Universidad del Sinú

Background Polyclads are a diverse group of marine free-living flatworms, with some species adapted to life in floating Sargassum mats. Recent studies suggest that, rather than being inherently pelagic, these flatworms should be classified as "clinging fauna", as they rely on floating substrates for habitat. New information This study documents, for the first time, the occurrence of Gnesioceros sargassicola and Chatziplana grubei in Sargassum along the Caribbean coast of Colombia. High-definition photographs of whole mounts and histological sections are provided for both species, along with detailed observations of their reproductive structures and 28S rDNA barcodes. These findings underscore the importance of exploring the fauna associated with Sargassum, contributing to a better understanding of polyclad distribution and raising the number of recorded species for Colombia to 26.

The demographic shift and epidemiological transition observed in the general population have also impacted migrant communities, becoming a significant public health concern that demands attention to ensure no one is left behind. Migrants in Latin America and the Caribbean region face unique risks due to exposures at different phases of the migration process, which may lead to a higher risk for chronic diseases over time. This chapter examines the current knowledge on chronic diseases among migrants in the region, highlighting critical gaps, barriers, and social determinants of health while exposing the urgent need for more comprehensive research and public health responses. Although the evidence remains scarce, often relying on self-reported data, methodological and structural challenges further limit research and policy development. The chapter emphasizes the growing problem of undiagnosed and poorly managed chronic diseases due to limited healthcare access across the region. It explores the influence of social determinants such as migratory status, socioeconomic disadvantages, health systems shortcomings, and psychosocial factors like discrimination on worsening health outcomes. The following sections call for clinically measured data collection, tailored interventions, and policies addressing health’s social determinants while actively involving migrants to mitigate the chronic disease burden.

Objectives This study aimed to develop and validate a clinical score for the prediction of critical care entrance in children with dengue. Methods We conducted a retrospective cohort study using admissions from January 2019 to August 2021, at Hospital Infantil Napoleón Franco Pareja, in Cartagena, Colombia. We included all children 18 years or younger, with a positive immunoglobulin M or nonstructural protein 1 laboratory test and admitted for follow-up at the emergency department. We selected variables retrospectively collected on emergency admission for feature selection. We assessed discrimination and calibration in the development dataset, using 1000 bootstrap replications for internal validation. Data from 2019 to 2020 were used for development and 2021 for temporal validation. We report the c -statistic for discrimination with 95% confidence intervals (CIs), as well as the calibration intercept and slope. Results One thousand three hundred eighty-five patients were included for development and internal validation. In temporal validation with 519 additional patients, the c -statistic was 0.82 (95% CI: 0.77–0.87), with a calibration slope of 0.98 (95% CI: 0.77–1.18). We selected the 50 th percentile of the distribution of predicted probability of critical care entrance (5%) as a threshold value for increased alert at emergency admission, missing 10% of all cases that need to enter critical care (sensitivity of 90% with 95% CI of 82–95, and specificity of 48% with 95% CI of 41–50). Conclusions Our validated model can be useful to predict critical care entrance in children with dengue. We recommend the validation and potential recalibration of our score in other clinical settings.

A new hyphenated technique using thin-layer chromatography (TLC) to separate analytes in mixtures, coupled with mid-infrared (MIR) laser spectroscopy for identification and quantification, is presented. The method, which provides a means for rapid screening of analytes that is practical, low-cost, fast, robust, and reproducible, was tested using nitroaromatic and aliphatic nitro high explosives (HEs) as target analytes. HEs are anthropogenic contaminants containing an -NO2 group. For validation of the new technique, a direct comparison of the 2,4,6-trinitrotoluene (TNT) spectrum, obtained by attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy coupled with TLC, was carried out. The MIR laser spectroscopy-based method was evaluated by calculating the analytical figures of merit regarding the calibration curves’ linearity and the method’s sensitivity and precision. The TNT spectrum obtained by the MIR laser method showed two prominent and characteristic bands of the explosive at approximately 1350 cm⁻¹ and 1550 cm⁻¹ compared to the spectrum acquired by ATR-FTIR. The detection limit calculated for TNT was 84 ng, while the quantification limit was 252 ng. Multivariate analysis was used to evaluate the spectroscopic data to identify sources of variation and determine their relation. Partial least squares (PLS) regression analysis and PLS combined with discriminant analysis (PLS-DA) were used for quantification and classification. The new technique, TLC-QCL, is amenable to a smaller footprint with further developments in MIR laser technology, making it portable for fieldwork.

