Reviewing Challenges of Predicting Protein Melting Temperature Change Upon Mutation Through the Full Analysis of a Highly Detailed Dataset with High-Resolution Structures.

Predicting the effects of mutations on protein stability is a key problem in fundamental and applied biology, still unsolved even for the relatively simple case of small, soluble, globular, monomeric, two-state-folder proteins. Many articles discuss the limitations of prediction methods and of the datasets used to train them, which result in low reliability for actual applications despite globally capturing trends. Here, we review these and other issues by analyzing one of the most detailed, carefully curated datasets of melting temperature change (ΔTm) upon mutation for proteins with high-resolution structures. After examining the composition of this dataset to discuss imbalances and biases, we inspect several of its entries assisted by an online app for data navigation and structure display and aided by a neural network that predicts ΔTm with accuracy close to that of programs available to this end. We pose that the ΔTm predictions of our network, and also likely those of other programs, account only for a baseline-like general effect of each type of amino acid substitution which then requires substantial corrections to reproduce the actual stability changes. The corrections are very different for each specific case and arise from fine structural details which are not well represented in the dataset and which, despite appearing reasonable upon visual inspection of the structures, are hard to encode and parametrize. Based on these observations, additional analyses, and a review of recent literature, we propose recommendations for developers of stability prediction methods and for efforts aimed at improving the datasets used for training. We leave our interactive interface for analysis available online at http://lucianoabriata.altervista.org/papersdata/proteinstability2021/s1626navigation.html so that users can further explore the dataset and baseline predictions, possibly serving as a tool useful in the context of structural biology and protein biotechnology research and as material for education in protein biophysics.

Five-year outcomes of an oropharynx-directed treatment approach for unknown primary of the head and neck.

PURPOSE: Squamous cell carcinoma of unknown primary (SCCHNUP) is commonly treated with comprehensive radiation to the laryngopharynx and bilateral necks. In 1998, we established a departmental policy to treat SCCHNUP with radiation directed to the oropharynx and bilateral neck. METHODS: From 1998-2011, 60 patients were treated - N1: 18%, N2: 75% and N3: 7%. 82% underwent neck dissection. 55% received IMRT and 62% underwent concurrent chemoradiotherapy. RESULTS: At median follow-up of 54months, 5 patients failed regionally and 4 emerged with a primary (tongue base, hypopharynx and thoracic esophagus). Five-year rates of regional control, primary emergence, distant metastasis, disease-free survival and overall survival were 90%, 10%, 20%, 72% and 79%, respectively. The 5year rate of primary emergence in a non-oropharynx site was 3%. CONCLUSION: This is the first demonstration that an oropharynx-directed approach yields low rates of primary emergence in SCCHNUP with excellent oncologic outcomes.

Low rates of contralateral neck failure in unilaterally treated oropharyngeal squamous cell carcinoma with prospectively defined criteria of lateralization.

BACKGROUND: Unilateral radiotherapy (RT) of oropharyngeal carcinomas is accepted for patients with lateralized primary and low-volume nodal disease. Utilizing prospectively defined criteria of laterality and staging positron emission tomography (PET)/CT, we studied outcomes in patients with advanced-stage oropharyngeal cancer undergoing unilateral RT. METHODS: Thirty-seven patients with oropharyngeal tumors >1 cm from midline regardless of node status underwent unilateral RT and were followed prospectively. Patient characteristics: T1 = 11; T2 = 22; T3 = 4; N0 = 3; N1 = 9; N2a = 3; N2b = 21; and Nx = 1. Dosimetry were determined and weekly National Comprehensive Cancer Network (NCCN) distress thermometer data were collected. RESULTS: At median follow-up of 32 months, 3-year locoregional control, contralateral regional failure, distant metastasis-free survival, and disease-free survival were 96%, 0%, 7%, and 93%, respectively. CONCLUSION: Low rates of contralateral neck failure are demonstrated utilizing prospectively defined criteria for unilateral RT. The tolerances of contralateral organs are respected and patients report low to moderate levels of distress throughout treatment.

Soil C and N models that integrate microbial diversity.

