Using image segmentation models to analyse high-resolution earth observation data: new tools to monitor disease risks in changing environments.

BACKGROUND: In the near future, the incidence of mosquito-borne diseases may expand to new sites due to changes in temperature and rainfall patterns caused by climate change. Therefore, there is a need to use recent technological advances to improve vector surveillance methodologies. Unoccupied Aerial Vehicles (UAVs), often called drones, have been used to collect high-resolution imagery to map detailed information on mosquito habitats and direct control measures to specific areas. Supervised classification approaches have been largely used to automatically detect vector habitats. However, manual data labelling for model training limits their use for rapid responses. Open-source foundation models such as the Meta AI Segment Anything Model (SAM) can facilitate the manual digitalization of high-resolution images. This pre-trained model can assist in extracting features of interest in a diverse range of images. Here, we evaluated the performance of SAM through the Samgeo package, a Python-based wrapper for geospatial data, as it has not been applied to analyse remote sensing images for epidemiological studies. RESULTS: We tested the identification of two land cover classes of interest: water bodies and human settlements, using different UAV acquired imagery across five malaria-endemic areas in Africa, South America, and Southeast Asia. We employed manually placed point prompts and text prompts associated with specific classes of interest to guide the image segmentation and assessed the performance in the different geographic contexts. An average Dice coefficient value of 0.67 was obtained for buildings segmentation and 0.73 for water bodies using point prompts. Regarding the use of text prompts, the highest Dice coefficient value reached 0.72 for buildings and 0.70 for water bodies. Nevertheless, the performance was closely dependent on each object, landscape characteristics and selected words, resulting in varying performance. CONCLUSIONS: Recent models such as SAM can potentially assist manual digitalization of imagery by vector control programs, quickly identifying key features when surveying an area of interest. However, accurate segmentation still requires user-provided manual prompts and corrections to obtain precise segmentation. Further evaluations are necessary, especially for applications in rural areas.

Automated deep learning segmentation of neuritic plaques and neurofibrillary tangles in Alzheimer disease brain sections using a proprietary software.

Neuropathological diagnosis of Alzheimer disease (AD) relies on semiquantitative analysis of phosphorylated tau-positive neurofibrillary tangles (NFTs) and neuritic plaques (NPs), without consideration of lesion heterogeneity in individual cases. We developed a deep learning workflow for automated annotation and segmentation of NPs and NFTs from AT8-immunostained whole slide images (WSIs) of AD brain sections. Fifteen WSIs of frontal cortex from 4 biobanks with varying tissue quality, staining intensity, and scanning formats were analyzed. We established an artificial intelligence (AI)-driven iterative procedure to improve the generation of expert-validated annotation datasets for NPs and NFTs thereby increasing annotation quality by >50%. This strategy yielded an expert-validated annotation database with 5013 NPs and 5143 NFTs. We next trained two U-Net convolutional neural networks for detection and segmentation of NPs or NFTs, achieving high accuracy and consistency (mean Dice similarity coefficient: NPs, 0.77; NFTs, 0.81). The workflow showed high generalization performance across different cases. This study serves as a proof-of-concept for the utilization of proprietary image analysis software (Visiopharm) in the automated deep learning segmentation of NPs and NFTs, demonstrating that AI can significantly improve the annotation quality of complex neuropathological features and enable the creation of highly precise models for identifying these markers in AD brain sections.

Habitat selection and refuge-use by a color polymorphic salamander reveal behavioral niche differences.

Color polymorphic species provide an excellent opportunity to investigate the ecology and evolution of intraspecific niche differences. The red-backed salamander, Plethodon cinereus, is a fully terrestrial lungless salamander with two common color forms, striped and unstriped. Previous research suggests the morphs may be differentially adapted to surface and subsurface microhabitats, with the unstriped morph being more fossorial. This hypothesis predicts that the unstriped morph should be more sensitive to the risks of surface activity (e.g., thermal stress, dehydration, predation), and therefore be more selective than striped morphs when choosing soil surface microhabitats. To test this hypothesis, we experimentally manipulated leaf litter mass in small forest patches (~0.45 m2). Leaf litter addition reduced soil temperatures, buffered against changes in air temperature, and likely provided physical protection from predators. Over 3 years, we found that unstriped adults responded positively to leaf litter addition, but striped adults did not. In addition, unstriped morphs spent significantly more time in protective refuges (opaque, moistened tubes) than striped morphs in laboratory assays. Taken together, the field and laboratory results support the hypothesis that the unstriped morph is more sensitive to the risks of surface activity, and therefore is more likely to be fossorial. This difference in microhabitat use, combined with spatiotemporal variation in leaf litter accumulation on the forest floor, may play an important role in the maintenance of the polymorphism.

