Hypoxic indices for obstructive sleep apnoea severity and cardiovascular disease risk prediction: A comparison and application in a community population.

BACKGROUND AND OBJECTIVE: The apnoea-hypopnoea index (AHI) and oxygen desaturation index (ODI) encounter challenges in capturing the intricate relationship between obstructive sleep apnoea (OSA) and cardiovascular disease (CVD) risks. Although novel hypoxic indices have been proposed to tackle these limitations, there remains a gap in comprehensive validation and comparisons across a unified dataset. METHODS: Samples were derived from the Sleep Heart Health Study (SHHS), involving 4485 participants aged over 40 years after data quality screening. The study compared several key indices, including AHI, ODI, the reconstructed hypoxic burden (rHB), the percentage of sleep time with the duration of respiratory events causing desaturation (pRED_3p) and the sleep breathing impairment index (SBII), in relation to CVD mortality and morbidity risks. Adjusted Cox proportional models were employed to calculate hazard ratios (HRs) for each index, and comparisons were performed. RESULTS: SBII and pRED_3p exhibited significant correlations with both CVD mortality and morbidity, with SBII showing the highest adjusted HR (95% confidence interval) for mortality (2.04 [1.25, 3.34]) and pRED_3p for morbidity (1.43 [1.09-1.88]). In contrast, rHB was only significant in predicting CVD mortality (1.63 [1.05-2.53]), while AHI and ODI did not show significant correlations with CVD outcomes. The adjusted models based on SBII and pRED_3p exhibited optimal performance in the CVD mortality and morbidity datasets, respectively. CONCLUSION: This study identified the optimal indices for OSA-related CVD risks prediction, SBII for mortality and pRED_3p for morbidity. The open-source online platform provides the computation of the indices.

Integrated Fibrous Iontronic Pressure Sensors with High Sensitivity and Reliability for Human Plantar Pressure and Gait Analysis.

Flexible sensing systems (FSSs) designed to measure plantar pressure can deliver instantaneous feedback on human movement and posture. This feedback is crucial not only for preventing and controlling diseases associated with abnormal plantar pressures but also for optimizing athletes' postures to minimize injuries. The development of an optimal plantar pressure sensor hinges on key metrics such as a wide sensing range, high sensitivity, and long-term stability. However, the effectiveness of current flexible sensors is impeded by numerous challenges, including limitations in structural deformability, mechanical incompatibility between multifunctional layers, and instability under complex stress conditions. Addressing these limitations, we have engineered an integrated pressure sensing system with high sensitivity and reliability for human plantar pressure and gait analysis. It features a high-modulus, porous laminated ionic fiber structure with robust self-bonded interfaces, utilizing a unified polyimide material system. This system showcases a high sensitivity (156.6 kPa-1), an extensive sensing range (up to 4000 kPa), and augmented interfacial toughness and durability (over 150,000 cycles). Additionally, our FSS is capable of real-time monitoring of plantar pressure distribution across various sports activities. Leveraging deep learning, the flexible sensing system achieves a high-precision, intelligent recognition of different plantar types with a 99.8% accuracy rate. This approach provides a strategic advancement in the field of flexible pressure sensors, ensuring prolonged stability and accuracy even amidst complex pressure dynamics and providing a feasible solution for long-term gait monitoring and analysis.

Prognostic and Immune Landscape Analysis of Ubiquitination-related Genes in Hepatocellular Carcinoma: Based on Bulk and Single-cell RNA Sequencing Data.

