Phosphorylation of Calcineurin at a novel serine-proline rich region orchestrates hyphal growth and virulence in Aspergillus fumigatus.

The fungus Aspergillus fumigatus is a leading infectious killer in immunocompromised patients. Calcineurin, a calmodulin (CaM)-dependent protein phosphatase comprised of calcineurin A (CnaA) and calcineurin B (CnaB) subunits, localizes at the hyphal tips and septa to direct A. fumigatus invasion and virulence. Here we identified a novel serine-proline rich region (SPRR) located between two conserved CnaA domains, the CnaB-binding helix and the CaM-binding domain, that is evolutionarily conserved and unique to filamentous fungi and also completely absent in human calcineurin. Phosphopeptide enrichment and tandem mass spectrometry revealed the phosphorylation of A. fumigatus CnaA in vivo at four clustered serine residues (S406, S408, S410 and S413) in the SPRR. Mutation of the SPRR serine residues to block phosphorylation led to significant hyphal growth and virulence defects, indicating the requirement of calcineurin phosphorylation at the SPRR for its activity and function. Complementation analyses of the A. fumigatus ΔcnaA strain with cnaA homologs from the pathogenic basidiomycete Cryptococcus neoformans, the pathogenic zygomycete Mucor circinelloides, the closely related filamentous fungi Neurospora crassa, and the plant pathogen Magnaporthe grisea, revealed filamentous fungal-specific phosphorylation of CnaA in the SPRR and SPRR homology-dependent restoration of hyphal growth. Surprisingly, circular dichroism studies revealed that, despite proximity to the CaM-binding domain of CnaA, phosphorylation of the SPRR does not alter protein folding following CaM binding. Furthermore, mutational analyses in the catalytic domain, CnaB-binding helix, and the CaM-binding domains revealed that while the conserved PxIxIT substrate binding motif in CnaA is indispensable for septal localization, CaM is required for its function at the hyphal septum but not for septal localization. We defined an evolutionarily conserved novel mode of calcineurin regulation by phosphorylation in filamentous fungi in a region absent in humans. These findings suggest the possibility of harnessing this unique SPRR for innovative antifungal drug design to combat invasive aspergillosis.

Transcriptional activation of heat shock protein 90 mediated via a proximal promoter region as trigger of caspofungin resistance in Aspergillus fumigatus.

Invasive aspergillosis is a deadly infection for which new antifungal therapies are needed. Heat shock protein 90 (Hsp90) is an essential chaperone in Aspergillus fumigatus representing an attractive antifungal target. Using a thiamine-repressible promoter (pthiA), we showed that genetic repression of Hsp90 significantly reduced virulence in a murine model of invasive aspergillosis. Moreover, substituting the A. fumigatus hsp90 promoter with 2 artificial promoters (potef, pthiA) and the Candida albicans hsp90 promoter resulted in hypersensitivity to caspofungin and abolition of the paradoxical effect (resistance at high caspofungin concentrations). By inducing truncations in the hsp90 promoter, we identified a 100-base pair proximal sequence that triggers a significant increase of hsp90 expression (≥1.5-fold) and is essential for the paradoxical effect. Preventing this increase of hsp90 expression was sufficient to abolish the paradoxical effect and therefore optimize the antifungal activity of caspofungin.

In vitro activity of calcineurin and heat shock protein 90 Inhibitors against Aspergillus fumigatus azole- and echinocandin-resistant strains.

Due to the limited number of antifungals and the emergence of resistance, new therapies against invasive aspergillosis are needed. We show that calcineurin inhibitors are active in vitro against both azole- and echinocandin-resistant Aspergillus fumigatus strains. The heat shock protein 90 (Hsp90) inhibitor geldanamycin had modest activity when used alone, but its combination with caspofungin or tacrolimus (FK506) resulted in fungicidal activity against azole-resistant strains. Targeting the Hsp90-calcineurin axis is a promising alternative strategy against azole-resistant A. fumigatus strains.

A study of segment weight optimization with the CMS XiO step-and-shoot IMRT technique for prostate cancer.