Background The psychometric properties of the Satisfaction with Life Scale for Children (SWLS-C) are presented (Gadermann et al., Soc Indic Res 96:229–47, 2010). Methods A total of 1,242 children participated (48.3% boys and 51.7% girls), aged between 10 and 14 years (M = 12.19, SD = 1.54). A confirmatory factor analysis (CFA) was conducted to evaluate the factorial structure of the SWLS-C, assuming a unidimensional model using the diagonally weighted least squares (DWLS) estimation method due to the lack of normality assumption. Internal consistency was calculated using Cronbach's alpha and McDonald's omega, and convergent validity was assessed using the Spearman Rho coefficient between the total SWLS-C score and the Life Satisfaction evaluations from the SLSS and the Perceived Social Support scale by Zimet. The effect of age and sex variables was estimated as predictors through a multivariate regression model. Results The fit and goodness indices (RMSEA =.058, CFI =.098, TLI =.096, GFI =.099). Conclusions Show that the scale is valid and reliable for assessing life satisfaction in Colombian children and adolescents.

The rapid expansion of the IoT has led to increasing concerns about security, particularly in the early stages of communication where many IoT application-layer protocols, such as CoAP and MQTT, lack native support for secure key exchange. This absence exposes IoT systems to critical vulnerabilities, including dictionary attacks, session hijacking, and MitM threats, especially in resource-constrained environments. To address this challenge, this paper proposes the integration of OWL, a password-authenticated key exchange (PAKE) protocol, into existing IoT communication frameworks. OWL introduces a lightweight and secure mechanism for establishing high-entropy session keys from low-entropy credentials, without reliance on complex certificate infrastructures. Its one-round exchange model and resistance to both passive and active attacks make it particularly well-suited for constrained devices and dynamic network topologies. The originality of the proposal lies in embedding OWL directly into protocols like CoAP, enabling secure session establishment as a native feature rather than as an auxiliary security layer. Experimental results and formal analysis indicate that OWL achieves reduced authentication latency and lower computational overhead, while enhancing scalability, resilience, and protocol performance. The proposed solution provides an innovative, practical, and efficient framework for securing IoT communications from the foundational protocol level.

Background: Hashimoto’s thyroiditis (HT) is the most common autoimmune thyroid disease (AITD) and is characterized by the presence of thyroid autoantibodies against thyroid peroxidase and/or thyroglobulin. Several studies have found that the global prevalence of HT has increased in recent decades, while others show the opposite. Methods and Results: The objective of this scoping review was to synthesize and analyze the different studies that have evaluated the prevalence of HT (in adults) and the possible associated factors. The following databases were consulted, as follows: MEDLINE, Web of Science, PubMed, and Scopus. The search terms “epidemiology”, “prevalence”, and “Hashimoto disease” and “Hashimoto thyroiditis” were used. The search was limited to articles published between January 1965 and October 2024, and only articles in English were considered. In order to reduce selection bias, each article was scrutinized using the JBI Critical Appraisal Checklist independently by two authors. Studies were included if the number of participants (study population and/or cases and controls, depending on the study design) was clearly described and duplicate studies were excluded. A total of 59 studies were identified, the vast majority of them used a cross-sectional design, using different methods of disease assessment. Conclusions: Globally, the prevalence of HT is estimated to be between 5–10%; some areas with prevalences > 20% and others < 0.5% were identified. Prevalence is also higher in women than in men. Multiple underlying factors (genetic, epigenetic, environmental, and lifestyle), together with socioeconomic, nutritional, overdiagnosis, inter alia, may explain (at least in part) the wide variability in the prevalence of HT.

Controlling forage quality and grazing are crucial for sustainable livestock production, health, productivity, and animal performance. However, the limited availability of reliable handheld sensors for timely pasture quality prediction hinders farmers’ ability to make informed decisions. This study investigates the in-field dynamics of Mombasa grass (Megathyrsus maximus) forage biomass production and quality using optical techniques such as visible imaging and near-infrared (VIS-NIR) hyperspectral proximal sensing combined with machine learning models enhanced by covariance-based error reduction strategies. Data collection was conducted using a cellphone camera and a handheld VIS-NIR spectrometer. Feature extraction to build the dataset involved image segmentation, performed using the Mahalanobis distance algorithm, as well as spectral processing to calculate multiple vegetation indices. Machine learning models, including linear regression, LASSO, Ridge, ElasticNet, k-nearest neighbors, and decision tree algorithms, were employed for predictive analysis, achieving high accuracy with R² values ranging from 0.938 to 0.998 in predicting biomass and quality traits. A strategy to achieve high performance was implemented by using four spectral captures and computing the reflectance covariance at NIR wavelengths, accounting for the three-dimensional characteristics of the forage. These findings are expected to advance the development of AI-based tools and handheld sensors particularly suited for silvopastoral systems.