Background: Despite significant advances in tumor immunotherapy, hepatocellular carcinoma (HCC) remains a malignancy with a challenging prognosis. The increasing research emphasizes the crucial role of ubiquitination in tumor immunotherapy. However, the establishment of prognostic signatures based on ubiquitination-related genes (UbRGs) and their role in immunotherapy are still lacking in HCC. Methods: We employed datasets from TCGA and GEO for transcriptome differential expression analysis and single-cell RNA sequencing analysis. Applying weighted gene co-expression network analysis, cox regression, lasso, selection and visualization of the most relevant features, and gradient boosting machine, we identified hub UbRGs as a gene signature to develop a prognostic model. We evaluated the predictive utility concerning clinical characteristics as well as its role in the immune landscape and immunotherapy potential. Additionally, western blotting, reverse transcription-quantitative PCR, and immunofluorescence were employed to detect the expression and sub-localization of hub genes. Results: Three hub UbRGs (BOP1, CDC20, and UBE2S) were identified as a gene signature. In particular, the high-risk group exhibited notable characteristics, including higher tumor mutation burden, enrichment in immune-related pathways, up-regulation immune checkpoint, and higher immunity scores. Treatment response to immunotherapy varied based on the expression of PD-1 and CTLA-4. Furthermore, single-cell data analysis revealed heterogeneous expression of hub UbRGs across different cell subtypes, while cytological experiments provided additional confirmation of the high expression of hub UbRGs in HCC. Conclusion: Our study provides valuable insights into the identification of novel ubiquitination-related biomarkers with potential applications for prognosis, immunotherapy prediction, and drug sensitivity in HCC.

Impact of N-Methyl-2-pyrrolidone Erosion on Surface Functional Groups and Pore Evolution in Coals of Different Ranks.

In low-permeability coal reservoirs, utilizing the organic solvent N-methyl-2-pyrrolidone (NMP) has emerged as an effective approach to improving the coal pore structure and enhancing coalbed methane productivity. However, the exact mechanisms of how solvent erosion alters functional groups and develops pores remain incompletely understood. This study utilized Fourier transform infrared spectroscopy and low-field nuclear magnetic resonance to assess the impact of NMP on the functional groups and pore structures of lignite, bituminous coal, and anthracite. The results indicate that a 6 h treatment with NMP led to an increased proportion of oxygen-containing functional groups in all coal samples, accompanied by a decrease in hydroxyls and aliphatic hydrocarbons. The aromaticity of the coal samples was enhanced to varying degrees, most notably for lignite. In terms of pore modification, the porosity of lignite and bituminous coal increased by 84.82 and 43.56%, while anthracite experienced a porosity increase of 3.04%, indicating a diminished effectiveness of NMP as the coal rank increased. These findings suggest that NMP selectively dissolves specific organic molecules in coals, thereby enhancing pore connectivity and promoting a transition from micro- to meso- and macropores. These findings highlight the potential of NMP in enhancing coalbed methane production and advance our understanding of the mechanisms behind solvent erosion.

Correlation Between Impaired Sensitivity to Thyroid Hormones and Serum Uric Acid in Female Patients With Obesity and After Laparoscopic Sleeve Gastrectomy.

OBJECTIVE: An alterable risk factor for hyperuricemia is obesity. Additionally, obese people may have a moderate form of acquired resistance to thyroid hormones. Thyrotropin, thyroid hormones, and obesity all interact subtly. However, the connection between thyroid hormone sensitivity and hyperuricemia in obese patients both before and after laparoscopic sleeve gastrectomy (LSG) has not yet been clarified. The objective of our study was to investigate the connection between impaired thyroid hormone sensitivity and elevated uric acid (UA) levels before and after LSG. METHODS: In total, 1054 euthyroid patients with obesity (481 males, 573 females), 248 (143 female patients) of whom underwent subsequent LSG, were enrolled in this retrospective study. Anthropometric measurements and thyroid hormone and UA levels were taken before and 3 months after LSG. RESULTS: Female patients with obesity with impaired sensitivity to thyroid hormones had higher UA levels (P for trend <.01). The odds ratio of the fourth vs first quartile of thyroid feedback quantile index, thyrotropin index, and thyrotropin-thyroxine resistance index were 4.285 (confidence interval: 1.360-13.507), 3.700 (confidence interval: 1.276-10.729), and 2.839 (confidence interval: 1.014-7.948), respectively, with robust relationships with female hyperuricemia (all P < .05). However, there was only a positive correlation between the decline in UA levels and thyroid feedback quantile index, thyrotropin, and thyrotropin-thyroxine resistance index in female patients following LSG. CONCLUSION: Female hyperuricemia is correlated with higher thyroid hormone resistance index scores. Resistance to thyroid hormones was greatly improved by LSG. The decrease in UA levels after surgery is correlated with the improvement of thyroid hormone resistance after LSG.

