Underwater motion scene image restoration based on an improved U-Net network.

Active underwater polarization imaging is a common underwater imaging method, which uses the polarization difference between the reflected light and the scattered light in the underwater scene to suppress the scattered light, so as to improve the imaging quality of the underwater scene. However, the implementation often requires the acquisition of multiple polarization images, which is not suitable for the restoration of images of underwater motion scenes. To address the problem, a U-AD-Net deep learning network model based on a single polarized image is proposed, taking the polarization information of the single polarized image as the feature input, based on the classic U-Net network model, and introducing Dense-Net and spatial attention module. The learning ability and generalization ability of the proposed model for deep features are enhanced, and the polarization information that is most helpful to the image restoration is extracted, so as to restore the scene image more comprehensively. IE, AG, UCIQE, and SSIM are selected as evaluation metrics to assess the quality of the restored images. Experimental results show that the images restored through this proposed method contain richer detail information, having an obvious advantage to the existing network models. Since only a single polarized image is needed for restoration, this method has dynamic adaptability to underwater moving scene restoration.

Association of serum vitamin C levels with Asthma in adults: results of NHANES 2003-2006 and mendelian randomization study.

BACKGROUND: The protective effect of vitamin C as an antioxidant against asthma in adults remains controversial. This study used an observational study and Mendelian randomization (MR) analysis to investigate the association between adult asthma and serum vitamin C levels. METHODS: Using information from the National Health and Nutrition Examination Survey (NHANES) 2003-2006, we carried out an observational study. A multivariate logistic regression model was employed to examine the connection between adult asthma and serum vitamin C levels. We used the inverse-variance weighted (IVW) method of MR analysis as the primary method to analyze the causal effect of serum vitamin C levels on asthma in adults. RESULTS: A total of 8,504 participants were included in the observational study, including 639 in the asthma group and 7,865 in the non-asthma group. Before sample weighting, serum vitamin C was associated with a reduced risk of asthma in adults (OR = 0.798, 95% CI: 0.673-0.945, P = 0.009). After sample weighting, serum vitamin C was not associated with adult asthma risk (OR = 0.829, 95% CI: 0.660 ~ 1.042, P = 0.104). MR analysis showed no causal relationship between serum vitamin C and adult asthma in either the UK Biobank (OR = 0.957, 95% CI: 0.871 ~ 1.053, P = 0.370) or FinnGen (OR = 0.973, 95% CI: 0.824 ~ 1.149, P = 0.750) cohorts. CONCLUSION: Our study did not support a causal association between serum vitamin C levels and adult asthma risk. The relationship between serum vitamin C and adult asthma requires further research.

Converting Plastic Wastes to Naphtha for Closing the Plastic Loop.

To solve the serious environmental problem and huge resource waste of plastic pollution, we report a tandem catalytic conversion of low-density polyethylene (LDPE) into naphtha, the key feedstock for renewable plastic production. Using ß zeolite and silicalite-1-encapsulated Pt nanoparticles (Pt@S-1), a naphtha yield of 89.5% is obtained with 96.8% selectivity of C5-C9 hydrocarbons at 250 °C. The acid sites crack long-chain LDPE into olefin intermediates, which diffuse within the channels of Pt@S-1 to encounter Pt nanoparticles. The hydrogenation over confined metal matches cracking steps by selectively shipping the olefins with right size, and the rapid diffusion boosts the formation of narrow-distributed alkanes. A conceptual upgrading indicates it is suitable for closing the plastic loop, with a significant energy saving of 15% and 30% reduced greenhouse gas emissions.

Flexible Self-Powered Sensing System Based on Novel DNA Circuit Strategy and Graphdiyne for Thalassemia Gene by Rapid Naked-Eye Tracking and Open-Circuit Voltage.

