Incident dementia and long-term exposure to constituents of fine particle air pollution: A national cohort study in the United States.

Growing evidence suggests that fine particulate matter (PM2.5) likely increases the risks of dementia, yet little is known about the relative contributions of different constituents. Here, we conducted a nationwide population-based cohort study (2000 to 2017) by integrating the Medicare Chronic Conditions Warehouse database and two independently sourced datasets of high-resolution PM2.5 major chemical composition, including black carbon (BC), organic matter (OM), nitrate (NO3-), sulfate (SO42-), ammonium (NH4+), and soil dust (DUST). To investigate the impact of long-term exposure to PM2.5 constituents on incident all-cause dementia and Alzheimer's disease (AD), hazard ratios for dementia and AD were estimated using Cox proportional hazards models, and penalized splines were used to evaluate potential nonlinear concentration-response (C-R) relationships. Results using two exposure datasets consistently indicated higher rates of incident dementia and AD for an increased exposure to PM2.5 and its major constituents. An interquartile range increase in PM2.5 mass was associated with a 6 to 7% increase in dementia incidence and a 9% increase in AD incidence. For different PM2.5 constituents, associations remained significant for BC, OM, SO42-, and NH4+ for both end points (even after adjustments of other constituents), among which BC and SO42- showed the strongest associations. All constituents had largely linear C-R relationships in the low exposure range, but most tailed off at higher exposure concentrations. Our findings suggest that long-term exposure to PM2.5 is significantly associated with higher rates of incident dementia and AD and that SO42-, BC, and OM related to traffic and fossil fuel combustion might drive the observed associations.

Regulation of metal homoeostasis by two F-group bZIP transcription factors bZIP48 and bZIP50 in rice.

Zinc (Zn) deficiency not only impairs plant growth and development but also has negative effects on human health. Rice (Oryza Sativa L.) is a staple food for over half of the global population, yet the regulation of Zn deficiency response in rice remains largely unknown. In this study, we provide evidence that two F-group bZIP transcription factors, OsbZIP48/50, play a crucial role in Zn deficiency response. Mutations in OsbZIP48/50 result in impaired growth and reduced Zn/Fe/Cu content under Zn deficiency conditions. The N-terminus of OsbZIP48/OsbZIP50 contains two Zn sensor motifs (ZSMs), deletion or mutation of these ZSMs leads to increased nuclear localization. Both OsbZIP48 and OsbZIP50 exhibit transcriptional activation activity, and the upregulation of 1117 genes involved in metal uptake and other processes by Zn deficiency is diminished in the OsbZIP48/50 double mutant. Both OsbZIP48 and OsbZIP50 bind to the promoter of OsZIP10 and activate the ZDRE cis-element. Amino acid substitution mutation of the ZSM domain of OsbZIP48 in OsbZIP50 mutant background increases the content of Zn/Fe/Cu in brown rice seeds and leaves. Therefore, this study demonstrates that OsbZIP48/50 play a crucial role in regulating metal homoeostasis and identifies their downstream genes involved in the Zn deficiency response in rice.

Clinical Characteristics and Molecular Genetic Analysis of a Pedigree with Glanzmann's Thrombasthenia.

Objective: The objective of this study was to investigate the clinical phenotype and genetic etiology of Glanzmann's thrombasthenia in a consanguineous pedigree. Methods: Clinical data and ancillary test results were collected from pedigrees with Glanzmann's thrombasthenia. High-throughput sequencing was used to detect variants in the proband. Candidate variants were verified by Sanger sequencing. Results: Two patients in the pedigree were homozygous for the c.2248C>T (p. Arg750Ter) variant of the ITGB3 gene. The parents and maternal grandmother, who didn't have any recurrent haemorrhage, were found to carry a heterozygous c.2248C>T variant of the ITGB3 gene, which was absent in the aunt and paternal grandmother. Conclusion: The homozygous variant c.2248C>T (p. Arg750Ter) in the ITGB3 gene underlies the disease in this pedigree. This diagnosis will facilitate genetic counselling in this pedigree for better patient management and life guidance.

