Effects of artificial management on culm properties of Dendrocalamus brandisii.

The artificial cultivation and management were extensively carried out in Dendrocalamus brandisii stands. However, the influences of artificial management on the anatomical and chemical characteristics of the bamboo culms were unknown. In this study, the fiber morphology, chemical composition and sugar accumulation of the D. brandisii culms with management and without management were compared in order to determine the influences of artificial management on bamboo culms. The results indicated that artificial management had a significant influence on the fiber morphology, resulting in shorter fiber length, larger L/T ratio, and smaller W/Lu value. However, the management not only increased the contents of moisture, ash, SiO2, and extractive, but also increased the holocellulose contents and decreased the lignin contents, as compared to those without management. Moreover, the management significantly increased the endogenous carbohydrates storage in the culms so as to improve the shoot production. The bamboos under management conditions could still be utilized as a raw material for papermaking. This provided a theoretical basis for the artificial management of D. brandisii stands.

Cellulose-reinforced highly stretchable and adhesive eutectogels as efficient sensors.

A cellulose-reinforced eutectogel was constructed by deep eutectic solvent (DES) and cotton linter cellulose. Cellulose was dispersed in the ternary DES consisting of acrylic acid, choline chloride and AlCl3·6H2O. The photoinitiator was then introduced into the system to in situ polymerize acrylic acid monomer to form transparent and ionic conductive eutectogels while keeping all the DES. The crosslinks formed by Al3+ induced ionic bonds and reversible links formed by hydrogen bonds give the eutectogels high stretchability (3200 ± 200 % tensile strain), self-adhesive (52.1 kPa to glass), self-healing and good mechanical strength (670 kPa). The eutectogels were assembled into sensors and epidermal patch electrodes that demonstrated high quality human motion sensing and physiological signal detection (electrocardiogram and electromyography). This work provides a facile way to design flexible electronics for sensing.

Self-Healing and Wide Temperature-Tolerant Cellulose-Based Eutectogels for Reversible Humidity Detection.

A kind of ionic conductive gel (also named eutectogel) is developed from an inorganic salt (ZnCl2)-based deep eutectic solvent (DES). The ternary DES consists of ZnCl2, acrylic acid, and water, and cotton linter cellulose is introduced into the DES system to tailor its mechanical and conductive properties. Enabled by the extensive hydrogen bonds and ion-dipole interactions, the obtained eutectogel displays superior ionic conductivity (0.33 S/m), high stretchability (up to 2050%), large tensile strength (1.82 MPa), and wide temperature tolerance (-40 to 60 °C). In particular, the water-induced coordination interactions can tune the strength of hydrogen/ionic bonds in the eutectogels, imparting them with appealing humidity sensing ability in complex and extreme conditions.

Deep learning and big data mining for Metal-Organic frameworks with high performance for simultaneous desulfurization and carbon capture.

Carbon capture and desulfurization of flue gases are crucial for the achievement of carbon neutrality and sustainable development. In this work, the "one-step" adsorption technology with high-performance metal-organic frameworks (MOFs) was proposed to simultaneously capture the SO2 and CO2. Four machine learning algorithms were used to predict the performance indicators (NCO2+SO2, SCO2+SO2/N2, and TSN) of MOFs, with Multi-Layer Perceptron Regression (MLPR) showing better performance (R2 = 0.93). To address sparse data of MOF chemical descriptors, we introduced the Deep Factorization Machines (DeepFM) model, outperforming MLPR with a higher R2 of 0.95. Then, sensitivity analysis was employed to find that the adsorption heat and porosity were the key factors for SO2 and CO2 capture performance of MOF, while the influence of open alkali metal sites also stood out. Furthermore, we established a kinetic model to batch simulate the breakthrough curves of TOP 1000 MOFs to investigate their dynamic adsorption separation performance for SO2/CO2/N2. The TOP 20 MOFs screened by the dynamic performance highly overlap with those screened by the static performance, with 76 % containing open alkali metal sites. This integrated approach of computational screening, machine learning, and dynamic analysis significantly advances the development of efficient MOF adsorbents for flue gas treatment.

