Search

Introduction: Effective medical education must balance clinical service demands for institutions and learning needs of trainees. The question of whether these are competing demands or can serve complementary roles has profound impacts on graduate medical education, ranging from funding decisions to the willingness of community-based hospitals and physicians to include learners at their clinical sites. Our objective in this article was to systematically review the evidence on the impact of medical trainees on productivity and efficiency in the emergency department (ED).Methods: We queried PubMed, Embase, Scopus, and Web of Science from earliest available dates to March 2023. We identified all studies evaluating the impact of medical students and/or residents in the ED on commonly used productivity and efficiency metrics. Only studies in EDs in the United States were included. No additional filters were used. We assessed the risk of bias of included studies using the Risk of Bias in Non-randomized Studies – of Interventions (ROBINS-I) tool. Certainty of evidence was rated using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. Study findings were combined in a narrative synthesis and reported according to PRISMA guidelines.Results: The literature search yielded 3,390 unique articles for abstract screening. Eighty-one abstracts were identified as relevant to our PICO question (population, intervention, control, and outcomes), 76 of which had retrievable full-text articles and the themes of which were discussed in a narrative synthesis. We selected 13 of the full-text articles for final inclusion in a systematic review. Studies were roughly split between observational (6) and quasi-experimental (7) designs. The majority of studies (11) were single-site studies. Only two studies could be graded as low risk of bias per the ROBINS-I tool.Conclusion: Low-GRADE evidence suggests that students and residents decrease ED efficiency by a statistically small effect size of debatable clinical importance. Residents provide a moderate boost to ED productivity. Students do not produce a statistically or clinically significant impact on ED productivity. Residents increase emergency department relative value units revenue by $26.30 an hour, while students have no impact. Both types of learners decrease efficiency.

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community. In an expected sample of approximately 2000 CHR individuals and 640 matched healthy controls, AMP SCZ will collect clinical, environmental, and cognitive data along with multimodal biomarkers, including neuroimaging, electrophysiology, fluid biospecimens, speech and facial expression samples, novel measures derived from digital health technologies including smartphone-based daily surveys, and passive sensing as well as actigraphy. The study will investigate a range of clinical outcomes over a 2-year period, including transition to psychosis, remission or persistence of CHR status, attenuated positive symptoms, persistent negative symptoms, mood and anxiety symptoms, and psychosocial functioning. The global reach of AMP SCZ and its harmonized innovative methods promise to catalyze the development of new treatments to address critical unmet clinical and public health needs in CHR individuals.

Understanding the impact of repository gas, generated from degradation of waste and its interaction with the host rock, is essential when assessing the performance and safety function of long-term disposal systems for radioactive waste. Numerical models based on conventional multi-phase flow theory have historically been applied to predict the outcome and impact of gas flow on different repository components. However, they remain unable to describe the full complexity of the physical processes observed in water-saturated experiments (e.g., creation of dilatant pathways) and thus, the development of novel representations for their description is required when assessing fully saturated clay-based systems. This was the primary focus of Task A within the international cooperative project DECOVALEX-2019 (D-2019) and refinement of these approaches is the primary focus of this study (Task B in the current phase of DECOVALEX-2023). This paper summarises development of enhanced numerical representations of key processes and compares the performance of each model against high-quality laboratory test data. Experimental data reveals that gas percolation in water-saturated compacted bentonite is characterised by four key features: (i) a quiescence phase, followed by (ii) the gas breakthrough, which leads to a (iii) peak value, which is then followed by (iv) a negative decay. Three models based on the multiphase flow theory have been developed. These models can provide good initial values and reasonable responses for gas breakthrough (although some of them still predict a too-smooth response). Peak gas pressure values are in general reasonably well captured, although maximum radial stress differences are observed at 48 mm from the base of the sample. Here, numerical peak values of 12.8 MPa are predicted, whereas experimental values are about 11 MPa. These models are also capable of providing a reasonable representation of the negative pressure decay following peak pressure. However, other key specific features (such as the timing of gas breakthrough) still require a better representation. The model simulations and their comparison with experimental data show that these models need to be further improved with respect to model parameter calibration, the numerical representation of spatial heterogeneities in material properties and flow localisation, and the upscaling of the related physical processes and parameters. To further understand gas flow localisation, a new conceptual model has been developed, which shows that discrete channels can possibly be induced through the instability of gas-bentonite interface during gas injection, thus providing a new perspective for modeling gas percolation in low-permeability deformable media.