NFXL1 functions as a transcriptional activator required for thermotolerance at reproductive stage in Arabidopsis.

Plants are highly susceptible to abiotic stresses, particularly heat stress during the reproductive stage. However, the specific molecular mechanisms underlying this sensitivity remain largely unknown. In the current study, we demonstrate that the Nuclear Transcription Factor, X-box Binding Protein 1-Like 1 (NFXL1), directly regulates the expression of DEHYDRATION-RESPONSIVE ELEMENT-BINDING PROTEIN 2A (DREB2A), which is crucial for reproductive thermotolerance in Arabidopsis. NFXL1 is upregulated by heat stress, and its mutation leads to a reduction in silique length (seed number) under heat stress conditions. RNA-Seq analysis reveals that NFXL1 has a global impact on the expression of heat stress responsive genes, including DREB2A, Heat Shock Factor A3 (HSFA3) and Heat Shock Protein 17.6 (HSP17.6) in flower buds. Interestingly, NFXL1 is enriched in the promoter region of DREB2A, but not of either HSFA3 or HSP17.6. Further experiments using electrophoretic mobility shift assay have confirmed that NFXL1 directly binds to the DNA fragment derived from the DREB2A promoter. Moreover, effector-reporter assays have shown that NFXL1 activates the DREB2A promoter. The DREB2A mutants are also heat stress sensitive at the reproductive stage, and DEREB2A is epistatic to NFXL1 in regulating thermotolerance in flower buds. It is known that HSFA3, a direct target of DREB2A, regulates the expression of heat shock proteins genes under heat stress conditions. Thus, our findings establish NFXL1 as a critical upstream regulator of DREB2A in the transcriptional cassette responsible for heat stress responses required for reproductive thermotolerance in Arabidopsis.

National Cohort Study of Long-Term Exposure to PM2.5 Components and Mortality in Medicare American Older Adults.

There is increasing evidence linking long-term fine particulate matter (PM2.5) exposure to negative health effects. However, the relative influence of each component of PM2.5 on health risk is poorly understood. In a cohort study in the contiguous United States between 2000 and 2017, we examined the effect of long-term exposure to PM2.5 main components and all-cause mortality in older adults who had to be at least 65 years old and enrolled in Medicare. We estimated the yearly mean concentrations of six key PM2.5 compounds, including black carbon (BC), organic matter (OM), soil dust (DUST), nitrate (NO3-), sulfate (SO42-), and ammonium (NH4+), using two independently sourced well-validated prediction models. We applied Cox proportional hazard models to evaluate the hazard ratios for mortality and penalized splines for assessing potential nonlinear concentration-response associations. Results suggested that increased exposure to PM2.5 mass and its six main constituents were significantly linked to elevated all-cause mortality. All components showed linear concentration-response relationships in the low exposure concentration ranges. Our research indicates that long-term exposure to PM2.5 mass and its essential compounds are strongly connected to increased mortality risk. Reductions of fossil fuel burning may yield significant air quality and public health benefit.

Decreased GDF9 and BMP15 in follicle fluid and granulosa cells and outcomes of IVF-ET among young patients with low prognosis.