Dielectric Barrier Discharge Plasma-Assisted Preparation of Chitosan-Based Hydrogels.

Chitosan is widely used in the production of various hydrogels due to its non-biological toxicity, good biocompatibility, and strong biodegradability. However, chitosan-based hydrogels have not been widely used in tissue engineering due to their poor mechanical strength, poor stability and high biotoxicity of cross-linking agents. As a green technology, low temperature plasma is rich in active groups that can be involved in various chemical reactions, such as replacing the components on the chitosan chain, contributing to the cross-linking of chitosan. In this study, a plasma-assisted preparation method of chitosan-based hydrogels was developed and the properties, including mechanics, water absorption, and degradation (or stability), were characterized and analyzed. It is proved that plasma treatment plays a significant role in improving the mechanical strength and stability of hydrogels.

USP40 promotes hepatocellular carcinoma cell proliferation, migration and stemness by deubiquitinating and stabilizing Claudin1.

BACKGROUND: Hepatocellular carcinoma (HCC) is a prevalent malignant tumor that poses a major threat to people's lives and health. Previous studies have found that multiple deubiquitinating enzymes are involved in the pathogenesis of HCC. The purpose of this work was to elucidate the function and mechanism of the deubiquitinating enzyme USP40 in HCC progression. METHODS: The expression of USP40 in human HCC tissues and HCC cell lines was investigated using RT-qPCR, western blotting and immunohistochemistry (IHC). Both in vitro and in vivo experiments were conducted to determine the crucial role of USP40 in HCC progression. The interaction between USP40 and Claudin1 was identified by immunofluorescence, co-immunoprecipitation and ubiquitination assays. RESULTS: We discovered that USP40 is elevated in HCC tissues and predicts poor prognosis in HCC patients. USP40 knockdown inhibits HCC cell proliferation, migration and stemness, whereas USP40 overexpression shows the opposite impact. Furthermore, we confirmed that Claudin1 is a downstream gene of USP40. Mechanistically, USP40 interacts with Claudin1 and inhibits its polyubiquitination to stabilize Claudin1 protein. CONCLUSIONS: Our study reveals that USP40 enhances HCC malignant development by deubiquitinating and stabilizing Claudin1, suggesting that targeting USP40 may be a novel approach for HCC therapy.

Early bone loss in patients with obstructive sleep apnea: a cross-sectional study.

BACKGROUND: Obstructive sleep apnea (OSA) and osteoporosis are both prevalent diseases with shared pathophysiological mechanisms and risk factors. However, the association between the two diseases is seldom studied. This study aimed to identify the link between OSA and bone metabolism. METHODS: Male participants aged 30-59-years who visited the sleep clinic were continuously recruited. Polysomnography was used to evaluate sleep and respiratory conditions. Blood samples were collected to detect metabolic, inflammatory and bone turnover indicators. High-resolution peripheral quantitative computer tomography was used to measure the non-dominant lateral radius and tibia. RESULTS: Ninety subjects were recruited. The cortical area (Ct.Ar) of tibia of the severe OSA group was significantly higher than that of the mild and moderate OSA groups (P = 0.06 and P = 0.048). There were significant differences between the four groups in terms of total volumetric bone mineral density (vBMD) (F = 2.990, P = 0.035), meta trabecular vBMD (F = 3.696, P = 0.015), trabecular thickness (Tb.Th) (F = 7.060, P = 0.000) and cortical thickness (Ct.Th) (F = 4.959, P = 0.003). The mean values of the OSA groups were lower than control group. Hypopnea index and percentage of total sleep time with SpO2 < 90% were both positively correlated with alkaline phosphatase (R = 0.213, P = 0.044; R = 0.212, P = 0.045). Sleep efficiency was correlated with multiple indicators of the radius. CONCLUSIONS: In non-elderly male populations, OSA patients tended to have lower vBMD, Tb.Th and Ct.Th than non-OSA patients. The negative effect of OSA may mainly affect the osteogenesis process, and is presumed to be related to sleep-related hypoxemia and sleep efficiency.