Based on the controllable instantaneous self-assembly ability of long-chain branched DNA nanostructures and the synergistic effect between nucleic acid amplification without enzymes, a highly sensitive and highly specific self-powered biosensing platform is developed. Two-dimensional graphdiyne is prepared, modified on flexible carbon cloth, and then functionalized with gold nanoparticles. When DNA mi-tubes are applied on it, target thalassemia gene CD122 triggers a dual-catalytic hairpin assembly reaction. The generated nanoscale DNA is precisely captured by the DNA mi-tube, exposing binding sites and activating the hybridization chain reaction to form long-chain branched DNA. Double-stranded DNA, along with dendritic DNA carrying a large number of guanine bases, precisely captures the signal molecule methylene blue (MB), generating a significant electrochemical signal. The redox reaction of MB also causes a proportional change in the system's color, achieving a colorimetric detection functionality. An efficient dual-mode self-powered sensing platform, therefore, is established for detecting the thalassemia gene CD122. The linear response range of target concentration to open-circuit voltage and RGB Blue value is 0.0001-10,000 pM. The detection limit under electrochemical mode is 36.3 aM (S/N = 3), and under colorimetric mode, it is as low as 12.1 aM (S/N = 3). The new method exhibits high sensitivity, excellent selectivity, and high accuracy, providing a universal strategy for designing novel biosensing platforms that can be extended to the detection of other biomolecules.

CA916798 predicts poor prognosis and promotes Gefitinib resistance for lung adenocarcinoma.

BACKGROUND: Our previous studies have identified CA916798 as a chemotherapy resistance-associated gene in lung cancer. However, the histopathological relevance and biological function of CA916798 in lung adenocarcinoma (LUAD) remains to be delineated. In this study, we further investigated and explored the clinical and biological significance of CA916798 in LUAD. METHODS: The relationship between CA916798 and clinical features of LUAD was analyzed by tissue array and online database. CCK8 and flow cytometry were used to measure cell proliferation and cell cycle of LUAD after knockdown of CA916798 gene. qRT-PCR and western blotting were used to detect the changes of cell cycle-related genes after knockdown or overexpression of CA916798. The tumorigenesis of LUAD cells was evaluated with or without engineering manipulation of CA916798 gene expression. Response to Gefitinib was evaluated using LUAD cells with forced expression or knockdown of CA916798. RESULTS: The analysis on LUAD samples showed that high expression of CA916798 was tightly correlated with pathological progression and poor prognosis of LUAD patients. A critical methylation site in promoter region of CA916798 gene was identified to be related with CA916798 gene expression. Forced expression of CA916798 relieved the inhibitory effects of WEE1 on CDK1 and facilitated cell cycle progression from G2 phase to M phase. However, knockdown of CA916798 enhanced WEE1 function and resulted in G2/M phase arrest. Consistently, chemical suppression of CDK1 dramatically inhibited G2/M phase transition in LUAD cells with high expression of CA916798. Finally, we found that CA916798 was highly expressed in Gefitinib-resistant LUAD cells. Exogenous expression of CA916798 was sufficient to endow Gefitinib resistance with tumor cells, but interference of CA916798 expression largely rescued response of tumor cells to Gefitinib. CONCLUSIONS: CA916798 played oncogenic roles and was correlated with the development of Gefitinib resistance in LUAD cells. Therefore, CA916798 could be considered as a promising prognostic marker and a therapeutic target for LUAD.

Pneumonia-Plus: a deep learning model for the classification of bacterial, fungal, and viral pneumonia based on CT tomography.