PURPOSE: To analyze the level of growth differentiation factor 9 (GDF9) and bone morphogenetic protein 15 (BMP15) in follicle fluid (FF) and granulosa cells (GCs) derived from young patients with low prognosis for in vitro fertilization and embryo transfer (IVF-ET) treatment. METHODS: A prospective cohort study was carried out by enrolling 52 young patients with low prognosis according to the POSEIDON classification group 3 (low prognosis group) and 51 young patients with normal ovarian reserve (control group). The concentration of the GDF9 and BMP15 proteins in FF was determined by enzyme-linked immunosorbent assay. The mRNA level of the GDF9 and BMP15 in the GCs was measured by quantitative real-time PCR. RESULTS: The concentration of GDF9 (1026.72 ± 159.12 pg/mL vs. 1298.06 ± 185.41 pg/mL) and BMP15 (685.23 ± 143.91 pg/mL vs. 794.37 ± 81.79 pg/mL) in FF and the mRNA level of GDF9 and BMP15 in the GCs and the live birth rate per treatment cycle started (30.77% vs. 50.98%) and oocytes retrieved (4.25 ± 1.91 vs.12.04 ± 4.24) were significantly lower, whereas the canceled cycle rate was significantly higher (9.62% vs. 0) in the low prognosis group compared with the control group (P < 0.05). The expression of GDF9 and BMP15 in the ovary was positively correlated with live birth (P < 0.05). CONCLUSION: The expression of GDF9 and BMP15 in the ovary was decreased in young patients with low prognosis accompanied by a poorer outcome of IVF-ET treatment. TRIAL REGISTRATION: ChiCTR1800016107 (Chinese Clinical Trial Registry), May 11, 2018. ( http://www.chictr.org.cn/edit.aspx?pid=27216&htm=4 ).

Sex hormones and physical function among the Chinese oldest-old and centenarian women.

BACKGROUND: Physical independence is crucial for overall health in the elderly individuals. The life expectancy of women has been shown to be higher than that of men, which is also known as the "male-female health-survival paradox". Sex hormones may be one of the explanations. However, the relationships between sex hormones and physical function remain unclear in the elderly females. This study was designed to explore these relationships among the Chinese oldest-old and centenarian women. METHODS: Data from 1226 women were obtained from the China Hainan Centenarian Cohort Study. Home interviews, physical examinations and blood analyses were conducted using standardized procedures. Variables including age, Han ethnicity, illiteracy, smoker, drinker, estradiol (E2), testosterone (T), follicle-stimulating hormone, and luteinizing hormone were used in the multivariate logistic and linear regression analyses. RESULTS: In all the participants, age [beta (95% confidence interval): - 0.84 (- 0.98, - 0.71)] and E2 levels [beta (95% confidence interval): - 0.22 (- 0.28, - 0.17)] were negatively associated with activities of daily living (ADLs) in the multivariate linear regression analyses (P < 0.05 for all). We also observed significantly negative associations of age [odds ratio (95% confidence interval): 0.90 (0.88, 0.91)] and E2 levels [odds ratio (95% confidence interval): 0.98 (0.98, 0.99)] with physical normality in the multivariate logistic regression analyses (P < 0.05 for all). Age and E2 levels gradually decreased with increases in the ADL quartiles across all the participants (P < 0.05 for all). CONCLUSIONS: This study demonstrated that E2 levels were negatively associated with physical function among the Chinese oldest-old and centenarian women.

[Application of extracorporeal membrane oxygenation in the treatment of persistent pulmonary hypertension of the newborn]. / 体外膜肺氧合技术在持续肺动脉高压新生儿救治中的临床应用.