The potential interaction between chemosensitivity and the development of cardiovascular disease in obstructive sleep apnea.

OBJECTIVES: Chemosensitivity is an essential part of the pathophysiological mechanisms of obstructive sleep apnea (OSA). Not only does OSA have a certain relationship with the comorbidity of cardiovascular disease (CVD) but also chemosensitivity plays a crucial role in the development of CVD. This study aims to investigate the potential interaction between chemosensitivity and the development of CVD in OSA. METHODS: A total of 169 participants with suspected OSA were included. Data were gathered on the parameters of polysomnography and baseline clinical features. Peripheral chemosensitivity was evaluated by employing the rebreathing test. The lifetime CVD risk was computed using the China-PAR (Prediction for atherosclerotic CVD Risk in China) risk equation. RESULTS: After controlling for covariates, participants with chemosensitivity levels in the second and fifth quantiles tended to hold an increased proportion of high lifetime CVD risk (OR 10.90, 95%CI [2.81-42.28]; OR 6.78, 95%CI [1.70-27.05], respectively). The diagnosis of OSA would significantly increase the 10-year and lifetime CVD risks in participants with low chemosensitivity, while no such differences were found in participants with high chemosensitivity. CONCLUSION: Higher lifetime CVD risk was associated with participants who had greater peripheral chemosensitivity. In terms of the CVD outcomes, adult patients with a relatively low level of chemosensitivity may be primarily related to their diagnosis of OSA, whereas adult patients with a relatively high level of chemosensitivity may be more strongly associated with their elevated levels of chemosensitivity rather than OSA.

The convenient method and application for monitoring the health of traffic sign poles based on mobile phone.

Traffic sign poles are crucial components of the highway system, and their maintenance mainly relies on the subjective judgment of staff, which is low-efficiency and will lead to mistaken inspections. This paper proposes a convenient and effective method to monitor the health of sign poles by using a mobile phone. It is unknown whether a mobile phone can be used as a conventional acceleration sensor. Therefore, the performance of the mobile phone was initially tested to ensure its suitability for acquiring the acceleration data of the traffic sign pole. The results show that the acceleration sensor of mobile phones is high-performance and can be used as a traditional acceleration sensor under the similar sampling frequency. The mobile phone can measure the 1st, 2nd and 5th natural frequencies of the traffic sign pole. Although the 1st and 5th natural frequencies have a large error with simulation, the 2nd natural frequency is accurate and stable. The looseness of the base connection greatly impacts on the 2nd natural frequency, which can be used as a measure of the loose base connection. The 2nd natural frequency was measured for 21 times and found to conform to a normal distribution. The relationship between the 2nd natural frequency and base connection loosening was investigated, which fitted to the equation. The fitting result is good and can be used to predict the degree of sign pole base connection loosening. Therefore, the mobile phone based convenient health monitoring method for traffic sign poles is feasible.

Redefining Comorbid Insomnia and Sleep Apnea: The Association of Sleep Breathing Impairment and Insomnia with Incident Diabetes.

