Resumen: Tras una cirugía de reemplazo articular, la presencia del material protésico, la intervención quirúrgica y los factores de riesgo del paciente predisponen la aparición de una infección protésica. En general las tasas de infección rondan el 1,5% en las prótesis de cadera y el 2,5% en las de rodilla. Los protocolos de tratamiento consisten en una combinación de medidas quirúrgicas junto con un tratamiento farmacológico sistémico de rifampicina y fluoroquinolonas en monoterapia o en combinación durante al menos 3-9 meses. El desarrollo de nanopartículas cargadas con antibióticos permite la administración selectiva en el lugar de la infección, reduciendo los efectos adversos sistémicos del antibiótico y logrando la liberación controlada del mismo. Por ello, el objetivo del presente trabajo fue el desarrollo de una formulación de nanopartículas poliméricas de ciprofloxacino por el método de doble emulsión (W/O/W) extracción-evaporación del solvente para su administración local en el tratamiento de infecciones protésicas. Para el desarrollo y optimización de las formulaciones se ha empleado el diseño experimental. Se ha realizado un diseño factorial completo (L12) de dos niveles para evaluar y determinar el grado de influencia de diversos parámetros del proceso de elaboración en las características de estos nanosistemas. Gracias a este diseño se determinó que la hidrofobicidad del polímero y la cantidad de ciprofloxacino fueron los únicos factores que mostraron una influencia estadísticamente significativa en el tamaño de partícula y carga de antibiótico de las nanopartículas, respectivamente. Por último, se ha estudiado el perfil de liberación del ciprofloxacino en las formulaciones seleccionadas. Con el fin de garantizar las condiciones sink, previamente se evaluó la solubilidad del fármaco en tampón fosfato a distintos valores de pH. Este estudio demostró que el ciprofloxacino presenta baja solubilidad a pH >6 y forma soluciones sobresaturadas metaestables a pH 6 y 5.5. La formulación elaborada con PLGA-502, 15mg de ciprofloxacino y NaCl en la fase externa acuosa, se seleccionó como la formulación más adecuada, mostrando un tamaño de partícula de 307 nm, un PDI de 0.28, una eficacia de encapsulación de 62.46% y una liberación controlada del ciprofloxacino durante al menos 7 días.

Abstract: At the present time, climate change and antimicrobial resistance are considered as the most critical threats, affecting human, animal, plant, and environmental health. Although these terms may initially appear different, they are interconnected and share similarities in their causes (human interventions and natural cycles), health, and societal consequences. Climate change is associated through direct and indirect pathways with an increase in infectious diseases. Nonetheless, the association between global warming and antimicrobial resistance requires a comprehensive summary of evidence exploring it. Methods: A literature review was conducted to identify and describe the association between climate change and the rapid emergence and spread of antimicrobial resistance. The search was conducted in the following databases: PubMed, Web of Science, Scopus, Embase, Epistemonikos, and Google Scholar. The search period was restricted to articles published from January 2010 to June 2021. Additionally, a snowballing approach was conducted to identify any additional papers. Data extraction included study location, weather factors, environmental elements, antibiotics, and bacteria analysed, as well as the results. Results: 29 articles were included (ten literature or systematic reviews, eight experimental, six ecological, four observational, and one quasi-experimental). In terms of location, all the studies were conducted in countries between 35° and 75° north latitude. The results suggested some evidence of the effects of climate change (alterations in temperature, precipitation, and humidity) on the emergence and rapid spread of antimicrobial resistance in different environments (water, soil, cryosphere, and air). Temperature was described as a main effect of climate change that had effects on antibiotic resistance (increasing bacteria growth, altering metabolism, inducing crossprotection, and facilitating horizontal gene transfer between bacteria). Additionally, results also described the association between altered rain patterns and humidity and antimicrobial resistance, through the runoff of antibiotic molecules or the transport of antibiotic resistance mechanisms to other areas. Conclusions: This literature review has underscored the association between climate change and antimicrobial resistance. According to the results shown in the selected studies, the alterations in weather factors resulting from climate change have varying effects on the emergence and spread of antibiotic resistance. However, further research is imperative to decipher the complex interactions between other environmental processes, pollutants, patterns of antibiotic consumption, wastewater, animal migration, and regions below the latitudes covered in this literature review.

