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.

Diabatic Potential Energy Surfaces of SrH2+ and Dynamics Studies of the Sr+(5s2S) + H2 Reaction.

Based on the ab initio energy points of both ground and excited states, a neural network fitting method combined with a specific function was successfully used to construct the diabatic potential energy surfaces (PESs) of the SrH2+ system. The topographical features of the diabatic PESs were examined in detail. The results indicate that the nonadiabatic transition characteristics between ground and excited states are accurately described by the newly constructed diabatic PESs. To verify the validity and applicability of the diabatic PESs, as well as the nonadiabatic effects during the reaction process, the quantum dynamics studies of the Sr+(5s2S) + H2 reaction were performed based on both adiabatic and diabatic PESs. The dynamics results indicate that adiabatic dynamics results are dozens of times larger than those of nonadiabatic. This illustrates the significant effect of nonadiabaticity, indicating that adiabatic dynamics results often overestimate the actual values. The integral cross sections (ICSs) were calculated and compared with the experimental data. The diabatic ICSs are in good agreement with the experimental results. The reasonable dynamics results indicate that the newly constructed diabatic PESs are suitable for the relevant dynamics studies.

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.

Construction of diabatic potential energy surfaces for the SiH2+ system and dynamics studies of the Si+(2P1/2, 3/2) + H2 reaction.

The construction of diabatic potential energy surfaces (PESs) for the SiH2+ system, related to the ground (12A') and excited states (22A'), has been successfully achieved. This was accomplished by utilizing high-level ab initio energy points, employing a neural network fitting method in conjunction with a specifically designed function. The newly constructed diabatic PESs are carefully examined for dynamics calculations of the Si+(2P1/2, 3/2) + H2 reaction. Through time-dependent quantum wave packet calculations, the reaction probabilities, integral cross sections (ICSs), and differential cross sections (DCSs) of the Si+(2P1/2, 3/2) + H2 reaction were reported. The dynamics results indicate that the total ICS is in excellent agreement with experimental data within the collision energy range studied. The results also indicate that the SiH+ ion is hardly formed via the Si+(2P3/2) + H2 reaction. The results from the DCSs suggest that the "complex-forming" reaction mechanism predominates in the low collision energy region. Conversely, the forward abstraction reaction mechanism is dominant in the high collision energy region.

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.

A 3-D Near-Field Source Localization Approach Based on the Combination of a Phase Interferometer, the Centroid Algorithm and the Perpendicular Foot Algorithm.

In this study, several 3-dimensional (3-D) parameter estimation and localization algorithms for wireless near-field (NF) sources are proposed employing the uniform circular array (UCA) structure. In the single-base-station case, the algebraic relation is demonstrated between the azimuth angle under the far-field (FF) assumption and the actual NF source firstly. Secondly, two groups of antenna pairs are selected with distances less than half the wavelength, which are called short baselines in the interferometer method. The foregoing short-baseline method is qualified to localize an NF source. In addition, a long-baseline method is also proposed with further research. Two groups of antenna pairs with distances greater than half the wavelength are selected as two long baselines. In the multiple-base-stations case, another two novel algorithms are also proposed. The first one is the centroid algorithm, which is based on the centroid calculation of three estimated source locations. And the second one is the perpendicular foot algorithm, which takes the perpendicular foot within three estimated source locations as the final positioning location. Simulation results illustrate that the proposed algorithms can achieve higher localization accuracy than the conventional 3-D Root MUSIC method. Moreover, the long-baseline method performs better than the short-baseline method. And it is also shown that the proposed perpendicular foot algorithm shows better performance than the proposed centroid algorithm.

Effects of pore characteristics on CO2 adsorption performance of coal slime with different metamorphic degrees.