Rationale: Obstructive sleep apnea (OSA) is a prevalent sleep disorder that is frequently comorbid with insomnia and often accompanied by metabolic diseases such as type 2 diabetes. Although the apnea-hypopnea index (AHI) is currently the diagnostic criterion for gauging the severity of OSA, the AHI has not consistently predicted incident diabetes. Objectives: To test whether a combined insomnia-OSA (COMISA) phenotype based on comorbid insomnia and sleep breathing impairment index (COMISA-SBII) predicts incident diabetes and to compare the association with an AHI definition of COMISA (COMISA-AHI) in the MrOS (Osteoporotic Fractures in Men) study. Methods: The study samples came from participants in the MrOS sleep study without diabetes at their baseline examination. The SBII was derived as the product of the duration of each respiratory event (apnea and hypopnea) and the accompanying desaturation area from baseline unattended polysomnography. A subgroup of individuals classified as having comorbid insomnia (difficulties falling asleep, waking up in the middle of the night and/or early morning awakenings >15 times per month, and daytime impairments) and sleep breathing impairment (greater than 50th percentile of SBII) were identified at baseline. The primary outcome was incident diabetes during the follow-up visits. Cox proportional models were built to assess the adjusted hazard ratios of COMISA-AHI and COMISA-SBII. Prediction model performances of incident diabetes were compared across different models. Results: A total of 2,365 men (mean age, 76 yr) without diabetes at baseline were included. During a median follow-up of 10.0 years, diabetes developed in 181. After adjusting for demographic characteristics, comorbidities, and behavioral risk factors, participants with COMISA-SBII had a higher risk of incident diabetes (hazard ratio, 1.82; 95% confidence interval, 1.15-2.89) than those without sleep disorders (those with an SBII ⩽13.17 and no insomnia). The result remained significant in the risk competing model. Compared with COMISA-AHI, the addition of COMISA-SBII to a crude model with established risk factors significantly improved the predictive value of incident diabetes. Conclusions: COMISA-SBII, but not COMISA-AHI, predicted incident diabetes after accounting for multiple covariates in a cohort of older men. A comorbid insomnia phenotype based on SBII plus insomnia symptoms may be an important clinical subtype.

A Lightweight convolutional neural network for nicotine prediction in tobacco by near-infrared spectroscopy.

The content of nicotine, a critical component of tobacco, significantly influences the quality of tobacco leaves. Near-infrared (NIR) spectroscopy is a widely used technique for rapid, non-destructive, and environmentally friendly analysis of nicotine levels in tobacco. In this paper, we propose a novel regression model, Lightweight one-dimensional convolutional neural network (1D-CNN), for predicting nicotine content in tobacco leaves using one-dimensional (1D) NIR spectral data and a deep learning approach with convolutional neural network (CNN). This study employed Savitzky-Golay (SG) smoothing to preprocess NIR spectra and randomly generate representative training and test datasets. Batch normalization was used in network regularization to reduce overfitting and improve the generalization performance of the Lightweight 1D-CNN model under a limited training dataset. The network structure of this CNN model consists of four convolutional layers to extract high-level features from the input data. The output of these layers is then fed into a fully connected layer, which uses a linear activation function to output the predicted numerical value of nicotine. After the comparison of the performance of multiple regression models, including support vector regression (SVR), partial least squares regression (PLSR), 1D-CNN, and Lightweight 1D-CNN, under the preprocessing method of SG smoothing, we found that the Lightweight 1D-CNN regression model with batch normalization achieved root mean square error (RMSE) of 0.14, coefficient of determination (R 2) of 0.95, and residual prediction deviation (RPD) of 5.09. These results demonstrate that the Lightweight 1D-CNN model is objective and robust and outperforms existing methods in terms of accuracy, which has the potential to significantly improve quality control processes in the tobacco industry by accurately and rapidly analyzing the nicotine content.

A retrospective study of the role of hypercapnia in patients with acromegaly.

