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Trichoepithelioma is a benign neoplasm that shares both clinical and histological features with basal cell carcinoma. It is important to distinguish these neoplasms because they require different clinical behavior and therapeutic planning. Many studies have addressed the use of immunohistochemistry to improve the differential diagnosis of these tumors. These studies present conflicting results when addressing the same markers, probably owing to the small number of basaloid tumors that comprised their studies, which generally did not exceed 50 cases. We built a tissue microarray with 162 trichoepithelioma and 328 basal cell carcinoma biopsies and tested a panel of immune markers composed of CD34, CD10, epithelial membrane antigen, Bcl-2, cytokeratins 15 and 20 and D2-40. The results were analyzed using multiple linear and logistic regression models. This analysis revealed a model that could differentiate trichoepithelioma from basal cell carcinoma in 36% of the cases. The panel of immunohistochemical markers required to differentiate between these tumors was composed of CD10, cytokeratin 15, cytokeratin 20 and D2-40. The results obtained in this work were generated from a large number of biopsies and resulted in the confirmation of overlapping epithelial and stromal immunohistochemical profiles from these basaloid tumors. The results also corroborate the point of view that trichoepithelioma and basal cell carcinoma tumors represent two different points in the differentiation of a single cell type. Despite the use of panels of immune markers, histopathological criteria associated with clinical data certainly remain the best guideline for the differential diagnosis of trichoepithelioma and basal cell carcinoma.

Since Aedes aegypti was identified as vector of yellow fever and dengue, its dispersal is relevant for disease control. We studied the dispersal of Ae. aegypti in temperate areas of Argentina during egglaying, using the existing population and egg traps. Two independent replicas of a unique experimental design involving mosquitoes dispersing from an urbanized area to adjacent non-urbanized locations were carried out and analyzed in statistical terms. We found relationship between stochastic variables related to the egg-laying mosquito activity (ELMA), useful to assess dispersal probabilities, despite the lack of knowledge of the total number of ovipositions in the zone. We propose to evaluate the egg-laying activity as minus the logarithm of the fraction of negative ovitraps at different distances from the buildings. Three zones with different oviposition activity were determined, a corridor surrounding the urbanization, a second region between 10 and 25 m and the third region extending from 30 to 45 m from the urbanization. The landscape (plant cover) and the human activity in the area appear to have an influence in the dispersal of Ae. aegypti. The proposed method worked consistently in two different replicas.

In tropical forest communities, seedling recruitment can be limited by the number of fruit produced by adults. Fruit production tends to be highly unequal among trees of the same species, which may be due to environmental factors. We observed fruit production for ~2,000 trees of 17 species across 3 years in a wet tropical forest in Costa Rica. Fruit production was modeled as a function of tree size, nutrient availability, and neighborhood crowding. Following model selection, tree size and neighborhood crowding predicted both the probability of reproduction and the number of fruit produced. Nutrient availability only predicted only the probability of reproduction. In all species, larger trees were more likely to be reproductive and produce more fruit. In addition, number of fruit was strongly negatively related to presence of larger neighboring trees in 13 species; presence of all neighboring trees had a weak‐to‐moderate negative influence on reproductive status in 16 species. Among various metrics of soil nutrient availability, only sum of base cations was positively associated with reproductive status, and for only four species. Synthesis Overall, these results suggest that direct influences on fruit production tend to be mediated through tree size and crowding from neighboring trees, rather than soil nutrients. However, we found variation in the effects of neighbors and nutrients among species; mechanistic studies of allocation to fruit production are needed to explain these differences. We observed fruit production for ~2,000 trees of 17 species across three years in a wet tropical forest in Costa Rica. Fruit production was negatively related to presence of larger neighboring trees in 13 species, but relationships between fruit production and soil nutrient availability were less common. These results suggest that influences on fruit production tend to be mediated through tree size and crowding rather than soil nutrients.