Criterios de aislamiento preventivo para la detección de portadores de bacterias multirresistentes en pacientes ingresados en la UCI: estudio multicéntrico dentro del programa Resistencia Zero / Preventive isolation criteria for multidrug-resistant bacteria detection in patients admitted to the ICU: Multicenter study within the Zero Resistance program

Objetivo: Conocer el rendimiento de los criterios de aislamiento preventivo del programa Resistencia Zero (RZ) e identificar los factores que pudieran mejorar su rendimiento. Diseño: Estudio de cohorte prospectivo y multicéntrico. Ámbito: Unidades de cuidados críticos que aplicaban el protocolo RZ, y que aceptaron la invitación al estudio. Pacientes o participantes: Pacientes a los que se les realizaron cultivos de vigilancia (nasal, faríngeo, axilar y rectal) y/o diagnósticos al ingreso en la UCI. Intervenciones: Análisis de los factores de riesgo (FR) RZ y otras variables del registro ENVIN. Se realizó un estudio univariable y multivariable con metodología de regresión logística binaria (significación con p<0,05). Se efectuó análisis de sensibilidad y especificidad para cada uno de los factores seleccionados. Variables de interés principales: Portador de bacteria multirresistente (BMR) al ingreso en la UCI, FR (antecedente de colonización/infección por BMR, ingreso hospitalario en los 3 meses previos, uso de antibiótico el mes previo, estar institucionalizado, diálisis y otras condiciones crónicas) y comorbilidades. Resultados: Participaron 2.252 pacientes de 9 UCI españolas. Fueron identificados BMR en 283 (12,6%). Ciento noventa y tres (68,2%) presentaban algún FR (OR: 4,6; IC 95%: 3,5-6,0). Todos los FR del programa RZ alcanzaron significación estadística (sensibilidad: 66%; especificidad: 79%), siendo el antecedente de BMR el factor con más peso. Inmunodepresión, tratamiento antibiótico al ingreso y sexo masculino son FR adicionales para BMR. Se aislaron BMR en 87 (31,8%) sin FR. (AU)

Objective: To verify the validity of a check list of risk factors (RF) proposed by the Spanish “Resistencia Zero” project (RZ) in the detection of multi-resistant bacteria (MRB), as well as to identify other possible RF for colonization and infection by MRB at intensive care (ICU) admission. Design: A prospective cohort study, conducted in 2016. Setting: Multicenter study, patients who needed admission to adult critical care units that applied the RZ protocol and accepted the invitation for the study. Patients or participants: Consecutive sample of patients admitted to ICU, who underwent surveillance (nasal, pharyngeal, axillary, and rectal) or clinical cultures. Interventions: Analysis of the RF of RZ project, in addition to other comorbidities, included in the ENVIN registry. A univariate and multivariate study was conducted, with binary logistic regression methodology (significance with P<.05). Sensitivity and specificity analyses were performed for each of the selected factors. Main variables of interest: Carrier of BMR at ICU admission, RF (previous MRB colonization/infection, hospital admission in the previous 3 months, antibiotic use in the past month, institutionalization, dialysis, and other chronic conditions) and comorbidities. Results: Two thousand two hundred and seventy patients were included from 9 Spanish ICUs. We identified BMR in 288 (12.6% of total patients admitted). One hundred and ninety-three (68.2%) had some RF (OD 4.6 -95% CI 3.5-6.0). All 6 RF from check list achieved statistical significance in the univariate analysis (sensitivity 66%, specificity 79%). Immunosuppression, antibiotic use at ICU admission and male gender were additional RF for BMR. BMR were isolated in 87 patients (31.8%) without RF. (AU)

Efficacy, Pharmacokinetics, and Toxicity Profiles of a Broad Anti-SARS-CoV-2 Neutralizing Antibody.

