Large-Scale Conformational Changes of Trypanosoma cruzi Proline Racemase Predicted by Accelerated Molecular Dynamics Simulation

Chagas' disease, caused by the protozoan parasite Trypanosoma cruzi (T. cruzi), is a life-threatening illness affecting 11–18 million people. Currently available treatments are limited, with unacceptable efficacy and safety profiles. Recent studies have revealed an essential T. cruzi proline racemase enzyme (TcPR) as an attractive candidate for improved chemotherapeutic intervention. Conformational changes associated with substrate binding to TcPR are believed to expose critical residues that elicit a host mitogenic B-cell response, a process contributing to parasite persistence and immune system evasion. Characterization of the conformational states of TcPR requires access to long-time-scale motions that are currently inaccessible by standard molecular dynamics simulations. Here we describe advanced accelerated molecular dynamics that extend the effective simulation time and capture large-scale motions of functional relevance. Conservation and fragment mapping analyses identified potential conformational epitopes located in the vicinity of newly identified transient binding pockets. The newly identified open TcPR conformations revealed by this study along with knowledge of the closed to open interconversion mechanism advances our understanding of TcPR function. The results and the strategy adopted in this work constitute an important step toward the rationalization of the molecular basis behind the mitogenic B-cell response of TcPR and provide new insights for future structure-based drug discovery

Plantar calcaneal spurs in older people: longitudinal traction or vertical compression?

<p>Abstract</p> <p>Background</p> <p>Plantar calcaneal spurs are common, however their pathophysiology is poorly understood. This study aimed to evaluate the prevalence and correlates of plantar calcaneal spurs in a large sample of older people.</p> <p>Methods</p> <p>Weightbearing lateral foot radiographs of 216 people (140 women and 76 men) aged 62 to 94 years (mean age 75.9, <smcaps>SD</smcaps> 6.6) were examined for plantar calcaneal and Achilles tendon spurs. Associations between the presence of spurs and sex, body mass index, radiographic measures of foot posture, self-reported co-morbidities and current or previous heel pain were then explored.</p> <p>Results</p> <p>Of the 216 participants, 119 (55%) had at least one plantar calcaneal spur and 103 (48%) had at least one Achilles tendon spur. Those with plantar calcaneal spurs were more likely to have Achilles tendon spurs (odds ratio [OR] = 2.0, 95% confidence interval [CI] 1.2 to 3.5). Prevalence of spurs did not differ according to sex. Participants with plantar calcaneal spurs were more likely to be obese (OR = 7.9, 95% CI 3.6 to 17.0), report osteoarthritis (OR = 2.6, 95% CI 1.6 to 4.8) and have current or previous heel pain (OR = 4.6, 95% CI 2.3 to 9.4). No relationship was found between the presence of calcaneal spurs and radiographic measures of foot posture.</p> <p>Conclusion</p> <p>Calcaneal spurs are common in older men and women and are related to obesity, osteoarthritis and current or previous heel pain, but are unrelated to radiographic measurements of foot posture. These findings support the theory that plantar calcaneal spurs may be an adaptive response to vertical compression of the heel rather than longitudinal traction at the calcaneal enthesis.</p

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Acute periodontal lesions

This is a review and update on acute conditions affecting the gingival tissues, including abscesses in the periodontium, necrotizing periodontal diseases, and other acute conditions that cause gingival lesions with acute presentation, such as infectious process not associated with oral bacterial biofilms, muco-cutanenous disorders, and traumatic and allergic lesions. A periodontal abscess is clinically important since it is a relatively frequent dental emergency, it can compromise the periodontal prognosis of the affected tooth, and because bacteria within the abscess have been identified, mainly by the type of etiology, and there are clear diffrences between those affecting a previously existing periodontal pocket ahd those affecting healthy sites. Therapy for this acute condition consists of drainage and tissue debridement, with individual evaluation of the need for systemic antimicrobial therapy. the definitive treatment of the pre-existing condition should be accomplished after the acute phase is controlled. Necrotizing periodontal disease (NPD) present three typical clinical features : papilla necrosis, gingival bleeding, and pain. Although the prevalence of these diseases is not high, their importance is clear, since they represent the most severe conditions associated with dental biofilm, with very rapid tissue destruction. In adittion to bacteria, the etiology of NPD includes numerous factors that alter the host response and predispose to these diseases, including HIV infection, malnutrition, stress, and tobacco smoking. The treatment consists of superficial debridement, careful mechanical oral hygiene, rinsing with chlorhexidine, and daily re-evaluation. Systemic antimicrobials may be used adjunctively in severe cases or in non-responding conditions and the best option is metronidazole.Once the acute disease is under control, definitive treatment should be provided, including the adequate therapy for the pre-existing gingivitis or periodontitis. Among other acute conditions affecting the periodontal tissues, but not caused by the microorganisms present in oral biofilms , are infectious diseases, muco-cutaneous diseases and traumatic or allergic lesions. In most cases, the gingival envolvement is not severe, though they are common and may prompt a dental emergency visit. These conditions may the direct result of a trauma or the consequence of the breaking of vesicles and bullae. A proper differential diagnosis is important for an adequate management of the case

Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands