DCE-MRI and parametric imaging in monitoring response to neoadjuvant chemotherapy in breast carcinoma : a preliminary report

Purpose: Neoadjuvant chemotherapy is recommended in patients with locally advanced breast cancer. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) enables evaluation of the tumour neovasculature that occurs prior to any volume change, which helps identify early treatment failures and allows prompt implementation of second-line therapy. Material and methods: We conducted a prospective study in 14 patients with histopathologically proven breast cancer. DCE-MRI data were acquired using multisection, T1-weighted, 3D vibe sequences with fat suppression before, during, and after IV bolus injection (0.1 mmol/kg body weight, Gadoversetamide, Optimark). Post-processing of dynamic contrast perfusion data was done with the vendor's Tissue 4D software to generate various dynamic contrast parameters, i.e. Ktrans, Kep, Ve, initial area under the time signal curve (IAUC), apparent diffusion coefficient (ADC), and enhancement curve. Patients underwent MRI examinations at baseline, and then after two cycles, and finally at completion of chemotherapy. Results: Based on Sataloff criteria for pathological responses, four patients out of 14 were responders, and 10 were non-responders. At the 2nd MRI examination, IAUC was significantly smaller in responders than in non-responders (p = 0.023). When the results of the first and second MRI examinations were compared, Kep decreased from baseline to the second MRI (p = 0.03) in non-responders and in responders (p = 0.04). This change was statistically significant in both groups. The ADC values increased significantly in responders from baseline to the third MRI (p = 0.012). Conclusions: In our study, IAUC and ADC were the only parameters that reliably differentiated responders from non-responders after two and three cycles of chemotherapy

Water-stable perovskite-on-polymer fluorescent microspheres for simultaneous monitoring of pH, urea, and urease

Perovskite materials have attracted attention due to their excellent optical and electrical properties; however, their unsatisfactory stability limits their application in biochemical detection. In this paper, CsPbBr3 perovskite quantum dots were successfully encapsulated in poly(styrene/acrylamide) microspheres, using a swelling–shrinking method. The manufactured perovskite microspheres (PDPS composites) not only maintained strong photoluminescence (PL) stability but also demonstrated great water solubility. Additionally, a real-time pH monitoring platform was constructed based on the prepared PDPS composites and dopamine, and the system showed a good linear relationship in a pH range of 4–12. Furthermore, urea could be hydrolyzed to produce hydroxyl groups, thereby increasing the pH of the solution. Therefore, this system was then extended for urea and urease detection. As a result, the detection limits of urea and urease were recorded as 1.67 μM and 2.1 mU/mL, respectively. This development provides an interesting demonstration of the expanding list of applications of perovskite materials

A systematic literature review of current understanding and future scope on green intellectual capital

Purpose: This paper intends to scrutinize evolution and the growth of literature on green intellectualcapital(GIC)over the period 2008 to 2022, consequences of green intellectual capital, its sectoralclassification, current trends and future scope of research.Design/methodology: For a better understanding of this concept, a systematically arranged reviewwas performed following PRISMA framework. For this, data has been extracted from Scopus and Webof Science databases because they are the largest databases and provide international coverage. Collecteddata was confined on the basis of inclusion and exclusion criteria. The paper was sectioned into twotypes of analysis: bibliometric analysis and content analysis. Findings: Results highlighted that green intellectual capital has important meanings in influencingorganisational performance namely economic, social and financial performance. Studies were focusedmainly on Asian countries using quantitative analysis and deduced that researchers were mainly focusedon manufacturing sector. Findings depict that GIC translates into explicit results but when itscomponents’ effects are analysed, they individually show ambiguous results.Research limitations/implications: This study will provide useful insights to researchers,practitioners, managers and policy makers. Findings suggest intangible resource- green intellectual capitalshould be managed efficaciously which will provide competitive benefits and also contribute toorganisations’ financial, social and environmental performance.Originality/value: The existing literature needs to be comprehended and streamlined by interpretingthe nuances in the existing research work for enabling synergy in deciphering the explicit outcomes ofthe extant literature. Also, there are only a few studies focusing on this construct and on its systematicliterature reviewPeer Reviewe

Investigation of Compressor Cascade Flow Using Physics- Informed Neural Networks with Adaptive Learning Strategy

