In Situ Quantitative Monitoring of Adsorption from Aqueous Phase by UV-vis Spectroscopy: Implication for Understanding of Heterogeneous Processes.

The development of in situ techniques to quantitatively characterize the heterogeneous reactions is essential for understanding physicochemical processes in aqueous phase. In this work, a new approach coupling in situ UV-vis spectroscopy with a two-step algorithm strategy is developed to quantitatively monitor heterogeneous reactions in a compact closed-loop incorporation. The algorithm involves the inverse adding-doubling method for light scattering correction and the multivariate curve resolution-alternating least squares (MCR-ALS) method for spectral deconvolution. Innovatively, theoretical spectral simulations are employed to connect MCR-ALS solutions with chemical molecular structural evolution without prior information for reference spectra. As a model case study, the aqueous adsorption kinetics of bisphenol A onto polyamide microparticles are successfully quantified in a one-step UV-vis spectroscopic measurement. The practical applicability of this approach is confirmed by rapidly screening a superior adsorbent from commercial materials for antibiotic wastewater adsorption treatment. The demonstrated capabilities are expected to extend beyond monitoring adsorption systems to other heterogeneous reactions, significantly advancing UV-vis spectroscopic techniques toward practical integration into automated experimental platforms for probing aqueous chemical processes and beyond.

Dynamic accuracy measurement method for star trackers using a time-synchronized high-accuracy turntable.

Star trackers are typically used in a spacecraft to provide absolute attitude information to the on-board attitude control system so as to promote high accuracy. The performance of the star tracker is rather important. Attitude incorrectness provided by star trackers may lead to bad navigation with big deviations, even failure of satellites. Therefore, how to realize and verify the accuracy is crucial. As a matter of fact, it is difficult to validate accuracy of star trackers on the ground, especially for star trackers under highly dynamic conditions. In this paper, an accuracy measurement method for star trackers under dynamic conditions is proposed, utilizing a high-accuracy swing table to provide reference to compare. To this end, a swing table, star tracker, and the test equipment are synchronized, in order to reduce systematic errors. As the motion trajectory of the swing table can be set beforehand, the initial attitude of the star tracker can be predicted through a set of coordinate transformations. As a result, the star tracker is able to keep tracking, regardless of the angular velocity of the swing table. This makes the statistical sample points more sufficient and the results more reliable. Moreover, it can evaluate the angular velocity of star trackers up to 20°/s. In comparison with the conventional method with simulated stars, this method utilizes real navigation stars as observation targets making the measurement results much closer to the on-orbit performance. Lastly, but much more importantly, it can also verify the performance of a star tracker in one experiment, such as sensitivity, static performance, capture probability, and so on. Experimental results demonstrate that the proposed method is effective, especially for highly dynamic star trackers. Such a measurement environment is close to the in-orbit conditions, and it can satisfy the stringent requirement for star trackers under high dynamics.

Discriminating atypical parotid carcinoma and pleomorphic adenoma utilizing extracellular volume fraction and arterial enhancement fraction derived from contrast-enhanced CT imaging: A multicenter study.

OBJECTIVES: To investigate the added value of extracellular volume fraction (ECV) and arterial enhancement fraction (AEF) derived from enhanced CT to conventional image and clinical features for differentiating between pleomorphic adenoma (PA) and atypical parotid adenocarcinoma (PCA) pre-operation. METHODS: From January 2010 to October 2023, a total of 187 cases of parotid tumors were recruited, and divided into training cohort (102 PAs and 51 PCAs) and testing cohort (24 PAs and 10 atypical PCAs). Clinical and CT image features of tumor were assessed. Both enhanced CT-derived ECV and AEF were calculated. Univariate analysis identified variables with statistically significant differences between the two subgroups in the training cohort. Multivariate logistic regression analysis with the forward variable selection method was used to build four models (clinical model, clinical model+ECV, clinical model+AEF, and combined model). Diagnostic performances were evaluated using receiver operating characteristic (ROC) curve analyses. Delong's test compared model differences, and calibration curve and decision curve analysis (DCA) assessed calibration and clinical application. RESULTS: Age and boundary were chosen to build clinical model, and to construct its ROC curve. Amalgamating the clinical model, ECV, and AEF to establish a combined model demonstrated superior diagnostic effectiveness compared to the clinical model in both the training and test cohorts (AUC = 0.888, 0.867). There was a significant statistical difference between the combined model and the clinical model in the training cohort (p = 0.0145). CONCLUSIONS: ECV and AEF are helpful in differentiating PA and atypical PCA, and integrating clinical and CT image features can further improve the diagnostic performance.

