Annual Change in Fungal Concentrations and Allergic Sensitization Rates to Alternaria and Cladosporium in Korea During the Period 1998-2022.

PURPOSE: Atmospheric fungi are associated with respiratory allergies in humans, and some fungal spores can cause allergic diseases. Environmental and biological factors influence the concentrations of atmospheric spores. In this study, we evaluated the climate change-induced annual variations in fungal spore concentrations and allergic sensitization rates in the Seoul Metropolitan Area over a period of 25 years. METHODS: Fungal spores and pollen were obtained from Hanyang University Seoul and Guri Hospitals; they were identified and counted for 25 years (1998-2022). The study participants included patients who underwent tests for allergic diseases in both hospitals. Their allergenic sensitization rates were determined via allergic skin prick and serum tests, after which their sensitization rates to allergenic fungi and pollens were calculated. The daily climatic variables were obtained from the Korea Meteorological Administration. RESULTS: The total annual atmospheric fungal concentrations decreased in both areas during the period. Simultaneously, we recruited 21,394 patients with allergies (asthma, 1,550; allergic rhinitis, 5,983; and atopic dermatitis, 5,422) from Seoul and Guri Hospitals for allergenic fungal sensitization evaluations over the period. The allergenic fungal sensitization rates decreased annually in both areas over that time `+(Alternaria [3.5%] and Cladosporium [4.4%] in 1998; Alternaria [0.2%] and Cladosporium [0.2%] in 2022). In contrast, the annual pollen concentrations increased with the sensitization rates to pollen in children. CONCLUSIONS: The atmospheric fungal concentrations decreased annually, with allergic sensitization rate decreasing over the period of 25 years. Allergenic fungal sporulation could decrease with climate changes, such as desertification and drought. Extended monitoring periods and further large-scale studies are required to confirm the causality and to evaluate the impact of climate change.

Increased sensitization rates to tree pollens in allergic children and adolescents and a change in the pollen season in the metropolitan area of Seoul, Korea.

INTRODUCTION: Children with allergies are at greater risk of becoming sensitized to allergenic pollens in response to environmental changes. This study investigated the relationship between changes in pollination associated with meteorologic changes and the sensitization rates of children to tree pollen allergens in the metropolitan area of Seoul, Korea. METHODS: The study population consisted of 8,295 children who visited the pediatric allergy clinics at Hanyang University Seoul and Guri Hospital for allergy symptoms between January 1, 1998, and December 31, 2019. Pollen was collected at the two hospitals during the study using a Burkard 7-day sampler. Meteorologic data were obtained from the National Weather Service. RESULTS: Among the major tree pollens, the largest increase in allergic sensitization was to oak, hazel, and alder pollens (0.28% annually). The pollen-sensitization rates increased annually within younger age groups. The duration of the pollen season was 98 days in 1998 and 140 days in 2019. Positive correlations were determined between the duration of the pollen season and the rates of sensitization to tree pollens, as well as between the pollen-sensitization rates and increasing temperature. CONCLUSIONS: This study demonstrated the correlation between weather changes and the resulting changes in the pollen season with sensitization rates to allergenic pollens in children living in the Seoul metropolitan area. An annual increase in sensitization rates in younger children was determined. This pattern is expected to continue due to continuing climate change.

Can We Determine Sasang Constitutional Body Type Merely by Facial Inspection?

OBJECTIVES: This study aimed to assess the inter-observer concordance rate of anthroscopic examination on facial features among experts in Sasang constitutional medicine (SCM) in order to evaluate the presence of statistical differences in facial structural characteristics among different body types of Sasang constitution (SC), and to develop an objective method for facial analysis for diagnosing SC types to prevent SCM experts from misdiagnosis by their perceptional errors about faces. METHODS: This was a double-blinded cross-sectional study conducted on 174 people's faces. Ten SCM experts participated in this study. Frontal and lateral photographs of subjects were standardized and displayed to 10 SCM experts for diagnosing the SC type by anthroscopic examination alone (experiment 1). The subjects' faces were analyzed by photogrammetric method to investigate the presence of any typical structural characteristics of the faces to differentiate SC type (experiment 2). Comparing subjects' SC type with anthroscopic diagnosis by 10 SCM experts, the inter-observer concordance rates were measured (experiment 1). Using photogrammetric facial analysis, a multinomial logistic model was made for analyzing the correlation of SC type and subjects' facial structural configuration (experiment 2). RESULTS: The inter-observer concordance rate of anthroscopic examination was 2.9% in experiment 1. Using a multinomial logistic fitting model, the predicted probability for determining SC type was 52.8-57.6% in experiment 2 (p < 0.05). Prototype composite faces were also created from photographs of subjects who received the same SC type from the SCM experts. CONCLUSIONS: As SC type cannot be precisely diagnosed using anthroscopic examination alone, SCM needs a definitive objective and scientific diagnosing method to be a scientifically verified alternative medicine and be globalized in future.

Photogrammetric Analysis of Attractiveness in Indian Faces.