OBJECTIVES: To study the clinical value of extracorporeal membrane oxygenation (ECMO) in the treatment of persistent pulmonary hypertension of the newborn (PPHN). METHODS: A retrospective analysis was performed on the medical data of 11 neonates with PPHN who were treated with ECMO in the Neonatal Intensive Care Unit of Zhongshan People's Hospital from January 2015 to December 2021, involving the neonates' general information, clinical diagnosis, laboratory results, duration of ECMO treatment, complications during ECMO treatment, length of hospital stay, and outcome. RESULTS: Of the 11 neonates, 10 (91%) had successful weaning from ECMO, and 8 (73%) survived. For the 11 neonates, the mean duration of ECMO treatment was (81±50) hours (range: 26 to 185 hours), the mean duration of ventilator use was (198±105) hours (range: 57 to 392 hours), and the mean length of hospital stay was (22±15) days (range: 2 to 49 days). The oxygenation index and blood lactate level were significantly improved after 24 hours of ECMO treatment among the 11 neonates (P<0.05). Ten neonates had significantly reduced pulmonary artery pressure after 24 hours of ECMO treatment (P<0.05). One neonate had a progressive increase in the pulmonary artery pressure during EMCO treatment, succumbing to death. This neonate was diagnosed with alveolar capillary dysplasia based on the histopathological findings of the lung tissue and whole-exome sequencing results. Among the 11 children, 5 had intracranial hemorrhage, 1 had disseminated intravascular coagulation, 1 had gastric hemorrhage, 2 had pulmonary hemorrhage, 1 had renal insufficiency, and 3 had bleeding at the puncture site during ECMO treatment. CONCLUSIONS: ECMO is effective for the treatment of PPHN, however, the high incidence of complications of ECMO treatment suggests that it is important to carefully assess the indications and timing of ECMO treatment and improve the management of ECMO, which can improve the weaning rate and survival rate.

AI detection of mild COVID-19 pneumonia from chest CT scans.

OBJECTIVES: An artificial intelligence model was adopted to identify mild COVID-19 pneumonia from computed tomography (CT) volumes, and its diagnostic performance was then evaluated. METHODS: In this retrospective multicenter study, an atrous convolution-based deep learning model was established for the computer-assisted diagnosis of mild COVID-19 pneumonia. The dataset included 2087 chest CT exams collected from four hospitals between 1 January 2019 and 31 May 2020. The true positive rate, true negative rate, receiver operating characteristic curve, area under the curve (AUC) and convolutional feature map were used to evaluate the model. RESULTS: The proposed deep learning model was trained on 1538 patients and tested on an independent testing cohort of 549 patients. The overall sensitivity was 91.5% (195/213; p < 0.001, 95% CI: 89.2-93.9%), the overall specificity was 90.5% (304/336; p < 0.001, 95% CI: 88.0-92.9%) and the general AUC value was 0.955 (p < 0.001). CONCLUSIONS: A deep learning model can accurately detect COVID-19 and serve as an important supplement to the COVID-19 reverse transcription-polymerase chain reaction (RT-PCR) test. KEY POINTS: • The implementation of a deep learning model to identify mild COVID-19 pneumonia was confirmed to be effective and feasible. • The strategy of using a binary code instead of the region of interest label to identify mild COVID-19 pneumonia was verified. • This AI model can assist in the early screening of COVID-19 without interfering with normal clinical examinations.

Critical Role of Simultaneous Reduction of Atmospheric Odd Oxygen for Winter Haze Mitigation.

The lockdown due to COVID-19 created a rare opportunity to examine the nonlinear responses of secondary aerosols, which are formed through atmospheric oxidation of gaseous precursors, to intensive precursor emission reductions. Based on unique observational data sets from six supersites in eastern China during 2019-2021, we found that the lockdown caused considerable decreases (32-61%) in different secondary aerosol components in the study region because of similar-degree precursor reductions. However, due to insufficient combustion-related volatile organic compound (VOC) reduction, odd oxygen (Ox = O3 + NO2) concentration, an indicator of the extent of photochemical processing, showed little change and did not promote more decreases in secondary aerosols. We also found that the Chinese provinces and international cities that experienced reduced Ox during the lockdown usually gained a greater simultaneous PM2.5 decrease than other provinces and cities with an increased Ox. Therefore, we argue that strict VOC control in winter, which has been largely ignored so far, is critical in future policies to mitigate winter haze more efficiently by reducing Ox simultaneously.

Association of blood lead levels with preeclampsia: A cohort study in China.