ELM2-SANT Domain-Containing Scaffolding Protein 1 Regulates Differentiation and Maturation of Cardiomyocytes Derived From Human-Induced Pluripotent Stem Cells.

BACKGROUND: ELMSAN1 (ELM2-SANT domain-containing scaffolding protein 1) is a newly identified scaffolding protein of the MiDAC (mitotic deacetylase complex), playing a pivotal role in early embryonic development. Studies on Elmsan1 knockout mice showed that its absence results in embryo lethality and heart malformation. However, the precise function of ELMSAN1 in heart development and formation remains elusive. To study its potential role in cardiac lineage, we employed human-induced pluripotent stem cells (hiPSCs) to model early cardiogenesis and investigated the function of ELMSAN1. METHODS AND RESULTS: We generated ELMSAN1-deficient hiPSCs through knockdown and knockout techniques. During cardiac differentiation, ELMSAN1 depletion inhibited pluripotency deactivation, decreased the expression of cardiac-specific markers, and reduced differentiation efficiency. The impaired expression of genes associated with contractile sarcomere structure, calcium handling, and ion channels was also noted in ELMSAN1-deficient cardiomyocytes derived from hiPSCs. Additionally, through a series of structural and functional assessments, we found that ELMSAN1-null hiPSC cardiomyocytes are immature, exhibiting incomplete sarcomere Z-line structure, decreased calcium handling, and impaired electrophysiological properties. Of note, we found that the cardiac-specific role of ELMSAN1 is likely associated with histone H3K27 acetylation level. The transcriptome analysis provided additional insights, indicating maturation reduction with the energy metabolism switch and restored cell proliferation in ELMSAN1 knockout cardiomyocytes. CONCLUSIONS: In this study, we address the significance of the direct involvement of ELMSAN1 in the differentiation and maturation of hiPSC cardiomyocytes. We first report the impact of ELMSAN1 on multiple aspects of hiPSC cardiomyocyte generation, including cardiac differentiation, sarcomere formation, calcium handling, electrophysiological maturation, and proliferation.

A Radiomics-Based Nomogram Using Ultrasound Carotid Plaque Evaluation For Predicting Cerebro-Cardiovascular Events In Asymptomatic Patients.

RATIONALE AND OBJECTIVES: This study aims to assess whether a radiomics-based nomogram correlates with a higher risk of future cerebro-cardiovascular events in patients with asymptomatic carotid plaques. Additionally, it investigates the nomogram's contribution to the revised Framingham Stroke Risk Profile (rFSRP) for predicting cerebro-cardiovascular risk. MATERIALS AND METHODS: Predictive models aimed at identifying an increased risk of future cerebro-cardiovascular events were developed and internally validated at one center, then externally validated at two other centers. Survival curves, constructed using the Kaplan-Meier method, were compared through the log-rank test. RESULTS: This study included a total of 2009 patients (3946 images). The final nomogram was generated using multivariate Cox regression variables, including dyslipidemia, lumen diameter, plaque echogenicity, and ultrasonography (US)-based radiomics risk. The Harrell's concordance index (C-index) for predicting events-free survival (EFS) was 0.708 in the training cohort, 0.574 in the external validation cohort 1, 0.632 in the internal validation cohort, and 0.639 in the external validation cohort 2. The final nomogram showed a significant increase in C-index compared to the clinical, conventional US, and US-based radiomics models (all P < 0.05). Furthermore, the final nomogram-assisted method significantly improved the sensitivity and accuracy of radiologists' visual qualitative score of plaque (both P < 0.001). Among 1058 patients with corresponding 1588 plaque US images classified as low-risk by the rFSRP, 75 (7.1%) patients with corresponding 93 (5.9%) carotid plaque images were appropriately reclassified to the high-risk category by the final nomogram. CONCLUSION: The radiomics-based nomogram demonstrated accurate prediction of cerebro-cardiovascular events in patients with asymptomatic carotid plaques. It also improved the sensitivity and accuracy of radiologists' visual qualitative score of carotid plaque and enhanced the risk stratification ability of rFSRP. SUMMARY: The radiomics-based nomogram allowed accurate prediction of cerebro-cardiovascular events, especially ipsilateral ischemic stroke in patients with asymptomatic carotid atherosclerotic plaques. KEY RESULTS: The radiomics-based nomogram allowed accurate prediction of cerebro-cardiovascular events, especially ipsilateral ischemic stroke in patients with asymptomatic carotid atherosclerotic plaques. The radiomics-based nomogram improved the sensitivity and accuracy of radiologists' visual qualitative score of carotid plaque. The radiomics-based nomogram improved the discrimination of high-risk populations from low-risk populations in asymptomatic patients with carotid atherosclerotic plaques and the risk stratification capability of the rFSRP.