This needs analysis study sought to identify the contextual requirements to design and implement a blended learning program in English at a Colombian public university. Data on teachers' and administrators' perceptions were gathered through a questionnaire, interviews, and focus groups and analyzed using grounded theory. Findings revealed the need to invest considerably in new personnel and e-infrastructure. Likewise, students' context should be considered to design EFL blended programs. Teachers and students should be offered ICT and methodological professional development. Finally, the program should carefully balance the integration of face-to-face and online modalities. This investigation can help the academic community of language educators and curriculum designers carry out needs analysis studies for creating contextualized blended learning programs.

First (L1) and second (L2) language speakers process information differently. The current study explores whether L1 and L2 English language speakers process the emotional connotations of high and low-frequency words using the emotional Stroop task. With this task, we measure the reaction time required to name the color of words with positive, neutral, and negative valence. The sample was 100 participants, 50 L1 English speakers and 50 L2 English speakers. Our results show that L2 English speakers process words slower than L1 English speakers do. L1 English speakers processed positive words faster than negative words, but L2 English speakers displayed a reversed pattern, which indicates L2 emotional attenuation for negative words.

This article begins by analysing the fields of application of cargo drones at an international level, to then determine the most used configurations and with the best performance to lift important loads, from which a coaxial octocopter drone with X8 configuration was designed and built, with a payload capacity of up to 20 kg and a flight range of 45 minutes. The relevance to build in Ecuador of this type of drones was also analysed and thus minimize technological dependence. The results showed that it starts with 31% of national components and that by executing activities aimed at reducing dependency, in a period of 5 years it can reach 63.8% of national components for the construction of drones of these characteristic.

microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms' role in ecology and human health.

INTRODUCTION: Most patients with HPV-positive oropharyngeal squamous cell carcinoma (OPSCC) have an excellent response to chemoradiation, and trials are now investigating de-escalated treatment. However, up to 25% of patients with HPV-positive OPSCC will experience recurrence, and up to 5% will even progress through primary treatment. Currently, there are no molecular markers to identify patients with poor prognosis who would be harmed by de-escalation. Herein we report the clinical and genomic characteristics of persistent HPV-positive OPSCC after definitive platinum-based chemoradiation therapy. METHODS: Patients with HPV-positive OPSCC treated with curative intent platinum-based chemoradiation between 2007 and 2017 at two institutions and with a persistent locoregional disease were included. We evaluated clinical characteristics, including smoking status, age, stage, treatment, and overall survival. A subset of five patients had tissue available for targeted exome DNA sequencing and RNA sequencing. Genomic analysis was compared to a previously published cohort of 47 treatment-responsive HPV+ OPSCC tumors after batch correction. Mutational landscape, pathway activation, and OncoGPS tumor states were employed to characterize these tumors. RESULTS: Ten patients met the inclusion criteria. The tumor and nodal stages ranged from T1 to T4 and N1 to N2 by AJCC 8th edition staging. All patients were p16-positive by immunohistochemistry, and eight with available in situ hybridization were confirmed to be HPV-positive. The 1-year overall survival from the time of diagnosis was 57%, and the 2-year overall survival was 17%. TP53 mutations were present in three of five (60%) persistent tumors compared to 2% (one of 47) of treatment-responsive HPV-positive tumors (p = 0.008). Other genes with recurrent mutations in persistent HPV-positive OPSCC tumors were NF1, KMT2D, PIK3C2B, and TFGBR2. Compared to treatment-responsive HPV-positive tumors, persistent tumors demonstrated activation of DNA Repair and p53, EMT, MYC, SRC, and TGF-beta signaling pathways, with post-treatment samples demonstrating significant activation of the PI3K-EMT-Stem pathways compared to pretreatment samples. CONCLUSION: Chemoradiation-resistant HPV-positive OPSCC occurs infrequently but portends a poor prognosis. These tumors demonstrate higher rates of p53 mutation and activation of MYC, SRC, and TGF-beta pathways. A comparison of tumors before and after treatment demonstrates PI3K-EMT-Stem pathways post-treatment in HPV-positive tumors with persistent disease after platinum-based chemoradiation.