BACKGROUND: Preeclampsia is the main cause of maternal and perinatal death, especially in developing countries. Multiple studies suggest that blood lead levels in pregnancy are a risk factor for preeclampsia, even with low levels of blood lead. But less knows the dose-effect relationship of preeclampsia in low blood lead levels. OBJECTIVES: This study aims to assess the association between blood lead levels and preeclampsia and to explore its dose-effect relationship between low blood lead levels and preeclampsia. METHODS: The retrospective cohort study was consecutively conducted in a comprehensive tertiary hospital in Foshan city of Guangdong Province, China, from August 1, 2019, to November 30, 2019. Blood lead levels were measured in maternal whole blood in 12-27 (+6) weeks of pregnancy, using atomic absorption spectrometer. Preeclampsia diagnosis was ascertained from the electronic medical records system. The risk of preeclampsia was estimated by multivariable logical regression analysis, and a two-stage linear regression model was established to find out the dose-effect. RESULTS: A total of 2174 people were included in this study, and 59 (2.7%) women developed preeclampsia. The dose-effect analysis revealed a non-linear association between blood lead levels and the risk of preeclampsia, with a cut-off point at 4.2 µg/dl. When blood lead levels were over 4.2 µg/dl, the risk of preeclampsia increased significantly with an increase in blood lead levels (OR = 2.05, 95%CI: 1.50, 2.81). In the multivariate regression models, per 1 µg/dl increment in blood lead levels was associated with 43% higher risk of developing preeclampsia (OR = 1.43,95%CI:1.17,1.74). Moreover, the association between blood lead levels and preeclampsia was stable in different subgroups. CONCLUSIONS: Low levels of lead exposure had a dose-effect relationship of preeclampsia, with a cut-off point at 4.2 µg/dl. Blood lead levels had a non-linear association with preeclampsia. When the blood lead levels were higher than 4.2 µg/dl, the risk of preeclampsia increases by 105% for every 1 µg/dl increase in blood lead levels.

Isolation and identification of microorganisms in Kazakhstan koumiss and their application in preparing cow-milk koumiss.

Koumiss is a type of famous fermented mare milk and considered an important nutritious beverage in central Asian countries. However, the production of koumiss cannot meet public demand in the market due to availability of mare milk. In the present study, 52 lactic acid bacteria and 20 yeast strains from traditional homemade Kazakhstan koumiss were isolated and identified. The isolates were used in a trial that included fermented cow milk, and the flavor profiles, color, and taste to determine their contribution in the co-fermentation of cow milk. Based on the sensory evaluation, KZLAB13 and KZY10 strains were selected as the best cofermentation combinations. The optimal fermentation conditions were confirmed as the ratio of the starter culture 2.4:1.6 % (vol/vol) KZLAB13 strain to KZY10 strain and a temperature of 36°C for 16 h using response surface methodology. After evaluating the quality of the optimized cow-milk koumiss compared with the Kazakhstan koumiss, results suggested that cow milk fermented by these 2 strains possessed a promising taste, flavor, and physicochemical and rheological properties. Altogether, our results showed that cow milk fermented with a combination of KZLAB13 and KZY10 strains can simulate the taste, flavor, and quality of traditional koumiss. Our study provided a novel alternative to mare-milk koumiss and could be used in dairy programs to fulfill the needs of people.

Abundant Biogenic Oxygenated Organic Aerosol in Atmospheric Coarse Particles: Plausible Sources and Atmospheric Implications.

Secondary organic aerosol (SOA) is a key component in atmospheric aerosols, strongly influencing air quality and climate. Most previous studies focused on SOA formation in the fine aerosol mode, and little is known about SOA formation across a broader size range, especially for the coarse aerosol mode. In this study, we coupled radiocarbon analysis and the offline aerosol mass spectrometric method to characterize water-soluble organic matter in size-segregated samples between 0.056 and 18 µm collected in urban Shenzhen, China. For the first time, detailed size distributions of different types of oxygenated organic aerosols (OOAs) are obtained. Fossil fuel OOA was mostly distributed in fine particles, and biogenic OOA occurred mostly in coarse particles. Organic composition and correlation analyses suggested that the major source of the coarse-mode OOA was more plausible to be heterogeneous reactions of biogenic volatile organic compounds (VOCs) on soil dust rather than primary biological materials. If so, this mechanism would complement the missing sinks of biogenic VOCs, significantly influence the regional and global organic aerosol budgets, and thus should be considered in air quality and climate models. This study highlights the urgent need for laboratory simulations of heterogeneous reactions of various VOCs on soil dust.

