Managing health risks of perfluoroalkyl acids in aquatic food from a river-estuary-sea environment affected by fluorochemical industry

Substantial perfluoroalkyl acids (PFAAs) production still occurs in China, and the consumption of aquatic products is a critical exposure pathway of PFAAs in humans. In this study, specimens of 16 freshwater and 40 marine species were collected in the river-estuary-sea environment affected by a mega fluorochemical industry park in China in 2015, and the edible tissues of these organisms were analyzed for PFAA levels. Perfluorooctanoic acid (PFOA) was the dominating contaminant with an overall contribution of more than 90%, and concentrations as high as 2161 ng/g wet weight (measured in the freshwater winkle). All species with the greatest PFOA levels were benthic. The trophic magnification factor (TMF) of PFOA was 1.10 for freshwater species and 1.28 for marine species, indicating that PFOA was slightly magnifying. Analysis of carbon source indicated that freshwater species were more benthic feeding, while marine species were more pelagic feeding. Aquatic food consumption screening values of PFOA were modified according to estimated daily intake (EDI) values, which generated recommendations for limited meal categories and the do-not-eat category. Thus, this study provides recommendations for mitigating the health risks of PFAA-contaminated aquatic food, ranging from food selection to consumption frequency and proper food processing

Application of Machine Learning Algorithms to Predict Central Lymph Node Metastasis in T1-T2, Non-invasive, and Clinically Node Negative Papillary Thyroid Carcinoma

Purpose: While there are no clear indications of whether central lymph node dissection is necessary in patients with T1-T2, non-invasive, clinically uninvolved central neck lymph nodes papillary thyroid carcinoma (PTC), this study seeks to develop and validate models for predicting the risk of central lymph node metastasis (CLNM) in these patients based on machine learning algorithms. Methods: This is a retrospective study comprising 1,271 patients with T1-T2 stage, non-invasive, and clinically node negative (cN0) PTC who underwent surgery at the Department of Endocrine and Breast Surgery of The First Affiliated Hospital of Chongqing Medical University from February 1, 2016, to December 31, 2018. We applied six machine learning (ML) algorithms, including Logistic Regression (LR), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGBoost), Random Forest (RF), Decision Tree (DT), and Neural Network (NNET), coupled with preoperative clinical characteristics and intraoperative information to develop prediction models for CLNM. Among all the samples, 70% were randomly selected to train the models while the remaining 30% were used for validation. Indices like the area under the receiver operating characteristic (AUROC), sensitivity, specificity, and accuracy were calculated to test the models' performance. Results: The results showed that ~51.3% (652 out of 1,271) of the patients had pN1 disease. In multivariate logistic regression analyses, gender, tumor size and location, multifocality, age, and Delphian lymph node status were all independent predictors of CLNM. In predicting CLNM, six ML algorithms posted AUROC of 0.70–0.75, with the extreme gradient boosting (XGBoost) model standing out, registering 0.75. Thus, we employed the best-performing ML algorithm model and uploaded the results to a self-made online risk calculator to estimate an individual's probability of CLNM (https://jin63.shinyapps.io/ML_CLNM/). Conclusions: With the incorporation of preoperative and intraoperative risk factors, ML algorithms can achieve acceptable prediction of CLNM with Xgboost model performing the best. Our online risk calculator based on ML algorithm may help determine the optimal extent of initial surgical treatment for patients with T1-T2 stage, non-invasive, and clinically node negative PTC

The role of autophagy in cardiovascular disease: Cross-interference of signaling pathways and underlying therapeutic targets

Autophagy is a conserved lysosomal pathway for the degradation of cytoplasmic proteins and organelles, which realizes the metabolic needs of cells and the renewal of organelles. Autophagy-related genes (ATGs) are the main molecular mechanisms controlling autophagy, and their functions can coordinate the whole autophagic process. Autophagy can also play a role in cardiovascular disease through several key signaling pathways, including PI3K/Akt/mTOR, IGF/EGF, AMPK/mTOR, MAPKs, p53, Nrf2/p62, Wnt/β-catenin and NF-κB pathways. In this paper, we reviewed the signaling pathway of cross-interference between autophagy and cardiovascular diseases, and analyzed the development status of novel cardiovascular disease treatment by targeting the core molecular mechanism of autophagy as well as the critical signaling pathway. Induction or inhibition of autophagy through molecular mechanisms and signaling pathways can provide therapeutic benefits for patients. Meanwhile, we hope to provide a unique insight into cardiovascular treatment strategies by understanding the molecular mechanism and signaling pathway of crosstalk between autophagy and cardiovascular diseases

Regulating C2H2/CO2 adsorption selectivity by electronic-state manipulation of iron in metal-organic frameworks

Article reports a metal electronic-state manipulation strategy to construct a pair of isostructural and interconvertible Fe-MOFs featuring open Fe centers with different electron densities for efficient C₂H₂/CO₂ separation. The authors show that the presence of Fe[II] centers with a medium-spin-state trail plays a crucial role in the enhanced C₂H₂ selective adsorption

On the Origin of Tibetans and Their Genetic Basis in Adapting High-Altitude Environments

