Changes in frailty and incident cardiovascular disease in three prospective cohorts.

BACKGROUND AND AIMS: Previous studies found that frailty was an important risk factor for cardiovascular disease (CVD). However, previous studies only focused on baseline frailty status, not taking into consideration the changes in frailty status during follow-up. The aim of this study was to investigate the associations of changes in frailty status with incident CVD. METHODS: This study used data of three prospective cohorts: China Health and Retirement Longitudinal Study (CHARLS), English Longitudinal Study of Ageing (ELSA), and Health and Retirement Study (HRS). Frailty status was evaluated by the Rockwood frailty index and classified as robust, pre-frail, or frail. Changes in frailty status were assessed by frailty status at baseline and the second survey which was two years after the baseline. Cardiovascular disease was ascertained by self-reported physician-diagnosed heart disease (including angina, heart attack, congestive heart failure, and other heart problems) or stroke. Cox proportional hazard models were used to calculate the hazard ratio (HR) and 95% confidence interval (95% CI) after adjusting for potential confounders. RESULTS: A total of 7116 participants from CHARLS (female: 48.6%, mean age: 57.4 years), 5303 from ELSA (female: 57.7%, mean age: 63.7 years), and 7266 from HRS (female: 64.9%, mean age: 65.1 years) were included according to inclusion and exclusion criteria. The median follow-up periods were 5.0 years in the CHARLS, 10.7 years in the ELSA, and 9.5 years in the HRS. Compared with stable robust participants, robust participants who progressed to pre-frail or frail status had increased risks of incident CVD (CHARLS, HR = 1.84, 95% CI: 1.54-2.21; ELSA, HR = 1.53, 95% CI: 1.25-1.86; HRS, HR = 1.59, 95% CI: 1.31-1.92). In contrast, frail participants who recovered to robust or pre-frail status presented decreased risks of incident CVD (CHARLS, HR = 0.62, 95% CI: 0.47-0.81; ELSA, HR = 0.49, 95% CI: 0.34-0.69; HRS, HR = 0.70, 95% CI: 0.55-0.89) when compared with stable frail participants. These decreased risks of incident CVD were also observed in pre-frail participants who recovered to robust status (CHARLS, HR = 0.66, 95% CI: 0.52-0.83; ELSA, HR = 0.65, 95% CI: 0.49-0.85; HRS, HR = 0.71, 95% CI: 0.56-0.91) when compared with stable pre-frail participants. CONCLUSIONS: Different changes in frailty status are associated with different risks of incident CVD. Progression of frailty status increases incident CVD risks, while recovery of frailty status decreases incident CVD risks.

The ZmNF-YC1-ZmAPRG pathway modulates low phosphorus tolerance in maize.

Phosphorus (P) is an essential nutrient for plant growth and yield. Low phosphate use efficiency makes it important to clarify the molecular mechanism of low P stress. In our previous studies, a P efficiency gene ZmAPRG was identified. Here, we further screened the upstream regulator ZmNF-YC1 of ZmAPRG by yeast one hybrid (Y1H) assay, and found it was a low inorganic phosphorus (Pi)-inducible gene. The results of dual luciferase assays, expression analysis, and ChIP-qPCR assays showed that ZmNF-YC1 is a positive regulator of ZmAPRG. Overexpression of ZmNF-YC1 improved low P tolerance, whereas knockout of ZmNF-YC1 decreased low P tolerance in maize. Bimolecular fluorescence complementation (BiFC), yeast two hybrid (Y2H) assay, and yeast three hybrid (Y3H) assay further showed that ZmNF-YC1 can interact with ZmNF-YB14, and recruit ZmNF-YA4/10 to form NF-Y complexes. Transcriptional activation assay confirmed that the NF-Y complexes can activate the promoters of ZmAPRG. Meanwhile, transcriptome and metabolome analyses indicated that overexpression of ZmAPRG improves low P tolerance by regulating lipid composition and photosynthetic capacity, and chlorophyll fluorescence parameters provided evidence in support of this hypothesis. Furthermore, overexpression of ZmAPRG increased grain yield in inbred and hybrid maize under low P conditions. Taken together, our research revealed a low P tolerance mechanism of the ZmNF-YC1-ZmAPRG pathway.

