Institutional violence from police militarization and drug cartel wars as a 'Big Event' and its influence on drug use harms and HIV risk in people who inject drugs on the U.S.-Mexico border.

BACKGROUND: Globally, the US-Mexico Border is one of the largest drug trafficking regions, with Ciudad Juarez (CJ) and El Paso (EP) making up the second-largest border crossing in the world. Border communities are places where the risk of drug use harm and infectious diseases such as HIV are augmented due to the confluence of factors operating across the physical, social, economic and policy environment. Although the two cities are economically, culturally, and socially intertwined, each has distinct criminal justice systems and policy practices aimed at curtailing substance use. Between 2008 and 2011, the CJ/EP region experienced an unprecedented level of violence that stemmed from the intersection of police militarization and drug cartel wars, which profoundly shaped every aspect of life. Little research has documented the impact of drug cartel wars on the drug use and health harms of people who inject drugs (PWID) living in CJ and EP. The purpose of the study is to understand the effect that the drug cartel war had on the drug use harms and HIV risk of PWID. METHODS: We conducted 40 in-depth interviews with people who inject drugs who resided in CJ or EP and had used heroin or crack cocaine in the last 30 days, and asked how police militarization and drug cartel war affected their daily lives. The risk environment framework informed the analysis and interpretation of findings. RESULTS: Findings indicated that the risk environment was profoundly altered as PWID residing in CJ experienced profound changes in their daily lives that promoted engagement in behaviors that increased drug use and health harms including HIV risk, exacerbated trauma, and prevented use of substance use treatment and harm reduction services. The risk environment was also altered in EP, where PWID experienced drug supply shortages, violent policing practices, and reduced availability of harm reduction services. Findings underscore the permeability of risk environments across geographical borders. CONCLUSION: The intersection of law enforcement militarization and drug cartel wars can be conceptualized as a 'big event' because it disrupts the drug market economy, leads to drug shortages, promotes entrance into the drug market economy by people who use drugs, reshapes drug use sites, and constrains the provision of harm reduction services. The stability of the harm reduction system in CJ was negatively impacted and limited the ability of individuals to reduce harm. Our findings show that drug cartel wars render the CJ/EP region extremely susceptible to drug use and health harms, while also creating vulnerability by severely restricting its ability to respond. Traditional recommendations to intervene to limit the impact of risk environments on the drug use harms of PWID need to be reconsidered in the context of drug cartel wars.

Social and environmental determinants influencing injection drug use and HIV risk among two sister cities on the US-Mexico border: a comparative cross-sectional study, 2016-2018.

The economic, social, cultural and political milieus that influence injection drug-related HIV risk behaviors along the US-Mexico border in the previous decade have been studied comparing cities on an East-West axis. In an effort to inform interventions targeting factors beyond the individual level, we used a cross-sectional study design comparing people who inject drugs during 2016-2018, living on a North-South axis, in two cities-Ciudad Juárez, Chihuahua, Mexico and El Paso, Texas, USA-situated at the midpoint of the 2000 US-Mexico borderland stretch. We conceptualize injection drug use and its antecedents and consequences as influenced by factors operating at various levels of influence. Results of analysis comparing samples recruited from each border city indicated significant differences in demographic, socioeconomic, micro- and macro-level factors that affect risk. Similarities emerged in individual-level risk behaviors and some dynamics of risk at the drug use site most frequented to use drugs. In addition, analyses testing associations across samples indicated that different contextual factors such as characteristics of the drug use sites influenced syringe sharing. In this article, we reflect on the potential tailored interventions needed to target the context of HIV transmission risk among people who use drugs and reside in binational environment.

Predicting pharmaceutical inkjet printing outcomes using machine learning.

