Autism Severity and Comorbid Symptoms in Children with ASD

Individuals with autism spectrum disorder (ASD) are reported to evince high rates of comorbid symptoms. Co-occurring disorders among individuals with ASD are often difficult to assess and diagnose accurately. Also, comorbid conditions frequently exacerbate symptoms of ASD. Different treatment regimens may be effective for comorbid symptoms in ASD; however, research looking at comorbid symptoms and ASD is limited. The current study aimed to extend the literature in this area by examining the relationship between ASD and comorbid symptoms. First, the current study assessed how often and how severely comorbid symptoms were endorsed. Further, autism severity was used to predict comorbid symptoms. Autism severity was measured using the Autism Spectrum Disorder- Diagnostic Child Version (ASD-DC), and comorbid symptoms were obtained using the Autism Spectrum Disorders-Comorbidity Child Version (ASD-CC). A simple regression was conducted using the ASD-DC total score as the predictor and ASD-CC total score as the dependent variable. Then, a series of regression analyses was conducted with ASD severity as the predictor and ASD-CC subscores as dependent variables. In the current study, a high rate of comorbid behaviors was reported. Also, the current study found that autism severity predicted overall comorbid symptoms. Specifically, autism severity significantly predicted repetitive behaviors, tantrum behaviors, and avoidant behaviors. This finding is of considerable clinical value as it suggests that individuals with more severe ASD symptoms also contend with greater comorbid symptoms. This is concerning as these comorbid symptoms alter symptom presentation and further exacerbate deficits, indicating that it is crucial for clinicians to routinely evaluate these comorbid symptoms. Further implications of these findings are discussed

An Initial Psychometric Evaluation of the Korean Version of the Matson Evaluation of Social Skills with Youngsters-II (K-Messy-II)

Social skills impairment in autism spectrum disorder (ASD) is often considered a hallmark of the disorder. Impairments in social skills impede the development of meaningful social relationships in individuals with ASD. As children get older, social relationships and environments become more complex, further increasing social skills impairments and distress. Although social skill training has received a lot of attention in the last decade, more reliable and valid social skills measures that are adapted to use in the ASD population are needed. Given that social norms and expectations differ across cultures, more culturally valid measures are needed. The Matson Evaluation of Social Skills with Youngsters-II (MESSY-II) is one of the most researched social skills measures that have been used internationally. To date, there are a limited number of social skills ratings scales in South Korea. Therefore, the current study examined the factor structure and psychometric properties of the Korean version of the MESSY-II (K-MESSY-II). In addition, potential differences among the factors with respect to age cohorts in Korean children and adolescents with ASD were examined. Finally, the cultural relevancy of the K-MESSY-II items was assessed. This study demonstrated that the K-MESSY-II is a psychometrically sound measure that may be used to enhance evaluation and treatment of social skills in children and adolescents, including those with ASD in South Korea

Spinal Stereotactic Body Radiotherapy (SBRT) Planning Techniques

Stereotactic body radiotherapy (SBRT) delivers a highly conformal and hypofractionated radiation dose to a small target with minimal radiation applied to the surrounding areas. The spine is an ideal site for SBRT owing to its relative immobility, the potential clinical benefits of high-dose delivery to this area, and the presence of adjacent critical structures such as the spinal cord, esophagus, and bowel. However, with the potential for radiation myelopathy if the dose is delivered inaccurately or if the spinal cord dose limit is set too high, proper treatment planning techniques for SBRT are important. Intensity modulation techniques are useful for spinal SBRT because of a rapid dose falloff and spinal cord avoidance. In this chapter, various planning techniques will be discussed and reviewed

The mapKurator System: A Complete Pipeline for Extracting and Linking Text from Historical Maps

Documents hold spatial focus and valuable locality characteristics. For example, descriptions of listings in real estate or travel blogs contain information about specific local neighborhoods. This information is valuable to characterize how humans perceive their environment. However, the first step to making use of this information is to identify the spatial focus (e.g., a city) of a document. Traditional approaches for identifying the spatial focus of a document rely on detecting and disambiguating toponyms from the document. This approach requires a vocabulary set of location phrases and ad-hoc rules, which ignore important words related to location. Recent topic modeling approaches using large language models often consider a few topics, each with broad coverage. In contrast, the spatial focus of a document can be a country, a city, or even a neighborhood, which together, is much larger than the number of topics considered in these approaches. Additionally, topic modeling methods are often applied to broad topics of news articles where context is easily distinguishable. To identify the geographic focus of a document effectively, we present a simple but effective Joint Embedding of multi-LocaLitY (JELLY), which jointly learns representations with separate encoders of document and location. JELLY significantly outperforms state-of-the-art methods for identifying spatial focus from documents from a number of sources. We also demonstrate case studies on the arithmetic of the learned representations, including identifying cities with similar locality characteristics and zero-shot learning to identify document spatial focus.Comment: 4 pages, 4 figure

Ovarian Gynandroblastoma with a Juvenile Granulosa Cell Tumor Component in a Postmenopausal Woman: A Case Report and Literature Review

Gynandroblastoma is an extremely rare sex cord-stromal tumor with both female (granulosa cell tumor) and male (Sertoli-Leydig cell tumor) elements. Juvenile granulosa cell tumors are also very rare and are so named because they usually occur in children and adolescents. A 71-year-old woman with right upper quadrant abdominal pain visited our hospital. Pelvic computed tomography showed a large multilocular cystic mass, suspected to be of ovarian origin. We performed a total abdominal hysterectomy (total abdominal hysterectomy was performed) with bilateral salpingo-oophorectomy. A 13-cm multilocular cystic mass with serous fluid was observed in her right ovary. Upon microscopic examination, the solid component of the mass showed both Sertoli-Leydig cell and juvenile granulosa cell differentiation, which we diagnosed as gynandroblastoma. Gynandroblastoma with a juvenile granulosa cell tumor component is extremely rare and, until now, only six cases have been reported in the English literature. We report the first gynandroblastoma with a juvenile granulosa cell tumor component diagnosed in an elderly patient, along with a literature review