A hybrid material composed of IRMOF-3 and ZnO (IRMOF-3/ZnO) was synthesized to enhance photocatalytic methylene blue (MB) degradation under visible-light irradiation. Scanning electron microscopy, Fourier-transform infrared spectroscopy, X-ray diffraction, and diffuse-reflectance UV-Vis analyses confirmed the successful integration of ZnO into the IRMOF-3 framework. Compared with unmodified IRMOF-3, the hybrid demonstrated superior MB decomposition, as evidenced by faster reaction rate constants and shorter half-lives. Monitoring the MB absorbance at 670 nm (λmax) revealed more pronounced colorant removal when IRMOF-3/ZnO was exposed to a visible-light source. Diffuse-reflectance UV-Vis spectroscopy showed that IRMOF-3 has a band gap of 2.7 eV, whereas IRMOF-3/ZnO exhibits a slightly higher band gap of 2.8 eV. This modest shift, coupled with the strong interaction between the ZnO semiconductor and the MOF’s amine functionalities, enabled two distinct energy-transfer pathways: intermolecular transfer from IRMOF-3 linkers (acting as visible-light antennas) to ZnO, and intramolecular transfer from Zn to IRMOF-3. Together, these pathways generated abundant free radicals for efficient dye degradation. Despite the necessity for careful synthesis protocols and control of operating conditions to preserve the MOF structure and optimize ZnO loading, the IRMOF-3/ZnO hybrid shows promise as a robust, cost-effective photocatalyst for water-pollutant remediation, taking advantage of the more abundant visible region of solar light.

Background: Suicide is a global public health issue, particularly in low- and middle-income countries and among vulnerable groups such as adolescents. Despite increasing research efforts, understanding the psychosocial factors associated with suicidal behavior remains a challenge. This study examines family and personal histories of suicidal behavior, exposure to violence, empathy, and perceived social support in adolescents who have received healthcare services in Ecuador. Methods: A cross-sectional study was conducted with 438 adolescents aged 12 to 18 years. Participants were classified into suicide attempt survivors (AS, n = 58) and non-attempters (NAS, n = 380). A characterization questionnaire was applied (prior hospitalization for suicide attempt, family history, and survivor condition), the Alexian Brother Urge to Self-Injure scale, the Plutchik Suicide Risk Scale, the Multidimensional Scale of Perceived Social Support, and the Cognitive and Affective Empathy Test. Results: Adolescents with a history of suicide attempts exhibited higher levels of self-injurious behavior impulse (OR = 8.90, CI 95% [4.28-18.52], p < 0.001), Gravity attempt (OR = 8.162, CI 95% [4.34-15.37], p < 0.001), and suicide risk (OR = 2.90, CI 95% [1.42-5.94], p = 0.006). A significant association was found between suicide attempts and exposure to domestic (p = 0.000), school (p = 0.000), and sexual violence (p = 0.000). A family history of suicide attempts increased the likelihood of suicidal behavior in adolescents (OR = 2.40, CI 95% [1.12-5.16], p = 0.022). In contrast, perceived family support acted as a potential protective factor (OR = 0.36, CI 95% [0.15-0.91], p = 0.055). Conclusions: These findings highlight the need for prevention strategies that address social and developmental factors.

This study evaluates DNA damage and multi-element exposure in populations from La Mojana, a region of North Colombia heavily impacted by artisanal and small-scale gold mining (ASGM). DNA damage markers from the cytokinesis-block micronucleus cytome (CBMN-Cyt) assay, including micronucleated binucleated cells (MNBN), nuclear buds (NBUDs) and nucleoplasmic bridges (NPB), were assessed in 71 exposed individuals and 37 unexposed participants. Exposed individuals had significantly higher MNBN frequencies (PR = 1.26, 95% CI: 1.02–1.57, p = 0.039). Principal Component Analysis (PCA) identified the “Soil-Derived Mining-Associated Elements” (PC1), including V, Fe, Al, Co, Ba, Se and Mn, as being strongly associated with high MNBN frequencies in the exposed population (PR = 10.45, 95% CI: 9.75–12.18, p < 0.001). GAMLSS modeling revealed non-linear effects of PC1, with greater increases in MNBN at higher concentrations, especially in exposed individuals. These results highlight the dual role of essential and toxic elements, with low concentrations being potentially protective but higher concentrations increasing genotoxicity. Women consistently exhibited higher MNBN frequencies than men, suggesting sex-specific susceptibilities. This study highlights the compounded risks of chronic metal exposure in mining-impacted regions and underscores the urgent need for targeted interventions to mitigate genotoxic risks in vulnerable populations.