Inkjet printing has been extensively explored in recent years to produce personalised medicines due to its low cost and versatility. Pharmaceutical applications have ranged from orodispersible films to complex polydrug implants. However, the multi-factorial nature of the inkjet printing process makes formulation (e.g., composition, surface tension, and viscosity) and printing parameter optimization (e.g., nozzle diameter, peak voltage, and drop spacing) an empirical and time-consuming endeavour. Instead, given the wealth of publicly available data on pharmaceutical inkjet printing, there is potential for a predictive model for inkjet printing outcomes to be developed. In this study, machine learning (ML) models (random forest, multilayer perceptron, and support vector machine) to predict printability and drug dose were developed using a dataset of 687 formulations, consolidated from in-house and literature-mined data on inkjet-printed formulations. The optimized ML models predicted the printability of formulations with an accuracy of 97.22%, and predicted the quality of the prints with an accuracy of 97.14%. This study demonstrates that ML models can feasibly provide predictive insights to inkjet printing outcomes prior to formulation preparation, affording resource- and time-savings.

Accelerating 3D printing of pharmaceutical products using machine learning.

Three-dimensional printing (3DP) has seen growing interest within the healthcare industry for its ability to fabricate personalized medicines and medical devices. However, it may be burdened by the lengthy empirical process of formulation development. Active research in pharmaceutical 3DP has led to a wealth of data that machine learning could utilize to provide predictions of formulation outcomes. A balanced dataset is critical for optimal predictive performance of machine learning (ML) models, but data available from published literature often only include positive results. In this study, in-house and literature-mined data on hot melt extrusion (HME) and fused deposition modeling (FDM) 3DP formulations were combined to give a more balanced dataset of 1594 formulations. The optimized ML models predicted the printability and filament mechanical characteristics with an accuracy of 84%, and predicted HME and FDM processing temperatures with a mean absolute error of 5.5 °C and 8.4 °C, respectively. The performance of these ML models was better than previous iterations with a smaller and a more imbalanced dataset, highlighting the importance of providing a structured and heterogeneous dataset for optimal ML performance. The optimized models were integrated in an updated web-application, M3DISEEN, that provides predictions on filament characteristics, printability, HME and FDM processing temperatures, and drug release profiles (https://m3diseen.com/predictionsFDM/). By simulating the workflow of preparing FDM-printed pharmaceutical products, the web-application expedites the otherwise empirical process of formulation development, facilitating higher pharmaceutical 3DP research throughput.

Key stakeholder perspectives on the use of research about supported employment for racially and ethnically diverse patients with mental illness in the United States.

OBJECTIVE: To explore how stakeholders responded to research evidence regarding supported employment (e.g., vocational rehabilitation), and ways evidence could be incorporated into policy and action. DATA SOURCES: Qualitative data were collected from three stakeholder groups-people with lived experience of mental health challenges, community health advocates, and state health policy makers. STUDY DESIGN: This study consisted of two sequential steps. First, three focus groups were conducted after presenting stakeholder groups (inclusive of 22 participants) with simulation data showing that improvement in employment status had a stronger impact on mental health than improvement in education or income for racially/ethnically diverse groups. Second, with guidance from focus group findings, researchers conducted additional in-depth interviews (n = 19) to gain a deeper understanding of the opportunities and challenges related to incorporating these findings into policy and practice. DATA COLLECTION/EXTRACTION METHODS: Focus groups and in-depth interviews were conducted, audio recorded, transcribed, and analyzed using a thematic analysis approach. PRINCIPAL FINDINGS: People with lived experience described the positive effect of employment in their own life while highlighting the need to increase workplace accommodations and social supports for those with mental health challenges. Across stakeholder groups, participants emphasized the need for linguistic and cultural competence to promote equity in delivery of supported employment programs. Stakeholders also underscored that centralizing existing resources and using evidence-based approaches are crucial for successful implementation. CONCLUSION: Implementing effective supported employment programs should focus on meeting the specific needs of target individuals, as many of those needs are not considered in current employment-related programming. Collecting information from diverse users of research demonstrates what other aspects of supported employment are required for the likelihood of successful uptake. Implementation and dissemination efforts need to fortify collaborations and knowledge transfer between stakeholders to optimize supported employment and mental health resources.

Early Remdesivir to Prevent Progression to Severe Covid-19 in Outpatients.