Topological Data Analysis Combined with High-Throughput Computational Screening of Hydrophobic Metal-Organic Frameworks: Application to the Adsorptive Separation of C3 Components.

The shape and topology of pores have significant impacts on the gas storage properties of nanoporous materials. Metal-organic frameworks (MOFs) are ideal materials with which to tailor to the needs of specific applications, due to properties such as their tunable structure and high specific surface area. It is, therefore, particularly important to develop descriptors that accurately identify the topological features of MOF pores. In this work, a topological data analysis method was used to develop a topological descriptor, based on the pore topology, which was combined with the Extreme Gradient Boosting (XGBoost) algorithm to predict the adsorption performance of MOFs for methane/ethane/propane. The final results show that this descriptor can accurately predict the performance of MOFs, and the introduction of the topological descriptor also significantly improves the accuracy of the model, resulting in an increase of up to 17.55% in the R2 value of the model and a decrease of up to 46.1% in the RMSE, compared to commonly used models that are based on the structural descriptor. The results of this study contribute to a deeper understanding of the relationship between the performance and structure of MOFs and provide useful guidelines and strategies for the design of high-performance separation materials.

The hidden curves of risk: a nonlinear model of cumulative risk and school bullying victimization among adolescents with autism spectrum disorder.

BACKGROUND: School bullying victimization (SBV) occurs more frequently in students with autism spectrum disorder (ASD) in general education than in special classes, and there is a cumulative risk effect on SBV exposure among young people with ASD reported by their parents and teachers. However, SBV is a personal experience, the predictive patterns of cumulative risk on SBV reported by themselves and its psychological mechanism remain unclear. This study aims to explore the relationship between cumulative risk and SBV based on self-report, and to test whether internalizing problems mediates this relationship among adolescents with ASD placed in regular classes. METHODS: This study used data from the Taiwan Special Needs Education Longitudinal Study (SNELS) in 2011. The analysis included 508 adolescents with ASD who were in regular classes across Taiwan. The primary variables under study were the quality of friendship interactions, teacher-student relationship, school connection, perceived stigma, the impact caused by the disabilities, internalizing problem, and whether the participants had experienced SBV over the past semester, while control variables were adaptability and social-emotional skills. Established risk factors were summed to form a cumulative risk score. RESULTS: The cumulative risk was positively associated with SBV. The relationship was characterized by the nonlinear pattern of the quadratic function (negative acceleration model) between cumulative risk and SBV. Internalizing problem played a partial mediating role in the effect of cumulative risk on SBV. CONCLUSIONS: Intervention measures to reduce SBV should include the strategies to reduce the number of risks to which adolescents with ASD in regular classes are exposed, comprehensive prevention targeting each risk factor is needed specially when the number of risks is one or two, and more attention needs to be given to their internalizing problem in various ways.

Influence of flowering on the anatomical structure, chemical components and carbohydrate metabolism of Bambusa tuldoides culms at different ages.

Bamboo forests, which have come to occupy large areas in recent years, naturally undergo the process of blooming. However, bamboo culms and rhizomes degenerate after the plants bloom, resulting in widespread loss of raw materials. Systematic research on the properties and physiology of bamboo culms after flowering is lacking, and whether flowering bamboo culms could be used as raw materials in industry is unclear. In this paper, we compared and measured the fiber morphology, chemical components, and sugar metabolism indexes of non-flowering and flowering Bambusa tuldoides culms at different ages. The results showed that the fibers in the middle internodes of both non-flowering and flowering B. tuldoides culms had the longest length. The fibers completed their elongation within 1 year, but the fiber walls were continually deposited with age. The levels of the chemical components in the nonflowering culms also continually increased with age. The nonstructural carbohydrate (NSC) content and sugar metabolism indexes showed the highest levels in the 2-year culms and then declined in the 3-year culms. Compared to young culms that had not yet flowered, the 3-month-old and 1-year-old flowering culms had a significant decrease in the fiber length and tangential diameter, and their holocellulose and lignin levels also decreased, while the levels of ash, SiO2, 1% NaOH extractives, and benzene-ethanol extractives increased. A correlation analysis showed that sugar catabolism was accelerated in the flowering cluster, which could lead to "starvation death" in bamboo and which had a significant negative impact on the anatomical and chemical properties of the bamboo culms. Generally, the flowering bamboo culms had shorter fibers, higher levels of extractives and ash, and lower holocellulose content, which indicated that bamboo flowering has an adverse effect on the application of such components in the production of pulp, in papermaking, and in other processing and utilization activities. This study revealed the physiological changes in flowering B. tuldoides culms and provided a theoretical basis to inform the utilization of culms in this species.