Gestational malaria is a life-threatening disease that affects pregnant women in endemic regions. Infection with parasites of the genus Plasmodium, transmitted by infected mosquitoes, can trigger complications for the mother and fetus. We present the description of a clinical case of gestational malaria complicated by Plasmodium vivax in a 25-year-old multiparous patient in the third trimester of pregnancy from an endemic area in the department of Córdoba, Colombia. Admission to the intensive care unit for 3 days and an emergency cesarean section were necessary due to serious complications, such as anemia, severe thrombocytopenia, and hypertensive symptoms. Treatment included the use of chloroquine and red blood cell and platelet transfusions to address hematologic complications. After the cesarean section, the patient made a satisfactory recovery and was prescribed primaquine for 14 days. The importance of surveillance and adequate management of gestational malaria is highlighted to prevent serious complications during pregnancy and in the postpartum period. This clinical case highlights the complexity of gestational malaria and the need for a comprehensive approach to its management, with special attention to hematologic, hypertensive, and obstetric complications that may arise in this clinical context.

Pipeline filling and emptying are critical hydraulic procedures involving transient two-phase air–water interactions, which can cause pressure surges and structural risks. Traditional Digital Twin models rely on one-dimensional (1D) approaches, which cannot capture air–water interactions. This study integrates Computational Fluid Dynamics (CFD) models into a Digital Twin framework for improved predictive analysis. A CFD-based Digital Twin is developed and validated using real-time pressure measurements, incorporating 2D and 3D CFD models, mesh sensitivity analysis, and calibration procedures. Key contributions include a CFD-driven Digital Twin for real-time monitoring and machine learning (ML) techniques to optimise pressure surges. ML models trained with experimental and CFD data reduce reliance on computationally expensive CFD simulations. Among the 31 algorithms tested, decision trees, efficient linear models, and ensemble classifiers achieved 100% accuracy for filling processes, while k-Nearest Neighbours (KNN) provided 97.2% accuracy for emptying processes. These models effectively predict hazardous pressure peaks and vacuum conditions, confirming their reliability in optimising pipeline operations while significantly reducing computational time.

We investigated the hysteresis, pseudo-critical, and compensation behaviors of a quasi-spherical FeCo alloy nanoparticle (2 nm in diameter) using Monte Carlo simulations with thermal bath-type algorithms and a 3D mixed Ising model. The nanostructure was modeled in a body-centered cubic lattice (BCC) through the following configurations: spin S=3/2 for Co and Q=2 for Fe. These simulations reveal that, under the influence of crystal and magnetic fields, the nanoparticle exhibits compensation phenomena, exchange bias, and pseudo-critical temperatures. Knowledge of this type of phenomena is crucial for the design of new materials, since compensation temperatures and exchange bias improve the efficiency of advanced magnetic devices, such as sensors and magnetic memories. Meanwhile, pseudo-critical temperatures allow the creation of materials with controlled phase transitions, which is vital for developing technologies with specific magnetic and thermal properties. An increase in single-ion anisotropies within the nanosystem leads to higher pseudo-critical and compensation temperatures, as well as superparamagnetic behavior at low temperatures.

Introduction: At present, cancer represents one of the main causes of mortality both globally and in Colombia, with a growing trend that could position it as the leading cause of death shortly, surpassing other diseases of great health impact. Cardiotoxicity associated with antineoplastic treatments can manifest itself at different times, either during the administration of chemotherapy or sometime after its completion, becoming evident only when clinical complications such as heart failure have developed. Therefore, it is essential to use diagnostic tools to identify patients at greater risk of developing cardiotoxicity associated with administering chemotherapeutic agents. Methods: We conducted a descriptive observational cohort study, which included patients over 18 years of age with an active diagnosis of cancer, both of hematological or nonhematological origin, who were treated in a university hospital in Colombia between 2016 and 2019. Results: One hundred ninety-seven patients were included, with a mean age of 53. During follow-up, 20 patients (10%) developed cardiotoxicity, with an incidence density of 3.64% person-months. Dyslipidemia was the most prevalent comorbidity (45%), followed by arterial hypertension (28.7%). Non-Hodgkin's lymphoma was the most frequent oncologic diagnosis (40.3%), with an incidence of cardiotoxicity of 13%. Patients exposed to anthracyclines had a higher incidence of cardiotoxicity (11.8%) compared to those not exposed (5.7%), with a relative risk of 2.074 (95% confidence interval = 1.91-2.24). The left ventricular ejection fraction was significantly lower in patients with cardiotoxicity (55.3%) compared to those without cardiotoxicity (62.1%) (p = 0.029). Conclusions: Taking into account the usefulness of echocardiography and the use of biomarkers found in this study and referred to in the literature, we can determine that these studies, far from being routine, are one of the main strategies that the clinician has to favor the early and timely identification of those patients who are developing a cardiotoxic effect; therefore, it is essential to include these tools in the algorithms of care as a model of serial monitoring. This is not only to reduce the incidence of cardiotoxicity but also as part of an integral management of the oncologic patient to increase the efficiency of pharmacological treatment and improve the quality of life of the patients treated in the short, medium, and long term.

