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Human activities have resulted in the eutrophication of rivers, leading to heightened concerns regarding the occurrence of filamentous algal blooms. With the increasing utilization of rivers by humans, the occurrence of these nuisance filamentous algae is expected to increase in frequency in the future. Blooms primarily occur due to energy congestion at the trophic level of primary producers, resulting from inefficient energy flow in both the bottom-up and top-down pathways. To investigate the mechanism underlying the outbreak of filamentous algae, two streams in the southern Taihang catchment with different nutrient conditions were selected for this study. The objective of this study was to understand the effects of nutrient levels and other potential factors on the distribution and succession of filamentous algae. Our findings revealed a positive correlation between nutrient conditions and the biomass of filamentous algae. Cladophora and Spirogyra were identified as the dominant species among filamentous algae, each exhibiting unique distribution patterns in the two streams. Spirogyra thrived predominantly in the Baligou stream, where lower nutrient levels and warmer temperatures prevailed. In contrast, Cladophora flourished in the nutrient-rich Nanping stream at colder temperatures. Results from the generalized linear model indicated that the biomass of Cladophora was influenced by nutrient concentration, water depth, water temperature, and macrobenthic biomass. The biomass of Spirogyra, on the other hand, was primarily determined by water temperature, nutrient concentrations, water depth, and velocity. The positive correlation between Cladophora and macrobenthos revealed a possible mutually beneficial relationship, suggesting that macrobenthos may promote the growth of Cladophora by inhibiting periphytic diatoms. In return, the macrobenthos benefit from a secure refuge and an environment conducive to foraging and reproduction. This study suggested that to alleviate energy flow congestion in the benthic food chain, it is advisable to address this issue by either reducing nutrient loadings in rivers or enhancing the presence of benthivorous fishes in streams. [ABSTRACT FROM AUTHOR]

Objective: To analyze risk factors associated with bladder dysfunction in patients with type 2 diabetes mellitus (T2DM) and to construct a prediction model for early prediction of diabetic bladder dysfunction (DBD). Methods: We included hospitalized patients with T2DM from the endocrinology department of Shenzhen Hospital, Southern Medical University, Shenzhen, China, from January 2019 to 2022. Factors associated with DBD in bivariate analysis with a p < 0.05 were included in a multivariate logistic regression analysis. Multivariate logistic regression analysis was used to determine independent risk factors and to construct a prediction model. The prediction model was presented as the model formula. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of the above risk factors and the prediction model for DBD. The model was internally verified by Boostrap resampling 1000 times. Results: Two hundred and eleven patients were included in this study, and they were divided into the DBD group (n = 101) and the non‐DBD group (n = 110). Eight variables showed significant significance in the bivariate analysis, including age, diabetic peripheral neuropathy (DPN), glycated hemoglobin (HbA1c), urinary microalbumin (mALB), red blood cell count (RBC), white blood cell count (WBC), absolute neutrophil count (ANC), percentage of monocyte (Mono%). Furthermore, multivariate logistic regression analysis revealed that age (OR [95% CI]: 1.077 [1.042−1.112]), p < 0.001; DPN (OR [95% CI]: 2.373 [1.013−5.561]), p = 0.047; HbA1c (OR [95% CI]: 1.170 [1.029−1.330]), p = 0.017 and ANC (OR [95% CI]: 1.234 [1.059−1.438]), p = 0.007 were independent risk factors for the DBD. The prediction model formula was Logit (p) = −6.611 + 0.074 age + 0.864 DPN + 0.157 HbA 1 c + 0.078 ANC. The area under the ROC curve (AUC) for the four risk factors were 0.676, 0.582, 0.618, and 0.674, respectively. The prediction model predicted DBD with higher accuracy than the individual risk factors, AUC = 0.817 (95% CI: 0.757−0.877), and the sensitivity and specificity were 88.1% and 50.0%, respectively. The model internal validation results showed that the AUC = 0.804 (95% CI: 0.707−0.901), and the calibration curve is close to the ideal diagonal line. Conclusions: Age, DPN, HbA1c, and ANC were risk factors for DBD. The prediction model constructed based on the four risk factors had a good predictive value for predicting the occurrence of DBD. [ABSTRACT FROM AUTHOR]

Most of the known ionic electrical components are fabricated from petroleum-based raw materials and are not recyclable or degradable. A necessary solution involving the green fabrication of ionic conductors, which requires efficiency, scalability, and environmental friendliness, should be developed. Herein, we prepared a liquid-free dynamic polymer network based on the biobased monomer thioctic acid. Through simple and efficient copolymerization, the synthetic performance of the ionic conductive elastomer was effectively adjusted. With its high transparency, good extensibility, and ideal conductivity, the synthetic elastomer was applied in a strain sensor to detect the movements of organisms. Due to its dynamic disulfide bonds and various noncovalent interactions, the synthetic ionic conductive elastomer exhibited an intrinsic self-healing ability, a desirable recyclability, and certain degradability. This research provides a new perspective and method for coordinating synthetic efficiency, multilevel structures, and overall performance of smart materials for soft electronic devices. [ABSTRACT FROM AUTHOR]

By doping different concentrations of Mg2+ at Ni site, the (00l)‐oriented La2MgxNi1‐xMnO6 (abbreviated as LMxNMO, x = 0, 0.1, 0.2, 0.3, 0.4) double‐perovskite thin films were epitaxially grown by pulsed laser deposition. The substitutional effect of Mg2+ on the structural and magnetic properties of the films is comprehensively investigated. It is found that with the increase of Mg‐doping concentration, the in‐plane and out‐of‐plane lattice constants as well as the cell volume of the LMxNMO thin films increase, which could be ascribed to the radius difference between Mg2+ and Ni2+/Ni3+ ions, resulting in the in‐plane compressive stress in LMxNMO films. When the Mg‐doping concentration is small (x ≤ 0.1), the doped Mg2+ tends to substitute Ni3+, which restrains the intensity of antiferromagnetic interaction between Ni3+‐O‐Mn3+, resulting in the reduced the exchange bias field as well as the increased the saturation magnetization. However, when the Mg‐doping concentration increases to x ≥ 0.2, Mg2+ becomes to mainly replace Ni2+ position, which could inhibit the super‐exchange ferromagnetic interaction between Ni2+‐O‐Mn4+ magnetic paths and thus reduce the saturation magnetization. The enhanced magnetic properties can be obtained in the LM0.1NMO double‐perovskite thin film, with a large saturation magnetization of 492.12 emu/cm3 and a high Curie temperature of 262.7 K. [ABSTRACT FROM AUTHOR]