Since their arrival in the Tibetan Plateau during the Neolithic Age, Tibetans have been well-adapted to extreme environmental conditions and possess genetic variation that reflect their living environment and migratory history. To investigate the origin of Tibetans and the genetic basis of adaptation in a rigorous environment, we genotyped 30 Tibetan individuals with more than one million SNP markers. Our findings suggested that Tibetans, together with the Yi people, were descendants of Tibeto-Burmans who diverged from ancient settlers of East Asia. The valleys of the Hengduan Mountain range may be a major migration route. We also identified a set of positively-selected genes that belong to functional classes of the embryonic, female gonad, and blood vessel developments, as well as response to hypoxia. Most of these genes were highly correlated with population-specific and beneficial phenotypes, such as high infant survival rate and the absence of chronic mountain sickness

Sparse Representation of Brain Aging: Extracting Covariance Patterns from Structural MRI

An enhanced understanding of how normal aging alters brain structure is urgently needed for the early diagnosis and treatment of age-related mental diseases. Structural magnetic resonance imaging (MRI) is a reliable technique used to detect age-related changes in the human brain. Currently, multivariate pattern analysis (MVPA) enables the exploration of subtle and distributed changes of data obtained from structural MRI images. In this study, a new MVPA approach based on sparse representation has been employed to investigate the anatomical covariance patterns of normal aging. Two groups of participants (group 1∶290 participants; group 2∶56 participants) were evaluated in this study. These two groups were scanned with two 1.5 T MRI machines. In the first group, we obtained the discriminative patterns using a t-test filter and sparse representation step. We were able to distinguish the young from old cohort with a very high accuracy using only a few voxels of the discriminative patterns (group 1∶98.4%; group 2∶96.4%). The experimental results showed that the selected voxels may be categorized into two components according to the two steps in the proposed method. The first component focuses on the precentral and postcentral gyri, and the caudate nucleus, which play an important role in sensorimotor tasks. The strongest volume reduction with age was observed in these clusters. The second component is mainly distributed over the cerebellum, thalamus, and right inferior frontal gyrus. These regions are not only critical nodes of the sensorimotor circuitry but also the cognitive circuitry although their volume shows a relative resilience against aging. Considering the voxels selection procedure, we suggest that the aging of the sensorimotor and cognitive brain regions identified in this study has a covarying relationship with each other

Aerodynamics of a Wing with a Wingtip Flapper

In the present study, an oscillating membrane flapper was pivotally attached to the tip of a conventional rigid wing. Stroke-averaged aerodynamic forces were measured for the range of the flapping frequency, showing significant increases in the lift coefficient and lift-to-drag ratio for the wing with a flapper. Major vortex patterns were deduced from observations of smoke-wire visualization and 2D phase-locked particle image velocimetry (PIV). The centerline of the primary vortex wanders in the counterclockwise direction. On the contrary, its core rotates in the same sense of rotation as a wingtip vortex in a conventional wing. The secondary weaker vortex of opposite rotation lasts for a half stroke. The vortex ring sheds from the flapper during the second half of the upstroke and pronation. The outer parts of the vortex system are much stronger than the inner ones. The circulation and size of vortices decrease significantly at the most distant station from the wing. Strong vertical jets were found in smoke-wire visualization and confirmed with velocity and vorticity fields obtained by PIV. These jets are formed between undulating vortices and inside of the vortex ring. The jet airflow moves away from the flapper and downward or upward depending on the flapping direction.Open access journal.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Confirming the diversity of the brain after normalization: an approach based on identity authentication.

During the development of neuroimaging, numerous analyses were performed to identify population differences, such as studies on age, gender, and diseases. Researchers first normalized the brain image and then identified features that represent key differences between groups. In these studies, the question of whether normalization (a pre-processing step widely used in neuroimaging studies) reduces the diversity of brains was largely ignored. There are a few studies that identify the differences between individuals after normalization. In the current study, we analyzed brain diversity on an individual level, both qualitatively and quantitatively. The main idea was to utilize brain images for identity authentication. First, the brain images were normalized and registered. Then, a pixel-level matching method was developed to compute the identity difference between different images for matching. Finally, by analyzing the performance of the proposed brain recognition strategy, the individual differences in brain images were evaluated. Experimental results on a 150-subject database showed that the proposed approach could achieve a 100% identification ratio, which indicated distinct differences between individuals after normalization. Thus, the results proved that after the normalization stage, brain images retain their main distinguishing information and features. Based on this result, we suggest that diversity (individual differences) should be considered when conducting group analysis, and that this approach may facilitate group pattern classification

Reversible Phase Transformation in Ti₂AlC Films during He Radiation and Subsequent Annealing

Ti2AlC film can be used as a protective coating for fuel cladding materials and structural materials in nuclear reactors. However, the related radiation damage and the helium (He) effects have not been well understood. In this work, the He radiation effects on Ti2AlC thin films, deposited by reactive magnetron sputtering, were studied. In addition to the detailed characterization of the radiation-induced defects and He bubbles, phase transformation was identified and investigated during film deposition, ion irradiation, and subsequent annealing. Results suggested that the hexagonal close-packed (hcp) Ti2AlC was formed from a solid-solution face-centered cubic (fcc) (Ti2Al)C phase during the film deposition process. A phase transformation from hcp-Ti2AlC to fcc-(Ti2Al)C happened during the He ion irradiation, while a reversible phase transformation from fcc-(Ti2Al)C to hcp-Ti2AlC occurred during the post annealings at temperatures above 600 °C. The reversible phase transformation indicates dynamic restoration of this material and provides insights into the design of new irradiation-damage-tolerant ceramic materials