The National University Toribio Rodríguez de Mendoza (UNTRM) is a state-owned university in Chachapoyas, Peru. The UNTRM was founded on September 18, 2000.
La duplicación craneofacial, denominada diprosopia, constituye una anomalía congénita poco frecuente clasificada como una forma de gemelación conjunta simétrica. Esta malformación se caracteriza por la duplicación parcial o completa de estructuras cefálicas y faciales, originada por alteraciones en la morfogénesis embrionaria durante la fase temprana de gastrulación. La etiología de esta condición es multifactorial e incluye factores genéticos, ambientales, nutricionales y exposición a agentes teratogénicos. Entre los principales agentes teratogénicos identificados se encuentran los benzimidazoles antihelmínticos, la radiación ionizante, y el consumo de plantas tóxicas durante la gestación. Destaca particularmente Veratrum californicum, cuyo alcaloide ciclopamina inhibe específicamente la vía de señalización Sonic Hedgehog (Shh), esencial en el desarrollo craneofacial normal. Adicionalmente, se han asociado especies forrajeras teratogénicas prevalentes en regiones semiáridas, como Mimosa tenuiflora, Cenostigma pyramidalis y Cynodon plectostachyus, que inducen malformaciones óseas, muerte embrionaria y lo que coloquialmente se denomina 'fetos monstruosos'. Estas alteraciones provocan abortos, alta mortalidad neonatal y pérdidas productivas significativas en explotaciones pecuarias, con tasas de incidencia que oscilan entre 0.5 y 0.8 % del total de nacimientos. El presente reporte documenta un caso de diprosopia parcial en un caprino, aportando evidencia morfológica y discutiendo las posibles causas embriológicas en el contexto de la región norte del Perú.
In high-altitude trout raceways, dissolved oxygen (DO) declines are brief and start from a narrow margin below saturation. We built a solar-powered floating node with five water-quality channels, a serviceable probe cartridge, switched sensor rails and store-before-transmit telemetry and operated it for 89 days in a raceway at 2100 m a.s.l. (Amazonas, Peru). It recorded 25,522 five-minute observations (99.57% coverage) with 99.95% packet delivery. Under calibration transfer, DO error was 0.100 mg L−1 and the field variability of temperature, DO and turbidity exceeded it 3.5–4.2-fold. On a chronologically separated test period, three-hour DO RMSE was 0.180 mg L−1 with five-channel inputs and 0.260 mg L−1 with DO-history inputs alone, against 0.362 mg L−1 for an hour-of-day control. Six-hour gains were not resolved: departures from the diel course had decorrelated, the test period shifted toward low DO and turbidity events, and out-of-range conductivity produced spurious troughs. A three-hour DO < 6.5 mg L−1 classifier reached ROC-AUC 0.946 and, with two-sample confirmation, detected all 24 complete low-DO episodes, against 15 with DO history alone. Battery-terminal measurements showed the awake controller as the largest identified load; calculated balances indicated that the installed 15 W module sustains the five-minute cycle and that deep-sleep standby would cut daily charge by 80–91%.
BACKGROUND:Peru recorded one of the world's highest COVID-19 mortality rates, with nearly 4.5 million reported cases and 220,000 deaths by March 2024. Understanding the emergence and spread of SARS-CoV-2 variants in this context is key to informing effective public health responses. This study describes the genomic diversity, transmission dynamics, and geographic spread of SARS-CoV-2 in Peru from 2020 to 2024. METHODS:We analyzed nearly 50,000 high-quality public SARS-CoV-2 genome sequences collected nationwide between March 2020 and March 2024. Phylogeographic and mutational analyses were performed to identify variant lineages, trace their origins, and map viral movements within and beyond Peru. RESULTS:We show that Peru's epidemic waves were shaped by the emergence of locally evolved variants, including Lambda (C.37), Gamma (P.1.12), and Omicron (XBB.2.6 and DJ.1) sub-lineages. The city of Lima acted as the primary hub for inter-regional spread, accounting for 47.3% of inferred viral movements to other departments, notably Ancash, Cusco, and Piura. Peru was the source of various lineages that spread internationally, primarily to Chile, the USA, and Europe. Mutational analysis highlighted critical mutations in the spike protein, including L452Q and F490S in Lambda, associated with immune evasion and increased transmissibility. CONCLUSIONS:This work demonstrates the capacity of genomic surveillance in Peru to detect and track emerging SARS-CoV-2 variants, providing insights into regional and global transmission dynamics in a high-transmission, middle-income country setting. Sustained, cost-effective genomic monitoring, combined with strengthened bioinformatics and laboratory capacity, is essential for pandemic preparedness in resource-limited settings.
Background Dengue remains a major public health challenge in endemic settings. Evidence on the psychosocial predictors of dengue vaccination intention remains limited in Peru. This study aimed to identify predictors of dengue vaccination intention among adults in selected endemic areas of Peru using partial least squares structural equation modeling (PLS-SEM). Methods A cross-sectional study was conducted among 573 adults from selected provinces in Amazonas and Ancash, Peru, between June 2024 and December 2025. Data was collected using an adapted and validated multidimensional questionnaire. The model was estimated using SmartPLS 4.1.1.8 with 5,000 bootstrap resamples. Perceived benefit and attitude toward the dengue vaccine were integrated into a second-order construct termed favorable evaluation of the vaccine (FEV) to address their lack of discriminant validity. Results FEV was the strongest predictor of vaccination intention (β = 0.849, p < 0.001; f 2 = 1.749). Trust in key actors significantly predicted FEV (β = 0.557, p < 0.001) and perceived risk (β = 0.351, p < 0.001). Perceived risk did not significantly predict vaccination intention directly (β = −0.035, p = 0.237) but showed a significant positive indirect effect through FEV (β = 0.173, p < 0.001). Religiosity significantly predicted FEV and perceived risk, although its effect sizes were small. The model explained 69.2% of the variance in vaccination intention (R 2 = 0.692). Conclusions Favorable evaluation of the vaccine emerged as the strongest predictor of dengue vaccination intention in the structural model. Trust in key actors was an important predictor of favorable vaccine evaluation and perceived risk, whereas perceived risk predicted vaccination intention indirectly through FEV rather than directly. These findings may inform vaccination communication strategies in dengue-endemic settings.
Modern energy networks constitute complex dynamic systems characterized by operational uncertainty and nonlinear behavior. The objective of this research was to develop a physical-computational framework to analyze the stability and adaptive capacity of energy networks subjected to stochastic perturbations. A nonlinear dynamic model based on ordinary differential equations was employed, integrating Monte Carlo simulation, Latin Hypercube sampling, an Energy Antifragility Index (EAI), sensitivity analysis using Sobol indices, and bifurcation analysis. The results revealed fragile, resilient, and antifragile behaviors, with resilient scenarios predominating. Coupling intensity and perturbation magnitude were the parameters with the greatest influence on the system. Likewise, a critical threshold associated with the emergence of multiple equilibrium states and dynamic transitions was identified. It is concluded that the integration of nonlinear dynamics and probabilistic simulation makes it possible to understan