OBJECTIVES: This study aims to develop a deep learning algorithm, Pneumonia-Plus, based on computed tomography (CT) images for accurate classification of bacterial, fungal, and viral pneumonia. METHODS: A total of 2763 participants with chest CT images and definite pathogen diagnosis were included to train and validate an algorithm. Pneumonia-Plus was prospectively tested on a nonoverlapping dataset of 173 patients. The algorithm's performance in classifying three types of pneumonia was compared to that of three radiologists using the McNemar test to verify its clinical usefulness. RESULTS: Among the 173 patients, area under the curve (AUC) values for viral, fungal, and bacterial pneumonia were 0.816, 0.715, and 0.934, respectively. Viral pneumonia was accurately classified with sensitivity, specificity, and accuracy of 0.847, 0.919, and 0.873. Three radiologists also showed good consistency with Pneumonia-Plus. The AUC values of bacterial, fungal, and viral pneumonia were 0.480, 0.541, and 0.580 (radiologist 1: 3-year experience); 0.637, 0.693, and 0.730 (radiologist 2: 7-year experience); and 0.734, 0.757, and 0.847 (radiologist 3: 12-year experience), respectively. The McNemar test results for sensitivity showed that the diagnostic performance of the algorithm was significantly better than that of radiologist 1 and radiologist 2 (p < 0.05) in differentiating bacterial and viral pneumonia. Radiologist 3 had a higher diagnostic accuracy than the algorithm. CONCLUSIONS: The Pneumonia-Plus algorithm is used to differentiate between bacterial, fungal, and viral pneumonia, which has reached the level of an attending radiologist and reduce the risk of misdiagnosis. The Pneumonia-Plus is important for appropriate treatment and avoiding the use of unnecessary antibiotics, and provide timely information to guide clinical decision-making and improve patient outcomes. CLINICAL RELEVANCE STATEMENT: Pneumonia-Plus algorithm could assist in the accurate classification of pneumonia based on CT images, which has great clinical value in avoiding the use of unnecessary antibiotics, and providing timely information to guide clinical decision-making and improve patient outcomes. KEY POINTS: • The Pneumonia-Plus algorithm trained from data collected from multiple centers can accurately identify bacterial, fungal, and viral pneumonia. • The Pneumonia-Plus algorithm was found to have better sensitivity in classifying viral and bacterial pneumonia in comparison to radiologist 1 (5-year experience) and radiologist 2 (7-year experience). • The Pneumonia-Plus algorithm is used to differentiate between bacterial, fungal, and viral pneumonia, which has reached the level of an attending radiologist.

Development and External Validation of Machine Learning-Based Models for Predicting Lung Metastasis in Kidney Cancer: A Large Population-Based Study.

The accuracy of indices widely used to evaluate lung metastasis (LM) in patients with kidney cancer (KC) is insufficient. Therefore, we aimed at developing a model to estimate the risk of developing LM in KC based on a large population size and machine learning algorithms. Demographic and clinicopathologic variables of patients with KC diagnosed between 2004 and 2017 were retrospectively analyzed. We performed a univariate logistic regression analysis to identify risk factors for LM in patients with KC. Six machine learning (ML) classifiers were established and tuned using the ten-fold cross-validation method. External validation was performed using clinicopathologic information from 492 patients from the Southwest Hospital, Chongqing, China. Algorithm performance was estimated by analyzing the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, precision, recall, F1 score, clinical decision analysis (DCA), and clinical utility curve (CUC). A total of 52,714 eligible patients diagnosed with KC were enrolled, of whom 2,618 developed LM. Variables of age, sex, race, T stage, N stage, tumor size, histology, and grade were identified as important for the prediction of LM. The extreme gradient boosting (XGB) algorithm performed better than other models in both the internal validation (AUC: 0.913, sensitivity: 0.873, specificity: 0.809, and F1 score: 0.325) and the external validation (AUC: 0.904, sensitivity: 0.750, specificity: 0.878, and F1 score: 0.364). This study established a predictive model for LM in KC patients based on ML algorithms which showed high accuracy and applicative value. A web-based predictor was built using the XGB model to help clinicians make more rational and personalized decisions.

Biomechanical evaluation of reconstruction of the posterior complex in restorative laminoplasty with miniplates.

