Pullback Exponential Attractors for Nonautonomous Klein-Gordon-Schrödinger Equations on Infinite Lattices

This paper proves the existence of the pullback exponential attractor for the process associated to the nonautonomous Klein-Gordon-Schrödinger equations on infinite lattices

Nano Titania Applications in Cancer Theranostics

Titanium is one of the most abundantly utilized nanomaterials for human consumption. Biomedical applications of nano titania include sunscreens, drug delivery, prosthetic implants, bioimaging probes, and antimicrobial and antirheumatic agents for various treatment of diseases, including autoimmune disease, neurogenerative diseases, cardiovascular, musculoskeletal, and cancer. Its applications as a drug delivery vehicle and photosensitizer in cancer therapy and diagnosis are highly appreciated, especially for skin and natural cavities applications. The reactive oxygen species (i.e., H2O2, OH., OH2, 1O2, etc.) generation properties of nano titania after activation with light or ultrasound make it ideal for apoptosis induction in neoplastic cells. In addition, the singlet oxygen (1O2) generating properties make it suitable for bioimaging deep-seated and superficial tumors after activation. Nano titania is highly biocompatible with negligible adverse effects. In this chapter, we will focus on the anticancer effects of nano titania on various types of cancers by employing it as a drug delivery vehicle and sensitizer for external source-activated modalities viz. photodynamic and sonodynamic therapy

Association of GSDMD with microvascular-ischemia reperfusion injury after ST-elevation myocardial infarction

ObjectivesLittle is known about the clinical prognosis of gasdermin D (GSDMD) in patients with ST-elevation myocardial infarction (STEMI). The purpose of this study was to investigate the association of GSDMD with microvascular injury, infarction size (IS), left ventricular ejection fraction (LVEF), and major adverse cardiac events (MACEs), in STEMI patients with primary percutaneous coronary intervention (pPCI).MethodsWe retrospectively analyzed 120 prospectively enrolled STEMI patients (median age 53 years, 80% men) treated with pPCI between 2020 and 2021 who underwent serum GSDMD assessment and cardiac magnetic resonance (CMR) within 48 h post-reperfusion; CMR was also performed at one year follow-up.ResultsMicrovascular obstruction was observed in 37 patients (31%). GSDMD concentrations ≧ median (13 ng/L) in patients were associated with a higher risk of microvascular obstruction and IMH (46% vs. 19%, P = 0.003; 31% vs. 13%, P = 0.02, respectively), as well as with a lower LVEF both in the acute phase after infarction (35% vs. 54%, P < 0.001) and in the chronic phase (42% vs. 56%, P < 0.001), larger IS in the acute (32% vs. 15%, P < 0.001) and in the chronic phases (26% vs. 11%, P < 0.001), and larger left ventricular volumes (119 ± 20 vs. 98 ± 14, P = 0.003) by CMR. Univariable and multivariable Cox regression analysis results showed that patients with GSDMD concentrations ≧ median (13 ng/L) had a higher incidence of MACE (P < 0.05).ConclusionsHigh GSDMD concentrations in STEMI patients are associated with microvascular injury (including MVO and IMH), which is a powerful MACE predictor. Nevertheless, the therapeutic implications of this relation need further research

Short-Term Load Forecasting Based on the Transformer Model

From the perspective of energy providers, accurate short-term load forecasting plays a significant role in the energy generation plan, efficient energy distribution process and electricity price strategy optimisation. However, it is hard to achieve a satisfactory result because the historical data is irregular, non-smooth, non-linear and noisy. To handle these challenges, in this work, we introduce a novel model based on the Transformer network to provide an accurate day-ahead load forecasting service. Our model contains a similar day selection approach involving the LightGBM and k-means algorithms. Compared to the traditional RNN-based model, our proposed model can avoid falling into the local minimum and outperforming the global search. To evaluate the performance of our proposed model, we set up a series of simulation experiments based on the energy consumption data in Australia. The performance of our model has an average MAPE (mean absolute percentage error) of 1.13, where RNN is 4.18, and LSTM is 1.93

Validation of stage groupings in the eighth edition of the tumor node metastasis classification for lung adenocarcinoma

Background The purpose of this study was to validate stage groupings in the 8th edition of the tumor node metastasis (TNM) classification for lung adenocarcinoma and explore the non‐anatomic factors that influence the prognosis of lung adenocarcinoma patients in China. Methods We retrospectively analyzed the data of 291 lung adenocarcinoma patients at our department between 2008 and 2013. Logrank tests and Cox regression models were used to analyze survival among adjacent stage groupings. Kaplan–Meier curves were used to estimate overall survival (OS). Results There were significant differences in OS in adjacent stage groupings in early stages in the 8th edition. There were also significant differences between patients treated with radical surgery and limited resection (P = 0.027). Lepidic predominant adenocarcinoma (LPA) had better survival rates than acinar predominant (APA), papillary predominant, and solid predominant with mucin production adenocarcinoma (SPA) (P = 0.008). Survival rates of micropapillary predominant adenocarcinoma were lower than the others (P = 0.003). EGFR mutations were closely associated with lepidic predominant (65%, P = 0.56) but less commonly associated with solid predominant with mucin production adenocarcinoma (24%, P = 0.02). There was no significant difference in survival between EGFR gene mutation‐positive and negative groups (P = 0.402). Conclusion The 8th edition TNM may be more accurate and applicable than the 7th edition for Chinese lung adenocarcinoma patients who have undergone surgical treatment. Stage IV patients may gain survival improvement from radical surgery

Lyophilization based isolation of exosomes

Exosomes are nanoscale extracellular vesicles which regulate intercellular communication. They have great potential for application in nanomedicine. However, techniques for their isolation are limited by requirements for advanced instruments and costly reagents. In this study, we developed a lyophilization-based method for isolating exosomes from cultured cells. The isolated exosomes were characterized for protein content using Bradford assay, and for size distribution and shape using scanning electron microscopy (SEM) and nanoparticles tracking analysis (NTA). In addition, CD63, CD9, CD81, HSP70 and TSG101 were evaluated as essential exosomal surface markers using Western blot. Drug loading and release studies were performed to confirm their drug delivery properties using an in vitro model. Exosomes were also loaded with commercial dyes (Cy5, Eosin) for the evaluation of their drug delivery properties. All these characterizations confirmed successful exosome isolation with measurements of less than 150 nm, having a typical shape, and by expressing the known exosome surface protein markers. Finally, tyrosine kinase inhibitors (dasatinib and ponatinib) were loaded on the exosomes to evaluate their anticancer effects on leukemia cells (K562 and engineered Ba/F3-BCR-ABL) using MTT and Annexin-PI assays. The expression of MUC1 protein on the exosomes isolated from MCF-7 cells also indicated that their potential diagnostic properties were intact. In conclusion, we developed a new method for exosome isolation from cultured cells. These exosomes met all the essential requirements in terms of characterization, drug loading and release ability, and inhibition of proliferation and apoptosis induction in Ph+ leukemia cells. Based on these results, we are confident in presenting the lyophilization-based exosome isolation method as an alternative to traditional techniques for exosome isolation from cultured cells