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Trismus/reduced mouth opening (RMO) is a common side effect of radiotherapy (RT) for head and neck cancer (HNC). The objective was to measure RMO, identify risk factors for RMO, and determine its impact on quality of life (QOL). OraRad is an observational, prospective, multicenter cohort study of patients receiving curative intent RT for HNC. Interincisal mouth opening measurements (n = 565) and patient-reported outcomes were recorded before RT and every 6 months for 2 years. Linear mixed-effects models were used to evaluate change in mouth opening and assess the relationship between trismus history and change in QOL measures. Interincisal distance decreased from a mean (SE) of 45.1 (0.42) mm at baseline to 42.2 (0.44) at 6 months, with slight recovery at 18 months (43.3, 0.46 mm) but no additional improvement by 24 months. The odds of trismus (opening <35 mm) were significantly higher at 6 months (odds ratio [OR] = 2.21, 95% CI: 1.30 to 3.76) and 12 months (OR = 1.87, 95% CI: 1.08 to 3.25) compared with baseline. Females were more likely to experience trismus at baseline and during follow-up (P <.01). Patients with oral cavity cancer had the highest risk for trismus at baseline and post-RT (P <.01). RMO was associated with higher RT dose to the primary site and receiving concomitant chemotherapy (P <.01). Trismus was associated with self-reported difficulty opening the mouth and dry mouth (P <.01). A decrease in mouth opening is a common treatment-related toxicity after RT, with some recovery by 18 months. Trismus has a significant impact on survivor QOL. [ABSTRACT FROM AUTHOR]

Abstract Background Mechanistic biosimulation can be used in drug development to form testable hypotheses, develop predictions of efficacy before clinical trial results are available, and elucidate clinical response to therapy. However, there is a lack of tools to simultaneously (1) calibrate the prevalence of mechanistically distinct, large sets of virtual patients so their simulated responses statistically match phenotypic variability reported in published clinical trial outcomes, and (2) explore alternate hypotheses of those prevalence weightings to reflect underlying uncertainty in population biology. Here, we report the development of an algorithm, MAPEL (Mechanistic Axes Population Ensemble Linkage), which utilizes a mechanistically-based weighting method to match clinical trial statistics. MAPEL is the first algorithm for developing weighted virtual populations based on biosimulation results that enables the rapid development of an ensemble of alternate virtual population hypotheses, each validated by a composite goodness-of-fit criterion. Results Virtual patient cohort mechanistic biosimulation results were successfully calibrated with an acceptable composite goodness-of-fit to clinical populations across multiple therapeutic interventions. The resulting virtual populations were employed to investigate the mechanistic underpinnings of variations in the response to rituximab. A comparison between virtual populations with a strong or weak American College of Rheumatology (ACR) score in response to rituximab suggested that interferon β (IFNβ) was an important mechanistic contributor to the disease state, a signature that has previously been identified though the underlying mechanisms remain unclear. Sensitivity analysis elucidated key anti-inflammatory properties of IFNβ that modulated the pathophysiologic state, consistent with the observed prognostic correlation of baseline type I interferon measurements with clinical response. Specifically, the effects of IFNβ on proliferation of fibroblast-like synoviocytes and interleukin-10 synthesis in macrophages each partially counteract reductions in synovial inflammation imparted by rituximab. A multianalyte biomarker panel predictive for virtual population therapeutic responses suggested population dependencies on B cell-dependent mediators as well as additional markers implicating fibroblast-like synoviocytes. Conclusions The results illustrate how the MAPEL algorithm can leverage knowledge of cellular and molecular function through biosimulation to propose clear mechanistic hypotheses for differences in clinical populations. Furthermore, MAPEL facilitates the development of multianalyte biomarkers prognostic of patient responses in silico.

Hereditary sensory and autonomic neuropathy type 1 (HSAN1) causes sensory loss that predominantly affects the lower limbs, often preceded by hyperpathia and spontaneous shooting or lancinating pain. It is caused by several missense mutations in the genes encoding 2 of the 3 subunits of the enzyme serine palmitoyltransferase (SPT). The mutant forms of the enzyme show a shift from their canonical substrate L-serine to the alternative substrate L-alanine. This shift leads to increased formation of neurotoxic deoxysphingolipids (dSLs). Our initial analysis showed that in HEK cells transfected with SPTLC1 mutants, dSL generation was modulated in vitro in the presence of various amino acids. We therefore examined whether in vivo specific amino acid substrate supplementation influenced dSL levels and disease severity in HSAN1. In mice bearing a transgene expressing the C133W SPTLC1 mutant linked to HSAN1, a 10% L-serine-enriched diet reduced dSL levels. L-serine supplementation also improved measures of motor and sensory performance as well as measures of male fertility. In contrast, a 10% L-alanine-enriched diet increased dSL levels and led to severe peripheral neuropathy. In a pilot study with 14 HSAN1 patients, L-serine supplementation similarly reduced dSL levels. These observations support the hypothesis that an altered substrate selectivity of the mutant SPT is key to the pathophysiology of HSAN1 and raise the prospect of L-serine supplementation as a first treatment option for this disorder., Introduction Hereditary sensory and autonomic neuropathy type 1 (HSAN1) is caused by several missense mutations in the SPTLC1 and SPTLC2 genes, which encode 2 of 3 subunits of the enzyme [...]

Objective: The aim of this study was to examine effects of radiation therapy (RT) for head and neck cancer (HNC) on periodontal disease and relationships to caries.Study Design: A multicenter prospective observational cohort study (OraRad) was conducted in patients undergoing RT for HNC. Assessments were conducted by calibrated examiners at the pre-RT (baseline) visit (n = 533), the 12-month visit (n = 414), and the 24-month visit (n = 365).Results: The average whole mouth mean (standard error (SE)) distance from the cementoenamel junction to the gingival margin (CEJ-GM) decreased significantly from 0.43 (0.04) mm at baseline to 0.24 (0.04) mm at 12 months and 0.11 (0.04) mm at 24 months (P ≤ .001). Whole mouth mean (SE) percentage of sites with CEJ-GM distance of <0 mm increased significantly from 23.3% (1.0%) at baseline to 28.5% (1.0%) at 12 months and 30.5% (1.1%) at 24 months (P ≤ .02). Higher mean radiation dose to the mandible was associated with a greater increase in the percentage of mandibular sites with CEJ-GM distance of <0 mm (P = .003). Both mean CEJ-GM distance and the percentage of sites with a CEJ-GM distance <0 mm were strongly associated with whole mouth mean proportion of decayed, missing, and filled surfaces, as well as proportion of decayed or filled facial/buccal surfaces specifically, (P < .001), with greater gingival recession associated with increased caries.Conclusions: RT for HNC leads to mandibular gingival recession in a dose-dependent manner. This gingival recession may contribute to increased risk for cervical caries seen in these patients. [ABSTRACT FROM AUTHOR]

Abstract Background Genomic sequencing of SNPs is increasingly prevalent, though the amount of familial information these data contain has not been quantified. Methods We provide a framework for measuring the risk to siblings of a patient's SNP genotype disclosure, and demonstrate that sibling SNP genotypes can be inferred with substantial accuracy. Results Extending this inference technique, we determine that a very low number of matches at commonly varying SNPs is sufficient to confirm sib-ship, demonstrating that published sequence data can reliably be used to derive sibling identities. Using HapMap trio data, at SNPs where one child is homozygotic major, with a minor allele frequency ≤ 0.20, (N = 452684, 65.1%) we achieve 91.9% inference accuracy for sibling genotypes. Conclusion These findings demonstrate that substantial discrimination and privacy risks arise from use of inferred familial genomic data.

Tributaries provide spawning habitat for three of four major sub-stocks of Lake Erie walleye (Sander vitreus). Despite anthropogenic degradation and the extirpation of other potamodromous species, the Maumee River, Ohio, USA continues to support one of the largest fish migrations in the Laurentian Great Lakes. To determine if spawning habitat availability and quality could limit production of Maumee River walleye, two habitat suitability models were created for the lower 51 km of the Maumee River and the distribution and numbers of walleye eggs deposited in a 25 km stretch of river were assessed. Walleye eggs were collected using a diaphragm pump at 7 and 10 sites from March/April to May 2014 and 2015. The habitat suitability models showed that <3% of the river yielded 'good' walleye spawning habitat and 11–38% yielded 'moderate' walleye spawning habitat, depending on the model. However, a large set of rapids at river kilometer 28 and more than five river kilometers of less suitable habitat separated areas of 'good' habitat. The rapids may present a migratory barrier for many spawning walleye, as modeled water velocities exceed maximum estimated walleye swim speeds 71–100% of days during pre-spawn migration and spawning during the study period. In both study years, there was a sharp decline in mean egg numbers from spawning sites downstream of the rapids (439.7 eggs/2 min tow ± 990.6 SD) to upstream sites (5.9 eggs/2 min tow ± 19.4 SD). Physical barriers like rapids may reduce spawning habitat connectivity and could limit walleye production in the Maumee River. [ABSTRACT FROM AUTHOR]