OBJECTIVE: To evaluate the biomechanical effects of different miniplates on restorative laminoplasty. METHODS: Assembled restorative laminoplasty models were developed based on 3D printed L4 lamina. Based on different internal fixations, the research was divided into H-shaped miniplates (HSMs) group, two-hole miniplates (THMs) group, and L-shaped miniplates (LSMs) group. The static and dynamic compression tests were analyzed to investigate the biomechanical effects of different internal fixations in restorative laminoplasty, until the failure and fracture of miniplates, or the collapse of miniplates. The static compression tests adopted the speed control mode, and the dynamic fatigue compression tests adopted the load control mode. RESULTS: The "door close" and the collapse of lamina occurred in THMs group and LSMs group, and plate break occurred in LSMs group. However, these phenomenon was absent in HSMs group, and only plate crack around a screw and looseness of a screw tail cap were found in HSMs group. The sustainable yield load of HSMs group was greater than that of THMs group and LSMs group (P < 0.05). No significant difference in yielding-displacement was found between HSMs group and LSMs group (P > 0.05), while both were much less than that of THMs (P < 0.05). Moreover, the compressive stiffness and the axial displacement under the same mechanical load were arranged as follows: HSMs group > LSMs group > THMs group (P < 0.05). The results of dynamic compression test revealed that the peak load of HSMs group could reached 873 N and was 95% of the average yield load of the static compression, and was better than that in THMs group and LSMs group (P < 0.05). Besides, according to the fatigue life-peak load diagram, the ultimate load of HSMs group was more than twice that of THMs group or LSMs group. CONCLUSIONS: The mechanical strength of H-shaped miniplates was superior to two-hole miniplates and L-shaped miniplates in maintaining spinal canal enlargement and spinal stability, and was more excellent in fatigue stability and ultimate load.

Superior performance of a graphdiyne self-powered biosensor with exonuclease III-assisted signal amplification for sensitive detection of microRNAs.

Graphdiyne (GDY) is an sp and sp2 co-hydrocarbon allotrope whose particular structure endows it with many fascinating properties, including abundant chemical bonds, high conjugation, natural pores, high carrier mobility, high conductivity and stability, etc. In this work, two-dimensional graphdiyne is prepared as an electrode substrate material coupling with an exonuclease III-assisted amplification strategy to construct a superior-performance self-powered biosensor based on enzymatic biofuel cells for highly sensitive detection of the tumour marker miRNA-21. Glucose oxidase (GOD) is first immobilized on the GDY/AuNP composite to prepare a bioconjugate. GDY/AuNP modified carbon cloth is used as an enzyme biofuel cell electrode, which is then modified with bilirubin oxidase as a biocathode. The bioconjugate binds to GOD through specific binding to the bioanode. When miRNA-21 is present, specific recognition by exonuclease III in the system results in cleavage of the capture probe, and miRNA-21 is recovered and involved in the cycle. The target miRNA-21 then causes corresponding changes in the open-circuit voltage of the self-powered system. Based on this, a sensitive detection method was constructed, within the scope from 0.1 fM to 0.1 nM with a shallow detection limit of 55.2 aM (S/N = 3). The new approach triumphantly has been used to detect miRNA-21 in serum, which provides a compelling new way for early diagnosis of related cancers.

Multidimensional Evaluation of All-Cause Mortality Risk and Survival Analysis for Hospitalized Patients with COVID-19.

