Search Results (10)

Knee osteoarthritis (OA) affects over 650 million patients worldwide. Total knee replacement is aimed at end-stage OA to relieve symptoms of pain, stiffness and reduced mobility. However, the role of imaging modalities in monitoring symptomatic disease progression remains unclear. This study aimed to compare machine learning (ML) models, with and without imaging features, in predicting the two-year Western Ontario and McMaster Universities Arthritis Index (WOMAC) score for knee OA patients. We included 2408 patients from the Osteoarthritis Initiative (OAI) database, with 629 patients from the Multicenter Osteoarthritis Study (MOST) database. The clinical dataset included 18 clinical features, while the imaging dataset contained an additional 10 imaging features. Minimal Clinically Important Difference (MCID) was set to 24, reflecting meaningful physical impairment. Clinical and imaging dataset models produced similar area under curve (AUC) scores, highlighting low differences in performance AUC < 0.025). For both clinical and imaging datasets, Gradient Boosting Machine (GBM) models performed the best in the external validation, with a clinically acceptable AUC of 0.734 (95% CI 0.687–0.781) and 0.747 (95% CI 0.701–0.792), respectively. The five features identified included educational background, family history of osteoarthritis, co-morbidities, use of osteoporosis medications and previous knee procedures. This is the first study to demonstrate that ML models achieve comparable performance with and without imaging features. Full article

Knee osteoarthritis (KOA) is characterized by low-grade inflammation, loss of articular cartilage, subchondral bone remodeling, synovitis, osteophyte formation, and pain. Strong, continuous pain may indicate the need for joint replacement in patients with end-stage OA, although postoperative pain (POP) of at least a two-month duration persists in 10–40% of patients with OA. Study purpose: The inflammation observed in joint tissues is linked to pain caused by the production of proinflammatory cytokines. Since the biosynthesis of cytokines requires energy, their production is supported by extensive metabolic conversions of carbohydrates and fatty acids, which could lead to a disruption in cellular homeostasis. Therefore, this study aimed to investigate the association between POP development and disturbances in energy metabolic conversions, focusing on carbohydrate and fatty acid metabolism. Methods: Peripheral blood samples were collected from 26 healthy subjects and 50 patients with end-stage OA before joint replacement surgery. All implants were validated by orthopedic surgeons, and patients with OA demonstrated no inherent abnormalities to cause pain from other reasons than OA disease, such as malalignment, aseptic loosening, or excessive bleeding. Pain levels were assessed before surgery using the visual analogue scale (VAS) and neuropathic pain questionnaires, DN4 and PainDETECT. Functional activity was evaluated using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Three and six months after surgery, pain indices according to a VAS of 30 mm or higher were considered. Total RNA isolated from whole blood was analyzed using quantitative real-time RT-PCR (qRT-PCR) for the expression of genes related to carbohydrate and fatty acid metabolism. Protein levels of the examined genes were measured using an ELISA in the peripheral blood mononuclear cells (PBMCs). We used qRT-PCR because it is the most sensitive and reliable method for gene expression analysis, while an ELISA was used to confirm our qRT-PCR results. Key findings: Among the study cohort, 17 patients who reported POP demonstrated significantly higher (p < 0.05) expressions of the genes PKM2, LDH, SDH, UCP2, CPT1A, and ACLY compared to pain-free patients with KOA. Receiver-operating characteristic (ROC) curve analyses confirmed the association between these gene expressions and pain development post-arthroplasty. A principle component analysis identified the prognostic values of ACLY, CPT1A, AMPK, SDHB, Caspase 3, and IL-1β gene expressions for POP development in the examined subjects. Conclusion: These findings suggest that the disturbances in energy metabolism, as observed in the PBMCs of patients with end-stage KOA before arthroplasty, may contribute to POP development. An understanding of these metabolic processes could provide insights into the pathogenesis of KOA. Additionally, our findings can be used in a clinical setting to predict POP development in end-stage patients with KOA before arthroplasty. Full article

(1) Background: Clinically useful prediction models for chronic postsurgical pain (CPSP) in knee replacement (TKA) are lacking. (2) Methods: In our prospective, multicenter study, a wide-ranging set of 91 variables was collected from 933 TKA patients at eight time points up to one year after surgery. Based on this extensive data pool, simple and complex prediction models were calculated for the preoperative time point and for 6 months after surgery, using least absolute shrinkage and selection operator (LASSO) 1se and LASSO min, respectively. (3) Results: Using preoperative data only, LASSO 1se selected age, the Revised Life Orientation Test on pessimism, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC)—subscore pain and the Timed “Up and Go” Test for prediction, resulting in an area under the curve (AUC) of 0.617 and a Brier score of 0.201, expressing low predictive power only. Using data up to 6 months after surgery, LASSO 1se included preoperative Patient Health Questionnaire-4, Knee Injury and Osteoarthritis Outcome Score (KOOS)—subscore pain (pain) 3 months after surgery (month), WOMAC pain 3 and 6 months, KOOS subscore symptoms 6 months, KOOS subscore sport 6 months and KOOS subscore Quality of Life 6 months. This improved the predictive power to an intermediate one (AUC 0.755, Brier score 0.168). More complex models computed using LASSO min did little to further improve the strength of prediction. (4) Conclusions: Even using multiple variables and complex calculation methods, the possibility of individual prediction of CPSP after TKA remains limited. Full article