We recently reported the isolation and characterization of an anti-SARS-CoV-2 antibody, called IgG-A7, that protects transgenic mice expressing the human angiotensin-converting enzyme 2 (hACE-2) from an infection with SARS-CoV-2 Wuhan. We show here that IgG-A7 protected 100% of the transgenic mice infected with Delta (B.1.617.2) and Omicron (B.1.1.529) at doses of 0.5 and 5 mg/kg, respectively. In addition, we studied the pharmacokinetic (PK) profile and toxicology (Tox) of IgG-A7 in CD-1 mice at single doses of 100 and 200 mg/kg. The PK parameters at these high doses were proportional to the doses, with serum half-life of ~10.5 days. IgG-A7 was well tolerated with no signs of toxicity in urine and blood samples, nor in histopathology analyses. Tissue cross-reactivity (TCR) with a panel of mouse and human tissues showed no evidence of IgG-A7 interaction with the tissues of these species, supporting the PK/Tox results and suggesting that, while IgG-A7 has a broad efficacy profile, it is not toxic in humans. Thus, the information generated in the CD-1 mice as a PK/Tox model complemented with the mouse and human TCR, could be of relevance as an alternative to Non-Human Primates (NHPs) in rapidly emerging viral diseases and/or quickly evolving viruses such as SARS-CoV-2.

Implantación de un equipo de asistencia al trauma grave. Análisis de la activación y tiempos de asistencia en pacientes ingresados en UCI / Implementation of a severe trauma assistance team: Analysis of activation and attendance times in patients admitted to the ICU

Objetivo Analizar los factores asociados a la activación del equipo de asistencia al trauma grave (EATG) en pacientes que ingresan en la Unidad de Cuidados Intensivos (UCI), medir su repercusión en los tiempos de asistencia, y analizar los grupos de pacientes según activación y nivel de afectación anatómica. Diseño Estudio de cohortes prospectivo del trauma grave que ingresan en UCI. Desde junio 2017 a mayo 2019. Factores de riesgo de la activación analizados con regresión logística y árbol de clasificación tipo CART. Ámbito UCI hospital de segundo nivel. Pacientes Pacientes ingresados de forma consecutiva. Intervenciones Ninguna. Variables de intereses principales Activación del EATG. Variables demográficas. Puntuación de la gravedad de la lesión (ISS), intencionalidad, mecanismo, tiempos de asistencia, complicaciones evolutivas y mortalidad. Resultados Ingresaron un total de 188 pacientes (46,8% de activación EATG), edad mediana de 52 (37-64) años (activados 47 (27-62) vs. no activados 55 (42-67) p = 0,023), varones 84,0%. No diferencias en la mortalidad según activación. El modelo logístico encuentra como factores: la atención (16,6 [2,1-13,2]) e intubación prehospitalaria (4,2 [1,8-9,8]) y, la lesión grave de extremidades inferiores (4,4 [1,6-12,3]). Padecer una caída accidental (0,2 [0,1-0,6]) hace menos probable la activación. El modelo CART selecciona el tipo de mecanismo del traumatismo y es capaz de separar los traumatismos de alta y baja energía. Conclusiones Los factores asociados con activación del ETAG fueron la atención prehospitalaria, requerir intubación previa, mecanismos de alta energía y lesiones graves de extremidades inferiores. Menores tiempos de asistencia si activación sin influir en la mortalidad. Debemos mejorar la activación en pacientes mayores con traumatismos de baja energía y sin atención prehospitalaria (AU)

Objective To analyse the factors associated with the activation of the severe trauma care team (STAT) in patients admitted to the ICU, to measure its impact on care times, and to analyse the groups of patients according to activation and level of anatomical involvement. Design Prospective cohort study of severe trauma admitted to the ICU. From June 2017 to May 2019. Risk factors for the activation of the STAT analysed with logistic regression and CART type classification tree. Setting Second level hospital ICU. Patients Patients admitted consecutively. Interventions No. Main variables of interest STAT activation, demographic variables, injury severity (ISS), intentionality, mechanism, assistance times, evolutionary complications, and mortality. Results A total of 188 patients were admitted (46.8% of STAT activation), median age of 52 (37–64) years (activated 47 (27–62) vs. not activated 55 (42–67), p = 0.023), males 84.0%. No difference in mortality according to activation. The logistic model finds as factors: care (16.6 (2.1–13.2)) and prehospital intubation (4.2 (1.8–9.8)) and severe lower extremity injury (4.4 (1.6–12.3)). Accidental fall (0.2 (0.1–0.6)) makes activation less likely. The CART model selects the type of trauma mechanism and can separate high and low energy trauma. Conclusions Factors associated with STAT activation were prehospital care, requiring prior intubation, high-energy mechanisms, and severe lower extremity injuries. Shorter care times if activated without influencing mortality. We must improve activation in older patients with low-energy trauma and without prehospital care (AU)

Preventive isolation criteria for the detection of multidrug-resistant bacteria in patients admitted to the Intensive Care Unit: A multicenter study within the Zero Resistance program.