Potential of deep learning in assessing pneumoconiosis depicted on digital chest radiography.

OBJECTIVES: To investigate the potential of deep learning in assessing pneumoconiosis depicted on digital chest radiographs and to compare its performance with certified radiologists. METHODS: We retrospectively collected a dataset consisting of 1881 chest X-ray images in the form of digital radiography. These images were acquired in a screening setting on subjects who had a history of working in an environment that exposed them to harmful dust. Among these subjects, 923 were diagnosed with pneumoconiosis, and 958 were normal. To identify the subjects with pneumoconiosis, we applied a classical deep convolutional neural network (CNN) called Inception-V3 to these image sets and validated the classification performance of the trained models using the area under the receiver operating characteristic curve (AUC). In addition, we asked two certified radiologists to independently interpret the images in the testing dataset and compared their performance with the computerised scheme. RESULTS: The Inception-V3 CNN architecture, which was trained on the combination of the three image sets, achieved an AUC of 0.878 (95% CI 0.811 to 0.946). The performance of the two radiologists in terms of AUC was 0.668 (95% CI 0.555 to 0.782) and 0.772 (95% CI 0.677 to 0.866), respectively. The agreement between the two readers was moderate (kappa: 0.423, p<0.001). CONCLUSION: Our experimental results demonstrated that the deep leaning solution could achieve a relatively better performance in classification as compared with other models and the certified radiologists, suggesting the feasibility of deep learning techniques in screening pneumoconiosis.

Correlations between quantitative parameters of contrast-enhanced ultrasound and vasculogenic mimicry in murine tumor model: a novel noninvasive technique for assessment?

OBJECTIVE: Vasculogenic mimicry (VM) is a novel mechanism of tumor blood supply distinct from endothelial vessel (EV). VM is associated with malignancy, invasion, metastasis, and poor prognosis. Hitherto a noninvasive method for the assessment of VM in vivo has been lacking. METHODS: Contrast-enhanced ultrasound (CEUS) was performed to evaluate the quantitative parameters of tumors in mice. CD31 immunohistochemistry-Periodic Acid-Schiff double staining was conducted to identify the VM or EV in tumor tissues. Correlations between perfusion parameters and VM density was analyzed by Pearson correlation test. RESULTS: By the 15th day after tumor inoculation, the EV and VM density was 31.15 ± 7.14 and 14.11 ± 2.99 per 200× field. The maximal intensity (IMAX) was 301.19 ± 191.56%, and the rise time (RT), time to peak (TTP) and mean transit time (mTT) were 17.38 ± 7.82 s, 20.27 ± 9.61 s and 58.09 ± 26.44 s, respectively. VM density positively correlated to RT (r = 0.3598, P = 0.0226), TTP (r = 0.3733, P = 0.0177) and mTT(r = 0.6483, P <  0.0001), whereas EV density positively correlated to IMAX (r = 0.4519, P = 0.0034). The vascular diameter of VM was substantially larger than that of EV (43.81 ± 5.88 µm vs 11.21 ± 4.13 µm). CONCLUSION: Three quantitative parameters related to VM were obtained and the relationships between CEUS and VM were established. CEUS might thus provide a novel noninvasive method to assess VM in vivo.

Arabidopsis JINGUBANG Is a Negative Regulator of Pollen Germination That Prevents Pollination in Moist Environments.

