Benthic pH gradients across a range of shelf sea sediment types linked to sediment characteristics and seasonal variability

This study used microelectrodes to record pH profiles in fresh shelf sea sediment cores collected across a range of different sediment types within the Celtic Sea. Spatial and temporal variability was captured during repeated measurements in 2014 and 2015. Concurrently recorded oxygen microelectrode profiles and other sedimentary parameters provide a detailed context for interpretation of the pH data. Clear differences in profiles were observed between sediment type, location and season. Notably, very steep pH gradients exist within the surface sediments (10–20 mm), where decreases greater than 0.5 pH units were observed. Steep gradients were particularly apparent in fine cohesive sediments, less so in permeable sandier matrices. We hypothesise that the gradients are likely caused by aerobic organic matter respiration close to the sediment–water interface or oxidation of reduced species at the base of the oxic zone (NH4+, Mn2+, Fe2+, S−). Statistical analysis suggests the variability in the depth of the pH minima is controlled spatially by the oxygen penetration depth, and seasonally by the input and remineralisation of deposited organic phytodetritus. Below the pH minima the observed pH remained consistently low to maximum electrode penetration (ca. 60 mm), indicating an absence of sub-oxic processes generating H+ or balanced removal processes within this layer. Thus, a climatology of sediment surface porewater pH is provided against which to examine biogeochemical processes. This enhances our understanding of benthic pH processes, particularly in the context of human impacts, seabed integrity, and future climate changes, providing vital information for modelling benthic response under future climate scenarios

Learning biophysically-motivated parameters for alpha helix prediction

<p>Abstract</p> <p>Background</p> <p>Our goal is to develop a state-of-the-art protein secondary structure predictor, with an intuitive and biophysically-motivated energy model. We treat structure prediction as an optimization problem, using parameterizable cost functions representing biological "pseudo-energies". Machine learning methods are applied to estimate the values of the parameters to correctly predict known protein structures.</p> <p>Results</p> <p>Focusing on the prediction of alpha helices in proteins, we show that a model with 302 parameters can achieve a Q_{<it>α </it>}value of 77.6% and an SOV_{<it>α </it>}value of 73.4%. Such performance numbers are among the best for techniques that do not rely on external databases (such as multiple sequence alignments). Further, it is easier to extract biological significance from a model with so few parameters.</p> <p>Conclusion</p> <p>The method presented shows promise for the prediction of protein secondary structure. Biophysically-motivated elementary free-energies can be learned using SVM techniques to construct an energy cost function whose predictive performance rivals state-of-the-art. This method is general and can be extended beyond the all-alpha case described here.</p

Pediatric Solid Tumors in Resource-Constrained Settings: A Review of Available Evidence on Management, Outcomes, and Barriers to Care

International disparities in outcomes from pediatric solid tumors remain striking. Herein, we review the current literature regarding management, outcomes, and barriers to care for pediatric solid tumors in low- and middle-income countries (LMICs). In sub-Saharan Africa, Wilms Tumor represents the most commonly encountered solid tumor of childhood and has been the primary target of recent efforts to improve outcomes in low-resource settings. Aggressive and treatment-resistant tumor biology may play a role in poor outcomes within certain populations, but socioeconomic barriers remain the principal drivers of preventable mortality. Management protocols that include measures to address socioeconomic barriers have demonstrated early success in reducing abandonment of therapy. Further work is required to improve infrastructure and general pediatric care to address disparities

Impact of PET/CT on initial staging, restaging and treatment management of anal cancer: a clinical case with literature review

Distant extrapelvic metastases appear in approximately in 10% of the patients with squamous cell anal cancer (SCAC) and survival depends on the treatment strategy. Exact staging leads to optimal planning of multimodality therapy and the adequate evaluation of treatment response can improve the prognosis of the disease. Diagnosis and staging of SCAC are commonly performed using contrast-enhanced computerized tomography(CT) and interpretation of the findings for tumor biological behavior. F18-fluoro-2 deoxy-D glucose positron emission tomography((18)F-FDG PET) reveals aspects of tumor function and allows metabolic measurements. Combined PET/CT scans permit exact localization with anatomical criteria of the hypermetabolic (18)F-FDG avid malignant lesions. We present a patient with SCAC in whom, according to PET/CT findings, the initial stage was changed from II (T2N0M0) to III A (T2N2M0). Radiation therapy (RT) and chemotherapy achieved a good therapeutic response but early follow up revealed new paraaortic lymph node (LN) metastases, as well as an uncommon left supraclavicular LN metastasis from the same primary carcinoma. The disease was restaged as stage IV (T2N2M1) and radiation therapy was substituted by chemotherapy