Quantification of urinary podocyte-derived migrasomes for the diagnosis of kidney disease.

Migrasomes represent a recently uncovered category of extracellular microvesicles, spanning a diameter range of 500 to 3000 nm. They are emitted by migrating cells and harbour a diverse array of RNAs and proteins. Migrasomes can be readily identified in bodily fluids like serum and urine, rendering them a valuable non-invasive source for disease diagnosis through liquid biopsy. In this investigation, we introduce a streamlined and effective approach for the capture and quantitative assessment of migrasomes, employing wheat germ agglutinin (WGA)-coated magnetic beads and flow cytometry (referred to as WBFC). Subsequently, we examined the levels of migrasomes in the urine of kidney disease (KD) patients with podocyte injury and healthy volunteers using WBFC. The outcomes unveiled a substantial increase in urinary podocyte-derived migrasome concentrations among individuals with KD with podocyte injury compared to the healthy counterparts. Notably, the urinary podocyte-derived migrasomes were found to express an abundant quantity of phospholipase A2 receptor (PLA2R) proteins. The presence of PLA2R proteins in these migrasomes holds promise for serving as a natural antigen for the quantification of autoantibodies against PLA2R in the serum of patients afflicted by membranous nephropathy. Consequently, our study not only pioneers a novel technique for the isolation and quantification of migrasomes but also underscores the potential of urinary migrasomes as a promising biomarker for the early diagnosis of KD with podocyte injury.

The cellular response and molecular mechanism of superoxide dismutase interacting with superparamagnetic iron oxide nanoparticles.

This study explored the response of superoxide dismutase (SOD) under superparamagnetic iron oxide nanoparticles (SPIONs)-induced oxidative stress using combined cellular and molecular methods. Results found that SPIONs induced the inhibition of catalase activity, the U-inverted change of SOD activity and the accumulation of reactive oxygen species (ROS), leading to oxidative damage and cytotoxicity. The change of intracellular SOD activity was resulted from the increase of molecular activity induced by directly interacting with SPIONs and ROS-inhibition of activity. The increase of molecular activity could be attributed to the structural and conformational changes of SOD, which were caused by the direct interaction of SOD with SPIONs. The SOD-SPIONs interaction and its interacting mechanism were explored by multi-spectroscopy, isothermal titration calorimetry and zeta potential assays. SOD binds to SPIONs majorly via hydrophobic forces with the involvement of electrostatic forces. SPIONs approximately adsorb 11 units of SOD molecule with the binding affinity of 2.99 × 106 M-1. The binding sites on SOD were located around Tyr residues, whose hydrophilicity increased upon interacting with SPIONs. The binding to SPIONs loosened the peptide chains, changed the secondary structure and reduced the aggregation state of SOD.

Expression of a single-chain monellin (MNEI) mutant with enhanced stability in transgenic mice milk.