Purpose: Provide empirical validation of the model developed by García Moreno et al. (2016) on the factors influencing the adoption of e-business in firms. Design/methodology/approach: Consideration is given to the method for measuring each one of the variables included in the model. Use has been made of the e-Business Watch database, which contains measures for the theoretical model's three categories: firm, technology, and environment. Multinomial logistic regression models have been provided. Findings: The variables included have revealed significant statistical relationships for the model in question, although the intensity of the relationships differs. the variables related to the environment also reveal statistically significant relationships, whereby the attitude of trading partners appears to have a relevant and growing impact on e-business adoption. Research limitations/implications: Data come from just one database: the e-Business Watch database/enriched data from alternative databases could be included. Practical implications: The infrastructure of information and communications technologies (ICTs) is confirmed to be a determining factor in e-business development. Nevertheless, the effect of competitor rivalry has a more erratic influence that is encapsulated in a significant relationship in intermediate models, with a sharper increase in the likelihood of being in the category of customer-focused firms, and less internally focused. Social implications: The human capital linked to ICTs is a driving force behind the adoption of these practices. Albeit with a more moderate effect, note should also be taken of the capacity for entering into relationships with third parties within the scope of ICTs, with significant effects that become more robust as they are tested in models that seek to explain the probability of recording higher levels of e-business adoption.Originality/value: The article presents a first empirical analysis to apply the previous developed model published in this journal in 2016.

Synaptic depression is prominent among synapses, but the underlying mechanisms remain uncertain. Here, we use paired patch clamp recording to study neuromuscular transmission between the caudal primary motor neuron and target skeletal muscle in zebrafish. This synapse has an unusually low number of release sites, all with high probabilities of release in response to low-frequency stimulation. During high-frequency stimulation, the synapse undergoes short-term depression and reaches steady-state levels of transmission that sustain the swimming behavior. To determine the release parameters underlying this steady state, we applied variance analysis. Our analysis revealed two functionally distinct subclasses of release sites differing by over 60-fold in rates of vesicle reloading. A slow reloading class requires seconds to recover and contributes to depression onset but not the steady-state transmission. By contrast, a fast reloading class recovers within tens of milliseconds and is solely responsible for steady-state transmission. Thus, in contrast to most current models that assign levels of steady-state depression to vesicle availability, our findings instead assign this function to nonuniform release site kinetics. The duality of active-site properties accounts for the highly nonlinear dependence of steady-state depression levels on frequency.

Background To investigate the association between critical and communicative oral health literacy (OHL) and oral health outcomes (status, oral health-related quality of life and practices) in adults. Methods This cross-sectional study examined a household probability sample of 248 adults, representing 149,635 residents (20–64 years old) in Piracicaba-SP, Brazil. Clinical oral health and socioeconomic and demographic data, as well as data on oral health-related quality of life (OHIP-14) and health practices were collected. The oral examinations were carried out in the participants’ homes, using the World Health Organization criteria for oral diseases. The critical and communicative OHL instrument was the primary independent variable, and it was measured using five Likert items that were dichotomized as ‘high’ (‘agree’ and ‘strongly agree’ responses for the 5 items) and ‘low’ OHL. Binary and multinomial logistic regressions were performed on each outcome (oral health status and practices), controlling for age, sex and socioeconomic status (SES). Results Approximately 71.5% presented low OHL. When adjusted for age and sex (first model) low OHL was associated with untreated caries (Odds Ratio = 1.92, 95% Confidence Interval = 1.07–3.45), tooth brushing <3 times a day (OR = 2.00, 1.11–3.62) and irregular tooth flossing (OR = 2.17, 1.24–3.80). After SES inclusion in the first model, significant associations were found for low OHL when the outcomes were: presence of biofilm (OR = 1.83, 1.08–3.33), dental care for emergency only (OR = 2.24, 1.24–4.04) and prevalence of oral health impact on quality of life (OR = 2.06, 1.15–3.69). Conclusion Adjusting for age, sex and SES, OHL is related to a risk factor (biofilm) and a consequence of poor oral health (emergency dental visits) and can interfere with the impact of oral diseases on quality of life. As low OHL can be modified, the results support oral health promotion strategies directed at improving critical and communicative oral health literacy in adult populations.

Background In South Africa, age-disparate to sexual relationships where the age difference between partners is 5 years or greater is an important contributor to the spread of HIV. However, little is known about the predictors of age-disparate sexual relationships. This study investigates factors associated with age-disparate sexual relationships among males and females in South Africa. Methods This analysis used the 2012 nationally representative population-based household survey conducted using multi-stage stratified cluster sampling design. Multivariate multinomial stepwise logistic regression models were used to determine factors associated with age-disparate sexual relationships. Results Of 15,717 participants, who responded to the question on age-disparate sexual relationships, 62% males versus 58.5% females had partners within 5 years older or younger, 34.7% of males versus 2.7% of females had partners at least 5 years younger and 3.3% of males versus 38.8% of females had partners at least 5 years older. Among both males and females predictors of age-disparate sexual relationships were education, employment, socioeconomic status, locality type, age at sexual debut, condom use at last sexual act and HIV status while race was also an additional predictor for among females. Including unprotected sex and risk of HIV infection among adolescent girls and young women with sexual partners 5 years older their age. Conclusions This study suggest that there is a need for reprioritizing the combination of behavioural and structural interventions to address risky sexual behaviours, unprotected sex, poverty, limited education and gender inequitable norms related to age-disparate sexual relationships and HIV.