BACKGROUND: Acromegaly is a multisystemic disease characterized by an excessive release of growth hormone (GH) and insulin-like growth factor-1. Obstructive sleep apnea (OSA) is a common consequence of acromegaly, and hypercapnia is frequently observed in patients with acromegaly, OSA, and obesity. However, the effects of hypercapnia on acromegaly remain unknown. This study was designed to investigate whether there are differences in clinical symptoms, sleep variables, and biochemical remission after surgery for acromegaly in patients with OSA with or without hypercapnia. METHODS: A retrospective analysis was conducted involving patients with acromegaly and OSA. The pharmacotherapy history for acromegaly before surgery, anthropometric measures, blood gas, sleep monitoring data, and biochemical assays of hypercapnic and eucapnic individuals were collected 1-2 weeks before surgery. Univariate and multivariate logistic regression analyses were performed to determine the risk factors for failed postoperative biochemical remission. RESULTS: In this study, 94 patients with OSA and acromegaly were included. Among them, 25 (26.6%) had hypercapnia. The hypercapnic group had higher body mass index (92% vs. 62.3%; p = 0.005) and poorer nocturnal hypoxemia index. No serological differences were found between the two groups. According to the post-surgery GH level, 52 patients (55.3%) reached biochemical remission. Univariate logistic regression analysis revealed that diabetes mellitus (odds ratio [OR], 2.59; 95% confidence interval [CI], 1.02-6.55), instead of hypercapnia (OR, 0.61; 95% CI, 0.24-1.58), was associated with lower remission rates. Patients who received pharmacotherapy for acromegaly before surgery (OR, 0.21; 95% CI, 0.06-0.79) and had higher thyroid-stimulating hormone levels (OR, 0.53; 95% CI, 0.32-0.88) were more likely to have biochemical remission after surgery. Multivariate analysis further showed that only diabetes mellitus (OR, 3.29; 95% CI, 1.15-9.46) and preoperative pharmacotherapy (OR, 0.21; 95% CI, 0.06-0.83) remained significant. Hypercapnia, hormone levels, and sleep indicators had no effect on biochemical remission after surgery. CONCLUSIONS: Single-center evidence shows that hypercapnia alone may not be a risk factor for lower biochemical remission rates. Correcting hypercapnia does not appear to be required before surgery. More evidence is needed to further support this conclusion.

Shorter respiratory event duration is related to prevalence of type 2 diabetes.

Background: Obstructive sleep apnea (OSA) is a heterogeneous sleep disorder often comorbid with metabolic diseases, and type 2 diabetes (T2DM) is one of them. Although apnea hypopnea index (AHI) is currently the diagnostic criteria for OSA severity, a controversial relationship between AHI and T2DM has been found. On the other hand, the duration of apnea-hypopnea events has been shown to be a useful metric for predicting mortality. This study aimed to test whether average respiratory event duration was associated with prevalence of T2DM. Methods: Patients referred to the sleep clinic were recruited in the study. Baseline clinical characteristics and polysomnography parameters including average respiratory event duration were collected. The association of average respiratory event duration with the prevalence of T2DM was evaluated by univariate and multivariate logistic regression analyses. Results: A total of 260 participants were enrolled, and 92 (35.4%) had T2DM. Univariate analysis revealed that age, body mass index (BMI), total sleep time, sleep efficiency, history of hypertension, and shorter average respiratory event duration were associated with T2DM. In multivariate analysis, only age and BMI remained significant. While average respiratory event duration was insignificant in multivariate analysis, subtype event analysis showed that shorter average apnea duration was both significant in univariate (OR, 0.95; 95% CI, 0.92-0.98) and multivariate analyses (OR, 0.95; 95% CI, 0.91-0.99). Neither average hypopnea duration nor AHI was associated with T2DM. Significant association (OR, 1.19; 95% CI, 1.12-1.25) was observed between shorter average apnea duration and lower respiratory arousal threshold after multivariate adjustment. However, causal mediation analysis revealed no mediating effect of arousal threshold on average apnea duration and T2DM. Conclusion: The average apnea duration may be a useful metric in the diagnosis of OSA comorbidity. Shorter average apnea duration indicating poor sleep quality and augmented autonomic nervous system responses might be the potential pathological mechanisms leading to T2DM.