BACKGROUND: Remdesivir improves clinical outcomes in patients hospitalized with moderate-to-severe coronavirus disease 2019 (Covid-19). Whether the use of remdesivir in symptomatic, nonhospitalized patients with Covid-19 who are at high risk for disease progression prevents hospitalization is uncertain. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving nonhospitalized patients with Covid-19 who had symptom onset within the previous 7 days and who had at least one risk factor for disease progression (age ≥60 years, obesity, or certain coexisting medical conditions). Patients were randomly assigned to receive intravenous remdesivir (200 mg on day 1 and 100 mg on days 2 and 3) or placebo. The primary efficacy end point was a composite of Covid-19-related hospitalization or death from any cause by day 28. The primary safety end point was any adverse event. A secondary end point was a composite of a Covid-19-related medically attended visit or death from any cause by day 28. RESULTS: A total of 562 patients who underwent randomization and received at least one dose of remdesivir or placebo were included in the analyses: 279 patients in the remdesivir group and 283 in the placebo group. The mean age was 50 years, 47.9% of the patients were women, and 41.8% were Hispanic or Latinx. The most common coexisting conditions were diabetes mellitus (61.6%), obesity (55.2%), and hypertension (47.7%). Covid-19-related hospitalization or death from any cause occurred in 2 patients (0.7%) in the remdesivir group and in 15 (5.3%) in the placebo group (hazard ratio, 0.13; 95% confidence interval [CI], 0.03 to 0.59; P = 0.008). A total of 4 of 246 patients (1.6%) in the remdesivir group and 21 of 252 (8.3%) in the placebo group had a Covid-19-related medically attended visit by day 28 (hazard ratio, 0.19; 95% CI, 0.07 to 0.56). No patients had died by day 28. Adverse events occurred in 42.3% of the patients in the remdesivir group and in 46.3% of those in the placebo group. CONCLUSIONS: Among nonhospitalized patients who were at high risk for Covid-19 progression, a 3-day course of remdesivir had an acceptable safety profile and resulted in an 87% lower risk of hospitalization or death than placebo. (Funded by Gilead Sciences; PINETREE ClinicalTrials.gov number, NCT04501952; EudraCT number, 2020-003510-12.).

Machine learning predicts 3D printing performance of over 900 drug delivery systems.

Three-dimensional printing (3DP) is a transformative technology that is advancing pharmaceutical research by producing personalized drug products. However, advances made via 3DP have been slow due to the lengthy trial-and-error approach in optimization. Artificial intelligence (AI) is a technology that could revolutionize pharmaceutical 3DP through analyzing large datasets. Herein, literature-mined data for developing AI machine learning (ML) models was used to predict key aspects of the 3DP formulation pipeline and in vitro dissolution properties. A total of 968 formulations were mined and assessed from 114 articles. The ML techniques explored were able to learn and provide accuracies as high as 93% for values in the filament hot melt extrusion process. In addition, ML algorithms were able to use data from the composition of the formulations with additional input features to predict the drug release of 3D printed medicines. The best prediction was obtained by an artificial neural network that was able to predict drug release times of a formulation with a mean error of ±24.29 min. In addition, the most important variables were revealed, which could be leveraged in formulation development. Thus, it was concluded that ML proved to be a suitable approach to modelling the 3D printing workflow.

[Primary Healthcare e-SUS: determinant attributes for the adoption and use of a technological innovation]. / e-SUS Atenção Primária: atributos determinantes para adoção e uso de uma inovação tecnológica.

The study aimed to analyze the adoption and use of the Primary Healthcare e-SUS (PHC e-SUS) as a technological innovation from the perspective of workers in primary healthcare (PHC). This was a sequential exploratory mixed-methods study (QUAN → qual) in municipalities in the interior of São Paulo state, Brazil, drawing on Diffusion of Innovation Theory. The quantitative component was analytical cross-sectional, applying a validated questionnaire to 114 PHC workers. The model was tested by applying partial least squares structural equation modeling (PLS-SEM) using SmartPLS 2.3.0. The qualitative study was descriptive-exploratory, using interviews (n = 10) with thematic content analysis, aimed at understanding the attributes that did not influence the adoption and use of PHC e-SUS. The attributes "experimentation", "ease of use", "relative advantage", and "compatibility" did not display statistical significance, indicating that they were not determinant attributes for the adoption and use of PHC e-SUS. Integration of the data evidenced failures in connectivity; lack of time to feed the system in real time and training; lack of prior experimentation; abrupt presentation of the system; and lack of skill with the technology. The results can assist other municipalities in Brazil with the implementation of the PHC e-SUS in relation to the importance of the organizational infrastructure, as well as training in the technology's use and handling. The study contributes to reflections and proposals for interventions in the problems faced in daily work with the adoption and use of a technological innovation such as the PHC e-SUS.