Monellin is a sweet protein that may be used as a safe and healthy sweetener. However, due to its low stability, the application of monellin is currently very limited. Here, we describe a wild-type, a double-sites mutant (E2N/E23A) and a triple-sites mutant (N14A/E23Q/S76Y) of single-chain monellin (MNEI) expressed in transgenic mice milk. Based on enzyme-linked immunoassay (ELISA), Western blot, and sweetness intensity testing, their sweetness and stability were compared. After boiling for 2 min at different pH conditions (2.5, 5.1, 6.8, and 8.2), N14A/E23Q/S76Y-MNEI showed significantly higher sweetness and stability than the wild-type and E2N/E23A-MNEI. These results suggest that N14A/E23Q/S76Y-MNEI shows remarkable potential as a sweetener in the future.

EfficientTrain++: Generalized Curriculum Learning for Efficient Visual Backbone Training.

The superior performance of modern computer vision backbones (e.g., vision Transformers learned on ImageNet-1K/22K) usually comes with a costly training procedure. This study contributes to this issue by generalizing the idea of curriculum learning beyond its original formulation, i.e., training models using easier-to-harder data. Specifically, we reformulate the training curriculum as a soft-selection function, which uncovers progressively more difficult patterns within each example during training, instead of performing easier-to-harder sample selection. Our work is inspired by an intriguing observation on the learning dynamics of visual backbones: during the earlier stages of training, the model predominantly learns to recognize some 'easier-to-learn' discriminative patterns in the data. These patterns, when observed through frequency and spatial domains, incorporate lower-frequency components, and the natural image contents without distortion or data augmentation. Motivated by these findings, we propose a curriculum where the model always leverages all the training data at every learning stage, yet the exposure to the 'easier-to-learn' patterns of each example is initiated first, with harder patterns gradually introduced as training progresses. To implement this idea in a computationally efficient way, we introduce a cropping operation in the Fourier spectrum of the inputs, enabling the model to learn from only the lower-frequency components. Then we show that exposing the contents of natural images can be readily achieved by modulating the intensity of data augmentation. Finally, we integrate these two aspects and design curriculum learning schedules by proposing tailored searching algorithms. Moreover, we present useful techniques for deploying our approach efficiently in challenging practical scenarios, such as large-scale parallel training, and limited input/output or data pre-processing speed. The resulting method, EfficientTrain++, is simple, general, yet surprisingly effective. As an off-the-shelf approach, it reduces the training time of various popular models (e.g., ResNet, ConvNeXt, DeiT, PVT, Swin, CSWin, and CAFormer) by [Formula: see text] on ImageNet-1K/22K without sacrificing accuracy. It also demonstrates efficacy in self-supervised learning (e.g., MAE). Code is available at: https://github.com/LeapLabTHU/EfficientTrain.

Podocyte SIRPα reduction aggravates lupus nephritis via promoting T cell inflammatory responses.

Signal-regulatory protein alpha (SIRPα) has recently been found to be highly expressed in podocytes and is essential for maintaining podocyte function. However, its immunoregulatory function in podocytes remains elusive. Here, we report that SIRPα controls podocyte antigen presentation in specific T cell activation via inhibiting spleen tyrosine kinase (Syk) phosphorylation. First, podocyte SIRPα under lupus nephritis (LN) conditions is strongly downregulated. Second, podocyte-specific deletion of SIRPα exacerbates renal disease progression in lupus-prone mice, as evidenced by an increase in T cell infiltration. Third, SIRPα deletion or knockdown enhances podocyte antigen presentation, which activates specific T cells, via enhancing Syk phosphorylation. Supporting this, Syk inhibitor GS-9973 prevents podocyte antigen presentation, resulting in a decrease of T cell activation and mitigation of renal disease caused by SIRPα knockdown or deletion. Our findings reveal an immunoregulatory role of SIRPα loss in promoting podocyte antigen presentation to activate specific T cell immune responses in LN.

Estimating non-productive water losses in irrigated Platycladus orientalis plantations in semi-arid mountainous: Based on stable isotopes.