BACKGROUND: The objective of this study was to assess the attractive facial features of the Indian population. We tried to evaluate subjective ratings of facial attractiveness and identify which facial aesthetic subunits were important for facial attractiveness. METHODS: A cross-sectional study was conducted of 150 samples (referred to as candidates). Frontal photographs were analyzed. An orthodontist, a prosthodontist, an oral surgeon, a dentist, an artist, a photographer and two laymen (estimators) subjectively evaluated candidates' faces using visual analog scale (VAS) scores. As an objective method for facial analysis, we used balanced angular proportional analysis (BAPA). Using SAS 10.1 (SAS Institute Inc.), the Turkey's studentized range test and Pearson correlation analysis were performed to detect between-group differences in VAS scores (Experiment 1), to identify correlations between VAS scores and BAPA scores (Experiment 2), and to analyze the characteristic features of facial attractiveness and gender differences (Experiment 3); the significance level was set at P=0.05. RESULTS: Experiment 1 revealed some differences in VAS scores according to professional characteristics. In Experiment 2, BAPA scores were found to behave similarly to subjective ratings of facial beauty, but showed a relatively weak correlation coefficient with the VAS scores. Experiment 3 found that the decisive factors for facial attractiveness were different for men and women. Composite images of attractive Indian male and female faces were constructed. CONCLUSIONS: Our photogrammetric study, statistical analysis, and average composite faces of an Indian population provide valuable information about subjective perceptions of facial beauty and attractive facial structures in the Indian population.

Resampling-based similarity measures for high-dimensional data.

An important issue in classification is the assessment of sample similarity. This is nontrivial in high-dimensional or megavariate datasets--datasets that are comprised of simultaneous measurements on thousands of features, many of which carry little or no information regarding consistent sample differences. Conventional similarity measures do not work particularly well for such data. As an alternative, we propose a distance measure that is based on a refiltering process: at each step of the process a random subset of features is selected and a cluster analysis is performed using only this subset; the relative frequency with which a pair of samples clusters together across several such random subsets forms the similarity measure. The features chosen at any step may be completely random or enriched by awarding the more informative features a higher chance of selection; this enrichment turns out to be particularly effective. We use actual datasets from the burgeoning genomics literature to demonstrate the superior performance of this similarity measure, especially the enriched form of the similarity measure, compared to more conventional measures such as Euclidean distance or correlation, or, if the data are categorical, Hamming distance.

Assessment of anthropogenic influences on surface water quality in urban estuary, northern New Jersey: multivariate approach.

Concentrations of selected heavy metals (Cd, Cr, Cu, Pb, Ni, Fe, and Zn), nutrients (NO (3) (-) and NH(3)), fecal coliform colonies, and other multiple physical-chemical parameters were measured seasonally from 12 locations in an urban New Jersey estuary between 1994 and 2008. Stepwise regression, principal component analysis, and cluster analysis were used to group water quality results and sampling locations, as well as to assess these data's relationship to sewage treatment effluents and the distance to the mouth of the river. The BOD(5), NH(3), NO (3) (-) and fecal coliform counts clustered as one group and positively correlated to the distances from treated effluent and the measures of magnitude at the discharge points. Dissolved solids and most metal species scored high along a single principal component axes and were significantly correlated with the proximity to the industrialized area. From these data, one can conclude that the effluent discharge has been a main source of anthropogenic input to the Hackensack River over the past 15 years. Therefore, the greatest improvement to water quality would come from eliminating the few remaining combined sewer overflows and improving the removal of nutrients from treated effluents before they are discharged into the creeks and river.

Mucosal expression of ENaC and AQP in experimental otitis media induced by Eustachian tube obstruction.

OBJECTIVE: We investigated the expression of the epithelial sodium channel (ENaC) and aquaporins (AQPs) in the middle ear mucosa of a rat model of otitis media with effusion caused by surgical obstruction of the Eustachian tube. METHODS: Sixty-four rats were randomly assigned to either undergo unilateral Eustachian tube obstruction (groups 1, 2, and 3) or to undergo no procedure (control group). Bony Eustachian tubes were approached through ventral incisions and obstructed with electrocautery. On days 14, 28, and 56, the ears were evaluated, and the rats were sacrificed for otoscopic evaluation and real-time RT-PCR. Immunohistochemistry was done for ENaC-alpha and AQP-1. RESULTS: The level of ENaC-alpha expression decreased 0.28- and 0.73-fold at 2 and 4 weeks, respectively, but increased 1.48-fold at 8 weeks (p<0.05). The change in ENaC-beta expression at 2 weeks was insignificant. However, the level of ENaC-beta expression increased 3.17- and 7.85-fold at 4 and 8 weeks, respectively (p<0.05). The level of ENaC-gamma expression increased 1.51-, 4.82- and 14.79-fold at 2, 4 and 8 weeks, respectively (p<0.05). The level of AQP-1 expression decreased 0.10- and 0.04-fold at 4 and 8 weeks, respectively (p<0.05). The change in AQP4 expression at 4 and 8 weeks was insignificant (p>0.05). The pattern of immunoreactivity of ENaC-alpha and AQP-1 was similar with that of gene expression. CONCLUSION: The experimental methods provoked reproducible otitis media with effusion. This model is well suited for studies of middle ear homeostasis during disease pathogenesis. Middle ear mucosa homeostasis is altered significantly by ETO, and the subunits of AQP proteins show a characteristic expression pattern over time.

Enriched random forests.

Although the random forest classification procedure works well in datasets with many features, when the number of features is huge and the percentage of truly informative features is small, such as with DNA microarray data, its performance tends to decline significantly. In such instances, the procedure can be improved by reducing the contribution of trees whose nodes are populated by non-informative features. To some extent, this can be achieved by prefiltering, but we propose a novel, yet simple, adjustment that has demonstrably superior performance: choose the eligible subsets at each node by weighted random sampling instead of simple random sampling, with the weights tilted in favor of the informative features. This results in an 'enriched random forest'. We illustrate the superior performance of this procedure in several actual microarray datasets.