OBJECTIVE: To verify the validity of a checklist of risk factors (RFs) proposed by the Spanish "Zero Resistance" project (ZR) in the detection of multidrug-resistant bacteria (MRB), and to identify other possible RFs for colonization and infection by MRB on admission to the Intensive Care Unit (ICU). DESIGN: A prospective cohort study, conducted in 2016. SETTING: Multicenter study, patients requiring admission to adult ICUs that applied the ZR protocol and accepted the invitation for participating in the study. PATIENTS OR PARTICIPANTS: Consecutive sample of patients admitted to the ICU and who underwent surveillance (nasal, pharyngeal, axillary and rectal) or clinical cultures. INTERVENTIONS: Analysis of the RFs of the ZR project, in addition to other comorbidities, included in the ENVIN registry. A univariate and multivariate analysis was performed, with binary logistic regression methodology (significance considered for p < 0.05). Sensitivity and specificity analyses were performed for each of the selected factors. MAIN VARIABLES OF INTEREST: Carrier of MRB on admission to the ICU, RFs (previous MRB colonization/infection, hospital admission in the previous 3 months, antibiotic use in the past month, institutionalization, dialysis, and other chronic conditions) and comorbidities. RESULTS: A total of 2270 patients from 9 Spanish ICUs were included. We identified MRB in 288 (12.6% of the total patients admitted). In turn, 193 (68.2%) had some RF (OR 4.6, 95%CI: 3.5-6.0). All 6 RFs from the checklist reached statistical significance in the univariate analysis (sensitivity 66%, specificity 79%). Immunosuppression, antibiotic use on admission to the ICU and the male gender were additional RFs for MRB. MRB were isolated in 87 patients without RF (31.8%). CONCLUSIONS: Patients with at least one RF had an increased risk of being carriers of MRB. However, almost 32% of the MRB were isolated in patients without RFs. Other comorbidities such as immunosuppression, antibiotic use on admission to the ICU and the male gender could be considered as additional RFs.

Exploring self-regulation theory as a mechanism of the effects of psychological contract fulfillment: The role of emotional intelligence.

As self-regulation theory has increasingly been used as a theoretical lens to explain the effects of psychological contract evaluations and employee outcomes, we test whether emotional intelligence (an ability for self-regulation) is a potential moderator of these relationships. More concretely, using a multiple times survey design in an education-based organization with 247 participants, we examined whether emotional intelligence moderates the mediation effect of emotional exhaustion on the relationship between psychological contract fulfillment and turnover intentions. Using a structural equations model (SEM) framework, our results support our hypotheses that individuals with low emotional intelligence do not experience the benefits of having fulfilled psychological contracts. Psychological contract fulfillment significantly reduces the likelihood of emotional exhaustion but only for individuals with high emotional intelligence. Consequently, turnover intentions are lower for emotionally intelligent individuals who experience the fulfillment of psychological contracts. Theoretical and practical implications are discussed. We conclude our study by suggesting that emotional intelligence should be considered as a relevant individual difference in future psychological contract research.

Utilizing Contrast-Enhanced Ultrasonography with Phosphatidylserine Microbubbles to Detect Placental Inflammation in Rhesus Macaques.

The ability to comprehensively monitor physiological and detect pathophysiologic processes early during pregnancy can reduce maternal and fetal morbidity and mortality. Contrast-enhanced ultrasound (CEUS) is a non-invasive imaging technology that utilizes the acoustic detection of microbubbles to examine vascular spaces. Furthermore, microbubbles conjugated to specific compounds can focus studies on precise physiological pathways. We hypothesized that CEUS with phosphatidylserine microbubbles (MB-PS) could be employed to monitor placental inflammation. We tested this hypothesis in rhesus macaques (Macaca mulatta), a translational and relevant animal model of human placental health. As placental inflammation impacts many at-risk pregnancies, we performed CEUS with MB-PS in pregnant macaques fed a high-fat diet (e.g., a western-style diet, WSD) in the presence or absence of testosterone (T) to mimic the increased risk of polycystic ovary syndrome and subfertility. We have previously demonstrated a placental inflammation phenotype in this model, and, thus, we related the MB-PS CEUS signal intensity to placental inflammation markers: selectin p and angiopoietins. Testosterone exposure increased the MB-PS signal in the placental microcirculation on the maternal side compared to control animals. We found that T increased placental weight and decreased angiopoietin 2 (ANGPT2) immunoreactivity. Furthermore, a significant inverse correlation was found between MB-PS signal and ANGPT2. This indicated that CEUS with MB-PS can be used to monitor placental parameters. We propose that CEUS with MB-PS could aid in the identification of pregnancies at risk of placental vascular compromise.