Background: Coronavirus disease 2019 (COVID-19) has caused over 3.8 million deaths globally. Up to date, the number of death in 2021 is more than that in 2020 globally. Here, we aimed to compare clinical characteristics of deceased patients and recovered patients, and analyze the risk factors of death to help reduce mortality of COVID-19. Methods: In this retrospective study, a total of 2719 COVID-19 patients were enrolled, including 109 deceased patients and 2610 recovered patients. Medical records of all patients were collected between February 4, 2020, and April 7, 2020. Clinical characteristics, laboratory indices, treatments, and deep-learning system- assessed lung lesion volumes were analyzed. The effect of different medications on survival time of fatal cases was also investigated. Results: The deceased patients were older (73 years versus 60 years) and had a male predominance. Nausea (10.1% versus 4.1%) and dyspnea (54.1% versus 39.2%) were more common in deceased patients. The proportion of patients with comorbidities in deceased patients was significantly higher than those in recovered patients. The median times from hospital admission to outcome in deceased patients and recovered patients were 9 days and 13 days, respectively. Patients with severe or critical COVID-19 were more frequent in deceased group. Leukocytosis (11.35×109/L versus 5.60×109/L) and lymphocytopenia (0.52×109/L versus 1.58×109/L) were shown in patients who died. The level of prothrombin time, activated partial prothrombin time, D-dimer, aspartate aminotransferase, alanine aminotransferase, urea, creatinine, creatine kinase, glucose, brain natriuretic peptide, and inflammatory indicators were significantly higher in deceased patients than in recovered patients. The volumes of ground-glass, consolidation, total lesions and total lung in all patients were quantified. Complications were more common in deceased patients than in recovered patients; respiratory failure (57.8%), septic shock (36.7%), and acute respiratory distress syndrome (26.6%) were the most common complications in patients who died. Many treatments were more frequent in deceased patients, such as antibiotic therapy (88.1% versus 53.7%), glucocorticoid treatment (70.6% versus 11.0%), intravenous immunoglobin treatment (36.6% versus 4.9%), invasive mechanical ventilation (62.3% versus 3.8%). Antivirals, antibiotics, traditional Chinese medicines and glucocorticoid treatment may significantly increase the survival time of fatal cases. Quantitative computed tomography imaging results were correlated with biochemical markers. Conclusions: Most patients with fatal outcomes were more likely to have common comorbidities. The leading causes of death were respiratory failure and multiple organ dysfunction syndrome. Acute respiratory distress syndrome, respiratory failure and septic shock were the most common serious complications. Antivirals, antibiotics, traditional Chinese medicines, and glucocorticoid treatment may prolong the survival time of deceased patients with COVID-19.

Vitamin B6 prevents Isocarbophos-induced posterior cerebral artery injury in offspring rats through up-regulating S1P receptor expression.

We have previously reported that the long-term exposure of Isocarbophos, a kind of organophosphorus compounds, induces vascular dementia (VD) in rats. Studies have also shown that organophosphorus compounds have adverse effects on offsprings. Vitamin B6 is a coenzyme mainly involved in the regulation of metabolism and has been demonstrated to ameliorate VD. Sphingosine-1-phosphate (S1P), a biologically active lipid, plays a vital role in the cardiovascular system. However, whether S1P is involved in the therapeutic effects of Vitamin B6 on posterior cerebral artery injury has yet to be further answered. In the present study, we aimed to explore the potential influence of Vitamin B6 on Isocarbophos-induced posterior cerebral artery injury in offspring rats and the role of the S1P receptor in this process. We found that Vitamin B6 significantly improves the vasoconstriction function of the posterior cerebral artery in rats induced by Isocarbophos by the blood gas analysis and endothelium-dependent relaxation function assay. We further demonstrated that Vitamin B6 alleviates the Isocarbophos-induced elevation of ICAM-1, VCAM-1, IL-1, and IL-6 by using the enzyme-linked immunosorbent assay kits. By performing immunofluorescence and the western blot assay, we revealed that Vitamin B6 prevents the down-regulation of S1P in posterior cerebral artery injury. It is worth noting that Fingolimod, the S1P inhibitor, significantly inhibits the Vitamin B6-induced up-regulation of S1P in posterior cerebral artery injury. Collectively, our data indicate that Vitamin B6 may be a novel drug for the treatment of posterior cerebral artery injury and that S1P may be a drug target for its treatment.

Novel model for cancer-specific survival of patients with pulmonary sarcomatoid carcinoma: A population-based analysis and external validation.