Between comments and repeat visit: capturing repeat visitors with a hybrid approach

Purpose Understanding customers' revisiting behavior is highlighted in the field of service industry and the emergence of online communities has enabled customers to express their prior experience. Thus, purpose of this study is to investigate customers' reviews on an online hotel reservation platform, and explores their postbehaviors from their reviews. Design/methodology/approach The authors employ two different approaches and compare the accuracy of predicting customers' post behavior: (1) using several machine learning classifiers based on sentimental dimensions of customers' reviews and (2) conducting the experiment consisted of two subsections. In the experiment, the first subsection is designed for participants to predict whether customers who wrote reviews would visit the hotel again (referred to as Prediction), while the second subsection examines whether participants want to visit one of the particular hotels when they read other customers' reviews (dubbed as Decision). Findings The accuracy of the machine learning approaches (73.23%) is higher than that of the experimental approach (Prediction: 58.96% and Decision: 64.79%). The key reasons of users' predictions and decisions are identified through qualitative analyses. Originality/value The findings reveal that using machine learning approaches show the higher accuracy of predicting customers' repeat visits only based on employed sentimental features. With the novel approach of integrating customers' decision processes and machine learning classifiers, the authors provide valuable insights for researchers and providers of hospitality services

Self supervised convolutional kernel based handcrafted feature harmonization: Enhanced left ventricle hypertension disease phenotyping on echocardiography

Radiomics, a medical imaging technique, extracts quantitative handcrafted features from images to predict diseases. Harmonization in those features ensures consistent feature extraction across various imaging devices and protocols. Methods for harmonization include standardized imaging protocols, statistical adjustments, and evaluating feature robustness. Myocardial diseases such as Left Ventricular Hypertrophy (LVH) and Hypertensive Heart Disease (HHD) are diagnosed via echocardiography, but variable imaging settings pose challenges. Harmonization techniques are crucial for applying handcrafted features in disease diagnosis in such scenario. Self-supervised learning (SSL) enhances data understanding within limited datasets and adapts to diverse data settings. ConvNeXt-V2 integrates convolutional layers into SSL, displaying superior performance in various tasks. This study focuses on convolutional filters within SSL, using them as preprocessing to convert images into feature maps for handcrafted feature harmonization. Our proposed method excelled in harmonization evaluation and exhibited superior LVH classification performance compared to existing methods.Comment: 11 pages, 7 figure

Long-term risk of all-cause mortality in live kidney donors: a matched cohort study

Background Long-term outcomes of live kidney donors remain controversial, although this information is crucial for selecting potential donors. Thus, this study compared the long-term risk of all-cause mortality between live kidney donors and healthy control. Methods We performed a retrospective cohort study including donors from seven tertiary hospitals in South Korea. Persons who underwent voluntary health screening were included as controls. We created a matched control group considering age, sex, era, body mass index, baseline hypertension, diabetes, estimated glomerular filtration rate, and dipstick albuminuria. The study outcome was progression to end-stage kidney disease (ESKD), and all-cause mortality as identified in the linked claims database. Results We screened 1,878 kidney donors and 78,115 health screening examinees from 2003 to 2016. After matching, 1,701 persons remained in each group. The median age of the matched study subjects was 44 years, and 46.6% were male. Among the study subjects, 2.7% and 16.6% had underlying diabetes and hypertension, respectively. There were no ESKD events in the matched donor and control groups. There were 24 (1.4%) and 12 mortality cases (0.7%) in the matched donor and control groups, respectively. In the age-sex adjusted model, the risk for all-cause mortality was significantly higher in the donor group than in the control group. However, the significance was not retained after socioeconomic status was included as a covariate (adjusted hazard ratio, 1.82; 95% confidence interval, 0.87–3.80). Conclusion All-cause mortality was similar in live kidney donors and matched non-donor healthy controls with similar health status and socioeconomic status in the Korean population

Metabolic risks in living kidney donors in South Korea

Background Considering the growing prevalence of Western lifestyles and related chronic diseases occurring in South Korea, this study aimed to explore the progression of metabolic risk factors in living kidney donors. Methods This study enrolled living kidney donors from seven hospitals from 1982 to 2016. The controls were individuals that voluntarily received health check-ups from 1995 to 2016 that were matched with donors according to age, sex, diabetes status, baseline estimated glomerular filtration rate, and date of the medical record. Data on hyperuricemia, hypertension, hypercholesterolemia, and overweight/obesity were collected to determine metabolic risks. Logistic regressions with interaction terms between the medical record date and donor status were used to compare the trends in metabolic risks over time in the two groups. Results A total of 2,018 living kidney donors and matched non-donors were included. The median age was 44.0 years and 54.0% were women. The living kidney donors showed a lower absolute prevalence for all metabolic risk factors, except for those that were overweight/obese, than the non-donors. The proportion of subjects that were overweight/obese was consistently higher over time in the donor group. The changes over time in the prevalence of each metabolic risk were not significantly different between groups, except for a lower prevalence of metabolic risk factors ≥ 3 in donors. Conclusion Over time, metabolic risks in living kidney donors are generally the same as in non-donors, except for a lower prevalence of metabolic risk factors ≥3 in donors