Overwintering performance of bamboo leaves, and establishment of mathematical model for the distribution and introduction prediction of bamboos.

Bamboo has great economic values and is used extensively in many industries, and their natural distribution range was divided into 12 zones in China according to the temperature of their geographical distribution in previous works. Different bamboo species had significantly different abilities in low-temperature tolerance, which need to be considered carefully during ex-situ introduction. In this paper, we observed and evaluated the low-temperature damage of 19 bamboo species in winter, and measured the physiological changes of bamboo leaves. A total of 3060 leaf samples were obtained from 102 core collections in 34 bamboo species from the 5 regions of Chinese mainland for anatomical comparison, in order to screen out the key anatomical indicators related to their low-temperature tolerance and to establish a mathematical prediction model for bamboo introduction. The results showed that the low-temperature resistance of clustered bamboos was generally lower than that of the scattered bamboos. The decreased temperature led to the constant decrease of net photosynthetic rate and transpiration rate, but the increase of soluble sugar content in all bamboo species. There was no dormancy for all bamboo species in winter. The temperate bamboos showed lower photosynthesis as compared to tropical bamboos in winter. The leaf shape of bamboos was closely related to their distribution. A total of 13 leaf indicators were screened and more suitable to estimate the low-temperature tolerant abilities of bamboos and to predict their distribution. The MNLR (multiple nonlinear regression) mathematical model showed the highest fitting degree and the optimal prediction ability in the potential northernmost introduction range of bamboos. This study lay a foundation for bamboo introduction, and could also reduce the economic losses caused by the wrong introduction.

The mediating effect of job satisfaction and emotional exhaustion on the relationship between psychological empowerment and turnover intention among Chinese nurses during the COVID-19 pandemic: a cross-sectional study.

BACKGROUND: Turnover intention occurs frequently in nurses and psychological empowerment has been shown to be major factors that influence turnover intention. However, little is known about the driving force behind turnover intention among nurses in China during the COVID-19 pandemic. OBJECTIVES: To investigate the mediating role of job satisfaction and emotional exhaustion on the association between psychological empowerment and turnover intention among Chinese nurses during the COVID-19 pandemic. METHODS: A cross-sectional design was conducted in China. A total of 507 nurses completed scales of psychological empowerment, job satisfaction, emotional exhaustion and turnover intention anonymously. Descriptive analysis, Pearson's correlation analysis in SPSS 23.0 and structural equation modeling (SEM) by Mplus 7.4 RESULTS: Psychological empowerment had a significantly effect on turnover intention through three significantly indirect pathways: (1) through job satisfaction (B = -0.14, SE = .03, 95% CI = [-.19, -.09]). (2) through emotional exhaustion (B = -0.07, SE = .02, 95% CI = [-.11, -.03]). (3) through the chain mediating effect of "job satisfaction → emotional exhaustion" (B = -0.12, SE = .02, 95% CI = [-.16, -.09]). CONCLUSIONS: Intervention measures to reduce the incidence of turnover intention of nurses should include the evaluations of work demands and emotional exhaustion of nurses and organization's management strategies to promote their psychological empowerment and job satisfaction.

Interpretable Machine-Learning and Big Data Mining to Predict Gas Diffusivity in Metal-Organic Frameworks.