Abstract The COVID-19 pandemic led to a global crisis that forced governments to implement restrictive measures to control the spread of the disease. Although these restrictions, such as community quarantines, played a pivotal role in stabilizing healthcare systems, they also caused forced closures of various economic sectors that resulted in huge societal costs and severely impacted the marginalized. In order to understand and quantify the economic impact of the COVID-19 pandemic in the Philippines, an integrated modeling approach, which combined an epidemiological compartmental model and an economic model, was utilized. The evolving nature of COVID-19 required continuous updating of the integrated model which this paper illustrates by applying three versions of the model in three different phases of the pandemic. Scenario-based estimates of active COVID-19 cases and economic losses, expressed in terms of foregone income, are produced for each of the model versions. Analysis of the results provided a retrospective view of the losses the economy had incurred during the pandemic, along with implications for public policy. The insights presented in this paper emphasize the importance of using an integrated modeling approach to guide pandemic response.

This paper evaluates the nonlinear dynamics of a melanoma cancer model through the iterative technique of finding compact invariant sets (LMCIS). The objective is to discover equilibrium points, ascertain their stability qualities, and determine the presence of compact invariant sets within the model. For instance, this approach is assessed in a model demonstrating the interplay between four cellular populations and administrating interleukin-12 (IL-12) immunotherapy. Nevertheless, the mechanism by which this anti-cancer therapy operates has yet to be completely defined. The approach is evaluated using severe treatment situations to provide evidence for the presence of equilibrium points inside the iteratively confined zone and to assess its effectiveness. The outcomes derived from using this approach were then compared with a conventional iteration of Newton’s method. Newton’s approach extends to the resolution of the system of equations inside the model, facilitating the identification of the equilibrium points with a small tolerance error. While the iterations of the localization algorithm were set close to the results obtained by this method. Finally, the simulation outcomes are shown via the utilization of MATLAB R2020b. The findings demonstrate the temporal progression of the model under the effect of immunotherapy and without it.

Abstract Background Adverse events in psychiatric settings present ongoing challenges for both patients and staff. Despite advances in psychiatric interventions and treatments, research on early warning scores and tools to predict patient deterioration is limited. This review provides a summary of the few tools that have been developed in a psychiatric setting, comparing machine learning (ML) and nonmachine learning/traditional methodologies. The outcomes of interest include the selected key variables that contribute to adverse events and the performance and validation measures of the predictive models. Methods Three databases, Ovid MEDLINE, PsycINFO, and Embase, were searched between February 2023 and April 2023 to identify all relevant studies that included a combination of (and were not limited to) the following search terms: "Early warning," "Alerting tool," and "Psychiatry". Peer-reviewed primary research publications were included without imposing any date restrictions. A total of 1,193 studies were screened. A total of 9 studies met the inclusion and exclusion criteria and were included in this review. The PICOS model, the Joanna Briggs Institute (JBI) Reviewer's Manual, and PRISMA guidelines were applied. Results This review identified nine studies that developed predictive models for adverse events in psychiatric settings. Encompassing 41,566 participants across studies that used both ML and non-ML algorithmic approaches, performance metrics, primarily AUC ROC, varied among studies between 0.62 and 0.95. The best performing model that had also been validated was the random forest (RF) ML model, with a score of 0.87 and a high sensitivity of 74% and a specificity of 88%. Conclusion Currently, few predictive models have been developed for adverse events and patient deterioration in psychiatric settings. The findings of this review suggest that the use of ML and non-ML algorithms show moderate to good performance in predicting adverse events at the hospitals/units where the tool was developed. Understanding these models and the methodology of the studies is crucial for enhancing patient care as well as staff and patient safety research. Further research on the development and implementation of predictive tools in psychiatry should be carried out to assess the feasibility and efficacy of the tool in psychiatric patients.