BACKGROUND/OBJECTIVE: We aimed to develop a comprehensive and effective nomogram for predicting cancer-specific survival (CSS) in patients with pulmonary sarcomatoid carcinoma (PSC). METHODS: Data for patients diagnosed with PSC between 2004 and 2018 from the Surveillance, Epidemiology, and End Results database were retrospectively collected and randomly divided into training and internal validation sets. We then retrospectively recruited patients diagnosed with PSC to construct an external validation cohort from the Southwest Hospital. A prognostic nomogram for CSS was established using independent prognostic factors that were screened from the multivariate Cox regression analysis. The performance of the nomogram was evaluated using area under the receiver operating characteristic (ROC) curves, Harrell's concordance index (C-index), calibration diagrams, and decision curve analysis (DCA). The clinical value of the nomogram and tumor, nodes, and metastases (TNM) staging system was compared using the C-index and net reclassification index (NRI). RESULTS: Overall, 1356 patients with PSC were enrolled, including 876, 377, and 103 in the training, internal validation, and external validation sets, respectively. The C-index and ROC curves, calibration, and DCA demonstrated satisfactory nomogram performance for CSS in patients with PSC. In addition, the C-index and NRI of the nomogram suggested a significantly higher nomogram value than that of the TNM staging system. Subsequently, a web-based predictor was developed to help clinicians obtain this model easily. CONCLUSIONS: The prognostic nomogram developed in this study can conveniently and precisely estimate the prognosis of patients with PSC and individualize treatment, thereby assisting clinicians in their shared decision-making with patients.

Study on the application of percutaneous closed pleural brushing combined with cell block technique in the diagnosis of malignant pleural effusion.

INTRODUCTION: This study was to investigate the diagnostic value of percutaneous closed pleural brushing (CPBR) followed by cell block technique for malignant pleural effusion (MPE) and the predictive efficacy of pleural fluid carcinoembryonic antigen (CEA) for epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma patients with MPE. METHODS: All patients underwent closed pleural biopsy (CPB) and CPBR followed by cell block examination. MPE-positive diagnostic rates between the two methods were compared. Univariate and multivariate analyses were performed to determine factors influencing the EGFR mutations. Receiver operating characteristic (ROC) curve was used to analyze the predictive efficacy of pleural fluid CEA for EGFR mutations. RESULTS: The cumulative positive diagnostic rates for MPE after single and twice CPBR followed by cell block examination were 80.5% and 89.0%, higher than CPB (45.7%, 54.3%) (P < 0.001). Univariate analysis showed that EGFR mutation was associated with pleural fluid and serum CEA (P < 0.05). Multivariate analysis showed that pleural fluid CEA was an independent risk factor for predicting EGFR mutation (P < 0.001). The area under the curve (AUC) of pleural fluid CEA for EGFR mutation prediction was 0.774, higher than serum CEA (P = 0.043), but no difference with the combined test (P > 0.05). CONCLUSION: Compared with CPB, CPBR followed by the cell block technique can significantly increase the positive diagnostic rate of suspected MPE. CEA testing of pleural fluid after CPBR has a high predictive efficacy for EGFR mutation in lung adenocarcinoma patients with MPE, implying pleural fluid extracted for cell block after CPBR may be an ideal specimen for genetic testing.

A sandwich-type dual-mode biosensor based on graphdiyne and DNA nanoframework for ultra-sensitive detection of CD142 gene.

Thalassemia is a globally prevalent single-gene blood disorder, with nearly 7% of the world's population being carriers. Therefore, the development of specific and sensitive methods for thalassemia detection holds significant importance. Herein, a sandwich-type electrochemical/colorimetric dual-mode biosensor is developed based on gold nanoparticles (AuNPs)/graphdiyne (GDY) and DNA nanoframeworks for ultra-sensitive detection of CD142 gene associated with sickle cell anemia. Utilizing AuNPs/GDY as the substrate electrode, the fabricated sandwiched DNA nanoframework not only improves selectivity but also introduces numerous signal probes to further amplify the output signal. In the electrochemical mode, glucose oxidase catalyzes the oxidation of glucose, generating electrons that are transferred to the biocathode for a reduction reaction, resulting in an electric signal proportional to the target concentration. In the colorimetric mode, glucose oxidase catalyzes the generation of H2O2 from glucose, and with the aid of horseradish peroxidase, H2O2 oxidizes 3,3',5,5'-tetramethylbenzidine to produce a colored product, enabling colorimetric detection of the target. The dual-mode biosensor demonstrates a detection range of 0.0001-100 pM in the electrochemical mode and a detection range of 0.0001-10,000 pM in the colorimetric mode. The detection limit in the electrochemical mode is determined to be 30.4 aM (S/N=3), while in the colorimetric mode is of 35.6 aM (S/N=3). This dual-mode detection achieves ultra-sensitive detection of CD142, demonstrating broad prospects for application.