The molecular mechanism of pollen germination and pollen tube growth has been revealed in detail during the last decade, while the mechanism that suspends pollen grains in a dormant state is largely unclear. Here, we identified the JINGUBANG (JGB) gene by screening pollen-specific genes for those that are unnecessary for pollen germination. We showed that the pollen of the jgb loss-of-function mutant exhibited hyperactive germination in sucrose-only medium and inside the anther, while this phenotype was rescued by the transgenic expression of JGB in jgb plants. JGB contains seven WD40 repeats and is highly conserved in flowering plants. Overexpression of JGB inhibits pollen germination. These results indicate that JGB is a novel negative regulator of pollen germination. In addition, we found that jasmonic acid (JA) abundance was significantly elevated in jgb pollen, while exogenous application of methyl jasmonate rescued the inhibition of pollen germination in plants overexpressing JGB Based on the molecular features of JGB and on the finding that it interacts with a known JA biosynthesis-related transcription factor, TCP4, we propose that JGB, together with TCP4, forms a regulatory complex that controls pollen JA synthesis, ensuring pollination in moist environments.

High-throughput computational screening of metal-organic frameworks with topological diversity for hexane isomer separations.

The adsorption separation of C6-C8 hydrocarbons in metal-organic frameworks (MOFs) has attracted extensive attention worldwide due to its technical feasibility and high energy efficiency in the petroleum industry. In this study, a large-scale computational screening of 13 512 MOFs with topological diversity was carried out to search optimal candidates for the simultaneous separation of two dimethyl butanes (DMB) from the quinary equimolar mixture of hexane isomers. We first screened out 841 MOFs according to their geometrical properties such as pore limited diameter (PLD) and volumetric surface area. Subsequently, high-performing MOFs were ranked out by an evaluation metric of adsorption performance score (APS), that is the product of the adsorption capacity of DMB and the selectivity of DMB over normal and mono-branched hexane isomers (N + M), on the basis of the predicted capacities by the grand canonical Monte Carlo (GCMC) simulations at 10 bar and 433 K. The structure-property relationships were established between APS and MOF descriptors such as density, PLD, etc. Among the screened 841 MOFs, the MOF with highest APS was MOF-163 because it provided an ideal pore topology with the 6.85 Å annular channel to distinguish DMB from the N + M isomers. The breakthrough predictions further demonstrated that the dimensionless residence time of 2,2-dimethylbutane (22DMB) was significantly different from that of n-hexane; this indicated that MOF-163 was a superior candidate for the dynamic separation of hexane isomers. Radial distribution function, adsorption equilibrium configurations and mass center probability density distributions were investigated to elucidate why MOF-163 could differentiate DBM from the N + M isomers. The molecular-level insights proposed in this study will facilitate the development of new MOFs for the separation of hydrocarbons in the petroleum industry.

Oestradiol: any role in cardiovascular risk factors in female centenarians of Hainan?

BACKGROUND: Previous studies reported that low level of oestradiol (E2) was associated with higher risk of cardiovascular disease (CVD). However, little study examined the relationship between E2 and CVD in longevous women, which were deficient in serum E2 for the post-menopausal status. Therefore, this study aims to explore the association between E2 and CVD risk factors in a group of female centenarians of Hainan, China. METHODS: A total of 413 female centenarians (aged from 100 to 115) from China Hainan Centenarian Cohort Study (CHCCS) were enrolled in this study. Home interviews were conducted to collected data on demographic characteristics, health-related lifestyles, and anthropometrics. The level of serum E2 was assessed in the Clinical Laboratory of Hainan branch of PLA General Hospital. The variables of CVD risk factors, including blood pressures, lipids and blood glucose, were measured through standard procedures. RESULTS: Significant negative correlations between levels of serum E2 and TC, HDL-C, and LDL-C were observed in this study. Compared with the highest group of E2, the odds ratio and 95% confidence intervals of high LDL-C in groups 3, 2 and 1 were OR1.94 (CI0.82-4.62), OR3.61 (CI1.27-10.25) and OR9.29 (CI2.08-41.53), respectively. Similarly, the prevalence of hypertension was decreased with the increase of serum E2. The odds ratio and 95% confidence intervals of stage-2 hypertension in groups 3, 2 and 1 versus highest E2 group were OR1.34 (CI0.49-3.72), OR1.36 (CI0.47-3.99) and OR1.38 (CI0.45-4.20), respectively. CONCLUSIONS: This study examined the relationship between E2 and CVD risk factors in a group of community-based female centenarians. A negative correlations between serum E2 levels and CVD risk factors, i.e. high level of LDL-C, TC, and hypertension were observed in this population. Besides, the level of serum E2 is also negatively correlated with HDL-C. Further studies on the correlation between serum E2 and CVD risk factors, especially dyslipidemia, in longevous and post-menopausal women are warranted.

