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E-learning Continuing Professional Development (CPD) is an activity demonstrated to improve the quality of healthcare delivery. The CPD of medical and nursing staff in high income countries (HICs) is commonplace. CPD of administrative staff is less common, but increasingly frequent. In low- and middle-income countries (LMICs), CPD of any kind is infrequent, particularly in rural and remote areas. The aim of this study was to describe a hospital-based e-learning CPD program for clinical and non-clinical personnel as a unique example of a successful, ongoing educational pilot, quality improvement program involving a broad cohort of employees, in a country that does not require such activities. Using the online educational platform Chamilo, e-learning modules were created for eight groups including clinical and non-clinical employees. Upon completion of each module, one to two paragraph discussions were provided for each incorrect answer submitted. Two additional chances were offered for the employee to achieve a passing score of 70%. This study reports on the first 10-month period of the program. All participants achieved the 70% passing threshold after the first or second attempt. There was 100% participation by the employees required to complete the e-learning modules. Employee feedback suggested the modules were good for continuing education, but some felt the CPD was imposed on them. E-learning CPD is an important and emerging element for CPD and may provide opportunities for healthcare service quality improvement as part of broader pedagogical modalities, such as conferences and directed readings, in rural and remote areas of LMICs. These pilot programs could provide important information to develop Spanish-language e-learning CPD programs across a broader region, promote collaboration with regional professional societies, and possibly contribute to the establishment of national health program CPD standards.

Season is a major determinant of infectious disease rates, including arboviruses spread by mosquitoes, such as dengue, chikungunya, and Zika. Seasonal patterns of disease are driven by a combination of climatic or environmental factors, such as temperature or rainfall, and human behavioral time trends, such as school year schedules, holidays, and weekday-weekend patterns. These factors affect both disease rates and healthcare-seeking behavior. Seasonality of dengue fever has been studied in the context of climatic factors, but short- and long-term time trends are less well-understood. With 2009-2016 medical record data from patients diagnosed with dengue fever at two hospitals in rural Ecuador, we used Poisson generalized linear modeling to determine short- and long-term seasonal patterns of dengue fever, as well as the effect of day of the week and public holidays. In a subset analysis, we determined the impact of school schedules on school-aged children. With a separate model, we examined the effect of climate on diagnosis patterns. In the first model, the most important predictors of dengue fever were annual sinusoidal fluctuations in disease, long-term trends (as represented by a spline for the full study duration), day of the week, and hospital. Seasonal trends showed single peaks in case diagnoses, during mid-March. Compared to the average of all days, cases were more likely to be diagnosed on Tuesdays (risk ratio (RR): 1.26, 95% confidence interval (CI) 1.05-1.51) and Thursdays (RR: 1.25, 95% CI 1.02-1.53), and less likely to be diagnosed on Saturdays (RR: 0.81, 95% CI 0.65-1.01) and Sundays (RR: 0.74, 95% CI 0.58-0.95). Public holidays were not significant predictors of dengue fever diagnoses, except for an increase in diagnoses on the day after Christmas (RR: 2.77, 95% CI 1.46-5.24). School schedules did not impact dengue diagnoses in school-aged children. In the climate model, important climate variables included the monthly total precipitation, an interaction between total precipitation and monthly absolute minimum temperature, an interaction between total precipitation and monthly precipitation days, and a three-way interaction between minimum temperature, total precipitation, and precipitation days. This is the first report of long-term dengue fever seasonality in Ecuador, one of few reports from rural patients, and one of very few studies utilizing daily disease reports. These results can inform local disease prevention efforts, public health planning, as well as global and regional models of dengue fever trends.

Over a period of twelve years, the author's vision of improving the health of rural Ecuadorians has evolved from an initial emphasis on primary health care to secondary care. The local community convinced him of the critical need for an efficiently managed, high-quality, and affordable rural secondary care hospital. Exploring a variety of funding options, the hospital ultimately achieved financial sustainability, principally through Ecuadorian public sources. Now, in partnership with the Ministry of Public Health (MOH), the rural hospital model that evolved in Pedro Vicente Maldonado is being adapted as a pilot project in an existing MOH rural hospital. [PUBLICATION ABSTRACT]