In this study, we utilize the emerging Physics Informed Neural Networks (PINNs) approach for the first time to predict the flow field of a compressor cascade. Different from conventional training methods, a new adaptive learning strategy that mitigates gradient imbalance through incorporating adaptive weights in conjunction with dynamically adjusting learning rate is used during the training process to improve the convergence of PINNs. The performance of PINNs is assessed here by solving both the forward and inverse problems. In the forward problem, by encapsulating the physical relations among relevant variables, PINNs demonstrate their effectiveness in accurately forecasting the compressor's flow field. PINNs also show obvious advantages over the traditional CFD approaches, particularly in scenarios lacking complete boundary conditions, as is often the case in inverse engineering problems. PINNs successfully reconstruct the flow field of the compressor cascade solely based on partial velocity vectors and near-wall pressure information. Furthermore, PINNs show robust performance in the environment of various levels of aleatory uncertainties stemming from labeled data. This research provides evidence that PINNs can offer turbomachinery designers an additional and promising option alongside the current dominant CFD methods

The need of diagrams based on Toulmin schema application: an aeronautical case study

In this article, Justification Diagrams are introduced for structuring evidence to support conclusions that are reached from results of simulation studies. An industrial application is used to illustrate the use of the Justification Diagrams. Adapted from the Toulmin schema, the aim of Justification Diagram is to define a comprehensive, auditable and shareable notation to explain the results, the input data, the assumptions made and the techniques applied, to construct a cogent conclusion. Further, the Justification Diagrams provide a visual representation of the argument that aims to corroborate the specified claims, or conclusions. A large part of this work is based on the application of the Justification Diagrams in the context of the European project, TOICA. The Justification Diagrams were used to structure all justifications that would be needed to convince an authority that a simulation process, and the associated results, upheld a particular conclusion. These diagrams are built concurrently in a product development process that accompanies the various stages of Verification and Validation (V&V) and where, for each design stage of V&V, argumentation is constructed by aggregating evidence and documents produced at this design stage

Prediction of peptidoglycan hydrolases- a new class of antibacterial proteins

Comparison of performance of the three approaches using known 250 peptidoglycan hydrolases. (XLSX 8 kb

A Comprehensive Survey of Data Mining Techniques on Time Series Data for Rainfall Prediction

Time series data available in huge amounts can be used in decision-making. Such time series data can be converted into information to be used for forecasting. Various techniques are available for prediction and forecasting on the basis of time series data. Presently, the use of data mining techniques for this purpose is increasing day by day. In the present study, a comprehensive survey of data mining approaches and statistical techniques for rainfall prediction on time series data was conducted. A detailed comparison of different relevant techniques was also conducted and some plausible solutions are suggested for efficient time series data mining techniques for future algorithms.

Epidemiološka tipizacija bakterije Staphylococcus aureus na osnovi DNA polimorfizma duljine restrikcijskoga fragmenta gena coa

Twenty one Staphylococcus aureus isolates of bovine mastitic milk origin from herds at different locations were analysed for their coa gene products and RFLP patterns. One of the isolates was coa gene deficient whereas the rest revealed polymorphism in the coa gene. The isolates revealed three different types of coa gene products (600, 680 or 850 bp) and three distinct RFLP patterns were obtained with AluI digests of PCR products. Amplicons of 600 bp produced only one fragment of 300 bp (Pattern I), amplicons of 680 bp produced two fragments of 210 and 260 bp (pattern II) and amplicons of 850 bp produced 3 bands at 170, 290 and 390 bp (pattern III). It was concluded that not all the S. aureus isolates possessed the coa gene, the coa genotype was location-specific and this character of the isolates can be used in epidemiological investigations.Dvadeset i jedan izolat bakterije Staphylococcus aureus iz mlijeka krava s upalom vimena iz različitih stada bio je analiziran na proizvode njezina gena coa i polimorfizam duljine restrikcijskih fragmenata (PDRF). U jednom izolatu nije bio dokazan gen coa dok je u ostalim ustanovljen polimorfizam u tom genu. Izolati su pokazali tri različita tipa proizvoda gena coa (600, 680 ili 850 bp), a cijepanjem PCR proizvoda enzimom AluI dobivena su tri različita uzorka PDRF. Amplikoni od 600 bp imali su samo jedan fragment od 300 bp (uzorak I). Amplikoni od 680 bp pocijepali su se na dva fragmenta, jedan od 210, a drugi od 260 bp (uzorak II). Amplikoni od 850 bp pocijepali su se na tri fragmenta: 170, 290 i 390 bp (uzorak III). Zaključuje se da svi izolati vrste Staphylococcus aureus ne posjeduju gen coa, te da je genotip coa bio specifičan po svojoj lokaciji i da se ta značajka izolata može rabiti u epidemiološkim istraživanjima