El objetivo del presente artículo es realizar una aproximación a la situación de la osteopatía pediátrica en España y proponer la creación de una mesa de diálogo inter y multidisciplinar que permita avanzar en su regulación y ordenación profesional. Actualmente no existe un estándar académico que regule este tipo de formación en nuestro país. La ausencia de regulación predispone a que haya una gran variedad de perfiles profesionales, con formaciones académicas dispares, practicando la osteopatía. Este hecho puede tener implicaciones sobre la seguridad y calidad de la atención que reciben los/las pacientes/usuarios/as, principalmente los grupos vulnerables y dependientes de la población, como son los/las menores de edad. La creación de una mesa de diálogo también permitiría clarificar la práctica profesional de la osteopatía pediátrica y cuál es su bien interno para con la sociedad española. El papel de la bioética puede ser importante a la hora de integrar diferentes voces.

Abstract d-Xylitol is a naturally occurring sugar alcohol present in diverse plants that is used as an alternative sweetener based on a sweetness similar to sucrose and several health benefits compared to conventional sugar. However, current industrial methods for d-xylitol production are based on chemical hydrogenation of d-xylose, which is energy-intensive and environmentally harmful. However, efficient conversion of l-arabinose as an additional highly abundant pentose in lignocellulosic materials holds great potential to broaden the range of applicable feedstocks. Both pentoses d-xylose and l-arabinose are converted to d-xylitol as a common metabolic intermediate in the native fungal pentose catabolism. To engineer a strain capable of accumulating d-xylitol from arabinan-rich agricultural residues, pentose catabolism was stopped in the ascomycete filamentous fungus Aspergillus niger at the stage of d-xylitol by knocking out three genes encoding enzymes involved in d-xylitol degradation (ΔxdhA, ΔsdhA, ΔxkiA). Additionally, to facilitate its secretion into the medium, an aquaglyceroporin from Saccharomyces cerevisiae was tested. In S. cerevisiae, Fps1 is known to passively transport glycerol and is regulated to convey osmotic stress tolerance but also exhibits the ability to transport other polyols such as d-xylitol. Thus, a constitutively open version of this transporter was introduced into A. niger, controlled by multiple promoters with varying expression strengths. The strain expressing the transporter under control of the PtvdA promoter in the background of the pentose catabolism-deficient triple knock-out yielded the most favorable outcome, producing up to 45% d-xylitol from l-arabinose in culture supernatants, while displaying minimal side effects during osmotic stress. Due to its additional ability to extract d-xylose and l-arabinose from lignocellulosic material via the production of highly active pectinases and hemicellulases, A. niger emerges as an ideal candidate cell factory for d-xylitol production from lignocellulosic biomasses rich in both pentoses. In summary, we are showing for the first time an efficient biosynthesis of d-xylitol from l-arabinose utilizing a filamentous ascomycete fungus. This broadens the potential resources to include also arabinan-rich agricultural waste streams like sugar beet pulp and could thus help to make alternative sweetener production more environmentally friendly and cost-effective.

