While drinking water disinfection has effectively prevented waterborne diseases, an unintended consequence is the generation of disinfection byproducts (DBPs). Epidemiological studies have ...consistently observed an association between consumption of chlorinated drinking water with an increased risk of bladder cancer. Out of the >600 DBPs identified, regulations focus on a few classes, such as trihalomethanes (THMs), whose concentrations were hypothesized to correlate with the DBPs driving the toxicity of disinfected waters. However, the DBPs responsible for the bladder cancer association remain unclear. Utilities are switching away from a reliance on chlorination of pristine drinking water supplies to the application of new disinfectant combinations to waters impaired by wastewater effluents and algal blooms. In light of these changes in disinfection practice, this article discusses new approaches being taken by analytical chemists, engineers, toxicologists and epidemiologists to characterize the DBP classes driving disinfected water toxicity, and suggests that DBP exposure should be measured using other DBP classes in addition to THMs.
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IJS, KILJ, NUK, PNG, UL, UM
Solar-induced chlorophyll fluorescence (SIF) brings major advancements in measuring terrestrial photosynthesis. Several recent studies have evaluated the potential of SIF retrievals from the Orbiting ...Carbon Observatory-2 (OCO-2) in estimating gross primary productivity (GPP) based on GPP data from eddy covariance (EC) flux towers. However, the spatially and temporally sparse nature of OCO-2 data makes it challenging to use these data for many applications from the ecosystem to the global scale. Here, we developed a new global ‘OCO-2’ SIF data set (GOSIF) with high spatial and temporal resolutions (i.e., 0.05°, 8-day) over the period 2000–2017 based on a data-driven approach. The predictive SIF model was developed based on discrete OCO-2 SIF soundings, remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological reanalysis data. Our model performed well in estimating SIF (R2 = 0.79, root mean squared error (RMSE) = 0.07 W m−2 μm−1 sr−1). The model was then used to estimate SIF for each 0.05° × 0.05° grid cell and each 8-day interval for the study period. The resulting GOSIF product has reasonable seasonal cycles, and captures the similar seasonality as both the coarse-resolution OCO-2 SIF (1°), directly aggregated from the discrete OCO-2 soundings, and tower-based GPP. Our SIF estimates are highly correlated with GPP from 91 EC flux sites (R2 = 0.73, p < 0.001). They capture the expected spatial and temporal patterns and also have remarkable ability to highlight the crop areas with the highest daily productivity across the globe. Our product also allows us to examine the long-term trends in SIF globally. Compared with the coarse-resolution SIF that was directly aggregated from OCO-2 soundings, GOSIF has finer spatial resolution, globally continuous coverage, and a much longer record. Our GOSIF product is valuable for assessing terrestrial photosynthesis and ecosystem function, and benchmarking terrestrial biosphere and Earth system models.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Alzheimer's disease is characterized by sustained neuroinflammation leading to memory loss and cognitive decline. The past decade has witnessed tremendous efforts in Alzheimer's disease research; ...however, no effective treatment is available to prevent disease progression. An increasing body of evidence suggests that neuroinflammation plays an important role in Alzheimer's disease pathogenesis, alongside the classical pathological hallmarks such as misfolded and aggregated proteins (e.g., amyloid-beta and tau). Firstly, this review summarized the clinical and pathological characteristics of Alzheimer's disease. Secondly, we outlined key aspects of glial cell-associated inflammation in Alzheimer's disease pathogenesis and provided the latest evidence on the roles of microglia and astrocytes in Alzheimer's disease pathology. Then, we revealed the double-edged nature of inflammatory cytokines and inflammasomes in Alzheimer's disease. In addition, the potential therapeutic roles of innate immunity and neuroinflammation for Alzheimer's disease were also discussed through these mechanisms. In the final section, the remaining key problems according to the current research status were discussed.
