Unexpectedly high nitrate levels in a pristine forest river on the Southeastern Qinghai-Tibet Plateau.

River nitrate (NO3-) pollution is a global environmental issue. Recently, high NO3- levels in some pristine or minimally-disturbed rivers were reported, but their drivers remain unclear. This study integrated river isotopes (δ18O/δ15N-NO3- and δD/18O-H2O), 15N pairing experiments, and qPCR to reveal the processes driving the high NO3- levels in a nearly pristine forest river on the Qinghai-Tibet Plateau. The river isotopes suggested that, at the catchment scale, NO3- removal was prevalent in summer, but weak in winter. The pristine forest soils contributed more than 90 % of the riverine NO3-, indicating the high NO3- backgrounds. The release of soil NO3- to the river was "transport-limited" in both seasons, i.e., the NO3- production/stock in the soils exceeded the capacity of hydrological NO3- leaching. In summer, this regime and the NO3--plentiful conditions in the soils associated with the strong NO3- nitrification led to the high riverine NO3- levels. While the in-soil nitrification was weak in winter, the leaching of legacy NO3- resulted in the consistently high NO3- levels. This study provides insights into the reasons for high NO3- levels in pristine or minimally-disturbed rivers worldwide and highlights the necessity to consider NO3- backgrounds when evaluating anthropogenic NO3- pollution in rivers.

Spontaneous Co-Assembly of Cellulose Nanocrystals and TiO2 Nanorods Followed by Calcination to Form Cholesteric Inorganic Nanostructures.

Chiral nanomaterials possess unique electronic, magnetic, and optical properties that are relevant to a wide range of applications including photocatalysis, chiral photonics, and biosensing. A simple, bottom-up method to create chiral, inorganic structures is introduced that involves the co-assembly of TiO2 nanorods with cellulose nanocrystals (CNCs) in water. To guide experimental efforts, a phase diagram was constructed to describe how phase behavior depends on the CNCs/TiO2/H2O composition. A lyotropic cholesteric mesophase was observed to extend over a wide composition range as high as 50 wt % TiO2 nanorods, far exceeding other examples of inorganic nanorods/CNCs co-assembly. Such a high loading enables the fabrication of inorganic, free-standing chiral films through removal of water and calcination. Distinct from the traditional templating method using CNCs, this new approach separates sol-gel synthesis from particle self-assembly using low-cost nanorods.

From Soil to River: Revealing the Mechanisms Underlying the High Riverine Nitrate Levels in a Forest Dominated Catchment.

Elevated riverine nitrate (NO3-) levels have led to increased eutrophication and other ecological implications. While high riverine NO3- levels were generally ascribed to anthropogenic activities, high NO3- levels in some pristine or minimally disturbed rivers were reported. The drivers of these unexpectedly high NO3- levels remain unclear. This study combined natural abundance isotopes, 15N-labeling techniques, and molecular techniques to reveal the processes driving the high NO3- levels in a sparsely populated forest river. The natural abundance isotopes revealed that the NO3- was mainly from soil sources and that NO3- removal processes were insignificant. The 15N-labeling experiments also quantitatively showed that the biological NO3- removal processes, i.e., denitrification, dissimilatory NO3- reduction to ammonium (DNRA), and anaerobic ammonia oxidation (anammox), in the soils and sediments were weak relative to nitrification in summer. While nitrification was minor in winter, the NO3- removal was insignificant relative to the large NO3- stock in the catchment. Stepwise multiple regression analyses and structural equation models revealed that in summer, nitrification in the soils was regulated by the amoA-AOB gene abundances and NH4+-N contents. Low temperature constrained nitrification in winter. Denitrification was largely controlled by moisture content in both seasons, and anammox and DNRA could be explained by the competition with nitrification and denitrification on their substrate (nitrite-NO2-). We also revealed the strong hydrological control on the transport of soil NO3- to the river. This study effectively revealed the mechanisms underlying the high NO3- levels in a nearly pristine river, which has implications for the understanding of riverine NO3- levels worldwide.