Resumen: Introducción: La lipoatrofia facial carece de criterios clínicos estándar para su diagnóstico y tratamiento; sin embargo, los pacientes con atrofia hemifacial aumentan afectando la salud mental de los pacientes que la padecen. El lipoinjerto se ha rescatado como una opción de tratamiento eficaz y seguro. Objetivo: Mostrar los resultados de la restauración volumétrica autóloga en pacientes con hemiatrofia adiposa facial. Método: Estudio multicéntrico, descriptivo, longitudinal y prospectivo realizado en 29 pacientes atendidos en el Hospital Hermanos Ameijeiras, Cuba y en la clínica EIMEC, España en el período julio 2018 a julio 2023. Se incluyeron ambos sexos, entre 19 y 75 años, con asimetría facial por disminución unilateral del tejido celular subcutáneo. Resultados: La edad media fue 47,9 años. Predominaron las mujeres con 79,3%. Predominaron la etiología idiopática, autoinmune y trauma orbitario con 17,2% cada uno. Según el grado de severidad fue mayor el grado II con 65,5%, el grado III representó el 34,5% del total. Respecto a la cantidad de tejido adiposo injertado en 62,1% fue de 31 a 60 ml y en 27,6% mayor de 60 ml. Según el número de aplicaciones del injerto el 72,4% requirió una y el 27,6% dos aplicaciones. El 93,1% no presentaron complicaciones y el 6,9% refirieron reabsorción del 50% del injerto. El 100% los pacientes refirió satisfacción con el procedimiento y los resultados fueron evaluados como buenos; al presentar mejoría, ausencia de complicaciones y satisfacción del paciente, en el 86,21%. Conclusión: La lipotransferencia autóloga asistida con células madre del tejido adiposo constituye una opción de tratamiento seguro que ofrece buenos resultados en la corrección de la asimetría causada por lipoatrofia hemifacial. Abstract: Introduction: Facial lipoatrophy lacks standard clinical criteria for its diagnosis and treatment; however, patients with hemifacial atrophy increase, affecting the mental health of patients who suffer from it. Lipografting has been rescued as an effective and safe treatment option. Objective: To show the results of autologous volumetric restoration in patients with facial adipose hemiatrophy. Method: Multicenter, descriptive, longitudinal and prospective study carried out on 29 patients treated at the Hermanos Ameijeiras Hospital, Cuba and the EIMEC clinic, Spain in the period from July 2018 to July 2023. Both sexes were included, between 19 and 75 years old, with facial asymmetry due to unilateral decrease in subcutaneous cellular tissue. Results: The average age was 47.9 years. Women predominated with 79.3%. The most common etiologies were idiopathic, autoimmune and orbital trauma, each accounting for 17.2%. According to the degree of severity, grade II was the highest, with 65.5%, and grade III represented 34.5% of the total. Regarding the amount of grafted adipose tissue, 62.1% of the cases were 31 to 60 ml, and 27.6% more than 60 ml. According to the number of graft applications, 72.4% required one and 27.6% two applications. 93.1% had no complications and 6.9% reported 50% reabsorption of the graft. Patient satisfaction reached 100% and the results were classified as good in 86.21%; when there was improvement, without complications as well as patient satisfaction. Conclusion: Autologous lipotransfer assisted with adipose tissue stem cells is a safe treatment option that offers good results in correcting asymmetry caused by hemifacial lipoatrophy.

Abstract Background Neuroinflammation is involved in the pathogenesis of almost every central nervous system disorder. As the brain’s innate immune cells, microglia fine tune their activity to a dynamic brain environment. Previous studies have shown that repeated bouts of peripheral inflammation can trigger long-term changes in microglial gene expression and function, a form of innate immune memory. Methods and results In this study, we used multiple low-dose lipopolysaccharide (LPS) injections in adult mice to study the acute cytokine, transcriptomic, and microglia morphological changes that contribute to the formation of immune memory in the frontal cortex, hippocampus, and striatum, as well as the long-term effects of these changes on behavior. Training and tolerance of gene expression was shared across regions, and we identified 3 unique clusters of DEGs (2xLPS-sensitive, 4xLPS-sensitive, LPS-decreased) enriched for different biological functions. 2xLPS-sensitive DEG promoters were enriched for binding sites for IRF and NFkB family transcription factors, two key regulators of innate immune memory. We quantified shifts in microglia morphological populations and found that while the proportion of ramified and rod-like microglia mostly remained consistent within brain regions and sexes with LPS treatment, there was a shift from ameboid towards hypertrophic morphological states across immune memory states and a dynamic emergence and resolution of events of microglia aligning end-to-end with repeated LPS. Conclusions Together, findings support the dynamic regulation of microglia during the formation of immune memories in the brain and support future work to exploit this model in brain disease contexts.

