Conversion of Phosphogypsum into Porous Calcium Silicate Hydrate for the Removal and Recycling of Pb(II) and Cd(II) from Wastewater.

The discharge of lead and cadmium wastewater, along with the pollution caused by phosphogypsum, represents a particularly urgent environmental issue. This study employed a straightforward hydrothermal method to convert phosphogypsum into porous calcium silicate hydrate (P-CSH), which was then used to remove and recover Pb(II) and Cd(II) from wastewater. The adsorption capacities of P-CSH for Pb(II) and Cd(II) were notably high at 989.3 mg/g and 290.3 mg/g, respectively. The adsorption processes adhered to the pseudo-second-order kinetics model and the Langmuir isotherm model. Due to identical adsorption sites on P-CSH for both Pb(II) and Cd(II), competitive interaction occurred when both ions were present simultaneously. Additionally, the adsorption efficacy was minimally impacted by the presence of common coexisting cations in wastewater. The dominant mechanisms for removing Pb(II) and Cd(II) via P-CSH were chemical precipitation and surface complexation. Moreover, the adsorbed heavy metals were efficiently separated and reclaimed from the wastewater through a stepwise desorption process. The primary components of the residue from stepwise desorption were quartz and amorphous SiO2. Following dissolution via pressurized alkaline leaching, this residue could be recycled for synthesizing P-CSH. This research offered a new strategy for the resourceful use of phosphogypsum and heavy metal wastewater.

Interphase Engineering via Solvent Molecule Chemistry for Stable Lithium Metal Batteries.

Lithium metal battery has been regarded as promising next-generation battery system aiming for higher energy density. However, the lithium metal anode suffers severe side-reaction and dendrite issues. Its electrochemical performance is significantly dependant on the electrolyte components and solvation structure. Herein, a series of fluorinated ethers are synthesized with weak-solvation ability owing to the duple steric effect derived from the designed longer carbon chain and methine group. The electrolyte solvation structure rich in AGGs (97.96 %) enables remarkable CE of 99.71 % (25 °C) as well as high CE of 98.56 % even at -20 °C. Moreover, the lithium-sulfur battery exhibits excellent performance in a wide temperature range (-20 to 50 °C) ascribed to the modified interphase rich in LiF/LiO2. Furthermore, the pouch cell delivers superior energy density of 344.4 Wh kg-1 and maintains 80 % capacity retention after 50 cycles. The novel solvent design via molecule chemistry provides alternative strategy to adjust solvation structure and thus favors high-energy density lithium metal batteries.

Bacillus pfraonensis sp. nov., a new strain isolated from a probiotic feed additive with low cytotoxicity and antimicrobial activity.

Probiotic products containing living microorganisms are gaining popularity, increasing the importance of their taxonomic status. A Bacillus-like isolate, 70 b, cultured from a probiotic feed additive, was ambiguity in taxonomic assignment and could be a novel member of Bacillus cereus group. The results of colony and cellular morphology, physiological and biochemical analysis mainly including growth performance, carbon source utilization, and rMLST and MLST were not conclusive. Fatty acids profile and molecular genetic analysis especially ANI, DDH, and core genome SNPs-based phylogenetic tree confirmed 70 b as one novel species of B. cereus group and proposed as Bacillus pfraonensis sp. nov. Comparative genomic analysis revealed the genetic differences between 70 b and other species of B. cereus group. Pseudomycoicidin was identified in 70 b. 70 b was active against multidrug-resistant pathogenic strains MRSA. The findings support 70 b is a novel species with low cytotoxicity and antimicrobial activity, and provides a better understanding of its unique characteristics and probiotic potential, and exploration of bioactive potential.

Deep learning-based polygenic risk analysis for Alzheimer's disease prediction.