O estudo objetivou analisar a adoção e o uso do e-SUS Atenção Primária (e-SUS APS) como inovação tecnológica na perspectiva dos profissionais da atenção primária à saúde (APS). Trata-se de um estudo de método misto explanatório sequencial (QUAN → qual) realizado em municípios do interior de São Paulo, Brasil, utilizando a Teoria da Difusão de Inovação. O estudo quantitativo foi do tipo transversal analítico, aplicando-se um questionário validado a 114 profissionais da APS. Para testar o modelo do estudo, aplicou-se a modelagem de equações estruturais de mínimos quadrados parciais (PLS-SEM) por meio do software SmartPLS 2.3.0. O estudo qualitativo teve caráter descritivo-exploratório, por meio de entrevistas (n = 10) analisadas por análise temática de conteúdo, visando entender os atributos que não influenciaram a adoção e o uso do e-SUS APS. Os atributos "experimentação", "facilidade de uso", "vantagem relativa" e "compatibilidade" não apresentaram significância estatística, indicando não serem atributos determinantes para adoção e uso do e-SUS APS. Na integração dos dados, evidenciaram-se: falhas de conectividade; ausência de tempo para alimentação do sistema em tempo real e de capacitação; não experimentação prévia; apresentação abrupta do sistema e ausência de habilidade com a tecnologia. Os resultados podem auxiliar os demais municípios do Brasil na implantação e/ou efetivação do e-SUS APS, no que tange à importância da infraestrutura organizacional, bem como na capacitação para utilização e manuseio da tecnologia. Este estudo contribui para reflexões e propostas de intervenções aos problemas enfrentados no cotidiano do trabalho quanto à adoção e ao uso de uma inovação tecnológica, como o e-SUS APS.

El objetivo del estudio fue analizar la adopción y uso del e-SUS Atención Primaria (e-SUS APS), como innovación tecnológica, desde la perspectiva de los profesionales de la atención primaria en salud (APS). Se trata de un estudio de método mixto secuencial explicativo (CUAN → Cual) realizado en municipios del interior de São Paulo, utilizando la Teoría de la Difusión de Innovación. El estudio cuantitativo fue de tipo transversal analítico, aplicándose un cuestionario validado a 114 profesionales de la APS. Para probar el modelo del estudio se aplicó el modelado de ecuaciones estructurales de mínimos cuadrados parciales (PLS-SEM), a través del software SmartPLS 2.3.0. El estudio cualitativo tuvo carácter descriptivo-exploratorio, mediante entrevistas (n = 10), analizadas por análisis de contenido temático, con el objetivo de entender los atributos que no influenciaron en la adopción y uso de la e-SUS APS. Los atributos "probar", "facilidad de uso", "ventaja relativa" y "compatibilidad" no presentaron significación estadística, indicando no ser atributos determinantes para la adopción y uso de la e-SUS APS. En la integración de los datos se evidenciaron: fallos de conectividad; ausencia de tiempo para alimentación del sistema en tiempo real y de capacitación; no pruebas previas; presentación abrupta del sistema y ausencia de habilidad con la tecnología. Los resultados pueden ayudar a los demás municipios de Brasil en la implantación y/o efectuación de la e-SUS APS, en lo que atañe a la importancia de la infraestructura organizativa, así como la capacitación para la utilización y manejo de la tecnología. Este estudio contribuye a las reflexiones y propuestas de intervenciones, respecto a los problemas enfrentados en el día a día del trabajo, en cuanto a la adopción y uso de una innovación tecnológica, como la e-SUS APS.

e-SUS Atenção Primária: atributos determinantes para adoção e uso de uma inovação tecnológica / Primary Healthcare e-SUS: determinant attributes for the adoption and use of a technological innovation / e-SUS Atención Primaria: atributos determinantes para la adopción y uso de una innovación tecnológica