End-to-end sequence-structure-function meta-learning predicts genome-wide chemical-protein interactions for dark proteins.

Systematically discovering protein-ligand interactions across the entire human and pathogen genomes is critical in chemical genomics, protein function prediction, drug discovery, and many other areas. However, more than 90% of gene families remain "dark"-i.e., their small-molecule ligands are undiscovered due to experimental limitations or human/historical biases. Existing computational approaches typically fail when the dark protein differs from those with known ligands. To address this challenge, we have developed a deep learning framework, called PortalCG, which consists of four novel components: (i) a 3-dimensional ligand binding site enhanced sequence pre-training strategy to encode the evolutionary links between ligand-binding sites across gene families; (ii) an end-to-end pretraining-fine-tuning strategy to reduce the impact of inaccuracy of predicted structures on function predictions by recognizing the sequence-structure-function paradigm; (iii) a new out-of-cluster meta-learning algorithm that extracts and accumulates information learned from predicting ligands of distinct gene families (meta-data) and applies the meta-data to a dark gene family; and (iv) a stress model selection step, using different gene families in the test data from those in the training and development data sets to facilitate model deployment in a real-world scenario. In extensive and rigorous benchmark experiments, PortalCG considerably outperformed state-of-the-art techniques of machine learning and protein-ligand docking when applied to dark gene families, and demonstrated its generalization power for target identifications and compound screenings under out-of-distribution (OOD) scenarios. Furthermore, in an external validation for the multi-target compound screening, the performance of PortalCG surpassed the rational design from medicinal chemists. Our results also suggest that a differentiable sequence-structure-function deep learning framework, where protein structural information serves as an intermediate layer, could be superior to conventional methodology where predicted protein structures were used for the compound screening. We applied PortalCG to two case studies to exemplify its potential in drug discovery: designing selective dual-antagonists of dopamine receptors for the treatment of opioid use disorder (OUD), and illuminating the understudied human genome for target diseases that do not yet have effective and safe therapeutics. Our results suggested that PortalCG is a viable solution to the OOD problem in exploring understudied regions of protein functional space.

A prediction model for classifying maternal pregnancy smoking using California state birth certificate information.

BACKGROUND: Systematically recorded smoking data are not always available in vital statistics records, and even when available it can underestimate true smoking rates. OBJECTIVE: To develop a prediction model for maternal tobacco smoking in late pregnancy based on birth certificate information using a combination of self- or provider-reported smoking and biomarkers (smoking metabolites) in neonatal blood spots as the alloyed gold standard. METHODS: We designed a case-control study where childhood cancer cases were identified from the California Cancer Registry and controls were from the California birth rolls between 1983 and 2011 who were cancer-free by the age of six. In this analysis, we included 894 control participants and performed high-resolution metabolomics analyses in their neonatal dried blood spots, where we extracted cotinine [mass-to-charge ratio (m/z) = 177.1023] and hydroxycotinine (m/z = 193.0973). Potential predictors of smoking were selected from California birth certificates. Logistic regression with stepwise backward selection was used to build a prediction model. Model performance was evaluated in a training sample, a bootstrapped sample, and an external validation sample. RESULTS: Out of seven predictor variables entered into the logistic model, five were selected by the stepwise procedure: maternal race/ethnicity, maternal education, child's birth year, parity, and child's birth weight. We calculated an overall discrimination accuracy of 0.72 and an area under the receiver operating characteristic curve (AUC) of 0.81 (95% confidence interval [CI] 0.77, 0.84) in the training set. Similar accuracies were achieved in the internal (AUC 0.81, 95% CI 0.77, 0.84) and external (AUC 0.69, 95% CI 0.64, 0.74) validation sets. CONCLUSIONS: This easy-to-apply model may benefit future birth registry-based studies when there is missing maternal smoking information; however, some smoking status misclassification remains a concern when only variables from the birth certificate are used to predict maternal smoking.