Using a hierarchy of three sigmoid growth models with increasing complexity, i.e., number of parameters, we reanalyzed kinetic data for heterogeneous nucleation—the number of nuclei N(t) vs. time t—from archetypical experiments on the electrodeposition of mercury on platinum by I. Markov and E. Stoycheva, to obtain two scales: N_max and τ. The universal character of the studied phenomenon was revealed when replotting the original data as α ≡ N(t)/N_max vs. t/τ. Yet the simplest model, the recently introduced α₂₁ model which is aimed to describe diffusion-limited growth in 2D, α₂₁ = tanh²(2t/τ₂₁), fits all datasets with an R² ≥ 0.989. This can be rationalized by attracting the non-classical notion of two-step nucleation—the nuclei form in a metastable phase which, in this case, grows on the electrode surface. Beyond the universality, we find the dependence of the two obtained scales on the overvoltage, which is increased systematically from 83 to 88 mV to generate the six N(t) datasets for each of the two electrode types—planar and hemispherical. Surprisingly, for one of them, the planar electrode, there is a discontinuity in the dependence—an almost horizontal jump from 85 to 86 mV, while for the hemispherical electrode, τ decreases smoothly. Full article

Recent works show that glass-forming liquids display Fickian non-Gaussian Diffusion, with non-Gaussian displacement distributions persisting even at very long times, when linearity in the mean square displacement (Fickianity) has already been attained. Such non-Gaussian deviations temporarily exhibit distinctive exponential tails, with a decay length $\lambda$ growing in time as a power-law. We herein carefully examine data from four different glass-forming systems with isotropic interactions, both in two and three dimensions, namely, three numerical models of molecular liquids and one experimentally investigated colloidal suspension. Drawing on the identification of a proper time range for reliable exponential fits, we find that a scaling law $\lambda \left(t\right)\propto t^{\alpha }$, with $\alpha \simeq 1/3$, holds for all considered systems, independently from dimensionality. We further show that, for each system, data at different temperatures/concentration can be collapsed onto a master-curve, identifying a characteristic time for the disappearance of exponential tails and the recovery of Gaussianity. We find that such characteristic time is always related through a power-law to the onset time of Fickianity. The present findings suggest that FnGD in glass-formers may be characterized by a “universal” evolution of the distribution tails, independent from system dimensionality, at least for liquids with isotropic potential. Full article

This article proposes a possible path devoted to upper secondary school and early university students, as well as training teachers, with the aim to build a conscious approach to the learning/teaching of the conics, which uses, for an educational purpose, the close relationship between conics as loci of points of a plane and conics as sections of a cone. In this path, we will refer to some elements taken from the history of mathematics relating to a particular conic: the parabola. These elements could help students to discover and realize the transition from a parabola considered as a curve in a plane to the same parabola considered on a cone of which it is a section, as well as the inverse passage, and to grasp the profound link between two presentations of the same geometric object. Both steps will be carried out through constructions made with the use of the GeoGebra dynamic geometry software. In addition, it will be highlighted how the construction of conics by points has allowed the creation of lenses and mirrors, which represents a practical application of geometry very relevant to physics and astronomy. Such a practical approach could help students to overcome the difficulty in understanding conics by making the argument less abstract. Moreover, this path could build up an environment in which teachers and students could explore some semiotic registers and their changes, through which Mathematics expresses itself. In the final part, an educational experiment of the path that was proposed will be shown to the students of the Master’s degree course of “mathematics education” at the Department of Mathematics and Computer Science of the University of Calabria. The results of this experiment are described in detail and seem to confirm that the twofold view of the parabola as a section of a cone and as locus of points of a plane helps the students in understanding its meaning in both theoretical and applicative fields. Full article