Coupling geochemical and microbial molecular techniques to reveal catchment-scale nitrate yield and fluvial export dynamics.

The disturbance of reactive nitrogen (N) on ecosystems and biogeochemical cycles is now one of the most severe environmental problems worldwide. Nitrate (NO3-) is usually a dominant reactive N species in river ecosystems. Excessive NO3- concentrations in rivers have led to eutrophication and consequent ecological and environmental damages. Quantifying catchment-scale NO3- yield and export dynamics is crucial for effective remediation of river NO3- pollution. Frequently, natural abundance isotopes of NO3- in a river (δ15N/δ18O-NO3-) are applied to identify sources and potential transformations of NO3- at a catchment scale, while microbial molecular techniques and 15N pairing experiments are employed to reveal the NO3- production and removal processes and their underlying mechanisms in microenvironments (e.g., sediments and soils). In this study, we developed a novel protocol that couples these complementary geochemical and molecular techniques to quantify catchment-scale NO3- yield and fluvial export dynamics. The protocol links microscopic processes with catchment-scale geochemical characteristics to explicitly describe the NO3- cycling processes and their underlying abiotic and biotic mechanisms within a catchment. We applied the protocol to the Dadu and Jiazela catchments on the Qinghai-Tibet Plateau, and demonstrated the effectiveness of the protocol in determining NO3- yield and export dynamics in the catchments.

Anthropogenic impacts on the nitrate pollution in an urban river: Insights from a combination of natural-abundance and paired isotopes.

Urban rivers are often characterized by high nitrate (NO3-) loadings. High NO3- loadings cause water quality and ecological damages, which undermines the sustainable development of cities. To date, the drivers of these high NO3- loadings remain unclear. This study, for the first time, integrated natural-abundance isotopes (δ15 N/δ18O-NO3- and δD/δ18O-H2O) and 15N-pairing techniques to comprehensively reveal the anthropogenic impacts on the NO3- pollution in an urban river. Natural-abundance isotopes suggested that in both the wet and dry seasons, the NO3- was predominantly from the conservative mixing of different sources, and biological NO3- removal was minor. The 15N-pairing experiments supported the natural-abundance isotope data, quantitatively showing that in-soil nitrification was prevailing, while NO3- removal processes (denitrification, anammox, and dissimilatory NO3- reduction to ammonium) were weak. A Bayesian isotope-mixing model showed that soil sources (soil organic nitrogen and chemical fertilizer) dominated the NO3- in the upper reaches, while in the lower reaches, the impermeable riparian zone short-circuited the access of soils to the river. Here, the wastewater treatment plants became a significant source of NO3-. This study quantitatively revealed the drivers of high NO3- loadings in an urban river, and generated important clues for effective NO3- pollution control and remediation in urban rivers.

A Machine Learning-Based Predictive Model for Predicting Lymph Node Metastasis in Patients With Ewing's Sarcoma.

Objective: In order to provide reference for clinicians and bring convenience to clinical work, we seeked to develop and validate a risk prediction model for lymph node metastasis (LNM) of Ewing's sarcoma (ES) based on machine learning (ML) algorithms. Methods: Clinicopathological data of 923 ES patients from the Surveillance, Epidemiology, and End Results (SEER) database and 51 ES patients from multi-center external validation set were retrospectively collected. We applied ML algorithms to establish a risk prediction model. Model performance was checked using 10-fold cross-validation in the training set and receiver operating characteristic (ROC) curve analysis in external validation set. After determining the best model, a web-based calculator was made to promote the clinical application. Results: LNM was confirmed or unable to evaluate in 13.86% (135 out of 974) ES patients. In multivariate logistic regression, race, T stage, M stage and lung metastases were independent predictors for LNM in ES. Six prediction models were established using random forest (RF), naive Bayes classifier (NBC), decision tree (DT), xgboost (XGB), gradient boosting machine (GBM), logistic regression (LR). In 10-fold cross-validation, the average area under curve (AUC) ranked from 0.705 to 0.764. In ROC curve analysis, AUC ranged from 0.612 to 0.727. The performance of the RF model ranked best. Accordingly, a web-based calculator was developed (https://share.streamlit.io/liuwencai2/es_lnm/main/es_lnm.py). Conclusion: With the help of clinicopathological data, clinicians can better identify LNM in ES patients. Risk prediction models established in this study performed well, especially the RF model.