Assessment of aortic and peripheral arterial stiffness in patients with knee osteoarthritis by ultrasound Doppler derived pulse wave velocity.

Information regarding regional arterial stiffness assessment in osteoarthritis (OA) was scarce and sometimes contradictory. We aimed to investigate the aortic, lower limb peripheral arterial stiffness and their associations with knee OA. Patients with primary knee OA and matched non-OA controls were prospectively enrolled from two medical centers in China. The carotid-femoral pulse wave velocity (cfPWV) and femoral-ankle pulse wave velocity (faPWV) were measured using a novel ultrasound technique. A total of 238 participants (including 128 patients with knee OA and 110 controls) were included. In OA patients, cfPWV was significantly higher than that of non-OA controls (9.40 ± 1.92 vs 8.25 ± 1.26 m/s, P < 0.0001). However, faPWV measurements in OA patients (12.10 ± 2.09 m/s) showed no significant difference compared with that of the controls (11.67 ± 2.52 m/s, P = 0.130). Multiple regression analysis revealed that cfPWV was independently associated with knee OA (P < 0.0001) after adjusting for the confounding factors including age, gender, smoking, mean blood pressure, body mass index, heart rate, high-sensitivity C-reactive protein and lipids profiles. In contrast, faPWV did not show independent association with knee OA (P = 0.372) when after adjusting for confounding factors. In addition, Spearman's correlation analysis showed cfPWV had a significant correlation with Kellgren-Lawrence score (rs = 0.2333, P = 0.008), but no correlation was founded between faPWV with Kellgren-Lawrence score (rs = 0.1624, P = 0.067) in OA patients. This study demonstrated that stiffening of aorta, but not lower limb arteries, was independently associated with knee OA. Our findings may call for further implementation of routine aortic stiffness assessments so as to evaluate cardiovascular risk in patients with OA.

Simultaneous Interfacial Defect Passivation and Bottom-Up Excess PbI2 Management via Rubidium Chloride in Highly Efficient Perovskite Solar Cells with Suppressed Hysteresis.

In halide perovskite solar cells (PSCs), moderate lead iodide (PbI2) can enhance device efficiency by providing some passivation effects, but extremely active PbI2 leads to the current density-voltage hysteresis effect and device instability. In addition, defects distributed on the buried interface of tin oxide (SnO2)/perovskite will lead to the photogenerated carrier recombination. Here, rubidium chloride (RbCl) is introduced at the buried SnO2/perovskite interface, which not only acts as an interfacial passivator to interact with the uncoordinated tin ions (Sn4+) and fill the oxygen vacancy on the SnO2 surface but also converts PbI2 into an inactive (PbI2)2RbCl compound to stabilize the perovskite phase via a bottom-up evolution effect. These synergistic effects deliver a champion PCE of 22.13% with suppressed hysteresis for the W RbCl PSCs, in combination with enhanced environmental and thermal stability. This work demonstrates that the interfacial defect passivation and bottom-up excess PbI2 management using RbCl modifiers are promising strategies to address the outstanding challenges associated with PSCs.

Aerobic Oxidative Carboxylation of Styrene Over Cobalt Catalysts: Integrated CO2 Capture and Conversion.

