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Abstract Objectives: To investigate the diagnostic performance of single-source dual-energy computed tomography (DECT) based on gemstone spectral imaging technology (including Discovery CT750HD and Revolution CT) in patients with suspected feet/ankles gouty arthritis, and evaluate the urate deposition with a novel semi-quantitative DECT scoring system. Methods: A total of 196 patients were consecutively included. Feet and ankles were evaluated in all patients by single-source DECT scan. The 2015 EULAR/ACR criteria were used as the reference for the diagnosis of gout. The sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of DECT for the diagnosis of gout in the early (≤1 year), middle (1-3 years), and late (> 3 years) disease durations were calculated. Besides, a novel semi-quantitative DECT scoring system was assessed for the measurement of urate deposition, and the correlation between the scores and the clinical and serological data were also evaluated. Moreover, the influences of artifacts on the diagnostic performance of DECT were also determined. Results: The sensitivity, specificity, and AUC of DECT in 196 patients were 38.10, 96.43%, and 0.673 in the early-stage group; 62.96, 100.00%, and 0.815 in the middle-stage group; and 77.55, 87.50%, and 0.825 in the late-stage group, respectively. The overall diagnostic accuracies in the AUC of DECT (Discovery CT750HD and Revolution CT) in the middle and late stages of gout were higher than that in the early stage of gout. Besides, the monosodium urate crystals were deposited on the first metatarsophalangeal joints and ankles/midfeet. Age, the presence of tophus, bone erosion, and disease duration considerably affected the total urate score. No statistical difference in the positive detection of nail artifact, skin artifact, vascular calcification, and noise artifact was found between the case and control groups. Conclusion: DECT (Discovery CT750HD and Revolution CT) showed promising diagnostic accuracy for the detection of urate crystal deposition in gout but had limited diagnostic sensitivity for short-stage gout. Longer disease duration, the presence of tophus, and bone erosion were associated with the urate crystal score system. The artifacts do not remarkably affect the diagnostic performance of DECT in gout.

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In previous observational studies, we have separately characterized patients with multiple myeloma (MM) both from Latin America (LA) and from Asia. Here, we analyze these two datasets jointly, in order to assess the overall survival (OS) in these two world regions. Data were available from 3664 patients (1968 from LA and 1696 from Asia); all of whom diagnosed between 1998 and 2007. Approximately, 26% of patients in both world regions underwent transplantation. OS (from diagnosis of MM) was explored with Kaplan-Meier analyses and Cox proportional hazards models. Patients from LA were significantly younger and had hypercalcemia more often than Asian patients, who in turn had higher proportions of anemia and International Staging System (ISS) stage III disease. The median OS was 56 months in LA, and 47 months in Asia (hazard ratio [HR] = 0.83; 95% confidence interval [CI], 0.76 to 0.91; P < 0.001). In multivariable analysis, age, ISS stage III, anemia, hypercalcemia, and world region remained significantly associated with OS (P < 0.001 for all covariates). These results were largely driven by patients not undergoing transplantation, as no difference in OS emerged between the two world regions in univariable or multivariable analysis for transplanted patients. Despite adverse prognostic features differentially favoring each region, and adjusting for such differences, we found an OS advantage for patients from LA, in comparison with contemporaneous patients from Asia. Whether this is due to different biological features, differences in access to novel agents (especially thalidomide in earlier periods of the study), unmeasured confounders, or the play of chance, remain unknown.

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We develop a novel statistical approach for classifying generalists and specialists in two distinct habitats. Using a multinomial model based on estimated species relative abundance in two habitats, our method minimizes bias due to differences in sampling intensities between two habitat types as well as bias due to insufficient sampling within each habitat. The method permits a robust statistical classification of habitat specialists and generalists, without excluding rare species a priori. Based on a user-defined specialization threshold, the model classifies species into one of four groups: (1) generalist; (2) habitat A specialist; (3) habitat B specialist; and (4) too rare to classify with confidence. We illustrate our multinomial classification method using two contrasting data sets: (1) bird abundance in woodland and heath habitats in southeastern Australia and (2) tree abundance in second-growth (SG) and old-growth (OG) rain forests in the Caribbean lowlands of northeastern Costa Rica. We evaluate the multinomial model in detail for the tree data set. Our results for birds were highly concordant with a previous nonstatistical classification, but our method classified a higher fraction (57.7%) of bird species with statistical confidence. Based on a conservative specialization threshold and adjustment for multiple comparisons, 64.4% of tree species in the full sample were too rare to classify with confidence. Among the species classified, OG specialists constituted the largest class (40.6%), followed by generalist tree species (36.7%) and SG specialists (22.7%). The multinomial model was more sensitive than indicator value analysis or abundance-based phi coefficient indices in detecting habitat specialists and also detects generalists statistically. Classification of specialists and generalists based on rarefied subsamples was highly consistent with classification based on the full sample, even for sampling percentages as low as 20%. Major advantages of the new method are (1) its ability to distinguish habitat generalists (species with no significant habitat affinity) from species that are simply too rare to classify and (2) applicability to a single representative sample or a single pooled set of representative samples from each of two habitat types. The method as currently developed can be applied to no more than two habitats at a time.

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Primary cutaneous amyloidosis (PCA) is an itchy skin disorder associated with amyloid deposits in the superficial dermis. The disease is relatively common in Southeast Asia and South America. Autosomal dominant PCA has been mapped earlier to 5p13.1-q11.2 and two pathogenic missense mutations in the OSMR gene, which encodes the interleukin-6 family cytokine receptor oncostatin M receptor beta (OSMRbeta), were reported. Here, we investigated 29 Taiwanese pedigrees with PCA and found that 10 had heterozygous missense mutations in OSMR: p.D647V (one family), p.P694L (six families), and p.K697T (three families). The mutation p.P694L was associated with the same haplotype in five of six families and also detected in two sporadic cases of PCA. Of the other 19 pedigrees that lacked OSMR pathology, 8 mapped to the same locus on chromosome 5, which also contains the genes for 3 other interleukin-6 family cytokine receptors, including interleukin-31 receptor A (IL31RA), which can form a heterodimeric receptor with OSMRbeta through interleukin-31 signaling. In one family, we identified a point mutation in the IL31RA gene, c.1562C>T that results in a missense mutation, p.S521F, which is also sited within a fibronectin type III-like repeat domain as observed in the OSMR mutations. PCA is a genetically heterogeneous disorder but our study shows that it can be caused by mutations in two biologically associated cytokine receptor genes located on chromosome 5. The identification of OSMR and IL31RA gene pathology provides an explanation of the high prevalence of PCA in Taiwan as well as new insight into disease pathophysiology.

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