New Metrics from Polysomnography: Precision Medicine for OSA Interventions.

Obstructive sleep apnea (OSA) is a highly preventable disease accompanied by multiple comorbid conditions. Despite the well-established cardiovascular and neurocognitive sequelae with OSA, the optimal metric for assessing the OSA severity and response to therapy remains controversial. Although overnight polysomnography (PSG) is the golden standard for OSA diagnosis, the abundant information is not fully exploited. With the development of deep learning and the era of big data, new metrics derived from PSG have been validated in some OSA consequences and personalized treatment. In this review, these metrics are introduced based on the pathophysiological mechanisms of OSA and new technologies. Emphasis is laid on the advantages and the prognostic value against apnea-hypopnea index. New classification criteria should be established based on these metrics and other clinical characters for precision medicine.

The association between urinary polycyclic aromatic hydrocarbon metabolites and liver function among US population: a cross-sectional study.

Most studies have focused on the pulmonary toxicity of inhaled PAHs to date; therefore, their hepatotoxic consequences are yet unknown. The main aim of this study is to examine the association between urinary polycyclic aromatic hydrocarbons (PAHs) and liver function parameters among the US population. The data included in this study were from the National Health and Nutritional Examination Survey (NHANES) 2003-2016. Finally, we included 2515 participants from seven cycles of the NHANES. Logistic regression was performed to calculate the association between each PAH and liver function parameters (elevated vs. normal) with odds ratio (OR) and 95% confidence intervals (CIs), along with adjustment for confounding variables. P < 0.05 was considered to indicate a statistically significant difference. All analyses were performed using R software 4.0.1. In the present study, all 2515 individuals were aged ≥ 18 years, 1211 males, and 1304 females. The average age normal was 45.56 ± 20.20, and the elevated was 46.04 ± 19.73 years, respectively. The results of logistic regression indicated that increased 9-hydroxyfluorene (OR = 2.11, 95% CI = [1.52, 2.95], P < 0.001), 2-hydroxyfluorene (OR = 1.61, 95% CI = [1.23, 2.11], P < 0.001), and 3-hydroxyfluorene (OR = 1.54, 95% CI = [1.21, 1.95], P < 0.001) were associated with elevated GGT. In conclusion, 9-hydroxyfluorene is associated with elevated GGT level, and the effect of 9-hydroxyfluorene on GGT is modified by other PAHs, which means that 9-hydroxyfluorene has a greater influence on GGT when other PAHs are increased.

Preparation of Functionalized Zr-Based MOFs and MOFs/GO for Efficient Removal of 1,3-Butadiene from Cigarette Smoke.

Removal of 1,3-butadiene from cigarette smoke plays an important role in human health and environmental protection. Herein, a series of UiO-66 X% containing different ratios of the -NH2 group was synthesized via the solvothermal method by using terephthalic acid (H2BDC) and 2-aminoterephthalic acid (NH2-BDC) as ligands. Using GO as support, a series of UiO-66-NH2/GO Y% were prepared by controlling the ratio of UiO-66-NH2 and GO. The effects of -NH2 and GO contents on the structure and composition of MOFs were investigated. Finally, the different -NH2 contents of UiO-66 X% and the different GO contents of UiO-66-NH2/GO Y% were applied in 1,3-butadiene removal from cigarette smoke. The results showed that UiO-66 X% with the higher contents of -NH2 showed a higher rate of 1,3-butadiene removal, and UiO-66-NH2/GO Y% with the GO contents of 5% showed the highest removal rate of about 33.85%, which was 25.54% higher than that of activated carbon. In addition, the saturation capacity of the adsorbent materials for 1,3-butadiene was as high as 210.01-239.54 mg/g, showing great potential in reducing harmful components in cigarette smoke and environmental protection.

Just-in-Time Learning-Integrated Partial Least-Squares Strategy for Accurately Predicting 71 Chemical Constituents in Chinese Tobacco by Near-Infrared Spectroscopy.