Anti-HLA Class I alloantibodies in platelet transfusion refractoriness: From mechanisms and determinants to therapeutic prospects.

Patients with hematological disorders and severe thrombocytopenia require extensive and iterative platelet transfusion support. In these patients, platelet transfusion refractoriness represents a serious adverse transfusion event with major outcomes for patient care. Recipient alloantibodies against the donor HLA Class I antigens expressed at the cell surface of platelets result in a rapid removal of transfused platelets from the circulation and thus, therapeutic and prophylactic transfusion failure leading to a major bleeding risk. In this case, the only way to support the patient relies on the selection of HLA Class I compatible platelets, an approach restricted by the limited number of HLA-typed donors available and the difficulty of meeting the demand in an emergency. However, not all patients with anti-HLA Class I antibodies develop refractoriness to platelet transfusions, raising the question of the intrinsic characteristics of the antibodies and the immune-mediated mechanisms of platelet clearance associated with a refractory state. In this review, we examine the current challenges in platelet transfusion refractoriness and detail the key features of the antibodies involved that should be considered. Finally, we also provide an overview of future therapeutic strategies.

Detection and genetic characterization of feline retroviruses in domestic cats with different clinical signs and hematological alterations.

Feline leukemia virus (FeLV) and feline immunodeficiency virus (FIV) are globally distributed retroviruses that infect domestic cats and cause various syndromes that can lead to death. The aim of this study was to detect and genotype feline retroviruses in Mexican domestic cats. We used PCR assays to identify proviral DNA and viral RNA in 50 domestic cats with different clinical signs and hematological alterations. Endogenous FeLV (enFeLV) was identified in the genomic DNA of all cats in the study, and we detected transcripts of the LTR region of enFeLV in 48 individuals. Exogenous FeLV (exFeLV) was found in 13 cats. Furthermore, we detected FIV proviral DNA in 10 cats. The enFeLV sequences were shown to be the most variable, while the exFeLV sequences were highly conserved and related to previously reported subgroup A sequences. Sequencing of the FIV gag gene revealed the presence of subtype B in the infected cats.

Reversible Shielding and Immobilization of Liposomes and Viral Vectors by Tailored Antibody-Ligand Interactions.

Controlling the time and dose of nanoparticulate drug delivery by administration of small molecule drugs holds promise for efficient and safer therapies. This study describes a versatile approach of exploiting antibody-ligand interactions for the design of small molecule-responsive nanocarrier and nanocomposite systems. For this purpose, antibody fragments (scFvs) specific for two distinct small molecule ligands are designed. Subsequently, the surface of nanoparticles (liposomes or adeno-associated viral vectors, AAVs) is modified with these ligands, serving as anchor points for scFv binding. By modifying the scFvs with polymer tails, they can act as a non-covalently bound shielding layer, which is recruited to the anchor points on the nanoparticle surface and prevents interactions with cultured mammalian cells. Administration of an excess of the respective ligand triggers competitive displacement of the shielding layer from the nanoparticle surface and restores nanoparticle-cell interactions. The same principle is applied for developing hydrogel depots that can release integrated AAVs or liposomes in response to small molecule ligands. The liberated nanoparticles subsequently deliver their cargoes to cells. In summary, the utilization of different antibody-ligand interactions, different nanoparticles, and different release systems validates the versatility of the design concept described herein.

Structure, Bioactivity and Analytical Methods for the Determination of Yucca Saponins.