For gas separation and catalysis by metal-organic frameworks (MOFs), gas diffusion has a substantial impact on the process' overall rate, so it is necessary to determine the molecular diffusion behavior within the MOFs. In this study, an interpretable machine learing (ML) model, light gradient boosting machine (LGBM), is trained to predict the molecular diffusivity and selectivity of 9 gases (Kr, Xe, CH4 , N2 , H2 S, O2 , CO2 , H2 , and He). For these 9 gases, LGBM displays high accuracy (average R2 = 0.962) and superior extrapolation for the diffusivity of C2 H6 . And this model calculation is five orders of magnitude faster than molecular dynamics (MD) simulations. Subsequently, using the trained LGBM model, an interactive desktop application is developed that can help researchers quickly and accurately calculate the diffusion of molecules in porous crystal materials. Finally, the authors find the difference in the molecular polarizability (ΔPol) is the key factor governing the diffusion selectivity by combining the trained LGBM model with the Shapley additive explanation (SHAP). By the calculation of interpretable ML, the optimal MOFs are selected for separating binary gas mixtures and CO2 methanation. This work provides a new direction for exploring the structure-property relationships of MOFs and realizing the rapid calculation of molecular diffusivity.

Facile fabrication of strong and conductive cellulose hydrogels with wide temperature tolerance for flexible sensors.

Cellulose-based ionic conductive hydrogels (ICHs) have found extensive applications in flexible electronics and multifunctional sensors. However, simultaneous realization of sufficient conductivity, superior mechanical property and extreme environment tolerance for ICHs remains to be a huge challenge. In this work, a facile one-pot approach was developed to fabricate ICHs by directly dissolving cotton linter cellulose and polyvinyl alcohol (PVA) in a concentrated ZnCl2 solution. By regulating the content of PVA in ICHs, the optimal hydrogel (Gel-5) exhibits a tensile strength of 0.30 MPa, a compressive strength of 2.05 MPa and a conductivity of 8.16 S m-1. Moreover, the resulting dual-network ICHs present high transparency, good thermal reversibility and desirable ionic conductivity. Due to the high concentration of inorganic salts in the porous dual-network structure, the ICH presents good anti-drying and anti-freezing (as low as -90 °C) properties. Such hydrogel can be assembled into multi-functional sensors for human motion and temperature monitoring, and they demonstrate durable sensitivity, cycling stability in a wide operating temperature. This work will shed light on the design of cellulose-based hydrogels with good ionic conductivity and mechanical performance under extreme conditions.

Runoff Estimation of Jiulong River Based on Acoustic Doppler Current Profiler Online Monitoring Data and Its Implication for Pollutant Flux Estimation.

The runoff of the Jiulong River (JLR) is a key parameter that affects the estimation of pollutant flux into Xiamen Bay (XMB). The precise runoff estimation of the JLR can be used to determine the accuracy of the pollutant flux estimation flowing into XMB. In this study, to analyze the hydrological dynamic characteristics and identify the correlation between fixed-site real-time ocean current observations and cross-sectional navigation flow observations, we conducted six navigation observations on two cross-sections of the JLR estuary during the spring tide and neap tide in the normal season, wet season, and dry season in 2020. Simultaneously, we measured hydrological observation data by a fixed-site buoy located in the JLR estuary and collected runoff data that were measured upstream of the JLR. The results showed that the average correlation coefficient between the average velocity of the fixed-point buoy and average velocity of the section was more than 0.90, higher than expected, the minimum average deviation was 4%, and the minimum sample standard error was 5.7%, which was a good result. In this study, we constructed a model for estimating the runoff of the JLR into the sea. The findings demonstrated that Acoustic Doppler Current Profiler (ADCP) online monitoring data were useful to estimate runoff of the JLR with high accuracy, could promote the accuracy of estimated pollutant flux of the JLR's discharge into XMB, and could provide more scientific and reliable basic data for future load flux estimation research.

Dexamethasone-induced hyperglycaemia in COVID-19: Glycaemic profile in patients without diabetes and factors associated with hyperglycaemia.