Se realizó el reconocimiento geológico del noreste de la ciudad de Moa, Holguín, área que ocupa el reparto Rolo Monterrey, con el objetivo de mostrar la geomorfología, el comportamiento de los procesos geológicos, la litología de la región y el impacto ambiental que lo afecta. Para la realización del trabajo fueron seleccionados seis puntos de interés significativos del área. Quedan expuestos las principales características geológicas y geomorfológicas del noreste de la ciudad de Moa.

Mothers of children with chronic conditions or disabilities have benefited from mindfulness programs, yet culturally relevant mindfulness programs for Spanish-speaking mothers are lacking. We aimed to explore how this population experienced a peer-led mindfulness program to inform adaptations. Sixteen mothers attended a 6-week program and completed semi-structured interviews. Using a realist evaluation framework, we explored relationships between participants' context, the program's mechanisms and outcomes. Our thematic analysis found that four contextual factors--faith, self-concept as a woman and mother, trauma, and level of social support--influenced how participants experienced the mechanisms. Mechanisms included having positive experiences when trying practices, engaging in self-reflection, and sharing life experiences and learning in community. The mechanisms led to four outcomes: emotion regulation, savoring daily life experiences, empowerment to practice self-care and common humanity. Faith was an important enabling factor because participants had positive experiences when integrating their faith with program content. Future research should examine adaptations that invite participants to explore this synergy. Self-reflection should also be emphasized because it increased motivation to use practices and helped address barriers to engagement. Because the four contextual factors apply to many Spanish-speaking immigrants, these adaptations could enhance mindfulness programs for this population more broadly.

In the SARS-CoV-2 lineage, RNA elements essential for its viral life cycle, including genome replication and gene expression, have been identified. Still, the precise structures and functions of these RNA regions in coronaviruses remain poorly understood. This lack of knowledge points out the need for further research to better understand these crucial aspects of viral biology and, in time, prepare for future outbreaks. In this research, the in silico analysis of the cis RNA structures that act in the alpha-, beta-, gamma-, and deltacoronavirus genera has provided a detailed view of the presence and adaptation of the structures of these elements in coronaviruses. The results emphasize the importance of these cis elements in viral biology and their variability between different viral variants. Some coronavirus variants in some groups, depending on the cis element (stem-loop1 and -2; pseudoknot stem-loop1 and -2, and s2m), exhibited functional adaptation. Additionally, the conformation flexibility of the s2m element in the SARS variants was determined, suggesting a coevolution of this element in this viral group. The variability in secondary structures suggests genomic adaptations that may be related to replication processes, genetic regulation, as well as the specific pathogenicity of each variant. The results suggest that RNA structures in coronaviruses can adapt and evolve toward different viral variants, which has important implications for viral adaptation, pathogenicity, and future therapeutic strategies.

Background: COVID-19-associated pulmonary aspergillosis (CAPA) has emerged as a relatively common complication. Multiple studies described this relationship in critical patients, however its incidence and outcome in other risk groups such as immunosuppressed patients remains unknown. In this sense, we aimed to evaluate the rates and outcomes of CAPA in hematological patients and according to the different hematological malignances, comparing to invasive pulmonary aspergillosis (IPA) in non-COVID-19 ones. Methods: Nationwide, population-based and retrospective observational cohort study including all adult patients with hematological malignancies admitted in Spain since March 1, 2020 to December 31, 2021. The main outcome variable was the diagnosis of IPA during hospitalization in hematological patients with or without COVID-19 at admission. The rate of CAPA compared to IPA in non-COVID-19 patients in each hematological malignancy was also performed, as well as survival curve analysis. Findings: COVID-19 was diagnosed in 3.85 % (4367 out of 113,525) of the hematological adult inpatients. COVID-19 group developed more fungal infections (5.1 % vs. 3 %; p