Yucca is one of the main sources of steroidal saponins, hence different extracts are commercialized for use as surfactant additives by beverage, animal feed, cosmetics or agricultural products. For a deeper understanding of the potential of the saponins that can be found in this genus, an exhaustive review of the structural characteristics, bioactivities and analytical methods that can be used with these compounds has been carried out, since there are no recent reviews on the matter. Thus, a total of 108 saponins from eight species of the genus Yucca have been described. Out of these, the bioactivity of 68 saponins derived from the isolation of Yucca or other genera has been evaluated. Regarding the evaluation and quality control of the saponins from this genus LC-MS technique is the most often used. Nevertheless, the development of methods for their routine analysis in commercial preparations are needed. Moreover, most of the studies found in the literature have been carried out on Y. schidigera extract, since is the most often used for commercial purposes. Only eight of the 50 species that belong to this genus have been studied, which clearly indicates that the identification of saponins present in Yucca genus is still an unresolved question.

Evaluation of switch-mediated costimulation in trans on universal CAR-T cells (UniCAR) targeting CD123-positive AML.

Chimeric antigen receptor T cells (CAR-T) targeting CD19 have achieved significant success in patients with B cell malignancies. To date, implementation of CAR-T in other indications remains challenging due to the lack of truly tumor-specific antigens as well as control of CAR-T activity in patients. CD123 is highly expressed in acute myeloid leukemia (AML) blasts including leukemia-initiating cells making it an attractive immunotherapeutic target. However, CD123 expression in normal hematopoietic progenitor cells and endothelia bears the risk of severe toxicities and may limit CAR-T applications lacking fine-tuned control mechanisms. Therefore, we recently developed a rapidly switchable universal CAR-T platform (UniCAR), in which CAR-T activity depends on the presence of a soluble adapter called targeting module (TM), and confirmed clinical proof-of-concept for targeting CD123 in AML with improved safety. As costimulation via 4-1BB ligand (4-1BBL) can enhance CAR-T expansion, persistence, and effector functions, a novel CD123-specific TM variant (TM123-4-1BBL) comprising trimeric single-chain 4-1BBL was developed for transient costimulation of UniCAR-T cells (UniCAR-T) at the leukemic site in trans. TM123-4-1BBL-directed UniCAR-T efficiently eradicated CD123-positive AML cells in vitro and in a CDX in vivo model. Moreover, additional costimulation via TM123-4-1BBL enabled enhanced expansion and persistence with a modulated UniCAR-T phenotype. In addition, the increased hydrodynamic volume of TM123-4-1BBL prolonged terminal plasma half-life and ensured a high total drug exposure in vivo. In conclusion, expanding the soluble adapter optionality for CD123-directed UniCAR-T maintains the platforms high anti-leukemic efficacy and immediate control mechanism for a flexible, safe, and individualized CAR-T therapy of AML patients.

Chitin/Metal-Organic Framework Composites as Wide-Range Adsorbent.

Composites based on chitin (CH) biopolymer and metal-organic framework (MOF) microporous nanoparticles have been developed as broad-scope pollutant absorbent. Detailed characterization of the CH/MOF composites revealed that the MOF nanoparticles interacted through electrostatic forces with the CH matrix, inducing compartmentalization of the CH macropores that led to an overall surface area increase in the composites. This created a micro-, meso-, and macroporous structure that efficiently retained pollutants with a broad spectrum of different chemical natures, charges, and sizes. The unique prospect of this approach is the combination of the chemical diversity of MOFs with the simple processability and biocompatibility of CH that opens application fields beyond water remediation.

Intoxicaciones agudas con pesticidas para fines suicidas en Costa Rica durante la década de 2010-2020 / SuicideSuicide attempts due to pesticide poisoning in Costa Rica during the 2010-2020 decade

Resumen Introducción: La intoxicación con plaguicidas es de los métodos más utilizados por los suicidas, especialmente en países agrícolas de ingreso medio-bajo. El objetivo de la investigación fue describir y analizar la situación epidemiológica de la intoxicación aguda por plaguicidas con fines suicidas en Costa Rica durante los años 2010-2020. Materiales y métodos: Se recopilaron datos del Centro Nacional para el Control de Intoxicaciones (CNCI) de las intoxicaciones agudas con plaguicidas para fines suicidas durante el 2010-octubre 2020 y datos del Instituto Nacional de Estadística y Censos (INEC) de las defunciones por suicidios con plaguicidas durante los años 2010-2019. Los datos se analizaron por sexo, edad, provincia, agente tóxico, ruta de absorción, severidad del cuadro clínico y mortalidad. Resultados: De las 3240 intoxicaciones agudas totales con plaguicidas para fines suicidas durante los años 2010-octubre 2020, el 64.7% eran hombres y 35.3% mujeres; 31.9% de las intoxicaciones ocurrieron en personas en edades entre los 20-29 años y 21% entre 30-39 años; 23.4% de los incidentes ocurrieron en la provincia de Alajuela y 19.7% en San José; el 75% de los plaguicidas utilizados eran de uso agrícola; en el 17.2% de las intoxicaciones utilizaron Glifosato y 15.9% Paraquat; en 98.3% de los casos la ruta de absorción fue por ingestión; 65.3% de los casos fueron reportados con sintomatología leve según el CNCI. Durante el 2010-2019, 432 personas murieron por suicidio utilizando plaguicidas, lo que significa una mortalidad anual promedio de 13.3% de las intoxicaciones agudas con plaguicidas para fines suicidas Conclusiones: La epidemiología de los intentos suicidas utilizando pesticidas en CR es muy similar a los patrones internacionales predominando hombres jóvenes en zonas agrícolas y que tienen acceso a los pesticidas. Es necesario fortalecer medidas e implementar políticas para la regulación, almacenaje y manejo adecuado de los plaguicidas.