The aim of this study was to compare IMRT optimization in the CMS XiO radiotherapy treatment planning system, with and without segment weight optimization. Twenty-one prostate cancer patients were selected for this study. All patients were initially planned with step-and-shoot IMRT (S-IMRT). A new plan was then created for each patient by applying the segment weight optimization tool (SWO-IMRT). Analysis was performed on the (SWO-IMRT) and (S-IMRT) plans by comparing the total number of segments, monitor units, rectal and bladder dose. The study showed a statistically significant reduction in the total number of segments (mean: 25.3%; range: 16.8%-31.1%) with SWO-IMRT as compared to S-IMRT (p < 0.0001). Similarly, a mean reduction of 3.8% (range: 0.4%-7.7%) in the total MU was observed with SWO-IMRT (p < 0.0001). The study showed an average rectal dose decrease of 13.7% (range: 7.9%-21.4%) with SWO-IMRT (p < 0.0001). We also observed a statistically significant reduction of 26.7% (range: 16.0%-41.4%; p < 0.0001) in the mean dose to the posterior one-third rectum and an overall reduction in mean bladder dose of 2.2% (range: 0.1%-6.1%) for SWO-IMRT (p < 0.0001). This study shows that the segment weight optimization method significantly reduces the total number of segments and the dose to the rectum for IMRT prostate cancer. It also resulted in fewer monitor units for most of the prostate cases observed in this study.

Community and Campus COVID-19 Risk Uncertainty Under University Reopening Scenarios: Model-Based Analysis.

BACKGROUND: Significant uncertainty has existed about the safety of reopening college and university campuses before the COVID-19 pandemic is better controlled. Moreover, little is known about the effects that on-campus students may have on local higher-risk communities. OBJECTIVE: We aimed to estimate the range of potential community and campus COVID-19 exposures, infections, and mortality under various university reopening plans and uncertainties. METHODS: We developed campus-only, community-only, and campus × community epidemic differential equations and agent-based models, with inputs estimated via published and grey literature, expert opinion, and parameter search algorithms. Campus opening plans (spanning fully open, hybrid, and fully virtual approaches) were identified from websites and publications. Additional student and community exposures, infections, and mortality over 16-week semesters were estimated under each scenario, with 10% trimmed medians, standard deviations, and probability intervals computed to omit extreme outliers. Sensitivity analyses were conducted to inform potential effective interventions. RESULTS: Predicted 16-week campus and additional community exposures, infections, and mortality for the base case with no precautions (or negligible compliance) varied significantly from their medians (4- to 10-fold). Over 5% of on-campus students were infected after a mean of 76 (SD 17) days, with the greatest increase (first inflection point) occurring on average on day 84 (SD 10.2 days) of the semester and with total additional community exposures, infections, and mortality ranging from 1-187, 13-820, and 1-21 per 10,000 residents, respectively. Reopening precautions reduced infections by 24%-26% and mortality by 36%-50% in both populations. Beyond campus and community reproductive numbers, sensitivity analysis indicated no dominant factors that interventions could primarily target to reduce the magnitude and variability in outcomes, suggesting the importance of comprehensive public health measures and surveillance. CONCLUSIONS: Community and campus COVID-19 exposures, infections, and mortality resulting from reopening campuses are highly unpredictable regardless of precautions. Public health implications include the need for effective surveillance and flexible campus operations.

Potential Community and Campus Covid-19 Outcomes Under University and College Reopening Scenarios.

