The crystal structure of human Rogdi provides insight into the causes of Kohlschutter-Tonz Syndrome

Kohlschutter-Tönz syndrome (KTS) is a rare autosomal-recessive disorder of childhood onset characterized by global developmental delay, spasticity, epilepsy, and amelogenesis imperfecta. Rogdi, an essential protein, is highly conserved across metazoans, and mutations in Rogdi are linked to KTS. However, how certain mutations in Rogdi abolish its physiological functions and cause KTS is not known. In this study, we determined the crystal structure of human Rogdi protein at atomic resolution. Rogdi forms a novel elongated curved structure comprising the ?? domain, a leucine-zipper-like four-helix bundle, and a characteristic ??-sheet domain. Within the ?? domain, the N-terminal H1 helix (residues 19-45) pairs with the C-terminal H6 helix (residues 252-287) in an antiparallel manner, indicating that the integrity of the four-helix bundle requires both N- and C-terminal residues. The crystal structure, in conjunction with biochemical data, indicates that the ?? domain might undergo a conformational change and provide a structural platform for protein-protein interactions. Disruption of the four-helix bundle by mutation results in significant destabilization of the structure. This study provides structural insights into how certain mutations in Rogdi affect its structure and cause KTS, which has important implications for the development of pharmaceutical agents against this debilitating neurological disease

Target selection for T-cell therapy in epithelial ovarian cancer: systematic prioritization of self-antigens

Adoptive T cell-receptor therapy (ACT) could represent a promising approach in the targeted treatment of epithelial ovarian cancer (EOC). However, the identification of suitable tumor-associated antigens (TAAs) as targets is challenging. We identified and prioritized TAAs for ACT and other immunotherapeutic interventions in EOC. A comprehensive list of pre-described TAAs was created and candidates were prioritized, using predefined weighted criteria. Highly ranked TAAs were immunohistochemically stained in a tissue microarray of 58 EOC samples to identify associations of TAA expression with grade, stage, response to platinum, and prognosis. Preselection based on expression data resulted in 38 TAAs, which were prioritized. Along with already published Cyclin A1, the TAAs KIF20A, CT45, and LY6K emerged as most promising targets, with high expression in EOC samples and several identified peptides in ligandome analysis. Expression of these TAAs showed prognostic relevance independent of molecular subtypes. By using a systematic vetting algorithm, we identified KIF20A, CT45, and LY6K to be promising candidates for immunotherapy in EOC. Results are supported by IHC and HLA-ligandome data. The described method might be helpful for the prioritization of TAAs in other tumor entities

PEDIA: prioritization of exome data by image analysis

Purpose Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. Methods Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. Results The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20–89% and the top 10 accuracy rate by more than 5–99% for the disease-causing gene. Conclusion Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis

Endocrine and Growth Abnormalities in 4H Leukodystrophy Caused by Variants in POLR3A, POLR3B, and POLR1C.

CONTEXT: 4H or POLR3-related leukodystrophy is an autosomal recessive disorder typically characterized by hypomyelination, hypodontia, and hypogonadotropic hypogonadism, caused by biallelic pathogenic variants in POLR3A, POLR3B, POLR1C, and POLR3K. The endocrine and growth abnormalities associated with this disorder have not been thoroughly investigated to date. OBJECTIVE: To systematically characterize endocrine abnormalities of patients with 4H leukodystrophy. DESIGN: An international cross-sectional study was performed on 150 patients with genetically confirmed 4H leukodystrophy between 2015 and 2016. Endocrine and growth abnormalities were evaluated, and neurological and other non-neurological features were reviewed. Potential genotype/phenotype associations were also investigated. SETTING: This was a multicenter retrospective study using information collected from 3 predominant centers. PATIENTS: A total of 150 patients with 4H leukodystrophy and pathogenic variants in POLR3A, POLR3B, or POLR1C were included. MAIN OUTCOME MEASURES: Variables used to evaluate endocrine and growth abnormalities included pubertal history, hormone levels (estradiol, testosterone, stimulated LH and FSH, stimulated GH, IGF-I, prolactin, ACTH, cortisol, TSH, and T4), and height and head circumference charts. RESULTS: The most common endocrine abnormalities were delayed puberty (57/74; 77% overall, 64% in males, 89% in females) and short stature (57/93; 61%), when evaluated according to physician assessment. Abnormal thyroid function was reported in 22% (13/59) of patients. CONCLUSIONS: Our results confirm pubertal abnormalities and short stature are the most common endocrine features seen in 4H leukodystrophy. However, we noted that endocrine abnormalities are typically underinvestigated in this patient population. A prospective study is required to formulate evidence-based recommendations for management of the endocrine manifestations of this disorder

Experimental and simulative characterization of a fin and tubes heat exchanger with PCM for process heat applications

Thermal storage is one option to make solar or conventional process heat applications more efficient. Phase change material (PCM) storages offer the potential to keep constant temperatures for different time periods. In this paper a fin and tubes heat exchanger filled with the sugar alcohol D-mannitol was characterized regarding its usability as PCM storage in the temperature range between 100 and 250 °C. D-mannitol melts at ca. 166 °C. Different heating and cooling experiments were carried out. The specific heat capacity of the PCM as well as the latent heat was determined. The heat flow into the storage was determined at different mass flow rates for heating and cooling processes. During the measurements thermal losses to the ambient were very high leading to high uncertainties. Due to the viscosity of D-mannitol natural convection between the fins seems to have no significant influence on heat transfer during melting of the PCM. Some results led to the assumption that the heat distribution in the heat exchanger was not even. A simulation model was created and a first validation was carried out. Geometry improvement with the aim of more even heat distribution and higher charge and discharge power will be carried out by using the simulation model and further measurements