BACKGROUND: The polygenic nature of Alzheimer's disease (AD) suggests that multiple variants jointly contribute to disease susceptibility. As an individual's genetic variants are constant throughout life, evaluating the combined effects of multiple disease-associated genetic risks enables reliable AD risk prediction. Because of the complexity of genomic data, current statistical analyses cannot comprehensively capture the polygenic risk of AD, resulting in unsatisfactory disease risk prediction. However, deep learning methods, which capture nonlinearity within high-dimensional genomic data, may enable more accurate disease risk prediction and improve our understanding of AD etiology. Accordingly, we developed deep learning neural network models for modeling AD polygenic risk. METHODS: We constructed neural network models to model AD polygenic risk and compared them with the widely used weighted polygenic risk score and lasso models. We conducted robust linear regression analysis to investigate the relationship between the AD polygenic risk derived from deep learning methods and AD endophenotypes (i.e., plasma biomarkers and individual cognitive performance). We stratified individuals by applying unsupervised clustering to the outputs from the hidden layers of the neural network model. RESULTS: The deep learning models outperform other statistical models for modeling AD risk. Moreover, the polygenic risk derived from the deep learning models enables the identification of disease-associated biological pathways and the stratification of individuals according to distinct pathological mechanisms. CONCLUSION: Our results suggest that deep learning methods are effective for modeling the genetic risks of AD and other diseases, classifying disease risks, and uncovering disease mechanisms.

Polygenic diseases, such as Alzheimer's disease (AD), are those caused by the interplay between multiple genetic risk factors. Statistical models can be used to predict disease risk based on a person's genetic profile. However, there are limitations to existing methods, while emerging methods such as deep learning may improve risk prediction. Deep learning involves computer-based software learning from patterns in data to perform a certain task, e.g. predict disease risk. Here, we test whether deep learning models can help to predict AD risk. Our models not only outperformed existing methods in modeling AD risk, they also allow us to estimate an individual's risk of AD and determine the biological processes that may be involved in AD. With further testing and optimization, deep learning may be a useful tool to help accurately predict risk of AD and other diseases.

High-Current Capable and Non-Flammable Protic Organic Electrolyte for Rechargeable Zn Batteries.

Rechargeable Zinc batteries (RZBs) are considered a potent competitor for next-generation electrochemical devices, due to their multiple advantages. Nevertheless, traditional aqueous electrolytes may cause serious hazards to long-term battery cycling through fast capacity fading and poor Coulombic efficiency (CE), which happens due to complex reaction kinetics in aqueous systems. Herein, we proposed the novel adoption of the protic amide solvent, N-methyl formamide (NMF) as a Zinc battery electrolyte, which possesses a high dielectric constant and high flash point to promote fast kinetics and battery safety simultaneously. Dendrite-free and granular Zn deposition in Zn-NMF electrolyte assures ultra-long lifespan of 2000 h at 2.0 mA cm-2 /2.0 mAh cm-2 , high CE of 99.57 %, wide electrochemical window (≈3.43 V vs. Zn2+ /Zn), and outstanding durability up to 10.0 mAh cm-2 . This work sheds light on the efficient performance of the protic non-aqueous electrolyte, which will open new opportunities to promote safe and energy-dense RZBs.

Empowering Zn Electrode Current Capability Along Interfacial Stability by Optimizing Intrinsic Safe Organic Electrolytes.

Metallic Zn is one of the most promising anodes, but its practical application has been hindered by dendritic growth and serious interfacial reactions in conventional electrolytes. Herein, ionic liquids are adopted to prepare intrinsically safe electrolytes via combining with TEP or TMP solvents. With this synergy effect, the blends of TEP/TMP with an IL fraction of ≈25 wt% are found to be promising electrolytes, with ionic conductivities comparable to those of standard phosphate-based electrolytes while electrochemical stabilities are considerably improved; over 1000 h at 2.0 mA cm-2 and ≈350 h at 5.0 mA cm-2 with a large areal capacity of 10 mAh cm-2 . The use of functionalized IL turns out to be a key factor in enhancing the Zn2+ transport due to the interaction of Zn2+ ions with IL-zincophilic sites resulting in reduced interfacial resistance between the electrodes and electrolyte upon cycling leading to spongy-like highly porous, homogeneous, and dendrite-free zinc as an anode material.

A Novel Filler for Gel Polymer Electrolyte with a High Lithium-Ion Transference Number toward Stable Cycling for Lithium-Metal Anodes in Lithium-Sulfur Batteries.