El objetivo de la investigación fue analizar el comportamiento de las exportaciones de café colombiano de la partida 090111190000 durante el periodo 2019-2023, considerando los efectos de la crisis climática en la producción. La metodología adoptó un enfoque cuantitativo y descriptivo, con un diseño no experimental lon-gitudinal, utilizando datos de Trademap organizados en Excel. Este enfoque permitió evaluar las variaciones en el valor FOB y las cantidades exportadas hacia diferentes mercados internacionales, especialmente aquellos con una alta demanda como Estados Unidos, Bélgica, Alemania y China. Los resultados indican que Estados Unidos se mantuvo como el principal destino de exportación en términos de valor FOB, acumulando más de 6 millones de dólares, seguido de Bélgica y Alemania. Sin embargo, la tendencia de exportación hacia Estados Unidos mostró un decrecimiento del 33.82% en 2022-2023, mientras que China experimentó un crecimiento significativo del 75.40% en el mismo periodo, lo que lo posiciona como un mercado emergente relevante para las exportaciones colombianas de café. Las conclusiones destacan la importancia de la diversificación de mercados para la sostenibilidad de las exportaciones de café colombiano, especialmente ante la crisis climática que afecta la productividad en regiones tradicionales. Se sugiere que las estrategias de internacionalización deben centrarse en mercados emergentes como China, aprovechando su tendencia de crecimiento, y reforzar las relaciones con Europa para mantener la competitividad del café colombiano en un contexto global cambiante.

The present study explores the [2π + 4π] cycloaddition reaction with the participation of a buta-1,3-diene series with sulfur dioxide. This investigation employs the molecular electron density theory (MEDT), using the 6-311G(d,p) basis set coupled with the MPWB1K method. Analysis of SO2 reactivity reveals a predominance of the monosynaptic basin V(S2) with a population of 3.14 e and asymmetric NBO charges, where sulfur (1.597) acts as an electrophilic site. The study of chemical potentials shows that SO2 (μ = 5.37 eV) reacts with dienes via polar interactions, primarily targeting the nucleophilic carbons C1 and C7. The activation energies, ranging from 10.44 to 14.95 kcal.mol⁻¹, indicate high barriers, with thermodynamically stable products (∆G range from − 7.35 to − 10.45 kcal.mol⁻¹). The ELF and QTAIM results reveal complex electronic reorganizations without covalent bonds at the transition states, highlighting significant non-covalent interactions. Among the products, P3 stands out for its high binding affinity (− 6.6 kcal.mol⁻¹) and promising ADMET profile, suggesting potential applications in molecular modeling and protein interaction, despite CYP1A2 inhibition.

Considering the limitations of monotherapies due to chemoresistance and side effects, this research aimed to determine whether low doses of sulforaphane (SFN) combined with docetaxel (DCT) could enhance therapeutic efficacy. Prostate cancer cell lines LNCaP and PC-3 were treated with individual IC50 doses of SFN and DCT and half-reduced IC50 values for the SFN:DCT combination. Metabolic markers, including glucose consumption, lactate production, reactive oxygen species (ROS), mitochondrial mass, and caspase activity, were assessed. In LNCaP cells, the SFN:DCT combination reduced cell viability to 50%, comparable to DCT monotherapy (48%). Caspase 3 activation was also higher with SFN:DCT (2.4 ± 0.75 RFU) than DCT alone (2.1 ± 0.47 RFU), while caspase 8 activation remained comparable, indicating equivalent effectiveness at lower concentrations. In PC-3 cells, the combination induced caspase 3 activation (1.16 ± 0.0484 RFU) at levels slightly lower than DCT (1.51 ± 0.2062 RFU) but achieved greater reductions in mitochondrial mass, reflecting its ability to target metabolic vulnerabilities in aggressive phenotypes. Our findings suggest that the SFN:DCT combination is a promising strategy for early-stage prostate cancer. By achieving comparable efficacy to DCT monotherapy at low doses, the SFN:DCT combination maintains the therapeutic impact, mitigating the adverse effects of conventional DCT treatment.