The direct synthesis of cyclic carbonates through oxidative carboxylation of alkenes using CO2 and O2 offers a sustainable and carbon-neutral method for CO2 utilization, which is, however, still a largely unexplored field. Here we develop a single-atom catalyst (SAC) Co-N/O-C as the earth-abundant metal catalyst for the oxidative carboxylation of styrene with CO2 and O2. Remarkably, even using the flue gas as an impure CO2 and O2 source, desired cyclic carbonate could be obtained with moderate productivity, which shows the potential for integrated CO2 capture and conversion, leveraging the high CO2 adsorption capacity of Co-N/O-C. In addition, the catalyst can be reused five times without an obvious decline in activity. Detailed characterizations and theoretical calculations elucidate the crucial role of single Co atoms in activating O2 and CO2, as well as controlling selectivity.

Multiple signal amplification strategy induced by biomarkers of lung cancer: A self-powered biosensing platform adapted for smartphones.

Lung cancer is a major malignant cancer with low survival rates, and early diagnosis is crucial for effective treatment. Herein, a biosensing platform that is self-powered derived from a capacitor-coupled EBFC has been developed for ultra-sensitive real-time identification of microRNA-21 (miRNA-21) with the assistance of a mobile phone. The flexible substrate of the platform is prepared on a carbon paper modified with graphdiyne and gold nanoparticles. The biosensor employs DNAzyme-mediated dual strand displacement amplification, which enhances the signal output intensity of the EBFC and improves selectivity. The coupling of the capacitor with the EBFC significantly amplifies the sensing signal, causing a 10.6-fold surge in current respond and further improving the sensitivity of the sensing platform. The established detection approach demonstrates a linear relationship varied from 0.0001 to 10,000 pM, with a sensitivity down to 32.3 aM as the minimum detectable limit, which has been effectively utilized for detecting miRNA-21 in practical samples. This sensing system provides strong support for the construction of portable detection devices, and the strategy of the platform construction provides an effective method for ultra-sensitive and accurate detection of miRNA, holding great potential in clinical diagnosis, prognosis evaluation, and drug screening for cancer.

The neuroprotective effect of LCZ696 on methamphetamine-induced cognitive impairment in mice.

OBJECTIVE: Methamphetamine (METH) exposure commonly causes cognitive impairment. An angiotensin II receptor/neprilysin inhibitor (ARNI), LCZ696 has been demonstrated to inhibit inflammation, oxidative stress and apoptosis. The present study was designed to examine the effect of LCZ696 on METH-induced cognitive impairment and the underlying mechanism. METHODS: Following daily treatment of either saline or METH (5 mg/kg) for 5 consecutive days, the cognitive function was tested using the Y-maze and the Novel Object Recognition (NOR) in Experiment 1. In Experiment 2, mice were initially treated with saline or LCZ696 (60 mg/kg) for 9 consecutive days, followed by LCZ696, METH or saline for 5 days. Cognitive testing was carried out as Experiment 1. In Experiment 3, SH-SY5Y cells were treated with either METH (2.5 Mm) or ddH2O for 12 h. The apoptosis and reactive oxygen species (ROS) level of SH-SY5Y were examined. In Experiment 4, SH-SY5Y cells were pretreated with either ddH2O or LCZ696 (70um) for 30 min, followed by ddH2O or METH treatment for 12 h. Nrf2 and HO-1 protein expression was examined in the ventral tegemental area (VTA) of all the animals and SH-SY5Y cells. RESULTS: LCZ696 significantly improved METH-induced cognitive impairment, in conjunction with decreased apoptosis and ROS levels in VTA of METH-treated mice and SH-SY5Y cells. METH significantly decreased Nrf2 and HO-1 protein expression in VTA of mice and SH-SY5Y cells, which was reversed by LCZ696 treatment. CONCLUSION: LCZ696 yields a neuroprotective effect against METH-induced cognitive dysfunction via the Nrf2/HO-1 signaling pathway.