Resumo: O estudo objetivou analisar a adoção e o uso do e-SUS Atenção Primária (e-SUS APS) como inovação tecnológica na perspectiva dos profissionais da atenção primária à saúde (APS). Trata-se de um estudo de método misto explanatório sequencial (QUAN → qual) realizado em municípios do interior de São Paulo, Brasil, utilizando a Teoria da Difusão de Inovação. O estudo quantitativo foi do tipo transversal analítico, aplicando-se um questionário validado a 114 profissionais da APS. Para testar o modelo do estudo, aplicou-se a modelagem de equações estruturais de mínimos quadrados parciais (PLS-SEM) por meio do software SmartPLS 2.3.0. O estudo qualitativo teve caráter descritivo-exploratório, por meio de entrevistas (n = 10) analisadas por análise temática de conteúdo, visando entender os atributos que não influenciaram a adoção e o uso do e-SUS APS. Os atributos "experimentação", "facilidade de uso", "vantagem relativa" e "compatibilidade" não apresentaram significância estatística, indicando não serem atributos determinantes para adoção e uso do e-SUS APS. Na integração dos dados, evidenciaram-se: falhas de conectividade; ausência de tempo para alimentação do sistema em tempo real e de capacitação; não experimentação prévia; apresentação abrupta do sistema e ausência de habilidade com a tecnologia. Os resultados podem auxiliar os demais municípios do Brasil na implantação e/ou efetivação do e-SUS APS, no que tange à importância da infraestrutura organizacional, bem como na capacitação para utilização e manuseio da tecnologia. Este estudo contribui para reflexões e propostas de intervenções aos problemas enfrentados no cotidiano do trabalho quanto à adoção e ao uso de uma inovação tecnológica, como o e-SUS APS.

Abstract: The study aimed to analyze the adoption and use of the Primary Healthcare e-SUS (PHC e-SUS) as a technological innovation from the perspective of workers in primary healthcare (PHC). This was a sequential exploratory mixed-methods study (QUAN → qual) in municipalities in the interior of São Paulo state, Brazil, drawing on Diffusion of Innovation Theory. The quantitative component was analytical cross-sectional, applying a validated questionnaire to 114 PHC workers. The model was tested by applying partial least squares structural equation modeling (PLS-SEM) using SmartPLS 2.3.0. The qualitative study was descriptive-exploratory, using interviews (n = 10) with thematic content analysis, aimed at understanding the attributes that did not influence the adoption and use of PHC e-SUS. The attributes "experimentation", "ease of use", "relative advantage", and "compatibility" did not display statistical significance, indicating that they were not determinant attributes for the adoption and use of PHC e-SUS. Integration of the data evidenced failures in connectivity; lack of time to feed the system in real time and training; lack of prior experimentation; abrupt presentation of the system; and lack of skill with the technology. The results can assist other municipalities in Brazil with the implementation of the PHC e-SUS in relation to the importance of the organizational infrastructure, as well as training in the technology's use and handling. The study contributes to reflections and proposals for interventions in the problems faced in daily work with the adoption and use of a technological innovation such as the PHC e-SUS.

Resumen: El objetivo del estudio fue analizar la adopción y uso del e-SUS Atención Primaria (e-SUS APS), como innovación tecnológica, desde la perspectiva de los profesionales de la atención primaria en salud (APS). Se trata de un estudio de método mixto secuencial explicativo (CUAN → Cual) realizado en municipios del interior de São Paulo, utilizando la Teoría de la Difusión de Innovación. El estudio cuantitativo fue de tipo transversal analítico, aplicándose un cuestionario validado a 114 profesionales de la APS. Para probar el modelo del estudio se aplicó el modelado de ecuaciones estructurales de mínimos cuadrados parciales (PLS-SEM), a través del software SmartPLS 2.3.0. El estudio cualitativo tuvo carácter descriptivo-exploratorio, mediante entrevistas (n = 10), analizadas por análisis de contenido temático, con el objetivo de entender los atributos que no influenciaron en la adopción y uso de la e-SUS APS. Los atributos "probar", "facilidad de uso", "ventaja relativa" y "compatibilidad" no presentaron significación estadística, indicando no ser atributos determinantes para la adopción y uso de la e-SUS APS. En la integración de los datos se evidenciaron: fallos de conectividad; ausencia de tiempo para alimentación del sistema en tiempo real y de capacitación; no pruebas previas; presentación abrupta del sistema y ausencia de habilidad con la tecnología. Los resultados pueden ayudar a los demás municipios de Brasil en la implantación y/o efectuación de la e-SUS APS, en lo que atañe a la importancia de la infraestructura organizativa, así como la capacitación para la utilización y manejo de la tecnología. Este estudio contribuye a las reflexiones y propuestas de intervenciones, respecto a los problemas enfrentados en el día a día del trabajo, en cuanto a la adopción y uso de una innovación tecnológica, como la e-SUS APS.

