137 research outputs found

    Processing of Individual Items during Ensemble Coding of Facial Expressions

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    There is growing evidence that human observers are able to extract the mean emotion or other type of information from a set of faces. The most intriguing aspect of this phenomenon is that observers often fail to identify or form a representation for individual faces in a face set. However, most of these results were based on judgments under limited processing resource. We examined a wider range of exposure time and observed how the relationship between the extraction of a mean and representation of individual facial expressions would change. The results showed that with an exposure time of 50 ms for the faces, observers were more sensitive to mean representation over individual representation, replicating the typical findings in the literature. With longer exposure time, however, observers were able to extract both individual and mean representation more accurately. Furthermore, diffusion model analysis revealed that the mean representation is also more prone to suffer from the noise accumulated in redundant processing time and leads to a more conservative decision bias, whereas individual representations seem more resistant to this noise. Results suggest that the encoding of emotional information from multiple faces may take two forms: single face processing and crowd face processi

    Cucumber SUPERMAN Has Conserved Function in Stamen and Fruit Development and a Distinct Role in Floral Patterning

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    This is the published version. Copyright 2014 Public Library of Science.The Arabidopsis SUPERMAN (SUP) gene encodes a C2H2 type zinc finger protein that is required for maintaining the boundaries between stamens and carpels, and for regulating development of ovule outer integument. Orthologs of SUP have been characterized in bisexual flowers as well as dioecious species, but it remains elusive in monoecious plants with unisexual flowers on the same individual. Here we isolate the SUP ortholog in Cucumis sativus L (CsSUP), a monoecious vegetable. CsSUP is predominantly expressed in female specific organs: the female flower buds and ovules. Ectopic expression of CsSUP in Arabidopsis can partially complement the fruit development in sup-5 mutant, and its over-expression in wide-type leads to reduced silique length, suppressed stamen development and distorted petal patterning. Our data suggest that CsSUP plays conserved as well as distinct roles during flower and fruit development, and it may function in the boundaries and ovules to balance petal patterning, stamen and ovule development in Arabidopsis

    Development and Validation of a Nomogram for Predicting Pulmonary Infection in Patients Receiving Immunosuppressive Drugs

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    Objective: Pulmonary infection (PI), a severe complication of immunosuppressive therapy, affects patients\u27 prognosis. As part of this study, we aimed to construct a pulmonary infection prediction (PIP) model and validate it in patients receiving immunosuppressive drugs (ISDs). Methods: Totally, 7,977 patients being treated with ISDs were randomised 7:3 to the developing (n = 5,583) versus validation datasets (n = 2,394). Our predictive nomogram was established using the least absolute shrinkage and selection operator (LASSO) and multivariate COX regression analyses. With the use of the concordance index (C-index) and calibration curve, the prediction performance of the final model was evaluated. Results: Among the patients taking immunosuppressive medication, PI was observed in 548 (6.9%). The median time of PI occurrence after immunosuppressive therapy was 123.0 (interquartile range: 63.0, 436.0) days. Thirteen statistically significant independent predictors (sex, age, hypertension, DM, malignant tumour, use of biologics, use of CNIs, use of methylprednisolone at 500 mg, use of methylprednisolone at 40 mg, use of methylprednisolone at 40 mg total dose, use of oral glucocorticoids, albumin level, and haemoglobin level) were screened using the LASSO algorithm and multivariate COX regression analysis. The PIP model built on these features performed reasonably well, with the developing C-index of 0.87 (sensitivity: 85.4%; specificity: 81.0%) and validation C-indices of 0.837, 0.829, 0.832 and 0.830 for predicting 90-, 180-, 270- and 360-day PI probability, respectively. The decision curve analysis (DCA) and calibration curves displayed excellent clinical utility and calibration performance of the nomogram. Conclusion: The PIP model presented herein could aid in the prediction of PI risk in individual patients who receive immunosuppressive treatment and help personalise clinical decision-making