Planted forests in semi-arid regions provide invaluable ecological functions such as windbreak, sand fixation, carbon fixation, and oxygen release, improving the ecological environment and maximizing the carbon sink benefits of forests. Therefore, accurately assessing non-productive water losses in water-scarce regions is crucial for estimating water requirements of irrigation-dependent plantations. From March to October 2023, we collected the stable isotopes of precipitation, irrigation water, soil water, and other relevant data. The Craig-Gordon model was used to evaluate the non-productive water losses in irrigated Platycladus orientalis plantations, focusing on the dissipation and vertical migration process under both sufficient and insufficient water supply conditions. The results demonstrated that preferential flow and piston flow coexisted during soil water infiltration, while both types occurred under sufficient watering conditions, but piston flow dominated when there was insufficient watering. We estimated the average non-productive losses for irrigated P. orientalis plantations at 27.0 %, with peak losses up to 40.3 %. Moreover, we observed a lower rate of non-productive losses under sufficient water supply conditions (12.2 %) compared with insufficient water supply conditions (33.6 %). Our results indicated that vertical migration pathway of soil water emerged as a significant determinant factor affecting non-productive water losses, and also influenced by meteorological factors, water inputs, and soil properties. To optimize water utilization in semi-arid irrigated mountainous plantations, we recommend reducing amount of each irrigation and increasing frequency of irrigation.

Effects of epidural analgesia on intrapartum maternal fever and maternal outcomes: an updated systematic review and meta-analysis.

OBJECTIVE: Epidural-related maternal fever in women is a common clinical phenomenon that leads to adverse consequences for mothers and neonates. The meta-analysis aimed to quantify the risk for intrapartum maternal fever after epidural analgesia (EA) stratified according to parity. The secondary objective was to investigate the association between EA and maternal outcomes. METHODS: An electronic literature search of the Medline/PubMed, Embase, Cochrane Library, Wanfang Data, and China National Knowledge Infrastructure databases was performed to identify studies reporting the occurrence of intrapartum fever in parturients. Studies were reviewed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, and meta-analysis was performed using Review Manager version 5.3. RESULTS: Seventeen randomized controlled trials (RCTs) (5959 parturients) were included. Odds ratios for maternal fever in the analysis were 4.17 (95% confidence interval (CI) 2.93-5.94) and 5.83 (95% CI 4.96-6.87), respectively. Results of subgroup analysis according to parity were consistent. EA significantly prolonged the length of the first stage of labor (MD 34.52 [95% CI 12.13-56.91]) and the second stage of labor (MD 9.10 [95% CI 4.51-13.68]). Parturients who received EA were more likely to undergo instrumental delivery (OR 2.03 [95% CI 1.44-2.86]) and oxytocin augmentation (OR 1.45 [95% CI 1.12-1.88]). There were no differences in cesarean delivery rates between the EA and non-EA groups. CONCLUSIONS: Parturients who received EA exhibited a higher incidence of intrapartum fever. Credibility of the subgroup analyses was low because the mixed group did not effectively represent multiparas.

MS/MS-based molecular networking discovery of sesquiterpenes from Carpesium abrotanoides L. with their cytotoxic and acetylcholinesterase inhibitory activity.

Employing an MS/MS-based molecular networking-guided strategy, three new eudesmane-type sesquiterpenes (1-3) and one undescribed pseudoguaianolide sesquiterpene (8), along with four known eudesmane-type sesquiterpene lactones (4-7) were extracted and purified from the herbs of Carpesium abrotanoides L. Structural elucidation encompassed comprehensive spectroscopic analysis, NMR calculations, DP4+ analysis, and ECD calculations. The cytotoxicity activity of all isolates was evaluated against two human hepatoma carcinoma cells (HepG2 and Hep3B) in vitro. It was demonstrated that compounds 2 and 4 showed moderate cytotoxic against HepG2 and Hep3B cells. Furthermore, all compounds were evaluated for their acetylcholinesterase (AChE) inhibitory activity. Particularly noteworthy is that, in comparison to the positive control, compound 1 demonstrated significant AChE inhibition with an inhibition rate of 77.86%. In addition, the inhibitory mechanism of compound 1 were investigated by in silico docking analyze and molecular dynamic simulation.