M3DISEEN: A novel machine learning approach for predicting the 3D printability of medicines.

Artificial intelligence (AI) has the potential to reshape pharmaceutical formulation development through its ability to analyze and continuously monitor large datasets. Fused deposition modeling (FDM) three-dimensional printing (3DP) has made significant advancements in the field of oral drug delivery with personalized drug-loaded formulations being designed, developed and dispensed for the needs of the patient. The FDM 3DP process begins with the production of drug-loaded filaments by hot melt extrusion (HME), followed by the printing of a drug product using a FDM 3D printer. However, the optimization of the fabrication parameters is a time-consuming, empirical trial approach, requiring expert knowledge. Here, M3DISEEN, a web-based pharmaceutical software, was developed to accelerate FDM 3D printing using AI machine learning techniques (MLTs). In total, 614 drug-loaded formulations were designed from a comprehensive list of 145 different pharmaceutical excipients, 3D printed and assessed in-house. To build the predictive tool, a dataset was constructed and models were trained and tested at a ratio of 75:25. Significantly, the AI models predicted key fabrication parameters with accuracies of 76% and 67% for the printability and the filament characteristics, respectively. Furthermore, the AI models predicted the HME and FDM processing temperatures with a mean absolute error of 8.9 °C and 8.3 °C, respectively. Strikingly, the AI models achieved high levels of accuracy by solely inputting the pharmaceutical excipient trade names. Therefore, AI provides an effective holistic modeling technology and software to streamline and advance 3DP as a significant technology within drug development. M3DISEEN is available at (http://m3diseen.com/predictions/).

Factors related to the adoption of the Brazilian National Immunization Program Information System.

BACKGROUND: One way to optimize the adoption and use of technological innovations is to understand how those involved perceive, assess and decide to use them. This study aims to analyze the attributes that influence the adoption and use of the Brazilian National Immunization Program Information System (NIPIS) from the perspective of vaccination room workers. METHODS: This is a mixed method research, and a quantitative cross-sectional analytical study, with concomitant triangulation of data, carried out in a region of Brazil by using the Diffusion of Innovation Theory. We used a questionnaire with 183 nursing professionals who work at vaccination rooms in 12 municipalities. To test the research model, partial least squares structural equation modeling (PLS-SEM) and SmartPLS 2.3.0 have been applied to estimate the model. The qualitative research had a descriptive-exploratory character, using interviews (n = 18) analyzed through thematic analysis. RESULTS: The model proposed showed a mean correlation between the perceived attributes in the adoption and use of NIPIS. The results of the multiple regression indicated that the attributes "relative advantage" and "image" have a significant effect at 5% level (T > 1.97), positively influence the adoption and use of NIPIS; the attribute "voluntary use" negatively influences the adoption and use of the system; the attributes "experimentation", "compatibility", "profitability", and "ease of use" did not influence the adoption and use of NIPIS. Emphasis has been placed on aspects that weaken the adoption and use of NIPIS such as lack of good quality internet and resistance to use the technology by some professionals. Workers perceive the importance of NIPIS for the municipality and point out that technological innovation provides data at an individual level, inserted in real time, which makes it possible to assess vaccination coverage. Lack of an unstable internet compromises data release due to system slowness. CONCLUSIONS: The mixed method allowed an in-depth analysis of the adoption and use of NIPIS in the Western Health Macroregion of Minas Gerais State, and similarities were observed in the results. The attribute "relative advantage" is the one that most influences the adoption and use of NIPIS, which is the strongest predictor of innovation adoption rate.

