Project description:The application of serum creatinine and cystatin C in patients with CKD has been limited to using estimated glomerular filtration rate (eGFR). Criteria for choosing the best GFR estimating equation are 1) accuracy in estimating measured GFR, 2) optimal discrimination of clinical outcomes, and 3) association with CKD risk factors and outcomes similar to that of measured GFR. Notably, these criteria are often not in agreement; and while the last criterion is the most important, it has been widely overlooked. The primary problem with eGFR is that the non-GFR determinants of serum creatinine and cystatin C, as well as their surrogates (age, sex, and race), associate with CKD risk factors and outcomes. This leads to a distorted understanding of CKD, though eGFR based on serum creatinine appears to be less biased than eGFR based on cystatin C. Because of this problem, the use of eGFR should be limited to settings where knowing actual GFR is relevant and eGFR is more informative about GFR than serum creatinine or cystatin C alone. Such settings include staging CKD severity by GFR and dosing medications cleared by glomerular filtration. Alternatively, the diagnosis of CKD, the longitudinal progression of CKD, and prognostic models for CKD are settings where serum creatinine and cystatin C can be better applied and interpreted without eGFR.
Project description:Determination of molecular weight parameters of native and, in particular, technical lignins are based on size exclusion chromatography (SEC) approaches. However, no matter which approach is used, either conventional SEC with a refractive index detector and calibration with standards or multi-angle light scattering (MALS) detection at 488 nm, 633 nm, 658 nm, or 690 nm, all variants can be severely erroneous. The lack of calibration standards with high structural similarity to lignin impairs the quality of the molar masses determined by conventional SEC, and the typical fluorescence of (technical) lignins renders the corresponding MALS data rather questionable. Application of MALS detection at 785 nm by using an infrared laser largely overcomes those problems and allows for a reliable and reproducible determination of the molar mass distributions of all types of lignins, which has been demonstrated in this study for various and structurally different analytes, such as kraft lignins, milled-wood lignin, lignosulfonates, and biorefinery lignins. The topics of calibration, lignin fluorescence, and lignin UV absorption in connection with MALS detection are critically discussed in detail, and a reliable protocol is presented. Correction factors based on MALS measurements have been determined for commercially available calibration standards, such as pullulan and polystyrene sulfonate, so that now more reliable mass data can be obtained also if no MALS system is available and these conventional calibration standards have to be resorted to.
Project description:Understanding how systems with many semi-autonomous parts reach a desired target is a key question in biology (e.g., Drosophila larvae seeking food), engineering (e.g., driverless navigation), medicine (e.g., reliable movement for brain-damaged individuals), and socioeconomics (e.g., bottom-up goal-driven human organizations). Centralized systems perform better with better components. Here, we show, by contrast, that a decentralized entity is more efficient at reaching a target when its components are less capable. Our findings reproduce experimental results for a living organism, predict that autonomous vehicles may perform better with simpler components, offer a fresh explanation for why biological evolution jumped from decentralized to centralized design, suggest how efficient movement might be achieved despite damaged centralized function, and provide a formula predicting the optimum capability of a system's components so that it comes as close as possible to its target or goal.
Project description:Liquid-liquid phase separation (LLPS) of biomolecules has emerged as a new paradigm in cell biology, and the process is one proposed mechanism for the formation of membraneless organelles (MLOs). Bacterial cells have only recently drawn strong interest in terms of studies on both liquid-to-liquid and liquid-to-solid phase transitions. It seems that these processes drive the formation of prokaryotic cellular condensates that resemble eukaryotic MLOs. In this review, we present an overview of the key microbial biomolecules that undergo LLPS, as well as the formation and organization of biomacromolecular condensates within the intracellular space. We also discuss the current challenges in investigating bacterial biomacromolecular condensates. Additionally, we highlight a summary of recent knowledge about the participation of bacterial biomolecules in a phase transition and provide some new in silico analyses that can be helpful for further investigations.
Project description:The recent biotechnological progress has allowed life scientists and physicians to access an unprecedented, massive amount of data at all levels (molecular, supramolecular, cellular and so on) of biological complexity. So far, mostly classical computational efforts have been dedicated to the simulation, prediction or de novo design of biomolecules, in order to improve the understanding of their function or to develop novel therapeutics. At a higher level of complexity, the progress of omics disciplines (genomics, transcriptomics, proteomics and metabolomics) has prompted researchers to develop informatics means to describe and annotate new biomolecules identified with a resolution down to the single cell, but also with a high-throughput speed. Machine learning approaches have been implemented to both the modelling studies and the handling of biomedical data. Quantum computing (QC) approaches hold the promise to resolve, speed up or refine the analysis of a wide range of these computational problems. Here, we review and comment on recently developed QC algorithms for biocomputing, with a particular focus on multi-scale modelling and genomic analyses. Indeed, differently from other computational approaches such as protein structure prediction, these problems have been shown to be adequately mapped onto quantum architectures, the main limit for their immediate use being the number of qubits and decoherence effects in the available quantum machines. Possible advantages over the classical counterparts are highlighted, along with a description of some hybrid classical/quantum approaches, which could be the closest to be realistically applied in biocomputation.
Project description:Evidence-based interventions to favor more harmonious interactions in difficult relationships remain scarce. This study examined whether compassion training may have beneficial effects in an ongoing tense relationship with a disliked person, by reducing schadenfreude toward them and increasing felt interpersonal closeness. 108 participants were assigned to one of three 5-week trainings in a longitudinal randomized controlled study: compassion training, reappraisal training (emotion regulation control condition), or Italian language training (neutral active control condition). The disliked person was not targeted during the trainings to test potential transfer effects. Misfortune scenarios and a measure of interpersonal closeness were used to test whether schadenfreude and closeness feelings toward a disliked person changed from pre- to post-training, across different experimental and control groups. Only compassion and reappraisal trainees reported a decrease of schadenfreude feelings toward the disliked person compared to their pre-training ratings, no changes were observed in the Italian language training. Importantly, feelings of closeness toward the disliked person increased in the compassion training group compared to the other two groups. This increase of closeness feelings could be a central mechanism for improving social interactions. These transfer effects open new perspectives concerning emotion regulation interventions in conflict resolution.
Project description:Peripheral nerve injuries are a frequent and disabling condition, which affects 13 to 23 per 100.000 persons each year. Severe cases, with structural disruption of the nerve, are associated with poor functional recovery. The experimental treatment using nerve grafts to replace damaged or shortened axons is limited by technical difficulties, invasiveness, and mediocre results. Other therapeutic choices include the adjunctive application of cultured Schwann cells and nerve conduits to guide axonal growth. The bone marrow is a rich source of mesenchymal cells, which can be differentiated in vitro into Schwann cells and subsequently engrafted into the damaged nerve. Alternatively, undifferentiated bone marrow mesenchymal cells can be associated with nerve conduits and afterward transplanted. Experimental studies provide evidence of functional, histological, and electromyographical improvement following transplantation of bone-marrow-derived cells in animal models of peripheral nerve injury. This paper focuses on this new therapeutic approach highlighting its direct translational and clinical utility in promoting regeneration of not only acute but perhaps also chronic cases of peripheral nerve damage.