AIMS: To evaluate glycaemic profiles of COVID-19 patients without diabetes receiving dexamethasone and determine factors associated with hyperglycaemia. METHODS: All subjects without pre-existing diabetes receiving dexamethasone 6 mg for COVID-19 in a non-critical care setting were identified. Glucose profiles were obtained from capillary blood glucose (BG). Univariate and multivariate analyses were performed to identify factors associated with dexamethasone-induced hyperglycaemia (BG ≥ 10 mmol/L). RESULTS: Of 254 subjects, 129 (50.8%) were male with age 51.1 ± 18.2 years and weight 89.7 ± 26.3 kg. Hyperglycaemia post-dexamethasone occurred in 121 (47.6%). Glucose excursions began within three hours (6.8 ± 1.4 mmol/L pre-dexamethasone vs 8.7 ± 2.4 mmol/L at ≤ 3 h, p < 0.001) and peaked at 7-9 h (10.5 ± 2.3 mmol/L, p < 0.001 vs pre-dexamethasone). BGs post-intravenous were higher than post-oral administration for the initial six hours. Hyperglycaemic subjects were older (57.8 ± 17.5 years vs 45.0 ± 16.6 years, p < 0.001), had higher initial glucose (6.3 ± 1.0 vs 5.9 ± 0.9 mmol/L, p = 0.004), higher HbA1c (5.8 ± 0.3% [40 ± 3.5 mmol/mol] vs 5.5 ± 0.4% [37 ± 4.1 mmol/mol], p < 0.001) higher C-reactive protein (CRP) (100 ± 68 vs 83 ± 58 mg/L, p = 0.026), and lower eGFR (79 ± 17 vs 84 ± 16 mL/min/1.73 m2, p = 0.045). Mortality was greater in the hyperglycaemia group (9/121 [7.4%] vs 2/133 [1.5%], p = 0.02). Age, HbA1c and CRP were independently associated with hyperglycaemia. CONCLUSIONS: Half of subjects without diabetes experienced hyperglycaemia post-dexamethasone for COVID-19, peak occurring after 7-9 h. Age, HbA1c and CRP were associated with hyperglycaemia.

Meta-Analysis of the Relationship between the Prognosis of Acute Cerebral Infarction Intravenous Lysis and Cerebral Microbleeds Based on Intelligent Medical Care.

The accelerated pace of life leads to people's unhealthy living habits such as irregular diet, irregular work and rest, and fatigued work. The incidence of acute cerebral infarction (ACI) is increasing year by year. Intravenous thrombolysis is the best solution for clinical treatment of ACI, but intravenous thrombolysis increases the risk of cerebral microbleeds and even seriously damages the brain of patients. It is crucial to analyze the relationship between intravenous thrombolysis of ACI and cerebral microbleeds. Using intelligent medical methods such as BP neural network (BPNN), meta-analysis was carried out on the prognosis of ACI intravenous thrombolysis and cerebral microbleeds, and the basic data indicators, living habits indicators, and ACI intravenous thrombolysis indicators of ACI patients were analyzed. The experimental results showed that the odds ratios (OR) of systolic blood pressure before ACI intravenous thrombolysis, blood glucose concentration after ACI intravenous thrombolysis, diastolic blood pressure before ACI intravenous thrombolysis, and diastolic blood pressure after ACI intravenous thrombolysis on cerebral microbleeds after ACI intravenous thrombolysis were 0.97, 0.44, 0.13, and 0.07, respectively. Long-term intravenous thrombolysis with ACI, high systolic blood pressure after NIHSS thrombolysis with high scores, and blood glucose concentration before thrombolysis had OR >1, which were risk factors for cerebral microbleeds after intravenous thrombolysis with ACI. Therefore, paying attention to the risk factors of cerebral microbleeds during ACI intravenous thrombolysis can effectively reduce cerebral microbleeds after ACI intravenous thrombolysis and improve the treatment efficiency of ACI patients.

Thyrotropinoma with silent somatotroph and lactotroph adenoma during pregnancy.