Abstract Introduction: Pesticides self-poisoning is one of the most popular suicide methods especially in lower middle class income agricultural countries. The objective of this research is to describe and analyze the epidemiological situation of suicide attempts due to pesticide poisoning in Costa Rica during the last decade. Materials and methods: Data of pesticides self-poisoning goes all the way from 2010 until October 2020. That information was collected from the National Center for Poisoning Control (CNCI, stands for the initials in spanish) database and National Institute for Statistics and Census (INEC in spanish) data of pesticides self-poisoning deaths from 2010-2019. All data was analyzed by sex, age, province, toxic agent, route of absorption, clinical severity and mortality. Results: There were 3240 total cases of suicide attempts due to pesticides during 2010-october 2020; 64.7% of this poisoning were in men and 35.3% in women, 31.9% of the poisoning persons were in age with a range between 20-29 years and 21% between 30-39 years old; 23.4% of cases were reported in Alajuela and 19.7% in San José; 75% of the cases used agricultural pesticide; 17.2% of the poisonings occurred due to Glifosato and 15.9% due to Paraquat; ingestion was the route of absorption in 98.3% of the cases; and 65.3% reported mild clinical severity. During 2010-2019, 432 people died due to suicide using pesticides as a weapon, which means an average mortality of 13.3% of all the suicide attempts with pesticides in this period. Conclusions: Costa Rica´s epidemiology of suicide attempts using pesticides is very similar to international epidemiology, where most of the cases are young men that have access to pesticides and lived-in agricultural areas. It´s necessary to implement policies for the regulations, storage and proper management of pesticides in order to prevent suicide.

In vitro Characterization of Anti-SARS-CoV-2 Intravenous Immunoglobulins (IVIg) Produced From Plasma of Donors Immunized With the BNT162b2 Vaccine and Its Comparison With a Similar Formulation Produced From Plasma of COVID-19 Convalescent Donors.

Despite vaccines are the main strategy to control the ongoing global COVID-19 pandemic, their effectiveness could not be enough for individuals with immunosuppression. In these cases, as well as in patients with moderate/severe COVID-19, passive immunization with anti-SARS-CoV-2 immunoglobulins could be a therapeutic alternative. We used caprylic acid precipitation to prepare a pilot-scale batch of anti-SARS-CoV-2 intravenous immunoglobulins (IVIg) from plasma of donors immunized with the BNT162b2 (Pfizer-BioNTech) anti-COVID-19 vaccine (VP-IVIg) and compared their in vitro efficacy and safety with those of a similar formulation produced from plasma of COVID-19 convalescent donors (CP-IVIg). Both formulations showed immunological, physicochemical, biochemical, and microbiological characteristics that meet the specifications of IVIg formulations. Moreover, the concentration of anti-RBD and ACE2-RBD neutralizing antibodies was higher in VP-IVIg than in CP-IVIg. In concordance, plaque reduction neutralization tests showed inhibitory concentrations of 0.03-0.09 g/L in VP-IVIg and of 0.06-0.13 in CP-IVIg. Thus, VP-IVIg has in vitro efficacy and safety profiles that justify their evaluation as therapeutic alternative for clinical cases of COVID-19. Precipitation with caprylic acid could be a simple, feasible, and affordable alternative to produce formulations of anti-SARS-CoV-2 IVIg to be used therapeutically or prophylactically to confront the COVID-19 pandemic in middle and low-income countries.