Reduced tillering and dwarfing genes alter root traits and rhizo-economics in wheat.

The tiller inhibition (tin) and Reduced height (Rht) genes strongly influence the carbon partitioning and architecture of wheat shoots, but their effects on the energy economy of roots have not been examined in detail. We examined multiple root traits in three sets of near-isogenic wheat lines (NILs) that differ in the tin gene or various dwarfing gene alleles (Rht-B1b, Rht-D1b, Rht-B1c and Rht-B1b + Rht-D1b) to determine their effects on root structure, anatomy and carbon allocation. The tin gene resulted in fewer tillers but more costly roots in an extreme tin phenotype with a Banks genetic background due to increases in root-to-shoot ratio, total root length, and whole root respiration. However, this effect depended on the genetic background as tin caused both smaller shoots and roots in a different genetic background. The semi-dwarf gene Rht-B1b caused few changes to the root structure, whereas Rht-D1b, Rht-B1c and the double dwarf (Rht-B1b + Rht-D1b) decreased the root biomass. Rht-B1c reduced the energy cost of roots by increasing specific root length, increasing the volume of cortical aerenchyma and by reducing root length, number, and biomass without affecting the root-to-shoot ratio. This work informs researchers using tin and Rht genes how to modify root system architecture to suit specific environments.

Materials Challenges in the Electric Vehicle Transition.

The ongoing transition toward electric vehicles (EVs) is changing materials used for vehicle production, of which the consequences for the environmental performance of EVs are not well understood and managed. We demonstrate that electrification coupled with lightweighting of automobiles will lead to significant changes in the industry's demand not only for battery materials but also for other materials used throughout the entire vehicle. Given the automotive industry's substantial consumption of raw materials, changes in its material demands are expected to trigger volatilities in material prices, consequently impacting the material composition and attractiveness of EVs. In addition, the materials recovered during end-of-life recycling of EVs as the vehicle fleet turns over will impact recycled material supplies both positively and negatively, impacting material availabilities and the economic incentive to engage in recycling. These supply chain impacts will influence material usage and the associated environmental performance of not only the automotive sector but also other metal-heavy industries such as construction. In light of these challenges, we propose the need for new research to understand the dynamic materials impacts of the EV transition that encompasses its implications on EV adoption and fleet life cycle environmental performance. Effectively coordinating the coevolution of material supply chains is crucial for making the sustainable transition to EVs a reality.

In situ biosynthesized polyphosphate nanoparticles/reduced graphene oxide composite electrode for highly sensitive detection of heavy metal ions.

The development of an effective sensing platform is critical for the electrochemical detection of heavy metal ions (HMIs) in water. In this study, we fabricated a newly designed sensor through the in situ assembly of reduced graphene oxide (rGO) and polyphosphate nanoparticles (polyP NPs) on a carbon cloth electrode via microorganism-mediated green biochemical processes. The characterization results revealed that the rGO produced via microbial reduction had a three-dimensional porous structure, serving as an exceptional scaffold for hosting polyP NPs, and the polyP NPs were evenly distributed on the rGO network. In terms of detecting HMIs, the numerous functional groups of polyP NPs play a major role in the coordination with the cations. This electrochemical sensor, based on polyP NPs/rGO, enabled the individual and simultaneous determination of lead ion (Pb2+) and copper ion (Cu2+) with detection limits of 1.6 nM and 0.9 nM, respectively. Additionally, the electrode exhibited outstanding selectivity for the target analytes in the presence of multiple interfering metal ions. The fabricated sensor was successfully used to determine Pb2+/Cu2+ in water samples with satisfactory recovery rates ranging from 92.16% to 104.89%. This study establishes a facile, cost-effective, and environmentally friendly microbial approach for the synthesis of electrode materials and the detection of environmental pollutants.