There is a paucity of data studying patients and complaints presenting to emergency departments (EDs) in low- and middle-income countries. The town of Pedro Vicente Maldonado (PVM) is located in the northwestern highlands of Ecuador. Hospital PVM (HPVM) is a rural teaching hospital providing family medicine residency training. These physicians provide around-the-clock acute medical care in HPVM's ED. This study provides a first look at a functioning ED in rural Latin America by reviewing one year of ED visits to HPVM. All ED visits between April 14, 2013, and April 13, 2014, were included and analyzed, totaling 1,239 patient visits. Data were collected from their electronic medical record and exported into a de-identified Excel® database where it was sorted and categorized. Variables included age, gender, mode of arrival, insurance type, month and day of the week of the service, chief complaint, laboratory and imaging requests, and disposition. We performed descriptive statistics, and where possible, comparisons using Student's T or chi-square, as appropriate. Of the 1239 total ED visits, 48% were males and 52% females; 93% of the visits were ambulatory, and 7% came by ambulance. Sixty-three percent of the patients had social security insurance. The top three chief complaints were abdominal pain (25.5%), fever (15.1%) and trauma (10.8%). Healthcare providers requested labs on 71.3% of patients and imaging on 43.2%. The most frequently requested imaging studies were chest radiograph (14.9%), upper extremity radiograph (9.4%), and electrocardiogram (9.0%). There was no seasonal or day-of-week variability to number of ED patients. The chief complaint of human or animal bite made it more likely the patient would be admitted, and the chief complaint of traumatic injury made it more likely the patient would be transferred. Analysis of patients presenting to a rural ED in Ecuador contributes to the global study of acute care in the developing world and also provides a self-analysis identifying disease patterns of the area, training topics for residents, areas for introducing protocols, and information to help planning for rural EDs in low- and middle-income countries.

Season is a major determinant of infectious disease rates, including arboviruses spread by mosquitoes, such as dengue, chikungunya, and Zika. Seasonal patterns of disease are driven by a combination of climatic or environmental factors, such as temperature or rainfall, and human behavioral time trends, such as school year schedules, holidays, and weekday-weekend patterns. These factors affect both disease rates and healthcare-seeking behavior. Seasonality of dengue fever has been studied in the context of climatic factors, but short- and long-term time trends are less well-understood. With 2009—2016 medical record data from patients diagnosed with dengue fever at two hospitals in rural Ecuador, we used Poisson generalized linear modeling to determine short- and long-term seasonal patterns of dengue fever, as well as the effect of day of the week and public holidays. In a subset analysis, we determined the impact of school schedules on school-aged children. With a separate model, we examined the effect of climate on diagnosis patterns. In the first model, the most important predictors of dengue fever were annual sinusoidal fluctuations in disease, long-term trends (as represented by a spline for the full study duration), day of the week, and hospital. Seasonal trends showed single peaks in case diagnoses, during mid-March. Compared to the average of all days, cases were more likely to be diagnosed on Tuesdays (risk ratio (RR): 1.26, 95% confidence interval (CI) 1.05—1.51) and Thursdays (RR: 1.25, 95% CI 1.02—1.53), and less likely to be diagnosed on Saturdays (RR: 0.81, 95% CI 0.65—1.01) and Sundays (RR: 0.74, 95% CI 0.58—0.95). Public holidays were not significant predictors of dengue fever diagnoses, except for an increase in diagnoses on the day after Christmas (RR: 2.77, 95% CI 1.46—5.24). School schedules did not impact dengue diagnoses in school-aged children. In the climate model, important climate variables included the monthly total precipitation, an interaction between total precipitation and monthly absolute minimum temperature, an interaction between total precipitation and monthly precipitation days, and a three-way interaction between minimum temperature, total precipitation, and precipitation days. This is the first report of long-term dengue fever seasonality in Ecuador, one of few reports from rural patients, and one of very few studies utilizing daily disease reports. These results can inform local disease prevention efforts, public health planning, as well as global and regional models of dengue fever trends. Dengue fever exhibits a seasonal pattern in many parts of the world, much of which has been attributed to climate and weather. However, additional factors may contribute to dengue seasonality. With 2009— 2016 medical record data from rural Ecuador, we studied the short- and long-term seasonal patterns of dengue fever, as well as the effect of school schedules and public holidays. We also examined the effect of climate on dengue. We found that dengue diagnoses peak once per year in mid-March, but that diagnoses are also affected by day of the week. Dengue was also impacted by regional climate and complex interactions between local weather variables. This is the first report of long-term dengue fever seasonality in Ecuador, one of few reports from rural patients, and one of very few studies utilizing daily disease reports. This is the first report on the impacts of school schedules, holidays, and weekday-weekend patterns on dengue diagnoses. These results suggest a potential impact of human behaviors on dengue exposure risk. More broadly, these results can inform local disease prevention efforts and public health planning, as well as global and regional models of dengue fever trends.