Fabrication-induced even-odd discrepancy of magnetotransport in few-layer MnBi2Te4.

The van der Waals antiferromagnetic topological insulator MnBi2Te4 represents a promising platform for exploring the layer-dependent magnetism and topological states of matter. Recently observed discrepancies between magnetic and transport properties have aroused controversies concerning the topological nature of MnBi2Te4 in the ground state. In this article, we demonstrate that fabrication can induce mismatched even-odd layer dependent magnetotransport in few-layer MnBi2Te4. We perform a comprehensive study of the magnetotransport properties in 6- and 7-septuple-layer MnBi2Te4, and reveal that both even- and odd-number-layer device can show zero Hall plateau phenomena in zero magnetic field. Importantly, a statistical survey of the optical contrast in more than 200 MnBi2Te4 flakes reveals that the zero Hall plateau in odd-number-layer devices arises from the reduction of the effective thickness during the fabrication, a factor that was rarely noticed in previous studies of 2D materials. Our finding not only provides an explanation to the controversies regarding the discrepancy of the even-odd layer dependent magnetotransport in MnBi2Te4, but also highlights the critical issues concerning the fabrication and characterization of 2D material devices.

US-based Sequential Algorithm Integrating an AI Model for Advanced Liver Fibrosis Screening.

Background Noninvasive tests can be used to screen patients with chronic liver disease for advanced liver fibrosis; however, the use of single tests may not be adequate. Purpose To construct sequential clinical algorithms that include a US deep learning (DL) model and compare their ability to predict advanced liver fibrosis with that of other noninvasive tests. Materials and Methods This retrospective study included adult patients with a history of chronic liver disease or unexplained abnormal liver function test results who underwent B-mode US of the liver between January 2014 and September 2022 at three health care facilities. A US-based DL network (FIB-Net) was trained on US images to predict whether the shear-wave elastography (SWE) value was 8.7 kPa or higher, indicative of advanced fibrosis. In the internal and external test sets, a two-step algorithm (Two-step#1) using the Fibrosis-4 Index (FIB-4) followed by FIB-Net and a three-step algorithm (Three-step#1) using FIB-4 followed by FIB-Net and SWE were used to simulate screening scenarios where liver stiffness measurements were not or were available, respectively. Measures of diagnostic accuracy were calculated using liver biopsy as the reference standard and compared between FIB-4, SWE, FIB-Net, and European Association for the Study of the Liver guidelines (ie, FIB-4 followed by SWE), along with sequential algorithms. Results The training, validation, and test data sets included 3067 (median age, 42 years [IQR, 33-53 years]; 2083 male), 1599 (median age, 41 years [IQR, 33-51 years]; 1124 male), and 1228 (median age, 44 years [IQR, 33-55 years]; 741 male) patients, respectively. FIB-Net obtained a noninferior specificity with a margin of 5% (P < .001) compared with SWE (80% vs 82%). The Two-step#1 algorithm showed higher specificity and positive predictive value (PPV) than FIB-4 (specificity, 79% vs 57%; PPV, 44% vs 32%) while reducing unnecessary referrals by 42%. The Three-step#1 algorithm had higher specificity and PPV compared with European Association for the Study of the Liver guidelines (specificity, 94% vs 88%; PPV, 73% vs 64%) while reducing unnecessary referrals by 35%. Conclusion A sequential algorithm combining FIB-4 and a US DL model showed higher diagnostic accuracy and improved referral management for all-cause advanced liver fibrosis compared with FIB-4 or the DL model alone. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Ghosh in this issue.

High-Performance Reconfigurable Pipeline Implementation for FPGA-Based SmartNIC.

