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Analysis of risk factors for poor wound healing after Nuss procedure for pectus excavatum and establishment of a predictive model
Chaotic and quasi-periodic dynamics in fractional-order nonlinear wave systems within dispersive-dissipative media
Emerging roles of the cancerous inhibitor of protein phosphatase 2A (CIP2A) in ovarian cancer
Abstract Ovarian cancer (OvCa) is the sixth most common gynaecological cancer in the UK, accounting for over 200,000 deaths worldwide. Cancerous Inhibitor of Phosphatase 2 A (CIP2A) is an oncoprotein and an endogenous inhibitor of PP2A. CIP2A is a key regulator for cellular processes (e.g. proliferation, DNA damage) and is involved in the progression of many malignancies. In this study we provide a comprehensive overview of its role in OvCa making use of in silico tools, clinical samples and in vitro models. CIP2A is overexpressed in OvCa patients, with metastatic patients having significantly higher expression when compared to patients with malignant and benign ovarian tumours. High CIP2A expression reduces both overall-and progression-free survival, whereas an R530T mutation is predicted to cause structural destabilisation of the CIP2A dimer. We also provide evidence for microRNA (miRNA) and mRNA target interactions with CIP2A. Finally, we have studied the effects of CIP2A inhibition in an in vitro BRCA2 model compared to BRCA2 wild-type OvCa cells, using RNA-sequencing. Gene enrichment pointed towards changes p53 pathway, protein metabolism, transporter activity, DNA replication, and cell cycle. Our data provide a novel insight into the role of CIP2A in OvCa and the potential of drug repurposing for therapeutic interventions.
Towards precision agriculture: metaheuristic model compression for enhanced pest recognition
An interval type-2 fuzzy multi-criteria decision-making approach for patient bed allocation
A promising natural material for pollutants removal
Association of urine parabens with liver function in US adolescents based on NHANES 2007–2016
Deep learning framework for hourly air pollutants forecasting using encoding cyclical features across multiple monitoring sites in Beijing
Abstract Environmental managers and citizens alike are concerned with air quality. Early warning systems for air pollution are essential to prevent health issues and implement effective prevention strategies. This paper proposes a comprehensive, reliable system with air quality prediction and assessment modules for China’s air pollution. In this study, six air pollutants were observed, including Carbon Monoxide (CO), Nitrogen Dioxide (NO2), Ozone (O3), Sulphur Dioxide (SO2), Fine particulate matter (PM2.5), and Coarse particulate matter (PM10). The current dataset includes hourly air pollutants data from 10 national air-quality monitoring sites, such as Aotizhongxin, Changping, Dongsi, Guanyuan, Huairou, Nongzhanguan, Shunyi, Tiantan, Wanliu, and Wanshouxigong. The dataset was recorded hourly from 01/03/2013 to 28/02/2017. Deep Neural Networks (DNNs) and Convolutional Neural Networks (CNNs) were developed with both unencoded and encoded features to address the forecasting challenge of multivariate time series, specifically in predicting air pollution concentrations. The results showed that, the top accuracy was as follows: 93.8% at the Wanshouxigong station using CNN-Encoded, 91.9% at the Nongzhanguan station using (DNN-Encoded and CNN-Encoded), 93.4% at Aotizhongxin station using DNN-Encoded, 96.2% at Nongzhanguan station using DNN-Encoded, 94% at Dongsi station using CNN-Unencoded, and 92.4% at Aotizhongxin station using (CNN-Unencoded and DNN-Encoded) in forecasting CO, NO2, O3, PM2.5, PM10 and SO2 pollutants, respectively. The findings indicated that the suggested approaches are efficient and dependable for environmental supervisors in the monitoring and management of air pollution.