Industrial agriculture is yearly responsible for the loss of 55-100 Pg of historical soil carbon and 9.9 Tg of reactive nitrogen worldwide. Therefore, management practices should be adapted to preserve ecological processes and reduce inputs and environmental impacts. In particular, the management of soil organic matter (SOM) is a key factor influencing C and N cycles. Soil microorganisms play a central role in SOM dynamics. For instance, microbial diversity may explain up to 77 % of carbon mineralisation activities. However, soil microbial diversity is actually rarely taken into account in models of C and N dynamics. Here, we review the influence of microbial diversity on C and N dynamics, and the integration of microbial diversity in soil C and N models. We found that a gain of microbial richness and evenness enhances soil C and N dynamics on the average, though the improvement of C and N dynamics depends on the composition of microbial community. We reviewed 50 models integrating soil microbial diversity. More than 90 % of models integrate microbial diversity with discrete compartments representing conceptual functional groups (64 %) or identified taxonomic groups interacting in a food web (28 %). Half of the models have not been tested against an empirical dataset while the other half mainly consider fixed parameters. This is due to the difficulty to link taxonomic and functional diversity.

Microbial Diversity Indexes Can Explain Soil Carbon Dynamics as a Function of Carbon Source.

Mathematical models do not explicitly represent the influence of soil microbial diversity on soil organic carbon (SOC) dynamics despite recent evidence of relationships between them. The objective of the present study was to statistically investigate relationships between bacterial and fungal diversity indexes (richness, evenness, Shannon index, inverse Simpson index) and decomposition of different pools of soil organic carbon by measuring dynamics of CO2 emissions under controlled conditions. To this end, 20 soils from two different land uses (cropland and grassland) were incubated with or without incorporation of 13C-labelled wheat-straw residue. 13C-labelling allowed us to study residue mineralisation, basal respiration and the priming effect independently. An innovative data-mining approach was applied, based on generalized additive models and a predictive criterion. Results showed that microbial diversity indexes can be good covariates to integrate in SOC dynamics models, depending on the C source and the processes considered (native soil organic carbon vs. fresh wheat residue). Specifically, microbial diversity indexes were good candidates to help explain mineralisation of native soil organic carbon, while priming effect processes seemed to be explained much more by microbial composition, and no microbial diversity indexes were found associated with residue mineralisation. Investigation of relationships between diversity and mineralisation showed that higher diversity, as measured by the microbial diversity indexes, seemed to be related to decreased CO2 emissions in the control soil. We suggest that this relationship can be explained by an increase in carbon yield assimilation as microbial diversity increases. Thus, the parameter for carbon yield assimilation in mathematical models could be calculated as a function of microbial diversity indexes. Nonetheless, given limitations of the methods used, these observations should be considered with caution and confirmed with more experimental studies. Overall, along with other studies on relationships between microbial community composition and SOM dynamics, this study suggests that overall measures of microbial diversity may constitute relevant ways to include microbial diversity in models of SOM dynamics.

A New Dip Coating Method to Obtain Large-Surface Coatings with a Minimum of Solution.

A new, simple bi-phasic dip-coating method is developed. This method is considered as a great improvement of the technique for research, development and production, since expensive, rare, harmful, or time-evolving solutions can now be easily deposited on large surfaces and on a single side from very little amounts of solution.

Engineering functionality gradients by dip coating process in acceleration mode.

In this work, unique functional devices exhibiting controlled gradients of properties are fabricated by dip-coating process in acceleration mode. Through this new approach, thin films with "on-demand" thickness graded profiles at the submillimeter scale are prepared in an easy and versatile way, compatible for large-scale production. The technique is adapted to several relevant materials, including sol-gel dense and mesoporous metal oxides, block copolymers, metal-organic framework colloids, and commercial photoresists. In the first part of the Article, an investigation on the effect of the dip coating speed variation on the thickness profiles is reported together with the critical roles played by the evaporation rate and by the viscosity on the fluid draining-induced film formation. In the second part, dip-coating in acceleration mode is used to induce controlled variation of functionalities by playing on structural, chemical, or dimensional variations in nano- and microsystems. In order to demonstrate the full potentiality and versatility of the technique, original graded functional devices are made including optical interferometry mirrors with bidirectional gradients, one-dimensional photonic crystals with a stop-band gradient, graded microfluidic channels, and wetting gradient to induce droplet motion.