The genetic basis of severe COVID-19 has been thoroughly studied, and many genetic risk factors shared between populations have been identified. However, reduced sample sizes from non-European groups have limited the discovery of population-specific common risk loci. In this second study nested in the SCOURGE consortium, we conducted a genome-wide association study (GWAS) for COVID-19 hospitalization in admixed Americans, comprising a total of 4702 hospitalized cases recruited by SCOURGE and seven other participating studies in the COVID-19 Host Genetic Initiative. We identified four genome-wide significant associations, two of which constitute novel loci and were first discovered in Latin American populations (BAZ2B and DDIAS). A trans-ethnic meta-analysis revealed another novel cross-population risk locus in CREBBP. Finally, we assessed the performance of a cross-ancestry polygenic risk score in the SCOURGE admixed American cohort. This study constitutes the largest GWAS for COVID-19 hospitalization in admixed Latin Americans conducted to date. This allowed to reveal novel risk loci and emphasize the need of considering the diversity of populations in genomic research.

β-arrestins play a key role in G protein-coupled receptor (GPCR) internalization, trafficking, and signaling. Whether β-arrestins act independently of G protein-mediated signaling has not been fully elucidated. Studies using genome-editing approaches revealed that whereas G proteins are essential for mitogen-activated protein kinase activation by GPCRs., β-arrestins play a more prominent role in signal compartmentalization. However, in the absence of G proteins, GPCRs may not activate β-arrestins, thereby limiting the ability to distinguish G protein from β-arrestin-mediated signaling events. We used β2-adrenergic receptor (β2AR) and its β2AR-C tail mutant expressed in human embryonic kidney 293 cells wildtype or CRISPR-Cas9 gene edited for Gαs, β-arrestin1/2, or GPCR kinases 2/3/5/6 in combination with arrestin conformational sensors to elucidate the interplay between Gαs and β-arrestins in controlling gene expression. We found that Gαs is not required for β2AR and β-arrestin conformational changes, β-arrestin recruitment, and receptor internalization, but that Gαs dictates the GPCR kinase isoforms involved in β-arrestin recruitment. By RNA-Seq analysis, we found that protein kinase A and mitogen-activated protein kinase gene signatures were activated by stimulation of β2AR in wildtype and β-arrestin1/2-KO cells but absent in Gαs-KO cells. These results were validated by re-expressing Gαs in the corresponding KO cells and silencing β-arrestins in wildtype cells. These findings were extended to cellular systems expressing endogenous levels of β2AR. Overall, our results support that Gs is essential for β2AR-promoted protein kinase A and mitogen-activated protein kinase gene expression signatures, whereas β-arrestins initiate signaling events modulating Gαs-driven nuclear transcriptional activity.

Mathematical models supported by a robust automated data pipeline proved to be useful tools for a data-driven and science-based response and policy-making during the COVID-19 pandemic in the Philippines. In the first year of the pandemic, FASSSTER (Feasibility Analysis on Syndromic Surveillance using Spatio-Temporal Epidemiological modeleR) used a compartmental model to generate scenario-based projections of COVID-19 cases. The emergence of the Delta variant, however, and the administration of vaccines over the second half of 2021 caused significant changes in the Philippine pandemic landscape. This necessitated making adjustments to the model to better capture the local disease transmission dynamics and address policy questions posed by stakeholders regarding COVID-19 over that period. The extended model was then utilized to generate case projections by applying different intervention scenarios, specifically, scenarios involving vaccination coverage, compliance to public health standards and active detection of cases. The new model demonstrated reliability in terms of capturing historical data and in producing relatively accurate short-term projections. In turn, most of the projections generated by the model had been used in support of case monitoring and policy-making in the country. This paper illustrates the significance of enhancing mathematical models in response to the dynamic nature of the COVID-19 pandemic.