Although the lithium metal is considered as the most promising anode for high energy density batteries, uncontrolled lithium dendrite growth and continuous side reactions with electrolyte hinder its practical applications for rechargeable batteries. Herein, we prepared a gel polymer electrolyte by synthesizing a novel 250 nm filler (KMgF3), which is greatly beneficial to the formation of a uniformly deposited lithium-metal anode. This is due to the regulation effect of KMgF3 that double the lithium-ion transference number up to 0.63 and adjust the solid electrolyte interphase layer full of dense LiF and flexible polycarbonates, which greatly reduces the side reactions on the lithium-metal surface and inhibits the growth of lithium dendrites. Consequently, the composite gel polymer electrolyte guarantees a stable long cycle performance of more than 1400 h with 1 mA h cm-2 for symmetric cells. Moreover, the composite gel polymer electrolyte demonstrates high compatibility and great promise for rechargeable lithium-sulfur (Li-S) batteries.

A Computationally Efficient Approach to Segmentation of the Aorta and Coronary Arteries Using Deep Learning.

Early detection and diagnosis of coronary artery disease could reduce the risk of developing a heart attack. The coronary arteries are optimally visualised using computed tomography coronary angiography (CTCA) imaging. These images are reviewed by specialist radiologists who evaluate the coronary arteries for potential narrowing. A lack of radiologists in the UK is a constraint to timely diagnosis of coronary artery disease, particularly in the acute accident and emergency department setting. The development of automated methods by which coronary artery narrowing can be identified rapidly and accurately are therefore timely. Such complex computer based tools also need to be sufficiently computationally efficient that they can run on servers typically found in hospital settings, where graphical processing units for example are unavailable. We propose a fully automatic two-dimensional Unet model to segment the aorta and coronary arteries on CTCA images. Two models are trained to segment two regions of interest, (1) the aorta and the coronary arteries or (2) the coronary arteries alone. Our method achieves 91.20% and 88.80% dice similarity coefficient accuracy on regions of interest 1 and 2 respectively. Compared with a semi-automatic segmentation method, our model performs better when segmenting the coronary arteries alone. The performance of the proposed method is comparable to existing published two-dimensional or three-dimensional deep learning models. Importantly, the algorithmic and graphical processing unit memory efficiencies are maintained such that the model can be deployed without requiring graphical processing units, and therefore can be used in a hospital setting.

High Molecular Weight Polyacrylonitrile Precursor for S@pPAN Composite Cathode Materials with High Specific Capacity for Rechargeable Lithium Batteries.

Sulfurized pyrolyzed poly(acrylonitrile) (S@pPAN) demonstrates high sulfur utilization, no polysulfide dissolution, no self-discharge, and extremely stable cycling. Its precursor, PAN, directly determines the performances of cathode materials, including the sulfur content and its utilization for S@pPAN composite materials. Adopting PAN with the molecular weight approaching 550,000 as the precursor, the sulfur content in S@pPAN approaches 55 wt %, and its reversible specific capacity was 901 mAh g-1(composite) at 50 °C with sulfur utilization over 98%. Moreover, it enabled stable cycling and excellent high rate capability with a specific capacity of 645 mAh g-1 at 5 C. These significantly enhanced electrochemical properties are mainly due to the high molecular weight of the PAN precursor, which provides more space to accommodate amorphous sulfur, along with improved interfacial resistance of S@pPAN.

Prospect of Sulfurized Pyrolyzed Poly(acrylonitrile) (S@pPAN) Cathode Materials for Rechargeable Lithium Batteries.

Lithium-sulfur (Li-S) batteries are one of the most promising next-generation batteries owing to their ultra-high theoretical energy density and that sulfur is an abundant resource. During the past 20 years, various sulfur materials have been reported. As a molecular-scale sulfur-composite cathode, sulfurized pyrolyzed poly(acrylonitrile) (S@pPAN) exhibits several competitive advantages in terms of its electrochemical behavior. Although it was first reported in 2002 S@pPAN is currently attracting increasing attention. In this Minireview, we summarize its molecular model and explore the correlation between its structure and its exceptional electrochemical performance. We classify the modification strategies into three types, including material improvement, binder, and electrolyte screening. Several research and development directions are also suggested.