Summary: Thyrotropinomas are an uncommon cause of hyperthyroidism and are exceedingly rarely identified during pregnancy, with limited evidence to guide management. Most commonly they present as macroadenomas and may cause symptoms of mass effect including headache, visual field defects and hypopituitarism. We present a case of a 35-year-old woman investigated for headaches in whom a 13 mm thyrotropinoma was found. In the lead-up to planned trans-sphenoidal surgery (TSS), she spontaneously conceived and surgery was deferred, as was pharmacotherapy, at her request. The patient was closely monitored through her pregnancy by a multi-disciplinary team and delivered without complication. Pituitary surgery was performed 6 months post-partum. Isolated secondary hypothyroidism was diagnosed postoperatively and replacement thyroxine was commenced. Histopathology showed a double lesion with predominant pituitary transcription factor-1 positive, steroidogenic factor negative plurihormonal adenoma and co-existent mixed thyroid-stimulating hormone, growth hormone, lactotroph and follicle-stimulating hormone staining with a Ki-67 of 1%. This case demonstrates a conservative approach to thyrotropinoma in pregnancy with a successful outcome. This highlights the need to consider the timing of intervention with careful consideration of risks to mother and fetus. Learning points: Thyrotropinomas are a rare cause of secondary hyperthyroidism. Patients may present with hyperthyroidism or symptoms of mass effect, including headaches or visual disturbance. Thyrotropinoma in pregnancy presents a number of pituitary-related risks including pituitary apoplexy and compression of local structures. Hyperthyroidism in pregnancy raises the risk of complications including spontaneous abortion, preeclampsia, low birthweight and premature labour. Timing of medical and surgical therapies must be carefully considered. A conservative approach requires careful monitoring in case emergent intervention is required.

Mechanistic Investigation of Enhanced Catalytic Selectivity toward Alcohol Oxidation with Ce Oxysulfate Clusters.

Ceria-based materials have been highly desired in photocatalytic reactions due to their redox properties and strong oxygen storage and transfer ability. Herein, we report the structures of one CeCe70 oxysulfate cluster and four MCe70 clusters (M = Cu, Ni, Co, and Fe) with the same Ce70 core. As noted, single-crystal X-ray diffraction confirmed the structures of CeCe70 and the MCe70 series, while Raman spectroscopy indicated an increase in oxygen defects upon the introduction of Cu and Fe ions. The clusters catalyzed the oxidation of 4-methoxybenzyl alcohol under ultraviolet light. CuCe70 and FeCe70 exhibited enhanced reactivity compared to CeCe70 and improved aldehyde selectivity compared to control experiments. In comparison with their homogeneous congeners, the CeCe70/MCe70 clusters altered the location of radical generation from the bulk solution to the clusters' surfaces. Mechanistic studies highlight the role of oxygen defects and specific transition metal introduction for efficient photocatalysis. The mechanistic pathway in this study provides insight into how to select or design a highly selective catalyst for photocatalysis.

Bisphosphonate Drug Holidays: Evidence From Clinical Trials and Real-World Studies.

Bisphosphonates (BPs) are commonly used in the treatment of osteoporosis and are effective in the prevention of fragility fracture. Long-term use has been associated with the development of atypical femur fractures (AFFs) and osteonecrosis of the jaw (ONJ). Drug holidays seek to reduce the risk of insufficiency fractures (AFFs) while maintaining durable effects of long-term treatment in the prevention of fragility fracture. Guidelines suggest that BP drug holidays be considered after 3 to 5 years. However individual factors impacting this decision and outcomes are unclear. This review examines key factors in the planning of a safe BP drug holiday and surrogate markers of fracture risk in patients discontinuing treatment. Fifteen randomized control trials and 19 real-world studies were included, including nationwide prospective studies from several countries. Increases in bone turnover markers (BTMs) and reductions in bone mineral density (BMD) were generally observed during BP drug holidays. Resurgent bone turnover was problematic in high-risk patients in whom fractures recurred as early as 12 months following a drug holiday. Risk factors for holiday-related fractures included older age, low hip BMD, underweight, low medication adherence, and prevalent/incident fractures. Zoledronic acid conferred the most durable reduction in fractures, particularly after six annual infusions. Five years of alendronate was insufficient in preventing vertebral fractures in high-risk patients embarking on a drug holiday. Relatively faster offset of antiresorptive effect was seen in risedronate users with more frequent fractures than alendronate during a drug holiday. Studies directly counterbalancing effects of long-term treatment on AFF risk versus drug holiday outcomes in the same population were lacking. In the absence of persistently high fracture risk and following a specific treatment duration dependent on the BP used, drug holidays are safe and mitigate the risk of AFF. However, anti-resorptive effects diminish over time; ongoing monitoring and careful planning of BP resumption is necessary. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Catalytic Degradation of Polyethylene Terephthalate Using a Phase-Transitional Zirconium-Based Metal-Organic Framework.