With the rapid development of Carbon Capture, Utilization and Storage (CCUS) technology, it is necessary to explore the feasibility of coal slime as a porous carbon material for CO2 capture. In this paper, scanning electron microscopy (SEM) was used to observe the morphological characteristics of coal slime samples with different metamorphic degrees, and the pore structure of coal slime was explored by low temperature N2 adsorption and low-pressure CO2 adsorption experiments. The pore distribution characteristics were analyzed, and the adsorption law of different metamorphic degrees were summarized through CO2 isothermal adsorption experiments. The results showed that: The specific surface area (SSA) and pore volume (PV) of the mesopores of the coal slime exhibited a U-shaped distribution with coal rank, and are much smaller than that of its micropores. Micropores less than 2 nm are the main adsorption space of coal slime, its PV accounted for 59%, 60%, 71%, and SSA accounted for 92%, 93%, 95%, obviously, which are dominant at all stages. The linear correlation fitting coefficients R2 between the limiting adsorbed amount a of CO2 and the micropores PV and the SSA were up to 0.830 and 0.887, respectively. The coal slime has good adsorption performance for CO2. Based on the Langmuir model to fit the limit adsorption amount, a-value can reach 41.774 cm3 g-1, 32.072 cm3 g-1, 38.457 cm3 g-1 at 303 K with the increase of Rmax. Studying the impact of coal slime on CO2 adsorption performance provides a theoretical basis for the subsequent preparation of energy storage materials and is of great significance for the safe, efficient and economic capture and sequestration of CO2, to alleviate the serious situation of the environment and realizing the dual-carbon goal.

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.

Association between factors in life course and physiological disorders among the middle-aged and older population in Zhoushan city of Zhejiang province. / æµ™æ±ŸçœèˆŸå±±å¸‚ä¸­è€å¹´äººç¾¤ç”Ÿå‘½åŽ†ç¨‹å› ç´ ä¸Žç”Ÿç†å¤±è°ƒçš„å ³è”ç ”ç©¶.

OBJECTIVES: To analyze the associations between factors in life course and physiological disorders in the middle-aged and elderly population of Zhoushan city of Zhejiang province, and the mediating roles of lifestyle and mental health. METHODS: A total of 1553 island residents aged ≥45 years were enrolled from the Zhejiang Metabolic Syndrome Cohort Zhoushan Liuheng Sub-cohort. The demographic information, life-course information, lifestyle, and mental health information of participants were documented, and blood samples of were collected. The status of aging was evaluated by physiological disorders calculation model developed by authors previously. The Shapley value decomposition method was used to assess the cumulative and relative contribution of multiple factors in life course to the aging. Principal component analysis and hierarchical cluster analysis were used to classify subgroups. General linear regression model was used to assess the associations between the life-course subgroups and physiological disorders. Five key factors associated with aging were finally identified. Logistic regression model, general linear regression model, and mediation analysis model were used to assess the complex associations between life-course subgroups, key factors, unhealthy lifestyle, mental health, and aging. RESULTS: Shapley value decomposition method indicated that eight types of life-course factors explained 6.63% (SE=0.0008) of the individual physiological disorders variance, with the greatest relative contribution (2.78%) from adversity experiences in adulthood. The study participants were clustered into 4 subgroups, and subgroups experiencing more adversity in adulthood and having low educational attainment or experiencing more trauma and having poorer relationships in childhood had significantly higher levels of physiological disorders. Life-course subgroups and key factors (childhood trauma and health, adversity experience in adulthood, and lower education) were positively associated with unhealthy lifestyles (ß=0.12-0.41, P<0.05). In addition, life-course subgroups and key factors (adversity experience in adulthood) were positively associated with psychological problems (OR=2.14-4.68, P<0.05). Unhealthy lifestyle scores showed a marginal significant association with physiological disorders (ß=0.03, P=0.055). However, no significant association was found between psychological problems and physiological disorders (ß=0.03, P=0.748). The results of the mediation analysis model suggested that unhealthy lifestyles partially mediated the associations between life-course subgroups, adversity experience in adulthood and physiological disorders. CONCLUSIONS: Multiple life-course factors contribute about 6% of the variance in physiological disorders in the middle aged and elderly population of the study area; subgroups with adverse life course experiences have higher levels of aging; and the association may be partially mediated by unhealthy lifestyles.

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.