Linkage of cell division cycle 42 with clinical features, treatment response and survival in adult Philadelphia chromosome negative acute lymphoblastic leukemia.

Cell division cycle 42 (CDC42) regulates the progression of leukemia via mediating proliferation and immune evasion of malignant cells. The study aimed to investigate the correlation of CDC42 with clinical features, treatment response, event-free survival (EFS) and overall survival (OS) in adult Philadelphia chromosome negative acute lymphoblastic leukemia (Ph- ALL) patients. CDC42 expression in bone marrow mononuclear cells was detected in 78 adult Ph- ALL patients and 10 donors using real-time reverse transcriptase-polymerase chain reaction. CDC42 was increased in adult Ph- ALL patients compared with donors (p < .001). Besides, elevated CDC42 was linked with pro-B ALL or early-T ALL (p = .038) and white blood cell (WBC) elevation at diagnosis (p = .025). Fifty (64.1%) and 23 (29.5%) patients had complete remission (CR) at 1 month and minimal residual disease (MRD) after CR, respectively. CDC42 was inversely associated with CR at 1 month (p = .034), but not MRD after CR (p = .066). Concerning survival, patients with CDC42 ≥ 3.310 (cut by median value in patients) showed a shortened EFS (p = .006) and OS (p = .036) compared to those with CDC42 < 3.310. In detail, patients with CDC42 ≥ 3.310 and CDC42 < 3.310 had 5-year EFS rate of 29.9% and 45.4%, and 5-year OS rate of 39.4% and 63.6%, correspondingly. Further multivariate Cox's regression analyses revealed that CDC42 ≥ 3.310 was independently related to shorter EFS (hazard ratio = 2.933, p = .005). Elevated CDC42 is related with pro-B ALL or early-T ALL, WBC elevation at diagnosis, unfavorable treatment response and worse survival in adult Ph- ALL patients.

The response of structure and nitrogen removal function of the biofilm on submerged macrophytes to high ammonium in constructed wetlands.

The ammonium exceedance discharge from sewage treatment plants has a great risk to the stable operation of subsequent constructed wetlands (CWs). The effects of high ammonium shocks on submerged macrophytes and epiphytic biofilms on the leaves of submerged macrophytes in CWs were rarely mentioned in previous studies. In this paper, the 16S rRNA sequencing method was used to investigate the variation of the microbial communities in biofilms on the leaves of Vallisneria natans plants while the growth characteristics of V. natans plants were measured at different initial ammonium concentrations. The results demonstrated that the total chlorophyll and soluble sugar synthesis of V. natans plants decreased by 51.45% and 57.16%, respectively, and malondialdehyde content increased threefold after 8 days if the initial NH4+-N concentration was more than 5 mg/L. Algal density, bacterial quantity, dissolved oxygen, and pH increased with high ammonium shocks. The average removal efficiencies of total nitrogen and NH4+-N reached 73.26% and 83.94%, respectively. The heat map and relative abundance analysis represented that the relative abundances of phyla Proteobacteria, Cyanobacteria, and Bacteroidetes increased. The numbers of autotrophic nitrifiers and heterotrophic nitrification aerobic denitrification (HNAD) bacteria expanded in biofilms. In particular, HNAD bacteria of Flavobacterium, Hydrogenophaga, Acidovorax, Acinetobacter, Pseudomonas, Aeromonas, and Azospira had higher abundances than autotrophic nitrifiers because there were organic matters secreted from declining leaves of V. natans plants. The analysis of the nitrogen metabolic pathway showed aerobic denitrification was the main nitrogen removal pathway. Thus, the nitrification and denitrification bacterial communities increased in epiphytic biofilms on submerged macrophytes in constructed wetlands while submerged macrophytes declined under ammonium shock loading.