Highly Reversible Lithium-Metal Anode and Lithium-Sulfur Batteries Enabled by an Intrinsic Safe Electrolyte.

Rechargeable lithium-metal batteries have gained significant attention as potential candidates of energy storage systems; however, severe safety issues including flammable electrolyte and dendritic lithium formation hinder their further practical application. In this work, we develop a novel intrinsic flame-retardant electrolyte, which enables a stable and dendrite-free cycling with lithium plating/stripping Coulombic efficiency of up to 99.1% over 500 cycles. Raman spectra indicate that no free molecular solvent exists, and X-ray photoelectron spectroscopy reveals the LiF-rich interphase on the Li-metal anode. When coupled with sulfurized pyrolyzed poly(acrylonitrile) cathode, it shows a benign electrochemical reversibility with the areal capacity of up to 3.41 mAh cm-2 after 70 cycles. To further check its compatibility with sulfur cathode, a higher sulfur content (51.6%) is examined with the areal capacity of 3.92 mAh cm-2 and sulfur utilization of 81.7%. This work provides an alternative for safe and high-performance Li-S batteries via a novel electrolyte strategy.

An Intrinsic Flame-Retardant Organic Electrolyte for Safe Lithium-Sulfur Batteries.

Safety concerns pose a significant challenge for the large-scale employment of lithium-sulfur batteries. Extremely flammable conventional electrolytes and dendritic lithium deposition cause severe safety issues. Now, an intrinsic flame-retardant (IFR) electrolyte is presented consisting of 1.1 m lithium bis(fluorosulfonyl)imide in a solvent mixture of flame-retardant triethyl phosphate and high flashpoint solvent 1,1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoropropyl (1:3, v/v) for safe lithium-sulfur (Li-S) batteries. This electrolyte exhibits favorable flame-retardant properties and high reversibility of the lithium metal anode (Coulombic efficiency >99 %). This IFR electrolyte enables stable lithium plating/stripping behavior with micro-sized and dense-packing lithium deposition at high temperatures. When coupled with a sulfurized pyrolyzed poly(acrylonitrile) cathode, Li-S batteries deliver a high composite capacity (840.1 mAh g-1 ) and high sulfur utilization of 95.6 %.

CXCR7 is not obligatory for CXCL12-CXCR4-induced epithelial-mesenchymal transition in human ovarian cancer.

Although the CXCL12-CXCR4/CXCR7 chemokine axis is demonstrated to play an integral role in tumor progression, the controversy exists and the role of CXCL12-CXCR4/CXCR7 signaling axis in epithelial-mesenchymal transition (EMT) of human ovarian cancer has not been explored. Here, we showed that in ovarian cancer CXCL12 induced EMT phenotypes including the spindle-like cell morphology, podia and stress fiber formation, a decrease in E-cadherin expression, and increases in mesenchymal N-cadherin and vimentin expressions. These effects of CXCL12 could be antagonized by the CXCR4 antagonist AMD3100, but not by the anti-CXCR7 antibody. The expressions of the EMT markers were significantly down-regulated by the CXCR4 siRNA, and up-regulated by the pcDNA3.1/CXCR4 plasmid, whereas not affected by the CXCR7 siRNA. Furthermore, intraperitoneal administration of AMD3100 inhibited tumor dissemination and growth in the nude mice inoculated with ovarian IGROV-1 cells with a concomitant reduction in EMT marker expressions. Collectively, these data suggest that CXCR4, rather than CXCR7, plays a key role in CXCL12-activated EMT phenotypes, and targeting the CXCL12-CXCR4 chemokine axis represents a potential therapeutic strategy to prevent ovarian cancer progression.

Metastatic cancer cells compensate for low energy supplies in hostile microenvironments with bioenergetic adaptation and metabolic reprogramming.