As the key module of programmable switches or the SmartNIC card, the packet processing pipeline undertakes the task of packet forwarding and processing. However, the current pipeline for the FPGA-based SmartNIC is inflexible, and the related reconfigurable commercial device designs are closed-source. To solve this problem, this paper proposes a high-performance reconfigurable pipeline design, which has fully reconfigurable match-action units, supporting various network functions by its flexible reconfiguration. The fields of the match key and the size of the match table can be reconfigured without recompiling the HDL code or modifying the hardware. The processing rules and action instructions for the pipeline can be dynamically installed by the configuration module at runtime. We implement our design on the Xilinx Alveo U200 board with a Virtex UltraScale+ XCU200-2FSGD2104E FPGA and show that the designed pipeline supports fast reconfiguration to implement new network functions and that the throughput of the designed pipeline reaches 100 Gbps with low latency.

Impact of Continuous Nursing on Quality of Life and Psychological Well-being in Advanced Lung Cancer Patients.

Objectives: This study aimed to analyze the psychological status and quality of life (QoL) of patients with advanced lung cancer and assess the impact of continuous nursing intervention on these parameters. Methods: A total of 160 advanced lung cancer patients were randomly assigned to a control group or a study group, with 80 patients in each. The control group received the routine nursing intervention, while the study group received the continuous nursing intervention, including health record establishment, regular follow-ups, diet guidance, health knowledge education, psychological counseling, and work and rest guidance. Inflammatory markers (IL-6, TNF-α, PGE2, and SP), Spitzer Quality of Life Index (SQLI), anxiety and depression self-evaluation scales, Visual Analogue Scale (VAS) for pain, and patient satisfaction were measured before and after 4 weeks of intervention. Results: Post-intervention, the study group showed a significant reduction in serum IL-6 and TNF-α levels (P < .001), improved SQLI scores (P = .002), and lower anxiety and depression scores (P < .001) compared to the control group. A significant negative correlation between psychological status and QoL was observed (P < .001). The study group also reported lower VAS pain scores (P < .001) and higher patient satisfaction (P = .000) after the intervention. Conclusions: Continuous nursing intervention has significantly improved psychological well-being, alleviated pain, and enhanced the overall quality of life for patients facing advanced lung cancer. These results indicate that a comprehensive and sustained nursing intervention strategy can serve as an effective approach to improve the well-being of individuals navigating advanced lung cancer during chemotherapy.

Evaluation of disease severity and prediction of severe cases in children hospitalized with influenza A (H1N1) infection during the post-COVID-19 era: a multicenter retrospective study.

BACKGROUND: The rebound of influenza A (H1N1) infection in post-COVID-19 era recently attracted enormous attention due the rapidly increased number of pediatric hospitalizations and the changed characteristics compared to classical H1N1 infection in pre-COVID-19 era. This study aimed to evaluate the clinical characteristics and severity of children hospitalized with H1N1 infection during post-COVID-19 period, and to construct a novel prediction model for severe H1N1 infection. METHODS: A total of 757 pediatric H1N1 inpatients from nine tertiary public hospitals in Yunnan and Shanghai, China, were retrospectively included, of which 431 patients diagnosed between February 2023 and July 2023 were divided into post-COVID-19 group, while the remaining 326 patients diagnosed between November 2018 and April 2019 were divided into pre-COVID-19 group. A 1:1 propensity-score matching (PSM) was adopted to balance demographic differences between pre- and post-COVID-19 groups, and then compared the severity across these two groups based on clinical and laboratory indicators. Additionally, a subgroup analysis in the original post-COVID-19 group (without PSM) was performed to investigate the independent risk factors for severe H1N1 infection in post-COIVD-19 era. Specifically, Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to select candidate predictors, and logistic regression was used to further identify independent risk factors, thus establishing a prediction model. Receiver operating characteristic (ROC) curve and calibration curve were utilized to assess discriminative capability and accuracy of the model, while decision curve analysis (DCA) was used to determine the clinical usefulness of the model. RESULTS: After PSM, the post-COVID-19 group showed longer fever duration, higher fever peak, more frequent cough and seizures, as well as higher levels of C-reactive protein (CRP), interleukin 6 (IL-6), IL-10, creatine kinase-MB (CK-MB) and fibrinogen, higher mechanical ventilation rate, longer length of hospital stay (LOS), as well as higher proportion of severe H1N1 infection (all P < 0.05), compared to the pre-COVID-19 group. Moreover, age, BMI, fever duration, leucocyte count, lymphocyte proportion, proportion of CD3+ T cells, tumor necrosis factor α (TNF-α), and IL-10 were confirmed to be independently associated with severe H1N1 infection in post-COVID-19 era. A prediction model integrating these above eight variables was established, and this model had good discrimination, accuracy, and clinical practicability. CONCLUSIONS: Pediatric H1N1 infection during post-COVID-19 era showed a higher overall disease severity than the classical H1N1 infection in pre-COVID-19 period. Meanwhile, cough and seizures were more prominent in children with H1N1 infection during post-COVID-19 era. Clinicians should be aware of these changes in such patients in clinical work. Furthermore, a simple and practical prediction model was constructed and internally validated here, which showed a good performance for predicting severe H1N1 infection in post-COVID-19 era.