    Analysis of air quality changes and causes in the Liaoning region from 2017 to 2022

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    Using the air quality monitoring data from the Department of Ecology and Environment of Liaoning Province for the period from 2017 to 2022, the temporal and spatial changes in the concentrations of various air pollutants in the Liaoning region for the periods from 2017 to 2019 and 2020 to 2022 were analyzed by using the Evaluation on the meteorological condition index of PM2.5 pollution (EMI) and the ArcGIS Kriging Interpolation Method, and the contributions of pollution reduction to the changes in the air quality of the Liaoning region were assessed. The results show that after the implementation of emission reduction measures, the quality of the atmospheric environment in the Liaoning region has significantly improved, and the mean concentrations of PM2.5, PM10, SO2, NO2, CO and O3 are all reduced by a certain magnitude in the period 2020 to 2022 compared with the period 2017 to 2019; Based on the EMI index calculation, the average EMI index in Liaoning during the period 2020 to 2022 is about 1.7% lower than the average value of the region during the period 2017 to 2019, and the atmospheric dispersion conditions are relatively good; From the perspective of daily changes in pollutant concentrations, the trend of PM2.5 and PM10 concentrations changed from double peaks and single valleys to single peaks and single valleys, and there were no significant changes in the types of valleys for CO, SO2, NO2, and O3, whereas the peaks of O3 concentrations during the daytime were basically the same as in previous years, and the concentrations during the nighttime were slightly higher than in previous years. Classification by topographic areas revealed that the mean pollutant concentration for the period from 2017 to 2019 was more significant than the mean value for the period from 2020 to 2022, except for O3, where the air quality in the mountainous areas of Liaodong and Liaoxi was better than that of the Liaohe Plain, and regional classification by coastal and inland, where the air quality in the coastal areas was better than that of the inland areas

    Encephalitozoon hellem infection after haploidentical allogeneic hematopoietic stem cell transplantation in children: a case report

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    BackgroundEncephalitozoon hellem (E. hellem) infection is a zoonotic disease, rarely observed in individuals, causing various clinical manifestations including diarrhea, keratoconjunctivitis, cystitis, etc. E. hellem infection after hematopoietic stem-cell transplantation (HSCT) is a rare, serious complication.Case presentationHerein, we present a case of E. hellem infection developing during HLA-haploidentical HSCT in a 9-year-old boy who suffered from aplastic anemia. On 15 days after HSCT, the patient developed recurrent and prolonged fever, diarrhea and hematuria. It is challenging to differentiate whether the symptoms mentioned in this case are caused by graft-versus-host disease (GVHD) or a specific infection. Based on the result of metagenomic next-generation sequencing (mNGS) and clinical observation, the patient was diagnosed as E. hellem infection, and received albendazole and decreased the immunosuppressive treatment. Finally, he had recovered.ConclusionWe should pay attention to the uncommon disease caused by the E. hellem infection after HSCT, especially in cases with immune reconstitution unrecovered. Among those rare infection, mNGS can be performed for better understanding the source of infection and targeted therapy, which can benefit the patients

    Computed tomography guided electromagnetic navigation system in percutaneous laser ablation for treating primary lung cancer: a case report

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    BackgroundThe majority of patients of lung cancer have already lost the chance of surgery at the time of diagnosis. Percutaneous local thermal ablation is a precise minimally invasive technique and a viable alternative to surgical treatment. Compared with radiofrequency ablation and microwave ablation, percutaneous laser ablation for the treatment of lung tumors is less commonly used and reported, especially for primary lung cancer.Case presentationA 63-year-old male patient with mixed pulmonary nodules selected computed tomography-guided electromagnetic navigation system for percutaneous biopsy and laser ablation therapy. The puncture point was determined through Computed tomography scanning, along with the placement of the electromagnetic navigation system locators. After rapid on-site evaluation and pathological examination of the puncture tissue specimen, the diagnosis of lung adenocarcinoma was confirmed. A 980-nanometer wavelength semiconductor laser fiber was inserted into the appropriate position guided by the electromagnetic navigation system. Subsequently, a power of 7 watt was applied to ablate the tumor for 30 seconds, then pause for 60 seconds before repeating the procedure. Positron emission tomography-Computed tomography examination was performed 1 month after operation, suggesting complete response of the tumor.ConclusionHere, we present a case of percutaneous laser ablation treatment for primary lung cancer guided by computed tomography-electromagnetic navigation system. As a more precise, shorter duration, impedance-independent, safe and effective minimally invasive thermal ablation method, it is expected to gain wider application and become a novel alternative for surgical treatment