A large cross-sectional study on the prevalence and predictors of donor and donation images in patients after heart transplantation
Abstract Recovery and clinical outcomes following organ transplantation may be negatively influenced by psychological distress. Limited reports from recipients indicate that thoughts and feelings related to the donor/transplanted organ – referred to as donor and donation images (DDI) – may be a source of such distress. The term DDI encompasses all thoughts and emotions that organ recipients associate with the donor or the donated organ. However, empirical knowledge of DDI remains limited. This quantitative survey involving 407 participants represents the first and largest study to quantitatively examine DDI in patients after heart transplantation (HTX). The results revealed a very high prevalence of DDI (91%), with occurrences reported intermittently and often clustered around the time of transplantation, both before and after HTX. Psychological distress predicted the occurrence of DDI before and after HTX and almost all emotions experienced and reported pre-HTX were associated with higher odds of pre-HTX DDI, suggesting it may be a concurrent phenomenon of overall emotional activation. Due to the involvement of emotions associated with uncertainty and low personal control, along with high situational control, DDI may be a part of coping. Some reported avoiding DDI suggesting that, sometimes, they might also represent a stressor. Future studies should further investigate the effects of DDI, including its impact on transplant outcome.
Nonlinear electronic oscillators as time sensors for high-precision positioning applications
Evaluation of the potential for diagnosis of fungal keratitis using a Fusarium-specific antibody
An integrated widely targeted metabolomics and network pharmacology study of Persicaria runcinata var. Sinensis against arthritis
Cyclodextrin attenuates atherosclerosis by diminishing gasdermin D (GSDMD)-mediated pyroptosis
Temporally consistent Koopman autoencoders for forecasting dynamical systems
Exposure of cells to near-infrared irradiation relaxes chromatin compaction and facilitates recognition of cyclo-butane pyrimidine dimers
Abstract Ultraviolet A and B (UVA 320–400 nm and UVB 280–320 nm) induced cyclobutane-pyrimidine dimers (CPDs) are the most critical lesions caused by environmental sun exposure. Here we show that CPD removal is accelerated when, in addition to UV, cells are simultaneously exposed to water-filtered near-infrared (nIR, 750–1600 nm). The described effect is dose-dependent on the nIR-dose and is found in skin keratinocytes and fibroblasts. Accelerated removal of CPDs, which coincides with chromatin relaxation and faster CPD recognition, occurs after nIR exposure. While nIR alone does not affect cellular survival, co-exposure to UVB leads to reduced cellular survival and an increased number of mutations. Increasing single strand break levels (SSB) occur transiently after nIR exposure and independent of reactive oxygen species (ROS) formation. These data suggest that the rate-limiting step in the NER repair process – damage recognition – is facilitated by nIR-induced chromatin relaxation, causing the accumulation of unnatural high levels of SSBs and single stranded DNA, unfavourable for the cell fate resulting in reduced survival and increased mutation rates. Since nIR modulates the UV-dependent damage response, risk estimation of solar radiation-induced DNA damage should not only consider the UV components but also include the nIR fraction of the solar spectrum.
Socioeconomic disparities in heat vulnerability among adults in Finland
Nomogram for the prediction of the prognosis of patients with triple-negative invasive ductal carcinoma of breast after neoadjuvant chemotherapy
The prognostic significance of the NMD core factor UPF1 in low-grade glioma
Relationship between free fatty acids and diabetic retinopathy in male patients with type 2 diabetes
Abstract This study aims to evaluate the association between fasting serum free fatty acids (FFAs) and diabetic retinopathy (DR) in a population of Chinese men with type 2 diabetes mellitus (T2DM). A total of 781 eligible subjects participated in this cross-sectional study. We collected clinical data and information about the patient’s examination and laboratory tests. The Shapiro–Wilk test was employed to assess the normality of continuous variables. For continuous variables with non-normal distributions, the Mann–Whitney U test and the Kruskal-Wallis test was utilized for comparisons. Categorical variable comparisons were performed using the chi-square test. Logistic regression analyses and restricted cubic spline (RCS) curves were conducted to examine the association between FFAs levels and DR. FFAs levels were slightly lower in the DR group compared to the NDR group (0.35 vs. 0.41 mmol/L, p < 0.05). The logistic regression model did not identify a statistically significant linear relationship between FFAs levels and DR incidence (OR = 0.776, 95% CI: 0.308–1.955, p = 0.591). After adjusting for various confounding factors, RCS curves revealed a U-shaped relationship between FFAs and DR. This relationship was validated in subgroup analyses stratified by age, diabetes duration, BMI, and alcohol consumption status. The U-shaped curve was evident in most subgroups, indicating that both low and high levels of FFAs are associated with an increased risk of DR. IIn this study, we found a U-shaped relationship between FFAs and DR in Chinese men with T2DM. Both low and high levels of FFAs were associated with an increased risk of DR.