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These results signify that all four dimensions of HRQOL represented by the BRFSS Core HRQOL Module are important predictors of both short-term and long-term adverse health events among older adults. This brief scale may be particularly useful for assessing the health of older adults in clinical settings and large-scale epidemiological studies.

The whole-brain functional connectivity (FC) pattern obtained from resting-state functional magnetic resonance imaging data are commonly applied to study neuropsychiatric conditions such as autism spectrum disorder (ASD) by using different machine learning models. Recent studies indicate that both hyper- and hypo- aberrant ASD-associated FCs were widely distributed throughout the entire brain rather than only in some specific brain regions. Deep neural networks (DNN) with multiple hidden layers have shown the ability to systematically extract lower-to-higher level information from high dimensional data across a series of neural hidden layers, significantly improving classification accuracy for such data. In this study, a DNN with a novel feature selection method (DNN-FS) is developed for the high dimensional whole-brain resting-state FC pattern classification of ASD patients vs. typical development (TD) controls. The feature selection method is able to help the DNN generate low dimensional high-quality representations of the whole-brain FC patterns by selecting features with high discriminating power from multiple trained sparse auto-encoders. For the comparison, a DNN without the feature selection method (DNN-woFS) is developed, and both of them are tested with different architectures (i.e., with different numbers of hidden layers/nodes). Results show that the best classification accuracy of 86.36% is generated by the DNN-FS approach with 3 hidden layers and 150 hidden nodes (3/150). Remarkably, DNN-FS outperforms DNN-woFS for all architectures studied. The most significant accuracy improvement was 9.09% with the 3/150 architecture. The method also outperforms other feature selection methods, e.g., two sample t-test and elastic net. In addition to improving the classification accuracy, a Fisher's score-based biomarker identification method based on the DNN is also developed, and used to identify 32 FCs related to ASD. These FCs come from or cross different pre-defined brain networks including the default-mode, cingulo-opercular, frontal-parietal, and cerebellum. Thirteen of them are statically significant between ASD and TD groups (two sample t-test p < 0.05) while 19 of them are not. The relationship between the statically significant FCs and the corresponding ASD behavior symptoms is discussed based on the literature and clinician's expert knowledge. Meanwhile, the potential reason of obtaining 19 FCs which are not statistically significant is also provided.

Objective. To examine the relationship between health-related quality of life (HRQOL) and health service use among older adults with osteoarthritis (OA). Methods. Subjects were 9,043 Medicare-enrolled survey respondents with a prior International Classification of Diseases, Ninth Revision code for OA. Analyses examined the relationship of 5 Centers for Disease Control and Prevention HRQOL items (general health, mental health, pain, activity limitation, and sleep) to physician visits, prescription analgesic or antiinflammatory use, and arthroplasty during 1 year of followup. Results. In analyses controlling for demographic and health-related variables, greater pain frequency was associated with increased odds of visiting a physician, using analgesic or antiinflammatory drugs, and having arthroplasty (P < 0.001). Poorer general health was associated with increased odds of analgesic or antiinflammatory use but decreased odds of arthroplasty (P < 0.01). More days of activity limitation and poor mental health were associated with decreased odds of analgesic or antiinflammatory use (P < 0.01). Conclusion. These HRQOL variables, especially pain frequency, can be valuable tools for estimating future health care use among older adults with OA.

Language and communication deficits are among the core features of autism spectrum disorder (ASD). Reduced or reversed asymmetry of language has been found in a number of disorders, including ASD. Studies of healthy adults have found an association between language laterality and anatomical measures but this has not been systematically investigated in ASD. The goal of this study was to examine differences in gray matter volume of perisylvian language regions, connections between language regions, and language abilities in individuals with typical left lateralized language compared to those with atypical (bilateral or right) asymmetry of language functions. 14 adolescent boys with ASD and 20 typically developing adolescent boys participated, including equal numbers of left-and right-handed individuals in each group. Participants with typical left lateralized language activation had smaller frontal language region volume and higher fractional anisotropy of the arcuate fasciculus compared to the group with atypical language laterality, across both ASD and control participants. The group with typical language asymmetry included the most right-handed controls and fewest left-handers with ASD. Atypical language laterality was more prevalent in the ASD than control group. These findings support an association between laterality of language function and language region anatomy. They also suggest anatomical differences may be more associated with variation in language laterality than specifically with ASD. Language laterality therefore may provide a novel way of subdividing samples, resulting in more homogenous groups for research into genetic and neurocognitive foundations of developmental disorders.

