Bisphenol A (BPA) is a common endocrine disruptor widely found in commercial products. Despite negative human health effects, its usage is not fully banned worldwide with ongoing human exposure from sources including dust, aerosol particles, and surfaces. Although attention has been paid to the abundance of alternatives with similar structures that are replacing BPA, uncertainties remain with respect to their chemical transformations and products, toxicity, and environmental fate. We provide the first experimental and modeling assessment of gas-particle multiphase OH oxidation of BPA and six common bisphenol alternatives. We examine the transformation of condensed-phase BPA and its alternatives using an oxidation flow reactor with products monitored by online mass spectrometry. Fourteen products were identified and used to develop a generic mechanism applicable to all bisphenols and to provide inputs into an environmental fate model (PROduction-to-Exposure; PROTEX). Our modeling results highlight the role of heterogeneous surface reactions in determining the indoor retention of these chemicals and their relative environmental persistence indoors and outdoors. All investigated parent molecules yield transformation products predicted to accumulate indoors, with extended indoor persistence if a long chemical lifetime on surfaces (e.g., >100 weeks) is assumed. Evidence of phenoxy radical presence upon oxidation raises a human health risk concern.

Our study evaluates the diagnostic accuracy of ChatGPT-4o in classifying various skin lesions, highlighting its limitations in distinguishing squamous cell carcinoma from basal cell carcinoma using dermatoscopic images.

Monitoring dynamic balance during gait is critical for fall prevention in the elderly. The current study aimed to develop recurrent neural network models for extracting balance variables from a single inertial measurement unit (IMU) placed on the sacrum during walking. Thirteen healthy young and thirteen healthy older adults wore the IMU during walking and the ground truth of the inclination angles (IA) of the center of pressure to the center of mass vector and their rates of changes (RCIA) were measured simultaneously. The IA, RCIA, and IMU data were used to train four models (uni-LSTM, bi-LSTM, uni-GRU, and bi-GRU), with 10% of the data reserved to evaluate the model errors in terms of the root-mean-squared errors (RMSEs) and percentage relative RMSEs (rRMSEs). Independent -tests were used for between-group comparisons. The sensitivity, specificity, and Pearson's r for the effect sizes between the model-predicted data and experimental ground truth were also obtained. The bi-GRU with the weighted MSE model was found to have the highest prediction accuracy, computational efficiency, and the best ability in identifying statistical between-group differences when compared with the ground truth, which would be the best choice for the prolonged real-life monitoring of gait balance for fall risk management in the elderly.

Glioblastoma (GBM) stands as the most aggressive and lethal among the main types of primary brain tumors. It exhibits malignant growth, infiltrating the brain tissue, and displaying resistance toward treatment. GBM is a complex disease characterized by high degrees of heterogeneity. During tumour growth, microglia and astrocytes, among other cells, infiltrate the tumour microenvironment and contribute extensively to gliomagenesis. Tumour-associated macrophages (TAMs), either of peripheral origin or representing brain-intrinsic microglia, are the most numerous nonneoplastic populations in the tumour microenvironment in GBM. The complex heterogeneous nature of GBM cells is facilitated by the local inflammatory tumour microenvironment, which mostly induces tumour aggressiveness and drug resistance. The immunosuppressive tumour microenvironment of GBM provides multiple pathways for tumour immune evasion, contributing to tumour progression. Additionally, TAMs and astrocytes can contribute to tumour progression through the release of cytokines and activation of signalling pathways. In this review, we summarize the role of the microenvironment in GBM progression, focusing on neuroinflammation. These recent advancements in research of the microenvironment hold the potential to offer a promising approach to the treatment of GBM in the coming times.

Functional neuroimaging conducted at regular intervals throughout sleep deprivation reveals key thalamocortical connectivity changes that characterize the transition from a well-rested to a sleep-deprived state. Decreased thalamic connectivity is distributed across sensorimotor, visual, and limbic networks, including subcortical structures such as the parahippocampal gyrus and hippocampus. Associated changes in globally efficiency closely track group-level deficits in psychomotor vigilance, suggesting that thalamic-cortical interactions play a role in wake maintenance during sleep deprivation. These patterns of connectivity disruptions may reflect transient, sleep-like states arising from unstable wakefulness. Causal modeling indicates impaired self-inhibition within the thalamus is a dominant feature of sleep deprivation, which likely contributes to wake-state instability and attentional lapses.