Osteoarthritis (OA) pain implies an indication for joint replacement in patients with end-stage OA. However, chronic postoperative pain is observed in 10–40% of patients with OA. Here, we identified genes whose expression in the peripheral blood before surgery could denote the risk of postoperative pain development. We examined the peripheral blood of 26 healthy subjects and 50 patients with end-stage OA prior to joint replacement surgery. Pain was evaluated before surgery using the visual analog scale (VAS) index and neuropathic pain questionnaires, Douleur Neuropathique 4 Questions (DN4) and PainDETECT questionnaires. Functional activity was assessed using the Western Ontario and McMaster Universities osteoarthritis index (WOMAC). Three and six months after surgery, pain indices according to VAS of 30% and higher were considered. Metalloproteinase (MMP)-9 and tissue inhibitor of metalloproteinase (TIMP)1 protein levels were measured using ELISA in the peripheral blood mononuclear cells (PBMCs). Total RNA isolated from whole blood was analysed using quantitative real-time RT-PCR for caspase-3, MMP-9, TIMP1, cathepsins K and S, tumour necrosis factor (TNF)α, interleukin (IL)-1β, and cyclooxygenase (COX)-2 gene expression. Seventeen patients reported post-surgical pain. Expression of cathepsins K and S, caspase-3, TIMP1, IL-1β, and TNFα genes before surgery was significantly higher in these patients compared to pain-free patients with OA. Receiver-operating characteristic (ROC) curve analyses confirmed significant associations between these gene expressions and the likelihood of pain development after arthroplasty. High baseline expression of genes associated with extracellular matrix destruction (cathepsins S and K, TIMP1), inflammation (IL-1β, TNFα), and apoptosis (caspase-3) measured in the peripheral blood of patients with end-stage OA before knee arthroplasty might serve as an important biomarker of postoperative pain development. Full article

Maize plants are often infected with fungal pathogens of the genus Fusarium. Taxonomic characterization of these species by microscopic examination of pure cultures or assignment to mating populations is time-consuming and requires specific expertise. Reliable taxonomic assignment may be strengthened by the analysis of DNA sequences. Species-specific PCR assays are available for most Fusarium pathogens, but the number of species that infect maize increases the labor and costs required for analysis. In this work, a diagnostic assay for major Fusarium pathogens of maize based on the analysis of melting curves of PCR amplicons was established. Short segments of genes RPB2 and TEF-1α, which have been widely used in molecular taxonomy of Fusarium, were amplified with universal primers in a real-time thermocycler and high-resolution melting (HRM) curves of the products were recorded. Among major Fusarium pathogens of maize ears, F. cerealis, F. culmorum, F. graminearum, F. equiseti, F. poae, F. temperatum, F. tricinctum, and F. verticillioides, all species except for the pair F. culmorum/F. graminearum could be distinguished by HRM analysis of a 304 bp segment of the RPB2 gene. The latter two species could be differentiated by HRM analysis of a 247 bp segment of the TEF-1α gene. The assay was validated with DNA extracted from pure cultures of fungal strains, successfully applied to total DNA extracted from infected maize ears and also to fungal mycelium that was added directly to the PCR master mix (“colony PCR”). HRM analysis thus offers a cost-efficient method suitable for the diagnosis of multiple fungal pathogens. Full article

It is a fact that the frequency domain spectroscopy (FDS) curve at different temperatures can be corrected by the shift factor (α_T) extracted from the master curve. However, the α_T and master curve reported by previous works are distinctive due to the difference in the construction algorithm. Therefore, it is of great significance to report a universal approach for extracting α_T. In this work, the unaged oil-immersed pressboards with different moisture content (mc%) are firstly prepared and selected as the research specimen. Then, the α_T of FDS curves on the above pressboard is extracted based upon the master curve technique. The influence mechanism under the various test temperature (T) and mc% is therefore analyzed so as to establish a universal model for predicting the α_T. The present findings reveal that the α_T value extracted from FDS curves is both temperature-dependent and moisture-dependent. In addition, the predicted α_T is not only suitable for temperature correction on FDS curve of same type pressboard with different insulation conditions (moisture contents and aging degrees), but also maintains considerable accuracy when applied to different types of pressboard. Therefore, the obtained conclusions will provide a universal method for temperature correction on FDS curve of transformer polymer insulation. Full article

Cattle are considered to be the main reservoir for Shiga toxin-producing Escherichia coli (STEC) and are often the direct or indirect source of STEC outbreaks in humans. Accurate measurement of the concentration of shed STEC in cattle feces could be a key answer to questions concerning transmission of STEC, contamination sources and efficiency of treatments at farm level. Infected animals can be identified and the contamination level quantified by real-time quantitative PCR (qPCR), which has its specific limitations. Droplet digital PCR (ddPCR) has been proposed as a method to overcome many of the drawbacks of qPCR. This end-point amplification PCR is capable of absolute quantification independent from any reference material and is less prone to PCR inhibition than qPCR. In this study, the qPCR-based protocol described by Verstraete et al. (2014) for Shiga toxin genes stx1 and stx2 and the intimin gene eae quantification was optimized for ddPCR analysis. The properties of ddPCR and qPCR using two different mastermixes (EMM: TaqMan^® Environmental Master Mix 2.0; UMM: TaqMan^® Universal PCR Master Mix) were evaluated, using standard curves and both artificial and natural contaminated cattle fecal samples. In addition, the susceptibility of these assays to PCR-inhibitors was investigated. Evaluation of the standard curves and both artificial and natural contaminated cattle fecal samples suggested a very good agreement between qPCR using EMM and ddPCR. Furthermore, similar sensitivities and no PCR inhibition were recorded for both assays. On the other hand, qPCR using UMM was clearly prone to PCR inhibition. In conclusion, the ddPCR technique shows potential for the accurate absolute quantification of STEC on the farms, without relying on standardized reference material. Full article