Abstract: Mixed microbial cultures have become a preferred choice of biocatalyst for chain elongation systems due to their ability to convert complex substrates into medium chain carboxylates. However, the complexity of the effects of process parameters on the microbial metabolic networks is a drawback that makes the task of optimizing product selectivity challenging. Here, we studied the effects of small air contaminations on the microbial community dynamics and the product formation in anaerobic bioreactors fed with lactate, acetate and H2/CO2. Two stirred tank reactors and two bubble column reactors were operated with H2/CO2 gas recirculation for 139 and 116 days, respectively, at pH 6.0 and 32°C with a hydraulic retention time of 14 days. One reactor of each type had periods with air contamination (between 97 ± 28 and 474 ± 33 mL O2 L−1 d−1, lasting from 4 to 32 days), while the control reactors were kept anoxic. During air contamination, production of n-caproate and CH4 was strongly inhibited, whereas no clear effect on nbutyrate production was observed. In a period with detectable O2 concentrations that went up to 18%, facultative anaerobes of the genus Rummeliibacillus became predominant and only n-butyrate was produced. However, at low air contamination rates and with O2 below the detection level, Coriobacteriia and Actinobacteria gained a competitive advantage over Clostridia and Methanobacteria, and propionate production rates increased to 0.8–1.8 mmol L−1 d−1 depending on the reactor (control reactors 0.1–0.8 mmol L−1 d−1). Moreover, i-butyrate production was observed, but only when Methanobacteria abundances were low and, consequently, H2 availability was high. After air contamination stopped completely, production of n-caproate and CH4 recovered, with n-caproate production rates of 1.4–1.8 mmol L−1 d−1 (control 0.7–2.1 mmol L−1 d−1). The results underline the importance of keeping strictly anaerobic conditions in fermenters when consistent n-caproate production is the goal. Beyond that, micro-aeration should be further tested as a controllable process parameter to shape the reactor microbiome. When odd-chain carboxylates are desired, further studies can develop strategies for their targeted production by applying micro-aerobic conditions.

Abstract: Botulism is caused by a potent neurotoxin that blocks neuromuscular transmission, resulting in death by asphyxiation. Currently, the therapeutic options are limited and there is no antidote. Here, we harness the structural and trafficking properties of an atoxic derivative of botulinum neurotoxin (BoNT) to transport a function-blocking single-domain antibody into the neuronal cytosol where it can inhibit BoNT serotype A (BoNT/A1) molecular toxicity. Post-symptomatic treatment relieved toxic signs of botulism and rescued mice, guinea pigs, and nonhuman primates after lethal BoNT/A1 challenge. This platform might enable delivery of antibodies and other protein-based therapeutics to previously inaccessible intraneuronal targets. Resumen: El botulismo es causado por una potente neurotoxina que bloquea la transmisión neuromuscular, provocando la muerte por asfixiamiento. Actualmente, las opciones de tratamiento son limitadas y no existe un antídoto. En este artículo aprovechamos las propiedades estructurales y de tráfico neuronal de un derivado atóxico de la neurotoxina botulínica (BoNT) para transportar un anticuerpo que bloquea la función al citosol neuronal, donde puede inhibir la toxicidad molecular del serotipo A de la BoNT (BoNT /A1). El tratamiento post-sintomático alivió los signos tóxicos del botulismo y rescató de la muerte a ratones, conejillos de indias y primates no humanos después de la exposición letal a BoNT / A1. Esta plataforma podría permitir la administración de anticuerpos y otros terapéuticos basados en proteínas a blancos intraneuronales que previamente eran inaccesibles.