BACKGROUND: Significant uncertainty exists in many countries about the safety of, and best strategies for, reopening college and university campuses until the Covid-19 pandemic is better controlled. Little also is known about the effects on-campus students may have on local higher-risk communities. We aimed to estimate potential community and campus Covid-19 exposures, infections, and mortality due to various university reopening and precaution plans under current ranges of assumptions and uncertainties. METHODS: We developed and calibrated campus-only, community-only, and campus-x-community epidemic differential equation and agent-based models. Input parameters for campus and surrounding communities were estimated via published and grey literature, scenario development, expert opinion, accuracy optimization algorithms, and Monte Carlo simulation; models were cross-validated against each other using February-June 2020 data from heterogeneous U.S. counties and states. Campus opening plans (spanning various fully open, hybrid, and fully virtual approaches) were identified from websites and publications. All scenarios were simulated assuming 16-week semesters and estimated ranges for Covid-19 prevalence among community residents and arriving students, precaution compliance, contact frequency, virus attack rates, and tracing and isolation effectiveness. Additional student and community exposures, infections, and mortality were estimated under each scenario, with 10% trimmed medians, standard deviations, and probability intervals computed to omit extreme outlier scenarios. Factorial analyses were conducted to identify intervention inputs with largest and smallest effects. RESULTS: As a base case with no precautions (or no compliance), predicted 16-week student infections and mortality under normal operations ranged significantly from 471 to 9,495 (median: 2,286, SD: 2,627) and 0 to 123 (median: 9, SD: 14) per 10,000 students, respectively. The maximum active exposures across a semester was 15.76% of all students warranting tracing. Total additional community exposures, infections, and mortality ranged from 1 to 187, 13 to 820, and 1 to 21 per 10,000 residents, respectively. 1% and 5% of on-campus students were infected after a mean (SD) of 11 (3) and 76 (17) days, respectively; >10% students infected by the end of a semester in 34.8% of scenarios, with the greatest increase (first inflection point) occurring on aver-age on day 84 (SD: 10.2 days). Common reopening precautions reduced infections by 24% to 26% and mortality by 36% to 50% in both populations. Uncertainties in many factors, however, produced tremendous variability in all results, ranging from medians by -67% to +342%. CONCLUSIONS: Consequences on community and student Covid-19 exposures, infections, and mortality of reopening physical campuses are very highly unpredictable, depending on a combination of random chance, controllable (e.g. physical layouts), and uncontrollable (e.g. human behavior) factors. Implications include needs for criteria to adapt campus operations mid-semester, methods to detect when necessary, and contingency plans for doing so.

RADBIOMOD: A simple program for utilising biological modelling in radiotherapy plan evaluation.

PURPOSE: Radiotherapy plan evaluation is currently performed by assessing physical parameters, which has many limitations. Biological modelling can potentially allow plan evaluation that is more reflective of clinical outcomes, however further research is required into this field before it can be used clinically. METHODS: A simple program, RADBIOMOD, has been developed using Visual Basic for Applications (VBA) for Microsoft Excel that incorporates multiple different biological models for radiotherapy plan evaluation, including modified Poisson tumour control probability (TCP), modified Zaider-Minerbo TCP, Lyman-Kutcher-Burman normal tissue complication probability (NTCP), equivalent uniform dose (EUD), EUD-based TCP, EUD-based NTCP, and uncomplicated tumour control probability (UTCP). RADBIOMOD was compared to existing biological modelling calculators for 15 sample cases. RESULTS: Comparing RADBIOMOD to the existing biological modelling calculators, all models tested had mean absolute errors and root mean square errors less than 1%. CONCLUSIONS: RADBIOMOD produces results that are non-significantly different from existing biological modelling calculators for the models tested. It is hoped that this freely available, user-friendly program will aid future research into biological modelling.

Automatic tracking of gold seed markers from CBCT image projections in lung and prostate radiotherapy.

PURPOSE: To construct a method and software to track gold seed implants in prostate and lung patients undergoing radiotherapy using CBCT image projections. METHODS: A mathematical model was developed in the MatLab (Mathworks, Natick, USA) environment which uses a combination of discreet cosine transforms and filtering to enhance several edge detection methods for identifying and tracking gold seed fiducial markers in images obtained from Varian (Varian Medical Systems, Palo Alto, USA) and Elekta (Kungstensgatan, Sweden) CBCT projections. RESULTS: Organ motion was captured for 16 prostate patients and 1 lung patient. CONCLUSION: Image enhancement and edge detection is capable of automatically tracking markers for up to 98% (Varian) and 79% (Elekta) of CBCT projections for prostate and lung markers however inclusion of excessive bony anatomy (LT and RT LAT) inhibit the ability of the model to accurate determine marker location.