Efficient Photocatalytic Desulfurization in Air through Improved Photogenerated Carriers Separation in MOF MIL101/Carbon Dots-g-C3N4 Nanocomposites.

The extensive industrial applications of fuel oil, a critical strategic resource, are accompanied by significant environmental and health concerns due to the presence of sulfur-containing compounds in its composition, which result in hazardous combustion waste. Extensive research has been conducted to develop technologies for low-vulcanization fuel production to address this issue. Consequently, the investigation of catalysts for environmentally friendly and safe photocatalytic desulfurization becomes imperative. To that end, we have designed efficient MIL-101(Fe)/CQDs@g-C3N4 (MIL101/CDs-C3N4) Z-scheme heterojunction photocatalysts with high carrier separation and mobility through a thermal polymerization-hydrothermal strategy. The high concentration of photogenerated carriers facilitates the activation of oxygen and H2O2, leading to increased production of ROS (⋅O2 -, ⋅OH, h+), thereby enhancing the photocatalytic desulfurization (PODS). Additionally, DFT (Density functional theory) calculations were utilized to determine the electron migration pathways of the catalysts and adsorption energies of DBT (dibenzothiophene). Moreover, Gibbs free energy calculations indicated that MIL101/CDs-C3N4 exhibited the lowest activation energy for oxygen and H2O2. The mechanism of photocatalytic desulfurization was proposed through a combination of theoretical calculations and experimental studies. This study provides guidance for the development of MOF-based Z-scheme systems and their practical application in desulfurization processes.

Metabolite Stability in Archived Neonatal Dried Blood Spots Used for Epidemiologic Research.

Epidemiologic studies of low-frequency exposures or outcomes using metabolomics analyses of neonatal dried blood spots (DBS) often require assembly of samples with substantial differences in duration of storage. Independent assessment of stability of metabolites in archived DBS will enable improved design and interpretation of epidemiologic research utilizing DBS. Neonatal DBS routinely collected and stored as part of the California Genetic Disease Screening Program between 1983 and 2011 were used. The study population included 899 children without cancer before age 6 years, born in California. High-resolution metabolomics with liquid-chromatography mass spectrometry was performed, and the relative ion intensities of common metabolites and selected xenobiotic metabolites of nicotine (cotinine and hydroxycotinine) were evaluated. In total, we detected 26,235 mass spectral features across 2 separate chromatography methods (C18 hydrophobic reversed-phase chromatography and hydrophilic-interaction liquid chromatography). For most of the 39 metabolites related to nutrition and health status, we found no statistically significant annual trends across the years of storage. Nicotine metabolites were captured in the DBS with relatively stable intensities. This study supports the usefulness of DBS stored long-term for epidemiologic studies of the metabolome. -Omics-based information gained from DBS may also provide a valuable tool for assessing prenatal environmental exposures in child health research.

Matching entropy based disparity estimation from light field data.

A major challenge for matching-based disparity estimation from light field data is to prevent mismatches in occlusion and smooth regions. An effective matching window satisfying three characteristics: texture richness, disparity consistency, and anti-occlusion should be able to prevent mismatches to some extent. According to these characteristics, we propose matching entropy in the spatial domain of the light field to measure the amount of correct information in a matching window, which provides the criterion for matching window selection. Based on matching entropy regularization, we establish an optimization model for disparity estimation with a matching cost fidelity term. To find the optimum, we propose a two-step adaptive matching algorithm. First, the region type is adaptively determined to identify occluding, occluded, smooth, and textured regions. Then, the matching entropy criterion is used to adaptively select the size and shape of matching windows, as well as the visible viewpoints. The two-step process can reduce mismatches and redundant calculations by selecting effective matching windows. The experimental results on synthetic and real data show that the proposed method can effectively improve the accuracy of disparity estimation in occlusion and smooth regions and has strong robustness for different noise levels. Therefore, high-precision disparity estimation from 4D light field data is achieved.

Maternal migraine and risk of pediatric cancers.

