary evidence but require cautious cross-modality extrapolation. Single-session irradiation must be distinguished from thermal capsulotomy; dose, prescription isodose, irradiated volume, and delayed toxicity require joint interpretation. We use “functional disconnection” as a hypothesis concerning downstream effects of tissue injury, not evidence of a nonablative or reversible treatment. Priorities include harmonized longitudinal imaging, dose-volume-connectivity analyses, cognitive and behavioral surveillance, and controlled evaluation of ERP timing. Current evidence supports a network-informed research framework without establishing a post-radiosurgery plasticity window or superiority of connectivity over conventional planning variables.
Artisanal and small-scale gold mining (ASGM) mobilizes metal-rich sediments and trace contaminants into river systems, creating ecological and toxicological risks in tropical catchments. Distinguishing mining-derived contamination from natural hydrogeochemical variability remains difficult in data-poor regions with strong seasonal sediment transport. Here, we combined monthly community-based water-quality observations, laboratory ICP-MS measurements, and Bayesian multivariate hierarchical modelling to quantify the relative influence of basin hydrogeochemistry, seasonal hydrology, and mining activity on river metal assemblages in two Sierra Leone basins with contrasting degrees of ASGM impact.Metal variability was dominated by basin-scale hydrogeochemical controls and particle-associated transport, while mining-affected catchments showed additional enrichment in Mn, Co, Ni, Cr, and Pb, elements of potential toxicological concern for aquatic ecosystems and downstream water users. Seasonal hydrology modulated concentrations but did not obscure the mining signal. The probabilistic modelling framework separated natural and anthropogenic controls while accounting for metal covariance and uncertainty in environmental effects.Low-cost multi-metal colorimetric kits were unreliable for detecting mining gradients, whereas community-led turbidity measurements provided an operational proxy for sediment-associated disturbance. These results support a tiered monitoring strategy combining frequent community turbidity observations with targeted laboratory analyses of Mn, Co, Ni, Cr, and Pb to identify contamination hotspots of potential ecological and exposure concern. The approach provides an adaptable early-warning framework for other data-limited ASGM-affected regions, though regional recalibration would be needed to account for differing geology, climate and hydrology.
Type 1 diabetes mellitus (T1DM) is an autoimmune disease characterized by the destruction of pancreatic β-cells, leading to chronic hyperglycemia and lifelong dependence on exogenous insulin. Increasing evidence indicates that T1DM is a highly heterogeneous condition driven by complex interactions among genetic, immune, environmental, and metabolic factors, which collectively influence disease prediction, diagnosis, prevention, and treatment. To date, no curative or durable remission-inducing therapy for T1DM is available. Current therapeutic approaches, acknowledging both the central role of the immune system and the emerging contribution of β-cell stress to disease pathogenesis, include targeted immunotherapies, cytokine inhibitors, tolerance-inducing strategies, and β-cell–protective agents. Despite promising advances, highlighted by the approval of teplizumab, achieving the ultimate therapeutic goal in T1DM, namely preventing or halting disease progression, will require closing critical gaps in our understanding of disease etiopathogenesis and heterogeneity to enable individualized, stage-specific interventions. Consequently, the development, implementation, and clinical validation of novel, easily accessible, and measurable biomarkers, capable of stratifying individuals with T1DM and predicting therapeutic responses, represent a high priority. In this context, circulating microRNAs emerge as an attractive class of candidate biomarkers. In parallel, it is essential to integrate autoantibody screening into routine clinical care through structured, population-based programs.