Abstract: The disorders caused by mutations in genes encoding subunits and accessory proteins of cohesin complex are collectively termed as cohesinopathies. The best known cohesinopathy is Cornelia de Lange Syndrome (CdLS), which is a multisystem developmental disorder characterized by facial dysmorphism, limb malformations, growth and cognitive impairment. Mutations in five genes, encoding subunits of the cohesin complex (SMC1A, SMC3, RAD21) and its regulators (NIPBL, HDAC8), are responsible for ∼70% of CdLS cases. We describe a 16-year-old boy with facial dysmorphism, growth retardation, intellectual disability, hirsutism and small hands, who has a small Supernumerary Marker Chromosome (sSMC) present in mosaic form. sSMC is composed of two duplicated segments encompassing 17 genes including SMC1A gene, at the regions Xp11.22 and Xp11.21q11.1. Clinical comparison between our patient with a previously reported individual with a SMC1A duplication and four male carriers of similar sSMC reported in databases, suggest that they all share clinical features related to cohesinopathies. Although our patient does not have the classical CdLS craniofacial phenotype, he has pre and postnatal growth retardation, intellectual disability and mild musculoskeletal anomalies, features commonly seen in patients with cohesinopathies.

Abstract: Cornelia de Lange Syndrome (CdLS) is a congenital autosomal dominant (NIPBL, SMC3 and RAD21) or Xlinked (SMC1A and HDAC8) disorder characterized by facial dysmorphism, pre and postnatal growth retardation, developmental delay and/or intellectual disability, and multiorgan involvement. Musculoskeletal malformations are usually bilateral and affect mainly the upper limbs; the range goes from brachyclinodactyly to severe reduction defects. Instead lower extremities are usually less and mildly involved. Here, we report on a 3-year-old Senegalese boy with typical craniofacial CdLS features, pre and postnatal growth retardation, atrial septal defect, developmental delay and right ipsilateral limb malformations, consistent with oligodactyly of the 3rd and 4th fingers, tibial agenesis and fibula hypoplasia. Exome sequencing and Sanger sequencing showed a novel missense mutation in NIPBL gene (c.6647A>G; p.(Tyr2216Cys)), which affects a conserved residue located within NIPBL HEAT repeat elements. Pyrosequencing analysis of NIPBL gene, disclosed similar levels of wild-type and mutated alleles in DNA and RNA samples from all tissues analyzed (oral mucosa epithelial cells, peripheral blood leukocytes and fibroblasts). These findings indicated the absence of somatic mosaicism, despite of the segmental asymmetry of the limbs, and confirmed biallelic expression for NIPBL transcripts, respectively. Additionally, conditions like Split-hand/foot malformation with long-bone deficiency secondary to duplication of BHLHA9 gene have been ruled out by the array-CGH and MLPA analysis. To our knowledge, this is the first CdLS patient described with major ipsilateral malformations of both the upper and lower extremities, that even though this finding could be due to a random event, expands the spectrum of limb reduction defects in CdLS.

Abstract: Seasonal influenza is an infectious disease of multi-causal etiology and a major cause of mortality worldwide that has been associated with environmental factors. In the attempt to model and predict future outbreaks of seasonal influenza with multiple environmental factors, we face the challenge of increased dimensionality that makes the models more complex and unstable. In this paper, we propose a nowcasting and forecasting framework that compares the theoretical approaches of Single Environmental Factor and Multiple Environmental Factors. We introduce seven solutions to minimize the weaknesses associated with the increased dimensionality when predicting seasonal influenza activity levels using multiple environmental factors as external proxies. Our work provides evidence that using dimensionality reduction techniques as a strategy to combine multiple datasets improves seasonal influenza forecasting without the penalization of increased dimensionality.