    A new integrated and homogenized global monthly land surface air temperature dataset for the period since 1900

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    A new dataset of integrated and homogenized monthly surface air temperature over global land for the period since 1900 [China Meteorological Administration global Land Surface Air Temperature (CMA-LSAT)] is developed. In total, 14 sources have been collected and integrated into the newly developed dataset, including three global (CRUTEM4, GHCN, and BEST), three regional and eight national sources. Duplicate stations are identified, and those with the higher priority are chosen or spliced. Then, a consistency test and a climate outlier test are conducted to ensure that each station series is quality controlled. Next, two steps are adopted to assure the homogeneity of the station series: (1) homogenized station series in existing national datasets (by National Meteorological Services) are directly integrated into the dataset without any changes (50% of all stations), and (2) the inhomogeneities are detected and adjusted for in the remaining data series using a penalized maximal t test (50% of all stations). Based on the dataset, we re-assess the temperature changes in global and regional areas compared with GHCN-V3 and CRUTEM4, as well as the temperature changes during the three periods of 1900–2014, 1979–2014 and 1998–2014. The best estimates of warming trends and there 95% confidence ranges for 1900–2014 are approximately 0.102 ± 0.006 °C/decade for the whole year, and 0.104 ± 0.009, 0.112 ± 0.007, 0.090 ± 0.006, and 0.092 ± 0.007 °C/decade for the DJF (December, January, February), MAM, JJA, and SON seasons, respectively. MAM saw the most significant warming trend in both 1900–2014 and 1979–2014. For an even shorter and more recent period (1998–2014), MAM, JJA and SON show similar warming trends, while DJF shows opposite trends. The results show that the ability of CMA-LAST for describing the global temperature changes is similar with other existing products, while there are some differences when describing regional temperature changes

    Vitamin D and cause-specific vascular disease and mortality:a Mendelian randomisation study involving 99,012 Chinese and 106,911 European adults

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    Household, community, sub-national and country-level predictors of primary cooking fuel switching in nine countries from the PURE study

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    Introduction. Switchingfrom polluting (e.g. wood, crop waste, coal)to clean (e.g. gas, electricity) cooking fuels can reduce household air pollution exposures and climate-forcing emissions.While studies have evaluated specific interventions and assessed fuel-switching in repeated cross-sectional surveys, the role of different multilevel factors in household fuel switching, outside of interventions and across diverse community settings, is not well understood. Methods.We examined longitudinal survey data from 24 172 households in 177 rural communities across nine countries within the Prospective Urban and Rural Epidemiology study.We assessed household-level primary cooking fuel switching during a median of 10 years offollow up (∼2005–2015).We used hierarchical logistic regression models to examine the relative importance of household, community, sub-national and national-level factors contributing to primary fuel switching. Results. One-half of study households(12 369)reported changing their primary cookingfuels between baseline andfollow up surveys. Of these, 61% (7582) switchedfrom polluting (wood, dung, agricultural waste, charcoal, coal, kerosene)to clean (gas, electricity)fuels, 26% (3109)switched between different polluting fuels, 10% (1164)switched from clean to polluting fuels and 3% (522)switched between different clean fuels

    Household, community, sub-national and country-level predictors of primary cooking fuel switching in nine countries from the PURE study

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