Characteristics of second-hand exposure to aerosols from e-cigarettes: A literature review since 2010.

In recent years, the use of electronic vaping products (also named e-cigarettes) has increased due to their appealing flavors and nicotine delivery without the combustion of tobacco. Although the hazardous substances emitted by e-cigarettes are largely found to be much lower than combustible cigarettes, second-hand exposure to e-cigarette aerosols is not completely benign for bystanders. This work reviewed and synthesized findings on the second-hand exposure of aerosols from e-cigarettes and compared the results with those of the combustible cigarettes. In this review, different results were integrated based upon sampling locations such as residences, vehicles, offices, public places, and experimental exposure chambers. In addition, the factors that influence the second-hand exposure levels were identified by objectively reviewing and integrating the impacts of combustible cigarettes and e-cigarettes on the environment. It is a challenge to compare the literature data directly to assess the effect of smoking/vaping on the indoor environment. The room volume, indoor air exchange rate, puffing duration, and puffing numbers should be considered, which are important factors in determining the degree of pollution. Therefore, it is necessary to calculate the "emission rate" to normalize the concentration of pollutants emitted under various experimental conditions and make the results comparable. This review aims to increase the awareness regarding the harmful effects of the second-hand exposure to aerosols coming from the use of cigarettes and e-cigarettes, identify knowledge gaps, and provide a scientific basis for future policy interventions with regard to the regulation of smoking and vaping.

Relative apical sparing obtained with speckle tracking echocardiography is not a sensitive parameter for diagnosing light-chain cardiac amyloidosis.

Background: Distinguishing light-chain cardiac amyloidosis (AL CA) from left ventricular wall thickening (LVWT) resulted from other etiologies has proven to be challenging. This study aimed to determine the sensitivity and specificity of relative apical sparing in diagnosing AL CA and investigate the differences in clinical and echocardiographic characteristics between AL CA patients with apical sparing and those with non-apical sparing. Methods: A total of 63 consecutive patients with AL CA, 102 consecutive patients with LVWT (including 51 hypertrophic cardiomyopathy (HCM) and 51 hypertension) and 33 healthy individuals were recruited retrospectively at Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology. Conventional and speckle tracking echocardiography were performed on all subjects. Results: Although wall thickening was observed in all patients, almost all functional parameters were worse in AL CA, except for relative apical longitudinal strain (LS) (P=0.906). Of 63 patients with AL CA, only 17.5% (n=11) showed an apical sparing pattern. Patients with apical sparing had poorer cardiac performance than those with non-apical sparing. Relative apical sparing showed the lowest diagnostic accuracy with an area under the curve (AUC) of 0.58 [95% confidence interval (CI): 0.49-0.67, sensitivity: 17.5%, specificity: 98.0%, P=0.095] to detect AL CA, but right ventricular strain (RVS) (AUC: 0.86, P<0.001) showed the highest among all echocardiographic parameters. When diagnosing AL CA patients with non-apical sparing, RVS continued to maintain excellent diagnostic accuracy (AUC: 0.84, P<0.001), followed by left atrial reservoir strain (LASr) (AUC: 0.77, P<0.001). Conclusions: The diagnostic value of relative apical sparing for AL CA was limited with low sensitivity. In clinical practice, the diagnosis of early AL CA patients should not solely rely on relative apical sparing.