The characteristics of carotid body tumors in high-altitude region: Analysis from a single center.

OBJECTIVES: Though carotid body tumors are rare, increasing attentions have been given because of malignant transformation and high surgical risk. However, at present, the characteristics and etiology still remain unclear. Our study was designed to describe the clinical features of carotid body tumors in our institution and to compare the results with previous reports. METHODS: We retrospectively reviewed carotid body tumor patients diagnosed in our institution from January 2015 to May 2020. The demographics, comorbidities, lesion location, anatomic characteristics, complications, and postoperative outcomes were evaluated. Carotid body tumor measurements were determined from computed tomography, magnetic resonance imaging, and carotid arteriography examination. We described and compared the clinical features of carotid body tumors in our institution and other reports. RESULTS: We totally identified 122 carotid body tumor cases for the present analysis. The mean age was 50.26 years, with the majority being female (82%). The commonest presentation was a painless neck mass (68%). For the distribution of nationality, most patients were the Han nationality (69.7%). The mean altitude of habitat of patients was 2689.4 km; 19.7% patients suffered bilateral lesions. The main blood supply of carotid body tumors was from external carotid artery (54.1%). For patients who received operation, 11 (11.2%) patients experienced cranial nerve injury. The maximal diameter of tumors was 3.99 ± 1.98 cm in male and 3.38 ± 1.36 cm in female. The volume of tumors was 31.49 ± 29.76 cm3 in male and 15.27 ± 13.06 cm3 in female. The distance to base of skull of tumors was 3.39 ± 1.07 cm (3.99 ± 1.98 cm in male vs 3.38 ± 1.36 cm, P < 0.05). Two patients (2.04%) were identified as having malignant carotid body tumor. CONCLUSIONS: Though carotid body tumor had a low morbidity and multitudinous clinicopathologic features, it was apt to middle-aged women and the main blood supply was from external carotid artery. The painless neck mass was the commonest presentation of carotid body tumors. There were significant difference between male and female patients regarding platelet, hemoglobin, distance to base of skull, tumor volume, altitude of habitat, carotid body tumor location, and hypertension.

Reduced Graphene Oxide-Reinforced Polymeric Films with Excellent Mechanical Robustness and Rapid and Highly Efficient Healing Properties.

The fabrication of nanofiller-reinforced intrinsic healable polymer composite films with both excellent mechanical robustness and highly efficient healability is challenging because the mobility of the polymer chains is suppressed by the incorporated nanofillers. In this study, we exploit the reversible host-guest interactions between nanofillers and the matrix polymer films and report the fabrication of intrinsically healable, reduced graphene oxide (RGO)-reinforced polymer composite films capable of conveniently and repeatedly healing cuts of several tens of micrometers wide. The healable films can be prepared via layer-by-layer assembly of poly(acrylic acid) (PAA) with complexes of branched poly(ethylenimine) grafted with ferrocene (bPEI-Fc) and RGO nanosheets modified with ß-cyclodextrin (RGO-CD) (denoted as bPEI-Fc&RGO-CD). The as-prepared PAA/bPEI-Fc&RGO-CD films are mechanically robust with a Young's modulus of 17.2 ± 1.9 GPa and a hardness of 1.00 ± 0.30 GPa. The healing process involves two steps: (i) healing of cuts in an oxidation condition in which the host-guest interactions between bPEI-Fc and RGO-CD nanosheets are broken and the cuts on the films are healed; and (ii) reconstruction of host-guest interactions between bPEI-Fc and RGO-CD nanosheets via reduction to restore the original mechanical robustness of the films.