Serotyping versus genotyping in infected sheep and goats with small ruminant lentiviruses.

Despite SRLV infection being endemic in Mexico, there is little information regarding which genotypes are present. We compared serotyping and PCR-sequencing results from sheep and goats infected with SRLV. We separated plasma and peripheral blood leukocytes (PBL) from 1940 blood samples from sheep and goats from 12 states across Mexico. To detect SRLV infection, we tested plasma samples using two commercial ELISA kits (VMRD and Eradikit SRLV Screening). Then, we serotyped the infecting virus (A/ B) using Eradikit SRLV Genotyping. PBL DNA was used to detect the proviral genome via PCR. Positive amplicons were sequenced to identify viral genotypes using a phylogenetic analysis. Also, we analysed for residues differences in the sequences of a capsid epitope between genotypes. The serological results indicated a higher detection of seropositive animals using the VMRD ELISA compared to Eradikit, with 21 % and 15.3 % more in sheep and goats respectively. Only 25.7 % of the ELISA serotyping results matched those from PCR-sequencing. PCR-sequencing was able to identify genotype A, B and coinfections in animals classified as indeterminate by the ELISA test. This lack of sensitivity may be related to the lack of epitopes from the matrix and transmembrane peptides used by ELISA screening. Sequences analysis revealed that SRLVs found in sheep cluster with genetic subtypes A2 and B1, while those in goats cluster with subtypes A1 and B1. Serotyping did not prove to be an adequate method for predicting the viral genotype (A and / or B) in infections caused by SRLV.

Methodology for the design and economic assessment of anaerobic digestion plants to produce energy and biofertilizer from livestock waste.

The generation and poor disposal of waste from livestock industries is the major cause of pollution of water sources, soil, and air. Therefore, profitable alternatives are required for their correct disposal and use. Anaerobic digestion plants are a technologically viable solution to overcome this problem. In this study, it is proposed a methodology for the design and economic assessment of projects using anaerobic digestion plants to produce electrical energy, thermal energy, and biofertilizer from livestock waste. The methodology is developed based on the assumption that the process is mainly composed of an anaerobic digester and an electric generator having a Diesel-cycle internal combustion engine. It is programmed in "MS Excel" sheet and assessed using technical and economic data from a three real anaerobic digestion plants. The methodology obtains technical parameters such as energy production efficiency with an average difference of 35% compared to the real plants data. In addition, the unit capital costs are calculated, obtaining a value of €3789/kW with a difference of 21.1%, as well as unit operating costs of €729/kW per year with a difference of 15.2%. The financial viability of the project is assessed by calculating the net present value and obtaining €577,050 with a difference of 17.8% and an internal rate of return with a percentage difference of 3%. The proposed methodology specifies the technical parameters and the basic engineering of an anaerobic digestion plant in a stationary state, where the basic streams and dimensions of primary equipment, such as anaerobic reactors and electric generators, are specified. Moreover, the methodology calculates capital and operating expenses for an anaerobic digestion plant, which may be useful to assess the technical and financial feasibility for a project of this type.

Deep Learning for Semantic Segmentation vs. Classification in Computational Pathology: Application to Mitosis Analysis in Breast Cancer Grading.

Existing computational approaches have not yet resulted in effective and efficient computer-aided tools that are used in pathologists' daily practice. Focusing on a computer-based qualification for breast cancer diagnosis, the present study proposes two deep learning architectures to efficiently and effectively detect and classify mitosis in a histopathological tissue sample. The first method consists of two parts, entailing a preprocessing of the digital histological image and a free-handcrafted-feature Convolutional Neural Network (CNN) used for binary classification. Results show that the methodology proposed can achieve 95% accuracy in testing, with an F1-score of 94.35%. This result is higher than the results using classical image processing techniques and also higher than the approaches combining CCNs with handcrafted features. The second approach is an end-to-end methodology using semantic segmentation. Results showed that this algorithm can achieve an accuracy higher than 95% in testing and an average Dice index of 0.6, higher than the existing results using CNNs (0.9 F1-score). Additionally, due to the semantic properties of the deep learning approach, an end-to-end deep learning framework is viable to perform both tasks: detection and classification of mitosis. The results show the potential of deep learning in the analysis of Whole Slide Images (WSI) and its integration to computer-aided systems. The extension of this work to whole slide images is also addressed in the last sections; as well as, some computational key points that are useful when constructing a computer-aided-system inspired by the proposed technology.