Paeonol protects against hypertension in spontaneously hypertensive rats by restoring vascular endothelium.

The present study focused on the effect of paeonol, one of the main components of Guizhi Fuling Pill, on blood pressure, cerebral blood flow, and vascular endothelium injury in spontaneously hypertensive rats to provide theoretical basis for the treatment of hypertension. After treatment with paeonol, the mean arterial pressure (MAP) of LSHRT and HSHRT rats decreased gradually with the prolongation of treatment time. The systolic blood flow velocity (Vs), diastolic blood flow velocity (Vd) and mean blood flow velocity (Vm) were significantly increased after paeonol treatment (p < 0.05). Paeonol effectively improved the blood pressure and increased the cerebral blood flow velocity in spontaneously hypertensive rats. This may be related to the fact that paeonol reduced the blood viscosity and the oxidative stress and improved the antioxidant capacity. Moreover, paeonol protected vascular endothelial cells and reduced vascular endothelial injury in spontaneously hypertensive rats.

Practical Determination of the Solubility Parameters of 1-Alkyl-3-methylimidazolium Bromide ([CnC1im]Br, n = 5, 6, 7, 8) Ionic Liquids by Inverse Gas Chromatography and the Hansen Solubility Parameter.

The physicochemical properties of four 1-alkyl-3-methylimidazolium bromide ([CnC1im]Br, n = 5, 6, 7, 8) ionic liquids (ILs) were investigated in this work by using inverse gas chromatography (IGC) from 303.15 K to 343.15 K. Twenty-eight organic solvents were used to obtain the physicochemical properties between each IL and solvent via the IGC method, including the specific retention volume and the Flory⁻Huggins interaction parameter. The Hildebrand solubility parameters of the four [CnC1im]Br ILs were determined by linear extrapolation to be δ 2 ( [ C 5 C 1 im ] Br ) = 25.78 (J·cm-3)0.5, δ 2 ( [ C 6 C 1 im ] Br ) = 25.38 (J·cm-3)0.5, δ 2 ( [ C 7 C 1 im ] Br ) =24.78 (J·cm-3)0.5 and δ 2 ( [ C 8 C 1 im ] Br ) = 24.23 (J·cm-3)0.5 at room temperature (298.15 K). At the same time, the Hansen solubility parameters of the four [CnC1im]Br ILs were simulated by using the Hansen Solubility Parameter in Practice (HSPiP) at room temperature (298.15 K). The results were as follows: δ t ( [ C 5 C 1 im ] Br ) = 25.86 (J·cm-3)0.5, δ t ( [ C 6 C 1 im ] Br ) = 25.39 (J·cm-3)0.5, δ t ( [ C 7 C 1 im ] Br ) = 24.81 (J·cm-3)0.5 and δ t ( [ C 8 C 1 im ] Br ) = 24.33 (J·cm-3)0.5. These values were slightly higher than those obtained by the IGC method, but they only exhibited small errors, covering a range of 0.01 to 0.1 (J·cm-3)0.5. In addition, the miscibility between the IL and the probe was evaluated by IGC, and it exhibited a basic agreement with the HSPiP. This study confirms that the combination of the two methods can accurately calculate solubility parameters and select solvents.