BACKGROUND: Maternal migraine has been linked to adverse birth outcomes including low birth weight and preterm birth, as well as congenital anomalies in offspring. It has been speculated that this may be due to the use of medications in pregnancy, but lifestyle, genetic, hormonal, and neurochemical factors could also play a role. There is evidence for varying cancer incidences among adults with migraine. Here, we utilized data from national registries in Denmark to examine associations between maternal diagnoses of migraine and risk for cancer in offspring. METHODS: We linked several national registries in Denmark to identify cases from the Cancer Registry among children less than 20 years (diagnoses 1996-2016) and controls from the Central Population Register, matched to cases by birth year and sex (25:1 matching rate). Migraine diagnoses were identified from the National Patient Register using International Classification of Diseases, versions 8 and 10 codes and migraine-specific acute or prophylactic treatment recorded in the National Pharmaceutical Register. We used logistic regression to estimate the risk of childhood cancers associated with maternal migraine. RESULTS: Maternal migraine was positively associated with risk for non-Hodgkin lymphoma (odds ratio [OR] = 1.70, 95% confidence interval [CI]: 1.01-2.86), central nervous system tumors ([OR = 1.31, 95% CI: 1.02-1.68], particularly glioma [OR = 1.64, 95% CI: 1.12-2.40]), neuroblastoma (OR = 1.75, 95% CI: 1.00-3.08), and osteosarcoma (OR = 2.60, 95% CI: 1.18-5.76). CONCLUSIONS: Associations with maternal migraine were observed for several childhood cancers, including neuronal tumors. Our findings raise questions about the role of lifestyle factors, sex hormones, genetic, and neurochemical factors in the relationship between migraine and childhood cancers.

Ferryl Ion in the Photo-Fenton Process at Acidic pH: Occurrence, Fate, and Implications.

Fenton processes produce reactive species that can oxidize organic compounds in natural and engineered systems. While it is well-documented that Fenton reactions produce hydroxyl radical (HO•) under acidic conditions, we demonstrated the generation of ferryl ion (FeIVO2+) in the UV/Fe(III) and UV/Fe(III)/H2O2 systems at pH 2.8 using methyl phenyl sulfoxide (PMSO) as the probe compound. Moreover, we clarified that FeIVO2+ is parallelly formed via the oxidation of Fe(III) by HO• and the O-O homolysis of [FeIII-OOH]2+ in the photo-Fenton process. The rate constant for the reaction between HO• and Fe3+ measured by laser flash photolysis was 4.41 × 107 M-1 s-1. The rate constant and quantum yield for thermal and photo O-O homolysis of [FeIII-OOH]2+ complex were 1.4 × 10-2 s-1 and 0.3, respectively, which were determined by fitting PMSO2 formation. While FeIVO2+ forms predominantly through the reaction between HO• and Fe3+ in the absence of H2O2, the relative contribution of [FeIII-OOH]2+ O-O homolysis to FeIVO2+ formation highly depends on the molar ratio of [H2O2]0/[Fe(III)]0, the level of HO• scavenging, and incident irradiance in the UV/Fe(III)/H2O2 system. Accordingly, an optimized kinetic model was developed by incorporating FeIVO2+-involved reactions into the conventional photo-Fenton model, which can accurately predict Fe(II) formation and contaminant decay in the UV/Fe(III) and UV/Fe(III)/H2O2 systems. Our study illuminated the underlying formation mechanism of reactive oxidative species in the photo-Fenton process and highlighted the role of FeIVO2+ evolution in modulating the iron cycle and pollutant abatement therein.

Sensitive and discriminative detection of cysteine by a Nile red-based NIR fluorescence probe.