Accurately quantifying gross primary production (GPP) globally is critical for assessing plant productivity, carbon balance, and carbon-climate feedbacks, while current GPP estimates exhibit ...substantial uncertainty. Solar-induced chlorophyll fluorescence (SIF) observed by the Orbiting Carbon Observatory-2 (OCO-2) has offered unprecedented opportunities for monitoring land photosynthesis, while its sparse coverage remains a bottleneck for mapping finer-resolution GPP globally. Here, we used the global, OCO-2-based SIF product (GOSIF) and linear relationships between SIF and GPP to map GPP globally at a 0.05° spatial resolution and 8-day time step for the period from 2000 to 2017. To account for the uncertainty of GPP estimates resulting from the SIF-GPP relationship, we used a total of eight SIF-GPP relationships with different forms (universal and biome-specific, with and without intercept) at both site and grid cell levels to estimate GPP. Our results showed that all of the eight SIF-GPP relationships performed well in estimating GPP globally. The ensemble mean 8-day GPP was generally highly correlated with flux tower GPP for 91 eddy covariance flux sites across the globe (R2 = 0.74, Root Mean Square Error = 1.92 g C m−2 d−1). Our fine-resolution GPP estimates showed reasonable spatial and seasonal variations across the globe and fully captured both seasonal cycles and spatial patterns present in our coarse-resolution (1°) GPP estimates based on coarse-resolution SIF data directly aggregated from discrete OCO-2 soundings. SIF-GPP relationships with different forms could lead to significant differences in annual GPP particularly in the tropics. Our ensemble global annual GPP estimate (135.5 ± 8.8 Pg C yr−1) is between the median estimate of non-process based methods and the median estimate of process-based models. Our GPP estimates showed interannual variability in many regions and exhibited increasing trends in many parts of the globe particularly in the Northern Hemisphere. With the availability of high-quality, gridded SIF observations from space (e.g., TROPOMI, FLEX), our novel approach does not rely on any other input data (e.g., climate data, soil properties) and therefore can map GPP solely based on satellite SIF observations and potentially lead to more accurate GPP estimates at regional to global scales. The use of a universal SIF-GPP relationship versus biome-specific relationships can also avoid the uncertainty associated with land cover maps. Our novel, independent GPP product (GOSIF GPP), freely available at our data repository, will be valuable for studying photosynthesis, carbon cycle, agricultural production, and ecosystem responses to climate change and disturbances, informing ecosystem management, and benchmarking terrestrial biosphere and Earth system models.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Baicalin, which is isolated from Radix Scutellariae, possesses strong biological activities including an anti-inflammation property. Recent studies have shown that the anti-inflammatory effect of ...baicalin is linked to toll-like receptor 4 (TLR4), which participates in pathological changes of central nervous system diseases such as depression. In this study, we explored whether baicalin could produce antidepressant effects via regulation of TLR4 signaling in mice and attempted to elucidate the underlying mechanisms.
A chronic unpredictable mild stress (CUMS) mice model was performed to explore whether baicalin could produce antidepressant effects via the inhibition of neuroinflammation. To clarify the role of TLR4 in the anti-neuroinflammatory efficacy of baicalin, a lipopolysaccharide (LPS) was employed in mice to specially activate TLR4 and the behavioral changes were determined. Furthermore, we used LY294002 to examine the molecular mechanisms of baicalin in regulating the expression of TLR4 in vivo and in vitro using western blot, ELISA kits, and immunostaining. In the in vitro tests, the BV2 microglia cell lines and primary microglia cultures were pretreated with baicalin and LY292002 for 1 h and then stimulated 24 h with LPS. The primary microglial cells were transfected with the forkhead transcription factor forkhead box protein O 1 (FoxO1)-specific siRNA for 5 h and then co-stimulated with baicalin and LPS to investigate whether FoxO1 participated in the effect of baicalin on TLR4 expression.