Gathering Diverse Perspectives to Tackle "Wicked Problems": Racial/Ethnic Disproportionality in Educational Placement.

Among students receiving behavioral health and special education services, racial/ethnic minority students are consistently overrepresented in settings separate from general classrooms. Once separated, many young people struggle to improve academically and face significant difficulty upon trying to return to a general education setting. Given the complex, ongoing, and multifaceted nature of this challenge, racial/ethnic disproportionality can be identified as a "wicked problem," for which solutions are not easily identified. Here, we describe our community-engaged research efforts, eliciting perspectives from relevant partners in an ongoing dialogue, to better integrate diverse stakeholders' perspectives when attempting to address such disparities. We conducted focus groups and qualitative interviews with members of three stakeholder groups: community-serving organizations, individuals with lived experience of behavioral health conditions, and state-level policymakers, with a shared interest in addressing racial and ethnic disparities. Participant responses illustrated the "wickedness" of this problem and highlighted the need for additional supports for students, families, and school personnel, increased collaboration across relevant systems and agencies, and reduced barriers related to funding. Overall, this methodology bridged differing perspectives to develop, in concert with our partners, a shared language of the problem and a core set of issues to consider when seeking to effect change.

The cell wall proteome from two strains of Pseudocercospora fijiensis with differences in virulence.

Pseudocercospora fijiensis causes black Sigatoka disease, the most important threat to banana. The cell wall is crucial for fungal biological processes, including pathogenesis. Here, we performed cell wall proteomics analyses of two P. fijiensis strains, the highly virulent Oz2b, and the less virulent C1233 strains. Strains were starved from nitrogen to mimic the host environment. Interestingly, in vitro cultures of the C1233 strain grew faster than Oz2b in PDB medium, suggesting that C1233 survives outside the host better than the highly virulent Oz2b strain. Both strains were submitted to nitrogen starvation and the cell wall proteins were isolated and subjected to nano-HPLC-MS/MS. A total of 2686 proteins were obtained from which only 240 had a known function and thus, bioinformatics analyses were performed on this group. We found that 90 cell wall proteins were shared by both strains, 21 were unique for Oz2b and 39 for C1233. Shared proteins comprised 24 pathogenicity factors, including Avr4 and Ecp6, two effectors from P. fijiensis, while the unique proteins comprised 16 virulence factors in C1233 and 11 in Oz2b. The P. fijiensis cell wall proteome comprised canonical proteins, but thirty percent were atypical, a feature which in other phytopathogens has been interpreted as contamination. However, a comparison with the identities of atypical proteins in other reports suggests that the P. fijiensis proteins we detected were not contaminants. This is the first proteomics analysis of the P. fijiensis cell wall and our results expands the understanding of the fundamental biology of fungal phytopathogens and will help to decipher the molecular mechanisms of pathogenesis and virulence in P. fijiensis.

Cetoacidosis diabética tras cambio de insulina por exenatida / Diabetic ketoacidosis after switching insulin for exenatide

No disponible

Técnica de hemofiltración veno-venosa continua / Technique of continuous veno-venous hemofiltration", "_i": "

La hemofiltración veno–venosa continua (HFVVC), es unatécnica realizada en pacientes postoperados de cirugía cardíaca;consiste en extraer agua plasmática del sistema circulatorio,a través de una membrana semipermeable (hemoconcentrador)por convección y gradiente de presión, con el objetivode disminuir hipervolemia, mejorar la función renal, eliminarmediadores de respuesta inflamatoria y optimizar el estado hemodinámicode los pacientes. Este procedimiento es realizadopor el personal de enfermería de perfusión en la unidad de terapiaintensiva con un circuito que se arma y diseña en unárea blanca. Una de las principales ventajas que se le adjudicana las terapias de HFVVC, es la tolerancia hemodinámica ala extracción de grandes volúmenes de líquido en forma gradualy controlada, en pacientes en estado crítico.