The United Nations Development Programme Human Development Index (HDI) aggregates information on achievements in health, education and income. These achievements are given a weight of one-third each. These weights have been the subject of long-standing controversy, from the moment the HDI was released in 1990. Alternative weights reflecting stated citizen preferences are obtained in this paper using a discrete choice experiment involving a survey 2578 adult residents of the United Kingdom. Health is the most important achievement, with a mean weight of 0.428, followed by income and education, with mean weights of 0.292 and 0.280 respectively. Evidence in support of the view that HDI weights should vary among achievements and countries is provided, based on cluster and econometric analysis of the survey data.

Misdiagnosis, arbitrary charges, annoying queues, and clinic waiting times among others are long-standing phenomena in the medical industry across the world. These factors can contribute to patient anxiety about misdiagnosis by clinicians. However, with the increasing growth in use of big data in biomedical and health care communities, the performance of artificial intelligence (Al) techniques of diagnosis is improving and can help avoid medical practice errors, including under the current circumstance of COVID-19. This study aims to visualize and measure patients' heterogeneous preferences from various angles of AI diagnosis versus clinicians in the context of the COVID-19 epidemic in China. We also aim to illustrate the different decision-making factors of the latent class of a discrete choice experiment (DCE) and prospects for the application of AI techniques in judgment and management during the pandemic of SARS-CoV-2 and in the future. A DCE approach was the main analysis method applied in this paper. Attributes from different dimensions were hypothesized: diagnostic method, outpatient waiting time, diagnosis time, accuracy, follow-up after diagnosis, and diagnostic expense. After that, a questionnaire is formed. With collected data from the DCE questionnaire, we apply Sawtooth software to construct a generalized multinomial logit (GMNL) model, mixed logit model, and latent class model with the data sets. Moreover, we calculate the variables' coefficients, standard error, P value, and odds ratio (OR) and form a utility report to present the importance and weighted percentage of attributes. A total of 55.8% of the respondents (428 out of 767) opted for AI diagnosis regardless of the description of the clinicians. In the GMNL model, we found that people prefer the 100% accuracy level the most (OR 4.548, 95% CI 4.048-5.110, P<.001). For the latent class model, the most acceptable model consists of 3 latent classes of respondents. The attributes with the most substantial effects and highest percentage weights are the accuracy (39.29% in general) and expense of diagnosis (21.69% in general), especially the preferences for the diagnosis \"accuracy\" attribute, which is constant across classes. For class 1 and class 3, people prefer the AI + clinicians method (class 1: OR 1.247, 95% CI 1.036-1.463, P<.001; class 3: OR 1.958, 95% CI 1.769-2.167, P<.001). For class 2, people prefer the AI method (OR 1.546, 95% CI 0.883-2.707, P=.37). The OR of levels of attributes increases with the increase of accuracy across all classes. Latent class analysis was prominent and useful in quantifying preferences for attributes of diagnosis choice. People's preferences for the \"accuracy\" and \"diagnostic expenses\" attributes are palpable. AI will have a potential market. However, accuracy and diagnosis expenses need to be taken into consideration.

Despite its importance, homeowners’ supply type decision has been under-researched due to data limitations. We construct a dataset of 4,037 apartment units in Gangdong district, Seoul, Korea over a 46-quarter period (2011Q1–2022Q2). We simultaneously analyse both the asset and space markets. The results show that the estimated probability and estimated volume of sale from supply type choice models are statistically significant in both the sales and rental price models. The key findings of our study are two. We find that the housing sales and rental markets interact and co-move together. We also demonstrate that the institution of the two-year lease contract period influences the transaction probabilities in both the sales and rental markets. For the supply type decision model, the estimated sale-transaction (rental-transaction) price significantly impacts the sale-transaction (rental-transaction) volume. However, no significant relationship was found between the estimated sale price and rental-transaction volume, nor between the estimated rental price and sale-transaction volume. The results of the forecast-performance comparison show that the integrated supply model_T/probability (calibrated) is the best for sales volume, whereas the two-year lagged value is the best for rental-volume estimation. This demonstrates institutional effects in the rental-housing market in Korea.