The administration of baicalin (especially 60 mg/kg) dramatically ameliorated CUMS-induced depressive-like symptoms; substantially decreased the levels of interleukin-1 beta (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor alpha (TNF-α) in the hippocampus; and significantly decreased the expression of TLR4. The activation of TLR4 by the LPS triggered neuroinflammation and evoked depressive-like behaviors in mice, which were also alleviated by the treatment with baicalin (60 mg/kg). Furthermore, the application of baicalin significantly increased the phosphorylation of phosphatidylinositol 3-kinase (PI3K), protein kinase B (AKT), and FoxO1. The application of baicalin also promoted FoxO1 nuclear exclusion and contributed to the inhibition of the FoxO1 transactivation potential, which led to the downregulation of the expression of TLR4 in CUMS mice or LPS-treated BV2 cells and primary microglia cells. However, prophylactic treatment of LY294002 abolished the above effects of baicalin. In addition, we found that FoxO1 played a vital role in baicalin by regulating the TLR4 and TLR4-mediating neuroinflammation triggered by the LPS via knocking down the expression of FoxO1 in the primary microglia.
Collectively, these results demonstrate that baicalin ameliorated neuroinflammation-induced depressive-like behaviors through the inhibition of TLR4 expression via the PI3K/AKT/FoxO1 pathway.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Mafic–ultramafic intrusions comagmatic with Proterozoic massif-type anorthosites can provide insights into the parental magma from which large volumes of hyper-feldspathic rocks are produced. Recent ...deep drilling has unveiled a large olivine–Ti-magnetite-rich layered intrusion (named Dawusunangou) beneath the Damiao massif-type anorthosite complex in the North China Craton. The layered intrusion is composed of alternating olivine–Ti-magnetite-rich dark layers and plagioclase-rich light layers (ca. 35–80% plagioclase), with the latter also containing pod- or lens-shaped pyroxene–Ti-magnetite-rich aggregates. This layered intrusion shows low Mg# and REE patterns similar to the overlying Damiao anorthosite complex. Baddeleyite Pb–Pb geochronology yielded indistinguishable crystallization ages of ca. 1735 Ma for both the Dawusunangou layered intrusion and the Damiao anorthosite complex, suggesting coeval emplacement. Using the average bulk compositions of the two intrusions, mass balance calculations assuming 30–40% Dawusunangou and 70–60% Damiao would give a composition similar to high-Al basaltic magma. Collectively, these features indicate that the Dawusunangou layered intrusion represents the mafic residues after the segregation of the Damiao anorthosites from high-Al basaltic parental magma. A short-lived magma chamber is thought to have supplied the two intrusions. In situ crystallization with variable nucleation rates for plagioclase combined with the mafic minerals crystallizing in equilibrium proportions resulted in the formation of repeated dark and light layers of the Dawusunangou layered intrusion. The two intrusions are interpreted to have formed by multiple magma injections, instead of continuous differentiation of one melt. The parental magma was derived from a depleted mantle source with significant crustal contribution during magma evolution. The large Nd–Hf isotopic variations suggest contamination by Paleoarchean to Neoarchean crust.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, SIK, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Artificial synapses can boost neuromorphic computing to overcome the inherent limitations of von Neumann architecture. As a promising memristor candidate, ferroelectric tunnel junctions (FTJ) enable ...the authors to successfully emulate spike‐timing‐dependent synapses. However, the nonlinear and asymmetric synaptic weight update under repeated presynaptic stimulation hampers neuromorphic computing by favoring the runaway of synaptic weights during learning. Here, the authors demonstrate an FTJ whose conductivity varies linearly and symmetrically by judiciously combining ferroelectric domain switching and oxygen vacancy migration. The artificial neural network based on this FTJ‐synapse achieves classification accuracy of 96.7% during supervised learning, which is the closest to the maximum theoretical value of 98% achieved to date. This artificial synapse also demonstrates stable unsupervised learning in a noisy environment for its well‐balanced spike‐timing‐dependent plasticity response. The novel concept of controlling ionic migration in ferroelectric materials paves the way toward highly reliable and reproducible supervised and unsupervised learning strategies.
By combining ferroelectric domain switching and oxygen vacancy migration, a ferroelectric tunnel junction artificial synapse with intrinsic nonlinearity as low as 0.13–0.17 and symmetric weight updating is developed, which greatly improved the classification accuracy of neural network hardware in supervised learning to 96.7% and enhanced robustness to noise during unsupervised learning.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Critical patients with the coronavirus disease 2019 (COVID-19), even those whose nucleic acid test results had turned negative and those receiving maximal medical support, have been noted to progress ...to irreversible fatal respiratory failure. Lung transplantation (LT) as the sole therapy for end-stage pulmonary fibrosis related to acute respiratory distress syndrome has been considered as the ultimate rescue therapy for these patients.
