PREDICT-GTN 1: Can we improve the FIGO scoring system in gestational trophoblastic neoplasia?

Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.     

The Value of Lung Injury Score in Assessing the Outcome of Patients with Rib Fracture

Background and Purpose:   

Management of rib fractures constitutes a major part of the trauma workload of any unit. Rib fractures result in disrupted chest wall mechanics and ventilatory insufficiency. The ability of a lung injury scoring system to predict the degree of respiratory dysfunction after rib fractures was evaluated.     

Spontaneous keloids in siblings

The authors report two rare cases of 'non-syndromic spontaneous keloids' occuring in siblings. This represents another unexplored area in the field of 'keloid challenge', warranting further research and development.     

Recombinant Helicobacter bilis Protein P167 for Mouse Serodiagnosis in a Multiplex Microbead Assay

Infection of mice with Helicobacter bilis is widespread in research and commercial mouse colonies. Therefore, sensitive, specific, and high-throughput assays are needed for rapid and accurate testing of mice in large numbers. This report describes a novel multiplex assay, based on fluorescent microbeads, for serodetection of H. bilis infection. The assay requires only a few microliters of serum to perform and is amenable to a high-throughput format. Individual microbead sets were conjugated to purified, H. bilis-specific, recombinant proteins P167C and P167D and bacterial membrane extracts from H. bilis and Helicobacter hepaticus. For detecting H. bilis infection in the microbead multiplex assay, P167C and P167D provided significantly higher sensitivities (94 and 100%, respectively) and specificities (100 and 95%, respectively) than membrane extract (78% sensitivity and 65% specificity). Microbead multiplex assay results were validated by enzyme-linked immunosorbent assay. Purified recombinant proteins showed low batch-to-batch variation; this feature allows for ease of quality control, assay robustness, and affordability. Thus, recombinant antigens are highly suitable in the multiplex microbead assay format for serodetection of H. bilis infection.     

Effect of nitration on protein tyrosine phosphatase and protein phosphatase activity in neuronal cell membranes of newborn piglets

Protein tyrosine phosphatase predominantly determines the status of protein tyrosine kinase-dependent phosphorylation of specific proteins and controls the survival and death of neurons. Previous studies have shown that protein tyrosine phosphatase activity is decreased during hypoxia in cortical membranes of the newborn piglet. We have also shown that nitric oxide (NO) free radicals are generated during hypoxia, and may result in modification of protein tyrosine phosphatase via peroxynitrite-mediated modification. The present study tests the hypothesis that the hypoxia-induced decrease in protein tyrosine phosphatase activity is NO-mediated. To test this hypothesis, in vitro experiments were conducted by measuring protein tyrosine phosphatase activity in the presence of an NO donor, sodium nitroprusside (SNP), or peroxynitrite. Since 3-nitrotyrosine is produced as a consequence of peroxynitrite reactions, we have also examined the effect of 3-nitrotyrosine on protein phophatase activity. Cerebral cortical P(2) membranes were prepared from seven normoxic newborn piglets and each sample was divided into three aliquots: a control group, a SNP group (exposed to 200 microM SNP), and a peroxynitrite group (exposed to 100 microM peroxynitrite). Protein tyrosine phosphatase activity was determined spectrophotometrically in the presence or absence of 2 microM bpV(phen), a highly selective inhibitor of protein tyrosine phosphatase. The protein tyrosine phosphatase activity was 198+/-25 nmol/mg protein/h in the normoxic group, 177+/-30 nmol/mg protein/h in the SNP group (p=NS versus normoxic) and 77+/-20 nmol/mg protein/h in the peroxynitrite group (p<0.001 versus normoxic). The results show that peroxynitrite but not SNP exposure results in decreased protein tyrosine phosphatase activity in vitro. Furthermore 3-nitrotyrosine (100 microm), a product of peroxynitrite, decreased the enzyme activity from 926+/-102 to 200+/-77 (p<0.001). We conclude that protein tyrosine phosphatase regulation is mediated by peroxynitrite. We propose that hypoxia-induced NO production leading to peroxynitrite formation is a potential mechanism of protein tyrosine phosphatase inactivation in vivo. The NO-induced decrease in protein tyrosine phosphatase and protein phosphatase activity, leading to Bcl-2 protein phosphorylation and loss of its antiapoptotic activity may be a NO-mediated mechanism of programmed cell death in the hypoxic brain.     

Prediction of Ecofriendly Concrete Compressive Strength Using Gradient Boosting Regression Tree Combined with GridSearchCV Hyperparameter-Optimization Techniques

A crucial factor in the efficient design of concrete sustainable buildings is the compressive strength (Cs) of eco-friendly concrete. In this work, a hybrid model of Gradient Boosting Regression Tree (GBRT) with grid search cross-validation (GridSearchCV) optimization technique was used to predict the compressive strength, which allowed us to increase the precision of the prediction models. In addition, to build the proposed models, 164 experiments on eco-friendly concrete compressive strength were gathered for previous researches. The dataset included the water/binder ratio (W/B), curing time (age), the recycled aggregate percentage from the total aggregate in the mixture (RA%), ground granulated blast-furnace slag (GGBFS) material percentage from the total binder used in the mixture (GGBFS%), and superplasticizer (kg). The root mean square error (RMSE) and coefficient of determination (R²) between the observed and forecast strengths were used to evaluate the accuracy of the predictive models. The obtained results indicated that—when compared to the default GBRT model—the GridSearchCV approach can capture more hyperparameters for the GBRT prediction model. Furthermore, the robustness and generalization of the GSC-GBRT model produced notable results, with RMSE and R² values (for the testing phase) of 2.3214 and 0.9612, respectively. The outcomes proved that the suggested GSC-GBRT model is advantageous. Additionally, the significance and contribution of the input factors that affect the compressive strength were explained using the Shapley additive explanation (SHAP) approach.     

Multi-Objective Optimization of Process Parameters during Micro-Milling of Nickel-Based Alloy Inconel 718 Using Taguchi-Grey Relation Integrated Approach

This research investigates the machinability of Inconel 718 under conventional machining speeds using three different tool coatings in comparison with uncoated tool during milling operation. Cutting speed, feed rate and depth of cut were selected as variable machining parameters to analyze output responses including surface roughness, burr formation and tool wear. It was found that uncoated and AlTiN coated tools resulted in lower tool wear than nACo and TiSiN coated tools. On the other hand, TiSiN coated tools resulted in highest surface roughness and burr formation. Among the three machining parameters, feed was identified as the most influential parameter affecting burr formation. Grey relational analysis identified the most optimal experimental run with a speed of 14 m/min, feed of 1 μm/tooth, and depth of cut of 70 μm using an AlTiN coated tool. ANOVA of the regression model identified the tool coating parameter as most effective, with a contribution ratio of 41.64%, whereas cutting speed and depth of cut were found to have contribution ratios of 18.82% and 8.10%, respectively. Experimental run at response surface optimized conditions resulted in reduced surface roughness and tool wear by 18% and 20%, respectively.