Metastasis accounts for the majority of cancer-related mortalities, and the complex processes of metastasis remain the least understood aspect of cancer biology. Metabolic reprogramming is associated with cancer cell survival and metastasis in a hostile envi-ronment with a limited nutrient supply, such as solid tumors. Little is known regarding the differences of bioenergetic adaptation between primary tumor cells and metastatic tumor cells in unfavorable microenvironments; to clarify these differences, the present study aimed to compare metabolic reprogramming of primary tumor cells and metastatic tumor cells. SW620 metastatic tumor cells exhibited stronger bioenergetic adaptation in unfavorable conditions compared with SW480 primary tumor-derived cells, as determined by the sustained elevation of glycolysis and regulation of the cell cycle. This remarkable glycolytic ability of SW620 cells was associated with high expression levels of hexokinase (HK)1, HK2, glucose transporter type 1 and hypoxia-inducible factor 1α. Compared with SW480 cells, the expression of cell cycle regulatory proteins was effectively inhibited in SW620 cells to sustain cell survival when there was a lack of energy. Furthermore, SW620 cells exhibited a stronger mesenchymal phenotype and stem cell characteristics compared with SW480 cells; CD133 and CD166 were highly expressed in SW620 cells, whereas expression was not detected in SW480 cells. These data may explain why metastatic cancer cells exhibit greater microenvironmental adaptability and survivability; specifically, this may be achieved by upregulating glycolysis, optimizing the cell cycle and reprogramming cell metabolism. The present study may provide a target metabolic pathway for cancer metastasis therapy.

Pharmacokinetic differences of mifepristone between sexes in animals.

Mifepristone (RU486) is developed originally as a contraceptive used by hundreds of millions of women world-wide, and also reported as a safe and long-term psychotic depressant, or as a cancer chemotherapeutic agent used by both sexes. In our preliminary study aimed at developing mifepristone as a cancer metastatic chemopreventive, we coincidentally observed that blood mifepristone concentrations in female rats seem to be higher than those in male ones post administration. To substantiate if the pharmacokinetic differences between sexes exist, we established a fast UPLC-MS/MS method to determine mifepristone concentrations in plasma, and analyzed blood concentrations of mifepristone over time in rats and dogs of both sexes. Mifepristone in plasma or incubation liquid was recovered by liquid-liquid extraction using 1 mL of ethyl acetate. Chromatographic separation was performed on a C18 column at 35 °C, with a gradient elution consisting of methanol and water containing 0.1% (v/v) formic acid at a flow rate of 0.3 mL/min. And pharmacokinetic parameters such as elimination half-life, and mean residence time were calculated by using the non-compartmental pharmacokinetics data analysis software. In this work, administrations of mifepristone to rats and beagle dogs revealed that the plasma concentrations of mifepristone (AUC, Cmax) were significantly higher (P < 0.05) in females than that in males. In vitro liver microsomal incubation experiments showed that the metabolic rate of mifepristone in males was higher than that in females, which was consistent with the results of in vivo experiments. In general, we first found the sex-related differences about pharmacokinetic properties of mifepristone and revealed the metabolism difference of hepatic microsomal enzyme is the main reason.

Mifepristone inhibits ovarian cancer metastasis by intervening in SDF-1/CXCR4 chemokine axis.

SDF-1/CXCR4 signaling axis determines the proliferative potential and site-specific cancer metastasis. Recent studies suggest involvement of the axis and steroidal hormone in ovarian cancer metastasis. Here we hypothesize that mifepristone (RU486), a well-known progesterone-based abortifacient, might interfere this axis and inhibit ovarian cancer metastasis. Mifepristone at concentrations < IC50 inhibited expression of CXCR4 on cell surface of ovarian cancer SKOV-3 and IGROV-1, and reduced expression of the intracellular CXCR4 protein and its related mRNA activated by SDF-1. SDF-1 significantly stimulated proliferation of SKOV-3 and IGROV-1 cells with concomitant increases in intracellular phosphorylation of Akt and ERK. SDF-1 activated cell chemotatic migration and actin polymerization, and up-regulated expression of MMP-2, MMP-9, COX-2, VEGF without influencing the adhesion molecules ICAM-1 and integrins ß1, α1, α3, α5, and α6. The above-mentioned effects of SDF-1 could be antagonized by mifepristone concentration-dependently, and CXCR4 antagonist AMD3100. Mifepristone suppressed the SDF-1-induced migration, invasion and adhesion of the cancer cells to extracellular matrixes. Three-day pretreatment of nude mice with mifepristone (5 and 20 mg/kg/day) followed by a single intraperitoneal IGROV-1 inoculation, along with repeated SDF-1 and mifepristone administrations in turn every other day for 36 days significantly reduced ascitic fluid, metastatic foci, tumor weight and immunoreactivity of CXCR4 in comparison with the SDF-1-treated control. Our results suggest that mifepristone inhibit SDF-1/CXCR4 signaling axis, may have preventive and therapeutic effects on ovarian cancer metastasis.