From February 10 to March 10, 2020, three male patients were urgently assessed and listed for transplantation. After conducting a full ethical review and after obtaining assent from the family of the patients, we performed three LT procedures for COVID-19 patients with illness durations of more than one month and extremely high sequential organ failure assessment scores.
Two of the three recipients survived post-LT and started participating in a rehabilitation program. Pearls of the LT team collaboration and perioperative logistics were summarized and continually improved. The pathological results of the explanted lungs were concordant with the critical clinical manifestation, and provided insight towards better understanding of the disease. Government health affair systems, virology detection tools, and modern communication technology all play key roles towards the survival of the patients and their rehabilitation.
LT can be performed in end-stage patients with respiratory failure due to COVID-19-related pulmonary fibrosis. If confirmed positive-turned-negative virology status without organ dysfunction that could contraindicate LT, LT provided the final option for these patients to avoid certain death, with proper protection of transplant surgeons and medical staffs. By ensuring instant seamless care for both patients and medical teams, the goal of reducing the mortality rate and salvaging the lives of patients with COVID-19 can be attained.
Synthetic DNA motors have great potential to mimic natural protein motors in cells but the operation of synthetic DNA motors in living cells remains challenging and has not been demonstrated. Here we ...report a DNAzyme motor that operates in living cells in response to a specific intracellular target. The whole motor system is constructed on a 20 nm gold nanoparticle (AuNP) decorated with hundreds of substrate strands serving as DNA tracks and dozens of DNAzyme molecules each silenced by a locking strand. Intracellular interaction of a target molecule with the motor system initiates the autonomous walking of the motor on the AuNP. An example DNAzyme motor responsive to a specific microRNA enables amplified detection of the specific microRNA in individual cancer cells. Activated by specific intracellular targets, these self-powered DNAzyme motors will have diverse applications in the control and modulation of biological functions.
Background Deep learning (DL) algorithms are gaining extensive attention for their excellent performance in image recognition tasks. DL models can automatically make a quantitative assessment of ...complex medical image characteristics and achieve increased accuracy in diagnosis with higher efficiency. Purpose To determine the feasibility of using a DL approach to predict clinically negative axillary lymph node metastasis from US images in patients with primary breast cancer. Materials and Methods A data set of US images in patients with primary breast cancer with clinically negative axillary lymph nodes from Tongji Hospital (974 imaging studies from 2016 to 2018, 756 patients) and an independent test set from Hubei Cancer Hospital (81 imaging studies from 2018 to 2019, 78 patients) were collected. Axillary lymph node status was confirmed with pathologic examination. Three different convolutional neural networks (CNNs) of Inception V3, Inception-ResNet V2, and ResNet-101 architectures were trained on 90% of the Tongji Hospital data set and tested on the remaining 10%, as well as on the independent test set. The performance of the models was compared with that of five radiologists. The models' performance was analyzed in terms of accuracy, sensitivity, specificity, receiver operating characteristic curves, areas under the receiver operating characteristic curve (AUCs), and heat maps. Results The best-performing CNN model, Inception V3, achieved an AUC of 0.89 (95% confidence interval CI: 0.83, 0.95) in the prediction of the final clinical diagnosis of axillary lymph node metastasis in the independent test set. The model achieved 85% sensitivity (35 of 41 images; 95% CI: 70%, 94%) and 73% specificity (29 of 40 images; 95% CI: 56%, 85%), and the radiologists achieved 73% sensitivity (30 of 41 images; 95% CI: 57%, 85%;
= .17) and 63% specificity (25 of 40 images; 95% CI: 46%, 77%;
= .34). Conclusion Using US images from patients with primary breast cancer, deep learning models can effectively predict clinically negative axillary lymph node metastasis. Artificial intelligence may provide an early diagnostic strategy for lymph node metastasis in patients with breast cancer with clinically negative lymph nodes. Published under a CC BY 4.0 license.
See also the editorial by Bae in this issue.
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