Near-infrared spectroscopy has been widely used to characterize the chemical composition of tobacco because it is fast, economical, and nondestructive. However, few predictive models perform ideally when applied to large spectral libraries of tobacco and its various chemical indicators. In this study, the just-in-time learning-integrated partial least-squares (JIT-PLS) modeling strategy was applied for the first time to quantitatively analyze 71 chemical components in Chinese tobacco. Approximately 18000 tobacco samples from China were analyzed to find appropriately similar measurements and propose suitable and flexible similar subsets from the calibration for each test sample. In total, 879 representative aged tobacco leaf samples and 816 cigarette samples were used as external instances to evaluate the practical predicting ability of the proposed method. The most suitable similar subsets for each test sample could be selected by limiting the Euclidean distance and number of similar subsets to 0-3.0 × 10-9 and 10-300, respectively. The majority of the JIT-PLS models performed significantly better than traditional PLS models. Specifically, using JIT-PLS instead of traditional PLS models increased the R 2 values from 0.347-0.984 to 0.763-0.996, and from 0.179-0.981 to 0.506-0.989 for the prediction of 67 and 71 components in aged tobacco leaf and cigarette samples, respectively. Good prediction ability was demonstrated for routine chemical components, polyphenolic compounds, organic acids, and other compounds, with the mean ratios of prediction to deviation (RPDmean) being 7.74, 4.39, 4.05, and 5.48, respectively). The proposed methodology could simultaneously determine 67 major components in large and complicated tobacco spectral libraries with high precision and accuracy, which will assist tobacco and cigarette quality control in collecting as well as processing stages.

Design and experimental research of a 28 GHz TE01 mode 160° miter bend for electron cyclotron resonance ion source.

In this paper, a 28 GHz TE01 mode 160° miter bend employing two plane mirrors is proposed based on the quasi-optical technique and the coupled wave theory to realize high-efficiency transmission for the electron cyclotron resonance ion source. First, the TE01 mode was converted to TE0n hybrid modes with Gaussian beam characteristics by means of the designed mode converter. Second, the phase shift section was implemented to eliminate the phase difference of the hybrid modes. Then, upon reflection of two plane mirrors, the propagation direction of a wave beam is deviated by 160°. Finally, the hybrid modes were converted to the TE01 mode using the same structures of the phase shift section and the mode converter. The simulation results reveal that the TE01 mode transmission efficiency reaches 95.22% at the central frequency of 28 GHz. Additionally, the designed 160° miter bend has been fabricated, installed, and measured. The experimental results show that the power transmission efficiency reaches 98.54% including diffraction losses and ohmic losses.

Simultaneous analysis of multiple pesticide residues in tobacco by magnetic carbon composite-based QuEChERS method and liquid chromatography coupled to quadrupole time-of-flight mass spectrometry.

Magnetic carbon composite (Fe3O4@C) was synthesized and applied as a reversed-dispersive solid-phase extraction sorbent for the simultaneous analysis of 40 pesticide residues in tobacco by ultrahigh-performance liquid chromatography coupled to quadrupole time-of-fight mass spectrometry. Compared to the traditional QuEChERS method, the optimized Fe3O4@C simplified clean-up process and exhibited better clean-up capability than conventional sorbents. The pesticides were qualitatively identified by accurate mass of protonated molecules, fragment ions, isotopic peak clusters, and retention time, and quantitatively determined by matrix-matched external standard method. Good linearity of the proposed method was obtained with R value greater than 0.997 for all target pesticides at concentration levels of 2-200 µg/L. The limit of detection ranged from 0.14 to 2.67 µg/kg. The recoveries and relative standard deviations of all target pesticides at three spiked concentrations of 20, 50 and 200 µg/kg were in the ranges of 80.8%-113.3% and 0.6%-16.3%, respectively. Compared with the reported methods for the analysis of multiple pesticide residues in tobacco, the proposed method has the advantages of simple to operate, high clean-up ability and less time-consuming in clean-up process.