A Flavonoid Glycoside Compound from Murraya paniculata (L.) Interrupts Metastatic Characteristics of A549 Cells by Regulating STAT3/NF-κB/COX-2 and EGFR Signaling Pathways.

Metastasis remains the leading cause of death from lung carcinoma. It is urgent to find safe and efficient pre-metastasis preventive agents for cancer survivors. We isolated a flavonoid glycoside, hexamethoxy flavanone-o-[rhamnopyranosyl-(1 â†’ 4)-rhamnopyranoside (HMFRR), from the traditional Chinese medicine (TCM) Murraya paniculata (L.) that can effectively inhibit the adhesion, migration, and invasion of lung adenocarcinoma A549 cells in vitro. Molecular and cellular studies demonstrated that HMFRR significantly downregulated the expressions of cell adhesion-related and invasion-related molecules such as integrin ß1, EGFR, COX-2, MMP-2, and MMP-9 proteins. Additionally, HMFRR effectively downregulated the expressions of epithelial-mesenchymal transition (EMT) markers (N-cadherin and vimentin) and upregulated that of E-cadherin. Moreover, these inhibitions were mediated by interrupting STAT3/NF-κB/COX-2 and EGFR/PI3K/AKT signaling pathways. Furthermore, HMFRR counteracted the expressions of cell adhesion molecules (ICAM-1, VCAM-1, and E-selectin) stimulated by interleukin-1ß in human pulmonary microvascular endothelial cells (HPMECs). As a result, HMFRR interrupted the adhesion of A549 cells to HPMECs. Collectively, these results indicate that HMFRR may become a good candidate for cancer metastatic chemopreventive agents by interrupting the STAT3/NF-κB/COX-2 and EGFR signaling pathways.

Metapristone (RU486 derivative) inhibits cell proliferation and migration as melanoma metastatic chemopreventive agent.

Uncontrolled cell proliferation and metastasis are the two well-known manifestations of melanoma. We hypothesized that metapristone, a potential cancer metastatic chemopreventive agent derived from mifepristone (RU486), had a dual function to fight cancer. In the present study, our findings clearly demonstrated that metapristone had modest cytostatic effect in melanoma cells. Metapristone inhibited cell viability and induced both early and late apoptosis in B16F10 and A375 cells in a time- and concentrate-dependent manner. Metapristone-treatment caused the cell arrest at the G0/G1 stage, and the inhibition of colony formation in B16F10 cells. Western blot analysis further revealed that metapristone treatment elicited a decline of Akt and ERK phosphorylation and Bcl-2, and facilitated expression of total P53 and Bax in A375 cells. In addition, cell migration and invasion were significantly suppressed by metapristone through down-regulating the expression of MMP-2, MMP-9, N-cadherin and vimentin, whereas up-regulating E-cadherin expression. Notably, metapristone exhibited anti-metastatic activity in melanoma B16F10 cells in vivo. Our results reveal metapristone, having the dual function of anti-proliferation and anti-migration for melanoma cell lines, may be a useful chemopreventive agent to reduce the risk of melanoma cancer metastasis.

Abortifacient metapristone (RU486 derivative) interrupts CXCL12/CXCR4 axis for ovarian metastatic chemoprevention.

Recent global epidemiological studies revealed the lower ovarian cancer death from long-term use of oral contraceptives. However, the underlying mechanism of action is not clear. Here, we use the abortifacient metapristone (RU486 derivative) to test the hypothesis that the contraceptives might interrupt CXCL12/CXCR4 chemokine axis to inhibit ovarian cancer metastasis. Metapristone at concentrations (