Season is a major determinant of infectious disease rates, including arboviruses spread by mosquitoes, such as dengue, chikungunya, and Zika. Seasonal patterns of disease are driven by a combination of climatic or environmental factors, such as temperature or rainfall, and human behavioral time trends, such as school year schedules, holidays, and weekday-weekend patterns. These factors affect both disease rates and healthcare-seeking behavior. Seasonality of dengue fever has been studied in the context of climatic factors, but short- and long-term time trends are less well-understood. With 2009-2016 medical record data from patients diagnosed with dengue fever at two hospitals in rural Ecuador, we used Poisson generalized linear modeling to determine short- and long-term seasonal patterns of dengue fever, as well as the effect of day of the week and public holidays. In a subset analysis, we determined the impact of school schedules on school-aged children. With a separate model, we examined the effect of climate on diagnosis patterns. In the first model, the most important predictors of dengue fever were annual sinusoidal fluctuations in disease, long-term trends (as represented by a spline for the full study duration), day of the week, and hospital. Seasonal trends showed single peaks in case diagnoses, during mid-March. Compared to the average of all days, cases were more likely to be diagnosed on Tuesdays (risk ratio (RR): 1.26, 95% confidence interval (CI) 1.05-1.51) and Thursdays (RR: 1.25, 95% CI 1.02-1.53), and less likely to be diagnosed on Saturdays (RR: 0.81, 95% CI 0.65-1.01) and Sundays (RR: 0.74, 95% CI 0.58-0.95). Public holidays were not significant predictors of dengue fever diagnoses, except for an increase in diagnoses on the day after Christmas (RR: 2.77, 95% CI 1.46-5.24). School schedules did not impact dengue diagnoses in school-aged children. In the climate model, important climate variables included the monthly total precipitation, an interaction between total precipitation and monthly absolute minimum temperature, an interaction between total precipitation and monthly precipitation days, and a three-way interaction between minimum temperature, total precipitation, and precipitation days. This is the first report of long-term dengue fever seasonality in Ecuador, one of few reports from rural patients, and one of very few studies utilizing daily disease reports. These results can inform local disease prevention efforts, public health planning, as well as global and regional models of dengue fever trends. Footnotes * https://doi.org/10.3886/E109165V1

Lipid microdomains are postulated to regulate many membrane-associated processes but have remained highly controversial. Here we provide the first direct evidence that the plasma membrane of intact, live cells is comprised of a sub-resolution mixture of approximately 76% ordered and 24% disordered lipid domains, which correspond to liquid-ordered and -disordered model membranes. These measurements were based on the unmixing of fluorescence lifetime decays (phasor analysis) obtained from environmentally sensitive membrane dyes that report the degree of lipid packing. Using the transmembrane protein Linker for Activation of T cells (LAT) as an example, we demonstrate that association with ordered domains retarded LAT diffusion and decreased clustering in meso-scaled protein domains as analysed by super-resolution microscopy. Our data therefore propose a membrane model in which the majority of the plasma membrane is covered by cholesterol-dependent, ordered lipid domains that contribute to the non-random distribution and diffusion of membrane constituents. The plasma membrane is thought to comprise a patchwork of ordered and disordered microdomains; however, direct evidence for this in intact cells remains elusive. Using unmixing of fluorescence lifetime decays, Owen et al . show that ordered domains occupy a majority of the plasma membrane surface in living cells.

Gaus and colleagues show that the conformational states of the tyrosine kinase Lck intrinsically control its distribution and clustering at the plasma membrane. Phosphorylation of the T cell antigen receptor (TCR) by the tyrosine kinase Lck is an essential step in the activation of T cells. Because Lck is constitutively active, spatial organization may regulate TCR signaling. Here we found that Lck distributions on the molecular level were controlled by the conformational states of Lck, with the open, active conformation inducing clustering and the closed, inactive conformation preventing clustering. In contrast, association with lipid domains and protein networks were not sufficient or necessary for Lck clustering. Conformation-driven Lck clustering was highly dynamic, so that TCR triggering resulted in Lck clusters that contained phosphorylated TCRs but excluded the phosphatase CD45. Our data suggest that Lck conformational states represent an intrinsic mechanism for the intermolecular organization of early T cell signaling.

Emerging evidence supports the concept that T helper type 17 (T H 17) cells, in addition to mediating autoimmunity, have key roles in mucosal immunity against extracellular pathogens. Interleukin-22 (IL-22) and IL-17A are both effector cytokines produced by the T H 17 lineage, and both were crucial for maintaining local control of the Gram-negative pulmonary pathogen, Klebsiella pneumoniae . Although both cytokines regulated CXC chemokines and granulocyte colony–stimulating factor production in the lung, only IL-22 increased lung epithelial cell proliferation and increased transepithelial resistance to injury. These data support the concept that the T H 17 cell lineage and its effector molecules have evolved to effect host defense against extracellular pathogens at mucosal sites.

In quiescent T cells, the signaling adaptor Lat aggregates into cell-surface clusters. Gaus and colleagues demonstrate that pre-existing clusters of Lat do not participate in signaling from the T cell antigen receptor, which relies instead on recruitment of Lat from subsynaptic vesicles. Engaged T cell antigen receptors (TCRs) initiate signaling through the adaptor protein Lat. In quiescent T cells, Lat is segregated into clusters on the cell surface, which raises the question of how TCR triggering initiates signaling. Using super-resolution fluorescence microscopy, we found that pre-existing Lat domains were neither phosphorylated nor laterally transported to TCR activation sites, which suggested that these clusters do not participate in TCR signaling. Instead, TCR activation resulted in the recruitment and phosphorylation of Lat from subsynaptic vesicles. Studies of Lat mutants confirmed that recruitment preceded and was essential for phosphorylation and that both processes were independent of surface clustering of Lat. Our data suggest that TCR ligation preconditions the membrane for vesicle recruitment and bulk activation of the Lat signaling network.