Cysteine (Cys) is a significant biological mercaptan that achieves key roles in several important physiological processes, such as reversible redox homeostasis in living organisms. Abnormal levels of Cys in the human body are directly related to many diseases. In this work, we constructed a sensitive sensor (Cys-NR) by connecting a Cys recognition group to a Nile red derivative. Due to photo-induced electron transfer (PET), the Cys-NR probe showed little fluorescence at 650 nm. With the addition of Cys to the assay solution, the chlorine unit of the probe was substituted by the thiol group of Cys. Further, the amino and sulfhydryl groups in cysteine underwent an intramolecular rearrangement, which led to the Cys-NR probe water solution turning from colorless to pink with an enhancement in fluorescence. The red fluorescence at 650 nm increased about 20 times. Based on the turn-on signal, a selective Cys detection method is developed. The probe signal is not affected by various potential interferences or other competing biothiols and the limit of detection (LOD) is determined to be 0.44 µM. In addition, the probe is further employed for imaging of Cys in live cells, revealing good biological imaging ability that could provide a new way of intracellular Cys detection.

The impact of non-adiabatic effects on reaction dynamics: a study based on the adiabatic and non-adiabatic potential energy surfaces of CaH2.

The two-state non-adiabatic potential energy matrices of the CaH2+ system are calculated via a diabatization approach by using a neural network model. Subsequently, the adiabatic and non-adiabatic potential energy surfaces (PESs) are constructed based on these non-adiabatic potential energy matrices. Furthermore, based on the adiabatic and non-adiabatic PESs, the Ca+(4s2S) + H2(X1Σ+g) → H(2S) + CaH+(X1Σ+) reaction is studied using the time-dependent wave packet method. Comparative analysis of the experimental and theoretical integral reaction cross-sections (ICSs) indicates that the maximum deviation between the results obtained from the adiabatic PES and the corresponding experimental value is 12.7 bohr2; in contrast, the maximum discrepancy between the theoretical result derived from the non-adiabatic PES and the experimental value is merely 0.42 bohr2. The potential well along the reaction path acts as a 'filter', selectively guiding intermediates with longer lifetimes in the potential well back to the reactant channel. This phenomenon indicates that the non-adiabatic effects significantly influence the reaction dynamics of the CaH2+ system.

Effect of intermolecular interaction of the charge-transfer complex between molecular "tweezers" and C60/C70 on second-order nonlinear optical properties.

To enhance understanding of the correlation between the intermolecular interaction and second-order nonlinear optical (NLO) properties, we studied a "molecular tweezer" with two corannulene substituents linked by a tetrahydro[5]helicene imide, which enabled highly sensitive and selective complexation of C60/C70 through convex-concave π-π interactions. The geometric structure, molecular orbitals, intermolecular interactions, electron absorption spectra and second-order NLO properties of the charge-transfer (CT) complexes formed by molecular tweezers and C60/C70 were studied by density functional theory. Larger fullerenes helped to increase the intermolecular interaction and CT, thereby increasing the first hyperpolarizabilities of CT complexes. Embedding of lithium ions helped to enhance the electron-absorption ability of fullerenes, thereby increasing the intermolecular interaction and intermolecular CT and, thus, enhancing their first hyperpolarizability significantly. Our data indicated that, through structure adjustment (including increasing the volume of fullerene and embedding alkali metal ions), we could enhance intermolecular interactions and improve intermolecular CT significantly. These actions could improve the second-order NLO properties of CT complexes.

Exposure to nitrosatable drugs during pregnancy and childhood cancer: A matched case-control study in Denmark, 1996-2016.