Objective. Little is known about how specific radiographic features are related to hand strength in osteoarthritis (OA). This study examined associations of radiographic variables with pinch and grip strength among individuals with radiographic hand OA.Methods. Participants (n ‫؍‬ 700, 80% female, mean age 69 years) were part of a study on the genetics of generalized OA. All had bilateral radiographic hand OA. Linear models were used to examine associations of grip and pinch strength with 1) OA in joint groups (proximal interphalangeal, metacarpophalangeal [MCP], carpometacarpal [CMC]), 2) OA in rays (first through fifth), and 3) summed Kellgren/Lawrence (K/L) grades for severity of OA in all joints. Adjusted models controlled for age, sex, hand pain, chondrocalcinosis, and hand hypermobility. Mixed models accounted for clustering within families.Results. In bivariate analyses, all joint groups, all rays, and total summed K/L grades were significantly negatively associated with grip and pinch strength (P < 0.05). In adjusted models, the only joint group significantly associated with grip strength was the CMCs, and only OA in the MCP joint was significantly associated with pinch strength (P < 0.05). The only ray significantly associated with grip strength (P < 0.05) was ray 1, and no individual rays were significantly associated with pinch strength. A higher summed K/L grade was significantly associated with both lower grip strength and lower pinch strength.Conclusion. Among individuals with radiographic hand OA, increasing radiographic severity is associated with reduced grip and pinch strength, even when controlling for self-reported pain. Individuals with radiographic OA in specific locations (CMC joints, MCP joints, and ray 1) may be at particular risk for reduced hand strength.

BackgroundFragile X syndrome (FXS) is the leading inherited cause of autism spectrum disorder, but there remains debate regarding the clinical presentation of social deficits in FXS. The aim of this study was to compare individuals with FXS to typically developing controls (TDC) and individuals with idiopathic autism spectrum disorder (ASD) across two social eye tracking paradigms.MethodsIndividuals with FXS and age- and gender-matched TDC and individuals with idiopathic ASD completed emotional face and social preference eye tracking tasks to evaluate gaze aversion and social interest, respectively. Participants completed a battery of cognitive testing and caregiver-reported measures for neurobehavioral characterization.ResultsIndividuals with FXS exhibited reduced eye and increased mouth gaze to emotional faces compared to TDC. Gaze aversive findings were found to correlate with measures of anxiety, social communication deficits, and behavioral problems. In the social interest task, while individuals with idiopathic ASD showed significantly less social preference, individuals with FXS displayed social preference similar to TDC.ConclusionsThese findings suggest fragile X syndrome social deficits center on social anxiety without the prominent reduction in social interest associated with autism spectrum disorder. Specifically designed eye tracking techniques clarify the nature of social deficits in fragile X syndrome and may have applications to improve phenotyping and evaluate interventions targeting social functioning impairments.

Objective. To compare the ability of 3 database-derived comorbidity scores, the Charlson Score, Elixhauser method, and RxRisk-V, in predicting health service use among individuals with osteoarthritis (OA). Methods. The study population comprised 306 patients who were under care for OA in the Veterans Affairs (VA) health care system. Comorbidity scores were calculated using 1 year of data from VA inpatient and outpatient databases (Charlson Score, Elixhauser method), as well as pharmacy data (RxRisk-V). Model selection was used to identify the best comorbidity index for predicting 3 health service use variables: number of physician visits, number of prescriptions used, and hospitalization probability. Specifically, Akaike's Information Criterion (AIC) was used to determine the best model for each health service outcome variable. Model fit was also evaluated. Results. All 3 comorbidity indices were significant predictors of each health service outcome (P < 0.01). However, based on AIC values, models using the RxRisk-V and Elixhauser indices as predictor variables were better than models using the Charlson Score. The model using the RxRisk-V index as a predictor was the best for the outcome of prescription medication use, and the model with the Elixhauser index was the best for the outcome of physician visits. Conclusion. The Rx-Risk-V and Elixhauser are suitable comorbidity measures for examining health services use among patients with OA. Both indices are derived from administrative databases and can efficiently capture comorbidity among large patient populations.