Polyethylene terephthalate (PET) is utilized as one of the most popular consumer plastics worldwide, but difficulties associated with recycling PET have generated a severe environmental crisis with most PET ending its lifecycle in landfills. We report that zirconium-based metal-organic framework (Zr-MOF) UiO-66 deconstructs waste PET into the building blocks terephthalic acid (TA) and mono-methyl terephthalate (MMT) within 24 hours at 260 °C (total yield of 98 % under 1 atm H2 and 81 % under 1 atm Ar). Extensive structural characterization studies reveal that during the degradation process, UiO-66 undergoes an intriguing transformation into MIL-140A, which is another Zr-MOF that shows good catalytic activity toward PET degradation under similar reaction conditions. These results illustrate the diversity of applications for Zr-MOFs and establish MOFs as a new class of polymer degradation catalysts with the potential to address long-standing challenges associated with plastic waste.

Polyacetylenes from Codonopsis lanceolata Root Induced Apoptosis of Human Lung Adenocarcinoma Cells and Improved Lung Dysbiosis.

Codonopsis lanceolata is a perennial smelly herbaceous plant and widely employed for the treatment of various lung cancer and inflammation. However, the anticancer substances in C. lanceolata and their underlying mechanisms had not been well clarified. In this study, six compounds were obtained from the water extracts of C. lanceolata polyacetylenes (CLP) and then identified as syringin, codonopilodiynoside A, lobetyol, isolariciresinol, lobetyolin, and atractylenolide III. Treatment with CLP remarkably suppressed the cell proliferation, colony formation, migration, and invasion of A549 cells. Synergistic effects of lobetyolin and lobetyol were equivalent to the antiproliferative activities of CLP, while other compounds did not have any inhibition on the viabilities of A549 cells. CLP also reduced the expression of Ras, PI3K, p-AKT, Bcl-2, cyclin D1, and CDK4 but increased the expression of Bax, GSK-3ß, clv-caspase-3, and clv-caspase-9, which could be reversed by the PI3K activator 740YP. Furthermore, CLP retarded the growths of tumor and lung pathogenic bacteria in mice. It demonstrated that lobetyolin and lobetyol were the main antitumor compounds in C. lanceolata. CLP induced cell apoptosis of lung cancer cells via inactivation of the Ras/PI3K/AKT pathway and ameliorated lung dysbiosis, suggesting the therapeutic potentials for treating human lung cancer.

Heterometallic CeIV/ VV Oxo Clusters with Adjustable Catalytic Reactivities.

Heterometallic CeIV/M oxo clusters are underexplored yet and can benefit from synergistic properties from combining cerium and other metal cations to produce efficient redox catalysts. Herein, we designed and synthesized a series of new Ce12V6 oxo clusters with different capping ligands: Ce12V6-SO4, Ce12V6-OTs (OTs: toluenesulfonic acid), and Ce12V6-NBSA (NBSA: nitrobenzenesulfonic acid). Single crystal X-ray diffraction (SCXRD) for all three structures reveals a Ce12V6 cubane core formulated [Ce12(VO)6O24]18+ with cerium on the edges of the cube, vanadyl capping the faces, and sulfate on the corners. While infrared spectroscopy (IR), ultraviolet-visible spectroscopy (UV-vis), electrospray ionization mass spectrometry (ESI-MS), and proton nuclear magnetic resonance (1H NMR) proved the successful coordination of the organic ligands to the Ce12V6 core, liquid phase 51V NMR and small-angle X-ray scattering (SAXS) confirmed the integrity of the clusters in the organic solutions. Furthermore, functionalization of the Ce12V6 core with organic ligands both provides increased solubility in term of homogeneous application and introduces porosity to the assemblies of Ce12V6-OTs and Ce12V6-NBSA in term of heterogeneous application, thus allowing more catalytic sites to be accessible and improving reactivity as compared to the nonporous and less soluble Ce12V6-SO4. Meanwhile, the coordinated ligands also influenced the electronic environment of the catalytic sites, in turn affecting the reactivity of the cluster, which we probed by the selective oxidation of 2-chloroethyl ethyl sulfide (CEES). This work provides a strategy to make full use of the catalytic sites within a class of inorganic sulfate capped clusters via organic ligand introduction.