Abstract: Objective: Determine the population prevalence and trends of cleft lip and / or palate (CL/P) by department for Colombia in the period 2009 - 2015. Methods: Prevalence study based on Individual Registry of Health Services in general population from 2009 to 2015. All people diagnosed with CL/P were included for all ages, type of diagnosis and any type of health services in the mentioned period. The prevalence rate was calculated by period and point for each year, for each department and according to the type of cleft. Stationarity on time series was evaluated using (Dickey-Fuller) and (Phillips-Perron), the trends and prevalence ratios were calculated using Poisson regression. Results: 15,225 people with CL/P were identified, where 53.3% were men. The national period prevalence of CL/P is 3.37 per 10 000 (IC95%: 3.3-3.4) with upward trend (PR = 1.34 95% CI: 1.0 - 1.8 p = 0.05) and non-stationary behavior. The national period prevalence of CL is 0.93 per 10 000, CP 1.17 per 10 000 and CLP 1.26 per 10 000, where CLP is sub classify into CLPu (0.83 per 10 000), and CLPb (0.43 per 10 000). At the departmental level, the highest CL/P prevalence is Guaviare (11.2 95% CI: 8.6 – 14.2), followed by Guainía (8.4 95% CI:5.4 – 12.2) and the lowest Quindío (0.49 95% CI: 0.3 – 0.7) Conclusions: In Colombia, the national period prevalence of CL/P is 3.37 per 10 000 with upward trend at national level indicates an increase on prevalence from 2009 to 2015.

Abstract: Objective: To analyze the population prevalence and birth prevalence of oral clefts in Colombia from 2009 to 2017. Methods: A cross-sectional study using information from the National Administrative Records of Colombia. The data came from 2 types of administrative records (Surveillance System and the Individual Registry of Service Provision) and the oral health national survey. Population prevalence and birth prevalence by type of cleft lip and/or cleft (CL/P) ratios were calculated using Poisson distribution for count data and to assess stationary tests on time series (Dickey-Fuller) and (Phillips-Perron) was used. Results: Population prevalence in Colombia was 3.27 per 10 000 inhabitants (95% confidence interval [CI], 3.21-3.32) and birth prevalence was 6.0 per 10 000 live births (95% CI, 5.67-6.35). Bogot´a have the highest population prevalence with CL/P. In the analysis of trends for the prevalence proportion by type of clefts in newborn babies with cleft, it was observed that the highest proportion was for babies with CLP. Cleft lip (CL) has increased from 17.4% in 2014 to 34.2% in 2017, cleft palate (CP) has decreased from 32.9% to 20.2%; and CLP changed from 49.6% to 45.5% in the same period. Conclusions: The population prevalence was 3.27 per 10 000 inhabitants. Births prevalence was 6.0 per 10 000 live births, and Orinoquia and Amazonia have higher rates than the national average. The administrative registers are adequate systems to know the behavior of oral clefts. The CL/P had a nonstationary trend during the period 2014 to 2017.

Abstract: Background: Seasonal Influenza is considered to be a cyclic and ordered sequence of values, influenced by external factors that can be predicted and used to detect disease outbreaks and monitoring. In machine learning, the key challenges that limit these analyses are in model explainability and limitations associated with ecological bias. Aim: Determine the best environmental variable selection method to predict Seasonal Influenza in Norway, using an environmental medicine approach combined with machine learning techniques. Methods: This is a quasi-experimental study that compares three approaches (non-variable selection, isolate component, and multipollutant mixture), represented in five methods (univariable, bivariable, multivariable AME, multivariable PCA, multivariable LDA). Per method, the best co-variable combination will be performed, following the internal rules of each method. The best covariable combination is the result of three components: variable selection, validation data set and lag. The first one involves 13 environmental variables (temperature, relative humidity, specific humidity, air pressure, wind speed, precipitation, CO, NO, NO2, O3, PM10, PM2,5 and SO2); second one compares a test dataset compiled from the data from 2019, last year (2018) and a synthetic environmental (avg. 2013-2018) data set in the validation process; and the third one compares a combination of lag from 0 to 12. All the predictions are made using ARIMA algorithm. The evaluation is given in terms of MAE, MSE, RMSE, OR. The training set is from 2 Jun 2013 (week 22/2013) to 28 May 2018 (week 21/2018), and test set is from (week 22/2018) to (week 21/2019) with a window of predictions of 52 weeks. Results: The increment of dimensionality in the environmental variable selection introduce different noise levels and optimize the prediction. Considerations that impact the explainability, usability, ecological bias and performance will be described. Conclusion: The increment of dimensionality in the variable selection has a better impact on performance than using complex algorithms.