BACKGROUND: Nitrosatable drugs can be synthesized to N-nitroso compounds in human stomach. In a pregnant woman, N-nitroso compounds can be translocated to the fetus through the placenta. Maternal exposure of nitrosatable compounds during pregnancy has been associated with childhood brain tumors and leukemia. However, few studies have investigated an association between nitrosatable drug exposure during pregnancy and childhood cancer. We examined if maternal prescriptions of nitrosatable drugs received during pregnancy are associated with childhood cancer. METHODS: A matched case-control study was conducted using Danish nationwide registry data from 1995 to 2016. Each childhood cancer case was matched with twenty-five controls. Maternal exposure of nitrosatable drugs during pregnancy was identified from the Danish National Prescription Register. A multivariable conditional logistic regression model was used to estimate adjusted odds ratios (adj.OR) with 95% confidence intervals (CI) for each childhood cancer type. RESULTS: Maternal prescriptions of nitrosatable drugs positively associate with central nervous system tumors (adj.OR = 1.25; 95% CI = 1.04-1.51) and neuroblastoma (adj.OR = 1.96; 95% CI = 1.34-2.85) in offspring. We also observed a positive association between perinatal exposure of nitrosatable drugs and acute lymphoblastic leukemia (adj.OR = 1.31; 95% CI = 1.07-1.59), however, it appeared to be due to confounding by indication, i.e., maternal infections. CONCLUSION: Nitrosatable drug use during pregnancy potentially increased risk of central nervous system tumors and neuroblastoma. While a positive association between maternal prescriptions of nitrosatable drugs and acute lymphoblastic leukemia should be interpreted cautiously because of confounding by indication.

BIOMARKERS OF MATERNAL SMOKING AND THE RISK OF RETINOBLASTOMA IN OFFSPRING.

PURPOSE: Previous studies examining the risk of retinoblastoma with maternal smoking were inconclusive, likely due in part to the reliance on self-reported maternal smoking. This study uses biomarkers of tobacco smoking in neonatal dried blood spots to investigate associations between maternal smoking and retinoblastoma in offspring. METHODS: The authors randomly selected 498 retinoblastoma cases and 895 control subjects born between 1983 and 2011 from a population-based case-control study in California. Maternal pregnancy-related smoking was measured using the following three metrics: provider or self-reported smoking during pregnancy, cotinine, and hydroxycotinine in neonatal blood. The authors used multivariable logistic regression to estimate the effects of maternal tobacco smoking on retinoblastoma. RESULTS: Using all metrics (biomarkers or self-report), maternal smoking late in pregnancy or early postpartum was related to retinoblastoma (all types; odds ratio = 1.44, 95% confidence interval: 1.00-2.09). Relying on cotinine or hydroxycotinine to ascertain smoking, maternal smoking was related to unilateral retinoblastoma (odds ratio = 1.66, 95% confidence interval: 1.08-2.57). CONCLUSION: The results indicate that maternal smoking during pregnancy may be a risk factor for retinoblastoma, particularly among unilateral cases.

Influence of circulation types on temporal and spatial variations of ozone in Beijing.

This study analyzes the impact of circulation types (CTs) on ozone (O3) pollution in Beijing. The easterly high-pressure (SWW) circulation occurred most frequently (30%; 276 day), followed by northwesterly high-pressure (AN) circulation (24.3%; 224 day). The SWW type had the highest O3 anomaly of +17.28 µg/m3, which was caused by excellent photochemical reactions, poor diffusion ability and regional transport. Due to the higher humidity and precipitation in the low-pressure type (C), the O3 increase (+8.02 µg/m3) was less than that in the SWW type. Good diffusion/wet deposition and weak formation ability contributed to O3 decrease in AN (-12.54 µg/m3) and northerly high-pressure (ESN) CTs (-12.26 µg/m3). The intra-area transport of O3 was significant in polluted circulations (SWW- and C-CTs). In addition, higher temperature, radiation and less rainfall also contributed to higher O3 in northern Beijing under the SWW type. For the clean CTs (AN and ESN CTs), precursor amount and intra-area transport played a dominant role in O3 distribution. Under the northeasterly low-pressure CT, better formation conditions and higher precursor amount combined with the intra-area southerly transport to cause higher O3 values in the south than in the north. The higher O3 in the northwestern area under the northeasterly high-pressure type was influenced by weaker titration loss and high O3 concentration in previous day. Annual variation in the CTs contributed up to 86.1% of the annual variation in O3. About 78%-83% of the diurnal variation in O3 resulted from local meteorological factors.