The continuous veno-venous hemofiltration (HFVVC), is atechnique realized in post-operated patients of cardiac surgery;it consists of extracting plasmatic water of the circulatorysystem, through a semi permeable membrane (hemoconcentrador)by convection and pressure gradient, with the aimof diminishing hipervolemia, improving the renal function,to eliminate mediators of inflammatory answer and to optimizethe hemodinámico state of the patients. This procedureis realized by the personnel of perfusion infirmary in theunit of intensive therapy with a circuit that weapon and isdesigned in a white area. One of the main advantages thatare adjudged to the HFVVC therapies, is the tolerance haemodynamicsto the extraction of great volumes of liquid ingradual and controlled form, in patients in critical state.

New coating stent design for patients with high-risk coronary lesions for thrombotic events: early and long-term results of the Camouflage registry.

BACKGROUND: Semisynthetic coating of the Camouflage bare-metal stent (BMS) (Eucatech AG, Rheinfelden, Germany) mimics luminal endothelial cell glycocalix, potentially preventing the activation of the coagulation system. Purpose. We sought to determine in a clinical registry the acute and long-term clinical and angiographic outcomes of this BMS design in patients with acute coronary syndromes (ACS) or who were unable to be on long-term clopidogrel therapy. METHODS: From March 2007 to December 2008, 150 patients undergoing coronary stent implantation at three centers in Buenos Aires, Argentina, were included in our registry. Patients with ACS, including non-ST-elevation myocardial infarction (NSTEMI) and STelevation MI (STEMI), or those unable to be on long-term dual antiplatelet therapy were considered for inclusion. The primary endpoint was a major adverse cardiovascular event (MACE) defined as the incidence of cardiac death, MI or target lesion revascularization (TLR). The incidence of acute and late stent thrombosis (ST) was also analyzed. Angiographic late loss and the presence of late stent malapposition (LSM) was recorded at 9-month follow up. Clopidogrel was prescribed for 1 month. RESULTS: 54.7% of patients had acute MI, 36% had STEMI and 20.7% of patients were ineligible for long-term clopidogrel therapy because of previously planned non-vascular or general surgery within 30 days after percutaneous coronary intervention. During 11.5 months of clinical follow up, 2% suffered cardiac death, 4% had a MI, 8.9% underwent TLR and the overall cumulative major adverse cardiac event rate was 15.3%. No patient developed acute or late ST. There were no in-hospital complications for patients who underwent surgery. Intravascular ultrasound studies did not detect the presence of late malapposition. CONCLUSION: In this high-risk thrombotic patient population, the Camouflage coated stent design demonstrated a very good safety profile, as reflected by the low incidence of hard adverse cardiac events including ST at follow up.

Comparing the electronic properties and docking calculations of heme derivatives on CYP2B4.

Cytochrome P-450 is a group of enzymes involved in the biotransformation of many substances, including drugs. These enzymes possess a heme group (1) that when it is properly modified induces several important physicochemical changes that affect their enzymatic activity. In this work, the five structurally modified heme derivatives 2-6 and the native heme 1 were docked on CYP2B4, (an isoform of P450), in order to determine whether such modifications alter their binding form and binding affinity for CYP2B4 apoprotein. In addition, docking calculations were used to evaluate the affinity of CYP2B4 apoprotein-heme complexes for aniline (A) and N-methyl-aniline (NMA). Results showing the CYP2B4 heme 4- and heme 6-apoprotein complexes to be most energetically stable indicate that either hindrance effects or electronic properties are the most important factors with respect to the binding of heme derivatives at the heme-binding site. Furthermore, although all heme-apoprotein complexes demonstrated high affinity for both A and NMA, the CYP2B4 apoprotein-5 complex had higher affinity for A, and the heme 6 complex had higher affinity for NMA. Finally, surface electronic properties (SEP) were calculated in order to explain why certain arginine residues of CYP2B4 apoprotein interact with polarizable functionalities, such as ester groups or sp ( 2 ) carbons, present in some heme derivates. The main physicochemical parameter involved in the recognition process of the heme derivatives, the CYP2B4 apoprotein and A or NMA, are reported.